bluuebunny/crossref_metadata_2025_split huggingface dataset:
Robust optimization of a radiotherapy pretreatment preparation workflow
Authors: Hoffmans-Holtzer Nienke , Smolenaers Luuk , Olofsen-van Acht Manouk , Hoogeman Mischa , Balvert Marleen , Petit Steven 
Published: August 2023

Abstract

Objective. Increasing cancer incidence, staff shortage and high burnout rate among radiation oncologists, medical physicists and radiation technicians are putting many departments under strain. Operations research (OR) tools could optimize radiotherapy processes, however, clinical implementation of OR-tools in radiotherapy is scarce since most investigated optimization methods lack robustness against patient-to-patient variation in duration of tasks. By combining OR-tools, a method was developed that optimized deployment of radiotherapy resources by generating robust pretreatment preparation schedules that balance the expected average patient preparation time (F
mean) with the risk of working overtime (RoO). The method was evaluated for various settings of an one-stop shop (OSS) outpatient clinic for palliative radiotherapy. Approach. The OSS at our institute sees, scans and treats 3–5 patients within one day. The OSS pretreatment preparation workflow consists of a fixed sequence of tasks, which was manually optimized for radiation oncologist and CT availability. To find more optimal sequences, with shorter F
mean and lower RoO, a genetic algorithm was developed which regards these sequences as DNA-strands. The genetic algorithm applied natural selection principles to produce new sequences. A decoder translated sequences to schedules to find the conflicting fitness parameters F
mean and RoO. For every generation, fitness of sequences was determined by the distance to the estimated Pareto front of F
mean and RoO. Experiments were run in various OSS-settings. Main results. According to our approach, the expected F
mean of the current clinical schedule could be reduced with 37%, without increasing RoO. Additional experiments provided insights in trade-offs between F
mean, RoO, working shift length, number of patients treated on a single day and staff composition. Significance. Our approach demonstrated that OR-tools could optimize radiotherapy resources by robust pretreatment workflow scheduling. The results strongly support further exploration of scheduling optimization for treatment preparation also outside a one-stop shop or radiotherapy setting.
Patient specific quality assurance in SBRT: a systematic review of measurement-based methods
Authors: Malatesta Tiziana , Scaggion Alessandro , Giglioli Francesca Romana , Belmonte Gina , Casale Michelina , Colleoni Paolo , Falco Maria Daniela , Giuliano Alessia , Linsalata Stefania , Marino Carmelo , Moretti Eugenia , Richetto Veronica , Sardo Anna , Russo Serenella , Mancosu Pietro 
Published: August 2023

Abstract
This topical review focuses on Patient-Specific Quality Assurance (PSQA) approaches to stereotactic body radiation therapy (SBRT). SBRT requires stricter accuracy than standard radiation therapy due to the high dose per fraction and the limited number of fractions. The review considered various PSQA methods reported in 36 articles between 01/2010 and 07/2022 for SBRT treatment. In particular comparison among devices and devices designed for SBRT, sensitivity and resolution, verification methodology, gamma analysis were specifically considered. The review identified a list of essential data needed to reproduce the results in other clinics, highlighted the partial miss of data reported in scientific papers, and formulated recommendations for successful implementation of a PSQA protocol.
A wireless physiological parameter monitoring system with a treatment feedback function during neonatal phototherapy
Authors: He Ziliang , Zhang Benjin , Zhang Jing , Xiao Zhenghua , He Ling , Yang Gang 
Published: August 2023

