Products made from animal fur and skin have been a major part of human civilization. However, in modern society, the unsustainable consumption of these products – often considered luxury goods – has many negative environmental impacts. This study explores how people’s perceptions of biodiversity affect their attitudes and behaviors toward consumption. To investigate the information process deeper, we add the moderation of beliefs about biodiversity loss. Following the Bayesian Mindsponge Framework (BMF) analytics, we use mindsponge-based reasoning for constructing conceptual models (...) and employ Bayesian analysis aided by Markov Chain Monte Carlo (MCMC) algorithms on a dataset of 535 Vietnamese urban residents. The results show that people’s preference for using products made from animal skin/fur is negatively associated with perceived consequences of biodiversity loss when they believe biodiversity loss is real and a major problem. In contrast, if urban residents believe biodiversity loss is unreal or not a significant issue, the association between perceived consequences of biodiversity loss and personal preference happens in the opposite direction. The same effects of biodiversity loss perception on people’s possession of skin/fur products was not found, indicating a more complex information process on behaviors compared to attitudes. Nevertheless, in the scenario that people believe biodiversity loss is not a significant issue, the higher the perceived consequences of biodiversity loss are, the greater number of animal-based products they likely own. Our results suggest that policymakers should not neglect the factor of personal belief besides knowledge and awareness in environmental campaigns. (shrink)

Case law retrieval is the task of locating truly relevant legal cases given an input query case. Unlike information retrieval for general texts, this task is more complex with two phases (legal case retrieval and legal case entailment) and much harder due to a number of reasons. First, both the query and candidate cases are long documents consisting of several paragraphs. This makes it difficult to model with representation learning that usually has restriction on input length. Second, the concept of (...) relevancy in this domain is defined based on the legal relation that goes beyond the lexical or topical relevance. This is a real challenge because normal text matching will not work. Third, building a large and accurate legal case dataset requires a lot of effort and expertise. This is obviously an obstacle to creating enough data for training deep retrieval models. In this paper, we propose a novel approach called supporting model that can deal with both phases. The underlying idea is the case–case supporting relation and the paragraph–paragraph as well as the decision-paragraph matching strategy. In addition, we propose a method to automatically create a large weak-labeling dataset to overcome the lack of data. The experiments showed that our solution has achieved the state-of-the-art results for both case retrieval and case entailment phases. (shrink)

This paper proposes several recurrent neural network-based models for recognizing requisite and effectuation parts in Legal Texts. Firstly, we propose a modification of BiLSTM-CRF model that allows the use of external features to improve the performance of deep learning models in case large annotated corpora are not available. However, this model can only recognize RE parts which are not overlapped. Secondly, we propose two approaches for recognizing overlapping RE parts including the cascading approach which uses the sequence of BiLSTM-CRF models (...) and the unified model approach with the multilayer BiLSTM-CRF model and the multilayer BiLSTM-MLP-CRF model. Experimental results on two Japan law RRE datasets demonstrated advantages of our proposed models. For the Japanese National Pension Law dataset, our approaches obtained an \ score of 93.27% and exhibited a significant improvement compared to previous approaches. For the Japan Civil Code RRE dataset which is written in English, our approaches produced an \ score of 78.24% in recognizing RE parts that exhibited a significant improvement over strong baselines. In addition, using external features and in-domain pre-trained word embeddings also improved the performance of RRE systems. (shrink)

The book examines the psycho-religious mechanism behind the violent extremism of suicide attacks in the post-9/11 world. It employs the mindsponge concept, an original dataset, and original research results obtained from the authors' statistical investigations using the Hamiltonian Markov chain Monte Carlo technique. It provides insights and implications for policymakers and strategists in their efforts to engage in peace talks and reduce violent conflicts worldwide.

Space tourism is an emerging field where few people have direct experience. However, considering the potential in the near future, it is beneficial to better understand how related information influences people’s attitudes about this new form of tourism. Employing information-processing-based Bayesian Mindsponge Framework (BMF) analytics on a dataset of 361 respondents consuming content related to space tourism on Chinese social media, we found that induced happiness and impression are positively associated with willingness to try space tourism. Information authenticity positively moderates (...) these two associations. Our findings emphasize three aspects of information during the processes of reception and filtering: meaning, intensity, and trust. Since promotional materials for space tourism rely heavily on mental simulations rather than objective feedback, creative uses of digital technology are advantageous. However, precautions must be taken to prevent exploitation, such as false advertising, exaggeration, and emotional manipulation. (shrink)

