Indole-Based Compounds as Promising Inhibitors of SARS-CoV-2

This review focused on the recent development of indole-based compounds as anti- SARS-CoV-2 agents with focus on the following objectives: 1) present the design strategy of indole-based compounds as promising inhibitors; 2) focus on recent developments of indole-based compounds and their anti-severe acute respiratory syndrome  coronavirus 2 and anti-severe acute respiratory syndrome coronavirus  activities; 3) summarize molecular docking and the structure–activity relationship, in hopes to inspire the development of new and more creative approaches; and 4) offer perspectives on how indole scaffolds might be exploited in the future

Insecurity of detector-device-independent quantum key distribution

Detector-device-independent quantum key distribution (ddiQKD) held the promise of being robust to detector side-channels, a major security loophole in QKD implementations. In contrast to what has been claimed, however, we demonstrate that the security of ddiQKD is not based on post-selected entanglement, and we introduce various eavesdropping strategies that show that ddiQKD is in fact insecure against detector side-channel attacks as well as against other attacks that exploit device's imperfections of the receiver. Our attacks are valid even when the QKD apparatuses are built by the legitimate users of the system themselves, and thus free of malicious modifications, which is a key assumption in ddiQKD.Comment: 7 pages, 5 figures, 1 tabl

Breast Pump for Low-Resource Settings

ME450 Capstone Design and Manufacturing Experience: Winter 2015Exclusive breastfeeding for the first six months of life is highly recommended by the United Nations Children’s Fund (UNICEF) and World Health Organization (WHO) based on its extraordinary range of benefits to both mothers and children. However, only 15% of infants aged 0 to 6 months in some least developed countries such as Nigeria and only 38% of infants worldwide are exclusively breastfed. The low breastfeeding rates are due in large part to a mother’s need to return to work, where mothers have no access to breastfeeding or expressing breast milk at work. Existing commercial grade and personal-use breast pumps are cost prohibitive and difficult to maintain for mothers in low-resource settings where clean water is a challenge and electricity is not available. Therefore, the team designed and prototyped a cheap, easy to clean, and easy to maintain breast pump for working mothers in low-resource settings.http://deepblue.lib.umich.edu/bitstream/2027.42/111327/1/09_Report.pd

Hyperbolic Space with Hierarchical Margin Boosts Fine-Grained Learning from Coarse Labels

Learning fine-grained embeddings from coarse labels is a challenging task due to limited label granularity supervision, i.e., lacking the detailed distinctions required for fine-grained tasks. The task becomes even more demanding when attempting few-shot fine-grained recognition, which holds practical significance in various applications. To address these challenges, we propose a novel method that embeds visual embeddings into a hyperbolic space and enhances their discriminative ability with a hierarchical cosine margins manner. Specifically, the hyperbolic space offers distinct advantages, including the ability to capture hierarchical relationships and increased expressive power, which favors modeling fine-grained objects. Based on the hyperbolic space, we further enforce relatively large/small similarity margins between coarse/fine classes, respectively, yielding the so-called hierarchical cosine margins manner. While enforcing similarity margins in the regular Euclidean space has become popular for deep embedding learning, applying it to the hyperbolic space is non-trivial and validating the benefit for coarse-to-fine generalization is valuable. Extensive experiments conducted on five benchmark datasets showcase the effectiveness of our proposed method, yielding state-of-the-art results surpassing competing methods.Comment: Accepted by NeurIPS 202