Search Results (130,960)

Deflection is a crucial indicator for structural safety assessment and maintenance of engineering structures. Traditional deflection inspection methods are confronted with the difficulty in selecting reference points, and therefore these methods are usually applied in short-term monitoring of structures. In this context, a novel strategy for automatic deflection inspection of beam-like composite structures which overcomes the difficulty in selecting reference points is put forward in this article. First, deflection assessment of composite structures using long-gauge fiber optic sensing was theoretically established. The relationship between vertical displacement and monitored average strain is irrelevant to external loads. The approach is applicable to both linear and nonlinear stages of structures, and deflection distribution along the structures can be estimated. Second, a four-point loading experiment on a wood–concrete composite beam which was installed with long-gauge fiber optic sensors was performed to verify the reliability of the deflection inspection method. Deflection was estimated under three conditions: (1) without considering composite action; (2) considering composite action but neglecting interface slip; and (3) considering both composite action and interface slip. Meanwhile, displacement meters were also installed to verify the calculated results. Experimental results indicate that the presented strategy has high precision. Hence, the presented method serves as an innovative option for assessing composite structures in both the short and long term. Full article

Background: Biliary tract cancers (BTCs), encompassing cholangiocarcinoma and gallbladder carcinoma, are aggressive malignancies with poor prognosis and increasing incidence in selected regions worldwide. Advances in imaging, biomarker profiling, immunotherapy, and targeted therapies have improved treatment options but have also increased the economic pressure on health systems. Understanding the economic evidence on BTC is therefore important for resource allocation and health technology assessment. Methods: We systematically searched PubMed/MEDLINE, Embase, Scopus, and Web of Science for peer-reviewed economic studies of BTC published from January 2010 to March 2025. Eligible studies included cost-effectiveness, cost–utility, cost–benefit, cost-of-illness, and resource-use analyses. The review followed PRISMA reporting principles. Reporting completeness was assessed using CHEERS 2022, and methodological credibility was appraised using the Drummond framework. Results: Twenty studies were included: 13 cost-effectiveness or cost–utility analyses and seven cost-of-illness or resource-use studies. Conventional chemotherapy strategies, including gemcitabine plus cisplatin in some settings and other cytotoxic combinations in selected jurisdictions, generally produced more favorable economic results than newer systemic therapies, although findings varied by country, threshold, comparator, and price assumptions. First-line immunotherapy combinations and biomarker-directed targeted therapies frequently produced ICERs above jurisdiction-specific willingness-to-pay thresholds at current prices, often requiring substantial price reductions to approach cost-effectiveness. Real-world studies showed high resource use and costs, particularly with hospitalizations and later treatment lines. Evidence on screening and prevention was limited, with one study suggesting that ultrasound surveillance may be cost-effective in a liver fluke-endemic region of Thailand. Discussion: The available economic evidence suggests that affordability and jurisdiction-specific value assessment are central to BTC policy decisions. Current prices for several immunotherapy and targeted agents limit cost-effectiveness in published models, while evidence on prevention, early detection, and care-pathway interventions remains sparse and context-specific. Full article

The ongoing Palestinian conflict, particularly the escalation in Gaza since October 2023, has raised pressing concerns regarding human rights and international justice. This study explores how university students in northern Spain perceive the situation in Palestine, analyzing their levels of knowledge, emotional responses, and critical positioning. Using a mixed-method approach based on an online questionnaire and the Grid Elaboration Method, data were gathered from 147 students enrolled in education-related programs. The findings reveal three core themes in students’ representations of the conflict: resistance as a form of national identity, humanitarian suffering of civilians, and structural injustice perpetuated by global power dynamics. Gender and academic background influenced discursive emphasis, with Social Education students showing more politicized perspectives and women focusing more on Palestinian dignity and resistance. These insights underscore the potential of higher education to foster critical thinking, empathy, and engagement with international conflicts, and highlight the role of universities in cultivating a culture of peace and human rights. Full article

