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Bài viết vận dụng lí thuyết tiếp nhận, nhấn mạnh khái niệm Tầm đón đợi để khảo sát bản dịch Thần Khúc của Lê Trí Viễn và Nguyễn Văn Hoàn nhằm tìm kiếm những đặc điểm nổi bật của công tác dịch thuật và nghiên cứu Thần Khúc tại Việt Nam. Trong quá trình này, sự thay đổi tầm đón đợi đối với hai bản dịch được xem như một quá trình đặt ra các giới hạn, mở rộng tiếp nhận một cách liên tục không ngừng.

We describe and illustrate Aristolochia nuichuaensis (Aristolochiaceae) as a new species from southern Vietnam. It has a cordate leaf blade, an up to 16(20)-cm-long inflorescence axis, a strongly constricted, oblong cylindrically-shaped upper part of tube, with outer surface uniformly purple, inner surface uniformly white, a campanulate limb, 4.5–5.0 cm in diam., with non-revolute lobes, a whitish outer surface of limb with visible purple streaks, a white inner surface of limb with sunken dark-purple streaks and verrucoses, an elliptic and white throat, and a gynostemium with three acute lobes. Its phenology, ecology, and comparisons with some morphologically similar species are presented. The diagnostic characters place A. nuichuaensis in the subgenus Siphisia. We also provide an identification key and a checklist with information on the distributions of the known Siphisia species in Vietnam.

In this paper we present an efficient example-based method for Gaussian denoising of CT images. In the proposed method, an image is considered as a sum of the three frequency bands: low-band, middle-band and high-band. We assume that the noise component is often mixed into the middle-band and the high-band in order to better preserve the high-frequency details in the image we perform denoising on these two bands. The method is based on a sparse representation model in which a set of standard images is used to construct the example dictionaries. The experimental results demonstrate that the proposed denoising method can preserve well the high-frequency details. The objective and subjective comparisons also show that the proposed our method outperforms other state-of-the-art denoising methods.

Natural prefabricated vertical drains (NPVDs) produced from biodegradable materials such as jute and coir have some distinct advantages over conventional polymeric prefabricated vertical drains (CPVDs). For instance, NPVDs are not only able to discharge excess pore pressure effectively but are also beneficial to the environment thanks to their biodegradability. However, due to the biodegradability of the natural fibres, NPVDs can sometimes deteriorate too quickly in an adverse environment such as in highly acidic clay, which hampers the dissipation of excess pore pressure. In this paper, an analytical solution for radial consolidation that considers the time-dependent decay of drain discharge capacity is therefore proposed. The solution is applied to an exponential form of reduction of the drain discharge capacity, and then verified with the experimental results obtained in previous studies. The effect of drain degradation on soil consolidation is simulated using a finite element method (ABAQUS) and these numerical results are then compared to those obtained from the analytical approach. In addition, a new and flexible method using a matching factor to convert the parameters from axisymmetric to plane strain models is introduced and applied to radial consolidation. The modelling outcomes indicate a significant retardation of excess pore pressure dissipation due to drain degradation and this suggests the need to exercise caution when using biodegradable NPVDs.

ObjectiveTo inform development of guidelines for hypertension management in Vietnam, we evaluated the cost-effectiveness of different strategies on screening for hypertension in preventing cardiovascular disease (CVD).MethodsA decision tree was combined with a Markov model to measure incremental cost-effectiveness of different approaches to hypertension screening. Values used as input parameters for the model were taken from different sources. Various screening intervals (one-off, annually, biannually) and starting ages to screen (35, 45 or 55 years) and coverage of treatment were analysed. We ran both a ten-year and a lifetime horizon. Input parameters for the models were extracted from local and regional data. Probabilistic sensitivity analysis was used to evaluate parameter uncertainty. A threshold of three times GDP per capita was applied.ResultsCost per quality adjusted life year (QALY) gained varied in different screening scenarios. In a ten-year horizon, the cost-effectiveness of screening for hypertension ranged from cost saving to Int$ 758,695 per QALY gained. For screening of men starting at 55 years, all screening scenarios gave a high probability of being cost-effective. For screening of females starting at 55 years, the probability of favourable cost-effectiveness was 90% with one-off screening. In a lifetime horizon, cost per QALY gained was lower than the threshold of Int$ 15,883 in all screening scenarios among males. Similar results were found in females when starting screening at 55 years. Starting screening in females at 45 years had a high probability of being cost-effective if screening biannually was combined with increasing coverage of treatment by 20% or even if sole biannual screening was considered.ConclusionFrom a health economic perspective, integrating screening for hypertension into routine medical examination and related coverage by health insurance could be recommended. Screening for hypertension has a high probability of being cost-effective in preventing CVD. An adequate screening strategy can best be selected based on age, sex and screening interval.

