Strategies and challenges to facilitate situated learning in virtual worlds post-Second Life

Virtual worlds can establish a stimulating environment to support a situated learning approach in which students simulate a task within a safe environment. While in previous years Second Life played a major role in providing such a virtual environment, there are now more and more alternative—often OpenSim-based—solutions deployed within the educational community. By drawing parallels to social networks, we discuss two aspects: how to link individually hosted virtual worlds together in order to implement context for immersion and how to identify and avoid “fake” avatars so people behind these avatars can be held accountable for their actions

A Comparative Study of ECG-derived Respiration in Ambulatory Monitoring using the Single-lead ECG.

Cardiorespiratory monitoring is crucial for the diagnosis and management of multiple conditions such as stress and sleep disorders. Therefore, the development of ambulatory systems providing continuous, comfortable, and inexpensive means for monitoring represents an important research topic. Several techniques have been proposed in the literature to derive respiratory information from the ECG signal. Ten methods to compute single-lead ECG-derived respiration (EDR) were compared under multiple conditions, including different recording systems, baseline wander, normal and abnormal breathing patterns, changes in breathing rate, noise, and artifacts. Respiratory rates, wave morphology, and cardiorespiratory information were derived from the ECG and compared to those extracted from a reference respiratory signal. Three datasets were considered for analysis, involving a total 59 482 one-min, single-lead ECG segments recorded from 156 subjects. The results indicate that the methods based on QRS slopes outperform the other methods. This result is particularly interesting since simplicity is crucial for the development of ECG-based ambulatory systems

The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity

BACKGROUND: Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity. METHODS: Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions. RESULTS: Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms. CONCLUSIONS: Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly

Cold-Induced Changes in the Protein Ubiquitin

Conformational changes are essential for protein-protein and protein-ligand recognition. Here we probed changes in the structure of the protein ubiquitin at low temperatures in supercooled water using NMR spectroscopy. We demonstrate that ubiquitin is well folded down to 263 K, although slight rearrangements in the hydrophobic core occur. However, amide proton chemical shifts show non-linear temperature dependence in supercooled solution and backbone hydrogen bonds become weaker in the region that is most prone to cold-denaturation. Our data suggest that the weakening of the hydrogen bonds in the β-sheet of ubiquitin might be one of the first events that occur during cold-denaturation of ubiquitin. Interestingly, the same region is strongly involved in ubiquitin-protein complexes suggesting that this part of ubiquitin more easily adjusts to conformational changes required for complex formation

Fully automated high-quality NMR structure determination of small 2H-enriched proteins

Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and sidechain resonance assignments, and weeks or even months of data collection and interpretation. Here we demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Our strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins. As an example, we demonstrate the determination of a high-quality 3D structure of a small 8 kDa protein, E. coli cold shock protein A (CspA), using <4 days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone RMSD value of 0.5 Å, an all atom RMSD value of 1.2 Å to the crystal structure for well-defined regions, and RMSD value of 1.1 Å to crystal structure for core, non-solvent exposed sidechain atoms. Cross validation of the structure with 15N- and 13C-edited NOESY data obtained with a perdeuterated 15N, 13C-enriched 13CH3 methyl protonated CspA sample confirms that essentially all of these independently-interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR

Underground Phased Arrays and Beamforming Applications

This chapter presents a framework for adaptive beamforming in underground communication. The wireless propagation is thoroughly analyzed to develop a model using the soil moisture as an input parameter to provide feedback mechanism while enhancing the system performance. The working of array element in the soil is analyzed. Moreover, the effect of soil texture and soil moisture on the resonant frequency and return loss is studied in detail. The wave refraction from the soil–air interface highly degrades the performance of the system. Furthermore, to beam steering is done to achieve high gain for lateral component improving the UG communication. The angle enhancing the lateral wave depends upon dielectric properties and usually ranges from 0∘ to 16∘. These dielectric properties change with the change in soil moisture and soil texture. It is shown from the experiments that optimal UG lateral angle is high at lower soil moisture readings and decreases with decrease in soil moisture. A planar structure of antenna array and different techniques for optimization are proposed for enhanced soil moisture adaptive beamforming. UG channel impulse response is studied from the beamforming aspect to identify the components of EM waves propagating through the soil. An optimum steering method for beamforming is presented which adapts to the changing values of soil moisture. Finally, the limitations of UG beamforming are presented along with the motivation to use it

Delivered dose quantification in prostate radiotherapy using online 3D cine imaging and treatment log files on a combined 1.5T magnetic resonance imaging and linear accelerator system

Background and purpose: Monitoring the intrafraction motion and its impact on the planned dose distribution is of crucial importance in radiotherapy. In this work we quantify the delivered dose for the first prostate patients treated on a combined 1.5T Magnetic Resonance Imaging (MRI) and linear accelerator system in our clinic based on online 3D cine-MR and treatment log files. Materials and methods: A prostate intrafraction motion trace was obtained with a soft-tissue based rigid registration method with six degrees of freedom from 3D cine-MR dynamics with a temporal resolution of 8.5–16.9 s. For each fraction, all dynamics were also registered to the daily MR image used during the online treatment planning, enabling the mapping to this reference point. Moreover, each fraction's treatment log file was used to extract the timestamped machine parameters during delivery and assign it to the appropriate dynamic volume. These partial plans to dynamic volume combinations were calculated and summed to yield the delivered fraction dose. The planned and delivered dose distributions were compared among all patients for a total of 100 fractions. Results: The clinical target volume underwent on average a decrease of 2.2% ± 2.9% in terms of D99% coverage while bladder V62Gy was increased by 1.6% ± 2.3% and rectum V62Gy decreased by 0.2% ± 2.2%. Conclusions: The first MR-linac dose reconstruction results based on prostate tracking from intrafraction 3D cine-MR and treatment log files are presented. Such a pipeline is essential for online adaptation especially as we progress to MRI-guided extremely hypofractionated treatments