Background: A complex interplay between viral activity and host immune responses drives the progression of liver fibrosis in chronic hepatitis B. The T helper 17 (Th17) immune pathway, which produces the pro-inflammatory cytokine interleukin-17A (IL-17A), has been implicated in hepatic fibrogenesis. However, the relationship between IL-17A levels, IL-17A G197A (rs2275913) gene SNP, and the degree of liver fibrosis across different phases of the natural history of chronic hepatitis B remains insufficiently explored. Methods: This study employed an analytical observational design with a cross-sectional approach in treatment-naïve patients with chronic hepatitis B. The degree of liver fibrosis was assessed using liver elastography. IL-17A (rs2275913) gene SNP was analysed using Real-Time PCR, while serum IL-17A levels were measured using enzyme-linked immunosorbent assay. Statistical analyses included Spearman’s correlation, the contingency coefficient, the Chi-square test, the Kruskal–Wallis test, and the Mann–Whitney test, with a significance level set at p < 0.05. Results: A total of 76 patients with chronic hepatitis B were included in this study. The phase of disease progression was significantly associated with the degree of liver fibrosis (p = 0.016). Median IL-17A levels increased in parallel with fibrosis severity (p = 0.003), with a particularly significant association observed during the R phase (p = 0.002). However, no significant association was found between the IL-17A G197A (rs2275913) gene SNP and either liver fibrosis severity or serum IL-17A levels. Conclusions: Elevated serum IL-17A levels were associated with greater liver fibrosis severity, particularly during the reactivation phase of chronic hepatitis B. These findings suggest a potential relationship between IL-17A-mediated immune responses and liver fibrosis in patients with chronic hepatitis B. Full article

Background: Suicide is a major mental health concern, particularly among university students facing unique stressors. Understanding their attitudes toward suicide is essential for effective prevention, yet the existing literature lacks a systematic review on this population. This review synthesises and evaluates the literature on attitudes toward suicide among university students. Methods: A systematic search was conducted on four databases (MEDLINE, Web of Science, Scopus, and PubMed) using Medical Subject Headings terms and keywords identified from previous studies. The search, conducted in February 2024, included studies published between 2014 and 2024. One researcher screened the titles and abstracts, while two independent researchers extracted the data. Twenty-one articles (N participants = 13,424) were selected for further assessment. Quantitative designs were the most common (n = 18), followed by qualitative (n = 2) and mixed-method designs (n = 1), spanning multiple regions. Themes were derived by organising findings into thematic categories based on recurring patterns across the studies. Results: Two core themes emerged: Factors associated with attitudes toward suicide and their associations with suicide outcomes. Conclusions: The review underscores the need for culturally sensitive approaches to address negative attitudes toward suicide and promote help-seeking among university students, highlighting the importance of further research in this area. Full article

Accurate and non-destructive volume estimation of agricultural products is essential for precision agriculture, yet remains challenging when transitioning from controlled laboratory conditions to complex orchard environments. Although 2D image-based volume estimation methods provide a cost-effective and scalable solution, existing studies are fragmented and lack a unified perspective on their real-world applicability. This review presents a systematic synthesis of 2D image-based volume estimation methods, explicitly framed through the laboratory-to-orchard transition. We categorized existing volume estimation approaches according to the sensing modality into monocular RGB-based approaches and depth-assisted methods, and further reviewed them based on the image processing methods. A key finding is that high-precision geometric estimation can be achieved in laboratory environments, whereas deep learning and RGB-D fusion have driven a shift from conventional geometric modeling toward data-driven and hybrid learning frameworks in orchard settings. However, 2D image-based volume estimation remains fundamentally limited by scale ambiguity, severe occlusion, and sensitivity to illumination and background variability in real orchard environment. Overall, this review provides a unified perspective for understanding volume estimation methodology across environments and offers guidance for developing robust, scalable, and field-deployable volume estimation systems for real-world agricultural applications. Full article

