Target-Aware Neural Architecture Search and Deployment for Keyword Spotting

Keyword spotting (KWS) utilities have become increasingly popular on a wide range of mobile and home devices, representing a prolific application field for Convolutional Neural Networks (CNNs), which are commonly exploited to perform keyword classification. Addressing the challenges of targeting such resource-constrained platforms, requires a careful definition of the CNN architecture and the overall system implementation. These reasons have led to a growing need for design and optimization flows, able to intrinsically take into account the system's performance when ported on the target platform. In this work, we present a design methodology based on Neural Architecture Search, exploited to combine the exploration of the optimal network topology, the audio pre-processing scheme, and the data quantization policy. The proposed design flow includes target-awareness in the exploration loop, comparing the different design alternatives according to a model-based pre-evaluation of metrics like execution latency, memory footprint, and energy consumption, evaluated considering the application's execution on the target processing platform. We have tested our design flow to obtain target-specific CNNs for a resource-constrained commercial platform, the ST SensorTile. Considering two different application scenarios, enabling the comparison with the state-of-the-art of efficient CNN-based models for KWS, we have obtained up to a 1.8% accuracy improvement and a 40% footprint reduction in the most favorable case

Aminoacid substitutions in the glycine zipper affect the conformational stability of amyloid beta fibrils

The aggregation of amyloid-beta peptides is associated with the pathogenesis of Alzheimer’s disease. The hydrophobic core of the amyloid beta sequence contains a GxxxG repeated motif, called glycine zipper, which involves crucial residues for assuring stability and promoting the process of fibril formation. Mutations in this motif lead to a completely different oligomerization pathway and rate of fibril formation. In this work, we have tested G33L and G37L residue substitutions by molecular dynamics simulations. We found that both protein mutations may lead to remarkable changes in the fibril conformational stability. Results suggest the disruption of the glycine zipper as a possible strategy to reduce the aggregation propensity of amyloid beta peptides. On the basis of our data, further investigations may consider this key region as a binding site to design/discover novel effective inhibitors. Communicated by Ramaswamy H. Sarma

Neuraghe: Exploiting CPU-FPGA synergies for efficient and flexible CNN inference acceleration on zynQ SoCs

Deep convolutional neural networks (CNNs) obtain outstanding results in tasks that require human-level understanding of data, like image or speech recognition. However, their computational load is significant, motivating the development of CNN-specialized accelerators. This work presents NEURAghe, a flexible and efficient hardware/software solution for the acceleration of CNNs on Zynq SoCs. NEURAghe leverages the synergistic usage of Zynq ARM cores and of a powerful and flexible Convolution-Specific Processor deployed on the reconfigurable logic. The Convolution-Specific Processor embeds both a convolution engine and a programmable soft core, releasing the ARM processors from most of the supervision duties and allowing the accelerator to be controlled by software at an ultra-fine granularity. This methodology opens the way for cooperative heterogeneous computing: While the accelerator takes care of the bulk of the CNN workload, the ARM cores can seamlessly execute hard-to-accelerate parts of the computational graph, taking advantage of the NEON vector engines to further speed up computation. Through the companion NeuDNN SW stack, NEURAghe supports end-to-end CNN-based classification with a peak performance of 169GOps/s and an energy efficiency of 17GOps/W. Thanks to our heterogeneous computing model, our platform improves upon the state-of-the-art, achieving a frame rate of 5.5 frames per second (fps) on the end-to-end execution of VGG-16 and 6.6fps on ResNet-18

The impact of natural compounds on s-shaped aβ42 fibril: From molecular docking to biophysical characterization

The pursuit for effective strategies inhibiting the amyloidogenic process in neurodegenerative disorders, such as Alzheimer’s disease (AD), remains one of the main unsolved issues, and only a few drugs have demonstrated to delay the degeneration of the cognitive system. Moreover, most therapies induce severe side effects and are not effective at all stages of the illness. The need to find novel and reliable drugs appears therefore of primary importance. In this context, natural compounds have shown interesting beneficial effects on the onset and progression of neurodegenerative diseases, exhibiting a great inhibitory activity on the formation of amyloid aggregates and proving to be effective in many preclinical and clinical studies. However, their inhibitory mechanism is still unclear. In this work, ensemble docking and molecular dynamics simulations on S-shaped Aβ42 fibrils have been carried out to evaluate the influence of several natural compounds on amyloid conformational behaviour. A deep understanding of the interaction mechanisms between natural compounds and Aβ aggregates may play a key role to pave the way for design, discovery and optimization strategies toward an efficient destabilization of toxic amyloid assemblies

In silico Investigations of the Mode of Action of Novel Colchicine Derivatives Targeting β-Tubulin Isotypes: A Search for a Selective and Specific β-III Tubulin Ligand

The cardinal role of microtubules in cell mitosis makes them interesting drug targets for many pharmacological treatments, including those against cancer. Moreover, different expression patterns between cell types for several tubulin isotypes represent a great opportunity to improve the selectivity and specificity of the employed drugs and to design novel compounds with higher activity only on cells of interest. In this context, tubulin isotype βIII represents an excellent target for anti-tumoral therapies since it is overexpressed in most cancer cells and correlated with drug resistance. Colchicine is a well-known antimitotic agent, which is able to bind the tubulin dimer and to halt the mitotic process. However, it shows high toxicity also on normal cells and it is not specific for isotype βIII. In this context, the search for colchicine derivatives is a matter of great importance in cancer research. In this study, homology modeling techniques, molecular docking, and molecular dynamics simulations have been employed to characterize the interaction between 55 new promising colchicine derivatives and tubulin isotype βIII. These compounds were screened and ranked based on their binding affinity and conformational stability in the colchicine binding site of tubulin βIII. Results from this study point the attention on an amide of 4-chlorine thiocolchicine. This colchicine-derivative is characterized by a unique mode of interaction with tubulin, compared to all other compounds considered, which is primarily characterized by the involvement of the α-T5 loop, a key player in the colchicine binding site. Information provided by the present study may be particularly important in the rational design of colchicine-derivatives targeting drug resistant cancer phenotypes

Chronic Intermittent Ethanol Regulates Hippocampal GABA(A) Receptor Delta Subunit Gene Expression.

Chronic ethanol consumption causes structural and functional reorganization in the hippocampus and induces alterations in the gene expression of gamma-aminobutyric acid type A receptors (GABAARs). Distinct forced intermittent exposure models have been used previously to investigate changes in GABAAR expression, with contrasting results. Here, we used repeated cycles of a Chronic Intermittent Ethanol paradigm to examine the relationship between voluntary, dependence-associated ethanol consumption, and GABAAR gene expression in mouse hippocampus. Adult male C57BL/6J mice were exposed to four 16-h ethanol vapor (or air) cycles in inhalation chambers alternated with limited-access two-bottle choice between ethanol (15%) and water consumption. The mice exposed to ethanol vapor showed significant increases in ethanol consumption compared to their air-matched controls. GABAAR alpha4 and delta subunit gene expression were measured by qRT-PCR at different stages. There were significant changes in GABAAR delta subunit transcript levels at different time points in ethanol-vapor exposed mice, while the alpha4 subunit levels remained unchanged. Correlated concurrent blood ethanol concentrations suggested that GABAAR delta subunit mRNA levels fluctuate depending on ethanol intoxication, dependence, and withdrawal state. Using a vapor-based Chronic Intermittent Ethanol procedure with combined two-bottle choice consumption, we corroborated previous evidences showing that discontinuous ethanol exposure affects GABAAR delta subunit expression but we did not observe changes in alpha4 subunit. These findings indicate that hippocampal GABAAR delta subunit expression changes transiently over the course of a Chronic Intermittent Ethanol paradigm associated with voluntary intake, in response to ethanol-mediated disturbance of GABAergic neurotransmission

