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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 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]

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]

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]

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]

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]

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]

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]

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]

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]

To find an alternative that is closer to clinical reality in terms of cavity geometry and configuration factor, this study investigated the pushout test on in vitro adhesive testing to coronal dentin when compared to the established shear test, both in a standardized approach. For a feasible comparison between both tests, the pushout specimen was adjusted in thickness (1.03 ± 0.05 mm) and cavity diameter (1.42 ± 0.03 mm) to receive a bonding area (4.63 ± 0.26 mm2) that matches that of the shear test (4.57 ± 0.13 mm2). Though, the configuration factor between both tests differs largely (pushout 1.5 ± 0.08; shear bond 0.20 ± 0.01). The bond strength of five different adhesives (n = 20) was investigated for both tests. The pushout test registered a high number of invalid measurements (30%) due to concomitant dentin fracture during testing. In contrast to the shear test, the pushout test failed to discriminate between different adhesives (p = 0.367). Both tests differed largely from each other when comparing adhesive groups. When solely looking at the valid specimens, Weibull modulus reached higher values in the pushout approach. Conclusively, the pushout test in this specific setup does not distinguish as precisely as the shear bond test between different adhesives and needs adaption to be routinely applied in adhesive dentistry. [ABSTRACT FROM AUTHOR]

In this article, four new families named as Weibull extended exponentiated-X (WEE-X), Lomax extended exponentiated-X (LEE-X), Logistic extended exponentiated-X (LGCEE-X), and Burr III extended exponentiated-X (BIIIEE-X) with their quantile functions are proposed. The expressions for distribution function and density function of BIIIEE-X family are written in terms of linear combinations of the exponentiated densities based to parent model. New models, i.e., Weibul extended exponentiated Weibull (WEEW), Lomax extended exponentiated Weibull (LEEW), Logistic extended exponentiated Weibull (LGCEEW), and Burr III extended exponentiated-Weibull (BIIIEEW) distributions are derived, were plotted for functions of probability density and hazard rate at different levels of parameters. Some mathematical properties of the BIIIEEW model are disclosed. The maximum likelihood method for the BIIIEEW model are described. Numerical applications of the BIIIEEW model to disease of cancer datasets are provided. [ABSTRACT FROM AUTHOR]

The aim of this work was to measure the lifetime of neural implant test samples at two different temperatures, using a method that allows the precise measurement of the sample lifetime, further analysis with the use of Weibull statistics, and examination of the applicability of the Van't Hoff rule. The correct estimation of the lifetime of neural implants is important to avoid preliminary failures, when used in humans. The novelty lies in the precise data due to the measurement approach, the application of the Weibull statistics to neural test samples, and the examination of the Van't Hoff rule's applicability to the longevity of polyimide-based neural implant samples. Several samples that consisted of interdigitated gold strands, encapsulated in polyimide were soaked in ringer solution. One batch was soaked at a temperature of 37 °C, and another was soaked at a temperature of 57 °C. Voltage was applied and measured to identify the occurrence of failures. The long-term experiment was stopped after 458 days for the samples at 37 °C and 423 days for the samples at 57 °C, with several samples still being intact at both temperature levels. The time to failure was measured and used to identify the Weibull parameters that would describe the behavior of the samples. The median lifetime of the samples changed from 363 days at 37 °C to 138 days at 57 °C. The scale and shape factor changed from 396 and 3.7 at 37 °C to 138 and 2 at 57 °C, respectively. The measured mean, median times, and Weibull scale factors were lower than expected from the Van't Hoff rule. The use of the Van't hoff rule with 2 Δ T / 10 ° C for accelerated lifetime tests would lead to an estimation of longer lifetimes than realistic. A reaction rate constant around 1.47 appears more appropriate. While a fourfold difference in lifetime would be expected, only a 2.65-fold difference in the median lifetime and a roughly 2.2-fold difference in the mean and Weibull scale factor were observed. The shift of the Weibull shape parameter from 3.7 at 37 °C to 2 at 57 °C with rising temperatures was observed, indicating differences in failure reasons and stronger aging at lower temperatures. The used method is simple to apply and interpret and allows for a precise anticipation of sample lifetimes. [ABSTRACT FROM AUTHOR]

