Quick Annotator: an open-source digital pathology based rapid image annotation tool.

Image-based biomarker discovery typically requires accurate segmentation of histologic structures (e.g. cell nuclei, tubules, and epithelial regions) in digital pathology whole slide images (WSIs). Unfortunately, annotating each structure of interest is laborious and often intractable even in moderately sized cohorts. Here, we present an open-source tool, Quick Annotator (QA), designed to improve annotation efficiency of histologic structures by orders of magnitude. While the user annotates regions of interest (ROIs) via an intuitive web interface, a deep learning (DL) model is concurrently optimized using these annotations and applied to the ROI. The user iteratively reviews DL results to either (1) accept accurately annotated regions or (2) correct erroneously segmented structures to improve subsequent model suggestions, before transitioning to other ROIs. We demonstrate the effectiveness of QA over comparable manual efforts via three use cases. These include annotating (1) 337,386 nuclei in 5 pancreatic WSIs, (2) 5,692 tubules in 10 colorectal WSIs, and (3) 14,187 regions of epithelium in 10 breast WSIs. Efficiency gains in terms of annotations per second of 102×, 9×, and 39× were, respectively, witnessed while retaining f-scores >0.95, suggesting that QA may be a valuable tool for efficiently fully annotating WSIs employed in downstream biomarker studies

Successful transition from fed-batch to continuous manufacturing within a mAb process development cycle

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Experimental investigation of kinematic pile bending in layered soils using dynamic centrifuge modelling

This research provides an insight into the previously unexplored aspects of kinematic pile bending, especially for large-intensity earthquakes where the soil behaviour is highly non-linear. In this study, a series of dynamic centrifuge experiments was conducted on pile foundations embedded in a two-layered soil profile to investigate the kinematic effects on pile foundations during model earthquakes. A single pile and a closely spaced 3 × 1 row pile group were used as model pile foundations, and the soil model consisted of a soft clay underlain by dense sand. It was observed that the peak kinematic pile bending moment occurs slightly beneath the interface of the soil layers and this depth is larger for the pile group compared to a single pile. Also, the piles in a group attract lower bending moments but carry larger residual kinematic pile bending moments compared to a single pile. Furthermore, the elastic solutions available in the literature for estimating the kinematic pile bending moments are shown to yield satisfactory results only for small-intensity earthquakes, but vastly underestimate for large-intensity earthquakes, if methods are applied injudiciously. The importance of considering soil non-linearity effects and accurate determination of shear strain at the interface of layered soils during large-intensity earthquakes for a reliable assessment of kinematic pile bending moment from methods in the literature is demonstrated using dynamic centrifuge test data. </jats:p

Improving Prostate Cancer Detection with Breast Histopathology Images

Deep neural networks have introduced significant advancements in the field of machine learning-based analysis of digital pathology images including prostate tissue images. With the help of transfer learning, classification and segmentation performance of neural network models have been further increased. However, due to the absence of large, extensively annotated, publicly available prostate histopathology datasets, several previous studies employ datasets from well-studied computer vision tasks such as ImageNet dataset. In this work, we propose a transfer learning scheme from breast histopathology images to improve prostate cancer detection performance. We validate our approach on annotated prostate whole slide images by using a publicly available breast histopathology dataset as pre-training. We show that the proposed cross-cancer approach outperforms transfer learning from ImageNet dataset.Comment: 9 pages, 2 figure

Centrifuge modelling of the behaviour of pile groups under vertical eccentric load

Annular shaped pile groups are a very common foundation layout for onshore wind turbines and other slender structures. In this study, their performance under vertical loads of moderate to high eccentricity, including moment rotation response and bearing capacity, was investigated by centrifuge testing on small scale physical models embedded in kaolin clay. To identify experimentally the capacity of the examined pile groups under different load paths, the model foundations were loaded monotonically until a clear collapse mechanism was achieved. The testing procedure and the proposed interpretation methodology can be easily adapted to load paths or pile layouts other than those considered in the current study. The experimental data can be adopted as a useful benchmark for mathematical models aimed at predicting the response of pile groups to complex load paths. The results of this testing program can also be used to assess the degree of conservatism of current methods adopted by industry for the design of piled foundations subjected to eccentric loads

