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BackgroundThis study aims to investigate the clinical outcome between high-flow nasal cannula (HFNC) and non-invasive ventilation (NIV) therapy in mild to moderate hypoxemic patients on the first ICU day and to develop a predictive model of 48-h intubation.MethodsThe study included adult patients from the MIMIC III and IV databases who first initiated HFNC or NIV therapy due to mild to moderate hypoxemia (100

Abstract Background The role of prophylactic antibiotics in preventing ventilator-associated pneumonia (VAP) in patients undergoing invasive mechanical ventilation (IMV) remains unclear. This network meta-analysis compared the efficacy and safety of antibiotic prophylaxis in preventing VAP in an IMV population in intensive-care units (ICUs). Methods We searched the PubMed, Web of Science, Embase, and Cochrane Library databases from inception to December 2021, to identify relevant studies assessing the impact of prophylactic antibiotics on the incidence of VAP, the mortality, and the duration of ICU stays and hospitalization to perform a meta-analysis. Results Thirteen studies (2144 patients) were included, 12 of which were selected for the primary analysis, which revealed that treatment with prophylactic antibiotics resulted in a lower VAP rate compared with control groups [risk ratio (RR) = 0.62]. Bayesian network meta-analysis indicated that aerosolized tobramycin and intravenous ampicillin–sulbactam presented the greatest likelihood being the most efficient regimen for reducing VAP. Conclusions Antibiotic prophylaxis may reduce the incidence of VAP, but not the mortality, for adult patients undergoing IMV in ICUs. Tobramycin via nebulization and ampicillin–sulbactam via intravenous administration presented the greatest likelihood of being the most efficient regimen for preventing VAP. However, well-designed randomized studies are warranted before definite recommendations can be made.

The corrosion damage of rebars is a leading cause of structural failure in reinforced concrete structures. Timely detection and evaluation of corrosion damage are crucial for ensuring structural safety. The self-magnetic flux leakage (SMFL) technology is often used due to its unique advantages in detecting corrosion damage of rebars. However, challenges persist in theoretically characterizing corrosion damage and exploring influencing factors. Therefore, the magnetic dipole theory model coupled with multiple-shaped defects is proposed and the influence of corrosion expansion force on the detection of corrosion damage is analyzed. The results show that the standard deviation of the magnetic field intensity induced by corrosion varied by up to 833%, while that induced by corrosion expansion force did not exceed 10%. So the changes in the SMFL field induced by corrosion damage play the dominant role and the influence of corrosion expansion force can be ignored. In addition, corrosion damage experiments on reinforced concrete based on the SMFL technology were conducted. The results indicate that the SFML curves of rebars change monotonically with the increasing corrosion degree. Significant variations in the curves correspond well with the locations of severe corrosion on the rebars. There is a positive relationship between the proposed magnetic parameters and the corrosion degree of the rebars. Furthermore, a corrosion damage evaluation model considering multiple parameters is developed to predict the corrosion degree of rebars. The prediction results demonstrate high accuracy, with an average absolute error of only 8.33%, which is within 10%.

Based on the development status of subway train driving technology at home and abroad, the necessity of subway train intelligent driving development and research was expounded.In view of the poor interpretability of machine learning algorithms used in current unmanned driving, with an introduction of fuzzy system, a metro train unmanned driving system based on man-machine hybrid intelligence was proposed, which realized man-machine hybrid intelligence in two ways.The subway train driverless system combined with cognitive system was explored, which a future-oriented solution for the realization of strong artificial intelligence subway train driverless system in the real sense was provided.

Based on the current development status of subway train driving technology in China and abroad, the four stages of subway train driving technology development were proposed and explained as manual driving, automatic driving, unmanned driving, and intelligent unmanned driving.After summarizing the construction situation of unmanned subway trains in China, the disadvantages of the current train control methods based on neural network-based machine learning methods were addressed.Then, the basic block diagram of metro intelligent unmanned driving based on man-machine hybrid intelligence was put forward and the deep fuzzy system was introduced.A promising solution for the combination of expert experience in dealing with emergency and interpretable AI algorithms for unmanned driving system to evolve into intelligent unmanned driving was provided.

Accurate measurement of the stress in steel structures is crucial for structural health monitoring. To achieve this goal, a novel technique, the laser ultrasonic technique, was used in absolute stress measurement in this study. The feasibility of this technique has been verified through theoretical analysis and finite element (FE) analysis. A stress measurement experiment in steel specimens was conducted and the relationship between ultrasonic relative wave velocity and stress was explored. The results revealed that there is a similar linear correlation between the ultrasonic relative wave velocity and absolute stress. The stress can be obtained based on ultrasonic relative wave velocity. According to the stress measurement results, it was found that the absolute error between the measured stress and theoretical stress was largest when the stress level was low, and that the measured error of stress gradually decreased with increases in the applied stress. The relative error between the measured stress and the theoretical stress was within 10% when the stress was higher than 100 MPa. This further verifies the reliability of the laser ultrasonic technique under high-stress conditions. Additionally, the impact of temperature and surface roughness on stress measurement was analyzed. The stress error in stress measurement increased similarly linearly with the increase in temperature and increased non-linearly with the increase in roughness. The corresponding compensation methods were proposed to effectively improve the accuracy of measurement.

