Electronic Health Records: An International Perspective on "Meaningful Use"

Examines the extent of meaningful use of electronic health records in Denmark, New Zealand, and Sweden, including sharing information with organizations, health authorities, and patients. Outlines challenges of and insights into encouraging U.S. adoption

Computer - Supported Cooperative Work - Concepts and Trends

The research field Computer-Supported Cooperative Work (CSCW) is concerned with understanding social interaction and the design, development, and evaluation of technical systems supporting social interaction in teams and communities – or in other words it is about researching the use of computer-based technology for supporting collaboration. The field was coined in the 1980th by researchers from computer science, information science and social science. In this paper we will briefly introduce CSCW – its concepts and current trends - and thereby focus on the role of Informatics in the field – from application integration to ubiquitous user interfaces

Scaling up the self-optimization model by means of on-the-fly computation of weights

The Self-Optimization (SO) model is a useful computational model for investigating self-organization in "soft" Artificial life (ALife) as it has been shown to be general enough to model various complex adaptive systems. So far, existing work has been done on relatively small network sizes, precluding the investigation of novel phenomena that might emerge from the complexity arising from large numbers of nodes interacting in interconnected networks. This work introduces a novel implementation of the SO model that scales as $\mathcal{O}\left(N^{2}\right)$ with respect to the number of nodes $N$, and demonstrates the applicability of the SO model to networks with system sizes several orders of magnitude higher than previously was investigated. Removing the prohibitive computational cost of the naive $\mathcal{O}\left(N^{3}\right)$ algorithm, our on-the-fly computation paves the way for investigating substantially larger system sizes, allowing for more variety and complexity in future studies.Comment: 7 pages, 7 figure

On the use of associative memory in Hopfield networks designed to solve propositional satisfiability problems

Hopfield networks are an attractive choice for solving many types of computational problems because they provide a biologically plausible mechanism. The Self-Optimization (SO) model adds to the Hopfield network by using a biologically founded Hebbian learning rule, in combination with repeated network resets to arbitrary initial states, for optimizing its own behavior towards some desirable goal state encoded in the network. In order to better understand that process, we demonstrate first that the SO model can solve concrete combinatorial problems in SAT form, using two examples of the Liars problem and the map coloring problem. In addition, we show how under some conditions critical information might get lost forever with the learned network producing seemingly optimal solutions that are in fact inappropriate for the problem it was tasked to solve. What appears to be an undesirable side-effect of the SO model, can provide insight into its process for solving intractable problems.Comment: 7 pages, 4 figure

Social-science research and the general social surveys

'Social-science research has been transformed over the last generation by the advent and expansion of the general social surveys (GSS). The GSS model of research has created a infrastructure for the social sciences designed to address the interests and research agenda of scholars and their students; cover a wide range of topics; utilize reliable, valid, and generalizable measurement; and provide data both across nations and across time. This design in turn has generated widespread analysis and notably contributed to our understanding of social processes and societal change.' (author's abstract)

O papel da engenharia de túneis na tomada de decisão de alternativas em projetos rodoferroviários

TCC (graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia Civil.A infraestrutura de um país tem grande importância em seu desenvolvimento e as decisões cabem principalmente aos tomadores de decisão do setor público, os quais muitas vezes não possuem conhecimento técnico de engenharia. Devido a isso, as tomadas de decisão tendem a passar por uma análise financeira apenas, visando a alternativa mais barata e desprezando possíveis alternativas como a de traçados rodoferroviários com túneis, por exemplo. Mesmo que as obras de túneis tendam a ser mais onerosas, elas trazem resultados únicos como redução de acidentes de trânsito, redução do tempo de viagem, redução de manutenção, redução do impacto ambiental entre outros. Este trabalho tem por objetivo explorar a visão técnica da engenharia de túneis nas tomadas de decisão de alternativas em projetos rodoferroviários. Explora-se métodos de construção de túneis, métodos de tomada de decisão, traz-se cinco exemplos de casos representativos e duas análises de custo-benefício de obras reais. Conclui-se que as tomadas de decisão de projeto rodoferroviários englobam uma série de fatores que muitas vezes são extremamente complicados de se contabilizar através de valores monetários.A country's infrastructure is of great importance in its development. However, decisions are mainly made by decision makers from the public sector, who often do not have technical engineering knowledge. Due to this fact, decision-making tends to go through a financial analysis only, focusing on the cheapest alternative and ignoring possible alternatives such as tunneling for road-rail projects. Even though tunneling works tend to be more costly, they bring unique results such as reducing traffic accidents, reducing travel time, reducing maintenance, reducing environmental impact, among others. This paper aims to explore the technical vision of tunnel engineering in decision-making for alternatives in road-rail projects. It explores tunnel construction methods, decision-making methods, five representative case examples and two cost benefit analyses of real works. It is concluded that the road-railway project decision-making involves a series of factors that are often extremely complicated to account through monetary values

A Combined Score of Circulating miRNAs Allows Outcome Prediction in Critically Ill Patients

Background and aims: Identification of patients with increased risk of mortality represents an important prerequisite for an adapted adequate and individualized treatment of critically ill patients. Circulating micro-RNA (miRNA) levels have been suggested as potential biomarkers at the intensive care unit (ICU), but none of the investigated miRNAs displayed a sufficient sensitivity or specificity to be routinely employed as a single marker in clinical practice. Methods and results: We recently described alterations in serum levels of 7 miRNAs (miR-122, miR-133a, miR-143, miR-150, miR-155, miR-192, and miR-223) in critically ill patients at a medical ICU. In this study, we re-analyzed these previously published data and performed a combined analysis of these markers to unravel their potential as a prognostic scoring system in the context of critical illness. Based on the Youden’s index method, cut-off values were systematically defined for dysregulated miRNAs, and a “miRNA survival score” was calculated. Patients with high scores displayed a dramatically impaired prognosis compared to patients with low values. Additionally, the predictive power of our score could be further increased when the patient’s age was additionally incorporated into this score. Conclusions: We describe the first miRNA-based biomarker score for prediction of medical patients’ outcome during and after ICU treatment. Adding the patients’ age into this score was associated with a further increase in its predictive power. Further studies are needed to validate the clinical utility of this score in risk-stratifying critically ill patients

Validation of mesoscale models

The topics discussed include the following: verification of cloud prediction from the PSU/NCAR mesoscale model; results form MAPS/NGM verification comparisons and MAPS observation sensitivity tests to ACARS and profiler data; systematic errors and mesoscale verification for a mesoscale model; and the COMPARE Project and the CME

A quick guide for student-driven community genome annotation

High quality gene models are necessary to expand the molecular and genetic tools available for a target organism, but these are available for only a handful of model organisms that have undergone extensive curation and experimental validation over the course of many years. The majority of gene models present in biological databases today have been identified in draft genome assemblies using automated annotation pipelines that are frequently based on orthologs from distantly related model organisms. Manual curation is time consuming and often requires substantial expertise, but is instrumental in improving gene model structure and identification. Manual annotation may seem to be a daunting and cost-prohibitive task for small research communities but involving undergraduates in community genome annotation consortiums can be mutually beneficial for both education and improved genomic resources. We outline a workflow for efficient manual annotation driven by a team of primarily undergraduate annotators. This model can be scaled to large teams and includes quality control processes through incremental evaluation. Moreover, it gives students an opportunity to increase their understanding of genome biology and to participate in scientific research in collaboration with peers and senior researchers at multiple institutions