Development of a space cold atom clock

Atomic clocks with cold atoms play important roles in the field of fundamental physics as well as primary frequency standards. Operating such cold atom clocks in space paves the way for further exploration in fundamental physics, for example dark matter and general relativity. We developed a space cold atom clock (SCAC), which was launched into orbit with the Space Lab TG-2 in 2016. Before it deorbited with TG-2 in 2019, the SCAC had been working continuously for almost 3 years. During the period in orbit, many scientific experiments and engineering tests were performed. In this article, we summarize the principle, development and in-orbit results. These works provide the basis for construction of a space-borne time-frequency system in deep space.     

Convergent genomic signatures of high-altitude adaptation among domestic mammals

Abundant and diverse domestic mammals living on the Tibetan Plateau provide useful materials for investigating adaptive evolution and genetic convergence. Here, we used 327 genomes from horses, sheep, goats, cattle, pigs and dogs living at both high and low altitudes, including 73 genomes generated for this study, to disentangle the genetic mechanisms underlying local adaptation of domestic mammals. Although molecular convergence is comparatively rare at the DNA sequence level, we found convergent signature of positive selection at the gene level, particularly the EPAS1 gene in these Tibetan domestic mammals. We also reported a potential function in response to hypoxia for the gene C10orf67, which underwent positive selection in three of the domestic mammals. Our data provide an insight into adaptive evolution of high-altitude domestic mammals, and should facilitate the search for additional novel genes involved in the hypoxia response pathway.     

Predicting future dynamics from short-term time series using an Anticipated Learning Machine

Predicting time series has significant practical applications over different disciplines. Here, we propose an Anticipated Learning Machine (ALM) to achieve precise future-state predictions based on short-term but high-dimensional data. From non-linear dynamical systems theory, we show that ALM can transform recent correlation/spatial information of high-dimensional variables into future dynamical/temporal information of any target variable, thereby overcoming the small-sample problem and achieving multistep-ahead predictions. Since the training samples generated from high-dimensional data also include information of the unknown future values of the target variable, it is called anticipated learning. Extensive experiments on real-world data demonstrate significantly superior performances of ALM over all of the existing 12 methods. In contrast to traditional statistics-based machine learning, ALM is based on non-linear dynamics, thus opening a new way for dynamics-based machine learning.     

Programmable deformation of patterned bimorph actuator swarm

Graphene-based actuators featuring fast and reversible deformation under various external stimuli are promising for soft robotics. However, these bimorph actuators are incapable of complex and programmable 3D deformation, which limits their practical application. Here, inspired from the collective coupling and coordination of living cells, we fabricated a moisture-responsive graphene actuator swarm that has programmable shape-changing capability by programming the SU-8 patterns underneath. To get better control over the deformation, we fabricated SU-8 micropattern arrays with specific geometries and orientations on a continuous graphene oxide film, forming a swarm of bimorph actuators. In this way, predictable and complex deformations, including bending, twisting, coiling, asymmetric bending, 3D folding, and combinations of these, have been achieved due to the collective coupling and coordination of the actuator swarm. This work proposes a new way to program the deformation of bilayer actuators, expanding the capabilities of existing bimorph actuators for applications in various smart devices.     

Electro-mechanically controlled assembly of reconfigurable 3D mesostructures and electronic devices based on dielectric elastomer platforms

The manufacture of 3D mesostructures is receiving rapidly increasing attention, because of the fundamental significance and practical applications across wide-ranging areas. The recently developed approach of buckling-guided assembly allows deterministic formation of complex 3D mesostructures in a broad set of functional materials, with feature sizes spanning nanoscale to centimeter-scale. Previous studies mostly exploited mechanically controlled assembly platforms using elastomer substrates, which limits the capabilities to achieve on-demand local assembly, and to reshape assembled mesostructures into distinct 3D configurations. This work introduces a set of design concepts and assembly strategies to utilize dielectric elastomer actuators as powerful platforms for the electro-mechanically controlled 3D assembly. Capabilities of sequential, local loading with desired strain distributions allow access to precisely tailored 3D mesostructures that can be reshaped into distinct geometries, as demonstrated by experimental and theoretical studies of ∼30 examples. A reconfigurable inductive–capacitive radio-frequency circuit consisting of morphable 3D capacitors serves as an application example.     

Genomic consequences of population decline in critically endangered pangolins and their demographic histories

Pangolins are among the most critically endangered animals due to heavy poaching and worldwide trafficking. However, their demographic histories and the genomic consequences of their recent population declines remain unknown. We generated high-quality de novo reference genomes for critically endangered Malayan (Manis javanica, MJ) and Chinese (M. pentadactyla, MP) pangolins and re-sequencing population genomic data from 74 MJs and 23 MPs. We recovered the population identities of illegally traded pangolins and previously unrecognized genetic populations that should be protected as evolutionarily distinct conservation units. Demographic reconstruction suggested environmental changes have resulted in a population size fluctuation of pangolins. Additionally, recent population size declines due to human activities have resulted in an increase in inbreeding and genetic load. Deleterious mutations were enriched in genes related to cancer/diseases and cholesterol homeostasis, which may have increased their susceptibility to diseases and decreased their survival potential to adapt to environmental changes and high-cholesterol diets. This comprehensive study provides not only high-quality pangolin reference genomes, but also valuable information concerning the driving factors of long-term population size fluctuations and the genomic impact of recent population size declines due to human activities, which is essential for pangolin conservation management and global action planning.     

Local and teleconnected temperature effects of afforestation and vegetation greening in China

Afforestation in China provides carbon sequestration and prevents soil erosion, but its remote impacts on climate in other regions via the coupling of forest energy fluxes with atmospheric circulation are largely unknown. Here, we prescribe inventory-based forest cover change and satellite-observed leaf area index from 1982 to 2011 in a coupled land-atmosphere model to simulate their biophysical climate effects. Both local and global surface air temperatures show a seasonal contrast in response to past vegetation cover expansion over China: a phenomenon we primarily attribute to a variation of seasonality of vegetation greening. A large cooling in spring results in concurrent decreases in geopotential height over China and zonal wind over Mongolia, causing a dipole structure in the upper troposphere over the Arctic. This accounts for ∼58% of simulated spring warming over the Russian Arctic and ∼61% of simulated spring cooling over the Canadian Artic. Our results imply that spring vegetation dynamics in China may affect climate in northern high latitudes.     

Understanding divergent domestication traits from the whole-genome sequencing of swamp- and river-buffalo populations

Domesticated buffaloes have been integral to rice-paddy agro-ecosystems for millennia, yet relatively little is known about the buffalo genomics. Here, we sequenced and assembled reference genomes for both swamp and river buffaloes and we re-sequenced 230 individuals (132 swamp buffaloes and 98 river buffaloes) sampled from across Asia and Europe. Beyond the many actionable insights that our study revealed about the domestication, basic physiology and breeding of buffalo, we made the striking discovery that the divergent domestication traits between swamp and river buffaloes can be explained with recent selections of genes on social behavior, digestion metabolism, strengths and milk production.