COVID-19: Exercise Behavior of College Students Communicating at Home

Background: During the outbreak and spread of COVID-19, the extension of college students' time spent studying at home changed their physical exercise behavior and affected the physical activity behavior of the whole family.Methods: A questionnaire survey was conducted among 1,582 college students using a specific measurement scale. A total of 305 urban college students were selected as research subjects. SPSS24.0 and AMOS24.0 were used for statistical analysis.Results: During the COVID-19 transmission period, the pair correlation coefficients of exercise behavior, exercise attitude, and family exercise conditions were 0.63, 0.36, and 0.25, respectively. The influence on family exercise behavior is as follows: college students' exercise behavior (0.403), family exercise support (0.329), and college students' exercise attitude (0.257). The most significant influence on family exercise support is college students' exercise attitude (0.509). The regression model of family exercise behavior standardization had 0.74 and 0.44 explanatory power to family exercise behavior and family exercise support, respectively.Conclusions: The individual-level interventions were assessed by considering the interaction between individual exercise behavior and individual factors. In addition, the exercise environment exhibited a regulatory role and should be controlled. At the interpersonal level, the communication of the college students regarding exercise behavior was bidirectional. Exercise support for family members is an important factor affecting two-way communication and has a significant effect. With the development of the exercise behavior theory, the interaction between individuals is the origin of the spread of group behavior. The data suggest that instead of one-way influence two-way influence mechanisms should be proposed to assess the transformation from the individual to group exercise behavior.

Consumers’ Purchase Behavior Preference in E-Commerce Platform Based on Data Mining Algorithm

E-commerce platform can recommend products to users by analyzing consumers’ purchase behavior preference. In the clustering process, the existing methods of purchasing behavior preference analysis are easy to fall into the local optimal problem, which makes the results of preference analysis inaccurate. Therefore, this paper proposes a method of consumer purchasing behavior preference analysis on e-commerce platform based on data mining algorithm. Create e-commerce platform user portrait template with consumer data records, select attribute variables and set value range. This paper uses data mining algorithm to extract the purchase behavior characteristics of user portrait template, takes the characteristics as the clustering analysis object, designs the clustering algorithm of consumer purchase behavior, and grasps the common points of group behavior. On this basis, the model of consumer purchase behavior preference is established to predict and evaluate the behavior preference. The experimental results show that the accuracy rate of this method is 91.74%, the recall rate is 88.67%, and the F1 value is 90.17%, which are higher than the existing methods, and can provide consumers with more satisfactory product information push.

Assessing the Employee Well-Being and Performance in Small-Sized Construction Organization

Performance in paid work has for many years been studied as an important form of individual and group behavior, with researchers and practitioners often aiming for its enhancement through job design, staff selection and development, or shaping managerial style and organizational culture. In parallel with this interest in performance, psychologists in employment settings have also worked to understand the sources and consequences of well-being, motivation and performance. These three variables are examined together in the assessing the employee well-being in small-sized construction organization in Ekiti State. Employee well-being is considered as an important tool for enhancing worker’s performance and construction sector is not an exception. It has been empirically established that well-being has positive impact on construction worker’s performance. Moreover, empirical studies have shown that performance in the sector has been decreasing globally. This study therefore aims at understand the demanding working environment of the construction industry and the factors which lead to employees being troubled. The researcher was of the opinion that an improved well-being of employees can significantly improve the organization productivity. Quantitative research design was employed with same questionnaire administered on the population covered. Random sampling techniques were used to select small-sized construction organization sampled from a selected population in Ekiti State, Nigeria. Purposive sampling was used to administer questionnaires to various employees. 75questionnaires were administered to employee collectively and 70 was filled and returned which constitute 93.3% success rate. Questionnaire was designed in Likert scale of 1-5. Analysis was done by statistical packages for social sciences version 17. Descriptive statistics which include mean percentile and tables were used to present the data. One Way Analysis of Variance was used to determine whether there is relationship between well-being and organization performance. Data analysis and results on the factors affecting small-sized construction organization employee well-being indicates that there is a statistically significant linear relationship between well-being and performance. The result also revealed that there is a positive and significant relationship between well-being and employee’s performance which reinforces the reinforcement and expectancy theory of remuneration especially the concept of Thorndike’s Law of Effect meaning a response followed by a reward is more likely to recur in the future. The study concluded that well-being has impact on employees and organization performance and recommend that the employers of labor both private and government must not take the well-being of their employees for granted because it will result in low productivity.

Sci-Fi Fandoms in the Digital Age

This chapter discusses the evolution of the Doctor Who, Star Wars, and Star Trek fandoms from their beginnings to their current releases. These brief histories highlight how fans communicated with each other before social media and how those communications changed with the advent of the internet and social media. The dynamics of online groups, individual behavior in online groups, and the life cycle of a group are all discussed before moving onto trolling and the spectrum of online incivility. Overall, most of the trolling that occurs in sci-fi fandoms comes from devotion to the franchise rather than from the desire to be divisive or negative. However, some online incivility is solely guided by sexism, racism, and the desire to sow social discord. Two examples of sexist and racist fan behavior from Star Wars: The Last Jedi illustrates the different motivations of fandom trolls as well as ways to respond. Although every fandom is different, group behavior is predictable thus insights from these iconic sci-fi fandoms can be applied to many different fandoms.

