Development of Formation Flying CubeSats and Operation Systems for the CANYVAL-C Mission: Launch and Lessons Learned

The CubeSat Astronomy NASA and Yonsei using Virtual telescope ALignment for Coronagraph (CANYVAL-C) is a technology demonstration mission that shows the concept of a virtual space telescope using two CubeSats in formation flying. The final goal of the mission is to obtain several images of the solar corona during an artificial solar eclipse created by the two CubeSats, Timon (1U CubeSat) and Pumbaa (2U CubeSat). To implement this mission, two CubeSats in formation flying and a ground segment have been developed. The CubeSats were constructed mainly with commercial off the shelf components, sharing the bus architecture. The payload of each CubeSat is a visible camera and an occulter to block the light from the photosphere of the Sun. The occulter is composed of tape measures and a black-colored polyimide film; the system size is smaller than 0.5U (10 × 10 × 5 cm3) while it stowed and enlarged to 0.75 × 0.75 m2 after spreading the film. The 3D-printed propulsion system is smaller than 0.5U and facilitates accurate positioning maneuvers of Pumbaa. The on-board computer has multi-task processing capabilities and a space-saving configuration which is integrated with the GNSS receiver and the UHF transceiver. The core technology for the mission implementation is the precise formation flying guidance, navigation, and control system with a cold-gas propulsion system and an inter-satellite link system. The specification of each CubeSat system was evaluated using numerical simulations and ground testing. To operate CubeSats, the ground segment was constructed with some components, including the UHF ground station (UGS), flight dynamics system (FDS), mission analysis and planning system (MAPS), and spacecraft operation system (SOS). Each component works under the environment of an integrated graphic user interface. In particular, the UGS handles the RF communication, data storage, and instrument control for tracking CubeSats. The FDS processes the navigation data to precisely estimate absolute position and velocity. Then, the MAPS determines the allowable mission schedule and parameter set for implementing maneuvers of each CubeSat. Using the MAPS, feasibility of the mission operation canbe ensured through numerical simulations based on the solutions from the FDS. Finally, the SOS is the interface system between each component, processing telemetry and generating telecommand. The CubeSats were launched on March 22, 2021, by Soyuz-2.1a with a Fregat stage

Charge-spin correlation in van der Waals antiferromagenet NiPS3

Strong charge-spin coupling is found in a layered transition-metal trichalcogenide NiPS3, a van derWaals antiferromagnet, from our study of the electronic structure using several experimental and theoretical tools: spectroscopic ellipsometry, x-ray absorption and photoemission spectroscopy, and density-functional calculations. NiPS3 displays an anomalous shift in the optical spectral weight at the magnetic ordering temperature, reflecting a strong coupling between the electronic and magnetic structures. X-ray absorption, photoemission and optical spectra support a self-doped ground state in NiPS3. Our work demonstrates that layered transition-metal trichalcogenide magnets are a useful candidate for the study of correlated-electron physics in two-dimensional magnetic material.Comment: 6 pages, 3 figur

A Review of Suicide Risk Assessment Tools and Their Measured Psychometric Properties in Korea

While there has been a slew of review studies on suicide measurement tools until now, there were not any reviews focusing on suicide assessment tools available in Korea. This review aimed to examine the psychometric properties of tools developed in Korea or the translated versions from the original tools in their foreign language and to identify potential improvements and supplements for these tools. A literature search was done using the Korean academic information search service, Research Information Service System, to identify the suicide measures to be included in this review. Abstracts were screened to identify which measures were used to assess suicide-related factors. Based on the established inclusion and exclusion criteria, 18 tools remained and we assessed their psychometric properties. The current review indicated several major findings. First, many of the tools did not report predictive validity and even those with predictive validity were based on past suicide attempts. Second, some of the tools overlooked the interactive component for the cause of suicide. In addition, information to supplement the self-reported and clinician-administered reports by collecting reports from the subjects' families and acquaintances is needed. It is also important to develop a screening tool that examines other aspects of an individual's personal life, including unemployment, bereavement, divorce, and childhood trauma. Moreover, tools that have been studied in more diverse groups of the population are needed to increase external validity. Finally, the linguistic translation of the tools into Korean needs to consider other cultural, social, and psychological factors of the sample of interest

Data Exchange in Cluster Structure for Longevity of IoT

In the Internet of Things (IoT), the scope of wireless sensor nodes is extended to things deployed in a pervasive world. For various IoT service applications, things can gather and share their information with each other through self-decision-making. Therefore, we cannot apply the existing information aggregation methods of wireless sensor networks to the IoT environment, which aim to transmit the collected data to only a sink node or a central server. Moreover, since the existing methods involve all the sensor nodes in the process of data exchange, they can cause an increase in the network traffic, delay of data transmission, and amount of energy consumed by things. In this paper, we propose a clustering-property-based data exchange method for efficient energy consumption in IoT networks. First, the proposed method assigns properties to each thing according to the characteristics of the obtained data. Second, it constructs a cluster network considering the location of things and their energy consumption. Finally, the things in a cluster communicate with other things in a different cluster based on their properties. In the experiment, the proposed method exhibits a better performance than the existing method. Owing to the energy-saving effect, we demonstrate that the proposed method results in a more reliable network and improves the longevity of IoT networks

