Brain segmentation based on multi-atlas guided 3D fully convolutional network ensembles

In this study, we proposed and validated a multi-atlas guided 3D fully convolutional network (FCN) ensemble model (M-FCN) for segmenting brain regions of interest (ROIs) from structural magnetic resonance images (MRIs). One major limitation of existing state-of-the-art 3D FCN segmentation models is that they often apply image patches of fixed size throughout training and testing, which may miss some complex tissue appearance patterns of different brain ROIs. To address this limitation, we trained a 3D FCN model for each ROI using patches of adaptive size and embedded outputs of the convolutional layers in the deconvolutional layers to further capture the local and global context patterns. In addition, with an introduction of multi-atlas based guidance in M-FCN, our segmentation was generated by combining the information of images and labels, which is highly robust. To reduce over-fitting of the FCN model on the training data, we adopted an ensemble strategy in the learning procedure. Evaluation was performed on two brain MRI datasets, aiming respectively at segmenting 14 subcortical and ventricular structures and 54 brain ROIs. The segmentation results of the proposed method were compared with those of a state-of-the-art multi-atlas based segmentation method and an existing 3D FCN segmentation model. Our results suggested that the proposed method had a superior segmentation performance

Set-Based Face Recognition Beyond Disentanglement: Burstiness Suppression With Variance Vocabulary

Set-based face recognition (SFR) aims to recognize the face sets in the unconstrained scenario, where the appearance of same identity may change dramatically with extreme variances (e.g., illumination, pose, expression). We argue that the two crucial issues in SFR, the face quality and burstiness, are both identity-irrelevant and variance-relevant. The quality and burstiness assessment are interfered with by the entanglement of identity, and the face recognition is interfered with by the entanglement of variance. Thus we propose to separate the identity features with the variance features in a light-weighted set-based disentanglement framework. Beyond disentanglement, the variance features are fully utilized to indicate face quality and burstiness in a set, rather than being discarded after training. To suppress face burstiness in the sets, we propose a vocabulary-based burst suppression (VBS) method which quantizes faces with a reference vocabulary. With interword and intra-word normalization operations on the assignment scores, the face burtisness degrees are appropriately estimated. The extensive illustrations and experiments demonstrate the effect of the disentanglement framework with VBS, which gets new state-of-the-art on the SFR benchmarks. The code will be released at https://github.com/Liubinggunzu/set_burstiness.Comment: ACM MM 2022 accepted, code will be release

Learning network storage curriculum with experimental case based on embedded systems

In this paper, we present an experimental case for the course of Network Storage and Security, which benefited from an improved learning outcome for our students. The newly designed experiments-based contents are merged into the current course to help students obtain practical experiences about network storage. The experiments aim to build a network storage system based on available resources instead of any specialized network storage equipment. Technically, students can learn general practical knowledge of network storage on iSCSI (a network storage protocol based on IP technology) and also the technologies of embedded system. Through the experimental case, we found that it could fully enhance students\u27 comprehensive and practical abilities, develop students\u27 teamwork spirit and creativity, and especially improve the learning outcome of network storage curriculum. These learning and thinking methods can also be generalized and applied to other computer science related courses

Ethyl 6-methyl-2-p-tolyl­pyrazolo[1,5-a]pyridine-5-carboxyl­ate

In the title mol­ecule, C18H18N2O2, the bicyclic ring system and the benzene ring form a dihedral angle of 13.45 (3)°. In the crystal structure, weak inter­molecular C—H⋯O hydrogen bonds link mol­ecules into chains propagated along [201]

