An Introduction to SPEARS (Spectrum Education Awareness)

This presentation provides an overview of the SPectrum Education AwaRenesS (SPEARS) initiative developed by the NASA Spectrum Office under HEO/SCaN. SPEARS is a strategic initiative that is comprised of fourteen (14) activities/tasks targeted for various stakeholders within and external to NASA and from the spectrum and non-spectrum communities. These activities will also facilitate fostering partnerships and enhance the regulatory and policy understanding with international spectrum regulators and other space agencies. Further, SPEARS will institute several activities geared to promote spectrum management and to gain the interest of the next and future generations of spectrum managers, through Science, Technology, Engineering, and Mathematics (STEM) outreach

Role of Notch signaling pathway in bone marrow mesenchymal stem cell therapy for phosgene inhalationinduced lung injury in rats

Purpose: To determining the expression and role of the Notch signaling pathway (NSP) in phosgene inhalation-induced lung injury in rats, and the therapeutic effect of bone marrow mesenchymal stem cell (MSC) on the lung lesions.Methods: Wistar rats (220 - 280 g) were randomly assigned to air inhalation group, phosgene inhalation group, and mesenchymal stem cell (MSC) intervention group. Each group had 8 rats. Directional flow phosgene inhalation device was used to produce phosgene inhalation-induced lung injury in the rats. Serum inflammatory cytokines (TNF-α, IL-8 and IL-6) were determined using ELISA assay kits. The expressions of proteins related to the NSP (Notch1, Notch2, Hes1, Hes5) were quantified using Western blot.Results: Phosgene inhalation brought about significant increase in TNF-α, IL-8 and IL-6 levels (p < 0.01), but MSC intervention significantly reduced the expressions of these inflammatory factors to varying degrees (p < 0.05), although their levels were still significantly high, relative to the air inhalation group. Results from western blot showed that the Notch1, Notch2, Hes1 and Hes5 were upregulated in the phosgene inhalation group, when relative to the air inhalation group (p < 0.01). Protein expressions in the MSC intervention group were lower than those in the non-intervention groups (p < 0.05).Conclusion: Phosgene inhalation activates Notch signaling pathway, while MSC intervention inhibits this signaling pathway. Thus, inhibition of NSP may be implicated in the protective effect of MSC therapy against phosgene-induced lung injury.Keywords: Phosgene, Lung injury, Notch signalling pathway, Mesenchymal stem cell

On the Construction of Lightweight Orthogonal MDS Matrices

In present paper, we investigate 4 problems. Firstly, it is known that, a matrix is MDS if and only if all sub-matrices of this matrix of degree from 1 to $n$ are full rank. In this paper, we propose a theorem that an orthogonal matrix is MDS if and only if all sub-matrices of this orthogonal matrix of degree from 1 to $\lfloor\frac{n}{2}\rfloor$ are full rank. With this theorem, calculation of constructing orthogonal MDS matrices is reduced largely. Secondly, Although it has been proven that the $2^d\times2^d$ circulant orthogonal matrix does not exist over the finite field, we discover that it also does not exist over a bigger set. Thirdly, previous algorithms have to continually change entries of the matrix to construct a lot of candidates. Unfortunately, in these candidates, only very few candidates are orthogonal matrices. With the matrix polynomial residue ring and the minimum polynomials of lightweight element-matrices, we propose an extremely efficient algorithm for constructing $4\times4$ circulant orthogonal MDS matrices. In this algorithm, every candidate must be an circulant orthogonal matrix. Finally, we use this algorithm to construct a lot of lightweight results, and some of them are constructed first time

CP-consensus: a Blockchain Protocol Based on Synchronous Timestamps of Compass Satellite

Bitcoin, the first decentralized cryptocurrency, achieves great success but also encounters many challenges. In this paper, we mainly focus on Bitcoin\u27s five challenges: low network synchronization; poor throughput; high information propagation delay; vulnerabilities to fork-based attacks and consumption of a large amount of computational power to maintain the blockchain. To address these challenges, we present the CP-consensus, a blockchain protocol based on synchronous timestamps of the Compass satellite. Firstly, CP-consensus provides a quasi-synchronous network for nodes. Specifically, nodes synchronously begin or end in each phase. Secondly, the block propagation delay is significantly reduced by adopting cache-nodes. Moreover, the block verification delay is significantly reduced since it is limited only by the size of block-header. Thirdly, CP-consensus has a high throughput with a larger block size since that the block size does not influence the consistency of CP-consensus. Fourthly, CP-consensus resists fork-based attacks and consumes a small amount of computational power. Finally, parameters setting and the security of CP-consensus are discussed

Loamit: A Blockchain-based Residual Loanable-limit Query System

Currently, the blockchain technology is experiencing an exponential growth in the academia and industry. Blockchain may provide the fault-tolerance, tamper-resistance, credibility and privacy to users. In this paper, we propose a blockchain-based residual loanable-limit query system, called Loamit. Firstly, to the best of our knowledge, it is the first work to prevent that a client, who lacks the ability to repay, borrows an un-repayable amount of money from independent banks without releasing the personal privacy of client. Specifically, if a client wants to borrow a certain amount of money from a bank, then the bank can get the client\u27s residual loanable-limit in the alliance of banks without knowing details of the client\u27s previous loans and repayments. Secondly, most of data in Loamit is verifiable. Therefore, malicious banks can be checked out. Thirdly, Loamit is fault-tolerant since it may work smoothly as long as a certain number of banks are active and honest. Finally, we deploy the Loamit system on the Ethererum private blockchain and give the corresponding performance evaluation

SARS-CoV-2 Vaccine-Related Liver Failure: Active Hepatitis B and Comprehensive Literature Analysis

SARS-CoV-2 infection or vaccination is closely associated with liver injury, and autoimmune hepatitis episodes have been described, but liver failure has not been reported. Here, we report the case of a 41-year-old man, presenting with fatigue, anorexia after activity, greasy, decreased intake, yellow urine, and occasionally acid reflux in the stomach, occurring 2–3 weeks after receiving the first dose of inactivated SARS-CoV-2 vaccination, thought to be associated with his underlying chronic hepatitis B and fatty liver condition. The patient took the drug irregularly and did not achieve viral conversion to negative and appear rtA181T-resistant HBV mutation. Recently, the laboratory results showed abnormal liver function with high alanine aminotransferase (ALT), aspartate aminotransferase (AST), and γ-glutamyl transferase (GGT), and there was no improvement in liver function after hepatoprotective therapy, and the serum hepatitis B virus (HBV) concentration was greater than 2.0 × 106 IU/mL. Later, after being admitted to our hospital, it was found that he was in, malaise, jaundice, his eyes and sclera were yellow, his lungs were coarse breath sounds, his liver function was abnormally elevated, and his HBV virus developed a drug-resistant mutation. He has no history of autoimmune disease and tests negative for autoimmune antibodies. He became severely ill after intermittently stopping HBV treatment, worsened liver injury after inactivated SARS-CoV-2 vaccination, and was diagnosed with acute-on-chronic liver failure (ACLF). By summarizing the case report, it will provide important information on the vaccine safety assessment of vaccine components, immunization routes, and dosage for people with underlying liver disease

Long-lived quantum memory enabling atom-photon entanglement over 101 km telecom fiber

Long-distance entanglement distribution is the key task for quantum networks, enabling applications such as secure communication and distributed quantum computing. Here we report on novel developments extending the reach for sharing entanglement between a single $^{87}$Rb atom and a single photon over long optical fibers. To maintain a high fidelity during the long flight times through such fibers, the coherence time of the single atom is prolonged to 7 ms by applying a long-lived qubit encoding. In addition, the attenuation in the fibers is minimized by converting the photon's wavelength to the telecom S-Band via polarization-preserving quantum frequency conversion. This enables to observe entanglement between the atomic quantum memory and the emitted photon after passing 101 km of optical fiber with a fidelity better than 70.8$\pm$2.4%. The fidelity, however, is no longer reduced due to loss of coherence of the atom or photon but in the current setup rather due to detector dark counts, showing the suitability of our platform to realize city-to-city scale quantum network links.Comment: 11 pages, 8 figures, comments are welcom

SHMC-Net: A Mask-guided Feature Fusion Network for Sperm Head Morphology Classification

Male infertility accounts for about one-third of global infertility cases. Manual assessment of sperm abnormalities through head morphology analysis encounters issues of observer variability and diagnostic discrepancies among experts. Its alternative, Computer-Assisted Semen Analysis (CASA), suffers from low-quality sperm images, small datasets, and noisy class labels. We propose a new approach for sperm head morphology classification, called SHMC-Net, which uses segmentation masks of sperm heads to guide the morphology classification of sperm images. SHMC-Net generates reliable segmentation masks using image priors, refines object boundaries with an efficient graph-based method, and trains an image network with sperm head crops and a mask network with the corresponding masks. In the intermediate stages of the networks, image and mask features are fused with a fusion scheme to better learn morphological features. To handle noisy class labels and regularize training on small datasets, SHMC-Net applies Soft Mixup to combine mixup augmentation and a loss function. We achieve state-of-the-art results on SCIAN and HuSHeM datasets, outperforming methods that use additional pre-training or costly ensembling techniques.Comment: Published on ISBI 202