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Abstract Energy scarcity in the world and the pollutants resulting from excessive use of conventional energy aroused the need for sustainable alternatives that are environment friendly. A multi-use thermoelectric refrigerator powered by solar energy to obtain the lowest consumption with the highest efficiency. The designed refrigerator is based on the Peltier effect using Peltier units where a temperature difference is created between the junctions by applying a voltage difference across the junction. This study investigates the performance of a refrigerator cooling system powered by a photovoltaic (PV) system. The research aims to assess the efficiency, effectiveness, and feasibility of utilizing solar energy to drive refrigeration, particularly in off-grid or environmentally conscious applications. Through a comprehensive experimental setup and data analysis, the study examines energy consumption, cooling efficiency, and overall system performance under varying conditions. The findings contribute valuable insights into the potential of PV-powered refrigerators as sustainable cooling solutions. It relies on a control unit that measures the resulting temperature to determine the appropriate connection mode to give the highest cooling efficiency. The average solar radiation when operating for 8 h, for the different seasons of the year was 149.5, 67.5, 119.3, and 118.3 w/m2 in summer, winter, spring, and fall, respectively. The average cooling energy consumption was 107.25, 137.04, 107, and 138.08 w for temperatures (20 ± 1, 15 ± 1, 20 ± 2, and 15 ± 2) °C respectively that proof solar radiation is sufficient to produce energy for the summer of cooling temperatures up to 15 °C, while in the spring and fall it is sufficient to 20 °C. The Fast not Eco mode is the least energy consuming and the fastest cooling, it can be used for rapid cooling at a short time less than an hour. The best mode in the case of continuous operation is the case of as next Eco mode cooling temperature of 20 ± 0.1 °C. The MATLAB Simulink model was developed to reduce the design cycle and facilitate the integration of solar photovoltaic with the TEC. The optimal operating point is identified through simulation and validated through experimental analysis, the optimal COP was 71.089% by Response surface methodology (RSM).

Numerous common human disorders, including cancer, high blood pressure, high cholesterol, inflammatory bowel diseases, obesity, and oral health issues, have been linked to changes in the composition and activity of the gut microbiota. This review aimed to highlight the significance of probiotics due to their positive impacts on gut microbiota, overall human health, cancer prevention, and production of bioactive compounds. Therefore, modifying the gut microbiota's balance can be highly beneficial for maintaining the human health. Probiotics are live microbial supplements, when consumed with meals; they help the host by harmonizing his/ her intestinal microflora. Supplements containing these good bacteria can be used up, or they can be added to dairy-free or non-dairy foods and drinks. Probiotics are mainly categorized into two main genera; mainly Lactobacillus spp. and Bifidobacterium spp. Probiotics are vital for maintaining a healthy microbiota; especially in cancer patients. They enhance the production of anticancer enzymes, apoptosis, autophagy, immunology, and other processes. Additionally, probiotics produce various bioactive molecules such as short-chain fatty acids, enzymes, vitamins, and exopolysaccharides with antibacterial attributes. Consequently, probiotics are utilized in food technology to develop the functional foods that promote the human health.

The trajectory tracking is important to make the WMR move autonomously from the starting point to the destination along a predefined time. Implementing of trajectory tracking control is a fundamental part to accomplish its application tasks. In this article a new method by using a hybrid controller has been presented to solve the problem of the trajectory tracking of four mecanum wheeled mobile robot. Proposed controller is depending on modeling of robot kinematic and dynamic equations. The novelty in this work is that, an optimal control system self-tuning parameters based on an optimization algorithm for these models of the mobile robot is utilized. The optimal control type that is used in this work is the Linear Quadratic Regulator (LQR) controller. LQR is used to control the actuator torque that is required in each wheel to achieve the robot task. The parameters of the LQR controller are tuned by using Ant Colony Optimization (ACO). For results simulation, MATLAB/ Simulink is used for circular and infinity shape trajectories. Results show that when the robot follows a circular trajectory, the values of position trajectory error values are reduced to small value (ex=3.218 *10-5m) and (ey= 2.224*10-5m) in xo and yo directions, respectively and remained almost at these values until the end of the simulation time. The maximum orientation error is (= 0.103rad), and convergent to zero after two seconds of the mobile robot movement. Also when the robot follows an infinity shape trajectory, the position trajectory error values are (ey) and () are reduced to small value -4.078 *10-4m and 3.174*10-4rad respectively, while, (ex) is reduced to 5.263*10-4 m after about 15 seconds.

Abstract Background Chronic migraine is a debilitating neurological condition that significantly impairs both individual and socioeconomic outcomes. The aim of the present study was to estimate the remission rates of chronic migraine to episodic migraine, and to identify potential predictors of chronic migraine remission. In addition, to assess impact of chronic migraine remission on headache related disability. Results Out of 300 individuals with chronic migraine (CM) who attended to our institution and continued for follow up in the period from the 1st of January 2021 up to the end of December 2022, approximately 82 cases (27.3%) had remitting CM, while 117 cases (39.0%) had persistent CM, and 101 cases (33.7%) had transitional CM. On multivariate model for detection of potential predictors of CM remission revealed that patients with lowest headache frequency (15–19 frequency/month) were much more likely to remit (OR = 577.826, 95% CI: 15.259 to 21,881.228, P = 0.001) than those with high-frequency CM (25–30 frequency/month), patients with non CM with allodynia (0–2) were more likely to remit (OR = 139.374, 95% CI: 4.634 to 419.879, P = 0.004) compared to those with moderate to severe CM with allodynia (≥ 6). Additionally, those using Topiramate or beta-blockers were more likely to achieve remission (OR = 23.325, 95% CI: 3.289 to 165.400, P = 0.002, and OR = 34.205, 95%CI: 3.591 to 325.842, P = 0.002, respectively), and also non-smokers were 11 times more likely to achieve remission compared to smokers (OR = 11.370, 95% CI: 1.702 to 75.934, P = 0.012). Conclusion These findings identified several potential predictors of remission among patients with chronic headache. However, the majority of these prognostic factors are modifiable.

Abstract This paper presents the exponentiated alpha-power log-logistic (EAPLL) distribution, which extends the log-logistic distribution. The EAPLL distribution emphasizes its suitability for survival data modeling by providing analytical simplicity and accommodating both monotone and non-monotone failure rates. We derive some of its mathematical properties and test eight estimation methods using an extensive simulation study. To determine the best estimation approach, we rank mean estimates, mean square errors, and average absolute biases on a partial and overall ranking. Furthermore, we use the EAPLL distribution to examine three real-life survival data sets, demonstrating its superior performance over competing log-logistic distributions. This study adds vital insights to survival analysis methodology and provides a solid framework for modeling various survival data scenarios.

Abstract The primary purpose of this article is to examine the issue of estimating the finite population distribution function from auxiliary information, such as population mean and rank of the auxiliary variables, that are already known. In order to better estimate the distribution function (DF) of a finite population, two improved estimators are developed. The bias and mean squared error of the suggested and existing estimators are derived up to the first order of approximation. To improve the efficiency of an estimators, we compare the suggested estimators with existing counterpart. Based on the numerical outcomes, it is to be noted that the suggested classes of estimators perform well using six actual data sets. The strength and generalization of the suggested estimators are also verified using a simulation analysis. Based on the result of actual data sets and a simulation study, we observe that the suggested estimator outperforms as compared to all existing estimators which is compared in this study.

This paper introduces a novel logarithmic beta generated family of distributions, designed specifically for the nuanced analysis of medical data. Through meticulous development, we have establish a comprehensive suite of distributional properties, including quantiles, moments, and hazard rate functions. Central to our contributions is the exploration of the power function distribution, a pivotal sub-model within this innovative family, demonstrating unparalleled flexibility across a broad spectrum of data types. Our investigation delves into seven prominent parameter estimation techniques, rigorously assessing their efficacy through both simulation studies and real-life medical datasets. This comparative analysis highlights the superior performance of the proposed model against existing standards, particularly through improved goodness-of-fit measures across four distinct medical science lifetime datasets. The findings highlight the new model's dominance in capturing complex data patterns, attributable to its adaptable density and hazard rate functions. These attributes significantly enhance modeling capabilities, paving the way for more precise and reliable medical research outcomes. The study concludes by emphasizing the model's potential in advancing statistical methodologies for medical science, backed by theoretical and empirical validations of its superior performance and versatility.

