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Ying Chen,1,2,* Wen-Xia Li,1,2,* Jia-Hua Wu,1,2 Geng-Hang Chen,2 Chun-Min Yang,1,2 Hai Lu,1,2 Xi Wang,3 Shu-Sen Wang,4 Heng Huang,5 Li Cai,6 Li Zhao,7 Rou-Jun Peng,8 Ying Lin,9 Jun Tang,3 Jian Zeng,10 Le-Hong Zhang,11 Yong-Li Ke,12 Xian-Ming Wang,13 Xin-Mei Liu,14 An-Qin Zhang,15 Fei Xu,4 Xi-Wen Bi,4 Jia-Jia Huang,4 Ji-Bin Li,16 Dan-Mei Pang,17 Cong Xue,4 Yan-Xia Shi,4 Zhen-Yu He,18 Huan-Xin Lin,18 Xin An,4 Wen Xia,4 Ye Cao,16 Ying Guo,16 Ruo-Xi Hong,4 Kui-Kui Jiang,4 Yong-Yi Zhong,4 Ge Zhang,19 Piyawan Tienchaiananda,20 Masahiro Oikawa,21 Zhong-Yu Yuan,4 Qian-Jun Chen22,23 1Department of Breast Surgery, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, People’s Republic of China; 2Department of Breast Surgery, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, People’s Republic of China; 3Department of Breast Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China; 4Department of Medical Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China; 5Department of Breast Oncology, Lianjiang People’s Hospital, Lianjiang, People’s Republic of China; 6Department of Medical Oncology, The Affiliated Tumour Hospital of Harbin Medical University, Harbin, People’s Republic of China; 7Department of Breast Oncology, Guangzhou First People Hospital, Guangzhou, People’s Republic of China; 8Department of Integrated Therapy in Oncology, Sun Yat-sen University Cancer Center, the State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, People’s Republic of China; 9Department of Breast Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, People’s Re

In this research, the developing process of a piezoresistive pressure sensor working in the atmosphere environment applied in micro aerial vehicle using the MEMS fabrication method is introduced. The sensor consists of four Au/Cr piezoresistors in a Wheatstone bridge configuration on a wet oxidized silicon diaphragm. To fabricate the sensor, three lithographic steps were conducted: the first one is to define the resistors and Au/Cr lines/pads, the second and the third ones are to determine the width and the thickness of the square SiO2/Si diaphragm, respectively. The sensor diaphragm shape and thickness were defined by the anisotropic etching of Si in tetramethylammonium hydroxide (TMAH) solution, and the resistors array are formed by sputtering and wet etching method. The sensor size is ~6000 µm by 6000 µm. The sensor output voltage was measured for various applied pressure levels from 0 to 1.2 bar with 5V voltage supply. The fabricated sensor also exhibits a sensitivity of 50.01 mV/bar.

Purpose: This paper summarized and systematized the case of China's policies applied to attract angel investment which turned this country into a global highlight in angel investment. Theoretical framework: The authors conducted a literature review on start-up and angel investment to introduce angel investment in China, analyze the role of angel investments in developing start-ups, and factor determinants and policy of angel investment in China. Design/Methodology/Approach: This paper uses qualitative method to provide overviews on the case of China in attracting angel investment for their start-ups with an updated analysis on their relevant factor determinants and policies that contributed to the success of China. Findings: It is found that the Chinese Government has actively carried out packages, including tax incentives, built programs, investment cooperation funds, developed networks, and angel investment education systems to boost funding readiness for firms. They also focus on promoting the start-up ecosystem and providing financial support to implement an innovation-driven development strategy to raise the nation's competitiveness. Research, practical & social implications: This paper provides some suggestions for Chinese government in making policies to enhance the role of angel investments in developing start-ups. Originality/Value: This paper contributes to the evolvement of research about start- up and angel investment, particularly in China, in the context of high-tech production and breakthrough technologies, by providing a policy perspective to imply lessons for other countries.

In this paper, we present a robust and low complexity deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the scene of a remote sensing image. In particular, we firstly evaluate different low complexity and benchmark deep neural networks: MobileNetV1, MobileNetV2, NASNetMobile, and EfficientNetB0, which present the number of trainable parameters lower than 5 Million (M). After indicating best network architecture, we further improve the network performance by applying attention schemes to multiple feature maps extracted from middle layers of the network. To deal with the issue of increasing the model footprint as using attention schemes, we apply the quantization technique to satisfy the maximum of 20 MB memory occupation. By conducting extensive experiments on the benchmark datasets NWPU-RESISC45, we achieve a robust and low-complexity model, which is very competitive to the state-of-the-art systems and potential for real-life applications on edge devices., Comment: 8 pages

Semantic communication has emerged as the breakthrough beyond the Shannon theorem by transmitting and receiving semantic information instead of data bits or symbols regardless of its content. This paper proposes a two-stage reconstruction process to boost the system's performance. In the first phase, the image information is first decoded from the noisy received data by exploiting the channel knowledge. The decoded image is enhanced by a post-filter and image statistics. Different metrics are exploited to evaluate the image restoration quality of our considered model. Numerical results are obtained using natural images that verify the superior improvements of the proposed two-stage reconstruction process over the traditional decoded data. Moreover, the different metrics assessing the system performance based on their criteria can be conflicted with each other., Comment: 6 pages, 5 figures. Accepted by the IEEE ATC 2022

