Search Results (251)

The development of multifunctional conductive hydrogels with rapid self-healing capabilities and powerful sensing functions is crucial for advancing wearable electronics. This study designed and prepared a polyvinyl alcohol (PVA)–borax hydrogel incorporating carbon nanotubes (CNTs) and biomass carbon nanospheres (CNPs) as dual-carbon fillers. This hydrogel exhibits excellent conductivity, mechanical flexibility, and self-recovery properties. Serving as a highly sensitive piezoresistive sensor, it efficiently converts mechanical stimuli into reliable electrical signals. Sensing tests demonstrate that the CNT/CNP/PVA–borax hydrogel sensor possesses an extremely fast response time (88 ms) and rapid recovery time (88 ms), enabling the detection of subtle and rapid human motions. Furthermore, the hydrogel sensor also exhibits outstanding cyclic stability, maintaining stable signal output throughout continuous loading–unloading cycles exceeding 3200 repetitions. The hydrogel sensor’s characteristics, including rapid self-healing, fast-sensing response/recovery, and high fatigue resistance, make the CNT/CNP/PVA–borax conductive hydrogel an ideal choice for multifunctional wearable sensors. It successfully monitored various human motions. This study provides a promising strategy for high-performance self-healing sensing devices, suitable for next-generation wearable health monitoring and human–machine interaction systems. Full article

Background: The Fujiang River, a first-order branch of Jialing River, has for years been separated into six segments by six cascading hydropower stations in its downstream. However, the impact of cascading hydropower stations on its aquatic biota communities remains unclear. Methods: eDNA samples were collected in the upper, middle, and lower reaches of each river fragment during March, May, July, and December 2023, and after species identification, various statistical analyses including β-diversity, NMDS and MantelTest were performed using the R platform. Results: A total of 82 fish species belonging to 15 families were identified. The fish communities in the six fragments of the downstream Fujiang River showed a high degree of overlap, and a notable aggregation of fish communities between the upper, middle, and lower areas within each river section was also observed. Flow velocity (FV) and water temperature (TEMP) were found to be important factors in shaping fish distribution. Conclusion: Fish composition and distribution trend towards homogenization in the downstream of the Fujiang River. Full article

Carnitine (CA) is a chiral amino acid and mostly comes from meat and dairy products. CA cannot be found in fruits, vegetables, or other plants, so vegetarians are deficient in CA. CA exists in the form of D-carnitine (D-CA) and L-carnitine (L-CA); only L-carnitine has biological activity. L-CA promotes the oxidation of fatty acids and then causes the effect of weight loss. In this study, the fluorescence probe was established by using graphene oxide-modified cadmium telluride (CdTe) QDs (GO-CdTe QDs) for the chiral recognition of carnitine enantiomers. GO-CdTe QDs present fluorescence. D-CA enhances the fluorescence spectral signal of the GO-CdTe QDs system, while L-CA weakens its spectral signal. Based on this phenomenon, we determined D-carnitine and L-carnitine. Full article

Understanding the spatiotemporal dynamics of vegetation net primary productivity (NPP) and its drivers is critical to sustainable land -carbon management, carbon-neutral development, and ecological restoration in fragile karst landscapes. This study proposes a Pearson Correlation—Deep Transformer (PCADT) model that integrates attention mechanisms and geospatial covariates to enhance NPP estimation accuracy in Guangxi, China—a global karst hotspot. Leveraging multisource remote sensing data (2015–2020), PCADT achieves 10.7% higher predictive accuracy (R² = 0.83 vs. conventional models) at 500 m resolution, thereby capturing the fine-scale heterogeneity essential for sustainability planning. The results reveal a significant annual NPP increase (4.14 gC·m⁻²·a⁻¹, p < 0.05), with eastern areas exhibiting higher baseline productivity (1129 gC·m⁻² in Wuzhou) but western regions showing steeper growth rates (5.2% vs. 2.1%). Vegetation carbon sequestration capacity, validated against MOD17A3HGF data (R² = 0.998), demonstrates spatial consistency (east > west), with forest-dominated Wuzhou contributing 6.5 TgC annually. Mechanistic analyses identify precipitation as the dominant climatic driver (partial r = 0.62, p < 0.01), surpassing temperature sensitivity, while bimodal NPP-altitude peaks (300 m and 900 m) and land -use transitions (e.g., forest-to-cropland conversions) explain 18.5% of NPP variability and reduce regional carbon stocks by 4593 tC. The PCADT framework offers a scalable solution for precision carbon management by emphasizing the role of anthropogenic interventions—such as afforestation—in alleviating climatic constraints. It advocates for spatially adaptive strategies to optimize water resource utilization, enhance forest conservation, and promote sustainable land -use transitions. By identifying areas where water -scarcity relief and targeted afforestation would yield the highest carbon returns, the PCADT framework directly supports SDG 13 (Climate Action) and SDG 15 (Life on Land), providing a strategic blueprint for sustainable development in water-limited karst regions globally. Full article

