Search Results (4,901)

Accurate and automated identification of water bodies from satellite imagery is critical for environmental monitoring, water resource management, and disaster response. Current deep learning approaches, however, suffer from a strong dependence on manual hyperparameter tuning, which limits their automation capability and robustness in complex, multi-scale scenarios. To overcome this limitation, this study proposes a fully automated segmentation framework that synergistically integrates an enhanced U-Net model with a novel hybrid evolutionary optimization strategy. Extensive experiments on public Kaggle and Sentinel-2 datasets demonstrate the superior performance of our method, which achieves a Pixel Accuracy of 96.79% and an F1-Score of 94.75, outperforming various mainstream baseline models by over 10% in key metrics. The framework effectively addresses the class imbalance problem and enhances feature representation without human intervention. This work provides a viable and efficient path toward fully automated remote sensing image analysis, with significant potential for application in large-scale water resource monitoring, dynamic environmental assessment, and emergency disaster management. Full article

This paper presents an experimental longitudinal mode control approach for a biomimetic underwater robot. Input–output models for surge velocity and pitch angle were derived through experiments, considering the fish robot body with servo motors and control pins as a single system to solve the problem of fish robots, which are complex and nonlinear, and also contain uncertainty. Closed-loop control systems were designed using PID controllers based on these models, and their performance was verified through simulations and experiments. Surge velocity and pitch angle response models were developed for nominal surge velocities of 0.2 m/s and 0.4 m/s. The surge velocity response models exhibited high agreement rates of 75.25% and 81.23% between the identified linear models and experimental results at 0.2 m/s and 0.4 m/s, respectively. In contrast, the pitch angle response model showed lower agreement rates of 68.02% and 34.24% between the identified linear model and experimental results at 0.2 m/s and 0.4 m/s, respectively. The gain margin and phase margin of the surge controller were 28.7 dB and 116°, and 37.2 dB and 70.6°, respectively. For the pitch response model, the low-frequency gain of the transfer function was very small at −31 dB when the nominal surge velocity was 0.2 m/s; this gain increased to −8 dB when the nominal surge velocity was increased to 0.4 m/s. It was observed that the initial value responses of the pitch angle converged to 0° with some oscillations in both the simulations and experiments. Therefore, it is believed that by identifying a linear model and subsequently designing a controller based on it, the surge velocity of the fish robot can be effectively controlled while stabilizing its pitch angle. Full article

As well as having corrosion resistance and mechanical properties, medical metallic biomaterials used in metal implants must allow imaging by MRI for prognostic diagnosis. Alloys based on Ti, Fe, Co, etc., have the disadvantage that those constituent elements have higher magnetic susceptibility than the tissue surrounding the metallic implant, and this condition results in defects and distortions (“artifacts”) in MR images during MRI imaging. In consideration of this issue, MRI-compatible low-magnetic-susceptibility materials are currently being researched and developed. In this study, microstructural control of Zr-based alloys by alloy design and heat treatment was investigated. The problem with pure Zr is its low corrosion resistance due to the α-phase of its hexagonal-close-packed (HCP) structure. However, alloys that were alloyed and solution heat-treated to a β-phase (body-centered cubic (BCC) structure) showed high corrosion resistance. In particular, when Zr-15Nb-5Ti-3Cr, which has relatively high corrosion resistance, was subjected to aging heat treatment at 673 K for 1.8 ks, precipitation of fine ω-phase in the β-phase was confirmed. The metallographic structure in which the ω-phase precipitated in the β-phase provided high corrosion resistance [≧1000 mV (vs. SHE)] derived from the β-phase, as well as low magnetic susceptibility (approximately 1.2 × 10⁻⁶ cm³/g), due to the effect of the ω-phase. This study provides guidelines for microstructural control to achieve both low magnetic susceptibility and high corrosion resistance in Zr-based metallic biomaterials for medical use. Full article

We develop a new mathematical framework for describing impurity diffusion in multiphase, stochastically inhomogeneous media with internal deterministic mass sources. The main contribution of the paper is the structural preservation of the original multiphase problem while reducing it to a single integro-differential diffusion equation for the entire body. Using a Feynman diagram technique, we obtain a Dyson-type equation for the averaged concentration field; its kernel (mass operator) summarizes the cumulative effect of random phase interfaces and internal sources. This diagrammatic formulation offers clear advantages: it systematically organizes the contributions of complex interphase interactions and source terms, ensures convergence of the Neumann-series solution, and facilitates extensions to more intricate source distributions. The approach allows us to analyze the behavior of the averaged impurity concentration under various temporally or spatially distributed internal sources and provides a foundation for further refinement of transport models in complex multiphase systems. Full article

In reinforcement learning (RL), reward function design is critical to the learning efficiency and final performance of agents. However, in complex tasks such as humanoid motion tracking, traditional static weighted reward functions struggle to adapt to shifting learning priorities across training stages, and designing a suitable shaping reward is problematic. To address these challenges, this paper proposes a two-layered reward reinforcement learning framework. The framework decomposes the reward into two layers: an upper-level goal reward that measures task completion, and a lower-level optimizing reward that includes auxiliary objectives such as stability, energy consumption, and motion smoothness. The key innovation lies in the online optimization of the lower-level reward weights via an online meta-heuristic optimization algorithm. This online adaptivity enables goal-conditioned reward shaping, allowing the reward structure to evolve autonomously without requiring expert demonstrations, thereby improving learning robustness and interpretability. The framework is tested on a gymnastic motion tracking problem for the Unitree G1 humanoid robot in the Isaac Gym simulation environment. The experimental results show that, compared to a static reward baseline, the proposed framework achieves 7.58% and 10.30% improvements in upper-body and lower-body link tracking accuracy, respectively. The resulting motions also exhibit better synchronization and reduced latency. The simulation results demonstrate the effectiveness of the framework in promoting efficient exploration, accelerating convergence, and enhancing motion imitation quality. Full article

Hybrid energy systems (HESs) have garnered significant interest in recent years because they combine many energy sources to enhance efficiency and dependability. This review article thoroughly examines the most effective design approaches and tactics for improving performance in hybrid energy systems through efficient energy management. The problem encompasses multiple aspects of HES design optimization, such as identifying the most efficient component sizes, choosing the most appropriate technology, and setting up the system. Furthermore, it involves implementing an energy management system (EMS) to optimize the system’s overall efficiency. Moreover, this article examines difficulties, current progress, and potential research prospects. A hybrid system, which integrates renewable sources with backup units, provides a cost-efficient, eco-friendly, and dependable energy supply and outperforms single-source systems in satisfying diverse load requirements. An essential factor in these hybrid systems is the precise evaluation of the ideal dimensions of the components to ensure that they sufficiently meet all the load requirements while minimizing both the initial investment and ongoing operating expenses. This study extensively examines suitable methods for determining the proper sizes, as the current body of literature describes. These methods can significantly enhance renewable energy systems’ economic feasibility and practicality, promoting their wider adoption. Full article

Background/Objectives: The prison environment presents a unique context for examining the impact of addiction on physical and psychological functioning. Individuals with substance use disorders (SUDs) are overrepresented in correctional facilities and often experience greater emotional difficulties and impaired physical capacity. This study aimed to conduct a comparative analysis of psychological and functional profiles between addicted and non-addicted male inmates in a semi-open correctional facility. Methods: The study included 47 male prisoners (19 addicted, 28 non-addicted). Physical performance was assessed using the Countermovement Jump (CMJ), handgrip strength, the Functional Movement Screen (FMS), and the FitLight reaction time test. Psychological functioning was evaluated using six standardized questionnaires: problem-focused, emotion-focused, and avoidant coping strategies, depression (PHQ-9), perceived stress (PSS-10), and self-compassion (SCS). Results: No statistically significant differences (p > 0.05) were found between addicted and non-addicted inmates in physical performance parameters. Addicted individuals demonstrated slightly higher handgrip strength with lower variability, while non-addicted inmates showed slightly better lower-body power in the CMJ test. Functional movement quality and reaction speed were similar between groups. Psychological assessments also revealed no significant differences between the groups. Coping styles, depressive symptoms, perceived stress levels, and self-criticism scores were comparable in both populations. In the addicted group, deeper squats correlated with lower stress (rho = −0.46, p = 0.047), and better hurdle step performance correlated with emotion-focused coping (rho = 0.46, p = 0.048). Conclusions: Although no statistically significant differences were found between addicted and non-addicted male inmates in the assessed physical and psychological outcomes, the limited sample size and context-specific nature of this pilot study suggest that these findings should be viewed as preliminary and interpreted with caution. Nonetheless, the observed associations between physical performance and psychological variables indicate subtle interconnections between motor capacity, stress perception, and coping mechanisms that merit further investigation in larger, longitudinal studies. Full article

Plastic recycling has been a challenge worldwide due to various reasons, including limited profit margins, the demand for high-quality plastic reprocessing techniques to make products comparable to those from virgin materials, and challenges in sorting and processing. This problem became particularly urgent in the small towns in the U.S., where plastic waste was shipped overseas for treatment, but now it is not accepted in some countries. This study aims to understand the plastic value chain and find the necessary factors for a circular economy model of both environmental and economic settings. In this study, an educational plastics reprocessing workspace was developed with manufacturing processes such as shredding, filament extruding, 3D printing, and injection molding. A series of products was developed to increase the value of the recycled polymers. In addition, quality control of recycled polymers such as polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), polyethylene terephthalate (PET), and polyethylene terephthalate glycol (PETG) was examined. By collaborating with a university manufacturing lab, this work illustrates how plastics can be collected, prepared, and reprocessed, serving as a platform for student learning and community outreach. This study contributes to the body of knowledge by presenting a case-based educational model for community-level plastic recycling and reprocessing in a college town context. Full article

Temperatures reported for astronomical objects are commonly extreme, and all are ascertained indirectly, using spectroscopy. However, narrow spectral peaks record microscopic behavior (transitions), whereas temperature is a macroscopic (bulk) feature of an object. Using macroscopic theories of heat, light, and their transport, we show that temperature is best defined in terms of the radiant flux of an object (Stefan–Boltzmann law)—including that from large gas bodies—because this flux defines which objects are hotter or colder, and because relevance to mathematical order is the essential attribute of any measurable quantity. Laboratory examples further show that spectroscopic determinations of temperature require the following: (1) use of a large spectral range relevant to that temperature; (2) observation of the unique peak shape characteristic of thermal emissions; (3) accounting for reflections at surfaces; and, most importantly, (4) that conditions are optically thick, a condition fostered by large object size and high temperatures. Temperature of monatomic gas is accurately described by classical kinetic theory because molecular translations are unaffected by electron dynamics. Inelastic molecular collisions provide continuous thermal emissions under optically thick conditions attained in immense astronomical environments. We show how thermal and non-thermal spectroscopic features can be distinguished. Our findings are applied to star-forming regions, intergalactic media, lightning, the Sun’s surface and the corona. Our results resolve long-standing problems regarding heat sources. Full article

Person re-identification (re-ID) aims to retrieve images of a given individual from different camera views. Obstacles obstructing parts of a pedestrian’s body often result in incomplete identity information, impairing recognition performance. To address the occlusion problem, a method called Multi-Branch Interaction Network (MBIN) is proposed, which exploits the information interaction between different branches to effectively characterize occluded pedestrians for person re-ID. The method consists primarily of a hard branch, a soft branch, and a view branch. The hard branch enhances feature robustness via a unified horizontal partitioning strategy. The soft branch improves the high-level feature representation via multi-head attention. The view branch fuses multi-view feature maps to form a comprehensive representation via a dual-classifier fusion mechanism. Moreover, a mutual knowledge distillation strategy is employed to promote knowledge exchange among the three branches. Extensive experiments are conducted on widely used person re-ID datasets to validate the effectiveness of our method. Full article

This work is a logical continuation of the study of the chemical composition of the waters of the Lovozersky district (Kola Peninsula, Russia), where an indigenous population resides. The problem statement is caused by the discovery of rare and rare earth elements in drinking water and the high rate of illness among the residents of the Lovozersky district. The goal of this work is to assess the quality of natural waters in the village of Krasnoshchelye (Kola Peninsula, Russia) and compare it with the composition of other waters in the Kola Peninsula, taking into account sanitary standards (maximum permissible concentrations) and biologically significant concentrations. As a result, the chemical composition of surface and groundwater was studied, their quality was characterized, and the forms of element migration in the “solution–crystalline substance” system in water and the human body (using the stomach as an example) were examined. The results of studies of drinking water in the village of Krasnoshchelye indicate that the macro-(Ca, Mg, Na, K) and microelement (Co, Cu, Mn, Ni, V, Zn, Cr) composition has lower concentrations in terms of biological significance for the elemental balance of humans than the recommended levels for them. The exceptions are the elements U, Th, and Y, whose concentrations are several times higher than their lower limits of biologically significant concentrations. In the human body, within the “water–gastric juice” system, the forms of the migration of elements and newly formed phases depend not only on the acidity of the stomach but also on the amount of gastric juice, which are individual characteristics of a person and their age. It has been established that well water contains rare elements and up to 50 µg L⁻¹ of rare earth elements, and changes in their migration forms can lead to accumulation in the human body and become a cause of diseases of the nervous system and other organs. Full article

Plastic pollution represents a significant emerging environmental problem. Micro-sized particles of synthetic polymers—microplastics (MPs)—have been identified in all parts of marine ecosystems. In the marine environment, organisms are exposed to MPs, which undergo a constant process of physicochemical and biological degradation. Utilization of UV irradiation as the optimal exposure factor in the simulation of fundamental natural conditions is a widely accepted approach. This enables the study of the harmful effects of such particles when interacting with aquatic organisms. This study aimed to investigate the effect of pristine and photoaging primary polystyrene microspheres (µPS) at three concentrations on the viability and DNA integrity of the sperm of the sand dollars Scaphechinus mirabilis. The results of the investigation demonstrated that IR spectroscopy revealed structural changes in polystyrene, confirming the oxidative degradation of the polymer under UV irradiation. The study demonstrated that artificially aged µPS exhibited a more pronounced effect than pristine particles, as evidenced by reduced sperm viability and increased DNA damage. Thus, the resazurin test showed that after exposure to UV-irradiated µPS, sperm viability decreased to 83–85% at concentrations of 10 and 100 particles and to 70% at a concentration of 1000. In addition, the Comet assay showed that the particles increased the percentage of DNA in the tail from 20% to 30% in a dose-dependent manner. The findings substantiate and augment the existing body of experimental data of the toxicity of aged plastic fragments, thereby underscoring the need for further study into the toxicity of aged MPs on marine invertebrates. Full article

