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Epidemiological models feature reliable and valuable insights into the prevention and transmission of life-threatening illnesses. In this study, a novel SIR mathematical model for COVID-19 is formulated and examined. The newly developed model has been thoroughly explored through theoretical analysis and computational methods, specifically the continuous Galerkin–Petrov (cGP) scheme. The next-generation matrix approach was used to calculate the reproduction number (R0)({R}_{0}). Both disease-free equilibrium (DFE) (E0)({E}^{0}) and the endemic equilibrium (E⁎)({E}^{\ast }) points are derived for the proposed model. The stability analysis of the equilibrium points reveals that (E0)({E}^{0}) is locally asymptotically stable when R01{R}_{0}\gt 1. We have examined the model’s local stability (LS) and global stability (GS) for endemic equilibrium \text{ }and DFE based on the number (R0)({R}_{0}). To ascertain the dominance of the parameters, we examined the sensitivity of the number (R0)({R}_{0}) to parameters and computed sensitivity indices. Additionally, using the fourth-order Runge–Kutta (RK4) and Runge–Kutta–Fehlberg (RK45) techniques implemented in MATLAB, we determined the numerical solutions. Furthermore, the model was solved using the continuous cGP time discretization technique. We implemented a variety of schemes like cGP(2), RK4, and RK45 for the COVID-19 model and presented the numerical and graphical solutions of the model. Furthermore, we compared the results obtained using the above-mentioned schemes and observed that all results overlap with each other. The significant properties of several physical parameters under consideration were discussed. In the end, the computational analysis shows a clear image of the rise and fall in the spread of this disease over time in a specific location.

Identifying the most optimal wearable health technology devices for hospitals is a crucial step in emergency decision-making. The multi-attribute group decision-making method is a widely used and practical approach for selecting wearable health technology devices. However, because of the various factors that must be considered when selecting devices in emergencies, decision-makers often struggle to create a comprehensive assessment method. This study introduced a novel decision-making method that took into account various factors of decision-makers and has the potential to be applied in various other areas of research. First, we introduced a list of aggregation operators based on Pythagorean hesitant fuzzy rough sets, and a detailed description of the desired characteristics of the operators under investigation were provided. The proposed operators were validated by a newly defined score and accuracy function. Second, this paper used the proposed approach to demonstrate the Pythagorean hesitant fuzzy rough technique for order of preference by similarity to ideal solution (TOPSIS) model for multiple attribute decision-making and its stepwise algorithm. We developed a numerical example based on suggested operators for the evaluation framework to tackle the multiple-attribute decision-making problems while evaluating the performance of wearable health technology devices. In the end, the sensitivity analysis has confirmed the performance and reliability of the proposed framework. The findings indicated that the models being examined demonstrated greater reliability and efficacy compared to existing methodologies.

In this manuscript, we carried out a thorough analysis of the general SIR model for epidemics. We broadened the model to include vaccination, treatment, and incidence rate. The vaccination rate is a testament to the alternatives made by individuals when it comes to receiving vaccinations and merging with the community of the recovered. The treatment rate measures how often people who have contracted a disease are able to transition into the recovered category. The continuous Galerkin-Petrov method, specifically the cGP(2)-method, is employed to calculate the numerical solutions of the models. The cGP(2)-method imperative to analyse two unknowns over every time interval. The unknowns can be determined by solving a block system of size (2 × 2). This approach demonstrates a strong level of precision throughout the entire time interval, with an impressive rate of convergence at the discrete time points. In addition, the article investigates the concept of the basic reproduction number ([Formula: see text]) and explores the intricacies of conducting sensitivity analysis of the developed system.

Western Asia represents a mixing pot of diverse bat species with distributions spanning across other geographic regions. Yet, relative to other regions, there is a significant gap in coordinated bat research in Western Asia, thereby resulting in a relatively limited number of curated occurrence records.The Western Asia Bat Research Network (WAB-Net) project was created to strengthen research capacity and knowledge of the diversity and distribution of bat species in a little-studied region, as well as to collect data to characterise the diversity and prevalence of coronaviruses in diverse bat species. Over a four-year period (2018–2022), we documented 4,278 individual records for 41 bat species using a cross-sectional survey approach at 50 sites in seven Western Asian countries, specifically Armenia, Azerbaijan, Georgia, Jordan, Oman, Pakistan and Turkiye. At each site, we captured, on average, 90 individual bats (range: 9-131) over multiple consecutive nights and used standardised methods to collect demographic and morphological data from captured individuals. We additionally completed a systematic evaluation of environmental characterisation and human-bat interactions at all 50 sites. Here, we report individual occurrence records and site conditions from this multi-country, multi-year sampling effort.

Multi-modal biometric schemes, which leverage more than one sensor, offer significant advantages over uni-modal schemes in terms of accuracy and robustness against attacks. In this paper, we present a novel behavioral multi-biometric user authentication scheme that employs data fusion for biometric-based authentication. The proposed scheme extracts two types of data (Electromyography (EMG) and movements) from a single user’s clapping action type, via a worn smartwatch. During the user enrollment phase, the scheme creates a digital identity of the user based on the arm’s movement and EMG signatures generated through the entire period of clapping action. In the verification phase, the scheme authenticates users based on the detected combined EMG and movement signature. The experimental analysis of the proposed scheme employing a Deep Neural Network classifier demonstrates its efficacy; our classifier achieves a True Accept Rate of 94.37%, a False Accept Rate of just 0.11%, and an accuracy of 97.13%. Furthermore, it is experimentally demonstrated that augmenting the training dataset via Generative Adversarial Networks leads to even better performance; with improved TAR (up to $\approx 96$ %) and accuracy (up to 97.94%), while decreasing FAR (from 0.11% to 0.082%). These results showcase the effectiveness and robustness of the proposed bi-modal behavioral biometric scheme for smartwatch user authentication.

In this research, we introduce the intuitionistic hesitant fuzzy rough set by integrating the notions of an intuitionistic hesitant fuzzy set and rough set and present some intuitionistic hesitant fuzzy rough set theoretical operations. We compile a list of aggregation operators based on the intuitionistic hesitant fuzzy rough set, including the intuitionistic hesitant fuzzy rough Dombi weighted arithmetic averaging aggregation operator, the intuitionistic hesitant fuzzy rough Dombi ordered weighted arithmetic averaging aggregation operator, and the intuitionistic hesitant fuzzy rough Dombi hybrid weighted arithmetic averaging aggregation operator, and demonstrate several essential characteristics of the aforementioned aggregation operators. Furthermore, we provide a multi attribute decision-making approach and the technique of the suggested approach in the context of the intuitionistic hesitant fuzzy rough set. A real-world problem for selecting a suitable worldwide partner for companies is employed to demonstrate the effectiveness of the suggested approach. The sensitivity analysis of the decision-making results of the suggested aggregation operators are evaluated. The demonstrative analysis reveals that the outlined strategy has applicability and flexibility in aggregating intuitionistic hesitant fuzzy rough information and is feasible and insightful for dealing with multi attribute decision making issues based on the intuitionistic hesitant fuzzy rough set. In addition, we present a comparison study with the TOPSIS approach to illustrate the advantages and authenticity of the novel procedure. Furthermore, the characteristics and analytic comparison of the current technique to those outlined in the literature are addressed.

Abstract Rabies, commonly referred to as the endemic disease of the impoverished in Pakistan, remains a significant public health concern. Globally, it contributes to over 55,000 fatalities annually, with 31,000 cases reported in Asia, predominantly among children. In Karachi, the yearly occurrence of rabies ranges between 7 and 9.8 cases per million individuals. However, the actual burden is likely underestimated due to underreporting. Key challenges in Pakistan include limited awareness and increasing dog bite incidents. To address this, comprehensive educational programs focusing on proper wound care, the ineffectiveness of homemade remedies, the importance of early medical intervention, and the administration of vaccines and post‐exposure prophylaxis are imperative. Implementing a One Health model, encompassing mass vaccination, cost‐effective treatments, training on intradermal vaccine administration, accurate data collection, and community awareness initiatives, is essential for rabies control. This article aims to provide policymakers and scholars with valuable insights into the primary factors and challenges of controlling endemic human rabies in Pakistan and proposes effective strategies for its control, with the ultimate goal of achieving rabies‐free status by 2030.

The transportation sector is among the highest contributors to the increase in greenhouse gas emissions in European nations, with private cars emerging as the primary source. Although reducing emissions presents a formidable challenge, the emergence of battery electric vehicles (BEVs) offers a promising and sustainable avenue toward achieving zero greenhouse gases within the transportation infrastructure. Since the 1990s, the Norwegian parliament has fervently supported this transition, leveraging public awareness campaigns and a range of financial incentives for its users nationwide. The widespread utilization of BEVs promises substantial health benefits, including ensuring cleaner air for all citizens regardless of their socioeconomic status and fostering improvements in public health outcomes. This transition potentially curtails hundreds of thousands of annual deaths attributed to climate change, enhances the quality of life, bolsters civilian productivity, and fuels economic and population growth. The adoption of BEVs offers a myriad of advantages, including reduced health risks and premature mortality, as well as a quieter environment with diminished noise pollution. Nonetheless, the integration of BEVs necessitates robust road infrastructure with considerable maintenance costs, alongside limitations on driving range for users. Concerns arise regarding potential particle emissions from BEV tire wear due to the increased weight of batteries compared to conventional vehicles. Rapid acceleration capabilities may accelerate tire degradation, contributing to higher particle emissions, of which only 10% to 20% remain suspended in the air, whereas the majority settles on road surfaces, posing a threat to nearby aquatic ecosystems when washed into water bodies and soils. While BEVs hold promise for valuable benefits, successful policy creation and implementation require a detailed awareness of their limitations and challenges to ensure a comprehensive approach to sustainable mobility and public health improvement. Therefore, more research on the limitations of BEVs can help inform improved tactics for maximizing their benefits while limiting potential disadvantages.

Abstract The removal of toxic dye pigments from the environment is of utmost importance since even trace amounts of these pollutants can lead to harmful impacts on ecosystems. Heterogeneous photocatalysis is a potential technique for eliminating microbiological, inorganic, and organic pollutants from wastewater. Here, we report the band gap alteration of ZnO by making its composites with CuSe to enhance photocatalytic activity. The purpose is to develop metal oxide nanocomposites (ZnO/CuSe) as an effective and efficient material for the photodegradation of methyl blue. The photocatalysts, ZnO nanorods, CuSe, and ZnO/CuSe nanocomposites of different weight ratios were synthesized by the simple and cost-effective technique of precipitation. UV–Vis spectra verified that the ZnO/CuSe photocatalyst improved absorption in the visible region. The optical bandgap of ZnO/CuSe nanocomposites reduced from 3.37 to 2.68 eV when CuSe concentration increased from 10 to 50%. ZnO/CuSe composites demonstrated better photocatalytic activity than ZnO when exposed to UV–visible light. The pure ZnO nanorods could absorb UV light and the nanocomposites could absorb visible light only; this was attributed to the transfer of excited high-energy electrons from ZnO to CuSe.

This paper presents a novel robust output feedback control that simultaneously performs both stabilization and trajectory tracking for a class of underactuated nonholonomic systems despite model uncertainties, external disturbance, and the absence of velocity measurement. To solve this challenging problem, a generalized normal form has been successfully created by employing an input–output feedback linearization approach and a change in coordinates (diffeomorphism). This research mainly focuses on the stabilization problem of nonholonomic systems that can be transformed to a normal form and pose several challenges, including (i) a nontriangular normal form, (ii) the internal dynamics of the system are non-affine in control, and (iii) the zero dynamics of the system are not in minimum phase. The proposed scheme utilizes combined backstepping and sliding mode control (SMC) techniques. Furthermore, the full-order high gain observer (HGO) has been developed to estimate the derivative of output functions and internal dynamics. Then, full-order HGO and the backstepping SMC have been integrated to synthesize a robust output feedback controller. A differential-drive type (2,0) the wheeled mobile robot has been considered as an example to support the theoretical results. The simulation results demonstrate that the backstepping SMC exhibits robustness against bounded uncertainties.

Environmental science and pollution research has benefits around the globe. Human activity produces more garbage throughout the day as the world's population and lifestyles rise. Choosing a garbage disposal site (GDS) is crucial to effective disposal. In illuminated of the advancements in society, decision-makers concede a significant challenge for assessing an appropriate location for a garbage disposal site. This research used a multi-attribute decision-making (MADM) approach based on $ q $-rung orthopair hesitant fuzzy rough ($ q $-ROHFR) Einstein aggregation information for evaluating GDS selection schemes and providing decision-making (DM) support to select a suitable waste disposal site. In this study, first, q-ROHFR Einstein average aggregation operators are integrated. Some intriguing characteristics of the suggested operators, such as monotonicity, idempotence and boundedness were also explored. Then, a MADM technique was established using the novel concept of $ q $-ROHFR aggregation operators under Einstein t-norm and t-conorm. In order to help the decision makers (DMs) make a final choice, this technique aims to rank and choose an alternative from a collection of feasible alternatives, as well as to propose a solution based on the ranking of alternatives for a problem with conflicting criteria. The model's adaptability and validity are then demonstrated by an analysis and solution of a numerical issue involving garbage disposal plant site selection. We performed a the sensitivity analysis of the proposed aggregation operators to determine the outcomes of the decision-making procedure. To highlight the potential of our new method, we performed a comparison study using the novel extended TOPSIS and VIKOR schemes based on $ q $-ROHFR information. Furthermore, we compared the results with those existing in the literature. The findings demonstrate that this methodology has a larger range of information representation, more flexibility in the assessment environment, and improved consistency in evaluation results.

