15 research outputs found

    Unraveling the nature of quasi van der Waals Epitaxy of magnetic topological insulators Cr: (BixSb1-x)2Te3 on a GaAs (111) substrate through coherently strained interface

    Full text link
    Quasi van der Waals Epitaxy (qvdWE) has been realized for decades at the interfaces between 3D and 2D materials or van der Waals materials. The growth of magnetic topological insulators (MTI) Cr: (BixSb1-x)2Te3 (CBST) on GaAs (111) substrates for Quantum Anomalous Hall Effect (QAH) is actually one of the examples of qvdWE, which is not well noticed despite the fact that its advantages have been used in growth of various MTI materials. This is distinguished from the growth of MTIs on other substrates. Although the qvdWE mode has been used in many 2D growth on III-V substrates, the specific features and mechanisms are not well demonstrated and summarized yet. Here in this work, we have for the first time shown the features of both coherent interfaces and the existence of strain originating from qvdWE at the same time.Comment: 5 figures, 1 table. Already shown in APS March Meeting 2023 and 202

    The Interaction Analysis between the Sympathetic and Parasympathetic Systems in CHF by Using Transfer Entropy Method

    No full text
    Congestive heart failure (CHF) is a cardiovascular disease associated with autonomic dysfunction, where sympathovagal imbalance was reported in many studies using heart rate variability (HRV). To learn more about the dynamic interaction in the autonomic nervous system (ANS), we explored the directed interaction between the sympathetic nervous system (SNS) and the parasympathetic nervous system (PNS) with the help of transfer entropy (TE). This article included 24-h RR interval signals of 54 healthy subjects (31 males and 23 females, 61.38 ± 11.63 years old) and 44 CHF subjects (8 males and 2 females, 19 subjects’ gender were unknown, 55.51 ± 11.44 years old, 4 in class I, 8 in class II and 32 in class III~IV, according to the New York Heart Association Function Classification), obtained from the PhysioNet database and then segmented into 5-min non-overlapping epochs using cubic spline interpolation. For each segment in the normal group and CHF group, frequency-domain features included low-frequency (LF) power, high-frequency (HF) power and LF/HF ratio were extracted as classical estimators of autonomic activity. In the nonlinear domain, TE between LF and HF were calculated to quantify the information exchanging between SNS and PNS. Compared with the normal group, an extreme decrease in LF/HF ratio (p = 0.000) and extreme increases in both TE(LF→HF) (p = 0.000) and TE(HF→LF) (p = 0.000) in the CHF group were observed. Moreover, both in normal and CHF groups, TE(LF→HF) was a lot greater than TE(HF→LF) (p = 0.000), revealing that TE was able to distinguish the difference in the amount of directed information transfer among ANS. Extracted features were further applied in discriminating CHF using IBM SPSS Statistics discriminant analysis. The combination of the LF/HF ratio, TE(LF→HF) and TE(HF→LF) reached the highest screening accuracy (83.7%). Our results suggested that TE could serve as a complement to traditional index LF/HF in CHF screening

    A Sleep Apnea Detection Method Based on Unsupervised Feature Learning and Single-Lead Electrocardiogram

    No full text

    An improved 3D-UNet-based brain hippocampus segmentation model based on MR images

    No full text
    Abstract Objective Accurate delineation of the hippocampal region via magnetic resonance imaging (MRI) is crucial for the prevention and early diagnosis of neurosystemic diseases. Determining how to accurately and quickly delineate the hippocampus from MRI results has become a serious issue. In this study, a pixel-level semantic segmentation method using 3D-UNet is proposed to realize the automatic segmentation of the brain hippocampus from MRI results. Methods: Two hundred three-dimensional T1-weighted (3D-T1) nongadolinium contrast-enhanced magnetic resonance (MR) images were acquired at Hangzhou Cancer Hospital from June 2020 to December 2022. These samples were divided into two groups, containing 175 and 25 samples. In the first group, 145 cases were used to train the hippocampus segmentation model, and the remaining 30 cases were used to fine-tune the hyperparameters of the model. Images for twenty-five patients in the second group were used as the test set to evaluate the performance of the model. The training set of images was processed via rotation, scaling, grey value augmentation and transformation with a smooth dense deformation field for both image data and ground truth labels. A filling technique was introduced into the segmentation network to establish the hippocampus segmentation model. In addition, the performance of models established with the original network, such as VNet, SegResNet, UNetR and 3D-UNet, was compared with that of models constructed by combining the filling technique with the original segmentation network. Results: The results showed that the performance of the segmentation model improved after the filling technique was introduced. Specifically, when the filling technique was introduced into VNet, SegResNet, 3D-UNet and UNetR, the segmentation performance of the models trained with an input image size of 48 × 48 × 48 improved. Among them, the 3D-UNet-based model with the filling technique achieved the best performance, with a Dice score (Dice score) of 0.7989 ± 0.0398 and a mean intersection over union (mIoU) of 0.6669 ± 0.0540, which were greater than those of the original 3D-UNet-based model. In addition, the oversegmentation ratio (OSR), average surface distance (ASD) and Hausdorff distance (HD) were 0.0666 ± 0.0351, 0.5733 ± 0.1018 and 5.1235 ± 1.4397, respectively, which were better than those of the other models. In addition, when the size of the input image was set to 48 × 48 × 48, 64 × 64 × 64 and 96 × 96 × 96, the model performance gradually improved, and the Dice scores of the proposed model reached 0.7989 ± 0.0398, 0.8371 ± 0.0254 and 0.8674 ± 0.0257, respectively. In addition, the mIoUs reached 0.6669 ± 0.0540, 0.7207 ± 0.0370 and 0.7668 ± 0.0392, respectively. Conclusion: The proposed hippocampus segmentation model constructed by introducing the filling technique into a segmentation network performed better than models built solely on the original network and can improve the efficiency of diagnostic analysis

