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Nguyen Duy Dat,Ton That Loc,Mai Thuan Trieu,Dong Thanh Nguyen,Khuong Quoc Nguyen,My Linh Nguyen,Anh Duy Duong Le,Hai Nguyen Tran 한국화학공학회 2022 Korean Journal of Chemical Engineering Vol.39 No.4
Two new composites from synthetic clay-like materials and carbon spheres were developed. Layered doubledhydroxides (LDH) were synthesized from the coprecipitation of Mg2+ and Al3+ ions. Spherical hydrochar (SH) wasprepared from pure glucose through hydrothermal carbonization at 190 oC. The composite LDH–SH was synthesizedthrough a simple hydrothermal method of the mixture of LDH and SH. Another composite, LDO-SB, was directly preparedthrough the carbonization of LDH-SH at 500 oC. Under such high temperature, LDH was converted to layereddoubled oxides (LDO), and SH was transferred to spherical biochar (SB). Those materials were characterized by chemicalstability, surface morphology and element composition, crystal structure, surface functional group, and texturalcharacteristic. They were applied for removing cationic dye (methylene blue; MB) and anionic dye (Congo red; CR)under different pH solutions. Three adsorption components—kinetics, isotherm, and thermodynamics—were conductedunder batch experimenters. Results demonstrated that the LDH or LDO particles were assembled on the surfaceof SH or SB, respectively. The surface area, total pore volume, and average pore width of LDH–SH and LDO-SBwere 58.5 and 198m2/g, 0.319 and 0.440 cm3/g, and 21.8 and 8.89 nm, respectively. The maximum adsorption capacityof the materials, calculated from the Langmuir model, at 30 oC for CR and MB dyes was 1589 and 78.6mg/g (LDOSB)and 499 and 226mg/g (LDH-SH), respectively. The composites exhibited a higher affinity to anionic than cationicdyes, which resulted from the great contribution of the clay-like materials. Therefore, they can serve as a promisingcomposite for the decolorization of wastewater.
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NGO, Chi Thanh,NGUYEN, Thi Ngoc Mai,NGUYEN, Duy Dat,LE, Hoang Ba Huyen,LE, Van Cuong,LE, Thi Binh Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.9
The study aims to investigate factors affecting enterprise's satisfaction and loyalty toward the Social Security's online public services, looking at the case of Thanh Hoa province, Vietnam. This study employs samples with 216 enterprises that use online public system of Thanh Hoa province's Social Security. The research model is closely linked to the SERVQUAL model developed by Parasuraman, Zeithaml and Berry (1988). We propose 23 scales that constitute the quality of service, three scales that constitute Customer Satisfaction and three components that constitute Customer Loyalty. This study use the tool of Exploratory Factor Analysis (EFA), Cronbach's Alpha test, Confirm Factor Analysis (CFA) and Structural Equation Modeling (SEM) in order to address the question of satisfaction and loyalty. The result shows that the factor with the most impact is Reliability, next is Capacity of staffs, Tangibles, Attitude of staffs, and the least impacting factor is Empathy; moreover, the results also show that Satisfaction has a strong impact on Customer Loyalty. The findings of this study suggest that Thanh Hoa province's Social Security should: (i) strengthen the reliability of online service system; (ii) build capacity for staffs; (iii) develop the responsiveness of electronic transactions systems; and (iv) improve the empathy of staffs.
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Truong Giang Nguyen,Thanh Khiem Nguyen,Ham Hoi Nguyen,Hong Son Trinh,Tuan Hiep Luong,Minh Trong Nguyen,Van Duy Le,Hai Dang Do,Kieu Hung Nguyen,Van Minh Do,Quang Huy Tran,Cuong Thinh Nguyen 한국간담췌외과학회 2024 Annals of hepato-biliary-pancreatic surgery Vol.28 No.1
Backgrounds/Aims: Parenchymal-sparing anatomical hepatectomy (Ps–AH) based on portal ramification of the right anterior section (RAS) is a new technique to avoid unnecessarily transecting too much liver parenchyma, especially in cases of major anatomical hepatectomy. Methods: We prospectively assessed 26 patients with primary hepatic malignancies having undergone major Ps–AH based on portal ramification of the RAS from August 2018 to August 2022 (48 months). The perioperative indications, clinical data, intra-operative index, pathological postoperative specimens, postoperative complications, and follow-up results were retrospectively evaluated. Results: Among the 26 patients analyzed, there was just one case that had intrahepatic cholangiocarcinoma The preoperative level of α– Fetoprotein was 25.2 ng/mL. All cases (100%) had Child–Pugh A liver function preoperatively. The ventral/dorsal RAS was preserved in 19 and 7 patients, respectively. The mean surgical margin was 6.2 mm. The mean surgical time was 228.5 minutes, while the mean blood loss was 255 mL. In pathology, 5 cases (19.2%) had microvascular invasion, and in the group of HCC patients, 92% of all cases had moderate or poor tumor differentiation. Six cases (23.1%) of postoperative complications were graded over III according to the Clavien–Dindo system, including in three patients resistant ascites or intra-abdominal abscess that required intervention. Conclusions: Parenchymal-sparing anatomical hepatectomy based on portal ramification of the RAS to achieve R0-resection was safe and effective, with favorable short-term outcomes. This technique can be used widely in clinical practice.
