Search Results (757)

This study systematically investigates the effects of demineralization on the pyrolysis characteristics, kinetics, and thermodynamics of three biomass types (eucalyptus, straw, and miscanthus) using thermogravimetric analysis (TGA) combined with multiple kinetic approaches. The Coats–Redfern integral model was employed to determine the reaction mechanisms. The results indicate that the primary weight-loss temperature ranges for eucalyptus, straw, and miscanthus were 222.02~500.23 °C, 205.43~500.13 °C, and 202.30~490.52 °C, respectively. Demineralization increased the initial pyrolysis temperature and significantly enhanced the reaction rates. Kinetics analysis revealed that the ash content significantly influences the activation energy of the pyrolysis reaction. The average activation energies follow the trend eucalyptus (193.48 kJ/mol) < miscanthus (245.66 kJ/mol) < straw (290.13 kJ/mol). After demineralization, the activation energies of both straw and miscanthus pyrolysis decreased, with the largest reduction observed in straw, which dropped by 77.53 kJ/mol. However, the activation energy for eucalyptus pyrolysis increased by 12.52 kJ/mol after demineralization. The Coats–Redfern model and thermodynamic analysis demonstrated that each type of biomass followed distinct reaction mechanisms at different stages, which were altered after demineralization. Additionally, demineralization leads to higher ΔH and Gibbs free energy ΔG for eucalyptus, but lower values for straw and miscanthus, which indicate that the ash content has a significant impact on the biomass pyrolysis reaction. These findings provide fundamental insights into the role of ash in biomass pyrolysis kinetics and offer theoretical support for the design of pyrolysis reactors. Full article

Browning significantly impacts the commercial value of luffa (luffa cylindrica) and is primarily driven by the metabolic processes of phenolic acids. Investigating changes in phenolic acids during browning aids in understanding the physiological mechanisms underlying this process and provides a basis for improving storage, processing, variety breeding, and utilization of germplasm resources. This study compared browning-resistant (‘30’) and browning-sensitive (‘256’) luffa varieties using high-throughput sequencing and metabolomics techniques. The results revealed 55 genes involved in the phenylpropanoid biosynthesis pathway, including 8 phenylalanine ammonia-lyase (PAL) genes, 20 peroxidase (POD) genes, 2 polyphenol oxidase (PPO) genes associated with tyrosine metabolism, and 37 peroxisome-related genes. Real-time quantitative (qPCR) was employed to validate 15 browning-related genes, revealing that the expression levels of LcPOD21 and LcPOD6 were 12.5-fold and 25-fold higher in ‘30’ compared to ‘256’, while LcPAL5 and LcPAL4 were upregulated in ‘30’. Enzyme analysis showed that catalase (CAT) and phenylalanine ammonia-lyase (PAL) activities were higher in ‘30’ than in ‘256’. Conversely, superoxide dismutase (SOD) and polyphenol oxidase (PPO) activities were reduced in ‘30’, whereas CAT activity was upregulated. The concentrations of cinnamic acid, p-coumaric acid, trans-5-O-(4-coumaroyl)mangiferic acid, and caffealdehyde were lower in browning-resistant luffa ‘30’ than in browning-sensitive luffa ‘256’, suggesting that their levels influence browning in luffa. These findings elucidate the mechanisms underlying browning and inform strategies for the storage, processing, and genetic improvement of luffa. Full article

Soil respiration (Rt), consisting of heterotrophic (Rh) and autotrophic respiration (Ra), plays a vital role in terrestrial carbon cycling and is sensitive to soil temperature and moisture. In dryland agriculture, plastic film mulching (PM) is widely used to regulate soil hydrothermal conditions, but its effects on Rt components and their temperature sensitivity (Q₁₀) across regions remain unclear. A two-year field study was conducted at two rain-fed maize sites: Anding (warmer, semi-arid) and Yuzhong (colder, drier). PM significantly increased Rt, Rh, and Ra, especially Ra, due to enhanced root biomass and improved microclimate. Yield increased by 33.6–165%. Peak respiration occurred earlier in Anding, aligned with maize growth and soil temperature. PM reduced Q₁₀ of Rt and Ra in Anding, but only Ra in Yuzhong. Rh Q₁₀ remained stable, indicating microbial respiration was less sensitive to temperature changes. Structural equation modeling revealed that Rt and Ra were mainly driven by soil temperature and root biomass, while Rh was more influenced by microbial biomass carbon (MBC) and dissolved organic carbon (DOC). Despite increased CO₂ emissions, PM improved carbon emission efficiency (CEE), particularly in Yuzhong (+67%). The application of PM is recommended to enhance yield while optimizing carbon efficiency in dryland farming systems. Full article