    Novel Variant Serotype of Streptococcus suis Isolated from Piglets with Meningitis

    Full text link
    Choir apse, general view of the upper apse; Little remains of the abbey's important and influential medieval glazing. The windows of the Rayonnant choir and nave, probably the most important 13th-century ensemble in the Paris region before the glazing of the Sainte-Chapelle, were destroyed in the Revolution. They are documented only in a sketch, one of a series (Compiègne, Mus. Mun. Vivenel) made in 1794-1795 by Charles Percier, and the reliability of even this has been challenged (Lillich). Most of the glass outside of the ambulatory was reconstructed during the 19th century. Source: Grove Art Online; http://www.groveart.com/ (accessed 2/3/2008

    Strong phonon-magnon coupling of an O/Fe(001) surface

    No full text

    Viral infection detection using metagenomics technology in six poultry farms of eastern China.

    No full text
    With rapidly increasing animal pathogen surveillance requirements, new technologies are needed for a comprehensive understanding of the roles of pathogens in the occurrence and development of animal diseases. We applied metagenomic technology to avian virus surveillance to study the main viruses infecting six poultry farms in two provinces in eastern China. Cloacal/throat double swabs were collected from 60 birds at each farm according to a random sampling method. The results showed that the method could simultaneously detect major viruses infecting farms, including avian influenza virus, infectious bronchitis virus, Newcastle disease virus, rotavirus G, duck hepatitis B virus, and avian leukemia virus subgroup J in several farms. The test results were consistent with the results from traditional polymerase chain reaction (PCR) or reverse transcription-PCR analyses. Five H9N2 and one H3N8 avian influenza viruses were detected at the farms and were identified as low pathogenic avian influenza viruses according to HA cleavage sites analysis. One detected Newcastle disease virus was classified as Class II genotype I and avirulent type according to F0 cleavage sites analysis. Three avian infectious bronchitis viruses were identified as 4/91, CK/CH/LSC/99I and TC07-2 genotypes by phylogenetic analysis of S1 genes. The viral infection surveillance method using metagenomics technology enables the monitoring of multiple viral infections, which allows the detection of main infectious viruses

    Tuning the size of skyrmion by strain at the Co/Pt₃ interfaces

    Get PDF
    Based on density functional theory calculations, we elucidated the tunability of the atomic structures and magnetic interactions of Co/Pt₃ interface (one layer of hcp(0001) Co and three layers of fcc(111) Pt) and thus the skyrmion sizes using strain. The dispersion relations of the spin spiral in the opposite directions, E(q) and E(-q), were evaluated based on generalized Bloch equations. Effective exchange coupling (EC) and Dzyaloshinsky-Moriya interaction (DMI) parameters between different neighbors Ji and di at different lattice constants were derived by fitting the resulting spin spiral dispersion E(q) to EC model with DMI and E(q)- E(-q) formula, respectively. We observed an increase in DMI and a significant decrease in EC with an increase in strain. Hence, the size of Ne´ el-type skyrmions determined by the ratio of EC/DMI can be controlled by applying strain, leading to an effective approach to tailor the formation of skyrmion lattices by inducing slight structural modifications on the magnetic thin films

    Regulation of cerebral blood flow boosts precise brain targeting of vinpocetine-derived ionizable-lipidoid nanoparticles

    No full text
    Abstract Despite advances in active drug targeting for blood-brain barrier penetration, two key challenges persist: first, attachment of a targeting ligand to the drug or drug carrier does not enhance its brain biodistribution; and second, many brain diseases are intricately linked to microcirculation disorders that significantly impede drug accumulation within brain lesions even after they cross the barrier. Inspired by the neuroprotective properties of vinpocetine, which regulates cerebral blood flow, we propose a molecular library design centered on this class of cyclic tertiary amine compounds and develop a self-enhanced brain-targeted nucleic acid delivery system. Our findings reveal that: (i) vinpocetine-derived ionizable-lipidoid nanoparticles efficiently breach the blood-brain barrier; (ii) they have high gene-loading capacity, facilitating endosomal escape and intracellular transport; (iii) their administration is safe with minimal immunogenicity even with prolonged use; and (iv) they have potent pharmacologic brain-protective activity and may synergize with treatments for brain disorders as demonstrated in male APP/PS1 mice
    corecore