Extant literature suggests a positive correlation between social trust (also called generalized trust) and life satisfaction. However, the psychological pathways underlying this relationship can be complex. Using the Bayesian Mindsponge Framework (BMF), we examined the influence of social trust in a high-violence environment. Employing Bayesian analysis on a sample of 1237 adults in Cali, Colombia, we found that in a linear relationship, generalized trust is positively associated with life satisfaction. However, in a model including the interactions between trust and education (...) level as well as between trust and socioeconomic status, generalized trust is found to be negatively associated with life satisfaction. In this non-linear relationship, both education level and socioeconomic status have moderating effects against the negative association between generalized trust and life satisfaction. In other words, less educated people living in worse socioeconomic conditions are more likely to have lower life satisfaction when they have higher levels of social trust. In contrast, highly educated people living in better socioeconomic conditions are more likely to have higher life satisfaction when they have higher levels of social trust. Due to the facilitating function of trust in information processing, lowering the rigor of the filtering system in a high-violence social environment will likely put an individual at risk. Based on our findings, we suggest that policymakers should consider the impacts of social contexts when advocating for increasing social trust. We also recommend that researchers carefully examine the psychological mechanism underlying an observed association before making suggestions for policymaking. (shrink)

Cheating is widely considered a condemnable behavior in society and a big problem in the educational system. In this study, we employ the information-processing-based Bayesian Mindsponge Framework to explore deeper the subjective cost-benefit evaluation involving the perceived value of cheating. Conducting Bayesian analysis on 493 university students from Germany, Vietnam, China, Taiwan, and Japan, we found that students who have more positive attitudes toward cheating are more likely to cheat. However, a higher capability of cognitive reflection acts as a moderator (...) that negates the above effect. Re-evaluation of prior thoughts allows for more accurate assessments of the associated risks and possible costs, which help reduce the probability of carrying out cheating behavior. As rapid technological advancement may introduce new and efficient cheating methods, a better understanding of the psychology of cheating in students can help schools prepare better countermeasures. (shrink)

Extant literature suggests a positive correlation between social trust (also called generalized trust) and life satisfaction. However, the psychological pathways underlying this relationship can be complex. Using the Bayesian Mindsponge Framework (BMF), we examined the influence of social trust in a high-violence environment. Employing Bayesian analysis on a sample of 1237 adults in Cali, Colombia, we found that in a linear relationship, generalized trust is positively associated with life satisfaction. However, in a model including the interactions between trust and education (...) level as well as between trust and socioeconomic status, generalized trust is found to be negatively associated with life satisfaction. In this non-linear relationship, both education level and socioeconomic status have moderating effects against the negative association between generalized trust and life satisfaction. In other words, less educated people living in worse socioeconomic conditions are more likely to have lower life satisfaction when they have higher levels of social trust. In contrast, highly educated people living in better socioeconomic conditions are more likely to have higher life satisfaction when they have higher levels of social trust. Due to the facilitating function of trust in information processing, lowering the rigor of the filtering system in a high-violence social environment will likely put an individual at risk. Based on our findings, we suggest that policymakers should consider the impacts of social contexts when advocating for increasing social trust. We also recommend that researchers carefully examine the psychological mechanism underlying an observed association before making suggestions for policymaking. (shrink)

Food prices are a daily concern in many households’ decision-making, especially when people want to have healthier diets. Employing Bayesian Mindsponge Framework (BMF) analytics on a dataset of 710 Indonesian citizens, we found that people from wealthier households are less likely to have concerns about food prices. However, the degree of health considerations in food consumption was found to moderate against the above association. In other words, people of higher income-based social classes may worry more about food prices if they (...) care more about the health impacts of their food choices. These findings provide more insights for policymakers on the psychological aspects of promoting the balance between finance and health in food consumption. (shrink)

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 Bayesian Mindsponge Framework (BMF) analytics to go deeper into the information processing mechanisms underlying the expressions of trust. Conducting 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. (shrink)

This document represents some preliminary and unpublished content of a chapter in the edited book titled A New Theory of Serendipity: Nature, Emergence and Mechanism, which will soon be published and distributed by De Gruyter Poland (Sciendo Imprint; part of Walter de Gruyter GmbH, Berlin, Germany). A proper referencing should be like: Quan-Hoang Vuong, Tam-Tri Le, Quy Khuc, Minh-Hoang Nguyen. (2022). A new theory of serendipity. In: QH Vuong. (Ed.) A New Theory of Serendipity: Nature, Emergence and Mechanism (pp. (...) 91-108). Berlin, Germany: De Gruyter. (shrink)

This article addresses the problem of automatically extracting legal indices which express the important contents of legal documents. Legal indices are not limited to single-word keywords and compound-word keywords, they are also clause keywords. We approach index extraction using structural information of Japanese sentences, i.e. chunks and clauses. Based on the assumption that legal indices are composed of important tokens from the documents, extracting legal indices is treated as a problem of collecting chunks and clauses that contain as many important (...) tokens as possible. Each token is assigned a weight which is a statistical score, e.g. TF–IDF and Okapi BM25, to indicate its importance. The importance of a chunk or clause is determined based on the average weight of tokens included in that chunk or clause. Then, highly weighted chunks and clauses are recognized as the indices for legal documents. The experimental results on Japanese National Pension Act data show that our proposed method achieves better performance than TextRank, the most popular unsupervised method in extracting single-word and compound-word keywords. In addition, this approach is also applicable to extract clause keywords with high performance. (shrink)

