Memristive Devices and Systems: Modeling, Properties and Applications

Copyright © 2023 The Authors. The memristor is considered to be a promising candidate for next-generation computing systems due to its nonvolatility, high density, low power, nanoscale geometry, nonlinearity, binary/multiple memory capacity, and negative differential resistance. [...]This research received no external funding

Epigenetic inactivation of the miR-34a in hematological malignancies

miR-34a is a transcriptional target of p53 and implicated in carcinogenesis. We studied the role of miR-34a methylation in a panel of hematological malignancies including acute leukemia [acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL)], chronic leukemia [chronic lymphocytic leukemia (CLL) and chronic myeloid leukemia (CML)], multiple myeloma (MM) and non-Hodgkin's lymphoma (NHL). The methylation status of miR-34a promoter was studied in 12 cell lines and 188 diagnostic samples by methylation-specific polymerase chain reaction. miR-34a promoter was unmethylated in normal controls but methylated in 75% lymphoma and 37% myeloma cell lines. Hypomethylating treatment led to re-expression of pri-miR-34a transcript in lymphoma cells with homozygous miR-34a methylation. In primary samples at diagnosis, miR-34a methylation was detected in 4% CLL, 5.5% MM samples and 18.8% of NHL at diagnosis but none of ALL, AML and CML (P = 0.011). In MM patients with paired samples, miR-34a methylation status remained unchanged at progression. Amongst lymphoid malignancies, miR-34a was preferentially methylated in NHL (P = 0.018), in particular natural killer (NK)/T-cell lymphoma. In conclusion, amongst hematological malignancies, miR-34a methylation is preferentially hypermethylated in NHL, in particular NK/T-cell lymphoma, in a tumor-specific manner, therefore the role of miR-34a in lymphomagenesis warrants further study. © The Author 2010. Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected]

A Brain-Inspired In-Memory Computing System for Neuronal Communication via Memristive Circuits

This work was supported in part by the National Natural Science Foundation of China under Grant U1909201 and Grant 62001149, and the Natural Science Foundation of Zhejiang Province under Grant LQ21F010009

Design and Implementation of a Flexible Neuromorphic Computing System for Affective Communication via Memristive Circuits

National Natural Science Foundation of China under Grant 62001149, Natural Science Foundation of Zhejiang Province under Grant LQ21F010009 and Fundamental Research funds for the provincial Universities of Zhejiang under Grant GK229909299001-06

A physics-oriented memristor model with the coexistence of NDR effect and RS memory behavior for bio-inspired computing

Bio-inspired computing promises fundamentally different ways to advances in artificial intelligence with extreme energy efficiency. Memristive technologies due to the non-volatility, high density, low-power, and synaptic bionic properties can help in realizing bio-inspired architecture and its hardware implementation. This paper proposes a novel physics-oriented memristor model with coexistence of negative differential resistance (NDR) effect and resistive switching (RS) memory behavior for bio-inspired computing. Firstly, an Ag/TiOx/FTO memristor is fabricated using sol-gel and magnetron sputtering method, and its performance test demonstrates that the coexistence of NDR effect and RS memory behavior can be modulated by the moisture. Then, a physical-oriented memristor model is constructed, which provides the possibility to explore the dynamics of the coexistence of NDR effect and RS memory behavior in simulation. Furthermore, a memristor-based affective computing circuit emulating the process of human affective associative learning is designed. The experiment demonstrates that the coexistence of NDR effect and RS memory behavior can change the memory time without additional circuit and cost, which is expected to realize the automatic conversion from short-term memory to long-term memory in bio-inspired computing.National Natural Science Foundation of China under Grant 62001149 and Natural Science Foundation of Zhejiang Province under Grant LQ21F010009

Memristive Circuit Design of Sequencer Network for Human Emotion Classification

Mental health problem is an increasingly common social issue leading to diseases such as depression, addiction, and heart attack. Facial expression is one of the most natural and universal signals for human beings to convey their emotional states and behavior intentions. Numerous studies have been conducted on automatic human emotion classification that can effectively establish the relationship between facial expression and mental health, while still suffer from intensive computation and low efficiency. Here, we present a memristive circuit design of Sequencer network for human emotion classification, which offers an environmentally friendly approach with low cost and easily deployable hardware. Specifically, a kind of eco-friendly memristor is fabricated using two-dimensional (2D) materials, and the corresponding testing performance is conducted to make sure its efficiency and stability. Then, the memristor-based Sequencer block, as a core component of Sequencer network, consisting of bidirectional long short-term memory (BiLSTM) circuit and some necessary function circuit modules is proposed. Based on this, the memristive Sequencer network can be achieved. Furthermore, the proposed memristive Sequencer network is applied for human emotion classification. The experimental results demonstrate that the proposed circuit has advantages in computational efficiency and cost, comparable to the main existing software-based methods.National Natural Science Foundation of China (grant no. 62001149) and the Natural Science Foundation of Zhejiang Province (grant no. LQ21F010009)

Fractional crystallization of monosulfide solid solution from sulfide liquids lead to the PGE enrichment in the Jinchuan Ni-Cu sulfide deposit, western China

Discordant lenses of Pt-Pd enriched zones (ores bearing up to 1.0 ppm of Pt or Pd) have recently been identified in the sulfide-bearing peridotite of the Jinchuan Cu-Ni-PGE (Platinum group element) sulfide deposit, China. Chalcopyrite, pyrrhotite, and pentlandite occur in both Pt-Pd enriched zones and normal ores, but Cu-bearing minerals such as cubanite and Bi-, Te-, and As-bearing minerals are more abundant in the Pt-Pd enriched zones. Sperrylite is the major Pt-host minerals in the Pt-Pd enriched zones interstinally and occurs mainly as euhedral grains within base-metal sulfides which occur among the cumulates of olivine. PGE-enrichment is found only in sulfide-bearing samples. In orebody # 1 and orebody 24, Rh, Ru, and Ir are positively correlated, but a negative Ir-Pd and Ir-Pt correlation. However in orebody 2 Rh, Ru, Pt, Pd and Ir are positively correlated. Taken together, the elemental correlations and mineralogical data support a model for the origin of Pt-Pd rich ores in Orebody 1 and Orebody 24 of the Jinchuan deposit are consistent with fractional crystallization of monosulfide solid solution from sulfide liquids on cooling; The origin of Orebody 2 involves variable magma/sulfide liquid mass ratios (R-factors).published_or_final_versio

A Brain-inspired Hierarchical Interactive In-memory Computing System and its Application in Video Sentiment Analysis

Fundamental Research Funds for the Provincial University of Zhejiang (Grant Number: GK229909299001-06); 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62001149); 10.13039/501100004731-Natural Science Foundation of Zhejiang Province (Grant Number: LQ21F010009)

A Flexible Memristor Model with Electronic Resistive Switching Memory Behavior and its Application in Spiking Neural Network

National Natural Science Foundation of China under Grant U1909201, Grant 62001149; Natural Science Foundation of Zhejiang Province under Grant LQ21F010009

EMSN: An Energy-Efficient Memristive Sequencer Network for Human Emotion Classification in Mental Health Monitoring

Fundamental Research Funds for the Provincial University of Zhejiang (Grant Number: GK229909299001-06); 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62001149); Natural Science Foundation of Zhejiang Province (Grant Number: LQ21F010009)