Search Results (1,846)

Electric motors play a decisive role in electric vehicles by converting electrical energy into mechanical motion across various drivetrain components. However, failures in these motors can interrupt the motor function, with approximately 40% of these failures stemming from bearing issues. Key contributors to bearing degradation include shaft voltage, bearing current, and electric discharge material spalling current, especially in motors powered by inverters or variable frequency drives. This review explores the tribological and vibrational aspects of bearing currents, analyzing their mechanisms and influence on electric motor performance. It addresses the challenges faced by electric vehicles, such as high-speed operation, elevated temperatures, electrical conductivity, and energy efficiency. This study investigates the origins of bearing currents, damage linked to shaft voltage and electric discharge material spalling current, and the effects of lubricant properties on bearing functionality. Moreover, it covers various methods for measuring shaft voltage and bearing current, as well as strategies to alleviate the adverse impacts of bearing currents. This comprehensive analysis aims to shed light on the detrimental effects of bearing currents on the performance and lifespan of electric motors in electric vehicles, emphasizing the importance of tribological considerations for reliable operation and durability. The aim of this study is to address the engineering problem of bearing failure in inverter-fed EV motors by integrating electrical, tribological, and lubrication perspectives. The novelty lies in proposing a conceptual link between lubricant breakdown and damage morphology to guide mitigation strategies. The study tasks include literature review, analysis of bearing current mechanisms and diagnostics, and identification of technological trends. The findings provide insights into lubricant properties and diagnostic approaches that can support industrial solutions. Full article

In vitro propagation of avocado faces several limitations. To optimize the establishment phase, we evaluated three plant material types: etiolated shoots, 30-day covered field shoots, and uncovered field shoots, collected at two time points. Biochemical and anatomical analyses were conducted to understand material performance during establishment. Across both collection times, etiolated shoots exhibited minimal oxidation, enhanced bud sprouting, reduced malondialdehyde (MDA) and reactive oxygen species (ROS) levels, increased peroxidase (POD) activity, and improved xylem development, consistently outperforming field-derived materials. Using etiolated shoots, we optimized disinfection and in vitro multiplication protocols. Pre-disinfection with 3 mL L⁻¹ Phyton 27^® and 2% sodium hypochlorite yielded the highest survival rates. In multiplication experiments, varying concentrations of 6-benzylaminopurine (BAP) and meta-topolin (MT), supplemented with gibberellic acid (GA₃), did not significantly affect growth variation. However, 8.88 µM BAP with 0.29 µM GA₃ resulted in the greatest number of sprouted buds. Full article

A wide range of strategies have been developed to modulate dysfunctional brain activities. This narrative review provides a comparative analysis of biophysical, genetic, and biological neuromodulation approaches with an emphasis on their known or unknown molecular targets and translational potential. The review incorporates data from both preclinical and clinical studies covering deep brain stimulation, transcranial electrical and magnetic stimulation, focused ultrasound, chemogenetics, optogenetics, magnetogenetics, and toxin-based neuromodulation. Each method was assessed based on specificity, safety, reversibility, and mechanistic clarity. Biophysical methods are widely used in clinical practice but often rely on empirical outcomes due to undefined molecular targets. Genetic tools offer cell-type precision in experimental systems but face translational barriers related to delivery and safety. Biological agents, such as botulinum neurotoxins, provide long-lasting yet reversible inhibition via well-characterized molecular pathways. However, they require stereotaxic injections and remain invasive. To overcome individual limitations and improve targeting, delivery, and efficacy, there is a growing interest in the synthesis of multiple approaches. This review highlights a critical gap in the mechanistic understanding of commonly used methods. Addressing this gap by identifying molecular targets may help to improve therapeutic precision. This concise review could be valuable for researchers looking to enter the evolving field of the neuromodulation of brain function. Full article

