Search Results (6,368)

This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors. Full article

The probability density function (PDF) of the product of two normal random variables remains an open discussion. Researchers have proposed many forms of PDFs. Among these, two notable PDFs are an analytical solution with infinite summation and an integral form with transformation. For practical computation, they must be estimated. The form with infinite summation must be truncated to a finite summation, and the form still in integration must be computed numerically. As a result of this estimation, an error occurs in the value of the estimation. This paper derives upper bounds for the estimation error resulting from truncation and numerical approximation in integral calculations. The upper bound error between the exact PDF and the truncated PDF is expressed as a geometric series using Bessel function inequality and Stirling’s approximation. The geometric formula allows the quantification of the total truncation error to be determined. For the PDF, which is still in integration form, the trapezoidal rule is used for numeric calculation. Hence, the error can be determined using the error-bound formula. The two estimated PDFs have their own advantages and disadvantages. The truncated PDF gives a relatively small upper bound value compared to the numerical calculation integral form PDF for a small value domain. However, the truncated PDF fails to perform for a large value domain, and only the integral form PDF can be used. The error for the estimation is applied to the conventional mass measurement. The results demonstrate that the error can be controlled through an analytical approach. Full article

Former coal mining in the Ruhr area of North Rhine-Westphalia, Germany, leads to significant challenges in flood management due to drainless sinks in urban areas caused by ground depression. Consequently, pumping stations have been constructed to enable the drainage of incoming river discharge, preventing overland flooding. However, in the event of the failure of pumping stations, these areas are exposed to a higher flood risk. To address this issue, a methodology has been developed to assess the probability of pumping failures by identifying the most significant failure mechanisms and integrating them into a Bayesian network. To evaluate the impact on the flood inundation probability, a new approach is applied that defines pump failure scenarios depending on available pump discharge capacity and integrates them into a flood inundation probability map. The result is a method to estimate the flood inundation probability stemming from pumping failure, which allows the integration of internal failure mechanisms (e.g., technical or electronic failure) as well as external failure mechanisms (e.g., sedimentation or heavy rainfall). Therefore, authorities can assess the most probable pumping failures and their impact on flood risk management strategies. Full article

The global shift towards cleaner energy sources is driving the adoption of hydrogen as an environmentally friendly alternative to fossil fuels. Among the forms currently available, Liquid Hydrogen (LH₂) offers high energy density and efficient storage, making it suitable for large-scale transport by rail. However, the flammability of hydrogen poses serious safety concerns, especially when transported through confined spaces such as railway tunnels. In case of an accidental LH₂ release from a freight train, the rapid accumulation and potential ignition of hydrogen could cause catastrophic consequences, especially if freight and passenger trains are present simultaneously in the same tunnel tube. In this study, a three-dimensional computational fluid dynamics model was developed to simulate the dispersion and explosion of LH₂ following an accidental leak from a freight train’s cryo-container in a single-tube double-track railway tunnel, when a passenger train queues behind it on the same track. The overpressure results were analyzed using probit functions to estimate the fatality probabilities for the passenger train’s occupants. The analysis suggests that a significant number of fatalities could be expected among the passengers. However, shorter users’ evacuation times from the passenger train’s wagons and/or longer distances between the two types of trains might reduce the number of potential fatalities. The findings, by providing additional insight into the risks associated with LH₂ transport in railway tunnels, indicate the need for risk mitigation measures and/or traffic management strategies. Full article

Air pollution from fine particulate matter (PM2.5) is a recurring crisis in Northern Thailand, largely driven by seasonal biomass burning. This study investigates how socioeconomic and individual characteristics shape labor allocation during high-exposure periods. Using survey data from 400 individuals across eight provinces in April–May 2024, we applied a logit model to estimate the probability of reducing work hours. Results show heterogeneous and non-linear patterns of avoidance. The probability of work reduction rose across higher income strata but peaked in the third stratum before declining in the fourth, reflecting the trade-off between avoidance and the opportunity cost of foregone earnings. Education exhibited a strong awareness effect, with each additional year increasing avoidance behavior. Outdoor workers and individuals with respiratory conditions were most likely to reduce work, indicating rational prioritization under greater exposure risks. Together, these findings demonstrate environmental inequality: lower-income and less-educated groups remain disproportionately exposed due to limited coping capacity. The regional context of Northern Thailand further amplifies these vulnerabilities. Policy interventions should prioritize protective measures for vulnerable groups while promoting long-term alternatives to biomass burning. By highlighting nuanced behavioral responses, this study extends evidence on environmental inequality in developing-country contexts. Full article

