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Impact of depression on in-hospital outcomes for adults with type 2 myocardial infarction:A United States population-based analysis

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World Journal of Cardiology 2024年第7期16卷 412-421页

作者： sivaram Neppala Himaja Dutt Chigurupati Shaylika Chauhan Mrunal Teja Chinthapalli Rupak Desai Department of Internal Medicine University of Texas at San AntonioSan AntonioTX 78249United States Department of Internal Medicine New York Medical College at Saint Michael’s Medical CenterNewarkNJ 07102United States Department of Internal Medicine Geisinger Health SystemWikes-BarrePA 18702United States Department of Internal Medicine Mayo ClinicRochesterMN 55905United States Independent Researcher AtlantaGA 30079United States

BACKGROUND Type 2 myocardial infarction(T2MI)is an ischemic myocardial injury in the context of oxygen supply/demand mismatch in the absence of a primary coronary ***,though there is a rising prevalence of depression and its potential association with type 1 myocardial infarction(T1MI),data remains nonexistent to evaluate the asso-ciation with *** To identify the prevalence and risk of T2MI in adults with depression and its impact on the in-hospital *** We queried the National Inpatient Sample(2019)to identify T2MI hospitalizations using Internal Classification of Diseases-10 codes in hospitalized adults(≥18 years).In addition,we compared sociodemographic and comorbidities in the T2MI cohort with vs without comorbid ***,we used multivariate regression analysis to study the odds of T2MI hospitalizations with vs without depression and in-hospital outcomes(all-cause mortality,cardiogenic shock,cardiac arrest,and stroke),adjusting for *** significance was RESULTS There were 331145 adult T2MI hospitalizations after excluding T1MI(median age:73 years,52.8%male,69.9%white);41405(12.5%)had depression,the remainder;289740 did not have *** analysis revealed lower odds of T2MI in patients with depression vs without[adjusted odds ratio(aOR)=0.88,95%confidence interval(CI):0.86-0.90,P=0.001].There was the equal prevalence of prior MI with any revascularization and a similar prevalence of peripheral vascular disease in the cohorts with depression vs without *** is a greater prevalence of stroke in patients with depression(10.1%)vs those without(8.6%).There was a slightly higher prevalence of hyperlipidemia in patients with depression vs without depression(56.5%vs 48.9%),as well as obesity(21.3%vs 17.9%).There was generally equal prevalence of hypertension and type 2 diabetes mellitus in both *** was no significant difference in elective and non-elective admissions frequency b

关键词： Type 2 myocardial infarction Depression Major adverse cardiovascular events Mortality Stroke Cardiac arrest Outcomes

Intelligent recognition system for viewpoint variations on gait and speech using CNN-CapsNet

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International Journal of Intelligent Computing and Cybernetics 2022年第3期15卷 363-382页

作者： G.Merlin Linda N.V.S.Sree Rathna Lakshmi N.Senthil murugan Rajendra Prasad Mahapatra V.Muthukumaran M.sivaram Department of Computer Science and Engineering SRM Institute of Science and Technology–Vadapalani CampusChennaiIndia Department of Electronics and Communication Engineering Agni College of TechnologyChennaiIndia School of Computer Science and Engineering VIT-AP UniversityAmaravatiIndia Department of Computer Science and Engineering SRM Institute of Science and TechnologyGhaziabadIndia Department of Mathematics School of Applied SciencesREVA UniversityBangaloreIndia Faculty of Information Technology Ton Duc Thang UniversityHo Chi Minh CityVietnam

Purpose-The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and *** proposes a convolutional neural network-based capsule network(CNN-CapsNet)model and outlining the performance of the system in recognition of gait and speech *** proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech ***/methodology/approach-This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNNand used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in *** proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of ***-This research work provides recognition of signal,biometric-based gait recognition and sound/speech *** evaluations are conducted on three aspects of scenarios,namely fixed-view,cross-view and multi-view *** main parameters for recognition of gait are speed,change in clothes,subjects walking with carrying object and intensity of *** limitations/implications-The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware *** implications-This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor *** can also act as a pre-requisite tool to analyze,identify,detect and verify the malware ***/value-This proposed research work proves to be performing better for the recognition of gait and speech when

关键词： Intelligent system Gait recognition Convolutional neural network Deep learning Capsule network Viewpoint variations

A New Directional Algebraic Fast Multipole Method Based Iterative Solver for the Lippmann-Schwinger Equation Accelerated with HODLR Preconditioner

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Communications in Computational Physics 2022年第9期32卷 1061-1093页

作者： Vaishnavi Gujjula sivaram Ambikasaran Department of Mathematics Indian Institute of Technology MadrasChennai 600036India