Abstract

Objective. Neonatal jaundice is a common condition in the early stages of newborns, and phototherapy is a fast, safe and effective method that is used to treat it. However, recent studies have shown that phototherapy may elicit side effects in infants, such as hypothermia, hyperthermia and dehydration. To improve the quality of phototherapy and the prognosis of patients, the changes in neonatal physiological parameters during phototherapy should be monitored to give better feedback to pediatricians or the phototherapy system. However, the current standard of clinical care during neonatal phototherapy with hard-wired devices limits this realization. Approach. Here, we developed a prototype of a neonatal wearable device, which can wirelessly potentially monitor the jaundice value, transepidermal water loss, skin wettedness factor and body orientation during phototherapy, and conducted prototype validation experiments. We also set up user-friendly interfaces and an analysis system on custom software, all designed to make the future addition of data interfaces for treatment feedback functions easier. Main results. The preliminary in vitro experiment demonstrated the effectiveness of simultaneous monitoring of the required physiological parameters. And further suggestions and specific operations are discussed in terms of optimization of the treatment of neonatal jaundice. Significance. It is believed that the established system has the potential to provide a basis for future phototherapy nursing guidelines and physiological monitoring standards.
Metamaterial-based acoustic enhanced sensing for gearbox weak fault feature diagnosis
Authors: Pan Huafei , Ding Xiaoxi , Qiao Hui , Huang Wenbin , Xiao Jiawei , Zhang Ying 
Published: August 2023

Abstract
In gear fault diagnosis of practical engineering, the gear fault signal is affected by external strong noise interference, the multipath superposition and interface loss of the internal fault excitation transmission, which leads to weak feature of incipient fault signals, making the gear fault diagnosis difficult. Inspired by the acoustic manipulation capabilities of acoustic metamaterials, this study proposes a method for weak gear fault feature diagnosis via gradient acoustic metamaterial (GAM), which utilises the acoustic rainbow capture and compression ability to reduce the difficulty of gear incipient fault diagnosis. According to the gear frequency modulation/amplitude modulation modulation principle, enhancement of fault feature frequencies can be achieved by collecting gear acoustic signals from the selected air gaps in GAM structure. In this study, the feasibility of GAM-based gear weak fault feature diagnosis is proved by experiments, which verify the multiscale feature denoising and frequency selective enhancement characteristics of GAM. The results show that the amplitude of the target signal is amplified more than eight times, the sideband component containing the fault signal is enhanced obviously, and the effect of denoising outside the target sideband is evident, making the fault feature can be easily identified from the weak fault signal after demodulation. By comparing with digital filtering in traditional signal processing, this method is more straightforward in extracting weak gear fault features. Additionally, this method adopts non-contact measurement method with micro-electroMechanical system (MEMS) microphone, which has advantages over acceleration sensors in overcoming the space limitation. All in all, the proposed method is effective and facilitates the identification of weak gear faults.
A self-loading suction cup driven by a resonant dielectric elastomer actuator
Authors: Wu Chuang , Cai Anjiang , Li Xiaozheng , Gao Xing , Cao Chongjing 
Published: August 2023

Abstract
Suction cups are widely utilized in industries and robotics fields for object manipulation and robotic positioning. Conventional vacuum pumps can remove fluid from the suction cup continuously, enabling reliable adhesion. However, the bulky and rigid nature limits their integration with soft robotics. On the other hand, suction cups driven by soft smart materials offer better integration with soft robots but face challenges in achieving continuous fluid removal, resulting in potential suction failures in case of seal breaks. Aiming to address this limitation, a novel self-loading suction cup driven by a resonant dielectric elastomer actuator is proposed. This mechanism allows for continuous and efficient removal of the enclosed fluid in the sucker, thereby achieving successful and sustained adhesion. The structure design is presented and its fundamental working principles are revealed through theoretical analysis and experiments. The effects of several key design parameters (i.e., actuation electric field amplitude, moving mass, substrate roughness) on the performance of the suction cup are experimentally characterized to achieve performance optimization. This design demonstrates a maximum net suction force of 24.9 N (12.7 kPa), which is equivalent to 80 times its body weight. The suction cup design holds potential application values in soft robots, surveillance and environmental monitoring.
A computational insight into Rb2ASbX6 (A=Tl, Cu & X=I, Cl) double perovskites for energy storage and optoelectronic applications
Authors: Qaid Saif M H , Jamil Muhammad , Munir Junaid , Ghaithan Hamid M , Ahmed Abdullah Ahmed Ali , Ain Qurat ul 
Published: August 2023