Human detection is a popular issue and has been widely used in many applications. However, including complexities in computation, leading to the human detection system implemented hardly in real-time applications. This paper presents the architecture of hardware, a human detection system that was simulated in the ModelSim tool. As a co-processor, this system was built to off-load to Central Processor Unit (CPU) and speed up the computation timing. The 130x66 RGB pixels of static input image attracted features and classify by using the Histogram of Oriented Gradient (HOG) algorithm and Support Vector Machine (SVM) algorithm, respectively. As a result, the accuracy rate of this system reaches 84.35 percent. And the timing for detection decreases to 0.757 ms at 50MHz frequency (54 times faster when this system was implemented in software by using the Matlab tool).

The convex rope problem is to find a counterclockwise or clockwise convex rope starting at the vertex a and ending at the vertex b of a simple polygon P, where a is a vertex of the convex hull of P and b is visible from infinity. The convex rope mentioned is the shortest path joining a and b that does not enter the interior of P. In this paper, the problem is reconstructed as the one of finding such shortest path in a simple polygon and solved by the method of multiple shooting. We then show that if the collinear condition of the method holds at all shooting points, then these shooting points form the shortest path. Otherwise, the sequence of paths obtained by the update of the method converges to the shortest path. The algorithm is implemented in C++ for numerical experiments., Comment: 21 pages, 10 figures, added references for the proof of Theorem 3 Corrected some spelling errors and replace some figures

Effective eutrophication control, especially for decentralized wastewater treatment, has received increasing attention in recent years. In view of this, iron oxide coated sand (IOS) granules, a recycled waste product from the drinking water industry, was investigated for phosphorus removal from goat farm wastewater, both at laboratory-scale and at full-scale. Brunauer-Emmett-Teller adsorption revealed a high specific surface area (249 m2/g) of the IOS. Fourier Transform Infrared Spectroscopy and X-ray Diffraction demonstrated that Fe(III) compounds are the main functional component and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy showed that Fe and O elements covered more than 84% of the surface of the IOS. The IOS granules showed good phosphorus adsorption capacity over a wide pH range during laboratory-scale batch tests. Moreover, the phosphorus adsorption was very fast and the residual phosphorus concentration dropped below 0.02 mg/L within an hour at a dosage of 20 g/L. After adsorption, the exhausted IOS could be regenerated by using 0.5 M KOH, and more than 80% adsorption capacity remained. Laboratory-scale column tests with real wastewater originating from a goat farm were run and Bed Depth Service Time and Bohart–Adams models were applied in view of scale-up. Based on this, a full-scale IOS based fixed bed reactor was designed, built and tested at a goat farm. A TP removal efficiency of 99% with a 0.87 m3 IOS fixed bed reactor (fed at 2.2 m3/d) was obtained. The TP concentration in the effluent remained below 0.3 mg/L for nearly 400 days, achieving long term TP removal. This study demonstrates that IOS based treatment is an ecological and environmentally friendly method, suitable for full-scale (decentralized) wastewater treatment.

Objectives This study quantified the secondhand smoke (SHS) concentration in a sample of public places in Vietnam to determine changes in SHS levels 5 years after a public smoking ban was implemented. Methods Two monitoring campaigns, one in 2013 (before the tobacco control law was implemented) and another in 2018 (5 years after the implementation of the law) were conducted in around 30 restaurants, cafeterias and coffee shops in major cities of Vietnam. Concentrations of PM2.5, as an indicator of SHS, were measured by portable particulate matter monitors (TSI SidePak AM510 and Air Visual Pro). Results The geometric mean PM2.5 concentration of all monitored venues was 87.7 µg/m3 (83.7–91.9) in the first campaign and 55.2 µg/m3 (53.7–56.7) in the second campaign. Pairwise comparison showed the PM2.5 concentrations in the smoking observed area was triple and double those in the non-smoking area and the outdoor environment. After adjusting for sampling locations and times, the SHS concentration 5 years after the implementation of the tobacco control law reduced roughly 45%. Conclusion The study results indicate an improvement in air quality in public places in Vietnam via both the reduction in PM2.5 levels and the number of people observed smoking. However, greater enforcement of the free-smoke legislation is needed to eliminate SHS in public places in Vietnam.

Through the implementation of the topic tourism post COVID-19: Sustainable Tourism as a solution, the researcher has focused on researching and solving the following issues: Systematizing the theoretical foundations of tourist development and sustainable tourism development and identify variables influencing sustainable tourism development. Analyzing the Vietnam tourism sector during the COVID-19 era and assessing the present state of tourism development in Danang in all aspects, including the number of visitors, travel services, accommodation, retail, entertainment, human resources, and promotion activities. Simultaneously, evaluating the existing state of city tourist growth from the standpoint of long-term development. The emphasis is placed on analyzing the feasible elements, flaws, and problems that must be addressed to promote sustainable tourism..

