Feeding of the Brycon cephalus, Triportheus elongatus and Semaprochilodus insignis (osteichthyes, characiformes) larvae in Solimões/Amazonas River and floodplain areas.

Information on larval fish feeding is essential for understanding their trophic relations, including the management in conditions totally or partially controlled by humans. An experiment was designed to evaluate the larval diets of three commercially important species. Four varzea-lakes and the adjacent river were sampled with bongo and hand nets from January 1993 to November 1995. Larval diets were evaluated by length-classes and capture sites, and were tested by two factor ANOVA. The larvae were feeding in all habitats, except in the flooded forests. The three species had different diets, which varied with their length and lake. The rotifers were the main initial food item of the three species, replaced by fish larvae in Brycon cephalus, cladocerans in Triportheus elongatus and detritus in Semaprochilodus insignis. The increase of the ingestion limit, as the larvae grew, was higher than the increase in the consumed prey size for the three species.

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Automatic generation of ETL physical systems from BPMN conceptual models

ETL conceptual modeling is a very important activity in any data warehousing system project implementation. Owning a high-level system representation allowing for a clear identification of the main parts of a data warehousing system is clearly a great advantage, especially in early stages of design and development. However, the effort to model conceptually an ETL system rarely is properly rewarded. Translating ETL conceptual models directly into something that saves work and time on the concrete implementation of the system process it would be, in fact, a great help. In this paper we present and discuss a hybrid approach to this problem, combining the simplicity of interpretation and power of expression of BPMN on ETL systems conceptualization with the use of ETL patterns to produce automatically an ETL skeleton, a first prototype system, which has the ability to be executed in a commercial ETL tool like Kettle.

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Natural diet and feeding habits of a freshwater prawn (Macrobrachium carcinus: Crustacea, Decapoda) in the estuary of the Amazon River

Macrobrachium carcinus is a Brazilian native prawn with recognized potential for use in aquaculture activities. However, there is little information about the natural diet and feeding habits of this species. The aim of this study was the identification of the diet items of M. carcinus based on the analysis of the stomach contents. Specimens were collected in the Amazon River estuary between January 2009 and January 2010. The stomach analysis was carried out by using the frequency of occurrence (FO), methods of points (MP) and feeding index (FI). It was observed that prawns fed on detritus, animals and plant fragments as the most important food items. Sediment accounted for the main stomach content, accounting for 43.2% by the MP, 44.9% by FI and 100% by the FO. Sexual differences in feeding preferences were not found in this study, and seasonal differences in the frequency of items ingested by M. carcinus were not observed. The results indicated that M. carcinus can be considered omnivorous species, but with an important carnivorous component, similar to that found in other Macrobrachium species.

Diet and ecomorphology of Leporinus reticulatus (Characiformes: Anostomidae) from the upper Rio Juruena, MT, Brazil: ontogenetic shifts related to the feeding ecology

The conservation of diverse and well-distributed fish taxa, as the genus Leporinus, relies intrinsically on the knowledge of the ecological attributes of its representatives. Aiming to increase this knowledge, studies on diet and ecomorphology are ideal to provide important information about species ecology. Thus, this study aimed to analyze aspects of feeding ecology of L. reticulatus, from the upper Rio Juruena, Mato Grosso State, Brazil. The diet of specimens in different ontogenetic stages was compared, as well as their teeth morphology and ecomorphological attributes. Leporinus reticulatus presented omnivorous diet, with higher consumption of invertebrates by smaller specimens (younger ones), and gradual introduction of plant items in larger specimens (older ones). The items consumed by the individuals and the ecomorphological attributes indicated that the species is generalist and opportunistic, besides its association with the river bottom, evidencing a benthic feeding behavior. This species presents a gradual ontogenetic modification in teeth shape and mouth positioning, ranging from a terminal mouth with tricuspid teeth, in smaller specimens, to an inferior mouth with spatula shaped teeth with no cusps, in larger specimens.The ecomorphological attributes indicate an increasing swimming efficiency, and ability for performing vertical displacements, along the ontogenetic development, which in addition to the morphological ontogenetic alterations in the buccal apparatus, contributes to a better ability to explore another niches.

Automatic eye blink detection using consumer web cameras

This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%

Automatic distinction of Fernando Pessoas’ heteronyms

Text Mining has opened a vast array of possibilities concerning automatic information retrieval from large amounts of text documents. A variety of themes and types of documents can be easily analyzed. More complex features such as those used in Forensic Linguistics can gather deeper understanding from the documents, making possible performing di cult tasks such as author identi cation. In this work we explore the capabilities of simpler Text Mining approaches to author identification of unstructured documents, in particular the ability to distinguish poetic works from two of Fernando Pessoas' heteronyms: Alvaro de Campos and Ricardo Reis. Several processing options were tested and accuracies of 97% were reached, which encourage further developments.

