High mobility in a van der Waals layered antiferromagnetic metal

Magnetic van der Waals (vdW) materials have been heavily pursued for fundamental physics as well as for device design. Despite the rapid advances, so far magnetic vdW materials are mainly insulating or semiconducting, and none of them possesses a high electronic mobility - a property that is rare in layered vdW materials in general. The realization of a magnetic high-mobility vdW material would open the possibility for novel magnetic twistronic or spintronic devices. Here we report very high carrier mobility in the layered vdW antiferromagnet GdTe3. The electron mobility is beyond 60,000 cm2 V-1 s-1, which is the highest among all known layered magnetic materials, to the best of our knowledge. Among all known vdW materials, the mobility of bulk GdTe3 is comparable to that of black phosphorus, and is only surpassed by graphite. By mechanical exfoliation, we further demonstrate that GdTe3 can be exfoliated to ultrathin flakes of three monolayers, and that the magnetic order and relatively high mobility is retained in approximately 20-nm-thin flakes

Depletion of thymopoietin inhibits proliferation and induces cell cycle arrest/apoptosis in glioblastoma cells

BACKGROUND: Glioblastoma (GBM) is the most malignant nervous system tumor with an almost 100 % recurrence rate. Thymopoietin (TMPO) has been demonstrated to be upregulated in various tumors, including lung cancer, breast cancer, and so on, but its role in GBM has not been reported. This study was aimed to determine the role of TMPO in GBM. METHODS: Publicly available Oncomine dataset analysis was used to explore the expression level of TMPO in GBM specimens. Then the expression of TMPO was knocked down in GBM cells using lentiviral system, and the knockdown efficacy was further validated by real-time quantitative PCR and western blot analysis. Furthermore, the effects of TMPO silencing on GBM cell proliferation and apoptosis were examined by MTT, colony formation, and flow cytometry analysis. Meanwhile, the expression of apoptotic markers caspase-3 and poly(ADP-ribose) polymerase (PARP) were investigated by western blot analysis. RESULTS: This study observed that the expression of TMPO in GBM specimens was remarkably higher than that in normal brain specimens. Moreover, knockdown of TMPO could significantly inhibit cell proliferation and arrest cell cycle progression at the G2/M phase. It also found that TMPO knockdown promoted cell apoptosis by upregulation of the cleavage of caspase-3 and PARP protein levels which are the markers of apoptosis. CONCLUSIONS: The results suggested TMPO might be a novel therapeutic target for GBM

Unraveling the Role of the rssC Gene of Serratia marcescens by Atomic Force Microscopy

100學年度研究獎補助論文[[abstract]]The product and direct role of the rssC gene of Serratia marcescens is unknown. For unraveling the role of the rssC gene, atomic force microscopy has been used to identify the surfaces of intact S. marcescens wild-type CH-1 cells and rssC mutant CH-1ΔC cells. The detailed surface topographies were directly visualized, and quantitative measurements of the physical properties of the membrane structures were provided. CH-1 and CH-1ΔC cells were observed before and after treatment with lysozyme, and their topography-related parameters, e.g., a valley-to-peak distance, mean height, surface roughness, and surface root-mean-square values, were defined and compared. The data obtained suggest that the cellular surface topography of mutant CH-1ΔC becomes rougher and more precipitous than that of wild-type CH-1 cells. Moreover, it was found that, compared with native wild-type CH-1, the cellular surface topography of lysozyme-treated CH-1 was not changed profoundly. The product of the rssC gene is thus predicted to be mainly responsible for fatty-acid biosynthesis of the S. marcescens outer membrane. This study represents the first direct observation of the structural changes in membranes of bacterial mutant cells and offers a new prospect for predicting gene expression in bacterial cells.[[journaltype]]國外[[incitationindex]]SCI[[booktype]]紙本[[countrycodes]]GB

Free-surface topography measurements of liquid layers over a smoothly varying bed

This study introduces a single-camera synthetic Schlieren technique for measuring free-surface topography in fluid layers over a smoothly varying solid bed. By modeling light refraction through weakly deformed air–liquid and weakly varying liquid–solid interfaces, we establish a linear relationship between free-surface gradients and pattern displacements that yields an explicit bed-independent formulation for upward-looking configurations. The proposed framework incorporates coordinate mapping to correct refraction-induced parallax distortion influenced by the bed shape. Validation experiments featuring sinusoidal bed topography and wedge-shaped sloped bed topography achieve accurate spatiotemporal reconstruction of both static capillary meniscus profiles and dynamic water drop ripple evolution. The present method advances experimental capabilities for quantifying interfacial hydrodynamics in multi-layer fluid systems.</p

EDT-MCFEF: a multi-channel feature fusion model for emergency department triage of medical texts

