Topological chiral kagome lattice

Chirality, a fundamental structural property of crystals, can induce many unique topological quantum phenomena. In kagome lattice, unconventional transports have been reported under tantalizing chiral charge order. Here, we show how by deforming the kagome lattice to obtain a three-dimensional (3D) chiral kagome lattice in which the key band features of the non-chiral 2D kagome lattice - flat energy bands, van Hove singularities (VHSs), and degeneracies - remain robust in both the $k_z$ = 0 and $\pi$ planes in momentum space. Given the handedness of our kagome lattice, degenerate momentum points possess quantized Chern numbers, ushering in the realization of Weyl fermions. Our 3D chiral kagome lattice surprisingly exhibits 1D behavior on its surface, where topological surface Fermi arc states connecting Weyl fermions are dispersive in one momentum direction and flat in the other direction. These 1D Fermi arcs open up unique possibilities for generating unconventional non-local transport phenomena at the interfaces of domains with different handedness, and the associated enhanced conductance as the separation of the leads on the surface is increased. Employing first-principles calculations, we investigate in-depth the electronic and phononic structures of representative materials within the ten space groups that can support topological chiral kagome lattices. Our study opens a new research direction that integrates the advantages of structural chirality with those of a kagome lattice and thus provides a new materials platform for exploring unique aspects of correlated topological physics in chiral lattices.Comment: 7 pages, 4 figure

WD‐UNeXt: Weight loss function and dropout U‐Net with ConvNeXt for automatic segmentation of few shot brain gliomas

Abstract Accurate segmentation of brain gliomas (BG) is a crucial and challenging task for effective treatment planning in BG therapy. This study presents the weight loss function and dropout U‐Net with ConvNeXt block (WD‐UNeXt), which precisely segments BG from few shot MRI. The ConvNeXt block, which comprises the main body of the network, is a structure that can extract more detailed features from images. The weight loss function addresses the issue of category imbalance, thereby enhancing the network's ability to achieve more precise segmentation. The training set of BraTS2019 was used to train the network and apply it to test data. Dice similarity coefficient (DSC), sensitivity (Sen), specificity (Spec) and Hausdorff distance (HD) were used to assess the performance of the method. The experimental results demonstrate that the DSC of whole tumour, tumour core and enhancing tumour reached 0.934, 0.911 and 0.851, respectively. Sen of the sub‐regions achieved 0.922, 0.911 and 0.867. Spec and HD reached 1.000, 1.000, 1.000 and 3.224, 2.990, 2.844, respectively. Compared with the performance of state‐of‐the‐art methods, the DSC and HD of WD‐UNeXt were improved to varying degrees. Therefore, this method has considerable potential for the segmentation of BG

Prediction of Thermal Barrier Coatings Microstructural Features Based on Support Vector Machine Optimized by Cuckoo Search Algorithm

Microstructural features have a vital effect on the comprehensive performance of thermal barrier coatings (TBCs) and highly depend on the thermal spray processing parameters. Herein, a novel hybrid machine-learning method was proposed to predict the microstructural features of TBCs using thermal spray processing parameters based on a support vector machine method optimized by the cuckoo search algorithm (CS-SVM). In this work, atmospheric-plasma-sprayed (APS) TBCs samples with multifarious microstructural features were acquired by modifying the spray powder size, spray distance, and spray power during thermal spray processing. The processing parameters were used as the inputs for the CS-SVM model. Then, the porosity, the pore-to-crack ratio, the maximum Feret’s diameter, the aspect ratio, and the circularity were counted and treated as the targets for the CS-SVM model. After optimization and training procedure of the CS-SVM model, the predicted results were compared to the results of experimental data, as a result, the squared correlation coefficient (R2) of CS-SVM model showed that the prediction accuracy reached by over 95%, and the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were less than 0.1, which also verified the reliability of the CS-SVM model. Finally, this study proposed a novel and efficient microstructural feature prediction that could be potentially employed to improve the performance of TBCs in service

rTMS Induces Brain Functional and Structural Alternations in Schizophrenia Patient With Auditory Verbal Hallucination

