bluuebunny/crossref_metadata_2025_split huggingface dataset:
Humour in self-translation
Authors: Dore Margherita 
Published: September 2022

Abstract
This introduction sets off by reflecting on migration in relation to multilingualism and self-translation. It explores the migration phenomenon over time but focuses in particular on the 21st century and the way migrants seek integration into the hosting country while, at the same time, remaining profoundly connected to their culture and language of origin. This aspect is not only advocated, but it is also praised as a means of encouraging insiders to be more open towards outsiders. It also considered important to help insiders to become more tolerant and reflect on their own identity. The second part of this chapter is instead devoted specifically to humour in self-translation, its characteristics and driving reasons. One important aspect that is also emphasised here is that humour self-translation is a virtually unexplored area in both Humour Studies and Translation Studies, and this volume seeks to contribute to filling this gap. The chapter concludes with an overview of the contributions included herein. It also offers a reflection on the way humour and self-translation can jointly be explored to better understand how these two natural human traits shape and are shaped by reality.
Punning herself
Authors: Richters Marlisa A. 
Published: September 2022

Abstract

Plays on words, humorous or not, pose serious challenges to the translator, as Dirk Delabastita (1997), among many others, has stated. Self-translators know the intended communicative effect behind the puns, giving them a privileged perspective regarding their translation. This is the case with author Nancy Huston, born in 1953 in Alberta, Canada, and residing permanently in France since 1973. She started using self-translation consistently after discovering she could thereby improve her work, which regularly includes wordplays.
This work looks at puns from two of her earlier self-translated novels, comparing Huston’s English and French version to see how she deals with the complexity they entail. Following Delabastita’s typology of puns (1996: 128, 2014: 604), Huston’s puns are both vertical and horizontal wordplay, display paronymy and homophony as well as many more aspects. This chapter comments on cases of pun-to-pun translation, pun-to-alliteration, pun-to-no pun, etc. Huston herself claims she desires the two versions to be as alike as possible (Mi-Kung YI, 2001), and this article aims at confirming this.
From traduttore, traditore to traduttore, creatore
Authors: Friedman Ursula Deser 
Published: September 2022

Abstract
This paper presents cases of un-translation, substitution, and creative augmentation in the self-translated English-Mandarin short stories of Ha Jin and Pai Hsien-yung, ultimately problematizing the un-translatability of humour in literary (self-)translation. Ha Jin (1956–) augments the Chinese language translated text of his short stories “In the Crossfire/Liang Mian Jia Gong 两面夹攻” and “A Good Fall”/落地 Luo di from his 2010 anthology A Good Fall by adding wordplay, aphorisms, and other splashes of creative humour not present in the English language source text. In the English translation of his short story “A Sky Full of Bright, Twinkling Stars/Man tian li liang jingjing de xingxing 满天里亮晶晶的星星” from his self-translated anthology Taipei People/Taibei Ren (1971), Pai Hsien-yung (1937–) translates character names phonetically to preserve the source text puns, and domesticates the source text for the English-speaking readership by dividing long, cascading sentences into short staccato phrases. Through these case studies of creative subversion in self-translation, I argue that self-translators destabilise their source texts and invite the possibility for innumerable possible translated iterations.
Humour, language variation and self-translation in stand-up comedy
Authors: Dore Margherita 
Published: September 2022

Abstract
This chapter concentrates on self-translation, humour and language variation in Marsha De Salvatore’s stand-up routines. She is a professional Italian American comedian whose one-woman shows talk about her chronic illness (i.e., Beta-Thalassemia Major) and her life in Italy as a “half-expatriate”.
By comparing the original English scripts and the Italian scripts she self-translated, this study explores the mechanisms at work in creating humorous scripts in two different languages. The textual analysis is supported by De Salvatore’s answers during a semi-structured interview. The findings show that when discussing her chronic illness, De Salvatore consciously mixes tragedy and comedy to defy stereotypes about sick people, win over her audience and persuade them to donate blood. In her show about her life, she relies mostly on disparaging humorous comments targeting herself, her friends and her Calabrian family. Interestingly, her scripts in English are mainly constructed on the opposition between English and Italian (and Calabrian) language and culture. Conversely, her self-translated scripts recast this opposition between Italian and Calabrian, albeit retaining some English, since her audience normally has a good grasp of it. Besides, the Italian versions appear tamer when dealing with topics such as sex, which may depend on the fact that this culture is generally more sensitive to taboo humour. However, localising and compensatory strategies make the Italian scripts as effective as the English versions in triggering humour and successfully creating comedian-audience affiliation.
iTranslate or iWrite?
Authors: Sasaki Anna 
Published: September 2022

