Search Results (34,848)

Understanding the carbon emission efficiency of apple production (APCEE) is critical for promoting green and low-carbon agricultural development. However, the spatiotemporal dynamics and driving factors of APCEE in China remain inadequately explored. This study employs life cycle assessment, super-efficiency slacks-based measures, and a panel Tobit model to evaluate the carbon footprint, APCEE, and its determinants in China’s two major production regions from 2003 to 2022. The results reveal that: (1) Producing one ton of apples in China results in 0.842 t CO₂e emissions. Land carbon intensity and total carbon emissions peaked in 2010 (28.69 t CO₂e/ha) and 2014 (6.52 × 10⁷ t CO₂e), respectively, exhibiting inverted U-shaped trends. Carbon emissions from various production areas show significant differences, with higher pressure on carbon emission reduction in the Loess Plateau region, especially in Gansu Province. (2) The APCEE in China exhibits a W-shaped trend (mean: 0.645), with overall low efficiency loss. The Bohai Bay region outperforms the Loess Plateau and national averages. (3) The structure of the apple industry, degree of agricultural mechanization, and green innovation positively influence APCEE, while the structure of apple cultivation, education level, and agricultural subsidies negatively impact it. Notably, green innovation and agricultural subsidies display lagged effects. Moreover, the drivers of APCEE differ significantly between the two major production regions. These findings provide actionable pathways for the green and low-carbon transformation of China’s apple industry, emphasizing the importance of spatially tailored green policies and technology-driven decarbonization strategies. Full article

This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (R_ds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and R_ds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article

 Heat stress transcription factor (Hsf) families play important roles in abiotic stress responses. However, previous studies reported that HsfBs genes may play diverse roles in response to heat stress. Here, we conducted functional analysis on a woodland strawberry Class B Hsf gene, FvHsfB1a, to improve thermotolerance. The structure of FvHsfB1a contains a typical Hsf domain for DNA binding at the N-terminus, and FvHsfB1a belongs to the B1 family of Hsfs. The FvHsfB1a protein was localized in the nucleus. The FvHsfB1a gene was expressed in various strawberry tissues and highly induced by heat treatment. Under heat stress conditions, ectopic expression of FvHsfB1a in Arabidopsis improves thermotolerance, with higher germination and survival rates, a longer primary root length, higher proline and chlorophyll contents, lower malonaldehyde (MDA) and O²⁻ contents, better enzyme activities, and greater expression of heat-responsive and stress-related genes compared to WT. FvWRKY75 activates the promoter of the FvHsfB1a gene through recognizing the W-box element. Similarly, FvWRKY75-OE lines also displayed a heat-tolerant phenotype, exhibiting more proline and chlorophyll contents, lower MDA and O²⁻ contents, and higher enzyme activities under heat stress. Taken together, our study indicates that FvHsfB1a is a positive regulator of heat stress.  Full article

Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R² = 0.86; Q²_LOO = 0.86) built from 52 steroidal structures, we identified molecular features associated with high anticancer potential, specifically increased polarizability and reduced electronegativity. From a virtual library of 271 DFT-optimized analogs, 31 compounds were selected based on predicted potency (pIC₅₀ > 7.0) and screened via molecular docking against PR (PDB 2W8Y), HER2 (PDB 7JXH), and ER-α (PDB 6VJD). Seven candidates showed strong binding affinities (ΔG ≤ −9 kcal/mol for at least two targets), with Estero-255 emerging as the most promising. This compound demonstrated excellent conformational stability, a robust hydrogen-bonding network, and consistent multitarget engagement. Molecular dynamics simulations over 100 nanoseconds confirmed the structural integrity of the top ligands, with low RMSD values, compact radii of gyration, and stable binding energy profiles. Key interactions included hydrophobic contacts, π–π stacking, halogen–π interactions, and classical hydrogen bonds with conserved residues across all three targets. These findings highlight Estero-255, alongside Estero-261 and Estero-264, as strong multitarget candidates for further development. By potentially disrupting the PI3K/AKT/mTOR signaling pathway, these compounds offer a promising strategy for overcoming resistance in hormone-driven breast cancer. Experimental validation, including cytotoxicity assays and ADME/Tox profiling, is recommended to confirm their therapeutic potential. Full article

