CUPre: Cross-domain Unsupervised Pre-training for Few-Shot Cell Segmentation

While pre-training on object detection tasks, such as Common Objects in Contexts (COCO) [1], could significantly boost the performance of cell segmentation, it still consumes on massive fine-annotated cell images [2] with bounding boxes, masks, and cell types for every cell in every image, to fine-tune the pre-trained model. To lower the cost of annotation, this work considers the problem of pre-training DNN models for few-shot cell segmentation, where massive unlabeled cell images are available but only a small proportion is annotated. Hereby, we propose Cross-domain Unsupervised Pre-training, namely CUPre, transferring the capability of object detection and instance segmentation for common visual objects (learned from COCO) to the visual domain of cells using unlabeled images. Given a standard COCO pre-trained network with backbone, neck, and head modules, CUPre adopts an alternate multi-task pre-training (AMT2) procedure with two sub-tasks -- in every iteration of pre-training, AMT2 first trains the backbone with cell images from multiple cell datasets via unsupervised momentum contrastive learning (MoCo) [3], and then trains the whole model with vanilla COCO datasets via instance segmentation. After pre-training, CUPre fine-tunes the whole model on the cell segmentation task using a few annotated images. We carry out extensive experiments to evaluate CUPre using LIVECell [2] and BBBC038 [4] datasets in few-shot instance segmentation settings. The experiment shows that CUPre can outperform existing pre-training methods, achieving the highest average precision (AP) for few-shot cell segmentation and detection

The Changing Patterns of Coronavirus Disease 2019 (COVID-19) in China: A Tempogeographic Analysis of the Severe Acute Respiratory Syndrome Coronavirus 2 Epidemic.

BACKGROUND: Evaluating whether an infectious disease has reached a turning point is important for planning additional intervention efforts. This study aimed to analyze the changing patterns and the tempogeographic features of the coronavirus disease 2019 (COVID-19) epidemic in China, to provide further evidence for real-time responses. METHODS: Daily data on COVID-19 cases between 31 December 2019 and 26 February 2020 were collected and analyzed for Hubei and non-Hubei regions in China. Observed trends for new and cumulative cases were analyzed through joinpoint regression analysis. Spatial analysis was applied to show the geographic distribution and changing patterns of the epidemic. RESULTS: By 26 February 2020, 78 630 confirmed COVID-19 cases had been reported in China. In Hubei, an increasing trend (slope = 221) was observed for new cases between 24 January and 7 February 2020, after which a decline commenced (slope = -868). However, as the diagnosis criteria changed, a sudden increase (slope = 5530) was observed on 12 February, which sharply decreased afterward (slope = -4898). In non-Hubei regions, the number of new cases increased from 20 January to 3 February and started to decline afterward (slope = -53). The spatial analysis identified Chongqing, Guangzhou, Shenzhen, Changsha, Nanchang, Wenzhou, Shanghai, Xinyang, Jining, and Beijing as the hotspots outside of Hubei Province in China. CONCLUSIONS: The joinpoint regression analysis indicated that the epidemic might be under control in China, especially for regions outside of Hubei Province. Further improvement in the response strategies based on these new patterns is needed

Large-eddy simulation of gas–liquid two-phase flow in a bubble column reactor using a modified sub-grid scale model with the consideration of bubble-eddy interaction

The Eulerian–Eulerian Large-eddy simulations (LES) of gas–liquid two-phase flow in a cylindrical bubble column reactor have been conducted. When considering the turbulent eddy viscosity in LES, apart from the well-accepted contributions from shear turbulence and bubble induced turbulence (BIT), the effect of the interaction between entrained bubbles and eddies with a similar turbulence length scale to the sub-grid scale (SGS) cannot be neglected. With the consideration of the bubble response to the eddies on the induced sub-grid stresses, a modified SGS model, which incorporates the Stokes number, St, was proposed. The results of LES clearly indicate that the use of the modified SGS model can effectively capture the transient bubbly flow in the cylindrical bubble column. The power turbulent kinetic energy spectrum obtained in LES indicates that a slope similar to Komogorov -5/3 scaling law and the -3 scaling law can still be identified for a critical frequency f=10.70 Hz. © 2020 The Author(s

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Fetal Brain Tissue Annotation and Segmentation Challenge Results

