Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks

Address event representation (AER) cameras have recently attracted more attention due to the advantages of high temporal resolution and low power consumption, compared with traditional frame-based cameras. Since AER cameras record the visual input as asynchronous discrete events, they are inherently suitable to coordinate with the spiking neural network (SNN), which is biologically plausible and energy-efficient on neuromorphic hardware. However, using SNN to perform the AER object classification is still challenging, due to the lack of effective learning algorithms for this new representation. To tackle this issue, we propose an AER object classification model using a novel segmented probability-maximization (SPA) learning algorithm. Technically, 1) the SPA learning algorithm iteratively maximizes the probability of the classes that samples belong to, in order to improve the reliability of neuron responses and effectiveness of learning; 2) a peak detection (PD) mechanism is introduced in SPA to locate informative time points segment by segment, based on which information within the whole event stream can be fully utilized by the learning. Extensive experimental results show that, compared to state-of-the-art methods, not only our model is more effective, but also it requires less information to reach a certain level of accuracy.Comment: AAAI 2020 (Oral

Revealing the mechanisms of semantic satiation with deep learning models

The phenomenon of semantic satiation, which refers to the loss of meaning of a word or phrase after being repeated many times, is a well-known psychological phenomenon. However, the microscopic neural computational principles responsible for these mechanisms remain unknown. In this study, we use a deep learning model of continuous coupled neural networks to investigate the mechanism underlying semantic satiation and precisely describe this process with neuronal components. Our results suggest that, from a mesoscopic perspective, semantic satiation may be a bottom-up process. Unlike existing macroscopic psychological studies that suggest that semantic satiation is a top-down process, our simulations use a similar experimental paradigm as classical psychology experiments and observe similar results. Satiation of semantic objectives, similar to the learning process of our network model used for object recognition, relies on continuous learning and switching between objects. The underlying neural coupling strengthens or weakens satiation. Taken together, both neural and network mechanisms play a role in controlling semantic satiation

Molecular and morphological evidence support a new species of Rosaceae Prunus subg. Cerasus from Wuyishan National Park, southeast China

Prunus tongmuensis, a new species of cherry blossom, is described and illustrated from Wuyishan National Park, southeast China. This species is characterized by its tubular to nearly bottle-shaped receptacles and dark purple drupes. It can be distinguished from other wild cherry trees by its flowers and leaves, reddish brown young leaves, presence of 1–2 glands at the base of leaves, petioles densely covered with yellowish brown villi, longer pedicels (0.6–2.5 cm), villous pistil, and dark purple drupes. In the present study, we conducted a comprehensive morphological study based on specimens of the new species and its morphologically close species, field observations, and examination of pollen morphology. In addition, our phylogenetic analysis based on the complete plastid genome sequences further confirms the status of the new species and indicates that it is closely related to Prunus clarofolia, however, it notably differs in leaf shape, size, petiole villus color, gland location, timing of flower and leaf openings, and reflexed or spread sepals, as well as drupe color

Adaptive and learning control for SI engine model with uncertainties

Air-fuel ratio control is a challenging control problem for port-fuel-injected and throttle-body-fuel-injected spark ignition (SI) engines, since the dynamics of air manifold and fuel injection of the SI engines are highly nonlinear and often with unmodeled uncertainties and disturbance. This paper presents nonlinear control approaches for multi-input multi-output engine models, by developing adaptive control and learning control design methods. Theoretical proofs are established that ensure that proposed controllers are able to give asymptotical tracking performance. As a comparison, the method applying global linearizing controller can give accurate tracking for the engine model without uncertainty and disturbance, but it fails to keep tracking performance when uncertainty is incorporated into the system. Adaptive control and learning control approaches are capable of dealing with both constant uncertainty and time-varying periodic uncertainty. Simulation results illustrate the efficacy of the proposed controllers

Engine control design using globally linearizing control and sliding mode

In this paper the control design methods for spark ignition engine models are discussed. Both single-input single-output (SISO) and multi-input multi-output (MIMO) systems are investigated for the design of an engine control system. A comprehensive comparative study for two classes of non-linear control methods, i.e. globally linearizing control (GLC) and sliding mode control, is given. The simulations results are presented to illustrate the capability and performance of the two kinds of controllers. The results show that the controller applying GLC can give accurate tracking for the engine model without uncertainty and disturbance; however, it fails to keep good tracking performance when uncertainty is considered. In contrast, the controller using the sliding mode is able to achieve the target, which shows that the engine system with the proposed sliding mode controller has good robustness to uncertainty and disturbance. © 2010 The Institute of Measurement and Control

Molecular and morphological evidence support a new species of Rosaceae Prunus subg. Cerasus from Wuyishan National Park, southeast China

Prunus tongmuensis, a new species of cherry blossom, is described and illustrated from Wuyishan National Park, southeast China. This species is characterized by its tubular to nearly bottle-shaped receptacles and dark purple drupes. It can be distinguished from other wild cherry trees by its flowers and leaves, reddish brown young leaves, presence of 1–2 glands at the base of leaves, petioles densely covered with yellowish brown villi, longer pedicels (0.6–2.5 cm), villous pistil, and dark purple drupes. In the present study, we conducted a comprehensive morphological study based on specimens of the new species and its morphologically close species, field observations, and examination of pollen morphology. In addition, our phylogenetic analysis based on the complete plastid genome sequences further confirms the status of the new species and indicates that it is closely related to Prunus clarofolia, however, it notably differs in leaf shape, size, petiole villus color, gland location, timing of flower and leaf openings, and reflexed or spread sepals, as well as drupe color

Multifaceted cytoprotection by synthetic polyacetylenes inspired by the ginseng-derived natural product, panaxytriol

We describe herein the discovery of a series of panaxytriol (PXT)-derived polyacetylene small molecules with promising cytoprotective activity. In mouse xenograft models, we have demonstrated the capacity of our synthetic analogs to mitigate a range of cancer therapeutic agent-induced toxicities, including body weight loss, lethality, neurotoxicity, and hematotoxicity. Our PXT analogs have also been found to reduce radiation-induced body weight loss and lethality in mouse models. Moreover, several PXT analogs appear to exhibit moderate in vivo antiinflammatory activity as well as in vitro immunoenhancing capabilities. These compounds appear to derive their activity through induction of cancer preventive phase 2 enzymes. The studies described herein suggest that coadministration of a PXT-derived agent with cancer chemotherapeutics or radiation therapy may serve to mitigate a range of therapy-associated toxicities

Favorable Interactions between Enfuvirtide and 1-β-d-2,6-Diaminopurine Dioxolane In Vitro

We evaluated the in vitro anti-human immunodeficiency virus type 1 (HIV-1) interactions between 1- β-d-2,6-diaminopurine dioxolane (DAPD) and enfuvirtide (T-20) against clinical isolates sensitive and resistant to reverse transcriptase and protease inhibitors. Interactions between T-20 and DAPD were synergistic to nearly additive, with combination index values ranging from 0.53 to 1.06 at 95% inhibitory concentrations. These studies suggest that a combination of T-20 and DAPD might be useful in the treatment of antiretroviral drug-experienced patients