Tune in to your emotions: a robust personalized affective music player

The emotional power of music is exploited in a personalized affective music player (AMP) that selects music for mood enhancement. A biosignal approach is used to measure listeners’ personal emotional reactions to their own music as input for affective user models. Regression and kernel density estimation are applied to model the physiological changes the music elicits. Using these models, personalized music selections based on an affective goal state can be made. The AMP was validated in real-world trials over the course of several weeks. Results show that our models can cope with noisy situations and handle large inter-individual differences in the music domain. The AMP augments music listening where its techniques enable automated affect guidance. Our approach provides valuable insights for affective computing and user modeling, for which the AMP is a suitable carrier application

Optical properties of MgH2 measured in situ in a novel gas cell for ellipsometry/spectrophotometry

The dielectric properties of alpha-MgH2 are investigated in the photon energy range between 1 and 6.5 eV. For this purpose, a novel sample configuration and experimental setup are developed that allow both optical transmission and ellipsometric measurements of a transparent thin film in equilibrium with hydrogen. We show that alpha-MgH2 is a transparent, colour neutral insulator with a band gap of 5.6 +/- 0.1 eV. It has an intrinsic transparency of about 80% over the whole visible spectrum. The dielectric function found in this work confirms very recent band structure calculations using the GW approximation by Alford and Chou [J.A. Alford and M.Y. Chou (unpublished)]. As Pd is used as a cap layer we report also the optical properties of PdHx thin films.Comment: REVTeX4, 15 pages, 12 figures, 5 table

Magnetic fields in cosmic particle acceleration sources

We review here some magnetic phenomena in astrophysical particle accelerators associated with collisionless shocks in supernova remnants, radio galaxies and clusters of galaxies. A specific feature is that the accelerated particles can play an important role in magnetic field evolution in the objects. We discuss a number of CR-driven, magnetic field amplification processes that are likely to operate when diffusive shock acceleration (DSA) becomes efficient and nonlinear. The turbulent magnetic fields produced by these processes determine the maximum energies of accelerated particles and result in specific features in the observed photon radiation of the sources. Equally important, magnetic field amplification by the CR currents and pressure anisotropies may affect the shocked gas temperatures and compression, both in the shock precursor and in the downstream flow, if the shock is an efficient CR accelerator. Strong fluctuations of the magnetic field on scales above the radiation formation length in the shock vicinity result in intermittent structures observable in synchrotron emission images. Resonant and non-resonant CR streaming instabilities in the shock precursor can generate mesoscale magnetic fields with scale-sizes comparable to supernova remnants and even superbubbles. This opens the possibility that magnetic fields in the earliest galaxies were produced by the first generation Population III supernova remnants and by clustered supernovae in star forming regions.Comment: 30 pages, Space Science Review

Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

BACKGROUND: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. METHODS: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. RESULTS: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). CONCLUSIONS: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics

Eco-evolutionary dynamics on deformable fitness landscapes

Conventional approaches to modelling ecological dynamics often do not include evolutionary changes in the genetic makeup of component species and, conversely, conventional approaches to modelling evolutionary changes in the genetic makeup of a population often do not include ecological dynamics. But recently there has been considerable interest in understanding the interaction of evolutionary and ecological dynamics as coupled processes. However, in the context of complex multi-species ecosytems, especially where ecological and evolutionary timescales are similar, it is difficult to identify general organising principles that help us understand the structure and behaviour of complex ecosystems. Here we introduce a simple abstraction of coevolutionary interactions in a multi-species ecosystem. We model non-trophic ecological interactions based on a continuous but low-dimensional trait/niche space, where the location of each species in trait space affects the overlap of its resource utilisation with that of other species. The local depletion of available resources creates, in effect, a deformable fitness landscape that governs how the evolution of one species affects the selective pressures on other species. This enables us to study the coevolution of ecological interactions in an intuitive and easily visualisable manner. We observe that this model can exhibit either of the two behavioural modes discussed in the literature; namely, evolutionary stasis or Red Queen dynamics, i.e., continued evolutionary change. We find that which of these modes is observed depends on the lag or latency between the movement of a species in trait space and its effect on available resources. Specifically, if ecological change is nearly instantaneous compared to evolutionary change, stasis results; but conversely, if evolutionary timescales are closer to ecological timescales, such that resource depletion is not instantaneous on evolutionary timescales, then Red Queen dynamics result. We also observe that in the stasis mode, the overall utilisation of resources by the ecosystem is relatively efficient, with diverse species utilising different niches, whereas in the Red Queen mode the organisation of the ecosystem is such that species tend to clump together competing for overlapping resources. These models thereby suggest some basic conditions that influence the organisation of inter-species interactions and the balance of individual and collective adaptation in ecosystems, and likewise they also suggest factors that might be useful in engineering artificial coevolution

