bluuebunny/crossref_metadata_2025_split huggingface dataset:
democracy in Taiwanese presidential inaugural addresses
Authors: Hsu Hsiao-Ling , Lai Huei-ling , Liu Jyi-Shane 
Published: November 2022

Abstract
This study explored metaphorical expressions related to democracy in 15 Taiwanese presidential inaugural
addresses. The source domain concepts mapped to understand democracy were examined and the relationship between these
metaphorical expressions and ideologies was teased out by employing the discourse-historical approach. Our analysis demonstrates
that various source domain concepts were utilized to discuss democracy, and most newly-emerged types occurred after the
success of the first direct presidential election in 1996. A more detailed analysis of the source domain elements showed that
different scenarios were highlighted, reflecting specific ideologies embedded along with the social, historical and political
situation.
Universality? Cross-linguistic influence?
Authors: Chung Chi-ting Alvan , Chen Chun-yin Doris 
Published: November 2022

Abstract
The present study investigated the use of apology response (AR) strategies by L1-Chinese L2-English learners and L1-English L2-Chinese learners from a cross-linguistic perspective. A total of 18 Taiwanese college students who were learning English as a foreign language and 18 foreigners in Taiwan who were learning Chinese as a second language were recruited to complete an oral discourse completion task both in Chinese and English. The major findings are as follows: First, the two groups showed no significant difference in their choice of AR strategies, both favoring Acceptance and Minimization, two face-preserving types, to show politeness. Second, cross-linguistic influence was found to affect our participants’ AR performances. Both positive and negative influences occurred. Finally, regarding the use of multiple strategies, both groups of participants tended to combine Acceptance with other strategies to maintain social relationships. The results showed both language universal and language-specific features in the AR realizations in Chinese and English. The dominant use of positive response strategies, namely Acceptance and Minimization, highlights the profound influence of politeness principles.
On the use ofsì?(‘yes?’) as invariant follow-up in Italian
Authors: Viola Lorella 
Published: November 2022

AbstractFollow-ups are elliptical interrogative forms typically constituting an utterance in their own right. They are used to signal attention to the interlocutor, to encourage them to continue or as a reply to a call. This paper investigates the invariant follow-upsì?(‘yes?’) in Italian and it argues that it represents a case of pragmatic language change. To this end, it investigates the diachronic distribution, collocation and contexts of usage ofsì?in a variety of language sources in relation to plausible, equivalent expressions (i.e.,dimmianddica[‘tell me’]). The analysis will show that since its earliest record of use in films in 1960, the frequency of occurrence of this form has dramatically increased to the point that, today, it is the preferred device. The study will also provide solid evidence of positive correlations between the use ofyes?in English language audio-visual products and the use ofsì?in scripted and real-use Italian, strongly suggesting that the marker would in fact be a case of pragmatic borrowing from English.
Multiconfiguration b-AsP-based doping systems with enriched elements (C and O): novel materials for spintronic devices
Authors: Liu Fangqi , Xu Jialu , Wang Tongtong , Yu Qiang , Wang Wenyue , Zhang Yong , Wu Jian , Zhu Sicong 
Published: November 2022

Abstract
Black arsenical phosphorus (b-AsP), a derivative of black phosphorus, is a bimetallic alloy compound with the advantage of high carrier mobility, high stability, and tailorable configuration. However, lack of an effective tool to facilitate the application of AsP as a magnetic device. Herein, band gap modulation and the introduction of magnetism can be achieved by doping non-metallic atoms in three different AsP configurations. And the doping of the same atom will cause variation in the electronic structure depending on the configuration. Surprisingly, doping with both enriched elements C and O transforms AsP into a magnetic material. Furthermore, the source of the magnetic moment is explained by solving the wave function of the doped AsP, which is caused by the orbital coupling of the C and O atoms to AsP. To excavate the potentials of this magnetic AsP system for magnetic devices, field-effect transistors based on two doped armchair AsP3 nanoribbons are simulated. The devices show considerable negative differential conductivity effect and good spin filtering efficiency. These findings suggest that AsP doping with enriched elements C and O could be an excellent candidate for future spintronics applications.
Application of enhanced empirical wavelet transform and correlation kurtosis in bearing fault diagnosis
Authors: Xue Jijun , Xu Hao , Liu Xiaodong , Zhang Di , Xu Yonggang 
Published: November 2022

