The role of ion exchange in the passivation of In Zn P nanocrystals with ZnS

We have investigated the chemical state of In(Zn)P/ZnS core/shell nanocrystals (NCs) for color conversion applications using hard X-ray absorption spectroscopy (XAS) and photoluminescence excitation (PLE). Analyses of the edge energies as well as the X-ray absorption fine structure (XAFS) reveal that the Zn(2+) ions from ZnS remain in the shell while the S(2−) ions penetrate into the core at an early stage of the ZnS deposition. It is further demonstrated that for short growth times, the ZnS shell coverage on the core was incomplete, whereas the coverage improved gradually as the shell deposition time increased. Together with evidence from PLE spectra, where there is a strong indication of the presence of P vacancies, this suggests that the core-shell interface in the In(Zn)P/ZnS NCs are subject to substantial atomic exchanges and detailed models for the shell structure beyond simple layer coverage are needed. This substantial atomic exchange is very likely to be the reason for the improved photoluminescence behavior of the core-shell particles compare to In(Zn)P-only NCs as S can passivate the NCs surfaces

A Continuous-Time Dynamic Factor Model for Intensive Longitudinal Data Arising from Mobile Health Studies

Intensive longitudinal data (ILD) collected in mobile health (mHealth) studies contain rich information on multiple outcomes measured frequently over time that have the potential to capture short-term and long-term dynamics. Motivated by an mHealth study of smoking cessation in which participants self-report the intensity of many emotions multiple times per day, we propose a dynamic factor model that summarizes the ILD as a low-dimensional, interpretable latent process. This model consists of two submodels: (i) a measurement submodel -- a factor model -- that summarizes the multivariate longitudinal outcome as lower-dimensional latent variables and (ii) a structural submodel -- an Ornstein-Uhlenbeck (OU) stochastic process -- that captures the temporal dynamics of the multivariate latent process in continuous time. We derive a closed-form likelihood for the marginal distribution of the outcome and the computationally-simpler sparse precision matrix for the OU process. We propose a block coordinate descent algorithm for estimation. Finally, we apply our method to the mHealth data to summarize the dynamics of 18 different emotions as two latent processes. These latent processes are interpreted by behavioral scientists as the psychological constructs of positive and negative affect and are key in understanding vulnerability to lapsing back to tobacco use among smokers attempting to quit.Comment: Main text is 19 pages with 4 figures and 1 table. Supporting material is 25 page

S_3 Symmetry and Neutrino Masses and Mixings

Based on a universal seesaw mass matrix model with three scalars \phi_i, and by assuming an S_3 flavor symmetry for the Yukawa interactions, the lepton masses and mixings are investigated systematically. In order to understand the observed neutrino mixing, the charged leptons (e, \mu, \tau) are regarded as the 3 elements (e_1, e_2, e_3) of S_3, while the neutrino mass-eigenstates are regarded as the irreducible representation (\nu_\eta, \nu_\sigma, \nu_\pi) of S_3, where (\nu_\pi, \nu_\eta) and \nu_\sigma are a doublet and a singlet, respectively, which are composed of the 3 elements (\nu_1, \nu_2, \nu_3) of S_3.Comment: 16 pages, no figure, version to appear in EPJ-

The Validity of MotionSense HRV in Estimating Sedentary Behavior and Physical Activity under Free-Living and Simulated Activity Settings.

MotionSense HRV is a wrist-worn accelerometery-based sensor that is paired with a smartphone and is thus capable of measuring the intensity, duration, and frequency of physical activity (PA). However, little information is available on the validity of the MotionSense HRV. Therefore, the purpose of this study was to assess the concurrent validity of the MotionSense HRV in estimating sedentary behavior (SED) and PA. A total of 20 healthy adults (age: 32.5 ± 15.1 years) wore the MotionSense HRV and ActiGraph GT9X accelerometer (GT9X) on their non-dominant wrist for seven consecutive days during free-living conditions. Raw acceleration data from the devices were summarized into average time (min/day) spent in SED and moderate-to-vigorous PA (MVPA). Additionally, using the Cosemed K5 indirect calorimetry system (K5) as a criterion measure, the validity of the MotionSense HRV was examined in simulated free-living conditions. Pearson correlations, mean absolute percent errors (MAPE), Bland-Altman (BA) plots, and equivalence tests were used to examine the validity of the MotionSense HRV against criterion measures. The correlations between the MotionSense HRV and GT9X were high and the MAPE were low for both the SED (r = 0.99, MAPE = 2.4%) and MVPA (r = 0.97, MAPE = 9.1%) estimates under free-living conditions. BA plots illustrated that there was no systematic bias between the MotionSense HRV and criterion measures. The estimates of SED and MVPA from the MotionSense HRV were significantly equivalent to those from the GT9X; the equivalence zones were set at 16.5% for SED and 29% for MVPA. The estimates of SED and PA from the MotionSense HRV were less comparable when compared with those from the K5. The MotionSense HRV yielded comparable estimates for SED and PA when compared with the GT9X accelerometer under free-living conditions. We confirmed the promising application of the MotionSense HRV for monitoring PA patterns for practical and research purposes

Tribimaximal Neutrino Mixing and a Relation Between Neutrino- and Charged Lepton-Mass Spectra

