This article discusses Islamic Banking System and its mode of leasing in the light of the objectives of Shari＇ah. It explores that the objectives behind the introduction of Islamic finance and banking system were the...This article discusses Islamic Banking System and its mode of leasing in the light of the objectives of Shari＇ah. It explores that the objectives behind the introduction of Islamic finance and banking system were the elimination of capitalist banking interest, exploitation of poor segment of the society and the establishment of an economic system which may lead to sustain a balance economic order and social justice. In this context, it intends to analyze the mode of leasing provided by Islamic Banking system in the light of the objectives of Shari＇ah and discloses that although Islamic Banking system is based on the principle of mudarbah, musharkah and Ijarah and deals with the customers in that context, yet apparently, the effects of these transactions are not much different from capitalist modes due to same consequences and effects of these transactions. It thus, provides a comparative analysis of the issue, i.e., mode of leasing at both Islamic and capitalist Banks. It argues that a common man can not avail Islamic financing/leasing if he lacks financial resources. If a poor person tries to purchase something by way of ijarah through Islamic Banking finance, he does not find any difference in the payment of the total cost between capitalist mode of leasing and Islamic mode of ijarah. Hence, this article concludes that although Islamic financing achieved a remarkable development among the Muslims, yet there is a need to revise the policy and system of Islamic financing in the light of the objectives of Shari＇ah. It also concludes that the mode of leasing provided at Islamic Banks does not accomplish the objectives of its establishment which is public interest. At present, this system is unable to assist the poor segment of the society or to provide ease to them.展开更多
The specific concepts of Islamic capital market are based on transparency, accountability, and no asymmetric information. A capital market is said to be efficient with respect to an information item if the prices of s...The specific concepts of Islamic capital market are based on transparency, accountability, and no asymmetric information. A capital market is said to be efficient with respect to an information item if the prices of securities fully impound the return implication of that item. This study has two main objectives. Firstly, for testing the efficiency of Islamic capital market which focuses on Jakarta Islamic Index （JII）. Secondly, by this research finding the regulator can make a good solution to create the real Islamic capital market. This study concludes that the Islamic capital market is not efficient in information. This is proved by test, where the result for both mean adjusted model and market adjusted model shows not significant, which means that the stock price that occurred has not been able to reflect a strong relationship with the real conditions that exist within the company. The second conclusion is the magnitude of abnormal return suggests that the market still has asymmetric information that will cause the occurrence of abnormal return. This is very unfortunate because Islamic capital market should be efficient in reflecting information transparency that could create a fair price in accordance with the real condition of the company＇s stock issuance.展开更多
This letter evaluates Shahid et al’s study in 2025 on the rising hepatitis A virus(HAV)among adults in Pakistan,highlighting a shift in the virus’s epidemiology.Once primarily a childhood disease in low-income regio...This letter evaluates Shahid et al’s study in 2025 on the rising hepatitis A virus(HAV)among adults in Pakistan,highlighting a shift in the virus’s epidemiology.Once primarily a childhood disease in low-income regions,HAV is now increasingly affecting adults,also seen globally due to improved sanitation.The study highlights public health challenges from adult HAV infections,which can lead to complications like coagulopathy and acute liver failure.It also has limitations,including being a single-center study and lacking seroprevalence and socioeconomic data,indicating the need for further research.This letter calls for urgent public health measures to extend adult vaccination programs and improve sanitation to address the increasing HAV infection in adult populations.展开更多
Public-and private-sector organizations have adopted artificial intelligence(AI)to meet the challenges of the Fourth Industrial Revolution.The successful implementation of AI is a challenging task,and previous researc...Public-and private-sector organizations have adopted artificial intelligence(AI)to meet the challenges of the Fourth Industrial Revolution.The successful implementation of AI is a challenging task,and previous research has advocated the need to explore key readiness before AI implementation.The objective of this study is to identify the AI readiness factors explored by different authors in past research.To achieve this,we conducted a rigorous literature review.The approach used in the systematic literature review is also discussed.A rigorous review of 52 studies from various journals and databases(Science Direct,Springer Link,Institute of Electrical and Electronics Engineers,Emerald,and Google Scholar)identified 23 AI readiness factors.The key factors identified were mainly related to organizational information technology infrastructure,top management support,resource availability,collaborative culture,organizational size,organizational capability,compatibility,data quality,and financial budget,whereas the other 15 were potential factors in AI readiness.All of these factors should be considered before the implementation of AI in any organization.The findings also reflect a high failure rate,including AI readiness factors,which are intended to facilitate AI adoption in organizations and reduce the frequency of failures.These factors will aid management in developing an effective strategy for AI implementation in organizations.展开更多
