Staphylococcus sp na produção primária de leite: aspectos de saúde pública

Staphylococcus is one of the more important causes of the called Foodborne Disease(FD), being that from the 40 species described from genus, the more important is Staphylococcus aureus. During years believed that the S. aureus was the only specie from genus able to produce enterotoxins, responsable for the clinical frame in humans, but latest studies report the isolation of other species both positive coagulase (PC) as negative with enterotoxigenic potential. The symptoms of this intoxication appear after a short period of incubation (2-6 hours) and usually characterized by nausea, vomits, abdominal ache, diarrhea, and rarely is fatal. For the toxin to be formed in food is necessary that bacteria population to be at least 105 UFC/g, being that such toxins characterized by presenting great resistance front of gastrointestinal proteases and of homemade termical treatment. Among the main foods that might carry the microorganism, the milk and its derivatives have highlights. The contamination of the product might happen as from the milk from cows with clinical and/or subclinical mastitis, as the Staphylococcus genus is one of the main agents etiologic from this disease, equipments utensils badly sanitized equipments and utensils and from the manipulators. The control of these factors configures as fundamental condition for the achievement of a safe, quality product, which doesn’t offer risk to the consumers

Desenvolvimento de um sistema para navegação de robôs móveis por caminhos em plantações

The use of mobile robots in the agriculture turns out to be interesting in tasks of cultivation and application of pesticides in minute quantities to reduce environmental pollution. In this paper we present the development of a system to control an autonomous mobile robot navigation through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features, and then submitting such characteristic features to a support vector machine to find out the most appropriate route. As the overall goal of the project to which this work is connected is the robot control in real time, the system will be embedded onto a hardware platform. However, in this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route.

Atividades com robótica educacional para as aulas de matemática do 6. ao 9. ano do ensino fundamental: utilização da metodologia LEGO® Zoom Education

Pós-graduação em Matemática - IBILCE

Um modelo cognitivo baseado na atenção para consciência em robôs inteligentes

Understanding consciousness is one of the most fascinating challenges of our time. From ancient civilizations to modern philosophers, questions have been asked on how one is conscious of his/her own existence and about the world that surrounds him/her. Although there is no precise definition for consciousness, there is an agreement that it is strongly related to human cognitive processes such as: thinking, reasoning, emotions, wishes. One of the key processes to the arising of the consciousness is the attention, a process capable of promoting a selection of a few stimuli from a huge amount of information that reaches us constantly. Machine consciousness is the field of the artificial intelligence that investigate the possibility of the production of conscious processes in artificial devices. This work presents a review about the theme of consciousness - in both natural and artificial aspects -, discussing this theme from the philosophical and computational perspectives, and investigates the feasibility of the adoption of an attentional schema as the base to the cognitive processing. A formal computational model is proposed for conscious agents that integrates: short and long term memories, reasoning, planning, emotion, decision making, learning, motivation and volition. Computer experiments in a mobile robotics domain under USARSim simulation environment, proposed by RoboCup, suggest that the agent can be able to use these elements to acquire experiences based on environment stimuli. The adoption of the cognitive architecture over the attentional model has potential to allow the emergence of behaviours usually associated to the consciousness in the simulated mobile robots. Further implementation under this model could potentially allow the agent to express sentience, selfawareness, self-consciousness, autonoetic consciousness, mineness and perspectivalness. By performing computation over an attentional space, the model also allows the ...

Análise da pressão intra-abdominal em pacientes submetidos à cirurgia abdominal oncológica internados em Unidade de Terapia Intensiva

Pós-graduação em Pesquisa e Desenvolvimento (Biotecnologia Médica) - FMB

Mapeamento da cinemática inversa de um manipulador robótico utilizando redes neurais artificiais configuradas em paralelo

Pós-graduação em Engenharia Elétrica - FEIS

On Modular Design of Field Robotic Systems

Robots are needed to perform important field tasks such as hazardous material clean-up, nuclear site inspection, and space exploration. Unfortunately their use is not widespread due to their long development times and high costs. To make them practical, a modular design approach is proposed. Prefabricated modules are rapidly assembled to give a low-cost system for a specific task. This paper described the modular design problem for field robots and the application of a hierarchical selection process to solve this problem. Theoretical analysis and an example case study are presented. The theoretical analysis of the modular design problem revealed the large size of the search space. It showed the advantages of approaching the design on various levels. The hierarchical selection process applies physical rules to reduce the search space to a computationally feasible size and a genetic algorithm performs the final search in a greatly reduced space. This process is based on the observation that simple physically based rules can eliminate large sections of the design space to greatly simplify the search. The design process is applied to a duct inspection task. Five candidate robots were developed. Two of these robots are evaluated using detailed physical simulation. It is shown that the more obvious solution is not able to complete the task, while the non-obvious asymmetric design develop by the process is successful.

