Psychometric properties of the Italian versions of the Gambling Urge Scale (GUS) and the Gambling Refusal Self-Efficacy Questionnaire (GRSEQ)

Gambling urges and gambling refusal self-efficacy beliefs play a major role in the development and maintenance of problem gambling. This study aimed to translate the Gambling Urge Scale (GUS) and the Gambling Refusal Self-Efficacy Questionnaire (GRSEQ) from English to Italian (GUS-I, GRSEQ-I) and to test their factor structure, internal consistency, construct validity, concurrent validity, and gender differences in 513 individuals from the Italian community. Factor structure and construct validity were tested through Confirmatory Factor Analysis, internal consistency through Cronbach’s alpha, concurrent validity through correlations with gambling-related cognitions (GRCS-I), probable pathological gambling (SOGS-I), and gambling functioning (GFA-R-I). Results confirmed that the 6 items of the GUS-I load highly on one dimension of Gambling Urge, and each of the 26 items of the GRSEQ-I load highly on their relevant sub-dimension, among the following: situations/thoughts, drugs, positive emotions, negative emotions. Both scales are internally consistent and show concurrent validity with gambling-related cognitions, probable pathological gambling, and gambling functioning. Males score higher than females at the GUS-I; females score higher than males at the GRSEQ-I. The findings from the present study suggest that the GUS-I and the GRSEQ-I are internally consistent and valid scales for the assessment of gambling urges and gambling refusal self-efficacy in Italian individuals from the community, with significant repercussions in terms of assessment, prevention, and intervention

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology

Cost analysis of school-based intermittent screening and treatment of malaria in Kenya

<p>Abstract</p> <p>Background</p> <p>The control of malaria in schools is receiving increasing attention, but there remains currently no consensus as to the optimal intervention strategy. This paper analyses the costs of intermittent screening and treatment (IST) of malaria in schools, implemented as part of a cluster-randomized controlled trial on the Kenyan coast.</p> <p>Methods</p> <p>Financial and economic costs were estimated using an ingredients approach whereby all resources required in the delivery of IST are quantified and valued. Sensitivity analysis was conducted to investigate how programme variation affects costs and to identify potential cost savings in the future implementation of IST.</p> <p>Results</p> <p>The estimated financial cost of IST per child screened is US$6.61 (economic cost US$ 6.24). Key contributors to cost were salary costs (36%) and malaria rapid diagnostic tests (RDT) (22%). Almost half (47%) of the intervention cost comprises redeployment of existing resources including health worker time and use of hospital vehicles. Sensitivity analysis identified changes to intervention delivery that can reduce programme costs by 40%, including use of alternative RDTs and removal of supervised treatment. Cost-effectiveness is also likely to be highly sensitive to the proportion of children found to be RDT-positive.</p> <p>Conclusion</p> <p>In the current context, school-based IST is a relatively expensive malaria intervention, but reducing the complexity of delivery can result in considerable savings in the cost of intervention.</p> <p>(Costs are reported in US$ 2010).</p

The self-organizing fractal theory as a universal discovery method: the phenomenon of life

A universal discovery method potentially applicable to all disciplines studying organizational phenomena has been developed. This method takes advantage of a new form of global symmetry, namely, scale-invariance of self-organizational dynamics of energy/matter at all levels of organizational hierarchy, from elementary particles through cells and organisms to the Universe as a whole. The method is based on an alternative conceptualization of physical reality postulating that the energy/matter comprising the Universe is far from equilibrium, that it exists as a flow, and that it develops via self-organization in accordance with the empirical laws of nonequilibrium thermodynamics. It is postulated that the energy/matter flowing through and comprising the Universe evolves as a multiscale, self-similar structure-process, i.e., as a self-organizing fractal. This means that certain organizational structures and processes are scale-invariant and are reproduced at all levels of the organizational hierarchy. Being a form of symmetry, scale-invariance naturally lends itself to a new discovery method that allows for the deduction of missing information by comparing scale-invariant organizational patterns across different levels of the organizational hierarchy

Operation and performance of the ATLAS Tile Calorimeter in Run 1

The Tile Calorimeter is the hadron calorimeter covering the central region of the ATLAS experiment at the Large Hadron Collider. Approximately 10,000 photomultipliers collect light from scintillating tiles acting as the active material sandwiched between slabs of steel absorber. This paper gives an overview of the calorimeter’s performance during the years 2008–2012 using cosmic-ray muon events and proton–proton collision data at centre-of-mass energies of 7 and 8TeV with a total integrated luminosity of nearly 30 fb−1. The signal reconstruction methods, calibration systems as well as the detector operation status are presented. The energy and time calibration methods performed excellently, resulting in good stability of the calorimeter response under varying conditions during the LHC Run 1. Finally, the Tile Calorimeter response to isolated muons and hadrons as well as to jets from proton–proton collisions is presented. The results demonstrate excellent performance in accord with specifications mentioned in the Technical Design Report