Search Results (934)

To further enhance the economic performance of fuel cell vehicles (FCVs), this study develops a model-adaptive model predictive control (MPC) strategy. This strategy leverages the dynamic relationship between proton exchange membrane fuel cell (PEMFC) output characteristics and temperature to track its optimal operating temperature (OOT), addressing challenges of temperature control accuracy and high energy consumption in the PEMFC thermal management system (TMS). First, PEMFC and TMS models were developed and experimentally validated. Subsequently, the PEMFC power–temperature coupling curve was experimentally determined under multiple operating conditions to serve as the reference trajectory for TMS multi-objective optimization. For MPC controller design, the TMS model was linearized and discretized, yielding a predictive model adaptable to different load demands for stack temperature across the full operating range. A multi-constrained quadratic cost function was formulated, aiming to minimize the deviation of the PEMFC operating temperature from the OOT while accounting for TMS parasitic power consumption. Finally, simulations under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions evaluated the OOT tracking performance of both PID and MPC control strategies, as well as their impact on stack efficiency and TMS energy consumption at different ambient temperatures. The results indicate that, compared to PID control, MPC reduces temperature tracking error by 33%, decreases fan and pump speed fluctuations by over 24%, and lowers TMS energy consumption by 10%. These improvements enhance PEMFC operational stability and improve FCV energy efficiency. Full article

Fungi, from saprophytes to pathogens, face predictable daily fluctuations in light, temperature, humidity, and nutrient availability. To cope, they have evolved an internal circadian clock that confers a major adaptive advantage. This review critically synthesizes current knowledge on the molecular architecture and physiological relevance of fungal circadian systems, moving beyond the canonical Neurospora crassa model to explore the broader phylogenetic diversity of timekeeping mechanisms. We examine the core transcription-translation feedback loop (TTFL) centered on the FREQUENCY/WHITE COLLAR (FRQ/WCC) system and contrast it with divergent and non-canonical oscillators, including the metabolic rhythms of yeasts and the universally conserved peroxiredoxin (PRX) oxidation cycles. A central theme is the clock’s role in gating cellular defenses against oxidative, osmotic, and nutritional stress, enabling fungi to anticipate and withstand environmental insults through proactive regulation. We provide a detailed analysis of chrono-pathogenesis, where the circadian control of virulence factors aligns fungal attacks with windows of host vulnerability, with a focus on experimental evidence from pathogens like Botrytis cinerea, Fusarium oxysporum, and Magnaporthe oryzae. The review explores the downstream pathways—including transcriptional cascades, post-translational modifications, and epigenetic regulation—that translate temporal signals into physiological outputs such as developmental rhythms in conidiation and hyphal branching. Finally, we highlight critical knowledge gaps, particularly in understudied phyla like Basidiomycota, and discuss future research directions. This includes the exploration of novel clock architectures and the emerging, though speculative, hypothesis of “chrono-therapeutics”—interventions designed to disrupt fungal clocks—as a forward-looking concept for managing fungal infections. Full article

Heart rate (HR) is strongly affected by the autonomic nervous system (ANS), while its spontaneous fluctuations, called heart rate variability (HRV), report about the dynamics of the complex, vegetative regulation of the heart rhythm. Hence, HRV is widely considered an important marker of the ANS effects on the cardiac system, and as such, a crucial diagnostic tool in cardiology. In order to obtain nontrivial results from HRV analysis, it would be desirable to establish exact, universal interrelations between the typical HRV parameters and HR itself. That, however, has not yet been fully accomplished. Hence, our aim was to perform a comparative statistical analysis of ECG recordings from a public database, with a focus on the HR dependence of typical HRV parameters. We revealed their fundamental connections, which were substantiated by basic mathematical considerations, and were experimentally demonstrated via the analysis of 24 h of ECG recordings of more than 200 healthy individuals. The large database allowed us to perform unique age-cohort analyses. We confirmed the HR dependence of typical time-domain parameters, such as RMSSD and SDNN, frequency-domain parameters such as the VLF, LF, and HF components, and nonlinear indices such as sample entropy and DFA exponents. In addition to shedding light on their relationship, we are the first, to our knowledge, to identify a new, diffuse structure in the VHF regime as an important indicator of SNS activity. In addition, the demonstrated age dependence of the HRV parameters gives important new insight into the long-term changes in the ANS regulation of the cardiac system. As a possible molecular physiological mechanism underlying our new findings, we suggest that they are associated with Piezo2 channel function and its age-related degradation. We expect our results to be utilized in HRV analysis related to both medical research and practice. Full article

