Fabrication and Characterization of Montmorillonite Clay/Agar-Based Magnetic Composite and Its Biological and Electrical Conductivity Evaluation.

Montmorillonite clay and agar are naturally occurring materials of significant importance in designing biocompatible materials tailored for applications in biotechnology and medicine. The introduction of magnetic properties has the potential to significantly boost their characteristics and expand their applications. In this study, we have successfully synthesized highly intercalated magnetic composites, incorporating magnetic iron oxide nanoparticles (MNPs), montmorillonite clay (MMT), and agar (AG), through a thermo-physicomechanical method. Three samples of MMT-AG with 2, 1.5, and 0.5% MNPs and three sample composites of MNPs-AG with 2, 1, and 0.5% MMT clay are prepared. The synthesized composites were characterized by SEM, XRD, TGA, DTA, and FTIR. SEM analysis revealed a uniform dispersion of MNPs and MMT in the composite. The XRD pattern confirmed the presence of MNPs in the composite site. The TGA and DTA results demonstrated improved thermal stability due to the MNP incorporation. FTIR spectra showed all of the constituents of agar, MNPs, and MMT clay. The swelling ratio was observed to range from 835% to 1739%. The swelling study indicated an increased hydrophobicity with the addition of MNPs to the composite. Antibacterial activities revealed a significant inhibition of Escherichia coli (E. coli) growth by ranging from 10 to 19 nm in the composite. The composite also exhibited a considerable antioxidant action, with IC50 values of 7.96, 46.55, and 57.58 µg/mL, and electrical properties just like conductors.

Role of dietary fiber and lifestyle modification in gut health and sleep quality.

Dietary fiber has an immense role in the gut microbiome by modulating juvenile growth, immune system maturation, glucose, and lipid metabolism. Lifestyle changes might disrupt gut microbiota symbiosis, leading to various chronic diseases with underlying inflammatory conditions, obesity, and its associated pathologies. An interventional study of 16 weeks examined the impact of psyllium husk fiber with and without lifestyle modification on gut health and sleep quality in people with central obesity (men = 60 and women = 60), those aged from 40 to 60 years, those having WC ≥ 90 cm (men) and WC ≥ 80 cm (women), and no history of any chronic disease or regular medication. The participants were subgrouped into three intervention groups, namely, the psyllium husk fiber (PSH) group, the lifestyle modification (LSM) group, and the LSM&PSH group and control group with equal gender bifurcation (men = 15 and women = 15). A 24-h dietary recall, gastrointestinal tract (GIT) symptoms, and sleep quality analysis data were collected on validated questionnaires. The analyses of variance and covariance were used for baseline and post-intervention, respectively. Student's t-test was applied for pre- and post-intervention changes on the variable of interest. The intervention effect on GIT health was highly significant (P < 0.001). The mean GIT scores of the LSM, PSH, and LSM&PSH groups were 2.99 ± 0.14, 2.49 ± 0.14, and 2.71 ± 0.14, respectively, compared to the mean GIT scores of the control group. No significant (P = 0.205) effect of either intervention was observed on sleep quality. The study concluded that psyllium husk fiber significantly improved the GIT symptoms, while no significant effect of the intervention was observed on sleep quality analysis.

A novel approach towards web browser using the concept of a complex spherical fuzzy soft information.

The modern technology is the practical application of scientific knowledge, whether in industry or daily life, for goals or purposes. More quickly than any other technological advancement in human history, digital technologies have advanced. The technology sector is expanding and provides both new educational opportunities and innovative, exciting products. Right now, one of the most widely used and fascinating technologies is the web browser. This article introduced the novel concepts of complex spherical fuzzy soft relations (CSFSRs) by using the Cartesian Product (CP) of two complex spherical fuzzy soft sets (CSFSSs). Additionally, examples are used to clarify various types of relations. Because it discusses all levels of membership, abstinence, and non-membership with multidimensional variables, the CSFSRs have a detailed structure. The CSFSR-based modelling tools developed in this research, which primarily rely on the score function, can be used to choose the best Web browser. The transaction could be as easy as users sharing records via a functional web browser. Finally, the advantages of this suggested structure are illustrated by contrasting it with alternative structures.

