Search Results (2,067)

Stem lodging significantly reduces soybean yield stability, particularly under dense planting and intercropping systems. Stem breaking strength is a key component of lodging resistance, but its genetic basis remains incompletely understood. In this study, an F₂ population consisting of 167 individuals derived from a cross between nanxiadou25 (NXD25, high stem breaking strength) and Shiyuehuang (SYH, low stem breaking strength) was analyzed using bulked segregant analysis with whole-genome resequencing (BSA-Seq) to identify loci associated with stem breaking strength. The trait showed broad quantitative variation in the F₂ population, ranging from 20.1 to 673.7 N. Two extreme bulks were constructed using 30 plants with the highest values and 30 plants with the lowest values. QTL-seq detected 21 candidate intervals at the 95% confidence level, among which, three major loci on Chr07, Chr13, and Chr16 exceeded the 99% threshold and were designated qBR7.2, qBR13.1, and qBR16.1. By integrating large-effect SNP/InDel variation, marker development, RNA-seq profiling, and qRT-PCR validation, nine candidate genes were retained for further study, and three marker-linked genes were highlighted as high-priority candidates. RNA-seq identified 9617 differentially expressed genes between the two parents. In addition, three co-dominant InDel markers, Chr07_01, Chr13_17, and Chr16_83, showed phenotype-consistent polymorphism in extreme F₂ individuals. These findings provide valuable loci, candidate genes, and molecular markers for soybean lodging-resistance breeding. Full article

Salt cavern Compressed Air Energy Storage (CAES) is one of the critical technologies for energy storage and an important infrastructure supporting the construction of new power systems and facilitating the achievement of the dual carbon goals. The salt rock resources in China are primarily composed of continental strata salt rocks, characterized by high heterogeneity, well-developed thin-layer interbedding, dissolution resistance among different lithologies, and significant creep variations. These features, to some extent, limit the improvement of wellbore construction accuracy, the reliability of abandoned well sealing, the safety of natural gas storage operations, and enhancements in gas injection–brine displacement efficiency. This study takes the continental bedded salt rock in the Dawenkou Basin as the research object and adopts a method combining theoretical analysis and field engineering verification to improve the systematic construction technology system, covering the whole process of drilling engineering, abandoned well plugging, the design of an injection and brine extraction device, and gas injection and brine drainage. The research results optimize four key technologies, including precise wellbore trajectory control, dual-section milling, and multi-stage redundant plugging of abandoned wells and long-term anti-corrosion completion with laser cladding, and dual-mode adaptive gas injection and brine drainage, and improve the technical system from wellbore construction to salt cavity formation. This study can provide valuable theoretical references and engineering demonstration guidance for underground space development projects in similar salt basins in China. Full article

Background/Objectives: Pancreatic cancer (PC) should be diagnosed in its early stages. Therefore, it is necessary to identify high-risk individuals of PC. Methods: Between 2001 and 2017, 1542 PC cases were diagnosed at two tertial care institutions. Of these, 117 cases had undergone abdominal contrast-enhanced computed tomography (CE-CT) 1–10 years before PC diagnosis and were classified as the PC group. Meanwhile, 43,102 cases underwent abdominal CE-CT for close examination of non-pancreatic diseases in the same period, of which 1170 were randomly selected. Of these, 117 cases were matched to the PC group with the propensity score and designated the non-PC group. Pancreatic volumetry was performed using the 3D image analysis system for abdominal CE-CT in both groups and various measurements were compared. In PC group, CE-CT taken 1–10 years before the onset of PC was analyzed. Results: After propensity score matching, baseline characteristics did not significantly differ between the two groups. The whole pancreatic volume/body surface area (BSA) (p = 0.014), volume of main pancreatic duct (MPD) plus cystic lesion/BSA (p < 0.001), volume of pancreatic parenchyma/BSA (p = 0.002), ratio of cross-sectional areas (p = 0.033), and MPD diameter/BSA (p < 0.001) significantly differed between the two groups. In subgroup analysis of patients without cystic lesions, the whole pancreatic volume/BSA, volume of MPD/BSA, volume of pancreatic parenchyma/BSA, ratio of cross-sectional areas, and MPD diameter/BSA significantly differed between the two groups. Conclusions: Pancreatic volumetry could identify patients at high risk of PC. Full article

