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This study investigates the impact of carding and blending recycled carbon fibers (rCF) with crimped thermoplastic polypropylene (PP) fibers on the mechanical properties of rCF, using a Weibull statistical approach. Tensile properties of rCF were evaluated before and after carding with varying rCF/PP blend ratios (100/0%, 85/15%, 70/30%, and 50/50%). A comparison between the two-parameter and three-parameter Weibull models showed that the two-parameter model provided a better fit for rCF properties before carding. The results show that adding crimped PP fibers during carding helps to decrease the stress-at-break disparity and move their distribution to higher values. Furthermore, a slight increase in tensile modulus was observed in carded rCF, with higher PP ratios associated with smaller scatter modulus distributions. Elongation at break remained consistent, with the Weibull modulus increasing slightly with carding and the inclusion of PP fibers, indicating improved consistency. Overall, carding rCF with PP fibers helped in the mechanical property uniformity of the resulting carded webs without compromising tensile performance. This work shows the potential of the carding process with or without thermoplastic fibers to efficiently realign and give continuity to discontinuous recycled carbon fibers. [ABSTRACT FROM AUTHOR]

The present paper tackles the important issue of tensile ultimate strength of ceramic matrix composites, using a multiscale approach. The ultimate strength is investigated at the successive increasing length scales inherent to 2D woven SiC/SiC composites, i.e., single filaments, fibre tow, unidirectional composite (minicomposites), and 2D woven composite. First, experimental results on tensile behavior under strain-controlled conditions are summarized for tows, minicomposites, and composites. Then, models of tow ultimate failures under controlled force and strain are presented. The exact criterion of tow failure is developed for filament fracture initiation and then propagation based on applied stress and on filament strength gradient. The model of the ultimate failure of the composite under strain-controlled conditions is based on the strength of filaments in the presence of matrix cracks and the overstress induced by interactions of broken filaments and the matrix. The variability of ultimate strengths of filaments, minicomposites, and composites at various gauge lengths is described by linear p-quantile diagrams, which indicates that the data follow a normal distribution function. The contribution of structural effects to the variability of composite and minicomposite strength under strain-controlled loading is analyzed. Their dependence on specimen size is related to the reproducibility of critical flaw population and structural effects. [ABSTRACT FROM AUTHOR]

The step‐stress procedure is a popular accelerated test used to analyze the lifetime of highly reliable components. This paper considers a simple step‐stress accelerated test assuming a cumulative exposure model with uncensored lifetime data following a Weibull distribution. The maximum likelihood approach is often used to analyze accelerated stress test data. Another approach is to use the Bayesian inference, which is useful when there is limited data available. In this paper, the parameters of the model are estimated based on the objective Bayesian viewpoint using non‐informative priors. Our main aim is to propose the maximal data information prior (MDIP) presented by Zellner (1984) as an alternative prior to the conventional independent gamma priors for the unknown parameters, in situations where there is little or no a priori knowledge about the parameters. We also obtain the Bayes estimators based on both classes of priors, assuming three different loss functions: square error loss function (SELF), linear‐exponential loss function (LINEX), and generalized entropy loss function (GELF). The proposed MDIP prior is compared with the gamma priors via Monte Carlo simulations by examining their biases and mean square errors under the three loss functions, and coverage probability. Additionally, we employ the Markov Chain Monte Carlo (MCMC) algorithm to extract characteristics of marginal posterior distributions, such as the Bayes estimator and credible intervals. Finally, a real lifetime data is presented to illustrate the proposed methodology. [ABSTRACT FROM AUTHOR]

Flight data for deep space satellites launched and operated between 1991 and 2020 is analyzed to generate various reliability metrics. Satellite reliability is first estimated by the Kaplan‐Meier estimator, then parameterized through the Weibull distribution. This general process is applied to a general satellite data set that included all deep space satellites launched between 1991 and 2020, as well as two data subsets. One subset focuses on deployable satellites, while the other introduces a methodology of normalizing satellite lifetimes by satellite design life. Results from the general data set prove deep space satellites suffer from infant mortality while the results from the deployable data subset show deployable deep space satellites are only reliable over short periods of time. Results from the design life normalized data set give promising results, with satellites having a relatively high chance of reaching their design life. Available information regarding specific modes of failure is also leveraged to generate a percent contribution to overall satellite failure for eight distinct failure modes. Satellite failure due to crashing, in‐space propulsion failure, and telemetry system failure are proven to drive both early in life failure and later in life failure, making them the main causes of decreased reliability. [ABSTRACT FROM AUTHOR]

Drug products meeting the dissolution specifications is crucial in order to ensure consistent clinical performance. However, in certain cases, wider dissolution specifications may be required based on product behaviour. While the justification of such wider specifications may be challenging from a regulatory context, approaches such as physiological-based biopharmaceutics modeling (PBBM) can be utilised for this purpose. Product DRL is a fixed-dose combination product consisting of immediate release (IR) and extended-release (ER) portions. For the ER portion, the dissolution specifications consisted of four time points, and a proposal was made to relax the specification at the 2h time point (from 50–70% to 45–67%) to reduce the batch failures at the commercial scale. To support the wider specification, a PBBM was developed and extensively validated with literature & in-house studies. Virtual bioequivalence was performed using the pivotal clinical study data. Virtual dissolution profiles for proposed wider specifications were generated using three different approaches. The incorporation of lower and upper dissolution profiles into the model indicated the absence of impact on in vivo performance thereby justifying the specifications. Regulatory acceptance of proposed specifications with PBBM indicated the significance of using modeling approaches to reduce repeated testing thereby facilitating faster approvals. [ABSTRACT FROM AUTHOR]

In this paper, we introduce an innovative Software Reliability Growth Model (SRGM) designed to tackle the pivotal challenges associated with software reliability in the contemporary digital landscape, where the prevalence of online systems is ubiquitous. This SRGM integrates Imperfect Debugging (ID), Testing Coverage (TC), Testing Effort (TE), and error generation into a cohesive framework. Employing a sigmoid function to encapsulate TE, it incorporates three distinct TC functions: Delayed S-shaped, Exponential, and Logistic. This model relies on foundational assumptions, including the proportionality of fault detection rates to remaining faults, the introduction of new faults during debugging, and the intricate connection between fault detection and code coverage. The Mean Value Function (MVF) is computed through these differential equations, and the resultant MVFs are systematically tabulated for all models. An examination of the sigmoid TE function and the Weibull TE function across diverse datasets, utilizing a range of goodness-of-fit criteria including Mean Square Error (MSE), Pham's Criterion (PC), Predictive Risk Ratio (PRR), Bayesian Information Criterion (BIC), and Akaike's Information Criterion (AIC), reveals the superior performance of the sigmoid TE function over the Weibull counterpart across various datasets and evaluation criteria. In conclusion, this paper introduces a groundbreaking SRGM that seamlessly integrates ID, TC, and TE, offering valuable insights for assessing software reliability in the dynamic landscape of modern digital systems. [ABSTRACT FROM AUTHOR]

Gasification is a technology that optimistically utilizes biomass to produce syngas (consisting of H2, CO, CO2, CH4) that can be used as an energy source while reducing excess CO2 emissions. However, if there are frequent failures due to unplanned maintenance activities, the engine performance will not be optimal. Therefore, an up-to-date reliability study is needed as a basis for updating preventive maintenance activities to maintain the quality of the engine so that it continues to operate properly and is durable. This research aims to analyze the reliability, unreliability, and availability of the Mobile Biomass Gasifier (Prototype3), as well as study the failure patterns measured using the shape parameter (ß) with the Weibull distribution. The focus of this research is on the Suction blower which based on Pareto results is the equipment with the highest failure frequency. The results show that the average reliability is smaller than the failure rate. In addition, the value of the shape parameter (ß) > 1, which means that the damage rate increases as the component ages. The implication of this study shows the need to update the preventive maintenance (PM) schedule by considering the addition of new PM activities that are in accordance with the duration of the life of the components that cause machine damage. [ABSTRACT FROM AUTHOR]

This study investigated the mechanical behavior of silicon carbide fiber-reinforced silicon carbide matrix (SiC f /SiC) cladding using expanding plug tests at 0.5 and 2 mm/min. A three-stage mechanical response for SiC f /SiC was observed, with significant differences in Stage 3 between specimens tested at different rates. Specimens tested at the slower rate (0.5 mm/min) exhibited a characteristic hoop strength of 112.4 MPa and homogeneous destruction behavior, indicative of uniform stress distribution. In contrast, the hoop stress in SiC f /SiC became unsteady at the faster rate (2 mm/min), leading to cracking at a lower nominal proportional limit stress (PLS), structural instability, non-uniform fiber pull-out, and a lower characteristic hoop strength of 92.4 MPa. This suggests that similar phenomena might occur at higher loading rates during internal pressure shock. Therefore, considering the application of SiC f /SiC, to conduct hoop strength testing at faster rates was recommend, such as 2 mm/min. [ABSTRACT FROM AUTHOR]

Fiber Reinforced Polymer (FRP) composites are known for their exceptional resistance to harsh conditions, impressive durability, and high tensile strength, making them increasingly popular in structural applications. However, the inherent variability of composite materials poses a critical challenge, particularly in tensile strength, which directly impacts the safety and durability of structures. This study evaluated the tensile strength of 395 specimens, including 103 carbon fiber-reinforced polymer (CFRP) rods and 293 hybrid glass-carbon FRP (HFRP) rods, tested according to the GB 30022–2013 standard. To analyze the data, four statistical distributions—normal, lognormal, Weibull, and Gamma—were applied, and a goodness-of-fit test identified the Weibull distribution as the most suitable model. The study further proposed standardized tensile strength values of 2,912.40 MPa for 5 mm CFRP rods and 2,230.98 MPa, 2,385.12 MPa, and 2,517.44 MPa for 6, 7, and 8 mm HFRP rods, respectively. These findings provide valuable insights into the tensile performance of FRP rods, contributing to enhanced design and safety standards for FRP-based structural elements and offering practical references for mitigating material variability in construction applications.

Wind energy production is rapidly expanding worldwide, yet studies on wind energy potential in India remain limited. This study evaluates the wind power potential and conducts an economic cost analysis of wind turbine generator installations at varying hub heights (10m to 150 m) across 21 locations in India, representing a novel contribution to the field. The selected locations include 11 sites in Gujarat (Location-1), 10 sites in Tamil Nadu (Location-2), and one site in Ravangla, Sikkim (Location-3). Cubic factors methods are implemented to estimate Weibull parameters. Results reveal that at 150 m hub height, wind power density ranges from 123.17 to 308.86 W/m² in Gujarat, 80.64 to 427.12 W/m² in Tamil Nadu, and 183.24 W/m² in Sikkim. Kaluneerkulam in Tamil Nadu demonstrates excellent wind category potential, with energy costs ranging from $0.0165 to $0.0076 per kWh, decreasing as hub height increases. Sites across all three locations exhibit moderate to steady wind speeds, making them suitable for wind energy exploitation. An economic analysis of nine wind turbine types shows that Tamil Nadu achieves the lowest energy cost variation, followed by Gujarat and Sikkim. This study provides valuable insights for optimizing wind energy utilization in India.

