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Trust and GenAI in Education: A scoping review of the frontier and roads ahead
No full textA scoping review of trust in genAI within formal educatio
Anushrut’s Theory: Magnetically-Assisted Vehicle
No full textAnushrut’s Theory proposes a magnetically-assisted transportation system that reduces mechanical friction and electrical energy consumption by combining passive magnetic lift with active, pulsed electromagnetic propulsion. The core idea is to minimize continuous energy use while maintaining controlled and efficient vehicle motion.
In this theory, the vehicle is equipped with permanent magnets positioned at the front and rear, oriented with like poles facing the magnetic track. These permanent magnets generate a repulsive magnetic force against corresponding magnets embedded in the track. This repulsion partially or fully lifts the vehicle above the guideway, significantly reducing physical contact and mechanical friction. Because permanent magnets do not require electrical power to maintain their magnetic field, this lift mechanism operates passively, contributing to high energy efficiency.
Motion and directional control are achieved using electromagnets placed within the vehicle. Unlike conventional systems that rely on continuous propulsion, Anushrut’s Theory uses short, controlled electrical pulses to the electromagnets. When energized, these electromagnets interact with the magnetic field of the track to generate forward or backward thrust. By pulsing the electromagnets only when acceleration, deceleration, or directional change is required, the system avoids unnecessary energy consumption.
The vehicle operates without wheels, relying entirely on magnetic forces for lift, guidance, and propulsion. A lightweight chassis is essential to maximize the effectiveness of magnetic lift and to maintain system stability. Electronic control units regulate current flow, pulse timing, and direction, allowing smooth and precise motion control.
Anushrut’s Theory is primarily intended as a small-scale, experimental and educational model, demonstrating how magnetic repulsion and intermittent electrical input can work together to create a low-friction, energy-efficient propulsion system. While not designed for immediate high-speed commercial transport, the theory provides a foundation for future research into magnetically assisted vehicles, maglev systems, and hybrid transportation technologies.
In summary, Anushrut’s Theory presents a novel approach to transportation by emphasizing passive magnetic lift, minimal electrical usage, wheel-less motion, and precise control, offering insights into sustainable and efficient mobility systems
FUMIE_Manual_v.2.2.Pdf
No full textAn English version of Uchida & Mori (2018) "FUMIE_Test_Administration_Manual_v.2.2.Pdf.
The Universal Memory Model (UMM): A Multimodal Architecture for Persistent Episodic–Semantic Memory in Artificial Intelligense Systems
No full textThis paper proposes a universal memory architecture for AI systems that supports persistent episodic and semantic memory across multimodal inputs. The Universal Memory Model (UMM) integrates canonicalization, embedding-based encoding, salience filtering, episodic storage, semantic consolidation, contradiction handling, and attention-based retrieval. The model addresses context window limitations, memory drift, and long-term knowledge stability
Mega-Sporting Events as Instruments of Soft Power: A Scoping Review of Destination Image, Place Branding and Sustainability
No full textThis scoping review examines how mega-sporting events function as instruments of soft power, with particular emphasis on their influence on destination image, place branding, and sustainability. By systematically mapping and synthesizing existing literature, the study identifies key themes, theoretical approaches, and methodological trends related to the strategic use of mega-events to shape international perceptions, enhance territorial competitiveness, and promote sustainable development. The review also highlights research gaps and future directions for scholars and policymakers interested in sport, tourism, and global image-making
Measurement of implicit and explicit interpretation bias and its association with depressive symptoms
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BIBLIOMETTRIC ANALYSIS PROTOCOL
No full textThis study explores the integration of Artificial Intelligence (AI) in mathematics education through a bibliometric and scoping analysis of Scopus-indexed literature from 2015 to June 2025. It aims to identify publication trends, influential authors, methodologies, types of scholarly works, research gaps, and future directions for AI in mathematics education. Highlighting AI's potential to enhance teaching and learning, the study addresses a significant gap in region-specific reviews and provides valuable insights for researchers, educators, policymakers, and curriculum designers. Using bibliometric techniques, it seeks to present a comprehensive overview of AI's impact on mathematics education