Auditory neurofeedback training (NFT) based on brain–computer interfaces (BCIs) has recently entered the precision motor domain as a task-embedded neural state regulation paradigm. Compared to traditional standalone NFT approaches (e.g., relaxation or attention training designed to enhance general cognitive abilities), task-embedded paradigms integrate feedback directly into the motor task execution process. However, this design inevitably creates a dual-task scenario, and the effects of such a scenario on neural activity and behavioral performance have received limited systematic investigation in the existing literature. This study designed and implemented a closed-loop BCI system employing five-level heartbeat sound feedback and used this system as a research platform to examine the immediate neural mechanism changes and potential dual-task interference effects induced by single-session auditory NFT in moderately skilled shooters. The system maps real-time EEG features onto graded auditory signals varying in playback rate and volume intensity, incorporating a dynamic threshold adjustment mechanism. Twenty-two moderately skilled shooters completed three within-subject conditions (no-sound baseline, SMR enhancement, and theta suppression) in a single session with 32-channel EEG and behavioral data recorded simultaneously. Analyses employed whole-brain cluster-based permutation tests, cross-frequency coupling analysis, and functional connectivity analysis. Cluster-based permutation tests revealed that theta feedback induced a significant frontal 4–7 Hz suppression cluster (cluster p = 0.004), whereas SMR feedback did not produce significant 12–15 Hz enhancement at the group level. Theta feedback elicited cross-frequency spillover as follows: sensorimotor SMR power decreased significantly in theta responders (d = −0.69), with frontal theta and sensorimotor SMR changes positively correlated (r = 0.67, p < 0.001). Functional connectivity analysis using debiased weighted phase lag index (dwPLI) further demonstrated significant theta-band network reorganization (cluster p = 0.034). At the neural level, clear modulation effects were observed, but shooting ring values did not improve significantly under feedback conditions, and aiming time was significantly prolonged—a behavioral pattern consistent with potential dual-task interference from task-embedded auditory feedback. Single-session auditory NFT can act on the prefrontal cognitive control network and induce cross-frequency network reorganization, but the feedback channel itself constitutes a parallel task that may limit the short-term transfer of induced neural states to behavioral performance. This study examined the neural mechanisms of task-embedded auditory NFT and reported the dual-task costs that have been less characterized in prior “task + feedback” research, providing design considerations and preliminary mechanistic evidence for future development of auditory NFT in precision motor skill training. Full article

Artificial intelligence (or AI) is rapidly transforming digital learning environments, reshaping how educational processes are organized, how knowledge is produced, and how learning is evaluated. Despite a growing body of research on AI in education, existing studies often examine technological, pedagogical, and ethical dimensions in isolation, leaving a lack of integrative frameworks capable of explaining how AI restructures learning environments as a whole. This study addresses this gap by proposing a three-layer conceptual framework that models AI-mediated learning environments through the interaction of efficiency, pedagogy, and ideology. The framework conceptualizes AI integration as a system of interdependent processes: the efficiency layer captures the optimization of educational activities through automation and data-driven personalization; the pedagogical layer explains how AI reshapes learning processes, feedback cycles, and learner strategies; and the ideological layer examines the normative assumptions embedded within AI systems, including issues of epistemic authority, linguistic norms, and algorithmic bias. Drawing on a structured synthesis of recent empirical research across domains such as generative AI tools, automated feedback systems, intelligent tutoring systems, and AI-supported assessment, the study demonstrates how these dimensions interact to structure contemporary digital learning environments and generate both affordances and tensions. The main theoretical contribution lies in advancing a system-level analytical framework that moves beyond tool-specific approaches and enables a more integrated understanding of AI in education. In practical terms, the framework provides educators and policymakers with a lens to critically evaluate AI integration, supporting more informed decisions on assessment design, sustainable learning practices, and inclusive digital education. Full article