Lifetime Assessments of Weapon Organics and Polymers FY05 Annual Report

Non-nuclear organics, while not yet regarded to be at risk, figure in a large percentage of Significant Findings Investigations. Further, early application of advanced lifetime, compatibility, and base-lining assessments for LEP replacement materials and emerging materials for the Reliable Replacement Warhead (RRW) provides data for rational material choices. This task is currently assessing the chemical and mechanical characteristics of a variety of weapon organics prioritized by the risk-consequence of material aging. The majority of effort to date has been dedicated to silicone elastomer components known to lose their load resistance with age, with additional effort dedicated to urethane adhesives. This fiscal year, we have focused on initial aging studies of UNI620-3, a candidate replacement material for DC745U, and Adiprene (LW520). Aging studies of S5455, originally scheduled for testing in FY05, were postponed until FY07. We have initiated aging studies on these materials by employing accelerated aging tests with exposure to Co-60 {gamma}-radiation and elevated temperatures and studying their mechanical properties using a variety of analytical tools including nuclear magnetic resonance (NMR), dynamic mechanical analysis (DMA), and differential scanning calorimetry (DSC). Additionally, we have investigated aging signatures present in parts returned from surveillance as well as initiated long and short term stress relaxation studies for a thorough understanding of compression set occurring in silicone elastomers components. Additional investigations of aging processes in fluoropolymer binders and the combined effects of radiation and tensile set on silicone pads were performed. Finally, we have used temperature programmed desorption (TPD) studies to significantly improve the accuracy of our H{sub 2}O outgassing model in comparison with last year through the use of the isoconversion technique as well as to measure the equilibrium vapor pressure of hydrogenated DPB pellets. This report satisfies the milestones/deliverables for the L3 task 'Update chemical and mechanical aging models for cushion/pads/adhesives' and all data will be input into the L2 milestone 'Bill's token L2 milestone'

Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays

BACKGROUND: Tissue microarrays (TMAs) have become a valuable resource for biomarker expression in translational research. Immunohistochemical (IHC) assessment of TMAs is the principal method for analysing large numbers of patient samples, but manual IHC assessment of TMAs remains a challenging and laborious task. With advances in image analysis, computer-generated analyses of TMAs have the potential to lessen the burden of expert pathologist review. METHODS: In current commercial software computerised oestrogen receptor (ER) scoring relies on tumour localisation in the form of hand-drawn annotations. In this study, tumour localisation for ER scoring was evaluated comparing computer-generated segmentation masks with those of two specialist breast pathologists. Automatically and manually obtained segmentation masks were used to obtain IHC scores for thirty-two ER-stained invasive breast cancer TMA samples using FDA-approved IHC scoring software. RESULTS: Although pixel-level comparisons showed lower agreement between automated and manual segmentation masks (κ=0.81) than between pathologists' masks (κ=0.91), this had little impact on computed IHC scores (Allred; [Image: see text]=0.91, Quickscore; [Image: see text]=0.92). CONCLUSIONS: The proposed automated system provides consistent measurements thus ensuring standardisation, and shows promise for increasing IHC analysis of nuclear staining in TMAs from large clinical trials

Analytical solution for the side-fringing fields of narrow beveled heads

By using conical coordinates, exact analytical solutions for three-dimensional side-fringing fields of recording heads that are beveled in the down-track direction are found. These solutions are derived under the assumption of zero gap length. The side-fringing fields for the two limiting cases of infinitesimally narrow heads and semi-infinitely wide heads are presented and compared

Assessment of bridge natural frequency as an indicator of scour using centrifuge modelling

Funder: Gates Cambridge Trust (GB)Abstract: One of the most prevalent causes of bridge failure around the world is “scour”—the gradual erosion of soil around a bridge foundation due to fast-flowing water. A reliable technique for monitoring scour would help bridge engineers take timely countermeasures to safeguard against failure. Although vibration-based techniques for monitoring structural damage have had limited success, primarily due to insufficient sensitivity, these have tended to focus on the detection of local damage. High natural frequency sensitivity has recently been reported for scour damage. Previous experiments to investigate this have been limited as a result of the cost of full-scale testing and the fact that scaled-down soil-structure models tested outside a centrifuge do not adequately simulate full-scale behaviour. This paper describes the development of what is believed to be the first-ever centrifuge-testing programme to establish the sensitivity of bridge natural frequency to scour. A 1/60 scale model of a two-span integral bridge with 15 m spans was tested at varying levels of scour. For the fundamental mode of vibration, these tests found up to a 40% variation in natural frequency for 30% loss of embedment. Models of three other types of foundation, which represent a shallow pad foundation, a deep pile bent and a deep monopile, were also tested in the centrifuge at different scour levels. The shallow foundation model showed lower frequency sensitivity to scour than the deep foundation models. Another important finding is that the frequency sensitivity to “global scour” is slightly higher than the sensitivity to “local scour”, for all foundation types. The level of frequency sensitivity (3.1–44% per scour depth equivalent to 30% of embedment of scour) detected in this experiment demonstrates the potential for using natural frequency as an indicator of both local and global scour of bridges, particularly those with deep foundations