New dual method for elastica regularization.

The Euler's elastica energy regularizer has been widely used in image processing and computer vision tasks. However, finding a fast and simple solver for the term remains challenging. In this paper, we propose a new dual method to simplify the solution. Classical fast solutions transform the complex optimization problem into simpler subproblems, but introduce many parameters and split operators in the process. Hence, we propose a new dual algorithm to maintain the constraint exactly, while using only one dual parameter to transform the problem into its alternate optimization form. The proposed dual method can be easily applied to level-set-based segmentation models that contain the Euler's elastic term. Lastly, we demonstrate the performance of the proposed method on both synthetic and real images in tasks image processing tasks, i.e. denoising, inpainting, and segmentation, as well as compare to the Augmented Lagrangian method (ALM) on the aforementioned tasks.

Application of Inertial Measurement Units and Machine Learning Classification in Cerebral Palsy: Randomized Controlled Trial.

BACKGROUND: Cerebral palsy (CP) is a physical disability that affects movement and posture. Approximately 17 million people worldwide and 34,000 people in Australia are living with CP. In clinical and kinematic research, goniometers and inclinometers are the most commonly used clinical tools to measure joint angles and positions in children with CP. OBJECTIVE: This paper presents collaborative research between the School of Electrical Engineering, Computing and Mathematical Sciences at Curtin University and a team of clinicians in a multicenter randomized controlled trial involving children with CP. This study aims to develop a digital solution for mass data collection using inertial measurement units (IMUs) and the application of machine learning (ML) to classify the movement features associated with CP to determine the effectiveness of therapy. The results were calculated without the need to measure Euler, quaternion, and joint measurement calculation, reducing the time required to classify the data. METHODS: Custom IMUs were developed to record the usual wrist movements of participants in 2 age groups. The first age group consisted of participants approaching 3 years of age, and the second age group consisted of participants approaching 15 years of age. Both groups consisted of participants with and without CP. The IMU data were used to calculate the joint angle of the wrist movement and determine the range of motion. A total of 9 different ML algorithms were used to classify the movement features associated with CP. This classification can also confirm if the current treatment (in this case, the use of wrist extension) is effective. RESULTS: Upon completion of the project, the wrist joint angle was successfully calculated and validated against Vicon motion capture. In addition, the CP movement was classified as a feature using ML on raw IMU data. The Random Forrest algorithm achieved the highest accuracy of 87.75% for the age range approaching 15 years, and C4.5 decision tree achieved the highest accuracy of 89.39% for the age range approaching 3 years. CONCLUSIONS: Anecdotal feedback from Minimising Impairment Trial researchers was positive about the potential for IMUs to contribute accurate data about active range of motion, especially in children, for whom goniometric methods are challenging. There may also be potential to use IMUs for continued monitoring of hand movements throughout the day. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12614001276640, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367398; ANZCTR ACTRN12614001275651, https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=367422.

A comparative study of phytoplankton community structure and biomass determined by HPLC-CHEMTAX and microscopic methods during summer and autumn in the central Bohai Sea, China.

As the largest inland sea of China, the Bohai Sea has confronted significant environmental changes in recent decades, and a shift of phytoplankton community from diatoms to dinoflagellates was observed by microscopic method in previous studies. However, the counting of some small-sized non-diatoms (e.g., flagellates and cyanobacteria) have long been neglected due to the limitation of this method. In this study, we measured the phytoplankton community structure and abundance in the central Bohai Sea in summer and autumn of 2015 by employing both microscopic method and high-performance liquid chromatography (HPLC) pigments - CHEMTAX analysis. The results of microscopic counting showed that the phytoplankton community was characterized by diatoms, dinoflagellates, and chrysophytes, which contained a total of 107 species. Dinoflagellates and diatoms co-dominated in summer while the latter became the dominant group in autumn. Compared with microscopic counting, CHEMTAX analysis allowed identification of a larger number of phytoplankton groups (including 8 phyla). The results of CHEMTAX analysis showed that besides diatoms and dinoflagellates, the small-sized non-diatoms (i.e., flagellates and cyanobacteria) also played an important role. Diatoms and cyanobacteria dominated the total Chl a (contributing 32.5% and 17.1%, respectively), followed by cryptophytes, dinoflagellates, and prasinophytes in the summer. A short-term summer to autumn variability of phytoplankton abundance and community was observed. Temperature and nutrient availability affected the succession of the phytoplankton community from diatoms and non-diatoms co-dominance in the summer to absolute diatoms dominance in the autumn. A direct comparison of algal cell abundance and CHEMTAX biomass showed that a significant positive correlation was observed only for dinoflagellates (P < 0.01) in the autumn. Our work provides some basic information on the dynamics of small-sized flagellates and cyanobacteria in this area, and also suggests that a combination of both the methods is needed in future investigations to better understand the current status as well as the future changes of phytoplankton community.

Hemolytic and cytotoxic activity from cultures of Aureococcus anophagefferens-a causative species of brown tides in the north-western Bohai Sea, China.

Brown tides were first observed in 2009 in the north-western Bohai Sea (Qinhuangdao sea area), China, and blooms have occurred at different scales in late spring every year since then. Although the detrimental effects on marine organisms of the causative phytoplankton species Aureococcus anophagefferens have been extensively studied, the mechanism remains poorly understood. We used erythrocytes and adrenal gland chromaffin tumor cells (PC12) to explore the hemolytic activity and cytotoxicity, respectively, of chloroform and methanol extracts of cultured A. anophagefferens isolated from the north-western Bohai Sea area. The methanol extracts showed no hemolytic or cytotoxic activity. Chloroform extracts had a potent hemolytic effect on rabbit erythrocytes; thin layer chromatography (TLC) indicated that the hemolysin was a kind of glycolipid compound. Erythrocyte lysis assay showed that erythrocytes of sea bream were sensitive to the hemolysin, whereas those of human and chicken erythrocytes were insensitive. The hemolytic effects were elevated as temperatures rose from 4 °C to 37 °C. Hemolytic blocking experiments showed that sphingomyelin and d-xylose can inhibit hemolysis significantly, while osmotic protectants with different hydrated molecular diameters had no inhibition, and the hemolysins had no obvious phospholipase activity. The chloroform extracts of A. anophagefferens had significant inhibitory effects on the viability of PC12 cells, and can induce efflux of lactic dehydrogenase (LDH) of PC12 cells and lead to their necrosis.