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A novel two-parameter continuous model titled the entropy-transformed Weibull (ET-W) distribution has been developed via the entropy transformation. A new framework has been investigated and found to meet the criteria of the probability function. By significantly improving the functional shape and having the ability to model the most likely form of the hazard rate function, this novel modification has increased the adaptability of typical model. Some of its core characteristics, such as its statistical and computational features, are simply and clearly presented. To examine the ultimate performance of maximum likelihood estimators during the process of estimating model parameters, a comprehensive simulation analysis has been conducted. The effectiveness of the suggested distribution is illustrated through the modeling of real datasets. [ABSTRACT FROM AUTHOR]

Bacterial contamination is a major public health concern on a global scale. Treatment resistance in bacterial infections is becoming a significant problem that requires solutions. We were interested in obtaining new polymeric functionalized compounds with antibacterial properties. Three components (polymeric amine, aldehyde, and phosphite) were used in the paper in a modified "one-pot" Kabachnik–Fields reaction, in tetrahydrofuran at 60 °C, to create the N-C-P skeleton in aminophosphonate groups. Two copolymers were thus prepared starting from an acrylonitriledivinylbenzene (AN-15%DVB) copolymer containing pendant primary amine groups modified by grafting aminophosphonate groups, i.e., aminobenzylphosphonate (Bz-DVB-AN) and aminoethylphosphonate (Et-DVB-AN). The two copolymers were characterized by FT-IR spectroscopy, SEM-EDX, TGA, and antibacterial properties. It was shown that the novel products have antibacterial qualities against S. aureus and E. coli bacteria. The sample with the strongest antibacterial activity was Et-DVB-AN. We assessed how well the Weibull model and the first-order kinetic model represent the inactivation of microbial cells in our samples. The main advantage of the new antibacterial agents developed in this work is their easy recovery, which helps to avoid environmental contamination. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the most important risk factors that influence productive life (PL) and to estimate genetic parameters for PL using a Weibull proportional hazards model in two Spanish dairy goat breeds belonging to different production systems. The dataset consisted of 70,695 and 49,176 lactation records of Florida and Payoya females, respectively, collected over the last two decades. A total of 6,227 (24.21%) Florida and 3,452 (20.42%) Payoya females had censored information. The pedigree included a total of 56,901 animals for Florida and 59,957 for Payoya. The effects included in the model for both breeds were the age at first kidding and the herd-year-season of birth of the doe as time-independent effects; and the age at kidding, the herd-year-season of kidding, the within-herd class of milk production deviation and the combination between the lactation number and the duration of lactation as time-dependent effects. Estimation of genetic parameters was made using a Weibull proportional hazards model using Survival Kit V6.0 software. The results from the Weibull animal models gave estimates of additive genetic variances of 0.99 ± 0.0003 and 0.156 ± 0.021, which corresponds to a heritability of 0.43 ± 0.025 and 0.11 ± 0.021 for Florida and Payoya, respectively. The magnitude of heritability obtained for PL suggests that a substantial response to selection may be expected for longevity, especially in the Florida breed. These results may contribute to the development of a routine genetic evaluation to improve PL in Spanish dairy goat breeds. HIGHLIGHTS: A Weibull proportional hazards model has been used to analyse productive life in Spanish goat breeds raised under different production systems. Productive life is influenced by many factors, with milk production the most important. According to the heritability estimated, a significant genetic response could be obtained by direct selection for productive life, especially in the Florida breed. [ABSTRACT FROM AUTHOR]

To investigate the effects of repeated sodium hypochlorite stress on the resistance of Salmonella enterica Serovar Enteritidis (S. Enteritidis) LWCC1051. LWCC1051 was exposed to Trypticase Soy Broth (TSB) containing sodium hypochlorite concentrations of 9 mmol/L, 10 mmol/L, and 11 mmol/L. After 13 repeated transfers and incubations, three sodium hypochlorite resisted LWCC1051 strains were obtained. The D-values and colony morphologies of these strains were assessed. Their survival rates at 60 °C, 65 °C, 70 °C, 75 °C, and − 20 °C were determined and lethality curves at these temperatures were fitted using the Weibull model. Additionally, the Minimal Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) for these strains in various chemicals, including malic acid, citric acid, ascorbic acid, acetic acid, lactic acid, hydrochloric acid, sodium hydroxide, potassium hydroxide, calcium chloride, sodium chloride, and potassium chloride were ascertained. Sodium hypochlorite concentrations of 9 mmol/L, 10 mmol/L, and 11 mmol/L in TSB induced sodium hypochlorite resistance in S. Enteritidis. D-value increased with the frequency of stress exposure. Higher concentrations of sodium hypochlorite resulted in greater D-values and noticeable differences in colony morphologies. The Weibull model accurately represented the temperature resistance curves of LWCC1051 at the specified temperatures. With increasing sodium hypochlorite stress, both high and low-temperature resistances of LWCC1051 improved. Furthermore, under acetic acid stress, the MIC and MBC values of LWCC1051 strains, post exposure to 9 mmol/L, 10 mmol/L, and 11 mmol/L sodium hypochlorite, doubled. Sodium hypochlorite stress enhances the cross-resistance of LWCC1051 to high temperature, low temperature, and acetic acid treatments. [ABSTRACT FROM AUTHOR]

Urban systems are vulnerable to disturbances from both natural and human origins, which can disrupt their normal functioning. Evaluating the resilience of these systems, particularly the main transportation networks and their usage levels, is crucial and innovative for understanding the impacts of such disturbances. Thus, this work aims to assess resilience in urban mobility through the probability of a particular journey using a specific mode: "surviving" through critical travel time. To achieve this, a methodology was developed based on the Weibull model with gamma heterogeneity (hazard-based duration models), which was applied to a medium-sized Portuguese municipality. Eighteen groups representing active populations were set and compared. The results indicated that using the bus and cycling are the most resilient modes of transport, whereas walking is the least resilient. Additionally, a specific group was identified as having lower mobility resilience, making them more vulnerable to disruptions in the transport system. Finally, the findings of this study demonstrate the practical application of this methodology, which relies on travel time to assess resilience and, thus, guide political attention and actions to the less resilient mode. Future research should aim to develop a comprehensive framework that incorporates several variables to fully describe the complex nature of transport systems and their resilience. [ABSTRACT FROM AUTHOR]

