China's rise and the 'Chinese dream' in international relations theory

The rise of China/East Asia and the perceived decline of the US/West pose an emerging question about how international relations (IR) theory should respond to this change. Increasingly, there have been heated discussions among Chinese IR academics over a desirable Chinese contribution to IR theory (IRT), particularly the possibility of building a distinctive Chinese IRT. Inevitably, this drive towards theorizing from a Chinese perspective also creates a backlash among not only Western but also other Chinese scholars as they question the ‘nationalistic’ if not ‘hegemonic’ discourse of the scholarship. Drawing on the sociology of scientific knowledge framework, this article examines the linkages between the vibrant dynamics of the Chinese theoretical debates and the actual practices of Chinese scholars in realizing their claims. It suggests that this investigation can serve as a springboard into a better appreciation of the theory–practice and power–knowledge relationships in the context of Chinese IR

Edge Assignment and Data Valuation in Federated Learning

Federated Learning (FL) is a recent Machine Learning method for training with private data separately stored in local machines without gathering them into one place for central learning. It was born to address the following challenges when applying Machine Learning in practice: (1) Communication cost: Most real-world data that can be useful for training are locally collected; to bring them all to one place for central learning can be expensive, especially in real-time learning applications when time is of the essence, for example, predicting the next word when texting on a smartphone; and (2) Privacy protection: Many applications must protect data privacy, such as those in the healthcare field; the private data can only be seen by its local owner and as such the learning may only use a content-hiding representation of this data, which is much less informative. To fulfill FL’s promise, this dissertation addresses three important problems regarding the need for good training data, system scalability, and uncertainty robustness: 1. The effectiveness of FL depends critically on the quality of the local training data. We should not only incentivize participants who have good training data but also minimize the effect of bad training data on the overall learning procedure. The first problem of my research is to determine a score to value a participant’s contribution. My approach is to compute such a score based on Shapley Value (SV), a concept of cooperative game theory for profit allocation in a coalition game. In this direction, the main challenge is due to the exponential time complexity of the SV computation, which is further complicated by the iterative manner of the FL learning algorithm. I propose a fast and effective valuation method that overcomes this challenge. 2. On scalability, FL depends on a central server for repeated aggregation of local training models, which is prone to become a performance bottleneck. A reasonable approach is to combine FL with Edge Computing: introduce a layer of edge servers to each serve as a regional aggregator to offload the main server. The scalability is thus improved, however at the cost of learning accuracy. The second problem of my research is to optimize this tradeoff. This dissertation shows that this cost can be alleviated with a proper choice of edge server assignment: which edge servers should aggregate the training models from which local machines. Specifically, I propose an assignment solution that is especially useful for the case of non-IID training data which is well-known to hinder today’s FL performance. 3. FL participants may decide on their own what devices they run on, their computing capabilities, and how often they communicate the training model with the aggregation server. The workloads incurred by them are therefore time-varying, and unpredictably. The server capacities are finite and can vary too. The third problem of my research is to compute an edge server assignment that is robust to such dynamics and uncertainties. I propose a stochastic approach to solving this problem

Vietnam's emergence as a middle power in Asia: unfolding the power-knowledge nexus

With Asia's current geopolitical rise, International Relations communities in China, Japan and India have attempted to develop indigenous theoretical approaches that attract heated scholarly debates. Little attention, however, is paid to the state of affairs in weaker states. As power today is widely diffused to various actors in the international system beyond the big powers, the power-knowledge literature should be broadened to respond to the growing multiplexity of world order and the call for diversity of International Relations knowledge. As a case in point, this study examines how Vietnam's emerging middle power status has shaped policy and scholarly discourses in the country regarding the trajectory of Vietnam's foreign policy and the burgeoning interest of its International Relations community in a Vietnamese School of Diplomacy. Such scholarly endeavour will help shed light on the heightened agency of middle powers in world politics and the prospects for a Southeast Asian contribution to global International Relations heritage

Secular trend, seasonality and effects of a community-based intervention on neonatal mortality: follow-up of a cluster-randomised trial in Quang Ninh province, Vietnam.

BACKGROUND: Little is know about whether the effects of community engagement interventions for child survival in low-income and middle-income settings are sustained. Seasonal variation and secular trend may blur the data. Neonatal mortality was reduced in a cluster-randomised trial in Vietnam where laywomen facilitated groups composed of local stakeholders employing a problem-solving approach for 3 years. In this analysis, we aim at disentangling the secular trend, the seasonal variation and the effect of the intervention on neonatal mortality during and after the trial. METHODS: In Quang Ninh province, 44 communes were allocated to intervention and 46 to control. Births and neonatal deaths were assessed in a baseline survey in 2005, monitored during the trial in 2008-2011 and followed up by a survey in 2014. Time series analyses were performed on monthly neonatal mortality data. RESULTS: There were 30 187 live births and 480 neonatal deaths. The intervention reduced the neonatal mortality from 19.1 to 11.6 per 1000 live births. The reduction was sustained 3 years after the trial. The control areas reached a similar level at the time of follow-up. Time series decomposition analysis revealed a downward trend in the intervention areas during the trial that was not found in the control areas. Neonatal mortality peaked in the hot and wet summers. CONCLUSIONS: A community engagement intervention resulted in a lower neonatal mortality rate that was sustained but not further reduced after the end of the trial. When decomposing time series of neonatal mortality, a clear downward trend was demonstrated in intervention but not in control areas. TRIAL REGISTRATION NUMBER: ISRCTN44599712, Post-results

Anthropogenic impacts on the water chemistry of a transboundary river system in Southeast Asia

