Identification of nonlinear heat transfer laws from boundary observations

We consider the problem of identifying a nonlinear heat transfer law at the boundary, or of the temperature-dependent heat transfer coefficient in a parabolic equation from boundary observations. As a practical example, this model applies to the heat transfer coefficient that describes the intensity of heat exchange between a hot wire and the cooling water in which it is placed. We reformulate the inverse problem as a variational one which aims to minimize a misfit functional and prove that it has a solution. We provide a gradient formula for the misfit functional and then use some iterative methods for solving the variational problem. Thorough investigations are made with respect to several initial guesses and amounts of noise in the input data. Numerical results show that the methods are robust, stable and accurate

Prevalence of Antibodies against Avian Influenza A (H5N1) Virus among Cullers and Poultry Workers in Ho Chi Minh City, 2005

Background: Between 2003 and 2005, highly pathogenic avian influenza A (H5N1) viruses caused large scale outbreaks in poultry in the Ho Chi Minh City area in Vietnam. We studied the prevalence of antibodies against H5N1 in poultry workers and cullers who were active in the program in Ho Chi Minh City in 2004 and 2005. Methodology/Principal Findings: Single sera from 500 poultry workers and poultry cullers exposed to infected birds were tested for antibodies to avian influenza H5N1, using microneutralization assays and hemagglutination inhibition assay with horse blood. All sera tested negative using microneutralization tests. Three samples showed a 1:80 titer in the hemagglutination inhibition assay. Conclusions/Significance: This study provides additional support for the low transmissibility of clade 1 H5N1 to humans, but limited transmission to highly exposed persons cannot be excluded given the presence of low antibody titers in some individuals. © 2009 Schultsz et al.published_or_final_versio

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

TESOL Teachers’ Engagement with the Native Speaker Model: How Does Teacher Education Impact on Their Beliefs?

© 2017, © The Author(s) 2017. This research investigates non-native English teachers’ engagement with the native speaker model, i.e. whether they agree/disagree with measuring English teaching and learning performance against native speaker standards. More importantly, it aims to unearth the impact of teacher education on teachers’ attitudes and beliefs about “native-speakerness”. Data were gathered from an online survey delivered to 85 Vietnamese TESOL teachers who had completed one of 19 Master’s level TESOL programmes offered overseas and in Vietnam, followed by in-depth interviews with 20 participants. The results revealed that teacher education strengthened the teachers’ beliefs about the linguistic diversity of English and led them to question the native and non-native divide by providing relevant input and opportunities to engage in critical discussion on nativeness, as well as fruitful learning experience. However, language proficiency is an area where “native-speakerness” still dominates, and where teacher education did not exert much influence. These findings shed light on the role of TESOL teacher training in influencing teacher beliefs about the native speaker model, and suggest that teacher education programmes dedicate more space for teachers to critically explore the construct of language teacher proficiency