A dual-mode variable gain amplifier (VGA) with a wide-dynamic-range is proposed in this paper. The VGA is designed in a 0.18 μm CMOS process, and it has a body-driven variable load cell and binary gain array structure to implement both the digitally stepped programmable gain amplifier (PGA) mode and the analog-controlled VGA mode. This design removes additional digital conversion modules when integrated into an automatic gain control (AGC) loop, which simplifies the whole system architecture significantly. The design is also able to address several limitations of conventional VGAs, such as a single control mode, low AGC compatibility, and a narrow gain range. The simulation results after post-layout indicate that at PGA mode, the design has an ultra-wide gain band of −0.03 to 126.9 dB with a constant gain step of 1 dB. And in VGA mode, it allows smooth, continuous gain adjustment over a large range of −25.3 dB to 187.4 dB. The bandwidth of −3 dB is more than 45 MHz in both modes. The whole VGA uses 1.026 mW and has a core size of 0.011 mm². The output 1-dB compression point (OP1dB) was −1.57 dBm at minimum gain in the PGA mode and −4.02 dBm in the VGA mode. Besides, PVT analysis, Monte Carlo simulations and AGC system-level verification are evident enough to prove that the suggested VGA has high immunity to PVT (Process, Voltage, Temperature) variations, stable processes and high practicality in engineering applications. Full article

Chromium slag, a chromium-bearing solid waste characterized by substantial environmental hazards yet with appreciable resource potential, has become a focal topic in solid-waste pollution control and the circular economy. Centered on the overarching logic of “evidence chain–system boundary–scalable and verifiable acceptance,” this review systematically synthesizes recovery technologies, industrial-scale utilization pathways, and the key challenges associated with the detoxification and resource utilization of chromium slag. From the perspective of recovery technologies, we examine pyrometallurgical and hydrometallurgical routes, solidification/stabilization (S/S), and bioelectrochemical coupling approaches, elucidating their fundamental principles, applicability boundaries, and critical nodes where environmental burdens may be transferred across media. We emphasize that process design should concurrently consider detoxification efficiency, resource recovery performance, and whole-process pollution control. Regarding utilization pathways, this review highlights three major routes with strong scale-up relevance—metallurgical process co-treatment (CAP–sintering–blast furnace), bulk utilization in construction materials, and high-value utilization—and analyzes their industrial potential and engineering constraints. Particular attention is given to the lack of long-term leaching and durability evidence, which represents a central bottleneck limiting product-side credibility. Furthermore, we discuss cross-cutting challenges including the long-term stabilization of Cr(VI), the verifiability of “green utilization” concepts, cost and economic feasibility, and standardized acceptance criteria. We propose that future research should shift from single-process optimization toward multi-objective, system-level evaluation, and establish a full-chain evidence system covering “speciation/mineral phases–process mechanisms–environmental behavior–risk assessment–engineering scale-up–standardized acceptance.” This review aims to provide a systematic analytical framework and practical reference for improving comparability across resource-utilization technologies and supporting engineering decision-making for chromium slag management. Full article

Background/Objectives: Opioid use disorder (OUD) is caused by a complex interplay between genetic and non-genetic factors. DNA methylation is an epigenetic mechanism that modulates gene expression. Data on DNA methylation and opioid addiction and treatment are limited. This association study was designed to assess the difference in genome-wide methylation patterns between individuals with OUD in methadone maintenance treatment (MMT) (n = 114) and those with OUD who achieved long-term abstinence (>10 years) without mu opioid receptor agonist treatment (n = 136). Methods: Differential DNA methylation analysis was performed in whole blood using the Illumina EPIC array. Results: A total of 135 differentially methylated probes (DMPs) reached epigenome-wide significance (p < 1 × 10⁻⁷), controlling for sex, age, estimates of blood cell proportions, and the first two principal components based on genome-wide SNP genotypes. The methylation sites were annotated to 157 genes, including 32% long non-coding RNAs. These genes are related to several systems, including cell adhesion (e.g., SAXO4), immune system and inflammation (e.g., UBTF, USP39, C10orf90, PRKCA), stress response (e.g., CRHR1, GPR19), and spermatogenesis (e.g., SPATA16, COX7B2). DMP cg11641410 is located in lncRNA ENSG00000254687, an antisense to OPRK1. Six of the DMPs were also identified in a related longitudinal study of MMT. Conclusions: At this point, it is not possible to determine whether the minor methylation differences observed in this study cause clinically relevant changes in gene expression. However, these findings have the potential to identify biomarkers and to provide new targets for treatment optimization. Full article

Indigenous sheep breeds represent valuable reservoirs of genetic diversity shaped by long-term adaptation to local environments and management systems. Greek autochthonous sheep breeds remain underrepresented in genomic and functional studies. The objective of this study was to characterize and compare coding sequence variation in three indigenous Greek sheep breeds—Lesvos (LES), Serres (SER), and Thrace (THR)—and to identify shared and breed-associated functional patterns. The study was designed using a two-stage approach, comprising a discovery (exploratory) phase and a validation phase. In the discovery phase, whole genome sequencing data (one animal per breed; total n = 3; mean sequencing depth ~36.9×) were analyzed to identify protein-altering exonic variants, focusing on missense single-nucleotide polymorphisms (SNPs) and exonic insertions/deletions (indels). Variants were examined at breed-specific and comparative levels, followed by functional enrichment analyses using Gene Ontology (GO) and KEGG pathways. Normalized variant density metrics identified genes with elevated polymorphism levels. In the validation phase, a subset of prioritized missense SNPs was genotyped in an independent cohort of 54 animals (18 per breed) using MassARRAY genotyping. Genes harboring prioritized missense SNPs showed a conserved enrichment profile across breeds, dominated by genome maintenance, DNA repair, cytoskeletal organization, and core regulatory functions. Distinct breed-associated patterns were also observed. LES showed enrichment in metabolic, biosynthetic, and sensory-related processes, SER in regulatory and signaling functions, and THR in cytoskeletal, extracellular matrix, and organelle-associated pathways. Polymorphism density analyses highlighted highly variable genes across breeds, including olfactory receptor (OR) gene families, keratin-associated protein genes (KRTAPs), and loci involved in immune and regulatory functions (e.g., PRKDC, CDH15). The validation phase confirmed the expected allele frequency patterns for most prioritized SNPs, supporting the robustness of the approach. This study identifies functionally relevant coding variation across Greek indigenous sheep breeds, revealing conserved genomic patterns and breed-associated signatures linked to metabolic, structural, and regulatory processes. Full article

Within the context of the UN 2030 Agenda for Sustainable Development and Education for Sustainable Development (ESD), this study draws on a Web of Science dataset (n = 815, 1991–2025) and employs a mixed approach combining scientometric mapping with framework analysis and tool comparison. It systematically reviews the knowledge structure, methodological evolution, and tool genealogy of Campus Sustainability Assessment (CSA). The results reveal a paradigmatic shift from an operations-oriented focus to a whole-of-institution and impact-oriented perspective. Representative tools can be grouped into five categories by purpose—improvement-oriented, ranking and benchmarking, education and curriculum, standards and certification, and policy advocacy and recognition—and can be mapped onto the four domains of governance, academics, operations, and engagement in alignment with the Sustainable Development Goals (SDGs). Synthesizing quantitative and qualitative evidence, three systemic shortcomings are identified: excessive reliance on self-reporting with limited verification, insufficient evidence of learning outcomes and key competencies, and weak interoperability of indicators across educational stages and frameworks. Looking ahead, four actionable research pathways are proposed: (1) assessment of key competencies centered on learning outcomes with stronger curriculum–practice alignment; (2) policy–indicator interoperability and vertical integration grounded in SDGs and national or sectoral standards; (3) stakeholder co-design enabling an assessment–improvement loop; and (4) remote-sensing-based multi-scale monitoring and data governance. The contribution of this study lies in advancing a unified four-domain framework under a process–outcome–impact evidence chain, while suggesting cross-stage and cross-tool alignment and complementarity. This provides methodological support and an implementation roadmap for shifting CSA from measuring performance to empowering improvement. Full article

