bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visible-Light-Mediated Oxidation of 1-Benzyl-3,4-dihydroisoquinolines with Dioxygen: A Switchable Synthesis of 1-Benzoylisoquinolines and 1-Benzoyl-3,4-dihydroisoquinolines
Authors: Wu Hongli , Gan Haifeng , Ma Peipei 
Published: August 2023

AbstractA visible-light-mediated metal-free oxidation of 1-benzyl-3,4-dihydroisoquinolines (1-BnDHIQs) for the switchable preparation of a wide range of 1-benzoylisoquinolines (BzIQs) and 1-benzoyl-3,4-dihydroisoquinolines (BzDHIQs) is realized using dioxygen as the oxidant. This protocol provides a facile route for the efficient synthesis of isoquinoline alkaloids. Mechanistic investigations suggest that a radical pathway and an ionic pathway may exist simultaneously, with both pathways proceeding via a common key peroxide intermediate to give the oxidized products.
A mathematical model for the process of accumulation of scientific knowledge in the early modern period
Authors: Zamani Maryam , El-Hajj Hassan , Vogl Malte , Kantz Holger , Valleriani Matteo 
Published: August 2023

AbstractIn the present work, we model the diffusion of scientific knowledge embodied in the textbooks of the Sphaera corpus. This corpus consists of more than 350 different editions of textbooks used for teaching astronomy in European universities during the early modern period. Connections between the editions are based on mutual semantic knowledge and are arranged in a multiplex network of four layers, with each layer representing a different semantic relation. The modeling aims for a better understanding (and possible prediction) of the process of knowledge accumulation in the various editions. We consider semantic text-parts as knowledge units transferred between the editions, and show how these units spread using both an SI model and its modified version, the Bass model. Both models include a parameter representing the rate of transfer, which is interpreted as the mechanism underlying the process of knowledge accumulation; the Bass model has an extra parameter that represents the rate of external influence and stands out as the “resistance to adoption from” and “resistance to be influenced by” other knowledge systems. The modeling has helped us to chart the path and mechanisms of knowledge transformation in the early modern period. Networks are identified by adding further layers whose graphs express socioeconomic relationships and conditional sub-networks. The comparison between the model and these layers enables us to conclude that the accumulation of knowledge was highly dependent on the institutional embedding of scientific production because the diffusion of knowledge was mostly determined by the economic constraints of early modern printers and publishers. It further suggests that geographic proximity played a role—although secondary—in the diffusion of knowledge but only under the condition that the book producers involved were still living. The transformation of early modern scientific knowledge is, therefore, highly dependent on the institutional and economic contexts of the book producers.
Recent dissertations on L2 pronunciation
Authors: Levis John M. , Zawadzki Zoë 
Published: August 2023

AbstractThis editorial summarizes 40 recent dissertations (2018–2023) on L2 pronunciation topics. Although it was nearly impossible to pigeonhole dissertations into single sub-categories (e.g., pronunciation training studies often also address questions of intelligibility), we have organized them into six main topic areas: Teachers and Learners; Special Contexts; Prosody and Fluency; Technology; Pronunciation Training; and Intelligibility, Comprehensibility and Accentedness. The wide range of dissertations from around the world indicates a bright future for the field.
Implementation of Fall Armyworm Management Plan in Ghana
Authors: Williams Frances , Marwijk Anne van , Rware Harrison , Essegbey George , Besah Patrick , Duah Solomon , Hevi Walter , Karbo Naaminong , Quaye Wilhemina , Watiti James 
Published: August 2023

