Nguyen Minh

Daoist philosophy remains deeply relevant to contemporary global challenges, particularly in cultivating Nature Quotient (NQ), fostering peace-building and social harmony, navigating disruptions associated with artificial intelligence, and reflecting on the widening socio-economic inequality. However, Daoism is often perceived as mystical and rooted in symbolic metaphysics, which can create barriers to its adoption in modern societies that increasingly prioritize justified and scientifically validated knowledge. This paper introduces the Kingfisherish perspective—developed primarily through the thought and philosophy of Professor Quan-Hoang Vuong—and demonstrates its strong alignment with the Daoist philosophies of Laozi and Zhuangzi. Both perspectives embrace a monistic worldview, illuminate the uncertain nature of knowledge, and highlight the relativity and non-linearity of value as individuals seek dynamic equilibrium with reality (i.e., alignment with the Dao) to reduce uncertainty. Furthermore, Kingfisherish and Daoist thinking both emphasize “order-induced blindness,” whereby artificially constructed social orders and stabilized structures obscure the authentic dynamics of reality and drift away from the Dao. To counter this, they encourage humility and compassion, and employ paradoxes, contradictions, and absurdist reasoning as cognitive pathways that help people overcome unjustified beliefs, convictions, and prejudices and gently guide individuals toward deeper alignment with the Dao. This strong conceptual resonance provides a meaningful conduit for re-examining ancient Daoist philosophies through a scientific lens—particularly quantum-mechanics-inspired reasoning and information-processing theories—while simultaneously drawing on their enduring wisdom to inform responses to pressing contemporary challenges.

Coastal engagement activities have been explored for their measurable health benefits, including both physical and mental health outcomes. These activities may foster a deeper sense of connection to nature following every visit to the coast, such as watching the sunset, beach walking, spending time on the beach, wildlife spotting, shell collecting, engaging in beach and water sports, mountain biking, and participating in seagoing activities. However, limited research has examined the moderating effect of nature connectedness on the relationship between these activities and health outcomes, both physically and mentally. This study aimed to analyse how the relationships between coastal activities and perceived mental and general health conditions in the previous year are moderated by the level of nature connectedness among adult visitors. By analyzing the dataset of 1,939 Flemish individuals engaged in the Belgian coast, under the Bayesian Mindsponge Framework (BMF), this study found a crucial moderating role of coastal nature connectedness. Findings showed that coastal activities are negatively associated with mental and general health scores, but with the moderating effect of nature connectedness, this negative association may shift. In each level of nature connectedness, coastal activities showed different effects on mental and general health conditions, with higher improvement found in mental health scores. Findings indicate that, beyond the type of coastal activities, nature connectedness is an essential subjective sense that determines therapeutic benefits. This study highlights the complex interplay of environmental factors, subjective perceptions, and biophysical-psychological interactions in shaping individual health outcomes. There is a need for targeted coastal management strategies to facilitate nature-based activities that promote nature-connectedness and, subsequently, coastal healing capabilities.

Traditional engineering courses typically approach teaching and problem solving by focusing on the physical dimensions of those problems without consideration of dynamic social and ethical dimensions. As such, projects can fail to consider human rights, community questions and concerns, broader impacts upon society, or otherwise result in inequitable outcomes. And, despite the fact that students in engineering receive training on the Professional Code of Ethics for Engineers, to which they are expected to adhere in practice, many students are unable to recognize and analyze real-life ethical challenges as they arise. Indeed, research has found that students are typically less engaged with ethics—defined as the sensitivity and judgment of microethics and macroethics, sensitivity to diversity, and interest in promoting organizational ethical culture—at the end of their engineering studies than they were at the beginning. As such, many studies have focused on developing and improving the curriculum surrounding ethics through, for instance, exposing students to ethics case studies. However, such ethics courses often present a narrow and simplified view of ethics that students may struggle to integrate with their broader experience as engineers. Thus, there is a critical need to unpack the complexity of ethical behavior amongst engineering students in order to determine how to better foster ethical judgment and behavior. Promoting ethical behavior among engineering students and developing a culture of ethical behavior within institutions have become goals of many engineering programs. Towards this goal, we would like to present an overview of the current scholarship of engineering ethics and propose a theoretical framework of ethical behavior using a review of articles related to engineering ethics from 1997-2020. The review engages in theories across disciplines including philosophy, education, and psychology. In this work-in-progress paper, we present a subset of initial results based on a review of the first 50 articles out of the systematically selected 409 articles from Springer, Engineering Village, and EBSCO-Education Full Text. Preliminary results identify two major kinds of drivers of ethical behavior, namely individual level ethical behavior drivers and institutional drivers. Our preliminary results indicate that a sensitivity to both microethics and macroethics as well as the implicit and explicit understanding of ethics are essential in promoting ethical behavior amongst students. Furthermore, while drivers of ethical behavior at the individual level is important, one should not ignore the roles of the drivers of ethical behavior at the institutional level in promoting a collective ethical culture within organizations. The review also points to a need to focus on increasing students’ macroethical sensitivity to topics such as sustainability and protection of human rights. This research thus addresses the need, driven by existing scholarship, 2 to identify a conceptual framework for explaining how ethical judgment and behavior in engineering can be further promoted.

