Egocentric Perception using a Biologically Inspired Software Retina Integrated with a Deep CNN

We presented the concept of of a software retina, capable of significant visual data reduction in combination with scale and rotation invariance, for applications in egocentric and robot vision at the first EPIC workshop in Amsterdam [9]. Our method is based on the mammalian retino-cortical transform: a mapping between a pseudo-randomly tessellated retina model (used to sample an input image) and a CNN. The aim of this first pilot study is to demonstrate a functional retina-integrated CNN implementation and this produced the following results: a network using the full retino-cortical transform yielded an F1 score of 0.80 on a test set during a 4-way classification task, while an identical network not using the proposed method yielded an F1 score of 0.86 on the same task. On a 40K node retina the method reduced the visual data bye×7, the input data to the CNN by 40% and the number of CNN training epochs by 36%. These results demonstrate the viability of our method and hint at the potential of exploiting functional traits of natural vision systems in CNNs. In addition, to the above study, we present further recent developments in porting the retina to an Apple iPhone, an implementation in CUDA C for NVIDIA GPU platforms and extensions of the retina model we have adopted

Emergence of a Dynamic Super-Structural Order Integrating Antiferroelectric and Antiferrodistortive Competing Instabilities in EuTiO3

Microscopic structural instabilities of EuTiO3 single crystal were investigated by synchrotron x-ray diffraction. Antiferrodistortive (AFD) oxygen octahedral rotational order was observed alongside Ti derived antiferroelectric (AFE) distortions. The competition between the two instabilities is reconciled through a cooperatively modulated structure allowing both to coexist. The electric and magnetic field effect on the modulated AFD order shows that the origin of large magnetoelectric coupling is based upon the dynamic equilibrium between the AFD - antiferromagnetic interactions versus the electric polarization - ferromagnetic interactions

LoCoH: nonparameteric kernel methods for constructing home ranges and utilization distributions.

Parametric kernel methods currently dominate the literature regarding the construction of animal home ranges (HRs) and utilization distributions (UDs). These methods frequently fail to capture the kinds of hard boundaries common to many natural systems. Recently a local convex hull (LoCoH) nonparametric kernel method, which generalizes the minimum convex polygon (MCP) method, was shown to be more appropriate than parametric kernel methods for constructing HRs and UDs, because of its ability to identify hard boundaries (e.g., rivers, cliff edges) and convergence to the true distribution as sample size increases. Here we extend the LoCoH in two ways: "fixed sphere-of-influence," or r-LoCoH (kernels constructed from all points within a fixed radius r of each reference point), and an "adaptive sphere-of-influence," or a-LoCoH (kernels constructed from all points within a radius a such that the distances of all points within the radius to the reference point sum to a value less than or equal to a), and compare them to the original "fixed-number-of-points," or k-LoCoH (all kernels constructed from k-1 nearest neighbors of root points). We also compare these nonparametric LoCoH to parametric kernel methods using manufactured data and data collected from GPS collars on African buffalo in the Kruger National Park, South Africa. Our results demonstrate that LoCoH methods are superior to parametric kernel methods in estimating areas used by animals, excluding unused areas (holes) and, generally, in constructing UDs and HRs arising from the movement of animals influenced by hard boundaries and irregular structures (e.g., rocky outcrops). We also demonstrate that a-LoCoH is generally superior to k- and r-LoCoH (with software for all three methods available at http://locoh.cnr.berkeley.edu)

A de novo reference transcriptome for Bolitoglossa vallecula, an Andean mountain salamander in Colombia

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Arenas Gomez, C. M., Woodcock, M. R., Smith, J. J., Voss, S. R., & Delgado, J. P. A de novo reference transcriptome for Bolitoglossa vallecula, an Andean mountain salamander in Colombia. Data in Brief, 29, (2020): 105256, doi:10.1016/j.dib.2020.105256.The amphibian order Caudata, contains several important model species for biological research. However, there is need to generate transcriptome data from representative species of the primary salamander families. Here we describe a de novo reference transcriptome for a terrestrial salamander, Bolitoglossa vallecula (Caudata: Plethodontidae). We employed paired-end (PE) illumina RNA sequencing to assemble a de novo reference transcriptome for B. vallecula. Assembled transcripts were compared against sequences from other vertebrate taxa to identify orthologous genes, and compared to the transcriptome of a close plethodontid relative (Bolitoglossa ramosi) to identify commonly expressed genes in the skin. This dataset should be useful to future comparative studies aimed at understanding important biological process, such as immunity, wound healing, and the production of antimicrobial compounds.This work was funded by a research grant from COLCIENCIAS 569 (GRANT 027-2103) and CODI (Programa Sostenibilidad) 2013–2014 of the University of Antioquia. A PhD fellowship to the first author, Claudia Arenas was funded by the COLCIENCIAS 567 Grant. We thank the lab of Juan Fernando Alzate from the University of Antioquia for their help in developing our bioinformatic methodological approach. We thank Andrea Gómez and Melisa Hincapie for their help in animal collection and husbandry