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In an era of significant geopolitical shifts, unrelenting violent confrontation, nationalism and identity politics, the institutions in which Canada and its allies have invested significant capital such as trade, political, and security organisations are being tested and stretched to the limit. This edition will look back on Canadäs approach to encouraging democracy abroad, it will consider ways to enhance middle power democracy statecraft in an era of growing international and domestic insecurity, backsliding and populism, and discern patterns and recurring themes in Canadian support for rights and democracy, as well as efforts to grapple with novel trends like digital threats to democracy.

The 4th International Symposium on Mechanobiology (ISMB) organized by the Australian Society for Mechanobiology (AuSMB) took place at the Sydney Nanoscience Hub at the University of Sydney, Australia, from the 6th to the 9th of November 2022. This conference started in 2011 with the founding of the Society in Shanghai, China, and has occurred every three years also visiting Okayama (2014) and more recently Singapore (2017). This is the first time this conference was held in Australia.The primary purpose of the 4th International Symposium on Mechanobiology (ISMB) was to act as a forum for dissemination of cutting-edge research and innovation in the field of mechanobiology. It brought together 200+ delegates from both the Australian and International communities (students, scientists, clinicians, engineers and stakeholders from academia, industry and other organisations) working in the broader field of mechanobiology to discuss new and exciting advances in the field. This collection reflects the diverse and multidisciplinary nature of mechanobiology research spanning length scales and organ systems.Chapter 4 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book presents the current trends in deep learning-based object detection framework with a focus on logo detection tasks. It introduces a variety of approaches, including attention mechanisms and domain adaptation for logo detection, and describes recent advancement in object detection frameworks using deep learning. We offer solutions to the major problems such as the lack of training data and the domain-shift issues.This book provides numerous ways that deep learners can use for logo recognition, including: Deep learning-based end-to-end trainable architecture for logo detection Weakly supervised logo recognition approach using attention mechanisms Anchor-free logo detection framework combining attention mechanisms to precisely locate logos in the real-world images Unsupervised logo detection that takes into account domain-shift issues from synthetic to real-world images Approach for logo detection modeling domain adaption task in the context of weakly supervised learning to overcome the lack of object-level annotation problem.The merit of our logo recognition technique is demonstrated using experiments, performance evaluation, and feature distribution analysis utilizing different deep learning frameworks.The book is directed to professors, researchers, practitioners in the field of engineering, computer science, and related fields as well as anyone interested in using deep learning techniques and applications in logo and various object detection tasks.