Summary: Sherwin Carlquist proposed several functional interpretations for vessel diameter, including that narrow vessels were hydraulically "safe" while wide diameter vessels were more vulnerable to embolism. He applied these ideas both across species and biomes, and within xylem tissue, where function of growth ring types was inferred from vessel diameter polymorphisms (occurrence of differing vessel diameter classes within a tissue). Following on Carlquist's ideas, we were interested in evaluating if vessel diameter polymorphism could be linked to vulnerability-to-embolism curve shape. Vulnerability curves were fit with a model that included a continuous shape term (alpha). We predicted that high variation in vessel diameter would result in lower alpha (more r-shaped) curves whereas low variation would produce higher alpha (more s-shaped) curves, with potential for intermediate curve types. Our findings support Carlquist's functional interpretations of vessel diameter. Vessel diameter polymorphism was strongly correlated to vulnerability curve shape. Homogeneous vessel diameters were associated with more s-shaped curves. As vessel diameter polymorphism increased, alpha declined and curves became more linear. High polymorphism was associated with r-shaped curves. There was no relationship between vessel length and curve shape. Vessel diameter was strongly correlated with a common estimate of embolism resistance (P50), with wider diameter vessels associated with increased vulnerability. Vulnerability curves show enormous variety in shape and scale, and both parameters are likely critical in understanding and predicting plant function. Carlquist's ecological anatomy data, predictions, and functional inferences will continue to be valuable as we expand our understanding of structure–function links in plant anatomy. [ABSTRACT FROM AUTHOR]

The Same--Different task presents two stimuli in close succession and participants must indicate whether they are completely identical or if there are any attributes that differ. While the task is simple, its results have proven difficult to explain. Notably, response times are characterized by a fast-same effect whereby Same responses are faster than Different responses even though identical stimuli should be exhaustively processed to be accurate. Herein, we examine a little more than a quarter million response times (N = 255,744) obtained from 327 participants who participated in one of 14 variants of the task involving minor changes in the stimuli or their durations. We performed distribution fitting and analyzed estimated parameters stemming from the ex-Gaussian, lognormal, and Weibull distributions to infer the cognitive processing characteristics underlying this task. The results exclude serial processing of the stimuli and do not support dual-route processing. The fast-same effect appears only through a shift of the entire response time distributions, a feature impossible to detect solely with mean response time analyses. An attention-modulated process driven by entropy may be the most adequate model of the fast-same effect. [ABSTRACT FROM AUTHOR]

Highlights: The experimental survival probability of one irregular shaped rock was established via 105 drop tests using mortar replicas. The derivation and validation of an analytical model to predict the survival probability of brittle rocks of irregular shape upon collinear impact is presented. The survival probability predicted by the model was found to fall withing 5% of the experimental data with an excellent goodness of fit coefficient (R2 ~ 93%). [ABSTRACT FROM AUTHOR]

In this article, we present statistical inference of unknown lifetime parameters based on a progressive Type‐I interval censored dataset in presence of independent competing risks. A progressive Type‐I interval censoring scheme is a generalization of an interval censoring scheme, allowing intermediate withdrawals of test units at the inspection points. We assume that the lifetime distribution corresponding to a failure mode belongs to a log‐location‐scale family of distributions. Subsequently, we present the maximum likelihood analysis for unknown model parameters. We observe that the numerical computation of the maximum likelihood estimates can be significantly eased by developing an expectation‐maximization algorithm. We demonstrate the same for three popular choices of the log‐location‐scale family of distributions. We then provide Bayesian inference of the unknown lifetime parameters via Gibbs Sampling and a related data augmentation scheme. We compare the performance of the maximum likelihood estimators and Bayesian estimators using a detailed simulation study. We also illustrate the developed methods using a progressive Type‐I interval censored dataset. [ABSTRACT FROM AUTHOR]

Natural Fibers are one of the important growing markets in the domain of bio-composites' processing, due to an unprecedented increase in environmental and economic challenges. As a result, proper selection of the natural fibers that meet the requirements for environment-friendly bio-composites is an important phase as it can heavily enhance the achievement of low-cost design for better sustainable societies. In general, Multi-Criteria Decision Making (MCDM) is considered as a powerful tool that helps designers and decision-makers to accomplish their intended goals. The current research paper extends a material selection model that incorporates Weibull distribution in the Analytical Hierarchical Process (AHP). The strength of this model lies in its ability to account the dispersion in material properties objectively and consider a pre-defined quality level at the time of the material selection process. A case study is presented in this study to illustrate the potential and applicability of the proposed method. The results show that the ranking is dynamic and is highly sensitive to the scenarios of six sigma levels. From the analytical outcomes, the study found that NENDRAN BANANA is the most appropriate fiber that can be used in the hybridization process to design a passenger-vehicle center-lever parkingbrake component with a reasonable defect per million opportunities. [ABSTRACT FROM AUTHOR]

