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Diclofenac sodium aqueous systems at low concentrations: Interconnection between physicochemical properties and action on hydrobionts

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Journal of Environmental Sciences 2020年第2期32卷 177-186页

作者： irina S.Ryzhkina Yuliya v.Kiseleva Lyaisan I.Murtazina Tatyana v.Kuznetsova Erik R.Zainulgabidinov Igor v.Knyazev Andrew M.Petrov Sergey E.Kondakov Alexander I.Konovalov Arbuzov Institute of Organic and Physical Chemistry FRC Kazan Scientific CenterRussian Academy of Sciences8 Arbuzov str.Kazan 420088Russia Institute for Problems of Ecology and Mineral Wealth Use of Tatarstan Academy of Sciences 28 Daurskaya Str.Kazan 420087Russia Lomonosov Moscow State University Chemistry Dept.1/3 Lenin HillsMoscow 119899Russia

Diclofenac sodium(DS) is a widely used nonsteroidal anti-inflammatory drug(NSAIDs).NSAIDs are poorly removed during standard wastewater *** consequences of the presence of NSAIDs in rivers and lakes at 10-11–10-8 mol/L are not yet established;therefore, ecotoxicologists have focused their efforts on studying the effect of lowconcentration NSAIDs on fish and hydrobionts, and also on predicting the potential risks to *** provides some information about the bioeffects of some NSAID solutions in low concentrations but there is no physicochemical explanation for these *** the physicochemical patterns of DS solutions in the low range of concentrations and establishing an interconnection between the solutions’ physicochemical properties and bioeffects can provide a conceptually new and important source of information regarding the unknown effects of *** physicochemical properties and action of DS solutions on Ceriodaphnia affinis cladocerans,Paramecium caudatum infusoria, Chlorella vulgaris unicellular green algae, as well as on the growth of the roots of Triticum vulgare wheat seeds, were studied in the calculated concentration range of 1 × 10-3–1 × 10-18 mol/*** relationship between these phenomena was established using the certified procedures for monitoring the toxicity of natural water and *** was shown for the first time that water solutions of DS are dispersed systems in which the dispersed phase undergoes a rearrangement with dilution, accompanied by changes in its size and properties, which affects the nonmonotonic dependences of the system’s physicochemical properties and could cause nonmonotonic changes in action on hydrobionts in the low concentration range.

关键词： Diclofenac sodium Low concentration Aqueous solutions Physicochemical properties Hydrobionts Toxicity

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Growth of Micropropagated Solanum tuberosum *** under Artificial Solar Spectrum and Different Mono-and Polychromatic LED Lights

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Horticultural Plant Journal 2022年第2期8卷 205-214页

作者： Olga v.Grishchenko Eugeny P.Subbotin irina v.Gafitskaya Yulia v.vereshchagina Elena v.Burkovskaya Yulia A.Khrolenko valeria P.Grigorchuk Olga v.Nakonechnaya victor P.Bulgakov Yuri N.Kulchin Federal Scientific Center of the East Asia Terrestrial Biodiversity Far Eastern Branch of the Russian Academy of SciencesVladivostok 690022Russia Institute of Automation and Control Processes Far Eastern Branch of the Russian Academy of SciencesVladivostok 690041Russia

In agriculture,LED light sources have increasingly replaced the standard luminescent lamps and have acquired an important role in plant *** studied the effect of different light sources such as narrow-band LEDs(bright blue,blue,green,yellow,deep red,and red)and wide-band LEDs(cold white,white,warm white,full spectrum,and an artificial solar spectrum sun box constructed by us)on development of potato plantlets in *** luminescent lamps were used as a *** light intensity of 49μmol·m^(-2)·s^(-1)was provided in all light *** showed that the long-wave narrow-band light treatments were inapplicable for potato micropropagation,because plantlets were weak with small leaves,inhibited roots,and significantly elongated *** lights provided growth of shortened plantlets with large leaves,well-growing roots,and abundant green *** chlorophyll content was lower under blue and bright blue light and was at the same level in the remained *** differences in the stomatal apparatus development were observed depending on the light *** differences were not always reflected in the plantlet phenotype:e.g.,plantlets under blue and bright blue lights showed no differences in any characteristics except stomatal density and size of stomatal guard *** found no significant effect of blue light portion in the white lights and full spectrum on plantlet *** artificial solar spectrum sun box was the most suitable for potato micropropagation,because it supported the development of plantlets with good fitness,uniform internodes length,abundant roots and green mass accumulation.

关键词： Solanum tuberosum LED Artificial solar light Growth Micropropagation

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IoT-Cloud Empowered Aerial Scene Classification for Unmanned Aerial vehicles

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Computers, Materials & Continua 2022年第3期70卷 5161-5177页

作者： K.R.Uthayan G.Lakshmi vara Prasad v.Mohan C.Bharatiraja irina v.Pustokhina Denis A.Pustokhin vicente García Díaz Department of Information Technology Sri Sivasubramaniya Nadar College of EngineeringChennai603110India Department of Information Technology QIS College of Engineering&TechnologyOngole523001India Department of Electronics and Communications Engineering Saranathan College of EngineeringTrichy620012India Department of Electrical and Electronics Engineering SRMInstitute of Science and TechnologyChennai603203India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Science University of OviedoOviedo33003Spain

Recent trends in communication technologies and unmanned aerial vehicles(UAvs)find its application in several areas such as healthcare,surveillance,transportation,***,the integration of Internet of things(IoT)with cloud computing environment offers several benefits for the UAv *** the same time,aerial scene classification is one of the major research areas in UAv-enabledMEC *** UAv aerial imagery,efficient image representation is crucial for the purpose of scene *** existing scene classification techniques generate mid-level image features with limited representation capabilities that often end up in producing average ***,the current research work introduces a new DL-enabled aerial scene classificationmodel *** presented model enables theUAvs to capture aerial imageswhich are then transmitted to MEC for further ***,CapsuleNetwork(CapsNet)-based feature extraction technique is applied to derive a set of useful feature vectors from the aerial *** is important to have an appropriate hyperparameter tuning strategy,since manual parameter tuning of DL model tend to produce several configuration *** order to achieve this and to determine the hyperparameters of CapsNetmodel,Shuffled Shepherd Optimization(SSO)algorithm is ***,Backpropagation Neural Network(BPNN)classification model is applied to determine the appropriate class labels of aerial *** performance of SSO-CapsNet model was validated against two openly-accessible datasets namely,UC Merced(UCM)Land Use dataset andWHU-RS *** proposed SSO-CapsNet model outperformed the existing state-of-the-art methods and achieved maximum accuracy of 0.983,precision of 0.985,recall of 0.982,and F-score of 0.983.

关键词： Artificial intelligence mobile edge computing unmanned aerial vehicles deep learning optimization

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Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

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Computers, Materials & Continua 2022年第8期72卷 2429-2444页

作者： Thavavel vaiyapuri K.Priyadarshini A.Hemlathadhevi M.Dhamodaran Ashit Kumar Dutta irina v.Pustokhina Denis A.Pustokhin College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electronics and Communication Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Panimalar Engineering CollegeChennai600123India Department of Electronics and Communication Engineering M.Kumarasamy College of EngineeringKarur639113India Department of Computer Science and Information System College of Applied SciencesAlMaarefa UniversityRiyadh11597Kingdom of Saudi Arabia Department of Entrepreneurship and Logistics Plekhanov Russian University of Economics117997MoscowRussia Department of Logistics State University of Management109542MoscowRussia

Due to global financial crisis,risk management has received significant attention to avoid loss and maximize profit in any *** the financial crisis prediction(FCP)process is mainly based on data driven decision making and intelligent models,artificial intelligence(AI)and machine learning(ML)models are widely *** article introduces an intelligent feature selection with deep learning based financial risk assessment model(IFSDL-FRA).The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or *** addition,the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection(WSOA-FS)manner to an optimum selection of feature ***,Deep Random vector Functional Link network(DRvFLN)classification technique was applied to properly allot the class labels to the financial ***,improved fruit fly optimization algorithm(IFFOA)based hyperparameter tuning process is carried out to optimally tune the hyperparameters of the DRvFLN *** enhancing the better performance of the IFSDL-FRA technique,an extensive set of simulations are implemented on benchmark financial datasets and the obtained outcomes determine the betterment of IFSDL-FRA technique on the recent state of art approaches.

