bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of JET runaway electron beams in

D
2

-rich shattered pellet injection mitigation experiments
Authors: Sommariva C. , Pau A. , Silburn S. , Reux C. , Hoppe M. , Buratti P. , Ficker O. , Morales Rennan B. , Fontana M. , Sun H. , Carvalho P. , Sheena M. , Gerasimov S. , Szepesi G. , Boboc A. , Coffey I. , Kiptily V. , Sauter O. , Pautasso G. , Paz-Soldan C. , Decker J. ,   JET Contributors
Published: August 2024

The publication provide further insights into the dynamics of JET runaway electron (RE) beams mitigated by D2-rich shattered pellet injection (SPI) (Reux et al 2022 Plasma Phys. Control. Fusion
64 034002). Multi-diagnostic analyses show that mechanisms causing continuous RE losses and energy transfer from hot electrons to cold background plasma can act before the SPI. After the SPI, measurements are compatible with a reduction of the maximum energy and pitch angle of the RE distribution while the population of supra-thermal electrons increases. The RE population growth is likely due to electron avalanche. Dark island-like pattern chains, characterised by an integer poloidal mode number and a certain minor radius, are identified in the JET RE beam synchrotron radiation videos. The synchrotron island dynamics is studied via a newly developed computer vision code (Sommariva and Silburn https://c4science.ch/source/pSpiPTV/). The radial motion of synchrotron island chains is found to be consistent with the most plausible time evolution of the radial current density profile compatible with both the RE synchrotron videos and the total RE current time trace. Similarly, correlations are identified between the temporal progression of the synchrotron islands poloidal rotation frequency and sudden MHD relaxation events. Loss-of-RE events probably caused by non-linear interactions between synchrotron islands are observed for the first time. Experimental evidences suggest that synchrotron islands are possibly related to the existence of magnetic islands which may lead to the development of new RE beam mitigation strategies.
Modelling of ICRH slow wave propagation and absorption in Wendelstein 7-X stellarator
Authors: Grekov D. , Albert C. , Turkin Yu. , Volkova Yu.
Published: August 2024

The propagation and absorption of the slow waves (SWs) in the three-ion plasma of the Wendelstein 7-X stellarator have been investigated by ray tracing. The aim of the study is to obtain a qualitative notion of the penetration into the plasma and absorption of the wave excited by the potential difference between the antenna conductors and the antenna box. It has been discovered that the rays propagate along the magnetic field lines over a significant distance, up to 6 m, from the antenna. They weakly, to a depth of 0.1 m, penetrate into the plasma. Absorption of the SWs by electrons does not lead to the generation of the currents capable of affecting the plasma equilibrium. Most of the SWs are absorbed beyond the region of ion–ion hybrid resonance in the zone of cyclotron resonance of 3He ions at the periphery of the plasma. The ICRH of the three-ion W 7-X plasma will be used to heat 3He ions to high energies and simulate the confinement of alpha particles in an optimized stellarator configuration. The presence of a source of hot 3He ions, which are poorly confined, at the periphery of the plasma can affect the experimental results.
Markovian description of a wide class of feedback-controlled systems: application to the feedback flashing ratchet
Authors: Ruiz-Pino Natalia , Prados Antonio
Published: August 2024

In feedback-controlled systems, an external agent—the feedback controller—measures the state of the system and modifies its subsequent dynamics depending on the outcome of the measurement. In this paper, we build a Markovian description for the joint stochastic process that comprises both the system and the controller variables. This Markovian description is valid for a wide class of feedback-controlled systems, allowing for the inclusion of errors in the measurement. The general framework is motivated and illustrated with the paradigmatic example of the feedback flashing ratchet.
Robot material processing and hardware-in-the-loop-based real-time simulations
Authors: Ziada Osama A Q , Zhang Yanxi , Algabroun Hatem , Abiri Olufunminiyi , Olaogun Olayinka , Singh Gurtej , Foroushany Ali Hajian , Pocorni Jetro Kenneth
Published: August 2024

This paper presents a cyber-physical production system that consists of a simulation, an industrial robot cell, and sensors. The industrial robot hardware, used for welding and additive manufacturing applications, is connected or “in-the-loop” with a real-time target machine on which simulations are running. These simulations are updated in real-time by the data provided by process sensors. Particular focus is given to wire-arc additive manufacturing (WAAM). Still, the cyber-physical system allows use in other robot-based material processes, such as sheet forming, (dis)assembly and material handling applications. It is also argued that the proposed cyber-physical system can be used so that it competes against the concept of using machine learning to optimize manufacturing processes. The proposed cyber-physical system enables the transition from traditional robot automation to autonomous robot systems.
Carbon-Aramid Fiber/Epoxy Hybrid Composite Laminates with the Presence of Defect: An Experimental Study
Authors: Junaedi H , Sebaey T A
Published: August 2024

