Simulation and visualization of flow in a new miniature mixer for multiphase polymer systems

A newly designed mixer, the Alberta polymer asymmetric minimixer (APAM), was compared to the MiniMAX molder with flow simulation and flow visualization techniques to evaluate the performance of the mixers. The APAM has a unique, asymmetric design consisting of a varying clearance between the rotor blade tips and the cup wall, which enables the material to be squeezed, stretched, and kneaded in high‐shear and converging zones. Flow simulation showed that substantial folding and axial movement occurred in this mixer and that the pressure and velocity profiles exhibited high values at the rotor tip with the smallest rotor tip/cup clearance. In contrast, the MiniMAX molder had very simple flow patterns, which were insufficient to induce good dispersive and distributive mixing. These results concurred with those from an earlier work that studied the structure of blends and nanocomposites processed in the APAM compared to other polymer processing equipment. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 136–142, 2005     

Detecting Semantic Anomalies in Truck Weigh-in-Motion Traffic Data Using Data Mining

Monitoring data from event-based monitoring systems are becoming more and more prevalent in civil engineering. An example is truck weigh-in-motion (WIM) data. These data are used in the transportation domain for various analyses, such as analyzing the effects of commercial truck traffic on pavement materials and designs. It is important that such analyses use good quality data or at least account appropriately for any deficiencies in the quality of data they are using. Low quality data may exist due to problems in the sensing hardware, in its calibration, or in the software processing the raw sensor data. The vast quantities of data collected make it infeasible for a human to examine all the data. The writers propose a data mining approach for automatically detecting semantic anomalies i.e., unexpected behavior in monitoring data. The writers’ method provides automated assistance to domain experts in setting up constraints for data behavior. The effectiveness of this method is shown by reporting its successful application to data from an actual WIM system, the experimental data the Minnesota department of transportation collected by its Minnesota road research project (Mn/ROAD) facilities. The constraints the expert set up by applying this method were useful for automatic anomaly detection over the Mn/ROAD data, i.e., they detected anomalies the expert cared about, e.g., unlikely vehicles and erroneously classified vehicles, and the misclassification rate was reasonable for a human to handle (usually less than 3%). Moreover, the expert gained insights about system behavior, such as realizing that a system-wide change had occurred. The constraints detected, for example, periods in which the WIM system reported that roughly 20% of the vehicles classified as three-axle single-unit trucks had only one axle.     

Efficient Craig interpolation for linear Diophantine (dis)equations and linear modular equations

The use of Craig interpolants has enabled the development of powerful hardware and software model checking techniques. Efficient algorithms are known for computing interpolants in rational and real linear arithmetic. We focus on subsets of integer linear arithmetic. Our main results are polynomial time algorithms for obtaining interpolants for conjunctions of linear Diophantine equations, linear modular equations (linear congruences), and linear Diophantine disequations. We also present an interpolation result for conjunctions of mixed integer linear equations. We show the utility of the proposed interpolation algorithms for discovering modular/divisibility predicates in a counterexample guided abstraction refinement (CEGAR) framework. This has enabled verification of simple programs that cannot be checked using existing CEGAR based model checkers. This paper is an extended version of [14]. This research was sponsored by the Gigascale Systems Research Center (GSRC), Semiconductor Research Corporation (SRC), the National Science Foundation (NSF), the Office of Naval Research (ONR), the Naval Research Laboratory (NRL), the Defense Advanced Research Projects Agency (DARPA), the Army Research Office (ARO), and the General Motors Collaborative Research Lab at CMU. The views and conclusions contained in this document are those of the author and should not be interpreted as representing the official policies, either expressed or implied, of GSRC, SRC, NSF, ONR, NRL, DARPA, ARO, GM, or the U.S. government.     

When does abstraction help?

Abstraction is a leading technique for coping with large state spaces. Abstraction over-approximates the transitions of the original system or the automaton that models it and may introduce nondeterminism. In applications where determinism is essential, we say that an abstraction function is helpful if, after determining and minimizing the abstract automaton, we end up with fewer states than the original automaton. We show that abstraction functions are not always helpful; in fact, they may introduce an exponential blow-up. We study the problem of deciding whether a given abstraction function is helpful for a given deterministic automaton and show that it is PSPACE-complete.     

