425 research outputs found
First person – Shweta Yadav
No full textABSTRACT
First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Shweta Yadav is the first author on ‘RDGBα localization and function at membrane contact sites is regulated by FFAT–VAP interactions’, published in Journal of Cell Science. Shweta is a post-doctoral associate in the laboratory of Prof. Juan Botas at Baylor College of Medicine, Texas, USA, investigating neurodegenerative diseases.</jats:p
The social correlates of value consensus
No full textThis paper examines societal value consensus, or the extent to which individuals within a culture share similar values. This topic has been extensively theoretically discussed, but has received limited empirical attention. This paper explores the social variables of economic equality, religiosity and religious homogeneity and their relation to value consensus. Publicly available data from the latest wave of World Values Survey (N = 73,256), CIA world factbook and the World Bank World Development Indicators are used for analysis. Results reveal that value consensus is not correlated with religiosity, religious homogeneity or economic equality. Implications of these findings, with specific reference to economic developmental theories are discussed.M.A.Includes bibliographical referencesby Shweta A. Kulkarn
Adaptive geolocation based interference control for hierarchical cellular network with femtocells
No full textThis thesis presents adaptive interference control methods to mitigate undesirable interference effects from femtocells to macrocell users in hierarchical cellular networks. The study in this thesis begins by quantifying the deterioration in performance experienced by macrocell users on the downlink in a simulated 3G/CDMA environment. Our baseline results show that the median deterioration in signal-to-interference plus noise ratio (SINR) observed for the macrocell users may be up to 10dB and the outage probability increases by large extend. In the next part of study, we propose interference mitigation schemes - ‘Proximity Based Iterative’ (PBI) scheme and ‘Adaptive Interference Scaling’ (AIS) scheme to adjust femtocell power to reduce femtocell interference effect on macrocell users. We show that previously studied mechanisms like the load-spillage, utility based power adaptation usually require relatively high system overhead due to over-the-air signalling for estimation of interference. Proposed PBI and AIS schemes avoid such over-the-air signalling and make use of geo-location information and backhaul signalling for the femtocell interference estimation. These schemes achieve power re-distribution by scaling power uniformly across femtocells, while allowing the network operators to set desired target data rates. Results from simulations show that the PBI and AIS schemes are able to increase the number of macrocell users achieving chosen target data rates by up to 158% when compared with the value when femtocell transmission power is at maximum. However, in case of the PBI scheme, results shows that 25% of femtocell users may receive rates below the target rate. The AIS scheme provides an improvement over the PBI scheme by adjusting femtocell power according to the interference contribution by each femtocell. Thus, AIS achieves better performance and only up to 12:2% of femtocell users receive rates below the target rate. This study concludes with parametric evaluation of system throughput as a function of both macrocell and femtocell user densities. Qualitative results are provided to support the conclusion.M.S.Includes bibliographical referencesby Shweta Sagar
sj-docx-2-pit-10.1177_15269248211064888 - Supplemental material for Prerenal Transplant Education and Evaluation Positively Impacts Outcomes
No full textSupplemental material, sj-docx-2-pit-10.1177_15269248211064888 for Prerenal Transplant Education and Evaluation Positively Impacts Outcomes by Michelle T. Jesse, Erin Clifton and
Dean Y. Kim, Dayna Nicholson, Rujuta Patil, Shweta Bhavsar, Soham Desai, Kendyll Gartrelle, Anne Eshelman, Elizabeth Fleagle, Brian Ahmedani, Noelle E. Carlozzi, Amy Tang, Anita Patel in Progress in Transplantation</p
sj-docx-3-pit-10.1177_15269248211064888 - Supplemental material for Prerenal Transplant Education and Evaluation Positively Impacts Outcomes
No full textSupplemental material, sj-docx-3-pit-10.1177_15269248211064888 for Prerenal Transplant Education and Evaluation Positively Impacts Outcomes by Michelle T. Jesse, Erin Clifton and
Dean Y. Kim, Dayna Nicholson, Rujuta Patil, Shweta Bhavsar, Soham Desai, Kendyll Gartrelle, Anne Eshelman, Elizabeth Fleagle, Brian Ahmedani, Noelle E. Carlozzi, Amy Tang, Anita Patel in Progress in Transplantation</p
sj-docx-1-pit-10.1177_15269248211064888 - Supplemental material for Prerenal Transplant Education and Evaluation Positively Impacts Outcomes
No full textSupplemental material, sj-docx-1-pit-10.1177_15269248211064888 for Prerenal Transplant Education and Evaluation Positively Impacts Outcomes by Michelle T. Jesse, Erin Clifton and
Dean Y. Kim, Dayna Nicholson, Rujuta Patil, Shweta Bhavsar, Soham Desai, Kendyll Gartrelle, Anne Eshelman, Elizabeth Fleagle, Brian Ahmedani, Noelle E. Carlozzi, Amy Tang, Anita Patel in Progress in Transplantation</p
Roll-Call: an energy efficient radio frequency identification system.
