Search Results (55,219)

The Industrial Internet of Things (IIoT) has become a cornerstone of modern industrial automation, enabling real-time monitoring, intelligent decision-making, and large-scale connectivity across cyber–physical systems. However, the growing scale, heterogeneity, and dynamic behavior of IIoT environments significantly expand the attack surface and challenge the effectiveness of conventional security mechanisms. In this paper, we propose DeepSense, a hybrid and adaptive anomaly and intrusion detection framework specifically designed for resource-constrained and heterogeneous IIoT deployments. DeepSense integrates three complementary components: DataSense, a realistic data pipeline and experimental testbed supporting synchronized sensor and network data processing; RuleSense, a lightweight rule-based detection layer that provides fast, deterministic, and interpretable anomaly screening at the edge; and NeuroSense, a learning-driven detection module comprising an adaptive ensemble of 22 machine learning and deep learning models spanning classical, neural, hybrid, and Transformer-based architectures. NeuroSense operates as a second detection stage that validates suspicious events flagged by RuleSense and enables both coarse-grained and fine-grained attack classification. To support rigorous and practical assessment, this work further introduces a comprehensive performance evaluation framework that extends beyond accuracy-centric metrics by jointly considering detection quality, latency, resource efficiency, and detection coverage, alongside an optimization-based process for selecting Pareto-optimal model ensembles under realistic IIoT constraints. Extensive experiments across diverse detection scenarios demonstrate that DeepSense exhibits strong generalization, lower false positive rates, and robust performance under evolving attack behaviors. The proposed framework provides a scalable and efficient IIoT security solution that meets the operational requirements of Industry 4.0 and the resilience-oriented objectives of Industry 5.0. Full article

Sea ice classification is of fundamental importance for polar monitoring and global climate research. Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a frontier technology in polar remote sensing due to its high spatiotemporal resolution and cost-effectiveness. Based on BeiDou System Reflectometry (BDS-R) data acquired from the Fengyun-3E (FY-3E) satellite, this study introduces a classification approach that integrates multi-dimensional sea ice information. A comprehensive feature set was constructed by integrating the Spectral Entropy (SE) of the Normalized Integrated Delay Waveform (NIDW) First-order Differential Curve to characterize the oscillatory complexity of the trailing edge power decay process as a scattering dynamic property, the Root Mean Square height (RMS) to characterize the attenuation magnitude of scattering intensity arising from surface roughness and related factors as a scattering intensity attenuation property, and salinity (S) and L-band brightness temperature (TB) data from SMOS to describe dielectric and radiative properties. These novel features are combined with traditional GNSS-R features. After selecting the optimal feature set via an ablation study, the features were used to train a Random Forest (RF) classifier for sea ice classification. Validated against Ocean and Sea Ice Satellite Application Facility (OSI SAF) sea ice type products, the proposed method yielded an overall accuracy of 93.86% and a Kappa coefficient of 0.8061. The integration of multi-dimensional features notably improved the identification of Multi-Year Ice (MYI), achieving a Recall of 85.11% and an F1-score of 84.43%. These results indicate that the proposed multi-dimensional feature set provides an effective solution for GNSS-R-based sea ice classification. Full article

Internet Gaming Disorder (IGD) has emerged as an increasingly prevalent behavioral health concern among late adolescent university students, a vulnerable population with emotional distress due to the developmental changes and academic pressures. This research explored the direct correlations between IGD and Mental Health Disorder (MHD), such as depression, anxiety, and stress in Saudi Arabia (SA) with study discipline as a moderator. A total of 480 students participated in the developed self-structured questionnaire, and Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to analyze the obtained data. The results showed that IGD can exert a positive and significant association with all three aspects of MHD. Moreover, the PLS-SEM slope analysis indicated that study discipline can significantly moderate the link from IGD to both anxiety and depression, with university students in health, science, and engineering fields displaying higher symptoms of depression and anxiety as compared to their peers in humanities and social sciences. However, study discipline failed to moderate the link from IGD to stress. These findings can be interpreted through maladaptive coping mechanisms and behavioral addiction, whereby extreme IG can contribute to social withdrawal, reduce sleep quality, and worsen stress regulation, specifically during the late adolescence period. The results extend current research on IGD by emphasizing the disciplinary differences in mental health vulnerability and offering more empirical evidence from a Middle Eastern context. The study highlighted the urgent need for discipline-oriented mental health screening and targeted proactive interventions to deal with unsettled IG attitude within a higher education context. Full article

