Crystal structure of the outer membrane protein OmpU from Vibrio cholerae at 2.2 Å resolution

Vibrio cholerae causes a severe disease that kills thousands of people annually. The outer membrane protein OmpU is the most abundant outer membrane protein in V. cholerae, and has been identified as an important virulence factor that is involved in host-cell interaction and recognition, as well as being critical for the survival of the pathogenic V. cholerae in the host body and in harsh environments. The mechanism of these processes is not well understood owing to a lack of the structure of V. cholerae OmpU. Here, the crystal structure of the V. cholerae OmpU trimer is reported to a resolution of 2.2 Å. The protomer forms a 16-β-stranded barrel with a noncanonical N-terminal coil located in the lumen of the barrel that consists of residues Gly32–Ser42 and is observed to participate in forming the second gate in the pore. By mapping the published functional data onto the OmpU structure, the OmpU structure reinforces the notion that the long extracellular loop L4 with a β-hairpin-like motif may be critical for host-cell binding and invasion, while L3, L4 and L8 are crucially implicated in phage recognition by V. cholerae

Detecting Targets above the Earth's Surface Using GNSS-R Delay Doppler Maps: Results from TDS-1

: Global Navigation Satellite System (GNSS) reflected signals can be used to remotely sense the Earth’s surface, known as GNSS reflectometry (GNSS-R). The GNSS-R technique has been applied to numerous areas, such as the retrieval of wind speed, and the detection of Earth surface objects. This work proposes a new application of GNSS-R, namely to detect objects above the Earth’s surface, such as low Earth orbit (LEO) satellites. To discuss its feasibility, 14 delay Doppler maps (DDMs) are first presented which contain unusually bright reflected signals as delays shorter than the specular reflection point over the Earth’s surface. Then, seven possible causes of these anomalies are analysed, reaching the conclusion that the anomalies are likely due to the signals being reflected from objects above the Earth’s surface. Next, the positions of the objects are calculated using the delay and Doppler information, and an appropriate geometry assumption. After that, suspect satellite objects are searched in the satellite database from Union of Concerned Scientists (UCS). Finally, three objects have been found to match the delay and Doppler conditions. In the absence of other reasons for these anomalies, GNSS-R could potentially be used to detect some objects above the Earth’s surface.Peer ReviewedPostprint (published version

Analyzing Anomalous Artefacts in TDS-1 Delay Doppler Maps

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Global Navigation Satellite System Reflectometry (GNSS-R) uses the GNSS reflected signals to study parameters of the Earth's surface such as ocean surface height, wind speed, soil moisture, sea surface target detection. In this paper fourteen DDMs (Delay Doppler Maps) of TechDemoSat-1 (TDS-1) containing anomalous artefacts are presented and analyzed. Anomalous artefacts are not caused by the reflection from Earth surface targets, occultation, nor the leakages of direct signals, but likely - according to their delays- from reflection of targets above the Earth's surface (either airborne or spaceborne).Postprint (author's final draft

Roles of Scaling and Instruction Tuning in Language Perception: Model vs. Human Attention

Recent large language models (LLMs) have revealed strong abilities to understand natural language. Since most of them share the same basic structure, i.e. the transformer block, possible contributors to their success in the training process are scaling and instruction tuning. However, how these factors affect the models' language perception is unclear. This work compares the self-attention of several existing LLMs (LLaMA, Alpaca and Vicuna) in different sizes (7B, 13B, 30B, 65B), together with eye saccade, an aspect of human reading attention, to assess the effect of scaling and instruction tuning on language perception. Results show that scaling enhances the human resemblance and improves the effective attention by reducing the trivial pattern reliance, while instruction tuning does not. However, instruction tuning significantly enhances the models' sensitivity to instructions. We also find that current LLMs are consistently closer to non-native than native speakers in attention, suggesting a sub-optimal language perception of all models. Our code and data used in the analysis is available on GitHub