bluuebunny/crossref_metadata_2025_split huggingface dataset:
Language use in pop culture over three decades
Authors: Csomay Eniko , Young Ryan 
Published: September 2020

AbstractAnalyzing variation in language features in literature and telecinematic discourse provides valuable insights into society’s shifting values and perspectives. In this study, we carry out a keyword analysis on the language of three series ofStar Trektelevision dialogues, broadcast in the 1960s, 1980s, and 1990s, from two perspectives: (i) keywords across the three series highlighting words that are unique to one series in contrast to the other two, providing insights about changes of foci across time; (ii) keywords in relation to gender depicting potential differences in gender roles and how these may change through time across the series.
A linguistic typology of American television
Authors: Berber Sardinha Tony , Veirano Pinto Marcia 
Published: September 2020

AbstractThis paper presents the first entirely linguistic typology of contemporary American television, derived from a multi-dimensional (MD) analysis of the USTV corpus. The USTV corpus comprises 930 texts from 191 different TV programs, classified into 31 different registers (including nine telecinematic ones: drama series, miniseries, movies, sitcoms, soap operas, general animation, children’s animation, short-feature animation, and children’s and teens’ shows). The linguistic typology we present in this study is based on the linguistic characteristics present in the individual programs, with no a priori textual categorizations. A cluster analysis grouped the individual programs into clusters that shared similar dimensional profiles. The resulting typology comprises nine different text types – namely Presentation of information, Opinion and discussion, Analysis and debate, Description, Interactive recount, Engaging demonstration, Playful discourse, Simplified interaction, and Simulated conversation. The paper discusses and illustrates each text type and considers how telecinematic discourse relates to each of them.
Why are there growing divisions between traditional grammars and theoretical and experimental linguistic works (and how can they be overcome)?
Authors: Struckmeier Volker 
Published: September 2020

AbstractThe present article discusses a worrying development, whereby some traditional grammars become less aligned with the findings of linguistics research. The article gives examples of such discrepancies, illustrated here on the basis of the description of German. It also aims to describe a possible cause for this development. On the one hand, it seems that the grammatical descriptions found in school grammars have in some cases ceased to reflect discussions in (and formats of) current theories of grammar. They have also chosen, to a degree, to ignore empirical findings made by linguistic research. However, the article seeks to demonstrate that this may in large part be caused by the nature of the linguistic theories and experimental research approaches themselves, as well as the presentation of these projects in the literature: The granularity of the descriptions (and the objects described) that theoretical and experimental research assess simply does not match the kinds of generalisations that traditional grammars (school grammars, especially) aim for. To illustrate this point, specific issues with linguistic theories, methods and conventions are presented, which may make it difficult for school grammars to react to the results in a principled way.
Probing the era of reheating for reconstructed inflationary potential in the RS II braneworld
Authors: Bhattacharya Sukannya , Das Kumar , Gangopadhyay Mayukh R 
Published: September 2020

Abstract
We analyse the epoch of reheating after an inflationary phase in the Randall–Sundrum type-II braneworld, where we did not consider any particular model of inflation, but rather reconstructed the inflationary potential solving the flow equations using Monte Carlo (MC) approach. It is shown numerically that a potential conceived through the MC reconstruction technique can be represented by an effective potential as a function of the number of e-foldings (N). Then, the epoch of reheating is studied for this reconstructed potential. The relation between the reheating temperature (T
reh) and the five-dimensional Planck mass (M
5) is established. Moreover, it is argued that there is a stringent bound on the critical reheating temperature that also translates to a tight bound on M
5.
An implantable microelectrode array for chronic in vivo epiretinal stimulation of the rat retina
Authors: Yoon E , Koo B , Wong J , Elyahoodayan S , Weiland J D , Lee C D , Petrossians A , Meng E 
Published: September 2020