Seamounts are distributed globally across the oceans and are generally considered oases of biomass abundance as well as hotspots of species richness. Diverse microbial communities are essential for biogeochemical cycling, yet their functional partitioning among seamounts with geographic features remains poorly investigated. Through metagenomic sequencing and genome-resolved analysis, we revealed that Proteobacteria (33.18–40.35%) dominated the bacterial communities, while Thaumarchaeota (5.98–10.86%) were the predominant archaea. Metagenome-assembled genomes uncovered 117 medium-quality genomes, 81.91% of which lacked species-level annotation, highlighting uncultured diversity. In the Nazuna seamount, which is located in the Marcus-Wake seamount region, microbiomes exhibited heightened autotrophic potential via the 3-hydroxypropionate cycle and dissimilatory nitrate reduction, whereas in the Magellan seamounts regions, nitrification and organic nitrogen metabolism were prioritized. Sulfur oxidation genes dominated Nazuna seamount microbes, with 33 MAGs coupling denitrification to sulfur redox pathways. Metal resistance genes for tellurium, mercury, and copper were prevalent, alongside habitat-specific iron transport systems. Cross-feeding interactions mediated by manganese, reduced ferredoxin, and sulfur–metal integration suggested adaptive detoxification strategies. This study elucidates how deep-sea microbes partition metabolic roles and evolve metal resilience mechanisms across geographical niches. It also supports the view that microbial community structure and metabolic function across seamount regions are likely influenced by the geomorphological features of the seamounts. Full article

This study investigates the effects of unverifiable green signals—vague environmental claims, trust-substitute cues, and function-stacking—on consumer purchasing behaviors in e-commerce settings. Using detailed product-level data collected from two major Chinese online platforms, Taobao and Pinduoduo, during the peak shopping period in November 2023, we analyze the impact of these signals on product sales using ordinary least squares (OLS), instrumental variable (IV), and propensity score matching (PSM) methods. Results indicate that vague environmental language and function-stacking significantly boost sales across platforms, highlighting consumers’ preference for easily interpretable and seemingly comprehensive products. However, trust-substitute signals exhibit mixed effects, with them being beneficial on platforms with stronger credibility frameworks (Taobao) and less effective or even detrimental on platforms characterized by price competition and weaker governance (Pinduoduo). This study contributes to the literature on consumer trust and digital greenwashing by identifying platform-specific responses to unverifiable eco-claims and underscoring the importance of heuristic processing theories and trust formation mechanisms in digital marketing contexts. These findings underscore the complex dynamics of greenwashing strategies and stress the necessity for enhanced regulation and clearer communication standards to protect consumers and genuinely support sustainable consumption. Full article

Cytosine DNA methylation (5mCs) is an important epigenetic modification in genomic research. However, the methylation states of some cytosine sites are not available due to the limitations of different studies, and there are few tools developed to deal with this problem, especially in plants, which have more methylation types than animals. Here, we report PlantDeepMeth, a novel deep learning model that utilizes deep learning to predict DNA methylation states in plants. The evaluation of PlantDeepMeth on known cytosine sites in both the Brassica rapa and Arabidopsis thaliana genomes shows good performance in predicting methylation states, indicating that the tool is good at learning patterns for methylation imputation. Motif analysis of the model’s predictions identified specific motifs associated with hypo- or hyper-methylation states in B. rapa and A. thaliana, further revealing key regulatory patterns captured by the model. Moreover, cross-species validation between B. rapa and A. thaliana demonstrated the generalizability of PlantDeepMeth, with the model maintaining high performance across different plant species. These results highlight the effectiveness of PlantDeepMeth and demonstrate the potential of deep learning to advance plant genomics research. Full article

