Search Results (2,610)

Cancer is a complex disease characterized by uncontrolled proliferation and progression toward metastasis. The activation and maintenance of these processes demand increased energy production. Traditional cancer therapies often target broad energy-generating mechanisms to inhibit cancer growth. However, the field of oncology is increasingly shifting toward more potent, precise, and personalized treatment strategies. This shift has fueled interest in novel cancer metabolic pathway targets. This review focuses on proline metabolism, an amino acid pathway that has been observed to be altered across various cancer subtypes. Proline has emerged as one of the most consistently deregulated non-essential amino acids in cancer biology. Proline metabolism is intimately linked to mitochondria function and energy regulation through mechanisms such as reactive oxygen species, ATP production, and interactions with the tumor microenvironment. Due to its dichotomous nature, proline metabolism functions are highly context dependent, varying across cancer subtypes. While this provides a potential novel therapeutic target, it also presents unique challenges and knowledge gaps. Full article

The rise in social media has blurred work–life boundaries, and concerns have been raised about its impact on employee well-being. This study examines how excessive social media use at work (ESMU) and social media use for work during non-work hours (SMUNW) affect turnover intention. Social media exhaustion is tested as a mediator, and resilience is tested as a moderator. Survey data were collected from 453 civil servants in Shandong Province, China. Hierarchical regression and the PROCESS MARCO were used for analysis. The results indicate that ESMU (β = 0.42, p < 0.001) and SMUNW (β = 0.14, p < 0.01) both significantly increase turnover intention. Social media exhaustion mediates these relationships, while resilience reduces their negative impact. Our findings contribute to technostress research by clarifying how digital demands influence public employees. For managers and organizations, the results highlight the need to set boundaries for work-related social media use; monitor employees’ digital exhaustion; and foster resilience through recruitment, training, and organizational support. Full article

Objective: Mental fatigue (MF) worsens soccer performance. Further knowledge is needed to understand MF’s effects on soccer players and its underlying mechanisms. Our aim was to analyze the subjective, objective, and neural MF-related outcomes induced by different type of tasks. Methods: A randomized crossover experimental design with repeated measures was used. Thirteen amateur soccer players (M_age = 23 ± 5.43) completed three conditions: cognitive (30 min. Stroop.), physical (30 min. cycling), or combined (30 min. Stroop while cycling). Ratings of mental fatigue (measured via the Visual Analogue Scale), electroencephalographical signals (electroencephalography), and psychomotor performance (Brief-Psychomotor Vigilance Test) were measured pre- and post-condition. Soccer-related decision-making (TacticUP^® test) was assessed post-condition. Results: Linear Mixed Models analysis revealed increments in perceived mental fatigue in all conditions, especially cognitive (p = 0.004) and combined (p < 0.0001) conditions. Psychomotor performance worsened, especially for cognitive (p = 0.039) and combined (p = 0.009) conditions. The Individual Alpha Peak Frequency was lower after the cognitive task (p = 0.040) and compared with the physical task (p = 0.021). The Alpha midline power increased after the cognitive task in the central-frontal (p = 0.047) and central-posterior brain regions (p = 0.043). Conclusions: Cognitive and combined conditions were found to be more mentally demanding and fatiguing than single physical tasks. This was also reflected by an impaired reaction time. Based on the neural activity recorded, the performance impairments caused by mental fatigue were caused by reduced brain readiness (i.e., a lower Alpha Peak Frequency). However, non-significant changes were found in soccer-related decision-making. Coaches should consider the type of training tasks they recommend in light of their different effects on mental fatigue and performance. Full article

Background/Objectives: The global threat of antimicrobial resistance is a significant public health challenge, leading to prolonged hospitalizations, increased costs, and elevated mortality. Romania faces one of Europe’s highest burdens of antimicrobial consumption and resistance. This study aimed to investigate the factors that influence antibiotic prescribing practices among physicians in pediatric care in Romania. Method: This quantitative, cross-sectional study collected data using a self-administered, structured questionnaire from 154 healthcare professionals (family physicians, pediatricians, and other specialists) providing pediatric care in Romania. Participants were recruited via non-probability convenience sampling. The 29-question survey gathered demographic data and explored perceptions and practices regarding antibiotic therapy in children using a 5-point Likert scale. Results: The majority of participants were family physicians (64.94%) with over 15 years of experience (53.90%), primarily practicing in urban settings (61.69%). Only 21.43% had attended an antibiotic stewardship course in the last three years. Physicians generally base their prescribing on clinical symptoms. While physicians strongly agreed they follow guidelines, personal experience also held significant weight. High parental demand for antibiotics was perceived, but physicians largely denied ceding to parental tone or insistence without a medical indication. A strong consensus existed on antibiotic overuse in Romanian children, and a high interest in continuous education on rational antibiotic use was noted. Pediatricians showed significantly higher guideline adherence and diagnostic test use than family physicians. Rural physicians reported lower guideline adherence and less frequent diagnostic testing. Stewardship course participation and access to rapid diagnostic tests were associated with more evidence-based practices. Conclusions: Romanian physicians exhibit a nuanced approach to antibiotic prescribing, balancing guidelines with personal experience and facing significant perceived parental pressure. Professional profile (specialty, experience, practice environment) and access to diagnostic resources significantly influence prescribing decisions. Full article

