Blistering Behavior of Beryllium and Beryllium Alloy under High-Dose Helium Ion Irradiation.

Beryllium (Be) has been selected as the solid neutron multiplier material for a tritium breeding blanket module in ITER, which is also the primary option of the Chinese TBM program. But the irradiation swelling of beryllium is severe under high temperature, high irradiation damage and high doses of transmutation-induced helium. Advanced neutron multipliers with high stability at high temperature are desired for the demonstration power plant (DEMO) reactors and the China Fusion Engineering Test Reactor (CFETR).

Factors Influencing the Answerability and Popularity of a Health-Related Post in the Question-and-Answer Community: Infodemiology Study of Metafilter.

Background: The web-based health question-and-answer (Q&A) community has become the primary and handy way for people to access health information and knowledge directly.

Objective: The objective of our study is to investigate how content-related, context-related, and user-related variables influence the answerability and popularity of health-related posts based on a user-dynamic, social network, and topic-dynamic semantic network, respectively.

Methods: Full-scale data on health consultations were acquired from the Metafilter Q&A community.

Self-Supervised 3D Behavior Representation Learning Based on Homotopic Hyperbolic Embedding.

Behavior sequences are generated by a series of spatio-temporal interactions and have a high-dimensional nonlinear manifold structure. Therefore, it is difficult to learn 3D behavior representations without relying on supervised signals. To this end, self-supervised learning methods can be used to explore the rich information contained in the data itself.

Graph-Based Self-Training for Semi-Supervised Deep Similarity Learning.

Semi-supervised learning is a learning pattern that can utilize labeled data and unlabeled data to train deep neural networks. In semi-supervised learning methods, self-training-based methods do not depend on a data augmentation strategy and have better generalization ability. However, their performance is limited by the accuracy of predicted pseudo-labels.

In Situ Observation of Thermoelastic Martensitic Transformation of Cu-Al-Mn Cryogenic Shape Memory Alloy with Compressive Stress.

The thermoelastic martensitic transformation and its reverse transformation of the Cu-Al-Mn cryogenic shape memory alloy, both with and without compressive stress, has been dynamically in situ observed. During the process of thermoelastic martensitic transformation, martensite nucleates and gradually grow up as they cool, and shrink to disappearance as they heat. The order of martensite disappearance is just opposite to that of their formation.

Therapeutic Effects of Melatonin on Ocular Diseases: Knowledge Map and Perspective.

Melatonin plays a critical role in the pathophysiological process including circadian rhythm, apoptosis, and oxidative stress. It can be synthesized in ocular tissues, and its receptors are also found in the eye, triggering more investigations concentrated on the role of melatonin in the eye. In the past decades, the protective and therapeutic potentials of melatonin for ocular diseases have been widely revealed in animal models.

Enhanced interaction in TiO/BiVO heterostructures via MXene TiC-derived 2D-carbon for highly efficient visible-light photocatalysis.

Heterostructured photocatalysts play a significant role in the removal of contaminants by decreasing the recombination of the photo-induced charges. Herein, we presented novel TiO/C/BiVO ternary hybrids employing a 2D layered TiC MXene precursor, overcoming the lattice mismatching of TiO/BiVO binary heterostructures simultaneously. Raman and XPS analyses proved the strong coupling effects of TiO, carbon and BiVO components, and the heterostructures were identified from high-resolution transmission electron microscopy results.

Range clusters based time-of-flight 3D imaging obstacle detection in manifold space.

A new obstacle detection method using time-of-flight 3D imaging sensor based on range clusters is proposed. To effectively reduce the influence of outlier and noise in range images, we utilize intensity images to estimate noise deviation of the range images and a weighted local linear smoothing is used to project the data into a new manifold surface. The proposed method divides the 3D imaging data into range clusters with different shapes and sizes according to the distance ambient relation between the pixels, and some regulation criterions are set to adjust the range clusters into optimal shape and size.

Briefing in family characteristics of microRNAs and their applications in cancer research.

MicroRNAs (miRNAs) are endogenous, short, non-coding RNA molecules that are directly involved in the post-transcriptional regulation of gene expression. Dysregulation of miRNAs is usually associated with diseases. Since miRNAs in a family intend to have common functional characteristics, proper assignment of miRNA family becomes heuristic for better understanding of miRNA nature and their potentials in clinic.

Supervised preserving projection for learning scene information based on time-of-flight imaging sensor.

In this paper, we propose a new supervised manifold learning approach, supervised preserving projection (SPP), for the depth images of a 3D imaging sensor based on the time-of-flight (TOF) principle. We present a novel manifold sense to learn scene information produced by the TOF camera along with depth images. First, we use a local surface patch to approximate the underlying manifold structures represented by the scene information.