Patterning-Induced Ferromagnetism of Fe3GeTe2 van der Waals Materials beyond Room Temperature.

Magnetic van der Waals (vdW) materials have emerged as promising candidates for spintronics applications, especially after the recent discovery of intrinsic ferromagnetism in monolayer vdW materials. There has been a critical need for tunable ferromagnetic vdW materials beyond room temperature. Here, we report a real-space imaging study of itinerant ferromagnet Fe3GeTe2 and the enhancement of its Curie temperature well above ambient temperature. We find that the magnetic long-range order in Fe3GeTe2 is characterized by an unconventional out-of-plane stripe-domain phase. In Fe3GeTe2 microstructures patterned by a focused ion beam, the out-of-plane stripe domain phase undergoes a surprising transition at 230 K to an in-plane vortex phase that persists beyond room temperature. The discovery of tunable ferromagnetism in Fe3GeTe2 materials opens up vast opportunities for utilizing vdW magnets in room-temperature spintronics devices

Broken-Symmetry States in Quantum Hall Superlattices

We argue that broken-symmetry states with either spatially diagonal or spatially off-diagonal order are likely in the quantum Hall regime, for clean multiple quantum well (MQW) systems with small layer separations. We find that for MQW systems, unlike bilayers, charge order tends to be favored over spontaneous interlayer coherence. We estimate the size of the interlayer tunneling amplitude needed to stabilize superlattice Bloch minibands by comparing the variational energies of interlayer-coherent superlattice miniband states with those of states with charge order and states with no broken symmetries. We predict that when coherent miniband ground states are stable, strong interlayer electronic correlations will strongly enhance the growth-direction tunneling conductance and promote the possibility of Bloch oscillations.Comment: 9 pages LaTeX, 4 figures EPS, to be published in PR

A 3D Organically Synthesised Porous Carbon Material for Lithium Ion Batteries

We report the first organically synthesized sp–sp3 hybridized porous carbon, OSPC‐1. This new carbon shows electron conductivity, high porosity, the highest uptake of lithium ions of any carbon material to‐date, and the ability to inhibit dangerous lithium dendrite formation. The new carbon exhibits exceptional potential as anode material for lithium‐ion batteries (LIBs) with high capacity, excellent rate capability, long cycle life, and potential for improved safety performance

Manipulating chiral-spin transport with ferroelectric polarization

A collective excitation of the spin structure in a magnetic insulator can transmit spin-angular momentum with negligible dissipation. This quantum of a spin wave, introduced more than nine decades ago, has always been manipulated through magnetic dipoles, (i.e., timereversal symmetry). Here, we report the experimental observation of chiral-spin transport in multiferroic BiFeO3, where the spin transport is controlled by reversing the ferroelectric polarization (i.e., spatial inversion symmetry). The ferroelectrically controlled magnons produce an unprecedented ratio of up to 18% rectification at room temperature. The spin torque that the magnons in BiFeO3 carry can be used to efficiently switch the magnetization of adja-cent magnets, with a spin-torque efficiency being comparable to the spin Hall effect in heavy metals. Utilizing such a controllable magnon generation and transmission in BiFeO3, an alloxide, energy-scalable logic is demonstrated composed of spin-orbit injection, detection, and magnetoelectric control. This observation opens a new chapter of multiferroic magnons and paves an alternative pathway towards low-dissipation nanoelectronics

The complete chloroplast genome sequence of Lithocarpus litseifolius (Hance) Chun 1837 (Fagaceae) and phylogenetic analysis

Lithocarpus litseifolius (Hance) Chun 1837 is an evergreen tree of Fagaceae, which can be used as sweet tea, natural sweetener, and precious medicinal material. The complete chloroplast genome of L. litseifolius was sequenced and its phylogenetic relationship was analyzed in this study. The chloroplast genome of L. litseifolius has a circular structure with a length of 161,322 bp, and it contains a pair of inverted repeat regions (IRs 25,897 bp), a large single copy (LSC 90,551 bp), and a small single copy (SSC 18,977 bp). There were 131 genes identified, including 37 tRNA, 8 rRNA, and 86 mRNA genes. Phylogenetic analysis of 23 species of Fagaceae indicated that Lithocarpus is monophyletic with strong bootstrap, and L. litseifolius is genetically closely related to Lithocarpus polystachyus

Quantitative Characteristics of the Current Multi-Source Precipitation Products over Zhejiang Province, in Summer, 2019

Precipitation data with fine quality plays vital roles in hydrological-related applications. In this study, we choose the high-quality China Merged Precipitation Analysis data (CMPA) as the benchmark for evaluating four satellite-based precipitation products (PERSIANN-CCS, FY4A QPE, GSMap_Gauge, IMERG-Final) and one model-based precipitation product (ERA5-Land), respectively, at 0.1°, hourly scales over the Zhejiang province, China, in summer, from June to August 2019. The main conclusions were as follows—(1) all other products demonstrate similar patterns with CMPA (~325.60 mm/h, std ~0.07 mm/h), except FY4A QPE (~281.79 mm/h, std ~0.18 mm/h), while, overall, the PERSIANN-CCS underestimates the precipitation against CMPA with a mean value around 236.29 mm/h (std ~0.06 mm/h), and the ERA5-Land, GSMap_Guage, and IMERG-Final generally overestimate the precipitation with a mean value around 370.00 mm/h (std ~0.06 mm/h). (2) The GSMap_Gauge outperforms IMERG-Final against CMPA with CC ~0.50 and RMSE ~1.51 mm/h, and CC ~0.48 and RMSE ~1.64 mm/h, respectively. (3) The PERSIANN-CCS significantly underestimates the precipitation (CC ~0.26, bias ~−35.03%, RMSE ~1.81 mm/h, probability of detection, POD, ~0.33, false alarm ratio, FAR, ~0.47), potentially due to its weak abilities to capture precipitation events and estimate the precipitation. (4) Though ERA5-Land has the best ability to capture precipitation events (POD ~0.78), the largest misjudgments (FAR ~0.54) result in its great uncertainties with CC ~ 0.39, which performs worse than those of GSMap_Gauge and IMERG-Final. (5) The ranking of precipitation products, in terms of the general evaluation metrics, over Zhejiang province is GSMap_Gauge, IMERG-Final, ERA5-Land, PERSIANN-CCS, and FY4A QPE, which provides valuable recommendations for applying these products in various related application fields