Accurate and real-time detection of rice shelling rate (SR) and brown rice breakage rate (BR) is crucial for intelligent hulling sorting but remains challenging because of small grain size, dense adhesion, and uneven illumination causing missed detections and blurred boundaries in traditional YOLOv8n. This paper proposes a high-precision, lightweight solution based on an enhanced YOLOv8n with improvements in network architecture, feature fusion, and attention mechanism. The backbone’s C2f module is replaced with C2f-Faster-CGLU, integrating partial convolution (PConv) local convolution and convolutional gated linear unit (CGLU) gating to reduce computational redundancy via sparse interaction and enhance small-target feature extraction. A bidirectional feature pyramid network (BiFPN) weights multiscale feature fusion to improve edge positioning accuracy of dense grains. Attention mechanism for fine-grained classification (AFGC) is embedded to focus on texture and damage details, enhancing adaptability to light fluctuations. The Detect_Rice lightweight head compresses parameters via group normalization and dynamic convolution sharing, optimizing small-target response. The improved model achieved 96.8% precision and 96.2% mAP. Combined with a quantity–mass model, SR/BR detection errors reduced to 1.11% and 1.24%, meeting national standard (GB/T 29898-2013) requirements, providing an effective real-time solution for intelligent hulling sorting. Full article

Tea is one of the most consumed beverages in the world, belonging to the category of compounds known as tannins and flavonoids. One of the polyphenols found in large amounts in green tea leaves (Camellia sinensis) is epigallocatechin-3-O-gallate (EGCG). Though EGCG has shown some pharmacological effects, to date, it has not been utilised as a therapeutic agent. This is attributed to the fact that EGCG lacks adequate stability, and it is known to degrade through epimerization or auto-oxidation processes, especially when it is exposed to light, temperature fluctuations, some pH values, or the presence of oxygen. Consuming green tea with EGCG can alleviate the effects of bone diseases, such as osteoporosis, and support faster bone regeneration in the case of fractures. Therefore, this review focuses on the current state of research, highlighting the effects of EGCG on bone biology, such as enhancing osteoblast differentiation, promoting bone mineralisation, improving bone microarchitecture, and inhibiting osteoclastogenesis through the modulation of the RANK/RANKL/OPG pathway. Additionally, EGCG exerts antioxidant, anti-inflammatory, and dose-dependent effects on bone cells. It also downregulates inflammatory markers (TNF-α, IL-1β, and COX-2) and reduces oxidative stress via the inhibition of reactive oxygen species generation and the activation of protective signalling pathways (e.g., MAPK and NF-κB). Studies in animal models confirm that EGCG supplementation leads to increased bone mass and strength. These findings collectively support the further exploration of EGCG as an adjunct in the treatment and prevention of metabolic bone diseases. The authors aim to present the relationship between EGCG and bone health, highlighting issues for future research and clinical applications. Full article

The accurate extraction of navigational regions from images of navigational waters plays a key role in ensuring on-water safety and the automation of unmanned vessels. Nonetheless, current technological methods encounter significant challenges in addressing fluctuations in water surface illumination, reflective disturbances, and surface undulations, among other disruptions, in turn making it challenging to achieve rapid and precise boundary segmentation. To cope with these challenges, in this paper, we propose a coordinate-aware multi-scale feature network (GASF-ResNet) method for water segmentation. The method integrates the attention module Global Grouping Coordinate Attention (GGCA) in the four downsampling branches of ResNet-50, thus enhancing the model’s ability to capture target features and improving the feature representation. To expand the model’s receptive field and boost its capability in extracting features of multi-scale targets, the Avoidance Spatial Pyramid Pooling (ASPP) technique is used. Combined with multi-scale feature fusion, this effectively enhances the expression of semantic information at different scales and improves the segmentation accuracy of the model in complex water environments. The experimental results show that the average pixel accuracy (mPA) and average intersection and union ratio (mIoU) of the proposed method on the self-made dataset and on the USVInaland unmanned ship dataset are 99.31% and 98.61%, and 98.55% and 99.27%, respectively, significantly better results than those obtained for the existing mainstream models. These results are helpful in overcoming the background interference caused by water surface reflection and uneven lighting in the aquatic environment and in realizing the accurate segmentation of the water area for the safe navigation of unmanned vessels, which is of great value for the stable operation of unmanned vessels in complex environments. Full article

