Search Results (391)

Rubber aggregate concrete (RAC) offers excellent frost resistance and impact toughness, but the incorporation of rubber particles substantially reduces its compressive strength, limiting structural applications. Existing improvement strategies have mainly relied on a single modification route, whereas the dynamic compressive response of RAC containing both ceramic balls and steel fibers remains insufficiently clarified. Here, a ceramic ball–steel fiber rubber aggregate concrete (CBSFRC) was investigated using quasi-static compression, a Φ120 mm split Hopkinson pressure bar system, and high-speed photography. Three steel-fiber volume fractions (1.0%, 1.5%, and 2.0%) were tested. The CBSFRC waveform displayed a characteristic ‘low-first, high-second’ double-peak pattern, in contrast to the ‘high-first, low-second’ pattern of the reference rubber aggregate concrete (CRC). At the common interpolated strain rates of 40, 45, and 50 s⁻¹, the dynamic compressive strengths of CBSFRC were 35.9–53.6% higher than those of CRC; no extrapolation was used. The largest quasi-static strength increase among the tested mixtures was 51.7%. The observed CBSFRC ultimate strains and strain energy densities ranged from 11.1–17.5 × 10⁻³ to 8.1–14.1 × 10⁵ J/m³, respectively. Matched-rate analysis showed that the largest DIF increment was 18.8% for SF-1CBRC at 40 s⁻¹, whereas the largest strain-energy-density increment was 70.2% for SF-1.5CBRC at 50 s⁻¹. These results describe the tested range and do not establish a universal optimum steel-fiber content. Full article

Infrared and visible image fusion (IVIF) is a vital approach to enhance scene representation by fusing the thermal structure of infrared images and the texture details of visible images. However, unlike natural images, remote sensing (RS) imagery typically exhibits sparser semantics and textures (e.g., small vehicles and buildings), which degrade the performance of common IVIF methods. To address this issue, we propose ${\mathrm{C}}^2$Fusion, a Collaborative Conditional difFusion method for the IVIF task of RS images. First, we propose a dual-branch conditional diffusion network to disentangle structure and texture features, and a feature refinement network that adaptively fuses the branch outputs. Second, for adapting to the features of RS images, we propose a series of loss functions (e.g., edge consistency loss, texture consistency loss, high-frequency consistency loss, low-frequency consistency loss and collaborative loss) to further improve the performance on fusing RS imagery. Qualitative and quantitative experiments show that for the IVIF task of RS imagery, our ${\mathrm{C}}^2$Fusion achieves leading or competitive performance compared with state-of-the-art methods, particularly in structural clarity, detail preservation, and visual coherence. Full article

Hemophilia is an X-linked inherited bleeding disorder, classified as type A or type B. Therapeutic advances offer new treatment options that improve disease control and reduce associated complications, including inhibitor development and hemophilic arthropathy. This document aims to update the Mexican hemophilia consensus, reviewing current evidence on diagnosis and management, and addressing gaps in the treatment and follow-up of patients in Mexico, aligning local needs with international recommendations. A PubMed literature search covering the last five years (up to September 2025) was conducted, prioritizing consensus statements, guidelines, and systematic reviews. Using the Delphi methodology, a structured questionnaire was submitted electronically to forty-four experts. Aspects without initial agreement were discussed at an in-person meeting. Consensus was defined as at least 80% of votes in favor. Recommendations were issued across six domains: laboratory diagnosis, genetic testing, management of hemophilia A and B without and with inhibitors, adjuvant treatments, and gene therapy. The recommendations address prophylaxis with coagulation factor concentrates, non-factor therapies, immune tolerance induction, perioperative management, pain management, and eligibility criteria and follow-up protocols for gene therapy with adeno-associated viral vectors. This consensus provides updated, evidence-based recommendations adapted to the Mexican healthcare context, identifying priority areas, including timely access to non-factor therapies and gene therapy, development of a national referral network for complex cases, and inclusion of novel therapeutic agents in the institutional essential medicines list, with the aim of improving the quality of life of people with hemophilia in Mexico. Full article

Reconstructing 3D building models from point clouds acquired by UAV sensors remains challenging due to irregular building geometries and sensor noise. This paper proposes an unsupervised, geometry-oriented reconstruction method based on the line-symmetric bilateral point distribution features. The method constructs baselines from farthest point pairs within local bounding spheres, then applies dual-parameter constraints (point–line distance and point statistics on both sides of a line of symmetry) combined with density peak ranking to detect building corners without training data. Evaluations show that the method reduces Cloud-to-Mesh error by 15–20% over Polyfit, DIF method, and PolyGNN, while retaining fine details in complex L-shaped and U-shaped buildings. Reconstruction quality remains stable under 0.05 m Gaussian noise. The training-free, lightweight design enables scalable, automated 3D building reconstruction for digital-twin applications. Full article

