Delayed matching to two-picture samples by individuals with and without disabilities: an analysis of the role of naming

Delayed matching to complex, two-picture samples (e.g., cat-dog) may be improved when the samples occasion differential verbal behavior. In Experiment 1, individuals with mental retardation matched picture comparisons to identical single-picture samples or to two-picture samples, one of which was identical to a comparison. Accuracy scores were typically high on single-picture trials under both simultaneous and delayed matching conditions. Scores on two-picture trials were also high during the simultaneous condition but were lower during the delay condition. However, scores improved on delayed two-picture trials when each of the sample pictures was named aloud before comparison responding. Experiment 2 replicated these results with preschoolers with typical development and a youth with mental retardation. Sample naming also improved the preschoolers' matching when the samples were pairs of spoken names and the correct comparison picture matched one of the names. Collectively, the participants could produce the verbal behavior that might have improved performance, but typically did not do so unless the procedure required it. The success of the naming intervention recommends it for improving the observing and remembering of multiple elements of complex instructional stimuli.     

An Ecological View of School Counselor Ratios and Student Academic Outcomes: A National Investigation

The effect of student‐to‐school‐counselor ratios on academic outcomes has been widely studied, yet few researchers have taken a multilevel approach. Using the nationally representative High School Longitudinal Study: 2009 dataset, the authors found ratios were significantly associated with student grade point average (GPA) and graduation. Attending a Title I school also was associated with students’ GPA, advanced placement/international baccalaureate credits earned, and postsecondary course taking. The authors discuss implications for advocacy and practice, contextualizing their findings within an ecological framework.     

Cross-sectional age differences in personality: Evidence from nationally representative samples from Switzerland and the United States

Identifying reliable patterns of age differences in personality can help clarify the nature of adult personality development. Previous studies have been limited because many have relied on convenience samples. In this study, we examined age differences in personality in two nationally representative samples, one from Switzerland and one from the United States. The results indicated that Agreeableness and Conscientiousness were positively associated with age, whereas Extraversion was negatively associated with age. However, the magnitude of age differences for Extraversion was much smaller than for Agreeableness and Conscientiousness. Openness showed a more complex trend such that 30- to 34-year-olds scored lower on Openness than younger age groups, whereas older groups scored somewhere in between. Inconsistent age differences were observed for Neuroticism.     

Bidirectional feature selection with global and local structure preservation for small size samples

Collecting samples is a challenging task for face recognition, especially for some real-world applications such as law enhancement and ID card identification, where there is usually single sample per person (SSPS) used to train a face recognition system. To extract discriminative features from the small size samples, in this paper we propose virtual samples via bidirectional feature selection with global and local structure preservation (VS-BFS-GL) to augment the number of training samples. In VS-BFS-GL, bidirectional feature selection is developed, which introduces L_2,1 norm to explore the face variations from both horizontal and vertical directions. Further, to include more variations in the virtual images, the global structure information and sample-specified local structure information of the SSPP training set are considered. By integrating bidirectional feature selection, global and local structure, the limited training samples are fully utilized and more knowledge are mined. To further improve the effectiveness of VS-BFS-GL, an auxiliary database containing different face variations can be used to explore the local structure information. We extensively evaluated the proposed approach on AR and FERET database. The promising recognition results demonstrate that VS-BFS-GL is robust to expression, pose and partial occlusion variations in the faces.     

La recherche scientifique sur les prélèvements biologiques réalisés dans le cadre des autopsies et objets de scellés judiciaires. Nécessité d’une adaptation législative

Currently, it is legally impossible to conduct scientific research on tissue and organ samples taken from forensic autopsies. In fact, the law schedules the destruction of such samples at the end of the judicial investigation, and the common law rules governing cadaver research cannot be applied to the forensic context. However, nothing seems in itself to stand in the way of such research since, despite their specific nature, these samples from forensic autopsies could be subject, following legislative amendments, to common law relating to medical research on samples taken from deceased persons. But an essential legislative amendment will have the goal firstly to allow the Biomedicine Agency to become authorized to issue a research permit and secondly, to change the research conditions in terms of the non-opposition of the deceased to the said research. Such an amendment would be a true breakthrough because it would allow teams to continue to move forward calmly in research, and allow this research to be placed within a legal framework, which would promote international exchanges.     

Improving the image of student‐recruited samples: A commentary

This commentary argues that the quality and usefulness of student‐recruited data can be evaluated by examining the external validity and generalization issues related to this sampling method. Therefore, we discuss how the sampling methods of student‐ and non‐student‐recruited samples can enhance or diminish external validity and generalization. Next, we present the advantages of the student‐recruited sampling method (heterogeneity of the sample, student learning, cost reduction, and elaborate research designs) and conclude with making additional suggestions on how to improve the quality of these data.     

Effect of intermittent reinforcement on acquisition and retention in delayed matching-to-sample in pigeons

Experiments 1 and 2 involved independent groups that received primary reinforcement after a correct match with a probability of 1.0, .50 or .25. Correct matches that did not produce primary reinforcement produced a conditioned reinforcer. Both experiments revealed little evidence that acquisition or retention was adversely affected by use of intermittent reinforcement. Experiment 3 involved a group that received 100% reinforcement and two others that received 25% reinforcement, one of which received conditioned reinforcement and the other did not. Following acquisition and retention testing, birds in group 100% and group 25% with conditioned reinforcement were exposed to 25% reinforcement and no conditioned reinforcement. Results revealed that conditioned reinforcement was important in promoting acquisition but was irrelevant in maintaining performance. It was concluded that intermittent reinforcement, especially when combined with conditioned reinforcement during acquisition, supports levels of acquisition and retention comparable to that of continuous reinforcement. Theoretically, the findings are consistent with an extension of Blough's instance-based theory of discrimination performance and, practically, they suggest that use of intermittent reinforcement could result in increased efficiency and economy in labs using delayed matching.     

Statistical inference of minimum rank factor analysis

For any given number of factors, Minimum Rank Factor Analysis yields optimal communalities for an observed covariance matrix in the sense that the unexplained common variance with that number of factors is minimized, subject to the constraint that both the diagonal matrix of unique variances and the observed covariance matrix minus that diagonal matrix are positive semidefinite. As a result, it becomes possible to distinguish the explained common variance from the total common variance. The percentage of explained common variance is similar in meaning to the percentage of explained observed variance in Principal Component Analysis, but typically the former is much closer to 100 than the latter. So far, no statistical theory of MRFA has been developed. The present paper is a first start. It yields closed-form expressions for the asymptotic bias of the explained common variance, or, more precisely, of the unexplained common variance, under the assumption of multivariate normality. Also, the asymptotic variance of this bias is derived, and also the asymptotic covariance matrix of the unique variances that define a MRFA solution. The presented asymptotic statistical inference is based on a recently developed perturbation theory of semidefinite programming. A numerical example is also offered to demonstrate the accuracy of the expressions.This work was supported, in part, by grant DMS-0073770 from the National Science Foundation.