Correlated states in twisted double bilayer graphene

Electron-electron interactions play an important role in graphene and related systems and can induce exotic quantum states, especially in a stacked bilayer with a small twist angle. For bilayer graphene where the two layers are twisted by a "magic angle", flat band and strong many-body effects lead to correlated insulating states and superconductivity. In contrast to monolayer graphene, the band structure of untwisted bilayer graphene can be further tuned by a displacement field, providing an extra degree of freedom to control the flat band that should appear when two bilayers are stacked on top of each other. Here, we report the discovery and characterization of such displacement-field tunable electronic phases in twisted double bilayer graphene. We observe insulating states at a half-filled conduction band in an intermediate range of displacement fields. Furthermore, the resistance gap in the correlated insulator increases with respect to the in-plane magnetic fields and we find that the g factor according to spin Zeeman effect is ~2, indicating spin polarization at half filling. These results establish the twisted double bilayer graphene as an easily tunable platform for exploring quantum many-body states

Transcriptional regulation of Bcl-2 gene by the PR/SET domain family member PRDM10

Bcl-2 (B-cell lymphoma 2) protein is localized in the outer membrane of mitochondria, where it plays an important role in promoting cellular survival and inhibiting the actions of pro-apoptotic proteins. PRDM10 is a member of the PR/SET family of epigenetic regulators and may play a role in development and cell differentiation. Here we show that human PRDM10 contributes to the transcriptional regulation of human Bcl-2 gene. We found that PRDM10-depletion in human cells reduced the expression of Bcl-2 protein and over-expression of PRDM10 promoted Bcl-2 protein expression. Furthermore, luciferase reporter activity of Bcl-2 gene P1 promoter was significantly increased in cells co-transfected with PRDM10, and PRDM10 was able to bind to the Bcl-2 P1 promoter in vivo. Using The Cancer Genome Atlas (TCGA) data set, we found weak positive correlation between PRDM10 and Bcl-2 in several cancer types including cancers of the breast, colon, and lung tissues. These data identify a novel function for PRDM10 protein and provide insights on the transcriptional control of Bcl-2 expression

Caulobacter and Novosphingobium in tumor tissues are associated with colorectal cancer outcomes

Diversity and composition of the gut microbiome are associated with cancer patient outcomes including colorectal cancer (CRC). A growing number of evidence indicates that Fusobacterium nucleatum (Fn) in CRC tissue is associated with worse survival. However, few studies have further analyzed the differences in bacteria in tumor tissues of different patients depending on the survival time of CRC patients. Therefore, there is a need to further explore the bacterial differences in tumor tissues of patients with different prognoses and to identify key bacteria for analysis. Here, we sought to compare the differences in tumor microbiome between patients with long-term survival (LS) longer than 3 years or 4 and 5 years and patients with short-term survival (SS) in the present study cohort. We found that there were significant differences in tumor microbiome between the LS and SS and two bacteria—Caulobacter and Novosphingobium—that are present in all of the three groups. Furthermore, by analyzing bacteria in different clinical features, we also found that lower levels of microbiome (Caulobacter and Novosphingobium) have long-term survival and modulating microbiome in tumor tissue may provide an alternative way to predict the prognosis of CRC patients

Room-temperature correlated states in twisted bilayer MoS2_2

Moir\'e superlattices have emerged as an exciting condensed-matter quantum simulator for exploring the exotic physics of strong electronic correlations. Notable progress has been witnessed, but such correlated states are achievable usually at low temperatures. Here, we report the transport evidences of room-temperature correlated electronic states and layer-hybridized SU(4) Hubbard model simulator in AB-stacked MoS$_2$ homo-bilayer moir\'e superlattices. Correlated insulating states at moir\'e band filling factors v = 1, 2, 3 are unambiguously established in twisted bilayer MoS$_2$. Remarkably, the correlated electronic states can persist up to a record-high critical temperature of over 285 K. The realization of room-temperature correlated states in twisted bilayer MoS$_2$ can be understood as the cooperation effects of the stacking-specific atomic reconstruction and the resonantly enhanced interlayer hybridization, which largely amplify the moir\'e superlattice effects on electronic correlations. Furthermore, extreme large non-linear Hall responses up to room-temperature are uncovered near correlated insulating states, demonstrating the quantum geometry of moir\'e flat conduction band.Comment: 13 pages, 3 figure

Modeling response of glacier discharge to future climate change, Gacier No.1, Ürümqi

Glaciers are known to be prone to climate change. The Xinjiang Uyghur Autonomous Region, China, has approximately 20,000 glaciers, which accounts for half number of glaciers in China. One of important function of glacier is that it provides meltwater, therefore, the glacier response to a warming temperature in this area is becoming critical to be investigated in relation to water sustainable development. The Ürümqi Glacier No.1 (UG1), as one of the most important glaciers, has a dominant role of providing meltwater for the capital city, Ürümqi. In this thesis, the Distributed Enhanced Temperature Index Model (DETIM) was employed, and calibrated to perform UG1’s historical discharge pattern. Then the calibrated discharge model was grafted to future climate projection of four Representative Concentration Pathways (RCPs) from fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), in order to investigate UG1’s water supply potential in the future. Moreover, UG1’s water supply role was discussed under a dynamic interaction between water supply and human society in the end. The result showed that the computation meltwater volume is between 121 million m³ to 131 million m³ in 35 years, from 2016 to 2050

Modeling response of glacier discharge to future climate change, Gacier No.1, Ürümqi

Glaciers are known to be prone to climate change. The Xinjiang Uyghur Autonomous Region, China, has approximately 20,000 glaciers, which accounts for half number of glaciers in China. One of important function of glacier is that it provides meltwater, therefore, the glacier response to a warming temperature in this area is becoming critical to be investigated in relation to water sustainable development. The Ürümqi Glacier No.1 (UG1), as one of the most important glaciers, has a dominant role of providing meltwater for the capital city, Ürümqi. In this thesis, the Distributed Enhanced Temperature Index Model (DETIM) was employed, and calibrated to perform UG1’s historical discharge pattern. Then the calibrated discharge model was grafted to future climate projection of four Representative Concentration Pathways (RCPs) from fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), in order to investigate UG1’s water supply potential in the future. Moreover, UG1’s water supply role was discussed under a dynamic interaction between water supply and human society in the end. The result showed that the computation meltwater volume is between 121 million m³ to 131 million m³ in 35 years, from 2016 to 2050

Causal calibration: iteratively calibrating LiDAR and camera by considering causality and geometry

Abstract The external calibration between 3D LiDAR and 2D camera is an extremely important step towards multimodal fusion for robot perception. However, its accuracy is still unsatisfactory. To improve the accuracy of calibration, we first analyze the interference factors that affect the performance of the calibration model under a causal inference framework in this study. Guided by the causality analysis, we present Iter-CalibNet (Iterative Calibration Convolutional Neural Network) to infer a 6 degrees of freedom (DoF) rigid body transformation between 3D LiDAR and 2D camera. By downscaling point clouds to obtain more overlapping region between 3D–2D data pair and applying iterative calibration manner, the interference of confounding bias in the calibration model is effectively eliminated. Moreover, our Iter-CalibNet adds non-local neural network after each convolution operation to capture the transformation relationship. We also combine the geometric loss and photometric loss obtained from the interframe constraints to optimize the calibration accuracy. Extensive experiments demonstrate that our Iter-CalibNet can achieve leading performance by comparison with other CNN based and traditional calibration methods