| 1. |
- Giang, Kim Bao, et al.
(author)
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Relative Importance of Different Attributes of Graphic Health Warnings on Tobacco Packages in Viet Nam
- 2016
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In: Asian Pacific Journal of Cancer Prevention. - 1513-7368. ; 17, s. 79-84
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Journal article (peer-reviewed)abstract
- Graphic health warnings (GHW) on tobacco packages have proven to be effective in increasing quit attempts among smokers and reducing initial smoking among adolescents. This research aimed to examine the relative importance of different attributes of graphic health warnings on tobacco packages in Viet Nam. A discrete choice experimental (DCE) design was applied with a conditional logit model. In addition, a ranking method was used to list from the least to the most dreadful GHW labels. With the results from DCE model, graphic type was shown to be the most important attribute, followed by cost and coverage area of GHW. The least important attribute was position of the GHW. Among 5 graphic types (internal lung cancer image, external damaged teeth, abstract image, human suffering image and text), the image of lung cancer was found to have the strongest influence on both smokers and non-smokers. With ranking method, the image of throat cancer and heart diseases were considered the most dreadful images. GHWs should be designed with these attributes in mind, to maximise influence on purchase among both smokers and non-smokers.
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| 2. |
- Chu, Dinh-Toi, et al.
(author)
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An update on obesity : Mental consequences and psychological interventions
- 2019
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In: Diabetes & Metabolic syndrome. - : Elsevier. - 1871-4021 .- 1878-0334. ; 13:1, s. 155-160
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Research review (peer-reviewed)abstract
- Besides physical consequences, obesity has negative psychological effects, thereby lowering human life quality. Major psychological consequences of this disorder includes depression, impaired body image, low self-esteem, eating disorders, stress and poor quality of life, which are correlated with age and gender. Physical interventions, mainly diet control and energy balance, have been widely applied to treat obesity; and some psychological interventions including behavioral therapy, cognitive behavioral therapy and hypnotherapy have showed some effects on obesity treatment. Other psychological therapies, such as relaxation and psychodynamic therapies, are paid less attention. This review aims to update scientific evidence regarding the mental consequences and psychological interventions for obesity. (c) 2018 Diabetes India. Published by Elsevier Ltd. All rights reserved.
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| 3. |
- Duc, Duong M., 1984-, et al.
(author)
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Smoking Initiation and Cessation among Youths in Vietnam : A Longitudinal Study Using the Chi Linh Demographic-Epidemiological Surveillance System (CHILILAB DESS)
- 2017
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In: AIMS PUBLIC HEALTH. - : AMER INST MATHEMATICAL SCIENCES-AIMS. - 2327-8994. ; 4:1, s. 1-18
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Journal article (peer-reviewed)abstract
- Study of smoking initiation and cessation is particularly important in adolescent population because smoking prevention and cessation at this time may prevent several health consequences later in life. There is a very limited knowledge about the determinants of smoking initiation and cessation among youths in Vietnam. This limits the development and implementation of appropriately targeted anti-smoking prevention interventions. This study applied pooled data from 3 rounds of a longitudinal survey in the Chi Linh Demographic-Epidemiological Surveillance System (CHILILAB DESS) in a northern province in Vietnam to analyse the determinants of smoking initiation and cessation among youths. The total of youths in the first round, second, and third rounds was 12,406, 10,211, and 7,654, respectively. The random-effects logit model controlling for both time-variant and time-invariant variables was conducted to explore the associated factors with new smokers and quitters. We found an increase trend of new smokers (7.0% to 9.6%) and quitters (27.5% to 31.4%) during 2009-2013. Smoking initiation and cessation are the result of multifactorial influences of demographic and health behaviours and status. Demographic background (older youths, male, unmarried youths, and youths having informal work) and health behaviours and status (youths who had smoking family members and/or smoking close friends, and had harmful drinking) were more likely to initiate smoking and more difficult to quit smoking. Among these variables, youths who had smoking close-friends had the highest likelihood of both initiating smoking and failed quitting. Our results could represent the similar health problems among youths in peri-urban areas in Vietnam. Further, our findings suggested that anti-smoking interventions should involve peer intervention, integrated with the reduction of other unhealthy behaviours such as alcohol consumption, and to focus on adolescents in their very early age (10-14 years old).
