The Shangla Complex ophiolite represents a relic of the Neo-Tethyan oceanic lithosphere along the Indus Suture Zone(also known as the Main Mantle Thrust)in northern Pakistan.This section,thrust onto the continental ma...The Shangla Complex ophiolite represents a relic of the Neo-Tethyan oceanic lithosphere along the Indus Suture Zone(also known as the Main Mantle Thrust)in northern Pakistan.This section,thrust onto the continental margin between the Indian and Karakoram(Asian)plates,is predominantly composed of depleted harzburgites,dunites and chromitites.In this study,we conducted a thorough analysis of mineralogy,whole-rock geochemistry(major oxides,trace elements,PGE),and integrated Re-Os isotopic data from mantle-derived peridotites to understand their petrogenesis and melt evolution.These peridotites exhibit a depleted nature,characterized by a low modal composition of clinopyroxene,a wide forsterite content range in olivine(86.5 to 95.2),and a large variation in Cr#values(25.1–91.4).Their diverse whole-rock geochemistry further suggests varying degrees of partial melting.The Cpx-harzburgites show high average Al_(2)O_(3)(1.83 wt.%),CaO(2.27 wt.%),ΣREE(12.9 ppb),and^(187)Os/^(188)Os values between 0.13095 and 0.12571.On the other hand,the depleted harzburgites and dunites exhibit lower average Al_(2)O_(3)(0.57 wt.%and 0.14 wt.%,respectively),CaO concentration(0.59 wt.%and 0.21 wt.%,respectively),and∑REE concentrations,measured at 12.7 ppb and 8.9 ppb,respectively.The^(187)Os/^(188)Os ratios in the depleted harzburgites and dunites range from 0.12643 to 0.11777,indicating they are less radiogenic compared to the Cpx-harzburgites.The spoon-shaped rare earth elements(REE)patterns suggest that the Cpx-harzburgites underwent low degrees of partial melting(∼10%–15%),whereas the depleted harzburgites and dunites indicate somewhat higher degrees of partial melting(additional melting of the Cpx-harzburgites).The PGE abundances in these depleted harzburgites and dunites are linked to the partial melting of Cpx-harzburgites,resulting in a boninitic-like melt.Their low degree of melting and melt extraction suggests that Cpx-harzburgites initially formed at a mid-ocean ridge(MOR)spreading center or a distal fore-arc basin.In contrast,the depleted harzburgites and dunites were formed during a second phase of melting,followed by refertilization,closely associated with a supra-subduction zone(SSZ)setting.The Re-Os isotopic systematics of the Shangla Complex peridotites reveal model age clusters of ca.250 Ma and ca.450 Ma,potentially corresponding to significant tectonic events in the geodynamic evolution of the Neo-Tethyan,Rheic,and Proto-Tethyan oceans.展开更多
In this study we theoretically demonstrate ultrahigh-resolution two-dimensional atomic localization within a three-levelλ-type atomic medium via superposition of asymmetric and symmetric standing wave fields.Our anal...In this study we theoretically demonstrate ultrahigh-resolution two-dimensional atomic localization within a three-levelλ-type atomic medium via superposition of asymmetric and symmetric standing wave fields.Our analysis provides an understanding of the precise spatial localization of atomic positions at the atomic level,utilizing advanced theoretical approaches and principles of quantum mechanics.The dynamical behavior of a three-level atomic system is thoroughly analyzed using the density matrix formalism within the realm of quantum mechanics.A theoretical approach is constructed to describe the interaction between the system and external fields,specifically a control field and a probe field.The absorption spectrum of the probe field is thoroughly examined to clarify the spatial localization of the atom within the proposed configuration.A theoretical investigation found that symmetric and asymmetric superposition phenomena significantly influence the localized peaks within a two-dimensional spatial domain.Specifically,the emergence of one and two sharp localized peaks was observed within a one-wavelength domain.We observed notable influences of the intensity of the control field,probe field detuning and decay rates on atomic localization.Ultimately,we have achieved an unprecedented level of ultrahigh resolution and precision in localizing an atom within an area smaller thanλ/35×λ/35.These findings hold promise for potential applications in fields such as Bose-Einstein condensation,nanolithography,laser cooling,trapping of neutral atoms and the measurement of center-of-mass wave functions.展开更多
We present a flexible manipulation and control of solitons via Bose-Einstein condensates.In the presence of Rashba spin-orbit coupling and repulsive interactions within a harmonic potential,our investigation reveals t...We present a flexible manipulation and control of solitons via Bose-Einstein condensates.In the presence of Rashba spin-orbit coupling and repulsive interactions within a harmonic potential,our investigation reveals the numerical local solutions within the system.By manipulating the strength of repulsive interactions and adjusting spin-orbit coupling while maintaining a zero-frequency rotation,diverse soliton structures emerge within the system.These include plane-wave solitons,two distinct types of stripe solitons,and odd petal solitons with both single and double layers.The stability of these solitons is intricately dependent on the varying strength of spin-orbit coupling.Specifically,stripe solitons can maintain a stable existence within regions characterized by enhanced spin-orbit coupling while petal solitons are unable to sustain a stable existence under similar conditions.When rotational frequency is introduced to the system,solitons undergo a transition from stripe solitons to a vortex array characterized by a sustained rotation.The rotational directions of clockwise and counterclockwise are non-equivalent owing to spin-orbit coupling.As a result,the properties of vortex solitons exhibit significant variation and are capable of maintaining a stable existence in the presence of repulsive interactions.展开更多
In context with a recent announcement by the World Health Organization(WHO)holding an emergency towards an infectious illness indistinguishable from smallpox,monkeypox(mpox)carried a high case fatality(12%)[1,2].The v...In context with a recent announcement by the World Health Organization(WHO)holding an emergency towards an infectious illness indistinguishable from smallpox,monkeypox(mpox)carried a high case fatality(12%)[1,2].The variable distribution of cases during 2022-2023 in non-endemic regions i.e.,Europe(20000),China(1098),US(475),India(75),Japan(31),Pakistan(11)may cause an overwhelming demise with an additional burden on the economy[3].展开更多
Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive data.Traditional detection methods often fail to keep pace with ...Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive data.Traditional detection methods often fail to keep pace with the evolving sophistication of cyber threats.This paper introduces a novel hybrid ensemble learning framework that leverages a combination of advanced machine learning algorithms—Logistic Regression(LR),Support Vector Machines(SVM),eXtreme Gradient Boosting(XGBoost),Categorical Boosting(CatBoost),and Deep Neural Networks(DNN).Utilizing the XSS-Attacks-2021 dataset,which comprises 460 instances across various real-world trafficrelated scenarios,this framework significantly enhances XSS attack detection.Our approach,which includes rigorous feature engineering and model tuning,not only optimizes accuracy but also effectively minimizes false positives(FP)(0.13%)and false negatives(FN)(0.19%).This comprehensive methodology has been rigorously validated,achieving an unprecedented accuracy of 99.87%.The proposed system is scalable and efficient,capable of adapting to the increasing number of web applications and user demands without a decline in performance.It demonstrates exceptional real-time capabilities,with the ability to detect XSS attacks dynamically,maintaining high accuracy and low latency even under significant loads.Furthermore,despite the computational complexity introduced by the hybrid ensemble approach,strategic use of parallel processing and algorithm tuning ensures that the system remains scalable and performs robustly in real-time applications.Designed for easy integration with existing web security systems,our framework supports adaptable Application Programming Interfaces(APIs)and a modular design,facilitating seamless augmentation of current defenses.This innovation represents a significant advancement in cybersecurity,offering a scalable and effective solution for securing modern web applications against evolving threats.展开更多
Algorithms for steganography are methods of hiding data transfers in media files.Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial i...Algorithms for steganography are methods of hiding data transfers in media files.Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image analysis.Images with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for classification.To address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of images.Support Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or cover.The Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the proposedmethod.Using WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.展开更多
Hepatitis C virus(HCV) is a potent human pathogen and is one of the main causes of chronic hepatitis round the world. The present review describes the evidencebased consensus on the diagnosis, prevention and managemen...Hepatitis C virus(HCV) is a potent human pathogen and is one of the main causes of chronic hepatitis round the world. The present review describes the evidencebased consensus on the diagnosis, prevention and management of HCV disease. Various techniques, for the detection of anti-HCV immunoglobulin G immunoassays, detection of HCV RNA by identifying virus-specific molecules nucleic acid testings, recognition of core antigen for diagnosis of HCV, quantitative antigenassay, have been used to detect HCV RNA and core antigen. Advanced technologies such as nanoparticlebased diagnostic assays, loop-mediated isothermal amplification and aptamers and Ortho trak-C assay have also come to the front that provides best detection results with greater ease and specificity for detection of HCV. It is of immense importance to prevent this infection especially among the sexual partners, injecting drug users, mother-to-infant transmission of HCV, household contact, healthcare workers and people who get tattoos and piercing on their skin. Management of this infection is intended to eradicate it out of the body of patients. Management includes examining the treatment(efficacy and protection), assessment of hepatic condition before commencing therapy, controlling the parameters upon which dual and triple therapies work, monitoring the body after treatment and adjusting the co-factors. Examining the treatment in some special groups of people(HIV/HCV co-infected, hemodialysis patients, renal transplanted patients).展开更多
Methanol cross-over effects from the anode to the cathode are important parameters for reducing catalytic performance in direct methanol fuel cells.A promising candidate catalyst for the cathode in direct methanol fue...Methanol cross-over effects from the anode to the cathode are important parameters for reducing catalytic performance in direct methanol fuel cells.A promising candidate catalyst for the cathode in direct methanol fuel cells must have excellent activity toward oxygen reduction reaction and resistance to methanol oxidation reaction.This review focuses on the methanol tolerant noble metal-based electrocatalysts,including platinum and palladium-based alloys,noble metal–carbon based composites,transition metal-based catalysts,carbon-based metal catalysts,and metal-free catalysts.The understanding of the correlation between the activity and the synthesis method,electrolyte environment and stability issues are highlighted.For the transition metal-based catalyst,their activity,stability and methanol tolerance in direct methanol fuel cells and comparisons with those of platinum are particularly discussed.Finally,strategies to enhance the methanol tolerance and hinder the generation of mixed potential in direct methanol fuel cells are also presented.This review provides a perspective for future developments for the scientist in selecting suitable methanol tolerate catalyst for oxygen reduction reaction and designing high-performance practical direct methanol fuel cells.展开更多
For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself ...For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems.With the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is reduced.Matrix computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this algorithm.The proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its usefulness.By the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than EKRLS.This new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input data.Multiple experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.展开更多
