Binarized Convolutional Neural Networks with Separable Filters for Efficient Hardware Acceleration

State-of-the-art convolutional neural networks are enormously costly in both compute and memory, demanding massively parallel GPUs for execution. Such networks strain the computational capabilities and energy available to embedded and mobile processing platforms, restricting their use in many important applications. In this paper, we push the boundaries of hardware-effective CNN design by proposing BCNN with Separable Filters (BCNNw/SF), which applies Singular Value Decomposition (SVD) on BCNN kernels to further reduce computational and storage complexity. To enable its implementation, we provide a closed form of the gradient over SVD to calculate the exact gradient with respect to every binarized weight in backward propagation. We verify BCNNw/SF on the MNIST, CIFAR-10, and SVHN datasets, and implement an accelerator for CIFAR-10 on FPGA hardware. Our BCNNw/SF accelerator realizes memory savings of 17% and execution time reduction of 31.3% compared to BCNN with only minor accuracy sacrifices.Comment: 9 pages, 6 figures, accepted for Embedded Vision Workshop (CVPRW

Non-continuous piecewise nonlinear frequency modulation pulse with variable sub-pulse duration in a MIMO SAR radar system

This paper proposes an implementation of non-continuous piecewise nonlinear frequency modulation (N-PNLFM) signals in MIMO radar which are composed of a sequence of N-PNLFM subpulses. The N-PNLFM subpulse can be divided into three segments, the first and third segment are composed of linear frequency modulation (LFM) waveforms. The LFM waveforms in each N-PNLFM subpulse will be orthogonal in one sequence of our new N-PNLFM signal. A non-linear frequency modulation (NLFM) waveform is in the central component of each N-PNLFM subpulse, the bandwidths of each NLFM waveforms are distributed randomly. Each subpulse can be controlled by different variable parameters in both auto-correlation and cross-correlation functions. In order to suppress the high sidelobes in the new N-PNLFM signal and increase the diversity of signals, each subpulse duration is also distributed randomly. Our proposed PNLFM signals are optimized by applying a particle swarm optimization (PSO) algorithm. Comparing with other PNLFM signals, numerous simulations illustrate that our implementation achieves better performance

The metabolic enzyme AdhE controls the virulence of <i>Escherichia coli</i> O157:H7

Classical studies have focused on the role that individual regulators play in controlling virulence gene expression. An emerging theme, however, is that bacterial metabolism also plays a key role in this process. Our previous work identified a series of proteins that were implicated in the regulation of virulence. One of these proteins was AdhE, a bi-functional acetaldehyde-CoA dehydrogenase and alcohol dehydrogenase. Deletion of its gene (adhE) resulted in elevated levels of extracellular acetate and a stark pleiotropic phenotype: strong suppression of the Type Three Secretion System (T3SS) and overexpression of non-functional flagella. Correspondingly, the adhE mutant bound poorly to host cells and was unable to swim. Furthermore, the mutant was significantly less virulent than its parent when tested in vivo, which supports the hypothesis that attachment and motility are central to the colonization process. The molecular basis by which AdhE affects virulence gene regulation was found to be multifactorial, involving acetate-stimulated transcription of flagella expression and post-transcriptional regulation of the T3SS through Hfq. Our study reveals fascinating insights into the links between bacterial physiology, the expression of virulence genes, and the underlying molecular mechanism mechanisms by which these processes are regulated

Graphene oxide does not seem to improve the fracture properties of injection molded

ABSTRACT: Scientific literature presents a number of examples in which the mechanical properties of materials are significantly improved by adding small amounts of nano-particles. In many cases, the addition of such nano-particles is performed on polymer-matrix composites, with reported improvements in mechanical, optical, thermal or electrical properties. Therefore, the potential of this technology is huge and a great deal of research work is being performed with the aim of generating new advanced engineering materials. However, this paper presents the other side of the coin. The authors have introduced small amounts of Graphene Oxide (up to 1%) in PA6 with the aim of studying their effect on the fracture properties of the resulting composites. For the particular conditions analyzed here, no improvements in the fracture behavior (in both cracked and notched conditions) have been observed (a similar conclusion may be obtained for the tensile behavior). Other types of material properties were not covered in the analysis. Sharing this kind of (negative) results may save other researchers time and budget, and it is a much more common practice in other fields of science.The authors of this work would like to express their gratitude to the Spanish Ministry of Science and Innovation for the financial support of the project PGC2018-095400-B-I00 “Comportamiento en fractura de materiales compuestos nano-reforzados con defectos tipo entalla”, on the results of which this paper is based

Objective tropical cyclone extratropical transition detection in high‐resolution reanalysis and climate model data