The use of biosynthesized metallic and bimetallic nanoparticles (NPs) as biocides for plant protection has gained significant attention in recent years due to their potential for sustainable and ecofriendly crop protection. In this review article, we discussed the biosynthesis of metallic and bimetallic NPs using various biological sources such as plants, fungi, bacteria, and algae. We explore the plausible mechanisms behind the biocidal activity of these NPs, including their ability to disrupt cellular structures, inhibit enzyme activity, induce oxidative stress, and modulate plant defense responses. We also highlight the challenges and limitations associated with the use of biosynthesized NPs, including their potential toxicity to nontarget organisms, potential impact on soil health, and the need for standardized protocols for their synthesis and characterization. Additionally, we discuss the potential strategies for overcoming these challenges, including the use of biocompatible stabilizers, controlled release formulations, and targeted delivery systems. Overall, biosynthesized metallic and bimetallic NPs hold promise as effective biocides for plant protection, but further research is needed to fully understand their mechanisms of action, optimize their efficacy, and ensure their safe and sustainable use in agriculture. In addition to exploring the biocidal mechanisms and challenges of using biosynthesized metallic and bimetallic NPs for plant protection, this review also delves into the cost-benefit analysis of their application in agriculture.

Abstract There are numerous contagious diseases caused by pathogenic microorganisms, including bacteria, viruses, fungi, and parasites, that have the propensity to culminate in fatal consequences. A communicable disease is an illness caused by a contagion agent or its toxins and spread directly or indirectly to a susceptible animal or human host by an infected person, animal, vector, or immaterial environment. Human immunodeficiency virus (HIV) infection, hepatitis A, B, and C, and measles are all examples of communicable diseases. Acquired immunodeficiency syndrome (AIDS) is a communicable disease caused by HIV infection that has become the most severe issue facing humanity. The research work in this paper is to numerically explore a mathematical model and demonstrate the dynamics of HIV/AIDS disease transmission using a continuous Galerkin–Petrov time discretization of a higher-order scheme, specifically the cGP(2)-scheme. Depict a graphical and tabular comparison between the outcomes of the mentioned scheme and those obtained through other classical schemes that exist in the literature. Further, a comparison is performed relative to the well-known fourth-order Ruge–Kutta (RK4) method with different step sizes. By contrast, the suggested approach provided more accurate results with a larger step size than RK4 with a smaller step size. After validation and confirmation of the suggested scheme and code, we implement the method to the extended model by introducing a treatment rate and show the impact of various non-linear source terms for the generation of new cells. We also determined the basic reproduction number and use the Routh-Hurwitz criterion to assess the stability of disease-free and unique endemic equilibrium states of the HIV model.

Abstract The precise selection of suppliers to fulfill production requirements is a fundamental component of all manufacturing and process industries. Due to the increasing consumption levels, green supplier selection (GSS) has been one of the most important issues for environmental preservation and sustainable growth. The present work aims to develop a technique based on Fermatean hesitant fuzzy rough set (FHFRS), a robust fusion of Fermatean fuzzy set, hesitant fuzzy set, and rough set for GSS in the process industry. On the basis of the operational rules of FHFRS, a list of innovative Fermatean hesitant fuzzy rough weighted averaging operators has been established. Further, several intriguing features of the proposed operators are highlighted. To cope with the ambiguity and incompleteness of real-world decision-making (DM) challenges, a DM algorithm has been developed. To illustrate the applicability of the methodology, a numerical example for the chemical processing industry is presented to determine the optimum supplier. The empirical findings suggest that the model has a significant application of scalability for GSS in the process industry. Finally, the improved FHFR-VIKOR and TOPSIS approaches are employed to validate the proposed technique. The results demonstrate that the suggested DM approach is practicable, accessible, and beneficial for addressing uncertainty in DM problems.

Water contamination can be detrimental to the human health due to higher concentration of carcinogenic heavy metals such as chromium (Cr) in the wastewater. Many traditional methods are being employed in wastewater treatment plants for Cr removal to control the environmental impacts. Such methods include ion exchange, coagulation, membrane filtration, and chemical precipitation and microbial degradation. Recent advances in materials science and green chemistry have led to the development of nanomaterial that possess high specific surface areas and multiple functions, making them suitable for removing metals such as Cr from wastewater. Literature shows that the most efficient, effective, clean, and long-lasting approach for removing heavy metals from wastewater involves adsorbing heavy metals onto the surface of nanomaterial. This review assesses the removal methods of Cr from wastewater, advantages and disadvantages of using nanomaterial to remove Cr from wastewater and potential negative impacts on human health. The latest trends and developments in Cr removal strategies using nanomaterial adsorption are also explored in the present review.

Abstract Tobacco Harm Reduction (THR) offers a promising approach to addressing the significant burden of smoking in Afghanistan. Over three million Afghans smoke daily, making it a leading cause of preventable deaths in the country. While the previous Afghan government implemented various tobacco cessation policies and strategies, these measures were only partially effective in reducing the number of smokers or smoking-related deaths. In 2021, community-based initiatives in Kabul and Herat started advocating for Tobacco Harm Reduction (THR) as a novel, realistic, and practical approach proven to promote smoking abstinence and minimize tobacco harm. However, implementing THR strategies in Afghanistan faces numerous challenges, including a lack of governmental support, funding issues, unfavorable market conditions, the high cost-effectiveness of THR products, and misconceptions about these products. To effectively promote THR in Afghanistan and overcome these challenges, it will be necessary to implement THR policies that support THR products for smokers, regulate the market for these products, produce them locally with healthcare professional oversight, conduct more engaging advocacy campaigns, and secure domestic sponsors.

Anti-viral medication is comparably incredibly beneficial for individuals who are infected with numerous viruses. Mathematical modeling is crucial for comprehending the various relationships involving viruses, immune responses and health in general. This study concerns the implementation of a continuous Galerkin-Petrov time discretization scheme with mathematical models that consist of nonlinear ordinary differential equations for the hepatitis B virus, the Chen system and HIV infection. For the Galerkin scheme, we have two unknowns on each time interval which have to be computed by solving a 2×2 block system. The proposed method is accurate to order 3 in the whole time interval and shows even super convergence of order 4 in the discrete time points. The study presents the accurate solutions achieved by means of the aforementioned schemes, presented numerically and graphically. Further, we implemented the classical fourth-order Runge-Kutta scheme accurately and performed various numerical tests for assessing the efficiency and computational cost (in terms of time) of the suggested schemes. The performances of the fourth order Runge-Kutta and the Galerkin-Petrov time discretization approaches for solving nonlinear ordinary differential equations were compared, with applications towards certain mathematical models in epidemiology. Several simulations were carried out with varying time step sizes, and the efficiency of the Galerkin and Runge Kutta schemes was evaluated at various time points. A detailed analysis of the outcomes obtained by the Galerkin scheme and the Runge-Kutta technique indicates that the results presented are in excellent agreement with each other despite having distinct computational costs in terms of time. It is observed that the Galerkin scheme is noticeably slower and requires more time in comparison to the Runge Kutta scheme. The numerical computations demonstrate that the Galerkin scheme provides highly precise solutions at relatively large time step sizes as compared to the Runge-Kutta scheme.