This year is the 50th anniversary of Besag's classic auto‐models publication, a cornerstone in the development of modern‐day spatial statistics/econometrics. Besag struggled for nearly two decades to make his conceptualization collectively successful across a wide suite of random variables. But only his auto‐normal, and to a lesser degree his auto‐logistic/binomial, were workable. Others, like his auto‐Poisson, were effectively failures, whereas still others, such as potentials like an auto‐Weibull, defied even awkward mathematical incorporations of spatial lag terms. Besag circumvented this impediment by introducing an auto‐normal random effects components (within a Bayesian estimation context), building upon his single total success. This article describes an alternative approach, partly paralleling his reformulation while avoiding inserting spatial lag terms directly into probability density/mass functions, implanting spatial autocorrelation into cumulative distributions functions (CDFs), instead, via a spatially autocorrelated uniform distribution. The already existing probability integral transform and quantile function mathematical statistics theorems enable this mechanism to spatialize any random variable, with these new ones labeled sui‐models. [ABSTRACT FROM AUTHOR]

Tree size is one of the major factors that determines harvester productivity and is heavily influenced by forest managerial activities. Stand silvicultural management can lead to managing tree size, the distribution of tree size, and tree height amongst others. Understanding the effect of tree size distribution on harvesting productivity is central for optimizing management of operations. To investigate the effects of tree size distribution on harvester productivity, productivity functions for a medium and larger-sized harvester were applied to harvester derived tree size distributions from 35 clearfelled pine stands. These functions were applied to a normal distribution of trees covering the same tree size ranges. Productivity differences were analysed on a stand-by-stand basis. Results showed that for the larger harvester, productivity rates remained constant (67.1 vs. 67.6 m3·PMH− 1) indicating relatively little sensitivity to variations in tree size distributions. Although the standard deviation (SD) halved from 11.6 to 5.6 in the case of the uniform tree distribution. The smaller harvester productivity decreased by 15% from 47.3 to 40.1 m3·PMH− 1 and the coefficient of variation (CV) by 6% in the same transition to a uniform distribution. Further investigation was done on more skewed tree size distributions, a family of nine Weibull distributions was generated, representing combinations of three mean DBH classes (25 cm, 30 cm, and 35 cm) and three levels of CV (15%, 20%, 25%), for each DBH class. Results clearly indicate that different distribution shapes have different effects on different machine sizes, and that a low CV correlates to a higher productivity in larger tree sizes. A more uniform tree size distribution also provides more predictable results (lower CV), which would promote machine scheduling and result in fewer discrepancies on production rates. [ABSTRACT FROM AUTHOR]

For a proposed multi-source all-renewable microgrid in Nigeria's Middlebelt region, this paper presents a multi-temporal approach to the investigation of the uncertainty in the potential of renewable energy resources. The wind, solar, and hydropower resources for a proposed multisource all-renewable off-grid community microgrid are considered using an array of probabilistic techniques. The peculiar variances in the location's climate throughout the year make the more common method of annual models of renewable resources unsuitable for power system planning. Consequently, a more granular model of its renewable resources over time is needed. Therefore, for the chosen location, for each renewable resource, a composite multitemporal maximum-likelihood estimation-based (MLE) probabilistic model for characterization is developed. A total of 39 probabilistic models are developed. Up to 40% improvement in the accuracy of the statistical measures for renewable resource uncertainty was observed. Multi-temporal approach provides more accurate information for power system planning over time than the conventional approach of single aggregate models, especially for hydropower, which is strongly affected by the relatively sporadic occurrence of rainfall. The study shows that solar energy is promising, hydropower potential is seasonal and complementary, and wind potential is low at the location considered in this study. [ABSTRACT FROM AUTHOR]

To enhance the impact resistance of high-performance concrete (HPC), a novel efficient solution was adopted by incorporating basalt fibers (BF) and polypropylene fibers (PF) as reinforcement materials in this work. To this end, the effects of single BF (BHC) and PF (PHC) as well as their combinations (BPHPC) on the impact energy consumption, ductility ratio, and toughness factor were explored through drop weight impact test of concrete considering fiber volume contents (0.1%, 0.15%, 0.2%) to evaluate the impact resistance of the concrete. The Weibull distribution function model is used to fit the drop weight impact test results and predict the probability of failure. Moreover, the fracture-resistance enhancement mechanism of fiber is analyzed at a microscopic level. Test results showed that the number of impacts resisted by the HPC can follow well the two-parameter Weibull distribution. Compared with the single BF and single PF, the combination of 0.15% BF and 0.1% PF yields favorable impact resistance, thus exhibiting a positive hybrid effect. [ABSTRACT FROM AUTHOR]

Background and Objectives: Accurately estimating tree height is crucial for assessing forest stand volume and above-ground biomass. Nonlinear mixed-effects models, incorporating random effects to address variation between plots while preserving the diameter-height relationship, enhance model precision by accounting for both intergroup and intragroup variation. Consequently, this study aimed to develope a Height-Diameter relationship for Oak (Quercus Castanefolia C.A.M) using nonlinear models and nonlinear mixed-effect models within uneven-aged broadleaved stands situated in Golestan province, specifically within the Shast-kalateh, Jafar-abad, and Loveh forestry areas. Materials and Methods: We employed a systematic sampling approach to collect field data across a 150×200 m grid (comprising 71 circular plots), where we recorded tree species, height, and diameter at breast height (DBH) for all trees in each plot. Initially, we scrutinized 20 non-linear diameter-height models to identify candidate models. Subsequently, in the second stage, these models were refined using a mixed-effect model incorporating dominant height, mean quadratic DBH, basal area, BAL, stand volume, and tree density as covariates. Results: The results of fitting non-linear models for Oak indicated that RMSE and R² ranged between 15-17% (3-4 meters) and 0.4-0.62, respectively. Integrating dominant height, mean quadratic DBH, basal area, BAL, stand volume, and tree density as random effects in the nonlinear mixed-effect model enhanced R² by approximately 10 to 16%, while reducing RMSE by about 2-3% (0.2-1 m). Conclusion: The study demonstrated that employing the nonlinear mixed- effect method, as opposed to traditional nonlinear regression models, enhanced the accuracy of height estimation, particularly within uneven-aged broadleaved stands. These models effectively capture height variability within stands, presenting a viable alternative for height estimation despite limited prior research in this domain. Further investigations into employing nonlinear mixed-effect models for key species in the Hyrcanian forests and other vegetation regions of Iran are mperative. The precise insights derived can inform sustainable forest management and conservation strategies, with potential applications in forest planning endeavors. [ABSTRACT FROM AUTHOR]

