Voltage Stability & Control, is very crucial compared to other Power System (PS) Quality and Stability issues. Long-Vertical-Power-Flows in Conventional Grids, causes voltage drops which in turn causes huge power losses, especially in the Medium Voltage (MV) and Low Voltage (LV) Distribution Networks. Such technical losses in abysmally-planned weak distribution networks, lead to substantial loss of revenues to the utility grid. Apart from classic Voltage Regulation (VR) techniques, with the rise of Distributed Generation (DG) based on Renewable Energy Sources (RES), Horizontal-Power-Flows can be introduced in the network, through various Smart Grid techniques. Coupling such sources, near load centers shall mitigate long flows from expensive conventional sources at times of huge demands, improving feeders’ Voltage Profile. This Ancillary Service of Voltage Support from DG RESs shall thereby alleviate revenue losses caused by long-power-flows in weak distribution grids. For a developing country like Pakistan, loss of revenue from an already expensive utility gives huge blow to the economy. So, a similar technique for voltage support is proposed for an 11-kV feeder, which faces similar problem, and the results are remarkable. The technique is implemented using OpenDSS Tool by modelling 3MWp PV Penetration along with some future storage.

Herein we foremost detailed the numerical modeling of the double absorber layer- methyl ammonium lead iodide– carbon nitride layer solar cell and subsequently provided in-depth insight on the active layer associated with dominant radiative and non-radiative recombination losses limiting the efficiency ( ) of the solar cell. Under recombination kinetics phenomena, we explored the influence of Radiative recombination, Auger recombination, Shockley Read Hall recombination, the energy distribution of defects; Band Tail recombination (Hoping Model), Gaussian distribution, metastable defect states including single donor (0/+), single acceptor (-/0), Double Donor (0/+/2+), double acceptor (2/-/0-), and the interface layer defects on the output characteristics of the solar cell. Setting defect (or trap) density to with uniform energy distribution of defects for all the layers, we achieved the of 24. 16 %. A considerable enhancement in power conversion efficiency was perceived as we reduced the trap density to for the absorber layers. Further, it was observed that for the absorber layer with double donor defect states, the active layer should be carefully synthesized to reduce crystal order defects to keep the total defect density as low as to achieve efficient device characteristics

Topological defects such as magnetic monopoles that may have formed during cosmological phase transitions in the early universe. The Kibble mechanisms govern the formation of this defects and their abundance is influenced by the correlation length and the temperature-dependent Higgs mass. The Magnetic monopoles are particularly interested but their excessive production poses the monopole problem which is challenge to the standard model. Many solutions including symmetry breaking patterns and thermal pair production have been proposed to mitigate the monopole problem. Detecting monopoles would offer valuable insights into high-energy physics and the early universe. Detection of (even) a single monopole could revolutionize our current knowledge of the universe.

As a traditional Muslim country, the problem of gender discrimination in employment among women in Pakistan is more common. If we let it develop without taking measures, it will seriously restrict the speed and quality of Pakistan’s domestic economic development in the long run. In this study, the author obtained the first-hand information on the employment status of professional women in the Rahim Yar Khan region of Pakistan through questionnaire survey, supplemented by the public data of the Federal Statistical Office of Pakistan, and combined with the existing research results of the predecessors. Sex discrimination in employment of professional women in Pakistan. Through the collection of the data obtained from the questionnaire, the author found that economic factors are one of the main factors that cause local women to encounter gender discrimination in employment. Specifically, it includes the imbalance of labor supply and demand and the pursuit of maximum profits. At the same time, the traditional Muslim culture, women's own literacy and the imperfect legal system in Pakistan are also the key factors that cause female employees in the local area to encounter gender discrimination in employment. Women’s gender discrimination in employment is a universal problem. In any country in the world, gender discrimination may exist as long as women are involved in the work. Based on Pakistan's basic national conditions and relevant professional knowledge, the author provides several suggestions for eliminating the problem of gender discrimination in employment for local female employees in Pakistan. 1) The Pakistani government should further promote the domestic economic growth, increase the number of jobs, and ease the imbalance between the supply and demand of labor. At the same time, encourage self-employment and provide corresponding policy support. A variety of measures are also intended to address local gender discrimination in employment for women. 2) The government's leadership accelerates the transformation of the concept of the whole society. On the one hand, it requires the whole society to correctly understand the social status and social contribution of women, and strives to bring the concept of equality between men and women into the hearts of the people. It is intended to encourage qualified women to go out of the family to participate in social work. At the same time, correctly guide corporate values. Enterprises should not unilaterally pursue the maximization of interests, and should take the initiative to assume social responsibilities. 3) Women should also actively and consciously improve their literacy. Including not only active learning advanced cultural knowledge and professional skills. For the professional skills that have already been mastered, you must study harder and make yourself more and more progressive. At the same time, families should guarantee that girls of the appropriate age receive the education they deserve, so that they can gather their strengths in the workplace in the future.

Hyperlipidemia is an identified risk factor for metabolic syndrome, obesity and cardiovascular complications characterized by elevated levels of lipids in blood. The present study aimed to inhibit HMG-CoA reductase with 15-oxoursolic acid through in-vivo and in-silico assessments. HFD-induced hyperlipidemia in rats was developed with a marked increase in total cholesterol (58.34 ± 0.21 mg/dl), triglycerides (45.45 ± 0.39 mg/dl), LDL-c (66.12 ± 0.10 mg/dl), VLDL-c (19.34 ± 0.16 mg/dl), and a decrease in HDL-c (10.34 ± 0.18 mg/dl). The oral administration of 15-oxoursolic acid at a concentration of 30 mg/Kg b.w significantly reduced the serum concentration of total cholesterol (42.65 ± 0.54 mg/dl), triglycerides (32.33 ± 0.16 mg/dl), LDL-c (50.34 ± 0.15 mg/dl) and VLDL-c (13.15 ± 0.45 mg/dl) respectively and an increased in the serum HDL-c (18.56 ± 0.34 mg/dl). 15-oxo ursolic acid also caused a decrease in the coronary risk index and atherogenic risk index. In-silico studies of 15-oxoursolic acid with HMG-CoA reductase showed significant interaction capability with binding energy (-9.26805 Kcal/mol). It is concluded that 15-oxoursolic acid could significantly reduce the total cholesterol, triglycerides and LDL levels in HFD-induced hyperlipidemia rats which might lead to new medication with significant hypolipidemic potential.

A reliable and affordable energy supply is a fundamental prerequisite for reducing poverty, promoting investment, and boosting economic growth in the developing world. Among the different challenges that developing countries face, chronic energy crises are harrowing. The crises result from the unsatisfactory state of the central grid, a misguided energy mix, and ill-informed policies, among other things. The possibility of solving energy crises through a variety of alternative solutions is worth exploring. This review discusses two paths of energy development side by side: a traditional “hard” path of energy development (i.e., central grid extension powered by fossil fuels and nuclear energy expansion) and a relatively recent “soft” path of energy development, which is based on energy conservation and the deployment of renewable energy resources. This paper focuses on one central axis of the discussion: centralization vs. decentralization. This discussion, in turn, has technological, economic/business, and political dimensions. Finally, the paper discusses the significance of the debate from meeting the developing world’s energy demands. The paper intends not to prefer one or another path of energy development, nor it gives recommendations on diffusing or adopting those development paths. Instead, it explores the literature’s central arguments that might help frame the questions for further research. While this debate could be used to ask interesting questions that might help solve the energy crisis in the developing world, the discussion informs countries to advance policies specific to their circumstances under the umbrella of a sound and thoughtful energy productivity policy framework.

The goal of the next generation World Wide Web is machine readability through linked databases. To improve web search, integration, and mining in local languages like Urdu, there is a growing need to develop ontologies and vocabulary in these languages. The majority of people use the web in local languages for agriculture, social media interaction, news, etc. How to create agents for the integration of web data. In our country, the literacy ratio is very low and IT literacy is negligible. More comprehensive information for its target audience is only possible through the World Wide Web. Our first target is to improve and enhance the use of social media and the web in local languages. That will encourage its constructive use in Urdu for society and the economy. The Web in natural languages is the source of income for small and medium enterprises. The semantic web is concerned with linked databases and structured data. In this work, we are focused on some selected ontologies to be translated into natural languages. Expertise in Ontology Engineering helps us in job production. Ontology Engineering has extensive freelancing opportunities. Only if the web is correctly interpreted in regional languages is an economic boost achievable. A standardized foundation for data sharing and reuse on the internet is provided by the Semantic Web. In other words, a group of standards and technology that enables computers to comprehend the semantics (meaning) of material on the Web.

Drinking water supplies in the developing world often serve as a biosphere for various organisms. Viral gastroenteritis is a neglected area of research in Pakistan, there is no data for the prevalence of enteric viruses in drinking water of the largest city of Karachi. The present study aimed to provide a survey of the existence of enteric viruses: human adenovirus (HAdV), human enteroviruses (hEV), and genotype A rotavirus (GARV) in tap water. Using a simple PCR approach, we detected 20%, 43%, and 23% of HAdV, hEV, and GARV in tap water respectively. We have also shown an overall quality of tap water at the pumping station and consumer tap. Moreover, we assessed the efficiency of small-scale water treatment methods for the removal of viruses.

We present the design and overall development of an eight degrees of freedom (DOF) based Bioinspired Quadruped Robot (BiQR). The robot is designed with a skeleton made of cedar wood. The wooden skeleton is based on exploring the potential of cedar wood to be a choice for legged robots’ design. With a total weight of 1.19 kg, the robot uses eight servo motors that run the position control. Relying on the inverse kinematics, the control design enables the robot to perform the walk gait-based locomotion in a controlled environment. The robot has two main aspects: 1) the initial wooden skeleton development of the robot showing it to be an acceptable choice for robot design, 2) the robot’s applicability as a low-cost legged platform to test the locomotion in a laboratory or a classroom setting.

Building an ethical culture is challenging and a basic requirement of the companies to embed transparency in their systems, creating a positive image; serving the internal and external communities. This paper based on detailed interviews of 12 family owned businesses over a period of 16 months explores how these companies build the ethical culture, identifying the ethical culture sustainability triggers, challenges and role of religion in such practices. The values, culture, community and social norms are identified as major ingredients of a sustainable ethical culture development and implementation of the ethical policies and procedures require institutional and structural mechanisms for effectiveness in family owned businesses. The findings at numerous occasions are in contrast to the literature, whereas, in other instances are similar. The religion, society, family image, the entrepreneurs themselves and their family members play a vital role. Non-interference in private matters of the employees, whistle blowing, code of ethics, training and awareness creation and a number of other factors play a leading role in ethical culture development in family businesses.

The long term sustainability and longevity of the business life cycle depends on correct understanding of the contextual constituents, triggers and dynamics, pre-startup planning, strategy and financial forecasting where business plans are developed to understand and forecast project viability, pitch ideas and secure funding. At the same time there is a lack of one page startup business model. Identifying this need, a ‘startup business strategy frame’ has been developed through learnings and encompassing design thinking, the business canvas and other strategy models and approaches. It provides a logical sequential flow and connects value drivers on environmental, strategic including operational and financial levels of proposed startup in a sequential format. To arrive at the frame as a logical conclusion a website www.strategizestartup.com is developed to build startup business model and plans in a time and cost effective process. The website assists the startups at each stage through a work and guidebook. The website takes the user from creative ideation by charting the context to build the strategy and measuring the financial impact. This startup strategy model will alleviate the problems for the first and second stage entrepreneurs to ideate creatively and strategizing. It also eradicates the issues related to reading and understanding long plans which could be an exhaustive and cumbersome process.

Machine learning (ML) is enabling augmented reality (AR) to gain popularity in various fields, including gaming, entertainment, healthcare, and education. ML enhances AR applications in education by providing accurate visualizations of objects. For AR systems, ML algorithms facilitate the recognition of objects and gestures from kindergarten through university. The purpose of this survey is to provide an overview of various ways in which ML techniques can be applied within the field of AR within education. The first step is to describe the background of AR. In the next step, we will discuss the ML models that are used in AR education applications. Additionally, we discuss how ML is used in AR. Each subgroup’s challenges and solutions can be identified by analyzing these frameworks. In addition, we outline several research gaps and future research directions in ML-based AR frameworks for education.

The effect of Gymnema Sylvestre supplementation on beta cell and hepatic activity was explored in an alloxan-induced hyperglycemic rat model. Adult rats were made hyperglycemic via a single inj. (i.p) of Alloxan (120mg/kg b.w). Gymnema Sylvestre was supplemented @250mg/kg and 500mg/kg b.w. Blood glucose levels were constantly monitored. After 21 days, rats were euthanized, and blood and tissues (pancreas and liver) were collected for biochemical, expression, and histological analysis. One-way ANOVA was used to compare the means of different treatment groups. Gymnema Sylvestre significantly reduced blood glucose levels with a subsequent increase in plasma insulin levels in a dosage-dependent manner. Total oxidant status (TOS), malondialdehyde, LDL, VLDL, ALT, AST, triglyceride, total cholesterol, total protein, C-reactive protein, and cortisol levels were reduced significantly in alloxan-treated hyperglycemic rats supplemented with Gymnema Sylvestre as compared to control. Significantly raised paraoxonase, arylesterase, albumin, and HDL levels were also observed in Gymnema Sylvestre supplemented hyperglycemic rats. Increased mRNA expression of Ins-1, Ins-2, Gck, Pdx1, Mafa, and Pax6 were observed, while decreased expression of Cat, Sod1, Nrf2, and NF-kB was observed in the pancreas. Whereas increased mRNA expression of Gck, Irs1, SREBP1c, and Foxk1 and decreased expression of Irs2, ChREBP, Foxo1, and FoxA2 were observed in the liver. The current study indicates the potent effect of Gymnema Sylvestre on the transcription modulation of the insulin gene in the alloxan-induced hyperglycemic rat model. Enhanced plasma insulin levels further help to improve hyperglycemia-induced dyslipidemia through transcriptional modulation of hepatocytes.

In advanced world stroke is one of the disabling cause of death that can be managed with thrombolysis if presents early despite further risk of intracerebral haemorrhage. Secondary prevention is an important objective in ischaemic stroke where recurrence is very high with subsequent stroke. Carotid End Arterectomy impact a definitive and effective role for both symptomatic and asymptomatic carotid stenosis for secondary stroke prevention in selective cases. Thrombolysis is a potential primary management for certain group whereas carotid surgery employs secondary preventative measure in a specified ischaemic stroke group.

