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Comparison of microscopy and PCR for the detection of human Plasmodium species and Plasmodium knowlesi in southern Myanmar

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Asian Pacific Journal of Tropical Biomedicine 2017年第8期7卷 680-685页

作者： Thu Zar Han Kay Thwe Han Kyin Hla Aye Thaung Hlaing Kyaw Zin Thant indra vythilingam MD Programme Faculty of Medicine&Health SciencesUCSI University Department of Medical Research Lower Myanmar Vector Borne Diseases Control Unit Department of Health Department of Parasitology University Malaya

To determine the distribution of Plasmodium (P) species including Plasmodium knowlesi and to compare the specificity and sensitivity of microscopy with nested PCR in malaria *** study was conducted in Kawthaung, southern Myanmar. Ninety clinically suspected malaria patients were screened for malaria by Giemsa stained microscopy and confirmed by nested *** the participants, 57 (63.3%) were positive and 33 (36.7%) were negative by microscopy. Of positive samples, 39 (68.4%) were Plasmodium falciparum, 17 (29.8%) Plasmodium vivax and 1 (1.8%) Plasmodium malariae, whereas 59-amplified by PCR were 40 (67.8%), 18 (30.5%) and 1 (1.7%) respectively. PCR amplified 2 microscopy negative samples. Two samples of P. falciparum detected by microscopy were amplified as P. vivax and vice versa. All samples were negative for Plasmodium ovale, P. knowlesi and mixed infections. Microscopy had a very good measure of agreement (κ = 0.95) compared to nested PCR. Sensitivity and specificity of microscopy for diagnosis of P. falciparum were 92.5% (95% CI: 79.6-98.4) and 96.0% (95% CI: 86.3-99.5) respectively, whereas for P. vivax were 83.3% (95% CI: 58.6-96.4) and 97.2% (95% CI: 90.3-99.7).ConclusionsP. knowlesi was not detected by both microscopy and PCR. Giemsa stained microscopy can still be applied as primary method for malaria diagnosis and is considered as gold standard. As to the lower sensitivity of microscopy for vivax malaria, those with previous history of malaria and relapse cases should be diagnosed by RDT or PCR combined with microscopy. Inaccuracy of species diagnosis highlighted the requirement of training and refresher courses for microscopists.

关键词： Malaria Plasmodium Plasmodium knowlesi Microscopy

Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi Bui Dam Duc Nguyen Hiep Van Le indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Induction of osteoblast differentiation in human adipose derived stem cells by lanthanum ions

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Journal of Rare Earths 2014年第11期32卷 1080-1088页

作者： Harini D indra R Rajaram A Rama Rajaram Department of Biochemistry Central Leather Research Institute Department of Biophysics Central Leather Research Institute

Adipose derived stem cells represent a readily available source of adult stem cells for various biomedical applications. In this study, the proliferation and osteogenic differentiation potential of lanthanum nitrate（La3＋） on human adipose derived mesenchymal stem cells（hADSCs） were investigated for the first time and compared with that of dexamethasone（Dex）. Our results provided evidence that La3＋ at 50 μmol/L concentration promoted proliferation of hADSCs upto 2.4 fold when treated for 21 d in DMEM medium. Treatment of hADSCs with La3＋ containing osteogenic induction medium（α-MEM with ascorbic acid and β-glycerophosphate） for 7 d resulted in higher calcium deposition than that in the presence of Dex（0.1 μmol/L） as shown by Alizarin red S and von Kossa staining. Scanning electron micrographs also showed more extracellular matrix mineralization in the presence of La3＋. After 7 d of treatment with La3＋（10 μmol/L） the expression of RunX2, osteopontin（OP） and osteocalcin（OC） increased 3.4, 5.5 and 2.7 fold respectively. Our results provided evidence that in the presence of La3＋ osteogenic differentiation occurred earlier than that in the presence of Dex.

