Committee Machines—A Universal Method to Deal with Non-Idealities in RRAM-Based Neural Networks

Artificial neural networks (ANNs) are notoriously power- and time-consuming when implemented on conventional von Neumann computing systems. Recent years have seen an emergence of research in hardware that strives to break the bottleneck of von Neumann architecture and optimise the data flow; namely to bring memory and computing closer together. One of the most often suggested solutions is the physical implementation of ANNs in which their synaptic weights are realised with analogue resistive devices, such as resistive random-access memory (RRAM). However, various device- and system-level non-idealities usually prevent these physical implementations from achieving high inference accuracy. We suggest applying a well-known concept in computer science -- committee machine (CM) -- in the context of RRAM-based neural networks. Using simulations and experimental data from three different types of RRAM devices, we show that CMs employing ensemble averaging can successfully increase inference accuracy in physically implemented neural networks that suffer from faulty devices, programming non-linearities, random telegraph noise, cycle-to-cycle variability and line resistance. Importantly, we show that the accuracy can be improved even without increasing the number of devices

Committee Machines—A Universal Method to Deal with Non-Idealities in Memristor-Based Neural Networks

Arti ficial neural networks are notoriously power- and time-consuming when implemented on conventional von Neumann computing systems. Consequently, recent years have seen an emergence of research in machine learning hardware that strives to bring memory and computing closer together. A popular approach is to realise artifi cial neural networks in hardware by implementing their synaptic weights using memristive devices. However, various device- and system-level non-idealities usually prevent these physical implementations from achieving high inference accuracy. We suggest applying a well-known concept in computer science|committee machines|in the context of memristor-based neural networks. Using simulations and experimental data from three different types of memristive devices, we show that committee machines employing ensemble averaging can successfully increase inference accuracy in physically implemented neural networks that suffer from faulty devices, device-to-device variability, random telegraph noise and line resistance. Importantly, we demonstrate that the accuracy can be improved even without increasing the total number of memristors

Deficiency and Also Transgenic Overexpression of Timp-3 Both Lead to Compromised Bone Mass and Architecture In Vivo

Tissue inhibitor of metalloproteinases-3 (TIMP-3) regulates extracellular matrix via its inhibition of matrix metalloproteinases and membrane-bound sheddases. Timp-3 is expressed at multiple sites of extensive tissue remodelling. This extends to bone where its role, however, remains largely unresolved. In this study, we have used Micro-CT to assess bone mass and architecture, histological and histochemical evaluation to characterise the skeletal phenotype of Timp-3 KO mice and have complemented this by also examining similar indices in mice harbouring a Timp-3 transgene driven via a Col-2a-driven promoter to specifically target overexpression to chondrocytes. Our data show that Timp-3 deficiency compromises tibial bone mass and structure in both cortical and trabecular compartments, with corresponding increases in osteoclasts. Transgenic overexpression also generates defects in tibial structure predominantly in the cortical bone along the entire shaft without significant increases in osteoclasts. These alterations in cortical mass significantly compromise predicted tibial load-bearing resistance to torsion in both genotypes. Neither Timp-3 KO nor transgenic mouse growth plates are significantly affected. The impact of Timp-3 deficiency and of transgenic overexpression extends to produce modification in craniofacial bones of both endochondral and intramembranous origins. These data indicate that the levels of Timp-3 are crucial in the attainment of functionally-appropriate bone mass and architecture and that this arises from chondrogenic and osteogenic lineages

The relationships between problem characteristics, achievement-related behaviors, and academic achievement in problem-based learning

This study investigated the influence of five problem characteristics on students' achievement-related classroom behaviors and academic achievement. Data from 5,949 polytechnic students in PBL curricula across 170 courses were analyzed by means of path analysis. The five problem characteristics were: (1) problem clarity, (2) problem familiarity, (3) the extent to which the problem stimulated group discussion, (4) self-study, and (5) identification of learning goals. The results showed that problem clarity led to more group discussion, identification of learning goals, and self-study than problem familiarity. On the other hand, problem familiarity had a stronger and direct impact on academic achievement

Are tutor behaviors in problem-based learning stable? A generalizability study of social congruence, expertise and cognitive congruence

