Who Matters, Teacher or Parents?

Published in Tsinghua Journal of Education, the study examines the influence of parents and teachers on students' academic performance in Chinese through a survey of more than 4,000 students in grades 3 to 6. Based on the achievement goal theory, this study constructs a theoretical model of the relationship between students' perceived achievement goals and their academic achievements in Chinese and takes learning style as a mediator variable to explore the influence of students' perceived achievement goals from teachers and parents on their academic achievements in Chinese

A holistic model to infer mathematics performance: the interrelated impact of student, family and school context variables

The present study aims at exploring predictors influencing mathematics performance. In particular, the study focuses on internal students' characteristics (gender, age, metacognitive experience, mathematics self-efficacy) and external contextual factors (GDP of school location, parents' educational level, teachers' educational level, and teacher beliefs). A sample of 1749 students and 91 teachers from Chinese primary schools were involved in the study. Path analysis was used to test the direct and indirect relations between the predictors and mathematics performance. Results reveal that a large proportion of mathematics performance can be directly predicted from students' metacognitive experiences. In addition, other student characteristics and contextual variables influence mathematics performance in direct or indirect ways

Curriculum sequencing and the acquisition of clock reading skills among Chinese and Flemish children

The present study reexamines the adoption of clock reading skills in the primary mathematics curriculum. In many Western countries, the mathematics curriculum adopts a number of age-related stages for teaching clock reading skills, that were defined by early research (e.g., Friedman & laycock, 1989; Piaget, 1969). Through a comparison of Flemish and Chinese student’s clock reading abilities, the current study examines whether these age-related stages are a solid base for teaching clock reading skills. By means of both quantitative (ANOVA’s) and qualitative (textbook analysis) methods, the present study indicates that the alternative way of teaching clock reading skills in China, i.e., at the age of six instead of staggered out over several grades, results in a two years earlier acquisition of clock reading skills. This indicates that the previously age-related stages in children’s acquisition of clock reading are not universal, nor the most effective way to teach these skills to young children

Inverse problems in medical ultrasound images - applications to image deconvolution, segmentation and super-resolution

In the field of medical image analysis, ultrasound is a core imaging modality employed due to its real time and easy-to-use nature, its non-ionizing and low cost characteristics. Ultrasound imaging is used in numerous clinical applications, such as fetus monitoring, diagnosis of cardiac diseases, flow estimation, etc. Classical applications in ultrasound imaging involve tissue characterization, tissue motion estimation or image quality enhancement (contrast, resolution, signal to noise ratio). However, one of the major problems with ultrasound images, is the presence of noise, having the form of a granular pattern, called speckle. The speckle noise in ultrasound images leads to the relative poor image qualities compared with other medical image modalities, which limits the applications of medical ultrasound imaging. In order to better understand and analyze ultrasound images, several device-based techniques have been developed during last 20 years. The object of this PhD thesis is to propose new image processing methods allowing us to improve ultrasound image quality using postprocessing techniques. First, we propose a Bayesian method for joint deconvolution and segmentation of ultrasound images based on their tight relationship. The problem is formulated as an inverse problem that is solved within a Bayesian framework. Due to the intractability of the posterior distribution associated with the proposed Bayesian model, we investigate a Markov chain Monte Carlo (MCMC) technique which generates samples distributed according to the posterior and use these samples to build estimators of the ultrasound image. In a second step, we propose a fast single image super-resolution framework using a new analytical solution to the l2-l2 problems (i.e., $\ell_2$-norm regularized quadratic problems), which is applicable for both medical ultrasound images and piecewise/ natural images. In a third step, blind deconvolution of ultrasound images is studied by considering the following two strategies: i) A Gaussian prior for the PSF is proposed in a Bayesian framework. ii) An alternating optimization method is explored for blind deconvolution of ultrasound

Ultrasound compressive deconvolution with lp-norm prior

International audienceIt has been recently shown that compressive sampling is an interesting perspective for fast ultrasound imaging. This paper addresses the problem of compressive deconvolution for ultrasound imaging systems using an assumption of generalized Gaussian distributed tissue reflectivity function. The benefit of compressive deconvolution is the joint volume reduction of the acquired data and the image resolution improvement. The main contribution of this work is to apply the framework of compressive deconvolution on ultrasound imaging and to propose a novel ℓp-norm (1 ≤ p ≤ 2) algorithm based on Alternating Direction Method of Multipliers. The performance of the proposed algorithm is tested on simulated data and compared with those obtained by a more intuitive sequential compressive deconvolution method

Joint Segmentation and Deconvolution of Ultrasound Images Using a Hierarchical Bayesian Model Based on GeneralizedGaussian Priors

International audienceThis paper proposes a joint segmentation and deconvolution Bayesian method for medical ultrasound (US) images. Contrary to piecewise homogeneous images, US images exhibit heavy characteristic speckle patterns correlated with the tissue structures. The generalized Gaussian distribution (GGD) has been shown to be one of the most relevant distributions for characterizing the speckle in US images. Thus, we propose a GGD-Potts model defined by a label map coupling US image segmentation and deconvolution. The Bayesian estimators of the unknown model parameters, including the US image, the label map, and all the hyperparameters are difficult to be expressed in a closed form. Thus, we investigate a Gibbs sampler to generate samples distributed according to the posterior of interest. These generated samples are finally used to compute the Bayesian estimators of the unknown parameters. The performance of the proposed Bayesian model is compared with the existing approaches via several experiments conducted on realistic synthetic data and in vivo US images

Joint Bayesian Deconvolution And Point Spread Function Estimation For Ultrasound Imaging

International audienceThis paper addresses the problem of blind deconvolution for ultrasound images within a Bayesian framework. The prior of the unknown ultrasound image to be estimated is assumed to be a product of generalized Gaussian distributions. The point spread function of the system is also assumed to be unknown and is assigned a Gaussian prior distribution. These priors are combined with the likelihood function to build the joint posterior distribution of the image and PSF. However, it is difficult to derive closed-form expressions of the Bayesian estimators associated with this posterior. Thus, this paper proposes to build estimators of the unknown model parameters from samples generated according to the model posterior using a hybrid Gibbs sampler. Simulation results performed on synthetic data allow the performance of the proposed algorithm to be appreciated

Combustion Catalyst: Nano‐Fe2O3 and Nano‐Thermite Al/ Fe2O3 with Different Shapes

In order to enable the energetic materials to possess a more powerful performance, adding combustion catalysts is a quite effective method. Granular, oval, and polyhedral Fe2O3 particles have been prepared by the hydrothermal method and used to fabricate Al/Fe2O3 thermites. All the Fe2O3 and Al/Fe2O3 thermite samples were characterized using a combination of experimental techniques including scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), X‐ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), transmission electron microscope (TEM), and high‐resolution TEM (HRTEM). The non‐isothermal decomposition kinetics of the composites and nitrocellulose (NC) can be modeled by the Avrami‐Erofeev equation f(α)=3(1–α)[–ln(1–α)]1/3/2 in differential form. Through the thermogravimetric analysis infrared (TG‐IR) analysis of decomposition processes and products, it is speculated that Fe2O3 and Al/Fe2O3 can effectively accelerate the thermal decomposition reaction rate of NC by promoting the O‐NO2 bond cleavage. Adding oxides or thermites can distinctly increase the burning rate, decrease the burning rate pressure exponent, increase the flame temperature, and improve the combustion wave structures of the ammonium perchlorate/hydroxyl‐terminated polybutadiene (AP/HTPB) propellants. Among the three studied, different shapes of Fe2O3, the granular Fe2O3, and its corresponding thermites (Al/Fe2O3(H)) exhibit the highest burning rate due to larger surface area associated with smaller particle size. Moreover, Al/Fe2O3(H) thermites have more effective combustion‐supporting ability for AP/HTPB propellants than Fe2O3 structures and the other two as‐prepared Al/Fe2O3 thermites

The intestinal metal transporter ZIP14 maintains systemic manganese homeostasis

ZIP14 (encoded by the solute carrier 39 family member 14 (SLC39A14) gene) is a manganese transporter that is abundantly expressed in the liver and small intestine. Loss-of-function mutations in SLC39A14 cause severe hypermanganesemia. Because the liver is regarded as the main regulatory organ involved in manganese homeostasis, impaired hepatic manganese uptake for subsequent biliary excretion has been proposed as the underlying disease mechanism. However, liver-specific Zip14 KO mice exhibit decreased manganese only in the liver and do not develop manganese accumulation in other tissues under normal conditions. This suggests that impaired hepatobiliary excretion is not the primary cause for manganese overload observed in individuals lacking functional ZIP14. We therefore hypothesized that increased intestinal manganese absorption could induce manganese hyperaccumulation when ZIP14 is inactivated. To elucidate the role of ZIP14 in manganese absorption, here we used CaCo-2 Transwell cultures as a model system for intestinal epithelia. The generation of a ZIP14-deficient CaCo-2 cell line enabled the identification of ZIP14 as the major transporter mediating basolateral manganese uptake in enterocytes. Lack of ZIP14 severely impaired basolateral-to-apical (secretory) manganese transport and strongly enhanced manganese transport in the apical-to-basolateral (absorptive) direction. Mechanistic studies provided evidence that ZIP14 restricts manganese transport in the absorptive direction via direct basolateral reuptake of freshly absorbed manganese. In support of such function of intestinal ZIP14 in vivo, manganese levels in the livers and brains of intestine-specific Zip14 KO mice were significantly elevated. Our findings highlight the importance of intestinal ZIP14 in regulating systemic manganese homeostasis.National Institutes of Health [R00DK104066]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]