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Acute ischemic stroke (AIS) is a most prevalent cause of serious long-term disability worldwide. Accurate prediction of stroke prognosis is highly valuable for effective intervention and treatment. As such, the present retrospective study aims to provide a reliable machine learning-based model for prognosis prediction in AIS patients. Data from AIS patients were collected retrospectively from the Second Affiliated Hospital of Xuzhou Medical University between August 2017 and July 2019. Independent prognostic factors were identified by univariate and multivariate logistic analysis and used to develop machine learning (ML) models. The ML model performance was assessed by area under the receiver operating characteristic curve (AUC) and radar plot. Shapley Additive explanations (SHAP) values were used to interpret the importance of all features included in the predictive model. A total of 677 AIS patients were included in the present study. Poor prognosis was observed in 209 patients (30.9%). Six variables, including neuron specific enolase (NSE), homocysteine (HCY), S-100β, dysphagia, C-reactive protein (CRP), and anticoagulation were included to establish ML models. Six different ML algorithms were tested, and Random Forest model was selected as the final predictive model with the greatest AUC of 0.908. Moreover, according to SHAP results, NSE impacted the predictive model the most, followed by HCY, S-100β, dysphagia, CRP and anticoagulation. Based on the RF model, an online tool was constructed to predict the prognosis of AIS patients and assist clinicians in optimizing patient treatment. The present study revealed that NSE, HCY, CRP, S-100β, anticoagulation, and dysphagia were important factors for poor prognosis in AIS patients. ML algorithms were used to develop predictive models for predicting the prognosis of AIS patients, with the RF model presenting the optimal performance. [ABSTRACT FROM AUTHOR]

Nanoscale zero-valent iron (nZVI) has received increasing attention as a new technology that can provide cost-effective solutions in the remediation and treatment of contaminated soils due to its large surface area and high surface reactivity. nZVI can remove/transfer a wide range of contaminants such as heavy metals, inorganic salts and organic matter from the soil. This bibliometric analysis focused on the application of nZVI in soil remediation. A total of 1255 research papers were traced and analyzed between 1997 and 2022. The use of nZVI for soil remediation has undergone three stages of development and has received a great deal of attention in the last decade. A range of environmental science-related journals provides a stable platform for publishing and discussing papers on this topic. The contributions of different countries, institutions and authors to this topic were analyzed. A complex cooperation network between them was constructed. Keyword analysis was used to understand the different research directions on this topic. Most of these efforts have focused on the preparation and modification of nZVI. The mechanism of its use for the remediation of different pollutants has also been described in detail. Some examples of field applications have also been reported. Finally, the current status of this topic based on bibliometrics and its future perspectives are summarized. [ABSTRACT FROM AUTHOR]

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Purpose: The aim of this work was to investigate the risk factors for cement leakage and new-onset OVCF after Percutaneous vertebroplasty (PVP) and to develop and validate a clinical prediction model (Nomogram). Methods: Patients with Osteoporotic VCF (OVCF) treated with PVP at Liuzhou People's Hospital from June 2016 to June 2018 were reviewed and met the inclusion criteria. Relevant data affecting bone cement leakage and new onset of OVCF were collected. Predictors were screened using univariate and multi-factor logistic analysis to construct Nomogram and web calculators. The consistency of the prediction models was assessed using calibration plots, and their predictive power was assessed by tenfold cross-validation. Clinical value was assessed using Decision curve analysis (DCA) and clinical impact plots. Results: Higher BMI was associated with lower bone mineral density (BMD). Higher BMI, lower BMD, multiple vertebral fractures, no previous anti-osteoporosis treatment, and steroid use were independent risk factors for new vertebral fractures. Cement injection volume, time to surgery, and multiple vertebral fractures were risk factors for cement leakage after PVP. The development and validation of the Nomogram also demonstrated the predictive ability and clinical value of the model. Conclusions: The established Nomogram and web calculator (https://dr-lee.shinyapps.io/RefractureApp/) (https://dr-lee.shinyapps.io/LeakageApp/) can effectively predict the occurrence of cement leakage and new OVCF after PVP. [ABSTRACT FROM AUTHOR]

In the context of coordination of connected autonomous vehicles (CAVs), the platooning operation is a promising application. The formulation of a single stream of CAVs is conducive to traffic efficiency and merging operations extend the benefits for multilane road users. However, the problem of simultaneous merging and platooning lacks comprehensive investigation. A solution is formulated in this paper through a new scheme that considers inter-vehicle safety distance constraints and distributed deployment utilizing local inter-vehicle information exchanges. A distributed consensus-based controller synthesized with a collision avoidance design is developed to direct the CAVs to maintain the velocity and spacing required to avoid inter-vehicle collisions. Furthermore, a framework fusing an agent motion model with vehicle controllers based on a dynamics model that facilitates both longitudinal and lateral controls is proposed, contributing to a cross-model planning-tracking controller. Theoretical proof of asymptotic stability of the proposed controller and its collision avoidance capability are also elaborated. The merging and platooning function was tested in a hardware-in-the-loop (HiL) experiment, demonstrating the precise tracking performance and comparable merging responses to a typical multiagent system. In comparison with trajectory-based merging algorithms, the proposed framework is able to achieve finer stepwise tracking results without centralized coordination or predefined trajectories. [ABSTRACT FROM AUTHOR]

