To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure email@example.com
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
The interaction of the electron beam with materials during TEM/STEM imaging often leads to radiation damage. While a variety of low-dose techniques can help mitigate beam damage, true dose management starts with knowing the precise total accumulated dose and dose rate that a sample has seen throughout an experiment. AXON Dose allows users to calibrate their instruments, track electron dose/dose rate across a sample as a function of time and location, and quantify the impact of dose on individual samples.
Reliable spatially resolved compositional analysis through atom probe tomography requires an accurate placement of the detected ions within the three-dimensional reconstruction. Unfortunately, for heterogeneous systems, traditional reconstruction protocols are prone to position some ions incorrectly. This stems from the use of simplified projection laws which treat the emitter apex as a spherical cap, although the actual shape may be far more complex. For instance, sampled materials with compositional heterogeneities are known to develop local variations in curvature across the emitter due to their material phase specific evaporation fields. This work provides three pivotal precursors to improve the spatial accuracy of the reconstructed volume in such cases. First, we show scanning probe microscopy enables the determination of the local curvature of heterogeneous emitters, thus providing the essential information for a more advanced reconstruction considering the actual shape. Second, we demonstrate the cyclability between scanning probe characterization and atom probe analysis. This is a key ingredient of more advanced reconstruction protocols whereby the characterization of the emitter topography is executed at multiple stages of the atom probe analysis. Third, we show advances in the development of an electrostatically driven reconstruction protocol which are expected to enable reconstruction based on experimental tip shapes.
The papers in this forum offer an interdisciplinary assessment of the state of the field of Anglican Studies and perspectives on future trajectories. The first three papers, on liturgy, history, and world Anglicanism, offer an assessment of the respective state of these areas of Anglican Studies. The second set, on theology, sociology of religion, and biblical studies, stake out positions on how these disciplines inform the work of Anglican Studies. A concluding essay offers a synthesis of these papers, focusing on the themes of local contexts for Anglicanism, a further complexification of decolonizing processes in Anglicanism, and the critical role of conversation in Anglican Studies regarding disciplines, languages, and power dynamics.
The objectives of this study were (1) to develop and validate a simulation model to estimate daily probabilities of healthcare-associated infections (HAIs), length of stay (LOS), and mortality using time varying patient- and unit-level factors including staffing adequacy and (2) to examine whether HAI incidence varies with staffing adequacy.
The study was conducted at 2 tertiary- and quaternary-care hospitals, a pediatric acute care hospital, and a community hospital within a single New York City healthcare network.
All patients discharged from 2012 through 2016 (N = 562,435).
We developed a non-Markovian simulation to estimate daily conditional probabilities of bloodstream, urinary tract, surgical site, and Clostridioides difficile infection, pneumonia, length of stay, and mortality. Staffing adequacy was modeled based on total nurse staffing (care supply) and the Nursing Intensity of Care Index (care demand). We compared model performance with logistic regression, and we generated case studies to illustrate daily changes in infection risk. We also described infection incidence by unit-level staffing and patient care demand on the day of infection.
Most model estimates fell within 95% confidence intervals of actual outcomes. The predictive power of the simulation model exceeded that of logistic regression (area under the curve [AUC], 0.852 and 0.816, respectively). HAI incidence was greatest when staffing was lowest and nursing care intensity was highest.
This model has potential clinical utility for identifying modifiable conditions in real time, such as low staffing coupled with high care demand.
Background:Pseudomonas aeruginosa is an important nosocomial pathogen associated with intrinsic and acquired resistance mechanisms to major classes of antibiotics. To better understand clinical risk factors for drug-resistant P. aeruginosa infection, decision-tree models for the prediction of fluoroquinolone and carbapenem-resistant P. aeruginosa were constructed and compared to multivariable logistic regression models using performance characteristics. Methods: In total, 5,636 patients admitted to 4 hospitals within a New York City healthcare system from 2010 to 2016 with blood, respiratory, wound, or urine cultures growing PA were included in the analysis. Presence or absence of drug-resistance was defined using the first culture of any source positive for P. aeruginosa during each hospitalization. To train and validate the prediction models, cases were randomly split (60 of 40) into training and validation datasets. Clinical decision-tree models for both fluoroquinolone and carbapenem resistance were built from the training dataset using 21 clinical variables of interest, and multivariable logistic regression models were built using the 16 clinical variables associated with resistance in bivariate analyses. Decision-tree models were optimized using K-fold cross validation, and performance characteristics between the 4 models were compared. Results: From 2010 through 2016, prevalence of fluoroquinolone and carbapenem resistance was 32% and 18%, respectively. For fluoroquinolone resistance, the logistic regression algorithm attained a positive predictive value (PPV) of 0.57 and a negative predictive value (NPV) of 0.73 (sensitivity, 0.27; specificity, 0.90) and the decision-tree algorithm attained a PPV of 0.65 and an NPV of 0.72 (sensitivity 0.21, specificity 0.95). For carbapenem resistance, the logistic regression algorithm attained a PPV of 0.53 and a NPV of 0.85 (sensitivity 0.20, specificity 0.96) and the decision-tree algorithm attained a PPV of 0.59 and an NPV of 0.84 (sensitivity 0.22, specificity 0.96). The decision-tree partitioning algorithm identified prior fluoroquinolone resistance, SNF stay, sex, and length-of-stay as variables of greatest importance for fluoroquinolone resistance compared to prior carbapenem resistance, age, and length-of-stay for carbapenem resistance. The highest-performing decision tree for fluoroquinolone resistance is illustrated in Fig. 1. Conclusions: Supervised machine-learning techniques may facilitate prediction of P. aeruginosa resistance and risk factors driving resistance patterns in hospitalized patients. Such techniques may be applied to readily available clinical information from hospital electronic health records to aid with clinical decision making.
The seemingly aberrant coiling of heteromorphic ammonoids suggests that they underwent more significant changes in hydrostatic properties throughout ontogeny than their planispiral counterparts. Such changes may have been responses to different selective pressures at different life stages. The hydrostatic properties of three species of Didymoceras (D. stevensoni, D. nebrascense, and D. cheyennense) were investigated by creating virtual 3D models at several stages during growth. These models were used to compute the conditions for neutral buoyancy, hydrostatic stability, orientation during life, and thrust angles (efficiency of directional movement). These properties suggest that Didymoceras and similar heteromorphs lived low-energy lifestyles with the ability to hover above the seafloor. The resultant static orientations yielded a downward-facing aperture in the hatchling and a horizontally facing aperture throughout most of the juvenile stage, before terminating in an upward direction at maturity. Relatively high hydrostatic stabilities would not have permitted the orientation of Didymoceras to be considerably modified with active locomotion. During the helical phase, Didymoceras would have been poorly suited for horizontal movement, yet equipped to pirouette about the vertical axis. Two stages throughout growth, however, would have enhanced lateral mobility: a juvenile stage just after the formation of the first bend in the shell and the terminal stage after completion of the U-shaped hook. These two more mobile phases in ontogeny may have improved juvenile dispersal potential and mate acquisition during adulthood, respectively. In general, life orientation and hydrostatic stability change more wildly for these aberrantly coiled ammonoids than their planispiral counterparts.