关键词： Financial risks intelligent models financial crisis prediction deep learning feature selection metaheuristics

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Deep Learning Based Intelligent and Sustainable Smart Healthcare Application in Cloud-Centric IoT

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Computers, Materials & Continua 2021年第2期66卷 1987-2003页

作者： K.v.Praveen P.M.Joe Prathap S.Dhanasekaran I.S.Hephzi Punithavathi P.Duraipandy irina v.Pustokhina Denis A.Pustokhin Department of Information Technology St.Peters College of Engineering and TechnologyChennai600054India Department of Information Technology RMD Engineering CollegeChennai601206India Department of Computer Science and Engineering Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Computer Science and Engineering Sphoorthy Engineering CollegeHyderabad501510India Department of Electrical and Electronics Engineering J B Institute of Engineering and TechnologyHyderabad500075India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia

Recent developments in information technology can be attributed to the development of smart cities which act as a key enabler for next-generation intelligent systems to improve security,reliability,and *** healthcare sector becomes advantageous and offers different ways to manage patient information in order to improve healthcare service *** futuristic sustainable computing solutions in e-healthcare applications depend upon Internet of Things(IoT)in cloud computing *** energy consumed during data communication from IoT devices to cloud server is significantly high and it needs to be reduced with the help of clustering *** current research article presents a new Oppositional Glowworm Swarm Optimization(OGSO)algorithmbased clustering with Deep Neural Network(DNN)called OGSO-DNN model for distributed healthcare *** OGSO algorithm was applied in this study to select the Cluster Heads(CHs)from the available IoT *** selected CHs transmit the data to cloud server,which then executes DNN-based classification process for healthcare *** extensive simulation analysis was carried out utilizing a student perspective healthcare data generated from UCI repository and IoT devices to forecast the severity level of the disease among *** proposed OGSO-DNN model outperformed previous methods by attaining the maximum average sensitivity of 96.956%,specificity of 95.076%,the accuracy of 95.764%and F-score value of 96.888%.

关键词： IoT devices healthcare deep learning energy efficiency glowworm swarm optimization

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A pilot survey on antimicrobial activity and diversity of soil-derived actinobacteria from different depths in Gudzhirganskoe saline lake in Eastern Siberia

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Journal of Oceanology and Limnology 2023年第4期41卷 1307-1320页

作者： Qin YANG Puyu GUO Elena Y.ABIDUEvA Elena v.LAvRENTYEvA irina M.LISEvICH Ilya A.OSTERMAN Petr v.SERGIEv Shaowei LIU Chunmei XUE Chenghang SUN Department of Microbial Chemistry Institute of Medicinal BiotechnologyChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100050China Beijing Key Laboratory of Antimicrobial Agents Institute of Medicinal BiotechnologyChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100050China College of Life Sciences Jiamusi UniversityJiamusi 154000China Institute of General and Experimental Biology Siberian BranchRussian Academy of SciencesUlan-Ude 670047Russia Center of Life Sciences Skolkovo Institute of Science and TechnologyMoscow 101135Russia Department of Chemistry A.N.Belozersky Institute of Physico-Chemical BiologyLomonosov Moscow State UniversityMoscow 101135Russia

To explore pharmaceutical actinobacteria from salty environments in Siberia,8 soil samples were collected from different depths of Gudzhirganskoe saline lake,the Republic of Buryatia,***,635 actinobacterial strains affiliated with 21 genera in 12 families of 7 orders were obtained by culture-dependent *** predominant genus was Streptomyces(74.5%),followed by Microbacterium(4.9%),Agromyces(3.5%),Nocardiopsis(3.0%),and Kitasatospora(2.5%).Seven strains showed relatively low 16 S rRNA similarities(validly described ***-seven strains were selected as representatives to evaluate their antimicrobial activities and underlying mechanisms by paper-disk diffusion method and a double fluorescent protein reporter system(pDualrep 2),*** sp.S 6 b 3-1 was highlighted due to its strong inhibitory activities against Gram-positive bacteria and underlying antibacterial mechanism by inducing the SOS response in the reporter ***-1,(R)-6-[1-(benzoyloxy)ethyl]-phenazine-1-carboxylic acid,an analogue of saphenamycin was finally isolated from the culture broth of Streptomyces *** study preliminarily explored the actinobacterial diversity of soil samples collected in the highly alkaline and saline lake Gudzhirganskoe by culture-dependent approach and their capacity to produce antibiotics for the first time,which revealed that it deserves to make more efforts to discover new actinobacterial species and potential new antibiotics from the saline lake in Eastern Siberia.

