Technological advances in medical data collection such as high-resolution
histopathology and high-throughput genomic sequencing have contributed to the
rising requirement for multi-modal biomedical modelling, specifically for
image, tabular, and graph data. Most multi-modal deep learning approaches use
modality-specific architectures that are trained separately and cannot capture
the crucial cross-modal information that motivates the integration of different
data sources. This paper presents the Hybrid Early-fusion Attention Learning
Network (HEALNet): a flexible multi-modal fusion architecture, which a)
preserves modality-specific structural information, b) captures the cross-modal
interactions and structural information in a shared latent space, c) can
effectively handle missing modalities during training and inference, and d)
enables intuitive model inspection by learning on the raw data input instead of
opaque embeddings. We conduct multi-modal survival analysis on Whole Slide
Images and Multi-omic data on four cancer cohorts of The Cancer Genome Atlas
(TCGA). HEALNet achieves state-of-the-art performance, substantially improving
over both uni-modal and recent multi-modal baselines, whilst being robust in
scenarios with missing modalities.

采用新技术对医学数据进行收集，如高分辨率组织病理学和高通量基因组测序，为多模态生物医学建模提供了支持。本文介绍了一种灵活的多模态融合架构 —— 混合早期融合注意力学习网络（HEALNet），能够有效处理训练和推断中缺失的模态，提供了最新的多模态基准，并在存在缺失模态的场景中获得卓越性能。

HEALNet -- 混合多模态融合为异构生物医学数据

HEALNet -- Hybrid Multi-Modal Fusion for Heterogeneous Biomedical Data

Satellite communications have recently entered a period of renewed interest
motivated by technological advances and nurtured through private investment and
ventures. The present survey aims at capturing the state of the art in SatComs,
while highlighting the most promising open research topics. Firstly, the main
innovation drivers are motivated, such as new constellation types, on-board
processing capabilities, nonterrestrial networks and space-based data
collection/processing. Secondly, the most promising applications are described
i.e. 5G integration, space communications, Earth observation, aeronautical and
maritime tracking and communication. Subsequently, an in-depth literature
review is provided across five axes: i) system aspects, ii) air interface, iii)
medium access, iv) networking, v) testbeds & prototyping. Finally, a number of
future challenges and the respective open research topics are described.

本文对卫星通信的现状进行了调研，首先介绍了主要创新驱动力如新型星座、机载处理能力、非地球网络和基于空间的数据收集 / 处理；然后，描述了最有前景的应用，如 5G 集成、空间通信、地球观测、航空和海上跟踪与通信；随后，本文提供了五个维度的深入文献综述: i) 系统方面，ii) 空气接口，iii) 媒体访问，iv) 网络，v) 试验平台和原型制作。最后，描述了未来的一些挑战和相应的研究课题。

新空间时代的卫星通信：调查与未来挑战

Satellite Communications in the New Space Era: A Survey and Future  Challenges

Photonic quantum technologies represent a promising platform for several
applications, ranging from long-distance communications to the simulation of
complex phenomena. Indeed, the advantages offered by single photons do make
them the candidate of choice for carrying quantum information in a broad
variety of areas with a versatile approach. Furthermore, recent technological
advances are now enabling first concrete applications of photonic quantum
information processing. The goal of this manuscript is to provide the reader
with a comprehensive review of the state of the art in this active field, with
a due balance between theoretical, experimental and technological results. When
more convenient, we will present significant achievements in tables or in
schematic figures, in order to convey a global perspective of the several
horizons that fall under the name of photonic quantum information.

本文全面回顾了光子量子技术的现状，特别关注了单光子的优点及其在量子信息处理，远距离通信，复杂现象仿真等领域的广泛应用和最新技术进展。