Improved exponential type mean estimators for non-response case using two concomitant variables in simple random sampling.

This paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and comparisons are made with the existing estimators. The proposed estimators are observed more efficient as compared to the considered estimators in the literature. For instance, the classical [4] unbiased estimator, the estimator of [9], and other existing estimators under the explained conditions. The theoretical results are supported numerically by using real-life data sets, under the criteria of bias, mean square error, percent relative efficiency and mathematical conditions. It is also clear from the numerical results that the suggested exponential estimators performed better than the estimators in the literature.

Investigation of surface hardness, thermostability, tribo-corrosion, and microstructural morphological properties of microwave-synthesized high entropy alloy FeCoNiMnCu coating claddings on steel.

Deposition of high entropy alloy FeCoNiMnCu on SS-304 was carried out by microwave energy for application in "solid oxide fuel-cell (SOFC) interconnects". The ball-milling has been performed by taking "Fe, Co, Ni, Mn, and Cu" in equal 20 wt. % of before deposited on SS-304 substrate. The deposited steel with 20% Fe 20% Co 20% Ni 20% Mn 20% Cu high entropy alloy (HEA) was exposed to thermal-exposure in the air for up to 10 weeks at 800 °C. The uniform cladding distribution of 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA particles can be apparently observed on SS-304 substrate by utilizing Scanning Electron Microscope (SEM), and Optical microscopy analysis. Homogeneity in the interfacial layer was evident by employing Scanning Electron Microscope (SEM) characterization. Results have indicated that after the thermal exposure of deposited steel with 20% Fe 20% Co 20% Ni 20% Mn 20% Cu in the air for up to ten weeks at 800 °C, a "protective Cr2O3 layer", and "high-entropy spinel coating" of (Fe, Co, Ni, Mn, Cu)3O4 have been formed. During microwave cladding, the emergence of harder-phases has contributed to the raised hardness. The wear behavior after coating of 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA on SS-304 substrate has significantly enhanced due to the strengthened wear resistance and hardness of the coatings. Findings have exhibited that the formation of (Fe, Co, Ni, Mn, Cu)3O4 phase is a potential coating material for "SOFC interconnects" applications. Moreover, the cladding of SS304 with a composition of 20% Fe, 20% Co, 20% Ni, 20% Mn, and 20% Cu has demonstrated remarkable stability under thermal expansion studies. As the findings have revealed that the composite cladding has efficiently withstand significant variations in volume when subjected to elevated temperatures for a prolonged period of time, thus, exhibiting its superior thermal stability for SOFC-interconnect applications. Furthermore, the SEM images of the cladding surface, surface hardness, and tribocorrosion behavior of the coated material have been observed to identify the 20% Fe 20% Co 20% Ni 20% Mn 20% Cu HEA coating effect on SS-304 steel-substrate.

Global dynamics and computational modeling approach for analyzing and controlling of alcohol addiction using a novel fractional and fractal-fractional modeling approach.

In recent years, alcohol addiction has become a major public health concern and a global threat due to its potential negative health and social impacts. Beyond the health consequences, the detrimental consumption of alcohol results in substantial social and economic burdens on both individuals and society as a whole. Therefore, a proper understanding and effective control of the spread of alcohol addictive behavior has become an appealing global issue to be solved. In this study, we develop a new mathematical model of alcohol addiction with treatment class. We analyze the dynamics of the alcohol addiction model for the first time using advanced operators known as fractal-fractional operators, which incorporate two distinct fractal and fractional orders with the well-known Caputo derivative based on power law kernels. The existence and uniqueness of the newly developed fractal-fractional alcohol addiction model are shown using the Picard-Lindelöf and fixed point theories. Initially, a comprehensive qualitative analysis of the alcohol addiction fractional model is presented. The possible equilibria of the model and the threshold parameter called the reproduction number are evaluated theoretically and numerically. The boundedness and biologically feasible region for the model are derived. To assess the stability of the proposed model, the Ulam-Hyers coupled with the Ulam-Hyers-Rassias stability criteria are employed. Moreover, utilizing effecting numerical schemes, the models are solved numerically and a detailed simulation and discussion are presented. The model global dynamics are shown graphically for various values of fractional and fractal dimensions. The present study aims to provide valuable insights for the understanding the dynamics and control of alcohol addiction within a community.

