Search Results (1,275)

Time- and space-resolved radiation emitted by the plasma produced by a 0.8 ns duration at full width half maximum, ~600 MW maximum power microwave (~9.6 GHz) pulse traversing a hydrogen-, helium-, or air-filled circular waveguide, is studied. Gas ionization by microwaves is an old subject but the regime investigated in the present experimental research, of very high-power microwaves and very short pulses using modern diagnostic tools, is new and follows a series of new studies performed so far only in our laboratory, revealing non-linear phenomena never observed before. In the present research, plasma radiation is observed along a slit made in a circular waveguide wall by either an intensified fast frame camera or a streak camera. Using calibrated input and output couplers, the transmission and reflection coefficients of the high-power microwaves were determined over a broad range of gas pressures, 0.1 kPa < P < 90 kPa. It was found that the intensity of the plasma light emission increases significantly after the high-power microwave pulse has left the waveguide. Depending on pressure, the radiation is either uniform along the slit, while the front of the emitted light follows the microwave pulse at a velocity close to its group velocity, or it remains in the vicinity of the input window, indicating that the plasma density is above critical density. It was also found that the radial distribution of radiation depends on pressure. At pressures <10 kPa, when the electron oscillatory energy reaches 20 keV close to the waveguide axis, light emission forms faster near the waveguide walls, where the ionization rate is maximal. Otherwise, when pressure is >80 kPa, light emission is most intense on the axis where the electron oscillatory energy is ~100 eV and the ionization rate is maximal. We also studied the UV radiation from the plasma, the duration of which was found to be longer than the duration of visible light emission. This indicates the existence of energetic electrons for tens of ns after the high-power microwave pulse has left the observation region. Considering that the emitted light intensity depends on the plasma density and temperature, the observed data may be used for a comparison with the results of collisional radiative models if the electron time and spatial energy distribution is known. Full article

Printed circuit heat exchangers (PCHE) are ideal for use in very demanding operating conditions. In addition, they are characterized by very high efficiency, which can still be increased. This paper presents new concepts for improving PCHE heat exchangers. The aim of the described work was to evaluate the potential for improving the performance of printed circuit heat exchangers by incorporating open-cell metal foam as the heat exchanger packing material. The evaluation was conducted based on the results of numerical simulation of supercritical carbon dioxide cooling flowing through printed circuit heat exchanger channels filled with 40 PPI copper foam with 90% porosity. A unit periodic region of the heat exchanger comprising two adjacent straight channels for cold and hot fluid was analyzed. The channels had a semicircular cross-section and a length of 200 mm. Studies were conducted for three different channel diameters—2, 3, and 4 mm. The range of mass flux variations for cold fluid (water) and hot fluid (sCO₂) were 300–1500 kg/(m²·s) and 200–800 kg/(m²·s), respectively. It was found that in channels filled with metal foam, carbon dioxide cooling is characterized by a higher heat transfer coefficient than in channels without metal foam. In channels of the same diameter, heat flux was 33–63% higher in favor of the channel with metal foam. Thermal effectiveness of the heat exchanger with metal foam can be up to 20% higher than in the case of a heat exchanger without foam. Despite very high pressure drop through channels filled with metal foam, thermal–hydraulic performance can also be higher—even 4.7 in the case of a 2 mm channel. However, both these parameters depend on flow conditions and channel diameter, and under certain conditions may be lower than in a heat exchanger without metal foam. The results of the presented work indicate a new direction for the development of PCHE heat exchangers and confirm that the use of metal foams in the construction of PCHE heat exchangers can contribute to increasing the efficiency and effectiveness of the processes in which they are used. Full article

