Search Results (23,020)

Skeletal muscle atrophy is a critical health issue affecting the quality of life of elderly individuals and patients with chronic diseases. These conditions induce dysregulation of glucocorticoid (GC) secretion. GCs play a critical role in maintaining homeostasis in the stress response and glucose metabolism. However, prolonged exposure to GC is directly linked to muscle atrophy, which is characterized by a reduction in muscle size and weight, particularly affecting fast-twitch muscle fibers. The GC-activated glucocorticoid receptor (GR) decreases protein synthesis and facilitates protein breakdown. Numerous antagonists have been developed to mitigate GC-induced muscle atrophy, including 11β-HSD1 inhibitors and myostatin and activin receptor blockers. However, the clinical trial results have fallen short of the expected efficacy. Recently, several emerging pathways and targets have been identified. For instance, GC-induced sirtuin 6 isoform (SIRT6) expression suppresses AKT/mTORC1 signaling. Lysine-specific demethylase 1 (LSD1) cooperates with the GR for the transcription of atrogenes. The kynurenine pathway and indoleamine 2,3-dioxygenase 1 (IDO-1) also play crucial roles in protein synthesis and energy production in skeletal muscle. Therefore, a deeper understanding of the complexities of GR transactivation and transrepression will provide new strategies for the discovery of novel drugs to overcome the detrimental effects of GCs on muscle tissues. Full article

Mining (1) operations in remote areas (2) face significant challenges related to energy supply, high fuel costs, and limited infrastructure. This study investigates the potential for achieving energy independence (3) and resilience (4) in such environments through the integration of renewable energy sources (5) and battery–electric mining equipment. Using the “Studena Vrila” underground bauxite mine as a case study, a comprehensive techno-economic and environmental analysis was conducted across three development models. These models explore incremental scenarios of solar and wind energy adoption combined with electrification of mobile machinery. The methodology includes calculating levelized cost of energy (LCOE), return on investment (ROI), and greenhouse gas (GHG) reductions under each scenario. Results demonstrate that a full transition to RES and electric machinery can reduce diesel consumption by 100%, achieve annual savings of EUR 149,814, and cut GHG emissions by over 1.7 million kg CO₂-eq. While initial capital costs are high, all models yield a positive Net Present Value (NPV), confirming long-term economic viability. This research provides a replicable framework for decarbonizing mining operations in off-grid and infrastructure-limited regions. Full article

To address the shortcomings of poor convergence and the ease of falling into local optima when using the traditional gold rush optimization (GRO) algorithm to solve the complex scheduling problem of a combined cooling, heating, and power (CCHP) microgrid system, an optimal scheduling model for a microgrid based on the improved gold rush optimization (IGRO) algorithm is proposed. First, the Halton sequence is introduced to initialize the population, ensuring a uniform and diverse distribution of prospectors, which enhances the algorithm’s global exploration capability. Then, a dynamically adaptive weighting factor is applied during the gold mining phase, enabling the algorithm to adjust its strategy across different search stages by balancing global exploration and local exploitation, thereby improving the convergence efficiency of the algorithm. In addition, a weighted global optimal solution update strategy is employed during the cooperation phase, enhancing the algorithm’s global search capability while reducing the risk of falling into local optima by adjusting the balance of influence between the global best solution and local agents. Finally, a t-distribution mutation strategy is introduced to improve the algorithm’s local search capability and convergence speed. The IGRO algorithm is then applied to solve the microgrid scheduling problem, with the objective function incorporating power purchase and sale cost, fuel cost, maintenance cost, and environmental cost. The example results show that, compared with the GRO algorithm, the IGRO algorithm reduces the average total operating cost of the microgrid by 3.29%, and it achieves varying degrees of cost reduction compared to four other algorithms, thereby enhancing the system’s economic benefits. Full article

In modern agriculture, tractors play a crucial role in powering tools and implements. Proper operation of agricultural tractors in mechanized field operations can support sustainable agriculture and reduce emissions of pollutants such as carbon dioxide (CO₂). This has been a recurring concern associated with agricultural intensification for food production. This study aimed to evaluate the optimization of tractor gears and engine speed during crop operations to minimize CO₂ emissions and promote sustainability. The experiment was conducted using a strip plot design with subdivided sections and six replications, following a double factorial structure. The first factor evaluated was the type of agricultural implement (disc harrow, subsoiler, or sprayer), while the second factor was the engine speed setting (nominal or reduced). Operational and energy performance metrics were analyzed, including fuel consumption and CO₂ emissions, travel speed, effective working time, wheel slippage, and working depth. Optimized gear selection and engine speeds resulted in a 20 to 40% reduction in fuel consumption and CO₂ emissions. However, other evaluated parameters remain unaffected by the reduced engine speed, regardless of the implement used, ensuring the operation’s quality. Thus, optimizing operator training or configuring machines allows for environmental impact reduction, making agricultural practices more sustainable. Full article