This study aims to enhance the performance of an innovative steel slag–ceramsite foam concrete (SSCFC) to advance sustainable green building materials. An eco-friendly composite construction material was developed by integrating industrial by-product steel slag (SS) with lightweight ceramsite. Employing a three-factor, three-level orthogonal experimental design at a fixed density of 800 kg/m³, 12 mix proportions (including a control group) were investigated with the variables of water-to-cement (W/C) ratio, steel slag replacement ratio, and ceramsite replacement ratio. The governing mechanisms of the W/C ratio, steel slag replacement level, and ceramsite replacement proportion on the SSCFC’s fluidity and compressive strength (CS) were elucidated. The synergistic application of range analysis and analysis of variance (ANOVA) quantified the significance of factors on target properties, and partial least squares regression (PLSR)-based prediction models were established. The test results indicated the following significance hierarchy: steel slag replacement > W/C ratio > ceramsite replacement for fluidity. In contrast, W/C ratio > ceramsite replacement > steel slag replacement governed the compressive strength. Verification showed R² values exceeding 65% for both fluidity and CS predictions versus experimental data, confirming model reliability. Multi-criteria optimization yielded optimal compressive performance and suitable fluidity at a W/C ratio of 0.4, 10% steel slag replacement, and 25% ceramsite replacement. Full article

The evidence for photobiomodulation in reducing postoperative pain after endodontic instrumentation is classified as low or very low certainty, indicating a need for further research. Longitudinal pain assessments over 24 h are crucial, and studies should explore these pain periods. Background/Objectives: This double-blind, randomized controlled clinical trial evaluated the effect of PBM on pain following single-visit endodontic treatment of maxillary molars at 4, 8, 12, and 24 h. Primary outcomes included pain at 24 h; secondary outcomes included pain at 4, 8, and 12 h, pain during palpation/percussion, OHIP-14 analysis, and frequencies of pain. Methods: Approved by the Research Ethics Committee (5.598.290) and registered in Clinical Trials (NCT06253767), the study recruited adults (21–70 years) requiring endodontic treatment in maxillary molars. Fifty-eight molars were randomly assigned to two groups: the PBM Group (n = 29), receiving conventional endodontic treatment with PBM (100 mW, 333 mW/cm², 9 J distributed at 3 points near root apices), and the control group (n = 29), receiving conventional treatment with PBM simulation. Pain was assessed using the Visual Analog Scale. Results: Statistical analyses used chi-square and Mann–Whitney tests, with explained variance (η²). Ten participants were excluded, leaving 48 patients for analysis. No significant differences were observed in postoperative pain at 24, 4, 8, or 12 h, or in palpation/percussion or OHIP-14 scores. Pain frequencies ranged from 12.5% to 25%. Conclusions: PBM does not influence post-treatment pain in maxillary molars under these conditions. These results emphasize the importance of relying on well-designed clinical trials to guide treatment decisions, and future research should focus on personalized dosimetry adapted to the anatomical characteristics of the treated dental region to enhance the accuracy and efficacy of therapeutic protocols. Full article

Accurate melt pool geometry prediction is essential for ensuring quality and reliability in Laser Powder Bed Fusion (L-PBF). However, small experimental datasets and limited physical interpretability often restrict the effectiveness of traditional machine learning (ML) models. This study proposes a hybrid framework that integrates an explicit thermal model with ML algorithms to improve prediction under sparse data conditions. The explicit model—calibrated for variable penetration depth and absorptivity—generates synthetic melt pool data, augmenting 36 experimental samples across conduction, transition, and keyhole regimes for 316 L stainless steel. Three ML methods—Multilayer Perceptron (MLP), Random Forest, and XGBoost—are trained using fivefold cross-validation. The hybrid approach significantly improves prediction accuracy, especially in unstable transition regions (D/W ≈ 0.5–1.2), where morphological fluctuations hinder experimental sampling. The best-performing model (MLP) achieves R² > 0.98, with notable reductions in MAE and RMSE. The results highlight the benefit of incorporating physically consistent, nonlinearly distributed synthetic data to enhance generalization and robustness. This physics-augmented learning strategy not only demonstrates scientific novelty by integrating mechanistic modeling into data-driven learning, but also provides a scalable solution for intelligent process optimization, in situ monitoring, and digital twin development in metal additive manufacturing. Full article