Background/Objectives: Despite legal frameworks acknowledging the need to protect the rights of female prisoners, penitentiary systems often neglect gender-specific needs, particularly for foreign women. Among them, Muslim women face distinct challenges linked to cultural and religious practices, which are frequently unmet in prison contexts. This review aims to explore the academic literature on the experiences of Muslim women in detention. Methods: A systematic review was conducted using three major bibliographic databases—Scopus, PubMed, and Web of Science—covering the period from 2010 to 2024. Inclusion criteria focused on peer-reviewed studies examining the condition of Muslim women in prison. Of the initial pool, only four articles met the criteria and were included in the final analysis. Results: The review reveals a marked scarcity of research on Muslim women in prison at both national and international levels. This gap may be due to their limited representation or cultural factors that hinder open discourse. The selected studies highlight key issues, including restricted access to services, limited ability to practice religion, and language and cultural barriers. These challenges contribute to increased psychological vulnerability, which is often underestimated in prison settings. Conclusions: There is an urgent need for targeted research and culturally competent training for prison staff to adequately support Muslim women in detention. Greater academic and institutional attention is essential to develop inclusive policies that consider the intersection of gender, religion, and migration, particularly in the post-release reintegration process. Full article

The Mayanghe National Nature Reserve, a key habitat for the endangered François’ langur (Trachypithecus francoisi), faces significant anthropogenic disturbances, including extensive distribution of croplands, roads, and settlements. These human-modified features are predominantly concentrated at elevations between 500 and 800 m and on slopes of 10–20°, which notably overlap with the core elevation range utilized by François’ langur. Spatial analysis revealed that langurs primarily occupy areas within the 500–800 m elevation band, which comprises only 33% of the reserve but hosts a high density of human infrastructure—including approximately 4468 residential buildings and the majority of cropland and road networks. Despite slopes >60° representing just 18.52% of the area, langur habitat utilization peaked in these steep regions (exceeding 85.71%), indicating a strong preference for rugged karst terrain, likely due to reduced human interference. Habitat type analysis showed a clear preference for evergreen broadleaf forests (covering 37.19% of utilized areas), followed by shrublands. Landscape pattern metrics revealed high habitat fragmentation, with 457 discrete habitat patches and broadleaf forests displaying the highest edge density and total edge length. Connectivity analyses indicated that distribution areas exhibit a more continuous and aggregated habitat configuration than control areas. These results underscore François’ langur’s reliance on steep, forested karst habitats and highlight the urgent need to mitigate human-induced fragmentation in key elevation and slope zones to ensure the species’ long-term survival. Full article

This study synthesizes the rapidly expanding evidence on how digital technologies reshape international trade, with a particular focus on small and medium-sized enterprises (SMEs). Guided by two research questions—(RQ1) How do digital tools influence the volume and composition of cross-border trade? and (RQ2) How do these effects vary by countries’ development level and firm size?—we conducted a PRISMA-compliant systematic literature review covering 2010–2024. Searches across eight major databases yielded 1857 records; after duplicate removal, title/abstract screening, full-text assessment, and Mixed Methods Appraisal Tool (MMAT 2018) quality checks, 86 peer-reviewed English-language studies were retained. Findings reveal three dominant technology clusters: (1) e-commerce platforms and cloud services, (2) IoT-enabled supply chain solutions, and (3) emerging AI analytics. E-commerce and cloud adoption consistently raise export intensity—doubling it for digitally mature SMEs—while AI applications are the fastest-growing research strand, particularly in East Asia and Northern Europe. However, benefits are uneven: firms in low-infrastructure settings face higher fixed digital costs, and cybersecurity and regulatory fragmentation remain pervasive obstacles. By integrating trade economics with development and SME internationalization studies, this review offers the first holistic framework that links national digital infrastructure and policy support to firm-level export performance. It shows that the trade-enhancing effects of digitalization are contingent on robust broadband penetration, affordable cloud access, and harmonized data-governance regimes. Policymakers should, therefore, prioritize inclusive digital-readiness programs, while business leaders should invest in complementary capabilities—data analytics, cyber-risk management, and cross-border e-logistics—to fully capture digital trade gains. This balanced perspective advances theory and practice on building resilient, equitable digital trade ecosystems. Full article

