Artificial Optoelectronic Synapse Based on Violet Phosphorus Microfiber Arrays.

Memristor-based artificial synapses are regarded as the most promising candidate to develop brain-like neuromorphic network computers and overcome the bottleneck of Von-Neumann architecture. Violet phosphorus (VP) as a new allotrope of available phosphorus with outstanding electro-optical properties and stability has attracted more and more attention in the past several years. In this study, large-scale, high-yield VP microfiber vertical arrays have been successfully developed on a Sn-coated graphite paper and are used as the memristor functional layers to build reliable, low-power artificial synaptic devices. The VP devices can well mimic the major synaptic functions such as short-term memory (STM), long-term memory (LTM), paired-pulse facilitation (PPF), spike timing-dependent plasticity (STDP), and spike rate-dependent plasticity (SRDP) under both electrical and light stimulation conditions, even the dendritic synapse functions and simple logical operations. By virtue of the excellent performance, the VP artificial synapse devices can be conductive to building high-performance optic-neural synaptic devices simulating the human-like optic nerve system. On this basis, Pavlov's associative memory can be successfully implemented optically. This study provides a promising approach for the design and manufacture of VP-based artificial synaptic devices and outlines a direction with multifunctional neural devices.

SiC@NiO Core-Shell Nanowire Networks-Based Optoelectronic Synapses for Neuromorphic Computing and Visual Systems at High Temperature.

1D nanowire networks, sharing similarities of structure, information transfer, and computation with biological neural networks, have emerged as a promising platform for neuromorphic systems. Based on brain-like structures of 1D nanowire networks, neuromorphic synaptic devices can overcome the von Neumann bottleneck, achieving intelligent high-efficient sensing and computing function with high information processing rates and low power consumption. Here, high-temperature neuromorphic synaptic devices based on SiC@NiO core-shell nanowire networks optoelectronic memristors (NNOMs) are developed. Experimental results demonstrate that NNOMs attain synaptic short/long-term plasticity and modulation plasticity under both electrical and optical stimulation, and exhibit advanced functions such as short/long-term memory and "learning-forgetting-relearning" under optical stimulation at both room temperature and 200 °C. Based on the advanced functions under light stimulus, the constructed 5 × 3 optoelectronic synaptic array devices exhibit a stable visual memory function up to 200 °C, which can be utilized to develop artificial visual systems. Additionally, when exposed to multiple electronic or optical stimuli, the NNOMs effectively replicate the principles of Pavlovian classical conditioning, achieving visual heterologous synaptic functionality and refining neural networks. Overall, with abundant synaptic characteristics and high-temperature thermal stability, these neuromorphic synaptic devices offer a promising route for advancing neuromorphic computing and visual systems.

A non-metallic SERS-based immunoassay founded by light-harvesting effect and strengthened chemical enhancement.

Owing to its promising biocompatibility and reliable sensitivity, semiconductor-guided surface-enhanced Raman scattering (SERS) technology has aroused widespread concern in clinical immunoassays. Herein, the well-improved light capture capability of MoS2 with a novel three-dimensional (3D) flower-like morphology was combined with the synergistic chemical enhancement from a MoS2@red phosphorus (RP) hybrid system, facilitating an attractive non-metallic SERS-based detection of ferritin in serum. Owing to the remarkable enhancement factors of both the immunoprobe and immunosubstrate, which were comparable to noble metal, an extremely low limit detection of 11.5 pg mL-1 was achieved in the absence of fluorescence interference. In particular, the trace ferritin in the clinical serum sample was successfully monitored, demonstrating superior sensitivity to the traditional chemiluminescent method. Overall, this study convincingly revealed the feasibility and reliability of SERS-based immunoassays induced by biocompatible semiconductors, which has opened a new way to implement the detection and tracking of biomarkers in the human body.

Meroterpenoids from Daphne genkwa shows promising in vitro antitumor activity via inhibiting PI3K/Akt/mTOR signaling pathway in A549 cells.

Phytochemical investigation into the leaves and branches of Daphne genkwa afforded 25 meroterpenoids (1-16) including nine pairs of enantiomers (1a/1b-8a/8b and 12a/12b), among which 20 compounds have been reported in the present work for the first time. The structures with absolute configurations of the new molecules (excluding 10-13) were established via comprehensive spectroscopic analyses especially electronic circular dichroism (ECD) and Mosher's methods. A preliminary in vitro cell viability assay revealed remarkable cytotoxicities of selective compounds against A549 (lung), Hela (cervical), MDA-MB231 (breast) and MCF-7 (breast) cancer cells, and compound 8a showed the best inhibitory activity with IC50 values in the range of 3.12-4.67 µM toward the four cell lines. Subsequent in vitro antitumor evaluation of 8a disclosed that it could inhibit the proliferation and metastasis, as well as induce significant apoptosis and cycle arrest, of A549 cells. Further mechanistic investigations revealed that 8a could exert its antitumor activity via inhibiting the PI3K/Akt/mTOR signaling pathway.