In the present period, a new fast-spreading pandemic disease, officially recognised Coronavirus disease 2019 (COVID-19), has emerged as a serious international threat. We establish a novel mathematical model consists of a system of differential equations representing the population dynamics of susceptible, healthy, infected, quarantined, and recovered individuals. Applying the next generation technique, examine the boundedness, local and global behavior of equilibria, and the threshold quantity. Find the basic reproduction number $R_0$ and discuss the stability analysis of the model. The findings indicate that disease fee equilibria (DFE) are locally asymptotically stable when $R_0 < 1$ and unstable in case $R_0 > 1$. The partial rank correlation coefficient approach (PRCC) is used for sensitivity analysis of the basic reproduction number in order to determine the most important parameter for controlling the threshold values of the model. The linearization and Lyapunov function theories are utilized to identify the conditions for stability analysis. Moreover, solve the model numerically using the well known continuous Galerkin Petrov time discretization scheme. This method is of order 3 in the whole-time interval and shows super convergence of order 4 in the discrete time point. To examine the validity and reliability of the mentioned scheme, solve the model using the classical fourth-order Runge-Kutta technique. The comparison demonstrates the substantial consistency and agreement between the Galerkin-scheme and RK4-scheme outcomes throughout the time interval. Discuss the computational cost of the schemes in terms of time. The investigation emphasizes the precision and potency of the suggested schemes as compared to the other traditional schemes.

The Lonngren wave equation, which simulates electrical signals in the semiconductor material known as tunnel diode, is taken into account in this work. New rational, trigonometric, and hyperbolic type travelling wave solutions are obtained by solving the non-linear equation using the advanced exp -Ψ(η)-expansion function technique. Graphs and simulations are used to show the relationships between the coefficient of the non-linearity term and other variables, as well as how these terms affect the wave behaviour in the presented solutions. By assigning special values to the constants in the solutions, a physical analysis is also carried out to determine how the conductivity of the model affects the propagation and dispersion of electrical impulses. In order to demonstrate the originality of our findings, we also developed a table-based comparison of the obtained solutions with those found in the literature.

The current study scrutinizes exact singular solitary, kink, anti-kink, bell-shaped, and periodic traveling wave solutions for the newly implemented 3-dimensional Wazwaz-Benjamin-Bona-Mahony (WBBM) equations family using a modified Exp-function approach. In spite of the presence of several trigonometric, hyperbolic, and rational functions, some new exact solitary, hyperbolic, and periodic traveling wave solutions to the considered equations are obtained by putting the modified Exp-function method into practice using the computer program Maple. The arrangement of the functions tanh, sech2, tan, and sec2 expresses the specific solutions produced by the defined procedure. The information was obtained to evaluate how well the suggested method could compute the exact solutions of the WBBM equations that could be applied to nonlinear water model applications in the ocean and coastal engineering. To show the physical composition and properties of the discovered solitons, contour, three-, and two-dimensional graphs are plotted using the computer program Mathematica. The acquired results imply that the proposed method can be applied to find various, enhanced, useful, and compatible solutions for other important nonlinear partial differential equations. All of the solutions given have been qualified by swapping the respective equations with those generated via the computer program Maple. Furthermore, we compared our obtained results with the solutions already put forward in the literature.

In developing nations, the human immunodeficiency virus (HIV) infection, which can lead to acquired immunodeficiency syndrome (AIDS), has become a serious infectious disease. It destroys millions of people and costs incredible amounts of money to treat and control epidemics. In this research, we implemented a Legendre wavelet collocation scheme for the model of HIV infection and compared the new findings to previous findings in the literature. The findings demonstrate the precision and practicality of the suggested approach for approximating the solutions of HIV model. Additionally, establish an autonomous non-linear model for the transmission dynamics of healthy CD4+ T-cells, infected CD4+ T-cells and free particles HIV with a cure rate. Through increased human immunity, the cure rate contributes to a reduction in infected cells and viruses. Using the Routh-Hurwitz criterion, we determine the basic reproductive number and assess the stability of the disease-free equilibrium and unique endemic equilibrium of the model. Furthermore, numerical simulations of the novel model are presented using the suggested approach to demonstrate the efficiency of the key findings.

Abstract Background Fruit bats play an important role in pollination and seed dispersal, and their conservation is important to maintain the productivity of some crops and natural ecosystems. The objective of this study was to investigate the knowledge, attitudes, and perception of fruit bats by orchard farmers and agricultural communities in Pakistan. Methods The present survey was conducted in two districts (i.e. Sheikhupura and Malakand districts) within Punjab and Khyber Pakhtunkhwa provinces based on the higher number of fruit growing areas and bat roosting sites. A total of 200 (100 per district) close-ended questionnaires with 53 questions were administered to randomly selected respondents within the selected communities associated with fruit orchards, including orchard owners, laborers, and members of the surrounding community. Each questionnaire was divided into seven sections (i.e., demographic information, environmental and public health effects of bats, knowledge about bats, perception and control of bats, non-lethal methods adopted to control bats, and different myths about bats). Results A majority of respondents (59%, n = 118) mis-classified bats as birds instead of mammals despite more than 84% reporting that they have observed bats. Nearly 71.5% of orchard farmers perceived that their fruits are contaminated by bats during consumption, and a majority believe that bats destroy orchards (62.5%) and are responsible for spreading disease. Mythology about bats was ambiguous, as 49% of those surveyed did not perceived bats to bring good luck (49%), and 50% did not perceived them to be bad omens either. Most respondents have never killed a bat (68%) nor would they kill a bat if given the opportunity (95%). Regarding the control of bats, the greatest percentage of respondents strongly disagree with shooting bats (36%) and strongly agree with leaving bats alone (42.5%). Conclusions This study provides a better understanding of the sociodemographic factors associated with knowledge, attitude and perception of bats from fruit orchard owners, labourers and local people. We recommend educational interventions for targeted groups in the community, highlighting the ecosystem services and importance of bat conservation to improve people’s current knowledge regarding the role of bats and reduce direct persecution against bats.