Objectives: The objectives of this review are to explore the effects of various nutrition and exercise lifestyle interventions on pregnancy outcomes in individuals with, or at risk of, gestational diabetes mellitus (GDM), as well as to examine whether interventions that are culturally and/or religiously sensitive influence clinical and behavioural outcomes. Methods: This study was conducted as a narrative review. PRISMA was used solely as a reporting guide to enhance transparency in the search and study selection process. PubMed/MEDLINE, CINAHL, and Scopus were searched for studies published up to November 2025. Intervention-based studies evaluating nutrition, physical activity, or combined lifestyle interventions targeting either GDM incidence, insulin use, or glycemic outcomes were included. Forty-three studies met eligibility criteria. Study designs consisted primarily of randomized controlled trials (RCTs) with one case–control and one quasi-experimental design trial. Results: Combined lifestyle interventions generally showed the most consistent improvements in glycemic control; however, findings were not uniform across all studies, and reporting on insulin outcomes was limited. The Mediterranean, low-glycemic index (LGI) and DASH diets, along with supervised, prenatal exercise programs with low–moderate intensity, delivered at least three times per week, were effective in managing GDM. Regarding culturally or religiously sensitive interventions, only one study was identified. Conclusions: Lifestyle interventions may improve glycemic outcomes in GDM; however, further high-quality research is needed, particularly studies incorporating culturally and religiously sensitive approaches and improved reporting of insulin-related outcomes. Full article

In Ghana’s political landscape, actors from both ruling and opposition parties deploy a range of linguistic and rhetorical strategies in their pursuit of political power. Prominent among these is political labeling, a discursive practice used to construct favorable self-images while delegitimizing opponents through derogatory and face-threatening expressions. This study examines how political labeling functions as a strategic tool for identity construction and power negotiation in Ghana’s electoral landscape. Situated within the fields of political discourse and communication studies, the study demonstrates how labeling operates simultaneously as a rhetorical and framing device that reflects and reinforces underlying sociopolitical power dynamics. Drawing on empirical data from major Ghanaian news portals, the study adopts an integrated analytical framework combining Framing Theory and the Theory of Impoliteness. It analyzes public labeling directed at three prominent political figures across three election cycles (2016, 2020, and 2024). The findings show that politicians, activists, and their supporters strategically deploy labels to reconstruct rivals’ identities, inflict reputational damage, and provoke ridicule, thereby undermining their perceived competence and public credibility. Focusing on derogatory labels, we argue that political labeling serves primarily to generate emotional responses, shape public perception, and mobilize collective action, ultimately influencing the trajectory of national political discourse. By examining the interplay between language, identity construction, and power, this research offers a nuanced account of how political labeling shapes individual attitudes, group dynamics, and the broader political culture in Ghana. Full article

