Integration of ROS navigation stack with dynamic environment information in gazebo simulation

Sensing the environment is a crucial task that robots have to perform to navigate autonomously. Furthermore, it must be well executed to make navigation safer and collision- free. As autonomous mobile robots are being deployed in several applications, they often encounter dynamic habitats, where sensing and perceiving the environment becomes harder. This work proposes integrating a wireless sensor network with the Robotic Operating System to incorporate data into layered costmaps used by the robot to navigate, feeding the algorithms with advanced information about the territory. The architecture was tested in simulation, where we could validate the structure and collect data showing improved paths calculated and reduced computational load through better parametrization. Thus, this strategy ensures that the advanced information about the environment has improved the navigation process.The authors are grateful to the Research Centre in Digitalization and Intelligent Robotics (CeDRI) for sharing its facilities and material, and also to the Foundation for Science and Technology (FCT, Portugal) for financial support as mentioned earlier.info:eu-repo/semantics/publishedVersio

Infall models of Class 0 protostars

We have carried out radiative transfer calculations of infalling, dusty envelopes surrounding embedded protostars to understand the observed properties of the recently identified ``Class 0'' sources. To match the far-infrared peaks in the spectral energy distributions of objects such as the prototype Class 0 source VLA 1623, pure collapse models require mass infall rates \sim10^{-4}\msunyr$^{-1}$. The radial intensity distributions predicted by such infall models are inconsistent with observations of VLA 1623 at sub-mm wavelengths, in agreement with the results of Andre et al. (1993) who found a density profile of $\rho \propto r^{-1/2}$ rather than the expected $\rho \propto r^{-3/2}$ gradient. To resolve this conflict, while still invoking infall to produce the outflow source at the center of VLA 1623, we suggest that the observed sub-mm intensity distribution is the sum of two components: an inner infall zone, plus an outer, more nearly constant-density region. This explanation of the observations requires that roughly half the total mass observed within 2000 AU radius of the source lies in a region external to the infall zone. The column densities for this external region are comparable to those found in the larger Oph A cloud within which VLA 1623 is embedded. The extreme environments of Class 0 sources lead us to suggest an alternative or additional interpretation of these objects: rather than simply concluding with Andre et al. that Class 0 objects only represent the earliest phases of protostellar collapse, and ultimately evolve into older ``Class I'' protostars, we suggest that many Class 0 sources could be the protostars of very dense regions. (Shortened)Comment: 22 pages, including 3 PostScript figures, accepted for publication in The Astrophysical Journa

Implementation of boolean neural networks on parallel computers

This paper analyses the parallel implementation using networks of transputers of a neural structure belonging to a particular class of neural architectures known as GSN neural networks. These architectures, belonging to the general clasa of RAM-based networks and composed 01 digitally specified processing nodes, have been implemented using different processing topologies, and performance in relatíon to both training and testing efficiency in a practical pattern recognition task has been evaluated.Eje: Redes Neuronales. Algoritmos genéticosRed de Universidades con Carreras en Informática (RedUNCI

Human-machine interfaces based on EMG and EEG applied to robotic systems

<p>Abstract</p> <p>Background</p> <p>Two different Human-Machine Interfaces (HMIs) were developed, both based on electro-biological signals. One is based on the EMG signal and the other is based on the EEG signal. Two major features of such interfaces are their relatively simple data acquisition and processing systems, which need just a few hardware and software resources, so that they are, computationally and financially speaking, low cost solutions. Both interfaces were applied to robotic systems, and their performances are analyzed here. The EMG-based HMI was tested in a mobile robot, while the EEG-based HMI was tested in a mobile robot and a robotic manipulator as well.</p> <p>Results</p> <p>Experiments using the EMG-based HMI were carried out by eight individuals, who were asked to accomplish ten eye blinks with each eye, in order to test the eye blink detection algorithm. An average rightness rate of about 95% reached by individuals with the ability to blink both eyes allowed to conclude that the system could be used to command devices. Experiments with EEG consisted of inviting 25 people (some of them had suffered cases of meningitis and epilepsy) to test the system. All of them managed to deal with the HMI in only one training session. Most of them learnt how to use such HMI in less than 15 minutes. The minimum and maximum training times observed were 3 and 50 minutes, respectively.</p> <p>Conclusion</p> <p>Such works are the initial parts of a system to help people with neuromotor diseases, including those with severe dysfunctions. The next steps are to convert a commercial wheelchair in an autonomous mobile vehicle; to implement the HMI onboard the autonomous wheelchair thus obtained to assist people with motor diseases, and to explore the potentiality of EEG signals, making the EEG-based HMI more robust and faster, aiming at using it to help individuals with severe motor dysfunctions.</p

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

Background: Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion: We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions: We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters

Egg components and offspring survival vary with group size and laying order in a cooperative breeder

