Search Results (5,154)

Screen content images (SCIs) exhibit complex structural heterogeneity, rendering traditional statistics-based natural scene image quality assessment (NR-IQA) metrics ineffective. Although deep learning models achieve high prediction accuracy, their prohibitive computational demands preclude deployment in latency-sensitive industrial scenarios. While existing handcrafted lightweight SCI-IQA metrics reduce computational overhead, most rely on unsegmented global feature pooling or holistic edge statistics (e.g., edge histograms or Fisher vector coding), thereby diluting locally critical text-edge distortions in vast homogeneous backgrounds. To address this limitation, we propose an ultra-lightweight, deep-learning-free NR-IQA framework centered on human visual masking. Unlike existing lightweight methods, our approach explicitly employs dual-scale Canny edge operators to partition SCIs into edge-sensitive and flat background regions. Guided by this visual prior, structural degradations and micro-compression textures are extracted region-wise using Sobel gradients and uniform local binary patterns (LBPs) and aggregated with global Commission Internationale de I’Eclairage L*a*b*(CIELAB) color statistics into a compact 60-dimensional descriptor. A grid-search-optimized Support Vector Regression (SVR) maps these features to subjective quality scores. Extensive cross-validation on the SIQAD and SCID datasets demonstrates that our metric outperforms existing handcrafted lightweight SCI metrics and traditional NSS models, while achieving accuracy competitive with representative full-reference metrics. Consuming only 79.3 ms per image on a standard CPU, it offers a practical accuracy–efficiency trade-off for resource-constrained periodic quality monitoring. Full article

Teacher leadership has gained increasing attention since the 1980s. With the various operationalizations of teacher leadership in research and practice as well as mixed results of effects of teacher leadership, we sought to investigate the difference in teacher leadership under the school reform and renewal approaches. We delineated nuanced differences in teacher leadership under the two approaches and provided empirical illustrations, including (a) boundary spanning vs. embedded co-construction, (b) compliant sense-making vs. holistic, generative sense-making, (c) episodic, task-based engagement vs. sustained, identity-based stewardship, (d) initiative-driven activation vs. developmental capacity building, and (e) parallel leadership vs. integrated leadership. The illustrations were based on three large school leadership projects conducted from 2017 to the present. The article creates a nuanced understanding of teacher leadership by situating its construct and practice in a larger school improvement context. Full article

One of the most common dynamic phenomena occurring in surface waters is the transport of soluble and insoluble contaminants from various sources, such as industry and agriculture. A key concern associated with this transport is the rate at which contaminants migrate downstream to a point of interest, as well as their overall impact. In order to characterize the transport of contaminants in a body of surface water (in this case, a river), this study applied a one-dimensional advection–dispersion model that incorporated transient storage effects. This enabled the characterization of nutrient transport considering varying flow velocities along the river’s course. Adopting a more comprehensive, systemic approach enables a more holistic environmental application and facilitates parameterization of a considerably larger river than in previous case studies. The model’s innovation lies in using routinely monitored water quality constituents to evaluate their ability to inform the characterization of mixing conditions and solute transport in surface water streams. Its dynamic nature provides a reasonable approximation of the real system’s behavior over time. Finally, for management purposes, the proposed model can be replicated without extensive changes to its fundamental structure. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) is caused by excessive fat accumulation in the liver (steatosis) and affects approximately 38% of adults globally. MASLD may progress from simple steatosis to fibrosis and cirrhosis and is closely related to other cardio-metabolic conditions (e.g., obesity and type 2 diabetes), posing a risk factor for cardiovascular disease. Currently, lifestyle modification and weight reduction remain the main initial treatment options. Existing data suggest that there is low awareness among patients regarding MASLD diagnosis and its subsequent management. Therefore, this study aimed to develop a rich understanding of the lived experiences, concerns, and support needs of adults with MASLD. Methods: A qualitative design was applied, utilizing semi-structured interviews. Adults living with MASLD were invited to talk about their diagnosis and discuss their lived experiences. Participants were interviewed by telephone or video call, and each interview was transcribed and analyzed with a reflexive thematic analysis approach. Results: Twenty-five adults with MASLD (age range: 24–79 years; 40% men) were interviewed. The emergent key themes related to communication and emotions at diagnosis; independently seeking further information; lived experiences post-diagnosis; support needs; and future concerns. Many participants reported receiving the diagnosis incidentally, and a number of issues were raised regarding lack of clarity at the point of diagnosis. Additional concerns included information obtainable via the internet, symptoms, social relationships, stigma, and lifestyle modification. Future anxieties related mainly to fears of disease progression, while support needs were predominantly focused on information and follow-up. Conclusions: The concerns and support needs identified by this study highlight key issues/themes that should inform education and support initiatives by relevant healthcare services aiming to improve the lived experiences and holistic management of adults with MASLD. Full article

