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Geographic distribution of arsenic contamination in the Himalayan Rivers flowing through Pakistan: Implications for its natural source and effects of anthropogenic activities

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International Journal of Sediment Research 2023年第4期38卷 543-555页

作者： Ishtiaque Hussain Hafiz Ur.Rehman Takaaki Itai Junaid Ali Khattak Abida Farooqi Environmental Geochemistry Laboratory Department of Environmental Sciences Faculty of Biological Sciences Quaid-i-Azam University Department of Environmental Sciences University of Baltistan Skardu Graduate School of Sciences and Engineering Kagoshima University Department of Earth and Planetary Environmental Science (UG) Graduate School of Science The University of Tokyo Department of Earth and Planetary Physics (UG) Graduate School of Science The University of Tokyo Department of Earth and Planetary Science (GR) Graduate School of Science The University of Tokyo

Arsenic(As) in natural hydrological systems is known as a worldwide major environmental concern. A geochemical and sedimentological study was done to ascertain the origin and geographical distribution of As in surface water and fluvial sediment collected from the floodplains/basins of the River Indus and its four major tributaries that drain through the northern Pakistan. The hydrogeochemical compositions of all five rivers were similar with calcium(Ca2+) and bicarbonate(HCO3-) being the dominating ions. The concentration of As ranged from 0.62-24.05 μg/L(average 3.7 ± 3.5 μg/L, n = 61) in river water, 2.3-23.4 mg/kg(average 5.7 ± 3.9 mg/kg) in suspended sediment, and 2.0-13 mg/kg(average4.13 ± 2.3 mg/kg) in fluvial sediment. Various approaches were used, including mineralogical, sequential extraction, geochemical, and statistical analyses to investigate the distribution, behavior, and potential sources of As in the sediment. The effect of geological factors on the distribution of As was also studied.No noticeable changes in the relative abundance of minerals were observed in the sediment at different locations along the river. Both mineralogical and statistical analyses showed that silicate minerals like muscovite, biotite, and chloride are the main As reservoir while oxides minerals like hematite and magnetite, which are minor components in the sediment are second largest As carrier. A geochemical baseline, using the normalization and cumulative frequency distribution curves was constructed for As.The estimated mean human contribution of As was 3.4% in the Indus River, 1.9% in the Jhelum River, 13.7%in the Chenab River, 17.5% in the Ravi River and 5.4% in the Sutlej River, indicating relatively higher effects of anthropogenic activity along the Chenab River and Ravi River. The almost negligible effects of anthropogenic activities were additionally confirmed through the pollution assessment parameters estimated from the geo-enrichment, contamination factors, and accumulation index analyses. The current data sugg

关键词： Arsenic Indus basin Geochemical baseline Source Contamination assessment

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Studies on the effects of pre-firing and sintering temperature on NSDC nanocomposite electrolytes

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Progress in Natural Science:Materials International 2022年第1期32卷 128-134页

作者： Saddam hussain Yangping Li Fida hussain Memon Sabir hussain Lei Li Khalid hussain Thebo State Key Laboratory of Solidification Processing School of Materials Science and Engineering Northwestern Polytechnical University Department of Electrical Engineering Sukkur IBA University Department of Space Science University of the Punjab University of Chinese Academy of Sciences

Solid oxide fuel cells（SOFCs） technology, with fuel flexibility, is one of the most promising power generation technology. However, the high operating temperature of SOFCs has hindered their commercial applications. As a crucial requirement to enhance its performance, SOFCs electrolytes should operate at a low temperature. Carbonate/ceria composites are developed as electrolytes for low operating temperature SOFCs, and a better understanding of the mechanism of its ionic conductivity serves this purpose. In this work, ceria-carbonate composite electrolyte, Na;CO;/samarium doped ceria（NSDC） were synthesized by the co-precipitation method.The synthesized electrolytes were characterized by X-ray diffraction（XRD）, scanning electron microscopy（SEM）,X-ray photoelectron spectroscopy（XPS）, and UV–Vis spectroscopy. The XRD and SEM results showed that the sintered NSDC nanocomposite comprised a single-phase dense electrolyte structure. The crystallite size of the NSDC nanocomposite was greatly affected by the different pre-firing temperatures and different sintering temperatures. Also, the ionic conductivity of the prepared NSDC nanocomposite electrolytes was strongly dependent on the pre-firing and sintering temperatures. The NSDC nanocomposite electrolytes were pre-fired at 950°C and650°C and sintered at 1200°C and 900°C respectively, had ionic conductivity in H;and air high as 0.36 S/cm and 0.3 S/cm.

