Rubrics as a Foundation for Assessing Student Competencies: One Public Administration Program’s Creative Exercise

Since implementation of the Network of Schools of Public Policy, Affairs, and Administration (NASPAA) standards for accreditation in 2009, public administration programs have been developing programmatic competencies that reflect NASPAA’s universal standards. Likewise, myriad efforts have analyzed data related to student and program progress toward achievement of these competencies. This article adds to that conversation by recounting the approach to assessing competencies used in the Department of Public Administration at Portland State University. There, newly developed rubrics reflect each of the department’s 10 competencies to examine whether students are acquiring the desired knowledge and skills. This article discusses the development and design of the rubrics as well as elements of gaining faculty and student input in the process

The environmental benefits and challenges of a composite car with structural battery materials

One way to reduce the environmental impact of an electric vehicle is to reduce the vehicle’s mass. This can be done by substitution of conventional materials such as steel, aluminium, and plastics with carbon fibre composites, or possibly even with structural battery composite materials. In the latter case, another consequence is that the size of the vehicle battery is reduced as the structural battery composite not only provides structural integrity, but also stores energy. This study assesses the change in life cycle environmental impacts related to transitioning from a conventional battery electric vehicle to a vehicle with components made from either carbon fibre composites or structural battery composites, with the aim of identifying environmental challenges and opportunities for cars with a high share of composite materials. Results show that a transition to carbon fibre composites and structural battery composite materials today would (in most cases) increase the total environmental impact due to the energy intensive materials production processes. The two major contributors to the environmental impacts for the structural battery composite materials are energy intensive structural battery material manufacturing process and carbon fibre production process, both of which can be expected to decrease their energy consumption as the technology maturity level increases and other production and manufacturing processes are developed. For future assessments, more effort needs to be put on collecting primary data for large-scale structural battery composites production and on assessing different technology development routes

Unpacking estimates of task duration: The role of typicality and temporality

Research in task duration judgment has shown that unpacking a multifaceted task into components prior to estimating its duration increases estimates. In three studies, we find that unpacking a complex task can increase, decrease, or leave unaffected task duration estimates depending on the typicality of the unpacked components and their temporal position in the task sequence. Unpacking atypical long components increases task duration estimates, while unpacking atypical short components decreases estimates (Study 1). Unpacking atypical early components increases task duration estimates, while unpacking atypical late components decreases estimates (Study 2). Unpacking typical early or late components leaves estimates unaffected (Study 3). We explain these results based on the idea that task duration estimation involves a mental simulation process, and by drawing on theories of unpacking in probability judgment that emphasize the role of the typicality of the unpacked components. These findings hint at a deep conceptual link between probability judgment and task duration estimation but also show differences, such as the influence that temporality exerts on estimated duration. © 2013 Elsevier Inc

The Grizzly, February 13, 2014

Annual Job, Internship and Networking Fair Brings Potential Employers to the Ursinus Campus • International Medical Corps Representative to Speak This Wednesday • History Department Holds Nazi Regime Lecture • ZBS Group to Perform in Valentine\u27s Day Improv Workshop • Recycle Mania Returns to UC • Students Bring Composting to Lower • Wismer Music Open to Input • TLI Reps to Visit Hong Kong • Opinion: Smartphones Make Communication a Chore; The Endgame of Piracy is Product Placement • Men\u27s Lacrosse Boasts Strong Senior Class • All-American Football Player Announces He is Gay • Winter Sports Regular Season Coming to Closehttps://digitalcommons.ursinus.edu/grizzlynews/1897/thumbnail.jp

Three-dimensional structure determination from a single view

The ability to determine the structure of matter in three dimensions has profoundly advanced our understanding of nature. Traditionally, the most widely used schemes for 3D structure determination of an object are implemented by acquiring multiple measurements over various sample orientations, as in the case of crystallography and tomography (1,2), or by scanning a series of thin sections through the sample, as in confocal microscopy (3). Here we present a 3D imaging modality, termed ankylography (derived from the Greek words ankylos meaning 'curved' and graphein meaning 'writing'), which enables complete 3D structure determination from a single exposure using a monochromatic incident beam. We demonstrate that when the diffraction pattern of a finite object is sampled at a sufficiently fine scale on the Ewald sphere, the 3D structure of the object is determined by the 2D spherical pattern. We confirm the theoretical analysis by performing 3D numerical reconstructions of a sodium silicate glass structure at 2 Angstrom resolution and a single poliovirus at 2 - 3 nm resolution from 2D spherical diffraction patterns alone. Using diffraction data from a soft X-ray laser, we demonstrate that ankylography is experimentally feasible by obtaining a 3D image of a test object from a single 2D diffraction pattern. This approach of obtaining complete 3D structure information from a single view is anticipated to find broad applications in the physical and life sciences. As X-ray free electron lasers (X-FEL) and other coherent X-ray sources are under rapid development worldwide, ankylography potentially opens a door to determining the 3D structure of a biological specimen in a single pulse and allowing for time-resolved 3D structure determination of disordered materials.Comment: 30 page