Dynamics of the time-fractional reaction-diffusion coupled equations in biological and chemical processes.

This paper aims to demonstrate a numerical strategy via finite difference formulations for time fractional reaction-diffusion models which are ubiquitous in chemical and biological phenomena. The time-fractional derivative is considered in the Caputo sense for both linear and nonlinear problems. First, the Caputo derivative is replaced with a quadrature formula, then an implicit method is used for the remaining part. In the linear case, the proposed strategy reduces the time fractional models into linear simultaneous equations. In nonlinear cases, Quasilinearization is utilized to tackle the nonlinear parts. With this strategy, solutions of the fractional system transform into linear algebraic systems which are easy to solve. Next, the Von Neumann method is implemented to examine the stability of the scheme which discloses that the scheme is unconditionally stable. Further, the applicability of the presented scheme is tested with different linear and nonlinear models which include the one dimensional Schnakenberg and Gray-Scott models, and one and two dimensional Brusselator models. To analyze the accuracy of the present technique two norms namely, L ∞ and L 2 , and relative error are addressed. Moreover, the obtained outcomes are shown tabulated and graphically which identifies that the scheme properly works for the time fractional reaction-diffusion systems.

Enhancing tribo-mechanical, microstructural morphology, and corrosion performance of AZ91D-magnesium composites through the synergistic reinforcements of silicon nitride and waste glass powder.

The present investigation has employed recycled waste glass powder (WGP) and silicon nitride (Si3N4) as reinforcing-agents within AZ91D-matrix composites. The composites were fabricated by employing the vacuum stir casting technique to mitigate the effects of oxidation and to ensure homogeneity, uniformity, and superior wettability among the AZ91D-matrix and reinforcements. A microscopic study provided confirmation of a uniform dispersion of WGP and Si3N4 particles throughout the AZ91D-matrix. The tensile strength of the AZ91D/WGP/Si3N4 composites rise with the inclusion of WGP particulates by up to 1.5 percent in AZ91D/7.5% Si3N4. However, the tensile strength of the AZ91D/9%Si3N4 composite have showed maximum value as compared to other chosen formulations/combinations in the current investigation. The tensile strength of AZ91D/1.5% WGP/7.5% Si3N4 composites has strengthened up to 12.13 percent with the comparison of base alloy AZ91D-matrix. In A1 formulated composite, the amount of WGP particulate has enhanced the hardness of the AZ91D-alloy by up to 1.5 percent. Findings, nevertheless has exhibited that the A6 formulated composite had superior outcomes in terms of hardness. The incorporation of "reinforcing-constituent particulates" with 1.5%WGP + 7.5%Si3N4 combination within the AZ91D-matrix, has further increased fatigue-strength by around 57.84 percent. A weight-loss of 0.312 mg was being unveiled for the A1 formulated fabricated composite. The weight-loss for the A6 formulated fabricated composite, however, was reported to be 0.294 mg. At 5 N loads, 2 m/s sliding speed, and 1000 m of sliding distance, the developed 1.5%WGP/7.5%Si3N4/AZ91D composites was reported to have a rate of wear, and frictional coefficient of 0.0025 mm3/m and 0.315, respectively. The investigation employing scanning electron microscopy (SEM) identified the presence of corrosion pits on the surfaces that had undergone corrosion. These pits were found to be a result of localised surface assaults occurring in corrosive environments. Additionally, SEM pictures of the worn surfaces indicated the emergence of microcracks, which may be associated to the conditions of cyclic loading. Moreover, the tensile-fractography examination for the developed 1.5%WGP/7.5%Si3N4/AZ91D composites has exhibited the brittle fracture failure, including cracks and debonding phenomena. In addition, the EDS spectra-analysis have revealed an apparent existence of the observed Mg-peak, Si-peak, Al-peak, Ca-peak, and O-peak for the 1.5%WGP/7.5%Si3N4/AZ91D composites. Furthermore, the utilisation of X-ray diffraction analysis effectively determined the existence of hard phases inside the AZ91D-matrix, which significantly contributed to the reported enhancement in wear resistance. The development of harder-phases has included, α-Mg, Al12Mg17, SiO2, Si3N4, MgO, and CaO phases within the composite has been accountable for the enhancement of the tribomechanical, and wear-resistance characteristics of the AZ91D/WGP/Si3N4 composites. The Si3N4 has been discovered to have a substantial impact on enhancing mechanical performance and raising the resistance to wear.

