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Abstract Background This study aimed to explore the prevalence and related risk factors of sarcopenia in patients on maintenance hemodialysis (MHD). Methods This cohort study enrolled 165 patients on MHD. The patients were divided into sarcopenia and non-sarcopenia groups based on the presence of sarcopenia or not. Sarcopenia was diagnosed according to the consensus of the Asian Sarcopenia Working Group that considers reduced muscle mass and decreased muscle strength (19). The muscle mass was measured using the multi-frequency bioelectrical impedance (Inbody260) and skeletal muscle index (SMI) was used:

IntroductionThis research seeks to investigate how early rehabilitation nursing, guided by Orem’s self-care theory, affects cognitive function, neurological function, and daily living skills in individuals who have suffered a traumatic brain injury (TBI).MethodsA study was conducted with 108 patients with traumatic brain injury who were hospitalized at our facility from January 2021 to March 2023. Based on their admission dates, the participants were separated into a control group (n = 56) and an observation group (n = 52). The control group received standard nursing care, while the observation group received a combination of conventional treatment and nursing interventions based on Orem’s self-care model. The research assessed alterations in the ability to perform daily tasks (Activities of Daily Living, ADL), neurological health (National Institutes of Health Stroke Scale, NIHSS; Glasgow Coma Scale, GCS), and cognitive abilities (Montreal Cognitive Assessment Scale, MoCA; Mini-Mental State Examination, MMSE) in both sets of participants prior to and following 4 and 8 weeks of nursing assistance.ResultsFollowing the intervention, the group being observed showed notably increased ADL scores at 4 weeks (p

Analysing the relationship between economic growth and carbon emissions may help China to determine how to reduce carbon emissions. This study examined 221 Chinese prefecture-level cities using data from 2003 to 2018 to investigate the possible inverted U-shaped relationship between carbon emissions and economic growth, based on per capita nighttime light brightness. This revealed a significant inverted U-shaped relationship between per capita nighttime and carbon emissions with a per capita GDP of 139.8 thousand Yuan corresponding to the turning point. For China to achieve its carbon emissions peak before 2030, the per capita GDP growth rate would need to be at least 6.6 %. Therefore, for help prefecture-level cities to achieve peak carbon, they must strive towards high-quality economic growth and accelerate transformation of economic growth modes to improve low-carbon pilot policies, and such projects should be implemented in more cities. Efforts to achieve peak should be accelerated first in eastern cities and later in western cities.

Abstract Optimizing the spatial layout of the national territory is crucial for realizing the transformation and development of resource-oriented cities in the context of high-quality development in the new period. This paper takes Tongling City as a case study, based on the analysis of the historical development foundation, then uses the SD-FLUS comprehensive model to carry out a systematic analysis of the transformation in five dimensions of economy, society, population, science and technology, resources and environment, and discusses the optimization of spatial pattern under the contextual simulation. The conclusions are as follows: ① The hierarchical framework of “system-indicator-element” is not only internally interconnected, but also inextricably linked with the relationship between the various categories of the land use system. ② Decrease of cropland, forest, water, grassland, and barren decreases from the economic development, social progress, and comprehensive development, and there is a small increase in the area under the scenario of resource and environmental protection, and the direction of the change of the impervious is in the opposite direction. ③ Cultivated land is retained in situ and concentrated to a small extent, forested land is reduced to a small extent while the status quo is maintained, and the Yangtze River water system will be retained and protected to a large extent, but part of the waters of Zongyang County will give way to the expansion of construction land under the development objectives of the new county. Building land will be expanded and extended to the northeast in the original site area, while the southwest corner of the original county center will be expanded to some extent in Zongyang County to promote the county’s economic development.

Abstract Radar‐based human activity recognition is considered as a competitive solution for the elderly care health monitoring problem, compared to alternative techniques such as cameras and wearable devices. However, raw radar signals are often contaminated with noise, clutter, and other artifacts that significantly impact recognition performance, which highlights the importance of prepossessing techniques that enhance radar data quality and improve classification model accuracy. In this study, two different human activity classification models incorporated with pre‐processing techniques have been proposed. The authors introduce wavelet denoising methods into a cyclostationarity‐based classification model, resulting in a substantial improvement in classification accuracy. To address the limitations of conventional pre‐processing techniques, a deep neural network model called Double Phase Cascaded Denoising and Classification Network (DPDCNet) is proposed, which performs end‐to‐end signal‐level classification and achieves state‐of‐the‐art accuracy. The proposed models significantly reduce false detections and would enable robust activity monitoring for older individuals with radar signals, thereby bringing the system closer to a practical implementation for deployment.