Abstract
The traditional empirical wavelet transform (EWT) based on the Meyer wavelet and scale-space method can decompose a signal into several empirical modes. However, this method is not effective in dealing with strong noise and non-stationary signals, which may lead to modal mixing or even decompose too many invalid components. For this purpose, a method based on the combination of enhanced empirical wavelet transform (EEWT) and correlation kurtosis (CK) is proposed in this paper. Firstly, the EEWT is used to segment the spectrum based on the characteristics of the spectrum fluctuations. It uses the minimum points of the envelope as the boundaries of the segmented spectrum. Secondly, a filter bank is constructed based on these boundaries and a maximum value order statistics filter segments the Fourier spectrum with the adaptive decomposition of the signals. Finally, the envelope spectrum generated by CK is used to screen the bearing fault information, which belongs to the decomposition of a signal into empirical modes, so that the rolling bearing fault can be accurately diagnosed. The method’s effectiveness is verified by simulated signal experiments and rolling bearing fault signals. The results show that the performance of the proposed method in this paper is better than that of the traditional EWT. Therefore, the method can be applied to the field of bearing faults or other mechanical fault diagnosis directions.
Enhanced neural network model for regional ionospheric modeling and evaluation under different solar-geomagnetic conditions
Authors: Dong Yanfeng , Gao Chengfa , Long Fengyang , Nie Wenfeng , Juan Jose Miguel , Rovira-Garcia Adria , Zhang Ruicheng 
Published: November 2022

Abstract
Monitoring spatiotemporal variations of ionospheric vertical total electron content (VTEC) is crucial for space weather and satellite positioning. In the present study, an enhanced neural network (ENN) model is proposed to capture the changing characteristics of ionospheric VTEC and compared with the traditional mathematical models, i.e. the POLYnomial (POLY) model, generalized trigonometric series function and spherical harmonic function (SHF) model. The ionospheric VTEC data obtained from 31 permanent global positioning system stations in the southwest region of China on 26 August and 8 September, 2017, were used to test the performance of the mentioned models under different Solar-geomagnetic conditions. The ENN model is derived from the ensemble learning method, and the disadvantage that simple backpropagation neural network learners that are not robust enough is weakened by the ENN model. After statistical analysis and single-frequency precise point positioning (SF-PPP) experiments, it is demonstrated that the ENN model is superior to the above three mathematical models, regardless of the solar-geomagnetic conditions. In terms of mean absolute error, root mean square error, standard deviation, and mean absolute percentage error, the ENN model outperforms the SHF model, which is the best mathematical model in the analysis, by 40.7%, 30.20%, 29.88%, 38.04% under quiet solar-geomagnetic conditions, and by 37.66%, 29.93%, 30.96%, 32.01% under active solar-geomagnetic conditions. In addition, the accuracy of the SF-PPP is greatly affected by the error caused by ionosphere. In the static SF-PPP experiment of this study, the ENN model can better correct ionospheric error. Under quiet and active solar-geomagnetic conditions, the SF-PPP accuracy can be improved by 85.1% and 85.2% with the ionosphere delay correction from the ENN model.
Seizure forecasting using machine learning models trained by seizure diaries
Authors: Gleichgerrcht Ezequiel , Dumitru Mircea , Hartmann David A , Munsell Brent C , Kuzniecky Ruben , Bonilha Leonardo , Sameni Reza 
Published: November 2022