Dialysis machines operate in an uncertain environment with several sources of disturbances; therefore, it is necessary to take account of the uncertainties during all their life phases. This paper presents a study of the random reliability of the dialysis machine in a stochastic environment through the two-parameter for Weibull distribution. The shape and scale parameters were estimated through analytical and graphical methods based on the failure history of the devices. The formulation of the analytical methods and their exploitation using numerical simulations was one of the objectives of this work. The uncertainties in the stochastic environment of the machines are related to variability in physical and geometric parameters, fluctuations in load conditions, stress boundary conditions, and also to physical laws and simplifying assumptions used in the modeling process. The Weibull parameters introduced these uncertainties, and their effect on the device's reliability was studied. The main contribution is the study of the effect of the uncertainties in Weibull parameters on the reliability of the dialysis machine. The question of the uncertainties in the Weibull parameters was treated. The involved parameters were considered a Gaussian variable, and their means and standard deviations were calculated in several configurations of the dialysis devices. The random failure rate and reliability were treated and discussed. The random systematic inspection period is studied to install an efficient preventive maintenance program.

Thermal death kinetics of Salmonella Enteritidis in ground chicken in the presence of ribwort, sorrel and yarrow extracts mixture (1%) was investigated by fitting the inactivation curves to the log–linear and Weibull models. The thermal inactivation curves were fitted well to both models (r2 ≥ 0.94). The times required for 4–log reduction in the S. Enteritidis population were shortened by 47–64% in ground chicken supplemented with the herbal extract mixture (p < 0.05). The 4–log reduction times calculated using the Weibull model were 0.13–13.6% longer than those extrapolated with the log–linear model. The z values in the ground chicken samples with and without herbal extract were 5.08°C (r2 = 0.97) and 5.57°C (r2= 0.94), respectively. The results suggest that the mixture of these extracts increased the thermal sensitivity of S. Enteritidis significantly at tested temperatures. In addition, using the Weibull model to calculate thermal death kinetics may reduce the underestimation of the thermal reduction times. Practical applications: This research aimed to investigate the effects of an herbal extract mixture consisting of ribwort, sorrel, and yarrow on the thermal resistance of Salmonella Enteritidis in ground chicken. While these plants are recognized for their antimicrobial and antioxidant properties, there are not many studies conducted to explore their effects on foodborne pathogens in the food matrix. As far as we know, this is the first study that examines the impact of these plants on the thermal resistance of S. Enteritidis in ground chicken. We determined the thermal death kinetics of S. Enteritidis in ground chicken with and without the herbal extract mixture using curve fitting to log‐linear and Weibull models. The findings of this study could help the food industry to develop cooking conditions for Salmonella‐free chicken products. [ABSTRACT FROM AUTHOR]

The feeding of bees is an important factor for their survival, and currently, the use of transgenics is common among producers, since the use of these has reduced production costs, however, there is a great debate as to whether transgenics can harm pollinators. that are in farming regions. Thus, the objective was to evaluate the longevity of Apis mellifera bees using different compositions of transgenic and conventional soy and corn diets, foods that can be substitutes for pollen as a protein source for the hive. For that, the theory of Survival Analysis was used, where the data were constituted by interval censorship, because the time of death is not exactly known. The survival function was estimated using the Weibull regression model with the presence of two covariables: whether the diet is transgenic or not, and the protein content. The adequacy of the model was verified by the graphs of the linearizations using a script developed for the Survival package of the R software, in addition to carrying out the likelihood ratio test at 1% probability, concluding that the presence of the two covariables in the model is significant. In this way, the survival curves of the bees and the estimated risk were constructed, concluding that the GM foods did not have a negative effect on the survival of the bees. [ABSTRACT FROM AUTHOR]

The objective of this study was to 1) compare the stress corrosion coefficient (n) of a Y-TZP obtained by two fatigue tests: cyclic and dynamic and 2) evaluate the effect of frequency in the characteristic lifetime and the existence of interaction between the cyclic fatigue and slow crack growth. A total of 145 Y-TZP specimens were produced in accordance with the manufacturer's instructions. These specimens, measuring 4.0 × 3.0 × 25.0 mm, were used for dynamic (n = 70) and cyclic fatigue tests (n = 75). The specimens were obtained from CAD/CAM blocks, sectioned, and sintered in a furnace at 1530 °C with a heating rate of 25 °C/min. They were tested in their "as-sintered" form without any additional surface treatment. The fatigue tests were conducted using a four-point bending to obtain the slow crack growth parameters (n). The cyclic fatigue test was also conducted in two frequencies (2 and 10 Hz), using stress levels between 350 and 600 MPa. Data from these tests were analyzed using ASTM C 1368–00 formulas and Weibull statistics. Scanning electron microscope (SEM) was used for fracture surface analysis to identify the origin of the fracture. Critical defect size was measured and used, along with flexural strength values, to estimate fracture toughness. Dynamic fatigue test data were used to obtain subcritical crack growth (SCG) parameters and perform Weibull statistical analysis. The cyclic fatigue data were used in the General Log-linear Model equation using the ALTA PRO software. Data were analyzed using one-way ANOVA followed by Tukey post-hoc tests and Student's t-test at a significance level of p ≤ 0.05. In the dynamic fatigue test, the values obtained for σ fo and n were 667 and 54, respectively. This parameter indicates how the strength of the material diminishes over time due to internal cracks. The Weibull parameters obtained from the same test results were m = 7.9, σ 0 = 968, 9 and σ 5% = 767, which indicates the reliability of the material. The Weibull parameters obtained by cyclic fatigue were statistically similar for the two frequencies used, the m * was 0.17 (2 Hz) and 0.21 (10 Hz); characteristic lifetimes (η) were 1.93 × 106 and 40,768, respectively. The n values obtained by cyclic fatigue were 48 and 40 at frequencies of 2 and 10 Hz, respectively. There was no effect of the frequency, the stress level or the interaction of the two in the Y-TZP lifetime, when analysed by General Log Linear Model. the n values obtained by cyclic and dynamic fatigue tests showed no statistically significant difference and the effect of frequency in the characteristic lifetime and the existence of interaction between the cyclic fatigue and subcritical growth were not observed in the tested specimens. • The type of fatigue test did not affect the coefficients of susceptibility to subcritical growth (n) for a dental Y-TZP. • The frequency used in the cyclic fatigue test had no influence on the fatigue parameters of the Y-TZP tested. • There was an increase in the defect size with decreasing loading rate, which explains the drop in strength. [ABSTRACT FROM AUTHOR]