Exploring the Lifelong Changes of Interaction between Cingulo-Opercular Network and Other Cognitive Control Related Functional Networks Based on Multiple Connectivity Indices.

BACKGROUND: The cingulo-opercular network (CON) has been proposed to play a central role in cognitive control. The lifetime change mechanism of its integrity and interaction with other cognitive control-related functional networks (CCRNs) is closely associated with developing cognitive control behaviors but needs further elucidation. METHODS: The resting-state functional magnetic resonance imaging data were recorded from 207 subjects, who were divided into three age groups: age 4-20, 21-59, and 60-85 years old. For each group, multiple indices (cross-correlation, total independence, and Granger causality) within CON and between CON and other cognitive control-related functional networks (dorsal attention network, DAN; central executive network, CEN; default mode network, DMN) were calculated and correlated with age to yield maps that delineated the changing pattern of CON-related interaction. RESULTS: We found three main results. (1) The connectivity indices within the CON and between CON and the other three CCRNs showed significant enhancement from childhood to early adulthood (age 4-20 years), (2) mild attenuation within CON from early adulthood to middle age (age 21-59 years), and (3) significant attenuation within CON and between CON and DMN in the elder group (age 60-85 years). CONCLUSIONS: The results indicated the prominently increased integrity of within-CON and CON-CCRNs communication, mildly weakened within-CON communication, and significantly attenuated within-CON and CON-DMN communication, characterizing distinct changing patterns of CON-interaction at three different stages that covered a life-long span.

Structures and Electronic and Hydrogen Storage Properties of Magnesium Scandium Hydrides.

MgH2 is well known as a potential hydrogen storage material. However, its high thermodynamic stability, high dissociation temperature, slow absorption, and desorption kinetics severely limit its application. Aiming at these shortcomings, we try to improve the hydrogen storage property of MgH2 by doping with transition metal Sc atoms. The structures and electronic and hydrogen storage properties of Mg-Sc-H systems have been systematically studied by combining the crystal structure analysis by particle swarm optimization and density functional theory method. The results show that the structure of MgScH8 with the R3 space group is the most stable one, which is proved to be a wide-band gap (2.96 eV) semiconductor. The possible decomposition pathways, which are crucial for the applicability of R3-MgScH8 as a hydrogen storage material, are studied, and the pathway of MgScH8 → ScH6 + Mg + H2 is found to be the most favorable one under 107.8 GPa pressure, while above 107.8 GPa, MgScH8 → Mg + Sc + 4H2 becomes the most thermodynamically stable pathway and releases the maximum amount of hydrogen. Based on the root mean square deviation calculation, it is found that R3-MgScH8 begins to melt at 400 K. The result of ab initio molecular dynamics simulations shows that the hydrogen release capacity (4.04 wt %) can be easily achieved at 500 K, thus making MgScH8 a potential hydrogen storage material.

Estimating critical values from electrocardiogram using a deep ordinal convolutional neural network.

BACKGROUND: Critical values are commonly used in clinical laboratory tests to define health-related conditions of varying degrees. Knowing the values, people can quickly become aware of health risks, and the health professionals can take immediate actions and save lives. METHODS: In this paper, we propose a method that extends the concept of critical value to one of the most commonly used physiological signals in the clinical environment-Electrocardiogram (ECG). We first construct a mapping from common ECG diagnostic conclusions to critical values. After that, we build a 61-layer deep convolutional neural network named CardioV, which is characterized by an ordinal classifier. RESULTS: We conduct experiments on a large public ECG dataset, and demonstrate that CardioV achieves a mean absolute error of 0.4984 and a ROC-AUC score of 0.8735. In addition, we find that the model performs better for extreme critical values and the younger age group, while gender does not affect the performance. The ablation study confirms that the ordinal classification mechanism suits for estimating the critical values which contain ranking information. Moreover, model interpretation techniques help us discover that CardioV focuses on the characteristic ECG locations during the critical value estimation process. CONCLUSIONS: As an ordinal classifier, CardioV performs well in estimating ECG critical values that can help people quickly identify different heart conditions. We obtain ROC-AUC scores above 0.8 for all four critical value categories, and find that the extreme values (0 (no risk) and 3 (high risk)) have better model performance than the other two (1 (low risk) and 2 (medium risk)). Results also show that gender does not affect the performance, and the older age group has worse performance than the younger age group. In addition, visualization techniques reveal that the model pays more attention to characteristic ECG locations.

