检索结果-南通市图书馆

Approach to loss of response to advanced therapies in inflammatory bowel disease

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

World Journal of Gastroenterology 2024年第22期30卷 2902-2919页

作者： Nikil Vootukuru Abhinav vasudevan Department of Gastroenterology and Hepatology Eastern HealthVictoriaBox Hill 3128Australia Eastern Health Clinical School Monash UniversityVictoriaBox Hill 3128Australia

BACKGROUND Remarkable progress over the last decade has equipped clinicians with many options in the treatment of inflammatory bowel *** now have the unique opportunity to provide individualized treatment that can achieve and sustain remission in many ***,issues of primary non-response(PNR)and secondary loss of response(SLOR)to non-tumour necrosis factor inhibitor(TNFi)therapies remains a common *** issues include the choice of optimization of therapy,identifying when dose optimization will recapture response,establishing optimal dose for escalation and when to switch *** To explores the issues of PNR and SLOR to non-TNFi *** This review explores the current evidence and literature to elucidate management options in cases of PNR/*** will also explore potential predictors for response following SLOR/PNR to therapies including the role of therapeutic drug monitoring(TDM).RESULTS In the setting of PNR and loss of response to alpha-beta7-integrin inhibitors and interleukin(IL)-12 and IL-23 inhibitors dose optimization is a reasonable option to capture *** Janus kinase inhibitors dose optimization can be utilized to recapture response with loss of *** The role of TDM in the setting of advanced non-TNFi therapies to identify patients who require dose optimization and as a predictor for clinical remission is not yet established and this remains an area that should be addressed in the future.

关键词： Inflammatory bowel disease Ulcerative colitis Crohn Biologics Interleukin-12 and interleukin-23 inhibitors Alpha-beta7-integrin inhibitors Janus kinase inhibitors Sphingosine-1-phosphate receptor modulators

A Hybrid Approach for Plant Disease Detection Using E-GAN and CapsNet

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computer Systems Science & Engineering 2023年第7期46卷 337-356页

作者： N.vasudevan T.Karthick Department of Data Science and Business Systems School of ComputingSRM Institute of Science and TechnologyKattankulathurTamilnadu603203India

Crop protection is a great obstacle to food safety,with crop diseases being one of the most serious *** diseases diminish the quality of crop *** detect disease spots on grape leaves,deep learning technology might be *** the other hand,the precision and efficiency of identification remain *** quantity of images of ill leaves taken from plants is often *** an uneven collection and few images,spotting disease is *** plant leaves dataset needs to be expanded to detect illness accurately.A novel hybrid technique employing segmentation,augmentation,and a capsule neural network(CapsNet)is used in this paper to tackle these *** proposed method involves three ***,a graph-based technique extracts leaf area from a plant *** second step expands the dataset using an Efficient Generative Adversarial Network ***,a CapsNet identifies the illness and *** proposed work has experimented on real-time grape leaf images which are captured using an SD1000 camera and PlantVillage grape leaf *** proposed method achieves an effective classification of accuracy for disease type and disease stages detection compared to other existing models.

关键词： Feature extraction neural network disease segmentation pattern analysis

Analysis of Bio-inspired Fishbone Based Corrugated Rib for Adaptive Camber Morphing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Bionic Engineering 2023年第3期20卷 1083-1102页

作者： R.Jini Raj J.Bruce Ralphin Rose A.vasudevan Department of Mechanical Engineering Anna University Regional CampusTirunelveli627007India Saveetha School of Engineering SIMATSChennai600124India

Bioinspired active camber morphing is an innovative solution for the aerodynamic performance enhancement of flight vehicles such as Micro Aerial Vehicles(MAVs)and Unmanned Aerial Vehicles(UAVs).In the present article,a bio-inspired Fish Bone Active Camber(FishBAC)corrugated rib design concept with and without a spine for an Unmanned Aerial Vehicle(UAV)is *** wing model is composed of multiple corrugated ribs and a splitted spar for connecting each *** rib geometry is subjected to static structural analysis using ANSYS Finite Element Analysis(FEA)module under the unit load *** deformation modes are first extracted from the solution of the wind tunnel test and the elastically deformed NACA 4412 profile will be used to perform Fluid-Structure Interaction(FSI)studies as a partly coupled *** corrugated rib with spine design is a stable structure as inspired from nature species that can withstand elastic and inertial *** fluid dynamics(CFD)simulation is performed to compute the coefficient of lift(Cl),coefficient of drag(Cd)at different Angle of Attack(AoA)for a modified NACA 4412 airfoil and the pressure loads acting on the deformed shape is *** Cl obtained for the modified airfoil at lower AoA is about 60–80%higher and the maximum Cl(Clmax)is 62%higher than the baseline *** Cd of modified airfoil is reduced about 20%at the AoAα=3°as compared with the baseline *** proposed corrugated rib structure has been successfully 3D printed with Polylactic Acid plus(PLA+)material and the wind tunnel testing is done to validate the Cl,Cd values obtained through CFD simulations and the results are presented.

