Examples facilitate divergent thinking: The effects of timing and quality.

The study investigated the effects of examples' timing and quality on divergent thinking (DT). In study 1, participants received two novel or common examples in the early or late stage of the realistic presented problem task. Results revealed higher fluency and flexibility in the late stage than that in the early stage. Moreover, originality was higher in the novel-example condition than that in the common-example condition. In study 2, participants solved alternative uses task (AUT) and received examples as in study 1. Results replicated beneficial effects of timing and quality on DT in study 1. Furthermore, in the late stage, fluency and flexibility were higher in the novel-example condition than that in the common one. These findings indicate that timing and quality affect example effect on DT, with late or novel examples facilitating DT. More importantly, in AUT, examples quality moderates the role of timing in DT's fluency and flexibility.

Instructor-learner brain coupling discriminates between instructional approaches and predicts learning.

The neural mechanisms that support naturalistic learning via effective pedagogical approaches remain elusive. Here we used functional near-infrared spectroscopy to measure brain activity from instructor-learner dyads simultaneously during dynamic conceptual learning. Results revealed that brain-to-brain coupling was correlated with learning outcomes, and, crucially, appeared to be driven by specific scaffolding behaviors on the part of the instructors (e.g., asking guiding questions or providing hints). Brain-to-brain coupling enhancement was absent when instructors used an explanation approach (e.g., providing definitions or clarifications). Finally, we found that machine-learning techniques were more successful when decoding instructional approaches (scaffolding vs. explanation) from brain-to-brain coupling data than when using a single-brain method. These findings suggest that brain-to-brain coupling as a pedagogically relevant measure tracks the naturalistic instructional process during instructor-learner interaction throughout constructive engagement, but not information clarification.

Instructor-learner body coupling reflects instruction and learning.

It is widely accepted that nonverbal communication is crucial for learning, but the exact functions of interpersonal coordination between instructors and learners remain unclear. Specifically, it is unknown what role instructional approaches play in the coupling of physical motion between instructors and learners, and crucially, how such instruction-mediated Body-to-Body Coupling (BtBC) might affect learning. We used a video-based, computer-vision Motion Energy Analysis (MEA) to quantify BtBC between learners and instructors who used two different instructional approaches to teach psychological concepts. BtBC was significantly greater when the instructor employed a scaffolding approach than when an explanation approach was used. The importance of the instructional approach was further underscored by the fact that an increase in motion in the instructor was associated with boosted BtBC, but only during scaffolding; no such relationship between the instructor movements and BtBC was found during explanation interactions. Finally, leveraging machine learning approaches (i.e., support vector and logistic regression models), we demonstrated that both learning outcome and instructional approaches could be decoded based on BtBC. Collectively, these results show that the real-time interaction of teaching and learning bodies is important for learning and that the instructional approach matters, with possible implications for both in-person and online learning.

[Speaker gender identification based on audio fractal dimension and pitch feature].

Automatic speaker gender identification based on voice feature is an important task in voice processing and analysis fields. In this paper non-linear parameters such as fractal dimension are applied to be one part of feature space for improving the ability of describing speaker gender feature through conventional linear parameters method. Pitch is picked using lifting scheme, and audio fractal dimension is extracted. Then based on Takens theory, the time delay method is used to reconstruct the phase space of fractal dimension sequence. And fractal dimension complexity is obtained by calculating Approximate Entropy. Three dimension feature vectors, including the pitch, the fractal dimension and the fractal dimension complexity, are applied to speaker gender identification. Experiment results show that through adding non-linear parameters, compared with the linear parameter using one dimension only such as pitch, the proposed method is more accurate and robust, and thus provides a new way for speaker gender identification.

[A research in speech endpoint detection based on boxes-coupling generalization dimension].

In this paper, a new calculating method of generalized dimension, based on boxes-coupling principle, is proposed to overcome the edge effects and to improve the capability of the speech endpoint detection which is based on the original calculating method of generalized dimension. This new method has been applied to speech endpoint detection. Firstly, the length of overlapping border was determined, and through calculating the generalized dimension by covering the speech signal with overlapped boxes, three-dimension feature vectors including the box dimension, the information dimension and the correlation dimension were obtained. Secondly, in the light of the relation between feature distance and similarity degree, feature extraction was conducted by use of common distance. Lastly, bi-threshold method was used to classify the speech signals. The results of experiment indicated that, by comparison with the original generalized dimension (OGD) and the spectral entropy (SE) algorithm, the proposed method is more robust and effective for detecting the speech signals which contain different kinds of noise in different signal noise ratio (SNR), especially in low SNR.

Post-marketing safety surveillance and reevaluation of Motherwort injection: A clinical study of 10 094 cases.

OBJECTIVE: To investigate the safety profiles of Motherwort injection (MI). METHODS: A multi-center, prospective and drug- derived hospital intensive monitoring method was conducted to assess the safety of MI in real world applications. This study was based on a very large population after the injection was approved and marketed in China. All patients using the injection in participating hospitals were monitored to determine the incidence, pattern, severity and outcome of associated adverse events. RESULTS: The post-marketing surveillance was performed in 10 094 female patients from April to December, 2015. The incidence of adverse drug reactions (ADRs) was 0.79¡ë(8/10 094). Among the 8 patients, the reported adverse events mainly included systemic abnormalities, such as fever, chills and eyelid edema; skin and appendages disorders, such as pruritus and rash; gastrointestinal disorders, such as nausea, abdominal distension and pain; heart rate and rhythm disorders, such as palpitation and increased heart rate. All of these ADRs were mild in severity. CONCLUSION: In this study the ADRs incidence rate of MI is very low, which supports that it is generally safe for use in obstetric and gynecological diseases. However, the total number of 8 ADRs recorded over a relatively short time span seems limited, and the low number of reports could not represent an absolute guarantee of safety.