Legal text retrieval serves as a key component in a wide range of legal text processing tasks such as legal question answering, legal case entailment, and statute law retrieval. The performance of legal text retrieval depends, to a large extent, on the representation of text, both query and legal documents. Based on good representations, a legal text retrieval model can effectively match the query to its relevant documents. Because legal documents often contain long articles and only some parts are relevant (...) to queries, it is quite a challenge for existing models to represent such documents. In this paper, we study the use of attentive neural network-based text representation for statute law document retrieval. We propose a general approach using deep neural networks with attention mechanisms. Based on it, we develop two hierarchical architectures with sparse attention to represent long sentences and articles, and we name them Attentive CNN and Paraformer. The methods are evaluated on datasets of different sizes and characteristics in English, Japanese, and Vietnamese. Experimental results show that: (i) Attentive neural methods substantially outperform non-neural methods in terms of retrieval performance across datasets and languages; (ii) Pretrained transformer-based models achieve better accuracy on small datasets at the cost of high computational complexity while lighter weight Attentive CNN achieves better accuracy on large datasets; and (iii) Our proposed Paraformer outperforms state-of-the-art methods on COLIEE dataset, achieving the highest recall and F2 scores in the top-N retrieval task. (shrink)

This paper applies a proposed modified stochastic fractal search algorithm (MSFS) for dealing with all constraints of optimal reactive power dispatch (ORPD) and finding optimal solutions for three different cases including power loss optimization, voltage deviation optimization, and L-index optimization. The proposed MSFS method is newly constructed in the paper by modifying three new solution update mechanisms on standard stochastic fractal search algorithm (SSFS). The first modification is to keep only one formula and abandon one formula in the diffusion process (...) while the second modification and the third modification are used in the first update and the second update. In two updates of SSFS, solutions with low quality are updated with high probability while other solutions with high quality do not get chances to be updated. This manner results in the fact that some promising solutions around the high quality solutions can be missed. In order to tackle this restriction, the second modification of MSFS is to newly update the worst solutions in the first update and the best solutions in the second update. In the third modification, all existing formulas of SSFS in the two updates are abandoned and the same new proposed technique is used for updating such solutions in two updates. Compared to SSFS, the three modifications can bring advantages to MSFS such as using smaller number of produced solutions per iteration, spending shorter execution time, finding better optimal solutions, and owning more stable search ability. Furthermore, the proposed method also sees its effectiveness and robustness over SSFS by testing on IEEE 30-bus system and IEEE 118-bus system with three different single objectives for each system. The proposed method can find less minimum, average, and maximum for all the cases in addition to faster search speed. Besides, the proposed method is also compared to other methods such as PSO-based method group, GA-based method group, DE-based method group, and other recent methods. Result comparisons also indicate that the proposed method can be more efficient than almost all these methods with respect to less minimum and smaller values of control parameters. As a result, evaluation of the performance of the proposed method is that it should be used for seeking solutions of ORPD problem. (shrink)

This paper presents a novel improved firefly algorithm (IFA) to deal the problem of the optimal operation of thermal generating units (OOTGU) with the purpose of reducing the total electricity generation fuel cost. The proposed IFA is developed based on combining three improvements. The first is to be based on the radius between two solutions, the second is updated step size for each considered solution based on different new equations, and the third is to slightly modify a formula producing new (...) solutions by using normally distributed random numbers and canceling uniform random numbers of conventional firefly algorithm (FA). The effect of each proposed improvement on IFA is investigated by executing five benchmark functions and two different systems. The performance of IFA is investigated on six other study cases consisting of different types of objective function and complex level of constraints. The objective function considers single fuel with quadratic form and nonconvex form, and multifuels with the sum of several quadratic and nonconvex functions while a set of constraints taken into account are power loss, prohibited zone, ramp rate limit, spinning reserve, and all constraints in transmission power networks. The obtained results indicate the proposed improvements in terms of high optimal solution quality, stabilization of search ability, and fast convergence compared with FA. In addition, the comparisons with other methods also lead to a conclusion that the proposed method is a very promising optimization tool for systems with quadratic fuel cost function and with complicated constraints. (shrink)

