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A kidney transplant has become an option for many people with end-stage kidney failure. However, not all patients are likely to receive a kidney transplant. This study is conducted to identify some characteristics of patients with renal transplant indications for kidney transplantation from 26 hospitals in Hanoi. According to the research results, in 2020, Hanoi has 3,220 patients on dialysis with the average age of 54, mainly from 46-65, more males than females. More than 95% of the causes of dialysis are chronic glomerulonephritis, hypertension, and diabetes; up to 65% of the dialysis time is over 5 years, blood type O patients account for 43% and 25% of dialysis patients with hepatitis C. Out of a total of 3,220 patients, 2,400 (74%) of patients have indicated a kidney transplant with an average age of nearly 49 years, of which men (55%) are more than women (45%); dialysis time less than 5 years accounts for the highest percentage with 43%, 25% of patients with indicated kidney transplantation are HCV positive; chronic kidney failure due to chronic glomerulonephritis and hypertension, diabetes are two main groups of causes, accounting for 94% of dialysis patients who are indicated for transplant.

Online reviews are valuable sources of information to help companies to make good decisions for business intelligence. In this study, we propose an Automatic Aspect-based Sentiment Summarization (AAbSS) system that has two components and can generate a summary as an output. The first component is the Aspect-based Knowledge Representation and Selection (AKRS) used to represent reviews based on aspects and their polarities for selecting aspect-based knowledge. To represent and selection knowledge, a set of frequency of polarity opinion strength, a summation of frequency of aspect, and an information of aspect are initiated. The second component is the Summary Format Generation (SFG) used to automatically generate three kinds of formats. In this component (SFG), new representations for visual and structured summaries, and a new way of applied natural language generation for a textual summary are proposed. In the experiments, 13 domains from benchmark datasets of customer reviews, e.g. cell phone, digital camera, etc. are used. The proposed system not only fast generates summaries having good performance when compared to other summaries generated by other systems and easily updated when adding new reviews in the same domain but also does not spend memory capacity to save any raw data.

This article examines the role of co-skewness and co-kurtosis in explaining portfolio excess returns utilizing time-series and Fama–Macbeth cross-sectional regression methods in the context of an emerging market. The sample consists of listed firms in Vietnam stock market covering the period from September 2011 to December 2016. This paper reports that co-skewness and co-kurtosis are not important in explaining stock returns in Vietnam stock market. More importantly, we find that market risk premium is the most important factor while other popular factors such as SMB, HML and UMD have minor impact on stock returns. This finding is crucial in identifying factors significantly influencing stock returns in emerging equity markets. This paper also supports the proposition that findings from advanced markets might not be able to generalize into the context of emerging markets. The finding has direct implications for portfolio analysis and risk management.

Handicraft production is usually chaotic and difficult to monitor, since its products and manufacturing processes are complex. As all the manufacturing steps rely on varied skill levels of the workers, the situation is even more stochastic. There are several common problems, such as inappropriate production method, line unbalance, excessive stock, lack of production planning and control phases, etc. They stem from the lack of suitable operation model, redundant workforce usage, and insufficient internal training activities, which lead to the waste of human resources. In this paper, a roadmap to improve the operational efficiency of handicraft manufacturing is suggested, using Lean-Six Sigma methodology and tools. A case study is conducted in a Vietnamese firm to show the validity of the approach.

Knowledge-based engineering (KBE) helps to automate the design of products and corresponding manufacturing systems. The automation is achieved via engineering knowledge representation in computer-processable formats, i.e. languages. It becomes possible to capture product design and manufacturing processes knowledge and let software applications to handle it suggesting better options for a product and/or a manufacturing system. In this paper we demonstrate an application and corresponding methodology to design and evaluate the performance of a product. The approach can be extended to different engineering problem domains saving the time used for product design.

Knowledge-based engineering (KBE) has been described as a phase in the evolution of CAD, and as the capture and re-use of engineering knowledge. One interpretation of the latter is the use of code to digitally store and apply engineering knowledge. Using CAD software programmatically may seem counterintuitive. However, programmatic CAD provides opportunities for KBE and Industrie 4.0 (I4.0). KBE has been successfully applied in aerospace and automotive industries but is less common for Engineer-to-Order industries. Many attribute this to the time it takes to create and add knowledge to a KBE system, and the need for non-programmers to write code. This paper offers a KBE system that, by programmatic use of CAD, automatically adds weld paths to assembly models from STEP-files. The paths may be extracted and exported for generating robot code for a welding robot and for other I4.0 applications.

