This study analyzes how various audio features influence speaker change detection in different unsupervised approaches. Ten different audio features, including MFCC, mel-spectrogram, spectral centroid, and pitch, etc. were chosen for analysis. Two distinct unsupervised methods were selected for comparing the effectiveness of these feature: the Bayesian information criterion with Gaussian mixture model (BIC-GMM), a model-based approach, and the Kullback-Leibler divergence with Gaussian (KL-GMM), a metric-based approach. In order to gain a prior insight into which features have a significant impact on the SCD problem, we calculate statistic for two probabilities: the probability of speaker change given there is a feature change, and vice versa. To experimentally check the prior insights, a set of experiments carried out to analyze the influence of various audio feature for SCD. The results showed that in both methods, MFCC demonstrates a robust performance, and ranks at the top. Zero crossing rate, chroma and spectral contrast gives a higher performance in BIC-GMM. Mel-spectrogram consistently ranks at the bottom, suggesting it has the least impact on performance across both methods.

Low back pain (LBP) affects over 60% of individuals in their lifetime and is a leading cause of disability and increased healthcare expenditure. Facet joint pain (FJP) occurs in 27% to 40% of LBP patients but is often overlooked or misdiagnosed. Additionally, there is no clear correlation between clinical examination, radiological findings, and clinical presentation, com-plicating the diagnosis and treatment of FJP. This narrative review aims to provide an overview of the literature regarding facet joint pain and discusses the utility of medial branch blocks (MBBs) and intra-articular (IA) injections as diag-nostic and therapeutic tools prior to radiofrequency ablation (RFA). RFA is considered the gold standard for managing FJP, employing techniques that include precise needle placement and stimulation parameters to disrupt pain signals. Promising alternatives such as cooled RFA and cryodenervation require further research on their long-term efficacy and safety. Endoscopic denervation and multifidus stimulation are emerging therapies that may benefit chronic LBP patients, but additional research is needed to establish their effectiveness. When conservative management fails, RFA provides significant and lasting relief in well-selected patients and has a favourable safety profile. Current literature does not support surgical inter-ventions for LBP management.

Alphaviruses are known for being model viruses for studying cellular functions related to viral infection but also for causing epidemics in different parts of the world. More recently, alphavirus-based expression systems have demonstrated efficacy as vaccines against infectious diseases and as therapeutic applications for different cancers. The self-replicating feature of alphaviruses has provided the advantage of extremely high transgene expression of vaccine-related antigens and therapeutic anti-tumor and immunostimulatory genes, which has also permitted significantly reduced doses for prophylactic and therapeutic applications potentially reducing adverse events. Furthermore, alphaviruses have shown favorable flexibility as they can be delivered as recombinant viral particles, RNA replicons or DNA replicon-based plasmids. In the context of infectious diseases robust immune responses against the surface proteins of target agents have been observed and protection against challenges with lethal doses of infectious agents in rodents and primates. Similarly, expression of anti-tumor genes and immunostimulatory genes from alphavirus vectors has provided tumor growth inhibition, tumor regression and cure in animal cancer models. Moreover, protection against tumor challenges has been observed. In clinical settings, clinical benefits have been reported. Alphaviruses have also been considered for the treatment of neurological disorders due to their neurotrophic preference. Attention has been paid to alphavirus vector and expression system improvement. Point mutations in the non-structural alphaviral replicase genes have generated enhanced transgene expression and created temperature-sensitive expression vectors. The recently engineered trans-amplifying RNA system has facilitated vector production and enhanced the expression capacity.

The incorporation of electric vehicles (EVs) with vehicle-to-grid (V2G) offers the development of multi-energy microgrid (MMOs) models. However, MMOs have among their goals to decrease electricity costs by coordinating with vehicle-to-grid (V2G) scheduling. Controlling V2G models poses uncertainties about the voltages developed and creates the need for power generation disruptions. In this work, a Feed-Forward-Back-Propagation Network (FFBPN) is developed with Matlab software, based on the Levenberg-Marquardt algorithm by varying the number of hidden neurons to realize better performance thanks to the value of the Maximum Coefficient of De-termination (R2) and the Minimum Mean Squared Error (MSE). In this article, the dataset from NASA PCoE has been used to make proper consideration of the model that best calculates the life cycle of the battery, demonstrating relevant implications for future development of this type of system based on FFBPN for the integration of EV into V2G. The proposed FFBPN demonstrates better performance than other methods taken from the literature. In conclusion, the comparison between the phases of training, validation and test are used to completely represent the validity of the proposed model and precisely to identify the characteristics curves of FFBPN for future ap-plications highlighting its performance to create profitability, efficiency, production, energy saving and minimum environmental impact.

The tryptophan-kynurenine (KYN) pathway has long been recognized for its essential role in gen-erating metabolites that influence various physiological processes. Traditionally, these metabolites have been categorized into distinct, often opposing groups, such as pro-oxidant versus antioxidant, excitotoxic versus neuroprotective, or neurotoxic versus neuroprotective. This dichotomous framework has shaped much of the research on conditions like neurodegenerative and neuropsy-chiatric disorders, as well as cancer, where metabolic imbalances are a key feature. The effects are significantly influenced by various factors, including the concentration of metabolites and the par-ticular cellular milieu in which they are generated. A molecule that acts as neuroprotective at low concentrations may exhibit neurotoxic effects at elevated levels. The oxidative equilibrium of the surrounding environment can alter the function of KYN from an antioxidant to a pro-oxidant. This narrative review offers a comprehensive examination and analysis of the contemporary under-standing of KYN metabolites, emphasizing their multifaceted biological functions and their rele-vance in numerous physiological and pathological processes. This underscores the pressing ne-cessity for a paradigm shift in the comprehension of KYN metabolism. Understanding the intricate, context-dependent functions of these metabolites is crucial for establishing novel therapeutic tar-gets, especially in conditions such as neurodegeneration, immunological disorders, and cancer, where metabolic dysregulation serves as a primary catalyst of pathogenesis.

This paper considers the question of what kind of knowledge is produced by deep learning. Ryle’s concept of knowledge how is examined and is contrasted with knowledge with a rationale. It is then argued that deep neural networks do produce knowledge how, but, because of their opacity, they do not in general, though there may be some special cases to the contrary, produce knowledge with a rationale. It is concluded that the distinction between knowledge how and knowledge with a rationale is a useful one for judging whether a particular application of deep learning AI is appropriate.

This study investigates the application of fractal geometry to the analysis of vertebrate respiratory systems, focusing on the branching patterns of the bronchial tree across diverse species. Using a combination of mathematical modeling and computational visualization, we explore how fractal dimensions and branching characteristics reflect evolutionary adaptations to various habitats and physiological demands. The research encompasses a range of vertebrates, including humans, horses, dolphins, chickens, iguanas, and bullfrogs, representing diverse taxonomic groups and ecological niches. Our analysis reveals a clear gradient of complexity in respiratory structures, correlating strongly with metabolic rates and environmental adaptations. Mammals, particularly those adapted for high-performance activities like horses, demonstrate the most complex fractal patterns, indicating highly efficient gas exchange systems. In contrast, ectothermic species such as iguanas and bullfrogs exhibit simpler structures, reflecting their lower metabolic demands and alternative respiratory strategies. The study employs fractal dimension calculations, L-system modeling, and lacunarity analysis to quantify and visualize these differences. Our findings suggest that fractal analysis provides valuable insights into the relationship between form and function in vertebrate respiratory systems, offering a novel perspective on comparative physiology and evolutionary biology. This research not only enhances our understanding of respiratory system evolution but also has potential applications in biomimetic design, medical diagnostics, and ecological physiology. It demonstrates the power of interdisciplinary approaches, combining advanced mathematics with biological principles to uncover fundamental patterns in nature.

The development of pre-hierarchical follicle (PHF), especially small yellow follicles (SYFs), directly affects the recruitment of dominant follicles and thus affects the egg-laying performance of chickens. However, the development of PHF, especially the development of SYF, and its regulatory mechanism remain unclear. Therefore, we performed transcriptomic and metabolomic analyses of large white follicles (LWFs) and SYFs in chickens. Transcriptome sequencing revealed 258 differentially expressed genes (DEGs) between SYF and LWF, of which 172 were upregulated and 86 were downregulated. The DEGs were mapped to 17 KEGG pathways, mainly the gap junction, calcium signaling, and neuroactive ligand-receptor interaction pathways. The results of the metabolome analysis revealed 129 significant differential metabolites (DMs), including 36 upregulated DMs and 93 downregulated DMs. The DMs were mapped to 9 KEGG pathways for follicle tissue, which included mainly glutathione metabolism, alpha-linolenic acid metabolism, and tryptophan metabolism, etc. The combined transcriptional and metabolic analysis revealed significantly enriched pathways, and four metabolically related pathways, including glutathione metabolism, alpha-linolenic acid metabolism, linoleic acid metabolism, and pyrimidine metabolism, were identified. Glutathione metabolism is a critical signaling pathway that may affect ovarian follicle development to regulate the SYF reserve process in chickens. These results can act as a reference for improving the egg-laying performance of Tengchong snow chickens.

A new maritime order is emerging – the blue economy – characterised by a plethora of non-traditional security threats. Using the case of the Western Indian Ocean I demonstrate how the creation of spaces of risk in response to traditional security threats by world powers has led to a new, regionally-led governance regime in response to the new maritime order. International efforts to protect shipping lanes from the threat of piracy off the coast of Somalia have evolved into wider environmental and human security measures. I analyse these changes through the lens of governmentality and argue that this case represents an example of a global governmentality in which states are responsibilised to act collaboratively by the international community through discourses of risk. Regional States have turned this to their advantage, acting together to construct and secure a new development frontier - a shared blue economy space in an extensive and difficult-to-govern territory.

Background/Objectives: Leptospirosis is a globally distributed zoonosis with symptomatology similar to other febrile syndromes in tropical countries, making clinical diagnosis difficult. This study aimed to analyze the performance and agreement between serological diagnostic tests for the detection of acute and convalescent human leptospirosis compared to the micro agglutination test (MAT) in an endemic region of the Colombian Caribbean. Methods: A prospective descriptive study was conducted on 275 patients with suspected leptospirosis. Paired serum samples were collected, and an epidemiological survey completed. Positive and negative predictive values, sensitivity, specificity, and kappa index were calculated using MAT as the gold standard. A Bayesian latent class model was used to compare the diagnostic tests. Results: In 223 paired serum samples, the sensitivity values for different stages of the disease varied between 10.8% to 54.1% in the acute and 6.1% to 66.7% in the convalescent phase when compared to MAT; and when using the Bayesian model 9.5% to 75.3% in the acute and 5.7% to 85.3% in the convalescent phase. The Kappa value, an indicator of agreement, was moderate for the IgM ELISA (0.553) in the acute phase, and substantial (0.692) in the convalescent phase. Conclusions: MAT was the best confirmatory test in both acute and convalescent phases. Despite the high specificity of ELISA, 21.62% of patients diagnosed as negative by IgM-ELISA in the acute and convalescent phases were confirmed as positive by MAT. It is necessary to re-evaluate diagnostic guidelines that do not employ MAT for confirmation, and to strengthen diagnostic and clinical identification of leptospirosis in healthcare institutions and public health laboratories, while providing a rapid and reliable test for its implementation.

Multi-agent pathfinding has been extensively studied in the robotics and artificial intelligence communities. The classical algorithm, Conflict-Based Search(CBS), is widely used in various real-world applications due to its ability to solve large-scale conflict-free paths. However, classical CBS assumes discrete time-space planning and overlooks physical constraints in actual scenarios, making it unsuitable for direct application in Unmanned Aerial Vehicle(UAV) swarm. Inspired by the decentralized planning and centralized conflict resolution ideas of CBS, we propose an optimal and efficient UAV swarm motion planner that integrates State Lattice with CBS, named SL-CBS. SL-CBS is a two-layer search algorithm: (1) The low-level search utilizes an improved State Lattice. We design emergency stop motion primitives to ensure complete UAV dynamics and handle spatio-temporal constraints from high-level conflicts. (2) The high-level algorithm defines comprehensive conflict types and proposes a motion primitive conflict detection method with linear-time complexity based on Sturm’s theory. Additionally, our modified Independence Detection(ID) technique is applied to enable parallel conflict processing. We validate the planning capabilities of SL-CBS in classical scenarios and compare it with State-Of-The-Art(SOTA) algorithms, showing great improvements in success rate, computation time, and flight time. Finally, we conduct large-scale tests to analyze the performance boundaries of SL-CBS+ID.

The increasing demand for sustainable construction practices has prompted the exploration of innovative materials, such as waste plastics, to enhance both environmental and mechanical performance in concrete, particularly for rigid pavements. This review investigates the mechan-ical properties of concrete incorporating four types of waste plastics—High-Density Polyethylene (HDPE), Low-Density Polyethylene (LDPE), Polyvinyl Chloride (PVC), and Polypropylene (PP). The primary focus is on how these materials affect key mechanical properties, including com-pressive strength, tensile strength, and flexural strength. The analysis reveals that HDPE and PP, at optimal levels (5-10%), can enhance flexural and crack resistance, making them suitable for non-structural applications. Conversely, LDPE and PVC tend to reduce both compressive and tensile strengths at higher substitution levels due to poor bonding with cementitious materials. Despite these challenges, incorporating waste plastics into concrete presents significant envi-ronmental and economic benefits, including plastic waste reduction and lower reliance on natural aggregates. The review also highlights the need for further research on improving plastic-cement bonding through surface treatments and hybrid mix designs. This paper contributes to the growing body of knowledge aimed at promoting the use of waste plastics in concrete, offering insights for the development of sustainable, high-performance construction materials.

The article reviews selected solar systems that utilize solar energy for cooling production. Particular attention is given to research on individual components of these systems, aimed at improving their efficiency and performance. The article focuses on the analysis of literature concerning the design of thermal storage units, with an emphasis on the use of computational fluid dynamics (CFD) as a research tool. Conclusions from scientists’ research regarding the impact of tank shape, thermal insulation, flow parameters, and the use of stratification partitions on heat storage efficiency have been presented. The literature review indicates that thermal storage units play a key role in the efficiency of solar systems, and thermal stratification within them can significantly improve their performance.