Precognition is an anomaly in information transmission and interpretation. Extant literature suggests that paranormal beliefs and gender may have significant influences on this unknown information process. This study examines the effects of these two factors, including their interactions, on precognition performance by employing the Bayesian Mindsponge Framework (BMF) analytics. Using Bayesian analysis on secondary data of 60 participants, we found that men may have higher chances to score a hit in a precognition task compared to women. Interestingly, stronger beliefs in (...) the paranormal may decrease the success probability in performing precognition tasks. Considering the interactions between the two factors, the effect of paranormal beliefs on precognition task performance is stronger in men than women. Using mindsponge-based reasoning, we argue that paranormal beliefs may increase the interference of imagination in the reception of hypothetical precognitive information. Women tend to rely more on intuition, which may lessen the interference effect of imagination on hypothetical psi reception. Based on the findings, we suggest that researchers should be careful when assessing participants’ psi potential for experiments. We also demonstrate some advantages of utilizing the BMF in parapsychological research. (shrink)

Coastal protection is crucial to human development since the ocean has many values associated with the economy, ecosystem, and culture. However, most ocean protecting efforts are currently ineffective due to the burdens of finance, lack of appropriate management, and international cooperation regimes. For aiding bottom-up initiatives for ocean protection support, this study employed the Mindsponge Theory to examine how the public’s perceived economic and cultural values influence their willingness to support actions to protect the ocean. Analyzing the European-Union-Horizon-2020-funded dataset of (...) 709 respondents from 42 countries, we discovered that perceived economic values have negative effects on the tendency of ocean protection supports (i.e., food, transportation, renewable energy, oil and gas, and recreation). In contrast, certain perceived cultural values can help increase the willingness to do so (i.e., mental well-being and sense of identity). However, the effects of perceived cultural values are only moderately reliable. These findings suggest that designing cultural information delivery campaigns can help promote coastal reserve supports, such as fundraisings and preserving the oceans from the community. (shrink)

Online book fairs are being held in Vietnam to replace traditional offline events that have been shelved owing to the COVID-19 crisis. This study aims to explore book consumers’ perceptions regarding digital book fairs and their evaluation of the first-ever national online book fair held in Vietnam. In-depth interviews were conducted to obtain insights from people who had attended the online book event. The findings provide acceptance of and support for the organization of digital book fairs during the COVID-19 pandemic. (...) Attendees generally appreciated the convenience of the national online book fair and the promotional programmes offered by various publishers and distributors. Furthermore, some attendees enjoyed the novelty of the event and the feeling of being included in the reading community. Nevertheless, most of the attendees highlighted several limitations, especially the lack of social and face-to-face interaction. These findings have implications for online book fair organizers, publishers, and book distributors alike. (shrink)

The nationwide economic reform in 1986 transformed Vietnam from a centrally planned economy to a socialist-oriented market economy. Entrepreneurs and entrepreneurial spirits within the populace are suggested to fuel the structural changes. Despite the importance of entrepreneurship in Vietnam’s economy, studies in Vietnam mainly pay attention to the practical aspects of entrepreneurial activities and neglect the cognitive and theoretical aspects of entrepreneurship. Thus, the current study employs the information-processing perspective of the Mindsponge Theory to explore how entrepreneurs’ knowledge accumulation can (...) affect their perceived likelihood of business success. Bayesian analysis indicates that business-related experience positively affects entrepreneurs’ business success likelihood. Greater willingness/readiness to transform thinking, acting, and beliefs can improve the business success of entrepreneurs who study others’ failures carefully. However, for entrepreneurs who perceive learning from others’ failures as unnecessary, higher willingness/readiness to transform diminishes their chance of success. Based on these findings, we recommend Vietnamese entrepreneurs accumulate knowledge through experience, learning, and an open mind for better decision-making and innovation creation capabilities. However, the learning process should be selective. (shrink)

After employing the mindsponge mechanism and 3D information process of creativity to explain the serendipity process in previous chapters, we realize that it may be helpful to delve into the relations between serendipity and the formulation of new values and information connections through non-linear processes. Thus, this chapter summarizes some preliminary attempts to use non-linear information processes to explain serendipity. We also briefly mention the benefits of information exchange among members of social groups and explain this approach.

In this paper, a proposed modified stochastic fractal search algorithm is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. Two single-objective functions are considered to be reduction of power loss and reduction of total cost of energy loss and capacitor investment while satisfying limit of capacitors, limit of conductor, and power balance of the systems. MSFS was developed by performing three new mechanisms including new diffusion mechanism and (...) two new update mechanisms on the conventional stochastic fractal search algorithm. As a result, MSFS can reduce 0.002%, 0.003%, and 0.18% of the total power loss from SFS for the three study systems. As compared to other methods, MSFS can reduce power loss from 0.07% to 3.98% for the first system, from 3.7% to 7.3% for the second system, and from 0.92% to 6.98% for the third system. For the reduction of total cost, the improvement level of the proposed method over SFS and two other methods is more significant. It is 0.03%, 1.22%, and 5.76% for the second system and 2.31%, 0.87%, and 3.77% for the third system. It is emphasized that the proposed method can find the global optimal solutions for all study cases while SFS was still implementing search process nearby or far away from the solutions. Furthermore, MSFS can converge to the best solutions much faster than these compared methods. Consequently, it can be concluded that the proposed method is very effective for finding the best location and size of added capacitors in distribution power systems. (shrink)

