Algorithms for Sparse Linear Classifiers in the Massive Data Setting

Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classification problems in high dimensions. However, current algorithms for training sparse classifiers typically scale quite unfavorably with respect to the number of training examples. This paper proposes online and multi-pass algorithms for training sparse linear classifiers for high dimensional data. These algorithms have computational complexity and memory requirements that make learning on massive data sets feasible. The central idea that makes this possible is a straightforward quadratic approximation to the likelihood function

Measuring the Muon Flux of Neutrino Beams with a Novel Gas Cherenkov Detector

The Deep Underground Neutrino Experiment is a future long-baseline neutrino experiment that plans to make measurements of neutrino oscillation parameters. This experiment will require accurate estimates of the neutrino fluxes through the near and far detectors; however, these estimates rely heavily on Monte-Carlo models of hadronic interactions. In order to verify these Monte-Carlo flux estimates with physical data, the by-product muon beam can be observed using modest detectors. These measurements of the muon flux can then be used in conjunction with hadronic models to constrain predictions of the neutrino flux. In order to perform measurements of the muon flux of the future Deep Underground Neutrino Experiment, a muon monitoring system will be implemented. As part of this muon monitoring system, a novel Cherenkov detector will perform measurements of the muon beam spectrum and divergence. This thesis describes the research and development efforts to determine this detector design\u27s capabilities that are currently being undertaken at the University of Colorado Boulder and at the Fermi National Accelerator Lab in Illinois

Learning to Sing from the Same Sheet of Music: A Study of Family Preservation Integration Projects for High-Risk, School-Age Children and Their Families in Minnesota.

The idea of integrating social service programs began emerging in the 1980s. In 1990 the Minnesota legislature funded demonstration projects for integrating programs for high-risk children in the schools. This study surveyed thirty-one integration projects in Minnesota in 1992. All were contacted by phone and seven were chosen for on-site focus group discussions. This report presents an overall view of the problems these projects confronted, case studies of seven strong programs, recommendations, and a prototype of how to set up an integration project for school-age children. The work was also presented in capsule form in a CURA Reporter article in September 1993

East Meets West: An International Dialogue on Mediation and Med-Arb in the United States and China

This Second Beijing Arbitration Commission (BAC)/Straus Institute for Dispute Resolution International Videoconference, following up on last year\u27s successful inaugural program, will provide different perspectives on the current BAC initiative and evolving attitudes toward mediation and med-arb. Topics include: (1) the development and current state of business mediation in the U.S.; (2) the challenges and opportunities confronting China in developing stand-alone business mediation; (3) reflections on the skills necessary for mediators; (4) common pitfalls in mediation; (5) perspectives on med-arb (as opposed to stand-alone mediation); and (6) how to most effectively use mediation in conjunction with arbitration procedures

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Primary care treatment of insomnia: study protocol for a pragmatic, multicentre, randomised controlled trial comparing nurse-delivered sleep restriction therapy to sleep hygiene (the HABIT trial).

Introduction Insomnia is a prevalent sleep disorder that negatively affects quality of life. Multicomponent cognitive-behavioural therapy (CBT) is the recommended treatment but access remains limited, particularly in primary care. Sleep restriction therapy (SRT) is one of the principal active components of CBT and could be delivered by generalist staff in primary care. The aim of this randomised controlled trial is to establish whether nurse-delivered SRT for insomnia disorder is clinically and cost-effective compared with sleep hygiene advice. Methods and analysis In the HABIT (Health-professional Administered Brief Insomnia Therapy) trial, 588 participants meeting criteria for insomnia disorder will be recruited from primary care in England and randomised (1:1) to either nurse-delivered SRT (plus sleep hygiene booklet) or sleep hygiene booklet on its own. SRT will be delivered over 4 weekly sessions; total therapy time is approximately 1 hour. Outcomes will be collected at baseline, 3, 6 and 12 months post-randomisation. The primary outcome is self-reported insomnia severity using the Insomnia Severity Index at 6 months. Secondary outcomes include health-related and sleep-related quality of life, depressive symptoms, use of prescribed sleep medication, diary and actigraphy-recorded sleep parameters, and work productivity. Analyses will be intention-to-treat. Moderation and mediation analyses will be conducted and a cost-utility analysis and process evaluation will be performed. Ethics and dissemination Ethical approval was granted by the Yorkshire and the Humber - Bradford Leeds Research Ethics Committee (reference: 18/YH/0153). We will publish our primary findings in high-impact, peer-reviewed journals. There will be further outputs in relation to process evaluation and secondary analyses focussed on moderation and mediation. Trial results could make the case for the introduction of nurse-delivered sleep therapy in primary care, increasing access to evidence-based treatment for people with insomnia disorder

14-3-3 Proteins Interact with a Hybrid Prenyl-Phosphorylation Motif to Inhibit G Proteins

Signaling through G proteins normally involves conformational switching between GTP- and GDP-bound states. Several Rho GTPases are also regulated by RhoGDI binding and sequestering in the cytosol. Rnd proteins are atypical constitutively GTP-bound Rho proteins, whose regulation remains elusive. Here, we report a high-affinity 14-3-3-binding site at the C terminus of Rnd3 consisting of both the Cys241-farnesyl moiety and a Rho-associated coiled coil containing protein kinase (ROCK)-dependent Ser240 phosphorylation site. 14-3-3 binding to Rnd3 also involves phosphorylation of Ser218 by ROCK and/or Ser210 by protein kinase C (PKC). The crystal structure of a phosphorylated, farnesylated Rnd3 peptide with 14-3-3 reveals a hydrophobic groove in 14-3-3 proteins accommodating the farnesyl moiety. Functionally, 14-3-3 inhibits Rnd3-induced cell rounding by translocating it from the plasma membrane to the cytosol. Rnd1, Rnd2, and geranylgeranylated Rap1A interact similarly with 14-3-3. In contrast to the canonical GTP/GDP switch that regulates most Ras superfamily members, our results reveal an unprecedented mechanism for G protein inhibition by 14-3-3 proteins

The cellular expression of antiangiogenic factors in fetal primate macula

PURPOSE. To characterize the cellular expression patterns of antiangiogenic factorsdifferentially regulated in the fetal human macula. METHODS. RNA was extracted from macular, nasal, and surround biopsies of three human fetal retinas at midgestation. Relative levels of expression of pigment epithelium- derived factor (PEDF), brain natriuretic peptide (BNP), collagen type IV_2 (COL4A2), and natriuretic peptide receptors A and C (NPRA and NPRC) were determined with quantitative PCR. Cellular expression of PEDF and BNP was investigated by in situ hybridization on retinal sections from monkeys aged between fetal day 55 and 11 years. BNP, COL4A2, and NPRA proteins were localized by immunohistochemistry. Labeling was imaged and quantified by confocal microscopy and optical densitometry. RESULTS. Quantitative PCR confirmed higher levels of PEDF and BNP and lower levels of COL4A2 in the macula at midgestation. PEDF mRNA was detected in ganglion cells (GCs) and the pigment epithelium (RPE). BNP mRNA was detected in GCs and macroglia, although BNP immunoreactivity (IR) was predominantly perivascular. COL4A2-IR was detected in large blood vessels and NPRA-IR on the retinal vascular endothelium, GC axons in fetal retinas, and cone axons at all ages. Optical densitometry showed a graded expression of PEDF and BNP at all ages, with highest levels of expression in GCs in the developing fovea. CONCLUSIONS. Because the retinal vessels initially form in the GC layer, it is likely that PEDF has a key role in defining and maintaining the foveal avascular area. The precise role of BNP is unclear, but it may include both antiangiogenic and natriuretic functions