A5037705126- Advanced Memory and Neural Computing
- Hepatocellular Carcinoma Treatment and Prognosis
- Ferroelectric and Negative Capacitance Devices
- Adversarial Robustness in Machine Learning
- Cancer, Lipids, and Metabolism
- Block Copolymer Self-Assembly
- Neural dynamics and brain function
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Sarcoma Diagnosis and Treatment
- Software-Defined Networks and 5G
- Anomaly Detection Techniques and Applications
- Advanced Graph Neural Networks
- Generative Adversarial Networks and Image Synthesis
- Pancreatic and Hepatic Oncology Research
- Polymer crystallization and properties
- Modular Robots and Swarm Intelligence
- Multiple and Secondary Primary Cancers
- EEG and Brain-Computer Interfaces
- Angiogenesis and VEGF in Cancer
- Ferroptosis and cancer prognosis
- Network Security and Intrusion Detection
- Water Quality Monitoring Technologies
- Advanced Optical Network Technologies
- Rheology and Fluid Dynamics Studies
- CAR-T cell therapy research
Tsinghua University
2020-2025
National Computer Network Emergency Response Technical Team/Coordination Center of Chinar
2019-2025
Chinese Institute for Brain Research
2025
Xinjiang Institute of Engineering
2022-2024
Hebei Provincial Center for Disease Control and Prevention
2023
Lanzhou Petrochemical Polytechnic
2023
Peking University
2019-2022
Peking University Cancer Hospital
2019-2022
King Center
2021
Beijing Advanced Sciences and Innovation Center
2020-2021
Abstract There is a growing trend to design hybrid neural networks (HNNs) by combining spiking and artificial leverage the strengths of both. Here, we propose framework for general computation HNNs introducing units (HUs) as linkage interface. The not only integrates key features these computing paradigms but also decouples them improve flexibility efficiency. HUs are designable learnable promote transmission modulation information flows in HNNs. Through three cases, demonstrate that can...
Recent advances in artificial intelligence have enhanced the abilities of mobile robots dealing with complex and dynamic scenarios. However, to enable computationally intensive algorithms be executed locally multitask low latency high efficiency, innovations computing hardware are required. Here, we report TianjicX, a neuromorphic that can support true concurrent execution multiple cross-computing-paradigm neural network (NN) models various coordination manners for robotics. With...
ABSTRACT Brain-inspired computing, drawing inspiration from the fundamental structure and information-processing mechanisms of human brain, has gained significant momentum in recent years. It emerged as a research paradigm centered on brain–computer dual-driven multi-network integration. One noteworthy instance this is hybrid neural network (HNN), which integrates computer-science-oriented artificial networks (ANNs) with neuroscience-oriented spiking (SNNs). HNNs exhibit distinct advantages...
Current artificial systems suffer from catastrophic forgetting during continual learning, a limitation absent in biological systems. Biological mechanisms leverage the dual representation of specific and generalized memories within corticohippocampal circuits to facilitate lifelong learning. Inspired by this, we develop circuits-based hybrid neural network (CH-HNN) that emulates these representations, significantly mitigating both task-incremental class-incremental learning scenarios. Our...
Memristive devices based on two-dimensional (2D) semiconducting materials have emerged as highly promising neuromorphic due to their intrinsic atomic body and unique properties. However, the migration redistribution of anions induces built-in electric field at 2D materials/electrode interface. It inevitably leads nonlinearity saturation conductance change, which are key challenges synaptic achieve high accuracy applications. In this work, we report a vertical heterostructure formed by...
Carbapenem-resistant Klebsiella pneumoniae (CRKP), as one of the most common drug-resistant bacteria threatening human health, is hyper-resistant to multiple antimicrobial drugs and carbapenems, which can be dealt with only limited clinical treatment options. This study described epidemiological characteristics CRKP in this tertiary care hospital from 2016 2020. Specimen sources included blood, sputum, alveolar lavage fluid, puncture secretions a burn wound, urine. Among 87...
Hepatocellular carcinoma (HCC) is one of the most deadly tumors. Prognosis patients with HCC generally poor due to high recurrence rate. In present study, TaqMan Real-time PCR microRNA Array was used identify differentially expressed miRNAs from 10 tumor tissue samples (5 group vs. 5 non-recurrence group) and matched serum samples. Four (miR-486–5p, miR-422a, miR-125b miR-139–5p) were further quantified in 20 tissues 116 patients' before they received hepatectomy. Univariate analysis...
