Put Your Imperfections Behind You: Temporal Landmarks Spur Goal Initiation When They Signal New Beginnings

People often fail to muster the motivation needed to initiate goal pursuit. Across five laboratory experiments, we explored occasions when people naturally experience enhanced motivation to take actions that facilitate goal pursuit and why certain dates are more likely to spur goal initiation than others. We present causal evidence that emphasizing a temporal landmark denoting the beginning of a new time period increases people’s intentions to initiate goal pursuit. In addition, we propose and show that people’s strengthened motivation to begin pursuing their aspirations following such temporal landmarks originates in part from the psychological disassociation these landmarks induce from a person’s past, imperfect self

Removal Efficiencies in Full-scale Biotrickling Filters used to clean Pig House Exhaust Air

In this study, we tested the performance and perspectives of four full-scale biotrickling filters based on Leca® (Light Expanded Clay Aggregates), a mechanically stable, non-degradable filter media, known to absorb odorous compounds such as H2S and methanethiol. The four filters varied in: filter thickness, carrying media, and the presence of dust filters. Biological Leca® filters were found to be capable of reducing NH3, H2S and odour by up to 96%, 80% and 78%, respectively. Clogging was observed to occur after approximately 100 days, but the installation of a dust filter successfully eliminated this problem

The Biological Embedding of Early-life Adversity: Using Salivary Biomarkers to Examine the Influence of Maternal Psychological Well-being on Child Neuroendocrine-immune Functioning

Background: Neuroendocrine-immune (NEI) regulation is essential for maintaining health. Through repeated activation of the stress response, early-life adversity may lead to dysregulation of the NEI network and increase risk of inflammatory-related disease. Studying NEI functioning during childhood, however, has been limited by the need for biologic data, which has been largely restricted to blood-based measures. Objectives: Using salivary biomeasures of immune activity (cytokines) this study examined: 1) the nature and correlates of salivary cytokines in children; and 2) the role of early-life adversity in moderating child NEI functioning. Methods: Data were drawn from the Fetus to Five study, a laboratory-based study of mother-child pairs. Children participated in stress-inducing tasks and provided four saliva samples. Mothers completed a survey about child health, family sociodemographics, and maternal mental health. Saliva was assayed for four inflammatory cytokines (IL-1β, IL-6, IL-8, TNFα) and markers of autonomic nervous system (ANS) and hypothalamic-pituitary-adrenal (HPA) activity (alpha-amylase (sAA), cortisol). Multilevel mixed models examined relations between cytokines and child health and demographic factors, and associations with sAA and cortisol. Composite scores reflecting socioeconomic status (SES) and maternal distress were created for each child using factor analysis of SES and maternal psychological (depressive symptoms, anxiety, stress) variables. Multilevel mixed models for cortisol examined child cortisol-cytokine relations and interactions between maternal distress and cytokines on cortisol, adjusting for SES. Results: Cytokines were largely unrelated to health and demographic factors, but were associated with oral health measures. Among boys, cytokines were positively associated with sAA and inversely associated with cortisol. In the full sample, positive maternal distress-cytokine interactions on cortisol for IL-1β, IL-6 and TNFα indicated that as maternal distress increased, inverse cytokine-cortisol relations became weaker. These interactions were driven by significant interactions among girls. Conclusions: Salivary cytokines in children reflect oral immune processes. Relations between cytokines and markers of ANS and HPA activity in saliva, however, mirror those in serum, suggesting NEI functioning may be studied using salivary biomeasures. Among girls, regardless of SES, maternal distress was associated with less efficient regulation of child inflammatory activity by cortisol. This desensitization may increase inflammatory-related disease risk and contribute to health disparities

Salivary total Immunoglobulin G as a surrogate marker of oral immune activity in salivary bioscience research

The integration of salivary biomeasures in biobehavioral, psychophysiological, and clinical research has greatly expanded our ability to study the biopsychosocial processes underlying health. Much of this research, however, has failed to adequately assess and adjust for the impact of oral immune activity on salivary biomeasure concentrations and associations with serum levels. Aiming to improve the validity and reliability of salivary biomeasure data, we examine salivary total Immunoglobulin G (IgG) as a potential surrogate marker of oral inflammation and immune activity. During a single study visit in Baltimore, Maryland, healthy young adult participants provided matched blood and saliva samples (N=99; age 18–37 years, 42% female) and completed an oral health questionnaire. Biospecimens were assayed for total IgG and immune markers related to inflammation (cytokines), blood in saliva (transferrin), and tissue remodeling (matrix metalloproteinase-8). Total IgG (μg/mL) concentrations were higher in serum than saliva. Salivary total IgG was associated with some self-reported oral health measures, and strongly positively associated with all salivary immune markers. Controlling for salivary total IgG may be a feasible, affordable approach to adjusting salivary biomeasure findings for the influence of the oral immune environment when it is not possible or practical to obtain clinical oral health data

Censored data considerations and analytical approaches for salivary bioscience data

Left censoring in salivary bioscience data occurs when salivary analyte determinations fall below the lower limit of an assay’s measurement range. Conventional statistical approaches for addressing censored values (i.e., recoding as missing, substituting or extrapolating values) may introduce systematic bias. While specialized censored data statistical approaches (i.e., Maximum Likelihood Estimation, Regression on Ordered Statistics, Kaplan-Meier, and general Tobit regression) are available, these methods are rarely implemented in biobehavioral studies that examine salivary biomeasures, and their application to salivary data analysis may be hindered by their sensitivity to skewed data distributions, outliers, and sample size. This study compares descriptive statistics, correlation coefficients, and regression parameter estimates generated via conventional and specialized censored data approaches using salivary C-reactive protein data. We assess differences in statistical estimates across approach and across two levels of censoring (9% and 15%) and examine the sensitivity of our results to sample size. Overall, findings were similar across conventional and censored data approaches, but the implementation of specialized censored data approaches was more efficient (i.e., required little manipulations to the raw analyte data) and appropriate. Based on our review of the findings, we outline preliminary recommendations to enable investigators to more efficiently and effectively reduce statistical bias when working with left-censored salivary biomeasure data

Scalable Group Level Probabilistic Sparse Factor Analysis

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a group level scalable probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex noise models than the presently considered.Comment: 10 pages plus 5 pages appendix, Submitted to ICASSP 1

Free-induction-decay magnetometer based on a microfabricated Cs vapor cell

We describe an optically pumped Cs magnetometer containing a 1.5 mm thick microfabricated vapor cell with nitrogen buffer gas operating in a free-induction-decay (FID) configuration. This allows us to monitor the free Larmor precession of the spin coherent Cs atoms by separating the pump and probe phases in the time domain. A single light pulse can sufficiently polarize the atomic sample however, synchronous modulation of the light field actively drives the precession and maximizes the induced spin coherence. Both amplitude and frequency modulation have been implemented with noise floors of 3 pT / √ Hz and 16 pT / √ Hz respectively within the Nyquist limited bandwidth of 500 Hz