Poly(methyl methacrylate) and polyacrylonitrile dispersions stabilized by gelatin

Methyl methacrylate was polymerized in an aqueous medium in the presence of gelatin using potassium persulfate as initiator. The dispersion mode of polymerization, when the monomer is completely miscible with water, was investigated and compared with an emulsion process, which proceeds at higher monomer concentration. Spherical and relatively uniform polymer particles were formed. Macroscopic precipitation of polymer is prevented by combination of the steric stabilization by grafted gelatin and of repulsive electrostatic interactions from the initiator residues attached to the particle surface. Static and dynamic light scattering have been used to determine the molar mass (molar mass of the whole dispersion particle, M_wD ～ 10⁸-10⁹ g mol^?1) and hydrodynamic radius (R_hD ～ 50-120 nm) of the particles. The number of particles per unit volume does not depend on overall monomer concentration, and it is higher, and therefore the particle size is smaller, than that observed for the soapless emulsion polymerization. The addition of gelatin may be thus used to modify the particle size. Acrylonitrile dispersions were prepared under similar conditions. Unlike methyl methacrylate, this monomer does not swell the polymer particles. While poly(methyl methacrylate) particles are spherical and relatively uniform, the polyacrylonitrile dispersions consist of polydisperse aggregates of tiny polymer particles.     

Characterization of six-coordinated iron (V) in an oxide lattice

On the basis of a discussion of the correlations between the stability of the d³ configuration and the symmetry and size of the cation site, six-coordinated iron (V) has been stabilized in the La₂LiFeO₆ perovskite-type oxide and characterized by magnetic susceptibility, Mössbauer resonance and EPR measurements.     

Evaluation of the effectiveness of features selected by discriminant analysis methods

New theoretical and practical results concerning the use of discriminant analysis for feature selection are presented in the paper. Numerical values for the eigenvalues of the matrix SW_W⁻¹ S_B (within-class and between-class scatter matrices) are investigated. An analytic expression for their minimum value representing the minimum effectiveness is derived. Differences between real values and these minimum values are important for the evaluation of the effectiveness of features and thus for feature selection.     

Fast branch & bound algorithms for optimal feature selection

A novel search principle for optimal feature subset selection using the Branch & Bound method is introduced. Thanks to a simple mechanism for predicting criterion values, a considerable amount of time can be saved by avoiding many slow criterion evaluations. We propose two implementations of the proposed prediction mechanism that are suitable for use with nonrecursive and recursive criterion forms, respectively. Both algorithms find the optimum usually several times faster than any other known Branch & Bound algorithm. As the algorithm computational efficiency is crucial, due to the exponential nature of the search problem, we also investigate other factors that affect the search performance of all Branch & Bound algorithms. Using a set of synthetic criteria, we show that the speed of the Branch & Bound algorithms strongly depends on the diversity among features, feature stability with respect to different subsets, and criterion function dependence on feature set size. We identify the scenarios where the search is accelerated the most dramatically (finish in linear time), as well as the worst conditions. We verify our conclusions experimentally on three real data sets using traditional probabilistic distance criteria.     

Shotgun protein sequencing by tandem mass spectra assembly

The analysis of mass spectrometry data is still largely based on identification of single MS/MS spectra and does not attempt to make use of the extra information available in multiple MS/MS spectra from partially or completely overlapping peptides. Analysis of MS/MS spectra from multiple overlapping peptides opens up the possibility of assembling MS/MS spectra into entire proteins, similarly to the assembly of overlapping DNA reads into entire genomes. In this paper, we present for the first time a way to detect, score, and interpret overlaps between uninterpreted MS/MS spectra in an attempt to sequence entire proteins rather than individual peptides. We show that this approach not only extends the length of reconstructed amino acid sequences but also dramatically improves the quality of de novo peptide sequencing, even for low mass accuracy MS/MS data.     

Influence of opposite sex on attraction produced by pioneer sex of four bark beetle species cohabiting pine in the Southern United States

Catches ofDendroctonus frontalis andIps avulsus on traps surrounding bolts infested with both sexes of each species in the gallery were not significantly different from catches at bolts infested only with the sex which normally pioneers the host colonization process. In contrast, the presence of the second sex in the gallery significantly reduced catches ofI. grandicollis andI. calligraphus and, additionally, the presence of females in the male galleries ofI. calligraphus significantly reduced the catch ofI. avulsus females as compared with their response to bolts infested with the maleI. calligraphus only.     

Calibration and quantification of fast intracellular motion (FIM) in living cells using correlation analysis

Video rate confocal laser scanning microscopy at the highest spatial and temporal resolution of backscattered light (BSL) imaging allowed for regular observation of fast intracellular motion (FIM) first revealed in living neoplastic cells. However, the absence of an objective evaluation has hampered further study of the mechanisms and biological significance of FIM. Particularly, a quantification of apparent differences in velocities that would complement and improve the current demonstration of FIM by color coding using the combination of red-green-blue (RGB) images had been missing. Standard methods of tracking or pattern recognition could not be applied because of the fuzzy nature of images of FIM. A search for a suitable method led to correlation analysis. It was calibrated on Brownian motion and a known type of motion, such as cell marginal ruffling, compared with FIM. Results approved its explanatory potential. Therefore, several crucial incidences of FIM could be analyzed. Apart from an argument against viewing FIM as a manifestation of simple Brownian motion, the correlation analysis of FIM in the adjacent peripheries of a rat fibroblast and a K4 rat sarcoma cell confirmed the notion of higher and uneven distribution of velocity of FIM in a tumor cell so far shown in color-coded images only. This result and other yet unpublished observations indicate that the velocity and topology of FIM can also contribute to a biological distinction between neoplastic and normal cells. Regular application of the correlation analysis should further expand the study of FIM for its mechanisms and predictive value. Such an approach should be thoroughly examined for a contribution to the knowledge of cancer cells.     

Generalised multi-pattern-based verification of programs with linear linked structures

The paper deals with the problem of automatic verification of programs working with extended linear linked dynamic data structures, in particular, pattern-based verification is considered. In this approach, one can abstract memory configurations by abstracting away the exact number of adjacent occurrences of certain memory patterns. With respect to the previous work on the subject the method presented in the paper has been extended to be able to handle multiple patterns, which allows for verification of programs working with more types of structures and/or with structures with irregular shapes. The experimental results obtained from a prototype implementation of the method show that the method is very competitive and offers a big potential for future extensions.     

Language models for detection of unknown attacks in network traffic

In this paper, we propose a method for network intrusion detection based on language models. Our method proceeds by extracting language features such as n-grams and words from connection payloads and applying unsupervised anomaly detection—without prior learning phase or presence of labeled data. The essential part of this procedure is linear-time computation of similarity measures between language models of connection payloads. Particular patterns in these models decisive for differentiation of attacks and normal data can be traced back to attack semantics and utilized for automatic generation of attack signatures. Results of experiments conducted on two datasets of network traffic demonstrate the importance of high-order n-grams and variable-length language models for detection of unknown network attacks. An implementation of our system achieved detection accuracy of over 80% with no false positives on instances of recent remote-to-local attacks in HTTP, FTP and SMTP traffic.