Objectives: To investigate the prognosis significance of preoperative serum alpha-fetoprotein (AFP) and correlation with clinicopathological factors hepatocellular carcinoma (HCC) patients who underwent hepatectomy. Materials Methods: Clinicopathological data retrospective analysis were collected for 251 HCC undergoing hepatectomy in this study. According to AFP level, categorized into AFP-negative (0-20ng/mL) AFP-positive (>20 ng/mL) groups Kaplan-Meier Cox proportional hazard regression...
Synaptic plasticity plays a critical role in the expression power of brain neural networks. Among diverse rules, synaptic scaling presents indispensable effects on homeostasis maintenance and strength regulation. In current modeling brain-inspired spiking networks (SNN), backpropagation through time is widely adopted because it can achieve high performance using small number steps. Nevertheless, mechanism has not yet been well touched. this work, we propose an experience-dependent adaptive...
Retroperitoneal liposarcoma (RLPS) is the most common subtype of retroperitoneal soft tissue sarcoma, characterized by a high recurrence rate and insensitivity to radiotherapy chemotherapy.The function tumor microenvironmental components, especially tumor-associated fibroblasts (TAFs), remains unclear in RLPS.The crosstalk between cells stromal should be clarified for therapy target discovery RLPS.In this study, we demonstrated that TAFs from dedifferentiated (DDLPS) could attract LPS...
AIM:To describe a three-dimensional model (3DM) to accurately reconstruct anatomic relationships of centrally located hepatocellular carcinomas (HCCs). METHODS:From March 2013 July 2014, reconstructions and visual simulations HCCs were performed in 39 patients using 3D subject-based computed tomography (CT) with customdeveloped software.CT images used for the reconstruction Couinaud's pedicles hepatic veins, calculation corresponding tumor territories segments was Yorktal DMIT software.The...
The effect of geometrical asymmetry β (described by the length-diameter ratio rods) on rod-coil diblock copolymer phase behavior is studied implementation self-consistent field theory (SCFT) in three-dimensional (3D) position space while considering rod orientation spherical surface. diagrams at different show that aspect rods influences not only order-disorder transition (ODT) but also order-order (OOT). By exploring diagram with interactions between and coils plotted against β, similar to...
Hepatocellular adenomas (HCAs), with a risk of malignant transformation into hepatocellular carcinoma (HCC), classically develop in young women who are taking oral contraceptives. It is now clear that HCAs may also occur men. However, it rarely reported male patients non-cirrhotic livers. This study aimed to characterize the malignancy occurring patients.All underwent hepatectomy at Cancer Institute and Hospital, Chinese Academy Medical Sciences Peking Union College between January 1, 1999...
Biological spiking neurons with intrinsic dynamics underlie the powerful representation and learning capabilities of brain for processing multimodal information in complex environments. Despite recent tremendous progress neural networks (SNNs) handling Euclidean-space tasks, it still remains challenging to exploit SNNs non-Euclidean-space data represented by graph data, mainly due lack effective modeling framework useful training techniques. Here we present a general spike-based that enables...
We employ a rod–coil multiblock molecular chain model to investigate folding behavior, which is significant characteristic in semicrystalline polymers, by using the method of self-consistent field theory (SCFT).
As the representatives of brain-inspired models at neuronal level, spiking neural networks (SNNs) have shown great promise in processing spatiotemporal information with intrinsic temporal dynamics. SNNs are expected to further improve their robustness and computing efficiency by introducing top-down attention architectural which is crucial for human brain support advanced intelligence. However, this attempt encounters difficulties optimizing largely due lack annotations. Here, we develop a...
CD8-PE 1.98% 4.56% 1.56% 1.01% 4.61% 1.99% CD4-APC (d) Control group Reserpine SJZ0.2 SJZ0.6 SJZ1
Service Function Chaining (SFC) has received considerable attentions due to its potential in remarkably improving the flexibility and efficiency of networks. Network Functions Virtualization (NFV) Software-Defined Networking (SDN) are becoming promising ways for realizing SFC. A key feature SDN/NFV networks is capability dynamically composing network functions into complex services. In this paper, we first introduce SFC instantiation form it as model Shortest Path Tour Problem, then find...
On the basis of self-consistent field theory (SCFT), we demonstrate that X-shaped rod–coil molecules with hydrogen-bonding groups self-assemble into Archimedean tiling patterns including [36], [44], [63], [3.4.6.4], and [(3.6)2], dual dual-[32.4.3.4]. The rod blocks form edges polygons, coil fill in inner spaces existence hydrogen bonds further decreases domain size. A new mechanism is proposed to guide formation patterns: fabrication controlled by relationship between length–diameter ratio...