Analysis of the convective heat transfer through straight fin by using the Riemann-Liouville type fractional derivative: Probed by machine learning.

This work aims to analyze the transfer of heat through new fractional-order convective straight fins by using the Riemann-Liouville type fractional derivatives. The convection through the fins is considered in such a way that the thermal conductivity depends on the temperature. The transformed fractional-order problems are constituted through an optimization problem in such a way that the L2 norm remains minimal. The objective functions are further analyzed with the hybrid Cuckoo search (HCS) algorithm that use the artificial neural network (ANN) mechanism. The impacts of the fractional parameter ß, the thermo-geometric parameter of fin ψ, and dimensionless thermal conductivity α are explained through figures and tables. The fin efficiency during the whole process is explained with larger values of ψ. It is found that the larger values of ψ decline the fin efficacy. The fractional parameter declines the thermal profile as we approach the integer order. The convergence of HCS algorithm is performed in each case study. The residual error touches E-14 for the integer order of α. The present results are validated through Table 6 by comparing with HPM, VIM and LHPM, while the error for HCS-ANN touches E-13. This proves that the proposed HCS is efficient.

Utilization of discarded face masks in combination with recycled concrete aggregate and silica fume for sustainable civil construction projects.

The coronavirus (COVID-19) pandemic has not only had a severe impact on global health but also poses a threat to the environment. This research aims to explore an innovative approach to address the issue of increased waste generated by the pandemic. Specifically, the study investigates the utilization of discarded face masks in combination with recycled concrete aggregate (RCA) and Silica Fume (SFM) in civil construction projects. The disposable face masks were processed by removing the ear loops and nose strips, and then cutting them into small fibers measuring 20 mm in length, 5 mm in width, and 0.46 mm in thickness, resulting in an aspect ratio of 24. Various proportions of SFM and RCA were incorporated into the concrete mix, with a focus on evaluating the compressive strength, split tensile strength, and durability of the resulting material. The findings indicate that the addition of SFM led to improvements in both compressive and split tensile strength, while no significant impact on durability was observed.

Provenance, diagenesis, and depositional environment of Miocene Kamlial Formation, Azad Jammu and Kashmir, Sub Himalayas, Pakistan: Evidences from field observations and petrography.

Petrographical characterization and field observations were caried out to evaluate Kamlial Formation in Bagh district, Azad Jammu and Kashmir. Based on detailed petrography, the lithic arenite consisted of quartz (20-25%), feldspar (7-11%), rock fragments (20-37%), cementing materials (11-21%), and accessory minerals. Grains are mostly angular to subrounded and poorly to moderately sorted. The analysis revealed that the lithic arenite is mineralogically immature; also, the current activity during the time of deposition was low. Polycrystalline quartz indicates that the sandstone was derived from metamorphic source, while monocrystalline quartz indicates a granitic origin. Quartz having an angular shape suggests the source rock was near the depositional site, while quartz having a rounded shape represents long transportation. The presence of feldspar in the lithic arenite suggests the rocks were deposited at high relief or cold temperatures. Primary porosity in sandstone was reduced by calcite cements around the grain, while secondary porosity was developed by fracturing of quartz and feldspar. Tectonic uplift in the study area was demonstrated by fractured quartz and mica in thin sections. Field observations of various sedimentary structures were observed such as load casts, ripple marks, and mud cracks, etc. The presence of conglomerates and load casts in the study area indicates that the Kamlial sandstone was deposited by fluvial and shallow marine environment. Furthermore, the ripple marks indicate that the tidal flat environment controlled the deposition of the sediments.

Impact of chemical reaction on Eyring-Powell fluid flow over a thin needle with nonlinear thermal radiation.

