Initial assessment of reliability of a self-administered web-based neuropsychological test battery

AbstractIntroductionWeb-based neuropsychological testing can be an important tool in meeting the increasing demands for neuropsychological assessment in the clinic and in large research studies. The primary aim of this study was to investigate practice effects and reliability of self-administered web-based neuropsychological tests in Memoro. Due to lack of consistent analysis and reporting of reliability in the literature, especially intraclass correlation coefficients (ICC), we highlight how using different ICC measures results in different estimates of reliability.Method61 (31 females) participants (mean age 53.3 years) completed the Memoro tests twice with a median of 14 days between testing.ResultsPractice effects were detected for all cognitive measures (d = 0.32–0.61), most pronounced for memory measures. Reliability estimated using two-way random effects single measure absolute agreement ICC(2,1) were between 0.55 and 0.74. Two-way mixed effects average measure consistency ICC(3,2), ranged from 0.79 to 0.89. Reliability was highest for the processing speed task and lower for the memory tasks.ConclusionsMemoro tests had test-retest reliability similar to that of traditional, computerized and web-based test batteries used clinically and in research. It is important to carefully choose and specify the ICC implemented, as ICC(2,1) and ICC(3,2) give different results and reflect reliability of different measures

Effect of green manure management on barley yields and N-recovery

Mulching of GM herbage can increase cereal yields compared to its removal. However, the same GM herbage removed for biogas production will provide biogas residue that can be used as spring fertilizer to cereals. This will improve N-recovery and reduce the risk for N pollution. Cooperation with existing biogas plants will be more efficient, as building small biogas plants are costly and challenging

Exploiting Evolution for an Adaptive Drift-Robust Classifier in Chemical Sensing

Gas chemical sensors are strongly affected by drift, i.e., changes in sensors' response with time, that may turn statistical models commonly used for classification completely useless after a period of time. This paper presents a new classifier that embeds an adaptive stage able to reduce drift effects. The proposed system exploits a state-of-the-art evolutionary strategy to iteratively tweak the coefficients of a linear transformation able to transparently transform raw measures in order to mitigate the negative effects of the drift. The system operates continuously. The optimal correction strategy is learnt without a-priori models or other hypothesis on the behavior of physical-chemical sensors. Experimental results demonstrate the efficacy of the approach on a real problem

Kinect Depth Sensor Evaluation for Computer Vision Applications

This technical report describes our evaluation of the Kinect depth sensor by Microsoft for Computer Vision applications. The depth sensor is able to return images like an ordinary camera, but instead of color, each pixel value represents the distance to the point. As such, the sensor can be seen as a range- or 3D-camera. We have used the sensor in several different computer vision projects and this document collects our experiences with the sensor. We are only focusing on the depth sensing capabilities of the sensor since this is the real novelty of the product in relation to computer vision. The basic technique of the depth sensor is to emit an infrared light pattern (with an IR laser diode) and calculate depth from the reflection of the light at different positions (using a traditional IR sensitive camera). In this report, we perform an extensive evaluation of the depth sensor and investigate issues such as 3D resolution and precision, structural noise, multi-cam setups and transient response of the sensor. The purpose is to give the reader a well-founded background to choose whether or not the Kinect sensor is applicable to a specific problem

Channel diffusion of sodium in a silicate glass

We use classical molecular dynamics simulations to study the dynamics of sodium atoms in amorphous Na$_2$O-4SiO$_2$. We find that the sodium trajectories form a well connected network of pockets and channels. Inside these channels the motion of the atoms is not cooperative but rather given by independent thermally activated hops of individual atoms between the pockets. By determining the probability that an atom returns to a given starting site, we show that such events are not important for the dynamics of this system.Comment: 10 pages of Latex, 5 figures, one figure added, text expande