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Purpose: Sarcopenia is considered to be an important predictor of adverse outcomes following spinal surgery, but the specific relationship between the two is not clear. The purpose of this meta-analysis is to systematically review all relevant studies to evaluate the impact of sarcopenia on spinal surgery outcomes. Methods: We systematically searched PubMed, Embase and the Cochrane Library for relevant articles published on or before January 9, 2023. The pooled odds ratio (OR) with 95% confidence intervals (CIs) was calculated in a random effects meta-analysis. The main outcome was the risk of adverse outcomes after spinal surgery, including adverse events and mortality. This systematic review and meta-analysis was conducted following the PRISMA guidelines to evaluate the impact of sarcopenia on spinal surgery outcomes. In addition, we also conducted a subgroup analysis and leave-one-out sensitivity analyses to explore the main sources of heterogeneity and the stability of the results. Results: Twenty-four cohort studies, with a total of 243,453 participants, met the inclusion criteria. The meta-analysis showed that sarcopenia was significantly associated with adverse events (OR 1.63, 95% CI 1.17–2.27, P < 0.001) but was no significantly associated with mortality (OR 1.17, 95% CI 0.93–1.46, P = 0.180), infection (OR 2.24, 95% CI 0.95–5.26, P < 0.001), 30-day reoperation (OR 1.47, 95% CI 0.92–2.36, P = 0.413), deep vein thrombosis (OR 1.78, 95% CI 0.69–4.61, P = 0.234), postoperative home discharge (OR 0.60, 95% CI 0.26–1.37, P = 0.002) and blood transfusion (OR 3.28, 95% CI 0.74–14.64, P = 0.015). Conclusion: The current meta-analysis showed that patients with sarcopenia have an increased risk of adverse events and mortality after spinal surgery. However, these results must be carefully interpreted because the number of studies included is small and the studies are significantly different. These findings may help to increase the clinicians' awareness of the risks concerning patients with sarcopenia to improve their prognosis. [ABSTRACT FROM AUTHOR]

To tackle the issue of the traditional intelligent diagnostic algorithm's insufficient utilization of correlation characteristics within the time series of fault signals and to meet the challenges of accuracy and computational complexity in rotating machinery fault diagnosis, a novel approach based on a recurrence binary plot (RBP) and a lightweight, deep, separable, dilated convolutional neural network (DSD-CNN) is proposed. Firstly, a recursive encoding method is used to convert the fault vibration signals of rotating machinery into two-dimensional texture images, extracting feature information from the internal structure of the fault signals as the input for the model. Subsequently, leveraging the excellent feature extraction capabilities of a lightweight convolutional neural network embedded with attention modules, the fault diagnosis of rotating machinery is carried out. The experimental results using different datasets demonstrate that the proposed model achieves excellent diagnostic accuracy and computational efficiency. Additionally, compared with other representative fault diagnosis methods, this model shows better anti-noise performance under different noise test data, and it provides a reliable and efficient reference solution for rotating machinery fault-classification tasks. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the adhesion of municipal solid waste incinerator bottom ash (MSWIBA) and limestone to asphalt using the principles of surface energy theory. MSWIBA asphalt mixes are known for their satisfactory water stability, with adhesion being a crucial factor, as demonstrated in previous freeze-thaw splitting tests. Contact angles of ground MSWIBA and limestone were measured using a capillary rise test, eliminating the influence of material surface structure. Subsequently, adhesion work and spalling work were calculated to correlate with water-induced damage. The results showed that the sequence of adhesion work was fine MSWIBA > limestone > coarse MSWIBA, while the sequence of spalling work was coarse MSWIBA > limestone > fine MSWIBA. The adhesion of MSWIBA asphalt mixes was evaluated using the water boiling test image method to validate the findings of surface energy theory. In both asphalt tests, the spalling rate followed this sequence: coarse MSWIBA > limestone > fine MSWIBA. The Adhesion index ER ranked as follows: ER Fine MSWIBA > ER limestone > ER coarse MSWIBA. These results suggest that the water stability of MSWIBA asphalt mixes is influenced by the surface energy of the components. Consequently, indices derived from surface energy theory can be applied in formulating and predicting the properties of MSWIBA asphalt mixes. [ABSTRACT FROM AUTHOR]