This review provides a comprehensive overview of natural rubber(NR)composites,focusing on their properties,compounding aspects,and renewable practices involving natural fibre reinforcement.The properties of NR are inf...This review provides a comprehensive overview of natural rubber(NR)composites,focusing on their properties,compounding aspects,and renewable practices involving natural fibre reinforcement.The properties of NR are influenced by the compounding process,which incorporates ingredients such as elastomers,vulcanizing agents,accelerators,activators,and fillers like carbon black and silica.While effective in enhancing properties,these fillers lack biodegradability,prompting the exploration of sustainable alternatives.The potential of natural fibres as renewable reinforcements in NR composites is thoroughly covered in this review,highlighting both their advan-tages,such as improved sustainability,and the challenges they present,such as compatibility with the rubber matrix.Surface treatment methods,including alkali and silane treatments,are also discussed as solutions to improve fibre-matrix adhesion and mitigate these challenges.Additionally,the review highlights the potential of oil palm empty fruit bunch(EFB)fibres as a natural fibre reinforcement.The abundance of EFB fibres and their alignment with sustainable practices make them promising substitutes for conventional fillers,contributing to valuable knowledge and supporting the broader move towards renewable reinforcement to improve sustain-ability without compromising the key properties of rubber composites.展开更多
The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for centuries.The aging process alters the brain structure that affects functions a...The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for centuries.The aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as Alzheimer's disease.Beyond these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging brain.Understanding these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect cognition.This review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of Alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly Alzheimer's disease.展开更多
Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2....Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2.5 concentrations is essential for mitigating health risks;however,the inherent nonlinearity and dynamic variability of air quality data present significant challenges.This study conducts a systematic evaluation of deep learning algorithms including Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and the hybrid CNN-LSTM as well as statistical models,AutoRegressive Integrated Moving Average(ARIMA)and Maximum Likelihood Estimation(MLE)for hourly PM2.5 forecasting.Model performance is quantified using Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and the Coefficient of Determination(R^(2))metrics.The comparative analysis identifies optimal predictive approaches for air quality modeling,emphasizing computational efficiency and accuracy.Additionally,CNN classification performance is evaluated using a confusion matrix,accuracy,precision,and F1-score.The results demonstrate that the Hybrid CNN-LSTM model outperforms standalone models,exhibiting lower error rates and higher R^(2) values,thereby highlighting the efficacy of deep learning-based hybrid architectures in achieving robust and precise PM2.5 forecasting.This study underscores the potential of advanced computational techniques in enhancing air quality prediction systems for environmental and public health applications.展开更多
Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the lim...Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.展开更多
In this study,we investigate a variety of exact soliton solutions of general(2+1)-dimensional Bogoyavlensky–Konopelchenko equation via the exp(-Φ(η))-expansion method and modified Kudryashov method.The exact soluti...In this study,we investigate a variety of exact soliton solutions of general(2+1)-dimensional Bogoyavlensky–Konopelchenko equation via the exp(-Φ(η))-expansion method and modified Kudryashov method.The exact solutions are characterized in the form of hyperbolic,trigonometric and rational function solutions using exp(-Φ(η))-expansion method,whereas the solution in the form of hyperbolic function expression is obtained by the modified Kudryashov method.These exact solutions also include kink,bright,dark,singular and periodic soliton solutions.The graphical interpretation of the exact solutions is addressed for specific choices of the parameters appearing in the solutions.展开更多
Background:Stimuli-responsive drug delivery systems introduced nowadays to enable enhanced drug release upon exogenous stimulus.Research focuses on developing systems for co-administration of drugs to overcome limitat...Background:Stimuli-responsive drug delivery systems introduced nowadays to enable enhanced drug release upon exogenous stimulus.Research focuses on developing systems for co-administration of drugs to overcome limitations of single-drug chemotherapy,such as low response rates,ineffective treatment completion,and drug resistance,leading to aggressive proliferation and recurrence.This research focuses on utilizing the amphiphilic polymer quaternary ammonium palmitoyl glycol chitosan(GCPQ)as a carrier to load hydrophobic curcumin(CUR)and hydrophilic doxorubicin(DOX)to reach the desired target and release the cargo upon exogenous stimuli of ultrasound.Methods:The nanoformulation synthesized using a biocompatible approach,resulting in a stable DOX-CUR-GCPQ nano-formulation upon physicochemical characterization and in vitro analysis using ultrasound.Results:The mean hydrodynamic diameter of DOX-CUR-GCPQ nanomicelles was measured as 95±1.23 nm,PDI 0.32±0.87,zeta potential−35±1.78 mV,and encapsulation efficiency 87.32%±0.3 and 79.42%±0.5 for DOX and CUR respectively.Biocompatibility studies revealed minimal hemolytic activity and biocompatible behavior of the nano-formulation,the co-loaded polymer-based nano-formulation when exposed to Ultrasound at a frequency of 1.5 MHz,for 40 s,on Hep2c cancer cell lines showed a higher release of 89% after 48 h.Moreover,a higher amount of drug internalized within the cells(P<0.0001).Conclusion:The exhibited lower cell viability and IC50(70μg/mL)which demonstrated that ultrasound waves likely facilitated the penetration and uptake of the amphiphilic polymer encapsulating dual drugs into the Hep2c cancer cells,allowing for more efficient delivery of the drugs(DOX and CUR)and broadens the spectrum of anticancer therapy.展开更多
Mango farming significantly contributes to the economy,particularly in developing countries.However,mango trees are susceptible to various diseases caused by fungi,viruses,and bacteria,and diagnosing these diseases at...Mango farming significantly contributes to the economy,particularly in developing countries.However,mango trees are susceptible to various diseases caused by fungi,viruses,and bacteria,and diagnosing these diseases at an early stage is crucial to prevent their spread,which can lead to substantial losses.The development of deep learning models for detecting crop diseases is an active area of research in smart agriculture.This study focuses on mango plant diseases and employs the ConvNeXt and Vision Transformer(ViT)architectures.Two datasets were used.The first,MangoLeafBD,contains data for mango leaf diseases such as anthracnose,bacterial canker,gall midge,and powdery mildew.The second,SenMangoFruitDDS,includes data for mango fruit diseases such as Alternaria,Anthracnose,Black Mould Rot,Healthy,and Stem and Rot.Both datasets were obtained from publicly available sources.The proposed model achieved an accuracy of 99.87%on the MangoLeafBD dataset and 98.40%on the MangoFruitDDS dataset.The results demonstrate that ConvNeXt and ViT models can effectively diagnose mango diseases,enabling farmers to identify these conditions more efficiently.The system contributes to increased mango production and minimizes economic losses by reducing the time and effort needed for manual diagnostics.Additionally,the proposed system is integrated into a mobile application that utilizes the model as a backend to detect mango diseases instantly.展开更多
The Asian Houbara(Chlamydotis macqueenii),a vulnerable species,is under significant threat from habitat degradation and anthropogenic pressures in Pakistan's arid landscapes.This study addresses the urgent need fo...The Asian Houbara(Chlamydotis macqueenii),a vulnerable species,is under significant threat from habitat degradation and anthropogenic pressures in Pakistan's arid landscapes.This study addresses the urgent need for conservation by identifying critical habitats,analyzing the influence of environmental and human factors on species distribution,and projecting future habitat shifts under climate change scenarios.Using the Max Ent model,which achieves a robust predictive accuracy(AUC=0.854),we mapped current and future habitat suitability under Shared Socioeconomic Pathways(SSP126,SSP370,SSP585)for the years 2040 and 2070.Presently,the suitable habitat extends over 217,082 km^(2),with 52,751 km^(2) classified as highly suitable.Key environmental drivers,identified via the Jackknife test,revealed that annual mean temperature(Bio1)and slope play a dominant role in determining habitat suitability.Projections show significant habitat degradation;however,under SSP585,highly suitable areas are expected to expand by up to 24.92%by 2070.Despite this increase,vast areas remain unsuitable,posing serious risks to population sustainability.Moreover,only 2115 km^(2) of highly suitable habitat currently falls within protected zones,highlighting a critical conservation shortfall.These findings highlight the imperative for immediate,targeted conservation efforts to secure the species'future in Pakistan's desert ecosystems.展开更多
Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in ne...Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in networks and systems.Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data,learn patterns,and anticipate potential threats.Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly.Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks.This research advocates for proactive measures and adaptive technologies in defending digital environments.Improvements in detection ability by organizations will assist in safeguarding assets and integrity in operations in this increasingly digital world.This paper draws on the categorization of cyber threat detection methods using hesitant bipolar fuzzy Frank operators.Categorization is a step that is necessary for systematic comparison and assessment of detection methods so that the most suitable method for particular cybersecurity requirements is chosen.Furthermore,this research manages uncertainty and vagueness that exists in decision-making by applying hesitant bipolar fuzzy logic.The importance of the work lies in how it fortifies cybersecurity architectures with a formal method of discovering optimal detection measures and improving responsiveness,resulting in holistic protection against dynamic threats.展开更多
The evaluation and assessment of network security is a decision-making(DM)problem that occurs in an environment with multiple criteria,which have uncertainty,bipolarity,and extra-related information.The traditional ap...The evaluation and assessment of network security is a decision-making(DM)problem that occurs in an environment with multiple criteria,which have uncertainty,bipolarity,and extra-related information.The traditional approaches fail to address the need to acquire a wide range of information for the assessment,especially in situations where the criteria have both positive and negative aspects and contain extra fuzzy information.Therefore,in this manuscript,we aim to introduce a DM approach based on the concept of bipolar complex fuzzy(BCF)Yager aggregation operators(AOs).The related properties of these aggregation operators(AOs)are also discussed.Moreover,in this article,we diagnose the Yager operations in the setting of BCF.The basic idea of the interpreted operators and DM approach is to access the problem linked with the network security that is to evaluate and select the finest network security control and network security protocols for protecting and safeguarding the network of any organization or home(case studies).Finally,to exhibit the supremacy and success of the described theory,we examine them with the prevailing theories.展开更多