Cellulose-based aerogel is an environmentally friendly multifunctional material that is renewable, biodegradable, and easily surface-modified. However, due to its flammability, cellulose serves as an ignition source in fire incidents, leading to the combustion of building materials and resulting in significant economic losses and safety risks. Consequently, it is essential to develop cellulose-based building materials with flame-retardant properties. Initially, a porous cellulose-based flame-retardant aerogel was successfully synthesized through freeze-drying, utilizing lignocellulose as the raw material. Subsequently, phosphorylation of cellulose was coupled with Ca²⁺ cross-linking via self-assembly and surface deposition effects to enhance its flame-retardant properties. Finally, the synthesized materials were characterized using infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, mechanical compression testing, and scanning electron microscopy. The aerogel of the phosphorylated cellulose nanofibrils cross-linked via 1.5% CaCl₂ exhibited the most effective flame-retardant properties and the best mechanical characteristics, achieving a UL-94 test rating of V-0 and a maximum flame-retardant rate of 90.6%. Additionally, its compressive strength and elastic modulus were recorded at 0.39 and 0.98 MPa, respectively. The preparation process is environmentally friendly, yielding products that demonstrate significant flame-retardant effects and are non-toxic. This product is anticipated to replace polymer-based commercial aerogel materials, representing a sustainable solution to the issue of “white pollution”. Full article

The Japanese encephalitis virus is an arbovirus that causes severe damage to the central nervous system. At present, there are still 67,900 cases of Japanese encephalitis worldwide every year, which poses a global public health concern and causes great economic losses to animal husbandry. In this study, we analyzed the epidemiology, transmission, and evolution of JEV based on the NCBI database. E and NS1 were emphatically analyzed for amino acid variation and predicted protein structure. Gene recombination and the evolutionary rate of JEV were analyzed using RDP 4 and BEAST. The maximum clade credibility tree of E was reconstructed to estimate the time of the most recent common ancestor. Chinese genotype Ⅰ (GI) strain recombination events occurred in the C, M/PrM, E, NS2A, NS4B, and NS5 proteins, and genotype III (GIII) strains occurred in the E, NS1, NS3, NS4A, and NS5 proteins. The average evolutionary rates of JEV were comparable (3.3830 × 10⁻⁴, 2.0481 × 10⁻⁴, 3.5650 × 10⁻⁴, 2.2423 × 10⁻⁴, 3.0844 × 10⁻⁴, and 1.9757 × 10⁻⁴ substitutions/site/year for the JEV-I whole genome, JEV-III whole genome, JEV-I E gene, JEV-III E gene, JEV-I NS1 gene, and JEV-III NS1 gene, respectively). The MCC tree revealed the evolutionary order was GⅢ, GⅠ, GⅤ, GⅡ, and GⅣ. This study was expected to provide theoretical support for vaccine development and comprehensive prevention and treatment of JEV. Full article

Marigold (Tagetes erecta L.), a crop of significant medicinal, ornamental, and economic value, faces severe industrialization challenges due to weed-induced yield losses (up to 60%). This study aims to identify safe and highly efficient herbicides for marigold, assess their effects on dominant weeds and crop safety, and provide a practical basis for large-scale cultivation. We evaluated 11 pre-emergence herbicides, 13 post-emergence herbicides, and agronomic practices (plastic mulch) through three field trials to optimize weed control, crop safety, and productivity. In Experiment 1, pre-emergence applications of pendimethalin (35% SC) and oxyfluorfen (240 g/L EC) under plastic mulch suppressed 85–99% of grass and broad-leaved weeds, elevating marigold yield to 1655.6 kg/667 m² and increasing lutein content by 10.7% compared to controls, with no phytotoxicity to subsequent wheat (Triticum aestivum L.)or broad beans (Vicia faba L.). Experiment 2 demonstrated that post-cultivation soil treatment with metolachlor · oxyfluorfen · pendimethalin (50% EC) enhanced weed suppression (47.8–53.6%) and yield (3.4% increase) while ensuring crop safety. Experiment 3 revealed that the post-emergence herbicides haloxyfop-P-methyl (108 g/L EC) and fomesafen (250 g/L SL) achieved over 92% reduction in grass weed biomass and over 75% reduction in broadleaf weed density, respectively, alongside a 6.1% yield improvement. Therefore, region-specific strategies are recommended based on local agronomic conditions: high-value production zones should adopt integrated systems combining plastic mulch with pre-emergence herbicides; arid lands with extended crop rotation intervals require pre-emergence herbicides after intertillage and earthing-up; labor-abundant regions can rotate targeted post-emergence herbicides to delay resistance evolution. This study provides data-driven optimization strategies for comprehensive weed management in marigold fields, offering practical solutions to enhance industrial productivity and ecological sustainability. Full article

