Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system\u27s use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications

Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression

Although melanoma occurs more rarely than several other skin cancers, patients' long term survival rate is extremely low if the diagnosis is missed. Diagnosis is complicated by a high discordance rate among pathologists when distinguishing between melanoma and benign melanocytic lesions. A tool that provides potential concordance information to healthcare providers could help inform diagnostic, prognostic, and therapeutic decision-making for challenging melanoma cases. We present a melanoma concordance regression deep learning model capable of predicting the concordance rate of invasive melanoma or melanoma in-situ from digitized Whole Slide Images (WSIs). The salient features corresponding to melanoma concordance were learned in a self-supervised manner with the contrastive learning method, SimCLR. We trained a SimCLR feature extractor with 83,356 WSI tiles randomly sampled from 10,895 specimens originating from four distinct pathology labs. We trained a separate melanoma concordance regression model on 990 specimens with available concordance ground truth annotations from three pathology labs and tested the model on 211 specimens. We achieved a Root Mean Squared Error (RMSE) of 0.28 +/- 0.01 on the test set. We also investigated the performance of using the predicted concordance rate as a malignancy classifier, and achieved a precision and recall of 0.85 +/- 0.05 and 0.61 +/- 0.06, respectively, on the test set. These results are an important first step for building an artificial intelligence (AI) system capable of predicting the results of consulting a panel of experts and delivering a score based on the degree to which the experts would agree on a particular diagnosis. Such a system could be used to suggest additional testing or other action such as ordering additional stains or genetic tests.Comment: Accepted at ECCV 2022 AIMIA Workshop. arXiv admin note: text overlap with arXiv:2109.0755

Differential Transfer Ionization Cross Sections for 50175-keV Proton-Helium Collisions

We have measured coincidences between neutralized projectiles and He recoil ions for 50175-keV proton-helium collisions. From the data we obtained transfer ionization (TI) cross sections differential in the projectile scattering angle. Laboratory scattering angles range from 0 to 2.0 mrad. The experimental method allowed separation of the postcollision charge states of the target atoms. The ratio of the cross sections for TI to the sum of TI and single capture, F, is presented as a function of projectile scattering angle. Comparison is made to previous measurements of this ratio where data is available. The differential cross sections are compared to dynamical classical trajectory Monte Carlo (dCTMC) calculations. Agreement in the shape of the differential cross sections is good between the theory and measurement over the entire energy range

CheapStat: An Open-Source, “Do-It-Yourself” Potentiostat for Analytical and Educational Applications

Although potentiostats are the foundation of modern electrochemical research, they have seen relatively little application in resource poor settings, such as undergraduate laboratory courses and the developing world. One reason for the low penetration of potentiostats is their cost, as even the least expensive commercially available laboratory potentiostats sell for more than one thousand dollars. An inexpensive electrochemical workstation could thus prove useful in educational labs, and increase access to electrochemistry-based analytical techniques for food, drug and environmental monitoring. With these motivations in mind, we describe here the CheapStat, an inexpensive (<$80), open-source (software and hardware), hand-held potentiostat that can be constructed by anyone who is proficient at assembling circuits. This device supports a number of potential waveforms necessary to perform cyclic, square wave, linear sweep and anodic stripping voltammetry. As we demonstrate, it is suitable for a wide range of applications ranging from food- and drug-quality testing to environmental monitoring, rapid DNA detection, and educational exercises. The device's schematics, parts lists, circuit board layout files, sample experiments, and detailed assembly instructions are available in the supporting information and are released under an open hardware license

An evaluation of staining techniques for marking daily growth in scleractinian corals

Author Posting. © The Author(s), 2012. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Experimental Marine Biology and Ecology 440 (2013): 126-131, doi:10.1016/j.jembe.2012.12.003.In situ skeletal markers have been widely used to quantify skeletal growth rates of scleractinian corals on sub-annual time-scales. Nevertheless, an evaluation of different techniques, both in terms of their efficacy and potential impacts on the growth process itself, has not been undertaken. Here the effects of exposure to four different dyes (alizarin, alizarin complexone, calcein, oxytetracycline) and isotope spikes (Ba and Sr) on the growth rates of scleractinian corals are compared. Oxytetracycline increased coral growth. Alizarin, alizarin complexone, calcein, and Sr and Ba isotope spikes had no significant effect on coral growth, but polyp extension appeared reduced during exposure to alizarin and alizarin complexone. Calcein provided a more intense fluorescent mark than either alizarin or alizarin complexone. Isotope spikes were challenging to locate using isotope ratio analysis techniques. Thus, calcein appears best suited for marking short-term calcification increments in corals, while a combination of alizarin or alizarin complexone and calcein may be useful for dual labeling experiments as there is little overlap in their fluorescence spectra.Funding for this work was provided by a Lizard Island Doctoral Fellowship, the Ocean Life Institute, NSF OCE-1041106, and an International Society for Reef Studies / Ocean Conservancy Fellowship. This material is based upon work supported under a National Science Foundation Graduate Research Fellowship and a National Science Foundation International Post-Doctoral Fellowship

Climate Change and Extreme Weather Adaptation Options for Transportation Assets in the Bay Area Pilot Project

The Metropolitan Transportation Commission (MTC), the San Francisco Bay Conservation and Development Commission (BCDC), the California Department of Transportation, District 4 (Caltrans) and San Francisco Bay Area Rapid Transit District (BART) have partnered on a collaborative sub- regional pilot project to assess adaptation options for a subset of key transportation assets vulnerable to sea level rise in Alameda County. This study builds on the Adapting to Rising Tides: Transportation Vulnerability and Risk Assessment Pilot Project which was completed in 2011 and identified representative critical transportation assets vulnerable to sea level rise. Both projects were funded by the Federal Highway Administration. The first study developed detailed risk profiles for approximately 30 transportation assets including road, rail and transit. Having identified the risks, and in order to move from assessment to action, three focus areas within Alameda County containing \u2018core\u2019 transportation assets and \u2018adjacent\u2019 community assets were selected for further study to ensure a thorough understanding of their vulnerabilities. Once that enhanced vulnerability had been assessed, a set of detailed, representative adaptation strategies have been developed as potential solutions to protect key bridge, highway, transit and community assets from future inundation

Creating a new vision for the future: A report from the Blue Ribbon Commission

Many opportunities have been presented to coordinate, collaborate, and to create new activities, services, and structures to better meet the needs of current and potential members. Rather than attempting to evaluate the merits of each of these three avenues in this report, the goal is foster an informed conversation about the future. The choices made by the organizations may include a combination of activities among these three categories. The critical next step is for a wider conversation among members of the organizations to take place concerning the future of the profession

A database of marine phytoplankton abundance, biomass and species composition in Australian waters

There have been many individual phytoplankton datasets collected across Australia since the mid 1900s, but most are unavailable to the research community. We have searched archives, contacted researchers, and scanned the primary and grey literature to collate 3,621,847 records of marine phytoplankton species from Australian waters from 1844 to the present. Many of these are small datasets collected for local questions, but combined they provide over 170 years of data on phytoplankton communities in Australian waters. Units and taxonomy have been standardised, obviously erroneous data removed, and all metadata included. We have lodged this dataset with the Australian Ocean Data Network (http://portal.aodn.org.au/) allowing public access. The Australian Phytoplankton Database will be invaluable for global change studies, as it allows analysis of ecological indicators of climate change and eutrophication (e.g., changes in distribution; diatom:dinoflagellate ratios). In addition, the standardised conversion of abundance records to biomass provides modellers with quantifiable data to initialise and validate ecosystem models of lower marine trophic levels