Physiological adaptations of active postmenopausal women and matched men to the multi-day Sardinia Selvaggio Blu wild trek: a gender-comparative pilot study

Purpose: To evaluate the effects of wild trekking by examining, in postmenopausal women, the physiological adaptations to an intensive 5-day wild trek and comparing their responses to those displayed by a group of men of comparable age, training status and mountaineering skills. Methods: Six healthy, active postmenopausal women in their sixth decade of life participated in the study. Six men of comparable age and training status were also enrolled for gender-based comparisons. The participants traversed the Selvaggio Blu wild trek (Sardinia, Italy) completing a total of 56 km, for an overall height differential of 14,301 m. During all 5-day trek, subjects were supervised by two alpine guides. Changes in body composition, cardiorespiratory fitness, and metabolic patterns of energy expenditure were evaluated before and after the intervention. Results: Total energy expenditure during the trek was significantly higher (p = 0.03) in women (12.88 ± 3.37 kcal/h/kg) than men (9.27 ± 0.89 kcal/h/kg). Extracellular (ECW) and intracellular water (ICW) increased significantly following the trek only in women (ECW: − 3.8%; p = 0.01; ICW: + 3.4%; p = 0.01). The same applied to fat-free mass (+ 5.6%; p = 0.006), fat mass (− 20.4%; p = 0.006), skeletal muscle mass (+ 9.5%; p = 0.007), and appendicular muscle mass (+ 7.3%; p = 0.002). Peak VO2/kg (+ 9.4%; p = 0.05) and fat oxidation (at 80 W: + 26.96%; p = 0.04; at 100 W: + 40.95%; p = 0.02; at 120 W: + 83.02%; p = 0.01) were found increased only in women, although no concurrent changes in partial pressure of end-tidal CO2 (PETCO2) was observed. Conclusions: In postmenopausal women, a 5-day, intensive and physically/technically demanding outdoor trekking activity led to significant and potentially relevant changes in body composition, energy balance and metabolism that are generally attained following quite longer periods of training

Proteomic study of antibiotic resistance in Escherichia coli strains

Enteropathogen Escherichia coli infection is the most common type of colibacillosis of young animals (primarily pigs and calves), and it is cause of diarrhoea among travellers and children in the developing world. The main virulence attributes of pathogens Escherichia coli are adhesins and enterotoxins, which are mostly regulated on large plasmids. In the current study, comparative proteomics was applied to identify changes in proteins responsible for antibiotic resistance in different in vivo isolates Escherichia coli. In particular it has been studied strains with same virulence factors, but a completely different antibiotic profile, obtained from different organs of the same anima

Proteomics evaluation of molecular mechanisms involved in pathogenesis of Salmonella spp.

Salmonella species are an important group of enteric pathogens which could be penetrate the intestinal epithelial barrier and are capable of causing disease (i.e. they are pathogenic). Many foods, particularly foods of animal origin and other foods which may be subject to faecal contamination have been identified as vehicles for the transmission of this pathogen to humans. Those of particular importance include meat, poultry, eggs, milk, fruit and vegetables. Spread of this pathogen may occur in the food processing environment through cross contamination from raw food or infected food handlers. The molecular bases for Salmonella adherence to and invasion of epithelial cells are distinct and complex and a large number of Salmonella genes are required for entry into cultured epithelial cells. Salmonella enterica serotypes are closely related genetically but they are significantly different in pathogenic potentials. Deep inside the relative responsible mechanisms may be a key to more general understanding of the invasiveness of intestinal bacterial infections. This study represents a classic proteomic approach combining 2D gel electrophoresis and mass spectrometry for the comparative analysis of the proteomes of different species of Salmonella isolated from food with the principle aim to find biomarkers to understand pathogenesis mechanism