Abstract

Objectives. People with refractory epilepsy are overwhelmed by the uncertainty of their next seizures. Accurate prediction of future seizures could greatly improve the quality of life for these patients. New evidence suggests that seizure occurrences can have cyclical patterns for some patients. Even though these cyclicalities are not intuitive, they can be identified by machine learning (ML), to identify patients with predictable vs unpredictable seizure patterns. Approach. Self-reported seizure logs of 153 patients from the Human Epilepsy Project with more than three reported seizures (totaling 8337 seizures) were used to obtain inter-seizure interval time-series for training and evaluation of the forecasting models. Two classes of prediction methods were studied: (1) statistical approaches using Bayesian fusion of population-wise and individual-wise seizure patterns; and (2) ML-based algorithms including least squares, least absolute shrinkage and selection operator, support vector machine (SVM) regression, and long short-term memory regression. Leave-one-person-out cross-validation was used for training and evaluation, by training on seizure diaries of all except one subject and testing on the left-out subject. Main results. The leading forecasting models were the SVM regression and a statistical model that combined the median of population-wise seizure time-intervals with a test subject’s prior seizure intervals. SVM was able to forecast 50%, 70%, 81%, 84%, and 87% of seizures of unseen subjects within 0, 1, 2, 3 to 4 d of mean absolute forecasting error, respectively. The subject-wise performances show that patients with more frequent seizures were generally better predicted. Significance. ML models can leverage non-random patterns within self-reported seizure diaries to forecast future seizures. While diary-based seizure forecasting alone is only one of many aspects of clinical care of patients with epilepsy, studying the level of predictability across seizures and patients paves the path towards a better understanding of predictable vs unpredictable seizures on individualized and population-wise bases.
Characterization of rheumatic heart disease from electrocardiogram recordings
Authors: Asmare Melkamu Hunegnaw , Chuma Amsalu Tomas , Varon Carolina , Woldehanna Frehiwot , Janssens Luc , Vanrumste Bart 
Published: November 2022

Abstract

Objective. Rheumatic Heart Disease (RHD) is one of the highly prevalent heart diseases in developing countries that can affect the pericardium, myocardium, or endocardium. Rheumatic endocarditis is a common RHD variant that gradually deteriorates the normal function of the heart valves. RHD can be diagnosed using standard echocardiography or listened to as a heart murmur using a stethoscope. The electrocardiogram (ECG), on the other hand, is critical in the study and identification of heart rhythms and abnormalities. The effectiveness of ECG to identify distinguishing signs of rheumatic heart problems, however, has not been adequately examined. This study addressed the possible use of ECG recordings for the characterization of problems of the heart in RHD patients. Approach. To this end, an extensive ECG dataset was collected from patients suffering from RHD (PwRHD), and healthy control subjects (HC). Bandpass filtering was used at the preprocessing stage. Each data was then standardized by removing its mean and dividing by its standard deviation. Delineation of the onsets and offsets of waves was performed using KIT-IBT open ECG MATLAB toolbox. PR interval, QRS duration, RR intervals, QT intervals, and QTc intervals were computed for each heartbeat. The median values of the temporal parameters were used to eliminate possible outliers due to missed ECG waves. The data were clustered in different age groups and sex. Another categorization was done based on the time duration since the first RHD diagnosis. Main results. In 47.2% of the cases, a PR elongation was observed, and in 26.4% of the cases, the QRS duration was elongated. QTc was elongated in 44.3% of the cases. It was also observed that 62.2% of the cases had bradycardia. Significance. The end product of this research can lead to new medical devices and services that can screen RHD based on ECG which could somehow assist in the detection and diagnosis of the disease in low-resource settings and alleviate the burden of the disease.
Hysteretic behaviour and structural control performance of a piezoelectric friction damper
Authors: Zhang Xiaolong , Luo Qixing , Han Qinghua , Lu Yan , Wang Yue 
Published: November 2022

Abstract
This study proposes a novel piezoelectric friction damper (PFD). Experiments and numerical simulations are carried out to investigate the mechanical model of the PFD, and the effects of loading speed, displacement amplitude, voltage, friction plate material, piezoelectric stack actuator dimensions, and spring parameters on the hysteretic characteristics of the PFD. Results show that the PFD attains a stable mechanical performance within the design loading speed and displacement amplitude. The piezoelectric stack actuator functioning as a friction control device, can increase friction by 54% at 120 V. In damper design, an appropriate increase of the constraint stiffness of the damper and a piezoelectric stack actuator with the same stiffness as the damper constraint can achieve greater output force, and the preload of the spring should be greater than the friction to prevent residual displacement. The PFD has better seismic performance for large-span cable dome structures than the traditional friction damper. The vertical peak displacement and acceleration reduction ratio reached 45.1% and 67.7% with PFDs, respectively. The PFD with semi-active control is suitable for large-span spatial structures.
Analysis of pulsatile combined electroosmotic and shear-driven flow of generalized Maxwell fluids in a microchannel with slip-dependent zeta potential
Authors: Mahanta Kaushik , Panda Swapnil , Banerjee Debanjan , Pati Sukumar , Biswas Pankaj 
Published: November 2022