Eurofleets+ is a consortium of 42 research vessel operators aiming to provide access to ship-time for high-quality marine campaigns, including equipment and remote sampling access. From the start, the project has given data management a central place. This approach acknowledges the important drivers of efficient data management: a) broad acquisition by means of a data management plan, b) adequate transformation by software agents and c) integrating the exchange technology used by data repositories such as SeaDataCloud, all three designed to work together. [...]

This paper presents a study of roughness of surface of centreless grinding workpiece with horizontal feed. The testing material used in this study is SAE1045 steel. This study was conducted with three main contents. The first one is an experimental study that determines the impact of dressing feed rate, depth of dressing, horizontal feed rate and the velocity of control wheel to roughness of workpiece surface. The second one is to build the roughness model of workpiece surface by the response surface method. The third one is to use the roughness model to predict the surface roughness, and compare with roughness value when testing. The issues that need to be carried out in subsequent studies have also been mentioned in this paper.

This paper aims to investigate the influence of credit risk management on bank performance, thereby compare the influence of credit risk management between stateowned banks and private banks in Vietnam. A sample of 15 listed banks from 2009 to 2018 is used and a Mundlak approach is employed to examine the search objective. Overall, the finding supports the importance of credit risk management on bank performance, but shows an ambiguous result regarding the influence of credit riskmanagement between state-owned banks and private banks in Vietnam.

The recent rapid advancement of Internet coverage as well as easier access to Internetconnected computational mobile devices like smartphones have given us the opportunity to resolve some existing problems in university, one of which is the lack of an scheduling system for appointments for students and professors/counsellors/university offices. This project attempt to create a system to tackle the problem, including a client mobile application and a REST API.

Storytelling, which is often promoted as a suitable methodological approach in teaching young learners, has been under-used and under-researched in EFL primary schools. This study introduces a storytelling innovation to put the young learner-oriented approach in practice. The innovation provides a structure to redesign textbook lessons into storytelling lessons in order to offer young learners interactive opportunities to use language in meaningful contexts. The research was conducted in two phases. The first phase employed a qualitative approach to examine the current state of using stories and storytelling in teaching EFL in state primary schools in Vietnam. This phase involved the participation of 21 teachers and groups of Grade 5 students from 18 primary schools. Classroom observations, in-depth interviews with teachers, and group interviews with students were conducted to collect data. The results showed that stories were mainly used to introduce target language items in the presentation stage of the textbook lessons which had a presentation-practice-production structure. The lessons consisted mainly of mechanical practice and, ineffective group work, and afforded learners few opportunities for interactive activities. The second phase was an intervention study to examine the implementation of storytelling innovation lessons. Two teachers and two classes, who participated in Phase 1, joined Phase 2 of the study. One teacher and one class were used as the comparison group while the others employed the innovation for one teaching term. Data were collected from pre-and post-storytelling speaking tests, classroom observations, in-depth interviews with teachers, and group interviews with students. The quantitative findings revealed that at the end of the study the intervention group significantly outperformed the comparison group in their oral language production. The qualitative data showed that the students in the intervention group were highly engaged in storytell

This paper describes our study on using mutilingual BERT embeddings and some new neural models for improving sequence tagging tasks for the Vietnamese language. We propose new model architectures and evaluate them extensively on two named entity recognition datasets of VLSP 2016 and VLSP 2018, and on two part-of-speech tagging datasets of VLSP 2010 and VLSP 2013. Our proposed models outperform existing methods and achieve new state-of-the-art results. In particular, we have pushed the accuracy of part-of-speech tagging to 95.40% on the VLSP 2010 corpus, to 96.77% on the VLSP 2013 corpus; and the F1 score of named entity recognition to 94.07% on the VLSP 2016 corpus, to 90.31% on the VLSP 2018 corpus. Our code and pre-trained models viBERT and vELECTRA are released as open source to facilitate adoption and further research., Comment: Accepted at the Conference PACLIC 2020

The FPT.AI team participated in the SHINRA2020-ML subtask of the NTCIR-15 SHINRA task. This paper describes our method to solving the problem and discusses the official results. Our method focuses on learning cross-lingual representations, both on the word level and document level for page classification. We propose a three-stage approach including multilingual model pre-training, monolingual model fine-tuning and cross-lingual voting. Our system is able to achieve the best scores for 25 out of 30 languages; and its accuracy gaps to the best performing systems of the other five languages are relatively small., Comment: Accepted to NTCIR-15

The paper presents the results of analyzing the relationship between cutting force components and the force components exerting on the workrest blade, the ratio of slip - acceleration of the rotation motion between the part and control wheel, translational motion acceleration of the part along the axial axis when longitudinal feed centerless grinding. From that, the method of calculating cutting force components is calculated by measuring the force components exerting on the workrest blade, the ratio of slip, cceleration of the rotation motion between the part with control wheel, translational motion acceleration of the part along the axial axis. On that basis, this research also provides orientation for the construction of a system to measure the force, acceleration, velocity components, ... Then the development direction for the next research is also mentioned in the article.