Background: Acute myeloid leukemia with extramedullary disease (EMD-AML) represents a distinct clinical entity associated with diagnostic and therapeutic challenges, and its prognostic significance remains uncertain. Methods: A retrospective study of 617 adults with newly diagnosed AML (2005–2018) was conducted, analyzing 246 patients with EMD-AML and 371 without EMD involvement. The clinical characteristics and treatment outcomes were analyzed. Propensity score matching (PSM) was applied to adjust for baseline confounders. Results: Patients with isolated EMD-AML and those with concurrent bone marrow involvement had comparable clinical outcomes. NPM1 mutations (48% vs. 25%, p = 0.0002) and t(8;21) translocation (23.2% vs. 3.7%, p < 0.001) were enriched in the EMD-AML cohort. After PSM, EMD-AML patients achieved a higher overall response rate compared with non-EMD-AML (88.1% vs. 72.0%, p = 0.0002) but experienced significantly higher relapse rates (35.7% vs. 15.5%, p < 0.0001). Despite the achievement of a higher response rate, EMD-AML was associated with shorter median overall survival (OS) (14.2 vs. 64.1 months, p < 0.0001) and event-free survival (EFS) (9.5 vs. 55.9 months, p < 0.0001). In a multivariable analysis, EMD-AML remained independently associated with worse OS and EFS (OS HR 1.79, p = 0.01; EFS HR 1.95, p = 0.001). Allogeneic hematopoietic stem cell transplantation did not confer a survival advantage in EMD-AML patients. Conclusions: EMD-AML, whether isolated or concurrent with bone marrow disease, represents a high-risk entity characterized by poor long-term outcomes despite strong initial response rates. Obtaining tissue biopsies for molecular profiling may help improve risk stratification, identify targetable mutations and guide individualized treatment. Full article

This article introduces novel methodologies, coordinate systems, and procedures in computational geometry that further develop a Euclidean-based relationalistic framework. The objective is to describe tools using object-oriented relational elements with symmetry, anchored to a fixed point in a relational model, that generate structured point sets serving as blueprints for geometric figures and physical structures representing their source objects. Geometric operations and transformations construct ratio figures and ordered proportional structures. Using discrete $\mathbb{N}$-Euclidean geometry, two relational coordinate systems are introduced—polar-vertex coordinates and radial coordinates—both formed through discrete geometric operations. A relational unit circle of fixed magnitude is defined by a 4::1 proportional equivalence between radius and angular ratios, independent of real-number or arc-length geometry. Euclid’s theory of proportion is extended from static abstract magnitudes to symmetry-driven geometric construction, and a square-pyramid geometric blueprint is produced from an Earth ratio figure with accurate dimensional magnitudes. The findings reveal a novel commensurability between the radius of a circle and the side length of a square using a shared fixed point coupled via a 3:4:5 Pythagorean-triple triangle, introducing the concept of ordered proportions. Full article

Mast cells are heterogeneous, tissue-resident immune sentinels best known for their roles in allergy and peripheral inflammation. The discovery of mast cells within the meninges and brain parenchyma over a century ago raised enduring questions regarding their function in the central nervous system (CNS), their ontogeny, and distinction from peripheral counterparts. Brain mast cells are sparse and predominantly located in perivascular niches rather than forming dense aggregates, a feature that has made them difficult to study. Nevertheless, accumulating evidence implicates mast cells in diverse aspects of CNS physiology and pathology, including regulation of blood–brain barrier permeability and neurovascular function, as well as immune surveillance in contexts of infection and injury. The ability of mast cells to communicate with neighboring glial and neuronal networks suggests potential roles in modulating neural activity, development, and behavior, although this dimension remains incompletely understood. Much of the foundational literature predates advanced immunological tools, contributing to persistent misconceptions regarding the identity and significance of brain mast cells. In this review, we outline the history of research investigating this enigmatic aspect of mast cell biology, clarifying what is known, what remains speculative, and how emerging insights may help redefine the boundaries between classical immunology and neuroscience. Full article

Triple-negative breast cancer (TNBC) has been associated with a poorer prognosis than other subtypes, due to its more aggressive behaviour. Since 2020, significant advances in locoregional and systemic therapy have improved outcomes for patients with TNBC, but the implementation of these treatments remains inconsistent across Canada. There is, therefore, a critical need for evidence-informed, consensus-driven guidance to support the integration of new therapies into practice. Research Excellence, Active Leadership Canadian Breast Cancer Alliance (REAL Alliance), a pan-Canadian group of breast cancer specialists and Breast Cancer Canada, a patient advocacy organization, convened to develop national clinical consensus recommendations for the management of breast cancer. Through a selective literature review and modified Delphi process of national experts in the fields of medical oncology, radiation oncology, surgical oncology and pharmacy, REAL Alliance developed national consensus recommendations for the management of TNBC. The result is a set of 23 recommendations: four overall general recommendations, 11 in early-stage TNBC, and eight in metastatic TNBC. These recommendations are intended for oncology healthcare professionals, and are intended to guide evidence-informed, consistent care across Canada. Full article