This paper describes an objective technique for detecting the extratropical transition (ET) of tropical cyclones (TCs) in high‐resolution gridded climate data. The algorithm is based on previous observational studies using phase spaces to define the symmetry and vertical thermal structure of cyclones. Storm tracking is automated, allowing for direct analysis of climate data. Tracker performance in the North Atlantic is assessed using 23 years of data from the variable‐resolution Community Atmosphere Model (CAM) at two different resolutions (ΔX∼55 km and 28 km), the Climate Forecast System Reanalysis (CFSR, ΔX∼38 km), and the ERA‐Interim Reanalysis (ERA‐I, ΔX∼80 km). The mean spatiotemporal climatologies and seasonal cycles of objectively detected ET in the observationally constrained CFSR and ERA‐I are well matched to previous observational studies, demonstrating the capability of the scheme to adequately find events. High‐resolution CAM reproduces TC and ET statistics that are in general agreement with reanalyses. One notable model bias, however, is significantly longer time between ET onset and ET completion in CAM, particularly for TCs that lose symmetry prior to developing a cold‐core structure and becoming extratropical cyclones, demonstrating the capability of this method to expose model biases in simulated cyclones beyond the tropical phase.Key PointsAn objective detection technique for tracking tropical cyclone extratropical transition in gridded climate data is describedObjectively calculated extratropical transition climatology in high‐resolution reanalyses closely match observational studiesTropical cyclones in CAM take too long to undergo extratropical transition highlighting model biases requiring further investigationPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136754/1/jame20355_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136754/2/jame20355.pd

Validation of the Remote Automated ki:e Speech Biomarker for Cognition in Mild Cognitive Impairment:Verification and Validation following DiME V3 Framework

INTRODUCTION: Progressive cognitive decline is the cardinal behavioral symptom in most dementia-causing diseases such as Alzheimer's disease. While most well-established measures for cognition might not fit tomorrow's decentralized remote clinical trials, digital cognitive assessments will gain importance. We present the evaluation of a novel digital speech biomarker for cognition (SB-C) following the Digital Medicine Society's V3 framework: verification, analytical validation, and clinical validation. METHODS: Evaluation was done in two independent clinical samples: the Dutch DeepSpA (N = 69 subjective cognitive impairment [SCI], N = 52 mild cognitive impairment [MCI], and N = 13 dementia) and the Scottish SPeAk datasets (N = 25, healthy controls). For validation, two anchor scores were used: the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating (CDR) scale. RESULTS: Verification: The SB-C could be reliably extracted for both languages using an automatic speech processing pipeline. Analytical Validation: In both languages, the SB-C was strongly correlated with MMSE scores. Clinical Validation: The SB-C significantly differed between clinical groups (including MCI and dementia), was strongly correlated with the CDR, and could track the clinically meaningful decline. CONCLUSION: Our results suggest that the ki:e SB-C is an objective, scalable, and reliable indicator of cognitive decline, fit for purpose as a remote assessment in clinical early dementia trials

Identification of Neuroglycan C and Interacting Partners as Potential Susceptibility Genes for Schizophrenia in a Southern Chinese Population

Chromosome 3p was reported by previous studies as one of the regions showing strong evidence of linkage with schizophrenia. We performed a fine-mapping association study of a 6-Mb high-LD and gene-rich region on 3p in a Southern Chinese sample of 489 schizophrenia patients and 519 controls to search for susceptibility genes. In the initial screen, 4 SNPs out of the 144 tag SNPs genotyped were nominally significant (P &lt; 0.05). One of the most significant SNPs (rs3732530, P = 0.0048) was a non-synonymous SNP in the neuroglycan C (NGC, also known as CSPG5) gene, which belongs to the neuregulin family. The gene prioritization program Endeavor ranked NGC 8th out of the 129 genes in the 6-Mb region and the highest among the genes within the same LD block. Further genotyping of NGC revealed 3 more SNPs to be nominally associated with schizophrenia. Three other genes (NRG1, ErbB3, ErbB4) involved in the neuregulin pathways were subsequently genotyped. Interaction analysis by multifactor dimensionality reduction (MDR) revealed a significant two-SNP interaction between NGC and NRG1 (P = 0.015) and three-SNP interactions between NRG1 and ErbB4 (P = 0.009). The gene NGC is exclusively expressed in the brain. It is implicated in neuro-development in rats and was previously shown to promote neurite outgrowth. Methamphetamine, a drug that may induce psychotic symptoms, was reported to alter the expression of NGC Taken together, these results suggest that NGC may be a novel candidate gene, and neuregulin signaling pathways may play an important role in schizophrenia. (C) 2009 Wiley-Liss, Inc

Palladium-catalyzed heteroallylation of unactivated alkenes – synthesis of citalopram

A palladium-catalyzed difunctionalization of unactivated alkenes with tethered nucleophiles is reported. The versatile reaction occurs with simple allylic halides and can be carried out under air. The methodology provides rapid access to a wide array of desirable heterocyclic targets, as illustrated by a concise synthesis of the widely prescribed antidepressant citalopram