Background: The chromosomal microdeletion syndrome 2q13 is characterized by craniofacial dysmorphism, developmental delay, intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, cardiac abnormalities, and seizures. Case Presentation: In this study, we present a descriptive genomic observation of a teenage boy presenting with epilepsy, intellectual disability, and mild facial dysmorphism, found to carry a 48.55 kb 2q13 microdeletion restricted to the BUB1 locus alongside a concurrent 11q21 microdeletion. While his clinical features overlap with the 2q13 microdeletion spectrum, the exact pathogenic contribution of each variant remains a subject of hypothesis due to the lack of parental inheritance data. Conclusions: Further research is necessary to ascertain the impact of the concurrence of small deletions on these disorders. This case underscores the clinical complexity introduced by compound minor copy number variations and emphasizes the value of molecular cytogenetics in evaluating idiopathic neurodevelopmental disorders. Full article

Economic systems worldwide are facing an urgent need to build resilience, and digital inclusive finance (DIF), as a key component, can effectively enhance urban economic resilience (UER) through technological convergence and resource optimization. Existing research has largely examined the relationship between DIF and UER within a linear causal framework, lacking an in-depth analysis of interactions within complex systems. Drawing on complex adaptive systems (CAS) theory, this study re-examines the relationship between the two using panel data from 283 Chinese cities covering the period 2012–2024. The findings reveal that: (1) DIF significantly enhances UER, with the strongest promotional effect observed on resistance and recovery capacity, followed by innovation and transformation capacity, whilst the impact on adaptive capacity is relatively minor. (2) There are structural differences in the contributions across dimensions of DIF, and an asymmetric matching relationship exists with the subsystems of UER. (3) Mechanism tests indicate that the process by which DIF enhances UER aligns with three pathways: the reduction of transaction costs, the stimulation of consumer vitality, and the driving force of technological innovation, and that such mediation effects exhibit structural differences at the dimensional level. Furthermore, the enhancement effect of DIF is more pronounced in cities with weaker resilience, demonstrating a convergence effect. This study enriches the application of CAS theory in the field of urban economic governance and provides a reference for developing economies to enhance UER through DIF. Full article

Digital inclusive finance (DIF) is gradually becoming an important driver of the high-quality development of rural industries. Based on panel data from 30 provinces in China from 2013 to 2023, building the high-quality development of rural industries index system and the digital new quality productivity (DNQP) index system, this study tests the impact and mechanisms of DIF on the high-quality development of rural industries. The main results show that DIF significantly promotes the high-quality development of rural industries. Furthermore, DIF facilitates this development by fostering DNQP. The study also identifies threshold effects, with DIF and DNQP serving as threshold variables. Additionally, the study examines the heterogeneity of the empowerment effect, demonstrating that this promoting effect is more pronounced in non-major grain-producing areas and regions with high-level fiscal support for agriculture. The findings provide theoretical and empirical evidence to support sustainable rural industrial development and offer policy implications for leveraging digital finance in rural contexts. Full article

The increasing deployment of Unmanned Aerial Vehicles (UAVs) in critical operations exposes them to cyberattacks. Although deep learning-based Intrusion Detection Systems (IDSs) are effective, they are susceptible to adversarial attacks that manipulate input features to avoid detection. Conventional feature selection methods do not distinguish between features critical to model accuracy and those essential for preserving cyberattack operational validity. To address this, we propose a Dual-Impact Feature Selection (DIFS) framework for robust UAV-IDS models. Our approach evaluates features based on two criteria: the first is Model Performance Impact (MPI), using Integrated Gradients (IG) and Local Interpretable Model-agnostic Explanations (LIME) to measure feature influence on detection accuracy, and the second is Functionality Preservation Criterion (FPC), a clustering-based method that assesses whether a feature is indispensable for cyberattack execution. Features with high MPI and FPC are identified as Dual-Impact Features (DIFs). We generate constrained adversarial attacks that perturb these DIFs to create realistic evasion samples. Using these samples for adversarial training, we develop three robust UAV-IDS Convolutional Neural Network (CNN) models. Evaluated on three UAV network intrusion datasets, our framework demonstrates improved resilience. The models achieve up to 99.8% detection accuracy while reducing Attack Success Rate (ASR) to as low as 0.002, supporting their potential for designing adversary-resistant detection systems for UAV networks. Full article