关键词： Bioinspired design Active morphing Fish bone Wind tunnel CFD

Deep learning for exploring ultra-thin ferroelectrics with highly improved sensitivity of piezoresponse force microscopy

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

npj Computational Materials 2023年第1期9卷 2066-2073页

作者： Panithan Sriboriboon Huimin Qiao Owoong Kwon Rama K.vasudevan Stephen Jesse Yunseok Kim School of Advanced Materials and Engineering Sungkyunkwan University(SKKU)SuwonRepublic of Korea Research Center for Advanced Materials Technology Core Research InstituteSuwonRepublic of Korea Center for Nanophase Materials Sciences Oak Ridge National LaboratoryOak RidgeTNUSA

Hafnium oxide-based ferroelectrics have been extensively studied because of their existing ferroelectricity,even in ultra-thin film ***,studying the weak response from ultra-thin film requires improved measurement *** general,resonance-enhanced piezoresponse force microscopy(PFM)has been used to characterize ferroelectricity by fitting a simple harmonic oscillation model with the resonance ***,an iterative approach,such as traditional least squares(LS)fitting,is sensitive to noise and can result in the misunderstanding of weak *** this study,we developed the deep neural network(DNN)hybrid with deep denoising autoencoder(DDA)and principal component analysis(PCA)to extract resonance *** DDA/PCA-DNN improves the PFM sensitivity down to 0.3 pm,allowing measurement of weak piezoresponse with low excitation voltage in 10-nm-thick Hf_(0.5)Zr_(0.5)O_(2) thin *** hybrid approaches could provide more chances to explore the low piezoresponse of the ultra-thin ferroelectrics and could be applied to other microscopic techniques.

关键词： spectrum ferroelectric excitation

Design and Development of an Intelligent Energy Management System for a Smart Grid to Enhance the Power Quality

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Energy Engineering 2023年第8期120卷 1747-1761页

作者： Nisha vasudevan vasudevan Venkatraman A.Ramkumar T.Muthukumar A.Sheela M.Vetrivel R.J.Vijaya Saraswathi F.T.Josh Department of Electrical and Electronics Engineering Kalasalingam Academy of Research and EducationTamil NaduIndia Department of Computer Science Engineering Kalasalingam Academy of Research and EducationTamil NaduIndia Department of Electrical and Electronics Engineering Kongunadu College of Engineering and TechnologyTamil NaduIndia Department of Electrical and Electronics Engineering Kongu Engineering CollegeTamil NaduIndia Department of Electrical and Electronics Engineering Narasu’s Sarathy Institute of TechnologyTamil NaduIndia Department of Electrical and Electronics Engineering Panimalar Engineering CollegeTamil NaduIndia Department of Electrical and Electronics Engineering Karunya Institute of Technology&SciencesTamil NaduIndia

MigroGrid(MG)has emerged to resolve the growing demand for *** because of its inconsistent output,it can result in various power quality(PQ)*** is a problem that is becoming more and more important for the reliability of power systems that use renewable energy ***,the employment of nonlinear loads will introduce harmonics into the system and,as a result,cause distortions in the current and voltage waveforms as well as low power quality issues in the supply ***,this research focuses on power quality enhancement in the MG using hybrid shunt ***,the performance of the filter mainly depends upon the design,and stability of the *** efficiency of the proposed filter is enhanced by incorporating an enhanced adaptive fuzzy neural network(AFNN)*** performance of the proposed topology is examined in a MATLAB/Simulink environment,and experimental findings are provided to validate the effectiveness of this ***,the results of the proposed controller are compared with Adaptive Fuzzy Back-Stepping(AFBS)and Adaptive Fuzzy Sliding(AFS)to prove its superiority over power quality improvement in *** the analysis,it can be observed that the proposed system reduces the total harmonic distortion by about 1.8%,which is less than the acceptable limit standard.

关键词： Artificial intelligence resistive inductive load shunt hybrid filter smart grid adaptive fuzzy back-stepping power factor

Learning the right channel in multimodal imaging: automated experiment in piezoresponse force microscopy

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

npj Computational Materials 2023年第1期9卷 2008-2015页

作者： Yongtao Liu Rama K.vasudevan Kyle P.Kelley Hiroshi Funakubo Maxim Ziatdinov Sergei V.Kalinin Center for Nanophase Materials Sciences Oak Ridge National LaboratoryOak RidgeTN 37923USA Department of Materials Science and Engineering Tokyo Institute of TechnologyYokohama 226-8502Japan Computational Sciences and Engineering Division Oak Ridge National LaboratoryOak RidgeTN 37923USA Department of Materials Science and Engineering University of TennesseeKnoxvilleTN 37996USA

We report the development and experimental implementation of the automated experiment workflows for the identification of thebest predictive channel for a phenomenon of interest in spectroscopic measurements. The approach is based on the combinationof ensembled deep kernel learning for probabilistic predictions and a basic reinforcement learning policy for channel selection. Itallows the identification of which of the available observational channels, sampled sequentially, are most predictive of selectedbehaviors, and hence have the strongest correlations. We implement this approach for multimodal imaging in piezoresponse forcemicroscopy (PFM), with the behaviors of interest manifesting in piezoresponse spectroscopy. We illustrate the best predictivechannel for polarization-voltage hysteresis loop and frequency-voltage hysteresis loop areas is amplitude in the model samples. Thesame workflow and code are applicable for any multimodal imaging and local characterization methods.

