Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring

Artificial Intelligence and Terrestrial LiDAR Point Clouds in Forest Monitoring: Academic Report Academic Background With the increasing importance of global climate change and forest resource management, precision forestry has become a key direction in modern forest management. Precision forestry relies on high-precision forest data collection and...

AutoStory: Generating Diverse Storytelling Images with Minimal Human Efforts

AutoStory: Generating Diverse Storytelling Images with Minimal Human Efforts

Academic Background and Problem Statement Story Visualization is a task aimed at generating a series of visually consistent images from a story described in text. This task requires the generated images to be of high quality, aligned with the text description, and consistent in character identities across different images. Despite its wide range of...

SIRCLE Model Reveals Mechanisms of Phenotype Regulation in Renal Cancer

Executive Report on the Study of ccRCC Regulatory Mechanisms Using the SIRCLE Model Background Overview Clear Cell Renal Cell Carcinoma (ccRCC) is the most prevalent form of kidney cancer, accounting for 70% of renal malignancies. The development and progression of ccRCC involve intricate remodeling of the kidney epigenome, transcriptome, proteome,...

Spatio-Temporal Graph-Based Generation and Detection of Adversarial False Data Injection Evasion Attacks in Smart Grids

Title: Generating and Detecting Spatio-Temporal Graph-Based Adversarial False Data Injection Evasion Attacks in Smart Grids Background With the continuous development of modern smart grids, the grid, as a typical Cyber-Physical System (CPS), faces numerous security threats due to the extensive exchange of data between its components. Among these, F...

An On-Chip Full-Stokes Polarimeter Based on Optoelectronic Polarization Eigenvectors

Research on On-Chip Full-Stokes Polarimeters Based on Optoelectronic Polarization Eigenvectors Academic Background The polarization state of light plays a significant role in optical communication, biomedical diagnostics, remote sensing, cosmology, and other fields. The Stokes vector, consisting of four parameters, is used to fully describe the pol...

Single-Cell RNA Sequencing and Machine Learning Reveal Relationship Between CD8+ T Cells and Uveal Melanoma Metastasis

Academic Report on “Machine Learning and Single-cell RNA Sequencing Reveal Relationship Between Intratumor CD8+ T Cells and Uveal Melanoma Metastasis” published in Cancer Cell International in 2024 Research Background and Purpose Uveal melanoma (UM) is the most common intraocular malignant tumor in adults. After receiving radiation or surgical trea...

Integrated Single-Cell Multiomic Analysis Reveals Novel Regulators of HIV Latency Reversal

Comprehensive Single-Cell Multi-Omics Study on HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation This paper, titled “Integrated single-cell multiomic analysis of HIV latency reversal reveals novel regulators of viral reactivation,” was jointly completed by Manickam Ashokkumar, Wenwen Mei, and several other researchers from institu...

Machine Learning for Automating Subjective Assessment of Arm Movement Abnormality After Acquired Brain Injury

Machine Learning for Automating Subjective Assessment of Arm Movement Abnormality After Acquired Brain Injury

Automated Clinical Assessment of Abnormal Walking Movements in ABI Patients Through Image Extraction and Classification Systems Academic Background Walking disability is a common physical impairment following Acquired Brain Injury (ABI). ABI typically includes stroke and traumatic brain injury, with a global incidence of approximately 1.5 million c...

Post-Stroke Hand Gesture Recognition via One-Shot Transfer Learning Using Prototypical Networks

Background Introduction Stroke is one of the leading causes of death and disability worldwide, with the total number of stroke patients increasing globally due to population aging and urbanization. Although advances in treatment have reduced mortality rates, the number of survivors requiring rehabilitation has increased significantly. This is parti...

Towards Machine Learning-Based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection

Towards Machine Learning-Based Quantitative Hyperspectral Image Guidance for Brain Tumor Resection

Study on the Role of Machine Learning-Assisted Quantitative Hyperspectral Imaging in Brain Tumor Resection Background Introduction Complete resection of malignant gliomas has always been challenged by the difficulty of distinguishing tumor cells in invasive regions. The background of this study is: In neurosurgery, the application of 5-aminolevulin...