The hydraulic systems of deepwater Blowout Preventers (BOPs) are crucial for ensuring the reliability and safety of offshore oil and gas extraction operations. A functional failure can lead to uncontrolled blowouts, resulting in casualties and significant economic losses on the rig. The Direct Drive Valve (DDV) and the Subsea Plated Mounted (SPM) valve are key components that help maintain the proper functioning of the hydraulic system in deepwater BOPs. This study begins by utilizing the Weibull analysis method to assess the reliability of the DDV and SPM valves using limited fault data samples. To enhance the accuracy of predictions, Weibull parameters are estimated through various methods, including Maximum Likelihood Estimation (MLE), Least Squares Estimation (LSE), and a combination of Correlation Coefficient Optimization with Support Vector Regression (CCO + SVR).Given the challenges in gathering extensive fault data for DDV and SPM valves—due to complex subsea environments, cost constraints, time limitations, and other factors—this study proposes a method employing a Back Propagation Neural Network (BPNN) model to augment the limited fault data samples. To ensure the reliable operation of the DDV and SPM valves, preventive maintenance cycles are established at 2840 and 7550 operations, respectively. At the same reliability level, as the number of operational cycles increases, the remaining service life of the valves gradually decreases, leading to a higher probability of failure over a shorter timeframe. The Mean Remaining Life (MRL) of the DDV and SPM valves, corresponding to different operational times, is analyzed, providing essential reference points for their usage and maintenance. When the extended data sample is utilized for reliability evaluation, the reliability characteristics of the small fault data samples are effectively reflected, and the parameter prediction error remains low. This indicates that the extended data sample is more suitable for reliability evaluation. • Weibull reliability models for DDV and SPM valves are studied. • The methods of Weibull parameter estimation are compared and studied. • Methods for extending fault data using deep learning methods are developed. • The accuracy of the extended fault data is studied. [ABSTRACT FROM AUTHOR]

Ceramic dental prostheses exhibit increasing failure rates with service time. In particular, veneered crowns and bridges are susceptible to chipping and other fracture modes of failure. The purpose of this manuscript is to introduce a computational methodology and associated software that can predict the time-dependent probability of failure for ceramic prostheses and subsequently design proof test protocols to significantly enhance their reliabilities and lifetimes. Transient reliability and corresponding proof testing theories are introduced. These theories are coded in the Ceramic Analysis and Reliability Evaluation of Structures (CARES/Life) code. This software will be used to demonstrate the predictive capability of the theory as well as its use in designing proof test protocols to significantly improve the reliability (survival probability) and lifetime for dental prostheses. A three-unit fixed dental prosthesis (FDP) with zirconia core (ZirCAD) and veneering ceramic (ZirPress) are used to compare the predicted probabilities of failure to general clinical results. In addition, the capability to use proof testing to significantly improve the performance (reliability and lifetime) for this restoration is demonstrated. The probability of failure, P f , after five years without proof testing is predicted to be 0.337. This compares to clinical studies showing the failure rate to be between 0.2 and 0.23 after 5 years. After 10 years, reference 18 found the clinical failure rate for similar bridges (but not the same) to be up to 0.28 compared to the predicted P f of 0.38. The difference may be due to the analysis applying the load at an inclination of 75° which is more critical than vertical loading. In addition, clinical studies often report a simple survival rate instead of using Kaplan-Meier analysis to properly account for late enrollees. Therefore, true clinical failure rates may be higher than reported and may more closely match the predictions of this manuscript. The effectiveness of proof testing increases with selecting materials less susceptible to slow crack growth (higher SCG exponent, N). For example, proof testing the ZirPress glass-veneered bridges with N = 43.4 analyzed in this manuscript at 400 N bite force for 1 s which induces a failure rate during proof testing of 0.31, reduces the P f of bridges not proof tested from 0.45 to an attenuated-proof-tested probability of failure P fa of 0.21 after 20 years of usage. If another material is selected with improved resistance to SCG of N = 60 and the same loading conditions, the failure rate for the proof tested bridges after 20 years of service drops to 2 in 10,000 from 2.4 in 100 had they been not proof tested. The failure rate during proof testing for this material would be 5.1 in 100. Proof testing a material with absolutely no susceptibility to SCG at the same service load (in this case 285 N, not even the 400 N load used above) results in 0 % failure rate and is of course independent of time. The transient reliability and proof test theory presented in this paper and associated computational software CARES/Life were successful in predicting the performance of ceramic dental restorations when compared to clinical data. Well-designed proof test protocols combined with proper material selection can significantly enhance the reliabilities and lifetimes of ceramic prostheses. This proof test capability can be a translational technology if properly applied to dental restorations. [ABSTRACT FROM AUTHOR]

For the rotor, achieving relatively high aerodynamic performance in specific wind conditions is a long-term goal. Inspired by the remarkable flight characteristics of owls, an optimal trailing edge serration design is investigated and proposed for a wind turbine rotor blade. Fluid flow interaction with the proposed serrations is explored for different wind conditions. The result is supported by subsequent validation with three-dimensional numerical tools. The present work employs a statistical-numerical method to predict and optimize the shape of the serrations for maximum aerodynamic improvement. The optimal combination is found using the Taguchi method with three factors: Amplitude, wavelength, and serration thickness. The viability of the solution on an application is assessed using the Weibull distribution of wind in three selected regions. Results show that the presence of serration is capable of improving the annual power generation in all the investigated cities by up to 12%. The rated speed is also shifted from 10 m/s to 8 m/s for most configurations. Additionally, all configurations show similar trends for the instantaneous torque, where an increase is observed in pre-rated speed, whereas a decrease is noticed in the post-rated speed region. A look at the flow field pattern for the optimal design in comparison with the clean blade shows that the modified blade is able to generate more lift in the pre-stall region, while for the post-stall region, early separation and increased wake dominate the flow. [ABSTRACT FROM AUTHOR]