To validate the effectiveness of the grooved diaphragm with back peninsulas and trenches (GDPT) and the radial basis function neural network (RBFNN)-based dimension generator in the development of a 1 kPa piezoresistive micropressure sensor, this paper presents a comprehensive investigation into the design, fabrication, and characterization of the anticipative sensor prototype. The GDPT achieves favorable sensing stress and reduced deflection, enabling a favorable trade-off between sensitivity and nonlinearity; the RBFNN-based generator efficiently determines practicable dimensions for the complex structure, offering a significant improvement over the conventional trial-and-error process. Characterization results demonstrate that the fabricated sensor achieves sensitivity of 13.01 mV/(V·kPa) and nonlinearity of 0.26% FS within the pressure range of 0–1 kPa, in good agreement with the preset design target. This work verifies the validity of the proposed approach and offers a holistic methodology for developing high-performance piezoresistive sensors. Full article

Since the late 1960s, project management researchers have studied the factors contributing to project success, with Dr. Barnes introducing the “Iron Triangle” concept in 1969. Initially composed of scope, time, and cost, subsequent interpretations have varied, with quality, stakeholder satisfaction, risk management, and sustainability proposed as additional vertices. However, it is difficult to reach a consensus on the definitive concepts of the Iron Triangle. This study proposes a new Iron Triangle that incorporates the concept of “value” along with cost and schedule, consistent with Lean Construction principles. Through a comprehensive literature review and critical analysis, the study identifies systematically excluded dimensions of the traditional Iron Triangle, emphasizing stakeholder satisfaction, sustainability, and innovation. The research aims to understand how these dimensions enhance traditional project management models by integrating Lean Construction principles. The results reveal a dynamic relationship among cost, schedule, and value, challenging the traditional assumption of inverse proportionality. The proposed model emphasizes the importance of value generation, promoting customer focus, eliminating waste, and continuous improvement. It encourages a holistic approach to project assessment, recognizing the multifaceted nature of success. This new paradigm suggests further research into strategies that assess cost, schedule, and value in construction projects. Full article

Buildings have significant impacts on the environment throughout their life cycle in terms of energy and water consumption, material usage, and waste generation. This study aims to evaluate the Sivas Train Station and Sivas High-Speed Train Station buildings, which were constructed in different periods and with different construction techniques, within the scope of sustainable renovation. In the study, the literature on sustainable architecture and building renovation approaches was reviewed; field observations, archival documents, interviews, and on-site measurements of temperature, thermal transmittance, and lighting were utilized. The buildings were compared based on criteria such as energy and water efficiency, material selection, and waste management. The findings indicate that the lack of insulation, old joinery, and absence of windbreaks in the Sivas Train Station, as well as the extensive glass surfaces, high user traffic, entrance layout, and operational issues with technical systems in the High-Speed Train Station, lead to energy losses. The lack of independent monitoring of water consumption in both buildings, the absence of systems for using rainwater, snow and graywater, and the inadequacy of waste separation practices have been identified as significant deficiencies. As a result of the study, different renovation strategies were proposed, preserving the original values of the historical structure and adapting the new structure to real usage conditions. It was concluded that sustainable renovation should be considered a continuous and holistic process that includes not only physical interventions but also building management, user training, regular monitoring, inspection, and certification. Full article

