Search Results (146)

In many fields, including engineering, biology and economics, modeling and analyzing lifetime data is crucial for understanding the reliability and survival characteristics of systems and components. To address the limitations of existing lifetime distributions in capturing complex hazard rate behaviors, this article introduces a new and flexible two-parameter distribution, the power length-biased XLindley (PLXL) distribution. This distribution extends the XLindley distribution family by incorporating a power transformation applied to a length-biased variant, thereby enriching its structural flexibility. It can model a variety of hazard rate shapes, including increasing, decreasing, decreasing–increasing–decreasing and inverted bathtub forms, making it suitable for a range of real-world applications. We derive the statistical properties of the PLXL distribution and develop parameter estimation methods based on the maximum likelihood and the least squares approach. We conduct a comprehensive simulation study to evaluate the performance of the proposed estimators in terms of bias and mean squared error. The practical utility and superior adaptability of the PLXL distribution are demonstrated by applying it to real lifetime data sets. Full article

Proteins play an important role in living organisms, and, for most of them, the function depends on their structure. There are some proteins that have similar properties but different structures. An example of this is ice-binding proteins (IBPs), which have different structures but share the ability to bind to ice. Many organisms have evolved such proteins to help them survive in cold environments. Therefore, it is important to study the oligomeric state of the active form in solutions. The activity of IBP is related to the area of their ice-binding site. We have demonstrated the presence of oligomeric forms of protein in solution using multiple techniques, such as mass spectrometry, native gel electrophoresis, atomic force microscopy (AFM), isothermal titration calorimetry (ITC) and small-angle X-ray scattering (SAXS). It is noteworthy that, to date, there have been no reports of the oligomerization of ice-binding protein from Longhorn sculpin. Additionally, our findings suggest that larger molecules may influence the ability of proteins to bind to ice. In our study, the ice-binding protein forms elongated assemblies with limited intermonomer interfaces. The combination of SAXS and AFM data indicates a structure that combines compactness and flexibility and probably consists of four monomeric units. The employment of molecular modelling methodologies resulted in the attainment of a tetrameric complex that is in alignment with AFM data. Details of oligomers observed using the methods in our study emphasize the importance of different techniques that complement each other in resolving structural features. Additionally, we suggest that the protein particles, which were dispersed on the surface, exhibit softness or the form planar complexes with loose quaternary structures. It is conceivable that, depending on ionic strength and/or temperature, the various oligomeric forms of the ice-binding protein form thermodynamically more favorable complexes than their monomeric forms. Full article

This paper introduces the Marshall–Olkin unit-exponentiated-half-logistic (MO-UEHL) distribution, a novel three-parameter model designed to enhance the flexibility of the unit-exponentiated-half-logistic distribution through the incorporation of the Marshall–Olkin transformation. Defined on the unit interval $(0,1)$, the MO-UEHL distribution is well-suited for modeling proportional data exhibiting asymmetry. The Marshall–Olkin tilt parameter $\alpha$ explicitly controls the degree and direction of asymmetry, enabling the density to range from highly right-skewed to nearly symmetric unimodal forms, and even to left-skewed configurations for certain parameter values, thereby offering a direct mathematical representation of symmetry breaking in bounded proportional data. The resulting model achieves this versatility without relying on exponential terms or special functions, thus simplifying computational procedures. We derive its key mathematical properties, including the probability density function, cumulative distribution function, survival function, hazard rate function, quantile function, moments, and information-theoretic measures such as the Shannon and residual entropy. Parameter estimation is explored using maximum likelihood, maximum product spacing, ordinary and weighted least-squares, and Cramér–von Mises methods, with simulation studies evaluating their performance across varying sample sizes and parameter sets. The practical utility of the MO-UEHL distribution is demonstrated through applications to four real datasets from environmental and engineering contexts. The results highlight the MO-UEHL distribution’s potential as a valuable tool in reliability analysis, environmental modeling, and related fields. Full article