The transformation of the transportation sector is critical for achieving Sustainable Development Goal 7 (SDG 7). As the world’s largest auto market, China has implemented various policies to promote sustainable transportation, particularly through the adoption of new energy vehicles (NEVs), thereby increasing the share of renewables in energy consumption and improving energy efficiency. Among these policies, the NEV driving restrictions exemption (NEV-DRE) policy has emerged as a key non-financial incentive to stimulate NEV demand. This study focuses on how the NEV-DRE policy affects the demand side of NEVs in the transportation sector. Employing a difference-in-differences design on a comprehensive dataset of vehicle transactions across 82 prefecture-level pilot cities from 2011 to 2019, this study provides robust causal evidence that the NEV-DRE policy significantly increases NEV sales. Furthermore, this study finds that this growth in demand is primarily driven by an increased consumer preference for domestic pure electric sedans. The policy proves more effective in cities with general driving restrictions, purchasing restrictions, and greater environmental awareness. Our findings demonstrate how innovative traffic management measures can be transformed into effective industrial policy tools, accelerating the adoption of renewable energy in the transportation sector. This study offers valuable insights for policymakers in China and elsewhere on how to design non-financial incentives to promote sustainable transportation, thereby promoting sustainable energy transitions and contributing to the achievement of SDG 7. Full article

This study comprehensively evaluates the impact of remote work intensity on employee well-being, productivity, and sustainable practices within the IT sector, utilizing a cross-sectional online survey of 1003 employees. Findings reveal that remote work consistently boosts self-rated health, enhances perceived productivity, and promotes the adoption of sustainable workplace practices, with these benefits largely consistent across gender and most age groups. However, its effect on perceived stress is complex and significantly age-dependent, showing increased stress for younger employees (under 25) while mid-career professionals (26–35) experience stress reduction. Perceived stress did not emerge as a statistically significant mediator in the remote work-productivity relationship, suggesting that positive effects on productivity are primarily driven by direct mechanisms such as increased autonomy and flexibility. This research contributes to the Job Demands-Resources and Self-Determination Theory by illuminating how digital work demands and psychological needs are experienced heterogeneously across demographics in the remote context. Practical implications emphasize the need for differentiated stress management strategies tailored to younger employees, as well as a broader promotion of remote work, to enhance sustainable behavior within organizations. Methodologically, the study highlights the value of utilizing large, non-probability datasets, along with carefully constructed proxy scales, and proposes the future integration of AI-powered analytics for deeper insights. Full article

With increasing global energy demand and depletion of onshore oil–gas resources, deep-sea hydrocarbon exploration and development have become strategically vital. As core subsea transportation equipment, the performance of helico-axial multiphase pumps directly determines the efficiency and economic feasibility of deep-sea extraction. However, non-uniform inflow patterns caused by uneven gas–liquid distribution in pipelines degrade pressure-boosting capability and reduce pump efficiency under actual operating conditions. To address this, an optimization method employing helical static mixers was developed. A mixer with a 180° helical angle was designed and installed upstream of the pump inlet. Numerical simulations demonstrate that the mixer enhances gas-phase distribution uniformity in stratified flow, improving efficiency and head across varying gas void fractions (GVFs). At a stratification height ratio (Ψ) of 0.32, efficiency increased by 15.41% and head rose by 15.64 m, while turbulent kinetic energy (TKE) at the impeller outlet decreased by up to 50%. For slug flow conditions, the mixer effectively suppressed gas volume fraction fluctuations, consistently improving efficiency under different slug flow coefficients (φ) with a maximum head increase of 9.82%. The optimized flow field exhibits uniform gas–liquid velocity distribution, stable pressure boosting, and significantly reduced TKE intensity within impeller passages. Full article

