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The high-quality of financial reporting provides suitable information for economic decision-making of the country whilst, the low quality of financial reporting causes a serious impact on the economy. This research aims to classify financial reporting quality (FRQ) as well as determines the drivers of FRQ. This study uses a panel dataset from 2014 to 2020 that is collected from the Vietnamese listed companies. The study applies machine learning algorithms to classify and assess FRQ of non-financial companies on the Vietnamese stock exchange. New contribution considers the FRQ, on the auditor's opinion and the variance between pre-audit and post-audit profit. This research classifies FRQ into normal and poor categories, and a rate of 9.35% in the sample is considered poor FRQ. This research shows that the return on assets’ ratio and the ownership concentration have the most important influence on FRQ. Furthermore, the results which are predicting FRQ by using the random forest algorithm have an accuracy rate of 94%. This study is valuable for the forecast of FRQ and for the support of stakeholders in decision-making. With the high accuracy of machine learning techniques and its usage, it can help analysts and investors in generating reliable accounting information for decision-making purposes. Corporate sector needs to pay attention towards financial ratios and reinforcement of corporate governance.

The distance from the nearest concrete exposed surface to the centroidal axis of main longitudinal steel re-inforcing bars, so-called axis distance, plays a critical role in ensuring the safety of reinforced concrete (RC) structures under fire, as it helps the rebars not being directly exposed to heating in a fire incident. However, a large axis distance value could reduce the effective height as well as the beam’s flexural strength at ambient condition. In order to determine the appropriate values of axis distance, this article developes a data-driven method for predicting the flexural strength deterioration (FSD) of RC beams under ISO 834 standard fire based on the material and geometrical inputs. This method consists of two main stages: (i) Establishing a theoretical/experimental database by collecting experimental data from the literature; and (ii) Engineering a probabilis-tic model based on the Bayesian Neural Network. The results obtained show that the proposed approach is a practical tool that is capable of performing quick and reasonably accurate analysis such as degradation curves of FSD against exposure time. In addition, the uncertainty related to the prediction results is also evaluated, providing useful information for structural fire engineers to achieve conservative designs.

Bài báo xem xét ảnh hưởng của chất lượng dồn tích đến giá trị của các doanh nghiệp niêm yết ở Việt Nam. Nghiên cứu sử dụng phương pháp hồi quy tác động cố định, tác động ngẫn nhiên và hồi quy tổng quát, với dữ liệu thu thập trong giai đoạn 2010 - 2020, với 6847 quan sát. Kết quả nghiên cứu đã phát hiện chất lượng dồn tích có ảnh hưởng ngược chiều chiều đến giá trị doanh nghiệp. Ngoài ra, nghiên cứu cũng cho thấy quy mô doanh nghiệp và khả năng sinh lời có ảnh hưởng thuận chiều đến giá trị doanh nghiệp, trái lại đòn bẩy tài chính ảnh hưởng ngược chiều đến giá trị doanh nghiệp. Các kết quả nghiên cứu thực nghiệm là cơ sở hữu ích giúp doanh nghiệp nâng cao giá trị, từ đó giúp doanh nghiệp cần xem xét các việc cung cấp thông tinh, nâng cao tính minh bạch và nâng cao chất lượng báo cáo tài chính.

Determining structures' dynamic response is a challenging and time-consuming problem because it requires iteratively solving the governing equation of motion with a significantly small time step to ensure convergent results. This study proposes an alternative approach based on the deep learning paradigm working in a complementary way with conventional methods such as the finite element method for quickly forecasting the responses of structures under random wind loads with reasonable accuracy. The approach works in a sequence-to-sequence fashion, providing a good trade-off between the prediction performance and required computation resources. Sequences of known wind loads plus time history response of the structure are aggregated into a 3D tensor input before going through a deep learning model, which includes a long short-term memory layer and a time distributed layer. The output of the model is a sequence of structures' future responses, which will subsequently be used as input for computing structure' next response. The credibility of the proposed approach is demonstrated via an example of a two-dimensional three-bay nine-story reinforced concrete frame structure.