BackgroundThe fragmentation of the medical insurance system is a major challenge to achieving health equity. In response to this problem, the Chinese government is pushing to establish the unified Urban and Rural Resident Basic Medical Insurance (URRBMI) system by integrating the New Rural Cooperative Medical Scheme and the Urban Resident Basic Medical Insurance. By the end of 2020, URRBMI had been implemented almost entirely across China. Has URRBMI integration promoted health equity for urban and rural residents? ObjectiveThis study aims to examine the effect of URRBMI integration on the health level of residents and whether the integration can contribute to reducing health disparities and promoting health equity. MethodsWe used the staggered difference-in-differences method based on the China Family Panel Studies survey from 2014 to 2018. Our study had a nationally representative sample of 27,408 individuals from 98 cities. We chose self-rated health as the measurement of health status. In order to more accurately discern whether the sample was covered by URRBMI, we obtained the exact integration time of URRBMI according to the official documents issued by local governments. Finally, we grouped the sample by urban and rural areas, regions, and household income to examine the impact of the integration on health equity. ResultsWe found that overall, the URRBMI integration has improved the health level of Chinese residents (B=0.066, 95% CI 0.014-0.123; P=.01). In terms of health equity, the results showed that first, the integration has improved the health level of rural residents (B=0.070, 95% CI 0.012-0.128; P=.02), residents in western China (B=0.159, 95% CI 0.064-0.255; P

Accurately predicting wind speeds is of great significance in various engineering applications, such as the operation of high-speed trains. Machine learning models are effective in this field. However, existing studies generally provide deterministic predictions and utilize decomposition techniques in advance to enhance predictive performance, which may encounter data leakage and fail to capture the stochastic nature of wind data. This work proposes an advanced framework for the prediction and early warning of wind speeds by combining the optimized gated recurrent unit (GRU) and adaptive kernel density estimator (AKDE). Firstly, 12 samples (26,280 points each) were collected from an extensive open database. Three representative metaheuristic algorithms were then employed to optimize the parameters of diverse models, including extreme learning machines, a transformer model, and recurrent networks. The results yielded an optimal selection using the GRU and the crested porcupine optimizer. Afterwards, by using the AKDE, the joint probability density and cumulative distribution function of wind predictions and related predicting errors could be obtained. It was then applicable to calculate the conditional probability that actual wind speed exceeds the critical value, thereby providing probabilistic-based predictions in a multilevel manner. A comparison of the predictive performance of various methods and accuracy of subsequent decisions validated the proposed framework.

Background: Nintedanib and pirfenidone are preferred pharmacological therapies for patients with idiopathic pulmonary fibrosis (IPF). However, evidence favoring antifibrotic therapy in patients with non-IPF fibrosing interstitial lung diseases (ILD) is limited. Objective: To investigate the effects of antifibrotic therapy on disease progression, all-cause mortality, and acute exacerbation (AE) risk in patients with non-IPF fibrosing ILDs. Design: Meta-analysis. Data sources and methods: Electronic databases were searched for articles published before 28 February 2023. Studies that evaluated the efficacy of antifibrotic agents in patients with fibrosing ILDs were selected. The primary outcome was the disease progression risk, and the secondary outcomes included all-cause mortality and AE risk. The GRADE criteria were used for the certainty of evidence assessment. Results: Nine studies with 1990 participants were included. Antifibrotic therapy reduced the rate of patients with disease progression (five trials with 1741 subjects; relative risk (RR), 0.56; 95% CI, 0.42–0.75; p

The advanced anaerobic digestion process enhances sludge resource utilization. However, thermal hydrolysis pretreatment of anaerobically digested sludge reduces dewatering efficiency due to excessive organic matter decomposition. This necessitates significant time and effort for sludge conditioning in wastewater treatment plants. Using conditioning agents can achieve high dewatering efficiency. This study investigates how the order of adding coagulants and flocculants impacts the dewatering performance of digested sludge. The results indicate that, compared to the flocculation–coagulation process with the same dosage, the coagulation–flocculation process leads to a 15–20% increase in the average particle size of digested sludge. The content of polysaccharides and proteins in S-EPS decreases by 28.8–30.8% and 10.1–11.3%, respectively. The filter cake solids content increases by 8.5%, and there is an increase in surface water channels within the flocs. This is because initially adding coagulants efficiently adsorbs small particles, forming larger aggregates that settle effectively. This promotes the breakdown of extracellular polymeric substances, releasing more bound water. Adding flocculants later bridges the aggregates, further enhancing settling and filtration performance, thereby improving sludge dewatering efficiency. These research findings contribute to a better understanding of the mechanisms of coagulant and flocculant co-conditioning for digested sludge and provide recommendations for optimizing sludge conditioning steps.

The density fields constructed by traditional mass assignment methods are susceptible to irritating discreteness, which hinders morphological measurements of cosmic large-scale structure (LSS) through Minkowski functionals (MFs). To alleviate this issue, fixed-kernel smoothing methods are commonly used in the literature, at the expense of losing substantial structural information. In this work, we propose to measure MFs with the Delaunay tessellation field estimation (DTFE) technique, with the goal of maximizing the extraction of morphological information from sparse tracers. We perform our analyses starting from matter fields and progressively extending to halo fields. At the matter-field level, we elucidate how discreteness affects morphological measurements of LSS. Then, by comparing with the traditional Gaussian smoothing scheme, we preliminarily showcase the advantages of DTFE for enhancing measurements of MFs from sparse tracers. At the halo-field level, we first numerically investigate various systematic effects on MFs of DTFE fields, which are induced by finite voxel sizes, halo number densities, halo weightings, and redshift space distortions (RSDs), respectively. Then, we explore the statistical power of MFs measured with DTFE for extracting the cosmological information encoded in RSDs. We find that MFs measured with DTFE exhibit improvements by ∼2 orders of magnitude in discriminative power for RSD effects and by a factor of ∼3–5 in constraining power on the structure growth rate over the MFs measured with Gaussian smoothing. These findings demonstrate the remarkable enhancements in statistical power of MFs achieved by DTFE, showing enormous application potentials for our method in extracting various key cosmological information from galaxy surveys.

Underground cavities have complex spatial structures and geological settings, their arrangement is dense and crisscrossed. The construction system involves multiple work surfaces, levels, and processes. The close integration of construction simulation with actual production conditions is crucial for enhancing the guidance that simulation results provide for practical engineering. Therefore, from the perspective of optimizing construction organization and management, this article comprehensively considers various factors in the construction process, innovatively introduces the principle of production line balance and the concept of rule cycle, and combines technology and management, an underground cavities construction simulation system (UCCSS) is developed. In UCCSS, a hierarchical model is built and calculation are performed on models with different construction methods by modifying the parameters as per the actual engineering characteristics. The simulation results are comprehensively analysed to determine the optimal construction programme. An application case is proposed based on the construction organisation design of the long and parallel diversion tunnels at the CB Hydropower Station. The results show that the system has good practicality and credibility and can provide guidance for the construction organisation design of underground cavities with various features. [ABSTRACT FROM AUTHOR]

Self-assembled DNA nanostructures hold great promise in biosensing, drug delivery and nanomedicine. Nevertheless, challenges like instability and inefficiency in cellular uptake of DNA nanostructures under physiological conditions limit their practical use. To tackle these obstacles, this study proposes a novel approach that integrates the cationic polymer polyethyleneimine (PEI) with DNA self-assembly. The hypothesis is that the positively charged linear PEI can facilitate the self-assembly of DNA nanostructures, safeguard them against harsh conditions and impart them with the cellular penetration characteristic of PEI. As a demonstration, a DNA nanotube (PNT) was successfully synthesized through PEI mediation, and it exhibited significantly enhanced stability and cellular uptake efficiency compared to conventional Mg2+-assembled DNA nanotubes. The internalization mechanism was further found to be both clathrin-mediated and caveolin-mediated endocytosis, influenced by both PEI and DNA. To showcase the applicability of this hybrid nanostructure for biomedical settings, the KRAS siRNA-loaded PNT was efficiently delivered into lung adenocarcinoma cells, leading to excellent anticancer effects in vitro. These findings suggest that the PEI-mediated DNA assembly could become a valuable tool for future biomedical applications. [ABSTRACT FROM AUTHOR]

Decarbonylative and dehydrogenative cascade annulation of aldehydes with N‐(o‐cyanobiaryl)acrylamides was developed for the synthesis of a broad spectrum of alkyl‐ and carbonyl‐substituted pyrido[4,3,2‐gh]phenanthridines. Secondary and tertiary aldehydes can undergo the decarbonylative cascade under DTBP/malonic acid conditions, while aryl, primary, and secondary aldehydes can undergo dehydrogenative reaction under TBHP system. Such transformations were triggered by alkyl and acyl radicals, and the annulations were accomplished through intramolecular additions of carbon‐centered radical to nitrile group and iminyl radical to aromatic ring. [ABSTRACT FROM AUTHOR]

Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image recognition in the medical field, which requires large-scale and high-quality training datasets consisting of raw images and annotated images. However, suitable experimental datasets for cervical spine X-ray are scarce. We fill the gap by providing an open-access Cervical Spine X-ray Atlas (CSXA), which includes 4963 raw PNG images and 4963 annotated images with JSON format (JavaScript Object Notation). Every image in the CSXA is enriched with gender, age, pixel equivalent, asymptomatic and symptomatic classifications, cervical curvature categorization and 118 quantitative parameters. Subsequently, an efficient algorithm has developed to transform 23 keypoints in images into 77 quantitative parameters for cervical spine disease diagnosis and treatment. The algorithm's development is intended to assist future researchers in repurposing annotated images for the advancement of machine learning techniques across various image recognition tasks. The CSXA and algorithm are open-access with the intention of aiding the research communities in experiment replication and advancing the field of medical imaging in cervical spine. [ABSTRACT FROM AUTHOR]

This article discusses the diagnosis and treatment of non-pigmented basal cell carcinoma (BCC), the most common type of skin malignancy. Non-pigmented BCC can be challenging to diagnose due to its lack of pigment. The article describes a case study of a 59-year-old female with non-pigmented BCC on her nose. The diagnosis was made using dermoscopy, reflectance confocal microscopy (RCM), and high-frequency ultrasound (HFUS). Mohs micrographic surgery was performed to remove the tumor, guided by HFUS to accurately delineate the surgical boundary. The article concludes that noninvasive imaging techniques, such as dermoscopy, RCM, and HFUS, can aid in the diagnosis and treatment of non-pigmented BCC. [Extracted from the article]