Forest soil short term response to prescribed fire: an approach by Principal Components Analysis

In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.

Short-term Wind Forecasting to Support Virtual Power Player Operation

This paper proposes a wind speed forecasting model that contributes to the development and implementation of adequate methodologies for Energy Resource Man-agement in a distribution power network, with intensive use of wind based power generation. The proposed fore-casting methodology aims to support the operation in the scope of the intraday resources scheduling model, name-ly with a time horizon of 10 minutes. A case study using a real database from the meteoro-logical station installed in the GECAD renewable energy lab was used. A new wind speed forecasting model has been implemented and it estimated accuracy was evalu-ated and compared with a previous developed forecast-ing model. Using as input attributes the information of the wind speed concerning the previous 3 hours enables to obtain results with high accuracy for the wind short-term forecasting.

Short-term Load Forecasting Based on Load Profiling

Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility company, and they have received increasing attention from researches of this field study. Many mathematical methods have been developed for load forecasting. This work aims to develop and implement a load forecasting method for short-term load forecasting (STLF), based on Holt-Winters exponential smoothing and an artificial neural network (ANN). One of the main contributions of this paper is the application of Holt-Winters exponential smoothing approach to the forecasting problem and, as an evaluation of the past forecasting work, data mining techniques are also applied to short-term Load forecasting. Both ANN and Holt-Winters exponential smoothing approaches are compared and evaluated.

Stochastic Short-term Incentive-based Demand Response Scheduling of Load-serving Entities

In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

Multiagent System Architecture for Short-term Operation of Integrated Microgrids

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid’s internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

Short-term Wind Speed Forecasting using Support Vector Machines

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

Frailty as a predictor of short-term adverse outcomes

The objectives of this study were to compare how different frailty measures (Frailty Phenotype/FP, Groningen Frailty Indicator/GFI and Tilburg Frailty Indicator/TFI) predict short-term adverse outcomes. Secondarily, adopting a multidimensional approach to frailty (integral conceptual model–TFI), this study aims to compare how physical, psychological and social frailty predict the outcomes. A longitudinal study was carried out with 95 community-dwelling elderly. Participants were assessed at baseline for frailty, determinants of frailty, and adverse outcomes (healthcare utilization, quality of life, disability in basic and instrumental activities of daily living/ADL and IADL). Ten months later the outcomes were assessed again. Frailty was associated with specific healthcare utilization indicators: the FP with a greater utilization of informal care; GFI with an increased contact with healthcare professionals; and TFI with a higher amount of contacts with a general practitioner. After controlling for the effect of life-course determinants, comorbidity and adverse outcome at baseline, GFI predicted IADL disability and TFI predicted quality of life. The effect of the FP on the outcomes was not significant, when compared with the other measures. However, when comparing TFI’s domains, the physical domain was the most significant predictor of the outcomes, even explaining part of the variance of ADL disability. Frailty at baseline was associated with adverse outcomes at follow-up. However, the relationship of each frailty measure (FP, GFI and TFI) with the outcomes was different. In spite of the role of psychological frailty, TFI’s physical domain was the determinant factor for predicting disability and most of the quality of life.

Using data mining with time series data in short-term stocks prediction

Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

A multi-objective model for scheduling of short-term incentive-based demand response programs offered by electricity retailers

In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

Use of a fluorescence-based approach to assess short-term responses of the alga Pseudokirchneriella subcapitata to metal stress

This work explores the use of fluorescent probes to evaluate the responses of the green alga Pseudokirchneriella subcapitata to the action of three nominal concentrations of Cd(II), Cr(VI), Cu(II) and Zn(II) for a short time (6 h). The toxic effect of the metals on algal cells was monitored using the fluorochromes SYTOX Green (SG, membrane integrity), fluorescein diacetate (FDA, esterase activity) and rhodamine 123 (Rh123, mitochondrial membrane potential). The impact of metals on chlorophyll a (Chl a) autofluorescence was also evaluated. Esterase activity was the most sensitive parameter. At the concentrations studied, all metals induced the loss of esterase activity. SG could be used to effectively detect the loss of membrane integrity in algal cells exposed to 0.32 or 1.3 μmol L−1 Cu(II). Rh123 revealed a decrease in the mitochondrial membrane potential of algal cells exposed to 0.32 and 1.3 μmol L−1 Cu(II), indicating that mitochondrial activity was compromised. Chl a autofluorescence was also affected by the presence of Cr(VI) and Cu(II), suggesting perturbation of photosynthesis. In conclusion, the fluorescence-based approach was useful for detecting the disturbance of specific cellular characteristics. Fluorescent probes are a useful diagnostic tool for the assessment of the impact of toxicants on specific targets of P. subcapitata algal cells.

