Search Results (5,634)

Wildfires are a critical driver of landscape transformation on Earth, representing a dynamic and ephemeral process that poses challenges for accurate early detection. To address this challenge, researchers have increasingly turned to deep learning techniques, which have demonstrated remarkable potential in enhancing the performance of wildfire detection systems. This paper provides a comprehensive review of fire detection using deep learning, spanning from 1990 to 2023. This study employed a comprehensive approach, combining bibliometric analysis, qualitative and quantitative methods, and systematic review techniques to examine the advancements in fire detection using deep learning in remote sensing. It unveils key trends in publication patterns, author collaborations, and thematic focuses, emphasizing the remarkable growth in fire detection using deep learning in remote sensing (FDDL) research, especially from the 2010s onward, fueled by advancements in computational power and remote sensing technologies. The review identifies “Remote Sensing” as the primary platform for FDDL research dissemination and highlights the field’s collaborative nature, with an average of 5.02 authors per paper. The co-occurrence network analysis reveals diverse research themes, spanning technical approaches and practical applications, with significant contributions from China, the United States, South Korea, Brazil, and Australia. Highly cited papers are explored, revealing their substantial influence on the field’s research focus. The analysis underscores the practical implications of integrating high-quality input data and advanced deep-learning techniques with remote sensing for effective fire detection. It provides actionable recommendations for future research, emphasizing interdisciplinary and international collaboration to propel FDDL technologies and applications. The study’s conclusions highlight the growing significance of FDDL technologies and the necessity for ongoing advancements in computational and remote sensing methodologies. The practical takeaway is clear: future research should prioritize enhancing the synergy between deep learning techniques and remote sensing technologies to develop more efficient and accurate fire detection systems, ultimately fostering groundbreaking innovations. Full article

Accurate prediction of electricity consumption is crucial for energy management and allocation. This study introduces a novel approach, named Attention-based Multivariate Temporal Convolutional Network (AMTCN), for electricity consumption forecasting by integrating attention mechanisms with multivariate temporal convolutional networks. The method involves feature extraction from diverse time series of different feature variables using dilated convolutional networks. Subsequently, attention mechanisms are employed to capture the correlation and contextually important information among various features, thereby enhancing the model’s predictive accuracy. The AMTCN method exhibits universality, making it applicable to various prediction tasks in different scenarios. Experimental evaluations are conducted on four distinct datasets, encompassing electricity consumption and weather temperature aspects. Comparative experiments with LSTM, ConvLSTM, GRU, and TCN—widely-used deep learning methods—demonstrate that our AMTCN model achieves significant improvements of 57% in MSE, 37% in MAE, 35% in RRSE, and 12% in CORR metrics, respectively. This research contributes a promising approach to accurate electricity consumption prediction, leveraging the synergy of attention mechanisms and multivariate temporal convolutional networks, with broad applicability in diverse forecasting scenarios. Full article

In smart ranch management, cattle behavior recognition and tracking play a crucial role in evaluating animal welfare. To address the issues of missed and false detections caused by inter-cow occlusions and infrastructure obstructions in the barn environment, this paper proposes a multi-object tracking method called YOLO-BoT. Built upon YOLOv8, the method first integrates dynamic convolution (DyConv) to enable adaptive weight adjustments, enhancing detection accuracy in complex environments. The C2f-iRMB structure is then employed to improve feature extraction efficiency, ensuring the capture of essential features even under occlusions or lighting variations. Additionally, the Adown downsampling module is incorporated to strengthen multi-scale information fusion, and a dynamic head (DyHead) is used to improve the robustness of detection boxes, ensuring precise identification of rapidly changing target positions. To further enhance tracking performance, DIoU distance calculation, confidence-based bounding box reclassification, and a virtual trajectory update mechanism are introduced, ensuring accurate matching under occlusion and minimizing identity switches. Experimental results demonstrate that YOLO-BoT achieves a mean average precision (mAP) of 91.7% in cattle detection, with precision and recall increased by 4.4% and 1%, respectively. Moreover, the proposed method improves higher order tracking accuracy (HOTA), multi-object tracking accuracy (MOTA), multi-object tracking precision (MOTP), and IDF1 by 4.4%, 7%, 1.7%, and 4.3%, respectively, while reducing the identity switch rate (IDS) by 30.9%. The tracker operates in real-time at an average speed of 31.2 fps, significantly enhancing multi-object tracking performance in complex scenarios and providing strong support for long-term behavior analysis and contactless automated monitoring. Full article

