H. Nguyen

The rapid advancement of Information Technology (IT) platforms and programming languages has transformed the dynamics and development of human society. The cyberspace and associated utilities are expanding, leading to a gradual shift from real-world living to virtual life (also known as cyberspace or digital space). The expansion and development of Natural Language Processing (NLP) models and Large Language Models (LLMs) demonstrate human-like characteristics in reasoning, perception, attention, and creativity, helping humans overcome operational barriers. Alongside the immense potential of artificial intelligence (AI) are new security loopholes and more complex information security risks. As society is still trying to transition to a new phase to adapt to technological changes, the AI revolution continues to unfold, necessitating a reconsideration of the trajectory of societal transformation as it could exacerbate the aforementioned information security risks. Specifically, how should society evolve to keep pace with the transformative impact of the current AI technology wave? How can we manage and harness their power while ensuring information security as our presence in the virtual world increases? This article aims to shed light on and address these questions.

Circular economy (CE), a sustainability concept that promotes resource efficiency and waste reduction, has garnered significant popularity in recent years due to its potential to address pressing environmental and economic challenges. This study employs the Bayesian mindsponge framework (BMF) to explore what drives young adults’ pro-environmental behavior and purchases of green products at different levels of price. The results show that young adult’s knowledge of CE and care about environmental protection and energy saving encourages the practice of waste classification, while factors that affect their willingness to pay (WTP) more for green and energy-saving products vary at different price tiers.

Motivated by the increasing economic significance of investment advisory industries and the prevalence of wrongdoing in financial planning services, we examine whether, and to what extent, employee misconduct is shaped by their local corruption culture. Using novel data of more than 4.7 million adviser-year observations of financial advisers and the Department of Justice’s data on corruption, we find that financial advisers and advisory firms located in areas with higher levels of corruption are more likely to commit misconduct. These results hold for both individual advisor and firm level analyses and are robust to the use of various fixed effects, model specifications, proxies for corruption and misconduct, and an instrumental variable approach. Using the passage of the Dodd-Frank Whistleblower Provision, which provides incentives for reporting corruption incidences and thereby reduces the incentives for fraud, we find that the relation between local corruption culture and adviser misconduct is attenuated after the provision enacted by the SEC. Overall, our study highlights the externalities of corruption culture on individual ethics and the essential role of whistleblowing laws in reducing corruption-prone norms.

In our ever technologically driven and mediatized society, we face the existential risk of falling into an info-calypse as much as an eco-calypse. To complement the list of values of a progressive culture put forth by Harrison (Natl Interest 60:55–65, 2000) and Vuong (Econ Bus Lett 10(3):284–290, 2021), this short essay proposes cultivating a new cultural value of protecting the infosphere. It argues rewarding practices and products that strengthen the integrity of infosphere as part of the newly emerged corporate social responsibility (CSR) practices are highly beneficial for the fight against contaminations of the infosphere, i.e., misinformation, disinformation, damaging contents, etc.

The book consists of 16 chapters divided into three main parts, emphasizing the market system and financial-monetary control mechanisms. The book provides readers with significant economic advances. Thanks to a relatively extensive system of materials collected, chosen and computed over a long period of time from various domestic and international sources since Vietnam's independence. The book has highlighted the unresolved concerns and proposals based on examinations of the changing process of mechanisms and policies in general and for the financial industry, banks and markets in particular. The study also focuses on Vietnam's real estate market, gold, stock market and US dollar market.

Forests play fundamental roles in the Earth’s ecosystems. With the great capability of carbon sequestration, tropical forests are expected to contribute substantially to reducing the CO2 in Earth’s atmosphere. However, global tropical forest areas have declined drastically over the last few decades due to pressures from socio-economic development pursuit. The current essay aims to demonstrate the ongoing global deforestation crisis and its underlying drivers and discuss the vital roles of tropical forests in the socio-economic development in the face of climate change when developed countries start to tighten the carbon emission control regulations (e.g., European Union’s Carbon Border Adjustment Mechanism). It suggests why developing countries in tropical regions, particularly Vietnam, should not sacrifice forests for short- and medium-term socio-economic goals but capitalize on them to leverage long-term development. Moreover, evidence of Vietnamese political leaders’ commitment to forest protection and sustainable development is also provided.

Many problems in Multi-Agent Systems (MASs) research are formulated in terms of the abilities of a coalition of agents. Existing approaches to reasoning about coalitional ability are usually focused on games or transition systems, which are described in terms of states and actions. Such approaches however often neglect a key feature of multi-agent systems, namely that the actions of the agents require resources. In this paper, we describe a logic for reasoning about coalitional ability under resource constraints in the probabilistic setting. We extend Resource-bounded Alternating-time Temporal Logic (RB-ATL) with probabilistic reasoning and provide a standard algorithm for the model-checking problem of the resulting logic Probabilistic resource-bounded ATL (pRB-ATL). We implement model-checking algorithms and present experimental results using simple multi-agent model-checking problems of increasing complexity.

