Deep neural architectures for dialect classification with single frequency filtering and zero-time windowing feature representations.

The goal of this study is to investigate advanced signal processing approaches [single frequency filtering (SFF) and zero-time windowing (ZTW)] with modern deep neural networks (DNNs) [convolution neural networks (CNNs), temporal convolution neural networks (TCN), time-delay neural network (TDNN), and emphasized channel attention, propagation and aggregation in TDNN (ECAPA-TDNN)] for dialect classification of major dialects of English. Previous studies indicated that SFF and ZTW methods provide higher spectro-temporal resolution. To capture the intrinsic variations in articulations among dialects, four feature representations [spectrogram (SPEC), cepstral coefficients, mel filter-bank energies, and mel-frequency cepstral coefficients (MFCCs)] are derived from SFF and ZTW methods.

A quantum chemical view of the interaction of RNA nucleobases and base pairs with the side chains of polar amino acids.

Hydrogen bonding between amino acids and nucleobases is important for RNA-protein recognition. As a first step toward understanding the physicochemical features of these contacts, the present work employs density functional theory calculations to critically analyze the intrinsic structures and strength of all theoretically possible model hydrogen-bonded complexes involving RNA nucleobase edges and polar amino acid side chains. Our geometry optimizations uncover a number of unique complexes that involve variable hydrogen-bonding characteristics, including conventional donor-acceptor interactions, bifurcated interactions and single hydrogen-bonded contacts.

Structural Patterns and Stabilities of Hydrogen-Bonded Pairs Involving Ribonucleotide Bases and Arginine, Glutamic Acid, or Glutamine Residues of Proteins from Quantum Mechanical Calculations.

Ribonucleotide:protein interactions play crucial roles in a number of biological processes. Unlike the RNA:protein interface where van der Waals contacts are prevalent, the recognition of a single ribonucleotide such as ATP by a protein occurs predominantly through hydrogen-bonding interactions. As a first step toward understanding the role of hydrogen bonding in ribonucleotide:protein recognition, the present work employs density functional theory to provide a detailed quantum-mechanical analysis of the structural and energetic characteristics of 18 unique hydrogen-bonded pairs involving the nucleobase/nucleoside moiety of four canonical ribonucleotides and the side chains of three polar amino-acid residues (arginine, glutamine, and glutamic acid) of proteins.

Analysis of aperiodicity in artistic Noh singing voice using an impulse sequence representation of excitation source.

Aperiodicity in the voice source is caused by changes in the vocal fold vibrations, other than the normal quasi-periodicity and the turbulence at the glottis. The aperiodicity appears to be one of the main properties that is responsible for conveying the emotion in artistic voices. In this paper, the feasibility of representing the excitation source characteristics in artistic (Noh) singing voice by an impulse-like sequence in the time domain is examined.

Interaction of aspartic acid and asparagine with RNA nucleobases: a quantum chemical view.

Communicated by Ramaswamy H. Sarma.

Subsegmental level analysis of high arousal speech using the zero-time windowing method.

Speech produced by a speaker in emotionally charged situations, such as anger, happiness, and shout corresponds to high arousal speech. Changes in the production characteristics such as increase in the subglottal air pressure, increase in the glottal closed phase in each cycle, and increase in the rate of glottal vibration are observed in the high arousal speech. Acoustic parameters such as glottal closed quotient and fundamental frequency (F) are used to characterize the high arousal speech.

BrainSegNet: a convolutional neural network architecture for automated segmentation of human brain structures.

Automated segmentation of cortical and noncortical human brain structures has been hitherto approached using nonrigid registration followed by label fusion. We propose an alternative approach for this using a convolutional neural network (CNN) which classifies a voxel into one of many structures. Four different kinds of two-dimensional and three-dimensional intensity patches are extracted for each voxel, providing local and global (context) information to the CNN.

Structural landscape of base pairs containing post-transcriptional modifications in RNA.

Base pairs involving post-transcriptionally modified nucleobases are believed to play important roles in a wide variety of functional RNAs. Here we present our attempts toward understanding the structural and functional role of naturally occurring modified base pairs using a combination of X-ray crystal structure database analysis, sequence analysis, and advanced quantum chemical methods. Our bioinformatics analysis reveals that despite their presence in all major secondary structural elements, modified base pairs are most prevalent in tRNA crystal structures and most commonly involve guanine or uridine modifications.

Effects of point mutations on the thermostability of B. subtilis lipase: investigating nonadditivity.

Molecular level understanding of mutational effects on stability and activity of enzymes is challenging particularly when several point mutations are incorporated during the directed evolution experiments. In our earlier study, we have suggested the lack of consistency in the effect of point mutations incorporated during the initial generations of directed evolution experiments, towards conformational stabilization of B. subtilis lipase mutants of later generations.

Understanding the thermostability and activity of Bacillus subtilis lipase mutants: insights from molecular dynamics simulations.

Improving the thermostability of industrial enzymes is an important protein engineering challenge. Point mutations, induced to increase thermostability, affect the structure and dynamics of the target protein in several ways and thus can also affect its activity. There appears to be no general rules for improving the thermostabilty of enzymes without adversely affecting their enzymatic activity.