Determining the local dark matter density with LAMOST data

Measurement of the local dark matter density plays an important role in both Galactic dynamics and dark matter direct detection experiments. However, the estimated values from previous works are far from agreeing with each other. In this work, we provide a well-defined observed sample with 1427 G \& K type main-sequence stars from the LAMOST spectroscopic survey, taking into account selection effects, volume completeness, and the stellar populations. We apply a vertical Jeans equation method containing a single exponential stellar disk, a razor thin gas disk, and a constant dark matter density distribution to the sample, and obtain a total surface mass density of $\rm {78.7 ^{+3.9}_{-4.7}\ M_{\odot}\ pc^{-2}}$up to 1 kpc and a local dark matter density of$0.0159^{+0.0047}_{-0.0057}\,\rm M_{\odot}\,\rm pc^{-3}$. We find that the sampling density (i.e. number of stars per unit volume) of the spectroscopic data contributes to about two-thirds of the uncertainty in the estimated values. We discuss the effect of the tilt term in the Jeans equation and find it has little impact on our measurement. Other issues, such as a non-equilibrium component due to perturbations and contamination by the thick disk population, are also discussed.Comment: 11 pages, 10 figure

Measurements of Correlated Insulator Gaps in a Transition Metal Dichalcogenide Moir\'e Superlattice

Moir\'e superlattices of transitional metal dichalcogenides exhibit strong electron-electron interaction that has led to experimental observations of Mott insulators and generalized Wigner crystals. In this letter, we report direct measurements of the thermodynamic gaps of these correlated insulating states in a dual-gate WS2/WSe2 moir\'e bilayer. We employ the microwave impedance microscopy to probe the electronic features in both the graphene top gate and the moir\'e bilayer, from which we extract the doping dependence of the chemical potential of the moir\'e bilayer and the energy gaps for various correlated insulating states utilizing the Landau quantization of graphene. These gaps are relatively insensitive to the application of an external electric field to the WS2/WSe2 moir\'e bilayer

Valley-polarized Exitonic Mott Insulator in WS2/WSe2 Moir\'e Superlattice

Strongly enhanced electron-electron interaction in semiconducting moir\'e superlattices formed by transition metal dichalcogenides (TMDCs) heterobilayers has led to a plethora of intriguing fermionic correlated states. Meanwhile, interlayer excitons in a type-II aligned TMDC heterobilayer moir\'e superlattice, with electrons and holes separated in different layers, inherit this enhanced interaction and strongly interact with each other, promising for realizing tunable correlated bosonic quasiparticles with valley degree of freedom. We employ photoluminescence spectroscopy to investigate the strong repulsion between interlayer excitons and correlated electrons in a WS2/WSe2 moir\'e superlattice and combine with theoretical calculations to reveal the spatial extent of interlayer excitons and the band hierarchy of correlated states. We further find that an excitonic Mott insulator state emerges when one interlayer exciton occupies one moir\'e cell, evidenced by emerging photoluminescence peaks under increased optical excitation power. Double occupancy of excitons in one unit cell requires overcoming the energy cost of exciton-exciton repulsion of about 30-40 meV, depending on the stacking configuration of the WS2/WSe2 heterobilayer. Further, the valley polarization of the excitonic Mott insulator state is enhanced by nearly one order of magnitude. Our study demonstrates the WS2/WSe2 moir\'e superlattice as a promising platform for engineering and exploring new correlated states of fermion, bosons, and a mixture of both

Risk analysis and assessment of water resource carrying capacity based on weighted gray model with improved entropy weighting method in the central plains region of China

The issue of global water shortage is a serious concern. The scientific evaluation of water resource carrying capacity (WRCC) serves as the foundation for implementing measures to protect water resources. In addition, most of the studies are based on the analysis and research of regional WRCC from the aspects of water quantity and water quality. There are few studies on the four aspects of water resources endowment conditions, society, economy and ecological environment, which is difficult to scientifically and accurately reflect the analysis and evaluation of regional WRCC by the four systems. Therefore, it is necessary to conduct a deeper discussion and Analysis on this topic. This study presents a WRCC index system and corresponding ranking criteria based on 20 influencing factors from four aspects: water resources endowment (WRE), economy, society, and ecological environment. In addition, by combining the improved entropy weighting method (EWM) with gray correlation analysis, the weighted gray technique for order preference by similarity to an ideal solution (TOPSIS) model is proposed for analyzing and assessing WRCC risk. Finally, the WRCC of the study area from 2012 to 2021 is comprehensively evaluated in the central plains region of China (CPROC) as an example. The results show that the comprehensive evaluation obtained a multi-year average value of 0.2935, and the water resources shortage in the CPROC is generally in grade III status. The comprehensive average value of Beijing is 0.345, and the comprehensive average value of Henan is 0.397. The overall degree of water resources shortage is in the state of grade V shortage, Shaanxi is in the state of grade IV shortage, and the degree of water resources in Tianjin and Shanxi is relatively good. This study provides corresponding scientific basis and methodological guidance for the sustainable utilization of water resources and healthy socio-economic performance in the CPROC