Background: Major Depressive Disorder is one of the most common mental disorders, and it is the main cause of disability worldwide with a prevalence ranging from 7 to 21%. Objective: The goal of this study was to predict the time it took for patients with severe depressive disorders at Jimma University Medical Center to experience their initial symptomatic recovery. Study design: The researchers utilized a prospective study design. Methods: Patients with major depressive disorder were followed up on at Jimma University Medical Center from September 2018 to August 2020 for this study. The Gamma and Inverse Gaussian frailty distributions were employed with Weibull, Log-logistic, and Log-normal as baseline hazard functions. Akaike Information Criteria were used to choose the best model for describing the data. Results: This study comprised 366 patients, with 54.1% of them experiencing their first symptomatic recovery from a severe depressive disorder. The median time from the onset of symptoms to symptomatic recovery was 7 months. In the study area, there was a clustering effect in terms of time to first symptomatic recovery from major depressive disorder. According to the Log-normal Inverse-Gaussian frailty model, marital status, chewing khat, educational status, work status, substance addiction, and other co-variables were significant predictors of major depressive disorder (p-value < 0.05). Conclusion: The best model for describing the time to the first symptomatic recovery of major depressive disorder is the log-normal Inverse-Gaussian frailty model. Being educated and working considerably were the variables that reduces the time to first symptomatic recovery from major depressive disorder; whereas being divorced, chewing khat, substance abused and other co-factors were the variables that significantly extends the time to first symptomatic recovery. [ABSTRACT FROM AUTHOR]

Background: Major Depressive Disorder is one of the most common mental disorders, and it is the main cause of disability worldwide with a prevalence ranging from 7 to 21%. Objective: The goal of this study was to predict the time it took for patients with severe depressive disorders at Jimma University Medical Center to experience their initial symptomatic recovery. Study design: The researchers utilized a prospective study design. Methods: Patients with major depressive disorder were followed up on at Jimma University Medical Center from September 2018 to August 2020 for this study. The Gamma and Inverse Gaussian frailty distributions were employed with Weibull, Log-logistic, and Log-normal as baseline hazard functions. Akaike Information Criteria were used to choose the best model for describing the data. Results: This study comprised 366 patients, with 54.1% of them experiencing their first symptomatic recovery from a severe depressive disorder. The median time from the onset of symptoms to symptomatic recovery was 7 months. In the study area, there was a clustering effect in terms of time to first symptomatic recovery from major depressive disorder. According to the Log-normal Inverse-Gaussian frailty model, marital status, chewing khat, educational status, work status, substance addiction, and other co-variables were significant predictors of major depressive disorder (p-value < 0.05). Conclusion: The best model for describing the time to the first symptomatic recovery of major depressive disorder is the log-normal Inverse-Gaussian frailty model. Being educated and working considerably were the variables that reduces the time to first symptomatic recovery from major depressive disorder; whereas being divorced, chewing khat, substance abused and other co-factors were the variables that significantly extends the time to first symptomatic recovery. [ABSTRACT FROM AUTHOR]

• Explored a novel finite mixture modelling approach to deal with dependent competing risks data. • Assumed a more realistic scenario of competing risks data with multiple causes of failure. • Considered a flexible progressive first failure censoring scheme. • Different cause-specific lifetime distributions are assumed to belong to proportional hazard family of distributions. • A Diabetic Retinopathy dataset is analysed in details assuming some important members of the proportional hazard family. This paper proposes a flexible mixture modeling approach to analyze competing risks data with multiple causes of failure under a progressive first-failure censoring scheme where the causes may not be independent. The failure time distributions corresponding to different causes of failure are assumed to belong to the flexible proportional hazard family of distributions, some important members of which are Weibull, Burr XII and Gompertz distributions. We address the problem here from a classical viewpoint. The point estimates of the parameters can be easily obtained by employing the maximum likelihood principle. For interval estimation purposes, we resort to using the asymptotic confidence intervals. An extensive simulation study is carried out to validate our proposed model. Finally, a diabetic retinopathy treatment dataset is used as an application to study the effectiveness of our proposed model assuming some important members of the proportional hazard family. [ABSTRACT FROM AUTHOR]