The cosmetics industry has been seeking to develop products with renewable natural ingredients to reduce the use of or even replace synthetic substances. Biosurfactants can help meet this demand. These natural compounds are renewable, biodegradable, and non-toxic or have low toxicity, offering minimal risk to humans and the environment, which has attracted the interest of an emerging consumer market and, consequently, the cosmetics industry. The aim of the present study was to produce a biosurfactant from the yeast Starmerella bombicola ATCC 22214 cultivated in a mineral medium containing 10% soybean oil and 5% glucose. The biosurfactant reduced the surface tension of water from 72.0 ± 0.1 mN/m to 33.0 ± 0.3 mN/m after eight days of fermentation. The yield was 53.35 ± 0.39 g/L and the critical micelle concentration was 1000 mg/L. The biosurfactant proved to be a good emulsifier of oils used in cosmetic formulations, with emulsification indices ranging from 45.90 ± 1.69% to 68.50 ± 1.10%. The hydrophilic–lipophilic balance index demonstrated the wetting capacity of the biosurfactant and its tendency to form oil-in-water (O/W) emulsions, with 50.0 ± 0.20% foaming capacity. The biosurfactant did not exhibit cytotoxicity in the MTT assay or irritant potential. Additionally, an antioxidant activity of 58.25 ± 0.32% was observed at a concentration of 40 mg/mL. The compound also exhibited antimicrobial activity against various pathogenic microorganisms. The characterisation of the biosurfactant using magnetic nuclear resonance and Fourier transform infrared spectroscopy revealed that the biomolecule is a glycolipid with an anionic nature. The results demonstrate that biosurfactant produced in this work has potential as an active biotechnological ingredient for innovative, eco-friendly cosmetic formulations. Full article

To investigate the effect of liquid-phase laser ablation on the hardness of WC-Co cemented carbide, this study performed hardness testing, elemental distribution analysis, and XRD phase analysis. The influence of ablation times on the hardness, elemental distribution, and phase composition of WC-Co cemented carbide was examined, and a model describing the hardness evolution mechanism under liquid-phase laser ablation was proposed. The results demonstrated that the hardness of WC-Co cemented carbide increased with the number of ablations. After 14 ablation times, the maximum hardness reached 2800 HV, representing an increase of 51%–56% compared to the matrix hardness. As the number of ablations increased, the content of ditungsten carbide (W₂C) and tungsten carbide (WC) in the cemented carbide increased, the WC grain size decreased, the dislocation density increased, and the distribution became more uniform. The refinement of WC grains and the elevated dislocation density facilitated stronger intergranular bonding, thereby significantly enhancing the material’s hardness. This study provides theoretical guidance for improving the surface mechanical properties of WC-Co cemented carbide tools through liquid-phase laser ablation. Full article

