In the solar system, Icy Worlds such as Europa and Enceladus hold great potential for extraterrestrial life and may provide humanity an answer, within this century, to the age-old question of life beyond Earth. Exo-AUV technology shows promise in life detection in the icy shell, at the ice-water interface and on the seafloor of Exo-ocean. Space agencies, including NASA and DLR, are enthusiastic about deploying Exo-AUVs to explore life in these regions. However, the where and how to find life, the technologies to be utilized and the goals to be achieved are crucial aspects for future Exo-AUV life detection missions on Icy Worlds. This study delves into a hypothetical mission of life detection on Europa, discussing science goals, detectable objects, potential regions and biogenic analysis for Icy Worlds. It proposes a life detection strategy for Icy Worlds based on Exo-AUVs, presents key contextual elements for Exo-AUV operations, outlines technological requirements for hull, payloads and autonomy, introduces the current state of Exo-AUV research and addresses existing challenges. This study also suggests a roadmap for conceptual development of Exo-AUV and a Concept of Operations for Multiple Exo-AUV System (ConOps for MEAS). This system aims to assist planetary scientists and astrobiologists in exploring Icy Worlds, identifying robust biosignatures and potentially discovering extant organisms, even prebiotic chemical systems.

Recently, the group led by Chuan-Feng Li and Zong-Quan Zhou at University of Science and Technology of China has successfully demonstrated an integrated spin-wave quantum memory, by implementing spin-wave quantum storage protocols using a specially developed device.

The Defence Resources Agency and TalTech have joined forces to jointly develop technologies and efficient technical solutions aimed at strengthening national defense. The Agency offers engineering and IT students opportunities to address national defense challenges as part of their studies and theses, and assists the university in finding supervisors with expertise in national defense. The first tasks have already been assigned to the students.

An adaptive capacitor that can sense and learn through optical stimuli enables learning and recognition tasks.

Pollination by animals contributes to a third of global food production, but little research has been done into the extent to which the identity of pollinators, pollen and crop varieties influence fruit quality when it comes to the nutritional, sensory and commercial value of crops. Pollinators influence the quality of crops through their movement patterns on the plantations and through the plant variety they visit. In an article published in Trends in Plant Science, researchers from the University of Göttingen argue that the blanket promotion of pollinators has so far been too much of a priority – at the expense of plant quality, which could be improved by taking into account the species-specific behaviour of pollinators and the distribution patterns of crop varieties in the field.

In recent years, the advancement of multimodal large language models (MLLMs) has increasingly demonstrated their potential in medical data mining. However, the diversity and heterogeneity nature of medical images and radiology reports can pose significant challenges to the universality of data mining methods.

To address these challenges, a team led by Dr. Xin Zhang from the Institute of Medical Research, Northwestern Polytechnical University in Xi’an, China, systematically evaluated the performance of Gemini and GPT-series models across various medical tasks. Their findings validate the application potential of multimodal large models in the medical domain.