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In recent years, research on the manipulation and control of microrobot has gradually matured. In order to improve the intelligence of microrobots, navigation study also becomes an important research topic. In practice, microrobots could be disturbed by the flowing liquid when it moves in a microfluidic environment. As a result, the actual trajectory of microrobots will deviate from the intended one. In this paper, firstly, different algorithms for the navigation of microrobots in a simulated plant leaf vein environment are investigated. According to the simulation results, RRT*-Connect is then selected as the path planning algorithm with a relatively better performance. Based on the pre-planned trajectory, a fuzzy PID controller is further designed for precise trajectory tracking, which can effectively eliminate the random disturbance caused by micro-fluid flow during the motion and make it quickly recover to a stable movement state.

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The increasing demand for precise load forecasting for distribution networks has become a crucial requirement due to the continual surge in power consumption. Accurate forecasting of peak loads for distribution networks is paramount to ensure that power grids operate smoothly and to optimize their configuration. Many load forecasting methods do not meet the requirements for accurate data and trend fitting. To address these issues, this paper presents a novel forecasting model called Prophet-LSTM, which combines the strengths of the Prophet model's high trend fitting and LSTM model's high prediction accuracy, resulting in improved accuracy and effectiveness of peak load forecasting. The proposed algorithm models the distribution network peak load using the Prophet-LSTM algorithm. The researchers then analyzed the experimental data and model of the algorithm to evaluate its effectiveness. We found that the Prophet-LSTM algorithm outperformed the Prophet and LSTM models individually in peak load prediction. We evaluate the proposed model against commonly used forecasting models using MAE (mean absolute error) and RMSE (root mean square error) as evaluation metrics. The results indicate that the proposed model has better forecasting accuracy and stability. As a result, it can predict the peak load of distribution networks more accurately. In conclusion, this study offers a valuable contribution to load forecasting for distribution networks. The proposed Prophet-LSTM algorithm provides a more precise and stable prediction, making it a promising approach for future applications in distribution network load forecasting. [ABSTRACT FROM AUTHOR]

The integration of technology has been a constant fact in various areas of architecture. Currently there are innovative tools to be used both in the architectural design process and in professional practice, so its incorporation in architectural education is necessary for the preparation of future professionals. However, the incorporation of technology in architectural education is a process that involves various factors, so this article aimed to analyze the technologies and software that have been incorporated into architectural education to establish criteria in this regard, in addition to identifying the pedagogical approaches used for their incorporation. A systematic review was carried out through three online scientific databases and a quantitative-qualitative analysis was performed. The results suggest that the most incorporated technology and software are Virtual Reality and Rhinoceros respectively. The main reason for integrating a certain technology or software is the need to encourage the adaptation of these to the current demands of the area. Four main criteria used for the incorporations were identified: selection of learning resources, learning design, implementation and degree of success and evaluation. In terms of pedagogical approaches, the constructivist approach was found to be the most used. The incorporation positively influence the teaching-learning process in architecture education, however, there are limitations to their complete satisfaction, so studies on the subject are necessary, especially in specific contexts. [ABSTRACT FROM AUTHOR]

Robotic tectonics have been integrated into the architectural profession through automated construction for more than a decade, advancing sustainability initiatives in the industry and increasing the quality of building construction. Over the years, avant-garde architects have explored the feasibility of this new design paradigm through the integration of newly-developed digital design software into automated construction. This robotic digital workflow continues to push designers to re-think the complete architecture process (from design conception to physical construction) and guides the building industry towards more precise, efficient, and sustainable development. However, in the current environment of architectural education, professional courses can be fragmented, thematic, and overly academic. Such content is not inherently compatible with the latest technological developments. The lack of understanding and application of digital technological can subsequently lead to the lack of sustainable development in architectural education. In this paper, we aim to introduce a new didactic pedagogical approach that is reliant on the principles of robotic tectonics and is defined through linear development in four distinct, developmental stages (based on information gleaned from four "Robotic Tectonics" workshops and various other rich teaching practices). This pedagogical framework provides interdisciplinary knowledge to architecture students and enables them to use advanced digital tools such as robots for automated construction, laying the groundwork for the discovery of new and complex building processes that will redefine architecture in the near future. [ABSTRACT FROM AUTHOR]