Accounting conservatism and banking expertise on board of directors

Previous studies show mixed evidence of the role of banking expertise on the board of directors on accounting conservatism. In this paper, we add to this growing literature by providing an innovative way to measure banking expertise based on life-time working history in banks of all individual directors on the board. We find that accounting conservatism is negatively affected by banking expertise on the board. Also, the results indicate that banking expertise on the board has a more pronounced impact on accounting conservatism when firms have high bankruptcy risk and when firms have high financial leverage. The evidence has some implications for boards of directors

n-Gram-based text compression

We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.Web of Scienceart. no. 948364

A Big Data Smart Agricultural System: Recommending Optimum Fertilisers For Crops

Nutrients are important to promote plant growth and nutrient deficiency is the primary factor limiting crop production. However, excess fertilisers can also have a negative impact on crop quality and yield, cause an increase in pollution and decrease producer profit. Hence, determining the suitable quantities of fertiliser for every crop is very useful. Currently, the agricultural systems with internet of things make very large data volumes. Exploiting agricultural Big Data will help to extract valuable information. However, designing and implementing a large scale agricultural data warehouse are very challenging. The data warehouse is a key module to build a smart crop system to make proficient agronomy recommendations. In our paper, an electronic agricultural record (EAR) is proposed to integrate many separate datasets into a unified dataset. Then, to store and manage the agricultural Big Data, we built an agricultural data warehouse based on Hive and Elasticsearch. Finally, we applied some statistical methods based on our data warehouse to extract fertiliser information such as a case study. These statistical methods propose the recommended quantities of fertiliser components across a wide range of environmental and crop management conditions, such as nitrogen (N), phosphorus (P) and potassium (K) for the top ten most popular crops in EU

Prevalence of gestational diabetes mellitus in eastern and southeastern Asia: A systematic review and meta-analysis

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Aim. To review the prevalence of gestational diabetes mellitus (GDM) in Eastern and Southeastern Asia. Methods. We systematically searched for observational studies on GDM prevalence from January 2000 to December 2016. Inclusion criteria were original English papers, with full texts published in peer-reviewed journals. The quality of included studies was evaluated using the guidelines of the National Health and Medical Research Council, Australia. Fixed effects and random effects models were used to estimate the summary prevalence of GDM and the corresponding 95% confidence intervals (CI). Results. A total of 4415 papers were screened, and 48 studies with 63 GDM prevalence observations were included in the final review. The pooled prevalence of GDM was 10.1% (95% CI: 6.5%–15.7%), despite substantial variations across nations. The prevalence of GDM in lower- or upper-middle income countries was about 64% higher than in their high-income counterparts. Moreover, the one-step screening method was twice more likely to be used in diagnosing GDM when compared to the two-step screening procedure. Conclusions. The prevalence of GDM in Eastern and Southeastern Asia was high and varied among and within countries. There is a need for international uniformity in screening strategies and diagnostic criteria for GDM

Prevalence and Determinants of Medication Adherence among Patients with HIV/AIDS in Southern Vietnam

This study was conducted to determine the prevalence and determinants of medication adherence among patients with HIV/AIDS in southern Vietnam. METHODS: A cross-sectional study was conducted in a hospital in southern Vietnam from June to December 2019 on patients who began antiretroviral therapy (ART) for at least 6 months. Using a designed questionnaire, patients were considered adherent if they took correct medicines with right doses, on time and properly with food and beverage and had follow-up visits as scheduled. Multivariable logistic regression was used to identify determinants of adherence. KEY FINDINGS: A total of 350 patients (from 861 medical records) were eligible for the study. The majority of patients were male (62.9%), and the dominant age group (≥35 years old) accounted for 53.7% of patients. Sexual intercourse was the primary route of transmission of HIV (95.1%). The proportions of participants who took the correct medicine and at a proper dose were 98.3% and 86.3%, respectively. In total, 94.9% of participants took medicine appropriately in combination with food and beverage, and 75.7% of participants were strictly adherent to ART. The factors marital status (odds ratio (OR) = 2.54; 95%CI = 1.51-4.28), being away from home (OR = 1.7; 95%CI = 1.03-2.78), substance abuse (OR = 2.7; 95%CI = 1.44-5.05), general knowledge about ART (OR = 2.75; 95%CI = 1.67-4.53), stopping medication after improvement (OR = 4.16; 95%CI = 2.29-7.56) and self-assessment of therapy adherence (OR = 9.83; 95%CI = 5.44-17.77) were significantly associated with patients' adherence. CONCLUSIONS: Three-quarters of patients were adherent to ART. Researchers should consider these determinants of adherence in developing interventions in further studies

