LC-TTFS: Towards Lossless Network Conversion for Spiking Neural Networks with TTFS Coding

The biological neurons use precise spike times, in addition to the spike firing rate, to communicate with each other. The time-to-first-spike (TTFS) coding is inspired by such biological observation. However, there is a lack of effective solutions for training TTFS-based spiking neural network (SNN). In this paper, we put forward a simple yet effective network conversion algorithm, which is referred to as LC-TTFS, by addressing two main problems that hinder an effective conversion from a high-performance artificial neural network (ANN) to a TTFS-based SNN. We show that our algorithm can achieve a near-perfect mapping between the activation values of an ANN and the spike times of an SNN on a number of challenging AI tasks, including image classification, image reconstruction, and speech enhancement. With TTFS coding, we can achieve up to orders of magnitude saving in computation over ANN and other rate-based SNNs. The study, therefore, paves the way for deploying ultra-low-power TTFS-based SNNs on power-constrained edge computing platforms

BEVControl: Accurately Controlling Street-view Elements with Multi-perspective Consistency via BEV Sketch Layout

Using synthesized images to boost the performance of perception models is a long-standing research challenge in computer vision. It becomes more eminent in visual-centric autonomous driving systems with multi-view cameras as some long-tail scenarios can never be collected. Guided by the BEV segmentation layouts, the existing generative networks seem to synthesize photo-realistic street-view images when evaluated solely on scene-level metrics. However, once zoom-in, they usually fail to produce accurate foreground and background details such as heading. To this end, we propose a two-stage generative method, dubbed BEVControl, that can generate accurate foreground and background contents. In contrast to segmentation-like input, it also supports sketch style input, which is more flexible for humans to edit. In addition, we propose a comprehensive multi-level evaluation protocol to fairly compare the quality of the generated scene, foreground object, and background geometry. Our extensive experiments show that our BEVControl surpasses the state-of-the-art method, BEVGen, by a significant margin, from 5.89 to 26.80 on foreground segmentation mIoU. In addition, we show that using images generated by BEVControl to train the downstream perception model, it achieves on average 1.29 improvement in NDS score.Comment: 13 pages, 8 figure

Long Short-term Memory with Two-Compartment Spiking Neuron

The identification of sensory cues associated with potential opportunities and dangers is frequently complicated by unrelated events that separate useful cues by long delays. As a result, it remains a challenging task for state-of-the-art spiking neural networks (SNNs) to identify long-term temporal dependencies since bridging the temporal gap necessitates an extended memory capacity. To address this challenge, we propose a novel biologically inspired Long Short-Term Memory Leaky Integrate-and-Fire spiking neuron model, dubbed LSTM-LIF. Our model incorporates carefully designed somatic and dendritic compartments that are tailored to retain short- and long-term memories. The theoretical analysis further confirms its effectiveness in addressing the notorious vanishing gradient problem. Our experimental results, on a diverse range of temporal classification tasks, demonstrate superior temporal classification capability, rapid training convergence, strong network generalizability, and high energy efficiency of the proposed LSTM-LIF model. This work, therefore, opens up a myriad of opportunities for resolving challenging temporal processing tasks on emerging neuromorphic computing machines

Severe Maternal Hyperglycemia Exacerbates the Development of Insulin Resistance and Fatty Liver in the Offspring on High Fat Diet

Background. Adverse maternal environments may predispose the offspring to metabolic syndrome in adulthoods, but the underlying mechanism has not been fully understood. Methods. Maternal hyperglycemia was induced by streptozotocin (STZ) injection while control (CON) rats received citrate buffer. Litters were adjusted to eight pups per dam and then weaned to standard diet. Since 13 weeks old, a subset of offspring from STZ and CON dams were switched to high fat diet (HFD) for another 13 weeks. Glucose and insulin tolerance tests (GTT and ITT) and insulin secretion assay were performed; serum levels of lipids and leptin were measured. Hepatic fat accumulation and islet area were evaluated through haematoxylin and eosin staining. Results. STZ offspring exhibited lower survival rate, lower birth weights, and growth inhibition which persisted throughout the study. STZ offspring on HFD showed more severe impairment in GTT and ITT, and more profound hepatic steatosis and more severe hyperlipidemia compared with CON-HFD rats. Conclusions. Offspring from diabetic dams would be prone to exhibit low birth weight and postnatal growth inhibition, but could maintain normal glucose tolerance and insulin sensitivity. HFD accelerates development of insulin resistance in the offspring of diabetic dams mainly via a compensatory response of islets

