bluuebunny/crossref_metadata_2025_split huggingface dataset:
A single case neuroimaging study of tickertape synesthesia
Authors: Hauw Fabien , El Soudany Mohamed , Rosso Charlotte , Daunizeau Jean , Cohen Laurent 
Published: July 2023

AbstractReading acquisition is enabled by deep changes in the brain’s visual system and language areas, and in the links subtending their collaboration. Disruption of those plastic processes commonly results in developmental dyslexia. However, atypical development of reading mechanisms may occasionally result in ticker-tape synesthesia (TTS), a condition described by Francis Galton in 1883 wherein individuals “see mentally in print every word that is uttered (…) as from a long imaginary strip of paper”. While reading is the bottom–up translation of letters into speech, TTS may be viewed as its opposite, the top–down translation of speech into internally visualized letters. In a series of functional MRI experiments, we studied MK, a man with TTS. We showed that a set of left-hemispheric areas were more active in MK than in controls during the perception of normal than reversed speech, including frontoparietal areas involved in speech processing, and the Visual Word Form Area, an occipitotemporal region subtending orthography. Those areas were identical to those involved in reading, supporting the construal of TTS as upended reading. Using dynamic causal modeling, we further showed that, parallel to reading, TTS induced by spoken words and pseudowords relied on top–down flow of information along distinct lexical and phonological routes, involving the middle temporal and supramarginal gyri, respectively. Future studies of TTS should shed new light on the neurodevelopmental mechanisms of reading acquisition, their variability and their disorders.
Impact of mercury on photosynthetic performance of Lemna minor: a chlorophyll fluorescence analysis
Authors: Singh Hanwant , Kumar Deepak , Soni Vineet 
Published: July 2023

AbstractThe purpose of this study was to evaluate the effectiveness of chlorophyll fluorescence analysis in detecting the effects of mercury (Hg) treatment in duckweed species Lemna minor. The results showed that Hg treatment (ranging from 0.0 to 0.4 µM) significantly impacted the plant's photosynthetic ability, with a decrease in variable chlorophyll fluorescence, energy fluxes, density of reaction centers, and performance index. Complete inhibition of electron transport was observed in plants treated with high Hg concentrations, and the quantum yield of primary photochemistry and the ratio of dissipated energy to absorption both decreased with increasing Hg concentrations. Performance Index (PI) was significantly affected by the Hg concentrations, reaching zero in plants treated with the highest Hg concentration. Overall, JIP analysis was found to be an effective tool for detecting deleterious effects of Hg in plants.
Enhanced electrocatalytic activity of fluorine doped tin oxide (FTO) by trimetallic spinel ZnMnFeO4/CoMnFeO4 nanoparticles as a hydrazine electrochemical sensor
Authors: Saei Jalal Niazi , Asadpour-Zeynali Karim 
Published: July 2023

AbstractIn the present study, ZnMnFeO4 and CoMnFeO4 tri-metallic spinel oxide nanoparticles (NPs) were provided using hydrothermal methods. The nanoparticles have been characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), Fourier transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), and electrochemical techniques. A reliable and reproducible electrochemical sensor based on ZnMnFeO4/CoMnFeO4/FTO was fabricated for rapid detection and highly sensitive determination of hydrazine by the DPV technique. It is observed that the modified electrode causes a sharp growth in the oxidation peak current and a decrease in the potential for oxidation, contrary to the bare electrode. The cyclic voltammetry technique showed that there is high electrocatalytic activity and excellent sensitivity in the suggested sensor for hydrazine oxidation. Under optimal experimental conditions, the DPV method was used for constructing the calibration curve, and a linear range of 1.23 × 10−6 M to 1.8 × 10−4 M with a limit of detection of 0.82 ± 0.09 μM was obtained. The obtained results indicate that ZnMnFeO4/CoMnFeO4/FTO nano sensors exhibit pleasant stability, reproducibility, and repeatability in hydrazine measurements. In addition, the suggested sensor was efficiently employed to ascertain the hydrazine in diverse samples of cigarette tobacco.
A fuzzy based dietary clinical decision support system for patients with multiple chronic conditions (MCCs)
Authors: Marashi-Hosseini Leila , Jafarirad Sima , Hadianfard Ali Mohammad 
Published: July 2023

