Search Results (587)

The transition from early non-standalone 5G deployments to 5G Standalone and, more recently, 5G-Advanced has turned mobile networks into flexible, programmable infrastructures capable of supporting private, industrial, and research-oriented deployments for the development of beyond-5G applications and architectures. Evaluating these networks’ capabilities, however, remains challenging because commercial platforms often provide limited access to internal interfaces, radio parameters, and network measurements. This paper presents an open-source private 5G SA testbed for beyond-5G application validations built using Open5GS, srsRAN, Ettus USRP N310 software-defined radio, programmable SIM cards, and commercial 5G customer-premise equipment. The platform is deployed in a semi-anechoic chamber. End-to-end operation is validated through subscriber registration, authentication, PDU session establishment, and external data connectivity. The performance of the implemented 5G network is evaluated using throughput, block error rate, modulation and coding scheme, and gNB trace logs. Unlike previous open-source 5G testbeds that primarily use RF waveguides, individual network components, or a limited set of radio configurations, the proposed platform combines COTS SIM-based UE operation with a controlled over-the-air evaluation of FDD/TDD and multiple antenna configurations and correlates application-level throughput with internal gNB radio metrics. For FDD downlink operation, the average throughput increased by approximately 74% from 1 × 1 to 2 × 2 and by a further 57% from 2 × 2 to 4 × 4, although the additional peak-throughput gain from 2 × 2 to 4 × 4 remained limited. The platform provides a reproducible environment for validating beyond-5G mechanisms, comparing network configurations, and studying the behavior of future open-source 5G SA systems under controlled conditions. Full article

Improving foundational mathematical competency remains an important challenge in educational technology and instructional system design. This study presents the design, development, and evaluation of Z-Card, a game-based instructional framework intended to improve students’ mastery of fundamental integer operations. The instructional intervention was developed using the ADDIE instructional design model and validated through expert evaluation based on instructional objectives, design quality, organizational structure, playability, and instructional usefulness. A quasi-experimental pre-test–post-test design involving Grade 7 students was employed to evaluate learning effectiveness using paired sample t-tests and ANCOVA. The results demonstrated statistically significant improvements in mathematical performance among students exposed to the Z-Card framework, with a large treatment effect after controlling for prior knowledge. Expert evaluations likewise indicated high acceptability across all design dimensions. The findings demonstrate that structured game-based instructional systems can effectively integrate learner engagement, conceptual reinforcement, and assessment-driven instructional support. The proposed framework contributes to educational technology by providing a scalable model for designing interactive learning environments that enhance foundational mathematics instruction. Full article

Background/Objectives: Empirical research exploring the linkages between community leisure facility diversity, distinct facility categories, and mental health outcomes among older populations remains scarce, especially regarding gender-specific variations. Methods: Grounded in social capital theory, this study establishes an analytical framework to unpack the underlying mechanisms of these relationships. Based on a sample of 10,270 adults aged 60 and older drawn from the 2023 CLASS, structural equation modeling is applied to investigate the correlational patterns, indirect transmission pathways, and gender heterogeneity embedded in these associations. Results: The results indicate that community leisure facility diversity is positively correlated with better mental health status among older adults, with a total association coefficient of 0.052. Social networks partially mediate this correlational pattern, with an indirect association value of 0.010. Five facility categories exhibit significant positive total associations with mental health, namely senior activity rooms (0.038), fitness centers (0.053), chess and card rooms (0.031), libraries (0.028), and community canteens (0.043), while their indirect association pathways present divergent features. Notably, the linkages between community leisure facilities and mental health are more pronounced for older men. Five facility types show significant positive associations with male mental health, whereas for older women, only senior activity rooms and fitness centers yield significant correlational patterns. Conclusions: These findings suggest that community leisure facility planning can be optimized by shifting from simple quantity expansion to refined, targeted provision with gender-sensitive design. Adopting gender-informed strategies, particularly prioritizing socially supportive facilities and reducing usage barriers for older women, offers a valuable direction for building age-friendly communities and promoting healthy aging. Full article

