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Aiming at the minority samples cannot be effectively diagnosed when the samples are limited and imbalanced, a multiple classifier ensemble of the weighted and balanced distribution adaptation method (MC-W-BDA) is presented to solve the rolling bearing’s fault diagnosis problem under the limited samples imbalance. We adopt random sampling to obtain enough different training sample sets whose base classifiers are trained in the Reproducing Kernel Hilbert Space. The appropriate base classifiers are integrated into strong classifiers by multiple classifier ensemble strategy to obtain the final result of classification. In addition, we propose A-distance method to automatically set the optimal parameter (balance factor) in MC-W-BDA. Experimental verification verifies the feasibility and effectiveness of proposed approach.In this paper, simultaneous state estimation and parameters identification for a class of nonlinear systems are addressed. With the aim of solving this problem, an adaptive observer based on the sliding mode (AOSM) approach is designed. The main advantage of the proposed adaptive observer design is that it combines the robustness and finite time convergence of the sliding mode observers, with the simplicity of tuning of high-gain observers, reducing tuning effort. The finite time convergence of the proposed adaptive observer is established using a Lyapunov approach. Furthermore, a comparative study of the proposed adaptive observer against schemes from literature is presented, in order to show the advantages of the proposed approach. Finally, numerical results are provided to demonstrate the effectiveness and performance of the proposed approach under noise and external disturbances.Seasonality is a fundamental and common property of most time series in the real world. In this article, we propose a grey seasonal least square support vector regression, abbreviated as GSLSSVR, by combining the dummy variables, framework of the LSSVR model, and grey accumulation generation operation to reflect seasonal variations in functional forms, variables, and parameters. Our framework provides an intuitive and simple set up of arbitrary seasonality in any feature, which considerably enhances model realism. Further, the regulation method is introduced to increase the stability and generalization of the newly proposed model. Using the Lagrange multipliers algorithm, the model parameters are obtained by solving a set of linear equations. In addition, the last block evaluation is developed, which has the same size in the validating and testing data, to identify the hyperparameters of this novel model. For verification purposes, four real seasonal time series having various characteristics are employed in this work, including quarterly electricity consumption, monthly cargo throughput, monthly crude oil production, and monthly gasoline production in China. Experimental results demonstrate that our proposed model can provide for analysis of seasonal regulatory measures and is validated to be superior to other prevalent forecasting models referring to the SGM(1,1), SFGM(1,1), LSSVR, SARIMA-GARCH, and BPNN models. Ultimately, our model is highly recommended for addressing issues with periodic and nonlinear features.

Besides surgical complications, a variety of adverse events may affect patients’ comfort and outcome. The purpose of this prospective study was to identify the incidence and impact of all unexpected events in pediatric surgical patients.

All unexpected events that occurred in our department during the period of February 2017-July 2018 were prospectively assessed. Complications associated with surgery, non-surgical treatment, errors and organizational problems were included. Events were classified using a modified version of Clavien-Dindo. Sentinel events were defined as death, serious injury, or the risk thereof (grade IV-V). Organizational events were analyzed separately. All events were discussed during morbidity and mortality-conferences, and the results and measures were documented.

Unexpected events occurred in 297 of 1605 patients (18.5%), of whom 1124 (70%) had undergone surgery. More than half of all events were not associated with an operation (n=237; 54%). selleck The severity of all events was mostlyith surgical and non-surgical treatment and organizational alterations are documented prospectively. In our study, most events were minor and did not substantially affect patients’ outcomes. Prospective assessment helped to identify organizational shortcomings and develop preventive strategies.

Preservation of the azygos vein (AV) maintains normal venous drainage of the mediastinum and decreases postoperative congestion. The modification of esophageal atresia (EA) repair by preserving AV may prevent postoperative complications and may lead to better outcomes. The data from the Turkish Esophageal Atresia Registry (TEAR) were evaluated to define the effect of AV preservation on postoperative complications of patients with EA.

Data from TEAR for a period of five years were evaluated. Patients were enrolled into two groups according to the preservation of AV. Patients with divided (DAV) and preserved AV (PAV) were evaluated for demographic and operative features and postoperative complications for the first year of life. The DAV and PAV groups were compared according to the postoperative complications, such as fistula recanalization, symptomatic strictures, anastomotic leaks, total number of esophageal dilatations, and anti-reflux surgery. In addition, respiratory problems, which required treatment,omplications, with exception of respiratory problems. AV should be preserved as much as possible to maintain a normal mediastinal anatomy and to avoid respiratory complications.

0.05). The rate of respiratory problems, which required treatment, was significantly higher in the DAV group (p less then 0.05) CONCLUSION The data in the TEAR demonstrated that preserving the AV during EA repair led to no significant advantage on postoperative complications, with exception of respiratory problems. AV should be preserved as much as possible to maintain a normal mediastinal anatomy and to avoid respiratory complications.