A dataset of blockade, vandalism, and harassment activities for the cause of climate change mitigation.

Environmental activism is crucial for raising public awareness and support toward addressing the climate crisis. However, using climate change mitigation as the cause for blockade, vandalism, and harassment activities might be counterproductive and risk causing negative repercussions and declining public support. The paper describes a dataset of metadata of 89 blockade, vandalism, and harassment events happening 13 countries in recent years. The dataset comprises three main categories: 1) Events, 2) Activists, and 3) Consequences. For researchers interested in environmental activism, climate change, and sustainability, the dataset is helpful in studying the effectiveness and appropriateness of strategies to raise public awareness and support. For researchers in the field of security studies and green criminology, the dataset offers resources to study features and impacts of blockade, vandalism, and harassment events. The Bayesian Mindsponge Framework (BMF) analytics was employed to validate the dataset. Consequently, the estimated result aligns with the Mindsponge Theory's theoretical reasoning.

The Overlooked Contributors to Climate and Biodiversity Crises: Military Operations and Wars.

The military-industrial complex, military operations, and wars are major contributors to exacerbating both climate change and biodiversity crises. However, their environmental impacts are often shadowed due to national security reasons. The current paper aims to go through the devastating impacts of military operations and wars on climate change and biodiversity loss and challenges that hinder the inclusion of military-related activities into environmental crisis mitigation efforts. The information blind spot induced by concerns about national security reasons jeopardizes the efforts to involve the military-industrial complex and military operations in the global climate and biodiversity agendas. Besides that, many military-related challenges, such as specificity of operational requirements and lifecycles, dependence on fossil fuels, complex supply change, inadequate civilian technologies and innovations, and requirements of structural changes, can hinder emission reduction. Meanwhile, wars and conflicts not only threaten to drain all human and material resources available to tackle environmental problems but also inflict long-lasting destructions, pains, and trauma that can lead to hatred and distrust among nations and parties. With the rising hatred and distrust, global agreement and commitment to address climate change and biodiversity will hardly be achieved. Thus, promoting peace is the humanistic and planetary conscience.

Trust Is for the Strong: How Health Status May Influence Generalized and Personalized Trust.

In the trust-health relationship, how trusting other people in society may promote good health is a topic often examined. However, the other direction of influence-how health may affect trust-has not been well explored. In order to investigate this possible effect, we employed the Bayesian Mindsponge Framework (BMF) analytics to go deeper into the information processing mechanisms underlying the expressions of trust. Conducting a Bayesian analysis on a dataset of 1237 residents from Cali, Colombia, we found that general health status is positively associated with generalized trust, but recent experiences of illnesses/injuries have a negative moderating effect. Personalized trust is largely unchanged across different general health conditions, but the trust level becomes higher with recent experiences of illnesses/injuries. Psychophysiological mechanisms of increasing information filtering intensity toward unfamiliar sources during a vulnerable state of health is a plausible explanation of found patterns in generalized trust. Because established personal relationships are reinforced information channels, personalized trust is not affected as much. Rather, the results suggest that people may rely even more on loved ones when they are in bad health conditions. This exploratory study shows that the trust-health relationship can be examined from a different angle that may provide new insights.

Corn Cobs' Biochar as Green Host of Salt Hydrates for Enhancing the Water Sorption Kinetics in Thermochemical Heat Storage Systems.

Heat storage technologies are essential for increasing the use of solar energy in the household sector. Their development can be achieved by designing new storage materials; one way is to impregnate a porous matrix with hygroscopic salts. In this article, the possibility of using biochar-based composite sorbents to develop promising new heat storage materials for efficient thermal storage is explored. Biochar-based composites with defined salt loadings (5, 10, 15, and 20%) were produced by impregnating MgSO4 into a biochar matrix derived from corn cobs. The new materials demonstrated a high water sorption capacity of 0.24 g/g (20MgCC). After six successive charging-discharging cycles (dehydration/dehydration cycles), only a negligible variation of the heat released and the water uptake was measured, confirming the absence of deactivation of 20MgCC upon cycling. The new 20MgCC composite showed an energy storage density of 635 J/g (Tads = 30 °C and RH = 60%), higher than that of other composites containing a similar amount of hydrate salt. The macroporous nature of this biochar increases the available surface for salt deposition. During the hydration step, the water molecules effectively diffuse through a homogeneous layer of salt, as described by the intra-particle model applied in this work. The new efficient biochar-based composites open a low-carbon path for the production of sustainable thermal energy storage materials and applications.

Examining the Influence of Exploration and Parental Education Attainment on Students' Acceptance of Collectivist Values.

Exploration can help students access a wider range of information and make connections among values within the natural and social world. This study investigated the relationship between students' previous exploration of their surroundings and their acceptance of collectivist values in the context of China. A sample of 343 college students was analyzed based on the Bayesian Mindsponge Framework to explore this relationship. The results revealed a positive association between students' prior exploration of surroundings and their degree of collectivist orientation. Furthermore, parental education attainment was found to negatively moderate this association, albeit with a small effect size. These findings contribute to the understanding of how information acquisition influences students' acceptance of collectivist values and highlight the potential role of the family infosphere in shaping this relationship.

A dataset of Chinese drivers' driving behaviors and socio-cultural factors related to driving.

Given the high fatality rate due to road traffic accidents in China, understanding the factors influencing aggressive driving behaviors among Chinese drivers is essential to alleviate the problem. The paper describes a dataset of 1039 Chinese drivers' driving behaviors and the socio-cultural factors associated with the behaviors. The dataset was collected through an online survey. The dataset comprises five main categories: 1) driving information, 2) aggressive driving behaviors, 3) friend/peer influence, 4) family influence, and 5) socio-demographic information. The dataset is valuable for public health and transportation researchers to explore factors influencing drivers' driving behaviors and public safety in China. The dataset's construct validity was confirmed by the Bayesian Mindsponge Framework (BMF) analytics. Specifically, the analysis shows that safe driving behaviors are affected by information promoting safe driving that is passively and actively absorbed from friends/peers (friends/peers being role models and friends'/peers' support, respectively). The result is consistent with the Mindsponge Theory's information-processing mechanism in human minds.

How AI's Self-Prolongation Influences People's Perceptions of Its Autonomous Mind: The Case of U.S. Residents.

The expanding integration of artificial intelligence (AI) in various aspects of society makes the infosphere around us increasingly complex. Humanity already faces many obstacles trying to have a better understanding of our own minds, but now we have to continue finding ways to make sense of the minds of AI. The issue of AI's capability to have independent thinking is of special attention. When dealing with such an unfamiliar concept, people may rely on existing human properties, such as survival desire, to make assessments. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 266 residents in the United States, we found that the more people believe that an AI agent seeks continued functioning, the more they believe in that AI agent's capability of having a mind of its own. Moreover, we also found that the above association becomes stronger if a person is more familiar with personally interacting with AI. This suggests a directional pattern of value reinforcement in perceptions of AI. As the information processing of AI becomes even more sophisticated in the future, it will be much harder to set clear boundaries about what it means to have an autonomous mind.

Near-Suicide Phenomenon: An Investigation into the Psychology of Patients with Serious Illnesses Withdrawing from Treatment.

Patients with serious illnesses or injuries may decide to quit their medical treatment if they think paying the fees will put their families into destitution. Without treatment, it is likely that fatal outcomes will soon follow. We call this phenomenon "near-suicide". This study attempted to explore this phenomenon by examining how the seriousness of the patient's illness or injury and the subjective evaluation of the patient's and family's financial situation after paying treatment fees affect the final decision on the treatment process. Bayesian Mindsponge Framework (BMF) analytics were employed to analyze a dataset of 1042 Vietnamese patients. We found that the more serious the illnesses or injuries of patients were, the more likely they were to choose to quit treatment if they perceived that paying the treatment fees heavily affected their families' financial status. Particularly, only one in four patients with the most serious health issues who thought that continuing the treatment would push themselves and their families into destitution would decide to continue the treatment. Considering the information-filtering mechanism using subjective cost-benefit judgments, these patients likely chose the financial well-being and future of their family members over their individual suffering and inevitable death. Our study also demonstrates that mindsponge-based reasoning and BMF analytics can be effective in designing and processing health data for studying extreme psychosocial phenomena. Moreover, we suggest that policymakers implement and adjust their policies (e.g., health insurance) following scientific evidence to mitigate patients' likelihood of making "near-suicide" decisions and improve social equality in the healthcare system.

An analytical framework-based pedagogical method for scholarly community coaching: A proof of concept.