The present study was performed to determine the antibiotic resistance genes (ARGs), virulence determinants, and mobile genetic elements in multidrug-resistant Escherichia coli CUK-76 isolated from wastewater in Himachal Pradesh, India. Whole genome sequencing was performed using the Illumina Miseq system, and the draft genome sequence was assembled by Unicycler v0.5.1 and annotated by the NCBI Prokaryotic Genome Annotation Pipeline (PGAP v6.10). The bioinformatics-based prediction analysis was performed using ResFinder v4.7.2 and CARD v4.0.1 (antibiotic resistance genes), VirulenceFinder v2.0, VFDB and MGEFinder v1.0.3 (virulence determinants), PlasmidFinder v2.0.1 (plasmid sequences), MLST v2.0 (sequence type), ISFinder and TnCentral v2.0 (insertion sequences and transposons), PathogenFinder2 v0.6.0 (pathogenicity), RAST (subsystems category) and Phigaro (prophage sequences). The draft genome of E. coli CUK-76 strain comprised 4,607,136 bp with a GC content of 51%. Genome annotation revealed 4498 genes of which 4289 were protein-coding genes, 78 RNA genes, and 131 pseudogenes. It was related to sequence type ST949 and its predicted resistome consisted of bla_CTX-M-15, bla_TEM-1B (class A β-lactamase genes), bla_EC-14 (class C β-lactamase gene), aph(6)-Id, aph(3″)-Ib, qnrS1, sul2, tet(A), and dfrA14 genes. Additionally, multiple virulence genes, two plasmid sequences viz. IncFIB(K) and IncFIB(AP001918), insertion sequences, transposons and prophage sequences were detected. The genomic dataset of this strain will be a valuable resource for comparative genomic studies on E. coli. Full article

The Eddy Covariance station provides observations of agrometeorological variables and surface energy fluxes, collected from 2019 to 2022, in a citrus orchard located in the Souss-Massa plain, Morocco. The present dataset comprises measurements recorded via a set of aboveground and subsurface sensors. The aboveground setup consistently measures air temperature, relative humidity, wind speed, net radiation, and precipitation. Additionally, the subsurface setup continuously tracks soil temperature, moisture, and electrical conductivity at depths from 5 to 80 cm, along with soil heat flux. Moreover, these setups enable the measurement of turbulent fluxes (sensible and latent heat). Given the limited availability of long-term agrometeorological data in semi-arid regions of the Mediterranean, this paper addresses a critical data gap by providing a reliable agrometeorological dataset. The latter consists of two types of data: 30 min interval files and high-frequency files (20 Hz, i.e., one measurement every 50 ms). The processing of this data involved Card Convert, MATLAB EC-Pack, and Excel, with data quality control performed by removing outliers and excluding nighttime fluxes. The dataset is organized in a table and provided in a .csv format with standard metadata. It is designed for a wide range of applications, including evapotranspiration modeling, satellite product validation, agroclimatic monitoring, determining crop irrigation requirements, precision irrigation planning, and water management. Additionally, the dataset can be reused for crop and hydrological model calibration, as well as soil moisture and crop stress prediction using machine learning algorithms. Full article

Cities face increasingly complex sustainability challenges that demand cross-sector collaboration, yet existing participatory tools rarely integrate internationally recognised sustainability frameworks with systems-based visualisation in a way that supports coordinated action across diverse stakeholders. This paper presents the Placemaking Maptivity, a card-based serious game that operationalises the ISO 37101 cross-analysis matrix—six sustainability purposes against twelve areas of action—as a shared analytical scaffold for participatory neighbourhood planning. Following a Design Science Research approach, this formative artefact-development study iteratively refined the tool through four rounds of beta testing in online, in-person, and mixed-stakeholder international configurations, drawing use cases from the EU-funded REEFLEX, PROBONO, and eFORT projects. Each game mechanic is traced to a defined learning objective using the Learning Mechanics–Game Mechanics (LM-GM) framework. Stakeholder feedback across iterations provides preliminary observations that the Maptivity supports identification of multi-purpose contributions, mapping of interdependencies, and collaborative prioritisation of next steps while highlighting facilitation, timing, and contextual adaptation as critical success factors. Whether the tool improves planning quality, learning outcomes, or decision-making effectiveness compared to alternative approaches remains a question for future, more rigorously designed evaluation studies. We discuss the formative character of these results, set out limitations, and propose a more rigorous summative evaluation protocol to support broader scaling and adoption of the methodology. Full article