Concrete building systems require decisions at both the member and the building level, because locally efficient cross sections do not necessarily lead to a favorable whole-building response. This study presents a two-level comparative framework comprising (i) a member-level parametric assessment of nine reinforced-concrete and composite cross-section families across six concrete grades (54 scenarios) and (ii) a building-level ETABS assessment of seven structural configurations (Models A–G) derived from a residential reinforced-concrete frame benchmark. At the member level, the alternatives were evaluated based on axial resistance, along with simplified screening-level CO₂ and cost proxies. At the member level, axial resistance increased with concrete grade, although the marginal benefit diminished at higher grades for steel-dominant layouts. Balanced composite sections showed the most favorable normalized strength-to-material-proxy trends, whereas steel-heavy alternatives provided high absolute resistance but lower overall efficiency. The comparison between the member-level hybrid-section screening and the building-level composite configuration further showed that promising local section behavior does not automatically translate into superior whole-building performance. At the building level, the compared configurations were assessed through vertical base reactions, modal properties, and top-level lateral displacement response. Replacing solid beams and columns with hollow members of identical outer dimensions reduced the self-weight-related base reaction from 9591 to 8832 kN (7.9%) but slightly increased the top-level displacement response, indicating a mass–stiffness trade-off. Larger improvements were obtained when the global lateral-force-resisting mechanism was modified directly: the braced configuration produced the shortest fundamental period ($T_1=0.433$ s) and the lowest displacement response, while the core-wall configuration also reduced both period and displacement substantially. By contrast, the height-extended configuration produced the most flexible response among Models A–F. An additional exploratory variant with semi-rigid beam-to-column connections (Model G) confirmed that connection-level flexibility produces a measurable but moderate increase in period and displacement relative to the reference frame, without altering the global load-resisting mechanism. Overall, the results confirm that member-level and building-level assessments should be treated as complementary decision levels in early-stage structural design. Full article

Automated cellular detection using deep learning is a key strategy for optimising cervical cancer screening by reducing the healthcare workload and inter-observer variability. However, analysing Whole Slide Image (WSI) patches presents challenges such as annotation scarcity, morphological complexity, and class imbalance. This study systematically evaluates YOLO11-n, YOLO11-s, and YOLO11-m to assess the impact of target variable granularity and training paradigms on performance. Four strategies were analysed: independent and multi-class models, each evaluated at both the specific cell label and diagnostic macro-group levels. To ensure clinical robustness, patient-level data partitioning was implemented to prevent data leakage. Performance was measured using precision, recall, and mAP (0.5 and 0.5:0.95). The results reveal critical trade-offs between fine-grained discrimination and model generalisation when varying the architectural complexity and labelling strategies. The findings indicate that diagnostic aggregation improves stability, whereas single-class training optimises specialised detection. These results provide methodological guidelines for designing AI-assisted screening systems and may inform future extensions of WSI-level diagnostic pipelines. Full article

