Search Results (2,284)

Background and Aims: This study explored the feasibility of performing intestinal reconstruction after enterostomy in infants using ultrasound-guided epidural anesthesia with sedation, aiming to avoid invasive airway manipulation and the use of opioids. Methods: We included twenty infants scheduled for intestinal reconstruction in this prospective case series. Success was defined by the absence of additional general anesthesia and invasive airway management. The secondary endpoints were the need for additional intraoperative anesthetic and analgesic drugs and postoperative analgesics in the recovery room. The study was approved by the Ethics Commission at the Medical University of Vienna (ref. 1133/2017, approval date 24 August 2017) and registered in the German Clinical Trial Register (DRKS ID: DRKS00012683, approval date 15 July 2019). Results: Nineteen out of twenty procedures were successfully performed with epidural anesthesia under spontaneous breathing and without airway manipulation; one child required endotracheal intubation due to an unexpected, extensive surgical procedure. No child needed systemic analgesics in the recovery room. Conclusions: Epidural anesthesia with sedation can effectively minimize airway manipulation and reduce general anesthesia requirements for intestinal reconstruction in infants. Full article

Background: Human papillomavirus (HPV) is the most prevalent sexually transmitted infection with significant health implications, especially for women living with human immunodeficiency virus (HIV). The variability in reported prevalence and genotype distribution of HPV among HIV-positive women across different regions in Africa necessitates a comprehensive and systemic examination. Methods: A systematic search was conducted across several databases. A random effect model was used to evaluate study heterogeneity through Q statistics and I² measures. Publication bias was assessed using funnel plots and Egger’s tests. Risk factors for HPV among HIV-positive women were summarized qualitatively. This review was registered with PROSPERO: CRD42024525123. Result: Twenty-three studies involving 9954 HIV-positive women were combined to estimate HPV prevalence. The overall prevalence of all HPV types was 49.4% (95% CI: 42.43, 56.38), with evidence of heterogeneity (Q = 520.92, df = 16, I² = 96.93%, p < 0.0001). The prevalence of high-risk HPV was 45.26% (95% CI: 31.02, 59.91), showing heterogeneity across studies (Q = 439.18, df = 10, p < 0.0001, I² = 97.72%). Low-risk HPV had a prevalence of 24.98% (95% CI: 12.27, 40.41), with variation among studies (Q = 134.39, df = 6, p < 0.0001, I² = 95.54%). The most frequent genotypes were 16, 18, 52, 33, and 35. A higher cluster of differentiation 4 (CD4) count is associated with a lower prevalence of HPV. Conclusions: The pooled HPV prevalence among HIV-positive women in Africa is lower compared to previous studies, but the slow decline poses challenges to meet the WHO’s goal of eliminating HPV-related cervical cancer by 2030. Therefore, enhanced prevention efforts, including HPV self-sampling, improved vaccination coverage, and early treatment interventions, are essential to meet the goal of eliminating HPV-related cervical cancer. Full article

In resource-constrained edge environments—such as mobile devices, IoT systems, and electric vehicles—energy-efficient Convolution Neural Network (CNN) accelerators on mobile Field Programmable Gate Arrays (FPGAs) are gaining significant attention for real-time object detection tasks. This paper presents a low-power implementation of the Tiny YOLOv4 object detection model on the Xilinx ZCU104 FPGA platform by using Register Transfer Level (RTL) optimization techniques. We proposed three RTL techniques in the paper: (i) Local Explicit Clock Enable (LECE), (ii) operand isolation, and (iii) Enhanced Clock Gating (ECG). A novel low-power design of Multiply-Accumulate (MAC) operations, which is one of the main components in the AI algorithm, was proposed to eliminate redundant signal switching activities. The Tiny YOLOv4 model, trained on the COCO dataset, was quantized and compiled using the Tensil tool-chain for fixed-point inference deployment. Post-implementation evaluation using Vivado 2022.2 demonstrates around 29.4% reduction in total on-chip power. Our design supports real-time detection throughput while maintaining high accuracy, making it ideal for deployment in battery-constrained environments such as drones, surveillance systems, and autonomous vehicles. These results highlight the effectiveness of RTL-level power optimization for scalable and sustainable edge AI deployment. Full article