Abstract
The design, fabrication, and testing of a microelectrode array for chronic in vivo stimulation of the rat retina is presented. Epiretinal positioning of the array introduced design challenges associated with the surgical implantation approach into the rat ocular orbit. These anatomical and surgical challenges were overcome using microfabrication of thin-film Parylene C and platinum to create the array followed by thermal post-processing steps to achieve the required array geometry. An electroplated platinum-iridium coating was employed to increase the electrode charge storage capacity and then verified in benchtop electrochemical characterization. Preliminary in vivo implantations with sham devices containing no metal revealed chronic biocompatibility (up to 6 weeks) and acute trials with functional arrays illustrated device robustness against surgical trauma. This work represents the first epiretinal implant development for the rat animal model via a suitable soft neural interface device enabled through polymer MEMS micromachining.
Numerical study of biosensor based on α-MoO3/Au hyperbolic metamaterial at visible frequencies
Authors: Wei Chenwei , Cen Mengjia , Chui Hsiang-Chen , Cao Tun 
Published: September 2020

Abstract
Hyperbolic metamaterials (HMMs) attract increasing attentions due to their unique optical properties and offer new approaches for realizing novel functionalities in emerging photonic meta-devices. Tunable is one of the most attractive optical properties since multifunction optical devices are one of the important research directions. So far, most active HMMs working in the visible region are based on the combination of metal and phase-change chalcogenides and the performance is limited by the optical losses of phase-change chalcogenides and interdiffusion of the metals with phase-change chalcogenides. In this work, incorporating α-phase molybdenum trioxide (α-MoO3) and Au, an active and low loss HMM device is proposed in the visible region and can effectively overcome the shortcoming. A tunable plasmonic biosensor based on prism coupled α-MoO3/Au HMM is further designed by enhancing Goos–Hänchen (GH) shift, since GH shift is highly sensitive to the refractive index of the substrate. The calculated refractive index sensitivity of this proposed biosensor is of the order of 106 nm/refractive index unit. The proposed approach offers new direction for potential application in the development of the active ultrasensitive biosensor operating at visible range.
All-MBE grown InAs/GaAs quantum dot lasers with thin Ge buffer layer on Si substrates
Authors: Yang Junjie , Liu Zizhuo , Jurczak Pamela , Tang Mingchu , Li Keshuang , Pan Shujie , Sanchez Ana , Beanland Richard , Zhang Jin-Chuan , Wang Huan , Liu Fengqi , Li Zhibo , Shutts Samuel , Smowton Peter , Chen Siming , Seeds Alwyn , Liu Huiyun 
Published: September 2020

Abstract
A high-performance III–V quantum-dot (QD) laser monolithically grown on Si is one of the most promising candidates for commercially viable Si-based lasers. Great efforts have been made to overcome the challenges due to the heteroepitaxial growth, including threading dislocations and anti-phase boundaries, by growing a more than 2 µm thick III–V buffer layer. However, this relatively thick III–V buffer layer causes the formation of thermal cracks in III–V epi-layers, and hence a low yield of Si-based optoelectronic devices. In this paper, we demonstrate a usage of thin Ge buffer layer to replace the initial part of GaAs buffer layer on Si to reduce the overall thickness of the structure, while maintaining a low density of defects in III–V layers and hence the performance of the InAs/GaAs QD laser. A very high operating temperature of 130 °C has been demonstrated for an InAs/GaAs QD laser by this approach.
Probing the martensite transition and thermoelectric properties of Co
x
TaZ (Z
= Si, Ge, Sn and x
= 1, 2): a study based on density functional theory
Authors: Dutt Rajeev , Pandey Dhanshree , Chakrabarti Aparna 
Published: September 2020

