Search Results (27,642)

Radiation use efficiency (RUE) is closely associated with cotton biomass and yield, yet the synergistic regulation of phenotypic structure and physiological potential remains unclear. A field experiment (2024–2025) in Anyang, China, utilized three independent trials: six sowing dates (from 12 April to 12 May at 6-day intervals, S1–S6), six planting densities (1.5, 3.3, 5.1, 6.9, 8.7, and 10.5 × 10⁴ plants·ha⁻¹, D1–D6), and ten cultivars with distinct architectures (V1–V10). Feature importance and structural relationships were quantified via random forest (RF) and partial least squares structural equation modeling (PLS-SEM). Results indicated that delaying sowing reduced true leaf number (TLN) and plant height (PH), with the April 24 sowing (S3) optimizing leaf area index (LAI, 2.57) and light interception rate (iPAR, 0.61). Increasing density significantly enhanced population-level LAI, above-ground biomass, and RUE, despite a progressive decline in TLN. Among cultivars, CCRI 60 (V6) exhibited superior structural traits (PH: 72.94 cm; iPAR: 0.61), while CCRI 113 (V8) exhibited the highest maximum carboxylation rate (V_cmax, 88.9 μmol·m⁻²·s⁻¹) and RUE (4.88 g·MJ⁻¹). Across the comprehensive dataset (integrating the density, sowing date, and cultivar trials), iPAR exhibited the highest relative importance (42.01%) for RUE variation, while associated structural traits (PH, LAI, TLN) yielded a cumulative relative importance of 41.69%. RUE was strongly associated with biomass accumulation (path coefficient > 0.97), which subsequently optimized yield components. Conversely, within the cultivar-comparison subset, the relative importance of iPAR decreased to 17.95%, while V_cmax rose significantly to 19.20%. PLS-SEM indicated that canopy structure exerted a significant negative association with photosynthetic potential (V_cmax, J_max) within this cultivar subset (path coefficient ≈ −0.51), whereas enhanced physiological potential was positively associated with resource allocation to yield components (path coefficient ≈ 0.57). Consequently, mitigating the inherent trade-off between canopy structure and leaf photosynthetic capacity is critical for further improving RUE and cotton yield under similar production environments. Full article

Rapid urbanization and industrialization have profoundly affected aquatic ecosystems in urban rivers, with phytoplankton taxa and functional group composition being particularly sensitive to environmental changes. Field surveys were conducted in the Nanming River, Guiyang, in October 2018 and July 2019, with 33 sampling sites evenly distributed across the upstream, midstream, and downstream reaches. The results revealed that: (1) The phytoplankton community comprised 6 phyla, 53 genera, and 61 species, dominated by Bacillariophyta, Chlorophyta, and Cyanobacteria. The community was classified into 20 functional groups, among which B, D, MP, P, and S1 were dominant and exhibited clear spatial heterogeneity along the longitudinal gradient. (2) Analysis of variance indicated that physicochemical parameters were the dominant factors explaining the variation in phytoplankton taxonomic and functional groups, with their independent contribution significantly higher than that of anthropogenic disturbance indicators and geographical factors. Redundancy analysis further identified NH₄-N, TP, and TN as key environmental factors. Spearman’s correlation analysis further indicated that human activities alter ambient environmental conditions, which are significantly correlated with dissolved oxygen and chlorophyll a levels, thereby driving the differentiation of phytoplankton niches. (3) Functional group succession followed a distinct spatial pattern: upstream areas were dominated by groups P, SN, and Y, reflecting agricultural non-point source inputs; midstream areas were dominated by groups W1, H1, and S1, characteristic of urban complex pollution; and downstream areas were dominated by groups C and X1, indicating cumulative nutrient loading. Collectively, this study elucidates the driving mechanisms of phytoplankton dynamics in karst urban rivers and provides a scientific foundation for water quality monitoring, eutrophication risk pre-warning, and aquatic ecological restoration. Full article

