Increasing evidences have indicated that microRNAs (miRNAs) are functionally associated with the development and progression of various complex human diseases. However, roles miRNAs in multiple biological processes or diseases their underlying molecular mechanisms still not been fully understood yet. Predicting potential miRNA-disease associations by integrating heterogeneous datasets is great significance to biomedical research. Computational methods could obtain a short time, which...

Abstract Accumulating evidences have shown that plenty of miRNAs play fundamental and important roles in various biological processes the deregulations are associated with a broad range human diseases. However, mechanisms underlying dysregulations still not been fully understood yet. All previous computational approaches can only predict binary associations between diseases miRNAs. Predicting multiple types disease-miRNA further broaden our understanding about molecular basis level In this...

Image caption is becoming important in the field of artificial intelligence. Most existing methods based on CNN-RNN framework suffer from problems object missing and misprediction due to mere use global representation at image-level. To address these problems, this paper, we propose a global-local attention (GLA) method by integrating local object-level with image-level through mechanism. Thus, our proposed can pay more how predict salient objects precisely high recall while keeping context...

In recent years, the task of automatically generating image description has attracted a lot attention in field artificial intelligence. Benefitting from development convolutional neural networks (CNNs) and recurrent (RNNs), many approaches based on CNN-RNN framework have been proposed to solve this achieved remarkable process. However, two problems remain be tackled which most existing methods use only image-level representation. One problem is object missing, some important objects may...

Mixed dish is a food category that contains different dishes mixed in one plate, and popular Eastern Southeast Asia. Recognizing individual image important for health related applications, e.g. calculating the nutrition values. However, most existing methods focus on single classification are not applicable to mixed-dish recognition. The new challenge recognizing images complex ingredient combination severe overlap among dishes. In order tackle these problems, we propose novel approach...

Traditional regression framework of object locali-zation such as Overfeat often suffers from the problem inaccurate scoring due to separate classification network and upon inconsistent regions. To tackle this problem, in paper, we propose a novel localization based on multiple complementary region proposal methods view rather than regression. On top our framework, first combine proposals during both training testing means data augmentation generate more dense reliable for fusion, then...

In the past year, there has been a growing trend in applying Large Language Models (LLMs) to field of medicine, particularly with advent advanced language models such as ChatGPT developed by OpenAI. However, is limited research on LLMs specifically addressing oncology-related queries. The primary aim this was develop specialized model that demonstrates improved accuracy providing advice related oncology. We performed an extensive data collection online question-answer interactions centered...

Abstract Gm PAP 3, a purple acid phosphatase from soybean ( Glycine max ), was previously shown to alleviate salt stress in BY ‐2 cells and Arabidopsis thaliana by reducing oxidative damage. To make use of 3 for crop improvement, we investigated whether the protective function is persistent rice. Compared with untransformed wild type, transgenic rice plants exhibited enhanced germination rate, longer shoots roots, higher survival rate under stress, when compared control. In addition, also...

Mixed dish is a food category that contains different dishes mixed in one plate, and popular Eastern Southeast Asia. Recognizing the individual image important for health related applications, e.g. to calculate nutrition values of dish. However, most existing methods focus on single classification are not applicable recognition images. The main challenge comes from three aspects: wide range types, complex combination with severe overlap between large visual variances same type caused by...

In E-commerce recommendation, Click-Through Rate (CTR) prediction has been extensively studied in both academia and industry to enhance user experience platform benefits. At present, most popular CTR methods are concatenation-based models that represent items by simply merging multiple heterogeneous features including ID, visual, text into a large vector. As these modalities have moderately different properties, directly concatenating them without mining the correlation reducing redundancy...

With the rapid development of short video industry, traditional e-commerce has encountered a new paradigm, video-driven e-commerce, which leverages attractive videos for product showcases and provides both item services users. Benefitting from dynamic visualized introduction items,video-driven shown huge potential in stimulating consumer confidence promoting sales. In this paper, we focus on retrieval task, facing following challenges: (1) Howto handle heterogeneities among users, items,...

Mixed dish, which mixes different types of dishes in one plate, is a popular kind food East and Southeast Asia. Identifying the dish type mixed essential for dietary tracking, gains increasing research attention recently. Nevertheless, detection challenging task because large visual variances among canteens, known as domain shifting problem. Since collecting annotating sufficient training samples each canteen model difficult, more practical way developing models that can adapt quickly to...