A5101776258- Topic Modeling
- Natural Language Processing Techniques
- Advanced Malware Detection Techniques
- Network Security and Intrusion Detection
- Geological and Geochemical Analysis
- Geochemistry and Geologic Mapping
- Multimodal Machine Learning Applications
- earthquake and tectonic studies
- RNA Research and Splicing
- Privacy-Preserving Technologies in Data
- High-pressure geophysics and materials
- Mobile Crowdsensing and Crowdsourcing
- RNA modifications and cancer
- Advanced Text Analysis Techniques
- Software Testing and Debugging Techniques
- Soybean genetics and cultivation
- Medical Research and Treatments
- IoT and Edge/Fog Computing
- Advanced Data Storage Technologies
- Image Enhancement Techniques
- Blockchain Technology Applications and Security
- Agricultural pest management studies
- Particle Detector Development and Performance
- Advanced Image Processing Techniques
- E-commerce and Technology Innovations
Second Affiliated Hospital of Nanjing Medical University
2024-2025
China Pharmaceutical University
2025
University of Michigan
2025
Rensselaer Polytechnic Institute
2025
Brookhaven National Laboratory
2025
Oak Ridge National Laboratory
2025
Central China Normal University
2025
Massachusetts Institute of Technology
2025
Los Alamos National Laboratory
2025
New Jersey Institute of Technology
2025
According to the recent report, 12 000 new Android malware samples will be generated every day. Efficient identification of evolving is an urgent challenge. Traditional methods based on structured features such as permissions and sensitive application programming interface (API) calls lack high-level behavioral semantics detect malware. The call graphs (CG) are good at semantic analysis but face problem huge time space consumption, which leads low detection efficiency. In this paper, we...
Abstract Protein lactylation is an emerging field. To advance the exploration of its biological functions, here we develop a comprehensive workflow that integrates proteomics to identify lactylated sites, genetic code expansion (GCE) for expression site-specifically proteins in living cells, and integrated functional analysis (IFA) platform evaluate their effects. Using combined wet-and-dry-lab strategy, conserved at ALDOA-K147, which hypothesize plays significant role. Expression this ALDOA...
This R&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time of high-rate streams from sPHENIX experiment tracking detectors. The limitations 15 kHz maximum trigger rate imposed calorimeters can be negated intelligent use streaming technology system. approach efficiently identifies low...
Although pre-trained models (PLMs) have achieved remarkable improvements in a wide range of NLP tasks, they are expensive terms time and resources. This calls for the study training more efficient with less computation but still ensures impressive performance. Instead pursuing larger scale, we committed to developing lightweight yet powerful trained equal or friendly rapid deployment. technical report releases our model called Mengzi, which stands family discriminative, generative,...
Prompt learning with immensely large Casual Language Models (CLMs) has been shown promising for attribute-controllable text generation (CTG). However, vanilla prompt tuning tends to imitate training corpus characteristics beyond the control attributes, resulting in a poor generalization ability. Moreover, it is less able capture relationship between different further limiting performance. In this paper, we propose new CTG approach, namely DisCup, which incorporates attribute knowledge of...
Abstract Background Edaravone dexborneol has been reported as an effective neuroprotective agent in the treatment of acute ischemic stroke (AIS). This study aimed at investigating impact edaravone on functional outcomes and systematic inflammatory response AIS patient. Methods All participants were recruited from AISRNA (registered 21/11/2019, NCT04175691 [ClinicalTrials.gov]) between January 2022 December 2022. The patients divided into two groups based whether they received (37.5 mg/12...
Abstract Still in its infancy, the functions of lactylation remain elusive. To address this, we established a comprehensive workflow for studies that integrates discovery sites with proteomics, expression site-specifically lactylated proteins living cells via genetic code expansion (GCE), and evaluation resulting biological consequences. Specifically, developed wet-and-dry-lab combined proteomics strategy, identified highly conserved at ALDOA-K147. Driven by potential significance, expressed...
Controllable Text Generation (CTG) is emerging area in the field of natural language generation (NLG). It regarded as crucial for development advanced text technologies that better meet specific constraints practical applications. In recent years, methods using large-scale pre-trained models (PLMs), particular widely used transformer-based PLMs, have become a new paradigm NLG, allowing more diverse and fluent text. However, due to limited level interpretability deep neural networks,...
Conversational Emotion Recognition (CER) aims at classifying the emotion of each utterance in a conversation. For target utterance, its is jointly determined by multiple factors, such as conversation topics, labels and intra/inter-speaker influences, conversational context it. Then an important research question arises: can effects these contextual factors be sufficiently captured current CER models? To answer this question, we carry out empirical study on four representative models...
There is limited advancement on seed number per pod (SNPP) in soybean breeding, resulting low yield China. To address this issue, we identified PIN1 and CKX gene families that regulate SNPP Arabidopsis, analyzed the differences of auxin cytokinin pathways, constructed interaction networks PIN1, CKX, yield-related genes cowpea. First, relative expression level (REL) plasma membrane localization phosphorylation levels protein were less than cowpea, which make transport efficiency lower...
Since the data samples on client devices are usually non-independent and non-identically distributed (non-IID), this will challenge convergence of federated learning (FL) reduce communication efficiency. This paper proposes FedQMIX, a node selection algorithm based multi-agent reinforcement learning(MARL), to address these challenges. Firstly, we observe connection between model weights distribution, clustering can group clients with similar distribution into same cluster. Secondly, propose...
Ongoing exploration in East Junggar, Northwest China, has led to the discovery of intrusion-related Yundukala Au–Cu–Co deposit. The alteration and mineralization deposit are closely related diorite gabbro-diorite, whereas geochemical features these ore-related plutons still unclear. In this study, order unlock nature ore-forming magmas, zircon U–Pb dating, whole-rock major trace elemental Sr–Nd isotope analysis, as well O–Hf were conducted. Our results show that gabbro-diorite both generated...
East Junggar is an important part of the Central Asia Orogenic Belt and has developed a multi‐epoch multi‐type metallogenic system. Yundukala recently discovered large intrusion‐related Au–Cu–Co deposit. The No. 1 main mineralization zone mainly occurs in contact area between fine‐grained diorite basalt. Massive vein have there, but ore‐bearing stratum, intrusive rocks, ages are not clear. Zircon SHRIMP U–Pb dating porphyritic yields 416.1 ± 3.9 Ma 411.1 7.5 Ma, respectively. dioritoid...
This paper concentrates on the problem of job security scheduling under cloud computing environment. The Architecture platform is made up four layers, including 1) SOA architecture, 2) Management Middleware, 3) Resource virtualization and 4) Physical Resources. Next, we formally describe computing. To guarantee level scheduling, demand trust are defined in our work. Afterwards, proposed genetic algorithm based proposed. main innovation lies that utilize each chromosome to represent a...
This paper presents a new approach to improve multiple choice and defect detection in cross-border shipments using deep learning (DRL). The design process involves the integration of real-time data from sources create comprehensive transportation models, including route optimization, cost reduction, poor research methods. DRL project is intended use multi-agent manage complex decision-making processes dynamic logistics environment. hybrid anomaly system combines statistics with machine...
Prompt learning with immensely large Casual Language Models (CLMs) has been shown promising for attribute-controllable text generation (CTG). However, vanilla prompt tuning tends to imitate training corpus characteristics beyond the control attributes, resulting in a poor generalization ability. Moreover, it is less able capture relationship between different further limiting performance. In this paper, we propose new CTG approach, namely DisCup, which incorporates attribute knowledge of...