The BLi03719 protein of Bacillus licheniformis DSM13 belongs to the most abundant extracellular proteins under phosphate starvation conditions. In this study, the function of this phosphate starvation inducible protein was determined. An amino-acid sequence analysis of the BLi03719-encoding gene showed a high similarity with genes encoding the barnase of Bacillus amyloliquefaciens FZB42 and binase-like RNase of Bacillus pumilus SARF-032. The comparison of the control strain and a BLi03719-deficient strain revealed a strongly reduced extracellular ribonuclease activity of the mutant. Furthermore, this knockout mutant exhibited delayed growth with yeast RNA as an alternative phosphate and carbon source. These results suggest that BLi03719 is an extracellular ribonuclease expressed in B. licheniformis under phosphate starvation conditions. Finally, a BLi03719 mutant showed an advantageous effect on the overexpression of the heterologous amyE gene under phosphate-limited growth conditions.

We have designed the complete electronic system for an implanted sensory NFC-A tag (type 1) that monitors a physiological parameter, e.g. blood glucose, dehydration, bladder pressure, to name some of the target applications that we pursue. The tag is meant to be implanted under the skin and is powered by an NFC reader held close to it, such as a smart phone or a smart watch. The electronic system consists of a sensor front-end, ADC, NFC-A transceiver and NFC power harvester. In its present status, the physical layer of the communication and the power harvester have been implemented on one ASIC, and the sensor front-end and ADC on another, while the digital circuits realizing the higher level NFC protocol have been implemented on an FPGA. Simulations and a few preliminary test results are presented in this paper. The ultimate goal after thorough testing of this first prototype is to integrate all of these modules on a single ASIC.

We have studied theoretically (including computer simulations) magnetic properties of aggregates of ferromagnetic amorphous nanogranules in the presence of direct exchange between the neighboring granules and random anisotropy fields. We show that such a system can be considered as ferromagnetic glass. We demonstrate (basing on analytical considerations as well as on the results of numerical simulations) that the system is decomposed to clusters or domains with nearly collinear orientation of magnetization. The size of the domains depends on the ratio of the exchange interaction and random anisotropy. For quasi-2D structures we predict that the dipole–dipole interactions between the granules lead to a formation of magnetic vortices. Moreover, the computer simulations also reproduce the puzzling increase of the thermoremanent magnetization observed experimentally, which is expected to be a result of a temperature-dependent decrease in the anisotropy (or a temperature-dependent increase in the exchange). We also consider the structures with weak intergranular exchange and show that they are characterized by the presence of two critical temperatures.

We propose and analyze in details the revised model of XPROB, an infinite family of pool-based anonymous communication systems that can be used in various applications including high performance computing environments. XPROB overcomes the limitations of APROB Channel that only resists a global delaying adversary (GDA). Each instance of XPROB uses a pool mix as its core component to provide resistance against a global active adversary (GAA), a stronger yet more practical opponent than a GDA. For XPROB, a GAA can drop messages from users but cannot break the anonymity of the senders of messages. Analysis and experimental evaluations show that each instance of XPROB provides greater anonymity than APROB Channel for the same traffic load and user behaviors (rate and number of messages sent). In XPROB, any message can be delivered with high probability within a few rounds after its arrival into the system; thus, an opponent cannot be certain when a message will be delivered. Furthermore, users can choose their own preference balance between anonymity and delay. Through the evaluation, we prove that XPROB can provide anonymity for users in high-performance computing environments.