In recent times,there has been a surge of attention towards advanced high-performance materials for storing energy,specifically in supercapacitors.One encouraging method involves utilizing nanocomposites based on tran...In recent times,there has been a surge of attention towards advanced high-performance materials for storing energy,specifically in supercapacitors.One encouraging method involves utilizing nanocomposites based on transition metal oxides/graphene which have demonstrated significant potential for improving capacitance.The electrochemical properties of titanium oxide doped graphene in current research have been improved through the incorporation of rare earth metals.The hydrothermal technique was chosen for the fabrication of nanocomposites as electrode materials.X-ray diffraction(XRD),Raman spectroscopy,Fourier transform infrared spectroscopy(FT-IR),and scanning electron microscopy(SEM) approaches were employed for the characterization of nanocomposites.Ternary and quaternary nanocomposites with 2 wt% rare earth elements doped with titanium oxide and graphene were synthesized with various ratios of lanthanum and cerium as dopants.In 2 wt% La:Ce-TiO_(2)/rGO,lanthanum,and cerium were doped in 1:1,1:3,and 1:5 ratios.2 wt% La:Ce(1:5)-TiO_(2)/rGO among co-doped composites exhibits better capacitive performance as determined through cyclic voltammetry and galvanostatic charge-discharge.Among all the nanocomposites 422 F/g was the maximum depicted by 2 wt%La:Ce(1:5)-TiO_(2)/rGO at a scan rate of 10 mV/s(potential window from-0.4 to+0.6 V) and 1895 F/g at1 mV/s(potential window-0.6 to+0.6 V).specific capacitance was also determined via GCD,and a maximum capacitance of 486 F/g is depicted by 2 wt% La:Ce(1:5)-TiO_(2)/rGO.The same composites have also served as promising electrode materials in terms of columbic efficiency,power,and energy density.展开更多
Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has alway...Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.展开更多
Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the l...Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the literature.However,chaos theory has not been extensively investigated in AO.Moreover,it is still not applied in the parameter estimation of electro-hydraulic systems.In this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique.An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline technique.The investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and respectively.Friedman test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization problems.However,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.展开更多
Background:Colocasia esculenta(L.)Schott,known as the taro vegetable,possesses various beneficial effects and is traditionally used in folk medicine.This study explores the ameliorative antioxidant and hepatoprotectiv...Background:Colocasia esculenta(L.)Schott,known as the taro vegetable,possesses various beneficial effects and is traditionally used in folk medicine.This study explores the ameliorative antioxidant and hepatoprotective effect of a methanolic extract of the C.esculenta flower(ME-CEF)against oxidative damage and hepatotoxicity in mice.Methods:The antioxidant efficacy of ME-CEF was assessed using 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic)(ABTS)and 2,2-diphenyl-1-picrylhydrazyl(DPPH)scavenging assay.The hepatoprotective effect was investigated by an assessment of liver injury indicators(amino transferase[ALT],aspartate amino transferase[AST],alkaline phosphatase[ALP],bilirubin,creatinine)and normalizing lipid profiles(cho-lesterol[CHO],triglyceride[TG],high-density lipoprotein[HDL],and low-density li-poprotein[LDL])along with histopathological study and antioxidant enzymes(CAT).A phytochemical analysis,both qualitative and quantitative,was conducted,including gas chromatography-tandem mass spectrometry(GC-MS/MS)analysis and an in silico molecular docking study.Results:The Result Showed that ME-CEF Possesses Moderate ABTS and DPPH Scavenging Activity with IC_(50) Values of 117.18 and 160.41μg/mL.As Illustrated by Reducing Liver Enzymes(ALT,AST,ALP,Bilirubin,Creatinine)and Lipid Profile(CHO,TG,LDL)and Raising HDL Levels(p<0.01),ME-CEF Dose Dependently Mitigated CCl_(4)-Induced Acute Liver Injury.Furthermore,ME-CEF Blocked Hepatic Oxidative Stress by Boosting Antioxidant Enzymes(CAT)and Preventing Liver Tissue Damage and Apoptosis.In Silico Investigations Also Showed a Promising Binding Affinity with Tumor Necrosis Factor α(TNF-α),Interleukin 6(IL-6),PRAP-1,and Xanthin Oxidoreductase,which Displayed Antioxidant and Hepatoprotective Candidacy while Notable Safety and Efficacy Profile Was Also Documented through ADME/T Studies.Histopathological Analysis Showed Reduced Hepatocellular Necrosis and Vascular Congestion in Silymarin and Extract Groups.Conclusion:Based on these results,our findings strongly recommend the medicinal use of the plant,highlighting its antioxidant and hepatoprotective potentials.展开更多
文摘This article discusses Islamic Banking System and its mode of leasing in the light of the objectives of Shari＇ah. It explores that the objectives behind the introduction of Islamic finance and banking system were the elimination of capitalist banking interest, exploitation of poor segment of the society and the establishment of an economic system which may lead to sustain a balance economic order and social justice. In this context, it intends to analyze the mode of leasing provided by Islamic Banking system in the light of the objectives of Shari＇ah and discloses that although Islamic Banking system is based on the principle of mudarbah, musharkah and Ijarah and deals with the customers in that context, yet apparently, the effects of these transactions are not much different from capitalist modes due to same consequences and effects of these transactions. It thus, provides a comparative analysis of the issue, i.e., mode of leasing at both Islamic and capitalist Banks. It argues that a common man can not avail Islamic financing/leasing if he lacks financial resources. If a poor person tries to purchase something by way of ijarah through Islamic Banking finance, he does not find any difference in the payment of the total cost between capitalist mode of leasing and Islamic mode of ijarah. Hence, this article concludes that although Islamic financing achieved a remarkable development among the Muslims, yet there is a need to revise the policy and system of Islamic financing in the light of the objectives of Shari＇ah. It also concludes that the mode of leasing provided at Islamic Banks does not accomplish the objectives of its establishment which is public interest. At present, this system is unable to assist the poor segment of the society or to provide ease to them.
