Nonnegative moment coordinates on finite element geometries

In this paper, we introduce new generalized barycentric coordinates (coined as {\em moment coordinates}) on nonconvex quadrilaterals and convex hexahedra with planar faces. This work draws on recent advances in constructing interpolants to describe the motion of the Filippov sliding vector field in nonsmooth dynamical systems, in which nonnegative solutions of signed matrices based on (partial) distances are studied. For a finite element with $n$ vertices (nodes) in $\mathbb{R}^2$, the constant and linear reproducing conditions are supplemented with additional linear moment equations to set up a linear system of equations of full rank $n$, whose solution results in the nonnegative shape functions. On a simple (convex or nonconvex) quadrilateral, moment coordinates using signed distances are identical to mean value coordinates. For signed weights that are based on the product of distances to edges that are incident to a vertex and their edge lengths, we recover Wachspress coordinates on a convex quadrilateral. Moment coordinates are also constructed on a convex hexahedra with planar faces. We present proofs in support of the construction and plots of the shape functions that affirm its properties

Mood and the Market: Can Press Reports of Investors’ Mood Predict Stock Prices?

We examined whether press reports on the collective mood of investors can predict changes in stock prices. We collected data on the use of emotion words in newspaper reports on traders’ affect, coded these emotion words according to their location on an affective circumplex in terms of pleasantness and activation level, and created indices of collective mood for each trading day. Then, by using time series analyses, we examined whether these mood indices, depicting investors’ emotion on a given trading day, could predict the next day’s opening price of the stock market. The strongest findings showed that activated pleasant mood predicted increases in NASDAQ prices, while activated unpleasant mood predicted decreases in NASDAQ prices. We conclude that both valence and activation levels of collective mood are important in predicting trend continuation in stock prices

Corporate rumor activity, belief and accuracy

An integrated model relating workplace rumor activity, belief, and accuracy is proposed and tested. Senior VPs of Communications from a sample of Fortune-500 corporations and CEOs of established public relations firms were surveyed regarding rumor episodes that they had experienced. Results confirmed previous research on the role of uncertainty, anxiety, and belief in rumor activity. In addition, a reduced sense of control mediated the effects of uncertainty on anxiety, and anxiety mediated the effects of importance on rumor activity. Evidence was found for the roles of group bias in how strongly a rumor is believed. Rumor activity was also implicated in the formation of more accurate rumors. The significance of these results for rumor theory and for Public Relations practitioners is presented. (C) 2002 Elsevier Science Inc. All rights reserved

Psychological motivations in rumor spread

Psychological research on rumors was spurred by the need to manage information and public morale during the Second World War. Social interchange serves three broad goals: acting effectively, building and maintaining relationships, and managing favorable self-impressions. The goal of acting effectively refers to the need to respond and cope with the environment in a competent and adaptive manner. Accurate knowledge of people's physical and social environment is vital for responding effectively to the environment. The goal of building and maintaining relationships is central to the survival and functioning of humans as social animals. This goal motivates several social behaviors, including compliance with norms and requests in order to please others, impression management and self-presentation tactics such as ingratiation, and even outright deception. The goal of maintaining the positive self-image refers to the need in people to feel positive about themselves

Assessment of different {RANS} turbulence models in mini-channels for the cooling of {MW}-class gyrotron resonators

The adoption of high-speed water flow in mini-channels is a viable option for the cooling system of the resonant cavity in gyrotrons, which are a candidate technology for the external plasma heating in nuclear fusion reactors. The evaluation of the performance of such mini-channel cooling system is a combined fluid dynamics and heat transfer phenomenon which seeks more attention to a highly accurate compu-tational analysis. In this study, a computational-based comparative platform is proposed to evaluate the performance and fidelity of the applied turbulence models which are utilized to study the mini-channel cavity cooling systems in gyrotrons. A full-size mock-up of the gyrotron resonator equipped with mini-channels has been realized and tested in 2019 by THALES to check its total pressure drop applying a wide range of water flow rates, including that available for the gyrotron operation. In parallel, a numerical model of the mock-up has been developed using the commercial software STAR-CCM + , and simulations have been performed using different RANS turbulence closures, and namely: SST k -omega, realizable k-epsilon and Lag EB k-epsilon. The detailed comparison of the computed hydraulic characteristics (i.e., a range of pres-sure drop measurements at different flow rates) to the set of measured values has been addressed using a multivariate metric to assess the performance of different turbulence models in pure hydraulic sim-ulations. This comparative platform reveals a significant clarified difference in fidelity among the RANS models. Based on the performed comparative studies against the entire set of available experimental data, the Lag EB k-epsilon closure provides the best performance among the other turbulence models and can be applied for the future studies of the mini-channel cavity cooling systems of the gyrotron resonators. (C) 2022 Elsevier Ltd. All rights reserved