The local uniform convergence of positive harmonic function sequence

The Harnack distance on space  and its conformal invariance were constructed and studied by Herron. In this paper, we obtain the Harnack distance on domains  in . Then, we use this concept to investigate some properties of the positive harmonic function class. These results are obtained in the complex plane, so it is advantageous to take some tools of the complex analysis. The main result of this paper is the property of the local uniform convergence of the positive harmonic sequences on a domain in the complex plane.The Harnack distance on space  and its conformal invariance were constructed and studied by Herron. In this paper, we obtain the Harnack distance on domains  in . Then, we use this concept to investigate some properties of the positive harmonic function class. These results are obtained in the complex plane, so it is advantageous to take some tools of the complex analysis. The main result of this paper is the property of the local uniform convergence of the positive harmonic sequences on a domain in the complex plane

Uncertainty Quantification in the Directed Energy Deposition Process Using Deep Learning-Based Probabilistic Approach

peer reviewedThis study quantifies the effects of uncertainty raised from process parameters, material properties, and boundary conditions in the directed energy deposition (DED) process of M4 High-Speed Steel using deep learning (DL)-based probabilistic approach. A DL-based surrogate model is first constructed using the data obtained from a finite element (FE) model, which was validated against experiment. Then, sources of uncertainty are characterized by the probabilistic method and are propagated by the Monte-Carlo (MC) method. Lastly, the sensitivity analysis (SA) using the variance-based method is performed to identify the parameters inducing the most uncertainty to the melting pool depth. Using the DL-based surrogate model instead of solely FE model significantly reduces the computational time in the MC simulation. The results indicate that all sources of uncertainty contribute to a substantial variation on the final printed product quality. Moreover, we find that the laser power, the convection, the scanning speed, and the thermal conductivity contribute the most uncertainties on the melting pool depth based on the SA results. These findings can be used as insights for the process parameter optimization of the DED process.EDPOM

Policy Response, Social Media and Science Journalism for the Sustainability of the Public Health System Amid the COVID-19 Outbreak: The Vietnam Lessons

Vietnam, with a geographical proximity and a high volume of trade with China, was the first country to record an outbreak of the new Coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 or SARS-CoV-2. While the country was expected to have a high risk of transmission, as of April 4, 2020—in comparison to attempts to contain the disease around the world—responses from Vietnam are being seen as prompt and effective in protecting the interests of its citizens, with 239 confirmed cases and no fatalities. This study analyzes the situation in terms of Vietnam’s policy response, social media and science journalism. A self-made web crawl engine was used to scan and collect official media news related to COVID-19 between the beginning of January and April 4, yielding a comprehensive dataset of 14,952 news items. The findings shed light on how Vietnam—despite being under-resourced—has demonstrated political readiness to combat the emerging pandemic since the earliest days. Timely communication on any developments of the outbreak from the government and the media, combined with up-to-date research on the new virus by the Vietnamese science community, have altogether provided reliable sources of information. By emphasizing the need for immediate and genuine cooperation between government, civil society and private individuals, the case study offers valuable lessons for other nations concerning not only the concurrent fight against the COVID-19 pandemic but also the overall responses to a public health crisis

Dexamethasone and long-term outcome of tuberculous meningitis in Vietnamese adults and adolescents.

