Search Results (18,339)

This research explores the phenomenon of plate-end (PE) debonding in reinforced concrete (RC) beams strengthened with fiber-reinforced polymer (FRP) composites. This type of failure represents a key mechanism that undermines the structural performance and efficiency of FRP reinforcement systems. Despite the widespread use of FRP in structural repair due to its high strength and corrosion resistance, PE debonding—often triggered by shear or inclined cracks—remains a major challenge. Traditional computational models for predicting PE debonding suffer from low accuracy due to the nonlinear relationship between influencing parameters. To address this, the research employs machine learning techniques and SHapley Additive exPlanations (SHAP), to develop more accurate and explainable predictive models. A comprehensive database is constructed using key parameters affecting PE debonding. Machine learning algorithms are trained and evaluated, and their performance is compared with existing normative models. The study also includes parameter importance and sensitivity analyses to enhance model interpretability and guide future design practices in FRP-based structural reinforcement. Full article

Fertility-sparing treatments (FSTs) have gained importance for young female cancer patients, especially those with early-stage cervical, ovarian, and endometrial cancers. However, concerns about the long-term safety of these procedures, particularly in more advanced cancers, persist. A literature review was conducted using databases such as PubMed, Scopus, and Web of Science. The search terms included “fertility preservation” and “gynaecological cancer”. Articles published between 2014 and 2024 were considered, with 39 articles cited in the paper. The inclusion criteria were female patients undergoing FST. Studies were excluded if prior treatments impacted fertility or if oncological outcomes were inadequately reported. Radical trachelectomy, laparoscopic fertility-sparing surgeries, and cryopreservation techniques, such as ovarian tissue vitrification and oocyte cryopreservation, offer viable options for preserving fertility in early-stage gynecological cancer patients. Radical trachelectomy and cryopreservation showed positive reproductive outcomes, with pregnancy rates of 30–50% in early-stage cases. GnRH analogs during chemotherapy also demonstrated benefits in maintaining fertility. Despite these advances, recurrence in more advanced stages (FIGO IA2 and beyond) remains a concern. Minimally invasive surgeries like robotic-assisted procedures demonstrated comparable fertility outcomes to traditional methods but with fewer complications. FST is a promising option for women with early-stage cancer, offering favorable reproductive and survival outcomes. However, further research is needed to confirm long-term oncological safety in advanced stages. Multidisciplinary approaches and individualized treatment planning are essential for optimizing outcomes. Full article

Background: Colonoscopy remains the gold standard for colorectal cancer screening. Deep learning systems with real-time computer-aided polyp detection (CADe) demonstrate high accuracy in controlled research settings and preliminary randomized controlled trials (RCTs) report favorable outcomes in clinical settings. This study aims to evaluate the efficacy of AI-assisted colonoscopy compared to standard colonoscopy focusing on Polyp Detection Rate (PDR) and Adenoma Detection Rate (ADR), and to explore their implications for clinical practice. Methods: A systematic search was conducted using multiple indexing databases for RCTs comparing AI-assisted to standard colonoscopy. Random-effect models were utilized to calculate pooled odds ratios (ORs) with 95% confidence intervals. The risk of bias was assessed using the Cochrane Risk of Bias Tool, and heterogeneity was quantified using I statistics. Results: From 22,762 studies, 12 RCTs (n = 11,267) met the inclusion criteria. AI-assisted colonoscopy significantly improved PDR (OR 1.31, 95% CI 1.08–1.59, p = 0.005), despite heterogeneity among studies (I² = 79%). While ADR showed improvement with AI-assisted colonoscopy (OR 1.24, 95% CI, 0.98–1.58, p = 0.08), the result was not statistically significant and had high heterogeneity (I² = 81%). Conclusions: AI-assisted colonoscopy significantly enhances PDR, highlighting its potential role in colorectal cancer screening programs. However, while an improvement in the ADR was observed, the results were not statistically significant and showed considerable variability. These findings highlight the promise of AI in improving diagnostic accuracy but also point to the need for further research to better understand its impact on meaningful clinical outcomes. Full article

To address the fragmentation and weak correlation of knowledge in the design method domain, this paper proposes a framework for constructing a knowledge graph driven by multi-source heterogeneous data. The process involves collecting multi-source heterogeneous data and subsequently utilizing text mining and natural language processing techniques to extract design themes and method elements. A “theme–stage–attribute” three-dimensional mapping model is established to achieve semantic coupling of knowledge. The BERT-BiLSTM-CRF (Bidirectional Encoder Representations from Transformers-Bidirectional Long Short-Term Memory-Conditional Random Field) model is employed for entity recognition and relation extraction, while the Sentence-BERT (Sentence Bidirectional Encoder Representations from Transformers) model is used to perform multi-source knowledge fusion. The Neo4j graph database facilitates knowledge storage, visualization, and querying, forming the basis for developing a prototype of a design method recommendation system. The framework’s effectiveness was validated through experiments on extraction performance and knowledge graph quality. The results demonstrate that the framework achieves an F1 score of 91.2% for knowledge extraction, and an 8.44% improvement over the baseline. The resulting graph’s node and relation coverage reached 94.1% and 91.2%, respectively. In complex semantic query tasks, the framework shows a significant advantage over traditional classification systems, achieving a maximum F1 score of 0.97. It can effectively integrate dispersed knowledge in the field of design methods and support method matching throughout the entire design process. This research is of significant value for advancing knowledge management and application in innovative product design. Full article