Weighted K-Means (WKM) algorithms are increasingly important with the increase of data dimension. WKM faces an initialization problem that is more complicated than K-Means’ because in addition to picking initial cluster centers, it should also provide feature weights. Moreover, the one-dimensional solution to WKM’s widely used objective function is unacceptable in most cases. Yet, the initialization of WKM, especially the initialization of feature weight, has been largely ignored. This paper studies the problem by analyzing Feature weight self-adjustment K-Means(FWSA K-Means), a popular WKM proposed to avoid the one-dimensional solution. Experimental results suggest that the algorithm is actually easy to cluster mainly based on a single feature information when it is not well initialized. Moreover, the paper argues that initial feature weights and cluster centers are equally important in determining the final partition. Therefore it suggests using feature level constraints to improve the initialization and proposes a semi-supervised algorithm Constrained FWSA K-Means (CFWSA K-Means). The algorithm uses constraints in evaluating feature weights and clusters to guide their evolution at the stage of initialization. Experimental results suggest that it is effective and robust in utilizing constraints. In addition, if its initialization process is started by the cluster centers provided by BRIk, an initialization approach for K-Means, the performance can be further improved.

IntroductionPositive airway pressure (PAP) therapy is currently the first-line respiratory support technique for acute respiratory failure (ARF) due to acute cardiogenic pulmonary edema (ACPE), but the accompanied adverse events and patient's intolerance with treatment in some cases limited its use in clinical practice. Some recent trials indicated that high-flow nasal cannula oxygen (HFNO) is a promising alternative to PAP therapy. In order to choose the optimum treatment for patients with ACPE, this network meta-analysis will firstly compares the efficacy of HFNO, PAP, and conventional oxygen therapy (COT).Methods and analysisThe Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols 2015 statement and its extension for network meta-analysis will be followed in the conduct of this investigation. We will examine these databases: PubMed, EMBASE, Cochrane Central Register of Controlled Trials and Web of Science. The ClinicalTrials.gov and World Health Organization International Clinical Trials Registry Platform Search Portal will be used to search ongoing trials. Only randomized controlled trials meeting the eligibility criteria will be included. Through the Cochrane Collaboration's tool, the included studies' risk of bias will be assessed. The pairwise meta-analysis will be performed with RevMan 5.4.1 software. A Bayesian network meta-analysis will use random-effects models to derive odds ratios for the treatment effects of all interventions compared to each other using R software (version 3.6.1), and the rjags and gemtc packages. The Q statistic and I2 index will be used for investigating the heterogeneity, and subgroup analysis or sensitivity analysis will be used to explore the source of heterogeneity. In addition, the Grading of Recommendations Assessment, Development and Evaluation system will be used to inspect the quality of evidence.

BackgroundJAK (Janus kinases) inhibitors have been proposed as a promising treatment option for the coronavirus disease-2019 (COVID-19). However, the benefits of JAK inhibitors and the optimum thereof for COVID-19 have not been adequately defined.MethodsDatabases were searched from their inception dates to 17 June 2022. Eligible studies included randomized controlled trials and observational studies. Extracted data were analyzed by pairwise and network meta-analysis. The primary outcome was the coefficient of mortality.ResultsTwenty-eight studies of 8,206 patients were included and assessed qualitatively (modified Jadad and Newcastle–Ottawa Scale scores). A pairwise meta-analysis revealed that JAK inhibitors effectively reduced the mortality (OR = 0.54; 95% CI: 0.46–0.63; P < 0.00001; I2 = 32%) without increasing the risk of adverse events (OR = 1.02; 95% CI: 0.88–1.18; P = 0.79; I2 = 12%). In a network meta-analysis, clinical efficacy benefits were seen among different types of JAK inhibitors (baricitinib, ruxolitinib, and tofacitinib) without the observation of a declined incidence of adverse events. The assessment of rank probabilities indicated that ruxolitinib presented the greatest likelihood of benefits regarding mortality and adverse events.ConclusionJAK inhibitors appear to be a promising treatment for COVID-19 concerning reducing mortality, and they do not increase the risk of adverse events vs. standard of care. A network meta-analysis suggests that mortality benefits are associated with specific JAK inhibitors, and among these, ruxolitinib presents the greatest likelihood of having benefits for mortality and adverse events.Systematic review registration[www.crd.york.ac.uk/prospero], identifier [CRD42022343338].