Competing risks modeling plays a pivotal role in both reliability analysis for scientific and engineering fields and survival analysis within medical research. In real-world scenarios, failure or death (from a biological perspective) often arises from multiple risk factors that compete with one another. To adequately capture these complexities, it is essential to employ a flexible probabilistic framework, such as the competing risks model, which ensures suitability for intricate risk scenarios (e.g., analyzing data from aggressive diseases where treatment response and disease progression are closely interwoven). This study introduces Stacy’s competing risks model, built upon Stacy’s generalized gamma distribution, offering enhanced robustness and flexibility over existing models. The paper first develops the mathematical properties of the proposed model, followed by a detailed exploration of parameter estimation through various estimation methods. A key focus is accurately estimating shape parameters to gain deeper insights into the survival and failure mechanisms associated with the underlying phenomenon. The performance of different estimation approaches is assessed using Monte Carlo simulations, with results indicating that the least square, Cramér–von Mises, Anderson–Darling, right Anderson–Darling, and weighted least square had better performance and stable estimation accuracy compared with maximum likelihood maximum product of spacings methods. The model is applied to two real-world blood cancer datasets to demonstrate practical applicability, showing the superior performance and outstanding fit of the Anderson–Darling method among the other methods. The findings highlight the superior performance of Stacy’s competing risks model, supported by low Kolmogorov–Smirnov statistics and high p-values, affirming its suitability and robustness in modeling blood cancer data compared to other standard models. Full article

Background: Tooth autotransplantation represents a biologically favourable treatment option for replacing missing or non-restorable teeth in paediatric patients. However, its long-term prognosis and variability in reported success rates warrant a high-quality synthesis of the available evidence. Methods: A systematic review was conducted following the PRISMA 2020 guidelines. A comprehensive search of PubMed, Scopus, Web of Science, and Cochrane CENTRAL was performed up to May 2024 for clinical studies on autotransplantation of immature permanent teeth in patients under 18 years. Study selection, data extraction, and risk-of-bias assessment (using ROBINS-I and JBI tools) were performed independently by two reviewers. Aggregated success and survival proportions with 95% confidence intervals were calculated through descriptive quantitative synthesis. Results: Three retrospective studies, comprising 404 transplanted teeth, were included in the analysis. The aggregated success proportion was 85.4% (95% CI: 74.4–92.1%), and the aggregated survival proportion was 94.2% (95% CI: 85.0–97.9%), with a mean follow-up ranging from 12 to 168 months. A key finding was that all included studies consistently reported the use of immature donor teeth (¹/₂–³/₄ root formation) and short-term flexible splinting, which appears to be a critical factor for these successful outcomes. Conclusions: Autotransplantation of developing teeth in paediatric patients demonstrates high survival (≈94%) and favourable success (≈85%), with minimal inter-study variability. When performed with immature donor roots and short-term flexible splinting, the procedure provides a predictable biological alternative to prosthetic or implant rehabilitation in growing individuals. However, the limited number of eligible studies highlights the need for future multicentre prospective research to standardise protocols and confirm long-term outcomes in paediatric populations. Full article

This paper introduces the UG-EM (Unconditional Gamma-Exponential Model) as a new compound lifetime model designed to enhance flexibility in tail behavior compared to traditional distributions. The UG-EM model provides a unified framework for analyzing deviations from symmetry in survival data, effectively capturing right-skewed patterns, which are commonly observed in real-world lifetime phenomena. The main analytical properties are derived, including the probability density, cumulative distribution, hazard and reversed-hazard functions, mean residual life, and several measures of dispersion and uncertainty. The effects of the UG-EM parameters (α and λ) are examined, showing that increasing either parameter can cause a temporary reduction in entropy H(T) at early times followed by a long-term increase; in some cases, the influence of α is stronger than that of λ. Parameter estimation is carried out using the maximum likelihood method and assessed through Monte Carlo simulations to evaluate estimator bias and variability, highlighting the significant role of sample size in estimation accuracy. The proposed model is applied to three survival datasets (Lung, Veteran, and Kidney) and compared with classical alternatives such as Exponential, Weibull, and Log-normal distributions using standard goodness-of-fit criteria. Results indicate that the UG-EM model offers superior flexibility and can capture patterns that simpler models fail to represent, although the empirical results do not demonstrate a clear, consistent superiority over standard competitors across all tested datasets. The paper also discusses identifiability issues, estimation challenges, and practical implications for reliability and medical survival analysis. Recommendations for further theoretical development and broader model comparison are provided. Full article

