Resistenz gegenüber Online-Werbung - Einflussfaktoren und Konsequenzen der Werberesistenz im Internet

Die weltweit wachsende Akzeptanz des Mediums Internet führt zu einem steigenden Interesse der Werbeindustrie an der Nutzung des Mediums zur werblichen Kommunikation. Parallel wird in der sich verschärfenden wissenschaftlichen und öffentlichen Diskussion deutlich, dass beim Rezipienten erhebliche Widerstände gegen Werbung im Internet auftreten. In der Konsumentenverhaltensforschung mangelt es jedoch an wissenschaftlichen Untersuchungen, die sich mit der Thematik Werberesistenz detailliert auseinandersetzen. Die vorliegende Arbeit befasst sich daher zunächst mit der konzeptuellen Erarbeitung des Konstrukts Werberesistenz durch eine umfangreiche Analyse bisheriger Konzeptualisierungsansätze. Die Auswertung impliziert ein Resistenzverständnis, das sich durch die Kombination einer Einstellungs- und einer Verhaltenskomponente auszeichnet. In einem komplexen Hypothesensystem werden anschließend persönlichkeitsbezogene sowie vom Management beeinflussbare Determinanten der Werberesistenz modelliert. Die empirische Prüfung des Hypothesensystems erfolgt mittels der LISREL-Kausalanalyse (n=316). Die Ergebnisse der Studie bestätigen die Konzeptualisierung des Konstrukts Werberesistenz. Im hergeleiteten Bezugsrahmen kann die Relevanz der allgemeinen Werbeeinstellung, der persönlichkeitsbezogenen Merkmale Extraversion und Neurotizismus sowie die wahrgenommene Freiheitseinengung durch zu häufige Werbekontakte als Determinanten der Werberesistenz identifiziert werden. Abschließend werden konkrete Maßnahmen erläutert, wie das Marketingmanagement Resistenzen gegenüber OnlineWerbung unterbinden kann

A generalized Markov sampler

A recent development of the Markov chain Monte Carlo (MCMC) technique is the emergence of MCMC samplers that allow transitions between different models. Such samplers make possible a range of computational tasks involving models, including model selection, model evaluation, model averaging and hypothesis testing. An example of this type of sampler is the reversible jump MCMC sampler, which is a generalization of the Metropolis-Hastings algorithm. Here, we present a new MCMC sampler of this type. The new sampler is a generalization of the Gibbs sampler, but somewhat surprisingly, it also turns out to encompass as particular cases all of the well-known MCMC samplers, including those of Metropolis, Barker, and Hastings. Moreover, the new sampler generalizes the reversible jump MCMC. It therefore appears to be a very general framework for MCMC sampling. This paper describes the new sampler and illustrates its use in three applications in Computational Biology, specifically determination of consensus sequences, phylogenetic inference and delineation of isochores via multiple change-point analysis

Reefs at Risk: A Map-Based Indicator of Threats to the Worlds Coral Reefs

This report presents the first-ever detailed, map-based assessment of potential threats to coral reef ecosystems around the world. "Reefs at Risk" draws on 14 data sets (including maps of land cover, ports, settle-ments, and shipping lanes), information on 800 sites known to be degraded by people, and scientific expertise to model areas where reef degradation is predicted to occur, given existing human pressures on these areas. Results are an indicator of potential threat (risk), not a measure of actual condition. In some places, particularly where good management is practiced, reefs may be at risk but remain relatively healthy. In others, this indicator underestimates the degree to which reefs are threatened and degraded.Our results indicate that:Fifty-eight percent of the world's reefs are poten-tially threatened by human activity -- ranging from coastal development and destructive fishing practices to overexploitation of resources, marine pollution, and runoff from inland deforestation and farming.Coral reefs of Asia (Southeastern); the most species-rich on earth, are the most threatened of any region. More than 80 percent are at risk (undermedium and high potential threat), and over half are at high risk, primarily from coastal development and fishing-related pressures.Overexploitation and coastal development pose the greatest potential threat of the four risk categories considered in this study. Each, individually, affects a third of all reefs.The Pacific, which houses more reef area than any other region, is also the least threatened. About 60 percent of reefs here are at low risk.Outside of the Pacific, 70 percent of all reefs are at risk.At least 11 percent of the world's coral reefs contain high levels of reef fish biodiversity and are under high threat from human activities. These "hot spot" areas include almost all Philippine reefs, and coral communities off the coasts of Asia, the Comoros, and the Lesser Antilles in the Caribbean.Almost half a billion people -- 8 percent of the total global population -- live within 100 kilometers of a coral reef.Globally, more than 400 marine parks, sanctuaries, and reserves (marine protected areas) contain coral reefs. Most of these sites are very small -- more than 150 are under one square kilometer in size. At least 40 countries lack any marine protected areas for conserving their coral reef systems

Glacier algae accelerate melt rates on the south-western Greenland Ice Sheet

Melting of the Greenland Ice Sheet (GrIS) is the largest single contributor to eustatic sea level and is amplified by the growth of pigmented algae on the ice surface, which increases solar radiation absorption. This biological albedo-reducing effect and its impact upon sea level rise has not previously been quantified. Here, we combine field spectroscopy with a radiative-transfer model, supervised classification of unmanned aerial vehicle (UAV) and satellite remote-sensing data, and runoff modelling to calculate biologically driven ice surface ablation. We demonstrate that algal growth led to an additional 4.4–6.0 Gt of runoff from bare ice in the south-western sector of the GrIS in summer 2017, representing 10 %–13 % of the total. In localized patches with high biomass accumulation, algae accelerated melting by up to 26.15±3.77 % (standard error, SE). The year 2017 was a high-albedo year, so we also extended our analysis to the particularly low-albedo 2016 melt season. The runoff from the south-western bare-ice zone attributed to algae was much higher in 2016 at 8.8–12.2 Gt, although the proportion of the total runoff contributed by algae was similar at 9 %–13 %. Across a 10 000 km2 area around our field site, algae covered similar proportions of the exposed bare ice zone in both years (57.99 % in 2016 and 58.89 % in 2017), but more of the algal ice was classed as “high biomass” in 2016 (8.35 %) than 2017 (2.54 %). This interannual comparison demonstrates a positive feedback where more widespread, higher-biomass algal blooms are expected to form in high-melt years where the winter snowpack retreats further and earlier, providing a larger area for bloom development and also enhancing the provision of nutrients and liquid water liberated from melting ice. Our analysis confirms the importance of this biological albedo feedback and that its omission from predictive models leads to the systematic underestimation of Greenland's future sea level contribution, especially because both the bare-ice zones available for algal colonization and the length of the biological growth season are set to expand in the future

Use of mental health services among disaster survivors: predisposing factors

<p>Abstract</p> <p>Background</p> <p>Given the high prevalence of mental health problems after disasters it is important to study health services utilization. This study examines predictors for mental health services (MHS) utilization among survivors of a man-made disaster in the Netherlands (May 2000).</p> <p>Methods</p> <p>Electronic records of survivors (n = 339; over 18 years and older) registered in a mental health service (MHS) were linked with general practice based electronic medical records (EMRs) of survivors and data obtained in surveys. EMR data were available from 16 months pre-disaster until 3 years post-disaster. Symptoms and diagnoses in the EMRs were coded according to the International Classification of Primary Care (ICPC). Surveys were carried out 2–3 weeks and 18 months post-disaster, and included validated questionnaires on psychological distress, post-traumatic stress reactions and social functioning. Demographic and disaster-related variables were available. Predisposing factors for MHS utilization 0–18 months and 18–36 months post-disaster were examined using multiple logistic regression models.</p> <p>Results</p> <p>In multiple logistic models, adjusting for demographic and disaster related variables, MHS utilization was predicted by demographic variables (young age, immigrant, public health insurance, unemployment), disaster-related exposure (relocation and injuries), self-reported psychological problems and pre- and post-disaster physician diagnosed health problems (chronic diseases, musculoskeletal problems). After controlling for all health variables, disaster intrusions and avoidance reactions (OR:2.86; CI:1.48–5.53), hostility (OR:2.04; CI:1.28–3.25), pre-disaster chronic diseases (OR:1.82; CI:1.25–2.65), injuries as a result of the disaster (OR:1.80;CI:1.13–2.86), social functioning problems (OR:1.61;CI:1.05–2.44) and younger age (OR:0.98;CI:0.96–0.99) predicted MHS utilization within 18 months post-disaster. Furthermore, disaster intrusions and avoidance reactions (OR:2.29;CI:1.04–5.07) and hostility (OR:3.77;CI:1.51–9.40) predicted MHS utilization following 18 months post-disaster.</p> <p>Conclusion</p> <p>This study showed that several demographic and disaster-related variables and self-reported and physician diagnosed health problems predicted post-disaster MHS-use. The most important factors to predict post-disaster MHS utilization were disaster intrusions and avoidance reactions and symptoms of hostility (which can be identified as symptoms of PTSD) and pre-disaster chronic diseases.</p

International Nonregimes: A Research Agenda1

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146934/1/j.1468-2486.2007.00672.x.pd

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements