Graphic-Card Cluster for Astrophysics (GraCCA) -- Performance Tests

In this paper, we describe the architecture and performance of the GraCCA system, a Graphic-Card Cluster for Astrophysics simulations. It consists of 16 nodes, with each node equipped with 2 modern graphic cards, the NVIDIA GeForce 8800 GTX. This computing cluster provides a theoretical performance of 16.2 TFLOPS. To demonstrate its performance in astrophysics computation, we have implemented a parallel direct N-body simulation program with shared time-step algorithm in this system. Our system achieves a measured performance of 7.1 TFLOPS and a parallel efficiency of 90% for simulating a globular cluster of 1024K particles. In comparing with the GRAPE-6A cluster at RIT (Rochester Institute of Technology), the GraCCA system achieves a more than twice higher measured speed and an even higher performance-per-dollar ratio. Moreover, our system can handle up to 320M particles and can serve as a general-purpose computing cluster for a wide range of astrophysics problems.Comment: Accepted for publication in New Astronom

Efficacy of Sanfujiu to Treat Allergies: Patient Outcomes at 1 Year after Treatment

Sanfujiu is a treatment method of applying herbal paste onto the acupoints Fengmen and Feishu during the three hottest days of summer to treat patients with allergies. The objectives of this study were to determine the treatment efficacy at 1 year after the Sanfujiu treatment, and examine variations in the perceived efficacy of Sanfujiu among different subgroups, based on the patients' ages, diagnoses and number of reactive symptoms immediately after the treatment. We enrolled 105 patients who completed Sanfujiu treatment at a medical university hospital in Taipei as the subjects. One year after treatment, trained interviewers conducted telephone interviews with the patients. Approximately 60% of them perceived the treatment as being effective at 1 year later, which was higher than that at 1 week after treatment (45.7%). Younger subjects (<19 years of age) and patients with asthma were more likely to report the treatment as being effective. Patients who had more reactive symptoms after the third Sanfujiu treatment were more likely to report the treatment as being effective. The results demonstrated that Sanfujiu was moderately effective, as perceived by patients in Taiwan, in treating their allergic symptoms

VNTRDB: a bacterial variable number tandem repeat locus database

Variable number tandem repeat-PCR (VNTR-PCR) is a novel method developed for molecular typing of microorganisms. This method has proven useful in epidemiological studies in medical microbiology. Although hundreds of bacterial genomes have been sequenced, variable number tandem repeats (TRs) derived from comparative genome analyses are scarce. This may hamper their application to the surveillance of bacteria in molecular epidemiology. Here, we present a freely accessible variable number tandem repeat database (VNTRDB) that is intended to be a resource for helping in the discovery of putatively polymorphic tandem repeat loci and to aid with assay design by providing the flanking sequences that can be used in subsequent PCR primer design. In order to reveal possible polymorphism, each TR locus was obtained by comparing the sequences between different sets of bacterial genera, species or strains. Through this comparison, TRs which are unique to a genus can also be identified. Moreover, a visualization tool is provided to ensure that the copy number and locus length of repeats are correct. The VNTRDB is available at

Play as You Like: Timbre-enhanced Multi-modal Music Style Transfer

Style transfer of polyphonic music recordings is a challenging task when considering the modeling of diverse, imaginative, and reasonable music pieces in the style different from their original one. To achieve this, learning stable multi-modal representations for both domain-variant (i.e., style) and domain-invariant (i.e., content) information of music in an unsupervised manner is critical. In this paper, we propose an unsupervised music style transfer method without the need for parallel data. Besides, to characterize the multi-modal distribution of music pieces, we employ the Multi-modal Unsupervised Image-to-Image Translation (MUNIT) framework in the proposed system. This allows one to generate diverse outputs from the learned latent distributions representing contents and styles. Moreover, to better capture the granularity of sound, such as the perceptual dimensions of timbre and the nuance in instrument-specific performance, cognitively plausible features including mel-frequency cepstral coefficients (MFCC), spectral difference, and spectral envelope, are combined with the widely-used mel-spectrogram into a timber-enhanced multi-channel input representation. The Relativistic average Generative Adversarial Networks (RaGAN) is also utilized to achieve fast convergence and high stability. We conduct experiments on bilateral style transfer tasks among three different genres, namely piano solo, guitar solo, and string quartet. Results demonstrate the advantages of the proposed method in music style transfer with improved sound quality and in allowing users to manipulate the output

Deep Learning-based Fall Detection Algorithm Using Ensemble Model of Coarse-fine CNN and GRU Networks

Falls are the public health issue for the elderly all over the world since the fall-induced injuries are associated with a large amount of healthcare cost. Falls can cause serious injuries, even leading to death if the elderly suffers a "long-lie". Hence, a reliable fall detection (FD) system is required to provide an emergency alarm for first aid. Due to the advances in wearable device technology and artificial intelligence, some fall detection systems have been developed using machine learning and deep learning methods to analyze the signal collected from accelerometer and gyroscopes. In order to achieve better fall detection performance, an ensemble model that combines a coarse-fine convolutional neural network and gated recurrent unit is proposed in this study. The parallel structure design used in this model restores the different grains of spatial characteristics and capture temporal dependencies for feature representation. This study applies the FallAllD public dataset to validate the reliability of the proposed model, which achieves a recall, precision, and F-score of 92.54%, 96.13%, and 94.26%, respectively. The results demonstrate the reliability of the proposed ensemble model in discriminating falls from daily living activities and its superior performance compared to the state-of-the-art convolutional neural network long short-term memory (CNN-LSTM) for FD

Method-specific suicide rates and accessibility of means:a small-area analysis in Taipei City, Taiwan

Abstract. Background: Few studies have investigated whether means accessibility is related to the spatial distribution of suicide. Aims: To examine the hypothesis that indicators of the accessibility to specific suicide methods were associated with method-specific suicide rates in Taipei City, Taiwan. Method: Smoothed standardized mortality ratios for method-specific suicide rates across 432 neighborhoods and their associations with means accessibility indicators were estimated using Bayesian hierarchical models. Results: The proportion of single-person households, indicating the ease of burning charcoal in the home, was associated with charcoal-burning suicide rates (adjusted rate ratio [aRR] = 1.13, 95% credible interval [CrI] = 1.03–1.25). The proportion of households living on the sixth floor or above, indicating easy access to high places, was associated with jumping suicide rates (aRR = 1.16, 95% CrI, 1.04–1.29). Neighborhoods’ adjacency to rivers, indicating easy access to water, showed no statistical evidence of an association with drowning suicide rates (aRR = 1.27, 95% CrI = 0.92–1.69). Hanging and overall suicide rates showed no associations with any of these three accessibility indicators. Limitations: This is an ecological study; associations between means accessibility and suicide cannot be directly inferred as causal. Conclusion: The findings have implications for identifying high-risk groups for charcoal-burning suicide (e.g., vulnerable individuals living alone) and preventing jumping suicides by increasing the safety of high buildings