Background: Considerable progress has been made in dengue management, however the lack of appropriate predictors of severity has led to huge number of unwanted admissions mostly decided on the grounds of warning signs. Apoptosis related mediators,among others, are known to correlate with severe dengue (SD) although no predictive validity is established. The objective of this study was to investigate the association of plasma cell-free DNA (cfDNA) with SD, and evaluate its prognostic value in SD prediction at acute phase. Methods: This was a hospital-based prospective cohort study conducted in Vietnam.All the recruited patients were required to be admitted to the hospital and were strictly monitored for various laboratory and clinical parameters(including progression to SD) until discharged. Plasma samples collected during acute phase (6-48 h before defervescence) were used to estimate the level of cfDNA. Results: Of the 61 dengue patients,SD patients (n = 8)developed shock syndrome in 4.8 days (95% CI 3.7-5.4) after the fever onset. Plasma cfDNA levels before the defervescence of SD patients were significantly higher than the non-SD group (p = 0.0493). From the receiver operating characteristic (ROC) curve analysis, a cut-off of > 36.9 ng/mL was able to predict SD with a good sensitivity (87.5%), specificity (54.7%), and area under the curve (AUC) (0.72, 95% CI 0.55-0.88; p = 0.0493).Conclusions: Taken together, these findings suggest that cfDNA could serve as a potential prognostic biomarker of SD. Studies with cfDNA kinetics and its combination with other biomarkers and clinical parameters would further improve the diagnostic ability for SD., Annals of Clinical Microbiology and Antimicrobials, 18(1), art.no.10; 2019

This work investigates the task-oriented dialogue problem in mixed-domain settings. We study the effect of alternating between different domains in sequences of dialogue turns using two related state-of-the-art dialogue systems. We first show that a specialized state tracking component in multiple domains plays an important role and gives better results than an end-to-end task-oriented dialogue system. We then propose a hybrid system which is able to improve the belief tracking accuracy of about 28% of average absolute point on a standard multi-domain dialogue dataset. These experimental results give some useful insights for improving our commercial chatbot platform FPT.AI, which is currently deployed for many practical chatbot applications., Comment: Accepted for conference PACLING 2019

Objectives Food composition data are key for many nutrition related activities in research, planning and policy. Combatting micronutrient malnutrition among women and young children using sustainable food based approaches, as aimed at in the SMILING project, requires high quality food composition data. Methods In order to develop capacity and to align procedures for establishing, updating and assessing the quality of key nutrient data in the food composition tables in Southeast Asia, a detailed roadmap was developed to identify and propose steps for this. This included a training workshop to build capacity in the field of food composition data, and alignment of procedures for selecting foods and nutrients to be included for quality assessment, and update of country specific food composition tables. The SEA partners in the SMILING project finalised a country specific food composition table (FCT) with updated compositional data on selected foods and nutrients considered key for designing nutrient dense and optimal diets for the target groups. Results Between 140 and 175 foods were selected for inclusion in the country specific FCTs. Key-nutrients were: energy, protein, total fat, carbohydrates, iron, zinc, (pro-)-vitamin A, folate, calcium, vitamin D, vitamin B1, vitamin B2, vitamin B3, vitamin B6, vitamin B12 and vitamin C. A detailed quality assessment on 13 key-foods per nutrient was performed using international guidelines. Nutrient data for specific local food items were often unavailable and data on folate, vitamin B12 and vitamin B6 contents were mostly missing. For many foods, documentation was not available, thereby complicating an in-depth quality assessment. Despite these limitations, the SMILING project offered a unique opportunity to increase awareness of the importance of high quality well documented food composition data. Conclusion for Practise The self-reported data quality demonstrated that there is considerable room for improvement of the nutrient d

Background and aims: Management of familial hypercholesterolaemia (FH) may vary across different settings due to factors related to population characteristics, practice, resources and/or policies. We conducted a survey among the worldwide network of EAS FHSC Lead Investigators to provide an overview of FH status in different countries. Methods: Lead Investigators from countries formally involved in the EAS FHSC by mid-May 2018 were invited to provide a brief report on FH status in their countries, including available information, programmes, initiatives, and management. Results: 63 countries provided reports. Data on FH prevalence are lacking in most countries. Where available, data tend to align with recent estimates, suggesting a higher frequency than that traditionally considered. Low rates of FH detection are reported across all regions. National registries and education programmes to improve FH awareness/knowledge are a recognised priority, but funding is often lacking. In most countries, diagnosis primarily relies on the Dutch Lipid Clinics Network criteria. Although available in many countries, genetic testing is not widely implemented (frequent cost issues). There are only a few national official government programmes for FH. Under-treatment is an issue. FH therapy is not universally reimbursed. PCSK9-inhibitors are available in ∼2/3 countries. Lipoprotein-apheresis is offered in ∼60% countries, although access is limited. Conclusions: FH is a recognised public health concern. Management varies widely across countries, with overall suboptimal identification and under-treatment. Efforts and initiatives to improve FH knowledge and management are underway, including development of national registries, but support, particularly from health authorities, and better funding are greatly needed.