The analysis of specific habitat conditions involves a systematic assessment of environmental variables such as temperature, hydrology, and vegetation, to clarify species’ ecological requirements and develop conservation strategies. Common approaches include statistical modelling, various Habitat Suitability Index (HSI) models, and GIS-based spatial analyses, which quantify factors like topography, land cover and anthropogenic pressures. Today, machine learning (ML) methods are widely applied across engineering disciplines, including water resources management. In this study, ML methods, particularly model trees, are employed to model and predict key abiotic factors relevant to fish communities. The research focuses on the bioindicator species Barbus balcanicus (brook barbel), which inhabits the middle part of the Sutla River (transboundary river basin between Croatia and Slovenia) and serves as an indicator of ecological conditions in this system. Using ML, models for water depth, water velocity, and water temperature were developed and applied together with SWAT (Soil and Water Assessment Tool) data to determine the HSI for future scenarios to support habitat assessment and water management planning. Full article

This paper presents a parity space-based fault detection (FD) method for networked control systems (NCSs) subject to denial-of-service (DoS) attacks resulting in packet dropouts. To begin with, a parity relation that takes into account DoS attacks is constructed utilizing the available input and output data during a time-varying window. Based on the parity relation, a residual generator is proposed without introducing transmission errors caused by DoS attacks. Additionally, an $H_{-}/H_2$ optimization scheme is developed for the design of residual to achieve a trade-off between the sensitivity to faults and the robustness against the disturbance/noise. Then, an adaptive residual evaluation function with a unified threshold is also proposed for no DoS attack scenario and DoS attack scenarios. Furthermore, the relationship between the traditional residual generator with the proposed one is explored, and an online FD algorithm is presented. Finally, the effectiveness of the proposed approach is demonstrated on a linearized longitudinal model of an autonomous underwater vehicle (AUV), and a comparison with an existing parity space approach is also provided. Full article

Renewable energy is being increasingly integrated into power grids. As a result, the three-phase grid-connected inverter (GCI) faces power transfer limitations caused by small-signal stability issues. To improve energy utilization and enhance stability, this paper employs an impedance-based method to analyze the small-signal stability power boundary of the GCI. This boundary is then quantified using the generalized Nyquist criterion (GNC). Our analysis reveals that the power boundary decreases as the grid short-circuit ratio (SCR) decreases or the phase-locked loop (PLL) bandwidth increases. To address this problem, we propose an impedance reshaping method that cancels the negative resistance effect introduced by PLL feedforward. This approach raises the small-signal stability power limit to the rated power and ensures stable operation under grid impedance variations and high PLL bandwidth. Finally, impedance analysis and experimental verification confirm both the theoretical correctness and the practical effectiveness of the proposed method in extending the stability power boundary. Full article

Wavefront sensing (WFS) is fundamental to adaptive optics, astronomical observation, biological microscopy, and free-space optical communications. However, conventional approaches—including Shack–Hartmann sensors, shearing interferometers, and transport of intensity equation-based methods—are inherently limited by trade-offs among spatial sampling density, angular dynamic range, and device compactness and have rarely been extended to the mid-infrared range. Here, we propose an on-chip mid-infrared wavefront sensing scheme operating based on vectorial photocurrent manipulation and analyze the properties of the proposed device through finite-element simulations. The proposed device comprises a hexagonal array of antenna-integrated graphene pixels, each equipped with three contacts and a microlens. Based on the antenna-induced vectorial photocurrent manipulation, angle-dependent absorption is translated into photocurrent signals, potentially enabling unambiguous recovery of both the elevation and azimuth angles of the incident light over an effective angular dynamic range of ±28°. The hexagonal layout provides a high spatial sampling density of 11,547 mm⁻². Southwell algorithm-based wavefront reconstruction and numerical simulations yield faithful recovery of parabolic, conical, and quadrangular pyramidal wavefronts. In addition, simulation results indicate that this approach can enable high-fidelity reconstruction of both the phase and intensity distributions of an object based on angular-spectrum diffraction theory. Overall, this work theoretically demonstrates a new route toward high-density wavefront measurement and complex light field imaging in the mid-infrared range without a conventional imaging lens. Full article

