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Abstract Direct electron detectors in scanning transmission electron microscopy give unprecedented possibilities for structure analysis at the nanoscale. In electronic and quantum materials, this new capability gives access to, for example, emergent chiral structures and symmetry-breaking distortions that underpin functional properties. Quantifying nanoscale structural features with statistical significance, however, is complicated by the subtleties of dynamic diffraction and coexisting contrast mechanisms, which often results in a low signal-to-noise ratio and the superposition of multiple signals that are challenging to deconvolute. Here we apply scanning electron diffraction to explore local polar distortions in the uniaxial ferroelectric Er(Mn,Ti)O3. Using a custom-designed convolutional autoencoder with bespoke regularization, we demonstrate that subtle variations in the scattering signatures of ferroelectric domains, domain walls, and vortex textures can readily be disentangled with statistical significance and separated from extrinsic contributions due to, e.g., variations in specimen thickness or bending. The work demonstrates a pathway to quantitatively measure symmetry-breaking distortions across large areas, mapping structural changes at interfaces and topological structures with nanoscale spatial resolution.

Summary: Endomucin (EMCN) currently represents the only hematopoietic stem cell (HSC) marker expressed by both murine and human HSCs. Here, we report that EMCN+ long-term repopulating HSCs (LT-HSCs; CD150+CD48−LSK) have a higher long-term multi-lineage repopulating capacity compared to EMCN− LT-HSCs. Cell cycle analyses and transcriptional profiling demonstrated that EMCN+ LT-HSCs were more quiescent compared to EMCN− LT-HSCs. Emcn−/− and Emcn+/+ mice displayed comparable steady-state hematopoiesis, as well as frequencies, transcriptional programs, and long-term multi-lineage repopulating capacity of their LT-HSCs. Complementary functional analyses further revealed increased cell cycle entry upon treatment with 5-fluorouracil and reduced granulocyte colony-stimulating factor (GCSF) mobilization of Emcn−/− LT-HSCs, demonstrating that EMCN expression by LT-HSCs associates with quiescence in response to hematopoietic stress and is indispensable for effective LT-HSC mobilization. Transplantation of wild-type bone marrow cells into Emcn−/− or Emcn+/+ recipients demonstrated that EMCN is essential for endothelial cell-dependent maintenance/self-renewal of the LT-HSC pool and sustained blood cell production post-transplant.

Optimizing the landscape structure and spatial configuration of the basin is one of the most important ways to reduce the harm of non-point source pollution (NPSP) to water bodies. The coupling relationship between the “source-sink” landscape pattern and NPSP process had long been a research hotspot of “source-sink” landscape theory. However, the “source-sink” landscape index represented by the classic location-weighted landscape index (LWLI) is suitable only for watersheds with similar environmental backgrounds, and cannot reflect the spatiotemporal heterogeneity of phosphorus output between watersheds with large differences in environmental backgrounds. In this study, 15 tributary watersheds in the Poyang Lake Basin were selected as the case study. The characteristics of “source-sink” landscape structure in 2020 were described by using landscape area structure indices. Moreover, the classical LWLI was modified by adding the topographic wetness index, soil erodibility index and vegetation interception index, and by evaluating the spatiotemporal differences in the effect of “source-sink” landscape patterns on phosphorus export in three hydrological periods (normal, wet and dry) by pearson correlation analysis and redundancy analysis. We found that (1) the proportion of “sink” landscape (greater than 58%) was greater than that of “source” landscape (less than 40%) in all sub-watersheds. In addition, the results of Lorentz curves showed that when the elevation and slope increased, the proportion of “source” landscape decreased and the proportion of “sink” landscape increased. (2) the classical and modified LWLI values were less than 0.5, which indicated that the potential contribution of the “sink” landscape was greater than that of the “source” landscape. (3) The correlation between the classical LWLI and total phosphorus (TP) in the wet period and normal period was stronger than the correlation between all “source-sink” landscape area structure indices and TP, indicating that the LWLI was more effective in describing TP loss than were the “source-sink” landscape area structure indices. (4) the correlation of the modified LWLI with TP in the three periods were stronger than those of the classical LWLI with TP, which indicated that the modified LWLI could better indicate the coupling relationship between the “source-sink” landscape pattern and the phosphorus output by introducing the factors of terrain runoff, soil erodibility and vegetation interception. This study can help with the evaluation of the spatial and temporal heterogeneity of nutrient loss in different watersheds with various landscape patterns, and provide a basis for scientific prevention and control of NPSP.

Abstract To scientifically and reasonably evaluate air quality with a large amount of monitored data, this paper proposes a new evaluation method called ideal grey close function cluster correlation analysis (IGCFCCA). Taking the air quality in Ningxia Province, China, as an example, according to China’s air quality standard, SO2, NO2, PM10, PM2.5 and O3 are selected as evaluation indexes to perform the evaluation. The results show that the air quality in this region in 2018 can be divided into three classifications, among which the relatively poor air quality in March, April and May is the first classification, the better air quality in August and September is the third classification, and the air quality in other months falls under the second classification. Correlation analysis is used to qualitatively determine that these three classifications correspond to first-level air quality in China’s air quality standard, and the correlation degree, which is the distance between the three classifications and the first-level air quality, is quantitatively determined. Specifically, the correlation degrees of the first-classification, second-classification and third-classification of air quality are 0.674, 0.697 and 0.71, respectively. The research results indicate potential directions and objectives for air quality management to achieve scientific management.

Abstract In pursuit of scientific discovery, vast collections of unstructured structural and functional images are acquired; however, only an infinitesimally small fraction of this data is rigorously analyzed, with an even smaller fraction ever being published. One method to accelerate scientific discovery is to extract more insight from costly scientific experiments already conducted. Unfortunately, data from scientific experiments tend only to be accessible by the originator who knows the experiments and directives. Moreover, there are no robust methods to search unstructured databases of images to deduce correlations and insight. Here, we develop a machine learning approach to create image similarity projections to search unstructured image databases. To improve these projections, we develop and train a model to include symmetry-aware features. As an exemplar, we use a set of 25,133 piezoresponse force microscopy images collected on diverse materials systems over five years. We demonstrate how this tool can be used for interactive recursive image searching and exploration, highlighting structural similarities at various length scales. This tool justifies continued investment in federated scientific databases with standardized metadata schemas where the combination of filtering and recursive interactive searching can uncover synthesis-structure-property relations. We provide a customizable open-source package ( https://github.com/m3-learning/Recursive_Symmetry_Aware_Materials_Microstructure_Explorer ) of this interactive tool for researchers to use with their data.

Abstract Ferroelectrics are being increasingly called upon for electronic devices in extreme environments. Device performance and energy efficiency is highly correlated to clock frequency, operational voltage, and resistive loss. To increase performance it is common to engineer ferroelectric domain structure with highly‐correlated electrical and elastic coupling that elicit fast and efficient collective switching. Designing domain structures with advantageous properties is difficult because the mechanisms involved in collective switching are poorly understood and difficult to investigate. Collective switching is a hierarchical process where the nano‐ and mesoscale responses control the macroscopic properties. Using chemical solution synthesis, epitaxially nearly‐relaxed (100) BaTiO3 films are synthesized. Thermal strain induces a strongly‐correlated domain structure with alternating domains of polarization along the [010] and [001] in‐plane axes and 90° domain walls along the [011] or [011¯$ar{1}$] directions. Simultaneous capacitance–voltage measurements and band‐excitation piezoresponse force microscopy revealed strong collective switching behavior. Using a deep convolutional autoencoder, hierarchical switching is automatically tracked and the switching pathway is identified. The collective switching velocities are calculated to be ≈500 cm s−1 at 5 V (7 kV cm−1), orders‐of‐magnitude faster than expected. These combinations of properties are promising for high‐speed tunable dielectrics and low‐voltage ferroelectric memories and logic.