Proteolytic enzymes, which play a crucial role in peptide bond cleavage, are widely applied in various industries. In this study, protease-producing bacteria were isolated and characterized from marine sediments collected from the Yellow Sea, China. Comprehensive screening and 16S rDNA sequencing identified a promising G4 strain as Bacillus atrophaeus. Following meticulous optimization of fermentation conditions and medium composition via response surface methodology, protease production using strain G4 was significantly enhanced by 64%, achieving a yield of 3258 U/mL. The G4 protease exhibited optimal activity at 50 °C and pH 7.5, demonstrating moderate thermal stability with 52% residual activity after 30-min incubation at 50 °C—characteristics typical of an alkaline protease. Notably, the enzyme retained over 79% activity across a broad pH range (6–11) and exhibited excellent salt tolerance, maintaining over 50% activity in a saturated NaCl solution. Inhibition by phenylmethylsulfonyl fluoride, a serine protease inhibitor, confirmed its classification as a serine protease. The enzyme’s potential in generating bioactive peptides was further demonstrated through hydrolysis of sheep (Ovis aries) placenta, resulting in a hydrolysate with notable antioxidant properties. The hydrolysate exhibited a 64% superoxide anion scavenging activity, surpassing that of reduced glutathione. These findings expand the current understanding of Bacillus atrophaeus G4 proteases and provide a foundation for innovative sheep placenta utilization with potential industrial applications. Full article

As a major global health challenge, hepatocellular carcinoma (HCC) still faces substantial limitations in its treatment options. This study investigates the anti-HCC potential of ACY-1215, a selective Histone deacetylase 6 (HDAC6) inhibitor, and its mechanism targeting p53 regulation. In vitro studies conducted with HepG2 and SMMC-7721 cells revealed that ACY-1215 markedly inhibited HCC cell proliferation, migratory capacity, and invasive potential, as evidenced by CCK-8, colony formation, and Transwell assays. Furthermore, ACY-1215 induced caspase-dependent apoptosis. Mechanistically, ACY-1215 enhanced p53 acetylation by disrupting HDAC6-p53 interaction, thereby stabilizing p53 protein levels. Concurrently, it inhibited Murine Double Minute 2 (MDM2)-mediated ubiquitination, blocking proteasomal degradation and prolonging p53 half-life. This dual modulation restored p53 transcriptional activity, leading to the upregulation of downstream effector molecules associated with cell cycle regulation and apoptosis. Collectively, our findings reveal that ACY-1215 exerts potent anti-HCC effects through coordinated regulation of p53 acetylation and ubiquitination, offering a novel dual-targeting strategy for HCC therapy. Full article