Knowledge-based engineering aims to automate product design processes. Researches in manufacturing try to find optimal way to reduce the time required to go from intangible idea to a product in hands of a customer. With the advances of Information and Communication Technologies, it becomes possible to integrate and use information generated at different phases of a product lifecycle. That includes deciding on how robots should operate, which have got a key role in automation of manufacturing processes. Use of formalized representation of engineering knowledge for industrial robots’ application can allow for better decision making. This paper proposes an approach for integrating product design with robot applications using Knowledge Fusion language. The Knowledge Fusion allows to capture engineering knowledge in computer-processable format that can be later used for automating design and manufacturing processes. An approach is illustrated with Siemens NX tools framework.

One of the factors improving businesses in business intelligence is summarization systems which could generate summaries based on sentiment from social media. However, these systems could not produce automatically, they used annotated datasets. To automatically produce sentiment summaries without using the annotated datasets, we propose a novel framework using pattern rules. The framework has two procedures: 1) pre-processing and 2) aspect knowledgebase generation. The first procedure is to check and correct misspelt words (bigram and unigram) by a proposed method, and tag part-of-speech all words. The second procedure is to automatically generate aspect knowledgebase used to produce sentiment summaries by the sentiment summarization systems. Pattern rules and semantic similarity-based pruning are used to automatically generate aspect knowledgebase from social media. In the experiments, eight domains from benchmark datasets of reviews are used. The performance evaluation of our proposed approach shows the high performance when compared to other approaches.

Background The prevalence of risk factors for poor outcomes from aneurysmal subarachnoid hemorrhage (SAH) varies widely and has not been fully elucidated to date in Vietnam. Understanding the risk and prognosis of aneurysmal SAH is important to reduce poor outcomes in Vietnam. The aim of this study, therefore, was to investigate the rate of poor outcome at 90 days of ictus and associated factors from aneurysmal SAH in the country. Methods We performed a multicenter prospective cohort study of patients (≥18 years) presenting with aneurysmal SAH to three central hospitals in Hanoi, Vietnam, from August 2019 to August 2020. We collected data on the characteristics, management, and outcomes of patients with aneurysmal SAH and compared these data between good (defined as modified Rankin Scale (mRS) of 0 to 3) and poor (mRS, 4–6) outcomes at 90 days of ictus. We assessed factors associated with poor outcomes using logistic regression analysis. Results Of 168 patients with aneurysmal SAH, 77/168 (45.8%) were men, and the median age was 57 years (IQR: 48–67). Up to 57/168 (33.9%) of these patients had poor outcomes at 90 days of ictus. Most patients underwent sudden-onset and severe headache (87.5%; 147/168) and were transferred from local to participating central hospitals (80.4%, 135/168), over half (57.1%, 92/161) of whom arrived in central hospitals after 24 hours of ictus, and the initial median World Federation of Neurological Surgeons (WFNS) grading score was 2 (IQR: 1–4). Nearly half of the patients (47.0%; 79/168) were treated with endovascular coiling, 37.5% (63/168) were treated with surgical clipping, the remaining patients (15.5%; 26/168) did not receive aneurysm repair, and late rebleeding and delayed cerebral ischemia (DCI) occurred in 6.1% (10/164) and 10.4% (17/163) of patients, respectively. An initial WFNS grade of IV (odds ratio, OR: 15.285; 95% confidence interval, CI: 3.096–75.466) and a grade of V (OR: 162.965; 95% CI: 9.975–2662.318) were independently associated with poor outcomes. Additionally, both endovascular coiling (OR: 0.033; 95% CI: 0.005–0.235) and surgical clipping (OR: 0.046; 95% CI: 0.006–0.370) were inversely and independently associated with poor outcome. Late rebleeding (OR: 97.624; 95% CI: 5.653–1686.010) and DCI (OR: 15.209; 95% CI: 2.321–99.673) were also independently associated with poor outcome. Conclusions Improvements are needed in the management of aneurysmal SAH in Vietnam, such as increasing the number of aneurysm repairs, performing earlier aneurysm treatment by surgical clipping or endovascular coiling, and improving both aneurysm repairs and neurocritical care.

Aspect-based online information on social media plays a vital role in influencing people’s opinions when consumers concern with their decisions to make a purchase, or companies intend to pursue opinions on their product or services. Determining aspect-based opinions from the online information is necessary for business intelligence to support users in reaching their objectives. In this study, we propose the new aspect extraction and scoring system which has three procedures. The first procedure is normalizing and tagging part-of-speech for sentences of datasets. The second procedure is extracting aspects with pattern rules. The third procedure is assigning scores for aspects with SentiWordNet. In the experiments, benchmark datasets of customer reviews are used for evaluation. The performance evaluation of our proposed system shows that our proposed system has high accuracy when compared to other systems.

Digital twin plays a key role in the current development of smart manufacturing systems. Through simulation in the cyber world, real phenomena in the physical world can be predicted and optimized before the final implementation. The usage of the digital twin is enhanced along with the uprising of Industry 4.0, in which data availability supports the further insight of system status, helping the operation managers understand their system and perform resources adjustment more easily. Based on this digitization mature, Lean 4.0, a new concept elaborated from Lean manufacturing, has been interested recently. There are several technologies constituted digital twin that provide a favourable condition for Lean 4.0, such as augmented reality, cloud computing. In this paper, the integration of the Real-time Locating System (RTLS) into digital twin is proposed, which facilitates the performance of Lean 4.0 in manufacturing operation. Not only gain effective control over the facility’s assets, but this integration also enhances the resources utilization, cut down operational wastes, thus brings a better turnover for industrial systems. A case study of successful implementation is shown, which proved the possible advantages of this approach.

Biomedical Image Processing, such as human organ segmentation and disease analysis, is a modern field in medicine development and patient treatment. Besides there are many kinds of image formats, the diversity and complexity of biomedical data is still a big issue to all of researchers in their applications. In order to deal with the problem, deep learning give us a successful and effective solutions. Unet and LSTM are two general approaches to the most of case of medical image data. While Unet helps to teach a machine in learning data from each image accompanied with its labelled information, LSTM helps to remember states from many slices of images by times. Unet gives us the segmentation of tumor, abnormal things from biomedical images and then the LSTM gives us the effective diagnosis on a patient disease. In this paper, we show some scenarios of using Unets and LSTM to segment and analysis on many kinds of human organ images and results of brain, retinal, skin, lung and breast segmentation.

Automatic facial expression recognition (FER) has gained much attention due to its applications in human-computer interaction. Among the approaches to improve FER tasks, this paper focuses on deep architecture with the attention mechanism. We propose a novel Masking Idea to boost the performance of CNN in facial expression task. It uses a segmentation network to refine feature maps, enabling the network to focus on relevant information to make correct decisions. In experiments, we combine the ubiquitous Deep Residual Network and Unet-like architecture to produce a Residual Masking Network. The proposed method holds state-of-the-art (SOTA) accuracy on the well-known FER2013 and private VEMO datasets.

In this work, a photonic-silicon-based 1✕3 reconfigurable simultaneous three-mode selective router has been demonstrated by the proof-of-concept. The device can be flexibly controlled to route three input modes of TE0, TE1, and TE2 to three outputs by utilizing three controllable Ti thermo-optic phase shifters as drivers. The proposed router is constructed from a Ψ -junction coupler and two kinds of 3✕3 multi-mode interference (MMI) couplers. The proposed device can attain low insertion loss smaller than 5 dB and crosstalk below −20 dB in broadband of 40-nm thanks to the numerical simulation-based optimization. Furthermore, the proposed router has relatively large fabrication tolerances of width and height and consumes a low electric power consumption. The proposed device is reconfigurable for simultaneous three guided modes, and thus, leading to a promising potential to widely apply for broadband optical signal processing in the mode-division multiplexing systems.

Despite rapid evolution in the area of microbial natural products chemistry, there is currently no open access database containing all microbially produced natural product structures. Lack of availability of these data is preventing the implementation of new technologies in natural products science. Specifically, development of new computational strategies for compound characterization and identification are being hampered by the lack of a comprehensive database of known compounds against which to compare experimental data. The creation of an open access, community-maintained database of microbial natural product structures would enable the development of new technologies in natural products discovery and improve the interoperability of existing natural products data resources. However, these data are spread unevenly throughout the historical scientific literature, including both journal articles and international patents. These documents have no standard format, are often not digitized as machine readable text, and are not publicly available. Further, none of these documents have associated structure files (e.g., MOL, InChI, or SMILES), instead containing images of structures. This makes extraction and formatting of relevant natural products data a formidable challenge. Using a combination of manual curation and automated data mining approaches we have created a database of microbial natural products (The Natural Products Atlas, www.npatlas.org) that includes 24 594 compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. This database is accompanied by an interactive web portal that permits searching by structure, substructure, and physical properties. The Web site also provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. These interactive tools offer a powerful knowledge base for natural products discovery with a central interface for structure and property-based searching and presents new viewpoints on structural diversity in natural products. The Natural Products Atlas has been developed under FAIR principles (Findable, Accessible, Interoperable, and Reusable) and is integrated with other emerging natural product databases, including the Minimum Information About a Biosynthetic Gene Cluster (MIBiG) repository, and the Global Natural Products Social Molecular Networking (GNPS) platform. It is designed as a community-supported resource to provide a central repository for known natural product structures from microorganisms and is the first comprehensive, open access resource of this type. It is expected that the Natural Products Atlas will enable the development of new natural products discovery modalities and accelerate the process of structural characterization for complex natural products libraries., The Natural Products Atlas is a new online database of microbially derived natural product structures, designed as a comprehensive open access repository for the scientific community.

AIM: This work is aimed to describe anatomical features and variants of the prostatic artery (PA) using digital subtraction angiography (DSA). METHODS: This is a descriptive statistic study. We reviewed the DSA of 348 patients, who had a PA embolisation to reduce the benign prostatic hyperplasia (BPH) symptoms at Radiology Department of Bach Mai Hospital from Oct – 2014 to Oct – 2018. RESULTS: PA was found at 660 pelvic halves, of which 30 pelvic halves (4.5%) had two PAs, 630 pelvic halves had one PA. In terms of the origin of PA, in total 690 PAs, the percentage of type 1, 2, 3, 4 and 5 was successively 33.9%, 13.9%, 18.3%, 23.9% and 10.4%, respectively. Atherosclerosis of PA observed in 20.9%. The ‘corkscrew’ pattern was found in 30.4%. The average diameter of PA was 1.5 ± 0.34mm. The anastomosis of PA with surrounding arteries was common. PA may supply rectum (6.1%), seminal vesical (9.6%), bladder (5.2%), contralateral prostatic parenchyma (13.0%), surrounding soft-tissues (3.5%). CONCLUSION: The common trunk with SVA superior vesical artery was the most common origin of PA. Anastomoses of PA with surrounding tissues were complex.

Eco-environmental vulnerability assessment is crucial for environmental and resource management. However, evaluation of eco-environmental vulnerability over large areas is a difficult and complex process because it is affected by many variables including hydro-meteorology, topography, land resources, and human activities. The Thua Thien – Hue Province and its largest river system, the Perfume River, are vital to the social-economic development of the north central coastal region of Vietnam, but there is no zoning system for environmental protection in this region. An assessment framework is proposed to evaluate the vulnerable eco-environment in association with 16 variables with 6 of them constructed from Landsat 8 satellite image products. The remaining variables were extracted from digital maps. Each variable was evaluated and spatially mapped with the aid of an analytical hierarchy process (AHP) and geographical information system (GIS). An eco-environmental vulnerability map is assorted into six vulnerability levels consisting of potential, slight, light, medium, heavy, and very heavy vulnerabilities, representing 14%, 27%, 17%, 26%, 13%, 3% of the study area, respectively. It is found that heavy and very heavy vulnerable areas appear mainly in the low and medium lands where social-economic activities have been developing rapidly. Tiny percentages of medium and heavy vulnerable levels occur in high land areas probably caused by agricultural practices in highlands, slash and burn cultivation and removal of natural forests with new plantation forests. Based on our results, three ecological zones requiring different development and protection solutions are proposed to restore local eco-environment toward sustainable development. The proposed integrated method of remote sensing (RS), GIS, and AHP to evaluate the eco-environmental vulnerability is useful for environmental protection and proper planning for land use and construction in the future.

Document layout analysis or page segmentation is the task of decomposing document images into many different regions such as texts, images, separators, and tables. It is still a challenging problem due to the variety of document layouts. In this paper, we propose a novel hybrid method, which includes three main stages to deal with this problem. In the first stage, the text and non-text elements are classified by using minimum homogeneity algorithm. This method is the combination of connected component analysis and multilevel homogeneity structure. Then, in the second stage, a new homogeneity structure is combined with an adaptive mathematical morphology in the text document to get a set of text regions. Besides, on the non-text document, further classification of non-text elements is applied to get separator regions, table regions, image regions, etc. The final stage, in refinement region and noise detection process, all regions both in the text document and non-text document are refined to eliminate noises and get the geometric layout of each region. The proposed method has been tested with the dataset of ICDAR2009 page segmentation competition and many other databases with different languages. The results of these tests showed that our proposed method achieves a higher accuracy compared to other methods. This proves the effectiveness and superiority of our method.

