A5055173266- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Mental Health Research Topics
- Advanced Neuroimaging Techniques and Applications
- Advanced MRI Techniques and Applications
- Face Recognition and Perception
- RFID technology advancements
- Cell Image Analysis Techniques
- Transcranial Magnetic Stimulation Studies
- Nanomaterials for catalytic reactions
- Bioinformatics and Genomic Networks
- Attention Deficit Hyperactivity Disorder
- Supply Chain and Inventory Management
- Traumatic Brain Injury Research
- Neural and Behavioral Psychology Studies
- Optical Imaging and Spectroscopy Techniques
- Outsourcing and Supply Chain Management
- Image Processing Techniques and Applications
- Video Analysis and Summarization
- Catalytic Processes in Materials Science
- AI in cancer detection
- E-commerce and Technology Innovations
- Phosphorus and nutrient management
- Deception detection and forensic psychology
Sichuan University
2015-2024
Institute of Process Engineering
2023
Propagation des Ondes : Étude Mathématique et Simulation
2022
West China Medical Center of Sichuan University
2020
Chengdu University of Information Technology
2015-2019
Peking University
2018
University of Electronic Science and Technology of China
2009-2018
Hangzhou Dianzi University
2018
University of Macau
2014
RobotSystem (Czechia)
2013
Abstract This comparative study aims to identify a biocompatible and effective crosslinker for preparing gelatin sponges. Glutaraldehyde (GTA), genipin (GP), 1-ethyl-3-(3-dimethyl aminopropyl)carbodiimide (EDC), microbial transglutaminase (mTG) were used as crosslinking agents. The physical properties of the prepared samples characterized, material degradation was studied in vitro with various proteases vivo through subcutaneous implantation sponges rats. Adipose-derived stromal stem cells...
Quantizing the Breast Imaging Reporting and Data System (BI-RADS) criteria into different categories with single ultrasound modality has always been a challenge. To achieve this, we proposed two-stage grading system to automatically evaluate breast tumors from images five based on convolutional neural networks (CNNs).This new developed automatic was consisted of two stages, including tumor identification grading. The constructed network for identification, denoted as ROI-CNN, can identify...
Abstract Deception is not a rare occurrence among human behaviors; however, the present brain mapping techniques are insufficient to reveal neural mechanism of deception under spontaneous or controlled conditions. Interestingly, functional near-infrared spectroscopy (fNIRS) has emerged as highly promising neuroimaging technique that enables continuous and noninvasive monitoring changes in blood oxygenation volume brain. In this study, fNIRS was used combination with complex network theory...
Abstract Aging is closely associated with cognitive decline affecting attention, memory and executive functions. The hippocampus the core brain area for human memory, learning, cognition processing. To delineate individual functional patterns of pivotal to reveal neural basis aging. In this study, we developed a group‐guided parcellation approach based on semisupervised affinity propagation clustering using resting‐state magnetic resonance imaging identify subregions each subregion during A...
Abstract Childhood maltreatment (CM) has a long impact on physical and mental health of children. However, the neural underpinnings CM are still unclear. In this study, we aimed to establish associations between functional connectome large‐scale brain networks influences evaluated through Trauma Questionnaire (CTQ) at individual level based resting‐state magnetic resonance imaging data 215 adults. A novel mapping approach was employed identify subject‐specific network connectivities (FNCs)....
Clustering analysis is a promising data-driven method for analyzing functional magnetic resonance imaging (fMRI) time series data. The huge computational load, however, creates practical difficulties this technique. We present novel approach, integrating principal component (PCA) and supervised affinity propagation clustering (SAPC). In method, fMRI data are initially processed by PCA to obtain preliminary image of brain activation. SAPC then used detect different activation patterns....
Conduct disorder (CD) is characterized by a persistent pattern of antisocial behavior and aggression in childhood adolescence. Previous task-based resting-state functional magnetic resonance imaging (fMRI) studies have revealed widespread brain regional abnormalities adolescents with CD. However, whether the networks (RSNs) are altered CD remains unknown. In this study, fMRI data were first acquired from eighteen male pure age- gender-matched typically developing (TD) individuals....
With the increasing of sludge emissions and people's demand for better dwelling environment, resource utilization receives much concern in recent years. Currently, co-processing cement kiln has been considered as a sustainable way to dispose Japan well Europe United States. Huaxin begun since 2008. So far, 65000 tons successfully disposed. This paper focus on 3 ways through certain project examples.
In this work, we present a novel access pattern estimation approach for parallel particle tracing in flow field visualization based on deep neural networks. With strong generalization ability, develop Long Short-term Memory (LSTM)-based model, which is capable of learning accurate patterns with only few training samples and representing the learned small storage overhead. Equipped prediction prefetching functions driven by developed our framework employs CPUs GPUs together tasks. We...
Abstract Autism spectrum disorder (ASD) and Attention-deficit/hyperactivity (ADHD) are two typical neurodevelopmental disorders that have a long-term impact on physical mental health. ASD is usually comorbid with ADHD thus shares highly overlapping clinical symptoms. Delineating the shared distinct neurophysiological profiles important to uncover neurobiological mechanisms guide better therapy. In this study, we aimed establish behaviors, functional connectome, network properties differences...
Abstract A conspicuous property of brain development or maturity is coupled with coordinated synchronized structural co-variation. However, there still a lack effective approach to map individual covariance network. Here, we developed novel network method using dynamic time warping algorithm and applied it delineate developmental trajectories topological organizations from childhood early adulthood large sample 655 individuals Human Connectome Project-Development dataset. We found that the...
// Feng-Mei Lu 1 , Jian-Song Zhou 2 Jiang Zhang 3 Xiao-Ping Wang and Zhen Yuan Bioimaging Core, Faculty of Health Sciences, University Macau, Macau SAR, China Mental Institute, Second Xiangya Hospital, Central South University, Hunan Province Technology Institute Psychiatry, Key Laboratory Psychiatry Province, Changsha, School Electrical Engineering Information, Sichuan Chengdu, Correspondence to: Yuan, email: zhenyuan@umac.mo Zhou, zhoujs2003@126.com Keywords: conduct disorder,...
Abstract Visual perceptual decoding is one of the important and challenging topics in cognitive neuroscience. Building a mapping model between visual response signals contents key point decoding. Most previous studies used peak to decode object categories. However, brain activities measured by functional magnetic resonance imaging are dynamic process with time dependence, so cannot fully represent whole process, which may affect performance Here, we propose based on long short‐term memory...
Functional MRI (fMRI) data-processing methods based on changes in the time domain involve, among other things, correlation analysis and use of general linear model with statistical parametric mapping (SPM). Unlike conventional fMRI data methods, which aim to blood-oxygen-level-dependent (BOLD) response voxels as a function time, theory power spectrum (PS) focuses completely understanding dynamic energy change interacting systems. We propose new convolution PS (CPS) data, matched filtering,...
We conducted a systematic investigation of the reflectance diffuse optical tomography using continuous wave (CW) measurements and nonlinear reconstruction algorithms. illustrated suggested how to fine-tune methods in order optimize target localization with depth-adaptive regularizations, reduce boundary noises reconstructed images logarithm based objective function, improve quantification transport models, resolve crosstalk problems between absorption scattering contrasts CW measurements....