BackgroundLow-frequency transcranial magnetic stimulation (rTMS) over the left temporoparietal cortex reduces the auditory verbal hallucination (AVH) in schizophrenia. However, the underlying neural basis of the rTMS treatment effect for schizophrenia remains not well understood. This study investigates the rTMS induced brain functional and structural alternations and their associations with clinical as well as neurocognitive profiles in schizophrenia patients with AVH.MethodsThirty schizophrenia patients with AVH and thirty-three matched healthy controls were enrolled. The patients were administered by 15 days of 1 Hz rTMS delivering to the left temporoparietal junction (TPJ) area. Clinical symptoms and neurocognitive measurements were assessed at pre- and post-rTMS treatment. The functional (amplitude of low-frequency fluctuation, ALFF) and structural (gray matter volume, GMV) alternations were compared, and they were then used to related to the clinical and neurocognitive measurements after rTMS treatment.ResultsThe results showed that the positive symptoms, including AVH, were relieved, and certain neurocognitive measurements, including visual learning (VisLearn) and verbal learning (VerbLearn), were improved after the rTMS treatment in the patient group. Furthermore, the rTMS treatment induced brain functional and structural alternations in patients, such as enhanced ALFF in the left superior frontal gyrus and larger GMV in the right inferior temporal cortex. The baseline ALFF and GMV values in certain brain areas (e.g., the inferior parietal lobule and superior temporal gyrus) could be associated with the clinical symptoms (e.g., positive symptoms) and neurocognitive performances (e.g., VerbLearn and VisLearn) after rTMS treatment in patients.ConclusionThe low-frequency rTMS over the left TPJ area is an efficacious treatment for schizophrenia patients with AVH and could selectively modulate the neural basis underlying psychiatric symptoms and neurocognitive domains in schizophrenia

Nondestructive Evaluation of Thermal Barrier Coatings Interface Delamination Using Terahertz Technique Combined with SWT-PCA-GA-BP Algorithm

Thermal barrier coatings (TBCs) are usually subjected to the combined action of compressive stress, tensile stress, and bending shear stress, resulting in the interfacial delamination of TBCs, and finally causing the ceramic top coat to peel off. Hence, it is vital to detect the early-stage subcritical delamination cracks. In this study, a novel hybrid artificial neural network combined with the terahertz nondestructive technology was presented to predict the thickness of interface delamination in the early stage. The finite difference time domain (FDTD) algorithm was used to obtain the raw terahertz time-domain signals of 32 TBCs samples with various thicknesses of interface delamination, not only that, the influence of roughness and the thickness of the ceramic top layer were considered comprehensively when modeling. The stationary wavelet transform (SWT) and principal component analysis (PCA) methods were employed to extract the signal features and reduce the data dimensions before modeling, to make the cumulative contribution rate reach 100%, the first 31 components of the SWT detail data was used as the input data during modeling. Finally, a back propagation (BP) neural network method optimized by the genetic algorithm (GA-BP) was proposed to set up the interface delamination thickness prediction model. As a result, the root correlation coefficient R2 reached over 0.95, the various errors—including the mean square error, mean squared percentage error, and mean absolute percentage error—were less than or equal to 0.53. All these indicators proved that the trained hybrid SWT-PCA-GA-BP model had excellent prediction performance and high accuracy. Finally, this work proposed a novel and convenient interface delamination evaluation method that could also be potentially utilized to evaluate the structural integrity of TBCs

Tissue Distribution of trans-Resveratrol and Its Metabolites after Oral Administration in Human Eyes