Embedded Subscriber Identity Modules (eSIMs) enable consumer devices to install mobile subscriptions remotely under the GSMA SGP.22 standard for Remote SIM Provisioning (RSP). Because RSP sessions rely on classical elliptic-curve cryptography and eSIM profiles can remain active for 5 to 20 years, recorded provisioning traffic faces a concrete Harvest-Now–Decrypt-Later (HNDL) threat. Upgrading the network transport to post-quantum Transport Layer Security (TLS) is often assumed to be sufficient. However, SGP.22 exchanges the keys that protect the profile across the local host-to-chip interface, beneath the transport layer. This paper presents a systematic post-quantum cryptography (PQC) migration framework for consumer RSP. We model four configurations of the SGP.22 on-card key-agreement step and determine, under a quantum key-recovery adversary, which configurations resist HNDL and what resources they require. We combine symbolic verification in ProVerif with a device-grounded evaluation that pairs provisioning and memory observations from a sysmocom C2T research embedded Universal Integrated Circuit Card (eUICC) with strict-instruction-set PQC measurements on an STM32 Nucleo-F446RE development board with an ARM Cortex-M4F core. Among the configurations studied, hybrid classical and post-quantum key exchange is the minimum configuration that resists HNDL, whereas a fully post-quantum configuration also protects authentication against signature forgery. Under the tested platform and resource assumptions, volatile Random Access Memory (RAM), rather than computation, is the binding deployment constraint. We therefore propose a capability-negotiation mechanism that would match a migration configuration to the memory advertised by each card. Full article

Background/Objectives: Needle-related procedures such as venipuncture are common in pediatric hospitals and are a major cause of pain, fear and distress for those affected. Despite the availability of a wide range of evidence-based support options, it is often the professionals who decide which interventions are offered. In this study, we adapted the CARD^TM (Comfort, Ask, Relax, Distract) system for needle-related procedures in hospitals. CARD^TM was originally developed to encourage children to actively participate in their vaccination process at school. It allows them to choose from numerous evidence-based interventions in the four different letter categories (C-A-R-D) to reduce pain, fear and related vaccination symptoms. Our aim was to examine perceptions of CARD^TM for needle-related procedures in a children’s hospital, including aspects of acceptability, feasibility, self-efficacy in managing fear and pain, and overall experiences. Methods: A qualitative descriptive design was used. The sample included nine children aged 10 to 15 undergoing needle-related procedures and seven nurses who performed these procedures. We conducted individual interviews and asked them about their experiences with CARD^TM. Data were evaluated using qualitative content analysis. Results: Four themes were identified: awareness of options and needs; relationship building; empowerment; and acceptability. CARD^TM helped children identify available options, prepare themselves, recognize their own needs and select strategies. CARD^TM offered a concrete framework for action that promoted participation and self-efficacy and strengthened the relationship between nurses and children. In practice, CARD^TM was perceived to be easy to implement and acceptable. Conclusions: The present findings suggest the applicability of CARD^TM for hospital needle-related procedures. Full article