We report on structural and magnetic properties of granular films consisting of 2.5 nm Ni nanoparticles. The films are fabricated by the original laser electrodispersion technique, which allows producing nearly monodisperse and amorphous particles. Atomic force microscopy (AFM) study shows that in 8 nm thickness films the particles are self-assembled in clusters with the lateral size 100–150 nm and the height of about 8 nm. Performed by SQUID, the films magnetization measurements reveal superparamagnetic behaviour, characteristic for an ensemble of non-interacting single domain magnetic particulates. It is found that the magnetic moment of the particulate is equal to that of about 3000 individual Ni nanoparticles and the blocking temperature is close to room temperature. Defined from magnetic measurements, the size of single domain particulates correlates well with the size of the clusters determined from AFM images. We propose that exchange interaction plays an important role in the formation of the particulates by aligning the magnetic moments of the individual Ni nanoparticles inside the clusters. Presence of magnetic clusters with high blocking temperature makes the fabricated films potentially useful for high-density magnetic data storage applications.

International audience; A volume integral formulation using facet elements to compute eddy currents in thin conductive shells is presented. The formulationis general and considers the field variation through the depth due to the skin effect. The formulation leads to an equivalent lumpedelements circuit that can be coupled with an external circuit. The resolution of the circuit is achieved by the independent loopsmethod. The formulation has been validated because of two numerical examples. Results are compared with an axisymmetricfinite-element method (FEM) and another shell formulation implemented in a 3-D FEM.

Background There is an economic burden associated with hypertension both worldwide and in Vietnam. In Vietnam, patients with uncontrolled high blood pressure are hospitalized for further diagnosis and initiation of treatment. Because there is no evidence on costs of inpatient care for hypertensive patients available yet to inform policy makers, health insurance and hospitals, this study aims to quantify direct costs of inpatient care for these patients in Vietnam. Methods A retrospective study was conducted in a hospital in Vietnam. Direct costs were analyzed from the health-care provider’s perspective. Hospital-based costing was performed using both bottom-up and micro-costing methods. Patients with sole essential or primary hypertension (ICD-code I10) and those comorbid with sphingolipid metabolism or other lipid storage disorders (ICD-code E75) were selected. Costs were quantified based on financial and other records of the hospital. Total cost per patient resulted from an aggregation of laboratory test costs, drug costs, inpatient-days’ costs and other remaining costs, including appropriate allocation of overheads. Both mean and medians, as well as interquartile ranges (IQRs) were calculated. In addition to a base-case analysis, specific scenarios were analyzed. Results 230 patients were included in the study (147 cases with I10 code only and 83 cases with I10 combined with E75). Median length of hospital stay was 6 days. Median total direct costs per patient were US$65 (IQR: 37 -95). Total costs per patient were higher in the combined hypertensive and lipid population than in the sole hypertensive population at US$78 and US$53, respectively. In all scenarios, hospital inpatient days’ costs were identified as the major cost driver in the total costs. Conclusions Costs of hospitalization of hypertensive patients is relatively high compared to annual medication treatment at a community health station for hypertension as well as to the total health expenditure per capita in Vietnam. Given that untreated/undetected hypertension likely leads to more expensive treatments of complications, these findings may justify investments by the Vietnamese health-care sector to control high blood pressure in order to save downstream health care budgets. Electronic supplementary material The online version of this article (doi:10.1186/s12913-014-0514-4) contains supplementary material, which is available to authorized users.

We propose in this paper a novel example-based method for Gaussian denoising of CT images. In the proposed method, denoising is performed with the help of a set of example CT images. We construct, from the example images, a database consisting of high and low-frequency patch pairs and then use the Markov random field to denoise. The proposed denoising method can restore the high-frequency band that is often lost by the traditional noise-filters. Moreover, it is very effective for images corrupted by heavy noise. Experimental results also show that the proposed method outperforms other state-of-the-art denoising methods both in the objective and subjective evaluations.