The depletion of resources and emission of hazardous gases have been identified with conventional sources of energy. The negative influence of conventional sources of energy on the environment necessitates the call for the use of renewable and sustainable energy sources, such as wind. Wind power is one of the available renewable energy sources in Nigeria with huge potential that can be tapped in order to contribute to its energy mix. Wind energy utilization in Nigeria is poor because the available data in all six geopolitical political regions for system design have not been fully analyzed and implemented. Wind energy projects are liable to failure if proper analysis is not done. Therefore, before any location could be considered suitable or unsuitable for wind power generation, the power density must be determined using the standard approach. This study, therefore, evaluated the wind energy potential of Omu Aran, Nigeria using Weibull and Rayleigh models. Five-year data collected from the metrological station of the Landmark University on Lat. 8.14 °N; Long. 5.10 °E were processed and analyzed in Matlab computer software using a code developed for two statistical modeling methods (Weibull and Rayleigh). The actual mean yearly wind speed of 3.964 m/s for Kwara falls in the low wind speed. Although the power density for hours of the day, months, and seasonal variation ranged from 24 to 141 W/m², more than 50% of the power density for daily hours was less than 100 W/m² which indicated that Omu Aran, Nigeria belongs to class 1. The coefficient of efficiency for Weibull probability distribution ranged from 39.95 to 94.9, while the coefficient of determination (COD) R² ranged from 0.66 to 0.98. This range of performance values for the Weibull model, when compared to the Rayleigh model, was within the acceptable limits for prediction accuracy; hence, the Weibull probability distribution function can be used for the preliminary design of wind power plants for Kwara State, Nigeria. Therefore, it would help the relevant stakeholders in wind power project investment to make the appropriate decision. [ABSTRACT FROM AUTHOR]

A group sequential design allows investigators to sequentially monitor efficacy and safety as part of interim testing in phase III trials. Literature is well developed in the case of continuous and binary outcomes, however, in case of trials with a time-to-event outcome, popular methods of sample size calculation often assume proportional hazards. In situations where the proportional hazards assumption is inappropriate as indicated by historical data, these popular methods are very restrictive. In this paper, a novel simulation-based group sequential design is proposed for a two-arm randomized phase III clinical trial with a survival endpoint for the non-proportional hazards scenario. By assuming that the survival times for each treatment arm follow two different Weibull distributions, the proposed method utilizes the concept of Relative Time to calculate the efficacy and safety boundaries at selected interim testing points. The test statistic used to generate these boundaries is asymptotically normal, allowing p-value calculation at each boundary. Many design features specific to time-to-event data can be incorporated with ease. Additionally, the proposed method allows the flexibility of having the accelerated failure time model and the proportional hazards model as constrained special cases. Real life applications are discussed demonstrating the practicality of the proposed method.

Characterization of the diameter distribution of forest stands managed for timber production provides accurate estimates of existing wood volume by diameter class and area unit. It provides the basis for determining the stand's ecological and economic value, its structure, the potential for ecosystem services, and appropriate management practices. Patula pine is one of the most important conifers in southern Mexico and requires biometric tools to improve management strategies. This study aimed to use the Bayesian approach to estimate the parameters of Johnson's SB (JSB) and Weibull (W) probability density functions (pdf) and to model the diameter distribution of patula pine stands in southern Mexico. We used data from 462 diameter distributions derived from 66 permanent 400 m2 sampling plots. The results indicated that the Bayesian approach was appropriate for estimating the JSB and W pdf parameters. Due to the similarity between the nonparametric tests and the goodness-of-fit statistics of the functions, the graphical analysis helped to select the W function as the better option to adequately model the diameter distribution of the analyzed stands. The equations developed for parameter prediction of the W function with stand variables allowed us to characterize and project the theoretical distribution of diameter classes in a simple accurate way with variables easily obtained from forest inventories. The Bayesian approach proved to be an effective method for estimating the pdf parameters used. This allowed for the correct characterization of the observed diameter distribution, and its implementation was easy for executing the procedure. Diameter distribution models are a powerful tool for forest inventory and management of patula pine stands analyzed in southern Mexico.