Special section on advances in reachability analysis and decision procedures: contributions to abstraction-based system verification

Reachability analysis asks whether a system can evolve from legitimate initial states to unsafe states. It is thus a fundamental tool in the validation of computational systems—be they software, hardware, or a combination thereof. We recall a standard approach for reachability analysis, which captures the system in a transition system, forms another transition system as an over-approximation, and performs an incremental fixed-point computation on that over-approximation to determine whether unsafe states can be reached. We show this method to be sound for proving the absence of errors, and discuss its limitations for proving the presence of errors, as well as some means of addressing this limitation. We then sketch how program annotations for data integrity constraints and interface specifications—as in Bertrand Meyer’s paradigm of Design by Contract—can facilitate the validation of modular programs, e.g., by obtaining more precise verification conditions for software verification supported by automated theorem proving. Then we recap how the decision problem of satisfiability for formulae of logics with theories—e.g., bit-vector arithmetic—can be used to construct an over-approximating transition system for a program. Programs with data types comprised of bit-vectors of finite width require bespoke decision procedures for satisfiability. Finite-width data types challenge the reduction of that decision problem to one that off-the-shelf tools can solve effectively, e.g., SAT solvers for propositional logic. In that context, we recall the Tseitin encoding which converts formulae from that logic into conjunctive normal form—the standard format for most SAT solvers—with only linear blow-up in the size of the formula, but linear increase in the number of variables. Finally, we discuss the contributions that the three papers in this special section make in the areas that we sketched above.     

Similarity versus social ambition effects in the assessment of interpersonal acceptance in the classroom.

Evaluated the manner in which variations in sociometric formulations highlight differing effects of academic status on social acceptance in the classroom in 2 parallel studies with 619 7th, 8th, and 9th graders. Ss completed alternately worded versions of an interpersonal relationship assessment technique. As expected, versions emphasizing personal desires or willingness to interact led to findings indicating heightened acceptance for targets of higher academic status (social ambition). In contrast, versions leading Ss to consider realistic costs or limitations evoked higher acceptance for targets of similar rather than different social status (similarity). The contingency between sociometric formulation and outcome was consistent with level of aspiration and social exchange theories and points to the distinctive role of both desire and cost–benefit considerations in choice of social relations among adolescents. (29 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The chemistry behind the artist's palette

The origin of color in organic and inorganic artists' pigments is discussed and, where possible, is related to their physical properties such as lightfastness and brilliance. Included in the discussion are the nature of color, the types of chemical species that exhibit color, and the structural features of these compounds that make them colored. The compounds are categorized according to the structural properties that enable them to absorb visible radiation.     

Differential Effects of Halofuginone Enantiomers on Muscle Fibrosis and Histopathology in Duchenne Muscular Dystrophy

Progressive loss of muscle and muscle function is associated with significant fibrosis in Duchenne muscular dystrophy (DMD) patients. Halofuginone, an analog of febrifugine, prevents fibrosis in various animal models, including those of muscular dystrophies. Effects of (+)/(−)-halofuginone enantiomers on motor coordination and diaphragm histopathology in mdx mice, the mouse model for DMD, were examined. Four-week-old male mice were treated with racemic halofuginone, or its separate enantiomers, for 10 weeks. Controls were treated with saline. Racemic halofuginone-treated mice demonstrated better motor coordination and balance than controls. However, (+)-halofuginone surpassed the racemic form’s effect. No effect was observed for (−)-halofuginone, which behaved like the control. A significant reduction in collagen content and degenerative areas, and an increase in utrophin levels were observed in diaphragms of mice treated with racemic halofuginone. Again, (+)-halofuginone was more effective than the racemic form, whereas (−)-halofuginone had no effect. Both racemic and (+)-halofuginone increased diaphragm myofiber diameters, with no effect for (−)-halofuginone. No effects were observed for any of the compounds tested in an in-vitro cell viability assay. These results, demonstrating a differential effect of the halofuginone enantiomers and superiority of (+)-halofuginone, are of great importance for future use of (+)-halofuginone as a DMD antifibrotic therapy.     

SP1 protein-based nanostructures and arrays

Controlled formation of complex nanostructures is one of the main goals of nanoscience and nanotechnology. Stable Protein 1 (SP1) is a boiling-stable ring protein complex, 11 nm in diameter, which self-assembles from 12 identical monomers. SP1 can be utilized to form large ordered arrays; it can be easily modified by genetic engineering to produce various mutants; it is also capable of binding gold nanoparticles (GNPs) and thus forming protein-GNP chains made of alternating SP1s and GNPs. We report the formation and the protocols leading to the formation of those nanostructures and their characterization by transmission electron microscopy, atomic force microscopy, and electrostatic force microscopy. Further control over the GNP interdistances within the protein-GNP chains may lead to the formation of nanowires and structures that may be useful for nanoelectronics.     

Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma

Magnetic Resonance Materials in Physics, Biology and Medicine - Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI....