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This study investigated the cognitive and social processes through which high school students acquire the differential concepts through communication in a dynamic geometry environment through some cases. Additionally, we observed how a dynamic geometry environment affects these processes. To achieve this objective, eight students were recruited by using the pre-test results and divided into an experimental group and a control group. The learning environment for the two groups was designed to be the same except for jointly manipulating Geogebra on the laptop in the experimental group. Students' discourse was analyzed using an analysis framework that applied both Piaget's (1959) linguistic categories and Rutherford's (2011) neo-Piagetian model. We found that the dynamic geometry environment improved communication among students and their achievement levels. In particular, graphic and dynamic representations created by dragging stimulated students' interest and increased communication among them. Although the quality of communication was somewhat different in the discourse analysis of the two groups, each participant's role was confirmed in the co-construction of knowledge among all cases of eight students. We expect that precise verbal information on various representations of mathematical content in the process of understanding the concepts of students could be an opportunity to prepare educational environments corresponding thereto.

The present study discusses a pilot intervention for youth in a predominantly Latinx rural community in the U.S. The intervention incorporated multimodal creative activities into the social cognitive career theory-based healthcare career program. Participants (N = 75) were assessed for healthcare career self-efficacy, outcome expectations, and interests (pre-/post-intervention). Their healthcare career task self-efficacy and interests scores significantly increased overall. By race/ethnicity groups, however, only White students reported an increase in healthcare interests, and only students of color an increase in healthcare career task self-efficacy. This provides preliminary evidence for the effectiveness of the proposed intervention. Implications for services and research are discussed.

Although light microscopy (LM) images are widely used to observe various bodily tissues, including salivary glands, reaching a satisfactory spatial resolution in the final images remains a major challenge. The objective of this study was to model a robust blind deconvolution algorithm using the extracted structure and analyze its applicability to LM images. Given LM images of the salivary glands, the proposed robust blind deconvolution method performs non-blind deconvolution after estimating the structural map and kernel of each image. To demonstrate the usefulness of the proposed algorithm for LM images, the perceptual sharpness index (PSI), Blanchet's sharpness index (BSI), and natural image quality evaluator (NIQE) were used as evaluation metrics. We demonstrated that when the proposed algorithm was applied to salivary gland LM images, the PSI and BSI were improved by 7.95% and 7.44%, respectively, compared with those of the conventional TV-based algorithm. When the proposed algorithm was applied to an LM image, we confirmed that the NIQE value was similar to that of a low-resolution image. In conclusion, the proposed robust blind deconvolution algorithm is highly applicable to salivary gland LM images, and we expect that further applications will become possible. [ABSTRACT FROM AUTHOR]

Most previous studies on orofacial muscle strength have focused on older adults with conditions associated with sensorimotor deficits, such as stroke. However, the modifiable oral health factors that directly impact orofacial muscle strength and swallowing ability in healthy older adults remain unexplored. This pilot study explored the potential factors associated with orofacial muscle strength, particularly oral health conditions, in 70 healthy adults aged ≥65 years living independently without any diseases that cause dysphagia or sensorimotor deficits. The Iowa Oral Performance Instrument (IOPI) was used to assess orofacial muscle strength (tongue elevation, and cheek and lip compression). Statistical analyses were conducted using an independent t-test, one-way ANOVA, and multivariate linear regression. In the final regression models after adjustment, older age and fewer remaining teeth were significantly associated with reduced tongue and cheek strengths (p < 0.05). Socio-demographic factors, such as age, and oral health conditions, such as discomfort in pronunciation or mastication due to oral problems, poor self-rated oral health, and reduced salivary flow, were associated with tongue, cheek, and lip muscle strengths (p < 0.05). Early active oral health interventions can help prevent a decline in orofacial muscle strength in healthy older adults. [ABSTRACT FROM AUTHOR]

Speckle noise in ultrasound images (UIs) significantly reduces the accuracy of disease diagnosis. The aim of this study was to quantitatively evaluate its feasibility in salivary gland ultrasound imaging by modeling the adaptive non-local means (NLM) algorithm. UIs were obtained using an open-source device provided by SonoSkills and FUJIFILM Healthcare Europe. The adaptive NLM algorithm automates optimization by modeling the isotropic search window, eliminating the need for manual configuration in conventional NLM methods. The coefficient of variation (COV), contrast-to-noise ratio (CNR), and edge rise distance (ERD) were used as quantitative evaluation parameters. UIs of the salivary glands revealed evident visualization of the internal echo shape of the malignant tumor and calcification line using the adaptive NLM algorithm. Improved COV and CNR results (approximately 4.62 and 2.15 times, respectively) compared with noisy images were achieved. Additionally, when the adaptive NLM algorithm was applied to the UIs of patients with salivary gland sialolithiasis, the noisy images and ERD values were calculated almost similarly. In conclusion, this study demonstrated the applicability of the adaptive NLM algorithm in optimizing search window parameters for salivary gland UIs. [ABSTRACT FROM AUTHOR]

Noise and blurring in light microscope images are representative factors that affect accurate identification of cellular and subcellular structures in biological research. In this study, a method for l1-norm-based blind deconvolution after noise reduction with non-subsampled contourlet transform (NSCT) was designed and applied to a light microscope image to analyze its feasibility. The designed NSCT-based algorithm first separated the low- and high-frequency components. Then, the restored microscope image and the deblurred and denoised images were compared and evaluated. In both the simulations and experiments, the average coefficient of variation (COV) value in the image using the proposed NSCT-based algorithm showed similar values compared to the denoised image; moreover, it significantly improved the results compared with that of the degraded image. In particular, we confirmed that the restored image in the experiment improved the COV by approximately 2.52 times compared with the deblurred image, and the NSCT-based proposed algorithm showed the best performance in both the peak signal-to-noise ratio and edge preservation index in the simulation. In conclusion, the proposed algorithm was successfully modeled, and the applicability of the proposed method in light microscope images was proved based on various quantitative evaluation indices. [ABSTRACT FROM AUTHOR]