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 This result and other yet unpublished observations indicate that the velocity and topology of FIM can also contribute to a biological distinction between neoplastic and normal cells.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.     

Controlling a Semiconductor Optical Amplifier Using a State-Space Model

We derive nonlinear and linear state-space control models for a multichannel semiconductor optical amplifier. Verified against the governing partial differential equations through simulation, the linear model tracks modulations up to 20% qualitatively well. Linear feedback control is then employed to design two interchannel crosstalk suppressing systems, one using state feedback into the electronic drive current and the other using optical output feedback into an optical control channel; the controller designed with the linear model is seen to work well even with 100% modulations of the nonlinear system. This linear state-space model opens the way for further robust analysis, design and control of integrated active photonic circuits     

Genetic algorithm for balancing reconfigurable machining lines

We consider the problem of designing a reconfigurable machining line. Such a line is composed of a sequence of workstations performing specific sets of operations. Each workstation is comprised of several identical CNC machines (machining centers). The line is required to satisfy the given precedence order, inclusion, exclusion and accessibility constraints on the given set of operations. Inclusion and exclusion are zoning constraints which oblige or forbid certain operations to be performed on the same workstation. The accessibility constraints imply that each operation has a set of possible part positions under which it can be performed. All the operations performed on the same workstation must have a common part position. Workstation times are computed taking into account processing and setup times for operations and must not exceed a given bound. The number of CNC machines at one workstation is limited, and the total number of machines must be minimized. A genetic algorithm is proposed. This algorithm is based on the permutation representation of solutions. A heuristic decoder is suggested to construct a solution from a permutation, so that the output solution is feasible w.r.t. precedence, accessibility, cycle time, and exclusion constraints. The other constraints are treated with a penalty approach. For a local improvement of solutions, a mixed integer programming model is suggested for an optimal design of workstations if the order of operations is fixed. An experimental evaluation of the proposed GA on large scale test instances is performed.     

Computing resultants on Graphics Processing Units: Towards GPU-accelerated computer algebra

In this article we report on our experience in computing resultants of bivariate polynomials on Graphics Processing Units (GPU). Following the outline of Collins’ modular approach [6], our algorithm starts by mapping the input polynomials to a finite field for sufficiently many primes m$m$. Next, the GPU algorithm evaluates the polynomials at a number of fixed points x∈_Zm$x\in {\mathbb{Z}}_m$, and computes a set of univariate resultants for each modular image. Afterwards, the resultant is reconstructed using polynomial interpolation and Chinese remaindering. The GPU returns resultant coefficients in the form of Mixed Radix (MR) digits. Finally, large integer coefficients are recovered from the MR representation on the CPU. All computations performed by the algorithm (except for, partly, Chinese remaindering) are outsourced to the graphics processor thereby minimizing the amount of work to be done on the host machine. The main theoretical contribution of this work is the modification of Collins’ modular algorithm using the methods of matrix algebra to make an efficient realization on the GPU feasible. According to the benchmarks, our algorithm outperforms a CPU-based resultant algorithm from 64-bit Maple 14 by a factor of 100.     

Benefits of Residual Aluminum in Ductile Iron

Two main chemistry systems of micro-inclusions can be identified in ductile iron: Ca-S-X and Mg-Si-O-X with the majority of the inclusions regardless of treatment type and location being of the second type, silicates. Laboratory investigations have shown that simple silicates were present in the matrix, while more complex silicates were present in conjunction with graphite, probably acting as graphite nucleation sites. In these more complex silicates, elevated levels of Al, Ca, Ce and La were typical. Comparing micro-particles embedded in iron matrix and graphite nodules of iron treated with pure Mg-metal and iron treated with MgFeSi alloy showed a higher amount of complex silicates with elevated Al-levels in the iron treated with MgFeSi. Further laboratory investigation was undertaken to explore which source of Al and which range of residual Al would have a favorable impact on the graphite nucleation in ductile iron. The work showed that a residual aluminum of 0.005 to 0.020 wt.% appears to be beneficial for improving ductile iron solidification characteristics without the incidence of pinholes. Greatest benefits were achieved when introducing the Al into the iron via an inoculant late during processing or via a pre-conditioner to the base iron. Al added via the MgFeSi provided less benefit. Some case studies illustrating the effect of Al in ductile iron are also presented, as Al-containing pre-conditioner or/and Al-bearing, FeSi inoculant application.