The toxic dye pigments, even in small quantities, can damage ecosystems. Removing organic, inorganic, and microbiological contaminants from wastewater via heterogeneous photocatalysis is a promising method. Herein, we report the band structure tuning of ZnO/CuO nanocomposites to enhance photocatalytic activity. The nanocomposites were synthesized by a chemical approach using step-wise implantation of p-type semiconductor CuO to n-type semiconductor ZnO. Various characterization techniques such as X-ray diffraction analysis (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray analysis (EDX) and UV spectroscopy were used to investigate the crystal structure, surface morphology, elemental composition and optical properties of the synthesized samples. As the CuO content increased from 10% to 50% in ZnO/CuO nanocomposites, the optical bandgap decreased from 3.36 to 2.14 eV. The photocatalytic activity of the samples was evaluated against the degradation of methylene blue (MB) under visible irradiation. Our study demonstrates a novel p–n junction oxide photocatalyst based on wt. 10% CuO/ZnO with superior photocatalytic activity. Effectively 66.6% increase in degradation rate was achieved for wt. 10% CuO/ZnO nanocomposite compared to pure ZnO nanoparticles.

The strain wave equation in micro-structured solids, which is significant in solid physics, is offered for consideration in this work. This is accomplished using the modified exp-function method, which is one of the most powerful ways for constructing abundantly distinct, accurate solutions to nonlinear partial differential equations. Wave propagation in microstructured solids is based on the structure of the strain wave equation. As a result, we were able to obtain a variety of new analytical solitary wave solutions like hyperbolic and complex function solutions with free parameters. Additionally, 2D and 3D plots are graphed for each of the solutions found in order to better comprehend their physical interpretation.

The present work implements the continuous Galerkin-Petrov method (cGP(2)-method) to compute an approximate solution of the model for HIV infection of $ \text{CD4}^{+} $ T-cells. We discuss and analyse the influence of different clinical parameters on the model. The work also depicts graphically that how the level of $ \text{CD4}^{+} $ T-cells varies with respect to the emerging parameters in the model. Simultaneously, the model is solved using the fourth-order Runge Kutta (RK4) method. Finally, the validity and reliability of the proposed scheme are verified by comparing the numerical and graphical results with those obtained through the RK4 method. A numerical comparison between the results of the cGP (2) method and the RK4 method reveals that the proposed technique is a promising tool for the approximate solution of non-linear systems of differential equations. The present study highlights the accuracy and efficiency of the proposed schemes as in comparison to the other traditional schemes, for example, the Laplace adomian decomposition method (LADM), variational iteration method (VIM), homotopy analysis method (HAM), homotopy perturbation method (HAPM), etc. In this study, two different versions of the HIV model are considered. In the first one, the supply of new $ \text{CD4}^{+} $ T-cells from the thymus is constant, while in the second, we consider the production of these cells as a monotonically decreasing function of viral load. The experiments show that the lateral model provides more reasonable predictions than the former model.

Abstract Wind power is often recognized as one of the best clean energy solutions due to its widespread availability, low environmental impact, and great cost-effectiveness. The successful design of optimal wind power sites to create power is one of the most vital concerns in the exploitation of wind farms. Wind energy site selection is determined by the rules and standards of environmentally sustainable development, leading to a low, renewable energy source that is cost effective and contributes to global advancement. The major contribution of this research is a comprehensive analysis of information for the multi-attribute decision-making (MADM) approach and evaluation of ideal site selection for wind power plants employing q-rung orthopair hesitant fuzzy rough Einstein aggregation operators. A MADM technique is then developed using q-rung orthopair hesitant fuzzy rough aggregation operators. For further validation of the potential of the suggested method, a real case study on wind power plant site has been given. A comparison analysis based on the unique extended TOPSIS approach is presented to illustrate the offered method’s capability. The results show that this method has a larger space for presenting information, is more flexible in its use, and produces more consistent evaluation results. This research is a comprehensive collection of information that should be considered when choosing the optimum site for wind projects.

The main objective of this article is to introduce the idea of a q-rung orthopair hesitant fuzzy rough set (q-ROHFRS) as a robust fusion of the q-rung orthopair fuzzy set, hesitant fuzzy set, and rough set. A q-ROHFRS is a novel approach to uncertainty modelling in multi-criteria decision making (MCDM). Various key properties of q-ROHFRS and some elementary operations on q-ROHFRSs are proposed. Based on the q-ROHFRS operational laws, novel q-rung orthopair hesitant fuzzy rough weighted averaging operators have been developed. Some interesting properties of the proposed operators are also demonstrated. Furthermore, by using the proposed aggregation operator, we develop a modified VIKOR method in the context of q-ROHFRS. The outcome of this research is to rank and select the best alternative with the help of the modified VIKOR method based on aggregation operators for q-ROHFRS. A decision-making algorithm based on aggregation operators and extended VIKOR methodology has been developed to deal with the uncertainty and incompleteness of real-world decision-making. Finally, a numerical illustration of agriculture farming is considered to demonstrate the applicability of the proposed methodology. Also, a comparative study is presented to demonstrate the validity and effectiveness of the proposed approach. The results show that the proposed decision-making methodology is feasible, applicable, and effective to address uncertainty in decision making problems.

DC motors are widely used in industries to provide mechanical power in speed and torque. The position and speed control of DC motors is receiving interest from the scientific community in robotics, especially in robotic arms, a flexible joint manipulator. The current research work is based on the position control of DC motors using experimental investigations in LabVIEW. The linear control strategy is applied to track the position and speed of the DC motor with comparative analysis in the LabVIEW platform and simulation analysis in MATLAB. The tracking error in the hardware setup based on LabVIEW programming is slightly greater than the simulation analysis in MATLAB due to the inertial load of the motor during steady-state conditions. The controller output shows the input voltage applied to the DC motor varies between 0 and 8 V to ensure minimal steady error while tracking the position and speed of the DC motor.

Abstract Coronavirus disease 2019 (COVID-19) emerged in late 2019, with the first case identified in Wuhan City, Hubei Province, China, on 12 December 2019. In order to perceive the comprehensive impact of this pandemic, we have to know that misinformation and denials about COVID-19 have surely exacerbated its diffusion and hindered the response against it. Turkmenistan remains one of the very few countries in the world that lacks reports about emerging cases of the novel coronavirus. Turkmen authorities claim that they have adopted all attainable measures required in order to combat the virus, asserting that COVID-19 has yet to reach their country. Despite the government’s reported absence of COVID-19 in the country, rumors, media reports and independent sources suggest the spread of the pandemic in Turkmenistan. By mid-June 2020, the outbreak was referred to as being serious with patients suffering extreme health risks, and following its state of disrepair and unethical practices, many of those anticipated to be COVID-19 infected tend to suffer at home, discouraging any interaction with the healthcare system. The civil society in Turkmenistan, for the time being, takes full part of the government’s duty in the process of informing and educating the public regarding the COVID-19 pandemic, and endeavors to keep the government and WHO accountable for behaving in such repressive ways that could lead to rather preventable loss of human life in Turkmenistan. Yet, efforts hang fire before unveiling the real situation, and Turkmenistan’s government owning up to the negations and roaming speculations, not only regarding the coronavirus crisis, but every public-related issue itself.