International audience; A volume integral formulation to compute eddy currents in non-magnetic conductive media is presented. The current distribution is approximated with facet finite elements. The formulation is general and leads to an equivalent lumped elements circuit. In order to ensure the solenoidality of the current distribution, an algorithm detecting the independent loops is then used for the resolution. The formulation is tested on TEAM workshop Problem 7. Even with coarse meshes, its accuracy is demonstrated.

According to the traditional viewpoint of Data mining, transactions are accumulated over a long period of time (in years) in order to find out the frequent patterns associated with a given threshold of support, and then they are applied to practice of business as important experience for the next business processes. From the point of view, many algorithms have been proposed to exploit frequent patterns. However, the huge number of transactions accumulated for a long time and having to handle all the transactions at once are still challenges for the existing algorithms. In addition, today, new characteristics of the business market and the regular changes of business database with too large frequency of added-deleted-altered operations are demanding a new algorithm mining frequent patterns to meet the above challenges. This article proposes a new perspective in the field of mining frequent patterns: accumulating frequent patterns along with a mathematical model and algorithms to solve existing challenges. Keywords—accumulating frequent patterns; data mining; frequent pattern; horizontal parallelization; representative set; vertical parallelization

The main objective of the Attribute Reduction problem in Rough Set Theory is to find and retain the set of attributes whose values vary most between objects in an Information System or Decision System. Besides, Mining Frequent Patterns aims finding items that the number of times they appear together in transactions exceeds a given threshold as much as possible. Therefore, the two problems have similarities. From that, an idea formed is to solve the problem of Attribute Reduction from the viewpoint and method of Mining Frequent Patterns. The main difficulty of the Attribute Reduction problem is the time consuming for execution, NP-hard. This article proposes two new algorithms for Attribute Reduction: one has linear complexity, and one has global optimum with concepts of Maximal Random Prior Set and Maximal Set.

This research proposes a new Big File Cloud (BFC) with its architecture and algorithms to solve difficult problems of cloud-based storage using the advantages of key-value stores. There are many problems when designing an efficient storage engine for cloud-based storage systems with strict requirements such as big-file processing, lightweight meta-data, low latency, parallel I/O, deduplication, distributed, high scalability. Keyvalue stores have many advantages and outperform traditional relational database in storing data for heavy load systems. This paper contributes a low-complicated, fixed-size meta-data design, which supports fast and highly-concurrent, distributed file I/O, several algorithms for resumable upload, download and simple data deduplication method for static data. This research applies the advantages of ZDB - an in-house key-value store which was optimized with auto-increment integer keys for solving big-file storage problems efficiently. The results can be used for building scalable distributed data cloud storage that support big-files with sizes up to several terabytes.

In this study, multiplex nested RT-PCR (mnRT-PCR) was applied to simultaneous detect multiplex PCR with the higher sensitivity of nested PCR that is required for avian influenza, infectious bronchitis and Newcastle disease virus using two steps of amplification. For the first PCR, primers that were specific for each virus were newly designed from the nucleoprotein gene of AIV, the nucleocapsid protein gene of IBV and the fusion protein gene of NDV to amplify products of 665, 386 and 236 nucleotides, respectively. The multiplex PCR step provides mass amplification using common primers, which increased markedly the sensitivity of the test. Non-specific reactions were not observed when other viruses and bacteria were used for evaluating the mnRT-PCR. As a field application, 172 samples were tested by RT-PCR and mnRT-PCR. Among these samples, the concordance rates for mnRT-PCR and the single conventional RT-PCR showed 98.9% (kappa=0.98) and 98.8% (kappa=0.96) similarity for IBV and AIV, respectively. As a result, it is recommended the multiplex nested PCR as an effective tool for detecting and studying the molecular epidemiology of various mixed infections of one or more of these viruses in poultry.

