Revisiting the need for formal education in visualization.

Defining visualization education is still a work in progress. Visualization education is not just a subject within computer science. Computer scientists are not always the appropriate choice to teach visualization courses on their own. Visualization is not just mastering a set of concepts but acquiring skills. Student should learn by doing, either using one tool or a variety of tools, depending on the course's focus.     

Deflection Calculation of FRP Reinforced Concrete Beams Based on Modifications to the Existing Branson Equation

Fundamental concepts of tension stiffening are used to explain why Branson’s equation for the effective moment of inertia Ie does not predict deflection well for fiber reinforced polymer (FRP) reinforced concrete beams. The tension stiffening component in Branson’s equation is shown to depend on the ratio of gross-to-cracked moment of inertia (Ig/Icr), and gives too much tension stiffening for beams with an Ig/Icr ratio greater than 3. FRP beams typically have an Ig/Icr ratio greater than 5, leading to a much stiffer response and underprediction of computed deflections as observed by others in the past. One common approach to computing deflection of FRP reinforced concrete beams has been to use a modified form of the Branson equation. This paper presents a rational development of appropriate modification factors needed to reduce the tension stiffening component in Branson’s original expression to realistic levels. Computed deflections using this approach give reasonable results with the right modification factor, and compare well with a more general unified approach that incorporates a realistic tension stiffening model. Comparison is made with the existing and past correction factors recommended by ACI 440 for predicting deflection of FRP beams. The method presently used by ACI 440 gives reasonable estimates of deflection for glass and carbon FRP reinforced beams. However, this method underestimates deflection of aramid FRP reinforced beams and is restricted to rectangular sections. A proposal is made for adoption of a simple modification factor that works well for all types of FRP bar and beam cross-sectional shape.     

Generation of gas bubbles in microflow using micropipette with ultrasound

Ultrasound was applied to a micropipette micromixer to improve dispersion of gas and liquid in a microchannel. Flow visualization using a high-speed camera was performed to examine the effect of ultrasonic irradiation on bubble generation in the microchannel. Basically, nitrogen gas was injected using a (0.5 µm ID) glass micropipette into ethanol flowing in a rectangular (100 µm×200 µm) microchannel on polydimethylsiloxane (PDMS). Gas and liquid flow rates were regulated using mass flow controllers. At aflow condition that is typical of bubbly flow, ultrasound was transmitted into the microchannel using a piezo-electric (PZT) transducer over a range of operating voltages (2 to 200 Vp-p) and frequencies (50 to 60 kHz). Images captured during the action of the PZT transducer indicate that bubble formation is influenced by ultrasound. When subjected to ultrasound above 50 Vp-p and at the resonant frequency of the PZT transducer, bubbles formed that were smaller and closer together, signifying enhanced shearing of the gas at the micropipette tip by the liquid. The observation of gas slugs occurring sooner might be attributed to the coalescence of gas bubbles that became closely spaced.     

The role of experience in liking "read-to-drink" alcoholic beverages.

Ready-to-drinks (RTDs) are composed of an alcoholic component and a soft-drink base and are primarily consumed by a youth market. The authors explored whether liking and experience with an RTD soft-drink base predicts liking for the RTD. Participants (N=350) from ages 12 to 30 years sampled 3 RTDs and their respective soft-drink and alcoholic components. For milk- and fruit-based RTDs, liking for and familiarity with their soft-drink base was the best predictor of liking for and familiarity with the RTD itself. For the Coke-based RTD, familiarity with and liking for bourbon best predicted familiarity with and liking for the RTD. All of these effects were consistent across blind and nonblind testing. The authors' results suggest that where there is perceptual similarity between the RTD and its soft-drink base, these beverages may provide an easy transition into alcohol consumption for novice drinkers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Computational Complexity of One-Dimensional Sandpiles

We prove that the one-dimensional sandpile prediction problem is in LOGDCFL, a subset of AC¹. The previously best known upper bound on the ACⁱ-scale was AC². Furthermore, we prove that the one-dimensional sandpile prediction problem is hard for TC⁰ and thus not in AC^1-ε for any constant ε > 0.     

Applications of the discrete element method in mechanical engineering

Compared to other fields of engineering, in mechanical engineering, the Discrete Element Method (DEM) is not yet a well known method. Nevertheless, there is a variety of simulation problems where the method has obvious advantages due to its meshless nature. For problems where several free bodies can collide and break after having been largely deformed, the DEM is the method of choice. Neighborhood search and collision detection between bodies as well as the separation of large solids into smaller particles are naturally incorporated in the method. The main DEM algorithm consists of a relatively simple loop that basically contains the three substeps contact detection, force computation and integration. However, there exists a large variety of different algorithms to choose the substeps to compose the optimal method for a given problem. In this contribution, we describe the dynamics of particle systems together with appropriate numerical integration schemes and give an overview over different types of particle interactions that can be composed to adapt the method to fit to a given simulation problem. Surface triangulations are used to model complicated, non-convex bodies in contact with particle systems. The capabilities of the method are finally demonstrated by means of application examples. Commemorative Contribution.     

Temporal Specificity of Extinction in Autoshaping.

Three experiments investigated the effects of varying the conditioned stimulus (CS) duration between training and extinction. Ring doves (Streptopelia risoria) were autoshaped on a fixed CS-unconditioned stimulus (US) interval and extinguished with CS presentations that were longer, shorter, or the same as the training duration. During a subsequent test session, the training CS duration was reintroduced. Results suggest that the cessation of responding during an extinction session is controlled by generalization of excitation between the training and extinction CSs and by the number of nonreinforced CS presentations. Transfer of extinction to the training CS is controlled by the similarity between the extinction and training CSs. Extinction learning is temporally specific. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Probing stress effects in HfO2 gate stacks with time dependent measurements

Effects of constant voltage stress (CVS) on gate stacks consisting of an ALD HfO₂ dielectric with various interfacial layers were studied with time dependent sensing measurements: DC I–V, pulse I–V, and charge pumping (CP) at different frequencies. The process of injected electron trapping/de-trapping on pre-existing defects in the bulk of the high-κ film was found to constitute the major contribution to the time dependence of the threshold voltage (V_t) shift during stress. The trap generation observed with the low frequency CP measurements is suggested to occur within the interfacial oxide layer or the interfacial layer/high-κ interface, with only a minor effect on V_t.     

A site selection model for high technology manufacturing firms in the United States

This article offers a quantitative model for site selection by high technology manufacturing firms. In the past, site selection studies have usually been qualitative in nature, and very subjective. This is an attempt to introduce a more objective quantitative approach. The site selection factors most important to high technology manufacturing firms were identified, ranked and weighted based on a US Joint Economic Committe survey of such firms. The eight most important factors were: the availability of technical and professional workers, labor costs, tax climate, academic institutions, cost of living, transportation for people, and access to markets. Demographic data on these factors were collected and analyzed for 32 developing high technology areas in the United States. By using the quantitative model, a score was developed for each area, allowing them to be ranked as R & D manufacturing environments. This model should prove a useful tool for both regional planners and high-tech companies seeking to relocate.