EventDrop: data augmentation for event-based learning

The advantages of event-sensing over conventional sensors (e.g., higher dynamic range, lower time latency, and lower power consumption) have spurred research into machine learning for event data. Unsurprisingly, deep learning has emerged as a competitive methodology for learning with event sensors; in typical setups, discrete and asynchronous events are first converted into frame-like tensors on which standard deep networks can be applied. However, over-fitting remains a challenge, particularly since event datasets remain small relative to conventional datasets (e.g., ImageNet). In this paper, we introduce EventDrop, a new method for augmenting asynchronous event data to improve the generalization of deep models. By dropping events selected with various strategies, we are able to increase the diversity of training data (e.g., to simulate various levels of occlusion). From a practical perspective, EventDrop is simple to implement and computationally low-cost. Experiments on two event datasets (N-Caltech101 and N-Cars) demonstrate that EventDrop can significantly improve the generalization performance across a variety of deep networks.Comment: IJCAI 202

Crystallization Control of N,N′-Dioctyl Perylene Diimide by Amphiphilic Block Copolymers Containing poly(3-Hexylthiophene) and Polyethylene Glycol

The preparation of micron- to nanometer-sized functional materials with well-defined shapes and packing is a key process to their applications. There are many ways to control the crystal growth of organic semiconductors. Adding polymer additives has been proven a robust strategy to optimize semiconductor crystal structure and the corresponding optoelectronic properties. We have found that poly(3-hexylthiophene) (P3HT) can effectively regulate the crystallization behavior of N,N′-dioctyl perylene diimide (C8PDI). In this study, we combined P3HT and polyethylene glycol (PEG) to amphiphilic block copolymers and studied the crystallization modification effect of these block copolymers. It is found that the crystallization modification effect of the block copolymers is retained and gradually enhanced with P3HT content. The length of C8PDI crystals were well controlled from 2 to 0.4 μm, and the width from 210 to 35 nm. On the other hand, due to the water solubility of PEG block, crystalline PEG-b-P3HT/C8PDI micelles in water were successfully prepared, and this water phase colloid could be stable for more than 2 weeks, which provides a new way to prepare pollution-free aqueous organic semiconductor inks for printing electronic devices

Opposing associations of Internet Use Disorder symptom domains with structural and functional organization of the striatum: A dimensional neuroimaging approach

Background: Accumulating evidence suggests brain structural and functional alterations in Internet Use Disorder (IUD). However, conclusions are strongly limited due to the retrospective case-control design of the studies, small samples, and the focus on general rather than symptom-specific approaches. Methods: We here employed a dimensional multi-methodical MRI-neuroimaging design in a final sample of n 5 203 subjects to examine associations between levels of IUD and its symptom-dimensions (loss of control/time management, craving/social problems) with brain structure, resting state and taskbased (pain empathy, affective go/no-go) brain function. Results: Although the present sample covered the entire range of IUD, including normal, problematic as well as pathological levels, general IUD symptom load was not associated with brain structural or functional alterations. However, the symptom-dimensions exhibited opposing associations with the intrinsic and structural organization of the brain, such that loss of control/time management exhibited negative associations with intrinsic striatal networks and hippocampal volume, while craving/social problems exhibited a positive association with intrinsic striatal networks and caudate volume. Conclusions: Our findings provided the first evidence for IUD symptom-domain specific associations with progressive alterations in the intrinsic structural and functional organization of the brain, particularly of striatal systems involved in reward, habitual and cognitive control processes

Polymorphisms at the F12 and KLKB1 loci have significant trait association with activation of the renin-angiotensin system