Background: Esophageal squamous cell carcinoma (ESCC) remains a highly lethal malignancy with limited therapeutic options, in part due to frequent activation of nuclear factor erythroid 2-related factor 2 (NFE2L2 or NRF2). Gain-of-function mutations in NRF2 disrupt its negative regulation by Kelch-like ECH-associated protein 1 (KEAP1), resulting in sustained NRF2 signaling that promotes tumor growth and resistance to chemotherapy and radiation. We previously identified the FDA-approved drug pyrimethamine (PYR) as an NRF2 inhibitor and demonstrated that inhibition of dihydrofolate reductase (DHFR) represents the primary mechanism underlying its NRF2-suppressive activity, supporting its advancement into a Phase I window-of-opportunity clinical trial (NCT 05678348). Meanwhile, in NRF2^W24C-KYSE70 and NRF2^D77V-KYSE180 cells, PYR promoted NRF2^Mut ubiquitination and proteasomal degradation and shortened its half-life. This study aims to explore additional modes of action by which PYR inhibits NRF2. Methods: Cell cycle analysis was performed by flow cytometry. Cell proliferation, apoptosis and chemosensitivity were assessed by Live-Cell Analysis System, while radiosensitivity was evaluated using X-ray irradiation and the CellTiter-Glo assay. Molecular interactions between NRF2 and KEAP1 were examined through Co-IP and PLA, and the direct binding of PYR to KEAP1 was quantified using ITC and SPR. Molecular docking and dynamic simulations were employed to predict potential PYR-binding pockets within the Kelch domain. Results: Using genetically defined isogenic ESCC cell models, we show that activation of mutant NRF2 (NRF2^Mut) or wild-type NRF2 (NRF2^WT) produces distinct, context-dependent effects on squamous differentiation, proliferation, and therapeutic response. We further demonstrate that PYR restores sensitivity to chemotherapy and ionizing radiation in NRF2^Mut ESCC cells. Mechanistically, short-term PYR treatment promotes KEAP1-dependent proteasome-mediated degradation of NRF2^W24C. Biochemical and biophysical assays indicate that PYR enhances the interaction between KEAP1 and NRF2^W24C in a manner associated with KEAP1-dependent proteasomal degradation. Computational modeling further suggests that PYR may engage a pocket within the Kelch domain to facilitate the NRF2^W24C-KEAP1 interaction. Conclusions: These findings show that PYR functionally restores KEAP1-mediated NRF2 degradation of select NRF2^Mut through a glue-like effect and overcomes therapy resistance in ESCC. Although the proposed glue-like mechanism remains hypothetical, this work supports further investigation into the NRF2–KEAP1 interaction and may inform the development of KEAP1-targeted strategies for NRF2^Mut cancers, including ESCC. Full article

