The
relative ease of Mössbauer spectroscopy and of density
functional theory (DFT) calculations encourages the use of Mössbauer
parameters as a validation method for calculations, and the use of
calculations as a double check on crystallographic structures. A number
of studies have proposed correlations between the computationally
determined electron density at the iron nucleus and the observed isomer
shift, but deviations from these correlations in low-valent iron β-diketiminate
complexes encouraged us to determine a new correlation for these compounds.
The use of B3LYP/def2-TZVP in the ORCA platform provides an excellent
balance of accuracy and speed. We provide here not only this new correlation
and a clear guide to its use but also a systematic analysis of the
limitations of this approach. We also highlight the impact of crystallographic
inaccuracies, DFT model truncation, and spin states, with intent to
assist experimentalists to use Mössbauer spectroscopy and calculations
together.
Background
Demographic characteristics are known to influence participation in cocurricular activities. Less studied are the effects of other background characteristics.
Purpose
We hypothesize that considering college knowledge and students' proactive behaviors in tandem with demographics provides better models for predicting such participation.
Method
We developed a questionnaire and administered it to 3,618 domestic third‐ and fourth‐year undergraduate engineering students at a large public R1 Midwestern university, yielding 860 responses. Logistic regression models predicting five types of cocurricular participation were constructed with demographic characteristics, college knowledge, and proactive behaviors in all combinations as predictors.
Results
Four of five types of cocurricular participation were better modeled using factors beyond demographics. Two were better modeled using only proactive behavior as predictors and two were better modeled using demographics in combination with either college knowledge or proactive behavior. Only one type of participation could be best predicted by demographics alone.
Conclusions
These findings contribute quantitative evidence establishing relationships between participation in engineering cocurricular activities and a wider range of factors than previously reported. Furthermore, they provide guidance for creating intervention programs because, unlike demographics, college knowledge and proactive behavior can be shaped by either the individual or the institution.
I n the publication, there were several errors in Table 12.In the column for S, the first six entries should have been 0, 1, 2, 0, 1, and 2 (since 0, 1, and 2 are the possible values of S for each of the high-spin iron(II) compounds L tBu FeCH 3 and Me L Me,Me Fe(η 5 -Ind)). The correct values of S were used for the computations, and therefore the paper's interpretations and conclusions are the same. We regret this error.
Executive functioning (EF) deficits co-occur frequently with autism spectrum disorder (ASD) and have a long-term detrimental impact on quality of life of children and their families. Timely identification of risk for EF vulnerabilities may hasten access to early intervention and alleviate their long-term consequences. This study examines (1) if EF deficits are elevated in toddlers with ASD compared to nonautistic siblings of children with ASD, typically developing (TYP) toddlers, and toddlers with atypical developmental presentation; and (2) if EF deficits have a detrimental effect on adaptive functioning in ASD. Participants were recruited between September 2014 and October 2019 and included 73 toddlers with ASD, 33 nonautistic siblings of children with ASD, 35 toddlers with atypical development, and 28 TYP toddlers matched on chronological age (M = 39.01 months, SD = 3.11). EF deficits were measured using the BRIEF-P; adaptive skills were measured using the VABS-II. Whenever appropriate, analyses were controlled for MSEL verbal and nonverbal developmental quotient, ADOS-2 autism severity scores, and sex. Analyses revealed that toddlers with ASD exhibited elevated BRIEF-P scores across all domains compared to each of the three comparison groups. Higher BRIEF-P scores were associated with lower adaptive social, communication, and daily living skills while controlling for symptom severity, verbal and nonverbal functioning, and sex. In conclusion, marked vulnerabilities in EF are already present in 3-year-old toddlers with ASD and are predictive of the level of adaptive functioning in ASD. EF vulnerabilities in toddlers should be targeted for intervention to improve long-term outcomes in ASD.
Lay SummaryMany children with autism experience vulnerabilities in executive functioning (EF), which may include challenges with inhibition, working memory, cognitive flexibility, and planning. The study shows that these vulnerabilities can already be detected at age three and that their presence is linked with lower social, communication, and daily living skills. Screening children with ASD for EF challenges and helping those who have difficulties may improve their long-term outcomes.
Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings for individuals in healthcare settings. Nevertheless, it remains unclear if it is possible to build robust dimensional predictive models of attention in neurodiverse populations. Here, we use five datasets to identify and validate functional connectome-based markers of attention. In dataset one, we use connectome-based predictive modelling and observe successful prediction of performance on an in-scan sustained attention task in a neurodiverse sample of youth. The predictions are not driven by confounds, such as head motion. In dataset two, we find the attention network model defined in dataset one generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets three to five, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attention in neurodiverse youth and support the further development of predictive dimensional models of other clinically-relevant phenotypes.
Her master's thesis investigates the relationships between library use and academic self-efficacy of undergraduate engineering students. Emma holds a master's degree from the University of Michigan School of Information and bachelor's degree in chemistry and women's, gender, and sexuality studies from Yale University.
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