Первое сообщение об Auerbachia chakravartyi (Myxosporea: Bilvavulida) из желчного пузыря Megalaspis cordyla во Вьетнаме

В 2017 г. в Тонкинском заливе было исследовано 20 экз. Megalaspis cordyla. Морфологическими и молекулярно-биологическими методами было установлено наличие в желчном пузыре 7 из 20 рыб (35 %) спор Auerbachia chakravartyi Narasimhamurti, Kalavati, Anuradha, Padma, 1990. Это первая находка представителей рода Auerbachia в морских рыбах Вьетнама

Enhancing Accuracy-Privacy Trade-off in Differentially Private Split Learning

Split learning (SL) aims to protect user data privacy by distributing deep models between client-server and keeping private data locally. Only processed or `smashed' data can be transmitted from the clients to the server during the SL process. However, recently proposed model inversion attacks can recover the original data from the smashed data. In order to enhance privacy protection against such attacks, a strategy is to adopt differential privacy (DP), which involves safeguarding the smashed data at the expense of some accuracy loss. This paper presents the first investigation into the impact on accuracy when training multiple clients in SL with various privacy requirements. Subsequently, we propose an approach that reviews the DP noise distributions of other clients during client training to address the identified accuracy degradation. We also examine the application of DP to the local model of SL to gain insights into the trade-off between accuracy and privacy. Specifically, findings reveal that introducing noise in the later local layers offers the most favorable balance between accuracy and privacy. Drawing from our insights in the shallower layers, we propose an approach to reduce the size of smashed data to minimize data leakage while maintaining higher accuracy, optimizing the accuracy-privacy trade-off. Additionally, a smaller size of smashed data reduces communication overhead on the client side, mitigating one of the notable drawbacks of SL. Experiments with popular datasets demonstrate that our proposed approaches provide an optimal trade-off for incorporating DP into SL, ultimately enhancing training accuracy for multi-client SL with varying privacy requirements

Epidemiology and Clinical Features of Dengue Hemorrhagic Fever in Ho Chi Minh City and the Centre for Tropical Diseases; Viet Nam

Dengue haemorrhagic fever (DHF) is one of the major infectious diseases in Viet Nam. In the south of Viet Nam, DHF occurs all the year round. The number of DHF cases has been recorded as the greatest one among many countries in the world (1983: 77,087 cases and 1,301 deaths; 1987: 83,905 cases and 904 deaths). The DHF morbidity rate in children in south of Viet Nam was high (380.73/100,000 population in the 1983 epidemic and 378.37/100,000 population in the 1987 epidemic). The mortality rate in Ho Chi Minh city (1981-1990) is 1.05 (/100,000 population) and the mean mortality rate (/total of cases) is 0.55%. The majority of confirmed cases were children of 5-9 years old. In the DHF with shock, hepatomegaly relates to the severe grades. In the traetment of DHF without shock, patients were given fluid to drink on the first day to prevent shock

ANALYSIS OF THE POPULARITY OF VOCABULARY USED WHEN PERFORMING SPEAKING ACTIVITIES IN THE CLASS OF FIRST-YEAR ENGLISH LANGUAGE STUDENTS IN THE DIRECTION OF DISCOURSE ANALYSIS

Vocabulary learning is extremely important when learning a foreign language. Fluency in a language depends on vocabulary and its use in specific situations. Speaking well is using vocabulary flexibly and speaking fluently. Researching the popularity of vocabulary is analyzing the prevalence of vocabulary used by linguistics students in communication from discourse analysis. This is a topic the research team is working on. This project will help the researchers learn about common vocabulary that students often use to communicate outside or in the classroom. Thereby understanding whether the vocabulary that students use is diverse, rich, and for the right purpose or not. This study will help students have a more comprehensive view of the ways to use words in communication. In addition, it also helps students improve their communication vocabulary, helps in exams and can be useful for later work. In this study, the research team will investigate the students' ability to use spoken vocabulary, i.e., frequency and extent of vocabulary usage.  Article visualizations

Performance Evaluation of Pre-foamed Ultra-lightweight Composites Incorporating Various Proportions of Slag

This research examines the feasibility of using a mixture of cement, fly ash, ground granulated blast-furnace slag, and river sand to manufacture pre-foamed ultra-lightweight composite (PULC). Four PULC specimens were prepared with the substitution of cement by slag at 0, 10, 20, and 30 % by weight. The engineering properties of PULC samples were evaluated through the tests of compressive strength, dry density, water absorption, drying shrinkage, and thermal conductivity. Besides, numerical simulation of heat transfer through the PULC brick wall and the microstructure observation were performed. The performance of PULC mixtures incorporating slag showed higher effectiveness than merely used cement. The substitution of 20 % cement by slag resulted in the highest compressive strength as well as the lowest value of water absorption of the PULC samples. Also, the efficiency of the thermal conductivity was in inverse proportion with the density of PULC specimens and it was right for water absorption and drying shrinkage. Moreover, numerical simulations showed that the temperature distribution values in the wall made by PULC material were smaller than in the wall made by the normal clay brick in the same position. Besides, the microstructure analysis revealed that the existence of slag generated a more dense structure of PULC samples with the addition of calcium-silicate-hydrate (C-S-H) gel, especially for a mix containing 20 % slag. Thus, the results of this study further demonstrated that a 20 % slag was the optimal content for the good engineering properties of the PULC samples

The experience of using e-commerce platforms affects the online purchase intention of customers in the FMCG (Fast moving consumer goods) sector in Hanoi city

In recent times, the Vietnamese e-commerce market is in a period of strong development, in addition, to the sharp increase in people’s demands to join e-commerce platforms after the epidemic. The research group started with an overview study, then research hypotheses and models were proposed. After conducting preliminary qualitative and quantitative research to adjust the appropriate scales, the research group created a questionnaire and collected data in online forms with a sample size of 350. Next, the data was entered into the software for SEM analysis. The results of the study indicate that the quality of the e-commerce platform has an indirect impact on the purchase intention through the positive impact on the trust and the negative impact on the perceived risk. Attitudes towards information, trust, perceived risk, and perceived usefulness have direct influences on purchase intention. Attitude towards information, trust, and perceived usefulness have positive effects on purchase intention, while perceived risk harms purchase intention. In addition, purchase intention is relatively strongly influenced by trust and perceived usefulness. Perceived risk and attitude towards information have little influence on purchase intention. Finally, the research team proposes some solutions for businesses to increase the purchase intention of consumers through e-commerce platforms. &nbsp

Primary Evaluation on Growth Performances of Stress Negative Piétrain Pigs Raised in Hai Phong Province of Vietnam

peer reviewedThe present study was carried out on 19 stress negative Piétrain pigs (Pietrain ReHal), consisting of 13 gilts and 6 young boars imported from Belgium, raised in the livestock farm of Dong Hiep (Hai Phong) in order to evaluate growth performances and their adaptability in the North of Vietnam. Results showed that the average body weight of the whole herd at 2, 4, 5.5, and 8.5 months old was 19.05, 51.05, 85.82, and 119.47 kg, respectively. During the growing periods, except the first stage, the male grew faster than the female and the pigs of the CT genotype grew faster than those of CC genotype although the difference was not significant (P>0.05). The average daily gain (ADG) was 528.56 grams for the whole herd. The ADG was higher for the male (546.48 grams) than for the female (520.29 grams), and its was higher for the CT than the CC, but the difference was not statistically significant (P>0.05). The feed conversion ratio (FCR) was 2.69 kg. The estimated lean percentage at 8.5 months old was 64.08%. The results indicate that Piétrain stress negative pigs could develop well on the farm conditions in Hai Phong, Vietnam

A Machine Learning-based Approach to Vietnamese Handwritten Medical Record Recognition

Handwritten text recognition has been an active research topic within computer vision division. Existing deep-learning solutions are practical; however, recognizing Vietnamese handwriting has shown to be a challenge with the presence of extra six distinctive tonal symbols and extra vowels. Vietnam is a developing country with a population of approximately 100 million, but has only focused on digitalization transforms in recent years, and so Vietnam has a significant number of physical documents, that need to be digitized. This digitalization transform is urgent when considering the public health sector, in which medical records are mostly still in hand-written form and still are growing rapidly in number. Digitization would not only help current public health management but also allow preparation and management in future public health emergencies. Enabling the digitalization of old physical records will allow efficient and precise care, especially in emergency units. We proposed a solution to Vietnamese text recognition that is combined into an end-to-end document-digitalization system. We do so by performing segmentation to word-level and then leveraging an artificial neural network consisting of both convolutional neural network (CNN) and a long short-term memory recurrent neural network (LSTM) to propagate the sequence information. From the experiment with the records written by 12 doctors, we have obtained encouraging results of 6.47% and 19.14% of CER and WER respectively

Using Solvent Vapor Annealing for the Enhancement of the Stability and Efficiency of Monolithic Hole-conductor-free Perovskite Solar Cells

In the last few years, perovskite solar cells have attracted enormous interest in the photovoltaic community due to their low cost of materials, tunable band gap, excellent photovoltaic properties and easy process ability at low temperature. In this work, we fabricated hole-conductor-free carbon-based perovskite solar cells with the monolithic structure: glass/FTO/bl-TiO$_{2}$/(mp-TiO$_{2}$/mp-ZrO$_{2}$/mp-carbon) perovskite. The mixed 2D/3D perovskite precursor solution composed of PbI$_{2}$, methylammonium iodide (MAI), and 5-ammoniumvaleric acid iodide (5-AVAI) was drop-casted through triple mesoporous TiO$_{2}$/ZrO$_{2}$/carbon electrode films. We found that the isopropyl alcohol (IPA) solvent vapor annealing strongly influenced on the growth of mixed 2D/3D perovskite on triple mesoscopic layers. It resulted in the better pore filling, better crystalline quality of perovskite layer, thus the improved stability and efficiency of perovskite solar cell was attributed to lower defect concentration and reduced recombination