This study investigated the tensile behaviors of hemp fiber bundles and examined how properties including tensile strength and Young's modulus vary with the bundle diameter. Hemp fibers were extracted, degummed, and separated into bundles of different diameters ranging from less than 50 μm to over 150 μm. Tensile tests were conducted on these fiber bundles using a rheometer-based tensile testing machine. The results showed that hemp fibers exhibited a tensile strength of 97.33 MPa and a Young's modulus of 3.77 GPa at a 50% survival probability. However, the scale parameters for breaking stress and Young's modulus were determined to be 620.57 MPa and 29.88 GPa, respectively. As the fiber bundle diameter increased, the tensile strength decreased significantly. This was attributed to the higher probability of defects and irregularities acting as weakness points in larger fiber bundles. In contrast, Young's modulus (stiffness) increased with increasing bundle diameter, likely due to improved fiber–fiber interactions. To further understand the variability and reliability of the tensile properties, statistical models were developed. The Weibull distribution analysis was applied, revealing critical insights into the variability of diameter, stress at break, Young's modulus, and strain at break. The Weibull parameters provided a comprehensive understanding of the fibers' mechanical reliability. Additionally, the Griffith model was employed to predict the strength and Young's modulus based on fiber diameters, supporting the observation that thinner fibers generally exhibited higher tensile strength due to fewer defects. Overall, this work highlights the importance of understanding structure–property relationships in natural fibers like hemp for optimizing their performance in composites. [ABSTRACT FROM AUTHOR]

Abstract A novel two-parameter continuous model titled the entropy-transformed Weibull (ET-W) distribution has been developed via the entropy transformation. A new framework has been investigated and found to meet the criteria of the probability function. By significantly improving the functional shape and having the ability to model the most likely form of the hazard rate function, this novel modification has increased the adaptability of typical model. Some of its core characteristics, such as its statistical and computational features, are simply and clearly presented. To examine the ultimate performance of maximum likelihood estimators during the process of estimating model parameters, a comprehensive simulation analysis has been conducted. The effectiveness of the suggested distribution is illustrated through the modeling of real datasets.

The aim of this study was to assess the most important risk factors that influence productive life (PL) and to estimate genetic parameters for PL using a Weibull proportional hazards model in two Spanish dairy goat breeds belonging to different production systems. The dataset consisted of 70,695 and 49,176 lactation records of Florida and Payoya females, respectively, collected over the last two decades. A total of 6,227 (24.21%) Florida and 3,452 (20.42%) Payoya females had censored information. The pedigree included a total of 56,901 animals for Florida and 59,957 for Payoya. The effects included in the model for both breeds were the age at first kidding and the herd-year-season of birth of the doe as time-independent effects; and the age at kidding, the herd-year-season of kidding, the within-herd class of milk production deviation and the combination between the lactation number and the duration of lactation as time-dependent effects. Estimation of genetic parameters was made using a Weibull proportional hazards model using Survival Kit V6.0 software. The results from the Weibull animal models gave estimates of additive genetic variances of 0.99 ± 0.0003 and 0.156 ± 0.021, which corresponds to a heritability of 0.43 ± 0.025 and 0.11 ± 0.021 for Florida and Payoya, respectively. The magnitude of heritability obtained for PL suggests that a substantial response to selection may be expected for longevity, especially in the Florida breed. These results may contribute to the development of a routine genetic evaluation to improve PL in Spanish dairy goat breeds.

This study addresses the critical challenges faced in cancer care, particularly in predicting survival times for patients with lung cancer and acute myeloid leukemia. Despite recent advancements in medical science, existing models often fall short in accurately capturing disease progression, leading to less effective clinical decision-making, and compromised patient outcomes. The need for advanced predictive models is urgent to improve survival time forecasts and enhance treatment strategies. In response to this, we introduce a novel probabilistic approach, the New Weibull (NEWE) model, which is part of a newly generated class designed to model cancer patient data more effectively. Our methodology includes using seven well-known estimation methods, each rigorously evaluated for consistency through Monte Carlo simulation studies focused on key metrics such as absolute bias, mean square error, and mean relative error. The datasets analyzed include survival times for twenty acute myeloid leukemia patients, 121 breast cancer patients from 1929 to 1938, 33 patients with acute myelogenous leukemia, data from eighteen individuals who died from causes unrelated to cancer, and survival times of advanced lung cancer patients undergoing standard chemotherapy. The NEWE model outperformed competing models, particularly in Anderson-Darling, Cramer-von Mises, and Kolmogorov-Smirnov tests, with significantly higher p-values. These findings highlight the NEWE model’s potential to transform predictive oncology by offering more precise survival time predictions, improving the quality of care and decision-making in cancer treatment.

Hepatitis E virus (HEV) is a zoonotic virus that infects humans when virus-containing pork products are consumed. This study aimed to explore MNV (murine norovirus) and HEV inactivation during cold smoking and ripening/fermentation treatments used for salami-like sausages (mettwurst). MNV inactivation was monitored in culture medium solution and in sausage while being subjected to a salami-like sausage manufacturing process. The inactivation of MNV in the solution was also monitored at room temperature (RT) for four weeks. HEV inactivation was monitored in solution during the cold smoking process and at RT. A TCID50 assay was used to calculate the infectious MNV and HEV titres. MNV survival was modelled using Bayesian inference. MNV load in solution decreased by as much as 4.7 (SD 0.9) log10 TCID50/ml when it was subjected to the cold smoking process. Modelling revealed that 99.999% MNV might be inactivated during the treatment when observed at a level of 95% CI (Bayesian Confidence Interval). On the contrary, MNV load decreased by only 1.8 (0.2) log10 when stored at RT. The low-titre HEV in solution was inactivated (> 1.1 (0.2) log10) when treated, and at RT. However, MNV was resistant in the sausage matrix during the cold smoking process (log10 reduction of 1.9 (0.5) TCID50/ml). Based on modelling, a substantial amount of virus would remain in the product, even when the uncertainty was considered. Hence, viruses, here exemplified by MNV, may not be inactivated from salami-like pork sausages during manufacturing, which poses a risk for consumers in real-life situations. [ABSTRACT FROM AUTHOR]