Medium-short-term and repetition effects of advergames on children consumer behaviour

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

Essays in health economics: Volume-Outcome Effect, upcoding behaviour and the evaluation of a short-term intervention program

Evidence in the literature suggests a negative relationship between volume of medical procedures and mortality rates in the health care sector. In general, high-volume hospitals appear to achieve lower mortality rates, although considerable variation exists. However, most studies focus on US hospitals, which face different incentives than hospitals in a National Health Service (NHS). In order to add to the literature, this study aims to understand what happens in a NHS. Results reveal a statistically significant correlation between volume of procedures and better outcomes for the following medical procedures: cerebral infarction, respiratory infections, circulatory disorders with AMI, bowel procedures, cirrhosis, and hip and femur procedures. The effect is explained with the practice-makes-perfect hypothesis through static effects of scale with little evidence of learning-by-doing. The centralization of those medical procedures is recommended given that this policy would save a considerable number of lives (reduction of 12% in deaths for cerebral infarction).

Nutritional follow-up of critically ill infants receiving short term parenteral nutrition

Few studies have tried to characterize the efficacy of parenteral support of critically ill infants during short period of intensive care. We studied seventeen infants during five days of total parenteral hyperalimentation. Subsequently, according to the clinical conditions, the patients received nutritional support by parenteral, enteral route or both up to the 10th day. Evaluations were performed on the 1st, 5th, and 10th days. These included: clinical data (food intake and anthropometric measurements), haematological data (lymphocyte count), biochemical tests (albumin, transferrin, fibronectin, prealbumin, retinol-binding protein) and hormone assays (cortisol, insulin, glucagon). Anthropometric measurements revealed no significant difference between the first and second evaluations. Serum albumin and transferrin did not change significantly, but mean values of fibronectin (8.9 to 16 mg/dL), prealbumin (7.7 to 18 mg/dL), and retinol-binding protein (2.4 to 3.7 mg/dL) increased significantly (p < 0.05) from the 1st to the 10th day. The hormonal study showed no difference for insulin, glucagon, and cortisol when the three evaluations were compared. The mean value of the glucose/insulin ratio was of 25.7 in the 1st day and 15.5 in the 5th day, revealing a transitory supression of this hormone. Cortisol showed values above normal in the beginning of the study. We conclude that the anthropometric parameters were not useful due to the short time of the study; serum proteins, fibronectin, prealbumin, and retinol-binding protein were very sensitive indicators of nutritional status, and an elevated glucose/insulin ratio, associated with a slight tendency for increased cortisol levels suggest hypercatabolic state. The critically ill patient can benefit from an early metabolic support.

Low efficacy of an ultra-short term, once-daily dose triple therapy with omeprazole, azithromycin, and secnidazole for Helicobacter pylori eradication in peptic ulcer

PURPOSE: To determine the eradication rate of an ultra-short treatment schedule for Helicobacter pylori infection in a population with peptic ulcers, using omeprazole, secnidazole, and azithromycin in a once-daily dose for 3 days. METHODS: Thirty patients with peptic ulcer diagnosed by upper endoscopy and for Helicobacter pylori infection by rapid urease test and histologic examination received omeprazole 40 mg, secnidazole 1000 mg, and azithromycin 500 mg, administered once daily for 3 days. A follow-up exam was performed 12 weeks after the end of the treatment. Patients who were negative for Helicobacter pylori infection by rapid urease test and histologic examination were considered cured. RESULTS: Patients were predominantly female, and the mean age was 50 years. Duodenal peptic ulcer was found in 73% of the patients. Eradication was achieved in 9 of the 28 (32%) patients as determined from the follow-up endoscopic exam. The eradication rate by intention to treat was 30%. Side effects were present in 3% of the patients, and compliance to treatment was total. CONCLUSIONS: In spite of the low rate of side effects and good compliance, the eradication index was low. A possible drawback of this therapy is that it reduces the efficacy of macrolide and nitroimidazole compounds in subsequent treatments.

Corrigendum to “Short-term changes in light distortion in orthokeratology subjects"

Artigo completo publicado na revista "BioMed Research International, (2015), 1-7" e disponível no RepositóriUM em: http://hdl.handle.net/1822/33375