Zika virus is a new global threat for 2016 that has been swept to almost all Americas and is now posing serious threats to the entire globe.This deadly virus is playing havoc to unborn lives because of its reported as...Zika virus is a new global threat for 2016 that has been swept to almost all Americas and is now posing serious threats to the entire globe.This deadly virus is playing havoc to unborn lives because of its reported association with upsurge of fetal deformation called microcephaly and neuropathic disorders including Guillain-Barrésyndrome.Till today,there is no vaccine prospect,antiviral therapy or licensed medical countermeasures to curb the teratogenic outcomes of this destructive viral infection.Diagnosis,treatment,chronicity and pathogenesis are still vague and unsettled.Therefore,this review article addresses all the aspects related to this disease to mitigate the explosive rise in Zika virus infection.展开更多
Hybrid density functional theory was used to investigate the structural,electronic,magnetic and elastic properties of the Laves phase binary intermetallics RFe_(2)(R=La,Ce,Pr and Nd) in C_(15) crystal structure.The ca...Hybrid density functional theory was used to investigate the structural,electronic,magnetic and elastic properties of the Laves phase binary intermetallics RFe_(2)(R=La,Ce,Pr and Nd) in C_(15) crystal structure.The calculated lattice constants of these materials are found in good agreement with the experiments.The band structures and density of states distribution confirm the metallic nature of all these intermetallics.The optimized energies in different magnetic phases and magnetic susceptibilities by postDFT treatments confirm that all the understudy compounds are ferromagnetic in nature.Elastic parameters were calculated from the cubic elastic coefficients C_(11),C_(12) and C_(44).The elastic properties reveal that these intermetallics are incompressible,ductile,elastically anisotropic and mechanically stable.Based on the metallic nature and ferromagnetic properties,it is expected that these intermetallics are suitable materials for spintronic technology.展开更多
AIM: To assess the association between chronic hepatitis C virus (HCV) infection and hepatocellular carcinoma (HCC) in Pakistan, and the genotype distribution among these HCC patients.METHODS: One hundred and sixty-on...AIM: To assess the association between chronic hepatitis C virus (HCV) infection and hepatocellular carcinoma (HCC) in Pakistan, and the genotype distribution among these HCC patients.METHODS: One hundred and sixty-one subjects with HCC were included in this study. Liver biopsy was performed on 145 of the patients; sixteen were excluded because they failed to fulfill the inclusion criteria. Qualitative polymerase chain reaction (PCR) was performed for hepatitis B virus and HCV. Samples positive for HCV RNA were genotyped using genotype-specif ic PCR and conf irmed by HCV 5' noncoding region sequencing analysis. RESULTS: Chronic HCV infection was identified a major risk factor (63.44% of tested HCC patients) forthe development of HCC. The time from HCV infection to appearance of cancer was 10-50 years. In the HCC patient population, broader distributions of genotypes were present with genotype 3a as the predominant genotype. Using the type-specific genotyping method, we found HCV genotype 3a in 40.96%, 3b in 15.66%, 1a in 9.63%, and 1b in 2.40% of HCC tissue samples. About 28% of cases were found with mixed genotypes. Two cases were unable to be genotyped because of low viral load. Sixty-six percent of treated patients with cirrhosis had an end of treatment response, but unfortunately they relapsed quickly when the treatment was discontin-ued, and HCC developed during a median 3.8 years. CONCLUSION: There was a strong association between chronic HCV infection and HCC in Pakistan, and between HCV genotype 3a and HCC.展开更多
In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial pattern....In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial pattern.Thereby,electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability.Due to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG domain.In this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as input.To minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant features.To this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the classification.Further,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test accuracy.Performance evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark schemes.Our proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.展开更多
One of the major concerns for the utilities in the Smart Grid(SG)is electricity theft.With the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which make...One of the major concerns for the utilities in the Smart Grid(SG)is electricity theft.With the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which makes it possible for advanced data analysis that was not previously possible.For this purpose,we have taken historical data of energy thieves and normal users.To avoid imbalance observation,biased estimates,we applied the interpolation method.Furthermore,the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing.By proposing an improved version of Zeiler and Fergus Net(ZFNet)as a feature extraction approach,we had able to reduce the model’s time complexity.To minimize the overfitting issues,increase the training accuracy and reduce the training loss,we have proposed an enhanced method by merging Adaptive Boosting(AdaBoost)classifier with Coronavirus Herd Immunity Optimizer(CHIO)and Forensic based Investigation Optimizer(FBIO).In terms of low computational complexity,minimized over-fitting problems on a large quantity of data,reduced training time and training loss and increased training accuracy,our model outperforms the benchmark scheme.Our proposed algorithms Ada-CHIO andAda-FBIO,have the low MeanAverage Percentage Error(MAPE)value of error,i.e.,6.8%and 9.5%,respectively.Furthermore,due to the stability of our model our proposed algorithms Ada-CHIO and Ada-FBIO have achieved the accuracy of 93%and 90%.Statistical analysis shows that the hypothesis we proved using statistics is authentic for the proposed technique against benchmark algorithms,which also depicts the superiority of our proposed techniques.展开更多
Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively.Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized envir...Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively.Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized environment.The load on the cloud data centers is growing day by day due to the rapid growth in cloud computing demand.Elasticity in cloud computing is one of the fundamental properties,and elastic load balancing automatically distributes incoming load to multiple virtual machines.This work is aimed to introduce efficient resource provisioning and de-provisioning for better load balancing.In this article,a model is proposed in which the fuzzy logic approach is used for load balancing to avoid underload and overload of resources.A Simulator in Matlab is used to test the effectiveness and correctness of the proposed model.The simulation results have shown that our proposed intelligent cloud-based load balancing system empowered with fuzzy logic is better than previously published approaches.展开更多
Cellulases and hemicellulases are the main industrial sources from different microorganisms used to depolymerise plant biomass to simple sugars that are converted to chemical intermediates and biofuels, such as ethano...Cellulases and hemicellulases are the main industrial sources from different microorganisms used to depolymerise plant biomass to simple sugars that are converted to chemical intermediates and biofuels, such as ethanol. Cellulases are formed adaptively, and several positive (xyr1, Ace2, HAP2/3/5) and negative (Ace1, Cre1) components involved in this regulation are now known. In this review, we summarise current knowledge about how cellulase biosynthesis is regulated, and outline recent approaches and suitable strategies for facilitating the targeted improvement of cellulase production by genetic engineering. Trichoderma reesei is the preferred organism for producing industrial cellulases. However, a more efficient heterologous expression system for enzymes from different organism is needed to further improve its cellulase mixture. In addition those optimizations of the promoter and linker for hybrid genes can dramatically improve the efficiency of heterologous expression of cellulase genes.展开更多
Objective: To determine the breadth of Zika virus(ZIKV)-associated brain anomalies in neonates and adults. Methods: Systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Met...Objective: To determine the breadth of Zika virus(ZIKV)-associated brain anomalies in neonates and adults. Methods: Systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA) statement using electronic databases ScienceDirect, Pubmed, Medline, Scopus, and Global Health Library.Only those research articles, case studies, case-control studies, case-cohort studies, crosssectional studies, and organizational survey reports were included in the study that reported any fetal outcomes for pregnant women who had infected with ZIKV during the gestational period and ZIKV-related neurological complications in adults as well. Results: Out of total 72 retrieved articles, 50 met the inclusion criteria. We estimated a significant increase in incidence of neural abnormalities such as Guillain-Barre syndrome and microcephaly in the regions that are experiencing ZIKV outbreaks. Other neurological malformations found in ZIKV patients include hydrancephaly/hydrops fetalis, myasthenia gravis,meningoencephalitis and myelitis. Conclusion: Our systematic analysis provides the broad spectrum of neurological malformations in ZIKV infected patients and these data further support the causal link of ZIKV with neurological disorders.展开更多
Zika virus(ZIKV) is rapidly spreading across the America and its devastating outcomes for pregnant women and infants have driven this previously ignored pathogen into the limelight.Clinical manifestations are fever,jo...Zika virus(ZIKV) is rapidly spreading across the America and its devastating outcomes for pregnant women and infants have driven this previously ignored pathogen into the limelight.Clinical manifestations are fever,joint pain or rash and conjunctivitis.Emergence of ZIKV started with a first outbrcak in the Pacific arca in 2007.a second large outbreak occurred in the Pacific in 2013/2014 and subsequently the virus spread in other Pacific islands.Threat of explosive global pandemic and severe clinical complications linked with the more immediate and recurrent epidemics necessitate the development of an effective vaccine.Several vaccine platforms such as DNA vaccine,recombinant subunit vaccine.ZIKV purified inactivated vaccine,and chimeric vaccines have shown potent efficacy in ritro and in rim trials.Moreover,number of drugs such as Sofosbuvir.BCX4450.NITD008 and 7-DMA are ready to enter phase I clinical trial because of proven anti-ZIKV activity.Monoclonal based antibodies offer promise as an intervention effective for use in pregnant women.In this review,we describe the advances in research on ZIKV such as research strategies for the development of antiviral drugs & vaccines,molecular evolution,epidemiology emergence,neurological complications and other teratogenic outcomes as well as pathogenesis.展开更多
Herein,we propose a scheme for the realization of two-dimensional atomic localization in aλ-type three-level atomic medium such that the atom interacts with the two orthogonal standing-wave fields and a probe field.B...Herein,we propose a scheme for the realization of two-dimensional atomic localization in aλ-type three-level atomic medium such that the atom interacts with the two orthogonal standing-wave fields and a probe field.Because of the spatially dependent atom-field interaction,the information about the position of the atom can be obtained by monitoring the probe transmission spectra of the weak probe field for the first time.A single and double sharp localized peaks are observed in the one-wavelength domain.We have theoretically archived high-resolution and high-precision atomic localization within a region smaller thanλ/25×λ/25.The results may have potential applications in the field of nano-lithography and advance laser cooling technology.展开更多
基金supported by a grant from the Science and Technology Innovation Program of Hunan Province(Grant No.2021RC4055)Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring,during the Postdoctoral research of the first author(Zaheen Ullah,Assistant Professor,University of Swat,Pakistan)at the Central South University,Changsha,China.
