Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

Many industrial sectors face increasing production demands and the need to reduce costs, without compromising the quality. The use of robotics and automation has grown significantly in recent years, but versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs for specific manufacturing tasks still relies on programming trajectory waypoints by hand. The use of virtual simulation software and the availability of the specimen digital models can facilitate robot programming. Nevertheless, in many cases, the virtual models are not available or there are excessive differences between virtual and real setups, leading to inaccurate robot programs and time-consuming manual corrections. Previous works have demonstrated the use of robot-manipulated optical sensors to map the geometry of samples. However, the use of simple user-defined robot paths, which are not optimized for a specific part geometry, typically causes some areas of the samples to not be mapped with the required level of accuracy or to not be sampled at all by the optical sensor. This work presents an autonomous framework to enable adaptive surface mapping, without any previous knowledge of the part geometry being transferred to the system. The novelty of this work lies in enabling the capability of mapping a part surface at the required level of sampling density, whilst minimizing the number of necessary view poses. Its development has also led to an efficient method of point cloud down-sampling and merging. The article gives an overview of the related work in the field, a detailed description of the proposed framework and a proof of its functionality through both simulated and experimental evidences

Use of the Resection Map system as guidance during hepatectomy

Industrial DesignIndustrial Design Engineerin

Tumor-derived GDF-15 blocks LFA-1 dependent T cell recruitment and suppresses responses to anti-PD-1 treatment

Immune checkpoint blockade therapy is beneficial and even curative for some cancer patients. However, the majority don’t respond to immune therapy. Across different tumor types, pre-existing T cell infiltrates predict response to checkpoint-based immunotherapy. Based on in vitro pharmacological studies, mouse models and analyses of human melanoma patients, we show that the cytokine GDF-15 impairs LFA-1/β2-integrin-mediated adhesion of T cells to activated endothelial cells, which is a pre-requisite of T cell extravasation. In melanoma patients, GDF-15 serum levels strongly correlate with failure of PD-1-based immune checkpoint blockade therapy. Neutralization of GDF-15 improves both T cell trafficking and therapy efficiency in murine tumor models. Thus GDF-15, beside its known role in cancer-related anorexia and cachexia, emerges as a regulator of T cell extravasation into the tumor microenvironment, which provides an even stronger rationale for therapeutic anti-GDF-15 antibody development. Experimental cancer immunology and therap

Moving from research generation to knowledge translation in end-of-life care in long term care

The recognition and importance of the need for palliative or end-of-life care in long term care has, over the last two decades, led to increased research, education and practice development initiatives in most developed countries. The breadth and depth of some of these initiatives has been catalogued by the European Association of Palliative Care Taskforce on Palliative Care in Long Term Care Settings for Older People.1,2 In total over 60 initiatives across 13 European countries were identified. These initiatives were mapped by level of change – that is at the national, regional, organisational, team or individual level, with many targeting more than one level. Unfortunately not possible as part of this mapping activity, was an evaluation to examine if any of these initiatives successfully translated into sustained knowledge or practice change. What is vital for improving end-of-life care for residents and families in long term care is for clinicians, researchers and policy makers to engage, not only in the generation of knowledge by engaging in research and knowledge dissemination from the publication of results in academic journals, but also the transfer of research-based knowledge into a form that can be used. This process is often referred to as knowledge translation (KT).3 KT focuses on methods or processes to increase clinician’s practice knowledge to improve outcomes and reduce the evidence–practice gap. The nexus between knowledge generation and KT is the synthesis of what is known on a topic (the best evidence available) and what will work in a local context