The thin needle is viewed as a revolutionary object since it has a thinner thickness than a boundary layer. As a consequence, scientific and engineering applications for instance electrical equipment, hot wire anemometers and geothermal power generation are significantly impacted by the flow deformed by a thin moving needle. MHD Eyring-Powell fluid flow over a thin needle perceiving heat source, chemical reaction and nonlinear thermal radiation is the subject of the current investigation. In addition, the present study utilizes the Buongiorno model to examine the special effects of the fluid's Brownian and thermophoretic forces. The solution of the dimensionless form of ODEs is produced by applying exact renovations to the given problem, which is determined by the structure of PDEs. The bvp4c algorithm, based on the finite difference approach is utilized to numerically solve such modified ODEs. For validation, the results obtained indicate good agreement when compared to the literature. Finally, a detailed graphical analysis of key parameters is shown and explained while keeping in mind the physical significance of flow parameters. The results show that as magnetic and fluid parameter values improve, the velocity gradient falls. Increasing heat source and radiation parameters optimises heat transfer rate. The augmentation of the Lewis number and chemical reaction accelerates the rate of mass transfer on the surface. Brownian motion and thermophoresis provide enhanced thermal performance for the fluid temperature. Growing the thermophoresis parameter from 0.1 to 0.3 upsurges the Nusselt number by 5.47% and the Sherwood number by 12.26%.

Magnetohydrodynamics and viscosity variation in couple stress squeeze film lubrication between rough flat and curved circular plates.

A simplified mathematical model has been developed for understanding combined effects of surface roughness, viscosity variation and couple stresses on the squeeze film behaviour of a flat and a curved circular plate in the presence of transverse magnetic field. The Stokes (1966) couple stress fluid model is included to account for the couple stresses arising due to the presence of microstructure additives in the lubricant. In the context of Christensen's (1969) stochastic theory for the lubrication of rough surfaces, two types of one-dimensional roughness patterns (radial and azimuthal) are considered. The governing modified stochastic Reynolds type equations are derived for these roughness patterns. Expressions for the mean squeeze film characteristics are obtained. Numerical computations of the results show that the azimuthal roughness pattern on the curved circular and flat plate results in more pressure buildup whereas performance of the squeeze film suffers due to the radial roughness pattern. Further the Lorentz force characterized by the Hartmann number, couple stress parameter and viscosity variation parameter improve the performance of the squeeze film lubrication as compared to the classical case (Non-magnetic, Newtonian case and non-viscous case).

Exploring the relationship between air quality index and lung cancer mortality in India: predictive modeling and impact assessment.

The Air Quality Index (AQI) in India is steadily deteriorating, leading to a rise in the mortality rate due to Lung Cancer. This decline in air quality can be attributed to various factors such as PM 2.5, PM 10, and Ozone (O3). To establish a relationship between AQI and Lung Cancer, several predictive models including Linear Regression, KNN, Decision Tree, ANN, Random Forest Regression, and XGBoost Regression were employed to estimate pollutant levels and Air Quality Index in India. The models relied on publicly available state-wise Air Pollution Dataset. Among all the models, the XGBoost Regression displayed the highest accuracy, with pollutant level estimations reaching an accuracy range of 81% to 98% during training and testing. The second-highest accuracy range was achieved by Random Forest. The paper also explores the impact of increasing pollution levels on the rising mortality rate among lung cancer patients in India.

An efficient framework for obtaining the initial cluster centers.

Clustering is an important tool for data mining since it can determine key patterns without any prior supervisory information. The initial selection of cluster centers plays a key role in the ultimate effect of clustering. More often researchers adopt the random approach for this purpose in an urge to get the centers in no time for speeding up their model. However, by doing this they sacrifice the true essence of subgroup formation and in numerous occasions ends up in achieving malicious clustering. Due to this reason we were inclined towards suggesting a qualitative approach for obtaining the initial cluster centers and also focused on attaining the well-separated clusters. Our initial contributions were an alteration to the classical K-Means algorithm in an attempt to obtain the near-optimal cluster centers. Few fresh approaches were earlier suggested by us namely, far efficient K-means (FEKM), modified center K-means (MCKM) and modified FEKM using Quickhull (MFQ) which resulted in producing the factual centers leading to excellent clusters formation. K-means, which randomly selects the centers, seem to meet its convergence slightly earlier than these methods, which is the latter's only weakness. An incessant study was continued in this regard to minimize the computational efficiency of our methods and we came up with farthest leap center selection (FLCS). All these methods were thoroughly analyzed by considering the clustering effectiveness, correctness, homogeneity, completeness, complexity and their actual execution time of convergence. For this reason performance indices like Dunn's Index, Davies-Bouldin's Index, and silhouette coefficient were used, for correctness Rand measure was used, for homogeneity and completeness V-measure was used. Experimental results on versatile real world datasets, taken from UCI repository, suggested that both FEKM and FLCS obtain well-separated centers while the later converges earlier.