Background/Aims: While pathogenic germline variants play a critical role in pediatric cancer susceptibility, traditional clinical genetics primarily focuses on single-gene interpretations. Transitioning to a systems-level analysis of inherited variation can uncover shared biological vulnerabilities, informing genetic counseling, surveillance, and targeted therapeutics. This study aims to implement an unsupervised machine learning framework to identify and characterize Germline Mutation Signatures (GMS) across diverse pediatric malignancies, elucidating latent genomic patterns that reveal shared oncogenic mechanisms. Methods: We analyzed germline whole-exome and whole-genome sequencing (WES/WGS) data from a retrospective cohort of 420 pediatric cancer patients and matched non-cancer controls. Variants were deeply annotated to capture multi-dimensional features, including predicted pathogenicity, splice-site disruption, regulatory impact, population frequency, and sequence context. To enable robust modeling, we integrated an augmented feature set encompassing evolutionary constraint, loss-of-function intolerance, and compositionally normalized substitution spectra. These high-dimensional annotations were processed using a deep autoencoder for non-linear representation learning, followed by Gaussian Mixture Modeling (GMM) of the latent space. Results: The framework delineated 13 signatures (GMS1–GMS13), yielding an optimal Davies–Bouldin index of 1.051. These signatures map to fundamental biological processes, including DNA repair deficiencies, transcription-coupled damage, replication stress, and aberrant RNA regulation. Crucially, these GMSs transcend traditional tissue-of-origin classifications, manifesting across multiple distinct cancer types. This observation indicates convergent germline etiologies and suggests potential shared susceptibilities to pathway-directed therapies. Conclusions: The discovery of these cross-cancer signatures provides a scalable, biologically interpretable framework for decoding inherited pediatric cancer risk. While the therapeutic mapping networks identified are currently exploratory and serve as a hypothesis-generating foundation, this deep learning-driven paradigm establishes a robust basis for stratified precision medicine. Pending prospective clinical validation, this approach holds significant translational potential to move beyond single-gene paradigms toward unified, systems-level precision oncology strategies. Full article

Background: Given the increasing consumption of ultra-processed foods (UPFs) and the public health importance of cognitive decline in ageing, understanding how UPFs impact cognitive performance is highly relevant. However, evidence in older adults - particularly in Italy—remains scarce, despite the country’s rapidly ageing population, its comparatively low UPF intake, and its distinct Mediterranean dietary context. Methods: We analysed cross-sectional data from 809 community-dwelling adults aged ≥ 65 years (59.4% women) participating in the NutBrain population-based cohort. Dietary intake was assessed using a 102-item semi-quantitative food frequency questionnaire, and daily grams of foods were classified according to the NOVA system into groups, which were analysed using a compositional data analysis approach. Global cognition and domain-specific performance were measured using standardised neuropsychological tests. Associations between NOVA groups and cognitive outcomes were estimated using multiple linear regression models adjusted for potential confounders. Gender-stratified analyses were also performed. Results: UPFs accounted for 21% of total energy intake, with bakery products as the main contributors. A relative increase of unprocessed or minimally processed foods was associated with better cognitive function (B = 0.36, p = 0.014), whereas a greater contribution of UPFs relative to the overall diet was associated with worse global cognitive function (B = −0.26, p = 0.003). The strongest associations were observed for episodic memory, particularly among women. Conclusions: A higher relative consumption of UPF was associated with worse global and memory-related cognitive performance. Longitudinal and experimental studies are warranted to clarify causality and underlying mechanisms. Full article

Background: Physical activity is a key modifiable factor influencing healthy aging, yet data on activity patterns and their physiological correlates in older adults from Central Asia remain limited. Understanding these relationships is essential for informing region-specific health promotion strategies. Objectives: This study assessed physical activity levels among urban-dwelling older adults in Astana, Kazakhstan, and examined associations between activity level, body composition, visceral fat accumulation, metabolic indicators, and muscle strength. Methods: A cross-sectional study was conducted among 608 adults aged ≥60 years (median age: 68 years; 82.1% women). Physical activity was measured using the validated Physical Activity Scale for the Elderly (PASE). Anthropometric and body composition indicators, including BMI, total and visceral fat, skeletal muscle mass, and handgrip strength, were evaluated. Spearman correlation and linear regression analyses were applied. The analyses were exploratory and did not include adjustment for potential confounders such as sex, chronic disease burden, or socioeconomic status; therefore, the observed associations should be interpreted with caution. Results: The median PASE score was 55.55, with 61.8% of participants demonstrating moderate activity levels, primarily through walking and household tasks. In analyses without adjustment for potential confounding factors, PASE scores showed weak inverse associations with visceral fat (ρ = −0.214; p < 0.001) and waist-to-hip ratio (ρ = −0.154; p < 0.001), as well as weak positive associations with handgrip strength. Across the reported significant associations, correlation coefficients ranged from |ρ| = 0.103 to 0.235, and the explanatory capacity of the regression models was low, with R² values ranging from 0.6% to 8.2%. Conclusions: Higher habitual physical activity may be linked to selected bioelectrical impedance parameters, WHR, and handgrip strength among urban older adults. Given the cross-sectional design, causal interpretation should be approached with caution. These findings provide meaningful regional baseline evidence for future longitudinal and intervention studies on physical activity and healthy aging in Central Asia. Full article

