Knowledge acquisition by networks of interacting agents in the presence of observation errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erdos-Renyi or Barabasi-Albert type. First, we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall performance of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.

ScriptLattes: an open-source knowledge extraction system from the Lattes platform

The Lattes platform is the major scientific information system maintained by the National Council for Scientific and Technological Development (CNPq). This platform allows to manage the curricular information of researchers and institutions working in Brazil based on the so called Lattes Curriculum. However, the public information is individually available for each researcher, not providing the automatic creation of reports of several scientific productions for research groups. It is thus difficult to extract and to summarize useful knowledge for medium to large size groups of researchers. This paper describes the design, implementation and experiences with scriptLattes: an open-source system to create academic reports of groups based on curricula of the Lattes Database. The scriptLattes system is composed by the following modules: (a) data selection, (b) data preprocessing, (c) redundancy treatment, (d) collaboration graph generation among group members, (e) research map generation based on geographical information, and (f) automatic report creation of bibliographical, technical and artistic production, and academic supervisions. The system has been extensively tested for a large variety of research groups of Brazilian institutions, and the generated reports have shown an alternative to easily extract knowledge from data in the context of Lattes platform. The source code, usage instructions and examples are available at http://scriptlattes.sourceforge.net/.

Upgrading a TCABR data analysis and acquisition system for remote participation using Java, XML, RCP and modern client/server communication/authentication

The TCABR data analysis and acquisition system has been upgraded to support a joint research programme using remote participation technologies. The architecture of the new system uses Java language as programming environment. Since application parameters and hardware in a joint experiment are complex with a large variability of components, requirements and specification solutions need to be flexible and modular, independent from operating system and computer architecture. To describe and organize the information on all the components and the connections among them, systems are developed using the extensible Markup Language (XML) technology. The communication between clients and servers uses remote procedure call (RPC) based on the XML (RPC-XML technology). The integration among Java language, XML and RPC-XML technologies allows to develop easily a standard data and communication access layer between users and laboratories using common software libraries and Web application. The libraries allow data retrieval using the same methods for all user laboratories in the joint collaboration, and the Web application allows a simple graphical user interface (GUI) access. The TCABR tokamak team in collaboration with the IPFN (Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa) is implementing this remote participation technologies. The first version was tested at the Joint Experiment on TCABR (TCABRJE), a Host Laboratory Experiment, organized in cooperation with the IAEA (International Atomic Energy Agency) in the framework of the IAEA Coordinated Research Project (CRP) on ""Joint Research Using Small Tokamaks"". (C) 2010 Elsevier B.V. All rights reserved.

Characterization of micro-bubble size distribution and flow configuration in DAF contact zone by a non-intrusive image analysis system and tracer tests

This paper aims to investigate the influence of some dissolved air flotation (DAF) process variables (specifically: the hydraulic detention time in the contact zone and the supplied dissolved air concentration) and the pH values, as pretreatment chemical variables, on the micro-bubble size distribution (BSD) in a DAF contact zone. This work was carried out in a pilot plant where bubbles were measured by an appropriate non-intrusive image acquisition system. The results show that the obtained diameter ranges were in agreement with values reported in the literature (10-100mm), quite independently of the investigated conditions. The linear average diameter varied from 20 to 30mm, or equivalently, the Sauter (d(3,2)) diameter varied from 40 to 50mm. In all investigated conditions, D(50) was between 75% and 95%. The BSD might present different profile (with a bimodal curve trend), however, when analyzing the volumetric frequency distribution (in some cases with the appearance of peaks in diameters ranging from 90-100mm). Regarding volumetric frequency analysis, all the investigated parameters can modify the BSD in DAF contact zone after the release point, thus potentially causing changes in DAF kinetics. This finding prompts further research in order to verify the effect of these BSD changes on solid particle removal efficiency by DAF.

Mock circulatory system for the evaluation of left ventricular assist devices, endoluminal prostheses, and vascular diseases

A new digital computer mock circulatory system has been developed in order to replicate the physiologic and pathophysiologic characteristics of the human cardiovascular system. The computer performs the acquisition of pressure, flow, and temperature in an open loop system. A computer program has been developed in Labview programing environment to evaluate all these physical parameters. The acquisition system was composed of pressure, flow, and temperature sensors and also signal conditioning modules. In this study, some results of flow, cardiac frequencies, pressures, and temperature were evaluated according to physiologic ventricular states. The results were compared with literature data. In further works, performance investigations will be conducted on a ventricular assist device and endoprosthesis. Also, this device should allow for evaluation of several kinds of vascular diseases.

