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This study utilizes the ResNet18 network to classify and recognize trajectories of planar mechanisms. This research begins by deriving formulas for trajectory points in various typical planar mechanisms, and the resulting trajectory images are employed as samples for training and testing the network. The classification of trajectory images for both upright and inverted configurations of a planar four-bar linkage is investigated. Compared with AlexNet and VGG16, the ResNet18 model demonstrates superior classification accuracy during testing, coupled with reduced training time and memory consumption. Furthermore, the ResNet18 model is applied to classify trajectory images for six different planar mechanisms in both upright and inverted configurations as well as to identify whether the trajectory images belong to the upright or inverted configuration for each mechanism. The test results affirm the feasibility and effectiveness of the ResNet18 network in the classification and recognition of planar mechanism trajectories. [ABSTRACT FROM AUTHOR]

The current study on the synthesis problems of four-bar mechanism trajectories primarily relies on establishing a numerical atlas based on trajectory characteristics and employing neural networks to synthesize mechanism parameters. However, this approach has several shortcomings, including a vast database, inefficient retrieval, and challenges in maintaining accuracy. This paper presents a method for synthesizing a trajectory-generation mechanism that combines the extreme gradient boosting (XGBoost) algorithm with a genetic algorithm (GA). The purpose is to synthesize, based on a particular trajectory, the dimensions and installation position parameters of a four-bar mechanism. The paper classifies the trajectories according to their shape features and geometric center placements, thereby improving the accuracy of the XGBoost model for synthesizing mechanisms. The XGBoost algorithm is employed to synthesize the basic dimensional parameters for the mechanism, with the relative slopes of trajectories as input features. The synthesized basic dimensional parameters are turned into parameters for the actual mechanism by researching the scaling, translation, and rotation relationships between mechanisms and the trajectories they generate. The accuracy of the generated trajectories from the synthesized mechanism can be improved by applying GA to optimize the mechanism parameters. Five comparative examples are provided in this research for the different scenarios of given trajectory curves and trajectory points. The effectiveness and accuracy of the proposed approach in this study are validated in comparison to existing research methods by comparing errors between the generated trajectories and the given trajectories. [ABSTRACT FROM AUTHOR]

Aim: This study aims to identify and reach a consensus among experts on the specific gastroenterology drugs that a gastroenterology nurse may be able to prescribe. Design: This study employs a modified Delphi design to reach a consensus among medical and nursing experts about the gastroenterology system drugs that nurses may prescribe medication. Method: From August 2019–November 2019, a two‐round study, consisting of 26 medical and nursing experts, was conducted using the Delphi method. IBM SPSS Ver. 22 and descriptive statistical software were used to analyse the results of the consultations. Results: A total of 37 drugs across nine categories are identified as relevant to Chinese nurses working in gastroenterology departments. Among them, four drugs are generally prescribed independently, 24 tend to be prescribed collaboratively and nine are prescribed either independently, or in collaboration with others. Conclusions: This list is a fundamental and dependable instrument for identifying the gastroenterology drugs that could possibly be prescribed by gastroenterology nurses in China. The research results have important guiding significance for the formulation and implementation of relevant policies for nurses to prescribe medicines. Impact: Nurse prescribing has become a global trend and is slowly gaining attention in China under the development strategy of 'Healthy China'. As such, this list will give some reference for policy formulation and implementation of future nurse prescribing in mainland China. [ABSTRACT FROM AUTHOR]