Extensive livestock farming is characteristic of the landscape of the Mediterranean regions of Southern Iberian Peninsula. These production systems based on dryland pastures provide a wide range of services and contribute to maintaining environmental balance when compared with intensive agricultural or other livestock production systems. The Portuguese Montado is a habitat of Community importance and is protected under the European Natura 2000 network. This makes any research aimed at preserving, maintaining, or restoring this ecosystem particularly important to ensure its sustainable management. The main objectives of this study were to evaluate: (i) the impact of dolomitic limestone application on soil pH; (ii) the relation between multiple soil parameters; (iii) the impact of grazing preferences and livestock stocking rates on topsoil compaction; (iv) temporal and spatial sheep grazing patterns and sward productivity, quality and floristic composition throughout the growing vegetative season. This study was carried out during the vegetative cycle of 2023/2024 on a 4-ha pasture field located at Mitra farm (Southern Portugal). The experimental design included four treatments resulting from the combination of limestone application (with and without) and stocking rate (traditional: 7 sheep ha⁻¹; high: 18 sheep ha⁻¹). Sheep grazing preferences, soil compaction and fertility, sward productivity, quality and floristic composition were monitored at 48 sampling areas. The results confirm that improving soil pH through the application of dolomitic limestone is an effective, although slow and gradual process. When combined with grazing management through increased stocking rates, several important outcomes were observed: (i) preferential grazing areas did not exhibit significant differences in soil trampling; (ii) higher stocking rates resulted in less selective grazing; (iii) soil amendment and higher livestock stocking rates contributed to greater pasture crude protein content; and (iv) the influence of pasture quality on grazing preferences depended on the phase of the pasture-grazing cycle. Overall, these findings are promising indicators of sustainability for extensive animal production in Mediterranean dryland silvopastoral systems. However, with regard to the sward, as this study only monitored a single growing season, will need to be validated in future studies. Full article

Modern Industrial Internet of Things (IIoT) integrates machine learning models for monitoring and control. However, they remain vulnerable to adversarial machine learning (AML) attacks, where an adversary adds small changes to the input data. These small changes degrade model quality, reduce accuracy, and can ultimately compromise the safety and security of the entire system. AML research in IIoT often focuses on individual attack types, defense methods, and datasets. Existing reviews lack a unified quantitative and system-level perspective. Therefore, a systematic literature review (SLR) is needed to provide a holistic analysis of existing attacks, defenses, and databases. This SLR analyzes 50 research articles to provide a holistic view of AML threats in IIoT systems and identifies seven distinct attack types: gradient-based perturbations, GAN-generated samples, poisoning attacks, reinforcement learning-based (RL) strategies, saliency-based feature manipulation, false data injection, and hybrid approaches. To illustrate the range of observed impacts, selected studies report the following degradation examples: saliency-based attacks cause accuracy reductions of 6–11 percentage points; iterative gradient attacks reduce accuracy from 95–99% to 30–40% in SIEM systems; and RL-based attacks reduce detection rates from 100% to 0% in rule-based IDS settings. In addition to the analysis of attack types, this SLR also evaluates current defense methods to protect IIoT systems. It has been observed that existing defense mechanisms lack generalization and require high computational resources. Moreover, the testing is performed under simplified threat models. The analysis of datasets further shows a clear gap between realistic industrial benchmarks (such as SWaT, WADI, and NSL-KDD) and synthetic datasets used for controlled experiments. By connecting attack behavior, defense performance, dataset characteristics, and system-level effects, this SLR identifies the key research gaps that must be addressed in future work. Full article

