Project description:This paper describes a dataset of 6284 land transactions prices and plot surfaces in 3 medium-sized cities in France (Besançon, Dijon and Brest). The dataset includes road accessibility as obtained from a minimization algorithm, and the amount of green space available to households in the neighborhood of the transactions, as evaluated from a land cover dataset. Further to the data presentation, the paper describes how these variables can be used to estimate the non-observable parameters of a residential choice function explicitly derived from a microeconomic model. The estimates are used by Caruso et al. (2015) to run a calibrated microeconomic urban growth simulation model where households are assumed to trade-off accessibility and local green space amenities.
Project description:Gene-environment correlations (rGE) have been demonstrated in behavioral genetic studies, but rGE have proven elusive in molecular genetic research. Significant gene-environment correlations may be difficult to detect because potential moderators could reduce correlations between measured genetic variants and the environment. Molecular genetic studies investigating moderated rGE are lacking. This study examined associations between child catechol-O-methyltransferase genotype and aspects of positive parenting (responsiveness and warmth), and whether these associations were moderated by parental personality traits (neuroticism and extraversion) among a general community sample of third, sixth, and ninth graders (N = 263) and their parents. Results showed that parent personality traits moderated the rGE association between youths' genotype and coded observations of positive parenting. Parents with low levels of neuroticism and high levels of extraversion exhibited greater sensitive responsiveness and warmth, respectively, to youth with the valine/valine genotype. Moreover, youth with this genotype exhibited lower levels of observed anger. There was no association between the catechol-O-methyltransferase genotype and parenting behaviors for parents high on neuroticism and low on extraversion. Findings highlight the importance of considering moderating variables that may influence child genetic effects on the rearing environment. Implications for developmental models of maladaptive and adaptive child outcomes, and interventions for psychopathology, are discussed within a developmental psychopathology framework.
Project description:Thanks to the work of politics and religion scholars, we now know a lot about the relationship between religion and voting in American presidential general elections. However, we know less about the influence of religion on individual vote choice in presidential primaries. This article fills that gap by exploring the relationship between religion and candidate preference in the 2008 and 2012 Republican primaries. Using pre-Super Tuesday surveys conducted by the Pew Research Center, I find that the Republican candidate who most explicitly appealed to religious voters (Mike Huckabee in 2008 and Rick Santorum in 2012) was the preferred candidate of Republican respondents who attended religious services at the highest levels, and that as attendance increased, so did the likelihood of preferring that candidate. I also find that identification as a born again Christian mattered to candidate preference. Specifically, born again Christians were more likely than non-born again Christians to prefer Huckabee to Mitt Romney, John McCain and Ron Paul in 2008, and Santorum to Romney in 2012. Although ideology was not the primary subject of this article, I find that ideology was also a statistically significant predictor of Republican candidate preference in both 2008 and 2012. This robust finding reinforces scholars' prior work on the importance of ideology in explaining presidential primary vote choice. The overall findings of the paper provide evidence that religion variables can add to our understanding of why voters prefer one candidate over another in presidential primaries.
Project description:We examine how religion contributes to rehabilitation, which we conceptualize as moral reform and operationalize in terms of self-identity, existential belief, and character. We hypothesize that religion contributes to identity transformation, a sense of meaning and purpose in life, and virtue development. We also hypothesize that faith-based rehabilitation reduces negative emotions and the risk of interpersonal aggression. We conducted a quasi-experiment on a faith-based program in a state jail and a maximum-security prison in Texas, using a convenience sample of male inmates. To test our hypotheses, we compare inmates who graduated the program with those who did not and applied manifest-variable structural equation modeling to analyze data from pretest and posttest surveys. Program participation was linked to an increase in religiosity, which contributed to identity transformation (cognitive and emotional transformations and crystallization of discontent), the perceived presence of meaning and purpose in life, and virtues (including self-control, compassion, and forgiveness). Faith-based rehabilitation in turn reduced state depression and anxiety and the probability of engaging in aggression toward another inmate. This study provides preliminary evidence of religion's rehabilitative effect on offenders; findings which hold promise for prison administrators looking for creative ways to support evidence-based and cost-effective approaches to rehabilitation within the correctional system.Supplementary informationThe online version contains supplementary material available at 10.1007/s12103-022-09707-3.
Project description:Spouses may affect each other's sleeping behaviour. In 47,420 spouse-pairs from the UK Biobank, we found a weak positive phenotypic correlation between spouses for self-reported sleep duration (r = 0.11; 95% CI = 0.10, 0.12) and a weak inverse correlation for chronotype (diurnal preference) (r = -0.11; -0.12, -0.10), which replicated in up to 127,035 23andMe spouse-pairs. Using accelerometer data on 3454 UK Biobank spouse-pairs, the correlation for derived sleep duration was similar to self-report (r = 0.12; 0.09, 0.15). Timing of diurnal activity was positively correlated (r = 0.24; 0.21, 0.27) in contrast to the inverse correlation for chronotype. In Mendelian randomization analysis, positive effects of sleep duration (mean difference=0.13; 0.04, 0.23 SD per SD) and diurnal activity (0.49; 0.03, 0.94) were observed, as were inverse effects of chronotype (-0.15; -0.26, -0.04) and snoring (-0.15; -0.27, -0.04). Findings support the notion that an individual's sleep may impact that of their partner, promoting opportunities for sleep interventions at the family-level.
Project description:Background: Methane yield and biogas productivity of biogas plants depend on microbial community structure and functionality, substrate supply, and general process parameters. Little is known, however, about the correlations between microbial community function and the process parameters. To close this knowledge gap the microbial community of 40 industrial biogas plants was evaluated by a metaproteomics approach in this study. Results: Liquid chromatography coupled to tandem mass spectrometry (Elite Hybrid Ion Trap Orbitrap) enabled the identification of 3138 metaproteins belonging to 162 biological processes and 75 different taxonomic orders. Therefore, database searches were performed against UniProtKB/Swiss-Prot and several metagenome databases. Subsequent clustering and principal component analysis of these data allowed to identify four main clusters associated to mesophilic and thermophilic process conditions, upflow anaerobic sludge blanket reactors and sewage sludge as substrate. Observations confirm a previous phylogenetic study of the same biogas plant samples that was based on 16S-rRNA gene by De Vrieze et al. (2015) (De Vrieze, Saunders et al. 2015). Both studies described similar microbial key players of the biogas process, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. In addition, a correlation study and a Gephi graph network based on the correlations between the taxonomic orders and process parameters suggested the presence of various trophic interactions, e.g. syntrophic hydrogen transfer between Thermoanaerobacteriales and Methanomicrobiales. For the elucidation of the main biomass degradation pathways the most abundant 1% of metaproteins were assigned to the KEGG map 1200 representing the central carbon metabolism. Additionally, the effect of the process parameters (i) temperature, (ii) organic loading rate (OLR), (iii) total ammonia nitrogen (TAN) and (iv) sludge retention time (SRT) on these pathways was investigated. For example high TAN correlated with hydrogenotrophic methanogens and bacterial one-carbon metabolism, indicating syntrophic acetate oxidation. Conclusion: This study shows the benefit of large-scale proteotyping of biogas plants, enabling the identification of general correlations between the process parameters and the microbial community structure and function. Changes in the level of microbial key functions or even in the microbial community type represent a valuable hint for process problems and disturbances.
