FPGA-Based CNN Inference Accelerator Synthesized from Multi-Threaded C Software

A deep-learning inference accelerator is synthesized from a C-language software program parallelized with Pthreads. The software implementation uses the well-known producer/consumer model with parallel threads interconnected by FIFO queues. The LegUp high-level synthesis (HLS) tool synthesizes threads into parallel FPGA hardware, translating software parallelism into spatial parallelism. A complete system is generated where convolution, pooling and padding are realized in the synthesized accelerator, with remaining tasks executing on an embedded ARM processor. The accelerator incorporates reduced precision, and a novel approach for zero-weight-skipping in convolution. On a mid-sized Intel Arria 10 SoC FPGA, peak performance on VGG-16 is 138 effective GOPS

Cardiac Troponin Assessment Following Atrial Fibrillation Ablation: Implications for Chest Pain Evaluation

Background: The range of elevation of troponin I (tI) that is within expected limits from left atrial radiofrequency ablation for atrial fibrillation (AF) is not well described, though such information may be of clinical value. Objectives: Identify the expected range of tI values post-atrial fibrillation (AF) ablation. Methods: 31 patients undergoing AF ablation had a single tI level drawn the day following the procedure. Clinical variables were also collected, such as ablation type and radiofrequency (RF) time. Results: Paroxysmal AF was present in 23 patients, and 8 had chronic AF. The average RF time was 2627.8 ± 737.5 seconds. The mean RF power was 61.7 ± 4.3W (range 55-70W). The mean RF temperature limit was 53.6 ± 2.0°C (range 50-55°C). There was no clinical or electrocardiographic evidence of coronary ischemia in this population. The mean tI the following day was 3.21 ± 1.5 (range 1.48-8.41). There was no correlation between RF time, ablation type, ablation catheter size, and ablation temperature or ablation power and tI levels. Conclusions: Troponin I elevation post-ablation was ubiquitous. Knowledge of expected post-ablation tI levels may be helpful in the evaluation of post-procedure chest pain

Ethics of Genetic and Biomarker Test Disclosures in Neurodegenerative Disease Prevention Trials

OBJECTIVE: Prevention trials for neurodegenerative diseases use genetic or other risk marker tests to select participants but there is concern that this could involve coercive disclosure of unwanted information. This has led some trials to use blinded enrollment (participants are tested but not told of their risk marker status). We examined the ethics of blinded vs transparent enrollment using well-established criteria for assessing the ethics of clinical research. METHODS: Normative analysis applying 4 key ethical criteria-favorable risk-benefit ratio, informed consent, fair subject selection, and scientific validity-to blinded vs transparent enrollment, using current evidence and state of Alzheimer disease (AD) and other prevention trials. RESULTS: Current evidence on the psychosocial impact of risk marker disclosure and considerations of scientific benefit do not support an obligation to use blinded enrollment in prevention trials. Nor does transparent enrollment coerce or involve undue influence of potential participants. Transparent enrollment does not unfairly exploit vulnerable participants or limit generalizability of scientific findings of prevention trials. However, if the preferences of a community of potential participants would affect the rigor or feasibility of a prevention trial using transparent enrollment, then investigators are required by considerations of scientific validity to use blinded enrollment. CONCLUSIONS: Considerations of risks and benefits, informed consent, and fair subject selection do not require the use of blinded enrollment for AD prevention trials. Blinded enrollment in AD prevention trials may sometimes be necessary because of the need for scientific validity, not because it prevents coercion or undue influence

LiSc(BH_4)_4 as a Hydrogen Storage Material: Multinuclear High-Resolution Solid-State NMR and First-Principles Density Functional Theory Studies