Products made from animal fur and skin have been a major part of human civilization. However, in modern society, the unsustainable consumption of these products – often considered luxury goods – has many negative environmental impacts. This study explores how people’s perceptions of biodiversity affect their attitudes and behaviors toward consumption. To investigate the information process deeper, we add the moderation of beliefs about biodiversity loss. Following the Bayesian Mindsponge Framework (BMF) analytics, we use mindsponge-based reasoning for constructing conceptual models (...) and employ Bayesian analysis aided by Markov Chain Monte Carlo (MCMC) algorithms on a dataset of 535 Vietnamese urban residents. The results show that people’s preference for using products made from animal skin/fur is negatively associated with perceived consequences of biodiversity loss when they believe biodiversity loss is real and a major problem. In contrast, if urban residents believe biodiversity loss is unreal or not a significant issue, the association between perceived consequences of biodiversity loss and personal preference happens in the opposite direction. The same effects of biodiversity loss perception on people’s possession of skin/fur products was not found, indicating a more complex information process on behaviors compared to attitudes. Nevertheless, in the scenario that people believe biodiversity loss is not a significant issue, the higher the perceived consequences of biodiversity loss are, the greater number of animal-based products they likely own. Our results suggest that policymakers should not neglect the factor of personal belief besides knowledge and awareness in environmental campaigns. (shrink)

Within the research community, it is generally accepted that consent processes for research should be culturally appropriate and tailored to the context, yet researchers continue to grapple with what valid consent means within specific stakeholder groups. In this study, we explored the consent practices and attitudes regarding essential information required for the consent process within hospital-based trial communities from four referral hospitals in Vietnam. We collected surveys from and conducted semi-structured interviews with study physicians, study nurses, ethics committee members, and (...) study participants and family members regarding their experiences of participating in research, their perspectives toward research, and their views about various elements of the consent process. In our findings, we describe three interrelated themes related to the consent process: words and regulation; reimbursement, suspicions, and joining; and responsibilities. In general, stakeholders had highly varied perspectives of nghiên cứu and researchers used varying levels of detail regarding all aspects of the study in the consent process to build trust with and/or promote potential research participants’ choices about taking part in research. Findings additionally highlight how researchers felt that offering financial reimbursements in a hospital setting, where payment for services was routine, would be unfamiliar to participants and could raise suspicions about the research. Participants, however, focused their discussions on reimbursement or alternative reasons for joining the study, such as health related benefits or altruism. Finally, participants often relied on their physician to help them decide about joining a study or not. Further research is needed to understand how researchers and participants make sense of and practice consent, and how that impacts participants’ decision-making about research participation. To promote valid consent within this context, it is important to engage with hospital-based trial communities as a whole. The data from this study will inform future research on consent, guide the revisions of consent related policies within our research sites and point to several larger issues surrounding researcher-participant expectations, communication, and trust. (shrink)

The digital era brings various benefits to adolescents. However, operating on the digital environment without sufficient knowledge and skills will expose them to multiple types of risks, especially in the country with low digital safety education rate like Vietnam. The current study examines factors that can contribute to cultivating adolescents’ digital resilience using the information-processing reasoning of the Mindsponge Theory. A UNESCO dataset of 1061 Vietnamese high school students was analyzed using the Bayesian Mindsponge Framework analytics. It is found that (...) adolescents’ daily Internet usage frequency, parents’ Internet safety guidance, and teachers’ safety guidance are positively associated with digital resilience. However, the effects of parents’ and teachers’ Internet safety guidance on digital resilience are conditional on the daily Internet usage frequency. Parents’ guidance only enhances adolescents’ digital resilience if they use the Internet less than four hours per day. In contrast, the positive effect of teachers’ guidance on adolescents’ digital resilience becomes stronger when the students spend more time on the Internet (more than 1 hour). Based on these findings, we suggest that adolescents can learn to minimize risks and protect themselves by exposing more to the digital environment. Parents’ and teachers’ supports are important in enhancing adolescents’ capability to deal with digital threats, but types of supports need to be carefully considered to avoid reverse impacts on adolescents’ resilience. (shrink)

Creativity is a crucial aspect of entrepreneurship. However, research on the information processing mechanism of creativity in relation to entrepreneurship is still very limited. To explore factors contributing to creativity performance among entrepreneurs in terms of information processing, we applied the Bayesian Mindsponge Framework. We used the Serendipity-Mindsponge-3D (SM3D) knowledge management theory to construct models and conducted Bayesian analysis on the most comprehensive and well-designed dataset of 3071 Vietnamese entrepreneurs up to date. We found that entrepreneurs who give more time (...) to their startup attempts are likely to have lower levels of creativity. Both factors of higher levels of knowledge within one’s discipline and better connections to out-of-discipline knowledge are positively associated with more creativity. While the effect of openmindedness on the relationship between within-discipline knowledge and creativity is unclear, openmindedness was found to have a positive moderating effect on the association between out-of-discipline knowledge and creativity. These findings support entrepreneurs in understanding the information processing mechanisms behind creativity for creating more effective knowledge management strategies. (shrink)

