Time filter

Source Type

Patiāla, India

Kumar R.,Central University of Punjab | Mittal S.,Central University of Punjab | Arora M.,Multani Mal Modi College | Babu J.N.,Central University of Punjab
Journal of Soils and Sediments | Year: 2016

Purpose: Arsenic (As) contamination of groundwater has received significant attention recently in district Bathinda, due to consequent health risk in this region. Soil is the one of the primary medium for arsenic transport to groundwater. Thus, there is an essential requirement for understanding the retention capacity and mobility of arsenic in the soils to ensure sustainability of the groundwater in the locality. Arsenic interaction with various physicochemical properties of soil would provide a better understanding of its leaching from the soil. Materials and methods: Fifty-one soil samples were collected from two regions of Bathinda district with extensive agricultural practices, namely, Talwandi Sabo and Goniana. The soils were analyzed for arsenic content and related physicochemical characteristic of the soil which influence arsenic mobility in soil. Adsorption studies were carried out to identify the arsenic mobilization characteristic of the soil. SEM-EDX and sequential extraction of arsenic adsorbed soil samples affirmed the arsenic adsorption and its mobility in soil, respectively. Multiple regression models have been formulated for meaningful soil models for the prediction of arsenic transport behavior and understand the adsorption and mobilization of arsenic in the soil matrices. Results and discussion: Region-wise analysis showed elevated levels of arsenic in the soil samples from Goniana region (mean 9.58 mg kg−1) as compared to Talwandi Sabo block (mean 3.38 mg kg−1). Selected soil samples were studied for As(V) and As(III) adsorption behavior. The characteristic arsenic adsorption by these soil samples fitted well with Langmuir, Freundlich, Temkin, and D-R isotherm with a qmax in the range of 45 to 254 mg kg−1 and 116 to 250 mg kg−1 for As(III) and As(V), respectively. Adsorption isotherms indicate weak arsenic retention capacity of the soil, which is attributed to the sandy loam textured soil and excessive fertilizer usage in this region. PCM and MLR analysis of the soil arsenic content and its adsorption strongly correlated with soil physicochemical parameters, namely, Mn, Fe, total/available phosphorus, and organic matter. Conclusions: Manganese and iron content were firmly established for retention of arsenic in soil, whereas its mobility was influenced by organic matter and total/available phosphorus. The poor adsorptive characteristic of these soils is the primary cause of higher arsenic concentration in groundwater of this region. A strong correlation between monitored arsenic and adsorbed As(III) with manganese suggests As(III) as the predominant species present in soil environment in this region. © 2015, Springer-Verlag Berlin Heidelberg.

Sharma A.K.,Central University of Punjab | Kumar R.,Central University of Punjab | Mittal S.,Central University of Punjab | Hussain S.,UGC-DAE Consortium for Scientific Research | And 3 more authors.
RSC Advances | Year: 2015

Zerovalent iron nanoparticles (nZVI) (11.8 ± 0.2% w/w) immobilized on microcrystalline cellulose (C-nZVI) were synthesized and studied for Cr(vi) sorption. The material showed good atom economy for Cr(vi) adsorption (562.8 mg g-1 of nZVI). Oxidation of cellulose to cellulose dialdehyde leads to in situ regeneration of nZVI which is responsible for the atom efficient Cr(vi) sorption by C-nZVI. © The Royal Society of Chemistry.

Silakari P.,Dr Hari Singh Gour University | Srivastava S.D.,Dr Hari Singh Gour University | Kohli D.V.,Dr Hari Singh Gour University | Srivastava S.K.,Dr Hari Singh Gour University | And 3 more authors.
Medicinal Chemistry Research | Year: 2011

Three-dimensional quantitative structure activity relationship (3D-QSAR) models was developed using molecular field analysis (MFA) for 36 anilinoquinazoline derivatives, inhibiting c-Src kinase. The QSAR model was developed using 29 compounds and its predictive ability was assessed using a test set of seven compounds. The predictive 3D-QSAR model has conventional r2 values of 0.961 while the cross-validated coefficient q 2 and bootstrap correlation coefficient rBS 2 values of 0.910 and 0.957, respectively. The developed model provides a powerful tool to design potent c-Src inhibitors as novel antitumor agents. Six new inhibitors were designed and their pIC50 were predicted. © 2010 Springer Science+Business Media, LLC.

Kumar A.,Multani Mal Modi College | Goyal V.,Punjabi University
Communications in Computer and Information Science | Year: 2011

Statistical Machine Translation model take the view that every sentence in the target language is a translation of the source language sentence with some probability. The best translation, of course, is the sentence that has the highest probability. A large sample of human translated text (parallel corpus) is examined by the SMT algorithms for automatic learning of translation parameters. SMT has undergone tremendous development in last two decades. A large number of tools has been developed for SMT and put to work on different language pairs with fair accuracy. This paper will give brief introduction to Statistical Machine Translation; tools available for developing Statistical Machine Translation systems based on Statistical approach and their comparative study. This paper will help researcher in finding the information about SMT tools at one place. © 2011 Springer-Verlag.

Teena P.,Mm University | Raman K.,Mm University | Jagjit K.,Mm University | Kuldeep K.,Multani Mal Modi College
Research Journal of Pharmacy and Technology | Year: 2014

Cannabis sativa Linnaeus (Cannabaceae) is a widely used plant of therapeutic and industrial importance. It produces two pigments: cannabinoids and tetrahydrocannabinol (THC), THC is responsible for its psychoactive properties which make its use important in medical field. The main objective of present work was to construct a biosensor using L-asparaginase extracted from C. sativa, the biosensor will be used for the measurement of asparagine levels in leukemic serum samples. Different immobilizing techniques such as Whatman filter paper, gelatin, agarose, agar, calcium alginate and hydrosol gel on nylon membrane were applied to develop a biosensor. Phenol red indicator was co immobilized with the enzyme and the change in color was noted which gave the indication of asparagine level. Hydrosol gel technique was the most suitable one with the fastest response time of 6-10 seconds, the detection range was 10-1 M to 10-10 M. The response time for the developed biosensor was lesser as compared to the earlier works. The biosensor fabricated from C. sativa is an efficient one as it gives fast response and a higher detection range. © 2014 Research Journal of Pharmacy and Technology All right reserved.

Discover hidden collaborations