Search Results (7,784)

Fibromyalgia (FM) is a chronic non-inflammatory disorder mainly characterized by widespread musculoskeletal pain, fatigue, sleep disturbances, and a constellation of other symptoms. For this reason, delineating a clear distinction between pure FM and FM-like picture attributable to other common diseases can be extremely challenging. Physicians must identify the most significant confounders in individual patients and implement an appropriate diagnostic workflow, carefully choosing a minimal (but sufficient) set of tests to be used for identifying the most plausible diseases in the specific case. This article discusses prevalent non-rheumatological conditions commonly observed in the general population that can manifest with clinical features similar to primary FM. Given their frequent inclusion in the differential diagnosis of FM patients, the focus will be on elucidating the distinctive clinical characteristics of each condition. Additionally, the most cost-effective and efficient diagnostic methodologies for accurately discerning these conditions will be examined. Full article

This study estimates transient and persistent technical efficiencies (TEs) using a generalized true random-effects (GTRE) model. We estimate the GTRE model using maximum likelihood and Bayesian estimation methods, then compare it to three simpler models nested within it to evaluate the robustness of our estimates. We use a panel data set of 945 observations collected from 344 rice farming households in Vietnam’s Mekong River Delta. The results indicate that the GTRE model is more appropriate than the restricted models for understanding heterogeneity and inefficiency in rice production. The mean estimate of overall technical efficiency is 0.71 on average, with transient rather than persistent inefficiency being the dominant component. This suggests that rice farmers could increase output substantially and would benefit from policies that pay more attention to addressing short-term inefficiency issues. Full article

Arable land green and low-carbon utilization (ALGLU) is an important pathway to safeguard food safety and achieve the green transformation and progress of agriculture, playing a crucial role in promoting agricultural ecological protection and economic sustainability. This study takes the Yangtze River Delta region (YRD), where rapid urbanization is most typical, as the study area. On the basis of fully considering the carbon sink function of arable land, the study measures the green and low-carbon utilization level of arable land in the region using the Super-slack and based measure (Super-SBM) model, and analyzes its spatial and temporal evolution using the spatial autocorrelation model, the center of gravity, and the standard ellipsoid model, and then analyzes its impact with the help of the geographic detector and the geographically weighted regression model. We analyzed the multifactor interaction and spatial heterogeneity of the factors with the help of the geodetector and geographically weighted regression model. Results: (1) The ALGLU in the YRD has shown a fluctuating upward tendency, increasing from 0.7307 in 2012 to 0.8604 in 2022, with a growth rate of 17.75%. The phased changes correspond to national agricultural development policies and the stages of socio-economic development. (2) There are significant spatial differences in the level of ALGLU in the YRD, with high levels distributed in the southwest of Jiangsu, northern Zhejiang, and northwest Anhui, while low levels are distributed in the southwest of the YRD. Positive spatial autocorrelation exists in the level of ALGLU in the YRD. The spatial transfer trends of the gravity and standard deviation ellipses essentially align with changes in the spatial pattern. (3) The level of ALGLU in the YRD is affected by many factors, with the intensity of interaction effects far exceeding that of individual factors. When considering single-factor effects, precipitation, topography, and farmers’ income levels are important factors influencing the level of ALGLU. In scenarios involving multiple-factor interactions, agricultural policies become the primary focus of interaction effects. Furthermore, the driving effects of influencing factors exhibit spatial heterogeneity, with significant differences in the direction and extent of driving effects of each factor in different cities. This study can provide valuable insights for future ALGLU in the YRD and regional sustainable development. Full article

In recent advancements in agricultural technology, quantum mechanics and deep learning integration have shown promising potential to revolutionize rice yield forecasting methods. This research introduces a novel Hybrid Quantum Deep Learning model that leverages the intricate processing capabilities of quantum computing combined with the robust pattern recognition prowess of deep learning algorithms such as Extreme Gradient Boosting (XGBoost) and Bidirectional Long Short-Term Memory (Bi-LSTM). Bi-LSTM networks are used for temporal feature extraction and quantum circuits for quantum feature processing. Quantum circuits leverage quantum superposition and entanglement to enhance data representation by capturing intricate feature interactions. These enriched quantum features are combined with the temporal features extracted by Bi-LSTM and fed into an XGBoost regressor. By synthesizing quantum feature processing and classical machine learning techniques, our model aims to improve prediction accuracy significantly. Based on measurements of mean square error (MSE), the coefficient of determination ($R^2$), and mean average error (MAE), the results are 1.191621 × 10⁻⁵, 0.999929482, and 0.001392724, respectively. This value is so close to perfect that it helps make essential decisions in global agricultural planning and management. Full article