Robust Template Matching Using Multiple-Layered Absent Color Indexing.

Color is an essential feature in histogram-based matching. This can be extracted as statistical data during the comparison process. Although the applicability of color features in histogram-based techniques has been proven, position information is lacking during the matching process. We present a conceptually simple and effective method called multiple-layered absent color indexing (ABC-ML) for template matching. Apparent and absent color histograms are obtained from the original color histogram, where the absent colors belong to low-frequency or vacant bins. To determine the color range of compared images, we propose a total color space (TCS) that can determine the operating range of the histogram bins. Furthermore, we invert the absent colors to obtain the properties of these colors using threshold hT. Then, we compute the similarity using the intersection. A multiple-layered structure is proposed against the shift issue in histogram-based approaches. Each layer is constructed using the isotonic principle. Thus, absent color indexing and multiple-layered structure are combined to solve the precision problem. Our experiments on real-world images and open data demonstrated that they have produced state-of-the-art results. Moreover, they retained the histogram merits of robustness in cases of deformation and scaling.

Identification of the prognostic value of ferroptosis-related gene signature in breast cancer patients.

BACKGROUND: Breast cancer (BRCA) is a malignant tumor with high morbidity and mortality, which is a threat to women's health worldwide. Ferroptosis is closely related to the occurrence and development of breast cancer. Here, we aimed to establish a ferroptosis-related prognostic gene signature for predicting patients' survival. METHODS: Gene expression profile and corresponding clinical information of patients from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) database. The Least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analysis model was utilized to construct a multigene signature. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and single-sample gene set enrichment analysis (ssGSEA) were performed for patients between the high-risk and low-risk groups divided by the median value of risk score. RESULTS: We constructed a prognostic signature consisted of nine ferroptosis-related genes (ALOX15, CISD1, CS, GCLC, GPX4, SLC7A11, EMC2, G6PD and ACSF2). The Kaplan-Meier curves validated the fine predictive accuracy of the prognostic signature (p < 0.001). The area under the curve (AUC) of the ROC curves manifested that the ferroptosis-related signature had moderate predictive power. GO and KEGG functional analysis revealed that immune-related responses were largely enriched, and immune cells, including activated dendritic cells (aDCs), dendritic cells (DCs), T-helper 1 (Th1), were higher in high-risk groups (p < 0.001). Oppositely, type I IFN response and type II IFN response were lower in high-risk groups (p < 0.001). CONCLUSION: Our study indicated that the ferroptosis-related prognostic signature gene could serve as a novel biomarker for predicting breast cancer patients' prognosis. Furthermore, we found that immunotherapy might play a vital role in therapeutic schedule based on the level and difference of immune-related cells and pathways in different risk groups for breast cancer patients.

Circulatory CD4-Positive T-Lymphocyte Imbalance Mediated by Homocysteine-Induced AIM2 and NLRP1 Inflammasome Upregulation and Activation Is Associated with Human Abdominal Aortic Aneurysm.

INTRODUCTION: CD4-positive T lymphocytes (CD4 cells) play a significant role in human abdominal aortic aneurysm (AAA). However, we know little about the role of the different CD4 subtypes. OBJECTIVE: We aimed to discover the circulatory CD4 phenotypic marker profile and the roles of the newly found T helper cell 9 (Th9) and follicular helper T cells (Tfh) and that of inflammasomes in CD4 cells from AAA patients. METHODS: We extracted CD4 cells from 30 AAA patients and 21 age-matched controls. Phenotype-specific transcription factors (TFs) and inflammasomes were analyzed with qRT-PCR. RESULTS: Th17-, Th1-, Th9-, and Tfh-specific TFs and inflammasome components NLRP1 (NLR family pyrin domain-containing 1), NLRP3, NLRC4, AIM2 (absent in melanoma 2), PYCARD (apoptosis speck-like protein containing a CARD), and CASP1 (caspase 1) were upregulated, and T regulatory cell- and Th2-specific TFs were downregulated in the patients' peripheral blood CD4 cells. Homocysteine was involved in Tfh and Th17 imbalance by AIM2 and NLRP1 inflammasome upregulation. Blood total cholesterol level correlated positively with NLRP1 expression, and blood low-density lipoprotein level correlated negatively with FOXP3 expression. CONCLUSIONS: Inflammasome-induced CD4 cell imbalance was involved in AAA. We thought that AAA might be a consequence of synergism between systemic immune imbalance and local autoimmunity.

