Search Results (172)

This work presents an interpretable machine learning (ML) system that uses composition- and physics-based descriptors to predict the bulk moduli of high-entropy alloys (HEAs). Extra Trees, Random Forest, Gradient Boosting, AdaBoost, and LightGBM are five ensemble ML algorithms that were systematically shaped and refined by hyperparameter fine-tuning. With a test R² of about 0.852 and an RMSE and MAE of about 5.49 GPa and 1.5 GPa, respectively, Extra Tree outperformed the other optimized models, indicating good generalization capacity for untested HEA compositions. The computational efficiency results showed that LightGBM had the fastest prediction speed (~4.24 ms), whereas Extra Trees had the shortest training time (~17.3 s). The majority of the optimized models had statistically equal prediction performance (p > 0.05), according to statistical validation using paired t-test analysis, even though residual error distributions for the Extra Tree model established consistent and unbiased predictions. To enhance the interpretability of the model, SHAP-based explainable analysis was performed, which included SHAP importance, dependence, and waterfall plots. The SHAP results revealed that the primary determinants impacting bulk modulus behavior in HEAs were Zr content, mean electronegativity, Al content, bond strength, and melting-temperature-related parameters. The proposed framework enables the rapid identification and design of next-generation HEAs by permitting precise and computationally efficient bulk modulus prediction, as well as physically significant insights into descriptor–property connections. Full article

The dynamics of methane (CH₄), nitrous oxide (N₂O) and carbon dioxide (CO₂) in groundwater have rarely been investigated. As dissolved gases they may be transported to distant sites and, hence, to the atmosphere. Crumps Cave (CC) is located on a perched aquifer in south-central Kentucky. Water was sampled at a waterfall within the cave located 15 m below the surface, at two adjacent surface wells 15 m and 50 m deep, providing samples from the epikarst and regional aquifer, respectively. Dissolved gases and geochemistry parameters were analyzed for seasonal changes across three years of weekly monitoring (2015–2017) using Kruskal–Wallis H tests and Bonferroni-corrected pairwise comparisons. Dissolved CO₂ concentrations are mainly controlled by percolation through the epikarst, influenced by soil respiration, and vary with rainfall and seasonal temperature fluctuations. CH₄ showed a site-dependent pattern: concentrations were significantly elevated in warm seasons at the shallow and deep wells, where anaerobic conditions and agriculturally derived organic matter promote methanogenesis; no seasonal variation was detected at the cave site, where oxic conditions limit CH₄ year-round. N₂O was significantly elevated in cold seasons at all three sites, driven by cold-season denitrification of agriculturally derived nitrates. N₂O did not differ between sites, indicating seasonal temperature-driven denitrification as the primary control rather than site hydrology, with cold-season denitrification of agriculturally derived nitrates from fertilizer application. Indirect gas emissions are characteristic of karst systems and may be transported or stored in aquifers through complex interactions of groundwater recharge, microbial activity, and seasonal land-use variability. Full article