Water scarcity and spatial variability in soil fertility are key constraints to stable grain production in the Huang-Huai-Hai Plain. However, the interaction mechanisms between regulated deficit irrigation and soil fertility influencing yield formation and water-nitrogen use efficiency in winter wheat remain unclear. In this study, a two-year field experiment (2022–2024) was conducted to investigate the effects of two irrigation regimes—regulated deficit irrigation during the heading to grain filling stage (D) and full irrigation (W)—under four soil fertility levels: F1 (N: P: K = 201.84: 97.65: 199.05 kg ha⁻¹), F2 (278.52: 135: 275.4 kg ha⁻¹), F3 (348.15: 168.75: 344.25 kg ha⁻¹), and CK (no fertilization). The results show that aboveground dry matter accumulation, total nitrogen content, pre-anthesis dry matter and nitrogen translocation, and post-anthesis accumulation significantly increased with fertility level (p < 0.05). Regulated deficit irrigation promoted the contribution of post-anthesis dry matter to grain yield under the CK and F1 treatments, but suppressed it under the F2 and F3 treatments. However, it consistently enhanced the contribution of post-anthesis nitrogen to grain yield (p < 0.05) across all fertility levels. Higher fertility levels prolonged the grain filling duration by 18.04% but reduced the mean grain filling rate by 15.05%, whereas regulated deficit irrigation shortened the grain filling duration by 3.28% and increased the mean grain filling rate by 12.83% (p < 0.05). Grain yield significantly increased with improved fertility level (p < 0.05), reaching a maximum of 9361.98 kg·ha⁻¹ under the F3 treatment. Regulated deficit irrigation increased yield under the CK and F1 treatments but reduced it under the F2 and F3 treatments. Additionally, water use efficiency exhibited a parabolic response to fertility level and was significantly enhanced by regulated deficit irrigation. Nitrogen partial factor productivity (NPFP) declined with increasing fertility level (p < 0.05); Regulated deficit irrigation improved NPFP under the F1 treatment but reduced it under the F2 and F3 treatments. The highest NPFP (41.63 kg·kg⁻¹) was achieved under the DF1 treatment, which was 54.81% higher than that under the F3 treatment. TOPSIS analysis showed that regulated deficit irrigation combined with the F1 fertility level provided the optimal balance among yield, WUE, and NPFP. Therefore, implementing regulated deficit irrigation during the heading–grain filling stage under moderate fertility (F1) is recommended as the most effective strategy for achieving high yield and efficient resource utilization in winter wheat production in this region. Full article

In response to the escalating climate crisis, reducing greenhouse gas emissions (GHG) has become a top priority for both the public and private sectors. The pavement industry plays a key role in this transition, offering innovative technologies that minimize environmental impacts without compromising performance. Among these, the incorporation of recycled tire rubber and warm-mix asphalt (WMA) additives represents a promising strategy to reduce energy consumption and resource depletion in road construction. This study conducts a comparative life cycle assessment (LCA) to evaluate the environmental performance of an asphalt pavement incorporating recycled rubber and a WMA additive—referred to as R-W asphalt—against a conventional hot-mix asphalt (HMA) pavement. The analysis follows the ISO 14040/44 standards, covering material production, transport, construction, and maintenance. Two service-life scenarios are considered: one assuming equivalent durability and another with a five-year extension for the R-W pavement. The results demonstrate environmental impact reductions of up to 57%, with average savings ranging from 32% to 52% across key impact categories such as climate change, land use, and resource use. These benefits are primarily attributed to lower production temperatures and extended maintenance intervals. The findings underscore the potential of R-W asphalt as a cleaner engineering solution aligned with circular economy principles and climate mitigation goals. Full article

The piston-type expander (PTE), as the primary output component, significantly influences the performance of an energy storage system. This paper proposes a non-cam variable valve actuation system for the PTE, supported by a mathematical model. An enhanced S-curve trajectory planning method is used to design the valve lift curve. The study investigates the effects of various valve lift design parameters on output power and efficiency at different rotational speeds, employing orthogonal design and SPSS Statistics 27 (Statistical Product and Service Solutions) simulations. A grey comprehensive evaluation method is used to identify optimal valve lift parameters for each speed. The results show that valve lift parameters influence PTE performance to varying degrees, with intake duration having the greatest effect, followed by maximum valve lift, while intake end time has the least impact. The non-cam PTE outperforms the cam-based PTE. At 800 rpm, the optimal design yields 7.12 kW and 53.5% efficiency; at 900 rpm, 8.17 kW and 50.6%; at 1000 rpm, 9.2 kW and 46.8%; and at 1100 rpm, 12.09 kW and 41.2%. At these speeds, output power increases by 18.37%, 11.42%, 11.62%, and 9.82%, while energy efficiency improves by 15.01%, 15.05%, 14.24%, and 13.86%, respectively. Full article