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Nguyen Ngoc Duy,Latsamy Xayavong,Nguyen Kim Uyen,Vinh Nguyen Thanh Pham,Tran Viet Nhan Hao 한국물리학회 2019 새물리 Vol.69 No.10
Nuclear physics is an obligatory subject for the general physics program of undergraduates in most of the natural science universities worldwide. In nuclear physics, the shell model is one of the most important models, and is well used to determine the spin-parity and the magnetic moment of a nucleus. Over ten years of teaching general physics, we have realize that most undergraduate students find calculating these parameters by using this shell model to be difficult due to the classification of the subshells and the intrinsic spin of nucleons. With the hope to help these students, in the present study, we introduce a graphical-user-interface (GUI) program to execute our selfdeveloped Shell Model Calculator (SMC) code written in the Visual Basic 6.0 (VB6) programming language. Our SMC validation results for the quantum quantities in a series of nuclei Z = 1 - 20 were compared with experimental data and found to be in good agreement. In general, we successfully developed an SMC program that can be used for teaching, learning, and researching nuclear physics in universities.
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Memory characteristics of poly-Si using MIC as an active layer on glass substrates
Nguyen, Thanh Nga,Jung, Sungwook,Nguyen, Van Duy,Yi, Junsin Institute of Physics [etc.] 2010 Journal of Physics. D, Applied Physics Vol.43 No.10
<P>In this paper the electrical properties of nonvolatile memory (NVM) using multi-stack gate insulators of oxide–nitride–oxynitride (ONOn) and an active layer of low temperature polycrystalline silicon (LTPS) were investigated. From hydrogenated amorphous silicon (a-Si : H), the LTPS thin film with a high crystalline fraction of 96% and a low surface roughness of 1.28 nm was fabricated by metal induced crystallization (MIC) with annealing conditions of 650 °C for 5 h on glass substrates. The LTPS thin film transistor or the NVM had a field effect mobility of (μ<SUB>FE</SUB>) 10 cm<SUP>2</SUP> V<SUP>−1</SUP> s<SUP>−1</SUP> and a threshold voltage (<I>V</I><SUB>TH</SUB>) of −3.5 V. The results demonstrated that the NVM had a memory window of 1.6 V with a programming and erasing (P/E) voltage of −14 V and 14 V in 1 ms. Moreover, retention properties of the memory were shown to exceed 80% after 10 years. Therefore, the LTPS fabricated by MIC has become a potential material for NVM application which is employed for the system integration of panel displays.</P>
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An Approximate DRAM Architecture for Energy-efficient Deep Learning
Nguyen, Duy Thanh,Chang, Ik-Joon The Institute of Semiconductor Engineers 2020 Journal of semiconductor engineering Vol.1 No.1
We present an approximate DRAM architecture for energy-efficient deep learning. Our key premise is that by bounding memory errors to non-critical information, we can significantly reduce DRAM refresh energy without compromising recognition accuracy of deep neural networks. To validate the key premise, we make extensive Monte-Carlo simulations for several well-known convolutional neural networks such as LeNet, ConvNet and AlexNet with the input of MINIST, CIFAR-10, and ImageNet, respectively. We assume that the highest-order 8-bits (in single precision) and 4-bits (in half precision) are protected from retention errors under the proposed architecture and then, randomly inject bit-errors to unprotected bits with various bit-error-rates. Here, recognition accuracies of the above convolutional neural networks are successfully maintained up to the 10<sup>-5</sup>-order bit-error-rate. We simulate DRAM energy during inference of the above convolutional neural networks, where the proposed architecture shows the possibility of considerable energy saving up to 10 ~ 37.5% of total DRAM energy.
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