关键词： hADSCs lanthanum osteoblast differentiation genes calcium deposition SEM RunX2 rare earths

Suboptimal Robust Stabilization of Discrete-time Mismatched Nonlinear System

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 352-359页

作者： Niladri Sekhar Tripathy indra Narayan Kar Kolin Paul Department of Electrical Engineering Indian Institute of Technology Delhi New Delhi Delphi-110016 India IEEE

This paper proposes a discrete-time robust control technique for an uncertain nonlinear system. The uncertainty mainly affects the system dynamics due to mismatched parameter variation which is bounded by a predefined known function. In order to compensate the effect of uncertainty, a robust control input is derived by formulating an equivalent optimal control problem for a virtual nominal system with a modified costfunctional. To derive the stabilizing control law for a mismatched system, this paper introduces another control input named as virtual input. This virtual input is not applied directly to stabilize the uncertain system, rather it is used to define a sufficient condition. To solve the nonlinear optimal control problem, a discretetime general Hamilton-Jacobi-Bellman(DT-GHJB) equation is considered and it is approximated numerically through a neural network(NN) implementation. The approximated solution of DTGHJB is used to compute the suboptimal control input for the virtual system. The suboptimal inputs for the virtual system ensure the asymptotic stability of the closed-loop uncertain system. A numerical example is illustrated with simulation results to prove the efficacy of the proposed control algorithm.

关键词： Discrete-time general Hamilton-Jacobi-Bellman(DT-HJB) equation discrete-time optimal control discrete-time robust control mismatched uncertainty nonlinear optimal control

Highly sensitive troponin I assay in the diagnosis of coronary artery disease in patients with suspected stable angina

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World Journal of Cardiology 2021年第12期13卷 745-757页

作者： indra Ramasamy Department of Biochemistry Worcester Royal HospitalWorcester WR51DDUnited Kingdom

BACKGROUND Evaluation of suspected stable angina patients with probable coronary artery disease(CAD)in the community is *** the United Kingdom,patients with suspected stable angina are referred by community physicians to be assessed by specialists within the hospital system in rapid access chest pain clinics(RACPC).The role of a highly sensitive troponin I(uscTnI)assay in the diagnosis of suspected CAD in a RACPC in a“real-life”setting in a non-academic hospital has not been *** To examine the diagnostic value of uscTnI(detection limit 0.12 ng/L,upper reference range 8.15 ng/L,and detected uscTnI in 96.8%of the reference population),in the evaluation of stable CAD in a non-selected patient group,with several co-morbidities,who presented to the *** One hundred and seventy two RACPC patients were assigned to either functional or anatomical testing according to the hospital *** The investigations offered to patients were exercise tolerance test 7.6%,24 h ECG 1.2%,Echocardiogram 14.5%,stress echocardiogram 8.1%,coronary computed tomography angiography(CCTA)12.8%,coronary angiogram 13.4%,17.4%were diagnosed with non-cardiac chest pain,3.5%treated as stable angina,8.2%reviewed by cardiologists,electronic medical records were not available in 10.4%.Receiver operating characteristic curves for CAD used uscTnI values measured in patients who underwent functional testing,angiogram or ***>0.52 ng/L showed 100%sensitivity and at>11.6 ng/L showed 100%*** the range>0.52-11.6 ng/L,uscTnI may not have the same diagnostic *** patients assigned to coronary angiogram higher concentrations of uscTnI was associated with severe *** levels of uscTnI and low pre-test probability of CAD(QRISK3)may decrease patient numbers assigned to *** The uscTnI diagnostic cut-off values in a RACPC will depend on patient population and their presenting *** the presence of clinical comorbidities and previous

关键词： Rapid access chest pain clinic Suspected stable angina Troponin I Coronary artery disease Coronary angiogram Coronary computed tomography angiography

Modeling of Optimal Deep Learning Based Flood Forecasting Model Using Twitter Data

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Intelligent Automation & Soft Computing 2023年第2期35卷 1455-1470页

作者： G.indra N.Duraipandian Department of Computer Science and Engineering RMK College of Engineering and TechnologyChennai601206India Department of Computer Science and Engineering Saveetha Engineering CollegeChennai602106India

Aﬂood is a signiﬁcant damaging natural calamity that causes loss of life and *** work on the construction ofﬂood prediction models intended to reduce risks,suggest policies,reduce mortality,and limit property damage caused byﬂ*** massive amount of data generated by social media platforms such as Twitter opens the door toﬂood *** of the real-time nature of Twitter data,some government agencies and authorities have used it to track natural catastrophe events in order to build a more rapid rescue ***,due to the shorter duration of Tweets,it is difﬁcult to construct a perfect prediction model for determiningﬂ*** learning(ML)and deep learning(DL)approaches can be used to statistically developﬂood prediction *** the same time,the vast amount of Tweets necessitates the use of a big data analytics(BDA)tool forﬂood *** this regard,this work provides an optimal deep learning-basedﬂood forecasting model with big data analytics(ODLFF-BDA)based on Twitter *** suggested ODLFF-BDA technique intends to anticipate the existence ofﬂoods using tweets in a big data *** ODLFF-BDA technique comprises data pre-processing to convert the input tweets into a usable *** addition,a Bidirectional Encoder Representations from Transformers(BERT)model is used to generate emotive contextual embed-ding from ***,a gated recurrent unit(GRU)with a Multilayer Convolutional Neural Network(MLCNN)is used to extract local data and predict theﬂ***,an Equilibrium Optimizer(EO)is used toﬁne-tune the hyper-parameters of the GRU and MLCNN models in order to increase prediction *** memory usage is pull down lesser than 3.5 MB,if its compared with the other algorithm *** ODLFF-BDA technique’s performance was validated using a benchmark Kaggle dataset,and theﬁndings showed that it outperformed other recent approaches signiﬁcantly.