In this study organic bulk heterojunction (BHJ) solar cell along with the spiro OMeTAD as a hole transport layer (HTL) and the PDINO as an electron transport layer (ETL) was simulated through the Solar Capacitance Simulator, one dimensional (SCAPS-1D) software to examine the performance of this type of polymer thin film organic solar cells. As an active layer the blend of polymer donor PBDB-T and non-fullerene acceptor ITIC-OE was used. Numerical simulation was performed by varying the thickness of HTL and active layer. Firstly, the HTL layer thickness was optimized to 50 nm, after that the active layer thickness varied up to 80 nm. These results of simulation demonstrated that the HTL thickness has rather little impact on efficiency while in the case of active layer thickness improves efficiency significantly. The temperature effect on the performance of solar cells was considered, by the simulation performed for temperature from 300 K up to 400 K and the efficiency of solar cell decreases with increasing temperature. Generally, polymer films usually are full of traps and defects, the density of defects (Nt) value was also introduced to the simulation, and it was confirmed that with the increasing of defect density (Nt), the efficiency of solar cell decreases. After thickness, temperature and defect density optimization, the reflection coating was also applied on it. It turned out that by introducing the reflection coating on the back side of solar cell, the efficiency increases by 2.5 %. Additionally, the positive effect of HTL and ETL doping on efficiency of this type of solar cells was demonstrated.

A newly identified novel coronavirus named as severe acute respiratory syndrome-related coronavirus2 (SARS‐CoV 2) has given rise to the global pandemic. SARS-CoV2 which causes coronavirus disease 2019 (COVID-19), is a positive-stranded RNA virus with nucleocapsid. It binds to host angiotensin-converting enzyme2 (ACE2) receptor through surface glycoprotein (S protein). These ACE 2 receptors are attached to the cell membranes of many organs. Thus, COVID-19 does not only result in acute respiratory distress syndrome but also affects multiple organ systems, requiring a multidisciplinary approach to manage this disease. COVID-19 can damage the myocardial cells and result in fulminant myocarditis, acute cardiac injury, cardiomyopathy, heart failure, cardiogenic shock, or arrhythmia. COVID-19 seeds harmful immune response through cytokine storm leading to indirect organ damage. In this literature review, the available data is comprehended regarding cardiovascular complications in COVID-19, and the correlation of biomarkers with the disease activity is discussed. This literature review also highlights the important treatment options and outcomes of the individual study.

Academic failure, low attendance, financial difficulties, and mental illness are some of the major reasons most students drop out of high schools. We investigated how high school dropout risk is affected by socioeconomic, demographic, and institutional characteristics. Therefore, research design is composed of a literature review, Questionnaire surveys by interviewing each student. Besides, the analysis and statistical modelling, the Logistic Regression method was used. The results show that academic performance, job, lack of interest and low learning ability were the significant individual characteristics that affect the high school dropout. Moreover, parental characteristics, including financial condition, lack of awareness, and education, are significant factors associated with high school dropout rates. Some other related factors, such as adaptability and influence of the peer groups, abandoning school by siblings, and extra responsibility at home and a joint family system, are also some notable factors that significantly affect the dropout rate in schools Malakand District of KP province. This research study delivered the results that contribute to the literature in education to identify different factors like student's own, parental, institutional, and household characteristics, which affect a student being a dropout from high school in Malakand district Pakistan.

Cadmium Sulfide nanoparticle (CdS-LA hybrid nanoparticles) was synthesized here by a green approach using the precursor cadmium acetate and sodium sulphide along with the extract of a plant Lathyrus aphaca L. containing the phytochemicals which were responsible for surface modification of nanoparticles. The nanoparticle was used to evaluate their inhibition potential against species of bacteria and fungi. The nanoparticles were characterized by XRD which demonstrates the hexagonal crystal structure. SEM confirms the homogenous surface appearance of the CdS-LA hybrid crystalline structure. EDX analysis confirms surface modification of nanoparticles by phytochemicals. FTIR confirmed the Cd-S linkage laterally with the related functional groups and the presence of metabolites on the surface of nanoparticles. The UV-visible spectroscopy confirmed the peak at the characteristic wavelength range but a slight shift occurred in the peak of the CdS nanoparticles due to the presence of the phytochemicals. This study particularly provides an environment-friendly strategy to synthesize the CdS nanoparticles capped by Lathyrus Aphaca L. extract that are biologically active due to the mediation of the plant extract. CdS-LA hybrid nanoparticles have shown inhibition potential against various species of bacteria and fungi and realize the biological importance of the green synthesis of nanoparticles especially mediated with the plant extract.

Cash holding is important for Chinese manufacturing firms coping with the increasing cost of financing and stiff market conditions. This study examines the impact of cash holding on the firm value of Chinese manufacturing firms. We find evidence that a non-linear relationship exists between cash holding and firm value in manufacturing firms of China. The study reveals that financially constrained firms having a higher level of cash holding negatively affects the firm value, while the unconstrained firms having a lower level of cash holding positively influences the firm value. Finally, this research is enriched by adopting the novel measure of managerial op-timism and reveals the interactive role of cash holding and optimism on firm value. The study concludes that managerial optimism influences the firm’s cash holding decisions and this is more costly for unconstrained firms.

We investigate the behavior of thermal quantum coherence in the Heisenberg XXX model for a two-qubit system placed in independently controllable Inhomogeneous magnetic fields applied to two qubits respectively. We discuss the behavior of quantum coherence by systematically varying the coupling parameter, magnetic field, and temperature for both ferromagnetic and antiferromagnetic cases. The results show the interesting behavior of quantum coherence in a certain range of parameters. Generally, it is observed that quantum correlations decay with temperature, but in the ferromagnetic case with uniform magnetic interaction, it rises with temperature up to a certain threshold value and ultimately it decreases its value to zero. Moreover, it is observed that preserving the quantum coherence for small temperatures is very hard with the increasing magnetic field because, at small temperatures, quantum coherence decays sharply with the increase in magnetic field whereas at larger temperatures it decays completely at fairly large values of the magnetic field. The variation of quantum coherence with uniform magnetic field in the antiferromagnetic case is observed to be Gaussian for larger temperature but at zero or nearly zero temperature, it behaves as a constant function for uniform magnetic field up to a threshold value and then decays to zero with an infinite slope. This shows the signature of quantum phase transition from quantum nature to classicality.

Emerging and reemerging pathogens is a global challenge for public health. Recently, a novel coronavirus disease emerged in Wuhan, Hubei province of China, in December 2019. It is named COVID-19 by World Health Organization (WHO). It is known to be caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) that affects the lower respiratory tract and manifests as pneumonia in humans. Coronaviruses (CoVs) are structurally more complicated as compared to other RNA viruses. This viral epidemic has led to the deaths of many, including the elderly or those with chronic disease or compromised immunity. Viruses cause infection and diseases in humans of varying degrees, upper respiratory tract infections (URTIs) cause common cold while lower respiratory tract infections induce pneumonia, bronchitis, and even severe acute respiratory syndrome (SARS). The costs of COVID-19 are not limited. It equally affects all the medical, sociological, psychological, and economic aspects globally. This is regarded as the third deadly outbreak in the last two decades after Severe Acute Respiratory Syndrome SARS (2002–2003) and Middle East Respiratory Syndrome MERS (2012). Based on the sequence homology of SARS-CoV-2, different animal sources including bats, snakes, and pangolins have been reported as potential carriers of this viral strain. Real-time RT-PCR represents the primary method for the diagnosis of new emerging viral strain SARS-CoV-2. The transmission dynamics suggest that SARS-CoV-2 is transmitted from person-to-person through direct contact or coughing, sneezing, and by respiratory droplets. Several anti-viral treatments including lopinavir/ritonavir, remdesivir, chloroquine phosphate, and abidor are also suggested with different recommendations and prescriptions. Protective and preventive strategies as suggested by various health organization i.e. WHO and US Center for Disease Control and Prevention (CDC) must be adopted by everyone. This review covers the important aspects of novel COVID-19 including characteristics, virology, symptoms, diagnostics, clinical aspects, transmission dynamics, and protective measures of COVID-19.

The aim of this article is introduced the concept of double framed T-soft fuzzy set (DFT-soft fuzzy set) which is the combination of soft set and fuzzy set. We also defined the notions and apply this concept in BCK/BCI-algebras. By using example, we also discussed the concept of double framed T-soft fuzzy algebra (DFT-soft fuzzy algebra) and double framed B-soft fuzzy algebra (DFB-soft fuzzy algebra) and also investigated their properties. Each double framed T-soft fuzzy algebra is double framed B-soft fuzzy algebra but by using example, we proved that converse may or may not be possible.

This study was to designed to develop sorafenib-loaded polymeric nanoparticles, surface-modified with pluronic F-127 for the effective treatment of hepatocellular (HCC) and renal cell carcinomas (RCC). Poly lactic coglycolic acid (PLGA) was used to encapsulate different concentrations of sorafenib by a simple modified solvent evaporation method applying pluronic F-127 as a surfactant and coating agent. The preformulation and characterization studies were conducted to evaluate the incompatibilities among sorafenib, PLGA and pluronic F-127, and physicochemical properties of the formulations, respectively. The sizes of the coated and plain PLGA nanoparticles were ~140 ± 14.7 nm and ~ 120 ± 10.1 nm, respectively. It has been confirmed from the in vitro release studies that PLGA sustained the release of sorafenib, avoiding the initial burst release, while the in vivo studies demonstared that surface-modified nanoparticles have greater affinity in the target aorgans than plain PLGA nanoparticles and free drug keeping the dose constant (20 mg/kg body weight). The delivery of sorafenib-loaded polymeric PLGA nanoparticles into the target tissues and their pharmacokinetic parameters have been improved significantly compared to the reported formulations.

As urban populations and transport demand expand, Pakistani metropolitan centers face traffic congestion and environmental challenges. This research aims to assess carpooling (CP) to alleviate traffic congestion, fuel demand, and pollution. This study was conducted in Islamabad, a fast-growing city with a high percentage of personal cars in Pakistan, to assess the travelers’ perceptions, and public acceptance of CP and determine the effects on traffic congestion, fuel consumption, and CO2 emissions. The investigation of travelers' perceptions towards CP was conducted through a stated preference questionnaire survey. A total of 700 responses from one million population of Islamabad were collected as per Sloven's Formula. SPSS and Smart PLS software were used for data analysis. Various factors influencing peoples’ travel perceptions, mode choice, and tendency to carpool, were categorized to evaluate the relationship between travelers’ perception and the tendency to carpool in the presence of mode choice as a mediating variable. Confirmatory factor analysis was conducted in SMART PLS to refine the number of scale items for each variable. One-way ANOVA, step-wise and mediated multiple regression analysis was conducted in SPSS to check the direct and mediating relationship between different variables. Moreover, the probability of reducing traffic congestion and assessing fuel reduction resulting from CP was also analyzed. The findings imply that travelers’ mode choice acts as a mediator between the relationship between travelers’ perception and tendency to carpool. Furthermore, results predicted that CP might reduce 0.25 million cars on the road, about 33.6% of the total private vehicles. Thereby, saving up to 546,810 barrels per year, about 3.42% of Pakistan's total petrol consumption. The findings of this study could be helpful for transport planners, environmentalists, and policymakers to implement carpool systems. Thus, reducing traffic congestion and harmful CO2 emissions and maintaining a sustainable environment.

Glaciers in northern Pakistan are a prime source of fresh water, providing headwater in the Indus River System and serving as a lifeline to millions of people in the region. These glaciers undergo continuous changes by melting due to global warming or accumulation due to snowfall/precipitation at higher altitudes. In this study, we used remote sensing data to quantify glacier changes in spatiotemporal variability in the past three decades. Five glaciers in the Gilgit region (near the junction of the Hindukush and Karakoram Mountains) with an extent of less than 5 square kilometers were selected, namely Phakor glacier, Karamber glacier, East Gammu glacier, Bhort glacier, and Bad-e-Swat glacier. The fluctuations in these glaciers were monitored using a digital elevation model (DEM) and a cloud-free continuous series of Landsat satellite pictures from the minimal snow cover season. The annual climatic trends were studied through spatially interpolated gridded climate data WοrldClim version-1 climate database for 1970 – 2000. We used it to study the variations of minimum and maximum temperature, solar radiation, and precipitation by preparing sub-sets from the original global grids. The temporal assessment of Bhort, Bad-e-Sawat, East Gammu, Karamber, and other rivers was also carried out. It is observed that the glaciers in the Gilgit watershed are rather stable. The little variability of glaciers is due to their geographic condition, altitude, topography, and orientation. The mapped glacier classes have been validated to check the accuracy assessment through an error matrix method. The kappa coefficient from the error matrix has been calculated to be 84 %. The study makes a critical input to a greater understanding of watershed controlling and hydrological processes in the upper Indus catchment's Gilgit watershed.

The elegance of mathematical models in quantum mechanics has often been seen with awe, and especially frustration. Nonetheless, the mathematical physics of quantum mechanics is fascinating beyond measure. And fortunately, there are quite baffling things about quantum mechanics that showed us what we never thought could be seen, making it simpler to figure out the behavior of physical systems without having to delve into the subtleties of the subject. In this paper, we present a review on the density of quantum states in an intuitive fashion that is easily comprehensible to undergraduate students with an elementary background in physics.

The purpose of this paper is to develop WebSecuDMiner algorithm to discover unusual web access patterns based on analysing the potential rules hidden in web server log and user navigation history. Design/methodology/approach: WebSecuDMiner uses equivalence class transformation (ECLAT) algorithm to extract user access patterns from the web log data, which will be used to identify the user access behaviours pattern and detect unusual one. Data extracted from the web serve log and user browsing behaviour is exploited to retrieve the web access pattern that is produced by the same user. Findings: WebSecuDMiner is used to detect whether any unauthorized access have been posed and take appropriate decisions regarding the review of the original rights of suspicious user. Research limitations/implications: The present work uses the database which is extracted from web serve log file and user browsing behaviour. Although the page is viewed by the user, the visit is not recorded in the server log file, since it can be access from the browser's cache.