Abstract
This chapter argues that the translation of humour can become a criterion for defining the self-translation of a children’s book. Not all literature written in a foreign language by the same author can be considered translation. In my chapter I propose a verification criterion for the translation of children’s literature by the original author based on the re-creation of humorous effects in translation. Humour in picture books comes in the form of anecdotes and allusions. The successful re-creation of humour preserves the entertainment value of picture books and answers theoretical claims concerning children’s literature translation. The loss of humorous effect results in the prevalence of the pedagogical value over the entertainment value. Such writing could be regarded as a writing that loses the source-text-target-text relationship. My findings are framed in Toury’s terms of acceptability and adequacy.
Multimodal strategies of creation and self-translation of humorous discourse in image-macro memes
Authors: Iaia Pietro Luigi 
Published: September 2022

Abstract
Image-macro memes are highly dynamic multimodal compositions that propagate online, mostly for humorous purposes. Yet, despite their increasing popularity and transformation into an important part of human community and social life, and notwithstanding the expansion of their areas of application, this novel mainstream phenomenon still deserves more recognition from scholars. This chapter focuses on the processes of creation and self-translation of memes by exploring the strategies of textualization and re-textualization that were activated by a number of undergraduate students from the University of Salento, Italy. This case study is divided into two main phases. In the first phase, participants were asked to create memes for Italian receivers, trying to provoke laughter through culture-bound stereotypes; in phase two, their productions had to be re-elaborated and reformulated to become accessible to international viewers. The comparison between the original versions and their resemiotisations will shed light on the reasons that led subjects to change the visual and/or verbal dimensions of their memes. The analysis will investigate to what extent modifications are meant to adapt the original oppositions between ‘possible/impossible’ or ‘normal/violation’ cognitive scripts, as well as the original representations of culture-bound pop icons. Finally, the examination of the multimodal re-arrangements will also inform a discussion on the influence of the cognitive construct of ‘implied receivers’ on the selection of the language and images that are expected to convey the senders’ intentionality through the hybrid texts under discussion.
E-shaped patch antenna for GaAs-based broadband THz detectors
Authors: Lian X R , Wang K , Bai X Q , Bai P , Li X H , Huang S H , Song W J , Shen W Z , Xu G Y , Zhang Y H 
Published: September 2022

Abstract
High-performance broadband terahertz (THz) photodetectors are of great interest driven by lots of applications. To improve the performance of the THz photodetector in a wide spectral coverage, the E-shaped patch antenna with three slots is proposed and studied in theory. GaAs-based homojunction interfacial work function internal photoemission (HIWIP) broadband THz detector is used as an example to demonstrate the effect in broadband detection. Due to the combined effect of the antenna and the microcavity, E-shaped patch antenna microcavity HIWIP increase the optical coupling efficiency in a broadband range from 2.1–20 THz by an average of four times. Considering the requirement to reduce the dark current, the etched E-shaped patch antenna microcavity HIWIP only retaining the active region beneath the antenna is further investigated. In contrast to the reference HIWIP, the coupling efficiency is improved by an average of 15 times in 2.3–20 THz. The high coupling efficiency of both structures leads to the significant improvement of the responsivity, noise equivalent power, and detectivity in a wide spectral coverage theoretically, which makes it possible to realize higher operating temperatures. Such a design scheme of E-shaped patch antenna structure provides a guideline for broadband THz detectors and can be used for other THz detectors.
The case of itinerant magnetism in CaMn2Al10: self-consistent renormalisation (SCR) theory study
Authors: Devanarayanan Bharathiganesh , Sharma Akariti , Patel Pratik D , Singh Navinder 
Published: September 2022

