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Arsenic In Water : Concerns And Treatment Technologies
Tien, Vinh Nguyen,Chaudhary, Durgananda Singh,Ngo, Huu Hao,Vigneswaran, Saravanamuthu 한국공업화학회 2004 Journal of Industrial and Engineering Chemistry Vol.10 No.3
Arsenic (As) contamination in groundwater raises grave concerns in many parts of the world. Arsenic can cause severe health problems even at very low concentration. In the first part of this review, the available technologies to treat As-rich water are discussed. It was found that even conventional technologies, which can be readily adopted in rural areas of the developing countries, can reduce As concentrations to the required level. The efficiency of the treatment technologies is better for removing As(V) than it is for As(II1). The second part of this paper presents laboratory-scale experimental results with respect to specific treatment technologies, such as high-rate flocculation and a new membrane-adsorption system, for As removal. The results indicate that up to 78% of the As was removed when using a packed polystyrene-bead filter with in-line FeC13 addition at a high loading rate (30 m3/m2h). When powder-activated carbon (PAC) was used as an adsorbent for in-line addition to the membrane hybrid system, 87% removal of As was achieved when the mixing time was 2.7 min, the velocity gradient was 87.8 s', the average permeate flux was 760 L/㎡h and the membrane pore size was 0.2 m.
Self-adjusting on-line cutting condition for high-speed milling process
Tien-Dung Hoang,Quang-Vinh Nguyen,Van-Cuong Nguyen,Ngoc-Hien Tran 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.8
The paper presents an intelligent control system for self-adjusting on-line cutting condition for high speed machining (self-HSM) with considering the tool-wear amount to keep the machined product’s quality in allowable limit. For realizing the self-HSM, the empirical analysis of variance (ANOVA) and artifical neural network (ANN) are used. The ANOVA is used for generating the empirical functions which are used as the boundary condition as well as constraint evaluation. The ANN is used for generating the new optimal cutting condition. Then, the self-HSM updates this cutting condition on the real machine - HS Super MC500. The new optimal cutting parameter is sent to the controller for updating the new machining condition to keep the machined part’s quality. The integration of the empirical analysis and ANN enables generating the optimal cutting parameters correctly and efficiently for high-speed milling.
Sukanyah Shanmuganathan,Tien Vinh Nguyen,W.G. Shim,Jaya Kandasamy,Andrzej Listowski,Saravanamuthu Vigneswaran 한국공업화학회 2014 Journal of Industrial and Engineering Chemistry Vol.20 No.6
Applying pre-treatments to remove dissolved organic matter from reverse osmosis (RO) feed can help toreduce organic fouling of the RO membrane. In this study the performance of granular activated carbon(GAC), a popular adsorbent, and purolite A502PS, an anion exchange resin, in removing effluent organicmatter (EfOM) from RO feed collected from a water reclamation plant located at Sydney Olympic Park,Australia were evaluated and compared through adsorption equilibrium, kinetics and fluidized bedexperiments. The maximum adsorption capacity (Qmax) of GAC calculated from the Langmuir model withRO feed was 13.4 mg/g GAC. The operational conditions of fluidized bed columns packed with GAC andpurolite A502PS strongly affected the removal of EfOM. GAC fluidized bed with a bed height of 10cm andfluidization velocity of 5.7 m/h removed more than 80% of dissolved organic carbon (DOC) during a 7 hexperiment. The average DOC removal was 60% when the bed height was reduced to 7 cm. Whencomparing GAC with purolite A502PS, more of the laterwas required to remove the same amount of DOC. The poorer performance of purolite A502PS can be explained by the competition provided by otherinorganic anions present in RO feed. A plug flow model can be used to predict the impact of the amount ofadsorbent and of the flow rate on removal of organic matter from the fluidized bed column.
BONEcheck: A digital tool for personalized bone health assessment
Dinh Tan Nguyen,Thao P. Ho-Le,Liem Pham,Vinh P. Ho-Van,Tien Dat Hoang,Thach S. Tran,Steve Frost,Tuan V. Nguyen 대한골다공증학회 2023 Osteoporosis and Sarcopenia Vol.9 No.3
Objectives: Osteoporotic fracture is a significant public health burden associated with increased mortality risk and substantial healthcare costs. Accurate and early identification of high-risk individuals and mitigation of their risks is a core part of the treatment and prevention of fractures. Here we introduce a digital tool called 'BONEcheck' for personalized assessment of bone health. Methods: The development of BONEcheck primarily utilized data from the prospective population-based Dubbo Osteoporosis Epidemiology Study and the Danish Nationwide Registry. BONEcheck has 3 modules: input data, risk estimates, and risk context. Input variables include age, gender, prior fracture, fall incidence, bone mineral density (BMD), comorbidities, and genetic variants associated with BMD. Results: Based on the input variables, BONEcheck estimates the probability of any fragility fracture and hip fracture within 5 years, subsequent fracture risk, skeletal age, and time to reach osteoporosis. The probability of fracture is shown in both numeric and human icon array formats. The risk is also contextualized within the framework of treatment and management options on Australian guidelines, with consideration given to the potential fracture risk reduction and survival benefits. Skeletal age was estimated as the sum of chronological age and years of life lost due to a fracture or exposure to risk factors that elevate mortality risk. Conclusions: BONEcheck is an innovative tool that empowers doctors and patients to engage in wellinformed discussions and make decisions based on the patient's risk profile. Public access to BONEcheck is available via https://bonecheck.org and in Apple Store (iOS) and Google Play (Android).