To study hydrogeological characteristics after the occurrence of abnormal water bursts from the weak water-rich (permeable) aquifer of the Changxing Formation limestone overlying deep working faces during production in Guizhou karst landform mining areas, hydrogeological data covering the exploration and production periods of the Xinhua mining region in Jinsha County, Guizhou Province, were collected. On the basis of surface and underground drilling, geophysical exploration techniques, empirical equations, and indoor material simulation methods, the hydrogeological evolution characteristics of the Changxing Formation limestone in the mining region after mining damage to coalbed 9 were studied. The research results indicated that the ratio of the height of the roof failure fracture zone (as obtained via numerical simulation and ground borehole detection) to the mining height exceeded 25.78, which is far greater than the empirical model calculation values (from 13.0 to 15.8). After mining the underlying coalbed 9, an abnormal water-rich area developed in the Changxing Formation limestone, and mining damage fractures led to the connection of the original dissolution fissures and karst caves within the limestone, resulting in the weak water-rich (permeable) aquifer of the Changxing Formation limestone becoming a strong water-rich (permeable) aquifer, which served as the water source for mine water bursts. Over time, after mining damage occurrence, the voids in the Changxing Formation limestone were gradually filled with various substances, yielding water storage space and connectivity decreases. The specific yield decreased with an increasing water burst time and interval after the cessation of mining in the supply area, and the correlation coefficient R was 0.964, indicating a high degree of correlation between the two parameters. Full article

Arid regions, while providing essential ecosystem services, are among the most ecologically vulnerable worldwide. Understanding and monitoring their long-term vegetation dynamics is essential for accurate environmental assessment and climate adaptation strategies. This study examined the spatiotemporal variations and driving forces of the vegetation dynamics in arid Northwestern China during 2000 to 2020, using the annual peak fractional vegetation cover (FVC) as the primary indicator. The Sen’s slope estimator with the Mann–Kendall test and the coefficient of variation were employed to assess the spatiotemporal variations in FVC, while the Pearson correlation, geographic detector model and random forest model were applied to identify the dominant driving factors for FVC. The results indicated that (1) overall vegetation cover was low (averaged peak FVC = 0.191), showing a spatial pattern of higher values in the northwest and lower values in the southeast; high FVC values were primarily observed in mountainous areas and river corridors; (2) the annual peak FVC increased significantly at a rate of 0.0508 yr⁻¹, with 33.72% of the region showing significant improvements and 5.49% degradation; (3) the spatial pattern of FVC was shaped by the distribution of land use types (59.46%), while the temporal dynamics of FVC were driven by land use changes (16.37%) and the land use intensity (37.56%); (4) both the spatial pattern and the temporal dynamics were limited by the environmental conditions. These findings highlight the critical role of anthropogenic activities in shaping the spatiotemporal variations in FVC, particularly emphasizing the distinct contributions of changes in land use types and land use intensity. This study could provide a scientific basis for sustainable land management and restoration strategies in arid regions facing global changes. Full article

The development of an integrated circuit faces the challenge of the physical limit of Moore’s Law. One of the most important “Beyond Moore” challenges is the scaling down of Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) versus their increasing static power consumption. This is because, at room temperature, the thermal emission transportation mechanism will cause a physical limitation on subthreshold swing (SS), which is fundamentally limited to a minimum value of 60 mV/decade for MOSFETs, and accompanied by an increase in off-state leakage current with the process of scaling down. Moreover, the impacts of short-channel effects on device performance also become an increasingly severe problem with channel length scaling down. Due to the band-to-band tunneling mechanism, Tunnel Field-Effect Transistors (TFETs) can reach a far lower SS than MOSFETs. Recent research works indicated that TFETs are already becoming some of the promising candidates of conventional MOSFETs for ultra-low-power applications. This paper provides a review of some advances in materials and structures along the evolutionary process of TFETs. An in-depth discussion of both experimental works and simulation works is conducted. Furthermore, the performance of TFETs with different structures and materials is explored in detail as well, covering Si, Ge, III-V compounds and 2D materials, alongside different innovative device structures. Additionally, this work provides an outlook on the prospects of TFETs in future ultra-low-power electronics and biosensor applications. Full article