关键词： Big data analytics predictive models deep learning ﬂood prediction twitter data hyperparameter tuning

Reaction kinetics modeling for lithium and cobalt recovery from spent lithium-ion batteries using acetic acid

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International Journal of Minerals,Metallurgy and Materials 2019年第1期26卷 98-107页

作者： Hendrik Setiawan Himawan Tri Bayu Murti Petrus indra Perdana Sustainable Mineral Processing Research Group Department of Chemical Engineering Faculty of Engineering Universitas Gadjah Mada

Lithium and cobalt recovery from spent lithium-ion batteries(LIBs) is a major focus because of their increased production and usage. The conventional method for recycling spent LIBs using inorganic acids produces harmful byproducts. In this work, the leaching agent was substituted with a less expensive and more environmentally friendly alternative—acetic acid—and a mathematical model was developed to describe the kinetics of the recovery process. The variables used were the pH value, temperature, H_2O_2 concentration, and the solid-to-liquid(S/L) ratio. The mathematical model used was the shrinking core model, which was modified to accommodate an equilibrium reaction. The experimental results show that the rate of recovery of Li and Co over time was only affected by temperature. The leaching behaviors of Li and Co were found to oppose each other. An increase in temperature resulted in increased recovery of Li but decreased recovery of Co because of the product-favoring endothermic reaction of Li and the reactant-favoring exothermic reaction of Co. The product of Li has a lower entropy value than the reactant as a free-moving ion, whereas the product of Co leaching has a higher entropy value as a stiff crystal complex. Thus, temperature conditioning is a pivotal factor in the leaching of spent LIBs.

关键词： spent libs lithium cobalt kinetics modeling recovery equilibrium

Gap characteristics and their effects on regeneration,dominance and early growth of woody species

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Journal of Plant Ecology 2009年第1期2卷 21-29页

作者： indra Prasad Sapkota Per Christer Oden Swedish University of Agricultural Sciences Southern Swedish Forest Research CentreTropical Silviculture and Seed Science GroupPO Box 49SE-23053 AlnarpSweden

Aims We aim to examine the canopy gap characteristics and evaluate their influence on regeneration,dominance and the early growth of woody species in seasonally dry Shorea robusta forests(Sal forests).Methods Sixty canopy gaps were surveyed in six randomly located transects belts in seasonally dry subtropical Sal forests of central *** transect belt was followed until 10 gap sites were *** equation for the area of an ellipse was used to calculate the size of canopy gap,measuring the longest axis and its perpendicular shorter ***,sizes,ages and causes of tree falls creating canopy gaps along with number and sizes of border trees were identified and *** gap inventories were carried out using square 25-m2 quadrats placed in the middle of each *** individuals>2 m in height within the quadrat were identified at the species level and their diameter at breast height was *** assigned a nested 4-m2 quadrat to the corner of each 25-m2 quadrat,within which all woody individuals>10 cm tall were identified at the species level,and counted them and their regeneration mechanisms were *** height and collar diameter of the tallest individuals were *** statistics was calculated for the variables of interests and Pearson correlation,linear regression,independent-sample t-test and chi-square test were used to relate them and to test for their *** Findings The study found mean gap size of 283 m2 and;50%gaps of 10–15 years *** created by natural single-tree falls were significantly more numerous,and their mean size was significantly smaller than those resulting from artificial causes or multiple-tree *** size correlated with the basal area of felled trees,but it did not correlate with the number of tree *** tree fall basal area was significantly positively correlated to the seed-originated seedling to resprout ratio,it was negatively correlated,along with gap area and th

关键词： canopy gap seedling density seedling growth basal area Sal forests Nepal