Foraging behavior of leaf cutting ants: How do workers search for their food?

Forager ants search for adequate food sources in nature and, after their discovery, decide whether the source is suitable or not for the colony. However, we asked “How do workers seek out the substrate for cultivation of the symbiontic fungus on which they feed? To answer this question, we evaluated the distance traveled by individual workers in the search of food and the distance traveled to return to the nest, as well as the time and velocity necessary for these activities. The results showed that the distance traveled by the leaf cutting ant, Atta sexdens rubropilosa (Linneus, 1758), in the search of food was greater than the distance traveled to return with the substrate to the colony. On the other hand, the mean time and velocity were similar for food search and return to the colony. These results support the hypothesis of information transfer, according to which the worker needs to return to the nest at the beginning of foraging to transfer information to other workers and thus to establish the process of worker ant foraging. It can be concluded that workers travel large distances in a random manner until finding their substrate, but the return to the nest is efficient considering the shorter distance traveled.

Factors Associated with Quality of Life in Patients with Systemic Arterial Hypertension

Background: Hypertensive patients present, in addition to worse cardiovascular health, lower health-related quality of life compared to normotensive subjects. Factors such as functional capacity, functional status, pain, participation in social activities, mental and emotional health, fatigue and energy level, along with perception of general health, seem to be relevant for evaluation in this population. However, evidence is unclear in hypertensive patients. Objective: To analyze the factors associated with quality of life in hypertensive patients. Methods: Forty-five patients were recruited. The dependent variables of the present study are the quality of life domains. Demographic data and clinical conditions were considered independent variables. The Medical Outcomes Short-Form Health Survey (SF-36) questionnaire was used to measure quality of life. Handgrip strength, blood pressure and anthropometric indicators were evaluated. Crude and adjusted linear regression analysis was used. Results: It was verified that education level, body mass index and muscle strength were associated with the functional capacity domain (p < 0,05), whereas systolic blood pressure was associated with the physical domain (p < 0,05). Women presented lower quality of life on the pain domain compared to men and educational level was associated with the social domain (p < 0,05). Conclusion: Hypertensive patients with lower levels of body mass index, higher levels of education and muscle strength presented a better quality of life on the physical domain, while the social aspects presented a positive relationship with education level. Women presented a worse quality of life on the pain domain compared to men

Model and implementation of body movement recognition using Support Vector Machines and Finite State Machines with cartesian coordinates input for gesture-based interaction

The growth in the use of gesture-based interaction in video games has highlighted the potential for the use of such interaction method for a wide range of applications. This paper presents the implementation of an enhanced model for gesture recognition as input method for software applications. The model uses Support Vector Machines (SVM) and Finite State Machines (FSM) and the implementation was based on a Kinect R device. The model uses data input based on Cartesian coordinates. The use of Cartesian coordinates enables more flexibility to generalise the use of the model to different applications, when compared to related work encountered in the literature based on accelerometer devices for data input. The results showed that the use of SVM and FSM with Cartesian coordinates as input for gesture-based interaction is very promising. The success rate in gesture recognition was 98%, from a training corpus of 9 sets obtained by recording real users’ gestures. A proof-of-concept implementation of the gesture recognition interaction was performed using the application Google Earth(R). A preliminary acceptance evaluation with users indicated that the interaction with the system via the implementation reported was satisfactory.Facultad de Informátic