A lithium salt of anionic scandium tetraborohydride complex, LiSc(BH_4)_4, was studied both experimentally and theoretically as a potential hydrogen storage medium. Ball milling mixtures of LiBH_4 and ScCl_3 produced LiCl and a unique crystalline hydride, which has been unequivocally identified via multinuclear solid-state nuclear magnetic resonance (NMR) to be LiSc(BH_4)_4. Under the present reaction conditions, there was no evidence for the formation of binary Sc(BH_4)_3. These observations are in agreement with our first-principles calculations of the relative stabilities of these phases. A tetragonal structure in space group I (#82) is predicted to be the lowest energy state for LiSc(BH_4)_4, which does not correspond to structures obtained to date on the crystalline ternary borohydride phases made by ball milling. Perhaps reaction conditions are resulting in formation of other polymorphs, which should be investigated in future studies via neutron scattering on deuterides. Hydrogen desorption while heating these Li−Sc−B−H materials up to 400 °C yielded only amorphous phases (besides the virtually unchanged LiCl) that were determined by NMR to be primarily ScB_2 and [B_(12)H_(12)]^(−2) anion containing (e.g., Li_2B_(12)H_(12)) along with residual LiBH_4. Reaction of a desorbed LiSc(BH_4)_4 + 4LiCl mixture (from 4LiBH_4/ScCl_3 sample) with hydrogen gas at 70 bar resulted only in an increase in the contents of Li_2B_(12)H_(12) and LiBH_4. Full reversibility to reform the LiSc(BH_4)_4 was not found. Overall, the Li−Sc−B−H system is not a favorable candidate for hydrogen storage applications

Evaluation of simulated O-3 production efficiency during the KORUS-AQ campaign: Implications for anthropogenic NOx emissions in Korea

We examine O3 production and its sensitivity to precursor gases and boundary layer mixing in Korea by using a 3-D global chemistry transport model and extensive observations during the KORea-US cooperative Air Quality field study in Korea, which occurred in May–June 2016. During the campaign, observed aromatic species onboard the NASA DC-8 aircraft, especially toluene, showed high mixing ratios of up to 10 ppbv, emphasizing the importance of aromatic chemistry in O3 production. To examine the role of VOCs and NOx in O3 chemistry, we first implement a detailed aromatic chemistry scheme in the model, which reduces the normalized mean bias of simulated O3 mixing ratios from –26% to –13%. Aromatic chemistry also increases the average net O3 production in Korea by 37%. Corrections of daytime PBL heights, which are overestimated in the model compared to lidar observations, increase the net O3 production rate by ~10%. In addition, increasing NOx emissions by 50% in the model shows best performance in reproducing O3 production characteristics, which implies that NOx emissions are underestimated in the current emissions inventory. Sensitivity tests show that a 30% decrease in anthropogenic NOx emissions in Korea increases the O3 production efficiency throughout the country, making rural regions ~2 times more efficient in producing O3 per NOx consumed. Simulated O3 levels overall decrease in the peninsula except for urban and other industrial areas, with the largest increase (~6 ppbv) in the Seoul Metropolitan Area (SMA). However, with simultaneous reductions in both NOx and VOCs emissions by 30%, O3 decreases in most of the country, including the SMA. This implies the importance of concurrent emission reductions for both NOx and VOCs in order to effectively reduce O3 levels in Korea

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules

Motivation: Network-based genome-wide association studies (GWAS) aim to identify functional modules from biological networks that are enriched by top GWAS findings. Although gene functions are relevant to tissue context, most existing methods analyze tissue-free networks without reflecting phenotypic specificity. Results: We propose a novel module identification framework for imaging genetic studies using the tissue-specific functional interaction network. Our method includes three steps: (i) re-prioritize imaging GWAS findings by applying machine learning methods to incorporate network topological information and enhance the connectivity among top genes; (ii) detect densely connected modules based on interactions among top re-prioritized genes; and (iii) identify phenotype-relevant modules enriched by top GWAS findings. We demonstrate our method on the GWAS of [18F]FDG-PET measures in the amygdala region using the imaging genetic data from the Alzheimer's Disease Neuroimaging Initiative, and map the GWAS results onto the amygdala-specific functional interaction network. The proposed network-based GWAS method can effectively detect densely connected modules enriched by top GWAS findings. Tissue-specific functional network can provide precise context to help explore the collective effects of genes with biologically meaningful interactions specific to the studied phenotype

Testing Multiple Hypotheses through IMP weighted FDR Based on a Genetic Functional Network with Application to a New Zebrafish Transcriptome Study

