Search Results (12,473)

Traditional Case-Based Reasoning (CBR) methods face significant methodological challenges, including limited information resources in case databases, methodologically inadequate similarity calculation approaches, and a lack of standardized case revision mechanisms. These limitations lead to suboptimal case matching and insufficient solution adaptation, highlighting critical gaps in the development of CBR methodologies. This paper proposes a novel CBR framework enhanced by generative AI, aiming to improve and innovate existing methods in three key stages of traditional CBR, thereby enhancing the accuracy of retrieval and the scientific nature of corrections. First, we develop an ontology model for comprehensive case representation, systematically capturing scenario characteristics, risk typologies, and strategy frameworks through structured knowledge representation. Second, we introduce an advanced similarity calculation method grounded in triangle theory, incorporating three computational dimensions: attribute similarity measurement, requirement similarity assessment, and capability similarity evaluation. This multi-dimensional approach provides more accurate and robust similarity quantification compared to existing methods. Third, we design a generative AI-based case revision mechanism that systematically adjusts solution strategies based on case differences, considering interdependence relationships and mutual influence patterns among risk factors to generate optimized solutions. The methodological framework addresses fundamental limitations in existing CBR approaches through systematic improvements in case representation, similarity computation, and solution adaptation processes. Experimental validation using actual case data demonstrates the effectiveness and scientific validity of the proposed methodological framework, with applications in risk assessment and emergency response scenarios. The results show significant improvements in case-matching accuracy and solution quality compared to traditional CBR approaches. This method provides a robust methodological foundation for CBR-based decision-making systems and offers practical value for risk management applications. Full article

In this study, an analysis was carried out of the combustion of pellets made from chamomile and English ryegrass biomass, including those with the addition of kaolin and urea, in terms of their physical and chemical properties. During combustion tests with synchronized timing, the concentrations of CO₂, CO, NO, and SO₂ in the flue gases were measured, along with the temperatures of the supplied air and the flue gases. The addition of kaolin improved combustion parameters, reduced CO emissions, and stabilized the combustion process, despite the deterioration of the mechanical durability of the pellets. Combustion in the drop-in burner (type B tests) showed higher energy efficiency (CEI) and lower flue gas toxicity (TI) than in the grate system (type A tests). The SiO₂ content in the chamomile ash explained its higher resistance to slagging, confirmed by characteristic ash temperatures. Comparison with other biofuels (straw, hay, sawdust) showed similarities or advantages in terms of reducing CO, NO, and SO₂ emissions. NO emissions were lower for pellets with urea and kaolin added, although in the case of biomass with high nitrogen content these relationships require further improvement. The research results indicate the potential of herbaceous biomass as a fuel in local heating systems. However, modification of such fuels is also associated with the need for further research on reducing emissions during unstabilized combustion phases, with particular emphasis on the ignition phase. Full article

Fatigue damage failure is a process where the mechanical properties of different materials continuously degrade under the action of cyclic loads. The cumulative analysis of fatigue damage has a significant impact on the service structure of major equipment. This paper starts from the mechanism of fatigue damage evolution, comprehensively considers the influence of the order of high-low cycle load mixed cyclic loading on the fatigue life performance, and based on the Manson-Halford nonlinear fatigue damage accumulation theory and the mechanism of relative cumulative damage, a new nonlinear damage accumulation fatigue life model is established, and a fatigue damage accumulation influencing factor D_cr is introduced to improve the prediction accuracy of the model. The new model proposed in this paper is verified through multi-level fatigue load data. By comparing the prediction results with other models under the same experimental conditions, the fatigue life prediction error precision of the new model is the best in similar cases, generally with an error precision between 10% and 20%, which proves the effectiveness and accuracy of the nonlinear damage accumulation model proposed in this paper. At the same time, the improved method in this paper has better stability while ensuring prediction accuracy. Full article

