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This study aimed to examine how varying concentrations (0.5%, 1.0%, 2.0%, 3.0%, and 4.0%) of nano-L-α phosphatidylcholine (nano-L-α-PC) affected the quality of post-thawed buffalo bull semen compared to the same concentrations of L-α-phosphatidylcholine (L-α-PC), while 20% egg yolk (EY) was used as a control. Ejaculates (n = 72) were collected from fertile buffalo bulls (n = 12) for 6 weeks. The ejaculates were pooled and divided into 11 groups (3 aliquots per group) extended with 20% EY (Group 1 without supplement), 0.5%, 1.0%, 2.0%, 3.0%, and 4.0% nano-L-α-PC (Groups 2–6), and 0.5%, 1.0%, 2.0%, 3.0%, and 4.0% L-α-PC (Groups 7–11) in tris buffer. After cryopreservation procedures, semen samples were thawed at 37 °C and then evaluated for sperm kinematics, acrosomes, plasma membranes, and DNA integrities. The seminal plasma was analyzed for malondialdehyde (MDA), superoxide dismutase (SOD), glutathione reduced (GSH), and catalase (CAT). Results demonstrated that extended semen samples containing 1.0-3.0% nano-L-α-PC and 1.0-4.0% L-α-PC showed high total motility compared to control, whereas at 0.5–4.0% of nano-L-α-PC and L-α-PC showed high progressive motility. Significant (P< 0.05) wobble levels were seen at 0.5, 1.0, and 3.0% nano-L-α-PC, and distance average path and velocity average path at 2.0% L-α-PC. Acrosome and plasma membrane integrities were markedly elevated (P< 0.0001) at 2.0% nano-L-α-PC and 4.0% L-α-PC. High DNA integrity metrics were noticed at 0.5–1.0% nano-L-α-PC, as well as 3.0% and 4% L-α-PC. Low MDA and high (SOD, GSH, and CAT) levels were observed at 2.0% nano-L-α-PC and 4.0% L-α-PC. In conclusion, the optimum concentration of nano-L-α-PC that improved semen quality was 2.0%, which is roughly equivalent to the effect of 4.0% L-α-PC.

Introduction The uncinate process (UP) is the most important and constant landmark in the ostiomeatal complex and the middle meatus.

Abstract Background Nonalcoholic steatohepatitis (NASH) is a severe form of nonalcoholic fatty liver disease (NAFLD) characterized by damage and inflammation of hepatocytes. Some medicinal plants have shown antioxidant and anti-inflammatory effects on liver cells. We aimed to investigate the hepatoprotective effect of Heptex® capsules containing 200 mg of Dukung Anak (a powdered extract from aerial parts of Phyllanthus niruri) and 100 mg of Milk Thistle (a powdered extract from fruits of Silybum marianum) in patients with an apparent risk factor for NASH. Methods This was a phase II, randomized, double-blind, placebo-controlled, three-arm, interventional clinical trial. Patients were randomized in a 1:1:1 ratio to receive placebo, low dose (one capsule) of Heptex®, or high dose (two capsules) of Heptex®. After 36 weeks, liver enzymes, Fib-4 score, lipid profile, CAP score, and kPa score were evaluated. Patients were monitored for safety throughout the treatment duration. Results A total of 146 patients were enrolled in the study. A significant decrease was observed in ALT levels in the low-dose group (57 IU/L to 40 IU/L, p = 0.026) and the high-dose group (61 IU/L to 47.5 IU/L, p

Abstract Strontium isotope (87Sr/86Sr) analysis with reference to strontium isotope landscapes (Sr isoscapes) allows reconstructing mobility and migration in archaeology, ecology, and forensics. However, despite the vast potential of research involving 87Sr/86Sr analysis particularly in Africa, Sr isoscapes remain unavailable for the largest parts of the continent. Here, we measure the 87Sr/86Sr ratios in 778 environmental samples from 24 African countries and combine this data with published data to model a bioavailable Sr isoscape for sub-Saharan Africa using random forest regression. We demonstrate the efficacy of this Sr isoscape, in combination with other lines of evidence, to trace the African roots of individuals from historic slavery contexts, particularly those with highly radiogenic 87Sr/86Sr ratios uncommon in the African Diaspora. Our study provides an extensive African 87Sr/86Sr dataset which includes scientifically marginalized regions of Africa, with significant implications for the archaeology of the transatlantic slave trade, wildlife ecology, conservation, and forensics.

This study utilized machine learning models to predict the discharge coefficient for a sharp-crested triangular side orifice (TSO). The chosen models were the Artificial Neural Network (ANN) and Gene Expression Programming (GEP). Development of the models was based on 570 experimental datasets, with 70% allocated for training and the remaining 30% for testing. Five nondimensional parameters were utilized as inputs for the models, including TSO’s crest height to its height (W*=W/H), main channel width to TSO’s base length (L*=B/L), main channel width to TSO’s height (H*=B/H), upstream flow depth to the TSO’s height (Y*=y1/H), and upstream Froude number of the main channel (Fr). While the discharge coefficient (Cd) was defined as the output. Then, the developed models were evaluated by three performance metrics, violin boxplots, and Taylor diagrams to ensure their reliability and accuracy. Furthermore, a sensitivity analysis was conducted to indicate the most effective parameter affecting the Cd value. The findings revealed that both models predicted very well compared to the actual values, with the ANN model emerging as the most reliable predictor. It exhibited the highest determination coefficient (R2), nearing 1, along with the lowest Mean-Square-Error (MSE) and Mean-Absolute-Error (MAE) values, both close to zero. The sensitivity analysis highlighted that the orifice crest height and Froude number significantly impacted the Cd value, contributing to more than 36%. In addition, the predicted discharge coefficient stayed within the range of ± 5.0% of the experimental values. Finally, the developed models demonstrated a high level of equivalence compared to previous studies, especially the ANN model. Therefore, these models are recommended as accurate, robust, and rapid tools to predict the TSO’s discharge coefficient.

