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Effect of temperature on aging and time-temperature superposition in nonergodic Laponite suspensions
Varun Awasthi,Yogesh M Joshi
Physics , 2009, DOI: 10.1039/b915105b
Abstract: We have studied the effect of temperature on aging dynamics of laponite suspensions by carrying out the rheological oscillatory and creep experiments. We observed that at higher temperatures the mechanism responsible for aging became faster thereby shifting the evolution of elastic modulus to lower ages. Significantly, in the creep experiments, all the aging time and the temperature dependent strain data superposed to form a master curve. Possibility of such superposition suggests that the rheological behavior depends on the temperature and the aging time only through the relaxation processes and both the variables do not affect the distribution but only the average value of relaxation times. In addition, this procedure allows us to predict long time rheological behavior by carrying out short time tests at high temperatures and small ages.
Comprehensive Review on Air Pollution Control Measures for Non-Attainment Cities of Uttar Pradesh, India  [PDF]
Khyati Sharma, Anchal Garg, Varun Joshi
Journal of Environmental Protection (JEP) , 2023, DOI: 10.4236/jep.2023.143010
Abstract: Introduction: The Indian state of Uttar Pradesh (UP) for the past many years has been reported to have many cities with highly polluted air quality. The state has been taking meticulous steps in combating air pollution in the form of action plans, introduced especially in its 17 non-attainment cities (NAC). To assess the progress and development of these action plans in UP, the present study has done an in-depth analysis and review of the state’s action plans and city micro action plans. Materials and Methods: In this research study, the analysis of the latest action plan reports, micro action plan reports as well as the recommendations for combating air pollution-related issues in the 17 NAC of the UP state has been well documented. Uttar Pradesh Pollution Control Board (UPPCB) has prepared these reports to highlight the progress of the plans in response to the growing air pollution in these cities. The information present in the reports has been used to further study sector-specific, category-specific action plans, institutional responsibility, and the present status of the action plans. Results: On average, the highest weightage in action plans was given to sector-specific categories such as Road dust and construction activities (24%). It was also observed that Urban local bodies (~50%) were majorly responsible to implement the action points and 56% of the action points were jointly implemented by multiple agencies.
Understanding Retinal Changes after Stroke  [PDF]
Varun Kumar
Open Journal of Ophthalmology (OJOph) , 2017, DOI: 10.4236/ojoph.2017.74037
Abstract:
Stroke is the fifth leading cause of death and disability in the United States. According to World Heart Federation, every year, 15 million people suffer from stroke worldwide out of which nearly 6 million people die and another 5 million people are disabled. Out of many organs affected after stroke, one of them is eye. Majority of the stroke victims suffer vision loss due to stroke-induced retinal damage. However, stroke-induced retinal damage and microvascular changes have not been given paramount importance in understanding stroke pathophysiology and predicting its occurrence. Retinal imaging can be a very powerful tool to understand and predict stroke. This review will highlight the importance of retinal changes in predicting occurrence of stroke, major retinal changes, the relationship between retinal diseases and stroke and moreover, molecular mechanisms delineating the stroke induced-retinal changes and therapeutics associated with it.
Efficiency of Currency Derivatives in Price Discovery Process: Evidences from India  [PDF]
Prashant Sharma, Varun Chotia
Theoretical Economics Letters (TEL) , 2019, DOI: 10.4236/tel.2019.95106
Abstract: The present study investigates the efficiency of currency derivatives market by assessing its contribution towards price discovery process using spot and future prices of four currencies (USD/INR, EURO/INR, GBP/INR and JPY/INR) traded on the National Stock Exchange (NSE), India. As per the investigation, it can be concluded that there is a long run equilibrium relationship between spot rates and future rates, with unidirectional causality running from future rates to spot rates for all currencies under consideration. As the futures markets contribute more to the price discovery, this implies that more investors are attracted to it. This in turn leads to more rational price discovery.
Theory of Quantum Relativity  [PDF]
Sudhanva Joshi
Journal of Quantum Information Science (JQIS) , 2016, DOI: 10.4236/jqis.2016.64016
Abstract: In this paper, I have studied the properties of atomic and molecular world along with general and special theories of relativity. This is an attempt to merge Gravity into the standard model in order to complete the Grand Unification Theory. The merger of gravity into the other forces i.e. electromagnetic, strong and weak nuclear forces should be well defined and in the boundaries of Gauge Group theory. The Lorentz transformations used in the theory too are invariant under SU(2) type of space. The relative force exerted on two separate quantum systems is also discussed along with Dark matter and Dark energy at a quantum level. I have also tried to solve the Banach-Tarski theorem by applications of Heisenbergs Uncertainty principle in the later part of the paper. Detailed particle Chirality in standard model is redefined to fit in the criterion of operators used in the same process. Possible existence of a new quasi particle is also included in the paper along with its properties.
Does Introduction of Stock Options Impact Stock Volatility? Empirical Evidence from Underlying Stocks in Indian Market  [PDF]
Himanshu Joshi
Theoretical Economics Letters (TEL) , 2018, DOI: 10.4236/tel.2018.810118
Abstract: Present study investigates the impact of single stock option trading on the volatility of the underlying stocks in Indian market using data of companies listed on National Stock Exchange (NSE) of India. The daily stock price data for a period of 1 year prior and post option introduction is extracted for 166 companies which offer options trading on the platform of NSE. Pre and post volatility of the underlying stocks is measured using standard deviation and GARCH (1, 1) model. Then the sample has been split into three groups based on the market capitalization of the stocks, i.e., large cap, mid cap, and small cap. Pre and post option listing volatility was tested for three groups separately. The highest average volatility is recorded for large cap stocks, followed by mid cap, and lowest for small cap stocks using GARCH (1, 1) model. This contrasts with the results of daily variance, as variance is highest for the small cap, followed by large cap and lowest for mid cap firms. Results show that for the large cap firms, volatility increases after the option listing, using both the measure of measures of volatility; and statistically insignificant decline has been recorded in the daily variance and average long-run volatility measure (VL) using GARCH (1, 1) model for mid cap, and small cap firms.
Option Trading, Information Asymmetry and Firm Innovativeness: Evidence from Stock Options Trading Firms from India  [PDF]
Himanshu Joshi
Theoretical Economics Letters (TEL) , 2018, DOI: 10.4236/tel.2018.811142
Abstract: Present study examines the effect of option listing and subsequent trading on the innovation in the context of publicly listed Indian firms. Innovation is defined in terms of input and output as R & D expense to sales, and number of patents filed by firm, respectively. Multiple regression analysis is conducted to identify drivers of innovations. Measures of innovation are used as dependent variables, while dummy for option trading is taken as independent variable along with other firm level control variables. The study also examines the determinants of the option listing on individual stocks using binary-logistic regression. Firm age, financial leverage, dividend payout, and profitability affect internal R & D allocations for the sample firms. As far as firm’s research output is concerned, firm leverage, institutional holding, option trading, and ESOP are the major determinants. Firm leverage adversely affects R & D input and R & D output alike. Dividend paying, large firms having higher institutional holdings are likely to attract stock option listing, while firms with high firm specific return variations are likely to have very low probability of option listing.
Lessons from Observation of Supplementary Immunization Activity in India
Varun Malhotra
Online Journal of Health & Allied Sciences , 2012,
Abstract: Successful conduction of supplementary immunization activity is vital both for prevention of transmission of Wild Polio Viruses, as well as outbreaks due to importation of infection to India. The present study attempts to identify reasons that restrict parents to bring their children to polio booths on ‘Polio Sunday’, and highlights the need for concerted house-to-house ‘search and vaccinate’ activities to ensure near 100% coverage of target children to achieve the aim of Polio Free India
DENDRIMER: POLYMER OF 21ST CENTURY
VARUN TRIVEDI
International Journal of Pharmaceutical Research and Bio-Science , 2012,
Abstract: The review aims majorly on four areas namely: Architecturing, Synthesis, Properties & Applications of the dendrimer. The unique architectural design of dendrimers, high degree of branching, multivalency, globular architecture and well-defined molecular weight, clearly distinguishes these structures as unique and optimum nanocarriers in medical applications such as drug delivery, gene transfection, tumor therapy, diagnostics, etc. Synthetic approaches lead to a dendritic architecture with properties amenable to modi cations of shape, size, polarity, surface properties and internal structure. Nanoparticle drug-delivery systems are the popular ones as are able to increase the selectivity and stability of therapeutic agents. However reticuloendothelial system (RES) uptake, drug leakage, immunogenicity, hemolytic toxicity, cytotoxicity, hydrophobicity restrict the use of these nanostructures. These shortcomings are overcome by surface engineering the dendrimer such as Polyester dendrimer, Citric acid dendrimer, Arginine dendrimer, Glycodendrimers, PEGylated dendrimers, etc. The bioactive agents can be easily encapsulated into the interior of the dendrimers or chemically attached i.e. conjugated or physically adsorbed onto the dendrimer surface, serving the desired properties of the carrier to the specific needs of the active material and its therapeutic applications. In addition to supplying a multivalent backbone for drug attachment, dendrimers also provide access to various new polymer architectures that are potentially relevant to drug delivery applications.
Explaining Human Behavior in Dynamic Tasks through Reinforcement Learning
Varun Dutt
Journal of Advances in Information Technology , 2011, DOI: 10.4304/jait.2.3.177-188
Abstract: Modeling human behavior in dynamic tasks can be challenging. As human beings possess a common set of cognitive processes, there should be certain robust cognitive mechanisms that capture human behavior in these dynamic tasks. This paper argues for a learning model of human behavior that uses a reinforcement learning (RL) mechanism that has been widely used in the fields of cognitive modeling, and judgement and decision making. The RL model has a generic decision-making structure that is well suited to explaining human behavior in dynamic tasks. The RL model is used to model human behavior in a popular dynamic control task called Dynamic Stock and Flows (DSF) that was used in a recent Model Comparison Challenge (MCC). The RL model’s performance is compared to a winner model that won the MCC, that also uses the RL mechanism, and that is the best known model to explain human behavior in the DSF task. Results of comparison reveal that the RL model generalizes to explain human behavior better than the winner model. Furthermore, the RL model is able to generalize to human data of best and worst performers better than the winner model. Implications of this research highlight the potential of using experienced-based mechanisms like reinforcement learning to explain human behavior in dynamic tasks.
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