Analyzing Customer Characteristics is an important issue in marketing. Recently, studies about Customer Characteristics focus on two main directions: Customer Identification and Making Decision. Many data mining theory are applied successfully to identify and classify customer, especially Rough Set Theory (Ali Ahmady 2009), (James J.H. Liou, Gwo-Hshiung Tzeng 2010), (Saiful Hafizah Jaaman 2009). But a key problem when using Rough Set Theory to identify important customer characteristics is time-consuming. Because of this reason, it is difficult to integrate Rough Set Theory into solving Customer Identification problem. Besides that, Making Decision is a necessary mission of Analyzing Customer Characteristics. Expected Opportunity Loss index is often used to make decisions under risk and uncertain situation (K. Khalili Damghani et al. 2009). However, it is too simple and does not reflect the experience values. This paper introduces a new model of Customer Characteristics which applies our proposed algorithm to identify Customer Characteristics and presents a Posterior Expected Opportunity Loss index to make decision.

Rough set is a widespread concept in computer science and is applicable in many fields such as artificial intelligence, expert systems, data mining, pattern recognition and decision support systems. One of key problems of knowledge acquisition in theoretical study of rough sets is attribute reduction. Attribute reduction also called feature selection eliminates superfluous attributes in the information system and improves efficiency of data analysis process. But reducing attributes is a NP-hard problem. Recently, to overcome the technical difficulty, there are a lot of research on new approaches such as maximal tolerance classification (Fang Yang et al. 2010), genetic algorithm (N. Ravi Shankar et al. 2010), topology and measure of significance of attributes (P.G. JansiRani and R. Bhaskaran 2010), soft set (Tutut Herawan et al. 2010), positive approximation (Yuhua Qian et al. 2010), dynamic programming (Walid Moudani et al. 2010). However, there are still some challenging research issues that time consumption is still hard problem in attribute reduction. This paper introduces a new approach with a model presented with definitions, theorems, operations. Set of maximal random prior forms is put forward as an effective way for attribute reduction. The algorithm for seeking maximal random prior set are proposed with linear complexity, contributes to solve absolutely problems in attribute reduction and significantly improve the speed of calculation and data analysis.

Frequent Pattern Mining is an important data mining task and it has been a focus theme in data mining research. One of the main issues in Frequent Pattern Mining is Sequential Pattern Mining retrieved the relationships among objects in sequential dataset. AprioriAll is a typical algorithm to solve the problem in Sequential Pattern Mining but its complexity is so high and it is difficult to apply in large datasets. Recently, to overcome the technical difficulty, there are a lot of researches on new approaches such as custom-built Apriori algorithm, modified Apriori algorithm, Frequent Pattern-tree and its developments, integrating Genetic algorithms, Rough Set Theory or Dynamic Function to solve the problem of Sequential Pattern Mining. However, there are still some challenging research issues that time consumption is still hard problem in Sequential Pattern Mining. This paper introduces a new approach with a model presented with definitions and operations. The proposed algorithm based on this model finds out the sequential patterns with quadratic time to solve absolutely problems in Sequential Pattern Mining and significantly improve the speed of calculation and data analysis.

International audience; Ce papier présente un couplage de la méthode multipôlaire rapide (Fast Multipole Method - FMM) avec une méthode intégrale de volume pour le calcul de courants induits dans une région mince conductrice. Grâce à ce couplage, les points forts de chaque méthode sont exploités: ne pas mailler la région air, ne pas stocker une matrice pleine. Un exemple de validation est présenté

Biosensors have been rapidly developed recently. Biological receptors, such as antibodies, must be immobilized on these sensors' surfaces to make the sensor capable of capturing a target analyte. In this research we studied how to modify a gold-coated surface of a microcantilever, a sensor with high potential in biological and medical applications. Thiol chemistry was adapted to create a cysteamine layer on a gold surface, and subsequently glutaraldehyde was used as a cross-linking agent to react with amine groups in receptors. In order to evaluate the efficiency of immobilizing protein on an Au surface and also whether the protein retains its biological activity, horseradish peroxidase enzyme (HRP) with its activity to catalyze a reaction between 2,2'-azino-bis [3-ethylbenzothiazoline-6-sulphonic acid] (ABTS) and was used as a testing protein. The result showed that HRP was immobilized successfully on cysteamine and glutaraldehyde layers and retained its activity. The cantilever's tip deflection was also measured, and results showed that each layer created surface stress and made the cantilever bend?in particular, the cysteamine layer induced bending as high as 6 ?m. An antibody of alpha-fetoprotein (AFP) was immobilized on the cantilever surface, and the measurement deflection showed that the sensor responded to solution containing AFP with concentration from 100 to 500 ng ml?1.

