An Idyl of Bar Harbor

A romantic poem published as a part of The Elite Library series and dedicated to Miss Nannie Garnett Emory

Environmental Impact Assessment: Boulevard Park Pedestrian Overpass Removal

The proposed action for the Boulevard Park Pedestrian Overpass is to remove the wooden structure and reroute the utilities underground. The utilities would be routed underneath the train tracks at the park entrance, connecting to Woods Coffee and up Bayview Drive. Irrigation and sewer will still be routed into the park but electricity, telecommunications and water will be routed out of the park. The utility conduits will be in separate trenches under the tracks. The park restrooms at the north end of the park will be abandoned to reduce utilities demands (especially water, electricity and sewer). Restrooms are still available in the park at Wood’s Coffee

Slideflow: Deep Learning for Digital Histopathology with Real-Time Whole-Slide Visualization

Deep learning methods have emerged as powerful tools for analyzing histopathological images, but current methods are often specialized for specific domains and software environments, and few open-source options exist for deploying models in an interactive interface. Experimenting with different deep learning approaches typically requires switching software libraries and reprocessing data, reducing the feasibility and practicality of experimenting with new architectures. We developed a flexible deep learning library for histopathology called Slideflow, a package which supports a broad array of deep learning methods for digital pathology and includes a fast whole-slide interface for deploying trained models. Slideflow includes unique tools for whole-slide image data processing, efficient stain normalization and augmentation, weakly-supervised whole-slide classification, uncertainty quantification, feature generation, feature space analysis, and explainability. Whole-slide image processing is highly optimized, enabling whole-slide tile extraction at 40X magnification in 2.5 seconds per slide. The framework-agnostic data processing pipeline enables rapid experimentation with new methods built with either Tensorflow or PyTorch, and the graphical user interface supports real-time visualization of slides, predictions, heatmaps, and feature space characteristics on a variety of hardware devices, including ARM-based devices such as the Raspberry Pi

Lamb wave mode spectroscopy on complex structures with amplitude-based feature detection

The need for fast and effective Non-Destructive Testing (NDT) techniques is ever present. Existing techniques such as ultrasonic testing, whilst established and reliable, face many limitations when considering large structures such as those found in the aerospace and green energy sectors. Wave mode, as well as other wavenumber based filtering techniques have been presented to address many of these limitations. This work describes a novel application of Wave Mode Spectroscopy (WMS) along with feature detection for complex geometric shapes. The specimen's geometry is found during the wavefields measurement through the use of a 3D Scanning Laser Doppler Vibrometer (SLDV) allowing the wavefield to be mapped to a 2D plane with limited distortion of the wavelength and without any prior knowledge of the part's geometry. This was shown to allow WMS to be applied to continuous, multi-frequency wavefields and generate accurate thickness maps. Monogenic signal analysis has been applied to the same measurement data to generate amplitude maps that allow the automatic detection of edge features through the use of a Canny edge detection algorithm

Evaluation of large language models as a diagnostic aid for complex medical cases

BackgroundThe use of large language models (LLM) has recently gained popularity in diverse areas, including answering questions posted by patients as well as medical professionals.ObjectiveTo evaluate the performance and limitations of LLMs in providing the correct diagnosis for a complex clinical case.DesignSeventy-five consecutive clinical cases were selected from the Massachusetts General Hospital Case Records, and differential diagnoses were generated by OpenAI’s GPT3.5 and 4 models.ResultsThe mean number of diagnoses provided by the Massachusetts General Hospital case discussants was 16.77, by GPT3.5 30 and by GPT4 15.45 (p < 0.0001). GPT4 was more frequently able to list the correct diagnosis as first (22% versus 20% with GPT3.5, p = 0.86), provide the correct diagnosis among the top three generated diagnoses (42% versus 24%, p = 0.075). GPT4 was better at providing the correct diagnosis, when the different diagnoses were classified into groups according to the medical specialty and include the correct diagnosis at any point in the differential list (68% versus 48%, p = 0.0063). GPT4 provided a differential list that was more similar to the list provided by the case discussants than GPT3.5 (Jaccard Similarity Index 0.22 versus 0.12, p = 0.001). Inclusion of the correct diagnosis in the generated differential was correlated with PubMed articles matching the diagnosis (OR 1.40, 95% CI 1.25–1.56 for GPT3.5, OR 1.25, 95% CI 1.13–1.40 for GPT4), but not with disease incidence.Conclusions and relevanceThe GPT4 model was able to generate a differential diagnosis list with the correct diagnosis in approximately two thirds of cases, but the most likely diagnosis was often incorrect for both models. In its current state, this tool can at most be used as an aid to expand on potential diagnostic considerations for a case, and future LLMs should be trained which account for the discrepancy between disease incidence and availability in the literature

In-flight calibration and verification of the Planck-LFI instrument

In this paper we discuss the Planck-LFI in-flight calibration campaign. After a brief overview of the ground test campaigns, we describe in detail the calibration and performance verification (CPV) phase, carried out in space during and just after the cool-down of LFI. We discuss in detail the functionality verification, the tuning of the front-end and warm electronics, the preliminary performance assessment and the thermal susceptibility tests. The logic, sequence, goals and results of the in-flight tests are discussed. All the calibration activities were successfully carried out and the instrument response was comparable to the one observed on ground. For some channels the in-flight tuning activity allowed us to improve significantly the noise performance.Comment: Long technical paper on Planck LFI in flight calibration campaign: 109 pages in this (not final) version, 100 page in the final JINST versio

Comparative risk assessment of school food environment policies and childhood diets, childhood obesity, and future cardiometabolic mortality in the United States

Background Promising school policies to improve children’s diets include providing fresh fruits and vegetables (F&V) and competitive food restrictions on sugar-sweetened beverages (SSBs), yet the impact of national implementation of these policies in US schools on cardiometabolic disease (CMD) risk factors and outcomes is not known. Our objective was to estimate the impact of national implementation of F&V provision and SSB restriction in US elementary, middle, and high schools on dietary intake and body mass index (BMI) in children and future CMD mortality. Methods We used comparative risk assessment (CRA) frameworks to model the impacts of these policies with input parameters from nationally representative surveys, randomized-controlled trials, and systematic reviews and meta-analyses. For children ages 5–18 years, this incorporated national data on current dietary intakes and BMI, impacts of these policies on diet, and estimated effects of dietary changes on BMI. In adults ages 25 and older, we further incorporated the sustainability of dietary changes to adulthood, effects of dietary changes on CMD, and national CMD death statistics, modeling effects if these policies had been in place when current US adults were children. Uncertainty across inputs was incorporated using 1000 Monte Carlo simulations. Results National F&V provision would increase daily fruit intake in children by as much as 25.0% (95% uncertainty interval (UI): 15.4, 37.7%), and would have small effects on vegetable intake. SSB restriction would decrease daily SSB intake by as much as 26.5% (95% UI: 6.4, 46.4%), and reduce BMI by as much as 0.7% (95% UI: 0.2, 1.2%). If F&V provision and SSB restriction were nationally implemented, an estimated 22,383 CMD deaths/year (95% UI: 18735, 25930) would be averted. Conclusion National school F&V provision and SSB restriction policies implemented in elementary, middle, and high schools could improve diet and BMI in children and reduce CMD mortality later in life

Rescue of mutant rhodopsin traffic by metformin-induced AMPK activation accelerates photoreceptor degeneration

Protein misfolding caused by inherited mutations leads to loss of protein function and potentially toxic ‘gain of function’, such as the dominant P23H rhodopsin mutation that causes retinitis pigmentosa (RP). Here, we tested whether the AMPK activator metformin could affect the P23H rhodopsin synthesis and folding. In cell models, metformin treatment improved P23H rhodopsin folding and traffic. In animal models of P23H RP, metformin treatment successfully enhanced P23H traffic to the rod outer segment, but this led to reduced photoreceptor function and increased photoreceptor cell death. The metformin-rescued P23H rhodopsin was still intrinsically unstable and led to increased structural instability of the rod outer segments. These data suggest that improving the traffic of misfolding rhodopsin mutants is unlikely to be a practical therapy, because of their intrinsic instability and long half-life in the outer segment, but also highlights the potential of altering translation through AMPK to improve protein function in other protein misfolding diseases