A corrected formula for uncertainty in estimations of gestational age from fetal head circumference measurements

Numerous publications over recent years have proposed methods for estimation of gestational age (GA) from fetal measurements including biparietal diameter, head circumference, crown-rump length and others. The manuscript of Altman and Chitty1 presented statistical modelling of data from 663 fetuses to define charts and tables for pregnancy dating based upon such measures. The resulting outputs are tables of mean GA estimates based upon each measurement, each with a corresponding standard deviation that encompasses the uncertainty in the prediction. We here address an erroneous result in the appendix of this work, associated with the uncertainty in GA prediction based upon derived head circumference measurements

The interaction between diabetes, body mass index, hepatic steatosis, and risk of liver resection: insulin dependent diabetes is the greatest risk for major complications

Background. This study aimed to assess the relationship between diabetes, obesity, and hepatic steatosis in patients undergoing liver resection and to determine if these factors are independent predictors of major complications. Materials and Methods. Analysis of a prospectively maintained database of patients undergoing liver resection between 2005 and 2012 was undertaken. Background liver was assessed for steatosis and classified as <33% and ≥33%. Major complications were defined as Grade III–V complications using theindo-Clavien classification. Results. 504 patients underwent liver resection, of whom 56 had diabetes and 61 had steatosis ≥33%. Median BMI was 26kg/m2 (16–54kg/m 2). 94 patients developed a major complication (18.7%). BMI ≥ 25kg/m2

Statistical models for identifying frequent hitters in high throughput screening

High throughput screening (HTS) interrogates compound libraries to find those that are “active” in an assay. To better understand compound behavior in HTS, we assessed an existing binomial survivor function (BSF) model of “frequent hitters” using 872 publicly available HTS data sets. We found large numbers of “infrequent hitters” using this model leading us to reject the BSF for identifying “frequent hitters.” As alternatives, we investigated generalized logistic, gamma, and negative binomial distributions as models for compound behavior. The gamma model reduced the proportion of both frequent and infrequent hitters relative to the BSF. Within this data set, conclusions about individual compound behavior were limited by the number of times individual compounds were tested (1–1613 times) and disproportionate testing of some compounds. Specifically, most tests (78%) were on a 309,847-compound subset (17.6% of compounds) each tested ≥ 300 times. We concluded that the disproportionate retesting of some compounds represents compound repurposing at scale rather than drug discovery. The approach to drug discovery represented by these 872 data sets characterizes the assays well by challenging them with many compounds while each compound is characterized poorly with a single assay. Aggregating the testing information from each compound across the multiple screens yielded a continuum with no clear boundary between normal and frequent hitting compounds

Systematic evaluation of radiological findings in the assessment of resectability of peri-ampullary cancer by CT using different contrast phase protocols

Aims: To determine the relative significance of radiological signs in determining the resectability of peri-ampullary cancer (PC) and to assess the value of multi-phase imaging in detecting these findings. Materials and Methods: Blinded, double re-reporting of pre-operative imaging from five hospitals was undertaken of 411 patients undergoing surgery for PC over an eight year period, of whom 119 patients were found to be inoperable at the time of surgery. Results: The median tumour size was 26.7 mm and the proportion of patients reported to have regional lymphadenopathy (RL), venous (VI) and arterial involvement (AI) was 24.7%, 11.5% and 3.9% respectively and was similar regardless of the number of contrast phases undertaken. Significant associations were however noted between individual risk factors: VI was closely associated with tumour size (p=0.002) and AI (p< 0.0001). In multi-variable analysis AI, VI and RL were independently associated with resectability (relative risk of resection =0.05, 0.31 and 0.51 respectively). Tumour size however was not associated with resectability when VI was included in the multivariate model

Rural–urban scaling of age, mortality, crime and property reveals a loss of expected self‑similar behaviour

The urban scaling hypothesis has improved our understanding of cities; however, rural areas have been neglected. We investigated rural–urban population density scaling in England and Wales using 67 indicators of crime, mortality, property, and age. Most indicators exhibited segmented scaling about a median critical density of 27 people per hectare. Above the critical density, urban regions preferentially attract young adults (25–40 years) and lose older people (> 45 years). Density scale adjusted metrics (DSAMs) were analysed using hierarchical clustering, networks, and self-organizing maps (SOMs) revealing regional differences and an inverse relationship between excess value of property transactions and a range of preventable mortality (e.g. diabetes, suicide, lung cancer). The most striking finding is that age demographics break the expected self-similarity underlying the urban scaling hypothesis. Urban dynamism is fuelled by preferential attraction of young adults and not a fundamental property of total urban population

A Heteroscedastic Bayesian Generalized Logistic Regression Model with Application to Scaling Problems