The Red River originating from Yunnan province, China is the second largest river in Vietnam in terms of length and discharge. Combination of water chemistry monitoring data of 4 years (2018–2022) from different sub-basins of the Red River (the Da, Lo, Thao, Tra Ly, and Day) with historical datasets indicates a decline in pH from 8.1 in 2000 to 7.7 in 2021, greater CO2 concentrations and a shift from waters naturally dominated by carbonate weathering to waters dominated by evaporite weathering. Such changes were most apparent in the delta area where heavy human activities have increased influxes of most dissolved chemicals, except SiO2. Evaporite weathering is particularly enhanced by mining and deforestation occurring in upstream regions of both China and Vietnam. Pyrite oxidation, alongside silicate weathering, is enhanced along the Red River Fault Zone but reduced in tributaries with a higher proportion of hydropower reservoirs. Longer water residence times in these large reservoirs (total volume > 2.7x1010 m3) located in the Da and Lo sub-basins have also increased primary productivity, leading to higher evasion/uptake of CO2 and SiO2, lower total dissolved solids (TDS), and higher pH. The total physical and chemical denudation rates of upstream mountain tributaries ranged between 0.107 ± 0.108 and 0.139 ± 0.137 mm yr−1, mainly due to reservoir implementation and instream aquatic biogeochemistry changes. Our findings demonstrate that anthropogenic activities are profound factors impacting the water chemistry of the Red River system

Mapping for engagement: setting up a community based participatory research project to reach underserved communities at risk for Hepatitis C in Ho Chi Minh City, Vietnam

Background: Approximately 1. 07 million people in Vietnam are infected with hepatitis C virus (HCV). To address this epidemic, the South East Asian Research Collaborative in Hepatitis (SEARCH) launched a 600-patient cohort study and two clinical trials, both investigating shortened treatment strategies for chronic HCV infection with direct-acting antiviral drugs. We conducted ethnographic research with a subset of trial participants and found that the majority were aware of HCV infection and its implications and were motivated to seek treatment. However, people who inject drugs (PWID), and other groups at risk for HCV were under-represented, although injecting drug use is associated with high rates of HCV. Material and Methods: We designed a community-based participatory research (CBPR) study to engage in dialogues surrounding HCV and other community-prioritized health issues with underserved groups at risk for HCV in Ho Chi Minh City. The project consists of three phases: situation analysis, CBPR implementation, and dissemination. In this paper, we describe the results of the first phase (i.e., the situation analysis) in which we conducted desk research and organized stakeholder mapping meetings with representatives from local non-government and community-based organizations where we used participatory research methods to identify and analyze key stakeholders working with underserved populations. Results: Twenty six institutions or groups working with the key underserved populations were identified. Insights about the challenges and dynamics of underserved communities were also gathered. Two working groups made up of representatives from the NGO and CBO level were formed. Discussion: Using the information provided by local key stakeholders to shape the project has helped us to build solid relationships, give the groups a sense of ownership from the early stages, and made the project more context specific. These steps are not only important preliminary steps for participatory studies but also for other research that takes place within the communities

Establishing and validating noninvasive prenatal testing procedure for fetal aneuploidies in Vietnam

Noninvasive prenatal testing (NIPT) for fetal aneuploidies has been widely adopted in developed countries. Despite the sharp decrease in the cost of massively parallel sequencing, the technical know-how and skilled personnel are still one of the major limiting factors for applying this technology to NIPT in low-income settings. Here, we present the establishment and validation of our NIPT procedure called triSure for detection of fetal aneuploidies.We established the triSure algorithm based on the difference in proportion of fetal and maternal fragments from the target chromosome to all chromosomes. Our algorithm was validated using a published data set and an in-house data set obtained from high-risk pregnant women in Vietnam who have undergone amniotic testing. Several other aneuploidy calling methods were also applied to the same data set to benchmark triSure performance.The triSure algorithm showed similar accuracy to size-based method when comparing them using published data set. Using our in-house data set from 130 consecutive samples, we showed that triSure correctly identified the most samples (overall sensitivity and specificity of 0.983 and 0.986, respectively) compared to other methods tested including count-based, sized-based, RAPIDR and NIPTeR.We have demonstrated that our triSure NIPT procedure can be applied to pregnant women in low-income settings such as Vietnam, providing low-risk screening option to reduce the need for invasive diagnostic tests

Associations of Underlying Health Conditions With Anxiety and Depression Among Outpatients: Modification Effects of Suspected COVID-19 Symptoms, Health-Related and Preventive Behaviors

Objectives: We explored the association of underlying health conditions (UHC) with depression and anxiety, and examined the modification effects of suspected COVID-19 symptoms (S-COVID-19-S), health-related behaviors (HB), and preventive behaviors (PB).Methods: A cross-sectional study was conducted on 8,291 outpatients aged 18–85 years, in 18 hospitals and health centers across Vietnam from 14th February to May 31, 2020. We collected the data regarding participant's characteristics, UHC, HB, PB, depression, and anxiety.Results: People with UHC had higher odds of depression (OR = 2.11; p < 0.001) and anxiety (OR = 2.86; p < 0.001) than those without UHC. The odds of depression and anxiety were significantly higher for those with UHC and S-COVID-19-S (p < 0.001); and were significantly lower for those had UHC and interacted with “unchanged/more” physical activity (p < 0.001), or “unchanged/more” drinking (p < 0.001 for only anxiety), or “unchanged/healthier” eating (p < 0.001), and high PB score (p < 0.001), as compared to those without UHC and without S-COVID-19-S, “never/stopped/less” physical activity, drinking, “less healthy” eating, and low PB score, respectively.Conclusion: S-COVID-19-S worsen psychological health in patients with UHC. Physical activity, drinking, healthier eating, and high PB score were protective factors