Efficient Serverless Function Scheduling at the Network Edge

Serverless computing is a promising approach for edge computing since its inherent features, e.g., lightweight virtualization, rapid scalability, and economic efficiency. However, previous studies have not studied well the issues of significant cold start latency and highly dynamic workloads in serverless function scheduling, which are exacerbated at the resource-limited network edge. In this paper, we formulate the Serverless Function Scheduling (SFS) problem for resource-limited edge computing, aiming to minimize the average response time. To efficiently solve this intractable scheduling problem, we first consider a simplified offline form of the problem and design a polynomial-time optimal scheduling algorithm based on each function's weight. Furthermore, we propose an Enhanced Shortest Function First (ESFF) algorithm, in which the function weight represents the scheduling urgency. To avoid frequent cold starts, ESFF selectively decides the initialization of new function instances when receiving requests. To deal with dynamic workloads, ESFF judiciously replaces serverless functions based on the function weight at the completion time of requests. Extensive simulations based on real-world serverless request traces are conducted, and the results show that ESFF consistently and substantially outperforms existing baselines under different settings

Progress of important clinical trials of breast cancer in China in 2022

Breast cancer has become the most common type of cancer in the world, harming the majority of women's physical and mental health and challenging clinical prevention and treatment of tumors. With the in-depth research on the pathogenesis and metastasis mechanism of breast cancer, as well as the development of translational research such as multiomics technology and tumor immunity, it has been proved that breast cancer has highly heterogeneous molecular and clinical characteristics. The clinical treatment methods of different subtypes of breast cancer are different and related, and the achievements in the field of breast cancer clinical research are fruitful. In 2022, results of important clinical trials have achieved for different subtypes of breast cancer. For the neo-adjuvant treatment of human epidermal growth factor receptor 2 (HER2) positive breast cancer, the PHEDRA study provided new adjuvant treatment options for HER2 positive breast cancer patients; And for the HER2 positive metastatic breast cancer, PHILA study and SYSUCC-002 study results provided reference for clinicians. For patients with brain metastasis, PERMEATE study showed that pyrrolitinib combined with capecitabine regimen was to become the preferred treatment scheme for HER2 positive brain metastasis population, especially for patients with brain metastasis without local radiotherapy. In hormone receptor positive breast cancer, a number of clinical trials (monarchE study, DAWNA-1 study, MONALEESA series of studies, etc.) of arbacilli, daracilli, rebosilli and others reported their efficacy on visceral metastasis. For triple-negative breast cancer, many clinical trials are under way. This paper aimed to review the recent advances in clinical research on breast cancer in the past year

Induced abortion in 30 Chinese provinces in 2013: a cross-sectional survey

Background: Galloping economic growth and reform in China in the past 30 years has led to dramatic social changes. Attitudes towards sex and sexual behaviour have changed, and premarital sex has become more acceptable. The methods of contraception have changed, and the use of highly effective or long-acting contraceptive methods tends to be decreasing, especially in urban areas. Abortion is commonly used to end unintended pregnancy. The aim of this study was to survey the current situation of induced abortions in selected hospitals in 30 provinces in China. Methods: This cross-sectional study was conducted in 295 randomly selected hospitals in 30 Chinese provinces between April and August, 2013. We collected data using a questionnaire filled by the abortion service providers for all women seeking abortion within 12 weeks of pregnancy during a period of two months. The information included self-reported demographic and economic characteristics, history of induced abortion, and use of contraception. The characteristics of women were summarised with counts (percentages) for categorical variables; mean (SD) and range for age of women. All participants signed a written informed consent of which they received a copy. Ethics approvals were obtained from both ethics committees of the National Research Institution for Family Planning (NRIFP), China, and of the Ghent University, Belgium. Findings: 79 174 women participated in the study (mean age 28∙9 years (SD 1∙7; range 13–58), of whom 27 134 (35%) were undergoing a first induced abortion, 28 637 (37%) a second abortion, and 22 682 (29%) a third or subsequent abortion. About a third of participants (31%) were not married and more than half (61%) were not local residents. The primary reasons for the unintended pregnancy were contraception failure (50%) and non-use of contraception (44%). Interpretation: This is the first nationwide large-scale study in 30 provinces to show that repeated induced abortion is high in China. A family planning programme for young and unmarried people is urgently needed to improve their access to information, advice, and services about contraception and to reduce unintended pregnancies and repeated induced abortion. Funding: The European Commission (EC) under the Seventh Framework Programme (FP7), project number 282490