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Search Results: 1 - 10 of 130683 matches for " V. Mushrif Tripathy "
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Infection, Disease, and Biosocial Processes at the End of the Indus Civilization
Gwen Robbins Schug, K. Elaine Blevins, Brett Cox, Kelsey Gray, V. Mushrif-Tripathy
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0084814
Abstract: In the third millennium B.C., the Indus Civilization flourished in northwest India and Pakistan. The late mature phase (2200-1900 B.C.) was characterized by long-distance exchange networks, planned urban settlements, sanitation facilities, standardized weights and measures, and a sphere of influence over 1,000,000 square kilometers of territory. Recent paleoclimate reconstructions from the Beas River Valley demonstrate hydro-climatic stress due to a weakened monsoon system may have impacted urban centers like Harappa by the end of the third millennium B.C. the impact of environmental change was compounded by concurrent disruptions to the regional interaction sphere. Climate, economic, and social changes contributed to the disintegration of this civilization after 1900 B.C. We assess evidence for paleopathology to infer the biological consequences of climate change and socio-economic disruption in the post-urban period at Harappa, one of the largest urban centers in the Indus Civilization. Bioarchaeological evidence demonstrates the prevalence of infection and infectious disease increased through time. Furthermore, the risk for infection and disease was uneven among burial communities. Corresponding mortuary differences suggest that socially and economically marginalized communities were most vulnerable in the context of climate uncertainty at Harappa. Combined with prior evidence for increasing levels of interpersonal violence, our data support a growing pathology of power at Harappa after 2000 B.C. Observations of the intersection between climate change and social processes in proto-historic cities offer valuable lessons about vulnerability, insecurity, and the long-term consequences of short-term strategies for coping with climate change.
Ancient Skeletal Evidence for Leprosy in India (2000 B.C.)
Gwen Robbins, V. Mushrif Tripathy, V. N. Misra, R. K. Mohanty, V. S. Shinde, Kelsey M. Gray, Malcolm D. Schug
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0005669
Abstract: Background Leprosy is a chronic infectious disease caused by Mycobacterium leprae that affects almost 250,000 people worldwide. The timing of first infection, geographic origin, and pattern of transmission of the disease are still under investigation. Comparative genomics research has suggested M. leprae evolved either in East Africa or South Asia during the Late Pleistocene before spreading to Europe and the rest of the World. The earliest widely accepted evidence for leprosy is in Asian texts dated to 600 B.C. Methodology/Principal Findings We report an analysis of pathological conditions in skeletal remains from the second millennium B.C. in India. A middle aged adult male skeleton demonstrates pathological changes in the rhinomaxillary region, degenerative joint disease, infectious involvement of the tibia (periostitis), and injury to the peripheral skeleton. The presence and patterning of lesions was subject to a process of differential diagnosis for leprosy including treponemal disease, leishmaniasis, tuberculosis, osteomyelitis, and non-specific infection. Conclusions/Significance Results indicate that lepromatous leprosy was present in India by 2000 B.C. This evidence represents the oldest documented skeletal evidence for the disease. Our results indicate that Vedic burial traditions in cases of leprosy were present in northwest India prior to the first millennium B.C. Our results also support translations of early Vedic scriptures as the first textual reference to leprosy. The presence of leprosy in skeletal material dated to the post-urban phase of the Indus Age suggests that if M. leprae evolved in Africa, the disease migrated to India before the Late Holocene, possibly during the third millennium B.C. at a time when there was substantial interaction among the Indus Civilization, Mesopotamia, and Egypt. This evidence should be impetus to look for additional skeletal and molecular evidence of leprosy in India and Africa to confirm the African origin of the disease.