Abstract
The present study investigates the flow characteristics for a pulsatile, combined electroosmotic and shear-driven flow of generalized Maxwell fluid through a straight planar microchannel including the effect of hydrodynamic slippage on asymmetric zeta potential. Mathematical expressions have been obtained in dimensionless form for the electrical potential distribution of the electrical double layer (EDL), velocity distribution and the volumetric flow rate after analytically solving the Poisson-Boltzmann and momentum equations. Critical values and critical ranges of time period of oscillating electric field have been obtained for no-slip and slip cases respectively where anomalous behaviour of dimensionless volumetric flow rate is observed. Flow rate magnitude sensitivity on hydrodynamic slippage is also analyzed. Moreover, critical values of the time period of oscillating electric field are obtained where the sensitivity of flow rate magnitude on the relaxation time of Maxwell fluid vanishes. Similarly, pivotal values of the time period of oscillating electric field are obtained at which the sensitivity of flow rate magnitude on the relaxation time of Maxwell fluid becomes invariant with the lower wall velocity.
Triggering of tearing instability by impurity radiation through resistive interchange reversal in a tokamak
Authors: Zeng Shiyong , Zhu Ping , Zhou Ruijie , Escande Dominique Frank 
Published: November 2022

Abstract
Recent MHD simulations find that the reversal of the local resistive interchange parameter

D

R

from negative to positive due to impurity radiation cooling is able to linearly destabilize the resistive tearing mode (TM) growth in a tokamak above a threshold in impurity level. A layer of perturbed Pfirsch–Schlüter current density and resistivity are also induced by the impurity radiation, which further govern the TM growth and saturation in the nonlinear stage. The impurity threshold and the TM growth strongly depend on the parallel thermal conductivity, and such a dependence derives from the impact on

D

R

of the fast parallel thermal equilibration along the helical magnetic field lines.
Acousto-optic k-space filtering for multifrequency laser beam shaping
Authors: Yushkov Konstantin B , Kupreychik Maxim I , Obydennov Dmitry V , Molchanov Vladimir Y 
Published: November 2022

Abstract
One of emerging applications of acousto-optic tunable filters (AOTFs) is spatial filtering of optical beams. A noncollinear AOTF has a tunable ring-shaped transfer function determined by geometry of the refractive index surface in a uniaxial crystal. We rigorously derive the geometrical parameters of the AOTF’s elliptic transfer function under noncritical phase matching condition in uniaxial crystals. This basic family of transfer functions can be used for synthesis of axially symmetric transfer functions with the help of multifrequency ultrasonic signals. A two-color tunable optical trap configuration is proposed based on a single AOTF used for laser beam shaping.
Preparation and characterization of Fe3O4 nanoparticles via a hydrothermal process with propanediol as the solvent
Authors: Liu Tao , Zhang Shuting , Xu Yueyang 
Published: November 2022

Abstract
Fe3O4 nanomaterials have received great attention in various technology fields. However, the limitations are Fe3O4 is easy to agglomerate and obtaining Fe3O4 nanoparticles of tunable magnetism and controllable size, and well-dispersed ability remains a challenge. In this study, a simple hydrothermal process with propanediol as the solvent was used to prepare Fe3O4 nanoparticles. In the optimization of preparation conditions, three key factors (hydrothermal temperature, hydrothermal time, and solvent volume) were optimized by x-ray diffraction (XRD) and vibrating sample magnetometer (VSM). The results showed that the magnetism and the phase content of the prepared Fe3O4 were controllable during the optimization process. The optimum hydrothermal temperature was 170 °C, hydrothermal time was 18 h and solvent volume was 40 ml. The elemental composition, surface morphology, and magnetic properties of Fe3O4 nanoparticles were characterized. The prepared Fe3O4 nanoparticles exhibited superparamagnetic properties and high crystallinity, with an average particle size of 20 nm, a specific surface area of 84.756 m2 g−1, a pore volume of 0.265 cm3 g−1, and saturation magnetization (Ms) of 129.38 emu g−1.
Recent progress on the mechanical exfoliation of 2D transition metal dichalcogenides
Authors: Li Yangang , Kuang Guizhi , Jiao Zhongjie , Yao Lin , Duan Ruihuan 
Published: November 2022

