Direct determination of the solar neutrino fluxes from solar neutrino data

We determine the solar neutrino fluxes from a global analysis of the solar and terrestrial neutrino data in the framework of three-neutrino mixing. Using a Bayesian approach we reconstruct the posterior probability distribution function for the eight normalization parameters of the solar neutrino fluxes plus the relevant masses and mixing, with and without imposing the luminosity constraint. This is done by means of a Markov Chain Monte Carlo employing the Metropolis-Hastings algorithm. We also describe how these results can be applied to test the predictions of the Standard Solar Models. Our results show that, at present, both models with low and high metallicity can describe the data with good statistical agreement.Comment: 24 pages, 1 table, 7 figures. Acknowledgments correcte

Comparison of Self-Reported Alcohol Consumption to Phosphatidylethanol Measurement among HIV-Infected Patients Initiating Antiretroviral Treatment in Southwestern Uganda

Background: Alcohol consumption among HIV-infected patients may accelerate HIV disease progression or reduce antiretroviral therapy adherence. Self-reported alcohol use is frequently under-reported due to social desirability and recall bias. The aim of this study was to compare self-reported alcohol consumption to phosphatidylethanol (PEth), a biomarker of alcohol consumption, and to estimate the correlation between multiple measures of self-reported alcohol consumption with PEth. Methods: The Uganda AIDS Rural Treatment Outcomes (UARTO) cohort is located in southwestern Uganda and follows patients on ART to measure treatment outcomes. Patients complete standardized questionnaires quarterly including questions on demographics, health status and alcohol consumption. Baseline dried blood spots (DBS) were collected and retrieved to measure PEth. Results: One hundred fifty samples were tested, and 56 (37.3%) were PEth positive (≥8 ng/mL). Of those, 51.7% did not report alcohol use in the past month. Men were more likely to under-report compared to women, OR 2.9, 95% CI = 1.26, 6.65) and those in the higher economic asset categories were less likely to under-report compared to those in the lowest category (OR = 0.41 95% CI: 0.17, 0.94). Among self-reported drinkers (n = 31), PEth was highly correlated with the total number of drinking days in the last 30 (Spearman R = 0.73, p<0.001). Conclusions: Approximately half of HIV infected patients initiating ART and consuming alcohol under-report their use of alcohol. Given the high prevalence, clinicians should assess all patients for alcohol use with more attention to males and those in lower economic asset categories who deny alcohol use. Among those reporting current drinking, self-reported drinking days is a useful quantitative measure

SUPPORT Tools for evidence-informed health Policymaking (STP) 17: Dealing with insufficient research evidence

This article is part of a series written for people responsible for making decisions about health policies and programmes and for those who support these decision makers

Algorithmic Complexity for Short Binary Strings Applied to Psychology: A Primer

Since human randomness production has been studied and widely used to assess executive functions (especially inhibition), many measures have been suggested to assess the degree to which a sequence is random-like. However, each of them focuses on one feature of randomness, leading authors to have to use multiple measures. Here we describe and advocate for the use of the accepted universal measure for randomness based on algorithmic complexity, by means of a novel previously presented technique using the the definition of algorithmic probability. A re-analysis of the classical Radio Zenith data in the light of the proposed measure and methodology is provided as a study case of an application.Comment: To appear in Behavior Research Method

Rule based classifier for the analysis of gene-gene and gene-environment interactions in genetic association studies

<p>Abstract</p> <p>Background</p> <p>Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative methods, because no single method will perform well in all scenarios. The aim of this work was to evaluate the performance of three selected rule based classifier algorithms, RIPPER, RIDOR and PART, for the analysis of genetic association studies.</p> <p>Methods</p> <p>Overall, 42 datasets were simulated with three different case-control models, a varying number of subjects (300, 600), SNPs (500, 1500, 3000) and noise (5%, 10%, 20%). The algorithms were applied to each of the datasets with a set of algorithm-specific settings. Results were further investigated with respect to a) the Model, b) the Rules, and c) the Attribute level. Data analysis was performed using WEKA, SAS and PERL.</p> <p>Results</p> <p>The RIPPER algorithm discovered the true case-control model at least once in >33% of the datasets. The RIDOR and PART algorithm performed poorly for model detection. The RIPPER, RIDOR and PART algorithm discovered the true case-control rules in more than 83%, 83% and 44% of the datasets, respectively. All three algorithms were able to detect the attributes utilized in the respective case-control models in most datasets.</p> <p>Conclusions</p> <p>The current analyses substantiate the utility of rule based classifiers such as RIPPER, RIDOR and PART for the detection of gene-gene/gene-environment interactions in genetic association studies. These classifiers could provide a valuable new method, complementing existing approaches, in the analysis of genetic association studies. The methods provide an advantage in being able to handle both categorical and continuous variable types. Further, because the outputs of the analyses are easy to interpret, the rule based classifier approach could quickly generate testable hypotheses for additional evaluation. Since the algorithms are computationally inexpensive, they may serve as valuable tools for preselection of attributes to be used in more complex, computationally intensive approaches. Whether used in isolation or in conjunction with other tools, rule based classifiers are an important addition to the armamentarium of tools available for analyses of complex genetic association studies.</p

