Search Results (808)

Under the scenario of global climate warming, meteorological risks affecting sunflower cultivation in Xinjiang’s 10th Division were investigated by developing a meteorological-growth coupling model. Field experiments were conducted at three representative stations (A1–A3) during 2023–2024 to assess temperature and precipitation impacts on yield and quality traits among sunflower cultivars with varying maturation periods. The main findings were: (1) Early-maturing cultivar B1 (RH3146) exhibited superior adaptation at low-temperature station A1, achieving 12% higher plant height and an 18% yield increase compared to regional averages. (2) At thermally variable station A2 (daily average temperature fluctuation ± 8 °C, precipitation CV = 25%), the late-maturing cultivar B3 showed enhanced stress resilience, achieving 35.6% grain crude fat content (15% greater than mid-maturing B2) along with 8–10% increases in seed setting rate and 100-grain weight. These improvements were potentially due to optimized photoassimilated allocation and activation of stress-responsive genes. (3) At station A3, characterized by high thermal-humidity variability (CV > 15%) during grain filling, B3 experienced a 15-day delay in maturation and a 3% reduction in ripeness. Two principal mitigation strategies are recommended: preferential selection of early-to-mid maturing cultivars in regions with thermal-humidity CV > 10%, improving yield stability by 23%, and optimization of sowing schedules based on accumulated temperature-precipitation modeling, reducing meteorological losses by 15%. These evidence-based recommendations provide critical insights for climate-resilient cultivar selection and precision agricultural management in meteorologically vulnerable agroecosystems. Full article

The non-metallic armored optoelectronic cable (NAOC) serves as a critical component in deep-sea scientific winch systems. Due to its low density and excellent corrosion resistance, it has been widely adopted in marine exploration. However, as the operational water depth increases, the NAOC is subjected to multi-layer winding on the drum, resulting in a cumulative temperature rise that can severely impair insulation performance and compromise the safety of deep-sea operations. To address this issue, this paper conducts temperature rise experiments on NAOCs using a distributed temperature sensing test rig to investigate the effects of the number of winding layers and current amplitude on their temperature rise characteristics. Based on the experimental results, an electromagnetic thermal multi-physics field coupling simulation model is established to further examine the influence of these factors on the maximum operation time of the NAOC. Finally, a multi-variable predictive model for maximum operation time is developed, incorporating current amplitude, the number of winding layers, and ambient temperature, with a fitting accuracy of 97.92%. This research provides theoretical and technical support for ensuring the safety of deep-sea scientific operations and improving the reliability of deep-sea equipment. Full article

Assessing the impact of community-based conservation programs on wildlife biodiversity remains a significant challenge. This pilot study was designed to develop and demonstrate a scalable, spatially explicit workflow using thermal infrared (TIR) imagery and unmanned aerial vehicles (UAVs) for non-invasive biodiversity monitoring. Conducted in a 2-hectare grassland area in Chitwan, Nepal, the study applied TIR-based grid sampling and multi-species occupancy models with thin-plate splines to evaluate how species detection and richness might vary between (1) morning and evening UAV flights, and (2) the Chitwan National Park and Kumroj Community Forest. While the small sample area inherently limits ecological inference, the aim was to test and demonstrate data collection and modeling protocols that could be scaled to larger landscapes with sufficient replication, and not to produce generalizable ecological findings from a small dataset. The pilot study results revealed higher species detection during morning flights, which allowed us to refine our data collection. Additionally, models accounting for spatial autocorrelation using thin plate splines suggested that community-based conservation programs effectively balanced ecosystem service extraction with biodiversity conservation, maintaining richness levels comparable to the national park. Models without splines indicated significantly higher species richness within the national park. This study demonstrates the potential for spatially explicit methods for monitoring grassland mammals using TIR UAV as indicators of anthropogenic impacts and conservation effectiveness. Further data collection over larger spatial and temporal scales is essential to capture the occupancy more generally for species with larger home ranges, as well as any effects of rainfall, flooding, and seasonal variability on biodiversity in alluvial grasslands. Full article

