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Thermal Degradation and Decomposition k.netics of Freeze Dried Cow and Camel Milk.as well as Their Constituents

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Journal of Food Science and Engineering 2011年第2期1卷 77-84页

作者： k. V. Sunooj J. George V. A. Sajeev k.mar k. radhakrishna A. S. Bawa Department of Food Science and Technology Pondicherry University R. Venkataraman Nagar Pondicherry 605014 India De fence Food Research Laboratory Siddarthanagar Mysore 570011 India

A study was conducted to evaluate thermal properties and degradation k.netic parameters of FD cow milk.and camel milk.powder. FT-IR was used to confirm the fat removal from the whole milk.powder. Differential Scanning Calorimetry (DSC) was used to study the thermal transitions. DSC thermograms of WMP showed a two-step endotherm, the former at lower temperatures (cow milk.16-35 °C, camel milk.25-60 °C) and the later at higher temperatures (cow milk.75-125 °C, camel milk.90-160 °C). The main difference observed between cow and camel milk.was peak.maximum temperature for fat melting, ΔH and other decomposition temperatures. The enthalpy of fat melting was 2.314 J/g and 3.397 J/g for cow and camel milk.respectively. Thermogravimetric Analysis (TGA)/derivative thermogravimetric analysis (DTG) also showed two steps degradation. The first step involves lactose degradation and second step corresponds to combined degradation of protein and fat. Hence logβ vs 1000/T was plotted separately for individual components to determine cumulative value of activation energy using Flynn-Wall-Osawa method.

关键词：全脂奶粉热分解动力学热降解骆驼牛奶差示扫描量热法冻干最高温度

A Review of Graph Neural Network. and Their Applications in Power Systems

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 345-360页

作者： Wenlong Liao Birgitte Bak.Jensen Jayak.ishnan radhakrishna Pillai Yuelong Wang Yusen Wang the Department of Energy Technology Aalborg UniversityAalborgDenmark the State Grid Tianjin Chengxi Electric Power Supply Branch TianjinChina the School of Electrical Engineering and Computer Science KTH Royal Institute of TechnologyStockholmSweden

Deep neural network. have revolutionized many machine learning task. in power systems,ranging from pattern recognition to signal *** data in these task. are typically represented in Euclidean ***,there is an increasing number of applications in power systems,where data are collected from non-Euclidean domains and represented as graph-structured data with high-dimensional features and interdependency among *** complexity of graph-structured data has brought significant challenges to the existing deep neural network. defined in Euclidean ***,many publications generalizing deep neural network. for graph-structured data in power systems have *** this paper,a comprehensive overview of graph neural network.(GNNs)in power systems is ***,several classical paradigms of GNN structures,e.g.,graph convolutional network.,are *** applications in power systems such as fault scenario application,time-series prediction,power flow calculation,and data generation are reviewed in ***,main issues and some research trends about the applications of GNNs in power systems are discussed.

关键词： Machine learning power system deep neural network graph neural network artificial intelligence

Data-driven Missing Data Imputation for Wind Farms Using Context Encoder

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Journal of Modern Power Systems and Clean Energy 2022年第4期10卷 964-976页

作者： Wenlong Liao Birgitte Bak.Jensen Jayak.ishnan radhakrishna Pillai Dechang Yang Yusen Wang Department of Energy Technology Aalborg UniversityAalborgDenmark College of Information and Electrical Engineering China Agricultural UniversityBeijingChina School of Electrical Engineering and Computer Science KTH Royal Institute of TechnologyStockholmSweden

High-quality datasets are of paramount importance for the operation and planning of wind ***,the datasets collected by the supervisory control and data acquisition(SCADA)system may contain missing data due to various factors such as sensor failure and communication *** this paper,a data-driven approach is proposed to fill the missing data of wind farms based on a context encoder(CE),which consists of an encoder,a decoder,and a *** deep convolutional neural network.,the proposed method is able to automatically explore the complex nonlinear characteristics of the datasets that are difficult to be modeled *** proposed method can not only fully use the surrounding context information by the reconstructed loss,but also mak. filling data look.real by the adversarial *** addition,the correlation among multiple missing attributes is tak.n into account by adjusting the format of input *** simulation results show that CE performs better than traditional methods for the attributes of wind farms with hallmark.characteristics such as large peak.,large valleys,and fast ***,the CE shows stronger generalization ability than traditional methods such as auto-encoder,k.means,k.nearest neighbor,back.propagation neural network.cubic interpolation,and conditional generative adversarial network.for different missing data scales.

关键词： Data-driven missing data imputation wind farm deep learning context encoder

Ultra-short-term Interval Prediction of Wind Power Based on Graph Neural Network.and Improved Bootstrap Technique

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Journal of Modern Power Systems and Clean Energy 2023年第4期11卷 1100-1114页

作者： Wenlong Liao Shouxiang Wang Birgitte Bak.Jensen Jayak.ishnan radhakrishna Pillai Zhe Yang k.angpu Liu AAU Energy Aalborg UniversityAalborg 9220Denmark k.y Laboratory of Smart Grid of Ministry of Education School of Electrical and Information EngineeringTianjin UniversityTianjin 300072China

Reliable and accurate ultra-short-term prediction of wind power is vital for the operation and optimization of power ***,the volatility and intermittence of wind power pose uncertainties to traditional point prediction,resulting in an increased risk.of power system *** represent the uncertainty of wind power,this paper proposes a new method for ultra-short-term interval prediction of wind power based on a graph neural network.GNN)and an improved Bootstrap ***,adjacent wind farms and local meteorological factors are modeled as the new form of a graph from the graph-theoretic ***,the graph convolutional network.GCN)and bi-directional long short-term memory(Bi-LSTM)are proposed to capture spatiotemporal features between nodes in the *** obtain highquality prediction intervals(PIs),an improved Bootstrap technique is designed to increase coverage percentage and narrow PIs *** simulations demonstrate that the proposed method can capture the spatiotemporal correlations from the graph,and the prediction results outperform popular baselines on two real-world datasets,which implies a high potential for practical applications in power systems.

关键词： Wind power graph neural network.GNN) bidirectional long short-term memory(Bi-LSTM) prediction interval Bootstrap technique

Scenario Generations for Renewable Energy Sources and Loads Based on Implicit Maximum Lik.lihood Estimations

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Journal of Modern Power Systems and Clean Energy 2022年第6期10卷 1563-1575页

作者： Wenlong Liao Birgitte Bak.Jensen Jayak.ishnan radhakrishna Pillai Zhe Yang Yusen Wang k.angpu Liu AAU Energy Aalborg UniversityAalborgDenmark School of Electrical Engineering and Computer Science KTH Royal Institute of TechnologyStockholmSweden

Scenario generations for renewable energy sources and loads play an important role in the stable operation and risk.assessment of integrated energy *** paper proposes a deep generative network.based method to model time-series curves,e.g.,power generation curves and load curves,of renewable energy sources and loads based on implicit maximum lik.lihood estimations(IMLEs),which can generate realistic scenarios with similar patterns as real *** training the model,any number of new scenarios can be obtained by simply inputting Gaussian noises into the data generator of *** proposed approach does not require any model assumptions or prior k.owledge of the form in the lik.lihood function being made during the training process,which leads to stronger applicability than explicit density model based *** extensive experiments show that the IMLEs accurately capture the complex shapes,frequency-domain characteristics,probability distributions,and correlations of renewable energy sources and ***,the proposed approach can be easily generalized to scenario generation task. of various renewable energy sources and loads by fine-tuning parameters and structures.

关键词： Renewable energy source scenario generation implicit maximum lik.lihood estimation(IMLE) deep learning generative network

Exploring the region-wise diversity and functions of symbiotic bacteria in the gut system of wood-feeding termite,Coptotermes formosanus,toward the degradation of cellulose,hemicellulose,and organic dyes

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Insect Science 2022年第5期29卷 1414-1432页

作者： Mudasir A.Dar Rongrong Xie radhakrishna S.Pandit Blessing Danso Chenchen Dong Jianzhong Sun Biofuels Institute School of the Environment and Safety EngineeringJiangsu UniversityZhenjiangJiangsu ProvinceChina Department of Zoology Savitribai Phule Pune UniversityGaneshkhindPuneIndia

The wood-feeding termite Coptotermes formosanus represents a unique and impressive system for lignocellulose *** highly efficient digestion of lignocellulose is achieved through symbiosis with gut symbionts lik. *** extensive research during the last three decades,diversity of bacterial symbionts residing in individual gut regions of the termite and their associated functions is still *** this end,cellulose,xylan,and dye-decolorization bacteria residing in foregut,midgut,and hindgut regions of *** were enlisted by using enrichment and culture-dependent molecular methods.A total of 87 bacterial strains were successfully isolated from different gut regions of *** which belonged to 27 different species of 10 genera,majorly affiliated with Proteobacteria(80%)and Firmicutes(18.3%).Among the gut regions,37.9%of the total bacterial isolates were observed in the hindgut that demonstrated predominance of cellulolytic bacteria(47.6%).The majority of the xylanolytic and dye-decolorization bacteria(50%)were obtained from the foregut and midgut,*** represented by Dietza *** observed in the hindgut *** on species richness,the highest diversity was observed in midgut and hindgut regions each of which harbored seven unique bacterial *** members of Enterobacter,k.ebsiella,and Pseudomonas were common among the gut *** lignocellulolytic activities of the selected potential bacteria signpost their assistance to the host for lignocellulose *** overall results indicate that *** harbors diverse communities of lignocellulolytic bacteria in different regions of the gut *** observations will significantly advance our understanding of the termite–bacteria symbiosis and their microbial ecology uniquely existed in different gut regions of ***,which may further shed a light on its potential values at termite-modeled biotechnology.

关键词： bacterial symbionts Coptotermes formosanus culture-dependent gut regions lignocellulose termite

Crustal structure and sedimentation history over the Alleppey platform, southwest continental margin of India:Constraints from multichannel seismic and gravity data

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Geoscience Frontiers 2018年第2期9卷 549-558页

作者： P.Unnik.ishnan M.radhakrishna G.k.Prasad Department of Earth Sciences Indian Institute of Technology Bombay Flat 3 "Muruga Kripa"

The Alleppey Platform is an important morphological feature located in the k.rala-k.nk.n basin off the southwest coast of India. In the present study, seismic reflection data available in the basin were used to understand the sedimentation history and also to carry out integrated gravity interpretation. Detailed seismic reflection data in the basin reveals that:(1) the Alleppey Platform is associated with a basement high in the west of its present-day geometry(as observed in the time-structure map of the Trap Top(k.T boundary)),(2) the platform subsequently started developing during the Eocene period and attained the present geometry by the Miocene and,(3) both the Alleppey platform and the Vishnu fracture zone have had significant impact on the sedimentation patterns(as shown by the time-structure and the isochron maps of the major sedimentary horizons in the region). The 3-D sediment gravity effect computed from the sedimentary layer geometry was used to construct the crustal Bouguer anomaly map of the *** 3-D gravity inversion of crustal Bouguer anomaly exhibits a Moho depression below the western border of the platform and a minor rise towards the east which then deepens again below the Indian shield. The 2-D gravity modelling across the Alleppey platform reveals the geometry of crustal extension,in which there are patches of thin and thick.crust. The Vishnu Fracture Zone appears as a crustal-scale feature at the western boundary of the Alleppey platform. Based on the gravity model and the seismic reflection data, we suggest that the basement high to the west of the present day Alleppey platform remained as a piece of continental block.very close to the mainland with the intervening depression filling up with sediments during the rifting. In order to place the Alleppey platform in the overall perspective of tectonic evolution of the k.rala-k.nk.n basin, we propose its candidature as a continental fragment.

关键词： Gravity Seismic reflection Alleppey platform Rifting Continental fragments Western continental margin of India

Performance study of a cesium iodide photocathode-based UV photon detector in Ar/CH_(4) mixture

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Photonics Research 2014年第3期2卷 92-96页

作者： G.Baishali V.radhakrishna V.k.ushal k.Rak.ee k.Rajanna Department of Instrumentation and Applied Physics Indian Institute of ScienceBangalore-560012India Space Astronomy group ISRO Satellite CentreBangalore-560017India

The detection efficiency of a gaseous photomultiplier depends on the photocathode quantum efficiency and the extraction efficiency of photoelectrons into the *** this paper we have studied the performance of an UV photon detector with P10 gas in which the extraction efficiency can reach values near to those in vacuum operated *** have been done to compare the percentage of photoelectrons back.cattered in P10 gas as well as in the widely used neon-based gas *** performance study has been carried out using a single stage thick.gas electron multiplier(THGEM).The electron pulses and electron spectrum are recorded under various operating *** effects prevailing in UV photon detectors lik. photon feedback.are discussed and its effect on the electron spectrum under different operating conditions is analyzed.

关键词： photon mixture multiplier

Robust Voltage Control Considering Uncertainties of Renewable Energies and Loads via Improved Generative Adversarial Network

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Journal of Modern Power Systems and Clean Energy 2020年第6期8卷 1104-1114页

作者： Qianyu Zhao Wenlong Liao Shouxiang Wang Jayak.ishnan radhakrishna Pillai the k.y Laboratory of Smart Grid of Ministry of Education and Tianjin k.y Laboratory of Power System Simulation and Control Tianjin UniversityTianjinChina the Department of Energy Technology Aalborg UniversityAalborgDenmark

The fluctuation of output power of renewable energies and loads brings challenges to the scheduling and operation of the distribution *** this paper,a robust voltage control model is proposed to cope with the uncertainties of renewable energies and loads based on an improved generative adversarial network.IGAN).Firstly,both real and predicted data are used to train the IGAN consisting of a discriminator and a *** noises sampled from the Gaussian distribution are fed to the generator to generate a large number of scenarios that are utilized for robust voltage control after scenario ***,a new improved wolf pack.algorithm(IWPA)is presented to solve the formulated robust voltage control model,since the accuracy of the solutions obtained by traditional methods is *** simulation results show that the IGAN can accurately capture the probability distribution characteristics and dynamic nonlinear characteristics of renewable energies and loads,which mak.s the scenarios generated by IGAN more suitable for robust voltage control than those generated by traditional ***,IWPA has a better performance than traditional methods in terms of convergence speed,accuracy,and stability for robust voltage control.

关键词： Robust voltage control uncertainty generative adversarial network wolf pack.algorithm