SOAP Services with Clarens: Guide for Developers and Administrators

The Clarens application server enables secure, asynchronous SOAP services to run on a Grid cluster such as one of those of the TeraGrid. There is a Client, who wants to use the service and understands the application domain enough to form a reasonable service request; a Developer, who is a power-user of the TeraGrid, who understands both Clarens and the application domain, and creates and deploys a service on a TeraGrid head node; and there is a Root system administrator, who controls the Clarens installation and the cluster on which it runs. The purpose of this document is to provide all of the information a service developer needs to know in order to deploy a Clarens service, with information also provided for the system administrator of the Clarens installation. First we discuss how each of the three roles see the service

Thermo-mechanical sensitivity calibration of nanotorsional magnetometers

We report on the fabrication of sensitive nanotorsional resonators, which can be utilized as magnetometers for investigating the magnetization dynamics in small magnetic elements. The thermo-mechanical noise is calibrated with the resonator displacement in order to determine the ultimate mechanical torque sensitivity of the magnetometer.Comment: 56th Annual Conference on Magnetism and Magnetic Material

Survival Analysis for Idiopathic Pulmonary Fibrosis using CT Images and Incomplete Clinical Data

Idiopathic Pulmonary Fibrosis (IPF) is an inexorably progressive fibrotic lung disease with a variable and unpredictable rate of progression. CT scans of the lungs inform clinical assessment of IPF patients and contain pertinent information related to disease progression. In this work, we propose a multi-modal method that uses neural networks and memory banks to predict the survival of IPF patients using clinical and imaging data. The majority of clinical IPF patient records have missing data (e.g. missing lung function tests). To this end, we propose a probabilistic model that captures the dependencies between the observed clinical variables and imputes missing ones. This principled approach to missing data imputation can be naturally combined with a deep survival analysis model. We show that the proposed framework yields significantly better survival analysis results than baselines in terms of concordance index and integrated Brier score. Our work also provides insights into novel image-based biomarkers that are linked to mortality

Learning To Pay Attention To Mistakes

In convolutional neural network based medical image segmentation, the periphery of foreground regions representing malignant tissues may be disproportionately assigned as belonging to the background class of healthy tissues \cite{attenUnet}\cite{AttenUnet2018}\cite{InterSeg}\cite{UnetFrontNeuro}\cite{LearnActiveContour}. This leads to high false negative detection rates. In this paper, we propose a novel attention mechanism to directly address such high false negative rates, called Paying Attention to Mistakes. Our attention mechanism steers the models towards false positive identification, which counters the existing bias towards false negatives. The proposed mechanism has two complementary implementations: (a) "explicit" steering of the model to attend to a larger Effective Receptive Field on the foreground areas; (b) "implicit" steering towards false positives, by attending to a smaller Effective Receptive Field on the background areas. We validated our methods on three tasks: 1) binary dense prediction between vehicles and the background using CityScapes; 2) Enhanced Tumour Core segmentation with multi-modal MRI scans in BRATS2018; 3) segmenting stroke lesions using ultrasound images in ISLES2018. We compared our methods with state-of-the-art attention mechanisms in medical imaging, including self-attention, spatial-attention and spatial-channel mixed attention. Across all of the three different tasks, our models consistently outperform the baseline models in Intersection over Union (IoU) and/or Hausdorff Distance (HD). For instance, in the second task, the "explicit" implementation of our mechanism reduces the HD of the best baseline by more than $26\%$, whilst improving the IoU by more than $3\%$. We believe our proposed attention mechanism can benefit a wide range of medical and computer vision tasks, which suffer from over-detection of background.Comment: Accepted at BMVC 202

Deep Learning-Based Long Term Mortality Prediction in the National Lung Screening Trial

In this study, the long-term mortality in the National Lung Screening Trial (NLST) was investigated using a deep learning-based method. Binary classification of the non-lung-cancer mortality (i.e. cardiovascular and respiratory mortality) was performed using neural network models centered around a 3D-ResNet. The models were trained on a participant age, gender, and smoking history matched cohort. Utilising both the 3D CT scan and clinical information, the models can achieve an AUC of 0.73 which outperforms humans at cardiovascular mortality prediction. The corresponding F1 and Matthews Correlation Coefficient are 0.60 and 0.38 respectively. By interpreting the trained models with 3D saliency maps, we examined the features on the CT scans that correspond to the mortality signal. By extracting information from 3D CT volumes, we can highlight regions in the thorax region that contribute to mortality that might be overlooked by the clinicians. Therefore, this can help focus preventative interventions appropriately, particularly for under-recognised pathologies and thereby reducing patient morbidity

Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking

Montage is a portable software toolkit for constructing custom, science-grade mosaics by composing multiple astronomical images. The mosaics constructed by Montage preserve the astrometry (position) and photometry (intensity) of the sources in the input images. The mosaic to be constructed is specified by the user in terms of a set of parameters, including dataset and wavelength to be used, location and size on the sky, coordinate system and projection, and spatial sampling rate. Many astronomical datasets are massive, and are stored in distributed archives that are, in most cases, remote with respect to the available computational resources. Montage can be run on both single- and multi-processor computers, including clusters and grids. Standard grid tools are used to run Montage in the case where the data or computers used to construct a mosaic are located remotely on the Internet. This paper describes the architecture, algorithms, and usage of Montage as both a software toolkit and as a grid portal. Timing results are provided to show how Montage performance scales with number of processors on a cluster computer. In addition, we compare the performance of two methods of running Montage in parallel on a grid.Comment: 16 pages, 11 figure

All purulence is local - epidemiology and management of skin and soft tissue infections in three urban emergency departments

BACKGROUND: Skin and soft tissue infection (SSTIs) are commonly treated in emergency departments (EDs). While the precise role of antibiotics in treating SSTIs remains unclear, most SSTI patients receive empiric antibiotics, often targeted toward methicillin-resistant Staphylococcus aureus (MRSA). The goal of this study was to assess the efficiency with which ED clinicians targeted empiric therapy against MRSA, and to identify factors that may allow ED clinicians to safely target antibiotic use. METHODS: We performed a retrospective analysis of patient visits for community-acquired SSTIs to three urban, academic EDs in one northeastern US city during the first quarter of 2010. We examined microbiologic patterns among cultured SSTIs, and relationships between clinical and demographic factors and management of SSTIs. RESULTS: Antibiotics were prescribed to 86.1% of all patients. Though S. aureus (60% MRSA) was the most common pathogen cultured, antibiotic susceptibility differed between adult and pediatric patients. Susceptibility of S. aureus from ED SSTIs differed from published local antibiograms, with greater trimethoprim resistance and less fluoroquinolone resistance than seen in S. aureus from all hospital sources. Empiric antibiotics covered the resultant pathogen in 85.3% of cases, though coverage was frequently broader than necessary. CONCLUSIONS: Though S. aureus remained the predominant pathogen in community-acquired SSTIs, ED clinicians did not accurately target therapy toward the causative pathogen. Incomplete local epidemiologic data may contribute to this degree of discordance. Future efforts should seek to identify when antibiotic use can be narrowed or withheld. Local, disease-specific antibiotic resistance patterns should be publicized with the goal of improving antibiotic stewardship

Investigation of the Effects of Oxygen and Other Considerations on the Shelf-Life of Craft Beer

The goal of this project was to determine the effects of dissolved oxygen (DO) and other phenomena on the shelf-life of Purgatory Beer Company’s Two-Car Garage Double IPA, maintained at two separate storage temperatures. Indigo carmine titration and oxygen analyzing equipment were used to identify the changing profile of DO, while sensory analysis and Fourier-transform infrared spectroscopy were used to measure variations in physical qualities and chemical composition. Data from these tests indicate that the DO reactions were most likely diffusion-limited. Recommendations of a 7-week shelf-life and refrigerated storage were made to Purgatory Beer Company after analysis

Quantitative polarized light microscopy of human cochlear sections

Dysfunction of the inner ear is the most common cause of sensorineural hearing loss, which is the most common sensory deficit worldwide. Conventional imaging modalities are unable to depict the microanatomy of the human inner ear, hence the need to explore novel imaging modalities. We provide the first characterization of the polarization dependent optical properties of human cochlear sections using quantitative polarized light microscopy (qPLM). Eight pediatric cadaveric cochlear sections, aged 0 (term) to 24 months, were selected from the US National Temporal Bone Registry, imaged with qPLM and analyzed using Image J. Retardance of the bony otic capsule and basilar membrane were substantially higher than that of the stria vascularis, spiral ganglion neurons, organ of Corti and spiral ligament across the half turns of the spiraling cochlea. qPLM provides quantitative information about the human inner ear, and awaits future exploration in vivo