文摘The Shangla Complex ophiolite represents a relic of the Neo-Tethyan oceanic lithosphere along the Indus Suture Zone(also known as the Main Mantle Thrust)in northern Pakistan.This section,thrust onto the continental margin between the Indian and Karakoram(Asian)plates,is predominantly composed of depleted harzburgites,dunites and chromitites.In this study,we conducted a thorough analysis of mineralogy,whole-rock geochemistry(major oxides,trace elements,PGE),and integrated Re-Os isotopic data from mantle-derived peridotites to understand their petrogenesis and melt evolution.These peridotites exhibit a depleted nature,characterized by a low modal composition of clinopyroxene,a wide forsterite content range in olivine(86.5 to 95.2),and a large variation in Cr#values(25.1–91.4).Their diverse whole-rock geochemistry further suggests varying degrees of partial melting.The Cpx-harzburgites show high average Al_(2)O_(3)(1.83 wt.%),CaO(2.27 wt.%),ΣREE(12.9 ppb),and^(187)Os/^(188)Os values between 0.13095 and 0.12571.On the other hand,the depleted harzburgites and dunites exhibit lower average Al_(2)O_(3)(0.57 wt.%and 0.14 wt.%,respectively),CaO concentration(0.59 wt.%and 0.21 wt.%,respectively),and∑REE concentrations,measured at 12.7 ppb and 8.9 ppb,respectively.The^(187)Os/^(188)Os ratios in the depleted harzburgites and dunites range from 0.12643 to 0.11777,indicating they are less radiogenic compared to the Cpx-harzburgites.The spoon-shaped rare earth elements(REE)patterns suggest that the Cpx-harzburgites underwent low degrees of partial melting(∼10%–15%),whereas the depleted harzburgites and dunites indicate somewhat higher degrees of partial melting(additional melting of the Cpx-harzburgites).The PGE abundances in these depleted harzburgites and dunites are linked to the partial melting of Cpx-harzburgites,resulting in a boninitic-like melt.Their low degree of melting and melt extraction suggests that Cpx-harzburgites initially formed at a mid-ocean ridge(MOR)spreading center or a distal fore-arc basin.In contrast,the depleted harzburgites and dunites were formed during a second phase of melting,followed by refertilization,closely associated with a supra-subduction zone(SSZ)setting.The Re-Os isotopic systematics of the Shangla Complex peridotites reveal model age clusters of ca.250 Ma and ca.450 Ma,potentially corresponding to significant tectonic events in the geodynamic evolution of the Neo-Tethyan,Rheic,and Proto-Tethyan oceans.
文摘In this study we theoretically demonstrate ultrahigh-resolution two-dimensional atomic localization within a three-levelλ-type atomic medium via superposition of asymmetric and symmetric standing wave fields.Our analysis provides an understanding of the precise spatial localization of atomic positions at the atomic level,utilizing advanced theoretical approaches and principles of quantum mechanics.The dynamical behavior of a three-level atomic system is thoroughly analyzed using the density matrix formalism within the realm of quantum mechanics.A theoretical approach is constructed to describe the interaction between the system and external fields,specifically a control field and a probe field.The absorption spectrum of the probe field is thoroughly examined to clarify the spatial localization of the atom within the proposed configuration.A theoretical investigation found that symmetric and asymmetric superposition phenomena significantly influence the localized peaks within a two-dimensional spatial domain.Specifically,the emergence of one and two sharp localized peaks was observed within a one-wavelength domain.We observed notable influences of the intensity of the control field,probe field detuning and decay rates on atomic localization.Ultimately,we have achieved an unprecedented level of ultrahigh resolution and precision in localizing an atom within an area smaller thanλ/35×λ/35.These findings hold promise for potential applications in fields such as Bose-Einstein condensation,nanolithography,laser cooling,trapping of neutral atoms and the measurement of center-of-mass wave functions.
基金the Natural Science Foundation of Zhejiang Province of China(Grant No.LZ22A050002)the National Natural Science Foundation of China(Grant Nos.12074343 and 11835011)Muhammad Idrees acknowledges support from the postdoctoral fellowship of Zhejiang Normal University(Grant No.YS304123952).
文摘We present a flexible manipulation and control of solitons via Bose-Einstein condensates.In the presence of Rashba spin-orbit coupling and repulsive interactions within a harmonic potential,our investigation reveals the numerical local solutions within the system.By manipulating the strength of repulsive interactions and adjusting spin-orbit coupling while maintaining a zero-frequency rotation,diverse soliton structures emerge within the system.These include plane-wave solitons,two distinct types of stripe solitons,and odd petal solitons with both single and double layers.The stability of these solitons is intricately dependent on the varying strength of spin-orbit coupling.Specifically,stripe solitons can maintain a stable existence within regions characterized by enhanced spin-orbit coupling while petal solitons are unable to sustain a stable existence under similar conditions.When rotational frequency is introduced to the system,solitons undergo a transition from stripe solitons to a vortex array characterized by a sustained rotation.The rotational directions of clockwise and counterclockwise are non-equivalent owing to spin-orbit coupling.As a result,the properties of vortex solitons exhibit significant variation and are capable of maintaining a stable existence in the presence of repulsive interactions.
