Optimizing C─C Coupling on Cu/Cu/Ga Interfaces by Enhancing Active Hydrogen Absorption for Excellent CO-to-C Electrosynthesis.

The electrocatalytic reduction of CO (CORR) to high-value chemicals and fuels offers a promising route for a clean carbon cycle. However, it often suffers from low catalytic activity and poor selectivity. Heterostructure construction has been shown to be an effective strategy for producing multi-carbon products, but the synergistic mechanisms between multiple active sites resulting from the reconstruction process remain unclear.

Decreased Subcutaneous Adipose Tissue Correlates with Higher Portal Hypertension And Poor Survival in Patients with Cirrhosis: A Retrospective Binary-center Study.

Introduction: This study aimed to investigate the impact of hepatic venous portal gradient (HVPG) on BC values and the prognostic value of BC value in cirrhotic patients.

Methods: A total of 173 cirrhotic patients with HVPG and Computed Tomography scan were screened retrospectively from a binary-center database. Seven BC values, including skeletal muscle index (SMI), subcutaneous adipose tissue index (SATI), deep SATI (dSATI), superficial SATI (sSATI), visceral adipose tissue index (VATI), and ratio of VATI and SATI (VSR) along with skeletal muscle radiodensity (SMRD), were analyzed.

Mainecoon: Implementing an Open-Source Web Viewer for DICOM Whole Slide Images with AI-Integrated PACS for Digital Pathology.

The rapid advancement of digital pathology comes with significant challenges due to the diverse data formats from various scanning devices creating substantial obstacles to integrating artificial intelligence (AI) into the pathology imaging workflow. To overcome performance challenges posed by large AI-generated annotations, we developed an open-source project named Mainecoon for whole slide images (WSIs) using the Digital Imaging and Communications in Medicine (DICOM) standard. Our solution incorporates an AI model to detect non-alcoholic steatohepatitis (NASH) features in liver biopsies, validated with the DICOM Workgroup 26 Connectathon dataset.

Construction and Multifunctional Photonic Applications of Light Absorption-Enhanced Silicon-Based Schottky Coupled Structures.

To expand the detection capabilities of silicon (Si)-based photodetector and address key scientific challenges such as low light absorption efficiency and short carrier lifetime in Si-based graphene photodetector. This work introduces a novel Si-based Schottky coupled structure by in situ growth of 3D-graphene and molybdenum disulfide quantum dots (MoS QDs) on Si substrates using chemical vapor deposition (CVD) and plasma-enhanced chemical vapor deposition (PECVD) techniques. The findings validate the "dual-enhanced absorption" effect, enhancing the understanding of the mechanisms that improve optoelectronic performance.

Inter-reader agreement of LI-RADS treatment response algorithm among three readers with different seniorities for hepatocellular carcinoma after locoregional therapy.

Background: The accurate evaluation of tumor response after locoregional therapy is crucial for adjusting therapeutic strategy and guiding individualized follow-up.

Purpose: To determine the inter-reader agreement of the LR-TR algorithm for hepatocellular carcinoma treated with locoregional therapy among radiologists with different seniority.

Material And Methods: A total of 275 treated observations on 249 MRI scans from 99 patients were retrospectively collected.

OOD-CV-v2 : An Extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images.

Enhancing the robustness of vision algorithms in real-world scenarios is challenging. One reason is that existing robustness benchmarks are limited, as they either rely on synthetic data or ignore the effects of individual nuisance factors. We introduce OOD-CV-v2, a benchmark dataset that includes out-of-distribution examples of 10 object categories in terms of pose, shape, texture, context and the weather conditions, and enables benchmarking of models for image classification, object detection, and 3D pose estimation.

Screening of identification algorithm for rodent-induced bare patches based on the drone imagery.

Rodent-infested bald spots are crucial indicators of rodent infestation in grasslands. Leveraging Unmanned Aerial Vehicle (UAV) remote sensing technology for discerning detrimental bald spots among plateau pikas has significant implications for assessing associated ecological hazards. Based on UAV-visible light imagery, we classified and recognized the characteristics of plateau pika habitats with five supervised classification algorithms, minimum distance classification (MinD), maximum likelihood classification (ML), support vector machine classification (SVM), Mahalanobis distance classification (MD), and neural network classification (NN) .

Accelerated proton dissociation in an excited state induces superacidic microenvironments around graphene quantum dots.

Investigating proton transport at the interface in an excited state facilitates the mechanistic investigation and utilization of nanomaterials. However, there is a lack of suitable tools for in-situ and interfacial analysis. Here we addresses this gap by in-situ observing the proton transport of graphene quantum dots (GQDs) in an excited state through reduction of magnetic resonance relaxation time.

Nitrogen-Doped 3D-Graphene Advances Near-Infrared Photodetector for Logic Circuits and Image Sensors Overcoming 2D Limitations.