Carbon-Aramid fiber-reinforced epoxy has been used extensively in the aerospace and automobile industries. The combination of high-strength carbon fiber and the high toughness of aramid fiber is believed to be beneficial to the structural behavior of composites. In the current study, Aramid fiber was sandwiched between carbon fiber layers to maintain high strength and toughness simultaneously. The behavior of the laminate with the presence of an open hole and single-edge notch was investigated. For justification, the response of the hybrid laminate was compared with two other laminates, one is made totally from carbon fiber-reinforced epoxy (CFRP) and the other is made from aramid fiber-reinforced epoxy (AFRP). The effect of an open hole was assessed by a tension test, while the single-edge notch effect was evaluated by the flexural test. Tensile and flexural tests were also performed on the regular samples. As per the current results, the notch sensitivity of hybrid laminate was found to be less than that of CFRP laminate. The CFRP laminate failure type was dominated by delamination. AFRP composite laminate failure was dominated by fiber breakage and crack propagation through the matrix. The hybrid composite laminates were dominated by fiber breakage of the AFRP laminates and delamination of CFRP outer layers. The flexural modulus of hybrid laminate resulted in the greatest value, followed by CFRP and AFRP. The hybrid laminate’s fracture toughness is significantly higher than that of CFRP but lower than that of AFRP.
Effect of multiple injection optimization on combustion characteristics of low-pressure EGR system engine
Authors: Liu Yiqiang , Meng Yufei , Liu Qiyuan , Zhang Huijun , Chen Cheng , Li Xiaonan
Published: August 2024

In recent years, reducing oil consumption and pollutant discharge in transportation industry has become an important measure to alleviate energy crisis and environmental pollution. Therefore, the fuel economy and emission characteristics of the engine have become an important index to evaluate the quality of an engine, so EGR technology has gradually become the standard of gasoline engines. But EGR is not always good. In order to alleviate the adverse effects of EGR on combustion, further research on engine combustion is needed. In order to study the effect of multiple injection strategy on engine combustion characteristics, this paper takes a high pressure direct injection gasoline engine equipped with low pressure EGR system as the research object, and verifies the designed multiple injection strategy on special test equipment. A large amount of combustion data of the engine under the same load, different fuel injection stages and fuel injection ratios were collected. By comparing the evaluation indexes of main pollutant emission, fuel consumption and combustion stability, it is found that with the increase of injection times, the combustion characteristics and knock of the engine show a trend of improvement. After using multiple injection strategies at 2000r/min, it can be seen that the optimized injection strategy has better emission characteristics and lower fuel consumption lower knock intensity than that before the injection mode optimization without affecting the power performance.
Experimental research on the flow flied of the nacelle and inlet of a civil aircraft with wind-mounted engines at low speed
Authors: Hu Renyu , Zhang Dongyun , Sun Haoran
Published: August 2024

Modern civil transport aircraft with wing-mounted engines are exposed to the upwash induced by the wing, resulting in the local angle of attack at the nacelle leading edge, notably greater than that of aircraft. Large local angles of attack can be combined with different engine airflow conditions, causing adversary aerodynamic phenomena to occur at different locations. Total and static pressures obtained in a wind tunnel test using a full-span aircraft model and simulating required engine airflow with an ejector indicate that during the around with landing configuration, the high suction peak will form on the bottom of the inlet with local air flow being supersonic and could lead to inlet distortion. In contrast, the engine that fails during takeoff climb will have a significant suction peak form on the top of the nacelle and might experience external separation and additional drag. Test results also demonstrate that well-designed nacelles can postpone these adversary phenomena until the aircraft stalls first.
Simulation and optimization of fuze circuit housing structural strength under a high overload environment
Authors: Wu Qi , Yan Lide , Zhang Hang , Hou Lei , Liang Pengfei , Hao Yaoyun , Duan Xiaochang , Xue Yubo , Ding Jinshan
Published: August 2024

With the continuous improvement of modern military equipment protection systems, the demand for ammunition to penetrate hard targets has become increasingly apparent. The projectile is subjected to a high overload environment during launching and penetrating hard targets. Fuze as the detonation control system of the projectile, is prone to significant deformation or even damage to its circuit housing structure in a high overload environment. The dynamic response of fuze circuit housing under high overload conditions is analyzed, and the housing structure is further optimized according to the simulation results to ensure that the fuze circuit housing can meet the strength requirements under a high overload environment.
Prediction of packing performance of pneumatic control valve based on stem mechanism model and VMD-SSA-LSTM
Authors: Shi Limiao , Yang Bin , Wang Yujin , Wang Xinze
Published: August 2024

Packing performance is one of the most important parts affecting the control operation of pneumatic control valves. In order to avoid the failure caused by packing wear and aging of pneumatic control valves after long-term use, this paper constructs a valve stem mechanism model and combines the advantage of deep learning to predict the packing performance of pneumatic control valves based on Long Short-term Memory (LSTM) and Variable Mode Decomposition (VMD) and Sparrow Search Algorithm (SSA). Firstly, the historical data of the actuator is calculated based on the mechanism model of the valve stem. The time-friction force obtained by the calculation is the parameter set. After the parameter set is subject to the variational mode decomposition, the parameter set is imported into the SSA-LSTM prediction model for prediction, and the prediction data is obtained.
Centerline measurement of rotary kilns based on the free station method
Authors: Niu Yuhan , Wu Jingbing , Zhang Yun
Published: August 2024

