PREDICTING THE INDIVIDUAL MOOD LEVEL BASED ON DIARY DATA

Understanding mood changes of individuals with depressive disorders is crucial in order to guide personalized therapeutic interventions. Based on diary data, in which clients of an online depression treatment report their activities as free text, we categorize these activities and predict the mood level of clients. We apply a bag-of-words text-mining approach for activity categorization and explore recurrent neuronal networks to support this task. Using the identified activities, we develop partial ordered logit models with varying levels of heterogeneity among clients to predict their mood. We estimate the parameters of these models by employing Markov Chain Monte Carlo techniques and compare the models regarding their predictive performance. Therefore, by combining text-mining and Bayesian estimation techniques, we apply a two-stage analysis approach in order to reveal relationships between various activity categories and the individual mood level. Our findings indicate that the mood level is influenced negatively when participants report about sickness or rumination. Social activities have a positive influence on the mood. By understanding the influences of daily activities on the individual mood level, we hope to improve the efficacy of online behavior therapy, provide support in the context of clinical decision-making, and contribute to the development of personalized interventions

Evaluation of a temporal causal model for predicting the mood of clients in an online therapy

Background Self-reported client assessments during online treatments enable the development of statistical models for the prediction of client improvement and symptom development. Evaluation of these models is mandatory to ensure their validity. Methods For this purpose, we suggest besides a model evaluation based on study data the use of a simulation analysis. The simulation analysis provides insight into the model performance and enables to analyse reasons for a low predictive accuracy. In this study, we evaluate a temporal causal model (TCM) and show that it does not provide reliable predictions of clients' future mood levels. Results Based on the simulation analysis we investigate the potential reasons for the low predictive performance, for example, noisy measurements and sampling frequency. We conclude that the analysed TCM in its current form is not sufficient to describe the underlying psychological processes. Conclusions The results demonstrate the importance of model evaluation and the benefit of a simulation analysis. The current manuscript provides practical guidance for conducting model evaluation including simulation analysis

Amplitude enhancements in Antarctic MF radar echoes

Enhancements in the amplitude of returns from a medium-frequency (MF) radar at Davis, Antarctica, have been identified and their potential use as a measure of polar mesosphere summer echoes (PMSE) has been explored. A method for finding these enhancements has been applied to data spanning the period from mid-1995 to the end of 1997. The character of these enhancements on short and long timescales has been studied, and factors that may affect their detection have been considered. It has been found that they are short-lived (2 min or less being most common) and largely limited to the months around summer. Apart from describing the character of these amplitude enhancements, this study illustrates the potential pitfalls associated with identifying a proxy measure of PMSE.D. J. Murphy, R. A. Vincenthttp://cat.inist.fr/?aModele=afficheN&cpsidt=85383

Unveiling Cosmic Dawn: the synergetic role of space and ground-based telescopes

Large scale structure and cosmolog

Long-term variability of mean winds in the mesosphere and lower thermosphere at low latitudes

Long-term variations of monthly mean zonal and meridional winds in the Mesosphere and Lower Thermosphere (MLT) at low-latitudes are analyzed using four medium frequency (MF) radars and three meteor radars located in the Asia-Oceania region. Radar data taken at close-by latitudes are appended to construct long-term data sets. With this, we have long-term data from five distinct latitudes within ±22° (viz., 22°N, ∼9°N, 0–2°N, 6–7°S and 21°S). The data length varies at different latitudes and spans a maximum of two decades during 1990–2010. The zonal winds show semiannual oscillation (SAO) at all locations with westward (eastward) winds during equinoxes (solstices). The month height pattern of SAO is similar within ±9° and is different at ±22°. The westward winds in the March equinox were enhanced every two or three years during 1990–2002. We define this phenomenon as Mesospheric Quasi-Biennial Enhancement (MQBE). Such signature is not clear after 2002. The meridional winds show annual oscillation (AO), with northward and southward winds during the December and June solstices, respectively. However, the timing at which the wind direction changes does not coincide at all latitudes. The amplitude of the AO is enhanced after 2004 and 2008 at ∼9°N and ∼7°S, respectively. Orthogonal components of SAO and AO are detected with persistent phase relation, which suggests that the zonal and meridional winds are coupled. The meridional winds show long-term trends at latitudes of ∼9°N and ∼6–7°S, but not at other latitudes. The zonal winds do not show significant long-term trends.N. Venkateswara Rao, T. Tsuda, D. M. Riggin, S. Gurubaran, I. M. Reid, and R. A. Vincen

