Experiences with Implementing Parallel Discrete-event Simulation on GPU

Modern graphics processing units (GPUs) offer much more computational power than recent CPUs by providing a vast number of simple, data-parallel, multithreaded cores. In this study, we focus on the use of a GPU to perform parallel discrete-event simulation. Our approach is to use a modified service time distribution function to allow more independent events to be processed in parallel. The implementation issues and alternative strategies will be discussed in detail. We describe and compare our experience and results in using Thrust and CUB, two open-source parallel algorithms libraries which resemble the C++ Standard Template Library, to build our tool. The experimental results show that our implementation can be two orders of magnitude faster than the sequential simulation for large-scale simulation models

Use of Multi-Functional Flexible Micro-Sensors for in situ Measurement of Temperature, Voltage and Fuel Flow in a Proton Exchange Membrane Fuel Cell

Temperature, voltage and fuel flow distribution all contribute considerably to fuel cell performance. Conventional methods cannot accurately determine parameter changes inside a fuel cell. This investigation developed flexible and multi-functional micro sensors on a 40 μm-thick stainless steel foil substrate by using micro-electro-mechanical systems (MEMS) and embedded them in a proton exchange membrane fuel cell (PEMFC) to measure the temperature, voltage and flow. Users can monitor and control in situ the temperature, voltage and fuel flow distribution in the cell. Thereby, both fuel cell performance and lifetime can be increased

Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis

Cardiovascular diseases are one of the leading global causes of mortality. Currently, clinicians rely on their own analyses or automated analyses of the electrocardiogram (ECG) to obtain a diagnosis. However, both approaches can only include a finite number of predictors and are unable to execute complex analyses. Artificial intelligence (AI) has enabled the introduction of machine and deep learning algorithms to compensate for the existing limitations of current ECG analysis methods, with promising results. However, it should be prudent to recognize that these algorithms also associated with their own unique set of challenges and limitations, such as professional liability, systematic bias, surveillance, cybersecurity, as well as technical and logistical challenges. This review aims to increase familiarity with and awareness of AI algorithms used in ECG diagnosis, and to ultimately inform the interested stakeholders on their potential utility in addressing present clinical challenges

Compact stellar systems in the Fornax cluster: a UV perspective

In recent years, increasing evidence for chemical complexity and multiple stellar populations in massive globular clusters (GCs) has emerged, including extreme horizontal branches (EHBs) and UV excess. Our goal is to improve our understanding of UV excess in the regime of both massive GCs and ultra-compact dwarf galaxies (UCDs). To this end, we use deep archival GALEX data of the central Fornax cluster to measure NUV and FUV magnitudes of UCDs and massive GCs. We obtain NUV photometry for a sample of 35 compact objects with -13.5<M_V<-10 mag. Of those, 21 objects also have FUV photometry. Roughly half of the sources fall into the UCD luminosity regime (M_V <=-11 mag). We find that seven out of 17 massive Fornax GCs exhibit a NUV excess with respect to expectations from stellar population models, even for models with enhanced Helium abundance. This suggests that not only He-enrichment has contributed to forming the EHB population of these GCs. The GCs extend to stronger UV excess than GCs in M31 and massive GCs in M87, at the 97% confidence level. Most of the UCDs with FUV photometry also show evidence for UV excess, but their UV colours can be matched by isochrones with enhanced Helium abundances and old ages 12-14 Gyrs. We find that Fornax compact objects with X-ray emission detected from Chandra images are almost disjunct in colour from compact objects with GALEX UV detection, with only one X-ray source among the 35 compact objects. However, since this source is one of the three most UV bright GCs, we cannot exclude that the physical processes causing X-ray emission also contribute to some of the observed UV excess.Comment: Research Note, 7 pages, 3 figures, accepted for publication in A&

The role of JAK-STAT signalling in the developing brain of Ts1Cje mouse model for Down syndrome

Introduction: The JAK-STAT signalling pathway is essential for proper regulation of the gliogenesis process during brain development. Both Down syndrome (DS) individuals and DS mouse model showed reduced number of neuron but increase number of astrocyte in the brain; suggesting that dysregulation of JAK-STAT signalling pathway may have occurred and led to neurogenic-to-gliogenic shift in the DS brain. Such a shift in the DS brain may contribute to the intellectual disability seen in the DS individual and learning and memory impairment in the mouse model. Therefore, understanding the role JAK-STAT signalling in the DS brain at early stage may implicate the underlying mechanism(s) causing the shift and provide novel therapeutics targets for cognition therapy among DS individuals. Method: In this study, the whole brain of Ts1Cje and disomic mice was collected at embryonic day (E) 10.5, E14 and postnatal day (P) 1.5. Here, we focus on Jak1, Jak2, Stat1, Stat3 and Stat6, which have been shown to express highly or stably during early brain development. Results: Both RT-qPCR and western blot analysis revealed the expression of Jak1 as significantly reduced in Ts1Cje at E14. In addition, phosphorylated Jak2 and Stat6 expression levels were decreased in Ts1Cje at E14 as compared to disomic mice. Our findings suggest that JAK1 is important for astrocytic differentiation while JAK2 is essential for neural stem cells proliferation and STAT6 is crucial in mediating immune signalling. Thus, further investigation on the function of Jak1, Jak2 and Stat6 may provide insight into neurogenic-to-gliogenic shift occur in the DS brain

Nanoparticles prepared from the water extract of Gusuibu (Drynaria fortunei J. Sm.) protects osteoblasts against insults and promotes cell maturation

Our previous study showed that Gusuibu (Drynaria fortunei J. Sm.) can stimulate osteoblast maturation. This study was further designed to evaluate the effects of nanoparticles prepared from the water extract of Gusuibu (WEG) on osteoblast survival and maturation. Primary osteoblasts were exposed to 1, 10, 100, and 1000 μg/mL nanoparticles of WEG (nWEG) for 24, 48, and 72 hours did not affect morphologies, viability, or apoptosis of osteoblasts. In comparison, treatment of osteoblasts with 1000 μg/mL WEG for 72 hours decreased cell viability and induced DNA fragmentation and cell apoptosis. nWEG had better antioxidant bioactivity in protecting osteoblasts from oxidative and nitrosative stress-induced apoptosis than WEG. In addition, nWEG stimulated greater osteoblast maturation than did WEG. Therefore, this study shows that WEG nanoparticles are safer to primary osteoblasts than are normal-sized products, and may promote better bone healing by protecting osteoblasts from apoptotic insults, and by promoting osteogenic maturation

Energetic Protons and Deuterons Emitted Following μ⁻ Capture by ³He Nuclei

Spectra of energetic protons and deuterons emitted following negative muon capture from rest in 3He have been measured for the first time. Significant capture strength is observed at high energy transfers (mμ- Ev \u3e60 MeV) for the two-body and three-body breakup channels, indicative of the importance of nucleon-nucleon correlations and meson exchange currents in the capture process. A simple plane wave impulse approximation calculation reproduces the proton spectrum reasonably well, but underpredicts the deuteron rate at the highest energies by a large factor