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Adherence to self-care practices, glycemic status and influencing factors in diabetes patients in a tertiary care hospital in Delhi

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World Journal of Diabetes 2018年第5期9卷 72-79页

作者： Saurav Basu Suneela Garg Nandini Sharma m meghachandra Singh sandeep Garg Department of Community medicine Maulana Azad Medical College Department of medicine Maulana Azad Medical College

AIm To assess the adherence to self-care practices,glycemic status and influencing factors in diabetes *** This was a cross-sectional observational analysis of baseline data from a quasi-experimental study conducted among 375 diabetic patients aged between 18 to 65years at a major public tertiary care centre in New Delhi,India during February-September’*** Summary of Diabetes Self-care activities measure was used to assess medical adherence in diabetic *** ended questions were used to identify facilitators and inhibitors of medical *** mean age of the study subjects was 49.7±10.2 years.A total of 201 men and 174 women were enrolled in the *** hundred nine(82.4%)subjects were adherent to their intake of anti-diabetic *** binary logistic regression,education level below primary school completion and absence of hypertensioncomorbidity were found to be independent predictors of medication *** resistance was an important factor impeding outdoor exercise among younger *** of diabetes in the study subjects was low with mean score of 3.1±2(maximum score=10).Suboptimal glycemic control was found in259(69%)subjects which was significantly more likely in patients on Insulin therapy compared to those on Oral Hypoglycemic agents alone(Pmedication adherence and glycemic *** suggests the need for enhanced physician focus for diabetic patient management.

关键词： Diabetes Adherence Glycemic control Insulin India

Influence of precursor solution concentration on the structural, optical and humidity sensing properties of spray-deposited TiO_2 thin films

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Journal of Semiconductors 2018年第12期39卷 13-18页

作者： Dipak L Gapale sandeep A Arote Balasaheb m Palve Ratan Y Borse S.N. Arts D.J.M. Commerce and B.N.S. Science College Sangamner Thin and Thick Film Laboratory Dept.of Electronics M.S.G. College Malegaon Camp (Pin 423105)

In the present paper,the influence of precursor concentration on the structural,optical,and humidity sensing properties of spray-deposited titanium dioxide(TiO) films are investigated. The TiOthin films were successfully deposited by spraying different precursor concentrations such as 0.075 m, 0.1 m, and 0.125 m of titanium trichloride solution onto glass substrates. X-ray diffractometry(XRD) studies confirmed the polycrystalline anatase phase of TiOwith dominant(101) plane. The crystallite size was found to increase with the increase in precursor concentration. The micro-strain and dislocation density in the film was observed to decrease as the crystallite size increased. The UV-vis spectra confirmed the optical absorbance edge of the samples shifted toward lower wavelengths with increased precursor concentration. The humidity sensing properties of the synthesized material were measured by monitoring the change in resistance of the sample with the change in relative *** material synthesized with 0.1 m precursor concentration, by using the spray pyrolysis method,shows good sensitivity and has a response time of 77.5 s and fast recovery time of 3 s.

关键词： titanium dioxide spray pyrolysis structural electrical gas sensing

Chemical composition and source apportionment of Pm2.5 and Pm2.5-10 in Trombay （mumbai, India）, a coastal industrial area

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Particuology 2018年第2期16卷 143-153页

作者： sandeep Police Sanjay Kumar Sahu mahesh Tiwari Gauri Girish Pandit Environmental monitoring and Assessment Section Bhabha Atomic Research Centre Mumbai 400085 India Homi Bhabha National Institute Anushakti Nagar Mumbai 400094 India

