A5036556281- Pulsars and Gravitational Waves Research
- Adsorption and biosorption for pollutant removal
- Gamma-ray bursts and supernovae
- Advanced biosensing and bioanalysis techniques
- Nanoplatforms for cancer theranostics
- Environmental remediation with nanomaterials
- Nanomaterials for catalytic reactions
- Numerical methods for differential equations
- Optical measurement and interference techniques
- Advanced Neural Network Applications
- Radiomics and Machine Learning in Medical Imaging
- Computational Physics and Python Applications
- Autonomous Vehicle Technology and Safety
- Pleistocene-Era Hominins and Archaeology
- Morphological variations and asymmetry
- DNA and Biological Computing
- TiO2 Photocatalysis and Solar Cells
- Extracellular vesicles in disease
- Vibration and Dynamic Analysis
- Electrocatalysts for Energy Conversion
- Brain Tumor Detection and Classification
- Advanced Photocatalysis Techniques
- Image and Signal Denoising Methods
- Astrophysical Phenomena and Observations
- Phosphorus and nutrient management
University of Shanghai for Science and Technology
2022-2025
Mongolian University of Science and Technology
2024
Inner Mongolia University of Science and Technology
2024
International Peace Maternity & Child Health Hospital
2024
Shanghai Jiao Tong University
2024
Huazhong University of Science and Technology
2023-2024
Central South University
2021-2024
University of Illinois Urbana-Champaign
2018-2023
Chongqing University of Technology
2022-2023
Changsha University of Science and Technology
2023
The exquisite sensitivity of the advanced LIGO detectors has enabled detection multiple gravitational wave signals. sophisticated design these mitigates effect most types noise. However, data streams are contaminated by numerous artifacts known as glitches: non-Gaussian noise transients with complex morphologies. Given their high rate occurrence, glitches can lead to false coincident detections, obscure and even mimic Therefore, successfully characterizing removing from is utmost importance....
Denoising of time domain data is a crucial task for many applications such as communication, translation, virtual assistants etc. For this task, combination recurrent neural net (RNNs) with Auto-Encoder (DAEs) has shown promising results. However, combined model challenged when operating low signal-to-noise ratio (SNR) embedded in non-Gaussian and non-stationary noise. To address issue, we design novel model, referred to 'Enhanced Deep Recurrent Auto-Encoder' (EDRDAE), that incorporates...
Volatile organic compounds (VOCs) play key roles in plant–plant communication, especially under attack by pests. E-2-hexenal is an important component of VOCs, and whether it can induce endogenous insect resistance plants not clear. Here, we show that activates early signaling events Arabidopsis (Arabidopsis thaliana) mesophyll cells, including H2O2 burst at the plasma membrane, directed flow calcium ions, increase cytosolic concentration. Treatment wild-type with increases their when...
The methods of geometric morphometrics are commonly used to quantify morphology in a broad range biological sciences. application these large datasets is constrained by manual landmark placement limiting the number landmarks and introducing observer bias. To move field forward, we need automate morphological phenotyping ways that capture comprehensive representations variation with minimal Here, present Morphological Variation Quantifier (morphVQ), shape analysis pipeline for quantifying,...
Abstract We introduce deep learning models to estimate the masses of binary components black hole mergers, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"><mml:mo stretchy="false">(</mml:mo><mml:msub><mml:mi>m</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>m</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo stretchy="false">)</mml:mo></mml:math> , and three astrophysical properties post-merger compact remnant, namely, final spin,...
The synergy effect realizes the rapid separation of photogenerated carriers and ultimately improves photoelectric conversion efficiency PFC.
DNA information storage provides an excellent solution for metadata due to its high density, programmability, and long-term stability. However, current research primarily focuses on the processes of storing reading data, lacking comprehensive solutions secure wiping. Herein, we present a method random sanitization in using CRISPR-Cas12a (RSDISC) based precise control thermodynamic energy primer-template hybridization. We utilize collateral cleavage (trans-activity) single-stranded (ssDNA) by...
The automatic generation of radiology reports is great significance, which can reduce the workload doctors and improve accuracy reliability medical diagnosis treatment, has attracted wide attention in recent years. Cross-modal mapping between images text, a key component generating high-quality reports, challenging due to lack corresponding annotations. Despite its importance, previous studies have often overlooked it or lacked adequate designs for this crucial component. In paper, we...
This review summarizes the application of various photothermal materials in detection circulating tumor cells (CTCs), and describes significance CTCs for early diagnosis prognosis.
Automated segmentation of liver tumors on CT scans is essential for aiding diagnosis and assessing treatment. Computer-aided can reduce the costs errors associated with manual processes ensure provision accurate reliable clinical assessments. However, in images vary significantly size have fuzzy boundaries, making it difficult existing methods to achieve segmentation. Therefore, this paper proposes MAEG-Net, a multi-scale adaptive feature fusion tumor network based edge guidance....
This report provides an overview of recent work that harnesses the Big Data Revolution and Large Scale Computing to address grand computational challenges in Multi-Messenger Astrophysics, with a particular emphasis on real-time discovery campaigns. Acknowledging transdisciplinary nature this document has been prepared by members physics, astronomy, computer science, data software cyberinfrastructure communities who attended NSF-, DOE- NVIDIA-funded "Deep Learning for Astrophysics: Real-time...
A bstract While protein sequence data is an emerging application domain for machine learning methods, small modifications to sequences can result in difficult-to-predict changes the protein’s function. Consequently, models typically do not use randomized augmentation procedures analogous those used computer vision or natural language, e.g., cropping synonym substitution. In this paper, we empirically explore a set of simple string manipulations, which augment when fine-tuning semi-supervised...
Abstract Perovskite materials with unique crystal structure have developed rapidly in recent years owing to their special physical and chemical properties, such as high light absorption extraordinary electrocatalytic properties. Metal halide perovskites are quite attractive various fields because of simple manufacturing process, adjustable band gap, good charge transfer performance, theoretical photoelectric conversion efficiency. Therefore, perovskite oxides mixed metal elements become...