Abstract
Fall armyworm (FAW), an invasive pest, was confirmed in Ghana in 2016. As a result, a group of stakeholders developed a national FAW management plan. This case considers a review of the management plan conducted through outcome harvesting, a Sprockler (story-based) inquiry, and interviews with key informants.
The review found evidence of stakeholder collaboration, increased public awareness of FAW and management practices, and more coordinated research into low-risk management options. It also found that the formal taskforce structure, common goals and ownership, effective collaboration and communication, and a commitment to implementing the action plan by all actors were the key factors in the FAW response. Challenges included a slow initial response, inadequate funds, and limitations in the agricultural extension system. Key steps to ensure future preparedness include implementation of the National Invasive Species Strategy and Action Plan (NISSAP), establishment of a standing taskforce and emergency fund to address new pest outbreaks, improved monitoring and surveillance especially at borders and ports of entry, strengthened research capacity, especially in pest risk analyses, involvement of all stakeholders at central and local levels, and development of generic and specific emergency response guidelines for future outbreaks.

Information
© CAB International 2023
Generation and optimization of cross-sections for electron-C4F7N collisions
Authors: Flynn M , Agan J , Neuber A , Stephens J 
Published: August 2023

Abstract
A complete and consistent set of electron-neutral collision cross-sections for the novel insulating gas C4F7N is reported. The set is composed of a combination of cross-sections previously reported in literature, optimized via a genetic algorithm in conjunction with a multi-term Boltzmann equation solver, and calculated ab initio using the R-matrix code Quantemol-EC. The finalized set accurately reproduces reported macroscopic rate and transport coefficients as well as Townsend coefficients and critical electric field strengths in C4F7N and its mixtures with nitrogen, carbon dioxide, and argon.
Long-term stability of molecular doped epigraphene quantum Hall standards: single elements and large arrays (R
K/236 ≈ 109 Ω)
Authors: Shetty Naveen , Bergsten Tobias , Eklund Gunnar , Avila Samuel Lara , Kubatkin Sergey , Cedergren Karin , He Hans 
Published: August 2023

Abstract
In this work we investigate the long-term stability of epitaxial graphene (epigraphene) quantum Hall resistance standards, including single devices and an array device composed of 236 elements providing R
K/236 ≈ 109 Ω, with R
K the von Klitzing constant. All devices utilize the established technique of chemical doping via molecular dopants to achieve homogenous doping and control over carrier density. However, optimal storage conditions and the long-term stability of molecular dopants for metrological applications have not been widely studied. In this work we aim to identify simple storage techniques that use readily available and cost-effective materials which provide long-term stability for devices without the need for advanced laboratory equipment. The devices are stored in glass bottles with four different environments: ambient, oxygen absorber, silica gel desiccant, and oxygen absorber/desiccant mixture. We have tracked the carrier densities, mobilities, and quantization accuracies of eight different epigraphene quantum Hall chips for over two years. We observe the highest stability (i.e. lowest change in carrier density) for samples stored in oxygen absorber/desiccant mixture, with a relative change in carrier density below 0.01% per day and no discernable degradation of quantization accuracy at the part-per-billion level. This storage technique yields a comparable stability to the currently established best storage method of inert nitrogen atmosphere, but it is much easier to realize in practice. It is possible to further optimize the mixture of oxygen absorber/desiccant for even greater stability performance in the future. We foresee that this technique can allow for simple and stable long-term storage of polymer-encapsulated molecular doped epigraphene quantum Hall standards, removing another barrier for their wide-spread use in practical metrology.
Real-time Monitoring Algorithm of Muscle State Based on sEMG Signal
Authors: Pang Peng , Wei Xiwen , Yang Xinnian 
Published: August 2023