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

Liquid-gas phase transition in nuclear multifragmentation

The equation of state of nuclear matter suggests that at suitable beam energies the disassembling hot system formed in heavy ion collisions will pass through a liquid-gas coexistence region. Searching for the signatures of the phase transition has been a very important focal point of experimental endeavours in heavy ion collisions, in the last fifteen years. Simultaneously theoretical models have been developed to provide information about the equation of state and reaction mechanisms consistent with the experimental observables. This article is a review of this endeavour.Comment: 63 pages, 27 figures, submitted to Adv. Nucl. Phys. Some typos corrected, minor text change

The influence of initial xylose concentration, agitation, and aeration on ethanol production by Pichia stipitis from rice straw hemicellulosic hydrolysate

Rice straw hemicellulosic hydrolysate was used as fermentation medium for ethanol production by Pichia stipitis NRRL Y-7124. Shaking bath experiments were initially performed aiming to establish the best initial xylose concentration to be used in this bioconversion process. In the sequence, assays were carried out under different agitation (100 to 200 rpm) and aeration (V flask/V medium ratio varying from 2.5 to 5.0) conditions, and the influence of these variables on the fermentative parameters values (ethanol yield factor, Y P/S; cell yield factor, Y X/S; and ethanol volumetric productivity, Q P) was investigated through a 22 full-factorial design. Initial xylose concentration of about 50 g/l was the most suitable for the development of this process, since the yeast was able to convert substrate in product with high efficiency. The factorial design assays showed a strong influence of both process variables in all the evaluated responses. The agitation and aeration increase caused a deviation in the yeast metabolism from ethanol to biomass production. The best results (Y P/S = 0.37 g/g and Q P = 0.39 g/l.h) were found when the lowest aeration (2.5 V flask/V medium ratio) and highest agitation (200 rpm) levels were employed. Under this condition, a process efficiency of 72.5% was achieved. These results demonstrated that the establishment of adequate conditions of aeration is of great relevance to improve the ethanol production from xylose by Pichia stipitis, using rice straw hemicellulosic hydrolysate as fermentation medium.The financial support from Fapesp (Brazil) is gratefully acknowledged

Search for supersymmetric particles in scenarios with a gravitino LSP and stau NLSP

Sleptons, neutralinos and charginos were searched for in the context of scenarios where the lightest supersymmetric particle is the gravitino. It was assumed that the stau is the next-to-lightest supersymmetric particle. Data collected with the DELPHI detector at a centre-of-mass energy near 189 GeV were analysed combining the methods developed in previous searches at lower energies. No evidence for the production of these supersymmetric particles was found. Hence, limits were derived at 95% confidence level.Comment: 31 pages, 14 figure

Measurement of the Forward-Backward Asymmetry in the B -> K(*) mu+ mu- Decay and First Observation of the Bs -> phi mu+ mu- Decay

We reconstruct the rare decays $B^+ \to K^+\mu^+\mu^-$, $B^0 \to K^{*}(892)^0\mu^+\mu^-$, and $B^0_s \to \phi(1020)\mu^+\mu^-$ in a data sample corresponding to $4.4 {\rm fb^{-1}}$ collected in $p\bar{p}$ collisions at $\sqrt{s}=1.96 {\rm TeV}$ by the CDF II detector at the Fermilab Tevatron Collider. Using $121 \pm 16$ $B^+ \to K^+\mu^+\mu^-$ and $101 \pm 12$ $B^0 \to K^{*0}\mu^+\mu^-$ decays we report the branching ratios. In addition, we report the measurement of the differential branching ratio and the muon forward-backward asymmetry in the $B^+$ and $B^0$ decay modes, and the $K^{*0}$ longitudinal polarization in the $B^0$ decay mode with respect to the squared dimuon mass. These are consistent with the theoretical prediction from the standard model, and most recent determinations from other experiments and of comparable accuracy. We also report the first observation of the $B^0_s \to \phi\mu^+\mu^- decay and measure its branching ratio${\mathcal{B}}(B^0_s \to \phi\mu^+\mu^-) = [1.44 \pm 0.33 \pm 0.46] \times 10^{-6}$using$27 \pm 6$signal events. This is currently the most rare$B^0_s$ decay observed.Comment: 7 pages, 2 figures, 3 tables. Submitted to Phys. Rev. Let