Coherent and non-coherent processing of multiband radar sensor data

Increasing resolution is an attractive goal for all types of radar sensor applications. Obtaining high radar resolution is strongly related to the signal bandwidth which can be used. The currently available frequency bands however, restrict the available bandwidth and consequently the achievable range resolution. As nowadays more sensors become available e.g. on automotive platforms, methods of combining sensor information stemming from sensors operating in different and not necessarily overlapping frequency bands are of concern. It will be shown that it is possible to derive benefit from perceiving the same radar scenery with two or more sensors in distinct frequency bands. Beyond ordinary sensor fusion methods, radar information can be combined more effectively if one compensates for the lack of mutual coherence, thus taking advantage of phase information. <P> At high frequencies, complex scatterers can be approximately modeled as a group of single scattering centers with constant delay and slowly varying amplitude, i.e. a set of complex exponentials buried in noise. The eigenanalysis algorithms are well known for their capability to better resolve complex exponentials as compared to the classical spectral analysis methods. These methods exploit the statistical properties of those signals to estimate their frequencies. Here, two main approaches to extend the statistical analysis for the case of data collected at two different subbands are presented. One method relies on the use of the band gap information (and therefore, coherent data collection is needed) and achieves an increased resolution capability compared with the single-band case. On the other hand, the second approach does not use the band gap information and represents a robust way to process radar data collected with incoherent sensors. Combining the information obtained with these two approaches a robust estimator of the target locations with increased resolution can be built

Lung Segmentation from Chest X-rays using Variational Data Imputation

Pulmonary opacification is the inflammation in the lungs caused by many respiratory ailments, including the novel corona virus disease 2019 (COVID-19). Chest X-rays (CXRs) with such opacifications render regions of lungs imperceptible, making it difficult to perform automated image analysis on them. In this work, we focus on segmenting lungs from such abnormal CXRs as part of a pipeline aimed at automated risk scoring of COVID-19 from CXRs. We treat the high opacity regions as missing data and present a modified CNN-based image segmentation network that utilizes a deep generative model for data imputation. We train this model on normal CXRs with extensive data augmentation and demonstrate the usefulness of this model to extend to cases with extreme abnormalities.Comment: Accepted to be presented at the first Workshop on the Art of Learning with Missing Values (Artemiss) hosted by the 37th International Conference on Machine Learning (ICML). Source code, training data and the trained models are available here: https://github.com/raghavian/lungVAE

An Internet-Based Tool for Use in Assessing the Likely Effect of Intensification on Losses of Nitrogen to the Environment

The EU Nitrates, Habitat and National Emissions Ceilings directives and the Kyoto Agreement mean that agricultural losses of NO3, NH3 and N2O are under scrutiny by national and international environmental authorities. When farmers wish to intensify their operations, the authorities must then assess the likely environmental impact of the change in operation. The FARM-N internet tool was developed to help farmers and authorities agree how the farm will be structured and managed in the future, and to provide an objective assessment of the environmental losses that will result

From Euclidean Geometry to Knots and Nets

This document is the Accepted Manuscript of an article accepted for publication in Synthese. Under embargo until 19 September 2018. The final publication is available at Springer via https://doi.org/10.1007/s11229-017-1558-x.This paper assumes the success of arguments against the view that informal mathematical proofs secure rational conviction in virtue of their relations with corresponding formal derivations. This assumption entails a need for an alternative account of the logic of informal mathematical proofs. Following examination of case studies by Manders, De Toffoli and Giardino, Leitgeb, Feferman and others, this paper proposes a framework for analysing those informal proofs that appeal to the perception or modification of diagrams or to the inspection or imaginative manipulation of mental models of mathematical phenomena. Proofs relying on diagrams can be rigorous if (a) it is easy to draw a diagram that shares or otherwise indicates the structure of the mathematical object, (b) the information thus displayed is not metrical and (c) it is possible to put the inferences into systematic mathematical relation with other mathematical inferential practices. Proofs that appeal to mental models can be rigorous if the mental models can be externalised as diagrammatic practice that satisfies these three conditions.Peer reviewe

Reproducibility of the peritoneal regression grading score for assessment of response to therapy in peritoneal metastasis.

The four-tiered peritoneal regression grading score (PRGS) assesses the response to chemotherapy in peritoneal metastasis (PM). The PRGS is used, for example, to assess the response to pressurised intraperitoneal aerosol chemotherapy (PIPAC). However, the reproducibility of the PRGS is currently unknown. We aimed to evaluate the inter- and intraobserver variability of the PRGS. Thirty-three patients who underwent at least three PIPAC treatments as part of the PIPAC-OPC1 or PIPAC-OPC2 clinical trials at Odense University Hospital, Denmark, were included. Prior to each therapy cycle, peritoneal quadrant biopsies were obtained and three haematoxylin and eosin (H&amp;E)-stained step sections were scanned and uploaded to a pseudonymised web library. For determining interobserver variability, eight pathologists assessed the PRGS for each quadrant biopsy, and Krippendorff's alpha and intraclass correlation coefficients (ICCs) were calculated. For determining intraobserver variability, three pathologists repeated their own assessments and Cohen's kappa and ICCs were calculated. A total of 331 peritoneal biopsies were analysed. Interobserver variability for PRGS of each biopsy and for the mean and maximum PRGS per biopsy set was moderate to good/substantial. The intraobserver variability for PRGS of each biopsy and for the mean and maximum PRGS per biopsy set was good to excellent/almost perfect. Our data support the PRGS as a reproducible and useful tool to assess response to intraperitoneal chemotherapy in PM. Future studies should evaluate the prognostic and predictive role of the PRGS

The "Artificial Mathematician" Objection: Exploring the (Im)possibility of Automating Mathematical Understanding

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer

Role of immunohistochemistry for interobserver agreement of Peritoneal Regression Grading Score in peritoneal metastasis.