This paper presents an end-to-end system for the automatic summarization of football matches through temporally accurate event spotting across six action categories: goal, card, substitution, kick-off, direct free-kick, and corner. These six classes were selected from the SoccerNet-v2 annotation taxonomy as a non-standard evaluation subset: the three standard SoccerNet-v2 classes (goal, card, substitution) are retained and extended with three additional context-dependent set-piece classes (kick-off, direct free-kick, and corner) that represent the primary unresolved challenge in temporal action spotting. We developed and empirically evaluated a framework based on a Temporal Convolutional Network (TCN) with capsule-based relational encoding applied to class-specific Time-Shift Encoded (TSE) labels using a composite segmentation-detection loss. Evaluated on the SoccerNet-v2 benchmark (300/100/100 train/validation/test splits) using the official PCA-compressed ResNet-152 features sampled at 2 FPS, the implemented TCN-Capsule baseline achieved a test-set mean Average Precision (mAP) of 58.16% at a 10 s tolerance threshold (δ = 20 frames), with a validation mAP of 58.55%, indicating strong generalization with only a 0.39 pp performance gap. The six per-class AP values underlying this result are Goal: 75.6%, Corner: 78.0%, Substitution: 56.9%, Card: 53.9%, Direct Free-kick: 52.8%, and Kick-off: 34.3%; the headline mAP is computed by the official SoccerNet area-under-precision-recall-curve script and is not a simple arithmetic average of these six values. In addition, five complementary evaluation metrics are introduced: Average Temporal Error (ATE), Temporal Recall@K (TR@K), Latency-to-Event (L2E), Temporal Causality Consistency (TCC), and Annotation Noise Sensitivity. The analysis reveals that visually salient events such as goals and corners are detected with high accuracy (AP > 75%, ATE < 5 s, AUC > 0.95 at frame-level), whereas context-dependent events, including kick-offs and direct free-kicks, remain challenging (AP < 55%, ATE > 8 s, AUC = 0.68–0.72). As future work, two architectural extensions are formally specified but not empirically evaluated: a Temporal Segment Network with Non-Local Blocks and a hybrid Transformer-CNN framework with optical flow fusion. Furthermore, an OpenCV-based highlight generation prototype is implemented; formal quality evaluation is planned as future work. Full article

Deep dermatophytosis is a rare, life-threatening fungal infection characterised by the invasion of dermatophytes beyond the superficial layers of keratinised tissue into the dermis and subcutaneous tissues. The present review aimed to identify the current knowledge on the role of Caspase Recruitment Domain-containing protein 9 (CARD9) deficiency in the pathogenesis, clinical spectrum, diagnosis, and management of deep dermatophytosis. For innate immune activation, CARD9 acts as an adaptor molecule. Basically, CARD9 helps mediate the connection between the fungal pattern recognition receptor (Dectin-1) and the NF-κB and MAPK signalling pathways, and it mediates cytokine production, thereby activating phagocytic activities. Thereby, any change or mutation in the CARD9 gene may disrupt these pathways, leading to dysfunctional neutrophils and impaired Th17-mediated antifungal immunity. Clinically, patients with CARD9 deficiency are immunocompetent but susceptible to recurrent and/or severe fungal infections [Candida, dermatophytes (Trichophyton spp.), and phaeohyphomycetes]. Deep dermatophytosis in these patients is usually chronic, treatment-resistant, and characterized by erythematous papules, nodules, plaques, ulcers, or necrotic lesions, most of which occur on the lower limbs. It usually occurs in adulthood and is more common in males. There have been instances of geographic clustering of CARD9 deficiency in Asia, North Africa, and the Middle East. Early recognition and genetic diagnosis of CARD9 mutations in patients with recurrent or atypical deep dermatophytosis. Although antifungal therapy is essential, hematopoietic stem cell transplantation can be a definitive treatment for selected patients with CARD9 deficiency. Thus, CARD9 deficiency is a critical factor in the better management of patients but remains an underrecognized cause of severe, treatment-resistant deep dermatophytosis, and early genetic diagnosis is essential for guiding targeted management and improving patient outcomes. This review emphasises the importance of CARD9 in antifungal immunity and underscores the need for greater clinical awareness and the incorporation of genetic evaluation into the management of deep dermatophytosis. Full article