This paper presents an extensive comparative study of four neural network models, including feed-forward networks, convolutional networks, recurrent networks and long short-term memory networks, on two sentence classification datasets of English and Vietnamese text. We show that on the English dataset, the convolutional network models without any feature engineering outperform some competitive sentence classifiers with rich hand-crafted linguistic features. We demonstrate that the GloVe word embeddings are consistently better than both Skip-gram word embeddings and word count vectors. We also show the superiority of convolutional neural network models on a Vietnamese newspaper sentence dataset over strong baseline models. Our experimental results suggest some good practices for applying neural network models in sentence classification., Comment: To appear in the 5th NAFOSTED Conference on Information and Computer Science

In this paper, we parameterize an excess loss-based multipath component (MPC) cross-polarization ratio (XPR) model in indoor and outdoor environments for above-6 GHz frequency bands. The results are based on 28 measurement campaigns in several frequency bands ranging from 15 to 80 GHz. A conventional XPR model of an MPC assuming a constant mean value fits our measurements very poorly and moreover overestimates the depolarization effect. Our measurements revealed a clear trend that the MPC XPR is inversely proportional to an excess loss in reference to the free-space path loss. The model is physically sound as a higher excess loss is attributed to more lossy interactions or to a greater number of interactions with objects, leading to a greater chance of depolarization. The measurements furthermore showed that the MPC XPR is not strongly frequency or environment dependent. In our MPC XPR model, an MPC with zero-dB excess loss has a mean XPR of 28 dB. The mean XPR decreases half-a-dB as the excess loss increases by every dB and the standard deviation around the mean is 6 dB. The model is applicable to existing channel models to reproduce realistic MPC XPRs for the above 6-GHz radio links., Comment: Submitted to IEEE Transactions on Wireless Communications

In this paper, we describe the development of an end-to-end factoid question answering system for the Vietnamese language. This system combines both statistical models and ontology-based methods in a chain of processing modules to provide high-quality mappings from natural language text to entities. We present the challenges in the development of such an intelligent user interface for an isolating language like Vietnamese and show that techniques developed for inflectional languages cannot be applied "as is". Our question answering system can answer a wide range of general knowledge questions with promising accuracy on a test set., Comment: In the proceedings of the HQA'18 workshop, The Web Conference Companion, Lyon, France

This paper presents an empirical study of two machine translation-based approaches for Vietnamese diacritic restoration problem, including phrase-based and neural-based machine translation models. This is the first work that applies neural-based machine translation method to this problem and gives a thorough comparison to the phrase-based machine translation method which is the current state-of-the-art method for this problem. On a large dataset, the phrase-based approach has an accuracy of 97.32% while that of the neural-based approach is 96.15%. While the neural-based method has a slightly lower accuracy, it is about twice faster than the phrase-based method in terms of inference speed. Moreover, neural-based machine translation method has much room for future improvement such as incorporating pre-trained word embeddings and collecting more training data., Comment: 4 pages, 2 figures, 4 tables, accepted to IALP 2017

This paper presents an empirical study of two widely-used sequence prediction models, Conditional Random Fields (CRFs) and Long Short-Term Memory Networks (LSTMs), on two fundamental tasks for Vietnamese text processing, including part-of-speech tagging and named entity recognition. We show that a strong lower bound for labeling accuracy can be obtained by relying only on simple word-based features with minimal hand-crafted feature engineering, of 90.65\% and 86.03\% performance scores on the standard test sets for the two tasks respectively. In particular, we demonstrate empirically the surprising efficiency of word embeddings in both of the two tasks, with both of the two models. We point out that the state-of-the-art LSTMs model does not always outperform significantly the traditional CRFs model, especially on moderate-sized data sets. Finally, we give some suggestions and discussions for efficient use of sequence labeling models in practical applications., Comment: To appear in the Proceedings of the 9th International Conference on Knowledge and Systems Engineering (KSE) 2017

This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity recognition (NER). Our toolkit is a combination of bidirectional Long Short-Term Memory (Bi-LSTM), Convolutional Neural Network (CNN), Conditional Random Field (CRF), using pre-trained word embeddings as input, which achieves state-of-the-art results on these three tasks. We provide both API and web demo for this toolkit., Comment: 4 pages, 5 figures, 6 tables, accepted to IJCNLP 2017

This paper presents a state-of-the-art system for Vietnamese Named Entity Recognition (NER). By incorporating automatic syntactic features with word embeddings as input for bidirectional Long Short-Term Memory (Bi-LSTM), our system, although simpler than some deep learning architectures, achieves a much better result for Vietnamese NER. The proposed method achieves an overall F1 score of 92.05% on the test set of an evaluation campaign, organized in late 2016 by the Vietnamese Language and Speech Processing (VLSP) community. Our named entity recognition system outperforms the best previous systems for Vietnamese NER by a large margin., Comment: 7 pages, 9 tables, 3 figures, accepted to PACLIC 2017