Project description:We assess the abilities of both specialized deep neural networks, such as PersonalityMap, and general LLMs, including GPT-4o and Claude 3 Opus, in understanding human personality by predicting correlations between personality questionnaire items. All AI models outperform the vast majority of laypeople and academic experts. However, we can improve the accuracy of individual correlation predictions by taking the median prediction per group to produce a "wisdom of the crowds" estimate. Thus, we also compare the median predictions from laypeople, academic experts, GPT-4o/Claude 3 Opus, and PersonalityMap. Based on medians, PersonalityMap and academic experts surpass both LLMs and laypeople on most measures. These results suggest that while advanced LLMs make superior predictions compared to most individual humans, specialized models like PersonalityMap can match even expert group-level performance in domain-specific tasks. This underscores the capabilities of large language models while emphasizing the continued relevance of specialized systems as well as human experts for personality research.
Project description:BackgroundTherapist's emotional reactions toward patients in clinical facilities are a key concept in the treatment of personality disorders. Considering only clinical settings specialized in treatment of personality pathology the present paper aimed at: (1) assessing any direct relationship between patient symptom severity and therapist emotional response; (2) exploring patients' functioning configurations that can be associated with specific therapist reactions (3) investigating whether these relationships remains significant when accounting for other setting variables related to patients or therapist.MethodsThe present study included 43 outpatients with personality disorders who underwent a psychotherapy treatment in two Italian facilities dedicated to outpatients with personality disorders and their 19 psychotherapists. The Symptom Checklist-90-Revised (SCL-90R) was used to explore clinical severity condition. Psychotherapists completed the Therapist Response Questionnaire (TRQ) to identify pattern of therapists' response and the Shedler-Westen Assessment Procedure-200 (SWAP-200) in order to assess personality traits of the patients.ResultsNo significant relationship between the clinical severity of the symptoms and the therapist' responses was found. Even when controlled for clinical severity condition, duration of the treatment, age and educational level of the patient or years of therapist experience, most of SWAP-200 traits appeared to be significant predictors of therapist' emotional responses.ConclusionsThe present study confirms the value of therapists' emotional response as a useful tool in understanding psychological processes related to clinical practice highlighting its context-dependent dimension.
Project description:Categorization of visual stimuli is an intrinsic aspect of human perception. Whether the cortical mechanisms underlying categorization operate in an all-or-none or graded fashion remains unclear. In this study, we addressed this issue in the context of the face-specific N170. Specifically, we investigated whether N170 amplitudes grade with the amount of face information available in an image, or a full response is generated whenever a face is perceived. We employed linear mixed-effects modeling to inspect the dependency of N170 amplitudes on stimulus properties and duration, and their relationships to participants' subjective perception. Consistent with previous studies, we found a stronger N170 evoked by faces presented for longer durations. However, further analysis with equivalence tests revealed that this duration effect was eliminated when only faces perceived with high confidence were considered. Therefore, previous evidence supporting the graded hypothesis is more likely to be an artifact of mixing heterogeneous "all" and "none" trial types in signal averaging. These results support the hypothesis that the N170 is generated in an all-or-none manner and, by extension, suggest that categorization of faces may follow a similar pattern.
Project description:ObjectiveThe current study examined trajectories of anxiety and depression symptoms at three-time points during the COVID-19 pandemic and examined correlates of those trajectories.DesignData were collected at three time points during the COVID-19 pandemic.ParticipantsThe sample in the current study consisted of 804 respondents who had completed the online questionnaire at all three time points designed for the study.ResultsUsing Latent Growth Mixture Modeling (LGMM) we identified four trajectories: (a) A resilient group reported consistently low levels of symptoms (62% anxiety and 72% depression), (b) a chronic group reported consistently high levels of symptoms (12% anxiety and 14% depression), (c) an emerging group reported low initial symptoms that increased steadily across time (20% anxiety and 13% depression), and (d) an improving group reported high initial symptoms that decreased across time (6% anxiety and 3% depression).ConclusionsThe salient conclusion that emerged from these results is that even in a severe and prolonged crisis, such as the COVID-19 pandemic, the most common outcome in the population is that of resilience. Moreover, examining predictors of these trajectories, we found that the resilience trajectory was associated with fewer economic difficulties due to the COVID-19, greater income, and self-identification as religious.