Abstract
Muscle fatigue can occur when we do too much physical activity in a short period of time, or if we have not been exercising regularly. For patients who need rehabilitation training, muscle fatigue has certain safety risks. Therefore, real-time monitoring of muscle fatigue is very necessary and meaningful. At present, there are few studies on the assessment of muscle status, and most of the methods are limited to the detection of fatigue threshold, lagging behind the occurrence of fatigue. This paper analyzes the change law of the fatigue process model and summarizes it, and designs it into a real-time evaluation algorithm of muscle state. First, the autoregressive moving average (ARMA) model is constructed utilizing surface electromyography (sEMG) and joint motion angle data. Next, the parameters are identified and monitored in real-time. Finally, hierarchical clustering is employed to categorize levels of fatigue. The algorithm is capable of capturing changes in fatigue-induced correlations between sEMG and the corresponding joint motion angles during dynamic movements, enabling accurate classification of muscle fatigue states. Experimental results have demonstrated the effectiveness of the algorithm, which has significant implications for real-time evaluation of human muscle state and the design of control systems in human-computer interaction.
Implementation and Design of Metro Process Quality Inspection System based on Image Processing Technology
Authors: Huang Lizhong , Zhang Quanwei 
Published: August 2023

Abstract
In recent years, China’s subway industry has entered a phase of rapid development, and at the same time, the commissioning of large-scale new lines has brought huge challenges to production and operation. In the quality inspection system of subway process, the traditional way is to use human as the carrier of quality inspection, but with the input of large-scale production lines, the manual inspection method is far from meeting the needs of industrial production. Based on the above background, this paper applies image processing technology to the quality inspection process of subway process, and completes the design and implementation of the quality inspection system of subway process based on image processing. In this paper, a lightweight feature-enhanced convolutional neural network model is proposed under the premise of ensuring efficiency. The model deepens the structure of the backbone feature extraction network, adds another prediction scale layer, realizes three-scale prediction, and enhances the semantic information of the shallow feature map, thus improving the detection accuracy of small-scale defects. At the same time, the algorithm has room for optimization and improvement in “identification of anti-loosening wire” and “accurate positioning of through-hole gaskets and washers without missing”.
Image Enhancement Algorithm of Foggy Sky with Sky based on Sky Segmentation
Authors: Sun Wei , Wu Jianli , Rashid Haroon 
Published: August 2023

Abstract
In recent years, image defogging has become a research hotspot in the field of digital image processing. Through defogging enhancement processing, the visual quality of foggy images can be significantly improved, and it is also an important part of subsequent image processing. To overcome the limitations of traditional image dehazing, an image enhancement algorithm for foggy image with sky based on sky segmentation is proposed. Firstly, based on K-means clustering and sky feature analysis, sky region recognition is performed for fog image with sky. Secondly, according to the pixels of sky region, the rough transmittance is corrected, and the dehazing image is obtained by dark channel prior image dehazing based on guided filter. Finally, the dehazing image is equalized by bi-histogram equalization. This algorithm effectively avoids the problem of color distortion and halo caused by the traditional dark channel prior dehazing algorithm in the sky area, and makes the restored foggy image have better global and local contrast.
A Camera Calibration Method for Limited Motion of Target in Space
Authors: Dang Zhiyuan , Yuan Yun , Geng Nan , Khel Naveed Ullah Kaka 
Published: August 2023

Abstract
In modern industrial production, vision measurement systems are widely used for product quality inspection. Camera calibration is a crucial step in vision measurement systems that directly affects the accuracy of measurement results. However, in practical applications, the limited space for measurement and restricted movement of calibration targets present new challenges for camera calibration. In this paper, we propose a camera calibration method that is suitable for calibration targets with limited movement space. This method only requires one image of the calibration target to complete system calibration, greatly simplifying the on-site calibration work. Experimental results show that our method has a re-projection error of 0.0187 pixels, indicating high reliability and applicability. The application of this method in the inspection of seamless steel pipes demonstrates its potential for practical industrial production.
Scratch Detection Method of Shaft Parts Based on Improved YOLOv5
Authors: Bai Haodong , Chen Guanyu , Fu Huiting , Liu Changying 
Published: August 2023

