Persuading Consumers With Social Attitudes

This paper analyzes persuasive advertising and pricing in oligopoly if firms sell differentiated products and consumers have heterogenous social attitudes towards the consumption by others. Deriving product demand from primitives, we show that the demand-enhancing effect of persuasive advertising varies across consumers and increases in the average degree of conformity. In equilibrium, both quality and cost leaders choose higher advertising intensities and charge higher prices than their competitors. In addition, we show that an increase in the average degree of conformity among consumers reinforces asymmetries between firms.Advertising, social attitude, consumption externality, quality

Selling When Brand Image Matters

This paper studies profit-maximizing seller behavior when brand image affects consumer demand. We consider a seller facing a population of consumers with heterogeneous tastes regarding product quality and brand image. First, we analyze “active branding” by the seller through costly advertising. Our analysis shows that advertising, price and profits are all increasing in the average valuation of brand image in the population. Second, we examine the role of “passive branding” emanating from the population’s consumption of the product. We demonstrate that seller profits increase in the average degree of conformity in the opulation whereas the price remains unaffected.Quality; brand image; advertising; conformity; exclusivity

Let Truth be the Prejudice? Multimodale Diskursanalyse zur ‚Wahrheit‘ fotografischer Bilder am Beispiel der Agentur Magnum Photos

Im vorliegenden Aufsatz wird die multimodale Diskursanalyse nach Gunther Kress beschrieben. Sie zeichnet sich unter anderem dadurch aus, dass sie nicht ausschließlich schriftsprachliche Materialisierungen von Diskursen untersucht. Sie untersucht auch weitere Modi, z. B. Bilder. Der Beitrag stellt zentrale Aspekte der multimodalen Diskursanalyse vor und diskutiert den Begriff der Modalität, welcher die Frage der Wahrheit anspricht. Anhand eines Beispiels wird ein mögliches Vorgehen bei einer multimodalen Diskursanalyse vorgestellt. Untersucht wird das Diskursfeld zur ‚Wahrheit‘ fotografischer Bilder in der professionellen fotografischen Praxis. Gegenstand ist die Agentur Magnum Photos. Erläutert wird, wie ein Korpus aus den textförmigen Veröffentlichungen sowie den Bildern in der agentureigenen Online-Bilddatenbank erstellt werden kann. Des Weiteren wird gezeigt, wie sich Diskurse als Gestaltungsmuster in den Bildern niederschlagen

Multi-core Interference-Sensitive WCET Analysis Leveraging Runtime Resource Capacity Enforcement

The performance and power efficiency of multi-core processors are attractive features for safety-critical applications, as in avionics. But increased integration and average-case performance optimizations pose challenges when deploying them for such domains. In this paper we propose a novel approach to compute a interference-sensitive Worst-Case Execution Time (isWCET) considering variable accesses delays due to the concurrent use of shared resources in multi-core processors. Thereby we tackle the problem of temporal partitioning as it is required by safety-critical applications. In particular, we introduce additional phases to state-of-the-art timing analysis techniques to analyse an applications resource usage and compute an interference delay. We further complement the offline analysis with a runtime monitoring concept to enforce resource usage guarantees. The concepts are evaluated on Freescale's P4080 multi-core processor in combination with SYSGO's commercial real-time operating system PikeOS and AbsInt's timing analysis framework aiT. We abstract real applications' behavior using a representative task set of the EEMBC Autobench benchmark suite. Our results show a reduction of up to 75% of the multi-core Worst-Case Execution Time (WCET), while implementing full transparency to the temporal and functional behavior of applications, enabling the seamless integration of legacy applications

The influence of rotator cuff tear type and weight bearing on shoulder biomechanics in an ex vivo simulator experiment