IntroductionTriage is a pivotal function within the operational framework of an emergency department, as it directly influences patient outcomes and hospital efficiency. However, traditional triage methods frequently depend on human judgment, which is susceptible to high subjectivity and low efficiency.MethodsTo address these issues, this paper presents a novel emergency department triage algorithm. The proposed EDT-MCFEF (Emergency Triage Algorithm Based on Multi-Channel Feature Extraction and Fusion) addresses numerous shortcomings of conventional triage methodologies. The model employs a hybrid masking approach and RoBERTa (Robustly Optimized BERT Approach) to facilitate feature enhancement and word vector processing of text. Moreover, the model employs a convolutional neural network (CNN) and a multi-headed attention (MHA) mechanism to extract text features from multiple channels, effectively capturing both local and global features. Furthermore, this paper introduces a multi-channel feature fusion method, which integrates local and global features and achieves comprehensive learning and optimization of feature information through dynamic weight adjustment.Results and discussionThe objective of this model is to enhance the accuracy and efficiency of emergency department triage, thereby providing scientific and technological support to the emergency department. In this paper, two medical text datasets are employed for experimental validation: a self-built emergency department triage dataset and a medical literature abstract dataset. The emergency department triage dataset consists of 28,000 English-annotated samples from 11 clinical departments, while the medical literature abstract dataset is a publicly available dataset (https://huggingface.co/datasets/123rc/medical_text). The experimental findings demonstrate that the proposed model exhibits superior accuracy to seven benchmark models utilized in this study on both medical text datasets, indicating its efficacy in handling imbalanced datasets. This suggests enhanced generalization and robustness. In addition to its strong classification ability, the model exhibits favorable interpretability through its multi-channel design, and the hybrid masking strategy supports data minimization and privacy protection, aligning with ethical AI principles. This approach holds promise for integration into clinical decision support systems for improved triage accuracy. The models and the self-built dataset presented in this paper are available at https://github.com/Yiii-master/EDT-MCFEF

Galactic Cirri at High Galactic Latitudes: I. Investigating Scatter in Slopes between Optical and far-Infrared Intensities

Based on the slopes between DESI $g,r$ and IRAS 100 $\mu m$ intensities, specifically $k_{g}$ and $k_{r}$, we have constructed a substantial sample of Galactic cirri. This sample covers 561.25 deg$^2$ at high Galactic latitudes (|b| $\geq$ 30$^{\circ}$), allowing for a systematic study of the physical parameters of the Galactic cirrus on a large scale, such as $g-r$ color, dust temperature, asymmetry factor and albedo. The ratio of $k_{g}$ and $k_{r}$ is consistent with the diffuse Galactic starlight model, suggesting that the diffuse starlight within our own Galaxy serves as the primary illumination source for the cirrus. Both $k_{g}$ and $k_{r}$ decrease slowly with increasing Galactic latitudes and IRAS 100 $\mu m$ intensities, while they do not have a correlation with Galactic longitudes. The distribution of $k_{g}$ and $k_{r}$ confirms a significant scatter in the slopes, reaching a factor of 4-5. Such large scatter cannot be explained by the weak correlation between the slopes and Galactic latitudes and IRAS 100 $\mu m$ intensities. Instead, it is attributed to substantial variations in the intrinsic properties of the dust, e.g., asymmetry factor and albedo. We propose that the properties of dust particles play a critical role in the observed scatter in slopes, making them the primary contributing factors. Moreover, the variations in dust properties within the cirrus are localized rather than exhibiting large-scale gradients.Comment: 26 pages, 16 figures, 2 tables. Accepted for publication in A

Asymmetric Synchronous Reference Frame-Based Frequency Coupling Suppression Control for Single-Phase Grid-Tied Converters

For single-phase grid-tied voltage-source converters (VSCs), frequency coupling suppression control (FCSC) emerges as a promising technique, streamlining controller design and stability analysis. However, its performance significantly degrades in the presence of grid frequency variations. This article presents an asymmetric synchronous reference frame (ASRF)-based FCSC for single-phase grid-tied converters. Leveraging the inverse generalized Park transformation-based symmetrical phase-locked loop (IGPT-SPLL) and the ASRF structure, both grid frequency adaptivity and frequency coupling suppression are realized. Under this control, the studied system is accurately modeled as a simple single-input single-output (SISO) admittance, facilitating design-oriented analysis. The proposed control method stands out for its grid frequency adaptability and the achievement of zero steady-state current error, all accomplished with the utilization of proportional-integral (PI) controllers only. Simulations and experimental results validate the effectiveness of the proposed method.</p

Learning Natural Consistency Representation for Face Forgery Video Detection

Face Forgery videos have elicited critical social public concerns and various detectors have been proposed. However, fully-supervised detectors may lead to easily overfitting to specific forgery methods or videos, and existing self-supervised detectors are strict on auxiliary tasks, such as requiring audio or multi-modalities, leading to limited generalization and robustness. In this paper, we examine whether we can address this issue by leveraging visual-only real face videos. To this end, we propose to learn the Natural Consistency representation (NACO) of real face videos in a self-supervised manner, which is inspired by the observation that fake videos struggle to maintain the natural spatiotemporal consistency even under unknown forgery methods and different perturbations. Our NACO first extracts spatial features of each frame by CNNs then integrates them into Transformer to learn the long-range spatiotemporal representation, leveraging the advantages of CNNs and Transformer on local spatial receptive field and long-term memory respectively. Furthermore, a Spatial Predictive Module~(SPM) and a Temporal Contrastive Module~(TCM) are introduced to enhance the natural consistency representation learning. The SPM aims to predict random masked spatial features from spatiotemporal representation, and the TCM regularizes the latent distance of spatiotemporal representation by shuffling the natural order to disturb the consistency, which could both force our NACO more sensitive to the natural spatiotemporal consistency. After the representation learning stage, a MLP head is fine-tuned to perform the usual forgery video classification task. Extensive experiments show that our method outperforms other state-of-the-art competitors with impressive generalization and robustness