Background: Lung cancer ranks as the leading cause of cancer-related mortality worldwide. The complexity of tumor delineation, crucial for radiation therapy, requires expertise often unavailable in resource-limited settings. Artificial Intelligence (AI), particularly with advancements in deep learning (DL) and natural language processing (NLP), offers potential solutions yet is challenged by high false positive rates. Purpose: The Oncology Contouring Copilot (OCC) system is developed to leverage oncologist expertise for precise tumor contouring using textual descriptions, aiming to increase the efficiency of oncological workflows by combining the strengths of AI with human oversight. Methods: Our OCC system initially identifies nodule candidates from CT scans. Employing Language Vision Models (LVMs) like GPT-4V, OCC then effectively reduces false positives with clinical descriptive texts, merging textual and visual data to automate tumor delineation, designed to elevate the quality of oncology care by incorporating knowledge from experienced domain experts. Results: The deployment of the OCC system resulted in a 35.0% reduction in the false discovery rate, a 72.4% decrease in false positives per scan, and an F1-score of 0.652 across our dataset for unbiased evaluation. Conclusions: OCC represents a significant advance in oncology care, particularly through the use of the latest LVMs, improving contouring results by (1) streamlining oncology treatment workflows by optimizing tumor delineation and reducing manual processes; (2) offering a scalable and intuitive framework to reduce false positives in radiotherapy planning using LVMs; (3) introducing novel medical language vision prompt techniques to minimize LVM hallucinations with ablation study; and (4) conducting a comparative analysis of LVMs, highlighting their potential in addressing medical language vision challenges. Full article

Fe³⁺-incorporated hydrogels are particularly valuable for wearable devices due to their tunable mechanical properties and ionic conductivity. However, conventional immersion-based fabrication fundamentally limits hydrogel performance because of heterogeneous ion distribution, ionic leaching, and scalability limitations. To overcome these challenges, we report a novel one-pot strategy where controlled amounts of Fe³⁺ are directly added to polyacrylamide-sodium acrylate (PAM-SA) precursor solutions, ensuring homogeneous ion distribution. Combining this with Photoinduced Electron/Energy Transfer Reversible Addition–Fragmentation Chain Transfer (PET-RAFT) polymerization enables efficient hydrogel fabrication under open-vessel conditions, improving its scalability. Fe³⁺ concentration achieves unprecedented modulation of mechanical properties: Young’s modulus (10 to 150 kPa), toughness (0.26 to 2.3 MJ/m³), and strain at break (800% to 2500%). The hydrogels also exhibit excellent compressibility (90% strain recovery), energy dissipation (>90% dissipation efficiency at optimal Fe³⁺ levels), and universal adhesion to diverse surfaces (plastic, metal, PTFE, and cardboard). Finally, these Fe³⁺-incorporated hydrogels demonstrated high effectiveness as strain sensors for monitoring finger/elbow movements, with gauge factors dependent on composition. This work provides a scalable, oxygen-tolerant route to tunable hydrogels for advanced wearable devices. Full article

This review examines the research progress on non-noble-metal-based catalysts for formaldehyde (HCHO) oxidation at room temperature. It begins with an introduction to the hazards of HCHO as an indoor pollutant and the urgency of its removal, comparing several HCHO removal technologies and highlighting the advantages of room-temperature catalytic oxidation. It delves into the classification, preparation methods, and regulation strategies for non-precious metal catalysts, with a focus on manganese-based, cobalt-based, and other transition metal-based catalysts. The effects of catalyst preparation methods, morphological structure, and specific surface area on catalytic performance are discussed, and the catalytic oxidation mechanisms of HCHO, including the Eley–Rideal, Langmuir–Hinshelwood, and Mars–van Krevelen mechanisms, are analyzed. Finally, the challenges faced by non-precious metal catalysts are summarized, such as issues related to the powder form of catalysts in practical applications, lower catalytic activity at room temperature, and insufficient research in the presence of multiple VOC molecules. Suggestions for future research directions are also provided. Full article

