Search Results (15,832)

Since their discovery in 2009, perovskite solar cells (PSCs) have demonstrated rapid progress. Ambient-processed, carbon-based PSCs utilizing a pre-heating step offer a cost-effective fabrication route. Nevertheless, the role of the compact titanium dioxide (TiO₂-c) layer in ambient conditions has remained under-explored and inconsistently reported in the literature. This study then investigated the impact of TiO₂-c layer thickness, ranging from 70 nm to 155 nm, on the performance of PSCs fabricated entirely in ambient air with high relative humidity (RH > 70%). The layers were deposited via the sol-gel spin-coating method. Experimental results then revealed that the thinnest layer (70 nm) yielded the lowest average power conversion efficiency (PCE) of 2.05% due to diminished J_sc and V_oc values. The optimized TiO₂-c thickness was also identified at 95 nm, achieving an average PCE of 2.95% and a peak efficiency of 4.5%. Structural analysis via XRD confirmed the presence of both anatase and brookite phases. Notably, increasing the thickness from 70 nm to 155 nm resulted in a slight reduction in the anatase peak and a corresponding increase in the brookite peak. The superior performance at 95 nm could be attributed to a balanced crystal intensity between these two phases. Furthermore, TiO₂-c thickness was found to correlate with larger aggregate formation, better uniform shape grains, and reduced surface roughness, significantly influencing the morphology of the subsequent mesoporous TiO₂-m layer. These findings then provided critical insights into how thickness variation in the TiO₂-c layer could influence the performance of ambient-processed carbon-based PSCs. Full article

In this study, the chemical composition of highland barley (HB), microwave fluidization HB (HB-1), extrusion and puffing HB (HB-2), and ultrafine pulverization HB (HB-3) were investigated based on untargeted metabolomics. In addition, RNA-seq transcriptomics, real-time polymerase chain reaction (qRT-PCR) and Western blot (WB) analysis were used to investigate the lipid metabolism mechanism of HB-1, induced by a high fat and cholesterol diet (HFCD). The results indicated that a total of 1292 metabolites were detected and classified into 78 distinct classes in the untargeted metabolomics analysis including fatty acyls, carboxylic acids and derivatives, glycerophospholipids, organooxygen compounds, prenol lipids, and so on. HB-1, HB-2, and HB-3 all increased the levels of amino acids and their derivatives, phenols, and carboxylic acid and its derivatives compared with HB. Furthermore, RNA-seq transcriptomic results indicated that HB-1 significantly modulated key genes of Cyp2c38, Cyp2b13, and Cyp2b9 related to steroid hormone biosynthesis and CD36, Plin4, and Fabp4 related to the PPAR signaling pathway, which played key roles in lipid metabolism. Moreover, qRT-PCR and WB results indicated that HB-1 obviously enhanced ADIPOQ expression level, while it reduced SCD-1, CD36, Fabp4, and SREBP-1c expression levels, suggesting that the alleviation of lipid metabolic dysregulation by HB-1 in hyperlipidemia mice might be mediated via participating in the PPARγ pathway. This study provided essential theoretical insights for the development and utilization of HB. Full article

Zearalenone (ZEA) is an estrogenic Fusarium mycotoxin widely contaminating feed and feedstuffs, and posing significant risks to animal health. This preliminary study aimed to evaluate the toxicological effects of dietary exposure to purified ZEA at doses ranging from below to above the Chinese regulatory limit (0.15 mg/kg) in weaned female piglets. Twenty piglets were randomly assigned to five groups (four piglets per group) receiving 0, 0.075, 0.15, 0.3, or 0.6 mg/kg ZEA for 42 days. Results suggested that ZEA promoted systemic oxidative stress, evidenced by decreased serum total antioxidant capacity (T-AOC) and increased malondialdehyde (MDA) content in liver across all doses, and in jejunal mucosa at ≥ 0.15 mg/kg (p < 0.01). Growth performance declined only at 0.6 mg/kg during days 29–42 (p < 0.01), while hemoglobin (HGB) levels (p < 0.01) and ileal villus height (p < 0.05) were reduced at all doses. ZEA also caused inflammatory dysregulation, as evidenced by decreased interleukin-4 (IL-4) levels in serum, liver, and intestinal tissues across all doses (p < 0.01), and disrupted reproductive hormones even at 0.075 mg/kg, as indicated by suppressed serum luteinizing hormone (LH) levels (p < 0.01), which progressed to histopathological damage in uterine and ovarian tissues at higher doses. These preliminary findings, together with significant correlations between oxidative stress markers and multi-organ parameters, suggest that low doses of purified ZEA may induce systemic oxidative stress and subclinical multi-organ toxicity in weaned female piglets, highlighting the need to incorporate redox status into risk assessment and to explore potential antioxidant-based mitigation strategies. However, given the small sample size, these results should be interpreted with caution and warrant validation in larger samples. Full article