文摘In context with a recent announcement by the World Health Organization(WHO)holding an emergency towards an infectious illness indistinguishable from smallpox,monkeypox(mpox)carried a high case fatality(12%)[1,2].The variable distribution of cases during 2022-2023 in non-endemic regions i.e.,Europe(20000),China(1098),US(475),India(75),Japan(31),Pakistan(11)may cause an overwhelming demise with an additional burden on the economy[3].
基金supported by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2024R513),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Cross-Site Scripting(XSS)remains a significant threat to web application security,exploiting vulnerabilities to hijack user sessions and steal sensitive data.Traditional detection methods often fail to keep pace with the evolving sophistication of cyber threats.This paper introduces a novel hybrid ensemble learning framework that leverages a combination of advanced machine learning algorithms—Logistic Regression(LR),Support Vector Machines(SVM),eXtreme Gradient Boosting(XGBoost),Categorical Boosting(CatBoost),and Deep Neural Networks(DNN).Utilizing the XSS-Attacks-2021 dataset,which comprises 460 instances across various real-world trafficrelated scenarios,this framework significantly enhances XSS attack detection.Our approach,which includes rigorous feature engineering and model tuning,not only optimizes accuracy but also effectively minimizes false positives(FP)(0.13%)and false negatives(FN)(0.19%).This comprehensive methodology has been rigorously validated,achieving an unprecedented accuracy of 99.87%.The proposed system is scalable and efficient,capable of adapting to the increasing number of web applications and user demands without a decline in performance.It demonstrates exceptional real-time capabilities,with the ability to detect XSS attacks dynamically,maintaining high accuracy and low latency even under significant loads.Furthermore,despite the computational complexity introduced by the hybrid ensemble approach,strategic use of parallel processing and algorithm tuning ensures that the system remains scalable and performs robustly in real-time applications.Designed for easy integration with existing web security systems,our framework supports adaptable Application Programming Interfaces(APIs)and a modular design,facilitating seamless augmentation of current defenses.This innovation represents a significant advancement in cybersecurity,offering a scalable and effective solution for securing modern web applications against evolving threats.
基金financially supported by the Deanship of Scientific Research at King Khalid University under Research Grant Number(R.G.P.2/549/44).
文摘Algorithms for steganography are methods of hiding data transfers in media files.Several machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image analysis.Images with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for classification.To address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of images.Support Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or cover.The Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the proposedmethod.Using WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.
文摘Hepatitis C virus(HCV) is a potent human pathogen and is one of the main causes of chronic hepatitis round the world. The present review describes the evidencebased consensus on the diagnosis, prevention and management of HCV disease. Various techniques, for the detection of anti-HCV immunoglobulin G immunoassays, detection of HCV RNA by identifying virus-specific molecules nucleic acid testings, recognition of core antigen for diagnosis of HCV, quantitative antigenassay, have been used to detect HCV RNA and core antigen. Advanced technologies such as nanoparticlebased diagnostic assays, loop-mediated isothermal amplification and aptamers and Ortho trak-C assay have also come to the front that provides best detection results with greater ease and specificity for detection of HCV. It is of immense importance to prevent this infection especially among the sexual partners, injecting drug users, mother-to-infant transmission of HCV, household contact, healthcare workers and people who get tattoos and piercing on their skin. Management of this infection is intended to eradicate it out of the body of patients. Management includes examining the treatment(efficacy and protection), assessment of hepatic condition before commencing therapy, controlling the parameters upon which dual and triple therapies work, monitoring the body after treatment and adjusting the co-factors. Examining the treatment in some special groups of people(HIV/HCV co-infected, hemodialysis patients, renal transplanted patients).
基金supported by the National Natural Science Foundations of China(22150410340)the Chongqing Science&Technology Commission(catc2018jcyjax0582)。
文摘Methanol cross-over effects from the anode to the cathode are important parameters for reducing catalytic performance in direct methanol fuel cells.A promising candidate catalyst for the cathode in direct methanol fuel cells must have excellent activity toward oxygen reduction reaction and resistance to methanol oxidation reaction.This review focuses on the methanol tolerant noble metal-based electrocatalysts,including platinum and palladium-based alloys,noble metal–carbon based composites,transition metal-based catalysts,carbon-based metal catalysts,and metal-free catalysts.The understanding of the correlation between the activity and the synthesis method,electrolyte environment and stability issues are highlighted.For the transition metal-based catalyst,their activity,stability and methanol tolerance in direct methanol fuel cells and comparisons with those of platinum are particularly discussed.Finally,strategies to enhance the methanol tolerance and hinder the generation of mixed potential in direct methanol fuel cells are also presented.This review provides a perspective for future developments for the scientist in selecting suitable methanol tolerate catalyst for oxygen reduction reaction and designing high-performance practical direct methanol fuel cells.
基金funded by Prince Sultan University,Riyadh,Saudi Arabia。
文摘For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems.With the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is reduced.Matrix computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this algorithm.The proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its usefulness.By the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than EKRLS.This new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input data.Multiple experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.