Theoretical modeling of the carbon dioxide injection into the porous medium saturated with methane and water taking into account the CO2 hydrate formation

In this work the mathematical model is constructed and the features of the injection of warm carbon dioxide (with the temperature higher than the initial reservoir temperature) into the porous reservoir initially saturated with methane gas and water are investigated. Self-similar solutions of the one-dimensional problem describing the distributions of the main parameters in the reservoir are constructed. The effect of the parameters of the injected carbon dioxide and the reservoir on the intensity of the CO2hydrate formation is analyzed

Label driven Knowledge Distillation for Federated Learning with non-IID Data

In real-world applications, Federated Learning (FL) meets two challenges: (1) scalability, especially when applied to massive IoT networks; and (2) how to be robust against an environment with heterogeneous data. Realizing the first problem, we aim to design a novel FL framework named Full-stack FL (F2L). More specifically, F2L utilizes a hierarchical network architecture, making extending the FL network accessible without reconstructing the whole network system. Moreover, leveraging the advantages of hierarchical network design, we propose a new label-driven knowledge distillation (LKD) technique at the global server to address the second problem. As opposed to current knowledge distillation techniques, LKD is capable of training a student model, which consists of good knowledge from all teachers' models. Therefore, our proposed algorithm can effectively extract the knowledge of the regions' data distribution (i.e., the regional aggregated models) to reduce the divergence between clients' models when operating under the FL system with non-independent identically distributed data. Extensive experiment results reveal that: (i) our F2L method can significantly improve the overall FL efficiency in all global distillations, and (ii) F2L rapidly achieves convergence as global distillation stages occur instead of increasing on each communication cycle.Comment: 28 pages, 5 figures, 10 table

Knowledge of Antiretroviral Treatment and Associated Factors in HIV-Infected Patients

This study aimed to assess the knowledge of antiretroviral (ARV) treatment and the associated factors in HIV-infected patients in Vietnam. We conducted a cross-sectional descriptive study of 350 human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) patients being treated with ARV at outpatient clinics at Soc Trang, Vietnam, from June 2019 to December 2019. Using an interview questionnaire, patients who answered at least eight out of nine questions correctly, including some required questions, were considered to have a general knowledge of ARV treatment. Using multivariate logistic regression to identify factors associated with knowledge of ARV treatment, we found that 62% of HIV-infected patients had a general knowledge of ARV treatment, with a mean score of 8.2 (SD 1.4) out of 9 correct. A higher education level (p < 0.001); working away from home (p = 0.013); getting HIV transmitted by injecting drugs or from mother-to-child contact (p = 0.023); the presence of tension, anxiety, or stress (p = 0.005); self-reminding to take medication (p = 0.024); and a high self-evaluated adherence (p < 0.001) were found to be significantly associated with an adequate knowledge of ARV treatment. In conclusion, education programs for patients, as well as the quality of medical services and support, should be strengthened

A breakthrough dynamic-osmotic membrane bioreactor/nanofiltration hybrid system for real municipal wastewater treatment and reuse.

This study designed a Dynamic-Osmotic membrane bioreactor/nanofiltration (OsMBR/NF) system for municipal wastewater treatment and reuse. Results indicated that a continuously rotating FO module with 60 RPM in Dynamic-OsMBR system could enhance shear stress and reduce cake layer of foulants, leading to higher flux (50%) compared to Traditional-OsMBR during a 40-operation day. A negligible specific reverse salt flux (0.059 G/L) and a water flux of 2.86 LMH were recorded when a mixture of 0.1 M EDTA-2Na/0.1 M Na2CO3/0.9 mM Triton114 functioned as draw solution (DS). It was found that the Dynamic-OsMBR/NF hybrid system could effectively remove pollutants (∼98% COD, ∼99% PO43-P, ∼93% NH4+-N, > 99% suspended solids) from wastewater. In short, this developed system can be considered a breakthrough technology as it successfully minimizes membrane fouling by shear force, and achieves high water quality for reuse by two membrane- barriers