Search Results (2,969)

Background and Objectives: Corneal collagen cross-linking (CXL) halts keratoconus progression, yet potential differences between conventional and accelerated protocols at one year remain uncertain. We analyzed the completed 12-month follow-up of a previously reported 6-month cohort to compare conventional (3 mW/cm² × 30 min; CXL 30) versus accelerated (9 mW/cm² × 10 min; CXL 10) CXL, interpreting outcomes within the ABCD framework alongside Kmax and curvature radii. Materials and Methods: In this single-center retrospective longitudinal analysis of prospectively collected routine clinical data, 22 eyes were included, with assessments performed at baseline and at 1, 3, 6, and 12 months of follow-up. Evaluated outcomes comprised ABCD stages (A–D), anterior and posterior radius of curvature (ARC and PRC), Kmax, pachymetric and elevation indices, as well as UDVA and BCVA. Within-group change used Friedman with Wilcoxon post hoc; between-group differences used Mann–Whitney (α = 0.05). Results: Both protocols resulted in significant visual improvement and Kmax reduction at 12 months (overall time effect: CXL 30 p < 0.001; CXL 10 p = 0.026). Median Kmax decreased 56.5 → 52.3 D (CXL 30) and 59.3 → 58.3 D (CXL 10). UDVA improved 0.2 → 0.6 (CXL 30) and 0.2 → 0.3 (CXL 10); BCVA 0.4 → 0.8 (CXL 30) and 0.2 → 0.5 (CXL 10). Tomographic analysis showed predominantly anterior changes, with a significant decrease in A stage in the CXL 30 group and an increase in ARC in both groups, more pronounced in CXL 30. In the late 6 → 12-month window, posterior metrics (PRC and posterior elevation) were largely stable; raw PRC change did not reach significance. Conclusions: Conventional and accelerated CXL both stabilized keratoconus at one year with meaningful functional gains. Beyond 6 months, remodeling was predominantly anterior; within-group findings suggested a more pronounced anterior tomographic response in the CXL 30 group. The 12-month visit may be useful for reassessing stability after CXL, although this study was not designed to determine optimal retreatment timing or optical rehabilitation strategy. Longer-term studies with standardized biomechanical and densitometric endpoints are warranted to assess durability and refine protocol selection. Full article

Background/Objectives: Parathyroid hormone (PTH), which rises compensatory with vitamin D insufficiency and has been shown to down-regulate vitamin D receptor expression, represents a biologically plausible effect modifier. We investigated whether pretreatment serum PTH modifies the effect of postoperative vitamin D supplementation on relapse-free survival, and whether adding tumor p53 status further refines subgroup identification in an exploratory analysis. Methods: This post hoc analysis utilized data from the AMATERASU trial (UMIN000001977), a single-center, randomized, double-blind, placebo-controlled trial evaluating vitamin D3 (2000 IU/day) versus placebo in patients with curatively resected stage I–III digestive tract cancers (maximum follow-up, 7.5 years). Patients were dichotomized at the cohort median PTH (41 pg/mL). The primary outcome was relapse-free survival (RFS), analyzed using multivariable Cox proportional hazards models. Results: Of 417 randomized patients, 410 had baseline PTH data. In the lower PTH subgroup (≤41 pg/mL), vitamin D significantly improved RFS compared with placebo (fully adjusted hazard ratio [HR], 0.45; 95% confidence interval [CI], 0.24–0.81; p = 0.008). Conversely, no benefit was observed in the higher PTH subgroup (>41 pg/mL; fully adjusted HR, 1.25; 95% CI, 0.64–2.44; p for interaction = 0.016). Exploratory stratification of 365 patients with p53 data showed that the supplementation benefit appeared greatest in patients with both low PTH (≤41 pg/mL) and p53-positive tumors (fully adjusted HR, 0.38; 95% CI, 0.18–0.78; p = 0.009). Conclusions: Pretreatment serum PTH is a candidate effect modifier of postoperative vitamin D supplementation in digestive tract cancers. Full article