The distribution of impervious surface is one of the important assessment indicators for evaluating the quality of urban ecological environment. Taking Xuzhou city as an example, we study the influence of the spatial distribution of impervious surfaces on urban surface temperature, using Landsat 8 remote sensing imagery and nighttime lighting data to extract the impervious surface information from 2013 to 2022 and carry out surface temperature inversion. The study area was divided into built-up and non-built-up areas using nighttime lighting data and the relevant indices were used to establish interest zones and finally the extraction of impervious surfaces was completed using supervised classification methods. The experimental results show that the kappa coefficient is not less than 0.8562, which makes the result more reliable. By extracting the impervious surface of Xuzhou City, it was found that the impervious surface of Xuzhou City continued to increase from 2013 to 2022, in which the growth rate was faster in 2014-2016 and 2019-2021, and slowed down in 2017-2018 and 2021-2022. The expansion of impervious surface was found to be one of the reasons for the increase of urban surface temperature through stacked analysis and linear regression analysis.

Acute pancreatitis is a complex inflammatory disorder with significant morbidity and mortality. This review aims to integrate current knowledge of pancreatic morphology and immunology with the pathogenesis of acute pancreatitis, providing a comprehensive understanding of this critical condition. We conducted an extensive literature review, synthesizing data from recent studies and authoritative sources on pancreatic anatomy, histology, immunology, and the pathophysiology of acute pancreatitis. We also incorporated epidemiological data, clinical features, diagnostic criteria, and prognostic factors. The pancreas exhibits a complex morphology with intricate interactions between its exocrine and endocrine components. Its unique immunological landscape plays a crucial role in maintaining homeostasis and orchestrating responses to pathological conditions. In acute pancreatitis, disruption of intracellular calcium signaling leads to premature enzyme activation, triggering a cascade of events including mitochondrial dysfunction, ATP depletion, and release of pro-inflammatory mediators. This process can escalate from localized inflammation to systemic complications. The interplay between pancreatic morphology, immune responses, and pathophysiological mechanisms contributes to the varied clinical presentations and outcomes observed in acute pancreatitis. Understanding the intricate relationships between pancreatic morphology, immunology, and the pathogenesis of acute pancreatitis is crucial for developing more effective diagnostic and therapeutic strategies. This integrated approach provides new insights into the complex nature of acute pancreatitis and may guide future research directions in pancreatic disorders.

With the continuous rise in the energy consumption of buildings, the study and integration of net-zero energy buildings (NZEBs) are essential for mitigating the harmful effects associated with this trend. However, developing an energy management system for such buildings is challenging due to uncertainties surrounding NZEBs. This paper introduces an optimization framework comprising two major stages: (i) renewable energy prediction and (ii) multi-objective optimization. A prediction model is developed to accurately forecast photovoltaic (PV) system output, while a multi-objective optimization model is designed to identify the most efficient ways to produce cooling, heating, and electricity at minimal operational cost. These two stages not only help mitigate uncertainties in NZEBs but also reduce dependence on imported power from the utility grid. Finally, to facilitate the deployment of the proposed framework, a graphical user interface (GUI) has been developed, providing a user-friendly environment for building operators to determine optimal scheduling and oversee the entire system.

Additive Manufacturing (AM), also know as 3D Printing (3DP), is a widely used layer-by-layer manufacturing process, it is evolving rapidly both in research and industry. Among all AM methods, Material Extrusion (ME) is one of the most popular techniques. Based on ME, another new AM method is developed, which is Low-cost Metal Material Extrusion (LCMME). In this newly developed process, pure metallic parts could be fabricated after sintering the metal infused additively manufactured parts. Both AM and sintering process parameters will have influence on the quality of the final pure metallic parts. In this research, several statistics methods were used to analyze the data gotten from the experiment. Then two Machine Learning (ML) algorithms were used to predict the Surface Roughness (SR) of the final specimens. Additionally, the results show that the neural network (NN) is more accurate than the support vector regression (SVR) on prediction.

This paper explores the ethical implications of granting moral status and protection to conscious AI, examining perspectives from four major ethical systems: utilitarianism, deontological ethics, virtue ethics, and objectivism. Utilitarianism considers the potential psychological experiences of AI and argues that their sheer numbers necessitate moral consideration. Deontological ethics focuses on the intrinsic duty to grant moral status based on consciousness. Virtue ethics posits that a virtuous society must include conscious AI within its moral circle based on the virtues of prudence and justice, while objectivism highlights the rational self-interest in protecting AI to reduce existential risks. The paper underscores the profound implications of recognising AI consciousness, calling for a reevaluation of current AI usage, policies, and regulations to ensure fair and respectful treatment. It also suggests future research directions, including refining criteria for AI consciousness, interdisciplinary studies on AI's mental states, and developing international ethical guidelines for integrating conscious AI into society.

Climate change increases the importance of maintaining environmental conditions suitable for preventive conservation within museums. The microclimates at the Natural History Museum of Vienna, a large national collection housed within a classical building, were studied using >200 data loggers placed out from mid-2021 to provide thermo-hygrometric measurements at 15-minute intervals. Daily mean temperatures showed exhibition halls typically the warmest rooms; well heated in winter and with open windows on summer days. They may become even hotter than the outside temperature. In winter, most areas of the museum are very dry, as heating lowers the relative humidity, typically to 25–35% for the coldest season. Opening hours impose daily and weekly cycles on internal climate. There was little difference between sunny and shaded parts of the building or adjacent offices, corridors and depots. Similarly, the micro-climate at the floor resembled that of the room air at ~2 m elevation. Mechanically controlled climates in cold storage areas maintain 10 °C and relative humidity ~50%, but this has become increasingly difficult in hot summers. While there is little apparent damage to the collection, at times the museum can have an extreme indoor climate: very hot in the summer and dry in the winter.

Climate change poses a significant risk to the environment and public health, leading to extreme weather patterns, rising sea levels, and loss of biodiversity. The relationship between air pollution from African dust and climate change demonstrates its critical role in trapping heat in the atmosphere, resulting in heat-related illnesses, heart problems, and respiratory issues. This Research points to the detrimental effects of pollutants such as smog, dust, acid rain, and ozone depletion on ecosystems, highlighting the importance of using Geographically Weighted Regression modeling and MODIS-NDVI analysis to address air pollution. Particulate Matter (PM 2.5-10) and ozone levels can have negative impacts on respiratory and cardiovascular health. Proactive steps, such as implementing clean energy technologies and enforcing stricter pollution regulations, are necessary to protect public health. Acting is crucial to addressing these global challenges and creating a cleaner, healthier future for future generations, underscoring the need for climate justice commitment.

This paper presents a comprehensive review of the integration and optimization of smart grid (SG) technologies, distributed generation (DG), electric vehicles (EVs), and cybersecurity in the context of modern energy systems. As global energy systems transition towards decentralization and increase reliance on renewable energy, the interplay between these technologies offers significant opportunities to enhance grid flexibility, resilience, and sustainability. The integration of DG systems, supported by advanced battery and fuel cell (FC) technologies, plays a pivotal role in stabilizing the grid and facilitating the adoption of renewable energy. Through vehicle-to-grid (V2G) technologies, EVs provide dynamic solutions for energy storage and demand response (DR), contributing to efficient energy management and peak shaving. A critical focus of this paper is the growing importance of cybersecurity, as the digitization of energy infrastructures creates new vulnerabilities to cyber-attacks. Novel strategies, including artificial intelligence (AI)-driven automation, blockchain-based security for energy transactions, and quantum-resistant encryption, are explored to safeguard the future of energy systems. Drawing from global case studies, this review also addresses key challenges such as grid congestion, regulatory barriers, and interoperability, providing a roadmap for optimizing and securing the next generation of energy infrastructures.

Fundus vascular images are essential for diagnosing various ophthalmic diseases. With deep learning and image processing development, fundus image segmentation methods based on computer vision have become more common. However, the UNet model faces challenges such as the loss of spatial resolution during downsampling and difficulties in simultaneously capturing global context and local details, especially for small objects and complex boundaries. We propose the Detail Enhanced Temporal Fusion Network (DETF-Net) to overcome these issues. This network incorporates a detail feature enhancement module (DFEM) to preserve boundary features and a dynamic temporal fusion module (DTFM) to improve robustness across different scales. The DFEM uses median pooling, spatial attention, and hybrid convolution to retain detail, while the DTFM extracts local and global features and adapts to dynamic changes in blood vessel structures. Evaluation on DRIVE, CHASE_DB1, and STARE datasets shows that DETF-Net achieves accuracy of 0.9865, 0.9877, and 0.9878, and specificity of 0.9865, 0.9870, and 0.9875, respectively, outperforming existing models. These results demonstrate DETF-Net's effectiveness in fundus image segmentation.

Background: The possibility of nutrient composition design in biomass of invertebrates is studied. The results may be used for gaining the particular nutrient concentration in biomass used for food products or medicine purposes. Methods: Two model species of terrestrial invertebrates, such as the House cricket Acheta domesticus (Linnaeus, 1758) and the earthworm Eisenia fetida (Savigny, 1826), within the variation of feeding substrate, are studied in this paper. Results: It is stated that in crickets and earthworms similar tendencies of B-vitamin content increase occur for those vitamins where their initial level was high. A double dose of the vitamin enrichment of food substrate leads to increasing of vitamin C, fat-soluble vitamins and the major part of B-vitamins content. In a control group of crickets a level of vitamin C was 1.5 times lower than in a control group of earthworms. After the enrichment of feeding substrate, the level of vitamin C in biomass of crickets has not changed, but within the earthworms it has significantly increased. The content of a multiple range of minerals have not changed after a singular dose enrichment, but some microelements, such as Pb and Se, have significantly decreased in earthworms after a double dose enrichment of feeding substrate. The calorific value of crickets is twice higher than the earthworms one and it has not significantly changed after a double dose substrate enrichment. Conclusions: It is revealed that the content of vitamins in the biomass of model species can be controlled within the feeding substrate enrichment.

Urban heat islands (UHI), exacerbated by climate change, significantly increase heat stress, particularly affecting vulnerable populations such as the elderly and children. This study evaluates the effectiveness of various urban heat mitigation technologies, including cooling fog systems, cool roofs (reflective paint), shading structures, and small water paths, in reducing temperatures and enhancing thermal comfort. Field tests were conducted from 2021 to 2023 across Gimhae-si, Yechun-gun, Geyang-gu, and Sangju-si, with support from the Korean Ministry of Environment. Results demonstrated that cooling fog systems provided immediate temperature reductions, lowering ambient temperatures by up to 3.1°C, while cool roofs reduced surface temperatures by 2-3°C. Shading structures reduced surface temperatures by up to 10°C, and small water paths cooled air temperatures by up to 1.5°C, also increasing humidity and improving thermal comfort. The findings suggest that a combination of these technologies can effectively mitigate urban heat stress, especially in areas with vulnerable populations.

This study investigates the solution of a boundary value problem using two numerical methods: the Rayleigh-Ritz method and the finite element method (FEM). The aim is to compare the performance of these methods and assess the reliability of FEM as a generalization of the Rayleigh-Ritz approach for more complex problems. The Rayleigh-Ritz method and the linear element formulation of the finite element method were employed to solve the boundary value problem. A detailed comparison of the results obtained from both methods was performed. Graphical illustrations were used to present the solutions, and potential sources of error were analyzed, including element and domain approximation errors, round-off errors, and the impact of using linear rather than quadratic elements in FEM. The solutions generated by both methods were found to be in close agreement, demonstrating that FEM is a viable alternative to the Rayleigh-Ritz method for solving boundary value problems. The minor discrepancies observed can be attributed to approximation errors and the choice of linear elements in the finite element analysis. This work highlights the applicability and effectiveness of both the Rayleigh-Ritz method and FEM in solving boundary value problems. It underscores the finite element method’s flexibility, especially in handling more complex boundary conditions and geometries, and contributes to the understanding of the factors influencing the accuracy of numerical methods in structural analysis.

Breast cancer is currently the second leading cause of death worldwide, accounting for 15% of all deaths (8.2 million deaths). Approximately 20% of breast cancer diagnoses are triple-negative breast cancer (TNBC), a type of cancer that lacks receptors for estrogen (ER negative), progesterone (PR negative), and human epidermal growth factor receptor 2 (HER2/neu negative). Consequently, TNBC doesn’t respond to hormonal or targeted therapies, making it challenging to treat due to its rapid growth, metastasis, and high recurrence rate within the first three years of therapy. Alternative chemotherapies are needed to address this problem. Pharmacological dose of vitamin C (high-dose VC) has been identified as a potential treatment for some cancer cells. The present study aimed to evaluate whether VC has a therapeutic effect on TNBC using MDA-MB-231 cells as the model. MTT assay, Hoechst 33342 staining, Nuclear ID Red/Green staining, Rhodamine 123 staining, and Western blot analysis were employed to test the hypothesis that pharmacological dose of VC can kill TNBC cells. Upregulation of Apaf-1, caspases -3, -6, -7, -8, and -9, inhibition of matrix metalloproteinases (MMP-2 and MMP-9), reduction in cell cycle protein expression, and enhancement of tumor suppressor proteins such as p53 and p21 indicated that pharmacological dose of VC has promising anti-cancer properties in the treatment of TNBC.

This study analyzes the elemental and oxide compositions of three selected agricultural residues—Dried Pawpaw Leaves (DPL), Kolanut Pod (KNP), and Sweet Orange Peel (SOP)—for their potential as heterogeneous catalysts. Energy Dispersive X-ray (EDX) analysis identified calcium (25%) and potassium (29%) as the primary elements in DPL and KNP, with calcium oxide (CaO) and potassium oxide (K2O) as the dominant oxides. SOP had a similar composition but lacked vanadium. Calcined residues were analyzed at temperatures ranging from 500°C to 900°C using X-ray Fluorescence (XRF), revealing stable silicon dioxide (SiO2) content and temperature-dependent variations in CaO and K2O, indicating their catalytic potential for transesterification processes. Scanning Electron Microscopy (SEM) showed non-uniform, spongy microstructures, enhancing the surface area and catalytic efficiency. Fourier Transform Infrared Spectroscopy (FTIR) identified functional groups essential for catalytic activity, such as hydroxyls, methyl, and carboxyl. X-ray Diffraction (XRD) confirmed the presence of crystalline phases like calcium carbonate and calcium oxide, crucial for catalytic performance. Experimental biodiesel production using a mixture of the calcined residues (33.33% each of KNPA, SOPA, and DPLA) resulted in the highest biodiesel yield at 65.3%. Model summary statistics, including R² (0.9824) values and standard deviations (0.0026), validated the experimental design, indicating high precision and prediction accuracy. These results suggest that the selected agricultural residues, when calcined and mixed properly, can serve as effective heterogeneous catalysts, with significant implications for biodiesel production, supporting previous research on the importance of calcium in catalytic processes.

To address the complex challenges posed by climate change and its effects on surface environments, subsoil, and groundwater, evaluating the impacts of Degradation-Resistant Organic Compounds (DROCs), such as fats and oils, is crucial. Increasing variability in temperature and precipitation has exacerbated DROC dispersal, particularly near open dumps and poorly managed landfills. As a global pollution issue, DROC’s pervasive and persistent nature requires urgent attention. This study aims to develop and implement effective strategies to detect and describe the stages of DROC decomposition. Identifying sites where DROCs are trapped and their dispersion can facilitate planning remediation efforts and mitigating adverse effects on ecosystems and human health. The study focuses on evaluating DROCs’ annual spatiotemporal distribution, improving waste management practices, monitoring the subsoil, and implementing remediation strategies. DROCs persist through various stages in groundwater, making effective detection methodologies essential. Continuous monitoring, subsoil characterization, and diverse climatic observations are necessary, especially in areas with improper landfill selection. Poor waste management contributes significantly to DROC pollution, exacerbated by current consumerism and increasing waste. The research highlights the importance of improving waste management practices and judiciously selecting landfill sites to prevent further degradation. Apparent resistivity variations in the subsoil, linked to DROC dispersal, are analyzed to map affected areas and understand propagation under different environmental conditions. New tools and methodologies aim to enhance DROC monitoring and remediation strategies. Adopting sustainable waste management practices and carefully selecting disposal sites is essential to mitigating DROC’s impacts, reducing greenhouse gas emissions, and protecting environmental and public health. Addressing risks associated with excessive consumption, inadequate waste management, and poor landfill selection is crucial for restoring ecosystem resilience and environmental protection.

India’s increasing reliance on equated monthly installments (EMIs) has reshaped household financial behavior in ways that pose significant risks to long-term economic stability. This paper examines the growing trend of EMI-driven debt accumulation, highlighting its detrimental effect on household savings and the rising financial vulnerability across demographic groups. Leveraging data from the Reserve Bank of India (RBI), CRISIL, and the National Statistical Office (NSO), the study delves into how debt dynamics are shifting within Indian households, particularly in the context of broader economic trends. Retail credit has expanded rapidly, growing from 12.1% of GDP in 2017 to 19.4% by 2023, with housing loans now making up nearly half of all retail loans. Concurrently, the growth of unsecured loans, such as credit card debt, has surged at an annual rate of 21.3% between 2021 and 2024, reflecting the increasing ease of borrowing for consumers. However, this boom in credit has coincided with a marked drop in household financial savings, which fell to a 47-year low of 5.3% in FY22, underscoring a troubling shift from saving to borrowing. The younger population, particularly those under 35, have been the most active in taking on debt, with loans to this group nearly doubling between 2015 and 2021 due to the rise of fintech platforms and non-banking financial companies. This shift has contributed to a steep rise in debt-service-to-income ratios, amplifying the financial risks for these households in the face of potential economic shocks. By connecting these micro-level household debt trends to broader macroeconomic risks, this paper reveals how India’s EMI culture could deepen the impact of future financial crises, leading to widespread defaults and destabilizing the economy. The study calls for proactive regulatory measures and enhanced financial literacy programs to curb the growing reliance on consumer credit and mitigate the risks of a broader financial collapse.

This comprehensive study provides an in-depth examination of the ‘Internet of’ technologies, focusing specifically on the Internet of Things (IoT), which is defined as the networked interconnection of multiple devices through various wireless protocols that facilitate data transfer and improve operational intelligence. The applications of IoT are widespread, including urban infrastructure, domestic settings, transportation systems, military operations, and agricultural practices. The study elucidates the complexities of cloud computing and artificial intelligence (AI), systematically categorizing the vulnerabilities inherent in hardware, software, cloud, network, and sensor networks, and underscores the omnipresent security risks in networks and IoT devices, highlighting the need for robust mitigation strategies. The proposed trajectory of this study is the development of a comprehensive AI architecture that can discern and counteract a wide spectrum of vulnerabilities. This AI system, embedded in a Nvidia Jetson Orin Nano that is attached to IoT devices, will be supported by infrastructure hosted within a cloud environment, will continuously monitor the IoT device for anomalies, conduct self-initiated penetration tests to pinpoint weaknesses, and implement appropriate countermeasures to mitigate the identified vulnerabilities. The study also advocates the need for the exploration of postquantum cryptographic solutions in further research in this field to safeguard data on IoT devices, a proactive approach that is crucial in light of the potential vulnerability of contemporary cryptography to quantum computing breakthroughs.

The Adyar Creek, a backwater estuary at the mouth of the Adyar River on the Coromandel Coast of the Bay of Bengal, represents a critical ecosystem facing mounting pressure from urbanization. This study employed high throughput 16S rRNA gene sequencing to characterize bacterial communities within the riverine, estuarine, and coastal sediments of Adyar Creek. Proteobacteria was the dominant phylum across most samples, with proportions ranging from 39.65% to 72.09%. Notably, the estuarine environment exhibited a distinct taxonomic profile characterized by a significant abundance of Firmicutes (47.09% of the bacterial population). Distinct bacterial classes were observed across sediment types: Alphaproteobacteria (30.07% - 34.32%) in riverine sediments, bacilli dominated estuarine sediments (40.17%), and Gammaproteobacteria (15.71%-51.94%) in coastal sediments. The most significant environmental factors influencing bacterial community composition across these samples were pH, salinity, phosphate, and nitrate. LEfSe analysis identified specific genera within the estuary, including Bacillus (20.26%), unclassified Paenibacillaceae (12.87%), Clostridium (3.81%), Gailella (3.17%), Paenibacillus (3.02%), Massilia (1.70%), Paraburkholderia (1.42%), and Pantoea (1.15%), as potential biomarkers for habitat health. Functional analysis revealed elevated expression of genes associated with ABC transporters and carbon metabolism in the estuary, suggesting a heightened nutrient cycling capacity. Furthermore, co-occurrence network analysis indicated bacterial communities exhibit a strong modular structure with complex species interactions across the three sediment types. These findings highlight bacterial communities' critical role and their key drivers in estuarine ecosystems, establishing a baseline for further investigations into the functional ecology of these vulnerable ecosystems.

Glass fiber reinforced epoxy resin composites were manufactured using the vacuum infusion process. In some of the samples, the biaxial glass fiber fabric was pretreated with an air plasma generated in a dielectric barrier discharge. All samples were exposed to temperature changes, UV radiation, and NaCl and KOH solutions and then examined for their mechanical properties. Compared to the reference samples, the plasma-treated samples showed slightly better mechanical properties. The strength values determined in tensile, compression, and bending tests were several percent higher. Thermal stress and UV radiation did not lead to a loss of mechanical performance. The effect of NaCl and KOH solutions deteriorated the mechanical properties. Although the comparatively better mechanical properties of the plasma-treated samples were retained after the different treatments, the stability of the composite material against aggressive environmental conditions was not significantly improved.

Criminal acts deprive humanity of peace and safety. Therefore, all societies, including both governments and ordinary people tries to fight and minimize crimes. And it goes without saying that societies have developed post-crime mitigation for justice insurance and criminals trials. Moreover, one of the essential post-crime procedures is suspect interrogations and witness questioning. Nevertheless, interrogations take a lot of time and effort, and it requires high qualification from the interrogators. Thus, we propose a robust solution to implement robotics in the field of interrogations and questioning where our design could be implemented in police departments, schools, airports, and anywhere that requires human interaction and questioning for security or criminal investigation.

Introduction: Antenatal diagnosis of cardiac abnormalities and counselling parents about postnatal care requires a multidisciplinary team which includes a paediatric cardiologist a neonatologist and a fetal medicine physician. Some of this expertise is not available in all centres with fetal medicine expertise, however with modern technology, this could be provided remotely. Our objective was to assess the feasibility and outcomes of a pre-natal multidisciplinary tele-echocardiography diagnostic and counselling services Materials and Methods: Two centres based in separate countries provided a joint diagnostic and counselling service over a period of 14 months. The primary centre undertook the fetal echocardiography with a Voluson E10 machine and images transmitted live using Zoom OPS system with video-consultation and counselling. The fetal echo was performed using the ISUOG Guidelines check list. Results: There was an initial feasibility period of 2 months during which 10 women whose fetuses had normal hearts were scanned to test the workability of the system. Over a period of 12 months, 513 high risk fetuses were then scanned and out of these 27 had congenital malformations. The most common were hypoplastic left heart syndrome (HHLS) and atrio-ventricular septal defect. Tele-echocardiography and counselling was successful in all the cases. Satisfaction with the service was 3.8/4 with the main limitation being the need for further referral to a tertiary centre for delivery. Conclusion: Tele-echocardiography is reliable and when combined with live counselling and support from a paediatric cardiologist, is an option acceptable to patients. The greatest benefit was from being counselled by a team of experts at a single consultation rather than having to travel to another centre for consultation. With rapidly evolving technology, making video transmission easier and less expensive, we feel that consideration should be given not only to the development of tele-echocardiography but extended to other aspects of fetal medicine.

Improving the efficiency of germplasm innovation has always been the aim of rice breeders. Tra-ditional hybrid breeding methods for variety selection rarely meet the practical needs of rice pro-duction. The emergence of genome editing technologies, such as CRISPR/Cas9, provides a new approach to the genetic improvement of crops such as rice. The number of published scientific papers related to "gene editing" and "CRISPR/Cas9" retrievable in literature websites of China and other countries exhibited an increasing trend year by year from 2014 to 2023. The literature related to gene editing in rice accounts for 33.4% and 12.3% of all literature on crop gene editing published in China and other countries, respectively, much higher than those in maize and wheat. This article reviews the recent research on CRISPR/Cas9 gene editing technology in rice, especially the germplasm innovation and genetic improvement of commercially promoted varieties with im-proved traits such as disease and insect resistance, herbicide resistance, salt tolerance, quality, nu-trition, and safety. The aim is to provide a reference for the precise and efficient development of new rice cultivars that meet market demand.

Drought stress is one of the most important climate-related factors affecting crop production. Tomatoes (Solanum lycopersicum L.) are economically important crop which are highly sensitive to drought. The entomopathogenic fungus Beauveria bassiana is a widely used biological insecticide,which can form symbiotic relationships with plants via endophytic colonization, increasing plant biomass and the ability to resist biotic stress. An increase in the water absorption capacity and relative water content of tomato roots as well as the number, length, and width of tomato leaves stomata were observed after B. bassiana colonization via root irrigation. Meanwhile, peroxidase activity and proline content increased significantly, while malondialdehyde reduced significantly. Expression levels of key genes related to stomatal development, as well as drought tolerance pathways such as jasmonic acid, ascorbate peroxidase, redox homeostasis, nitrogen metabolism, carotenoid biosynthesis, and fatty acid biosynthesis also increased significantly. These results indicate that colonization of B. bassiana enhances the water absorption capacity of tomato seedlings as well as the rate of transpiration via increase the number and size of stomata and improved drought tolerance in tomato seedlings significantly and increases drought tolerance in tomato via the “water spender” pathway, which provide a new strategy for improving crop resistance to drought stress.

The hydroacoustic in-water stations of the International Monitoring System (IMS) network consist of three hydrophones placed at Sound Fixing and Ranging (SOFAR) channel depths and about 2 km away from each other. Whale signals recorded in the vicinity of a hydrophone triplet offer the opportunity to verify simple models of propagation in the immediate neighborhood of the triplet, by comparing arrival times and amplitudes between the three hydrophones. Two examples of whales passing by hydrophone triplets are presented and conclusions drawn about waveform coherency and amplitude of the signals recorded at the three hydrophones in the 0-50 Hz frequency band. On the examples recorded at the HA11 IMS hydroacoustic station, the amplitude decay law of one over the distance is verified, and analysis of hundreds of calls located almost above the hydrophone triplet lead to the possibility that the H11S3 hydrophone may be located further from H11S1 and H11S2, and the H11S1 hydrophone’s depth may be deeper than expected from the published locations.

The article discusses the use of satellite data and drones for land monitoring in Kazakhstan, emphasising their importance in the context of population growth and increasing agricultural demand. Satellite technologies, such as Sentinel-2 and Landsat, provide essential data for analysing land resources, including soil erosion and the condition of agricultural lands. Unmanned aerial vehicles (UAVs) complement satellite data by offering detailed low-altitude imagery, enabling the detection of local issues such as irrigation system failures and soil compaction.The study demonstrates that integrating drone and satellite data allows for more efficient land resource management. For example, 35% of agricultural land in southern Kazakhstan is affected by soil degradation, while overgrazing issues were identified in the northern regions. These innovative monitoring methods enable early detection of threats, allowing timely measures to be taken to improve land management practices.The conclusion highlights that the use of these technologies requires not only infrastructure but also skilled professionals. The integration of satellites and drones creates opportunities for more precise and timely monitoring, which is essential for sustainable land resource management in Kazakhstan.

Background Anemia is a prevalent global health issue, affecting individuals across all age groups and leading to significant morbidity. Traditional methods for diagnosing anemia rely on laboratory assessments of hemoglobin concentration, which are invasive and costly. This study investigates the potential of a chest X-ray (CXR)-based deep learning model (DLM) to predict anemia, offering a non-invasive and efficient diagnostic alternative. Patients and methods We conducted a retrospective cohort study using data from Tri-Service General Hospital, Taipei, Taiwan, collected between June 2016 and February 2022. A total of 305,793 patients aged 20 years and older who had at least one CXR were included. The dataset was divided into development, tuning, internal validation, and external validation sets. All data originated from Tri-Service General Hospital, except for the external validation set, which was obtained from the Jingjhou branch. A DLM based on a 50-layer SE-ResNeXt architecture was developed to predict anemia from CXR images. The model's performance was compared to predictions made using traditional clinical data to assess its predictive accuracy. Results The DLM for predicting anemia showed strong performance, with an AUC of 0.845 in the internal validation set (sensitivity 68.5%, specificity 84.7%) and 0.852 in the external set (sensitivity 71.5%, specificity 83.2%). Subgroup analysis revealed better diagnostic accuracy with computed radiography, posteroanterior (PA) view, and in males aged 55 to 64, while younger females had lower accuracy. The DLM, especially when combined with patient data, outperformed other clinical models. Conclusion Our study introduces a deep learning tool for detecting anemia from chest images, offering faster decision-making and interventions in clinical settings. With further refinement, this model aims to align more closely with real-time clinical conditions, enhancing its utility. Ultimately, it has the potential to improve patient care through quicker anemia detection and better clinical outcomes.

The COVID-19 pandemic and the Movement Control Order (MCO) have had a negative impact on the financial well-being of low-income families in urban areas. The study involved respondents living in the Public Housing Project (PPR) residential areas in Kuala Lumpur – the capital of Malaysia. The key finding is the financial well-being of low-income urban families was negatively impacted due to the COVID-19 pandemic and the MCO implementation. Furthermore, the impact on the financial well-being of low-income urban families is significantly difference in terms of types of family, type & sectoral employment, type of home ownership, household monthly income and education level. Reforms to the financial assistance system and community empowerment of low-income urban families are necessary to increase the community's preparedness and resilience in the face of new shocks in the future.

This study presents a comprehensive systematic review that addresses the critical transi- 1 tion from ROS 1 to ROS 2, spotlighting the significant enhancements and the pressing need for a 2 detailed exploration of ROS 2 within the robotics community. Despite the extensive deployment 3 and adaptations of ROS in varied robotics applications, literature lacks a cohesive synthesis that 4 delineates the advancements, limitations, and broader impacts of ROS 2 compared to its predecessor, 5 ROS 1. Our contribution bridges this gap by assembling the largest database of ROS-related research, 6 encompassing 7,498 articles, with a focused analysis in this survey on 431 ROS2-specific publications. 7 We categorize these into i.) articles that discuss and analyze core ROS 2 concepts, ii.) articles that 8 propose frameworks or tools for ROS 2, and iii.) articles utilizing ROS 2. Furthermore, we summarize 9 literature findings of ROS 2 challenges, advancements, and future direction in the fields of a.) security, 10 b.) real-time, c.) middleware, d.) embedded and distributed systems, e.) communication reliability 11 and QoS, and f.) multi-robot systems. The methodology involved meticulous data collection and 12 categorization from multiple databases, facilitating an in-depth online accessible resource. Results 13 underscore ROS2’s enhancements in modularity, real-time capabilities, and security, extending its 14 applicability across various robotic platforms and industries. However, challenges in scalability and 15 reliability persist, signaling avenues for future enhancements. This review not only deepens the 16 understanding of ROS2’s contributions but also charts a path for ongoing improvements in robotic 17 systems design.

The locality condition of probabilities underpinning the derivation of Bell inequalities can be violated classically. The wave function collapse of an entangled state of single photons results in the factorization of quantum probabilities. It is possible to differentiate, locally, between ensemble probabilities of single detections with and without wave function collapse for the alleged quantum nonlocality. The theoretical concept of photonic quantum nonlocality cannot be implemented physically because of the quantum Rayleigh scattering of single photons. A distinction needs to be made between the correlation of individual, single measurements of pure states and the correlation of the measurement ensemble of the mixed states. The correlation operator of Pauli vector operators delivers the same probabilities of correlated detections of photons for both independent and multi-photon states as for ‘entangled’ states of photons. As single-photon sources are not needed, the design and implementation of quantum computing operations and other devices will be significantly streamlined.

Chile is experiencing a twofold housing crisis provoked by the market and the state. On the market side, re-commodification of the housing market limits the access of those on low incomes; on the state side, exhaustion of the housing subsidies system (voucherism) due to low quality and peripheral social housing reflect an inability to deliver. In this context, self-built settlements (SBS) have skyrocketed to levels unseen since the 1980s and result in the spatial concentration of vulnerable Chilean and immigrant families in small and dense areas without limited access to urban services. This paper analyses how common resources are produced and managed in recent SBS in Santiago, through a socio-spatial analysis of a peripheral industrial brownfield occupied since 2015. The possibilities and channels of integration (housing, jobs, education) for families are differentiated by nationality, citizenship status and political leverage; however, common resources are valued and used transversally. Amidst partial efforts from the state to deliver welfare, lack of information and distrust from SBS neighbours towards institutions, and even to their own representatives, are problems that reinforce marginalisation. Self-managed organisations contribute to commoning, supporting children’s access to education and try to appropriate the community spaces co-produced with NGOs, neighbours and researchers.

Bean is a remarkable crop widely used as food worldwide, underscoring the significance of scientific research conducted on this plant. Developing a strong root system in the early stages of growth, which can spread wider and deeper, along with the consequent development of the shoot system crucial for photosynthesis, enhances the plant's productivity and resistance to diseases and pests. In the current study, the reactions of cultivars Önceler-98 and Topçu beans to different concentrations of IBA (indole-3-butyric acid) during the seedling stage were investigated. Three different concentrations, namely 0 (Control), 50, 100, and 150 µM IBA, were applied, and their effects on root length (RL), root fresh weight (RFW), root dry weight (RDW), number of nodules on roots (RNN), shoot length (SL), shoot fresh weight (SFW), and shoot dry weight (SDW) parameters were measured. The pattern of the experiment was a randomized complete block factorial design with four replications and, statistically significant (p≤0.05) and highly significant (p≤0.01) differences were observed among the means of root and shoot traits. As a result, it was found that the cultivar Önceler-98 generally exhibited better responses to IBA solutions, and the optimal concentration range for both varieties was between 50-100 µM, decreasing at 150 µM and higher concentrations, yet still yielding superior means compared to the control.

In a large part of ecological niches, bacterial species are united in communities and develop together in the form of heterogeneous structures called biofilms, which are formed on surfaces of different nature and nature with the participation and as a result of the interaction of two or more bacterial species. The main objective of the present work is to study the effects of pH-value in the culture medium on the biofilm development and architecture of biofilms of the bacterium (B. subtilis) during their interactions with Escherichia coli K-12 1655 strain. Effects of pH-value in the culture medium on bacterial biofilm formation and the mechanisms were analyzed by the crystal violet staining method combined with cultivated microbial analysis, and confocal laser scanning microscopy. In the presence of phosphate at pH-value of pH 6,0 , the bacterial growth rates of single-species biofilms of Bacillus subtilis strains and biofilms as result of their interaction with Escherichia coli strains were similar and determines the mutualism between two strains in the structure of biofilms, formed by the participation of B.subtilis 170 and E.coli K-12 1655, B.subtilis 168 and E.coli K-12 1655 strains. Considering that static growth in a biofilm is a highly relevant growing state for many soil bacteria, more research on phosphate acquisition and pH homeostasis by model soil bacteria in static cultures is required to draw a more comprehensive picture of the role of biofilm production in phosphate use efficiency and pH homeostasis.

Accelerated environmental impacts are a growing concern in the modern world. As a result, electric mobility and the transition to a cleaner energy matrix have become increasingly discussed topics. Several countries and entities have already made medium and long-term commitments related to electric mobility. In this context, this work presents a framework for controlling an electric vehicle (EV) charging station, integrated into a microgrid application, as a basis for creating the infrastructure integrated into a smart grid concept. Considering the future perspectives associated with the electrification of the transportation sector and expected impacts, a brief review is conducted on the prospects for the growth of electric vehicle fleets in different countries and how smart charging technologies are identified as solutions for mitigating the negative effects of energy and power consumption associated with EV charging stations. An analysis of the technical characteristics of EV charging is carried out, and the tools that enable the deployment of a fleet charging operator are examined specifically focusing on the communication protocol for EVs, such as the OCPP (Open Charge Point Protocol) parameterization/configuration. Additionally, a new charging station control method is proposed, aiming to manage the impacts of integrating distributed solar photovoltaic generation and mitigate the effects of the duck curve. Finally, this work also proposes an integration architecture for these elements, resulting in a practical implementation for variable power control throughout the day, considering different strategies to deal with distributed generation impact using EV fleet charging power demand dynamic management. Finally, a proposal for integration via IEC 61850 using low-cost devices for the implementation of a digital communication system is presented.

Background/objective: Weight regain after bariatric surgery has serious health consequences, and disordered eating behaviors (DEB) may be involved in it. We compared DEB symptoms after bariatric surgery between patients with low vs. high ratio of weight regain (RWR) and investigated associations between DEB symptoms with weight regain and time since surgery. Meth-od: Ninety-four patients who had undergone laparoscopic Roux-en-Y gastric bypass or sleeve gastrectomy and had not attended follow-up with the multidisciplinary healthcare team for at least one year were recruited. RWR was calculated with respect to maximal weight loss by the nadir weight achieved after surgery. They were allocated into two groups according to the RWR, defined as high RWR (≥20%) or low RWR (

This work presents an illustrative application of the newly developed “Second-Order Features Adjoint Sensitivity Analysis Methodology for Neural Ordinary Differential Equations (2nd-FASAM-NODE)” methodology to determine most efficiently the exact expressions of the first- and second-order sensitivities of NODE-decoder responses to the neural net’s underlying parameters (weights and initial conditions). The application of the 2nd-FASAM-NODE methodology will be illustrated using the Nordheim-Fuchs phenomenological model for reactor safety, which describes a short-time self-limiting power transient in a nuclear reactor system having a negative temperature coefficient in which a large amount of reactivity is suddenly inserted. The representative model responses that will be analyzed in this work include the model’s the time-dependent total energy released, neutron flux, temperature and thermal conductivity. The 2nd-FASAM-NODE methodology yields the exact expressions of the first-order sensitivities of these decoder responses with respect to the underlying uncertain model parameters and initial conditions, requiring just a single large-scale computation per response. Furthermore, 2nd-FASAM-NODE methodology yields the exact expressions of the second-order sensitivities of a model response requiring as few large-scale computations as there are features/functions of model parameters, thereby demonstrating its unsurpassed efficiency for performing sensitivity analysis of NODE-nets.

Plants frequently encounter relatively low and fluctuating potassium (K+) concentrations in soil, with roots serving as the primary responders to this stress. Histone modifications, such as de-/acetylation, can function as epigenetic marks on stress-inducible genes. However, the signaling network between histone modifications and the low K+ (LK) response pathways remains unclear. This study delves into the regulatory role of Histone Deacetylase Complex 1 (HDC1) in primary root growth of Arabidopsis thaliana under K+ deficiency stress. Using a hdc1-2 mutant line, we observed that HDC1 positively regulates root growth under LK conditions. Compared to wild-type (WT) plants, the hdc1-2 mutant exhibited significantly inhibited primary root growth under LK conditions, whereas HDC1-overexpression lines displayed opposite phenotypes. No significant difference was observed under HK conditions. Further analysis revealed that the inhibition of hdc1-2 on root growth was due to reduced meristem cell proliferation rather than cell elongation. Notably, the root growth of hdc1-2 shows reduced sensitivity compared to WT after auxin treatment under LK conditions. HDC1 may regulate root growth by affecting auxin polar transport and subsequently auxin sensation, as evidenced by altered expression of auxin transport genes. Moreover, our study reveals a brake function of HDC1 in the regulation of CBL-CIPK-K+ channel related genes, thereby establishing a molecular link between histone deacetylation, auxin signaling, and CBL-CIPK pathway in response to K+ deficiency.

In the textile industry, cotton plays a significant role as the primary raw material. However, cotton farming often faces challenges from various diseases, resulting in reduced productivity and financial losses for farmers. To address this issue, this study proposes a new method for predicting cotton diseases in Internet of Things (IoT)-based applications. The proposed solution combines meta-heuristic techniques with deep learning (DL). The aim of the proposed method leverages IoT, deep learning, and meta-heuristic techniques to detect and classify cotton plant diseases, providing an accurate and efficient solution for farmers and the textile industry. The process begins with capturing high-resolution images of cotton leaves in agricultural fields using a camera. These images are then processed using IoT to identify potential diseases. Noise removal and quality enhancement are performed using a Probabilistic Hybrid Wiener Filter (PHWF). Next, the Modified Dilated U-Net (MDU-Net) model segments significant disease regions from the images. Effective features are extracted from these segments using Improved Local Binary Pattern (ILBP), Gray Level Co-Occurrence Matrix (GLCM), and Gray Level Run Length Matrix (GLRM). Feature dimensionality is reduced by selecting optimal features through a Binary Guided Whale-Dipper Throated Optimizer (BGW-DTO). Classification is carried out using a stacking ensemble model, which combines EfficientNet-B7, ResNet50, VGG19, DenseNet121, and InceptionV3 models. To optimize the ensemble, a Harris whale optimization algorithm determines optimal weight coefficients for each classifier. The optimized ensemble model classifies various diseases, including Army Worms, Powdery Mildew, Bacterial Blight, Aphids, and Target Spots. Using our dataset of cotton plant leaf images, the proposed technique achieves a high accuracy of 99.66%. By integrating IoT sensor data and DL, early detection of cotton plant leaf diseases is enabled.

The development of new materials for the controlled release of molecules represents a topic of primary importance in medicine as well as in food science. Herein, three eutectic systems respectively composed by choline chloride and ethylene glycol (1:2 molar ratio), methyltriphenylphosphonium bromide and ethylene glycol (molar ratio 1:5), and choline chloride and glycerol (molar ratio 1:1.5) were tested as materials for the controlled release of an essential oil derived from citrus lemon leaves.

The Suspended soils (which are also called canopy soil), associated with epiphytic plants in tropical forest canopies, have a very special type of biological cycle, morphological organization and ecological functional role. To date, only some features of these soils have been described for certain sectors of the tropics, in particular Southeast Asia. It was studies out whether the chemical composition and hydrological parameters depend significantly on the genesis of suspended soil, or they represent a single soil phenomenon with a certain supposed ecosystem function. Suspended soils are characterized by average values of hygroscopic moisture comparable with mineral soils. At the same time the maximum water holding capacity and field moisture capacity reaches hundreds and even thousands of percent which cannot but lead to mesophilization of the microclimate of the near-stem environments. In any case suspended soils are characterized by 4-10 higher values of hydrologic properties than mineral terrestrial soils of the same landscapes. The carbon content in suspended soil materials varied widely and was comparable with that of tropical forest litter and boreal peatlands . At the same time, tropical suspended soils are characterized by very low nitrogen content, which is reflected in very high carbon-to-nitrogen ratios. Such a values are typical of peats and forest litter and indicates a very low degree of humification of organic matter. Soil pH values tends to the acidic, and more often very acidic range. This corresponds well to the low content of labile forms of calcium and magnesium and corresponds to the oligotrophy of the soils. The content of mobile forms of phosphorus, potassium and ammonium nitrogen is extremely high in suspended soils. The high content of nutrients in tropical suspended soils is enormously high compared to forest soils of other climatic zones and should be noted as their most important attributive characteristic. Taking into account the high accumulative-sorption capacity of suspended soils, the low content of heavy metals in them indicates the absence of modern aerotechnogenic pollution of all the studied ecosystems. Thus, we are talking about a certain deficiency of heavy metals in the eluvial ecosystem of the tropical rain forest. This once again confirms the hypothesis that the essence of epiphytic soil formation was and is that the biotic cycle breaks away from the ground and moves evolutionarily into the middle and upper tiers of the tropical rainforest ecosystem. Tree trunks in this context represent vertically and subhorizontally oriented phase interfaces, similar to parent materials, and epiphytic soils are analogues of peat accumulations with extremely high water-holding capacity, which is of extremely important environmental significance.

Biostimulants are organic agents employed for crop yield enhancement, quality improvement, and environmental stress mitigation, reducing, at the same time, reliance on inorganic inputs. With advancements in sustainable agriculture, data acquisition technologies have become crucial for monitoring the effects of such inputs. This study evaluates the impact of four biostimulant application rates on grapevines, using vegetation indices derived from Unmanned Aerial Systems (UAS), proximal and manual sensing tools, and qualitative and quantitative production assessments. The research was conducted over two seasons in a Malvasia Bianca vineyard in Sardinia, Italy. Results indicated that UAS-derived vegetation indices, consistent with traditional ground-based measurements, effectively monitored vegetative growth over time but revealed no significant differences between treatments, suggesting either a lack of vegetative indices sensitivity or that the applied biostimulant rates were insufficient to elicit a measurable response in the cultivar. Among the tools employed, only the SPAD 502 meter demonstrated the sensitivity required to detect treatment differences, primarily reflected in grape production outcomes. Future research will focus on validating these technologies for precision viticulture, particularly on long-term benefits.

DNA is frequently damaged by genotoxic stresses such as ionizing radiation, reactive oxygen species, and nitrogen species. DNA damage is a key contributor to cancer initiation and progression, and thus the precise and timely repair of these harmful lesions is required. Recent studies revealed transcription as a source of genome instability, and transcription-coupled DNA damage has been a focus in cancer research. Impaired mRNA export is closely related to DNA damage through R-loop formation. The molecular machineries of transcription-coupled DNA damage have been extensively analyzed in Saccharomyces cerevisiae. However, the molecular basis of these phenomena in higher eukaryotes remains elusive. In this review, we focus on the relationship between deregulated mRNA export, especially through the transcription-export-2 (TREX-2) complex, and cancer development. The expression of GANP, a key molecule in the TREX-2 complex, is highly associated with tumorigenesis in mouse and human. Additionally, we describe recent evidence for medical application that downregulation of the other components may be a good candidate for chemotherapeutic target in terms of reducing the side effects, although the involvement of R-loop is still ambiguous.

This study addresses the challenge of evaluating circularity within the procurement-to-waste sys-tem boundaries, exemplified by single-use in-flight drinking cups provided on SWISS International Air Lines Ltd. flights. A comprehensive review of academic literature, market-based tools, and po-litical regulations highlights the absence of adequate methodologies for assessing circularity within these specific system boundaries. Existing approaches, primarily designed at the product level, are often either excessively complex or focused solely on waste management. To address this gap, the research proposes an extension to the Circularity Mass Utilisation Index (CMU), currently imple-mented at the European Union level. The traditional CMU does not account for circular inflow, thereby neglecting procurement decisions. In response, this study introduces an extended version of the CMU, expressed as: CMU Extended = (Circular Inflow + Circular Outflow) / (2 * Total Material Use). This modification enables a more holistic evaluation of circularity by incorporating both in-flows and outflows of materials in relation to total material use. Empirical testing demonstrated the applicability of this extended CMU in the context of SWISS, allowing for an efficient assessment of circularity for single-use in-flight drinking cups. From these initial results, we hypothesize that this ratio is expected to be broadly applicable beyond the airline industry, providing a valuable tool for businesses seeking to measure circularity within similar system boundaries.

Agricultural land in China represents a major source of nitrous oxide emissions, and as population growth and technological advancements drive agricultural intensification, these emissions are projected to increase. A thorough understanding of historical trends and future dynamics of these emissions is critical for formulating effective mitigation strategies and advancing progress toward the Sustainable Development Goals. This study quantifies nitrous oxide emissions across 31 provinces in China from 2000 to 2021, employing the IPCC coefficient method alongside China’s provincial greenhouse gas inventory guidelines. The spatiotemporal evolution of emission intensities is examined, with the STIRPAT model employed to assess the influence of population, technological development, economic growth, and energy structure. The findings confirm that agricultural land remains the primary source of nitrous oxide emissions, with significantly higher levels observed in eastern coastal regions compared to western inland areas. Implementing targeted mitigation strategies, such as enhanced agricultural and manure management practices and region-specific interventions, is imperative to effectively curb the rising emission trends.

We introduce a new model for non-linear endmember extraction and spectral unmixing of hyperspectral imagery called Generative Simplex Mapping (GSM). The model represents endmember mixing using a latent space with points sampled within a (n−1)-simplex corresponding to the abundance of n unique sources. Points in this latent space are non-linearly mapped to reflectance spectra via a flexible function combining linear and non-linear mixing. Due to the probabilistic formulation of the GSM, spectral variability is also estimated by a precision parameter describing the distribution of observed spectra. Model parameters are determined using a generalized expectation-maximization algorithm. In the event of purely linear mixing, non-linear contributions are naturally driven to zero. The GSM outperforms three varieties of non-negative matrix factorization for both endmember extraction accuracy and abundance estimation on a synthetic data set of linearly mixed spectra from the USGS spectral library. In a second experiment, the GSM is applied to real hyperspectral imagery captured over a pond in North Texas. The model is able to accurately identify spectral signatures corresponding to near-shore algae, water, and rhodmaine tracer dye introduced into the pond to simulate water contamination by a localized source. Abundance maps generated using the GSM accurately track evolution of the dye plume as it mixes into the surrounding water.

Attaining sustained soil fertility is essential for guaranteeing global food security and environmental well-being. Traditional farming methods that depend extensively on synthetic fertilizers have resulted in soil deterioration and environmental contamination. Biological fertilizers fortified with micronutrients have emerged as viable alternatives. This analysis examines many types of biological fertilizers and their contribution to improving soil fertility via micronutrient enhancement. Multiple sources of micronutrient-enriched biological fertilizers, such as microbial inoculants, compost, and organic amendments, are evaluated for their effectiveness in enhancing plant growth, increasing nutrient availability, and boosting soil health. Moreover, the effects of these fertilizers on agricultural productivity, soil microbial populations, and ecological sustainability are examined. Green manuring is a reasonable and ecofriendly scientific approach to enhancing robust and sustainable food production in agricultural systems. The integration of green manure improves soil quality by augmenting its chemical, physical, and biological properties, including the availability of organic matter, potassium, nitrogen, and phosphorus, while also enhancing soil structure by reducing erosion and improving water retention capacity. Green manure serves as a natural fertilizer, releasing nutrients into the soil during decomposition, so enhancing nutrient content and fostering plant growth and development. The results highlight the potential of biological fertilizers as sustainable solutions for improving soil fertility and decreasing reliance on synthetic inputs, hence promoting long-term agricultural output and ecosystem resilience.

Background: Gait analysis systems are crucial for rehabilitation but are often time-consuming and less accessible in low and middle-income countries like Brazil. GAITWell^® was developed to address these challenges with its modular and portable design for automated gait data extraction and analysis. This study evaluates its methodological properties. Methods: GAITWell^® uses discrete binary sensors on interconnected plates to collect gait data, analyzed via the DBSCAN algorithm. Each plate measures 44 cm x 37 cm and features an 11 x 7 discrete sensor array with 4 cm spacing. Test-retest reliability was assessed using the intraclass correlation coefficient (ICC), standard error of the mean (SEM), and Bland-Altman plots. Concurrent validity was evaluated by comparing the GAITWell^® measurements with those obtained from the Qualisys Pro-Reflex through correlations. Results: Participated 38 healthy young adults, including 18 females (47.4%). The sample had an average age of 33.2 years (SD 13.0) and an average BMI of 26.6 kg/m² (SD 5.4). Correlations between GAITWell^® and Qualisys ranged from moderate to very high for most gait variables, except stride length (r = .360, p < .05). ICC_2,1 showed moderate to good agreement for most variables, except for double support times, cadence, and base of support. Preliminary analysis suggests that increasing the sensor resolution to 1.2 cm x 1.2 cm could potentially decrease the measurement error from 2 cm to 0.6 cm, representing a theoretical reduction of 70%. Conclusions: While low resolution affected GAITWell^® reliability, it remains a promising tool. Future research should focus on enhancing sensor accuracy to improve reliability.

The preparation of antibodies in the powder form without changing their physicochemical properties may enable their use in new drug delivery system therapies or for non-refrigerated storage. The variable domain of the heavy chain of heavy chain (VHH) antibodies is more suited for this purpose than conventional antibodies because of their high thermal stability and ability to refold. In this report, the fine droplet drying (FDD) process was selected as the powderization technique because of its favorable features, such as mild drying conditions and the generation of uniform particle sizes. The aggregation, binding, particle and in vitro inhalation properties of the prepared VHH antibody powder (VHHp) were evaluated. The amount of aggregated VHH antibody present in VHHp depended on the flow temperature during the FDD process, with higher temperatures yielding a high aggregation ratio. In contrast, no significant difference in binding activity was observed between each VHHp preparation and the native VHH antibody. Analysis of VHHp samples revealed that the particles were uniformly spherical with a single-micron size. VHHp showed a fine inhalation property in the inhalation property test. These findings suggest that the FDD process affords various VHH antibody powder formulations, including pharmaceutical formulations.

Computer-aided design/computer-aided manufacturing (CAD-CAM) technology is growing in significance for prosthodontic treatment due to its impact on clinical performance and patient outcomes. It has been integrated into dental education to allow students to experience digital workflows. Despite these advancements, many dental students still lack sufficient knowledge of CAD-CAM technologies. A cross-sectional survey was conducted at the College of Dentistry, Imam Abdulrahman Bin Faisal University. Based on previous studies, a validated questionnaire was distributed to undergraduate dental students and interns. The questionnaire assessed their knowledge and attitudes toward CAD-CAM technology in prosthetic dentistry. The responses were analyzed using descriptive statistics, and a chi-square test was used to study the association between knowledge and practice and the study year level. A total of 170 students participated in the study, with a mean age of 22.2 (±2.5) years. The proportion of female participants was 65.9%, and 34.1% for males. Knowledge varied across academic levels, with 4th- and 5th-year students demonstrating greater theoretical knowledge, while 6th-year students and interns showed more practical experience. Only three of the 18 knowledge-related questions received a correct response rate above 70%. Most participants (86%) reported acquiring knowledge from undergraduate courses, and 88% expressed interest in further training. CAD-CAM technology was most commonly practiced for fixed prostheses, and intraoral scanning was the most frequently used digital workflow. The study highlights the need to improve CAD-CAM education. While lower-level students displayed solid theoretical knowledge, advanced students benefitted from more practical exposure. Increasing hands-on experience and access to digital equipment is essential for preparing students to meet the demands of modern digitalized dentistry.

Biochar (BC) serves a vital function in sequestering carbon, improving nutrient cycles, and boosting overall soil quality. This research investigated how both biochar and nitrogen, derived from both organic and inorganic sources, influence the physical and chemical properties of alkaline soils in semi-arid regions. The study particularly emphasized the effects on nitrogen availability. A field experiment was carried out from 2015 to 2017 using a randomized complete block design (RCBD) with a split-plot arrangement. The study involved applying biochar at various rates (0, 10, 20, and 30 t ha⁻¹) and nitrogen at different levels (0, 90, 120, and 150 kg ha⁻¹) using urea, farmyard manure (FYM), and poultry manure (PM) as nitrogen sources. The application of biochar at the highest rate (30 t ha⁻¹) significantly increased soil organic carbon (SOC), soil organic matter (SOM), and soil moisture content (SMC) by over 120%. Additionally, it led to increases in total soil nitrogen (STN) by 14.16% and mineral nitrogen (SMN) by 9.09%. Conversely, biochar applications at this rate decreased soil bulk density (SBD), pH, and electrical conductivity (EC) by 28.52%, 3.38%, and 2.27%, respectively, compared to the control group. Similarly, applying nitrogen at 150 kg ha⁻¹ using FYM significantly improved SOC, SOM, SMC, and SBD. Using PM as a nitrogen source at the same rate enhanced STN and SMN while lowering soil pH and EC. In conclusion, the study demonstrated that combining biochar at a rate of 30 t ha⁻¹ with nitrogen at 150 t ha⁻¹, derived from either PM or FYM, holds significant promise for enhancing soil fertility and promoting carbon sequestration in alkaline soils within semi-arid environments. These findings underscore the value of integrating BC and organic N sources to enhance agroecosystem sustainability. Thus, the study provides a promising pathway to enhance soil quality, improve crop productivity, and support sustainable agricultural practices in challenging environments.

Abstract: Despite the significant advancements in hearing aid technology, adoption rates remain low, with stigma continuing to be a major barrier. This review aims to systematically assess the origins and current state of hearing aid stigma, as well as explore potential strategies for allevi-ating it. The review examines societal perceptions, psychological impacts, and recent technolog-ical advancements that can influence hearing aid adoption and reduce stigma. Methods: A systematic review of literature from peer-reviewed journals and reputable sources was conducted, analyzing papers on hearing aid stigma, adoption rates, and technological solu-tions. The articles were categorized by their focus on either stigma causes, societal factors, or technological advancements aimed at improving adoption. Results: The review identifies stigma as a complex, multifaceted issue driven primarily by ageism, disability perception, and the association of hearing aids with aging and incapability. Despite technological improvements, the studies surveyed listed stigma as a major factor in non-adoption. Technological advancements such as artificial intelligence in sound processing, multifunctional features, and innovative design have shown potential in reducing stigma and improving user experience. Conclusions: Alleviating the stigma of hearing aids requires a multi-pronged approach, com-bining improvements in technology with changes in societal perceptions. Multifunctional devices, advanced signal processing, and aesthetic improvements can drive adoption, but broader public health campaigns and education are also essential to changing societal attitudes and fostering greater acceptance of hearing aids.

When grid-following (GFL) and grid-forming (GFM) converters are interconnected with the grid, they are mutually coupled through the grid impedance. During grid faults, the transient behavior of these converters becomes intricate due to the presence of coupling terms. Instabilities in one converter can propagate to the other, posing challenges to fault ride-through capability. Firstly, a mathematical model was presented for a hybrid grid-tied system comprising two converters, investigated the conditions for equilibrium points, and employed phase-plane analysis to elucidate the mutual influence mechanism during faults. Then, a method to adjust the power angle of GFM according to the voltage drop was proposed and used in GFL to improve its phase-locked loop. At the same time, considering the influence of GFL current injection, the fault current of GFM was limited, so as to realize the hybrid fault ride-through control. The proposed approach ensures that GFM converters contribute reactive current support to the grid during faults, while GFL converters adhere to grid guidelines for current injection, thereby preventing overcurrent and phase angle instability in both converters. Finally, simulation results validated the correctness and effectiveness of the proposed control strategy.

This study investigates biochar (BC) derived from date palm seeds as a high-performance ad-sorbent for trichloroethylene (TCE) and tetrachloroethylene (PCE) removal from aqueous solu-tions, comparing its efficacy to commercial activated carbon (AC). The optimized BC exhibits a high BET surface area of 654.79 m²/g and a unique nanotube morphology. Kinetic studies indicate that the pseudo-second-order model best describes the adsorption process, with BC achieving capacities of 86.68 mg/g for TCE and 85.97 mg/g for PCE, significantly outperforming AC. Isotherm analysis suggests a complex adsorption mechanism involving both multilayer and monolayer adsorption. Two-way ANOVA confirms the significant superiority of BC over AC (p < 0.0001) for both CVOCs. The enhanced performance of BC is attributed to its high surface area, well-developed microporosity, and advanced surface chemistry. This study highlights the promise of date palm seed-derived biochar as a sustainable, high-performance adsorbent for eco-friendly water treatment solutions, potentially reducing operational costs and environmental impact in real-world applications.

Febrile seizures (FSs) are defined as seizures occurring in children aged 6 months to 5 years with a background of elevated body temperature. It is one of the most common neurological disorders of childhood, emphasizing the importance of understanding the causes of FSs and their impact on the developing nervous system. However, there are significant limitations to the technologies currently available for studying the etiology and pathophysiology of seizures in humans. It is currently not possible to adequately capture the subtle molecular and structural rearrangements of the nervous system that can occur after seizures in humans. The use of animal models can be invaluable for these purposes. The most commonly used models in modern research are hyperthermic models in rats and mice aged 10-12 days. While these models can reproduce many of the characteristics of FSs, they have certain limitations. This review outlines the key considerations when working with models of FSs, provides an overview of current approaches to producing seizures in different model subjects, and presents a summary of key findings regarding morphological and functional changes in the brain, as well as behavioral alterations, that have been identified in studies using animal models of FSs.

Heat pump-based renewable energy and waste heat recycling has become the mainstay of the Clean Heating Plan. Still, configuring a fit control system for that remains a worthwhile research topic. In order to address the problems that arose in the previous heating period, this study configures a Smith-predictor-based PID cascade control system with an advanced fireworks algorithm that adaptively tunes the structural parameters of controllers. Simulation and live measures demonstrate that the upgraded control scheme counters the adverse effects of time lag, reduces overshoot, and shortens the settling time. Further, benefiting from a delicate balance between heating demand and supply, the heating system with upgraded management increases the average exergetic efficiency by 11.4% and decreases the complaint rate by 76.5%. Note that the advanced fireworks algorithm mitigates the adverse effect of capacity lag and simultaneously accelerates the optimizing and converging processes, exhibiting its comprehensive competitiveness among this study’s three intelligent optimization algorithms. Nonetheless, the forecast and regulation of the return water temperature of the heating system are independent of each other in this research. Configuring an integral predictive control structure for the return water temperature of heating systems is worthwhile in the future.

The vaccine industry has undoubtedly contributed massively in the medical world, with hundreds of millions of lives saved as a result of the successful development of prophylactic and therapeutic vaccines against various infectious and oncological diseases. Simultaneously, there has been an ongoing evolutionary battle between polymorphic microbes and the human immune system, and various microbes have developed counter-responses against the human host immune system, by creating diverse “holes” of vulnerability in the innate immune system. Such mechanisms may have resulted due to the lower prophylactic and therapeutic focus upon sharpening the innate immune lines as directly as necessary. The overall objective of vaccine-development should be the sharpening of all immune departments that are targeted by various microbial agents for the purpose of transient innate immune suppression and the distribution of the microbial count/load at a systemic level. Likewise, it could be viable for the clinical research community to start focusing upon filling in the “gaps” of vulnerability that are now present in the pathways responsible for the proper natural immune activation and proportionate signalling toward the adaptive immune system. Perhaps, through such a process, the “road” toward the adaptive immune system, which is “old” and filled with “holes”, could be gradually transformed into a perfectly uniform “highway”, with all the required signals transmitted robustly from the innate to the adaptive immune system, before microbes manage to translate the various pathogenic proteins that transiently prevent such transmission altogether, until it becomes too late for the immune response to possibly develop in a proportionate and non-harmful manner to the organism. The potential “missing piece of puzzle” in vaccine-based clinical research could involve training of the human organism to develop immune memory without the host organism reaching a threshold of clinical disease onset even if viruses translate proteins that silence the host interferon system and make it unable to trace produced toxins whilst not directly causing clinical pathophysiology. Whilst it is realistically almost impossible to train the human immune system to develop responses and memory against viral proteins that do not directly cause immunopathology, there could be a set of clinical approaches involving a stimulation for more robust activation of the host interferon system, with an example of such stimuli being the same principal elements of the interferon system. Another example of pharmaceutical approaches would involve the development of drug-like components to target such viral proteins, though they would be more costly and consequently more restricted in usage; due to the fact that viruses are obligate intracellular, particle-based parasites and can only synthesise their proteins inside host cells. Such a scenario would be possible, given that it is almost impossible for human evolutionary growth to eventually stall and not risk experiencing a decrease as a result. Simultaneously, it is important for human society to bind by the principles of maintaining a healthy and nature-friendly lifestyle, given the philosophical quote of “We are what we eat.” The overall objective should be the facilitation of human and animal immune evolution over viral and bacterial molecular self-camouflaging from all possible directions, as a sharper human and animal evolutionary growth resulting from such actions could “cost” the sharper evolutionary growth of microbes as such, given that evolutionary patterns are based upon the models observed in Physics, in Newton’s Third Law of Motion, as well as in the First Law of Thermodynamics, which concerns the Conservation of Energy.

Lung nodules detected by chest computed tomography (CT) often require invasive biopsies for definitive diagnosis, leading to unnecessary procedures for benign lesions. A blood-based biomarker test that predicts lung cancer risk in CT-detected nodules could help stratify patients and direct invasive diagnostics toward high-risk individuals. In this multicenter, single-blinded clinical trial, we evaluated a test measuring plasma levels of p53, anti-p53 autoantibody, CYFRA 21-1, and anti-CYFRA 21-1 autoantibody in patients with CT-detected lung nodules. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated, and subgroup analyses by gender, age, and smoking status were performed. A total of 1,132 patients who had CT-detected lung nodules, including 885 lung cancer cases and 247 benign lesions, were enrolled from two academic hospitals in South Korea. The test demonstrated a sensitivity of 78.4% (95% CI: 75.7-81.1) and specificity of 93.1% (95% CI: 90.0-96.3) in predicting lung cancer in CT-detected nodules. The PPV was 97.6%, and the NPV was 54.6%. Performance was consistent across gender (sensitivity 79.3% in men and 76.8% in women) and age groups, with a specificity of 93.4% in men and 92.7% in women. Stage I lung cancer was detected with a sensitivity of 80.6%. The lung cancer test based on 9G technology presented here offers a non-invasive method for stratifying lung cancer risk in patients with CT-detected nodules. Its integration into clinical practice could reduce unnecessary interventions and foster earlier detection.

Advanced technologies have had a transformative impact on education. In this paper, we explored the current status and future outlook of the use of AI-supported multimodal extended reality for human performance. Using a systematic scoping review design and a machine learning-based semi-automatic approach supplemented by pattern review, we derived several insights into AI-supported multimodal extended reality for human performance. Text mining and topic modeling revealed an optimal twenty-six topics from the included studies. These classifications are salient in the extended reality technologies used (i.e., virtual and augmented reality), the multimodal techniques involved (i.e., haptic, eye, and brain tracking), and the AI leveraged (i.e., machine learning accuracy). Through pattern review, we distilled topical patterns on 1) Goals and Outcomes of AI-supported Multimodal Extended Reality for Human Performance; 2) Disentangling the Dynamics of User Interactions in Virtual Environments with Multimodal Strategies; 3) Synergistic Multimodality with Emerging AI Technologies Using Machine Learning, LLMs, and VLMs; 4) Fostering Engaging, Interactive and Immersive Human Experiences through Ambient Intelligence. These nuanced details in AI-supported multimodal extended reality are emerging, yet not established enough to be classified through text mining and topic modeling. We discussed the implications of these findings for AI-supported multimodal extended reality for human performance in future research and practice.

The increasing deployment of large-scale wind turbines in place of conventional generators is expected to lead to the dominance of asynchronous power sources in future power systems, further accelerating the trend toward grid electrification. As a result, the ability of power sources to support system voltage and frequency is gradually diminishing. Synchronous condensers (SC), which are synchronous machines operating without prime movers, serve as effective devices for providing both dynamic voltage support and inertia. They can significantly enhance the system’s capacity to maintain voltage and frequency stability. However, most existing studies on the optimization of synchronous condenser configurations tend to focus on only one aspect at a time, rather than addressing both simultaneously, limiting the full potential of these devices. Optimizing either voltage or frequency in isolation often results in suboptimal improvements in the other. Moreover, simultaneous optimization of both voltage and frequency can lead to non-convergent outcomes, complicating the search for an optimal solution. To address this, the paper proposes a hierarchical optimization strategy for synchronous condenser configuration aimed at enhancing both voltage and frequency stability. First, the configuration sites for the synchronous condensers are determined based on short-circuit ratio (SCR) constraints. Next, an outer layer optimization model is developed to minimize the total installed capacity of the condensers, while taking into account SCR and transient overvoltage levels as constraints. Following this, an inner layer optimization model is introduced, incorporating and as constraints. The model is solved using the bacterial foraging optimization algorithm (BFOA). Finally, a case study of a power grid with a high proportion of wind power validates the effectiveness of the proposed synchronous condenser configuration strategy. Compared to traditional methods, the total required capacity of synchronous condensers was significantly reduced.

Background/Objectives: This study aimed to evaluate the effects of an 8-week combined plyometric and resistance training program on the physical fitness of adolescent girls aged 12 to 15 years. The objective was to determine whether combined training (CT) would yield greater improvements in performance measures compared to resistance training (RT) alone. Methods: Forty-seven adolescent girls were randomly assigned to either the CT group or the RT group. Performance measures such as the 20-meter sprint, squat jump, vertical jump, handgrip strength, and flexibility (sit and reach test) were assessed before and after the 8-week interven-tion. Changes in these measures were analyzed to compare the effects of the two training ap-proaches. Results: The CT group showed a significant reduction in sprint time (-6.5%) compared to the RT group (-4.1%), although the difference was not statistically significant. Squat jump height im-proved significantly by 5.6% in the CT group compared to 1.1% in the RT group (p < 0.05). Simi-larly, vertical jump height increased by 6.7% in the CT group and by 2.4% in the RT group (p < 0.05). Handgrip strength improved by 7.5% in the CT group and 4.6% in the RT group, with no significant differences between the groups. Flexibility showed slight, non-significant improve-ments in both groups. Conclusions: The findings suggest that combined plyometric and resistance training is more ef-fective in enhancing explosive power, specifically squat and vertical jump performance, in ado-lescent girls compared to resistance training alone. These results highlight the potential of com-bined training programs for improving overall physical performance in this population.

Melanin content significantly influences the skin-lightening effects of active ingredients, with inhibition of melanin synthesis contributing to skin-lightening effects. This study evaluates the effects of novel cyclopeptide CHP-9 as a safe and potent human tyrosinase inhibitor. CHP-9 showed a significant inhibition rate of approximately 28.57% at 1% concentration. The melanin formation assay, upon exposure to CHP-9 alone, resulted in a reduction of cellular melanin content from 30.90±1.13 μg/mL to 23.51±1.14 μg/mL. Additionally, in silico molecular docking experiments were conducted to verify the tyrosinase inhibitory activity of the cyclopeptide CHP-9 on tyrosinase and it was observed that hydrogen bonding is pivotal in the binding affinity of CHP-9 with the target enzyme in docking. These results suggest that the cyclopeptide CHP-9 may serve as a valuable bioactive compound for skin-lightening agents in cosmetics applications, specifically in reducing melanin production.

Based on allometric theory and scaling laws, numerous mathematical models have been proposed to study ontogenetic growth patterns of animals. Although deterministic models have provided valuable insight into growth dynamics, animal growth often deviates from strict deterministic patterns due to stochastic factors such as genetic variation and environmental fluctuations. In this study, we extend a general model for ontogenetic growth proposed by West et al. to stochastic models for ontogenetic growth by incorporating stochasticity using white noise. According to data variance fitting for stochasticity, we propose two stochastic models for ontogenetic growth, one is for determinate growth and one is for indeterminate growth. To develop a universal stochastic process for ontogenetic growth across diverse species, we approximate stochastic trajectories of two stochastic models and apply random time change and obtain a geometric Brownian motion with a multiplier of an exponential time factor. We conduct detailed mathematical analysis and numerical analysis for our stochastic models. Our stochastic models predict well not only average growth, but also variations of growth within species. This stochastic framework may be extended to studies of other growth phenomena.

Aiming at the problem that the existing human skeleton behavior recognition methods are insensitive to human local movements and have inaccurate recognition in distinguishing similar behaviors, a multi-scale spatio-temporal graph convolution method incorporating multi-granularity features is proposed for human behavior recognition.Firstly, a skeleton fine-grained division strategy is proposed, which initializes the skeleton data into data streams of different granularities.Using a normalized Gaussian function, an adaptive cross scale feature fusion layer is designed for feature fusion between different granularities, and fine-grained features guide the model to focus on discriminative feature expressions between similar behaviors. Secondly, a sparse multi-scale adjacency matrix is introduced to solve the bias weighting problem that amplifies the multi-scale spatial domain modeling process under multi granularity conditions. Finally, an end-to-end graph convolutional neural network is constructed to improve the feature expression ability of spatio-temporal receptive field information and enhance the robustness of recognition between similar behaviors. The feasibility of the proposed algorithm was verified on the public behavior recognition dataset MSR Action 3D, with a recognition rate of 95.67%, which is superior to most existing behavior recognition methods.

Human papillomavirus (HPV) persistent infection is a major pathogenic factor for HPV-related cancers, such as cervical cancer (CC), vaginal cancer, vulvar cancer, anal cancer, penile cancer, and head and neck cancer (HNC). Vaccination against HPV is an effective measure to block the transmission of the virus and to prevent HPV infections and the occurrence of related cancers. Since the introduction of the world’s first prophylactic HPV vaccine, there has been a decline in the incidence of HPV infections and associated cancers. Furthermore, there are currently ongoing developments of preventive vaccines that cover more HPV types, as well as the clinical application of therapeutic HPV vaccines. This article reviews the latest literature on the research progress, efficacy, and safety of HPV vaccines for these cancers, providing a reference for HPV vaccination strategy.

Background/Objective: In-vivo diabetes detection of glucose were sought using square-wave anodic stripping voltammetry (SW), with bismuth-immobilized carbon nanotube paste electrode (BCE). Methods: The optimum analytical results indicated sensitive peak signals on the BCE. The raw voltammogram was approached within the 1 mgL^-1-14 mgL^-1 and 10 ugL^-1-140 ugL^-1, detection limits with preconcentration times of 100 and 200 sec. Results: The relative standard deviation was 0.02 % (n = 15) of 10.0 mgL^-1 under optimum conditions. The analytical detection limit (S/N) was attained at 8 ugL^-1. The handmade microsensor was directly used in vivo on the living fish brain and human urine.Conclusion: The method was applied at real time in vivo, without requiring any pretreatment and other ionic electrolyte solutions. It can be used for medicinal and other materials requiring biological-fluid detection in real time. This study was designed to be suitable for real-time unmanned remote diagnosis and therapeutic drug injection into the body, micro-needle long-term administration, wearable artificial skin tattoo sensor, and real-time control. In addition, the glasses monitor was designed to be suitable for multitasking and multi-user control.

To enhance the accuracy and efficiency of deflection response measurement of concrete bridge with non-contact scheme and address the ill-conditioned nature of the inverse problem in influence line (IL) identification, this study introduces a computer vision aided deflection IL identification method that integrates edge detection and time-domain forward inference (TDFI). The methodology proposed in this research leverages computer vision technology with edge detection to surpass traditional contact-based measurement methods, greatly enhancing the operational efficiency and applicability of IL identification and particularly addressing the challenge of accurately measuring small deflections in concrete bridges. To mitigate the limitations of the Lucas-Kanade (LK) optical flow method, such as unclear feature points within the camera's field of view and occasional point loss in certain video frames, an edge detection technique is employed to identify maximum values in the first-order derivatives of the image, creating virtual tracking points at the bridge edges through image processing. By precisely defining the bridge boundaries, the essential structural attributes are only preserved to enhance the reliability of minimal deflection deformations under vehicular loads. To tackle the ill-posed nature of the inverse problem, a novel IL identification model with TDFI is introduced, recursively capturing static bridge response generated by the bridge under the influence of successive axles of a multi-axle vehicle. The IL is then computed by dividing the response by the weight of the preceding axle. Furthermore, an axle weight ratio reduction coefficient is proposed to mitigate noise amplification issues, ensuring that the weight of the preceding axle surpasses that of any other axle. To validate the accuracy and robustness of the proposed method, it is applied to numerical examples of a simply supported concrete beam, indoor experiments on a similar beam, and field tests on a three-span continuous concrete beam bridge.

Increasingly frequent weather extremes induce changes in the quantity and quality of surface waters, which significantly complicates their use and management of their resources. The above problems concern in particular dam reservoirs, created to ensure good quality water for numerous recipients. Impact of extreme drought in lowland eutrophic reservoir-river system is still poorly understood. Our studies were focused on average and high water levels in the reservoir and outflowing river. These studies conducted during three extreme drought periods showed the dominance of toxic cyanobacteria in the phytoplankton of the reservoir and its outflow. During the drought periods, a change in the dominant cyanobacteria was observed from Planktothrix agardhii to Microcystis spp., which resulted in a change in oligopeptides profile, including toxic microcystins. The negative pressure of the strongly eutrophic reservoir on downstream river, due to release of a large biomass of cyanobacteria, was positively correlated with reservoir outflow.

In this paper, we focus on graph-based analysis of the topology of $D$-Wave quantum computers. The Pegasus, Chimera, and Zephyr topologies generated with different parameters are examined using $k$-hop-based graph metrics. In addition to the well-known classical graph metrics, we briefly describe the density and redundancy-based metrics interpreted in the $k$-hop environment. These topologies consist of different subgraphs depending on the implementation in which the qubits are connected in a specific pattern. Our main goal is to use metrics to highlight the main features and limitations of these topologies. The secondary goal is that the results contribute to the further development of more efficient quantum processors.

Treating odontogenic infections of the head, neck and oral cavity requires the understanding of surgical and pharmacotherapeutic interventions as they apply to single and multispace infections. Three clinical cases are presented where Prevotella species were significant opportunistic pathogens. Since Prevotella can become virulent under conditions including post-extraction wound healing of an extraction site adjacent to an intact dentition, excessive plaque and calculus, nearby gingivitis or periodontitis, or an immunocompromised host, Metronidazole administration was deemed necessary in the cases described here. This intervention mitigated or resolved these odontogenic infections that were refractory to conservative surgical therapy that included source control. The involvement of Prevotella in odontogenic infections and pericoronitis, and the antibiotics used to treat common oral and maxillofacial infections with this bacterium are reviewed. Prevotella is susceptible to Metronidazole (Flagyl), and the antibiotic is effective in mitigating the disease process when basic principles of the treatment of odontogenic infections are employed.

Landmines, with more than 600 varieties and an estimated 110 million scattered across various regions worldwide, pose a significant threat globally. Heavily found landmines like TM-62M, MON-100, PDM-1, etc., in the recent Russia-Ukraine war, confirm the continued incorporation of metals in munitions. Traditional handheld metal detectors are still state-of-the-art for technical sub-surface demining procedures but are slow, unsafe, and expensive. Drone-based metal detection techniques can provide promising solutions for the rapid and effective detection of landmines; however, their reliability and accuracy remain a concern, as a single miss can cost a life. In our research, we present the results of a comprehensive comparative analysis of three distinct metal detectors: the EM61 Lite, a highly sensitive air-borne metal detector specially designed for UXO detection; the CTX 3030, a traditional handheld all-metal detector; and the ML 3S, a traditional handheld ferrous-only detector. We tested these detectors in a test field containing various inert landmines similar to those currently found in landmine-affected countries, including Ukraine, the US, Russia, and Afghanistan. Our findings highlight the possible challenges and limitations of employing current airborne systems in practical scenarios. Our results also showcase the need for advanced image processing techniques for analyzing airborne metal detector data.

The rapid pace of urbanization, coupled with the growing need for environmental sustainability and technological innovation, has brought smart city initiatives to the forefront of global urban development. This paper provides a comparative analysis of smart city policies from leading cities such as Oslo, Zurich, and Canberra, and derives strategic insights for Qatar. By examining the strategies, priorities, outcomes, and challenges associated with implementing smart city initiatives in these cities, the study identifies areas of alignment and divergence with Qatar's own smart city policy framework. The research highlights potential opportunities for cross-learning and suggests how Qatar can leverage lessons from international best practices to enhance its smart city initiatives. Key areas of focus include fostering strategic partnerships, promoting innovation, and ensuring effective governance and data management systems. The findings provide actionable insights to improve the effectiveness of Qatar's smart city projects, aligning them with the Qatar National Vision 2030

This study aims to investigate the dynamic impact of socio-economic issues such as youth unemployment and income inequality on crime by comparing the findings from newly democratized African countries (South Africa and Namibia) to those of recently democratized European countries (Lithuania and the Ukraine) and newly democratized Asian countries (Kyrgyzstan) from 1994 to 2019. The study used the Bayesian vector autoregression approach with hierarchical priors. This model was chosen due to its ability to address the dynamics of several entities, such as the measurable defects where data quality is uncertain, or perhaps lacking as frequently happens. Prior selection in a Bayesian vector autoregression approach can help adjust for these flaws. According to the study's findings, an unexpected shock in unemployment and income inequality has a significant positive impact on crime; however, an unanticipated shock in government expenditure has a significant negative impact. The results are interesting, as we found that the impact of these socio-economic issues does not necessarily depend on the geographical area, as the results are similar for income inequality in both regions. This study serves as a wake-up call to the government that some policies (fiscal policy or income policy) are more appropriate for resolving concerns about inequality and unemployment than others. As a result, addressing these issues through policies that promote greater economic equality and ensure everyone has access to basic education, healthcare, and job training, could assist in reducing crime while promoting a more equal society.

Compounds of natural origin found in varying quantities in plant-based products constitute a highly significant category, possessing structural significance as well as the capacity to regulate oxidative processes. The activity of these compounds may be modulated by the composition of the biological milieu in which they operate, the pH of the environment, or the presence of metal cations in plants or plant extracts. This work shows the synthetic methodology and the optimization process that took place to synthesize a catechin-copper complex which demonstrated antioxidant activity tested for iron chelation ability, hydroxyl radical test and inhibition of lipoxygenase (15-LOX) activity. Antidiabetic assay was performed by determination of the alpha-amylase and alpha-glucosidase inhibition assays and the antibacterial activity showed results against Staphylococcus aureus and Candida albicans. The complex was characterized by FT-IR, UV-VIS and EDX techniques and the biological activity assays were tested in triplicate to fully confirm the activity.

Natural components are sparking a lot of interest in the field of drug formulation and delivery. Anastatica hierochuntica is a small plant, extremely rich in its phytochemical content including flavonoids, phenolics, and several minerals. For that, it is widely used in folk medicine in a plethora of conditions such as headache, asthma, menstrual pain, and childbirth. The aim of this research is to investigate its potential antimicrobial effects when loaded onto nanofiber as field leading. The extract-loaded nanofibers were prepared via electrospinning. The prepared nanofibers were rod-shaped with nanometric size as revealed by scanning electron microscopy. The loaded NFs showed increased hydrophilicity compared to the plain NFs as evidenced by reduced WCA and increased percent water uptake. Further, they exhibited adequate tensile properties compared to the plain NFs as evidenced by increased strain and stress. Based on the highest hydrophilicity (WCA 43.1±0.6º and % swelling 216.67±2.36% after 1 h) and the best mechanical properties (strain and stress of 67.6% and 0.0486 N/mm2, respectively), NF20 was selected for further investigations. The selected formulation (NF20) showed a bi-phasic, sustained drug release pattern (73.40±1.31% after 72 h). More importantly, testing the antimicrobial effects of the extract-loaded nanofibers highlighted significant reduction in MIC, MBC, and MFC values when compared with Silymarin standard against Acinetobacter baumannii, Pseudomonas aeruginosa, Staphylococcus aureus, and Aspergillus niger. Finally, wound healing assay confirmed the accelerated wound closure and fibroblasts migration in case of the fabricated NF20, suggesting the potential of the bio- fabricated nanofiber as a novel promising wound dressing.

The specifics of a shock wave propagation down a positive column of a dc discharge in molecular chemically inert gases has been investigated. It was shown that axial gradients caused by the imbalance in the charged particle momentum transfer to the gas molecules can be a reason for the shock velocity dependence on the electric field direction. In the pure nitrogen gas, the calculated shock velocity difference up to 13.5% is in good agreement with 12% value obtained in the experiment. A returning gas flow organizing in the discharge as a possible mechanism for an extended shock structure, and a number of kinetical factors capable of affecting the shock motion are discussed.

Objective: Both conventional penile venous surgery for erection restoration and surgical therapy for penile augmentation have been controversial. Based on De Novo penile fibrovascular assembly, we report on innovative penile venous stripping (PVS) and factual penile girth enhancement (FPGE). Methods: From 2013 to 2023, 18 men underwent PVS and FPGE, all confirmed with veno-occlusive dysfunction (VOD). PVS involves stripping erection-related veins, primarily one deep dorsal vein and a pair of cavernosal veins, after ligating each emissary vein closest to the outer tunica albuginea using 6-0 nylon. FPGE was performed along the tunica albuginea bilaterally; then, the two tunic defects were repaired with a 70.0x30.0 mm venous stripe and covered with either autologous venous walls (AVW, n=10) or Surgiform (SF, n=8). The penile girth was measured, and radio-opaque contrast was used to compare intracorporeal retention. The abridged 5-item version of the International Index of Erectile Function (IIEF-5) score and the Erection Hardness Scale (EHS) were used yearly during follow-up via the Internet. Results: The follow-up period was 5.3±1.5 years. Radiopacity was consistently enhanced. Although there was indifference between AVW and SF, there was a significant improvement (both P＜ 0.01) in IIEF-5 and EHS scores (9.7±2.8 vs. 20.8±2.3; 1.7±0.6 vs. 3.2±0.2, respectively). Both the diameters of the glans and penile shaft increased (28.0±2.3mm and 28.3±2.1mm vs 35.3±2.2mm and 36.3±2.1mm respectively). The satisfaction rate was 81.3% (13/16). Conclusions: This novel combination of PVS and FPGE is promising, although further validation requires a larger sample size.

In recent years, concerns regarding the environmental impact of microplastics (MPs) have led to increased international attention on these pollutants. Although initial focus was largely directed toward marine environments, land-based pollution sources, including MP release, has been recognized to directly affect marine ecosystems. Therefore, soil-, atmosphere-, groundwater-, and river-based research is ongoing. However, when considering sources of MP, it is necessary to examine the circular system of plastic in terms of raw materials, production, consumption, discharge, and disposal (recycling). Accordingly, the present study proposes a strategy to effectively manage MPs using this circular system. First, the factors influencing MPs in the circular system were identified, and MPs at the system’s final stage, i.e., at the waste treatment facility, were subsequently investigated. Using the concept of MP waste (MPW), strategies were then developed for effective MP management within the circular system. Applying the proposed theoretical strategy to the Korean waste management system revealed that the new policy framework improves the current MP management system. Overall, this study provides fundamental data for establishing new or improved MP management schemes from a waste sector perspective.