Purpose The present study aimed to determine the serum level of asprosin, a novel glucogenic and orexigenic hormone, in NAFLD and hypothyroidism patients.Methods This is a case–control study that included three groups of age and sex-matched subjects: hypothyroid patients with NAFLD (n = 26), hypothyroid patients without NAFLD (n = 25) and normal control subjects (n = 27). A detailed clinical history was obtained, and an examination was performed. Laboratory tests included fasting plasma glucose and insulin, lipid profile, TSH, free T4, AST, ALT, albumin, and asprosin. The homeostatic model assessment of insulin resistance (HOMA-IR) score was calculated. Abdominal ultrasonography was performed to calculate the hepatorenal index and define participants with NAFLD. The data were statistically analyzed.Results There was a statistically significant difference between the three groups regarding serum asprosin concentration (p

Abstract Background Virtual Community of Practices (VCoP) simply is a method to use social media in extension, yet its roots depend on a combination of four concepts: community of practice, social media, social learning theory, and pluralistic extension. The technical action research design was followed to put the VCoP into action and explore its profile. This study aimed to introduce a community of practice using social network applications to policy makers in the agricultural sector. Methodology Action research was conducted to validate the use of a VCoP in the National Campaign of Wheat in Egypt. A baseline survey, a content analysis of VCoP conversations, and an assessment study were used to collect the data. The frequency, range, percentage, mean, and average score were used for statistical analysis. Results The VCoP reached 22.22% and 10.40% of the wheat farmers in the two target villages, respectively. A high degree of knowledge exchange was detected among members, while messages crossed the VCoP borders as friends were invited to join the group. The VCoP helped its members establish new relationships with other stakeholders, and they expressed their need to expand membership to include other stakeholders. The media used in the VCoP was satisfactory; however, the need for more video messages and internet links was expressed. Extension agents believe that the VCoP complements other extension methods. Farmers see greater potential for cooperation than conflict, while bias is minimal among research, extension, traders, and company agents. Conclusions Farmers and other service providers in a village can be aggregated in a VCoP. This approach has proven to be valid as an extension community method for generating and sharing information with high “reach”. Coordination and training are essential for running and managing groups. Yearly programs, rather than seasonal programs, are more suitable for sustainability.

Generalized Bayesian (GB) is a Bayesian approach based on the learning rate parameter (LRP) ($ 0 < \eta < 1 $) as a fraction of the power of the likelihood function. In this paper, we consider the GB method to perform inference studies for a class of exponential distributions. Generalized Bayesian estimators (GBE) and generalized empirical Bayesian estimators (GEBE) for the parameters of the considered distributions are obtained based on the censored type Ⅱ samples. In addition, generalized Bayesian prediction (GBP) and generalized empirical Bayesian prediction (GEBP) are considered using a one-sample prediction scheme. Monte Carlo simulations and illustrative example are performed for one parameter models to compare the performance of the GBE and GEBE estimation results and the GBP and GEBP prediction results for different values of the LRP.

We investigated certain properties of cumulative entropy related to the lifetime of consecutive $ k $-out-of-$ n $:F systems. First, we presented a technique to compute the cumulative entropy of the lifetimes of these systems and studied their preservation properties using the established stochastic orders. Furthermore, we derived valuable bounds applicable in cases where the distribution function of component lifetimes is complex or when systems consist of numerous components. To facilitate practical applications, we introduced two nonparametric estimators for the cumulative entropy of these systems. The efficiency and reliability of these estimators were demonstrated using simulated analysis and subsequently validated using real data sets.

Meckel's diverticulum, a congenital anomaly of the omphalomesenteric duct, is a rare cause of acute abdomen and poses significant diagnostic challenges due to its variable presentation and complications such as perforation. We present the case of a 19-year-old male with a 24-hour history of right iliac fossa pain progressing to generalized abdominal tenderness. Laboratory results showed leukocytosis and elevated C-reactive protein, while CT imaging suggested pneumoperitoneum and an inflamed Meckel diverticulum. Laparoscopic exploration, followed by conversion to laparotomy, confirmed a perforated Meckel diverticulum, which was resected with an uneventful recovery. This case highlights the importance of including Meckel's diverticulum in the differential diagnosis of acute abdomen in young patients, emphasizing the utility of CT imaging and the need for prompt surgical intervention to achieve favorable outcomes.

Background/purpose: Exploration of early practicing dental professionals' awareness and attitude toward inferior alveolar nerve block IANB will directly inform efforts to improve clinical practices and ensure patient safety. The aim was to highlight the students, interns, and junior dentists’ awareness and attitude toward the IANB, failure, and related complications in the Kingdom of Saudi Arabia (KSA). Materials and methods: An open web-based survey prepared according to the Checklist for reporting results of Internet e-surveys CHERRIES recommendations was designed and carried out across different regions of the KSA. The questionnaire was composed of four main sections including the participant's details, and qualifications; inferior alveolar nerve block delivery; participants' education, and training-related questions; and attitudes toward proposed solutions to overcome the related failure and complications. Results: 262 participants completed the questionnaire (94 dental students, 79 interns, and 89 junior dentists). There was a significant difference in the following findings: males performed IANBs more frequently than females (P

Abstract Deep eutectic electrolytes (DEEs) show promise for future electrochemical systems due to their adjustable buffer capacities. This study utilizes machine learning algorithms to analyse the carbon dioxide reduction reaction (CO2RR) in DEEs with a buffer capacity of approximately 10.21 mol/pH. The objective is to minimize undesired hydrogen evolution reactions (HER) and render CO2RR dominant in a membrane cell. The CO2RR process was found to be non-adiabatic, as the time of nuclear motion for CO3 2− in K2CO3 product, through CO2 ●− trapping, is 0.368 femtoseconds shorter than the 1.856 × 10−3s charge transfer relaxation time. Microkinetic analysis reveals that the rate of CO2RR to CO2 ●− is 2.14 × 103 mol/cm2/s2 with a rate constant of 2.1 × 1010 cm/s. Our findings demonstrate that ensemble and k-Nearest Neighbours algorithms learn the CO2RR dataset, achieving a prediction accuracy of over 99%. The models were verified visually and quantitatively by overlaying predicted and experimental dataset. Diagnostic and SHAP analyses highlighted the gradient boost ensemble algorithm, predicting asymptotic current densities of -4.114 mA/cm2 or -13.340 mA/cm2, with high turnover frequencies (TOF) of 3.79 × 1010 h-1 or 12.30 × 1010 h-1 for CO2 ●− or K2CO3 generation on silver electrodes, respectively. These results consider both accuracy and robustness against overfitting, providing an opportunity to optimize future non-aqueous electrolytes for convenient TOF measurements at industrially relevant current densities.

In most lifetime models, the bivariate -quantile inactivity time is a vector of increasing functions. A novel estimator of this vector was created and investigated under this assumption. It was expected that the application of this knowledge would improve the efficiency of the estimator. It was proven that the proposed estimator is consistent and converges weakly to a bivariate Gaussian process under a suitable transformation. A simulation study was conducted to compare the performance of the proposed estimator with that of the usual estimator. Finally, the application of the proposed estimator is illustrated by analyzing a dataset comprising the time to blindness in patients with diabetic retinopathy.

