Water detection in Sentinel-1 data using a Bayesian Convolutional Neural Network: Application of uncertainty estimations to identify error prone areas and improve the results

Floods are a natural hazard that can seriously impact the affected communities. Therefore, improvements in flood management are necessary to better prevent and manage flood disasters. These can be achieved by mapping flooded areas using remote sensing data such as Synthetic Aperture Radar (SAR) data. SAR has the advantage of covering large spatial extents and operating weather and daylight independently. While conventional methods exist to detect water in SAR data, Convolutional Neural Networks (CNNs) have produced excellent results. The results, however, do not come without inaccuracies and uncertainties. Therefore, Bayesian Convolutional Neural Networks (BCNNs) have been developed to estimate the uncertainties of the model. This study analyzes the conditions that prevail in misclassified areas. Certain landcover classes like bare soil show higher percentages of wrongly labeled pixels. The behavior of the estimated uncertainties is also tested over pixels that are wrongly and correctly labeled as well as over different landcover classes. It is found that uncertainties are higher over misclassified pixels and certain landcover types like bare soil and herbaceous vegetation. Based on the findings that uncertainties are elevated over falsely labeled pixels, the pixels are turned to their opposite class when exceeding an uncertainty threshold. After the re- labeling, the performance metrics are compared to the initial metrics. In this study, mul- tiple setups for relabeling are tested and compared. The approach is found to be working in certain areas. The study is conducted to confirm the applicability of BCNNs to generate precise flood mapping products and to estimate model uncertainties. The relabeling also aims to shorten the process of training data creation. Training data creation is a resource-intensive step. By improving the results after the classification, less accurate training data might be usa- ble to train the model. As a result, more training data can be efficiently generated to cover more expansive areas globally. The findings provide a basis to create more complete models in the future and further assist flood management

Airflow simulation in two-dimensional bifurcations.

This contribution describes the tested possibilities of a computational fluid dynamics(CFD) software package (FIDAP) to determine airflows in combination with heat and water vapour transport in two dimensional bifurcations simulating human lung bifurcations

Broadening participation in computing: Issues and challenges

In this paper we survey the literature to identify the issues and challenges of broadening participation in computer science, and provide some suggestions to address these challenges. Our attention focuses on redefining the way we approach computing education so that we can successfully entice students to computing that have not traditionally participated, thereby promoting diversity and increasing the total numbers of computing professionals. Based on the literature review, we propose an interactional model from the social sciences to inform the way in which we might restructure and broaden the definition of computing and provide some examples of strategies that we have found to be successful in practice. Copyright 2007 ACM

From Negative to Positive Integration. European State Aid Control through Soft and Hard Law

European state aid control, a part of competition policy, typically follows the logic of negative integration. It constrains the potential for Member States to distort competition by reducing their ability to subsidize industry. In addition, this paper argues, ambiguous Treaty rules and heterogeneous Member States' preferences have enabled the European Commission to act as a supranational entrepreneur, not only enforcing the prohibition of distortive state aid, but also developing its own vision of “good” state aid policy. In order to prevent or to settle political conflict about individual decisions, the Commission has sought to establish more general criteria for the state aid which it still deems admissible. These criteria have been codified into a complex system of soft law and, more recently, hard state aid law. The Commission has thus created positive integration “from above” and increasingly influences the objectives of national state aid policies

Snow Moving to Higher Elevations : Analyzing Three Decades of Snowline Dynamics in the Alps

In the Alps, snow cover dynamics can be monitored using Earth observation (EO). However, low revisit frequency and cloud cover pose a challenge to long‐term time series analysis using high spatial resolution EO images. In this study, we applied the random forest regression to model regional snowline elevations (RSEs). In this manner, daily snowline dynamics and their long‐term trends can be derived, despite the aforementioned challenges. Of the six investigated Alpine catchments between 1984 and 2018, a significant increasing trend of RSEs is shown in four catchments in the early ablation seasons (between 5.38 ± 2.64 and 11.29 ± 4.79 m·a−1) and five catchments in the middle ablation seasons (between 4.17 ± 2.62 and 8.76 ± 4.42 m·a−1). On average, the random forest regression models can explain 75% of the RSE variations. Furthermore, air temperature was found influential in snow persistence especially during middle and late ablation seasons

miR-16 and miR-103 impact 5-HT receptor signalling and correlate with symptom profile in irritable bowel syndrome

Irritable bowel syndrome (IBS) is a gut-brain disorder involving alterations in intestinal sensitivity and motility. Serotonin 5-HT4 receptors are promising candidates in IBS pathophysiology since they regulate gut motor function and stool consistency, and targeted 5-HT4R selective drug intervention has been proven beneficial in subgroups of patients. We identified a single nucleotide polymorphism (SNP) (rs201253747) c.∗61 T > C within the 5-HT4 receptor gene HTR4 to be predominantly present in diarrhoea-IBS patients (IBS-D). It affects a binding site for the miR-16 family and miR-103/miR-107 within the isoforms HTR4b/i and putatively impairs HTR4 expression. Subsequent miRNA-profiling revealed downregulation of miR-16 and miR-103 in the jejunum of IBS-D patients correlating with symptoms. In vitro assays confirmed expression regulation via three 3′UTR binding sites. The novel isoform HTR4b-2 lacking two of the three miRNA binding sites escapes miR-16/103/107 regulation in SNP carriers. We provide the first evidence that HTR4 expression is fine-tuned by miRNAs, and that this regulation is impaired either by the SNP c.∗61 T > C or by diminished levels of miR-16 and miR-103 suggesting that HTR4 might be involved in the development of IBS-D