Abstract
In this work, using density functional theory based electronic structure calculations, we carry out a comparative study of geometric, mechanical, electronic, magnetic, and thermoelectric properties of Co
x
TaZ alloys, where Z = Si, Ge and Sn and x = 1 and 2. In the present study, a systematic approach has been taken to perform calculations to probe the possibility of existence of a tetragonal (martensite) phase in these alloys and also to perform a comparative study of various physical properties of the six systems, mentioned above, in the cubic and possible tetragonal phases. From our calculations, a tetragonal phase has been found to be stable up to about 400 K in case of Co2TaSi and Co2TaGe alloys, and up to about 115 K for Co2TaSn, indicating the presence of room temperature cubic phase in the latter alloy unlike the former two. Further, the results based on the energetics and electronic structure have been found to corroborate well with the elastic properties. All the above-mentioned full Heusler alloys (FHAs) show magnetic behavior with metallicity in both the phases. However, their half Heusler counterparts exhibit non-magnetic semi-conducting behavior in the cubic phase. We calculate and compare the thermoelectric properties, in detail, of all the materials in the cubic and possible tetragonal phases. In the cubic phase, the half Heusler alloys exhibit improved thermoelectric properties compared to the respective FHAs. Furthermore, it is observed that the FHAs exhibit higher (by about an order of magnitude) values of Seebeck coefficients in their cubic phases, compared to those in the tetragonal phases (which are of the order of only a few micro-volts/Kelvin). The observed behaviors of the transport properties of the probed materials have been analyzed using the topology of the Fermi surface.
Elliptocyte detection technology based on super-resolution algorithms for a lensless imaging system
Authors: Li Jianwei , Dai Li , Yu Ningmei , Li Zhengpeng , Li Shuaijun 
Published: September 2020

Abstract
As typical poikilocytes, elliptocytes can indicate underlying diseases and are an important additional diagnostic parameter. The current method is to use a microscope for manual analysis of blood smears, which is non-automatic, time-consuming and requires skilled technicians. Lab-on-a-chip technology using a lensless imaging system provides a better solution. However, diffraction effects and low resolution are the two main problems faced by lensless imaging systems. In this paper, Fresnel diffraction at a straight edge is used to analyse the relationship between the red blood cell edge and diffraction rings. First, the diffraction characteristics of red blood cell edges are given. Next, the measurement accuracy is improved. The super-resolution algorithm proposed in this paper can make the measurement accuracy reach at least 1% of the pixel size, which can meet the needs of elliptocyte detection. Then, the complete elliptocyte detection algorithm is given. Finally, by analysing the diffraction characteristics of a typical elliptocyte in detail, a very good match with the elliptocyte images is achieved under the microscope. This proves that the detection technology is effective.
PV-Tower solar cell for small footprint photovoltaic energy harvesting for the internet of things application
Authors: Prakoso Ari Bimo , Rusli  , Wang Jianxiong , Lu Chenjin , Wang Hong 
Published: September 2020

Abstract
Development of Internet-of-Things requires the deployment of self-powered wireless sensor nodes (WSN). Towards this end, photovoltaic cells are often used to harvest ambient light energy. On the other hand, it is desirable to reduce the size of the WSN circuits as much as possible. However, WSN miniaturization will lead to less area available for solar cells and consequently, insufficient energy harvested to power the WSN. In this work, we develop a PV-Tower solar cell concept that offers a large active surface area for light absorption, while occupying only a small footprint. We demonstrate silicon-based PV-Tower solar cells with footprint areas of 0.2 mm2, 0.4 mm2, and 0.6 mm2, which can generate ≈80 times more power than conventional solar cells over the same footprint. We have also fabricated a small footprint PV-Tower module prototype that comprises 10 PV-Tower solar cells connected in series, which exhibits an open circuit voltage of 5.1 V. At the maximum power point, the module can deliver a voltage of 3.6 V and a power of ≈66.7 mW, which translates to an output power per footprint of ≈78.5 mW cm−2. By optimizing the module design, we estimate that there is room to significantly reduce its footprint and increase the output power per footprint by ≈10 times to 785 mW cm−2. The results show that the PV-Tower solar cell can serve as a compact small footprint photovoltaic energy harvesting device that can address the physical size constraints posed by miniaturization of the WSN circuit.
A study on the surface correction of large format infrared detectors
Authors: Zhang Wei-ting , Chen Xing , Ye Zhen-hua 
Published: September 2020