The objectives of this study were to determine the dose effect/s of glucose (G) and fructose (F) at different energy densities (ED) of diets on feed intake, body and organ weights, chemical composition of liver, feed conversion, and metabolomic indices (enzymes and hormones). Methods: Seventy-two 10-week-old male Wistar SPF rats were divided into 9 dietary groups and housed individually in metabolic cages. The control group was on a carbohydrate-free high lard diet (L), and for the other 8 treatment groups, the L content of the control diet was gradually replaced by G or F to decrease the dietary ED, in such a way that the nutrients (protein, minerals and vitamins) to energy ratio of the feeds remained constant. These experimental diets were fed to rats for 28 days. Feed intake and body weight were measured twice weekly. On the 28th day of the experiment, the rats were euthanized, and blood and organ samples were collected for further tests. Results and conclusions: The effects of F and G on twenty-six parameters were measured at different EDs of diets. Significant specific F effects (SFE) over the rats on G diets were found in case of feed intake (statistics with pooled data of feed intake (Fi) showed ~7% more feed intake of F rats: 10.8, 6.4, 9.5 and 2.0% at 5.28, 4.70, 4.23 and 3.85 kcal/g ED, respectively); body weight gain (the relation is polynomial; 8.0, 10.3, 0.1, and −10.2% at 5.28, 4.70, 4.23, and 3.85 kcal/g ED; it related to the weight change of viscera: liver, kidney and RWAT); liver fat (3.98, 21.42, 49.20 and 11.05% at 5.28, 4.70, 4.23, and 3.85 kcal/g ED, respectively); serum triglyceride (the relation is polynomial; 63.2, 88.1, 79.2 and 42.6% at 5.28, 4.73, 4.23, and 3.85 kcal/g ED, respectively); serum glucagon (−1.2, 380.2, 248.3 and 74.7% at 5.28, 4.70, 4.23, and 3.85 kcal/g ED, respectively), and serum leptin (9.59, 30.53, 72.64, and −46.49% at 5.28, 4.70, 4.23, and 3.85 kcal/g ED, respectively). An important conclusion is that in several cases, the effects of F and G were similar in the direction of change, but the magnitude of the effects was different. In case of feed conversion rate, there was no difference between the effect of G and F, however it is important to note that the higher the dietary energy and nutrient density, the better the feed conversion rate (FCR); The potential mechanism(s) of effect for each parameter is discussed and, where appropriate, the clinical relevance of the data compared to the known literature. Full article

Background/Objectives: This study aimed to identify the functional adaptations that enable competitive performance in a Paralympic cyclist with optimized bilateral transtibial prostheses compared to a conventional cyclist. Additionally, it describes the development of the prosthesis, designed through a user-centered engineering process incorporating Quality Function Deployment (QFD), Computer-Aided Design (CAD), Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), and topological optimization, with the final design (Design 1.4) achieving optimal structural integrity, aerodynamic efficiency, and anatomical fit. Methods: Both athletes performed a progressive cycling test with 50-watt increments every three minutes until exhaustion. Cardiorespiratory metrics, lactate thresholds, and joint kinematics were assessed. Results: Although the conventional cyclist demonstrated higher Maximal Oxygen Uptake (VO₂max) and anaerobic threshold, the Paralympic cyclist exceeded 120% of his predicted VO₂max, had a higher Respiratory Exchange Ratio (RER) [1.32 vs. 1.11], and displayed greater joint ranges of motion with lower trunk angular variability. Lactate thresholds were similar between athletes. Conclusions: These findings illustrate, in this specific case, that despite lower aerobic capacity, the Paralympic cyclist achieved comparable performance through efficient biomechanical and physiological adaptations. Integrating advanced prosthetic design with individualized evaluation appears essential to optimizing performance in elite adaptive cycling. Full article