Plot combine harvesters are specialized machines used in breeding trials, germplasm evaluation, and small-batch seed harvesting. Compared with conventional field combine harvesters, they have higher requirements for sample independence, grain integrity, seed purity, low residual grain, rapid plot switching, and plot-level data reliability. However, existing studies remain relatively fragmented, and many studies mainly focus on individual components, whereas analyses of whole-machine coordination, residual-grain control, crop adaptability, and data integration remain insufficient. This paper presents a structured review of the research progress in plot combine harvesters from an agricultural-engineering perspective, covering representative international and domestic models, headers, threshing and separation systems, cleaning systems, residual-seed removal devices, simulation methods, intelligent monitoring, and seed-quality sensing. Existing evidence indicates that plot combine harvesters are developing toward whole-machine low-residue design, coordinated threshing–cleaning–conveying optimization, standardized evaluation methods, sample identification, data traceability, and long-term field validation under continuous multi-plot harvesting conditions. Key challenges include coordinating small-batch intermittent material flow, controlling residual grain during frequent plot switching, balancing threshing completeness with seed protection, improving adaptability to different crops and breeding materials, and validating intelligent sensing technologies under field conditions. This paper provides an engineering reference for improving the mechanization, precision, and intelligence of breeding-trial harvesting equipment. Full article

Oral squamous cell carcinoma (OSCC) frequently develops within chronically injured oral mucosa and may be preceded by clinically recognizable oral potentially malignant disorders (OPMDs), which provide an important window for cancer interception. This review examines how etiological exposures, persistent inflammation, and lesion-specific epithelial–stromal–immune interactions cooperate during the transition from mucosal injury to dysplasia, carcinoma in situ, and invasive OSCC. Major carcinogenic exposures, including tobacco, alcohol, and areca nut, are considered together with context-dependent contributors such as microbial dysbiosis, viral infection, and immune-mediated epithelial injury. At the molecular level, inflammation-driven oral carcinogenesis involves cytokine and chemokine amplification, oxidative and nitrosative stress, NF-κB and STAT3 activation, the COX-2/PGE₂ axis, genomic instability, field cancerization, epithelial–stromal crosstalk, angiogenesis, immune dysregulation, and epigenetic and non-coding RNA-mediated reprogramming. Emerging tools such as molecular risk assessment, liquid biopsy, optical imaging, spatially resolved profiling, and artificial intelligence-assisted models may improve identification of high-risk lesions, although most biomarkers require further prospective validation. Prevention should therefore integrate exposure control, biopsy-based diagnosis, local treatment when indicated, long-term surveillance, and trial-based precision strategies according to lesion risk, intervention window, and safety profile. This review supports a shift from lesion-centered management toward risk-adapted precision prevention in inflammation-driven oral carcinogenesis. Full article

The sulphate–carbonate karst in the southern part of the Bratsk Reservoir has been active throughout the reservoir’s operation. Long-term monitoring of the coastal zone, interpretation of multi-temporal images, and field studies at the Khadakhan key site resulted in the creation of a conceptual model of coastal geosystem functioning in areas of sulphate–carbonate rock development under conditions of long-term and seasonal fluctuations in the reservoir water level. The structure of interactions within the coastal geosystem is organized at three hierarchical levels: (1) the intra-rock level, (2) the level of interacting factors, and (3) the level of interacting exogenous geological processes, whose activation is driven by an external factor—changes in the reservoir’s water level. We identified five stages of gully formation and the cyclic nature of the karst–erosion process in the coastal geosystem under conditions of seasonal and long-term reservoir water-level fluctuations. Our findings indicate that, when regulating reservoir water levels, dramatic drawdowns should be avoided. This conceptual model aims to improve the understanding of the impact of large reservoir operation on the dynamics of a complex of interacting coastal processes, as well as on the peculiarities of karst development in a boreal climate. Full article

Protecting the safety and well-being of children in public child welfare is one of the most critical and demanding jobs in social work. Burnout, secondary traumatic stress, and moral injury are prevalent in this field and often occur simultaneously. This intersectional experience impacts the deepest level of a person—their soul. When left unaddressed, these soul wounds come at a high cost to the workers, organizations they work for, the clients they serve, and their greater communities. This qualitative study sought to explore and identify the characteristics of soul care and the power it has to transform the lived experiences of child welfare workers. Collaborative, semi-structured interviews were conducted with seven workers who had been in this field for 10 or more years and described themselves as having good soul care. Findings from this study concluded the combination of strongly held core beliefs and engagement in a steady regulation loop constituted soul care. Soul care can occur regardless of circumstance. When a soul wound occurs, the Soul Wound Cycle is activated. The momentum of the regulation loop propels one’s movement through this cycle, allowing the processing of the soul wound, resulting in increased resiliency and regaining of equilibrium, ultimately leading to better outcomes for children. Full article

