Can an adequate energy intake be able to reverse the negative nitrogen balance in mechanically ventilated critically ill patients?

Purpose: Adequate energy provision and nitrogen losses prevention of critically ill patients are essentials for treatment and recovery. The aims of this study were to evaluate energy expenditure (EE) and nitrogen balance (NB) of critically ill patients, to classify adequacy of energy intake (El), and to verify adequacy of El capacity to reverse the negative NB. Methods: Seventeen patients from an intensive care unit were evaluated within a 24-hour period. Indirect calorimetry was performed to calculate patient`s EE and Kjeldhal for urinary nitrogen analysis. The total El and protein intake were calculated from the standard parenteral and enteral nutrition infused. Underfeeding was characterized as El 90% or less and overfeeding as 110% or greater of EE. The adequacy of the El (El EE(-1) x 100) and the NB were estimated and associated with each other by Spearman coefficient. Results: The mean EE was 1515 +/- 268 kcal d(-1) and most of the patients (11/14) presented a negative NB (-8.2 +/- 4.7 g.d(-1)). A high rate (53%) of inadequate energy intake was found, and a positive correlation between El EE(-1) and NB was observed (r = 0.670; P = .007). Conclusion: The results show a high rate of inadequate El and negative NB, and equilibrium between El and EE may improve NB. Indirect calorimetry can be used to adjust the energy requirements in the critically ill patients. (C) 2010 Elsevier Inc. All rights reserved.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

A Communication and Resources Management Scheme to Support the Smart Grid Integration of Multiplayers Access to Resources Information

The increasing and intensive integration of distributed energy resources into distribution systems requires adequate methodologies to ensure a secure operation according to the smart grid paradigm. In this context, SCADA (Supervisory Control and Data Acquisition) systems are an essential infrastructure. This paper presents a conceptual design of a communication and resources management scheme based on an intelligent SCADA with a decentralized, flexible, and intelligent approach, adaptive to the context (context awareness). The methodology is used to support the energy resource management considering all the involved costs, power flows, and electricity prices leading to the network reconfiguration. The methodology also addresses the definition of the information access permissions of each player to each resource. The paper includes a 33-bus network used in a case study that considers an intensive use of distributed energy resources in five distinct implemented operation contexts.

Data Mining Approach to support the Generation of Realistic Scenarios for Multi-Agent simulation of Electricity Markets

This paper presents the Realistic Scenarios Generator (RealScen), a tool that processes data from real electricity markets to generate realistic scenarios that enable the modeling of electricity market players’ characteristics and strategic behavior. The proposed tool provides significant advantages to the decision making process in an electricity market environment, especially when coupled with a multi-agent electricity markets simulator. The generation of realistic scenarios is performed using mechanisms for intelligent data analysis, which are based on artificial intelligence and data mining algorithms. These techniques allow the study of realistic scenarios, adapted to the existing markets, and improve the representation of market entities as software agents, enabling a detailed modeling of their profiles and strategies. This work contributes significantly to the understanding of the interactions between the entities acting in electricity markets by increasing the capability and realism of market simulations.

How reporting and controlling systems can be effectively designed to support the decision-making process: The case of a Software SME

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Service-oriented infrastructure to support the control, monitoring and management of a shop floor system

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Addressing Young People's Drinking in Northern Ireland: Action to Support the New Strategic Direction for Alcohol and Drugs

This action plan focuses on three main areas: • reducing young people’s demand for alcohol by providing information, education and training to young people and their parents; •restricting the supply of alcohol via measures to reduce accessibility to alcohol (including how alcohol is priced, marketed, and promoted); and • providing treatment and support for those who require additional help. While the emphasis of this action plan is on young people, it recognises that their drinking patterns are very much influenced by modelling the drinking patterns of adults in our society, and it therefore contains actions that will impact on the entire population. Alcohol misuse - however you measure the cost, whether to the individual, the family, the community, the health service, or society as a whole - is one of the biggest public health issues facing Northern Ireland.

A Method and Tool to Support the Analysis and Enhance the Understanding of Peer-to-Peer Learning Experiences

In this paper we look at how a web-based social software can be used to make qualitative data analysis of online peer-to-peer learning experiences. Specifically, we propose to use Cohere, a web-based social sense-making tool, to observe, track, annotate and visualize discussion group activities in online courses. We define a specific methodology for data observation and structuring, and present results of the analysis of peer interactions conducted in discussion forum in a real case study of a P2PU course. Finally we discuss how network visualization and analysis can be used to gather a better understanding of the peer-to-peer learning experience. To do so, we provide preliminary insights on the social, dialogical and conceptual connections that have been generated within one online discussion group.

Open video tools to support the production of online collaborative audiovisual projects : how to promote collective creation in e-learning

This paper analyses the use of open video editing tools to support the creation and production of online collaborative audiovisual projects for higher education. It focuses on the possibilities offered by these tools to promote collective creation in virtual environments.

eKnowledge Project: Developing and piloting a forum tool to support the collaborative construction of knowledge on the UOC's Virtual Campus

Final report of the eKnowledge's project, an online forum tool that offers consultants and students the chance to create spaces for asynchronous communication and collaboration.

Expression of E-Selectin and Vascular Cell Adhesion Molecule-1 in So-Called 'Negative' Appendices: First Results to Support the Pathological Diagnosis in Borderline Cases.

Background: Since the rate of histologically 'negative' appendices still ranges between 15 and 20%, appendicitis in 'borderline' cases remains a challenging disease. As previously described, cell adhesion molecule expression correlates with different stages of appendicitis. Therefore, it was of interest to determine whether the 'negative' appendix correlated with the absence of E-selectin or vascular cell adhesion molecule-1 (VCAM-1). Methods: Nineteen grossly normal appendices from a series of 120 appendectomy specimens from patients with suspected appendicitis were analysed in frozen sections for the expression of E-selectin and VCAM-1. As control, 5 normal appendices were stained. Results: This study showed a coexpression of E-selectin and VCAM-1 in endothelial cells in early and recurrent appendicitis. In patients with symptoms for less than 6 h, only E-selectin was detected. Cases with fibrosis and luminal obliteration were only positive for VCAM-1. In cases of early appendicitis with symptoms of less than 6 h duration, a discordance between histological and immunohistochemical results was found. Conclusions: This report indicates that E-selectin and VCAM-1 expression could be useful parameters in the diagnosis of appendicitis in borderline cases.

A design science approach to support the assessment of disruptive technology : the Swiss mobile payment case

Abstract In this thesis we present the design of a systematic integrated computer-based approach for detecting potential disruptions from an industry perspective. Following the design science paradigm, we iteratively develop several multi-actor multi-criteria artifacts dedicated to environment scanning. The contributions of this thesis are both theoretical and practical. We demonstrate the successful use of multi-criteria decision-making methods for technology foresight. Furthermore, we illustrate the design of our artifacts using build and-evaluate loops supported with a field study of the Swiss mobile payment industry. To increase the relevance of this study, we systematically interview key Swiss experts for each design iteration. As a result, our research provides a realistic picture of the current situation in the Swiss mobile payment market and reveals previously undiscovered weak signals for future trends. Finally, we suggest a generic design process for environment scanning.

Data Envelopment Analysis and non-discretionary inputs : How to select the most suitable model using multi-criteria decision analysis

Within Data Envelopment Analysis, several alternative models allow for an environmental adjustment. The majority of them deliver divergent results. Decision makers face the difficult task of selecting the most suitable model. This study is performed to overcome this difficulty. By doing so, it fills a research gap. First, a two-step web-based survey is conducted. It aims (1) to identify the selection criteria, (2) to prioritize and weight the selection criteria with respect to the goal of selecting the most suitable model and (3) to collect the preferences about which model is preferable to fulfil each selection criterion. Second, Analytic Hierarchy Process is used to quantify the preferences expressed in the survey. Results show that the understandability, the applicability and the acceptability of the alternative models are valid selection criteria. The selection of the most suitable model depends on the preferences of the decision makers with regards to these criteria.