Abstract
Double perovskites are considered to be outstanding materials for encountering the energy crises faced by the world community. This article comprehensively addresses the electronic structure, mechanical, optical and transport attributes of Rb2ASbX6 (A=Tl, Cu & X=I, Cl) double perovskites by using the DFT approach. The structural and thermodynamic stability is confirmed with negative formation energy and tolerance factor. An indirect bandgap of 1.06 eV for Rb2CuSbCl6 and a direct bandgap of 1.12 eV for Rb2TlSbI6 have been found. Mechanical properties are analyzed through elastic parameters. The absorption is found in visible as well as in ultraviolet regions with the minimum energy loss suggesting their possible use in optoelectronic applications. The thermoelectric ability is judged through the computation of transport parameters. The ZT values of 0.79 for

Rb

2

CuSbCl

6

and 0.75 for

Rb

2

TlSbI

6

endorsed their potential for renewable devices.
Nonlinear electromagnetic force analysis and compensation control of electromagnetic linear actuator
Authors: Yu Peng , Tan Cao , Yan Hao , Ge Wenqing , Sun Zhaoyue , Chen Xuewei 
Published: August 2023

Abstract
Nonlinear electromagnetic force is a common phenomenon in electromagnetic linear actuators (EMLA). This nonlinearity limits the application in high-precision control systems. For facilitating the controller design, the influencing factors of nonlinear electromagnetic force were analyzed, and the quadratic polynomial with unknown weights was designed to approximate the nonlinear relationship among electromagnetic force, excitation current and displacement. An adaptive integral robust control algorithm based on electromagnetic force compensation (AIRC-FC) was designed, which combined the adaptive control law of electromagnetic force nonlinear compensation, stable feedback and error signal continuous integral robust control. The tracking performance and the adaptability of the EMLA with and without compensation control were analyzed under different loads. The results show that AIRC-FC improve the tracking performance of the EMLA effectively, and maintain high control accuracy under different loads.
PBHs and GWs from 𝕋2-inflation and NANOGrav 15-year data
Authors: Mansoori Seyed Ali Hosseini , Felegary Fereshteh , Talebian Alireza , Sami Mohammad 
Published: August 2023

Abstract
In this paper, we propose a novel mechanism in 𝕋2-inflation to enhance the power spectrum large enough to seed primordial black holes (PBHs) formation. To accomplish this, we consider the coupling function between the inflaton field and 𝕋2 = TμνTμν
term. PBHs formed within this scenario can contribute partially or entirely to dark matter (DM) abundance. Furthermore, the amplification in the scalar power spectrum will concurrently produce significant scalar-induced gravitational waves (SIGWs) as a second-order effect. In addition, the energy spectrum associated with SIGWs can be compatible with the recent NANOGrav 15-year stochastic gravitational wave detection and fall into the sensitivity range of other forthcoming GW observatories.
Sea Cucumber Identification Fishing System Based on Hog Super Pixel Feature Extraction
Authors: Wang Min , Liu Xin , Chen Zhenrui , Lorenzini Enzo 
Published: August 2023

Abstract
Due to the refraction, reflection and absorption of light induced by seawater and suspended particles, the image recognition of underwater vehicle has the problem of low accuracy and difficult localization, and to solve this one problem, an improved LSTM classification algorithm (CH-LSTM) based on CLAHE and HOG is given. First, the improved CLAHE algorithm is used to enhance image by image noise removal and de-fogging, the problems of underwater image distortion, fine lines, and abrupt changes are solved in the aquaculture waters image. Then, the Histogram of Orientation Gradient (HOG) operator is used for feature extraction to describe the shape of sea cucumbers and generate feature vectors; finally, the LSTM algorithm is used to classify the feature vectors and avoid overfitting through memory gates, so the generalization ability of the model was enhanced. The identification and sorting experiments of underwater fishing sea cucumbers show that the proposed algorithm is superior, especially in the environment of poor water quality, and the identification and localization accuracy of sea cucumbers is improved compared with the traditional ground SVM and BP neural network algorithms, and the identification accuracy is above 95.28%.
Construction Site Safety Helmet Wearing Detection Method based on Improved YOLOv5
Authors: Fu Liang 
Published: August 2023