Uncertain regression model with autoregressive time series errors studies the relations between response variables and explanatory variables when the errors are dependence. The estimations of the unknown parameters are worth exploring in further research. The least square (LS) estimations were proposed to estimate the unknown parameters. However, when the outliers appear, we find that the LS is not effective. So, in this article, the least absolute deviations (LAD) and the maximum likelihood estimations (MLE) are proposed to estimate the unknown parameters. Moreover, some examples are given to verify the applicability and practicability of these two methods. The comparative analysis is given to verify that the proposed methods are more advantageous and effective than the least square method when the observed data are affected by outliers. Finally, the example of exploring the relationships between GDP and related influencing factors for China, from 2004 to 2020, is given to testify the practicability of the methods. [ABSTRACT FROM AUTHOR]

In order to prevent and reduce the disaster losses caused by compound disasters to cities, it was of great theoretical and practical significance to study the exposure degree of chain compound disaster system. Through the research and analysis of the exposure degree of chain compound disaster system, considering the existing research and defining the connotation of the exposure degree of the compound disaster system, the evaluation model and calculation method of the exposure degree of the chain compound disaster system were deduced and established. Taking the rainstorm-landslide disaster chain in Guangdong-Hong Kong-Macao Greater Bay Area as an example for empirical analysis, the evaluation index system of regional disaster chain exposure was screened and constructed from the aspects of population, economy and society. The order relationship analysis and TOPSIS method were used to calculate the single disaster exposure index of rainstorm and landslide in 52 districts and counties in the bay area. Then, the theoretical model of exposure degree of chain compound disaster system and ArcGIS image processing technology were used to obtain the zoning map of rainstorm-landslide disaster chain exposure in the Guangdong- Hong Kong-Macao Greater Bay Area, and the corresponding disaster prevention and mitigation measures were put forward according to the exposure degree attribute of each regional disaster chain. The results showed that the exposure index corresponding to the economically developed areas was significantly higher than that of other regions, and the low exposure were mainly in the relatively backward areas. Among the indicators, population density and GDP per land area account for the main position, which had the highest impact on regional exposure. By the exposure of regional compound disaster systems, reasonable scientific basis and decision-making support could serve for the government and relevant departments, helping the government, urban planners, and the public better understand and respond to disaster risks, thereby reduce the losses and impacts of disasters. [ABSTRACT FROM AUTHOR]

Aqueous rechargeable batteries (ARBs) are generally safer than non-aqueous analogues, they are also less-expensive, and more friendly to the environment. However, the inherent disadvantage of the narrow electrochemical window of H2O seriously restricts the energy density and output voltage of ARBs, especially aqueous rechargeable Fe-based batteries. Herein, we introduce a new battery system: the anode contains C@Fe/Fe2O3 composite, which is interfaced with an alkaline electrolyte; the cathode contains LiMn2O4 in contact with a neutral electrolyte. A Li+-conducting membrane is carefully selected to decouple the electrode-electrolyte, which effectively widens the electrochemical window to above 2.65 V, thereby enables an aqueous rechargeable iron battery. Its average output voltage is 1.83 V and its energy density is 235.3 Wh/kg at 549 W/kg. In this work, we propose the energy storage mechanism with the aid of density functional theory (DFT). The calculated reduction potential of the anode agrees with the experimental value. Furthermore, this battery system demonstrates long cycle lifespan of approximately 2500 cycles at 2 A/g, corresponding to a capacity retention of 82.1%. These results are very far superior than those of mainstream aqueous rechargeable Fe-based batteries, which guarantee future investigation for storing electricity energy. [ABSTRACT FROM AUTHOR]

Considering that different regions and races have different skeletal development stages, it is imperative to adopt appropriate standards for the age assessment of specific populations. The study aimed to identify a suitable method for knee epiphysis grading and evaluate the feasibility of age estimation based on magnetic resonance imaging (MRI) and X-ray in the Chinese population. MRI images and X-ray images of the knee were collected from 1018 volunteers and 833 volunteers aged 6–20 years old, respectively. A modified Kramer's classification method was used for the experiment. The minimum, maximum, mean, and standard deviation of radiography and MRI were defined for males and females in each age group. The ossification process in knee joints of the female volunteers occurred earlier compared to the male, and the X-ray grading was higher than that of the MRI during the same period. In the regression analysis, the R2 value with age of MRI was generally higher than the X-ray in males. MRI can be used as an effective, reliable, non-invasive, and non-radiation method for evaluating bone age. This study verified the feasibility of applying the knee epiphysis grading for forensic investigations in Chinese population. [ABSTRACT FROM AUTHOR]

