Sensor Adaptation and Development in Robots by Entropy Maximization of Sensory Data

A method is presented for adapting the sensors of a robot to the statistical structure of its current environment. This enables the robot to compress incoming sensory information and to find informational relationships between sensors. The method is applied to creating sensoritopic maps of the informational relationships of the sensors of a developing robot, where the informational distance between sensors is computed using information theory and adaptive binning. The adaptive binning method constantly estimates the probability distribution of the latest inputs to maximize the entropy in each individual sensor, while conserving the correlations between different sensors. Results from simulations and robotic experiments with visual sensors show how adaptive binning of the sensory data helps the system to discover structure not found by ordinary binning. This enables the developing perceptual system of the robot to be more adapted to the particular embodiment of the robot and the environment

Discovering Motion Flow by Temporal-Informational Correlations in Sensors

A method is presented for adapting the sensors of a robot to its current environment and to learn motion flow detection by observing the informational relations between sensors and actuators. Examples are shown where the robot learns to detect motion flow from sensor data generated by its own movement

Sequential sampling of junction trees for decomposable graphs

The junction-tree representation provides an attractive structural property for organizing a decomposable graph. In this study, we present a novel stochastic algorithm, which we call the junction-tree expander, for sequential sampling of junction trees for decomposable graphs. We show that recursive application of the junction-tree expander, expanding incrementally the underlying graph with one vertex at a time, has full support on the space of junction trees with any given number of underlying vertices. A direct application of our suggested algorithm is demonstrated in a sequential Monte Carlo setting designed for sampling from distributions on spaces of decomposable graphs, where the junction-tree expander can be effectively employed as proposal kernel; see the companion paper Olsson et al. 2019 [16]. A numerical study illustrates the utility of our approach by two examples: in the first one, how the junction-tree expander can be incorporated successfully into a particle Gibbs sampler for Bayesian structure learning in decomposable graphical models; in the second one, we provide an unbiased estimator of the number of decomposable graphs for a given number of vertices. All the methods proposed in the paper are implemented in the Python library trilearn.Comment: 31 pages, 7 figure

B747/JT9D flight loads and their effect on engine running clearances and performance deterioration; BCAC NAIL/P and WA JT9D engine diagnostics programs

Flight loads on the 747 propulsion system and resulting JT9D blade to outer airseal running clearances during representative acceptance flight and revenue flight sequences were measured. The resulting rub induced clearance changes, and engine performance changes were then analyzed to validate and refine the JT9D-7A short term performance deterioration model

Designing transformative spaces for sustainability in social-ecological systems

Transformations toward sustainability have recently gained traction, triggered in part by a growing recognition of the dramatic socio-cultural, political, economic, and technological changes required to move societies toward more desirable futures in the Anthropocene. However, there is a dearth of literature that emphasizes the crucial aspects of sustainability transformations in the diverse contexts of the Global South. Contributors to this Special Feature aim to address this gap by weaving together a series of case studies that together form an important navigational tool on the “how to” as well as the “what” and the “where to” of sustainability transformations across diverse challenges, sectors, and geographies. They propose the term “transformative space” as a “safe-enough” collaborative process whereby actors invested in sustainability transformations can experiment with new mental models, ideas, and practices that can help shift social-ecological systems onto more desirable pathways. The authors also highlight the challenges posed to researchers as they become “transformative space-makers,” navigating the power dynamics inherent in these processes. Because researchers and practitioners alike are challenged to provide answers to complex and often ambiguous or incomplete questions around sustainability, the ideas, reflections and learning gathered in this Special Feature provide some guidance on new ways of engaging with the world

Social support as a moderator in the relationship between intrusive thoughts and anxiety among Spanish-speaking Latinas with breast cancer.

ObjectiveIntrusive thoughts, defined as unwanted and recurrent thoughts about a stressful experience, are associated with psychological distress in women with breast cancer. This study assessed moderating effects of various social support dimensions on associations between intrusive thoughts and psychological distress among Latina breast cancer survivors.MethodsWe used baseline data from a randomized controlled trial of a stress management intervention delivered to 151 Spanish-speaking Latinas with nonmetastatic breast cancer within 1 year of diagnosis. Intrusive thoughts, four dimensions of social support (emotional/informational, tangible, affectionate, and positive social interaction), and symptoms of anxiety and depression were assessed through in-person interviews. Information on age, time since diagnosis, breast cancer variables, history of depression, and marital status served as covariates. Generalized linear models were used to investigate bivariate and multivariate associations and to explore moderation effects of the four dimensions of social support.ResultsIn bivariate models, intrusive thoughts were associated positively with depression (β = .024, .001) and anxiety (β = .047, P < .001) symptoms. Adjusting for other factors, intrusive thoughts remained associated with depression symptoms (β = .022, .008), regardless of level of social support (for all support dimensions). For anxiety, there were significant interactions of tangible (β = -.013, .034) and affectionate (β = -.022, .005) support with intrusive thoughts. Intrusive thoughts were associated more strongly with anxiety symptoms among women reporting less tangible and affectionate support than those with higher levels of these types of support.ConclusionsTangible and affectionate support have protective effects on anxiety symptoms among Spanish-speaking Latina breast cancer survivors experiencing intrusive thoughts, but not depression symptoms

Specificity of the inhibition of DNA synthesis by extracts from cloned normal, sarcoma-virus-transformed and revertant 3T3 cells.

Extracts containing tissue-specific DNA-inhibitory activity were prepared from normal FL (Swiss) and BALBc3T3 cells, from these cells transformed with sarcoma virus and from revertants cloned from the transformed cell lines. By testing all extracts on all cell lines we found that (1) production of and susceptibility to the inhibitors were decreased in transformed BALB/c cells (2) specificity varied with expression of the transforming genome, as an extract from a given cell line inhibited the growth of its cell of origin, e.g. revertant, more than normal or transformed cells, and (3) there was also a DNA-synthesis stimulator