Free-Flight Tests of Fifth-Stage Scout Entry Vehicle at Mach Numbers of 5 and 17

Measurements have been made in air at two Mach numbers of the static stability, normal force, and drag of a version of the fifth-stage Scout entry vehicle. The most significant result was that the design center of gravity led to a condition of static instability at small angles of attack at Mach number 17. At this Mach number, the static stability was a highly nonlinear function of the angle of attack. A useful method for analyzing free-flight data having this nonlinear behavior is included in this report. Comparisons were made between the measured aerodynamic coefficients and those estimated by Newtonian impact theory and by a method developed by Seiff and Whiting. The latter method gave good estimates of the normal-force-curve slope at both Mach numbers and of the moment-curve slope at the lower Mach number. It resulted in an overestimation of the static stability at Mach number 17, although it gave results decidedly closer to the experimental value than did Newtonian impact theory

Juvenile Arrest and Collateral Educational Damage in the Transition to Adulthood

Official sanctioning of students by the criminal justice system is a long-hypothesized source of educational disadvantage, but its explanatory status remains unresolved. Few studies of the educational consequences of a criminal record account for alternative explanations such as low self-control, lack of parental supervision, deviant peers, and neighborhood disadvantage. Moreover, virtually no research on the effect of a criminal record has examined the ‘‘black box’’ of mediating mechanisms or the consequence of arrest for postsecondary educational attainment. Analyzing longitudinal data with multiple and independent assessments of theoretically relevant domains, the authors estimate the direct effect of arrest on later high school dropout and college enrollment for adolescents with otherwise equivalent neighborhood, school, family, peer, and individual characteristics as well as similar frequency of criminal offending. The authors present evidence that arrest has a substantively large and robust impact on dropping out of high school among Chicago public school students. They also find a significant gap in four-year college enrollment between arrested and otherwise similar youth without a criminal record. The authors also assess intervening mechanisms hypothesized to explain the process by which arrest disrupts the schooling process and, in turn, produces collateral educational damage. The results imply that institutional responses and disruptions in students’ educational trajectories, rather than social-psychological factors, are responsible for the arrest–education link.Sociolog

Autonomous Optimization and Control for Central Plants with Energy Storage

A model predictive control (MPC) framework is used to determine how to optimize the distribution of energy resources across a central energy facility including chillers, water heaters, and thermal energy storage; present the results to an operator; and execute the plan. The objective of this MPC framework is to minimize cost in real-time in response to both real-time energy prices and demand charges as well as allow the operator to appropriately interact with the system. Operators must be given the correct intersection points in order to build trust before they are willing to turn the tool over and put it into fully autonomous mode. Once in autonomous mode, operators need to be able to intervene and impute their knowledge of the facilities they are serving into the system without disengaging optimization. For example, an operator may be working on a central energy facility that serves a college campus on Friday night before a home football game. The optimization system is predicting the electrical load, but does not have knowledge of the football game. Rather than try to include every possible factor into the prediction of the loads, a daunting task, the optimization system empowers the operator to make human-in-the-loop decisions in these rare scenarios without exiting autonomous (auto) mode. Without this empowerment, the operator either takes the system out of auto mode or allows the system to make poor decisions. Both scenarios will result in an optimization system that has low “on time†and thus saves little money. A cascaded, model predictive control framework lends itself well to allowing an operator to intervene. The system presented is a four tiered approach to central plant optimization. The first tier is the prediction of the energy loads of the campus; i.e., the inputs to the optimization system. The predictions are made for a week in advance, giving the operator ample time to react to predictions they do not agree with and override the predictions if they feel it necessary. The predictions are inputs to the subplant-level optimization. The subplant-level optimization determines the optimal distribution of energy across major equipment classes (subplants and storage) for the prediction horizon and sends the current distribution to the equipment level optimization. The operators are able to use the subplant-level optimization for “advisory†only and enter their own load distribution into the equipment level optimization. This could be done if they feel that they need to be conservative with the charge of the tank. Finally, the equipment level optimization determines the devices to turn on and their setpoints in each subplant and sends those setpoints to the building automation system. These decisions can be overridden, but should be extremely rare as the system takes device availability, accumulated runtime, etc. as inputs. Building an optimization system that empowers the operator ensures that the campus owner realizes the full potential of his investment. Optimal plant control has shown over 10% savings, for large plants this can translate to savings of more than US $1 million per year