The rotary kiln is an important production equipment in the building materials and metallurgy industry, and its operating conditions, safety, and efficiency largely determine the economic benefits of its users and the safety of workers on site. At present, the testing methods for each rotary kiln part are relatively mature and can be used to realize accurate measurements in a dynamic environment. However, the main means of measurement is limited by the site conditions, and the actual detection speed is slow; the preparation work is cumbersome and will be subject to the measurement of the site obstacles and other environmental factors constraints. In this paper, we propose and design an optimized rotary kiln centerline measurement method using the free station method and verify its feasibility with respect to the optimization of the centerline offset, which is an important measurement item in rotary kiln measurement.
Bushing fault diagnosis based on SVM and the improved sparrow search algorithm
Authors: Li Shengrong , Wang Yefan , He Zixi
Published: August 2024

In order to address the issue of low precision in traditional bushing fault diagnosis, a bushing fault diagnosis method based on an improved sparrow search algorithm (ISSA) and support vector machine (SVM) is proposed in this paper. Firstly, the bushing vibration signals are extracted by wavelet packet, and the feature vectors are used as inputs for the SVM. In view of the impact of support vector machine parameters on the model, a sparrow search algorithm is proposed for intelligent optimization. To prevent reaching a local optimum, adaptive inertia weight is added based on the original approach. The final bushing fault diagnosis model is established by training. Comparison experiments with three fault diagnosis models, SSA-SVM, PSO-SVM, and SVM, found that the proposed method achieves complete diagnosis in a shorter time, and the diagnostic accuracy rate is 96.5%, which verifies the feasibility and effectiveness of the model.
Estimation of ultrasonic flight time based on SHADE algorithm and extended kalman filtering
Authors: Mao Peng , Xiong Jinglin , Li Xisheng
Published: August 2024

Traditional methods of using ultrasound to measure oxygen concentration have the issue of inaccuracy and susceptibility to noise interference when measuring the time of flight (TOF) of ultrasonic echo signals. A proposed algorithm for ultrasonic parameter estimation, utilizing an asymmetric Gaussian model, aims to enhance the precision and reliability of TOF estimation, aiming to reduce the influence of noise interference. The algorithm combines an improved Self-Adaptive Differential Evolution (SHADE) algorithm based on successful historical records with an Extended Kalman Filter (EKF). The improved SHADE algorithm controls the degree of mutation strategy greediness during the mutation operation based on the number of iterations, thereby enhancing the algorithm’s iteration speed. Then, the obtained solution is used as the initial value for the EKF to estimate the model parameters, thus addressing the issue of EKF’s dependency on accurate initial values to obtain precise outputs. Through simulation and experimental measurements of ultrasonic oxygen concentration, several commonly used parameter estimation algorithms are compared with the proposed SHADE-EKF algorithm. Results demonstrate that the SHADE-EKF algorithm exhibits superior performance in estimating the TOF of ultrasonic waves.
Consistency and repeatability verification for vehicle in the loop test platform based on digital twin of proving ground
Authors: Huang Zhichen , Liu Qiangsheng , Chen Liang , Ke Yingjie , Huang Xiongdong , Zhang Xinghui
Published: August 2024

A high-confidence vehicle-in-the-loop test method based on the digital twin of proving ground (DTPG-VIL) is proposed for the test of autonomous driving vehicles. The overall architectural design of the DTPG-VIL and the corresponding components are introduced, with a focus on describing the scene simulation system based on the digital twin of the proving ground. A King Long intelligent driving sightseeing bus for test verification is introduced, and its positioning performance is verified by the high-definition positioning base station and GPS/INS combined navigation system to verify the accuracy of its positioning precision and meet the requirements of the digital twin test so that the DTPG-VIL can obtain more information from the bus. Taking the automatic emergency avoidance function as an example, the method, process, and experimental results of the control test between the DTPG-VIL test and the real vehicle test in a proving ground are designed. Through the correlation coefficient analysis and transient response analysis, consistency and repeatability comparisons are carried out to verify the high confidence of the digital twin test.
Dynamic time warping based instantaneous frequency estimation for rotating machineries under non-stationary operating conditions
Authors: Tao Xiyue
Published: August 2024

For tacho-less order tracking, it is crucial to achieve an accurate estimation of instantaneous phase and frequency under non-stationary conditions for fault diagnosis of mechanical systems. Therefore, an instantaneous frequency estimation method based on dynamic time warping for rotating machinery was proposed. Firstly, a mono-component signal is obtained by variational mode decomposition of multi-harmonic vibration signal generated in practical engineering. Then, a stationary reference signal is constructed by the mean frequency of the vibration signal, which is obtained by the signal spectrum. Aligning the vibration signal with the reference signal to obtain the rough phase estimation and warping path. Finally, a polynomial model is constructed to calculate the analytic expression of the smooth warping path to obtain the instantaneous frequency result. The simulation and experiment present that the dynamic time warping-based method can estimate the instantaneous frequency of the signal under non-stationary conditions. Compared with the classical Hilbert transform method, the proposed dynamic time-warping algorithm has stronger noise resistance.
Localization and detection of underwater acoustic communication signals using convolutional recursive neural networks
Authors: Ouyang Junjie , Zhang Leilei , Zhang Youwen
Published: August 2024