文摘The specific concepts of Islamic capital market are based on transparency, accountability, and no asymmetric information. A capital market is said to be efficient with respect to an information item if the prices of securities fully impound the return implication of that item. This study has two main objectives. Firstly, for testing the efficiency of Islamic capital market which focuses on Jakarta Islamic Index （JII）. Secondly, by this research finding the regulator can make a good solution to create the real Islamic capital market. This study concludes that the Islamic capital market is not efficient in information. This is proved by test, where the result for both mean adjusted model and market adjusted model shows not significant, which means that the stock price that occurred has not been able to reflect a strong relationship with the real conditions that exist within the company. The second conclusion is the magnitude of abnormal return suggests that the market still has asymmetric information that will cause the occurrence of abnormal return. This is very unfortunate because Islamic capital market should be efficient in reflecting information transparency that could create a fair price in accordance with the real condition of the company＇s stock issuance.
文摘This letter evaluates Shahid et al’s study in 2025 on the rising hepatitis A virus(HAV)among adults in Pakistan,highlighting a shift in the virus’s epidemiology.Once primarily a childhood disease in low-income regions,HAV is now increasingly affecting adults,also seen globally due to improved sanitation.The study highlights public health challenges from adult HAV infections,which can lead to complications like coagulopathy and acute liver failure.It also has limitations,including being a single-center study and lacking seroprevalence and socioeconomic data,indicating the need for further research.This letter calls for urgent public health measures to extend adult vaccination programs and improve sanitation to address the increasing HAV infection in adult populations.
文摘Public-and private-sector organizations have adopted artificial intelligence(AI)to meet the challenges of the Fourth Industrial Revolution.The successful implementation of AI is a challenging task,and previous research has advocated the need to explore key readiness before AI implementation.The objective of this study is to identify the AI readiness factors explored by different authors in past research.To achieve this,we conducted a rigorous literature review.The approach used in the systematic literature review is also discussed.A rigorous review of 52 studies from various journals and databases(Science Direct,Springer Link,Institute of Electrical and Electronics Engineers,Emerald,and Google Scholar)identified 23 AI readiness factors.The key factors identified were mainly related to organizational information technology infrastructure,top management support,resource availability,collaborative culture,organizational size,organizational capability,compatibility,data quality,and financial budget,whereas the other 15 were potential factors in AI readiness.All of these factors should be considered before the implementation of AI in any organization.The findings also reflect a high failure rate,including AI readiness factors,which are intended to facilitate AI adoption in organizations and reduce the frequency of failures.These factors will aid management in developing an effective strategy for AI implementation in organizations.
基金funded under the Collaborative Research Initiative Grant Scheme(C-RIGS),grant number C-RIGS24-016-0022 from IIUM.
文摘This review provides a comprehensive overview of natural rubber(NR)composites,focusing on their properties,compounding aspects,and renewable practices involving natural fibre reinforcement.The properties of NR are influenced by the compounding process,which incorporates ingredients such as elastomers,vulcanizing agents,accelerators,activators,and fillers like carbon black and silica.While effective in enhancing properties,these fillers lack biodegradability,prompting the exploration of sustainable alternatives.The potential of natural fibres as renewable reinforcements in NR composites is thoroughly covered in this review,highlighting both their advan-tages,such as improved sustainability,and the challenges they present,such as compatibility with the rubber matrix.Surface treatment methods,including alkali and silane treatments,are also discussed as solutions to improve fibre-matrix adhesion and mitigate these challenges.Additionally,the review highlights the potential of oil palm empty fruit bunch(EFB)fibres as a natural fibre reinforcement.The abundance of EFB fibres and their alignment with sustainable practices make them promising substitutes for conventional fillers,contributing to valuable knowledge and supporting the broader move towards renewable reinforcement to improve sustain-ability without compromising the key properties of rubber composites.
文摘The complex morphological,anatomical,physiological,and chemical mechanisms within the aging brain have been the hot topic of research for centuries.The aging process alters the brain structure that affects functions and cognitions,but the worsening of such processes contributes to the pathogenesis of neurodegenerative disorders,such as Alzheimer's disease.Beyond these observable,mild morphological shifts,significant functional modifications in neurotransmission and neuronal activity critically influence the aging brain.Understanding these changes is important for maintaining cognitive health,especially given the increasing prevalence of age-related conditions that affect cognition.This review aims to explore the age-induced changes in brain plasticity and molecular processes,differentiating normal aging from the pathogenesis of Alzheimer's disease,thereby providing insights into predicting the risk of dementia,particularly Alzheimer's disease.
