TTGA U-Net: Two-stage two-stream graph attention U-Net for hepatic vessel connectivity enhancement.

Accurate segmentation of hepatic vessels is pivotal for guiding preoperative planning in ablation surgery utilizing CT images. While non-contrast CT images often lack observable vessels, we focus on segmenting hepatic vessels within preoperative MR images. However, the vascular structures depicted in MR images are susceptible to noise, leading to challenges in connectivity.

Improving Cycle Life of Ni-Rich Li-Ion Battery Cathodes by Using Compartmentalized Anode and Cathode Electrolytes.

As new, ever more energy-dense battery materials are being developed, it is becoming increasingly challenging for electrolytes to cater for both requirements set by the anode and cathode. Ethylene carbonate plays a key role in forming a stable solid-electrolyte-interphase on the graphite anodes, but in combination with nickel-rich cathodes, such as LiNiMnCoO (NMC811), it leads to excessive cathode oxygen loss at high voltage. In this work, the study proposes a cell design, where different electrolytes are compartmentalized in the anode and the cathode.

Joint reconstruction algorithm: combining synchrotron radiation with conventional X-ray computed tomography for improved imaging.

Synchrotron radiation (SR) is an excellent light source for micro-CT (micro-computed tomography) applications due to its monochromaticity and high brightness, which are crucial for achieving high-resolution imaging. However, when scanning larger objects, the limited field of view (FOV) of SR will lead to data truncation, limiting its utilization efficiency. To address this limitation, this paper proposed a method to integrate conventional X-ray CT data to supplement the truncated SR data for joint reconstruction to improve imaging.

The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis.

The review summarizes the applications of CT and AI algorithms for prognostic models in IPF and procedures of model construction. It reveals the current limitations and prospects of AI-aid models, and helps clinicians to recognize the AI algorithms and apply them to more clinical work.

A bisalicylhydrazone based fluorescent probe for detecting Al with high sensitivity and selectivity and imaging in living cells.

A bisalicylhydrazone based fluorescence probe, bisalicyladehyde benzoylhydrazone (BS-BH), has been designed to detect Al. It exhibited high sensitivity and selectivity towards Al in methanol-water media in physiological condition. Large stokes shifts (∼122 nm) and over ∼1000-fold enhanced fluorescence intensity were observed, which was ascribed to the formation of the two relatively independent rigid extended π conjugated systems bridged by biphenyl group when binding with Al.

Reduced vowel space in video conferences via Zoom: Evidence from read speecha).

This exploratory study compared vowel space area (VSA) in face-to-face situations and video conference situations using the software Zoom. Twenty native German participants read word lists recorded before and after spontaneous conversation. The overall VSA in Zoom was reduced significantly by 11.

Highly restricted near-surface permafrost extent during the mid-Pliocene warm period.

Accurate understanding of permafrost dynamics is critical for evaluating and mitigating impacts that may arise as permafrost degrades in the future; however, existing projections have large uncertainties. Studies of how permafrost responded historically during Earth's past warm periods are helpful in exploring potential future permafrost behavior and to evaluate the uncertainty of future permafrost change projections. Here, we combine a surface frost index model with outputs from the second phase of the Pliocene Model Intercomparison Project to simulate the near-surface (~3 to 4 m depth) permafrost state in the Northern Hemisphere during the mid-Pliocene warm period (mPWP, ~3.

Thin Solid Polymer Electrolyte with High-Strength and Thermal-Resistant via Incorporating Nanofibrous Polyimide Framework for Stable Lithium Batteries.

Polyethylene oxide (PEO) based polymer electrolytes show promise in expanding the practical applications of lithium (Li) batteries. However, their applications in Li batteries are usually restricted owing to the lack of mechanical strength, poor oxidative stability, and relatively large thickness. Herein, a nanofibrous polyimide (PI) framework enhanced plasticized-PEO solid electrolyte is prepared to realize good mechanical and electrochemical performances.

Two-stage generative adversarial networks for metal artifact reduction and visualization in ablation therapy of liver tumors.

Purpose: The strong metal artifacts produced by the electrode needle cause poor image quality, thus preventing physicians from observing the surgical situation during the puncture process. To address this issue, we propose a metal artifact reduction and visualization framework for CT-guided ablation therapy of liver tumors.

Methods: Our framework contains a metal artifact reduction model and an ablation therapy visualization model.

Study on the Thermogravimetric Kinetics of Dehydrated Sewage Sludge Regulated by Cationic Polyacrylamide and Sawdust.

With the continuous increase in sewage-sludge production worldwide, the pyrolytic disposal of sludge has received great attention. To build knowledge on the kinetics of pyrolysis, first, sludge was regulated using appropriate amounts of cationic polyacrylamide (CPAM) and sawdust to study their enhancing effect on dehydration. Due to the effects of the charge neutralization and skeleton hydrophobicity, a certain dose of CPAM and sawdust reduced the sludge's moisture content from 80.

Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

Novel multimode thermal therapy by freezing before radio-frequency heating has achieved a desirable therapeutic effect in liver cancer. Compared with surgical resection, ablation treatment has a relatively high risk of tumor recurrence. To monitor tumor progression after ablation, we developed a novel survival analysis framework for survival prediction and efficacy assessment.

Automatic vertebral fracture and three-column injury diagnosis with fracture visualization by a multi-scale attention-guided network.

Deep learning methods have the potential to improve the efficiency of diagnosis for vertebral fractures with computed tomography (CT) images. Most existing intelligent vertebral fracture diagnosis methods only provide dichotomized results at a patient level. However, a fine-grained and more nuanced outcome is clinically needed.

Separation and Structural Characterization of a Novel Exopolysaccharide from .

The present study aims to analyze the structural characterization and antioxidant activity of a novel exopolysaccharide from (EPS2-1). For this purpose, EPS2-1 was purified through DEAE-52, Sephadex G-100, and Sephadex G-75 chromatography. The structural characterization of EPS2-1 was analyzed using high-performance gel permeation chromatography (HPGPC), Fourier transform infrared spectroscopy (FT-IR), methylation analysis, nuclear magnetic resonance (NMR) spectra, transmission electron microscope (TEM), and atomic force microscope (AFM).

Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma.

Objectives: To predict CTLA4 expression levels and prognosis of clear cell renal cell carcinoma (ccRCC) by constructing a computed tomography-based radiomics model and establishing a nomogram using clinicopathologic factors.

Methods: The clinicopathologic parameters and genomic data were extracted from 493 ccRCC cases of the Cancer Genome Atlas (TCGA)-KIRC database. Univariate and multivariate Cox regression and Kaplan-Meier analysis were performed for prognosis analysis.

Aggregation caused quenching to aggregation induced emission transformation: a precise tuning based on BN-doped polycyclic aromatic hydrocarbons toward subcellular organelle specific imaging.

Polycyclic aromatic hydrocarbons (PAHs) with boron-nitrogen (BN) moieties have attracted tremendous interest due to their intriguing electronic and optoelectronic properties. However, most of the BN-fused π-systems reported to date are difficult to modify and exhibit traditional aggregation-caused quenching (ACQ) characteristics. This phenomenon greatly limits their scope of application.

A CT reconstruction method based on constrained data fidelity range estimation.

For the CT iterative reconstruction, choosing the parameters of different regularization terms has been a difficult problem. Transforming the reconstruction problem into constrained optimization can solve this problem, but determining the constraint range and accurately solving it remains a challenge. This paper proposes a CT reconstruction method based on constrained data fidelity term, which estimates the distribution of the constraint function by Taylor expansion to determine the constraint range.

Lung cancer subtype classification using histopathological images based on weakly supervised multi-instance learning.

Subtype classification plays a guiding role in the clinical diagnosis and treatment of non-small-cell lung cancer (NSCLC). However, due to the gigapixel of whole slide images (WSIs) and the absence of definitive morphological features, most automatic subtype classification methods for NSCLC require manually delineating the regions of interest (ROIs) on WSIs.In this paper, a weakly supervised framework is proposed for accurate subtype classification while freeing pathologists from pixel-level annotation.

A Novel Tumor Progression Prediction Method for Multimode Ablation Treatment.

Objective: The multimode ablation of liver cancer, which uses radio-frequency heating after a pre-freezing process to treat the tumor, has shown significantly improved therapeutic effects and enhanced anti-tumor immune response. Unlike open surgery, the ablated lesions remain in the body after treatment, so it is critical to assess the immediate outcome and to monitor disease status over time. Here we propose a novel tumor progression prediction method for simultaneous postoperative evaluation and prognosis analysis.

Local changes in snow depth dominate the evolving pattern of elevation-dependent warming on the Tibetan Plateau.

Elevation-dependent warming (EDW), whereby warming rates are stratified by elevation, may increase the threat to the life-supporting solid water reservoir on the Tibetan Plateau. Previous studies have debated whether EDW exists and how it is driven. Using temperatures at 133 weather stations on the Tibetan Plateau during 17 different periods generated using a 30-year sliding window over 1973-2018, this study finds that the existence of EDW varies as the period moves forward, and critically it has become more severe over time.

A Weak Supervision-based Framework for Automatic Lung Cancer Classification on Whole Slide Image.

Classification of normal lung tissue, lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by pathological images is significant for clinical diagnosis and treatment. Due to the large scale of pathological images and the absence of definitive morphological features between LUAD and LUSC, it is time-consuming, laborious and challenging for pathologists to analyze the microscopic histopathology slides by visual observation. In this paper, a pixel-level annotation-free framework was proposed to classify normal tissue, LUAD and LUSC slides.