Table detection is a challenging problem and plays an important role in document layout analysis. In this paper, we propose an effective method to identify the table region from document images. First, the regions of interest (ROIs) are recognized as the table candidates. In each ROI, we locate text components and extract text blocks. After that, we check all text blocks to determine if they are arranged horizontally or vertically and compare the height of each text block with the average height. If the text blocks satisfy a series of rules, the ROI is regarded as a table. Experiments on the ICDAR 2013 dataset show that the results obtained are very encouraging. This proves the effectiveness and superiority of our proposed method.

The stoichiometry value x of WOx , or its oxidation state, is crucial for improving performances of the hole-selective contact heterojunction silicon solar cell. However, it is challenging to tune the films' oxidation state using the well-known evaporation method. In this study, a simulation was performed to analyze the effect of x on short-circuit current (Jsc) loss, attributed to the hole-selective contact in the device. Compared to the thickness of WOx layer, x has a more important role in minimizing Jsc loss. Based on the simulation, the WOx /c-Si heterojunction solar cells having hole-selective WOx contacts with tuned x to vary its oxidation state were fabricated using reactive magnetron sputtering. The relationships of the open-circuit voltage (Voc) and Jsc with respect to x were similar. The experimentally determined Jsc increased from 34.7 to 36.6 mA cm−2 when x was increased from 2.72 to 2.77; this result is consistent with the simulation. Nevertheless, fill factor (FF) reduced with the increase of x, owing to the reduced conductivity of WOx . Both oxidation state and film conductivity must be as high as possible to simultaneously achieve high Voc, Jsc, and FF. The lowest x yielded a solar cell efficiency of 13.3%.

An important aspect of increased international financial integration is the associated increase in volatility spillover. Analyzing volatility spillovers from advanced economies to emerging economies is clearly important for portfolio investment and risk management. This paper investigates volatility spillovers from the US equity market to stock markets of ASEAN economies. We use the augmented EGARCH model with the ICSS algorithm to control for the excessive volatility break over an extended period. We document a significant volatility spillover from the US to ASEAN equity markets and this finding is vital to investors. The paper has strong practical importance because an accurate prediction of volatility spillovers in international equity markets is crucial for mitigating portfolio risk.

This paper presents a method for document layout analysis. This method applies the analyzing of whitespace in maximum homogeneous regions. This method focuses on the balance between processing time and performance. It consists of two main stages: classification and segmentation. Firstly, by using the analysis of whitespace analysis on Maximum multi-layer horizontal homogeneous regions, the text and non-text elements are classified. Then, text regions are extracted by using mathematical morphology. Besides, non-text elements are classified into separators, tables, images via a machine learning approach. The proposed method's effectiveness is proved by the tests on UW-III (A1) datasets.

Housing and climate disasters have a close relation in Vietnam. Cyclones have been seen as the most common and dangerous hazards associated with critical damage and losses of local housing and livelihoods. Besides destructive strengths of cyclones, fragile physical and socio-economic conditions also contribute to increased housing vulnerability to storms. In addition, post-disaster housing reconstruction (PDHR) is still commonly seen as a single recovery action separated from the process of building resilient shelter and settlements in this country. This paper, therefore, examines the issues of disaster resilient housing in the light of PDHR to identify key factors required for a resilient housing system. A case study is applied to investigate these factors with the focus on the NGO Development Workshop France’s donor-built housing and the people’s self-built housing in Loc Tri Commune as the selected case. The results show that housing reconstruction can improve pre-disaster fragilities and needs to be viewed as one of key stages of the housing development process. Findings also suggested that, to build resilient housing, physical unsafe conditions should be focused at the same time of enhancing socio-economic and institutional aspects such as supporting local economy development, applying building permits for safe construction or improving governance mechanisms that low-income vulnerable families can access local professional services (i.e. local architects and engineers) for more regular consultations towards a safe and resilient construction.

There is a gap between 3D Printing’s fast pace of development and the acceptance of 3D Printing technologies by other industries and applications. This hesitation comes mostly from unanswered questions about the consistency, reproducibility, and quality of 3D printed products. Although the list of excellent examples demonstrating its potential keeps expanding, a wide and thorough adoption of the technology requires crucial, yet currently missing elements including consensus standards, quality control procedures, and measuring methodologies. Progress in developing these elements, however, has been rather limited.