Host genetic susceptibility to urogenital Chlamydia trachomatis (Ct) reinfection remains poorly understood. Coding variants identified in prior genome-wide association studies (GWAS) explained only a small fraction of the risk of reinfection. Our goal in this study was to characterize whether more risk would be captured by sequence variation that traditional GWAS insufficiently captures. Specifically, we evaluated the risk attributable to SNPs present in regulatory, non-coding regions; post-transcriptional regulation by microRNAs (miRNAs) that may depend on sequence variation in either the miRNA or the target mRNA; and copy number variants (CNVs). We analyzed GWAS data from African American women with or without documented urogenital Ct reinfection. Fine mapping and independent association analyses identified 30 unique index single-nucleotide polymorphisms (iSNPs), which were expanded to variants in linkage disequilibrium. Regulatory annotation was performed using HaploReg, RegulomeDB, FORGEdb, rSNPBase, and GTEx. We examined whether genes identified in the Ct reinfection GWAS are targeted by known Ct infection–associated microRNAs using curated databases. Genome-wide CNV calling was conducted using SNP intensity data, followed by stringent quality control and gene-level association testing. Functional annotation prioritized 7 SNPs with strong regulatory evidence, with stringent criteria for regulatory relevance, using HaploReg, RegulomeDB, FORGEdb, and rSNPBase. The strongest signals were observed at the CHIT1 locus, where multiple intronic variants (including rs2486963 and rs2244385) overlapped regulatory chromatin, altered transcription factor binding motifs, and acted as cis-expression quantitative trait loci for CHIT1 in whole blood. Additional regulatory variants were identified near TDRP, ERICH1, and DLGAP1, showing tissue-specific regulatory effects. MicroRNA analysis revealed extensive post-transcriptional targeting of SOCS6 and SULF1, while CHIT1 showed no curated Ct-associated miRNA interactions. CNV analysis identified 5775 high-confidence events, with nominal gene-level associations observed for ATAD3A, CARD14, TMEM240, and ZNF140. These results indicate that a greater fraction of the susceptibility to urogenital Ct reinfection may be driven by genetic variation affecting immune and epithelial pathways rather than protein-coding changes. Full article

This research focuses on the application of convolutional neural networks (CNNs) for fault detection in ignition coils and fuel injectors of a YESA 3140 gasoline engine. The objective is to design a CNN capable of identifying when the spark ignition engine (SIE) is operating under optimal conditions and when it presents specific power supply disconnection faults in the four injectors and four coils. Signals from the knock sensor (KS) and camshaft position sensor (CMP) of the SIE were acquired using a MyDAQ data acquisition card and LabVIEW software version 2024. A strict sampling protocol was followed: each replicate had a duration of 5 s while the engine was running at normal operating temperature and idle speed. Prior to each sampling, the SIE was operated with the corresponding fault induced for 5 min. The signals obtained from the KS sensor were transformed into spectrograms, which were then used to train various CNN models. The resulting CNN achieved a classification error of 3.21%. The algorithm was validated by inducing supervised faults in various Otto cycle engines. Full article

Large-scale language models can produce anomalous outputs that cannot be explained solely by the quality of input data. This article presents a systematic review and descriptive quantitative synthesis of published evidence on reasoning anomalies in LLMs. The study does not report original experiments, does not evaluate new model outputs, and does not implement the proposed framework. Instead, it consolidates numerical results manually extracted from published papers, public benchmarks and official system cards, with the derived datasets and figure-generation scripts. The review organizes reasoning-related anomalies into a taxonomy that distinguishes factual hallucinations, self-contradictions, unfaithful Chain-of-Thought traces, semantic rollback, snowball errors, distractor susceptibility and sycophancy bias. Published evidence indicates that irrelevant context can reduce accuracy below 30% in controlled mathematical reasoning settings, and that knowledge and reasoning tasks can differ by more than 12 percentage points in reported biomedical benchmarks. Existing mitigation techniques, including self-consistency, semantic entropy, process reward models and formal verification, are compared descriptively across heterogeneous studies and domains. Formal verification results, such as the 91.7% reported for VERGE on AR-LSAT, are explicitly limited to structured logical reasoning and should not be generalized to open-domain natural language reasoning. Finally, the article proposes a four-layer conceptual architecture grounded in access-consciousness and monitoring-consciousness operators, C_A(t) and C_M(t), for filtering context, generating reasoning paths, monitoring inferential discrepancies and activating selective correction. The framework is presented as an implementable research roadmap whose empirical validation, computational overhead and activation thresholds remain future work. Full article