In this study, the optimal design of the central pipe in a middle-deep geothermal heat pump (MD-GHP) system is studied using the response surface method to improve the system’s coefficient of performance (COP) and operational reliability. Firstly, a model describing the energy transfer and conversion mechanisms of the MD-GHP system, incorporating unsteady heat transfer in the central pipe, is established and validated using field test data. Secondly, taking the inner diameter, wall thickness, and effective thermal conductivity of the central pipe as design variables, the effects of these parameters on the COP of a 2700 m deep MD-GHP system are analyzed and optimized via the response surface method. The resulting optimal parameters are as follows: an inner diameter of 88 mm, a wall thickness of 14 mm, and an effective thermal conductivity of 0.2 W/(m·K). Based on these results, a composite central pipe composed of high-density polyethylene (HDPE), silica aerogels, and glass fiber tape is designed and fabricated. The developed pipe achieves an effective thermal conductivity of 0.13 W/(m·K) and an axial tensile force of 29,000 N at 105 °C. Compared with conventional PE and vacuum-insulated pipes, the composite central pipe improves the COP by 11% and 7%, respectively. This study proposes an optimization-based design approach for central pipe configuration in MD-GHP systems and presents a new composite pipe with enhanced thermal insulation and mechanical performance. Full article

This study presents the development and characterization of electrospun nanofibers composed of polyvinyl alcohol (PVA) and natural beeswax (BW). A stable emulsion containing 9 wt% PVA and 5 wt% BW was successfully formulated and electrospun. The effects of beeswax incorporation on solution properties-viscosity, conductivity, and surface tension—were systematically evaluated. Electrospinning was performed at 30 kV and a working distance of 14.5 cm, yielding nanofibers with diameters between 125 and 425 nm. Scanning electron microscopy (SEM) revealed increased surface roughness and diameter variability in PVA/BW fibers compared to the PVA. Fourier transform infrared spectroscopy (FTIR) confirmed physical incorporation of BW without evidence of chemical bonding. Thermogravimetric and differential scanning calorimetry analyses (TGA/DSC) demonstrated altered behavior and an expanded profile of temperature transitions due to the waxy components. The solubility test of the nanofiber mat in saline indicated that BW slows dissolution and improves the structural integrity of the fibers. This study demonstrates, for the first time, the incorporation of beeswax into electrospun PVA nanofibers with improved structural and thermal properties, indicating potential for further exploration in biomedical material design. Full article

The presented research examined the impact of using biodiesel as a fuel for existing diesel engines during the transition to the broader adoption of electric vehicles powered by renewable energy or through integrated hybrid drive systems. The authors considered previous research on this topic, which is demonstrated by a literature review. This paper will utilize the findings to further explore the potential of optimizing existing engines by using biodiesel and thus propose their continued use in the transition period as one of the clean fuels. This paper outlines the standards that define fuel quality and presents a test bench equipped with an experimental engine and specialized equipment for laboratory examination, enabling the measurement of emissions and the determination of cylinder pressure. To ensure the repeatability of the experimental conditions and facilitate future comparison of the obtained results, the engine examination was conducted according to the standard ESC 13-mode test. The examination process confirmed a significant reduction in particulate matter emissions (on average 40%) but, simultaneously, an increase in nitrogen oxide emissions (on average 25%), whose level, according to data from the literature, depends on the type of raw materials used for biodiesel production. Brake thermal efficiency is higher when operating with biodiesel (on average 1.5%). Still, it was concluded that the use of biodiesel in existing diesel engines is feasible only if the engines are equipped with variable systems for automatically adjusting the compression ratio, fuel injection time, valve timing, and so on. The outcomes from the examination conducted can be further processed by applying statistical methods and represent an essential database for further research in this scientific area. Full article

Background/Objectives: Dry eye disease (DED) is a multifactorial condition with complex pathophysiology involving tear film instability, ocular surface inflammation, and nerve dysfunction. This review summarizes current evidence on the different available therapies targeting these mechanisms. Methods: A review of clinical studies evaluating treatment outcomes for therapies targeting aqueous tear deficiency, Meibomian gland dysfunction, ocular surface inflammation, and ocular pain was conducted, with an emphasis on randomized controlled trials and meta-analyses where available. Results: Artificial tears provide symptomatic relief with limited impact on tear film stability. Punctal plugs improve tear retention but show variable efficacy across studies. Treatments targeting MGD—such as lipid-based lubricants, eyelid hygiene, thermal pulsation (LipiFlow, iLux), and intense pulsed light (IPL)—demonstrate improvements in gland function, though outcomes vary. Anti-inflammatory agents including cyclosporine, lifitegrast, and short-term corticosteroids improve ocular surface signs, with mixed symptom relief. Biologic therapies like autologous serum tears and platelet-rich plasma show promise for both signs and symptoms, but data remain inconsistent. Nerve-targeted therapies, including oral neuromodulators (gabapentin, antidepressants), botulinum toxin, and transcutaneous nerve stimulation, have shown potential for managing neuropathic ocular pain, although randomized data are limited. Overall, variability in study designs, patient populations, and outcome measures highlights the need for more rigorous research. Conclusions: Personalized, mechanism-based treatment strategies are essential for optimizing outcomes in DED. Future research should prioritize well-designed, controlled studies to clarify the role of emerging therapies and guide the individualized management of this heterogeneous condition. Full article

