A performance model for a local VoD system

Theme: Trends in Information Systems Engineering and Wireless Multimedia CommunicationsA multimedia information system provides an effective means to convey information to users. This paper studies the problem of carrying out video on demand (VoD) application over a high speed LAN to support Computer Supported Collaborative Working (CSCW) for people working in a local collaborative environment. A multimedia information system using HP 100VG-AnyLAN is proposed and setup for this purpose. Based on this system, a performance model is developed, which can be used to determine the requirement of network bandwidth and evaluate the system performance.published_or_final_versio

Advances in representing interactive methane in ModelE2-YIBs (version 1.1)

This is the final version. Available on open access from EGU via the DOI in this recordCode and data availability: The source code for the site-level YIBs model version 1.0 (Yue and Unger, 2015) is available at https://github.com/YIBS01/YIBS site (last access: 5 August 2015). The source code for the frozen CMIP5/AR5 version of the GISS ModelE2 (Schmidt et al., 2014) can be obtained from NASA GISS (https://www.giss.nasa.gov/tools/modelE/, last access: 31 July 2014). Included as supplemental information are the gridded natural methane fluxes and the numerical model output used to make the figures. Gridded files of natural methane fluxes associated with the Fung et al. (1991) dataset were obtained from NASA GISS (https://data.giss.nasa.gov/ch4_fung/, last access: 4 June 2014). Column-averaged methane concentrations from SCIAMACHY (Schneising et al., 2009) were obtained from the University of Bremen (http://www.iup.uni-bremen.de/sciamachy/NIR_NADIR_WFM_DOAS/index.html, last access: 27 April 2015). Other data used as model input or for analysis of model output are listed in the references.Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry-climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry-climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry-climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the US National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The wetland methane flux is calculated as a best fit; thus, the accuracy of this derived flux assumes accurate simulation of methane chemical loss in the atmosphere and accurate prescription of the other methane fluxes (anthropogenic and natural). The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 yr-1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 yr-1 and a global annual methane soil sink of 60 Tg CH4 yr-1. An interactive methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4±0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to-1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry-climate model is able to capture the principal processes that control atmospheric methane

Severe acute respiratory syndrome coronavirus nucleocapsid protein does not modulate transcription of the human FGL2 gene

Among the structural and nonstructural proteins of severe acute respiratory syndrome coronavirus (SARS-CoV), the nucleocapsid (N) protein plays pivotal roles in the biology and pathogenesis of viral infection. N protein is thought to dysregulate cell signalling and the transcription of cellular genes, including FGL2, which encodes a prothrombinase implicated in vascular thrombosis, fibrin deposition and pneumocyte necrosis. Here, we showed that N protein expressed in cultured human cells was predominantly found in the cytoplasm and was competent in repressing the transcriptional activity driven by interferon-stimulated response elements. However, the expression of N protein did not influence the transcription from the FGL2 promoter. More importantly, N protein did not modulate the expression of FGL2 mRNA or protein in transfected or SARS-CoV-infected cells. Taken together, our findings did not support the model in which SARS-CoV N protein specifically modulates transcription of the FGL2 gene to cause fibrosis and vascular thrombosis. © 2009 SGM.published_or_final_versio

Exploring the Cognitive Foundations of the Shared Attention Mechanism: Evidence for a Relationship Between Self-Categorization and Shared Attention Across the Autism Spectrum.

Published onlineJournal ArticleThis is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.The social difficulties of autism spectrum disorder (ASD) are typically explained as a disruption in the Shared Attention Mechanism (SAM) sub-component of the theory of mind (ToM) system. In the current paper, we explore the hypothesis that SAM's capacity to construct the self-other-object relations necessary for shared-attention arises from a self-categorization process, which is weaker among those with more autistic-like traits. We present participants with self-categorization and shared-attention tasks, and measure their autism-spectrum quotient (AQ). Results reveal a negative relationship between AQ and shared-attention, via self-categorization, suggesting a role for self-categorization in the disruption in SAM seen in ASD. Implications for intervention, and for a ToM model in which weak central coherence plays a role are discussed.This research was supported by the Australian Research Council (FLFL110100199) and the Canadian Institute for Advanced Research (Social Interactions Identity and Well-Being Program)

Ultrasound volume projection image quality selection by ranking from convolutional RankNet.