Glenohumeral biomechanics after rotator cuff (RC) tears have not been fully elucidated. This study aimed to investigate the muscle compensatory mechanism in weight-bearing shoulders with RC tears and asses the induced pathomechanics (i.e., glenohumeral translation, joint instability, center of force (CoF), joint reaction force). An experimental, glenohumeral simulator with muscle-mimicking cable system was used to simulate 30° scaption motion. Eight fresh-frozen shoulders were prepared and mounted in the simulator. Specimen-specific scapular anthropometry was used to test six RC tear types, with intact RC serving as the control, and three weight-bearing loads, with the non-weight-bearing condition serving as the control. Glenohumeral translation was calculated using instantaneous helical axis. CoF, muscle forces, and joint reaction forces were measured using force sensors integrated into the simulator. Linear mixed effects models (RC tear type and weight-bearing) with random effects (specimen and sex) were used to assess differences in glenohumeral biomechanics. RC tears did not change the glenohumeral translation (p > 0.05) but shifted the CoF superiorly (p ≤ 0.005). Glenohumeral translation and joint reaction forces increased with increasing weight bearing (p < 0.001). RC and deltoid muscle forces increased with the presence of RC tears (p ≤ 0.046) and increased weight bearing (p ≤ 0.042). The synergistic muscles compensated for the torn RC tendons, and the glenohumeral translation remained comparable to that for the intact RC tendons. However, in RC tears, the more superior CoF was close to where glenoid erosion occurs in RC tear patients with secondary osteoarthritis. These findings underscore the importance of early detection and precise management of RC tears

Screening for Incidental Sars-Cov-2 Infection in a Neurocritical Care Unit: A Longitudinal Diagnostic Prediction Model

Background: Rapid diagnosis of SARS-CoV-2 infection in patients not primarily assigned with the diagnosis of COVID-19 is highly relevant to effectively rule out virus transmission among patients and medical staff. The purpose is to develop a model for the prediction of the actual presence of a SARS-CoV-2 infection before a valid test result is available and to avoid unnecessary testing in Critical Care Units. Methods: Datasets of laboratory and blood gas analysis tests were collected retrospectively for the development and subsequent validation of machine learning (ML) based models. The data set was composed of 1. 254 SARS-CoV-2 positive cases, collected in an ICU dedicated to patients with COVID-19 pneumonia, 2a. 914 SARS-CoV-2 negative patients treated in a Neurocritical Care Unit and 2b. 32 patients treated for severe influenza pneumonia in a Medical ICU at the same hospital. The models were subsequently validated on a dataset collected from the Neurocritical Care Unit that consisted of data from 7 positive and 42 negative patients. Models were adapted to newly available laboratory values throughout their ICU stay. Extremely Randomized Trees (ERT) and Random Forest (RF) models were evaluated. A baseline model comprising fully grown trees, an optimized model including optimal values for the maximum depth, and a simplified model that only uses the 6 most important features were trained. Results: The overall best model, evaluated via crossvalidation on the development set, is an optimized ERT model with a ROC AUC value of 0.946. The model performance on the validation set is best for the simplified RF model achieving a ROC AUC value of 0.701. Gini feature and permutation importance for the simplified RF model revealed hemoglobin, procalcitonin, C-reactive protein, glomerular filtration rate based on CKD-EPI equation, creatinine, and urea as the most important input features. Using the simplified RF model and a threshold of 0.012 for the probability, a sensitivity above 80% with a specificity of 43% is achieved. Compared to a hypothetical daily testing regimen, using a threshold of 0.145, the simplified RF model detects all positive cases, and, with a false positive rate of 35%, daily tests might be reduced by two thirds. Conclusions: The model developed may support the medical staff in the ICUs by enabling faster and more reliable recognition of COVID-19. Unnecessary serial test sampling might be reduced. To ensure the quality of the model before clinical use, it should be further validated in prospective patient cohorts

Anura, Hylidae, Dendropsophus nahdereri (Lutz and Bokermann, 1963): distribution extension and new state record

Dendropsophus nahdereri is included in the Dendropsophus marmoratus group. Its distribution is known from the Brazilian states of Paraná and Santa Catarina. Here we report new records of this species and briefly describe the habitat of calling males. We found new localities of occurrence of D. nahdereri in Brazilian states of Santa Catarina and Rio Grande do Sul. We collected calling males in temporary lentic water bodies surrounded by arboreal vegetation, inside and on the border of native forest, and inside Pinus plantations near native forest