Pressurized intraperitoneal aerosol chemotherapy (PIPAC)-directed therapy is a new treatment option for peritoneal metastasis (PM). The 4-tiered Peritoneal Regression Grading Score (PRGS) has been proposed for assessment of histological treatment response. We aimed to evaluate the effect of immunohistochemistry (IHC) on interobserver agreement of the PRGS. Hematoxylin and eosin (H&amp;E)-stained and IHC-stained slides (n = 662) from 331 peritoneal quadrant biopsies (QBs) taken prior to 99 PIPAC procedures performed on 33 patients were digitalized and uploaded to a web library. Eight raters (five consultants and three residents) assessed the PRGS, and Krippendorff's alpha coefficients (α) were calculated. Results (IHC-PRGS) were compared with data published in 2019, using H&amp;E-stained slides only (H&amp;E-PRGS). Overall, agreement for IHC-PRGS was substantial to almost perfect. Agreement (all raters) regarding single QBs after treatment was substantial for IHC-PRGS (α = 0.69, 95% confidence interval [CI] = 0.66-0.72) and moderate for H&amp;E-PRGS (α = 0.60, 95% CI = 0.56-0.64). Agreement (all raters) regarding the mean PRGS per QB set after treatment was higher for IHC-PRGS (α = 0.78, 95% CI = 0.73-0.83) than for H&amp;E-PRGS (α = 0.71, 95% CI = 0.64-0.78). Among residents, agreement was almost perfect for IHC-PRGS and substantial for H&amp;E-PRGS. Agreement (all raters) regarding maximum PRGS per QB set after treatment was substantial for IHC-PRGS (α = 0.61, 95% CI = 0.54-0.68) and moderate for H&amp;E-PRGS (α = 0.60, 95% CI = 0.53-0.66). Among residents, agreement was substantial for IHC-PRGS (α = 0.66, 95% CI = 0.57-0.75) and moderate for H&amp;E-PRGS (α = 0.55, 95% CI = 0.45-0.64). Additional IHC seems to improve the interobserver agreement of PRGS, particularly between less experienced raters

A phase II study of Epirubicin in oxaliplatin-resistant patients with metastatic colorectal cancer and <i>TOP2A</i> gene amplification

ᅟ: The overall purpose of this study is to provide proof of concept for introducing the anthracycline epirubicin as an effective, biomarker-guided treatment for metastatic colorectal cancer (mCRC) patients who are refractory to treatment with oxaliplatin-based chemotherapy and have TOP2A gene amplification in their tumor cells. BACKGROUND: Epirubicin is an anthracycline that targets DNA topoisomerase 2-α enzyme encoded by the TOP2A gene. It is used for treatment of several malignancies, but currently not in CRC. TOP2A gene amplifications predict improved efficacy of epirubicin in patients with breast cancer and thus could be an alternative option for patients with CRC and amplified TOP2A gene. We have previously analysed the frequency of TOP2A gene aberrations in CRC and found that 46.6 % of these tumors had TOP2A copy gain and 2.0 % had loss of TOP2A when compared to adjacent normal tissue. The TOP2A gene is located on chromosome 17 and when the TOP2A/CEN-17 ratio was applied to identify tumors with gene loss or amplifications, 10.5 % had a ratio ≥ 1.5 consistent with gene amplification and 2.6 % had a ratio ≤ 0.8 suggesting gene deletions. Based on these observations and the knowledge gained from treatment of breast cancer patients, we have initiated a prospective clinical, phase II protocol using epirubicin (90 mg/m2 iv q 3 weeks) in mCRC patients, who are refractory to treatment with oxaliplatin. METHODS/DESIGN: The study is an open label, single arm, phase II study, investigating the efficacy of epirubicin in patients with oxaliplatin refractory mCRC and with a cancer cell TOP2A/CEN-17 ratio ≥ 1.5. TOP2A gene amplification measured by fluorescence in situ hybridization. A total of 25 evaluable patients (15 + 10 in two steps) will be included (Simon’s two-stage minimax design). Every nine weeks, response is measured by computed tomography imaging and evaluated according to RECIST 1.1. The primary end-point of the study is progression-free survival. TRIAL REGISTRATION: Eudract no. 2013-001648-79

Calibration to American options: numerical investigation of the de-Americanization method.

American options are the reference instruments for the model calibration of a large and important class of single stocks. For this task, a fast and accurate pricing algorithm is indispensable. The literature mainly discusses pricing methods for American options that are based on Monte Carlo, tree and partial differential equation methods. We present an alternative approach that has become popular under the name de-Americanization in the financial industry. The method is easy to implement and enjoys fast run-times (compared to a direct calibration to American options). Since it is based on ad hoc simplifications, however, theoretical results guaranteeing reliability are not available. To quantify the resulting methodological risk, we empirically test the performance of the de-Americanization method for calibration. We classify the scenarios in which de-Americanization performs very well. However, we also identify the cases where de-Americanization oversimplifies and can result in large errors