Han Thi Vo,Tien Duc Dao,Tuyen Van Duong,Tan Thanh Nguyen,Binh Nhu Do,Tinh Xuan Do,Khue Minh Pham,Vinh Hai Vu,Linh Van Pham,Lien Thi Hong Nguyen,Lan Thi Huong Le,Hoang Cong Nguyen,Nga Hoang Dang,Trung 질병관리청 2024 Osong Public Health and Research Persptectives Vol.15 No.1
Objectives: The incidence of posttraumatic stress disorder (PTSD) has increased, particularly among individuals who have recovered from coronavirus disease 2019 (COVID-19) infection. Health literacy is considered a “social vaccine” that helps people respond effectively to the pandemic. We aimed to investigate the association between long COVID-19 and PTSD, and to examine the modifying role of health literacy in this association.Methods: A cross-sectional study was conducted at 18 hospitals and health centers in Vietnam from December 2021 to October 2022. We recruited 4,463 individuals who had recovered from COVID-19 infection for at least 4 weeks. Participants provided information about their sociodemographics, clinical parameters, health-related behaviors, health literacy (using the 12-item short-form health literacy scale), long COVID-19 symptoms and PTSD (Impact Event Scale-Revised score of 33 or higher). Logistic regression models were used to examine associations and interactions.Results: Out of the study sample, 55.9% had long COVID-19 symptoms, and 49.6% had PTSD. Individuals with long COVID-19 symptoms had a higher likelihood of PTSD (odds ratio [OR], 1.68; 95% confidence interval [CI], 1.63–2.12; p<0.001). Higher health literacy was associated with a lower likelihood of PTSD (OR, 0.98; 95% CI, 0.97–0.99; p=0.001). Compared to those with long COVID-19 symptoms and the lowest health literacy score, those with long COVID-19 symptoms and a 1-point health literacy increment had a 3% lower likelihood of PTSD (OR, 0.97; 95% CI, 0.96–0.99; p=0.001).Conclusion: Health literacy was found to be a protective factor against PTSD and modified the negative impact of long COVID-19 symptoms on PTSD.
Jeong, Sanghyun,Choi, Yong Jun,Nguyen, Tien Vinh,Vigneswaran, Saravanamuthu,Hwang, Tae Moon Elsevier 2012 Journal of membrane science Vol.411 No.-
<P><B>Highlights</B></P><P>► Submerged membrane hybrid system (SMHS) with FeCl<SUB>3</SUB> flocculation and/or PAC adsorption. ► Low doses of ferric 0.5mg/L, PAC 0.5g/L removed 72% of DOC, reduced 5 times of UF-MFI. ► Both hydrophobic and hydrophilic compounds were significantly removed by hybrid system. ► 3 membrane fouling models (pore blockage, pore constriction, cake formation) were used. ► Among the 3 models, cake formation was found to be dominant in SMHS.</P> <P><B>Abstract</B></P><P>Three different submerged membrane hybrid systems (SMHSs) namely submerged membrane coagulation hybrid system (SMCHS), submerged membrane adsorption hybrid system (SMAHS), and submerged membrane coagulation–adsorption hybrid system (SMCAHS) were studied as pretreatment systems to seawater reverse osmosis (SWRO). The performances of these SMHSs were compared with that of submerged membrane system (without any coagulation or adsorption) in terms of trans-membrane pressure (TMP) development, critical flux, ultrafilter modified fouling index (UF-MFI), dissolved organic carbon (DOC) removal efficiency, and the removal of detailed organic fractions. The experimental results show that pretreatment by SMCAHS led to the best results in terms of organic removal and critical flux. With the low doses of ferric chloride (FeCl<SUB>3</SUB>) and powder activated carbon (PAC) of 0.5mg of Fe<SUP>3+</SUP>/L and 0.5g of PAC/L, respectively, this hybrid system could remove 72% of DOC and reduce the UF-MFI nearly five times. The initial DOC and UF-MFI of seawater used in this study were 2.53mg/L and 14,165s/L<SUP>2</SUP>, respectively. The application of three different membrane fouling models namely pore blockage, pore constriction, and cake formation models showed that cake formation was the predominant fouling mechanisms causing fouling in SMHSs.</P>