Sneutrino DM in the NMSSM with inverse seesaw mechanism

In supersymmetric theories like the Next-to-Minimal Supersymmetric Standard Model (NMSSM), the lightest neutralino with bino or singlino as its dominant component is customarily taken as dark matter (DM) candidate. Since light Higgsinos favored by naturalness can strength the couplings of the DM and thus enhance the DM-nucleon scattering rate, the tension between naturalness and DM direct detection results becomes more and more acute with the improved experimental sensitivity. In this work, we extend the NMSSM by inverse seesaw mechanism to generate neutrino mass, and show that in certain parameter space the lightest sneutrino may act as a viable DM candidate, i.e. it can annihilate by multi-channels to get correct relic density and meanwhile satisfy all experimental constraints. The most striking feature of the extension is that the DM-nucleon scattering rate can be naturally below its current experimental bounds regardless of the higgsino mass, and hence it alleviates the tension between naturalness and DM experiments. Other interesting features include that the Higgs phenomenology becomes much richer than that of the original NMSSM due to the relaxed constraints from DM physics and also due to the presence of extra neutrinos, and that the signatures of sparticles at colliders are quite different from those with neutralino as DM candidate.Comment: 33 page

The impacts of infectious disease pandemic on China’s edible vegetable oil futures markets: A long-term perspective

For the extremely important role of China in global edible vegetable oil market and its decisive measures in the epidemic controlling and stable economic recovery during the COVID-19 pandemic, the aim of this article is to inspect the quantitative impacts of infectious disease pandemic on the returns, volatilities and correlations of China’s edible vegetable oil futures markets by using a DCC-MVGARCH-X model incorporating Baidu searching index as the proxy of pandemic severity. Our empirical results show that infectious disease pandemic does have significantly positive impacts on the returns and volatilities of China’s soybean, canola and palm oil futures markets. Second, there are significant volatility spillover effects among the three vegetable oils, suggesting strong contagion effect from one oil market to the others. Third, soybean oil and palm oil show the largest correlation, while the dependence between canola oil and palm oil is the smallest one among the three pairwise correlations. Moreover, no matter to consider epidemic situation in China or in global environment, infectious disease pandemic has significant effects on these correlations

Analysis of secreted proteins of Magnaporthe grisea and the search for protein effectors

Magnaporthe grisea is a notorious pathogenic fungus that causes rice blast disease worldwide. Proteins secreted by the fungus are likely candidates for being effectors that are potentially recognized by determinants of resistance or susceptibility in host plants. However, knowledge of the role of secreted proteins of M. grisea is still limited. In this study, I identified 29 proteins that were secreted into culture filtrates from M. grisea strains expressing candidate proteins. I confirmed secretion of these proteins and tested them for elicitor activity on plants. Among them, I studied two groups: cell wall degrading enzymes (CWDEs) and small cysteine-rich proteins. Cysteine-rich proteins have been shown in other systems to function as elicitors. Initially, I expressed and purified proteins in M. grisea to obtain proteins by a homologous expression system. Although this was effective for a number of proteins, the need for greater amounts of protein led me to express several proteins in the Pichia pastoris system. Several candidate proteins were purified and found to induce symptoms on rice and maize. Hypothetical proteins MG10424.4 and MG09998.4 were both found to have elicitor activity. Lipase MG07016.4 did not induce response of plants and we concluded that the lipase activity of MG07016.4 does not function as an elicitor. I also purified a small cysteine-rich protein, which belongs to the group of cluster 180 proteins in M. grisea, MG10732.4 from P. pastoris. It is able to cause yellowing symptoms and hydrogen peroxide production in plants and it might contain elicitor activity