Working in academia is challenging, even more so for those with limited resources and opportunities. Researchers around the world do not have equal working conditions. The paper presents the structure, operation method, and conceptual framework of the SM3D Portal's community coaching method, which is built to help Early Career Researchers (ECRs) and researchers in low-resource settings overcome the obstacle of inequality and start their career progress. The community coaching method is envisioned by three science philosophies (cost-effectiveness, transparency spirit, and proactive attitude) and established and operated based on the Serendipity-Mindsponge-3D knowledge (SM3D) management framework (i.e., mindsponge thinking and Bayesian Mindsponge Framework analytics serve as the coaching program's foundational theory and analytical tools). The coaching method also embraces Open Science's values for lowering the cost of doing science and encouraging the trainees to be transparent, which is expected to facilitate the self-correcting mechanism of science through open data, open review, and open dialogue. Throughout the training process, members are central beneficiaries by gaining research knowledge and skills, acquiring publication as the training's product, and shifting their mindsets from "I can't do it" to "I can do it," and at the same time transforming a mentee to be ready for a future mentor's role. The coaching method is thus one of the members, for the member, by the members.•The paper provides the structure, operation method, and conceptual framework of the SM3D Portal's community coaching method, which is built to help Early Career Researchers (ECRs) and researchers in low-resource settings overcome the obstacle of inequality and start their career progress.•The paper presents three major science philosophies envisioning the establishment and operation of scholarly community coaching.•The paper employs the mindsponge theory and BMF analytics to construct a conceptual framework explaining how an environment is created to help shift members' mindsets from "I can't do it" to "I can do it."

Bosses without a heart: socio-demographic and cross-cultural determinants of attitude toward Emotional AI in the workplace.

Biometric technologies are becoming more pervasive in the workplace, augmenting managerial processes such as hiring, monitoring and terminating employees. Until recently, these devices consisted mainly of GPS tools that track location, software that scrutinizes browser activity and keyboard strokes, and heat/motion sensors that monitor workstation presence. Today, however, a new generation of biometric devices has emerged that can sense, read, monitor and evaluate the affective state of a worker. More popularly known by its commercial moniker, Emotional AI, the technology stems from advancements in affective computing. But whereas previous generations of biometric monitoring targeted the exterior physical body of the worker, concurrent with the writings of Foucault and Hardt, we argue that emotion-recognition tools signal a far more invasive disciplinary gaze that exposes and makes vulnerable the inner regions of the worker-self. Our paper explores attitudes towards empathic surveillance by analyzing a survey of 1015 responses of future job-seekers from 48 countries with Bayesian statistics. Our findings reveal affect tools, left unregulated in the workplace, may lead to heightened stress and anxiety among disadvantaged ethnicities, gender and income class. We also discuss a stark cross-cultural discrepancy whereby East Asians, compared to Western subjects, are more likely to profess a trusting attitude toward EAI-enabled automated management. While this emerging technology is driven by neoliberal incentives to optimize the worksite and increase productivity, ultimately, empathic surveillance may create more problems in terms of algorithmic bias, opaque decisionism, and the erosion of employment relations. Thus, this paper nuances and extends emerging literature on emotion-sensing technologies in the workplace, particularly through its highly original cross-cultural study. Supplementary Information: The online version contains supplementary material available at 10.1007/s00146-021-01290-1.

Building eco-surplus culture among urban residents as a novel strategy to improve finance for conservation in protected areas.

The rapidly declining biosphere integrity, representing one of the core planetary boundaries, is alarming. In particular, the global numbers of mammals, birds, fishes, and plants declined by 68% from 1970 to 2016. One of the most widely accepted measures to halt the rate of biodiversity loss is to maintain and expand protected areas that are effectively managed. However, doing so requires substantial finance derived from nature-based tourism, specifically visitors from urban areas. Using the Bayesian Mindsponge Framework (BMF) for conducting analysis on 535 Vietnamese urban residents, the current study examined how their biodiversity loss perceptions can affect their willingness to pay for the entrance fee and conservation in protected areas. We found that perceived environmental degradation, loss of economic growth, loss of nature-based recreation opportunities, and loss of knowledge as consequences of biodiversity loss indirectly affect the willingness to pay through the mediation of the attitude towards conservation. Notably, perceived knowledge loss also has a direct positive influence on the willingness to pay for the entrance fee and conservation. In contrast, perceived loss of health is negatively associated with the attitude towards conservation. Based on these findings, we suggest that building an eco-surplus culture among urban residents by stimulating their subjective cost-benefit judgments towards biodiversity loss can be a promising way to generate more finance from nature-based tourism for conservation in protected areas and ease the domestic government's and international organizations' funding allocation problems. Eco-surplus culture is a set of pro-environmental attitudes, values, beliefs, and behaviors shared by a group of people to reduce negative anthropogenic impacts on the environment and conserve and restore nature.

Escaping from Air Pollution: Exploring the Psychological Mechanism behind the Emergence of Internal Migration Intention among Urban Residents.

Rapid urbanization with poor city planning has resulted in severe air pollution in urban areas of low- and middle-income countries. Given the adverse impacts of air pollution, citizens may develop ideation of averting behaviors, including migration to another region. The current study explores the psychological mechanism and demographic predictors of internal migration intention among urban people in Hanoi, Vietnam-one of the most polluted capital cities in the world. The Bayesian Mindsponge Framework (BMF) analytics was used to construct a model and perform Bayesian analysis on a stratified random sampling dataset of 475 urban people. We found that migration intention was negatively associated with an individual's satisfaction with air quality. The association was moderated by the perceived availability of a nearby alternative (i.e., a nearby province/city with better air quality). The high migration cost due to geographical distance made the moderation effect of the perceived availability of a faraway alternative negligible. These results validate the proposed psychological mechanism behind the emergence of migration intention. Moreover, it was found that male and young people were more likely to migrate. While the brain drain effect did not clearly show, it is likely due to complex underlying interactions of various related factors (e.g., age and gender). The results hint that without air pollution mitigation measures, the dislocation of economic forces might occur and hinder sustainable urban development. Therefore, collaborative actions among levels of government, with the environmental semi-conducting principle at heart, are recommended to reduce air pollution.

Introduction to Bayesian Mindsponge Framework analytics: An innovative method for social and psychological research.

The paper introduces Bayesian Mindsponge Framework (BMF) analytics, a new analytical tool for investigating socio, psychological, and behavioral phenomena. The strengths of this method derive from the combination of the mindsponge mechanism's conceptual formulation power and Bayesian analysis's inferential advantages. The BMF-based research procedure includes six main steps, in which the mindsponge-based conceptualization and model construction is the key step that makes the method unique. Therefore, we elaborate on the fundamental components and functions of the mindsponge mechanism and summarize them into five memorable principles so that other researchers can capitalize directly. An exemplary analysis was performed using a dataset of 3071 Vietnamese entrepreneurs' decisiveness and perceptions of the likelihood of success/continuity to validate the method.•The paper provides five strong points of BMF analytics, originating from the good match between the mindsponge mechanism and Bayesian inference.•The paper also provides a step-by-step procedure for conducting BMF-based research.•The mindsponge mechanism's basic components and functions are elaborated and summarized into five core principles that can be applied directly for research conceptualization and model construction.

Virtual tree, real impact: how simulated worlds associate with the perception of limited resources.

Video games have long been considered an effective educational tool. Environmental education studies have found that games positively affect the feeling of nature connectedness, producing pro-environmental attitudes and behaviors. With growing urbanization, video games also provide chances to interact with nature. During the COVID-19 lockdown, Nintendo's Animal Crossing: New Horizon (ACNH) became a household name, with millions of copies sold worldwide. The article used the Bayesian multilevel model to analyze 640 survey responses of ACNH game players from various online communities. The correlations between the perception of limited resources and virtual planting and exploiting behaviors with the varying effect among ethnicities were explored. The findings suggested positive correlations between the perception and in-game actions among all ethnicities, regardless of whether the actions are planting or exploiting. While further evidence is needed, the findings suggest the restraints of game mechanics. To foster a pro-environmental culture, stakeholders can consider video games a novel technological aid to environmental education.

Good ethics cannot stop me from exploiting: The good and bad of anthropocentric attitudes in a game environment.

Video games have the potential to be a tool for communicating pro-environmental values. The present study examines the correlation between players' environmental attitudes and their interaction with virtual natural resources. This study constructs Bayesian ordinal logistic models to analyze survey data of 640 Animal Crossing: New Horizon (ACNH) players from 29 countries. Results show that the frequency of catching in-game animals (fish and insects) is positively correlated with the level of human centeredness in environmental attitudes. In addition, less anthropocentric players tend to use more sustainable methods to collect woods in ACNH. Such a particular way of interacting with in-game animals and trees based on their species may be attributable to players' environmental attitudes and game designs. This paper discusses how game design can play a role in promoting pro-environmental behaviors and highlights the moral implications of interactions with non-human beings.

The psychological mechanism of internet information processing for post-treatment evaluation.

Digital healthcare has been greatly benefiting the public health system, especially during the COVID-19 pandemic. In digital healthcare, information communication through the Internet is crucial. The current study explores how patients' accessibility and trust in Internet information influence their decisions and ex-post assessment of healthcare providers by employing the Bayesian Mindsponge Framework (BMF) on a dataset of 1,459 Vietnamese patients. We find that patients' accessibility to Internet information positively affects the perceived sufficiency of information for choosing a healthcare provider, and their trust in the information intensifies this effect. Internet information accessibility is negatively associated with post-treatment assessment of healthcare providers, and trust also moderates this effect. Moreover, patients considering professional reputation important while making a decision are more likely to regard their choices as optimal, whereas patients considering services important have contradicting tendencies. Based on these findings, a concern about the risk of eroding trust toward Internet sources about healthcare information is raised. Thus, quality control and public trust-building measures need to be taken to improve the effectiveness of healthcare-related communication through the Internet and facilitate the implementation of digital healthcare.