AbstractDue to the multifaceted nature of Multiple Chronic Conditions (MCCs), setting a diet for these patients is complicated and time-consuming. In this study, a clinical decision support system based on fuzzy logic was modeled and evaluated to aid dietitians in adjusting the diet for patients with MCCs. Mamdani fuzzy logic with 1144 rules was applied to design the model for MCCs patients over 18 years who suffer from one or more chronic diseases, including obesity, diabetes, hypertension, hyperlipidemia, and kidney disease. One hundred nutrition records from three nutrition clinics were employed to measure the system's performance. The findings showed that the diet set by nutritionists had no statistically significant difference from the diet recommended by the fuzzy model (p > 0.05), and there was a strong correlation close to one between them. In addition, the results indicated a suitable model performance with an accuracy of about 97%. This system could adjust the diet with high accuracy as well as humans. In addition, it could increase dietitians' confidence, precision, and speed in setting the diet for MCCs patients.
Factors associated with perceived fear of future pandemics and/or epidemics: a cross-sectional study in Cyprus
Authors: Alexandrou Romina , Kyprianidou Maria , Photiou Galatia , Kassianos Angelos P. , Giannakou Konstantinos 
Published: July 2023

AbstractThis study aims to understand the levels of fear experienced by individuals regarding future pandemics and/or epidemics among the general population of Cyprus and comprehensively examine the diverse factors that influence this perceived fear. The cross-sectional study was conducted from October 1st, 2022, to February 19th, 2023. A proportionate quota sampling method was used for the recruitment, by recruiting a fixed number of participants from each age group, sex, and place of residence. The study collected information on sociodemographic and health-related characteristics, health literacy, trust, COVID-19 vaccination information, and perceived fear of future epidemics and/or pandemics using a self-administered questionnaire. The survey included 1075 participants, with 53.7% of them reporting fear of future pandemics. Logistic regression analysis revealed that women (OR = 2.37, 95% CI 1.78, 3.16) and individuals vaccinated against COVID-19 (OR = 1.57, 95% CI 1.02, 2.43) were significantly more likely to experience fear of future pandemics. Moreover, higher levels of trust (OR = 1.04, 95% CI 1.02, 1.06) and higher health literacy (OR = 1.05, 95% CI 1.03, 1.08) were associated with an increased likelihood of fearing future pandemics. Conversely, unemployment (OR = 0.30, 95% CI 0.13, 0.65) and having a postgraduate education decreased the likelihood of fearing future pandemics (OR = 0.56, 95% CI 0.34, 0.90). The linear regression model revealed that older age (β = − 0.10, 95% CI − 0.14, − 0.05) was negatively associated with a higher score of fear regarding future pandemics. Conversely, being in a vulnerable group (β = 2.02, 95% CI 0.75, 3.28) and having at least one chronic disease (β = 1.76, 95% CI 0.68, 2.84) showed positive associations with increased fear of future epidemics and/or pandemics. The findings emphasize the need for relevant authorities to prioritize mental health and disseminate information in a manner that avoids spreading fear and panic, particularly among vulnerable population groups.
A statistical package for evaluation of hybrid performance in plant breeding via genomic selection
Authors: Chen Szu-Ping , Tung Chih-Wei , Wang Pei-Hsien , Liao Chen-Tuo 
Published: July 2023

AbstractHybrid breeding employs heterosis, which could potentially improve the yield and quality of a crop. Genomic selection (GS) is a promising approach for the selection of quantitative traits in plant breeding. The main objectives of this study are to (i) propose a GS-based approach to identify potential parental lines and superior hybrid combinations from a breeding population, which is composed of hybrids produced by a half diallel mating design; (ii) develop a software package for users to carry out the proposed approach. An R package, designated EHPGS, was generated to facilitate the employment of the genomic best linear unbiased model considering additive plus dominance marker effects for the hybrid performance evaluation. The R package contains a Bayesian statistical algorithm for calculating genomic estimated breeding value (GEBVs), GEBV-based specific combining ability, general combining ability, mid-parent heterosis, and better-parent heterosis. Three datasets that have been published in literature, including pumpkin (Cucurbita maxima), maize (Zea mays), and wheat (Triticum aestivum L.), were reanalyzed to illustrate the use of EHPGS.
Application of machine learning techniques to the modeling of solubility of sugar alcohols in ionic liquids
Authors: Bakhtyari Ali , Rasoolzadeh Ali , Vaferi Behzad , Khandakar Amith 
Published: July 2023