Background/Objectives: Self-adhesive flowable resins (SAFR) entered the market, eliminating the adhesive system application due to their self-adhesive technology. Guided by the PICO framework (Population, Intervention, Comparison, Outcome), the aim was to conduct a systematic review of clinical studies to compare the clinical performance of Self Adhesive Flowable Resin (SAFRs) with conventional flowable resins used for direct restorations. Methods: The protocol of this systematic review was registered in the International Prospective Register of Systematic Reviews (CRD42023394297) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. Five databases (PubMed, Embase, Web of Science, Scopus, and Cochrane Library) were searched from inception to July 2025. Nine randomized clinical trials were included, totaling 493 restorations in 232 patients. Clinical performance was assessed using USPHS or FDI criteria, with follow-up periods ranging from 6 months to 5 years. Data were pooled using a random-effects meta-analysis to calculate risk differences (RD) and 95% confidence intervals (CI) for marginal adaptation, retention, marginal staining, post-operative sensitivity, color stability, surface roughness, secondary caries, and anatomical form. Results: Meta-analysis showed no significant differences between SAFRs and CFRCs for in terms of: marginal adaptation (RD = 0.01; 95% CI: −0.02 to 0.04; p = 0.53; I² = 0%), retention (RD = 0.00; 95% CI: −0.02 to 0.03; p = 0.81; I² = 0%), marginal staining (RD = 0.01; 95% CI: −0.01 to 0.02; p = 0.51; I² = 0%), and post-operative sensitivity (RD = −0.01; 95% CI: −0.03 to 0.02; p = 0.62; I² = 0%). The certainty of the evidence for all outcomes was rated as moderate to high according to the GRADE assessment. Conclusions: SAFR restorations demonstrated comparable clinical performance to conventional resins; however, heterogeneity in follow-up duration and the scarcity of long-term data (>5 years) warrant caution. Full article

In loop-powered 4–20 mA transmitter systems, sensors like temperature, pressure, flow, and gas sensors are chosen based on specific application requirements. These systems are widely adopted in high-precision measurement scenarios, including industrial automation, process control, and environmental monitoring. The transmitter requires a high-performance analog front end (AFE) for precise amplification and signal conditioning. This paper presents a low-noise instrumentation amplifier (IA) for high-precision transmitter front ends, featuring a Successive Approximation Register (SAR)-assisted offset calibration architecture. The proposed structure integrates a chopper current-feedback instrumentation amplifier (CFIA) with an automatic offset calibration loop (AOCL), significantly suppressing internal offset errors and enabling high-accuracy signal acquisition under stringent power and environmental temperature constraints. The designed amplifier provides four selectable gain settings, covering a range from ×32 to ×256. Fabricated in a 0.18 μm CMOS process, the CFIA operates at a 1.8 V supply voltage, consumes a static current of 182 μA, and achieves an input-referred noise as low as 20.28 nV/√Hz at 1 kHz, with a common-mode rejection ratio (CMRR) up to 122 dB and a power-supply rejection ratio (PSRR) up to 117 dB. Experimental results demonstrate that the proposed amplifier exhibits excellent performance in terms of input-referred noise, offset voltage, PSRR, and CMRR, making it well-suited for front-end detection in field instruments that require direct interfacing with measured media. Full article

Multigrade classrooms represent a widely extended educational modality in rural contexts and territories with low demographic density. This organizational model, in which a single teacher serves students from different levels in the same space, poses particular challenges but also significant pedagogical opportunities. In this systemic literature review, a total of 40 international studies were analyzed according to the PRISMA guidelines, published between 2019 and 2024 in databases such as Scopus and ERIC. The objective of this analysis is to identify the main organizational and methodological approaches, as well as the strengths and weaknesses, associated with teaching in multigrade contexts. This systematic review has been prospectively registered in the Open Science Framework (OSF) under registration number: 64rsu. A qualitative thematic analysis was employed to organize the results into five categories: organizational models, pedagogical practices, teacher training, impact on learning, and school-community links. The findings underscore the efficacy of this model in promoting educational inclusion, cooperative learning, and curricular contextualization. Nevertheless, they also underscore the necessity for specific teacher training and support policies. This review offers a comparative and critical perspective that has the potential to inform the development of more effective pedagogical and training strategies in a range of educational settings. Full article