CDT-CAD: Context-Aware Deformable Transformers for End-to-End Chest Abnormality Detection on X-Ray Images

: Deep learning methods have achieved great success in medical image analysis domain. However, most of them suffer from slow convergency and high computing cost, which prevents their further widely usage in practical scenarios. Moreover, it has been proved that exploring and embedding context knowledge in deep network can significantly improve accuracy. To emphasize these tips, we present CDT-CAD, i.e., context-aware deformable transformers for end-to-end chest abnormality detection on X-Ray images. CDT-CAD firstly constructs an iterative context-aware feature extractor, which not only enlarges receptive fields to encode multi-scale context information via dilated context encoding blocks, but also captures unique and scalable feature variation patterns in wavelet frequency domain via frequency pooling blocks. Afterwards, a deformable transformer detector on the extracted context features is built to accurately classify disease categories and locate regions, where a small set of key points are sampled, thus leading the detector to focus on informative feature subspace and accelerate convergence speed. Through comparative experiments on Vinbig Chest and Chest Det 10 Datasets, CDT-CAD demonstrates its effectiveness in recognizing chest abnormities and outperforms 1.4% and 6.0% than the existing methods in AP50 and AR on VinBig dateset, and 0.9% and 2.1% on Chest Det-10 dataset, respectively

PLGA Microspheres of hGH of Preserved Native State Prepared Using a Self-Regulated Process

The challenges of formulating recombinant human growth hormone (rhGH) into sustained-release polymeric microspheres include two mutual causal factors, protein denaturing by the formulation process and severe initial burst release related with relative high dose. The stabilizers to protect the proteins must not evoke osmotic pressure inside the microspheres, and the contact of the protein with the interface between water and organic solution of the polymer must be minimized. To meet these criteria, rhGH was pre-formulated into polysaccharide particles via an aqueous–aqueous emulsion in the present study, followed by encapsulating the particles into microspheres through a self-regulated process to minimize the contact of the protein with the water–oil interface. Polysaccharides as the protein stabilizer did not evoke osmotic pressure as small sugar stabilizers, the cause of severe initial burst release. Reduced initial burst enabled reduced protein loading to 9% (from 22% of the once commercialized Nutropin depot), which in turn reduced the dosage form index from 80 to 8.7 and eased the initial burst. A series of physical chemical characterizations as well as biologic and pharmacokinetic assays confirmed that the present method is practically feasible for preparing microspheres of proteins

Molecule-Confined Engineering toward Superconductivity and Ferromagnetism in Two-Dimensional Superlattice

Superconductivity is mutually exclusive with ferromagnetism, because the ferromagnetic exchange field is often destructive to superconducting pairing correlation. Well-designed chemical and physical methods have been devoted to realize their coexistence only by structural integrity of inherent superconducting and ferromagnetic ingredients. However, such coexistence in freestanding structure with nonsuperconducting and nonferromagnetic components still remains a great challenge up to now. Here, we demonstrate a molecule-confined engineering in two-dimensional organic–inorganic superlattice using a chemical building-block approach, successfully realizing first freestanding coexistence of superconductivity and ferromagnetism originated from electronic interactions of nonsuperconducting and nonferromagnetic building blocks. We unravel totally different electronic behavior of molecules depending on spatial confinement: flatly lying Co­(Cp)₂ molecules in strongly confined SnSe₂ interlayers weaken the coordination field, leading to spin transition to form ferromagnetism; meanwhile, electron transfer from cyclopentadienyls to the Se–Sn–Se lattice induces superconducting state. This entirely new class of coexisting superconductivity and ferromagnetism generates a unique correlated state of Kondo effect between the molecular ferromagnetic layers and inorganic superconducting layers. We anticipate that confined molecular chemistry provides a newly powerful tool to trigger exotic chemical and physical properties in two-dimensional matrixes