Recent progress on artificial intelligence application for COVID-19 monitoring and mitigation system in Indonesia

COVID-19 is a serious public health issue in the world. The spread of COVID-19 has gone global. Indonesia is a country with a high rate of infectious cases worldwide. Multidisciplinary science also brings together to fight against COVID-19 in Indonesia. One of the important roles is artificial intelligence (AI). AI was also reported to help a vital role in public health. As a developing country, Indonesia also brings innovative AI approaches to help people with COVID-19, including classification, detection, diagnosis, prediction, telemedicine, and many more. This study elaborates the recent progress on AI application in Indonesia contributing to the fight against COVID-19 which has been reported in scientific papers/reports. Although research in this field is still not so developed, the existing innovations provide a new enthusiasm for public health and the benefits of the latest technology that can support human health, especially in facing a pandemic at Indonesia. It was found that there can be more research by utilizing AI approaches concerning public health and medicine in the future research work particularly in facing a pandemic condition

Factors influencing patient satisfaction with dental appearance and treatments they desire to improve aesthetics

Background: We assessed factors influencing patients’ satisfaction with their dental appearance and the treatments they desired to improve dental aesthetics. Methods: A cross-sectional study was performed out among 235 adult patients who visited the Hospital Universiti Sains Malaysia dental clinic. A structured, interviewer-guided questionnaire was used to identify patient satisfaction with their general dental appearance, cosmetic elements and desired treatments. Results: The 235 patients consisted of 70 males (29.8%) and 165 females (70.2%), of mean age 31.5 years (SD 13.0). Of these patients, 124 (52.8%) were not satisfied with their general dental appearance. In addition, 132 patients (56.2%) were not happy with the color of their teeth, 76 (32.3%), regarded their teeth were poorly aligned, 62 (26.4%), as crowded and 56 (23.4%) protruded. Dissatisfaction with tooth color was significantly higher in female than in male patients (odds ratio [OR] of 1.99 (95% confidence interval [CI] 1.13-3.50). Tooth whitening was the treatment most desired by patients (48.1%). Results of multiple logistic regression analysis showed that patient dissatisfaction with general dental appearance was significantly associated with female gender (OR = 2.18; 95% CI: 1.18-4.03), unhappiness with tooth color (OR = 3.05; 95% CI: 1.74-5.34) and the opinion that their teeth protruded (OR = 2.91, 95% CI: 1.44-5.91)

Gravitational Waves from Gravitational Collapse

Gravitational wave emission from the gravitational collapse of massive stars has been studied for more than three decades. Current state of the art numerical investigations of collapse include those that use progenitors with realistic angular momentum profiles, properly treat microphysics issues, account for general relativity, and examine non--axisymmetric effects in three dimensions. Such simulations predict that gravitational waves from various phenomena associated with gravitational collapse could be detectable with advanced ground--based and future space--based interferometric observatories.Comment: 68 pages including 13 figures; revised version accepted for publication in Living Reviews in Relativity (http://www.livingreviews.org

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe