Modeling Temporal Dynamics and Spatial Configurations of Actions Using Two-Stream Recurrent Neural Networks

Recently, skeleton based action recognition gains more popularity due to cost-effective depth sensors coupled with real-time skeleton estimation algorithms. Traditional approaches based on handcrafted features are limited to represent the complexity of motion patterns. Recent methods that use Recurrent Neural Networks (RNN) to handle raw skeletons only focus on the contextual dependency in the temporal domain and neglect the spatial configurations of articulated skeletons. In this paper, we propose a novel two-stream RNN architecture to model both temporal dynamics and spatial configurations for skeleton based action recognition. We explore two different structures for the temporal stream: stacked RNN and hierarchical RNN. Hierarchical RNN is designed according to human body kinematics. We also propose two effective methods to model the spatial structure by converting the spatial graph into a sequence of joints. To improve generalization of our model, we further exploit 3D transformation based data augmentation techniques including rotation and scaling transformation to transform the 3D coordinates of skeletons during training. Experiments on 3D action recognition benchmark datasets show that our method brings a considerable improvement for a variety of actions, i.e., generic actions, interaction activities and gestures.Comment: Accepted to IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 201

La banca central en tiempos de guerra: China 1927-1949

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, leída el 05-11-2020The central banking system has been a worldwide-adopted banking system since the 20th century, which influences political and economic structures profoundly in different countries to this day. Chinese Mainland is the second biggest economic entity, whose economic growth in the last 30 years gets the attention of the world. One hot topic is the function of China’s central banking system. But the works for studying the establishment of China’s central bank and the monetary thought debate behind the event still require further analysis. This thesis explains the establishment of China’s central banking system by following the monetary thought debate among Chinese economists, politicians, and foreign financial specialists. They provided advice for monetary policy from 1927 to 1949.This research has the following three main objectives: Revise the monetary thought debate from 1927 to 1949 among Chinese economists, politicians, and Western financial specialists on how to improve the Chinese monetary system and how to build an effective central-banking system during wartime. Demonstrate how the establishment of central banking was supported by the monetary theories provided in the monetary thought debate...El sistema de banca central ha sido el sistema bancario adoptado en todo el mundo desde el siglo XX, influyendo profundamente en las estructuras políticas y económicas de muchos países hasta nuestros días. China continental es la segunda potencia económica más grande a nivel internacional, cuyo crecimiento económico en los últimos 30 años ha llamado la atención en todo el mundo. Un tema candente relacionado con China es la función de su sistema de banca central. Sin embargo, los trabajos para estudiar la creación del banco central de China y el debate sobre el pensamiento monetario detrás de la aparición de dicha institución, aún requieren un análisis más detallado. Esta tesis explica el establecimiento del sistema de banca central de China siguiendo el debate del pensamiento monetario entre economistas y políticos chinos y especialistas financieros extranjeros, que brindaron asesoramiento para la política monetaria de 1927 a 1949...Fac. de Ciencias Económicas y EmpresarialesTRUEunpu

Chatbots in Drug Discovery: A Case Study on Anti-Cocaine Addiction Drug Development with ChatGPT

The birth of ChatGPT, a cutting-edge language model chatbot developed by OpenAI, ushered in a new era in AI, and this paper vividly showcases its innovative application within the field of drug discovery. Focused specifically on developing anti-cocaine addiction drugs, the study employs GPT-4 as a virtual guide, offering strategic and methodological insights to researchers working on generative models for drug candidates. The primary objective is to generate optimal drug-like molecules with desired properties. By leveraging the capabilities of ChatGPT, the study introduces a novel approach to the drug discovery process. This symbiotic partnership between AI and researchers transforms how drug development is approached. Chatbots become facilitators, steering researchers towards innovative methodologies and productive paths for creating effective drug candidates. This research sheds light on the collaborative synergy between human expertise and AI assistance, wherein ChatGPT's cognitive abilities enhance the design and development of potential pharmaceutical solutions. This paper not only explores the integration of advanced AI in drug discovery but also reimagines the landscape by advocating for AI-powered chatbots as trailblazers in revolutionizing therapeutic innovation

Покращення ресурсних характеристик літака шляхом оптимізації заклепкових з’єднань

Робота публікується згідно наказу Ректора НАУ від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт здобувачів вищої освіти в репозиторії університету". Керівник роботи: професор, д.т.н. Карускевич Михайло ВіталійовичThis master thesis is dedicated to optimization of aviation riveted joints by the reduction of secondary bending of aircraft skin components under the action of operational loads/ The methods of computer aided design CAD/CAE have been used, particularly CATIA та ABAQUS. The practical value of the diploma work lays in the improvement of the reliability and extension of the lifespan of aviation constructions by the optimization of the riveted joints geometry. The materials of the master's diploma can be used in the aviation industry and in the educational process of aviation specialties.Дана дипломна робота присвячена оптимізації заклепкових авіаційних з’єднань шляхом зменшення вторинного вигину елементів обшивки літака при дії експлуатаційних навантажень. В роботі було використано методи компьютерного проєктування за допомогою CAD/CAE систем проєктування та розрахунку, зокрема CATIA та ABAQUS. Практичне значення результату дипломної роботи магістра полягає в підвищенні надійності та довговічності авіаційних конструкцій, за рахунок оптимізації геометрії заклепкових з’єднань. Матеріали дипломної роботи магістра можуть бути використані в навчальному процесі та в практичній діяльності конструкторів спеціалізованих проєктних установ

Efficient Token-Guided Image-Text Retrieval with Consistent Multimodal Contrastive Training

Image-text retrieval is a central problem for understanding the semantic relationship between vision and language, and serves as the basis for various visual and language tasks. Most previous works either simply learn coarse-grained representations of the overall image and text, or elaborately establish the correspondence between image regions or pixels and text words. However, the close relations between coarse- and fine-grained representations for each modality are important for image-text retrieval but almost neglected. As a result, such previous works inevitably suffer from low retrieval accuracy or heavy computational cost. In this work, we address image-text retrieval from a novel perspective by combining coarse- and fine-grained representation learning into a unified framework. This framework is consistent with human cognition, as humans simultaneously pay attention to the entire sample and regional elements to understand the semantic content. To this end, a Token-Guided Dual Transformer (TGDT) architecture which consists of two homogeneous branches for image and text modalities, respectively, is proposed for image-text retrieval. The TGDT incorporates both coarse- and fine-grained retrievals into a unified framework and beneficially leverages the advantages of both retrieval approaches. A novel training objective called Consistent Multimodal Contrastive (CMC) loss is proposed accordingly to ensure the intra- and inter-modal semantic consistencies between images and texts in the common embedding space. Equipped with a two-stage inference method based on the mixed global and local cross-modal similarity, the proposed method achieves state-of-the-art retrieval performances with extremely low inference time when compared with representative recent approaches.Comment: Code is publicly available: https://github.com/LCFractal/TGD

Comparison of Rooting Strategies to Explore Rock Fractures for Shallow Soil-Adapted Tree Species with Contrasting Aboveground Growth Rates: A Greenhouse Microcosm Experiment

For tree species adapted to shallow soil environments, rooting strategies that efficiently explore rock fractures are important because soil water depletion occurs frequently. However, two questions: (a) to what extent shallow soil-adapted species rely on exploring rock fractures and (b) what outcomes result from drought stress, have rarely been tested. Therefore, based on the expectation that early development of roots into deep soil layers is at the cost of aboveground growth, seedlings of three tree species (Cyclobalanopsis glauca, Delavaya toxocarpa, and Acer cinnamomifolium) with distinct aboveground growth rates were selected from a typical shallow soil region. In a greenhouse experiment that mimics the basic features of shallow soil environments, 1-year-old seedlings were transplanted into simulated microcosms of shallow soil overlaying fractured bedrock. Root biomass allocation and leaf physiological activities, as well as leaf δ13C values were investigated and compared for two treatments: regular irrigation and repeated cycles of drought stress. Our results show that the three species differed in their rooting strategies in the context of encountering rock fractures, however, these strategies were not closely related to the aboveground growth rate. For the slowest-growing seedling, C. glauca, percentages of root mass in the fractures, as well as in the soil layer between soil and bedrock increased significantly under both treatments, indicating a specialized rooting strategy that facilitated the exploration of rock fractures. Early investment in deep root growth was likely critical to the establishment of this drought-vulnerable species. For the intermediate-growing, A. cinnamomifolium, percentages of root mass in the bedrock and interface soil layers were relatively low and exhibited no obvious change under either treatment. This limited need to explore rock fractures was compensated by a conservative water use strategy. For the fast-growing, D. toxocarpa, percentages of root mass in the bedrock and interface layers increased simultaneously under drought conditions, but not under irrigated conditions. This drought-induced rooting plasticity was associated with drought avoidance by this species. Although, root development might have been affected by the simulated microcosm, contrasting results among the three species indicated that efficient use of rock fractures is not a necessary or specialized strategy of shallow-soil adapted species. The establishment and persistence of these species relied on the mutual complementation between their species-specific rooting strategies and drought adaptations