What Drives Fitness Apps Usage? An Empirical Evaluation

Part 3: Creating Value through ApplicationsInternational audienceThe increased health problems associated with lack of physical activity is of great concern around the world. Mobile phone based fitness applications appear to be a cost effective promising solution for this problem. The aim of this study is to develop a research model that can broaden understanding of the factors that influence the user acceptance of mobile fitness apps. Drawing from Unified Theory of Acceptance and Use of Technology (UTAUT) and Elaboration Likelihood Model (ELM), we conceptualize the antecedents and moderating factors of fitness app use. We validate our model using field survey. Implications for research and practice are discussed

Recurrence of nephrotic syndrome following kidney transplantation is associated with initial native kidney biopsy findings

Background and objectives: Steroid-resistant nephrotic syndrome (SRNS) due to focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) is a leading cause of end-stage kidney disease in children. Recurrence of primary disease following transplantation is a major cause of allograft loss. The clinical determinants of disease recurrence are not completely known. Our objectives were to determine risk factors for recurrence of FSGS/MCD following kidney transplantation and factors that predict response to immunosuppression following recurrence. Methods: Multicenter study of pediatric patients with kidney transplants performed for ESKD due to SRNS between 1/2006 and 12/2015. Demographics, clinical course, and biopsy data were collected. Patients with primary-SRNS (PSRNS) were defined as those initially resistant to corticosteroid therapy at diagnosis, and patients with late-SRNS (LSRNS) as those initially responsive to steroids who subsequently developed steroid resistance. We performed logistic regression to determine risk factors associated with nephrotic syndrome (NS) recurrence. Results: We analyzed 158 patients; 64 (41%) had recurrence of NS in their renal allograft. Disease recurrence occurred in 78% of patients with LSRNS compared to 39% of those with PSRNS. Patients with MCD on initial native kidney biopsy had a 76% recurrence rate compared with a 40% recurrence rate in those with FSGS. Multivariable analysis showed that MCD histology (OR; 95% CI 5.6; 1.3–23.7) compared to FSGS predicted disease recurrence. Conclusions: Pediatric patients with MCD and LSRNS are at higher risk of disease recurrence following kidney transplantation. These findings may be useful for designing studies to test strategies for preventing recurrence

Regional variability in peatland burning at mid- to high-latitudes during the Holocene

Acknowledgements This work developed from the PAGES (Past Global Changes) C-PEAT (Carbon in Peat on EArth through Time) working group. PAGES has been supported by the US National Science Foundation, Swiss National Science Foundation, Swiss Academy of Sciences and Chinese Academy of Sciences. We acknowledge the following financial support: UK Natural Environment Research Council Training Grants NE/L002574/1 (T.G.S.) and NE/S007458/1 (R.E.F.); Dutch Foundation for the Conservation of Irish Bogs, Quaternary Research Association and Leverhulme Trust RPG-2021-354 (G.T.S); the Academy of Finland (M.V); PAI/SIA 80002 and FONDECYT Iniciación 11220705 - ANID, Chile (C.A.M.); R20F0002 (PATSER) ANID Chile (R.D.M.); Swedish Strategic Research Area (SRA) MERGE (ModElling the Regional and Global Earth system) (M.J.G.); Polish National Science Centre Grant number NCN 2018/29/B/ST10/00120 (K.A.); Russian Science Foundation Grant No. 19-14-00102 (Y.A.M.); University of Latvia Grant No. AAp2016/B041/Zd2016/AZ03 and the Estonian Science Council grant PRG323 (TrackLag) (N.S. and A.M.); U.S. Geological Survey Land Change Science/Climate Research & Development Program (M.J., L.A., and D.W.); German Research Foundation (DFG), grant MA 8083/2-1 (P.M.) and grant BL 563/19-1 (K.H.K.); German Academic Exchange Service (DAAD), grant no. 57044554, Faculty of Geosciences, University of Münster, and Bavarian University Centre for Latin America (BAYLAT) (K.H.K). Records from the Global Charcoal Database supplemented this work and therefore we would like to thank the contributors and managers of this open-source resource. We also thank Annica Greisman, Jennifer Shiller, Fredrik Olsson and Simon van Bellen for contributing charcoal data to our analyses. Any use of trade, firm, or product name is for descriptive purposes only and does not imply endorsement by the U.S. Government.Peer reviewedPostprin