Type 2 diabetes mellitus (T2DM) is frequently complicated by dyslipidemia, which accelerates insulin resistance and the progression of cardiovascular and hepatic diseases. While exercise intervention is a cornerstone of T2DM management, a systems-level understanding of its underlying molecular mechanisms remains incomplete. This article summarizes current evidence to propose that exercise functions as a signaling network regulator, concurrently modulating critical lipid metabolism-related signaling pathways: cyclic adenosine monophosphate (cAMP), phosphatidylinositol 3-kinase–protein kinase B (PI3K–AKT), forkhead box O (FOXO), and mitogen-activated protein kinase (MAPK) signaling pathways. We delineate how dysregulation of these signaling pathways contributes to lipid disorders in T2DM, highlighting their tissue-specific and often bidirectional roles. Subsequently, we detail the molecular adaptations induced by various exercise modalities—from aerobic training to high-intensity intervals—that restore homeostasis of this signaling network. By integrating these findings, we present a novel framework for precision exercise—defined as the tailoring of exercise modality, intensity, and volume based on an individual’s predominant signaling pathway disturbance, assessed via circulating or tissue-specific biomarkers. This framework advocates for future exercise prescriptions to be guided by molecular profiling alongside traditional physiological indicators. This mechanistic insight not only deepens our comprehension of exercise physiology but also paves the way for more effective, personalized strategies to combat T2DM and its metabolic complications. Full article

To investigate how natural inulin (FI) influences the quality of heat-induced beef myofibrillar protein (BMP) gels, BMP gel systems were prepared with graded FI concentrations (1%, 2%, 3%, 4%, and 5%). Texture analysis (TA), low-field nuclear magnetic resonance (LF-NMR), rheological measurements, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FT-IR) were used to systematically characterise changes in gel properties, water migration and distribution, microstructure, and protein secondary structure. The results showed that the improvement in gel quality produced by inulin was concentration-dependent. FI at addition levels of 1–2% promoted the ordered intermolecular cross-linking of beef myofibrillar proteins, thereby facilitating the formation of a homogeneous and compact three-dimensional gel network, as confirmed by SEM and CLSM observations. Notably, 2% FI was identified as the optimal addition level for the BMP gel system. Compared with the control group, this treatment produced the highest relative β-sheet content (82%) among all groups, optimised the internal water distribution of the gel by reducing the proportion of free water, enhanced the water-holding capacity of the gels (p < 0.05), and preserved the elasticity-dominated solid-state characteristics of the BMP gel system (tan δ < 1), indicating that FI improved gel strength without changing its fundamental properties. These findings provide an important theoretical basis and practical technical parameters for the development of functional beef products with both desirable texture and high dietary fibre content. Full article

Porcine circovirus type 2 (PCV2) is a pathogen of major importance in swine that is characterized by ongoing genetic evolution. To provide an updated epidemiological assessment for China, our study analyzed 1051 clinical samples collected from 27 provincial-level regions between 2023 and 2024. The overall PCV2 positivity rate was 65.18%, with detection rates showing significant seasonal variation, with higher rates in spring and summer. Genotypic analysis of 379 open reading frame 2 (ORF2) sequences identified PCV2d as the dominant genotype (78.89%), and no significant geographic clustering was observed. Coinfection with porcine reproductive and respiratory syndrome virus (PRRSV) is common, yet statistical tests have revealed an epidemiologically independent relationship between the two viruses. Notably, analysis of the capsid (Cap) protein revealed that high-frequency amino acid mutations were concentrated in immunodominant loop regions. These mutations resulted in genotype-specific substitutions within key neutralizing epitopes. This study provides the latest large-scale national baseline data on PCV2 in China for 2023–2024. It systematically analyzes the epidemiological characteristics of the dominant PCV2d genotype in the post-African Swine Fever era, the patterns of antigenic epitope mutations in the Cap protein, and their potential impact on vaccine efficacy. The study fills a gap in recent national epidemiological data on PCV2 in China and provides a basis for the targeted prevention and control of PCV2 and the updating of vaccine strains. Full article