BACKGROUND: Dexamethasone has been shown to reduce mortality in patients with tuberculous meningitis but the long-term outcome of the disease is unknown. METHODS: Vietnamese adults and adolescents with tuberculous meningitis recruited to a randomised, double-blind, placebo-controlled trial of adjunctive dexamethasone were followed-up at five years, to determine the effect of dexamethasone on long-term survival and neurological disability. RESULTS: 545 patients were randomised to receive either dexamethasone (274 patients) or placebo (271 patients). 50 patients (9.2%) were lost to follow-up at five years. In all patients two-year survival, probabilities tended to be higher in the dexamethasone arm (0.63 versus 0.55; p = 0.07) but five-year survival rates were similar (0.54 versus 0.51, p = 0.51) in both groups. In patients with grade 1 TBM, but not with grade 2 or grade 3 TBM, the benefit of dexamethasone treatment tended to persist over time (five-year survival probabilities 0.69 versus 0.55, p = 0.07) but there was no conclusive evidence of treatment effect heterogeneity by TBM grade (p = 0.36). The dexamethasone group had a similar proportion of severely disabled patients among survivors at five years as the placebo group (17/128, 13.2% vs. 17/116, 14.7%) and there was no significant association between dexamethasone treatment and disability status at five years (p = 0.32). CONCLUSIONS: Adjunctive dexamethasone appears to improve the probability of survival in patients with TBM, until at least two years of follow-up. We could not demonstrate a five-year survival benefit of dexamethasone treatment which may be confined to patients with grade 1 TBM. TRIAL REGISTRATION: ClinicalTrials.gov NCT01317654

A study on multi-criteria decision-making in powder mixed electric discharge machining cylindrical shaped parts

In life as well as in engineering, many times, it is necessary to choose the best option among many different options. That will be more difficult when the criteria given for the selection contradict each other. For example, when external cylindrical grinding, the minimum surface roughness requirement necessitates a small depth of cut and feed rate. The material removal rate will be reduced in this case, and this requirement will conflict with the maximum material removal rate requirement. To solve the above problem, a very useful tool is multi-criteria decision-making (MCDM). In this paper, for the first time, MCDM results for powder mixed discharge machining (PMEDM) cylindrical parts of SKD11 tool steel with copper electrodes have been presented. In this work, eighteen experiments with the L18 (16×53) design using the Taguchi method were conducted. Six main input process parameters include the powder concentration, the pulse current, the servo voltage, the pulse on time, and the pulse off time. To select an alternative that simultaneously ensures two criteria including minimum surface roughness (RS) and maximum material removal speed (MRS), four different MCDM methods including MAIRCA (Multi-Attributive Ideal-Real Comparative Analysis), MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution), TOPSIS (Technique for order of preference by similarity to ideal solution), and EAMR (Area-based Method of Ranking) and two methods of criteria weight calculation including MEREC (Method based on the Removal Effects of Criteria) and Entropy methods were selected. The results of MCDM when PMEDM SKD11 tool steel cylindrical parts with two methods for weight determination and four methods for solving MCDM problem were evaluated. In addition, the best alternative to ensure simultaneous minimum RS and maximum MRS was proposed

How Digital Natives Learn and Thrive in the Digital Age: Evidence from an Emerging Economy

As a generation of ‘digital natives,’ secondary students who were born from 2002 to 2010 have various approaches to acquiring digital knowledge. Digital literacy and resilience are crucial for them to navigate the digital world as much as the real world; however, these remain under-researched subjects, especially in developing countries. In Vietnam, the education system has put considerable effort into teaching students these skills to promote quality education as part of the United Nations-defined Sustainable Development Goal 4 (SDG4). This issue has proven especially salient amid the COVID−19 pandemic lockdowns, which had obliged most schools to switch to online forms of teaching. This study, which utilizes a dataset of 1061 Vietnamese students taken from the United Nations Educational, Scientific, and Cultural Organization (UNESCO)’s “Digital Kids Asia Pacific (DKAP)” project, employs Bayesian statistics to explore the relationship between the students’ background and their digital abilities. Results show that economic status and parents’ level of education are positively correlated with digital literacy. Students from urban schools have only a slightly higher level of digital literacy than their rural counterparts, suggesting that school location may not be a defining explanatory element in the variation of digital literacy and resilience among Vietnamese students. Students’ digital literacy and, especially resilience, also have associations with their gender. Moreover, as students are digitally literate, they are more likely to be digitally resilient. Following SDG4, i.e., Quality Education, it is advisable for schools, and especially parents, to seriously invest in creating a safe, educational environment to enhance digital literacy among students