From Compact Plasma Particle Sources to Advanced Accelerators with Modeling at Exascale

Developing complex, reliable advanced accelerators requires a coordinated, extensible, and comprehensive approach in modeling, from source to the end of beam lifetime. We present highlights in Exascale Computing to scale accelerator modeling software to the requirements set for contemporary science drivers. In particular, we present the first laser-plasma modeling on an exaflop supercomputer using the US DOE Exascale Computing Project WarpX. Leveraging developments for Exascale, the new DOE SCIDAC-5 Consortium for Advanced Modeling of Particle Accelerators (CAMPA) will advance numerical algorithms and accelerate community modeling codes in a cohesive manner: from beam source, over energy boost, transport, injection, storage, to application or interaction. Such start-to-end modeling will enable the exploration of hybrid accelerators, with conventional and advanced elements, as the next step for advanced accelerator modeling. Following open community standards, we seed an open ecosystem of codes that can be readily combined with each other and machine learning frameworks. These will cover ultrafast to ultraprecise modeling for future hybrid accelerator design, even enabling virtual test stands and twins of accelerators that can be used in operations.Comment: 4 pages, 3 figures, submitted to the 20th Advanced Accelerator Concepts Workshop (AAC22

Estimating the Continuous-Time Dynamics of Energy and Fat Metabolism in Mice

The mouse has become the most popular organism for investigating molecular mechanisms of body weight regulation. But understanding the physiological context by which a molecule exerts its effect on body weight requires knowledge of energy intake, energy expenditure, and fuel selection. Furthermore, measurements of these variables made at an isolated time point cannot explain why body weight has its present value since body weight is determined by the past history of energy and macronutrient imbalance. While food intake and body weight changes can be frequently measured over several weeks (the relevant time scale for mice), correspondingly frequent measurements of energy expenditure and fuel selection are not currently feasible. To address this issue, we developed a mathematical method based on the law of energy conservation that uses the measured time course of body weight and food intake to estimate the underlying continuous-time dynamics of energy output and net fat oxidation. We applied our methodology to male C57BL/6 mice consuming various ad libitum diets during weight gain and loss over several weeks and present the first continuous-time estimates of energy output and net fat oxidation rates underlying the observed body composition changes. We show that transient energy and fat imbalances in the first several days following a diet switch can account for a significant fraction of the total body weight change. We also discovered a time-invariant curve relating body fat and fat-free masses in male C57BL/6 mice, and the shape of this curve determines how diet, fuel selection, and body composition are interrelated

Rational Design of Temperature-Sensitive Alleles Using Computational Structure Prediction

Temperature-sensitive (ts) mutations are mutations that exhibit a mutant phenotype at high or low temperatures and a wild-type phenotype at normal temperature. Temperature-sensitive mutants are valuable tools for geneticists, particularly in the study of essential genes. However, finding ts mutations typically relies on generating and screening many thousands of mutations, which is an expensive and labor-intensive process. Here we describe an in silico method that uses Rosetta and machine learning techniques to predict a highly accurate “top 5” list of ts mutations given the structure of a protein of interest. Rosetta is a protein structure prediction and design code, used here to model and score how proteins accommodate point mutations with side-chain and backbone movements. We show that integrating Rosetta relax-derived features with sequence-based features results in accurate temperature-sensitive mutation predictions

Search for gravitational waves associated with the InterPlanetary Network short gamma ray bursts

We outline the scientific motivation behind a search for gravitational waves associated with short gamma ray bursts detected by the InterPlanetary Network (IPN) during LIGO's fifth science run and Virgo's first science run. The IPN localisation of short gamma ray bursts is limited to extended error boxes of different shapes and sizes and a search on these error boxes poses a series of challenges for data analysis. We will discuss these challenges and outline the methods to optimise the search over these error boxes.Comment: Methods paper; Proceedings for Eduardo Amaldi 9 Conference on Gravitational Waves, July 2011, Cardiff, U