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Establishing joint attention with a caregiver on a physical object provides an optimal environment for language learning for infants. In the present study, we investigated whether 12-month-olds and their mothers establish higher quality joint attention interactions in the presence of fewer compared to more toys. As a secondary goal, we investigated how different types of toys affect how mother-infant dyads establish joint attention. In a five-minute free play setting, mothers and infants participated in either Five Toy (n = 48) or Twelve Toy (n = 33) groups. They were given organizational (i.e., toys that require arrangement of parts), responsive (i.e., toys that emit sounds via manipulation), and symbolic toys (i.e., toys that elicit pretend play). [https://www.selleckchem.com/products/AC-220.html read more] Results showed that compared to the Twelve Toy group, joint attention interactions in the Five Toy group were less frequent, lasted longer, were more likely to be initiated by maternal following than by maternal directing of infants' attention, and more likely to be coordinated in which infants demonstrated awareness of the mothers' simultaneous attentional focus by looking at their mothers, vocalizing, or turn-taking. We further found longer joint attention durations on organizational compared to symbolic toys, which were preferred to a lesser extent by the dyads. With responsive toys, mothers were more likely to initiate joint attention by following their infants' attention. Joint attention interactions lasted longer and were more likely to be coordinated in the second half compared to the first half of the play session, suggesting that over time it became easier for the mothers and infants to settle on certain toys for more elaborate play. In sum, mothers and infants establish higher-quality joint attention with fewer toys in general and with organizational toys in particular.Language skills and mathematical competencies are argued to influence each other during development. While a relation between the development of vocabulary size and mathematical skills is already documented in the literature, this study further examines how children's ability to map a novel word to an unknown object as well as their ability to retain this word from memory may be related to their knowledge of number words. Twenty-five children were tested longitudinally (at 30 and at 36 months of age) using an eye-tracking-based fast mapping task, the Give-a-Number task, and standardized measures of vocabulary. The results reveal that children's ability to create and retain a mental representation of a novel word was related to number knowledge at 30 months, but not at 36 months while vocabulary size correlated with number knowledge only at 36 months. These results show that even specific mapping processes are initially related to the acquisition of number words and they speak for a parallelism between the development of lexical and number-concept knowledge despite their semantic and syntactic differences.<br /><br /> In Coordinated Joint Engagement (CJE), children acknowledge that they and their social partners are paying attention to the same object. The achievement of CJE, critical for healthy development, is at risk in infants with visual impairment (VI). Research on CJE in these children is limited because investigators use a child's gaze switch between social partner and object to index CJE. Research is needed that identifies CJE in children with VI using behaviors that do not require normal vision and that explores the relationship between CJE and visual function. This study aimed to (a) develop a protocol for identifying CJE in children with VI, and (b) explore the relationship between CJE and infants' visual acuity (VA) and contrast sensitivity (CS), measured with Preferential Looking (PL) techniques and Visual Evoked Potential (VEP).<br /><br /> A protocol that included 9 indices of CJE that did not require normal vision was developed to code videos of 20 infants with VI (mean age =1 year, 6 months, 27 days) and their ca VA exhibited less CJE.<br /><br /> Melanoma is a type of malignant skin cancer with high mortality, and its incidence is increasing rapidly in recent years. At present, the best treatment is surgical resection after early diagnosis. However, due to the high visual similarity between melanoma and benign melanocytic nevus, coupled with the scarcity and imbalance of data, traditional methods are difficult to achieve good recognition and detection results. Similarly, many machine learning methods have been applied to the task of skin disease detection and classification. However, the accuracy and sensitivity of the experiments are still not satisfactory. Therefore, this paper proposed a method to identify melanoma more efficiently and accurately.<br /><br /> We implemented a Mixed Skin Lesion Picture Generate method based on Mask R-CNN (MSLP-MR) to solve the problem of data imbalance. Besides, we designed a melanoma detection framework of Mask-DenseNet+ based on MSLP-MR. This method used Mask R-CNN to introduce the method of mask segmentation, and combined with the idea of ensemble learning to integrate multiple classifiers for weighted prediction. Compared with the ablation experiments, the accuracy, sensitivity and AUC of the proposed network classification are improved by 2.56%, 29.33% and 0.0345.<br /><br /> The experimental results on the ISIC dataset shown that the accuracy of the algorithm is 90.61%, the sensitivity reaches 78.00%, which is higher than the original methods; the specificity reaches 93.43%; and the AUC reaches 0.9502.<br /><br /> The method is feasible and effective, and achieves the preliminary goal of melanoma detection. It is greatly improved the detection accuracy and reached the level of visual diagnosis of doctors.<br /><br />The method is feasible and effective, and achieves the preliminary goal of melanoma detection. It is greatly improved the detection accuracy and reached the level of visual diagnosis of doctors.<br /><br /> Thrombus simulation plays an important role in many specialist areas in the field of medicine such as surgical education and training, clinical diagnosis and prediction, treatment planning, etc. Although a considerable number of methods have been developed to simulate various kinds of fluid flows, it remains a non-trivial task to effectively simulate thrombus because of its unique physiological properties in contrast to other types of fluids. To tackle this issue, this study introduces a novel method to model the formation mechanism of thrombus and its interaction with blood flow.<br /><br /> The proposed method for thrombus formation simulation mainly consists of three steps. First, we formulate the formation of thrombus as a particle-based model and obtain the fibrin concentration of the particles with a discretized form of the convection-diffusion-reaction equation; then, we calculate the velocity decay factor using the obtained fibrin concentration. Finally, the formation of thrombus can be simulated by applying the velocity decay factor on particles.