Abstract Purpose To evaluate the effect of zirconia priming with MDP-Salt before MDP containing primers and self-adhesive cement on the shear bond strength. Materials and methods Fully sintered high translucent zirconia specimens (n = 120) were assigned into 2 groups (n = 60 each): Control (No Pretreatment) and Methacryloyloxydecyl dihydrogen phosphate salt (MDP-Salt) pretreated. Each group was divided into 3 subgroups (n = 20) according to cementation protocol: 1) MDP + Silane primer and conventional resin cement, 2) MDP+ Bisphenyl dimethacrylate (BPDM) primer and conventional resin cement, and 3) MDP containing self-adhesive resin cement. Shear bond strength (SBS) was measured after 10,000 thermocycling. Contact angle was measured for tested groups. Surface topography was assessed using a 3D confocal laser scanning microscope (CLSM). Weibull analysis was performed for SBS and one-way ANOVA for contact angle and surface topography measurements (α = 0.05). Results The use of MDP-Salt significantly improved the SBS (p .05). MDP + BPDM showed a significantly lower characteristic strength compared to self-adhesive resin cement when both were pretreated with MDP-Salt. No difference between all tested groups in the surface topographic measurements while MDP-Salt showed the highest contact angle. Conclusion MDP-Salt pretreatment can improve bonding performance between zirconia and MDP containing products.

Objective: To evaluate the flexural strength and fatigue behavior of a novel 3D‐printed composite resin for definitive restorations. Materials and Methods: Fifty disc‐shaped specimens were manufactured from each of a nanohybrid composite resin (NHC), polymer‐infiltrated ceramic network (PICN), and 3D‐printed composite resin (3D) with CAD‐CAM technology. Biaxial flexural strength (σin) (n = 30 per group) and biaxial flexural fatigue strength (σff) (n = 20 per group) were measured using piston‐on‐three‐balls method, employing a staircase approach of 105 cycles. Weibull statistics, relative‐strength degradation calculations, and fractography were performed. The results were analyzed with 1‐way ANOVA and Games‐Howell post hoc test (α = 0.05). Results: Significant differences in σin and σff among the groups (p < 0.001) were detected. The NHC group provided the highest mean ± standard deviation σin and σff (237.3 ± 31.6 MPa and 141.3 ± 3.8 MPa), followed by the PICN (140.3 ± 12.9 MPa and 73.5 ± 9.9 MPa) and the 3D (83.6 ± 18.5 MPa and 37.4 ± 23.8 MPa) groups. The 3D group exhibited significantly lower Weibull modulus (m = 4.7) and up to 15% higher relative strength degradation with areas of nonhomogeneous microstructure as possible fracture origins. Conclusions: The 3D‐printed composite resin exhibited the lowest mechanical properties, where areas of nonhomogeneous microstructure developed during the mixing procedure served as potential fracture origins. Clinical Significance: The clinical indications of the investigated novel 3D‐printed composite resin should be limited to long‐term provisional restorations. A cautious procedure for mixing the components is crucial before the 3D‐printing process, since nonhomogeneous areas developed during the mixing could act as fracture origins. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the reliability and failure modes of ultrathin (0.5 mm) lithium disilicate, translucent and ultra‐translucent zirconia crowns for posterior teeth restorations. Materials and Methods: Fifty‐four mandibular first molar crowns of three ceramic materials: (1) Lithium disilicate (e.max CAD, Ivoclar Vivadent), (2) 3Y‐TZP (Zirconn Translucent, Vipi), and (3) 5Y‐PSZ (Cercon XT, Dentsply Sirona), with 0.5 mm of thickness were milled and cemented onto composite resin abutments. Eighteen samples of each group were tested under mouth‐motion step‐stress accelerated life testing in a humid environment using mild, moderate, and aggressive profiles. Data was subjected to Weibull statistics. Use level curves were plotted and reliability was calculated for a given mission of 100,000 cycles at 100, 200, and 300 N. Fractographic analyses of representative samples were performed in scanning electron microscope. Results: Beta (β) values suggest that failures were dictated by material's strength for lithium disilicate and by fatigue damage accumulation for both zirconias. No significant differences were detected in Weibull modulus and characteristic strength among groups. At a given mission of 100,000 cycles at 100 N, lithium disilicate presented higher reliability (98% CB: 95–99) regarding 3Y‐TZP and 5Y‐PSZ groups (84% CB: 65%–93% and 79% CB: 37&–94%, respectively). At 200 N, lithium disilicate reliability (82% CB: 66%–91%) was higher than 5Y‐PSZ (20% CB: 4%–44%) and not significantly different from 3Y‐TZP (54% CB: 32%–72%). Furthermore, at 300 N no significant differences in reliability were detected among groups, with a notable reduction in the reliability of all materials. Fractographic analyses showed that crack initiated at the interface between the composite core and the ceramic crowns due to tensile stress generated at the intaglio surface. Conclusions: Ultrathin lithium disilicate crowns demonstrated higher reliability relative to zirconia crowns at functional loads. Lithium disilicate and zirconia crown's reliability decreased significantly for missions at higher loads and similar failure modes were observed regardless of crown material. The indication of 0.5 mm thickness crowns in high‐load bearing regions must be carefully evaluated. Clinical Significance: Ultraconservative lithium disilicate and zirconia crowns of 0.5 mm thickness may be indicated in anterior restorations and pre‐molars. Their clinical indication in high‐load requirement regions must be carefully evaluated. [ABSTRACT FROM AUTHOR]

In this paper, the wind potential of Tindouf located in southern Algeria has been estimated; to determine wind characteristics (distributions and wind rose) and evaluate the wind energy density, the Weibull distribution model is a widely used method for calculating wind frequency distribution. The study used the maximum likelihood method to estimate the wind speed and direction. The wind speed class was found to be the most prevalent in autumn and winter, with the highest percentage in spring and summer. The wind power density of Tindouf was found to be 224.37 W/m², with the dominant sector being the west, accounting for 29.4% of wind time. The wind speed classes were most prevalent in the eastern sector, accounting for 20.4% of wind time. The wind power density varied from 121.60 W/m² in August to 335.85 W/m² in April, with the average seasonal density varying from 161.38 W/m² in autumn to 280.87 W/m² in spring. Tindouf location is classified as part of the PNL 4th classes, making it an ideal location for wind farms. Wind turbine rows must be oriented perpendicular to the west, generating energy continuously from January until peaking in May. [ABSTRACT FROM AUTHOR]