AbstractThe current trend of chemical industries demands green processing, in particular with employing natural substances such as sugar-derived compounds. This matter has encouraged academic and industrial sections to seek new alternatives for extracting these materials. Ionic liquids (ILs) are currently paving the way for efficient extraction processes. To this end, accurate estimation of solubility data is of great importance. This study relies on machine learning methods for modeling the solubility data of sugar alcohols (SAs) in ILs. An initial relevancy analysis approved that the SA-IL equilibrium governs by the temperature, density and molecular weight of ILs, as well as the molecular weight, fusion temperature, and fusion enthalpy of SAs. Also, temperature and fusion temperature have the strongest influence on the SAs solubility in ILs. The performance of artificial neural networks (ANNs), least-squares support vector regression (LSSVR), and adaptive neuro-fuzzy inference systems (ANFIS) to predict SA solubility in ILs were compared utilizing a large databank (647 data points of 19 SAs and 21 ILs). Among the investigated models, ANFIS offered the best accuracy with an average absolute relative deviation (AARD%) of 7.43% and a coefficient of determination (R2) of 0.98359. The best performance of the ANFIS model was obtained with a cluster center radius of 0.435 when trained with 85% of the databank. Further analyses of the ANFIS model based on the leverage method revealed that this model is reliable enough due to its high level of coverage and wide range of applicability. Accordingly, this model can be effectively utilized in modeling the solubilities of SAs in ILs.
Increased attention allocation to stimuli reflecting end-states of compulsive behaviors among obsessive compulsive individuals
Authors: Basel Dana , Magen Moriah , Lazarov Amit 
Published: July 2023

AbstractAttentional research in OCD has focused solely on threat stimuli, assumed to provoke related obsessions and ensuing compulsions. OCD-related stimuli depicting the completion of compulsive acts (“end-states”) have yet to be examined. Past research also neglected to explore the reliability of tasks used. Here, attention allocation to both stimuli types was examined. Participants with high (HOC) and low (LOC) levels of obsessive–compulsive symptoms freely viewed three blocks of 30 two-by-two picture matrices, each including two OCD-related (cleaning\checking\ordering) and two neutral pictures, presented for eight seconds, while their gaze was recorded. Participants completed two task versions – one with traditional threat stimuli and one with novel stimuli signaling compulsions end-states. Only the end-state version yielded significant results, showing that HOC participants, compared to LOC participants, spent significantly more time fixating on OCD-related stimuli. Results remained significant after controlling for anxiety, stress, and depression. Task reliability was high. OCD-related stimuli signaling end-states of compulsive behavior should be incorporated in attentional research in OCD.
Catalyst-controlled stereoselective carbon–heteroatom bond formations by N-heterocyclic carbene (NHC) organocatalysis
Authors: Wang Yanyan , Liu Yonggui , Zhao Sha , Long Yijie , Wu Xingxing 
Published: July 2023

This review highlights recent advances in stereoselective carbon–heteroatom bond forming reactions, including C–N, C–O, C–S, C–F, C–P, etc., that were enabled by NHC organocatalysis with a focus on new activation modes and reactive intermediates.
Novel approach for sparse aperture inverse synthetic aperture radar imaging via improved alternating direction method of multipliers algorithm
Authors: Yang Jiaxing , Wang Yong , Ma Yu 
Published: July 2023

AbstractAs a new algorithm to achieve sparse aperture inverse synthetic aperture radar (SA‐ISAR) imaging, the alternating direction method of multipliers (ADMM) suffers from selection of model parameters and the inability to discriminate the target and non‐target components. Therefore, an improved ADMM (I‐ADMM) algorithm is proposed to solve these problems. First, the particle swarm optimisation (PSO) algorithm is utilised to obtain the optimal model parameters. Aiming to adequately preserve the target's shape information in the ISAR image, a modified image entropy (IE) is proposed to be the objective function of the PSO. Then, a new regularisation function is obtained from the ADMM based ISAR image. The proposed algorithm can enhance the target components and suppress the non‐target components by utilising the regularisation function. Finally, results based on the simulated and measured data show that the proposed I‐ADMM algorithm not only achieves at least 9.4% improvement in IE but also greatly improves the image quality as visually compared with the traditional ADMM algorithm which validates the effectiveness and superiority of the proposed algorithm. [Correction added on 13/09/23, after first online publication: In the following sentence in abstract “Finally, results based on… the proposed algorithm.” 10% was changed as 9.4%.]
Reconnection-driven flares in 3D black hole magnetospheres
Authors: El Mellah I. , Cerutti B. , Crinquand B. 
Published: July 2023