The objectives of this paper are threefold. First, we introduce a novel distribution, named the Odd Perks-Lomax (OPL) distribution, which is derived from the Odd Perks-G family of distributions. Second, we explore the mathematical properties of the OPL distribution in detail. Third, we develop a group acceptance sampling plan tailored for truncated life tests, utilizing this new distribution. The OPL distribution extends the classical Lomax distribution by incorporating two additional parameters, enhancing its flexibility. Hypothetical plots of the hazard and probability density functions suggest that the OPL distribution is versatile and capable of fitting a wide range of data. Parameters were estimated using the maximum likelihood method. Group acceptance sampling plans (GASPs) based on truncated life tests were designed, and their effectiveness was evaluated through simulation studies and real-world applications. Empirical data from both engineering and medical domains were analyzed, demonstrating that the OPL distribution outperforms traditional distributions, such as the Weibull and Exponentiated Weibull distributions. The maximum likelihood estimates obtained from these datasets were reintroduced into the GASP framework, further validating its utility in statistical quality control applications.

The basic principle of the classical work of wavelet methods is that the empirical wavelet coefficients are shrunk, thresholded, or both shrunk and threshold level by level based on their volumes. A block wavelet shrinkage strategy that depends on neighboring coefficients, where the wavelet coefficients are divided into multiple groups, is proposed. That means the thresholding of coefficients in the middle of each block depends on the whole block’s data using the decimated wavelet method. The NeighBlock procedure combines the previously found advantages for block thresholding methods with those obtained using information about neighboring coefficients. In this article, we collect an image corrupted with level of noise, then applying Block method to remove the noise. More precisely, the construction is started from collecting image, computing wavelet coefficients, applying the method, then inverse the wavelet coefficients. Wavelet shrinkage is a practical case in regression techniques, particularly when the unknown image has distinctive features; this might cause an unsuitable picture. The biggest challenge in the image is to calculate the wavelet coefficients and to invert these coefficients to the image after treatment. To solve this problem two functions based on the Haar wavelet are built to compute these coefficients and then invert the wavelet coefficients to provide the estimate image. The main idea of a wavelet is to translate a given image to a discrete wavelet transform (DWT) which is usually corrupted by noise; shrink or thresh the wavelet coefficients to decrease the noise impact, then invert the DWT to calculate the proper unknown image. The difference between these tools is that shrinking changes the wavelet coefficients of individual magnitudes, while the thresh keeps shrinking or threshold wavelet coefficients towards zero. The main goal is to compere the proposed method to state-of-the-art methods, and show that the proposed method provides good denoising performance. The asymptotic and numerical performances of the proposed method of the estimator are investigated. In numerical comparisons with different approaches, the proposed estimator method performs excellently. We propose decimated wavelet shrinkage techniques based on neighboring coefficients. Extensive simulations demonstrate that techniques almost always give insignificant results than the classical method for the image.

This paper proposes a new family of estimators for population mean with a non-response using a simple random sampling. It specifically applies this method to estimate the mean in Turkey’s Education sector data sets, accounting for non-response. The study integrates additional information in the form of mean and cdf of the auxiliary variable which is highly positively correlated with the study variable to develop a general class of estimators tailored for the non-response using a simple random sampling scheme. Through numerical research, the characteristics of these estimators – namely, their biases and mean square errors – have been carefully investigated and deeply evaluated. The basic estimator of a population mean is under-performed by the suggested estimators. The empirical investigation validates the results, demonstrating the improved relative efficiency of the proposed estimator over the existing estimators, as demonstrated by theoretical and numerical comparisons.

Abstract Acute circulatory shock is a life-threatening emergency requiring an efficient and timely management plan, which varies according to shock etiology and pathophysiology. Specific guidelines have been developed for each type of shock; however, there is a need for a clear timeline to promptly implement initial life-saving interventions during the early phase of shock recognition and management. A simple, easily memorable bundle of interventions could facilitate standardized management with clear targets and specified timeline. The authors propose the “MINUTES” acronym which summarizes essential interventions which should be performed within the first 30 min following shock recognition. All the interventions in the MINUTES bundle are suitable for any patient with undifferentiated shock. In addition to the acronym, we suggest a timeline for each step, balancing the feasibility and urgency of each intervention. The MINUTES acronym includes seven sequential steps which should be performed in the first 30 min following shock recognition: Maintain “ABCs”, INfuse vasopressors and/or fluids (to support hemodynamic/perfusion) and INvestigate with simple blood tests, Ultrasound to detect the type of shock, Treat the underlying Etiology, and Stabilize organ perfusion.

Abstract Valve control for patients feeding saline is a sensitive issue. Such a valve is used to control the amount of important fluid entering the body. In this paper, we present an intelligent method based on fuzzy logic (FL) to deliver drugs and nutrients to patients through intravenous catheters. The proposed method is called intelligent saline controlling valve (ISCV) and relies on three inputs and two outputs. Specifically, the fluid’s drip, pressure, and the number of available bubbles are the three-valve inputs that control the two outputs which are the opening and closing. In other words, the ISCV controls the feeding saline for medical purposes. The obtained results show the success of the proposed method.

Bostonite rocks are widely spread in the Central Eastern Desert (CED) of Egypt, they are found in the form of sills or dykes injected in the Precambrian rocks. Postgeosynclinal (Hammamat) sediments were intruded by Postorogenic bostonites. The study of this area, using ground geophysical methods, aimed at tracking the radioactive mineralization under the surface, based on the possible association of this radioactive mineralization with some other mineralizations such as sulphides. The application of the self-potential survey shows that the highest negative anomalies are associated with the South El-Atshan bostonite sill and its contact zones. The depths to the centres of some selected anomalies range from 5.7 m to 24 m, half-widths oscillate from 6 to 32 m, with shallow dips towards the west and east directions. The horizontal-loop electromagnetic (HLEM) survey, which was conducted using four frequencies, revealed the presence of two conductive bodies. These conductive bodies possess narrow widths and depths, ranging from 25 m to 27 m, dipping towards the west direction with shallow angles of 25° and 40°, respectively. In addition, the induced polarization (IP) profile shows high chargeability values reaching more than 7.9 mV/V at depths starting from about 10 m to about 35 m. This zone corresponds to a high-resistance zone that may reflect a subsurface disseminated mineralization. The integration of the results obtained using the three techniques makes it possible to determine the most appropriate zones for the development of exploration in the area of investigation.

Abstract Background Updates on the aetiopathogenesis of acne vulgaris, particularly the inflammatory process, are becoming more and more clear. The TNF superfamily includes tumor necrosis factor (TNF) related weak inducer of apoptosis (TWEAK). It plays a significant part in a variety of inflammatory skin conditions, including psoriasis, alopecia areata and many others. However, its role in acne vulgaris remains questionable. Objectives We aim in this research to evaluate the circulating levels of TWEAK in various severities of acne vulgaris patients and their blood levels before and after oral treatment with isotretinoin. Methods This study includes 100 acne vulgaris patients and 100 healthy controls in a case‐control design. All cases, ranging in severity, were treated for 3 months with oral isotretinoin. Enzyme‐linked immunosorbent assay technique was used to measure serum TWEAK before and after 3 months of isotretinoin treatment. Results The serum TWEAK levels were significantly higher in patients than the healthy volunteers (p

الملخص: أهداف البحث: التحمل القلبي الرئوي مهم للمشاركة بشكل مريح في أنشطة الحياة اليومية. تستخدم اختبارات التمرين، مثل اختبار المشي لمدة ست دقائق، بشكل شائع لتقييم القدرة على التحمل القلبي الرئوي. نحن نهدف إلى دراسة تأثيرات اختبار المشي لمدة ست دقائق القائم على الممر والمعتمد على مختبر تحليل المشية في الوقت الحقيقي التفاعلي على الأداء الوظيفي. طريقة البحث: تم تقسيم ثلاثين رجلا أصحاء بشكل عشوائي إلى مجموعتين. أجرى المشاركون في المجموعة (أ) اختبار المشي لمدة ست دقائق على الممر، تليها فترة الراحة (ساعة واحدة)، وبعد ذلك، قاموا بإجراء اختبار المشي في الوقت الحقيقي للتحليل التفاعلي القائم على المشي لمدة ست دقائق. في المجموعة (ب)، أجرى المشاركون الاختبارات بتسلسل عكسي لتلك التي أجراها المشاركون في المجموعة (أ). النتائج: أدى اختبار المشي لمدة ست دقائق القائم على الممر إلى زيادة كبيرة في مسافة ست دقائق سيرا على الأقدام (6 ميجاوات) وسرعة المشي لمدة ست دقائق مقارنة باختبار المشي لمدة ست دقائق القائم على مختبر التحليل التفاعلي في الوقت الحقيقي. لم يلاحظ أي فروق ذات دلالة إحصائية بين المجموعتين في أي من النتائج الثانوية التالية: ضغط الدم الانقباضي، وضغط الدم الانبساطي، وتشبع الأكسجين، ومعدل ضربات القلب، وضيق التنفس، والتعب العام. ولوحظ وجود علاقة إيجابية قوية بين مسافة اختبار المشي البالغة ست دقائق وسرعة اختبار المشي لمدة ست دقائق. الاستنتاجات: لا ينبغي استخدام اختبار المشي لمدة ست دقائق القائم على الممر واختبار المشي في الوقت الحقيقي للتحليل التفاعلي القائم على المختبر لمدة ست دقائق بشكل تبادلي. Abstract: Objective: Cardiopulmonary endurance is important for comfortably participating in activities of daily living. Exercise tests, such as the 6-minute walk test (6MWT), are commonly used to evaluate cardiopulmonary endurance. We investigated the effects of the Gait Real-Time Analysis Interactive Lab (GRAIL)- and corridor-based 6MWTs on functional performance. Methods: Thirty healthy men were randomly divided into two groups. Group A participants performed a corridor-based 6MWT, followed by a washout period (1 h). Subsequently, they performed the GRAIL-based 6MWT. Group B participants performed the tests in the reverse order of that performed by Group A participants. Results: The corridor-based 6MWT resulted in significantly higher 6MW distance and 6MW speed than the GRAIL-based 6MWT. No significant differences were observed between the two groups in any of the following secondary outcomes: systolic blood pressure, diastolic blood pressure, oxygen saturation, heart rate, dyspnea, and overall fatigue. A strong positive correlation was observed between the 6MW distance and 6MW speed. Conclusion: The corridor- and GRAIL-based 6MWT should not be used interchangeably.

Numerical models of crop response to irrigation and weather forecasts with internet access should be fully utilized in modern irrigation management. In this respect, we developed a new numerical scheme to optimize irrigation depth that maximizes net income over each irrigation interval. The scheme applies volumetric water prices to inspire farmers to save water, and it provides growers with real-time estimates of irrigation depth and net income over the growing season. To evaluate this scheme, we carried out a field experiment for groundnut (Arachis hypogaea L.) grown in a sandy field of the Arid Land Research Center (ALRC), Tottori University, Japan. Two treatments were established to compare the net income of the proposed scheme with that of an automated irrigation system. Results showed that although the proposed scheme gave a larger amount of seasonal irrigation water 28%, it achieved 2.18 times of net income owing to 51% higher yield compared to results of the automated irrigation system. The accuracy of rainfall forecast had little effect on the scheme outputs, where the root mean square error (RMSE) between observed and forecasted rainfall was 4.63 mm. By utilizing numerical simulation information of the soil–plant–atmosphere system into the proposed scheme, it would be a more cost-effective tool for optimizing irrigation depths than automated irrigation systems.

In this study, the Topp-Leone family of distribution approach was used to modify the Burr Hatke Exponential distribution to provide adequate fits for some engineering and health data which previous existing distributions in the family of Burr Hatke Exponential have failed to do. The new distribution improves the robustness of Burr Hatke Exponential distribution by making it capable of modeling emerging new world complex data with varying features, possesses greater capacity and flexibility to model lifetime data, has better goodness of fit. Some mathematical properties of the derived distribution such as quantile function, moments, order statistics, entropies, etc were obtained and discussed. Some non-Bayesian estimation approaches like maximum likelihood estimation (ML), maximum Product spacing estimation (MPSE), Least squares estimation (LS), weighted least squares estimation (WLS), Cramer-von-Mises estimation (CVM), Anderson-Darling estimation (AD), and right-tailed Anderson Darling estimation (RTAD), as well as Bayesian method under independent gamma priors were adopted to estimate the parameters of the model and the various methods proved efficient. From the simulation results, the bias and root mean squared error for the parameters are relatively small and the become smaller as the sample size becomes larger. This shows convenience and improved estimation accuracy. We further constructed a regression model using the proposed distribution. Extensive simulation studies were used to determine the efficiency of the method in both the estimation of its parameters and that of the regression model. The TL-BHE regression was fitted on censored CD4 count data of HIV/AIDs patients. The competitiveness, applicability, and usefulness of the model were demonstrated using datasets and the results validate the theoretical findings. The results indicate that the TL-BHE distribution achieved better results than the baseline distribution and other variants of the classical distributions.

This study introduces a novel technique for achieving the global peak (GP) in solar photovoltaic (PV) systems under partial shadowing conditions (PSC) using the Dandelion Optimizer Algorithm (DOA), inspired by the dispersal of dandelion seeds in the wind. The proposed approach aims to enhance the power generation efficiency of PV systems across various scenarios, including dynamic uniform, dynamic PSCs, static uniform irradiances, and static PSCs. The proposed approach improves tracking efficiency, provides non-oscillatory steady-state responses, and reduces transients as well as enhancing the dynamic performance of the whole system. Simulation and hardware-in-loop (HIL) experiments demonstrate that the DOA outperforms several state-of-the-art techniques, such as hybrid grey wolf optimizer since-cosine algorithm (HGWOSCA), grasshopper optimization algorithm (GOA), dragonfly optimizer (DFO), particle swarm optimizer with gravitational search (PSOGS), PSO, cuckoo search algorithm (CSA), perturb &observe (P&O), and incremental conductance (INC), achieving average efficiencies of 99.93 %, 88.84 %, 94.48 %, 87.12 %, 88.05 %, 94.79 %, 93.82 %, 85.25 %, and 77.93 %, respectively. These results underscore the DOA's effectiveness in improving maximum power point tracking (MPPT) performance in solar arrays, particularly under challenging dynamic PSC conditions.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in late 2019 has accumulated a series of point mutations and evolved into several variants of concern (VOCs), some of which are more transmissible and potentially more severe than the original strain. The most notable VOCs are Alpha, Beta, Gamma, Delta, and Omicron, which have spread to various parts of the world. This study conducted surveillance in Jashore, Bangladesh to identify the prevalence of SARS-CoV-2 coinfected with dengue virus and their genomic effect on the emergence of VOCs. A hospital-based COVID-19 surveillance from June to August, 2021 identified 9 453 positive patients in the surveillance area. The study enrolled 572 randomly selected COVID-19-positive patients, of which 11 (2%) had dengue viral coinfection. Whole genome sequences of SARS-CoV-2 were analyzed and compared between coinfection positive and negative group. In addition, we extracted 185 genome sequences from GISAID to investigate the cross-correlation function between SARS-CoV-2 mutations and VOC; multiple ARIMAX(p,d,q) models were developed to estimate the average number of amino acid (aa) substitution among different SARS-CoV-2 VOCs. The results of the study showed that the coinfection group had an average of 30.6 (±1.7) aa substitutions in SARS-CoV-2, whereas the dengue-negative COVID-19 group had that average of 25.6 (±1.8; P

Abstract Background Postpartum depression (PPD) affects around 10% of women, or 1 in 7 women, after giving birth. Undiagnosed PPD was observed among 50% of mothers. PPD has an unfavorable relationship with women’s functioning, marital and personal relationships, the quality of the mother-infant connection, and the social, behavioral, and cognitive development of children. We aim to determine the frequency of PPD and explore associated determinants or predictors (demographic, obstetric, infant-related, and psychosocial factors) and coping strategies from June to August 2023 in six countries. Methods An analytical cross-sectional study included a total of 674 mothers who visited primary health care centers (PHCs) in Egypt, Yemen, Iraq, India, Ghana, and Syria. They were asked to complete self-administered assessments using the Edinburgh Postnatal Depression Scale (EPDS). The data underwent logistic regression analysis using SPSS-IBM 27 to list potential factors that could predict PPD. Results The overall frequency of PPD in the total sample was 92(13.6%). It ranged from 2.3% in Syria to 26% in Ghana. Only 42 (6.2%) were diagnosed. Multiple logistic regression analysis revealed there were significant predictors of PPD. These factors included having unhealthy baby adjusted odds ratio (aOR) of 11.685, 95% CI: 1.405–97.139, p = 0.023), having a precious baby (aOR 7.717, 95% CI: 1.822–32.689, p = 0.006), who don’t receive support (aOR 9.784, 95% CI: 5.373–17.816, p = 0.001), and those who are suffering from PPD. However, being married and comfortable discussing mental health with family relatives are significant protective factors (aOR = 0.141 (95% CI: 0.04–0.494; p = 0.002) and (aOR = 0.369, 95% CI: 0.146–0.933, p = 0.035), respectively. Conclusion The frequency of PPD among the mothers varied significantly across different countries. PPD has many protective and potential factors. We recommend further research and screenings of PPD for all mothers to promote the well-being of the mothers and create a favorable environment for the newborn and all family members.

Abstract Scientists know very little about the mechanisms underlying fish skin mucus, despite the fact that it is a component of the immune system. Fish skin mucus is an important component of defence against invasive infections. Recently, Fish skin and its mucus are gaining interest among immunologists. Characterization was done on the obtained silver nanoparticles Ag combined with Clarias gariepinus catfish epidermal mucus proteins (EMP-Ag-NPs) through UV–vis, FTIR, XRD, TEM, and SEM. Ag-NPs ranged in size from 4 to 20 nm, spherical in form and the angles were 38.10°, 44.20°, 64.40°, and 77.20°, Where wavelength change after formation of EMP-Ag-NPs as indicate of dark brown, the broad band recorded at wavelength at 391 nm. Additionally, the antimicrobial, antibiofilm and anticancer activities of EMP-Ag-NPs was assessed. The present results demonstrate high activity against unicellular fungi C. albicans, followed by E. faecalis. Antibiofilm results showed strong activity against both S. aureus and P. aeruginosa pathogens in a dose-dependent manner, without affecting planktonic cell growth. Also, cytotoxicity effect was investigated against normal cells (Vero), breast cancer cells (Mcf7) and hepatic carcinoma (HepG2) cell lines at concentrations (200–6.25 µg/mL) and current results showed highly anticancer effect of Ag-NPs at concentrations 100, 5 and 25 µg/mL exhibited rounding, shrinkage, deformation and granulation of Mcf7 and HepG2 with IC50 19.34 and 31.16 µg/mL respectively while Vero cells appeared rounded at concentration 50 µg/mL and normal shape at concentration 25, 12.5 and 6.25 µg/ml with IC50 35.85 µg/mL. This study evidence the potential efficacy of biologically generated Ag-NPs as a substitute medicinal agent against harmful microorganisms. Furthermore, it highlights their inhibitory effect on cancer cell lines.

In today's modern world, marketing is a fruitful source to grow a business by reaching a larger audience. This paper considers a popular social media source called LinkedIn.com as a way of marketing or reaching a larger audience. We consider a regression approach to explore the statistically significant role of the LinkedIn medium as a tool for reaching a larger audience. In addition to statistically exploring the role of the LinkedIn medium in the financial sector, we also introduce a new Weibull-based probability distribution, namely, the exponential TX inverse Weibull (for short'ETXI-Weibull') distribution. The ETXI-Weibull distribution is specially designed for analyzing LinkedIn marketing data. The beauty of the ETXI-Weibull distribution is that it satisfies the heavy-tailed characteristics, which are explored visually and mathematically. For the ETXI-Weibull distribution, the estimators are derived whose performances are evaluated visually and numerically through a simulation study. The ETXI-Weibull distribution is applied practically by considering the LinkedIn marketing data set as an example. Using certain established statistical tests, we observe that the ETXI-Weibull distribution provides an optimal fit to the LinkedIn marketing data set. Furthermore, a bivariate extension of the exponential TX inverse Weibull model is also introduced. Finally, the bivariate extension of the exponential TX inverse Weibull model is illustrated by modeling the LinkedIn marketing and sales data.

This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called ‘novel’. In addition, the existing CSIMs are distinguished as the members of the suggested CSIMs, respectively. The theoretical conditions under which the proposed IMs perform better are obtained by comparing the proposed IMs with the existing IMs. To validate the theoretical findings, the numerical and simulation studies are conducted on real and artificial populations, respectively.

Several random phenomena have been modeled by using extreme value distributions. Based on progressive type-Ⅱ censored data with three different distributions (i.e., fixed, discrete uniform, and binomial random removal), the statistical inference of the generalized extreme value distribution under liner normalization (GEVL distribution) parameters is investigated in this study. Since there is no analytical solution, determining the maximum likelihood parameters for the GEVL distribution is considered to be a problem. Standard numerical methods are frequently insufficient for this dilemma, requiring the use of artificial intelligence algorithms to address this difficulty. Here, nonlinear minimization and a genetic algorithm have been used to tackle that problem. In addition, Lindley approximation and Monte Carlo estimation were implemented via Metropolis-Hastings algorithms to carry out the Bayesian point estimation based on both the squared error loss function and LINEX loss functions. Moreover, the highest posterior density intervals were applied. The proposed theoretical inference techniques have been applied in a numerical simulation and a real-life example.

Background and Aim: Query fever (Q fever) is an endemic zoonotic disease and ruminants are considered to be the primary source of infection in humans. It is caused by Coxiella burnetii which is an obligate intracellular bacterial pathogen with a worldwide distribution. This study estimated the prevalence of Q fever in livestock with a history of abortion in Makkah Province, Saudi Arabia. Materials and Methods: Sera from 341 camels, 326 sheep, and 121 goats of either sex from various locations (Makkah, Jeddah, AL-Taif, AL-Qunfudah, AL-Laith, and AL-Kamil) were examined using a Q fever indirect enzyme-linked immunosorbent assay. Results: Among the 788 serum samples, 356 animals had anti-Coxiella burnetii immunoglobulin G antibodies with an overall seroprevalence of 45.4%. Significant differences were observed in seroprevalence between species and locations. Camels had the highest percentage of Q fever-positive sera, with a prevalence of 50.4%, followed by goats (44.6%) and sheep (36.8%), with a high significant difference between animals (p = 0.000). The prevalence was significantly higher in Makkah (65.4%) than in Jeddah (28.8%). Conclusion: C. burnetii infection is prevalent in agricultural animals, especially camels maintained at livestock farms in Makkah province. Therefore, these animals considered as the main source of Q fever infections in Saudi Arabia, which is also a reason for the abortion in these animals. Therefore, there is an urgent need for further studies on Q fever infection with interventional approaches for prevention and control.

Introduction Expiratory muscle weakness and dyspnoea are common in patients suffering from chronic obstructive pulmonary disease (COPD) and negatively affect their exercise capacity. We aimed to highlight the combined effect of Russian current and a threshold positive expiratory pressure (PEP) device on expiratory muscle strength, dyspnoea, and functional capacity in patients with COPD. Methods A total of 60 males with COPD were involved in this controlled randomised trial (age ranged 55–65 years and median body mass index [BMI] was 28.68–25.96) and randomly assigned into two equal groups (30 for each), to receive combined Russian current and PEP device (study group) or PEP device only (control group), for three sessions per week over a ten-week period. Maximum expiratory pressure (MEP), dyspnoea (modified Borg scale – MBS), and functional capacity (6-minute walk test) were assessed before and after the intervention. Results There was statistically significant improvement in all measured variables (MEP, MBS, and 6-minute walk test) in either the study group or the control group according to Wilcoxon’s sign rank test (all were p < 0.001 and p < 0.01, respectively), however, the study group showed a more significant improvement compared to the control group according to the Mann–Whitney U -test ( p < 0.001). Conclusions Combined Russian current and PEP device had a superior beneficial effect on improving dyspnoea and functional capacity by boosting the expiratory muscle strength in COPD patients, which could be implemented in their management, although further studies are needed to evaluate its maintenance effect.

Newsha Nikzad,1– 3,&ast; David Thomas Fuentes,4,&ast; Millicent Roach,2 Tasadduk Chowdhury,2 Matthew Cagley,2 Mohamed Badawy,4 Ahmed Elkhesen,5 Manal Hassan,6 Khaled Elsayes,7 Laura Beretta,8 Eugene Jon Koay,2 Prasun Kumar Jalal1 1Department of Medicine and Surgery, Baylor College of Medicine, Houston, TX, USA; 2Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 3Department of Internal Medicine, The University of Chicago Medical Center, Chicago, IL, USA; 4Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 5Department of Internal Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA; 6Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 7Department of Abdominal Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 8Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA&ast;These authors contributed equally to this workCorrespondence: Newsha Nikzad; Prasun Kumar Jalal, Email nnikzad@bcm.edu; jalal@bcm.eduBackground and Aims: Limited methods exist to accurately characterize the risk of malignant progression of liver lesions. Enhancement pattern mapping (EPM) measures voxel-based root mean square deviation (RMSD) of parenchyma and the contrast-to-noise (CNR) ratio enhances in malignant lesions. This study investigates the utilization of EPM to differentiate between HCC versus cirrhotic parenchyma with and without benign lesions.Methods: Patients with cirrhosis undergoing MRI surveillance were studied prospectively. Cases (n=48) were defined as patients with LI-RADS 3 and 4 lesions who developed HCC during surveillance. Controls (n=99) were patients with and without LI-RADS 3 and 4 lesions who did not develop HCC. Manual and automated EPM signals of liver parenchyma between cases and controls were quantitatively validated on an independent patient set using cross validation with manual methods avoiding parenchyma with artifacts or blood vessels.Results: With manual EPM, RMSD of 0.37 was identified as a cutoff for distinguishing lesions that progress to HCC from background parenchyma with and without lesions on pre-diagnostic scans (median time interval 6.8 months) with an area under the curve (AUC) of 0.83 (CI: 0.73– 0.94) and a sensitivity, specificity, and accuracy of 0.65, 0.97, and 0.89, respectively. At the time of diagnostic scans, a sensitivity, specificity, and accuracy of 0.79, 0.93, and 0.88 were achieved with manual EPM with an AUC of 0.89 (CI: 0.82– 0.96). EPM RMSD signals of background parenchyma that did not progress to HCC in cases and controls were similar (case EPM: 0.22 ± 0.08, control EPM: 0.22 ± 0.09, p=0.8). Automated EPM produced similar quantitative results and performance.Conclusion: With manual EPM, a cutoff of 0.37 identifies quantifiable differences between HCC cases and controls approximately six months prior to diagnosis of HCC with an accuracy of 89%.Plain Language Summary: Current surveillance and diagnostic methods in hepatocellular carcinoma are suboptimal. Enhancement pattern mapping is an imaging technique that quantifies lesion signals and may be useful in diagnostic and surveillance methods. Enhancement pattern mapping describes quantifiable differences between malignant and benign liver tissue on contrast-enhanced MRI. It amplifies lesion signal and distinguishes malignancy in a surveillance population. The novel imaging technique was investigated at single institution and analyzed lesions compared to cirrhotic parenchyma. Future efforts will include further risk stratification across LI-RADS group categories. The results provide evidence that enhancement pattern mapping uses available imaging data to distinguish hepatocellular carcinoma from non-cancerous parenchyma with and without benign lesions on scans six months prior to diagnosis with standard MRI. The technique introduces a prospective modality to improve diagnostic accuracy and early detection with the goal of improving clinical outcomes.Keywords: LI-RADS, MRI, radiomics, artificial intelligence, liver cancer, machine learning

Abstract Two new series of oxadiazole and pyrazoline derivatives were designed and synthesized as promising EGFR-TK inhibitors. The in vitro antiproliferative activity was studied against three human cancer cell lines; HCT116, HepG-2 and MCF7 using MTT assay. Compound 10c showed the most potent anticancer activity against all cancer cell lines, with IC50 range of 1.82 to 5.55 μM, while proving safe towards normal cells WI-38 (IC50 = 41.17 μM) compared to the reference drug doxorubicin (IC50 = 6.72 μM). The most active candidates 5a, 9b, 10a, 10b and 10c were further assessed for their EGFR-TK inhibition. The best of which, compounds 5a and 10b showed IC50 of 0.09 and 0.16 μM respectively compared to gefitinib (IC50 = 0.04 μM). Further investigation against other EGFR family members, showed that 5a displayed good activities against HER3 and HER4 with IC50 values 0.18 and 0.37 µM, respectively compared to gefitinib (IC50 = 0.35 and 0.58 µM, respectively). Furthermore, 5a was evaluated for cell cycle distribution and apoptotic induction on HepG-2 cells. It induced mitochondrial apoptotic pathway and increased accumulation of ROS. Molecular docking study came in agreement with the biological results. Compounds 5a and 10b showed promising drug-likeness with good physicochemical properties.

Shadi Chamseddine,1,&ast; Michael LaPelusa,2,&ast; Lianchun Xiao,3 Yehia I Mohamed,1 Sunyoung S Lee,1 Zishuo Ian Hu,1 Rikita I Hatia,4 Manal Hassan,4 James C Yao,1 Dan G Duda,5 Saumil Datar,6 Hesham M Amin,7,8 Ahmed O Kaseb1 1Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 2Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 3Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 4Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 5Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; 6Department of Internal Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA; 7Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 8MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA&ast;These authors contributed equally to this workCorrespondence: Hesham M Amin, Department of Hematopathology, The University of Texas MD Anderson Cancer Center, MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Houston, TX, 77030, USA, Tel +1 713 794-1769, Fax +1 713 792-7273, Email hamin@mdanderson.org Ahmed O Kaseb, Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX, 77030, USA, Tel +1-713-792-2828, Fax +1 713-745-1163, Email akaseb@mdanderson.orgIntroduction: In this study, we explored the potential of plasma growth hormone (GH) as a prognostic biomarker in patients with advanced HCC treated with durvalumab plus tremelimumab (D+T).Methods: In this study, we included 16 patients with advanced HCC who received D+T at MD Anderson Cancer Center between 2022 and 2023 and had plasma GH measurements recorded before treatment. Plasma GH levels were measured from prospectively collected blood samples and were correlated with progression-free survival (PFS) and overall survival (OS). The cutoff for normal GH levels in women and men was defined as ≤ 3.7 μg/L and ≤ 0.9 μg/L, respectively. The Kaplan–Meier method was employed to compute the median OS and PFS, while the Log rank test was applied to compare the survival outcomes between the GH-high and GH-low groups.Results: Sixteen patients were included in this analysis, two female and fourteen male, with a median age of 65.5 years. At the time of the analysis, the 6-month OS rate was 100% among GH-low patients (6 patients) and 30% among GH-high patients (10 patients). OS was significantly longer in GH-low patients (not evaluable) compared to GH-high patients (3.94 months) (p = 0.030). PFS was also significantly longer in GH-low patients (not evaluable) compared to the GH-high patients (1.87 months) (p = 0.036).Conclusion: Plasma GH is a prognostic biomarker in patients with advanced HCC treated with D+T. Given the relatively small patient cohort size, this finding should be further validated in larger randomized clinical trials in advanced HCC patients.Keywords: hepatocellular carcinoma, growth hormone, durvalumab, tremelimumab, overall survival, progression-free survival

