Monitoring spatial sustainable development: Semi-automated analysis of satellite and aerial images for energy transition and sustainability indicators

Solar panels are installed by a large and growing number of households due to the convenience of having cheap and renewable energy to power house appliances. In contrast to other energy sources solar installations are distributed very decentralized and spread over hundred-thousands of locations. On a global level more than 25% of solar photovoltaic (PV) installations were decentralized. The effect of the quick energy transition from a carbon based economy to a green economy is though still very difficult to quantify. As a matter of fact the quick adoption of solar panels by households is difficult to track, with local registries that miss a large number of the newly built solar panels. This makes the task of assessing the impact of renewable energies an impossible task. Although models of the output of a region exist, they are often black box estimations. This project's aim is twofold: First automate the process to extract the location of solar panels from aerial or satellite images and second, produce a map of solar panels along with statistics on the number of solar panels. Further, this project takes place in a wider framework which investigates how official statistics can benefit from new digital data sources. At project completion, a method for detecting solar panels from aerial images via machine learning will be developed and the methodology initially developed for BE, DE and NL will be standardized for application to other EU countries. In practice, machine learning techniques are used to identify solar panels in satellite and aerial images for the province of Limburg (NL), Flanders (BE) and North Rhine-Westphalia (DE).Comment: This document provides the reader with an overview of the various datasets which will be used throughout the project. The collection of satellite and aerial images as well as auxiliary information such as the location of buildings and roofs which is required to train, test and validate the machine learning algorithm that is being develope

Stakeholder theory: basic provisions and field studies

Розглянуто сутність і понятійний апарат теорії зацікавлених сторін (стейкхолдерів); обґрунтовано її основні положення з урахуванням сучасних підходів до розуміння сенсу існування підприємства; узагальнено підходи до класифікації ключових стейкхолдерів і визначено зміст основних областей дослідження теорії зацікавлених сторін.Today, the focus of the institutional theory of firm is shifted towards the stakeholder theory – an alternative to the neoclassical theory of firm that based on meeting the interests of the various participants in business activity. This direction, on the one hand, has considerable theoretical and applied significance, and on the other hand, is characterized by a certain incompleteness and inconsistencies. The paper considers the essence and the main concepts of the stakeholder theory, substantiates its key tenets according to the current approaches to understanding the enterprise’s raison d'etre; determines that all groups or individuals that influence on company business activities are its stakeholders whose interests should be considered by management; summarizes the approaches to the classification of the key stakeholders and determines the content of the main research areas of stakeholder theory (who are stakeholders, what are their interests and what are the ways they can realize these interests)

A generalized framework to predict continuous scores from medical ordinal labels

Many variables of interest in clinical medicine, like disease severity, are recorded using discrete ordinal categories such as normal/mild/moderate/severe. These labels are used to train and evaluate disease severity prediction models. However, ordinal categories represent a simplification of an underlying continuous severity spectrum. Using continuous scores instead of ordinal categories is more sensitive to detecting small changes in disease severity over time. Here, we present a generalized framework that accurately predicts continuously valued variables using only discrete ordinal labels during model development. We found that for three clinical prediction tasks, models that take the ordinal relationship of the training labels into account outperformed conventional multi-class classification models. Particularly the continuous scores generated by ordinal classification and regression models showed a significantly higher correlation with expert rankings of disease severity and lower mean squared errors compared to the multi-class classification models. Furthermore, the use of MC dropout significantly improved the ability of all evaluated deep learning approaches to predict continuously valued scores that truthfully reflect the underlying continuous target variable. We showed that accurate continuously valued predictions can be generated even if the model development only involves discrete ordinal labels. The novel framework has been validated on three different clinical prediction tasks and has proven to bridge the gap between discrete ordinal labels and the underlying continuously valued variables

Yeast mitochondrial protein Pet111p binds directly to two distinct targets in COX2 mRNA, suggesting a mechanism of translational activation

The genes in mitochondrial DNA code for essential subunits of the respiratory chain complexes. In yeast, expression of mitochondrial genes is controlled by a group of gene-specific translational activators encoded in the nucleus. These factors appear to be part of a regulatory system that enables concerted expression of the necessary genes from both nuclear and mitochondrial genomes to produce functional respiratory complexes. Many of the translational activators are believed to act on the 5\u27-untranslated regions of target mRNAs, but the molecular mechanisms involved in this regulation remain obscure. In this study, we used a combination of in vivo and in vitro analyses to characterize the interactions of one of these translational activators, the pentatricopeptide repeat protein Pet111p, with its presumed target, COX2 mRNA, which encodes subunit II of cytochrome c oxidase. Using photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation analysis, we found that Pet111p binds directly and specifically to a 5\u27-end proximal region of the COX2 transcript. Further, we applied in vitro RNase footprinting and mapped two binding targets of the protein, of which one is located in the 5\u27-untranslated leader and the other is within the coding sequence. Combined with the available genetic data, these results suggest a plausible mechanism of translational activation, in which binding of Pet111p may prevent inhibitory secondary structures from forming in the translation initiation region, thus rendering the mRNA available for interaction with the ribosome. © 2019 Jones et al

Climacteric Lowers Plasma Levels of Platelet-Derived Microparticles: A Pilot Study in Pre-versus Postmenopausal Women

Background: Climacteric increases the risk of thrombotic events by alteration of plasmatic coagulation. Up to now, less is known about changes in platelet-(PMP) and endothelial cell-derived microparticles (EMP). Methods: In this prospective study, plasma levels of microparticles (MP) were compared in 21 premenopausal and 19 postmenopausal women. Results: No altered numbers of total MP or EMP were measured within the study groups. However, the plasma values of CD61-exposing MP from platelets/megakaryocytes were higher in premenopausal women (5,364 x 10(6)/l, range 4,384-17,167) as compared to postmenopausal women (3,808 x 10(6)/l, range 2,009-8,850; p = 0.020). This differentiation was also significant for the subgroup of premenopausal women without hormonal contraceptives (5,364 x 10(6)/l, range 4,223-15,916; p = 0.047; n = 15). Furthermore, in premenopausal women, higher plasma levels of PMP exposing CD62P were also present as compared to postmenopausal women (288 x 10(6)/l, range 139-462, vs. 121 x 10(6)/l, range 74-284; p = 0.024). This difference was also true for CD63+ PMP levels (281 x 10(6)/l, range 182-551, vs. 137 x 10(6)/l, range 64-432; p = 0.015). Conclusion: Climacteric lowers the level of PMP but has no impact on the number of EMP in women. These data suggest that PMP and EMP do not play a significant role in enhancing the risk of thrombotic events in healthy, postmenopausal women. Copyright (C) 2012 S. Karger AG, Base