Terminal synchrones in the tail of comet 1965f

Position and velocity measurements of six synchrone emissions in tail of comet Ikeya-Sek

A three-month oscillation in the longitude of Jupiter's red spot

Periodic oscillations in longitude of Great Red Spot in Jupiter atmospher

Pathways from caring and engaging adults to youth vocational identity: the mediational roles of career search self-efficacy and goal capacity

This study examines the role played by access to caring and engaging adults, career search self-efficacy (CSSE), and goal capacity in the development of youth vocational identity. The study used a bootstrapping approach to analyze data, collected from a survey of 1,579 youths enrolled in 14 U.S. high schools, to test a hypothesized serial multiple mediation model. Results indicate both direct and multiple indirect pathways from adults influences to the youth vocational identity. Two specific pathways of influence were found through CSSE and goal capacity respectively. Additionally, a serial multiple mediation effect was found whereby CSSE and goal capacity collectively mediated the relationship. This indicates that greater access to caring and engaging adults contributes to higher CSSE, which accounts for a higher level of goal capacity, and eventually leads to the better vocational identity in youth. These findings establish notable implications for practices that are discussed in closing.First author draf

Recent measures of the latitude and longitude of jupiter's red spot

Latitude and longitude of Jupiter red spot measured from photographic plate

Latitude and longitude measurements of Jovian features in 1967-68

Photographic measurements of latitude and longitude of Jovian feature

The social psychology of seismic hazard adjustment: re-evaluating the international literature

The majority of people at risk from earthquakes do little or nothing to reduce their vulnerability. Over the past 40 years social scientists have tried to predict and explain levels of seismic hazard adjustment using models from behavioural sciences such as psychology. The present paper is the first to synthesise the major findings from the international literature on psychological correlates and causes of seismic adjustment at the level of the individual and the household. It starts by reviewing research on seismic risk perception. Next, it looks at norms and normative beliefs, focusing particularly on issues of earthquake protection responsibility and trust between risk stakeholders. It then considers research on attitudes towards seismic adjustment attributes, specifically beliefs about efficacy, control and fate. It concludes that an updated model of seismic adjustment must give the issues of norms, trust, power and identity a more prominent role. These have been only sparsely represented in the social psychological literature to date

A Computational Study of the Distribution of Particles in a Lab-Scale CFB Boiler

When two-fluid modeling is used to predict riser flows there have been difficulties in predicting the solids hold up in risers represented by the correct pressure drop profile. A way of encountering this inherent problem in current Eulerian-Eulerian CFD modeling is to approximate the actual particle size distribution by using more particle phases instead of the current practice of using one mean diameter. For the lab-scale CFB investigated, CFD simulations show that a mal-distribution occurs in the CFB; the larger particles are retained in the riser, whereas the intermediate and small particles are distributed both in the return leg and the riser. Simulations using an altered particle size distribution, i.e. a larger amount of large particles, show significant improvements in the pressure profile in the bottom part of the riser

Ascanius Project: MECH 401/402 Senior Capstone Experience

This report describes the analysis, design, and test, and launch of a high power reusable rocket. The design goals were to reach a target altitude of 3000’, deploy a payload module containing an egg that can be safely recovered, and record flight video. The rocket was 62.13 in long fully assembled, had a dry mass of 2.764 kg (3.077 kg wet), and was propelled using an I-class solid fuel rocket motor (Cesaroni I-216-CL). The nose cone and tail cone were fabricated by the team from carbon fiber reinforced polymer (CFRP) via wet layup and vacuum bagging. The fins were constructed from a carbon fiber-balsawood sandwich structure and designed to optimize aerodynamic performance (minimize drag and maximize lift). The motor mount consisted of an innovative “tubeless” design utilizing three centering rings and a 3D-printed ABS engine block. In order to ensure reusability, this design includes a dual deployment recovery system that uses a barometric altimeter to trigger flight events. A 15” drogue chute was set to deploy at apogee, which would control the initial descent while minimizing drift, and a 60” parachute deployed at 800’ was used to slow the rocket to a safe ground-hit velocity. At 900’, a self-contained egg module was deployed with its own parachute. The rocket achieved an apogee of 3556’, however a failure in the recovery system resulted in catastrophic fuselage damage on main parachute deployment. Design objectives, analyses, specifications, testing, and results are discussed in detail

Building more accurate decision trees with the additive tree.

The expansion of machine learning to high-stakes application domains such as medicine, finance, and criminal justice, where making informed decisions requires clear understanding of the model, has increased the interest in interpretable machine learning. The widely used Classification and Regression Trees (CART) have played a major role in health sciences, due to their simple and intuitive explanation of predictions. Ensemble methods like gradient boosting can improve the accuracy of decision trees, but at the expense of the interpretability of the generated model. Additive models, such as those produced by gradient boosting, and full interaction models, such as CART, have been investigated largely in isolation. We show that these models exist along a spectrum, revealing previously unseen connections between these approaches. This paper introduces a rigorous formalization for the additive tree, an empirically validated learning technique for creating a single decision tree, and shows that this method can produce models equivalent to CART or gradient boosted stumps at the extremes by varying a single parameter. Although the additive tree is designed primarily to provide both the model interpretability and predictive performance needed for high-stakes applications like medicine, it also can produce decision trees represented by hybrid models between CART and boosted stumps that can outperform either of these approaches