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

Aims. To investigate H. pylori infection rate and evaluate a combined set of tests for H. pylori diagnosis in Vietnamese patients with acute peptic ulcer bleeding (PUD). Methods. Consecutive patients with acute PUB were enrolled prospectively. Rapid urease test (RUT) with 3 biopsies was carried out randomly. Patients without RUT or with negative RUT received urea breath test (UBT) and serological and urinary H. pylori antibody tests. H. pylori was considered positive if RUT or any noninvasive test was positive. Patients were divided into group A (RUT plus noninvasive tests) and group B (only noninvasive tests). Results. The overall H. pylori infection rate was 94.2% (161/171). Groups A and B had no differences in demographic characteristics, bleeding severity, endoscopic findings, and proton pump inhibitor use. H. pylori-positive rate in group A was significantly higher than that in group B (98.2% versus 86.7%, p=0.004). The positive rate of RUT was similar at each biopsy site but significantly increased if RUT results from 2 or 3 sites were combined (p<0.05). Conclusions. H. pylori infection rate in Vietnamese patients with acute PUB is high. RUT is an excellent test if at least 2 biopsies are taken.

This chapter details the steps in surgical release of the carpel tunnel. From the palmar side, the transverse carpal ligament is reached, and it is slowly released until full opening of the carpal tunnel. Indications, essential steps, postoperative care, and sample operative dictation are included.

This chapter details the steps in performing a ligament reconstruction and tendon interposition. A subperiosteal longitudinal capsulotomy between the extensor pollicis brevis (EPB) and abductor pollicis longus (APL) tendons is made over the carpometarcarpal and scaphotrapezial joint. The trapezium is dissected and osteophytic bone between base of thumb and index metacarpal is removed. A bone tunnel is created through the first metacarpal. The ulnar half of the flexor carpi radialis (FCR) tendon is transected at the musculotendinous junction and is then passed through the bone tunnel. The tendon is tied and sutured onto itself using Krackow style technique. Remaining tendon is rolled and secured into the arthroplasty space. Indications, essential steps, postoperative care, and sample operative dictation are included.

This chapter describes in detail the surgical steps involved in the transaxillary approach to breast augmentation. While the procedure can be performed without endoscopic assistance, the authors prefer the endoscopic approach to allow for tissue visualization and creation of a precise tissue pocket. Refinements in the approach allow for placement of any breast implant type using a partial subpectoral, subfascial, or subglandular tissue pocket. The focus of this chapter is on partial subpectoral placement of smooth wall silicone gel devices, utilizing endoscopic assistance in creation of the tissue pocket. Indications, preoperative markings, surgical steps, postoperative care, operative dictation, and suggested readings are included.

This chapter details the steps in performing an open approach to cubital tunnel in situ decompression. Decompression is achieved by ulnar nerve dissection and fascia release for minimal compression and traction of the ulnar nerve. Indications, essential steps, postoperative care, and sample operative dictation are included.

This chapter describes in detail the surgical steps involved in the endoscopic approach to brow lift and forehead rejuvenation. Endoscopic assistance is utilized in this procedure. The preferred authors’ method of scalp fixation with the Endotine (Coapt, Inc.) device is discussed, although other fixation techniques can be employed in lieu of the Endotine device. Details of the trans-blepharoplasty approach in conjunction with the top-down endoscopic approach are discussed. Indications, preoperative markings, surgical steps, postoperative care, operative dictation, and suggested readings are included.

This chapter describes in detail the surgical steps involved in the open coronal approach to brow lift. Anatomical landmarks, pitfalls, and planes of dissection at different levels and locations are discussed. Resection of frown muscles and fixation of scalp are outlined. Indications, preoperative markings, surgical steps, postoperative care, operative dictation, and suggested readings are included.

This chapter details the steps in performing the Sauve–Kapandji Procedure. The distal radioulnar joint (DRUJ) is exposed and a segment of the ulnar shaft is resected. Kirschner wires are placed through the ulnar head and the arthrodesis site is packed with autologous bone grafts and fixed with two cannulated screws. Indications, essential steps, postoperative care, and sample operative dictation are included.

We propose a new design of a silicon chip for (de)multiplexing three optical modes based on a tilted-branch bus structure using silicon waveguide. Input lights at fundamental, first-order, and second-order modes in three-dimensional space are simultaneously demultiplexed and converted to three fundamental modes at three individual output ports. The device is designed and optimized via numerical simulation using three-dimensional beam propagation method (3D-BPM). Successful three-mode demultiplexing can be achieved over 150 nm wavelength band of telecom winodws with insertion loss smaller than 1.45 dB and crosstalk below -16 dB. The proposed device also features with a small footprint (8 μm × 950 μm) and a large fabrication tolerance against chip-size variations while maintaining the desired optical performance.