A deformable model for navigated laparoscopic gastrectomy based on finite elemental method.

Background: Accurate registration for surgical navigation of laparoscopic surgery is highly challenging due to vessel deformation. Here, we describe the design of a deformable model with improved matching accuracy by applying the finite element method (FEM).Material and methods: ANSYS software was used to simulate an FEM model of the vessel after pull-up based on laparoscopic gastrectomy requirements. The central line of the FEM model and the central line of the ground truth were drawn and compared. Based on the material and parameters determined from the animal experiment, a perigastric vessel FEM model of a gastric cancer patient was created, and its accuracy in a laparoscopic gastrectomy surgical scene was evaluated.Results: In the animal experiment, the FEM model created with Ogden foam material exhibited better results. The average distance between the two central lines was 6.5mm, and the average distance between their closest points was 3.8 mm. In the laparoscopic gastrectomy surgical scene, the FEM model and the true artery deformation demonstrated good coincidence.Conclusion: In this study, a deformable vessel model based on FEM was constructed using preoperative CT images to improve matching accuracy and to supply a reference for further research on deformation matching to facilitate laparoscopic gastrectomy navigation.

Magnetite hollow microspheres with a broad absorption bandwidth of 11.9 GHz: toward promising lightweight electromagnetic microwave absorption.

High-performance magnetite-based hollow spheres with the advantages of low density and low loading content are promising as an ideal lightweight electromagnetic (EM) wave absorption candidate. However, the effective preparation methods for these hollow spheres are still limited, and as a result, materials design and practical applications based on their size-dependent EM microwave attenuation properties are poorly accessible. In this study, high quality magnetite hollow spheres were successfully prepared by a simple, fast, one-step, and scalable plasma dynamic method with sole use of inexpensive precursors (oxygen and mild steel). The experimental results reveal that the as-prepared products are hollowed multiple-component magnetite spheres and have a very wide size distribution with a diameter of several tens of nanometers to hundreds of micrometers, which can be further separated into three fractions with different particle size distributions (0-30 µm, 30-100 µm, and >100 µm) by a simple magnetic separation method. The EM wave absorption results demonstrate that the hollow microspheres can exhibit excellent absorption ability with an effective absorption bandwidth (reflection loss ≤-10 dB) of 11.9 GHz from 3.7 to 15.6 GHz for an only 2 mm thick test absorber (50 wt% filler) and a maximum RL value of -36 dB at ∼8.2 GHz. Moreover, the positions of these resonant absorption peaks strongly depend on the sphere sizes and can be regulated at the L + C band, X band, and Ku band. Strikingly, differing from the nearly negligible microwave absorption for the ground powders, the dominating absorption mechanism for the hollow microspheres could be ascribed to the enhanced magnetic loss and multiple scattering due to the novel hollow magnetic structures, which are beneficial for the attenuation ability and improvements to their permeability and impedance matching.

General strategy for fabricating thoroughly mesoporous nanofibers.

Recently, preparation of mesoporous fibers has attracted extensive attentions because of their unique and broad applications in photocatalysis, optoelectronics, and biomaterials. However, it remains a great challenge to fabricate thoroughly mesoporous nanofibers with high purity and uniformity. Here, we report a general, simple and cost-effective strategy, namely, foaming-assisted electrospinning, for producing mesoporous nanofibers with high purity and enhanced specific surface areas. As a proof of concept, the as-fabricated mesoporous TiO2 fibers exhibit much higher photocatalytic activity and stability than both the conventional solid counterparts and the commercially available P25. The abundant vapors released from the introduced foaming agents are responsible for the creation of pores with uniform spatial distribution in the spun precursor fibers. The present work represents a critically important step in advancing the electrospinning technique for generating mesoporous fibers in a facile and universal manner.

Characterization of two homogalacturonan pectins with immunomodulatory activity from green tea.

