Random resistive memory-based deep extreme point learning machine for unified visual processing

Visual sensors, including 3D LiDAR, neuromorphic DVS sensors, and conventional frame cameras, are increasingly integrated into edge-side intelligent machines. Realizing intensive multi-sensory data analysis directly on edge intelligent machines is crucial for numerous emerging edge applications, such as augmented and virtual reality and unmanned aerial vehicles, which necessitates unified data representation, unprecedented hardware energy efficiency and rapid model training. However, multi-sensory data are intrinsically heterogeneous, causing significant complexity in the system development for edge-side intelligent machines. In addition, the performance of conventional digital hardware is limited by the physically separated processing and memory units, known as the von Neumann bottleneck, and the physical limit of transistor scaling, which contributes to the slowdown of Moore's law. These limitations are further intensified by the tedious training of models with ever-increasing sizes. We propose a novel hardware-software co-design, random resistive memory-based deep extreme point learning machine (DEPLM), that offers efficient unified point set analysis. We show the system's versatility across various data modalities and two different learning tasks. Compared to a conventional digital hardware-based system, our co-design system achieves huge energy efficiency improvements and training cost reduction when compared to conventional systems. Our random resistive memory-based deep extreme point learning machine may pave the way for energy-efficient and training-friendly edge AI across various data modalities and tasks

Modeling optimization design and amplification characteristics of O-band irregular Bragg bismuth-doped fiber amplifier

In recent years, O-band bismuth-doped fiber amplifier (BDFA) have been rapidly developed due to the fluorescence properties of bismuth-doped glass in the near-infrared (NIR) band, while there are still few studies on bismuth-doped fibers (BDF) with large mode fields as of now. In addition, although the use of a double-pass structure on the amplifier can lead to gain improvement, this also deteriorates the noise figure (NF). Therefore, the study of bismuth-doped fibers with large mode-field areas is a promising path to develop high-performance BDFA. In this work, taking a commercial bismuth-doped fiber as an instance, we first measured the refractive index distribution of the BDF in the O-band using a self-developed fiber refractive index tester, and thereby obtained its actual mode-field area. Then, based on this we further propose an irregular Bragg bismuth-doped fiber with the refractive index growing layer by layer. The results suggests that the effective mode-field area of this fiber reaches 401 um2 at 1320 nm, which is nearly 5.8 times that of a common single-mode BDF. Finally, we performed numerical simulations of the amplification performance based on this fiber. Under the condition of total pumping power of 8 W, the signal with −20 dBm input power obtains a gain of more than 54 dB and an NF of less than 5 dB at 1320 nm wavelength. This work demonstrates the great potential of this Bragg bismuth-doped fiber as an O-band high-gain amplifier and high-power laser

A liquid optical memristor using photochromic effect and capillary effect

In the era of the Internet of Things, photonic neuromorphic computing presents a promising method for real-time, local processing of vast quantities of data. However, the rigidity of materials used in such devices can considerably impact performance and longevity when subjected to mechanical deformation. In this study, we introduce a liquid optical memristor (LOM) based on an organic-inorganic hybrid in a liquid state. This novel approach offers programmable optical properties and significant mechanical flexibility thanks to the robust photochromic and capillary effects. We have developed a LOM with a 24 dB cm ^−1 modulation depth and over 3-bit nonvolatile memory states. By controlling the droplet morphology to mimic a synapse-like shape, the LOM can withstand strains over 400% and endure misalignment and bending. Furthermore, our findings substantiate the application of LOM for photonic neuromorphic computing systems, yielding 100% accuracy in pattern recognition. The easily-integratable LOM paves the way for the creation of flexible and wearable photonic neuromorphic computing systems

Genome-wide association study, population structure, and genetic diversity of the tea plant in Guizhou Plateau

Abstract Background Guizhou Plateau, as one of the original centers of tea plant, has a profound multi-ethnic cultural heritage and abundant tea germplasm resources. However, the impact of indigenous community factors on the genetic diversity, population structure and geographical distribution of tea plant is still unclear. Results Using the genotyping-by-sequencing (GBS) approach, we collected 415 tea plant accessions from the study sites, estimated genetic diversity, developed a core collection, and conducted a genome-wide association study (GWAS) based on 99,363 high-quality single-nucleotide polymorphisms (SNPs). A total of 415 tea accessions were clustered into six populations (GP01, GP02, GP03, GP04, GP05 and GP06), and the results showed that GP04 and GP05 had the highest and lowest genetic diversity (Pi = 0.214 and Pi = 0.145, respectively). Moreover, 136 tea accessions (33%) were selected to construct the core set that can represent the genetic diversity of the whole collection. By analyzing seven significant SNP markers associated with the traits such as the germination period of one bud and two leaves (OTL) and the germination period of one bud and three leaves (OtL), four candidate genes possibly related to OTL and OtL were identified. Conclusions This study revealed the impact of indigenous communities on the population structure of 415 tea accessions, indicating the importance of cultural practices for protection and utilization of tea plant genetic resources. Four potential candidate genes associated with the OTL and OtL of tea plant were also identified, which will facilitate genetic research, germplasm conservation, and breeding

The neuroanatomical basis for posterior superior parietal lobule control lateralization of visuospatial attention