Background: Currently, expected goal models are tools that enable quantitative analysis in the study of conventional sports, although they have seen very little application in the Paralympic context. Objective: To present a trained expected goals model for 5-a-side blind soccer games based on an analysis of 164 offensive plays by the national team that won first place at the 2022 IBSA Copa América. The novelty of this work lies in being, to our knowledge, the first expected goals (xG) model developed for Paralympic blind football (B1): conventional xG weights cannot be transferred directly because shooting in F5 is governed by auditory orientation, the absence of an offside rule, a smaller rebound-walled pitch, and fully blind executors, so a sport-specific, reproducible and SHAP-interpretable benchmark is required where none previously existed. Materials and Methods: The SHapley Additive exPlanations library was used to analyze the data via partial dependency plots, dependency scatter plots, waterfall plots, decision plots, and SHAP heatmaps. Additionally, ten machine learning algorithms were compared, including logistic regression, random forest, extra trees, gradient boosting, XGBoost, LightGBM, CatBoost, support vector machine, k-nearest neighbors, and multilayer perceptron, using a 70/30 stratification process with fivefold stratified cross-validation to define the main hyperparameters. Results: The most consistent model was CatBoost (F1 = 0.778; AUC-ROC = 0.913; AUC-PR = 0.828; MCC = 0.729; Brier = 0.072), which allowed for independent analysis and evaluation of the dataset. The five main offensive variables were determined to be (i) distance to the goal before the shot; (ii) lateral coordinate; (iii) absolute magnitude of the shooting angle; (iv) magnitude of the progression vector; (v) proximity to the side kickboard. However, none of these variables proved to be decisive in the tournament (n = 24), a characteristic that the model captured as a significant negative contribution from the opponent variable. Conclusions: The expected goals model considered for this study serves as a starting point for further analysis of tactical variables in 5-a-side soccer for the blind. Because the model was trained on a single team in a single tournament with few positive cases, these results should be read as preliminary, hypothesis-generating tactical insights rather than validated performance estimates, and require external validation before transfer to other teams or competitions. Full article

The bolted rotor system functions as a critical component in aero-engines and gas turbines. Additionally, the misalignment fault is a typical and common fault in bolted rotor systems. Nevertheless, current research on bolted rotor systems has not covered misalignment faults. Therefore, a mathematical model of bolted rotor systems incorporating misalignment faults is established in this work. The nonlinear dynamics of bolted rotor systems involving misalignment are investigated by the comparison of the frequency amplitude responses, waterfall diagrams, rotor orbits and time-varying stiffness. Moreover, an in-depth analysis is conducted on the variations in vibration behaviors of rotor systems under different misalignment degrees. Finally, the proposed model is examined using rotor-rig tests conducted under aligned and misaligned conditions. A consistent observation from the numerical and test results is that the 2× frequency resonance speed does not equate precisely to 0.5 times the critical speed. In addition, the 2× component undergoes a sudden change as the misalignment level rises. Full article

Sustainable rural tourism governance in the Global South faces a persistent challenge: enabling genuine community participation in destination management while protecting environmental assets and cultural heritage. This study examines participatory governance practices at Kampung Senyum Homestay, Cibeusi Village, West Java, Indonesia, a community-based tourism (CBT) initiative that has sustained operations for over eight years, despite a 60% failure rate among comparable initiatives. A qualitative case study design was employed, with data collected over six months (November 2022–May 2023) through participant observation (12 days), in-depth interviews with 14 stakeholders, and document analysis. Data were analyzed using Miles et al.’s interactive model and critical discourse analysis. Findings reveal three interrelated participation layers shaping tourism governance outcomes: interpersonal engagement fostering horizontal host–guest relationships (89% of tourists report kinship-based experiences); deliberative governance through musyawarah desa enabling community-led environmental stewardship, including the collective rejection of a proposal to bring 100 tourists monthly to protect waterfall ecosystems; and digital storytelling by youth extending local heritage narratives globally (150 posts, 7.2% engagement rate). The study proposes a ‘layered participation’ model demonstrating that tourism sustainability depends on participatory governance mechanisms that build social trust, integrate traditional ecological knowledge, and balance economic development with environmental conservation and cultural heritage management. The study also critically examines structural inequalities, including gender asymmetries, unequal benefit distribution, and linguistic barriers, that persist within participatory governance structures, offering a contextually grounded governance framework for rural tourism destinations in the Global South. Full article

The topographic features of the seafloor can be observed clearly via high-resolution side-scan sonar imagery. However, the faithful interpretation of a sonar image depends strongly on the accuracy with which the location of the sea bottom line can be tracked within the image, and current tracking methods function poorly under high sonar signal noise or suffer from high complexity. The present work addresses this issue by applying the characteristics of simple sonar waterfall maps in conjunction with robust edge detection and multi-scale analysis based on wavelet transform modulus maxima. The proposed tracking method is demonstrated to provide superior effectiveness and accuracy in comparison with existing baseline methods based on the results of experiments conducted with a representative side-scan sonar image with and without applied speckle noise. This superiority can be attributed to the good localization characteristics and multi-scale detection features of wavelet transform analysis, which can suppress the impact of noise in the sonar image on the accurate extraction of edge information. Full article

