GDM-VieweR: A new tool in R to visualize the evolution of fuzzy consensus processes

With the incorporation of web 2.0 frameworks the complexity of decision making situations has exponentially increased, involving in many cases many experts, and a huge number of different alternatives. In the literature we can find a great deal of methodologies to assist multi-person decision making. However these classical approaches are not prepared to deal with such a huge complexity and there is a lack of tools that support the decision processes providing some graphical information. Therefore the main objective of this contribution is to present an open source tool developed in R to provide a quick insight of the evolution of the decision making by means of meaningful graphical representations. Thanks to the modular architecture of this solution this tool can be easily adapted to work with various Group decision making methodologies

A Measure of Perceived Performance to Assess Resource Allocation

The final publication is available at Springer via http://dx.doi.org/10.1007/s00500-015-1696-3Performance measurement is a key issue when a company is designing new strategies to improve resource allocation. This paper offers a new methodology inspired by classic importance-performance analysis (IPA) that provides a global index of importance versus performance for firms. This index compares two rankings of the same set of features regarding importance and performance, taking into account underperforming features. The marginal contribution of each feature to the proposed global index defines a set of iso-curves that represents an improvement in the IPA diagram. The defined index, together with the new version of the diagram, will enable the assessment of a firm's overall performance and, therefore, enhance decision making in the allocation of resources. The proposed methodology has been applied to a Taiwanese multi-format retailer and managerial perceptions of performance and importance are compared to assess the firm's overall performance.Peer ReviewedPostprint (author's final draft

Intercalation of small molecules into DNA in chromatin is primarily controlled by superhelical constraint

The restricted access of regulatory factors to their binding sites on DNA wrapped around the nucleosomes is generally interpreted in terms of molecular shielding exerted by nucleosomal structure and internucleosomal interactions. Binding of proteins to DNA often includes intercalation of hydrophobic amino acids into the DNA. To assess the role of constrained superhelicity in limiting these interactions, we studied the binding of small molecule intercalators to chromatin in close to native conditions by laser scanning cytometry. We demonstrate that the nucleosome-constrained superhelical configuration of DNA is the main barrier to intercalation. As a result, intercalating compounds are virtually excluded from the nucleosome-occupied regions of the chromatin. Binding of intercalators to extranucleosomal regions is limited to a smaller degree, in line with the existence of net supercoiling in the regions comprising linker and nucleosome free DNA. Its relaxation by inducing as few as a single nick per ~50 kb increases intercalation in the entire chromatin loop, demonstrating the possibility for long-distance effects of regulatory potential

Promotoras as Mental Health Practitioners in Primary Care: A Multi-Method Study of an Intervention to Address Contextual Sources of Depression

We assessed the role of promotoras—briefly trained community health workers—in depression care at community health centers. The intervention focused on four contextual sources of depression in underserved, low-income communities: underemployment, inadequate housing, food insecurity, and violence. A multi-method design included quantitative and ethnographic techniques to study predictors of depression and the intervention’s impact. After a structured training program, primary care practitioners (PCPs) and promotoras collaboratively followed a clinical algorithm in which PCPs prescribed medications and/or arranged consultations by mental health professionals and promotoras addressed the contextual sources of depression. Based on an intake interview with 464 randomly recruited patients, 120 patients with depression were randomized to enhanced care plus the promotora contextual intervention, or to enhanced care alone. All four contextual problems emerged as strong predictors of depression (chi square, p < .05); logistic regression revealed housing and food insecurity as the most important predictors (odds ratios both 2.40, p < .05). Unexpected challenges arose in the intervention’s implementation, involving infrastructure at the health centers, boundaries of the promotoras’ roles, and “turf” issues with medical assistants. In the quantitative assessment, the intervention did not lead to statistically significant improvements in depression (odds ratio 4.33, confidence interval overlapping 1). Ethnographic research demonstrated a predominantly positive response to the intervention among stakeholders, including patients, promotoras, PCPs, non-professional staff workers, administrators, and community advisory board members. Due to continuing unmet mental health needs, we favor further assessment of innovative roles for community health workers

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Hybrid Model for Parkinson's Disease Prediction

Parkinson’s is a chronic, progressive neurological disease with no known cause that affects the central nervous system of older people and compromises their movement. This disorder can impair daily aspects of people and therefore identify their existence early, helps in choosing treatments that can reduce the impact of the disease on the patient’s routine. This work aims to identify Parkinson’s traces through a voice recording replications database applied to a fuzzy neural network to identify their patterns and enable the extraction of knowledge about situations present in the data collected in patients. The results obtained by the hybrid model were superior to state of the art for the theme, proving that it is possible to perform hybrid models in the extraction of knowledge and the classification of behavioral patterns of high accuracy Parkinson’s