Effect of chain stiffness on ion distributions around a polyelectrolyte in multivalent salt solutions

Ion distributions in dilute polyelectrolyte solutions are studied by means of Langevin dynamics simulations. We show that the distributions depend on the conformation of a chain while the conformation is determined by the chain stiffness and the salt concentration. We observe that the monovalent counterions originally condensed on a chain can be replaced by the multivalent ones dissociated from the added salt due to strong electrostatic interaction. These newly condensed ions give an important impact on the chain structure. At low and at high salt concentrations, the conformation of a semiflexible chain is rodlike. The ion distributions show similarity to those for a rigid chain, but difference to those for a flexible chain whose conformation is a coil. In the mid-salt region, the flexible chain and the semiflexible chain collapse but the collapsed chain structures are, respectively, disordered and ordered structures. The ion distributions hence show different profiles for these three chain stiffness with the curves for the semiflexible chain lying between those for the flexible and the rigid chains. The number of the condensed multivalent counterions, as well as the effective chain charge, also shows similar behavior, demonstrating a direct connection with the chain morphology. Moreover, we find that the condensed multivalent counterions form triplets with two adjacent monomers and are localized on the chain axis at intermediate salt concentration when the chain stiffness is semiflexible or rigid. The microscopic information obtained here provides valuable insight to the phenomena of DNA condensation and is very useful for researchers to develop new models.Comment: 28 pages, 10 figures, accepted for publication in JC

Progressor: Personalized visual access to programming problems

This paper presents Progressor, a visualization of open student models intended to increase the student's motivation to progress on educational content. The system visualizes not only the user's own model, but also the peers' models. It allows sorting the peers' models using a number of criteria, including the overall progress and the progress on a specific topic. Also, in this paper we present results of a classroom study confirming our hypothesis that by showing a student the peers' models and ranking them by progress it is possible to increase the student's motivation to compete and progress in e-learning systems. © 2011 IEEE

Generation of helical gears with new surfaces, topology by application of CNC machines

Analysis of helical involute gears by tooth contact analysis shows that such gears are very sensitive to angular misalignment that leads to edge contact and the potential for high vibration. A new topology of tooth surfaces of helical gears that enables a favorable bearing contact and a reduced level of vibration is described. Methods for grinding of the helical gears with the new topology are proposed. A TCA (tooth contact analysis) program for simulation of meshing and contact of helical gears with the new topology has been developed. Numerical examples that illustrate the proposed ideas are discussed

Effects of thermal and mechanical fatigue on the flexural strength of G40-600/PMR-15 cross-ply laminates

The effects of thermal and mechanical fatigue on the flexural strength of G40-600/PMR-15 cross-ply laminates with ply orientation of (0(2),90(2))2S and (90(2),0(2))2S are examined. The relative importance of shear and tensile stresses is examined by varying the span-to-depth ratios of flexural test specimens from 8 to 45. Acoustic emission signals are measured during the flexural tests in order to monitor the initiation and growth of damage. Optical microscopy is used to examine specimens for resin cracking, delamination, and fiber breaks after testing. Transverse matrix cracks and delaminations occur in all specimens, regardless of ply orientation, span-to-depth ratio, or previous exposure of specimens to thermal and mechanical fatigue. A small amount of fiber tensile fracture occurs in the outer 0 deg ply of specimens with high span-to-depth ratios. Because of the complex failure modes, the flexural test results represent the 'apparent' strengths rather than the true flexural or shear strengths for these cross-ply laminates. Thermal cycling of specimens prior to flexural testing does not reduce the apparent flexural strength or change the mode of failure. However, fewer acoustic events are recorded at all strains during flexural testing of specimens exposed to prior thermal cycling. High temperature thermal cycling (32 to 260 C, 100 cycles) causes a greater reduction in acoustic events than low temperature thermal cycling (-85 to +85 C, 500 cycles). Mechanical cycling (0 to 50 percent of the flexural strength, 100 cycles) has a similar effect, except that acoustic events are reduced only at strains less than the maximum strain applied during flexural fatigue

Testing for inconsistencies in the estimation of UK capital structure determinants

This article analyses the determinants of the capital structure of 1054 UK companies from 1991 to 1997, and the extent to which the influence of these determinants are affected by time-invariant firm-specific heterogeneity. Comparing the results of pooled OLS and fixed effects panel estimation, significant differences in the results are found. While the OLS results are generally consistent with prior literature, the results of our fixed effects panel estimation contradict many of the traditional theories of the determinants of corporate financial structure. This suggests that results of traditional studies may be biased owing to a failure to control for firm-specific, time-invariant heterogeneity. The results of the fixed effects panel estimation find larger companies to have higher levels of both long-term and short-term debt than do smaller firms, profitability to be negatively correlated with the level of gearing, although profitable firms tend to have more short-term bank borrowing than less profitable firms, and tangibility to positively influence the level of short-term bank borrowing, as well as all long-term debt elements. However, the level of growth opportunities appears to have little influence on the level of gearing, other than short-term bank borrowing, where a significant negative relationship is observed

Trajectory-Based Dynamic Map Labeling

In this paper we introduce trajectory-based labeling, a new variant of dynamic map labeling, where a movement trajectory for the map viewport is given. We define a general labeling model and study the active range maximization problem in this model. The problem is NP-complete and W[1]-hard. In the restricted, yet practically relevant case that no more than k labels can be active at any time, we give polynomial-time algorithms. For the general case we present a practical ILP formulation with an experimental evaluation as well as approximation algorithms.Comment: 19 pages, 7 figures, extended version of a paper to appear at ISAAC 201

Design of Spacecraft Formation Orbits Relative to a Stabilized Trajectory

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76533/1/AIAA-8433-932.pd

Modelling math learning on an open access intelligent tutor

This paper presents a methodology to analyze large amount of students’ learning states on two math courses offered by Global Fresh- man Academy program at Arizona State University. These two courses utilised ALEKS (Assessment and Learning in Knowledge Spaces) Arti- ficial Intelligence technology to facilitate massive open online learning. We explore social network analysis and unsupervised learning approaches (such as probabilistic graphical models) on these type of Intelligent Tu- toring Systems to examine the potential of the embedding representa- tions on students learning

PredictCS: Personalizing Programming learning by leveraging learning analytics

This paper presents a new framework to harness sources of programming learning analytics at a Higher Education Institution and how it has been progressively adopted at the classroom level to improve personalized learning. This new platform, called PredictCS, automatically detects lower-performing or “at-risk” students in computer programming modules and automatically and adaptively sends them feedback. PredictCS embeds multiple predictive models by leveraging multi-modal learning analytics of student data, including student characteristics, prior academic history, logged interactions between students and online resources, and students' progress in programming laboratory work, and their progression from introductory to advanced CS courses. Predictions are generated every week during the semester's classes. In addition, students are flexible to opt-in to receive pseudo real-time personalized feedback, which permits them to be aware of their predicted course performance. The adaptive feedback ranges from programming suggestions from top- performers in the class to resources that are suitable to bridge their programing knowledge gaps