This review comprehensively examines the application of deep learning technologies across the entire soybean production chain, encompassing areas such as disease and pest identification, weed detection, crop phenotype recognition, yield prediction, and intelligent operations. By systematically analyzing mainstream deep learning models, optimization strategies (e.g., model lightweighting, transfer learning), and sensor data fusion techniques, the review identifies their roles and performances in complex agricultural environments. It also highlights key challenges including data quality limitations, difficulties in real-world deployment, and the lack of standardized evaluation benchmarks. In response, promising directions such as reinforcement learning, self-supervised learning, interpretable AI, and multi-source data fusion are proposed. Specifically for soybean automation, future advancements are expected in areas such as high-precision disease and weed localization, real-time decision-making for variable-rate spraying and harvesting, and the integration of deep learning with robotics and edge computing to enable autonomous field operations. This review provides valuable insights and future prospects for promoting intelligent, efficient, and sustainable development in soybean production through deep learning. Full article

In order to explore the essence of the anticoccidiosis of anticoccidial drugs under bioelectric currents, the intermolecular double-proton transfer and conformational transformation of 4-pyridone-3-carboxylic acid were investigated by quantum chemistry calculations (at the M06-2X/6-311++G**, M06-2X/aug-cc-pVTZ and CCSD(T)/aug-cc-pVTZ levels) and finite temperature string (FTS) under external electric fields. The solvent effect of H₂O on the double-proton transfer was evaluated by the integral equation formalism polarized continuum model. The results indicate that the influences of the external electric fields along the direction of the dipole moment on double-proton transfer are significant. The corresponding products are controlled by the direction of the external electric field. Due to the first-order Stark effect, some good linear relationships form between the changes of the structures, atoms in molecules (AIMs) results, surface electrostatic potentials, barriers of the transition state, and the external electric field strengths. From the gas to solvent phase, the barrier heights increased. The spatial order parameters (ϕ, ψ) of the conformational transformation could be quickly converged through the umbrella sampling and parameter averaging, and thus the free-energy landscape for the conformational transformation was obtained. Under the external electric field, there is competition between the double-proton transfer and conformational transformation. The external electric field greatly affects the cooperativity transfer, while it has little effect on the conformational transformation. This study is helpful in the selection and updating of anticoccidial drugs. Full article

To address the challenges posed by the instability of renewable energy output and load fluctuations on grid operations and to support the low-carbon sustainable development of the energy system, this paper integrates artificial intelligence technology to establish an economic stability dispatch framework for distributed resource aggregators. A phased multi-contract collaborative scheduling model oriented toward sustainable development is proposed. Through intelligent algorithms, the model dynamically optimises decisions across the day-ahead and intraday phases: During the day-ahead scheduling phase, intelligent algorithms predict load demand and energy output, and combine with elastic performance-based response contracts to construct a user-side electricity consumption behaviour intelligent control model. Under the premise of ensuring user comfort, the model generates a 24 h scheduling plan with the objectives of minimising operational costs and efficiently integrating renewable energy. In the intraday scheduling phase, a rolling optimisation mechanism is used to activate energy storage capacity contracts and dynamic frequency stability contracts in real time based on day-ahead prediction deviations. This efficiently coordinates the intelligent frequency regulation strategies of energy storage devices and electric vehicle aggregators to quickly mitigate power fluctuations and achieve coordinated control of primary and secondary frequency regulation. Case study results indicate that the intelligent optimisation-driven multi-contract scheduling model significantly improves system operational efficiency and stability, reduces system operational costs by 30.49%, and decreases power purchase fluctuations by 12.41%, providing a feasible path for constructing a low-carbon, resilient grid under high renewable energy penetration. Full article

