Evaluation of a web-based application versus conventional instruction in the undergraduate curriculum of fixed prosthodontics

The present study aims to investigate the implications of web-based delivery of identical learning content for time efficiency and students' performance, as compared to conventional textbook resources.

The InterHerz project--a web-based psychological treatment for cardiac patients with depression: study protocol of a randomized controlled trial

Patients with heart disease often suffer from difficulties in psychological adaptation during cardiac rehabilitation. Mood disorders such as depression are known to be highly prevalent in cardiac patients and to have a negative impact on the progression of coronary heart disease. However, cardiac patients have difficulties to get psychological treatments due to low availability and motivational difficulties. Web-based interventions have been proven to be effective in treating depressive symptoms. Deprexis is a promising web-based psychological treatment which was devised for depressed patients. The aim of the study InterHerz is to examine if Deprexis is an effective psychological treatment to reduce stress and depression in cardiac patients.

Symptomatic management of fever by Swiss board-certified pediatricians: results from a cross-sectional, Web-based survey

Symptomatic management is often all that is recommended in children with fever. To date, only 2 nationwide surveys of pediatricians regarding their attitudes toward fever have been published.

Dynamic Optimization of SLA-Based Services Scaling Rules

Current advanced cloud infrastructure management solutions allow scheduling actions for dynamically changing the number of running virtual machines (VMs). This approach, however, does not guarantee that the scheduled number of VMs will properly handle the actual user generated workload, especially if the user utilization patterns will change. We propose using a dynamically generated scaling model for the VMs containing the services of the distributed applications, which is able to react to the variations in the number of application users. We answer the following question: How to dynamically decide how many services of each type are needed in order to handle a larger workload within the same time constraints? We describe a mechanism for dynamically composing the SLAs for controlling the scaling of distributed services by combining data analysis mechanisms with application benchmarking using multiple VM configurations. Based on processing of multiple application benchmarks generated data sets we discover a set of service monitoring metrics able to predict critical Service Level Agreement (SLA) parameters. By combining this set of predictor metrics with a heuristic for selecting the appropriate scaling-out paths for the services of distributed applications, we show how SLA scaling rules can be inferred and then used for controlling the runtime scale-in and scale-out of distributed services. We validate our architecture and models by performing scaling experiments with a distributed application representative for the enterprise class of information systems. We show how dynamically generated SLAs can be successfully used for controlling the management of distributed services scaling.