A CT-Based Lung Radiomics Nomogram for Classifying the Severity of Chronic Obstructive Pulmonary Disease.

Background: Chronic obstructive pulmonary disease (COPD) is a major global health concern, and while traditional pulmonary function tests are effective, recent radiomics advancements offer enhanced evaluation by providing detailed insights into the heterogeneous lung changes.

Purpose: To develop and validate a radiomics nomogram based on clinical and whole-lung computed tomography (CT) radiomics features to stratify COPD severity.

Patients And Methods: One thousand ninety-nine patients with COPD (including 308, 132, and 659 in the training, internal and external validation sets, respectively), confirmed by pulmonary function test, were enrolled from two institutions.

Multifunctional pressure and humidity sensor modulated by electrostatic interactions and hydrogen bonds for wearable health monitoring.

Breathing and urination, are vital physiological activities of the human body, continuous real-time monitoring of these physiological behaviors could offer timely feedback on an individual's health status. However, current monitoring techniques predominantly rely on cumbersome and intricate medical apparatuses, posing challenges in adapting to the diverse requirements of multi-scenario detection. Consequently, there is a growing interest in developing wearable devices capable of monitoring breathing and urination.

Optimization of municipal solid waste incineration for low-NO emissions through numerical simulation.

With urbanization, municipal solid waste (MSW) generation is increasing. Traditional landfill methods face land shortages and environmental pollution. Waste incineration, which reduces waste and recovers resources, has become a key management method.

Bioinspired High-Linearity, Wide-Sensing-Range Flexible Stretchable Bioelectronics Based on MWCNTs/GR/NdFeB/PDMS Nanocomposites for Human-Computer Interaction and Biomechanics Detection.

In recent years, flexible and stretchable strain sensors have emerged as a prominent area of research, primarily due to their remarkable stretchability and extremely low strain detection threshold. Nevertheless, the advancement of sensors is currently constrained by issues such as complexity, high costs, and limited durability. To tackle the aforementioned issues, this study introduces a lepidophyte-inspired flexible, stretchable strain sensor (LIFSSS).

Salvage radiotherapy for locally recurrent cervical and endometrial carcinoma: clinical outcomes and toxicities.

Background: The management of locally recurrent gynecological carcinoma remains a challenge due to the limited availability of data. This study aims to share our institutional experience in using definitive radiotherapy (RT) for the treatment of locally recurrent cervical and endometrial carcinoma.

Methods: The study retrospectively reviewed 20 patients in our hospital completing salvage 3D image-based HDR brachytherapy, with or without EBRT, for locally recurrent cervical and endometrial carcinoma after surgery.

Circ_0081723 enhances cervical cancer progression and modulates CREBRF via sponging miR-545-3p.

Circular RNAs (circRNAs) have been confirmed to be an important modulator and therapeutic target of cervical cancer (CC). The aim of this study is to explore the role and mechanism of circ_0081723 in CC progression. Circ_0081723, microRNA-545-3p (miR-545-3p), and CREB3 regulatory factor (CREBRF) levels were detected using quantitative real-time PCR (qRT-PCR) assay.

Experience with aortic arch inclusion technique using artificial blood vessel for type A aortic dissection: an application study.

Background: This study aimed to elucidate the methodology and assess the efficacy of the aortic arch inclusion technique using an artificial blood vessel in managing acute type A aortic dissection (ATAAD).

Methods: We conducted a retrospective review of 18 patients (11 males and 7 females, average age: 56.2 ± 8.

Study on the benefit analysis based on whole life cycle carbon emission calculation after the construction of photovoltaic systems in macau's construction waste landfills.

This study seeks to assess both environmental and economic effects associated with installing photovoltaic systems within construction waste landfills in Macau by employing an effective carbon emissions calculation methodology and benefit analysis method. Beginning by outlining characteristics and challenges associated with construction waste landfills, as well as photovoltaic systems used for this application in this paper. Here, we present a detailed outline of our methodology design, outlining its principles of life cycle analysis, data collection processes and the creation of carbon emissions calculation models.

CT whole lung radiomic nomogram: a potential biomarker for lung function evaluation and identification of COPD.

Background: Computed tomography (CT) plays a great role in characterizing and quantifying changes in lung structure and function of chronic obstructive pulmonary disease (COPD). This study aimed to explore the performance of CT-based whole lung radiomic in discriminating COPD patients and non-COPD patients.

Methods: This retrospective study was performed on 2785 patients who underwent pulmonary function examination in 5 hospitals and were divided into non-COPD group and COPD group.

Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules.

Objective: To develop and validate the model for predicting benign and malignant ground-glass nodules (GGNs) based on the whole-lung baseline CT features deriving from deep learning and radiomics.

Methods: This retrospective study included 385 GGNs from 3 hospitals, confirmed by pathology. We used 239 GGNs from Hospital 1 as the training and internal validation set; 115 and 31 GGNs from Hospital 2 and Hospital 3 as the external test sets 1 and 2, respectively.

Bio-Inspired FeMoS Microspheres as Bifunctional Electrocatalysts for Boosting Hydrogen Oxidation/Evolution Reactions in Alkaline Solution.

Developing robust and effectual nonprecious electrocatalysts for the bifunctional hydrogen oxidation and evolution reactions (HOR and HER) in alkaline electrolyte is of critical significance for the realization of future hydrogen economy but challenging. Herein, this work demonstrates a new routine for the preparation of bio-inspired FeMoS microspheres the one-step sulfuration of Keplerate-type polyoxometalate {MoFe}. The bio-inspired FeMoS microspheres feature potential-abundant structural defects and atomically precise iron doping and act as an effective bifunctional electrocatalyst for hydrogen oxidation/reduction reactions.