Brannen has recently pointed out that the observed charged lepton masses satisfy the relation m_e +m_\mu +m_\tau = {2/3} (\sqrt{m_e}+\sqrt{m_\mu}+\sqrt{m_\tau})^2, while the observed neutrino masses satisfy the relation m_{\nu 1} +m_{\nu 2} +m_{\nu 3} = {2/3} (-\sqrt{m_{\nu 1}}+\sqrt{m_{\nu 2}}+\sqrt{m_{\nu 3}})^2. It is discussed what neutrino Yukawa interaction form is favorable if we take the fact pointed out by Brannen seriously.Comment: 13 pages, presentation modifie

Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies

ObjectiveInsufficient engagement is a critical barrier impacting the utility of digital interventions and mobile health assessments. As a result, engagement itself is increasingly becoming a target of studies and interventions. The purpose of this study is to investigate the dynamics of engagement in mobile health data collection by exploring whether, how, and why response to digital self-report prompts change over time in smoking cessation studies.MethodData from two ecological momentary assessment (EMA) studies of smoking cessation among diverse smokers attempting to quit (N = 573) with a total of 65,974 digital self-report prompts. We operationalize engagement with self-reporting in term of prompts delivered and prompt response to capture both broad and more granular engagement in self-reporting, respectively. The data were analyzed to describe trends in prompt delivered and prompt response over time. Time-varying effect modeling (TVEM) was employed to investigate the time-varying effects of response to previous prompt and the average response rate on the likelihood of current prompt response.ResultsAlthough prompt response rates were relatively stable over days in both studies, the proportion of participants with prompts delivered declined steadily over time in one of the studies, indicating that over time, fewer participants charged the device and kept it turned on (necessary to receive at least one prompt per day). Among those who did receive prompts, response rates were relatively stable. In both studies, there is a significant, positive and stable relationship between response to previous prompt and the likelihood of response to current prompt throughout all days of the study. The relationship between the average response rate prior to current prompt and the likelihood of responding to the current prompt was also positive, and increasing with time.ConclusionOur study highlights the importance of integrating various indicators to measure engagement in digital self-reporting. Both average response rate and response to previous prompt were highly predictive of response to the next prompt across days in the study. Dynamic patterns of engagement in digital self-reporting can inform the design of new strategies to promote and optimize engagement in digital interventions and mobile health studies

PLASMA LEVEL OF FIBROBLAST GROWTH FACTOR 21 IS INDEPENDENTLY RELATED TO BLOOD PRESSURE

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Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data

Advances in digital technology have greatly increased the ease of collecting intensive longitudinal data (ILD) such as ecological momentary assessments (EMAs) in studies of behavior changes. Such data are typically multilevel (e.g., with repeated measures nested within individuals), and are inevitably characterized by some degrees of missingness. Previous studies have validated the utility of multiple imputation as a way to handle missing observations in ILD when the imputation model is properly specified to reflect time dependencies. In this study, we illustrate the importance of proper accommodation of multilevel ILD structures in performing multiple imputations, and compare the performance of a multilevel multiple imputation (multilevel MI) approach relative to other approaches that do not account for such structures in a Monte Carlo simulation study. Empirical EMA data from a tobacco cessation study are used to demonstrate the utility of the multilevel MI approach, and the implications of separating participant- and study-initiated EMAs in evaluating individuals’ affective dynamics and urge

Association of a rare variant of the TNFSF13B gene with susceptibility to Rheumatoid Arthritis and Systemic Lupus Erythematosus

Abstract: A rare variant (BAFF-var) of the tumor necrosis factor superfamily 13b (TNFSF13B) gene has been recently associated with multiple sclerosis (MS) and systemic lupus erythematosus (SLE). The aim of this study was to investigate the association between TNFSF13B BAFF-var and susceptibility to rheumatoid arthritis (RA) and replicate that association in SLE. 6,218 RA patients, 2,575 SLE patients and 4,403 healthy controls from three different countries were included in the study. TNFSF13B BAFF-var was genotyped using TaqMan allelic discrimination assay. PLINK software was used for statistical analyses. TNFSF13B BAFF-var was significantly associated with RA (p = 0.015, OR = 1.21, 95% CI = 1.03–1.41) in the Spanish cohort. A trend of association was observed in the Dutch (p = 0.115) and German (p = 0.228) RA cohorts. A meta-analysis of the three RA cohorts included in this study revealed a statistically significant association (p = 0.002, OR = 1.24, 95% CI = 1.10–1.38). In addition, TNFSF13B BAFF-var was significantly associated with SLE in the Spanish (p = 0.001, OR = 1.41, 95% CI = 1.14–1.74) and the German cohorts (p = 0.030, OR = 1.86, 95% CI = 1.05–3.28), with a statistically significant p-value obtained in the meta-analysis (p = 0.0002, OR = 1.46, 95% CI = 1.09–2.32). The results obtained confirm the known association of TNFSF13B BAFF-var with SLE and, for the first time, demonstrate that this variant contributes to susceptibility to RA.This work was supported by the following grants: P12-BIO-1395 from Consejería de Innovación, Ciencia y Tecnología, Junta de Andalucía (Spain), and the Cooperative Research Thematic Network (RETICS) program, RD16/0012/0004 (RIER), from Instituto de Salud Carlos III (ISCIII, Health Ministry, Madrid, Spain). DGS was supported by the Spanish Ministry of Economy and Competitiveness through the program FPI (SAF2015-66761-P)