A Method for Assessing Attentional Bias in Anxious Rats

A popular theory regarding the etiology of anxiety disorders asserts that they are developed and maintained by an attentional bias towards threat cues. The present study attempts to develop an animal model that parallels current human research on this bias. Adult rats were tested in a 3-choice serial reaction time task with aversive and appetitive signals, and their performance was compared against anxiety scores from elevated plus maze and open field sessions. A bias towards the aversive signal strongly correlated with anxiety scores, suggesting that this methodology could be used for further animal studies investigating their relationship

A Model for Optimal Human Navigation with Stochastic Effects

We present a method for optimal path planning of human walking paths in mountainous terrain, using a control theoretic formulation and a Hamilton-Jacobi-Bellman equation. Previous models for human navigation were entirely deterministic, assuming perfect knowledge of the ambient elevation data and human walking velocity as a function of local slope of the terrain. Our model includes a stochastic component which can account for uncertainty in the problem, and thus includes a Hamilton-Jacobi-Bellman equation with viscosity. We discuss the model in the presence and absence of stochastic effects, and suggest numerical methods for simulating the model. We discuss two different notions of an optimal path when there is uncertainty in the problem. Finally, we compare the optimal paths suggested by the model at different levels of uncertainty, and observe that as the size of the uncertainty tends to zero (and thus the viscosity in the equation tends to zero), the optimal path tends toward the deterministic optimal path

The Semi Implicit Gradient Augmented Level Set Method

Here a semi-implicit formulation of the gradient augmented level set method is presented. By tracking both the level set and it's gradient accurate subgrid information is provided,leading to highly accurate descriptions of a moving interface. The result is a hybrid Lagrangian-Eulerian method that may be easily applied in two or three dimensions. The new approach allows for the investigation of interfaces evolving by mean curvature and by the intrinsic Laplacian of the curvature. In this work the algorithm, convergence and accuracy results are presented. Several numerical experiments in both two and three dimensions demonstrate the stability of the scheme.Comment: 19 Pages, 14 Figure

Learning from Other Communities

This paper reflects a synopsis of the work in person/family-centered planning representative of its implementation across a variety of disability service systems, including prisons, schools, community-based service agencies and institutional settings. The authors who have contributed to this paper have direct experience in the field working with individuals who have disability labels of severe and persistent mental illness, mental retardation and developmental disabilities, and learning disabilities. It is their hope that this paper will serve to guide the emerging best practice in the design and delivery of person-centered service delivery systems

High-order ENO schemes applied to two- and three-dimensional compressible flow

High order essentially non-oscillatory (ENO) finite difference schemes are applied to the 2-D and 3-D compressible Euler and Navier-Stokes equations. Practical issues, such as vectorization, efficiency of coding, cost comparison with other numerical methods, and accuracy degeneracy effects, are discussed. Numerical examples are provided which are representative of computational problems of current interest in transition and turbulence physics. These require both nonoscillatory shock capturing and high resolution for detailed structures in the smooth regions and demonstrate the advantage of ENO schemes

Demography of Global Aging

Individuals aged 65 years and older currently make up a larger share of the population than ever before, and this group is predicted to continue growing both in absolute terms and relative to the rest of the population. This chapter begins by introducing the facts, figures, and forecasts surrounding the aging of populations across different countries at varying levels of development. In light of these trends, we examine challenges facing graying societies through the lenses of health, economics, and policy development. The chapter concludes with a selection of adaptable strategies that countries might consider to mitigate the strain – and to harness the full potential – of aging populations worldwide

Learning Haptic-based Object Pose Estimation for In-hand Manipulation Control with Underactuated Robotic Hands

Unlike traditional robotic hands, underactuated compliant hands are challenging to model due to inherent uncertainties. Consequently, pose estimation of a grasped object is usually performed based on visual perception. However, visual perception of the hand and object can be limited in occluded or partly-occluded environments. In this paper, we aim to explore the use of haptics, i.e., kinesthetic and tactile sensing, for pose estimation and in-hand manipulation with underactuated hands. Such haptic approach would mitigate occluded environments where line-of-sight is not always available. We put an emphasis on identifying the feature state representation of the system that does not include vision and can be obtained with simple and low-cost hardware. For tactile sensing, therefore, we propose a low-cost and flexible sensor that is mostly 3D printed along with the finger-tip and can provide implicit contact information. Taking a two-finger underactuated hand as a test-case, we analyze the contribution of kinesthetic and tactile features along with various regression models to the accuracy of the predictions. Furthermore, we propose a Model Predictive Control (MPC) approach which utilizes the pose estimation to manipulate objects to desired states solely based on haptics. We have conducted a series of experiments that validate the ability to estimate poses of various objects with different geometry, stiffness and texture, and show manipulation to goals in the workspace with relatively high accuracy

Function follows form : how connectivity patterns govern neural responses

Thesis (Ph. D. in Neuroscience)--Massachusetts Institute of Technology, Dept. of Brain and Cognitive Sciences, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references.Connectivity restricts and defines the information that a network can process. It is the substance of information processing that underlies the patterns of functional activity in the brain. By combining diffusion-weighted imaging or DWI, with fMRI, we are able to non-invasively measure connectivity and neural responses in the same individuals and directly relate these two measures to one another. In Chapter 2, I first establish the proof-of-principle that anatomical connectivity alone can predict neural responses in cortex, specifically of face-selectivity in the fusiform gyrus. I then extend this novel approach to the rest of the brain and test whether connectivity can accurately predict neural responses to various visual categories in Chapter 3. Finally, in Chapter 4, I compare and contrast the resulting models, which are essentially networks of connectivity that are functionally-relevant to each visual category, and demonstrate the type of knowledge that can be uncovered by directly integrating structure and function.by David Eugene Osher.Ph.D.in Neuroscienc

Avoid Simple Solutions and Quick Fixes: Lessons Learned From a Comprehensive Districtwide Approach to Improving Student Behavior and School Safety

We examine the effects of the Cleveland Metropolitan School District’s (CMSD) districtwide efforts to improve school safety, order, and conditions for learning. These approaches include implementing (1) a social and emotional learning program for elementary students (PATHS); (2) a planning model for students exhibiting academic or nonacademic needs (student support teams); and (3) a learner-centered approach to discipline (planning centers). We found that improved conditions for learning as well as student support interventions can foster safer, more productive schools. Suspension and expulsion rates decreased, but racial/ethnic disparities remained. Implementation quality also mediated outcomes. Transforming conditions contributing to exclusionary discipline often requires a sustained effort that should begin with an understanding that a culture of change, unlike “quick fixes” (e.g., metal detectors), requires time to engage stakeholders, cultivate their buy-in, and develop and implement an effective plan. We conclude with six recommendations addressing conditions for learning, student supports, and disciplinary disparities

Thriving, Robust Equity, and Transformative Learning & Development: A More Powerful Conceptualization of the Contributors to Youth Success

This new conceptualization of youth success draws from more than 180 sources and makes an argument for new definitions to propel practice and policy that addresses educational and racial equity. The paper:Introduces a formula and a rationale for addressing thriving, equity, and learning and development together that helps us better focus on actionable social factors;Summarizes prevailing definitions of thriving, equity, and learning and development (and related terms);Takes a deeper dive into the dimensions that contribute to individual and collective thriving;Offers powerful and aligned conceptualizations of thriving, equity, and learning and development;Describes the opportunities and conditions required to ensure that efforts to create "equitable educational outcomes" or "equitable learning and development opportunities" are as powerful and inclusive as possible