A STUDY OF INDONESIA’S STOCK MARKET: HOW PREDICTABLE IS IT?

Using monthly data from January 1995 to December 2017, this paper tests whetherIndonesian stock index returns are predictable. In particular, we use eight macrovariables to predict the Indonesian composite and six sectoral index returns using thefeasible generalized least squares estimator. Our results suggest that the Indonesianstock index returns are predictable. However, the predictability depends not only onthe macro predictor used but also on the indexes examined. Second, we find that themost popular predictor is the exchange rate, followed by the interest rate. Finally, ourmain findings hold for a number of robustness tests.Using monthly data from January 1995 to December 2017, this paper tests whetherIndonesian stock index returns are predictable. In particular, we use eight macrovariables to predict the Indonesian composite and six sectoral index returns using thefeasible generalized least squares estimator. Our results suggest that the Indonesianstock index returns are predictable. However, the predictability depends not only onthe macro predictor used but also on the indexes examined. Second, we find that themost popular predictor is the exchange rate, followed by the interest rate. Finally, ourmain findings hold for a number of robustness tests

Two-view Graph Neural Networks for Knowledge Graph Completion

We present an effective GNN-based knowledge graph embedding model, named WGE, to capture entity- and relation-focused graph structures. In particular, given the knowledge graph, WGE builds a single undirected entity-focused graph that views entities as nodes. In addition, WGE also constructs another single undirected graph from relation-focused constraints, which views entities and relations as nodes. WGE then proposes a GNN-based architecture to better learn vector representations of entities and relations from these two single entity- and relation-focused graphs. WGE feeds the learned entity and relation representations into a weighted score function to return the triple scores for knowledge graph completion. Experimental results show that WGE outperforms competitive baselines, obtaining state-of-the-art performances on seven benchmark datasets for knowledge graph completion.Comment: 13 pages; 3 tables; 3 figure

TERRORIST ATTACKS AND CORPORATE INVESTMENT IN INDONESIA

Using yearly data from 1997 to 2017, this paper studies the effect of terrorism (number of attacks) on corporate investment in Indonesia. Applying an investment-type model, we show that firms reduce their capital expenditure due to an increase in the number of terrorist attacks. On average, a one standard deviation increase in the number of terrorist attacks reduces corporate investment by 9.23%. We also find heterogenous reactions of firms to terrorism across different sectors and different panels based on firm characteristics. Finally, our main results remain consistent after performing several robustness tests

Beyond Traditional Approaches: Multi-Task Network for Breast Ultrasound Diagnosis

Breast Ultrasound plays a vital role in cancer diagnosis as a non-invasive approach with cost-effective. In recent years, with the development of deep learning, many CNN-based approaches have been widely researched in both tumor localization and cancer classification tasks. Even though previous single models achieved great performance in both tasks, these methods have some limitations in inference time, GPU requirement, and separate fine-tuning for each model. In this study, we aim to redesign and build end-to-end multi-task architecture to conduct both segmentation and classification. With our proposed approach, we achieved outstanding performance and time efficiency, with 79.8% and 86.4% in DeepLabV3+ architecture in the segmentation task.Comment: 7 pages, 3 figure

Homoisopogon a from Ophiopogon japonicus induces apoptosis in A549 – a non small cell lung cancer cell line

Lung cancer is the leading cause of death among Vietnamese people and can be divided into two major groups: small cell lung cancer (SCLC), and non-small cell lung cancer (NSCLC). It is estimated that 85% of patients was diagnosed as NSCLC. Therapy drugs that targeted lung cancer tumors with the epidermal growth factor receptor (EGFR) may initially provide benefit, but over time tumors can develop resistance. The recent discovery of EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has provided a new target for the theurapeutic agents in non-small cell lung cancer treatment. In our study, homoisopogon A, a new compound isolated from the tubers of Ophiopogon japonicus (Mach mon, in Vietnamese) effectively showed the cytotoxic activity to the EGFR and TKI-resistant NSCLC cell lines including human lung carcinoma A549, human lung adenocarcinoma NCI-H1975 and human lung adenocarcinoma NCI-H1650. The IC50 values of homoisopogon A against A549, NCI-H1975 and NCI-H1650 were determined as 6.26, 19.51, and 24.66 µM, respectively. Preliminary study on the mechanism of action using flow cytometry analysis was performed. Homoisopogon A treatment of A549 cells at concentration of 25 μM generated apoptosis in 27.5% of cells (7% early apoptosis and 20.5% late apoptosis) after 24h of treatment. The effect increased significantly at the concentration of 50 μM, the homoisoflavanone generated apoptosis in 83.8% of cells (23.5% early apoptosis and 60.3% late apoptosis). Treatment with homoisopogon A for 48h also resulted in typical apoptotic morphological changes in A549 cells under microscopic observation. The results strongly suggested that homoisopogon A induces apoptosis in EGFR and TKI-resistant-A549 cells, thus resulting in the cytotoxicity

Differentiation Effect of Two Alkaloid Fractions from Vietnamese Lycopodiaceae on Mouse Neural Stem Cells

Various Lycopodium alkaloids have been studied for their various biological activities including anti-inflammatory, antioxidant, immunomodulatory, and neuroprotective activities. Moreover, these alkaloid compounds have high potential in the treatment of neuron degenerative disease. This study has been carried out to test the effect of Huperzia serrata (Thunb.) Trevis, and Lycopodium clavatum L alkaloid fractions on the mouse neural stem cells (NSCs). Firstly, the alkaloid fractions were used to verify its toxicity on NSCs. The multiple concentrations of alkaloid fractions from H. serrata (0.044; 0.088; 0.175; 0.35; 0.7; 1.4 mg/ml) and L. clavatum (0.031; 0.063; 0.125; 0.25; 0.50; 1.0; 2.0 mg/ml) have been used for the treatment of NSCs at period of 48h incubation. Results of the study suggested that the IC50 value of H. serrata and L. clavatum was 0.56 mg/ml and 0.50 mg/ml, respectively. Then, the NSCs were differentiated in the presence of 5 and 10 µg/ml of alkaloid fraction from H. serrata; 0.625 and 1.25 µg/ml of alkaloid fraction from L. clavatum for 6 days. Here, we observed the primary NSCs treated with alkaloid fraction extract from H. serrata showed the increased gene expression level of early neuron TUBB3 and neuron-specific cytoskeleton MAP2. On the other hand, the L. clavatum alkaloid fraction increased the expression of neural stem cell marker genes (Nestin and PAX6) and decreased neuron marker genes. In conclusion, these results established that alkaloid fraction from H. serrata promoted differentiation of the mouse NSCs to neuron cells, and L. clavatum extract had a capacity for stemness maintenance

Clinical Characteristics and Histopathology of Idiopathic Epiretinal Membrane in Vietnam

BACKGROUND: Idiopathic epiretinal membrane (iERM) is an avascular proliferation of different types of cells between the posterior vitreous cortex and the internal limiting membrane. That causes visual impairment including blurry, distortion, scotoma. Many studies of iERM were done to describe the clinical characteristics and investigate the histopathology of this disease. Nonetheless, there has not been a study of iERM histopathology in Vietnam. AIMS: To describe clinical characteristics and histopathological results of idiopathic retinal membrane and the association between them. METHODS: A cross sectional decriptive study of 35 iERMs (33 patients) in Vietnam National Institute of Ophthalmology (VNIO). RESULTS: High morbidity incidence was in group age >50 years (32/35), female gender (26/35), limited movement works (27/35), and high educational levels (28/35). Distortion was the highest (77.14%), scotoma and floater was less frequent (28.5%, 45.7%). Macular edema in all cases and PVD and exudate were high frequent (65.7%, 62.8%). Symptom duration was 8.2 ± 4.7 months, (1-21 months). Mean of central macular thickness was 468.51 ± 97.24 µm (656-274 µm). Six types of cell were detected, including glial cell (35/35), fibroblast (23/35), myofibroblast (23/35), macrophage (13/35), lymphocyte (5/35) and neutrophil (2/35). The number of cell types in one sample ranged from 1-5 types (2.85 ± 1.28 cell types). Number of cell types were correlated to symptom duration (r = 0.47, p = 0.004, Pearson's test) and central macular thickness (r = 0.72, p < 0.001, Pearson's test). CONCLUSION: There were 6 types of cells in iERM. Glial cell was the most frequent cell, inflammatory cells (macrophage, lymphocyte, neutrophil) was also detected. The number of cell types was stastitically correlated to symptom duration and CMT