Risk attitude and risk behavior: Comparing Thailand and Vietnam

Are responses to a simple survey item sufficiently reliable in eliciting risk attitudes? Our angle in examining reliability is to conduct comparative research across Thailand and Vietnam. We find, first, that the survey item is informative about individual risk attitude because it is plausibly related to socio-demographic characteristics (including vulnerability), it is experimentally validated and has some predictive power. Second, however, we find major differences between both countries: whereas explained variances of regressions are tentatively higher in Vietnam, the predictive value of the survey item is much lower than in Thailand. Therefore, the survey item cannot be implemented across countries in an unreflected way. --risk attitude,socio-economic survey,household behavior,field experiment

Unusual Differential Diagnosis of Upper Abdominal Pain

We here present an interesting unusual case of upper abdominal pain. The patient was a 38-year-old man, who was admitted to our hospital complaining of right upper quadrant pain caused by a toothpick that perforated the anterior gastric wall and penetrated segment I of the liver. After endoscopic removal and an initially uneventful course, computed tomography revealed a perigastric abscess that was treated by repeated gastroscopic rinsing via an endoscopically placed catheter. After another three uneventful weeks, a liver abscess with minor tendency to constrict the portal vein was diagnosed, and a segment I liver resection together with abscess drainage was performed. The peculiarity of this case is the rarity of toothpick ingestion and gastric perforation in a young and healthy white Caucasian followed by development of a liver abscess after primary uneventful endoscopic removal. In light of this case, gastric perforation due to ingested foreign bodies such as toothpicks can be considered a rare cause of upper abdominal pain

CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks

General-purpose robots coexisting with humans in their environment must learn to relate human language to their perceptions and actions to be useful in a range of daily tasks. Moreover, they need to acquire a diverse repertoire of general-purpose skills that allow composing long-horizon tasks by following unconstrained language instructions. In this paper, we present CALVIN (Composing Actions from Language and Vision), an open-source simulated benchmark to learn long-horizon language-conditioned tasks. Our aim is to make it possible to develop agents that can solve many robotic manipulation tasks over a long horizon, from onboard sensors, and specified only via human language. CALVIN tasks are more complex in terms of sequence length, action space, and language than existing vision-and-language task datasets and supports flexible specification of sensor suites. We evaluate the agents in zero-shot to novel language instructions and to novel environments and objects. We show that a baseline model based on multi-context imitation learning performs poorly on CALVIN, suggesting that there is significant room for developing innovative agents that learn to relate human language to their world models with this benchmark.Comment: Accepted for publication at IEEE Robotics and Automation Letters (RAL). Code, models and dataset available at http://calvin.cs.uni-freiburg.d

Development of an Architecture for a Tele-Medicine-Based Longterm Monitoring System

Every day gigantic amounts of digital data are produced by billions of devices around the globe. Using this kind of data and develop applications of unlimited possibilities have created the Internet of Things (IoT) idea. Furthermore, wearable devices have taken up the recognition not only for private users, but also medical device producers and start-up companies. They have realized the potential of wearables in medical applications and their importance for the future of tele-medical systems, when being combined with an IoT based architecture. Despite the development of recent tele medicine platforms, none has used printed electronics to obtain physiological signals. This thesis will provide a description of an architecture, that not only uses an IoT application as backbone, but also a hybrid printed electronics design for ECG and Bioimpedance Pneumography measurements. The recorded bio-signals are transferred via Bluetooth Low Energy to a mobile gateway and then onto a server. On the server the data will be processed in order to obtain features of each signal that provide significant information about the patient’s health. Finally this data is stored in a backup system and can be viewed through a graphical user interface. As this thesis is rather a literature review than an experimental work, there will be no methods segment. An extensive background with the state-of-the-art technologies will be provided. The description of the architecture, shows that all the principal layers of an IoT application are met. Issues that arise with the usage of these systems are critically evaluated. This is the basis for researchers in the DISSE (DISappering SEnsors) project, in order to enable them to see the overall picture around their work within the project

Predicting the influence of a p2-symmetric substrate on molecular self-organization with an interaction-site model

An interaction-site model can a priori predict molecular selforganisation on a new substrate in Monte Carlo simulations. This is experimentally confirmed with scanning tunnelling microscopy on Fre´chet dendrons of a pentacontane template. Local and global ordering motifs, inclusion molecules and a rotated unit cell are correctly predicted

A summary

Coinciding with the Open Access Week 2010 we publish a study on the perceptions and usage trends amongst CSIC scientific community as regards Open Access in general and CSIC institutional repository in particular.Peer reviewe