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| 4. |
- Hoang, Duc-Hoang
(author)
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Essays on currency markets
- 2023
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Doctoral thesis (other academic/artistic)abstract
- This doctoral dissertation comprises three independent essays which cover different aspects of the currency market.The first paper, Long-run and short-run risk premium in currency market, investigates the risk premium of the long-run and short-run volatility component of exchange rate returns in the currency market. The results indicate that the risk price of long-run volatility innovation is significant and negative, whereas short-run volatility innovation has no effect on the carry trade returns. This result implies that investors require higher risk premiums to hold the high interest rate currencies under times of high uncertainty. In terms of a momentum strategy, the risk price of short-run volatility innovation is statistically and negatively significant, whereas the risk price of long-run innovation is insignificant. Therefore, long-run volatility cannot explain high returns of currency under the momentum strategy. High momentum returns, on the other hand, reward investors to bear the short-run volatility risk.The second paper, Central bank communication and asset correlations, examines the effect of Fed and ECB communications on the long-run stock-bond and stock-FX correlations. The paper demonstrates that negative tone in central banks’ communications results in a more negative stock-bond correlation, which supports the flight-to-quality phenomenon in both the U.S. and Euro areas. In contrast, results for stock-FX correlations are mixed. The Fed’s negative sentiment leads to opposite movements of U.S. stock prices and the U.S. dollar, whereas ECB’s negative sentiment drives Euro-area stock prices and EUR moving in the same direction. This result documents for the safe haven property of the U.S. dollar.The third paper, Can pre-FOMC predict exchange rates?, studies the predict power of text data for the EURUSD exchange rate returns on scheduled Federal Reserve Committee (FOMC) meeting days. We use text data from Dow Jones Newswire to measure hawkish-dovish sentiment scores before FOMC events. Then we use this score to predict post-FOMC policy rate changes and EURUSD exchange rate movements. Our empirical results show that pre-FOMC hawkish-dovish scores can predict policy rate changes. In addition, the U.S. dollar depreciates against the EUR if pre-FOMC news signals a rate cut and the U.S. dollar appreciates against the EUR if pre-FOMC news signals a rate hike. EURUSD exchange rate movements conditioned on pre-FOMC news are asymmetric: The absolute returns of EURUSD on dovish days are higher than those on hawkish days. We also document that a trading strategy based on pre-FOMC news exhibits economically and statistically high returns on FOMC days.
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| 5. |
- Hwang, Jihye, et al.
(author)
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The JCMT BISTRO Survey: A Spiral Magnetic Field in a Hub-filament Structure, Monoceros R2
- 2022
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In: Astrophysical Journal. - : American Astronomical Society. - 1538-4357 .- 0004-637X. ; 941:1
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Journal article (peer-reviewed)abstract
- We present and analyze observations of polarized dust emission at 850 μm toward the central 1 × 1 pc hub-filament structure of Monoceros R2 (Mon R2). The data are obtained with SCUBA-2/POL-2 on the James Clerk Maxwell Telescope (JCMT) as part of the B-fields in Star-forming Region Observations survey. The orientations of the magnetic field follow the spiral structure of Mon R2, which are well described by an axisymmetric magnetic field model. We estimate the turbulent component of the magnetic field using the angle difference between our observations and the best-fit model of the underlying large-scale mean magnetic field. This estimate is used to calculate the magnetic field strength using the Davis–Chandrasekhar–Fermi method, for which we also obtain the distribution of volume density and velocity dispersion using a column density map derived from Herschel data and the C18O (J = 3 - 2) data taken with HARP on the JCMT, respectively. We make maps of magnetic field strengths and mass-to-flux ratios, finding that magnetic field strengths vary from 0.02 to 3.64 mG with a mean value of 1.0 ± 0.06 mG, and the mean critical mass-to-flux ratio is 0.47 ± 0.02. Additionally, the mean Alfvén Mach number is 0.35 ± 0.01. This suggests that, in Mon R2, the magnetic fields provide resistance against large-scale gravitational collapse, and the magnetic pressure exceeds the turbulent pressure. We also investigate the properties of each filament in Mon R2. Most of the filaments are aligned along the magnetic field direction and are magnetically subcritical.
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| 6. |
- Li, Jing-Rebecca, et al.
(author)
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SpinDoctor : a Matlab toolbox for diffusion MRI simulation
- 2019
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In: NeuroImage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 202
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Journal article (peer-reviewed)abstract
- The complex transverse water proton magnetization subject to diffusion-encoding magnetic field gradient pulses in a heterogeneous medium can be modeled by the multiple compartment Bloch-Torrey partial differential equation (BTPDE). A mathematical model for the time-dependent apparent diffusion coefficient (ADC), called the H-ADC model, was obtained recently using homogenization techniques on the BTPDE. Under the assumption of negligible water exchange between compartments, the H-ADC model produces the ADC of a diffusion medium from the solution of a diffusion equation (DE) subject to a time-dependent Neumann boundary condition. This paper describes a publicly available Matlab toolbox called SpinDoctor that can be used 1) to solve the BTPDE to obtain the dMRI signal (the toolbox provides a way of robustly fitting the dMRI signal to obtain the fitted ADC); 2) to solve the DE of the H-ADC model to obtain the ADC; 3) a short-time approximation formula for the ADC is also included in the toolbox for comparison with the simulated ADC. The PDEs are solved by P 1 finite elements combined with built-in Matlab routines for solving ordinary differential equations. The finite element mesh generation is performed using an external package called Tetgen that is included in the toolbox. SpinDoctor provides built-in options of including 1) spherical cells with a nucleus; 2) cylindrical cells with a myelin layer; 3) an extra-cellular space (ECS) enclosed either a) in a box or b) in a tight wrapping around the cells; 4) deformation of canonical cells by bending and twisting. 5) permeable membranes for the BT-PDE (the H-ADC assumes negligible permeability). Built-in diffusion-encoding pulse sequences include the Pulsed Gradient Spin Echo and the Oscillating Gradient Spin Echo.
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| 7. |
- Nguyen, Thuy Trinh, et al.
(author)
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Multimodal machine learning for mental disorder detection : a scoping review
- 2023
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In: 27th international conference on knowledge based and intelligent information and engineering sytems (KES 2023). - : Elsevier. ; , s. 1458-1467
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Conference paper (peer-reviewed)abstract
- Recent advancements in machine learning and multimedia technologies have paved new ways for automatic medical diagnosis. In mental health, multimodal inputs such as visual and audible sensing data are promising to investigate the underlying mechanisms of many conditions, such as depression and bipolar disorders. With the increasing burden on healthcare systems, timely diagnosis of mental diseases using multiple modalities might benefit millions of people worldwide. This scoping review provides an exploratory overview of recent multimodal machine learning approaches for mental disorder screening. We also discuss a generalised end-to-end multimodal machine learning pipeline for future research and development of multimodal disease detection.
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| 8. |
- Nguyet, To Thi, et al.
(author)
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Enhanced response characteristics of NO2 gas sensor based on ultrathin SnS2 nanoplates : Experimental and DFT study
- 2024
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In: Sensors and Actuators A-Physical. - : Elsevier. - 0924-4247 .- 1873-3069. ; 373
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Journal article (peer-reviewed)abstract
- Layered-metal dichalcogenides with extraordinary characteristics of vast surface area, tunable bandgap and superior adsorption capability enable the potential for application in gas sensors. However, the synthesis of effective material for enhanced response performance remains a challenge. Herein, we exploited a fascinating sensitivity and selectivity towards NO2 gas detection using SnS2 nanoflakes prepared via the hydrothermal method. SnS2 nanoflakes with a thickness of 25 nm and an average diameter of approximately 500 nm show the potential for the detection of NO2 gas at low concentrations of ppb levels. The sensing properties of the SnS2 sensors were investigated for different concentrations of NO2 at various operating temperatures. The sensor exhibits the highest gas-sensing response of 161 at 250 οC upon exposure to 5 ppm of NO2 gas with fast response and recovery times. In addition, the sensor shows excellent selectivity with a low detection limit of ppb level. The electronic structure and gas-sensing mechanism are elucidated via finding density of states, charge density, and band structure based on DFT study which is calculated by the Vienna ab-initio simulation package (VASP). The considerable small adsorption energy reveals a physisorption of the NO2 molecules on the SnS2 surface (-0.174 eV), indicating the SnS2 nanoflakes are intriguing candidates for the speedy detection of NO2 gas.
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| 9. |
- Aarrestad, Thea, et al.
(author)
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Fast convolutional neural networks on FPGAs with hls4ml
- 2021
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In: Machine Learning: Science and Technology. - : IOP Publishing. - 2632-2153. ; 2:4
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Journal article (peer-reviewed)abstract
- We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on field-programmable gate arrays (FPGAs). By extending the hls4ml library, we demonstrate an inference latency of 5 mu s using convolutional architectures, targeting microsecond latency applications like those at the CERN Large Hadron Collider. Considering benchmark models trained on the Street View House Numbers Dataset, we demonstrate various methods for model compression in order to fit the computational constraints of a typical FPGA device used in trigger and data acquisition systems of particle detectors. In particular, we discuss pruning and quantization-aware training, and demonstrate how resource utilization can be significantly reduced with little to no loss in model accuracy. We show that the FPGA critical resource consumption can be reduced by 97% with zero loss in model accuracy, and by 99% when tolerating a 6% accuracy degradation.
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| 10. |
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