Fear expression is suppressed by tyrosine administration

Animal studies have demonstrated that catecholamines regulate several aspects of fear conditioning. In humans, however, pharmacological manipulations of the catecholaminergic system have been scarce, and their primary focus has been to interfering with catecholaminergic activity after fear acquisition or expression had taken place, using L-Dopa, primarily, as catecholaminergic precursor. Here, we sought to determine if putative increases in presynaptic dopamine and norepinephrine by tyrosine administered before conditioning could affect fear expression. Electrodermal activity (EDA) of 46 healthy participants (24 placebo, 22 tyrosine) was measured in a fear instructed task. Results showed that tyrosine abolished fear expression compared to placebo. Importantly, tyrosine did not affect EDA responses to the aversive stimulus (UCS) or alter participants' mood. Therefore, the effect of tyrosine on fear expression cannot be attributed to these factors. Taken together, these findings provide evidence that the catecholaminergic system influences fear expression in humans

Times have changed. Using a Pictorial Smartphone App to Collect Time Use Data in Rural Zambia.

One challenge of collecting socioeconomic data, such as data on time use, is recall biases. While time use researchers have continuously developed new methods to make data collection more accurate and easy, these methods are difficult to use in developing countries where study participants may have low literacy levels and no clock -based concepts of time. To contribute to the closing of this research gap, we developed a picture-based smartphone-app called Time-Tracker that allows the recording of data in real time to avoid recall biases. We pilot-tested the app in rural Zambia, collecting 2790 data days. In this paper, we compare the data recorded with the app to data collected with 24-hours-recall-questions. The results confirm the literature on recall biases, suggesting that using the app leads to valid results. We conclude that smartphone-apps using visual tools provide new opportunities for researchers collecting socioeconomic data in developing countries. Acknowledgement : We are especially grateful to all the farm families participating in the study. We are also grateful for the financial support from the Program of Accompanying Research for Agricultural Innovation , which is funded by the German Federal Ministry of Economic Cooperation and Development

Web scaling frameworks:A novel class of frameworks for scalable web services in cloud environments

The social web and huge growth of mobile smart devices dramatically increases the performance requirements for web services. State-of-the-art Web Application Frameworks (WAFs) do not offer complete scaling concepts with automatic resource-provisioning, elastic caching or guaranteed maximum response times. These functionalities, however, are supported by cloud computing and needed to scale an application to its demands. Components like proxies, load-balancers, distributed caches, queuing and messaging systems have been around for a long time and in each field relevant research exists. Nevertheless, to create a scalable web service it is seldom enough to deploy only one component. In this work we propose to combine those complementary components to a predictable, composed system. The proposed solution introduces a novel class of web frameworks called Web Scaling Frameworks (WSFs) that take over the scaling. The proposed mathematical model allows a universally applicable prediction of performance in the single-machine- and multi-machine scope. A prototypical implementation is created to empirically validate the mathematical model and demonstrates both the feasibility and increase of performance of a WSF. The results show that the application of a WSF can triple the requests handling capability of a single machine and additionally reduce the number of total machines by 44%