This paper employs a multi-task neural network (UWAELD) to simultaneously perform the Underwater Acoustic Communication Event Detection (UACED) and direction-of-arrival (DOA) mission. Typically, the UACED and DOA tasks are executed separately, as the UACED task is identified through time-frequency analysis, while the DOA task is identified through the amplitude and phase differences of the signal, making it very difficult to jointly perform both tasks. To overcome this, we utilize a logarithmic spectrogram for time-frequency analysis and stack the normalized eigenvectors obtained by processing the signal covariance matrix. We ultimately evaluate the network’s feasibility using simulation data and lake test data, utilizing acoustical signals measured in actual experiments. Finally, for the UADCED task, the error rate is only 6%, with an F1 score of 0.83; for the DOA task, the localization error is only 1.72°, with a localization recall score of 0.87. Additionally, for the DOA task, we employ the classical MUSIC algorithm to demonstrate the network’s superiority.
Ship accident re-enactment based on AIS data and virtual reality: a case study of “Xiang Xiang Yin Huo 0410” ship accident
Authors: Zhang Shuntao , Zhou Shibo , Shao Jinxing , Ren Luzhen
Published: August 2024

The recurrence of ship accidents was an effective method of maritime investigation. To analyze the cause of the sinking of “Xiang Xiang Yin Huo 0410”, a vessel accident recurrence simulation system was constructed by integrating an automatic identification system and virtual reality technology to replicate the navigation and accident process of the accident vessel. The voyaging process of the accident vessel was reduplicated in the simulation system according to the AIS information, such as speed, course, and turning speed. The mathematical model of accident vessel maneuvering was established by using MMG to reproduce the ship maneuvering scheme based on the maneuvering data before the accident obtained through on-the-spot investigation. The navigation and sinking process of the accident vessel were reproduced visually, and the cause of the accident was judged and analyzed intuitively by constructing a three-dimensional model of the accident vessel and a mathematical model of ocean waves. The actual application indicates that the ship’s navigation and accident process under external force, combined with the ship’s maneuvering data, automatic identification data, and hydrometeorological data, was consistent with the actual accident process of the accident. The method proposed in this paper provided a new idea for the investigation and analysis of maritime accidents.
Research on digital twin architecture of ship maneuverability simulation for system model
Authors: Yang Yunfan , Liu Xu , Yin Wenhui , Guo Yu , Bao Jiawei
Published: August 2024

With the development of civil and military requirements, ship maneuverability simulation systems tend to be complicated, and the traditional simulation methods are difficult to meet in terms of the development needs of digitalization. The joint simulation technology based on the FMI standard can realize the digital twin of complex system models, which can solve the difficult problem of multidisciplinary and multi-sub-system integration simulation. This paper analyzes the current domestic and foreign research content on joint simulation technology, digital twin technology, and complex system modeling, takes a typical Z-type maneuverability test as an example, establishes a multidisciplinary and cross-platform subsystem model, and designs and develops a ship maneuverability joint simulation algorithm and system software for the complex system model. The simulation results verify the effectiveness of the system modeling technique and the joint simulation technique based on FMI. Based on this system, the whole framework of the ship maneuverability simulation system, which is based on digital twins, is designed. According to the development requirements of ship maneuverability simulation, the main design framework, key technology, and implementation approach of this research method are given, which provides basic methods and ideas for the digital research of ship maneuverability simulation.
Haze generation and feature fusion network aiming at real-world single image dehazing
Authors: Pan Hao , Tang Huanle
Published: August 2024

Because most dehazing methods use synthesized haze images for training, they may perform well on synthesized datasets. However, when these methods are applied to real-world scenes, their performance may significantly decrease due to domain shift. Therefore, we propose a dehazing network for real-world hazy scenes. This network includes a haze generation network that can utilize the hazy information of real haze images to generate images that are closer to real hazy scenes, generating training pairs to address the domain shift problem. The network also includes a dehazing network that integrates feature fusion attention mechanisms, which can achieve better dehazing performance.
Research on thermal runaway early warning algorithm of lithium battery based on improved particle swarm algorithm optimized BP neural network
Authors: Yan Peng , Li Shaopeng , Wang Xiao , Cao Zhenkun
Published: August 2024

In response to the issues of false alarms and missed alarms in traditional fire alarm systems for energy storage station fire prevention and control, this study proposes a fire alarm approach employing improved PSO-BP neural networks. Firstly, we set adaptive inertial weights and asymmetric learning factors on the PSO algorithm that are automatically optimized as fitness changes to improve the optimization accuracy and convergence speed of the algorithm. Secondly, the thresholds or weights are mapped to random particles for training to obtain the optimal value. Finally, utilizing the Pyrosim software, a model of the battery cabinet was established, and the thermal runaway data samples were input into the neural network model for training. The test consequence indicates that the improved PSO-BP model achieved a 5% and 3.75% rise in precision relative to the neural network and PSO-BP model, respectively, while the frequency of iterations declined by 55% relative to the PSO-BP.
Active disturbance rejection control of a bearingless permanent magnet slice motor
Authors: Jiang Dikai , Meng Shuping , Xu Wenbo , Wei Zeyu , Li Chao , Wang Helong , Huang Shuxian
Published: August 2024

Bearingless permanent magnet slice motor has the advantages of easy stator-rotor isolation, no contact, simple structure, and high integration, which is a significant feature in the ultra-pure field of biology, chemistry, medical treatment, semiconductor manufacturing, aerospace, and other applications, as well as high-speed drive field. To realize the control of a bearingless permanent magnet slice motor, the mechanism of torque control, as well as suspension control, is systematically analyzed. On this basis, a simplified control parameter design method for decoupling torque and suspension is proposed, and the parameter tuning rules are given. For the problem of insufficient anti-disturbance performance of the suspension control under the traditional linear active disturbances rejection controller (LADRC), an improved LADRC strategy based on known disturbances is proposed, and an expansion state observer (ESO) with partially known disturbances is designed. The suspension accuracy and robustness of the system are verified by simulating the motor control with a Matlab/Simulink module. Finally, the improved LADRC control is used in a BPMSM prototype. The simulation and experimental results show that the improved LADRC control with the addition of known perturbations effectively improves the suspension control stability and accuracy compared to the traditional LADRC control.
Welding defect detection based on YOLOv8
Authors: Zhou Jianhang , Zhang Wang , Sui Xuejun , Chen Yuandong
Published: August 2024

In this paper, we propose an improvement scheme for the unclear boundary capture issues of the YOLOv8 algorithm in weld defect detection. We replace the Conv module with the CG black module in Backbone to enhance the algorithm’s ability to extract image features so as to capture weld defects more accurately. Meanwhile, the CBAM attention mechanism is introduced in the tail of the Backbone to improve the model’s capability to learn the correlation of different regions of the image and improve the generalization performance. The experimental findings substantiate that the enhanced algorithm exhibits superior accuracy in comparison to the original algorithm, recall rate, Map@0.5, and other indicators of the improved algorithm. The enhanced algorithm demonstrates a 3.6% increase in accuracy when contrasted with the original algorithm.
Enhancing safety in undersea exploration: a novel rescue strategy using genetic simulated annealing
Authors: Wu Yi , Tang Rui , Yan Boqiang
Published: August 2024

The increasing interest in undersea exploration necessitates the development of advanced safety and rescue strategies. This paper introduces a novel rescue strategy for manned submersible expeditions, emphasizing the use of a genetically simulated annealing algorithm to optimize rescue operations. By integrating this algorithm with multi-unit cooperative rescue tactics and optimal search path modeling, we propose a comprehensive approach to improve the efficiency and effectiveness of rescue operations. Our simulations in a maritime area of 10, 000 m × 10, 000 m demonstrate the algorithm’s ability to efficiently coordinate the rescue of multiple distressed submersibles, ensuring a rapid and strategic response to emergencies.
Spatio-temporal action detector with cross-stream knowledge transfer
Authors: Yang Xianyu
Published: August 2024

Relying on human labor for uninterrupted monitoring through surveillance systems is highly inefficient and prone to oversight, making intelligent surveillance have great application prospects and value. To implement this technology, spatio-temporal action detectors are typically used, which are neural networks capable of locating action instances simultaneously in both time and space dimensions. To address the issue of high computational demand commonly associated with 3D backbone architectures, we propose a Dynamic Cross-Stream MovingCenter Detector (DCMOC) based on a 2D backbone network, an improved version of the MOC detector. In the DCMOC detector, the movement branch and the bounding box branch correspond to the motion and appearance features of action instances, respectively. Through a designed cross-stream knowledge transfer module, feature knowledge is transferred between the two branches to enhance feature representation. To compare with existing spatio-temporal action detectors, experiments were conducted on two datasets, JHMDB and UCF101-24. The experiments demonstrate that the DCMOC detector achieves competitive performance with significantly lower computational requirements than existing 3D architecture models and achieves optimal performance on the video-map metric at high thresholds.
Design of multi-component gas measurement system based on STM32
Authors: Qi Xinyi , Zhang Shiqian , Yang Yanchao
Published: August 2024

To detect the concentration of toxic and harmful gases in the environment in a timely and effective manner, this article designs a multi-component gas measurement system based on the STM32 processor, which can effectively detect three toxic and harmful gases (CO, NO2, and SO2), a gas detection terminal for the concentration of two greenhouse gases (CO2 and CH4) and an inhalable particulate matter (PM2.5), and a handheld display terminal that can display the measured gas concentration in real-time. A practical application circuit for electrochemical sensors has been designed, simplifying the design of driving amplification circuits. Finally, the feasibility of the system was verified through automobile exhaust experiments.
Design and implementation of intelligent control system for non-evaporable getter pumps
Authors: Wang Chao , Yu Yaowei , Sun Hao , Cao Bin , Pan Hao , Fan Bin , Zuo Guizhong , Hu Jiansheng
Published: August 2024