Pm2.5 and Pm2.5 lo concentrations, elemental constituents, and sources in a densely populated coastal industrial area （Trombay, mumbai） were investigated in 2010 and *** Pm2.s and Pm2.s lo concentra- tions were 13.50-71.60 and 22.40-127.78 p^g/m3, respectively. The daily Pm25 concentrations exceeded the Indian Central Pollution Control Board limit （60 μg/m3） several days in winter. Of the elements analyzed, Si then Al had the highest concentrations in Pm2.5- 10, but black carbon then Si had the highest concentrations in Pm2.s. The element concentrations varied widely by season. Al, Ca, Fe, Si, and Ti con- centrations were highest in summer, Cl, mg, and Na concentrations were highest in the monsoon season, and the other trace metal concentrations in both Pm2.5 and Pm2.5-10 were highest in winter. The Pm2.5 and Pm2.5-10 sources were apportioned by positive matrix factorization. Pm2.5 and Pm2.5-10 had six dominant sources, crustal material （8.7% and 25.3%, respectively）, sea salt spray （6.1% and 15.0%, respectively）, coal/biomass combustion （25.5% and 13.8%, respectively）, fuel oil combustion （19.0% and 11.2%, respectively）, road traffic （ 17.7% and 12.6%, respectively）, and the metal industry （ 10.6% and 7.0%, respectively）. Anthropogenic sources clearly contributed most to Pm2.5 but natural sources contributed most to Pm2.5-10.

关键词： Trombay Pm2.5 Pm2.5-10 Black carbon metals Positive matrix factorization

Chlorination roasting-coupled water leaching process for potash recovery from waste mica scrap using dry marble sludge powder and sodium chloride

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International Journal of minerals,metallurgy and materials 2020年第9期27卷 1203-1215页

作者： sandeep Kumar Jena Jogeshwar Sahu Geetikamayee Padhy Swagatika mohanty Ajit Dash mineral Processing and Central Characterization Department Council of Scientific and Industrial Research(CSIR)-Institute of Minerals and Materials Technology(IMMT)BhubaneswarOdisha 751013India

The present paper reports the effective utilization of marble sludge powder(mSP)for the recovery of potash values from waste mica scrap using chlorination roasting-water leaching *** studies indicated the presence of dolomite as the major mineral phase in mSP,whereas muscovite and quartz were observed in the mica *** acid leaching studies suggest a maximum of 22%potash recovery under conditions:4 m H2SO4 acid,particle size of^100μm,stirring speed of 600 r/min,leaching temperature of 75℃,and leaching time of 90 *** chlorination roasting-water leaching process was adopted to achieve the lowest level of 80%-90%potash *** optimum conditions for the recovery of^93%potash from mica(~8.6wt%K2O)requires 900℃ roasting temperature,30 min roasting time,and 1:1:0.75 mass ratio of mica:mSP:*** roasting temperature and amount of NaCl are found to be the most important factors for the recovery *** reaction mechanism suggests the formation of different mineral phases,including sylvite(KCl),wollastonite,kyanite,and enstatite,during roasting,which were confirmed by X-ray diffraction(XRD)analyses and scanning electron microscopy(SEm)*** mSP-blended NaCl additive is more effective for potash recovery compared with the other reported commercial roasting additives.

关键词： potash recovery mica scrap marble sludge powder chlorination roasting water leaching

Imbalanced Classification in Diabetics Using Ensembled machine Learning

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Computers, materials & Continua 2022年第9期72卷 4397-4409页

作者： m.sandeep Kumar mohammad Zubair Khan Sukumar Rajendran Ayman Noor A.Stephen Dass J.Prabhu School of Information Technology and Engineering Vellore Institute of TechnologyVelloreTamil Nadu632014India Department of Computer Science and Information Taibah UniversityMedinaSaudi Arabia College of Computer Science and Engineering Taibah UniversityMedinaSaudi Arabia

Diabetics is one of the world’s most common diseases which are caused by continued high levels of blood *** risk of diabetics can be lowered if the diabetic is found at the early *** recent days,several machine learning models were developed to predict the diabetic presence at an early *** this paper,we propose an embedded-based machine learning model that combines the split-vote method and instance duplication to leverage an imbalanced dataset called PImA Indian to increase the prediction of *** proposed method uses both the concept of over-sampling and under-sampling along with model weighting to increase the performance of *** measures such as Accuracy,Precision,Recall,and F1-Score are used to evaluate the *** results we obtained using K-Nearest Neighbor(kNN),Naïve Bayes(NB),Support Vector machines(SVm),Random Forest(RF),Logistic Regression(LR),and Decision Trees(DT)were 89.32%,91.44%,95.78%,89.3%,81.76%,and 80.38%*** SVm model is more efficient than other models which are 21.38%more than exiting machine learning-based works.