Wind energy is one of the most significant renewable energy sources due to its widespread availability, low environmental impact, and great cost-effectiveness. The effective design of ideal wind energy extraction areas to generate electricity is one of the most critical issues in the exploitation of wind energy. The appropriate site selection for wind power plants is based on the concepts and criteria of sustainable environmental advancement, resulting in a low-cost and renewable energy source, as well as cost-effectiveness and job creation. The aim of this article is to introduce the idea of q-rung orthopair hesitant fuzzy rough set (q-ROHFRS) as a robust fusion of q-rung orthopair fuzzy set, hesitant fuzzy set, and rough set. A q-ROHFRS is a new approach towards modeling uncertainties in the multi-criteria decision making (MCDM). Various key properties of q-ROHFRS and some elementary operations on q-ROHFRSs are established. A list of novel q-rung orthopair hesitant fuzzy rough weighted geometric aggregation operators are developed on the basis of defined operational laws for q-ROHFRSs. Further, a decision making algorithm is developed to handle the uncertain and incomplete information in real word decision making problems. Then, a multi-attribute decision making method is established using q-rung orthopair hesitant fuzzy rough aggregation operators. Afterwards, a practical case study on evaluating the location of wind power plants is presented to validate the potential of the proposed technique. Further, comparative analysis based on the novel extended TOPSIS method is presented to demonstrate the capability of the proposed technique.

Incentive Based (IB) and Command and Control (CAC) instruments are identified in various legislative Acts and Policy documents based on the criteria of environmental economics. Despite the advantages of IB strategies the world of policy making is somewhat locked into the path of traditional approaches such as CAC and pose inertia to move forward in environmental policy making. An ethical shift is inevitable anywhere where there is a market failure and increased social costs and inefficiencies in government interventions to regulate the market. Regulations are discrete steps to address feedbacks in a complex system. Policy evaluation and testing criteria is used to evaluate and test the policies regulating marble extraction and processing in Pakistan. A set of policy and regulatory instruments are selected to be critiqued. The coexisting policy approaches found in the study shall be tested on system dynamics model for developing insights and long-term implications.

Conventional systems of medicine play a crucial role in maintaining healthcare. Herbal medicines are intact and less harmful to human beings than synthetic medicines. This study aimed to investigate the phytochemicals and in vivo hypolipidemic effect of chloroform extract of Lagenaria siceraria in Triton X-100 (100 mg/kg body weight) induced hyperlipidemic Wistar rats. The phytochemical characterization and estimation were performed on the base of the GC-MS approach. The Lagenaria siceraria extract (250 and 500 mg/kg bw) was administered orally to hyperlipidemic-induced rats for 7 days to examine its hypolipidemic activity. The experimental animals did not display any acute toxicity. Atorvastatin (10 mg/kg bw) was used as a standard drug. Administration of Lagenaria siceraria extract lowers the total cholesterol (TC), triglyceride (TG), and low-density lipoproteins-cholesterol (LDL-C) levels whereas elevating the high-density lipoproteins-cholesterol (HDL-C) level. Histological studies of the liver and heart also showed the hypolipidemic effect of the extract. On the 8th day, no inflammation of the liver, myocardial necrosis, fibrosis, or atypia was seen. Furthermore, binding affinity and plausible binding mode of stigmastan-3-ol with HMG-CoA reductase were predicted by molecular docking studies which showed the same interaction patterns as atorvastatin. Moreover, the docking results were refined by 100 ns MD simulations which revealed that stigmastan-3-ol extract formed a stable complex with protein and did not induce any conformational changes in protein structure.

This study focusses on the fabrication of nano-carriers for delivery of ciprofloxacin through the nanoprecipitation process. This was done to examine the release of drug at the pH of stomach to find out the antibacterial action of ciprofloxacin loaded nanoparticles (NPs). Prepared NPs were characterized by Fourier Transform Infra-Red (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), and particle size analyzer (PSA) techniques. Drug yield, loading, and sustained release was studied as function of time (up to 8 h). Antibacterial activity of ciprofloxacin loaded NPs were also determined against different gram-positive and gram-negative bacteria. Results revealed that nanoprecipitation is a suitable method for encapsulation of ciprofloxacin in poly(lactic-co-glycolic acid) PLGA NPs. The drug yield and drug loading were found to be 60%. The size range of NPs observed by PSA was in the range of 5.03–6.60 nm. It can be concluded that nanoformulation of ciprofloxacin loaded PLGA NPs can be used in stomach for longer period of time to enhance the bioavailability of the drug.

Abstract The present article aims to describe the status quo of the atmospheric air quality in Bishkek and the state measures taken to improve it and to give the perspective of research and policy development. Air pollution is one of the major environmental risks for premature death from respiratory diseases, cancer, strokes, heart attacks, diabetes, and other diseases. It exerts a negative effect on worker productivity and mental health. In the last 30 years, Bishkek, the capital of the Kyrgyz Republic, has turned from one of the cleanest and greenest cities in the former Soviet Union to one of the most polluted cities in the world. The roots of that transformation lie in the negative socio‐economic changes taking place in the country, including the population doubling of Bishkek mainly due to internal migration, uncontrolled construction of houses without relevant infrastructure, worsening socio‐economic conditions, increased number of used vehicles, and low quality of gasoline. The main sources of air pollution in Bishkek are domestic heating and vehicle exhaust fumes. During the winter, air pollution is aggravated by frequent temperature inversion and air stagnation due to air trapping by high‐rise buildings. The state's approaches and measures to address this issue are reflected in its laws and policies. The city and national government have taken a range of strategic measures to transform Bishkek into a green city with a favourable environment. Recommendations on research and policy development are provided in this perspective.

The survival of any country and state is conditional on the prosperity of its subjects, peace and tranquility, and the elimination of internal and external anarchy. If a country’s internal system suffers from disnity, if there is no balance of relations the between people and the authorities, it will not take long for this state of decline. That is why Islamic law has given such clear rules to the rulers and subjects that by following them any country can achieve prosperity. These principles and guidelines of Islamic law have been taken from the hadiths of the prophet ﷺ. The principles and teachings given by the Prophet (ﷺ) in this regard are of three kinds.Teachings that are shared between the authorities and the subjects, such as piety and piety, enjoining good and forbidding evil, self-accountability and subordination، And these are the foundations for the betterment of individual and collective life۔ Teachings that relate only to the authorities include a sense of responsibility, self-accountability and transparent accountability of subordinates, leniency towards subjects, enforcement of God's commandments, protection of national treasury, protection on internal and external fronts of the state, competence. It is important to give positions on the basis, protect the fundamental rights of the people and establish justice. Practicing them increases the respect of the authorities in the eyes of the subjects, makes the subjects happy and keeps them away from chaos and disorder and she volunteered voluntarily to assist the authorities in every possible way. Teaching is for the subjects and that is that all the members of the subjects should cooperate with the authorities in good deeds, avoid all kinds of rebellion and rebellion and the subjects should be related to brotherhood, love and selflessness. It sits in the hearts and because of this it is safe from all kinds of atrocities, it cannot be a tool of external forces and riotous elements which creates a peaceful environment and a stable society.