This study applies Computational Fluid Dynamics (CFD) and mathematical modeling to examine uterine and umbilical arterial blood flow during pregnancy, providing a more detailed understanding of hemodynamic changes across gestation. Statistical analysis of Doppler ultrasound data from a large cohort of more than 200 pregnant women (in the second and third trimesters) reveals significant increases in the umbilical arterial peak systolic velocity ($PSV$) between the 22nd and 30th weeks, while uterine artery velocities remain relatively stable, suggesting adaptations in vascular resistance during pregnancy. By combining the Navier–Stokes equations with Doppler ultrasound-derived inlet velocity profiles, we quantify several key fluid dynamics parameters, including time-averaged wall shear stress ($TAWSS$), oscillatory shear index ($OSI$), relative residence time ($RRT$), Reynolds number ($Re$), and Dean number ($De$), evaluating laminar flow stability in the uterine artery and secondary flow patterns in the umbilical artery. Since blood exhibits shear-dependent viscosity and complex rheological behavior, modeling it as a non-Newtonian fluid is essential to accurately capture pulsatile flow dynamics and wall shear stresses in these vessels. Unlike conventional imaging techniques, CFD offers enhanced visualization of blood flow characteristics such as streamlines, velocity distributions, and instantaneous particle motion, providing insights that are not easily captured by Doppler ultrasound alone. Specifically, CFD reveals secondary flow patterns in the umbilical artery, which interact with the primary flow, a phenomenon that is challenging to observe with ultrasound. These findings refine existing hemodynamic models, provide population-specific reference values for clinical assessments, and improve our understanding of the relationship between umbilical arterial flow dynamics and fetal growth restriction, with important implications for maternal and fetal health monitoring. Full article

The incorporation of phase change material (PCM) can enhance wall thermal performance and indoor thermal comfort, but practical applications still face challenges related to high costs and potential leakage issues. In this study, a novel dual-biomass-based shape-stabilized PCM (Bio-SSPCM) was proposed, wherein waste cooking fat and waste reed straw were, respectively, incorporated as the PCM substance and supporting material. The waste fat (lard) consisted of both saturated and unsaturated fatty acid glycerides, exhibiting a melting point about 21.2–41.1 °C and a melting enthalpy value of 40 J/g. Reed straw was carbonized to form a sustainable porous biochar supporting matrix, which was used for the vacuum adsorption of waste fat. The results demonstrate that the as-prepared dual-Bio-SSPCM exhibited excellent thermal performance, characterized by a latent heat capacity of 25.4 J/g. With the addition of 4 wt% of expanded graphite (EG), the thermal conductivity of the composite PCM reached 1.132 W/(m·K), which was 5.4 times higher than that of the primary lard. The thermal properties of the Bio-SSPCM were characterized using an analog T-history method. The results demonstrated that the dual-Bio-SSPCM exhibited exceptional and rapid heat storage and exothermic capabilities. The dual-Bio-SSPCM, prepared from waste cooking fat and reed straw, can be considered as environmentally friendly construction material for energy storage in line with the principles of the circular economy. Full article

Since the monotonicity of the best approximant is crucial to establish partial ordering methods, in this paper, we, respectively, characterize the best approximants in Banach function spaces and Lorentz spaces ${\Gamma }_{p,w}$, in which we especially focus on the monotonicity characterizations. We first study monotonicity characterizations of the metric projection operator onto sublattices in general Banach function spaces by the property $H_g$. The sufficient and necessary conditions for monotonicity of the metric projection onto cones and sublattices are then, respectively, established in ${\Gamma }_{p,w}$. The Lorentz spaces ${\Gamma }_{p,w}$ are also shown to be reflexive under the condition $R{B}_p$, which is the basis for the existence of the best approximant. As applications, by establishing the partial ordering methods based on the obtained monotonicity characterizations, the solvability and approximation theorems for best proximity points are deduced without imposing any contractive and compact conditions in ${\Gamma }_{p,w}$. Our results extend and improve many previous results in the field of the approximation and partial ordering theory. Full article