Abstract
We have applied the powerful self-consistent renormalization theory of spin fluctuations for the system CaMn2Al10 discovered in 2015 and was conjectured to be an itinerant magnet. We have calculated the inverse static i.e. (paramagnetic) susceptibility and have compared it with the experimental data (Steinke et al 2015 Phys. Rev. B 92 020413). The agreement is very good. We have calculated spin fluctuations at various temperatures and have also estimated the strength of the electronic correlation i.e. (U = 0.3136 eV) in the Hubbard Hamiltonian. Based on our quantitative explanation of the inverse static i.e. (paramagnetic) susceptibility data within the framework of self-consistent renormalization theory, we can decisively conclude CaMn2Al10 exhibits the phenomena of itinerant magnetism. Further, our density functional theory (DFT) and DFT + U calculations corroborate the strong Mn-Al hybridization which is the key to the itinerant magnetism in this system. Our estimated correlations strength will provide a foundation for further studies of itinerant magnetism in this system.
Statistical learning modeling based health indicator construction for machine condition monitoring
Authors: Deng Yanqing , Hou Bingchang , Shen Changqing , Wang Dong 
Published: September 2022

Abstract
Machine condition monitoring aims to evaluate machine health conditions by analyzing machine vibration signals, which is helpful to make timely maintenance decisions and prevent unexpected accidents. Currently, constructions of virtual and physical health indicators (HIs) are commonly used methods for machine condition monitoring. However, most classic physical and virtual HIs lack inherent thresholds, robustness, monotonicity, and interpretability for machine condition monitoring. In this paper, a statistical learning modeling based HI construction method for machine condition monitoring is proposed to solve these problems. Firstly, a statistical decision theory is suggested to clearly describe a machine condition monitoring objective, and subsequently shapes of square envelope spectra are robustly modeled by using a parametric statistical model called a penalized B-spline approximation. Further, an interpretable HI named B-spline weight HI (BSWHI) as well as an inherent statistical threshold is accordingly constructed based on the Mahalanobis distance between B-spline weights of testing samples and a healthy sample. Experiments on bearing and gear run-to-failure datasets are studied to show that the proposed BSWHI and its inherent statistical threshold can effectively detect early machine faults and simultaneously provide monotonic degradation assessment trends. The proposed interpretable BSWHI has achieved a substantial improvement over existing classic HIs.
Arbitrary position 3D tomography for practical application in combustion diagnostics
Authors: Sanned David , Lindström Johan , Roth Adrian , Aldén Marcus , Richter Mattias 
Published: September 2022

Abstract
This work aims to make three-dimensional (3D) tomographic techniques more flexible and accessible to in-situ measurements in practical apparatus by allowing arbitrary camera placements that benefit applications with more restrictive optical access. A highly customizable, in-house developed tomographic method is presented, applying smoothness priors through Laplacian matrices and hull constraints based on 3D space carving. The goal of this paper is to showcase a reconstruction method with full user control that can be adopted to various 3D field reconstructions. Simulations and experimental measurements of unsteady premixed CH4/air and ethanol (C2H5OH) diffusion pool flames were evaluated, comparing arbitrarily placed cameras around the probed domain to the more commonly used in-plane-half-circle camera arrangement. Reconstructions reproduced expected topological field features for both flame types. Results showed slight decrease in reconstruction quality for arbitrarily placed cameras compared to in-plane-half-circle arrangement. However, at lower numbers of camera views (N
q ⩽ 6) arbitrary placement showed better results. The introduced methodology will be useful for optically limited setups in terms of handling a priori information, camera placement and 3D field evaluation.
A conversion-type lithium artificial synapse with dispersed nano-silica fabricated by UV-curing method
Authors: Li Feifei , Zhang Jiani , Ling Huiqin , Hang Tao , Li Ming , Wu Yunwen 
Published: September 2022