关键词： automated policy modal

Role of nutrients in the utilization of polycyclic aromatic hydrocarbons by halotolerant bacterial strain

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2011年第2期23卷 282-287页

作者： Pugazhendi Arulazhagan Namsivayam vasudevan Department of Civil and Environmental Engineering Sung Kyun Kwan University300 CheonCheon-DongJangan-GuSuwon Gyeonggi-Do 440-746Republic of Korea Centre for Environmental Studies Anna UniversityChennai-600 025India

A halotolerant bacterial strain VA1 isolated from marine environment was studied for its ability to utilize polycylic aromatic hydrocarbons （PAHs） under saline condition. Anthracene and pyrene were used as representatives for the utilization of PAH by the bacterial strain. Glucose and sodium citrate were used as additional carbon sources to enhance the PAH utilization. The strain VA1 was able to utilize anthracene （73%） and pyrene （66%） without any additional substrate. In the presence of additional carbon sources （glucose]sodium citrate） the utilization of PAH was faster. PAH was utilized faster by VA 1 in the presence of glucose than sodium citrate. The stain utilized 87% and 83% of anthracene and pyrene with glucose as carbon source and with sodium citrate the strain utilized 81% and 76% respectively in 4 days. Urea as an alternative source of nitrogen also enhanced the utilization of PAHs （anthracene and pyrene） by the bacterial strain up to 88% and 84% in 4 days. Sodium nitrate as nitrogen source was not able to enhance the PAH utilization rate. Phenotypic and phlyogenetic analysis proved that the PAHs utilizing halotolerant strain VA1 belongs to Ochrobactrum sp.

关键词： biodegradation polycyclic aromatic hydrocarbons hatotolerant, Ochrobactrum sp

Local outlier factor and stronger one class classifier based hierarchical model for detection of attacks in network intrusion detection dataset

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2016年第4期10卷 755-766页

作者： Alampallam Ramaswamy vasudevan Subramanian SELVAKUMAR CDBR-SSE Lab Department of Computer Science and Engineering National Institute of Technology Tiruchirappalli (NITT) Tiruchirappalli 620015 India

Identification of attacks by a network intrusion detection system （NIDS） is an important task. In signature or rule based detection, the previously encountered attacks are modded, and signatures/rules are extracted. These rules are used to detect such attacks in future, but in anomaly or outlier detection system, the normal network traffic is modeled. Any deviation from the normal model is deemed to be an outlier/attack. Data mining and machine learning techniques are widely used in offline NIDS. Unsupervised and supervised learning techniques differ the way NIDS dataset is treated. The characteristic features of unsupervised and supervised learning are finding patterns in data, detecting outliers, and determining a learned function for input features, generalizing the data instances respectively. The intuition is that if these two techniques are combined, better performance may be obtained. Hence, in this paper the advantages of unsupervised and supervised techniques are inherited in the proposed hierarchical model and devised into three stages to detect attacks in NIDS dataset. NIDS dataset is clustered using Dirichiet process （DP） clustering based on the underlying data distribution. Iteratively on each cluster, local denser areas are identified using local outlier factor （LOF） which in turn is discretized into four bins of separation based on LOF score. Further, in each bin the normal data instances are modeled using one class classifier （OCC）. A combination of Density Estimation method, Reconstruction method, and Boundary methods are used for OCC model. A product rule combination of the three methods takes into consideration the strengths of each method in building a stronger OCC model. Any deviation from this model is considered as an attack. Experiments are conducted on KDD CUP＇99 and SSENet-2011 datasets. The results show that the proposed model is able to identify attacks with higher detection rate and low false alarms.

关键词： hierarchical model DP clustering LOF Dis-cretizer one class classifier NIDS

Minus Infinity Plus Infinity

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Semiconductor Science and Information Devices 2023年第1期5卷 1-2页

作者： Kasturi vasudevan Department of EE IIT Kanpur208016India

Mankind has always been fascinated by nature and has striven to understand its *** lies beyond the stars,what hides inside atoms,how to reach the stars,how to tap the vast energy inside the atoms,what is the correlation between space and time and how to exploit it-these are only a sample of the infinite questions to which we seek *** this editorial we explore some of the pressing issues that we are currently trying to address.

关键词： infinite stars Plus