The effect of high-fat diet on rat’s mood, feeding behavior and response to stress

An association between obesity and depression has been indicated in studies addressing common physical (metabolic) and psychological (anxiety, low self-esteem) outcomes. Of consideration in both obesity and depression are chronic mild stressors to which individuals are exposed to on a daily basis. However, the response to stress is remarkably variable depending on numerous factors, such as the physical health and the mental state at the time of exposure. Here a chronic mild stress (CMS) protocol was used to assess the effect of high-fat diet (HFD)-induced obesity on response to stress in a rat model. In addition to the development of metabolic complications, such as glucose intolerance, diet-induced obesity caused behavioral alterations. Specifically, animals fed on HFD displayed depressive- and anxious-like behaviors that were only present in the normal diet (ND) group upon exposure to CMS. Of notice, these mood impairments were not further aggravated when the HFD animals were exposed to CMS, which suggest a ceiling effect. Moreover, although there was a sudden drop of food consumption in the first 3 weeks of the CMS protocol in both ND and HFD groups, only the CMS-HFD displayed an overall noticeable decrease in total food intake during the 6 weeks of the CMS protocol. Altogether, the study suggests that HFD impacts on the response to CMS, which should be considered when addressing the consequences of obesity in behavior.

Development of a semi-automatic self learning pattern recognition system for the control of electronic boards

This project was funded under the Applied Research Grants Scheme administered by Enterprise Ireland. The project was a partnership between Galway - Mayo Institute of Technology and an industrial company, Tyco/Mallinckrodt Galway. The project aimed to develop a semi - automatic, self - learning pattern recognition system capable of detecting defects on the printed circuits boards such as component vacancy, component misalignment, component orientation, component error, and component weld. The research was conducted in three directions: image acquisition, image filtering/recognition and software development. Image acquisition studied the process of forming and digitizing images and some fundamental aspects regarding the human visual perception. The importance of choosing the right camera and illumination system for a certain type of problem has been highlighted. Probably the most important step towards image recognition is image filtering, The filters are used to correct and enhance images in order to prepare them for recognition. Convolution, histogram equalisation, filters based on Boolean mathematics, noise reduction, edge detection, geometrical filters, cross-correlation filters and image compression are some examples of the filters that have been studied and successfully implemented in the software application. The software application developed during the research is customized in order to meet the requirements of the industrial partner. The application is able to analyze pictures, perform the filtering, build libraries, process images and generate log files. It incorporates most of the filters studied and together with the illumination system and the camera it provides a fully integrated framework able to analyze defects on printed circuit boards.

Estimation of nonparametric probability density functions with applications to automatic speech recognition

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2007

Precipitation of barium sulfate in a semi-batch stirred tank reactor : influence of feeding policy on particle size and morphology

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2012

Multimodal automatic user disposition recognition in human-machine interaction

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2013

Non root feeding with two sources of zinc on Coffea arábica L. 'mundo novo'(B.Rodr.) Choussy

A trial was carried out on an eight old coffee plantation with visible zinc problems. The plantation was situated nearly the city of Jaú (22º30'S, 48º30'W). State of São Paulo, Brazil. The soil is classified as medium texture Oxisol of low base saturation (Latossol Vermelho Amarelo - fase arenosa). The pulverization program started in november 1977, followed in march and July 1978 (heavy harvest) and ended in march and July 1979 (light harvest). Is should be mentioned that a well reconized characteristic of arábica coffe is its habit of biennial bearing, a very heavy harvest is most often followed by a light load the next year. The following treatments and amounts of chemicals per cova hole (4 trees) were tested in accordance with a random block design: 1. 1 g of zinc (zinc sulphate, 0.5%) 2. 3 g of nitrogen (urea, 1.3%) 3. 1 g of zinc + 3 g of nitrogen (zinc sulphate 0.5% + urea 1.3%) 4. 0.25 g, 0.50 g, 1.00 g, 2.00 g of zinc plus 0.75 g, 1.50 g, 3.00 g and 6.00 of nitrogen (correspondent to NZN* 15-0-0-5 as 0.75%, 1-5%, 3.0% and 6.0% by v/v). Foliar absorption data were obtained by collecting the 3rd and 4th pairs of the coffee leaves and analysed them for N, P, K, Ca, Mg, S, B, Cu, Fe, Mn, and Zn. The main results may be summarized as follows: 1. The maximum calculated yields of clean coffee were obtained by the applications of 5.84 1 of NZN (1.13%) per hectare. 2. The applications of zinc sulphate (0.5%) and urea (1.3%) together or separate did not affected the coffee bean production. 3. The applications of 15.0 1 of NZN per hectare reduced the coffee yields. 4. Leaf damages and burning symptoms were observed by the applications of urea (1.3%) plus zinc sulphate (0.5%) and larger doses than 7.5 1 of NZN per hectare. 5. Leaf tissue analysis show that the concentrations of the elements were affecred by the age of the leaves and by the yields of the coffee trees. 6. The applications of increasing doses of NZN causes an increase in the concentration of zinc, manganese and boron in the leaves and decreased the concentration in calcium and potassium the leaves. 7. The concentration of zinc in the leaves associated with the heavy harvest, in July, was 70.0 ppm.

Diet, feeding behavior, growth, and numbers of a population of Cerberus rynchops (Serpentes: Homalopsinae) in Malaysia / Bruce C. Jayne, Harold K. Voris, Kiew Bong Heang.

n.s. no.50(1988)