On the possibility of q-scaling in high energy production processes

It has been noticed recently that transverse momenta (p_T) distributions observed in high energy production processes exhibit remarkably universal scaling behaviour. This is the case when a suitable variable replaces the usual p_T. On the other hand, it is also widely known that transverse momentum distributions in general follow a power-like Tsallis distribution, rather than an exponential Boltzmann-Gibbs, with a (generally energy dependent) nonextensivity parameter q. Here we show that it is possible to choose a suitable variable such that all the data can be fitted by the same Tsallis distribution (with the same, energy independent value of the q-parameter). Thus they exhibit q-scaling.Comment: Final version, accepted by J.Phys.

Comparing predictions made by a prediction model, clinical score, and physicians Pediatric asthma exacerbations in the emergency department

Background: Asthma exacerbations are one of the most common medical reasons for children to be brought to the hospital emergency department (ED). Various prediction models have been proposed to support diagnosis of exacerbations and evaluation of their severity. Objectives: First, to evaluate prediction models constructed from data using machine learning techniques and to select the best performing model. Second, to compare predictions from the selected model with predictions from the Pediatric Respiratory Assessment Measure (PRAM) score, and predictions made by ED physicians. Design: A two-phase study conducted in the ED of an academic pediatric hospital. In phase 1 data collected prospectively using paper forms was used to construct and evaluate five prediction models, and the best performing model was selected. In phase 2, data collected prospectively using a mobile system was used to compare the predictions of the selected prediction model with those from PRAM and ED physicians. Measurements: Area under the receiver operating characteristic curve and accuracy in phase 1; accuracy, sensitivity, specificity, positive and negative predictive values in phase 2. Results: In phase 1 prediction models were derived from a data set of 240 patients and evaluated using 10-fold cross validation. A naive Bayes (NB) model demonstrated the best performance and it was selected for phase 2. Evaluation in phase 2 was conducted on data from 82 patients. Predictions made by the NB model were less accurate than the PRAM score and physicians (accuracy of 70.7%, 73.2% and 78.0% respectively), however, according to McNemar’s test it is not possible to conclude that the differences between predictions are statistically significant. Conclusion: Both the PRAM score and the NB model were less accurate than physicians. The NB model can handle incomplete patient data and as such may complement the PRAM score. However, it requires further research to improve its accuracy

Using PICO to Align Medical Evidence with MDs Decision Making Models

Modern medicine is characterized by an “explosion” in clinical research information making practical application of Evidence-Based Medicine (EBM), problematic for many clinicians. We have developed a PICO-(evidence based search strategy focusing on Patient/Population, Intervention, Comparison and Outcome)-based framework for (indexing and retrieving medical evidence and we posit that the use of PICO allows for organizing evidence that is aligned with an MD’s decision making model. We describe a study where medical students evaluated our PICO-based approach and results show that students are eager to apply EBM but are hindered by a lack of specialist skills. Students reported that the PICO-based framework for organizing evidence provided an intuitive way of accessing and evaluating evidence and would be useful for their clinical tasks

Energy and Atomic Mass Dependence of Nuclear Stopping Power in Relativistic Heavy-Ion Collisions in Interacting Gluon Model

We present a Monte-Carlo simulation of energy deposition process in relativistic heavy-ion collisions based on a new realization of the Interacting-Gluon-Model (IGM) for high energy $N-N$ collisions. In particular we show results for proton spectra from collisions of $E_{lab}=200 \ GeV/N$ $^{32}$S beam incident on $^{32}$S target and analyze the energy and mass dependence of nuclear stopping power predicted by our model. Theoretical predictions for proton rapidity distributions of both $^{208}$Pb + $^{208}$Pb collisions at $E_{lab}=160 \ GeV/N$ CERN SPS and $^{197}$Au + $^{197}$Au at $\sqrt{s_{NN}}=200 \ GeV$ BNL RHIC are given.Comment: 10 pages in compressed uuencoded fil

Fluctuations of g-factors in metal nanoparticles: Effects of electron-electron interaction and spin-orbit scattering

We investigate the combined effect of spin-orbit scattering and electron-electron interactions on the probability distribution of $g$-factors of metal nanoparticles. Using random matrix theory, we find that even a relatively small interaction strength %(ratio of exchange constant $J$ and mean level %spacing \spacing $\simeq 0.3$) significantly increases $g$-factor fluctuations for not-too-strong spin-orbit scattering (ratio of spin-orbit rate and single-electron level spacing 1/\tau_{\rm so} \spacing \lesssim 1), and leads to the possibility to observe $g$-factors larger than two.Comment: RevTex, 2 figures inserte

A Task-based Support Architecture for Developing Point-of-care Clinical Decision Support Systems for the Emergency Department

Objectives: The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. Methods: The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. Results: The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE – a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. Conclusions: The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs

Modified Hagedorn formula including temperature fluctuation - Estimation of temperatures at RHIC experiments -

We have systematically estimated the possible temperatures obtained from an analysis of recent data on $p_t$ distributions observed at RHIC experiments. Using the fact that observed $p_t$ distributions cannot be described by the original Hagedorn formula in the whole range of transverse momenta (in particular above 6 GeV/c), we propose a modified Hagedorn formula including temperature fluctuation. We show that by using it we can fit $p_t$ distributions in the whole range and can estimate consistently the relevant temperatures, including their fluctuations.Comment: Some misprints corrected, references updated. To be published in Eur. Phys. J. C (2006

Emotional well-being in children with epilepsy: Family factors as mediators and moderators

Objective: Our objective was to examine the relationships of factors associated with children\u27s emotional well-being 2 years after diagnosis, and to examine if these relationships are mediated or moderated by family factors. Methods: Data came from a multicenter prospective cohort study of children with newly diagnosed epilepsy from across Canada (Health-Related Quality of Life in Children with Epilepsy Study; HERQULES, n = 373). Emotional well-being was assessed using the Quality of Life in Childhood Epilepsy Questionnaire (QOLCE-55). The relationships between clinical factors, family factors, and emotional well-being were assessed using multiple regression analyses. Results: Family functioning, family stress, and repertoire of resources that the families had to adapt to stressful events were significantly associated with poor emotional well-being 2 years after diagnosis (p \u3c 0.05) in the multivariable analysis. The effect of parental depressive symptoms was partially mediated by family functioning and family stress (p \u3c 0.01 and p = 0.02, respectively). Family resources acted as a moderator in the relationship between severity of epilepsy and emotional well-being (p \u3c 0.05). Significance: Based on our findings, efforts to strengthen the family environment may warrant attention. We suggest that clinicians take a family centered care approach by including families in treatment planning. Family centered care has been shown to improve family well-being and coping and in turn may reduce the impact of clinical factors on emotional well-being to improve long-term health-related quality of life