The Schenberg data acquisition and analysis: results from its first commissioning run

The Mario Schenberg gravitational wave detector has started its commissioning phase at the Physics Institute of the University of Sao Paulo. We have collected almost 200 h of data from the instrument in order to check out its behavior and performance. We have also been developing a data acquisition system for it under a VXI System. Such a system is composed of an analog-to-digital converter and a GPS receiver for time synchronization. We have been building the software that controls and sets up the data acquisition. Here we present an overview of the Mario Schenberg detector and its data acquisition system, some results from the first commissioning run and solutions for some problems we have identified.

Inteligência artificial aplicada à Zootecnia

Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

Simvastatin-induced cardiac autonomic control improvement in fructose-fed female rats

OBJECTIVE: Because autonomic dysfunction has been found to lead to cardiometabolic disorders and because studies have reported that simvastatin treatment has neuroprotective effects, the objective of the present study was to investigate the effects of simvastatin treatment on cardiovascular and autonomic changes in fructose-fed female rats. METHODS: Female Wistar rats were divided into three groups: controls (n=8), fructose (n=8), and fructose+ simvastatin (n=8). Fructose overload was induced by supplementing the drinking water with fructose (100 mg/L, 18 wks). Simvastatin treatment (5 mg/kg/day for 2 wks) was performed by gavage. The arterial pressure was recorded using a data acquisition system. Autonomic control was evaluated by pharmacological blockade. RESULTS: Fructose overload induced an increase in the fasting blood glucose and triglyceride levels and insulin resistance. The constant rate of glucose disappearance during the insulin intolerance test was reduced in the fructose group (3.4+ 0.32%/min) relative to that in the control group (4.4+ 0.29%/min). Fructose+simvastatin rats exhibited increased insulin sensitivity (5.4+0.66%/min). The fructose and fructose+simvastatin groups demonstrated an increase in the mean arterial pressure compared with controls rats (fructose: 124+2 mmHg and fructose+simvastatin: 126 + 3 mmHg vs. controls: 112 + 2 mmHg). The sympathetic effect was enhanced in the fructose group (73 + 7 bpm) compared with that in the control (48 + 7 bpm) and fructose+simvastatin groups (31+8 bpm). The vagal effect was increased in fructose+simvastatin animals (84 + 7 bpm) compared with that in control (49 + 9 bpm) and fructose animals (46+5 bpm). CONCLUSION: Simvastatin treatment improved insulin sensitivity and cardiac autonomic control in an experimental model of metabolic syndrome in female rats. These effects were independent of the improvements in the classical plasma lipid profile and of reductions in arterial pressure. These results support the hypothesis that statins reduce the cardiometabolic risk in females with metabolic syndrome.

Desenvolvimento de conceitos em cegos congênitos: caminhos de aquisição do conhecimento

O objetivo deste trabalho foi estudar o desenvolvimento de conceitos por cegos congênitos. Participaram sete cegos congênitos, de ambos os sexos, com idades entre 8 e 13 anos. Foi solicitado aos participantes que definissem 15 conceitos, subdivididos em concretos e abstratos. As respostas foram agrupadas em 13 categorias. Verificou-se que cada tipo de conceito envolve formas diferenciadas de definição e de utilização de recursos perceptivos. Foram identificados alguns meios utilizados pelo cego congênito na aquisição do conhecimento, evidenciando a multiplicidade de possibilidades de aquisição e expressão de conceitos. As implicações deste trabalho para o processo de ensino/aprendizagem de cegos foram consideradas.

O aluno cego: preconceitos e potencialidades

Este artigo analisa a cegueira, os preconceitos a ela associados e as potencialidades de pessoas cegas, especialmente do aluno cego. Salienta a ênfase dada ao sentido da visão no processo de aquisição de conhecimentos e considera os preconceitos comumente associados à capacidade de aprendizagem do cego.