Periodic inspection and assessment are important for scoliosis patients. 3D ultrasound imaging has become an important means of scoliosis assessment as it is a real-time, cost-effective and radiation-free imaging technique. With the generation of a 3D ultrasound volume projection spine image using our Scolioscan system, a series of 2D coronal ultrasound images are produced at different depths with different qualities. Selecting a high quality image from these 2D images is the crucial task for further scoliosis measurement. However, adjacent images are similar and difficult to distinguish. To learn the nuances between these images, we propose selecting the best image automatically, based on their quality rankings. Here, the ranking algorithm we use is a pairwise learning-to-ranking network, RankNet. Then, to extract more efficient features of input images and to improve the discriminative ability of the model, we adopt the convolutional neural network as the backbone due to its high power of image exploration. Finally, by inputting the images in pairs into the proposed convolutional RankNet, we can select the best images from each case based on the output ranking orders. The experimental result shows that convolutional RankNet achieves better than 95.5% top-3 accuracy, and we prove that this performance is beyond the experience of a human expert

Randomized controlled trial of traditional Chinese medicine (acupuncture and Tuina) in cerebral palsy: Part 1 - Any increase in seizure in integrated acupuncture and rehabilitation group versus rehabilitation group?

Objective: The objective of this study was to observe for any change in baseline seizure frequency with acupuncture in children with cerebral palsy. Methods: A randomized controlled study was conducted: Group I consisted of integrated acupuncture, tuina, and rehabilitation (physiotherapy, occupational therapy, and hydrotherapy) for 12 weeks; and Group II consisted of rehabilitation (physiotherapy, occupational therapy, and hydrotherapy) for 12 weeks. After a washout period of 4 weeks, Group II then received acupuncture and tuina for 12 weeks. Each subject received 5 daily acupuncture sessions per week for 12 weeks (total = 60 sessions). All children were assessed for any change in seizure frequency during treatment. Results: One hundred and sixteen (116) children were recruited and randomized into Group I (N = 58) and Group II (N = 58). Thirty-three (33) children withdrew (9 from Group I and 24 from Group II). Of the remaining 83 children, Group I consisted of 49 and Group II of 34 children. For baseline, 5 children (6%; 5/83) had seizures. During phase 1 (12 weeks) of integrative treatment and subsequent 4-week follow-up, 3 children in Group I had seizures. Among those 3 children with seizures, 1 child with prior history of recurrent febrile seizure had 3 more recurrent febrile seizures during acupuncture treatment and 2 children without any prior history of seizures had new-onset seizures (1 with 3 recurrent febrile seizures and 1 with afebrile seizure). For Group I, 2 children with epilepsy had no increase in seizure frequency during acupuncture treatment. For Group II during the phase 2 acupuncture period, none had increase in seizure frequency. In both groups, 4 of 5 children (80%; 2 in Group I and 2 in Group II) with seizures had no increase in seizure frequency during acupuncture treatment and follow-up. Conclusions: The risk of increasing seizure is not increased with acupuncture treatment for cerebral palsy. © 2008 Mary Ann Liebert, Inc.published_or_final_versio

Development of interfering RNA agents to inhibit SARS-associated coronavirus infection and replication.

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Potent inhibition of SARS-associated coronavirus (SCoV) infection and replication by type I interferons (IFN-α/β) but not by type II interferon (IFN-γ)

We sought to investigate the anti-severe acute respiratory syndrome (SARS)-associated coronavirus (SCoV) activities of type I (α and β) and type II (γ) interferons (IFN) in vitro. Type I IFNs protected cells from cytopathic effects (CPE) induced by SCoV, and inhibited viral genomic RNA replication in FRhk-4 cells (measured by quantitative RT-PCR) in a dose-dependent manner. Intracellular viral RNA copies were reduced 50% by IFN-α at a concentration of 25 U/ml and by IFN-β at a concentration of 14 U/ml. IFN-γ had fewer effects on inhibition of viral infection and replication. The type I IFN receptor signaling pathway in host cells is mainly involved in the inhibition of SCoV infection and replication. Type I IFNs could be used as potential agents for anti-SARS treatment.published_or_final_versio

