An unusual timing for symptomatic chest pain in an adult chest wall myofibroma: a case report

INTRODUCTION: Myofibromas are benign mesenchymal neoplasms that can present as solitary and multicentric lesions. They can occur in several locations and can occur at any age from neonates to elderly patients. However, most of the lesions are found in neonates and babies. It rarely occurs in adults. CASE PRESENTATION: A 29-year-old Taiwanese man presented with persistent dull chest pain in his right lateral chest wall for 2 weeks. A chest X-ray showed a faint patchy opacity over the periphery of his right upper lung zone. Computed tomography and magnetic resonance imaging showed a lobulated mass at the intercostal space between his right fifth and sixth ribs with contrast enhancement and bone invasion. Malignancy could not be excluded. A percutaneous needle aspiration biopsy failed due to technique issues, so he underwent a thoracotomy and the tumor was excised with Marlex mesh repairs for the thoracic defect. Pathology confirmed a myofibroma without malignancy. He recovered uneventfully and no local recurrence was detected at the 1-year follow-up examination. CONCLUSIONS: Chest wall myofibroma presenting with chest pain has never been reported in adults. It is a challenge to differentiate myofibroma from malignancy in chest wall preoperatively, such as seen in our patient. To the best of our knowledge, this has not been previously reported in the scientific literature. Although myofibroma rarely occurs in the chest wall and adults, it must be suspected in any chest wall tumor presenting with chest pain

Spectral Analysis for Semantic Segmentation with Applications on Feature Truncation and Weak Annotation

We propose spectral analysis to investigate the correlation between the accuracy and the resolution of segmentation maps for semantic segmentation. The current networks predict segmentation maps on the down-sampled grid of images to alleviate the computational cost. Moreover, these networks can be trained by weak annotations that utilize only the coarse contour of segmentation maps. Despite the successful achievement of these works utilizing the low-frequency information of segmentation maps, however, the accuracy of resultant segmentation maps may also be degraded in the regions near object boundaries. It is yet unclear for a theoretical guideline to determine an optimal down-sampled grid to strike the balance between the cost and the accuracy of segmentation. We analyze the objective function (cross-entropy) and network back-propagation process in frequency domain. We discover that cross-entropy and key features of CNN are mainly contributed by the low-frequency components of segmentation maps. This further provides us quantitative results to determine the efficacy of down-sampled grid of segmentation maps. The analysis is then validated on the two applications: the feature truncation method and the block-wise annotation that limit the high-frequency components of the CNN features and annotation, respectively. The results agree with our analysis. Thus the success of the existing work utilizing low-frequency information of segmentation maps now has theoretical foundation.Comment: 21 page

Learning satisfaction of undergraduates in single-sex-dominated academic fields in Taiwan

AbstractThe present study investigated relationships between undergraduates’ learning satisfaction, academic identity, self-esteem and feeling of depression and loneliness in Taiwan. Data were from a national survey in Taiwan. Participants were 15,706 third-year undergraduates (8719 female, 6987 male). The results showed that, after controlling for undergraduates’ academic performance and attitudes toward university and department, (1) learning satisfaction of females in male-dominant fields was negatively correlated with their feeling of depression, (2) learning satisfaction of males in female-dominant fields was positively correlated with their academic identity and self-esteem, and (3) learning satisfaction of undergraduates in non-dominated fields was positively correlated with their academic identity and self-esteem but also negatively correlated with their feelings of depression

BiRA-Net: Bilinear Attention Net for Diabetic Retinopathy Grading

Diabetic retinopathy (DR) is a common retinal disease that leads to blindness. For diagnosis purposes, DR image grading aims to provide automatic DR grade classification, which is not addressed in conventional research methods of binary DR image classification. Small objects in the eye images, like lesions and microaneurysms, are essential to DR grading in medical imaging, but they could easily be influenced by other objects. To address these challenges, we propose a new deep learning architecture, called BiRA-Net, which combines the attention model for feature extraction and bilinear model for fine-grained classification. Furthermore, in considering the distance between different grades of different DR categories, we propose a new loss function, called grading loss, which leads to improved training convergence of the proposed approach. Experimental results are provided to demonstrate the superior performance of the proposed approach.Comment: Accepted at ICIP 201

What can the structure of the palmprint tell us?

Since the olden days, palmistry has been used to foretell a person?s character traits and fate. The study of various lines and mounts of the palm helps the reader predict the person?s future. As research on palmprints progresses, there had been more uses of it being discovered, such as health prediction. These researches surface the need to further identify and make use of the mysteries of the palm. This paper aims to understand the different researches and its methods in disseminating the information for fortune telling and health prediction palmistry. With these understandings, the possibility of creating a database and query system for fortune telling and health prediction information is explored

Effect on Spasticity After Performance of Dynamic-Repeated-Passive Ankle Joint Motion Exercise in Chronic Stroke Patients

Spasticity associated with abnormal muscle tone is a common motor disorder following stroke, and the spastic ankle may affect ambulatory function. The purpose of this study was to investigate the short-term effect of dynamic-repeated-passive ankle movements with weight loading on ambulatory function and spastic hypertonia of chronic stroke patients. In this study, 12 chronic stroke patients with ankle spasticity and inefficient ambulatory ability were enrolled. Stretching of the plantar-flexors of the ankle in the standing position for 15 minutes was performed passively by a constant-speed and electrically powered device. The following evaluations were done before and immediately after the dynamic-repeated-passive ankle movements. Spastic hypertonia was assessed by the Modified Ashworth Scale (MAS; range, 0–4), Achilles tendon reflexes test (DTR; range, 0–4), and ankle clonus (range, 0–5). Improvement in ambulatory ability was determined by the timed up-and-go test (TUG), the 10-minute walking test, and cadence (steps/minute). In addition, subjective experience of the influence of ankle spasticity on ambulation was scored by visual analog scale (VAS). Subjective satisfaction with the therapeutic effect of spasticity reduction was evaluated by a five-point questionnaire (1 = very poor, 2 = poor, 3 = acceptable, 4 = good, 5 = very good). By comparison of the results before and after intervention, these 12 chronic stroke patients presented significant reduction in MAS and VAS for ankle spasticity, the time for TUG and 10-minute walking speed (p < 0.01). The cadence also increased significantly (p < 0.05). In addition, subjective satisfaction with the short-term therapeutic effect was mainly good (ranging from acceptable to very good). In conclusion, 15 minutes of dynamic-repeated-passive ankle joint motion exercise with weight loading in the standing position by this simple constant-speed machine is effective in reducing ankle spasticity and improving ambulatory ability