We present a fast iterative solver for scattering problems in 2D,where a penetrable object with compact support is *** representing the scattered field as a volume potential in terms of the Green’s function,we arrive at the Lippmann-Schwinger equation in integral form,which is then discretized using an appropriate quadrature *** discretized linear system is then solved using an iterative solver accelerated by Directional Algebraic Fast Multipole Method(DAFMM).The DAFMM presented here relies on the directional admissibility condition of the 2D Helmholtz kernel[1],and the construction of low-rank factorizations of the appropriate low-rank matrix sub-blocks is based on our new Nested Cross Approximation(NCA)[2].The advantage of the NCA described in[2]is that the search space of so-called far-field pivots is smaller than that of the existing NCAs[3,4].Another significant contribution of this work is the use of HODLR based direct solver[5]as a preconditioner to further accelerate the iterative *** one of our numerical experiments,the iterative solver does not converge without a *** show that the HODLR preconditioner is capable of solving problems that the iterative solver can *** noteworthy contribution of this article is that we perform a comparative study of the HODLR based fast direct solver,DAFMMbased fast iterative solver,and HODLR preconditioned DAFMM based fast iterative solver for the discretized Lippmann-Schwinger *** the best of our knowledge,this work is one of the first to provide a systematic study and comparison of these different solvers for various problem sizes and contrast *** the spirit of reproducible computational science,the implementation of the algorithms developed in this article is made available at https://***/vaishna77/Lippmann_Schwinger_Solver.

关键词： Directional Algebraic Fast Multipole Method Lippmann-Schwinger equation lowrank matrix Helmholtz kernel Nested Cross Approximation HODLR direct solver Preconditioner

Foreword to the Special Issue: Proceedings of the Fourth Workshop on SWCNT Growth Mechanisms Organized by NASA-JSC, Rice University and the Air Force Research Laboratory

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Nano Research 2009年第10期2卷 741-742页

作者： sivaram Arepali Sungkyunkwan University SuwonSungkyunkwan University 53 Myeongnyun dong3-gaJongno-guSeoulI 10-745Korea

The great potential of single-walled carbon nanotubes(SWCNTs)is limited by our inability to produce them in large quantities and consistently make available tubes of specific type.A better understanding of nucleation and growth mechanisms of SWCNTs is a first major step in that *** biennial series of growth mechanisms workshops(GMW03,05,07)conducted by NASA Johnson Space Center and Rice University brought together the world's experts in the field of nanotube synthesis and advanced this effort based on experiments,theory,and modeling.

关键词： mechanisms quantities synthesis

Solubilization and degradation of perchloroethylene (PCE) in cationic and nonionic surfactant solutions

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Journal of Environmental Sciences 2011年第8期23卷 1240-1248页

作者： sivaram Harendra Cumaraswamy Vipulanandan Department of Energy National Energy Technology Laboratory Civil and Environmental Engineering University of Houston N107 Engineering Bldg. 1 Houston TX 77204 USA

Solubilization of perchloroethylene （PCE） in a nonionic （Triton X-100） and a cationic （cetyltrimethylammonium bromide （CTAB）） surfactant solutions and the degradation of surfactant solubilized PCE using fine to nanosize Fe and bi-metallic Fe-Ni particles were investigated. Micelle partition coefficients （Kin） and molar solubility ratio （MSR） for PCE in 10 g/L of surfactant solutions have been quantified and the solubility of PCE （100 mg/L in water） in the surfactant solutions increased by about ten fold, Of the two suffactants studied, Triton X-100 solubilized the higher amount of PCE per gram of suffactant. To degrade solubilized PCE, both iron and bimetallic Fe-Ni particles were used in continuously stirred batch reactors. The iron and hi-metallic particles were synthesized using the solution method and the particles were characterized using the SEM, EDS, TEM and XRD. The PCE solubilized up to 500 mg/L in both surfactant solutions were totally degraded at various rates by 200 g/L of hi-metallic Fe-Ni particles in less than 20 hr, which is the highest concentration of PCE degraded in the shortest time compared to data in the literature. The degradations of PCE solubilized in surfactant solutions were represented by nonlinear kinetic relationships which depended on the type of surfactant used for solubilizing the PCE.

关键词： Fe-Ni particles perchloroethylene (PCE) solubilization degradation

Sorption and transport studies of cetyl trimethylammonium bromide (CTAB) and Triton X-100 in clayey soil

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Journal of Environmental Sciences 2013年第3期25卷 576-584页

作者： sivaram Harendra Cumaraswamy Vipulanandan Department of Energy National Energy Technology Laboratory Civil and Environmental Engineering University of Houston

Surfactants are soil washing agents and facilitators for subsurface remediation of hydrocarbon *** is important to understand the sorption and transport behavior of surfactants for enhanced soil *** adsorption and desorption isotherms of cetyl trimethylammonium bromide （CTAB） and Triton X-100 with sand and kaolinite have been *** clay had the highest sorption capacity compared to blasting *** parameters such as diffusion coefficient （D） and retardation factor （R） of the above mentioned surfactant solutions were determined in clayey soils （82.5% sand and 17.5% kaolinite mixture） with near zero and 0.1 g/L ionic *** was used as the electrolyte ***-Diffusion equation was used to model the breakthrough curves of the *** ion was chosen as the tracer material in order to characterize the *** and Triton X-100 were used to flush the perchloroethylene （PCE） contaminated *** effectiveness of CTAB and Triton X-100 in flushing the PCE from the contaminated soil was quantified.