Optical switches are key elements in many applications of optical communication networks. Multimode interference in optical waveguide is interesting in optical switches now. In this paper, a 3×3 all-optical switch based on 3×3 multimode interference (MMI) structures is proposed. This device use electro-optic effects as phase shifters. The switching states of the device can be controlled by adjusting the control voltages at the phase shifters in two arms. The transfer matrix method and numerical simulations are used for designing and optimizing the device structure.

In this paper, we introduce a new two mode division (de) multiplexer with optical properties of broad bandwidth, high mode conversion efficiency that is built on silicon-on-insulator (SOI) platform. By using an asymmetric directional coupler in the form of an MZI structure, mode (de)multiplexer from the fundamental mode TE0 and the firstorder mode TE1 can be achieved by numerically analysis. Performance analysis of the proposed device is carried out numerically. Simulation results by using three dimension beam propagation method (3D-BPM) incorporated with effective index method (EIM) show high performance of the device with operation efficiency larger than 98% (i.e., insertion loss less than 0.1 dB) in the range ±1 nm around the wavelength of 1550 nm.

This paper proposes a method to extract table cells from document images. In standard cases, we can extract the cells using the ruling lines. But, there are also cases where the ruling lines are omitted. In such cases, the existing lines, if any, and the distribution of text blocks is the only information to decompose the table. In our method, the input image is divided into text and lines images. And then, we decompose the table from those two images separately. Finally, we analyze the cells obtained from the previous step and decide the final result of the table decomposition.

This chapter discusses the key findings from the four case studies mentioned in the last chapter in terms of the first theme of this book, Community Participation, Consultation and Communication, in three main sections. The first section is the examination of the consultation and communication forms that emerged from the process of post-disaster housing reconstruction at the case-study sites (Fig. 5.1). The second section is the identification of key stakeholders whose consultative inputs are significant to promoting disaster-resilient housing. The third section focuses on a broader view to examine the need for supportive mechanisms to enable interactive discussions and shared learning dialogues between stakeholders involved in the design, procurement, and construction of local housing.

This paper presents an efficient ASIC implementation of the low area 8-bit AES encryption core using an optimized SBox for wireless networks. The proposed AES core supports 128- bit key length and 128-bit data blocks. The implementation results in a 90nm CMOS standard library show that the proposed AES encryption core has the maximum clock frequency of 452.5 MHz and higher resource usage efficiency compared with other designs.

Purpose: Traditional computed tomography (CT) units provide a maximum scan field-of-view (sFOV) diameter of 50 cm and a limited bore size, which cannot accommodate a large patient habitus or an extended simulation setup in radiation therapy (RT). Wide-bore CT scanners with increased bore size were developed to address these needs. Some scanners have the capacity to reconstruct the CT images at an extended FOV (eFOV), through data interpolation or extrapolation, using projection data acquired with a conventional sFOV. Objects that extend past the sFOV for eFOV reconstruction may generate image artifacts resulting from truncated projection data; this may distort CT numbers and structure contours in the region beyond the sFOV. The purpose of this study was to evaluate the dosimetric impact of image artifacts from eFOV reconstruction with a wide-bore CT scanner in radiotherapy (RT) treatment planning. Methods: Testing phantoms (i.e., a mini CT phantom with equivalent tissue inserts, a set of CT normal phantoms and anthropomorphic phantoms of the thorax and the pelvis) were used to evaluate eFOV artifacts. Reference baseline images of these phantoms were acquired with the phantom centrally positioned within the sFOV. For comparison, the phantoms were then shifted laterally and scanned partially outside the sFOV,more » but still within the eFOV. Treatment plans were generated for the thoracic and pelvic anthropomorphic phantoms utilizing the Eclipse treatment planning system (TPS) to study the potential effects of eFOV artifacts on dose calculations. All dose calculations of baseline and test treatment plans were carried out using the same MU. Results: Results show that both body contour and CT numbers are altered by image artifacts in eFOV reconstruction. CT number distortions of up to -356 HU for bone tissue and up to 323 HU for lung tissue were observed in the mini CT phantom. Results from the large body normal phantom, which is close to a clinical patient size, show average CT number changes of up to -49 HU. Wider distribution (i.e., standard deviation) of the HU values was seen when the phantom was placed at more than 2.8 cm beyond the 50 cm sFOV. Anthropomorphic phantom studies with several standard beam configurations show that body contour distortion causes tumor dose calculation reduction of 3.0 and 1.9% for 6 and 23 MV x-rays, respectively, when not accounting for tissue heterogeneities during dose computation. When heterogeneity correction is used in planning, the competing effects of the body contour distortion and the CT number distortion cause a smaller error in tumor dose calculation. Less than 0.9% error in calculated dose was observed in volumetric modulated arc therapy (VMAT) treatment plans. Conclusions: The image artifacts from eFOV reconstruction alter the CT numbers and body contours of the imaged objects, which has the potential to produce inaccuracies in dose calculations during radiotherapy treatment planning. The radiation therapy team should be aware of these image artifacts and their effects on target dose calculations during CT simulation as well as treatment planning.« less

