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Institution

Jadavpur University

EducationKolkata, India
About: Jadavpur University is a education organization based out in Kolkata, India. It is known for research contribution in the topics: Population & Fuzzy logic. The organization has 10856 authors who have published 27678 publications receiving 422069 citations. The organization is also known as: JU & Jadabpur University.


Papers
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Journal ArticleDOI
TL;DR: In this article, Fenton's reagent (Fe 2+ and H 2 O 2 ) was used to study the oxidative degradation of two direct dyes, Blue 2B (B54) and Red 12B (R31), in aqueous solution.

491 citations

Journal ArticleDOI
TL;DR: In this article, the authors reviewed the tribological advancement of different electroless nickel coatings based on the bath types, structure and also the tribo testing parameters in recent years.

477 citations

Journal ArticleDOI
TL;DR: A test for these two parameters is suggested to be a more stringent requirement than the traditional validation parameters to decide acceptability of a predictive QSAR model, especially when a regulatory decision is involved.
Abstract: Validation is a crucial aspect of quantitative structure-activity relationship (QSAR) modeling. The present paper shows that traditionally used validation parameters (leave-one-out Q(2) for internal validation and predictive R(2) for external validation) may be supplemented with two novel parameters r(m)(2) and R(p)(2) for a stricter test of validation. The parameter r(m)(2)((overall)) penalizes a model for large differences between observed and predicted values of the compounds of the whole set (considering both training and test sets) while the parameter R(p)(2) penalizes model R(2) for large differences between determination coefficient of nonrandom model and square of mean correlation coefficient of random models in case of a randomization test. Two other variants of r(m)(2) parameter, r(m)(2)((LOO)) and r(m)(2)((test)), penalize a model more strictly than Q(2) and R(2)(pred) respectively. Three different data sets of moderate to large size have been used to develop multiple models in order to indicate the suitability of the novel parameters in QSAR studies. The results show that in many cases the developed models could satisfy the requirements of conventional parameters (Q(2) and R(2)(pred)) but fail to achieve the required values for the novel parameters r(m)(2) and R(p)(2). Moreover, these parameters also help in identifying the best models from among a set of comparable models. Thus, a test for these two parameters is suggested to be a more stringent requirement than the traditional validation parameters to decide acceptability of a predictive QSAR model, especially when a regulatory decision is involved.

474 citations

Journal ArticleDOI
TL;DR: In this article, some additional variants of r m 2 metrics have been proposed and their applications in judging the quality of predictions of QSPR models have been shown by analyzing results of the QSPr models obtained from three different data sets (n = 119, 90, and 384).

467 citations

Journal ArticleDOI
16 Aug 2002-Talanta
TL;DR: Groundwater arsenic (As) contamination in West Bengal (WB, India) was first reported in December 1983, when 63 people from three villages of two districts were identified by health officials as suffering from As toxicity, and after years of research, additional affected villages are being identified on virtually every new survey.

466 citations


Authors

Showing all 10999 results

NameH-indexPapersCitations
Subir Sarkar1491542144614
Amartya Sen149689141907
Susumu Kitagawa12580969594
Praveen Kumar88133935718
Rodolphe Clérac7850622604
Rajesh Gupta7893624158
Santanu Bhattacharya6740014039
Swagatam Das6437019153
Anupam Bishayee6223711589
Michael G. B. Drew61131524747
Soujanya Poria5717513352
Madeleine Helliwell543709898
Tapas Kumar Maji542539804
Pulok K. Mukherjee5429610873
Dipankar Chakraborti5411512078
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202385
2022332
20211,949
20201,936
20191,737
20181,807