FUZZY C-MEANS CLUSTERING FOR MYOCARDIAL ISCHEMIA ESTIMATION WITH PULSE WAVEFORM ANALYSIS

[[abstract]]The purpose of this study is to build an automatic disease classification algorithm by pulse waveform analysis, based on a Fuzzy C-means clustering algorithm. A self designed three-axis mechanism was used to detect the optimal position to accurately measure the pressure pulse waveform (PPW). Considering the artery as a cylinder, the sensor should detect the PPW with the lowest possible distortion, and hence an analysis of the vascular geometry and an arterial model were used to design a standard positioning procedure based on the arterial diameter changed waveform for the X-axes ( perpendicular to the forearm) and Z-axes ( perpendicular to the radial artery). A fuzzy C-means algorithm was used to estimate the myocardial ischemia symptoms in 35 elderly subjects with the PPW of the radial artery. Two type parameters were used to make the features, one was a harmonic value of Fourier transfer, and the other was a form factor value. A receiver operating characteristics curve was used to determine the optimal decision function. The harmonic feature vector contain second, third and fourth harmonics (H-2, H-3, H-4) performed at the level of 69% for sensitivity and 100% for specificity while the form factor feature vector derived from left hand (LFF) and right hand (RFF) performed at the level of 100% for sensitivity and 53% for specificity. The FCM- and ROC-based clustering approach may become an efficient alternative for distinguishing patients in the risk of myocardial ischemia, besides the traditional exercise ECG examination

A novel compliance measurement in radial arteries using strain-gauge plethysmography

[[abstract]]We propose a novel method for assessing the compliance of the radial artery by using a two-axis mechanism and a standard positioning procedure for detecting the optimal measuring site. A modified sensor was designed to simultaneously measure the arterial diameter change waveform (ADCW) and pressure pulse waveform with a strain gauge and piezoresistor. In the x-axis scanning, the sensor could be placed close to the middle of the radial artery when the ADCW reached the maximum amplitude. In the z-axis scanning, the contact pressure was continuously increased for data measurement. Upon the deformation of the strain gauge following the change in the vascular cross-section, the ADCW was transferred to the change of the vascular radius. The loaded strain compliance of the radial artery (C-strain) can be determined by dividing the dynamic changed radius by the pulse pressure. Twenty-three untreated, mild or moderate hypertensive patients aged 29-85 were compared with 14 normotensive patients aged 25-62. The maximum strain compliance between the two groups was significantly different (p < 0.005). Of the hypertensive patients, 14 were at risk of developing hyperlipidemia. There was a significant difference between this and the normotension group (p < 0.005)

PROTINFO: new algorithms for enhanced protein structure predictions

We describe new algorithms and modules for protein structure prediction available as part of the PROTINFO web server. The modules, comparative and de novo modelling, have significantly improved back-end algorithms that were rigorously evaluated at the sixth meeting on the Critical Assessment of Protein Structure Prediction methods. We were one of four server groups invited to make an oral presentation (only the best performing groups are asked to do so). These two modules allow a user to submit a protein sequence and return atomic coordinates representing the tertiary structure of that protein. The PROTINFO server is available at

Deep convolutional neural network classifier for travel patterns using binary sensors

The early detection of dementia is crucial in independent life style of elderly people. Main intention of this study is to propose device-free non-privacy invasive Deep Convolutional Neural Network classifier (DCNN) for Martino-Saltzman's (MS) travel patterns of elderly people living alone using open dataset collected by binary (passive infrared) sensors. Travel patterns are classified as direct, pacing, lapping, or random according to MS model. MS travel pattern is highly related with person's cognitive state, thus can be used to detect early stage of dementia. The dataset was collected by monitoring a cognitively normal elderly resident by wireless passive infrared sensors for 21 months. First, over 70000 travel episodes are extracted from the dataset and classified by MS travel pattern classifier algorithm for the ground truth. Later, 12000 episodes (3000 for each pattern) were randomly selected from the total episodes to compose training and testing dataset. Finally, DCNN performance was compared with three other classical machine-learning classifiers. The Random Forest and DCNN yielded the best classification accuracies of 94.48% and 97.84%, respectively. Thus, the proposed DCNN classifier can be used to infer dementia through travel pattern matching

The Physical Effects of Aromatherapy in Alleviating Work-Related Stress on Elementary School Teachers in Taiwan

People use aromatherapy to relieve the symptoms of physical and psychological stress. However, previous studies have not precisely clarified a scientific basis for the beneficial effects of aromatherapy. Therefore, the overall purpose of this study was to elucidate the beneficial effect of aromatherapy in relieving work-related stress. Twenty-nine elementary school teachers from Taiwan participated in this study. The experimental procedures comprised 2 phases. First, we verified the effect of aromatherapy by conducting 2 blind tests. We used natural bergamot essential oil extracted from plants and synthesized a chemical essential oil as the placebo to do the aromatherapy. Second, we analyzed the performance of the aromatherapy treatment on the teachers who had various workloads. We measured the teachers’ heart rate variability to evaluate their autonomic nervous system activity. The results show that only the natural bergamot essential oil had an effect and that the aromatherapy treatment relieved work-related stress of teachers with various workloads. However, the aromatherapy treatment had a weak effect on young teachers who had a heavy workload. Moreover, the aromatherapy treatment exhibited no effect on teachers who belong to the abnormal body mass index subgroup having a heavy workload