Purpose: Cancer immunotherapy has transformed oncology, but underserved populations face persistent disparities in access and outcomes. This review explores how artificial intelligence (AI) can help mitigate these barriers. Methods: We conducted a narrative review based on peer-reviewed literature selected for relevance to artificial intelligence, cancer immunotherapy, and healthcare challenges, without restrictions on publication date. We searched three major electronic databases: PubMed, IEEE Xplore, and arXiv, covering both biomedical and computational literature. The search included publications from January 2015 through April 2024 to capture contemporary developments in AI and cancer immunotherapy. Results: AI tools such as machine learning, natural language processing, and predictive analytics can enhance early detection, personalize treatment, and improve clinical trial representation for historically underrepresented populations. Additionally, AI-driven solutions can aid in managing side effects, expanding telehealth, and addressing social determinants of health (SDOH). However, algorithmic bias, privacy concerns, and data diversity remain major challenges. Conclusions: With intentional design and implementation, AI holds the potential to reduce disparities in cancer immunotherapy and promote more inclusive oncology care. Future efforts must focus on ethical deployment, inclusive data collection, and interdisciplinary collaboration. Full article

Since the end of the Civil War, Cambodia has pursued economic development to enhance livelihoods, particularly in rural areas, where land is a critical resource. Previous studies have indicated that the country has changed land use and land cover. However, they have not explained how these changes can improve the livelihoods of local communities, thereby mitigating their negative impacts through an asset-based approach. Battambang Province, in the northwestern region, was the battleground until political integration in 1996. Since then, the province has been home to immigrants exploring the lands for livelihood. Thus, this study aims to examine agricultural livelihoods in the villages of Dei Kraham and Ou Toek Thla, located west of Battambang Town. These were selected because of their common characteristics. Adopting a quantitative approach and a sustainable livelihood framework, this study employed stratified random sampling to select 123 families for interviews across three population subgroups: old settlers, new settlers, and young settlers. In situ information was collected using structured questionnaires and analyzed using Kruskal–Wallis tests to assess the livelihood assets underlying the physical, natural, human, financial, and social capital. The statistical analysis results reveal no significant differences (p-value = 0.079) in livelihood assets between the strata at the village level. Meanwhile, significant differences were observed in physical, human, and financial capital between old and young settlers when examining the subgroups (p-value 0.000). The extent of the land resources held by old settlers was associated with household income and livelihoods related to agriculture. Based on livelihood asset scores, nearly half of the new settlers (0.49–0.5) and a quarter of the young settlers (0.47) are vulnerable groups requiring support. The youth will soon face an uncertain future if they do not prioritize education. Full article

Seed priming, traditionally viewed as a method for enhancing crop resilience to abiotic stress, has evolved into a multifaceted agronomic strategy. This review synthesizes the current findings demonstrating that priming influences plant development, metabolic regulation, and yield enhancement even under optimal conditions. By covering a wide range of crops, including cereals (e.g., wheat, maize, rice, and barley) as well as vegetables and horticultural species (e.g., tomato, carrot, spinach, and lettuce), we highlight the broad applicability of priming across agricultural systems. The underlying mechanisms include hormonal modulation, altered source–sink dynamics, accelerated phenology, and epigenetic memory. Various priming techniques are discussed, including hydropriming, osmopriming, biopriming, chemopriming, and nanopriming, with attention to their physiological and molecular effects. Special focus is given to the role of seed priming in advancing climate-smart and precision agriculture. By shifting the narrative from stress mitigation to holistic crop performance optimization, seed priming emerges as a key tool for sustainable agriculture in the face of global challenges. Full article

Evapotranspiration (ET) crucially regulates water storage dynamics and is an essential component of the terrestrial water cycle. Understanding ET dynamics is fundamental for sustainable water resource management, particularly in regions facing increasing drought risks under climate change. In regions like southwestern China, where extreme drought events are prevalent due to complex terrain and climate warming, ET becomes a key factor in understanding water availability and drought dynamics. Using the SWAT model, this study investigates ET dynamics and influencing factors in the Jizi Basin, Yunnan Province, a small basin with over 71% forest coverage. The model calibration and validation results demonstrated a high degree of consistency with observed discharge data and ERA5, confirming its reliability. The results show that the annual average ET in the Jizi Basin is 573.96 mm, with significant seasonal variations. ET in summer typically ranges from 70 to 100 mm/month, while in winter, it drops to around 20 mm/month. Spring ET exhibits the highest variability, coinciding with the occurrence of extreme hydrological events such as droughts. The monthly anomalies of ET effectively reproduce the spring and early summer 2019 drought event. Notably, ET variation exhibits significant uncertainty under scenarios of +1 °C temperature and −20% precipitation. Furthermore, although land use changes had relatively small effects on overall ET, they played crucial roles in promoting groundwater recharge through enhanced percolation, especially forest cover. The study highlights that, in addition to climate and land use, soil moisture and groundwater conditions are vital in modulating ET and drought occurrence. The findings offer insights into the hydrological processes of small forested basins in southwestern China and provide important support for sustainable water resource management and effective climate adaptation strategies, particularly in the context of increasing drought vulnerability. Full article

Accurate land cover classification is vital for informed water resource management, especially in irrigation-dependent regions facing increased climate variability. Using fused multi-sensor remote sensing imagery from Landsat 8 and Sentinel-2, this study assesses the effectiveness of three machine learning classifiers: Random Forest (RF), Gradient Tree Boosting (GTB), and Naive Bayes (NB) in creating land cover maps for the Tisza-Körös Valley Irrigation System (TIKEVIR) in Hungary. Water bodies, built-up areas, forests, grasslands, and major crops were among the important land cover categories that were classified for the two agricultural seasons (2018 and 2022). RF performed consistently in 2022 and reached its best accuracy in 2018 (OA = 0.87, KC = 0.83, PI = 0.94). While NB’s performance in 2022 remained less consistent, GTB’s performance increased. The findings show that RF works effectively for generating accurate land cover data, providing useful information for regional monitoring, and assisting in water and environmental management decision-making. Full article

With the continuous exploitation of bauxite mineral resources, Guangxi bauxite faces many difficulties in alumina production due to its characteristics of high silicon content, high iron content, and a low Al-Si ratio. In view of this, this study is closely related to the key link of bauxite pre-desiliconization and strives to break free from the status quo to improve the aluminum/silicon ratio and help optimize the subsequent alumina-refining process. In the work presented in this paper, the unique mineralogy of Guangxi bauxite was comprehensively considered, covering its complex mineral composition and fine distribution characteristics. The barium hydroxide pre-desilication technology was first used for in-depth experimental exploration, and the silicon removal efficiency under different working conditions was systematically compared. The system compared the silicon removal effect and the associated aluminum loss under different working conditions. The results of this study will lay a solid foundation for the rational and efficient development of bauxite in Guangxi, which is expected to reduce the cost of alumina production, improve the economic benefits for the Guangxi aluminum industry, simultaneously strengthen the efficiency of resource recycling, accelerate the sustainable development of the industry, and provide a useful reference example for subsequent similar studies. Full article