Abstract
Large format hybrid infrared focal array detectors, which require a wide range and high resolution, are of significant technical importance for earth observation systems and scientific space programmes. A typical large hybrid infrared focal plane array (IRFPA) detector formed by a detector chip is directly hybridized to a silicon readout integrated circuit (Si-ROIC) via indium bumps. However, for a large format IRFPA detector, the connection rate of the indium bumps strongly depends on the warpage of the Si-ROIC and the detector chip, which usually results from technological processes. In this paper, a surface correction structure is proposed to optimize the warpage of the Si-ROIC and the detector chip before flip-chip. The warpage of the Si-ROIC is analysed by the finite element method. The simulation results are in good agreement with the experiment. After optimization, the warpage of a 2048 × 2048 Si-ROIC decreased from 13 μm to less than 3 μm. Thus, it is beneficial to improve the IRFPA bump connection rate. Compared with traditional growth stress films, this method is more flexible and has easy accessibility. Eventually, it could enhance the stability of the large format IRFPA detector.
Double-valued strong-coupling corrections to Bardeen–Cooper–Schrieffer ratios
Authors: Talantsev E F 
Published: September 2020

Abstract
The experimental discovery of near-room-temperature (NRT) superconductivity in highlycompressed H3S, LaH10 and YH6 has restored fundamental interest in the electron–phonon pairing mechanism in superconductors. One of the prerequisites of phonon-mediated NRT superconductivity in highly compressed hydrides is strong electron–phonon interactions, which can be quantified by dimensionless ratios of the Bardeen–Cooper–Schrieffer (BCS) theory vs

k
B

T
c

/

ℏ

ω

l
n

variable, where Tc
is the critical temperature and

ω

l
n

is the logarithmic phonon frequency (Mitrovic et al 1984 Phys. Rev. B 29 184). However, all known strong-coupling correction functions for the BCS ratios are applicable for

k
B

T
c

/

ℏ

ω

l
n

< 0.20, which is not a high enough

k
B

T
c

/

ℏ

ω

l
n

range for NRT superconductors, because the latter exhibit variable values of 0.13 <

k
B

T
c

/

ℏ

ω

l
n

< 0.32. In this paper, we reanalyze the full experimental dataset (including data for highly compressed H3S) and find that the strong-coupling correction functions for the gap-to-critical-temperature ratio and for the specific-heat-jump ratio are double-valued nearly linear functions of

k
B

T
c

/

ℏ

ω

l
n

.
On the long-term stability of space-time crystals
Authors: Smits J , Stoof H T C , van der Straten P 
Published: September 2020

Abstract
We investigate a space-time crystal in a superfluid Bose gas. Using a well-controlled periodic drive we excite only one crystalline mode in the system, which can be accurately modeled in the rotating frame of the drive. Using holographic imaging we observe the stability of the crystal over an extended period of time and show the robustness of its structure in both space and time. By introducing a fourth-order term in the Hamiltonian we show that the crystal stabilizes at a fixed number of quanta. The results of the model are compared to the experimental data and show good agreement, with a small number of free parameters. The results yield insights in the long-term stability of the crystal, which can only be obtained by the combination of the extended control in the experiment and the nearly ab initio character of the model. From the model we derive a phase diagram of the system, which can be exploited in the future to study the phase transitions for this new state of matter in even more detail.
Semi-supervised Deep Learning in Motor Imagery-Based Brain-Computer Interfaces with Stacked Variational Autoencoder
Authors: Chen Junjian , Yu Zhuliang , Gu Zhenghui 
Published: September 2020

Abstract
Recently, deep learning methods have contributed to the development of motor imagery (MI) based brain-computer interface (BCI) research. However, these methods typically focused on supervised deep learning with the labelled data and failed to learn from the unlabelled data, where additional information may be critical for performance improvement in MI decoding. To address this problem, we propose a semi-supervised deep learning method based on the stacked variational autoencoder (SVAE) for MI decoding, where the input to the network is an envelope representation of EEG signal. Under the framework of SVAE, the labelled training data and unlabelled test data can be trained collaboratively. Experimental evaluation on the BCI IV 2a dataset reveals that SVAE outperforms competing methods and it also yields state-of-the-art performance in decoding MI tasks. Hence, the proposed method is a promising tool in the research of the MI-based BCI system.
Robust Learning Control for a Class of Uncertain Linear Motor Systems
Authors: Shou Qisheng , Xia Huijie , Yan Qiuzhen , Cai Jianping , Ma Yan , Bao Zhiyan 
Published: September 2020