Model Predictive Control for Central Plant Optimization with Thermal Energy Storage

An optimization framework is used in order to determine how to distribute both hot and cold water loads across a central energy plant including heat pump chillers, conventional chillers, water heaters, and hot and cold water (thermal energy) storage. The objective of the optimization framework is to minimize cost in response to both real-time energy prices and demand charges. The linear programming framework used allows for the optimal solution to be found in real-time. Real-time optimization lead to two separate applications: A planning tool and a real-time optimization tool. In the planning tool the optimization is performed repeatedly with a sliding horizon accepting a subset of the optimized distribution trajectory horizon as each subsequent optimization problem is solved. This is the same strategy as model predictive control except that in the design and planning tool the optimization is working on a given set of loads, weather (e.g. TMY data), and real-time pricing data and does not need to predict these values. By choosing the varying lengths of the horizon (2 to 10 days) and size of the accepted subset (1 to 24 hours), the design and planning tool can be used to find the design year’s optimal distribution trajectory in less than 5 minutes for interactive plant design, or the design and planning tool can perform a high fidelity run in a few hours. The fast solution times also allow for the optimization framework to be used in real-time to optimize the load distribution of an operational central plant using a desktop computer or microcontroller in an onsite Enterprise controller. In the real-time optimization tool Model Predictive Control is used; estimation, prediction, and optimization are performed to find the optimal distribution of loads for duration of the horizon in the presence of disturbances. The first distribution trajectory in the horizon is then applied to the central energy plant and the estimation, prediction, and optimization is repeated in 15 minutes using new plant telemetry and forecasts. Prediction is performed using a deterministic plus stochastic model where the deterministic portion of the model is a simplified system representing the load of all buildings connected to the central energy plant and the stochastic model is used to respond to disturbances in the load. The deterministic system uses forecasted weather, time of day, and day type in order to determine a predicted load. The estimator uses past data to determine the current state of the stochastic model; the current state is then projected forward and added to the deterministic system’s projection. In simulation, the system has demonstrated more than 10% savings over other schedule based control trajectories even when the subplants are assumed to be running optimally in both cases (i.e., optimal chiller staging, etc.). For large plants this can mean savings of more than US $1 million per year

Brief mindfulness training enhances cognitive control in socioemotional contexts: Behavioral and neural evidence.

In social contexts, the dynamic nature of others' emotions places unique demands on attention and emotion regulation. Mindfulness, characterized by heightened and receptive moment-to-moment attending, may be well-suited to meet these demands. In particular, mindfulness may support more effective cognitive control in social situations via efficient deployment of top-down attention. To test this, a randomized controlled study examined effects of mindfulness training (MT) on behavioral and neural (event-related potentials [ERPs]) responses during an emotional go/no-go task that tested cognitive control in the context of emotional facial expressions that tend to elicit approach or avoidance behavior. Participants (N = 66) were randomly assigned to four brief (20 min) MT sessions or to structurally equivalent book learning control sessions. Relative to the control group, MT led to improved discrimination of facial expressions, as indexed by d-prime, as well as more efficient cognitive control, as indexed by response time and accuracy, and particularly for those evidencing poorer discrimination and cognitive control at baseline. MT also produced better conflict monitoring of behavioral goal-prepotent response tendencies, as indexed by larger No-Go N200 ERP amplitudes, and particularly so for those with smaller No-Go amplitude at baseline. Overall, findings are consistent with MT's potential to enhance deployment of early top-down attention to better meet the unique cognitive and emotional demands of socioemotional contexts, particularly for those with greater opportunity for change. Findings also suggest that early top-down attention deployment could be a cognitive mechanism correspondent to the present-oriented attention commonly used to explain regulatory benefits of mindfulness more broadly

Mindfulness enhances episodic memory performance: Evidence from a multimethod investigation

Training in mindfulness, classically described as a receptive attentiveness to present events and experiences, has been shown to improve attention and working memory. Both are key to long-term memory formation, and the present three-study series used multiple methods to examine whether mindfulness would enhance episodic memory, a key form of long-term memory. In Study 1 (N = 143), a self-reported state of mindful attention predicted better recognition performance in the Remember-Know (R-K) paradigm. In Study 2 (N = 93), very brief training in a focused attention form of mindfulness also produced better recognition memory performance on the R-K task relative to a randomized, well-matched active control condition. Study 3 (N = 57) extended these findings by showing that relative to randomized active and inactive control conditions the effect of very brief mindfulness training generalized to free-recall memory performance. This study also found evidence for mediation of the mindfulness training—episodic memory relation by intrinsic motivation. These findings indicate that mindful attention can beneficially impact motivation and episodic memory, with potential implications for educational and occupational performance

Passion, music, and psychological well-being

Passionate music engagement is a defining feature of music fans worldwide. Although benefits to psychosocial well-being are often experienced by fans of music, some fans experience maladaptive outcomes from their music engagement. The Dualistic Model of Passion proposes that two types of passion—harmonious and obsessive—are associated with positive and negative outcomes of passionate engagement, respectively. This model has been employed in research on passion for a wide range of pursuits including music performers, but not for passionate listeners. The present study employed this model to investigate whether (1) harmonious passion for music is associated with positive music listening experiences and/or psychological well-being and (2) obsessive passion for music is associated with negative music listening experiences and/or psychological ill-being. Passionate fans (n = 197) of 40 different musical genres were surveyed about their experiences when listening to their favorite music. Measures included the passion scale, affective experiences with music, and psychological well-being and ill-being. Results supported the Dualistic Model of Passion. Structural equation modeling revealed that harmonious passion for music predicted positive affective experiences which, in turn, predicted psychological well-being. Conversely, obsessive passion for music predicted negative affective experiences which, in turn, predicted psychological ill-being. The findings suggest that the nature of passionate engagement with music has an integral role in the psychological impact of music engagement and implications for the well-being of music fans.</p

A Complete Scheme of Ionization Cooling for a Muon Collider

A complete scheme for production and cooling a muon beam for three specified muon colliders is presented. Parameters for these muon colliders are given. The scheme starts with the front end of a proposed neutrino factory that yields bunch trains of both muon signs. Emittance exchange cooling in slow helical lattices reduces the longitudinal emittance until it becomes possible to merge the trains into single bunches, one of each sign. Further cooling in all dimensions is applied to the single bunches in further slow helical lattices. Final transverse cooling to the required parameters is achieved in 50 T solenoids using high Tc superconductor at 4 K. Preliminary simulations of each element are presented.Comment: 3 pages, 6 figure

Childhood Sleep Problems, Response Inhibition, and Alcohol and Drug Outcomes in Adolescence and Young Adulthood

To our knowledge, no prospective studies examine the relationships among childhood sleep problems, adolescent executive functioning, and substance outcomes (i.e., substance use and substance-related problems). In this study, we examined whether childhood sleep problems predicted adolescent sleep problems and response inhibition. We also tested whether adolescent sleep problems and poor response inhibition mediated the relationship between childhood sleep problems and substance (alcohol and drug) outcomes in young adulthood.Study participants were 292 boys and 94 girls (M = 4.85, SD = 1.47) from a community sample of high-risk families and controls.When compared to their counterparts, those with trouble sleeping in childhood were twice as likely to have the same problem in adolescence. Childhood overtiredness predicted poor response inhibition in adolescence. Persistent trouble sleeping from childhood to adolescence and response inhibition in adolescence mediated the relationship between childhood sleep problems and drug outcomes in young adulthood, whereas overtiredness in childhood directly predicted alcohol use outcomes and alcohol-related problems in young adulthood.This is the first study showing a long-term relationship between childhood sleep measures and subsequent alcohol and drug outcomes. The developmental and clinical implications of these findings were discussed. Prevention and intervention programs may want to consider the role of sleep problems and response inhibition on substance use and abuse.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79313/1/j.1530-0277.2010.01178.x.pd