Introduction: Atrial fibrillation (AF) is common in patients with Brugada syndrome (BrS). The impact and significance of AF in this patient population needs to be further clarified. Method: We performed a systematic review and meta-analysis of studies comparing the risks of developing major arrhythmic events (MAEs) in patients with BrS with and without AF. Databases including MEDLINE, Embase, and Cochrane CENTRAL were searched from inception to July 2024, using appropriate search and MeSH terms. Data were sought on the comparison of patients with BrS with and without AF. The protocol was specified prior to the searches being performed, and standard meta-analytic techniques were used. Results: Thirteen observational studies were included (a total of 5413 patients). A significant increase in MAEs was observed in patients with both BrS and AF (20.6% vs. 7.8%; OR 2.81, 95% CI 1.82–4.34; p < 0.0001; I² = 46%). Significantly higher rates of syncope (33.3% vs. 23.4%; OR 1.97, 95% CI 1.04–3.76; p = 0.04, I² = 59%) and a significant increase in all-cause mortality (11.3% vs. 3.7%; OR 4.21, 95% CI 1.69–10.45; p = 0.002, I² = 0%) and sodium channel mutations (43.1% vs. 29.9%; OR 1.87, 95% CI 1.07–3.29; p = 0.028, I² = 0%) were observed for patients with BrS and AF. Conclusions: Patients with both BrS and AF seem to have a more severe disease phenotype. More research into the added role of AF in risk stratification of asymptomatic BrS patients is needed, but the prognostic implications of AF may need to be considered when developing future personalised medicine approaches in the BrS population. Full article

The integration of multimedia technologies is transforming teaching and learning in higher education, offering innovative ways to improve student engagement and learning outcomes. Although numerous studies investigate the impact of multimedia, there is still a clear need for a synthesis that brings together the latest evidence from a variety of disciplines and contexts. To address this need, this systematic review aims to summarize the empirical evidence and provide a clearer understanding of how multimedia is applied in higher education, to outline how educators can effectively design and the implications for curriculum design. This article focuses on three key research questions: (1) How does the integration of multimedia in higher education classrooms influence student engagement and learning outcomes? (2) How does the use of multimedia affect the development of specific skills? (3) What are the challenges and opportunities to integrate multimedia technologies into higher education? Relevant studies were systematically retrieved and screened from major academic databases, including ScienceDirect, Web of Science, IEEE Xplore, Wiley Online Library, Springer, Taylor & Francis, and Google Scholar. In total, 48 studies were selected from these sources for detailed analysis. The findings showed that multimedia tools enhance student engagement, motivation, and performance when integrated with clear pedagogical strategies. In addition, multimedia helps to develop skills such as creativity, digital literacy, and independent learning. However, challenges such as technical limitations, uneven infrastructure, and the need for ongoing teacher training remain significant difficulties in fully exploiting the benefits in higher education. Addressing these challenges requires coordinated institutional support, investment in professional development, and careful alignment of multimedia tools with pedagogical goals. Full article

Research on Mesoscale Convective Systems (MCSs) in Ecuador has focused on regional studies. However, it lacks a thorough and general examination of their relationship with the nation’s diverse orography and large-scale phenomena. This study conducts a climatological analysis of MCS occurrence throughout Ecuador’s natural regions. We perform this study using Sen’s Slope and the Mann–Kendall test. Teleconnections from the Pacific and Atlantic Oceans are studied through wavelet decomposition between time series and Pacific and Atlantic oceanic indices. The main factors that control MCS formation depend on the region. The Intertropical Convergence Zone (ITCZ) at the large scale affects the entire territory. In western Ecuador, MCS formation is mostly related to the El Niño current and the Chocó Low-Level Jet (CLLJ). The Orinoco Low-Level Jet (OLLJ) and evapotranspiration and nocturnal convection display the largest roles in the east. A progressive intensification of activity from Highlands-North in SON is detected (0.143 MCSs per year). MCSs contribute 26% of total precipitation on average, with regional variations from Coast-South (16.41%) to Amazon-North (44.13%). The research confirms existing knowledge about El Niño’s strong relationship (ρ = 0.7) with MCS occurrence in coastal areas while uncovering new complex patterns. The Trans-Nino Index (TNI) functions as a critical two-sided modulator that conventional analysis methods fail to detect. It produces null correlations over conventional time series of MCS occurrence yet emerges as a primary driver of low-frequency variability in the proposed six natural zones of Ecuador. Wavelet decomposition reveals contrasting TNI responses: Amazon-North shows positive correlation (0.73) while Amazon-South exhibits negative correlation (−0.70) at low frequencies. This affects Walker circulations dynamics over the Pacific Ocean. This research establishes fundamental knowledge about MCSs in Ecuador. It builds on a database with strong methodology as a backbone. The research provides essential information about the factors leading to convection in the country. This will help improve seasonal forecast accuracy and risk management effectiveness. Full article