Is Competition Making a Comeback? Discovering Methods to Keep Female Adolescents Engaged in STEM: A Phenomenological Approach

The decreasing number of women who are graduating in the Science, Technology, Engineering and Mathematics (STEM) fields continues to be a major concern. Despite national support in the form of grants provided by National Science Foundation, National Center for Information and Technology and legislation passed such as the Deficit Reduction Act of 2005 that encourages women to enter the STEM fields, the number of women actually graduating in these fields is surprisingly low. This research study focuses on a robotics competition and its ability to engage female adolescents in STEM curricula. Data have been collected to help explain why young women are reticent to take technology or engineering type courses in high school and college. Factors that have been described include attitudes, parental support, social aspects, peer pressure, and lack of role models. Often these courses were thought to have masculine and “nerdy” overtones. The courses were usually majority male enrollments and appeared to be very competitive. With more female adolescents engaging in this type of competitive atmosphere, this study gathered information to discover what about the competition appealed to these young women. Focus groups were used to gather information from adolescent females who were participating in the First Lego League (FLL) and CEENBoT competitions. What enticed them to participate in a curriculum that data demonstrated many of their peers avoided? FLL and CEENBoT are robotics programs based on curricula that are taught in afterschool programs in non-formal environments. These programs culminate in a very large robotics competition. My research questions included: What are the factors that encouraged participants to participate in the robotics competition? What was the original enticement to the FLL and CEENBoT programs? What will make participants want to come back and what are the participants’ plans for the future? My research mirrored data of previous findings such as lack of role models, the need for parental support, social stigmatisms and peer pressure are still major factors that determine whether adolescent females seek out STEM activities. An interesting finding, which was an exception to previous findings, was these female adolescents enjoyed the challenge of the competition. The informal learning environments encouraged an atmosphere of social engagement and cooperative learning. Many volunteers that led the afterschool programs were women (role models) and a majority of parents showed support by accommodating an afterschool situation. The young women that were engaged in the competition noted it was a friendly competition, but they were all there to win. All who participated in the competition had a similar learning environment: competitive but cooperative. Further research is needed to determine if it is the learning environment that lures adolescent females to the program and entices them to continue in the STEM fields or if it is the competitive aspect of the culminating activity. Advisors: James King and Allen Steckelberg

In-Flight Collision Avoidance Controller Based Only on OS4 Embedded Sensors

The major goal of this research was the development and implementation of a control system able to avoid collisions during the flight for a mini-quadrotor helicopter, based only on its embedded sensors without changing the environment. However, it is important to highlight that the design aspects must be seriously considered in order to overcome hardware limitations and achieve control simplification. The controllers of a UAV (Unmanned Aerial Vehicle) robot deal with highly unstable dynamics and strong axes coupling. Furthermore, any additional embedded sensor increases the robot total weight and therefore, decreases its operating time. The best balance between embedded electronics and robot operating time is desired. This paper focuses not only on the development and implementation of a collision avoidance controller for a mini-robotic helicopter using only its embedded sensors, but also on the mathematical model that was essential for the controller developing phases. Based on this model we carried out the development of a simulation tool based on MatLab/Simulink that was fundamental for setting the controllers' parameters. This tool allowed us to simulate and improve the OS4 controllers in different modeled environments and test different approaches. After that, the controllers were embedded in the real robot and the results proved to be very robust and feasible. In addition to this, the controller has the advantage of being compatible with future path planners that we are developing.

Development of an Autonomous Robot for Gas Storage Spheres Inspection

Inspection for corrosion of gas storage spheres at the welding seam lines must be done periodically. Until now this inspection is being done manually and has a high cost associated to it and a high risk of inspection personel injuries. The Brazilian Petroleum Company, Petrobras, is seeking cost reduction and personel safety by the use of autonomous robot technology. This paper presents the development of a robot capable of autonomously follow a welding line and transporting corrosion measurement sensors. The robot uses a pair of sensors each composed of a laser source and a video camera that allows the estimation of the center of the welding line. The mechanical robot uses four magnetic wheels to adhere to the sphere's surface and was constructed in a way that always three wheels are in contact with the sphere's metallic surface which guarantees enough magnetic atraction to hold the robot in the sphere's surface all the time. Additionally, an independently actuated table for attaching the corrosion inspection sensors was included for small position corrections. Tests were conducted at the laboratory and in a real sphere showing the validity of the proposed approach and implementation.

Modeling and Identification of an Open-frame Underwater Vehicle: The Yaw Motion Dynamics

A semi-autonomous unmanned underwater vehicle (UUV), named LAURS, is being developed at the Laboratory of Sensors and Actuators at the University of Sao Paulo. The vehicle has been designed to provide inspection and intervention capabilities in specific missions of deep water oil fields. In this work, a method of modeling and identification of yaw motion dynamic system model of an open-frame underwater vehicle is presented. Using an on-board low cost magnetic compass sensor the method is based on the utilization of an uncoupled 1-DOF (degree of freedom) dynamic system equation and the application of the integral method which is the classical least squares algorithm applied to the integral form of the dynamic system equations. Experimental trials with the actual vehicle have been performed in a test tank and diving pool. During these experiments, thrusters responsible for yaw motion are driven by sinusoidal voltage signal profiles. An assessment of the feasibility of the method reveals that estimated dynamic system models are more reliable when considering slow and small sinusoidal voltage signal profiles, i.e. with larger periods and with relatively small amplitude and offset.

Modelling shared attention through relational reinforcement learning

Shared attention is a type of communication very important among human beings. It is sometimes reserved for the more complex form of communication being constituted by a sequence of four steps: mutual gaze, gaze following, imperative pointing and declarative pointing. Some approaches have been proposed in Human-Robot Interaction area to solve part of shared attention process, that is, the most of works proposed try to solve the first two steps. Models based on temporal difference, neural networks, probabilistic and reinforcement learning are methods used in several works. In this article, we are presenting a robotic architecture that provides a robot or agent, the capacity of learning mutual gaze, gaze following and declarative pointing using a robotic head interacting with a caregiver. Three learning methods have been incorporated to this architecture and a comparison of their performance has been done to find the most adequate to be used in real experiment. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human in a controlled environment. The experimental results show that the robotic head is able to produce appropriate behavior and to learn from sociable interaction.

Detection of gait perturbations based on proprioceptive information. Application to Limit Cycle Walkers

Walking on irregular surfaces and in the presence of unexpected events is a challenging problem for bipedal machines. Up to date, their ability to cope with gait disturbances is far less successful than humans': Neither trajectory controlled robots, nor dynamic walking machines (Limit CycleWalkers) are able to handle them satisfactorily. On the contrary, humans reject gait perturbations naturally and efficiently relying on their sensory organs that, if needed, elicit a recovery action. A similar approach may be envisioned for bipedal robots and exoskeletons: An algorithm continuously observes the state of the walker and, if an unexpected event happens, triggers an adequate reaction. This paper presents a monitoring algorithm that provides immediate detection of any type of perturbation based solely on a phase representation of the normal walking of the robot. The proposed method was evaluated in a Limit Cycle Walker prototype that suffered push and trip perturbations at different moments of the gait cycle, providing 100% successful detections for the current experimental apparatus and adequately tuned parameters, with no false positives when the robot is walking unperturbed.

Robotic-assisted laparoscopic partial nephrectomy: initial experience in Brazil and a review of the literature

CONTEXT AND PURPOSE: Partial nephrectomy has become the standard of care for renal tumors less than 4 cm in diameter. Controversy still exists, however, regarding the best surgical approach, especially when minimally invasive techniques are taken into account. Robotic-assisted laparoscopic partial nephrectomy (RALPN) has emerged as a promising technique that helps surgeons achieve the standards of open partial nephrectomy care while offering a minimally invasive approach. The objective of the present study was to describe our initial experience with robotic-assisted laparoscopic partial nephrectomy and extensively review the pertinent literature. MATERIALS AND METHODS: Between August 2009 and February 2010, eight consecutive selected patients with contrast enhancing renal masses observed by CT were submitted to RALPN in a private institution. In addition, we collected information on the patients' demographics, preoperative tumor characteristics and detailed operative, postoperative and pathological data. In addition, a PubMed search was performed to provide an extensive review of the robotic-assisted laparoscopic partial nephrectomy literature. RESULTS: Seven patients had RALPN on the left or right sides with no intraoperative complications. One patient was electively converted to a robotic-assisted radical nephrectomy. The operative time ranged from 120 to 300 min, estimated blood loss (EBL) ranged from 75 to 400 mL and, in five cases, the warm ischemia time (WIT) ranged from 18 to 32 min. Two patients did not require any clamping. Overall, no transfusions were necessary, and there were no intraoperative complications or adverse postoperative clinical events. All margins were negative, and all patients were disease-free at the 6-month follow-up. CONCLUSIONS: Robotic-assisted laparoscopic partial nephrectomy is a feasible and safe approach to small renal cortical masses.Further prospective studies are needed to compare open partial nephrectomy with its minimally invasive counterparts.

Reasoning about shadows in a mobile robot environment

This paper describes a logic-based formalism for qualitative spatial reasoning with cast shadows (Perceptual Qualitative Relations on Shadows, or PQRS) and presents results of a mobile robot qualitative self-localisation experiment using this formalism. Shadow detection was accomplished by mapping the images from the robot’s monocular colour camera into a HSV colour space and then thresholding on the V dimension. We present results of selflocalisation using two methods for obtaining the threshold automatically: in one method the images are segmented according to their grey-scale histograms, in the other, the threshold is set according to a prediction about the robot’s location, based upon a qualitative spatial reasoning theory about shadows. This theory-driven threshold search and the qualitative self-localisation procedure are the main contributions of the present research. To the best of our knowledge this is the first work that uses qualitative spatial representations both to perform robot self-localisation and to calibrate a robot’s interpretation of its perceptual input.