This study evaluated the effects of expected progeny difference (EPD) grade and feeding system on carcass performance in Hanwoo steers using a large-scale field dataset collected under commercial production conditions. Records from 4561 steers (1466 fed total mixed fermented feed [TMF] and 3095 on a conventional separate-feeding system) across 269 farms in Korea from January 2023 to May 2025 were analyzed. Expected progeny difference grades for carcass weight (CWT), backfat thickness (BFT), ribeye area (REA), and marbling score (MBS) were classified A-D. Carcass performance significantly differed among EPD grades. Compared with grade D, grade A steers exhibited greater CWT (45.2 kg), less BFT (3.44 mm), greater REA (10.77 cm²), and greater MBS (1.57 units). Genetically superior animals reached slaughter age earlier. Steers fed TMF demonstrated higher CWT, BFT, REA, and MBS than conventionally fed steers. No significant interaction between EPD grade and feeding system was found for any carcass trait. These results indicate that EPD grades consistently predict carcass performance across different feeding environments, while TMF improves the absolute level of carcass traits. This large field dataset demonstrates that integrating Hanwoo EPD information with appropriate feeding management may support more efficient and profitable carcass production under commercial farm conditions. Full article

Pose estimation is an important task in the field of machine vision, being widely used in robot grasping, augmented reality, and other applications. Weakly textured objects pose severe challenges due to scarce texture and low-density features, becoming a bottleneck in robot grasping. This paper systematically reviews recent progress in weakly textured object pose estimation, classifying methods into traditional and deep learning categories, and further dividing deep learning methods into instance-level, category-level, and unseen object-level. This review further summarizes the core issues of generalization limitations, real-time contradictions, and data bottlenecks in existing research. Combined with the practical needs of weakly textured scenes, the review points out that multimodal fusion optimization, lightweight model design, and low-cost annotation technology development are the future core research directions. The research results can provide a reference for algorithm design, experimental verification, and engineering applications in the field of weakly textured object pose estimation. Full article

Six different twin boundary interface models were constructed by molecular dynamics simulations to investigate the effect of biaxial load ratio on the fracture behavior of titanium twin boundaries. Analysis of microstructural evolution indicates that twin boundaries exhibit a dual role during crack propagation. On one hand, they serve as preferential sites for void nucleation, promoting crack propagation along the twin boundary; on the other hand, they provide favorable sites for dislocation nucleation, inducing local plastic deformation at the crack tip, altering the crack path, and thereby hindering crack propagation. The crack propagation behavior in the ($\overline{1}0$11) and ($\overline{1}0$13) twin boundary models shows evident asymmetry: the crack on the left side mainly propagates through the void nucleation mechanism and exhibits a faster growth rate, while the right-side twin boundary inhibits crack propagation by favoring dislocation nucleation. In contrast, the crack propagation behavior in the ($\overline{1}0$12), ($\overline{2}1$11), ($\overline{2}1$12) and ($\overline{2}1$14) twin boundary models is largely symmetric on both sides, showing no significant difference in propagation rate. Stress field analysis further reveals that the differences in crack propagation behavior among the various twin boundary models mainly originate from the disparity in dislocation activity on both sides of the crack, resulting in different levels of stress concentration at the crack tip. When void nucleation occurs at the twin boundary interface, the stress concentration between the main crack and the void intensifies, promoting their coalescence and further propagation. Meanwhile, with an increase in biaxial load ratio, the stress concentration at the crack tip becomes more pronounced, further accelerating crack propagation. Full article