Children in residential care constitute a particularly vulnerable group at high risk of developing emotional and behavioral difficulties as a consequence of adverse experiences and dysfunctional family environments. Identifying risk and protective factors is essential for designing interventions tailored to their needs; however, the available research remains limited and does not always provide the evidence required to guide effective programs within the child protection system. The aim of this study was to examine the prevalence of emotional and behavioral problems among children in residential care and to analyze the role of family factors, sex, and age in these difficulties. The sample consisted of 210 children aged 6 to 18 years institutionalized in residential care centers and supervised apartments. A cross-sectional design was employed, administering the Strengths and Difficulties Questionnaire (SDQ) along with an ad hoc questionnaire to collect socio-family variables. The results reveal a high prevalence of emotional and behavioral difficulties. The multivariable models explained between 8.1% and 29.4% of the variance in emotional and behavioral functioning and showed that age, sex, exposure to gender-based violence, parental substance use, and parental intellectual disability were associated with specific emotional and behavioral dimensions. The study highlights the need to develop and implement educational and therapeutic programs aimed at strengthening children’s emotional regulation, addressing behavioral difficulties, and considering family-related adversity in intervention planning. Full article

The increasing diversity and complexity of modern mission scenarios have led to growing heterogeneity among nodes in mobile ad hoc networks: node functions, onboard devices, and operational parameters are becoming more diverse, and inter-node links are correspondingly no longer homogeneous. Such networks, termed heterogeneous functional chain networks, orchestrate nodes with distinct functions into multiple functional chains that cooperate to accomplish the overall mission. Accordingly, the evaluation of connectivity reliability in these networks has shifted from a topology-oriented paradigm to a functional structure-oriented one. This paper investigates the impact of dynamic reconfiguration mechanisms on the connectivity reliability of heterogeneous functional chain networks, accounting for node failures, node mobility, and link reliability. A Dynamic Reconfiguration Scheme (DRS) is designed based on the principles of minimum movement and minimum-ordinal decision node, and a suite of evaluation metrics—including normalized connectivity reliability, network quality, and connectivity reliability—is proposed together with a Monte Carlo simulation algorithm. The proposed approach is validated via MATLAB simulations involving 210 heterogeneous nodes organized into 70 functional chains. Results demonstrate that dynamic reconfiguration increases the terminal number of functional chains by 170.83% (from 12.10 ± 0.673 to 32.77 ± 2.241), improves normalized connectivity reliability by 170.73% (from 0.1729 ± 0.010 to 0.4681 ± 0.032), and enhances network quality by 82.96%. The connectivity reliability is further shown to evolve through three distinct temporal stages: an initial stable period where functional chains remain largely intact, a mid-stage fluctuation period characterized by iterative destruction–reconfiguration dynamics, and a late-stage degradation period triggered by candidate node pool depletion. Full article

Precise dimensional conformity of precast concrete members is critical for structural performance and on-site assembly accuracy, yet conventional manual inspection remains labor-intensive and unable to scale with modern production-line throughput. Existing scan-vs-BIM approaches address geometric verification in principle but are constrained by manual registration dependencies, the absence of machine-readable IFC-linked tolerance criteria, and limited validation under real factory yard conditions. This study presents a production-scale automated shape quality control (SQC) framework that closes all three gaps simultaneously. A purpose-designed two-point target device enables fully automated, repeatable registration seed-point extraction. A formal IFC property-set-linked rule engine architecture—comprising entity extraction, deviation computation, rule interpretation, and pass/fail decision stages—replaces ad hoc script-based tolerance checking with an interoperable, auditable compliance pipeline. Factory-scale validation on precast arch segments (n = 10) and wall panels (n = 12) achieved registration RMSE of 1.25–1.95 mm, pass rates exceeding 91%, and a 37.1% reduction in inspection time versus manual methods (95% CI: 34.5–39.6%; p < 0.001; Cohen’s d = 3.89). Repeatability testing yielded ICC = 0.971 and Bland–Altman limits of agreement of [−0.45, +1.07] mm. The framework represents a substantive step toward fully digital, production-integrated quality management for industrialized precast construction. Full article

