Tensionless Tales of Compactification

We study circle compactifications of tensionless bosonic string theory, both at the classical and the quantum level. The physical state condition for different representations of BMS$_3$, the worldsheet residual gauge symmetry for tensionless strings, admits three inequivalent quantum vacua. We obtain the compactified mass spectrum in each of these vacua using canonical quantization and explicate their properties.Comment: 55 page

Collating and validating indigenous and local knowledge to apply multiple knowledge systems to an environmental challenge: A case-study of pollinators in India

There is an important role for indigenous and local knowledge in a Multiple Evidence Base to make decisions about the use of biodiversity and its management. This is important both to ensure that the knowledge base is complete (comprising both scientific and local knowledge) and to facilitate participation in the decision making process. We present a novel method to gather evidence in which we used a peer-to-peer validation process among farmers that we suggest is analogous to scientific peer review. We used a case-study approach to trial the process focussing on pollinator decline in India. Pollinator decline is a critical challenge for which there is a growing evidence base, however, this is not the case world–wide. In the state of Orissa, India, there are no validated scientific studies that record historical pollinator abundance, therefore local knowledge can contribute substantially and may indeed be the principle component of the available knowledge base. Our aim was to collate and validate local knowledge in preparation for integration with scientific knowledge from other regions, for the purpose of producing a Multiple Evidence Base to develop conservation strategies for pollinators. Farmers reported that vegetable crop yields were declining in many areas of Orissa and that the abundance of important insect crop pollinators has declined sharply across the study area in the last 10–25 years, particularly Apis cerana, Amegilla sp. and Xylocopa sp. Key pollinators for commonly grown crops were identified; both Apris cerana and Xylocopa sp. were ranked highly as pollinators by farmer participants. Crop yield declines were attributed to soil quality, water management, pests, climate change, overuse of chemical inputs and lack of agronomic expertise. Pollinator declines were attributed to the quantity and number of pesticides used. Farmers suggested that fewer pesticides, more natural habitat and the introduction of hives would support pollinator populations. This process of knowledge creation was supported by participants, which led to this paper being co-authored by both scientists and farmers

Examining Macroeconomic Shocks Based on FOMC Projections

Each quarter the Federal Open Market Committee (FOMC) release the projections of its members for the current year values and several future year values of inflation, unemployment, real GDP growth, and the Federal Funds Rate and the overall report that is released is called Summary of Economic Projections (SEP). This thesis examines these projections through the lens of a standard textbook New Keynesian (NK) macro model. Typically, this model is used to generate impulse response functions to trace out the effect of a shock on the path of output, inflation, and interest rates over time. This study reverses this approach to derive the values of the shocks consisted in FOMC projections. We developed the empirical model by using the method of undetermined coefficients to determine the values of the model parameters. Based on this model, we solved for the values of the macroeconomic shocks. We assumed there are three shocks in the economy -the supply shock, the preference shock and the policy shock. The results should be taken as a beginning and not the final word on any issue surrounding the FOMC projections. But this study is informative in demonstrating the evolving nature of the FOMC projections and the implied values of the shocks within a standard model. The results have three perspectives. First, there are the implied value of the three shocks for the current and future years, all based on FOMC projections in December, September, June and March for 2019 to 2022. We compare the path of the FOMC-projected shocks to the path each shock would take from the current year value into the future based on the AR(1) model of the shocks. A second perspective is to examine these episodes for supply shock using alternative values for the AR(1) coefficients. A third perspective is provided by using realized historic values of the variables that the FOMC projects to calculate the implied values of the shocks, and compare these to the value of the shocks from FOMC projections. We aimed to understand Fed’s policy-making better and to understand Fed’s lengthy period of labelling inflation as “transitory” as well as their delay in starting to respond to the rising inflation rates with increase in the policy rate as one would expect from a Taylor rule

Tensionless tales of compactification

Abstract We study circle compactifications of tensionless bosonic string theory, both at the classical and the quantum level. The physical state condition for different representations of BMS3, the worldsheet residual gauge symmetry for tensionless strings, admits three inequivalent quantum vacua. We obtain the compactified mass spectrum in each of these vacua using canonical quantization and explicate their properties

Do follicular dendritic cells regulate lupus-specific B cells?

The factors that allow self-reactive B cells to escape negative selection and become activated remain poorly defined. In this review we describe recently published results in which a B cell receptor-knock-in mouse strain specific for nucleolar self-antigens was bred with mice deficient in complement C4 and discuss the implications for the lupus field. Absence of C4 leads to a breakdown in the elimination of autoreactive B cell clones at the transitional stage. This is characterized by a relative increase in their response to a range of stimuli, entrance into follicles and a greater propensity to form self-reactive germinal centers. In this review, a model is proposed in which, in the absence of complement C4, inappropriate clearance of apoptotic debris promotes chronic activation of myeloid cells and follicular dendritic cells, resulting in secretion of Type I interferon. This allows for the maturation and activation of self-reactive B cell clones leading to increased spontaneous formation of germinal centers and subsequent generation of autoantibodies. (C) 2014 Elsevier Ltd. All rights reserve

Exploring Internet Meme Activity during COVID-19 Lockdown Using Artificial Intelligence Techniques

The sudden outbreak of the novel coronavirus (nCoV-19, COVID-19) and its rampant spread led to a significant number of people being infected worldwide and disrupted several businesses. With most of the countries imposing serious lockdowns due to the increasing number of fatalities, the social lives of millions of people were affected. Although the lockdown led to an increase in network activities, online shopping, and social network usage, it also raised questions On the mental wellness of society. Interestingly, excessive usage of social networks also witnessed humor traveling across the Internet in the form of Internet Memes during the lockdown period. Humor is known to affect our well-being, decision-making, and psychological systems. In this paper, we have analyzed the Internet Meme activity in Social Networks during the COVID-19 Lockdown period. As humor is known to relieve individuals from psychological stress, it is necessary to understand how human beings adopted Internet Memes for coping up with the lockdown stress and stress-relieving mechanism during the lockdown period. In this paper, we have considered thirty popular memes and the increase in the number of their captions within the period (September 2017 to August 2020). An increase in Internet Meme activity since the lockdown period (March 2020) depicts an increase in online social behavior. We analyze the internet meme activity in social networks during the COVID-19 lockdown period using random forest, multi-layer perceptron, and instance-based learning algorithms followed by data visualization using line graph and Heat Map (8 & 15 clustered). We also compared the performance of the models using evaluation parameters like mean absolute error, root-mean-squared error & Kappa statistics and observed that random forest and instance-based learning algorithms perform better than multi-layer perceptrons. The result indicates that random forest and instance-based learning classifiers are having near perfect classification tendencies whereas multi-layer perceptrons showed around 97% classification accuracy