The impact of pulsed light treatment (PLT) on natural microbiota and inoculated microbes such as Salmonella Typhimurium, Bacillus cereus, and Aspergillus flavus on red chilies was investigated. Sequential drying did not completely inactivate the aerobic mesophiles and yeast and mold count. Hence, PLT (0.53–2.59 J cm−2) was employed as a decontamination technology on red chilies. PLT resulted in 8 log reduction of inoculated microorganisms on chilies at 2.59 J cm−2. The microbial inactivation kinetics followed Weibull distribution (R2 > 0.97) with β value of 1.1, 1.2, and 1.5 for S. Typhimurium, B. cereus, and A. flavus, respectively. Changes in structure and composition of cell components were identified by SEM and FTIR analysis. After PLT, phenolics, antioxidants, flavonoids, and capsaicinoids were better retained but a significant change in ascorbic acid and carotenoid's content was observed. Hence, PL can be a potential technology for decontamination of fresh and dried chilies along with maximum retention of bioactives. [ABSTRACT FROM AUTHOR]

We propose AFTNet, a novel network‐constraint survival analysis method based on the Weibull accelerated failure time (AFT) model solved by a penalized likelihood approach for variable selection and estimation. When using the log‐linear representation, the inference problem becomes a structured sparse regression problem for which we explicitly incorporate the correlation patterns among predictors using a double penalty that promotes both sparsity and grouping effect. Moreover, we establish the theoretical consistency for the AFTNet estimator and present an efficient iterative computational algorithm based on the proximal gradient descent method. Finally, we evaluate AFTNet performance both on synthetic and real data examples. [ABSTRACT FROM AUTHOR]

In this paper, we considered the constant false alarm rate (CFAR) detector in presence of Swerling 1 interfering targets surrounded in Weibull background. The proposed CFAR detector is inspired from a general test statistic that is given as a function of two selected scale invariant functions. It is based on the well known Weber-Haykin Order Statistics CFAR (WHOS-CFAR) detector and is given in terms of three ranked samples. Even in the face of several interfering targets, the investigation of the false alarm regulation demonstrates the robustness with respect to scale and shape clutter parameters. Moreover, through simulated and IPIX (Intelligent PIXel X-band radar) real data, the performance of the above WHOS-CFAR detector is checked for both homogeneous and heterogeneous environments and achieves the CFAR-ness property with immunity to circumstances involving interfering targets. [ABSTRACT FROM AUTHOR]

The subsidence of the earth's surface in mining areas is characterized by fast speed and large gradients. Conventional small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) monitoring can significantly underestimate results, making it challenging to capture the surface's temporal subsidence features. In this context, this paper proposes a method for monitoring subsidence in mining areas. It utilizes a phase unwrapping network (PUNet) and a fused Weibull model within the SBAS-InSAR framework to address nonlinear and large-gradient subsidence. The basic principle of this method is to first process the SAR images using the small baseline method to obtain the differential interferogram, utilizing the PUNet to obtain reliable large-gradient unwrapped phases. Next, the Weibull model parameters of each pixel are calculated based on the unwrapped phase, and the temporal subsidence of each point on the surface is determined using the calculated parameters. This method introduces a nonlinear model into the SBAS-InSAR solution, which is more consistent with the subsidence characteristics of mining areas. Through experimentation in a backfilled mining working face, the proposed method in this paper yields superior monitoring results compared to conventional approaches. [ABSTRACT FROM AUTHOR]

The avocado (Persea americana) is a fruit that possesses a high nutritional content and is abundant in phytochemical compounds. However, there is a lack of research conducted on the processing and preservation methods of this fruit. Application of innovative drying such as infrared drying could create a potential product from avocado for the food and cosmetics industry. In this study, two important factors, including temperature of infrared radiation (65, 70, 75 and 80 °C) and formulation (avocado pulp with and without maltodextrin (9 g/100 g pulp)), were investigated to determine the characteristic of drying behavior. The infrared drying was found to removed moisture from avocado pulp effectively. The drying kinetics in infrared drying of avocado pulp could be determined by the Weibull model. Deff values were estimated to range between 5.24 × 10−10 m2/s and 8.41 × 10−10 m2/s for avocado pulp with maltodextrin and between 6.10 × 10−10 m2/s to 9.18 × 10−10 m2/s for avocado pulp without maltodextrin. The activation energy for infrared drying of avocado pulp was found to be 30.77 and 26.74 kJ/mol corresponding to formulation with and without maltodextrin. It takes a short time in drying avocado pulp using infrared radiation showed high potential application in the production of high-quality dried avocado such as avocado powder.

Porous asphalt concrete (PAC) is typically used as a paving material for porous asphalt pavement in rainy areas due to its abundant interconnected pores structure. Not all interconnected pores in PAC are valid for permeability, mainly influenced by the composition of aggregate gradation. The main purpose of this paper is to investigate the effect of aggregate gradation on pores structure distribution in PAC by X-ray computed tomography (CT) system and digital image processing (DIP) techniques. The distributions of porosity, number and average equivalent diameter of air voids in middle part are much more evenly compared to the both ends in PAC specimens, accounting for about 70 % of the total of specimen height. The average equivalent diameter of interconnected air voids mainly ranges from 0.5 mm to 5 mm in PAC, accounting for about 80 % of the total numbers. For PAC with similar porosity, the larger the normal maximum aggregate size (NMAS), the less the number and the larger the average equivalent diameter of air voids (interconnected air voids), the smaller the difference between the interconnected porosity and porosity. For PAC with same NMAS, as the porosity increase, the number and average equivalent diameter of air voids (interconnected air voids) are respectively decreased and increased gradually, the difference between the interconnected porosity and porosity is also showed a decreasing trend. And then, the correlated equation is established among porosity, interconnected porosity and the composition of aggregate gradation. The distribution of air voids (interconnected air voids) size could be well described by the two-parameter Weibull model, and the relationships are explored and developed between Weibull model parameters and the composition of aggregate gradation.

