Learning Methodologies to Generate Kernel-Learning-Based Image Downscaler for Arbitrary Scaling Factors.

Displays and content have various resolutions and aspect ratios, requiring an image downscaler to adaptively reduce the image resolution. However, research on downscaling has garnered less attention than upscaling, including super-resolution. In practical display systems, simple interpolation, such as a bicubic filter that cannot preserve image details well, is still widely used for image downscaling rather than frame optimization-based or learning-based methods because of following reasons: frame optimization-based methods can effectively preserve image details after downscaling but are difficult to implement due to hardware costs. Learning-based methods have not been developed because defining a target downscaled image for training is difficult and training all downscaling factors is impossible. We propose a novel kernel-learning-based image downscaler to improve detail-preservation quality while supporting arbitrary downscaling factors using simple linear mapping. For this, a method to produce the ideal target downscaling result considering aliasing artifacts and detail preservation after downscaling is proposed. Then, we propose a training technique using the positional relationship between input and output pixels and a hierarchical region analysis to reproduce target images through simple kernel-based linear mapping. Lastly, a kernel-sharing technique is proposed to generate downscaling results for downscaling factors using a minimum number of trained kernels. In the simulation results, the proposed method demonstrated excellent edge preservation by improving the recall, precision, and F1 score, measuring the edge consistency between input and downscaled images, by up to 0.141, 0.079, 0.053, respectively, compared to benchmark methods. In a paired-comparison-based user study, the proposed method obtained the highest preference among benchmark methods using simple operations.

A Generative Adversarial Network-Based Image Denoiser Controlling Heterogeneous Losses.

We propose a novel generative adversarial network (GAN)-based image denoising method that utilizes heterogeneous losses. In order to improve the restoration quality of the structural information of the generator, the heterogeneous losses, including the structural loss in addition to the conventional mean squared error (MSE)-based loss, are used to train the generator. To maximize the improvements brought on by the heterogeneous losses, the strength of the structural loss is adaptively adjusted by the discriminator for each input patch. In addition, a depth wise separable convolution-based module that utilizes the dilated convolution and symmetric skip connection is used for the proposed GAN so as to reduce the computational complexity while providing improved denoising quality compared to the convolutional neural network (CNN) denoiser. The experiments showed that the proposed method improved visual information fidelity and feature similarity index values by up to 0.027 and 0.008, respectively, compared to the existing CNN denoiser.

Novel Calcium Zirconate Silicate Cement Biomineralize and Seal Root Canals.

This study evaluated the sealing ability of gutta-percha (GP) with a calcium silicate-based sealer and a novel calcium zirconate containing calcium silicate cement (ZC). The root canals of the extracted premolars were prepared, which were then randomly allocated to three experimental groups (12 root canals per group) for obturation by continuous wave of condensation with the GP and AH 26 sealer (CW); obturation using a single GP with a calcium silicate-based EndoSequence BC sealer (SC); or obturation with ZC. The roots were inserted into sterile Eppendorf tubes, which were inoculated coronally with Porphyromonas gingivalis. The amount of endotoxin leakage into the apical reservoirs were measured using the Limulus Amebocyte Lysate (LAL) assay over 21 days, with comparisons made using one-way ANOVA and Scheffe's tests (α = 0.05). After 21 days, 75% of the canals that had been obturated by SC, 50% of those obturated by CW and 42% of those obturated by ZC showed endotoxin leakage. The amount of leakage was higher in the SC canals than in the CW (p = 0.031) or ZC (p = 0.03) canals, although there was no significant difference in the amount of leakage for CW and ZC (p > 0.05). X-ray diffraction revealed the presence of tricalcium silicate (Ca3SiO5) and calcium zirconate (CaZrO3) in the synthesized ZC. Scanning electron microscopy revealed mineralized precipitates on the dentin of canals obturated by ZC. The novel calcium zirconate silicate cement appears to promote biomineralization and seal root canals at least as effectively as the conventional sealer.

Extremely low-frequency magnetic fields modulate nitric oxide signaling in rat brain.

Our previous study has shown that an extremely low-frequency magnetic field (ELF-MF) induces nitric oxide (NO) synthesis by Ca(2+) -dependent NO synthase (NOS) in rat brain. The present study was designed to confirm that ELF-MF affects neuronal NOS (nNOS) in several brain regions and to investigate the correlation between NO and nNOS activation. The exposure of rats to a 2 mT, 60 Hz ELF-MF for 5 days resulted in increases of NO levels in parallel with cGMP elevations in the cerebral cortex, striatum, and hippocampus. Cresyl violet staining and electron microscopic evaluation revealed that there were no significant differences in the morphology and number of neurons in the cerebral cortex, striatum, and hippocampus. Differently, the numbers of nNOS-immunoreactive (IR) neurons were significantly increased in those cerebral areas in ELF-MF-exposed rats. These data suggest that the increase in NO could be due to the increased expression and activation of nNOS in cells. Based on NO signaling in physiological and pathological states, ELF-MF created by electric power systems may induce various physiological changes in modern life.

Extraskeletal Ewing's sarcoma of the head and neck presenting as blindness.

Extraskeletal Ewing's sarcoma is rarely found in the head and neck regions. We report an unusual case of extraskeletal Ewing's Sarcoma of the parapharynx region in a 49-year-old man who presented with blindness. MRI examination showed marked enhancement of tumor thrombosis involving the superior sagittal sinus, straight sinus, transverse sinus, sigmoid sinus, and internal jugular vein. The final diagnosis was extraskeletal Ewing's sarcoma after biopsy of the internal jugular vein thrombosis by histopathological evaluation and immunohistochemical assay. In addition, the patient was diagnosed as having adenocarcinoma of the rectum by biopsy of the rectal mass. The patient was treated with systemic chemotherapy and showed improved response with durable remission. The patient's visual acuity, however, did not improve.

High incidence of mucosa-associated lymphoid tissue in primary thyroid lymphoma: a clinicopathologic study of 18 cases in the Korean population.

The present study aimed to evaluate the clinicopathologic features and treatment outcomes of patients with primary thyroid lymphoma (PTL). The patients included 14 women and four men with a median age of 50 years (range 31 - 82 years). Thirteen cases involved the thyroid alone (stage IE) and five cases involved the regional lymph nodes (stage IIE). Histopathologic studies revealed marginal zone B-cell lymphoma of mucosa-associated lymphoid tissue (MALT) in 13 patients and diffuse large B-cell lymphoma (DLBCL) in three patients. The other two patients showed features of both MALT and DLBCL. Surgery and chemotherapy with or without radiotherapy were performed. All patients achieved complete remission. All 18 patients were alive with a median follow-up period of 55 months. The prognosis of patients with primary thyroid lymphoma appears to be favourable.