Frequent pattern mining is a basic problem in data mining and knowledge discovery. The discovered patterns can be used as the input for analyzing association rules, mining sequential patterns, recognizing clusters, and so on. However, there is a posed question that how is objectivity measurement of frequent patterns? Specifically, in market basket analysis problem to find out association rules, whether or not the frequent patterns discovered represent exactly the needs of all customers. Or, these frequent patterns were only created by a few customers with too many purchases. In this paper, a mathematical space will be introduced with some new related concepts and propositions to design a new algorithm answering the above questions.

Frequent pattern mining is a basic problem in data mining and knowledge discovery. The discovered patterns can be used as the input for analyzing association rules, mining sequential patterns, recognizing clusters, and so on. However, discovering frequent patterns in large scale datasets is an extremely time consuming task. Most research in the area of association rule discovery has focused on the method of efficient frequent pattern discovery, e.g. Park, Chen & Yu (1995); Savasere, Omiecinski & Navathe (1995); Han, Pei & Yin (2000); Pei, Han, Lu, Nishio, Tang & Yang (2001). When seeking all associations that satisfy constraints on support and confidence, once frequent patterns have been identified, generating the association rules is trivial. In the last decade, various algorithms have been proposed on this problem, e.g. maximal pattern mining — Grahne & Zhu (2003); closed pattern mining — Pei, Han & Mao (2000); Grahne & Zhu (2003); mining the most interesting frequent patterns — Fu, Kwong & Tang (2000); Han, Wang, Lu & Tzvetkov (2002, 2005); Hirate, Iwahashi & Yamana (2004). However, some challenges are still existed and need to be overcome. In this paper, a mathematical space will be introduced with some new related concepts and propositions to design a new algorithm for solving frequent patterns mining problem. It is hoped that such an improved algorithm will be simple to implement and more efficient.

This paper deals with a three-dimensional thermal model for landmine detection problems and an inverse problem for reconstructing the physical parameters of buried objects. Moreover, solutions are given for the estimation of the soil thermal diffusivity and meteorological parameters, needed for solving the inverse problem. The paper describes the main fundamental principles of thermal modelling for buried object identification and illustrates the results on data acquired from a real minefield, together with qualitative and quantitative results illustrating the validity of the model.

A detailed description of the CLEARFAST system for thermal IR stand-off minefield survey is given. The system allows (i) a stand-off diurnal observation of hazardous area, (ii) detecting anomalies, i.e. locating and searching for targets which are thermally and spectrally distinct from their surroundings, (iii) estimating the physical parameters, i.e. depth and thermal diffusivity, of the detected anomalies, and (iv) providing panoramic (mosaic) images indicating the locations of suspect objects and known markers. The CLEARFAST demonstrator has been successfully deployed and operated, in November 2004, in a real minefield within the United Nations Buffer Zone in Cyprus. The paper describes the main principles of the system and illustrates the processing chain on a set of real minefield images, together with qualitative and quantitative results.

Bài viết hướng đến khảo sát hình ảnh đuôi lợn trong Trăm năm cô đơn của G. G. Marquez với tư cách là một hình tượng nghệ thuật. Trong quá trình này, đuôi lợn được nhìn dưới quy luật nghệ thuật từ phản ánh đến sáng tạo hiện thực. Theo đó, mối quan hệ giữa hình ảnh và hình tượng được khái lược làm cơ sở cho việc tìm hiểu bản chất và chức năng của hình tượng nghệ thuật như một thể chứa đựng nhiều tầng bậc văn hóa và tham gia tích cực vào việc hình thành giá trị nội dung và nghệ thuật tiểu thuyết.