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DAMPE (DArk Matter Particle Explorer) is a satellite-born experiment promoted by the Chinese Academy of Sciences, with the collaboration of Italian and Swiss agencies. Since December 2015, DAMPE flies at the altitude of 500 km and collects data smoothly. The detector is made of four sub-detectors: top layers of plastic scintillators, a silicontungsten tracker, a BGO calorimeter (32 radiation lengths), and a bottom boron-doped scintillator to detect delayed neutrons. The main goal of the experiment is the search for indirect signals of Dark Matter in the electron and photon spectra with energies up to 10 TeV. Furthermore DAMPE studies cosmic charged and gamma radiation. Moreover, the calorimeter depth and the large acceptance allow to measure cosmic ray fluxes in the range from 20 GeV up to hundreds of TeV with unprecedented precision. An overview of the latest results about the charged cosmic rays will be presented.

A disaster is a devastating incident that causes a serious disruption of the functions of a community. It leads to loss of human life and environmental and financial losses. Natural disasters cause damage and privation that could last for months and even years. Immediate steps need to be taken and social media platforms like Twitter help to provide relief to the affected public. However, it is difficult to analyze high-volume data obtained from social media posts. Therefore, the efficiency and accuracy of useful data extracted from the enormous posts related to disaster are low. Satellite imagery is gaining popularity because of its ability to cover large temporal and spatial areas. But, both the social media and satellite imagery require the use of automated methods to avoid the errors caused by humans. Deep learning and machine learning have become extremely popular for text and image classification tasks. In this paper, a review has been done on natural disaster detection through information obtained from social media and satellite images using deep learning and machine learning.

Antenna fingerprinting is critical for a range of physical-layer wireless security protocols to prevent eavesdropping. The fingerprinting process exploits manufacturing defects in the antenna that cause small imperfections in signal waveform, which are unique to each antenna and hence device identity. It is an established process for physical-layer wireless authentication with proven usage systems in terrestrial systems. The premise relies on accurate signal feature discovery from a large set of similar antennas and stable fingerprint patterns over the operational life of the antenna. However, in space, many low-cost satellite antennas suffer degradation from atomic oxygen (AO). This is particularly a problem for nano-satellites or impromptu temporary space antennas to establish an emergency link, both of which are designed to operate for a short time span and are currently not always afforded protective coating. Current antenna fingerprinting techniques only use Support Vector Machine (SVM) and Convolutional Neural Networks (CNNs) to take a snap-shot fingerprint before degradation, and hence fail to capture temporal variations due to degradation. Here, we show how we can perform robust antenna fingerprinting (99.34% accuracy) for up to 198 days under intense AO degradation damage using Recurrent Neural Networks (RNNs). We compare our RNN results with CNNs and SVM techniques using different signal features and for different Low-Earth Orbit (LEO) satellite scenarios. We believe this initial research can be further improved and has real-world impact on physical-layer security of short-term nano-satellite antennas in space.

Wireless sensor network (WSN) has been used in a wide range of applications in recent years. However, its use in space applications has yet to receive the same level of attention. In this paper, a survey on WSN for two major spacecraft applications namely the intra-satellite communication and inter-satellite communication is presented. The challenges and trade-offs will be discussed and a case study of using WSN for inter-satellite communication will be presented.

Taiji-1’s in-orbit magnetic property is significant for the improvement of the satellite’s attitude-control performance and the acceleration noise model of gravitational reference sensor. Test data of satellite drifts have been used to construct the model including interaction among the magnetic field; remnant magnetic moment and induced magnetic moment so as to estimate the satellite’s magnetic property. Using the global optimization method, the remnant magnetic moment of Taiji-1 is estimated to be (-1.42 -0.19 -0.06) Am².

This paper presents a flexible Telemetry, Tracking & Command (TT&C) transponder for Earth Observation (EO) small satellites. The proposed device adds to the state-of-the-art EO TT&C transponders the possibility of scientific data transfer thanks to the high downlink data-rate (up to 40 Mbps) and in-flight reconfigurability via Telecomand (TC). The integration of these features in one single device represents a considerable optimization in terms of mass budget, which is important for EO small satellites. Furthermore, in-flight reconfigurability of communication parameters via TC is important for in-orbit link optimization, which is especially useful for Low-Earth Orbit (LEO) satellites where visibility can be as short as few hundreds of seconds.

The proposed transponder is a digital radio unit working at 70 MHz intermediate frequency (IF). A new custom and configurable hardware accelerator was developed to cover intensive radio DSP functions at IF. The custom hardware is integrated in a single FPGA with a space-compliant processor core, for control, configuration and interface with the other satellite subsystems.

All the quantization parameters were fine-tailored to reach a trade-off between hardware complexity and implementation loss (IL). The IF RX/TX ports require eight bits and seven bits, respectively. The IL is 0.5 dB at BER = 10^-5 for the RX chain.

A system proof-of-concept was implemented on the Xilinx Virtex 6 VLX75T-FF484 FPGA. The total device occupation is 82%. The power consumption of the design fitted in FPGA is less than 2 W. The power consumption of the whole demonstrator board is less than 9 W.

Let $X$ and $Y$ be the complementary regions of a closed hypersurface $M$ in $S^4=X{\cup }_{M}Y$. We use the Massey product structure in $H^{\ast }(M;\mathbb{Z})$ to limit the possibilities for $\chi (X)$ and $\chi (Y)$. We show also that if ${\pi }_1(X)\ne 1$ then it may be modified by a 2-knot satellite construction, while if $\chi (X)\le 1$ and ${\pi }_1(X)$ is abelian then ${\beta }_1(M)\le 4$ or ${\beta }_1(M)=6$. Finally we use TOP surgery to propose a characterization of the simplest embeddings of $F\times S^1$.

Recent development in the applications of high temperature superconductor (HTS) filters is introduced. Breakthrough had been made in ultra selective band-pass filter with extremely small fractional bandwidth for 3G mobile base stations. Satisfactory results were achieved in the space qualification mechanical tests of the HTS filters. Field trail of the meteorological radar showed that with HTS subsystem the sensitivity and anti-interference ability of the radar were greatly improved.

Pairs of genus 2 mutant knots can have different Homfly polynomials, for example some 3-string satellites of Conway mutant pairs. We give examples which have different Kauffman 2-variable polynomials, answering a question raised by Dunfield et al. in their study of genus 2 mutants. While pairs of genus 2 mutant knots have the same Jones polynomial, given from the Homfly polynomial by setting v = s², we give examples whose Homfly polynomials differ when v = s³. We also give examples which differ in a Vassiliev invariant of degree 7, in contrast to satellites of Conway mutant knots.

Using complex database of satellite malfunctions within the period of 1974–1994 and cosmic ray activity indices, calculated by means of high mountain Alma-Ata neutron monitor data it was shown that malfunction frequency increases during seven days after increase of cosmic ray activity indices. It is significant for high altitude satellite with altitude more than 1000 km.