Short Message Service (SMS) spam is a serious problem in Vietnam because of the availability of very cheap pre-paid SMS packages. There are some systems to detect and filter spam messages for English, most of which use machine learning techniques to analyze the content of messages and classify them. For Vietnamese, there is some research on spam email filtering but none focused on SMS. In this work, we propose the first system for filtering Vietnamese spam SMS. We first propose an appropriate preprocessing method since existing tools for Vietnamese preprocessing cannot give good accuracy on our dataset. We then experiment with vector representations and classifiers to find the best model for this problem. Our system achieves an accuracy of 94% when labelling spam messages while the misclassification rate of legitimate messages is relatively small, about only 0.4%. This is an encouraging result compared to that of English and can be served as a strong baseline for future development of Vietnamese SMS spam prevention systems., Comment: 4 pages, IALP 2016

Semantic role labelling (SRL) is a task in natural language processing which detects and classifies the semantic arguments associated with the predicates of a sentence. It is an important step towards understanding the meaning of a natural language. There exists SRL systems for well-studied languages like English, Chinese or Japanese but there is not any such system for the Vietnamese language. In this paper, we present the first SRL system for Vietnamese with encouraging accuracy. We first demonstrate that a simple application of SRL techniques developed for English could not give a good accuracy for Vietnamese. We then introduce a new algorithm for extracting candidate syntactic constituents, which is much more accurate than the common node-mapping algorithm usually used in the identification step. Finally, in the classification step, in addition to the common linguistic features, we propose novel and useful features for use in SRL. Our SRL system achieves an $F_1$ score of 73.53\% on the Vietnamese PropBank corpus. This system, including software and corpus, is available as an open source project and we believe that it is a good baseline for the development of future Vietnamese SRL systems., Comment: 8 pages, ICDIM 2015

This paper demonstrates end-to-end neural network architectures for Vietnamese named entity recognition. Our best model is a combination of bidirectional Long Short-Term Memory (Bi-LSTM), Convolutional Neural Network (CNN), Conditional Random Field (CRF), using pre-trained word embeddings as input, which achieves an F1 score of 88.59% on a standard test set. Our system is able to achieve a comparable performance to the first-rank system of the VLSP campaign without using any syntactic or hand-crafted features. We also give an extensive empirical study on using common deep learning models for Vietnamese NER, at both word and character level., Comment: 14 pages, 5 figures, 7 tables, accepted to PACLING 2017, fix CRF formular

In this paper, we study semantic role labelling (SRL), a subtask of semantic parsing of natural language sentences and its application for the Vietnamese language. We present our effort in building Vietnamese PropBank, the first Vietnamese SRL corpus and a software system for labelling semantic roles of Vietnamese texts. In particular, we present a novel constituent extraction algorithm in the argument candidate identification step which is more suitable and more accurate than the common node-mapping method. In the machine learning part, our system integrates distributed word features produced by two recent unsupervised learning models in two learned statistical classifiers and makes use of integer linear programming inference procedure to improve the accuracy. The system is evaluated in a series of experiments and achieves a good result, an $F_1$ score of 74.77%. Our system, including corpus and software, is available as an open source project for free research and we believe that it is a good baseline for the development of future Vietnamese SRL systems., Comment: Accepted to the VNU Journal of Science

In this paper, we compare the radio propagation channels characteristics between 28 and 140 GHz bands based on the wideband (several GHz) and directional channel sounding in a shopping mall environment. The measurements and data processing are conducted in such a way to meet requirements for a fair comparison of large- and small- scale channel parameters between the two bands. Our results reveal that there is high spatial-temporal correlation between 28 and 140 GHz channels, similar numbers of strong multipath components, and only small variations in the large-scale parameters between the two bands. Furthermore, when including the weak paths there are higher total numbers of clusters and paths in 28 GHz as compared to those in 140 GHz bands. With these similarities, it would be very interesting to investigate the potentials of using 140 GHz band in the future mobile radio communications., Comment: This paper has been accepted to the 2018 12th European Conference on Antennas and Propagation (EuCAP), London, UK, April 2018

Parasitic clear water infiltration is known to increase the waste water volumes in most sewerage systems. Amongst others, a problem arising from that is a significant variation of waste water pollutant concentration over time, which complicates the purification process and increases its cost. Capitalizing on new extensive databases, we propose a new method for the identification of clear water infiltration rates based on data-mining and data consolidation of long time data series. Based on a straightforward anthropogenic tracer, together with a simple but rigorous water budget, the infiltrated volumes are quantified day-by-day for the entire zone treated by a major waste water treatment plant. Brussels city is used as an example of the applicability of the method over several years, demonstrating the significant seasonal changes in sewer infiltration rates in the area and the progress achieved so far by structural sewer repair., SCOPUS: ar.j, info:eu-repo/semantics/published