In this paper, we focus on two relative aging classes, namely increasing (decreasing) relative failure rate and increasing (decreasing) failure rate relative to average failure rate. We studied some reliability properties and connections with other classes of lifetime distributions. The main objective of this paper was to investigate the preservation properties of decreasing relative failure rate class and decreasing failure rate relative to average failure rate class under the structure of ($ n-k+1 $)-out-of-$ n $ system. We give some examples of parametric distributions to evaluate the correctness of the results.

Abstract Background Epigenome‐wide association studies have identified multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. This study aimed to test the hypothesis that an alcohol consumption epigenetic risk score (ERS) is associated with blood pressure (BP) traits. Results We implemented an ERS based on a previously reported epigenetic signature of 144 alcohol-associated CpGs in meta-analysis of participants of European ancestry. We found a one-unit increment of ERS was associated with eleven drinks of alcohol consumed per day, on average, across several cohorts (p

To investigate potentially dependent lifetimes, it is necessary to extend the $ \alpha $-quantile inactivity time to bivariate and multivariate frameworks. To extend this measure to a dynamic multivariate framework, all possible trajectories at time $ t $ are considered. The behavior of the extended $ \alpha $-quantile of inactivity time was investigated in relation to the corresponding multivariate hazard rate function. The $ \alpha $-quantile of the inactivity order is defined and discussed for the multivariate case. The difference between the two bivariate $ \alpha $-quantile functions of inactivity, which is an important measure for studying the effect of treatment on lifespan, was also investigated. This measure was used to analyze the effect of laser treatment on the delay of blindness. Two bootstrap approaches were implemented to construct confidence bounds for the difference measure.

Abstract In this paper, we prove that under weak assumptions on the reaction terms and diffusion coefficients, a positive solution exists for a one-dimensional case and a positive radial solution to a multidimensional case of a nonlocal elliptic problem. Additionally, we establish the uniqueness of the solution, with the fixed point theorem being the primary tool employed. Our results are new and generalize several existing results.

Abstract This paper studies some stochastic properties of random quantiles according to the newly defined reliability measure called reversed aging intensity function. Preservation property of reversed aging intensity order under random quantile is obtained and using it, a lower bound and an upper bound for the reversed aging intensity function of a random quantile are derived. Preservation of two related monotonic reliability classes under random quantiles is also studied. We finally apply our results for reliability analysis of series systems with heterogeneous component lifetimes. Examples are included to examine and analyze the obtained results.

Purpose The current study aimed to examine the acute effect of physioball wall squat training on knee joint active reposition senses and isokinetic parameters of knee flexion and extension in sedentary collegiate female students. Methods An experimental study was conducted with sixty sedentary female college students aged between 18 to 25 who were divided into two groups. The experimental group of 30 participants performed Swiss ball wall squats, spanning three sets of 12 repetitions each, with 30-second rest intervals between sets. The control group of 30 participants stood with a Swiss ball positioned behind their backs, replicating the same parameters as the experimental group but without squatting. The isokinetic 4 Pro device measured active knee joint repositioning senses and isokinetic parameters of knee flexion and extension. Results The findings revealed notable improvements in active knee repositioning senses and all isokinetic parameters of knee flexion and extension ( p < 0.05) in the experimental group post-training when compared to the control group. There were also significant differences detected between pre- and post-Swiss ball training intervention in the experimental group for all variables ( p < 0.05). Conclusions These results suggest that Swiss ball wall squat training could enhance knee joint position senses and isokinetic parameters, potentially reducing knee injuries in sedentary individuals.

Abstract This article investigates the behavior of hybrid FRP Concrete-Steel columns with an elliptical cross section. The investigation was carried out by gathering information through literature and conducting a parametric study, which resulted in 116 data points. Moreover, multiple machine learning predictive models were developed to accurately estimate the confined ultimate strain and the ultimate load of confined concrete at the rupture of FRP tube. Decision Tree (DT), Random Forest (RF), Adaptive Boosting (ADAB), Categorical Boosting (CATB), and eXtreme Gradient Boosting (XGB) machine learning techniques were utilized for the proposed models. Finally, these models were visually and quantitatively verified and evaluated. It was concluded that the CATB and XGB are standout models, offering high accuracy and strong generalization capabilities. The CATB model is slightly superior due to its consistently lower error rates during testing, indicating it is the best model for this dataset when considering both accuracy and robustness against overfitting.

This paper explored the concept of past Rényi entropy within the context of $ k $-record values. We began by introducing a representation of the past Rényi entropy for the $ n $-th lower $ k $-record values, sampled from any continuous distribution function $ F, $ concerning the past Rényi entropy of the $ n $-th lower $ k $-record values sampled from a uniform distribution. Then, we delved into the examination of the monotonicity properties of the past Rényi entropy of $ k $-record values. Specifically, we focused on the aging properties of the component lifetimes and investigated how they impacted the monotonicity of the past Rényi entropy. Additionally, we derived an expression for the $ n $-th lower $ k $-records in terms of the past Rényi entropy, specifically when the first lower $ k $-record was less than a specified threshold level, and then investigated several properties of the given formula.

Understanding the impact of obstacles on lid-driven cavity (LDC) flows is critical for advancing flow control and optimization in fluid dynamics. In this study, we numerically investigate steady, two-dimensional Newtonian fluid flow within a square cavity featuring a lid-driven motion at Reynolds number Re = 100 by solving governing equations with the Fractional Step Method on a staggered grid in the Finite Volume framework, providing high-resolution streamline plots and vorticity contours. A rectangular obstacle with a fixed width (W = 0.2L) and varying heights (H = 0.20L,0.25L,0.50L,0.60L,0.80L and 0.95L) is systematically placed in three configurations: 1) bottom left-corner, 2) bottom right-corner and 3) both bottom (left–right) corners. The study investigates the influence of obstacle placement and height on kinetic energy (KE), enstrophy (Z), and palinstrophy (P) as well as obstacles focusing on the modulation of primary (PV) and secondary (SV) vortices, energy metrics, and flow topology in lid-driven cavity (LDC) flows, focusing on configurations with single and double corner. Fluid motion control in constrained environments, such as industrial mixing where vortex dynamics in lid-driven cavities optimize mixing and reduce dead zones by adjusting obstacle configurations and heat transfer, demands a detailed understanding of energy dissipation and rotational dynamics. The physics involved in KE and vortex dynamics is that increasing obstacle height progressively reduces the kinetic energy across all configurations, with the sharpest decline (38 %) observed in dual-corner obstacles due to amplified flow constriction and enhanced boundary layer effects. Single-corner obstacles disrupt the flow asymmetrically, whereas dual-corner setups create balanced but more confined vortex structures, impacting energy distribution and flow control. In rotational energy (Z) and gradient intensities (P), dual-corner obstacles induce the highest rotational energy (192 % increase in Z) and vorticity gradients (127 % increase in P), revealing the interplay of sharp edges, shear layers, and enhanced vortex interactions. These features emphasize the potential for intensified mixing but also highlight the risks of energy dissipation in constrained environments. In flow structure transformations, obstacle-induced changes in streamline topology reveal critical transitions in vortex formation and interaction. In dual-corner configurations, secondary vortices coalesce into a single dominant structure at critical heights say at H = 0.50L, leading to a dramatic 1366.92 % increase in vortex area. However, excessive heights (H = 0.95L) suppress these vortices, creating stable but inefficiently mixed flow regimes. In addition, we discovered a new empirical relation among Pressure potential energy (PE) in three configurations for the steady-state solution and it can be generalised and holds for any positive reals H and W up to almost near 1L and 0.50L respectively. Also, the flow separation, reattachment with their locations of the formation and diminishing of tertiary vortices above the corner obstacles were captured and analysed.

Peristaltic movement of Ellis liquid with entropy effects through asymmetric propagating channel waves is discussed in this attempt. Slip effects of momentum, thermal and concentration are taken at channel walls. Transfer of heat and mass phenomenons are examined by considering the effects of viscous dissipation, chemical reaction and Soret. Entropy generation is discussed in the presence of irreversibilities due to fluid friction and heat and mass transfer. Flow equations are modeled using fixed frame of reference and then simplified these equations via long wave length and low Reynolds approximations. Here solution for the system of simplified equations are obtained in terms of series for small material parameter. With the help of obtained solutions flow quantities behavior is plotted against sundry dimensionless quantities.

This article explores how government organizations in Egypt, Tunisia, and Jordan use Facebook (FB) to advocate for the United Nations Sustainable Development Goal 5 (SDG 5). Guided by the Dragonfly Advocacy Model for evaluating social media advocacy and using CrowdTangle for FB content analysis, researchers analyzed advocacy efforts over eight and a half years, nearly midway through the planned implementation timeframe of the SDGs. Findings show that the SDG 5 targets most advocated by all three countries were those for women’s empowerment, eliminating violence, ending child marriage, and Female Genital Mutilation (FGM). “Reproductive health,” “technology,” and “unpaid work”’ were among the lowest-mentioned terms. Videos, animation, and influencers were key factors contributing to the effectiveness of FB posts. Gender inequities identified in these Middle Eastern countries, like FGM, honor killings, and inheritance rights, stood in contrast with Western concerns about abortion rights, access to contraception, flexible work arrangements, and digital inclusion.

The concept of α-quantile inactivity time was developed for situations with bivariate or multivariate random lifetimes. In this situation, each element has a specific history related to itself, indicating that the corresponding event occurred earlier. The behavior of the α-quantile inactivity time was specifically studied in relation to the corresponding multivariate hazard rate function. Applying the empirical bivariate distribution function, an estimator for the bivariate α-quantile inactivity time function is introduced. The asymptotic properties of the empirical distribution function and Taylor expansion are used to discuss its asymptotic behavior. Subsequently, the behavior of the proposed estimator was investigated in a simulation study. Finally, the applicability of the proposed concept and its estimator is illustrated by analyzing a dataset in the context of medical sciences.

In this work, energy harvesting from a proposed three-mode T-shaped structure, composed of a vertical beam, two horizontal beams, a center mass, and tip masses, is investigated to expand the frequency bandwidth for energy harvesting, without compromising the power density due to the additional mass of the structure, as is the case with most multi-mode harvesters. The aim is to cleverly use and position the additional mass to help induce higher and more uniform strain levels throughout the piezoelectric patch, leading to greater power generation to help counteract the added mass. A numerical model was developed to analyze the structure, to obtain voltage and power frequency responses, taking into effect the load resistance modeling and the accurate evaluation of resonance peaks by estimating each mode damping ratio. The validity of the model was confirmed by comparisons with previous experiments involving other structures, which demonstrated strong agreement. The excitation load was strategically applied to induce maximum displacement of the center and tip masses relative to the fixed ends in each mode. The outcomes reveal that the T-shaped configuration exhibits the capacity to generate higher maximum strain and a more uniform strain distribution across the piezoelectric patch when compared to previous L-shaped and traditional cantilever harvesters' designs. These characteristics yielded a power density higher than that of the L-shaped structure by approximately 70% with only around 20% addition in structure mass. Additionally, the multi-mode T-shaped structure boasts a significantly broader harvesting bandwidth due to the additional mode, without compromising power density, as was the case with L-shaped structures. Furthermore, the positioning of the tip mass was systematically altered to assess its impact on the frequency bandwidth and power output of the horizontal and vertical beams in the three bending modes, demonstrating great robustness and tuning capabilities.

GEO satellites require precise station-keeping and ensuring collision avoidance to maintain their desired orbital positions and ensure uninterrupted communication services. However, maneuvering these satellites poses significant challenges due to various geophysical factors and orbital perturbations. This work proposes a model predictive control for planned maneuver station-keeping and collision avoidance of GEO satellites using south, east, and west maneuvers. These maneuvers have been achieved using on/off chemical thrusters with a short firing time. The station-keeping problem is reformulated as an optimization problem using mixed-integer linear programming. MILP-MPC formulation simultaneously considers multiple objectives and constraints such as fuel consumption, maneuver planning, and collision avoidance for mitigating collision risks. Simulation results demonstrate the effectiveness of the proposed MILP-MPC framework compared to the real-time telemetry in achieving accurate station-keeping and collision-free operation while optimizing fuel consumption. The proposed controller increases the satellite lifetime by reducing the thruster firing time.