For nearly a century, since the discovery of penicillin by Alexander Fleming, we have used covalent inhibitors as antimicrobial drugs. The success of penicillin in treating microbial infections led to numerous other antibiotics containing β-lactam, the reactive warhead that forms the covalent adduct, exemplified by later-generation cephalosporins with approvals into 2020. In parallel, early non-β-lactam covalent agents also emerged, extending covalent mechanisms beyond β-lactam antibacterials to antifungal, antiparasitic, and antiviral applications. Despite the successes of covalent mechanisms of action, there are still considerable safety concerns due to the possibility of off-target covalent adducts which may lead to significant side effects. This review provides an overview of non-β-lactam covalent antimicrobials across all major pathogen classes, organized by their warhead class, covalency, and resistance mechanisms, and outlines design and clinical-level mitigation strategies. We trace the field from the serendipitous discovery of penicillin to the intentional design of new drugs, with a discussion of changes in perception and evolution of technology that enable modern covalent drug design. Full article

Biomass valorization plays a vital role in achieving carbon neutrality and circular economy frameworks. Owing to its carbon-rich structure, biomass represents a promising feedstock to produce bio-based hydrocarbons via biological and thermochemical pathways. While biological conversion routes have been extensively studied, their deployment at commercial scale is constrained by high capital costs and low product yields. In contrast, thermochemical conversion technologies are increasingly being explored as viable large-scale biomass valorization routes. This review presents a comprehensive assessment of thermochemical pathways, with particular emphasis on hydrothermal liquefaction (HTL). The review identifies hydrothermal liquefaction (HTL) as a strategically advantageous route for wet and heterogeneous biomass valorization, due to simultaneous yields of liquid biocrude, and solid hydrochar. The review emphasizes the application of biocrude upgradation processes like hydrodeoxygenation under biphasic solvent systems using sulfided NiMo and CoMo catalysts. Further, the review also establishes hydrochar as a tunable functional material rather than a mere byproduct for applications in fields of energy production, soil amendment, and heterogeneous catalysis. The review article examines technology readiness levels of different biomass valorization techniques, and suggests that while combustion, anaerobic digestion, torrefaction, and transesterification are commercially mature, HTL and carbon capture utilization and storage (CCUS)-integrated fuel synthesis pathways remain at intermediate readiness. Additionally, the review carries out an in-depth study on artificial intelligence and machine learning (AI and ML) applications in biomass valorization, where it observes that Tree-based ensemble models, particularly Random Forest and XGBoost, show strong performance for several HTL prediction tasks, while Gaussian Process Regression and neural network–Bayesian optimization approaches provide additional advantages for uncertainty estimation and process-level optimization. Finally, the future research opportunities in biomass valorization and AI/ML application in HTL-process optimization have been identified for improving the bio-based fuel production techniques. Full article

African soils face increasing levels of metal pollution due to industrialization, artisanal mining activities, improper waste management, and enhanced agricultural productivity. However, unlike many organic pollutants, heavy metals do not degrade naturally and therefore persist in environmental systems for prolonged periods. Heavy metals accumulate over many decades in the soil and bioaccumulate through the food chain causing severe health complications such as cancer, kidney problems, and neurological impairment. This paper reviews the current literature on the origin, prevalence, and behavior of the main pollutants Pb, Cd, Cr, As, Hg, and Cu. The major phytoremediation methods including phytoextraction, rhizofiltration, phytostabilization, and phytovolatilization are highlighted alongside in planta screening methods for hyperaccumulating plants including Berkheya coddii (Ni) and Haumaniastrum robertii (Co). The paper evaluates various enhancement techniques such as the use of chelators, Rhizobium inoculations, and genetic modifications. The significance of these approaches in tropical and subtropical climates is discussed. The paper suggests a holistic framework involving empirical kinetic modeling, geospatial machine learning (random forest, kriging), and molecular omics in prediction modeling. Major hurdles in such predictions include lack of field-based verification of the models, biotechnology safety of genetically modified (GM) organisms, and inadequate regulations. Future perspectives emphasize community-driven phytomining, biomass recycling, and resilient phytoremediation solutions. Full article

Individual tree crown (ITC) segmentation in structurally complex mixed forests remains challenging under limited annotation, uneven effective height-structure support, and severe inter-crown adhesion. Existing end-to-end instance segmentation methods often require substantial instance-level annotation, and their cross-domain transferability can degrade when applied to plots with different forest structures. This study proposes a probabilistic prior-constrained instance reconstruction framework that treats semantic segmentation output as an interpretable canopy prior and reconstructs object-level crowns through a structured post-processing pipeline. A height-aware canopy support mask (HCSM) converts the probability field into a credible operational domain through hysteresis thresholding, morphological reconstruction, and a height constraint. Constrained recovery within the support domain (E2GROW) repairs coverage deficiency through spatially bounded boundary adjustment with guard rails on area ratio and buffer distance. Selective splitting then addresses residual merge errors through branch-specific seed-guided partitioning, including an aggressive Voronoi reference branch and a more conservative LOCAL/marker-controlled watershed branch with explicit trigger and child-object filtering criteria. An instance-level evaluation loop based on Gate-3 Recall, a precision proxy, and threshold-crossing audits is used during module development as an iterative safeguard. On a single 500 × 500 m mixed conifer–broadleaf plot with 306 reference crowns retained for evaluation, the high-Recall VORv1 branch improves Recall from 0.369 to 0.673 over the internal R2 baseline produced by the semantic-prior-to-instance initialization procedure, whereas the balanced E2GROW configuration achieves the highest F1_proxy with fewer predicted objects; the overall gain originates from two distinct mechanisms: threshold-crossing boundary recovery for coverage-deficient crowns and local structural decomposition for merged crown groups. Sensitivity analysis indicates that the support-domain construction is stable across the explored parameter ranges, and that the two splitting branches realize a structural Recall–precision trade-off with no evidence of simple additive gains. The framework is modular and auditable, and its demonstrated applicability is strongest for annotation-scarce closed-canopy plots where a usable semantic canopy prior and height information are available. The reported evidence represents a single-site, within-plot methodological demonstration. Full article

Safety management evaluation in highway tunnel construction involves significant complexity due to multi-level, multi-indicator, and uncertain characteristics. To address these challenges, this study proposes an integrated evaluation approach combining the Analytic Hierarchy Process (AHP), Entropy Weight Method (EWM), and Set Pair Analysis (SPA). An evaluation index system is established from the perspective of system defensive capability, encompassing four dimensions—organizational, personnel, material, and information management—with 19 indicators. SPA is employed to quantify the relationships among indicators through identity, discrepancy, and opposition, while a hybrid weighting scheme combines subjective judgments and objective data. A confidence-based identification criterion is further introduced to improve the robustness of classification. The proposed model is applied to a highway tunnel project, and the results show good agreement with observed field conditions. The analysis indicates that the method effectively captures intermediate states and uncertainty in safety management systems while reducing bias associated with single weighting strategies and maximum membership-based decisions. The proposed framework provides a practical and reliable approach for safety management evaluation and supports risk-informed decision-making in tunnel construction. Full article

Soil salinization poses a significant global challenge to agriculture and the environment, leading to decreased soil fertility and hindered crop growth. Therefore, the development of effective and environmentally friendly soil improvement strategies is crucial for sustainable agriculture. In this study, a range of eco-friendly, versatile, and highly absorbent hydrogels for soil enhancement were created using itaconic acid (IA) as a hydrophilic monomer. Furthermore, their effectiveness and application in agriculture were thoroughly evaluated. The nano-iron-loaded IA-based hydrogels (nano-iron (III) oxide (nano-Fe₂O₃)/Poly itaconic acid (PIA)-Acrylamide (AM)/Sodium alginate (SA)) hydrogels demonstrated exceptional water absorption and retention capabilities. They exhibited remarkable soil conditioning properties by leveraging carboxyl groups for electrostatic adsorption of saline ions and the porous structure created by the crosslinked network. These features not only significantly facilitated gradual regulation of pH levels and salinity but also effectively enhanced organic matter in saline–alkali soil. Meanwhile, nano-Fe₂O₃ simultaneously served to stabilize the hydrogel structure and enhance crop nutrient absorption. Wheat cultivation trials demonstrated that the hydrogels notably enhanced the growth of 7-day-old wheat seedlings. The degradation rates of the hydrogels can be adjusted by varying the IA amount, allowing for the continuous release of small organic molecules to enhance soil quality, aligning with various crop growth cycles. Overall, these hydrogels function as environmentally friendly and versatile soil conditioners, offering significant potential for enhancing agricultural soil quality and expanding into related fields. Full article