Adaptive Hierarchical Origami Metastructures

Shape-morphing capabilities are crucial for enabling multifunctionality in both biological and artificial systems. Various strategies for shape morphing have been proposed for applications in metamaterials and robotics. However, few of these approaches have achieved the ability to seamlessly transform into a multitude of volumetric shapes post-fabrication using a relatively simple actuation and control mechanism. Taking inspiration from thick origami and hierarchies in nature, we present a new hierarchical construction method based on polyhedrons to create an extensive library of compact origami metastructures. We show that a single hierarchical origami structure can autonomously adapt to over 103 versatile architectural configurations, achieved with the utilization of fewer than 3 actuation degrees of freedom and employing simple transition kinematics. We uncover the fundamental principles governing theses shape transformation through theoretical models. Furthermore, we also demonstrate the wide-ranging potential applications of these transformable hierarchical structures. These include their uses as untethered and autonomous robotic transformers capable of various gait-shifting and multidirectional locomotion, as well as rapidly self-deployable and self-reconfigurable architecture, exemplifying its scalability up to the meter scale. Lastly, we introduce the concept of multitask reconfigurable and deployable space robots and habitats, showcasing the adaptability and versatility of these metastructures

Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection

Few-shot object detection, expecting detectors to detect novel classes with a few instances, has made conspicuous progress. However, the prototypes extracted by existing meta-learning based methods still suffer from insufficient representative information and lack awareness of query images, which cannot be adaptively tailored to different query images. Firstly, only the support images are involved for extracting prototypes, resulting in scarce perceptual information of query images. Secondly, all pixels of all support images are treated equally when aggregating features into prototype vectors, thus the salient objects are overwhelmed by the cluttered background. In this paper, we propose an Information-Coupled Prototype Elaboration (ICPE) method to generate specific and representative prototypes for each query image. Concretely, a conditional information coupling module is introduced to couple information from the query branch to the support branch, strengthening the query-perceptual information in support features. Besides, we design a prototype dynamic aggregation module that dynamically adjusts intra-image and inter-image aggregation weights to highlight the salient information useful for detecting query images. Experimental results on both Pascal VOC and MS COCO demonstrate that our method achieves state-of-the-art performance in almost all settings.Comment: Accepted by AAAI202

SARS-Cov-2 variants: biological and mathematical considerations for nomenclature

Coronavirus(CoV) is one of the most widely used words during the past two years. If it were announced that Delta CoV only affects animals such as pigs and wigeons while Omicron CoV does not even exist, surely people would be offended and question the credibility of whoever stated this. But both statements are true, scientifically. Ofnote, it was stated Delta CoV and Omicron CoV, not Delta variant or Omicron variant of SARS-CoV-2. Such potentially confusing naming of a globally important virus therefore warrants further analyses. At the subfamily level, CoVs are divided into four genera (Alpha, Beta, Gamma, Delta) and only viruses of the Alpha and Beta branch infect humans. Now that the Omicron variant of SARS-CoV-2 have taken over from the Delta variant globally, the issue of the double use of genus labels (Alpha, Beta, Gamma, Delta) for variant naming is mitigated. However, we can still pause and ponder whether the Greek symbols alone are indeed ideal for labeling waves of SARS-CoV-2 variants. Here we propose additional criteria for naming of variants that considers specific biological and molecular characteristics of the virus-cell interaction. Our aim is to define a biological and structurally defined metric that can be used to distinguish SARS-CoV-2 variants interactions with host cells. This metric could find utility with numerous human viruses and provide an additional parameter for improved naming of viruses

Maternal cobalt concentration and risk of spontaneous preterm birth: the role of fasting blood glucose and lipid profiles

IntroductionSpontaneous preterm birth (SPB) is a significant cause of neonatal mortality, yet its etiology remains unclear. Cobalt, an essential trace element, might be a risk factor for SPB. This study aims to investigate the relationship between maternal serum cobalt concentration and SPB, and to clarify the role of blood lipids and fasting blood glucose (FBG) in this relationship.MethodsWe conducted a nested case-control study within the Beijing Birth Cohort Study. Serum samples were obtained from 222 pregnant women with SPB and 224 controls during the first (7–13 weeks of pregnancy) and third trimesters (32–42 weeks of pregnancy). Serum cobalt concentration was determined using inductively coupled plasma mass spectrometry (ICP-MS). Fasting blood glucose and lipids levels were detected using a fully automated biochemical immunoassay instrument. Logistic regression models and linear regression models were established to explore the association between serum cobalt concentration and the risk of SPB in pregnant women, and to test the mediating effect of fasting blood glucose (FBG) and lipids.ResultsWe found that the serum cobalt concentration in mothers with SPB and controls was similar in the first trimester, with values of 0.79 (0.58–1.10) ng/mL and 0.75 (0.51–1.07) ng/mL, respectively. However, in the third trimester, the cobalt concentration increased to 0.88 (0.59–1.14) ng/mL and 0.84 (0.52–1.19) ng/mL, respectively. In the logistic regression model, when considering the third trimester of pregnancy, after adjusting for ethnicity, pre-pregnancy body mass index (BMI), maternal age, education, income, and parity, it was observed that the medium level of cobalt concentration (0.63–1.07 ng/ml) had a negative correlation with the risk of SPB. The odds ratio (OR) was 0.56, with a 95% confidence interval of 0.34–0.90 ng/mL and a p-value of 0.02. This suggests that cobalt in this concentration range played a protective role against SPB. Additionally, it was found that FBG in the third trimester of pregnancy had a partial intermediary role, accounting for 9.12% of the association. However, no relationship between cobalt and SPB risk was found in the first trimester.ConclusionDuring the third trimester, intermediate levels of maternal cobalt appear to offer protection against SPB, with FBG playing a partial mediating role. To further clarify the optimal cobalt concentrations during pregnancy for different populations, a multi-center study with a larger sample size is necessary. Additionally, exploring the specific mechanism of FBG’s mediating role could provide valuable insights for improving the prevention of SPB