Abstract
The rapid growth of information puts forward new requirements for computer including denser memory capacity and faster response beyond the traditional von Neumann architecture. One promising strategy is to employ novel computing devices such as artificial synapses (AS). Here, an Au/LPSE-SiO2/Si AS (LPSE-SiO2 AS) with a simple sandwich structure was fabricated by UV curing. LPSE-SiO2 AS emulated synaptic plasticity including excitatory postsynaptic current, paired-pulse facilitation, and spike-dependent plasticity. It also simulated the memory strengthening and forgetting analogue to biological system. The realization of synaptic plasticity is due to the homogeneously dispersed nano-silica in LPSE, which acts as lithium ions trapping center and conducts a reversible electrochemical conversion reaction with Li ions with pulse stimulation. These results indicate the potential for LPSE-SiO2 AS in future large-scale integrated neuromorphic networks.
Single event effects prediction of MOSFET device using deep learning
Authors: Zhao Rong , Wang Shulong , Duan Xiaoling , Cao Xianfa , Ma Lan , Chen Shupeng , Liu Hongxia , Chen Yanning , Zhang Haifeng , Zhao Yang 
Published: September 2022

Abstract
Single event effect (SEE) is an important problem in the reliability research of integrated circuits. The study of SEE of traditional MOSFET devices is mainly based on simulation software, which is characterized by slow simulation speed, large computation and time-consuming. In this paper, a SEE research method based on deep learning is proposed. The method relies on 28 nm MOSFET. The complete drain transient current pulse, transient current peak value and total collected charge can be obtained in a short time by inputting relevant parameters that affect the SEE. The accuracy of the network for predicting transient current peak and total collected charge is 96.95% and 97.53% respectively, and the mean goodness of fit of the network for predicting the drain transient current pulse curve is 0.985. Compared with TCAD Sentaurus software, the simulation speed is increased by 5.89 × 103 and 1.50 × 103 times respectively. This method has good prediction effect and provides a new possibility for the study of SEE.
Room temperature operated composite SnS–ZnS heterojunction based sensor for sub-ppm ethanol detection
Authors: Lalwani Suraj Kumar , Debnath Ajit , Sunny  
Published: September 2022

Abstract
The present work demonstrates the potential of metal sulphide SnS–ZnS composite towards detection of low concentration (sub ppm) ethanol at room temperature (27 °C). The fabricated sensor has shown excellent performance in terms of % response of 56.58% at 100 ppb owing to the low crystallite size observed from the x-ray diffraction (XRD) characterization. The sensor has been exposed to ethanol under relative humidity (RH) range of 40% RH to 80% RH. The sensor has shown fast response and appreciable selectivity towards ethanol. The elemental composition and valence states of the composite formed are shown using energy dispersive x-ray analysis and x-ray photoelectron spectroscopy. The excellent sensing behavior is also supposed to be contributed due to SnS–ZnS p-n heterojunction formation. XRD of the prepared sample has been done to find the crystal structure and crystallite size. Further, field emission scanning electron microscopy results have confirmed the low particle size of the sample which complements the high sensitivity of the sensor.
M3ResU-Net: a deep residual network for multi-center colorectal polyp segmentation based on multi-scale learning and attention mechanism
Authors: Fu Junhu , Lin Shengli , Zhou Pinghong , Guo Yi , Wang Yuanyuan 
Published: September 2022

