Branching Exponents of Synthetic Vascular Trees under Different Optimality Principles

Objective: The branching behavior of vascular trees is often characterized using Murray's law. We investigate its validity using synthetic vascular trees generated under global optimization criteria. Methods: Our synthetic tree model does not incorporate Murray's law explicitly. Instead, we show that its validity depends on properties of the optimization model and investigate the effects of different physical constraints and optimization goals on the branching exponent that is now allowed to vary locally. In particular, we include variable blood viscosity due to the Fåhræus–Lindqvist effect and enforce an equal pressure drop between inflow and the micro-circulation. Using our global optimization framework, we generate vascular trees with over one million terminal vessels and compare them against a detailed corrosion cast of the portal venous tree of a human liver. Results: Murray's law is fulfilled when no additional constraints are enforced, indicating its validity in this setting. Variable blood viscosity or equal pressure drop lead to different optima but with the branching exponent inside the experimentally predicted range between 2.0 and 3.0. The validation against the corrosion cast shows good agreement from the portal vein down to the venules. Conclusion: Not enforcing Murray's law increases the predictive capabilities of synthetic vascular trees, and in addition reduces the computational cost. Significance: The ability to study optimal branching exponents across different scales can improve the functional assessment of organs

Fingerprinting Soft Materials: A Framework for Characterizing Nonlinear Viscoelasticity

We introduce a comprehensive scheme to physically quantify both viscous and elastic rheological nonlinearities simultaneously, using an imposed large amplitude oscillatory shear (LAOS) strain. The new framework naturally lends a physical interpretation to commonly reported Fourier coefficients of the nonlinear stress response. Additionally, we address the ambiguities inherent in the standard definitions of viscoelastic moduli when extended into the nonlinear regime, and define new measures which reveal behavior that is obscured by conventional techniques.Comment: 10 pages, 3 figures, full-page double-space preprint forma

Calf health veterinary services: Making them work for calves, farmers and veterinarians

Background Despite an appetite among UK veterinarians (vets) and farmers to improve calf health, vets face challenges in delivering and sustaining proactive calf health services. Methods Forty-six vets and 10 veterinary technicians (techs) participated in a project to determine what makes calf health services successful while improving their own services. In four facilitated workshops and two seminars, carried out between August 2021 and April 2022, participants described their approaches to calf work, discussed measures of success, identified challenges and success factors, and addressed knowledge gaps. Results Many approaches to calf health services were described, and these could be categorised into three overlapping models. Success involved enthusiastic, knowledgeable vets/techs, supported by their practice team, fostering positive attitudes among farmers by providing the services they need, creating a tangible return on investment for farmers and the practice. Lack of time was identified as the most prominent challenge to achieving success. Limitations Participants were self-selected from one nationwide group of practices. Conclusion Successful calf health services depend on identifying the needs of calves, farmers and veterinary practices, and delivering measurable benefits to each. More calf health services embedded as a core part of farm veterinary practice could bring wide ranging benefits to calves, farmers and vets

First-in-human real-time AI-assisted instrument deocclusion during augmented reality robotic surgery

The integration of Augmented Reality (AR) into daily surgical practice is withheld by the correct registration of pre-operative data. This includes intelligent 3D model superposition whilst simultaneously handling real and virtual occlusions caused by the AR overlay. Occlusions can negatively impact surgical safety and as such deteriorate rather than improve surgical care. Robotic surgery is particularly suited to tackle these integration challenges in a stepwise approach as the robotic console allows for different inputs to be displayed in parallel to the surgeon. Nevertheless, real-time de-occlusion requires extensive computational resources which further complicates clinical integration. This work tackles the problem of instrument occlusion and presents, to the authors' best knowledge, the first-in-human on edge deployment of a real-time binary segmentation pipeline during three robot-assisted surgeries: partial nephrectomy, migrated endovascular stent removal, and liver metastasectomy. To this end, a state-of-the-art real-time segmentation and 3D model pipeline was implemented and presented to the surgeon during live surgery. The pipeline allows real-time binary segmentation of 37 non-organic surgical items, which are never occluded during AR. The application features real-time manual 3D model manipulation for correct soft tissue alignment. The proposed pipeline can contribute towards surgical safety, ergonomics, and acceptance of AR in minimally invasive surgery.This works presents the first-in-human edge deployment of a real-time AI-enabled augmented reality (AR) pipeline in robotic surgery. The application uses a binary segmentation model to effectively identify over 37 classes of non-organic items in the surgical scene, and uses this information to create an overlay visualization, solving the instrument occlusion problem, and preventing the possibly hazardous situation this implies, as well as adding a sense of depth to the AR. The solution is used during three real surgeries and segmentation results, application performance as well as qualitative surgical feedback are discussed.###imag