In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital step in the quantitative analysis of prenatal neurodevelopment both in the research and clinical context. However, manual segmentation of cerebral structures is time-consuming and prone to error and inter-observer variability. Therefore, we organized the Fetal Tissue Annotation (FeTA) Challenge in 2021 in order to encourage the development of automatic segmentation algorithms on an international level. The challenge utilized FeTA Dataset, an open dataset of fetal brain MRI reconstructions segmented into seven different tissues (external cerebrospinal fluid, grey matter, white matter, ventricles, cerebellum, brainstem, deep grey matter). 20 international teams participated in this challenge, submitting a total of 21 algorithms for evaluation. In this paper, we provide a detailed analysis of the results from both a technical and clinical perspective. All participants relied on deep learning methods, mainly U-Nets, with some variability present in the network architecture, optimization, and image pre- and post-processing. The majority of teams used existing medical imaging deep learning frameworks. The main differences between the submissions were the fine tuning done during training, and the specific pre- and post-processing steps performed. The challenge results showed that almost all submissions performed similarly. Four of the top five teams used ensemble learning methods. However, one team's algorithm performed significantly superior to the other submissions, and consisted of an asymmetrical U-Net network architecture. This paper provides a first of its kind benchmark for future automatic multi-tissue segmentation algorithms for the developing human brain in utero.Comment: Results from FeTA Challenge 2021, held at MICCAI; Manuscript submitte

Can Quantitative Easing Population Policy Rescue China's Sinking Fertility Rate? A Comparative Examination between Jiangsu and Zhejiang

China has a low level of fertility after many years of births control by government intervention. Challenged by an aging and low-fertility population, China’s one-child policy was abolished in 2013 and two Quantitative Easing Population Policies (QEPP) implemented in its stead. Based on a study of population evolutions in two eastern provinces in China, this paper analyzes the local factors affecting birthrate and shows that social development and certain other control variables significantly impact fertility rates. Thus, QEPP alone cannot reverse the sinking fertility rate; other public services relating to health and family planning should be considered as well.China ostenta un bajo nivel de fertilidad dado el control de natalidad efectuado desde hace años por el Estado. Desafiada por el envejecimiento de la población y una baja fertilidad, la política de un solo hijo desarrollada por el país fue abolida en 2013, momento en que se implementaron dos políticas de flexibilización cuantitativa de la población (QEPP en inglés) en su lugar. A partir del estudio de la evolución de la población en dos provincias orientales de China, este artículo analiza los factores locales que afectan la tasa de natalidad. Los resultados expresan que el desarrollo social y determinadas variables de control impactan significativamente en las tasas de fertilidad. Por lo tanto, la QEPP por sí sola no puede revertir la tasa de fertilidad actualmente en descenso, interpelando considerar otras orientaciones públicas vinculadas a la salud y planificación familiar.La Chine conserve un faible niveau de fertilité après de nombreuses années de contrôle des naissances par l'intervention du gouvernement. Face au vieillissement et à la faible fécondité de la population, la politique chinoise de l'enfant unique a été abolie en 2013 et deux politiques démographiques d'assouplissement quantitatif (QEPP) ont été mises en œuvre. Sur la base d'une étude des évolutions démographiques dans deux provinces de l'est de la Chine, cet article analyse les facteurs locaux affectant la natalité et montre que le développement social et certaines autres variables de contrôle ont un impact significatif sur les taux de fécondité. Ainsi, le QEPP ne peut à lui seul inverser la tendance à la baisse du taux de fécondité ; d'autres services publics liés à la santé et à la planification familiale doivent également être pris en compte

Auto-focusing system for microscope based on computational verb controllers

Abstract—In this paper, an auto-focusing system of microscope for integrated circuits (IC) analysis is presented. In this system, the Laplacian algorithm is used as the evaluation function, which provides a reference to the degree of defocus. The auto-focusing controlling algorithm based on computational verb theory consists of two controllers designed: The moving-speed controller and the moving-direction controller. Both controllers work well under the verb-control rules designed in this paper. It has shown that the system can focus accurately and quickly, and it can adjust itself when it is out of focus

Recovery of value-added anthocyanins from mulberry by a cation exchange chromatography

Anthocyanins are often targets in polyphenol analysis. However, it's hard to effectively separate anthocyanin from copigments such as phenolic acid and flavanols due to their similar structure. Thus, a cation exchange chromatography with 001 x 7 has been developed, which is available for anthocyanins isolation both on a small and large scale. The optimal process condition of anthocyanins isolation was determined. Compared to the macroporous adsorbent resins and Strong Cation Exchange resin (SCX), 001X7 shows greater economic advantages in large-scale purification of anthocyanins. More than 95% purity of the anthocyanin fraction can be achieved through this approach. This method shows a path to provide large quantities of copigments-free anthocyanins from mulberry polyphenols for the further study of its biological effects and may be extended to other analytical methods of polyphenol isolation from other plant materials