Improving Mechanical Ventilator Clinical Decision Support Systems with A Machine Learning Classifier for Determining Ventilator Mode

Clinical decision support systems (CDSS) will play an in-creasing role in improving the quality of medical care for critically ill patients. However, due to limitations in current informatics infrastructure, CDSS do not always have com-plete information on state of supporting physiologic monitor-ing devices, which can limit the input data available to CDSS. This is especially true in the use case of mechanical ventilation (MV), where current CDSS have no knowledge of critical ventilation settings, such as ventilation mode. To enable MV CDSS to make accurate recommendations related to ventilator mode, we developed a highly performant ma-chine learning model that is able to perform per-breath clas-sification of 5 of the most widely used ventilation modes in the USA with an average F1-score of 97.52%. We also show how our approach makes methodologic improvements over previous work and that it is highly robust to missing data caused by software/sensor error

Non-symmetric liquid crystal dimer containing a carbohydrate-based moiety

Peer reviewedPublisher PD

Sustainable Community Development Case Study of Collaboration, and Participation between a Nonprofit Organization and Governance

AbstractThe Lake Calumet Task Force (LCTF) is a nonprofit community organization that has developed the Green Economic Industrial Corridor (GEIC) plan. The GEIC plan presents the socio-economic needs of Lake Calumet’s communities and proposed improvements to the natural and built environment, which have been neglected for decades. There was a gap in knowledge regarding collaboration and formation of partnerships for the design and implementation of sustainable development strategies across other key stakeholders. The qualitative case study explored how LCTF can combine principles of cooperation, partnership, and participation, with the local governmental agency’s design and implementation strategies, to enlarge upon the feasibility of their sustainable development plan. The conceptual framework was guided by collaborative governance theory. The data were gathered through focus groups and individual interviews with the relevant stakeholders. Findings are that citizens in the community have a measure of distrust of the city’s leadership and politicians; and that honesty, openness, and social responsibility are needed to create a framework for sustainable development. However, participants also expressed willingness to establish relationships, build trust, collaborate with officials, and seek commitment from community organizations and leaders to create processes for galvanizing the community. Findings may be used by communities to exact positive social change, and to better serve their members

Topographic determinants of foot and mouth disease transmission in the UK 2001 epidemic

Background A key challenge for modelling infectious disease dynamics is to understand the spatial spread of infection in real landscapes. This ideally requires a parallel record of spatial epidemic spread and a detailed map of susceptible host density along with relevant transport links and geographical features. Results Here we analyse the most detailed such data to date arising from the UK 2001 foot and mouth epidemic. We show that Euclidean distance between infectious and susceptible premises is a better predictor of transmission risk than shortest and quickest routes via road, except where major geographical features intervene. Conclusion Thus, a simple spatial transmission kernel based on Euclidean distance suffices in most regions, probably reflecting the multiplicity of transmission routes during the epidemic

Elastic Reverse-Time Migration Imaging Using Perforation Shots and Vertical Receiver Arrays

Recent innovations in hydraulic-fracture stimulation have increased the prevalence of borehole seismic monitoring of microseisms. This research investigates elastic-wave propagation as it pertains to seismic sources within the local borehole vicinity and the utility of elastic-wave finite-difference solutions as a means to model elastic-wave propagation and as a kernel component in a reverse-time migration imaging condition. A 2-D fourth order spatially accurate finite-difference solution to the elastic-wave equation is implemented to model wave propagation in elastic media resulting from a variety of focal-mechanism types and orientations. This algorithm’s simulated wavefield is compared to that of a preexisting finite-difference solution implementation in seismic Unix’s suea2df and an approximate analytic solution to the elastic-wave equation. A modified elastic reverse-time migration imaging condition is presented and tested on synthetic data propagated through a single-diffractor, two horizontal interfaces, and a subset of the Marmousi 2 model. Each test case simulates common acquisition geometries encountered in a perforation shot monitoring in an unconventional well and is demonstrated to be a potentially feasible imaging technique for near borehole subsurface structure. Imaging quality is then demonstrated to be dependent on acquisition geometry as described by the Nyquist sampling theorem. The reverse-time migration algorithm is then invoked on a dataset acquired from a vertically oriented receiver array by Hess Oil Co. from perforation shots in the En-Person 3H well.Earth and Atmospheric Sciences, Department o

Pharmacy Student Self-Testing as a Predictor of Examination Performance

Objectives. To determine if student self-testing improves performance during a doctor of pharmacy course. Methods. Students were given access to online quizzes with a large pool of randomly selected questions specific to upcoming examination content. Quizzes were electronically scored immediately upon completion and students were provided corrective feedback. Results. Examination scores following implementation of the practice quizzes were significantly higher in all but the last testing period. The upper fiftieth percentile of students scored higher on both the practice quizzes and subsequent examinations in all but the fourth testing period. Conclusions. Providing pharmacy students with self-testing opportunities could increase their retention of course material and provide feedback to both students and educators regarding learning, as well as provide students with a measure of their metacognition

Permeation of CO₂ and N₂ through glassy poly(dimethyl phenylene) oxide under steady- and presteady-state conditions

Glassy polymers are often used for gas separations because of their high selectivity. Although the dual‐mode permeation model correctly fits their sorption and permeation isotherms, its physical interpretation is disputed, and it does not describe permeation far from steady state, a condition expected when separations involve intermittent renewable energy sources. To develop a more comprehensive permeation model, we combine experiment, molecular dynamics, and multiscale reaction–diffusion modeling to characterize the time‐dependent permeation of N₂ and CO₂ through a glassy poly(dimethyl phenylene oxide) membrane, a model system. Simulations of experimental time‐dependent permeation data for both gases in the presteady‐state and steady‐state regimes show that both single‐ and dual‐mode reaction–diffusion models reproduce the experimental observations, and that sorbed gas concentrations lag the external pressure rise. The results point to environment‐sensitive diffusion coefficients as a vital characteristic of transport in glassy polymers

Vegetation classification of Coffea on Hawaii Island using WorldView-2 satellite imagery

Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012