Legumes are important grains and forages, providing high-quality proteins, vitamins, and micronutrients to humans and animals. Medicago truncatula is a close relative of alfalfa (Medicago sativa). Caffeic acid O-methyltransferase (COMT), a key gene that is identified to be essential for melatonin synthesis, plays a significant role in plant growth, development, and abiotic stress responses. However, a systematic study on the COMT gene family in M. truncatula has still not been reported. In this study, 63 MtCOMT genes were identified and categorized into three groups. Gene structure and conserved motif analyses revealed the relative conservation of closely clustered MtCOMTs within each group. Duplicated events in MtCOMT members were identified, and segmental duplication was the main mean. Cis-acting element prediction revealed the involvement of MtCOMTs in growth and development and response to light, stress, and plant hormones. RNA-seq data analysis showed that 57 MtCOMTs varied under salt and drought stresses. The RT-qPCR expression patterns showed that MtCOMT9, MtCOMT13, MtCOMT22, MtCOMT24, MtCOMT43, and MtCOMT46 were related to salt and drought responses in M. truncatula. Additionally, Arabidopsis thaliana overexpressing MtCOMT13 displayed superior plant growth phenotypes and enhanced tolerance to salt and drought stresses through higher photosynthetic parameters and activities of antioxidant enzymes, which indicated that MtCOMT13 played an important role in positively regulating plant salt and drought tolerance. These findings contribute to an improved understanding of MtCOMTs’ roles in abiotic stress responses in M. truncatula, providing an important theoretical basis and genetic resource for legume species resistance breeding in the future. Full article

Foxtail millet is a drought-tolerant cereal and forage crop. The basic leucine zipper (bZIP) gene family plays important roles in regulating plant development and responding to stresses. However, the roles of bZIP genes in foxtail millet remain largely uninvestigated. In this study, 92 members of the bZIP transcription factors were identified in foxtail millet and clustered into ten clades. The expression levels of four SibZIP genes (SibZIP11, SibZIP12, SibZIP41, and SibZIP67) were significantly induced after PEG treatment, and SibZIP67 was chosen for further analysis. The studies showed that ectopic overexpression of SibZIP67 in Arabidopsis enhanced the plant drought tolerance. Detached leaves of SibZIP67 overexpressing plants had lower leaf water loss rates than those of wild-type plants. SibZIP67 overexpressing plants improved survival rates under drought conditions compared to wild-type plants. Additionally, overexpressing SibZIP67 in plants displayed reduced malondialdehyde (MDA) levels and enhanced activities of antioxidant enzymes, including catalase (CAT), superoxide dismutase (SOD), and peroxidase (POD) under drought stress. Furthermore, the drought-related genes, such as AtRD29A, AtRD22, AtNCED3, AtABF3, AtABI1, and AtABI5, were found to be regulated in SibZIP67 transgenic plants than in wild-type Arabidopsis under drought conditions. These data suggested that SibZIP67 conferred drought tolerance in transgenic Arabidopsis by regulating antioxidant enzyme activities and the expression of stress-related genes. The study reveals that SibZIP67 plays a beneficial role in drought response in plants, offering a valuable genetic resource for agricultural improvement in arid environments. Full article

This paper presents the computational design, fabrication, and control of a novel 3-degrees-of-freedom (DOF) soft parallel robot. The design is inspired by a delta robot structure. It is engineered to overcome the limitations of traditional soft serial robot arms, which are typically low in structural stiffness and blocking force. Soft robotic systems are becoming increasingly popular due to their inherent compliance match to that of human body, making them an efficient solution for applications requiring direct contact with humans. The proposed soft robot consists of three soft closed-loop kinematic chains, each of which includes a soft actuator and a compliant four-bar arm. The complex nonlinear dynamics of the soft robot are numerically modeled, and the model is validated experimentally using a 6-DOF electromagnetic position sensor. This research contributes to the growing body of literature in the field of soft robotics, providing insights into the computational design, fabrication, and control of soft parallel robots for use in a variety of complex applications. Full article

The first case of COVID-19 was detected in Bangladesh on 8 March 2020. Since then, the Government of Bangladesh (GoB) has implemented various measures to limit the transmission of COVID-19, including widespread testing facilities across the nation through a laboratory network for COVID-19 molecular testing. This study aimed to analyze the dynamics of SARS-CoV-2 in Bangladesh by conducting COVID-19 testing and genomic surveillance of the virus variants throughout the pandemic. Nasopharyngeal swabs were collected from authorized GoB collection centers between April 2020 and June 2023. The viral RNA was extracted and subjected to real-time PCR analysis in icddr,b’s Virology laboratory. A subset of positive samples underwent whole-genome sequencing to track the evolutionary footprint of SARS-CoV-2 variants. We tested 149,270 suspected COVID-19 cases from Dhaka (n = 81,782) and other districts (n = 67,488). Of these, 63% were male. The highest positivity rate, 27%, was found in the >60 years age group, followed by 26%, 51–60 years, 25% in 41–50 years, and the lowest, 9% in under five children. Notably, the sequencing of 2742 SARS-CoV-2 genomes displayed a pattern of globally circulating variants, Alpha, Beta, Delta, and Omicron, successively replacing each other over time and causing peaks of COVID-19 infection. Regarding the risk of SARS-CoV-2 infection, it was observed that the positivity rate increased with age compared to the under-5 age group in 2020 and 2021. However, these trends did not remain consistent in 2022, where older age groups, particularly those over 60, had a lower positivity rate compared to other age groups due to vaccination. The study findings generated data on the real-time circulation of different SARS-CoV-2 variants and the upsurge of COVID-19 cases in Bangladesh, which impacted identifying hotspots and restricting the virus from further transmission. Even though there is currently a low circulation of SARS-CoV-2 in Bangladesh, similar approaches of genomic surveillance remain essential for monitoring the emergence of new SARS-CoV-2 variants or other potential pathogens that could lead to future pandemics. Full article

Polymorphisms in the cholesteryl ester transfer protein (CETP) gene are known to be strongly associated with increased cardiovascular risk, primarily through their effects on the lipid profile and consequently on atherosclerotic risk. The acute heart rate response (AHRR) to physical activity is closely related to individual cardiovascular health. This study aimed to investigate the effect of CETP gene polymorphisms on AHRR. Our analysis examines the association of five single nucleotide polymorphisms (SNPs; rs1532624, rs5882, rs708272, rs7499892, and rs9989419) and their haplotypes (H) in the CETP gene with AHRR in 607 people from the Hungarian population. Individual AHRR in the present study was assessed using the YMCA 3-min step test and was estimated as the difference between resting and post-exercise heart rate, i.e., delta heart rate (ΔHR). To exclude the direct confounding effect of the CETP gene on the lipid profile, adjustments for TG and HDL-C levels, next to conventional risk factors, were applied in the statistical analyses. Among the examined five SNPs, two showed a significant association with lower ΔHR (rs1532624—C_dominant: B = −8.41, p < 0.001; rs708272—G_dominant: B = −8.33, p < 0.001) and reduced the risk of adverse AHRR (rs1532624—C_dominant: OR = 0.44, p = 0.004; rs708272—G_dominant: OR = 0.43, p = 0.003). Among the ten haplotypes, two showed significant association with lower ΔHR (H3—CAGCA: B = −6.81, p = 0.003; H9—CGGCG: B = −14.64, p = 0.015) and lower risk of adverse AHRR (H3—CAGCA: OR = 0.58, p = 0.040; H9—CGGCG: OR = 0.05, p = 0.009) compared to the reference haplotype (H1—AGACG). Our study is the first to report a significant association between CETP gene polymorphisms and AHRR. It also confirms that the association of the CETP gene with cardiovascular risk is mediated by changes in heart rate in response to physical activity, in addition to its effect on lipid profile. Full article

Background: Computed tomography (CT) is the preferred imaging modality for bone evaluation of the knee, while MRI of the bone is actively being developed. We present three techniques using short-interval delta ultrashort echo time (δUTE), field echo (FE), and FE with high resolution–deep learning reconstruction (HR–DLR) for direct bone MRI. Methods: Knees of healthy volunteers (n = 5, 3 females, 38 ± 17.2 years old) were imaged. CT-like images were generated by averaging images from multiple echoes and inverting. The bone signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were determined. Results: The δUTE depicted a cortical bone with high signal intensity but could not resolve trabeculae. In contrast, both the FE and FE HR–DLR images depicted cortical and trabecular bone with high signal. Quantitatively, while δUTE had a good bone SNR of ~100 and CNR of ~40 for the cortical bone, the SNR for the FE HR–DLR was significantly higher (p < 0.05), at over 400, and CNR at over 200. Conclusions: For 3D rendering of the bone surfaces, the δUTE provided better image contrast and separation of bone from ligaments and tendons than the FE sequences. While there still is no MRI technique that provides a perfect CT-like contrast, continued advancement of MRI techniques may provide benefits for specific use cases. Full article

Cannabis is cultivated for therapeutic and recreational purposes where delta-9 tetrahydrocannabinol (THC) is a main target for its therapeutic effects. As the global cannabis industry and research into cannabinoids expands, more efficient and cost-effective analysis methods for determining cannabinoid concentrations will be beneficial to increase efficiencies and maximize productivity. The utilization of machine learning tools to develop near-infrared (NIR) spectroscopy-based prediction models, which have been validated from accurate and sensitive chemical analysis, such as gas chromatography (GC) or liquid chromatography mass spectroscopy (LCMS), is essential. Previous research on cannabinoid prediction models targeted decarboxylated cannabinoids, such as THC, rather than the naturally occurring precursor, tetrahydrocannabinolic acid (THCA), and utilize finely ground cannabis inflorescence. The current study focuses on building prediction models for THCA concentrations in whole cannabis inflorescences prior to harvest, by employing non-destructive screening techniques so cultivators may rapidly characterize high-performing cultivars for chemotype in real time, thus facilitating targeted optimization of crossbreeding efforts. Using NIR spectroscopy and LCMS to create prediction models we can differentiate between high-THCA and even ratio classes with 100% prediction accuracy. We have also developed prediction models for THCA concentration with a R² = 0.78 with a prediction error average of 13%. This study demonstrates the viability of a portable handheld NIR device to predict THCA concentrations on whole cannabis samples before harvest, allowing the evaluation of cannabinoid profiles to be made earlier, therefore increasing high-throughput and rapid capabilities. Full article

Defect-engineering accelerates the conduction of lithium ions in the cathode materials of lithium-ion batteries. However, the effects of defect-engineering on ion conduction and its mechanisms in humid environments remain unclear in the academic discourse. Here, we report on the effect of vacancy defects on the electronic properties of and Li-ion diffusion in a LiFePO₄ material in humid environments. The research findings indicate that vacancy defects reduce the lattice constant and unit cell volume of LiFePO₄. Additionally, the water molecules occupy the Li-ion vacancies, leading to an increase in the lattice constant of LiFePO₄. The computational results of the electronic properties show that the introduction of water molecules induces a transition in LiFePO₄ from a semiconductor to a metallic behavior, with a transfer of 0.38 e of charge from the water molecules to LiFePO₄. Additionally, the migration barrier for Li ions in the H₂O + LiFePO₄ system is found to be 0.50 eV, representing an 11.1% increase compared to the pristine LiFePO₄ migration barrier. Our findings suggest that water molecules impede the migration of Li ions and provide important insights into the effect of defect-engineering on electronic properties and ion conduction under humid conditions. Full article

In this paper, partial energy processing is applied to the current sharing technique for multiphase LLC resonant converters. The proposed circuit consists of an LLC resonant converter and a flyback converter, where the flyback converter is only used for partial energy processing. The input voltage of the LLC resonant converter is fine-tuned by the flyback converter to solve the problem of a voltage gain difference between the two phases of the LLC resonant converter caused by the error of the resonant tank components, which prevents the output current from being nonequalized. Since the compensation power is much smaller than the output power, and only one phase will be during circuit operation, the impact on the overall efficiency is minimal. Due to the low dependence between the LLC resonant converter and the flyback converter, they are operated at different switching frequencies. In addition, due to the low dependence between each phase, the circuit can be expanded using odd and even phases. Full article

Fungal diseases are a major threat to the horticultural industry and cause substantial postharvest losses. While secondary metabolites from Trichoderma sp. have been explored for their antifungal properties, limited information exists on the phenolic compounds produced by less studied species like Trichoderma longibrachiatum. In this study, phenolic compounds were extracted from a liquid culture of T. longibrachiatum using various solvents and methods (conventional and ultrasonic-assisted). Phenolic compounds were quantified by spectrophotometry and identified by high-performance liquid chromatography with diode array detection (HPLC-DAD). The antifungal activity against Alternaria alternata and Fusarium oxysporum was determined by mycelial growth inhibition assays, maximum growth rate (µ_max) by the Gompertz equation, and spore germination tests. Although no significant differences (p ≥ 0.05) were found between the extraction methods, the type of solvent significantly influenced the phenolic content (p ≤ 0.05). Extraction with 70% ethanol showed the highest content of phenolic compounds and flavonoids. More than eight phenolic compounds were detected. Further, this is the first report of the phenolics ferulic, chlorogenic and p-coumaric acids identification in T. longibrachiatum, along with flavonoids such as epicatechin and quercetin, among others. The 70% ethanolic extracts notably inhibited the mycelial growth of A. alternata and F. oxysporum, reducing their maximum growth rate by 1.5 and 1.4 mm/h, respectively. Furthermore, p-coumaric and ferulic acids significantly inhibited spore germination of both pathogens, with a minimum inhibitory concentration (MIC) of 1.5 mg/mL and a minimum fungicidal concentration (MFC) of 2 mg/mL. These findings demonstrate the potential of T. longibrachiatum and its phenolic compounds as viable alternatives for biological control in horticulture and postharvest disease management. Full article

The present paper is dedicated to the examination of maximum and minimum results based on Green’s functions via delta fractional differences for a class of fractional boundary problems. For such a purpose, we built the corresponding Green’s functions based on the falling factorial functions. In addition, using the constructed Green’s function, the positivity of the function and its corresponding delta function are presented. We also verified the occurrence of two distinct functions with the same Green’s function. The maximality and minimality of the Green’s function show a good qualitative agreement. Finally, we considered some special examples to explain the obtained results. Full article