Synaptic Cleft Segmentation in Non-Isotropic Volume Electron Microscopy of the Complete Drosophila Brain

Neural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems. Volume electron microscopy in serial transmission or scanning mode has been demonstrated to provide the necessary resolution to segment or trace all neurites and to annotate all synaptic connections. Automatic annotation of synaptic connections has been done successfully in near isotropic electron microscopy of vertebrate model organisms. Results on non-isotropic data in insect models, however, are not yet on par with human annotation. We designed a new 3D-U-Net architecture to optimally represent isotropic fields of view in non-isotropic data. We used regression on a signed distance transform of manually annotated synaptic clefts of the CREMI challenge dataset to train this model and observed significant improvement over the state of the art. We developed open source software for optimized parallel prediction on very large volumetric datasets and applied our model to predict synaptic clefts in a 50 tera-voxels dataset of the complete Drosophila brain. Our model generalizes well to areas far away from where training data was available

Impact of the growing healthy mhealth program on maternal feeding practices, infant food preferences, and satiety responsiveness: Quasi-experimental study

© Catherine Georgina Russell, Elizabeth Denney-Wilson, Rachel A Laws, Gavin Abbott, Miaobing Zheng, Sharyn J Lymer, Sarah Taki, Eloise-Kate V Litterbach, Kok-Leong Ong, Karen J Campbell. Background: Infancy is an important life stage for obesity prevention efforts. Parents’ infant feeding practices influence the development of infants’ food preferences and eating behaviors and subsequently diet and weight. Mobile health (mHealth) may provide a feasible medium through which to deliver programs to promote healthy infant feeding as it allows low cost and easy access to tailored content. Objective: The objective of this study was to describe the effects of an mHealth intervention on parental feeding practices, infant food preferences, and infant satiety responsiveness. Methods: A quasi-experimental study was conducted with an mHealth intervention group (Growing Healthy) and a nonrandomized comparison group (“Baby's First Food"). The intervention group received access to a free app with age-appropriate push notifications, a website, and an online forum that provided them with evidence-based advice on infant feeding for healthy growth from birth until 9 months of age. Behavior change techniques were selected using the Behaviour Change Wheel framework. Participants in both groups completed three Web-based surveys, first when their infants were less than 3 months old (baseline, T1), then at 6 months (time 2, T2), and 9 months of age (time 3, T3). Surveys included questions on infant feeding practices and beliefs (Infant Feeding Questionnaire, IFQ), satiety responsiveness (Baby Eating Behaviour Questionnaire), and infant’s food exposure and liking. Multivariate linear regression models, estimated using maximum likelihood with bootstrapped standard errors, were fitted to compare continuous outcomes between the intervention groups, with adjustment for relevant covariates. Multivariate logistic regression adjusting for the same covariates was performed for categorical outcomes. Results: A total of 645 parents (Growing Healthy: n=301, Baby's First Food: n=344) met the eligibility criteria and were included in the study, reducing to a sample size of 546 (Growing Healthy: n=234, Baby's First Food: n=312) at T2 and a sample size of 518 (Growing Healthy: n=225, Baby's First Food: n=293) at T3. There were approximately equal numbers of boy and girl infants, and infants were aged less than 3 months at baseline (Growing Healthy: mean 7.0, SD 3.7 weeks; Baby's First Food: mean 7.9, SD 3.8 weeks), with Growing Healthy infants being slightly younger than Baby's First Food infants (P=.001). All but one (IFQ subscale “concerns about infant overeating or becoming overweight” at T2) of the measured outcomes did not differ between Growing Healthy and Baby's First Food. Conclusions: Although mHealth can be effective in promoting some health behaviors and offers many advantages in health promotion, the results of this study suggest that design and delivery characteristics needed to maximize the impact of mHealth interventions on infant feeding are uncertain. The sensitivity of available measurement tools and differences in baseline characteristics of participants may have also affected the results