Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
32,272
result(s) for
"Taylor, R."
Sort by:
Pathogenesis of type 2 diabetes: tracing the reverse route from cure to cause
The metabolic abnormalities of type 2 diabetes can be reversed reproducibly by bariatric surgery. By quantifying the major pathophysiological abnormalities in insulin secretion and insulin action after surgery, the sequence of events leading to restoration of normal metabolism can be defined. Liver fat levels fall within days and normal hepatic insulin sensitivity is restored. Simultaneously, plasma glucose levels return towards normal. Insulin sensitivity of muscle remains abnormal, at least over the weeks and months after bariatric surgery. The effect of the surgery is explicable solely in terms of energy restriction. By combining this information with prospective observation of the changes immediately preceding the onset of type 2 diabetes, a clear picture emerges. Insulin resistance in muscle, caused by inherited and environmental factors, facilitates the development of fatty liver during positive energy balance. Once established, the increased insulin secretion required to maintain plasma glucose levels will further increase liver fat deposition. Fatty liver causes resistance to insulin suppression of hepatic glucose output as well as raised plasma triacylglycerol. Exposure of beta cells to increased levels of fatty acids, derived from circulating and locally deposited triacylglycerol, suppresses glucose-mediated insulin secretion. This is reversible initially, but eventually becomes permanent. The essential time sequence of the pathogenesis of type 2 diabetes is now evident. Muscle insulin resistance determines the rate at which fatty liver progresses, and ectopic fat deposition in liver and islet underlies the related dynamic defects of hepatic insulin resistance and beta cell dysfunction. These defects are capable of dramatic reversal under hypoenergetic feeding conditions, completely in early diabetes and to a worthwhile extent in more established disease.
Journal Article
Predicting hospital admission at emergency department triage using machine learning
To predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.
This retrospective study included all adult ED visits between March 2014 and July 2017 from one academic and two community emergency rooms that resulted in either admission or discharge. A total of 972 variables were extracted per patient visit. Samples were randomly partitioned into training (80%), validation (10%), and test (10%) sets. We trained a series of nine binary classifiers using logistic regression (LR), gradient boosting (XGBoost), and deep neural networks (DNN) on three dataset types: one using only triage information, one using only patient history, and one using the full set of variables. Next, we tested the potential benefit of additional training samples by training models on increasing fractions of our data. Lastly, variables of importance were identified using information gain as a metric to create a low-dimensional model.
A total of 560,486 patient visits were included in the study, with an overall admission risk of 29.7%. Models trained on triage information yielded a test AUC of 0.87 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.88) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on patient history yielded an AUC of 0.86 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.87) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on the full set of variables yielded an AUC of 0.91 for LR (95% CI 0.91-0.91), 0.92 for XGBoost (95% CI 0.92-0.93) and 0.92 for DNN (95% CI 0.92-0.92). All algorithms reached maximum performance at 50% of the training set or less. A low-dimensional XGBoost model built on ESI level, outpatient medication counts, demographics, and hospital usage statistics yielded an AUC of 0.91 (95% CI 0.91-0.91).
Machine learning can robustly predict hospital admission using triage information and patient history. The addition of historical information improves predictive performance significantly compared to using triage information alone, highlighting the need to incorporate these variables into prediction models.
Journal Article
Supplying urban ecosystem services through multifunctional green infrastructure in the United States
This paper summarizes a strategy for supplying ecosystem services in urban areas through a participatory planning process targeting multifunctional green infrastructure. We draw from the literature on landscape multifunctionality, which has primarily been applied to agricultural settings, and propose opportunities to develop urban green infrastructure that could contribute to the sustainable social and ecological health of the city. Thinking in terms of system resilience, strategies might focus on the potential for green infrastructure to allow for adaptation and even transformation in the face of future challenges such as climate change, food insecurity, and limited resources. Because planning for multiple functions can be difficult when many diverse stakeholders are involved, we explored decision support tools that could be applied to green infrastructure planning in the early stages, to engage the public and encourage action toward implementing a preferred solution. Several specific ecosystem services that could be relevant for evaluating current and future urban green spaces include: plant biodiversity, food production, microclimate control, soil infiltration, carbon sequestration, visual quality, recreation, and social capital. Integrating such ecosystem services into small-scale greening projects could allow for creativity and local empowerment that would inspire broader transformation of green infrastructure at the city level. Those cities committing to such an approach by supporting greening projects are likely to benefit in the long run through the value of ecosystem services for urban residents and the broader public.
Journal Article
Soft limits of Yang-Mills amplitudes and conformal correlators
A
bstract
We study tree-level celestial amplitudes in Yang-Mills theory — Mellin transforms of multi-gluon scattering amplitudes that convert them into the correlators of conformal primary fields on two-dimensional celestial sphere. By using purely field-theoretical methods, we show that the soft conformal limit of celestial amplitudes, in which one of the primary field operators associated to gauge bosons becomes a dimension one current, is dominated by the contributions of low-energy soft particles. This result confirms conclusions reached by using Yang-Mills theory formulated in curvilinear coordinates, as pioneered by Strominger. By using well-known collinear limits of Yang-Mills amplitudes, we derive the OPE rules for the primary fields and the holomorphic currents arising in the conformally soft limit. The Ward identities following from OPE have the same form as the identities derived by using soft theorems.
Journal Article
Gap resonance and higher harmonics driven by focused transient wave groups
The first and higher harmonic components of the resonant fluid response in the gap between two identical fixed rectangular boxes are experimentally investigated in a wave basin. Gap response is excited by transient wave groups (being based on scaled versions of the autocorrelation function of sea-state spectra, representing NewWaves, the average shape of large waves in a sea state). Several different wave groups with different maximum surface elevations, spectral peak frequencies and bandwidths are used, while the bilge shape of the boxes and approach angle of the waves are also varied. Unlike a simple regular wave, it is complicated to separate the harmonic components for a transient wave group due to nonlinear wave–wave and wave–structure interactions. A four-phase combination methodology is used to separate the first four harmonic components, and this also allows higher harmonic components to be isolated with simple digital frequency filtering. Harmonic components up to 14th order in the incident wave amplitude have been extracted. It is shown that for an incident group with appropriate frequency content, the linear gap response may be substantially smaller than the second harmonic component, which is strongly driven via quadratic coupling of the linear terms from the incident wave and occurs in the gap resonant modes. Double frequency excitation may have important practical implications for offshore operations. Fourth and zeroth (long-wave) harmonics in the gap are further driven via quadratic coupling of the second harmonic itself. Linear damping coefficients for the first few modes of the gap resonant response are derived from measured time series using a numerical fit and shown to be higher than those from linear diffraction calculations.
Journal Article