In recent years, the modeling of time-to-events has emerged as a highly promising and dynamic research area. This field has witnessed a surge of research studies dedicated to developing novel statistical methodologies aimed at effectively handling time-to-event phenomena. These studies are motivated by the increasing recognition of the importance of time-related factors in various fields such as medicine, epidemiology, finance, and engineering. Researchers have been actively engaged in proposing innovative approaches to address the complexities associated with time-to-event data. The overarching goal is to enhance our understanding of event occurrence and duration, enabling more accurate predictions and informed decision-making. This research encompasses a wide range of topics, including survival analysis, reliability modeling, and event prediction. The motivation behind these research efforts stems from the need to overcome traditional limitations in time-to-event analysis and to explore new avenues for modeling and interpretation. By introducing advanced statistical techniques, researchers seek to capture the intricate dynamics of event processes, considering factors such as censoring, competing risks, and time-varying covariates. The proliferation of research studies in this domain reflects a collective effort to push the boundaries of statistical modeling and analysis, paving the way for more comprehensive and robust methodologies. As researchers continue to delve deeper into the intricacies of time-to-event data, the impact of these advancements extends to diverse applications, ultimately fostering innovation and progress across interdisciplinary fields. This paper adopts and implements a new statistical approach to propose a family of flexible distributions, namely, a new generalized-O family of distributions. For the newly obtained family, certain mathematical properties such as identifiability, quantile function, rth non-central moment, Lorenz curve, incomplete moments, and the expression of the Bonferroni curve are obtained. Furthermore, an extension of the Weibull model is introduced using the newly developed approach, namely, a new generalized Weibull model. The parameters of the new generalized version of the Weibull model are estimated by adopting a well-known estimation approach. Finally, a data set consists of sixty (60) observations representing the times of the survival of some patients infected by the COVID-19 epidemic is analyzed to illustrate the new generalized Weibull model.

Statistical methods have widespread applications in real-life scenarios. Researchers have expressed keen interest in implementing different functions to raise new probability distributions. However, very limited efforts have been made to raise new methodologies by applying trigonometric functions. In this paper, we propose a new method based on the trigonometric function. The suggested trigonometric-based method is called a new trigonometric cosine-G (NTC-G) family to generate flexible models. The new method is developed using the cosine function. A subcase of the NTC-G method termed as a new trigonometric cosine-Weibull (NTC-Weibull) is studied. Certain mathematical properties of the NTC-Weibull model are presented. For the NTC-Weibull model, the point estimators are acquired. Finally, the suitability of the NTC-Weibull distribution is demonstrated in light of a healthcare data set. Using the numerical and graphical approaches, the evaluation results of the NTC-Weibull distribution are compared with the Weibull and its four well-known existing modifications.

The flea beetle Nisotra uniformis Jacoby is a widespread pest of malvaceous crops for which synthetic chemical insecticides remain the principal control tool, particularly in sub-Saharan Africa. With the ultimate aim of developing a microbial alternative for N. uniformis control, we conducted laboratory experiments (25 ± 1°C; 70 - 80% RH) to evaluate the biological attributes of three Cameroonian isolates of the entomopathogenic fungi Beauveria bassiana (Balsamo-Crivelli) Vuillemin and Metarhizium anisopliae sensu lato (Metchnikoff) Sorokin. Spore germination rates of the isolates varied from 0.5% after 4 hrs to 100% after 24 hrs on PDA medium, with MIITAC11.3.4 spores germinating fastest. Pathogenicity tests consisted of dipping adult beetles in conidial suspensions. All isolates were pathogenic to N. uniformis, with corrected mortalities varying between 23.3 - 86.7%. BIITAC-O-2 had the lowest LC50 at 5.17 × 106 conidia/ml, while MIITAC11.3.4 and BIITAC6.2.2 had LC50 at 4.11 × 107 conidia/ml, and 2.00 × 108 conidia/ml, respectively. BIITAC6.2.2 produced the shortest time to the highest mortality rate (1.17 days) and the shortest LT50 of 1.64 days but only at the highest concentration, followed by the two highest concentrations of MIITAC11.3.4 (LT50 at 3.43 and 5.70 days). The c parameter in the Weibull model showed that BIITAC-O-2 caused the highest rate of increase in mortality (2.42) at the highest concentration, followed by MIITAC11.3.4 (1.09) and BIITAC6.2.2 (0.50). The results of our study provide the basis for including N. uniformis in the ongoing development of BIITAC6.2.2 and MIITAC11.3.4 into biopesticide while continuing with further laboratory studies on BIITAC-O-2.

In recent years, the modeling of time-to-events has emerged as a highly promising and dynamic research area. This field has witnessed a surge of research studies dedicated to developing novel statistical methodologies aimed at effectively handling time-to-event phenomena. These studies are motivated by the increasing recognition of the importance of time-related factors in various fields such as medicine, epidemiology, finance, and engineering. Researchers have been actively engaged in proposing innovative approaches to address the complexities associated with time-to-event data. The overarching goal is to enhance our understanding of event occurrence and duration, enabling more accurate predictions and informed decision-making. This research encompasses a wide range of topics, including survival analysis, reliability modeling, and event prediction. The motivation behind these research efforts stems from the need to overcome traditional limitations in time-to-event analysis and to explore new avenues for modeling and interpretation. By introducing advanced statistical techniques, researchers seek to capture the intricate dynamics of event processes, considering factors such as censoring, competing risks, and time-varying covariates. The proliferation of research studies in this domain reflects a collective effort to push the boundaries of statistical modeling and analysis, paving the way for more comprehensive and robust methodologies. As researchers continue to delve deeper into the intricacies of time-to-event data, the impact of these advancements extends to diverse applications, ultimately fostering innovation and progress across interdisciplinary fields. This paper adopts and implements a new statistical approach to propose a family of flexible distributions, namely, a new generalized- O family of distributions. For the newly obtained family, certain mathematical properties such as identifiability, quantile function, r th non-central moment, Lorenz curve, incomplete moments, and the expression of the Bonferroni curve are obtained. Furthermore, an extension of the Weibull model is introduced using the newly developed approach, namely, a new generalized Weibull model. The parameters of the new generalized version of the Weibull model are estimated by adopting a well-known estimation approach. Finally, a data set consists of sixty (60) observations representing the times of the survival of some patients infected by the COVID-19 epidemic is analyzed to illustrate the new generalized Weibull model. [ABSTRACT FROM AUTHOR]

This study investigated the effects of low-pressure cold plasma on the inactivation of Bacillus cereus vegetative cells and spores in an inert matrix (borosilicate glass slide) and in rice grains, using oxygen as ionization gas. Greater reductions in B. cereus counts were observed in vegetative cells rather than spores. The experimental data obtained show that both the power of the plasma treatment and the matrix proved to be determining factors in the inactivation of both the spores and vegetative cells of B. cereus. To characterize the inactivation of B. cereus, experimental data were accurately fitted to the Weibull model. A significant decrease in parameter "a", representing resistance to treatment, was confirmed with treatment intensification. Furthermore, significant differences in the "a" value were observed between spores in inert and food matrices, suggesting the additional protective role of the food matrix for B. cereus spores. These results demonstrate the importance of considering matrix effects in plasma treatment to ensure the effective inactivation of pathogenic microorganisms, particularly in foods with low water activity, such as rice. This approach contributes to mitigating the impact of foodborne illnesses caused by pathogenic microorganisms. [ABSTRACT FROM AUTHOR]

High moisture in Chinese medicine residues (CMR) can decrease the energy efficiency of thermochemical conversion, which necessitates the pre-drying. Owing to the complex constituents and decoction, CMR may possess distinct drying characteristics. It is necessary to understand its drying behaviors, effective moisture diffusivity, and pollutant emissions for future design and optimization of an industrial-level dryer. In this study, the drying of four types of typical CMR in hot nitrogen was performed. Their condensate and exhaust gas were collected and characterized. The results indicated that their drying process was dominated by internal moisture transport mechanism with a long falling rate stage. Drying temperature influenced their drying process more greatly than N2 velocity did. Residual sum of squares, root mean square error, and coefficient of determination indicated that Weibull model demonstrated their drying process best. Their effective moisture diffusivity was in the range of 1.224 × 10–8 to 4.868 × 10–8 m2/s, while their drying activation energy ranged from 16.93 to 30.39 kJ/mol. The acidic condensate had high chemical oxygen demand and total nitrogen concentration and yet low total phosphorus concentration. The concentration of total volatile organic compounds, non-methane hydrocarbons, H2S, and NH3 in the exhaust gas met the national emission limitation, while the deodorization of exhaust gas was required to remove odor smell. [ABSTRACT FROM AUTHOR]

The shelf life of green chillies is very low due to high-water activity (aw = 0.90 ± 0.01). Balancing aw and moisture content is crucial for maintaining freshness, quality and extending shelf life of green chillies. To attain microbial and biochemical stability, the aw should be reduced to 0.6 and 0.3, respectively. Hence, a controlled drying process was introduced. The 0.6 aw (62 ℃/360 min + 35 ℃/60 min) and 0.3 aw (75 ℃/600 min + 40 ℃/240 min) green chillies improved bioactives retention, colour and texture; but could not completely prevent the growth of microorganisms. Therefore, post-drying, a decontamination process i.e., pulsed light (PL) treatment of 0.53 to 2.59 Jcm−2 (1.7–2.1 kV/120–360 s) was employed. Along with microbial decontamination and enzyme inactivation, PL preserved better physicochemical characteristics in 0.6 and 0.3 aw than 0.9 (fresh) green chillies. While, there is 89.8%, 89.0%, 88.8%, and 93.3% retention of phenolics, antioxidants, flavonoids, and capsaicinoids, respectively, in 0.3 aw green chillies at PL fluence of 2.59 J cm−2 fluence. Alongside, ascorbic acid, carotenoids, and chlorophyll showed 30%, 19%, and 26% loss, respectively, in 0.6 aw green chillies at 2.59 J cm−2. Drying followed by PL treatment ensured that the green chillies were safe for consumption, and met regulatory standards while maintaining their quality attributes. Therefore, integrated approach combining drying followed by PL decontamination would be the suitable method for preserving the quality of the green chillies. [ABSTRACT FROM AUTHOR]

Simple Summary: Inbreeding is the mating of related individuals. Inbreeding has been used in the past to create new breeds. Individuals selected for inbreeding were those who had acquired the genes of their parents, leading to higher performance in a particular trait. However, the genetic and phenotypic effects of inbreeding can dramatically affect the herd. An inbred individual is more likely to be homozygous for any gene, so the animal may also show undesirable traits and a reduction in average phenotypic performance, which is called inbreeding depression. Inbreeding depression negatively affects mainly reproductive traits, fertility, growth parameters, and longevity. Inbreeding depression is essentially the opposite effect of heterosis, which is the result of crossing lines or breeds. This study aimed to estimate the average inbreeding coefficient in Slovak Simmental dairy cattle and evaluate the effect of inbreeding on the length of productive life. All pedigrees included 463,282 animals dating back to 1914. The inbreeding coefficients for each animal in the pedigree were computed using the software CFC 1.0. Length of productive life (LPL) was defined as the time (days) from the first calving to culling, death, or censoring. The influence of inbreeding on the length of productive life was calculated and tested using the Weibull proportional hazards model. The average inbreeding coefficient, the average number of discrete generation equivalents, and the average longest ancestral path for inbred animals were 0.01, 6.59, and 13.08, respectively. While the largest decrease in the mean coefficient of inbreeding was observed from the year of birth 1995 (F = 1.50%) to 2001 (F = 0.59%), an increasing trend of inbreeding in the population was found from 2003 onwards. A weak but significant effect of inbreeding on the length of productive life of Simmental cows was confirmed using survival analysis. [ABSTRACT FROM AUTHOR]

Desiccation tolerance of pathogenic bacteria is one strategy for survival in harsh environments, which has been studied extensively. However, the subsequent survival behavior of desiccation-stressed bacterial pathogens has not been clarified in detail. Herein, we demonstrated that the effect of desiccation stress on the thermotolerance of Escherichia coli O157:H7 in ground beef was limited, and its thermotolerance did not increase. E. coli O157:H7 was inoculated into a ground beef hamburger after exposure to desiccation stress. We combined a bacterial inactivation model with a heat transfer model to predict the survival kinetics of desiccation-stressed E. coli O157:H7 in a hamburger. The survival models were developed using the Weibull model for twodimensional pouched thin beef patties (ca. 1 mm), ignoring the temperature gradient in the sample, and a three-dimensional thick beef patty (ca. 10 mm), considering the temperature gradient in the sample. The two-dimensional (2-D) and three-dimensional (3-D) models were subjected to stochastic variations of the estimated Weibull parameters obtained from 1,000 replicated bootstrapping based on isothermal experimental observations as uncertainties. Furthermore, the 3-D model incorporated temperature gradients in the sample calculated using the finite element method. The accuracies of both models were validated via experimental observations under non-isothermal conditions using 100 predictive simulations. The root mean squared errors in the log survival ratio of the 2-D and 3-D models for 100 simulations were 0.25-0.53 and 0.32-2.08, respectively, regardless of the desiccation stress duration (24 or 72 h). The developed approach will be useful for setting appropriate process control measures and quantitatively assessing food safety levels. [ABSTRACT FROM AUTHOR]