Prenatal resource allocation to offspring can be influenced by maternal environment and offspring value, and affect offspring survival. An important pathway for flexible maternal allocation is via egg components such as nutrients and hormones. In cooperative breeders, females with helpers may increase resource allocation to eggs-'differential allocation'-or reduce it-'load-lightening'. Yet, helper effects on egg composition have been poorly studied. Moreover, it is unknown how helpers' presence modulates laying order effects on egg content and survival. Here, we investigated how maternal allocation varied with group size and laying order in the cooperatively breeding sociable weaver (Philetairus socius). We estimated interactive effects of helpers and laying order on allocation to egg mass, yolk nutrients-yolk mass, proteins, lipids, carotenoids, vitamin A and vitamin E-and hormones-testosterone, androstenedione, and corticosterone. Results concurred with the 'differential allocation' predictions. Females with more helpers produced later-laid eggs with heavier yolks and more lipids, and laid eggs overall richer in lipids. Proteins, antioxidants, and hormones were not found to vary with helper number. We then analyzed how helper number modulated laying order effects on survival. Females with more helpers did not specifically produce later-laid eggs with higher survival, but eggs laid by females with more helpers were overall more likely to fledge. These findings show that some egg components (yolk mass, lipids) can positively vary according to females' breeding group size, which may improve offspring fitness

Implementation of boolean neural networks on parallel computers

This paper analyses the parallel implementation using networks of transputers of a neural structure belonging to a particular class of neural architectures known as GSN neural networks. These architectures, belonging to the general clasa of RAM-based networks and composed 01 digitally specified processing nodes, have been implemented using different processing topologies, and performance in relatíon to both training and testing efficiency in a practical pattern recognition task has been evaluated.Eje: Redes Neuronales. Algoritmos genéticosRed de Universidades con Carreras en Informática (RedUNCI

O exercício de força muscular é eficiente para melhorar o desempenho no teste \ud de caminhada de 6 minutos em mulheres pós-menopausais?

Background: Walking speed seems to be related to aerobic capacity, lower limb strength, and functional mobility, however it is not clear whether there is a direct relationship between improvement in muscle strength and gait performance in early postmenopausal women. Objective: To evaluate the effect of muscle strengthening exercises on the performance of the 6-minute walk test in women within 5 years of menopause. Methods: The women were randomized into control group (n=31), which performed no exercise, and exercise group (n=27), which performed muscle strengthening exercises. The exercises were performed twice a week for 3 months. The exercise protocol consisted of warm-up, stretching, and strengthening of the quadriceps, hamstring, calf, tibialis anterior, gluteus maximus, and abdominal muscles, followed by relaxation. Muscular strength training started with 60% of 1MR (2 series of 10-15 repetitions), reaching 85% until the end of the 3-month period (4 series of 6 repetitions each). Results: The between-group comparisons pre- and post-intervention did not show any difference in distance walked, heart rate or blood pressure (p&gt;0.05), but showed differences in muscle strength post-intervention, with the exercise group showing greater strength (p&lt;0.05). In the within-group comparison, there were differences in final heart rate and quadriceps and hamstring strength pre- and post-intervention in the exercise group (p&lt;0.05). Conclusion: The results suggest that muscle strengthening of the lower limbs did not improve performance in the 6-minute walk test in this population of postmenopausal women. Trial registration ACTRN12609001053213.Bioengineering Unit of the School of Medicine of Ribeirao Preto, USPBioengineering Unit of the School of Medicine of Ribeirao Preto, USPFundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Sao Paulo, SP, BrazilFundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Sao Paulo, SP, Brazil [2007/54596-0, 2007/07606-0]Financiador de Estudos e Projetos (FINEP), Ribeirao Preto, SP, Brazil [1230/2005]Financiador de Estudos e Projetos (FINEP), Ribeirao Preto, SP, Brazi

Conhecer melhor a nossa biodiversidade: o Atlas de Mamíferos de Portugal

The Atlas of Mammals of Portugal compiles the most up-to-date and finest-resolution distribution database of Portuguese terrestrial and marine mammals (except bats) across the country (mainland and islands) and its Exclusive Economic Zone. The inclusion of marine mammals, which are often left out of mammal atlases, is of particular relevance in this work, especially given the large extent of the Exclusive Economic Zone of Portugal, which covers a substantial portion of the Eastern North Atlantic. This atlas was developed as part of a research project on vertebrate biogeography in the Iberian Peninsula and Western Europe, and it resulted from a combination of efforts of numerous individuals and entities. Its preparation consisted in the compilation of an unprecedented volume of mammal occurrence records in our country, whose subsequent selection was based on rigorous methods and validation procedures, according to international standards. In this article, we present a brief description of the background that motivated the elaboration of this atlas, the methodology used, the main results of this work, and its limitations. The Atlas of Mammals of Portugal has great potential to become an essential tool for better evaluation of the conservation status of mammal species in Portugal and, consequently, for improving their conservation and management in this country. We also make a call for additional contributions of mammal occurrence data, which can be included in subsequent editions of the Atlas