Oxidative stress is a key mediator of physiological dysfunction in aquatic organisms under environmental challenges, yet its comprehensive impacts on gill physiology require further clarification. This study investigated the molecular and cellular responses of Eriocheir sinensis gills to hydrogen peroxide (H₂O₂)-induced oxidative stress, integrating antioxidant defense, ion transport regulation, and stress-induced cell apoptosis and autophagy. Morphological alterations in the gill filaments were observed, characterized by septum degeneration, accumulation of haemolymph cells, and pronounced swelling. For antioxidant enzymes like catalase (CAT) and glutathione peroxidase (GPx), activities were enhanced, while superoxide dismutase (SOD) activity was reduced following 48 h of exposure. Overall, the total antioxidant capacity (T-AOC) showed a significant increase. The elevated concentrations of malondialdehyde (MDA) and H₂O₂ indicated oxidative stress. Ion transport genes displayed distinct transcription patterns: Na⁺-K⁺-2Cl⁻ co-transporter-1 (NKCC1), Na⁺/H⁺ exchanger 3 (NHE3), aquaporin 7 (AQP7), and chloride channel protein 2 (CLC2) were significantly upregulated; the α-subunit of Na⁺/K⁺-ATPase (NKAα) and carbonic anhydrase (CA) displayed an initial increase followed by decline; whereas vacuolar-type ATPase (VATP) consistently decreased, suggesting compensatory mechanisms to maintain osmotic balance. Concurrently, H₂O₂ triggered apoptosis (Bcl2, Caspase-3/8) and autophagy (beclin-1, ATG7), likely mediated by MAPK and AMPK signaling pathways. These findings reveal a coordinated yet adaptive response of crab gills to oxidative stress, providing new insights into the mechanistic basis of environmental stress tolerance in crustaceans. Full article

A comprehensive bibliometric analysis of literature is imperative to elucidate current research landscapes and hotspots in the interplay between gut microbiota and hypertension, identify knowledge gaps, and establish theoretical foundations for the future. We used publications retrieved from the Web of Science Core Collection (WoSCC) and SCOPUS databases (January 2001–December 2024) to analyze the annual publication trends with GraphPad Prism 9.5.1, to evaluate co-authorship, keywords clusters, and co-citation patterns with VOSviewer 1.6.20, and conducted keyword burst detection and keyword co-occurrence utilizing CiteSpace v6.4.1. We have retrieved 2485 relevant publications published over the past 24 years. A 481-fold increase in global annual publications in this field was observed. China was identified as the most productive country, while the United States demonstrated the highest research impact. For the contributor, Yang Tao (University of Toledo, USA) and the University of Florida (USA) have emerged as the most influential contributors. Among journals, the highest number of articles was published in Nutrients (n = 135), which also achieved the highest citation count (n = 5397). The emergence of novel research hotspots was indicated by high-frequency keywords, mainly “hypertensive disorders of pregnancy”, “mendelian randomization”, “gut-heart axis”, and “hepatitis B virus”. “Trimethylamine N-oxide (TMAO)” and “receptor” may represent promising new research frontiers in the gut microbiota–hypertension nexus. The current research trends are shifting from exploring the factors influencing gut microbiota and hypertension to understanding the underlying mechanisms of these factors and the potential therapeutic applications of microbial modulation for hypertension management. Full article

A metasurface capable of flexibly manipulating electromagnetic waves to realize holograms presents significant potential in millimeter-wave imaging systems and data storage domains. In this study, full-space three-dimensional holograms are realized from a reflection–transmission integrated reconfigurable metasurface, which can achieve nearly 360° phase coverage in reflection space and 180° phase coverage in transmission space. By adjusting the voltage applied to the constituting electronically tunable meta-atoms of the metasurface, an octahedron hologram constituted by three hologram images in different focal planes is generated in the reflection space at 6.25 GHz. Moreover, a diamond hologram, also composed of three hologram images in different focal planes, is achieved in the transmission space at 6.75 GHz. Both the numerical simulation and experimental measurement are performed to validate the full-space holograms implemented by the modified weighted Gerchberg–Saxton (WGS) algorithm with specific phase distribution in different imaging planes. The obtained results pave the way for a wide range of new applications, such as next-generation three-dimensional displays for immersive viewing experiences, high-capacity optical communication systems with enhanced data encoding capabilities, and ultra-secure anti-counterfeiting solutions that are extremely difficult to replicate. Full article