AbstractAiming at real-time monitoring of whether the construction site workers wear helmets correctly according to regulations, we present an improved model which based on the fifth You Only Look Once (YOLOv5) target detection algorithm for helmet wearing detection. Firstly, the clustering algorithm of the network model in the YOLOv5 is optimized to design size of the bounding box. Second, by inducing multi-scale image input to adapt to different image sizes, which enhance the generalization ability of the model. Finally, Complete Intersection over Union (CIoU) instead of original Generalized Intersection over Union (GIoU). CIoU_Loss can entirely consider the distance which are from center point to the length-width ratio between prediction box and ground truth box. The result of final experiment demonstrate that the improved model has a strong identification capability. The detection average precision reach by 92.1%, which can meet can meet the precision demands in actual situations.
A Multi-hop Path Query Answering Model for Knowledge Graph based on Neighborhood Aggregation and Transformer
Authors: Zou Jun , Wan Jing , Zhang Hao , Zhang Yunbing 
Published: August 2023

Abstract
Multi-hop path query answering is a complex task in which a path needs to be inferred from a knowledge graph that contains a head entity and multi-hop relations. The objective is to identify the corresponding tail entity accurately. The representation of the path is a critical factor in this task. However, existing methods do not adequately consider the context information of the entities and relations in the path. To address this issue, this paper proposes a novel multi-hop path query answering model that utilizes an enhanced reasoning path feature representation to incorporate intermediate entity information and improve the accuracy of path query answering. The proposed model utilizes the neighborhood to aggregate the entity representation in the reasoning path. It employs a recurrent skipping network to splice the embedding of the relationship and the entity in the reasoning path based on their weight. Additionally, the model adds the position representation to obtain the reasoning path representation. Moreover, the model uses Bi-GRU and Transformer to obtain the local and global context features of each entity in the reasoning path. Finally, the reasoning path feature representation is input into the feedforward neural network and predicted through the softmax layer. The effectiveness of the proposed model in addressing the multi-hop path query answering task is demonstrated by experimental results on the WN18RR and FB15K-237 datasets. Specifically, the proposed model outperforms existing methods in terms of accuracy.
Research on the Solution of Electromagnetic Loop Network
Authors: Gao Wenman , Chen Xiang 
Published: August 2023

Abstract
This paper mainly studies the solution of the electromagnetic ring network. Firstly, the current situation and main problems of the electromagnetic ring network are analyzed, then the principles and ideas of the electromagnetic ring network are studied, and then the effect of the electromagnetic ring network is analyzed through example verification. Through the above research, it is concluded that the development and construction of the power grid should be accelerated in combination with the load and power supply planning to create conditions for decoupling the electromagnetic loop network and eliminate the adverse effects of the operation of the electromagnetic loop network.
Optimal scheduling method of air source heat pump heating station considering optimal power flow of distribution network
Authors: Liu Yongming , Xu Xiaokang , Song Zilong 
Published: August 2023

Abstract
Participation of adjustable loads in demand response can alleviate power supply and demand challenges. As a typical adjustable load, this paper gives an optimal scheduling method considering optimal power flow in distribution networks of air source heat pumps, and studies adjustable load power allocation schemes for multiple distribution network nodes. The scheme with the goal of the lowest network loss determines the scheduling amount of the corresponding node heat supply stations to achieve optimal power flow dispatch, and the genetic algorithm is used to solve the model. Specific examples analysis shows that the proposed decision-making method can reasonably allocate power adjustments, prevent node voltage overruns in distribution networks, and reduce active power losses.
Multi-axis Current Loop Control Based on FPGA
Authors: Hu Yaorong , Chen Yuran , Zhao Jian , Wu Shan , Zou Jiang 
Published: August 2023

Abstract
In this paper, according to the three-loop control structure, FPGA is used as the control chip of the current loop, and the parallel control of the multi-axis motor is realized by hardware nation. The current loop code is written in Verilog HDL language, and the simulation results of each control module are given by the SignalTap simulation tool. The main contents include a parallel sampling of the multichannel encoder, parallel sampling of multichannel current, vector coordinate transformation control (CLARK module, PARK module, IPARK module), PI controller module, etc. The results show that the rich logic resources and powerful parallel processing ability of FPGA enable a single FPGA to control multiple motors at the same time. Compared with the traditional serial execution of the program, this method greatly reduces the whole calculation time of the servo system.
Operational failure mechanisms of electromagnetic potential transformer
Authors: Qi Peng , Wu Weili 
Published: August 2023