Introduction: Outcome of shelf acetabuloplasty in management of late onset Perthes’ disease can be affected by shelf resorption and inadequate femoral head containment. Various agents have been tried to enhance bone graft incorporation and reduce its resorption. The aim of this study was to assess whether Osteoset® (calcium sulphate pellets) can stimulate autogenous bone graft incorporation and prevent bone resorption after shelf acetabuloplasty for Perthes’ disease and whether its use can improve femoral head remodelling. Methods: Thirty-two children with Perthes’ disease who underwent shelf acetabuloplasty were divided into two groups. In 15 patients (study group) Osteoset (10 ml) mixed with autogenous bone grafts to create extra ‘shelf’ over deficient acetabulum was used. Seventeen patients who served as a control group were managed by shelf acetabuloplasty using autogenous bone graft without Osteoset. Both groups were similar with regards to age and severity of the condition. The mean age at operation was 9 years and 4 months. The mean follow-up was 53.3 and 61.5 months for Osteoset and control groups, respectively, when all patients reached skeletal maturity. On serial radiographs shelf area, extra-osseous shelf length, acetabular coverage and graft incorporation and femoral head sphericity were assessed. Results: Immediately post-operatively the shelf area and shelf length were similar in both groups. From 6 weeks post-operatively and thereafter shelf area and shelf length were significantly better in patients from the study (Osteoset) group. Patients from the control group showed a steady decline in graft area throughout the follow-up period. Graft incorporation was also faster in the Osteoset group. However, femoral head sphericity assessed by Stulberg classification was similar in both groups. Conclusion: Osteoset pellets improve graft volume, encourage earlier graft incorporation and inhibit later shelf resorption. Adding Osteoset does not improve femoral head remodelling following shelf acetabuloplasty for Perthes’ disease.

The use of carbonated mineral products in cement production reduces carbon emissions and enhances durability. This study evaluated the environmental sustainability of using mineral carbonated biomass fly ash (BFA) as a partial cement replacement in European cement production. Laboratory-scale and simulated large-scale scenarios were analysed. Incorporating 20% mineral carbonated BFA showed potential for a 33% reduction in the annual Global Warming Potential (GWP) of cement products. Energy consumption factors, such as ball milling and mineral carbonation processes, were evaluated using a machine learning model and comminution flow sheet model simulations. The machine learning model predicted CO2 absorption and energy requirements for mineral carbonation, showing greater efficiency in large-scale scenarios. Life cycle assessments consistently revealed GWP reductions for OPC-BFA mixtures, with additional emissions reductions when incorporating flow sheet modelling and machine learning data. However, the study's limitations include simplified CO2 flue gas treatment, use of the mean EU electricity mix, exclusion of transportation impacts, and reliance on simulation data. Additionally, the cement mix exhibited reduced compressive strength. This study highlights the potential of mineral carbonated BFA to reduce cement production's environmental impact while emphasising the need for balanced optimisation between sustainability and material performance.

Inflammatory fibroid polyps (IFPs) are rare submucosal lesions that usually arise in the stomach. It represents 0.1% of all gastric polypoid lesions and are frequently asymptomatic. It’s usually revealed by an abdominal pain. Gastrointestinal bleeding can occur when the polyp is ulcerated. We report a case of a 72-year-old female with an IFP of the prepyloric region. The head of the polyp was thirty-five millimeters in diameter. It was revealed by an upper gastrointestinal bleeding and epigastric pain. An endoscopic resection was performed.

In recent years, the remarkable photoelectric properties exhibited by perovskite materials have stimulated scientific inquiry, prompting investigations into novel perovskite variants and derivatives characterized by environmentally friendly attributes and robust stability. These materials offer potential as efficient solar light harvesters. Our study concentrates on elucidating the structural, electronic, and optical properties of the newly discovered stable lead-free double perovskite K2AgSbBr6, employing first-principles methods rooted in Density Functional Theory (DFT). We confirm the structural and dynamical stabilities of K2AgSbBr6 through computational analysis. Our calculations reveal that the examined compound exhibits characteristics of an indirect semiconductor, with a band gap of 0.857 eV (L-X). Notably, our findings demonstrate that the compound displays enhanced photovoltaic performance, as evidenced by elevated optical absorption coefficients exceeding 105 cm−1, surpassing those of CH3NH3PbI3. These results underscore the potential of K2AgSbBr6, a novel lead-free double perovskite, as a promising candidate for exceptional light-absorbing material spanning the UV and visible spectra.

This study addresses the pressing need for the Norwegian fishery sector to align with national reduction targets and mitigate its environmental impact. Norway has committed to reducing GHG emissions from the fishery sector by at least 40% by 2030 and 95% by 2050. We propose a mathematical model designed for the strategic renewal of the Norwegian fishing fleet by introducing low- and zero-emission propulsion systems. This model generates fleet renewal schedules that minimize the total operational and renewal costs while ensuring compliance with emission targets. We apply our model to a case study based on the Norwegian fishing fleet and determine the optimal decarbonization strategy. We then analyze the impact of changes in energy costs and emission taxes on this strategy through a sensitivity analysis Our results indicate that (1) fleet renewal is mainly driven by the emission reduction targets, rather than economic benefits, and (2) zero-emission propulsion systems are preferable to low-emission propulsion systems when decarbonizing the fleet.

This study presents a novel and sustainable method for integrating octadecane phase change material (PCM) into traditional building materials like mortar and gypsum using vacuum-impregnated biochar. Optimising the impregnation conditions resulted in a PCM-biochar composite with 62.21 % PCM loading and a latent heat energy of approximately 116.7 J.g−1, as measured by Differential Scanning Calorimetry (DSC). Thermogravimetric Analysis (TGA) confirmed the composite’s stability at high temperatures, while accelerated DSC validated its phase change capability and stability over 300 cycles. Characterisation via Scanning Electron Microscopy (SEM), Small-Angle X-ray Scattering (SAXS), X-ray Diffraction (XRD), and Solid-State Proton Nuclear Magnetic Resonance (1H NMR) verifies PCM retention within biochar pores and reveals interactions between PCM and biochar. Additionally, the non-pozzolanic nature of biochar is confirmed. Workability tests show reduced consistency with increased PCM-biochar content in mortar. At 40 % sand replacement rate with PCM-biochar, the compressive strength initially decreases by 45.50 % after 28 days, but it improves to 43 MPa after 120 days. Gypsum samples retain adequate strength for retrofitting applications (2 MPa), demonstrating the potential of PCM-biochar composites to enhance thermal energy storage in building materials, thereby supporting Net-zero building objectives.