Abstract Food security is a major element for the sustainability, stability and development of a country. However, despite fundamental efforts in fighting poverty, Afghanistan continues to struggle with food insecurity with a large proportion of its population living below the poverty line. With extreme climates, protracted conflict, and now COVID-19, food insecurity has become rampant and is on the rise in the country. Efforts have been reinforced to mitigate this issue, but a spate of obstacles which seems not to come to an end, has contributed to the deterioration of the situation. With the collaboration and efforts of international organizations, there remains a glimmer of hope to potentially reduce the gravity of the food insecurity in the country. This paper aims to highlight the efforts of Afghanistan in alleviating food insecurity with a focus on the impact of COVID-19 on this issue. It also presents recommendations that may help ameliorate the country’s food security status during and after the pandemic.

Abstract The Lancet Commission on Global Surgery (LCoGS) launched Global Surgery 2030 to address the surgical services inequities with a bias toward low‐income and middle‐income countries like the Philippines. The same inequity is observed particularly when it comes to the urban‐rural divide. With more than half of the population living in rural areas, access to surgery becomes a major challenge that further impedes the much‐needed health of an economically productive workforce. The Universal Health Care [UHC] Act (RA 11332) of 2019 ensures that all Filipinos have access to quality, cost‐effective, promotive, preventive, curative, rehabilitative, and palliative health services without causing a financial burden. Recognizing the provision of essential surgery, in the context of primary healthcare is important. It should be accessible, continuous, comprehensive, and coordinated at the time of need – parallel to the principle of primary health care. Driven by this concept and experiences, the authors conceptualized and presented the Philippine Rural Surgery model for future development and implementation. This is envisioned to provide essential surgery among local rural primary health care settings that is universal, accessible, cost‐effective and safe. As this is still new in the Philippines, we proposed tenets and recommendations based on WHO Health System Strengthening building blocks to guide stakeholders in creating formal plans towards institutionalization under the principles of UHC. Such access to surgical service in the context of a unique socio‐demography of the Philippines would be essential in attaining the parameters and provisions set by the UHC Act.

BackgroundDecline in cardio-metabolic health, immunity, and physical activity is associated with old age. Old people also find it difficult to engage in structured exercise programs. Therefore, there is a need to investigate common daily chores as an alternative for exercise that may also help in maintaining cardio-metabolic and immune health.ObjectiveWe aimed to investigate whether Salat, an obligatory Islamic prayer involving various physical movements and closely resembling yoga, enhances the benefits conferred by the current guidelines for physical activity.MethodsA total of 30 overweight adults (mean (SD) age of 53.5 (8.7) years) participated in this study. For a 4-week duration, we compared the effects of Salat before/after meals (Pre-MS/Post-MS) on selected immunological and metabolic parameters in serum samples. We also compared the effects of both Pre-MS/Post-MS regimens in young and old subjects to observe any age-related effects.ResultsMost of the baseline metabolic parameters and the count of immune cells were normal. Post-MS resulted in a significant reduction in body weight and percent body fat (%BF). Overall, Post-MS resulted in a clear leukocytosis with a significant increase in granulocytes, monocytes, and lymphocytes. When analyzing the lymphocyte compartment, a clear numerical increase was noted for T, B, and NK cells. The number of CD8+ T cells showed a statistically significant increase. Similarly, Post-MS induced leukocytosis in both young and old individuals, while the increase in granulocytes, monocytes, and lymphocytes was statistically significant in old subjects only.ConclusionThis study demonstrated that the Islamic obligatory and congressional Salat practice is capable of mimicking desirable pro-immune and pro-metabolic health effects.Clinical trial registration(UMIN000048901).

Abstract Kazakhstan announced the first cases of COVID‐19 in March 2020. Within a span of a few months, the pandemic ravaged all regions affecting vulnerable populations due to limited access to healthcare services and co‐morbidities. To minimize the spread of the pandemic, the government announced the implementation of containment measures such as quarantine, movement restrictions, and lockdowns among others. The collateral effect of the pandemic has disrupted economic and learning activities pushing several people below the poverty line. The pandemic revealed the weakness of healthcare including the acute shortage of essential medicines and lack of hospital beds. This calls for stringent measures to revive the economy and mitigate the reeling effect of the pandemic. As a result, Kazakhstan commenced COVID‐19 vaccination efforts in February 2021. To date, about 47.8% are fully vaccinated pushing Kazakhstan closer to achieving herd immunity at the 60% threshold. However, the country faces challenges such as vaccine hesitancy and uncertainty surrounding vaccine effectiveness against new variants of SARS‐CoV2, among others. This paper aims to explore the health and socioeconomic challenges caused by COVID‐19 in Kazakhstan, control strategies, vaccination campaigns and progress towards herd immunity.

In smart home environments, the interaction between a remote user and devices commonly occurs through a gateway, necessitating the need for robust user authentication. Despite numerous state-of-the-art user-authentication schemes proposed over the years, these schemes still suffer from security vulnerabilities exploited by the attackers. One severe physical attack is the node capture attack, which allows adversaries to compromise the security of the entire scheme. This research paper advances the state of the art by conducting a security analysis of user-authentication approaches regarding their vulnerability to node capture attacks resulting in revelations of several security weaknesses. To this end, we propose a secure user-authentication scheme to counter node capture attacks in smart home environments. To validate the effectiveness of our proposed scheme, we employ the BAN logic and ProVerif tool for verification. Lastly, we conduct performance analysis to validate the lightweight nature of our user-authentication scheme, making it suitable for IoT-based smart home environments.

Exploiting Radio Frequency Identification (RFID) technology in healthcare systems has become a common practice, as it ensures better patient care and safety. However, these systems are prone to security vulnerabilities that can jeopardize patient privacy and the secure management of patient credentials. This paper aims to advance state-of-the-art approaches by developing more secure and private RFID-based healthcare systems. More specifically, we propose a lightweight RFID protocol that safeguards patients’ privacy in the Internet of Healthcare Things (IoHT) domain by utilizing pseudonyms instead of real IDs, thereby ensuring secure communication between tags and readers. The proposed protocol has undergone rigorous testing and has been proven to be secure against various security attacks. This article provides a comprehensive overview of how RFID technology is used in healthcare systems and benchmarks the challenges faced by these systems. Then, it reviews the existing RFID authentication protocols proposed for IoT-based healthcare systems in terms of their strengths, challenges, and limitations. To overcome the limitations of existing approaches, we proposed a protocol that addresses the anonymity and traceability issues in existing schemes. Furthermore, we demonstrated that our proposed protocol had a lower computational cost than existing protocols and ensured better security. Finally, our proposed lightweight RFID protocol ensured strong security against known attacks and protected patient privacy using pseudonyms instead of real IDs.

Allah Almighty has made the life of the world in the Universe perishable. Therefore, he has also made the lives of human beings, animals, birds and insects living on the earth eternal. For the end of their lives, Allah Almighty has made different causes according to his Sunnah. Among these causes of the decline of worldly life are also diseases. On the other hand Allah Almighty has also created means to take life to the appointed time. Among these causes are medicines which can be used to prolong the life of this world till the appointed time. Therefore, along with diseases, Allah Almighty has also revealed to human beings various methods of treatment for diseases. One of these methods is the treatment of colors. Different colors have different effects on human life. The proof of this is stated in the Holy Quran “The Said! Ask Allah to tell us what color it is. Musa Said! My Allah says: let its color be deep yellow, that it may please the beholders.” Since man is naturally endowed with beauty, Allah Almighty has adorned the universe with colors. This blessing is also mentioned in various places in the Holy Qur’an, as the Almighty says: “Do they not look at the sky above them, how we have made it and adorned it, and there is no crack in it?” “On top of these Paradises will be green garments of cherubim and silk rings and they will be adorned with silver bracelets”. The importance of colors has been mentioned in the Holy Quran. Keeping in view the importance of colors, Azimi Sahib has described the treatment of colors as a natural means of treatment. He has written “Treatment” “Color therapy” and “Theory of Color and Lights”. According to him, due to the excess and deficiency of colors, the human body suffers from various diseases. And if the deficiency and excess of the desired color in the body is corrected, the disease can be got rid of. Sunlight and rays help to eliminate abuse. Describing the mental properties of red, he has called it the color of courage and love. When things go awry and expectations are dashed, red dominates the mental center. The red color in the center of the red is an indication of abnormal emotional attachment or emotional trauma. People in the red color are in moderation, they help others and use all their abilities in their favorite hobbies.

Purpose: The purpose of this study is to examine the regime shift behavior and interconnectedness between stock market volatility and exchange rate in a pre and post COVID context. Design/Methodology/Approach: For this purpose Pakistan India and China has been taken as emerging economies and USA UK and Japan as developed economies. Daily data of exchange rates and stock market indices have been used from Jan,1 2011 to Apr 30, 2021. Markov regime switching model, GARCH model and Granger causality test has been used. Findings: The outcomes of this study empirically confirmed that the Markov regime switching model is flexible model because it captures regime shifts in the mean and variance equation of all sample economies. Moreover, the sum of GARCH (1,1) indicates that volatility shocks are persistent except India. Study also concluded that exchange rate volatility has significant positive impact on stock market of Pakistan, USA and Japan in a pre COVID context. Implications/Originality/Value: A post COVID context has significant impact on the stock market of India, U.S.A. and U.K. Granger causality results indicates unidirectional relationship for Pakistan, China and USA. Whereas for Japan bi-directional relationship is found but for India and UK no directional causality exist.

The exponential growth of the Internet of Things (IoT) has led to the rapid expansion of interconnected systems, which has also increased the vulnerability of IoT devices to security threats such as distributed denial-of-service (DDoS) attacks. In this paper, we propose a machine learning pipeline that specifically addresses the issue of DDoS attack detection in IoT networks. Our approach comprises of (i) a processing module to prepare the data for further analysis, (ii) a dynamic attribute selection module that selects the most adaptive and productive features and reduces the training time, and (iii) a classification module to detect DDoS attacks. We evaluate the effectiveness of our approach using the CICI-IDS-2018 dataset and five powerful yet simple machine learning classifiers—Decision Tree (DT), Gaussian Naive Bayes, Logistic Regression (LR), K-Nearest Neighbor (KNN), and Random Forest (RF). Our results demonstrate that DT outperforms its counterparts and achieves up to 99.98% accuracy in just 0.18 s of CPU time. Our approach is simple, lightweight, and accurate for detecting DDoS attacks in IoT networks.

The laminar movement in an expanding and contracting permeable pipe or surface has recently attracted the attention of many scholars owing to its application in engineering and biological processes. The objective of the current study is to examine the influence of chemical processes on magnetized nanofluid flow over extending or shrinking permeable pipes with a heat reservoir. The flow equations are renovated into first ODEs by introducing the new variable and then numerically solved by RK4 with a shooting procedure. The effect of emerging factors on the flow features is observed using graphs and elaborated in detail. From the analysis, the temperature is raised when the heat source is increased in both cases of wall expansion or contraction but declines in the case of heat sinks. In the case of a heat source, the temperature rises as the Hartmann and Prandtl numbers are enhanced, but in the case of a heat sink, the temperature falls. In the presence of heat sinks and injections, when the thermophoresis factor is increased, the concentration of nanoparticles is increased in both wall expansion and contractions. In both situations of wall extension or contraction, along with injection, the concentration of nanoparticles is a decreasing function of Nb, while the concentration of nanoparticles is an increasing function in the case of a heat source. Additionally, for the confirmation of the RK4 code, the total average square residue error and average square residue error are also presented. For the stability analysis, the current work is compared with published work, and excellent agreement is established. The novelty of the present study is to investigate the effect of chemical reaction on magnetized nanofluid flow over extending and shrinking porous pipes with heat generation and absorption.

Abstract Coronavirus disease-19 (COVID-19) has been spreading in every part of the world, putting nations at risk with its pandemic status, including Indonesia. COVID-19 vaccine has been deemed as one of the most effective interventions to date for mitigating the spread and mortality from COVID-19. Responding to the situation, the Government of Indonesia (GOI) has allocated the means necessary to procure and distribute COVID-19 vaccines; placing into consideration the unique context of the country, recently categorized as a middle-income country and archipelagic with a population over 270 million. This article aims to present the challenges associated with the distribution of COVID-19 vaccination as well as recommendations to mitigate them, to ensure a timely and effective COVID-19 vaccination program in Indonesia.

Human Beings are the superior creature of Allah (Almighty) and humans attained this superiority because of some qualities. Firstly Allah made Human Beings responsible of their all deeds. Secondly Allah created human beings in best body structure and lastly Allah sent humans as his representatives in this world. Allah made pairs for every creature of this world and Human Beings are also made in couple i.e. Man and Woman. Allah (Almighty) assigned responsibilities to both the genders according to their natural physics as one is not capable of what other can do. Any change in these fundamental features of humans will result is disorder and chaos in human societies. In this research Change of Sex has been discussed in the light of Islamic Sharia and its consequences in the Human Society that a Human Being who has been living in the Society as man and if his sex is changed into woman then what kind of effects could occur in the Society, and a Human Being who was living in the society as woman and her sex is changed into man then what kind of consequences could occur in the society.