Rocks and soil excavated at construction sites can contain naturally occurring toxic substances. One low-cost means of managing the environmental burden posed by leaching of these substances is the attenuation layer method, which uses an adsorbent positioned between the fill and ground. Evaluation of adsorbent performance based on sorption tests is important for designing and optimizing attenuation layer methods; however, few studies have examined the effect of coexisting ions on sorption performance. Here, we examined the effects of these ions contained in soil extract solutions on the fluoride sorption performance of a commercial layered double-hydroxide (LDH)–based adsorbent used in the attenuation layer method. Batch and column sorption tests showed that the distribution coefficients in the presence of coexisting ions were 29%–72% lower than those in tests conducted without coexisting ions. Furthermore, the results of a solid-state analysis and various ion analyses suggest that competition for the sorption sites of LDH by sulfate ions in the soil extract solution was the cause of the reduced sorption performance. These findings imply that reliance only on deionized water-based sorption tests may overestimate the real-world sorption performance of LDH-based adsorbents. Full article

Highly efficient shielding materials, transparent in the visible and IR ranges are becoming important in practice. This stimulates the development of cheap methods for creating transparent conductors with low sheet resistance and high optical transparency. This work presents a complex approach based on preliminary modeling of the shielding characteristics of two-layer sandwich structures based on irregular aluminum mesh (IAM) formed by the cracked template method. Experimentally measured spectral dependences of the transmission coefficient of single-layer IAM are used as a reference point for modeling. According to the simulation results, two types of sandwich structures were designed using IAM, with varying filling factors and a fixed PMMA layer thickness of 4 mm. The experimentally measured shielding characteristics of the sandwich structures in the range of 0.01–7 GHz are in good agreement with the calculated data. The obtained structures demonstrate a shielding efficiency of 55.96 dB and 65.55 dB at a frequency of 3.5 GHz (the average range of 5G communications). At the same time, their optical transparency at a wavelength of 550 nm are 84.07% and 75.78%, respectively. Our sandwich structures show electromagnetic shielding performance and uniform diffraction pattern. It gives them an advantage over structures based on regular meshes. The obtained results highlight the prospect of the proposed comprehensive approach for obtaining highly efficient, low-cost optically transparent shielding structures. Such materials are needed for modern wireless communication systems and metrology applications. Full article

Cemented filling technology is an effective approach to solving tailings accumulation and goaf, with rheological properties serving as key indicators of slurry fluidity. Since slurry rheology is influenced by multiple factors, accurate prediction of its parameters is essential for optimizing filling design. In this study, we developed a model to predict static and dynamic yield stress using the extreme gradient boosting (XGBoost) algorithm, trained on 140 experimental samples (105 for training and 35 for validation, split 75:25). For comparison, adaptive boosting tree (ADBT), gradient boosting decision tree (GBDT), and random forest (RF) algorithms were also applied. Model performance was evaluated using four metrics: coefficient of determination (R²), mean absolute error (MAE), root mean square error (RMSE), and explained variance score (EVS). The Shapley additive explanation (SHAP) method was employed to interpret model outputs. The results show that XGBoost achieved superior predictive accuracy for slurry yield stress compared with other models. Analysis of importance revealed that underflow concentration had the strongest influence on predictions, followed by the binder-to-tailings ratio, while the fine-to-coarse tailings ratio contributed least. These findings highlight the potential of machine learning as a powerful tool for modeling the rheological parameters of filling slurry, offering valuable guidance for engineering applications. Full article

To avoid cumbersome casting procedures in the production of pervious concrete, a new type of casting method through coating cementitious paste onto the preplaced aggregate skeleton is developed. To optimize the key performances and reveal their governing mechanism, aggregate skeleton–cementitious paste-coating pervious concrete (ACPC) mixes with different porosity, water/cement (w/c) ratio and sand ratio were produced and had their permeability and strength tested. This study demonstrated that it is successful to produce pervious concrete by the novel casting method. Vibration of aggregate skeleton and high w/c ratio should not be adopted to avoid the formation of a layer of hardened paste at the bottom of the mix to block the vertical passage of water. In contrast to conventional concrete, a higher w/c ratio (from 0.23 to 0.34) generally resulted in a higher strength (from 3.77 to 8.71 MPa) of ACPC. A small amount of sand increased both the permeability and strength through the balling bearing effect and filling effect, respectively. Both the optimum sand ratio to achieve the highest vertical permeability and strength were found to be 0.05, which offered this porous structure concurrently satisfactory permeability (permeability coefficient higher than grade K2) and acceptable strength (compressive strength higher than 5 MPa). Key influencing factors of permeability and strength of ACPC were analyzed. This study can advance the technology of casting concrete and the production of pervious concrete as road pavement in the construction of “sponge city”. Full article