Against the backdrop of the increasingly urgent global climate governance situation, carbon emission reduction has gone beyond the simple scope of environmental protection and become an import benchmark for measuring the quality and sustainability of economic and social development. Drawing on data from 233 prefecture-level cities in China over the period 2015–2024, this study investigates the impact of digital inclusive finance (DIF) on urban carbon emission intensity (CI). The findings indicate that DIF significantly mitigates the effect on CI. Heterogeneity analysis further indicates that this mitigating effect is more pronounced in cities with higher initial CI. DIF also exerts a stronger influence on curbing CI in environmental protection cities and non-central cities. The results also confirm that industrial structure upgrading (ISU) and household consumption level (HCL) serve as mediating mechanisms in the causal pathways. Based on the above conclusions, this paper puts forward suggestions concerning the popularization and expanded coverage of DIF. The coordinated implementation of these suggestions helps DIF fully exert its bridging role between financial and environmental sustainability, providing robust instrumental support for achieving regional carbon emission reduction targets and comprehensively advancing the sustainable development of cities. Full article

This study investigates the effect of coal gangue aggregate fractal gradation on the dynamic mechanical behavior and impact failure mechanism of cemented coal gangue backfill composites. Four aggregate gradations with different mass fractal dimensions were designed, and static compression and split Hopkinson pressure bar (SHPB) dynamic compression tests were conducted. The effects of fractal dimension and strain rate on stress–strain response, dynamic peak strength, dynamic increase factor (DIF), deformation modulus, energy dissipation, and failure morphology were analyzed. The results show that the composites exhibit a clear strain-rate strengthening effect, with dynamic strength, DIF, and deformation modulus increasing as strain rate increases. Aggregate fractal dimension has a nonlinear regulatory effect on mechanical performance. Among the four tested gradations, the specimen with D_f = 2.41 exhibits the best overall static and dynamic bearing performance, which is attributed to a more continuous coarse-particle skeleton and improved fine-particle filling. When the fractal dimension is too low, insufficient fine-particle filling leads to discontinuous contacts and larger pores; when it is too high, excessive fine particles weaken coarse-particle interlocking and promote matrix-dominated deformation. Energy analysis and failure observations further indicate that an intermediate fractal gradation improves energy absorption and delays unstable crack propagation. These findings provide a reference for gradation optimization and dynamic stability evaluation of coal gangue-based cemented backfill materials. Full article

Background: High-grade serous ovarian carcinoma (HGSOC) can be subdivided into four prognostic molecular subtypes based on gene expression: C1/Mesenchymal (C1.MES), C2/Immunoreactive (C2.IMM), C4/Differentiated (C4.DIF) and C5/Proliferative (C5.PRO), each representing distinct biological characteristics with immune and stromal microenvironments. PrOTYPE enables prognosis and treatment guidance from biopsy material. Metastatic biopsies are often more accessible than primary adnexal sampling; their utility assumes stable tumor-intrinsic properties relative to the primary. Metastases may diverge due to microenvironmental pressure as well as the site-specific subtype dynamics. Methods: Treatment-naïve HGSOC specimens from 138 patients were profiled using the 55-gene nanostring PrOTYPE assay at adnexal, contralateral adnexal, and/or metastatic sites. Results: Adnexal PrOTYPE yielded expected distributions (21% C1.MES, 31% C2.IMM, 23% C4.DIF, 25% C5.PRO) with moderate reproducibility (κ = 0.49). Same-site replicate analysis showed substantial reproducibility (κ = 0.7). Non-adnexal sites were enriched for immune/mesenchymal subtypes (C1.MES/C2.IMM, 36/63 cases), most prominently at the omentum (24/32 C1.MES). C5.PRO was distinctly underrepresented at non-adnexal sites. Subtype shifts from adnexal to extra-adnexal sites were enriched for the second-place adnexal type prediction (p < 0.001). Detailed 55-gene analysis showed POSTN/CTSK were most commonly upregulated across metastatic sites. EMT pathway enrichment increased with metastatic distance (from adnexa to omentum, adj p < 0.05), paralleling—but independent of—C1.MES predominance. Conclusions: Adnexal PrOTYPE showed good stability. However, non-random subtype shifts and EMT enrichment at metastatic sites suggest dissemination selects pre-existing transcriptional plasticity rather than acquiring states de novo as HGSOC adapts to new microenvironments. Microenvironment changes may help predict metastatic potential and should be considered for precision medicine targeting. Full article