An intelligent control system for Non-Evaporable Getter (NEG) pumps was designed and developed. The main functions of the system include remote monitoring and remote control of key parameters of the NEG power supply, intelligent control of NEG working status according to NEG saturation status and vacuum chamber status, especially intelligent warning and protection of NEG from vacuum leaks and NEG supersaturation. The intelligent control system is proven stable and reliable, which provides a feasible logic architecture and control design for NEG pump application in future fusion devices.
Sound source localization based on data and neural network model
Authors: Xu Junjie , Li Binbin , Zhao Yang , Xue Shijie
Published: August 2024

In this study, the integration of sound source localization with neural network techniques is proposed. Firstly, the development history and basic principle of neural networks are introduced. Combined with the characteristics of sound source location, the residual neural network is analyzed, and the residual neural network is used as the neural network model. The sound signal received by the microphone array is computed by PHAT-SCOT and the output is trained as the input feature of ResNet. Finally, the results of indoor sound source location are obtained in the test set. Experimental findings demonstrate that the neural network-based localization algorithm exhibits robust localization accuracy across diverse environmental conditions.
A lightweight particle detection algorithm based on an improved YOLOv8
Authors: Wang Bowen , Liu Pan , Tian Hui , Ren Hongjun , Cao Yangjie , Li Shijiao , Qi Guochen , Zhu Mingfu , Wei Ronghan
Published: August 2024

A method for lightweight grain detection under transmission electron microscopy is proposed to address the issues of inadequate detection accuracy, slow speed, and high resource consumption, utilizing an improved YOLOv8. The approach involves substituting YOLOv8’s backbone structure with Mobilenetv3small, reducing model complexity while maintaining accuracy. Additionally, GsConv modules are applied to the feature enhancement network to optimize grain recognition and positioning. Experimental results show that the accuracy of the enhanced YOLOv8 reaches 97.4%, with a 66% reduction in parameters and a 70.7% decrease in computational demand, fulfilling the requirements for a lightweight experimental deployment.
A novel diamond-like carbon based photocathode for PICOSEC Micromegas detectors
Authors: Wang X. , Aleksan R. , Angelis Y. , Bortfeldt J. , Brunbauer F. , Brunoldi M. , Chatzianagnostou E. , Datta J. , Dehmelt K. , Fanourakis G. , Fiorina D. , Floethner K.J. , Gallinaro M. , Garcia F. , Giomataris I. , Gnanvo K. , Iguaz F.J. , Janssens D. , Kallitsopoulou A. , Kovacic M. , Kross B. , Legou P. , Lisowska M. , Liu J. , Maniatis I. , McKisson J. , Meng Y. , Muller H. , Oliveri E. , Orlandini G. , Pandey A. , Papaevangelou T. , Pomorski M. , Ropelewski L. , Sampsonidis D. , Scharenberg L. , Schneider T. , Shang L. , Shao M. , Sohl L. , van Stenis M. , Tsipolitis Y. , Tzamarias S.E. , Utrobicic A. , Vai I. , Veenhof R. , Vitulo P. , White S. , Xi W. , Zhang Z. , Zhou Y.
Published: August 2024

The PICOSEC Micromegas (MM) detector is a precise timing
gaseous detector based on a MM detector operating in a two-stage
amplification mode and a Cherenkov radiator. Prototypes equipped
with cesium iodide (CsI) photocathodes have shown promising time
resolutions as precise as 24 picoseconds (ps) for Minimum Ionizing
Particles. However, due to the high hygroscopicity and
susceptibility to ion bombardment of the CsI photocathodes,
alternative photocathode materials are needed to improve the
robustness of PICOSEC MM. Diamond-like Carbon (DLC) film have been
introduced as a novel robust photocathode material, which have shown
promising results. A batch of DLC photocathodes with different
thicknesses were produced and evaluated using ultraviolet light. The
quantum efficiency measurements indicate that the optimized
thickness of the DLC photocathode is approximately
3 nm. Furthermore, DLC photocathodes show good resistance to ion
bombardment in aging test compared to the CsI photocathode. Finally,
a PICOSEC MM prototype equipped with DLC photocathodes was tested in
muon beams. A time resolution of around 42 ps with a detection
efficiency of 97% for 150 GeV/c muons were obtained. These results
indicate the great potential of DLC as a photocathode for the
PICOSEC MM detector.
Performance of a coarsely pixelated LAPPD photosensor for the SoLID gas Cherenkov detectors
Authors: Xie J. , Peng C. , Joosten S. , Meziani Z.-E. , Camsonne A. , Jones M. , Malace S. , Kaczanowicz E. , Rehfuss M. , Sparveris N. , Paolone M. , Foley M. , Minot M. , Popecki M. , Zhao Z.W.
Published: August 2024