General models of talent development have highlighted the importance of a community of practice to nurture talent potential, with recent studies refining factors that contribute to the developmental journey. In music, an early model described three phases of talent development, while current research has focused on transitions between these. Choral music research has investigated conductors’ expertise and choristers’ experiences, highlighting positive social impacts for children in addition to the development of choral skills. The purpose of this qualitative case study was to investigate talent development of 11 elite middle school choristers utilising interviews. Thematic analyses identified four themes and 10 sub-themes, demonstrating that choristers followed a developmental pathway similar to choral conductors, acquiring vocal competence and mastery, nurturing a sense of belonging to a choral community, participating in meaningful experiences, and becoming advanced choristers through intensive training. Chorister talent development was also linked to personality development, with transformation in choral identity leading to growth in personal confidence. This study extends research into choral talent development by documenting the voices of middle school children participating in an advanced choir, showing that high levels of performance can be achieved through expert choral coaching and without sacrificing the enjoyment of singing. Full article

Hearing loss is often caused by genetic and environmental factors, with inherited mutations responsible for 50–60% of cases. The GJB2 gene, encoding connexin 26, is a major contributor to nonsyndromic sensorineural hearing loss (NSHL) due to its role in cellular communication critical for auditory function. In Taiwan, common deafness-associated genes include GJB2, SLC26A4, OTOF, MYO15A, and MTRNR1, which were similar to those found in other populations. The most common pathogenic genes is GJB2 mutations and the hearing level in children with GJB2 p.V37I/p.V37I or p.V37I/c.235delC was estimated to deteriorate at approximately 1 decibel hearing level (dB HL)/year. We found another common mutation in Taiwan Biobank, GJB2 p.I203T, which were identified in our data and individuals carrying this mutation experienced more severe hearing loss, suggesting a synergistic effect of these mutations on auditory impairment. We suggest GJB2 whole genetic screening is recommended for clinical management and prevention strategies in Taiwan. This study used data from the Taiwan Biobank to analyze allele frequencies of GJB2 gene variants. Predictive software (PolyPhen-2 version 2.2, SIFT for missense variants 6.2.1, MutationTaster Ensembl 112 and Alphamissense CC BY-NC-SA 4.0) assessed the pathogenicity of specific mutations. Additionally, 82 unrelated NSHL patients were screened for mutations in these genes using PCR and DNA sequencing. The study explored the correlation between genetic mutations and the severity of hearing loss in patients. Several common GJB2 mutation sites were identified from the Taiwan Biobank, including GJB2 p.V37I (7.7%), GJB2 p.I203T (6%), GJB2 p.V27I (31%), and GJB2 p.E114G (22%). Bioinformatics analysis classified GJB2 p.I203T as pathogenic, while GJB2 p.V27I and GJB2 p.E114G were considered polymorphisms. Patients with GJB2 p.I203T mutation experienced more severe hearing loss, emphasizing the potential interaction between the gene in auditory impairment. The mutation patterns of GJB2 in the Taiwanese population are similar to other East Asian regions. Although GJB2 mutations represent the predominant genetic cause of hereditary hearing loss, the corresponding mutant proteins exhibit detectable aggregation, particularly at cell–cell junctions, suggesting at least partial trafficking to the plasma membrane. Genetic screening for these mutations—especially GJB2 p.I203T (6%), GJB2 p.V27I (31%), and GJB2 p.E114G (22%)—is essential for the effective diagnosis and management of non-syndromic hearing loss (NSHL) in Taiwan. We found GJB2 p.I203T which were identified in our data and individuals carrying this mutation experienced more severe hearing loss, suggesting a synergistic effect of these mutations on auditory impairment. We suggest whole GJB2 gene sequencing in genetic screening is recommended for clinical management and prevention strategies in Taiwan. These findings have significant clinical and public health implications for the development of preventive and therapeutic strategies. Full article