Background/Objectives: This meta-analytical review assesses the relationship between effect size and replication success in genetic studies of athletic performance, focusing on the ACTN3 and ACE polymorphisms across power- and endurance-based sports. The analysis revealed substantial heterogeneity in reported effect sizes (overall I² = 72.3%), indicating considerable variability between studies, likely influenced by differences in population genetics, study design, and sample size. Methods: For ACTN3, the pooled effect sizes were 1.40 (95% CI: 1.18–1.65) for power sports and 1.35 (95% CI: 1.12–1.58) for endurance sports. Although the difference between these estimates is small, it reached statistical significance (p = 0.0237), reflecting the large sample size, but it remains of limited practical and clinical significance. For the ACE polymorphism, effect sizes were similar in both endurance (ES = 1.22, 95% CI: 1.05–1.41) and power sports (ES = 1.20, 95% CI: 1.03–1.43), with overlapping confidence intervals, indicating no meaningful difference in association strength between sport types. Effect sizes were calculated as odds ratios (OR) with 95% confidence intervals for case–control designs, with standardized conversion protocols applied for alternative study designs reporting standardized mean differences or regression coefficients. Results: Publication bias was detected, particularly in smaller studies on ACTN3 and power sports (Egger’s test p = 0.007). The pooled effect of ACTN3 in power sports (OR 1.40, 95% CI: 1.18–1.65, 95% PI: 0.89–2.20) was adjusted to OR 1.32 (95% CI: 1.15–1.51) following trim-and-fill publication bias correction. The high degree of heterogeneity (I² = 72.3%) cautions against overgeneralization of the pooled results and highlights the need for careful interpretation, robust replication studies, and standardized methodologies. Conclusions: The findings emphasize that, while genetic markers such as ACTN3 and ACE are statistically associated with athletic performance, the magnitude of these associations is modest and should be interpreted conservatively. Methodological differences and publication bias continue to limit the reliability of the evidence. Future research should prioritize large, well-powered, and methodologically consistent studies—ideally genome-wide approaches—to better account for the polygenic and multifactorial nature of elite athletic ability. Full article

Background and Objectives: Urinary incontinence (UI) is a prevalent issue among older adults and may require urodynamic studies (UDSs) for accurate diagnosis. However, these procedures can be uncomfortable and time-consuming, especially in a geriatric population, where certain practical restrictions may apply. This study examines whether posture of filling cystometry during UDSs in an older patient group affects diagnostic outcomes and whether a single UDS in one posture is sufficient for a reliable diagnosis or if multiple postures provide added value. Materials and Methods: This is a secondary analysis of the Think Dry: Optimalisation of Diagnostic Process of Urinary Incontinence in Older People study (NCT04094753), a prospective observational cohort study. Each patient underwent both sitting and standing filling cystometry during UDS. The final diagnosis was determined by the referring urologist by integrating results from both the sitting and standing groups alongside all available clinical data. Subsequently, each separate UDS was reviewed independently by a second, blinded, urologist, and a diagnosis was established based on a single UDS. The agreement between these independent diagnoses and the final diagnosis was then evaluated using Cohen’s kappa coefficient (κ). Results: Results from the UDS with the standing filling cystometry had an almost perfect agreement (κ = 0.92) with the final diagnosis, compared to only a moderate agreement (κ = 0.42) while sitting. Conclusions: UDS with standing filling cystometry may be sufficient for an accurate diagnosis, potentially eliminating the need for additional filling cystometry in the sitting position. By streamlining the diagnostic process, this approach could enhance efficiency, reduce patient burden, and optimize resource utilization in older adults. Full article