The interface between high-performance thermoelectric materials and electrodes critically governs the conversion efficiency and long-term reliability of thermoelectric generators under high-temperature operation. Here, we propose Al_xCoCrFeNi high-entropy alloys (HEA) as barrier layers to bond Cu-W electrodes with p-type skutterudite (p-SKD) thermoelectric materials. The HEA/p-SKD interface exhibited excellent chemical bonding with a stable and controllable reaction layer, forming a dense, defect-free (Fe,Ni,Co,Cr)Sb phase (thickness of ~2.5 μm) at the skutterudites side. The interfacial resistivity achieved a low value of 0.26 μΩ·cm² and remained at 7.15 μΩ·cm² after aging at 773 K for 16 days. Moreover, the interface demonstrated remarkable mechanical stability, with an initial shear strength of 88 MPa. After long-term aging for 16 days at 773 K, the shear strength retained 74 MPa (only 16% degradation), ranking among the highest reported for thermoelectric materials/metal joints. Remarkably, the joint maintained a shear strength of 29 MPa even after 100 continuous thermal cycles (623–773 K), highlighting its outstanding thermo-mechanical stability. These results validate the Al_xCoCrFeNi high-entropy alloys as an ideal interfacial material for thermoelectric generators, enabling simultaneous optimization of electrical and mechanical performance in harsh environments. Full article

This study explores the perceptions of future educators, specifically Early Childhood Education students at the Universities of Cádiz and Gdansk, regarding the interconnections between critical thinking and sustainability. The work aims to provide valuable insights into general teacher training, examining how these students’ experiences are contextualized within their respective educational systems and cultural contexts. To achieve this, eleven group interviews (three in Cádiz, eight in Gdansk) were conducted using a structured and expert-validated script. The transcribed data were qualitatively analyzed using QDA MINER v.6 software. Key findings reveal divergent perceptions of critical thinking among pre-service teachers: while Spanish students leaned towards a subjective understanding, Polish students emphasized an objective, data-driven approach. This distinction has significant implications for the conceptualization and teaching of critical thinking in educator training. Despite these differences, both groups of participants highlighted the necessity of implementing active methodologies in higher education (such as cooperative learning, problem-solving, and debates) to foster critical thinking, both for their own development and for preparing for their future practice with young children. This study also identified an excessive emphasis on theoretical aspects of sustainability in these future teachers’ training and a limited understanding of their practical application in the classroom. Furthermore, explicit connections between critical thinking and sustainability were scarce in student responses, highlighting a gap in current educator training in these areas. Collectively, the results suggest significant weaknesses in current teacher training efforts regarding the development of critical thinking and its effective integration with sustainability competencies. Full article

Ecosystem restoration represents a promising solution for enhancing ecosystem services and environmental sustainability. However, border regions—characterized by ecological fragility and geopolitical complexity—remain underrepresented in ecosystem service and restoration research. To fill this gap, we coupled spatially explicit models (e.g., InVEST and RUSLE) with scenario analysis to quantify the ecosystem service potential that could be achieved in China’s Tibetan borderlands under two interacting agendas: ecological restoration and border-strengthening policies. Restoration feasibility was evaluated through combining local biophysical constraints, economic viability (via restoration-induced carbon gains vs. opportunity costs), operational practicality, and simulated infrastructure expansion. The results showed that per-unit-area ecosystem services in border counties (particularly Medog, Cona, and Zayu) exceed that of interior Tibet by a factor of two to four. Combining these various constraints, approximately 4–17% of the border zone remains cost-effective for grassland or forest restoration. Under low carbon pricing (US$10 t⁻¹ CO₂), the carbon revenue generated through restoration is insufficient to offset the opportunity cost of agricultural production, constituting a major constraint. Habitat quality, soil conservation, and carbon sequestration increase modestly when induced by restoration, but a pronounced carbon–water trade-off emerges. Planned infrastructure reduces restoration benefits only slightly, whereas raising the carbon price to about US$50 t⁻¹ CO₂ substantially expands such benefits. These findings highlight both the opportunities and limits of ecosystem restoration in border regions and point to carbon pricing as the key policy lever for unlocking cost-effective restoration. Full article