Present status of understanding on the G6PD deficiency and natural selection
Tripathy V,Reddy B
Journal of Postgraduate Medicine , 2007,
Abstract: G6PD deficiency is a common hemolytic genetic disorder, particularly in the areas endemic to malaria. Individuals are generally asymptomatic and hemolytic anemia occurs when some anti-malarial drugs or other oxidizing chemicals are administered. It has been proposed that G6PD deficiency provides protection against malaria. Maintaining of G6PD deficient alleles at polymorphic proportions is complicated because of the X-linked nature of G6PD deficiency. A comprehensive review of the literature on the hypothesis of malarial protection and the nature of the selection is being presented. Most of the epidemiological, in vitro and in vivo studies report selection for G6PD deficiency. Analysis of the G6PD gene also reveals that G6PD-deficient alleles show some signatures of selection. However, the question of how this polymorphism is being maintained remains unresolved because the selection/fitness coefficients for the different genotypes in the two sexes have not been established. Prevalence of G6PD deficiency in Indian caste and tribal populations and the different variants reported has also been reviewed.
Optimal Promotion and Replenishment Policies for Profit Maximization Model under Lost Units  [PDF]
Pradip Kumar Tripathy, Monalisha Pattnaik, Prakash Tripathy
American Journal of Operations Research (AJOR) , 2012, DOI: 10.4236/ajor.2012.22031
Abstract: Ever since its introduction in the second decade of the past century, the economic order quantity (EOQ) model has been the subject of extensive investigations and extensions by academicians. The physical characteristics of stocked items dictate the nature of inventory policies implemented to manage and control. The question is how reliable are the EOQ models when items stocked deteriorate one time. This paper introduces a modified EOQ model in which it assumes that a percentage of the on-hand inventory is wasted due to deterioration. There is hidden cost not account for when modeling inventory cost. We study the problem of promotion for a deteriorating item subject to loss of these deteriorated units. The objective of this paper is to determine the optimal time length, optimal units lost due to deterioration, the promotional effort and the replenishment quantity so that the net profit is maximized and the numerical analysis show that an appropriate promotion policy can benefit the retailer and that promotion policy is important, especially for deteriorating items. Furthermore crisp decision making is shown to be superior to crisp decision making without promotional effort cost in terms of profit maximization.
Privacy Preserving Two-Party Hierarchical Clustering Over Vertically Partitioned Dataset  [PDF]
Animesh Tripathy, Ipsa De
Journal of Software Engineering and Applications (JSEA) , 2013, DOI: 10.4236/jsea.2013.65B006
Abstract: Data mining has been a popular research area for more than a decade. There are several problems associated with data mining. Among them clustering is one of the most interesting problems. However, this problem becomes more challenging when dataset is distributed between different parties and they do not want to share their data. So, in this paper we propose a privacy preserving two party hierarchical clustering algorithm vertically partitioned data set. Each site only learns the final cluster centers, but nothing about the individual’s data.
Microsatellite diversity among the primitive tribes of India
Mukherjee Malay,Tripathy V,Colah R,Solanki P
Indian Journal of Human Genetics , 2009,
Abstract: The present study was undertaken to determine the extent of diversity at 12 microsatellite short tandem repeat (STR) loci in seven primitive tribal populations of India with diverse linguistic and geographic backgrounds. DNA samples of 160 unrelated individuals were analyzed for 12 STR loci by multiplex polymerase chain reaction (PCR). Gene diversity analysis suggested that the average heterozygosity was uniformly high (> 0.7) in these groups and varied from 0.705 to 0.794. The Hardy-Weinberg equilibrium analysis revealed that these populations were in genetic equilibrium at almost all the loci. The overall G ST value was high (G ST = 0.051; range between 0.026 and 0.098 among the loci), reflecting the degree of differentiation/heterogeneity of seven populations studied for these loci. The cluster analysis and multidimensional scaling of genetic distances reveal two broad clusters of populations, besides Moolu Kurumba maintaining their distinct genetic identity vis-à-vis other populations. The genetic affinity for the three tribes of the Indo-European family could be explained based on geography and Language but not for the four Dravidian tribes as reflected by the NJT and MDS plots. For the overall data, the insignificant MANTEL correlations between genetic, linguistic and geographic distances suggest that the genetic variation among these tribes is not patterned along geographic and/or linguistic lines.