Flexible and wearable thermoelectric devices can convert body waste heat into electricity, showing a new direction to solve the long-lasting issue of energy supply on portable devices. However, thermoelectric fibers are prone to short circuits and failure due to sweat stains and washing practices. Therefore, it is quite necessary to solve this problem to realize the practical thermoelectric device. PDMS, with its excellent insulation and flexibility, can effectively address short-circuit issues by encapsulating the surface of thermoelectric fibers. In this work, hydrophilic nano-silica (H-SiO₂)-modified PDMS that insulates materials was prepared and coated on the surfaces of polyethyleneimine (PEI)- and hydrochloric acid (HCl)-treated dual-surface-modified thermoelectric fibers. The encapsulated fibers were then woven into spacer fabric to prepare thermoelectric textiles (TETs). After 50 water washing cycles, the fibers retained 97% of their conductivity, and the textiles continued to function normally underwater, indicating that the thermoelectric fibers are effectively protected under PDMS encapsulation. Full article

Background/Objectives: Sleep disorders, particularly insomnia, are increasingly recognized as key determinants of mental health. Disturbances in sleep architecture may exacerbate hormonal dysregulation, contributing to menstrual cycle irregularities and premenstrual syndrome (PMS). The study investigate the relationship between insomnia symptoms, menstrual problems, and PMS among nursing students. Methods: The cross-sectional study was conducted using a web-based survey (CAWI) among 72 female graduate nursing students. The questionnaire included questions about menstrual history, the presence of menstrual disorders, PMS symptoms, and lifestyle and body mass index (BMI). Insomnia was assessed using the Polish version of the Athens Insomnia Scale (AIS), taking ≥8 as the cutoff point. Logistic regression analysis with confounding variables was performed. Results: 70% of participants had PMS symptoms, 19.5% had irregular menstrual cycles, and 86.5% reported problems with menstrual bleeding. The mean AIS score was 10.1 (SD = 4.05). Women with insomnia were almost 4 times more likely to experience PMS symptoms (OR = 3.93; 95% CI 1.14–13.59), more than 7 times more likely to experience bleeding problems (OR = 7.56; 95% CI: 1.51–37.97), and each additional AIS score increased the risk of cycle irregularity by 24% (OR = 1.24, 95% CI 1.01–1.50). Conclusions: The findings indicate a significant association between insomnia symptoms, menstrual disturbances, and PMS, underscoring the complex links between sleep, reproductive, and mental health. Preventive interventions, particularly sleep hygiene education, may serve as an effective strategy to support women’s overall health and well-being. Full article

This study proposes a semi-analytic harmonic modeling method that significantly improves the accuracy and efficiency of complex magnetic field modeling by integrating numerical and analytical approaches. Compared to traditional methods such as the equivalent charge method and finite element method, this approach optimizes the distribution of surface and body charges in the magnetic dipole model and introduces a finite and variable permeability model to accommodate material non-uniformity. Through harmonic expansion and analytical optimization, the method more accurately reflects the characteristics of real magnets, providing an efficient and precise solution for complex magnetic field problems, particularly in the design of high-performance magnets such as Halbach arrays. In this study, the effectiveness of the new modeling method is verified through the combination of simulation and experiment: the magnetic field distribution of the new Halbach array is accurately simulated, and the applicability of the model in the description of complex magnetic fields is analyzed. The dynamic response ability of the optimized model is verified by modeling and simulating the variation of the permeability under actual conditions. The distribution of scalar potential energy with permeability was simulated to evaluate the adaptability of the model to the real physical field. Through the comparative analysis of simulation and experimental results, the advantages of the new method in modeling accuracy and efficiency are clearly pointed out, and the effectiveness of the semi-analytic harmonic modeling method and its wide application potential in the design of new magnetic fields are proved. In this study, a semi-analytic harmonic modeling method is proposed by combining numerical and analytical methods, which breaks through the efficiency bottleneck of traditional modeling methods, and achieves the unity of high precision and high efficiency in the magnetic field modeling of the new Halbach array, providing a new solution for the study of complex magnetic field problems. Full article