Dispersal is a key life‐history trait for most species and is essential to ensure connectivity and gene flow between populations and facilitate population viability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis.Here, we introduce a statistical framework to estimate standardised dispersal kernels from biased data. Based on this, we compare empirical dispersal kernels for European breeding birds considering age (average dispersal; natal, before first breeding; and breeding dispersal, between subsequent breeding attempts) and sex (females and males) and test whether different dispersal properties are phylogenetically conserved.We standardised and analysed data from an extensive volunteer‐based bird ring‐recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the different age and sex‐specific dispersal kernels for each bird species.The dispersal movements of the 234 European bird species analysed were statistically best explained by heavy‐tailed kernels, meaning that while most individuals disperse over short distances, long‐distance dispersal is a prevalent phenomenon in almost all bird species. The phylogenetic signal in both median and long dispersal distances estimated from the best‐fitted kernel was low (Pagel's λ < 0.25), while it reached high values (Pagel's λ >0.7) when comparing dispersal distance estimates for fat‐tailed dispersal kernels. As expected in birds, natal dispersal was on average 5 km greater than breeding dispersal, but sex‐biased dispersal was not detected.Our robust analytical framework allows sound use of widely available mark‐recapture data in standardised dispersal estimates. We found strong evidence that long‐distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events. [ABSTRACT FROM AUTHOR]

Due to the intermittent nature of wind, it is necessary to estimate the duration of wind generation for rapid restoration of power systems during the self-healing service process. Because of this, designing a mathematical model for short-term estimation of wind power delivery to variable loads based on reliability is essential to check the adequacy of electricity supply. The validity of the proposed novel hierarchical algorithmic solution is verified by experimental studies on the particular case of 66 MW Manjil wind farm in Iran. More specifically, this algorithm is designed based on Weibull distribution program in order to facilitate managing and analyzing big data sets of wind speeds, wind power generation, and power consumption. The ability to respond to the requested electrical energy, i.e. 1 MW-50 MW, was also determined online from the instantaneous wind and load inputs, and restoration was achieved for the quantitative ranges of 1 MW to 20 MW by local energy potential. Demonstrated results indicate that by applying the proposed solution approach, we will be able to restore variable responsive loads with accuracy reliability and wind power supply as well as an appropriate lifetime in the self-healing service for independent sections. [ABSTRACT FROM AUTHOR]

This study focused on examining and comparing the strength properties of untreated and surface-modified Giant Cavendish banana fibers. The banana fibers were mercerized using 0.06 M Sodium Hydroxide (NaOH) and treated using 0.003 M Potassium Permanganate (KMnO4) solutions. The untreated and surface-modified fibers were then subjected to a tensile test and the results analyzed using the Weibull Cumulative Distribution Function. KMnO4 treated banana fibers had a mean tensile strength of 209.321 ± 22.619 MNm-2, which translated to a 65.92% gain in strength while the mercerized banana fibers had a mean tensile strength of 162.233 ± 7.976 MNm-2, which was a 28.60% gain in strength. Mercerized banana fibers recorded a Weibull modulus of 7.6096 compared to the untreated fibers (4.7042) and KMnO4 treated fibers (3.2135). The banana fiber surface-modification using KMnO4 resulted in stronger fibers. However, the lower Weibull modulus of 3.2135 can be attributed to the introduction of flaws in to the fiber structure by the KMnO4 treatment. [ABSTRACT FROM AUTHOR]

The validity of the standard SPT test for the characterization of the strength of advanced ceramics is analyzed. Discs of PZT, alumina and silicon nitride with two different thicknesses were chosen for the analysis. Series of discs were tested and the Weibull distributions of strength were built. The fractographic analysis revealed green processing-related heterogeneities to be the critical defects in all specimens. A valid FEM method of calculation was established to get the effective volumes of standard SPT specimens with thicknesses between 0.2 and 1 mm. The relationships between the Weibull parameters of the distributions corresponding to different thicknesses were established using the effective volumes. For the standard SPT configuration, a simple empirical equation is proposed and verified to calculate the effective volume of SPT specimens of any thickness between 0.2 and 1 mm as a function of the specimen thickness and the Weibull modulus. [ABSTRACT FROM AUTHOR]

To carry out the forecast of meteorological data in order to perform an analysis of the solar and wind potential of the Camilo Daza airport of the city of Cúcuta, multilayer Perceptron-type neural networks configured with 9 4-4layer neurons and 10 times or iterations are used to adjust the procedural variables of the regression. For this, the methodology presented by Jorge Aguilera and Leocadio Hontoria and the Weibull probability density distribution are used, with the intention of guaranteeing a lower initial investment with adequate and complete use of the solar system, the wind system and the bank of batteries, so that the cost / investment / benefit ratio is viable. [ABSTRACT FROM AUTHOR]

Developing the engineering design standard of wind speed is a key aspect of the climate research in the Yangtze River Inland Waterway (YRIW), which is highly sensitive to extreme weather and climate processes. An engineering design wind speed projection model was established to evaluate the distribution of extreme wind speeds in the YRIW region at spatiotemporal scales from 1979 to 2100, integrating the Weibull distribution and generalized extreme value (GEV) distribution characteristics. We also used high-precision climate model products and integrated analysis methods to predict the evolution of engineering design wind speeds in the study area in the future. The results show that: (1) The maximum wind speed in the study area shows a decline—recovery trend in the historical period in general and a weak increase in Wuhan and Shanghai. (2) The maximum wind speed does not follow the Weibull distribution, and the extracted extreme wind speed types include type I, II, and III GEV distributions. (3) The updated inland port project design wind speed can meet the climatic and topographic characteristics of the YRIW. (4) The model of CNRM-CM6-1-HR product accurately captures the spatial and temporal characteristics of the maximum wind speed. (5) In the future, the design wind speed shows a slight decrease in Shanghai, Jiujiang and Yueyang. These findings provide a scientific theoretical reference and engineering reference for the development of design wind speeds for inland port projects at various cross-sections in the YRIW. [ABSTRACT FROM AUTHOR]

Algorithms for automated novelty detection and management are of growing interest but must address the inherent uncertainty from variations in non-novel environments while detecting the changes from the novelty. This paper expands on a recent unified framework to develop an operational theory for novelty that includes multiple (sub)types of novelty. As an example, this paper explores the problem of multi-type novelty detection in a 3D version of CartPole, wherein the cart Weibull-Open-World control-agent (WOW-agent) is confronted by different sub-types/levels of novelty from multiple independent agents moving in the environment. The WOW-agent must balance the pole and detect and characterize the novelties while adapting to maintain that balance. The approach develops static, dynamic, and prediction-error measures of dissimilarity to address different signals/sources of novelty. The WOW-agent uses the Extreme Value Theory, applied per dimension of the dissimilarity measures, to detect outliers and combines different dimensions to characterize the novelty. In blind/sequestered testing, the system detects nearly 100% of the non-nuisance novelties, detects many nuisance novelties, and shows it is better than novelty detection using a Gaussian-based approach. We also show the WOW-agent's lookahead collision avoiding control is significantly better than a baseline Deep-Q-learning Networktrained controller. [ABSTRACT FROM AUTHOR]

In this research, we present two-stage and purely sequential methodologies for estimating the scale parameter of the Moore and Bilikam family of lifetime distributions (see Moore and Bilikam in IEEE Trans Reliabil 27:64–67, 1978). We propose our methodologies under the minimum risk point estimation setup, whereby we consider the modified LINEX loss function plus non linear sampling cost. We study some interesting exact distributional properties associated with our stopping rules. We also present simulation analyses using Weibull distribution (special case of the Moore and Bilikam family) to check the performance of our two-stage and purely sequential procedures. Finally, we provide a real data set from COVID-19 and analyze it using the Weibull model in support of the practical utility of our proposed two-stage methodology. [ABSTRACT FROM AUTHOR]

This review critically examines the various ways in which the mechanical properties of wood have been understood. Despite the immense global importance of wood in construction, most understanding of its elastic and inelastic properties is based on models developed for other materials. Such models neglect wood's cellular and fibrous nature. This review thus questions how well models that were originally developed for homogeneous and effectively continuous materials can describe wood's mechanical properties. For example, the elastic moduli of wood have been found by many authors to depend on the size of the test specimen. Such observations are incompatible with classical elasticity theory. There is also much uncertainty about how well elastic moduli can be defined for wood. An analysis of different models for size effects of various inelastic properties of wood shows that these models only approximate the observed behaviour, and do not predict or explain the scatter in the results. A more complete understanding of wood's mechanical properties must take account of it being in some sense intermediate between a material and a structure. [ABSTRACT FROM AUTHOR]

Objectives: To characterize the mechanical and biological properties of three commercially available resins, which are currently used for provisional restorations and to compare them to an experimental resin intended for definitive fixed dental prostheses. Materials and methods: Three commercially available resins: Crowntec (CT, Saremco), Temporary C&B (FL, Formlabs), C&B MFH (ND, Nextdent), and the experimental resin: Permanent Bridge (PB, Saremco) were printed and subjected to biaxial flexural strength test, finite element analysis, Weibull analysis, scanning electron microscopy, cell proliferation, immunohistochemistry and cytotoxicity assays. Samples from CT, PB, and ND were provided directly from the manufacturers ensuring ideal workflow. FL was printed using the workflow as recommended by the manufacturer, using a Formlabs 2 printer and their post‐processing units Form Wash and Form Cure. Results: From the tested resins, PB yielded the best overall results in terms of mechanical properties. Cell proliferation and cytotoxicity did not show any significant differences among materials. PB showed higher values for probability of survival predictions (35%) when subjected to 250 MPa loads, whereas the other materials did not reach 10%. Significance: Despite mechanical differences between the evaluated materials, the outcomes suggest that 3D printed provisional resins may be used in clinical settings, following the manufacturers indications. New materials intended for long‐term use, such as the PB resin, yielded higher mechanical properties compared to the other materials. Alternative printing and post‐processing methods have not yet been evaluated and should be avoided until further literature is available. Clinical significance: 3D printed resins for provisional restorations have become popular with the emergence of new technologies. In this study, we evaluated three different commercially available resins for provisional restorations and one new experimental resin. The results from this study indicate that commercially available resins could be used in clinical settings under certain conditions and limited periods of time. Following the manufacturers protocols is of paramount importance to not compromise these properties. [ABSTRACT FROM AUTHOR]

This study aimed at determining and comparing the mechanical properties of natural, mercerized, and cornified sisal fibers. Sisal fiber morphology was modified by mercerization using a 0.06 Molar sodium hydroxide solution and by a seven-hour, seven cycle cornification at 100°C. The fiber strength properties were then determined and analyzed using the Weibull Cumulative Density Function. Mercerized sisal fibers displayed the most significant improvement in tensile strength with mean fracture stress of 271 MPa, which showed a 68.30% increase in tensile strength compared to untreated sisal fiber's 161.02 MPa. Cornified sisal fibers had a mean fracture stress value of 198.57 MPa, which was a 23.32% increase compared to untreated sisal fibers. Untreated sisal fibers had the highest Weibull Modulus of 7.616. Mercerized and cornified sisal fibers had Weibull Moduli of 6.175 and 4.723, respectively. These results show that although fiber surface treatment leads to a significant improvement of Kenyan sisal fiber strength properties, the delignification associated with mercerization and the collapse of the lamella structure that accompanies cornification either exacerbated existing flaws or introduced new flaws in the fibers. [ABSTRACT FROM AUTHOR]

The main objective of life test sampling plans developed under Type-I censoring, that is time truncation, is to make the decision about a lot with the minimum sample size for specified producer's and consumer's risks and mean life. In this article, we develop three new economical life test sampling plans by introducing a two-stage time-censoring scheme and making use of a modified exponentially weighted moving average statistic. From the comparison of life test sampling design parameters for generalized exponential and Weibull distributions, with a similar acceptance sampling plan in literature, we find the most economical life test sampling plan is the one that employs both above-mentioned scheme and statistic. We give two examples, including one real life example, to illustrate the performance of three new plans. Tables of life test sampling design parameters are simulated using software R.3.5.2. [ABSTRACT FROM AUTHOR]

A study of the distribution of the value of traded goods under the Harmonized System is presented. The ramifications of this classification system are found to exhibit an approximate power law decay, indicating complexity and self-organization in the nomenclature of traded merchandises. For almost all countries with available data, log-values of annually imported and exported goods are well described by three-parameter Weibull distributions. This distribution commonly appears in particles size distributions, suggesting a connection between random fragmentation processes and the mechanisms behind the international trade of merchandises. Analysis of the resulting values for the fitting parameters from 1995 to 2018 shows a nearly constant linear relationship between the parameters of the Weibull distributions, so that, for each country, the distribution of log-values can be approximately characterized by a single shape parameter β. The empirical findings of this paper suggest that specialization on trading a constant set of goods prevents the values of all traded merchandises from growing/decreasing simultaneously. [ABSTRACT FROM AUTHOR]

Background: A genome-wide association study (GWAS) correlates variation in the genotype with variation in the phenotype across a cohort, but the causal gene mediating that impact is often unclear. When the phenotype is protein abundance, a reasonable hypothesis is that the gene encoding that protein is the causal gene. However, as variants impacting protein levels can occur thousands or even millions of base pairs from the gene encoding the protein, it is unclear at what distance this simple hypothesis breaks down. Results: By making the simple assumption that cis-pQTLs should be distance dependent while trans-pQTLs are distance independent, we arrive at a simple and empirical distance cutoff separating cis- and trans-pQTLs. Analyzing a recent large-scale pQTL study (Pietzner in Science 374:eabj1541, 2021) we arrive at an estimated distance cutoff of 944 kilobasepairs (95% confidence interval: 767–1,161) separating the cis and trans regimes. Conclusions: We demonstrate that this simple model can be applied to other molecular GWAS traits. Since much of biology is built on molecular traits like protein, transcript and metabolite abundance, we posit that the mathematical models for cis and trans distance distributions derived here will also apply to more complex phenotypes and traits. [ABSTRACT FROM AUTHOR]

