Flight Hardware Packaging Design for Stringent EMC Radiated Emission Requirements

This packaging design approach can help heritage hardware meet a flight project's stringent EMC radiated emissions requirement. The approach requires only minor modifications to a hardware's chassis and mainly concentrates on its connector interfaces. The solution is to raise the surface area where the connector is mounted by a few millimeters using a pedestal, and then wrapping with conductive tape from the cable backshell down to the surface-mounted connector. This design approach has been applied to JPL flight project subsystems. The EMC radiated emissions requirements for flight projects can vary from benign to mission critical. If the project's EMC requirements are stringent, the best approach to meet EMC requirements would be to design an EMC control program for the project early on and implement EMC design techniques starting with the circuit board layout. This is the ideal scenario for hardware that is built from scratch. Implementation of EMC radiated emissions mitigation techniques can mature as the design progresses, with minimal impact to the design cycle. The real challenge exists for hardware that is planned to be flown following a built-to-print approach, in which heritage hardware from a past project with a different set of requirements is expected to perform satisfactorily for a new project. With acceptance of heritage, the design would already be established (circuit board layout and components have already been pre-determined), and hence any radiated emissions mitigation techniques would only be applicable at the packaging level. The key is to take a heritage design with its known radiated emissions spectrum and repackage, or modify its chassis design so that it would have a better chance of meeting the new project s radiated emissions requirements

Near-Infrared Survey and Photometric Redshifts in the Extended GOODS-North field

We present deep $J$ and $H$-band images in the extended Great Observatories Origins Deep Survey-North (GOODS-N) field covering an area of 0.22 $\rm{deg}^{2}$. The observations were taken using WIRCam on the 3.6-m Canada France Hawaii Telescope (CFHT). Together with the reprocessed $K_{\rm s}$-band image, the $5\sigma$ limiting AB magnitudes (in 2" diameter apertures) are 24.7, 24.2, and 24.4 AB mag in the $J$, $H$, and $K_{\rm s}$ bands, respectively. We also release a multi-band photometry and photometric redshift catalog containing 93598 sources. For non-X-ray sources, we obtained a photometric redshift accuracy $\sigma_{\mathrm{NMAD}}=0.036$ with an outlier fraction $\eta = 7.3\%$. For X-ray sources, which are mainly active galactic nuclei (AGNs), we cross-matched our catalog with the updated 2M-CDFN X-ray catalog from Xue et al. (2016) and found that 658 out of 683 X-ray sources have counterparts. $GALEX$ UV data are included in the photometric redshift computation for the X-ray sources to give $\sigma_{\mathrm{NMAD}} = 0.040$ with $\eta=10.5\%$. Our approach yields more accurate photometric redshift estimates compared to previous works in this field. In particular, by adopting AGN-galaxy hybrid templates, our approach delivers photometric redshifts for the X-ray counterparts with fewer outliers compared to the 3D-HST catalog, which fit these sources with galaxy-only templates

The association between socioeconomic status and traditional chinese medicine use among children in Taiwan

<p>Abstract</p> <p>Background</p> <p>Traditional Chinese medicine (TCM) utilization is common in Asian countries. Limited studies are available on the socioeconomic status (SES) associated with TCM use among the pediatric population. We report on the association between SES and TCM use among children and adolescents in Taiwan.</p> <p>Methods</p> <p>A National Health Interview Survey was conducted in Taiwan in 2001 that included 5,971 children and adolescents. We assessed the children's SES using the head of household's education, occupation and income. This information was used to calculate pediatric SES scores, which in turn were divided into quartiles. Children and adolescents who visited TCM in the past month were defined as TCM users.</p> <p>Results</p> <p>Compared to children in the second SES quartile, children in the fourth SES quartile had a higher average number of TCM visits (0.12 vs. 0.06 visits, p = 0.027) and higher TCM use prevalence (5.0% vs. 3.6%, p = 0.024) within the past month. The adjusted odds ratio (OR) for TCM use was higher for children in the fourth SES quartile than for those in the first SES quartile (OR 1.49; 95% confidence interval [CI] 1.02-2.17). The corresponding OR was 2.17 for girls (95% CI 1.24-3.78). The highest-SES girls (aged 10-18 years) were most likely to visit TCM practices (OR 2.47; 95% CI 1.25-4.90).</p> <p>Conclusions</p> <p>Children and adolescents with high SES were more likely to use TCM and especially girls aged 10-18 years. Our findings point to the high use of complementary and alternative medicine among children and adolescents.</p