MinT: Middleware for Cooperative Interaction of Things

This paper proposes an Internet of Things (IoT) middleware called Middleware for Cooperative Interaction of Things (MinT). MinT supports a fully distributed IoT environment in which IoT devices directly connect to peripheral devices easily construct a local or global network, and share their data in an energy efficient manner. MinT provides a sensor abstract layer, a system layer and an interaction layer. These enable integrated sensing device operations, efficient resource management, and active interconnection between peripheral IoT devices. In addition, MinT provides a high-level API to develop IoT devices easily for IoT device developers. We aim to enhance the energy efficiency and performance of IoT devices through the performance improvements offered by MinT resource management and request processing. The experimental results show that the average request rate increased by 25% compared to Californium, which is a middleware for efficient interaction in IoT environments with powerful performance, an average response time decrease of 90% when resource management was used, and power consumption decreased by up to 68%. Finally, the proposed platform can reduce the latency and power consumption of IoT devices

Traffic Measurement on Multiple Drive Lanes with Wireless Ultrasonic Sensors

An automated traffic measuring system for use on multiple drive lanes is proposed in this paper. This system, which uses ultrasonic sensors and a lateral scanning method, is suitable for use on real traffic roads. The proposed system can be easily established and maintained in various roadway environments. In addition, the system can be adjusted to measure traffic volumes according to the size and number of drive lanes. This paper describes the results of an experiment that the lateral scanning method can be easily applied to real traffic roads and provide a low error rate and real-time responses. This system can play an important role in accurately measuring traffic volumes as part of an intelligent transportation system

Relative Orbit Control Algorithms and Scenarios for the Inertial Alignment Hold Demonstration Mission by CubeSat Formation Flying

CANYVAL-C is a formation-flying mission that demonstrates a coronagraph utilizing two CubeSats. The coronagraph is a space telescope that blocks sunlight to examine the overcast regions around the sun. It is composed of optical and occult segments. Two spacecraft were aligned with respect to an inertial system to configure a virtual telescope using inertial alignment hold technology. The relative orbit control scenario for this mission involves rendezvous, differential air drag control, and inertial alignment holding. Orbit control algorithms and simple strategies that can be automatically constructed onboard have also been developed. For each maneuver, the control performance under the errors from navigation, attitude determination and control, and propulsion systems were assessed via Monte Carlo simulation, taking into account the hardware specifications and operations. In addition to the algorithm and strategy of this mission, the relative orbit control scenario was evaluated for its practicability using Monte Carlo simulations. The feasibility of this mission is ensured by a statistical analysis of the prospect of its success during its operation

Targeting Non-Oncogene Addiction for Cancer Therapy

While Next-Generation Sequencing (NGS) and technological advances have been useful in identifying genetic profiles of tumorigenesis, novel target proteins and various clinical biomarkers, cancer continues to be a major global health threat. DNA replication, DNA damage response (DDR) and repair, and cell cycle regulation continue to be essential systems in targeted cancer therapies. Although many genes involved in DDR are known to be tumor suppressor genes, cancer cells are often dependent and addicted to these genes, making them excellent therapeutic targets. In this review, genes implicated in DNA replication, DDR, DNA repair, cell cycle regulation are discussed with reference to peptide or small molecule inhibitors which may prove therapeutic in cancer patients. Additionally, the potential of utilizing novel synthetic lethal genes in these pathways is examined, providing possible new targets for future therapeutics. Specifically, we evaluate the potential of TONSL as a novel gene for targeted therapy. Although it is a scaffold protein with no known enzymatic activity, the strategy used for developing PCNA inhibitors can also be utilized to target TONSL. This review summarizes current knowledge on non-oncogene addiction, and the utilization of synthetic lethality for developing novel inhibitors targeting non-oncogenic addiction for cancer therapy

Deep Learning-Based Pulse Height Estimation for Separation of Pile-Up Pulses From NaI(Tl) Detector

Measured spectra in a high count rate environment are difficult to analyze because of the spectral distortions caused by the pulse pile-up effect. This study proposes a deep learning-based method for separating and predicting the true pulse height of a signal with pulse pile-up events for application to radiation measurement and spectroscopy with a scintillation detector. To train the deep learning model, pulse signals simulating scintillation pulses were prepared by using a predefined mathematical model with parameters determined by analysis of the scintillation pulse measured from a NaI(Tl) detector. To simulate realistic scintillation pulses, Gaussian noises corresponding to thermal and shot noises were added to the signals. The trained model was validated with signals measured from two gamma-ray sources, Na-22 and Cs-137. The model was then evaluated using two performance indicators, restoration and separation rates, which represent how much the net count is restored in the region of interest (ROI) and the separation accuracy depending on the time interval. As a result, the deep learning model was confirmed to correctly estimate the pulse heights in a high pile-up environment up to certain restoration and separation rates.N

Cobalt-Catalyzed C-F Bond Borylation of Aryl Fluorides

A mild and practical cobalt-catalyzed defluoroborylation of fluoroarenes is presented for the first time. The method permits straightforward functionalization of fluoroarenes, with high selectivity for borylation of C-F over C-H bonds, and a tolerance for aerobic conditions. Furthermore, two-step 18F-fluorination was achieved for expanding the scope of 18F-positron emission tomography probes. c. 2018 American Chemical Societ