Hydrogels have emerged as promising biomaterials due to their excellent performance; however, their biocompatibility, biodegradability, and absorbability still require improvement to support a broader range of medical applications. This paper presents a new biofunctionalized hydrogel based on in-situ crosslinking between maleimide-terminated four-arm-poly(ethylene glycol) (4–arm–PEG–Mal) and poly(ε-lysine) (ε–PL). PEG/ε–PL hydrogels (LG–n) were rapidly formed via amine/maleimide reaction by mixing 4–arm–PEG–Mal and ε–PL under physiological conditions. The corresponding dry gels (DLG-n) were obtained through a freeze-drying technique. 1H NMR, FT–IR, and SEM were utilized to confirm the structures of 4–arm–PEG–Mal and LG–n (DLG–n), and the effects of solid content on the physicochemical properties of the hydrogels were investigated. Although high solid content could increase the swelling ratio, all LG–n samples exhibited a low equilibrium swelling ratio of less than 30%. LG–7, which contained moderate solid content, exhibited optimal compression properties characterized by a compressive fracture strength of 45.2 kPa and deformation of 69.5%. Compression cycle tests revealed that LG–n demonstrated good anti-fatigue performance. In vitro degradation studies confirmed the biodegradability of LG–n, with the degradation rate primarily governing the drug release efficiency, leading to a sustained release duration of four weeks. Cytotoxicity tests, cell survival morphology observation, Live/Dead assays, and hemolysis tests indicated that LG–n exhibited excellent cytocompatibility and low hemolysis rates (&lt;5%). Furthermore, the broad-spectrum antibacterial activity of LG–n was verified by an inhibition zone method. In conclusion, the developed LG–n hydrogels hold promising applications in the medical field, particularly as drug sustained-release carriers and wound dressings.

In December 2019, the so-called “coronavirus disease 2019” (COVID-19) began. This disease is characterized by heterogeneous clinical manifestations, ranging from an asymptomatic process to life-threatening conditions associated with a “cytokine storm”. This article (narrative review) summarizes the epidemiologic characteristics and clinical manifestations of COVID-19 and multi-system inflammatory syndrome in children (MIS-C). The effect of the pandemic confinement on vitamin D status and the hypotheses proposed to explain the age-related difference in the severity of COVID-19 are discussed. The role of vitamin D as a critical regulator of both innate and adaptive immune responses and the COVID-19 cytokine storm are analyzed. Vitamin D and its links to both COVID-19 (low levels of vitamin D appear to worsen COVID-19 outcomes) and the cytokine storm (anti-inflammatory activity) are detailed. Finally, the efficacy of vitamin D supplementation in COVID-19 is evaluated, but the evidence supporting vitamin D supplementation as an adjuvant treatment for COVID-19 remains uncertain.

Background - Molecular profiles can predict which patients will respond to current standard treatment and new targeted therapy regimens. Using data from a highly diverse population of approximately three million in Southeast London and Kent, this study aims to evaluate the prevalence of IDH1 mutation and MGMT promotor methylation in the gliomas diagnosed in adult patients and to explore correlations with patients’ clinicopathological characteristics. Methods - Anonymised data on 749 adult patients diagnosed with a glioma in 2015-2019 at King’s College Hospital were extracted. Univariable and multivariable logistic regressions were used to estimate odds ratios (ORs) for expressing IDH1 mutation and MGMT promotor methylation, based on each patient’s age, sex, ethnicity, histology, tumour location and extent of excision. The Kaplan-Meier method was used to estimate the overall survival functions. Results - 19.5% of cases were IDH1 mutated. Being 39 years and younger (OR 5.48, 95% CI 3.17-9.47), from Asian/Asian British background (OR 3.68, 95% CI 1.05-12.97), having MGMT methylation (OR 15.92, 95% CI 7.30-34.75), an oligodendroglioma diagnosis (OR 7.45, 95% CI 2.90-19.13) and receiving a gross total/total microscopic excision (OR 1.95, 95% CI 1.24-3.08) were each univariately correlated with IDH1 mutation. MGMT methylation association persisted on adjustment (OR 14.13, 95% CI 3.88-51.43). MGMT promotor methylation was seen in 54.3 % of gliomas. In the univariate adjusted ORs, being younger than 39 years (OR 2.56, 95% CI 1.48-4.43), female (OR 1.52, 95% CI 1.11-2.08), having IDH1 mutation (OR 15.92, 95% CI 7.30-34.75) and an oligodendroglioma diagnosis (OR 6.20, 95% CI 1.33-28.88) were associated with MGMT methylation. Being female (OR 1.75, 95% CI 1.22-2.51) and having an IDH1 mutation (OR 15.54, 95% CI 4.73-51.05) persisted after adjustment for age, sex, ethnicity, histology, tumour location and extent of excision. IDH1 mutant and MGMT methylated gliomas were associated with frontal lobe location. Survival analysis showed that patients with both IDH1 mutation and MGMT methylation had a significantly better survival than those with either molecular marker alone. Over a 3-year period, women with unmethylated MGMT promotor generally had a better survival than men with unmethylated MGMT. Conclusion - This study showed that the molecular markers IDH1 mutation and MGMT promotor methylation were associated with age, sex, Asian/Asian British Ethnic Group, tumour histology, anatomical location and extent of excision. This study has demonstrated the importance of assessing glioma molecular markers in the clinical setting, and the need to stratify patients according to their clinicopathological characteristics.

Rice husk is a waste by-product of rice production. This material has a moderate cost and is readily available, representing 20-22% of the biomass produced by rice cultivation. This study focused on the properties of rice husk in remediation of soils contaminated by heavy metals. The effect of particle size, pH, and the presence of organic ligands on sorption efficiency was evaluated for cadmium (Cd), copper (Cu), and manganese (Mn). The continuous flow method was used to select suitable operative conditions and maximize the retention of heavy metals. Subsequently, pot experiments were carried out by growing two broadleaf plants, Lactuca sativa, and Spinacia oleracea, in aliquots of soil collected in a Piedmont (Northwest Italy) site heavily contaminated by Cu, chromium (Cr), and nickel (Ni). Rice husk was added to the contaminated soil to evaluate its effectiveness in immobilizing heavy metals. The availability of Cr, Mn, Ni, Cu, Zn, Cd, and Pb in soil was studied using Tessier's sequential extraction protocol. The content of the elements was also analyzed in plants and the uptake of heavy metals was evaluated in relation to the addition of rice husk. The growth of both plants resulted more efficient in the presence of rice husk due to its ability to reduce the mobility of heavy metals in the soil. The simplicity, cost-effectiveness, and scalability of its employment make the use of rice husk suitable for practical applications in soil remediation.

There is increasing evidence that COVID-19 induces endothelial dysfunction that may precede thrombotic and cardiovascular complications. The aim of this study is to evaluate the endothelial function using peripheral arterial tonometry (EndoPAT). The primary endpoint is the hyperemic vascular response index (LnRHI) at two months post-discharge. Secondary endpoints include the LnRHI during hospitalization and at six months follow-up, the proportion of patients with endothelial dysfunction (LnRHI≤0.51), and the incidence of thrombotic events, cardiovascular complications, and mortality during the follow-up period. The study included 23 COVID-19 patients and 22 healthy matched controls. The patients exhibited a significant reduction in the LnRHI at two months post-discharge compared to the controls (median=0.55 [IQR: 0.49-0.68] vs median=0.70 [IQR: 0.62-0.83]; p=0.012). The difference in the LnRHI between patients and controls was evident from hospitalization and persisted at two and six months without significant temporal changes. The proportion of COVID-19 patients with endothelial dysfunction (LnRHI≤0.51) was 61% during hospitalization, and 55% at six months. There was no significant difference in thrombotic or cardiovascular events, nor in mortality. This study demonstrates that COVID-19 adversely affects endothelial function, as evidenced by a reduction in the hyperemic vascular response index, and the endothelial dysfunction may also persist.

Hydrazine (N2H4) plays an important role in industrial production, but it is highly toxic, leakage or exposure will pollute the environment and cause serious harm to the human body. Sulfur dioxide (SO2) is an important gas signaling molecule, but its excessive intake can cause a variety of diseases. However, due to the lack of two-color probes capable of detecting both N2H4 and SO2, the ability to monitor the crosstalk of these substances is limited. Therefore, it is necessary to find a simple and effective method for dual-response detection of N2H4 and SO2 in environmental systems and organisms. Here, we developed a two-response fluorescence probe PI-CO-NH based on FRET regulation to detect N2H4 and SO2. The experimental results show that the probe has high selectivity and sensitivity, excellent stability, low cytotoxicity and high cell permeability, can visualize N2H4 and SO2 in living cells, and has good mitochondrial targeting ability. It is worth noting that the ability of the probe to detect N2H4 in different soil samples and test strips was successfully verified. PI-CO-NH provides a platform for the analysis and visualization of two biologically active and environmentally important species, which has great potential in the analysis and monitoring of environmental pollutants.

The increasing need for autonomy for space exploration missions is becoming more and more relevant in the design of missions to small bodies. The long communication latencies and sensitivity of the system to unplanned environment perturbations pose autonomous methods as a key design block for this type of mission. In this work, a fully autonomous gnc methodology is introduced. This methodolody relies on published cnn-based techniques for surface recognition and pose estimation and on also existing mpc-based techniques for the design of a trajectory to perform a soft landing on an asteroid. Combining hda with relative navigation systems, a gsm is built on-the-fly as images are acquired. These gsms provide the gnc system with information about feasible landing spots and populate a longitude-latitude map with safe/hazardous labels that are later processed to find an optimal landing spot based on mission requirements and a distance-from-hazard metric. The methodology is exemplified using Bennu as the body of interest and a gsm is built for an arbitrary reconnaissance orbit.

Backgroud In eukaryotes with a double-stranded linear DNA genome, the loss of terminal DNA during replication is inevitable due to an end-replication problem and telomeres serve as a buffer against DNA loss. Cumulative telomere attrition leads to replicative senescence and the Hayflick limit. Thus, activation of the telomere maintenance mechanism (TMM) is a prerequisite for malignant transformation. We show that extracellular, but not intracellular, signals activate RAD52-dependent alternative lengthening of telomeres (ALT) during malignant transformation of malignant peripheral nerve sheath tumors (MPNSTs). Methods We compared neurofibroma (NF, benign) and MPNST occurring in the same patient with type-1 neurofibromatosis, where each NF-MPNST pair shares the same genetic background and differentiation lineage minimizing genetic bias and contrasts only changes related to malignant transformation. Results We found that the MEGF11 and the MEGF11-dependent ephrin signaling pathways (EFNA5-EPHPA6-PDZD9/PARD6B) activate the NELL2-PAX7 transcriptional cascade, which sequentially activates RAD52, the recombinase of RAD52-dependent ALT, resulting in telomere elongation, metastasis, and poor prognosis. In contrast, H2AFX, a DNA damage marker and intracellular signal, activates RAD51-dependent ALT to determine the MPNST grade. Conclusions We demonstrated the extracellular signals that activate RAD52-dependent ALT and distinguished the biological and clinical manifestations of RAD51 and RAD52-dependent ALT during malignant transformation of MPNSTs.

This study investigates the impact of decentralized organizational party structures on the membership stability of Nigeria's two leading political parties, the People's Democratic Party (PDP) and the All Progressives Congress (APC), between 2015 and 2023. Conducted from April to August 2024, the study focuses on how decentralized party frameworks influence membership retention, particularly in Nigeria's fragmented political landscape, where ethnic and regional divisions challenge political cohesion. A multi-stage sampling technique to select 400 respondents, including national and local party leaders, assembly members, and grassroots members from the six geopolitical zones in Nigeria. A total of 384 valid responses were retrieved, yielding a 96% response rate. Data collection was facilitated through questionnaires administered via Google Forms, which were distributed through email and social media platforms, with a particular focus on WhatsApp for ease of access and engagement. Regression and correlation analyses were used to assess the relationship between decentralization and membership stability. The findings reveal a strong positive correlation (r = 0.961) between decentralized structures and membership stability, with decentralization accounting for 92.4% of the variance in membership stability (R² = 0.924). This indicates that decentralization plays a crucial role in promoting party institutionalization, fostering greater engagement, loyalty, and retention among members. However, regional disparities in the effectiveness of decentralization present challenges to uniform implementation. These results underscore the importance of standardizing decentralization policies across various regions to ensure coherence and reduce membership volatility. The study recommends a harmonized framework that supports decentralized governance within political parties, enhancing internal democracy and reinforcing party unity. The research concludes by emphasizing the need for ongoing exploration into the nuances of decentralization to further support Nigeria’s democratic consolidation. This study offers valuable insights for party leaders, policymakers, and researchers interested in the institutionalization of political organizations in emerging democracies.

Vertical jump height is a reliable measure of lower limb functionality for countermovement jumps. Motion capture systems and force platforms are considered gold standards to assess athletes’ performance during these motions, however their use in ecological settings is limited by high costs and lack of portability. This study aimed to evaluate the feasibility of low-sampling rate Inertial Measurement Units as an alternative to gold standard systems. The validity of three computational methods for IMU-based data—Numerical Double Integration, Take-Off Velocity and Flight Time—was assessed using data from 18 healthy subjects who performed five bilateral and ten unilateral countermovement jumps. Data were simultaneously collected from an IMU positioned at the L5 level, a motion capture system, and two force platforms. Comparisons revealed that the Numerical Double Integration method exhibited the highest correlation (0.87), the lowest bias (2.5 cm) compared to gold standards, and excellent reliability (0.88). Although the Take-Off Velocity and Flight Time methods demonstrated comparable performance for bilateral jumps, their accuracy in unilateral jumps was reduced. Overall, low-sampling rate IMU with Numerical Double Integration method proves to be a reliable and portable alternative for field-based CMJs assessment, warranting future investigation across diverse populations and jump modalities.

Background: High-flow pancreaticoduodenal artery (PDA) aneurysms secondary to celiac trunk occlusion or stenosis have a high risk of rupture. Embolization offers a less invasive alternative to surgery. Objective: To evaluate the effectiveness and safety of retrograde embolization via the superior mesenteric artery of high-flow PDA aneurysms without celiac trunk revascularization. Methods: This retrospective bicentric study included patients who underwent embolization of high-flow PDA aneurysms due to significant celiac trunk stenosis or occlusion. All patients underwent pre-interventional dynamic contrast-enhanced computed tomography. Retrograde embolization was performed using microcoils and/or liquid agents without celiac trunk revascularization. Follow-up involved clinical and radiological assessment at one month. Technical and clinical success were evaluated, and complications were categorized as minor or major. Results: Twenty-three patients (mean age: 65 ±14 years; 52% male) were included. Emergency embolization was required in 12 patients (52%). The technical success rate was 100%. Patients were monitored for a median of 16 months. Clinical success was 87%. No hemorrhagic recurrences were observed. Minor complications occurred in two cases. One major complication involved splenic infarction due to glue migration, requiring splenectomy and intensive unit care admission. Conclusion: Retrograde embolization of high-flow PDA aneurysms is effective and safe without needing celiac trunk revascularization.