7 research outputs found
Attention Paper: How Generative AI Reshapes Digital Shadow Industry?
The rapid development of digital economy has led to the emergence of various
black and shadow internet industries, which pose potential risks that can be
identified and managed through digital risk management (DRM) that uses
different techniques such as machine learning and deep learning. The evolution
of DRM architecture has been driven by changes in data forms. However, the
development of AI-generated content (AIGC) technology, such as ChatGPT and
Stable Diffusion, has given black and shadow industries powerful tools to
personalize data and generate realistic images and conversations for fraudulent
activities. This poses a challenge for DRM systems to control risks from the
source of data generation and to respond quickly to the fast-changing risk
environment. This paper aims to provide a technical analysis of the challenges
and opportunities of AIGC from upstream, midstream, and downstream paths of
black/shadow industries and suggest future directions for improving existing
risk control systems. The paper will explore the new black and shadow
techniques triggered by generative AI technology and provide insights for
building the next-generation DRM system
Addressing the Legacy Costs in an NDC Reform: Conceptualization, Measurement, Financing
Complete Tri-Axis Magnetometer Calibration with a Gyro Auxiliary
Magnetometers combined with inertial sensors are widely used for orientation estimation, and calibrations are necessary to achieve high accuracy. This paper presents a complete tri-axis magnetometer calibration algorithm with a gyro auxiliary. The magnetic distortions and sensor errors, including the misalignment error between the magnetometer and assembled platform, are compensated after calibration. With the gyro auxiliary, the magnetometer linear interpolation outputs are calculated, and the error parameters are evaluated under linear operations of magnetometer interpolation outputs. The simulation and experiment are performed to illustrate the efficiency of the algorithm. After calibration, the heading errors calculated by magnetometers are reduced to 0.5° (1σ). This calibration algorithm can also be applied to tri-axis accelerometers whose error model is similar to tri-axis magnetometers
Probing the Proteomics Dark Regions by VAILase Cleavage at Aliphatic Amino Acids
Proteomics emerges from the protein identification to protein functional elucidation, which depends to a large extent on the characterization of protein sequences. However, a large part of proteome sequences remains unannotated due to the limitation in proteolytic digestion by golden standard protease trypsin. Herein, we demonstrated that a cyanobacterial protease VAILase could specifically cleave at the short-chain aliphatic amino acids valine, alanine, leucine, isoleucine and threonine with cleavage specificity about 92% in total for proteomic analysis. The unique features of VAILase cleavage facilitate the characterization of most proteins and exhibit high complementarity to trypsin, and 22% of the covered sequences by VAILase are unique. VAILase can greatly improve the coverages of sequences with abundant aliphatic residues that are usually dark regions in conventional proteomic analysis, such as the transmembrane regions within anion exchanger 1 and photosystem II
Additional file 1 of A 3D “sandwich” co-culture system with vascular niche supports mouse embryo development from E3.5 to E7.5 in vitro
Additional file 1. Statistics of embryonic development