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Search Results: 1 - 10 of 3251 matches for " Cong Khanh Huynh "
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Generation of polycyclic aromatic hydrocarbons (PAHs) during woodworking operations
Evin D. Bruschweiler,Cong Khanh Huynh,Pascal Wild,Philippe Boiteux,Nancy B. Hopf
Frontiers in Oncology , 2012, DOI: 10.3389/fonc.2012.00148
Abstract: Occupational exposures to wood dust have been associated with an elevated risk of sinonasal cancer (SNC). Wood dust is recognized as a human carcinogen but the specific cancer causative agent remains unknown. One possible explanation is a co-exposure to; wood dust and polycyclic aromatic hydrocarbons (PAHs). PAHs could be generated during incomplete combustion of wood due to heat created by use of power tools. To determine if PAHs are generated from wood during common wood working operations, PAH concentrations in wood dust samples collected in an experimental chamber operated under controlled conditions were analyzed. In addition, personal air samples from workers exposed to wood dust (n = 30) were collected. Wood dust was generated using three different power tools: vibrating sander, belt sander, and saw; and six wood materials: fir, Medium Density Fiberboard (MDF), beech, mahogany, oak and wood melamine. Monitoring of wood workers was carried out by means of personal sampler device during wood working operations. We measured 21 PAH concentrations in wood dust samples by capillary gas chromatography-ion trap mass spectrometry (GC-MS). Total PAH concentrations in wood dust varied greatly (0.24–7.95 ppm) with the lowest being in MDF dust and the highest in wood melamine dust. Personal PAH exposures were between 37.5–119.8 ng m?3 during wood working operations. Our results suggest that PAH exposures are present during woodworking operations and hence could play a role in the mechanism of cancer induction related to wood dust exposure.
Case Report: Acute Fatty Liver of Pregnancy  [PDF]
Huynh Nguyen Khanh Trang, Hoang Thi Diem Tuyet
Open Journal of Obstetrics and Gynecology (OJOG) , 2017, DOI: 10.4236/ojog.2017.710102
Abstract: Acute fatty liver of pregnancy (AFLP) is a rare disease in Vietnam. Diagnosis by recorded literature is often difficult to distinguish from viral hepatitis, paraplegia, or bile duct disease, so AFLP diagnosis is often delayed. The prevalence of hepatitis B in Vietnam in pregnant women is estimated at 10% REF _Ref494526757 \r \h [1], preeclampsia is estimated at 0.2% REF _Ref494526760 \r \h [2]. A case pregnant woman has 35.5-week gestational age with AFLP, who was safely delivered both mother and infant at Hung Vuong hospital, Vietnam. A careful history and physical examination, in conjunction with compatible laboratory and ultrasound imaging results, are often sufficient to make the diagnosis, and liver biopsy is rarely indicated. Intensive adjuvant therapy and rapid birth control are essential for maternal and fetal outcomes.
Using Isotope Technology for Surface Water Environment Research in Southern Hanoi  [PDF]
Vo Thi Anh, Tran Khanh Minh, Trinh Van Giap, Ha Lan Anh, Nguyen Thanh Cong, Nguyen Hong Thinh, Vu Hoai
Journal of Environmental Protection (JEP) , 2016, DOI: 10.4236/jep.2016.78100
Abstract: The surface water in the southern of Hanoi capital is researched by identifying δ2H and δ18O stable isotopes together with EC, DO, BOD5, COD, TSS. Surface water samples for studying include the Red river, Nhue river and Kim Nguu river, Thanh Nhan lake, Yen So lake and Van Quan lake were collected in the dry season (April) and the rainy season (August) in 2015. The stable isotope analysis results showed that the δ18O values is a range from -42.53 to -64.05 and, the δ2H values is the range from -5.09 to -8.79 under global meteoric waterline (in the water vapor region). The δ2H results of the rivers and lakes in the dry season are more negative than the rainy season with a small difference. The δ18O results of lakes in the dry season are more negative than the rainy season, but the δ18O results of river in the dry season are more positive than the rainy season. The results of the EC, BOD, COD, DO, TSS analysis showed that surface water environment has changed clearly in the two seasons and the contamination level in the dry season is usually higher than the rainy season. The lakes and rivers strongly influenced by human activities led to seriously pollution are Van Quan lake and Yen So lake, Nhue river and Kim Nguu river.
Comparisons of VAR Model and Models Created by Genetic Programming in Consumer Price Index Prediction in Vietnam  [PDF]
Pham Van Khanh
Open Journal of Statistics (OJS) , 2012, DOI: 10.4236/ojs.2012.23029
Abstract: In this paper, we present an application of Genetic Programming (GP) to Vietnamese CPI in?ation one-step prediction problem. This is a new approach in building a good forecasting model, and then applying inflation forecasts in Vietnam in current stage. The study introduces the within-sample and the out-of-samples one-step-ahead forecast errors which have positive correlation and approximate to a linear function with positive slope in prediction models by GP. We also build Vector Autoregression (VAR) model to forecast CPI in quaterly data and compare with the models created by GP. The experimental results show that the Genetic Programming can produce the prediction models having better accuracy than Vector Autoregression models. We have no relavant variables (m2, ex) of monthly data in the VAR model, so no prediction results exist to compare with models created by GP and we just forecast CPI basing on models of GP with previous data of CPI.
Optimal Stopping Time for Holding an Asset  [PDF]
Pham Van Khanh
American Journal of Operations Research (AJOR) , 2012, DOI: 10.4236/ajor.2012.24062
Abstract: In this paper, we consider the problem to determine the optimal time to sell an asset that its price conforms to the Black-Schole model but its drift is a discrete random variable taking one of two given values and this probability distribution behavior changes chronologically. The result of finding the optimal strategy to sell the asset is the first time asset price falling into deterministic time-dependent boundary. Moreover, the boundary is represented by an increasing and continuous monotone function satisfying a nonlinear integral equation. We also conduct to find the empirical optimization boundary and simulate the asset price process.
The First Order Autoregressive Model with Coefficient Contains Non-Negative Random Elements: Simulation and Esimation  [PDF]
Pham Van Khanh
Open Journal of Statistics (OJS) , 2012, DOI: 10.4236/ojs.2012.25064
Abstract: This paper considered an autoregressive time series where the slope contains random components with non-negative values. The authors determine the stationary condition of the series to estimate its parameters by the quasi-maximum likelihood method. The authors also simulates and estimates the coefficients of the simulation chain. In this paper, we consider modeling and forecasting gold chain on the free market in Hanoi, Vietnam.
Optimal Stopping Time to Buy an Asset When Growth Rate Is a Two-State Markov Chain  [PDF]
Pham Van Khanh
American Journal of Operations Research (AJOR) , 2014, DOI: 10.4236/ajor.2014.43013