The SoLID spectrometer's gas Cherenkov counters require
photosensors that operate in a high luminosity and high background
environment. The reference design features arrays of 9 or 16 tiled
multi-anode photomultipliers (MaPMTs), distributed across 32
sectors, to serve the light-gas and heavy-gas Cherenkov counters,
respectively. To assess the viability of a pixelated INCOM Large
Area Picosecond Photodetector (LAPPDTM) as an alternative
photosensor to replace MaPMT arrays in either detector, we evaluated
its performance under realistic SoLID running conditions in Hall C
at the Thomas Jefferson National Accelerator Facility (Jefferson
Lab). The results of this test confirmed that the coarse-pixelated
(2.5 × 2.5 cm2 pixel size) LAPPD is capable of handling
the total projected signal and background rates of the three pillar
SoLID experiments. The tested photosensor detected Cherenkov signals
with the capability of separating single-electron events from pair
production events while rejecting background. Although the design
was not aimed at ring-imaging Cherenkov detectors, Cherenkov disk
images were captured in two different gas radiators. Through a
direct comparison with a GEANT4 simulation, we confirmed the
experimental performance of the LAPPD.
Quantitative analysis of the high speed and high precision waveform digital system for Jinping Neutrino Experiment
Authors: Yang Haoyan , Xue Tao , Jiang Lin , Pan Qiutong , Liang Bo , Liu Yinong , Li Jianmin
Published: August 2024

The Jinping Neutrino Experiment (JNE) aims to construct a
500-ton liquid scintillator detector for detecting and studying
neutrinos. In JNE data analysis, particle energy and position
reconstruction are crucial, with result accuracy closely related to
the performance of the waveform digitization system. This study
developed a quantitative model to explore correlations between
sampling characteristics (effective number of bits and sampling
rate) and detector system performance (single photoelectron charge
spectrum resolution and transfer time spread). Additionally, three
ADCs (Tsinghua ADC13B1G, ADI AD9695, TI ADS54J60) and MCP-PMTs were
utilized to validate the model accuracy. The experimental results
for the system charge spectrum resolution are in alignment with the
theoretical predictions. When the ENOB of the ADC exceeds 10.66-bit
and the sampling rate exceeds 1 GSPS, the system charge spectrum
resolution is better than 45%, approaching the PMT inherent
resolution of 44%. The transfer time spread within the system
demonstrates minimal impact from the ADC sampling characteristics.
These results serve as a reference for upgrading the JNE 60-channel
and 4000-channel readout electronic systems. Additionally, this
study can assist developers in maximizing the performance of physics
experiment readout electronics systems within constrained budgets.
Lactoferrin/CD133 antibody conjugated nanostructured lipid carriers for dual targeting of blood–brain-barrier and glioblastoma stem cells
Authors: Zhao Changhong , Zhu Xinshu , Yang Huili , Tan Jianmei , Gong Ruohan , Mei Chao , Cai Xiang , Su Zhenhong , Kong Fei
Published: August 2024

The main reasons for the difficulty in curing and high recurrence rate of glioblastoma multiforme (GBM) include: 1. The difficulty of chemotherapy drugs in penetrating the blood–brain barrier (BBB) to target tumor cells; 2. The presence of glioma stem cells (GSCs) leading to chemotherapy resistance. Therefore, breaking through the limitations of the BBB and overcoming the drug resistance caused by GSCs are the main strategies to address this problem. This study presents our results on the development of lactoferrin (Lf)/CD133 antibody conjugated nanostructured lipid carriers (Lf/CD133-NLCS) for simultaneously targeting BBB and GSCs. Temozolomide (TMZ) loaded Lf/CD133-NLCS (Lf/CD133-NLCS-TMZ) exhibited high-efficiency in vitro anti-tumor effects toward malignant glioma cells (U87-MG) and GSCs, while demonstrating no significant toxicity to normal cells at concentrations lower than 200 μg ml−1. The results of the in vitro targeting GBM study revealed a notably higher cellular uptake of Lf/CD133-NLCS-TMZ in U87-MG cells and GSCs in comparison to Lf/CD133 unconjugated counterpart (NLCS-TMZ). In addition, increased BBB permeability were confirmed for Lf/CD133-NLCS-TMZ compared to NLCS-TMZ both in vitro and in vivo. Taking together, Lf/CD133-NLCS-TMZ show great potential for dual targeting of BBB and GSCs, as well as GBM therapy based on this strategy.
Community effects associated with sunflower oil production: systematic review
Authors: Wahyuni A S
Published: August 2024

This systematic review explores the multifaceted landscape of community issues in the context of sunflower oil production. As a crucial component of the agro-industrial sector, sunflower oil production significantly contributes to global edible oil supplies. However, the socio-economic dynamics within communities engaged in this industry are complex and warrant a comprehensive examination. The study synthesises existing literature to identify community issues around sunflower oil production by following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. This study extracted 68 articles from the Scopus database relating the diverse impacts of sunflower oil production on communities. It resulted in 10 articles to analyse, focusing on health and socio-economic dynamics. A review of 10 relevant articles revealed that most of the reviewed studies indicate positive effects in terms of health outcomes. Especially in resource-constrained settings, sunflower oil distribution contributes to improved infant care. However, a notable exception exists in a Mexican case where toxic substances were found in the breast milk of mothers consuming sunflower oil, emphasising the importance of safety regulations in production. On the socio-economic front, limited research exists, with only two articles addressing this aspect. Nevertheless, these studies highlight the potential for job creation and positive environmental outcomes associated with sunflower oil production.
Market position of rapeseed products from the prime producing countries in the global market
Authors: Vieri A Y , Nurrochmat D R , Assen B W , Rosella E , Ekayani M , Purwawangsa H , Satria A
Published: August 2024

