bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pulsed production of antihydrogen
Authors: Amsler Claude , Antonello Massimiliano , Belov Alexander , Bonomi Germano , Brusa Roberto Sennen , Caccia Massimo , Camper Antoine , Caravita Ruggero , Castelli Fabrizio , Cheinet Patrick , Comparat Daniel , Consolati Giovanni , Demetrio Andrea , Di Noto Lea , Doser Michael , Fanì Mattia , Ferragut Rafael , Fesel Julian , Gerber Sebastian , Giammarchi Marco , Gligorova Angela , Glöggler Lisa Theresa , Guatieri Francesco , Haider Stefan , Hinterberger Alexander , Kellerbauer Alban , Khalidova Olga , Krasnický Daniel , Lagomarsino Vittorio , Malbrunot Chloé , Mariazzi Sebastiano , Matveev Viktor , Müller Simon , Nebbia Giancarlo , Nedelec Patrick , Nowak Lilian , Oberthaler Markus , Oswald Emmanuel , Pagano Davide , Penasa Luca , Petracek Vojtech , Povolo Luca , Prelz Francesco , Prevedelli Marco , Rienäcker Benjamin , Røhne Ole , Rotondi Alberto , Sandaker Heidi , Santoro Romualdo , Testera Gemma , Tietje Ingmari , Toso Valerio , Wolz Tim , Yzombard Pauline , Zimmer Christian , Zurlo Nicola 
Published: February 2021

AbstractAntihydrogen atoms with K or sub-K temperature are a powerful tool to precisely probe the validity of fundamental physics laws and the design of highly sensitive experiments needs antihydrogen with controllable and well defined conditions. We present here experimental results on the production of antihydrogen in a pulsed mode in which the time when 90% of the atoms are produced is known with an uncertainty of ~250 ns. The pulsed source is generated by the charge-exchange reaction between Rydberg positronium atoms—produced via the injection of a pulsed positron beam into a nanochanneled Si target, and excited by laser pulses—and antiprotons, trapped, cooled and manipulated in electromagnetic traps. The pulsed production enables the control of the antihydrogen temperature, the tunability of the Rydberg states, their de-excitation by pulsed lasers and the manipulation through electric field gradients. The production of pulsed antihydrogen is a major landmark in the AE$$\bar{g}$$
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IS experiment to perform direct measurements of the validity of the Weak Equivalence Principle for antimatter.
Effects of the Age, Sex, and Maternal Education of Monolingual Spanish-Speaking Preschool Children on Oral Narrative Production
Authors: Mendoza Manuel , Beltran-Navarro Beatriz , Matute Esmeralda , Rosselli Monica 
Published: February 2021

PurposeThe aim of the present cross-sectional study was to determine the effects of age, sex, and maternal education of monolingual Spanish-speaking preschoolers on both macrostructural (oral narrative quality) and microstructural measures (number of different words, communication units, mean length of utterance in both words and morphemes, and number of conjunctions) of their oral narrative production.MethodA total of 277 monolingual Spanish-speaking Mexican children aged 2;06–5;11 (years;months) and divided into four age groups (ages 2, 3, 4, and 5 years) were asked to retell a fictional story from the oral narrative ability task of theEvaluación Neuropsicológica Infantil–Preescolar.ResultsAppropriate internal consistency and interrater reliability were demonstrated. Pearson correlations between macro- and microstructural measures showed a positive association. A multivariate analysis of variance revealed a main effect for age, but not for sex, maternal education, or between-variables interactions. Partial eta-squared showed that age had a medium effect size on oral narrative quality and the number of different words and conjunctions, with a small effect size on communication units and mean length of utterance in words and morphemes. Hierarchical multiple regression analyses indicated that age explained the largest percentage of variance across the oral narrative measures.ConclusionsThe measures found to be most sensitive to the effect of age (number of different words, oral narrative quality, communication units, conjunctions) are also those most easily assessed by clinicians with limited training in linguistics. Results obtained for the number of different words and communication units were similar to those reported previously for English-speaking children.
Age‐optimal path planning for finite‐battery UAV‐assisted data dissemination in IoT networks
Authors: Changizi Abolfazl , Emadi Mohammad Javad 
Published: February 2021

AbstractUnmanned aerial vehicles have been widely used to assist wireless sensor networks due to ever‐increasing demands for Internet‐of‐things applications. To support timely delivery of information characterised by a recently introduced metric, termed as the age of information, this paper explores freshness of data in an unmanned aerial vehicle assisted wireless sensor network. Specifically, the authors consider a limited‐energy unmanned aerial vehicle moving towards the Internet‐of‐things devices to disseminate data packets provided by a data centre. Since the unmanned aerial vehicle cannot visit all the nodes in each flight turn due to its finite‐sized battery, the best sequence of nodes, from an age of information perspective, should be selected at the beginning of each flight turn. Thus, an unmanned aerial vehicle trajectory planning for data dissemination is proposed taking into account both maximal use of energy and freshness of data. To minimise the weighted sum age of information metric, by utilising the well‐known knapsack and travelling salesman problems, the authors propose an algorithm to efficiently select devices and the corresponding visiting order in each flight turn. Finally, to highlight performance of the proposed algorithm, and to investigate the effect of limited‐energy unmanned aerial vehicles, the number of nodes and flight turns, and simulation results are also provided and compared with other benchmark algorithms.
Coordination of multi‐agent systems with arbitrary convergence time
Authors: Nguyen Thanh Truong , Trinh Minh Hoang , Nguyen Chuong Van , Nguyen Nam Hoai , Ðặng Mỹ Văn 
Published: February 2021

AbstractThis paper proposes fixed‐time solutions to several problems in multi‐agent systems. First, a fixed‐time consensus protocol is investigated and under the assumption that the lower bound of smallest positive eigenvalue of the Laplacian matrix is known in advance, the consensus time of the protocol can be arbitrarily selected. Second, the consensus law to attenuate bounded disturbances acting on the system is modified. Third, the fixed‐time design method is applied to the orientation alignment and network localization problems. Finally, several simulations are provided to support the mathematical analysis.
Finite‐time consensus of leader‐following non‐linear multi‐agent systems via event‐triggered impulsive control
Authors: Chen Tao , Peng Shiguo , Zhang Zhenhua 
Published: February 2021

AbstractThis work is concerned with the finite‐time consensus of leader‐following non‐linear multi‐agent systems by means of distributed event‐triggered impulsive control. The finite‐time consensus protocol is first put forward based on event‐triggered impulsive strategies, where the impulsive instants are determined by the proposed event‐triggered condition. For the event‐triggered condition, it not only determines the impulsive instants but also effects the update time of the finite‐time control. Moreover, compared with the existing finite‐time controllers, the controller designed in this work does not contain any sign function, thereby overcoming the chattering phenomenon. In addition, without finding Zeno behaviour, the feasibility of the proposed control protocol is demonstrated. Lastly, simulations are employed to demonstrate the effectiveness of the proposed control schemes.
Image translation with dual‐directional generative adversarial networks
Authors: Ruan Congcong , Yuan Liuchun , Hu Haifeng , Chen Dihu 
Published: February 2021

AbstractImage‐to‐image translation is a class of vision and graphics problems where the goal is to learn the mapping between input images and output images. However, due to the unstable training and limited training samples, many existing GAN‐based works have difficulty in producing photo‐realistic images. Herein, dual‐directional generative adversarial networks are proposed, which consist of four adversarial networks, to produce images of high perceptual quality. In this framework, self‐reconstruction strategy is used to construct auxiliary sub‐networks, which impose more effective constraints on encoder‐generator pairs. Using this idea, this model can increase the use ratio of paired data conditioned on the same dataset and obtain well‐trained encoder‐generator pairs with the help of the proposed cross‐network skip connections. Moreover, the proposed framework not only produces realistic images but also addresses the problem where condition GAN produces sharp images containing many small, hallucinated objects. Training on multiple supervised datasets, convincing evidences are shown to prove that this model can achieve compelling results by latently learning a common feature representation. Qualitative and quantitative comparisons against other methods, demonstrate the effectiveness and superiority of the method.
Categorisation of power quality problems using long short‐term memory networks
Authors: Abdelsalam Abdelazeem A. , Hassanin Ahmed M. , Hasanien Hany M. 
Published: February 2021