Background/Objectives: The emergence of antimicrobial resistance has urged researchers to explore new antimicrobial agents, such as essential oils (EOs). The aim of this study was to examine chemical composition and antimicrobial activity of the EOs from the needles and green cones of four Pinus species (Pinus mugo Turra., P. nigra J.F., P. syilvestris L., and P. halepensis Miller) from Bosnia and Herzegovina. Methods: Chemical profiles of EOs were assessed by gas chromatography, while microdilution method was used to test their antimicrobial activity. A synergistic action of EOs and gentamicin was investigated by the checkerboard assay. Results: The chemical composition of the tested EOs showed a high percentage of α-pinene, (E)-caryophyllene, limonene, germacrene D, myrcene, and δ-3-carene. EO from green cones of P. sylvestris showed high efficiency against S. aureus and E. faecalis. The MIC of P. nigra cones’ EO was 100 μg/mL against E. coli. The EO of P. halepensis green cones demonstrated the strongest activity against E. faecalis. EOs of P. halepensis needles and green cones exhibited the highest activity against C. albicans. Further, synergistic interaction was detected in combination of the selected EOs/gentamicin toward S. aureus and K. pneumoniae. Conclusions: Among the tested EOs, oils of P. sylvestris cones and P. halepensis cones and needles showed the greatest antimicrobial activity. The same EOs and EO from P. nigra cones displayed synergistic potential in combination with gentamicin, supporting their utilization as antimicrobial agents alone or in combination with antibiotics, which is in line with their ethnopharmacological usage and circular bioeconomy principles. Full article

Space technology is integral to modern critical systems, including navigation, communication, weather, financial services, and defence. Despite its significance, space infrastructure faces unique cyber resilience challenges exacerbated by the size, isolation, cost, persistence of legacy systems, and lack of comprehensive cyber resilience engineering standards. This paper examines the engineering challenges associated with incorporating cyber resilience into space design, drawing on insights and experiences from industry experts. Through qualitative interviews with engineers, cybersecurity specialists, project managers, and testers, we identified key themes in engineering methodologies, cybersecurity awareness, and the challenges of integrating cyber resilience into space projects. Participants emphasised the importance of incorporating cybersecurity considerations from the earliest stages of design, advocating for principles such as zero-trust architecture and security by design. Our findings reveal that experts favour Model-Based Systems Engineering (MBSE) and Agile methodologies, highlighting their synergy in developing flexible and resilient systems. The study also underscores the tension between principles-based standards, which offer flexibility but can lead to inconsistent implementation, and compliance-based approaches, which provide clear measures but may struggle to adapt to evolving threats. Additionally, the research recognises significant barriers to achieving cyber resilience, including insider threats, the complexity of testing and validation, and budget constraints. Effective stakeholder engagement and innovative funding models are crucial for fostering a culture of cybersecurity awareness and investment in necessary technologies. This study highlights the need for a comprehensive cyber resilience framework that integrates diverse engineering methodologies and proactive security measures, ensuring the resilience of space infrastructure against emerging cyber threats. Full article

Jujube (Ziziphus jujuba Mill.), native to Southern Asia, stands out for its significant nutritional and therapeutic properties. Its adaptability and resilience have enabled its global cultivation, highlighting the necessity for comprehensive scientific research to fully harness its potential. Rich in bioactive compounds like flavonoids, polyphenols, vitamin C, polysaccharides, tannins, and saponins, jujube extracts exhibit notable antioxidant, anti-inflammatory, antimicrobial, and wound healing properties. These qualities have made jujube a popular ingredient in various skin and hair care formulations. The versatility of jujube extracts, along with their synergy with other herbal active ingredients, enables the development of targeted personal care solutions. These solutions address a range of concerns, including anti-aging, UV protection, brightening, moisturizing, and calming effects, as well as promoting hair health. Despite its potential, research on the cosmetic applications of Z. jujuba is still in its early stages, with only one clinical trial to date focusing on its skin-brightening effects. This review aims to consolidate the current and emerging research on the applications of jujube in conventional and medical cosmetics, highlighting its potential in enhancing skin and hair wellness. By providing a comprehensive overview, it seeks to pave the way for further studies and innovations in utilizing jujube for personal care. Full article

