A scalable multi-core architecture with heterogeneous memory structures for Dynamic Neuromorphic Asynchronous Processors (DYNAPs)

Neuromorphic computing systems comprise networks of neurons that use asynchronous events for both computation and communication. This type of representation offers several advantages in terms of bandwidth and power consumption in neuromorphic electronic systems. However, managing the traffic of asynchronous events in large scale systems is a daunting task, both in terms of circuit complexity and memory requirements. Here we present a novel routing methodology that employs both hierarchical and mesh routing strategies and combines heterogeneous memory structures for minimizing both memory requirements and latency, while maximizing programming flexibility to support a wide range of event-based neural network architectures, through parameter configuration. We validated the proposed scheme in a prototype multi-core neuromorphic processor chip that employs hybrid analog/digital circuits for emulating synapse and neuron dynamics together with asynchronous digital circuits for managing the address-event traffic. We present a theoretical analysis of the proposed connectivity scheme, describe the methods and circuits used to implement such scheme, and characterize the prototype chip. Finally, we demonstrate the use of the neuromorphic processor with a convolutional neural network for the real-time classification of visual symbols being flashed to a dynamic vision sensor (DVS) at high speed.Comment: 17 pages, 14 figure

Long-term Prairie Wetlands Extraction and Change Detection with Multi-spatial and Multi-temporal Remote Sensing Data

Prairie wetlands, also called “potholes”, provide both ecological and hydrological functions and have experienced dramatic change over the past century. This research aims to: 1) compare the capacity of Landsat and SPOT in mapping open water and wet areas with advanced classification methods; 2) monitor and quantify the changes in wetlands and drainage channels, between 1948 and 2009, with aerial photography; and 3) evaluate Landsat’s ability to extract historical wetland coverage data across seasons using a variety of methods. Results indicate that Landsat is capable for mapping open water, wet areas and other LULC types in PPR; however only 48.5% of wetland areas are identified as compared with air photos. Historical analysis of air photo generated wetland and drainage channels show that the whole basin’s wetlands rapidly decreased from 1958 to 1990 (24% to 13%) and slowly decreased from 1990 to 2009 (13% to 10%) with the least reduction in sub basin 1. Drainage channels slowly increased from 1958 to 1990 (119 km to 269 km) and dramatically increased from 1990 to 2009 (269 km to 931km). Wetland area is highly correlated with accumulated snowfall in the previous three years in sub basin 2 (r=0.91, p<0.05) due to its memory effect to previous water conditions. For the full basin, however, there were not enough years of data to prove this correlation. Even though the minimum distance algorithm in early spring is optimal for mapping wetlands in the Prairie Pothole Region (PPR), comparing with air photos, SPOT imagery underestimated wetlands smaller than 1200 m2, while Landsat imagery is not able to detect wetlands smaller than 900 m2 and underestimates areas smaller than 1600 m2. Although free-archived Landsat can detect water bodies larger than 900 m2, its ability to detect prairie wetland is limited due to missing numerous small-scale wetlands and misclassification of seasonal wetlands.

Application analysis on different suture of scleral flap in trabeculectomy

AIM: To research the application of scleral flap suture in trabeculectomy. <p>METHODS: Totally 114 primary angle-closure glaucoma patients, aged from 36-72 years old, were selected as the objects, and randomly divided into research group and control group. The two groups received different administration methods. Traditional sewing method of sclera flap was used in research group and improved sewing method of sclera flap was used in control group. <p>RESULTS: There was statistical differences between postoperative intraocular pressure of the patients in the observation group and the control group after 1d; 2wk; 1, 3mo(<i>P</i><0.05). There was no statistical difference in intraocular pressure between the two groups. There was statistical differences between incidence of shallow anterior chamber of the patients in the observation group and the control group postoperatively early stage(<i>P</i><0.05). After 6mo, the filtering bleb formation in observation group was no significantly better than control group(<i>P</i>>0.05).<p>CONCLUSION: It is safe and effective that the improved sewing method of sclera flap for trabeculectomy of acute angle-closure glaucoma, and it is a better method to avoid the occurrence of shallow anterior chamber than the traditional sewing method in the early stage after operation

Adaptive motor control and learning in a spiking neural network realised on a mixed-signal neuromorphic processor

Neuromorphic computing is a new paradigm for design of both the computing hardware and algorithms inspired by biological neural networks. The event-based nature and the inherent parallelism make neuromorphic computing a promising paradigm for building efficient neural network based architectures for control of fast and agile robots. In this paper, we present a spiking neural network architecture that uses sensory feedback to control rotational velocity of a robotic vehicle. When the velocity reaches the target value, the mapping from the target velocity of the vehicle to the correct motor command, both represented in the spiking neural network on the neuromorphic device, is autonomously stored on the device using on-chip plastic synaptic weights. We validate the controller using a wheel motor of a miniature mobile vehicle and inertia measurement unit as the sensory feedback and demonstrate online learning of a simple 'inverse model' in a two-layer spiking neural network on the neuromorphic chip. The prototype neuromorphic device that features 256 spiking neurons allows us to realise a simple proof of concept architecture for the purely neuromorphic motor control and learning. The architecture can be easily scaled-up if a larger neuromorphic device is available.Comment: 6+1 pages, 4 figures, will appear in one of the Robotics conference

The role of necroptosis in common respiratory diseases in children

Studies have shown that necroptosis (NEC) relies on a unique gene-regulated molecular pathway to cause cell death. With the development of knockout mouse models and specific molecular inhibitors of necrotic proteins, this cell death pathway has been considered one of the important causes of the pathogenesis of human diseases. In this review, we explored the possible roles and mechanisms of NEC in common respiratory diseases in children, such as acute lung injury, acute respiratory distress syndrome, pulmonary infection, childhood asthma, pulmonary hypertension, etc., in order to provide new ideas for the prevention and treatment of such diseases