First Measurements with NeXtRAD, a Polarimetric X/L Band Radar Network

NeXtRAD is a fully polarimetric, X/L Band radar network. It is a development of the older NetRAD system and builds on the experience gained with extensive deployments of NetRAD for sea clutter and target measurements. In this paper we will report on the first measurements with NeXtRAD, looking primarily at sea clutter and some targets, as well as early attempts at calibration using corner reflectors, and an assessment of the polarimetric response of the system. We also highlight innovations allowing for efficient data manipulation post measurement campaigns, as well as the plans for the coming years with this system

Evaluation of elicitation methods to quantify Bayes linear models

The Bayes linear methodology allows decision makers to express their subjective beliefs and adjust these beliefs as observations are made. It is similar in spirit to probabilistic Bayesian approaches, but differs as it uses expectation as its primitive. While substantial work has been carried out in Bayes linear analysis, both in terms of theory development and application, there is little published material on the elicitation of structured expert judgement to quantify models. This paper investigates different methods that could be used by analysts when creating an elicitation process. The theoretical underpinnings of the elicitation methods developed are explored and an evaluation of their use is presented. This work was motivated by, and is a precursor to, an industrial application of Bayes linear modelling of the reliability of defence systems. An illustrative example demonstrates how the methods can be used in practice

Calculating partial expected value of perfect information via Monte Carlo sampling algorithms

Partial expected value of perfect information (EVPI) calculations can quantify the value of learning about particular subsets of uncertain parameters in decision models. Published case studies have used different computational approaches. This article examines the computation of partial EVPI estimates via Monte Carlo sampling algorithms. The mathematical definition shows 2 nested expectations, which must be evaluated separately because of the need to compute a maximum between them. A generalized Monte Carlo sampling algorithm uses nested simulation with an outer loop to sample parameters of interest and, conditional upon these, an inner loop to sample remaining uncertain parameters. Alternative computation methods and shortcut algorithms are discussed and mathematical conditions for their use considered. Maxima of Monte Carlo estimates of expectations are biased upward, and the authors show that the use of small samples results in biased EVPI estimates. Three case studies illustrate 1) the bias due to maximization and also the inaccuracy of shortcut algorithms 2) when correlated variables are present and 3) when there is nonlinearity in net benefit functions. If relatively small correlation or nonlinearity is present, then the shortcut algorithm can be substantially inaccurate. Empirical investigation of the numbers of Monte Carlo samples suggests that fewer samples on the outer level and more on the inner level could be efficient and that relatively small numbers of samples can sometimes be used. Several remaining areas for methodological development are set out. A wider application of partial EVPI is recommended both for greater understanding of decision uncertainty and for analyzing research priorities

Fluorinated cyclohexanes: Synthesis of amine building blocks of the all- cis 2,3,5,6-tetrafluorocyclohexylamine motif

This paper reports the synthesis of three amine stereoisomers 5a–c of the tetrafluorocyclohexyl ring system, as building blocks for discovery chemistry programmes. The synthesis starts from a Birch reduction of benzonitrile, followed by an in situ methyl iodide quench. The resultant 2,5-cyclohexadiene was progressed via double epoxidations and then hydrofluorination ring opening reactions. The resultant fluorohydrin moieties were then converted to different stereoisomers of the tetrafluorocyclohexyl ring system, and then reductive hydrogenation of the nitrile delivered three amine stereoisomers. It proved necessary to place a methyl group on the cyclohexane ring in order to stabilise the compound against subsequent HF elimination. The two all-cis tetrafluorocyclohexyl isomers 5a and 5b constitute facially polarized cyclohexane rings, with fluorines on the electronegative face and hydrogens on the electropositive face

Novel Statistical Model for a Piece-Wise Linear Radiocarbon Calibration Curve

The process of calibrating radiocarbon determinations onto the calendar scale requires the setting of a specific statistical model for the calibration curve. This model specification will bear fundamental importance for the resulting inference regarding the parameter of interest—namely, in general, the calendar age associated to the sample that has been 14C-dated. Traditionally, the 14C calibration curve has been modelled simply as the piece-wise linear curve joining the (internationally agreed) high-precision calibration data points; or, less frequently, by proposing spline functions in order to obtain a smoother curve. We present a model for the 14C calibration curve which, based on specific characteristics of the dating method, yields a piece-wise linear curve, but one which rather than interpolating the data points, smooths them. We show that with this specific model if a piece-wise linear curve is desired, an underlying random walk model is implied as covariance structure (and vice versa). Furthermore, by making use of all the information provided by the calibration data in a comprehensive way, we achieve an improvement over current models by getting more realistic variance values for the calibration curve.The Radiocarbon archives are made available by Radiocarbon and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform February 202

Poly-ADP-Ribosylation of Estrogen Receptor-Alpha by PARP1 Mediates Antiestrogen Resistance in Human Breast Cancer Cells

Therapeutic targeting of estrogen receptor-α (ERα) by the anti-estrogen tamoxifen is standard of care for premenopausal breast cancer patients and remains a key component of treatment strategies for postmenopausal patients. While tamoxifen significantly increases overall survival, tamoxifen resistance remains a major limitation despite continued expression of ERα in resistant tumors. Previous reports have described increased oxidative stress in tamoxifen resistant versus sensitive breast cancer and a role for PARP1 in mediating oxidative damage repair. We hypothesized that PARP1 activity mediated tamoxifen resistance in ERα-positive breast cancer and that combining the antiestrogen tamoxifen with a PARP1 inhibitor (PARPi) would sensitize tamoxifen resistant cells to tamoxifen therapy. In tamoxifen-resistant vs. -sensitive breast cancer cells, oxidative stress and PARP1 overexpression were increased. Furthermore, differential PARylation of ERα was observed in tamoxifen-resistant versus -sensitive cells, and ERα PARylation was increased by tamoxifen treatment. Loss of ERα PARylation following treatment with a PARP inhibitor (talazoparib) augmented tamoxifen sensitivity and decreased localization of both ERα and PARP1 to ERα-target genes. Co-administration of talazoparib plus tamoxifen increased DNA damage accumulation and decreased cell survival in a dose-dependent manner. The ability of PARPi to overcome tamoxifen resistance was dependent on ERα, as lack of ERα-mediated estrogen signaling expression and showed no response to tamoxifen-PARPi treatment. These results correlate ERα PARylation with tamoxifen resistance and indicate a novel mechanism-based approach to overcome tamoxifen resistance in ER+ breast cancer