This paper investigates the impact of air quality and climate variability during the first wave of COVID-19 associated with accelerated transmission and lethality in Wuhan in China and four European metropolises (Milan, Madrid, London, and Bucharest). For the period 1 January–15 June 2020, including the COVID-19 pre-lockdown, lockdown, and beyond periods, this study used a synergy of in situ and derived satellite time-series data analyses, investigating the daily average inhalable gaseous pollutants ozone (O₃), nitrogen dioxide (NO₂), and particulate matter in two size fractions (PM2.5 and PM10) together with the Air Quality Index (AQI), total Aerosol Optical Depth (AOD) at 550 nm, and climate variables (air temperature at 2 m height, relative humidity, wind speed, and Planetary Boundary Layer height). Applied statistical methods and cross-correlation tests involving multiple datasets of the main air pollutants (inhalable PM2.5 and PM10 and NO₂), AQI, and aerosol loading AOD revealed a direct positive correlation with the spread and severity of COVID-19. Like in other cities worldwide, during the first-wave COVID-19 lockdown, due to the implemented restrictions on human-related emissions, there was a significant decrease in most air pollutant concentrations (PM2.5, PM10, and NO₂), AQI, and AOD but a high increase in ground-level O₃ in all selected metropolises. Also, this study found negative correlations of daily new COVID-19 cases (DNCs) with surface ozone level, air temperature at 2 m height, Planetary Boundary PBL heights, and wind speed intensity and positive correlations with relative humidity. The findings highlight the differential impacts of pandemic lockdowns on air quality in the investigated metropolises. Full article

Agroforestry systems are recognized as sustainable land use practices that foster environmental health and promote adaptive responses to global change. By harnessing the synergies between trees and agricultural activities, agroforestry systems provide multiple benefits, including soil conservation, biodiversity enhancement, and carbon sequestration. Windbreaks form integral elements of Hungarian agricultural landscapes, and the enhanced agroforestry subsidy framework might have a favorable impact on their expansion, underscoring the importance of evaluating their potential for carbon sequestration. In the present study, we assess the implications of doubling the extent of windbreak plantations in Hungary by planting an additional 14,256 hectares of windbreaks. We evaluate the total carbon sequestration and the annual climate change mitigation potential of the new plantations up to 2050. For the modeling, we use the recently developed Windbreak module of the Forest Industry Carbon Model, which is a yield table-based model specific to Hungary and allows for the estimation of living biomass, dead organic matter, and soil carbon balance. We project that new windbreak plantations will sequester 913 kt C by 2050, representing an average annual climate change mitigation potential of 144 kt CO₂ eq. Our findings reveal that doubling the extent of windbreak plantations could achieve an extra 5% carbon sequestration in forested areas as compared to business-as-usual (BAU) conditions. We conclude that new windbreak plantations on agricultural field boundaries have substantial climate change mitigation potential, underscoring agroforestry’s contribution to agricultural resilience and achieving Hungary’s climate goals set for the land-use (LULUCF) sector. Full article

