Declining glaciers endanger sustainable development of the oases along the Aksu-Tarim River (Central Asia)

Tarim River basin is the largest endorheic river basin in China. Due to the extremely arid climate the water supply solely depends on water originating from the glacierised mountains with about 75% stemming from the transboundary Aksu River. The water demand is linked to anthropogenic (specifically agriculture) and natural ecosystems, both competing for water. Ongoing climate change significantly impacts the cryosphere. The mass balance of the glaciers in Aksu River basin was clearly negative since 1975. The discharge of the Aksu headwaters has been increasing over the last decades mainly due to the glacier contribution. The average glacier melt contribution to total runoff is 30–37% with an estimated glacier imbalance contribution of 8–16%. Modelling using future climate scenarios indicate a glacier area loss of at least 50% until 2100. River discharge will first increase concomitant with glacier shrinkage until about 2050, but likely decline thereafter. The irrigated area doubled in the Aksu region between the early 1990s and 2020, causing at least a doubling of water demand. The current water surplus is comparable to the glacial runoff. Hence, even if the water demand will not grow further in the future a significant water shortage can be expected with declining glacial runoff. However, with the further expansion of irrigated agriculture and related industries, the water demand is expected to even further increase. Both improved discharge projections and planning of efficient and sustainable water use are necessary for further socioeconomic development in the region along with the preservation of natural ecosystems

Gene expression of inflammasome components in peripheral blood mononuclear cells (PBMC) of vascular patients increases with age

Background: Chronic low-grade inflammation is considered a driver of many age-related disorders, including vascular diseases (inflammaging). Inhibition of autophagic capacity with ageing was postulated to generate a pro-inflammatory condition via activation of inflammasomes, a group of Interleukin-1 activating intracellular multi-protein complexes. We thus investigated gene expression of inflammasome components in PBMC of 77 vascular patients (age 22–82) in association with age. Findings: Linear regression of real-time qRT-PCR data revealed a significant positive association of gene expression of each of the inflammasome components with age (Pearson correlation coefficients: AIM2: r = 0.245; P = 0.032; NLRP3: r = 0.367; P = 0.001; ASC (PYCARD): r = 0.252; P = 0.027; CASP1: r = 0.296; P = 0.009; CASP5: r = 0.453; P = 0.00003; IL1B: r = 0.247; P = 0.030). No difference in gene expression of AIM2, NLRP3, ASC CASP1, and CASP5 was detected between PBMC of patients with advanced atherosclerosis and other vascular patients, whereas IL1B expression was increased in PBMC of the latter group (P = 0.0005). Conclusion: The findings reinforce the systemic pro-inflammatory phenotype reported in elderly by demonstrating an increased phase-1 activation of inflammasomes in PBMC of vascular patients

Black-box Integration of Heterogeneous Modeling Languages for Cyber-Physical Systems

Robots belong to a class of Cyber-Physical Systems where complex software as a mobile device has to full tasks in a complex environment. Modeling robotics applications for analysis and code generation requires modeling languages for the logical software architecture and the system behavior. The MontiArcAutomaton modeling framework integrates six independently developed modeling languages to model robotics applications: a component & connector architecture description language, automata, I/O tables, class diagrams, OCL, and a Java DSL. We describe how we integrated these languages into MontiArcAutomaton a-posteriori in a black-box integration fashion.Comment: 6 pages, 4 figures. GEMOC Workshop 2013 - International Workshop on The Globalization of Modeling Languages, Miami, Florida (USA), Volume 1102 of CEUR Workshop Proceedings, CEUR-WS.org, 201

Geschäftsmodelle im Internet der Dinge

Zusammenfassung: Unternehmen, die heute primär in nicht-digitalen Branchen agieren, benötigen theoretisch und praktisch fundierte Hilfestellungen bei der Entwicklung und Umsetzung von Geschäftsmodellen im Internet der Dinge (Internet of Things, IoT). Durch unsere Untersuchung der Rolle des Internet in Geschäftsmodellen kommen wir zum Schluss, dass die Bedeutung des Internet in der Geschäftsmodellinnovation seit den 90er Jahren laufend zugenommen hat, dass jede Internet-Welle zu neuen digitalen Geschäftsmodellmustern geführt hat und dass die größten Umbrüche bisher in digitalen Branchen stattgefunden haben. Wir zeigen, dass digitale Geschäftsmodellmuster neu auch in der physischen Industrie relevant werden. Die Trennung von physischen und digitalen Branchen ist damit endgültig vorbei. Der Schlüssel dazu ist das IoT, das physische Produkte und digitale Services zu hybriden Lösungen verschmelzen lässt. Wir leiten eine sehr allgemein gehaltene Geschäftsmodelllogik für das IoT ab und stellen konkrete Bausteine und Muster von Geschäftsmodellen vor. Für die zentralen Herausforderungen bei der Umsetzung solcher hybriden Geschäftsmodelle zeigen wir erste Lösungsansätze auf

Panel 3 Acquiring and Implementing ERP: The View from Business and Academia

Since the early days of computing, organizations have aspired to integrated, enterprise-wide information systems architectures. Through the years, these aspirations have been reflected in the quest for integrated MIS, enterprise-wide data models, and integrated databases. In recent years, with the increasing demand for process integration both within and across organizational and industry boundaries, this quest has gained further momentum. Enterprise resource planning (ERP) systems, such as SAP, BaaN, Peoplesoft, and Oracle, are a recent business response to this quest. By providing integrated packaged solutions, not only do they provide an integrated system architecture for the organizations’ information processing needs, they also claim to provide ready-made “best-of-the-breed” solutions for particular lines of businesses. Furthermore, given their enterprise-wide scope and extensive impact on organizational and interorganizational business practices, the acquisition and implementation of these systems substantially affects both the organization and the nature of corporate IS practices and the responsibilities of corporate IS departments. While a number of high profile organizations such as Boeing, Mercedes-Benz, ABB, and Levi have recently adopted ERP as an integrated replacement for their enterprise-wide information infrastructure, recent press reports outline a number of issues with the adoption and implementation of ERP systems. Moreover, the adoption of so-called “best-of-breed” applications raises a number of questions about the appropriateness and value of cookie-cutter solutions to diverse organizational requirements

Integration of Heterogeneous Modeling Languages via Extensible and Composable Language Components

Effective model-driven engineering of complex systems requires to appropriately describe different specific system aspects. To this end, efficient integration of different heterogeneous modeling languages is essential. Modeling language integaration is onerous and requires in-depth conceptual and technical knowledge and ef- fort. Traditional modeling lanugage integration approches require language engineers to compose monolithic language aggregates for a specific task or project. Adapting these aggregates cannot be to different contexts requires vast effort and makes these hardly reusable. This contribution presents a method for the engineering of grammar-based language components that can be independently developed, are syntactically composable, and ultimately reusable. To this end, it introduces the concepts of language aggregation, language embed- ding, and language inheritance, as well as their realization in the language workbench MontiCore. The result is a generalizable, systematic, and efficient syntax-oriented composition of languages that allows the agile employment of modeling languages efficiently tailored for individual software projects.Comment: 12 pages, 11 figures. Proceedings of the 3rd International Conference on Model-Driven Engineering and Software Development. Angers, Loire Valley, France, pp. 19-31, 201

Phonons from Density-Functional Perturbation Theory using the All-Electron Full-Potential Linearized Augmented Plane-Wave Method FLEUR

Phonons are quantized vibrations of a crystal lattice that play a crucial role in understanding many properties of solids. Density functional theory (DFT) provides a state-of-the-art computational approach to lattice vibrations from first-principles. We present a successful software implementation for calculating phonons in the harmonic approximation, employing density-functional perturbation theory (DFPT) within the framework of the full-potential linearized augmented plane-wave (FLAPW) method as implemented in the electronic structure package FLEUR. The implementation, which involves the Sternheimer equation for the linear response of the wave function, charge density, and potential with respect to infinitesimal atomic displacements, as well as the setup of the dynamical matrix, is presented and the specifics due to the muffin-tin sphere centered LAPW basis-set and the all-electron nature are discussed. As a test, we calculate the phonon dispersion of several solids including an insulator, a semiconductor as well as several metals. The latter are comprised of magnetic, simple, and transition metals. The results are validated on the basis of phonon dispersions calculated using the finite displacement approach in conjunction with the FLEUR code and the phonopy package, as well as by some experimental results. An excellent agreement is obtained.Comment: 44 pages, 6 figure

Machine learning for non‐invasive sensing of hypoglycaemia while driving in people with diabetes

Aim: To develop and evaluate the concept of a non-invasive machine learning (ML) approach for detecting hypoglycaemia based exclusively on combined driving (CAN) and eye tracking (ET) data. Materials and Methods: We first developed and tested our ML approach in pronounced hypoglycaemia, and then we applied it to mild hypoglycaemia to evaluate its early warning potential. For this, we conducted two consecutive, interventional studies in individuals with type 1 diabetes. In study 1 (n = 18), we collected CAN and ET data in a driving simulator during euglycaemia and pronounced ypoglycaemia (blood glucose [BG] 2.0-2.5 mmol L-1). In study 2 (n = 9), we collected CAN and ET data in the same simulator but in euglycaemia and mild hypoglycaemia (BG 3.0-3.5 mmol L-1). Results: Here, we show that our ML approach detects pronounced and mild hypoglycaemia with high accuracy (area under the receiver operating characteristics curve 0.88 ± 0.10 and 0.83 ± 0.11, respectively). Conclusions: Our findings suggest that an ML approach based on CAN and ET data, exclusively, enables detection of hypoglycaemia while driving. This provides a promising concept for alternative and non-invasive detection of hypoglycaemia