Abstract
Two-dimensional (2D) transition metal dichalcogenides (TMDs) have attracted extensive attraction due to their unique properties in novel physical phenomena, such as superconductors, Moiré superlattices, ferromagnetics, Weyl semimetals, which all require the high quality of 2D TMDs. Mechanical exfoliation (ME) as a top-down strategy shows great potential to obtain 2D TMDs with high quality and large scale. This paper reviews the theoretical and experimental details of this method. Subsequently, diverse modified ME methods are introduced. Significantly, the recent progress of the Au-assisted ME method is the highlight. Finally, this review will have an insight into their advantages and limitations, and point out a rational direction for the exfoliation of TMDs with high quality and large size.
Flexible temperature sensor with high sensitivity ranging from liquid nitrogen temperature to 1200 °C
Authors: Liu Zhaojun , Tian Bian , Jiang Zhuangde , Li Shuimin , Lei Jiaming , Zhang Zhongkai , Liu Jiangjiang , Shi Peng , Lin Qijing 
Published: November 2022

AbstractFlexible temperature sensors have been extensively investigated due to their prospect of wide application in various flexible electronic products. However, most of the current flexible temperature sensors only work well in a narrow temperature range, with their application at high or low temperatures still being a big challenge. This work proposes a flexible thermocouple temperature sensor based on aerogel blanket substrate, the temperature-sensitive layer of which uses the screen-printing technology to prepare indium oxide and indium tin oxide. It has good temperature sensitivity, with the test sensitivity reaching 226.7μV °C−1. Most importantly, it can work in a wide temperature range, from extremely low temperatures down to liquid nitrogen temperature to high temperatures up to 1200 °C, which is difficult to be achieved by other existing flexible temperature sensors. This temperature sensor has huge application potential in biomedicine, aerospace and other fields.
Reduction of mutual coupling in a microstrip array antenna with circular polarization in the C-frequency band using a combination of DGS and EBG methods
Authors: Shirpay A , Rohaninezhad M R , Tavakoli M , Zarezadeh E 
Published: November 2022

Abstract
In this study, in the first stage, an antenna with circular polarization was designed with the technique of cutting the corners of radiation patches. Then a hybrid structure with DGS and EBG methods was presented. For this purpose, the designed structure of the combination of DGS and EBG, which was designed to reduce mutual coupling, was placed between the radiating elements of the antenna. This method is implemented on a microstrip antenna. The reduction of the coupling of this structure is based on the creation of a magnetic band gap. All simulation was performed numerically by CST Microwave Studio software. The simulation results showed that this structure, unlike previous structures, improves all the characteristics of the antenna, such as the antenna gain, antenna radiation efficiency, and antenna envelope correlation coefficient. Also, the resonant frequency of the antenna is 6.35 GHz, which reduces the coupling by 36.5 dB by placing the designed structure between the radiating elements of the antenna.
Representing collective thinking through cognitive networks
Authors: Duarte Denise , Guedes Gilvan R , Pereira Wesley H S , Ribeiro Rodrigo B 
Published: November 2022

AbstractThis article presents a novel quantitative approach using network features to represent community collective thinking. We propose a new function, called the cognitive affinity coefficient that maps individual cognitive links within a graph structure. This function transforms the data generated by the words chosen for an individual regarding a specific subject into an appropriate relational object for analysing cognitive networks. We apply our methodology to novel data on evocations about river floods, which allowed us to find communities inside the network according to their thinking about this subject and identify the most active individuals inside each one and, therefore, explicit their collective thinking. We also present a utility tool implemented in R, which allows the analysis of the data collected as a network.