Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes

Pathogenic/likely pathogenic variants in susceptibility genes that interrupt RNA splicing are a well-documented mechanism of hereditary cancer syndromes development. However, if RNA studies are not performed, most of the variants beyond the canonical GT-AG splice site are characterized as variants of uncertain significance (VUS). To decrease the VUS burden, we have bioinformatically evaluated all novel VUS detected in 732 consecutive patients tested in the routine genetic counseling process. Twelve VUS that were predicted to cause splicing defects were selected for mRNA analysis. Here, we report a functional characterization of 12 variants located beyond the first two intronic nucleotides using RNAseq in APC, ATM, FH, LZTR1, MSH6, PALB2, RAD51C, and TP53 genes. Based on the analysis of mRNA, we have successfully reclassified 50% of investigated variants. 25% of variants were downgraded to likely benign, whereas 25% were upgraded to likely pathogenic leading to improved clinical management of the patient and the family members.     

Local echo canceler with optimal input for true full-duplex speechscrambling system

The purpose of this paper is to focus on the local echo-canceling problem of full-duplex scrambled speech communications over a two-wire telephone network when the scrambling transformation is located between the handset and body of a telephone. Such a design makes possible very efficient protection against electromagnetic compromising emanation, which in turn substantially enhances the overall security of a protected communication. We propose a new adaptive FIR filter algorithm for local echo cancellation in such applications. The proposed algorithm differs from the conventional one by the construction of input signals in an optimal way using the D-optimal experiment design. In this way, at each step, we generate a new sample of the D-optimal pilot sequence for the filter parameter estimation. Consequently, the adaptation of the local echo canceler is defined as an initialization process in the first phase of each protected telephone call. The advantage in using the proposed adaptive FIR echo canceler is demonstrated through simulation results     

The joint mixing action of the static pre-mixer and the rotating drum mixer – Discrete element method approach

In this study, the mixing performance of coupled mixing action of the Komax static mixer (which is used as a pre-mixer) and rotating drum (applied as the final mixer) was explored in the maize meal mixing operation. The main objective of this paper was to predict the behaviour of the previously grinded maize particles, during the mixing process in static mixer and drum mixer, and to explore the possibilities to shorten the mixing time in the main mixer (in order to reduce the energy consumption).Three different experiments were performed: in the first experiment, possibilities of static mixer were explored, second experiment showed the mixing performance of rotating drum, and the combination of these two mixing devices was investigated in the third experiment. Homogeneity of the obtained mixtures was determined experimentally, by the “Microtracers” method.The Discrete Element Method was used for modelling of granular flow in the pre-mixing and final mixing applications, and to predict the inter-particle mixing quality within a static mixer and the rotating drum mixer. The results of the numerical simulation are compared with appropriate experimental results. The possible industrial application of this model could be the optimization of parameters of mixing systems taking into account the quality and the duration of the mixing process.     

Robust least mean square adaptive FIR filter algorithm

The authors propose a new robust adaptive FIR filter algorithm for system identification applications based on a statistical approach named the M estimation. The proposed robust least mean square algorithm differs from the conventional one by the insertion of a suitably chosen nonlinear transformation of the prediction residuals. The effect of nonlinearity is to assign less weight to a small portion of large residuals so that the impulsive noise in the desired filter response will not greatly influence the final parameter estimates. The convergence of the parameter estimates is established theoretically using the ordinary differential equation approach. The feasibility of the approach is demonstrated with simulations