In this article, we offer simple random sampling (SRS) based efficient class of estimators of population mean Y¯ utilizing additional information. The expression of the mean square error of the proposed class of estimators is deduced up to first degree approximation. The efficiency conditions are established which are enhanced numerically utilizing a simulation study consummated over symmetrical and asymmetrical populations. Real data sets are also utilized to exemplify the suggested estimators. The numerical findings are appeared rather acceptable demonstrating better advancement over the ordinary estimators.

The purpose of agriculture is to support humankind. There are currently 7.7 billion people on the planet and this figure will increase to nine billion by 2050. As the population grows, even greater amounts of food will be needed, creating a significant challenge for farmers. Emerging digital technologies such as hyper-automation have the potential to revolutionize conventional agricultural methods. This study assessed the current use of hyper-automation systems in agriculture and examined whether new uses of this technology could benefit agricultural industries. One example could be to use an automated variable-seed control system, which has reported seeding accuracy of 98 %, indicating a cost-effective solution. Overall, our analysis revealed that to sustain future agricultural production and ensure food security, countries throughout the world need to focus on hyper-automation in the agriculture sector.

Efficient scheduling and load balancing are essential for optimizing performance in multiprocessor systems. This study proposes a novel hybrid algorithm that integrates beam search and differential evaluation techniques within the domain of artificial intelligence (AI) to address these challenges. Our objective is to minimize the operational completion time (OCT), a critical metric for evaluating system performance. Beam search is utilized to explore the solution space effectively, enabling the algorithm to identify promising solutions. Moreover, we employ a differential evaluation approach to assess the quality of candidate solutions and guide the search toward optimal or near-optimal scheduling and load-balancing configurations. By combining these techniques, our hybrid algorithm aims to minimize OCT, thereby enhancing system throughput and resource utilization. Experimental evaluations demonstrate the effectiveness of our approach in achieving improved performance compared to traditional methods. This research contributes to advancing the field of AI in multiprocessor systems optimization, providing practical solutions for real-world deployment in high-performance computing environments.

The future electric loads in the Kingdom of Saudi Arabia (KSA) are increasing significantly, particularly in the Eastern Province of the KSA. These high-rise loads are primarily driven by the operational needs of the Saudi Arabian oil company Aramco, including oil refineries, and the infrastructures of the Saudi Basic Industries Corporation (SABIC) factories. This study aims to construct a nuclear power plant in that area to supplement and support the baseload currently covered by conventional generation units powered by fossil fuels within the Saudi Electricity Company (SEC) operations. The objective function is to minimize the operational costs of the power systems to the greatest extent possible. This paper describes a case study conducted using the IBM CPLEX Optimizer software to compare the operational costs of KSA’s power systems for a 24-h period. Two scenarios were considered and addressed: the first scenario without the inclusion of a nuclear power plant (NPP) and the second scenario with the inclusion of the NPP. The unit commitment problem was modeled for both scenarios. The obtained results revealed that the second scenario, which involved the penetration of the NPP, offered an optimal economic solution for operating KSA’s power systems. By employing the CPLEX Optimizer software and analyzing the unit commitment problem, this study provides valuable insights into the economic advantages of integrating the NPP into the power systems of the Kingdom of Saudi Arabia. The NPP shows viability in terms of minimizing the operational costs to 32.10 $/MWh compared to the first scenario where the operational costs were 42.10 $/MWh and resulted in almost 24% reduction in operational costs. In addition, the NPP is deemed as an optimal technology to contribute to the net zero goal by 2060, where it can reduce the reliance on fossil fuel power plants and contribute to the reduction of CO2 emissions.

ABSTRACT: The meat of the quail is one of the most delicious types, as it is rich in minerals and vitamins, especially vitamin K, which is useful in treating nervous diseases. In the present investigation, based on their live body weight, 270 genetically-enhanced white quail chicks of mixed sex were randomly assigned to 3 groups, each with 90 chicks. The first group's birds were slaughtered at 28 d of age. The birds in the second group were slaughtered at 31 d, and the birds in the third group were slaughtered at 34 d. Results showed no significant difference between the various groups in the overall mortality rate index at the end of each fattening stage (P > 0.05). There were substantial variations (P ≤ 0.05) in the average live weight index between the first and both groups at each group's marketing age. With increasing marketing age, body weight increases. Quail chicks raised for 34 d received the lowest EPEF (28.90 points), followed by those raised for 31 d and 28 d, which received 33.37 and 37.32 points, respectively. The economic feasibility of the 3 groups, no significant differences in the profit index were observed at the age of 28 d. Compared to the marketing age of the other 2 groups, it was noted that the profit index decreased as the birds advanced in age. Delaying marketing to 31 d leads to a decrease in profit by 5.7%, and delaying marketing to 34 d reduces the profit index to 26.36% compared to marketing at 28 d. For blood hematology parameters, a significant increase in the studied indicators with the age of the birds was observed through the study of blood indicators. Still, it did not reach the significance level. It could be concluded that 28 d is the ideal marketing age for the enhanced white quails, as it yielded the highest economic return and the best performance.

Statistical process control basically involves inspecting a random sample of the output from a process and deciding whether the process is producing products with characteristics that fall within a predetermined range. It is used extensively in the field of reliability engineering. The reliability of the production process is thoroughly monitored for any internal variation using the SPC. The aim is always to settle such variations through a proper control monitoring. If the underlying distribution of the process is known to the researcher than the use of parametric control charts are useful but in many cases when there is doubt about the distribution of the process then it is preferred to use non parametric control charts. In this paper we propose the modified Exponentially weighted moving average (EWMA), Double Exponentially weighted moving average (DEWMA), Hybrid Exponentially weighted moving average (HEWMA), Extended Exponentially weighted moving average (EEWMA), Modified Exponentially weighted moving average (MEWMA) and mix- type control charts by mixing these control charts with Tukey control chart EWMA-TCC, DEWMA-TCC, HEWMA-TCC, EEWMA-TCC, MEWMA-TCC for the shape parameter of the Kumaraswamy Lehmann-2 Power function distribution (KL2PFD).

A thorough understanding of SARS-CoV-2 genetic features is compulsory to track the ongoing pandemic across multiple geographical locations of the world. Thermo Fisher Scientific USA has developed the Ion AmpliSeq SARS-CoV-2 Research Panel for the targeted sequencing of SARS-CoV-2 complete genome with high coverage and lower error rate. In this study an alternative approach of complete genome sequencing has been validated using different commercial sequencing kits to sequence the SARS-CoV-2. Amplification of cDNA with the SARS-CoV-2 primer pool was performed separately using two different master mixes: 2X environmental master mix (EM) and Platinum™ PCR SuperMix High Fidelity master mix (PM) instead of 5X Ion AmpliSeq™ HiFi Mix whereas NEBNext® Fast DNA Library Prep Set for Ion Torrent™ kit was used as an alternative to Ion AmpliSeq Library Kit Plus for other reagents. This study demonstrated a successful procedure to sequence the SARS-CoV-2 whole genome with average ∼2351 depth and 98.1% of total the reads aligned against the reference sequence (SARS-CoV-2, isolate Wuhan-Hu-1, complete genome). Although genome coverage varied, complete genomes were retrieved for both reagent sets with a reduced cost. This study proposed an alternative approach of high throughput sequencing using Ion torrent technology for the sequencing of SARS-CoV-2 in developing countries where sequencing facilities are low. This blended sequencing technique also offers a low cost protocol in developing countries like Bangladesh.

Abstract Background Parkinson's disease (PD) is a chronic progressive neurodegenerative disabling disease and involves about 1–3% of the worldwide population over the age of 60. A significant prevalence of psychopathological symptoms has been recorded as most patients with PD developed over their disease course neuropsychiatric symptoms such as depression, anxiety, sleep disorders, psychosis, and cognitive and behavioral abnormalities. These non-motor symptoms, which could appear decades before motor ones, become disturbing symptoms during the later phases of the disease. Hence, the current research aims to study depressive symptoms in Parkinson's disease patients. Thirty-six patients with Parkinson’s disease aged from 40 to 65 years (20 males and 16 females) and 36 age and sex-matched controls (19 males and 17 females) were included in the study. Unified Parkinson’s Disease Rating Scale (UPDRS), Hoehn and Yahr scale, Schwab and England’s scale, Mini-Mental State Examination, Cognitive Ability Screening Instrument, and Hamilton Depression Rating Scale were applied to assess depression in both groups. Results Patients were 20 males and 16 females (mean age 52.44 ± 7.45), mean duration of Parkinsonism was 3.88 years. The mean value for Hoehn and Yahr scale was 1.97 ± 1.42, for UPDRS T was 42.41 ± 20.91 and Schwab England's scale was 74.77 ± 17.78. Concerning cognition, MMSE was significantly lower among patients 25.33 ± 3.63, than in the control group and CAS total was significantly lower in patients (16 ± 71.35) than in the control group 9.81 ± 84.62. Conclusion Depressive symptoms are widespread in Parkinson's disease. Depression should be strictly determined and addressed, particularly in patients with more advanced cognitive impairment who are at a higher risk of developing or worsening depression.

Abstract The main aim of this work is to study the main factors affecting the quality of the dried product and the energy requirements through optimizing these factors. To achieve that different drying systems (solar, hybrid solar and oven dryings), layers thickness (1, 2 and 3 cm) and drying temperatures (50, 60 and 70 °C) were used. The obtained results indicated that, the accumulated weight loss of marjoram leaves ranged from 73.22 to 76.9%, for all treatments under study. The moisture content of marjoram leaves ranged from 273.39 to 333.17, 258.02 to 333.04 and 269.38 to 324.90% d.b. for hybrid solar, oven and solar drying systems, respectively. The highest value of the drying rate of marjoram leaves (223.73 gwater kg−1 h−1) was obtained when the marjoram dried by oven drying system at 70 °C at 1 cm layer thickness. The highest values of the basil and marjoram oil content (2.91%) was obtained when the marjoram dried under sun drying system. The energy consumption for drying marjoram decreases with increasing drying temperature and layer thickness for hybrid solar and oven drying systems. The cost of dried marjoram dried under hybrid solar drying system was lower than those of oven drying system, the highest cost (13.48 LE kg−1) was obtained at a temperature of 50 °C and a layer thickness of 1 cm.

Abstract Several studies have shown association of single nucleotide polymorphisms (SNPs) of hepcidin regulatory pathways genes with impaired iron status. The most common is in the TMPRSS6 gene. In Africa, very few studies have been reported. We aimed to investigate the correlation between the common SNPs in the transmembrane protease, serine 6 (TMPRSS6) gene and iron indicators in a sample of Egyptian children for identifying the suitable candidate for iron supplementation. Patients and methods One hundred and sixty children aged 5–13 years were included & classified into iron deficient, iron deficient anemia and normal healthy controls. All were subjected to assessment of serum iron, serum ferritin, total iron binding capacity, complete blood count, reticulocyte count, serum soluble transferrin receptor and serum hepcidin. Molecular study of TMPRSS6 genotyping polymorphisms (rs4820268, rs855791 and rs11704654) were also evaluated. Results There was an association of iron deficiency with AG of rs855791 SNP, (P = 0.01). The minor allele frequency for included children were 0.43, 0.45 & 0.17 for rs4820268, rs855791 & rs11704654 respectively. Genotype GG of rs4820268 expressed the highest hepcidin gene expression fold, the lowest serum ferroportin & iron store compared to AA and AG genotypes (p = 0.05, p = 0.05, p = 0.03 respectively). GG of rs855791 had lower serum ferritin than AA (p = 0.04), lowest iron store & highest serum hepcidin compared to AA and AG genotypes (p = 0.04, p = 0.01 respectively). Children having CC of rs11704654 had lower level of hemoglobin, serum ferritin and serum hepcidin compared with CT genotype (p = 0.01, p = 0.01, p = 0.02) respectively. Conclusion Possible contribution of SNPs (rs855791, rs4820268 and rs11704654) to low iron status.

Background: Signal transduction induced by cytokines, which stimulates cell growth, proliferation, differentiation of germ cells, spermatogenesis, reproductive and testicular function. Objectives: The aim of this study is to evaluate seminal plasma as well as serum IL 17 levels in infertile male patients compared with fertile male with normal semen parameters. Patients and methods: This study is across-sectional case-control study that has been conducted on 40 infertile male patients and 10 fertile males as a control group, The patients were divided into four groups; group (A) included 10 patients with azoospermia, group (B) included 10 patients with oligozoospermia, group (C) included 10 patients with asthenozoospermia and group (D) included 10 patients with oligoasthenoteratozoospermia (OAT). All the patients in the four groups and the control group (E) are subjected to routine semen analysis and seminal, serum IL-17 was measured. Results: Seminal level of IL-17 is significantly reduced between control and patient groups . The mean is from (2.83 ± 0.6) to (11.19 ± 1.6) in azoospermia, (9.14 ± 2.3) in oligozoospermia, (9.25 ± 2.2) in asthenozoospermia and (10.88 ± 1.4) pg /ml in OAT group respectively, and (p= 0.004), The mean is from (25.31 ± 2.9) to (84.26 ± 10.0) in azoospermia, (78.51±6.6) in oligozoospermia, (65.60 ± 10.8) in asthenozoospermia and (82.43±8.5) pg/ml in AOT group respectively, and (p< 0.001). A significant negative correlation is found between seminal interleukin 17 level and the sperms count, concentration, Sperm total and progressive motility (r= -0.398, r = - 0.366, r = -0.429 and r = -0.394). And asignificant negative correlation is found between serum interleukin 17 level and the sperms count, concentration present in infertile men respectively (r= -0.338 and r = -0.341), and (p< 0.001). Conclusion: IL-17 plays an important role in male infertility and it had a negative correlation with sperm parameter.

Abstract Bio-diesel is used for engine as a replacement of diesel fuel which is characterized by lower emission, low pollution and renewable some of fuel. This study focus on how to enhance the production of bio-oil from Jatropha seeds by using microwave and ultrasonic as pre-treatments. To achieve that, the effects of extraction temperature (60, 80, 100 and 120 °C) and extraction screw speed (60, 90 and 120 rpm) on oil extraction yield and quality, extraction energy requirements and extraction time and were studied. Studying the effect of pretreatments by microwave and ultrasonic on the yield, energy and time of extraction were studied. The results most important indicate that the highest oil yield (25.1%) was recorded at 120 °C extraction temperature and 60 rpm screw speed. The energy required for extraction ranged from 8 to 11.5 W.h depending on temperature and speed of extraction. The results indicated that using both pretreatments improve the oil yield by 5.03% for microwave and by 6.75% for ultrasonic. Finally, the results concluded that to produce 1 kg of biodiesel you need 1.1 kg raw oil and consume from 2052.5 W.h energy requirement.