The synergistic development of ecosystems and socioeconomic systems constitutes a critical foundation for achieving Sustainable Development Goals (SDGs). Large river basins characterized by ecological and socioeconomic spatial heterogeneity frequently present contradictions and conflicts in regional sustainable development, thereby impeding the realization of SDGs. This study employed the Yellow River Basin (YRB), a typical large sediment-laden river system, as a case study. Based on the secondary water resource zones, the spatial variability and temporal evolution of ecosystem service value (ESV), population (POP), GDP, nighttime light (NTL), and Human Development Index (HDI) were analyzed at the water resource partition scale. A consistent mode was applied to quantify the spatiotemporal consistency between ESV and socioeconomic indicators across water resource partitions. The results indicated that from 1980 to 2020, the ESV of the YRB increased from 1079.83 × 10⁹ to 1139.20 × 10⁹ yuan, with no notable spatial pattern variation. From upstream to downstream, the population density, GDP per unit area, and NTL per unit area displayed increasing trends along the river course, whereas the total population, GDP, and NTL initially increased and then declined. Temporally, the population fluctuated with an overall upward tendency, while GDP and NTL experienced significant growth. The spatial distribution and temporal evolution of HDI remained comparatively stable. The coefficients of variation for population, GDP, and NTL were significantly higher than those for ecosystem services and HDI. The study highlighted an overall lack of coordination between ESV and socioeconomic development in the YRB, with relatively stable spatial patterns. These findings could offer a theoretical reference for the formulation of policies to enhance the synergistic development of ecosystems and socioeconomic systems in the YRB. Full article

Due to its persistence and potential negative effects on ecosystems and human health, microplastic pollution in aquatic environments has become a major worldwide concern. Photocatalytic degradation is a sustainable manner to degrade microplastics to non-toxic by-products. In this review, comprehensive discussion focuses on the synergistic effects of various photocatalytic materials including TiO₂, ZnO, WO₃, graphene oxide, and metal–organic frameworks for producing heterojunctions and involving multidimensional nanostructures. Such mechanisms can include the generation of reactive oxygen species and polymer chain scission, which can lead to microplastic breakdown and mineralization. The advancements of material modifications in the (nano)structure of photocatalysts, doping, and heterojunction formation methods to promote UV and visible light-driven photocatalytic activity is discussed in this paper. Reactor designs, operational parameters, and scalability for practical applications are also reviewed. Photocatalytic systems have shown a lot of development but are hampered by shortcomings which include a lack of complete mineralization and production of intermediary secondary products; variability in performance due to the fluctuation in the intensity of solar light, limited UV light, and environmental conditions such as weather and the diurnal cycle. Future research involving multifunctional, environmentally benign photocatalytic techniques—e.g., doped composites or composite-based catalysts that involve adsorption, photocatalysis, and magnetic retrieval—are proposed to focus on the mechanism of utilizing light effectively and the environmental safety, which are necessary for successful operational and industrial-scale remediation. Full article