Zinc nanoparticles (ZnNPs) open new opportunities for biomedical applications as a strategy against microbes and dye removal in an efficient way. The composite ZnNPs using Rhododendron arboreum (R. arboreum) stem bark were synthesized and characterized for UV-visible spectroscopy (UV-vis), Fourier transform infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The synthesized nanoparticles showed zones of inhibition of 23±0.09, 18±0.1 and 16±0.05 mm, against the Klebsiella pneumoniae (K. pneumoniae), Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli strains. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values against K. pneumoniae, S. aureus, and E. coli were found to be 34±0.21 and 72.71±0.47, 47±0.11 and 94.86±0.84 and 94±0.18 and 185.43±0.16 µg/mL, respectively. The biosynthesized ZnNPs resulted in significant eradication of the outer and inner membranes of the bacterial cells. Likewise, the synthesized ZnNPs showed time-dependent photocatalytic degradation activity and revealed 65% methyl orange dye degradation with an irradiation period of 6 hours. The findings of this study suggest the suitability of the novel R. arboreum stem bark-based ZnNPs as an effective ameliorant against bactericidal activities and photocatalysts for the removal of hazardous water contaminants.

In this research work the study of Buongiorno Model Darcy Forchheimer flow of Hybrid nanofluid flow on isothermal permeable stretch/shrink sheet with homogeneous and heterogeneous reaction is investigated. The effects of MHD, thermal radiation, viscous dissipation, Joule heating, and heat generation/absorption are taken into account. Hybrid nanofluids can act as a medium for heterogeneous-homogeneous reactions. The nanoparticles dispersed in the fluid can influence reaction kinetics and species transport, potentially, altering reaction rates and pathways. The applications of HNF in reactions, both homogeneous and heterogeneous, lie in leveraging their enhanced thermal properties, catalytic potential, and improved mixing capabilities to optimize reaction efficiency and control reaction conditions. Similarity transformation is used to convert a set of PDEs into a set of ODEs. HAM is used for the solution of the obtained ODEs system. In a heterogeneous reaction, the concentration gradient is amplified; in a homogeneous reaction, the impact is opposite. Moreover, at higher compositions of HNPs, the concentration and velocity rise while the temperature falls. Furthermore, as the values of homogeneous and heterogeneous reactions increase, the concentration falls. It is reliable with the idea that a greater reaction rate lowers the diffusion rate. Nevertheless, these parameters do not affect temperature or velocity.

During the last two decades, energy poverty has captured a growing attention of researchers and policymakers due to its strong association with economic poverty and poor economic performance. This study uses a broad set of macro level indicators and makes the first attempt to measure energy poverty and its impact on economic growth of Pakistan over the period 1990 to 2017. In particular, our energy poverty indicator considers four main dimensions of energy poverty, namely, energy services, clean energy, energy governance and energy affordability. Our main results show that though the overall energy poverty has reduced in Pakistan during the selected sample period, the country shows an increasing dependence on polluted energy supply in order to meet its growing demand of energy. In second stage of the investigation, we test the neoclassical growth theory where we incorporate energy poverty along with human capital as source of economic growth. Our cointegration results reveal a strong relationship between energy poverty and economic growth that is also dynamically stable in short run. These strong negative linkages between energy poverty with economic growth for the sample economy complement the previous literature on the subject.

The fatigue crack growth rate (FCGR) of aluminium alloys under the combined influence of temperature and humidity remains a relatively unexplored area, receiving limited attention due to its intricate nature and challenges in predicting the combined impact of these factors. The challenge was to investigate and address the specific mechanisms and interactions between temperature and humidity, as in coastal environment conditions, on the FCGR of aluminium alloy. The present study conducts a comprehensive investigation on the combined influence of temperature and humidity on the FCGR of Al6082 alloy. The fatigue pre-cracked compact tension specimens were corroded for 7 days and then subjected to various temperature and humidity conditions in a thermal chamber for 3 days to simulate coastal environments. The obtained data were analysed to determine the influence of temperature and humidity on the FCGR of Al6082 alloy. An empirical model was also established to predict fatigue life cycle values under these environmental conditions precisely. The correlation between FCGR and fracture toughness models was also examined. The Al6082 alloy exhibits a 34% increase in the Paris constant C, indicating reduced FCGR resistance due to elevated temperature and humidity levels. At the same time, fatigue, corrosion, moisture-assisted crack propagation, and hydrogen embrittlement lead to a 27% decrease in threshold fracture toughness. The developed model exhibited accurate predictions for fatigue life cycles, and the correlation between fracture toughness and FCGR showed less than 10% error, indicating a strong relationship between these parameters.

This paper discusses some of the most common misconceptions about large language models (LLMs), including the belief that they are sentient or conscious, that they are always accurate, and that they can replace human creativity. The paper also proposes a strategy for overcoming these misbeliefs, which involves educating the public about the capabilities and limitations of LLMs, developing guidelines for the responsible use of LLMs, and conducting more research to understand the potential impact of LLMs on society.

Over the last three decades, special economic zones (SEZs) have given new impetus to the ever-growing export-oriented industrialization in developing countries. Where various economies have benefited from SEZs, many zones have ended up becoming enclaves with trifling advantage. The SEZs in Pakistan have experienced the same fate and failed to contribute to exports, employment and creating linkages with the domestic economy. Recently under China Pakistan Economic Corridor (CPEC), SEZs are proposed to be set up in Pakistan; with a hope to fuel the stuttering economy. However, it is pertinent to first understand the local context and device policies considering stakeholders' perspectives. This study aims to identify the factors for the successful implementation of SEZs derived from the regional context of Pakistan. In-depth interviews are conducted from most relevant stakeholders, who have been involved in the development of SEZs. The results pointed towards the removal of political influence over zones and government taking the lead role in deciding the types of industry to be invited in these zones. Each zone should have a clear vision of development based on its regional advantage. The zone promotions should be based on competitiveness rather than fiscal incentives. Joint ventures and PPP to be encouraged inside the zones for sustainable operations.

Sugarcane is an important industrial crop of semitropical and tropical areas. Due to the importance of this crop it is cultivated on nearly 20 million hectares by more than 90 countries. This crop belongs to family Poaceae, a grass family which is economically vital tracheophyte family that has properties much like that of wheat, maize, rice and sorghum. The Poaceae family is globally vital for providing dietary macromolecules, carbohydrates, and different nutrients. The most important item of sugarcane for the consumption is sucrose that gets accumulated in the stalk internodes. Sucrose is taken out and refined by different mills which is used as a sweetener in human food industries and in the fermentation industry. Large production of alcohol is attained by Brazilian sugarcane industries.

The current study was formulated with the aim of assessing the impact of the Extent of Drug addiction on the Family environment and interventions for drug-addicted youth in rural areas of Dir Lower Khyber Pakhtunkhwa, Pakistan. The study comprised a dependent variable (Extent of Drug addiction) and an independent variable (Family Environment). A sample size of 266 was randomly selected for primary data collection through structured interviews. The collected information was evaluated through descriptive analysis (frequency and percentage distribution) and inferential analysis, specifically utilizing the Chi-square Statistical Test. The study concluded that drug addiction among youth has an adverse impact on the family environment, leading to instability and violent behavior. Further, families of drug-addicted youth experience a high level of dissatisfaction in relationships, often culminating in divorce. Similarly, the families of drug-addicted are characterized by low cohesion, role conflict, and tolerance. Thus, the government should formulate polices and strategies for the prevention of drug addiction, with speedy implementation across all institutional dynamics, including family. Moreover, It is also crucial to rehabilitate the lifeblood of a nation (youth) in terms of socio-economic, emotional and psychological growth. These recommendations were put forward in the light of the current study.

This comprehensive critical review shows how green buildings and energy optimization solutions improve indoor air quality as well as environmental quality (IEQ) and human health. Electricity-efficient green buildings create a better indoor atmosphere and save electricity. Green buildings improve occupant well-being through IAQ, thermal comfort, acoustics, and lighting. Renewable energy, green construction materials, and intelligent technologies increase sustainability and reduce environmental impact. Environmental hazards, architectural design, and societal variables can improve indoor air quality and subsequently reduce health risks linked with poor air quality. The evaluation highlights the pros and cons of low-cost IAQ sensors and equipment. These devices provide valuable insights, but calibration and validation using reference equipment are necessary to ensure accuracy and reliability. Architects, engineers, environmentalists, and policymakers are essential in creating green buildings with high IEQ. Prioritizing occupant comfort, health, and productivity ensures a sustainable and healthy future for future generations. However, continual monitoring and research are needed to improve green building practices and overcome construction problems. Intelligent models for continual on-field calibration of low-cost sensors may improve performance. Green buildings benefit occupants and the environment by optimizing energy use and using IAQ monitoring technologies.

In this paper a new monolithic Eulerian formulation in the framework of non-classical continuum is presented for the analysis of fluid-strucutre interaction problems. In this respect, Cosserat continuum theory taking into account the micro-rotational degrees of freedom of the particles is considered. Continuum description of the model and variational formulation of the governing flow dynamics for non-classical -fluid-structure interaction nCFSI is presented. The model is analyzed by computing a well known benchmark problem by Hecht and Pironneau [16]. The algorithmic description is presented and implemented using FreeFEM++. Code is validated with the benchmark solution of Turek and Hron [38] in case of flow around a flag attached with cylinder. New microstructral behavior of the solution is studied and numerical simulations and results are shown in the form of figures. Some interesting feature of the flow is observed and microstructural characteristics are discussed.

The world is growing very rapidly concerning technology. In the next-generation Internet, the existing architecture requires to be upgraded from Host-Centric Networking paradigm to Information-centric networking architecture. The unique aspect of information-centric networking is in-network cashing. Due to the system augmentation and In-network cashing technique, this novel system needs extremely high content security to ensure system integrity and maintenance. 5G network may be supported by the Information-Centric Network due to its high data transmission rate. In order to handle the serious security issues such as attack on confidentiality, authentication and integrity of the content, a Digital Signature based Access Control Mechanism in Information-Centric Network (DSAC) scheme is proposed to enhance security of ICN. Briefly, this new scheme uses Digital Signature, hash function, Trusted Third Party (TTP) and Proxy TTP. The client request for content, after receiving a request, the content provider generates and encrypts content with the digital signature and random value ‘k’ hash function and send it to TTP. After the signing process, the TTP sends the encryption hash key to Proxy TTP. In this proposed scheme authentication, confidentiality, the integrity aspects of the content security are improved.

Haemonchus contortus (H. contortus) is a gastrointestinal parasite affecting small ruminants, leading to a significant decline in animal productivity. In this study, we developed a nanovaccine by encapsulating the recombinant protein rHcES-15, derived from the excretory/secretory products of H. contortus, within biodegradable poly (D, L-lactide-co-glycolide) (PLGA) nanoparticles (NPs). To construct the nanovaccine, PLGA NPs were prepared using a modified double emulsion solvent evaporation technique. Scanning electron microscopy (SEM) illustrated successful encapsulation of rHcES-15 within PLGA NPs, with a size ranging between 350-400 nm. The encapsulation efficiency (EE) of the antigen in the nanovaccine was determined to be 72%. A total of forty experimental mice were divided into five groups, receiving the nanovaccine on day 0 and being humanely sacrificed at the end of the 14-day trial. The stimulation index (SI) from mice vaccinated with the nanovaccine indicated an amplified lymphocyte proliferation and a significant increase in anti-inflammatory cytokines (IL-4, IL-10, and IL-17). Furthermore, the percentages of T-cells (CD4+, CD8+) and dendritic cell phenotypes (CD83+, CD86+) were substantially upregulated in mice immunized with the nanovaccine compared to control groups and the rHcES-15 group. Similarly, higher levels of antigen-specific serum immunoglobulins (IgG1, IgG2a, IgM) were observed in response to the nanovaccine compared to both the antigenic (rHcES-15) and control groups. In conclusion, the data strongly supports the notion that encapsulation of rHcES-15 within PLGA NPs effectively stimulates immune cells in vivo, ultimately augmenting antigen-specific adaptive immune responses against H. contortus. This discovery highlights the promising potential of the nanovaccine, justifying additional investigations to ascertain its efficacy finally.

The multidisciplinary nature of the work required for research in the Covid-19 pandemic has created new challenges for health professionals in the battle against the virus. They need to be equipped with novel tools and resources ---that have emerged during the pandemic--- to gain access to breakthrough findings, know the latest developments, and to address their specific needs for rapid data acquisition, analysis, evaluation, and reporting. Because of the complex nature of the virus, the healthcare systems worldwide are severely impacted as the treatment and the vaccine for Covid-19 disease are not yet discovered. This leads to frequent changes in regulations and policies by governments and international organizations. Our analysis suggests that given the abundance of information sources, finding the most suitable tool for a given task is one of such challenges. But health professionals and policymakers need access to the most relevant, reliable, trusted, and latest information and tools that can be used in their day-to-day tasks of Covid-19 research and analysis. In this article, we present our analysis of various novel and important tools that have been specifically developed during the Covid-19 pandemic and that can be used by the health professionals community to help in advancing their analysis and research. These tools comprise of search engines, information repositories for literature and clinical trials, data sources, dashboards, and forecasting models. We present list of the minimally essential tools to serve a multitude of purposes, from hundreds of those developed since the beginning of the pandemic. A critical analysis is provided for the selected tools based on 17 parameters that can be useful for researchers and analysts for their evaluations. These parameters make up our evaluation framework and have not been used previously for analysis and evaluation. Hence, knowledge of the tools will not only increase the productivity but will also allow to explore new dimensions for using existing tools with more control, better management, and greater outcome of their research. In addition, the parameters used in our framework can be applied for future evaluations of similar tools and health professionals can adapt them for evaluation of other tools not covered in this analysis.

