Reactivity of ethylene oxide in contact with contaminants

Ethylene oxide (EO) is a very versatile compound with considerable energy in its ring structure. Its reactions proceed mainly via ring opening and are highly exothermic. Under some conditions, it is known to undergo a variety of reactions, such as isomerization, polymerization, hydrolysis, combustion and decomposition Due to its very reactive characteristic and widely industrial applications, EO has been involved in a number of serious incidents such as Doe Run 1962, Freeport 1974, Deer Park 1988 and Union Carbide Corporation’s Seadrift 1991. The impacts can be severe in terms of death and injury to people, damage to physical property and effects on the environment. For instance, the Union Carbide incident in 1991 caused one fatality and extensive damage to the plant with the property damage of up to 80 million dollars. Contamination has a considerable impact on EO reactivity by accelerating substantially its decomposition and playing a key role on EO incidents. In this work, the reactivity of EO with contaminants such as KOH, NaOH, NH4OH, and EDTA is evaluated. Useful information that is critical to the design and operation of safer chemical plant processes was generated such as safe storage temperatures (onset temperature), maximum temperature, maximum pressure, temperature vs. time, heat and pressure generation rates as a function of temperature and time to maximum rate using adiabatic calorimetry. A special arrangement for the filling-up of the cell was constructed due to the gaseous nature and toxicity of EO. A comparison of their thermal behavior is also presented since several contaminants are studied

Safety-oriented Resilience Evaluation in Chemical Processes

In the area of process safety, many efforts have focused on studying methods to prevent the transition of the state of the system from a normal state to an upset and/or catastrophic state, but many unexpected changes are unavoidable, and even under good risk management incidents still occur. The aim of this work is to propose the principles and factors that contribute to the resilience of the chemical process, and to develop a systematic approach to evaluate the resilience of chemical processes in design aspects. Based on the analysis of transition of the system states, the top-level factors that contribute to Resilience were developed, including Design, Detection Potential, Emergency Response Planning, Human, and Safety Management. The evaluation framework to identify the Resilience Design Index is developed by means of the multifactor model approach. The research was then focused on developing complete subfactors of the top-level Design factor. The sub-factors include Inherent Safety, Flexibility, and Controllability. The proposed framework to calculate the Inherent Safety index takes into account all the aspects of process safety design via many sub-indices. Indices of Flexibility and Controllability sub-factors were developed from implementations of well-known methodologies in process design and process control, respectively. Then, the top-level Design index was evaluated by combining the indices of the sub-factors with weight factors, which were derived from Analytical Hierarchical Process approach. A case study to compare the resilience levels of two ethylene production designs demonstrated the proposed approaches and gave insights on process resilience of the designs

Simple thermal-electrical model of photovoltaic panels with cooler-integrated sun tracker

This paper presents a simple thermal-electrical model of a photovoltaic panel with a cooler-integrated sun tracker. Based on the model and obtained weather data, we analyzed the improved overall efficiency in a year as well as the performance in each typical weather case for photovoltaic panels with fixed-tilt systems with a tilt angle equal to latitude, fixed-tilt systems with cooler, a single-axis sun tracker, and a cooler-integrated single-axis sun tracker. The results show that on a sunny summer day with few clouds, the performance of the photovoltaic panels with the proposed system improved and reached 32.76% compared with the fixed-tilt systems. On a sunny day with clouds in the wet, rainy season, because of the low air temperature and the high wind speed, the photovoltaic panel temperature was lower than the cooler’s initial set temperature; the performance of the photovoltaic panel with the proposed system improved by 12.55% compared with the fixed-tilt system. Simulation results show that, over one year, the overall efficiency of the proposed system markedly improved by 16.35, 13.03, and 3.68% compared with the photovoltaic panel with the fixed-tilt system, the cooler, and the single-axis sun tracker, respectively. The simulation results can serve as a premise for future experimental models

Information searching behaviors among Vietnamese students during first wave of the COVID-19 pandemic

This study aims to describe the COVID-19 related information searching behaviors and the relationship between those behaviors and the satisfaction with the COVID-19 related information searched on the Internet among university students during first wave of the COVID-19 pandemic in Vietnam

Deep Transfer Learning: A Novel Collaborative Learning Model for Cyberattack Detection Systems in IoT Networks

Federated Learning (FL) has recently become an effective approach for cyberattack detection systems, especially in Internet-of-Things (IoT) networks. By distributing the learning process across IoT gateways, FL can improve learning efficiency, reduce communication overheads and enhance privacy for cyberattack detection systems. Challenges in implementation of FL in such systems include unavailability of labeled data and dissimilarity of data features in different IoT networks. In this paper, we propose a novel collaborative learning framework that leverages Transfer Learning (TL) to overcome these challenges. Particularly, we develop a novel collaborative learning approach that enables a target network with unlabeled data to effectively and quickly learn knowledge from a source network that possesses abundant labeled data. It is important that the state-of-the-art studies require the participated datasets of networks to have the same features, thus limiting the efficiency, flexibility as well as scalability of intrusion detection systems. However, our proposed framework can address these problems by exchanging the learning knowledge among various deep learning models, even when their datasets have different features. Extensive experiments on recent real-world cybersecurity datasets show that the proposed framework can improve more than 40% as compared to the state-of-the-art deep learning based approaches.Comment: 12 page

Isolation of dengue serotype 3 virus from the cerebrospinal fluid of an encephalitis patient in Hai Phong, Vietnam in 2013

Dengue encephalitis (DE) is characterized as unusual presentation of dengue infection. Despite the reports that DE accounts for only 1-5% of dengue cases, this disease tends to be increasingly reported to threaten global human health throughout dengue endemic areas particularly in Southeast Asia. The molecular information of clinically characterized, neurotropic dengue virus (DENV) in human beings is extremely scarce despite it playing an important role in deciphering the pathogenesis of dengue-related neurological cases. Here we report a case of DE caused by DENV3 genotype III in a male patient with atypical symptoms of DENV infection in Hai Phong, Vietnam in 2013. The virus isolated from the cerebrospinal fluid of this case-patient was closely related to DENV3 genotype III strains isolated from serum of two other patients, who manifested classical dengue in the same year and residing in the same area as the case-patient. It is noteworthy to mention that in 2013, DENV3 genotype III was detected for the first time in Vietnam

The Efficacy of a Two-Fold Increase of H1-Antihistamine in the Treatment of Chronic Urticaria - the Vietnamese Experience

BACKGROUND: Chronic urticaria, a mast cell-driven condition, is common, debilitating and hard to treat. H1-antihistamines are the first line treatment of chronic urticaria, but often patients do not get satisfactory relief with the recommended dose. European guidelines recommend increased antihistamine doses up to four-fold. AIM: We conducted this study to evaluate the efficacy of increased H1-antihistamine doses up to two-fold in Vietnamese chronic urticaria patients. METHODS: One hundred and two patients with chronic urticaria were recruited for treatment with levocetirizine (n = 52) or fexofenadine (n = 50). Treatment started at the conventional daily dose of 5 mg levocetirizine or 180 mg fexofenadine for 2 weeks and then increased to 10 mg levocetirizine or 360 mg fexofenadine for 2 weeks if patients did not have an improvement in symptoms. At week 0, week 2 and week 4 wheal, pruritus, size of the wheal, total symptom scores, and associated side-effects were assessed. RESULTS: With the conventional dose, the total symptom scores after week 2 decreased significantly in both groups compared to baseline figures, i.e. 7.4 vs 2.3 for levocetirizine group and 8.0 vs 2.6 for fexofenadine group (p < 0.05). However, there were still 26 patients in each group who did not have improvements. Of these 26 patients, after having a two-fold increase of the conventional dose, 11.5% and 38.5% became symptom-free at week 4 in levocetirizine group and fexofenadine group, respectively. At week 4 in both groups, the total symptom scores had significantly decreased when compared with those at week 2 (2.8 ± 1.5 versus 4.7 ± 1.6 in levocetirizine group; 2.1 ± 1.9 versus 5.1 ± 1.4 in fexofenadine group). In both groups, there was no difference in the rate of negative side effects between the conventional dose and the double dose. CONCLUSION: This study showed that increasing the dosages of levocetirizine and fexofenadine by two-fold improved chronic urticaria symptoms without increasing the rate of negative side effects

Evaluation of awake prone positioning effectiveness in moderate to severe COVID-19

Evidence mainly from high income countries suggests that lying in the prone position may be beneficial in patients with COVID-19 even if they are not receiving invasive ventilation. Studies indicate that increased duration of prone position may be associated with improved outcomes, but achieving this requires additional staff time and resources. Our study aims to support prolonged (≥ 8hours/day) awake prone positioning in patients with moderate to severe COVID-19 disease in Vietnam. We use a specialist team to support prone positioning of patients and wearable devices to assist monitoring vital signs and prone position and an electronic data registry to capture routine clinical data

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions