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The STAR collaboration presents jet substructure measurements related to both the momentum fraction and the opening angle within jets in p+p and Au+Au collisions at √sNN =200GeV. The substructure observables include SoftDrop groomed momentum fraction (zg), groomed jet radius (Rg), and subjet momentum fraction (zSJ) and opening angle (θSJ). The latter observable is introduced for the first time. Fully corrected subjet measurements are presented for p+p collisions and are compared to leading-order Monte Carlo models. The subjet θSJ distributions reflect the jets leading opening angle and are utilized as a proxy for the resolution scale of the medium in Au+Au collisions. We compare data from Au+Au collisions to those from p+p which are embedded in minimum-bias Au+Au events in order to include the effects of detector smearing and the heavy-ion collision underlying event. The subjet observables are shown to be more robust to the background than zg and Rg. We observe no significant modifications of the subjet observables within the two highest-energy, back-to-back jets, resulting in a distribution of opening angles and the splittings that are vacuumlike. We also report measurements of the differential dijet momentum imbalance (AJ) for jets of varying θSJ. We find no qualitative differences in energy loss signatures for varying angular scales in the range 0.1< θSJ<0.3, leading to the possible interpretation that energy loss in this population of high-momentum dijet pairs, is due to soft medium-induced gluon radiation from a single color charge as it traverses the medium.

Participants of New England town meeting must follow protocols to participate in this direct democratic process. Over the past 200 years, the protocols have been enacted and adapted by participants in small towns across the region. Within annual meetings, one can find small breaches that could be interpreted as playful acts. In this paper, we use the comic frame as a theoretical lens to interpret instances of such play within the rhetorical deliberation of one New England town meeting. We analyze two instances where speakers playfully use recognized parts of town meeting to achieve their rhetorical ends. We conclude with a discussion of the way play can help accomplish identification in public discourse.

Research involving the use of augmentative and alternative communication (AAC) applications on mobile technology devices for children with autism spectrum disorder (ASD) needs to expand beyond teaching simple requesting skills. Children’s abilities to create multi-symbol AAC messages is one skill that can be further explored.

Are conservatives more simple-minded and happier than liberals? To revisit this question, 1,518 demographically diverse participants (52% females) were recruited from an online participant-sourcing platform and asked to write a narrative about the upcoming 2020 U.S. Presidential Election as well as complete self and candidates’ ratings of personality. The narratives were analyzed using three well-validated text analysis programs. As expected, extremely enthusiastic Trump supporters used less cognitively complex and more confident language than both their less enthusiastic counterparts and Biden supporters. Trump supporters also used more positive affective language than Biden supporters. More simplistic and categorical modes of thinking as well as positive emotional tone were also associated with positive perceptions of Trump’s, but not Biden’s personality. Dialectical complexity and positive emotional tone accounted for significant unique variance in predicting appraisals of Trump’s trustworthiness/integrity even after controlling for demographic variables, self-ratings of conscientiousness and openness, and political affiliation.

The unique advantage of visible resonance Raman (VRR) spectroscopy using 532 nm excitation wavelength for biological samples is the resonance enhancement of vibrational modes of chemical bonds from cells and tissues. The aim of this study is specifically to reveal the VRR characteristic spectra of different organs in mice, find the molecular alterations in the development of white matter and gray matter of mouse embryos at different ages and study the VRR spectral information of the mouse embryo head using VRR technology.

Almost half of the students who begin college are not retained at the institution in which they began. The purpose of this research was to explore the perceptions of first-year college students to improve their psychological and emotional well-being.  This quantitative study utilized the College Student Mentoring Scale that includes two interrelated constructs which are, Psychological and Emotional Support and The Existence of a Role Model. The research found that multiple factors impact first-year students' perceptions of their psychological and emotional well-being. Additional findings indicated that response levels were highest for The Existence of a Role Model.  It is the intention that this study will add to the somewhat limited research on improving the psychological and emotional well-being of first-year college students in higher education. Also, it will assist in future policies and practices by providing a foundation of the components that influence first-year student success through improving the effectiveness of peer mentoring programs.

In the last decade, a wide range of machine learning approaches were proposed and experimented to model highly nonlinear manufacturing processes. However, improving the performance of such models is challenging due to the complexity and high dimensionality of the manufacturing processes in general. In this paper, we propose bidirectional echo state reservoir networks (Bi-ESNs) trained using support vector machine privileged information method (SVM$$+$$) to model a winding machine process. The proposed model will be applied, tested and compared to reported models in the literature such as classical ESN with linear regression, ESN with a linear SVM readout, genetic programming, feedfoward neural network with backpropagation, radial basis function network, adaptive neural fuzzy inference system and local linear wavelet neural network. The developed results show that Bi-ESNs trained with SVM$$+$$are promising. It was able to provide better generalization performance compared to other models.

Selecting the appropriate, reasonable, and affordable health insurance plan becomes a very important question to solve for both employers and employees. Our research tries to locate the factors determining private sector health insurance plan enrolment decision, and also provides a guideline to both private companies and employees on health insurance plan selection strategies. By using Kaiser Family Foundation Annual Employer Health Benefits Survey (KFF EHBS) data, we apply random decision forest machine learning methodology to study the determinants of employees' health insurance selection, as well as to compare the prediction accuracy among different methodologies. The results indicate: 1) the employees at large firms and the firms with higher eligible rate would tend to choose PPO plan; 2) employees who need family coverage would have different choices comparing employees who seek for single coverage only; 3) employer's contribution and annual total contribution to the health insurance plan are the most important determinants on employees' insurance selection. The conclusion also can provide some suggestions to insurance companies on health insurance package design for different types of employers and employees.

People with autism spectrum disorder (ASD) are represented among those who espouse extremist thought and have committed violent acts associated with their beliefs. Media often highlight a perpetrator's psychiatric diagnosis following acts of mass violence, which in some instances has included ASD. ASD may itself not provide useful information for understanding motivations. Instead, understanding specific traits and neuropsychological and other vulnerabilities may offer an opportunity to make sense of these very complex events.

"Exploring the structural causes and consequences of inequalities based on a person's race, class, and gender, Poverty, Racism & Sexism: The Reality of Oppression in America concentrates on this formidable set of disadvantages, demonstrating how Americans are adversely affected by just one or a combination of three social factors. Grounded in sociological thought, the text highlights unfolding stories about major social inequalities and relentless campaigns for people's rights. Weaving together such concepts as individualism, social reproduction, social class, and intersectionality, the book provides a framework for readers to understand the vast injustices these groups encounter, where and why they originated, and why they continue to endure. Poverty, Racism & Sexism is a compact, versatile volume which will prove an invaluable resource for those studying social inequality, social problems, social stratification, contemporary American society, social change, urban sociology, and poverty and inequality"--

In online social networks (OSN), followers count is a sign of the social influence of an account. Some users expect to increase the followers count by following more accounts. However, in reality more followings do not generate more followers. In this paper, we propose a two player follow-unfollow game model and then introduce a factor for promoting cooperation. Based on the two player follow-unfollow game, we create an evolutionary follow-unfollow game with more players to simulate a miniature social network. We design an algorithm and conduct the simulation. From the simulation, we find that our algorithm for the evolutionary follow-unfollow game is able to converge and produce a stable network. Results obtained with different values of the cooperation promotion factor show that the promotion factor increases the total connections in the network especially through increasing the number of the follow follow connections.