Patients following brain tumour resection experience significant disability, yet rehabilitation is not typically delivered prior to adjuvant treatment such as radiation or chemotherapy. This study aims to characterize the medical and functional profiles, and function outcomes of patients with brain tumour admitted over the past four years to a pilot inpatient prehabilitation programme following brain tumour resection but prior to adjuvant therapy, and to compare these findings with those of patients in a standard acquired brain injury rehabilitation programme. We retrospectively reviewed the charts from a randomly selected sample of 58 prehabilitation inpatients and 112 patients with acquired brain injuries at Toronto Rehabilitation Institute between March 2020 and December 2024. Data abstracted included demographics, medical and functional profiles, Functional Independence Measure (FIM) scores, and discharge parameters. Compared with acquired brain injury subjects, prehabilitation subjects had significantly less physical (47% vs. 86%, p < 0.0001) but more communication (46% vs. 20%, p = 0.0005) impairments, though with similar mean FIM change (22.5 vs. 26.0, p = 0.082) and FIM efficiency (1.1 vs. 1.0, p = 0.78). While not reaching significance, they also experienced more mood issues during rehabilitation (30% vs. 18%, p = 0.075). These findings support that prehabilitation after brain tumour surgery but before adjuvant therapy is clinically effective within existing ABI rehabilitation programmes. However, prehabilitation programmes may benefit from staffing models that emphasize communication supports and mental health expertise. Full article

The ubiquitous use of electronic devices requires outdoor charging capabilities. A successful approach uses solar photovoltaic (PV)-powered picnic tables, but the existing designs share several limitations including proprietary designs that limit replication/modification and high costs. This study addresses these limitations by presenting the design of a novel open-source solar-powered picnic table fabricated from reused, decommissioned PVs and recycled plastic lumber. The open-source solar-powered picnic table acts as a conventional picnic table and provides electrical charging that supports learning and connectivity by providing outdoor power. The system integrates a 320 W PV module, maximum power point charge controller, and 12 V LiFePO₄ battery, enabling reliable off-grid power generation and storage. The device was validated under real outdoor operating conditions using everyday user loads, including smartphones, tablets, and laptops as individual and multiple connected devices at different times of the day and night. In addition to this functionality, the materials cost was <USD 450, 90–95% less than commercially available options. The system, built using recycled and repurposed components, further enhances sustainability while maintaining durability for outdoor deployment. These results indicate that open-source solar furniture can provide an affordable and replicable approach for expanding renewable-powered charging access in outdoor environments. Full article

In this study, Mask R-CNN was applied to 5-band raw reflectance images to detect potato plants in UAV images. The highest model performance across all metrics was achieved with a ResNeXt-101 backbone and transfer learning from the same model trained on apple orchard data. An F-1 score of 84.2% was achieved. To determine whether the plant was infected with PLB, two methods were used. In the first method, a Mask R-CNN with a DINOv3 small variant backbone was applied to 5-band raw reflectance images. The highest achieved F1-score was 69.05%. In the second method, classical ML classifiers were applied to the 5-band raw reflectance images and 16 associated vegetation index images. The highest F1-score (66.71%) was obtained with a decision tree classifier applied to the 16 vegetation index images. Feature importance analysis indicated that chlorophyll- and red-edge-related indices, such as CIgreen, TCARI, OSAVI2, and Red-edge NDVI, were the most discriminative features for distinguishing healthy and unhealthy potato plants. These results show the effectiveness of combining deep learning and machine learning approaches for potato late blight detection using UAV multispectral imagery. Full article

Shigella spp., and Escherichia coli exhibit notable genomic and phenotypic similarities, including serologically and genetically related somatic antigens. For example, the relationship among pathogenic strains E. coli 64474, O179, O188, and S. boydii O16 suggests a shared clonal origin. To evaluate their genomic proximity, a comparative genomics study was conducted using whole-genome sequencing. Comparative genomics involved rfb gene cluster regions and whole-genome comparisons. Phylogenomic inferences were performed using the virtual genome fingerprint (VGF) method with bootstrap support. The results revealed a high degree of genomic similarity and a close evolutionary relationship among E. coli strains, which also demonstrated genetic associations with clinically relevant pathotypes through the presence of virulence genes. Furthermore, serogroups 64474, O188, and S. boydii O16 exhibited close genetic relationships, suggesting that serotype 64474 could represent a novel serogroup, although its similarity to O188 indicates the influence of divergent factors. These findings support the hypothesis that these E. coli strains originated from a common clonal lineage, enhancing our understanding of serogroup diversity and the evolutionary dynamics within enteric pathogens. Full article