Improving Augmented Reality Through Deep Learning: Real-time Instrument Delineation in Robotic Renal Surgery

Several barriers prevent the integration and adoption of augmented reality (AR) in robotic renal surgery despite the increased availability of virtual three-dimensional (3D) models. Apart from correct model alignment and deformation, not all instruments are clearly visible in AR. Superimposition of a 3D model on top of the surgical stream, including the instruments, can result in a potentially hazardous surgical situation. We demonstrate real-time instrument detection during AR-guided robot-assisted partial nephrectomy and show the generalization of our algorithm to AR-guided robot-assisted kidney transplantation. We developed an algorithm using deep learning networks to detect all nonorganic items. This algorithm learned to extract this information for 65 927 manually labeled instruments on 15 100 frames. Our setup, which runs on a standalone laptop, was deployed in three different hospitals and used by four different surgeons. Instrument detection is a simple and feasible way to enhance the safety of AR-guided surgery. Future investigations should strive to optimize efficient video processing to minimize the 0.5-s delay currently experienced. General AR applications also need further optimization, including detection and tracking of organ deformation, for full clinical implementation

Mathematical model of blood and interstitial flow and lymph production in the liver.

We present a mathematical model of blood and interstitial flow in the liver. The liver is treated as a lattice of hexagonal \u2018classic\u2019 lobules, which are assumed to be long enough that end effects may be neglected and a two-dimensional problem considered. Since sinusoids and lymphatic vessels are numerous and small compared to the lobule, we use a homogenized approach, describing the sinusoidal and interstitial spaces as porous media. We model plasma filtration from sinusoids to the interstitium, lymph uptake by lymphatic ducts, and lymph outflow from the liver surface. Our results show that the effect of the liver surface only penetrates a depth of a few lobules\u2019 thickness into the tissue. Thus, we separately consider a single lobule lying sufficiently far from all external boundaries that we may regard it as being in an infinite lattice, and also a model of the region near the liver surface. The model predicts that slightly more lymph is produced by interstitial fluid flowing through the liver surface than that taken up by the lymphatic vessels in the liver and that the on-peritonealized region of the surface of the liver results in the total lymph production (uptake by lymphatics plus fluid crossing surface) being about 5 % more than if the entire surface were covered by the Glisson\u2013peritoneal membrane. Estimates of lymph outflow through the surface of the liver are in good agreement with experimental data. We also study the effect of non-physiological values of the controlling parameters, particularly focusing on the conditions of portal hypertension and ascites. To our knowledge, this is the first attempt to model lymph production in the liver. The model provides clinically relevant information about lymph outflow pathways and predicts the systemic response to pathological variations

A structured approach for governing sustainable heat transitions in building renovation of towns and cities

This is the final version. Available on open access from IOP Publishing via the DOI in this record. Pioneer cities have demonstrated a willingness and capability to decarbonise local heat systems, but support is needed to scale up action. Heat decarbonisation is not simply a technical challenge, but also a political and social one; stakeholders must inform decisions about appropriate technological and policy solutions and will, in turn, be affected by them. Taking three dimensions of stakeholders, technology, and policy, a structured approach which centres stakeholders is presented to help local government to collaboratively find appropriate technology and policy solutions, both at the strategic scale across the municipality and in localised pilot projects, and explores how to initialise and support heat decarbonisation in more cities.European Regional Development Fund (ERDF)Province of South-Holland (Netherlands)Ministry of Economic Affairs and Climate Policy (Netherlands

Neighborhood Racial Characteristics, Credit History, and Bankcard Credit in Indian Country

We examine whether concerns about lenders’ discrimination based on community racial characteristics can be empirically substantiated in the context of neighborhoods on and near American Indian reservations. Drawing on a large-scale dataset consisting of individual-level credit bureau records, we find that residing in a predominantly American Indian neighborhood is ceteris paribus associated with worse bankcard credit outcomes than residing in a neighborhood where the share of American Indian residents is low. While these results are consistent with the possibility of lenders’ discrimination based on community racial characteristics, we explain why our findings should not be readily interpreted as conclusive evidence thereof. We further find that consumer’s credit history is a robust and quantitatively more important predictor of bankcard credit outcomes than racial composition of the consumer’s neighborhood, and that the consumer’s location vis-à-vis a reservation exhibits no effect on bankcard credit outcomes