Abstract
The pre-extracted target object is always distorted due to many parts spots, surface reflection and other factors in traditional visual inspection. Therefore, a detection process based on improved YOLOv5 is proposed. In the early stage, for the optimization of light source, the circular light is generally used to successfully extract the region of interest, so as to reduce the scratches caused by image pretreatment, resulting in detection omission and distortion. Adding the ACON (All Class in One Network, ACON) activation function can improve the network feature extraction ability and the accuracy of the detection algorithm. Bounding box loss, means of target detection loss and classification loss are all significantly improved by the improved algorithm, far exceeding the performance of traditional detection methods, and all have a certain degree of reduction.
Design of Solar Endurance Control for Unmanned Aerial Vehicles based on Schmidt Trigger Control
Authors: Hu Xusheng , Liu Juan , Kocheril Rajesh 
Published: August 2023

Abstract
In order to improve the endurance of unmanned aerial vehicles (UAVs), a power supply controller with automatic switching between solar energy and battery was designed. The controller is mainly composed of an AT89C51 single chip microcomputer. By collecting ambient light intensity and comparing it with the preset light intensity of the system, the controller completes automatic switching of the power supply for solar unmanned aerial vehicles, thereby achieving continuous and stable power supply for solar unmanned aerial vehicles. In addition, the implementation method of the single-chip microcomputer program in the controller is also introduced. The control core is to use Schmidt de shake control to switch between solar energy and battery, and to test the various functions of the controller through the flight experiment of a small solar powered unmanned aerial vehicle. Tests have found that solar powered drones using this controller can navigate for a long time in weather with varying light intensity, and the device operates well, effectively improving the power stability of solar powered drones.
LSTM-based Fault Prediction for Ship Power Systems
Authors: Zhang Yi , Chen Ning , Jiang Yuhang , Adeshara Jatinkumar V 
Published: August 2023

Abstract
A ship power system refers to an isolated grid consisting of power generation, electrical energy conversion, transmission, distribution, and consumption. As the heart of the ship’s route, the ship’s power station should try to avoid malfunction, and the malfunction should be quickly investigated and recovered. In this paper, a stand-alone system of a ship power station is built for simulation using the Simulink software platform, and the fault voltage and current parameters of each phase are selected as the source of the data set and input to the Long Short Term Memory (LSTM) neural network algorithm for training and diagnostic prediction of faults. By comparing the diagnostic results with those of Back Propagation (BP) neural network, the results show that LSTM has an accuracy of 98.334%, which can diagnose the failure modes of ship power stations more accurately and has higher explanatory power for the predicted data.
Research on Evolvable Hardware Based on Improved Evolutionary Strategy
Authors: Zhu Min , Tang Long 
Published: August 2023

Abstract
Evolvable hardware (EHW) attracts a lot of researchers because of its excellent adaptive and self-organizing ability. Various of studies have been carried out to improve the evolutionary efficiency. There are mainly two ways: improving the structure of reconfigurable hardware and optimizing evolutionary algorithms. In this paper, we design the reconfigurable circuit based on the systolic array which could reduce the length of circuit coding. And then, an improved evolutionary strategy is proposed, which refers to the yin-yang pair optimization algorithm (YYPO). It can accelerate the evolutionary process and avoid the stalling effect by balancing the relationship between exploration and development. Some experiments were conducted to verify the effect and the results show that the improved method has better searching ability than the traditional evolutionary strategy.
Stroke Prediction Using the Trust Evaluation with Data Leakage Avoiding
Authors: Ye Xiaoyan , Xu Wenchao , Ye Xiaoying , Long Dan , Yin Qiuyang , Huang Binhua 
Published: August 2023