Three-Dimensional Simulation of the Shrinkage Behavior of Injection-Molded Poly Lactic Acid (PLA): Effects of Temperature, Shear Rate and Part Thickness

The effects of injection temperature, shear and part thickness on the linear shrinkage of injection-molded poly (lactic acid) (PLA) were intensively analyzed using the Autodesk Moldflow software. The obtained results showed that both melt temperature and shear rate had obvious effects on the linear shrinkage of PLA, i.e., the linear shrinkage of PLA increases significantly with the increase of melt temperature and shear rate. In addition, the shrinkage of high-crystallinity PLA was remarkably larger than that of low-crystallinity PLA, and thin-walled parts was larger than thick-walled ones in shrinkage

Biocontrol and Plant Growth-Promoting Activity of Rhizobacteria From Chinese Fields With Contaminatd Soils

The aim of this study was to inventory the types of plant growth‐promoting rhizobacteria (PGPR) present in the rhizosphere of plants grown in soils contaminated with heavy metals, recalcitrant organics, petroleum sewage or salinity in China. We screened 1223 isolates for antifungal activity and about 24% inhibited Rhizoctonia solani or Sclerotinia sclerotiorum. Twenty‐four strains inhibitory to R. solani, Gaeumannomyces graminis var. tritici and/or S. sclerotiorum and representing the dominant morphotypes were assayed for PGPR activity. Seven strains contained phlD, prnD, pltC or phzF genes and produced the antibiotics 2,4‐diacetylphloroglucinol, pyrrolnitrin, pyoluteorin and phenazines respectively. Six strains contained acdS, which encodes 1‐aminocyclopropane‐1‐carboxylic acid deaminase. Phylogenetic analysis of 16S rDNA and phlD, phzF and acdS genes demonstrated that some strains identified as Pseudomonas were similar to model PGPR strains Pseudomonas protegens Pf‐5, Pseudomonas chlororaphis subsp. aureofaciens 30–84 and P. brassicacearum Q8r1‐96. Pseudomonas protegens‐ and P. chlororaphis‐like strains had the greatest biocontrol activity against Rhizoctonia root rot and take‐all of wheat. Pseudomonas protegens and P. brassicacearum‐like strains showed the greatest promotion of canola growth. Our results indicate that strains from contaminated soils are similar to well‐described PGPR found in agricultural soils worldwide

Evolutionary history of two rare endemic conifer species from the eastern Qinghai-Tibet plateau

BACKGROUND AND AIMS: Understanding the population genetics and evolutionary history of endangered species is urgently needed in an era of accelerated biodiversity loss. This knowledge is most important for regions with high endemism that are ecologically vulnerable, such as the Qinghai–Tibet Plateau (QTP). METHODS: The genetic variation of 84 juniper trees from six populations of Juniperus microsperma and one population of Juniperus erectopatens, two narrow-endemic junipers from the QTP that are sister to each other, was surveyed using RNA-sequencing data. Coalescent-based analyses were used to test speciation, migration and demographic scenarios. Furthermore, positively selected and climate-associated genes were identified, and the genetic load was assessed for both species. KEY RESULTS: Analyses of 149 052 single nucleotide polymorphisms showed that the two species are well differentiated and monophyletic. They diverged around the late Pliocene, but interspecific gene flow continued until the Last Glacial Maximum. Demographic reconstruction by Stairway Plot detected two severe bottlenecks for J. microsperma but only one for J. erectopatens. The identified positively selected genes and climate-associated genes revealed habitat adaptation of the two species. Furthermore, although J. microsperma had a much wider geographical distribution than J. erectopatens, the former possesses lower genetic diversity and a higher genetic load than the latter. CONCLUSIONS: This study sheds light on the evolution of two endemic juniper species from the QTP and their responses to Quaternary climate fluctuations. Our findings emphasize the importance of speciation and demographic history reconstructions in understanding the current distribution pattern and genetic diversity of threatened species in mountainous regions