Abstract
In response to the problem of transformers blowing up or even burning up together with detuning devices in recent years, an assessment method based on the equivalent of transformer winding currents is proposed for potential transformers (Potential Transformer, PT) in low and medium voltage distribution networks. Firstly, the damage mechanism of potential transformers is analyzed and the thermal breakdown is identified as the main cause of damage to the winding insulation. At the same time, the winding currents under different faults are analyzed theoretically to identify the characteristics of various fault currents. Secondly, an operational failure indicator based on thermal equivalence, i.e. the fault current threshold indicator, is proposed in conjunction with the general voltage transformer specification. Finally, the proposed indicator is verified by means of ATP simulation software and combined with simulation tests. The results show that the proposed index can accurately reflect the winding failure of potential transformers, and the research results can provide a reference for the selection of potential transformers and the prevention of insulation breakdown.
Partial Discharge Suppression of the Oil-impregnated Paper by Depositing PTFE Thin Film via Magnetron Sputtering
Authors: Li Yanqing , Hao Jian , Liao Ruijin 
Published: August 2023

Abstract
The rapid development of HVDC (High Voltage Direct Current) transmission technology brings new challenges to insulation materials. Oil-paper insulation needs to be strengthened to prevent possible breakdown failure. In this paper, the PTFE functional film was fabricated by magnetron sputtering on the insulation pressboard surface to suppress partial discharge. The partial discharge test was conducted to compare the withstanding ability of the modified pressboard and the untreated pressboard. The results showed that partial discharge inception voltage increased by 18% for the modified pressboard. Phase-resolved partial discharge results also showed a great enhancement in partial discharge withstanding the ability of the PTFE function layer on the pressboard. The molecular simulation was conducted to give a possible explanation for the improvement. Higher bond levels and a large band gap of PTFE played a vital role.
Characteristic Analysis of the Equivalent Experimental System for Electrodynamic Suspension Linear Generator
Authors: Yu Jiaqi , Wang Chengen , Wang Haoyun , Tian Jihao 
Published: August 2023

Abstract
This paper presents an equivalent experimental method for the linear generator of the electrodynamic suspension (EDS) system. Compared with the full-size experimental device, the proposed method can reduce the cost and difficulty of the experiment. Firstly, the working principle of the linear generator is described, and the numerical analytical expression for the induced voltage of the linear generator is derived. Based on the expression, the mapping relationship between the suspension coil current, system scaling ratio, and the induced voltage is clarified. Then, an equivalent experimental device was designed and built. Comparisons between the numeric analytical calculation, the finite element analysis, and the experiment have verified the accuracy of the equivalent experimental method.
A New Power-Frequency Oscillation Suppression and Power Allocation Control Method Based on MPC in Multi-VSGs Parallel System
Authors: Zhao Xuejian , Liu Jianzheng 
Published: August 2023

Abstract
The virtual synchronous generator (VSG) technology can provide frequency support for power systems that are dominated by renewable power sources. However, it also introduces the characteristic of active power oscillation, which can cause power-frequency oscillation between parallel VSGs when there are disturbances in the load power or command power. To address this problem, this paper proposes that the idea of equivalent comparison can be used to compare the power-frequency interaction of N-VSGs parallel systems with the current-voltage interaction of N-RLC circuits. This allows us to establish a mathematical model of the parallel VSGs system based on Kirchhoff’s equation of the circuit. Using this model, we designed a new power-frequency oscillation suppression and a power allocation control method based on the model predictive control (MPC) in multi-VSGs parallel systems. This method can effectively suppress power-frequency oscillation in each VSG branch after a disturbance occurs, and accurately allocate active power according to instructions. Finally, simulation results confirm the effectiveness of the controller.