Bacterial Leaf Symbiosis in Angiosperms: Host Specificity without Co-Speciation

Bacterial leaf symbiosis is a unique and intimate interaction between bacteria and flowering plants, in which endosymbionts are organized in specialized leaf structures. Previously, bacterial leaf symbiosis has been described as a cyclic and obligate interaction in which the endosymbionts are vertically transmitted between plant generations and lack autonomous growth. Theoretically this allows for co-speciation between leaf nodulated plants and their endosymbionts. We sequenced the nodulated Burkholderia endosymbionts of 54 plant species from known leaf nodulated angiosperm genera, i.e. Ardisia, Pavetta, Psychotria and Sericanthe. Phylogenetic reconstruction of bacterial leaf symbionts and closely related free-living bacteria indicates the occurrence of multiple horizontal transfers of bacteria from the environment to leaf nodulated plant species. This rejects the hypothesis of a long co-speciation process between the bacterial endosymbionts and their host plants. Our results indicate a recent evolutionary process towards a stable and host specific interaction confirming the proposed maternal transmission mode of the endosymbionts through the seeds. Divergence estimates provide evidence for a relatively recent origin of bacterial leaf symbiosis, dating back to the Miocene (5–23 Mya). This geological epoch was characterized by cool and arid conditions, which may have triggered the origin of bacterial leaf symbiosis

Search for displaced vertices arising from decays of new heavy particles in 7 TeV pp collisions at ATLAS

We present the results of a search for new, heavy particles that decay at a significant distance from their production point into a final state containing charged hadrons in association with a high-momentum muon. The search is conducted in a pp-collision data sample with a center-of-mass energy of 7 TeV and an integrated luminosity of 33 pb^-1 collected in 2010 by the ATLAS detector operating at the Large Hadron Collider. Production of such particles is expected in various scenarios of physics beyond the standard model. We observe no signal and place limits on the production cross-section of supersymmetric particles in an R-parity-violating scenario as a function of the neutralino lifetime. Limits are presented for different squark and neutralino masses, enabling extension of the limits to a variety of other models.Comment: 8 pages plus author list (20 pages total), 8 figures, 1 table, final version to appear in Physics Letters

Standalone vertex finding in the ATLAS muon spectrometer

A dedicated reconstruction algorithm to find decay vertices in the ATLAS muon spectrometer is presented. The algorithm searches the region just upstream of or inside the muon spectrometer volume for multi-particle vertices that originate from the decay of particles with long decay paths. The performance of the algorithm is evaluated using both a sample of simulated Higgs boson events, in which the Higgs boson decays to long-lived neutral particles that in turn decay to bbar b final states, and pp collision data at √s = 7 TeV collected with the ATLAS detector at the LHC during 2011

Measurements of Higgs boson production and couplings in diboson final states with the ATLAS detector at the LHC

Measurements are presented of production properties and couplings of the recently discovered Higgs boson using the decays into boson pairs, H →γ γ, H → Z Z∗ →4l and H →W W∗ →lνlν. The results are based on the complete pp collision data sample recorded by the ATLAS experiment at the CERN Large Hadron Collider at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV, corresponding to an integrated luminosity of about 25 fb−1. Evidence for Higgs boson production through vector-boson fusion is reported. Results of combined fits probing Higgs boson couplings to fermions and bosons, as well as anomalous contributions to loop-induced production and decay modes, are presented. All measurements are consistent with expectations for the Standard Model Higgs boson