ObjectiveThis study seeks to evaluate the diagnostic value of computed tomography (CT) in pulmonary hypertension.MethodPubMed, Embase, Scopus, and Web of Science databases were searched to obtain the relevant English literature, and the retrieval time until June 2022. The quality of the included studies is evaluated using the QUADAS-2 tool. The quality of the included studies was assessed, followed by a meta-analysis, analyze heterogeneity, summarize sensitivity and specificity, draw the comprehensive subject working characteristics (sROC) curve, calculate the area under the curve and conduct subgroup analysis and sensitivity analysis to find the source of the heterogeneity.ResultsA total of 12 articles were included, all with pulmonary artery diameter/liter aortic diameter >1 or 1 as the diagnostic criteria for pulmonary hypertension, and a total of 1,959 patients were included. Deek’s funnel plot analysis suggests that there is no significant publication bias (P = 0.102). The combined sensitivity was 0.652 (95% CI: 0.579, 0.719), combined specificity was 0.830 (95% CI: 0.796, 0.880), positive likelihood ratio was 3.837 (95% CI: 3.215, 4.579), negative likelihood ratio was 0.419 (95% CI: 0.346, 0.507), diagnostic odds ratio was 9.157 (95% CI: 6.748, 12.427) and area under the summary receiver operating characteristic (SROC) curve was 0.84 (95% CI: 0.81, 0.87).ConclusionThe CT examination of pulmonary artery diameter/aortic artery hypertension is worthy of clinical application.

Recently, heat pump drying has been widely used in tobacco processing. Considering the importance of this issue, it is of significant importance to further investigate temperature distribution and energy analysis in the drying process. To develop an energy-saving, environmental-friendly, and high-quality tobacco drying method, temperature distribution, dehumidification performance, the economic issues, and thermal efficiency of a heat pump curing barn (HPCB) and a traditional coal-fired bulk curing barn (TCCB) were compared. The regional temperature eigenvalue model was applied to describe the temperature uniformity with HPCB and TCCB. Moreover, thermal efficiency was obtained through energy tests. The obtained results showed that HPCB is beneficial to improve the drying quality of tobacco. The performed analyses showed that the thermal efficiency of the TCCB and HPCB was 42.02% and 66.53%, respectively. Accordingly, heat pump technology is recommended for industrial drying of tobacco leaves and obtaining high-quality products.

In this study, the martensitic stainless-steel powder had been successfully deposited on the surfaces of 1045 wrought steel substrates using five types of laser metal deposition strategies. The results showed that a thin buffer layer can be naturally generated in-between the deposition layer and substrate owning to the dilution effect, producing functionally graded structures consisted of martensite dendrite matrices and intermetallic phases (e.g., M23(C, B)6). Unfortunately, the poor deformation characteristic of natural buffer layers can exacerbate the risk of cracking, leading to an incompatibility between martensitic stainless steel and forming steel. A thick artificial buffer layer was then designed by addition of Inconel 625 powder. Because of the formation of graded austenite phase in the artificial buffer layer, the yield strength of specimen was enhanced significantly. Hence, our study can be used for manufacture of reliable moulds with high surface hardness and structural strength and may be helpful in further developing hybrid forming strategy in the field of mould manufacture. When subjected to stress impact during mould filling, the artificial buffer layer with functionally graded properties would have a perfect capability to bear the deformation as the load increased, dramatically improving the reliability and functionality of moulds.

The combination of additive manufacturing and conventional metal forming processes provides the possibility for improvements of forming efficiency and flexibility. Substrate preheating is an implementable technique to improve the interface adhesion properties of the hybrid forming method. The present experiment investigates the adhesion of additive manufactured 316 L steel on P20 and 1045 steel substrates under two substrate temperatures, and the geometrical characterization, interfacial microstructure and mechanical property of the hybrid specimens were compared. As a result, it was found that the ratio of deposition height to the width was reduced and the width was increased under substrate preheating. Tensile results show that the ultimate strength of 1045 and 316 L hybrid specimens was obviously increased, while the properties of hybrid specimens P20 and 316 L were similar, under different substrate temperature conditions. For the hybrid specimens with the metallurgically bonding characteristic, the tensile properties can reach the level of 316 L depositioned specimens fabricated by laser metal deposition (LMD). Furthermore, substrate preheating had little effect on the microstructure of the laser metal deposition zone, and significant influence on the microstructure of the heat affected zone, which was reflected in the difference of the hardness distribution.

In light of the intrinsic relationship between weld fatigue damage and the characteristics of magnetic leakage signals, fatigue experiments were conducted on butt welds to analyze the evolution of magnetic leakage signal as fatigue cycles increased. The introduction of two-dimensional spectral entropy allowed for the construction of a fatigue stage division model based on the two-dimensional spectral entropy diagram. The results revealed that distinctions between magnetic leakage signal under loaded and unloaded conditions were solely evident in their magnitude, with consistent curve distribution trends observed across various fatigue cycles. Furthermore, the distribution pattern of magnetic leakage signal displayed significant fluctuations, characterized by a sharp gradient increase following the emergence of fatigue cracks. These distribution characteristics of magnetic leakage signal differed markedly from the magnetic field distribution at other fatigue stages, with a higher growth rate observed as fatigue cycles increased. The two-dimensional spectral entropy spectrum analysis of magnetic leakage signals at different fatigue stages indicated the disorder in the magnetic leakage signal distribution within the high fatigue zone, signifying the expansion of fatigue microcracks. To some extent, two-dimensional spectral entropy can serve as an early warning system for detecting fatigue cracks in welds and achieving early identification of fatigue microcracks. [ABSTRACT FROM AUTHOR]