A Framework for Intelligent Medical Diagnosis Using Rough Set with Formal Concept Analysis
B. K. Tripathy,D. P. Acharjya,V. Cynthya
International Journal of Artificial Intelligence & Applications , 2011,
Abstract: Medical diagnosis process vary in the degree to which they attempt to deal with different complicating aspects ofdiagnosis such as relative importance of symptoms, varied symptom pattern and the relation between diseases themselves. Based on decision theory, in the past many mathematical models such as crisp set, probability distribution,fuzzy set, intuitionistic fuzzy set were developed to deal with complicating aspects of diagnosis. But, many suchmodels are failed to include important aspects of the expert decisions. Therefore, an effort has been made to processinconsistencies in data being considered by Pawlak with the introduction of rough set theory. Though rough set hasmajor advantages over the other methods, but it generates too many rules that create many difficulties while takingdecisions. Therefore, it is essential to minimize the decision rules. In this paper, we use two processes such as preprocess and post process to mine suitable rules and to explore the relationship among the attributes. In pre processwe use rough set theory to mine suitable rules, whereas in post process we use formal concept analysis from thesesuitable rules to explore better knowledge and most important factors affecting the decision making.
A Framework for Intelligent Medical Diagnosis using Rough Set with Formal Concept Analysis
B. K. Tripathy,D. P. Acharjya,V. Cynthya
Computer Science , 2013,
Abstract: Medical diagnosis process vary in the degree to which they attempt to deal with different complicating aspects of diagnosis such as relative importance of symptoms, varied symptom pattern and the relation between diseases them selves. Based on decision theory, in the past many mathematical models such as crisp set, probability distribution, fuzzy set, intuitionistic fuzzy set were developed to deal with complicating aspects of diagnosis. But, many such models are failed to include important aspects of the expert decisions. Therefore, an effort has been made to process inconsistencies in data being considered by Pawlak with the introduction of rough set theory. Though rough set has major advantages over the other methods, but it generates too many rules that create many difficulties while taking decisions. Therefore, it is essential to minimize the decision rules. In this paper, we use two processes such as pre process and post process to mine suitable rules and to explore the relationship among the attributes. In pre process we use rough set theory to mine suitable rules, whereas in post process we use formal concept analysis from these suitable rules to explore better knowledge and most important factors affecting the decision making.
Genetic variability based on isozyme polymorphism among Fusarium oxysporum f. sp. ciceri isolates inciting wilt in chickpea
S.K. MUSHRIF* DEEPA KHULBE
Indian Phytopathology , 2011,
Abstract: Biochemical variability among the three isolates of Fusarium oxysporum f. sp. ciceri inciting wilt in chickpea was determined using starch gel electrophoresis technique involving five isozymes. The five isozymes tested in electrophoretic studies viz. Glucose-6-Phosphate dehydrogenase (G6PDH), 6 Phosphogluconate dehydrogenase (6PGDH), Malate dehydrogenase (MDH), Isocitrate dehydrogenase (IDH) and Superoxide dismutase (SOD) gave distinct isozyme profiles. These studies indicated that the Bangalore isolate differed from Gulbarga and Race-1(a designated race from ICRISAT) isolates. It was also noticed that the Gulbarga isolate was genetically closer to the Race-1 isolate. Bangalore isolate seems to be a novel evolving race of F. oxysporum f. sp. ciceri.
Histopathological Image Analysis Using Image Processing Techniques: An Overview
A. D. Belsare,M. M. Mushrif
Signal & Image Processing , 2012,
Abstract: This paper reviews computer assisted histopathology image analysis for cancer detection and classification. Histopathology refers to the examination of invasive or less invasive biopsy sample by a pathologist under microscope for locating, analyzing and classifying most of the diseases like cancer. The analysis of histoapthological image is done manually by the pathologist to detect disease which leads to subjective diagnosis of sample and varies with level of expertise of examiner. The pathologist examine the tissue structure, distribution of cells in tissue, regularities of cell shapes and determine benign and malignancy in image. This is very time consuming and more prone to intra and inter observer variability. To overcome this difficulty a computer assisted image analysis is needed for quantitative diagnosis oftissue. In this paper we reviews and summarize the applications of digital image processing techniquesfor histology image analysis mainly to cover segmentation and disease classification methods.
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