Hepatitis B and C are major health issues in developing countries such as Pakistan and Afghan-istan. The aim of this study was to determine the prevalence and effectiveness of a screening program for hepatitis B and C in a region with no existing programs, and to estimate their prev-alence in the general population in Khyber Pakhtunkhwa Province, Pakistan, as well as in Afghan refugees or migrants. A prospective cohort study was done in the general population of Peshawar and its adjacent districts, as well as migrants from neighboring provinces of Afghani-stan, who presented to our tertiary-care health facility. A Microsoft Excel registry was created for data collection, which were analyzed using IBM SPSS via descriptive analysis, normal distribution curve histograms, and chi-squared tests. A total of 9563 individuals were screened for hepatitis (5894 males and 3669 females), including Afghan migrants in Peshawar and surrounding districts. 876 individuals tested positive for hepatitis, with 538 positive for hepatitis B (383 males and 155 females) and 330 positive for hepatitis C (198 males and 134 females). Eight individuals had a hepatitis B and C co-infection. Among the study population, the prevalence rates were 2.2% for hepatitis B and 2.3% for hepatitis C, of which the Afghan migrants accounted for 2.7% and 0.5%, respectively. According to the gender-based distribution, hepatitis B was more prevalent in males, whereas there was no significant gender-based difference for hepatitis C. Our results highlight the need for a comprehensive approach to control hepatitis B and C in Pakistan and Afghanistan. Increased awareness, improved healthcare, and preventive measures such as screening and elimination programs to prevent severe liver diseases and eradicate hepatitis are necessary.

The paper discusses how joint damage and deterioration affect the seismic response of existing reinforced concrete frames with sub-standard beam-column joints. The available simplified modeling techniques are critically reviewed to propose a robust, yet computationally efficient technique for simulating the nonlinear behavior of substandard beam-column joints. Improvements over the existing models include simulation of the cyclic deterioration of joint stiffness and strength as well as pinching in the hysteretic response, implemented considering a deteriorating hysteretic rule. A fibre-section forced-based inelastic beam-column element is developed; considering improved material models and fixed-end rotation due to bond failure, rebars-slip and inelastic extension, to simulate the deteriorating cyclic behavior of existing pre-cracked beam-column members. For the assessment of frames with substandard exterior beam-column joints, a nonlinear model for the exterior joint is developed and validated through a full-scale quasi-static cyclic test performed on a substandard T-joint connection. The proposed model allows considering structural performance in risk assessment while accounting for true inelastic mechanisms at the joints.

Facial emotion detection is a challenging task that deals with emotion recognition. It has applications in various domains, such as behavior analysis, surveillance systems and human-computer interaction (HCI). Numerous studies have been implemented to detect emotions, including classical machine learning algorithms and advanced deep learning algorithms. For the machine learning algorithm, the hand-crafted feature needs to be extracted, which is a tiring task and requires human effort. Whereas in deep learning models, automated feature extraction is employed from samples. Therefore, in this study, we have proposed a novel and efficient deep learning model based on Neural Architecture Search Network utilizing superior artificial networks such as RNN and child networks. We performed the training utilizing the FER 2013 dataset comprising seven classes: happy, angry, neutral, sad, surprise, fear, and disgust. Furthermore, we analyzed the robustness of the proposed model on CK+ datasets and comparing with existing techniques. Due to the implication of reinforcement learning in the network, most representative features are extracted from the sample network. It extracts all key features without losing the key information. Our proposed model is based on one stage classifier and performs efficient classification. Our technique outperformed the existing models attaining an accuracy of 98.14%, recall of 97.57%, and precision of 97.84%.

Wheat pollen, characterized by its short lifespan, exhibits rapid germination after anthesis. The preservation of wheat pollen is contingent upon environmental factors, including temperature, relative humidity, light, and wind. The objective is to develop a method for preserving wheat pollen effectively, specifically for the purpose of breeding. The short longevity of wheat pollen grains renders it impractical to conduct tests for pollen viability and in vitro germination on a large scale. Herein, the impact of storage temperatures and duration was assessed on pollen viability and in vitro germination to optimize storage conditions for preserving pollen viability. Pollen grains from 50 diverse spring wheat genotypes, each with three replicates, were harvested and stored at temperatures of 22°C, -20°C, and 4°C. Subsequently, pollen viability and in vitro germination rates were determined after storage of 1, 3, and 6 days. The results revealed that storage temperatures, durations, genotypes, and their interactions had a statistically significant impact on both pollen viability and in vitro germination. Notably, when pollen was kept at 22°C, almost all genotypes exhibited a loss of pollen viability and in vitro germination after 1, 3, and 6 days of storage. Likewise, storage at -20°C failed to extend pollen germination. However, at a storage temperature of 4°C, the pollen of 36 wheat genotypes exhibited a range of 6-14% in vitro pollen germination and remained viable even for 6 days. Simple linear regression analysis further revealed a significant negative correlation between pollen viability, in vitro germination, and storage time and temperature. In conclusion, our findings underscore 4°C as the optimal temperature for preserving pollen viability and in vitro pollen germination in spring wheat for up to 6 days. The results of the present study suggests that pollen viability of wheat is genotype de-pendent, storage temperature and storage duration. Thus, the 36 wheat genotypes identified during the present work could be efficiently maintained at 4◦C for short-term storage (6 days) and could be further used for genetics and breeding purposes.

This study addresses the central question that how can a precise measurement of the gluon Parton Distribution Function (PDF) be attained, thereby enhancing our understanding of the intricate quark-gluon composition within nucleons? Through a dual approach involving Quantum Chromodynamics (QCD) and high-energy particle collisions, the research combines computational tools and experimental techniques, focusing on protons and neutrons. Scattering experiments and advanced detectors are utilized to probe nucleon structure. Theoretical frameworks like QCD equations and the Momentum Sum Rule investigate Parton Distribution Functions at specific momentum fractions and energy scales. The primary goal is to achieve an accurate measurement of the gluon PDF, crucial for unraveling strong force complexities and internal nucleon dynamics. The study's theoretical plots and equations illustrate hypothetical behaviors of gluon distribution, quark distribution, and splitting functions, contributing to a deeper understanding of fundamental particles.

Nigeria is the most populous country in the African continent. The aim of this study was to analyze risk factors for COVID-19 prevalence and deaths in all 6 geopolitical regions and 37 states in Nigeria. We analyzed the data retrieved from various sources, including Nigeria CDC, Nigeria National Bureau of Statistics, Unicef-Nigeria multiple indicator cluster survey and the Institute of Health Metrics and Evaluation, University of Washington. We examined 4 clinical risk factors (prevalence of TB, HIV, smoking and BCG vaccination coverage) and 5 sociodemographic factors (age ≥65, population density, literacy rate, unemployment and GDP per capita). Multivariate modeling was conducted using generalized linear model. Our analysis showed that the incidence of confirmed COVID-19 cases differed widely across the 37 states, from 0.09 per 100,000 in Kogi to 83.7 in Lagos. However, more than 70% of confirmed cases were concentrated in just 7 states: Lagos, Abuja, Oyo, Kano, Edo, Rivers and Delta. Case mortality rate (CMR) per million population also varied considerably, with Lagos, Abuja and Edo having CMR above 9. On bivariate analysis, higher CMR correlated positively with GDP and to a lesser extent with TB and population density. On multivariate analysis, which is more definitive, states with higher HIV prevalence and BCG coverage had lower CMR, while high GDP states had a greater CMR. This study indicates that COVID-19 has disproportionately affected certain states in Nigeria. Population susceptibility factors include higher economic development but not literacy or unemployment. Death rates were mildly lower in states with higher HIV prevalence and BCG vaccination coverage.

Single cell proteins are the dead dried cells of microorganisms or purified protein isolated from microorganism’s cell culture, used as a food supplement to humans’ food and animals feed. World suffer from malnutrition particularly developing countries, due to rapid increase in population, increased the demand for protein and nutrients requirement. Bacteria is potential microorganism for SCP production due to high protein content, fast generation time, bio-active secondary metabolites production and can grow on various substrates. Actinobacteria species and strain have capability to produce biological active compounds, produced about two-thirds of antibiotics available in the market, actively used as antibiotics, antiprotozoal, antifungal, antiviral, anticancer, anticholesterol, antihelminth and immunosuppressant. Actinomycetes can be used as probiotic as well as single cell protein that will deal with antibiotic as well as protein source.

Producing cherry tomatoes became interesting to know watering volume and growing design on growth, yield, and quality of cherry tomatoes. The research aimed to intend the best treatment for each treatment of watering volume and Growing design on the productivity and quality of cherry tomato cultivar Ruby. The study is an experimental exploration using RCBD factorial. The treatment factors include: Growing Design (greenhouse, Rain shelter, Screen house) and Watering Volume (100% Etc, 75% ETc, 50% ETc). The result showed that root dry weight and root-shoot ratio were found higher in the screen house design, while fruit firmness was higher in the rain shelter design. Considering the effect of watering volume, higher fruit diameter, heavier fruit, fruits per plant, ultimate fruit & biological yield per plant, higher root & shoot biomass, root-shoot ratio, leaf chlorophyll content, greater fruit skin firmness and elasticity was noted in the 100% ETc treatment. In contrast, the growth rate was higher in 50% ETc treatment. Cultivating cherry tomatoes in a greenhouse using a watering volume of 100% ETc under the results is recommended. These conditions have led to better growth, higher fruit yield, and improved fruit quality, making them favorable options for successful cherry tomato production.

Antimicrobial resistance (AMR) due to community carriage of antibiotic-resistant bacteria is highly prevalent in the WHO South-East Asia region. One of the major reasons is the misuse of antibiotics in animal farming practices and at community level, which threatens both human and animal health. However, this multifaceted One Health (OH) problem of antibiotic use (ABU) in poultry farms and respective farmers is not well studied in countries like Pakistan. Therefore, we conducted n OH cross-sectional study in rural Punjab to explore the current practices of ABU in poultry and poultry farmers, associated factors, their healthcare-seeking behaviour and biosecurity practices. We found all the participating farmers using antibiotics for poultry, 60% of which were Colistin sulphate and Amoxicillin trihydrate. The significant consumption of antibiotics in poultry farms (60%) and poultry farmers (50%) was without prescription. Most of the farms (85%) had no wastewater drainage system, causing direct shedding of poultry waste and antibiotic residue in the surrounding environment. Lack of farmers’ education, professional farm training and duration of farming experience were the significantly associated factors with ABU and knowledge of AMR. Our study implies the necessity of an integrated OH-AMR policy with the inclusion of farmers’ education, mass awareness, and strict antibiotic usage guidelines.

In this work, meshless methods are applied for the solution of two-dimensional steady-state heat conduction problems with nonlocal multi-point boundary conditions (NMBC). These meshless procedures are based on multiquadric radial basis function (MQ RBF) and its modified version (i.e. integrated MQ RBF). The proposed meshless methods which were recently published in \cite{Reutskiy2016} is compared with standard collocation method (i.e. Kansa's method). Three different sorts of solution domain are considered in which Dirichlet boundary condition is specified on some part of the boundary and is related to the unknown function values at a discrete set of interior points. The influence of NMBC on the accuracy and condition number of the system matrix associated to the proposed methods is investigated. The sensitivity of the shape parameter is also analyzed in the proposed methods. Performance of the proposed approaches in terms of accuracy and efficiency is confirmed on the benchmark problems.

Organizational diagnosis (OD) is a comprehensive review of an organization's objectives, re-source allocation, and utilization to achieve those objectives. This study employed OD to en-hance the effectiveness of the Department of Special Education within the Government of Punjab. A questionnaire based on Weisbord's six-box organizational model called the Organ-izational Diagnostic Questionnaire (ODQ), was administered to N=1200 participants, consist-ing of heads of top, middle, and bottom tiers at district and tehsil levels of special education schools, centers, and the main office. Out of these, 506 participants voluntarily completed the ODQ survey. The study findings indicated that the employees of the department possess a good understanding of the organization's objectives. However, there is a lack of opportunities for employee participation in departmental discussions, centralized decision-making, irra-tional task distribution, and unsupportive allocation of human resources. Additionally, there is poor communication, unsatisfactory promotions, incentives, and a lack of knowledge shar-ing among employees, as well as poor inter-relationships, conflicts, and ineffective help-seeking mechanisms. The study also revealed low readiness for change in the organization. Respondents' opinions differed significantly based on their qualifications, job experience, years served, and gender. To improve the department's capacity to absorb change, the study recommends enhancing collaboration and inter-departmental communication, soliciting comprehensive input from all tiers, and promoting employee participation, supportive supervision, and communication. The study contributes to the body of knowledge on OD and highlights the need for improved communication, collaboration, and employee participation, as well as a supportive and supervisory support system to enhance the effectiveness of organizations.

Yeast extract is widely used in different food industries as a flavoring agent or vitamin supplement. In this study, a process was optimized for the production of yeast extract from Baker’s yeast (Saccharomyces cerevisiae). A glass vessel stirred fermenter was used for the cultivation of yeast biomass. The effect of various physical and chemical factors was evaluated on the production of yeast cells and optimum conditions for the production of maximum yeast biomass were determined. The optimum growth was obtained at 30ºC with pH 4.5 using molasses as a substrate supplemented with urea at 150rpm. Yeast cells were then separated by centrifugation and ruptured and autolysis was observed to be the most feasible method. Among various method employed to dry the yeast extract, spray dryer appeared as most efficient one. Yeast extract obtained after drying was subjected to different analyses and compared with commercial yeast extract. The produced yeast extract was applied in media preparation to grow different microorganisms including yeast, bacteria and fungi and considerable growth was observed. These results indicated that the developed process is a cost effective alternate approach for the production of yeast extract.

Membrane transporters (MTs) are mainly localized at the plasma membrane (PM), tonoplast and vacuolar membrane (VM) of cells in all plant organs. Their work is to maintain the cellular homeostasis by controlling ionic movements across PM channels from roots to upper plant parts, xylem loading and remobilization of sugar molecules from photosynthesis tissues in the leaf (source) to roots, stem and seeds (sink) via phloem loading. The plant’s whole source-to-sink relationship is regulated by multiple transporting proteins in a highly sophisticated manner and driven based on different stages of plant growth and development (PG&D), and environmental changes. The MTs play a pivotal role in PG&D in terms of increased plant height, branches/tiller numbers, enhanced numbers, length and filled panicles per plant, seed yield and grain quality. Dynamic climatic changes disturbed the ionic balance (salt, drought and heavy metals) and sugar supply (cold and heat stress). Due to poor selectivity, some of the MTs also uptake toxic elements in the roots that negatively impact on PG&D, later on also exported to upper parts and then deteriorate the grain quality. As an adaptive strategy, in response to salt and HMs plants activated PM and VM localized MTs that export toxic elements into vacuole, and also translocate in the root’s tips and shoot. However, in case of drought, cold and heat stresses, MTs increased the water and sugar supply to all organs. In this review, we mainly reviewed recent literature from Arabidopsis, halophytes, and major field crops such as rice, wheat, maize and oilseed rape to argue on the global role of MTs in PG&D and abiotic stress tolerance. We also discussed the gene expression level changes and genomic variations within a species as well as within a family in response to developmental and environmental cues.