Isotopic and nuclear techniques, including fallout radionuclides (FRNs), fingerprinting (FP), and isotope hydrology (IH), are essential tools for assessing soil and water degradation. However, as in state-of-the-art reviews, isolated application of FRNs, FP and IH limits their potential to address complex, interconnected environmental processes across landscapes. This study proposes a novel methodology based on the concept of Synergistic Convergence to integrate FRNs, FP, and IH into a unified framework for assessing soil and water degradation. Validated through a case study in Cuba’s Hanabanilla sub-basin, the five-stage methodology improves the identification of erosion hotspots, sediment sources, and water resource vulnerabilities. Results demonstrate that combining FRNs (quantifying soil redistribution), FP (tracing sediment sources), and IH (evaluating water dynamics) provides a robust approach for sustainable landscape management, according to the United Nations Sustainable Development Goals (SDGs) and the One Health framework. The integrated methodology proves superior to the non-integrated approach, connecting causes (erosion), drivers (water), and consequences (sedimentation, pollution). The Synergistic Convergence methodology effectively integrates isotopic and nuclear techniques (INTs) (FRNs, FP, and IH), enabling a holistic assessment of soil and water degradation and their interactions within terrestrial and aquatic ecosystems. Full article

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system, mostly occurring during the reproductive period, and it is diagnosed more frequently in women. The sex biases in the incidence and course of both MS and its most commonly used animal model, experimental autoimmune encephalomyelitis (EAE), seem to be driven by fluctuations in sex hormones. The regulation of sex hormone synthesis and release relies on a dynamic hierarchical system—the hypothalamic–pituitary–gonadal (HPG) axis. This review provides an overview of the main characteristics of MS and EAE pathologies and explains the structure and function of the HPG axis in order to better understand the sex-specific features of MS and EAE. The particular role of sex hormones as culprits in the sex differences in these pathologies is covered, as well as the disturbances to the HPG axis that arise as a consequence of MS/EAE course. Finally, the use of sex hormones as potential adjuvant therapeutics for MS is discussed. Given the complexity and dynamism in the regulation of the HPG axis, an individual, holistic approach should be taken when considering sex hormones for the treatment of MS patients. Full article

The rapid paradigm shift from traditional keyword-matching algorithms to AI-driven answer engines has fundamentally disrupted Search Engine Optimization (SEO). As Large Language Models (LLMs) power modern Search Generative Experiences (SGEs), organizations must transition from legacy web analytics to sophisticated Business Intelligence (BI) frameworks to capture visibility. Despite the immense strategic implications of this shift, academic literature remains fragmented across computer science, information systems, and digital marketing management. To bridge this gap, this paper adopts an integrative literature review methodology, synthesizing 70 high-value studies selected from an initial corpus of 11,382 papers filtered to 2962 on-topic studies. Rather than utilizing restrictive systematic protocols (e.g., PRISMA) that isolate empirical data within narrow boundaries, the integrative approach enables a holistic synthesis of emerging, multi-disciplinary concepts necessary to decode a rapidly evolving phenomenon. Through this methodological lens, this study introduces the Signal–Structure–Surface–Score (4S) lifecycle framework, illustrating how AI-BI systems capture conversational search intents (Signal), architect machine-readable, entity-based data (Structure), optimize content for LLM retrieval and Generative Engine Optimization (Surface), and define novel attribution metrics for zero-click environments (Score). Furthermore, the paper maps the critical technical and strategic landscape, systematically evaluating prevailing trends (e.g., zero-click searches, AI-generated content velocity), core organizational challenges (e.g., search data attribution loss, algorithmic opacity), and emerging strategic opportunities (e.g., real-time intent mapping, competitor LLM audit trails). Ultimately, this paper bridges the gap between AI search mechanics and strategic BI measurement, providing a robust future research agenda designed to guide scholars and practitioners in navigating data-driven visibility in the age of generative search. Full article

Background/Objectives: Malnutrition adversely affects the clinical course of acute myeloid leukemia (AML), yet comparative data on objective nutritional indices remain limited. Methods: This study evaluated the prognostic performance of four indices—Controlling Nutritional Status (CONUT), Simple CONUT, Prognostic Nutritional Index (PNI), and Nutritional Risk Index (NRI)—on overall survival (OS) alongside the European LeukemiaNet (ELN) 2022 risk classification. Pre-treatment parameters of 236 newly diagnosed AML patients were retrospectively analyzed using Receiver Operating Characteristic (ROC) curves and multivariate Cox regression models. Results: In ROC analysis, only NRI demonstrated significant discriminative performance in predicting OS (Area Under the Curve = 0.637, p < 0.001), whereas CONUT, Simple CONUT, and PNI lacked statistical significance. Patients with low NRI scores had significantly worse survival than the high NRI group (median OS: 16.8 months versus not reached, p = 0.004), particularly within the ELN favorable risk category (2-year OS: 59.6% versus 93.5%, p = 0.022). Multivariate analysis established NRI as an independent predictor of mortality (Hazard Ratio = 0.967, p = 0.009) alongside age and ELN risk. Conclusions: In conclusion, NRI outperforms other nutritional indices and serves as an independent prognostic factor in AML, offering a more holistic and effective approach to clinical risk stratification. Full article

Gut microbiota research in inflammatory bowel disease (IBD) is transitioning from holistic community-level associations toward causal validation of individual bacteria and their metabolites. However, existing causal evidence is dispersed across diverse pathways and experimental models, lacking systematic integration and comparative assessment of evidence strength. Building on the concept of grading causal evidence in microbiome studies, we extend this approach into a five-tier progressive validation framework that covers the entire causal chain—from initial association discovery to the identification of specific effector metabolites. Using this framework, we systematically collate the single-bacterium–metabolite–host target axes that have been validated by high-level experimental methods. Focusing on four major pathways—AhR/tryptophan metabolism, bile acid/nuclear receptor signaling, short-chain fatty acid/vitamin/energy metabolism, and cell death-related pathogenic mechanisms—we integrate the molecular mechanisms through which specific bacteria and their causally linked metabolites regulate intestinal barrier integrity, immune responses, and inflammation resolution. We further discuss the modulatory influences of host genetics, diet, and medications on these axes, as well as therapeutic strategies such as live bacterial preparations, engineered probiotics, and postbiotics. Causal studies on individual bacteria and metabolites in IBD have progressed from isolated mechanistic discoveries towards systematic consolidation. It should be acknowledged, however, that most of the high-level evidence summarized in this review derives from animal models and preclinical studies, whereas robust human validation remains limited. In addition, protective mechanisms appear to considerably outnumber pathogenic ones, suggesting a marked imbalance in the current evidence base. To bridge the gap between mechanistic validation and clinical application, future research should focus on validating causal chains from animal models in well-designed human cohorts, exploring pathogenic mechanisms that drive disease onset, and clarifying interactions among different metabolites. By synthesizing available evidence, identifying key research gaps, and acknowledging translational limitations, this review aims to provide a foundational reference for researchers, while recognizing that further translational efforts are needed to move these preclinical findings toward clinical application. Full article

This paper analyzes contemporary medicine as a prime arena for the expression of “engaged spirituality”, understood as an action-oriented approach aimed at social and clinical change. The focus is on palliative care, a person-centered model that challenges biomedical reductionism by integrating the physical, psychological, and spiritual dimensions of the patient. Through a review of the state of the art, the article reconstructs the historical separation between “health” and “salvation”, highlighting the critical issues of the Italian context: “institutional inattention” and difficulties in managing religious pluralism. In contrast, international experiences and the adoption of technical tools demonstrate that spiritual care is now measurable and essential clinical competency. The analysis presents the results of empirical research which, through the voices of healthcare professionals, shows how palliative care translates spirituality into operational practice. By valuing the concept of “total pain”, this approach not only improves quality of life at the end of life but also serves as a holistic paradigm exportable to other medical fields, ensuring the recognition of the person’s integral dignity. Full article