Rapeseed is one of the most widely traded products in the world, with a total trade amounting to USD 14.1 billion. Rapeseed trade represents 0.067% of global trade. The largest Rapeseed exporters in 2021 were Canada (USD 5.17 billion), Australia (USD 2.20 billion), Ukraine (USD 1.37 billion), France (USD 1.01 billion), the Netherlands (USD 841 million), and Romania (USD 618 million). Rapeseed is commonly used in food products, health, cosmetics, and other industries. As international market demands and local needs drive rapeseed production, this research aims to identify opportunities for developing the Rapeseed industry and its derivatives based on local needs and global market trends in the world’s largest rapeseed-producing country. This study evaluated the market positioning of Rapeseed products in the international market and employed a “relative market share-market growth” matrix developed by Boston Consulting Group (BCG) for analysis. This study used secondary data from export data for rapeseed-exporting countries worldwide from 2020 to 2021 and was also enriched with some primary data collected from the site visits in 2023. The BCG matrix indicates the five largest rapeseed exporters globally, and additional countries visited in the study include Canada, Germany, the Netherlands, and Romania. The analysis using the BCG matrix assesses the performance of rapeseed products in various major exporting countries worldwide. This study indicates that Canada has significant potential for developing the Rapeseed industry and its derivatives based on global market trends
Simulating jurisdictional approach and scenario for sustainable palm oil using value chain dynamic model
Authors: Kusumadewi S D , Purnomo H , Okarda B , Azzahra M , Iswadi A M , Puspitaloka D , Nadhira S , Irawan P , Liswanti N
Published: August 2024

In Indonesia, the jurisdictional approach is one of a key strategy for enhancing sustainability for agricultural export commodity production such as palm oil. However, the implementation still faces some challenges, including monitoring and accountability. This research aims to develop a value chain dynamic model called JAPOS (Jurisdictional Approach Modelling for Palm Oil Sustainability) that can simulate the impact of scenario and intervention, including policy, on the various indicators of sustainability at the jurisdiction level such as palm oil production, Greenhouse Gases (GHGs) emissions, deforestation, and revenue from palm oil trade. We applied the model to simulate the results of multistakeholder processes at Sintang District, Indonesia, for the Sustainable Palm Oil Regional Action Plan (RAD KSB). The simulation shows that implementing the No Deforestation, No Peat, and No Exploitation (NDPE) policy will significantly impact (89%) the GHGs emissions reduction from the oil palm sector after ten years of implementation. However, it will cause around 24% production loss and an 18% loss in the revenue from the palm oil trade in Sintang District. Our model suggested that if NDPE is implemented along with intensification and premium price incentives, it will still significantly impact GHGs emission reduction and recover palm oil production and economic loss. This study shows the usefulness of the value chain dynamic model for policy scenario development in supporting the implementation of the jurisdictional approach.
Comparing CPO export duty in several periods in specific calculation policy
Authors: Nur’aeni S , Rifin A , Feryanto
Published: August 2024

Crude Palm Oil (CPO) mainly contributes to Indonesia’s export duty receipts. However, high CPO exports have led to a need for more availability in the domestic market, impacting price increases. Therefore, the government implemented the CPO export duty policy several times, restructuring the export duty and currently uses ad nature or specific calculations (absolute value tariffs). This study compares CPO export duty in several periods based on the reference price range and CPO export duty rate. The data used are secondary time series data from July 2015 to December 2023 which were analyzed using qualitative methods through policy document analysis. The analysis results show that as far as the specific export duty calculation is calculated, the government restructures the export duty with changes in the export duty rate and CPO reference price range. The comparison of export duty rates in the three periods shows that export duty rates are in line with the increase in CPO prices in the international market. The highest export duty rate is in period III.
Market competitiveness of sunflower seed and oil products
Authors: Nurrochmat NA , Indrawati I , Adzkia U , Ekayani M
Published: August 2024

Sunflower seed is one of the most widely traded products in the world, with total trade amounting to 20.36 million metric tons of total vegetable oil production in 2023. Sunflower seed is usually used as a material for cooking oil and food products, biofuel, cosmetics, and other derivates. Due to climate change and the fossil fuel energy crisis in Europe, the need for vegetable oil has increased; one is sunflower oil. Therefore, this research aims to identify the global sunflower market from its largest producing countries. This study uses primer data from interviews in some of the largest producer countries: the Netherlands, Romania, and Poland. Secondary data was also obtained from export data for sunflower-exporting countries worldwide from 2020 to 2021. The Boston Consulting Group (BCG) matrix is used for the data analysis to assess the performance of sunflower products in various major exporting countries worldwide. The results of this study show that Romania took the star position with the highest sunflower seed export, around 19.8% of the total economic value of 4.74 billion USD. Ukraine took the cash cow position in sunflower oil, and Turkiye took the cash cow position in the refined sunflower oil market. These positions indicate the dominance of the global market.