Inflammatory bowel diseases (IBD), including Crohn's disease and ulcerative colitis, is a disease of chronic inflammatory conditions of the intestinal tract due to disturbance of the inflammation and immune system. Symptoms of IBD include abdominal pain, diarrhea, bleeding, reduced weight, and fatigue. In IBD, the immune system attacks the intestinal tract's inner wall, causing chronic inflammation and tissue damage. In particular, IL-6 and IL-17 act on immune cells, including T cells and macrophages, to amplify the immune responses so that tissue damage and morphological changes occur. Of note, excessive calorie intake and obesity also affect the immune system due to inflammation caused by lipotoxicity and changes in lipids supply. Similarly, individuals with IBD have alterations in liver function after sustained high-fat diet feeding. In addition, excess dietary fat intake, along with alterations in primary and secondary bile acids in the colon, can affect the onset and progression of IBD because inflammatory cytokines contribute to insulin resistance; the factors include the release of inflammatory cytokines, oxidative stress, and changes in intestinal microflora, which may also contribute to the disease progression. However, interfering with de novo fatty acid synthase by deleting the enzyme acetyl-CoA-carboxylase 1 in intestinal epithelial cells leads to the deficiency of epithelial crypt structures and tissue regeneration, which seems to be due to Lgr5+ intestinal stem cell function. Thus, conflicting reports exist regarding high-fat diet effects on IBD animal models. This review will focus on the pathological basis of the link between dietary lipids intake and IBD and cover currently available pharmacological approaches.

3D reconstruction from a single 2D input is a classic problem in the field of computer vision. With the advancements in deep learning, the performance of 3D reconstruction has also significantly improved. The reconstruction task is more difficult for objects with no textures or complex deformations. This paper serves as a review of recent literature on 3D reconstruction from a single view, with a focus on deep learning methods from 2018 to 2021. Due to lack of standard datasets or 3D shape representation methods, it is hard make direct comparisons between all reviewed methods. However, this paper reviews different approaches for reconstructing 3d shape as depth maps, surface normals, point clouds and meshes; along with various loss functions and evaluation metrics used to train and evaluate these methods.

Human displacement is on the rise globally, and the increase in the burden of tuberculosis (TB) is also attributed to migrations worldwide. A significant number of such displacement occur in regions with considerably higher areas of TB burden. Displacements may delay in TB diagnosis and treatment, which possibly will lead to TB transmission among healthy individuals. In this study, we assessed the association of existing determinants after a protracted internal displacement of people with the delay in TB diagnosis and treatment outcomes. A cross-sectional study was conducted on internally displaced TB patients registered at selected health facilities in three urban districts of Pakistan from March 2019 to February 2020. The univariate and multivariate logistic regression model was used to assess the delay in diagnosis and treatment outcomes. IDPs with delay in initiation of treatment beyond 30 days were at high possibility of unsuccessful TB treatment outcomes (adjusted odds ratio AOR,2.60; 95% CI 1.06-6.40). Analysis of factors that affect health seeker behavior and timely treatment showed a significant association (p<0.05) in-between age group 55-65 years (AOR, 2.66; 95% CI 1.00-7.07), female patients (AOR, 2.42; 95% CI 1.21-4.81), visited non-formal health provider (AOR, 8.81; 95% CI 3.99-19.46), self-medication (AOR, 2.72; 95 % CI 1.37-5.37), poor knowledge of TB (AOR, 11.39; 95% CI 3.31-39.1), and perceived stigma (AOR, 8.81; 95% CI 3.99-19.4). Prolong delay in treatment was associated with unfavorable treatment outcomes among IDPs, more specifically. As migrants and IDPs are more likely to experience an interruption in care due to overall exclusion from social and health care services. Therefore, it is imperative to understand the barriers in providing public health care services, particularly in preventing and treating TB.

Tapping panel dryness (TPD) syndrome is a complex disease of Rubber tree (Hevea brasiliensis L.) which causes cessation of latex drainage upon tapping of rubber tree. Rubber tree virus (RTV1) was identified as a novel pathogen associated with rubber tree and a potential causal agent of TPD. RTV1 is a monopartite RNA virus that is linear, non-enveloped and has a single-stranded (ss) positive RNA genome of approximately 6081 nucleotides and is composed of two major open reading frames (ORFs), ORF1 (polyprotein), and ORF2 (movement protein. This study aimed to investigate the possibility of rubber genome encoded tree microRNAs (miRNAs) as novel therapeutic targets against RTV1 using in silico algorithms. Mature rubber tree miRNAs are retrieved from the miRBase database and are used for hybridization of RTV1 using five different five different computational algorithms including miRanda, RNA22, RNAhybrid and psRNATarget. A total of eleven common rubber tree miRNAs were identified based on consensus genomic positions. The consensus of four algorithms predicted the hybridization sites of hbr-miR396a and hbr-miR398 at common locus positions 6676, 1840 respectively. To validate the prediction, secondary structures of the consensual rubber tree miRNAs and free energy of duplex binding were calculated using the RNAfold and RNAcofold algorithms respectively. We created a plot between rubber tree miRNAs and RTV1 ORFs by using Circos algorithm. In this study, we predicted eleven consensual rubber tree miRNAs. Among these miRNAs, hbr-miR398 was identified as the most effectual miRNA that may target the ORF1 gene of the RTV1 genome. The predicted data will be important in the development of rubber trees resistant to RTV1.

Fruit production is an important part of the gross domestic product for many countries around the world especially to those who have a strong focus on agriculture. However, long-term maintenance and yield stability of fruit production may be threatened by the ongoing climate change and its consequences like extended drought periods, heavy rain events, and floodings. Genome editing, with its progressive technological developments, offers opportunities to adapt relevant fruit plant species to new climatic conditions. Among modern genome editing techniques, CRISPR/Cas, in particular, has the potential to support breeding for those fruit plant species with extended breeding cycles, e.g., perennial fruits. In this review, we discuss CRISPR/Cas and other genome editing techniques in detail and how these techniques can be applied to support the breeding of fruit plant species for adaptation to changing climates. The chronological history of CRISPR/Cas9 systems, their associated computational tools, genomic data sources, transformation methods along with their delivery vehicles, quality improvement, environmental-stress resiliency, limitations, and future perspectives will also be discussed with respect to securing future global fruit production.

Nowadays, more than 180 million people believe that the Holy Qur'an was sent by the Almighty Allah through Prophet Muhammad in 610-632 A.D in Mecca and Medina. However, the word Mecca (Q: 48:24) is mentioned only once in the entire Holy Qur'an, which is not related to the birth of the Prophet or any worship. Conventional Islam is mostly based on the hearsay of some Islamic narrators published in the eighth and ninth centuries. To think deeply and conduct research on the verses of the Holy Quran has been mentioned (special urge) directly and indirectly by this Holy Scripture itself many times but it would not be wrong to say that there is no scholarship on the verses of the Quran based on the research method described in the Holy Quran until the present century. Therefore, this paper has been dared to carry out by combining the methods of research followed in the Holy Quran and the academically accepted research methodology. The analysis shows that the results of almost fourteen hundred years of mythological history of conventional Islamic narrators are opposites. First of all, the proper name of the Prophet revealed by the Holy Quran is Ahmed, but Muhammad is an adjective and there are many such names. Secondly, this prophet was not born in Mecca, KSA, nor in 570/571 A.D, but in the Beqaa Valley of Lebanon, between the third and fourth centuries. Thirdly, the Muslim Hajj (pilgrimage) of Mecca is celebrated entirely according to the Lahwal Hadith (idle tales) (Q: 31:6) in the language of the Holy Quran. Originally the place designated for pilgrimage was in the Beqaa Valley, Lebanon. This article will have a double influence on the Muslim world, that is, Islamic scholars will think again deeply and research new ways of scholarship of the Holy Quran, instead of based on the hearsay of idle tales (Lahwal Hadith). On the contrary, those who are stubborn Islamic narrators, since they have already rejected the Holy Quran, will not hesitate to violently attack the researchers and they will not be positively motivated by this paper. This article specifically urges Islamic scholars to conduct in-depth studies on the most important issues of Islam using the Holy Quranic research method.

In this unprecedented era of computer-supported and distance learning, it is critical to rethink the way students are supported through vital skills like self-regulation and peer collaboration. A variety of digital media has emerged, allowing learners autonomy while requiring the ability to effectively regulate different components of the educational process for long-term academic success. We reviewed collaboration, communication, and self-regulation in digital learning environments as part of online learning. We discussed how these abilities are reflected in highly cited content. High-impact factor studies were identified using advanced software Herzing Publish or Perish to retrieve highly cited research publications metrics. The search resulted in 272 records from 2010 to 2022, 192 duplicates were identified to remove and 48 JCR articles were shortlisted for review. We examined and reflected on sufficient connections to make firm judgments about correlations of concepts. The review identified prominent themes surfaced in the high impact factor academic publication e.g., digital learning environment, interaction, engagement, feedback, self-efficacy, motivation, meta-cognition, achievement, technology, blended learning, and orientation of ICT. Many studies support different features of SRL &amp; PCL through different tools, access to educators or feedback, encouragement, and through peers. However, all of them discuss the processes that students use to self-regulate learning in these situations. It is suggested to examine whether the effectiveness of certain SRL processes varies by online learning mode.

The rapid growth of the elderly population is a major global demographic and social issue. Unfortunately, there is a shortage of pension plans and social se-curity programmes for this population in developing countries which has severe consequences for their quality of life and planetary health (PH) wellbeing. In this article, we aimed to better understand the pension systems in Ghana, Pakistan, and Myanmar, by reviewing the official government materials (such as pension reports) and published literature. We observed several policy implementation gaps and inequity in pension schemes for older people, specifically for informal and private sector workers. Considering the size of formal versus informal economies and the level of development index of each country, we suggest a wide variety of options in pension policies, financing, designing cash benefits and pension payments to cover all older citizens. This article addresses an unmet need of the elderly people, their wider environmental and economic sustainability to ensure social justice and resource utilization. The governments of developing countries should embrace and establish unique, inclusive, and friendly policies encompassing the informal sector to warrant older adults’ functional and planetary wellbeing with dignity and honor.

Our environment has been impacted by man-made pollutants mainly industries make substantial use of synthetic dyes which exhibit cytotoxicity and have significant environmental consequences. Effective photocatalyst-based approaches for degrading synthetic dyes into less toxic chemical are of great interest. Synthesizing NPs using biological approaches, particularly plant-based approaches offer advantages, decreasing the risk of NPs losing biocompatibility during synthesis, cost-effectiveness, and eco-friendliness. In this study, we employed a green synthesis method to produce manganese oxide nanoparticles (MnO NPs) utilizing leaf extract from the Lathyrus Aphaca plant. The synthesized MnOx NPs were characterized through various techniques; X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), and UV–visible spectroscopy. XRD analysis showed distinct peaks, indicated the presence crystallographic planes within the MnO₂ nanoparticles, thus confirming their crystalline structure. SEM study highlighted closely packed configurations with average size of approximately ≥ 50-70 nm, with well-defined boundaries. EDX analysis showed the presence of elemental manganese (Mn) in the samples, with peaks corresponding to Mn detected at lower energy levels, predominantly represented by MnO. FTIR, showed the presence of the O-O stretching mode at a frequency of 719 cm^-1, the presence of MnO₆ oxides of manganese, and peak at 548 cm^-1 corresponded to the Mn-O stretching mode. Furthermore, the green-synthesized manganese oxide nanoparticles exhibited promising photocatalytic and adsorption capabilities against Methylene Blue (MB) dye, leading to approximately 93.21% degradation of MB when treated with the green-synthesized MnO nanoparticles derived from plant extract. This highlights the efficacy and potential of these nanoparticles in environmental remediation applications, particularly in the degradation of methylene blue contaminants.

The wettability of the oil-brine-rock systems is very challenging mainly for the carbonate reservoirs and it plays a significant role to enhance the oil recovery (EOR). Carbonate rocks are mad-up of complex lithology, hence these requires careful treatments in controlling their wetting behavior for enhanced oil recovery. Therefore, it is extremely important to modify their wettability from an oil-wet rock behavior to a water-wet so that the residual oil can be produced efficiently. Thus, the present study has examined the effectiveness of alumina nanofluid as well as a new chemical methyl blue to alter the wettability. The methyl blue is released on massive scale from various industries i.e. pharma, textile and food industry which is a key environmental concern which contaminates the water table. Hence the study, explores the effects of MB and alumina nanofluid on the wettability. The effect of nanofluids formulated via dispersing the alumina nanoparticles in aqueous solutions at various concentration (0. 0.05, 0.3, 0.50, 0.75 and 1.0 wt. %) were tested for wettability modification under different physio-thermal conditions. Subsequently, the wettability change was examined for the samples treated with different concentrations of MB (10, 15, 30, 50 and 100 mg/L) for 7-days at two different temperatures of (25 and 50 0C). The results showed that hydrophobicity of the SML carbonate rock has significantly reversed while treating with alumina nanofluids and MB. Thus, the wettability modification/reversal via treatment of MB and alumina nanofluid can be an effective mechanism to hydrogen injection and for EOR processes.

This paper investigates an innovative photovoltaic cell configuration, denoted as “Au/CuSCN/RbGeI3/CdTe/ZnO/TiO2/FTO", using SCAPS-1D simulation. The research focuses on optimizing device performance by analyzing key components, including ZnO as the electron transport layer (ETL), RbGeI3 as the perovskite absorber layer, CuSCN as the hole transport layer (HTL), and CdTe as the active buffer layer. A comparison is made with the standard “Au/CuSCN/CH3NH3SnI3/CdTe/ZnO/TiO2/FTO" configuration under dark and illuminated conditions. Through an in-depth investigation involving temperature effects, generation rate analysis, RbGeI3 absorber layer thickness, Nd level, and interface defect levels, an optimized design for a unit area is achieved. The proposed solar cell demonstrates outstanding performance metrics, including an open circuit voltage (Voc) of 0.94V, a short circuit current density (Jsc) of 34.52mA/cm2, a fill factor (FF) of 77.77%, and an energy conversion efficiency (η) of 25.40%. These values significantly outperform the reference models with energy conversion efficiencies of 10.11% and 21.09%. Real-world applicability is validated by implementing these optimized characteristics in a photovoltaic system for Pakistan’s geographical location using PVSyst software. The suggested solar cell achieves a remarkable performance ratio (PR) of 85.6%, surpassing the PR of the reference basic solar cell model at 83%. The findings of this research offer a promising and superior solar cell design, incorporating innovative materials and optimization techniques to achieve exceptional energy conversion efficiency and overall performance. This study’s outcomes have the potential to advance photovoltaic technology and contribute to sustainable energy solutions worldwide.

In this work, we report the engineering of a sub-70 nm nanocomposite of ZnO/Zn2TiO4 using a low-temperature solution-phase method. Titanium isopropoxide and zinc acetate were used as precursors, and isopropyl alcohol and water were used as solvents. The investigation focused on the growth of nanocomposites by varying the concentrations of precursors and surfactants, as well as their efficiency within different pH ranges. All three ZnO/Zn2TiO4 nanocomposites consist of hexagonal wurtzite ZnO and Zn2TiO4 structures in the three nanocomposites. The crystallite size in three ZnO/Zn2TiO4 nanocomposites, with a hexagonal wurtzite ZnO structure, were measured to be 62.67, 40.34, and 39.50 nm. The crystallite size values in three ZnO/Zn2TiO4 nanocomposites were 26.15 nm, 25.36 nm, and 21.24 nm, respectively, with Zn2TiO4. Morphological observations, conducted using FESEM, reveal the formation of three ZnO/Zn2TiO4 nanocomposites across the entire sample. These nanocomposites resemble dispersed cotton packets, with sizes ranging from 18 to 350 nm. Peaks in the range of 610-1250cm-1 are attributed to Ti-O bond formation and peak located at 1350-1450 cm-1 are attributed to Zn-O bond formation. Also, EDX spectrum reveals peaks for various sample components such as Ti, O and Zn. UV spectrums confirmed the formation of three nanocomposite of ZnO/Zn2TiO4 as showing two peaks for each sample. Photocatalytic investigation carried out by analyzing the UV-Visible absorption spectra of methylene blue dye on the surface of ZnO/Zn2TiO4 nanocomposites, dye degradation at various irradiation time intervals, dye degradation at varied catalyst concentrations and the influence of pH on dye-degradation. Furthermore, the said nanocomposites were used to degrade environmental pollutant (Methylene blue dye). Different sets of experiments were conducted under ambient conditions which show an excellent photo catalytic degradation efficiency.

Salmonella enterica serovar Typhi, is one of the major infection spreading from consuming contaminated food and water. The poor sanitation is one the major cause for successful infection. S. typhi is responsible for causing typhoid fever, which is a growing public health concern in developing countries. This bacterium has acquired antimicrobial resistance to many promising which is a growing health concern for community. This study is aim to elucidate the molecular complexity of flouroquinolone resistance in S. Typhi isolates (n=286). Genomic data was downloaded from NCBI and analysis was done by Resfinder, MLST, and Pointfinder. Genomic analysis unveils a complex resistance profile, featuring antimicrobial resistance genes (ARG) including blaCTXM-15, blaTEM-1D, catA1, dfrA7, qnrS1, sul1, sul2, and tetA(B). The investigation focuses on mutations in DNA gyrA, parC, and qnrS1 genes which plays an important role in quinolone resistance. Mutation analysis reveals mutations such as DNA gyrA_S83F, DNA gyrA_D87N, DNA gyrA_S83Y, DNA gyrB_S464F, parC_S80I, and parE_L416F with the presence of qnrS1 gene produces resistance against quinolones. The Docking studies was conducted by “Autodock vina” and visualize by “Discovery studio” which demonstrate that these mutations leads to ciprofloxacin resistance, indicating reduced binding affinity, and altered solvent accessibility which indicates the structural changes at mutation sites. This study provides crucial insights into the molecular mechanisms driving flouroquinolone resistance in S. typhi, guiding future strategies to combat antibiotic resistance. Further validation through experimental mutagenesis is recommended, for targeted therapeutic interventions against the mounting threat of antibiotic-resistant S. typhi.

Worldwide, hypoxia-related conditions, including cancer, COVID-19, and neuro-degenerative diseases, often lead to multi-organ failure and significant mortality. Oxygen, crucial for cellular function, becomes scarce as levels drop below 10 mmHg (<2% O2), triggering mitochondrial dysregulation and activating hypoxia-induced factors (HiFs). Herein, Oxygen nanoBubbles (OnB), an emerging versatile oxygen de-livery platform, implies to offer a novel approach to address hypoxia-related pathologies. This review explores OnB oxygen delivery strategies and systems, including diffusion, ultrasound, photodynamic, and pH-responsive nanobubbles. It delves into the nanoscale mechanisms of OnB, elucidating their role in mitochondrial metabolism (TFAM, PGC1alpha), hypoxic responses (HiF-1alpha), and their interplay in chronic pathologies including cancer and neurodegenerative disorders, amongst others. By understanding these dynamics and underlying mechanisms, this article aims to contribute to our accruing knowledge of OnB and the developing potential in ameliorating hypoxia- and metabolic stress-related conditions and fostering innovative therapies.

In recent years, numerous topologies of single phase and three phase Field Excited Flux-Switching Machine (FEFSM) have been developed for several applications. Comparative study of three types of single-phase low-priced Field Excited Flux-Switching Machine (FEFSM) is presented in this paper. Both the conventional 8S/4P sub-part rotor design and 6S/3P salient rotor design have an overlapped winding arrangements between armature coil and field excitation coil that depicts high copper losses as well as results in increased size of motor. Additionally, FEFSM with salient structure of the rotor have high flux strength in the stator-core that has much impact on high iron losses. Copper consumption and iron loss being a crucial proportion in total machine losses. Therefore a novel topology of single phase modular rotor field excited FSM with 8S/6P configuration is proposed, which enable non-overlap arrangement between armature coil and FEC winding that facilitates devaluation in the copper losses. The proposed modular rotor design acquires reduced iron losses as well as reduced active rotor mass comparatively to conventional rotor design. It is very persuasive to analyze the best range of speed for these rotors to avoid cracks and deformation, the maximum tensile strength (can be measured with principal stress in research) of the rotor analysis is conducted using JMAG. A deterministic optimization technique is used to enhance the performance of 8S/6P modular rotor design. The electromagnetic performance of conventional sub-part rotor design, F1-A3-3P design and proposed novel-modular rotor design are analyzed by 3D-Finite Element Analysis (3D-FEA), includes flux linkage, flux distribution, flux strength, back-EMF, cogging torque, torque characteristics, iron losses and efficiency.

Chronic eosinophilic pneumonia (CEP) is an idiopathic disorder characterized by an abnormal and marked accumulation of eosinophils in the interstitial and alveolar spaces of the lung. Idiopathic chronic eosinophilic pneumonia is reported to comprise anywhere from 0-2.5% of cases within the registries of interstitial lung disease. Diagnosis is based on the clinical constellation of symptoms, characteristic radiographic findings and peripheral blood or BAL eosinophilia, in the absence of infection or drug-induced eosinophilia. There is no consensus on the dose and duration of treatment, but most authors recommend initial doses of prednisone at 0.5–1 mg/kg/day with gradual tapering of the dose for total treatment duration of 6–12 months.

This article discusses the fabrication of pullulan/polyvinyl alcohol (PVA) and PVA blends as carrier polymers for drug delivery. This study utilized coaxial electrospinning to encapsulate doxorubicin (DOX), a common anticancer drug, within nanofibers, which helped mitigate the adverse effects of DOX on normal cells. The study also demonstrated that the coaxial electrospinning technique using PVA/pullulan cores was effective in inhibiting the attachment and proliferation of HeLa cells, a type of cervical cancer cell. The use of pullulan/PVA and PVA blends as carrier polymers in conjunction with coaxial electrospinning could provide a safe and effective drug delivery system for the treatment of cervical and other solid malignancies. The study concluded that nanofibers showed promising results in inhibiting the growth of HeLa cells, indicating their potential as safe and effective drug delivery systems for treating cervical cancer and other solid malignant tumors.

One of the rapidly developing research areas in the power system is the integration of distributed generation (DG) with the distribution system. The size and location of DG sources had a considerable impact on power system networks. Artificial intelligence (AI) techniques can be used to address multidimensional problems relating to DG size and location in distribution systems. Heuristic optimization offers a reliable and effective method for solving complicated real-world problems. This work focuses on a hybrid approach that combines the two heuristic optimization methods i.e., Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for the optimal siting and sizing of DG in distribution systems. This hybrid approach combines ideas from GA and PSO and generates individuals in a new generation using both PSO mechanisms and the procedures found in GA. An extensive performance analysis of the IEEE 14 busbar standard test system is conducted to demonstrate the viability of the suggested methodologies. In the designated locations, DG is placed, and the outcomes have been verified. The results indicated that the right placement of DG injection enhances the voltage profile and lowers the distributed system’s power losses. These techniques offer unique methods for determining the location of the DG unit, demonstrating the potential of such a computational techniques to reduce computing time and complexity while simultaneously reducing human errors associated with hit-and-trail methods.

The power function distribution is a flexible waiting time model that may provide better fit for some failure data. This paper presents the comparison of the maximum likelihood estimates and the Bayes estimates of two-parameter power function distribution. The Bayes estimates are obtained, using conjugate priors, under five loss functions consist of square error, precautionary, weighted, LINEX and DeGroot loss function. The Gibbs sampling algorithm is proposed to generate samples from posterior distributions and in result the Bayes estimates are computed. The comparison of the maximum likelihood estimates and the Bayes estimates are done through the root mean squared errors. One real-life data set is analyzed to illustrate the evaluation of proposed methods of estimation. Finally, results from the simulation are discussed to assess the performance behavior of the maximum likelihood estimates and the Bayes estimates.

Today, satellite imagery has made a major contribution to the reconstruction and spatial prediction of sensitive or complex areas such as Pendjari and W Transboundary Reserves which constitute biodiversity reservoirs and habitats for wildlife conservation. Despite the protection to which they are subject, they remain dependent on climatic hazards that can influence their stability. This study has applied remote sensing techniques, combined with climate records from the last thirty years, to analyze the past dynamics of land use and climate changes, to predict the future states of the vegetation cover of the two national parks in Benin, as well as their periphery. The methodology used remote sensing and GIS techniques that allowed the supervised classification of Landsat images of 1985, 2000 and 2015. Climatic data were combined in R software to identify the break periods for climatic parameters. Finally, the predictive vegetation cover for the year 2030 was made by combining vegetation and climate in the "Land Change Modeler" extension. Ten land use and land cover classes were obtained. These are the agglomerations, mosaics of fields and fallows, water bodies, dense forests, gallery forests, clear forests and wooded savannahs, swamp forests and shrubby wooded savannahs, saxicolous savannahs and bare ground. The natural vegetation decreased from 90.85% in 1985 to 83.54% in 2000 then to 79.56% in 2015, a decline of 11.39% over a 30-year period. The analysis of the climatic curves revealed the presence of break, meaning drought frequency. The predictive modeling revealed that land use units projected to 2030 are consistent with past trends, but with the continued expansion of fields and fallows (2%) at the expense of vegetation cover. This study will motivate many others in the field.

In this study, we first discover some new concept coordinated UD-convex mappings with fuzzy-number values. After that, we look into Hermite-Hadamard type inequalities via fuzzy-number-valued coordinated UD-convex fuzzy-number-valued mapping (coordinated UD-convex FNVM). In the case of coordinated UD-convex FNVM, novel conclusions are derived by making particular decisions in recently proven inequalities. Additionally, it is demonstrated that the recently discovered inequalities are expansions of comparable findings in the literature. It is important to note that the main outcomes are validated by nontrivial examples.

Pakistan being an agricultural country is raising 146.5 million commercial and domestic poultry birds which generate around 544,831 tons of waste. This waste finds its final disposal in agricultural land as soil fertilizer or disposal site amendment. The uncontrolled use of poultry litter for this purpose results in environmental impacts such as the emission of methane, a greenhouse gas. However, other options like thermochemical conversion of this waste can offer a better solution wherein poultry litter can be used as low-cost carbon sources for the synthesis of Carbon Nanotubes (CNTs). In this study, efforts have been made to utilize this cheap and plenty of available carbon source for synthesis of CNTs in the presence of Ni/Mo/MgO as a catalyst, through pyrolysis. The optimum mole ratio of catalyst (4:0.2:1) was found to yield more carbon product. Furthermore, process parameters such as temperature, time, polymer & catalyst weight were also optimized. The best possible process parameters that resulted (pyrolysis time (12 min), temperature (825◦C), and catalyst weight (100 mg) good yield of CNTs . The structure and morphology of produced nanotubes were confirmed through X-ray Diffractometer (X-RD) & Scanning Electron Microscopy (SEM). The environmental application of the nanotubes was tested in synthetic chromium solution in the lab using a batch experiment. Different experimental conditions (pH, adsorbent dosage and contact time) were optimized to enhance the adsorption of Cr (VI) by carbon nanotubes and UV-Visible spectrophotometer was used at 540nm to measure the absorbance of Cr (VI). Results show that up to 81.83% of Cr (VI) removal was achieved by using 8 mg of CNTs at pH 3 with 400 rpm at 180 min of contact time. Thus, it was concluded that poultry litter can be a useful source for the synthesis of CNTs and thereby removal of Cr (VI) from industrial tanneries wastewater.