The article presents the research results on medicinal plant resources at Tan Phu Protective Forests, Dong Nai Province. Initially, 351 plant species have been identified for medicinal use, belonging to 83 families, 3 plant divisions; in which: Pinophyta has 1 species belonging to 1 family; Polypodiophyta has 11 species belonging to 4 families; Magnoliophyta has 339 species belonging to 78 families. The life form is very diverse with the woody group having the highest number of species 152 species (accounting for 43.3%), the group of herbs having 73 species (20.8%), the group of shrubs, having 72 species (20.5%); The liana has 40 species (11.4%) and the epiphytes has the least with 14 species (4.0%), respectively. Medicinal plants are mainly used to treat groups of pimples, rashes, inflammation with 155 species (accounting for 44.16%); the group used to treat colds and fever with 112 species (accounting for 31.9%); group used to treat dysentery, diarrhea with 107 species (30.5%); group used to treat low and painful anesthesia with 105 species (29.9%); in the digestive system with 104 species (29.63%), respectively. The most commonly used treatment is pounding for topical use and excellent for internal use. Recorded 07 species in Group IIA in Decree 06/2019/ND-CP; 06 species in the Vietnam Red Data Book (2007): 03 species classified as Vulnerable - VU; 03 species classified as Endangered - EN. The medicinal resources here are being over-exploited, so it is necessary to have measures for conservation and development.

Panax ginseng is a common natural product, which is well-known to have a wide range of pharmacological activities in cancer. Its metabolite, compound K (CK), has been reported to have anticancer activity. We aimed to systematically review the literature for evidence of anticancer effects of CK. We conducted a systematic search in eight databases. We included all in vitro and in vivo studies investigating the anticancer effects of CK with no restrictions. Quality assessment was applied by ToxRTool. Fifty-four articles were included in our study. The purity of CK in our included studies was at least 95%. The in vitro studies reported that CK had a potential anticancer activity on several cell lines including human lung cancer cell lines (A549, PC-9), nasopharyngeal carcinoma cell line (Hk-1), liver cancer cell line (BEL 7402), and pediatric acute myeloid leukemia cell lines (Kasumi-1, MV4-11). The in vivo studies reported a significant decrease in tumor volume in mice treated with CK. CK is a potential supplementary treatment in cancer chemotherapies. The safety and further clinical trials of CK should be explored for future drug development., Fundamental & Clinical Pharmacology, pp.1-29; 2023. doi:10.1111/fcp.12874

Bài báo xem xét tính thích hợp của thông tin kế toán trên báo cáo tài chính (BCTC) và giá trị doanh nghiệp. Nghiên cứu sử dụng dữ liệu bảng với 5706 quan sát, tại các doanh nghiệp niêm yết trên thị trường chứng khoán Việt Nam giai đoạn 2009 -2019. Kết quả hồi quy đa biến phát hiện tính thích hợp của thông tin kế toán có xu hướng tăng lên, nhưng có có ảnh hưởng ngược thuận chiều đến giá trị doanh nghiệp. Bên cạnh đó quy mô của doanh nghiệp có ảnh hưởng tích cực đến giá trị doanh nghiệp, trái lại cấu trúc vốn có quan hệ tiêu cực đến giá trị doanh nghiệp khi đo lương theo EV. Các kết quả nghiên cứu thực nghiệm là cơ sở hữu ích giúp doanh nghiệp có các giải pháp nâng cao tính hữu ích của thông tin trên BCTC từ đó nâng cao giá trị doanh nghiệp.

The Article Examines The Impact Of Cash Flow On The Need To Increase Funding In The Covid Pandemic Context And The Financial Constraints Of Listed Companies In Vietnam. We Build Hypotheses Based On The Self-Ranking Match Theory Framework And Research Overview. We Use Data From 5894 Observations For 2010-2020 And The General Regression Model - GLS To Test The Expected Hypotheses. The Research Results Show That Cash Flow Significantly Influences The External Financing Needs Of The Business. In Particular, The Cash Flow Impact And Increased Need For External Financing Are More Evident In Financial Constraints And The Context Of The Covid Pandemic. The Study Also Shows That The Group Of Companies With Financial Constraints Moved To Increase Funding When Cash Flow Was In Short Supply During The Covid Pandemic. Besides, The High Financial Leverage Ratio In The Previous Year Can Be One Of The Barriers For Businesses That Want To Access A Variety Of External Financing. The Study Contributes To The Analysis And Assessment Of The Problematic Situation Of Listed Companies. In The Future, This Study Can Be Extended When Approaching Businesses In The Financial Sector And Evaluating Other Macro Factors That Can Affect The Capital Sources Of Enterprises.