Linpan ecosystems, distinct to western Sichuan, China, are integral to regional biodiversity and carbon cycling. However, comprehensive biomass estimation for these systems has not been thoroughly investigated. This study seeks to fill this gap by enhancing the accuracy and precision of biomass estimation in these ecologically vital landscapes through the application of multi-source remote sensing techniques, specifically by integrating the strengths of optical and radar remote sensing data. The focus of this research is on the forest biomass of Linpan, encompassing the tree layer, which includes the trunk, branches, leaves, and underground roots. Specifically, the research focused on the Linpan ecosystems in the Wenjiang District of western Sichuan, utilizing an integration of Sentinel-1 SAR, Sentinel-2 multispectral, and GF-2 high-resolution data for multi-source remote sensing-based biomass estimation. Through the preprocessing of these data, Pearson correlation analysis was conducted to identify variables significantly correlated with the forest biomass as determined by field surveys. Ultimately, 19 key modeling factors were selected, including band information, vegetation indices, texture features, and phenological characteristics. Subsequently, three algorithms—multiple stepwise regression (MSR), support vector machine (SVM), and random forest (RF)—were employed to model biomass across mixed-type, deciduous broadleaved, evergreen broadleaved, and bamboo Linpan. The key findings include the following: (1) Sentinel-2 spectral data and Sentinel-1 VH backscatter coefficients during the summer, combined with vegetation indices and texture features, were critical predictors, while phenological indices exhibited unique correlations with biomass. (2) Biomass displayed a marked north–south gradient, characterized by higher values in the south and lower values in the north, with a mean value of 161.97 t ha⁻¹, driven by dominant tree species distribution and management intensity. (3) The RF model demonstrated optimal performance in mixed-type Linpan (R² = 0.768), whereas the SVM was more suitable for bamboo Linpan (R² = 0.892). The research suggests that integrating multi-source remote sensing data significantly enhances Linpan biomass estimation accuracy, offering a robust framework to improve estimation precision. Full article

Solar greenhouses are an important component of modern facility agriculture, and the dynamic changes in their internal environment directly affect crop growth and yield. Among these factors, crop transpiration releases water vapor through transpiration, directly altering the indoor humidity balance and forming a dynamic coupling with factors such as temperature and light. The environment of solar greenhouses exhibits highly nonlinear and multivariate coupling characteristics, leading to insufficient prediction accuracy in existing models. However, accurate predictions are crucial for regulating crop growth and yield. However, current mainstream greenhouse environmental prediction models still have obvious limitations when dealing with such complexity: traditional machine learning models and single-variable-driven models have issues such as insufficient accuracy (average MAE is 15–20% higher than in this study) and weak adaptability to nonlinear environmental changes in multi-environmental factor coupling predictions, making it difficult to meet the needs of precision farming. A review of relevant research over the past five years shows that while LSTM-based models perform well in time series prediction, they ignore the spatial correlations between environmental factors. Models incorporating attention mechanisms can capture key variables but suffer from high computational costs. To address these issues, this study proposes a prediction model based on multi-strategy optimization and gradient-boosting (GBDT) algorithms. By introducing a multi-scale feature fusion module, it addresses the accuracy issues in multi-factor coupling prediction. Additionally, it employs a lightweight network design to balance prediction performance and computational efficiency, filling the gap in existing research applications under complex greenhouse environments. The model optimizes data preprocessing and model parameters through Sobol sequence initialization, adaptive t-distribution perturbation strategies, and Gaussian–Cauchy mixture mutation strategies and combines CatBoost for modeling to enhance prediction accuracy. Experimental results show that the MSCSO–CatBoost model performs excellently in temperature prediction, with the mean absolute error (MAE) and root mean square error (RMSE) reduced by 22.5% (2.34 °C) and 24.4% (3.12 °C), respectively, and the coefficient of determination (R²) improved to 0.91, significantly outperforming traditional regression methods and combinations of other optimization algorithms. Additionally, the model demonstrates good generalization capability in predicting multiple environmental variables such as temperature, humidity, and light intensity, adapting to environmental fluctuations under different climatic conditions. This study confirms that combining multi-strategy optimization with gradient-boosting algorithms can significantly improve the prediction accuracy of solar greenhouse environments, providing reliable support for precision agricultural management. Future research could further explore the model’s adaptive optimization in complex climatic regions. Full article