Improving cultivated land use efficiency (CLUE) is a crucial pathway to solve China’s food security challenges. In recent years, the development of digital inclusive finance (DIF) has transformed the economic effects of input and output in the cultivated land utilization process. Employing Yangtze River Delta as the experimental area, which represents one of China’s most densely populated regions with the most acute arable land scarcity per capita, this study utilized a super-efficiency slacks-based measure (SBM) model that incorporated undesirable outputs to measure CLUE using a balanced panel data of 25 prefecture-level cities in the Yangtze River Delta from 2011 to 2023. Additionally, this study employed panel regression analysis combined with a mediation effect model to examine the impact of DIF on CLUE. The findings are as follows. (1) CLUE exhibits an upward trend throughout the study period, with significant improvements noted in the northwest regions, and evolves into a spatial distribution of “high in the northwest and low in the south.” (2) DIF effectively enhances CLUE, supported by extensive robustness tests. (3) Heterogeneity analysis reveals that the effect of DIF on CLUE varies systematically across contexts: it peaks in regions undergoing medium-level urbanization, remains most potent under extremely low credit availability, and is optimized by moderate bank outlet coverage. (4) Mechanism analysis demonstrates that the DIF positively influences CLUE by increasing fixed-asset investment in the primary industry. Based on these results, this study provides targeted policy recommendations for digital inclusive finance to serve the high-quality development of cultivated land utilization. Full article

Bullous pemphigoid (BP) is the most common autoimmune subepidermal blistering disease, predominantly affecting elderly patients with multiple comorbidities. This multicentre retrospective cohort study aimed to characterize the clinical profile, treatment patterns, and drug-associated cases of BP in a real-world setting. The study included 156 patients newly diagnosed with BP between 2020 and 2024 in four dermatology departments in Poland. Diagnosis was based on clinical features, and immunological assessment, including direct immunofluorescence (DIF), ELISA, and BIOCHIP-based indirect immunofluorescence. The mean age at diagnosis was 75.5 ± 10.9 years, and 78.85% of patients had at least one comorbidity, most commonly arterial hypertension, type 2 diabetes mellitus, and dyslipidemia. Severe pruritus was reported in 74.14% of evaluated patients. Blisters and erosions were the predominant clinical manifestations. Topical glucocorticosteroids were the most frequently used treatment, followed by systemic glucocorticosteroids and methotrexate. New drug exposure within 6 months before disease onset was identified in 14.74% of patients and was associated with a shorter time to diagnosis. Drug-associated cases showed lower BP180 ELISA positivity, although this did not remain significant after correction for multiple testing. These findings highlight the clinical complexity of BP and the importance of medication review and direct immunofluorescence in diagnostic evaluation. Full article

In Czochralski (CZ) silicon growth, controlling the ratio of crystal growth velocity to axial temperature gradient ($V/G$) is critical for defect management. However, the $V/G$ value is difficult to measure in real-time. Furthermore, it exhibits strong multivariate coupling and extreme non-stationarity under complex thermal fields. While standard deep learning models like LSTM are used for soft sensing, they often misidentify high-frequency hardware noise as true process dynamics, causing severe error amplification in multi-step predictions. To address this, we propose a Dual Information Filtering LSTM (DIF-LSTM). It utilizes an external context-aware mechanism to screen long-term steady-state redundant information and an internal denoising gate coupled with the LSTM input to explicitly block transient high-frequency noise. Furthermore, a confidence evaluation branch and residual decay fusion ensure stable multi-step forecasting. Experimental results an industrial-scale experimental silicon single crystal furnace show DIF-LSTM achieves superior accuracy, obtaining an $R^2$ of 0.9935 and a Mean Squared Error of $1.60\times {10}^{-6}$ at a 3-step horizon. Even at a 9-step horizon, it maintains an $R^2$ of 0.9422, significantly outperforming the baseline IF-LSTM (0.8498). Full article

Digital traceability has become an important capability in international trade, especially in high-regulation and high-risk supply chains. However, existing research has not fully explained how institutional, technological, and coordination-related conditions combine to produce successful outcomes. This study applies fuzzy-set Qualitative Comparative Analysis (fsQCA) to 24 trade-corridor/product-chain cases to identify the configurational drivers of Digital Traceability Success (DTS). The findings show that Digital Trade Readiness (DTR), Market Strictness (MKT), Digital Infrastructure (DIF), and Cross-border Coordination (COO) are highly consistent necessary conditions for DTS, whereas Blockchain-enabled Traceability (BCT) is not. The sufficiency analysis identifies one dominant pathway, DTR * PRK * MKT * DIF * COO, with perfect consistency and substantial coverage. These results indicate that traceability success emerges from the alignment of institutional readiness, regulatory pressure, infrastructural capacity, product-related risk, and cross-border coordination rather than from blockchain adoption alone. The study contributes to digital trade and supply-chain governance literature by offering a configurational explanation grounded in conjunctural causation and causal asymmetry. It also clarifies blockchain’s role as a contingent enabling component rather than a universally necessary determinant. Practically, the findings suggest that policymakers and firms should prioritize interoperable infrastructure, institutional readiness, and cross-border governance mechanisms over stand-alone technological solutions. Full article