The Effects of Social Information, Social Norms and Social Identity on Giving

Indiana University - Purdue University - Indianapolis (IUPUI)This philanthropic studies thesis aims to “increase the understanding of philanthropy, improve its practice, and enhance philanthropic participation” (Center on Philanthropy at Indiana University Overview) by studying the effects of social information, social norms and social identity on giving. It connects philanthropic studies research with theoretical developments in motivations for giving in economics, nonprofit management, nonprofit marketing, consumer behavior, and social psychology. It utilizes personal observations as well as quantitative methods including experiments and surveys on multiple samples including donors, undergraduate students and samples of the U.S. population. It generates actionable and efficacious knowledge to improve the practice of philanthropy. It contributes to the formation and growth of the young field called philanthropic studies - in theory, in methodology and in practice. This thesis includes five chapters. Chapter I will explain how the research question, philosophy and methodology are selected. This discussion will be for the entire thesis. Specific research questions, hypotheses, research designs, findings and implications will be explained in the subsequent chapters. Chapter II demonstrates the immediate and long-term effects of social information on donations and its boundary conditions in existing nonprofit donors in two field experiments. Chapter III shows that the psychological mechanism through which social information influences subsequent giving is perceived descriptive social norms in one field survey of donors and one laboratory experiment on undergraduate students. Chapter IV investigates how social identity congruency moderates the effect of social information on donations. It reports three field experiments on donors and samples of the general U.S. population and two laboratory experiments on undergraduate students. It shows that donors give more money to a public radio station if told that a previous donor with a similar identity also made a large contribution. This effect is more likely to occur when donors have high collective identity esteem and when attention is focused on others. Each chapter provides original fundraising techniques developed from these studies. Chapter V concludes with a discussion of the theoretical, methodological and practical contributions of this thesis and suggests directions for future research in philanthropic studies, and philanthropic psychology in particular

Studies on User Intent Analysis and Mining

Predicting the goals of users can be extremely useful in e-commerce, online entertainment, information retrieval, and many other online services and applications. In this thesis, we study the task of user intent understanding, trying to bridge the gap between user expressions to online services and their goals behind it. As far as we know, most of the existing user intent studies are focusing on web search and social media domain. Studies on other areas are not enough. For example, as people more and more rely our daily life on cellphone, our information needs expressing to mobile devices and related services are increasing dramatically. Studies of user intent mining on mobile devices are not much. And the intentions of using mobile devices are different from the ones we use web search engine or social network. So we cannot directly apply the existing user intention to this area. Besides, user's intents are not stable but changing over time. And different interests will impact each other. Modeling such kind of dynamic user interests can help accurately understand and predict user's intent. But there're few existing works in this area. Moreover, user intent could be explicitly or implicitly expressed by users. The implicit intent expression is more close to human's natural language and also have great value to recognize and mine. To make further studies of these challenges, we first try to answer the question of “What is the user intent?” By referring amount of previous studies, we give our definition of user intent as “User intent is a task-specific, predefined or latent concept, topic or knowledge-base that is under an expression from a user who is trying to express his goal of information or service need.“ Then, we focus on the driving scenario when a user using cellphone and study the user intent in this domain. As far as we know, it is the first time of user intent analysis and categorization in this domain. And we also build a dataset of user input and related intent category and attributes by crowdsourcing and carefully handcraft. With the user intent taxonomy and dataset in hand, we conduct a user intent classification and user intent attribute recognition by supervised machine learning models. To classify the user intent for a user intent query, we use a convolutional neural network model to build a multi-class classifier. And then we use a sequential labeling method to recognize the intent attribute in the query. The experiment results show that our proposed method outperforms several baseline models in precision, recall, and F-score. In addition, we study the implicit user intent mining method through web search log data. By using a Restricted Boltzmann Machine, we make use of the correlation of query and click information to learn the latent intent behind a user web search. We propose a user intent prediction model on online discussion forum using Multivariate Hawkes Process. It dynamically models user intentions change and interact over time.The method models both of the internal and external factors of user's online forum response motivations, and also integrated the time decay fact of user's interests. We also present a data visualization method, using an enriched domain ontology to highlight the domain-specific words and entity relations within an article.Ph.D., Information Studies -- Drexel University, 201

The Congestion Evolution of Jingzang Expressway and the Analysis on Participants’ Behavior

Road transportation networks are experiencing ever growing recurrent congestion and non-recurrent in developing China, which is a concurrent event. This paper takes Jingzang Expressway(G6) as an example, describes the saturation flow along the G6 compared with its designed capacity by the actual volume of each segment according to the density and structural characteristics of cars and trucks, and presents the congestion evolution in the past three years. Then provide inharmonious surveillance analysis among regions along this highway and game behavior between administers and carriers based on cost analysis. Finally, we point out that congestion is not only the road itself problems but also a social system problem, which should be transformed in the long term. Now we can apply some Intelligent Transport System to mitigate congestion