We propose that pet, feral, and free-roaming cats presented to high-volume spay/neuter clinics could serve as a source of data about lead exposure in disadvantaged communities where these clinics already operate.  https://www.selleckchem.com/products/asciminib-abl001.html  Such a non-invasive surveillance system using inert, unobtrusively obtained samples could be deployed to detect highly exposed cats, prompting to follow up contact to a cat's caretakers to recommend seeking lead testing for themselves, their families, and their neighbors.The anthropogenic pressure on the environment depends on the spatial scale. It is crucial to prioritise conservation actions at different spatial scales to be cost-efficient. Using horizon scanning with the Delphi technique, we asked what the most important conservation problems are in Poland at local and national scales. Twenty-six participants, PhD students, individually identified conservation issues important at the local and national scales. Each problem was then scored and classified into broader categories during the round discussions. Text mining, cross-sectional analyses, and frequency tests were used to compare the context, importance scores, and frequency of identified problems between the two scales, respectively. A total of 115 problems were identified at the local scale and 122 at the national scale. Among them, 30 problems were identical for both scales. Importance scores were higher for national than local problems; however, this resulted from different sets of problems identified at the two scales. Problems linked to urbanisation, education, and management were associated with the local scale. Problems related to policy, forestry, and consumerism were more frequent at the national scale. An efficient conservation policy should be built hierarchically (e.g. introducing adaptive governance), implementing solutions at a national scale with the flexibility to adjust for local differences and to address the most pressing issues.A growing body of research suggests that empathy predicts important work outcomes, yet limitations in existing measures to assess empathy have been noted. Extending past work on the assessment of empathy, this study introduces a newly developed set of emotion-eliciting film clips that can be used to assess both cognitive (emotion perception) and affective (emotional congruence and sympathy) facets of empathy in vivo. Using the relived emotions paradigm, film protagonists were instructed to think aloud about an autobiographical, emotional event from working life and relive their emotions while being videotaped. Subsequently, protagonists were asked to provide self-reports of the intensity of their emotions during retelling their event. In a first study with 128 employees, who watched the film clips and rated their own as well as the protagonists' emotions, we found that the film clips are effective in eliciting moderate levels of emotions as well as sympathy in the test taker and can be used to calculate reliable convergence scores of emotion perception and emotional congruence. Using a selected subset of six film clips, a second two-wave study with 99 employees revealed that all facet-specific measures of empathy had moderate-to-high internal consistencies and test-retest reliabilities, and correlated in expected ways with other self-report and test-based empathy tests, cognition, and demographic variables. With these films, we expand the choice of testing materials for empathy in organizational research to cover a larger array of research questions.The ability to detect phenotypic similarity or kinship in third-parties' faces is not perfect, but better than chance. Still, some humans are better than others at this task. Yet researchers in kinship detection have difficulties in building up large and diverse datasets of high-quality pictures of related persons. The current experiments tested a novel method for circumventing this difficulty by using morphing techniques in order to generate a wide array of stimuli derived from a limited number of individual pictures. Six experiments tested various stimuli (standard protocol, mirrored face, other-sex face, other-ethnicity face, other-expression face and antiface). Our benchmarks are the similarity or kinship scores achieved by participants when faced with pictures of real siblings. We show that all stimuli, except the antiface, elicit detection scores similar to those elicited by real pictures of actual siblings. In addition, by exploring different experiment parameters (simultaneous or sequential task, kinship or similarity task) and some individual characteristics, these experiments provide a better understanding of kinship detection in third parties. The validation of our new method will allow widening the range of available stimuli to the research community, and even to develop new ecologically relevant experimental protocols that are hardly or not feasible with veridical images.A statistical procedure is assumed to produce comparable results across programs. Using the case of an exploratory factor analysis procedure-principal axis factoring (PAF) and promax rotation-we show that this assumption is not always justified. Procedures with equal names are sometimes implemented differently across programs a jingle fallacy. Focusing on two popular statistical analysis programs, we indeed discovered a jingle jungle for the above procedure Both PAF and promax rotation are implemented differently in the psych R package and in SPSS. Based on analyses with 247 real and 216,000 simulated data sets implementing 108 different data structures, we show that these differences in implementations can result in fairly different factor solutions for a variety of different data structures. Differences in the solutions for real data sets ranged from negligible to very large, with 42% displaying at least one different indicator-to-factor correspondence. A simulation study revealed systematic differences in accuracies between different implementations, and large variation between data structures, with small numbers of indicators per factor, high factor intercorrelations, and weak factors resulting in the lowest accuracies. Moreover, although there was no single combination of settings that was superior for all data structures, we identified implementations of PAF and promax that maximize performance on average. We recommend researchers to use these implementations as best way through the jungle, discuss model averaging as a potential alternative, and highlight the importance of adhering to best practices of scale construction.