Hysterothylacium aduncum is a parasitic nematode that infects mainly marine fish. The information on the heterogeneity in the aggregation of macroparasites in fish species is still limited, particularly for the Raphidascarid nematode H. aduncum that infects exploitable marine fish species including horse mackerel (Trachurus trachurus). This study aimed to investigate the heterogeneity of the distribution of H. aduncum to better understand macroparasite aggregation in marine fish. Weibull tests comprising Maximum likelihood were used to analyze the frequency distribution of parasites within a fish host population over the three years period. The parasite, H. aduncum (third larval stage) prevalence was found to be 88% and the condition factor was 1.30∓0.029 in un-infected fish and 1.12∓0.022 in infected fish. The clustered pattern was observed in H. aduncum in horse mackerel. The relation between parasite load and the fish condition factor was found to be significant and conformity of length and weight was affected by parasite load. It is the first time that aggregation has been observed in H. aduncum distribution and forecasts of nematode intensity in horse mackerel. The findings related to the large individual variations suggest that this pattern is significant and should be considered for host-parasite dynamics. [ABSTRACT FROM AUTHOR]

In this paper, we propose, design, and evaluate a new hybrid terrestrial–underwater optical communication link for providing high-speed connectivity between land and underwater systems. A device based on an amplify-and-forward strategy is considered and used for the hybrid optical link. A performance analysis of the proposed hybrid system is then carried out, taking into account both the atmospheric and underwater channels and their respective degradation sources. Different networking scenarios and conditions are evaluated. To this end, the channel model of the terrestrial free-space optical (FSO) link is modeled using the Gamma–Gamma distribution, while the underwater optical link is modeled using the Weibull distribution. The former takes into account atmospheric and turbulence attenuation, geometric spread and pointing errors, while the latter takes into account underwater and turbulence attenuation and geometric spread. Accordingly, a new analytical closed-form expression for the bit error rate (BER), which depends on the cumulative distribution function of the holistic hybrid system, is derived. Analytical results show that pointing errors as well as atmospheric and oceanic turbulence seriously degrade the performance of the hybrid system. In addition, ocean turbulence leads to the occurrence of a BER floor in some scenarios. This is the first time that such a network is proposed and modeled under the assumption of critical channel impairments. [ABSTRACT FROM AUTHOR]

Standard survival models such as the proportional hazards model contain a single regression component, corresponding to the scale of the hazard. In contrast, we consider the so-called "multi-parameter regression" approach whereby covariates enter the model through multiple distributional parameters simultaneously, for example, scale and shape parameters. This approach has previously been shown to achieve flexibility with relatively low model complexity. However, beyond a stepwise type selection method, variable selection methods are underdeveloped in the multi-parameter regression survival modeling setting. Therefore, we propose penalized multi-parameter regression estimation procedures using the following penalties: least absolute shrinkage and selection operator, smoothly clipped absolute deviation, and adaptive least absolute shrinkage and selection operator. We compare these procedures using extensive simulation studies and an application to data from an observational lung cancer study; the Weibull multi-parameter regression model is used throughout as a running example. [ABSTRACT FROM AUTHOR]

Introduction: Recently, researchers have introduced new generated families of univariate lifetime distributions. These new generators are obtained by adding one or more extra shape parameters to the underlying distribution or compounding two distributions to get more flexibility in fitting data in different areas such as medical sciences, environmental sciences, and engineering. The addition of parameter(s) has been proven useful in exploring tail properties and for improving the goodness-of-fit of the family of the proposed distributions. Methods: A new Three-Parameter Weibull-Generalized Gamma (for short, “TWGG”) distribution which provides more flexibility in modeling lifetime data is developed using a two-component mixture of Weibull distribution (with parameters and Generalised Gamma distribution (with parameters . Some of its mathematical properties such as the density function, cumulative distribution function, survival function, hazard rate function, moment generating function, Renyi entropy and order statistics are obtained. The maximum likelihood estimation method was used in estimating the parameters of the proposed distribution and a simulation study is performed to examine the performance of the maximum likelihood estimators of the parameters. Results: Real life applications of the proposed distribution to two cancer datasets are presented and its fit was compared with the fit attained by some existing lifetime distributions to show how the TWGG distribution works in practice. Conclusion: The results suggest that the proposed model performed better than its competitors and it’s a useful alternative to the existing models.

Stochastic Configuration Network (SCN) has a powerful capability for regression and classification analysis. Traditionally, it is quite challenging to correctly determine an appropriate architecture for a neural network so that the trained model can achieve excellent performance for both learning and generalization. Compared with the known randomized learning algorithms for single hidden layer feed-forward neural networks, such as Randomized Radial Basis Function (RBF) Networks and Random Vector Functional-link (RVFL), the SCN randomly assigns the input weights and biases of the hidden nodes in a supervisory mechanism. Since the parameters in the hidden layers are randomly generated in uniform distribution, hypothetically, there is optimal randomness. Heavy-tailed distribution has shown optimal randomness in an unknown environment for finding some targets. Therefore, in this research, the authors used heavy-tailed distributions to randomly initialize weights and biases to see if the new SCN models can achieve better performance than the original SCN. Heavy-tailed distributions, such as Lévy distribution, Cauchy distribution, and Weibull distribution, have been used. Since some mixed distributions show heavy-tailed properties, the mixed Gaussian and Laplace distributions were also studied in this research work. Experimental results showed improved performance for SCN with heavy-tailed distributions. For the regression model, SCN-Lévy, SCN-Mixture, SCN-Cauchy, and SCN-Weibull used less hidden nodes to achieve similar performance with SCN. For the classification model, SCN-Mixture, SCN-Lévy, and SCN-Cauchy have higher test accuracy of 91.5%, 91.7% and 92.4%, respectively. Both are higher than the test accuracy of the original SCN.