Brain Drain out of the Blue: Pollution-Induced Migration in Vietnam.

Air pollution is a major problem that severely affects the health of inhabitants in developing countries' urban areas. To deal with the problem, they may consider migration to another place as an option, which can result in the loss of skillful and talented workforces. This situation is called the brain drain phenomenon. The current study employed the Bayesian mindsponge framework (BMF) on the responses of 475 urban inhabitants in Hanoi, Vietnam-one of the most polluted capital cities in the world-to examine the risk of losing talented workforces due to air pollution. Our results show that people with higher educational levels are more likely to have intentions to migrate both domestically and internationally due to air pollution. Regarding the domestic migration intention, younger people and males have a higher probability of migrating than their counterparts. Age and gender also moderate the association between educational level and international migration intention, but their reliability needs further justification. Based on these findings, we suggest that environmental stressors caused by air pollution can influence citizen displacement intention on a large scale through the personal psychological mechanism of cost-benefit judgment. Due to the risk of air pollution on human resources, building an eco-surplus culture is crucial for enhancing environmental and socio-economic resilience.

Telephone-Based Smoking Cessation Counseling Service: Satisfaction and Outcomes in Vietnamese Smokers.

BACKGROUND: As a method to acknowledge the devastating health and economic impacts of tobacco usage worldwide, telephone-based tobacco cessation counseling services have emerged as a potential tool to aid people in their quitting process. This study explores the satisfaction of smokers who use the QUITLINE service and factors associated with their quit attempts and cessation. METHODS: A cross-sectional survey of 110 participants was conducted from June to July 2016 at the Respiratory Center at Bach Mai Hospital, Hanoi, Vietnam. Multivariate logistic regression was used, and it was found that the percentage of people quitting smoking increased after using the service. RESULTS: In total, 65.5% of participants were completely satisfied with the counseling service. The mean score of staff/s capacity/responsiveness, motivation, and service convenience were 4.37 ± 0.78, 4.30 ± 0.81, and 4.27 ± 0.66, respectively. The smoking relapse rate was relatively high at 58.3%, which mainly resulted from cravings and busy work (26.2% and 14.3%, respectively). A higher satisfaction score in "Staffs' capacity and responsiveness" was negatively associated with "ever tried to quit smoking in consecutive 24 h" and actually quit smoking after receiving counseling. Meanwhile, a higher score in the "Motivation" domain was positively associated with both quit attempt indicators as well as actually quitting smoking after receiving counseling (OR = 9.48; 95%CI = 2.27; 39.57). CONCLUSIONS: These results suggest that it is crucial for decision makers to place more focus on countermeasures for smoking relapse and to strengthen the capacity of staff, especially in motivating clients. Interventions should also be maintained throughout a long period of time to prevent relapse.

On the social and conceptual structure of the 50-year research landscape in entrepreneurial finance.

In recent decades, drastic changes in global social-economic situations have led to significant shifts in the financial market for entrepreneurial firms, thus resulting in changes in entrepreneurial finance discipline. The current body of literature, despite its significant growth, has not provided an overview landscape of this research area. Consequently, this study aims to fill this gap by employing the bibliometric analysis of 6902 articles from 1970 to 2019 extracted from the Web of Science database. By doing so, this paper attempts to provide an overview of the discipline's research output, social and conceptual structure, and offer strategies facilitating the scientific development within the field. The findings indicate that entrepreneurial finance is a young and growing field with an exponential increase in the number of publications (approx. 19.75 percent per year) and rising collaboration tendency among authors. The 1991-2000 period is a crucial milestone of the field thanks to the remarkable growth and impact of studies during this period as well as simultaneously occurring historical events. We also notice a sign of Western ideological homogeneity from the collaboration networks and lists of most productive authors, institutions, and countries. Additionally, using thematic mapping, five major research domains are identified: "venture capital", "crowdfunding", "SMEs finance", "social entrepreneurship finance", "IPO and corporate governance". Based on these findings, we raise the concern of lacking diversity in entrepreneurial finance research and propose strategies for authors, journals, and policymakers to diversify the literature.

A scalable, secure, and interoperable platform for deep data-driven health management.

The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we illustrate the use of the PHD framework for large-scale applications in emerging multi-omics disease studies, such as collecting and visualization of diverse data types (wearable, clinical, omics) at a personal level, investigation of insulin resistance, and an infrastructure for the detection of presymptomatic COVID-19.