Background/Objectives: Patients with chronic kidney disease (CKD) have an increased risk of ischemic heart disease (IHD). Some discrepancies exist between cardiological and nephrological guidelines regarding the extent of diagnostic procedures in CKD patients who are candidates for kidney transplantation. The aim of this study was to assess the cardiac status of these patients after cardiological checkup. Methods: The present study included all kidney transplant candidates referred to the Regional Qualification Center between January 2021 and February 2024. We characterized the group of patients in whom IHD was diagnosed during the cardiological checkup. Results: Among 346 patients, IHD was newly identified in 44 (12.7%) subjects. These patients were significantly older [median 62.9 (51.9–65.4) vs. 47.2 (36.8–57.9) years; p < 0.001], had longer dialysis vintage [median 20 (12.5–42) vs. 14 (6–31) months; p < 0.05] and were more frequently diabetic (29.6 vs. 16.9%, p < 0.05) than the rest of the study cohort. Of note, they were also characterized by significantly more frequent manifestation of atherosclerosis lesions visualized using routine imaging methods (i.e., chest X-ray and abdominal aorta and iliac artery visualization). The stepwise logistic regression analysis revealed that age [OR 1.05 (1.02–1.09); p <0.01] and the ad hoc atherosclerotic score [OR 1.88 (1.27–2.77); p < 0.001] independently predicted the diagnosis of IHD during the cardiological qualification of potential kidney transplant candidates. Conclusions: During the cardiological examination, IHD was diagnosed in a substantial number of kidney transplant candidates. The presence of atherosclerotic lesions detected by routine noninvasive vascular system imaging methods may suggest the need for extending IHD diagnostics even in relatively young patients without clinical symptoms. Full article

In the digital era, enterprises face increasing pressure to align strategic objectives with operational execution under volatile and data-intensive conditions. Traditional management control systems often rely on lagging indicators and ad hoc interventions, limiting both performance visibility and sustainability outcomes. This study develops MOD-FCA, a prescriptive, multi-layered closed-loop management control framework that links value-centric outcomes to business-centric drivers through vertically aligned metrics, objective tensors, and tiered corrective routines. Using a longitudinal case study in a manufacturing enterprise, we illustrate how MOD-FCA enhances operational traceability, supports systematic deviation identification and response, and institutionalizes organizational knowledge for continuous improvement. Importantly, MOD-FCA is designed to support sustainable industrial practices by embedding sustainability-related metrics, such as resource efficiency, energy intensity, waste reduction, and process compliance, into the same metric deployment, deviation triggering, and corrective-action logic used for operational control. Qualitative feedback from managerial and operational roles indicates that MOD-FCA strengthens accountability, ensures role-aligned responses, and fosters proactive, data-driven decision-making. These findings provide both theoretical contributions to management control system design and practical guidance for enterprises seeking to achieve both operational excellence and long-term sustainability. Full article

Plantar orthoses play an important role in podiatric care, as they help to redistribute plantar loads, improve foot function, and support the treatment of various conditions, including diabetic foot disease. In this context, additive manufacturing has substantially expanded the capacity to produce customized orthoses through digital geometry acquisition, computational design, and controlled fabrication. From a biomimetic and bionic perspective, 3D-printed plantar orthoses can be understood as engineered interfaces that reproduce, support, or modulate key biomechanical functions of the human foot, including load redistribution, shock attenuation, adaptive stiffness, and gait stabilization. Additive manufacturing enables these biological and biomechanical principles to be translated into patient-specific devices through controlled geometry, graded structures, and material selection. Moreover, from a sustainability perspective, recycled polylactic acid (rPLA) has emerged as a material of potential interest for this type of application, not only because of its compatibility with 3D-printing processes but also because it offers the possibility of reusing polymer waste and reducing the consumption of virgin raw materials in devices whose service life may be limited. This review examines the conditional viability of recycled PLA for 3D-printed plantar orthoses by integrating direct clinical evidence on orthotic function with indirect technical evidence from material-level and process-level studies. The reviewed literature indicates that recycled PLA may offer environmental and economic benefits; however, repeated thermomechanical reprocessing may alter viscosity, dimensional consistency, crystallinity, interlayer adhesion, and mechanical reliability. Recent orthosis-focused studies show that extrusion-based technologies can be applied to customized insoles, lattice or internally reinforced structures, multimaterial systems, and emerging smart concepts; however, most of these developments still rely on virgin or ad hoc-designed materials rather than recycled feedstocks. Overall, the available evidence suggests that recycled PLA should not yet be regarded as a direct substitute for virgin PLA in plantar orthoses. At present, the evidence supporting the use of recycled PLA in plantar orthoses is predominantly indirect and technical rather than directly clinical. Its use appears technically promising, but its viability remains conditional and depends on feedstock traceability, control of the manufacturing process, the suitability of material properties for device function, and validation of the orthosis under clinical conditions. Full article