Background: Ischemia with no obstructive coronary artery disease (INOCA) is characterized by myocardial ischemia in the absence of significant coronary artery stenosis. Despite the lack of major obstructive lesions, patients often present with chest pain, making diagnosis and management a significant challenge. Materials and Methods: A comprehensive search strategy of electronic databases (2000 to 2024) was used to identify studies assessing pathophysiology, diagnosis, surgical treatments, interventions, and outcomes in INOCA. Clinical trials, observational studies, case-control studies, and cohort studies were included. Results: Emerging surgical treatments may have a role in certain subgroups of INOCA patients, particularly those with severe and persistent symptoms or underlying pathophysiological factors that do not respond adequately to pharmacological therapies. Transmyocardial revascularization (TMR) and sympathetic denervation procedures reduce coronary vasospasm in refractory angina. Trials have shown promise for coronary sinus occlusion. Autologous stem cell therapy is an innovative surgical approach that has shown promise in early trials but remains investigational. Selective surgical cardiac vein retroperfusion remains largely experimental, with limited clinical data. Conclusions: This review highlights the need for ongoing research and clinical trials to assess the effectiveness of surgical and nonsurgical options in INOCA. Although current data on surgical interventions is limited, these treatments may offer hope for patients with refractory symptoms. A personalized and multidisciplinary approach to management is essential for optimal patient outcomes. Full article

Hydrogen is a sustainable, clean source of energy and a viable alternative to carbon-based fossil fuels. To support the transport sector’s transition from fossil fuels to hydrogen, a hydrogen refuelling station network is being developed to refuel hydrogen-powered vehicles. However, hydrogen’s inherent properties present a significant safety challenge, and there have been several hydrogen incidents noted, with severe impacts to people and assets reported from operational hydrogen refuelling stations worldwide. This paper presents the outcome of an analysis of hydrogen incidents that occurred at hydrogen refuelling stations. For this purpose, the HIAD 2.1 and H2tool.org databases were used for the collection of hydrogen incidents. Forty-five incidents were reviewed and analysed to determine the frequent equipment failures in the hydrogen refuelling stations and the underlying causes. This study adopted a mixed research approach for the analysis of the incidents in the hydrogen refuelling stations. The analysis reveals that storage tank failures accounted for 40% of total reported incidents, hydrogen dispenser failures accounted for 33%, compressors accounted for 11%, valves accounted for 9%, and pipeline failures accounted for 7%. To enable the safe operation of hydrogen refuelling stations, hazards must be understood, effective barriers implemented, and learning from past incidents incorporated into safety protocols to prevent future incidents. Full article

Venous malformations (VMs) are rare, non-involuting, slow-flow, congenital anomalies of vascular morphogenesis, presenting as dilated venous channels with reduced perivascular cell coverage. The treatment may be conservative or surgical, including laser therapy. The management of small superficial VMs typically involves surgical excision. In larger or deeper VMs, the intralesional–endovascular injection of the sclerosing agent bleomycin is the gold standard, as it eliminates the dysplastic venous vessels by inducing fibrosis and therefore promotes regression of the lesion. This review explores the current literature regarding the role of bleomycin in venous malformation management, emphasizing the molecular pathways involved, the efficacy of sclerotherapy with bleomycin and its complications and the associated management challenges. It evaluates the clinical and histological features of venous malformations, alongside diagnostic methodologies and treatment strategies, drawing on the most recent bibliographic data. The literature was systematically reviewed using the PubMed database, offering insights into future research directions and highlighting innovative treatment approaches. Full article