AbstractRecognition of power quality (PQ) troubles is a critical task in the electrical power system. All previous works solve this problem using two‐step methodology: Feature extraction and classification steps with each step using its own techniques, and this consumes a computation time. The purpose of this study is to utilise a novel artificial intelligence (AI) technique for recognition of PQ events. The proposed AI technique is the long short‐term memory (LSTM) network, which detects and classifies the PQ events in one step. This technique extracts amplitude, disturbance duration and total harmonic distortion from the captured waveform, and the LSTM uses its own rules to classify the PQ events. Many simple PQ events such as interruption, sag, flicker, swell and surge or complex PQ events such as sag plus harmonics and swell plus harmonics are generated using MATLAB programming environment to evaluate the performance of LSTM. Also, real‐time measurements are collected from an industrial substation and are used to ensure the effectiveness of the proposed LSTM technique. A comparison with other techniques is conducted and the results verify the good performance of LSTM in classifying the PQ problems.
Optimal power rescheduling in interconnected AC/DC networks to maintain the voltage stability
Authors: Dalali Milad , Karegar Hossein Kazemi , Zeineldin Hatem H. 
Published: February 2021

AbstractThe main remedial actions to prevent voltage instability problems are load shedding and rescheduling of generating units. In AC/DC networks, the presence of high voltage direct current (HVDC) links equipped with voltage source converter (VSC) provides an efficient active and reactive power support. As the voltage stability is a local phenomenon, the rescheduling of an HVDC link could change the arrangement of critical buses and the stability margin of the entire power system as a remedial action. Considering this problem, a new optimization algorithm is proposed to provide the desired voltage stability margin in interconnected AC/DC networks taking into account the post contingency conditions and minimizing the cost of remedial actions. The regulation of the converter operating point is presented as a novel remedial action. The well‐known loading margin (LM) index is used as the voltage stability criterion and different VSC‐HVDC structures, i.e. single‐infeed, multi‐infeed and multi‐terminal HVDC systems are considered. The effectiveness of the proposed algorithm is evaluated using an AC/DC system comprising the IEEE 118‐bus and New England 39‐bus test systems. The results show that the proposed algorithm could provide the desired value of LM with the minimum value of load shedding and the control cost.
An optimal transmission line power control under non‐sinusoidal conditions using static synchronous series compensator
Authors: Nema Shruti , George Sincy 
Published: February 2021

AbstractIn view of the growing load demand in developing countries, overloading in existing transmission lines is a major concern. In addition to the voltage drop due to overloading, the proliferation of non‐linear loads in recent years distort the shape of sinusoidal voltage. Stable transmission of power through a transmission line under such condition is a challenge. In the presence of harmonics, control of transmittable power using static synchronous series compensator needs additional efforts, where increased power demand can be fulfilled by taking into consideration various other parameters. If an attempt is made to increase transmittable power through a transmission line using SSSC, power loss, the magnitude of voltage and its shape deteriorate in the presence of non‐linear loads. Thus, the trade‐off between transmittable power, transmission loss and voltage quality is tackled by optimal control of the compensator. In this study, a novel optimal control of SSSC is proposed with the objective of minimising transmission loss by maintaining the voltage within the limits while enhancing the transmittable power under non‐sinusoidal conditions. A two‐machine model of power system with 400 kV transmission line with parameters as per standards issued by the Central Electricity Authority is considered for validation of the algorithm using MATLAB platform and results are presented.
Bidding strategy of thermal power compound differential evolution game under the market mechanism of peak regulation auxiliary service
Authors: Dong Fugui , Li Wanying , Ji Zhengsen , Fatema Shafaq 
Published: February 2021

AbstractAs the main provider of peak regulation auxiliary services, thermal power units are particularly important to ensure their revenue in an uncertain environment. To obtain the optimal bidding strategy for thermal power units, a thermal power peak regulation bidding model based on the Northeast Power Grid's auxiliary service market bidding mechanism is established. Secondly, the evolutionary game theory is introduced into the bidding strategy of thermal power units. Meanwhile, in order to solve the multi‐party game problem, a compound differential evolution game algorithm is constructed to solve the two‐tiers bidding. Finally, based on the actual operating data of a typical day, the efficiency of the compound differential evolution game algorithm bidding strategy is verified, and the bidding strategy of thermal power units in different situations is discussed. The results show that when all units participate in peak regulation, the first‐tier quotation is an optimal strategy at 0.19 yuan kWh−1 and below, and the second‐tier quotation is distributed between 0.6–0.8 yuan kWh−1. When only some units are involved in peak regulation, the first‐tier quotation of thermal power units adopts a high price strategy, mostly at 0.3 yuan kWh−1, and the second‐tier quotation is still based on a high price strategy.
Effectiveness of incentives offered by mobile phone app to encourage cycling: A long‐term study
Authors: Huang Bingyuan , Thomas Tom , Groenewolt Benjamin , Claasen Yorick , van Berkum Eric 
Published: February 2021

AbstractReduction of car use is one of the most effective ways to tackle congestion‐related problems. Using positive incentives to stimulate bicycle use is one possibility to reduce car use. Cycling is a sustainable transport mode that uses little space and is healthy. There is evidence that positive incentives may be more effective than punishing travellers for undesirable behaviour, and the emergence of mobile applications for delivering interventions has opened up new opportunities for influencing travellers. So far, few studies have focused on exploring the effectiveness of positive incentives on long‐term behavioural change. We used the SMART app to deliver positive incentives to more than 6000 travellers in the Dutch region of Twente. The app automatically tracks users and provides incentives such as challenges with rewards, feedback, and messages. This study covers the period from March 2017 to June 2018, in which more than 1000 SMART users participated in monthly challenges. We evaluated the effects of the challenges and rewards and found that the challenges did encourage cycling and reduced car use in the short term. There is also some evidence for behavioural change over a longer time period.
An alternative reliability method to evaluate the regional traffic congestion from GPS data obtained from floating cars
Authors: Yuan Wubei , Wang Ping , Yang Jingwen , Meng Yun 
Published: February 2021

AbstractFast and reliable evaluation of regional traffic congestion is beneficial to more effective traffic control. Based on data accumulation in modern society, more and more data‐driven methods are proposed. However, it is still not easy to process the raw data to an interpretable level in practical applications. In this article, the GPS data are obtained from floating cars covering a large scale region in Xi'an, China. To link the original data to the spatiotemporal relationship of driving behaviour, a pre‐processing method with specified time–frequency rules is proposed. Through map matching and landmark mapping, it can be seen that the data dispersion degree has decreased and the quality of the original data has been improved. At the same time, deep learning methods and non‐parametric survival analysis methods are used to compare and evaluate traffic congestion. In addition, four different distributions (Exponential, Weibull, Log‐normal, and Log‐logistic) are tested to fit the accelerated failure time model (AFT), which is then compared with the Cox proportional hazards model (Cox). It is concluded that the most suitable parameter model for the test section of Xi'an South Second Ring Road is AFT (Lognormal). All those methods are tested on a randomly selected segment on the ring road in Xi'an. The results suggest dramatic improvement of data quality and successful evaluation of traffic conditions with high reliability. Potential application could be effective methods for traffic control and management in the smart city.
Ageing of DC conduction in thermally aged oil‐impregnated pressboard
Authors: Haque Nasirul , Dalai Sovan , Chatterjee Biswendu , Chakravorti Sivaji 
Published: February 2021

AbstractAgeing of the conduction process in a dielectric allows a better understanding of the phenomena. Available literature shows that the DC conductivity of oil impregnated pressboard increases with applied electric stress, particularly above 40 °C. However, the reason for this conductivity behaviour is not well understood. This paper attempts to understand the conduction mechanism of oil‐pressboard insulation and the effect of thermal ageing on it. For this purpose, DC conductivity measurements have been performed on oil impregnated pressboard specimens with varied ageing status at the electric field range 1 kV mm−1–15 kV mm−1 at 40 °C temperature. After a critical analysis, a new electric field dependent non‐linear conduction model was developed based on charge injection and thermally assisted “hopping” of charge carriers from one site to another site to explain charge transport in oil‐pressboard. The developed model fitted well with the measured experimental values of conductivity. It was also observed that certain model parameters, that is charge carrier density, charge mobility and potential barrier for charge hopping are dependent on the ageing status of the insulation that clearly affects the conduction process.
Framework for efficient dynamic analysis applied to a tubular generator for suspension applications
Authors: Kleijer Matthijs , Friedrich Léo A. J. , Gysen Bart L. J. , Lomonova Elena A. 
Published: February 2021

AbstractThis paper considers a slotless three‐phase tubular permanent magnet generator located in an automotive suspension system for the application of vibration energy harvesting. A two‐dimensional finite element method model of the harvester is produced and an experimental setup that contains the generator is constructed. Signal decomposition methods are applied to measured suspension displacement data and the resulting signal components are used as input for the model. Two approaches for signal decomposition are discussed, namely, the discrete Fourier transform and the continuous wavelet transform. The individual emf responses of the model are reconstructed to a single output, while a sideband prediction algorithm accounts for the non‐linearities in the system. The simulation results are compared with the reference measurements conducted on the setup to determine the accuracy of each of the signal decomposition methods.
Studies on prospect of HTV silicone rubber as dielectric material when reinforced with TiO2 nano particles
Authors: Pal Argha Kamal , Baral Arijit , Lahiri Abhijit 
Published: February 2021

AbstractThe present work aims to improve both the thermal and dielectric properties at power frequency of millable high temperature vulcanized silicone rubber (HTV SR) so that it can be used as housing material for transformer bushings or as a substitute to ceramic and glass insulators. For this purpose, nano sized titanium dioxide (TiO) particles have been incorporated into HTV SR. Samples of HTV SR, filled with different percentages by weight of nano TiO fillers have been synthesized along with one HTV SR sample without filler loading referred here as blank HTV SR sample in the subsequent sections. Morphological characterizations of these nano filler impregnated samples are carried out. Thermal, electrical and mechanical characterizations are performed and the results are compared with those obtained for blank HTV SR samples. Results showed that at lower filler concentrations, dielectric properties and thermal stability of HTV SR/TiO nanocomposites have improved to a considerable extent while retaining the mechanical properties.
Flexible capacitor characterisation using algebraic parameter identification approach
Authors: Martínez‐Lopez Andrea G. , Portillo‐Vélez Rogelio de J. , Rueda Diego Amador , Garcia Rodolfo , Tinoco Julio C. 
Published: February 2021

AbstractFlexible capacitive sensor devices have gained attention because of their versatility and adaptability to several requirements. However, the proper implementation of those devices into flexible electronic systems imply some challenges related to the readout strategies necessary to adequately determine capacitance values. Usually, electronic circuits are used to develop signal conditioning and processing tasks, as well as estimation of parameters. In this study, a free‐of‐signal conditioning strategy for capacitance measurement based on an algebraic parameter identification approach is presented. Furthermore, flexible capacitors over polyethylene terephthalate substrates and polydimethylsiloxane as dielectric material are fabricated with the aim to validate the behaviour of the capacitance measurement method. Experimental results are compared with standard recursive least square technique as well as standard capacitance metre. Overall results demonstrate the good performance of the proposed approach.