The right hemispheric dominance in visuospatial attention in human brain has been well established. Converging evidence has documented that ventral posterior parietal cortex (PPC) plays an important role in visuospatial attention. The role of dorsal PPC subregions, especially the superior parietal lobule (SPL) in visuospatial attention is still controversial. In the current study, we used repetitive transcranial magnetic stimulation (rTMS) and diffusion magnetic resonance imaging (MRI) techniques to test the role of posterior SPL in visuospatial attention and to investigate the potential neuroanatomical basis for right hemisphere dominance in visuospatial function. Transcranial magnetic stimulation (TMS) results unraveled that the right SPL predominantly mediated visuospatial attention compared to left SPL. Anatomical connections analyses between the posterior SPL and the intrahemispheric frontal subregions and the contralateral PPC revealed that right posterior SPL has stronger anatomical connections with the ipsilateral middle frontal gyrus (MFG), with the ipsilateral inferior frontal gyrus (IFG), and with contralateral PPC than that of the left posterior SPL. Furthermore, these asymmetric anatomical connections were closely related to behavioral performances. Our findings indicate that SPL plays a crucial role in regulating visuospatial attention, and dominance of visuospatial attention results from unbalanced interactions between the bilateral fronto-parietal networks and the interhemispheric parietal network

2-3 μm mid-infrared luminescence of Ho3(+)/Yb(3+) co-doped chloride-modified fluorotellurite glass

International audienceIn this paper, Ho(3+)/Yb(3+) co-doped chloride-modified fluorotellurite glasses with 2-3 μm mid-infrared luminescence are prepared. By measuring and investigating the transmission spectra and emission spectra, the prepared glasses show a high transmittance (91 %) and low maximum phonon energy (813 cm(-1)). Based on the measured absorption spectra, the Judd-Ofelt parameters and radiation characteristics were calculated in depth. In addition, with the assistance of phonons, the energy transfer between Ho(3+)/Yb(3+) ions further increases the mid-infrared fluorescence intensity. The calculated emission cross-section at 2.0 μm and 2.85 μm reach 16.47 × 10(-21) cm(2) and 7.8 × 10(-21) cm(2), respectively. It is worth mentioning that the quantum efficiencies of Ho(3+): (5)I(7)→(5)I(8) and (5)I(6)→(5)I(7) reach 51.47 % and 84.14 % respectively. The results having also in mind good thermal stability (ΔT = 102℃) and refractive index (n = 1.645) indicate that this glass has a promising application for the study of fiber lasers in the mid-infrared band

Large Exchange Bias Triggered by Transition Zone of Spin Glass

Abstract Exchange bias has increasingly practical significance in magnetoresistive and spintronic devices. However, the underlying mechanism of exchange bias in bulk compounds with the structural single‐phase and inhomogeneous magnetic phases is still elusive. Herein, based on experimental and simulation results, two important parameters are studied, i.e., the antiferromagnetic (AFM) volume fraction and the ferromagnetic (FM)/AFM interface area, which essentially determine the (spontaneous) exchange bias of Mn‐rich Ni44Co6Mn44‐xSn6+x (x = 0 ∼ 6) magnetic shape memory alloys. The substitution Sn for Mn changes magnetic ground state following the sequence of superparamagnetic/AFM → dilute spin glass/AFM → transition zone → cluster spin glass/AFM → FM, accompanying the growth of FM cluster and the weakening of AFM interactions. The results reveal that the magnetic ground state for exchange bias is optimized at transition zone between dilute spin glass/strong AFM and cluster spin glass/weak AFM, in which the optimal AFM volume fraction and FM/AFM interface area are achieved by tuning magnetic fields. A giant exchange bias field of 702.7 mT and a spontaneous exchange bias field of 318.7 mT are demonstrated. The work contributes to in‐depth understanding of (spontaneous) exchange bias in magnetically inhomogeneous compounds

Functional topography of the right inferior parietal lobule structured by anatomical connectivity profiles

The nature of the relationship between structure and function is a fundamental question in neuroscience, especially at the macroscopic neuroimaging level. Although mounting studies have revealed that functional connectivity reflects structural connectivity, whether similar structural and functional connectivity patterns can reveal corresponding similarities in the structural and functional topography remains an open problem. In our current study, we used the right inferior parietal lobule (RIPL), which has been demonstrated to have similar anatomical and functional connectivity patterns at the subregional level, to directly test the hypothesis that similar structural and functional connectivity patterns can inform the corresponding topography of this area. In addition, since the association between the RIPL regions and particular functions and networks is still largely unknown, post-hoc functional characterizations and connectivity analyses were performed to identify the main functions and cortical networks in which each subregion participated. Anatomical and functional connectivity-based parcellations of the RIPL have consistently identified five subregions. Our functional characterization using meta-analysis-based behavioral and connectivity analyses revealed that the two anterior subregions (Cl1 and Cl2) primarily participate in interoception and execution, respectively; whereas the posterior subregion (Cl3) in the SMG primarily participates in attention and action inhibition. The two posterior subregions (Cl4, Cl5) in the AG were primarily involved in social cognition and spatial cognition, respectively. These results indicated that similar anatomical and functional connectivity patterns of the RIPL are reflected in corresponding structural and functional topographies. The identified cortical connectivity and functional characterization of each subregion may facilitate RIPL-related clinical research. Hum Brain Mapp, 2016. © 2016 Wiley Periodicals, Inc