Background: Sarcopenia assessment provides significant prognostic information that outperforms body mass index and will help to guide interventions to optimize survival outcomes in cancer patients. Computed tomography (CT) is an opportunistic tool used for the assessment of low muscle mass criteria of sarcopenia in cancer patients, while nutritional ultrasound (NU) cutoff points for sarcopenia have been recently proposed. The objective of the present review is to evaluate if NU has a comparable accuracy as CT for the assessment of sarcopenia in cancer patients and could be useful in clinical setting. Methods: Systematic review was registered in Open Science Framework. PubMed and Scopus databases were searched in May and updated in August 2025. All published studies in which patients were evaluated using only one of the previously mentioned modalities, or those involving subjects with non–cancer-related pathologies, were excluded. Two reviewers independently evaluated the risk of bias of selected studies with the National Institutes of Health (NIH) Quality Assessment Tools, and results are presented following the PRISMA 2020 model for systematic reviews. Results: Six studies comprising a total of 1011 patients (57.27% male) were evaluated. Accuracy, variability, and agreement between NU and CT are presented. Conclusions: Main limitations of the evidence include the heterogeneity among studies and their risk of bias. Nevertheless, NU can be a useful tool for sarcopenia diagnosis and can provide a closer and a more flexible follow-up in cancer patients than CT. Full article

The present study aims to conduct a comprehensive comparative analysis of international standards (DNV, ABS, BV, etc.) that regulate the design of mooring systems for floating offshore wind turbines. The comparative analysis focuses on the safety factors applied to the line tension of mooring systems. Firstly, an extensive literature review of the most-used floating platforms in the offshore wind industry and their corresponding mooring configurations is presented. Afterwards, a case study is presented using the VolturnUS floating substructure as a reference for analyzing the coupled dynamic response of mooring analysis through OrcaFlex 11.4, where the numerical model used for the coupled dynamic response of moorings is validated by benchmarking against the OC3 Hywind platform model. Within the scope of the comparative analysis, all-chain and semi-taut hybrid systems under various operational and survival load conditions are considered. The results demonstrate the similarities and discrepancies in line tension utilization among the standards, highlighting the comparative conservatism in different environmental conditions. Furthermore, the study underscores the need for tailored safety factors in mooring designs, given the variability in assessment methods across design guidelines, thereby making the design more flexible and encouraging innovative mooring system solutions. Full article

This paper proposes a novel statistical test for evaluating exponentiality against the recently introduced EBUCL (Exponential Better than Used in Convex Laplace transform order) class of life distributions. The EBUCL class generalizes classical aging concepts and provides a flexible framework for modeling various non-exponential aging behaviors. The test is constructed using Laplace transform ordering and is shown to be effective in distinguishing exponential distributions from EBUCL alternatives. We derive the test statistic, establish its asymptotic properties, and assess its performance using Pitman’s asymptotic efficiency under standard alternatives, including Weibull, Makeham, and linear failure rate distributions. Critical values are obtained through extensive Monte Carlo simulations, and the power of the proposed test is evaluated and compared with existing methods. Furthermore, the test is extended to handle right-censored data, demonstrating its robustness and practical applicability. The effectiveness of the procedure is illustrated through several real-world datasets involving both censored and uncensored observations. The results confirm that the proposed test is a powerful and versatile tool for reliability and survival analysis. Full article

