Glass transitions in two-dimensional suspensions of colloidal ellipsoids

We observed a two-step glass transition in monolayers of colloidal ellipsoids by video microscopy. The glass transition in the rotational degree of freedom was at a lower density than that in the translational degree of freedom. Between the two transitions, ellipsoids formed an orientational glass. Approaching the respective glass transitions, the rotational and translational fastest-moving particles in the supercooled liquid moved cooperatively and formed clusters with power-law size distributions. The mean cluster sizes diverge in power law as approaching the glass transitions. The clusters of translational and rotational fastest-moving ellipsoids formed mainly within pseudo-nematic domains, and around the domain boundaries, respectively

Self-diffusion in two-dimensional hard ellipsoid suspensions

We studied the self-diffusion of colloidal ellipsoids in a monolayer near a flat wall by video microscopy. The image processing algorithm can track the positions and orientations of ellipsoids with sub-pixel resolution. The translational and rotational diffusions were measured in both the lab frame and the body frame along the long and short axes. The long-time and short-time diffusion coefficients of translational and rotational motions were measured as functions of the particle concentration. We observed sub-diffusive behavior in the intermediate time regime due to the caging of neighboring particles. Both the beginning and the ending times of the intermediate regime exhibit power-law dependence on concentration. The long-time and short-time diffusion anisotropies change non-monotonically with concentration and reach minima in the semi-dilute regime because the motions along long axes are caged at lower concentrations than the motions along short axes. The effective diffusion coefficients change with time t as a linear function of (lnt)/t for the translational and rotational diffusions at various particle densities. This indicates that their relaxation functions decay according to 1/t which provides new challenges in theory. The effects of coupling between rotational and translational Brownian motions were demonstrated and the two time scales corresponding to anisotropic particle shape and anisotropic neighboring environment were measured

Effect of Workpiece Motion on Forming Velocity in Electromagnetic Forming

The effect of workpiece motion on the forming velocity is analysed by the finite element method. To study the two factors of workpiece displacement and motional electromotive force, a static model, an incomplete motional model and a complete motional model are created. The incomplete motional model is simulated by the finite element software COMSOL, while the complete motional model is simulated by another finite element software Flux. To ensure the correctness of the model, the static model is created by both softwares. For the specific system treated in this paper, the results show that when the workpiece velocity is below 100 m/s, the workpiece displacement has only a small effect on the forming velocity. But when the workpiece velocity is above 200 m/s, the effect of the workpiece displacement on the forming velocity must be taken into account in the finite element model of the electromagnetic forming process

Development of Space-Time-Controlled Multi-Stage Pulsed Magnetic Field Forming and Manufacturing Technology at the WHMFC*

In November 2011, the Project of Basic Research of Forming by Space-Time-Controlled Multi-Stage Pulsed Magnetic Field (Stic-Must-PMF) was supported by the National Basic Research Program of China (973 Project, 2011.11-2016.08). It is aimed at achieving breakthroughs in manufacturing technology to solve current problems in forming largescale and complex sheet and tube parts and components, imposed by the limitations of existing equipment and materials forming properties. The objective of our research group focuses on the design principles and structural layout optimization of Stic-Must-PMF facility. And this paper will report the development of Stic-Must-PMF forming and manufacturing technology at the Wuhan National High Magnetic Field Center (WHMFC) including numerical modeling, experimental setup and experimental studies

Glass transitions in monolayers of colloidal ellipsoids

Glass formers constitute of anisotropic particles was mainly studied by simulations in three dimensions with incomplete phase diagrams. Here we studied the structures and the glassy dynamics for translational and rotational motions in quasi-two dimensional (2D) suspensions of colloidal ellipsoids at the single-particle level. At high densities, ellipsoids with large aspect ratio formed psuedo-nematic domains. Video microscopy revealed a two-step glass transition: rotational motion first becomes glassy due to the inter-domain freezing, then translational motion become glassy at a higher density due to inner-domain freezing. Between the two transitions, ellipsoids formed a