In genome-wide studies, hundreds of thousands of hypothesis tests are performed simultaneously. Bonferroni correction and False Discovery Rate (FDR) can effectively control type I error but often yield a high false negative rate. We aim to develop a more powerful method to detect differentially expressed genes. We present a Weighted False Discovery Rate (WFDR) method that incorporate biological knowledge from genetic networks. We first identify weights using Integrative Multi-species Prediction (IMP) and then apply the weights in WFDR to identify differentially expressed genes through an IMP-WFDR algorithm. We performed a gene expression experiment to identify zebrafish genes that change expression in the presence of arsenic during a systemic Pseudomonas aeruginosa infection. Zebrafish were exposed to arsenic at 10 parts per billion and/or infected with P. aeruginosa. Appropriate controls were included. We then applied IMP-WFDR during the analysis of differentially expressed genes. We compared the mRNA expression for each group and found over 200 differentially expressed genes and several enriched pathways including defense response pathways, arsenic response pathways, and the Notch signaling pathway

Defining synonymous codon compression schemes by genome recoding

Synthetic recoding of genomes, to remove targeted sense codons, may facilitate the encoded cellular synthesis of unnatural polymers by orthogonal translation systems. However, our limited understanding of allowed synonymous codon substitutions, and the absence of methods that enable the stepwise replacement of the Escherichia coli genome with long synthetic DNA and provide feedback on allowed and disallowed design features in synthetic genomes, have restricted progress towards this goal. Here we endow E. coli with a system for efficient, programmable replacement of genomic DNA with long (>100-kb) synthetic DNA, through the in vivo excision of double-stranded DNA from an episomal replicon by CRISPR/Cas9, coupled to lambda-red-mediated recombination and simultaneous positive and negative selection. We iterate the approach, providing a basis for stepwise whole-genome replacement. We attempt systematic recoding in an essential operon using eight synonymous recoding schemes. Each scheme systematically replaces target codons with defined synonyms and is compatible with codon reassignment. Our results define allowed and disallowed synonymous recoding schemes, and enable the identification and repair of recoding at idiosyncratic positions in the genome

Impact of RRAM Read Fluctuations on the Program-Verify Approach

The stochastic nature of the conductive filaments in oxide-based resistive memory (RRAM) represents a sizeable impediment to commercialization. As such, program-verify methodologies are highly alluring. However, it was recently shown that program-verify methods are unworkable due to strong resistance state relaxation after SET/RESET programming. In this paper, we demonstrate that resistance state relaxation is not the main culprit. Instead, it is fluctuation-induced false-reading (triggering) that defeats the program-verify method, producing a large distribution tail immediately after programming. The fluctuation impact on the verify mechanism has serious implications on the overall write/erase speed of RRAM

Spectral Energy Distributions of Local Luminous And Ultraluminous Infrared Galaxies

Luminous and ultraluminous infrared galaxies ((U)LIRGs) are the most extreme star forming galaxies in the universe. The local (U)LIRGs provide a unique opportunity to study their multi-wavelength properties in detail for comparison to their more numerous counterparts at high redshifts. We present common large aperture photometry at radio through X-ray wavelengths, and spectral energy distributions (SEDs) for a sample of 53 nearby LIRGs and 11 ULIRGs spanning log (LIR/Lsun) = 11.14-12.57 from the flux-limited Great Observatories All-sky LIRG Survey (GOALS). The SEDs for all objects are similar in that they show a broad, thermal stellar peak and a dominant FIR thermal dust peak, where nuLnu(60um) / nuLnu(V) increases from ~2-30 with increasing LIR. When normalized at IRAS-60um, the largest range in the luminosity ratio, R(lambda)=log[nuLnu(lambda)/nuLnu(60um)] observed over the full sample is seen in the Hard X-rays (HX=2-10 keV). A small range is found in the Radio (1.4GHz), where the mean ratio is largest. Total infrared luminosities, LIR(8-1000um), dust temperatures, and dust masses were computed from fitting thermal dust emission modified blackbodies to the mid-infrared (MIR) through submillimeter SEDs. The new results reflect an overall ~0.02 dex lower luminosity than the original IRAS values. Total stellar masses were computed by fitting stellar population synthesis models to the observed near-infrared (NIR) through ultraviolet (UV) SEDs. Mean stellar masses are found to be log(M/Msun) = 10.79+/-0.40. Star formation rates have been determined from the infrared (SFR_IR~45Msun/yr) and from the monochromatic UV luminosities (SFR_UV~1.3Msun/yr), respectively. Multiwavelength AGN indicators have be used to select putative AGN: about 60% of the ULIRGs would have been classified as an AGN by at least one of the selection criteria.Comment: 39 pages, including 12 figures and 11 tables; accepted for publication in ApJ