关键词： Gudzhirganskoe saline lake actinobacteria diversity antimicrobial activities phenazine antibiotic

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An Intelligent Deep Learning Based Xception Model for Hyperspectral Image Analysis and Classification

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Computers, Materials & Continua 2021年第5期67卷 2393-2407页

作者： J.Banumathi A.Muthumari S.Dhanasekaran S.Rajasekaran irina v.Pustokhina Denis A.Pustokhin K.Shankar Department of Information Technology University College of EngineeringNagercoil629004India Department of Computer Science and Engineering University College of EngineeringRamanathapuram623513India Department of Computer Science and Engineering Kalasalingam Academy of Research and EducationKrishnankoil626128India Department of Electrical Engineering PSN College of EngineeringTirunelveli627152India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia Department of Computer Applications Alagappa UniversityKaraikudi630001India

Due to the advancements in remote sensing technologies,the generation of hyperspectral imagery(HSI)gets significantly *** classification of HSI becomes a critical process in the domain of hyperspectral data *** massive availability of spectral and spatial details of HSI has offered a great opportunity to efficiently illustrate and recognize ground ***,deep learning(DL)models particularly,convolutional neural networks(CNNs)become useful for HSI classification owing to the effective feature representation and high *** this view,this paper introduces a new DL based Xception model for HSI analysis and classification,called Xcep-HSIC ***,the presented model utilizes a feature relation map learning(FRML)to identify the relationship among the hyperspectral features and explore many features for improved classifier ***,the DL based Xception model is applied as a feature extractor to derive a useful set of features from the FRML *** addition,kernel extreme learning machine(KELM)optimized by quantum-behaved particle swarm optimization(QPSO)is employed as a classification model,to identify the different set of class *** extensive set of simulations takes place on two benchmarks HSI dataset,namely Indian Pines and Pavia University *** obtained results ensured the effective performance of the XcepHSIC technique over the existing methods by attaining a maximum accuracy of 94.32%and 92.67%on the applied India Pines and Pavia University dataset respectively.

关键词： Hyperspectral imagery deep learning xception kernel extreme learning map parameter tuning

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High Security for De-Duplicated Big Data Using Optimal SIMON Cipher

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Computers, Materials & Continua 2021年第5期67卷 1863-1879页

作者： A.Muthumari J.Banumathi S.Rajasekaran P.vijayakarthik K.Shankar irina v.Pustokhina Denis A.Pustokhin Department of Computer Science and Engineering University College of EngineeringRamanathapuram623513India Department of Information Technology University College of EngineeringNagercoil629004India Department of EEE PSN College of Engineering(Anna University)Tirunelveli627152India Department of Information Science and Engineering Sir M.Visvesvaraya Institute of TechnologyBangalore56215India Department of Computer Applications Alagappa UniversityKaraikudi63003India Department of Entrepreneurship and Logistics Plekhanov Russian University of EconomicsMoscow117997Russia Department of Logistics State University of ManagementMoscow109542Russia

Cloud computing offers internet location-based affordable,scalable,and independent *** computing is a promising and a cost-effective approach that supports big data analytics and advanced applications in the event of forced business continuity events,for instance,pandemic *** handle massive information,clusters of servers are required to assist the equipment which enables streamlining the widespread quantity of data,with elevated velocity and modified *** deduplication model enables cloud users to efficiently manage their cloud storage space by getting rid of redundant data stored in the *** deduplication also saves network *** this paper,a new cloud-based big data security technique utilizing dual encryption is *** clustering model is utilized to analyze the Deduplication process hash *** kernel Fuzzy C means(MKFCM)was used which helps cluster the data stored in cloud,on the basis of confidence data encryption *** confidence finest data is implemented in homomorphic encryption data wherein the Optimal SIMON Cipher(OSC)technique is *** security process involving dual encryption with the optimization model develops the productivity *** this paper,the excellence of the technique was confirmed by comparing the proposed technique with other encryption and clustering *** results proved that the proposed technique achieved maximum accuracy and minimum encryption time.