Introduction: Healthcare service utilisation for type 2 diabetes (T2D) is suboptimal among people from culturally and linguistically diverse (CALD) backgrounds. Synthesised evidence on drivers influencing their healthcare access and utilisation across the continuum of care (CoC) is scarce. This review synthesised drivers of accessing and utilising healthcare services across the CoC for T2D from the perspectives of people from CALD backgrounds and their healthcare service providers (HSPs). Methods: Five databases (Scopus, PubMed, Web of Science, CINAHL, and PsycINFO) were searched from inception to November 2023. This review was prospectively registered with PROSPERO (ID: CRD42023491560). The McGill Mixed Methods Appraisal Tool (MMAT) was used to assess the quality of articles included in this systematic review. Studies were included if they were primary research involving people from CALD backgrounds and/or their HSPs, and reported data related to access to and utilisation of services across the CoC. The CoC framework was used to conduct a guided thematic analysis for qualitative findings and narrative synthesis was used to summarise quantitative findings. Results: Thirty-five studies were included: 31 qualitative, 3 quantitative, and 1 mixed-method. Psychosocial (e.g., fear of treatment) and sociocultural barriers (e.g., stigma) were reportedly encountered at diagnosis and initiation of treatment. Language and cultural barriers were expressed by most people with T2D and their HSPs, especially at the monitoring and adherence stages of the CoC. Trusted relationships with HSPs and the cultural competency of the HSPs were facilitators of continued monitoring and adherence and long-term care and management. No barriers or facilitators were identified for decision-making to enter the healthcare systems, screening, and first point of contact aspects of the CoC from the perspectives of either patients or HSPs. Conclusions: Although included articles were heavily skewed towards qualitative studies, the synthesised evidence on factors influencing access to and utilisation of healthcare services for T2D can inform policymaking by highlighting pathways to improved use of healthcare services among these groups. Full article

This review synthesizes research on smart insole prototypes and their designs, focusing on those incorporating artificial intelligence (AI) and a wireless communication/transmission system. The main objective of this work is to summarize existing studies, identify key trends, evaluate the performance of these innovative biomechanical tools, and recognize the factors that could lead to optimization. This comprehensive analysis includes studies from PubMed, Scopus, and Web of Science databases and other investigations on the critical themes to consider. It follows strict inclusion and exclusion criteria, ensuring the quality and accuracy of the overview. The findings emphasize significant progress in smart insoles, particularly in AI-enhanced prototypes, while addressing existing challenges and problems. This review helps guide potential future research and define practical application directions. The growing importance of biomechanics, especially on smart insoles, underscores the considerable potential of these innovations to monitor and improve human movement in both clinical and non-clinical settings, promising a future of more effective and personalized health and performance interventions. This protocol was registered with the International Platform of Registered Systematic Review and Meta-Analysis Protocols (INPLASY) on 6 February 2025 and was last updated on 6 February 2025. Full article