The purpose of this study was to investigate the stability of three distinct tutor behaviors (1) use of subject-matter expertise, (2) social congruence and (3) cognitive congruence, in a problem-based learning (PBL) environment. The data comprised the input from 16,047 different students to a survey of 762 tutors administered in three consecutive semesters. Over the three semesters each tutor taught two of the same course and one different course. A generalizability study was conducted to determine whether the tutor behaviors were generalizable across the three measurement occasions. The results indicate that three semesters are sufficient to make generalizations about all three tutor behaviors. In addition the results show that individual differences between tutors account for the greatest differences in levels of expertise, social congruence and cognitive congruence. The study concludes that tutor behaviors are fairly consistent in PBL and somewhat impervious to change. Implications of these findings for tutor training are discussed

Comprehensive Study in the Inhibitory Effect of Berberine on Gene Transcription, Including TATA Box

Berberine (BBR) is an established natural DNA intercalator with numerous pharmacological functions. However, currently there are neither detailed reports concerning the distribution of this alkaloid in living cells nor reports concerning the relationship between BBR's association with DNA and the function of DNA. Here we report that the distribution of BBR within the nucleus can be observed 30 minutes after drug administration, and that the content of berberine in the nucleus peaks at around 4 µmol, which is twelve hours after drug administration. The spatial conformation of DNA and chromatin was altered immediately after their association with BBR. Moreover, this association can effectively suppress the transcription of DNA in living cell systems and cell-free systems. Electrophoretic mobility shift assays (EMSA) demonstrated further that BBR can inhibit the association between the TATA binding protein (TBP) and the TATA box in the promoter, and this finding was also attained in living cells by chromatin immunoprecipitation (ChIP). Based on results from this study, we hypothesize that berberine can suppress the transcription of DNA in living cell systems, especially suppressing the association between TBP and the TATA box by binding with DNA and, thus, inhibiting TATA box-dependent gene expression in a non-specific way. This novel study has significantly expanded the sphere of knowledge concerning berberine's pharmacological effects, beginning at its paramount initial interaction with the TATA box

Search for rare quark-annihilation decays, B --> Ds(*) Phi

We report on searches for B- --> Ds- Phi and B- --> Ds*- Phi. In the context of the Standard Model, these decays are expected to be highly suppressed since they proceed through annihilation of the b and u-bar quarks in the B- meson. Our results are based on 234 million Upsilon(4S) --> B Bbar decays collected with the BABAR detector at SLAC. We find no evidence for these decays, and we set Bayesian 90% confidence level upper limits on the branching fractions BF(B- --> Ds- Phi) Ds*- Phi)<1.2x10^(-5). These results are consistent with Standard Model expectations.Comment: 8 pages, 3 postscript figues, submitted to Phys. Rev. D (Rapid Communications

Advances in the role of sacral nerve neuromodulation in lower urinary tract symptoms

Sacral neuromodulation has been developed to treat chronic lower urinary tract symptoms, resistant to classical conservative therapy. The suspected mechanisms of action include afferent stimulation of the central nervous system and modulation of activity at the level of the brain. Typical neuromodulation is indicated both in overactivity and in underactivity of the lower urinary tract. In the majority of patients, a unilateral electrode in a sacral foramen and connected to a pulse generator is sufficient to achieve significant clinical results also on long term. In recent years, other urological indications have been explored

Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure.

OBJECTIVE: We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP). METHODS: We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses. RESULTS: We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P = 4e-273) and cis-DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1. CONCLUSION: We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings

A novel TOPSIS–CBR goal programming approach to sustainable healthcare treatment

Cancer is one of the most common diseases worldwide and its treatment is a complex and time-consuming process. Specifically, prostate cancer as the most common cancer among male population has received the attentions of many researchers. Oncologists and medical physicists usually rely on their past experience and expertise to prescribe the dose plan for cancer treatment. The main objective of dose planning process is to deliver high dose to the cancerous cells and simultaneously minimize the side effects of the treatment. In this article, a novel TOPSIS case based reasoning goal-programming approach has been proposed to optimize the dose plan for prostate cancer treatment. Firstly, a hybrid retrieval process TOPSIS–CBR [technique for order preference by similarity to ideal solution (TOPSIS) and case based reasoning (CBR)] is used to capture the expertise and experience of oncologists. Thereafter, the dose plans of retrieved cases are adjusted using goal-programming mathematical model. This approach will not only help oncologists to make a better trade-off between different conflicting decision making criteria but will also deliver a high dose to the cancerous cells with minimal and necessary effect on surrounding organs at risk. The efficacy of proposed method is tested on a real data set collected from Nottingham City Hospital using leave-one-out strategy. In most of the cases treatment plans generated by the proposed method is coherent with the dose plan prescribed by an experienced oncologist or even better. Developed decision support system can assist both new and experienced oncologists in the treatment planning process