Sheep wool is a natural fiber from various sheep breeds, mainly used in clothing for its insulation properties. It makes up a small share of global fiber production, which is declining as synthetic fibers replace wool and meat farming becomes more profitable. Wool from slaughter sheep, often unsuitable for textiles, is treated as biodegradable waste. The aim of the study was to develop a fully biodegradable composite of natural origin from a polylactide (PLA) matrix reinforced with sheep wool and to select the optimal modifications (chemical) of sheep wool fibers to obtain modified properties, including mechanical properties. The behavior of the composites after exposure to aging conditions simulating naturally occurring stimuli causing biodegradation and thus changes in the material’s performance over its lifespan was also examined. Dynamic thermal analysis was used to describe and parameterize the obtained data and their variables, and the mechanical properties were investigated. The research culminated in a microscopic analysis along with changes in surface properties. The study demonstrated that wool-reinforced composites exhibited significantly improved resistance to UV degradation compared to pure PLA, with samples containing 15% unmodified wool showing a 54% increase in storage modulus at 0 °C after aging. Chemical modifications using nitric acid, iron compounds, and tar were successfully implemented to enhance fiber–matrix compatibility, resulting in increased glass transition temperatures and modified mechanical properties. Although wool fiber is not a good choice for modifications to increase mechanical strength, adding wool fiber does not improve mechanical properties but also does not worsen them much. Wool fibers are a good filler that accelerates degradation and are also a waste, which reduces the potential costs of producing such a biocomposite. The research established that these biocomposites maintain sufficient mechanical properties for packaging applications while offering better environmental resistance than pure polylactide, contributing to the development of circular economy solutions for agricultural waste valorization. So far, no studies have been conducted in the literature on the influence of sheep wool and its modified versions on the mechanical properties and the influence of modification on the degradation rate of PLA/sheep wool biocomposites. Full article

This paper focuses on the use of advanced optimization design strategies to improve the performance and service life of engine pistons, with emphasis on enhancing their stiffness, strength, and dynamic characteristics. As a core component of the engine, the structural design and optimization of the piston are of great significance to its efficiency and reliability. First, a three-dimensional (3D) model of the piston was constructed and imported into ANSYS Workbench for finite element modeling and high-quality meshing. Based on the empirical formula, the actual working environment temperature and heat transfer coefficient of the piston were accurately determined and used as boundary conditions for thermomechanical coupling analysis to accurately simulate the thermal and deformation state under complex working conditions. Dynamic characteristic analysis was used to obtain the displacement–frequency curve, providing key data support for predicting resonance behavior, evaluating structural strength, and optimizing the design. In the optimization stage, five geometric dimensions are selected as design variables. The deformation, mass, temperature, and the first to third natural frequencies are considered as optimization goals. The response surface model is constructed by means of the design of the experiments method, and the fitted model is evaluated in detail. The results show that the models are all significant. The adequacy of the model fitting is verified by the “Residuals vs. Run” plot, and potential data problems are identified. The “Predicted vs. Actual” plot is used to evaluate the fitting accuracy and prediction ability of the model for the experimental data, avoiding over-fitting or under-fitting problems, and guiding the optimization direction. Subsequently, the sensitivity analysis was carried out to reveal the variables that have a significant impact on the objective function, and in-depth analysis was conducted in combination with the response surface. The multi-objective genetic algorithm (MOGA), screening, and response surface methodology (RSM) were, respectively, used to comprehensively optimize the objective function. Through experiments and analysis, the optimal solution of the MOGA algorithm was selected for implementation. After optimization, the piston mass and deformation remained relatively stable, and the working temperature dropped from 312.75 °C to 308.07 °C, which is conducive to extending the component life and improving the thermal efficiency. The first to third natural frequencies increased from 1651.60 Hz to 1671.80 Hz, 1656.70 Hz to 1665.70 Hz, and 1752.90 Hz to 1776.50 Hz, respectively, significantly enhancing the dynamic stability and vibration resistance. This study integrates sensitivity analysis, response surface models, and genetic algorithms to solve multi-objective optimization problems, successfully improving piston performance. Full article