Abstract
Early detection of the severe disease -- stroke is a key step toward effective treatment. Stroke disease data is imbalanced and normally contains the majority of negative cases (without stroke) and the minority of positive cases (stroke). Previous work has used SMOTE to deal with imbalanced data, but most researchers have implemented it for the entire dataset, which means the “answer” was silently “be told” and saved in the entire data, causing data leakage. Moreover, the previous work uses accuracy only as the metrics make the result less guaranteed. We propose a method using the SMOTE applied to the training set only and apply 13 machine learning classifiers for predicting stroke. We combine the AUC with accuracy as evaluation metrics in the stroke prediction task, which can elevate the confidence level of the assessment of results. The experiment shows that misused SMOTE and standardization can cause data leakage and the combined metrics can evaluate models with higher trustworthiness. We conclude that using our method can avoid data leakage and assess the model with higher trustworthiness.
Control Strategy of Circulating Current Suppression for Modular Multilevel Converter
Authors: Wang Xiaolei , Zheng Quan , Zhong Jianying , Zhang Lixin , Wang Zhijun , Wang Nan , Yan Dengke 
Published: August 2023

Abstract
The structural characteristics of modular multilevel converters (MMC) lead to circulating current problems, which increases the requirements for device capacity and withstand voltage levels. Therefore, this paper proposes a circulating current suppression strategy based on new sliding mode control. This strategy uses a variable approach rate to reduce chattering caused by sliding mode control. Compared with the circulating current suppression strategy using traditional PI control, it enhances the anti-interference of the circulating current suppression strategy. Finally, this paper builds the MATLAB/Simulink simulation model and experimental platform. The results show that the strategy has good anti-interference performance.
Implementation of Control Standardization Based on HCM5000G DC Control and Protection Platform
Authors: Yang Chengfei , Liu Xuhui , Li Fengqi , Li Jun , Feng Xuan , Gu Xianghong 
Published: August 2023

Abstract
This paper introduces the whole construction of the control standardization simulation system based on the HCM5000G DC control and protection platform, which can meet the requirements of engineering design and various control performance indexes by adopting the standardization design of the self-control and localization platform. In this paper, the construction principle of the standardized control system and the optimization strategy of the control structure are discussed in detail, and the engineering simulation model is realized by using the real-time digital simulation system with the layered and distributed standardized interface design, which provides an important reference for the future large-scale application of the control and protection of DC Engineering.
Fault Diagnosis Strategy for Solar Cells Based on Reverse Derivation of I-V Curve
Authors: Sun Min , Zhao Huaxing , Chen Bo , Zeng Wei , Yang Zaineng 
Published: August 2023

Abstract
This paper proposes a fault diagnosis strategy for solar cells based on the reverse derivation of the I-V curve. This strategy does not require real-time monitoring of the surface irradiance and average temperature of the solar cell during operation. It only needs to calculate(establish) the I-V curve library under different irradiance and solar cell temperature in advance, then measure the open circuit voltage and short circuit current of the photovoltaic module during operation. And the measured voltage and current at the maximum power point can determine whether the solar cell is faulty. The possible faults of various solar cells are simulated by setting up experimental equipment, and the method is used for fault diagnosis. Experimental results show that the proposed method can effectively monitor various faults of solar cells. The method improves the accuracy of fault detection of the solar cell, enhances the reliability and economical benefits of the photovoltaic power station, and realizes online fault detection of the solar cell.
An Improved Loss Calculation Method for MMCs
Authors: Song Yonghui , Xiong Xiaofu 
Published: August 2023

Abstract
Accurate loss calculation of power devices in the submodules of the modular multilevel converter (MMC) is significant. The loss calculation of MMC is closely related to its control strategies, such as the nearest level modulation (NLC) method and the capacitor voltage balancing method based on sequencing. The loss distribution characteristics and calculation of power devices are different in different control methods, and the loss distribution characteristics are complex and difficult to calculate. This shorting adversely affects MMC parameter design and reliability analysis. However, the existing methods cannot achieve an accurate calculation of MMC loss. To address the above problems, an improved loss calculation method is presented by detailed analyzing the working principle and the loss distribution of variable submodules (SM). The proposed loss calculation method can accurately calculate the power devices’ loss under various control methods and different topologies. The correctness and effectiveness of the improved loss calculation method are verified through Matlab/Simulink software.