Two natural homogalacturonan (HG) pectins (MW ca. 20 kDa) were isolated from green tea based on their immunomodulatory activity. The crude tea polysaccharides (TPS1 and TPS2) were obtained from green tea leaves by hot water extraction and followed by 40% and 70% ethanol precipitation, respectively. Two homogenous water soluble polysaccharides (TPS1-2a and TPS1-2b) were obtained from TPS1 after purification with gel permeation, which gave a higher phagocytic effect than TPS2. A combination of composition, methylation and configuration analyses, as well as NMR (nuclear magnetic resonance) spectroscopy revealed that TPS1-2a and TPS1-2b were homogalacturonan (HG) pectins consisting of a backbone of 1,4-linked α-D-galacturonic acid (GalA) residues with 28.4% and 26.1% of carboxyl groups as methyl ester, respectively. The immunological assay results demonstrated that TPS1-2, which consisted mainly of HG pectins, showed phagocytosis-enhancing activity in HL-60 cells.

TiO2 nanotube arrays-based photoelectrocatalyst: Tri-Doping engineering and carbon coating engineering boosting visible activity, and stable hydrogen evolution.

The integration of non-metallic doping and carbon coating for TiO2-based photoelectrocatalysts can be recognized as a promising strategy to enhance their hydrogen production performance. To this end, this study explored the carbon coating engineering to induce stable multi-element doping with an aim to develop high-performance TiO2 nanotube array-based photoelectrocatalysts. The resulting structures consisted of carbon-nitrogen-sulfur-tri-doped TiO2 nanotube arrays with a nitrogen-sulfur-codoped carbon coating (CNS-TNTA/NSC). The fabrication process involved a one-step, low-cost strategy of the carbon-coated tridoped reaction confined in vacuum space, utilizing polymer thiourea sealed in a controlled environment. Compared the photocurrent density of CNS-TNTA/NSC with pristine TNTA, the photocurrent enhancement of approximately 18.3-fold under simulated sunlight and a remarkable increase of 32.8-fold under simulated visible light conditions. The enhanced photocatalytic activity under visible light was ascribed to two factors: First, C, N, and S tri-doping and Ti3+ created a diverse array of impurity energy levels within the band gap, which synergistically narrowed the band gap and further enhanced response to the visible light range. Second, the presence of a carbon coating shell doped with N and S can greatly promote electron transfer and efficient electron-hole pair separation. This study could provide significant insights concerning the design of sophisticated photoanodes.

Renewable symmetric supercapacitors assembled with lignin nanoparticles-based thin film electrolyte and carbon aerogel electrodes.

Lignin as a natural biopolymer is becoming increasingly in demand due to its eco-friendly properties, while lignin-based electrolyte with high conductivity and reliable durability for applications in supercapacitors is still challenging. Herein, a facile method to prepare lignin nanoparticles (LNPs)-based solid electrolyte thin film (LF) was proposed through chemical cross-linking reaction. The fabricated LF exhibited a distinctive spongy porous structure with the ionic conductivity of 3.26 mS cm-1, demonstrating the exceptional flexibility and favorable mechanical properties. Moreover, the assembly of all-LNPs-based symmetric supercapacitor (SSC) devices was achieved using LF electrolyte and LCA electrodes for the first time, confirming the LF3 electrolyte superior to commercial cellulose separator in capacitive behaviour. This SSC device exhibited a specific capacitance of 122.7 F g-1 at 0.5 A g-1 and the maximum energy density of 17.04 W h kg-1. Furthermore, the incorporation of sodium alginate (SA) significantly enhanced the ionic conductivity of SA/LF3 electrolyte, and the resulting SSC device delivered a higher specific capacitance of 174.5 F g-1 at 0.5 A g-1 and the maximum energy and power densities of 24.24 W h kg-1 and 5023 W kg-1, respectively. This study proposes a promising approach for sustainable utilization of lignin in energy storage applications.

Screening Tool for Paroxysmal Atrial Fibrillation Based on a Deep-Learning Algorithm Using Printed 12-Lead Electrocardiographic Records during Sinus Rhythm.

Background: Recent advancements in artificial intelligence (AI) have significantly improved atrial fibrillation (AF) detection using electrocardiography (ECG) data obtained during sinus rhythm (SR). However, the utility of printed ECG (pECG) records for AF detection, particularly in developing countries, remains unexplored. This study aims to assess the efficacy of an AI-based screening tool for paroxysmal AF (PAF) using pECGs during SR. Methods: We analyzed 5688 printed 12-lead SR-ECG records from 2192 patients admitted to Beijing Chaoyang Hospital between May 2011 to August 2022. All patients underwent catheter ablation for PAF (AF group) or other electrophysiological procedures (non-AF group). We developed a deep learning model to detect PAF from these printed SR-ECGs. The 2192 patients were randomly assigned to training (1972, 57.3% with PAF), validation (108, 57.4% with PAF), and test datasets (112, 57.1% with PAF). We developed an applet to digitize the printed ECG data and display the results within a few seconds. Our evaluation focused on sensitivity, specificity, accuracy, F1 score, the area under the receiver-operating characteristic curve (AUROC), and precision-recall curves (PRAUC). Results: The PAF detection algorithm demonstrated strong performance: sensitivity 87.5%, specificity 66.7%, accuracy 78.6%, F1 score 0.824, AUROC 0.871 and PRAUC 0.914. A gradient-weighted class activation map (Grad-CAM) revealed the model's tailored focus on different ECG areas for personalized PAF detection. Conclusions: The deep-learning analysis of printed SR-ECG records shows high accuracy in PAF detection, suggesting its potential as a reliable screening tool in real-world clinical practice.

Highly Promising 2D/1D BP-C/CNT Bionic Opto-Olfactory Co-Sensory Artificial Synapses for Multisensory Integration.

The development of high-performance artificial synaptic neuromorphic devices poses a significant challenge in the creation of biomimetic sensing neural systems that seamlessly integrate both sensory and computational functionalities. In pursuit of this objective, promising bionic opto-olfactory co-sensory artificial synapse devices are constructed utilizing the BP-C/CNT (2D/1D) hybrid filter membrane as the resistive layer. Experimental results demonstrated that the devices seamlessly integrated the light modulation, gas detection, and biological synaptic functions into a single device while addressing the challenge with separating artificial synaptic devices from sensors. These devices offered the following advantages: 1) Simulating visual synapses, they can effectively replicate fundamental synaptic functions under both electrical and optical stimulation. 2) By emulating olfactory synapse responses to specific gases, they can achieve ultra-low detection limits and rapid identification of ethanol and acetone gases. 3) They enable photo-olfactory co-sensing simulations that mimic synaptic function under light-modulated pulse conditions in distinct gas environments, facilitating the study of synaptic learning rules and Pavlovian responses. This work provides a pioneering approach for exploring highly stable 2D BP-based optoelectronics and advancing the development of biomimetic neural systems.

Harnessing a silicon carbide nanowire photoelectric synaptic device for novel visual adaptation spiking neural networks.

Visual adaptation is essential for optimizing the image quality and sensitivity of artificial vision systems in real-world lighting conditions. However, additional modules, leading to time delays and potentially increasing power consumption, are needed for traditional artificial vision systems to implement visual adaptation. Here, an ITO/PMMA/SiC-NWs/ITO photoelectric synaptic device is developed for compact artificial vision systems with the visual adaption function. The theoretical calculation and experimental results demonstrated that the heating effect, induced by the increment light intensity, leads to the photoelectric synaptic device enabling the visual adaption function. Additionally, a visual adaptation artificial neuron (VAAN) circuit was implemented by incorporating the photoelectric synaptic device into a LIF neuron circuit. The output frequency of this VAAN circuit initially increases and then decreases with gradual light intensification, reflecting the dynamic process of visual adaptation. Furthermore, a visual adaptation spiking neural network (VASNN) was constructed to evaluate the photoelectric synaptic device based visual system for perception tasks. The results indicate that, in the task of traffic sign detection under extreme weather conditions, an accuracy of 97% was achieved (which is approximately 12% higher than that without a visual adaptation function). Our research provides a biologically plausible hardware solution for visual adaptation in neuromorphic computing.

[Discussion on the quality marker of rehmanniae radix praeparata in the Chinese Pharmacopoeia].

OBJECTIVE: In the Chinese Pharmacopoeia (2010 edition), the minimum limit of verbascoside (acteoside) in Rehmanniae Radix Praeparata (RRP) was set at 0.20%, the rationality of the standard was evaluated in this paper. METHODS: 10 samples of Rehmanniae Radix (RR) and RRP were collected or prepared. According to the traditional method, different samples of RRP were prepared from the same batch of RR, and the content of verbascoside was determined by HPLC. RESULTS: The average content of verbascoside in RR and RRP was 0.0226% and 0.0097%, respectively, and their difference was up to the level of P < 0.01. The content of verbascoside was found decreased with processing time increasing. Long-time storage also results in substantial loss of verbascoside. CONCLUSION: Processing results in verbascoside decreasing significantly. It is unreasonable that RR and RRP have the same standard in the content of verbascoside. It is suggested that the maximum limit of verboscoside should be set in the new version of Chinese pharmacopoeia.