BACKGROUND: Plasma coagulation Factor XIIa (Hageman factor; encoded by F12) and kallikrein (KAL or Fletcher factor; encoded by KLKB1) are proteases of the kallikerin-kinin system involved in converting the inactive circulating prorenin to renin. Renin is a key enzyme in the formation of angiotensin II, which regulates blood pressure, fluid and electrolyte balance and is a biomarker for cardiovascular, metabolic and renal function. The renin-angiotensin system is implicated in extinction learning in posttraumatic stress disorder. METHODS & RESULTS: Active plasma renin was measured from two independent cohorts- civilian twins and siblings, as well as U.S. Marines, for a total of 1,180 subjects. Genotyping these subjects revealed that the carriers of the minor alleles at the two loci- F12 and KLKB1 had a significant association with reduced levels of active plasma renin. Meta-analyses confirmed the association across cohorts. In vitro studies verified digestion of human recombinant pro-renin by kallikrein (KAL) to generate active renin. Subsequently, the active renin was able to digest the synthetic substrate angiotensinogen to angiotensin-I. Examination of mouse juxtaglomerular cell line and mouse kidney sections showed co-localization of KAL with renin. Expression of either REN or KLKB1 was regulated in cell line and rodent models of hypertension in response to oxidative stress, interleukin or arterial blood pressure changes. CONCLUSIONS: The functional variants of KLKB1 (rs3733402) and F12 (rs1801020) disrupted the cascade of enzymatic events, resulting in diminished formation of active renin. Using genetic, cellular and molecular approaches we found that conversion of zymogen prorenin to renin was influenced by these polymorphisms. The study suggests that the variant version of protease factor XIIa due to the amino acid substitution had reduced ability to activate prekallikrein to KAL. As a result KAL has reduced efficacy in converting prorenin to renin and this step of the pathway leading to activation of renin affords a potential therapeutic target

Large-scale reconfiguration of connectivity patterns among attentional networks during context-dependent adjustment of cognitive control

The ability to adjust our behavior flexibly depending on situational demands and changes in the environment is an important characteristic of cognitive control. Previous studies have proved that this type of adaptive control plays a crucial role in selective attention, but have barely explored whether and how attentional networks support adaptive control. In the present study, a Stroop task with a different proportion of incongruent trials was used to investigate the brain activity and connectivity of six typical attentional control networks (i.e., the fronto-parietal network (FPN), cingulo-opercular network (CON), default mode network (DMN), dorsal attention network (DAN), and ventral attention network/salience network (VAN/SN)) in the environment with changing control demand. The behavioral analysis indicated a decreased Stroop interference (incongruent vs. congruent trial response time [RT]) with the increase in the proportion of incongruent trials within a block, indicating that cognitive control was improved there. The fMRI data revealed that the attenuate Stroop interference was accompanied by the activation of frontal and parietal regions, such as bilateral dorsolateral prefrontal cortex and anterior cingulate cortex. Crucially, the improved cognitive control induced by the increased proportion of incongruent trials was associated with the enhanced functional connectivity within the five networks, and a greater connection between CON with the DAN/SN, and between DMN with the CON/DAN/SN. Meanwhile, however, the functional coupling between the FPN and VAN was decreased. These results suggest that flexible regulations of cognitive control are implemented by the large-scale reconfiguration of connectivity patterns among the attentional networks

An Optical Neuromorphic Sensor with High Uniformity and High Linearity for Indoor Visible Light Localization

Abstract The visible light localization system holds great promise as a highly accurate indoor positioning method. However, it still suffers deficiencies including high latency and power consumption, and large area cost. To address these issues, a high energy efficient spiking localization system inspired by the biological spatial representation system is presented. This system utilizes an optical neuromorphic sensor, consisting of a compact NbOx‐based threshold switching memristor and a photoresistor. The key lies in the system's ability to convert analog light information into electrical spikes, resembling the behavior of sensory neurons, which enables the encoding of light illuminance through spiking frequency. Consequently, the system achieves high uniformity, high linearity (≈10%), and high sensitivity (≈1.1 kHz Lux−1 and ≈72.7 kHz cm−1 for light illuminance and distance detection, respectively), indicating its potential suitability for visible light localizations. By leveraging a spiking neural network classifier, the system successfully distinguishes locations with different illuminances. After 150 epochs, it achieves an accuracy of 97%, showcasing the feasibility of using the spiking localization system in real‐world applications. The approach of spike‐based light positioning is a leap forward toward the development of future compact, highly energy‐efficient visible light localization systems