Uncooled microbolometers play a pivotal role in infrared detection owing to their compactness, low power consumption, and cost-effectiveness. This review comprehensively summarizes recent progress in thermistor materials and focal plane arrays (FPAs), highlighting improvements in sensitivity and integration. Vanadium oxide (VO_x) remains predominant, with Al-doped films via atomic layer deposition (ALD) achieving a temperature coefficient of resistance (TCR) of −4.2%/K and significant 1/f noise reduction when combined with single-walled carbon nanotubes (SWCNTs). Silicon-based materials, such as phosphorus-doped hydrogenated amorphous silicon (α-Si:H), exhibit a TCR exceeding −5%/K, while titanium oxide (TiO_x) attains TCR values up to −7.2%/K through ALD and annealing. Emerging materials including GeSn alloys and semiconducting SWCNT networks show promise, with SWCNTs achieving a TCR of −6.5%/K and noise equivalent power (NEP) as low as 1.2 mW/√Hz. Advances in FPA technology feature pixel pitches reduced to 6 μm enabled by vertical nanotube thermal isolation, alongside the 3D heterogeneous integration of single-crystalline Si-based materials with readout circuits, yielding improved fill factors and responsivity. State-of-the-art VO_x-based FPAs demonstrate noise equivalent temperature differences (NETD) below 30 mK and specific detectivity (D*) near 2 × 10¹⁰ cm⋅Hz ^1/2/W. Future advancements will leverage materials-driven innovation (e.g., GeSn/SWCNT composites) and process optimization (e.g., plasma-enhanced ALD) to enable ultra-high-resolution imaging in both civil and military applications. This review underscores the central role of material innovation and system optimization in propelling microbolometer technology toward ultra-high resolution, high sensitivity, high reliability, and broad applicability. Full article

The APSIM (Agricultural Production Systems Simulator)-Wheat model has been widely used to simulate wheat growth, but the sensitivity characteristics of the model parameters at different soil moisture levels in arid regions are unknown. Based on 2023~2025 winter wheat field data from the Changji Experimental Site, Xinjiang, China, this study conducted a global sensitivity analysis of the APSIM-Wheat model using Morris and EFAST methods. Twenty-one selected parameters were perturbed at ±50% of their baseline values to quantify the sensitivity of the aboveground total dry matter (WAGT) and yield to parameter variations. Parameters exhibiting significant effects on yield were identified. The calibrated APSIM model performance was evaluated against field observations. The results indicated that the order of influential parameters varied slightly across different soil moisture levels. However, the WAGT output was notably sensitive to accumulated temperature from seedling to jointing stage (T1), accumulated temperature from the jointing to the flowering period (T2), accumulated temperature from grain filling to maturity (T4), and crop water demand (E1). Meanwhile, yield output showed greater sensitivity to number of grains per stem (G1), accumulated temperature from flowering to grain filling (T3), potential daily grain filling rate during the grain filling period (P1), extinction coefficient (K), T1, T2, T4, and E1. The sensitivity indices of different soil moisture levels under Morris and EFAST methods showed highly significant consistency. After optimization, the coefficient of determination (R²) was 0.877~0.974, the index of agreement (d-index) was 0.941~0.995, the root mean square error (RMSE) was 319.45~642.69 kg·ha^–1, the mean absolute error (MAE) was 314.69~473.21 kg·ha^–1, the residual standard deviation ratio (RSR) was 0.68~0.93, and the Nash–Sutcliffe efficiency (NSE) was 0.26~0.57, thereby enhancing the performance of the model. This study highlights the need for more careful calibration of these influential parameters to reduce the uncertainty associated with the model. Full article