The study and investigation of the behavior of monetary phenomena is an interesting subject for actuaries and practitioners. In the recent age and development in the monetary and financial phenomena, cryptocurrency has gained much attention from actuaries. Over the past decade, several research studies have emerged on modeling and forecasting cryptocurrency exchange rates. This paper also contributes to the modeling of cryptocurrency exchange rates using a new version of the Logistic distribution, namely, a new cotangent-Logistic distribution. The mathematical properties and estimators of the new cotangent-logistic distribution's parameters are obtained. We illustrate the new cotangent-Logistic distribution using two financial data sets representing the log-returns of the Bitcoin and Ethereum prices. We compare the new cotangent-Logistic distribution with the baseline Logistic distribution and its modified version. Using the p-value and three other statistical tests, we show that the new cotangent-Logistic distribution repeatedly provides the optimal fit to cryptocurrency exchange rates.

Moniezia expansa worms are a significant source of alkaline phosphatase (ALP) and acetylcholinesterase (AChE) enzymes. The current study presents a simple and reproducible ALP and AChE purification method from Moniezia expansa helminthes by precipitating the proteins with ammonium sulfate and chromatography on the Sephacryl S-300 column. The M. expansa ALP purified at 1070.8 U/mg, displaying 6.0 purification folds and 53.6% yield, while M. expansa AChE is at 5250 U/mg, displaying 2.0 purification folds and 43% yield. The M. expansa ALP isoenzyme displayed its optimum activity at pH 9.6, while the M. expansa AChE isoenzyme displayed its optimum activity at pH 8.0. The affinity of M. expansa ALP for several substrates revealed that p-nitrophenyl phosphate preferentially cleaved with a Km value of 4.4 mM. M. expansa AChE preferentially cleaved acetylthiocholine iodide with a Km value of 0.9 mM. M. expansa ALP is strongly stimulated with Co2+, Mn2+, Ni2+, and Mg2+and reduced with Zn2+, Cu2+, Ca2+, EDTA and DTT. On the other hand, M. expansa AChE is significantly induced with Co2+, Zn2+, and Ni2+and inhibited with Mg2+, Ca2+, EDTA, 1,10-phenanthroline and eserine. The antisera of the purified M. expansa ALP and AChE found effective for determining the two enzymes in different unknown sera from different animal species, including humans, sheep and fish. These results may provide a possible future application of such enzymes in producing ALP and AChE-coated ELISA plates for research purposes.

Nitrate poisoning due to the consumption of cabbages was diagnosed in a small goat flock, in Qena city, Egypt. The methylene blue 1% antidote (1 mg/kg BW) was given intravenously to the poisoned goats. Nitrate poisoning was confirmed in blood plasma, saliva, urine, and cabbage dry matter samples. The dark brown blood and methemoglobin fraction were 47.25 ± 0.58%. Green cabbage containing 7.1% nitrate on dried materials was fed to the goats. The nitrate concentration in the saliva was (59.50 ± 4.67), compared to the healthy goats reared in the same area and tested positive in the plasma and urine of intoxicated goats. Intoxication induced a significant decline in the Red Blood Cells count, hemoglobin concentration, and HCT % (P

This article defines a new distribution using a novel alpha power-transformed method extension. The model obtained has three parameters and is quite effective in modeling skewed, complex, symmetric, and asymmetric datasets. The new approach has one additional parameter for the model. Certain distributional and mathematical properties are investigated, notably reliability, quartile, moments, skewness, kurtosis, and order statistics, and several approaches of estimation, notably the maximum likelihood, least square, weighted least square, maximum product spacing, Cramer-Von Mises, and Anderson Darling estimators of the model parameters were obtained. A Monte Carlo simulation study was conducted to evaluate the performance of the proposed techniques of estimation of the model parameters. The actuarial measures are computed for our recommended model. At the end of the paper, two insurance applications are illustrated to check the potential and utility of the suggested distribution. Evaluation using four selection criteria indicates that our recommended model is the most appropriate probability model for modeling insurance datasets.

Biochar derived from poultry manure increases nutrient availability and promotes plant growth. This study investigated the effect of biochar with mycorrhizal and/or plant growth-promoting rhizobacteria on soil fertility, chemical properties, oil, and seed yield of Black Cumin (Nigella sativa L.) plants. A split-plot design with three replicates was employed, with biochar derived from poultry litter (BC) applied at rates of 0, 5, and 10 t ha−1, with beneficial microbes such as arbuscular mycorrhizal fungi (AMF) and plant growth-promoting rhizobacteria (PGPR) affecting the growth of Black Cumin plants, and some soil properties, such as pH, electrical conductivity (EC), soil organic matter (SOM) and fertility index (FI), showing significant differences (p ≤ 0.05) among biochar and/or bio-fertilizer treatments. All biochar treatments with or without bio-fertilizers significantly increased pH, EC, OM and FI in comparison to the control treatment. The results demonstrated that applying biochar at the highest rate (10 t ha−1) increased fresh and dry capsule weights by 94.51% and 63.34%, respectively, compared to the control treatment (C). These values were significantly increased by 53.05 and 18.37%, compared to untreated plants when combined with AMF and PGPR. Furthermore, when biochar was applied in conjunction with both AMF and PGPR, fresh and dry capsule weights saw significant increases of 208.84% and 91.18%, respectively, compared to the untreated control treatment. The interaction between biochar, AMF, and PGPR significantly improved plant growth, yield, soil properties, and the fixed and volatile oil content of Black Cumin. These findings suggest that the combined application of biochar, AMF, and PGPR enhances nutrient availability and uptake, leading to improved growth and higher yields in Black Cumin plants, resulting in increased yield production.

Background and Objectives: Navigation systems are designed to enhance surgical precision, improving patient outcomes and reducing the risk of implant misplacement. In this study, we have evaluated a novel orthopedic surgical platform that utilizes CT imaging with AI-based algorithms to automate several critical aspects of total hip arthroplasty. It contains three modules—preoperative planning, navigation during surgery, and follow-up analysis. The primary objective of the current study was to evaluate the precision of the navigation tool in cup placement, i.e., whether the information displayed for navigation correctly reflected the actual position of the implant. Materials and Methods: Surgery outcomes of 15 inter-rater measurements on human cadavers and 18 surgeries on patients who underwent total hip replacement using the navigation tool were analyzed. Results: In the inter-rater assessment, the mean errors were −0.31 ± 1.42° for anteversion, 1.06 ± 1.73° for inclination, and −0.94 ± 1.76 mm for cup position depth. In patients’ surgeries, the mean errors were −0.07 ± 2.72° for anteversion, −0.2 ± 0.86° for inclination, and 0.28 ± 0.78 mm for cup depth. Conclusions: The navigation tool offers intra-operative guidance on notable precision in cup placement, thereby effectively mitigating the risk of cup malpositioning outside the patient-specific safe zone.

Tribolium castaneum is a challenging pest of stored products, causing significant economic losses. The present study explored the efficacy of Coridothymus capitatus essential oil and its primary constituent, carvacrol, as eco-friendly alternatives for managing this pest. To evaluate their insecticidal potential, repellency, fumigant toxicity, and antifeedant properties, progeny inhibition assays were performed. Carvacrol exhibited superior repellency compared to the essential oil, achieving a 92% repellency rate at 2 mg/cm2. Both compounds demonstrated significant fumigant toxicity against T. castaneum, with LC50 values of 168.47 and 106.5 μL/L for the essential oil and carvacrol, respectively, after 24 h. Carvacrol also outperformed the essential oil in antifeedant activity, inducing an 80.7% feeding deterrence at 1.17 mg/g. Moreover, both treatments effectively suppressed the development of the pest’s progeny. These results collectively underscore the potent insecticidal properties of C. capitatus essential oil and carvacrol, particularly carvacrol, as promising candidates for the sustainable management of T. castaneum in stored product protection.