In this paper we consider the problem of determining the optimal time to buy an asset in a position of an uptrend or downtrend in the financial market and currency market as well as other markets. Asset price is modeled as a geometric Brownian motion with drift being a two-state Markov chain. Based on observations of asset prices, investors want to detect the change points of price trends as accurately as possible, so that they can make the decision to buy. Using filtering techniques and stochastic analysis, we will develop the optimal boundary at which investors implement their decisions when the posterior probability process reaches a certain threshold.

When to Sell an Asset Where Its Drift Drops from a High Value to a Smaller One  [PDF]
Pham Van Khanh
American Journal of Operations Research (AJOR) , 2015, DOI: 10.4236/ajor.2015.56040

To solve the selling problem which is resembled to the buying problem in [1], in this paper we solve the problem of determining the optimal time to sell a property in a location the drift of the asset drops from a high value to a smaller one at some random change-point. This change-point is not directly observable for the investor, but it is partially observable in the sense that it coincides with one of the jump times of some exogenous Poisson process representing external shocks, and these jump times are assumed to be observable. The asset price is modeled as a geometric Brownian motion with a drift that initially exceeds the discount rate, but with the opposite relation after an unobservable and exponentially distributed time and thus, we model the drift as a two-state Markov chain. Using filtering and martingale techniques, stochastic analysis transform measurement, we reduce the problem to a one-dimensional optimal stopping problem. We also establish the optimal boundary at which the investor should liquidate the asset when the price process hit the boundary at first time.

Assessment of Microalbuminuria for Early Diagnosis and Risk Prediction in Dengue Infections
Nguyen Thi Hanh Tien, Phung Khanh Lam, Huynh Thi Le Duyen, Tran Van Ngoc, Phan Thi Thanh Ha, Nguyen Tan Thanh Kieu, Cameron Simmons, Marcel Wolbers, Bridget Wills
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0054538
Abstract: Background Dengue is the most important arboviral infection of humans. Following an initial febrile period, a small proportion of infected patients develop a vasculopathy, with children at particular risk for severe vascular leakage and shock. Differentiation between dengue and other common childhood illnesses is difficult during the early febrile phase, and risk prediction for development of shock is poor. The presence of microalbuminuria is recognized as a useful early predictor for subsequent complications in a number of other disorders with vascular involvement. Significant proteinuria occurs in association with dengue shock syndrome and it is possible that early-phase microalbuminuria may be helpful both for diagnosis of dengue and for identification of patients likely to develop severe disease. Methodology/Principal Findings We measured formal urine albumin to creatinine ratios (UACRs) in daily samples obtained from a large cohort of children with suspected dengue recruited at two outpatient clinics in Ho Chi Minh City, Vietnam. Although UACRs were increased in the 465 confirmed dengue patients, with a significant time trend showing peak values around the critical period for dengue-associated plasma leakage, urine albumin excretion was also increased in the comparison group of 391 patients with other febrile illnesses (OFI). The dengue patients generally had higher UACRs than the OFI patients, but microalbuminuria, using the conventional cutoff of 30 mg albumin/g creatinine discriminated poorly between the two diagnostic groups in the early febrile phase. Secondly UACRs did not prove useful in predicting either development of warning signs for severe dengue or need for hospitalization. Conclusion/Significance Low-level albuminuria is common, even in relatively mild dengue infections, but is also present in many OFIs. Simple point-of-care UACR tests are unlikely to be useful for early diagnosis or risk prediction in dengue endemic areas.
Student-based Collaborative Network for Delivering Information of Natural Disasters and Climate Adaptation
Chien Huynh,Phuong Huynh
Computer Science , 2013,
Abstract: The student generation nowadays is considered as the Net Generation who grow up in the age of Internet and mobile technology and prefer bringing technological application into their life. The Learning Resource Center, an academic information center, takes the initiative in developing a collaborative network with the participation of students for delivering information of natural disasters and climate adaptation to the people who live in the vulnerable areas of Thua Thien Hue province. The network is aimed at helping local people mitigating vulnerabilities and adapting to the globally climate change for a better life.
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