Recent literature highlights the crucial role of deadwood in forests, emphasizing its contribution to biodiversity conservation, soil fertility, climate change mitigation, and bioenergy production. However, managing deadwood presents challenges as decision-makers must balance trade-offs and synergies between these ecological benefits. A participatory approach, incorporating user opinions, can support effective decision-making. This study surveyed 1207 university students from Iran, Italy, and Türkiye to explore their perceptions of deadwood’s role and the potential trade-offs among climate change mitigation, biodiversity conservation, and bioenergy production. Results indicate a high level of awareness among students regarding deadwood’s ecological functions, but preferences vary significantly across cultural and regional contexts. Results show that for students of all three countries, the most important function related to the deadwood in forests is the provision of microhabitats for wildlife, while in second place for Iranian students, there is bioenergy production, and for Turkish and Italian students, soil fertilization. In addition, results highlight that students prefer the management strategies based on leaving both standing dead trees and lying deadwood in the forest. This study reinforces existing literature on deadwood’s importance for biodiversity and underscores the need for informed policies that balance ecological values with practical management considerations. Full article

Sentinel-3 synergy (SYN) VEGETATION (VGT) products were designed to provide continuity to the SPOT/VEGETATION (SPOT VGT) base products archive. Since the PROBA-V mission acted as a gap filler between SPOT VGT and Sentinel-3, and in principle, a continuous series of data products from the combined data archives of SPOT VGT (1998–2014), PROBA-V (2013–2020) and Sentinel-3 SYN VGT (from 2018 onwards) are available to users, the consistency of Sentinel-3 SYN VGT with both the latest SPOT VGT (VGT-C3) and PROBA-V (PV-C2) archives is highly relevant. In past years, important changes have been implemented in the SYN VGT processing baseline. The archive of SYN VGT products is therefore intrinsically inconsistent, leading to different consistency levels with SPOT VGT and PROBA-V throughout the years. A spatio-temporal intercomparison of the combined time series of VGT-C3, PV-C2 and Sentinel-3 SYN VGT 10-day NDVI composite products with an external reference from LSA-SAF, and an intercomparison of Sentinel-3 SYN V10 products with a climatology of VGT-C3 resp. PV-C2 for three distinct periods with different levels of product quality have shown that the subsequent processing baseline updates have indeed resulted in better-quality products. It is therefore essential to reprocess the entire Sentinel-3 SYN VGT archive; a uniform data record of standard SPOT VGT, PROBA-V and Sentinel-3 SYN VGT products, spanning over 25 years, would provide valuable input for a wide range of applications. Full article

In managing ecosystem services (ESs), it is vital to understand and effectively regulate the trade-offs and synergies (ToSs) involved. This study investigates the Tianshan Mountains (TSMs), utilizing the InVEST (Integrated Valuation of ESs and Tradeoffs) model to evaluate ecosystem service changes from 2000 to 2020, while employing univariate linear regression to examine their spatiotemporal dynamics. Pearson correlation analysis was also conducted to assess how climatic variables (temperature and precipitation) and vegetation indicators (NDVI, normalized difference vegetation index) influence the overall ecosystem service benefits. The findings reveal notable spatial heterogeneity and dynamic shifts in ESs across the TSMs, with strong synergies observed between carbon storage (CS) and other services (such as habitat quality, HQ; soil conservation, SC; and water yield, WY), especially in areas experiencing increased vegetation. However, the connection between HQ and WY was comparatively weaker and occasionally exhibited negative correlations during specific periods, highlighting the intricate trade-offs among various services. The correlation analysis further showed that climate and vegetation changes significantly impact ecosystem service benefits, with declining precipitation and rising temperatures reducing these benefits, whereas higher NDVI was associated with improved service functions. Ultimately, this study emphasizes the necessity of recognizing and managing ToSs in ESs to promote sustainable regional ecosystem development. Full article

This study adopts an integrative review approach to explore the differences and similarities between smart cities and sustainable cities. The research starts by performing two systematic literature reviews about both paradigms and, after that, employs a thematic analysis to identify key themes, definitions, and characteristics that differentiate and connect these two urban development concepts. The findings reveal more similarities than differences between the two paradigms. Despite this, some key differences are identified. Smart cities are characterized by their use of advanced information and communication technologies to enhance urban infrastructure, improve public services, and optimize resource management. In contrast, sustainable cities focus on environmental conservation, social equity, and economic viability to ensure long-term urban resilience and quality of life. This study is important because it clarifies both concepts and highlights the potential for integrating smart and sustainable city strategies to address contemporary urban challenges more holistically. The findings also suggest a convergence towards the concept of ‘smart sustainable cities’, which leverage technology to achieve sustainability goals. Finally, this study concludes by identifying research gaps and proposing a future research agenda to further understand and optimize the synergy between smart and sustainable urban development paradigms. Full article

To maintain the carbon dioxide concentration below the no-return threshold for climate change, we must consider the reduction in anthropic emissions coupled to carbon capture methods applied in synergy. In our recent papers, we proposed a green and reliable method for carbon mineralization using ascorbic acid aqueous solution as the reducing agent for carbon (IV) to carbon (III), thus obtaining oxalic acid exploiting green reagents. Oxalic acid is made to mineralize as calcium (as the model cation) oxalate. Oxalates are solid-state reservoirs suitable for long-term carbon storage or carbon feedstock for manufacturing applications. The carbon mineralization reaction is a double-step process (carbon reduction and oxalate precipitation), and the carbon capture efficiency is invariably represented by a double-slope curve we formerly explained as a decrease in the reducing effectiveness of ascorbic acid during reaction. In the present paper, we demonstrated that the reaction proceeds via a “pure CO₂-capture” stage in which ascorbic acid oxidizes into dehydroascorbic acid and carbon (IV) reduces to carbon (III) and a “mixed” stage in which the redox reaction competes with the degradation of ascorbic acid in producing oxalic acid. Despite the irreversibility of the reduction reaction, that was demonstrated in abiotic conditions, the analysis of costs according to the market price of the reagents endorses the application of the method. Full article

Kinematics, kinetics and biomechanics of human gait are widely investigated fields of research. The biomechanics of locomotion have been described as characterizing muscle activations and synergistic control, i.e., spatial and temporal patterns of coordinated muscle groups and joints. Both kinematic synergies and muscle synergies have been extracted from locomotion data, showing that in healthy people four–five synergies underlie human locomotion; such synergies are, in general, robust across subjects and might be altered by pathological gait, depending on the severity of the impairment. In this work, for the first time, we apply the mixed matrix factorization algorithm to the locomotion data of 15 healthy participants to extract hybrid kinematic–muscle synergies and show that they allow us to directly link task space variables (i.e., kinematics) to the neural structure of muscle synergies. We show that kinematic–muscle synergies can describe the biomechanics of motion to a better extent than muscle synergies or kinematic synergies alone. Moreover, this study shows that at a functional level, modular control of the lower limb during locomotion is based on an increased number of functional synergies with respect to standard muscle synergies and accounts for different biomechanical roles that each synergy may have within the movement. Kinematic–muscular synergies may have impact in future work for a deeper understanding of modular control and neuro-motor recovery in the medical and rehabilitation fields, as they associate neural and task space variables in the same factorization. Applications include the evaluation of post-stroke, Parkinson’s disease and cerebral palsy patients, and for the design and development of robotic devices and exoskeletons during walking. Full article

Wheelchair basketball players often develop shoulder pain due to repetitive wheelchair propulsion motion. Wheelchair propulsion involves two phases, push and recovery, with several different muscles simultaneously active in each phase. Although differences in the coordinated activity of multiple muscles may influence the mechanism of injury occurrence, there have been no studies investigating muscle synergy in wheelchair propulsion motion. Twelve healthy adult males with no previous wheelchair driving experience were included. The surface electromyography data of 10 muscles involved in shoulder joint movements were measured during a 20 m wheelchair propulsion motion. Muscle synergies were extracted using non-negative matrix factorization analysis of the electromyography data. Four muscle synergies were identified during wheelchair propulsion. Synergy 1 reflects propulsion through shoulder flexion and elbow flexion, while Synergy 2 involves shoulder flexion and elbow extension. Synergy 3 describes shoulder extension returning the upper limb, which has moved forward during the push, back to its original position, and Synergy 4 relates to stabilize the shoulder girdle during the recovery phase. This study is the first to explore muscle synergy during wheelchair propulsion, and the data from healthy participants without disabilities or pain will provide a baseline for future comparisons with data from wheelchair basketball players. Full article