To improve the accuracy and stability of X-ray pulsar time-delay estimation for multi-scenario celestial remote sensing and navigation, this paper proposes a time-delay estimation method based on a waterfall-plot multi-criteria framework and develops an end-to-end simulation framework for multi-scenario applications. First, a pulsar profile waterfall-plot model is built, and principal component analysis is performed to characterize candidate periodic structures. The contribution rate of the principal eigenvalue is used to describe the overall significance of the candidate period, and the projection variance of the first principal component is used to measure the prominence of the candidate pattern in the principal subspace. Second, support vector regression is used to fit the peak track of the waterfall plot, and a regression slope is used to describe the geometric stability of the candidate period. These three indicators are fused for pulsar period and time-delay estimation. Tests based on Insight-HXMT satellite observation data show that, compared with the ${\chi }^2$ and $Z^2$ test methods, our method improves time-delay estimation accuracy by 68.68% and 50.43%, respectively. Multi-scenario navigation simulations indicate positioning improvements of approximately 0.83 km, 3.04 km, and 1.05 km in the Earth-orbiting, Earth–Moon transfer, and Mars approach scenarios, respectively. These results suggest that the proposed framework can improve pulsar time-delay estimation and may provide useful measurement support for celestial remote sensing and navigation. Full article

Acute coronary syndrome (ACS) remains a leading cause of death and morbidity worldwide. The pathophysiology of ACS has been largely interpreted through abnormalities of the coronary arteries and the microvascular bed. However, the coronary circulation is fundamentally a closed-loop system, in which the venous component represents the final link in myocardial blood return. In contrast to the extensive literature on arterial and microvascular disease, there are relatively few studies on the coronary venous system (CVS) in the context of ACS. The CVS is important in relation to ACS from two complementary perspectives. First, structural or functional abnormalities of the CVS can contribute to myocardial ischemia; second, coronary venous flow can reflect the hemodynamic outcomes of acute ischemia and reperfusion. The ‘vascular waterfall’ phenomenon is considered one of the primary mechanisms governing coronary venous return, linking myocardial compression and venous pressure to the flow from the coronary sinus (CS) into the right atrium. Experimental and clinical evidence has shown that CS thrombosis is associated with myocardial infarction and may also complicate ACS. Furthermore, studies evaluating CS blood flow generally show a decrease in the acute phase of ischemia and an increase after reperfusion. However, the existing evidence is limited and largely based on small observational studies. Therefore, this review aimed to examine the pathophysiological mechanisms and hemodynamic behavior of the CVS in ACS, starting from embryological development. Full article

Waterfalls are common natural heritage objects. Their assessments often focus on physical properties of waterfalls and/or visitors’ judgments. However, local conditions determining the visibility of waterfalls also matter. These conditions can be understood as visual accessibility. It is proposed to assess the latter semi-quantitatively regarding physical availability of different views of waterfalls, the scalability of these views, opportunities for taking natural photographs and recreation, seasonality, the presence of physical barriers for observation, the influence of natural shadows, and the presence of safety challenges. The assessment procedure is objective because it deals with real landscape peculiarities and not with perceived aesthetics. Several small waterfalls visited by crowds of tourists in two different regions of Russia were used to exemplify the proposed approach. It was established that the Risyoksky and Batareysky waterfalls in the Murmansk Region (Russian Arctic) have limited visual accessibility, and that of the Sakhraysky, Oselkovy, and Filimonova waterfalls in the Republic of Adygeya (Russian South) is moderate. Generally, visual accessibility complicates the perception of waterfalls, and the outcomes of its assessment hold practical importance in natural heritage and tourism management. Full article