Background: Motor imagery (MI) is defined as the cognitive ability to simulate motor movements while suppressing muscular activity. The electroencephalographic (EEG) signals associated with lower limb MI have become essential in brain–computer interface (BCI) research aimed at assisting individuals with motor disabilities. Objective: This systematic review aims to evaluate methodologies for acquiring and processing EEG signals within brain–computer interface (BCI) applications to accurately identify lower limb MI. Methods: A systematic search in Scopus and IEEE Xplore identified 287 records on EEG-based lower-limb MI using artificial intelligence. Following PRISMA guidelines (non-registered), 35 studies met the inclusion criteria after screening and full-text review. Results: Among the selected studies, 85% applied machine or deep learning classifiers such as SVM, CNN, and LSTM, while 65% incorporated multimodal fusion strategies, and 50% implemented decomposition algorithms. These methods improved classification accuracy, signal interpretability, and real-time application potential. Nonetheless, methodological variability and a lack of standardization persist across studies, posing barriers to clinical implementation. Conclusions: AI-based EEG analysis effectively decodes lower-limb motor imagery. Future efforts should focus on harmonizing methods, standardizing datasets, and developing portable systems to improve neurorehabilitation outcomes. This review provides a foundation for advancing MI-based BCIs. Full article

Background: Dehydration is a prevalent and potentially serious condition, particularly affecting vulnerable populations such as children and older adults. Prompt recognition and intervention are critical for preventing associated complications. Methods: A systematic review and meta-analysis were conducted, registered in PROSPERO (CRD42024594780), to identify key clinical and demographic risk factors associated with dehydration. A comprehensive search of PubMed, Scopus, and the Cochrane Library was performed for studies published between 2000 and 2024. The risk of bias in included studies was assessed using the Newcastle–Ottawa Scale and the Cochrane Risk-of-Bias (RoB) tool. Ten studies met the inclusion criteria for quantitative synthesis. Based on pooled diagnostic metrics, a preliminary scoring tool was developed for dehydration risk stratification. Results: The pooled sensitivity and specificity of common clinical signs, such as thirst, dry mouth, and dark urine, were 85% (95% CI: 80–90%) and 70% (95% CI: 65–75%), respectively. The positive predictive value (PPV) was 75%, and the negative predictive value (NPV) was 80%. Pediatric subgroup analysis yielded the most robust data, while data for adult and elderly populations were limited. A conceptual risk scoring system was proposed based on relative diagnostic utility, though it has not yet been externally validated. Conclusions: Simple clinical signs demonstrate reasonable diagnostic accuracy for identifying individuals at risk of dehydration. The proposed scoring system offers a promising, evidence-informed framework for early risk assessment but requires further validation in prospective studies before integration into clinical practice. Full article

Background/Objectives: Introducing new transformative surgical technology involves navigating a complex process from design to implementation, often hindered by various barriers that delay the transition into clinical practice. This review critically examines the barriers, proposes a unified guide for medical device implementation in the Australian healthcare system utilising the validated Medtech Innovation Guide, and compares regulatory frameworks in Australia, the United Kingdom, and the United States of America. Methods: We conducted a literature review using MEDLINE and EMBASE with MeSH terms or emtree terms and keywords “new OR novel” AND “surgical device OR medical device OR health technology OR surgical technology OR surgical instrument OR transformative technology OR technological innovation OR technological change” AND “implementation OR adoption OR innovation adoption” AND “surgery OR surgical” AND “Australia”. We also assessed governmental websites (gov.au) and documents as well as the Royal Australasian College of Surgeons (RACS) website, policies, and position statements. Furthermore, Australian medical technology start-up companies were asked for any published roadmaps. Results: Four key stakeholder groups were identified: medical professionals, government, hospitals, and patients/consumers. Barriers include surgeon scepticism, regulatory hurdles (e.g., Australian Register of Therapeutic Goods), hospital clearance processes, and meeting patient expectations. To address these challenges, we propose a five-phase system: surgical device development (phase one), compliance with regulatory processes (phase two), research and experimentation (phase three), finalisation for product launch (phase four), and product launch and assessment (phase five). Conclusions: By following our five-phase guide, innovators may better navigate the complexities of integrating transformative surgical technologies into Australian healthcare. Although there are limitations, this approach is based on the validated Medtech Innovation Guide and may help both experienced and inexperienced practitioners better implement innovative technology; however, real-world validation is required. Full article

