Signal Processing
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2021 ◽  
Bianca Pircher ◽  
Thomas Pircher ◽  
Andreas Feigenspan

Glutamate is an essential neurotransmitter for signal processing in the vertical pathway of the mammalian retina, where it is involved in the distribution of visual information into several parallel channels. The excitatory effects of glutamate are mediated by AMPA-, kainate-, and NMDA-type ionotropic glutamate receptors (iGluRs). The expression patterns of these receptors in the vertebrate retina have been investigated so far with mainly immunocytochemical, in-situ hybridization, and electrophysiological/pharmacological techniques. Here, we have used scRNA sequencing data from chicken, mouse, macaque, and human retina to describe and compare the profile of iGluR expression in major retinal cell types across species. Our results suggest that major retinal cell types each express a unique set of iGluRs with substantial differences between non-mammalian and mammalian retinae. Expression of iGluRs has been investigated in more detail for amacrine and bipolar cell types of the human retina, each showing minor variations of a common pattern. The differential expression of iGluRs is likely to convey unique signal processing properties to individual elements of the retinal circuitry.

2021 ◽  
Ryan H Boe ◽  
Vinay Ayyappan ◽  
Lea Schuh ◽  
Arjun Raj

Accurately functioning genetic networks should be responsive to signals but prevent transmission of stochastic bursts of expression. Existing data in mammalian cells suggests that such transcriptional "noise" is transmitted by some genes and not others, suggesting that noise transmission is tunable, perhaps at the expense of other signal processing capabilities. However, systematic claims about noise transmission in genetic networks have been limited by the inability to directly measure noise transmission. Here we build a mathematical framework capable of modeling allelic correlation and noise transmission. We find that allelic correlation and noise transmission correspond across a broad range of model parameters and network architectures. We further find that limiting noise transmission comes with the trade-off of being unresponsive to signals, and that within the parameter regimes that are responsive to signals, there is a further trade-off between response time and basal noise transmission. Using a published allele specific single cell RNA-sequencing dataset, we found that genes with high allelic odds ratios are enriched for cell-type specific functions, and that within multiple signaling pathways, factors which are upstream in the pathway have higher allelic odds ratios than downstream factors. Overall, our findings suggest that some degree of noise transmission is required to be responsive to signals, but that minimization of noise transmission can be accomplished by trading-off for a slower response time.

Anuranjan Pandey

Abstract: In the tropical jungle, hearing a species is considerably simpler than seeing it. The sounds of many birds and frogs may be heard if we are in the woods, but the bird cannot be seen. It is difficult in this these circumstances for the expert in identifying the many types of insects and harmful species that may be found in the wild. An audio-input model has been developed in this study. Intelligent signal processing is used to extract patterns and characteristics from the audio signal, and the output is used to identify the species. Sound of the birds and frogs vary according to their species in the tropical environment. In this research we have developed a deep learning model, this model enhances the process of recognizing the bird and frog species based on the audio features. The model achieved a high level of accuracy in recognizing the birds and the frog species. The Resnet model which includes block of simple and convolution neural network is effective in recognizing the birds and frog species using the sound of the animal. Above 90 percent of accuracy is achieved for this classification task. Keywords: Bird Frog Detection, Neural Network, Resnet, CNN.

2021 ◽  
Vol 4 (1) ◽  
Vincent Mukwaya ◽  
Stephen Mann ◽  
Hongjing Dou

AbstractAlthough the complexity of synthetic cells has continued to increase in recent years, chemical communication between protocell models and living organisms remains a key challenge in bottom-up synthetic biology and bioengineering. In this Review, we discuss how communication channels and modes of signal processing can be established between living cells and cytomimetic agents such as giant unilamellar lipid vesicles, proteinosomes, polysaccharidosomes, polymer-based giant vesicles and membrane-less coacervate micro-droplets. We describe three potential modes of chemical communication in consortia of synthetic and living cells based on mechanisms of distributed communication and signal processing, physical embodiment and nested communication, and network-based contact-dependent communication. We survey the potential for applying synthetic cell/living cell communication systems in biomedicine, including the in situ production of therapeutics and development of new bioreactors. Finally, we present a short summary of our findings.