关键词： Cloud security deduplication clustering optimization big data dual encryption

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Photoluminescence of Ag-In-S/ZnS quantum dots: Excitation energy dependence and low-energy electronic structure

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Nano Research 2019年第7期12卷 1595-1603页

作者： irina v. Martynenko Anvar S. Baimuratov Florian Weigert Jose X. Soares Lorena Dhamo Philip Nickl Ilona Doerfel Jutta Pauli Ivan D. Rukhlenko Alexander v. Baranov Ute Resch-Genger Federal Institute for Materials Research and Testing (BAM) Unter den Eichen 8712205 BerlinGermany ITMO University 49 Kronverksky Pr.St. Petersburg197101Russia University of Porto Rua de Jorge Viterbo Ferreira2284050-313 PortoPortugal Institute of Photonics and Optical Sciences (IPOS) School of PhysicsThe University of SydneyCamperdown 2006NSWAustralia

Cd-free Ⅰ-Ⅲ-Ⅵ group semiconductor quantum dots (QDs) like Ag-ln-S and Cu-ln-S show unstructured absorption spectra with a pronounced Urbach tail,rendering the determination of their band gap energy (Eg) and the energy structure of the exciton ***,the origin of the broad photoluminescence (PL) band with lifetimes of several hundred nanoseconds is still *** encouraged us to study the excitation energy dependence (EED) of the PL maxima,PL spectral band widths,quantum yields (QYs),and decay kinetics of AlS/ZnS QDs of j different size,composition,and surface capping *** results were then correlated with the second derivatives of the corresponding absorption *** excellent match between the onset of changes in PL band position and spectral width with the minima found for the second derivatives of the absorption spectra underlines the potential of the EED approach for deriving Eg values of these ternary QDs from PL *** PL QY is,however,independent of excitation energy in the energy range *** the EED of the PL features of the AlS/ZnS QDs we could also derive a mechanism of the formation of the low-energy electronic *** was additionally confirmed by a comparison of the EED of PL data of as-synthesized and size-selected QD ensembles and the comparison of these PL data with PL spectra of single *** results indicate a strong contribution of intrinsic inhomogeneous PL broadening to the overall emission features of AlS/ZnS QDs originating from radiative transitions from a set of energy states of defects localized at different positions within the quantum dot volume,in addition to contributions from dimensional and chemical *** mechanism was confirmed by numerically modelling the absorption and PL energies with a simple mass approximation for spherical QDs and a modified donor-acceptor model,thereby utilizing the advantages of previously proposed PL mechanisms of ternary *** findings will

关键词： core/shell quantum dot silver indium sulfide defect photoluminescence photoluminescence quantum yield single-dot spectroscopy

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Design of QoS Aware Routing Protocol for IoT Assisted Clustered WSN

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Computers, Materials & Continua 2022年第5期71卷 3785-3801页

作者： Ashit Kumar Dutta S.Srinivasan Bobbili Prasada Rao B.Hemalatha irina v.Pustokhina Denis A.Pustokhin Gyanendra Prasad Joshi Department of Computer Science and Information Systems College of Applied SciencesAlmaarefa UniversityRiyadh13713Kingdom of Saudi Arabia Saveetha School of Engineering Saveetha Institute of Medical and Technical SciencesSaveetha NagarThandalamChennai602105India Department of Electrical and Electronics Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Electronics and Communication Engineering Thirumalai Engineering CollegeKancheepuram631551India Department of Entrepreneurship and Logistics Plekhanov Russian University of Economics117997MoscowRussia Department of Logistics State University of Management109542MoscowRussia Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea

In current days,the domain of Internet of Things(IoT)and Wireless Sensor Networks(WSN)are combined for enhancing the sensor related data transmission in the forthcoming networking *** and routing techniques are treated as the effective methods highly used to attain reduced energy consumption and lengthen the lifetime of the WSN assisted IoT *** this view,this paper presents an Ensemble of Metaheuristic Optimization based QoS aware Clustering with Multihop Routing(EMOQoSCMR)Protocol for IoT assisted *** proposed EMO-QoSCMR protocol aims to achieve QoS parameters such as energy,throughput,delay,and *** proposed model involves two stage processes namely clustering and ***,the EMO-QoSCMR protocol involves crossentropy rain optimization algorithm based clustering(CEROAC)technique to select an optimal set of cluster heads(CHs)and construct ***,oppositional chaos game optimization based routing(OCGOR)technique is employed for the optimal set of routes in the IoT assisted *** proposed model derives a fitness function based on the parameters involved in the IoT nodes such as residual energy,distance to sink node,*** proposed EMOQoSCMR technique has resulted to an enhanced NAN of 64 nodes whereas the LEACH,PSO-ECHS,E-OEERP,and iCSHS methods have resulted in a lesser NAN of 2,10,42,and 51 *** performance of the presented protocol has been evaluated interms of energy efficiency and network lifetime.

关键词： Internet of things wireless sensor networks clustering routing metaheuristics cluster head selection QoS parameters

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