Low-frequency (LF) time code timing technology holds significant importance in civilian applications such as radio-controlled clocks. This study focuses on the design and implementation of a high-precision Binary Phase Code (BPC) LF time code signal generator. A generator system was constructed, demonstrating good stability, superior resolution, and flexible adjustment capabilities for both amplitude and phase. The system employs an ARM + FPGA cooperative architecture: the ARM processor is responsible for parsing and scheduling the time code data, while the FPGA implements carrier wave generation and high-precision digital modulation. This digital processing is combined with analog circuitry to achieve digital-to-analog (D/A) signal conversion. Compared to traditional methods, carrier generation is achieved using Direct Digital Synthesis (DDS) technology. Digital modulation techniques enable the precise control of the modulation depth (adjustable between 70% and 90%) and phase (with a resolution of 1 ns). A sliding window algorithm was utilized for time difference calculation and compensation. Testing confirmed the stability of key signal parameters, including integrity, carrier frequency and modulation depth. These results validate the feasibility and superiority of the digital LF time code generation technology proposed in this study, providing a valuable reference for the development of next-generation timing equipment. Full article

In UGC-based knowledge trading platforms, the abundance of personalized content often leads to varying quality levels. By incorporating embedded advertising, platforms can incentivize knowledge producers to produce high-quality content; however, the uncertainty in managing embedded advertisements increases the complexity of pricing knowledge products. This paper examines the impact of embedded advertising on the pricing of knowledge products, aims to maximize the profits of both knowledge producer and the platform. Based on Stackelberg game theory, two pricing decision models are developed under different advertising management modes: the platform-managed mode (where the platform determines the advertising intensity) and the advertiser-managed mode (where the advertiser determines the advertising intensity). The study analyzes the effects of UGC product quality, consumer sensitivity to advertising, and power structure on knowledge product pricing, and derives threshold conditions for optimal pricing. The results indicate that (1) When the quality of UGC knowledge product exceeds a certain threshold, platform-managed advertising becomes profitable. (2) Under the platform-managed mode, both the platform and knowledge producer can adopt price-increasing strategies to enhance profits. (3) Under the advertiser-managed mode, the platform can leverage differences in power structure to optimize revenue, while knowledge producer can actively enhance his pricing power to achieve mutual benefits with the platform. This study provides theoretical support and practical guidance for advertising cooperation mechanisms and pricing strategies for knowledge products in UGC-based knowledge trading platforms. Full article

This study examines the progress, challenges, and successes in implementing Sustainable Development Goal 12 (SDG12), focusing on responsible consumption and production, using Qatar as a case study. The State has integrated Sustainable Consumption and Production (SCP) into national policies, established coordination mechanisms, and implemented action plans aligned with SDG12 targets. Achievements include renewable energy adoption, waste management reforms, and sustainable public procurement, though challenges persist in rationalizing fossil fuel subsidies, addressing data gaps, and enhancing corporate sustainability reporting. Efforts to reduce food loss and waste through redistribution programs highlight the country’s resilience, despite logistical obstacles. The nation has also advanced hazardous waste management, environmental awareness, and sustainable tourism policies, though gaps in data systems and policy coherence remain. Qatar’s approach provides a valuable local-to-global example of balancing resource-dependent economies with sustainability goals. Its strategies and lessons offer potential adaptability for other nations, especially those facing similar challenges in achieving SDG12. By strengthening data systems, enhancing policy integration, and fostering regional and international cooperation, Qatar’s efforts underscore the importance of aligning economic growth with environmental stewardship, serving as a blueprint for global sustainability initiatives. Full article

The Fit for 55 package introduced by the European Union aims to achieve a 55% reduction in greenhouse gas emissions by 2030. In parallel, increasingly stringent exhaust gas regulations have intensified research into alternative fuels. Ethanol presents a promising option due to its compatibility with gasoline, higher octane rating, and lower exhaust emissions compared to conventional gasoline. Additionally, ethanol can be derived from agricultural waste, further enhancing its sustainability. This study examines the impact of two ethanol–gasoline blends (E10, E20) on emissions and performance in a turbocharged gasoline direct injection (TGDI) spark-ignition (SI) engine. The investigation is conducted using three-dimensional computational fluid dynamics (3D CFD) simulations to minimize development time and costs. This paper details the model development process and presents the initial results. The boundary conditions for the simulations are derived from one-dimensional (1D) simulations, which have been validated against experimental data. Subsequently, the simulated performance and emissions results are compared with experimental measurements. The E10 simulations correlated well with experimental measurements, with the largest deviation in cylinder pressure being an RMSE of 1.42. In terms of emissions, HC was underpredicted, while CO was overpredicted compared to the experimental data. For E20, the IMEP was slightly higher at some operating points; however, the deviations were negligible. Regarding emissions, HC and CO emissions were higher with E20, whereas NOx and CO₂ emissions were lower. Full article