5-Fluorouracil Induced Intestinal Mucositis via Nuclear Factor-κB Activation by Transcriptomic Analysis and In Vivo Bioluminescence Imaging

5-Fluorouracil (5-FU) is a commonly used drug for the treatment of malignant cancers. However, approximately 80% of patients undergoing 5-FU treatment suffer from gastrointestinal mucositis. The aim of this report was to identify the drug target for the 5-FU-induced intestinal mucositis. 5-FU-induced intestinal mucositis was established by intraperitoneally administering mice with 100 mg/kg 5-FU. Network analysis of gene expression profile and bioluminescent imaging were applied to identify the critical molecule associated with 5-FU-induced mucositis. Our data showed that 5-FU induced inflammation in the small intestine, characterized by the increased intestinal wall thickness and crypt length, the decreased villus height, and the increased myeloperoxidase activity in tissues and proinflammatory cytokine production in sera. Network analysis of 5-FU-affected genes by transcriptomic tool showed that the expression of genes was regulated by nuclear factor-κB (NF-κB), and NF-κB was the central molecule in the 5-FU-regulated biological network. NF-κB activity was activated by 5-FU in the intestine, which was judged by in vivo bioluminescence imaging and immunohistochemical staining. However, 5-aminosalicylic acid (5-ASA) inhibited 5-FU-induced NF-κB activation and proinflammatory cytokine production. Moreover, 5-FU-induced histological changes were improved by 5-ASA. In conclusion, our findings suggested that NF-κB was the critical molecule associated with the pathogenesis of 5-FU-induced mucositis, and inhibition of NF-κB activity ameliorated the mucosal damage caused by 5-FU

SAQC: SNP Array Quality Control

<p>Abstract</p> <p>Background</p> <p>Genome-wide single-nucleotide polymorphism (SNP) arrays containing hundreds of thousands of SNPs from the human genome have proven useful for studying important human genome questions. Data quality of SNP arrays plays a key role in the accuracy and precision of downstream data analyses. However, good indices for assessing data quality of SNP arrays have not yet been developed.</p> <p>Results</p> <p>We developed new quality indices to measure the quality of SNP arrays and/or DNA samples and investigated their statistical properties. The indices quantify a departure of estimated individual-level allele frequencies (AFs) from expected frequencies via standardized distances. The proposed quality indices followed lognormal distributions in several large genomic studies that we empirically evaluated. AF reference data and quality index reference data for different SNP array platforms were established based on samples from various reference populations. Furthermore, a confidence interval method based on the underlying empirical distributions of quality indices was developed to identify poor-quality SNP arrays and/or DNA samples. Analyses of authentic biological data and simulated data show that this new method is sensitive and specific for the detection of poor-quality SNP arrays and/or DNA samples.</p> <p>Conclusions</p> <p>This study introduces new quality indices, establishes references for AFs and quality indices, and develops a detection method for poor-quality SNP arrays and/or DNA samples. We have developed a new computer program that utilizes these methods called SNP Array Quality Control (SAQC). SAQC software is written in R and R-GUI and was developed as a user-friendly tool for the visualization and evaluation of data quality of genome-wide SNP arrays. The program is available online (<url>http://www.stat.sinica.edu.tw/hsinchou/genetics/quality/SAQC.htm</url>).</p

A framework for human microbiome research

A variety of microbial communities and their genes (the microbiome) exist throughout the human body, with fundamental roles in human health and disease. The National Institutes of Health (NIH)-funded Human Microbiome Project Consortium has established a population-scale framework to develop metagenomic protocols, resulting in a broad range of quality-controlled resources and data including standardized methods for creating, processing and interpreting distinct types of high-throughput metagenomic data available to the scientific community. Here we present resources from a population of 242 healthy adults sampled at 15 or 18 body sites up to three times, which have generated 5,177 microbial taxonomic profiles from 16S ribosomal RNA genes and over 3.5 terabases of metagenomic sequence so far. In parallel, approximately 800 reference strains isolated from the human body have been sequenced. Collectively, these data represent the largest resource describing the abundance and variety of the human microbiome, while providing a framework for current and future studies

