Seasonal changes of leaf Nitrogen content in trees of Amazonian floodplains

In Amazonian floodplains the trees are exposed to extreme flooding of up to 230 days a year. Waterlogging of the roots and stems affects growth and metabolic activity of the trees. An increased leaf fall in the aquatic period and annual increment rings in the wood indicate periodical growth reductions. The present study aims at documenting seasonal changes of metabolism and vitality of adult trees in the annual cycle as expressed by changes of leaf nitrogen content. Leaves of six tree species common in floodplains in Central Amazonia and typical representants of different growth strategies were collected every month between May 1994 and June 1995 in the vicinity of Manaus, Brazil. Mean leaf nitrogen content varied between 1.3% and 3.2% in the non-flooded trees. Three species showed significantly lower Ν content in the flooded period (p=0.05, 0.001, 0.001), the difference ranging 20-25% lower than in the non-flooded period. Two species showed no significant difference while Nectandra amazonum showed 32% more Ν in the flooded season (p=0.001). Leaf nitrogen content was generally high when new leaves were flushed (in the flooded period) and decreased continuously thereafter in all species. Three species showed an additional peak of nitrogen during the first month of the terrestrial phase, in leaves which had flushed earlier, indicating that flooding may disturb nitrogen uptake.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Soil mineral N dynamics beneath mixtures of leaves from legume and fruit trees in Central Amazonian multi-strata agroforests

Long term applications of leguminous green mulch could increase mineralizable nitrogen (N) beneath cupuaçu trees produced on the infertile acidic Ultisols and Oxisols of the Amazon Basin. However, low quality standing cupuaçu litter could interfere with green mulch N release and soil N mineralization. This study compared mineral N, total N, and microbial biomass N beneath cupuaçu trees grown in two different agroforestry systems, north of Manaus, Brazil, following seven years of different green mulch application rates. To test for net interactions between green mulch and cupuaçu litter, dried gliricidia and inga leaves were mixed with senescent cupuaçu leaves, surface applied to an Oxisol soil, and incubated in a greenhouse for 162 days. Leaf decomposition, N release and soil N mineralization were periodically measured in the mixed species litter treatments and compared to single species applications. The effect of legume biomass and cupuaçu litter on soil mineral N was additive implying that recommendations for green mulch applications to cupuaçu trees can be based on N dynamics of individual green mulch species. Results demonstrated that residue quality, not quantity, was the dominant factor affecting the rate of N release from leaves and soil N mineralization in a controlled environment. In the field, complex N cycling and other factors, including soil fauna, roots, and microclimatic effects, had a stronger influence on available soil N than residue quality.

BeSmart2: A multicriteria decision aid application

This paper presents an improved version of an application whose goal is to provide a simple and intuitive way to use multicriteria decision methods in day-to-day decision problems. The application allows comparisons between several alternatives with several criteria, always keeping a permanent backup of both model and results, and provides a framework to incorporate new methods in the future. Developed in C#, the application implements the AHP, SMART and Value Functions methods.

Global warming in Amazonia: impacts and Mitigation

Global warming has potentially catastrophic impacts in Amazonia, while at the same time maintenance of the Amazon forest offers one of the most valuable and cost-effective options for mitigating climate change. We know that the El Niño phenomenon, caused by temperature oscillations of surface water in the Pacific, has serious impacts in Amazonia, causing droughts and forest fires (as in 1997-1998). Temperature oscillations in the Atlantic also provoke severe droughts (as in 2005). We also know that Amazonian trees die both from fires and from water stress under hot, dry conditions. In addition, water recycled through the forest provides rainfall that maintains climatic conditions appropriate for tropical forest, especially in the dry season. What we need to know quickly, through intensified research, includes progress in representing El Niño and the Atlantic oscillations in climatic models, representation of biotic feedbacks in models used for decision-making about global warming, and narrowing the range of estimating climate sensitivity to reduce uncertainty about the probability of very severe impacts. Items that need to be negotiated include the definition of "dangerous" climate change, with the corresponding maximum levels of greenhouse gases in the atmosphere. Mitigation of global warming must include maintaining the Amazon forest, which has benefits for combating global warming from two separate roles: cutting the flow the emissions of carbon each year from the rapid pace of deforestation, and avoiding emission of the stock of carbon in the remaining forest that can be released by various ways, including climate change itself. Barriers to rewarding forest maintenance include the need for financial rewards for both of these roles. Other needs are for continued reduction of uncertainty regarding emissions and deforestation processes, as well as agreement on the basis of carbon accounting. As one of the countries most subject to impacts of climate change, Brazil must assume the leadership in fighting global warming.

Mites (Arachnida, Acari) on Citrus sinensis L. Osbeck orange trees in the state of Amazonas, Northern Brazil

Despite the importance of citriculture in Brazil, very little is known about mite populations in citrus crops in the Northern Region. In the municipality of Manaus, 12 sprayed sweet orange orchards were surveyed every two weeks during seven months to record mite species amount, and to describe the abundance and distribution of the most important species. The size and age of the orchards varied from 3,360 to 88,080 m² and seven to 25 years, respectively. In the fourteen sampling period, leaves, twigs and fruits were collected from 12 trees, one per orchard. In total, 3,360 leaves, 672 twigs and 1,344 fruits were sampled from 168 trees. Mites were manually extracted from the fruits, and by the washing method on leaves and twigs. We identified pests with the potential to cause economic loss. Fourteen species of phytophagous and mycophagous mites from Eriophyidae, Tarsonemidae, Tenuipalpidae, and Tetranychidae were recorded. Brevipalpus phoenicis (Geijskes 1939) and Phyllocoptruta oleivora (Ashm., 1879), the two commonest phytophagous mites in other Brazilian regions were dominant, showing that local orchards are susceptible to their infestation. Eleven predatory mites were recorded, comprising 10% of the mite population, belonging to Phytoseiidae and Ascidae. Phytoseiidae was the richest family, with ten species. The results are discussed in relation to the temporal variation aspects and habitat use of the most important species. Long-term research encompassing chemical applications followed by evaluations of the mite community are necessary for a better management of the orchards, taking into consideration the seasonal phenology of key pests.

Normal aging and decision-making: a systematic review of the literature of the last 10 years

Objective Conduct a systematic review to investigate whether healthy elderly have deficits in the decision-making process when compared to the young. Methods We performed a systematic search on SciELO, Lilacs, PsycINFO, Scopus and PubMed database with keywords decision making and aging (according to the description of Mesh terms) at least 10 years. Results We found nine studies from different countries, who investigated 441 young and 377 elderly. All studies used the IOWA Gambling Task as a way of benchmarking the process of decision making. The analysis showed that 78% of the articles did not have significant differences between groups. However, 100% of the studies that assessed learning did find relevant differences. Furthermore, studies that observed the behavior of individuals in the face of losses and gains, 60% of articles showed that the elderly has more disadvantageous choices throughout the task. Conclusion: The consulted literature showed no consensus on the existence of differences in performance of the decision-making process between old and young, but it is observed that the elderly has deficits in learning and a tendency to fewer advantageous choices.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.

A voyage to the islands Madera, Barbados, Nieves, S. Christophers and Jamaica : with the natural history of the herbs and trees, four-footed beasts, fishes, birds, insects, reptiles, &c. of the last of those islands; to which is prefix'd, an introduction, wherein is an account of the inhabitants, air, waters, diseases, trade, &c. of that place, with some relations concerning the neighbouring continent, and islands of America. Illustrated with figures of the things described, which have not been heretofore engraved. In large copper-plates as big as the life /

Vol. 2