Cleft lip with or without cleft palate (CL/P) is one of the most common congenital craniofacial anomalies worldwide and presents significant functional, esthetic, and psychosocial challenges. Despite advances in multidisciplinary care and surgical reconstruction, complications such as impaired wound healing, scar formation, and growth disturbances warrant the development of novel regenerative and surgical strategies, which heavily rely on animal models at the pre-clinical stage. For the current narrative review, the literature search was performed by combining cleft phenotype terms with modeling-approach terms in six databases and was supplemented by manual review of reference lists from full-text articles. The included articles were summarized based on cleft type and the methods for cleft induction (chemically induced, genetically engineered, and surgically created). Particularly, chemical teratogens such as retinoic acid, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), corticosteroids, and 6-aminonicotinamide have been widely used to induce cleft phenotypes and elucidate environmental influences on palatogenesis, whereas genetic models have clarified the roles of key molecules and signaling pathways, including Sonic hedgehog (SHH), bone morphogenetic protein (BMP), and transforming growth factor-β (TGF-β), in the development of lip and palate. Meanwhile, the surgical models have focused on the alveolar cleft in skeletally mature animals for evaluating novel grafting materials. By comparing the strengths and limitations of existing models, this review highlights opportunities for improving experimental design and translational relevance in future cleft research. Overall, despite a wide range of CL/P animal models available, few replicate clinically relevant defect anatomy and the postnatal craniofacial deformation observed in CL/P patients, underscoring the need for the development of new models. Full article

Background:Scutellaria baicalensis (Scu) extract has been traditionally used in the treatment of stroke-related syndromes, yet its underlying molecular mechanisms, particularly those involving ferroptosis, remain to be fully elucidated. Purpose: This study aims to validate the hypothesis that Scu extract improves cerebral ischemia-reperfusion injury (CIRI) by inhibiting ferroptosis through the PI3K/AKT signaling pathway. Methods: This study employed middle cerebral artery occlusion (MCAO) in male Sprague-Dawley (SD) rats and oxygen–glucose deprivation/reoxygenation (OGD/R) models to evaluate the protective effects of Scu extract against CIRI. Multiple approaches were integrated to elucidate the underlying mechanisms. Furthermore, a range of experimental techniques, including neurological function assessment, TTC staining, histopathological analysis, biochemical assays, qPCR, transmission electron microscopy (TEM), reactive oxygen species (ROS) detection, Western blotting, and immunofluorescence, were used to comprehensively validate its neuroprotective effects. Results: Scu extract significantly improved neurological outcomes and attenuated brain injury in MCAO rats. Proteomic analysis revealed significant enrichment of ferroptosis-related pathways, which was supported by reduced mitochondrial damage, decreased iron accumulation, and restoration of the SLC7A11/GPX4 axis. Subsequently, UPLC/Q-TOF-MS analysis revealed that four major bioactive components were absorbed in MCAO rats. KEGG pathway analysis based on network pharmacology further indicated that the PI3K/AKT signaling pathway is a key regulatory target. Notably, pharmacological inhibition of PI3K with LY294002 markedly abolished the anti-ferroptotic effects of Scu extract, which was further confirmed in vitro. Conclusions: This study demonstrates that Scu extract confers neuroprotection against CIRI in MCAO rats potentially through inhibiting ferroptosis via activation of the PI3K/AKT pathway. Full article