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Journal of Innovative Optical Health Sciences 2012年第3期5卷 1-7页

作者： V.K.gOSTISHCHEV V.A.KHOMENKO A.g.KUZMINA g.p.KUZMIN g.B.IVAKHOV O.g.gApONENKO First Moscow State Medical University by I.M.Sechenov 119992 Mochovaya 11MoscowRussia Central TB Research Institute of the Russian Academy of Medical Sciences 107564 Yauzskaya Alley2MoscowRussia prokhorov general physics Institute of the Russian Academy of Sciences 119991 Vavilov 38MoscowRussia SpC Spectrolux MoscowRussia

The adequate method of antibiotic choice is reported using the laserfluorescence analysis of blood plasma with the laboratory diagnostic device"Spectrolux-MB".The method is based on the ability of micro-organisms and products of their vital functions(metabolism)tofluoresce under laser *** method offluorescence analysis has great prospects in urgent surgery and other medicine brunches due to its high information content,low cost(compared to other methods of express-diagnostics)and high speed of information acquisition.

关键词： Fluorescence antibiotic express-diagnosis sepsis

Convergence in leaf phenology traits of two understorey ferns in the northwestern Iberian peninsula

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Journal of plant Ecology 2018年第1期11卷 92-102页

作者： Luis g.Quintanilla Beatriz pías Department of Biology and geology Physics and Inorganic ChemistrySchool of Environmental Sciences and TechnologyRey Juan Carlos Universityc/Tulipán s/n28933 MóstolesMóstolesSpain Department of plant Sciences Faculty of BiologyComplutense of Madrid UniversityMadridSpain

Aims plants control leaf phenology to maximize annual photosynthetic *** ferns play an important ecological role in many habitats,especially forests,their phenology traits have been poorly ***,we investigate the leaf phenology of two ferns of the forest understorey and analyse the relationship between the timing of leaf emergence and spore dispersal and the effect of between-year climatic *** We compared the leafing and sporing phenologies of two ferns with very large(>2 m),overwintering leaves:Culcita macrocarpa and Woodwardia *** regularly monitored individuals of six popu-lations in the northwestern Iberian peninsula during a 3-year *** studied eight phenology variables:leafing start date,leafing end date,leaf expansion time,number of new leaves per individual,between-individual synchrony,within-individual synchrony,percentage of fertile leaves and spore release *** also determined leaf mass per area(LMA)and gathered data on air temperature and *** findings Both *** and *** produce few leaves(~2 leaves individual−1 year−1),which expand simultaneously for a very long period(from midwinter to early summer),are retained for more than 1 year(37 and 19 months,respectively)and have relatively high *** traits,together with large leaf size,have also been found in seed plants from the forest understorey and represent adap-tations to this light-limited *** of both study ferns are simultaneously released in late winter,with little between-year variation caused by differences in air *** remarkable similarity between species suggests that the convergence in tim-ing of leaf emergence favours the convergence in timing of spore dispersal.

关键词： Culcita macrocarpa leaf phenology spore dispersal temperate forest Woodwardia radicans

Optimized Deep Learning Model for Effective Spectrum Sensing in Dynamic SNR Scenario

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Computer Systems Science & Engineering 2023年第5期45卷 1279-1294页

作者： g.Arunachalam p.SureshKumar Department of Electronics and Communication Engineering Gnanamani College of TechnologyNamakkalTamil NaduIndia Department of Electrical and Electronics Engineering Mahendra Engineering College(Autonomous)NamakkalTamil NaduIndia

The main components of Cognitive Radio networks are primary Users(pU)and Secondary Users(SU).The most essential method used in Cognitive networks is Spectrum Sensing,which detects the spectrum band and opportunistically accesses the free white areas for different *** the free spaces helps to increase the spectrum *** the existing spectrum sensing techniques such as energy detectors,cyclo-stationary detectors suffer from various problems such as complexity,non-responsive behaviors under low Signal to Noise Ratio(SNR)and computational overhead,which affects the performance of the sensing *** algorithms such as Long-Short Term Memory(LSTM),Convolutional Neural Networks(CNN),and Recurrent Neural Networks(RNN)play an important role in designing intelligent spectrum sensing techniques due to the excellent learning ability of deep learning frameworks,but still require improvisation in terms of sensing accuracy under dynamic environmental *** paper,we propose the novel and hybrid CNN-Cuttle-Fish Optimized Long Short Term Memory(COLSTM),an improved version of LSTM that is well suited for the dynamic changes of environmental SNR with less computational overhead and *** proposed COLSTM based spectrum sensing technique exploits the various statistical features from spectrum data of pU to improve the sensing ***,the addition of shuttle-fish optimization in LSTM has reduced the computational overhead and complexity which in turn enhanced the sensing *** proposed methodology is validated on spectrum data acquired using Raspberrypi-RTLSDR experimental *** proposed spectrum sensing technique and the existing classical spectrum sensing techniques are *** results show that the proposed scheme has shown the brighter enhancement of performance under different SNR ***,the improvised performance has been achieved at low complexity and low computational over

关键词： Spectrum sensing cuttle-fish long short term memory raspberry pilow SNR convolutional neural networks

An Intelligent Hybrid Ensemble gene Selection Model for Autism Using DNN

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Intelligent Automation & Soft Computing 2023年第3期35卷 3049-3064页

作者： g.Anurekha p.geetha Department of Information Science and Technology College of EngineeringAnna UniversityChennai600025India

Autism Spectrum Disorder(ASD)is a complicated neurodevelopmen-tal disorder that is often identiﬁed in *** microarray data is used as a diagnostic tool to identify the genetics of the ***,microarray data is large and has a high ***,it suffers from the problem of *** microarray data,the sample size and variance of the gene expression will lead to overﬁtting and misclassiﬁ*** the autism gene(feature)subset from microarray data is an important and challenging research *** has to be efﬁciently addressed to improve gene feature selection and classiﬁ*** overcome the challenges,a novel Intelligent Hybrid Ensem-ble gene Selection(IHEgS)model is proposed in this *** proposed model integrates the intelligence of different feature selection techniques over the data *** this model,the initial gene selection is carried out by data perturba-tion,and theﬁnal autism gene subset is obtained by functional perturbation,which reduces the problem of dimensionality in microarray *** functional perturbation module employs three meta-heuristic swarm intelligence-based tech-niques for gene *** obtained gene subset is validated by the Deep Neural Network(DNN)*** proposed model is implemented using python with six National Center for Biotechnology Information(NCBI)gene expression *** the comparative study with other existing state-of-the-art systems,the proposed model provides stable results in terms of feature selection and clas-siﬁcation accuracy.

关键词： Autism spectrum disorder feature selection ensemble gene selection microarray gene expression deep neural network meta-heuristic

On-line Ladle Lining Temperature Estimation by Using Bounded Jacobian Nonlinear Observer

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Journal of Iron and Steel Research International 2016年第8期23卷 792-799页

作者： g.pHANOMCHOENg S.CHANTRANUWATHANA p.CHARUNYAKORN Mechanical Engineering Department Chulalongkorn University

The knowledge of transient temperature of the ladle wall is a key factor in optimizing energy consumption in steelmaking *** transient temperature needs to be estimated.A nonlinear lumped parameter model was used to model the thermal dynamics of the ***,the bounded Jacobian nonlinear observer was utilized to estimate the *** this method,the estimation model became a closed-loop model and the observer gains were obtained by solving linear matrix inequalities and simply implemented to the *** between the simulation and recorded data at a participating steel plant in Thailand showed that the nonlinear observer accurately estimated the temperature of the ladle *** estimated temperature was very useful in determining suitable tapping temperature for energy conservation and steel quality.

关键词： observer Observer Jacobian utilized gains participating determining simply Thailand optimizing

Targeting mitoNEET with pioglitazone for therapeutic neuroprotection after spinal cord injury

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Neural Regeneration Research 2017年第11期12卷 1807-1808页

作者： Alexander g.Rabchevsky Samir p.patel patrick g.Sullivan Spinal Cord and Brain Injury Research Center University of KentuckyLexingtonKYUSA Departments of physiology University of KentuckyLexingtonKYUSA Departments of Neuroscience University of KentuckyLexingtonKYUSA Veterans Administration Medical Center University of KentuckyLexingtonK.YUSA

There is mounting evidence that targeting mitochondrial dysfunction following neurotrauma could be key in developing effective therapeutic strategies since mitochondria are known to play a major role in cellular bioenergetics, function, and survival following traumatic spinal cord injury （SCI）（Rabchevsky et al., 2011）. Our research group is one of the pioneers in targeting mitochondrial dysfunction to foster functional neuroprotection, having documented that phar- macological maintenance of mitochondrial function acutely results in long-term neuroprotection and improved function- al recover. We have recently reported that treatment with the pleiotropic drug, pioglitazone, maintains acute mitochondrial integrity correlated with chronic tissue sparing and functional recovery after contusion SCI, but that this was not correlated with altered neuroinflammation （patel et al., 2017）. We herein propose that the mechanism（s） by which pioglitazone confers neuroprotection may not be entirely dependent upon its activation of peroxisome proliferator activated receptor （ppAR）,

关键词： Targeting mitoNEET therapeutic neuroprotection

Classifying Hematoxylin and Eosin Images Using a Super-Resolution Segmentor and a Deep Ensemble Classifier

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Intelligent Automation & Soft Computing 2023年第8期37卷 1983-2000页

作者： p.Sabitha g.Meeragandhi Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennaiTamilnaduIndia

Developing an automatic and credible diagnostic system to analyze the type,stage,and level of the liver cancer from Hematoxylin and Eosin(H&E)images is a very challenging and time-consuming endeavor,even for experienced pathologists,due to the non-uniform illumination and *** several Machine Learning(ML)and Deep Learning(DL)approaches are employed to increase the performance of automatic liver cancer diagnostic systems,the classi-ﬁcation accuracy of these systems still needs signiﬁcant improvement to satisfy the real-time requirement of the diagnostic *** this work,we present a new Ensemble Classiﬁer(hereafter called ECNet)to classify the H&E stained liver histopathology images *** proposed model employs a Dropout Extreme Learning Machine(DrpXLM)and the Enhanced Convolutional Block Attention Modules(ECBAM)based residual *** applies Voting Mechanism(VM)to integrate the decisions of individual classiﬁers using the average of probabilities ***,the nuclei regions in the H&E stain are seg-mented through Super-resolution Convolutional Networks(SrCN),and then these regions are fed into the ensemble DL network for classiﬁ*** effectiveness of the proposed model is carefully studied on real-world *** results of our meticulous experiments on the Kasturba Medical College(KMC)liver dataset reveal that the proposed ECNet signiﬁcantly outperforms other existing classiﬁca-tion networks with better accuracy,sensitivity,speciﬁcity,precision,and Jaccard Similarity Score(JSS)of 96.5%,99.4%,89.7%,95.7%,and 95.2%,*** obtain similar results from ECNet when applied to The Cancer genome Atlas Liver Hepatocellular Carcinoma(TCgA-LIHC)dataset regarding accuracy(96.3%),sensitivity(97.5%),speciﬁcity(93.2%),precision(97.5%),and JSS(95.1%).More importantly,the proposed ECNet system consumes only 12.22 s for training and 1.24 s for ***,we carry out the Wilcoxon statistical test to determine whether the ECN

关键词： Convolutional block attention modules dropout ELM ensemble classiﬁer liver cancer segmentation voting mechanism

Comparison between two tritrophic food chain models with multiple delays and anti-predation effect

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International Journal of Biomathematics 2021年第3期14卷 53-100页

作者： Debgopal Sahoo g.p.Samanta Department of Mathematics Indian Institute of Engineering Science and Technology Shibpur Howrah-711103India

Exploring the predator prey linkage in food chain system is the most familiar research work in population ***,some research experiments show that predator-prey interaction not only governed by direct hunting but also influenced by some indirect effect such as fear effect(felt by prey)that may change the physiological behavior of *** upon this fact,we consider a tritrophic food chain model incorporating with anti-predation response(fear effect)and multiple time delays for biomass conversion from prey to middle predator and middle to top *** analyze the resulting delay differential equations and explore how the anti-predation response level affects the population *** also investigate the effect of delay parameters,for which the model system switches its stability through *** compare all of our results between two different food chain models consisting of two different functional *** numerical simulations are performed to validate the effectiveness of the derived theoretical results.

关键词： Food chain functional response anti-predation response digestion delay Hopf-bifurcation

Analysis of a predator-prey model with herd behavior and disease in prey incorporating prey refuge

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International Journal of Biomathematics 2019年第1期12卷 133-171页

作者： Sangeeta Saha g.p.Samanta Department of Mathematics Indian Institute of Engineering Science and Technology Shibpur Howrah-711103India

In this work,we have introduced an eco-epidemiological model of an infected predator prey *** of prey refuge gives that a fraction of the infected prey is available to the predator for ***,to make the model more realistic to the environment,we have introduced strong Allee effect in the susceptible *** and positivity of the solution have been *** stability conditions of the equilibrium points have been found with the help of Routh-Hurwitz criterion and it has been observed that if a prey population is infected with a lethal disease,then both the prey(susceptible and infected)and predator cannot survive simultaneously in the system for any parametric *** disease transmission rate and the attack rate on the susceptible have an important role to control the system *** different values of these two key parameters,we have got only healthy or disease-free or predation-free or a fluctuating disease-free or even a fluctuating predator-free system with some certain parametric conditions.

关键词： Allee effect herd behavior infected prey refuge extinction bifurcations

Topology Driven Cooperative Self Scheduling for Improved Lifetime Maximization in WSN

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Computer Systems Science & Engineering 2023年第4期45卷 445-458页

作者： g.Brindha p.Ezhilarasi Department of Electronics and Communication Engineering Meenakshi College of EngineeringChennai600078India Department of Electronics and Communication Engineering St.Joseph’s College of EngineeringChennai600119India

In Wireless Sensor Network(WSN),scheduling is one of the important issues that impacts the lifetime of entire *** scheduling schemes have been proposed earlier to increase the lifetime of the ***,the results from such methods are compromised in terms of achieving high *** this objective to increase the lifetime of network,an Efficient Topology driven Cooperative Self-Scheduling(TDCSS)model is recommended in this *** of scheduling the network nodes in a centralized manner,a combined approach is *** on the situation,the proposed TDCSS approach performs scheduling in both the *** sharing the node statistics in a periodic manner,the overhead during the transmission of control packets gets *** in turn impacts the lifetime of all the ***,this also reduces the number of idle conditions of each sensor node which is required for every *** proposed method enables every sensor to schedule its own conditions according to duty cycle and topology *** scheduler monitors the network conditions whereas total transmissions occurs at every *** to this,the source can infer the possible routes in a cycle and approximate the available ***,based on the statistics of previous transmissions,the routes towards the sink are *** the routes found,a single optimal route with energy efficiency is selected to perform data *** cooperative approach improves the lifetime of entire network with high throughput performance.

关键词： WSN self-scheduling TDCSS scheduling lifetime maximization quality of service