Underwater dynamic target detection, classification, localization, and tracking (DCLT) is central to maritime surveillance and monitoring and increasingly relies on distributed AUV-based robotic sonar networks operating in passive listening and, when required, cooperative multistatic modes. Achieving a robust performance in realistic oceans remains challenging, because sensor placement must adapt to time-varying acoustic conditions and target priors while preserving acoustic communication connectivity, and because frequent reconfiguration under dynamic currents makes classical large-scale planning computationally expensive. This paper presents an integrated deep reinforcement learning (DRL)-based framework for passive-stage sonar placement and dynamic reconfiguration in distributed AUV networks. First, we cast placement as a constructive finite-horizon Markov decision process (MDP) and train a Proximal Policy Optimization (PPO) agent to sequentially build a collision-free layout on a discretized surveillance grid. The terminal reward is formulated to jointly optimize the environment-aware detection performance, computed from BELLHOP-based transmission loss models, and global network connectivity, quantified using algebraic connectivity. Second, to enable time-critical reconfiguration, we estimate flow-aware motion costs for all AUV–destination pairs using a PPO with a Long Short-Term Memory (LSTM) trajectory policy trained for partial observability. The learned policy can be deployed onboard, allowing each AUV to refine its path online using locally sensed currents, improving robustness to ocean-model uncertainty. The resulting cost matrix is solved via an efficient zero-element assignment method to obtain the optimal one-to-one reassignment. In the reported simulation studies, the proposed Sequential PPO placement method achieves a final reward 16–21% higher than Particle Swarm Optimization (PSO) and 2–3.7% higher than the Genetic Algorithm (GA), while the proposed PPO + LSTM planner reduces average travel time by 30.44% compared with A*. The proposed closed-loop architecture supports frequent re-optimization, scalable fleet operation, and a seamless transition to communication-supported cooperative multistatic tracking after detection, enabling efficient, adaptive DCLT in dynamic marine environments. Full article

The Nile River has played a central role in Egypt’s historical and cultural development, shaping ancient civilizations and settlement patterns. However, its course has changed dynamically over millennia, leaving behind buried channels and geomorphological features that are critical for reconstructing past hydrological landscapes. This study utilized Sentinel-2 satellite imagery within Google Earth Engine to develop a remote sensing method for analyzing spectral and temporal variations in vegetation as indicators of paleofluvial landforms and past river activity. The approach, applied to create ten seasonal representations, enhanced the detection of moisture-driven vegetation patterns. Here, the Moisture-Gradient Enhanced Vegetation Index (MGEVI) was developed to identify stable vegetated landforms and differentiate persistent moisture conditions from seasonal variations. Through this method, former river channels, river islands, and channel belts were identified, revealing patterns of past river activities. The results suggest a late anabranching phase of the Nile, characterized by the gradual stabilization of fluvial features in response to evolving hydrological conditions. A comparison between fluvial features identified through remote sensing and those mapped from TanDEM-X radar elevation data and historical maps revealed strong agreement, affirming the reliability of the remote sensing approach developed by this study. Evidence from sediment core analyses, stratigraphic correlation, and high-precision RTK field surveys further corroborated the existence of ancient, buried channels and islands within the study area. The study highlights the utility of multi-temporal satellite imagery analysis for reconstructing hydrological evolution and assessing past settlement suitability. Specifically, an inferred paleochannel near the Dendera Temple Complex suggests a possible hydrological connection between a former course of the Nile River and this archaeological site. These findings underscore the potential of remote sensing for large-scale geoarchaeological studies, offering scalable methodologies for identifying ancient river networks and supporting cultural heritage conservation in arid regions. Full article