Finite element (FE) models are widely used in structural health monitoring to represent real structures and assess their condition, but discrepancies often arise between numerical and actual structural behavior due to simplifying assumptions, uncertain parameters, and environmental influences. Temperature variation, in particular, significantly affects structural stiffness and modal properties, yet it is often treated as noise in traditional model updating methods. This study treats temperature changes as valuable information for model updating and structural damage quantification. The Bayesian model updating approach (BMUA) is a probabilistic approach that updates uncertain model parameters by combining prior knowledge with measured data to estimate their posterior probability distributions. However, traditional BMUA methods assume mass is known and only update stiffness. A novel BMUA framework is proposed that incorporates thermal buckling and temperature-dependent stiffness estimation and introduces an algorithm to eliminate the coupling effect between mass and stiffness by using temperature-induced stiffness changes. This enables the simultaneous updating of both parameters. The framework is validated through numerical simulations on a three-story aluminum shear frame under uniform and non-uniform temperature distributions. Under healthy and uniform temperature conditions, stiffness parameters were estimated with high accuracy, with errors below 0.5% and within uncertainty bounds, while mass parameters exhibited errors up to 13.8% that exceeded their extremely low standard deviations, indicating potential model bias. Under non-uniform temperature distributions, accuracy declined, particularly for localized damage cases, with significant deviations in both parameters. Full article

Background/Objectives: Accurate estimation of caloric intake from breastfeeding is essential for understanding infant nutrition during early life. However, most existing models rely on fixed assumptions and do not reflect the natural variability in feeding behaviors and human milk composition. This study aims to provide a realistic estimation of breast milk (BM) caloric intake throughout infancy using a probabilistic approach based on empirical data. Methods: A probabilistic model was developed using four variables: feeding frequency, volume per feeding, caloric density, and infant weight. Systematic reviews were conducted to inform the input values of the first three variables, and meta-analyses were performed when feasible. Infant weight was based on World Health Organization (WHO) growth standards. Variables were stratified by age and integrated into the model through appropriate probability distributions. Monte Carlo simulations were conducted to estimate caloric intake per kilogram of body weight, expressed both per day and per feeding, across all age groups. Results: The model showed a progressive decline in daily caloric intake per kilogram with age, consistent with decreasing feeding frequency and the introduction of complementary foods. In contrast, caloric intake per feeding increased with age. These findings align with WHO energy intake targets during exclusive breastfeeding and reflect expected physiological changes in infant growth and feeding behavior. Conclusions: This study provides a probabilistic framework for estimating BM caloric intake across infancy, accounting for interindividual and age-related variability. It offers a valuable research tool to support future studies on infant nutrition and feeding behavior using realistic, data-driven assumptions. Full article

Geological modeling is generally based on deterministic models, which provide a single representation of reality. Probabilistic modeling is more appropriate when quantifying or understanding the uncertainty associated with a parameter of interest as it considers several equally probable geological scenarios. The object of this study is to quantify the uncertainty in the estimation of the minerals in the Punta Alegre gypsum deposit, by applying a new method based on the simple normal equation geostatistical simulation technique. The Punta Alegre gypsum deposit is a sedimentary deposit of clastic origin, formed by the complex redeposition of salts, gypsum and other sediments. To carry out this research, 50 equiprobable scenarios were simulated, reproducing overburden, gypsum series (different types of gypsum) and intercalated non-mineral lithologies (limestone and other rocks) in a network of nodes measuring 5 × 5 × 5 m, using a training image, composites and prior probability maps as input data. As a result of scaling the previously simulated geological units, three-dimensional models of volume proportions and estimation error for gypsum were obtained for panels measuring 10 × 10 × 5 m. The quantification of the uncertainty of the gypsum volume, determined by the root mean square error, established that the volume estimation error is small at a global scale (6.51%), given that there is no significant variation when comparing the deterministic model with the gypsum proportion model obtained from the 50 simulated scenarios. Conversely, at the local scale, there is a significant variation in gypsum volume of 42% in the 10 × 10 × 5 m panels with a future impact on recoverable mining resources, given the uncertainty at a local scale, which will cause an increase in mining dilution due to the inclusion of non-mineral lithologies within the extracted mineral that will be sent to the processing plant. On the other hand, it will cause changes in the mining company’s plan in areas where there are panels that were previously accounted for by the deterministic model as minerals and are not actually exploitable. Full article