文摘Air pollution,specifically fine particulate matter(PM2.5),represents a critical environmental and public health concern due to its adverse effects on respiratory and cardiovascular systems.Accurate forecasting of PM2.5 concentrations is essential for mitigating health risks;however,the inherent nonlinearity and dynamic variability of air quality data present significant challenges.This study conducts a systematic evaluation of deep learning algorithms including Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and the hybrid CNN-LSTM as well as statistical models,AutoRegressive Integrated Moving Average(ARIMA)and Maximum Likelihood Estimation(MLE)for hourly PM2.5 forecasting.Model performance is quantified using Root Mean Squared Error(RMSE),Mean Absolute Error(MAE),Mean Absolute Percentage Error(MAPE),and the Coefficient of Determination(R^(2))metrics.The comparative analysis identifies optimal predictive approaches for air quality modeling,emphasizing computational efficiency and accuracy.Additionally,CNN classification performance is evaluated using a confusion matrix,accuracy,precision,and F1-score.The results demonstrate that the Hybrid CNN-LSTM model outperforms standalone models,exhibiting lower error rates and higher R^(2) values,thereby highlighting the efficacy of deep learning-based hybrid architectures in achieving robust and precise PM2.5 forecasting.This study underscores the potential of advanced computational techniques in enhancing air quality prediction systems for environmental and public health applications.
文摘Wireless Sensor Networks(WSNs)have emerged as crucial tools for real-time environmental monitoring through distributed sensor nodes(SNs).However,the operational lifespan of WSNs is significantly constrained by the limited energy resources of SNs.Current energy efficiency strategies,such as clustering,multi-hop routing,and data aggregation,face challenges,including uneven energy depletion,high computational demands,and suboptimal cluster head(CH)selection.To address these limitations,this paper proposes a hybrid methodology that optimizes energy consumption(EC)while maintaining network performance.The proposed approach integrates the Low Energy Adaptive Clustering Hierarchy with Deterministic(LEACH-D)protocol using an Artificial Neural Network(ANN)and Bayesian Regularization Algorithm(BRA).LEACH-D improves upon conventional LEACH by ensuring more uniform energy usage across SNs,mitigating inefficiencies from random CH selection.The ANN further enhances CH selection and routing processes,effectively reducing data transmission overhead and idle listening.Simulation results reveal that the LEACH-D-ANN model significantly reduces EC and extends the network’s lifespan compared to existing protocols.This framework offers a promising solution to the energy efficiency challenges in WSNs,paving the way for more sustainable and reliable network deployments.
文摘In this study,we investigate a variety of exact soliton solutions of general(2+1)-dimensional Bogoyavlensky–Konopelchenko equation via the exp(-Φ(η))-expansion method and modified Kudryashov method.The exact solutions are characterized in the form of hyperbolic,trigonometric and rational function solutions using exp(-Φ(η))-expansion method,whereas the solution in the form of hyperbolic function expression is obtained by the modified Kudryashov method.These exact solutions also include kink,bright,dark,singular and periodic soliton solutions.The graphical interpretation of the exact solutions is addressed for specific choices of the parameters appearing in the solutions.
文摘Background:Stimuli-responsive drug delivery systems introduced nowadays to enable enhanced drug release upon exogenous stimulus.Research focuses on developing systems for co-administration of drugs to overcome limitations of single-drug chemotherapy,such as low response rates,ineffective treatment completion,and drug resistance,leading to aggressive proliferation and recurrence.This research focuses on utilizing the amphiphilic polymer quaternary ammonium palmitoyl glycol chitosan(GCPQ)as a carrier to load hydrophobic curcumin(CUR)and hydrophilic doxorubicin(DOX)to reach the desired target and release the cargo upon exogenous stimuli of ultrasound.Methods:The nanoformulation synthesized using a biocompatible approach,resulting in a stable DOX-CUR-GCPQ nano-formulation upon physicochemical characterization and in vitro analysis using ultrasound.Results:The mean hydrodynamic diameter of DOX-CUR-GCPQ nanomicelles was measured as 95±1.23 nm,PDI 0.32±0.87,zeta potential−35±1.78 mV,and encapsulation efficiency 87.32%±0.3 and 79.42%±0.5 for DOX and CUR respectively.Biocompatibility studies revealed minimal hemolytic activity and biocompatible behavior of the nano-formulation,the co-loaded polymer-based nano-formulation when exposed to Ultrasound at a frequency of 1.5 MHz,for 40 s,on Hep2c cancer cell lines showed a higher release of 89% after 48 h.Moreover,a higher amount of drug internalized within the cells(P<0.0001).Conclusion:The exhibited lower cell viability and IC50(70μg/mL)which demonstrated that ultrasound waves likely facilitated the penetration and uptake of the amphiphilic polymer encapsulating dual drugs into the Hep2c cancer cells,allowing for more efficient delivery of the drugs(DOX and CUR)and broadens the spectrum of anticancer therapy.
基金funded by Princess Nourah bint Abdulrahman University and Researchers Supporting Project number(PNURSP2025R346)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Mango farming significantly contributes to the economy,particularly in developing countries.However,mango trees are susceptible to various diseases caused by fungi,viruses,and bacteria,and diagnosing these diseases at an early stage is crucial to prevent their spread,which can lead to substantial losses.The development of deep learning models for detecting crop diseases is an active area of research in smart agriculture.This study focuses on mango plant diseases and employs the ConvNeXt and Vision Transformer(ViT)architectures.Two datasets were used.The first,MangoLeafBD,contains data for mango leaf diseases such as anthracnose,bacterial canker,gall midge,and powdery mildew.The second,SenMangoFruitDDS,includes data for mango fruit diseases such as Alternaria,Anthracnose,Black Mould Rot,Healthy,and Stem and Rot.Both datasets were obtained from publicly available sources.The proposed model achieved an accuracy of 99.87%on the MangoLeafBD dataset and 98.40%on the MangoFruitDDS dataset.The results demonstrate that ConvNeXt and ViT models can effectively diagnose mango diseases,enabling farmers to identify these conditions more efficiently.The system contributes to increased mango production and minimizes economic losses by reducing the time and effort needed for manual diagnostics.Additionally,the proposed system is integrated into a mobile application that utilizes the model as a backend to detect mango diseases instantly.
基金the support of the Zoological Survey of Pakistan,and the Wildlife and Parks Department of Punjab for their assistance in this research。
文摘The Asian Houbara(Chlamydotis macqueenii),a vulnerable species,is under significant threat from habitat degradation and anthropogenic pressures in Pakistan's arid landscapes.This study addresses the urgent need for conservation by identifying critical habitats,analyzing the influence of environmental and human factors on species distribution,and projecting future habitat shifts under climate change scenarios.Using the Max Ent model,which achieves a robust predictive accuracy(AUC=0.854),we mapped current and future habitat suitability under Shared Socioeconomic Pathways(SSP126,SSP370,SSP585)for the years 2040 and 2070.Presently,the suitable habitat extends over 217,082 km^(2),with 52,751 km^(2) classified as highly suitable.Key environmental drivers,identified via the Jackknife test,revealed that annual mean temperature(Bio1)and slope play a dominant role in determining habitat suitability.Projections show significant habitat degradation;however,under SSP585,highly suitable areas are expected to expand by up to 24.92%by 2070.Despite this increase,vast areas remain unsuitable,posing serious risks to population sustainability.Moreover,only 2115 km^(2) of highly suitable habitat currently falls within protected zones,highlighting a critical conservation shortfall.These findings highlight the imperative for immediate,targeted conservation efforts to secure the species'future in Pakistan's desert ecosystems.
基金funded by Ongoing Research Funding program(ORF-2025-749),King Saud University,Riyadh,Saudi Arabia.
文摘Cyber threat detection is a crucial aspect of contemporary cybersecurity due to the depth and complexity of cyberattacks.It is the identification of malicious activity,unauthorized access,and possible intrusions in networks and systems.Modern detection methods employ artificial intelligence and machine learning to study vast amounts of data,learn patterns,and anticipate potential threats.Real-time monitoring and anomaly detection improve the capacity to react to changing threats more rapidly.Cyber threat detection systems aim to reduce false positives and provide complete coverage against the broadest possible attacks.This research advocates for proactive measures and adaptive technologies in defending digital environments.Improvements in detection ability by organizations will assist in safeguarding assets and integrity in operations in this increasingly digital world.This paper draws on the categorization of cyber threat detection methods using hesitant bipolar fuzzy Frank operators.Categorization is a step that is necessary for systematic comparison and assessment of detection methods so that the most suitable method for particular cybersecurity requirements is chosen.Furthermore,this research manages uncertainty and vagueness that exists in decision-making by applying hesitant bipolar fuzzy logic.The importance of the work lies in how it fortifies cybersecurity architectures with a formal method of discovering optimal detection measures and improving responsiveness,resulting in holistic protection against dynamic threats.
基金funded by Ongoing Research Funding Program(Grant OR-‐2025-749),King Saud University,Riyadh,Saudi Arabia.
文摘The evaluation and assessment of network security is a decision-making(DM)problem that occurs in an environment with multiple criteria,which have uncertainty,bipolarity,and extra-related information.The traditional approaches fail to address the need to acquire a wide range of information for the assessment,especially in situations where the criteria have both positive and negative aspects and contain extra fuzzy information.Therefore,in this manuscript,we aim to introduce a DM approach based on the concept of bipolar complex fuzzy(BCF)Yager aggregation operators(AOs).The related properties of these aggregation operators(AOs)are also discussed.Moreover,in this article,we diagnose the Yager operations in the setting of BCF.The basic idea of the interpreted operators and DM approach is to access the problem linked with the network security that is to evaluate and select the finest network security control and network security protocols for protecting and safeguarding the network of any organization or home(case studies).Finally,to exhibit the supremacy and success of the described theory,we examine them with the prevailing theories.
文摘In recent times,there has been a surge of attention towards advanced high-performance materials for storing energy,specifically in supercapacitors.One encouraging method involves utilizing nanocomposites based on transition metal oxides/graphene which have demonstrated significant potential for improving capacitance.The electrochemical properties of titanium oxide doped graphene in current research have been improved through the incorporation of rare earth metals.The hydrothermal technique was chosen for the fabrication of nanocomposites as electrode materials.X-ray diffraction(XRD),Raman spectroscopy,Fourier transform infrared spectroscopy(FT-IR),and scanning electron microscopy(SEM) approaches were employed for the characterization of nanocomposites.Ternary and quaternary nanocomposites with 2 wt% rare earth elements doped with titanium oxide and graphene were synthesized with various ratios of lanthanum and cerium as dopants.In 2 wt% La:Ce-TiO_(2)/rGO,lanthanum,and cerium were doped in 1:1,1:3,and 1:5 ratios.2 wt% La:Ce(1:5)-TiO_(2)/rGO among co-doped composites exhibits better capacitive performance as determined through cyclic voltammetry and galvanostatic charge-discharge.Among all the nanocomposites 422 F/g was the maximum depicted by 2 wt%La:Ce(1:5)-TiO_(2)/rGO at a scan rate of 10 mV/s(potential window from-0.4 to+0.6 V) and 1895 F/g at1 mV/s(potential window-0.6 to+0.6 V).specific capacitance was also determined via GCD,and a maximum capacitance of 486 F/g is depicted by 2 wt% La:Ce(1:5)-TiO_(2)/rGO.The same composites have also served as promising electrode materials in terms of columbic efficiency,power,and energy density.
基金fully supported by the University of Vaasa and VTT Technical Research Centre of Finland.
文摘Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.
基金funded by Taif University,Saudi Arabia,Project No.(TU-DSPP-2024-52).
文摘Aquila Optimizer(AO)is a recently proposed population-based optimization technique inspired by Aquila’s behavior in catching prey.AO is applied in various applications and its numerous variants were proposed in the literature.However,chaos theory has not been extensively investigated in AO.Moreover,it is still not applied in the parameter estimation of electro-hydraulic systems.In this work,ten well-defined chaotic maps were integrated into a narrowed exploitation of AO for the development of a robust chaotic optimization technique.An extensive investigation of twenty-three mathematical benchmarks and ten IEEE Congress on Evolutionary Computation(CEC)functions shows that chaotic Aquila optimization techniques perform better than the baseline technique.The investigation is further conducted on parameter estimation of an electro-hydraulic control system,which is performed on various noise levels and shows that the proposed chaotic AO with Piecewise map(CAO6)achieves the best fitness values of and at noise levels and respectively.Friedman test 2.873E-05,1.014E-04,8.728E-031.300E-03,1.300E-02,1.300E-01,for repeated measures,computational analysis,and Taguchi test reflect the superiority of CAO6 against the state of the arts,demonstrating its potential for addressing various engineering optimization problems.However,the sensitivity to parameter tuning may limit its direct application to complex optimization scenarios.
基金partially funded by the Bangladesh Council of Scientific and Industrial Research (BCSIR) as an R&D project work of the 2022–2023 fiscal year,reference no.:39.02.0000.011.14.157.2022/172 (Date:10.11.2022).
文摘Background:Colocasia esculenta(L.)Schott,known as the taro vegetable,possesses various beneficial effects and is traditionally used in folk medicine.This study explores the ameliorative antioxidant and hepatoprotective effect of a methanolic extract of the C.esculenta flower(ME-CEF)against oxidative damage and hepatotoxicity in mice.Methods:The antioxidant efficacy of ME-CEF was assessed using 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulfonic)(ABTS)and 2,2-diphenyl-1-picrylhydrazyl(DPPH)scavenging assay.The hepatoprotective effect was investigated by an assessment of liver injury indicators(amino transferase[ALT],aspartate amino transferase[AST],alkaline phosphatase[ALP],bilirubin,creatinine)and normalizing lipid profiles(cho-lesterol[CHO],triglyceride[TG],high-density lipoprotein[HDL],and low-density li-poprotein[LDL])along with histopathological study and antioxidant enzymes(CAT).A phytochemical analysis,both qualitative and quantitative,was conducted,including gas chromatography-tandem mass spectrometry(GC-MS/MS)analysis and an in silico molecular docking study.Results:The Result Showed that ME-CEF Possesses Moderate ABTS and DPPH Scavenging Activity with IC_(50) Values of 117.18 and 160.41μg/mL.As Illustrated by Reducing Liver Enzymes(ALT,AST,ALP,Bilirubin,Creatinine)and Lipid Profile(CHO,TG,LDL)and Raising HDL Levels(p<0.01),ME-CEF Dose Dependently Mitigated CCl_(4)-Induced Acute Liver Injury.Furthermore,ME-CEF Blocked Hepatic Oxidative Stress by Boosting Antioxidant Enzymes(CAT)and Preventing Liver Tissue Damage and Apoptosis.In Silico Investigations Also Showed a Promising Binding Affinity with Tumor Necrosis Factor α(TNF-α),Interleukin 6(IL-6),PRAP-1,and Xanthin Oxidoreductase,which Displayed Antioxidant and Hepatoprotective Candidacy while Notable Safety and Efficacy Profile Was Also Documented through ADME/T Studies.Histopathological Analysis Showed Reduced Hepatocellular Necrosis and Vascular Congestion in Silymarin and Extract Groups.Conclusion:Based on these results,our findings strongly recommend the medicinal use of the plant,highlighting its antioxidant and hepatoprotective potentials.