文摘Zika virus is a new global threat for 2016 that has been swept to almost all Americas and is now posing serious threats to the entire globe.This deadly virus is playing havoc to unborn lives because of its reported association with upsurge of fetal deformation called microcephaly and neuropathic disorders including Guillain-Barrésyndrome.Till today,there is no vaccine prospect,antiviral therapy or licensed medical countermeasures to curb the teratogenic outcomes of this destructive viral infection.Diagnosis,treatment,chronicity and pathogenesis are still vague and unsettled.Therefore,this review article addresses all the aspects related to this disease to mitigate the explosive rise in Zika virus infection.
文摘Hybrid density functional theory was used to investigate the structural,electronic,magnetic and elastic properties of the Laves phase binary intermetallics RFe_(2)(R=La,Ce,Pr and Nd) in C_(15) crystal structure.The calculated lattice constants of these materials are found in good agreement with the experiments.The band structures and density of states distribution confirm the metallic nature of all these intermetallics.The optimized energies in different magnetic phases and magnetic susceptibilities by postDFT treatments confirm that all the understudy compounds are ferromagnetic in nature.Elastic parameters were calculated from the cubic elastic coefficients C_(11),C_(12) and C_(44).The elastic properties reveal that these intermetallics are incompressible,ductile,elastically anisotropic and mechanically stable.Based on the metallic nature and ferromagnetic properties,it is expected that these intermetallics are suitable materials for spintronic technology.
基金Supported by Ministry of Science & Technology Government of Pakistan Scientific Project Grant
文摘AIM: To assess the association between chronic hepatitis C virus (HCV) infection and hepatocellular carcinoma (HCC) in Pakistan, and the genotype distribution among these HCC patients.METHODS: One hundred and sixty-one subjects with HCC were included in this study. Liver biopsy was performed on 145 of the patients; sixteen were excluded because they failed to fulfill the inclusion criteria. Qualitative polymerase chain reaction (PCR) was performed for hepatitis B virus and HCV. Samples positive for HCV RNA were genotyped using genotype-specif ic PCR and conf irmed by HCV 5' noncoding region sequencing analysis. RESULTS: Chronic HCV infection was identified a major risk factor (63.44% of tested HCC patients) forthe development of HCC. The time from HCV infection to appearance of cancer was 10-50 years. In the HCC patient population, broader distributions of genotypes were present with genotype 3a as the predominant genotype. Using the type-specific genotyping method, we found HCV genotype 3a in 40.96%, 3b in 15.66%, 1a in 9.63%, and 1b in 2.40% of HCC tissue samples. About 28% of cases were found with mixed genotypes. Two cases were unable to be genotyped because of low viral load. Sixty-six percent of treated patients with cirrhosis had an end of treatment response, but unfortunately they relapsed quickly when the treatment was discontin-ued, and HCC developed during a median 3.8 years. CONCLUSION: There was a strong association between chronic HCV infection and HCC in Pakistan, and between HCV genotype 3a and HCC.
基金The authors acknowledge the support from the Ministry of Education and the Deanship of Scientific Research,Najran University,Saudi Arabia,under code number NU/-/SERC/10/616.
文摘In the Smart Grid(SG)residential environment,consumers change their power consumption routine according to the price and incentives announced by the utility,which causes the prices to deviate from the initial pattern.Thereby,electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability.Due to the massive amount of data,big data analytics for forecasting becomes a hot topic in the SG domain.In this paper,the changing and non-linearity of consumer consumption pattern complex data is taken as input.To minimize the computational cost and complexity of the data,the average of the feature engineering approaches includes:Recursive Feature Eliminator(RFE),Extreme Gradient Boosting(XGboost),Random Forest(RF),and are upgraded to extract the most relevant and significant features.To this end,we have proposed the DensetNet-121 network and Support Vector Machine(SVM)ensemble with Aquila Optimizer(AO)to ensure adaptability and handle the complexity of data in the classification.Further,the AO method helps to tune the parameters of DensNet(121 layers)and SVM,which achieves less training loss,computational time,minimized overfitting problems and more training/test accuracy.Performance evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark schemes.Our proposed method has achieved a minimal value of the Mean Average Percentage Error(MAPE)rate i.e.,8%by DenseNet-AO and 6%by SVM-AO and the maximum accurateness rate of 92%and 95%,respectively.
文摘One of the major concerns for the utilities in the Smart Grid(SG)is electricity theft.With the implementation of smart meters,the frequency of energy usage and data collection from smart homes has increased,which makes it possible for advanced data analysis that was not previously possible.For this purpose,we have taken historical data of energy thieves and normal users.To avoid imbalance observation,biased estimates,we applied the interpolation method.Furthermore,the data unbalancing issue is resolved in this paper by Nearmiss undersampling technique and makes the data suitable for further processing.By proposing an improved version of Zeiler and Fergus Net(ZFNet)as a feature extraction approach,we had able to reduce the model’s time complexity.To minimize the overfitting issues,increase the training accuracy and reduce the training loss,we have proposed an enhanced method by merging Adaptive Boosting(AdaBoost)classifier with Coronavirus Herd Immunity Optimizer(CHIO)and Forensic based Investigation Optimizer(FBIO).In terms of low computational complexity,minimized over-fitting problems on a large quantity of data,reduced training time and training loss and increased training accuracy,our model outperforms the benchmark scheme.Our proposed algorithms Ada-CHIO andAda-FBIO,have the low MeanAverage Percentage Error(MAPE)value of error,i.e.,6.8%and 9.5%,respectively.Furthermore,due to the stability of our model our proposed algorithms Ada-CHIO and Ada-FBIO have achieved the accuracy of 93%and 90%.Statistical analysis shows that the hypothesis we proved using statistics is authentic for the proposed technique against benchmark algorithms,which also depicts the superiority of our proposed techniques.
