Addressing Issues for Graduate Students who are Single Parents with Dependent Children: What is the Role of Adult Education?

The purpose of this roundtable is to begin unveiling the experience of the graduate student who is also a single parent, while also suggesting supportive programs to improve their recruitment and success. This adult student population is underserved. Understanding their challenges is necessary to improve resources and student success

Effective Heuristic Methods for Finding Non-Optimal Solutions of Interest in Constrained Optimization Models

This paper introduces the SoI problem, that of finding non-optimal solutions of interest for constrained optimization models. SoI problems subsume finding FoIs (feasible solutions of interest), and IoIs (infeasible solutions of interest). In all cases, the interest addressed is post-solution analysis in one form or another. Post-solution analysis of a constrained optimization model occurs after the model has been solved and a good or optimal solution for it has been found. At this point, sensitivity analysis and other questions of import for decision making (discussed in the paper) come into play and for this purpose the SoIs can be of considerable value. The paper presents examples that demonstrate this and reports on a systematic approach, using evolutionary computation, for obtaining both FoIs and IoIs

Learning the Designer's Preferences to Drive Evolution

This paper presents the Designer Preference Model, a data-driven solution that pursues to learn from user generated data in a Quality-Diversity Mixed-Initiative Co-Creativity (QD MI-CC) tool, with the aims of modelling the user's design style to better assess the tool's procedurally generated content with respect to that user's preferences. Through this approach, we aim for increasing the user's agency over the generated content in a way that neither stalls the user-tool reciprocal stimuli loop nor fatigues the user with periodical suggestion handpicking. We describe the details of this novel solution, as well as its implementation in the MI-CC tool the Evolutionary Dungeon Designer. We present and discuss our findings out of the initial tests carried out, spotting the open challenges for this combined line of research that integrates MI-CC with Procedural Content Generation through Machine Learning.Comment: 16 pages, Accepted and to appear in proceedings of the 23rd European Conference on the Applications of Evolutionary and bio-inspired Computation, EvoApplications 202

Characterization of the brain functional architecture of psychostimulant withdrawal using single-cell whole brain imaging

Numerous brain regions have been identified as contributing to addiction-like behaviors, but unclear is the way in which these brain regions as a whole lead to addiction. The search for a final common brain pathway that is involved in addiction remains elusive. To address this question, we used male C57BL/6J mice and performed single-cell whole-brain imaging of neural activity during withdrawal from cocaine, methamphetamine, and nicotine. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical- to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway that leads to addiction

When fair is not equal: compassion and politeness predict allocations of wealth under different norms of equity and need

Growing evidence has highlighted the importance of social norms in promoting prosocial behaviors in economic games. Specifically, individual differences in norm adherence—captured by the politeness aspect of Big Five agreeableness—has been found to predict fair allocations of wealth to one’s partner in the dictator game. Yet most studies have used neutrally-framed paradigms, where players may default to norms of equality in the absence of contextual cues. In this study (N = 707), we examined prosocial personality traits and dictator allocations under salient real-world norms of equity and need. Extending on previous research, we found that—in addition to politeness—the compassion aspect of agreeableness predicted greater allocations of wealth when they were embedded in real-world norms. These results represent an important step in understanding the real-world implications of laboratory-based research, demonstrating the importance of both normative context and prosocial traits

Procedural personas as critics for dungeon generation

This paper introduces a constrained optimization method which uses procedural personas to evaluate the playability and quality of evolved dungeon levels. Procedural personas represent archetypical player behaviors, and their controllers have been evolved to maximize a specific utility which drives their decisions. A “baseline” persona evaluates whether a level is playable by testing if it can survive in a worst-case scenario of the playthrough. On the other hand, a Monster Killer persona or a Treasure Collector persona evaluates playable levels based on how many monsters it can kill or how many treasures it can collect, respectively. Results show that the implemented two-population genetic algorithm discovers playable levels quickly and reliably, while the different personas affect the layout, difficulty level and tactical depth of the generated dungeons.The research was supported, in part, by the FP7 ICT project C2Learn (project no: 318480) and by the FP7 Marie Curie CIG project AutoGameDesign (project no: 630665).peer-reviewe

Electromagnetic Pulses at Short-Pulse Laser Facilities

Electromagnetic Pulse (EMP) is a known issue for short-pulse laser facilities, and will also be an issue for experiments using the advanced radiographic capability (ARC) at the National Ignition Facility (NIF). The ARC diagnostic uses four NIF beams that are compressed to picosecond durations for backlighting ignition capsules and other applications. Consequently, we are working to understand the EMP due to high-energy (MeV) electrons escaping from targets heated by short-pulse lasers. Our approach is to measure EMP in the Titan short-pulse laser at Lawrence Livermore National Laboratory (LLNL) and to employ that data to establish analysis and simulation capabilities. We have installed a wide variety of probes inside and outside the Titan laser chamber. We have high-frequency B-dots and D-dots, a photodiode, and fast current-viewing and integrating current transformers. The probe outputs are digitized by 10 and 20 Gsample/s oscilloscopes. The cables and oscilloscopes are well shielded to reduce noise. Our initial measurement campaign has yielded data useful mainly from hundreds of MHz to several GHz. We currently are supplementing our high-frequency probes with lower-frequency ones to obtain better low-frequency data. In order to establish analysis and simulation capabilities we are modeling the Titan facility using various commercial and LLNL numerical electromagnetic codes. We have simulated EMP generation by having a specified number of electrons leave the target and strike the chamber wall and other components in the chamber. This short impulse of electrons has a corresponding broad spectrum, exciting high-frequency structure in the resulting EMP. In this paper, we present results of our initial measurement campaign and comparisons between the measurements and simulations

HIV Testing for Children in Resource-Limited Settings: What Are We Waiting For?

Scott Kellerman and Shaffiq Essajee argue that the time has come to increase access to HIV testing for children, especially in sub-Saharan Africa

Characterization of the brain functional architecture of psychostimulant withdrawal using single-cell whole brain imaging

Numerous brain regions have been identified as contributing to addiction-like behaviors, but unclear is the way in which these brain regions as a whole lead to addiction. The search for a final common brain pathway that is involved in addiction remains elusive. To address this question, we used male C57BL/6J mice and performed single-cell whole-brain imaging of neural activity during withdrawal from cocaine, methamphetamine, and nicotine. We used hierarchical clustering and graph theory to identify similarities and differences in brain functional architecture. Although methamphetamine and cocaine shared some network similarities, the main common neuroadaptation between these psychostimulant drugs was a dramatic decrease in modularity, with a shift from a cortical- to subcortical-driven network, including a decrease in total hub brain regions. These results demonstrate that psychostimulant withdrawal produces the drug-dependent remodeling of functional architecture of the brain and suggest that the decreased modularity of brain functional networks and not a specific set of brain regions may represent the final common pathway that leads to addiction