Aim and Objectives Background Design Methods Results Conclusion Relevance to Clinical Practice Patient or Public Contribution To investigate the prevalence of dysphagia in patients with COPD, identify the risk factors for dysphagia, develop a visual clinical prediction model and quantitatively predict the probability of developing dysphagia.Patients with COPD are at high risk of dysphagia, which is strongly linked to the acute exacerbation of their condition. The use of effective tools to predict its risk may contribute to the early identification and treatment of dysphagia in patients with COPD.A cross‐sectional design.From July 2021 to April 2023, we enrolled 405 patients with COPD for this study. The clinical prediction model was constructed according to the results of a univariate analysis and a logistic regression analysis, evaluated by discrimination, calibration and decision curve analysis and visualized by a nomogram. This study was reported using the TRIPOD checklist.In total, 405 patients with COPD experienced dysphagia with a prevalence of 59.01%. A visual prediction model was constructed based on age, whether combined with cerebrovascular disease, chronic pulmonary heart disease, acute exacerbation of COPD, home noninvasive positive pressure ventilation, dyspnoea level and xerostomia level. The model exhibited excellent discrimination at an AUC of .879. Calibration curve analysis indicated a good agreement between experimental and predicted values, and the decision curve analysis showed a high clinical utility.The model we devised may be used in clinical settings to predict the occurrence of dysphagia in patients with COPD at an early stage.The model can help nursing staff to calculate the risk probability of dysphagia in patients with COPD, formulate personalized preventive care measures for high‐risk groups as soon as possible to achieve early prevention or delay of dysphagia and its related complications and improve the prognosis.No patient or public contribution. [ABSTRACT FROM AUTHOR]

Optoelectronic devices, such as light‐emitting diodes, have been demonstrated as one of the most demanded forthcoming display and lighting technologies because of their low cost, low power consumption, high brightness, and high contrast. The improvement of device performance relies on advances in precisely designing novelty functional materials, including light‐emitting materials, hosts, hole/electron transport materials, and yet which is a time‐consuming, laborious and resource‐intensive task. Recently, machine learning (ML) has shown great prospects to accelerate material discovery and property enhancement. This review will summarize the workflow of ML in optoelectronic materials discovery, including data collection, feature engineering, model selection, model evaluation and model application. We highlight multiple recent applications of machine‐learned potentials in various optoelectronic functional materials, ranging from semiconductor quantum dots (QDs) or perovskite QDs, organic molecules to carbon‐based nanomaterials. We furthermore discuss the current challenges to fully realize the potential of ML‐assisted materials design for optoelectronics applications. It is anticipated that this review will provide critical insights to inspire new exciting discoveries on ML‐guided of high‐performance optoelectronic devices with a combined effort from different disciplines. [ABSTRACT FROM AUTHOR]

This exploratory study examined whether central auditory tests show differences between people living with HIV (PLWH) treated with two predominant antiretroviral drug therapy (ART) regimens. Cross-sectional. 253 PLWH (mean age 39.8 years) from the Shanghai Public Health Clinical Centre, China. The Hearing in Noise Test speech reception threshold (SRT) assessed central auditory function and the Montreal Cognitive Assessment (MoCA) assessed cognition. The relationship between ART regimen and SRT was evaluated with multivariable linear regression incorporating age, HIV duration, and peripheral hearing ability. Multivariable logistic regression was used to ascertain if SRT and ART regimen predicted MoCA impairment. The two predominant ART regimens differed by one drug (zidovudine or tenofovir). Participants taking the zidovudine-containing regimen had poorer SRT performance (p=.012) independent of age and hearing thresholds. MoCA scores did not differ between drug regimens, but a negative relationship was found between SRT and MoCA impairment (p=.048). ART regimens differed in their association with central auditory test performance likely reflecting neurocognitive changes in PLWH taking the zidovudine-containing regimen. Central auditory test performance also marginally predicted cognitive impairment, supporting further assessment of central auditory tests to detect neurocognitive deficits in PLWH. [ABSTRACT FROM AUTHOR]