The secondary sex ratio (SSR), defined as the ratio of male to female births in a population, has long been a subject of scientific inquiry due to its potential as a health indicator. The interplay between catastrophic events and the delicate balance of male and female births presents a nuanced and compelling study area. Natural disasters, such as earthquakes, hurricanes, floods, and volcanic eruptions, have been known to disrupt ecosystems and human populations, leading to both short-term and long-term consequences. Studies have suggested a potential influence of these disasters on the SSR, with varying degrees of impact observed across different regions and disaster types. Similarly, nuclear accidents, such as the infamous Chernobyl disaster, have sparked interest in their potential effects on human health and development. The release of radioactive materials into the environment can have far-reaching consequences, including impacts on reproductive outcomes. Through a rigorous examination of the existing literature, the present review aims to synthesize current knowledge on the impacts of natural disasters and nuclear accidents on the SSR and unravel the mechanisms that explain SSR fluctuations. By shedding light on the diverse influences shaping the SSR, this narrative review contributes to a deeper appreciation of the intricate interplay between environmental, biological, and societal factors that determines the SSR, calling for targeted strategies to mitigate potential adverse effects on sex ratios in the aftermath of such events. Full article

To obtain a flat top shaped passband in a conventional thin-film-based optical bandpass filter (OBF), it needs a large number of constitutional layers of thin films, which makes the film deposition systems more complicated and accumulates errors in film growth. A flat top and polarization-independent optical bandpass filter structure is proposed based on experimentally verified polarization independency in the form of a prism-pair coupled planar optical waveguide (POW). The POW is composed of two waveguide stacks, which consists of nine planar thin-film layers. Theoretical simulations show that the flat band top spans about 5 nm with transmittance over 97.8%. The passband is designed to be centered at 632.8 nm, the He-Ne laser wavelength, and the FWHM (full width at half maximum) bandwidth is about 35 nm. Within 0.5° tuning for the incident angle of the light, the passband could be shifted within 50 nm, while its transmittance fluctuates only less than 1% and the passband shape distorts only slightly. This type of OBF is potentially applicable in various fields of optical and laser spectroscopies. Full article

The urgent demand for sustainable energy solutions in the face of climate change and resource depletion has catalyzed a global shift toward cleaner energy production and more efficient storage technologies. Lithium-ion batteries (LIBs), as the cornerstone of modern portable electronics, electric vehicles, and grid-scale storage systems, are continually evolving to meet the growing performance requirements. In this dynamic context, two-dimensional (2D) materials have emerged as highly promising candidates for use in electrodes due to their layered structure, tunable electronic properties, and high theoretical capacity. Among 2D materials, molybdenum disulfide (MoS₂) has gained increasing attention as a promising low-dimensional candidate for LIB anode applications. This review provides a comprehensive yet concise overview of recent advances in the application of MoS₂ in LIB electrodes, with particular attention to its unique electrochemical behavior at the nanoscale. We critically examine the interplay between structural features, charge-storage mechanisms, and performance metrics—chiefly the specific capacity, rate capability, and cycling stability. Furthermore, we discuss current challenges, primarily poor intrinsic conductivity and volume fluctuations, and highlight innovative strategies aimed at overcoming these limitations, such as through nanostructuring, composite formation, and surface engineering. By shedding light on the opportunities and hurdles in this rapidly progressing field, this work offers a forward-looking perspective on the role of MoS₂ in the next generation of high-performance LIBs. Full article

The worldwide air pollution situation reveals significant environmental challenges. In addition to being a major contributor to the deterioration of air quality, particulate matter (PM) is also an important factor affecting the performance of solar energy systems given its ability to decrease light transmission to solar panels. As part of our research, the present investigation involves monitoring concentrations of PM using a high-performance optical instrument, the in situ calibration protocol of which is described in detail. For the city of Rabat, observations revealed significant variations in concentrations between day and night, with peaks observed around 8 p.m. correlating with high relative humidity and low wind speeds, and the highest levels recorded in February with a monthly average value reaching 75 µm/m³. In addition, an experimental protocol was set up for an analysis of the elemental composition of particles in the same city using SEM/EDS, providing a better understanding of their morphology. To assess the impact of meteorological variables on PM concentrations in two distinct climatic environments, a database from the city of Marrakech for the year 2024 was utilized. Overall, the distribution of PM values during this period did not fluctuate significantly, with a monthly average value not exceeding 45 µm/m³. The random forest method identified the most influential variables on these concentrations, highlighting the strong influence of the type of environment. The findings provide crucial information for the modeling of solar installations’ soiling and for improving understanding of local air quality. Full article

The present research is related to the application of artificial intelligence (AI) approaches for classifying surface textures, specifically regular reliefs patterns formed by ball burnishing operations. A two-stage methodology is employed, starting with the creation of regular reliefs (RRs) on test parts by ball burnishing, followed by 3D topography scanning with Alicona device and data preprocessing with Gwyddion, and Blender software, where the acquired 3D topographies are converted into a set of 2D images, using various virtual camera movements and lighting to simulate the symmetrical fluctuations around the tool-path of the real camera. Four pre-trained convolutional neural networks (DenseNet121, EfficientNetB0, MobileNetV2, and VGG16) are used as a base for transfer learning and tested for their generalization performance on different combinations of synthetic and real image datasets. The models were evaluated by using confusion matrices and four additional metrics. The results show that the pretrained VGG16 model generalizes the best regular reliefs textures (96%), in comparison with the other models, if it is subjected to transfer learning via feature extraction, using mixed dataset, which consist of 34,037 images in following proportions: non-textured synthetic (87%), textured synthetic (8%), and real captured (5%) images of such a regular relief. Full article

Rana dybowskii, widely distributed and extensively farmed in northeast China, holds significant economic value, particularly for its fallopian tubes, which are used as a traditional Chinese medicinal tonic known as “Oviductus Ranae.” As the light spectrum is a cost-effective regulatory factor in aquaculture, understanding its effects on the tadpole stage of R. dybowskii is critical for optimizing cultivation practices. This study investigated the effects of five light colors (white, red, yellow, blue, and green) on steroid hormone levels and gut microbiota composition in R. dybowskii tadpoles. Steroid hormone levels were measured on days 15, 30, 45, and 60 using high-performance liquid chromatography (HPLC), while gut microbial communities were analyzed through high-throughput 16S rRNA sequencing. Results showed that the testosterone (T) level of frogs in green light (group G) peaked on day 60 (2.62 ± 3.70 ng/g). The estradiol (E2) level in blue light (group B) also peaked on day 60 (2.87 ± 0.71 ng/g). Importantly, sex ratio analysis revealed that the proportion of females was highest under blue light, reaching 61.11%. Meanwhile, the richness and diversity of the gut bacterial community of the tadpoles was highest under yellow light, followed by blue light. These data suggest that hormone levels fluctuated and the composition of the gut flora of R. dybowskii changed under different light colors. Our results advance R. dybowskii physiological knowledge and support aquaculture practices. Full article

The air quality in the Beijing–Tianjin–Hebei region of China has markedly improved in recent decades. Characterizing current PM_2.5 transmission between cities in light of the continuous reduction in emissions from various sources is of great significance for the formulation of future regional joint prevention and control strategies. To address these issues, a WRF-CAMx modeling project was implemented to explore the pollution characteristics from the perspectives of transport flux, regional source apportionment, and the comprehensive impact of multiple pollutants from 2013 to 2020. It was found that the net PM_2.5 transport flux among cities declined considerably during the study period and was positively affected by the continuous reduction in emission sources. The variations in local emissions and transport contributions in various cities from 2013 to 2020 revealed differences in emission control policies and efforts. It is worth noting that under polluted weather conditions, obvious interannual differences in PM_2.5 transport fluxes in the BTH region were observed, emphasizing the need for more scientifically based regional collaborative control strategies. The change in the predominant precursor from SO₂ to NOx has posed new challenges for emission reduction. NOx emission reductions will significantly decrease PM_2.5 concentrations, while SO₂ and NH₃ reductions show limited effects. The reduction in NOx emissions might have a fluctuating impact on the generation of SOAs, possibly due to changes in atmospheric oxidation. However, the deep treatment of NOx has a positive effect on the synergistic improvement of multiple air pollutants. This emphasizes the need to enhance the reduction in NOx emissions in the future. The results of this study can serve as a reference for the development of effective PM_2.5 precursor control strategies and regional differentiation optimization improvement policies in the BTH region. Full article