Humans recognise reddish-coloured faces as angry. However, does facial colour also affect “implicit” facial expression perception of which humans are not explicitly aware? In this study, we investigated the effects of facial colour on implicit facial expression perception. The experimental stimuli were “hybrid faces”, in which the low-frequency component of the neutral facial expression image was replaced with the low-frequency component of the facial expression image of happiness or anger. In Experiment 1, we confirmed that the hybrid face stimuli were perceived as neutral and, therefore, supported implicit facial expression perception. In Experiment 2, the hybrid face stimuli were adjusted to natural and reddish facial colours, and their friendliness ratings were compared. The results showed that the expression of happiness was rated as more friendly than the expression of anger. In addition, the expression of happiness was rated as friendlier when the low-frequency happy component was red, but the friendliness rating of the expression of anger did not change when it was presented in red. In Experiment 3, we affirmed the implicit facial expression perception even in reddish colours. These results suggest that facial colour modulates the perception of implicit facial expressions in hybrid facial stimuli.

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.

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.

Vietnam has exhibited rapid economic growth over thirty years of comprehensive economic reforms. However, about half of the country’s active population remains in agriculture. In order to characterize the role of agriculture and livestock in Vietnam’s structural transformation, we assess ongoing dynamics at three complementary scales: national, sectoral (agriculture and livestock) and local (district of Bavi). We show that the transition since Doi Moi (Renovation) has given rise to a political economy that provides incentives to industries and services. However, labor abundance (due to population density) and limited land availability (85% of agricultural land is composed of less than 1 ha farms) have slowed the canonical structural transformation, and widened income inequality between agriculture and non-agricultural workers. In this ‘Lewis trap’ context, intensive livestock (as it is the case for aquaculture and horticulture) has played a significant role in increasing labor and land productivity, offering some perspectives to secure smallholder agricultural systems. But the emergence of those very intensive systems producing a lot of effluents has in the same time jeopardized sustainable development of rural and peri-urban areas. More recently, the political shift towards industrial corporate agriculture and large-scale farming has increased this pressure on the environment, and endangered inclusive agricultural development. Today, smallholder farming and rural communities encounter many challenges to exploit resources efficiently and gain access to input markets to achieve higher productivity and value added. To avoid the risk of poverty trap and to pursue a sustainable and inclusive development over the long run, deeper and wider reforms are needed based on smallholder viability, agroecological principles, and crop-livestock integration.

Words not only define our reality, they reveal and direct our attitudes toward that reality. This feature of language is especially problematic when it comes to our treatment of animals. In this supple, thoughtful, and closely argued work, Vietnamese-American scholar Hanh Nguyen examines the words we use in English and other languages to justify our abuse of other-than-human world. Reframing our metaphors, categories, and descriptions of animals we love, hate, and eat allows us to break long-standing habits and see our obligations and connections to non-human animals more clearly.

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.

Ortadoğu bölgesindeki çatışma ve istikrarsızlık ortamının ardında İran - Suudi Arabistan rekabeti bulunmaktadır. Bununla birlikte bu rekabetin politik doğası, çoğunlukla ana akım medya tarafından aşırı derecede basitleştirilmiştir. Benzer biçimde İran – Suudi Arabistan rekabetinin içindeki kimlik politikaları üzerine yazılmış literatürün büyük bir kısmı bölgesel istikrarsızlıkların kökeni ve kaynağını ağırlıklı olarak tarihlerinin genel ve betimleyici bir hesabını sunmuş veya oyuncuların iktidar mücadeleleri içerisinde Sünni ve Şii İslam’ın politikleşmesine ve manipülasyonuna odaklanmıştır. Halen mevcut olan kimlik politikaları üzerine teorileri sentezleyen, yani Primordializm, araçsallık, ve sosyal inşacılık, bu araştırmanın teorik modelini oluşturmaktadır. Bu modelde, mezhepsel kimlik – Ortadoğu toplumlarının ve yanı sıra bölgesel tarihin bir gerçeği olarak – sadece politik süreçler üzerine muazzam etkileri ölçülmedi, ayrıca politik uygulamalarda her düzeydeki politik aktörlerin kullanımıyla karşılaştırılmıştır.

Motivated by a call for risk discourse research in non-Western settings, this study examines how Vietnamese road safety video advertisements are constructed and interpreted. Following a literature review of risk and gender, the study first sets out socio-semiotic multimodal analysis of video advertisements to detail how concepts of risk and gender are constructed. Afterwards, I take an ethnographic-based approach in a series of interviews with professional Vietnamese women to gain insights into these concepts. Findings of the study reveal the expected female roles as wives and mothers in Vietnamese advertising as interpreted by Vietnamese women. The study contributes to an understanding of risk in this Asian setting and opens up the potential for a critical, interpretive approach to risk discourses that are grounded in lived experiences.

Introduction: Pathological tremor is the most common motor disorder in adults and characterized by involuntary, rhythmic muscular contraction leading to shaking movements in one or more parts of the body. Functional Electrical Stimulation and biomechanical loading using wearable orthoses have emerged as effective and non-invasive methods for tremor suppression. A variety of upper-limb orthoses for tremor suppression have been introduced; however, a systematic review of the mechanical design, algorithms for tremor extraction, and the experimental design is still missing.Methods: To address this gap, we applied a standard systematic review methodology to conduct a literature search in the PubMed and PMC databases. Inclusion criteria and full-text access eligibility were used to filter the studies from the search results. Subsequently, we extracted relevant information, such as suppression mechanism, system weights, degrees of freedom, algorithms for tremor estimation, experimental settings, and the efficacy.Results: The results show that the majority of tremor-suppression orthoses are active with 47% prevalence. Active orthoses are also the heaviest with an average weight of 561 ± 467 g, followed by semi-active 486 ± 395 g, and passive orthoses 191 ± 137 g. Most of the orthoses only support one DOF. Two-DOF and three-DOF orthoses account for 33 and 18%, respectively. The average efficacy of tremor suppression using wearable orthoses is 83 ± 13%. Active orthoses are the most efficient with an average efficacy of 83 ± 8%, following by the semi-active 77 ± 19%, and passive orthoses 75 ± 12%. Among different experimental setups, bench testing shows the highest efficacy at 95 ± 5%, this value dropped to 86 ± 8% when evaluating with tremor-affected subjects. The majority of the orthoses measured voluntary and/or tremorous motions using biomechanical sensors. Only one system was found to utilize EMG for tremor extraction.Conclusions: Our review showed an improvement in efficacy of using robotic orthoses in tremor suppression. However, significant challenges for the translations of these systems into clinical or home use remain unsolved. Future challenges include improving the wearability of the orthoses, and user control interfaces. We also suggest addressing non-technical challenges to make the technology more accessible.

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.

Transformer is a neural machine translation model which revolutionizes machine translation. Compared with traditional statistical machine translation models and other neural machine translation models, the recently proposed transformer model radically and fundamentally changes machine translation with its self-attention and cross-attention mechanisms. These mechanisms effectively model token alignments between source and target sentences. It has been reported that the transformer model provides accurate posterior alignments. In this work, we empirically prove the reverse effect, showing that prior alignments help transformer models produce better translations. Experiment results on Vietnamese-English news translation task show not only the positive effect of manually annotated alignments on transformer models but also the surprising outperformance of statistically constructed alignments reinforced with the flexibility of token-type selection over manual alignments in improving transformer models. Statistically constructed word-to-lemma alignments are used to train a word-to-word transformer model. The novel hybrid transformer model improves the baseline transformer model and transformer model trained with manual alignments by 2.53 and 0.79 BLEU, respectively. In addition to BLEU score, we make limited human judgment on translation results. Strong correlation between human and machine judgment confirms our findings.

In the current study, the orthographic knowledge required for writing Chinese characters was assessed among participants with L1 Vietnamese background who learn Chinese as a foreign language. A total of 42 undergraduates were recruited. They were invited to participate in a delayed Chinese character copying task consisting of 32 characters. Their Chinese character reading abilities were also obtained using a character naming task. All the tests were conducted online during the pandemic in 2021. Results indicated that the participants’ accuracy in the copying task was affected by the familiarity of the characters and the number of strokes of the characters. These effects minimized as reading performance increased. In the inter-stroke interval analysis, results indicated a significant boundary effect where ISIs between orthographic units were longer than ISIs within orthographic units, showing the participants’ tendency to chunk Chinese characters into functional units when they write. Only high achievers in the reading task demonstrated the use of both large and small grain-size units in writing, while the low achievers only used small grain-size units in their writing. We suggest that the delayed copying task incorporated with handwriting measures is an effective method to assess orthographic knowledge of L2 Chinese learners.

We consider a fishery model with two sites: (1) a marine protected area (MPA) where fishing is prohibited and (2) an area where the fish population is harvested. We assume that fish can migrate from MPA to fishing area at a very fast time scale and fish spatial organisation can change from small to large clusters of school at a fast time scale. The growth of the fish population and the catch are assumed to occur at a slow time scale. The complete model is a system of five ordinary differential equations with three time scales. We take advantage of the time scales using aggregation of variables methods to derive a reduced model governing the total fish density and fishing effort at the slow time scale. We analyze this aggregated model and show that under some conditions, there exists an equilibrium corresponding to a sustainable fishery. Our results suggest that in small pelagic fisheries the yield is maximum for a fish population distributed among both small and large clusters of school.