The analysis of lifetime data under censoring schemes plays a vital role in reliability studies and survival analysis, where complete information is often difficult to obtain. This work focuses on the estimation of the parameters of the recently proposed generalized Kavya–Manoharan exponential (GKME) distribution under progressive Type-I interval censoring, a censoring scheme that frequently arises in medical and industrial life-testing experiments. Estimation procedures are developed under both classical and Bayesian paradigms, providing a comprehensive framework for inference. In the Bayesian setting, parameter estimation is carried out using Markov Chain Monte Carlo (MCMC) techniques under two distinct loss functions: the squared error loss function (SELF) and the general entropy loss function (GELF). For interval estimation, asymptotic confidence intervals as well as highest posterior density (HPD) credible intervals are constructed. The performance of the proposed estimators is systematically evaluated through a Monte Carlo simulation study in terms of mean squared error (MSE) and the average lengths of the interval estimates. The practical usefulness of the developed methodology is further demonstrated through the analysis of a real dataset on survival times of guinea pigs exposed to virulent tubercle bacilli. The findings indicate that the proposed methods provide flexible and efficient tools for analyzing progressively interval-censored lifetime data. Full article

Clustered time-to-event data are quite common in survival analysis and finding a suitable model to account for dispersion as well as censoring is an important issue. In this article, we present a flexible model for repeated, overdispersed time-to-event data with right-censoring. We present here a general model by incorporating generalized gamma and normal random effects in a Weibull distribution to accommodate overdispersion and data hierarchies, respectively. The normal random effect has the property of being symmetrical, which means its probability density function is symmetric around its mean. While the random effects are symmetrically distributed, the resulting frailty model is asymmetric in its survival function because the random effects enter the model multiplicatively via the hazard function, and the exponentiation of a symmetric normal variable leads to lognormal distribution, which is right-skewed. Due to the intractable integrals involved in the likelihood function and its derivatives, the Monte Carlo approach is used to approximate the involved integrals. The maximum likelihood estimates of the parameters in the model are then numerically determined. An extensive simulation study is then conducted to evaluate the performance of the proposed model and the method of inference developed here. Finally, the usefulness of the model is demonstrated by analyzing a data on recurrent asthma attacks in children and a recurrent bladder data set known in the survival analysis literature. Full article

Background: Enterotoxigenic Escherichia coli (ETEC) is a zoonotic pathogen causing diarrhea and mortality in infants and livestock. Its numerous serotypes necessitate the urgent development of multivalent vaccines for effective prevention, thereby reducing public health and economic threats. Methods: Computational bioinformatics analyses were conducted on five major ETEC adhesins structural subunits (FaeG, FanC, FasA, FimF41a, and FedF). Dominant epitopes were selected and concatenated via flexible linkers, incorporating the PADRE sequence and LTb adjuvant to design a multi-epitope fusion antigen (MEFA). The recombinant MEFA protein was expressed in a prokaryotic system. Furthermore, molecular dynamics simulations, docking, and immune simulations assessed structural stability and immunogenicity. Immunoreactivity was tested by Western blot. Murine immunization evaluated antibody responses, lymphocyte proliferation, cytokine secretion, and protection against ETEC challenge. Results: Structural modeling showed an extended conformation, with docking and simulations indicating strong immune activation. Western blot confirmed MEFA immunoreactivity. MEFA induced high antigen-specific antibody titers, enhanced splenocyte proliferation, and increased IFN-γ and IL-4 secretion, indicating a Th2-biased response in mice. Vaccinated mice survived lethal ETEC challenge and maintained intestinal integrity. Conclusions: The MEFA candidate vaccine effectively induces robust humoral and cellular immune responses and provides protection against ETEC infection, representing a promising strategy for next-generation multivalent ETEC vaccines. Full article