The formation and evolution of ice in the Yellow River represent complex dynamic processes. To elucidate the structural characteristics of ice crystals and their governing mechanisms in the Inner Mongolia reach, this investigation utilized high-resolution Sentinel-2 satellite imagery to systematically monitor spatiotemporal variations in open-water formations across diverse channel morphologies throughout the ice regime period. Systematic ice sampling was conducted across diverse channel morphologies of the Yellow River to quantify critical parameters, including crystalline structure characteristics, equivalent diameter distributions, density variations, and sediment content profiles. The results indicate the transformation of open water resulting from various river configurations during the freezing season exhibits distinct characteristics, which are significantly influenced by temperature variations. Ice crystal characterization exhibits that the crystalline structure predominantly manifests as two primary forms: columnar and granular ice formations, with their distribution varying systematically across different channel configurations. Ice crystal morphology exhibits heterogeneity in both form and dimensional characteristics. Columnar ice consistently exhibits larger equivalent diameters compared to granular ice formations. A progressive enhancement in the equivalent diameter of crystals is observed along the vertical axis corresponding to the thickness of the ice during the growth process. The ranges of variation in ice crystal size, ice density, and mud content within ice exhibit differences contingent upon the specific crystal structures present. Observational studies and comparative analyses of ice samples from the Inner Mongolia reach of the Yellow River reveal that channel morphology, ambient thermal conditions, and hydrodynamic parameters are the primary determinants governing the variability in ice microstructure and its associated physical characteristics. This investigation provides fundamental scientific insights and quantitative data that advance our understanding of river ice microstructural characteristics. Full article

Buildings are responsible for over one-third of global energy use and greenhouse gas emissions, with heating and cooling being major contributors. Phase change materials (PCMs) offer a promising passive solution to improve thermal regulation and reduce heating and cooling loads. This review analyses different experimental and simulation-based studies on the integration of PCMs into building structures for enhancing building energy performance. The key variables examined include melting temperature, latent heat capacity, thermal conductivity (λ), PCM positioning (interior, exterior, or embedded), thickness, and climate zone. The results show that PCMs reduce heat transfer by up to 47.6%, stabilize indoor temperatures with up to a 46% reduction in fluctuations, and decrease heating and cooling demands by as much as 31%, depending on component placement and climate. The optimal melting range for moderate climates lies between 22 °C and 28 °C. This review identifies critical trade-offs between PCM quantity, placement, and climatic suitability and provides a matrix of design recommendations for various building types. Full article

Conventional methods for transporting biological materials typically use dry ice or ice for preservation but often overlook important aspects of temperature monitoring and metrological control. These methods generally do not include temperature sensors to track the thermal conditions of the materials during transport, nor do they apply essential metrological practices such as regular sensor calibration and stability checks. This lack of precise monitoring poses significant risks to the integrity of temperature-sensitive biological materials. This study presents a statistical analysis of DS18B20 digital temperature sensors used in an experimental refrigeration system based on thermoelectric modules. The aim was to verify sensor consistency and investigate sources of measurement error. The research was motivated by a prior phase of study, which revealed significant discrepancies of approximately 3 °C between experimental temperature data and numerical simulations. To investigate a potential cause, we conducted a case study analyzing measurements from three identical temperature sensors (same model, brand, and manufacturer). Statistical analyses included ANOVA (analysis of variance) and Tukey’s test with a 95% confidence interval. Since the data did not follow a normal distribution (p-value < 0.05), non-parametric methods such as the Kruskal–Wallis and Levene’s procedures were also applied. The results showed that all sensors recorded statistically significant different temperature values (p-value < 0.05). Although experimental conditions were kept consistent, temperature differences of up to 0.37 °C were observed between sensors. This finding demonstrates an inherent inter-sensor variability that, while within manufacturer specifications, represents a source of systematic error that can contribute to larger discrepancies in complex systems, highlighting the need for individual calibration. Full article

This study advances the development of self-sensing concrete through functionalization with carbon nanotubes (CNTs) for structural health monitoring. Through experimental analyses, it relies on its dual responsiveness to mechanical and thermal stimuli. Three-point bending and thermal tests were systematically conducted on concrete samples with CNT concentrations ranging from 0 to 0.05 wt.% of cement, evaluated at 7- and 28-day curing periods. Mechanical testing demonstrated curing-dependent behavior: At 7 days, mechanical strength and electrical current response exhibited pronounced variability across CNTs loadings, with optimal balance achieved at 0.01% CNTs. At 28 days, the tests show that the mechanical properties are relatively stabilized, reaching the highest value at 0.006 wt.% CNTs and achieving the best electrical sensitivity at 0.01 wt.% CNTs. The thermal experiments revealed faster current modulation in the 7-day samples than in the 28-day counterparts, with intermediate CNT concentrations (e.g., 0.01 wt.%) showing a more sensitive response. The sensitivity was analyzed for both mechanical and thermal changes to further evaluate the feasibility of using CNT-reinforced concrete as a sensor material. Conductivity measurements on fully cured samples indicated that all samples exhibited electrical conductivities in the 10⁻⁴ S/m range, suggesting semiconductive behavior, while 0.006 wt.% CNTs yielded the highest conductivity. Higher CNT content did not further improve conductivity, likely due to agglomeration disrupting the network. These findings confirm CNT-modified concrete’s dual electromechanical and thermal responsiveness and support its potential as a multifunctional sensing material. Full article

The short-term performance of ground heat exchangers (GHEs) is crucial for the optimal design of ground-source heat pumps (GSHPs), enhancing their contribution to sustainable energy solutions. Local short-time thermal response functions, or short-time g-functions (STGFs) derived from thermal response tests (TRTs), are of great interest for predicting the heat exchange due to their fast and simple applicability. The aim of this work is to perform a sensitivity analysis to assess the impact of thermal parameter variability and TRT operating conditions on the accuracy of the average fluid temperature (T_f) predictions obtained through a local STGF. First, the uncertainties associated with the borehole thermal resistance (R_b), transmitted from the soil volumetric heat capacity (C_S) or some models dependent on GHE characteristics, such as the Zeng model, were found to have a low impact in T_f resulting in long-term deviations of ±0.2 K. Second, several TRTs were carried out on the same borehole, changing input parameters such as the volumetric flow rate and heat injection rate, in order to obtain their corresponding STGF. Validation results showed that each T_f profile consistently aligned well with experimental data when applying intermittent heat rate pulses (being the most unfavorable scenario), implying deviations of ±0.2 K, despite the variabilities in soil conductivity (λ_S), soil volumetric heat capacity (C_S), and borehole thermal resistance (R_b). Full article

This study investigates the potential of low-cost, naturally available porous materials (PoMs), gravel, marble, flint, and sandstone, as thermal management for photovoltaic (PV) panels. Experiments were conducted in a controlled environment at a solar energy laboratory, where variables such as solar irradiance, ambient temperature, air velocity, and water flow were carefully regulated. A solar simulator delivering a constant irradiance of 1250 W/m² was used to replicate solar conditions throughout each 3 h trial. The test setup involved polycrystalline PV panels (30 W rated) fitted with cooling channels filled with PoMs of varying porosities (0.35–0.48), evaluated across water flow rates ranging from 1 to 4 L/min. Experimental results showed that PoM cooling significantly outperformed both water-only and passive cooling. Among all the materials tested, sandstone with a porosity of 0.35 and a flow rate of 2.0 L/min demonstrated the highest cooling performance, reducing the panel surface temperature by 58.08% (from 87.7 °C to 36.77 °C), enhancing electrical efficiency by 57.87% (from 4.13% to 6.52%), and increasing power output by 57.81% (from 12.42 W to 19.6 W) compared to the uncooled panel. The enhanced heat transfer (HT) was attributed to improved conductive and convective interactions facilitated by lower porosity and optimal fluid velocity. Furthermore, the cooling system improved I–V characteristics by stabilizing short-circuit current and enhancing open-circuit voltage. Comparative analysis revealed material-dependent efficacy—sandstone > flint > marble > gravel—attributed to thermal conductivity gradients (sandstone: 5 W/m·K vs. gravel: 1.19 W/m·K). The configuration with 0.35 porosity and a 2.0 L/min flow rate proved to be the most effective, offering an optimal balance between thermal performance and resource usage, with an 8–10% efficiency gain over standard water cooling. This study highlights 2.0 L/min as the ideal flow rate, as higher rates lead to increased water usage without significant cooling improvements. Additionally, lower porosity (0.35) enhances convective heat transfer, contributing to improved thermal performance while maintaining energy efficiency. Full article