Autonomous navigation of spacecraft formations for asteroid exploration

This paper presents an autonomous multi-sensor navigation approach for a formation of spacecraft flying in the proximity of a near Earth asteroid.Each spacecraft embarks a different combination of high resolution cameras, attitude sensors and LIDAR to estimate the stateof each spacecraft in the formation. The work investigates the combination of measurements coming from multiple heterogeneous sensors and nonlinear sequential filtering technique to enable a formation to autonomously navigate in the proximity of asteroids. This work is divided into two parts. Firstly, each spacecraft employs an Unscented Kalman Filter to data fuse multi-sensor measurements of the relative position of the spacecraft with respect to the asteroid possibly combined with measurements of the relative position of the spacecraft within the formation, thus determining position and velocity of each member. Secondly, the combination of the autonomous orbit determination with absolute measurements is considered. Absolute measurements include range and range rate measurements from the ground station and pseudo range rate measurements from on board Sun Doppler shift sensor. The combination of the two sets of measurements and state estimations from on-board and ground provides an interesting mean to accurately determine the orbit of asteroids

Quasi-biennial oscillation of the ionospheric wind dynamo

The interannual variation of the ionospheric solar quiet (Sq) current system is examined. A dense magnetometer network over Japan enables the accurate determination of the central position of the northern Sq current loop or the Sq current focus, during 1999–2015. It is found that the Sq focus latitude undergoes an interannual variation of ±2° with a period of approximately 28 months, similar to the quasi-biennial oscillation (QBO) in the tropical lower stratosphere. The QBO-like variation of Sq is particularly evident during 2005–2013. No corresponding interannual variability is found in solar extreme ultraviolet radiation. Comparisons with tidal winds, derived from a whole-atmosphere model, reveal that the QBO-like variation of the Sq current focus is highly correlated with the amplitude variations of migrating and nonmigrating diurnal tides in the lower thermosphere. The results suggest that the stratospheric QBO can influence the ionospheric wind dynamo through the QBO modulation of tides

Mechanical properties of in-situ synthesis of Ti-Ti3Al metal composite prepared by selective laser melting

Titanium composite strengthened by Ti3Al precipitations is considered to be one of the excellent materials that is widely used in engineering. In this work, we prepared a kind of Ti-Ti3Al metallic composite by in-situ synthesis technology during the SLM (selective laser melting) process, and analyzed its microstructure, wear resistance, microhardness, and compression properties. The results showed that the Ti-Ti3Al composite, prepared by in-situ synthesis technology based on SLM, had more homogeneous Ti3Al-enhanced phase dispersion strengthening structure. The grain size of the workpiece was about 1 μm, and that of the Ti3Al particle was about 200 nm. Granular Ti3Al was precipitated after the aluminum-containing workpiece formed, with a relatively uniform distribution. Regarding the mechanical properties, the hardness (539 HV) and the wear resistance were significantly improved when compared with the Cp-Ti workpiece. The compressive strength of the workpiece increased from 886.32 MPa to 1568 MPa, and the tensile strength of the workpiece increased from 531 MPa to 567 MPa after adding aluminum. In the future, the combination of in-situ synthesis technology and SLM technology can be used to flexibly adjust the properties of Ti-based materials

Protease‐Activatable Hybrid Nanoprobe for Tumor Imaging

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108698/1/adfm201400419.pd

Language teacher motivation in online contexts:The evolution of possible language teacher selves

This study investigates the motivation of language teachers through the lens of possible language teacher selves (Kubanyiova, 2009) in the context of online teaching, exploring how motivation evolves over time. Using a longitudinal qualitative approach, the study utilised semi-structured interviews and teaching diaries with 14 secondary school language teachers in China. Findings reveal that teachers’ motivation towards online teaching was multifaceted, with all participants establishing well-elaborated future self-images and nurturing expectations for their roles in future online teaching contexts. The study highlights the temporal dimension of teachers’ motivation, focusing on the evolving, dynamic shifts in the transformative patterns of possible language teacher selves. Notably, agency developed as a result of the evolving motivational change between participants’ ideal, ought-to, and feared selves, driving teachers to take agentive steps toward online pedagogy and inclusive educational practices. This process created a reinforcing cycle, where agency not only emerged from the transformation of possible selves but also reciprocally influenced the development of participants’ possible selves. The findings suggest that possible language teacher selves could serve as a theoretical framework for designing teacher professional development programmes, emphasising the cultivation of ideal selves and the transformation of feared and ought-to selves in order to enhance teachers’ agency

Statistical Study of Coincident Observations of Stratospheric Concentric Gravity Waves and Concentric Traveling Ionospheric Disturbances over the Continental U.S. in 2022

The 15th Symposium on Polar Science/Ordinary sessions [OS] Space and upper atmospheric sciences, Wed. 4 Dec. / 3F Conference room, The Institute of Statistical Mathematicsconference outpu

Simultaneous Mental Fatigue and Mental Workload Assessment with Wearable High-Density Diffuse Optical Tomography

Accurately assessing mental states—such as mental workload and fatigue— is crucial for ensuring the reliability and effectiveness of brain-computer interface (BCI)-based applications. Relying on signals from a limited brain region with low spatial resolution may fail to capture the full scope of relevant information. To address this, high-density diffuse optical tomography (HD-DOT), an emerging form of functional near-infrared spectroscopy (fNIRS) was employed in this study, which provides higher spatial resolution for hemodynamic measurements and enables the reconstruction of 3D brain images. An experiment protocol was designed to investigate both mental workload and fatigue, two critical components of cognitive state that often fluctuate concurrently in real-world scenarios. Machine learning methods were applied for subject-specific classification, achieving 95.14% mean accuracy for fatigue/non-fatigue and 97.93% for four n-back tasks using Random Forest, outperforming Support Vector Machines. These results highlight the transformative potential of HD-DOT in advancing multifaceted cognitive state assessment, paving the way for more precise, adaptable, and powerful BCI applications

NDN blockchain network topology performance analysis and optimization model

In order to further improve the network layer transmission performance of the blockchain system based on named data networking (NDN), a performance analysis and optimization model for the NDN blockchain network topology was proposed. The model included methods for calculating block synchronization time and block transmission redundancy in the NDN blockchain system, a network topology scoring system based on block synchronization time and block transmission redundancy, and an optimization scheme based on network topology attributes and scores. The model addressed the incompatibility of blockchain network topology evaluation models based on TCP/IP with NDN blockchain. Given the known network environment parameters and NDN network layer data synchronization methods, the performance metrics were calculated and analyzed, providing optimization solutions for actual NDN blockchain networking. The experimental results show that after analyzing and optimizing a 9-node network topology using this model, the optimized network topology reduces block synchronization time from 2.95 seconds to 2.37 seconds, a decrease of 19.66%, while maintaining the block transmission redundancy unchanged, and increases the score from 0.64 to 0.82. This demonstrates that the model has a good effect on improving the performance of NDN blockchain