Understanding milk yield recovery following clinical mastitis (CM) and its influencing factors is essential for controlling the effect of mastitis on milk yield. This study investigated the associations between quarter-level milk yield recovery and milk loss, somatic cell count (SCC), clinical severity, and causative pathogens. Recovery was measured as percentage recovery for inflamed and uninflamed quarters separately. We analyzed 117 CM cases, identifying 117 quarter-level milk yield perturbations (qMYPs) in inflamed quarters and 299 in uninflamed quarters. The recovery of qMYPs was compared across quickly, slowly, and non-recovered groups for inflamed and uninflamed quarters, based on the average and slope of percentage recovery over time, using the Mann–Whitney test. Correlation and regression analyses were conducted to assess associations with milk loss, SCC, clinical severity, and pathogens. Inflamed quarters showed similar recovery to uninflamed quarters in recovered groups but significantly worse recovery in the non-recovered group (p < 0.05). In inflamed quarters, greater milk loss, higher SCC, more severe clinical signs, and major pathogens were associated with worse recovery (correlation < 0). In uninflamed quarters, these factors were linked to worse early recovery (correlation < 0), whileled to improved recovery over time (correlation > 0). Additionally, short-term and long-term recovery were influenced differently in inflamed and uninflamed quarters. These findings improve understanding of CM recovery and may support selective treatment, reduce disease impact, and enhance animal welfare in dairy production. Full article

Background: Lattice Radiation Therapy (LRT), a spatially fractionated stereotactic radiotherapy (SBRT) technique, has shown promising results in the palliative treatment of large tumors. The focus of our first analysis of 56 lesions ≥7 cm was on the extent of shrinkage following palliative LRT (mean 50%) and assessment of its effect duration (: mean 6 months). Herewith we present an updated analysis of our single-center LRT cohort, with a focus on LRT outcome across diagnoses and applied LRT regimens. Methods: We assessed the clinical outcome following LRT in 66 patients treated for 81 lesions between 01.2022 and 05.2025. LRT protocols included simultaneous integrated boost (sib-) LRT in 49 lesions (5 × 4–5 Gy to the entire mass with sib of 9–13 Gy to lattice vertices). Alternatively mainly in pre-irradiated and/or very large lesions—a single-fraction stereotactic LRT (SBRT-LRT) of 1 × 20 Gy to vertices only was delivered to 26 lesions. In six cases with modest response to single fraction SBRT-LRT, the sib-LRT schedule was added 4–8 weeks later. Results: The median age was 68 years (18–93). Main tumor locations were abdomino-pelvic (n = 34) and thoracic (n = 17). Histopathological diagnoses included carcinoma (n = 34), sarcoma (n = 31), and melanoma (n = 16). 31% of all lesions have been previously irradiated. 73% of cases underwent concurrent or peri-LRT systemic therapy. The mean/median overall survival (OS) time of the cohort was 7.6/4.6 months (0.4–40.2), 11.9/5.8 months in 16/66 alive, and 6.4/4.3 months in deceased patients, respectively. 82% of symptomatic patients reported immediate subjective improvement (PROM), with a lifelong response duration in most cases. Progressive disease (PD: >10% increase in initial volume) was found in 9%, stable disease (SD +/−10% of initial volume) in 19% of scanned lesions, and shrinkage (>10% reduction in initial volume) in 75%, with a mean/median tumor volume reduction of 51/60%. The extent of shrinkage was found to be 11–30%/31–60%/61–100% in 38/24/38% of lesions. Response rates (PD, SD, shrinkage) following the two applied LRT regimens, as well as those related to sarcoma and carcinoma diagnoses, were found to be comparable. Treatment tolerance was excellent (G0-1). Conclusions: Palliative LRT provides rapid subjective relief in ~80% of symptomatic patients. Radiologic shrinkage was stated in 75% of FU-scanned lesions, with a lifelong effect duration in most patients. LRT was found effective across histologies, with a similar extent of shrinkage in carcinoma and sarcoma following 1F SBRT- and 5F sib-LRT regimens, respectively. Full article

The rapid growth of e-commerce has created substantial environmental impacts, driving the need for advanced optimization models to enhance supply chain sustainability. As consumer preferences shift toward environmental responsibility, organizations must adopt robust quantitative methods to reduce ecological footprints while ensuring operational efficiency. This study develops a novel hybrid multi-criteria decision-making (MCDM) model to evaluate and prioritize green suppliers under uncertainty, integrating the rough-Dombi best–worst method (BWM) and an improved Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The proposed model addresses two key challenges: (1) inconsistency in expert judgments through rough set theory and Dombi aggregation operators and (2) ranking instability via an enhanced TOPSIS formulation that mitigates rank reversal. Mathematically, the rough-Dombi BWM leverages interval-valued rough numbers to model subjective expert preferences, while the Dombi operator ensures flexible and precise weight aggregation. The modified TOPSIS incorporates a dynamic distance metric to strengthen ranking robustness. A case study of five e-commerce suppliers validates the model’s effectiveness, with results identifying cost, green competitiveness, and external environmental management as the dominant evaluation dimensions. Key indicators—such as product price, pollution control, and green design—are rigorously prioritized using the proposed framework. Theoretical contributions include (1) a new rough-Dombi fusion for criteria weighting under uncertainty and (2) a stabilized TOPSIS variant with reduced sensitivity to data perturbations. Practically, the model provides e-commerce enterprises with a computationally efficient tool for sustainable supplier selection, enhancing resource allocation and green innovation. This study advances the intersection of uncertainty modeling, operational research, and sustainability analytics, offering scalable methodologies for mathematical decision-making in supply chain contexts. Full article

Sensors are widely used in inland waterway buoys to monitor their position, but the collected data are often affected by noise, outliers, and irregular sampling intervals. To address these challenges, a standardized data processing framework is proposed. Outliers are identified using a hybrid approach combining interquartile range filtering and Isolation Forest algorithm. Interpolation methods are adaptively selected based on time intervals. For short-term gaps, cubic spline interpolation is applied, otherwise, a method that combines dominant periodicity estimation with physical constraints based on power spectral density (PSD) is proposed. An adaptive unscented Kalman filter (AUKF), integrated with the Singer motion model, are applied for denoising, dynamically adjusting to local noise statistics and capturing acceleration dynamics. Afterwards, a set of time-frequency features are extracted, including centrality, directional dispersion, and wavelet transform-based features. Taking the lower Yangtze River as a case study, representative buoys are selected based on dynamic time warping similarity. The features analysis result show that the movement of buoys is closely related to the dynamics dominated by the semi-diurnal tide, and is also affected by runoff and accidents. The method improves the quality and interpretability of buoy motion data, facilitating more robust monitoring and hydrodynamic analysis. Full article

Objectives: This study evaluated the comfort of using silicone tubes installed in the oral cavity as a reservoir for a hydrogel that allows for a slow delivery of the active substance acting locally or systemically. Methods: Perforated silicone tubes 8 cm long with two internal diameters were used: T1 (1.5 mm) and T2 (2.4 mm). The reservoirs were filled with hydrogel placebo formulations: carbomer 1.5% (C), hydroxyethylcellulose 4% (HEC), or hydroxypropylmethylcellulose (hypromellose) 3% (HPMC). Physical parameters of the gel were determined with a viscometer and a texture analyzer. During 4 h of application, the volunteers reported sensory perceptions, and the rate of gel erosion was evaluated. The results were correlated with the viscosity, rheology, and dissolution rate of the gels measured in vitro. Results: Volunteers reported only mild discomfort wearing the device, preferring smaller-sized tubes. The tubes were easy to apply and generally comfortable, with no reports of significant discomfort. Despite similar viscosity and rheology, the polymer type had a significant impact on erosion rate, both in vitro and in vivo. After 4 h of application in vivo, more than 90% of the carbomer gel remained in the tube, while in the case of less cohesive HPMC or HEC gels, this was about 50%. A statistically significant correlation was observed between the in vitro and in vivo mean erosion percentages for the HEC and HPMC gels. Conclusions: This study supports the use of silicone tubes as effective reservoir devices for prolonging the residence time of drug formulations in the oral cavity. Full article

