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关键词： Natural sciences   Physics   Computer science   Materials science  

摘要： Efficiently generating energetically stable crystal structures has long been a challenge in material design, primarily due to the immense arrangement of atoms in a crystal lattice. To facilitate the discovery of stable materials, we present a framework for the generation of synthesizable materials leveraging a point cloud representation to encode intricate structural information. At the heart of this framework lies the introduction of a diffusion model as its foundational pillar. To gauge the efficacy of our approach, we employed it to reconstruct input structures from our training datasets, rigorously validating its high reconstruction performance. Furthermore, we demonstrate the profound potential of point cloud-based crystal diffusion (PCCD) by generating materials, emphasizing their synthesizability. Our research stands as a noteworthy contribution to the advancement of materials design and synthesis through the cutting-edge avenue of generative design instead of conventional substitution or experience-based discovery.

关键词： Natural sciences   Applied sciences   Computer science  

摘要： Developing high-performance alloys is essential for applications in advanced electromagnetic energy conversion devices. In this study, we assess Fe-Co-Ni alloy compositions identified in our previous work through a machine learning (ML) framework, which used both multi-property ML models and multi-objective Bayesian optimization to design compositions with predicted high values of saturation magnetization, Curie temperature, and Vickers hardness. Experimental validation was conducted on two promising compositions synthesized using three different methods: arc melting, ball milling followed by spark plasma sintering (SPS), and chemical synthesis followed by SPS. The results show that the experimental property values of arc melted samples deviated less than 14% from predicted values. This work further explains how structural variations across synthesis methods impact property behavior, validating the robustness of ML-predicted compositions and highlighting a pathway for integrating processing conditions into alloy development.

关键词： Machine learning   Computer science   Ethics  

摘要： US technology company Meta has produced an AI model that can directly translate speech in one language to speech in another. Two scientists discuss the technical feats and ethical questions that underpin this advance in machine translation.

关键词： Computer science   Quantum information   Mathematics and computing  

摘要： Sang-Wook Han hopes that the technology will spark innovations in materials science, drug development, finance and defence.

关键词： Training   Loss measurement   Recommender systems   Fans   Electronic mail   Uncertainty   Motion pictures   Computer science   Vectors   Upper bound   Loss function   matrix factorization   outlier   recommender system (RS)  

摘要： Outliers are intrinsic to recommender systems (RSs) due to user uncertainty and bring large deviations to the total loss. Classical loss functions such as L-1 and L-2 do not consider this issue, thus biasing the model toward abnormal ratings. Advanced ones such as Logcosh, Huber, and Wing losses try to control model biasing;however, they do not consider the rating ranges of recommender systems. In this article, we propose a Seagull loss combining quadratic and softsign functions to handle this issue. The quadratic function aims to preserve or appropriately increase losses caused by small deviations, while softsign function aims to suppress losses caused by large deviations. It is distinguished from three types of popular losses. Compared with L-1 and L-2, it controls the upper bound, therefore suppressing the influence of outliers. Compared with Logcosh and Huber, it not only adjusts the loss of small deviations but also suppresses the loss of large deviations. Compared with Wing loss, it considers the characteristics of data in RSs and therefore is more suitable to the matrix factorization model. Experiments are undertaken on six real-world recommendation datasets in comparison with six popular loss functions. Results show that Seagull loss function has superiority to all losses above on mean absolute error (MAE) and root mean square error (RMSE) and slight inferiority to L-2 and Wing on hit ratio (HR), mean average precision (MAP), and normalized discounted cumulative gain (NDCG).

关键词： maths   engineering   physics   chemistry   computer science   Earth science  

关键词： Programming   Teaching and learning   Interdisciplinary pedagogy   Computer science   Business school   UTAUT  

摘要： PurposeThis study aims to develops an interdisciplinary business and computer science pedagogy for teaching and learning computer programming in business schools at higher education institutions and explores its associated benefits, challenges and ***/methodology/approachBased on a body of theories, an interdisciplinary pedagogy is developed and tested for programming education in a business context. Meanwhile, based on the unified theory of acceptance and use of technology, the authors used observation study and thematic analysis to explore opportunities, challenges and future improvements associated with this interdisciplinary *** developed pedagogy includes integrating humanism and construction theory, problem-based learning, cognitive development, active instructional strategies, synergy of individual and group programming tasks and creating an encouraging and inclusive learning environment. This study shows that business students perceive this novel pedagogy as highly valuable because it enhances their logical thinking and problem-solving abilities while giving them a sense of accomplishment. Although students face challenges in data preprocessing, error handling and translating theoretical knowledge, they find it useful to review teaching materials, seek peer support and learn independently through online resources. Further improvements in pedagogy include incorporating collaborative code reviews, using shared documents for troubleshooting and grouping students based on their prior programming *** implicationsThis interdisciplinary pedagogy can guide business schools to improve the quality of programming-related modules, enhance students' performance and prepare them for future ***/valueThis is the first interdisciplinary study investigating teaching programming in a business context.

摘要： This article has been retracted: please see Elsevier Policy on Article Withdrawal ( https://***/locate/withdrawalpolicy ). This article has been retracted at the request of the Editor-in-Chief of Theoretical Computer Science, Section A. The article is a duplicate of a paper that has already been published in Int. J. Nonlinear Anal. Appl., Volume 13 (2022), Issue 2, Pages 1893-1905, http://***/10.22075/ijnaa.2022.27403.3588 . One of the conditions of submission of a paper for publication is therefore that authors declare explicitly that the paper has not been previously published and is not under consideration for publication elsewhere. As such this article represents a misuse of the scientific publishing system. The scientific community takes a very strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.

关键词： Heuristic algorithms   Event detection   Predictive control   Prediction algorithms   Electronic mail   Trajectory   Economic indicators   Couplings   Computer science   Circuit stability   Coupled nonlinear systems   distributed model predictive control   dynamic self-triggered mechanism  

摘要： This article proposes a dynamic self-triggered distributed model predictive control algorithm for coupled nonlinear systems facing external disturbances and constraints on state and input variables. A dynamic self-triggered mechanism that combines the advantages of event-triggered and self-triggered strategies is designed to simultaneously reduce the frequencies of both sampling and solving optimization problems. Particularly, the triggering threshold is adaptively adjusted using a dynamic variable, which can effectively balance control performance and computational resources. Furthermore, through the construction of a two-model optimal control problem and the analysis of input-to-state practical stability for the overall system, a single-mode distributed model predictive control framework is established for each subsystem within the proposed algorithm, which enables a fully distributed implementation. Sufficient conditions for recursive feasibility and robust stability are investigated, and conservatism is reduced by eliminating the requirement for the system state to reach the terminal region in finite time. Finally, the effectiveness of the developed algorithm is validated through two numerical examples with comparisons.

关键词： Quantum physics   Computer science   History  

摘要： A century ago, physics had its Darwinian moment - a change in perspective that was as consequential for the physical sciences as the theory of evolution by natural selection was for biology. A century ago, physics had its Darwinian moment - a change in perspective that was as consequential for the physical sciences as the theory of evolution by natural selection was for biology.