A5044687301- Advancements in Battery Materials
- Supercapacitor Materials and Fabrication
- Advanced Battery Materials and Technologies
- Domain Adaptation and Few-Shot Learning
- Advanced Neural Network Applications
- Liver Disease Diagnosis and Treatment
- Pharmacogenetics and Drug Metabolism
- Advanced Vision and Imaging
- Liver physiology and pathology
- Image Processing and 3D Reconstruction
- Transition Metal Oxide Nanomaterials
- Robotics and Sensor-Based Localization
- Autonomous Vehicle Technology and Safety
- Advanced Chemical Sensor Technologies
- Pharmacological Effects and Toxicity Studies
- Graphene research and applications
- Traffic control and management
- Molecular Sensors and Ion Detection
- Conducting polymers and applications
- Analytical Chemistry and Sensors
- Multimodal Machine Learning Applications
- 3D Shape Modeling and Analysis
- Drug Transport and Resistance Mechanisms
- Pharmacological Effects of Natural Compounds
- Transportation Planning and Optimization
Dyson (United Kingdom)
2021-2024
Imperial College London
2018-2024
Tongji University
2021-2024
Jilin Agricultural University
2024
Northeast Electric Power University
2022-2024
Peking University
2024
Peking University Third Hospital
2024
Nanjing University of Science and Technology
2021-2024
Third Xiangya Hospital
2013-2023
Central South University
2014-2023
We propose a novel multi-task learning architecture, which allows of task-specific feature-level attention. Our design, the Multi-Task Attention Network (MTAN), consists single shared network containing global feature pool, together with soft-attention module for each task. These modules allow features from features, whilst simultaneously allowing to be across different tasks. The architecture can trained end-to-end and built upon any feed-forward neural network, is simple implement,...
We show for the first time that a multilayer perceptron (MLP) can serve as only scene representation in real-time SLAM system handheld RGB-D camera. Our network is trained live operation without prior data, building dense, scene-specific implicit 3D model of occupancy and colour which also immediately used tracking.Achieving via continual training neural against image stream requires significant innovation. iMAP algorithm uses keyframe structure multi-processing computation flow, with...
We present ReCo, a contrastive learning framework designed at regional level to assist in semantic segmentation. ReCo performs semi-supervised or supervised pixel-level on sparse set of hard negative pixels, with minimal additional memory footprint. is easy implement, being built top off-the-shelf segmentation networks, and consistently improves performance both methods, achieving smoother boundaries faster convergence. The strongest effect very few labels. With we achieve high-quality...
We present vMAP, an object-level dense SLAM system using neural field representations. Each object is repre-sented by a small MLP, enabling efficient, watertight modelling without the needfor 3D priors. As RGB-D camera browses scene with no prior in-formation, vMAP detects instances on-the-fly, and dynamically adds them to its map. Specifically, thanks power of vectorised training, can optimise as many 50 individual objects in single scene, extremely efficient training speed 5Hz map update....
Abstract Pharmacological inhibition of reactive oxygen species (ROS) is a potential strategy to prevent diabetes-induced cardiac dysfunction. This study was designed investigate precise effects antioxidant N ‑acetylcysteine (NAC) in alleviating diabetic cardiomyopathy (DCM). Echocardiography and histologic studies were performed 12 weeks after streptozocin injection. Protein levels involved endoplasmic reticulum stress (ERS) apoptosis analyzed by western blotting hearts or high-glucose (HG,...
We propose the Variational Shape Learner (VSL), a generative model that learns underlying structure of voxelized 3D shapes in an unsupervised fashion. Through use skip-connections, our can successfully learn and infer latent, hierarchical representation objects. Furthermore, realistic objects be easily generated by sampling VSL's latent probabilistic manifold. show trained end-to-end from 2D images to perform single image retrieval. Experiments show, both quantitatively qualitatively,...
Learning with auxiliary tasks can improve the ability of a primary task to generalise. However, this comes at cost manually labelling data. We propose new method which automatically learns appropriate labels for an task, such that any supervised learning be improved without requiring access further The approach is train two neural networks: label-generation network predict labels, and multi-task alongside task. loss incorporates network, so interaction between networks seen as form meta...
This review describes recent advances of strategies for the design and morphology control self-supported 1D nanostructured materials electrochromism.
Increased acid sphingomyelinase (ASMase) activity is associated with insulin resistance and cardiac dysfunction. However, the effects of ASMase on diabetic cardiomyopathy (DCM) molecular mechanism(s) underlying remain to be elucidated. We here investigated whether caused DCM through NADPH oxidase 4-mediated apoptosis.We used pharmacological genetic approaches coupled study murine cell line samples reveal mechanisms initiated by in hearts. The protein expression were upregulated, meanwhile...
Abstract In tumor therapeutics, the transition from conventional cytotoxic drugs to targeted molecular therapies, such as those targeting receptor tyrosine kinases, has been pivotal. Despite this progress, clinical outcomes have remained modest, with glioblastoma patients' median survival stagnating at less than 15 months. This underscores urgent need for more specialized treatment strategies. Our review delves into progression toward immunomodulation in glioma treatment. We dissect critical...
Amorphous and crystalline V<sub>2</sub>O<sub>5</sub> cathodes in sodium ion batteries express inverse capacity values at low high current densities.
Recent vision-language models have shown impressive multi-modal generation capabilities. However, typically they require training huge on massive datasets. As a more scalable alternative, we introduce Prismer, data- and parameter-efficient model that leverages an ensemble of domain experts. Prismer only requires small number components, with the majority network weights inherited from readily-available, pre-trained experts, kept frozen during training. By leveraging experts wide range...
Epithelial-mesenchymal transition (EMT) of retinal pigment epithelial (RPE) cells is a key fibrosis pathogenesis in proliferative vitreoretinopathy (PVR). However, few medicines can prevent membranes and cell proliferation the clinic. Nintedanib, tyrosine kinase inhibitor, has been shown to be anti-inflammatory multiple organ fibrosis. In our study, 0.1, 1, 10 μM nintedanib was added 20 ng/mL transforming growth factor beta 2 (TGF-β2)-induced EMT ARPE-19 cells. Western blot...
Large language models (LLMs) have recently been introduced to graph learning, aiming extend their zero-shot generalization success tasks where labeled data is scarce. Among these applications, inference over text-attributed graphs (TAGs) presents unique challenges: existing methods struggle with LLMs' limited context length for processing large node neighborhoods and the misalignment between embeddings LLM token space. To address issues, we establish two key principles ensuring derive...