Localizing and prioritizing roof greening opportunities for urban heat island mitigation: insights from the city of Krefeld, Germany

Context: Climate change may increase the frequency, intensity, and occurrence of urban heat islands (UHI) in cities worldwide, often with harmful impacts on citizens. Strategic planning and implementation of multifunctional green roofs promises to help mitigating UHI effects, but cities often lack up-to-date scientific understanding of best-suited locations. Objectives: The aim of this paper is to develop and apply a socio-ecological approach to explore and prioritize present and prospective opportunity spaces for roof greening based on remote sensing data to mitigate UHI effects. Methods: The city of Krefeld, Germany, serves as a case study. The research design consists of three steps, applied to the conditions of 2019 and a 2030 scenario: (i) Examining residents’ vulnerability to heat, (ii) Assessing existing green roofs and potentials for greening, and (iii) Prioritizing opportunity spaces for roof greening to reduce UHI effects. Results: Findings showed that the area of high vulnerability due to combined high heat exposures and densities of sensitive residents in Krefeld accounts for almost 300 hectares in 2019 and may triple until 2030. More than 90% of evaluated horizontal roofs have no vegetation cover. Highest priority for roof greening is attributed to 59 ha and 113 ha of roofs in 2019 and 2030, respectively. Conclusions: The findings can inform strategic roof greening efforts for climate adaptation, e.g. for the extension of cadasters, and facilitate communication to increase understandings, public and policy support, and implementation

Max Clara and Innsbruck - The origin of a German Nationalist and National Socialist career.

This investigation aims to summarize hitherto scattered pieces of evidence of the early biography of Max Clara, especially considering his connections with the Histological Institute of the University of Innsbruck. Max Clara was born in 1899 in South Tyrol, at that time part of the Habsburg Empire. After high school in Bozen and his participation in World War I, Clara studied medicine in Innsbruck, Austria and Leipzig, Germany, graduating from Innsbruck University in 1923. He joined the Corps Gothia, a German Student Corps, at the start of his studies and became socialized as a German nationalist. When the Tyrolean Parliament conducted an illegal referendum in 1921, in which a majority voted for the merger of Tyrol with Germany, the active members of the Gothia spontaneously removed the border barriers between Austria and Bavaria in the municipality of Scharnitz. They brought them to Innsbruck to be deposited in the statehouse. Clara's participation in this activity is not documented but is very likely. Seventy-four per cent of the members of this corps joined the Nazi party (Nationalsozialistische Deutsche Arbeiterpartei, NSDAP), even before the annexation of Austria by National Socialist (NS) Germany in 1938. Clara likely met Maximinian de Crinis, an SS officer and high-ranking member of the NS health administration, through contacts within their respective corps. De Crinis supported Clara decisively in the anatomist's appointments as chair of anatomy at the University of Leipzig and later at the University of Munich. Initially, Clara began his academic career at the Institute of Histology and Embryology in Innsbruck as (student) demonstrator, and in 1923 as an assistant. In December 1923 Clara had to leave Innsbruck for Blumau, South Tyrol to take over the medical surgery of his father, who had passed away unexpectedly. Back in Italy, he continued his histological research in his spare time and published a large number of scientific papers. His connections with Innsbruck and especially with histologist Jurg Mathis never ceased

A Socio-Technical Approach to Manage Analytics-as-a-Service – Results of an Action Design Research Project

The ability to generate business-relevant information and its use for business process improvements is a key success factor for businesses today. Answering the call for further research on success-relevant practices and instruments for managing business analytics, we report on the results of a three-year action design research project at a global car manufacturer. Drawing on the socio-technical systems theory, we identify seven meta-requirements and specify four principles for the design of an instrument to manage Analytics-as-a-Service(Aaas) portfolios. Our results reinforce the importance of coordinating different socio-technical components in business analytics initiatives and demonstrate how concrete management instruments, such as the proposed portfolio management tool, contribute to socio-technical alignment. For practitioners, the documented design components may provide guidance on how to design and implement similar instruments that support the management of Aaas portfolios

