NICE 2023 Zero-shot Image Captioning Challenge

In this report, we introduce NICE project\footnote{\url{https://nice.lgresearch.ai/}} and share the results and outcomes of NICE challenge 2023. This project is designed to challenge the computer vision community to develop robust image captioning models that advance the state-of-the-art both in terms of accuracy and fairness. Through the challenge, the image captioning models were tested using a new evaluation dataset that includes a large variety of visual concepts from many domains. There was no specific training data provided for the challenge, and therefore the challenge entries were required to adapt to new types of image descriptions that had not been seen during training. This report includes information on the newly proposed NICE dataset, evaluation methods, challenge results, and technical details of top-ranking entries. We expect that the outcomes of the challenge will contribute to the improvement of AI models on various vision-language tasks.Comment: Tech report, project page https://nice.lgresearch.ai

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Reduction of Ice Adhesion Using Surface Acoustic Waves: Nanoscale Vibration and Interface Heating Effects

Ice accumulation causes great risks to aircraft, electric power lines, and wind-turbine blades. For the ice accumulation on structural surfaces, ice adhesion force is a crucial factor, which generally has two main sources, for exampple, electrostatic force and mechanical interlocking. Herein, we present that surface acoustic waves (SAWs) can be applied to minimize ice adhesion by simultaneously reducing electrostatic force and mechanical interlocking, and generating interface heating effect. A theoretical model of ice adhesion considering the effect of SAWs is first established. Experimental studies proved that the combination of nanoscale vibration and interface heating effects lead to the reduction of ice adhesion on the substrate. With the increase of SAW power, the electrostatic force decreases due to the increase of dipole spacings, which is mainly attributed to the SAW induced nanoscale surface vibration. The interface heating effect leads to the transition of the locally interfacial contact phase from solid–solid to solid–liquid, hence reducing the mechanical interlocking of ice. This study presents a strategy of using SAWs device for ice adhesion reduction, and results show a considerable potential for application in deicing