On-line detection method for outliers of dynamic instability measurement data in geological exploration control process

Considering the characteristics of the vibration data detected by the unstable regulation process in the grinding and grading control system and the shortcomings of the traditional wavelet anomaly detection method, an online anomaly detection method combining autoregressive and wavelet analysis is proposed. By introducing the improved robust AR model, this method can overcome the problem that the time and frequency of traditional anomaly detection using wavelet analysis method cannot be well balanced and ensure the rationality of normal detection of process data. Considering the characteristics of parameter change and dynamic characteristics in the process of grinding and grading, the proposed method has the ability of on-line detection and parameter updating in real time, which ensures the control parameters of time-varying process control system. In order to avoid the problem that the traditional anomaly detection method needs to set the detection threshold, introduce the HMM to analyse the wavelet coefficients and update the HMM parameters online, which can ensure that the HMM can well reflect the distribution of the abnormal value of the process data. Through the experiment and application, it is proven that the anomaly data detection method proposed in this paper is more suitable for the detection data in the process of unstable regulation

Identification and quantification of anthocyanins in transgenic purple tomato

Citation: Su, X., Xu, J., Rhodes, D., Shen, Y., Song, W., Katz, B., … Wang, W. (2016). Identification and quantification of anthocyanins in transgenic purple tomato. Food Chemistry, 202, 184–188. https://doi.org/10.1016/j.foodchem.2016.01.128Anthocyanins are natural pigments derived from the phenylpropanoid pathway. Most tomatoes produce little anthocyanins, but the transgenic purple tomato biosynthesizes a high level of anthocyanins due to expression of two transcription factors (Del and Ros1). This study was to identify and quantify anthocyanins in this transgenic tomato line. Seven anthocyanins, including two new anthocyanins [malvidin-3-(p-coumaroyl)-rutinoside-5-glucoside and malvidin-3-(feruloyl)-rutinoside-5-glucoside], were identified by LC-MS/MS. Petunidin-3-(trans-coumaroyl)-rutinoside-5-glucoside and delphinidin-3-(trans-coumaroyl)-rutinoside-5-glucoside were the most abundant anthocyanins, making up 86% of the total anthocyanins. Compared to undetectable anthocyanins in the wild type, the contents of anthocyanins in the whole fruit, peel, and flesh of the Del/Ros1-transgenic tomato were 5.2 ± 0.5, 5.1 ± 0.5, and 5.8 ± 0.3 g/kg dry matter, respectively. Anthocyanins were undetectable in the seeds of both wide-type and transgenic tomato lines. Such novel and high levels of anthocyanins obtained in this transgenic tomato may provide unique functional products with potential health benefits

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Unscented Particle Filter for SOC Estimation Algorithm Based on a Dynamic Parameter Identification

In order to solve the problem that the model-based State of Charge (SOC) estimation method is too dependent on the model parameters in the SOC estimation of electric vehicles, an improved genetic algorithm is proposed in this paper. The method has the advantages of being able to quickly determine the search range, reducing the probability of falling into local optimum, and having high recognition accuracy. Then we can realize online dynamic identification of power battery model parameters and improve the accuracy of model parameter identification. In addition, considering the complex application environment and operating conditions of electric vehicles, an SOC estimation method based on improved genetic algorithm and unscented particle filter (improved GA-UPF) is proposed. And we compare the improved GA-UPF algorithm with the least square unscented particle filter (LS-UPF) and improved GA unscented Kalman filter (improved GA-UKF) algorithm. The comparison results show that the improved GA-UPF algorithm proposed in this paper has higher estimation accuracy and better stability. It also reflects the practicability and accuracy of the improved GA parameter identification algorithm proposed in this paper

Multi-Level Characteristic Basis Function Method For Analysis Of Scattering From Objects Embedded In Multi-Layered Media

The multi-level characteristic basis function method is adapted to analyze the problem of scattering from objects embedded in layered media. Inhomogeneous plane waves incident upon the layered media are used to construct multiple levels of characteristic basis functions (CBFs). The use of the CBFs helps reduce the size of the impedance matrix of the associated method of moment significantly, enabling us to employ direct solver as opposed to iterative solvers. The process of generating the reduced matrix is shown to be naturally parallel, and the reduced matrix to be well conditioned, which obviates the need of pre-conditioning. Numerical results are included to demonstrate the accuracy and efficiency of the present approach when used for the analysis of scattering from objects embedded in multi-layered media

Wake structure and hydrodynamic performance of flapping foils mimicking fish fin kinematics

Numerical simulations are used to investigate the wake structure and hydrodynamic performance of bionic flapping foils. The study is motivated by the quest to understand the fluid dynamics of fish fins and use it in the underwater propulsion. The simulations employ an immersed boundary method that makes it possible to simulate flows with complex moving boundaries on fixed Cartesian grids. A detailed analysis of the vortex topology shows that the wake of flapping foils is dominated by two sets of complex shaped vortex rings that convect at oblique angles to the wake centerline. The wake of these flapping foils is characterized by two oblique jets. Simulations are also used to examine the wake vortex and hydrodynamic performance over a range of Strouhal numbers and maximum pitch angles and the connection between the foil kinematics, vortex dynamics and force production is discussed. The results show that the variety law of the hydrodynamic performance with kinematic parameters strongly depends on the flow dynamics underlying the force production, including the orientation, interconnection and dissipation rate of the vortex rings. Keywords: Flapping foil, Immersed boundary method, Hydrodynamic performance, Wake vorte

Online Outlier Detection for Time-varying Time Series on Improved ARHMM in Geological Mineral Grade Analysis Process

Given the difficulty of accurate online detection for massive data collecting real-timely in a strong noise environment during the complex geological mineral grade analysis process, an order self-learning ARHMM (Autoregressive Hidden Markov Model) algorithm is proposed to carry out online outlier detection in the geological mineral grade analysis process. The algorithm utilizes AR model to fit the time series obtained from “Online x - ray Fluorescent Mineral Analyzer” and makes use of HMM as a basic detection tool, which can avoid the deficiency of presetting the threshold in traditional detection methods. The structure of traditional BDT (Brockwell-Dahlhaus-Trindade) algorithm is improved to be a double iterative structure in which iterative calculation from both time and order is applied respectively to update parameters of ARHMM online. With the purpose of reducing the influence of outlier on parameter update of ARHMM, the strategies of detection-before-update and detection-based-update are adopted, which also improve the robustness of the algorithm. Subsequent simulation by model data and practical application verify the accuracy, robustness, and property of online detection of the algorithm. According to the result, it is obvious that new algorithm proposed in this paper is more suitable for outlier detection of mineral grade analysis data in geology and mineral processing