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Exploring the potential of artificial intelligence techniques in prediction of the removal efficiency of vortex tube silt ejector

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International Journal of Sediment Research 2023年第4期38卷 615-627页

作者： Sanjeev Kumar chandra shekhar prasad ojha Nand Kumar Tiwari Subodh Ranjan Department of Civil Engineering Indian Institute of Technology Department of Civil Engineering National Institute of Technology

A vortex tube silt ejector is a curative hydraulic structure used to remove sediment deposits from canals and is recognized as one of the most efficient substitutes for physically removing canal sediment. The spatially varied flow in the channel and the rotational flow behavior in the tube make the silt removal process complex. It is even harder to accurately predict the silt removal efficiency by traditional models accurately. However, artificial intelligence(AI) and machine learning approaches have emerged as robust substitutes for studying complex processes. Therefore, this research makes use of AI approaches; support vector machine(SVM), random forest(RF), random tree(RT), and multivariate adaptive regression spline(MARS) to compute the vortex tube silt ejection efficiency using the laboratory data sets. The outcomes of the artificial intelligence(AI)-based techniques also were compared with traditional models. It was found that the RT model(root mean square error, RMSE = 2.165, Nash Sutcliffe efficiency, NSE = 0.98) outperforms the other applied approaches which had relatively more significant result errors. The sensitivity analysis of the process depicts the extraction ratio as the key parameter in the computation of vortex tube silt ejector removal efficiency. The findings of the AI-based approaches discussed in the current study might be helpful for hydraulic engineers as well as researchers in the assessment of the removal efficiency of vortex tube silt ejectors.

关键词： Vortex tube silt ejector Support vector machine Random forest Random tree Multivariate adaptive regression spline

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Evaluation of Various Linear Regression Methods for Downscaling of Mean Monthly Precipitation in Arid Pichola Watershed

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Natural Resources 2010年第1期1卷 11-18页

作者： Manish Kumar Goyal chandra shekhar prasad ojha 不详

In this paper, downscaling models are developed using various linear regression approaches namely direct, forward, backward and stepwise regression for downscaling of GCM output to predict mean monthly precipitation under IPCC SRES scenarios to watershed-basin scale in an arid region in India. The effectiveness of these regression approaches is evaluated through application to downscale the predictand for the Pichola lake region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. The selection of important predictor variables becomes a crucial issue for developing downscaling models since reanalysis data are based on wide range of meteorological measurements and observations. Direct regression was found to yield better performance among all other regression techniques explored in the present study. The results of downscaling models using both approaches show that precipitation is likely to increase in future for A1B, A2 and B1 scenarios, whereas no trend is discerned with the COMMIT.

关键词： Backward Forward Precipitation Regression Stepwise

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Application of PLS-Regression as Downscaling Tool for Pichola Lake Basin in India

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International Journal of Geosciences 2010年第2期1卷 51-57页

作者： Manish Kumar Goyal chandra shekhar prasad ojha 不详

In this paper, downscaling models are developed using Partial Least Squares (PLS) Regression for obtaining projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of this approach is demonstrated through application to downscale the predictand for the Pichola lake region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centers for Environmental Prediction (NCEP) reanalysis dataset for the period 1948-2000, and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001-2100. The selection of important predictor variables becomes a crucial issue for developing downscaling models since reanalysis data are based on wide range of meteorological measurements and observations. In this paper, we use PLS regression for quality prediction and its use for the variable selection based on the variable importance. The results of downscaling models using PLS regression show that precipitation is projected to increase in future for A2 and A1B scenarios, whereas it is least for B1 and COMMIT scenarios using predictors.