Purpose: To evaluate the effect of zirconia priming with MDP-Salt before MDP containing primers and self-adhesive cement on the shear bond strength. Materials and methods: Fully sintered high translucent zirconia specimens (n = 120) were assigned into 2 groups (n = 60 each): Control (No Pretreatment) and Methacryloyloxydecyl dihydrogen phosphate salt (MDP-Salt) pretreated. Each group was divided into 3 subgroups (n = 20) according to cementation protocol: 1) MDP + Silane primer and conventional resin cement, 2) MDP+ Bisphenyl dimethacrylate (BPDM) primer and conventional resin cement, and 3) MDP containing self-adhesive resin cement. Shear bond strength (SBS) was measured after 10,000 thermocycling. Contact angle was measured for tested groups. Surface topography was assessed using a 3D confocal laser scanning microscope (CLSM). Weibull analysis was performed for SBS and one-way ANOVA for contact angle and surface topography measurements (α = 0.05). Results: The use of MDP-Salt significantly improved the SBS (p <.05) for all tested subgroups. Self-adhesive cement showed an insignificant difference with MDP + Silane group for both groups (p >.05). MDP + BPDM showed a significantly lower characteristic strength compared to self-adhesive resin cement when both were pretreated with MDP-Salt. No difference between all tested groups in the surface topographic measurements while MDP-Salt showed the highest contact angle. Conclusion: MDP-Salt pretreatment can improve bonding performance between zirconia and MDP containing products. [ABSTRACT FROM AUTHOR]

Rainfall Statistical distribution fitting is essential for the design of water management and water related infrastructure. Future prediction of rainfall events can be made such as floods and drought for a given area of study if the statistical distribution was known. In this paper the rainfall data of 48 years in Erbil meteorological station in Erbil city was analyzed and fitted to several types of statistical distributions to find the best distribution. The Normal, Gamma and Weibull distributions model were used for annual and monthly rainfall and to the goodness of fit was found based on the p-value and the Anderson-Darling tests. The result shows that Weibull and Gamma functions are successful for all cases, while Normal function failed in a number of months but did very well in others. [ABSTRACT FROM AUTHOR]

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This study examines all of the equations necessary to derive the parameters for seven probability distributions of three parameters typically used in flood frequency research, namely the Pearson III (PE3), the generalized extreme value (GEV), the Weibull (W3), the log-normal (LN3), the generalized Pareto Type II (PG), the Rayleigh (RY) and the log-logistic (LL3) distributions, using the higher-order linear moments method (LH-moments). The analysis represents the expansion of previous research whose results were presented in previous materials, and is part of hydrological research aimed at developing a standard for calculating maximum flows based on L-moments and LH-moments. The given methods for calculating the parameters of the examined distributions are used to calculate the maximum flows on Romania's Prigor River. For both methods, the criterion for selecting the most suitable distribution is represented by the diagram of the L-skewness–L-kurtosis and LH-skewness–LH-kurtosis. The results for Prigor River show that the PG distribution is the best model for the L-moments method, the theoretical values of the statistical indicators being 0.399 and 0.221. The RY distribution is the best model for the LH-moments technique, with values of 0.398 and 0.192 for the two statistical indicators. [ABSTRACT FROM AUTHOR]

The characterisation of probability distribution plays an important role in statistical studies. There are various methods of characterisation available in the literature. The characterisation using truncated moments limits the observations; hence, researchers may save time and cost. In this paper, the characterisation of three general forms of continuous distributions based on doubly truncated moments has been studied. The results are given simply and explicitly. Further, the results have been applied to some well-known continuous distributions. [ABSTRACT FROM AUTHOR]

We study different methods for estimation the parameters of a mixture of Weibull and Gompertz distributions as a lifetime model, based on a complete sample. Maximum likelihood estimation and Bayes estimation under informative and non-informative priors have been obtained using the symmetric squared error (SE) loss function, the asymmetric Linear exponential (LINEX) loss function and general entropy (GE) loss function. Also, we discuss two-sample Bayesian prediction intervals of the proposed model. For the illustration of the developing results, some computation results for the proposed model is presented. [ABSTRACT FROM AUTHOR]

Recent research studies have shown that an integrated system can be constructed to provide future predictions when the inputs are from plot summary, a tree list, or a diameter distribution. The current study addresses the missing link, allowing this integrated system to also accept inputs from a stand table. In this study, different existing techniques were employed to process data in stand table format. Trees in each diameter class were modeled with a truncated Weibull distribution. A tree list was generated by dividing each diameter class into 0.2-cm sub-classes, the midpoint diameter of which represented diameter of an individual tree. Projecting the stand table was equivalent to growing trees in the tree list. Future tree survival and diameter growth were predicted by use of an individual-tree model, which was derived from a whole-stand model. This new method outperformed three existing stand table projection models, based on two error indices. [ABSTRACT FROM AUTHOR]

This paper investigates the maintainability of economizers of three coal-based boilers for making decision of selection of replacement or maintenance practices. A sudden failure in the economizer can result huge production loss hence, a suitable decision model is essential which provides a strong data base for making optimal decision. A practical model for making decision is developed with respect to failure/repair data of three different economizers and trend with serial correlation tests are conducted. An investigation is carried out to determine the idealized statistical probability distribution providing best fit distribution. Further their Reliability and Maintainability are calculated. The tests of trend and serial correlation show very fast increasing failure rate of economizer # 1&2 with respect to economizer # 3. The present paper highlights that the failure data of economizer # 1 and economizer # 2 follow the NHPP model with poor reliability condition which indicates that these economizers should be replaced to restore boiler system as new as. However, failure data of economizer #3 follows the Lognormal distribution with poor reliability condition which suggests to develop the Preventive Maintenance Interval (PMI) to restore the boiler system. The present model serves a strong ground to decide replacement/preventive maintenance policy for not only to economizers but also to any pressure parts of coal based boilers. [ABSTRACT FROM AUTHOR]