Comprehensive Comparisons of State-of-the-Art Gridded Precipitation Estimates for Hydrological Applications over Southern China

Satellite-based precipitation estimates with high quality and spatial-temporal resolutions play a vital role in forcing global or regional meteorological, hydrological, and agricultural models, which are especially useful over large poorly gauged regions. In this study, we apply various statistical indicators to comprehensively analyze the quality and compare the performance of five newly released satellite and reanalysis precipitation products against China Merged Precipitation Analysis (CMPA) rain gauge data, respectively, with 0.1° × 0.1° spatial resolution and two temporal scales (daily and hourly) over southern China from June to August in 2019. These include Precipitation Estimates from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5-Land), Fengyun-4 (FY-4A), Global Satellite Mapping of Precipitation (GSMaP), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG). Results indicate that: (1) all five products overestimate the accumulated rainfall in the summer, with FY-4A being the most severe; additionally, FY-4A cannot capture the spatial and temporal distribution characteristics of precipitation over southern China. (2) IMERG and GSMaP perform better than the other three datasets at both daily and hourly scales; IMERG correlates slightly better than GSMaP against CMPA data, while it performs worse than GSMaP in terms of probability of detection (POD). (3) ERA5-Land performs better than PERSIANN-CCS and FY-4A at daily scale but shows the worst correlation coefficient (CC), false alarm ratio (FAR), and equitable threat score (ETS) of all precipitation products at hourly scale. (4) The rankings of overall performance on precipitation estimations for this region are IMERG, GSMaP, ERA5-Land, PERSIANN-CCS, and FY-4A at daily scale; and IMERG, GSMaP, PERSIANN-CCS, FY-4A, and ERA5-Land at hourly scale. These findings will provide valuable feedback for improving the current satellite-based precipitation retrieval algorithms and also provide preliminary references for flood forecasting and natural disaster early warning

Comprehensive Comparisons of State-of-the-Art Gridded Precipitation Estimates for Hydrological Applications over Southern China

Satellite-based precipitation estimates with high quality and spatial-temporal resolutions play a vital role in forcing global or regional meteorological, hydrological, and agricultural models, which are especially useful over large poorly gauged regions. In this study, we apply various statistical indicators to comprehensively analyze the quality and compare the performance of five newly released satellite and reanalysis precipitation products against China Merged Precipitation Analysis (CMPA) rain gauge data, respectively, with 0.1° × 0.1° spatial resolution and two temporal scales (daily and hourly) over southern China from June to August in 2019. These include Precipitation Estimates from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5-Land), Fengyun-4 (FY-4A), Global Satellite Mapping of Precipitation (GSMaP), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG). Results indicate that: (1) all five products overestimate the accumulated rainfall in the summer, with FY-4A being the most severe; additionally, FY-4A cannot capture the spatial and temporal distribution characteristics of precipitation over southern China. (2) IMERG and GSMaP perform better than the other three datasets at both daily and hourly scales; IMERG correlates slightly better than GSMaP against CMPA data, while it performs worse than GSMaP in terms of probability of detection (POD). (3) ERA5-Land performs better than PERSIANN-CCS and FY-4A at daily scale but shows the worst correlation coefficient (CC), false alarm ratio (FAR), and equitable threat score (ETS) of all precipitation products at hourly scale. (4) The rankings of overall performance on precipitation estimations for this region are IMERG, GSMaP, ERA5-Land, PERSIANN-CCS, and FY-4A at daily scale; and IMERG, GSMaP, PERSIANN-CCS, FY-4A, and ERA5-Land at hourly scale. These findings will provide valuable feedback for improving the current satellite-based precipitation retrieval algorithms and also provide preliminary references for flood forecasting and natural disaster early warning

Glutathione S-Transferases S1, Z1 and A1 Serve as Prognostic Factors in Glioblastoma and Promote Drug Resistance through Antioxidant Pathways

The glutathione S-transferase (GST) family of detoxification enzymes can regulate the malignant progression and drug resistance of various tumors. Hematopoietic prostaglandin D synthase (HPGDS, also referred to as GSTS1), GSTZ1, and GSTA1 are abnormally expressed in multiple cancers, but their roles in tumorigenesis and development remain unclear. In this study, we used bioinformatics tools to analyze the connections of HPGDS, GSTZ1, and GSTA1 to a variety of tumors in genetic databases. Then, we performed biochemical assays in GBM cell lines to investigate the involvement of HPGDS in proliferation and drug resistance. We found that HPGDS, GSTZ1, and GSTA1 are abnormally expressed in a variety of tumors and are associated with prognoses. The expression level of HPGDS was significantly positively correlated with the grade of glioma, and high levels of HPGDS predicted a poor prognosis. Inhibiting HPGDS significantly downregulated GBM proliferation and reduced resistance to temozolomide by disrupting the cellular redox balance and inhibiting the activation of JNK signaling. In conclusion, this study suggested that HPGDS, GSTZ1, and GSTA1 are related to the progression of multiple tumors, and HPGDS is expected to be a prognostic factor in GBM