Benefits of exercise training in diabetic rats persist after three weeks of detraining

Regarding all benefits of exercise training, a question remains: how long are these benefits kept? This study evaluated the effect of 3-week detraining after 10 weeks of training in STZ-diabetic rats. Male Wistar rats were assigned into: sedentary controls, trained controls, trained-detrained controls. sedentary diabetic, trained diabetic and trained-detrained diabetic. Arterial pressure (AP) and heart rate (HR) were recorded by a data acquisition system. Baroreflex sensitivity (BRS) was evaluated by HR responses to AP changes induced by infusion of vasoactive drugs. Intrinsic heart rate (IHR), sympathetic tonus (ST) and vagal tonus (VT) were evaluated by pharmacological blockade with atenolol and atropine. Spectral analysis of systolic AP and HR variabilities (HRV) was performed to estimate autonomic modulation to the heart and vessels. Diabetes cardiovascular and autonomic dysfunctions were reversed by exercise training and partially maintained in the 3-week detraining period. In controls, training decreased AP and HR and improved BRS. changes that returned to baseline values after detraining. IHR and VT were improved in trained diabetic rats and remained in detrained diabetic ones. LF component of HRV decreased in trained control group. In diabetics. exercise training improved variance, and absolute LF and HF components of HRV. Only HF was maintained in detrained diabetic group. Moreover, there was an inverse relationship between plasma glucose and the absolute HF component of HRV. These changes probably determined the different survival rate of 80% in diabetic detrained and 51% in diabetic sedentary rats. (c) 2008 Elsevier B.V. All rights reserved.

Quality control of blood irradiation with a teletherapy unit: damage to stored red blood cells after cobalt-60 gamma irradiation

BACKGROUND: Previous publications have documented the damage caused to red blood cells (RBCs) irradiated with X-rays produced by a linear accelerator and with gamma rays derived from a Cs-137 source. The biologic effects on RBCs of gamma rays from a Co-60 source, however, have not been characterized. STUDY DESIGN AND METHODS: This study investigated the effect of 3000 and 4000 cGy on the in vitro properties of RBCs preserved with preservative solution and irradiated with a cobalt teletherapy unit. A thermal device equipped with a data acquisition system was used to maintain and monitor the blood temperature during irradiation. The device was rotated at 2 r.p.m. in the irradiation beam by means of an automated system. The spatial distribution of the absorbed dose over the irradiated volume was obtained with phantom and thermoluminescent dosimeters (TLDs). Levels of Hb, K+, and Cl- were assessed by spectrophotometric techniques over a period of 45 days. The change in the topology of the RBC membrane was investigated by flow cytometry. RESULTS: Irradiation caused significant changes in the extracellular levels of K+ and Hb and in the organizational structure of the phospholipid bilayer of the RBC membrane. Blood temperature ranged from 2 to 4 degrees C during irradiation. Rotation at 2 r.p.m. distributed the dose homogeneously (92%-104%) and did not damage the RBCs. CONCLUSIONS: The method used to store the blood bags during irradiation guaranteed that all damage caused to the cells was exclusively due to the action of radiation at the doses applied. It was demonstrated that prolonged storage of Co-60-irradiated RBCs results in loss of membrane phospholipids asymmetry, exposing phosphatidylserine (PS) on the cells` surface with a time and dose dependence, which can reduce the in vivo recovery of these cells. A time- and dose-dependence effect on the extracellular K+ and plasma-free Hb levels was also observed. The magnitude of all these effects, however, seems not to be clinically important and can support the storage of irradiated RBC units for at last 28 days.

The oscillatory bioelectrical signal from plants explained by a simulated electrical model and tested using Lempel-Ziv complexity

This paper demonstrates the oscillatory characteristics of electrical signals acquired from two ornamental plant types (Epipremnum pinnatum and Philodendron scandens - Family Araceae), using a noninvasive acquisition system. The electrical signal was recorded using Ag/AgCl superficial electrodes inside a Faraday cage. The presence of the oscillatory electric generator was shown using a classical power spectral density. The Lempel and Ziv complexity measurement showed that the plant signal was not noise despite its nonlinear behavior. The oscillatory characteristics of the signal were explained using a simulated electrical model that establishes that for a frequency range from 5 to 15 Hz, the oscillatory characteristic is higher than for other frequency ranges. All results show that non-invasive electrical plant signals can be acquired with improvement of signal-to-noise ratio using a Faraday cage, and a simple electrical model is able to explain the electrical signal being generated. (C) 2010 Elsevier B.V. All rights reserved.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.