This study evaluates the viability of a specific hybrid renewable energy system (HRES) installation designed for a remote community as a case study in Cuba. The system integrates solar, wind, and biomass resources to address localised challenges of energy insecurity and environmental degradation. Rather than offering a generalised evaluation of HRES technologies, this work focuses on the performance, impacts, and viability of this particular configuration within its unique geographical, social, and technical context. Using life cycle assessment (LCA) and input–output modelling, the research assesses environmental and socioeconomic impacts. The proposed HRES reduces greenhouse gas emissions by 60% (from 1.14 to 0.47 kg CO₂eq/kWh) and fossil energy consumption by 50% compared to diesel-based systems. Socioeconomic analysis reveals that the system generates 40.3 full-time equivalent (FTE) jobs, with significant employment opportunities in operation and maintenance. However, initial investments primarily benefit foreign suppliers due to Cuba’s reliance on imported components. The study highlights the potential for local economic gains through workforce training and domestic manufacturing of renewable energy technologies. These findings underscore the importance of integrating multiple renewable sources to enhance energy resilience and sustainability in Cuba. Policymakers should prioritise strategies to incentivise local production and capacity building to maximise long-term benefits. Future research should explore scalability across diverse regions and investigate policy frameworks to support widespread adoption of HRES. This study provides valuable insights for advancing sustainable energy solutions in Cuba and similar contexts globally. Full article

Most of the failures during the actual operation of equipment are caused by improper human operation, tools, spare parts, and environmental factors. These faults are routine. Conventional faults have been validated during equipment development, testing, identification, and maintenance processes, with clear definitions and clear fault tree analysis (FTA) conclusions. Digital twins can offer rapid and interactive diagnostic capabilities for routine equipment failures. To enhance the efficiency of routine fault diagnosis and the interactive experience of the diagnosis process, this paper proposes a digital twin-based equipment routine fault diagnosis model. On this basis, considering the excellent interactivity of the Interactive Electronic Technical Manual (IETM), a conventional equipment fault diagnosis scheme based on twin data and IETM is designed. This scheme converts the equipment fault tree into an IETM fault data model (DM), which is structured and stored in a database to form a fault database. Using real-time twin data of equipment as input, the FTA method is adopted to perform step-by-step fault diagnosis and isolation guidance operation through the IETM process DM combined with fault, while providing maintenance operation guidance. When the real-time twin data of the equipment is not completely consistent with the fault information in the fault library, the case analysis method is used to calculate the similarity between the real-time twin data of the equipment and the clearly defined fault symptom information in the fault library. Based on the set similarity threshold, IETM pushes fault DMs above the threshold for corresponding fault diagnosis isolation guidance. Full article

Complex task crowdsourcing (CTC) integrates distributed talent, knowledge, and ideas into innovation via the web; however, task decomposition remains a critical challenge. While existing studies focus primarily on workflow management for specific tasks, they leave a gap in decomposing more complex, creative tasks, which are characterized by the absence of objective ground truths, nonlinear dependencies, and non-sequential processes. To address this gap, we propose a novel integrated task decomposition framework for CTC that comprises three interconnected components. First, primary decomposition considers knowledge reuse by identifying similar past task decomposition schemes to inform the initial breakdown. Second, modifications to the scheme are guided by work breakdown structure (WBS)-based principles, which also serve as a foundation when no prior knowledge is available. Third, to enhance executability, a task package model is proposed to combine subtasks that share common resources, thereby reducing coordination costs and avoiding waste of workers’ capabilities. To solve this model, we develop an improved non-dominated sorting genetic algorithm (NSGA-II) to generate the final decomposition scheme. A case study from ZBJ.COM validates the feasibility and effectiveness of the proposed framework. Experimental results demonstrate that, compared to baseline algorithms, the improved NSGA-II better balances conflicting objectives and generates non-dominated solution sets with higher diversity and more uniform distribution. Full article