Statistical methods have widespread applications in real-life scenarios. Researchers have expressed keen interest in implementing different functions to raise new probability distributions. However, very limited efforts have been made to raise new methodologies by applying trigonometric functions. In this paper, we propose a new method based on the trigonometric function. The suggested trigonometric-based method is called a new trigonometric cosine- G (NTC- G) family to generate flexible models. The new method is developed using the cosine function. A subcase of the NTC- G method termed as a new trigonometric cosine-Weibull (NTC-Weibull) is studied. Certain mathematical properties of the NTC-Weibull model are presented. For the NTC-Weibull model, the point estimators are acquired. Finally, the suitability of the NTC-Weibull distribution is demonstrated in light of a healthcare data set. Using the numerical and graphical approaches, the evaluation results of the NTC-Weibull distribution are compared with the Weibull and its four well-known existing modifications. [ABSTRACT FROM AUTHOR]

In response to the problem of reduced durability of concrete structures in the northwest region of China under salt frost erosion, this study selected concrete specimens with different polypropylene fiber contents (0, 0. 6, 0.9, 1.2, 1.5 kg ⋅ m-3) and placed them in clear water, 3% NaCl, and 5% Na2SO4 solutions for freeze-thaw cycle testing. The changes in mass loss rate, dynamic elastic modulus and compressive strength of specimens were analyzed, and standard models were established based on Weibull theory and grey theory to predict the maximum service life of polypropylene fiber reinforced concrete structures. At the same time, SEM was used to analyze the mechanism of polypropylene fiber reinforced concrete. The results show that the damage caused by clear water freeze-thaw conditions to concrete is lower than that caused by salt freeze-thaw erosion with chloride salt causing the most severe erosion damage to mechanical properties of concrete. The infiltration of polypropylene fibers can effectively slow down the degradation rate of mechanical properties of concrete under freeze-thaw erosion and weaken the impact of external erosion on compressive strength. The optimal effect is achieved when the fiber content reaches 1.2 kg ⋅ m-3. The life prediction results of grey prediction model and Weibull model are roughly similar. The grey prediction model can only make large-scale inferences based on data currently contained, while Weibull model has more accurate prediction results. This result can provide theoretical guidance and basis for studying the mechanical properties of concrete and selecting the best model to predict the service life of concrete. [ABSTRACT FROM AUTHOR]

Symmetrical as well as asymmetrical statistical models play a prominent role in describing and predicting the real-world phenomena of nature. Among other fields, these models are very useful for modeling data in the sector of civil engineering. Due to the applicability of the statistical models in civil engineering and other related sectors, this paper offers a statistical methodology to improve the distributional flexibility of traditional models. The suggested method/approach is called the extended-X family of distributions. The proposed method has the ability to generate symmetrical and asymmetrical probability distributions. Based on the extended-X family approach, an updated version of the Weibull model, namely, the extended Weibull model, is studied. The proposed model is very flexible and has the ability to capture the symmetrical and asymmetrical shapes of its density function. For the extended-X method, the estimation of parameters, a simulation study, and some mathematical properties are derived. Finally, the practical illustration/usefulness of the suggested model is shown by analyzing two data sets taken from the field of engineering. Both data sets represent the fracture toughness of alumina (Al2O3). [ABSTRACT FROM AUTHOR]

This data article presents tensile properties of about 1200 single carbon fibres (PYROFIL™ TRW40 50L) tested at eight different gauge lengths in the range of L0∈ [20; 80] mm with approximately 150 tested fibres for each length. The equivalent fibre diameter distribution is presented, and the mean and standard deviation are found to be df=(7.37 ± 0.34) µm. The obtained stress-strain curves are analysed by a second-order polynomial fitting method. The initial modulus, E0= (220 ± 3) GPa, and the curvature coefficient α=(3600 ± 250) GPa are determined. The failure stress distribution is analysed by the Weibull model. A Weibull parameter of m¯=6.7±0.8 is determined, and the characteristic (σ0), median (σ˜) and mean (σ¯) failure stresses are found to scale linearly with the gauge length. A length scale independent stress-length factor of σ0m¯L0=(560±60)GPam¯m is determined. The fibre properties determined in this work can be used as parameters to model the mechanical behaviour of carbon fibre composites by Weibull scaling, as done in [1] and [2].

Relay protection devices contain numerous electronic components， and environmental factors such as temperature， humidity， and vibration can impact their reliability. Addressing the complex dynamic changes in temperature stress experienced by protection devices installed in switchgear during operation， this study considers environmental temperature as a random variable following a normal distribution. Based on the Arrhenius model and the Weibull model， conditional probability density functions along with probability density functions of temperature stress distribution are used to derive the overall probability density function， reliability function， and failure rate function of protection devices. Through numerical computation， the study assesses the impact of changes in temperature mean and variance parameters on the reliability of protection devices， providing a theoretical basis for reliability research on relay protection devices during field operation.

Mango powder is a nutrient-dense substance that can be used directly or as a supplement in food items. However, due to the high sugar content, the removal of moisture from mango was difficult. This study investigated an infrared drying technique for removing moisture from mango pulp to produce powder products. The experiment was designed in a three-factor full factorial design with the following variables: drying temperature (70, 75, and 80°C), maltodextrin content (0, 6, and 9 g/100 g pulp), and total soluble solid content (11 and 16°Brix). The findings indicated that the Weibull model was the most appropriate for describing the moisture removal of mango pulp during infrared drying. Higher temperature and maltodextrin content, along with reduced total soluble solid content, resulted in improved quality of the mango powder. Furthermore, the optimal drying conditions for mango powder were found as 11°Brix, 80°C, and 9% maltodextrin content, which could ensure the highest retention of total phenolics (59.874%), retention of reducing sugars (71.044%), total acidity (10.141%), and retention of DPPH radical scavenging activity (65.051%). To fully benefit from the rewards of infrared drying, it is essential to establish suitable pretreatment conditions or use additives to preserve component quality.

