The Role of Fear-Relevant Stimuli in Visual Search: A Comparison of Phylogenetic and Ontogenetic Stimuli.

It has been argued that phylogenetic fear-relevant stimuli elicit preattentive capture of attention. To distinguish between fear relevance and time of appearance in evolutionary history, the authors compare phylogenetic and ontogenetic fear-relevant and fear-irrelevant stimuli in a visual search task. The authors found no evidence for a special role of phylogenetic fear-relevant stimuli; it seems that fear relevance in general is more important than is the evolutionary age. The pattern of results indicates that attention toward threatening stimuli is mainly affected by a late component that prolongs the disengagement of attention. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attitudes toward instructors, social desirability, and behavioral intentions.

Examined whether student attitude toward instructors was related to subsequent behavior, such as the behavioral intention to take further courses with that instructor, and whether social desirability affected this relationship. 158 undergraduates completed instructor ratings, and a short form of the Marlowe-Crowne Social Desirability Scale. Principal components analysis and varimax rotation isolated 6 instructor rating factors. Ss also participated in a mock preregistration procedure assessing their intention to reregister for the same or different instructors. Results indicate that the 1st instructor rating factor, Instructor Skill, correlated .72 with intention to take further courses with that instructor. No other relationships or interactions were significant. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Charakterisierung zweier Karstsysteme mithilfe organischer Spurenstoffe

In the presented work the occurrence of organic micro-pollutants is discussed for two karst areas with different geological characteristics and land-use patterns. Within an urban moderately karstified catchment with a large number of local input sources (e.g. contaminated sites, sewer leakages), a greater variety of micro-pollutants is found compared to a rural area. Mostly the concentrations of these compounds decrease below quantification limits before emerging at the spring and can therefore only be detected by a comprehensive network of sampling points. Springs show the presence of micro-pollutants, either recently applied in large amounts or characterized by high persistence. At the outlet of a highly karstified and consequently highly permeable aquifer readily biodegradable compounds are detected. Due to high groundwater flow velocities investigations of micro-pollutants require a highly resolved monitoring. Therefore, beside substance properties, also hydrogeological characteristics affect the spectrum of detectable micro-pollutants.     

Alemtuzumab in Multiple Sclerosis: Mechanism of Action and Beyond

Alemtuzumab is a humanized monoclonal antibody against CD52 (cluster of differentiation 52) and is approved for the therapy of relapsing-remitting multiple sclerosis. The application of alemtuzumab leads to a rapid, but long-lasting depletion predominantly of CD52-bearing B and T cells with reprogramming effects on immune cell composition resulting in the restoration of tolerogenic networks. Alemtuzumab has proven high efficacy in clinical phase II and III trials, where interferon β-1a was used as active comparator. However, alemtuzumab is associated with frequent and considerable risks. Most importantly secondary autoimmune disease affects 30%–40% of patients, predominantly impairing thyroid function. Extensive monitoring and early intervention allow for an appropriate risk management. However, new and reliable biomarkers for individual risk stratification and treatment response to improve patient selection and therapy guidance are a significant unmet need. Only a deeper understanding of the underlying mechanisms of action (MOA) will reveal such markers, maximizing the best potential risk-benefit ratio for the individual patient. This review provides and analyses the current knowledge on the MOA of alemtuzumab. Most recent data on efficacy and safety of alemtuzumab are presented and future research opportunities are discussed.     

The Ribonuclease A Superfamily in Humans: Canonical RNases as the Buttress of Innate Immunity

In humans, the ribonuclease A (RNase A) superfamily contains eight different members that have RNase activities, and all of these members are encoded on chromosome 14. The proteins are secreted by a large variety of different tissues and cells; however, a comprehensive understanding of these proteins’ physiological roles is lacking. Different biological effects can be attributed to each protein, including antiviral, antibacterial and antifungal activities as well as cytotoxic effects against host cells and parasites. Different immunomodulatory effects have also been demonstrated. This review summarizes the available data on the human RNase A superfamily and illustrates the significant role of the eight canonical RNases in inflammation and the host defence system against infections.     

Influencing the sustainability of washing behavior by using motivational interviewing

Manufacturers of household appliances and detergents have made great and successful strides in recent years to meet the challenge of sustainable development. But it is primarily the consumer who, through her/his individual use of household appliances, has an essential impact on the energy and resource consumption of a household, particularly in the area of textile care. Considerable savings potentials have been identified by a number of studies. But which methods are suitable for convincing consumers to practice more sustainable washing behavior? In addition to the frequently used informational brochures, some authors have suggested using alternative channels and forms of communication. One of the options is motivational interviewing, which has so far mostly been used in the medical area but seems to be suited also for other applications. This study applies motivational interviewing to the field of household technology and examines if interviews which are based on this technique can influence aspects of the washing behavior that are strongly related to sustainability. For this purpose, the participants’ washing behavior was recorded in a washing diary before and after the intervention, and sustainability was operationalized and compared using several evaluated aspects. The data gathered show that the sustainability of washing behavior in the group of subjects studied increased after an intervention by means of motivational interviewing. It also showed that the necessity to increase the sustainability of washing behavior is still an issue. Personalized communication designed specifically for the target group, such as in motivational interviewing, seems to be suitable for this purpose and might also be used in the future by actors advising consumers.     

Improving the laser cutting process design by machine learning techniques

In the field of manufacturing engineering, process designers conduct numerical simulation experiments to observe the impact of varying input parameters on certain outputs of the production process. The disadvantage of these simulations is that they are very time consuming and their results do not help to fully understand the underlying process. For instance, a common problem in planning processes is the choice of an appropriate machine parameter set that results in desirable process outputs. One way to overcome this problem is to use data mining techniques that extract previously unknown but valuable knowledge from simulation results. This paper presents a hybrid machine learning approach for applying clustering and classification techniques in a laser cutting planning process. In a first step, a clustering algorithm is used to divide large parts of the simulation data into groups of similar performance values and select those groups that are of major interest (e.g. high cut quality results). Next, classification trees are used to identify regions in the multidimensional parameter space that are related to the found groups. The evaluation shows that the models accurately identify multidimensional relationships between the input parameters and the output values of the process. In addition to that, a combination of appropriate visualization techniques for clustering with interpretable classification trees allows designers to gain valuable insights into the laser cutting process with the aim of optimizing it through visual exploration.