Three-Dimensional Silver-Containing Polyoxotungstate Frameworks for Photocatalytic Aerobic Oxidation of Benzyl Alcohol.

Photocatalytic organic transformation derived by functionalized polyoxometalate (POM)-based metal-organic frameworks provides a feasible route for fine chemical synthesis. Herein, three kinds of photoactive three-dimensional silver-containing polyoxotungstate frameworks are synthesized with the formulas [AgL(OH)][Na(HO)][PWO]·HO (), [AgL][SiWO] (), and [Ag(HO)][AgL][BWO]·9HO () (L = 1,4-di(4H-1,2,4-triazol-4-yl)benzene). In compounds -, the cationic Ag-triazole clusters with diverse nuclei serve as nodes to assemble with rigid bridging ligands (L) and polyoxoanions to extend into stable three-dimensional frameworks, in which Keggin-type anions act as guests or pendants.

Applications of machine learning in tumor-associated macrophages.

Evaluation of tumor-host interaction and intratumoral heterogeneity in the tumor microenvironment (TME) is gaining increasing attention in modern cancer therapies because it can reveal unique information about the tumor status. As tumor-associated macrophages (TAMs) are the major immune cells infiltrating in TME, a better understanding of TAMs could help us further elucidate the cellular and molecular mechanisms responsible for cancer development. However, the high-dimensional and heterogeneous data in biology limit the extensive integrative analysis of cancer research.

A personalized DVH prediction model for HDR brachytherapy in cervical cancer treatment.

Purpose: Although the knowledge-based dose-volume histogram (DVH) prediction has been largely researched and applied in External Beam Radiation Therapy, it is still less investigated in the domain of brachytherapy. The purpose of this study is to develop a reliable DVH prediction method for high-dose-rate brachytherapy plans.

Method: A DVH prediction workflow combining kernel density estimation (KDE), k-nearest neighbor (kNN), and principal component analysis (PCA) was proposed.

A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy.

Purpose: Fast and accurate outlining of the organs at risk (OARs) and high-risk clinical tumor volume (HRCTV) is especially important in high-dose-rate brachytherapy due to the highly time-intensive online treatment planning process and the high dose gradient around the HRCTV. This study aims to apply a self-configured ensemble method for fast and reproducible auto-segmentation of OARs and HRCTVs in gynecological cancer.

Materials And Methods: We applied nnU-Net (no new U-Net), an automatically adapted deep convolutional neural network based on U-Net, to segment the bladder, rectum and HRCTV on CT images in gynecological cancer.

Revisiting the target-masker linguistic similarity hypothesis.

The linguistic similarity hypothesis states that it is more difficult to segregate target and masker speech when they are linguistically similar. For example, recognition of English target speech should be more impaired by the presence of Dutch masking speech than Mandarin masking speech because Dutch and English are more linguistically similar than Mandarin and English. Across four experiments, English target speech was consistently recognized more poorly when presented in English masking speech than in silence, speech-shaped noise, or an unintelligible masker (i.

Experimental study of the dispersion of cough-generated droplets from a person going up- or downstairs.

The dispersion of cough-generated droplets from a person going up- or downstairs was investigated through a laboratory experiment in a water tunnel. This experiment was carried out with a manikin mounted at inclination angles facing the incoming flow to mimic a person going up or down. Detailed velocity measurements and flow visualization were conducted in the water tunnel experiments.

LexFindR: A fast, simple, and extensible R package for finding similar words in a lexicon.

Language scientists often need to generate lists of related words, such as potential competitors. They may do this for purposes of experimental control (e.g.

Effects of slope and speed of escalator on the dispersion of cough-generated droplets from a passenger.

During the pandemic of COVID-19, the public is encouraged to take stairs or escalators instead of elevators. However, the dispersion of respiratory droplets in these places, featured by slopes and human motion, is not well understood yet. It is consequently unclear whether the commonly recommended social-distancing guidelines are still appropriate in these scenarios.

The motion of respiratory droplets produced by coughing.

Coronavirus disease 2019 has become a global pandemic infectious respiratory disease with high mortality and infectiousness. This paper investigates respiratory droplet transmission, which is critical to understanding, modeling, and controlling epidemics. In the present work, we implemented flow visualization, particle image velocimetry, and particle shadow tracking velocimetry to measure the velocity of the airflow and droplets involved in coughing and then constructed a physical model considering the evaporation effect to predict the motion of droplets under different weather conditions.

Effects of space sizes on the dispersion of cough-generated droplets from a walking person.

The dispersion of viral droplets plays a key role in the transmission of COVID-19. In this work, we analyze the dispersion of cough-generated droplets in the wake of a walking person for different space sizes. The air flow is simulated by solving the Reynolds-averaged Navier-Stokes equations, and the droplets are modeled as passive Lagrangian particles.

The importance of CT quantitative evaluation of emphysema in lung cancer screening cohort with negative findings by visual evaluation.

Introduction: One-stop quantitative evaluation of emphysema and lung nodule in lung cancer screening is very important for patient.

Objective: To evaluate the quantitative emphysema in the large-sample low-dose CT lung cancer screening cohort with negative CT findings by subjective visual assessment.

Methods: One thousand, two hundred and thirty-one participants with negative visual evaluation were included in this retrospective study.