Lymphedema is a frequent complication associated with breast cancer treatment. It is estimated that up to 30% of patients undergoing mastectomy develop this condition within 12 to 24 months post-surgery. In Mexico, the limited emphasis placed on lymphedema prevention in breast cancer patients is reflected in the insufficient coverage of this issue within official medical guidelines. In this review, research articles, systematic reviews, and official treatment guidelines were retrieved from PubMed, Google Scholar, Elsevier, SciELO, and Redalyc databases, to examine studies about the application and effectiveness of physiotherapy techniques for the prevention, diagnosis, and treatment of postmastectomy lymphedema. Our findings indicate that complex decongestive therapy (CDT) is considered the first-line treatment for lymphedema. Among its components, compression therapy shows the strongest individual evidence base. Nevertheless, studies consistently demonstrate that the combined use of all four components of CDT (manual lymphatic drainage, compression, skin care, and exercise) results in superior patient outcomes. Despite this, CDT is not routinely implemented as a standard of care for patients following mastectomy and/or lymphadenectomy in Mexico. Therefore, there is a pressing need to promote the inclusion of physiotherapy strategies, particularly CDT, in the prevention and management of postmastectomy lymphedema within national healthcare protocols. Full article

We propose a comprehensive literature review based on big data and V2X research to find promising tools to detect vehicles for traffic research and provide safe autonomous vehicle (AV) traffic. Presented data sources can provide real-time data for V2X systems and offline databases from VATnets for micro- and macro-modeling in traffic research. The authors want to present a set of sources that are not based on GNSS and other systems that could be interrupted by high-rise buildings and dense smart city infrastructure, as well as review of big data sources in traffic modeling that can be useful in future traffic research. Both reviews findings are summarized in tables at the end of the review sections of the paper. The authors added propositions in the form of two hypotheses on how traffic models can obtain data in the urban canyon connected environment scenario. The first hypothesis uses Roadside Units (RSUs) to retrieve data in similar ways to cellular data in traffic research and proves that this source is data rich. The second one acknowledges Bluetooth/Wi-Fi scanners’ research potential in V2X environments. Full article

Background: Bioelectrical impedance analysis (BIA) is a widely used field technique for assessing body composition in football. However, its reliance on population-specific regression equations limits its accuracy. Objective: This scoping review aimed to map the scientific literature on BIA applications in professional and semi-professional football, highlighting uses, limitations, and research opportunities. Methods: A comprehensive search was conducted in the scientific databases PubMed, EMBASE, Web of Science, and SPORTDiscus. Identified studies involved the use of BIA in professional and semi-professional football players (≥16 years) in the context of routine training and competition. Results: From 14,624 records, 39 studies met the inclusion criteria and were included. Three main applications were identified: (1) quantitative body composition assessment, (2) qualitative/semi-quantitative analysis (e.g., bioelectrical impedance vector analysis (BIVA)), and (3) muscle health and injury monitoring. Seven specific research areas emerged, including hydration monitoring, cross-method validation of body composition analyses, development of predictive models, sport phenotype identification, tracking training adaptations, performance/load assessment via phase angle, and localized BIA for injury diagnosis and recovery. Conclusions: While quantitative BIA estimates may lack individual-level precision, raw parameter analyses may offer valuable insights into hydration, cellular integrity, and muscle injury status, yet further research is needed to fully realize these applications. Full article

Modern societies are increasingly experiencing limited contact with nature, a phenomenon referred to as the “nature deficit.” The article presents a systematic review of the literature on this issue, with particular emphasis on the role of forests in mitigating its effects. The analysis, based on the Scopus and Web of Science databases, synthesizes the current state of knowledge on the consequences of nature deficit for physical, mental, and social health, while also highlighting the potential of forests as spaces supporting human well-being. The review process followed a systematic methodology, using precisely defined keyword combinations and multi-stage screening. From an initial pool of 88 publications, a critical selection process led to 11 articles that met the inclusion criteria and were analyzed in depth. The findings show that regular contact with nature reduces stress, anxiety, and ADHD symptoms, supports cognitive development, and im-proves concentration, creativity, and social skills. At the same time, there is a lack of consistent tools for clearly diagnosing nature deficit, and existing studies face significant methodological limitations (small samples, subjective measurements, lack of laboratory control). The article also identifies research gaps, particularly in the context of sustainable forest management, cultural differences, and the long-term health effects of exposure to nature. Full article

This scoping review investigates the use of fuzzy logic in serious games. Articles were searched in nine databases: ACM Digital Library, IEEE Xplore, IOPscience, MDPI, PubMed, ScienceDirect, Springer, Wiley, and Web of Science. The search retrieved 494 articles published between January 2020 and February 2025, of which 28 met the inclusion criteria. Specifically, four research questions were addressed, focusing on the taxonomy of serious games that use fuzzy logic, the characteristics of game design, the purpose and implementation of the fuzzy logic system within the game, and the experiments conducted in the studies. Results reported that 80% of the studies focused on educational serious games, while 20% addressed health applications. Mouse, keyboard, and smartphone touch screen were the most widely used interaction methods. The adventure genre was the most widely implemented in the studies (35.71%). Fuzzy logic was mainly used for adjusting game difficulty, followed by providing tailored feedback in the game. Mamdani inference was the most widely used inference method in the studies. Although 79% of the studies involved human participants in their experiments, 57% did not perform any statistical analysis of their results. Full article