Dietary antioxidants and phytochemicals are believed to support cognitive health, but evidence on composite dietary indices remains limited. This cross-sectional study of 1845 community-dwelling older adults in China investigated the associations of the composite dietary antioxidant index (CDAI) and dietary phytochemical index (DPI) with cognitive function and mild cognitive impairment (MCI). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA; Beijing version). MCI was diagnosed through a two-stage procedure: MoCA-based preliminary screening (with education-stratified cutoffs: 13/14 for illiterate, 19/20 for 1–6 years, 24/25 for ≥7 years) followed by neurologist confirmation. CDAI was calculated as the sum of the standardized intakes of six antioxidants (selenium, zinc, carotenoids, vitamin A, vitamin C, vitamin E); DPI was defined as the percentage of the total energy intake from phytochemical-rich foods (fruits, vegetables excluding potatoes, legumes including soy products, nuts, seeds, and whole grains). Multivariable linear regression, logistic regression, and receiver operating characteristic (ROC) curve analyses were performed. The basal metabolic rate (BMR) and systemic immune-inflammation index (SII; platelets × neutrophils/lymphocytes) were tested as potential statistical mediators. Each one-unit increase in CDAI was associated with a 0.068-point higher MoCA score (95% CI: 0.012–0.123), and each one-unit increase in DPI was associated with a 0.029-point higher MoCA score (95% CI: 0.008–0.050). BMR and SII partially mediated the association between CDAI and MoCA score, but temporal ordering remains unclear due to the cross-sectional design. When both CDAI and DPI were in the highest quartile, participants had a 46.3% lower risk of MCI compared with those with both indices in the lowest quartile (OR = 0.537, 95% CI: 0.308–0.935). A predictive model incorporating CDAI, inflammatory markers, and red blood cell parameters showed moderate discriminatory ability in this study sample (apparent AUC = 0.731, bootstrap-corrected AUC = 0.728). These findings suggest that a higher combined dietary antioxidant and phytochemical intake may be jointly associated with better cognitive function, although the cross-sectional design precludes causal inference. Full article

Background: Governments increasingly seek whole-system, public-health approaches to prevent serious youth violence. However, there is limited empirical evidence on how such approaches are implemented and sustained in complex, post-conflict settings characterised by coercive control, political instability, and fragmented system ownership. Aim: This study examines the Executive Programme on Paramilitarism and Organised Crime (EPPOC) in Northern Ireland as a system-level implementation architecture for addressing serious youth violence, with a focus on how coordinated action was enabled, constrained, and adapted over time. Methods: We conducted an embedded qualitative case study of EPPOC using systematic analysis of programme documentation, independent evaluations, oversight reports, and population-level data spanning nine years of delivery. Implementation science frameworks (ERIC, Proctor’s implementation outcomes, and CFIR) were applied retrospectively as analytic lenses to examine implementation strategies, outcomes, and contextual determinants. Results: EPPOC demonstrated strong implementation outcomes in acceptability and adoption across statutory and community sectors, supported by cross-government governance, trauma-informed workforce development, and shared learning systems. Penetration and sustainability were more variable and constrained by political instability, short-term funding cycles, uneven departmental ownership, and coercive community conditions. Conclusions: The findings suggest that the most transferable element of EPPOC is not individual interventions but the implementation architecture that enabled coordinated, trauma-responsive action across government in a highly complex environment. This architecture represents a potentially replicable design pattern for jurisdictions seeking to address serious youth violence where traditional programme models struggle to operate. Full article

This paper proposes an adaptive augmented anti-disturbance load relief control scheme for a solid launch vehicle. It can effectively satisfy the composite control requirements including high-precision attitude control, resistance to elastic frequency deviations, sudden wind disturbances, and active load relief. Firstly, the dynamic model of the elastic solid launch vehicle was established and subjected to small-perturbation linearization. Based on the state-space approach, the open-loop transfer function of the system was derived, and a basic PD controller with correction networks was presented. Subsequently, an adaptive augmented control law was designed to achieve adaptive variation in open-loop gain. Furthermore, a load relief control law was designed to address the launch vehicle’s need for load mitigation during the ascent phase through high-wind regions. Simultaneously, to further enhance disturbance rejection capability, a linear extended state observer was developed. Finally, frequency-domain methods and sinusoidal function analysis were applied to the four designed modules to evaluate the system’s stability margins, and the overall stability margin of the whole control system was calculated. Comprehensive time-domain simulation results and frequency-domain analysis examples demonstrate the effectiveness of the proposed method, which offers a novel solution for launch vehicle ascent control and facilitates meeting multi-constraint control requirements. Full article