This study is the first to investigate the performance of ultraviolet germicidal irradiation (UVGI) in underfloor air distribution (UFAD) systems. A simplified mathematical model is developed to predict airborne pathogen transport and inactivation by upper room UVGI in UFAD spaces. The proposed model is substantiated for the SARS-CoV-2 virus as a simulated pathogen through a comprehensive computational fluid dynamics methodology validated against published experimental data of upper room UVGI and UFAD flows. Simulations show an 11% decrease in viral concentration within the upper irradiated zone when a 15 W louvered germicidal lamp is utilized. Finally, a case study on Mycobacterium tuberculosis (M. tuberculosis) bacteria is carried out using the validated simplified model to optimize the use of return air and UVGI implementation, ensuring acceptable indoor air quality and enhanced energy efficiency. Results reveal that the UFAD-UVGI system may consume up to 13.6% less energy while keeping the occupants at acceptable levels of M. tuberculosis concentration and UV irradiance when operated with 26% return air and a UVGI output of 72 W. Full article

A series of Cu-MnO_x/GF catalytic electrodes, with graphite felt (GF) pretreated via microwave modification as the catalyst carrier, were prepared under various hydrothermal conditions and characterized using X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), X-ray photoelectron spectroscopy (XPS), N₂ adsorption–desorption, and Raman spectroscopy. The catalytic oxidation activity of catalytic Cu-MnO_x/GF electrodes toward toluene was evaluated in an all-solid-state electrocatalytic device under mild operating conditions. The evaluation results demonstrated that the microwave-modified catalytic electrode exhibited high electrocatalytic activity toward toluene oxidation, with Cu-MnO_x/700W-GF exhibiting significantly higher catalytic activity, indicating that an increase in catalyst loading capacity can promote the removal of toluene. Only CO₂ and CO were detected, with no other intermediates observed in the reaction process. Moreover, the catalytic effect was significantly affected by the relative humidity. The catalytic oxidation of toluene can be fully realized under a certain humidity, indicating that the conversion of H₂O to strongly oxidizing ·OH on the catalytic electrode is a key step in this reaction. Full article

The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. This study proposes a hierarchical adaptive feature aggregation network (HAF-YOLO) to improve detection precision in remote-sensing images. It addresses issues such as small object size, complex backgrounds, scale variation, and dense object distributions by incorporating three core modules: dynamic-cooperative multimodal fusion architecture (DyCoMF-Arch), multiscale wavelet-enhanced aggregation network (MWA-Net), and spatial-deformable dynamic enhancement module (SDDE-Module). DyCoMF-Arch builds a hierarchical feature pyramid using multistage spatial compression and expansion, with dynamic weight allocation to extract salient features. MWA-Net applies wavelet-transform-based convolution to decompose features, preserving high-frequency detail and enhancing representation of small-scale objects. SDDE-Module integrates spatial coordinate encoding and multidirectional convolution to reduce localization interference and overcome fixed sampling limitations for geometric deformations. Experiments on the NWPU VHR-10 and DIOR datasets show that HAF-YOLO achieved mAP50 scores of 85.0% and 78.1%, improving on YOLOv8 by 4.8% and 3.1%, respectively. HAF-YOLO also maintained a low computational cost of 11.8 GFLOPs, outperforming other YOLO models. Ablation studies validated the effectiveness of each module and their combined optimization. This study presents a novel approach for remote-sensing object detection, with theoretical and practical value. Full article

Curli fimbriae are a major component of biofilm formation in Escherichia coli, and their expression is regulated by numerous transcription factors and small regulatory RNAs (sRNAs). The RcsD-RcsC-RcsB phosphorelay system, which is involved in the envelope stress response, plays a role in this regulation. In this study, we report that DNase-I footprinting analysis revealed that the response regulator RcsB interacts with the −31 to +53 region of the promoter region of csgD, which encodes a major regulator of biofilm formation, and thus contributes to its transcriptional repression. Additionally, overexpression of RcsB or RcsB D56A that could not be phosphorylated by the histidine kinases RcsC and D both significantly reduced csgD expression and suppressed Curli formation. This indicates that the phosphorylation of RcsB has an insignificant impact on its affinity for its operator sites. Furthermore, we confirm that RcsB binds cooperatively to the csgD promoter region in the presence of the nucleoid-associated protein H-NS. Our study also confirms that RcsB positively regulates the expression of an sRNA, RprA, which is known to reduce mRNA csgD mRNA translation RprA via its binding to the 5′-untranslated region (UTR) of csgD. These findings indicate that, in E. coli, the RcsBCD system suppresses csgD expression through both direct transcriptional repression by the regulator RcsB and translational repression by the sRNA RprA. Full article