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.

Growing numbers of women in militaries worldwide, coupled with vast segments of women within war-affected populations globally, raise questions about gender as it structures trauma exposure, posttraumatic stress disorder, and other mental health consequences of war. In this study, we investigate the gendered associations between early-life wartime stress exposures and PTSD symptoms in older adulthood using data from the 2018 Vietnam Health and Aging Study, a unique data set documenting multiple dimensions of health and wartime stress exposures within a sample of older adults who occupied diverse roles during the American war in Vietnam. Our results indicate that the severity of recent PTSD symptoms is significantly and positively associated with the severity of wartime stress exposure among both men and women. Vietnamese men’s social positions, particularly their predominance in combat, exposed them to more numerous war-related stressors. However, Vietnamese women experience a greater PTSD penalty associated with some wartime stress exposures, likely due to the burden of protecting family in wartime and incorporation into military and paramilitary roles with lesser preparation, training, and support than men. We conclude that women who survive major wars, both as soldiers and civilians, bear a significant burden of armed conflict’s lasting toll upon mental health.

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.

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.

One of our entrenched intuitions about the mental is that every person is authoritative with respect to the propositional contents and attitudes of his own current mind. First-person authority is characterized by the following asymmetry: it is logically necessary that, whenever one sincerely ascribes the presence, or absence, of a certain intentional state to one's present self, there is a legitimate presumption that one is correct; whereas it is not logically necessary that, whenever one honestly attributes the presence, or absence, of a certain intentional state to any other individual or to one's non-present self, or makes a claim about the non-mental features of the external world, there is a legitimate presumption that one is correct. ;The problem is how to explain first-person authority. Unless such an explanation is available, there will not be satisfactory reason for thinking that our own current intentional states, over which we allegedly reign with epistemic authority, and others' intentional states, over which we supposedly do not exercise similar authority, are the same sort of state. There is no possible way for friends of first-person authority to avert skepticism about other minds until they succeed in ensuring that this authority can be explained. ;My dissertation consists of two chapters. In Chapter One, I lay out the problem of explaining first-person authority and argue that all attempts to solve this problem to date have failed. This chapter is largely negative. It argues against all actually proposed explanations of first-person authority. In Chapter Two, I contend that any attempt to explain it is doomed to fail, because there is no such thing as first-person authority. This chapter is mainly positive. It argues for eliminativism about first-person authority. A condensed version of this last argument is contained in the final section of the first chapter

This analysis used data, primarily from the 1997 Vietnamese Demographic and Health Survey (VN-DHS 1997), to determine the changes in contraceptive use in Vietnam. A descriptive analysis of individual, household and community characteristics was made to obtain a general description of contraceptive use. Multinomial logistic regression analyses were also performed on the currently married in (a) a sample of all women and (b) only those women who live in rural areas, to identify the strength of association that each variable has with the use of modern contraceptives. The use of any contraceptive method and the use of modern methods increased from 1988 to 1997. The primary contraceptive method utilized is the IUD and its use has increased substantially from 1988 to 1997. Younger women (aged 15–24) were less likely to use any contraceptive method. Women not desiring additional children were significantly more likely to use contraceptive methods than those desiring more children. Education has a clear impact on both contraceptive knowledge and use by women, with higher educated women being more likely to use a contraceptive method. Illiterate women with no formal education were significantly less likely to use modern methods of contraception. Differentials in contraceptive use exist regarding place of residence. Urban women are more likely than rural women to use contraception, but the difference is not large. Women living in mountainous areas are less likely to use contraception, compared with women living in the lowlands. Living standards, especially the availability of electricity in the community, have a large effect on the methods of contraception adopted by women. Religion is not strongly related to the contraceptive behaviour of women. There were significant differences in the use of contraceptives in communities with good quality of care, with increased contraceptive use corresponding to the increase in availability of family planning workers at communes, provision of counselling services at health facilities, and the volume of mass media family planning messages

This paper presents an enhanced ontology formalization, combining previous work in Conceptual Structure Theory and Order-Sorted Logic. Most existing ontology formalisms place greater importance on concept types, but in this paper we focus on relation types, which are in essence predicates on concept types. We formalize the notion of ‘predicate of predicates’ as meta-relation type and introduce the new hierarchy of meta-relation types as part of the ontology definition. The new notion of closure of a relation or meta-relation type is presented as a means to complete that relation or meta-relation type by transferring extra arguments and properties from other related types. The end result is an expanded ontology, called the closure of the original ontology, on which automated inference could be more easily performed. Our proposal could be viewed as a novel and improved ontology formalization within Conceptual Structure Theory and a contribution to knowledge representation and formal reasoning (e.g., to build a query-answering system for legal knowledge).