Background and objectives: The hepatoprotective activity of vitamin E and C is evident due to their ability of modulating the antioxidant pathway. In this study, we have evaluated the effects of α-tocopherol and ascorbic acid on paracetamol induced liver damage with offsetting various levels of drug treatment following an in vivo experimental protocol on Wistar albino male rats. Materials and Methods: The level of lipid peroxidation as well as histological examination of liver tissues were observed among 50 Wistar albino male rats to evaluate hepatoprotective effect of α-tocopherol and ascorbic acid on hepatocytes. The experiment was divided into 5 groups (10 rats in each group)- Basal control group (Group-I, with propylene glycol), Paracetamol treated control group (Group –II), α-tocopherol pretreated & paracetamol treated group (Group –III), Ascorbic acid pretreated & paracetamol treated group (Group –IV) and Ascorbic acid pretreated & paracetamol treated group (Group –IV). Results: The mean (± SD) Malondialdehyde (MDA) concentration were significantly reduced in α-tocopherol pretreated and paracetamol treated group (P<0.001), Ascorbic acid pretreated and paracetamol treated group (P≤0.05) and combined α-tocopherol with ascorbic acid pretreated & paracetamol treated group (P<0.001). Statistically significant differences in histological findings of rat liver were observed in paracetamol treated control group (P<0.001), ascorbic acid pretreated and paracetamol treated group (P<0.001). The serum alanine aminotransferase (ALT) level was also significantly higher in paracetamol treated group (P<0.001), α-tocopherol pretreated plus paracetamol treated group (P≤0.05) and in ascorbic acid pretreated plus paracetamol treated group (P<0.001). Conclusion: The combined pretreatment of α-tocopherol & ascorbic acid have better hepatoprotective effects than α-tocopherol or ascorbic acid alone against paracetamol induced liver damage. The decrement of free radicals produced by vitamin E could be a better hepatoprotective antioxidant than vitamin C in paracetamol induced toxicity.

Arsenic (As) is the most poisonous metalloid with negative effects on the plant and ecosystem. In the current study, observed that iron oxide nanoparticles (NPs) affected the molecular features of rice under arsenic (As) stress. The result showed that 1-D electrophoresis (SDS-PAGE) demonstrated variable expression of protein profiles. The polypeptide pattern was altered in the SDS-PAGE under arsenic stress. The findings also showed that low molecular weight polypeptides (MTs) expression was maximum under arsenic stress, while iron oxide NPs decreased the expression of these polypeptides and reduced the arsenic stress. RT-PCR was used to analyse the expression of the MYB transcriptional factor, WRKY, and OsGF14 genes in the rice plant. The results showed that these genes were up-regulated in response to arsenic stress, iron oxide NPs reduced arsenic stress, and Myeloblastosis (MYB), WRKY, and OsGF14 genes had very low expression levels. Our work showed that iron oxide nanoparticles (NPs) not only reduced the effects of arsenic stress but also decreased the expression of stress-related genes and metallothioneins (MTs).

Compressive residual stresses in thin films can inhibit crack propagation under normal or sliding contact loading, with associated enhancement of the coating apparent toughness, load bearing capacity and wear resistance. This study investigates the influence of residual stress distributions on the thin film/substrate adhesion using a nanoindenter coupled with scanning electron microscope (SEM) investigations of indentation induced failure modes. Reactive and un-reactive magnetron sputtering with ion plating was used to coat a (100) silicon substrate with aluminum nitride (AlN) with and without an aluminum (Al) adhesion layer. The presence of an Al bond layer gives additional interfacial tensile stress because of the difference in thermal expansion coefficient. Additionally, a different magnitude of residual stresses in the AlN coating was achieved by changing the applied bias voltage onto the substrate. Wafer curvature method and incremental focused ion beam (FIB) milling, combined with high-resolution in situ scanning electron microscopy (SEM) imaging and full field strain analysis by digital image correlation (DIC), were used to measure the average and in-depth stress residual stress distribution in the produced coatings. The adhesion energy was then quantified by using a nanoindentation based model. Results demonstrate that the additional tensile residual stress in the aluminum adhesion layer decrease significantly the coating adhesion, even in presence of a higher compressive stress state in the AlN top-layer. Therefore, the coatings without Al-layer showed better adhesion because of a more homogeneous compressive residual stress in comparison with the coating having Al layer, even though both groups of coatings are produced under same bias voltage. Results are discussed, and some general suggestions are made on the correlation between coating/substrate property combination and the adhesion energy of multilayer stacks. The results suggested that Al bond-layer and inhomogeneous residual stresses affected the adhesion of AlN negatively to a substrate like silicon.

Depth maps produced by LiDAR based approaches are sparse. Even high-end LiDAR sensors produce highly sparse depth maps, which are also noisy around the object boundaries. Depth completion is the task of generating a dense depth map from a sparse depth map. While the traditional approaches focus on directly completing this sparsity from the sparse depth maps, modern techniques use RGB images as a guidance tool to resolve this problem. Whilst many others rely on affinity matrices for depth completion. Based on these approaches, we have sub-divided the literature into two major categories; traditional approaches and backbone-based approaches. The latter is further sub-divided into two-branch, and spatial propagation approaches. The two-branch approaches still have a sub-category named guided-kernel approaches. In this paper, for the first time ever we present a comprehensive survey of depth completion methods. We present a novel taxonomy of depth completion approaches, review and detail different state-of-the art techniques within each category for depth completion of LiDAR data, and provide quantitative results for the approaches on KITTI and NYUv2 depth completion benchmark datasets.

Human activity recognition (HAR) using wearable sensors is gaining popularity in the healthcare domain, enabling continuous monitoring and timely interventions. The conventional HAR systems are centralised and need data sharing with a server for processing and model training. However, this data sharing leads to various challenges, such as privacy concerns, increased communication and storage costs, inefficient computational algorithms, data scarcity due to unwillingness to share, and difficulty achieving high accuracy and personalised models simultaneously. To overcome these challenges, this paper introduces a privacy and energy-aware federated learning (FL) framework for model training without data sharing. The proposed scheme incorporates spiking neural networks (SNNs), which are particularly suited for resource-constrained devices due to their event-driven information processing. The key idea is to synergise the strengths of SNNs and long short-term memory (LSTM) to create a hybrid model for robust HAR. The proposed hybrid spiking LSTM (S-LSTM) model uses the LSTM as an input layer to capture temporal dependencies efficiently, followed by spiking layers that replace the typical activation using leaky integrate-and-fire neurons. We employ the combination of surrogate gradient learning and backpropagation through time (BPTT) to update the weights of SNN layers in a supervised manner. The performance of the proposed model is evaluated using two publicly available datasets for both indoor and outdoor scenarios. The results show that the proposed S-LSTM performs much better than spike convolutional neural networks (S-CNN) and simple CNN, achieving the accuracy of 97% and 87% for indoor and outdoor datasets, respectively. Personalisation, also known as fine-tuning the global model using local data, is crucial in HAR. It allows the model to adapt to individual behaviour and preferences, making predictions more accurate. The results also show that personalisation improves the performance of participants up to 9% on average. Additionally, analysis with 50% random client participation reduces communication costs by 50% with minimal impact on accuracy.

Conventional plant breeding methods exploit already existing genomic variation in plants to develop a variety in 8 to 10 years, which can decrease the genetic variability of the plant’s genome. The ever-increasing food demand for cereals crops cannot be met by traditional breeding methods. In order to increase food production in less time, there is a dire need to improve breeding methods. Several conventional and molecular breeding methods are being used to improve the crops traits. Molecular researchers have developed new genome editing tools like CRISPR/Cas9, CRISPR/Cpf1, prime editing, base editing, dcas9 epigenetic modification, and several other transgene-free genomes editing approaches. These genome editing tools can improve the desired traits precisely and efficiently. Moreover, a newly developed breeding method “Speed Breeding” has revolutionized the agriculture by shortening the crop cycle. It can produce 5-6 generations of cereals in a year. In this review, we have summarized all these conventional and molecular breeding approaches to improve cereal crops.

Introduction: Child stunting remains a public health concern. It is characterized as poor cognitive and physical development in children due to inadequate nutrition during the first 1,000 days of life. Across South Asia, Pakistan has the second-highest prevalence of stunting. This study has assessed the most recent nationally representative data, the National Nutrition Survey (NNS) 2018, to identify the stunting prevalence and determinants among Pakistani children under five. Methods: The NNS 2018, a cross-sectional household-level survey, was used to conduct a secondary analysis. Data on malnutrition, dietary practices, and food insecurity was used to identify the prevalence of stunting among children under five years by demographic, socioeconomic, and geographic characteristics. The prevalence of stunting was calculated using the World Health Organization (WHO) height for age z-score references. Univariate and multivariable logistic regressions were conducted to identify factors associated with child stunting. Results: Analysis showed that out % of 52,602 children under five, 40.0% were found stunted. Male children living in rural areas were more susceptible to stunting. Furthermore, stunting was more prevalent among children whose mothers had no education, were between 20 and 34, and were employed. In the multivariable logistic regression, male children (AOR=1.08, 95% CI[1.04-1.14], P<0.001) from rural areas (AOR=1.07, 95% CI [1.01-1.14], P=0.014), with the presence of diarrhea in the last two weeks (AOR=1.15, 95% CI [1.06-1.25], P<0.001), with mothers who have no education (AOR=1.57, 95% CI [1.42-1.73], P<0.001) or lower levels of education (Primary: AOR=1.35, 95% CI [1.21-1.51], P<0.001; Middle: AOR=1.29, 95% CI [1.15-1.45], P<0.001) had higher odds of stunting. Younger children aged <6 months (AOR=0.53, 95% CI [0.48-0.58], P<0.001) and 6-23 months (AOR=0.89, 95% CI [0.84-0.94], P<0.001), with mothers aged 35-49 years (AOR=0.78, 95% CI [0.66-0.92], P=0.003) had lower odds of stunting. At the household level, the odds of child stunting were higher in the poorest households (AOR=1.64, 95% CI [1.46-1.83], P<0.001), with ≥7 members (AOR=1.09, 95% CI [1.04-1.15], P<0.001), with no access to improved sanitation facilities (AOR=1.14, 95% CI [1.06-1.22], P<0.001) and experiencing severe food insecurity (AOR=1.07, 95% CI [1.01-1.14], P=0.02). Conclusion: Child stunting in Pakistan is strongly associated with various factors, including gender, age, diarrhea, residence, maternal age and education, household size, food and wealth status, and access to sanitation. To address this, interventions must be introduced to make locally available food and nutritious supplements more affordable, improve access to safe water and sanitation, and promote female education for long-term reduction in stunting rates.

Keywords: Electrical power systems, Support vector machines, Random Forest, Machine learning, Wavelet transform, Transmission lines fault, Electrical power quality, Short circuit, Classification of faults, Localization of faults, Decision trees, Ensemble learning, K-nearest neighbors.

Optical switching is an essential part of photonic integrated circuits and the focus of research at the moment. In this research, an optical switch design working on the phenomenon of the guided-mode resonances in 3D photonic crystals-based structure is reported. The optical-switching mechanism is studied in a dielectric slab-waveguide-based structure operating in the near-infrared range in a telecom window of 1.55 µm. The mechanism is investigated by interference of two signals, i.e., the data signal and the control signal. The data signal is coupled into the optical structure and filtered utilizing guided-mode resonance, whereas, the control signal is index guided in the optical structure. The amplification or de-amplification of the data signal is controlled by tuning the spectral properties of the optical sources and structural parameters of the device. The parameters are optimized first using a single-cell model with periodic boundary conditions and later in a finite 3D-FDTD model of the device. The numerical design is computed in an open-source Finite Difference Time Domain simulation platform. Optical amplification in the range of 13.75 % is achieved in the data signal with a decrease in the linewidth up to 0.0079 µm and a quality factor of 114.58. The proposed device presents great potential in the field of photonic integrated circuits, biomedical technology, and programmable photonics.

Higher order femtoscopy measured to examine the heat exchanger characterization of the fluid debris produced in the collisions and investigated a remarkable suppression in the bosons interferences measurement. The analogous suppression can be analyzed to explore the coherence of boson thermal particle production sources at unprecedented energies. We illustrate the particles emissions from radiated sources with statistical coherence which induce the thermal particles interferences to probe the peculiarity of the heated sources as well as the distinctions about the heat exchangers in the collisions at higher temperature. We perspicacious that the bosons seem to the pertinent aspirant of heat exchanger, and the normalized three particles correlators evaluate the existence of such hybrid phases significantly. The key point of this research is that we analyze the three particles correlations with their normalized correlations by difference equations to determine the characteristics of heat exchanger and its applications. With such distinctive and efficient approach, we observe a significant difference in the correlation functions at higher temperature and momenta regimes.

The governance of public sector infrastructure projects became an important topic of interest in the project, programme and portfolio management literature during the last decade. Today, it is becoming a central focus for policymakers seeking to ensure success in selecting, designing and implementing government-sponsored programme of multi-projects. Due to the multiple underlying risks and complexities, the governance of infrastructure programme constitutes a critical element in strategic planning in developing countries. This paper has analyzed infrastructure development programme and revealed shortcomings in the areas of appraisal, decision-making, quality assurance and stakeholder management. Approaches to remedy these shortcomings have been proposed.

The present study was designed to check the prevalence of cancer in residents of District Bannu, Khyber Pakhtunkhwa. Patients' data were collected from three consulted Institutes during the year 2005-09. The data was analyzed for different parameters; year-wise, age-wise prevalence, gender-wise, occupation wise and marital status wise prevalence, addiction status, type of cancer, site affected, diagnostic tests performed and treatment of cancer. Results revealed that during 2005, a high number of cancer patients were present. A total of 172 patients were in the age group of 51-60 years, while only 11 patients were in the age group of 80 plus years. Female patients were more as compared to males. Married people were highly affected than unmarried. Patients addicted to smoking were highly affected than non-addicted patients. Malignancy was high in patients as compared to benign cancer. The most affected site was the blood system. The most affected people occupation wise were housewives followed by the farmer. A biopsy was mostly conducted for the diagnosis of cancer. Most of the patients were treated with chemotherapeutic agents. It has been revealed that the number of cancer patients decreased per annum. Moreover, the study should be conducted on the general population of Bannu as well as of the Khyber Pakhtunkhwa to sort out the total number of patients. The government should launch preventive, diagnostic programs so that prevalence may be minimized.