The ScenarioTools Play-Out of Modal Sequence Diagram Specifications with Environment Assumptions

Many software-intensive systems consist of multiple components that provide complex functionality by their interaction. The scenario-based languages LSCs and MSDs are intuitive, but precise means to specify interactions; the engineers can specify how a system can, must, or must not react to events in its environment. A key benefit of LSCs/MSDs is that they can be executed via the play-out algorithm, which allows engineers to perform an early automated analysis of the specification. However, LSCs/MSDs lack support for expressing also what can or cannot happen in the environment. This is crucial especially in embedded systems: very often, the software will only be able to satisfy its requirements if certain assumptions are made about the behavior of mechanical parts or the physical environment. We extend MSD specifications to formally express such environment assumptions, and propose a corresponding extension of the play-out algorithm. The concepts are implemented in a novel, Eclipse-based tool

Die interdisziplinäre Polytraumaversorgung am Universitätsklinikum Tübingen und der Berufsgenossenschaftlichen Unfallklinik Tübingen im Jahr 2012 mit Evaluation des Outcomes

Einleitung: Die Polytraumaversorgung erfordert seit jeher eine interdisziplinäre Zusammenarbeit unter erheblichem logistischen Aufwand. Dabei stellt neben der Komplexität der Verletzungsmuster auch die Heterogenität der beteiligten Berufsgruppen eine große Herausforderung dar. Um die unterschiedlichen Ressourcen der beteiligten Kliniken optimal zu nutzen wurde durch die Initiative TraumaNetzwerk ein hierarchisch gegliedertes Organisationskonzept entwickelt in welches die BGU Tübingen und das Universitätsklinikum Tübingen als überregionales Traumazentrum beteiligt ist. Ziel dieser Arbeit war es herauszufinden, in wie fern sich das erfasste Patientengut Tübingens des Jahres 2012 mit dem des TraumaRegisters der DGU im Jahr 2012 und der vergangenen 10 Jahre vergleichen lässt und ob das Outcome der Tübinger sich mit anderen Daten vergleichen lässt. Patienten und Methodik: Im Untersuchungszeitraum 2012 wurden im überregionalen Traumazentrum 130 Schwerstverletzte versorgt. Diese wurden gemäß den DGU-Richtlinien erfasst, sofern der ISS >9 gewesen ist. Die Datenerhebung erfolgte nach retrospektiv nach Aktenlage, im zur Erfassung diente der DGU-Erhebungsbogen Stand 3/2009. Die erhobenen Daten wurden nach Komplettierung der Datenerhebung anonymisiert in die Datenbank des Traumaregisters eingepflegt. Nach Abschluss der Datenerfassung und der Auswertung erfolgte der Vergleich mit den Daten der Online-Auswertung der eigenen Patienten und denen des Traumaregisters DGU. So konnte eine Analyse der eigenen Daten und der Vergleich mit dem gesamten Traumaregister erfolgen. Zur Objektivierung und besseren Vergleichbarkeit wurden verschieden Scoring-Systeme genutzt (ISS, RISC GOS, GCS, SAPS II, SOFA). Zudem wurde die Anwendbarkeit von Prognosescores überprüft. Ergebnisse: Im Untersuchungszeitraum wurden 130 Schwerstverletzte identifiziert und erfasst. Sowohl was die Geschlechtsverteilung (m:w 72,3% vs. 27,7%) als auch die Altersverteilung (Mittelwert 45,5 Jahre) angeht entspricht das Tübinger Patientengut denen anderer Arbeiten. Mit einer Verletzungsschwere von durchschnittlich ISS 22,9 sind die Tübinger schwerer Verletzt als im gesamten Traumaregister (ISS 17). Insgesamt waren 89 Patienten (71,2%) schwerst verletzt (ISS≥16) von denen 15 Patienten (12,3%) im Verlauf verstarben. Von allen Erfassten Patienten konnten 63 Patienten gut erholt entlassen werden. Insgesamt lassen sich die Ergebnisse durchaus mit dem Gesamtkollektiv TraumaRegister im gleichen Erhebungszeitraum vergleichen. Schlussfolgerung Im Hinblick auf die ländliche Struktur und unter Berücksichtigung der Tatsache, dass Tübingen als Überregionales Traumazentrum im Traumanetzwerk Südwürttemberg häufiger schwerst verletzte Patienten versorgen muss, lassen sich die erhobenen Daten nur bedingt mit denen des TraumaRegisters vergleichen. Gleichen sich die Patientenkollektive in Bezug auf Altersverteilung und Unfallmechanismen so unterscheiden sie sich in er Verlertzungsschwere und dem Outcome, vor allem bei letzterem liegen Tübinger Patienten, auch der Verlerzungsschwere geschuldet, mit einer höheren Letalität über den Daten des TraumaRegisters. Beachtet werden muss allerdings, dass die ländliche Struktur und ein Vergleich zu einem heterogenen Kollektiv gezogen wird. Diese bildet auch die Grundlage der Progrnosescores welche zwar einen gute Letalitätsvoraussage zulassen, aber eben nur bedingt auf das Tübinger Patientenkollektiv angewendet werden können

Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference standard, three CNNs were trained. Training sets balanced for infiltration status, lymph node location and additionally, masked images, were used for training. CNNs were evaluated using a separate test set and performance was compared to radiologists' assessments and random forest classifiers. Heatmaps maps were used to identify the performance determining image regions. The CNNs performed with an Area-Under-the-Curve of 0.95 (status balanced) and 0.86 (location balanced, masked), compared to an AUC of 0.81 of experienced radiologists. Interestingly, CNNs used anatomical surroundings to increase their performance, "learning" the infiltration probabilities of anatomical locations. In conclusion, CNNs have the potential to build a well performing CT-based biomarker for lymph node metastases in PCa, with different types of class balancing strongly affecting CNN performance

ScenarioTools Real-Time Play-Out for Test Sequence Validation in an Automotive Case Study

In many areas, such as automotive, healthcare, or production, we find software-intensive systems with complex real-time requirements. To efficiently ensure the quality of these systems, engineers require automated tools for the validation of the requirements throughout the development. This, however, requires that the requirements are specified in an analyzable way. We propose modeling the specification using Modal Sequence Diagrams (MSDs), which express what a system may, must, or must not do in certain situations. MSDs can be executed via the play-out algorithm to investigate the behavior emerging from the interplay of multiple scenarios; we can also test if traces of the final product satisfy all scenarios. In this paper, we present the first tool supporting the play-out of MSDs with real-time constraints. As a case study, we modeled the requirements on gear shifts in an upcoming standard on vehicle testing and use our tool to validate externally generated gear shift sequences

Exergy performance and optimization potential of refrigeration plants in free cooling operation

Exergy analysis has been widely used to assess refrigeration systems by evaluating exergy losses or exergy efficiency. The latter is mostly used as an indicator to determine the system performance, which requires the comparison of the actual system with its idealized reversible version, but not the practical achievable efficiency. Therefore, a practice-oriented evaluation method for refrigeration plants in free cooling operation is proposed, based on exergy analysis and technical standards as baseline. By considering the exergy input of auxiliary devices, the overall design of hydraulic circuits can be assessed on subsystem level. The achievable optimization potential compared to the state of the art in technology and the performance is revealed with the introduced optimization potential index (OPI). The application is demonstrated on a case study, where the analysis reveals an adequate operation of the field plant in general. Most cooling locations show potential for improvement, which is indicated by an OPI superior to zero. Moreover, the auxiliary electrical exergy input shows the same magnitude as the thermal exergy input, which emphasizes the importance of reducing the electrical energy usage of auxiliary devices in refrigeration plants to increase the performance