Climate impacts on material wealth inequality: global evidence from a subnational dataset

Worsening climatic conditions are a significant threat to livelihoods, health and well-being worldwide. In this paper, we estimate the impact of temperature and precipitation anomalies on inequality and poverty using a dataset combining comprehensive climatological data with subnational regional wealth and inequality measures derived from the Demographic and Health Surveys for 52 countries and 453 regions. Using the International Wealth Index as a comparative measure of material wealth, we find a significant impact of temperature anomalies on the distribution of material wealth. We estimate that an average temperature anomaly of one standard deviation in the past 4 years increases the regional Gini coefficient by 0.018 points and increases the share of extremely poor households by 4.1 percent. The impacts are stronger in rural areas. We find that temperature anomalies affect inequality through multiple channels, including agricultural employment, the deterioration of assets, decreased economic activity, higher unemployment and worsened access to healthcare. The impacts of precipitation anomalies on inequality, on the other hand, are more ambiguous

Matrix metalloproteinases and their inhibitors: promising novel biomarkers in severe sepsis?

The multicenter study conducted by Lorente and coworkers published in the previous issue of Critical Care demonstrates that matrix metalloproteinase (MMP)-9 and MMP-10 and their inhibitor tissue inhibitor of matrix metalloproteinase-1 (TIMP-1) are promising novel biomarkers to predict severity and outcome of sepsis. In recent years MMPs have emerged as biomarkers in a variety of diseases, such as sepsis, coronary artery disease, cancer, heart failure, chronic lung disease and rheumatoid arthritis. MMPs constitute a family of proteinases that are expressed during developmental, physiological, and pathophysiological processes, for example as a response to infection. Excessive inflammation following infection may cause tissue damage, and MMPs are implicated in causing this immunopathology. The activity of MMPs is regulated by secretion of specific inhibitors (TIMPs). Studies using MMP inhibitors and MMP knockout mice indicate that MMPs play an essential role in infection and in the host response to infection. The measurement of MMP-9 and MMP-10 and their inhibitor TIMP-1 in the intensive care setting could be an attractive noninvasive tool for determination of outcome of septic patients

Enhanced performance of ultra-thin Cu(In,Ga)Se2 solar cells deposited at low process temperature

To investigate the process temperature on the growth of ultra-thin (≤500 nm) Cu(In,Ga)Se2 (CIGSe) absorbers and the corresponding performance of solar cells, the process temperature was set to 610 °C and 440 °C, respectively. It was found that the low process temperature (440 °C) could reduce the inter- diffusion of Ga–In and thus result in a higher back [Ga]/([Ga]+[In]) ([Ga]/[III]) grading than at the temperature of 610 °C. The higher back [Ga]/[III] grading at 440 °C was evidenced to both electrically and optically contribute to the efficiency enhancement of the solar cells in contrast to the lower back [Ga]/[III] grading at 610 °C. It was also implied that the high back [Ga]/[III] grading was beneficial to the collection of carriers generated from the back-reflected light

Durchführbarkeit präklinischer Sonographie bei Patienten mit Luftnot und Thoraxschmerz im bodengebundenen Rettungsdienst im Landkreis Marburg/Biedenkopf

Gegenstand der Studie ist die Evaluation des p-CHEST Algorithmus, einer präklinischen thorakalen Notfallsonographie bei internistischen Patienten mit Dyspnoe und/oder Thoraxschmerz. Im Rahmen dieser Pilotstudie wurden im Zeitraum zwischen Oktober 2008 und April 2009 im Einsatzgebiet des Rettungsdienstes Mittelhessen 5662 Patienten im Einsatzgebiet des Rettungsdienstes Mittelhessen mit einem tragbaren Ultraschallgerät (SonoSite, Micromaxx) untersucht. Der Algorithmus erwies sich mit seinen 5 Standardschnitten als einfach in der Handhabung und ließ sich mit einer durchschnittlichen Dauer von 2 Minuten problemlos in den einsatztaktischen Ablauf integrieren. Die Untersuchung wurde sowohl am Einsatzort als auch während des Transportes durchgeführt. Die Befundqualität ist verlässlich und es ließen sich in 68% (n=38) der Fälle konkrete zusätzliche Informationen zu differentialdiagnostischen Überlegungen gewinnen. Die Ultraschalluntersuchung diente der Detektion von Pleura- und Perikardergüssen, einer Rechtsherzbelastung, eines Pneumothorax und einer eingeschränkten LV-Funktion. Durch die Ultraschalluntersuchung ließen sich akute z.T. lebensbedrohliche Erkrankungen wie kardiale Dekompensation, Lungenarterienembolie, Pneumothorax oder Perikardtamponade nachweisen oder ausschließen. Besonders hilfreich scheint der Algorithmus für das Diskriminieren von linkskardialer Dekompensation und exazerbierter COPD. In 25% (n=14) der Fälle ergaben sich therapeutische Konsequenzen beispielsweise für die Behandlung mit Vasodilatatoren oder diuretischer Medikamente, einer Antikoagulation oder für das Volumenmanagement. Ziel der Notfallsonographie ist das Verkürzen des therapiefreien Intervalls für eine Optimierung der Versorgung von Patienten mit Dyspnoe und/oder Thoraxschmerz. Limitierend für die Aussagekraft dieser Pilotstudie ist das kleine Patientenkollektiv. Zudem erfolgte die Notfallsonographie durch 4 erfahrene Internisten. Zusammenfassend erachten wir weitere Studien mit einem größeren Patientenkollektiv und einer höheren Anzahl an Untersuchern mit unterschiedlichem Erfahrungsgrad, gegebenenfalls auch mit nicht-ärztlichem Personal, für erforderlich, um die Verlässlichkeit des p-CHEST Algorithmus zu bestätigen

A Comparison of Autonomic Decision Making Techniques

Autonomic computing systems are capable of adapting their behavior and resources thousands of times a second to automatically decide the best way to accomplish a given goal despite changing environmental conditions and demands. Different decision mechanisms are considered in the literature, but in the vast majority of the cases a single technique is applied to a given instance of the problem. This paper proposes a comparison of some state of the art approaches for decision making, applied to a self-optimizing autonomic system that allocates resources to a software application, which provides direct performance feedback at runtime. The Application Heartbeats framework is used to provide the sensor data (feedback), and a variety of decision mechanisms, from heuristics to control-theory and machine learning, are investigated. The results obtained with these solutions are compared by means of case studies using standard benchmarks

SEEC: A Framework for Self-aware Management of Multicore Resources

This paper presents SEEC, a self-aware programming model, designed to reduce programming effort in modern multicore systems. In the SEEC model, application programmers specify application goals and progress, while systems programmers separately specify actions system software and hardware can take to affect an application (e.g. resource allocation). The SEEC runtime monitors applications and dynamically selects actions to meet application goals optimally (e.g. meeting performance while minimizing power consumption). The SEEC runtime optimizes system behavior for the application rather than requiring the application programmer to optimize for the system. This paper presents a detailed discussion of the SEEC model and runtime as well as several case studies demonstrating their benefits. SEEC is shown to optimize performance per Watt for a video encoder, find optimal resource allocation for an application with complex resource usage, and maintain the goals of multiple applications in the face of environmental fluctuations