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., Issue sup1

In Vietnam, the WHO Framework Convention on Tobacco Control (WHO FCTC) took effect in March 2005 while MPOWER has been implemented since 2008. This paper describes the progress and challenges of implementation of the MPOWER package in Vietnam. We can report that, in term of monitoring, Vietnam is very active in the Global Tobacco Surveillance System, completing two rounds of the Global Adult Tobacco Survey (GATS) and three rounds of the Global Youth Tobacco Survey (GYTS). To protect people from tobacco smoke, Vietnam has issued and enforced a law requiring comprehensive smoking bans at workplaces and public places since 2013. Tobacco advertising and promotion are also prohibited with the exception of points of sale displays of tobacco products. Violations come in the form of promotion girls, corporate social responsibility activities from tobacco manufacturers and packages displayed by retail vendors. Vietnam is one of the 77 countries that require pictorial health warnings to be printed on cigarette packages to warn about the danger of tobacco and the warnings have been implemented effectively. Cigarette tax is 70% of factory price which is equal to less than 45% of retail price and much lower than the recommendation of WHO. However, Vietnam is one of the very few countries that require manufacturers and importers to make "compulsory contributions" at 1-2% of the factory price of cigarettes sold in Vietnam for the establishment of a Tobacco Control Fund (TCF). The TCF is being operated well. In 2015, 67 units of 63 provinces/cities, 22 ministries and political-social organizations and 6 hospitals received funding from TCF to implement a wide range of tobacco control activities. Cessation services have been starting with a a toll-free quit-line but need to be further strengthened. In conclusion, Vietnam has constantly put efforts into the tobacco control field with high commitment from the government, scientists and activists. Though several remarkable achievements, Issue sup1

This paper specifies that research, analysis and estimate on marine environmental and biological conditions are very important for fishing ground forecast in offshore waters.The multi-variate regression equations among Catch Per Unit Efforts (CPUE), temperature structures and primary production have been established and used for monthly fishing ground forecast for purse-seine and drift-gillnet fisheries in the offshore waters of centralVietnam. The experiment forecast result in May, June and July, 2009 presented up to 60 percentage of acception. Meanwhile, the quantity of good forecasts are about 50% and the quantity of excellent forecasts ranks from 25 to 41%.The Length base Cohort Analyis (LCA) and Thompson and Bellmodels have been used for annual fishing ground forecast for Skipjack tuna (Katsuwonus pelamis) population, which is main object of drift-gillnet fishery. The forecast results showed that when yield in 2009 is 17,831 tonnes, its biomass in early that year is 111,906 tonnes and its forecast yield in 2010 is 18,211 tonnes. If the fishing effort in 2009 is X=1.0, its value of MSY (19,319 tonnes/year) will be gained corresponding to X=2.0.Keywords: Fishing ground forecast, offshore waters, purse-seine fishery, drift-gillnet fishery

This paper describes an efficient approach to improve the accuracy of a named entity recognition system for Vietnamese. The approach combines regular expressions over tokens and a bidirectional inference method in a sequence labelling model. The proposed method achieves an overall $F_1$ score of 89.66% on a test set of an evaluation campaign, organized in late 2016 by the Vietnamese Language and Speech Processing (VLSP) community., Comment: Submitted to the VLSP Workshop 2016

Hybrid multiple-antenna transceivers, which combine large-dimensional analog pre/postprocessing with lower-dimensional digital processing, are the most promising approach for reducing the hardware cost and training overhead in massive MIMO systems. This paper provides a comprehensive survey of the various incarnations of such structures that have been proposed in the literature. We provide a taxonomy in terms of the required channel state information (CSI), namely whether the processing adapts to the instantaneous or the average (second-order) CSI; while the former provides somewhat better signal-to-noise and interference ratio (SNIR), the latter has much lower overhead for CSI acquisition. We furthermore distinguish hardware structures of different complexities. Finally, we point out the special design aspects for operation at millimeter-wave frequencies., Comment: This is a companion document to a paper that will appear in the IEEE Communications Magazine, complemented with a full list of references

Vietnam’s adoption of the Doi Moi (renovation) policy in 1986 has generated significant and far-reaching impacts on Vietnam’s external relations, especially with China. However, so far there has been no major research in either Vietnamese or English that addresses this issue. The thesis seeks to fill this gap by examining the causal link between Doi Moi and Vietnam’s China policy since the late 1980s.Employing an analytical framework based on relevant International Relations theories and methods of archival study and case-study analysis, the thesis finds that economic considerations under Doi Moi have played an essential role in the shaping of Vietnam’s China policy as well as the trajectory of bilateral relations over the past three decades. After providing a historical background, the thesis will examine the conflicting effects that Doi Moi has generated on bilateral relations. It will demonstrate that Vietnam’s economic considerations following the adoption of Doi Moi contributed decidedly to the Sino-Vietnamese normalization in 1991 as well as the continuous improvements in bilateral ties ever since. At the same time, Vietnam’s economic activities in the South China Sea and China’s responses have intensified bilateral rivalry and put their ties under great constraints. The thesis then argues that Doi Moi has indeed brought Vietnam newfound opportunities to develop a multi-level omni-directional hedging strategy against China. Hanoi has accordingly strengthened economic ties and engagement mechanisms to maintain a stable and peaceful relationship with Beijing. However, it has also employed hard and soft balancing measures to counter China’s growing power, especially in the South China Sea.Finally, in assessing the future trajectory of bilateral ties, the thesis contends that sustained socio-economic development under Doi Moi as well as China’s “Four Modernizations” program will make democratization increasingly likely in both countries. However, even when both co

BACKGROUND: Seasonal variation affects food availability. However, it is not clear if it affects dietary intake and nutritional status of children in Vietnam. OBJECTIVES: This paper aims at examining the seasonal variation in nutrition status and dietary intake of children aged 24-59 months. DESIGN: A repeated cross-sectional study design was used to collect data of changes in nutritional status and diets of children from 24 to 59 months through four seasons in Chiem Hoa district, Tuyen Quang province, a predominately rural mountainous province of northern Vietnam. The quantitative component includes anthropometric measurements, 24 hours dietary recall and socio-economic characteristics. The qualitative component was conducted through focus group discussions (FGDs) with mothers of the children surveyed in the quantitative component. The purpose of FGDs was to explore the food habits of children during the different seasons and the behaviours of their mothers in relation to the food that they provide during these seasons. RESULTS: The prevalence of underweight among children aged 24-59 months is estimated at around 20-25%; it peaked in summer (24.9%) and reached a low in winter (21.3%). The prevalence of stunting was highest in summer (29.8%) and lowest in winter (22.2%). The prevalence of wasting in children was higher in spring and autumn (14.3%) and lower in summer (9.3%). Energy intake of children was highest in the autumn (1259.3 kcal) and lowest in the summer (996.9 kcal). Most of the energy and the nutrient intakes during the four seasons did not meet the Vietnamese National Institute of Nutrition recommendation. CONCLUSIONS: Our study describes some seasonal variation in nutrition status and energy intake among children in a mountainous area northern Vietnam. Our study indicated that the prevalence of stunting and underweight was higher in summer and autumn, while the prevalence of wasting was higher in spring and autumn. Energy intake did not always meet nat, Special Issue: Climate Change and Health in Vietnam

La Simalikalactone E (SkE) est un composé à fort potentiel antipaludique et anticancéreux, isolé de Quassia amara, une plante traditionnellement utilisée pour lutter contre le paludisme dans de nombreux pays tropicaux. Afin d'améliorer son rendement d'extraction, mais aussi d'acquérir des données de pharmacocinétique, deux méthodes de quantification de la SkE ont été développées et validées. La première fait appel à l'HPLC couplée à la MS utilisant un détecteur à trappe d'ion fonctionnant en mode Single Ion Monitoring. La seconde utilise l'UPLC-MS/MS utilisant un détecteur hybride trappe d'ion/triple quadripôle fonctionnant en mode Multiple Reaction Monitoring. Les limites de quantification de ces deux méthodes sont de 0,224 pour l'HPLC et 0,028 mg/L pour l'UPLC. L'application de ces deux méthodes a permis, non seulement d'identifier l'étape critique de la procédure nécessitant d'être améliorée afin d'optimiser le rendement d'isolement de la SkE, mais aussi d'examiner l'influence de différents paramètres (échelle d'extraction, nature et quantité de solvant, température, agitation et niveau de dessiccation) sur le rendement d'isolement. Des études in vitro et in vivo réalisées sur la préparation traditionnelle antipaludique à partir de feuilles de Q. amara a permis de conclure que malgré son excellente activité antiplasmodiale, la faible teneur en SkE dans la décoction de Q. amara ne permettait pas d'expliquer à elle seule son activité. Des composés phénoliques ont ainsi été identifiés dans la tisane (acide gallique, méthyl gallate et vitexine) et participent à cette activité. La méthode de quantification utilisant l'UPLC a également permis d'examiner le devenir de la SkE dans les fluides biologiques. Il a été démontré que la SkE n'était détectable dans le sang qu'après administration par voie intraveineuse à une concentration très faible (0,1 mg/L après 1 h) par rapport à la dose injectée, et qu'elle n'était pas détectable après administrations par voie orale ou int, Simalikalactone E (SkE) is a potential antimalarial and anticancer quassinoid isolated from Quassia amara, a plant traditionally used against malaria in many tropical countries. To improve the extraction yield and acquire the pharmacokinetic data of this molecule, two methods of quantification of SkE were developed and validated. The fisrt method used HPLC coupled to MS using an ion trap analyzer operating in Single Ion Monitoring detection. The second used UPLC coupled to MS/MS using a hybrid triple quadrupole/linear ion trap mass analyzer operating in Multiple Reaction Monitoring. The lower limits of quantification of these two methods were 0.224 and 0.028 mg/L for HPLC and UPLC, respectively. The application of these two methods allowed, to indentify the critical steps of the process requiring further improvement to optimize the SkE isolation yield and also the influence of different parameters such as the extraction scale, the nature and quantity of solvents, the temperature, the agitation and the drying process. In vitro and in vivo studies were realized on the traditional antimalarial preparation obtained from Q. amara leaves. They permitted to conclude that despite a strong antimalarial activity, SkE alone couldn't be responsible for the activity because of its very low content in the traditional decoction. Phenolic compounds (gallic acid, methyl gallate and vitexine) were therefore identified in the traditional decoction and have been found to be involved in the antimalarial activity of this preparation. The quantification methods were also used to examine the fate of SkE in biological fluids. This compound was only detectable in the blood after intravenous administration route and in a very low concentration (0.1 mg/L 1 hour after administration) compared to the given dose. SkE was not detectable after oral or intraperitoneal administration routes. Moreover, it was found that SkE was very quickly transformed in simulated intestinal fluid and more stable in

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