To carry out a 2D simulation of soft ground improved by vertical drains under embankment combined with vacuum preloading, a method to convert the axisymmetric consolidation of the drain to plane-strain consolidation is needed. The paper presents and verifies a proposed conversion method for a sandwich subsoil, where a sand layer is sandwiched between two clay layers, which is often found in many areas in Japan. The analyzed results showed that the proposed method produced very good matching results, not only for the drain having no-well resistance, but also for the drain having high well resistance in the subsoil.

A separation of text and non-text elements plays an important role in document layout analysis. A number of approaches have been proposed but the quality of separation result is still limited due to the complex of the document layout. In this paper, we present an efficient method for the classification of text and non-text components in document image. It is the combination of whitespace analysis with multi-layer homogeneous regions which called recursive filter. Firstly, the input binary document is analyzed by connected components analysis and whitespace extraction. Secondly, a heuristic filter is applied to identify non-text components. After that, using statistical method, we implement the recursive filter on multi-layer homogeneous regions to identify all text and non-text elements of the binary image. Finally, all regions will be reshaped and remove noise to get the text document and non-text document. Experimental results on the ICDAR2009 page segmentation competition dataset and other datasets prove the effectiveness and superiority of proposed method.

Textual data plays an important role in a number of applications such as image database indexing, document understanding, and image-based web searching. The target of automatic real-life text extracting in document images without character recognition module is to identify image regions that contain only text. These textual regions can then be either input of optical character recognition application or highlighted for user focusing. In this paper we propose a method which consists of three stages-preprocessing which improves contrast of grayscale image, multi-level thresholding for separating textual region from non-textual object such as graphics, pictures, and complex background, and heuristic filter, recursive filter for text localizing in textual region. In many of these applications, it is not necessary to identify all the text regions, therefor we emphasize on identifying important text region with relatively large size and high contrast. Experimental results on real-life dataset images demonstrate that the proposed method is effective in identifying textual region with various illuminations, size and font from various types of background.

Vietnam is undergoing a rapid social and economic developments resulting in speedy urbanization, changes in methods for animal production, food marketing systems, and food consumption habits. These changes will have major impacts on human exposures to food poisoning. The present case study aimed to estimate hospitalization costs of foodborne diarrhea cases in selected health facilities in Vietnam. This is a facility-based cost-of-illness study conducted in seven health facilities in Northern Vietnam. All suspect cases of foodborne diarrhea, as diagnosed by doctors, who admitted to the studied health facilities during June-August, 2013 were selected. Costs associated with hospitalization for foodborne diseases were estimated from societal perspective using retrospective approach. We included direct and indirect costs of hospitalization of foodborne diarrhea cases. During the study period, 87 foodborne diarrhea cases were included. On average, the costs per treatment episode and per hospitalization day for foodborne diarrhea case were US$ 106.9 and US$ 33.6 respectively. Indirect cost (costs of times to patient, their relatives due to the patient's illness) made up the largest share (51.3%). Direct medical costs accounted for 33.8%; direct non-medical costs (patient and their relatives) represented 14.9%. Cost levels and compositions varied by level of health facilities. More attentions should be paid on prevention, control of foodborne diarrhea cases in Vietnam. Ensuring safety of food depends on efforts of everyone involved in food chain continuum, from production, processing, and transport to consumption.

Holographic beam-steering is an attractive way to steer optical beams and potentially to engineer the channel matrix in optical multi-input multi-output systems. In visible-light communications, a partially coherent LED is typically used as the optical source. This paper presents a novel algorithm to design beam-steering holograms for such partially coherent sources. Details of the algorithm and experimental results are shown.