This work presents the design and simulation of a time-interleaved successive approximation register (SAR) analog-to-digital converter (ADC) implemented in GlobalFoundries’ 22 nm Fully Depleted Silicon-on-Insulator (FD-SOI) CMOS process. Motivated by the increasing demand for high-speed electrical links in data center and AI/ML applications, the proposed ADC architecture targets medium-resolution, high-throughput conversion with optimized power and area efficiency. The design leverages asynchronous SAR operation, bootstrapped sampling switches, and a hybrid binary/non-binary capacitive digital-to-analog converter (DAC) to achieve robust performance across process, voltage, and temperature (PVT) variations. System-level modeling using channel operating margin (COM) methodology guided the specification of key circuit blocks, enabling efficient trade-offs between resolution, speed, and power. Post-layout simulations demonstrated effective number of bits (ENOB) performance consistent with system requirements, while Monte Carlo analysis confirmed the statistical yield. The converter achieved competitive figures of merit compared to state-of-the-art designs, as benchmarked against the Murmann ADC survey. This work highlights critical design considerations for scalable mixed-signal architectures in advanced CMOS nodes and lays the foundation for future integration in high-speed SerDes systems. Full article

The genus Camellia offers valuable resources for tea production, oil extraction, and ornamental purposes, and its applications are expanding beyond traditional regions due to increasing human demands and advancements in research. To explore new therapeutic resources and identify key active metabolites, we conducted a non-targeted metabolomics analysis on three camellias. We also utilized network pharmacology to identify the potential targets of key metabolites involved in anti-inflammatory, antioxidant, antibacterial, and antiviral effects. A total of 385 significantly different metabolites were identified, with organic acids and derivatives, lipids and lipid-like molecules, and phenylpropanoids and polyketides being the top three metabolite classes. Of the 71 different phenylpropanoids and polyketides identified, 54 were common across all three cultivars, while 17 were unique. Network pharmacology further identified 78 potential molecular targets associated with the four therapeutic activities under study. Seven flavonoid glycosides, two flavans, two biflavonoids/polyflavonoids, and one flavone were highlighted as key active metabolites. Notably, Camellia japonica ‘Kōshi’ emerged as a promising material for future applications. The key active ingredients may contribute to the development of novel approaches for cosmetic, food, and medicinal applications, as well as germplasm innovation for new functional camellias. Full article

This paper presents a modular and distributed supervisory control integration framework for intelligent micro-manufacturing systems (MMSs) under event-level failures. Addressing the increasing demand for scalable and reliable supervisory control in both micro- and smart manufacturing, the proposed approach equips each subsystem with a detector automaton that classifies runtime states into Strictly robust, Recoverably robust, or Non-robust categories. Distributed supervisors then make real-time local decisions to ensure fault-tolerant evolution of system behaviors. Unlike conventional centralized or Petri net-based methods, the proposed automaton-based framework supports modular design and structural scalability. Quantitative comparisons show that the robustness-detection cost scales approximately linearly with the summed sizes of local graphs, indicating good structural scalability. Simulation studies validate the feasibility and scalability of the framework, demonstrating its effectiveness in maintaining production cycle reachability and its integration potential for micro-electro-mechanical systems (MEMS)-based production lines, micro-fabrication platforms, and smart factory environments. These results confirm that the proposed method can serve as a robust and deployable control layer for next-generation intelligent and micro-manufacturing integration architectures. Full article

The increasing demand for red wines, supported by their complex sensory features and rich biochemical composition, has encouraged cultivation in non-traditional viticultural regions. This study investigates the antioxidant potential and volatile composition of three red grape cultivars (Feteasca neagra, Merlot, and Pinot noir) cultivated in the Tarnave Vineyard, Romania, a region historically dedicated to white wines but now increasingly favorable to red varieties due to climate change. Antioxidant capacity, assessed via DPPH, Trolox equivalent antioxidant capacity (TEAC), and Ferric reducing antioxidant power (FRAP) assays, identified Feteasca neagra as the most potent (IC₅₀: 115.32 µg/mL; FRAP: 13.45 mmol TE/L). Gas chromatography–mass spectrometry (GC–MS) profiling identified 61 volatile compounds, with Pinot noir showing the highest concentration (99,018.57 µg/L). Multivariate analysis (ANOVA, PCA) confirmed significant varietal differences and terroir-specific influences on wine composition. Pinot noir was characterized by high levels of higher alcohols, esters, and lactones, yielding a floral and fruity aroma, while Feteasca neagra exhibited intense color, high flavonoid content (notably malvidin-3-glucoside), and vanilla–herbal notes. Merlot presented a balanced sensory profile with significant phenolic acid content. These findings highlight the chemical and sensory potential of the Tarnave Vineyard for premium red wine production. Full article