In Burke County, North Carolina, a Hepatitis A outbreak among unsheltered residents exposed gaps in access to clinic-based care and prompted early, ad hoc “backpack medicine” outreach efforts to deliver care directly in nontraditional settings. While this approach addressed immediate needs, it highlighted the inadequacy of isolated interventions, prompting local partners to pursue more structured, coordinated, and community-driven approaches to homeless health system design. This project report describes how Burke County Public Health, in partnership with the University of North Carolina at Chapel Hill, applied systems thinking, community coalition building, and human-centered design to transition from reactive outreach to a structured, sustainable mobile health delivery model for people experiencing homelessness. Guided by Community Coalition Action Theory (CCAT), partners used human-centered design methods to engage over 40 community stakeholders and 10 individuals with lived experience of homelessness or housing instability. Through empathy mapping, iterative prototyping, and thematic analysis, the team identified priority service gaps, defined operational requirements, and developed prototype service models, while building cross-agency readiness for implementation. Full article

Intelligent autonomous driving systems must not only predict the appropriate driving manoeuvre but also provide human-interpretable evidence that justifies the decision. However, existing methods typically address these objectives separately, leading to three practical limitations: multi-stage perception-to-language pipelines can propagate upstream perception errors into downstream explanations; post hoc saliency methods often produce pixel-level highlights that are difficult to interpret semantically; and decoupled decision and explanation modules cannot guarantee that the explanation reflects the same scene evidence used for behaviour prediction. In this paper, we propose a unified framework that jointly performs vehicle behaviour prediction and human-centric interpretation from a shared visual backbone. Specifically, a hierarchical Swin Transformer encodes the driving scene into a sequence of spatial tokens, which are processed by two complementary branches. The first branch, termed the Object Selection Module (OSM), learns a compact scene-level semantic representation through query-guided cross-attention, while the second branch extracts a small set of class-agnostic object-centric tokens without requiring bounding-box or segmentation supervision. These two representations are subsequently integrated by a Semantic–Object Fusion (SOF) module based on scaled dot-product attention, residual connections, and a feed-forward network. The behaviour prediction head operates on the fused representation, whereas the interpretation head leverages the semantic representation through a skip connection to preserve decision-relevant context. For surround-view perception, learnable per-camera embeddings are introduced to maintain viewpoint identity with negligible additional parameter cost. Furthermore, a compact language model fine-tuned via Low-Rank Adaptation (LoRA) generates fluent, label-conditioned natural-language justifications. Extensive experiments on two public benchmarks, BDD-OIA and nu-AD, demonstrate that the proposed framework consistently delivers superior performance and provides effective, human-readable interpretations of driving decisions. Full article

As Flying Ad Hoc Networks (FANETs) are highly vulnerable to security threats such as identity spoofing, session replay and man-in-the-middle attacks in open-air channels, it is crucial to design an authentication key agreement (AKA) scheme to ensure the security of unmanned aerial vehicle (UAV) swarm networking within FANETs. However, existing AKA schemes for FANETs often struggle to balance authentication efficiency and high dynamism within UAV swarms whilst meeting necessary security requirements. To address the issue, this paper proposes CUBAT-AKA (Collaborative UAV Batch Authentication and Tree-based Key Agreement), a lightweight UAV swarm authentication and key agreement scheme based on batch verification and a binary tree structure. The scheme constructs a secure and lightweight three-party authentication mechanism based on aggregated verification and the Chinese Remainder Theorem (CRT). By offloading computational tasks to the authentication center and aggregating authentication responses in batches, it significantly improves the efficiency of UAV access authentication in large-scale FANET scenarios. To address the dynamic nature of UAVs frequently joining and leaving clusters in FANETs, an improved binary tree-based key agreement method has been designed, reducing key update overhead to a logarithmic level and enabling lightweight session key distribution and updates for UAV clusters. Security analysis demonstrates that, under the random oracle model, CUBAT-AKA is resistant to eavesdropping, replay, man-in-the-middle, impersonation and collusion attacks, whilst ensuring forward and backward security during member changes. Performance analysis indicates that this scheme offers significant advantages over comparable solutions in terms of both UAV cluster access authentication efficiency and dynamic key agreement overhead. Full article