Purpose. This study was performed to measure the concentration of trans-resveratrol and its three metabolites in human eyes. Methods. The patients who underwent pars plana vitrectomy for rhegmatogenous retinal detachment were included. The participants were orally given trans-resveratrol-based supplement (Longevinex®). A suitable amount of conjunctiva, aqueous humor, and vitreous humor were obtained during the operation. High-performance liquid chromatography (HPLC) with mass spectrometry (LC/MS/MS) was used to detect the concentration of trans-resveratrol and its three metabolites in the various samples. Results. The average concentration of resveratrol in the conjunctiva was 17.19 ± 15.32 nmol/g (mean ± SD). The concentration of resveratrol in the aqueous humor was close to the limit of detection, but its metabolites could be quantified. The concentrations of resveratrol metabolites in the aqueous humor can be detected. In the vitreous humor, the average concentration of resveratrol-3-O-sulfate was 62.95 ± 41.97 nmol/L. The sulfate conjugations of resveratrol were recovered in the conjunctiva, aqueous humor, and vitreous humor. Conclusions. Resveratrol and its three metabolites can be detected in the ocular tissues after oral administration. Although the concentration of parent resveratrol was low in the eyes, its metabolites could be detected and may have a role in the treatment of ocular diseases

East Asian climate changes during the Quaternary as viewed from multiple proxies and modeling results

Quaternary monsoon changes in East Asia have been extensively investigated by proxy records from continental and marine archives. However, these proxy indicators often show controversial characteristics in terms of trends and rhythms, perplexing understanding of orbital-scale monsoon dynamics. Here we review the orbital-scale monsoon variability and dynamics in East Asia by comparing multiple proxies from loess, lake, speleothem, and marine records with the HadCM3 modeling result. Evolutionary power spectra of loess grain size and sea surface temperature exhibit a remarkable shift from 41- to 100-kyr cycles across the mid-Pleistocene transition (MPT), whereas other proxy records (e.g. 13C of loess carbonate, pollen concentration in lake sediments, and magnetic mineral compositions in marine sediments) display strong and persistent precession cycles through the Quaternary, along with distinct 100-kyr cycles after the MPT. Simulations with the HadCM3 climate model reveal that the effects of orbital parameters, ice volume, and CO2 concentration on the temperature, precipitation, and southerly winds are seasonally and spatially different in East Asia. In the summer season, orbitally induced insolation plays a dominant role in driving changes in these three climate variables except for summer precipitation in south China (20-30ºN), whilst annual changes in precipitation and temperature are jointly affected by insolation, ice volume, and CO2. Proxy-model comparison suggests that several land-based proxies are sensitive to changes in summer precipitation, annual precipitation, and annual temperature, though their responses to astronomical, ice, and CO2 forcing being quite different between north and south China. Our proxy-model comparison reveals that diverse expression of Quaternary climate periodicities was provoked by different sensitivities of marine and terrestrial proxies to seasonal and/or annual changes in precipitation and temperature, and by different responses of temperature and precipitation to insolation and ice/CO2 forcing. We suggest that understanding of Quaternary climate change can be deepened by further comparison of quantitatively reconstructed paleotemperature and precipitation data with results of high-resolution, regional climate models

Exploring the mechanism of luteolin by regulating microglia polarization based on network pharmacology and in vitro experiments

Abstract Neuroinflammation manifests following injury to the central nervous system (CNS) and M1/M2 polarization of microglia is closely associated with the development of this neuroinflammation. In this study, multiple databases were used to collect targets regarding luteolin and microglia polarization. After obtaining a common target, a protein–protein interaction (PPI) network was created and further analysis was performed to obtain the core network. Molecular docking of the core network with luteolin after gene enrichment analysis. In vitro experiments were used to examine the polarization of microglia and the expression of related target proteins. A total of 77 common targets were obtained, and the core network obtained by further analysis contained 38 proteins. GO and KEGG analyses revealed that luteolin affects microglia polarization in regulation of inflammatory response as well as the interleukin (IL)-17 and tumor necrosis factor (TNF) signaling pathways. Through in vitro experiments, we confirmed that the use of luteolin reduced the expression of inducible nitric oxide synthase (iNOS), IL-6, TNF-α, p-NFκBIA (p-IκB-α), p-NFκB p65, and MMP9, while upregulating the expression of Arg-1 and IL-10. This study reveals various potential mechanisms by which luteolin induces M2 polarization in microglia to inhibit the neuroinflammatory response