To investigate the dietary effects of Astragalus polysaccharides (APSs) on the growth performance, lipid metabolism, antioxidant activity, and non-specific immunity of Asian swamp eel (Monopterus albus) during the domestication stage, fish were randomly allocated into quadruplicate groups receiving Tenebrio molitor-based diets supplemented with Astragalus polysaccharides (APSs) at graded concentrations of 0 (CON), 700 (APS1), 1400 (APS2), and 2100 (APS3) mg/kg body weight for 28 days. The results showed that dietary APSs at 700–1400 mg/kg·bw significantly enhanced the weight gain rate (WG) and decreased the feed conversion ratio (FCR) of M. albus (p < 0.05). Concurrently, hematological analysis revealed that hemoglobin levels increased by 19.9% and 23.0% in the 700 and 1400 mg/kg APS groups, respectively (p < 0.05). In terms of lipid metabolism, supplementation with APSs significantly increased the serum high-density lipoprotein (HDL) content in all treatment groups (p < 0.05). Lower serum triglyceride (TG) levels were found in the APS2 group (p < 0.05), and decreased triglyceride (TG), cholesterol (CHO), and low-density lipoprotein (LDL) levels were displayed in the APS3 group (p < 0.05). Among the antioxidant parameters, the supplementation with 700 mg/kg·bw APSs significantly increased the glutathione peroxidase (GSH-Px) and catalase (CAT) activity levels of M. albus (p < 0.05). The APS2 group had a significantly increased total antioxidant capacity (T-AOC) and CAT activity levels (p < 0.05), and the APS3 group had significantly increased CAT activity levels (p < 0.05). In addition, the APS1 and APS3 groups had significantly reduced malondialdehyde (MDA) levels (p < 0.05). In terms of non-specific immunity, the APS1 and APS2 groups showed significantly increased superoxide dismutase (SOD) and lysozyme (LZM) activity levels of M. albus (p < 0.05), and the addition of 700 mg/kg·bw APSs significantly increased the levels of alkaline phosphatase (AKP) activity (p < 0.05). Furthermore, the levels of acid phosphatase (ACP) activity were significantly increased in all experimental groups (p < 0.05). In conclusion, the optimal APS addition for T. molitor as biocarrier bait is 700 mg/kg, corresponding to 352 mg/kg, which elicits improvements in the growth parameters, lipid homeostasis regulation, oxidative stress mitigation, and innate immune potentiation of M. albus during the domestication stage. Full article

The Qinling Mountains serve as the main water source for the Weihe River and Hanjiang River. However, the lack of sufficient observational data limits a deeper understanding and the utilization of its water resources. In this study, the Variable Infiltration Capacity (VIC) hydrological model is used to quantitatively analyze runoff changes and their impacts on these rivers, based on meteorological, land use, and elevation data. By using the hydrological parameter transplantation method, a parameterized system was established to simulate runoff variations from 1970 to 2020. Results showed that the total runoff of the Qinling Mountains in Shaanxi Province ranged between 13.26 and 44.47 billion m³/year, with an average perennial runoff of 25.05 billion m³/year. Over the past 51 years, the runoff volume has exhibited a slightly decreasing trend. The average runoff at the northern foothills is 3.56 billion m³/year, which accounts for 62.4% of the natural average runoff of the Weihe River (Huaxian Station). In contrast, the average runoff at the southern foothills is 21.49 billion m³/year, which accounts for 68.1% of the natural average runoff of the Hanjiang River (Huangjiagang Station). The significant variation in water vapor transport from the western equatorial Pacific to the region via the South China Sea has been identified as the primary reason for the changes in runoff. This quantitative study of runoff changes in the Qinling Mountains clarifies their influence on the Weihe River and the Hanjiang River and will provide a basis for the rational usage of ecological water. Full article

During substation inspection, operators are often exposed to hazardous working environments. It is necessary to use visual sensors to determine work status and perform action detection to distinguish between normal and dangerous actions in order to ensure the safety of operators. However, due to information security, privacy protection, and the rarity of dangerous scenarios, there is a scarcity of related visual action datasets. To address this issue, this study first introduces a virtual work platform, which includes a controller for the parameterized control of scenarios and human resources. It can simulate realistic substation inspection operations and generate synthetic action datasets using domain randomization and behavior tree logic. Subsequently, a spatiotemporal action detection algorithm is utilized for action detection, employing YOLOv8 as the human detector, Vision Transformer as the backbone network, and SlowFast as the action detection architecture. Model training is conducted using three datasets: a real dataset, a synthetic dataset generated via a VWP, and a mixed dataset comprising both real and synthetic data. Finally, using the model trained on the real dataset as a baseline, the evaluation results on the test set shows that the use of synthetic datasets in training improves the model’s average precision by up to 10.7%, with a maximum average precision of 73.61%. This demonstrates the feasibility, effectiveness, and robustness of synthetic data. Full article