Abstract

Abstract
Several classes of quantum circuits have been shown to provide a quantum computational advantage under certain assumptions. The study of ever more restricted classes of quantum circuits capable of quantum advantage is motivated by possible simplifications in experimental demonstrations. In this paper we study the efficiency of measurement-based quantum computation with a completely flat temporal ordering of measurements. We propose new constructions for the deterministic computation of arbitrary Boolean functions, drawing on correlations present in multi-qubit Greenberger, Horne, and Zeilinger (GHZ) states. We characterize the necessary measurement complexity using the Clifford hierarchy, and also generally decrease the number of qubits needed with respect to previous constructions. In particular, we identify a family of Boolean functions for which deterministic evaluation using non-adaptive MBQC is possible, featuring quantum advantage in width and number of gates with respect to classical circuits.

Abstract
The education sector faces unprecedented challenges, from rapidly evolving technologies to diverse learner needs, placing immense pressure on educators to adapt and innovate. Traditional teaching methods need help to keep pace with the demands of modern education, leading to gaps in personalized learning and student engagement. Ethical concerns surrounding AI integration in education remain a significant hurdle, requiring careful navigation and responsible implementation. Integrating Artificial Intelligence in Education: Enhancing Teaching Practices for Future Learning offers a comprehensive solution by exploring how AI can address these challenges and revolutionize education. Through a collection of insightful contributions, it provides practical strategies for integrating AI into teaching practices, empowering educators to personalize learning experiences and enhance student engagement. By examining AI ethics and responsible education, the book equips educators with the knowledge needed to navigate the ethical complexities of AI integration. This book is a practical guide for educators, researchers, policymakers, and practitioners who want to harness the potential of AI in education. It provides a roadmap for leveraging AI technologies to create adaptive learning environments, automate classroom tasks, and enhance instructional design. With a strong focus on practical insights and ethical considerations, this book is a valuable resource for anyone looking to navigate the intersection of AI and education. © 2025 by IGI Global. All rights reserved.

Abstract

Abstract
The concept of sustainable fashion is becoming more relevant in today's society. The purpose of this research is to identify the determinants of the purchase intention of sustainable fashion, and the relationship between price and the purchase of sustainable fashion. A questionnaire was administered, which made it possible to define the concept of sustainable fashion, to use PLS-SEM to identify the determinants, and to apply linear regression models and t-tests of two independent samples (two-tailed test). The concept of sustainable fashion comprises the dimensions of manufacturing with a reduced environmental impact, consuming second-hand fashion products, manufacturing in an environmentally friendly way, reusing fashion products, manufacturing to last longer, manufacturing according to fair trade principles, using recycled materials, and manufacturing from organic materials. The PLS-SEM results show that purchase intention is determined by consumer knowledge, environmental beliefs, and willingness to pay more. The research also revealed that there is a non-linear (quadratic or exponential) relationship between the price of the product and the price increase that consumers are willing to pay and that they value the dimensions of sustainable fashion differently. The purchase intention determinants of consumers and non-consumers of sustainable fashion are identical, yet the dimensions of sustainable fashion are valued differently by each group.

Abstract
This paper presents a simulation model of a Time of Flight distance sensor applying SimTwo robotics simulator in order to contribute to a mobile robotics application, in an educational context. The objective is to observe the sensor behavior, inside the simulation environment, face a set of experiments, such as an abrupt difference of distance, several angle inclinations and measurements to the maximum sensor range. The tests were performed using SimTwo being a high performance, open source, versatile, real time simulation environment, in which is possible to configure an specific sensor adding its features, which allows to achieve a realistic simulation. The results represented the expected sensor behavior for the proposed scenarios. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.