Minimum Density Hyperplanes

Associating distinct groups of objects (clusters) with contiguous regions of high probability density (high-density clusters), is central to many statistical and machine learning approaches to the classification of unlabelled data. We propose a novel hyperplane classifier for clustering and semi-supervised classification which is motivated by this objective. The proposed minimum density hyperplane minimises the integral of the empirical probability density function along it, thereby avoiding intersection with high density clusters. We show that the minimum density and the maximum margin hyperplanes are asymptotically equivalent, thus linking this approach to maximum margin clustering and semi-supervised support vector classifiers. We propose a projection pursuit formulation of the associated optimisation problem which allows us to find minimum density hyperplanes efficiently in practice, and evaluate its performance on a range of benchmark datasets. The proposed approach is found to be very competitive with state of the art methods for clustering and semi-supervised classification

Study of the consequence of excess indium in the active channel of InGaAs/InAlAs high electron mobility transistors on device properties

A study of the properties of In0.52Al0.48As/In0.53+xGa0.47−xAs high electron mobility transistors is carried out for 0%, 7%, and 12% excess In values in the channel. Theoretical analysis shows that the enhanced In causes a biaxial compressive strain of 0.49% to 0.84% in the channel, increases the band‐edge discontinuity from 0.437 to 0.500 eV, and reduces the carrier mass by 6%. Experimental characterizations support the theoretical predictions by demonstrating an increase of mobility from 9900 to 11 200 cm2/V s at 300 K, and a transconductance enhancement from 160 to at least 230 mS/mm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71236/2/APPLAB-52-9-728-1.pd

InAlAs/InGaAs/InP sub-micron HEMTs grown by CBE

The InAlAs/InGaAs/InP high electron mobility transistor (HEMT) lattice matched to InP offers excellent high frequency, low noise operation for MMICs and low-noise amplifiers. The InP channel in the InP/InAlAs HEMT offers the advantages of improved high field velocity and higher breakdown voltages (the potential for higher power applications) over InGaAs channel HEMTs. InAlAs has been grown for the first time by CBE using TMAA producing InGaAs/InAlAs and InP/InAlAs HEMTs. Sub-micron InGaAs/InAlAs HEMTs with planar Si doping have been fabricated with ft values of 150 GHz and fmax values of 160 GHz. This device showed excellent pinch-off charateristics, with a maximum transconductance of 890 mS/mm. The planar doped InGaAs channel HEMT had a higher ft than a similar uniformly doped device. However, the non-optimized structure of the planar doped device resulted in a large output conductance of 120 mS/mm, limiting fmax for that device. A sub-micron InP channel device was grown with a quantum well channel and double-sided planar Si doping. A sheet charge density of 4.4 x 1012 cm-2 and associated room temperature mobility of 2800 cm2/V[middle dot]s were achieved; however, the saturation current was low. The most likely causes for this are diffusion of the planar doping beneath the channel and the poor quality of the InP on InAlAs interface at the bottom of the quantum well channel.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30057/1/0000425.pd

Modelling Metrics for Transparency in Medical Systems

Transparency is a novel non-functional requirement for software systems. It is acclaimed to improve the quality of service since it gives users access to information concerning the system’s processes, clarifying who is responsible if something goes wrong. Thus, it is believed to support people’s right to a secure and private processing of their personal data. We define eight quality metrics for transparency and we demonstrate the usage and the effectiveness of the metrics by assessing transparency on the Microsoft HealthVault, an on-line platform for users to collect, store, and share medical records

An Integrated Approach for the Analysis of Biological Pathways using Mixed Models

Gene class, ontology, or pathway testing analysis has become increasingly popular in microarray data analysis. Such approaches allow the integration of gene annotation databases, such as Gene Ontology and KEGG Pathway, to formally test for subtle but coordinated changes at a system level. Higher power in gene class testing is gained by combining weak signals from a number of individual genes in each pathway. We propose an alternative approach for gene-class testing based on mixed models, a class of statistical models that

Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort

Background: Exacerbation-prone asthma is a feature of severe disease. Yet, the basis for its persistency remains unclear. Objectives: To determine the clinical and transcriptomic features of the frequent-exacerbator (FE) and of persistent FEs (PFE) in U-BIOPRED cohort. Methods: We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures. Results: Of 317 patients, 62.4 % were FE of whom 63.6% were PFE, while 37.6% were IE of whom 61.3% were PIE. Using multivariate analysis, FE was associated with short-acting beta-agonist use, sinusitis and daily oral corticosteroid use, while PFE with eczema, short-acting beta-agonist use and asthma control index. CEA Cell Adhesion Molecule 5 (CEACAM5) was the only differentially-expressed transcript in bronchial biopsies between PE and IE. There were no differentially-expressed genes in the other 4 compartments. There were higher expression scores for Type 2 , T-helper type-17 and Type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while higher expression scores of Type 2, Type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE. Conclusion: FE group and its PFE subgroup are associated with poor asthma control while expressing higher Type 1 and Type 2 activation pathways compared to IE and PIE, respectively

Epigenetic memory in induced pluripotent stem cells

Somatic cell nuclear transfer and transcription-factor-based reprogramming revert adult cells to an embryonic state, and yield pluripotent stem cells that can generate all tissues. Through different mechanisms and kinetics, these two reprogramming methods reset genomic methylation, an epigenetic modification of DNA that influences gene expression, leading us to hypothesize that the resulting pluripotent stem cells might have different properties. Here we observe that low-passage induced pluripotent stem cells (iPSCs) derived by factor-based reprogramming of adult murine tissues harbour residual DNA methylation signatures characteristic of their somatic tissue of origin, which favours their differentiation along lineages related to the donor cell, while restricting alternative cell fates. Such an ‘epigenetic memory’ of the donor tissue could be reset by differentiation and serial reprogramming, or by treatment of iPSCs with chromatin-modifying drugs. In contrast, the differentiation and methylation of nuclear-transfer-derived pluripotent stem cells were more similar to classical embryonic stem cells than were iPSCs. Our data indicate that nuclear transfer is more effective at establishing the ground state of pluripotency than factor-based reprogramming, which can leave an epigenetic memory of the tissue of origin that may influence efforts at directed differentiation for applications in disease modelling or treatment.National Institutes of Health (U.S.) (NIH grant RO1-DK70055)National Institutes of Health (U.S.) (NIH Grant RO1-DK59279)National Institutes of Health (U.S.) (American Recovery and Reinvestment Act (RC2-HL102815))National Institutes of Health (U.S.) (NIH (K99HL093212-01))Cooley’s Anemia FoundationNational Institutes of Health (U.S.) (NIH LLS (3567-07))National Institutes of Health (U.S.) (NIH grant R37CA054358)National Institutes of Health (U.S.) (NIH grant P50HG003233)National Institutes of Health (U.S.) (NIH grant R01AI047457)National Institutes of Health (U.S.) (NIH Grant R01AI047458)National Institutes of Health (U.S.) (CA86065)National Institutes of Health (U.S.) (HL099999)Thomas and Stacey Siebel FoundationCalifornia Institute for Regenerative Medicine (Fellowship T1-00001

The role of local adaptation in sustainable production of village chickens

Village chickens are ubiquitous in smallholder farming systems, contributing to household, local and national economies under diverse environmental, economic and cultural settings. However, they are raised in challenging environments where productivity is low while mortality is high. There is much interest in utilizing indigenous genetic resources to produce a chicken resilient to its environment, whilst providing the basis of an economically sustainable enterprise. Globally, however, a wide variety of interventions have so far proved unable to deliver sustainable improvements. Here, we show that regional differences in trait preferences and parasite burden are associated with distinct chicken genepools, likely in response to interacting natural and human-driven (economic and social) selection pressures. Drivers of regional differences include marketing opportunities, cultural preferences, agro-ecologies and parasite populations, and are evident in system adaptations, such as management practices, population dynamics and bird genotypes. Our results provide sound multidisciplinary evidence to support previous observations that sustainable poultry development interventions for smallholder farmers, including breeding programs, should be locally tailored and designed for flexible implementation

Sputum proteomics and airway cell transcripts of current and ex-smokers with severe asthma in U-BIOPRED: an exploratory analysis

Background: Severe asthma patients with a significant smoking history have airflow obstruction with reported neutrophilia. We hypothesise that multi-omic analysis will enable the definition of smoking and ex-smoking severe asthma molecular phenotypes. Methods: The U-BIOPRED severe asthma patients containing current-smokers (CSA), exsmokers (ESA), non-smokers (NSA) and healthy non-smokers (NH) was examined. Blood and sputum cell counts, fractional exhaled nitric oxide and spirometry were obtained. Exploratory proteomic analysis of sputum supernatants and transcriptomic analysis of bronchial brushings, biopsies and sputum cells was performed. Results: Colony stimulating factor (CSF)2 protein levels were increased in CSA sputum supernatants with azurocidin 1, neutrophil elastase and CXCL8 upregulated in ESA. Phagocytosis and innate immune pathways were associated with neutrophilic inflammation in ESA. Gene Set Variation Analysis of bronchial epithelial cell transcriptome from CSA showed enrichment of xenobiotic metabolism, oxidative stress and endoplasmic reticulum stress compared to other groups. CXCL5 and matrix metallopeptidase 12 genes were upregulated in ESA and the epithelial protective genes, mucin 2 and cystatin SN, were downregulated. Conclusion: Despite little difference in clinical characteristics, CSA were distinguishable from ESA subjects at the sputum proteomic level with CSA having increased CSF2 expression and ESA patients showed sustained loss of epithelial barrier processes