Fault tolerant trust based task scheduler using Harris Hawks optimization and deep reinforcement learning in multi cloud environment.

Cloud Computing model provides on demand delivery of seamless services to customers around the world yet single point of failures occurs in cloud model due to improper assignment of tasks to precise virtual machines which leads to increase in rate of failures which effects SLA based trust parameters (Availability, success rate, turnaround efficiency) upon which impacts trust on cloud provider. In this paper, we proposed a task scheduling algorithm which captures priorities of all tasks, virtual resources from task manager which comes onto cloud application console are fed to task scheduler which takes scheduling decisions based on hybridization of both Harris hawk optimization and ML based reinforcement algorithms to enhance the scheduling process. Task scheduling in this research performed in two phases i.e. Task selection and task mapping phases. In task selection phase, all incoming priorities of tasks, VMs are captured and generates schedules using Harris hawks optimization. In task mapping phase, generated schedules are optimized using a DQN model which is based on deep reinforcement learning. In this research, we used multi cloud environment to tackle availability of VMs if there is an increase in upcoming tasks dynamically and migrate tasks to one cloud to another to mitigate migration time. Extensive simulations are conducted in Cloudsim and workload generated by fabricated datasets and realtime synthetic workloads from NASA, HPC2N are used to check efficacy of our proposed scheduler (FTTHDRL). It compared against existing task schedulers i.e. MOABCQ, RATS-HM, AINN-BPSO approaches and our proposed FTTHDRL outperforms existing mechanisms by minimizing rate of failures, resource cost, improved SLA based trust parameters.

Numerical assessment of irreversibility in radiated Sutterby nanofluid flow with activation energy and Darcy Forchheimer.

Entropy generation is a concept that is primarily associated with thermodynamics and engineering, and it plays a crucial role in understanding and optimizing various processes and systems. Applications of entropy generation can be seen in turbo machinery, reactors, chillers, desert coolers, vehicle engines, air conditioners, heat transfer devices and combustion. Due to industrial applications entropy generation has gained attention of researchers. Owing such applications, current communication aims to model and analyzed the irreversibility in Sutterby nanoliquid flow by stretched cylinder. Momentum equation is reported by considering porosity, Darcy Forchheimer and magnetic field. While in energy equation radiation and Joule heating effects are accounted. Activation energy impact is accounted in the modeling of concentration equation. Thermodynamics second law is utilized for physical description of irreversibility analysis. Through similarity transformations dimensional equations representing flow are transformed to dimensionless ones. Numerical solution for ordinary system is obtained via Runge-Kutta-Fehlberg scheme in Mathematica platform through NDsolve code. Influence of prominent variables on velocity, entropy, temperature, Bejan number and concentration are graphically analyzed. Coefficient of skin friction, gradient of temperature and Sherwood number are numerically analyzed. The obtained results show that velocity field decreases through higher porosity and Forchheimer variables. Velocity and temperature curves shows an opposite trend versus magnetic parameter. A decay in concentration distribution is noticed through larger Schmidt number. Entropy generation amplifies against magnetic parameter and Brinkman number.

Empirical models for compressive and tensile strength of basalt fiber reinforced concrete.

When molten magma solidifies, basalt fiber (BF) is produced as a byproduct. Due to its remaining pollutants that could affect the environment, it is regarded as a waste product. To determine the compressive strength (CS) and tensile strength (TS) of basalt fiber reinforced concrete (BFRC), this study will develop empirical models using gene expression programming (GEP), Artificial Neural Network (ANN) and Extreme Gradient Boosting (XG Boost). A thorough search of the literature was done to compile a variety of information on the CS and TS of BFRC. 153 CS findings and 127 TS outcomes were included in the review. The water-to-cement, BF, fiber length (FL), and coarse aggregates ratios were the influential characteristics found. The outcomes showed that GEP can accurately forecast the CS and TS of BFRC as compared to ANN and XG Boost. Efficiency of GEP was validated by comparing Regression (R2) value of all three models. It was shown that the CS and TS of BFRC increased initially up to a certain limit and then started decreasing as the BF % and FL increased. The ideal BF content for industrial-scale BF reinforcement of concrete was investigated in this study which could be an economical solution for production of BFRC on industrial scale.

Rheological study of Hall current and slip boundary conditions on fluid-nanoparticle phases in a convergent channel.

Purpose: the purpose of this theoretical study was to analyze the heat transfer in the fluid-particle suspension model under the effects of a porous medium, magnetic field, Hall effects, and slip boundary conditions in a convergent channel with the addition of electrokinetic phenomena. The Darcy-Brinkman (non-Darcy porous medium) model was used to assess the effects of the porous medium. Methodology: the rheological equations of both models were transformed into a dimensionless form to obtain the exact solutions of the fluid and particle phase velocities, pressure gradient, volumetric flow rate, stream function, temperature distribution, and heat-transfer rate. To obtain an exact solution to the models, the physical aspects of the parameters are discussed, analyzed, and reported through graphs, contour plots, and in tabular form. Findings: mixing in hafnium particles in a viscous fluid provide 1.2% more cooling compared to with a regular fluid. A reduction of the streamlines was observed with the contribution of the slip condition. The utilization of the Darcy parameters upgraded both the fluid flow and temperature profiles, while the heat-transfer rate decreased by up to 3.3% and 1.7% with the addition of a magnetic field and porous medium, respectively. Originality: the current study is an original work of the authors and has not been submitted nor published elsewhere.

Predictors of mental health problems during the COVID-19 outbreak in Egypt in 2021.

Background: With the widespread outbreak of the coronavirus (COVID-19) pandemic, many countries, including Egypt, have tried to restrict the virus by applying social distancing and precautionary measures. Understanding the impact of COVID-19-induced risks and social distancing measures on individuals' mental health will help mitigate the negative effects of crises by developing appropriate mental health services. This study aimed to investigate the most contributing factors that affected individuals' mental health and how individuals' mental health has changed over the lockdown period in Egypt in 2021. Methods: The study draws on a nationally representative sample from the combined COVID-19 MENA Monitor Household Survey conducted by the Economic Research Forum. The data were collected in Egypt by phone over two waves in February 2021 and June 2021. The total number of respondents is 4,007 individuals. The target population is mobile phone owners aged 18-64 years. The 5-item World Health Organization Well-Being Index (WHO-5) is used to assess the individuals' mental health over the past 2 weeks during the pandemic. Penalized models (ridge and LASSO regressions) are used to identify the key drivers of mental health status during the COVID-19 pandemic. Results: The mean value of mental health (MH) scores is 10.06 (95% CI: 9.90-10.23). The average MH score for men was significantly higher than for women by 0.87. Rural residents also had significantly higher MH scores than their urban counterparts (10.25 vs. 9.85). Middle-aged adults, the unemployed, and respondents in low-income households experienced the lowest MH scores (9.83, 9.29, and 9.23, respectively). Individuals' mental health has deteriorated due to the negative impacts of the COVID-19 pandemic. Regression analysis demonstrated that experiencing food insecurity and a decrease in household income were independent influencing factors for individuals' mental health (p < 0.001). Furthermore, anxiety about economic status and worrying about contracting the virus had greater negative impacts on mental health scores (p < 0.001). In addition, women, middle-aged adults, urban residents, and those belonging to low-income households were at increased risk of poor mental health (p < 0.05). Conclusion: The findings reveal the importance of providing mental health services to support these vulnerable groups during crises and activating social protection policies to protect their food security, incomes, and livelihoods. A gendered policy response to the pandemic is also required to address the mental pressures incurred by women.