Abstract
Colorectal polyps are considered as an important precursor of colorectal cancer (CRC) in clinical diagnosis. A network automatically and accurately segmenting polyps can recognize, locate and finally help to remove polyps, greatly reducing the misdiagnosis rate. Although many neural networks for polyp segmentation have been proposed, there still exist some difficulties including the diversity of image backgrounds, the jelly effect, and the various shapes and sizes of different polyps. These factors lead to the segmentation accuracy remaining to be improved. In this paper, we propose M3ResU-Net including multi-scale learning and attention mechanisms, aiming to segment multi-center colorectal polyps. First, we implement the contrast limited adaptive histogram equalization (CLAHE) and data augmentation for multi-center data. Then, channel and spatial attention mechanisms are introduced to focus on polyp features and suppress interference features. Finally, in order to balance small target segmentation and the acquisition of global information, multi-scale learning with dilated convolutions is employed. We compared other five polyp segmentation methods on three publicly available datasets. In single-center experiments, M3ResU-Net reaches a Dice similarity coefficient (DSC) exceeding that of the best compared method by over 2%. In various multi-center experiments, M3ResU-Net all achieves a DSC over 0.8. The results demonstrate that M3ResU-Net is capable of assisting clinicians in polyp segmentation in the field of colonoscopy, which provides important and reliable support to improve diagnostic efficiency.
An unsupervised automated paradigm for artifact removal from electrodermal activity in an uncontrolled clinical setting
Authors: Subramanian Sandya , Tseng Bryan , Barbieri Riccardo , Brown Emery N 
Published: September 2022

Abstract

Objective. Electrodermal activity (EDA) reflects sympathetic nervous system activity through sweating-related changes in skin conductance and could be used in clinical settings in which patients cannot self-report pain, such as during surgery or when in a coma. To enable EDA data to be used robustly in clinical settings, we need to develop artifact detection and removal frameworks that can handle the types of interference experienced in clinical settings while salvaging as much useful information as possible. Approach. In this study, we collected EDA data from 70 subjects while they were undergoing surgery in the operating room. We then built a fully automated artifact removal framework to remove the heavy artifacts that resulted from the use of surgical electrocautery during the surgery and compared it to two existing state-of-the-art methods for artifact removal from EDA data. This automated framework consisted of first utilizing three unsupervised machine learning methods for anomaly detection, and then customizing the threshold to separate artifact for each data instance by taking advantage of the statistical properties of the artifact in that data instance. We also created simulated surgical data by introducing artifacts into cleaned surgical data and measured the performance of all three methods in removing it. Main results. Our method achieved the highest overall accuracy and precision and lowest overall error on simulated data. One of the other methods prioritized high sensitivity while sacrificing specificity and precision, while the other had low sensitivity, high error, and left behind several artifacts. These results were qualitatively similar between the simulated data instances and operating room data instances. Significance. Our framework allows for robust removal of heavy artifact from EDA data in clinical settings such as surgery, which is the first step to enable clinical integration of EDA as part of standard monitoring.
A fast sparse least squares support vector machine hysteresis model for piezoelectric actuator
Authors: Mao Xuefei , Du Haocheng , Sun Siwei , Liu Xiangdong , Shan Jinjun , Feng Ying 
Published: September 2022

Abstract
The inherent nonlinearities of piezoelectric actuator (PEA), especially hysteresis, greatly reduce the tracking performance of PEA. With a lot of computing resources consumed in the predicting process, the hysteresis modeling method of PEA based on the least-squares support vector machine (LSSVM) cannot be used for hysteresis compensation at high frequency. To solve this problem, a sequential selection approximate algorithm is proposed to obtain a fast sparse LSSVM (SLSSVM) hysteresis model. The SLSSVM model’s support vectors are only 6.8% of the original LSSVM model, by which the modeling speed and calculation speed are greatly improved. The experimental results show that the SLSSVM model improves the tracking accuracy when used in hybrid control system, especially for high frequency trajectories.
Shunts vs networks: tuning and comparison of centralized and decentralized piezoelectric vibration absorbers
Authors: Raze G , Dietrich J , Lossouarn B , Kerschen G 
Published: September 2022

Abstract
This work develops a unified modeling framework for piezoelectric structures controlled by passive shunts connected to a single transducer and/or networks interconnecting multiple transducers. A common tuning procedure for these different control approaches, termed decentralized and centralized approaches, respectively, is proposed. The generic model is then used to compare them in terms of vibration mitigation performance. It is shown that decentralization can be detrimental to performance in general. Digital vibration absorbers are then leveraged to realize the shunts and/or networks. In this regard, the proposed tuning procedure solely relies on characteristics that can be identified from the digital units of these absorbers. The theoretical developments are numerically and experimentally validated on piezoelectric beams.