Factors Affecting Credit Growth of Vietnamese Commercial Banks

This research analyzes the factors that affect the credit growthof the Vietnamese commercial banking system. This study usedata from the annual reports and financial statements of 16commercial banks listed on the HOSE, HNX, and UPCOMexchanges that have operated continuously from 2011 to 2020.Two linear regression models were employed with two dependentvariables: the credit growth rate and credit size. The findingsindicate that credit size in the previous period, the annualgrowth rate of capital mobilization, bank size, and return onassets (ROA) positively affect the credit growth of Vietnamesecommercial banks while liquidity ratio negatively affects them.Also, the bad debt ratio’s effect on credit growth is unclear. Hence,some suggestions and recommendations are given for commercialbanks to maintain stable, safe, and sustainable credit growth.JEL Classification: G21, E50, E5

Search for High Energy Skimming Neutrinos at a Surface Detector Array

In the present study we propose a new method for detectionof high energy cosmological muon neutrinos by transition radiations at amedium interface. The emerging electro-magnetic radiations induced by earth-skimming heavy charged leptons are able to trigger a few of aligned neighboringlocal water Cherenkov stations at  a surface detector array similar tothe Pierre Auger Observatory. The estimation applied tothe model of Gamma Ray Burst induced  neutrino fluxes and the spherical earth surface shows a competitive rate of muonneutrino events in the energy range below the GZK cut-off

GLUCOSIDES AND UREA DERIVATIVES FROM THE SEEDS OF SCAPHIUM MACROPODUM (MIQ.) BEUMÉE

Five known compounds {carbonylbis[imino(6-methyl-3,1-phenylenel)]}bis[carbamic acid] dimethyl ester (1), (1'R,3'S,5'R,8'S,2E,4E-dihydrophaseic acid) 3'-O-beta-D-glucopyranoside (2), 3-methylbutan-1-ol beta-D-glucopyranoside (3), astragalin (4) and daucosterol (5) were isolated from the methanol extract of the seeds of Scaphium macropodum (Miq.) Beumée. The structures of the isolated compounds were elucidated by the spectroscopic methods including NMR and MS, and also by comparison with the literature data. Compounds 1-3 were isolated from this plant for the first time

TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval

3D object retrieval is an important yet challenging task, which has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users. In order to overcome these limitations, this paper presents a novel SHREC challenge track focusing on text-based fine-grained retrieval of 3D animal models. Unlike previous SHREC challenge tracks, the proposed task is considerably more challenging, requiring participants to develop innovative approaches to tackle the problem of text-based retrieval. Despite the increased difficulty, we believe that this task has the potential to drive useful applications in practice and facilitate more intuitive interactions with 3D objects. Five groups participated in our competition, submitting a total of 114 runs. While the results obtained in our competition are satisfactory, we note that the challenges presented by this task are far from being fully solved. As such, we provide insights into potential areas for future research and improvements. We believe that we can help push the boundaries of 3D object retrieval and facilitate more user-friendly interactions via vision-language technologies.Comment: arXiv admin note: text overlap with arXiv:2304.0573

Mapping COVID-19-related research from Vietnam: a scoping review: Mapping COVID-19 related research in Vietnam

Introduction: The situation of COVID-19 pandemic is becoming more complex. The research institutes should focus on the most important challenge related to this outbreak at the national level. We aim to realize this scoping review to map publications on COVID-19 in Vietnam in order to guide research priorities and policies in the country. Methods: This study was conducted at the Thai Binh University of Medicine and Pharmacy, from May to August 2020, according to the guidance for conducting systematic scoping review. Results: A total of 72 studies met the inclusion criteria. The most frequent publications were original articles (27.8%), followed by letter to editor/correspondence (26.4%). According to the research priorities for COVID-19 set by the WHO, 41.7% studies focused on control and prevention of COVID-19, but none of studies on personal protective equipment or protocol for healthcare workers’ safety were conducted. 12.5% studies carried out a thorough investigation into epidemiology of the COVID-19 pandemic in Vietnam. Virology and genomics, natural history of the virus and its transmission in Vietnam were described by 18.1% papers. Only one study was conducted in terms of development for candidate therapeutics. Conclusion: We call for national investigation on treatment against SARS-CoV-2 and protocol for medical staff protection. The government and academic institutions should work in collaboration with international stakeholders, including the WHO, to combat together the COVID-19

Dynamic weighted ensemble for diarrhoea incidence predictions

Diarrhoea (DH) disease pose significant threats to national morbidity and mortality in Vietnam, especially on children. Being a climate sensitive disease, it has strong links to various meteorological factors like rainfalls or temperatures. Hence, together with global climate changes, the risk of diarrhoea has been increasing gradually while Vietnam is already a hotspot of diarrhoea worldwide. Thus, having an effective early warning system is becoming an urgent need. However, it has not been paid enough attention with very few research works, mainly focusing on quantilizing the relationships among various climate factors and diarrhoea incidences. Exploring more sophisticated machine learning techniques is therefore an interesting work towards more efficient and effective warning systems. This paper consists of two main contributions. First, many different state-of-the-art prediction models from traditional to most recent advantaged methods, e.g., SARIMA, SARIMAX, LSTM, CNN, Xgboost, SVM, LightGBM, Catboost, LightGBM, N-HiST, BlockRNN, TCN, TFT, or Transformer, are studied for predicting DH rates for a large number of locations (55 provinces) with different climates, geographics and socio-economy factors. It provides a useful view on the overall performances of different ML models on the prediction task, which is extremely useful for other researchers when developing early-warning systems for DH in other places. Second, we introduce a novel ensemble prediction model, called dynamic weighted ensemble (DWE), for further improving the DH prediction performance. DWE is a two layer ensemble approach. The first generates different meta models based on four base component models. The second layer employs a novel approach to predict the performances of all selected meta models and uses these predicted results to dynamically combine these models in a weighted scheme to produce final results. This is totally different to traditional ensemble approaches which only rely on fixed combinations of their components. To the best of our knowledge, DWE is also the first ensemble approach for diarrhoea prediction. Extensive experiments are conducted over all 55 provinces of Vietnam to demonstrate the performance of DWE and to reveal its important characteristics.</p

Aetiology and Potential Animal Exposure in Central Nervous System Infections in Vietnam.

An estimated 73% of emerging infections are zoonotic in origin, with animal contact and encroachment on their habitats increasing the risk of spill-over events. In Vietnam, close exposure to a wide range of animals and animal products can lead to acquisition of zoonotic pathogens, a number of which cause central nervous system (CNS) infections. However, studies show the aetiology of CNS infections remains unknown in around half of cases. We used samples and data from hospitalised patients with CNS infections, enrolled into the Vietnam Initiative on Zoonotic Infections multicentre study, to determine the association between aetiology and animal contact including those in whom the cause was unknown. Among 933 patients, a pathogen or an antibody response to it was identified in 291 (31.2%, 95% CI 28.3-34.3%). The most common pathogens were Streptococcus suis (n = 91 (9.8%, 8.0-11.9%)) and Japanese encephalitis virus (JEV) (n = 72 (7.7%, 6.1-9.7%)). Commonly reported animal contact included keeping, raising or handling (n = 364 (39.0%, 35.9-42.2%)) and handling, cooking or consuming raw meat, blood or viscera in the 2 weeks prior to symptom onset (n = 371 (39.8%, 36.6-43.0%)), with the latter most commonly from pigs (n = 343 (36.9%, 33.8-40.1%). There was no association between an unknown aetiology and exposure to animals in a multivariate logistic regression. Further testing for unknown or undetected pathogens may increase diagnostic yield, however, given the high proportion of zoonotic pathogens and the presence of risk factors, increasing public awareness about zoonoses and preventive measures can be considered

Etikonomi : jurnal ekonomi volume 21 (2) 2022

iii, 440 hlm, 29,4 x 20,7 c