Structure, function and diversity of the healthy human microbiome

Author Posting. © The Authors, 2012. This article is posted here by permission of Nature Publishing Group. The definitive version was published in Nature 486 (2012): 207-214, doi:10.1038/nature11234.Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this diversity remains unexplained, although diet, environment, host genetics and early microbial exposure have all been implicated. Accordingly, to characterize the ecology of human-associated microbial communities, the Human Microbiome Project has analysed the largest cohort and set of distinct, clinically relevant body habitats so far. We found the diversity and abundance of each habitat’s signature microbes to vary widely even among healthy subjects, with strong niche specialization both within and among individuals. The project encountered an estimated 81–99% of the genera, enzyme families and community configurations occupied by the healthy Western microbiome. Metagenomic carriage of metabolic pathways was stable among individuals despite variation in community structure, and ethnic/racial background proved to be one of the strongest associations of both pathways and microbes with clinical metadata. These results thus delineate the range of structural and functional configurations normal in the microbial communities of a healthy population, enabling future characterization of the epidemiology, ecology and translational applications of the human microbiome.This research was supported in part by National Institutes of Health grants U54HG004969 to B.W.B.; U54HG003273 to R.A.G.; U54HG004973 to R.A.G., S.K.H. and J.F.P.; U54HG003067 to E.S.Lander; U54AI084844 to K.E.N.; N01AI30071 to R.L.Strausberg; U54HG004968 to G.M.W.; U01HG004866 to O.R.W.; U54HG003079 to R.K.W.; R01HG005969 to C.H.; R01HG004872 to R.K.; R01HG004885 to M.P.; R01HG005975 to P.D.S.; R01HG004908 to Y.Y.; R01HG004900 to M.K.Cho and P. Sankar; R01HG005171 to D.E.H.; R01HG004853 to A.L.M.; R01HG004856 to R.R.; R01HG004877 to R.R.S. and R.F.; R01HG005172 to P. Spicer.; R01HG004857 to M.P.; R01HG004906 to T.M.S.; R21HG005811 to E.A.V.; M.J.B. was supported by UH2AR057506; G.A.B. was supported by UH2AI083263 and UH3AI083263 (G.A.B., C. N. Cornelissen, L. K. Eaves and J. F. Strauss); S.M.H. was supported by UH3DK083993 (V. B. Young, E. B. Chang, F. Meyer, T. M. S., M. L. Sogin, J. M. Tiedje); K.P.R. was supported by UH2DK083990 (J. V.); J.A.S. and H.H.K. were supported by UH2AR057504 and UH3AR057504 (J.A.S.); DP2OD001500 to K.M.A.; N01HG62088 to the Coriell Institute for Medical Research; U01DE016937 to F.E.D.; S.K.H. was supported by RC1DE0202098 and R01DE021574 (S.K.H. and H. Li); J.I. was supported by R21CA139193 (J.I. and D. S. Michaud); K.P.L. was supported by P30DE020751 (D. J. Smith); Army Research Office grant W911NF-11-1-0473 to C.H.; National Science Foundation grants NSF DBI-1053486 to C.H. and NSF IIS-0812111 to M.P.; The Office of Science of the US Department of Energy under Contract No. DE-AC02-05CH11231 for P.S. C.; LANL Laboratory-Directed Research and Development grant 20100034DR and the US Defense Threat Reduction Agency grants B104153I and B084531I to P.S.C.; Research Foundation - Flanders (FWO) grant to K.F. and J.Raes; R.K. is an HHMI Early Career Scientist; Gordon&BettyMoore Foundation funding and institutional funding fromthe J. David Gladstone Institutes to K.S.P.; A.M.S. was supported by fellowships provided by the Rackham Graduate School and the NIH Molecular Mechanisms in Microbial Pathogenesis Training Grant T32AI007528; a Crohn’s and Colitis Foundation of Canada Grant in Aid of Research to E.A.V.; 2010 IBM Faculty Award to K.C.W.; analysis of the HMPdata was performed using National Energy Research Scientific Computing resources, the BluBioU Computational Resource at Rice University