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Nguyen Van Hung,Bui Thi Minh Nguyet,Nguyen Huu Nghi,Nguyen Mau Thanh,Nguyen Duc Vu Quyen,Vo Thang Nguyen,Dao Ngoc Nhiem,Dinh Quang Khieu 대한환경공학회 2023 Environmental Engineering Research Vol.28 No.3
In this study, longan seeds - an agricultural by-product was used to fabricate activated carbon (LSAC) through two-step pyrolysis with pre-carbonization at low temperature in the first step and then activation by H3PO4. LSAC with large surface area and porous structure exhibits an excellent capacity of absorption towards both cationic dyes (methylene blue (MB), rhodamine-B (RhB)) and anionic dyes (methyl orange (MO), congo red (CR)). Experimental data can be described well by the pseudo-second kinetic model. The maximum adsorption capacity based on Langmuir isotherm model was found as 502.84; 397.77; 464.66 and 350.64 mg.g−1 for MB, RhB, MO and CR, respectively. The adsorption of MB, RhB and CR on LSAC is spontaneous and endothermic, while that for MO is spontaneous but exothermic. Furthermore, the adsorption mechanism of dyes on LSAC was also studied showing that it can occur by electrostatic interaction, hydrogen bonding, the filling of pores involving the interaction between dye ions with specific functional groups such as –OH, –COOH, –NH2 and –PO43− on the LSAC surface. These results suggest that LSAC material may be envisaged as a promising adsorbent for treatment of wastewater in textile industries.
Thang Phan,Ha Phan Ai Nguyen,Cao Khoa Dang,Minh Tri Phan,Vu Thanh Nguyen,Van Tuan Le,Binh Thang Tran,Chinh Van Dang,Tinh Huu Ho,Minh Tu Nguyen,Thang Van Dinh,Van Trong Phan,Binh Thai Dang,Huynh Ho Ngo The Korean Society for Preventive Medicine 2023 예방의학회지 Vol.56 No.4
Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic. Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher. Results: Participants' mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95). Conclusions: The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.
Thi Binh Nguyen Nguyen,Thi Kieu Diem Nguyen,Van Hue Trương,Thi Tuyet Ngoc Tran,van Bao Thang Phan,Thi Tuyen Nguyen,Hoang Bach Nguyen,Viet Quynh Tram Ngo,Van Tuan Mai,Paola Molicotti 질병관리본부 2023 Osong Public Health and Research Persptectives Vol.14 No.5
Objectives: Tuberculosis (TB) and drug-resistant TB (DR-TB) are national health burdens in Vietnam. In this study, we investigated the prevalence of rifampicin (RIF) and/or isoniazid (isonicotinic acid hydrazide, INH) resistance in patients with suspected TB, and applied appropriate techniques to help rapidly target DR-TB. Methods: In total, 1,547 clinical specimens were collected and cultured using the BACTEC MGIT system (Becton Dickinson and Co.). A resazurin microtiter assay (REMA) was used to determine the proportions of RIF and/or INH resistance. A real-time polymerase chain reaction panel with TaqMan probes was employed to identify the mutations of rpoB and katG associated with DR-TB in clinical isolates. Genotyping of the identified mutations was also performed. Results: A total of 468 Mycobacterium tuberculosis isolates were identified using the REMA. Of these isolates, 106 (22.6%) were found to be resistant to 1 or both antibiotics. Of the resistant isolates, 74 isolates (69.8%) were resistant to isoniazid (INH) only, while 1 isolate (0.94%) was resistant to RIF only. Notably, 31 isolates (29.24%) were resistant to both antibiotics. Of the 41 phenotypically INH-resistant isolates, 19 (46.3%) had the Ser315Thr mutation. There were 8 different rpoB mutations in 22 (68.8%) of the RIF-resistant isolates. The most frequently detected mutations were at codons 531 (37.5%), 526 (18.8%), and 516 (6.3%). Conclusion: To help prevent new cases of DR-TB in Vietnam, it is crucial to gain a comprehensive understanding of the genotypic DR-TB isolates.