Fast and accurate prediction of temperature evolutions in additive manufacturing process using deep learning

Typical computer-based parameter optimization and uncertainty quantification of the additive manufacturing process usually requires significant computational cost for performing high-fidelity heat transfer finite element (FE) models with different process settings. This work develops a simple surrogate model using a feedforward neural network (FFNN) for a fast and accurate prediction of the temperature evolutions and the melting pool sizes in a metal bulk sample (3D horizontal layers) manufactured by the DED process. Our surrogate model is trained using high-fidelity data obtained from the FE model, which was validated by experiments. The temperature evolutions and the melting pool sizes predicted by the FFNN model exhibit accuracy of 99% and 98%, respectively, compared with the FE model for unseen process settings in the studied range. Moreover, to evaluate the importance of the input features and explain the achieved accuracy of the FFNN model, a sensitivity analysis (SA) is carried out using the SHapley Additive exPlanation (SHAP) method. The SA shows that the most critical enriched features impacting the predictive capability of the FFNN model are the vertical distance from the laser head position to the material point and the laser head position.VINIF.2020.DA15 EDPOMP projec

INTEGRATED ASSESSMENT OF RISK LEVEL CAUSED BY HAZARDS IN THE COASTAL ZONE OF VIETNAM (CASES STUDY : CAM RANH-PHAN RI COASTAL ZONE)

Joint Research on Environmental Science and Technology for the Eart

HIV and Tuberculosis in Ho Chi Minh City, Vietnam, 1997–2002

An emerging HIV epidemic, concentrated in young, male, injection drug users, is responsible for increasing TB reporting rates in urban Vietnam

VẬT LIỆU TIO2/THAN HOẠT TÍNH TỪ TRO TRẤU VÀ KHẢ NĂNG HẤP PHỤ XANH METHYLENE

In the present work, TiO2/activated-carbon composite (TiO2/RHAC) was synthesized with an assembly method. Activated carbon was fabircated from rice husks. The water-soluble titanium complex was synthesized from anatase via the peroxide complex. The mixture of activated carbon and water-soluble TiO2 was calcined at 600 °C. The obtained samples were characterized by using XRD, SEM, EDX, and UV-Vis-DR. The results show that the obtained composites exhibit excellent adsorption toward methylene blue (MB). The equilibrium data fit the Langmuir isotherm model well. The maximum monolayer capacity calculated from the Langmuir model is 144.7 mg·g–1. The TiO2/RHAC could be self-cleaned after use by photocatalytic degradation. The adsorption capacity insignificantly decreases after three recycles of adsorption, and TiO2/RHAC is a promising adsorbent for removing dyes from the aqueous environment.Trong nghiên cứu này, TiO2/than hoạt tính từ tro trấu (TiO2/RHAC) đã được tổng hợp bằng phương pháp trộn lẫn than hoạt tính và phức titanium. Than hoạt tính được tổng hợp từ tro trấu và phức titanium hòa tan trong nước tổng hợp từ anatase bằng cách tạo phức peroxide. Hỗn hợp được nung trong môi trường thiếu oxy ở 600 °C. Vật liệu tổng hợp được phân tích bằng nhiễu xạ tia X, kính hiển vi điện tử quét và đẳng nhiệt hấp phụ/giải hấp phụ ni tơ. TiO2/RHAC có khả năng hấp phụ cao đối với xanh methylene. Số liệu đẳng nhiệt cân bằng tuân theo mô hình Langmuir và dung lượng hấp phụ cực đại tính theo mô hình này là 144,7 mg·g–1. Chất bị hấp phụ có thể được loại bỏ bằng cách chiếu sáng bằng đèn chiếu nhờ khả năng xúc tác quang hóa của nó. Sau ba lần tái sinh, dung lượng hấp phụ thay đổi không đáng kể. TiO2/RHAC có tiềm năng làm chất hấp phụ xử lý phẩm màu nói chung