Background: The CHA 2 DS 2 -VASc score was initially applied to stratify stroke risk in patients with atrial fibrillation (AF) and was found to be effective in predicting all-cause mortality outcomes. To date, it is still unclear whether circulating long non-coding RNAs (lncRNAs) as emerging biomarkers, can improve the predictive power of the CHA 2 DS 2 -VASc score in stroke and all-cause mortality., Methods: Candidate lncRNAs were screened by searching the literature and analyzing previous RNA sequencing results. After preliminary verification in 29 patients with AF, the final selected lncRNAs were evaluated by Cox proportional hazards regression in 192 patients to determine whether their relative expression levels were associated with stroke and all-cause mortality. The c-statistic, net reclassification improvement (NRI), and integrated discrimination improvement of the patients were calculated to evaluate the discrimination and reclassification power for stroke and all-cause mortality when adding lncRNA expression levels to the CHA 2 DS 2 -VASc score model., Results: Five plasma lncRNAs associated with stroke and all-cause mortality in AF patients were selected in our screening process. Patients with elevated H19 levels were found to have a higher risk of stroke (hazard ratio [HR] 3.264, 95% confidence interval [CI]: 1.364-7.813, P  = 0.008). Adding the H19 expression level to the CHA 2 DS 2 -VASc score significantly improved the discrimination and reclassification power of the CHA 2 DS 2 -VASc score for stroke in AF patients. In addition, the H19 level showed a marginally significant association with all-cause mortality (HR 2.263, 95% CI: 0.889-5.760, P  = 0.087), although it appeared to have no significant improvement for the CHA 2 DS 2 -VASc model for predicting all-cause mortality., Conclusions: Plasma expression of H19 was associated with stroke risk in AF patients and improved the discriminatory power of the CHA 2 DS 2 -VASc score. Therefore, lncRNA H19 served as an emerging non-invasive biomarker for stroke risk prediction in patients with AF., (Copyright © 2022 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.)

Objective: The prognostic value of interleukin-6 (IL-6) in patients with atrial fibrillation (AF) has not been fully elucidated. Therefore, we conducted a cohort study and a meta-analysis to assess the predictive value of IL-6 for stroke and mortality in patients with AF., Methods: A cohort study was performed in newly diagnosed non-valvular patients with AF. A total of 217 patients with AF were followed up for a mean of 27 months. A multivariate Cox regression analysis was used to evaluate the association between IL-6 and stroke/all-cause mortality. The incremental value was also assessed by adding IL-6 to the CHA2DS2-VASc score. Besides, a meta-analysis of all reported cohort studies and our cohort study was conducted to validate the association of circulating IL-6 and stroke/mortality in patients with AF., Results: Our cohort study showed that elevated plasma level of IL-6 was an independent risk factor for predicting stroke [hazard ratio (HR)=3.81; 95% confidence interval (CI), 1.11-13.05; p=0.033] and all-cause mortality (HR=3.11; 95% CI, 1.25-7.72; p=0.015) in patients with AF. Adding IL-6 levels to CHA2DS2-VASc score showed limited improvement of the predictive power for stroke [area under curve (AUC) from 0.81 to 0.88, p=0.006]. Meta-analysis confirmed that increased circulating level of IL-6 was significantly associated with increased risk of stroke (pooled HR=1.97; 95% CI, 1.22-3.17; p=0.006) and all-cause mortality (pooled HR=2.73; 95% CI, 2.29-3.25; p<0.001)., Conclusion: Increased circulating level of IL-6 was significantly associated with greater risk of stroke and all-cause mortality in patients with AF. Adding IL-6 biomarker to the CHA2DS2-VASc score may help to determine the management of AF treatment.

Streptococcal species constitute a large group of commensal and pathogenic Gram-positive bacteria that exist in a wide variety of habitats. The family of small RNAs is typically ranged in size from 50 to 300 nucleotides, and acts as regulators in bacteria. The last decade has witnessed the increasing findings of small RNAs (sRNAs), which play important regulatory roles in the variety of biological processes in streptococci. In this review, we summarized the recent achievements in the identification of streptococcal sRNAs, mainly in Streptococcus pyogenes and Streptococcus pneumoniae . In addition, we particularly focused on the functions that sRNAs exert in the regulatory networks of both phenotypical traits and pathogenicity. The fact that sRNAs act as a critical fine-tuning regulator of streptococci may not only reveal in-depth mechanisms of bacterial post-transcriptional regulations in response to environmental perturbance, but also provide promising approaches to the better management of streptococcal infections.