Humankind is facing many existential global problems that require international and transgenerational efforts to be solved. Preparing our next generation with sufficient knowledge and skills to deal with such problems is imperative. Fortunately, the digital environment provides foundational conditions for children’s and adolescents’ exploration and self-learning, which might help them cultivate the necessary knowledge and skills for future survival. We conducted the Bayesian Mindsponge Framework (BMF) analytics on a dataset of 2069 students from 54 Vietnamese elementary, secondary, and high schools (...) to test this presumption. The results showed that students with higher digital literacy are more curious and have better knowledge regarding global issues (i.e., climate change, disease, overpopulation, aging, etc.). Students’ curiosity also mediates the relationship between digital literacy and global issues knowledge. Based on these findings, we argue that digital explorative space is essential for digital natives’ education for survival, individually (i.e., for future employment requirements) and socially (i.e., for making informed decisions and creating innovations that can be helpful to society). Children’s and adolescents’ exposure to digital explorative space should be promoted to improve their digital literacy rather than prohibition. During the exploration, emotional intelligence is critical in mitigating existential risks, or threats, to digital natives to navigate and overcome chaotic processes occurring in unchartered waters in the virtual world. (shrink)

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. (shrink)

Computational drug repositioning has been proven as a promising and efficient strategy for discovering new uses from existing drugs. To achieve this goal, a number of computational methods have been proposed, which are based on different data sources of drugs and diseases. These methods approach the problem using either machine learning- or network-based models with an assumption that similar drugs can be used for similar diseases to identify new indications of drugs. Therefore, similarities between drugs and between diseases are usually (...) used as inputs. In addition, known drug-disease associations are also needed for the methods as prior information. It should be noted that those associations are still not well established due to the fact that many of marketed drugs have been withdrawn and this could affect the outcome of the methods. In this study, we propose a novel method named RLSDR to find new uses of drugs. More specifically, it relies on a semi-supervised learning model, Regularized Least Square, thus it does not require definition of non-drug-disease associations as previously proposed machine learning-based methods. In addition, the similarity between drugs measured by chemical structures of drug compounds and the similarity between diseases which share phenotypes can be represented in a form of either similarity network or similarity matrix as inputs of the method. Moreover, instead of using a gold-standard set of known drug-disease associations, we construct an artificial set of the associations based on known disease-gene and drug-target associations. Experiment results demonstrate that RLSDR achieves better prediction performance on the artificial set of drug-disease associations than that on the gold-standard ones in terms of area under the Receiver Operating Characteristic curve. In addition, it outperforms two representative network-based methods irrespective of the prior information of drug-disease associations. Novel indications for a number of drugs are also identified and validated by evidences from a different data resource. (shrink)

Air pollution is a considerable environmental stressor for urban residents in developing countries. Perceived health risks of air pollution might induce migration intention among inhabitants. The current study employed the Bayesian Mindsponge Framework (BMF) to investigate the rationale behind the domestic and international migration intentions among 475 inhabitants in Hanoi, Vietnam – one of the most polluted capital cities worldwide. We found that people perceiving more impacts of air pollution in their daily life are more likely to have migration intention. (...) The effect of perceived air pollution impact on international migration intention is stronger than that of domestic migration. Acknowledging a family member’s air pollution-induced sickness moderated the association between perceived air pollution impact and domestic migration intention, while the personal experience of air pollution-induced sickness did not. In contrast, the moderation effect of personal experience of sickness became significant in the international migration circumstance, but the effect of information about a family member’s sickness was trivial. The findings suggest that urban inhabitants’ consideration of air pollution averting strategies reflects some characteristics of Homo Oeconomicus. Additionally, the individual’s socio-economic decision is seemingly insignificant on a social scale. Still, through environmental stressors as catalysts, such decisions might result in considerable social outcomes (e.g., internal migration and emigration). (shrink)

We present our method for tackling a legal case retrieval task by introducing our method of encoding documents by summarizing them into continuous vector space via our phrase scoring framework utilizing deep neural networks. On the other hand, we explore the benefits from combining lexical features and latent features generated with neural networks. Our experiments show that lexical features and latent features generated with neural networks complement each other to improve the retrieval system performance. Furthermore, our experimental results suggest the (...) importance of case summarization in different aspects: using provided summaries and performing encoded summarization. Our approach achieved F1 of 65.6% and 57.6% on the experimental datasets of legal case retrieval tasks. (shrink)