关键词： Diabetics classification imbalanced data split-vote instance duplication

Hybrid generative regressionbased deep intelligence to predict the risk of chronic disease

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International Journal of Intelligent Computing and Cybernetics 2022年第1期15卷 144-164页

作者： sandeep Kumar Hegde monica R.mundada Department of Computer Science and Engineering M.S.Ramaiah Institute of TechnologyBangaloreIndia Department of Computer Science and Engineering NMAM Institute of TechnologyNitteIndia Visvesvaraya Technological University BelagaviIndia

Purpose-Chronic diseases are considered as one of the serious concerns and threats to public health across the *** such as chronic diabetes mellitus(CDm),cardio vasculardisease(CVD)and chronic kidney disease(CKD)are major chronic diseases responsible for millions of *** of these diseases is considered as a risk factor for the other two ***,noteworthy attention is being paid to reduce the risk of these *** amount of medical data is generated in digital form from smart healthcare appliances in the current *** numerous machine learning(mL)algorithms are proposed for the early prediction of chronic diseases,these algorithmic models are neither generalized nor adaptive when the model is imposed on new disease ***,these algorithms have to process a huge amount of disease data iteratively until the model *** limitation may make it difficult formLmodels to fit and produce imprecise results.A single algorithm may not yield accurate ***,an ensemble of classifiers built from multiple models,that works based on a voting principle has been successfully applied to solve many classification *** purpose of this paper is to make early prediction of chronic diseases using hybrid generative regression based deep intelligence network(HGRDIN)***/methodology/approach-In the proposed paper generative regression(GR)model is used in combination with deep neural network(DNN)for the early prediction of chronic *** GR model will obtain prior knowledge about the labelled data by analyzing the correlation between features and class ***,the weight assignment process of DNN is influenced by the relationship between attributes rather than random *** knowledge obtained through these processes is passed as input to the DNN network for further *** the inference about the input data instances is drawn at the DNN through the GR model,the model is named as

关键词： Deep neural network Generative regression Chronic disease Regularization maximum likelihood estimation

Unstructured Oncological Image Cluster Identification Using Improved Unsupervised Clustering Techniques

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Computers, materials & Continua 2022年第7期72卷 281-299页

作者： S.Sreedhar Kumar Syed Thouheed Ahmed Qin Xin S.sandeep m.madheswaran Syed muzamil Basha Dr.T.Thimmaiah Institute of Technology VTUKGFKarnatakaIndia School of Computing&Information Technology REVA UniversityBengaluruIndia Faculty of Science and Technology University of the Faroe IslandsFaroe IslandsDenmark K S School of Engineering BengaluruIndia muthayammal Engineering College RasipuramTamil NaduIndia

This paper presents,a new approach of medical Image Pixels Clustering(mIPC),aims to trace the dissimilar patterns over the magnetic Resonance(mR)image through the process of automatically identify the appropriate number of distinct clusters based on different improved unsupervised clustering schemes for enrichment,pattern predication and deeper *** proposed mIPC consists of two stages:clustering and *** the clustering stage,the mIPC automatically identifies the distinct number of dissimilar clusters over the gray scale mR image based on three different improved unsupervised clustering schemes likely improved Limited Agglomerative Clustering(iLIAC),Dynamic Automatic Agglomerative Clustering(DAAC)and Optimum N-means(ONm).In the second stage,the performance of mIPC approach is estimated by measuring Intra intimacy and Intra contrast of each individual cluster in the result of mR image based on proposed validation method namely Shreekum Intra Cluster measure(SICm).Experimental results showthat the mIPC approach is better suited for automatic identification of highly relative dissimilar clusters over the mR cancer images with higher Intra closeness and lower Intra contrast based on improved unsupervised clustering schemes.

关键词： magnetic resonance image unsupervised clustering scheme intra intimacy intra contrast iLIAC shreekum intra cluster measure medical image clustering

Changes in soil biochemical indicators at different wheat growth stages under conservation-based sustainable intensification of rice-wheat system

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Journal of Integrative Agriculture 2018年第8期17卷 1871-1880页

作者： Tanushree Bera sandeep Sharma H.S.Thind Yadvinder-Singh H.S.Sidhu m.L.Jat Department of Soil Science Punjab Agricultural University Borlaug Institute for South Asia (BISA) International Maize and Wheat Improvement Center (CIMMYT) CImmYT National Agricultural Science Complex

Soil microbes play critical roles in soil biogeochemistry, soil biological health and crop productivity. The current study evaluated the effects of tillage and residue management on changes in soil biochemical indicators at different growth stages of wheat after 5 years of rice-wheat system. Nine treatment combinations of tillage, crop establishment and crop residue management included three main plot treatments applied to rice:(1) conventional till direct dry seeded rice(CTDSR),(2) zero till direct dry seeded rice(ZTDSR), and(3) conventional puddled manual transplanted rice(CTPTR) and three subplot treatments in subsequent wheat:(1) conventional tillage with rice residue removed(CTW-R),(2) zero tillage with rice residue removed(ZTW-R) and(3) zero tillage with rice residue retained as surface mulch(ZTW+R). Irrespective of rice treatments, ZTW+R treatment had higher soil biochemical indicators compared with ZTW-R and CTW-R at all the growth stages of wheat. Generally, all the biochemical indicators were the highest at the flowering stage of wheat. Residual effect of rice treatments was also significant on biochemical quotients in wheat, which were the highest under ZTDSR followed by CTDSR and CTPTR. The present study provided three sensitive and reliable biochemical indicators(microbial biomass, basal soil respiration and microbial quotient) which respond rapidly to change in tillage and residue management practices in RWS of South Asia.

关键词： microbial metabolic quotients tillage practices residue retention cropping system

Root Structure,Distribution and Biomass in Five multipurpose Tree Species of Western Himalayas

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Journal of mountain Science 2014年第2期11卷 519-525页

作者： Kartar Singh VERmA sandeep KOHLI Rajesh KAUSHAL Om Parkash CHATURVEDI Department of Silviculture and Agroforestry Dr Yashwant Singh Parmar University of Horticulture & Forestry Plant Science Division Central Soil and Water Conservation Reserach & Training Institute

【Title】【Author】【Addresses】1The tree root distribution pattern and biomass of seventeen year old trees of Grewia optiva, morus alba, Celtis australis, Bauhinia variegata and Robinia pseudoacacia were studied by excavation method. B. variegata roots penetrated to a maximum depth of 4.78 m, whereas, m. alba roots were found down to 1.48 m depth. Lateral spread was minimum in B. variegata （1.10 m）and maximum inR. pseudoacacia （7.33 m）. maximum root biomass of 6.30 kg was found in R. pseudoacacia and minimum （2.43 kg） was found in m. alba. For four species viz.,G. optiva, m. alba, C. australis andR. pseudoacacia, 68%-87% root biomass occurred within top 0-30 cm soil depth, but forB. variegata this was only45%. The soil binding factor was maximum in G. optiva and minimum in B. variegata. Soil physico-chemical properties also showed wide variation. The study suggests thatB. variegata with a deep root system is the most suitable species for plantation under agroforestry systems. R. pseudoacacia and G. optiva with deep root systems, more lateral spread and high soil binding factor are suitable for plantation on degraded lands for soil conservation.

关键词： Root categories Root distribution Root biomass Soil binding factor Soil conservation Nutrients