High-Resolution Simulations for Vietnam - Methodology and Evaluation of Current Climate
Jack Katzfey,Kim Nguyen,John McGregor,Peter Hoffmann,Suppiah Ramasamy,Hiep Van Nguyen,Mai Van Khiem,Thang Van Nguyen,Kien Ba Truong,Thang Van Vu,Hien Thuan Nguyen,Tran Thuc,Doan Ha Phong,Bang Thanh Ng 한국기상학회 2016 Asia-Pacific Journal of Atmospheric Sciences Vol.52 No.2
To assist the government of Vietnam in its efforts to better understand the impacts of climate change and prioritise its adaptation measures, dynamically downscaled climate change projections were produced across Vietnam. Two Regional Climate Models (RCMs) were used: CSIRO’s variable-resolution Conformal-Cubic Atmospheric Model (CCAM) and the limited-area model Regional Climate Model system version 4.2 (RegCM4.2). First, global CCAM simulations were completed using bias- and variance-corrected sea surface temperatures as well as sea ice concentrations from six Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models. This approach is different from other downscaling approaches as it does not use any atmospheric fields from the GCMs. The global CCAM simulations were then further downscaled to 10 km using CCAM and to 20 km using RegCM4.2. Evaluations of temperature and precipitation for the current climate (1980-2000) were completed using station data as well as various gridded observational datasets. The RCMs were able to reproduce reasonably well most of the important characteristics of observed spatial patterns and annual cycles of temperature. Average and minimum temperatures were well simulated (biases generally less than 1oC), while maximum temperatures had biases of around 1oC. For precipitation, although the RCMs captured the annual cycle, RegCM4.2 was too dry in Oct.-Nov. (−60% bias), while CCAM was too wet in Dec.- Mar. (130% bias). Both models were too dry in summer and too wet in winter (especially in northern Vietnam). The ability of the ensemble simulations to capture current climate increases confidence in the simulations of future climate.
Least Square Cooperative Localization
Van Nguyen, Thang,Youngmin Jeong,Hyundong Shin,Win, Moe Z. IEEE 2015 IEEE Transactions on Vehicular Technology VT Vol.64 No.4
<P>Location awareness is becoming essential for emerging wireless applications where most network activities require the location information of network nodes, e.g., routing between nodes in ad-hoc sensor networks, positioning vehicles on the road, or tracking targets in underwater acoustic sensor networks. In particular, cooperation among nodes is highly beneficial for the localization accuracy and coverage in harsh environments. In this paper, we study least square (LS) cooperative localization in the presence of arbitrary non-line-of-sight (NLOS) ranging bias. To develop the network position error bound (PEB), we first derive the Fisher information matrix (FIM) for a general NLOS bias model and show that a Gaussian bias due to NLOS effects is the worst case that produces the extremal FIM, whereas a constant bias or equivalently full line-of-sight is the best situation leading to the largest FIM in a sense of Lowner partial ordering. We then analyze the asymptotic performance, such as uniform convergence, consistency, and efficiency, of LS cooperative localization to quantify the deviations of localization accuracy for LS, squared-range LS, and squared-range weighted LS solutions from the fundamental limit (i.e., Cramer-Rao lower bound) due to their practical tractability. We also propose a simple distributed algorithm for LS cooperative localization by integrating squared-range relaxation into Gaussian variational message passing on the localization network. To account for stochastic natures of node locations and populations, we further characterize the network PEB for Gilbert's disk localization network, where anchors and/or agents are randomly distributed in the network according to point processes.</P>
Secrecy Capacity of Nakagami-m Fading Channels
Thang Van Nguyen,Hien Quoc Ngo,Hyundong Shin 대한전자공학회 2009 ITC-CSCC :International Technical Conference on Ci Vol.2009 No.7
This paper concerns with the transmission of confidential data over Nakagami-m fading channels with three terminals-a sender, a receiver and an eavesdropper. Considering the problem of secure communications between two nodes over a Nakagami-m fading channel in the presence of eavesdropper, we derive the closed-form expressions of the ergodic secrecy capacity and outage probability for two scenarios with and without channel state information at the transmitter.
Machine Learning for Wideband Localization
Thang Van Nguyen,Youngmin Jeong,Hyundong Shin,Win, Moe Z. IEEE 2015 IEEE journal on selected areas in communications Vol.33 No.7
<P>Wireless localization has a great importance in a variety of areas including commercial, service, and military positioning and tracking systems. In harsh indoor environments, it is hard to localize an agent with high accuracy due to non-line-of-sight (NLOS) radio blockage or insufficient information from anchors. Therefore, NLOS identification and mitigation are highlighted as an effective way to improve the localization accuracy. In this paper, we develop a robust and efficient algorithm to enhance the accuracy for (ultrawide bandwidth) time-of-arrival localization through identifying and mitigating NLOS signals with relevance vector machine (RVM) techniques. We also propose a new localization algorithm, called the two-step iterative (TSI) algorithm, which converges fast with a finite number of iterations. To enhance the localization accuracy as well as expand the coverage of a localizable area, we continue to exploit the benefits of RVM in both classification and regression for cooperative localization by extending the TSI algorithm to a centralized cooperation case. For self-localization setting, we then develop a distributed cooperative algorithm based on variational Bayesian inference to simplify message representations on factor graphs and reduce communication overheads between agents. In particular, we build a refined version of Gaussian variational message passing to reduce the computational complexity while maintaining the localization accuracy. Finally, we introduce the notion of a stochastic localization network to verify proposed cooperative localization algorithms.</P>