The application of precast assembled pier systems in high-seismicity regions is often constrained by their seismic performance limitations. To validate the optimization effect of GFRP confinement on the hysteretic performance of bridge piers, this study first conducted axial compression tests on 54 glass fiber-reinforced polymer (GFRP)-confined concrete cylindrical specimens. The investigation focused on the effects of fiber layers (6 and 10), orientation angles ($\pm 45°$, $\pm 60°$, $\pm 80°$), slenderness ratios (2 and 4), and compression section configurations (fully loaded vs. core concrete loading only) on confinement efficacy. The experimental results demonstrate that specimens with $\pm 60°$ fiber angles achieved an optimal balance between strength and ductility, exhibiting an average strength enhancement of 298.0% and a maximum axial strain of 2.7% compared to unconfined concrete. Subsequently, two GFRP tube-confined concrete bridge piers with varying fiber layers (PRCG1: 6 layers; PRCG2: 10 layers) and one unconfined reference pier (PRC) were designed and fabricated. All specimens employed grout-filled sleeves to connect caps and piers. Pseudo-static tests revealed that GFRP confinement effectively mitigated damage in plastic hinge zones and enhanced seismic performance. Compared to the PRC, PRCG1 and PRCG2 exhibited increases in ultimate displacement by 19.50% and 28.57%, in ductility coefficients by 18.56% and 27.84%, and in cumulative hysteretic energy dissipation by 13.90% and 26.43%, respectively. At the 5% drift ratio, their load capacities increased by 26.74% and 23.25%, stiffnesses improved by 28.91% and 25.51%, and residual displacements decreased by 20.89% and 11.17%. The accuracy and applicability of the GFRP tube-confined bridge pier model, developed based on the Lam–Teng model, were validated through numerical simulations using the OpenSees fiber element approach. Full article

Accurate determination of the liquid crystal (LC) cell gap after filling is essential for ensuring device performance in LC-based optical applications. However, the introduction of birefringent materials significantly distorts the transmission spectrum, complicating traditional optical analysis. In this work, we propose a lightweight machine learning framework using a shallow multilayer perceptron (MLP) to estimate the cell gap directly from the transmission spectrum of filled LC cells. The model was trained on experimentally acquired spectra with peak-to-peak interferometry-derived ground truth values. We systematically evaluated different optimization algorithms, activation functions, and hidden neuron configurations to identify an optimal model setting that balances prediction accuracy and computational simplicity. The best-performing model, using exponential activation with eight hidden units and BFGS optimization, achieved a correlation coefficient near 1 and an RMSE below 0.1 μm across multiple random seeds and training–test splits. The model was successfully deployed on a Raspberry Pi 4, demonstrating real-time inference with low latency, memory usage, and power consumption. These results validate the feasibility of portable, edge-based LC inspection systems for in situ diagnostics and quality control. Full article

The mismatch of the coefficient of thermal expansion (CTE) between the reinforcement and the matrix leads to thermal residual stresses and defects upon cooling from the processing temperature to room temperature. The residual stresses and defects have a significant impact on the mechanical properties of metal-matrix composites. To investigate the effect of cooling temperature on the residual stresses’ distribution and mechanical properties of SiC/Al, we investigated the cooling process of SiC/Al from different initial temperatures to room temperature. We found that residual stresses mainly distributed in the interface of SiC/Al composites after cooling, and the higher the initial temperature of cooling, the higher the value of residual stresses and the greater the degree of atomic displacement. During the cooling process, the Shockley partials and stair-rod dislocations were the two dominant dislocation structures. After cooling, the length of Shockley partials was about 80% and the length of stair-rod dislocations was about 18%. The mechanical properties of SiC/Al composites reduced after cooling. These results have filled the gap in understanding the mechanism of defect evolution in SiC/Al composites under cooling conditions, as well as the influence of cooling conditions on the mechanical properties of the material. Full article