关键词： Solid oxide fuel cell NDSC Composite Electrolyte Ionic conductivity

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Optimization and comparative performance analysis of conventional and desiccant air conditioning systems regenerated by two different modes for hot and humid climates:Experimental investigation

Energy and Built Environment

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Energy and Built Environment 2023年第3期4卷 281-296页

作者： Taliv hussain Mechanical Engineering Department Aligarh Muslim UniversityAligarhIndia.202002

A desiccant air conditioning system is considered a capable alternative to a conventional air conditioning system because of its independent control of temperature,humidity and being eco-friendly.Also,to resolve the problem of more energy consumption for the restoration of a desiccant,structures comprising of desiccant can utilize thermal energy or complete waste heat to revive desiccant material.Therefore,this research work executes an experimental,optimization and comparative examination for conventional and desiccant air conditioning sys-tems regenerated by two different modes,i.***.firstly using(Mode-I)complete waste heat from condenser and secondly using(Mode-II)rod(electric heater)heat for regeneration at different process air inlet temperatures,i.e.(28,29.5,31,32.5,34,35.5 and 37°C),at different process air inlet velocities,i.e.(1.5,2.5,3.5 and 4.5 m/s)and a fix(2.5 m/s)regeneration air inlet velocity.Thus,optimization of performance parameters,i.e.VCOP,ECOP,dehumidification effectiveness,moisture removal capacity(kg/hr),DCOP,regeneration effectiveness and regeneration rate(kg/hr),is identified for achieving maximum efficiency of conventional and desiccant air con-ditioning systems under the above operating conditions.

关键词： Conventional air conditioning system Desiccant air conditioning system Mode-I,Mode-II,Optimization and performance parameters

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Optimal Islanding for Restoration of Power Distribution Systems Using Prim’s MST Algorithm

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CSEE Journal of Power and Energy Systems 2022年第2期8卷 599-608页

作者： Kaka Sanaullah Mingchao Xia Mazhar hussain Sharafat hussain Ammar Tahir the School of Electrical Engineering Beijing Jiaotong UniversityBeijing 10044China the School of Computer and Information Technology Beijing Jiaotong UniversityBeijing 10044China

Power systems can suffer outages,causing complete or partial disconnection of their power supply to load centers within the distribution networks.Distributed Generation(DG)plays an essential role in power systems.DG can be used as a back-up power source to enhance the resiliency and reliability of a power system.Island mode operations after outages in an active distributing network(ADN)is an effective way to maintain continuity of the power supply to significant loads.It is a quite complicated task for power system operators to find the power flow path.Previous studies have primarily used pre-defined guidelines to find feasible power flow paths,and have focused on multiple islands for restoration.In these studies,possible restoration pathfinding with DG was the fundamental weakness,and furthermore,the power of DG was limited to pre-defined boundaries in the form of islands.Therefore,in this study,a new algorithm has been proposed,which uses the minimum spanning tree(MST)method to find the most feasible path.The proposed algorithm starts at any random node(in this case,DG),and progresses by selecting the next node with the least cost(weight),thus considering all the nodes through which power will flow.The proposed model is formulated as a multiobjective program considering the priority of loads and minimum power loss.The effectiveness of the proposed model is tested on a modified IEEE69-bus distribution system with the penetration of multiple distributed generation sources at different nodes.Results were compared with the strategies found in literature,and the proposed method was found to be feasible and efficient.

关键词： Active distribution network distributed generation islanding multi-objective minimum spanning tree

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Heavy Metal/Metalloid Indexing and Balances in Agricultural Soils: Methodological Approach for Research

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Phyton-International Journal of Experimental Botany 2022年第12期91卷 2687-2697页

作者： Shahid hussain Department of Soil Science Faculty of Agricultural Sciences and TechnologyBahauddin Zakariya UniversityMultan60800Pakistan

Heavy metal(loid)accumulation in agricultural soils is a threat to the soil capacity,quality,and productivity.It also increases human exposure to heavy metal(loid)s via consumption of contaminated plant-based foods.The detrimental effects of soil contamination also deteriorate the environment of plants and animals.For sustainable agriculture,therefore,the soil must be protected from toxic levels of heavy metal(loid)s.Studies on heavy metal(loid)balances in agricultural soils are important in predicting future risks to sustainable production from agro-ecological zones and human exposure to heavy metal(loid)s.The latest and continuous indexing of the problem seems a prerequisite for sustainable agriculture.This review provides some background information and then summarizes key methodological approaches for studies on indexing and balance of heavy metal(loid)s in agricultural soils.In the end,important soil and health indices are explained that may be useful in understanding the extent of the problem.The provided information would contribute to sustainable heavy metal(loid)management in the agricultural soils,high crop production,better soil protection,and ultimately to human health.