No full textIn this thesis, we investigate two of the major challenges in pervasive systems: energy efficiency and co-existence of uncoordinated wireless messages by exploring the design of a Radio Frequency Identification (RFID) system intended to support the simultaneous and real time monitoring of thousands of entities. These entities, which may be individuals or inventory items, each carry a low-power transmit-only tag and are monitored by a collection of networked base-stations reporting to a central database. We have built a customized transmit-only tag with a small form-factor, and have implemented a real-time monitoring application intended to verify the presence of each tag in order to detect potential disappearance of a tag (perhaps due to item theft). Throughout the construction of our system, we have carefully engineered it for extended tag lifetime and reliable monitoring capabilities in the presence of packet collisions, while keeping the tags small and inexpensive.
The major challenge in this architecture (called Roll-Call) is to supply the energy needed for long range continuous tracking for a year or more of reporting once a second while keeping the tags (called PIPs) small and inexpensive. We have used this as a model problem for optimizing cost, size and lifetime across the entire pervasive, persistent system from firmware to protocol.M.S.Includes bibliographical references (p. 46-48)
Effectiveness of Vanilla in Gastro-Esophageal Reflux Disease: A Case Report
No full textGastro-esophageal reflux disease (GERD) is a very common GI condition seen worldwide that occurs when acidic stomach juices, or food and fluids back up from the stomach into the esophagus.(1) Homoeopathic treatment is a holistic approach given to a patient. In this article, a case of GERD is effectively treated using homoeopathic medicine vanilla. The reportorial presentation of Vanilla in GERD has also been showcased as it has poorly reflected in homoeopathic material medica.
Materials - The case was assessed using GERDQ questionnaire. The score has been taken in record before and after the homoeopathic treatment in order to evidently assess the case. Modified Naranjo MONARCH criteria has been used which an as essential tool to show a link between the treatment and impact on patient based on clinical outcome.
Conclusion – While using GERDQ questionnaire, we see an astonishing result and marked relief in complaint of gastro-esophageal reflux disease ultimately scaling down GERDQ score. An effective course of action is shown using Naranjo MONARCH criteria proving potential advancement with homoeopathic treatment. Along with that we came across a lesser known medicine such as VANILLA using Synthesis repertory which can conclusively improvise the scientific literature for further studies in regards to GERD
Machine Learning-Driven Remote Sensing Applications for Agriculture in India—A Systematic Review
No full textIn India, agriculture serves as the backbone of the economy, and is a primary source of employment. Despite the setbacks caused by the COVID-19 pandemic, the agriculture and allied sectors in India exhibited resilience, registered a growth of 3.4% during 2020–2121, even as the overall economic growth declined by 7.2% during the same period. The improvement of the agriculture sector holds paramount importance in sustaining the increasing population and safeguarding food security. Consequently, researchers worldwide have been concentrating on digitally transforming agriculture by leveraging advanced technologies to establish smart, sustainable, and lucrative farming systems. The advancement in remote sensing (RS) and machine learning (ML) has proven beneficial for farmers and policymakers in minimizing crop losses and optimizing resource utilization through valuable crop insights. In this paper, we present a comprehensive review of studies dedicated to the application of RS and ML in addressing agriculture-related challenges in India. We conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and evaluated research articles published from 2015 to 2022. The objective of this study is to shed light on the application of both RS and ML technique across key agricultural domains, encompassing “crop management”, “soil management”, and “water management, ultimately leading to their improvement. This study primarily focuses on assessing the current status of using intelligent geospatial data analytics in Indian agriculture. Majority of the studies were carried out in the crop management category, where the deployment of various RS sensors led yielded substantial improvements in agricultural monitoring. The integration of remote sensing technology and machine learning techniques can enable an intelligent approach to agricultural monitoring, thereby providing valuable recommendations and insights for effective agricultural management
Synthesis and crystalline properties of CdS incorporated polyvinylidene fluoride (PVDF) composite film
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