Power law scaling models have been used to understand the complexity of systems as diverse as cities, neurological activity, and rainfall and lightning. In the scaling framework, power laws and standard linear regression methods are widely used to estimate model parameters with assumed normality and fixed variance. Generalized linear models (GLM) can accommodate a wider range of distributions where the chosen distribution must meet the assumptions of the data to prevent model bias. We present a widely applicable Bayesian generalized logistic regression (BGLR) framework to more flexibly model a continuous real response addressing skew and heteroscedasticity. The Generalized Logistic Distribution (GLD) was selected to flexibly model skewed continuous data. This resulted in a nonlinear posterior distribution which may not have an analytical solution which can be solved numerically with Markov Chain Monte Carlo (MCMC) methods. We compared the BGLR model to standard and Bayesian normal models having fixed and varying variance when fitting power laws to 759 days of COVID-19 data. The BGLR yielded information beyond existing methods about the evolution of skew and skedasticity while revealing parameter bias of widely used methods. The BGLR flexibly modelled the complex characteristics necessary for an improved understanding of the propagation and dynamics of this infectious disease. The model is generally applicable and can be used as a template for modeling complexity with other distributions

Remote sensing of impervious surface growth: A framework for quantifying urban expansion and re-densification mechanisms

A substantial body of literature has accumulated on the topic of using remotely sensed data to map impervious surfaces which are widely recognized as an important indicator of urbanization. However, the remote sensing of impervious surface growth has not been successfully addressed. This study proposes a new framework for deriving and summarizing urban expansion and re-densification using time series of impervious surface fractions (ISFs) derived from remotely sensed imagery. This approach integrates multiple endmember spectral mixture analysis (MESMA), analysis of regression residuals, spatial statistics (Getis_Ord) and urban growth theories; hence, the framework is abbreviated as MRGU. The performance of MRGU was compared with commonly used change detection techniques in order to evaluate the effectiveness of the approach. The results suggested that the ISF regression residuals were optimal for detecting impervious surface changes while Getis_Ord was effective for mapping hot spot regions i n the regression residuals image. Moreover, the MRGU outputs agreed with the mechanisms proposed in several existing urban growth theories, but importantly the outputs enable the refinement of such models by explicitly accounting for the spatial distribution of both expansion and re - densification mechanisms. Based on Landsat data, the MRGU is somewhat restricted in its ability to measure re-densification in the urban core but this may be improved through the use of higher spatial resolution satellite imagery. The paper ends with an assessment of the present gaps in remote sensing of impervious surface growth and suggests some solutions. The application of impervious surface fractions in urban change detection is a stimulating new research idea which is driving future research with new models and algorithms

Statistical modeling of the coupled F-region ionosphere-thermosphere at high latitude during polar darkness

Statistical models have been developed for predicting the behavior of the coupled high‐latitude ionosphere‐thermosphere system. The modeled parameters were the F‐layer peak electron density, plasma structuring, ion temperature, neutral temperature, and the difference between these temperatures, which is a key term in the Joule heating equation. Ionospheric measurements from the European Incoherent Scatter Svalbard Radar and neutral atmosphere measurements from the colocated University College London Fabry‐Perot Interferometers have been made across a solar cycle. These data were all acquired during nighttime conditions as the observations with the Fabry‐Perot Interferometers are restricted to such times. Various geophysical proxies were tested to represent the processes that influence the modeled parameters. The dominant geophysical proxy for each modeled parameter was then determined. Multivariate models were also developed showing the combinations of parameters that best explained the observed variability. A comparison with climatology showed that the models give an improvement in every case with skill scores based on the mean square error of up to 0.88

How do modern transportation projects impact on development of impervious surfaces via new urban area and urban intensification? Evidence from Hangzhou Bay Bridge, China

Many countries have been constructing modern ground transportation projects. This raises questions about the impacts of such projects on development of impervious surfaces, yet there have been few attempts to systematically analyze these impacts. This paper attempts to narrow this information gap using the Hangzhou Bay Bridge project, China, as an exploratory case study. Using remotely sensed data, we developed a framework based on statistical techniques, wavelet multi-resolution analysis and Theil-Sen slope analysis to measure the changes in impervious surfaces. The derived changes were then linked to the bridge project with respect to socio-economic factors and land use development activities. The findings highlight that the analytical framework could reliably quantify the area, pattern and form of new urban area and urban intensification. Change detection analysis showed that urban area, GDP and the length of highways increased moderately in the pre-Hangzhou Bay Bridge period (1995–2002) while all of these variables increased more substantially during (2002–2009) and after (2009–2013) the bridge construction. The results indicate that the development of impervious surfaces due to new urban area came at the expense of permeable surfaces in the urban fringe and within rural regions, while urban intensification occurred mainly in the form of the redevelopment of older structures to modern high-rise buildings within existing urban regions. In the context of improved transportation infrastructure, our findings suggest that new urban area and urban intensification can be attributed to consecutive events which act like a chain reaction: construction of improved transportation projects, their impacts on land use development policies, effects of both systems on socio-economic variables, and finally all these changes influence new urban area and urban intensification. However, more research is needed to better understand this sequential process and to examine the broader applicability of the concept in other developing regions