ASPS: Augmented Segment Anything Model for Polyp Segmentation

Polyp segmentation plays a pivotal role in colorectal cancer diagnosis. Recently, the emergence of the Segment Anything Model (SAM) has introduced unprecedented potential for polyp segmentation, leveraging its powerful pre-training capability on large-scale datasets. However, due to the domain gap between natural and endoscopy images, SAM encounters two limitations in achieving effective performance in polyp segmentation. Firstly, its Transformer-based structure prioritizes global and low-frequency information, potentially overlooking local details, and introducing bias into the learned features. Secondly, when applied to endoscopy images, its poor out-of-distribution (OOD) performance results in substandard predictions and biased confidence output. To tackle these challenges, we introduce a novel approach named Augmented SAM for Polyp Segmentation (ASPS), equipped with two modules: Cross-branch Feature Augmentation (CFA) and Uncertainty-guided Prediction Regularization (UPR). CFA integrates a trainable CNN encoder branch with a frozen ViT encoder, enabling the integration of domain-specific knowledge while enhancing local features and high-frequency details. Moreover, UPR ingeniously leverages SAM's IoU score to mitigate uncertainty during the training procedure, thereby improving OOD performance and domain generalization. Extensive experimental results demonstrate the effectiveness and utility of the proposed method in improving SAM's performance in polyp segmentation. Our code is available at https://github.com/HuiqianLi/ASPS.Comment: Accepted by MICCAI202

Ferroptosis: a novel mechanism of cell death in ophthalmic conditions

Ferroptosis, a new type of programmed cell death proposed in recent years, is characterized mainly by reactive oxygen species and iron-mediated lipid peroxidation and differs from programmed cell death, such as apoptosis, necrosis, and autophagy. Ferroptosis is associated with a variety of physiological and pathophysiological processes. Recent studies have shown that ferroptosis can aggravate or reduce the occurrence and development of diseases by targeting metabolic pathways and signaling pathways in tumors, ischemic organ damage, and other degenerative diseases related to lipid peroxidation. Increasing evidence suggests that ferroptosis is closely linked to the onset and progression of various ophthalmic conditions, including corneal injury, glaucoma, age-related macular degeneration, diabetic retinopathy, retinal detachment, and retinoblastoma. Our review of the current research on ferroptosis in ophthalmic diseases reveals significant advancements in our understanding of the pathogenesis, aetiology, and treatment of these conditions

Debatrix: Multi-dimensional Debate Judge with Iterative Chronological Analysis Based on LLM

How can we construct an automated debate judge to evaluate an extensive, vibrant, multi-turn debate? This task is challenging, as judging a debate involves grappling with lengthy texts, intricate argument relationships, and multi-dimensional assessments. At the same time, current research mainly focuses on short dialogues, rarely touching upon the evaluation of an entire debate. In this paper, by leveraging Large Language Models (LLMs), we propose Debatrix, which makes the analysis and assessment of multi-turn debates more aligned with majority preferences. Specifically, Debatrix features a vertical, iterative chronological analysis and a horizontal, multi-dimensional evaluation collaboration. To align with real-world debate scenarios, we introduced the PanelBench benchmark, comparing our system's performance to actual debate outcomes. The findings indicate a notable enhancement over directly using LLMs for debate evaluation. Source code and benchmark data are available online at https://github.com/ljcleo/debatrix

Understanding the relationship between HCV infection and progression of kidney disease

Hepatitis C virus (HCV) can cause a range of kidney diseases. HCV is the primary cause of mixed cryoglobulinaemia, which leads to cryoglobulinaemic vasculitis and cryoglobulinaemic glomerulonephritis (GN). Patients with acute cryoglobulinaemic vasculitis often exhibit acute kidney disease due to HCV infection, which typically progresses to acute kidney injury (AKI). HCV also increases the risk of chronic kidney disease (CKD) and the likelihood of developing end-stage renal disease (ESRD). Currently, direct-acting antiviral agents (DAAs) can be used to treat kidney disease at different stages. This review focuses on key findings regarding HCV and kidney disease, discusses the impact of DAAs, and highlights the need for further research and treatment

The role of N6-methyladenosine (m6A) in kidney diseases

Chemical modifications are a specific and efficient way to regulate the function of biological macromolecules. Among them, RNA molecules exhibit a variety of modifications that play important regulatory roles in various biological processes. More than 170 modifications have been identified in RNA molecules, among which the most common internal modifications include N6-methyladenine (m6A), n1-methyladenosine (m1A), 5-methylcytosine (m5C), and 7-methylguanine nucleotide (m7G). The most widely affected RNA modification is m6A, whose writers, readers, and erasers all have regulatory effects on RNA localization, splicing, translation, and degradation. These functions, in turn, affect RNA functionality and disease development. RNA modifications, especially m6A, play a unique role in renal cell carcinoma disease. In this manuscript, we will focus on the biological roles of m6A in renal diseases such as acute kidney injury, chronic kidney disease, lupus nephritis, diabetic kidney disease, and renal cancer