Leaders in the nonprofit sector: leader and organizational level predictors of leader engagement in self-development activities

Includes bibliographical references.The purpose of the current study was to better understand the individual and organizational antecedents of leader self-development in the nonprofit sector. Data were collected from 94 nonprofit leaders and 340 nonprofit employees and volunteers. Individual-level analyses revealed that three leader characteristics (developmental efficacy, learning adaptability, and propensity to self-develop) significantly predicted multiple indicators of leader engagement in self-development activities. Multi-level analyses failed to support the expected relationship between organizational-level characteristics (organizational support for development, organizational barriers to development, learning environment) and leader engagement in self-development activities. Finally, five interactions of leader and organizational characteristics significantly predicted leader self-development outcomes, but were in the opposite direction than expected. Implications and opportunities for future research on leader self-development are discussed

Music as a mirror?: popular music lyrics and the COVID-19 health pandemic

Research on the relationship between significant global, socioeconomic developments and lyrical themes in pop music have indicated that deteriorating conditions are associated with an increase in negative emotional content and reproductive themes. The present research considers the presence of lyrical themes in charting pop music during the COVID-19 pandemic. We hypothesise that top-ranked weekly singles on the USA, UK and Australian charts throughout the COVID-19 pandemic would contain more negatively valenced lyrics than the charting songs during corresponding periods in previous years. Diction 7.0 software, a text analysis program designed to analyse content of a wide variety of social discourse, was used to analyse the song lyrics. A dataset was created based on the song lyrics of the top 5 weekly songs in the USA, UK and Australia from March-August 2020 and the songs charting between March-August of 2015-2019. Results from statistical analyses that consider the hypotheses will be discussed in the presentation. The findings are expected to broaden our understanding of the relationship between significant global events (i.e., health pandemics) and trends in popular music. Moreover, implications concerning how people use music as a comforting tool will be considered

Popular music lyrics and the COVID-19 pandemic

A limited amount of previous research suggests that deteriorating socioeconomic conditions may be associated with greater popularity of music lyrics featuring negative emotional content and references to relationships. The present research considered this in charting popular music before and during the first six months of the COVID-19 pandemic. A dataset based on the song lyrics of the top-5 charting weekly songs in the UK and USA from January 1999 to August 2020 was computer-analysed for interpersonal variables, such as satisfaction and human interest, and positive and negative emotional valence. Results indicated lower satisfaction and human interest in lyrics in the USA and UK in the first six months of the COVID-19 pandemic compared to the lyrics in charting songs in 2015-2019. The USA charting songs in 2020 also saw higher leveling and negative emotional content; and, when considering monthly data from 1999-2020, there was a positive association between economic misery and the number of negatively-valenced words. The findings broaden our understanding of the relationship between significant global events and trends in popular music

Kinematic Constraints on Formation of Bound States of Cosmic Strings - Field Theoretical Approach

Superstring theory predicts the potential formation of string networks with bound states ending in junctions. Kinematic constraints for junction formation have been derived within the Nambu-Goto thin string approximation. Here we test these constraints numerically in the framework of the Abelian-Higgs model in the Type-I regime and report on good agreement with the analytical predictions. We also demonstrate that strings can effectively pass through each other when they meet at speeds slightly above the critical velocity permitting bound state formation. This is due to reconnection effects that are beyond the scope of the Nambu-Goto approximation.Comment: 6 pages, 12 eps figures - matches the published versio

Shifting the Universe: Early Dark Energy and Standard Rulers

The presence of dark energy at high redshift influences both the cosmic sound horizon and the distance to last scattering of the cosmic microwave background. We demonstrate that through the degeneracy in their ratio, early dark energy can lie hidden in the CMB temperature and polarization spectra, leading to an unrecognized shift in the sound horizon. If the sound horizon is then used as a standard ruler, as in baryon acoustic oscillations, then the derived cosmological parameters can be nontrivially biased. Fitting for the absolute ruler scale (just as supernovae must be fit for the absolute candle magnitude) removes the bias but decreases the leverage of the BAO technique by a factor 2.Comment: 6 pages, 3 figure

Exploiting Cross Correlations and Joint Analyses

In this report, we present a wide variety of ways in which information from multiple probes of dark energy may be combined to obtain additional information not accessible when they are considered separately. Fundamentally, because all major probes are affected by the underlying distribution of matter in the regions studied, there exist covariances between them that can provide information on cosmology. Combining multiple probes allows for more accurate (less contaminated by systematics) and more precise (since there is cosmological information encoded in cross-correlation statistics) measurements of dark energy. The potential of cross-correlation methods is only beginning to be realized. By bringing in information from other wavelengths, the capabilities of the existing probes of dark energy can be enhanced and systematic effects can be mitigated further. We present a mixture of work in progress and suggestions for future scientific efforts. Given the scope of future dark energy experiments, the greatest gains may only be realized with more coordination and cooperation between multiple project teams; we recommend that this interchange should begin sooner, rather than later, to maximize scientific gains.Comment: Report from the "Dark Energy and CMB" working group for the American Physical Society's Division of Particles and Fields long-term planning exercise ("Snowmass"

Induced Gravity and the Attractor Dynamics of Dark Energy/Dark Matter

Attractor solutions that give dynamical reasons for dark energy to act like the cosmological constant, or behavior close to it, are interesting possibilities to explain cosmic acceleration. Coupling the scalar field to matter or to gravity enlarges the dynamical behavior; we consider both couplings together, which can ameliorate some problems for each individually. Such theories have also been proposed in a Higgs-like fashion to induce gravity and unify dark energy and dark matter origins. We explore restrictions on such theories due to their dynamical behavior compared to observations of the cosmic expansion. Quartic potentials in particular have viable stability properties and asymptotically approach general relativity.Comment: 11 pages, 10 figures, accepted in JCAP, results unchanged, an explanation added on perfect fluids for general spinor Lagrangian

ABC-SysBio—approximate Bayesian computation in Python with GPU support

Motivation: The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions

A multi-method assessment of attentional processes in chronic, treatment-resistant depression

Contains fulltext : 233751.pdf (Publisher’s version ) (Open Access)Attentional deficits as well as attentional biases towards negative material are related to major depression and might maintain chronicity. However, studies investigating attentional deficits and attentional biases in chronic, treatment-resistant depressed are lacking. The aim of the current study was to compare measures of attentional deficits and attentional bias between chronic, treatment-resistant depressed outpatients and never-depressed control participants. Attentional deficits were assessed with the attentional control scale (ACS) and the Stroop Color naming task. Attentional bias was measured with the exogenous cueing task (ECT) and an emotional Stroop task. Chronic, treatment-resistant depressed patients (n=80) showed significantly more attentional deficits than never-depressed controls (n=113) on the ACS and Stroop color-naming task. However, in contrast with hypotheses, no differences were found between chronic, treatment-resistant depressed patients and never-depressed individuals on the ECT or emotional Stroop task. The current findings indicate that chronic, treatment-resistant depressed patients present attentional deficits. The results however question whether this patient group shows attentional biases for negative material. Future research should include comparisons of chronic, treatment-resistant and non-chronically depressed patients. If replicated, these current results might indicate that focusing on improving attentional deficits could be a more promising target for treatment than addressing attentional biases.9 p