This paper focuses on the study of global existence (in time) of solutions to a weakly coupled system of Cauchy problem for semilinear σk-evolution models with δk-visco-elastic damping. The system consists of two equations, one involving the function u and the other involving the function v. The equations are characterized by a classical power nonlinearity and a derivative-type nonlinearity. The main objective is to investigate the relationship between the regularity assumptions on the initial data and the range of permissible exponents p1 and p2 in the power nonlinearity. The paper considers the system in a spatial domain Rn and a time domain (0,∞), with specific conditions on the parameters σ1, σ2, δ1, and δ2, under the symmetry property as well as the exponents p1 and p2. The initial data (u1,v1) are required to satisfy certain conditions in terms of their integrability and Sobolev regularity.

Salvia officinalis is used in a variety of medicinal and aromatic products. The effects of various treatments on sage (Salvia officinalis) plants were investigated in an open-field experiment conducted between 2021 and 2022. During the experiment, ZnO nanoparticles (NPs) were used at concentrations of 1.0 and 1.5 g/L, SiO2 NPs were used at concentrations of 0.1 and 0.2 g/L, and date palm pollen extracts (DPE) were used at concentrations of 15 and 25 g/L, in combination with NPK fertilizers at 75%, 50%, and 25%, respectively, with a control group of 100% NPK fertilizer. A treatment consisting of 75% NPK, 15 g/L DPE, 1.0 g/L ZnO NPs, and 0.1 g/L SiO2 NPs significantly improved vegetative traits and essential oil yield. Compared to the control in the growing seasons of 2021 and 2022, this treatment resulted in increases in plant height, chlorophyll index, fresh and dry weights, and essential oil yield (EOY) per plant of 23.40% and 28.30%, 27.56% and 26.54%, 42.17% and 42.95%, 64.10% and 62.79%, and 93.38% and 91.08%, respectively. Combinations of 25% NPK + 25 g/L DPE + 1.5 g/L ZnO nanoparticles + 0.2 g/L SiO2 NPs and 75% NPK + 0.1 g/L SiO2 NPs produced the highest essential oil percentage (EO%). During the experimental seasons, these treatments increased EO% by 15.45% and 26.25%. In total, 58 substances were identified across the different treatments in the essential oil composition analysis. There were 11 compounds in the 25% NPK, 25 g/L DPE, 1.5 g/L ZnO NPs, and 0.2 g/L SiO2 NPs treatments, and 32 in the 50% NPK, 25 g/L DPE, and 0.2 g/L SiO2 NPs treatments. Oxygenated hydrocarbons, sesquiterpenes, and monoterpenes varied by application. Thujone, camphor, manool, and ledol were the major constituents of the EO. Leaf chemical composition, antioxidant activity, and total phenolic compounds were significantly influenced by the treatments. In combination with DPE, ZnO and SiO2 NPs reduced the need for higher amounts of mineral NPK fertilizers. These agents can therefore be useful for advancing sustainable agricultural practices in novel and advantageous ways.

This study investigates a complex hybrid flow shop scheduling problem prevalent in the industrial sector, characterized by dedicated machines, availability dates, and delivery times. The primary objective is to minimize the total completion time (makespan) in a two-stage workshop setting. We conducted a comprehensive literature review, revealing a scarcity of research on this specific configuration, and employed the Simulated Annealing metaheuristic as our main resolution method. Special emphasis was placed on the meticulous parameterization and configuration of this metaheuristic, crucial for navigating the complexity of the problem.Our findings demonstrate the remarkable effectiveness of the Simulated Annealing method, particularly in achieving low deviation from the lower bound in larger problem sizes and specific instance classes. This consistency highlights the method’s robustness and suitability for complex scheduling scenarios. The study also reveals varying degrees of problem solvability across different instance classes, with computation times generally reasonable except in more challenging scenarios.

Abstract Concrete compressive strength (CS) is a crucial performance parameter in concrete structure design. Reliable strength prediction reduces costs and time in design and prevents material waste from extensive mixture trials. Machine learning techniques solve structural engineering challenges such as CS prediction. This study used Machine Learning (ML) models to enhance the prediction of CS, analyzing 1030 experimental CS data ranging from 2.33 to 82.60 MPa from previous research databases. The ML models included both non-ensemble and ensemble types. The non-ensemble models were regression-based, evolutionary, neural network, and fuzzy-inference-system. Meanwhile, the ensemble models consisted of adaptive boosting, random forest, and gradient boosting. There were eight input parameters: cement, blast-furnace-slag, aggregates (coarse and fine), fly ash, water, superplasticizer, and curing days, with the CS as the output. Comprehensive performance evaluations include visual and quantitative methods and k-fold cross-validation to assess the study’s reliability and accuracy. A sensitivity analysis using Shapley-Additive-exPlanations (SHAP) was conducted to understand better how each input variable affects CS. The findings showed that the Categorical-Gradient-Boosting (CatBoost) model was the most accurate prediction during the testing stage. It had the highest determination-coefficient (R2) of 0.966 and the lowest Root-Mean-Square-Error (RMSE) of 3.06 MPa. The SHAP analysis showed that the age of the concrete was the most critical factor in the predictive accuracy. Finally, a Graphical User Interface (GUI) was offered for designers to predict concrete CS quickly and economically instead of costly computational or experimental tests.

Abstract Aim of the work The study was conducted to evaluate the influence of theophylline pre-treatment on serum pharmacokinetics and milk elimination of tylosin following single intramuscular (IM) administrations in lactating goats. Methods and results In a cross-over study, tylosin was injected via intramuscular (IM) at a single dose of 15 mg/kg b.wt. After a one-month washout period goats received theophylline at a daily IM dose of 2 mg/kg b.wt. for seven consecutive days then tylosin was injected IM dose of 15 mg/kg b.wt. two hours after the last theophylline dosing. Blood samples were collected before and at 0.25, 0.5, 0.75, 1, 2, 4, 6, 8, 10, 12, and 24 h post-injection. Samples were left to clot and then centrifuged to yield serum. Milk samples were collected before and at 0.5, 1, 2, 4, 6, 8, 10, 12, 24, 48, and 72 h post-injection from each goat by hand milking. Tylosin serum concentrations were determined by high-performance liquid chromatography (HPLC). Tylosin concentrations versus time were analyzed by a noncompartmental method. Tylosin Cmax significantly declined from 1.73 ± 0.10 to 1.01 ± 0.11 µg/ml, and attained Tmax values of 2 and 1 h, respectively in theophylline-pretreated goats. Moreover, theophylline pretreatment significantly shortened the elimination half-life (t1/2el) from 6.94 to 1.98 h, t1/2ka from 0.62 to 0.36 h and the mean residence time (MRT) from 8.02 to 4.31 h, also Vz/F and AUCs decreased from 11.91 to 7.70 L/kg and from 12.64 to 4.57 µg*h/ml, respectively, consequently, theophylline enhanced the clearance (Cl/F) of tylosin from the body. Similarly, tylosin milk concentrations were significantly lower in theophylline-pretreated goats than in goats that received tylosin alone and were detected up to 24 and 72 h in both groups, respectively. Moreover, the t1/2el and AUCs were significantly decreased from 14.68 ± 1.97 to 4.72 ± 0.48 h, and from 181 to 67.20 µg*h/ml, respectively. Conclusions The withdrawal period for tylosin in goat milk is at least 72 h. Theophylline pretreatment significantly decreases serum and milk tylosin concentrations to subtherapeutic levels, which could have serious clinical consequences such as failure of therapy. This means that after administering tylosin to goats, milk from these animals should not be consumed for at least 96 h to ensure that the milk is free from residues of the antibiotic.