The hydrological processes of agricultural fields during the fallow season in east-central Mississippi remain poorly understood, due to the region’s unique rainfall patterns. This study utilized long-term rainfall records from 1924 to 2023 to evaluate runoff characteristics and the runoff response to various rainfall events during fallow seasons in Mississippi by applying the DRAINMOD model. The analysis revealed that the average rainfall during the fallow season was 760 mm over the past 100 years, accounting for 65% of the annual total. In dry, normal, and wet fallow seasons, the average rainfall was 528, 751, and 1010 mm, respectively, corresponding to runoff of 227, 388, and 602 mm. Runoff frequency increased with wetter weather conditions, rising from 16 events in dry seasons to 23 in normal seasons and 30 in wet seasons. Over the past century, runoff dynamics were predominantly regulated by high-intensity rainfall events during the fallow season. Very heavy rainfall events (mean frequency = 11 events) generated 215 mm of runoff and accounted for 53% of the total runoff, while extreme rainfall events (mean frequency = 2 events) contributed 135 mm of runoff, making up 34% of the total runoff. Water table depth played a critical role in shaping spring runoff dynamics. As the water table decreased from 46 mm in March to 80 mm in May, the soil pore space increased from 5 mm in March to 14 mm in May. This increased soil infiltration and water storage capacity, leading to a steady decline in runoff. The study found that the mean daily runoff frequency dropped from 13.5% in March to 7.6% in May, while monthly runoff decreased from 74 to 38 mm. Increased extreme rainfall (R95p) in April contributed over 45% of the total runoff and resulted in the highest daily mean runoff of 20 mm, compared to 18 mm in March and 16 mm in May. The results from this century-long historical weather data could be used to enhance field-scale water resource management, predict potential runoff risks, and optimize planting windows in the humid east-central Mississippi. Full article

Background: Compression garments (CG) may influence countermovement jump (CMJ) performance by altering hip and knee biomechanics, but existing evidence remains controversial. This study aimed to compare the effects of compression tights (CTs), compression shorts (CSs), and control shorts (CCs) on CMJ performance and lower-limb biomechanics. Methods: Nine physically active men from a university were recruited to perform CMJ while wearing CTs, CSs, and CCs in a randomized sequence for a within-subjects repeated-measures design. A Vicon 3D motion capture system and an AMTI 3D force plate were used to collect biomechanical data. Visual3D software was used to calculate the joint angle, moment, and force of the lower limbs. Results: Statistical parametric mapping analysis with repeated measures analysis of variance (ANOVA) revealed that during the propulsion phase of the CMJ, wearing CSs significantly reduced the hip flexion angle compared to wearing CCs (25–36%); meanwhile, wearing CTs significantly reduced the knee extension and flexion moment (34–35%) and decreased the hip extension moment during the propulsion phase (36–37%). In addition, CTs significantly reduced the hip abduction angle during the flight phase (37–39%), and CSs significantly reduced the hip anterior force during the landing phase (59–60%). Conclusions: Compression legwear significantly affected the hip and knee biomechanics in propulsion, but these differences were not sufficient to improve the CMJ height. Due to the improvement in hip biomechanics in the flight and landing phases, there may be potential benefits for movement transitions and landing performance in CMJ. Full article

Cotton is the most widely cultivated natural fiber crop worldwide, yet it is highly susceptible to various diseases and pests that significantly compromise both yield and quality. To enable rapid and accurate diagnosis of cotton diseases and pests—thus supporting the development of effective control strategies and facilitating genetic breeding research—we propose a lightweight model, the Resource-efficient Cotton Network (RF-Cott-Net), alongside an open-source image dataset, CCDPHD-11, encompassing 11 disease categories. Built upon the MobileViTv2 backbone, RF-Cott-Net integrates an early exit mechanism and quantization-aware training (QAT) to enhance deployment efficiency without sacrificing accuracy. Experimental results on CCDPHD-11 demonstrate that RF-Cott-Net achieves an accuracy of 98.4%, an F1-score of 98.4%, a precision of 98.5%, and a recall of 98.3%. With only 4.9 M parameters, 310 M FLOPs, an inference time of 3.8 ms, and a storage footprint of just 4.8 MB, RF-Cott-Net delivers outstanding accuracy and real-time performance, making it highly suitable for deployment on agricultural edge devices and providing robust support for in-field automated detection of cotton diseases and pests. Full article