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Radiometric and style product for the tunable light-guide picture running snapshot spectrometer (TuLIPSS).
The paper discusses the potential advantages of using ontologies for describing and modeling psychological research questions. The handling of dataset completion, unification, and its explanation by means of Artificial Intelligence and Machine Learning models is also discussed.
The paper discusses the potential advantages of using ontologies for describing and modeling psychological research questions. The handling of dataset completion, unification, and its explanation by means of Artificial Intelligence and Machine Learning models is also discussed.This study proposed a line of research on entrepreneurship based on the analysis of personality traits and geographical area. Its objective is to identify whether certain personality traits or sociocultural variables typical of a particular geographical area influence those who have already started an entrepreneurial activity to keep it up, in other words, to maintain their entrepreneurial intention. The research results reach a sample of 479 entrepreneurs from two Iberian Peninsula geographical areas. The analyse of the psychometric properties on the Entrepreneurial Orientation Questionnaire (EOQ) identified five dimensions of the enterprising personality. They also evidence that geographical location is a factor that contributes to the development of the entrepreneurial intentions that determine the business profile. The results show that entrepreneurs in the northern area tend to maintain their business than those in the central zone.When interacting with technology, attention is mainly driven by audiovisual and increasingly haptic stimulation. Olfactory stimuli are widely neglected, although the sense of smell influences many of our daily life choices, affects our behavior, and can catch and direct our attention. In this study, we investigated the effect of smell and sound on visuospatial attention in a virtual environment. We implemented the Bells Test, an established neuropsychological test to assess attentional and visuospatial disorders, in virtual reality (VR). We conducted an experiment with 24 participants comparing the performance of users under three experimental conditions (smell, sound, and smell and sound). The results show that multisensory stimuli play a key role in driving the attention of the participants and highlight asymmetries in directing spatial attention. We discuss the relevance of the results within and beyond human-computer interaction (HCI), particularly with regard to the opportunity of using VR for rehabilitation and assessment procedures for patients with spatial attention deficits.Problem finding (PF) and divergent thinking (DT) are considered to be indicators of creative potential. Previous studies, with different goals, suggest a positive correlation between PF and DT. However, none of these works have explicitly examined which index of DT is more associated with PF. The current investigation examined the association between PF and three main indexes of DT fluency, flexibility, and originality. It also tested whether such a relation differs based on task nature (verbal vs. figural). The sample consisted of 90 sixth graders who completed three tests (a) a verbal DT test, (b) a figural DT test, and (c) a PF test. Correlational analysis showed that flexibility was highly correlated with PF in the verbal DT test, whereas originality was significantly correlated with PF in the figural test. Results of the path analysis confirmed the results from correlational analyses and showed that verbal flexibility strongly predicted PF fluency, flexibility, and originality more than any other variable. Likelihood ratio test showed that using 1 or 3% cutoff for scoring originality did not significantly altered the results in both figural and verbal DT (vs. PF), while the likelihood ratio test showed significant differences between the figural and verbal DT. Finally, predictor variables in the verbal DT accounted for 40-58% of the variance in PF skills, whereas predictor variables in the figural DT accounted for 28-37% of the variance in PF skills. As suggested by experts in the field of PF, the role of flexibility in PF is a fertile area to be considered in future studies.Smartphone addiction is a behavioral dependence characterized by excessive or compulsive Internet use and a preoccupation with and loss of control over this use that interferes with an individual's daily functioning and results in negative mental processes and subsequent social consequences. Smartphone addiction can negatively impact physical and mental health as well as academic performance, sleep quality, and even interpersonal interaction and relationships. Based on the compensatory Internet use theory, this study explores the relationship between interpersonal sensitivity and smartphone addiction in college students and constructed a moderated mediation model. A sample of 881 college students was tested using the Interpersonal Sensitivity Scale, Smart Phone Addiction Scale, Fear of Missing Out Scale, and Relational Self-Construal Scale. We used AMOS 26.0 to conduct a confirmatory factor analysis and employed SPSS 24.0 to test our hypotheses. The results indicated that (1) interpersonal sensitivity was positively related to the fear of missing out and smartphone addiction; (2) the fear of missing out mediated the relationship between interpersonal sensitivity and mobile phone addiction; (3) relational self-construal moderated interpersonal sensitivity and the fear of missing out; and (4) relational self-construal moderated the mediating effect of the fear of missing out on the relationship between interpersonal sensitivity and smartphone addiction. We concluded that the fear of missing out and relational self-construal play a moderated mediation effect on the relationship between smartphone addiction and interpersonal sensitivity. Our findings provided some theoretical implications. Specifically, in addition to proposing a new approach for the study of smartphone addiction, we also introduced a theoretical basis for psychotherapy and intervention of smartphone addiction. In addition, this study also provides some insightful ideas for educational practitioners.Speech and language impairments are common pediatric conditions, with as many as 10% of children experiencing one or both at some point during development. Expressive language disorders in particular often go undiagnosed, underscoring the immediate need for assessments of expressive language that can be administered and scored reliably and objectively. In this paper, we present a set of highly accurate computational models for automatically scoring several common expressive language tasks. In our assessment framework, instructions and stimuli are presented to the child on a tablet computer, which records the child's responses in real time, while a clinician controls the pace and presentation of the tasks using a second tablet. The recorded responses for four distinct expressive language tasks (expressive vocabulary, word structure, recalling sentences, and formulated sentences) are then scored using traditional paper-and-pencil scoring and using machine learning methods relying on a deep neural network-based language representation model. All four tasks can be scored automatically from both clean and verbatim speech transcripts with very high accuracy at the item level (83-99%). In addition, these automated scores correlate strongly and significantly (ρ = 0.76-0.99, p less then 0.001) with manual item-level, raw, and scaled scores. These results point to the utility and potential of automated computationally-driven methods of both administering and scoring expressive language tasks for pediatric developmental language evaluation.Conversational impairments are well known among people with autism spectrum disorder (ASD), but their measurement requires time-consuming manual annotation of language samples. Natural language processing (NLP) has shown promise in identifying semantic difficulties when compared to clinician-annotated reference transcripts. Our goal was to develop a novel measure of lexico-semantic similarity - based on recent work in natural language processing (NLP) and recent applications of pseudo-value analysis - which could be applied to transcripts of children's conversational language, without recourse to some ground-truth reference document. We hypothesized that (a) semantic coherence, as measured by this method, would discriminate between children with and without ASD and (b) more variability would be found in the group with ASD. We used data from 70 4- to 8-year-old males with ASD (N = 38) or typically developing (TD; N = 32) enrolled in a language study. Participants were administered a battery of standardized diatterance, or NDR did not account for between group differences. The findings suggest that our pseudo-value-based method can be effectively used to identify specific semantic difficulties that characterize children with ASD without requiring a reference transcript.Partial hospitalization programming (PHP) is a treatment option available for individuals with eating disorders (ED) who have made insufficient progress in outpatient settings or are behaviorally or medically unstable. Research demonstrates that this level of care yields efficacy for the majority of patients. However, not all patients achieve recovery in PHP and later admit to a higher level of care (HLOC) including residential treatment or inpatient hospitalization. Although PHP is an increasingly common treatment choice for ED, research concerning outcome predictors in outpatient, stepped levels of care remains limited. Thus, the current study sought to identify the predictors of patients first admitted to PHP that later enter residential or inpatient treatment. Participants were 788 patients (after exclusions) enrolled in adolescent or adult partial hospitalization programs in a specialized ED clinic. selleck compound When compared to patients who maintained treatment in PHP, a significantly greater proportion of patients who discharged to a HLOC had previously received ED residential treatment. Moreover, patients who discharged to a HLOC were diagnosed with a comorbid anxiety disorder and reported greater anxious and depressive symptomatology. A logistic regression model predicting discharge from PHP to a HLOC was significant, and lower body mass index (BMI) was a significant predictor of necessitating a HLOC. Supplemental programming in partial hospitalization settings might benefit individuals with previous ED residential treatment experience, higher levels of anxiety and depression, and lower BMIs. Specialized intervention for these cases is both practically and economically advantageous, as it might reduce the risk of rehospitalization and at-risk patients needing to step up to a HLOC.This study aimed to determine whether the observed tendency to remember more positive than negative past events (positivity phenomena) also appears when recalling hypothetical events about the future. In this study, young, middle-aged, and older adults were presented with 28 statements about the future associated with the COVID-19 pandemic, half positive and half negative. In addition, half of these statements were endowed with personal implications while the other half had a more social connotations. Participants rated their agreement/disagreement with each statement and, after a distraction task, they recalled as many statements as possible. There was no difference in the agreement ratings between the three age groups, but the participants agreed with positive statements more than with negative ones and they identified more with statements of social content than of personal content. The younger and older individuals recalled more statements than the middle-aged people. More importantly, older participants recalled more positive than negative statements (positivity effect), and showed a greater tendency to turn negative statements into more positive or neutral ones (positivity bias).
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