In this study, we focused on investigating the properties of residual Tsallis entropy for order statistics. The reliability of engineering systems is highly influenced by order statistics, for example, when modeling the lifetime of a series system and the lifetime of a parallel system. The residual Tsallis entropy of the ith order statistic from a continuous distribution function and its deviation from the residual Tsallis entropy of the ith order statistics from a uniform distribution were investigated. In the mathematical framework, a method was provided to represent the residual Tsallis entropy of the ith order statistic in the continuous case with respect to the case where the distribution was uniform. This approach can provide insight into the behavior and properties of the residual Tsallis entropy for order statistics. We also investigated the monotonicity of the new uncertainty measure under different conditions. An investigation of these properties leads to a deeper understanding of the relationship between the position of the order statistics and the resulting Tsallis entropy. Finally, we presented the computational results and proposed estimators for estimating the residual Tsallis entropy of an exponential distribution. For this purpose, we derived a maximum likelihood estimator.

Ticks play the main role, in veterinary terms, in transmitting important pathogens. Rhipicephalus sanguineus is a widespread tick known for its ability to thrive in indoor environments and could be the main reservoir host for many TBDs. In this study, the acaricidal and larvicidal potential of Rosmarinus officinalis essential oil was evaluated against R. sanguineus. The aerial part of this plant was extracted by hydrodistillation and then analyzed by gas chromatography coupled with mass spectrometry (GC/MS). The yield obtained from this oil was 0.38%, its major chemical compounds were found to be Camphor (43.52%), Eucalyptol (13.66%), and Camphene (13.2%). The adult immersion test (AIT) using four concentrations (1µl/ml,2µl/ml,10µl/ml, 30µl/ml) revealed that this oil presented oviposition reduction percentages of 5.75%, 20.68%, 33.27%, and 46.84%, hatching reductions percentages of 5%, 15%, 35%, and 60%, and efficacy extract percentages of 10.46%, 32.58%, 56.63%, and 78.74% Further, the larval immersion test (LIT) using five concentrations (0.5µl/ml,1µl/ml, 2µl/ml, 3µl/ml, and 5µl/ml) revealed considerable larvicidal activities with LC50 and LC90 values of 2.286 µl/ml and 5.380 µl/ml, respectively. These results are encouraging and open interesting and promising horizons for its application as a bio-acaricide.

A new proportional stochastic order is defined based on the concept of quantile residual life. In addition, a new aging class of life distributions, namely, decreasing proportional failure rate distributions, was defined. Moreover, two other aging classes based on the proposed stochastic ordering are defined and investigated: decreasing proportional α-quantile residual life and its dual increasing proportional α-quantile residual life. The relationship between the proportional failure rate and proportional α-quantile residual life has been discussed. Some well-known and useful models are classified in terms of the proportional α-quantile residual life function. Finally, a new modified Pareto distribution with a decreasing proportional failure rate and an increasing proportional α-quantile residual life function was presented and studied.

Opaque surfaces, such as walls, are well-known for their significant contributions to heat loss and energy demands in buildings. However, transparent surfaces, such as windows, are equally critical to a building's energy performance. The design of these transparent elements requires a careful balance of various factors, including window size, glazing type, and orientation, each of which plays a pivotal role in enhancing energy efficiency. This study explores the optimization of these factors during the design process, emphasizing their impact on the overall building performance.This research evaluates the potential energy savings in a building archetype representative of the Algerian building stock. Utilizing the EnergyPlus simulation tool, the study conducted 1152 simulations on a baseline model to generate a comprehensive dataset detailing the building's energy demands for heating and cooling across various climatic conditions. The findings reveal that annual energy savings for this type of housing essentially depend on its climatic zone and can range from 6.92 % for a hot semi-arid climate (Bsh) to reach a maximum of 9.75 % in a cold semi-arid climate (Bsk), a window-to-wall ratio (WWR) of 60 % typically maximizes energy efficiency, low-E glazing proved most effective in most cases, although regions needing significant solar protection favored alternative glazing types. Optimal window orientation generally trends Eastward, except in regions where southern exposure better supports solar management, highlighting the complex relationship between architectural design choices and energy efficiency.

ABSTRACT: Heat stress induces mitochondrial dysfunction, thereby impeding skeletal muscle development and significantly impacting the economic efficiency of poultry production. This study aimed to investigate the effects of embryo thermal manipulation (TM, 41.5°C, 65% RH, 3 h/d during 16–18th embryonic age) on the mitochondrial function of the pectoralis major (PM) in broiler chickens exposed to thermoneutral (24 ± 1°C, 60% RH) or cyclic heat stress (35 ± 1°C, 60% RH, 12 h/d) from day 22 to 28, and to explore potential mechanisms involving transient receptor potential V2 (TRPV2). Additionally, in vitro experiments were conducted to assess the regulatory effects of TRPV2 pharmacological activation and inhibition on mitochondrial function in primary myotubes. The results revealed that TM had no discernible effect on the body weight and feed intake of broiler chickens under heat stress conditions (P > 0.05). However, it did delay the increase in rectal temperature and accelerate the decrease in serum T3 levels (P < 0.05). Furthermore, TM promoted the development of PM muscle fibers, significantly increasing myofiber diameter and cross-sectional area (P < 0.05). Under heat stress conditions, TM significantly upregulated the expression of mitochondrial electron transport chain (ETC) genes and TRPV2 in broiler PM muscle (P < 0.05), with a clear positive correlation observed between the two (P < 0.05). In vitro, pharmacological activation of TRPV2 not only increased its own expression but also enhanced mitochondrial ETC genes expression and oxidative phosphorylation function by upregulating intracellular calcium ion levels (P < 0.05). Conversely, TRPV2 inhibition had the opposite effect. Overall, this study underscores the potential of prenatal thermal manipulation in regulating postnatal broiler skeletal muscle development and mitochondrial function through the modulation of TRPV2 expression.