Photovoltaic systems deployed on large floating platforms in nearshore waters are strongly influenced by hydroelastic effects, nonlinear shallow-water waves, and variable bathymetry. This study develops a time-domain hydroelastic framework that couples the fully nonlinear non-hydrostatic wave model NHWAVE with a Rankine-source potential-flow solver and a discrete-module Cummins formulation. The wave model provides incident pressures and kinematics over uneven seabeds, while the potential-flow solver evaluates radiation and diffraction effects and transfers the resulting hydrodynamic coefficients into the time domain. Numerical simulations are carried out for a 600 m modular floating structure under regular waves over flat and sloped bathymetries with $tan\alpha =0.0133$, wave periods of 4–6 s, and wave heights of 0.3–1.0 m. The results show that bathymetric variation intensifies shoaling-induced excitation, modifies added-mass and damping distributions, increases the spatial non-uniformity of hydroelastic motions, and amplifies bending-moment RMS responses relative to the flat-bottom case. Additional comparisons between rigid-body and hydroelastic models show clear period-dependent redistribution of motions and bending demand. These results demonstrate that both local bathymetry and structural elasticity must be considered for the reliable analysis and design of nearshore floating photovoltaic systems and other large floating structures. Full article

This paper investigates the influence of three key parameters, which are the spacing of cutters, the dip angle of joints and the spacing of joints on the load evolution process of jointed rock masses from the perspective of rock-breaking mechanics. Furthermore, how variations in cutter spacing and joint characteristics affect cutting efficiency is studied from a macroscopic viewpoint, focusing on indicators such as specific energy (SE) for crack propagation and rock fragment formation. Based on the research results, a novel optimization approach for cutter spacing in jointed rock mass conditions is proposed. The optimal cutter spacings under varying joint conditions are calculated, and the effects of joint spacing and dip angle on cutter spacing optimization are systematically discussed. The results show that when the joint dip angle is 60°, the cutter spacing is 100 mm, and the joint spacing is 30 mm, the rock fragmentation efficiency reaches the highest. It is also found that the influence of the joint dip angle on the optimal cutter spacing is greater than that of the joint spacing. When the joint spacing is 70 mm, the corresponding optimal cutter spacing is 100.7 mm. When the joint dip angle increases from 0° to 60°, the optimal cutter spacing gradually increases to 112.8 mm. When the joint spacing is greater than 60 mm, the optimal hammer spacing of the hammer gradually decreases. Full article

Direct urea–hydrogen peroxide fuel cells (DUHPFCs) are promising for sustainable power generation, but their performance is governed by highly nonlinear material and operating interactions. This study develops a machine-learning framework employing a multi-output artificial neural network (ANN) to predict cell voltage, power density (PD), and substrate-based energy efficiency (SEE) of DUHPFCs. The ANN exhibits excellent predictive accuracy, achieving coefficients of determination (R²) above 0.995 and normalized root mean square errors (NRMSE) below 1.75 × 10⁻² for all outputs. Model interpretability is enhanced by using Shapley additive explanations and partial dependence plots, which identify current density as the dominant factor affecting DUHPFC performance, followed by temperature and anolyte composition. The ANN is coupled with a multi-objective Pareto-search algorithm optimization (PAO) to resolve the trade-offs among competing performance metrics. Under different optimization objectives, a DUHPFC with an Ni_0.2Co_0.8/Ni-foam anode is predicted to achieve a maximum PD of 45.6 mW/cm² with a low SEE of 2.6% or a maximum SEE of 15.2% with a moderate PD of 40.9 mW/cm². Additionally, a balanced operating regime is identified, achieving a PD of 43.1 mW/cm² and an SEE of 13.9%. Overall, the proposed framework provides an effective decision-support tool for optimizing DUHPFC performance under competing objectives. Full article