文摘Cloud computing is seeking attention as a new computing paradigm to handle operations more efficiently and cost-effectively.Cloud computing uses dynamic resource provisioning and de-provisioning in a virtualized environment.The load on the cloud data centers is growing day by day due to the rapid growth in cloud computing demand.Elasticity in cloud computing is one of the fundamental properties,and elastic load balancing automatically distributes incoming load to multiple virtual machines.This work is aimed to introduce efficient resource provisioning and de-provisioning for better load balancing.In this article,a model is proposed in which the fuzzy logic approach is used for load balancing to avoid underload and overload of resources.A Simulator in Matlab is used to test the effectiveness and correctness of the proposed model.The simulation results have shown that our proposed intelligent cloud-based load balancing system empowered with fuzzy logic is better than previously published approaches.
文摘Cellulases and hemicellulases are the main industrial sources from different microorganisms used to depolymerise plant biomass to simple sugars that are converted to chemical intermediates and biofuels, such as ethanol. Cellulases are formed adaptively, and several positive (xyr1, Ace2, HAP2/3/5) and negative (Ace1, Cre1) components involved in this regulation are now known. In this review, we summarise current knowledge about how cellulase biosynthesis is regulated, and outline recent approaches and suitable strategies for facilitating the targeted improvement of cellulase production by genetic engineering. Trichoderma reesei is the preferred organism for producing industrial cellulases. However, a more efficient heterologous expression system for enzymes from different organism is needed to further improve its cellulase mixture. In addition those optimizations of the promoter and linker for hybrid genes can dramatically improve the efficiency of heterologous expression of cellulase genes.
文摘Objective: To determine the breadth of Zika virus(ZIKV)-associated brain anomalies in neonates and adults. Methods: Systematic review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA) statement using electronic databases ScienceDirect, Pubmed, Medline, Scopus, and Global Health Library.Only those research articles, case studies, case-control studies, case-cohort studies, crosssectional studies, and organizational survey reports were included in the study that reported any fetal outcomes for pregnant women who had infected with ZIKV during the gestational period and ZIKV-related neurological complications in adults as well. Results: Out of total 72 retrieved articles, 50 met the inclusion criteria. We estimated a significant increase in incidence of neural abnormalities such as Guillain-Barre syndrome and microcephaly in the regions that are experiencing ZIKV outbreaks. Other neurological malformations found in ZIKV patients include hydrancephaly/hydrops fetalis, myasthenia gravis,meningoencephalitis and myelitis. Conclusion: Our systematic analysis provides the broad spectrum of neurological malformations in ZIKV infected patients and these data further support the causal link of ZIKV with neurological disorders.
文摘Zika virus(ZIKV) is rapidly spreading across the America and its devastating outcomes for pregnant women and infants have driven this previously ignored pathogen into the limelight.Clinical manifestations are fever,joint pain or rash and conjunctivitis.Emergence of ZIKV started with a first outbrcak in the Pacific arca in 2007.a second large outbreak occurred in the Pacific in 2013/2014 and subsequently the virus spread in other Pacific islands.Threat of explosive global pandemic and severe clinical complications linked with the more immediate and recurrent epidemics necessitate the development of an effective vaccine.Several vaccine platforms such as DNA vaccine,recombinant subunit vaccine.ZIKV purified inactivated vaccine,and chimeric vaccines have shown potent efficacy in ritro and in rim trials.Moreover,number of drugs such as Sofosbuvir.BCX4450.NITD008 and 7-DMA are ready to enter phase I clinical trial because of proven anti-ZIKV activity.Monoclonal based antibodies offer promise as an intervention effective for use in pregnant women.In this review,we describe the advances in research on ZIKV such as research strategies for the development of antiviral drugs & vaccines,molecular evolution,epidemiology emergence,neurological complications and other teratogenic outcomes as well as pathogenesis.
基金supported by the Zhejiang Provincial Natural Science Foundation of China under Grant No.LD18A040001the National Key Research and Development Program of China(No.2017YFA0304202)the National Natural Science Foundation of China(Grant No.11974309)。
文摘Herein,we propose a scheme for the realization of two-dimensional atomic localization in aλ-type three-level atomic medium such that the atom interacts with the two orthogonal standing-wave fields and a probe field.Because of the spatially dependent atom-field interaction,the information about the position of the atom can be obtained by monitoring the probe transmission spectra of the weak probe field for the first time.A single and double sharp localized peaks are observed in the one-wavelength domain.We have theoretically archived high-resolution and high-precision atomic localization within a region smaller thanλ/25×λ/25.The results may have potential applications in the field of nano-lithography and advance laser cooling technology.