This study addresses gas drainage challenges in the Pingdingshan NO.10 mine JI_15-16 coal seam through coupled COMSOL-FLAC^3D numerical simulations. The research evaluates the effectiveness of a cross-measure borehole drainage system. It analyzes the failure mechanisms of the surrounding rock in both the machine roadway and floor roadway of the 24130 working face under the influence of boreholes. The results demonstrate that extended drainage duration progressively reduces both gas content and pressure within the borehole-affected zone of the coal seam while enhancing the effective permeability of the JI_15-16 coal stratum. The operational system extracted 1,527,357 m³ of methane, achieving a pre-drainage efficiency of 59.18% through cross-measure boreholes. The measured gas content aligns with simulated predictions, though field-recorded gas pressure registered slightly higher than modeled values. This validated drainage design complies with the Pingmei Group’s regulations for coal and gas outburst prevention. Critically, cross-measure boreholes alter stress distribution around both coal and floor roadways, promoting plastic zone expansion. Consequently, during the development of the 24130 working face’s machine roadway, intensified ground pressure monitoring is essential near borehole locations in the roof, floor, and rib strata. Supplementary support reinforcement should be implemented when required to prevent rib spalling and roof collapse incidents. Full article

This paper presents a novel methodology for minimizing power losses in brushless DC (BLDC) motors through the implementation of adaptive flux control techniques. Conventional motor control strategies, such as direct torque control (DTC), typically employ fixed flux values, which often result in suboptimal performance, particularly under dynamic load and speed variations. To mitigate this inherent limitation, two adaptive flux control methods are introduced: incremental conductance (IncCond) and fuzzy logic. These proposed strategies facilitate real-time dynamic adjustment of the stator flux, thereby optimizing motor performance and significantly enhancing system efficiency. Experimental validation confirms the efficacy of these adaptive techniques, demonstrating substantial improvements in power loss reduction and overall efficiency when compared to traditional fixed flux control strategies. Notably, the fuzzy logic control strategy achieves the highest efficiency, registering a system efficiency of $66.59$%, which surpasses both the incremental conductance method and conventional fixed flux control. These findings underscore the considerable potential of adaptive flux control in applications where energy efficiency is paramount, including electric vehicles and renewable energy-driven systems. Full article

Background/Objectives: Beyond the core characteristics of the condition, autistic individuals often significantly struggle with postural balance. This pilot study aimed to investigate the effects of an immersive virtual reality-based training administered with Gait Real-time Analysis Interactive Lab (GRAIL) on postural balance of autistic children. Methods: A total of 20 autistic participants aged 6 to 13 were enrolled in a 5-week randomized, parallel-group, open-label, controlled trial, and received either balance training with the GRAIL system or no training. The trial was registered at ClinicalTrials.gov (identifier: NCT04276571). The primary outcome measures were the change in center of pressure (CoP) metrics during GRAIL balance assessments and the change in motor skills as assessed with Movement Assessment Battery for Children-2. Secondary outcome measures included parent-report Developmental Coordination Disorder Questionnaire, center of mass metrics, and gait parameters evaluated with GRAIL. ANCOVA tests were performed for all outcomes, with time (T0 and T1) as within-subjects factor, the group (training and control groups) as between-subjects factor, and considering age as covariate. Results: Slight but significant time by group interactions were found in some CoP metrics (i.e., sway path length, velocity in the antero-posterior direction, and the jerk). Conclusions: These findings preliminarily suggest that a virtual reality-based training may induce slight modifications in postural balance strategies, which can be enhanced with longer or more intensive training. Full article

This work aims to develop approaches to processing and interpreting spectral entropy outcomes in the context of seismic data, as well as to establish a methodological foundation for subsequent integration into practical monitoring solutions. The objective of this study is to evaluate the effectiveness of the Shannon spectral entropy method in detecting and assessing short-term seismic events through a seismogram analysis. This method has demonstrated sensitivity to variations in the spectral characteristics of the registered signals. A threshold value for the increase in spectral entropy information has been pinpointed for reliable P-wave detection. The results could be applied in real-time automated seismic monitoring systems. In addition to the conventional spectral analysis techniques, the proposed methodology may serve as the input to the neural network models used in seismological applications. Full article