关键词： surfactant sorption transport clayey soil

COVID-19 Virus Prediction Using CNN and Logistic Regression Classification Strategies

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Journal of Data Analysis and Information Processing 2022年第1期10卷 78-89页

作者： Asadi Srinivasulu Tarkeshwar Barua Srinivas Nowduri Madhusudhana Subramanyam sivaram Rajeyyagari Data Science Research Laboratory BlueCrest University Monrovia Liberia

COVID-19 virus is certainly considered as one of the harmful viruses amongst all the illnesses in biological science. COVID-19 symptoms are fever, cough, sore throat, and headache. The paper gave a singular function for the prediction of most of the COVID-19 virus diseases and presented with the Convolutional Neural Networks and Logistic Regression which might be the supervised learning and gaining knowledge of strategies for most of COVID-19 virus diseases detection. The proposed system makes use of an 8-fold pass determination to get a correct result. The COVID-19 virus analysis dataset is taken from Microsoft Database, Kaggle, and UCI websites gaining knowledge of the repository. The proposed studies investigate Convolutional Neural Networks (CNN) and Logistic Regression (LR) about the usage of the UCI database, Kaggle, and Google Database Datasets. This paper proposed a hybrid method for COVID-19 virus, most disease analyses through reducing the dimensionality of capabilities the usage of Logistic Regression (LR), after which making use of the brand new decreased function dataset to Convolutional Neural Networks and Logistic regression. The proposed method received the accuracy of 78.82%, sensitiveness of 97.41%, and specialness of 98.73%. The overall performance of the proposed system is appraised thinking about performance, accuracy, error rate, sensitiveness, particularity, correlation and coefficient. The proposed strategies achieved the accuracy of 78.82% and 97.41% respectively through Convolutional Neural Networks and Logistic Regression.

关键词： Machine Learning COVID-19 Virus Deep Learning ANN CNN and LR

Effect of the Laser Heating of Nanotube Nuclei on the Nanotube Type Population

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Nano Research 2009年第10期2卷 818-827页

作者： Pavel Nikolaev William Holmes Edward Sosa Peter Boul sivaram Arepalli Department of Energy Science Sungkyunkwan University300 Cheoncheon-dongJangan-guSuwon 440-746Korea Alan G.MacDiarmid NanoT ech Institute The University of Texas at Dallas800 West Campbell RoadRichardsonTX 75080USA ERC Inc./NASA Johnson Space Center Mail Stop ES-4P.O.Box 58561HoustonTX 77258USA

Many potential applications of carbon nanotubes are expected to benet from the availability of single-walled carbon nanotube materials enriched in metallic species,and specifically armchair *** present work focuses on the modification of the pulsed laser vaporization(PLV)technique to selectively produce certain carbon nanotube *** nuclei were“warmed-up”with an additional laser pulse,timed to coincide approximately with the nucleation *** effect of the second laser on the carbon vapor temperature was studied by emission *** type populations with and without warm-up were compared by means of absorption,photoluminescence,and Raman *** was found that the warm-up of nanotube nuclei with a laser pulse has a noticeable,albeit small,effect on the nanotube *** intensity of spectral features associated with(9,7)nanotube and its large chiral angle neighbors increased,while small chiral angle nanotubes decreased,with exception of the(15,0)*** experiment demonstrates that nanotube population during PLV synthesis can be manipulated in a controlled fashion.

关键词： Nanotube synthesis pulsed laser vaporization nanotube population

Shape, Color and Texture Based CBIR System Using Fuzzy LogicClassifier

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Computers, Materials & Continua 2019年第6期59卷 729-739页

作者： D.Yuvaraj M.sivaram B.Karthikeyan Jihan Abdulazeez Department of Computer Science Cihan University-Duhok-42001Kurdistan Region-Iraq Department of Computer Networking Lebanese French UniversityErbil-44001Kurdistan Region-Iraq School of Computing SASTRA Deemed UniversityThanjavur-613401India

The perfect image retrieval and retrieval time are the two major challenges inCBIR systems. To improve the retrieval accuracy, the whole database is searched basedon many image characteristics such as color, shape, texture and edge information whichleads to more time consumption. This paper presents a new fuzzy based CBIR method,which utilizes colour, shape and texture attributes of the image. Fuzzy rule based systemis developed by combining color, shape, and texture feature for enhanced image *** this approach, DWT is used to pull out the texture characteristics and the region basedmoment invariant is utilized to pull out the shape features of an image. Color similarityand texture attributes are extorted using customized Color Difference Histogram (CDH).The performance evaluation based on precision and BEP measures reveals the superiorityof the proposed method over renowned obtainable approaches.

关键词： Image retrieval color histogram texture edge orientation retrieval accuracy