Hakka traditional vernacular dwellings embody regionally specific climatic adaptation strategies. This study takes the Meizhou Guangludi enclosed house as a case study to evaluate its climate adaptability with longevity and passive survivability factors of the Hakka three-hall enclosed house under subtropical climatic conditions. A mixed research method is employed, integrating visualized parametric modeling analysis and on-site measurement comparisons to quantify wind, temperature, solar radiation/illuminance, and humidity, along with human comfort zone limits and building environment. The results reveal that nature erosion in the Guangludi enclosed house is the most pronounced during winter and spring, particularly on exterior walls below 2.8 m. Key issues include bulging, spalling, molding, and fractured purlins caused by wind-driven rain, exacerbated by low wind speeds and limited solar exposure, especially at test spots like the E8–E10 and N1–N16 southeast and southern walls below 1.5 m. Fungal growth and plant intrusion are severe where surrounding trees and fengshui forests restrict wind flow and lighting. In terms of passive survivability, the Guangludi enclosed house has strong thermal insulation and buffering, aided by the Huatai mound; however, humidity and day illuminance deficiencies persist in the interstitial spaces between lateral rooms and the central hall. To address these issues, this study proposes strategies such as adding ventilation shafts and flexible partitions, optimizing patio dimensions and window-to-wall ratios, retaining the spatial layout and Fengshui pond to enhance wind airflow, and reinforcing the identified easily eroded spots with waterproofing, antimicrobial coatings, and extended eaves. Through parametric simulation and empirical validation, this study presents a climate-responsive retrofit framework that supports the sustainability and conservation of the subtropical Hakka enclosed house. Full article

Background: Protective gear is a critical part of the police officer uniform. The required protective gear weighs over 9 kg and is rigid and bulky, creating deficits in physical performance essential for completing officer’s daily tasks and increasing risk of injury. Understanding the impedance the protective gear causes and how physical factors such as body composition increase this effect is critical to the safety and survival of the police officer. The purpose of this study was to evaluate the impact of protective gear on officer capabilities. Methods: Officers completed an 11-point assessment in two conditions: athletic attire (No Gear) and uniform + protective equipment (Gear). Results: Differences in power output (p < 0.001; p = 0.118), balance (p < 0.001; p = 0.771), functional movement (p = 0.002; p = 0.018), and flexibility (p < 0.001) were found between the two conditions. Conclusions: Decreased on-duty performance can affect officer safety and success. These results indicate the need for continued improvement of police officer safety equipment to ensure mobility and safety. Full article

The Maxwell–Boltzmann (MB) distribution is fundamental in statistical physics, providing an exact description of particle speed or energy distributions. In this study, a discrete formulation derived via the survival function discretization technique extends the MB model’s theoretical strengths to realistically handle lifetime and reliability data recorded in integer form, enabling accurate modeling under inherently discrete or censored observation schemes. The proposed discrete MB (DMB) model preserves the continuous MB’s flexibility in capturing diverse hazard rate shapes, while directly addressing the discrete and often censored nature of real-world lifetime and reliability data. Its formulation accommodates right-skewed, left-skewed, and symmetric probability mass functions with an inherently increasing hazard rate, enabling robust modeling of negatively skewed and monotonic-failure processes where competing discrete models underperform. We establish a comprehensive suite of distributional properties, including closed-form expressions for the probability mass, cumulative distribution, hazard functions, quantiles, raw moments, dispersion indices, and order statistics. For parameter estimation under Type-II censoring, we develop maximum likelihood, Bayesian, and bootstrap-based approaches and propose six distinct interval estimation methods encompassing frequentist, resampling, and Bayesian paradigms. Extensive Monte Carlo simulations systematically compare estimator performance across varying sample sizes, censoring levels, and prior structures, revealing the superiority of Bayesian–MCMC estimators with highest posterior density intervals in small- to moderate-sample regimes. Two genuine datasets—spanning engineering reliability and clinical survival contexts—demonstrate the DMB model’s superior goodness-of-fit and predictive accuracy over eleven competing discrete lifetime models. Full article