Comparison of Renal Function and Other Health Outcomes in Vegetarians versus Omnivores in Taiwan

Renal disease is one of the top 10 leading causes of death, and the incidence of end-stage renal disease in Taiwan is the highest in the world. Many dietitians consider the diet of plant origin consumed by vegans to be ‘lighter’ and ‘more healthful’ than the diet of both plant and animal origin consumed by omnivores. Dietary protein has significant effects on renal functions. The study explored the effects of both the diets on renal functions. The study subjects included 102 Buddhist nun vegetarians and an equal number of matched control group (omnivores). A cross-sectional study was performed to investigate the effects of the diet of plant origin and the diet of both plant and animal origin on renal functions. There was no difference in the renal functions between the two groups. However, systolic blood pressure, blood urea nitrogen, serum sodium, glucose, cholesterol levels, and urinary specific gravity were lower in the vegetarian group. Although these results were compatible with general concepts regarding diet of plant origin, after adjusting for age, the duration of intake of this diet had no effect on the renal functions. Based on the findings, it is concluded that the renal functions, in terms of the estimated glomerular filtration rate, were not different between the vegetarians and the omnivores

Detecting Slow Wave Sleep Using a Single EEG Signal Channel

Background: In addition to the cost and complexity of processing multiple signal channels, manual sleep staging is also tedious, time consuming, and error-prone. The aim of this paper is to propose an automatic slow wave sleep (SWS) detection method that uses only one channel of the electroencephalography (EEG) signal. New Method: The proposed approach distinguishes itself from previous automatic sleep staging methods by using three specially designed feature groups. The first feature group characterizes the waveform pattern of the EEG signal. The remaining two feature groups are developed to resolve the difficulties caused by interpersonal EEG signal differences. Results and comparison with existing methods: The proposed approach was tested with 1,003 subjects, and the SWS detection results show kappa coefficient at 0.66, an accuracy level of 0.973, a sensitivity score of 0.644 and a positive predictive value of 0.709. By excluding sleep apnea patients and persons whose age is older than 55, the SWS detection results improved to kappa coefficient, 0.76; accuracy, 0.963; sensitivity, 0.758; and positive predictive value, 0.812. Conclusions: With newly developed signal features, this study proposed and tested a single-channel EEG-based SWS detection method. The effectiveness of the proposed approach was demonstrated by applying it to detect the SWS of 1003 subjects. Our test results show that a low SWS ratio and sleep apnea can degrade the performance of SWS detection. The results also show that a large and accurately staged sleep dataset is of great importance when developing automatic sleep staging methods

KINEMATIC AND ELECTROMYOGRAPHIC ANALYSIS OF UPPER EXTREMITY IN ARM WRESTLING

Few studies of the kinematic features of arm wrestling exercise have been published. The purpose of this study was to initiate a concrete analysis of the kinematic characteristics and muscular activities involved in arm wrestling exercise. 12 healthy male volunteers were recruited in this study. The pectoralis major (PMJ) showed significantly higher muscle activity in winning position than in losing position (p=.039) and had significant influence on arm wrestling outcome (

Developing Mobile BIM/2D Barcode-Based Automated Facility Management System

Facility management (FM) has become an important topic in research on the operation and maintenance phase. Managing the work of FM effectively is extremely difficult owing to the variety of environments. One of the difficulties is the performance of two-dimensional (2D) graphics when depicting facilities. Building information modeling (BIM) uses precise geometry and relevant data to support the facilities depicted in three-dimensional (3D) object-oriented computer-aided design (CAD). This paper proposes a new and practical methodology with application to FM that uses an integrated 2D barcode and the BIM approach. Using 2D barcode and BIM technologies, this study proposes a mobile automated BIM-based facility management (BIMFM) system for FM staff in the operation and maintenance phase. The mobile automated BIMFM system is then applied in a selected case study of a commercial building project in Taiwan to verify the proposed methodology and demonstrate its effectiveness in FM practice. The combined results demonstrate that a BIMFM-like system can be an effective mobile automated FM tool. The advantage of the mobile automated BIMFM system lies not only in improving FM work efficiency for the FM staff but also in facilitating FM updates and transfers in the BIM environment

ATACgraph: Profiling genome-wide chromatin accessibility from ATAC-seq

Assay for transposase-accessible chromatin using sequencing data (ATAC-seq) is an efficient and precise method for revealing chromatin accessibility across the genome. Most of the current ATAC-seq tools follow chromatin immunoprecipitation sequencing (ChIP-seq) strategies that do not consider ATAC-seq-specific properties. To incorporate specific ATAC-seq quality control and the underlying biology of chromatin accessibility, we developed a bioinformatics software named ATACgraph for analyzing and visualizing ATAC-seq data. ATACgraph profiles accessible chromatin regions and provides ATAC-seq-specific information including definitions of nucleosome-free regions (NFRs) and nucleosome-occupied regions. ATACgraph also allows identification of differentially accessible regions between two ATAC-seq datasets. ATACgraph incorporates the docker image with the Galaxy platform to provide an intuitive user experience via the graphical interface. Without tedious installation processes on a local machine or cloud, users can analyze data through activated websites using pre-designed workflows or customized pipelines composed of ATACgraph modules. Overall, ATACgraph is an effective tool designed for ATAC-seq for biologists with minimal bioinformatics knowledge to analyze chromatin accessibility. ATACgraph can be run on any ATAC-seq data with no limit to specific genomes. As validation, we demonstrated ATACgraph on human genome to showcase its functions for ATAC-seq interpretation. This software is publicly accessible and can be downloaded at https://github.com/RitataLU/ATACgraph

Optical music recognition of the singer using formant frequency estimation of vocal fold vibration and lip motion with interpolated GMM classifiers

The main work of this paper is to identify the musical genres of the singer by performing the optical detection of lip motion. Recently, optical music recognition has attracted much attention. Optical music recognition in this study is a type of automatic techniques in information engineering, which can be used to determine the musical style of the singer. This paper proposes a method for optical music recognition where acoustic formant analysis of both vocal fold vibration and lip motion are employed with interpolated Gaussian mixture model (GMM) estimation to perform musical genre classification of the singer. The developed approach for such classification application is called GMM-Formant. Since humming and voiced speech sounds cause periodic vibrations of the vocal folds and then the corresponding motion of the lip, the proposed GMM-Formant firstly operates to acquire the required formant information. Formant information is important acoustic feature data for recognition classification. The proposed GMM-Formant method then uses linear interpolation for combining GMM likelihood estimates and formant evaluation results appropriately. GMM-Formant will effectively adjust the estimated formant feature evaluation outcomes by referring to certain degree of the likelihood score derived from GMM calculations. The superiority and effectiveness of presented GMM-Formant are demonstrated by a series of experiments on musical genre classification of the singer

Bridge scour evaluation based on ambient vibration

The vulnerability of bridges to hazards such as earthquakes, wind and floods necessitates special structural characteristics. To guarantee the stability of bridge structures, the precise evaluation of the scour depth of bridge foundation has recently become an important issue, as most of the unexpected damage to or collapse of bridges has been attributed to hydraulic issues. In this paper, a vibration-based bridge health monitoring system that utilizes only the response of superstructure to rapidly evaluate the embedded depth of a bridge column is proposed. To clarify the complex fluid-solid coupling phenomenon, the effects of embedded depth and water level were first verified through a series of static experiments. A confined finite element model simulated by soil spring effects was then established to illustrate the relationship between the fundamental frequency and the embedded depth. Using the proposed algorithm, the health of the bridge is able to be inferred by processing the ambient vibration response of the superstructure. To implement the proposed algorithm, a SHM prototype system monitoring environmental factors such as temperature, water level, and inclination was developed to support on-line processing. The performance of the proposed system was verified by a series of dynamic bridge scour experiments conducted in a laboratory flume and compared with readings from a water-proof camera. The results showed that using the proposed vibration-based bridge health monitoring system, the embedded depth of bridge column during complex scour processes is able to be reliably calculated