GIS and Geo-Positioning Developments in Coping With the Pandemic

This chapter deals with some technical aspects of the spatial strategy for overcoming the huge challenges posed by the pandemic. The focus of this chapter is to highlight the use of GIS tools and positioning technologies in diverse contexts to manage the threat of COVID-19. For this task, three stages of analysis are proposed. In a first preventive stage, some governments applied socioeconomic criteria drawn from existent statistical information to spatially identify the areas with a clear predisposition toward the accelerated spread of the contagion. In a second stage, when the pandemic fully reached a rapid pace of expansion and lockdown measures became necessary, the technologies helped to monitor the most affected areas and to establish a dashboard deployment for visualizing the severity of the catastrophe. In the third stage, after the establishment of control and mobility protocols, different governments resorted to mobile phone positioning as a resource for monitoring quarantine compliance and recognizing if social group behavior entailed any evident risk or spread.

Fertility Outcomes, Heritability and Genomic Associations of In-Group Preference and In-Group Marriage

Using data from the Midlife Development in the USA (MIDUS) sample (3070 men and 3182 women) and the Wisconsin Longitudinal Study (WLS; 2240 men and 2346 women), we aimed to investigate whether religious, ethnic and racial in-group preferences as well as religious homogamy are associated with reproductive outcome in terms of number of children. Using data from the MIDUS twin sample, we further estimated the inherited genetic component of in-group attitudes. Additionally, we analyzed the association of ∼50 polygenic scores (PGSs) recently published for the WLS study and in-group attitudes as an indicator of potential pleiotropic effects. We found in both samples that, with one exception, religious though not other in-group attitudes are associated with a higher reproductive outcome. Also, religious homogamy is associated with higher average number of children. The inherited component of all in-group attitudes ranges from ∼21% to 45% (MIDUS twin sample). PGSs associated with religious behavior are significantly positively associated with religious in-group attitudes as well as family attitudes. Further associations are found with PGS on life satisfaction (work) and, negatively, with PGS for any sort of addiction (smoking, alcohol and cannabis use), indicating pleiotropy. We conclude that the positive association between religious in-group attitudes as well as religious homogamy and reproductive outcome may indicate selective forces on religious in-group behavior. As all investigated in-group attitudes, however, have a substantial inherited component, we further speculate that potential previous reproductive benefits of racial and ethnic in-group preferences, if they ever existed, might have been substituted by religious in-group preferences.

Dynamic Phenotypic Switching and Group Behavior Help Non-Small Cell Lung Cancer Cells Evade Chemotherapy

Drug resistance, a major challenge in cancer therapy, is typically attributed to mutations and genetic heterogeneity. Emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance. However, the underlying mechanisms remain poorly understood. Here, we present a new mathematical approach with game theoretical underpinnings that we developed to model real-time growth data of non-small cell lung cancer (NSCLC) cells and discern patterns in response to treatment with cisplatin. We show that the cisplatin-sensitive and cisplatin-tolerant NSCLC cells, when co-cultured in the absence or presence of the drug, display dynamic group behavior strategies. Tolerant cells exhibit a ‘persister-like’ behavior and are attenuated by sensitive cells; they also appear to ‘educate’ sensitive cells to evade chemotherapy. Further, tolerant cells can switch phenotypes to become sensitive, especially at low cisplatin concentrations. Finally, switching treatment from continuous to an intermittent regimen can attenuate the emergence of tolerant cells, suggesting that intermittent chemotherapy may improve outcomes in lung cancer.

A METHOD FOR CHOOSING A STRATEGY FOR THE BEHAVIOR OF A CELLULAR AUTOMATON WHEN SOLVING THE PROBLEM OF FINDING TARGETS BY A GROUP OF MOVING OBJECTS

Currently, a large number of different mathematical models and methods aimed at solving problems of multidimensional optimization and modeling of complex behavioral systems have been developed. One of the areas of search for solutions is the search for solutions in conditions of incomplete information and the need to take into account changing external factors. Often such problems are solved by the method of complete search. In some conditions, the method of complete search can be significantly improved through the implementation and use of behavioral models of natural formations. Examples of such formations can be group behavior of insects, birds, fish, various flocks, etc. The idea of copying group activity of a shoal of fishes at the decision of problems of joint activity on extraction of food is used in work. The reasoning based on the simulation of the behavior of such a natural object allowed to justify the choice as a mathematical model - cellular automata. The paper examines the key features of such a model. Modeling of his work is carried out, strategies of behavior of group of mobile objects at search of the purposes are developed, key characteristics are investigated and the method of adaptive choice of strategy and change of rules of behavior taking into account features of the solved problem is developed. The search strategy is implemented in the work, which takes into account the need to solve the optimization problem on two parameters. The obtained results testify to the high descriptive possibility of such an approach, the possibility of finding the optimal strategy for the behavior of the cellular automaton and the formalization of the process of selecting the parameters of its operation. A further improvement of this approach can be the implementation of simulation to study the properties of the developed model, the formation of the optimal set of rules and parameters of the machine for the whole set of tasks.

Negative partisanship is not more prevalent than positive partisanship

The dominant narrative among scholars and political pundits characterizes American partisanship as overwhelmingly negative --- portraying citizens as more repelled by the opposing party than attached to their own party. To assess the valence of partisan identity, we use novel measures, several new and existing nationally representative surveys, and behavioral outcomes obtained from two experiments. Our findings consistently depart from the negative partisanship narrative. For the majority of Americans, partisanship is either equally positive and negative or more positive than negative. Only partisan leaners stand out as negative partisans. We pair these observational findings with experimental data that differentiate between positive group behavior and negative group behavior in the partisan context. We find that the behavioral manifestations of party identity similarly include both positive and negative biases in balance, reinforcing our conclusion that descriptions of partisanship as primarily negative are exaggerated.