Efficient CNNs via Passive Filter Pruning

Convolutional neural networks (CNNs) have shown state-of-the-art performance in various applications. However, CNNs are resource-hungry due to their requirement of high computational complexity and memory storage. Recent efforts toward achieving computational efficiency in CNNs involve filter pruning methods that eliminate some of the filters in CNNs based on the \enquote{importance} of the filters. The majority of existing filter pruning methods are either "active", which use a dataset and generate feature maps to quantify filter importance, or "passive", which compute filter importance using entry-wise norm of the filters without involving data. Under a high pruning ratio where large number of filters are to be pruned from the network, the entry-wise norm methods eliminate relatively smaller norm filters without considering the significance of the filters in producing the node output, resulting in degradation in the performance. To address this, we present a passive filter pruning method where the filters are pruned based on their contribution in producing output by considering the operator norm of the filters. The proposed pruning method generalizes better across various CNNs compared to that of the entry-wise norm-based pruning methods. In comparison to the existing active filter pruning methods, the proposed pruning method is at least 4.5 times faster in computing filter importance and is able to achieve similar performance compared to that of the active filter pruning methods. The efficacy of the proposed pruning method is evaluated on audio scene classification and image classification using various CNNs architecture such as VGGish, DCASE21_Net, VGG-16 and ResNet-50

E-PANNs: Sound Recognition Using Efficient Pre-trained Audio Neural Networks

Sounds carry an abundance of information about activities and events in our everyday environment, such as traffic noise, road works, music, or people talking. Recent machine learning methods, such as convolutional neural networks (CNNs), have been shown to be able to automatically recognize sound activities, a task known as audio tagging. One such method, pre-trained audio neural networks (PANNs), provides a neural network which has been pre-trained on over 500 sound classes from the publicly available AudioSet dataset, and can be used as a baseline or starting point for other tasks. However, the existing PANNs model has a high computational complexity and large storage requirement. This could limit the potential for deploying PANNs on resource-constrained devices, such as on-the-edge sound sensors, and could lead to high energy consumption if many such devices were deployed. In this paper, we reduce the computational complexity and memory requirement of the PANNs model by taking a pruning approach to eliminate redundant parameters from the PANNs model. The resulting Efficient PANNs (E-PANNs) model, which requires 36\% less computations and 70\% less memory, also slightly improves the sound recognition (audio tagging) performance. The code for the E-PANNs model has been released under an open source license.Comment: Accepted in Internoise 2023 conferenc

Medial prefrontal cortex population activity is plastic irrespective of learning

The prefrontal cortex is thought to learn the relationships between actions and their outcomes. But little is known about what changes to population activity in prefrontal cortex are specific to learning these relationships. Here we characterise the plasticity of population activity in the medial prefrontal cortex of male rats learning rules on a Y-maze. First, we show that the population always changes its patterns of joint activity between the periods of sleep either side of a training session on the maze, irrespective of successful rule learning during training. Next, by comparing the structure of population activity in sleep and training, we show that this population plasticity differs between learning and non-learning sessions. In learning sessions, the changes in population activity in post-training sleep incorporate the changes to the population activity during training on the maze. In non-learning sessions, the changes in sleep and training are unrelated. Finally, we show evidence that the non-learning and learning forms of population plasticity are driven by different neuron-level changes, with the non-learning form entirely accounted for by independent changes to the excitability of individual neurons, and the learning form also including changes to firing rate couplings between neurons. Collectively, our results suggest two different forms of population plasticity in prefrontal cortex during the learning of action-outcome relationships, one a persistent change in population activity structure decoupled from overt rule-learning, the other a directional change driven by feedback during behaviour

Elevated ACKR2 expression is a common feature of inflammatory arthropathies

Objectives. Chemokines are essential contributors to leucocyte accumulation at sites of inflammatory pathology. Interfering with chemokine or chemokine receptor function therefore represents a plausible therapeutic option. However, our currently limited understanding of chemokine orchestration of inflammatory responses means that such therapies have not yet been fully developed. We have a particular interest in the family of atypical chemokine receptors that fine-tune, or resolve, chemokine-driven responses. In particular we are interested in atypical chemokine receptor 2 (ACKR2), which is a scavenging receptor for inflammatory CC-chemokines and that therefore helps to resolve in vivo inflammatory responses. The objective of the current study was to examine ACKR2 expression in common arthropathies. Methods. ACKR2 expression was measured by a combination of qPCR and immuno-histochemistry. In addition, circulating cytokine and chemokine levels in patient plasma were assessed using multiplexing approaches. Results. Expression of ACKR2 was elevated on peripheral blood cells as well as on leucocytes and stromal cells in synovial tissue. Expression on peripheral blood leucocytes correlated with, and could be regulated by, circulating cytokines with particularly strong associations being seen with IL-6 and hepatocyte growth factor. In addition, expression within the synovium was coincident with aggregates of lymphocytes, potentially atopic follicles and sites of high inflammatory chemokine expression. Similarly increased levels of ACKR2 have been reported in psoriasis and SSc. Conclusion. Our data clearly show increased ACKR2 in a variety of arthropathies and taking into account our, and others’, previous data we now propose that elevated ACKR2 expression is a common feature of inflammatory pathologies