2021 ◽  
Maksym Popov ◽  
Igor Zavislyak ◽  
Hongwei Qu ◽  
A. M. Balbashov ◽  
M. R. Page ◽  

Abstract This report is on the observation and analysis of nonlinear magnetoelectric effects (NLME) for in-plane currents perpendicularly to the hexagonal axis in single crystals and liquid phase epitaxy grown thin films of barium hexaferrite. Measurements involved tuning of ferromagnetic resonance (FMR) at 56-58 GHz in the multidomain and single domain states in the ferrite by applying a current. Data on the shift in the resonance frequency with input electric power was utilized to estimate the variations in the magnetic parameter that showed a linear dependence on the input electric power. The NLME tensor coefficients were determined form the estimated changes in the magnetization and uniaxial anisotropy field. The estimated NLME coefficients for in-plane currents are shown to be much higher than for currents flowing along the hexagonal axis. Although the frequency shift of FMR was higher for the single domain resonance, the multi-domain configuration is preferable for device applications since it eliminates the need for a large bias magnetic field. Thus, multidomain resonance with current in the basal plane is favorable for use in electrically tunable miniature, ferrite microwave signal processing devices requiring low operating power.

2021 ◽  
Vol 11 (23) ◽  
pp. 11110
Oleksiy Borysenko ◽  
Svitlana Matsenko ◽  
Vjaceslavs Bobrovs

This paper presents and first scientifically substantiates the generalized theory of binomial number systems (BNS) and the method of their formation for reliable digital signal processing (DSP), transmission, and data storage. The method is obtained based on the general theory of positional number systems (PNS) with conditions and number functions for converting BNS with a binary alphabet, also allowing to generate matrix BNS, linear-cyclic, and multivalued number systems. Generated by BNS, binomial numbers possess the error detection property. A characteristic property of binomial numbers is the ability, on their basis, to form various combinatorial configurations based on the binomial coefficients, e.g., compositions or constant-weight (CW) codes. The theory of positional binary BNS construction and generation of binary binomial numbers are proposed. The basic properties and possible areas of application of BNS researched, particularly for the formation and numbering of combinatorial objects, are indicated. The CW binomial code is designed based on binary binomial numbers with variable code lengths. BNS is efficiently used to develop error detection digital devices and has the property of compressing information.

Diego Di Carlo ◽  
Pinchas Tandeitnik ◽  
Cedrić Foy ◽  
Nancy Bertin ◽  
Antoine Deleforge ◽  

AbstractThis paper presents a new dataset of measured multichannel room impulse responses (RIRs) named dEchorate. It includes annotations of early echo timings and 3D positions of microphones, real sources, and image sources under different wall configurations in a cuboid room. These data provide a tool for benchmarking recent methods in echo-aware speech enhancement, room geometry estimation, RIR estimation, acoustic echo retrieval, microphone calibration, echo labeling, and reflector position estimation. The dataset is provided with software utilities to easily access, manipulate, and visualize the data as well as baseline methods for echo-related tasks.


Abstract Gabardo and Nashed [‘Nonuniform multiresolution analyses and spectral pairs’, J. Funct. Anal.158(1) (1998), 209–241] have introduced the concept of nonuniform multiresolution analysis (NUMRA), based on the theory of spectral pairs, in which the associated translated set $\Lambda =\{0,{r}/{N}\}+2\mathbb Z$ is not necessarily a discrete subgroup of $\mathbb{R}$ , and the translation factor is $2\textrm{N}$ . Here r is an odd integer with $1\leq r\leq 2N-1$ such that r and N are relatively prime. The nonuniform wavelets associated with NUMRA can be used in signal processing, sampling theory, speech recognition and various other areas, where instead of integer shifts nonuniform shifts are needed. In order to further generalize this useful NUMRA, we consider the set $\widetilde {\Lambda }=\{0,{r_1}/{N},{r_2}/{N},\ldots ,{r_q}/{N}\}+s\mathbb Z$ , where s is an even integer, $q\in \mathbb {N}$ , $r_i$ is an integer such that $1\leq r_i\leq sN-1,\,(r_i,N)=1$ for all i and $N\geq 2$ . In this paper, we prove that the concept of NUMRA with the translation set $\widetilde {\Lambda }$ is possible only if $\widetilde {\Lambda }$ is of the form $\{0,{r}/{N}\}+s\mathbb Z$ . Next we introduce $\Lambda _s$ -nonuniform multiresolution analysis ( $\Lambda _s$ -NUMRA) for which the translation set is $\Lambda _s=\{0,{r}/{N}\}+s\mathbb Z$ and the dilation factor is $sN$ , where s is an even integer. Also, we characterize the scaling functions associated with $\Lambda _s$ -NUMRA and we give necessary and sufficient conditions for wavelet filters associated with $\Lambda _s$ -NUMRA.

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