In this groundbreaking study, we unveil the remarkable structural, electronic, and optical Properties of the newly discovered double perovskite material, K2AgBiI6, presenting a paradigm shift in materials science. The unique crystal structure and diverse atomic interactions inherent in this double perovskite make it an up-and-coming candidate for various technological applications, particularly in photovoltaics; owing to its stability and resistance to heat and humidity, we aim to shed light on the extraordinary potential of K2AgBiI6. Our study provides valuable insights for researchers engaged in tailored material design. We anticipate that the exceptional electronic properties of K2AgBiI6 will not only redefine the boundaries of materials engineering but also catalyze unprecedented advances in sustainable technology. Employing the powerful computational tool CASTEP, we conducted detailed electronic structure calculations within the framework of Density Functional Theory (DFT) to unravel the electronic properties of the double perovskite K2AgBiI6. Our investigation thoroughly explored structural properties, band structure, total density of states (DOS), and partial density of states (PDOS). Furthermore, we systematically examined the influence of different exchange-correlation functionals, including LDA, GGA, and m-GGA, on the electronic and optical features of the material by presenting a comparative analysis of these approximations.

IntroductionEnsuring young people receive adequate information and guidance about puberty is essential for healthy adolescent transitions. Although many countries are moving toward including comprehensive sexuality education in national curricula, content on puberty during early adolescence, including peer pressure and stigma related to physical and emotional changes, are rarely included. Limited evidence exists about the inclusion of puberty education in schools, and the role of teachers in delivering such content in low-and middle-income countries, including Sierra Leone.MethodsWe conducted a qualitative assessment using multiple methodologies (in-depth interviews with teachers; focus group discussions with girls and boys; key informant interviews with teacher training lecturers and government) to explore the feasibility and acceptability of a puberty education package (a teacher training guide and boys’ and girls’ puberty books) for primary school teachers to introduce puberty content in Sierra Leone.ResultsThree key themes were identified, including the importance of teacher comfort in discussing puberty, the value of the teacher’s guide for delivering puberty content, and system and resource constraints that impact the implementation of puberty education. Additional insights included how integrating puberty education into existing curriculum courses may be more effective than stand-alone puberty classes; education systems can enable in-service and pre-service teacher training, along with culturally appropriate puberty resources, to increase effective puberty education delivery in schools; and governments serve a key role in providing puberty education teacher training, ensuring sustainable funding to retain trained teachers, and offering guidance on national curriculum requirements on puberty education.DiscussionThere is a strong need to integrate puberty education into formal educational systems, with well trained teachers serving a valuable role in its delivery. Research is needed on how best to scale sustainable teacher training interventions to support the delivery of puberty education to adolescents in low- and middle-income contexts.

Thermal energy storage (TES) units featuring phase change materials (PCMs) have a crucial impact on efficient energy management. Since energy demands keep changing, and the world increasingly relies on sustainable energy sources, innovation is continuously required. New technologies, materials, and methods for energy storage must be developed to meet these shifting needs effectively. In this study, a triplex-tube heat exchanger (TTHE) was employed as a TES medium, utilizing PCM within the middle tube. Because of its high thermal energy storage capacity, RT50 was selected as the PCM. Four innovative arc-shaped fins were strategically integrated within the PCM space to accelerate heat release. The system was subjected to rotational speeds of 0.1, 0.3, 0.5, 1, and 1.5 rpm. The investigation was carried out in two stages: initially, the impact of varying rotational speeds on the discharging process of the PCM in a finless TTHE was explored; subsequently, the influence of the same speeds on the solidification behavior of the finned TTHE was analyzed. Natural convection and PCM’s solidification process were examined through the enthalpy-porosity method. The findings represented that in the absence of fins, the device’s rotation had a more noticeable impact on the solidification behavior; however, incorporating fins was much more influential. Up to 2850 s, all the finned systems had solidified entirely in the presence or absence of the rotational mechanism, while in the finless system with a rotational speed of 1.5, 30.52 % of the material was still unsolidified until this time. Finally, the influence of three key structural parameters of the fins: α (outer fins arc angle), β (inner fins arc angle), and S (space between fins) on the discharging time of the PCM was analyzed using an artificial neural network (ANN) model. The study offered critical insights for optimizing fin configuration by systematically varying these parameters within defined ranges. An ANN predictive model was also proposed to assist TES system manufacturers and developers in future design and optimization efforts. The results demonstrated that the optimal setting of the TTHE (with the parameters of α = 60°, β = 60°, S = 10 mm) achieved the liquid fraction of 0.1, 80.33 % faster than the finless system.

This study proposes a two-parameter survival model based on the Kavya-Manoharan transformation family and the Rayleigh-inverted Weibull distribution, the so-called Kavya-Manoharan-Rayleigh inverted Weibull distribution (KMRIWD). Various reliability measures and statistical properties of this distribution are analyzed. The parameters of the distribution are estimated using the maximum likelihood method and different sampling techniques. Using Monte Carlo simulations, the performance of the estimators is evaluated and compared. Finally, the model and numerous competitors are compared using real data sets, and it is shown that the KMRIWD has a better fit than all the competitors.

In this study, we introduce a new extension of the Fréchet distribution known as the new extended Fréchet (NE_Fr) model. The NE_Fr is created by combining the new extended X family of distributions and the Fréchet distribution. The NE_Fr has more flexibility than the classical Fréchet distribution and some generalizations of the Fréchet distribution. The probability density function of the NE_Fr can be decreasing, unimodal and right skewed shape but it's hazard rate function can be decreasing or up-side-down shape. Several mathematical properties of the new model were derived by calculating the quantile function, the ordinary moments, the incomplete moments, the moment generating function, the conditional moment, the Bonferroni curve and the Lorenz curve. Several entropy measures were developed for this purpose. The inferences from the NE_Fr distribution were investigated using several established methods such as maximum likelihood estimation, least squares and weighted least squares estimation, and Anderson-Darling estimation. The simulation results demonstrated the computational efficiency of these techniques. The proposed NE_Fr distribution was demonstrated to be useful by examining three actual data sets.