Sequential Deliberation for Social Choice

In large scale collective decision making, social choice is a normative study of how one ought to design a protocol for reaching consensus. However, in instances where the underlying decision space is too large or complex for ordinal voting, standard voting methods of social choice may be impractical. How then can we design a mechanism - preferably decentralized, simple, scalable, and not requiring any special knowledge of the decision space - to reach consensus? We propose sequential deliberation as a natural solution to this problem. In this iterative method, successive pairs of agents bargain over the decision space using the previous decision as a disagreement alternative. We describe the general method and analyze the quality of its outcome when the space of preferences define a median graph. We show that sequential deliberation finds a 1.208- approximation to the optimal social cost on such graphs, coming very close to this value with only a small constant number of agents sampled from the population. We also show lower bounds on simpler classes of mechanisms to justify our design choices. We further show that sequential deliberation is ex-post Pareto efficient and has truthful reporting as an equilibrium of the induced extensive form game. We finally show that for general metric spaces, the second moment of of the distribution of social cost of the outcomes produced by sequential deliberation is also bounded

Toxoplasma effectors targeting host signaling and transcription

Early electron microscopy studies revealed the elaborate cellular features that define the unique adaptations of apicomplexan parasites. Among these were bulbous rhoptry (ROP) organelles and small, dense granules (GRAs), both of which are secreted during invasion of host cells. These early morphological studies were followed by the exploration of the cellular contents of these secretory organelles, revealing them to be comprised of highly divergent protein families with few conserved domains or predicted functions. In parallel, studies on host-pathogen interactions identified many host signaling pathways that were mysteriously altered by infection. It was only with the advent of forward and reverse genetic strategies that the connections between individual parasite effectors and the specific host pathways that they targeted finally became clear. The current repertoire of parasite effectors includes ROP kinases and pseudokinases that are secreted during invasion and that block host immune pathways. Similarly, many secretory GRA proteins alter host gene expression by activating host transcription factors, through modification of chromatin, or by inducing small noncoding RNAs. These effectors highlight novel mechanisms by whichhas learned to harness host signaling to favor intracellular survival and will guide future studies designed to uncover the additional complexity of this intricate host-pathogen interaction

Supporting the retention of non-traditional students in Higher Education using a resilience framework

Student drop-out in higher education is an increasingly important issue across Europe, but there are substantial disparities between countries and institutions which suggest that variations in policies and practices may influence student retention and success. Numerous schemes have been devised to increase student retention, frequently focusing on non-traditional groups. Retention efforts include scholarships and bursaries, enhanced monitoring and support measures, and specialist teams of staff or peer mentors. Theoretical understanding of the withdrawal of non-traditional students typically draws on social and cultural capital concepts (Bourdieu, 1986), which may have led to a rather deterministic approach to student success. Research with non-traditional students on two distinct but related projects at a UK university led us to consider the concept of resilience in helping to understand student retention and success. This paper discusses the concept of resilience and – drawing on our experiences of using a resilience framework for analysis of risk and protective factors in these two projects – considers how it might be of use in supporting student retention in the wider European context

An association between anti-platelet drug use and reduced cancer prevalence in diabetic patients: results from the Vermont Diabetes Information System Study

<p>Abstract</p> <p>Background</p> <p>Diabetes is associated with an increased risk of several malignancies. Both diabetic patients and patients with cancer have an increase in platelet reactivity and platelet activation has recently emerged as a potential mediator of cancer progression. Drug therapies, such as aspirin, that reduce platelet reactivity reduce both cardiovascular and cancer risk.</p> <p>Methods</p> <p>We performed a cross-sectional analysis to assess the association between history of cancer and current anti-platelet drug use in a primary care population of adults with diabetes enrolled in the Vermont Diabetes Information System.</p> <p>Results</p> <p>Self-reported characteristics, medical history, and a complete medication list were recorded on 1007 diabetic adults. Fifty percent of diabetic patients used an anti-platelet drug. In unadjusted analysis, no association was seen between anti-platelet drug use and cancer history (OR = 0.93; <it>P </it>= .70). Platelet inhibitor use was associated with a decreased patient-reported history of malignancy in a multivariate logistic regression adjusted for age, sex, body mass index, comorbidity, and number of medications (OR = 0.66; CI 0.44-0.99; <it>P </it>= .045). Similar odds of association were seen in both males and females, and for aspirin and non-aspirin platelet inhibitor therapy.</p> <p>Conclusions</p> <p>Our data suggest an association between anti-platelet drug use and reduced cancer prevalence in patients with diabetes. Given the potentially large implications of our observations in the diabetic population, further studies are required to determine if this association is causal.</p

The Fifth Data Release of the Sloan Digital Sky Survey

This paper describes the Fifth Data Release (DR5) of the Sloan Digital Sky Survey (SDSS). DR5 includes all survey quality data taken through June 2005 and represents the completion of the SDSS-I project (whose successor, SDSS-II will continue through mid-2008). It includes five-band photometric data for 217 million objects selected over 8000 square degrees, and 1,048,960 spectra of galaxies, quasars, and stars selected from 5713 square degrees of that imaging data. These numbers represent a roughly 20% increment over those of the Fourth Data Release; all the data from previous data releases are included in the present release. In addition to "standard" SDSS observations, DR5 includes repeat scans of the southern equatorial stripe, imaging scans across M31 and the core of the Perseus cluster of galaxies, and the first spectroscopic data from SEGUE, a survey to explore the kinematics and chemical evolution of the Galaxy. The catalog database incorporates several new features, including photometric redshifts of galaxies, tables of matched objects in overlap regions of the imaging survey, and tools that allow precise computations of survey geometry for statistical investigations.Comment: ApJ Supp, in press, October 2007. This paper describes DR5. The SDSS Sixth Data Release (DR6) is now public, available from http://www.sdss.or

Intercalibration of the barrel electromagnetic calorimeter of the CMS experiment at start-up

Calibration of the relative response of the individual channels of the barrel electromagnetic calorimeter of the CMS detector was accomplished, before installation, with cosmic ray muons and test beams. One fourth of the calorimeter was exposed to a beam of high energy electrons and the relative calibration of the channels, the intercalibration, was found to be reproducible to a precision of about 0.3%. Additionally, data were collected with cosmic rays for the entire ECAL barrel during the commissioning phase. By comparing the intercalibration constants obtained with the electron beam data with those from the cosmic ray data, it is demonstrated that the latter provide an intercalibration precision of 1.5% over most of the barrel ECAL. The best intercalibration precision is expected to come from the analysis of events collected in situ during the LHC operation. Using data collected with both electrons and pion beams, several aspects of the intercalibration procedures based on electrons or neutral pions were investigated