Underachievers are an objective dissimilated group in the learning process. Math underachievers are a practical problem which should be addressed by present math educators. Through field survey and upon analysis of individual characteristics of underachievers from multiple perspectives of teachers, family education and students, a targeted conversion strategy is formulated. With focuses on teaching and learning method, the strategies for conversion of math underachievers in junior high schools are explored and summarized, followed by practical discussion on individual cases.
Tuberous sclerosis complex (TSC) is a multi-system genetic disorder. Most patients have germline mutations in TSC1 or TSC2 but, 10%–15% patients do not have TSC1/TSC2 mutations detected on routine clinical genetic testing. We investigated the contribution of low-level mosaic TSC1/TSC2 mutations in unsolved sporadic patients and families with TSC. Thirty-one sporadic TSC patients negative on routine testing and eight families with suspected parental mosaicism were sequenced using deep panel sequencing followed by droplet digital polymerase chain reaction. Pathogenic variants were found in 22/31 (71%) unsolved sporadic patients, 16 were mosaic (median variant allele fraction [VAF] 6.8% in blood) and 6 had missed germline mutations. Parental mosaicism was detected in 5/8 families (median VAF 1% in blood). Clinical testing laboratories typically only report pathogenic variants with allele fractions above 10%. Our findings highlight the critical need to change laboratory practice by implementing higher sensitivity assays to improve diagnostic yield, inform patient management and guide reproductive counseling.
The problem of single image rain removal has attracted tremendous attention as the blurry images caused by rain streaks can degrade the performance of many computer vision algorithms. Although deep learning based de-raining methods have achieved a significant success, there are still unresolved issues in terms of the performance. In this work, we propose a novel recurrent attention dense network (RADN) for single image de-raining. In RADN, a region-level attention module is first utilized to identify rain streaks regions for the subsequent removal task. As rain streaks have different sizes and shapes, a modified densely connected convolutional network (DenseNet) with dilation convolutions and reduced channels is developed for an effective feature representation. The rain streaks are removed stage by stage and a Gate Recurrent Unit (GRU) is incorporated to deliver useful information from previous stages to later stages for a better performance. Qualitative and quantitative evaluations on both synthetic and real-world datasets demonstrate that the proposed approach can achieve a remarkable performance in comparison with the state-of-the-art methods for single image rain removal.
Blurred images caused by rain streaks can degrade the performance of many computer vision algorithms. Therefore, the single-image rain removal problem has attracted tremendous interest. Although deep learning-based deraining methods have made significant progress, there are still many issues to be addressed in terms of improving the performance. We propose a recursive modified dense network for single-image deraining. As rain streaks have different sizes and shapes, contextual information is very important for rain removal. We use a dense network to extract image features and modify the network by removing all batch normalization layers. A simple deep network cannot completely remove rain streaks from the image, while increasing the network depth will make the computing more complicated. We take a dense block with loops to remove rain streaks stage by stage. Extensive experiments on both synthetic and real-world datasets show that the proposed method can achieve competitive results in comparison with the state-of-the-art methods for single-image rain removal.
Fever is an important clinical manifestation of new coronavirus pneumonia. In public health emergencies, it is necessary to start fever screening to control the rapid spread of influenza. The measurement and calibration technology of infrared body temperature screening instrument has been developed in recent years, and there are still shortcomings in the field use of infrared screening instrument. In order to fully understand the performance parameters of infrared screening instrument, further improve the performance of equipment and establish a unified reference standards. This study analysis and investigates the test results and performance parameters of multiple screening machines, improving the standardization and effectiveness of fever screening. The results indicate that blackbody can effectively reduce the error, avoid the appearance of larger error, large temperature fluctuation, and restrain the phenomenon of temperature drift to a certain extent.
Multi-contrast magnetic resonance imaging (MRI) is wildly applied to identify tuberous sclerosis complex (TSC) children in a clinic. In this work, a deep convolutional neural network with multi-contrast MRI is proposed to diagnose pediatric TSC. Firstly, by combining T2W and FLAIR images, a new synthesis modality named FLAIR
In order to study the influence by non-uniformity of illumination on testing performance of optical measurement system, the causes of non-uniformity were analyzed. We constructed the relationship model between interval distance of LED light source and illumination. The distribution of illumination with different intervals of LED were simulated. Then relationship model between viewing-field angle at object plane of optical system and illumination was established. Influence of viewing-field angle at object plane on distribution of illumination was studied. The experimental results indicate that non-uniform light source and wide viewing-field angle are two main causes for non-uniformity in optical imaging system. Larger interval distance of LED or viewing-field angle will result in non-uniformity of illumination.
Progressive myoclonic epilepsy (PME) is a group of rare diseases characterized by progressive myoclonus, cognitive impairment, ataxia, and other neurologic deficits. PME has high genetic heterogeneity, and more than 40 genes are reportedly associated with this disorder. SEMA6B encodes a member of the semaphorin family and was first reported to cause PME in 2020. Herein, we present a rare case of PME due to a novel SEMA6B gene mutation in a 6-year-old boy born to healthy non-consanguineous Chinese parents. His developmental milestones were delayed, and he developed recurrent atonic seizures and myoclonic seizures without fever at 3 years and 11 months of age. He experienced recurrent myoclonic seizures, non-convulsive status epilepticus (NCSE), atonic seizures, and atypical absence seizures during the last 2 years. At different time points since onset, valproic acid, levetiracetam, piracetam, and clobazam were used to control the intractable seizures. Notably, NCSE was controlled by a combination of piracetam with clobazam and valproic acid instead of intravenous infusion of midazolam and phenobarbital. Due to the limited number of cases reported to date, the clinical description of our case provides a better understanding of the genotype–phenotype correlations associated with PME and indicate that piracetam may be effective against NCSE in patients with SEMA6B -related PME.
The linear CCD camera which applies to micro-image measuring system must have been calibrated before working. The separate calibration method of linear CCD camera's internal and external orientation parameters is proposed in the paper. The imaging model of the linear camera has been studied, and the equal parallel lines are used to calibrate internal parameters of camera in the experiment where the industrial environment is simulated. In addition, parallel lines and tri-forked stencil are used to calibrate external orientation parameters in the industrial field, such as the attitude angel. The separate calibration method has reduced the calibration task in the industry, and the calibration template is easy to make. The results show that the testing accuracy improves greatly by using the calibrated camera for measuring the gauge, and the calibrated camera can be easily applied to other measurement environment.
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