Effects of Moderate Exercise on Relieving Mental Load of Elementary School Teachers

Long-term endurance exercise could increase activity of parasympathetic nervous and decrease activity of sympathetic nervous at rest. However, previous studies all focused on the effect of endurance training on heart rate variability (HRV) for athletes or sedentary subjects. In Taiwan, elementary school teachers teaching and processing the children’s and administrative problems always stand and walk. They will sit down only when they review and correct the students’ home work. Thus, the goal of this study was to elucidate the beneficial effect of moderate intensity exercise on relieving mental load of elementary school teachers. There were 20 participants in the exercise group and another 20 participants in the nonexercise group. The exercising teachers performed 12 weeks of moderate intensity exercise training for an average of 30 minutes per day, 3 times per week. HRV was measured before and after the 4th, 6th, and 12th weeks. The time and frequency domain parameters of HRV all had significant increases between the beginning and after 12 weeks of training. However, the time and frequency domain parameters of HRV in the nonexercise group had significant decreases between the beginning and after 12 weeks of training. The long-term moderate exercises can relieve mental load of elementary school teachers. Moreover, age was the considerable factor affecting HRV in this study

Automatic detection of the carotid artery boundary on cross-sectional MR image sequences using a circle model guided dynamic programming

Systematic aerobe training has positive effects on the compliance of dedicated arterial walls. The adaptations of the arterial structure and function are associated with the blood flow-induced changes of the wall shear stress which induced vascular remodelling via nitric oxide delivered from the endothelial cell. In order to assess functional changes of the common carotid artery over time in these processes, a precise measurement technique is necessary. Before this study, a reliable, precise, and quick method to perform this work is not present

Screening and Evaluation of Polyhydroxybutyrate-Producing Strains from Indigenous Isolate Cupriavidus taiwanensis Strains

Polyhydroxyalkanoate (PHA) is a biodegradable material with many potential biomedical applications, including medical implants and drug delivery. This study developed a system for screening production strains in order to optimize PHA production in Cupriavidus taiwanensis 184, 185, 186, 187, 204, 208, 209 and Pseudomona oleovorans ATCC 29347. In this study, Sudan black B staining, Infrared (IR) and Gas Chromatography (GC) analysis indicated that the best strain for PHA synthesis is C. taiwanensis 184, which obtains polyhydroxybutyrate (PHB). Cultivation of C. taiwanensis 184 under a pH of 7.0, at 30 °C, and at an agitation rate of 200 rpm, obtained a PHB content of 10% and PHB production of 0.14 g/L. The carbon and nitrogen types selected for analysis of PHB production by C. taiwanensis 184 were gluconic acid and NH4Cl, respectively. Optimal carbon/nitrogen ratio for PHB production was also determined. This study demonstrated a PHB content of 58.81% and a PHB production of 2.44 g/L when the carbon/nitrogen ratio of 8/1 was selected for C. taiwanensis 184. A two-stage fermentation strategy significantly enhanced PHB content and PHB production. Under a two-stage fermentation strategy with nutrient-limited conditions, C. taiwanensis 184 obtained a PHB content of 72% and a PHB concentration of 7 g/L. Finally, experimental results confirmed that optimizing the growth medium and fermentation conditions for cultivating the indigenous C. taiwanensis 184 strain substantially elevated PHB content from 10% to 72% and PHB production from 0.14 g/L to 7 g/L, respectively

ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP) : How Do Dense Core Properties Affect the Multiplicity of Protostars?

During the transition phase from a prestellar to a protostellar cloud core, one or several protostars can form within a single gas core. The detailed physical processes of this transition, however, remain unclear. We present 1.3 mm dust continuum and molecular line observations with the Atacama Large Millimeter/submillimeter Array toward 43 protostellar cores in the Orion molecular cloud complex (lambda Orionis, Orion B, and Orion A) with an angular resolution of similar to 0.'' 35 (similar to 140 au). In total, we detect 13 binary/multiple systems. We derive an overall multiplicity frequency (MF) of 28% +/- 4% and a companion star fraction (CSF) of 51% +/- 6%, over a separation range of 300-8900 au. The median separation of companions is about 2100 au. The occurrence of stellar multiplicity may depend on the physical characteristics of the dense cores. Notably, those containing binary/multiple systems tend to show a higher gas density and Mach number than cores forming single stars. The integral-shaped filament of the Orion A giant molecular cloud (GMC), which has the highest gas density and hosts high-mass star formation in its central region (the Orion Nebula cluster), shows the highest MF and CSF among the Orion GMCs. In contrast, the lambda Orionis GMC has a lower MF and CSF than the Orion B and Orion A GMCs, indicating that feedback from H ii regions may suppress the formation of multiple systems. We also find that the protostars comprising a binary/multiple system are usually at different evolutionary stages.Peer reviewe