Post-traumatic osteoarthritis (PTOA) is a distinct form of knee osteoarthritis characterized by accelerated joint degeneration following injury. It poses unique challenges in post-menopausal women due to hormonal changes and altered bone metabolism that create complex pathophysiological environments. This retrospective cohort study compared the effectiveness of different anti-osteoporotic medications in preventing total knee replacement (TKR) in 6155 postmenopausal women with PTOA treated between 2011 and 2021. We compared raloxifene and denosumab, with alendronate serving as the reference group. The primary outcome was TKR occurrence. Cox proportional hazards regression and inverse probability of treatment weighting (IPTW) were performed to estimate hazard ratios, with Kaplan–Meier survival analysis for time-to-event assessment. Participants’ mean (SD) age was 69.4 (10.0) years. Given the retrospective nature and typical delayed presentation of PTOA symptoms, cohort entry was defined as the concurrent diagnosis of PTOA and osteoporosis requiring anti-resorptive therapy. Over a mean follow-up of 5.47 years, 26 patients (0.42%) underwent TKR. Raloxifene was associated with a significantly reduced TKR risk compared to alendronate (IPTW-HR 0.81, 95% CI 0.67–0.99, p = 0.040), representing a 19% relative risk reduction. Kaplan–Meier analysis demonstrated raloxifene maintained the lowest cumulative TKR incidence compared to alendronate and denosumab over time, particularly beyond 5 years. These findings suggest that raloxifene may offer superior joint protection compared with alendronate and denosumab in postmenopausal women with PTOA, supporting its potential as a disease-modifying therapeutic option for this vulnerable population. Full article

This study presents a stochastic approach to assess bending moment demand in reinforced concrete beams subjected to vertical loads, incorporating uncertainties in material properties, geometry, and loading conditions. A Monte Carlo simulation framework was developed in Python version 3.9.3 using the OpenSeesPy library to analyze the variability of internal forces based on probabilistic input parameters. The analysis focuses on a four-span continuous beam representative of typical structural configurations in buildings. Probability distributions were assigned to key structural design parameters such as the unit weight of concrete ($\rho$), beam dimensions (b, h), column dimension (a), and applied loads, based on standard statistical assumptions and design guidelines. A total of 10,000 simulations were performed to obtain statistical descriptors of bending moment demand across the different spans. The results reveal significant variability in moment magnitudes, underscoring the importance of accounting for uncertainty in structural design. The proposed methodology enables the estimation of demand distributions and the identification of critical spans with higher sensitivity to parameter variations. Although the study does not evaluate structural capacity or failure probability, it contributes to the integration of stochastic techniques in the preliminary stages of design. Future work may include the incorporation of reliability 16 indices and comparisons with design code values. Full article

Background/Objectives: Biological therapies have emerged as targeted treatments for chronic rhinosinusitis with nasal polyps (CRSwNP), yet direct comparisons between agents remain limited. This network meta-analysis (NMA) aimed to evaluate and rank the efficacy and safety of biological therapies for CRSwNP in adult patients. Methods: We conducted a systematic review and NMA of randomized controlled trials (RCTs) assessing biological therapies for CRSwNP. A literature search was conducted through July 2025. Eligible RCTs compared approved or investigational biologics with a placebo and reported clinical, functional, or safety outcomes in adults with CRSwNP. The mean differences (MDs) in the least-squares mean change from baseline were used for continuous outcomes, and odds ratios (ORs) were used for binary outcomes. A frequentist random-effects model was used to estimate pooled effects and treatment rankings. SUCRA values and rank probabilities were derived to determine the relative efficacy and safety. Results: A total of 22 RCTs (46 reports; 4068 patients) evaluating eight biologics were included. Dupilumab consistently ranked among the top three agents across most efficacy outcomes, including nasal polyp score (NPS), nasal congestion score (NCS), SNOT-22, UPSIT, and endoscopic scores. CM310 and Tezepelumab also demonstrated strong performance in objective and symptom-based outcomes. For responder outcomes, CM310 was ranked best in minimal clinically important differences across multiple domains. PF-06817024 ranked best in minimizing any adverse events and serious adverse events. The placebo ranked worst across nearly all endpoints. Conclusions: Dupilumab, CM31 0, and Tezepelumab exhibit the most favorable efficacy profiles across multiple CRSwNP domains, while all drugs show a nearly similar safety profile. Full article