The accession and implementation of new generation free trade agreements bring numerous opportunities as well as challenges to Viet Nam, regarding trade, labor and investment. The increasing number of workers abroad puts a pressure on Vietnamese government to support them in new working cultures and environments. The application of chatbot, which has been known to help certain vulnerable groups such as patients, women and migrants could be one of the tools to support Vietnamese migrant workers by providing immediate information, network (...) connection and consultation. Analyzing the results of the qualitative interviews with 11 migrant workers and the group discussion with two sections from three public social media groups and three active informants, the article argues that migrant workers as a vulnerable group who are supposed to be promising users of chatbot due to their great demand and needs, may have a complicated form of trust and expectation in chatbot. (shrink)

Modern society faces major environmental problems, but there are many difficulties in studying the nature–human relationship from an integral psychosocial perspective. We propose the ecomind sponge conceptual framework, based on the mindsponge theory of information processing. We present a systematic method to examine the nature–human relationship with conceptual frameworks of system boundaries, selective exchange, and adaptive optimization. The theoretical mechanisms were constructed based on principles and new evidence in natural sciences. The core mechanism of ecomindsponge is the subjective sphere of (...) influence, which is the limited mental representation of information received from and processed based on the objective sphere of influence–actual interactions in reality. The subjective sphere is the sum of two sub-spheres: influencing (proactive) and being influenced (reactive). Maladaptation in thinking and behavior of the mind as an information collection-cum-processor results from the deviation of the subjective sphere from reality, which includes two main types: “stupidity” and “delusion”. Using Bayesian Mindsponge Framework (BMF) analytics on a dataset of 535 urban residents, we provide consistent statistical evidence on the proposed properties of subjective spheres. The dynamic framework of ecomindsponge can be used flexibly and practically for environmental research as well as other psychosocial fields. (shrink)

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.”. (shrink)

This paper is an empirical analysis of how culture, specifically tradition, affects well-being, i.e., happiness, life satisfaction, and financial satisfaction, along with socioeconomic factors in East Asia. Ordered probit regression model results show that women have higher happiness and satisfaction levels than men even in Confucian cultures in which men generally receive more favourable conditions than women. Additionally, marital status or the impact of religion had strong and positive effects on happiness and sometimes on life satisfaction but not on financial (...) satisfaction. Interestingly, tradition has a statistically significant and important effect on both life and financial satisfaction. Finally, the results show that individuals who value tradition greater also have higher levels of financial satisfaction. (shrink)

As conventionally understood, corruption relies on a set of universally agreed rules that determine what constitutes the appropriate allocation of organizational resources. This article explores whether rule-based approaches to corruption are applicable where business organizations, such as public private partnerships, and the public fundamentally disagree about what constitutes an appropriate allocation of resources. Drawing on empirical research about PPPs in Vietnam, this article compares how government, business organizations, and the public conceptualize the transfer of public assets into private ownership. It (...) argues that a public interest approach to corruption is needed where PPPs privatize public assets within the law, but against the express wishes of the public. (shrink)

Based on the properties and mechanism of serendipity presented in former chapters, this chapter discusses how to create an environment for higher serendipity encounters and attainment possibilities. We examine four types of environments with different navigational and useful information concentration combinations. Building a pro-serendipity culture will help create environments that value and supports serendipity across fields. Additionally, we also address the notion that serendipity is a skill. Thus, it can produce either good or bad impacts on a collective level, depending (...) on the ultimate purposes behind it. (shrink)

Objectives: The official implementation of clinical pharmacy in Vietnam has arrived relatively late, resulting in various stressors. This study aims to evaluate job stress level and suggest viable solutions.Methods: A cross-sectional study was conducted on clinical pharmacists in 128 hospitals in Ho Chi Minh City. Job stress questions were derived from the Healthcare Profession Stress Inventory.Results: A total of 197 CPs participated, giving a response rate of 82.4%. Participants were found to have moderate job stress with an overall mean stress (...) score of 1.5 and stress rate of 52.8%. The sample size was statistically adequate and the HPSI was valid and reliable. Patient care responsibility was the main stressor, especially in public hospitals, followed by job conflicts. Lack of experience, low income, and inability to participate in clinical ward rounds caused significant stress to CPs regarding job recognition and job uncertainty. More practice-oriented training programs in bachelor curricula and clinical practice should be applied to help CPs gain more experience, self-confidence, and diminish job stress.Conclusion: CPs in HCMC have moderate stress. More practice-oriented training programs should be prioritized to lessen stress for CPs. (shrink)

Food security is one of the major concerns in the Philippines. Although livestock and poultry production accounts for a significant proportion of the country’s agricultural output, smallholder households are still vulnerable to food insecurity. The current study aims to examine how livestock production and selling difficulties affect smallholder households’ food-insecure conditions. For this objective, Bayesian Mindsponge Framework (BMF) analytics was employed on a dataset of the Food and Agriculture Organization’s Data in Emergencies Monitoring (DIEM) system. We found that production and (...) selling difficulties significantly adversely affect food insecurity in the Philippines. However, their effects vary according to the severity of food insecurity. In particular, production and selling difficulties affect the households’ likelihood of eating less healthy and nutritious food equally. However, the production difficulties have more negligible impacts on the possibility of skipping meals and even ambiguous impacts on the likelihood of not eating for a whole day compared to the effects of selling difficulties. Moreover, we also found that the market plays a crucial role in facilitating not only livestock trading but also livestock production (e.g., purchase of feed and medicines). Based on these findings, we suggest that the livestock market needs to be expanded and regulated to maintain the balancing prices between livestock products and products and services used for livestock production, and facilitate the product-exchanging mechanism. (shrink)

This research proposes a modified metaheuristic optimization algorithm, named as improved stochastic fractal search, which is formed based on the integration of the quasiopposition-based learning and chaotic local search schemes into the original SFS algorithm for solving the optimal capacitor placement in radial distribution networks. The test problem involves the determination of the optimal number, location, and size of fixed and switched capacitors at different loading conditions so that the network total yearly cost is minimized with simultaneous fulfillment of operating (...) constraints. Also, the hourly on/off scheduling plans of switched shunt capacitors considering a modified cost objective function are obtained. The proposed ISFS algorithm has been tested on two IEEE 69-bus and 119-bus RDNs and a practical 152-bus RDN. For clarifying the effectiveness and validation of the ISFS, the simulated results have been compared with those of other previously utilized solution approaches in the literature as well as the original SFS. From result comparison, the proposed ISFS outperforms other previous approaches regarding solution quality and statistical performance for the compared cases, especially in the complex and large-scale networks. Notably, compared with the original SFS, the proposed ISFS shows a significantly better performance in all the tested cases. (shrink)

Recent significant changes in technology such as Artificial Intelligence and big data analysis have a wide impact in many areas of human societies, not least in education. Advances in efficien...

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. (shrink)

Nowadays, the power systems are getting more and more complicated because of the delays introduced by the communication networks. The existence of the delays usually leads to the degradation and/or instability of power system performance. On account of this point, the traditional load frequency control approach for power system sketches a destabilizing impact and an unacceptable system performance. Therefore, this paper proposes a new LFC based on adaptive integral second-order sliding mode control approach for the large-scale power system with communication (...) delays. First, a new linear matrix inequality is derived to ensure the stability of whole power systems using Lyapunov stability theory. Second, an AISOSMC law is designed to ensure the finite time reachability of the system states. To the best of our knowledge, this is the first time the AISOSMC is designed for LFC of the LSPSwCD. In addition, the report of testing results presents that the suggested LFC based on AISOSMC can not only decrease effectively the frequency variation but also make successfully less in mount of power oscillation/fluctuation in tie-line exchange. (shrink)

Natural language processing techniques contribute more and more in analyzing legal documents recently, which supports the implementation of laws and rules using computers. Previous approaches in representing a legal sentence often based on logical patterns that illustrate the relations between concepts in the sentence, often consist of multiple words. Those representations cause the lack of semantic information at the word level. In our work, we aim to tackle such shortcomings by representing legal texts in the form of abstract meaning representation, (...) a graph-based semantic representation that gains lots of polarity in NLP community recently. We present our study in AMR Parsing and AMR-to-text Generation specifically for legal domain. We also introduce JCivilCode, a human-annotated legal AMR dataset which was created and verified by a group of linguistic and legal experts. We conduct an empirical evaluation of various approaches in parsing and generating AMR on our own dataset and show the current challenges. Based on our observation, we propose our domain adaptation method applying in the training phase and decoding phase of a neural AMR-to-text generation model. Our method improves the quality of text generated from AMR graph compared to the baseline model. 2018; and “Legal Text Generation fromMeaning Representation”, published in the 32nd International Conference on Legal Knowledge and Information Systems 2019.). (shrink)

Cheating is a major problem in society, especially in the educational system. From the viewpoint of subjective cost-benefit analysis, concerns about reputation damage as well as considerations of cultural values against unethical behavior can help increase the perceived costs of cheating. To explore deeper into the psychological processes in such assessments, we employ Bayesian Mindsponge Framework (BMF) analytics – an information-processingbased method. Conducting Bayesian analysis on 493 university students from Germany, Vietnam, China, Taiwan, and Japan, we found that reputation concern (...) is negatively associated with cheating behavior. If a student embraces Confucian values, the above negating effect is stronger. Our findings support the notion that mentally simulated negative consequences of cheating reduce the probability of carrying out such behavior. As the educational system is changing rapidly due to technological advancement, a better understanding of the influences of sociocultural factors can be helpful in cheating prevention efforts. (shrink)