Bacterial contamination is a major public health concern on a global scale. Treatment resistance in bacterial infections is becoming a significant problem that requires solutions. We were interested in obtaining new polymeric functionalized compounds with antibacterial properties. Three components (polymeric amine, aldehyde, and phosphite) were used in the paper in a modified “one-pot” Kabachnik–Fields reaction, in tetrahydrofuran at 60 °C, to create the N-C-P skeleton in aminophosphonate groups. Two copolymers were thus prepared starting from an acrylonitriledivinylbenzene (AN-15%DVB) copolymer containing pendant primary amine groups modified by grafting aminophosphonate groups, i.e., aminobenzylphosphonate (Bz-DVB-AN) and aminoethylphosphonate (Et-DVB-AN). The two copolymers were characterized by FT-IR spectroscopy, SEM-EDX, TGA, and antibacterial properties. It was shown that the novel products have antibacterial qualities against S. aureus and E. coli bacteria. The sample with the strongest antibacterial activity was Et-DVB-AN. We assessed how well the Weibull model and the first-order kinetic model represent the inactivation of microbial cells in our samples. The main advantage of the new antibacterial agents developed in this work is their easy recovery, which helps to avoid environmental contamination.

This study investigated the tensile behaviors of hemp fiber bundles and examined how properties including tensile strength and Young’s modulus vary with the bundle diameter. Hemp fibers were extracted, degummed, and separated into bundles of different diameters ranging from less than 50 μm to over 150 μm. Tensile tests were conducted on these fiber bundles using a rheometer-based tensile testing machine. The results showed that hemp fibers exhibited a tensile strength of 97.33 MPa and a Young’s modulus of 3.77 GPa at a 50% survival probability. However, the scale parameters for breaking stress and Young’s modulus were determined to be 620.57 MPa and 29.88 GPa, respectively. As the fiber bundle diameter increased, the tensile strength decreased significantly. This was attributed to the higher probability of defects and irregularities acting as weakness points in larger fiber bundles. In contrast, Young’s modulus (stiffness) increased with increasing bundle diameter, likely due to improved fiber–fiber interactions. To further understand the variability and reliability of the tensile properties, statistical models were developed. The Weibull distribution analysis was applied, revealing critical insights into the variability of diameter, stress at break, Young’s modulus, and strain at break. The Weibull parameters provided a comprehensive understanding of the fibers’ mechanical reliability. Additionally, the Griffith model was employed to predict the strength and Young’s modulus based on fiber diameters, supporting the observation that thinner fibers generally exhibited higher tensile strength due to fewer defects. Overall, this work highlights the importance of understanding structure–property relationships in natural fibers like hemp for optimizing their performance in composites.

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A lab-scale reactor with a fixed-bed hematite catalyst for the effective decomposition of H2O2 and bacteria inactivation was designed. The bactericidal effect is the largest at a low initial bacterial count of 2·103 CFU/L, which is typical for natural surface waters. When using a 5 mM H2O2 solution and a residence time of 104 min, the reduction in the number of E. coli bacteria is about 3.5-log. At a higher initial bacterial count of 1-2·104 CFU/L, a 5 mM H2O2 solution reduces the bacteria number by about 4-log. The H2O2 decomposition follows the log-linear kinetics of a first-order reaction while the bacterial inactivation does not. The kinetics of bacterial inactivation was described using the Weibull model in the modified form: log10(N0/N) = b · tn. The values of the non-linearity parameter n were found to be lower than 1, indicating that bacterial inactivation slows down over time. With increasing initial H2O2 concentration, the rate parameter b increases while the non-linearity parameter n decreases. With increasing temperature, both parameters increase. The stability of the catalyst has been proved by XRD, FTIR, SEM, and ICP-OES. The concentration of iron leaching into water during disinfection is much lower than the limit declared by WHO for iron in drinking water. The results show that technical-grade hematite is a promising Fenton-like catalyst for water disinfection. The fixed-bed reactor can be the basis of the mobile installations for water purification in emergencies. [ABSTRACT FROM AUTHOR]

In this study, we evaluated the antibacterial effect of floating electrode–dielectric barrier discharge (FE-DBD) plasma (1.1 kV, 43 kHz, N2 1.5 m/s, 1–60 min) against Staphylococcus aureus and Salmonella Typhimurium in fried fish paste. In addition, a quality evaluation (pH, VBN) of fried fish paste was conducted after the FE-DBD plasma treatment. When FE-DBD plasma was used for treatment for 1, 5, 10, 20, 30, and 60 min, S. aureus decreased by 0.16–1.13 log10 CFU/g, and S. Typhimurium decreased by 0.25–1.13 log10 CFU/g. Both decreased > log10 CFU/g at 60 min. The D-value was 58.92, and R2 was 0.97 for S. aureus using first-order kinetics, and the D-value was 43.60, and R2 was 0.97 for S. Typhimurium using the Weibull model. There was no significant difference in pH after the FE-DBD plasma treatment (p > 0.05). Additionally, volatile basic nitrogen (VBN) significantly decreased as the treatment time increased (p < 0.05), and it was the lowest 3.46 at 60 min. Therefore, this FE-DBD plasma treatment could be considered a technology for preserving the quality of processed foods. [ABSTRACT FROM AUTHOR]

Quasi-static tensile tests are commonly used to determine the mechanical properties of fiber bundles. These tests are generally carried out at a low standard speed of 1 mm.min−1, which is recommended for elementary fibers, although other moderate and high speeds are rarely used. In this study, tensile tests were carried out on coir and sisal fiber bundles from the coastal region of Cameroon using four different speeds: 1, 2, 5, and 10 mm.min−1 to assess mechanical properties. Samples were prepared by attaching the two ends of each randomly selected fiber bundle to a paper frame to obtain a length of 30 mm. The results showed a significant effect of extension speed, indicating a decrease in tensile strength and Young's modulus, and an increase in strain at break with increasing speed. These trends were correlated with the power functions. A strong dependence between fiber bundle diameter and tensile strength was also observed. Furthermore, statistical analysis based on the Weibull distribution highlighted the dispersion of mechanical properties, demonstrating a reduction in dispersion with increasing extension speed for coir fibers. These data can be used to develop specific standards for these natural fibers and contribute to the advancement of composites based on plant fibers. [ABSTRACT FROM AUTHOR]

ObjectiveThis study aimed to clarify the heat inactivation mechanics of Salmonella in commercial crispy meat and provide guidance for its safe consumption by studying the inactivation pattern of Salmonella in crispy meat at different heating temperatures.MethodsThe crispy meat inoculated with 108 CFU/g Salmonella typhimurium was heat treated at 80 ℃， 90 ℃， 100 ℃， 110 ℃， and 120 ℃ for a certain time. The thermal inactivation curves of Salmonella in crispy meat were fitted using a linear model， a Logistic model， and a Weibull model， and the optimal model was verified by external experiments.ResultsThe results showed that compared with the linear model and the Logistic model， the Weibull model was more suitable to describe the thermal inactivation of Salmonella in crispy meat. The judgment coefficient R2 of the primary model was more than 0.992 1， and the R2 of the secondary model was 0.949 2 and 0.995 9， respectively. The accuracy Af and deviation Bf of the model verified at 95 ℃ and 105 ℃ were within the acceptable range， which indicated that the model constructed in this experiment can better describe the inactivation pattern of Salmonella in crispy meat in the temperature range of 80 ℃-120 ℃.ConclusionThis study is expected to guide the safe heating of crispy meat to reduce microbial risk during consumption.

In view of the problems of short storage periods, high cost, and high energy consumption in low-temperature storage and controlled atmospheric storage of garlic sprouts, pulsed vacuum drying (PVD) technology was applied in this study for improving the commodity value and reducing the storage cost of garlic sprouts. The drying characteristics and quality attributes of garlic sprouts at different temperatures (65, 70, and 75 °C) and pulsing ratios (2:4, 3:4, 4:4, 3:2, and 3:6) based on the different heating techniques of infrared radiation (FIR-PVD) and electronic panel conduction (EPC-PVD) were investigated. The results showed that EPC-PVD shortened drying time by 11.45–24.94% compared with FIR-PVD, while FIR-PVD achieved better quality in terms of color and allicin retention as compared with EPC-PVD. Prolonging the vacuum duration and reducing the atmospheric pressure duration were helpful in the formation of porous structures, thus obtaining a faster drying rate and better product quality. The Weibull model could precisely describe the drying kinetics of garlic sprouts. FIR-PVD at 75 °C and 3:4 was recommended as the most suitable drying condition due to the highest comprehensive score (0.7856) considering drying time and product quality. The findings provide a new idea for low carbon high-quality storage of garlic sprouts. [ABSTRACT FROM AUTHOR]

Control charts with conditional expected value (CEV) can be used with novel statistical techniques to monitor the means of moderately and lowly censored data. In recent years, machine learning and deep learning have been successfully combined with quality technology to solve many process control problems. This paper proposes a residual control chart combining a convolutional neural network (CNN) and support vector regression (SVR) for type-I censored data with the Weibull model. The CEV and exponentially weighted moving average (EWMA) statistics are used to generate training data for the CNN and SVR. The average run length shows that the proposed chart approach outperforms the traditional EWMA CEV chart approach in various shift sizes and censored rates. The proposed chart approach is suitable to be used in detecting small shift size for highly censored data. An illustrative example presents the application of the proposed method in an electronics industry. [ABSTRACT FROM AUTHOR]

The disintegration of red-bed mudstone is likely affected by the environment. Acid rain can significantly influence the disintegration process, but the corresponding mechanism remains to be studied. In this paper, the evolution of red-bed mudstone disintegration breakage was characterized through a static disintegration experiment under pH values ranging from 1.0 to 7.0 over 10 dry–wet cycles. Characteristics of the particle disintegration evolution in different acidic environments were expounded considering six disintegration indexes: the decay ratio, fractal dimension, particle gradation, grading entropy, disintegration ratio and relative breakage. Moreover, an evolution model of red-bed mudstone disintegration breakage was established based on the Weibull model with the shape (m) and slope (n) of the particle size distribution curve. With regard to the physical properties of the parameters, m and n represent the particle size of the mudstone particles most likely to disintegrate and the disintegration rate of the mudstone, respectively. The grading entropy was used to quantitatively characterize the degree of disorder and disintegration evolution of particles, which exhibited a downwards trend with an increasing number of dry–wet cycles and solution acidity. The disintegration ratio was applied to quantify the particle size distribution, which was then amended by replacing the initial gradation curve with the Weibull evolution model. The disintegration ratio was negatively correlated with both the number of cycles and solution acidity. Finally, relative breakage was proposed to describe the extent of rock disintegration under different dry–wet cycles, which was positively correlated with the number of cycles and solution acidity. The applicability of the Weibull model was verified via a comparison to the fractal model, and a three-segment fitting method based on three particle size groups was proposed to improve the fitting coefficient values of the fractal model. [ABSTRACT FROM AUTHOR]

Several new acceptance sampling plans using various probability distribution methods have been developed in the literature. However, there is no published work on the design of new sampling plans using trigonometric-based probability distributions. In order to cover this amazing and fascinating research gap, we first introduce a novel probabilistic method called a new modified cosine-G method. A special member of the new modified cosine-G method, namely, a new modified cosine-Weibull distribution, is examined and implemented. The density function of the new model possesses symmetrical as well as asymmetrical behaviors. The usefulness and superior fitting power of the new modified cosine-Weibull distribution are demonstrated by analyzing an asymmetrical data set. Furthermore, based on the new modified cosine-Weibull distribution, we develop a new repetitive acceptance sampling strategy for attributes with specified shape parameters. Finally, a real-world application is presented to illustrate the proposed repetitive acceptance sampling strategy. [ABSTRACT FROM AUTHOR]

Copyright of Modern Food Science & Technology is the property of Editorial Office of Modern Food Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)