Background: Atherosclerosis is a leading cause of cardiovascular morbidity and mortality worldwide. Although lipid-derived atherogenic indices are widely used for cardiovascular risk assessment, their relationship with sociodemographic factors, lifestyle behaviors, and health-related quality of life (HRQoL) in occupational populations remains insufficiently explored. This study aimed to evaluate the association between atherogenic risk, measured by total cholesterol/high-density lipoprotein cholesterol (TC/HDL-c), low-density lipoprotein cholesterol/high-density lipoprotein cholesterol (LDL-c/HDL-c), triglyceride/high-density lipoprotein cholesterol (TG/HDL-c), and atherogenic dyslipidemia (AD) and sociodemographic, lifestyle, and HRQoL variables in a large cohort of Spanish workers. Methods: We conducted a cross-sectional analysis of 100,014 Spanish workers aged 18–69 years, of whom 39.9% were women, with a mean age of 38.2 years (SD 10.2 or IQR) and 38.9 years (SD 10.3 or IQR) for men, during the health examinations carried out between 2021 and 2024. Sociodemographic variables included sex, age group, and occupational social class. Lifestyle factors comprised smoking status, adherence to the Mediterranean diet (MEDAS score), and physical activity (IPAQ categories). HRQoL was assessed using the 12-item Short Form Survey (SF-12), stratified into good vs. poor categories. Logistic regression models were applied to estimate odds ratios (OR) and 95% confidence intervals (CI) for moderate-to-high atherogenic risk across indices, adjusting for potential confounders. Results: Men exhibited a lower likelihood of moderate-to-high TC/HDL-c and LDL-c/HDL-c but a markedly higher probability of elevated TG/HDL-c and AD compared to women (OR range: 0.42–3.67, p < 0.001). A clear age-related gradient was observed across all indices, with participants aged 60–69 showing the highest risk (OR range: 2.28–7.84, p < 0.001). Lower social class, smoking, physical inactivity, poor diet, and poor SF-12 scores were significantly associated with increased atherogenic risk, with physical inactivity (OR up to 8.61) and poor diet (OR up to 4.98) emerging as the strongest predictors. Conclusions: Atherogenic risk in this large working cohort is strongly influenced by both traditional cardiovascular risk factors and HRQoL. Integrating lifestyle modification and quality-of-life improvement strategies into workplace health programs could substantially reduce the atherogenic burden. Longitudinal research is needed to confirm these associations and guide targeted interventions. Full article

Many parametric models can be enriched by introducing additional parameters through transmutation, mixing, or compounding techniques. In this paper, we develop the framework of doubly generalized transmutation models (DGTMs), obtained by the repeated application of rank transmutation maps and their generalizations. We show that several flexible families already available in the literature can be reinterpreted as instances of double or multiple transmutation, thus unifying apparently disparate constructions under a common perspective. A key feature of DGTMs is their ability to flexibly control symmetry through parameterization, enabling more accurate modeling of asymmetric or heavy-tailed phenomena. We also discuss the potential extension of these models to the bivariate case. In addition, we introduce the gentransmuted R package, Version 1.0, which provides routines for data generation, parameter estimation, and model comparison for generalized transmutation models. Two real data applications illustrate the practical advantages of this approach, highlighting improved model fit relative to classical alternatives. Our results underscore the value of transmutation-based methods as a systematic tool for generating flexible probability distributions and advancing their computational implementation. Full article

This paper addresses the challenges of fault diagnosis in gas turbines (GTs) utilized in oil and gas pipeline systems by proposing a novel multiparameter analysis framework that integrates dynamic, quantile-based Statistical Process Control (SPC) with prior domain knowledge. The proposed approach initially employs a dynamic quantile SPC model to establish adaptive control limits, effectively handling the non-stationarity and non-normality of gas turbine operational data. By analyzing parameter variations under typical operating conditions and incorporating expert insights, a multiparameter fault analysis matrix and corresponding weighting factors are constructed to facilitate fault diagnosis with prior knowledge. Furthermore, a fault probability model based on parameter change rates and weighting factors is developed to quantify the likelihood of different fault modes. An operating condition clustering and correction mechanism enables the dynamic adjustment of control limits, thereby preventing misdiagnoses caused by varying operational states. The validity of the proposed method is demonstrated using real data from a domestic pipeline gas turbine, validated by real domestic pipeline GT data, outperforming existing models, with a fault accuracy up to 10%. The approach efficiently estimates fault probabilities and accurately detects both sudden and gradual faults, significantly enhancing intelligent fault diagnosis capabilities for gas turbines. Full article

The Blue Schools initiative integrates the ocean into classroom learning through project-based approaches, cultivating environmental awareness and a deeper sense of responsibility toward marine ecosystems and human–ocean interactions. Although the European Blue School initiative has grown steadily since its launch in 2020, its uneven uptake raises important questions about the territorial factors that influence certification. This study examines the spatial determinants of Blue School certification in Mallorca, Spain, where a bottom-up pilot initiative successfully certified 100 schools. Using Maximum Entropy (MaxEnt) modeling, we estimated the spatial probability of certification based on 16 geospatial variables, including proximity to Blue Economy actors, hydrological networks, transport accessibility, and socio-economic indicators. The model achieved strong predictive performance (AUC = 0.84) and revealed that features such as freshwater ecosystems, traditional economic structures, and sustainable public transport play a greater role in school engagement than coastal proximity alone. The resulting suitability map identifies over 30 high-potential, non-certified schools, offering actionable insights for targeted outreach and educational policy. This research highlights the potential of presence-only modeling to guide the strategic expansion of Blue Schools networks. Full article