Background: SGLT2 inhibitors improve outcomes in heart failure with reduced ejection fraction (HFrEF), but whether early recovery patterns after initiation differ according to HF etiology in real-world practice remains uncertain. Objective: To evaluate whether ischemic versus non-ischemic etiology is associated with different 6-month cardiac, renal, biomarker, and exploratory metabolic trajectories after early in-hospital SGLT2 inhibitor initiation in HFrEF. Materials and Methods: In this prospective single-center observational cohort (2022–2025), consecutive adults hospitalized with first-presentation acute HFrEF who initiated empagliflozin or dapagliflozin within 48 h of admission were enrolled. Patients were classified as having ischemic cardiomyopathy (ICM) or non-ischemic cardiomyopathy (NICM). The primary analytic cohort included patients with paired baseline and 6-month echocardiography. The primary outcome was change in left ventricular ejection fraction (LVEF); eGFR and NT-proBNP were secondary outcomes. Exploratory metabolic/laboratory variables were summarized descriptively using paired available-case follow-up. The study was approved by the institutional ethics committee and registered in ClinicalTrials.gov under the CaRD registry framework (NCT06090591). Results: The paired 6-month echocardiographic analytic cohort comprised 241 patients who survived to reassessment (ICM n = 90; NICM n = 151). NICM showed greater improvement in LVEF than ICM (ΔLVEF +10% [IQR 0–18] vs. +5% [IQR 0–12]; p = 0.049) and a more favorable eGFR trajectory (ΔeGFR 0.30 [IQR −5.90 to 6.60] vs. −2.70 [IQR −12.60 to 3.40] mL/min/1.73 m²; p = 0.038). NT-proBNP declined substantially in both groups, with no between-group difference in change magnitude (p = 0.845), although 6-month values remained higher in ICM (p = 0.034). However, after multivariable adjustment, ischemic etiology was no longer independently associated with 6-month LVEF or eGFR outcomes. Exploratory metabolic findings varied descriptively by etiology but should be interpreted cautiously because follow-up completeness and background treatment intensity varied across variables. Conclusions: In this real-world cohort of patients with HFrEF who initiated SGLT2 inhibitors during hospitalization, HF etiology was associated with different short-term cardiorenal recovery patterns, whereas NT-proBNP reduction was similar across groups. These findings characterize etiology-related recovery within a treated cohort rather than differential SGLT2 inhibitor efficacy and should therefore be considered as hypothesis-generating. Full article

Elite women’s rugby has often been analysed using the male performance model as a reference, despite evidence that women’s rugby presents distinct game demands and potentially different risk profiles. This study aimed to compare the frequency of key contact-related events between elite men’s and women’s rugby. An observational, retrospective, comparative cohort study was conducted using official performance data from 135 international matches from the men’s and women’s Six Nations Championships. Variables were grouped into three categories: Open-Play, Static Phases, and Discipline. Independent samples t-tests, Mann–Whitney U tests, and Linear Discriminant Analysis were used to identify sex-based differences. The results showed that men presented a higher frequency of rucks lasting more than 6 s (p < 0.001), whereas no significant differences were found in total tackles (p = 0.378) or total rucks (p = 0.634). In Static Phases, women’s teams recorded significantly more scrums (p < 0.001). In Discipline, women conceded fewer free kicks (p = 0.003) but received more red cards (p = 0.020). In conclusion, elite women’s rugby shares some open-play characteristics with the men’s game but differs in scrum frequency and disciplinary profile, supporting the existence of a distinct contact and risk exposure profile that should be considered when designing training and prevention strategies. Full article