Vehicle ad hoc networks (VANETs) can help prevent traffic accidents through wireless communication; however, most studies are based on simulations or static evaluations. This research paper presents the design, implementation, and experimental evaluation of a prototype early-warning system for vehicle proximity based on VANETs using ESP-NOW. The prototype utilizes five ESP32-CAM nodes equipped with MaxSonar sensors installed in vehicles and an RSU unit with a Raspberry Pi for vehicle-to-infrastructure (V2I) communication. Field tests were conducted in Quito, Ecuador, at speeds ranging from 10 to 70 km/h, measuring latency, packet loss, and received signal strength (RSSI). The results show average latencies of 9.9 ms at 10 km/h and 114.5 ms at 70 km/h, with packet loss rates of 2% and 60%, respectively. Statistical analysis reveals 95% confidence intervals for latency ranging from ±0.98 ms to ±6.90 ms, while obstacles introduce marginal attenuation (p = 0.051) with significant dispersion (σ = 5.85 dB). The Doppler shift is negligible (155.6 Hz), but the channel coherence time (2.7 ms) explains the observed degradation. Models were obtained that relate speed to latency (R² = 0.994) and packet loss (R² = 0.991). The prototype is viable for early collision warning at urban speeds (up to 60 km/h), outperforming human reaction time (1.5 s). Full article

The increasing adoption of artificial intelligence (AI) in smart learning environments has heightened the need for systematic, reliable testing of AI-driven educational applications. Existing studies primarily rely on benchmark accuracy, manual testing, or user-based assessment, offering limited insight into robustness, coverage, and failure behavior. These limitations are driven by the lack of standardized intelligence quality criteria, inadequate test automation support, complex diversity in Q&A tasks, and the difficulty of automatically validating test results in smart learning applications. This paper investigates model-based AI testing for Q&A-based smart learning applications, using ChatGPT (GPT-5) as a case study to evaluate its intelligence quality in college algebra question answering tasks that support student learning. A three-dimensional (3D) AI testing framework structures testing along input, context, and output dimensions to enable model-driven test generation, controlled contextual variation, and consistent validation. College algebra problems selected from a standard undergraduate textbook are used to construct representative test cases. Controlled image-based data augmentation and structured similarity-based validation mechanisms are employed to support automated test execution and result analysis. Empirical results demonstrate that the proposed approach improves intelligence quality coverage and provides more diagnostic insight than ad hoc evaluation methods. Full article

The convergence of Software-Defined Networking (SDN) and Blockchain (BC) creates a symbiotic relationship in which SDN’s programmable global visibility complements BC’s decentralized, immutable trust model to address critical cybersecurity vulnerabilities and cyber attacks. Addressing the fragmentation in the current literature, this study rigorously investigates BC and SDN (B-SDN) integration with the primary objectives of: (1) differentiating impacts across varied sectors, including the Internet of Things (IoT), Smart Grids, and Vehicular Ad Hoc Networks (VANETs) and more; (2) analyzing critical performance metrics such as energy efficiency and scalability; (3) classifying mitigation, detection, and prevention schemes for specific threats; (4) examining novel Artificial Intelligence (AI) methods; and (5) identifying open challenges and future research directions. Methodologically, this study conducts a survey of state-of-the-art B-SDN studies to investigate six key areas: Industry-specific applications, security mechanisms, defense strategies, defenses against specific attacks, AI integration, and implementation performance. The findings demonstrate that B-SDN integration shows strong potential in simulated and prototype environments to mitigate specific high-impact threats, such as Distributed Denial of Service (DDoS), Man-in-the-Middle (MiTM), and spoofing, across various domains, including IoT, 5G/6G, VANETS, and Smart Grid. Despite the benefits and advantages promised by B-SDN, several limitations continue to exist, including the latency–security trade-off inherent to consensus protocols and scalability constraints in large-scale deployments. Finally, open research challenges persist in AI-driven automation, particularly in Federated Learning (FL) and in the development of standardized interoperability protocols required to enable the transition from conceptual models to operational systems. Full article

This paper introduces novel recurrence relations that enable the systematic calculation of derivatives for five fundamental Bessel function ratios: $J_{p\pm 1}\left(z\right)/J_p\left(z\right)$, $I_{p\pm 1}\left(z\right)/I_p\left(z\right)$, and $J_p^{\prime }\left(z\right)/J_p\left(z\right)$. The recursive structure reduces the calculation of this derivatives to algebraic operations, allowing for the explicit derivation of formulas up to the sixth order. These results are applied to generate new infinite series based exclusively on Bessel function zeros, extending the classical Rayleigh function framework. The methodology’s practical utility is demonstrated through application to an inverse Laplace transform problem arising in fluid mechanics, namely water hammer analysis. Additionally, we systematically extend and generalize Pedersen’s series, providing closed-form expressions for previously missing cases. The recursive framework established herein transforms what were once cumbersome ad hoc calculations into tractable algebraic procedures, opening new avenues for both theoretical exploration and engineering applications. Full article