The aim of this paper is to investigate dynamic adjustment of the in situ stress field and the stability of main faults in the Zhangbei strong seismic region. Firstly, we utilized in situ stress measurement and monitoring data to discuss the dynamic adjustment process of the in situ stress field. Subsequently, the Fault Slip Potential (FSP) v.1.0 software package was employed to calculate the fault slip potential of the main faults. Finally, the potential hazard of fault activity was assessed. The conclusions are as follows. (1) Since November 2015, the in situ stress field has been primarily influenced by NEE compressive tectonic action, with a slight enhancement in the near SN compressive tectonic action. (2) In the initial stage, NE-trending faults exhibited the highest stress accumulation levels, with near-EW-trending faults the lowest. Influenced by the enhanced near-SN-trending compressive action, as of 19 October 2020, near-EW-trending faults displayed the highest stress accumulation, followed by NW-trending faults, with NE-trending faults showing the least accumulation. (3) From November 2015 to October 2020, the in situ stress field was in a continuous accumulation process. Using the Shangyi–Pingquan fault as a boundary, fault activity in the southern part of the strong seismic region is more hazardous than that in the northern part. Full article

Multivariate time series anomaly detection holds critical application value in key domains such as industrial system monitoring, financial risk management, and medical surveillance. However, existing approaches face two major challenges: reconstruction-based or prediction-based models tend to adapt to anomalous patterns during training, thereby weakening the distinction between normal and abnormal samples; furthermore, the non-stationary nature of time series leads to distribution shifts between training and testing data, impairing model generalization. To address these issues, this paper proposes the TFCID model. The model innovatively leverages diffusion principles to effectively impute missing time series data while capturing significant frequency-domain features. In the temporal processing stream, an unconditional diffusion model combined with imputation masking is employed to achieve high-precision imputation of randomly missing values, effectively preventing anomalies from interfering with model training. In the frequency-domain processing stream, an amplitude-aware frequency-domain masked autoencoder is introduced to specifically capture periodic or trend-based pattern anomalies. The model mitigates distribution shift by constraining the discrepancy between temporal and frequency-domain representations via adversarial contrastive learning, and uses this discrepancy as a robust anomaly scoring metric. Experimental results on five public benchmark datasets show that TFCID significantly outperforms state-of-the-art methods in detection accuracy (F1-Score), validating its effectiveness in anomaly detection tasks. Full article

Honesty is essential for both individual development and the functioning of society. Although prior research has identified various factors that shape honest behavior, relatively little is known about whether adolescents’ honesty can be influenced by subtle morality-related cues, particularly among adolescents. The present study investigated whether exposure to verbal and visual morality-related cues would increase honest behavior in middle school students. Two behavioral experiments were conducted, each with 120 middle school students (aged 13–18) as participants. In Experiment 1, participants completed a Chinese idiom -unscrambling task with either the ethics-related or neutral characters. In Experiment 2, participants completed a visual cuing task involving either moral exemplar images or neutral images. In both experiments, honest behaviors were assessed via self-reported outcomes in a computerized coin-tossing task. Across both experiments, participants primed with morality-related words (Experiment 1) or moral exemplars (Experiment 2) demonstrated significantly more honest behavior in the coin toss task than those in the control group. These findings suggest that subtle verbal and visual morality-related cues can increase honest behavior in adolescents. The present study provides behavioral evidence that morality-related cues may shape honesty-related responding in adolescence and offers practical implications for promoting moral development through subtle contextual influences. Full article

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by dryness and itching. Steroids are the most common therapeutic agents, may induce skin atrophy, and damage the skin barrier. Therefore, we need to find a safer alternative option. Liquiritin (LQ), a flavonoid compound extracted from licorice rhizomes, possesses anticancer, anti-inflammatory, and antioxidant effects. This study aimed to investigate the therapeutic effects of LQ on AD, focusing on its potential skin barrier-protective and anti-inflammatory mechanisms. In this research, we prepared liquiritin carbomer gel (LQ-CG) and assessed its treatment effects on mice with AD triggered by 2,4-dinitrofluorobenzene (DNFB). It effectively attenuated AD progression by ameliorating skin lesions, decreasing epidermal thickness and mast cell infiltration, downregulating inflammatory cytokine levels, and restoring the expression of claudin-1, loricrin, and occludin. It also inhibited the release of TNF-α, IL-1β, and IL-6 in lipopolysaccharide (LPS)-stimulated RAW264.7 cells, and showed no significant toxicity to major organs in mice. In summary, our findings demonstrate that LQ-CG can effectively alleviate atopic symptoms by repairing the skin barrier and inhibiting inflammatory responses without causing significant changes in organ indices Full article