关键词： PLS Regression Precipitation VIP Score

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Analysis of Mean Monthly Rainfall Runoff Data of Indian Catchments Using Dimensionless Variables by Neural Network

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Journal of Environmental Protection 2010年第2期1卷 155-171页

作者： Manish Kumar Goyal chandra shekhar prasad ojha 不详

This paper focuses on a concept of using dimensionless variables as input and output to Artificial Neural Network (ANN) and discusses the improvement in the results in terms of various performance criteria as well as simplification of ANN structure for modeling rainfall-runoff process in certain Indian catchments. In the present work, runoff is taken as the response (output) variable while rainfall, slope, area of catchment and forest cover are taken as input parameters. The data used in this study are taken from six drainage basins in the Indian provinces of Madhya Pradesh, Bihar, Rajasthan, West Bengal and Tamil Nadu, located in the different hydro-climatic zones. A standard statistical performance evaluation measures such as root mean square (RMSE), Nash–Sutcliffe efficiency and Correlation coefficient were employed to evaluate the performances of various models developed. The results obtained in this study indicate that ANN model using dimensionless variables were able to provide a better representation of rainfall–runoff process in comparison with the ANN models using process variables investigated in this study.

关键词： Dimensional Variables Artificial Neural Networks Rainfall–Runoff

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Nanofluids:Critical issues,economics and sustainability perspectives

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Particuology 2024年第4期87卷 147-172页

作者： Sayantan Mukherjee Sylwia Wcislik Purna chandra Mishra Paritosh Chaudhuri Instiute for Plasma Research Gandhinagar GujaratIndia Department of Building Physics and Renewable Energy Faculy of Environmental EngineeringGeodesy and Renewable EnergyKielce University of TechnologyAleja Tysiaclecia Panstwa Polskiego 7.25-314 KielcePoland Thermal Research Laboratory(TRL) School of Mechanical Engineering.KIT Deemed to be UniversityBhubaneswarOdishaIndia Homi Bhabha National Instirute(HBNI) AnushaktinagarMumbai 400094India

According to the Scopus database,every year several hundreds of new research papers are published in the field of nanofluids.This area is attracting growing attention because of the significant improvement in the heat transfer and energy efficiency of the systems working with nanofluids.However,as results from numerous scientific studies conducted by independent laboratories,there are several fundamental problems related to the unambiguous determination of their physical properties,their production,and economic use.Although most studies often focus on one issue or cover one kind of research or math-ematical correlation,this review paper provides insights into many problems during nanofluids research by proposing solving possibilities,which is the strength of our work.The paper discusses the case of nanofluids quality,and morphology,thermal conductivity enhancement and the discrepancies in mathematical modelling,errors in dimensional and similarity analysis,nanofluid erosion,safety guide-lines,and toxicology tips.Moreover,the sustainability and economics of nanofluids usage are also being discussed.

关键词： Nanofluids Thermal conductivity Stability Erosion Economics Sustainability

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Genes linked to obesity-related infertility: bridging the knowledge gap

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生殖与发育医学(英文) 2024年第2期8卷 121-129页

作者： Sekar Praveen Kumar chandra Veerabathiran Ramakrishnan Human Cytogenetics and Genomics Laboratory Faculty of Allied Health Sciences Chettinad Academy of Research and Education Kelambakkam Tamil Nadu India

Genetic factors play a pivotal role in the complex relationship between obesity and infertility. This article delves into the genetics of obesity-related infertility, focusing on the essential genes and mechanisms in both sexes. We explored infertility factors in obese females, focusing on polycystic ovary syndrome (PCOS) and the influence of genes like insulin receptor (INSR), androgen receptor (AR), and follicle-stimulating hormone receptor (FSHR). Epigenetic changes are believed to contribute to PCOS-related infertility. The impact of adipokines and inflammation on obesity-related infertility has been discussed, with genes such as fat mass and obesity (FTO) and melanocortin-4-receptor (MC4R) playing significant roles. Genetic factors affecting sperm quality and function, including nuclear receptor subfamily 3 group C member 1 (NR3C1) and methylenetetrahydrofolate reductase (MTHFR), have been investigated in obesity-related infertility in males. Hormonal dysregulation influenced by genetic markers, such as leptin receptor (LEPR), tumor necrosis factor-alpha (TNF-α), and interleukin-6 (IL-6), was also examined. Genetic factors play a vital role in obesity-related infertility in both sexes. Genes involved in metabolism, hormonal regulation, and inflammation contribute to the complex association between obesity and infertility. Epigenetic changes further complicate the relationship. Understanding these genetic mechanisms is essential to address obesity-related infertility and develop personalized interventions.

关键词： Obesity Infertility PCOS DNA methylation Epigenetics

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An Autopsy and Histopathology-based Study to Ascertain the Cause of Death of Brought Dead Cases

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Journal of Forensic Science and Medicine 2024年第1期10卷 28-33页

作者： Chandan Bandyopadhyay Prabir chandra Paul Prabhas chandra Chakraborty Department of Forensic and State Medicine Medical CollegeKolkataWest BengalIndia Department of Pathology Jagannath Gupta Institute of Medical Science and HospitalKolkataWest BengalIndia Department of Forensic Medicine and Toxicology NRS Medical College and HospitalKolkataand M.G.M Medical College and L S.K HospitalKishanganjBiharIndia

Background and Objectives:The cases of apparent natural deaths are encountered in the hospital casualties who are noted dead at the time of the first medical attention and as such are labeled as“Brought Dead.”These include the cases of sudden death,unexplained death,and unattended death.The cause of such deaths is reported in the literature to emanate principally from the cardiovascular system,though there are some documented geographical,racial,and other variations.In the present study,we endeavored to detect the cause of such natural deaths in terms of the disease and the organ system involved,in the deceased individuals of the contemporary Bengali population,with cases due to obvious unnatural causes being excluded.Materials and Methods:An observational,cross-sectional study with 105(n=105,male:89,female:16)study subjects of age group of 20-80 years,selected by systemic random sampling,from the brought dead subjects coming to the mortuary of the NRS Medical College and Hospital for medicolegal autopsy from April 2011 to March 2012,excluding cases having a history of the obvious unnatural event.Organ system-wise gross examination was done,followed by tissue sampling for histopathological examination.The case-wise findings were tabulated and analyzed for descriptive statistics using SPSS software.Results:In the present study,89 cases were male(84.8%)and 16 cases were female(15.2%),which reflects a male:female ratio of 5.56:1.The dead bodies are mostly recovered from the footpaths(47 cases,44%).Sixty-four(61%)cases are of known identity.In 54 cases out of 105(51.4%),morbid pathology is detected in the respiratory system(RS),lobar pneumonia,and cavitary pulmonary tuberculosis being the most frequent disease entity,in both genders.Fifty-one years-sixty-five years is found to be the most commonly affected age group,in both genders.Interpretation and Conclusions:The present study shows that the most common organ system involved in brought dead cases is the RS,which is supported by a few Indian studies.

关键词： Autopsy brought dead cause of death histopathology

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Climate-change habitat shifts for the vulnerable endemic oak species(Quercus arkansana Sarg.)

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Journal of Forestry Research 2024年第1期35卷 117-127页

作者： Suresh chandra Subedi Seth Drake Binaya Adhikari Mark V.Coggeshall Department of Biological Sciences Arkansas Tech UniversityRussellvilleARUSA Department of Biology University of KentuckyLexingtonKYUSA School of Natural Resources University of Missouri203 ABNR BuildingColumbiaMO 65211USA

Quercus arkansana(Arkansas oak)is at risk of becoming endangered,as the total known population size is represented by a few isolated populations.The potential impact of climate change on this species in the near future is high,yet knowledge of its predicted effects is limited.Our study utilized the biomod2 R package to develop habi-tat suitability ensemble models based on bioclimatic and topographic environmental variables and the known loca-tions of current distribution of Q.arkansana.We predicted suitable habitats across three climate change scenarios(SSP1-2.6,SSP2-4.5,and SSP5-8.5)for 2050,2070,and 2090.Our findings reveal that the current suitable habitat for Q.arkansana is approximately 127,881 km^(2) across seven states(Texas,Arkansas,Alabama,Louisiana,Mississippi,Georgia,and Florida);approximately 9.5%is encompassed within state and federally managed protected areas.Our models predict that all current suitable habitats will disap-pear by 2050 due to climate change,resulting in a northward shift into new regions such as Tennessee and Kentucky.The large extent of suitable habitat outside protected areas sug-gests that a species-specific action plan incorporating pro-tected areas and other areas may be crucial for its conserva-tion.Moreover,protection of Q.arkansana habitat against climate change may require locally and regionally focused conservation policies,adaptive management strategies,and educational outreach among local people.

关键词： Biomod2 Climate change Conservation Habitat loss Habitat shift Species distribution modeling Oak species

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Flexible Covalent Organic Frameworks:Design,Synthesis,and Applications

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CCS Chemistry 2024年第4期6卷 856-881页

作者： Chunqing Ji Chengjun Kang Bidhan chandra Patra Dan Zhao Department of Chemical and Biomolecular Engineering National University of SingaporeSingapore 117585

Structural flexibility is an intriguing characteristic observed in materials that endows them with dynamic properties,allowing for intelligent adaptation and deformation in response to varying conditions.Covalent organic frameworks(COFs),a promising class of crystalline porous polymers,have garnered significant attention due to their unique features,including well-ordered,predesignable,and tunable structures,as well as their light-weighted nature and high thermal/chemical stability.Integrating flexibility into COFs offers a captivating pathway for developing advanced materials with dynamic properties and versatile functionalities.The flexible COF field is currently experiencing rapid expansion,and there is a growing need for systematic review articles that offer a comprehensive overview of the developments in this domain.In this mini-review,we delve into the factors that contribute to structural flexibility in COFs from the point of structural design.We summarize and categorize various modes of achieving flexibility across different dimensions,and discuss the potential applications of flexible COFs in vapor/gas adsorption,sensing,and smart membrane separations;further,we highlight their prospects and future research advancement.

关键词： covalent organic frameworks framework flexibility inducing factors flexibility modes smart materials

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Efficacy of intraovarian autologous platelet-rich plasma administration in women with low ovarian reserve: A systematic review and meta-analysis

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Asian pacific Journal of Reproduction 2024年第2期13卷 60-67页

作者： Yasmin Sabina Sa’diah Agung Dewanto Lukman A chandra Department of Obstetrics and Gynecology Faculty of MedicinePublic Health and NursingUniversitas Gadjah MadaYogyakartaIndonesia Department of Pharmacology and Therapy Faculty of MedicinePublic Health and NursingUniversitas Gadjah MadaYogyakartaIndonesia

Objective:To conduct a systematic examination and meta-analysis of the most reliable data from experimental studies evaluating the efficacy of autologous platelet-rich plasma(PRP)on low ovarian reserve.Methods:A comprehensive search was performed utilizing pertinent search terms across electronic databases,including PubMed,Cochrane,and Google Scholar.We included studies that assigned infertile women with low ovarian reserve in experimental studies.Ovarian reserve parameters were measured before and after PRP injection into ovaries.The data of each study was retrieved and subsequently compiled.Results:Of 301 articles collected and reviewed,six studies were finally included in the meta-analysis.Following PRP injection,infertile women showed a non-significant increase in anti-Mullerian hormone(AMH)level(MD=0.10;95%CI-0.04,0.23),a significant increase in antral follicular count(AFC)(MD=1.88;95%CI 0.47,3.29),and a non-significant reduction in follicle-stimulating hormone(FSH)level(MD=-0.22;95%CI-8.32,7.87).Conclusions:Autologous PRP may increase AFC,but not AMH.Although it is found beneficial in enhancing ovarian reserve(AFC),further research with strong evidence is still required.

关键词： Platelet-rich plasma Low ovarian reserve Ovarian rejuvenation

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