A method, which compares the angular acceleration and vibration spectrums of shafts and gears with physical characteristics of gearbox as tooth numbers and speed ratios, is proposed to find the source of gear rattle vibration. A mathematical and multi-body dynamics co-simulation model is built to reproduce the gear rattle phenomenon of one typical type of manual transmission. In the model, multi-body dynamics part is used for rotational motion and engagement simulation of gearbox shafts and gears, while mathematical part for control and data processing. The simulation results show that the sound source of the gear rattle from the first gear to the third gear is similar to the experimental results; different parameters like rotating damping, contact stiffness, contact damping, inertia moment and torque fluctuation making effects on gear rattle vibration strength are researched and simulated. The comparison of the simulation and experimental results shows that this method can provide recommendations for solving practical gear rattle problems. [ABSTRACT FROM AUTHOR]

A force-aided lever with a preload spring is not only force-saving but also energy-saving. Therefore, it has great potential to be applied to dry clutch actuations. However, the negative stiffness of the clutch diaphragm spring introduces unstable dynamics which becomes more intensive due to the preload spring. In order to explore the intensified unstability, this paper builds dynamic models for the rotating lever coupling a negative stiffness diaphragm spring and a preload spring. The stability analysis using the Routh-Huiwitz criterion shows that the open-loop system can never be stable due to the negative stiffness. Even if the diaphragm spring stiffness is positive, the system is still unstable when the preload of the spring exceeds an upper limit. A proportionalintegral- derivative (PID) closed-loop scheme addressing this problem is designed to stabilize the system. The stability analysis for the closed-loop system shows that stable region emerges in spite of the negative stiffness; the more the negative stiffness is, the less the allowed preload is. Further, the influences of the dimensions and PID parameters on the stability condition are investigated. Finally, the transient dynamic responses of the system subjected to disturbance are compared between the unstable open-loop and stabilized closed-loop systems. [ABSTRACT FROM AUTHOR]

Understanding the factors that contribute to population genetic structures and ecological niche divergence is crucial for elucidating the biogeographical history and speciation of plants. To disentangle the present phylogeographical patterns and evolutionary history of two closely related parapatric species from Ephedra ( Ephedra sinica and E. intermedia), we systematically profiled their population genetic structures, niche divergence and potential speciation processes based on sequence variation of four chloroplast DNA fragments and climate-based ecological niche modelling (ENM). Phylogenetic analyses suggested that E. sinica formed a monophyly which was nested in E. intermedia. The latter species formed two paraphyletic subclades, corresponding to Western and Eastern lineages. Furthermore, the phylogeographical analysis results indicated very significant inter- and intra-species genetic differentiation, and BEAST inference suggested that E. sinica diverged from E. intermedia at 3.20 million years ago (Ma; 95 % HPD: 2.05-8.10 Ma), while the Western lineage of E. intermedia diverged much earlier at 6.10 Ma (95 % HPD: 4.10-11.82 Ma). In addition, niche identity tests performed using MaxEnt strongly supported the hypothesis that the two sister species had significantly diverged on their ecological niches. Isolation by geographical and environment distance (IBD and IBE) tests suggested that the overall divergence of the populations from the two species were more influenced by environmental factors. Our data provide new insight into the ecological speciation of Ephedra and also provides molecular evidence for the identification and genetic conservation of these important pharmaceutical plants. [ABSTRACT FROM AUTHOR]

Most researches on transient fuel control of port fuel injection S.I. engine are carried out from the perspective of advanced mathematical theories. When it comes to practical control, there exist many limitations although they are more intelligent. In order to overcome the fuel wetting effect of PFI engine, the application-oriented transient fuel control is studied by analyzing the key parameters which are closely related with the engine transient characteristics. Both validity and simplicity are taken into consideration. Based on the fuel wall-wetting theory and popular fuel compensation strategy, short-term transient fuel(STF) and long-term transient fuel(LTF), as well as their individual decay approaches, are introduced. STF is to compensate the drastic fuel film loss caused by sudden throttle change, while the function of LTF is to compensate the fuel film loss by manifold air pressure( p) fluctuation. Each of them has their respective pros and cons. The engine fuel mass and air mass are also calculated for air-fuel ratio(AFR) according to ideal gas state equation and empirical equations. The vehicle acceleration test is designed for model validation. The engine experiences several mild and heavy accelerations corresponding to the gear change during vehicle acceleration. STF and LTF control are triggered reliably. The engine transient fuel control simulation adopts the same inputs as the test to ensure consistency. The logged test data are used to check the model output. The results show that the maximum fuel pulse width(FPW) error reaches 2 ms, and it only occurs under engine heavy acceleration condition. The average FPW error is 0.57 ms. The results of simulation and test are close overall, which indicates the accuracy of steady and transient fuel. The proposed research provides an efficient approach not only suitable for practical engineering application, but also for AFR prediction, fuel consumption calculation, and further studies on emission control. [ABSTRACT FROM AUTHOR]