The demand for high energy density in mobile devices (including vehicles and small ships) is increasing. Nickel–Manganese–Cobalt (NMC) ternary, as a battery cathode material, is increasingly being applied because of its higher energy density relative to LiFePO₄ or other traditional materials. But NMC also faces challenges, such as a high degeneration rate and heat generation. So these aspects of Ni content must be clarified. In the current study, two Ni-content battery cells were tested, and the results of other composition cathode cells from the literature were compared. And three typical Ni-content batteries were simulated for searching Ni effects on performance, capacity fade and heat generation. Some findings were achieved: (1) from 0.8 Ni content, it can be seen that the specific capacity growth rate (slope) was much greater than before; (2) cathode materials that have an odd number (that does not surpass 0.7) of Ni content showed a linear capacity degradation trend, but others did not; (3) the Li concentration within material particles did not correspond to absolute stress value but stress temporal gradient; and (4) during discharge, lower Ni content made the heat peak occur earlier but lowered the absolute value; the irreversible heat increased with Ni content non-linearly, so that the higher the Ni content went up, the higher the increase rate of the irreversible heat ratio. Thus, the results of this study can guide the design and application of high energy batteries for mobile devices. Full article

The rapid growth of the aging population, alongside functional decline and more older adults living independently, has increased demand for age-friendly infrastructure and walkable communities. This study proposes a quantitative framework to assess how multi-scale built environments influence older adults’ walkability, addressing the scarcity of scalable and interpretable models in age-friendly urban research. By combining the cumulative opportunity method, street-scene semantic segmentation, XGBoost, and GeoSHapley-based spatial effect analysis, the study finds that (1) significant spatial disparities in walkability exist in Xiamen’s central urban area. Over half of the communities (54.46%) failed to meet the minimum threshold (20 points) within the 15 min community life circle (15-min CLC), indicating inadequate infrastructure. The primary issue is low coverage of older adults’ welfare facilities (only 16.26% of communities are within a 15 min walk). Despite renovations in Jinhu Community, walkability remains low, highlighting persistent disparities. (2) Communities with abundant green space are predominantly newly developed areas (64.06%). However, these areas provide fewer facilities on average (2.3) than older communities (5.7), resulting in a “green space–service mismatch”, where visually appealing environments lack essential services. (3) Human perception variables such as safety, traffic flow, and closure positively influence walkability, while visual complexity, heat risk, exposure, and greenness have negative effects. (4) There is a clear supply and demand mismatch. Central districts combine high walkability with substantial older adults’ service demand. Newly built residential areas in the periphery and north have low density and insufficient pedestrian facilities. They fail to meet daily accessibility needs, revealing delays in age-friendly development. This framework, integrating nonlinear modeling and spatial analysis, reveals spatial non-stationarity and optimal thresholds in how the built environment influences walkability. Beyond methodological contributions, this study offers guidance for planners and policymakers to optimize infrastructure allocation, promote equitable, age-friendly cities, and enhance the health and wellbeing of older residents. Full article

Polyimide (PI) is widely used in aerospace, electronic packaging, and other fields due to its excellent dielectric and thermophysical properties. However, the performance of traditional PI materials under extreme conditions has become increasingly inadequate to meet the growing demands. To address this, this study designed a PI/Nano-Si₃N₄ advanced composite material and, based on molecular dynamics simulations, thoroughly explored the influence of silane coupling agents with different grafting densities on the interfacial microstructure and their correlation with the overall material’s physical properties. The results show that when the grafting density is 10%, the interfacial bonding of the PI/Nano-Si₃N₄ composite is optimized: non-bonded interaction energy increases by 18.4%, the number of hydrogen bonds increases by 32.5%, and the free volume fraction decreases to 18.13%. These changes significantly enhance the overall performance of the material, manifested by an increase of about 30 K in the glass transition temperature and a 49.5% improvement in thermal conductivity compared to pure PI. Furthermore, the system maintains high Young’s modulus and shear modulus in the temperature range of 300–700 K. The study reveals that silane coupling agents can effectively enhance the composite material’s overall performance by optimizing the interfacial structure and controlling the free volume, providing an efficient computational method for the design and performance prediction of advanced high-performance PI composites. Full article

Nowadays, virtual reality is experiencing widespread adoption, and its popularity is expected to grow in the next few decades. A relevant portion of virtual reality content is represented by 360-degree videos, which allow users to be surrounded by the video content and to explore it without limitations. However, 360-degree videos are extremely demanding in terms of storage and streaming requirements. At the same time, users are not able to enjoy the 360-degree content all at once due to the inherent limitations of the human visual system. For this reason, viewport prediction techniques have been proposed: they aim at forecasting where the user will look, thus allowing the transmission of the sole viewport content or the assignment of a different quality level for viewport and non-viewport regions. In this context, artificial intelligence plays a pivotal role in the development of high-performance viewport prediction solutions. In this work, we analyze the evolution of viewport prediction based on machine and deep learning techniques in the last decade, focusing on their classification based on the employed processing technique, as well as the input and output formats. Our review shows common gaps in the existing approaches, thus paving the way for future research. An increase in viewport prediction accuracy and reliability will foster the diffusion of virtual reality content in real-life scenarios. Full article