Acrylonitrile-based copolymers: Synthesis,characterization, and formation of ultrafiltration membranes utilized for the immobilization of proteins

Various high molecular weight copolymers of acrylonitrile and a vinyl comonomer containing an aryl amine, a pyridine, or an aliphatic hydroxyl group were synthesized via slurry polymerization techniques so as to contain from 1 to 15 mol % functional comonomer. The comonomer content was quantitated by ultraviolet absorbance, base titration of acid polymer salts, and/or relative chemical reactivity with trichloro-s-triazine. Thin films were cast from copolymer solutions, coagulated into unsupported ultrafiltration membrances, and characterized with respect to both water permeability and pore size distribution. Analysis by size exclusion chromatography of the membrane permeate of a pool of dextran fractions yielded a continuous distribution curve for membrane pore size over the range 1.5 to 70 nm. The ultrafiltration membranes were used for protein immobilization after appropriate chemical activation. The three distinct types of functional copolymers gave comparable results for α-chymotrypsin, with protein weight loadings of 6–12% and 40–65% retention of enzymatic specific activity.     

Color accurate monitors: Basic features and comparison of four monitors

Color accurate monitors are high resolution, luminance‐controlled displays with very large color gamut. They have internal controls to match specific color standards (e.g., sRGB, Adobe‐RGB, REC‐709) and well‐defined gamma functions (mostly γ = 2.2, but others such as Equal Probability of Detection, Digital Imaging and Communications in Medicine). Usually, they come with external tools for automatic calibration (like Chroma 5 or Spider) and for communicating with the host computer through USB port, and with software to control the calibration process. Most of them allow a calibration to a specific customer selected color gamut, besides the precalibrated standards, but limit the gray levels calibration to a gamma type function (typically γ = 2.2). Their unique properties, challenges, and applications will be discussed. A comparison between the properties of four monitors and optical test results of their parameters is presented.     

The educational electronic book as a tool for supporting children’s emergent literacy in low versus middle SES groups

The effects of an educational electronic book (e-book) on 149 five- to six-year-old kindergarteners’ emergent literacy levels were researched in two SES groups: low (LSES) (79 children) vs. middle (MSES) (70 children). In each SES group, children were randomly assigned to four groups. Three groups were assigned to work individually in one of three e-book activity modes: “Read story only”, “Read with dictionary”, or “Read and play” during three similar activity sessions and the fourth group served as a control which received the regular program of the kindergarten. Pre- and post-intervention emergent literacy measures included word meaning, word recognition, and phonological awareness. Results show that word meaning of children from both middle and low SES improved following the educational e-book activity, regardless of mode. Second, LSES children’s emergent literacy levels showed relatively greater improvement rates than did those of the MSES children. Third, children in the “Read with dictionary” and “Read and play” activity modes showed more improvement in their emergent literacy levels than did those in the “Read story only” mode. Implications for future research and for education are discussed.     

Evaluation of Face Datasets as Tools for Assessing the Performance of Face Recognition Methods

Face datasets are considered a primary tool for evaluating the efficacy of face recognition methods. Here we show that in many of the commonly used face datasets, face images can be recognized accurately at a rate significantly higher than random even when no face, hair or clothes features appear in the image. The experiments were done by cutting a small background area from each face image, so that each face dataset provided a new image dataset which included only seemingly blank images. Then, an image classification method was used in order to check the classification accuracy. Experimental results show that the classification accuracy ranged between 13.5% (color FERET) to 99% (YaleB). These results indicate that the performance of face recognition methods measured using face image datasets may be biased. Compilable source code used for this experiment is freely available for download via the Internet.     

Adaptive pattern recognition with rotation, scale, and shift invariance

Mutually orthogonal pattern distortions are handled by an adaptive optical recognition system. A double-channel system is presented that implements pattern recognition with rotation, scale, and shift invariance. The recognition process is based on a two-stage operation: An object-independent determination of one distortion parameter (the scale, in the example presented here) is performed, and then the recognition is completed by a shift- and rotation-invariant optical correlator that is adapted to the measured parameter. Thus, complete invariance to three distortion parameters is achieved by the combination of two channels. The overall process is performed efficiently and can be executed in real time.     

Context‐Dependent Crowd Evaluation

Many times, even if a crowd simulation looks good in general, there could be some specific individual behaviors which do not seem correct. Spotting such problems manually can become tedious, but ignoring them may harm the simulation's credibility. In this paper we present a data‐driven approach for evaluating the behaviors of individuals within a simulated crowd. Based on video‐footage of a real crowd, a database of behavior examples is generated. Given a simulation of a crowd, an analog analysis is performed on it, defining a set of queries, which are matched by a similarity function to the database examples. The results offer a possible objective answer to the question of how similar are the simulated individual behaviors to real observed behaviors. Moreover, by changing the video input one can change the context of evaluation. We show several examples of evaluating simulated crowds produced using different techniques and comprising of dense crowds, sparse crowds and flocks.     

Matching with don't-cares and a small number of mismatches

In matching with don't-cares and k mismatches we are given a pattern of length m and a text of length n, both of which may contain don't-cares (a symbol that matches all symbols), and the goal is to find all locations in the text that match the pattern with at most k mismatches, where k is a parameter. We present new algorithms that solve this problem using a combination of convolutions and a dynamic programming procedure. We give randomized and deterministic solutions that run in time O(nk²logm) and O(nk³logm), respectively, and are faster than the most efficient extant methods for small values of k. Our deterministic algorithm is the first to obtain an O(polylog(k)⋅nlogm) running time.