Abstract
The tracking problem for a class of linear motor systems with unknown input deadzone is addressed in this paper. Alignment condition is adopted to solve the initial position problem for iterative learning control systems, with the control law and learning laws being developed according to Lyapunov method. Iterative learning control technique and robust control technique are together adopted to compensate uncertainties and disturbances. The position state and velocity state can accurately track the desired trajectories over the whole interval, as the iteration number increases. In the end, a simulation example is presented to demonstrate the effectiveness of the designed control scheme.
Automatic Modeling Method Based on Bayesian Network
Authors: Han Lu , Shi Xianjun , Wang Taoyu 
Published: September 2020

Abstract
In fact, the relationship between fault and test is uncertain, and the traditional testability model cannot deal with uncertain information. Bayesian network model with uncertain information reasoning ability and self-learning ability has become a research hotspot. Aiming at the difficulty and high cost of Bayesian network testability model, a automatic modeling method based on Bayesian network was proposed. This method uses the circuit functional structure relationship characterized by EDA to provide the required conditions for the K2 algorithm, and verifies the results of the structure and parameter learning. Through this method, the Bayesian network model can continuously update the model structure and parameters by combining expert knowledge, historical experience and later use data, making the model more and more accurate. After simulation and comparison, the algorithm can effectively build a model and reduce the workload of related personnel.
Research on Harmonic Power Sharing Method Based on Intelligent Matching Virtual Harmonic Impedance
Authors: Zhu Jiaxiong , Qiang Jiang , Xiao Zhigang , Feng Chang 
Published: September 2020

Abstract
The mismatch between the feeder impedance of each parallel inverter connected to the public AC bus in the microgrid and its rated capacity will cause harmonic circulation in the system. In order to effectively suppress the harmonic circulating current and balance the power distribution among the inverter units, this paper introduces an adaptive virtual harmonic impedance controller in the harmonic domain to reshape the impedance of the system to match the feeder impedance, Dynamically adjust the harmonic current distribution, obtain the modulated wave through the measuring current and voltage double-loop control, and then drive the inverter to operate through the SPWM modulation circuit. MATLAB/Simulink simulation, the results show that the harmonic power distribution method based on virtual intelligent matching harmonic impedance raised in this paper can significantly suppress the harmonic circulating current between parallel inverter systems, and improve the quality of output voltage of parallel inverter systems. The accurate power distribution of the inverter is realized, and performance of inverter in parallel system with a nonlinear load is improved.
Consistent-Resolution Network for 3D Hand Shape Estimation from a Single RGB Image
Authors: Wu Qi , Chen Joya , Yao Zhiming , Zhou Xu , Wang Jianguo , Wang Shaonan , Yang Xianjun 
Published: September 2020

Abstract
We propose a novel method for 3D hand shape estimation from a single RGB image. Most exiting methods leverage a deep network to extract a low-resolution representation to estimate 3D coordinates, which always leads to the loss of spatial information. In contrast, we present a Consistent-Resolution Network (CRNet) to extract the same resolution representation as the original image, thus preserve more details about spatial information. Specifically, we introduce the recent high-resolution network (HRNet) to generate high-resolution feature maps, which can attain high-resolution representation of the original image. Then, we design a deconvolution module to recover this map to the size of the original image. Therefore, we can directly leverage this feature to learn the precise 2D shape and the depth map, and transfer them into 3D coordinates in the camera space. Through extensive experiments on a large real-world dataset FreiHAND, we show that our proposed method can predict precise and suitable 3D hand shape from a monocular view.
Design of Tire Damage Image Recognition System Based on Deep Learning
Authors: Zhang S Z , Wu Y H , Chang J 
Published: September 2020

Abstract
In view of the problems of low efficiency, prone to misjudgment, and complicated identification levels in the current market, the use of manual judgment methods for the cause of tire damage. A method of tire damage image recognition based on convolutional neural network algorithm is proposed, and an intelligent tire damage image recognition system is designed. Through image processing, feature extraction, classification and identification of the input tire damage image, the computer can automatically output the cause of the damage. The experimental results show the feasibility of this method and also improve the shortcomings of traditional manual judgment of the cause of tire damage.