The limitations of two-dimensional (2D) graphene in broadband photodetector are overcome by integrating nitrogen (N) doping into three-dimensional (3D) structures within silicon (Si) via plasma-assisted chemical vapor deposition (PACVD) technology. This contributes to the construction of vertical Schottky heterojunction broad-spectrum photodetectors and applications in logic devices and image sensors. The natural nanoscale resonant cavity structure of 3D-graphene enhances photon capture efficiency, thereby increasing photocarrier generation.

Hybrid ant colony-based inter-cluster routing protocol for FANET.

This study addresses the challenges in large-scale unmanned aerial vehicle (UAV) clusters, specifically the scalability issues and limitations of using reactive routing protocols for inter-cluster routing. These traditional methods place an excessive burden on cluster heads and struggle to adapt to frequently changing topologies, leading to decreased network performance. To solve these problems, we propose an innovative inter-cluster routing protocol (ICRP), which is based on a hybrid ant colony algorithm.

A novel method for quantitative determination of multiple substances using Raman spectroscopy combined with CWT.

The identification of mixed solutions is a challenging and important subject in chemical analysis. In this paper, we propose a novel workflow that enables rapid qualitative and quantitative detection of mixed solutions. We use a methanol-ethanol mixed solution as an example to demonstrate the superiority of this workflow.

A Tape-Wrapping Strategy towards Electrochemical Fabrication of Water-Dispersible Graphene.

Graphene has achieved mass production via various preparative routes and demonstrated its uniqueness in many application fields for its intrinsically high electron mobility and thermal conductivity. However, graphene faces limitations in assembling macroscopic structures because of its hydrophobic property. Therefore, balancing high crystal quality and good aqueous dispersibility is of great importance in practical applications.

Deep learning-based Raman spectroscopy qualitative analysis algorithm: A convolutional neural network and transformer approach.

Raman spectroscopy is a general and non-destructive detection technique that can obtain detailed information of the chemical structure of materials. In the past, when using chemometric algorithms to analyze the Raman spectra of mixtures, the challenges of complex spectral overlap and noise often limited the accurate identification of components. The emergence of deep learning has introduced a novel approach to qualitative analysis of mixed Raman spectra.

Rationale for immune checkpoint inhibitors plus targeted therapy for advanced renal cell carcinoma.

Renal cell carcinoma (RCC) is a frequent urological malignancy characterized by a high rate of metastasis and lethality. The treatment strategy for advanced RCC has moved through multiple iterations over the past three decades. Initially, cytokine treatment was the only systemic treatment option for patients with RCC.

Symmetry-Triggered Tunable Phosphorescence Lifetime of Graphene Quantum Dots in a Solid State.

Studying the phosphorescent mechanisms of carbon nanostructures synthesized by the "bottom-up" approach is key to understanding the structure modulation and the interfacial properties of carbon nanostructures. In this work, the relationships among symmetry of precursors in the "bottom-up" synthesis, structures of products, and phosphorescence lifetimes of graphene quantum dots (GQDs) are studied. The symmetry matching of precursors in the formation of a D graphene-like framework is considered the key factor in controlling the separability of sp domains in GQDs.

The Synergistic Effect on the Mimetic Optical Structure of Feline Eyes toward Household Health Monitoring of Acute and Chronic Diseases.

A breakthrough in the performance of bionic optical structures will only be achieved if we can obtain an in-depth understanding of the synergy mechanisms operating in natural optical structures and find ways to imitate them. In this work, inspired by feline eyes, an optical substrate that takes advantage of a synergistic effect that occurs between resonant and reflective structures was designed. The synergistic effect between the reflective and resonant components leads to a Raman enhancement factor (EF) of 1.

Fast proton transport enables the magnetic relaxation response of graphene quantum dots for monitoring the oxidative environment .

A magnetic relaxation switch (MRS) that targets small molecules such as HO is difficult to realize because of the small size of the targets, which cannot gather enough MRS probes to form aggregates and generate a difference in magnetic relaxation times. Therefore, the development of small molecule-targeted MRS is strongly dependent on changes in the interfacial structure of the probe, which modulates the proton transport behavior near the probe. Herein, functionalized graphene quantum dots (GQDs) consisting of GQDs with disulfide bonds, polyethylene glycol (PEG), and paramagnetic Gd were used as the MRS probe to sense HO.

Glasgow prognostic score and its derived scores predicts contrast-associated acute kidney injury in patients undergoing coronary angiography.

Background: Glasgow prognostic score (GPS) is a reliable scoring system reflecting both nutritional and inflammatory factors. The association of inflammation and nutrition with contrast-associated acute kidney injury (CA-AKI) has been validated. This study set out to determine the impact of GPS and its derived scores on CA-AKI incidence.