关键词： Food crops health risks soil contamination sustainable agriculture

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Effect of dark energy models on the energy content of charged and rotating black holes

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Chinese Physics C 2022年第1期46卷 196-206页

作者： Asia Liaqat Ibrar hussain School of Natural Sciences National University of Sciences and TechnologyH-12IslamabadPakistan School of Electrical Engineering and Computer Science National University of Sciences and TechnologyH-12IslamabadPakistan

The energy content of the charged-Kerr(CK)spacetime surrounded by dark energy(DE)is investigated using approximate Lie symmetry methods for the differential equations.For this,we consider three different DE scenarios:cosmological constant with an equation of state parameter$ω_(q)=-2/3,quintessence DE with an equation of state parameterω_(c)=-1,and a frustrated network of cosmic strings with an equation of state parameterω_(n)=-1/3.To study the gravitational energy of the CK black hole surrounded by the DE,we explore the symmetries of the 2nd-order perturbed geodesic equations.It is noticed,for all the values ofω,the exact symmetries are recovered as 2nd-order approximate trivial symmetries.These trivial approximate symmetries give the rescaling of arc length parameter s in this spacetime which indicates that the energy in the underlying spacetime has to be rescaled by a factor that depends on the black hole parameters and the DE parameter.This rescaling factor is compared with the factor of the CK spacetime found in[hussain et al.Gen.Relativ.Gravit.(2009)]and the effects of the DE on it are discussed.It is observed that for all the three values of the equation of state parameterω,the effect of DE results in decreased energy content of the black hole spacetime,regardless of values of the charge Q,spin a and the DE parameterα.This reduction in the energy content due to the involvement of the DE favours the idea of mass reduction of black holes by accretion of DE given by[Babichev et al.Phys.Rev.Lett.(2004)].

关键词： approximate Lie symmetries dark energy charged-Kerr black hole surrounded by dark energy energy content

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Invariant of Enhanced AES Algorithm Implementations Against Power Analysis Attacks

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Computers, Materials & Continua 2022年第7期72卷 1861-1875页

作者： Nadia Mustaqim Ansari Rashid hussain Sheeraz Arif Syed Sajjad hussain Department of Electronic Engineering Dawood University of Engineering&TechnologyKarachiPakistan Faculty of Engineering Sciences and Technology Hamdard UniversityKarachiPakistan Faculty of Information Technology Salim Habib UniversityKarachiPakistan Faculty of Computer Sciences SZABISTKarachiPakistan

The security of Internet of Things(IoT)is a challenging task for researchers due to plethora of IoT networks.Side Channel Attacks(SCA)are one of the major concerns.The prime objective of SCA is to acquire the information by observing the power consumption,electromagnetic(EM)field,timing analysis,and acoustics of the device.Later,the attackers perform statistical functions to recover the key.Advanced Encryption Standard(AES)algorithm has proved to be a good security solution for constrained IoT devices.This paper implements a simulation model which is used to modify theAES algorithm using logicalmasking properties.This invariant of the AES algorithm hides the array of bits during substitution byte transformation of AES.This model is used against SCAand particularly Power Analysis Attacks(PAAs).Simulation model is designed on MATLAB simulator.Results will give better solution by hiding power profiles of the IoT devices against PAAs.In future,the lightweight AES algorithm with false key mechanisms and power reduction techniques such as wave dynamic differential logic(WDDL)will be used to safeguard IoT devices against side channel attacks by using Arduino and field programmable gate array(FPGA).

关键词： Side channel attacks power analysis attacks network security masking advance encryption standard

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Efficient maximum power point tracker based on neural network and sliding-mode control for buck converters

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Clean Energy 2022年第5期6卷 716-725页

作者： hussain Attia Khaled Hossin Department of Electrical and Electronic Engineering American University of Ras Al KhaimahRas Al KhaimahUnited Arab Emirates Department of Mechanical and Industrial Engineering American University of Ras Al KhaimahRas Al KhaimahUnited Arab Emirates

This paper presents detailed design steps of an effective control system aiming to increase the solar energy harvested via photovoltaic power-generation systems.The design of an intelligent maximum power point tracker(MPPT)supported by a robust sliding-mode(SM)controller is discussed in this study.The proposed control scheme is designed to track the MPP and provide a smooth system response by removing the overshoot in the load current during any variation in the connected load.Such a system is suitable for DC-DC buck converter applications.The study begins with modelling the buck converter for a continuous current mode operation.The reference voltage of the tracking system is produced by the proposed neural network(NN)algorithm.The proposed intelligent MPPT integrated with an SM controller is simulated in a MATLAB®/Simulink®platform.The simulation results are analysed to investigate and confirm the satisfaction level of the adopted four-serially connected PV-modules system.The system performance is evaluated at a light intensity of 500 W/m^(2) and an ambient temperature of 25°C.Applying only the proposed NN algorithm guarantees the MPP tracking response by delivering 100 W at a resistive load of 13Ω,and 200 W at a load of 6.5Ω,respectively,with 99.77%system efficiency.However,this simultaneously demonstrates a current spike of~0.5 A when the load is varied from 50%to 100%.The integrated SM controller demonstrates a robust and smooth response,eliminating the existing current spike.

关键词： photovoltaic panel neural network algorithm MPPT sliding-mode controller buck converter

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Optimizing Optical Fiber Faults Detection:A Comparative Analysis of Advanced Machine Learning Approaches

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Computers, Materials & Continua 2024年第5期79卷 2697-2721页

作者： Kamlesh Kumar Soothar Yuanxiang Chen Arif hussain Magsi Cong Hu hussain Shah School of Electronics Engineering Beijing University of Posts and TelecommunicationsBeijing100876China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an710071China State Key Laboratory ofNetworking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)satisfaction.The emerging faultsin optical networks introduce challenges that can jeopardize the network with a variety of faults.The existingliterature witnessed various partial or inadequate solutions.On the other hand,Machine Learning(ML)hasrevolutionized as a promising technique for fault detection and prevention.Unlike traditional fault managementsystems,this research has three-fold contributions.First,this research leverages the ML and Deep Learning(DL)multi-classification system and evaluates their accuracy in detecting six distinct fault types,including fiber cut,fibereavesdropping,splicing,bad connector,bending,and PC connector.Secondly,this paper assesses the classificationdelay of each classification algorithm.Finally,this work proposes a fiber optics fault prevention algorithm thatdetermines to mitigate the faults accordingly.This work utilized a publicly available fiber optics dataset namedOTDR_Data and applied different ML classifiers,such as Gaussian Naive Bayes(GNB),Logistic Regression(LR),Support Vector Machine(SVM),K-Nearest Neighbor(KNN),Random Forest(RF),and Decision Tree(DT).Moreover,Ensemble Learning(EL)techniques are applied to evaluate the accuracy of various classifiers.In addition,this work evaluated the performance of DL-based Convolutional Neural Network and Long-Short Term Memory(CNN-LSTM)hybrid classifier.The findings reveal that the CNN-LSTM hybrid technique achieved the highestaccuracy of 99%with a delay of 360 s.On the other hand,EL techniques improved the accuracy in detecting fiberoptic faults.Thus,this research comprehensively assesses accuracy and delay metrics for various classifiers andproposes the most efficient attack detection system in fiber optics.

关键词： Fiber optics fault detection multiclassification machine learning ensemble learning

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Assessing the effectiveness of community managed forests for plant diversity conservation in Meghalaya,Northeast India

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Plant Diversity 2022年第3期44卷 243-254页

作者： Aabid hussain Mir Kiranmay Sarma Krishna Upadhaya Department of Environmental Studies North-Eastern Hill UniversityShillong793022MeghalayaIndia University School of Environment Management Guru Gobind Singh Indraprastha UniversityDwarka 16CNew Delhi110075India Department of Basic Sciences and Social Sciences North-Eastern Hill UniversityShillong793022MeghalayaIndia

In the state Meghalaya,northeast India,>80%of the forest lands are owned by local communities and managed by traditional institutions.These forests are under severe threats due to a number of human disturbances.The present study was conducted to assess the plant diversity and identify the community forests for priority conservation in Khasi Hills of Meghalaya.Floristic explorations carried out in the 87 forests reveals the presence of 1300 plant species of which 400 are either rare,endemic or threatened.Of the different forest categories,reserve forests had the highest number of species(1190),followed by sacred forests(987 species)and village forests(786 species).Majority of the forests(56)had high-species richness,irreplaceability level(42 forests)and vulnerability level(54).In terms of area,13.8%(1666.8 ha)fall under low risk while 1855 ha under high risk zone.High risk zone was mostly represented by village forests.An area of 7661.56 ha of community forests falls under high priority category and hence calls for immediate conservation actions.The conservation priority map generated in the present study will help to concentrate the protection strategy to the demarcated and adjoining areas and help conservationists and planners to evolve effective strategies for conservation of the community forests.

关键词： Conservation Disturbance Endemic Rare Threatened Village forest

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