Although the transition from the Waterfall model to Agile practices has accelerated software delivery, it has often weakened documentation practices, contributing to persistent information asymmetry between Product Managers and Developers. This study introduces an LLM-based reverse engineering framework designed to assist product management workflows by analyzing source code and generating enriched development tickets. The proposed Interactive Product Management Assistant leverages the long-context capabilities of Gemini 1.5 Pro together with a context-caching mechanism to analyze large codebases, identify ambiguities in product requests, highlight potential edge cases, detect possible cascading dependencies (“domino effects”), and generate code pointers that guide developers to relevant implementation areas. The framework was evaluated through case studies on several open-source projects, including WordPress, ERPNext, Ghost, and Odoo. The results suggest that the system can support requirement clarification, improve visibility of potential implementation impacts, and reduce exploratory effort during code analysis. In addition, the implemented preprocessing and caching mechanisms reduce analysis costs and improve operational efficiency during iterative interactions. Rather than providing a large-scale quantitative before-and-after comparison, this paper presents a qualitative case study and a proof-of-concept implementation to demonstrate the feasibility of the proposed approach. Overall, the findings demonstrate the feasibility of using LLM-assisted reverse engineering to support requirements analysis and product–developer collaboration, highlighting the potential of AI-based tools to complement traditional requirements engineering practices in complex software projects. Full article

Melanoides tuberculata is one of the world’s main invasive snail species; therefore, mapping its occurrence is essential for predicting its dispersion patterns and proposing control measures. This study aimed to map the occurrence of M. tuberculata and its associated parasites in a tourist waterfall complex located in Fortaleza dos Nogueiras, Southern Maranhão, Brazil. We collected snails over three months (July, August, and September 2025) in the Castanhão, Esmeralda, and Recanto das Águias waterfalls, and in the Panela stream, to estimate their reproductive stage and to assess the presence of parasites. We demonstrated for the first time the occurrence of M. tuberculata at all evaluated collection points. Morphological data of the shells suggested that the M. tuberculata populations were in the initial phase of their reproductive cycle; however, some specimens showed a complete reproductive stage. Additionally, we found M. tuberculata infected with trematode larvae that resembled the Gymnocephalus-type cercariae in the Castanhão waterfall and Panela stream. Therefore, we updated the distribution of M. tuberculata in Brazil and discussed the possible environmental and public health impacts of this species in the study area. Full article

Acute malnutrition affects 3.1% of children under five years of age in Amazonian communities in Peru, where limited access to health services constrains timely nutritional assessment. In this context, this study aimed to develop, implement, and evaluate NutriRadar, a mobile application for automated childhood nutritional classification based on the anthropometric standards of the World Health Organization (WHO). The application was developed using a waterfall software development methodology and implements the calculation of the Weight-for-Height Z-score (WHZ) from basic anthropometric variables (weight, height, age, and sex). NutriRadar was designed with offline functionality, deferred data synchronization, and compatibility with low-end mobile devices to support operational use in Amazonian settings. Field validation was conducted in two early childhood education institutions in Puerto Maldonado, Peru, and included anthropometric assessments of 75 children aged 3–4 years. The application demonstrated stable offline operation, response times suitable for clinical practice, and nutritional classification results equivalent to the WHO Anthro reference tool. NutriRadar represents a viable and reproducible digital automation solution for the operational application of a deterministic WHO anthropometric protocol, contributing to the reduction of operational errors and strengthening standardized nutritional assessment in resource-limited Amazonian contexts. Full article

Critical closing pressure (CCP) and the vascular waterfall have long been used to explain perfusion failure in shock, yet their physiological meaning has been inconsistently interpreted. CCP is frequently treated as a continuous downstream pressure and inserted into formulas such as mean arterial pressure (MAP) − CCP, implying that a collapse threshold behaves like an opposing pressure even when vessels remain open. Drawing on classical vascular mechanics, whole-bed flow studies, microvascular models, and contemporary clinical physiology, we show that this interpretation is incorrect. Tone-dependent arteriolar collapse does not behave as a Starling resistor: CCP is a threshold at which smooth-muscle tension exceeds intraluminal pressure and vessels close, not a pressure governing flow in patent vessels. Perfusion becomes heterogeneous because different vascular beds reach their collapse thresholds at different pressures (via excessive tone, extrinsic compression, or profound hypotension), disconnecting macro-haemodynamics from microcirculatory flow. This explains why systemic variables such as MAP and systemic vascular resistance (SVR) may appear adequate even while tissues are under-perfused, a phenomenon now termed haemodynamic incoherence. Reframing CCP as a binary collapse threshold resolves longstanding contradictions in the literature, clarifies why MAP-centred targets often fail, and unifies the behaviour of shock states within a four-interface model of circulatory coupling. Therapeutically, the aim is not to “restore a waterfall” but to reopen closed vascular territories by lowering excessive tone, relieving external pressure, or raising truly low arterial inflow. This mechanistic reinterpretation provides a more coherent, physiologically grounded approach to personalised perfusion management in critical illness. Full article

Background: Triple-negative breast cancer (TNBC), defined by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2) expression, is associated with increased BRCA1/2 mutation rates. Extracellular vesicles (EVs) play a pivotal role in TNBC progression. This study aimed to analyze BRCA1/2 mutations and identify EV-related biomarkers for TNBC by employing TNBC-related datasets and EV-related genes (EVRGs). Methods: Initially, BRCA1/2 mutations in TNBC patients were examined. Differentially expressed EVRGs (DE-EVRGs) were identified by integrating the results of both differential expression analysis and weighted gene co-expression network analysis (WGCNA). Biomarkers were identified using Receiver Operating Characteristic (ROC) and Kaplan–Meier (K–M) analyses. Finally, functional enrichment, drug prediction, molecular docking, and reverse transcription quantitative polymerase chain reaction (RT-qPCR) analyses were performed. Results: Waterfall plots indicated that TP53 exhibited the highest mutation frequency in both the mutation (MUT) and wild-type (WT) group. Four distinct types of immune cells (for example, eosinophils and neutrophils) showed significantly elevated expression levels in the WT group. Notably, PLA2G5 was identified as a biomarker of TNBC and its expression was significantly lower in TNBC (p = 0.0025). Functional analysis demonstrated that PLA2G5 is enriched in the “drug metabolism cytochrome P450” pathway. Finally, 20 drugs targeting PLA2G5 were identified, among which leukotriene C4 demonstrated a binding affinity of −7.2 kcal/mol. This finding suggests that leukotriene C4 has potential therapeutic applications for the treatment of TNBC. Conclusions: Our study found significant differences between the MUT and WT groups, identifying PLA2G5 as a biomarker for TNBC and offering a theoretical basis for TNBC treatment. Full article

In recent years, switched reluctance motors have emerged as a promising option for various applications due to their low manufacturing cost, rare-earth-free construction, and mechanical robustness. However, their widespread adoption is often limited by high torque ripple and acoustic noise. To address these challenges, this paper presents a comparative study of the acoustic noise performance of an 18/12 switched reluctance motor under various current control techniques. This comparison offers valuable insight into the motor’s vibroacoustic characteristics, which is essential for optimizing SRM performance, particularly in applications where noise reduction is critical. Dynamic simulations of an SRM are carried out in MATLAB/Simulink, and multi-physics analyses are performed in ANSYS Workbench. The multi-physics modeling includes electromagnetic, modal, and harmonic response analyses for four current control techniques evaluated across different operating speeds under light-load conditions. The simulation results are validated experimentally using an actual motor mounted on a dynamometer setup. The corresponding acoustic signatures for each control technique are presented as 2D plots of equivalent radiated power from simulations and sound power level from experimental tests. In addition, experimental waterfall diagrams are provided for each control technique. Full article