Spatiotemporal Frequency and Direction Sensitivities of Human Visual Areas Measured Using fMRI

Using functional magnetic resonance imaging (fMRI) we have studied the variation in response magnitude, in each visual area (V1–V5), as a function of spatial frequency (SF), temporal frequency (TF) and unidirectional motion versus counterphase flicker. Each visual area was identified in each subject using a combination of retinotopic mapping fMRI and cortical flattening techniques. A drifting (or counterphasing) sinusoidal grating was used as the stimulus in a study in which we parametrically varied SF between 0.4 and 7 cycles/degree and TF between 0 and 18 Hz. For each experiment we constructed fMRI amplitude tuning curves, averaged across subjects, for each visual area. The tuning curves that resulted are consistent with the known physiological properties of cells in the corresponding macaque visual areas, previous functional imaging studies, and in the case of V1, the psychophysically determined contrast sensitivity functions for spatial and temporal frequency. In the case of V3A, the SF tuning functions obtained were more similar to those found in single cell studies of macaque V3 rather than macaque V3A. All areas showed at least a moderate preference for directed versus counterphasing motion with V5 showing the largest preference. Visual areas V1, V2, V3, and V3A showed more direction sensitivity at low spatial frequencies, while VP, V4, and V5 had the highest drifting versus counterphasing ratios for higher spatial frequencies

Attentional suppression of activity in the human visual cortex

We have used fMRI to examine the nature of the changes that occur in the human visual cortex when an observer attends to a particular location in the visual image. Previous studies have shown that the magnitude of the response to a visual stimulus is increased when the observer attends to the stimulus. We show that, in addition, attention to a particular location results in a widespread suppression of activity levels at all other locations. This suggests that a key mechanism of attentional modulation may be that spontaneous (baseline) levels of neural activity are adjusted in a position-dependent manner across the entire visual field

Thrust Enhancement in Hypervelocity Nozzles by Chemical Catalysis

In the hypersonic flight regime, the air-breathing supersonic combustion ramjet (scramjet) has been shown to be a viable propulsion system. The current designs of scramjet engines provide performance benefits only up to a Mach number of 14. Performance losses increase rapidly as the Mach number increases. To extend the applicability of scram'jets beyond Mach 14, research is being conducted in the area of inlet and wave drag reduction, skin-friction and heat-transfer reduction, nozzle loss minimization, low-loss mixing, and combustion enhancement. For high Mach number applications, hydrogen is the obvious fuel choice because of its high energy content per unit mass in comparison with conventional fuels. These flight conditions require engines to operate at supersonic internal velocities, high combustor temperatures, and low static pressures. The high static temperature condition enhances the production of radicals such as H and OH, and the low-pressure condition slows the reaction rates, particularly the recombination reactions. High-temperature and low-pressure constraints, in combination with a small residence time, result in a radical-rich exhaust gas mixture exiting the combustor. At high Mach number conditions (due to low residence time), H and OH do not have enough time to recombine ; thus, a significant amount of energy is lost as these high-energy free radical are exhausted. The objective of the present study is to conduct a flowfield analysis for a typical nozzle geometry for NASP-type vehicle to assess for thrust enhancement in hypervelocity nozzles by substituting small amount of phosphine for hydrogen

Ascorbic acid, carotenoid contents and antioxidant properties of Australian summer carrot with different irrigation amounts on a free-draining, sandy soil

It is important to reduce the use of water for agricultural production in response to water scarcity and environmental concerns. The nutritive value in fruits and vegetables including carrot (Daucus carota L.), can be influenced by various climatic conditions, such as light intensity, temperature, and irrigation. The effect of differential irrigation treatments on the contents of ascorbic acid and carotenoid as well as antioxidant properties (antioxidant content, antiradical power, and antioxidant capacity) were studied in carrot (cv. Stefano) roots grown on a free-draining, sandy soil (Grey Karrakatta Sand) in the summer period. This soil has water holding capacities as low as 10-13% and requires irrigation up to 150% of class A pan evaporation (Epan) to optimize growth and quality. The irrigation treatments applied in this study consisted of 100% Epan replacement, 150% Epan replacement and crop factor. The soil water stress index calculation showed the soil water tension ranged from -2.4 to -7.6 kPa that was within the range between saturation and field capacity for sandy soil. The reduction of irrigation amount from 150% to 100% Epan did not differentiate the contents of ascorbic acid and total carotenoid, but it slightly decreased antioxidant properties of carrot grown in the free draining sandy soil