A significant attention has been made to the accurate detection of diabetes which is a big challenge for the research community to develop a diagnosis system to detect diabetes in a successful way in the IoT e-healthcare environment. Internet of Things (IOT) has emerging role in healthcare services which delivers a system to analyze the medical data for diagnosis of diseases applied data mining methods. The existing diagnosis systems have some drawbacks, such as high computation time, and low prediction accuracy. To handle these issues, we have proposed a IOT based diagnosis system using machine learning methods, such as preprocessing of data, feature selection, and classification for the detection of diabetes disease in e- healthcare environment. Model validation and performance evaluation metrics have been used to check the validity of the proposed system. We have proposed a filter method based on the Decision Tree (Iterative Dichotomiser 3) algorithm for highly important feature selection. Two ensemble learning Decision Tree algorithms, such as Ada Boost and Random Forest are also used for feature selection and compared the classifier performance with wrapper based feature selection algorithms also. Machine learning classifier Decision Tree has been used for the classification of healthy and diabetic subjects. The experimental results show that the Decision Tree algorithm based on selected features improves the classification performance of the predictive model and achieved optimal accuracy. Additionally, the proposed system performance is high as compared to the previous state-of-the-art methods. High performance of the proposed method is due to the different combinations of selected features set and GL, DPF, and BMI are more significantly important features in the dataset for prediction of diabetes disease. Furthermore, the experimental results statistical analysis demonstrated that the proposed method would be effectively detected diabetes disease and can easily be deployed in IOT wireless sensor technologies based e-healthcare environment.

The emergence of unmanned aerial vehicles (UAVs) raised multiple concerns, given their potential for malicious misuse in unlawful acts Vision-based counter-UAV applications offer a reliable solution compared to acoustic and radio frequency-based solutions because of their high detection accuracy in diverse weather conditions. The existing solutions work well on trained datasets, but their accuracy is relatively low for real-time detection. In this paper, we model deep learning-empowered solutions to improve the multi-class UAV's classification performance using single-shot object detection algorithms YOLOv5 and YOLOv7. The transfer learning is employed for performance improvement and rapid training with improved results. We customized a multi-class dataset containing multi-rotor, fixed-wing, and single-rotor UAVs in challenging weather conditions. Experiments show that the integration of transfer learning has achieved good results, with an overall best average-classification precision of 94\%, an average recall of 93.1\%, a mAP$@$0.5 average of 95.3\%, and an average F1 score of 92.33\%. The dataset and code are available as an open source: https://github.com/ZeeshanKaleem/YOLOV5-Large-vs-YOLOV7.git

Aim of this study is to gather information regarding the sustainability development goals from the public as well as the organizations of Pakistan. A sample of 500 respondents each from five main cities including employs and general public is selected for their opinion regarding sustainability development goal. The level of awareness as well as level of commitment towards the fulfilment of Sustainable Development Goals varies across the cities of Pakistan due to difference in literacy level. The commitment to achieve Sustainable Development Goals of the organizations across the selected cities varies according to the nature of the business, volume and the membership with the United Nations. This study provides the policy makers with the ground level data regarding the awareness and commitment of Pakistan based organizations and public towards SDGs fulfilment. A glance towards the attitudes of the people towards the subject matter could also be seen through this study. This a comprehensive study conducted at federal and provincial level of Pakistan which has yielded ground realities towards the implementation of SDGs. The results could be used for policy making and planning at national level and also serve as bench mark for other countries.

Validation and verification are the critical requirements in the knowledge acquisition method for the clinical decision support system (CDSS). After acquiring the medical knowledge from diverse sources, the rigorous validation and formal verification process are required before creating the final knowledge model. Previously, we have proposed a hybrid knowledge acquisition method for acquiring medical knowledge from clinical practice guidelines (CPGs) and patient data in the Smart CDSS for treatment of oral cavity cancer. The final knowledge model was created by combining knowledge models obtained from CPGs and patient data after passing through a rigorous validation process. However, detailed analysis shows that due to lack of formal verification process, it involves various inconsistencies in knowledge relevant to the formalism of knowledge, conformance to CPGs, quality of knowledge, and complexities of knowledge acquisition artifacts. Therefore, it is required to enhance a hybrid knowledge acquisition method that thwarts the inconsistencies using formal verification. This paper presents the verification process using the Z formal method and its outcome as an enhanced acquisition method – known as the refined knowledge acquisition (ReKA) method. The ReKA method adopted verification method and explored the mechanism of theorem proving using the Z notation. It enables to identify inconsistencies in the validation process used for hybrid knowledge acquisition. Additionally, it refines the hybrid knowledge acquisition method by discovering the missing steps in the current validation process at the acquisition stage. Consequently, ReKA adds a set of nine additional criteria to be used to have a final valid refined clinical knowledge model. The criteria ensure the validity of final knowledge model concerning formalism of knowledge, conformance to GPGs, quality of the knowledge, usage of stringent conditions and treatment plans, and inconsistencies possibly resulting from the complexities. Evaluation, using four medical knowledge acquisition scenarios, shows that newly added knowledge in CDSS due to the addition of criteria by ReKA method always produces a valid knowledge model. The final knowledge model was also evaluated with 1229 oral cavity patient cases, which outperformed with an accuracy of 72.57\% compared to a similar approach with an accuracy of 69.7\%. Furthermore, ReKA method identified a set of decision paths (about 47.8%) in the existing approach, which results in a final knowledge model with low quality, non-conformed from standard CPGs. In conclusion, ReKA is formally proved method which always yields valid knowledge model having high quality, supporting local practices, and influenced from standard guidelines.

Prosthetics have come a long way since their inception, and recent advancements in materials science have enabled the development of prosthetic devices with improved functionality and comfort. One promising area of research is the use of auxetic metamaterials in prosthetics. Auxetic materials have a negative Poisson's ratio, which means that they expand laterally when stretched, unlike conventional materials, which contract laterally. This unique property allows for the creation of prosthetic devices that can better conform to the contours of the human body and provide a more natural feel. In this review article, we provide an overview of the current state of the art in the development of prosthetics using auxetic metamaterials. We discuss the mechanical properties of these materials, including their negative Poisson's ratio and other properties that make them suitable for use in prosthetic devices. We also explore the limitations that currently exist in implementing these materials in prosthetic devices, including challenges in manufacturing and cost. Despite these challenges, the future prospects for the development of prosthetic devices using auxetic metamaterials are promising. Continued research and development in this field could lead to the creation of more comfortable, functional, and natural-feeling prosthetic devices. Overall, the use of auxetic metamaterials in prosthetics represents a promising area of research with the potential to improve the lives of millions of people around the world who rely on prosthetic devices.

Coronavirus that is also known as COVID-19 disease is produced by SARSCoV-2. This causative agent is highly contagious and can cause potentially fatal pneumonia worldwide with serious public health concerns. In the beginning among infected individuals, most of them were those who were mainly shown to the wet animal market in a big city of China known as Wuhan. So, it was suggested that this was almost certainly the zoonotic source of COVID-19illness. The transitional source of origin and their mode of transmission to humans were not known obviously. Conversely, from human to human rapidly transformation have been confirmed generally. Currently, there is no availability of FDA approved clinically antiviral drugs and/or vaccines to be used against the COVID-19. Afterward, SARS-CoV and MERS-CoV, the occurrence of SARS-CoV-2 has been manifested as the third sketch of an enormously pathogenic coronavirus into human population globally. In this review, we provide a brief overview of the history of COVID-19 in Pakistan up-to 18^th weeks after beginning, current situation, epidemiology, and its impact on the human population. Moreover, we focused on physiological variation during the incubation period, genome analysis of SARS-CoV2, supportive treatment approaches, and safety measures in the Pakistani population, which may be supportive for combating the risk of COVID-19 epidemic. We also reviewed the future approaches for the development of therapeutic interventions and vaccines to cope with the COVID-19 epidemic.

The extensive use of engineered nanoparticles (ENPs) such as zinc oxide nanoparticles (ZnO NPs) in various commercial fields has spurred significant concern about its possible toxicological effects of ZnO NPs on human health and eco-system. Therefore, it is substantial to understand the aggregation phenomena which could attenuate this effect. This data article provides information on aggregation of ZnO NPs under the influence of various parameters of water chemistry. Moreover, Taguchi orthogonal array L27(313) design matrix was used to evaluate the effect of multiple parameters in aqueous solution. The data were obtained from single beam UV-Vis spectrophotometer (Optizen 2120 UV, Mecasys, Korea) using Optizenview 4.2.5 PC interference software, Fourier transform infrared spectrometer (FT/IR-4700, spectroscopy, JASCO Analytical Instruments, Easton, USA) and particle electrophoresis (NanoZS, Zetasizer, Malvern Instruments Ltd, Worcestershire, UK). The dataset draws attention on dominant parameters influencing aggregation of ZnO NPs in water. The analysis of variance (ANOVA) data revealed that electrolyte concentration, type and natural organic matter (NOM) concentration were the most significant parameters. Furthermore, FT-IR data presents a possible mechanism of ZnO NPs stabilization in the presence of different NOM. This data will be helpful for the development of environmental risk assessment strategies and prediction of fate and mobility of other ENPs in the aquatic environment.

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

Agriculture sector is the backbone of developing countries for their economy. Growing world’s population is putting more pressure on agriculture sector and there is a need to develop new technology to address the crises of food safety and food shortage. Today’s agriculture has been entered in a new era where nanotechnology works as a technological advancement regarding entire agriculture crops, and food sector revolution, even though, it has prodigious applications in food production, food processing, food packaging, food storage and economic growth of industries. Moreover, nanotechnology is the best solution to solve problems related to better food and agriculture. Likewise, biotechnology, nanotechnology also raised high concerns upon safety on biodiversity, health and environment. Nanotechnology is providing efficient alternatives to increase the crop production by managing the insect/pests in agriculture in an eco-friendly manner. It also promotes plant efficiency to absorb nutrients. However, the concerns are very high regarding regulation, safety and approval of nanotechnology products by risk assessment authorities. The suggested review includes stupendous applications of nanotechnology in food and agriculture sector along with its prospective merits and associated risks.

We introduce the notion of generalized contraction on dualistic partial metric spaces. A fixed point theorem for mappings satisfying above mentioned contraction is obtained. Some consequences of our result are obtained. We construct an example to demonstrate the effectiveness of our result among the corresponding results in partial metric spaces. Our results provide substantial generalizations and improvements of several well known results existing in the comparable literature. We discuss an application of our fixed point results to show the existence of solution of functional equations.

In recent years, the digital economy has played an increasingly important role in enhancing productivity, fostering growth, and facilitating the emergence of digital banking. With the widespread adoption of digital financial services for financial inclusion, the banking sector is experiencing a demand for digital transformation. It is important to note that despite the many advantages of this change, it also disrupts the familiar banking experience that customers have grown to expect, as well as introducing potential risks to maintaining customer protection at previous levels. Many critics have raised concerns regarding customer protection and potential exposure to various risks that may arise from digital financial services, which may result in both financial and non-financial losses. These risks can impact customer retention as dissatisfied customers may switch to alternative service providers. Additionally, reputation can be affected since merely offering digital financial services may not sufficiently safeguard customers. To remain competitive, financial institutions must deliver a secure experience that aligns with customer expectations while considering economic factors and societal needs. This is why it is essential to comprehend the severity of the risk factors that influence the protection of customers in the realm of digitalized banking services and products. In this study, five factors have been identified that influence customer protection when using digital financial services in Pakistan. Based on the analysis conducted using SmartPLS, it appears that all the factors proposed in this study have a significant and positive impact on the protection of customers. In particular, the information provided remains of paramount importance when it comes to determining the level of protection that a customer is entitled to within digital financial services, followed by responsiveness, privacy, authentication, and encryption mechanisms. Due to these findings, the implementation of enhanced information security management principles becomes imperative for the development and progress of the Pakistani digital banking industry.

Retinitis pigmentosa (RP) clinically and genetically heterogeneous group of inherited retinal disorders (IRD) that result in retinal degeneration. This study aimed to identify the genetic findings of patients with autosomal recessive retinitis pigmentosa (arRP). Whole exome sequencing (WES) was performed in two unrelated Pakistani families underlying arRP. Data analysis and mutation screening was performed for all the known RP genes following bi-directional Sanger sequencing to determine whether any of the candidate variants co-segregated with the disease phenotype in the families. WES data analysis revealed a novel homozygous missense variant (c.1274T>C) in the in Tubby like Protein 1 (TULP1 NM_003322.6) gene in family 1 and a novel homozygous frameshift variant (c.351delC) in the retinoid isomerohydrolase 65 (RPE65 NM_000329.3) gene in family 2. The identified variants perfectly co-segregated with the disease phenotype within the families. Our results strongly suggest that mutations in TULP1 and RPE65 are responsible for the retinal phenotype in the affected individuals. These mutations will increase the mutation spectrum of these genes; furthermore, it will enhance our knowledge and understanding of the underlying molecular mechanisms of retinitis pigmentosa.

The antibiotic residues and pathogenic resistance against the drug are very common in poultry due to usage of antibiotics in their feed. It is the need of the time to use natural feed additives as effective alternatives instead of synthetic antibiotic. The aim of this study was to investigate the immune response of Nigella sativa and Curcuma longa in broilers under biological stress against Pasteurella multocida. The total 100, one-day old chicks were divided into 5 groups. The Groups 1 and 2 were served as control negative and control positive. Both control groups were receiving simple diet without any natural feed additives but infection was given in Group 2 at day 28 with the dose of 5.14×107 CFU by IV. Groups 3A & 3B were offered 2% seed powder of Nigella sativa, Groups 4A & 4B were offered Curcuma longa 1% in powdered form and Group 5A & 5B were offered both Curcuma longa 1% & Nigella sativa 2% in feed from day 1 and groups 3B, 4B and 5B were challenged with Pasteurella multocida. The Haemagglutination inhibition titter against Newcastle Disease Virus (NDV), feed conversion ratio, mortality, gross and histopathology were studied. The results of this study revealed that haemagglutination inhibition titers against NDV were highly significant (P< 0.05) in treated groups, highest titers (3A 6.8, 3B 6.4 and 5A 7.2) were obtained from treated Group. The feed conversion ratio (FCR) of Nigella sativa + Curcuma longa treated Groups (5A 1.57 and 3A 1.76) were higher as compared to other non-treated groups. The gross and histopathological changes were much severe in control positive, but less changes were seen in treated groups. Therefore, we recommend that natural feed additives; black cumin (Nigella sativa) and turmeric (Curcuma longa) act as immune enhancer in broilers against Pasteurella multocida.