The stresses at break of fragile materials like acrylic resin and composite material for orthopedic use measured in bending are higher than those measured in direct traction. Tests on a composite material for orthopedic use laminated with 6 glass-perlon-acrylic layers (PV-2P-VP) for orthopedic use made it possible to identify its mechanical characteristics and to highlight the influence of the direction of cutting of the samples. The mechanical properties of this material indicate dispersion in the direction of the orientation of the molding which shows values of stress at break and of the Young's modulus which are reduced compared to the values measured in the perpendicular direction. The choice motivates the statistical approach which leads us to apply the Weibull model to assess the dangerousness of a stress in terms of probability of failure. The theoretical predictions are in good agreement with the experimental values. The morphological study of the fracture facies makes it possible to draw up an inventory of the various mechanisms at the origin of the damage and the rupture of these materials and thus to locate the most dominant. [ABSTRACT FROM AUTHOR]

Brittle fracture of conventional plain concrete poses a major problem to civilian and military infrastructure safety against impact loading. In this research, a simple technique is proposed to improve the impact resistance of preplaced aggregate fibrous concrete (PAFC) by adding coarse aggregates precoated with asphalt. PAFC is an emerging form of composite with an atypical mixture of fibres and coarse aggregates premixed and pre-packed into the formwork to form a skeleton with cement grout being injected into it to fill all voids in the skeleton. In this research, eighteen different mixtures and six specimens per mixture were prepared and divided into four groups. The first and third groups comprised coarse aggregates subjected to single and double asphalt precoating, respectively, with a replacement of 25, 50, 75, and 100% of natural aggregates. The second and third mixtures comprised of a dosage of 2.5% of new hybrid hooked end-crimped steel fibre in addition to single and double-coated aggregates with the same replacement percentage of coarse aggregates. C-graded asphalt was used for single- and double-layered coating of the aggregates to absorb energy. All specimens were tested according to the guidelines of the ACI Committee 544 falling mass impact standard. An appropriate statistical tool, distribution of Weibull, was used to analyse the scattering of experimental test results, while impact strength was offered in terms of reliability. The findings indicated that the impact strength of concrete increased when asphalt-coated aggregate content increased from 25 to 100%. Impact performance of double-coated aggregate concrete was superior to the single-coated aggregate in fibrous and non-fibrous concretes. Further, the steel fibre significantly contributed to the increase in impact strength than the asphalt-coated aggregates. [ABSTRACT FROM AUTHOR]

In this paper, we analyze a combined terrestrial-underwater optical communication link for providing high-speed optical connectivity between onshore and submerge systems. For this purpose, different transmission signaling schemes were employed to obtain performance results in terms of average bit error rate (ABER). In this sense, from the starting point of a known conditional bit-error-rate (CBER) in the absence of turbulence, the behavior of the entire system is obtained by applying an amplify-and-forward (AF) based dual-hop system: The first link is a terrestrial free-space optical (FSO) system assuming a Málaga distributed turbulence and, the second one, is an underwater FSO system with a Weibull channel model. To obtain performance results, a semi-analytical simulation procedure is applied, using a hyper-exponential fitting technique previously proposed by the authors and leading to BER closed-form expressions and high-accuracy numerical results. [ABSTRACT FROM AUTHOR]

Offshore wind offers an excellent opportunity for domestic renewable energy production with a vast potential for future energy systems. Offshore wind resource assessment, however, can be challenging. Remote sensing data e.g., Synthetic Aperture Radar (SAR), provide high spatial resolution detailed information on the spatial variability of offshore wind and have been used for wind resource assessment, as well as for the long-term validation of wind speed estimates from other sources (e.g. Numerical Weather Prediction models). This paper focuses on the evaluation of a 26-month time-series of Sentinel-1 SAR Level 2 OCN products for wind resource assessment in the offshore areas around Cyprus. Sentinel data were evaluated against a 10-year regional reanalysis dataset (UERRA) time-series and wind measurements from 5 coastal meteorological stations in Cyprus. Comparison revealed an overall agreement between the fitted stations and Sentinel Weibull distributions while discrepancies exist between the two data sources and UERRA. Bias observed between Sentinel and UERRA Weibull-derived statistics appears to be spatially dependent. Preliminary wind power assessment results indicate a significant wind power potential for the southwestern offshore areas of Cyprus, surpassing 400 W / m 2 on average, offering thus economically viable solutions in terms of a future offshore wind power project development. [ABSTRACT FROM AUTHOR]

A new class of distributions called Marshall-Olkin Zubair-G family is proposed in this study. Some statistical properties of the family are derived and two special distributions namely, Marshall-Olkin Zubair Nadarajah-Haghighi and Marshall-Olkin Zubair Weibull distributions are developed. The plots of the density and hazard rate functions of the special distributions exhibit different shapes for chosen parameter values, making them good candidates for modeling different types of datasets. A real life application using the Marshall-Olkin Zubair Nadarajah-Haghighi distribution revealed that it performs better than other existing extensions of the Nadarajah-Haghighi distribution for the given dataset. [ABSTRACT FROM AUTHOR]