Context. Low-luminosity supermassive and stellar-mass black holes (BHs) may be embedded in a collisionless and highly magnetized plasma. They show nonthermal flares indicative of particles being accelerated up to relativistic speeds by dissipative processes in the vicinity of the BH. During near-infrared flares from the supermassive BH Sagittarius A* (Sgr A*), the GRAVITY Collaboration detected circular motion and polarization evolution, which suggest the presence of transient synchrotron-emitting hot spots moving around the BH.
Aims. We study 3D reconnecting current layers in the magnetosphere of spinning BHs to determine whether plasma-loaded flux ropes which are formed near the event horizon could reproduce the hot spot observations and help constrain the BH spin.
Methods. We performed global 3D particle-in-cell simulations in Kerr spacetime of a pair plasma embedded in a strong and large-scale magnetic field originating in a perfectly conducting disk in prograde Keplerian rotation.
Results. A cone-shaped current layer develops which surrounds the twisted open magnetic field lines threading the event horizon. Spinning magnetic field lines coupling the disk to the BH inflate and reconnect a few gravitational radii above the disk. This quasi-periodic cycle accelerates particles, which accumulate in a few macroscopic flux ropes rotating with the outermost coupling magnetic field line. Once flux ropes detach, they propagate in the current layer following what appears as a rapidly opening spiral when seen face-on. A single flux rope carries enough relativistic electrons and positrons to emit synchrotron radiation at levels suitable to reproduce the peak-luminosity of the flares of Sgr A* but it quickly fades away as it flows away.
Conclusions. Our kinematic analysis of the flux ropes motion favors a BH spin of 0.65 to 0.8 for Sgr A*. The duration of the flares of Sgr A* can only be explained provided the underlying magnetic loop seeded in the disk mid-plane has a finite lifetime and azimuthal extension. In this scenario, the hot spot corresponds to a spinning arc along which multiple reconnection sites power the net emission as flux ropes episodically detach.
Concordancing for CADS
Authors: Gillings Mathew , Mautner Gerlinde 
Published: July 2023

Abstract
Concordance analysis is widely recognised as one of the main techniques in a corpus linguist’s toolkit. However,
despite a growing body of work critically exploring previously unquestioned mainstays of corpus methods (Mautner, 2015; Taylor & Marchi, 2018), this has not
focused on concordance analysis specifically. In this paper, we aim to discuss issues that researchers may encounter when
interpreting concordances. We begin in Step One with a cursory examination of 800 concordance lines in order to identify potential
issues. In Step Two, we assess the distribution of those issues in a reduced sample of 200. As a result, we identify eight
interpretability issues: noise in the corpus, non-standard syntax, unclear referring expressions, unclear quotation source
attribution, technical terms/jargon, acronyms/initialisms, unspecific co-text, and lines unrelated to the research question. After
reflecting on practical challenges, we discuss the epistemological implications of removing concordance lines uncritically and
suggest ten recommendations for future work.
Perspectivized estar-sentences with aesthetic adjectives across American Spanish
varieties
Authors: Gumiel-Molina Silvia , Moreno-Quibén Norberto , Pérez-Jiménez Isabel 
Published: July 2023

Abstract
The article describes the behavior of aesthetic adjectives (bonito ‘beautiful’) in the so-called
innovative constructions with estar ‘be
estar
’, documented in some American varieties of
Spanish. These innovative structures (El poema está bonito ‘The poem is beautiful’) do not compare stages of the
subject with respect to an aesthetic property (as would be their meaning in general Spanish), but rather express a perspectivized
assertion, linked to the subjective judgment of the speaker about a particular quality. The article explains this pattern of
variation on the basis of the work by Gumiel-Molina, Moreno-Quibén and Pérez-Jiménez
(2020) and Moreno-Quibén (2022), according to which the classes of
adjectives that appear in perspectivized estar-sentences have undergone a process of argument augmentation.
Aesthetic adjectives in innovative estar-construction have an experiencer in their argument structure in the
varieties of Spanish where this construction is possible. This experiencer serves as the basis for establishing the comparison
required by estar and ultimately gives rise to the subjective/perspectivized meaning of the copular
structure.
Fan indirect subtitling of Cdramas by women in Latin America and the Caribbean
Authors: Moreno García Luis Damián 
Published: July 2023

Abstract
Despite its controversial status, indirect translation remains one of the most prevalent translation methods and efforts have been made to explore the positive effects of this practice. The present article aims to contribute to such endeavours by researching the potential of indirect fansubbing for the promotion of several key areas of the United Nations’ Fourth Sustainable Development Goal (SDG). The article reports on a fansubbing community consisting of Chinese to Spanish amateur subtitlers who have mobilised indirect translation to attain linguistic proficiency, translational skills and cultural literacy. Results from fieldwork and qualitative data show that indirect subtitles might enhance Spanish-speaking communities’ appreciation of foreign languages and cultures by providing access to otherwise inaccessible audiovisual products. The present research finds potential for indirect fansubbing as an autodidactic method capable of promoting a culture of lifelong learning, global citizenship, and the appreciation of cultural diversity, factors conducive to the fourth SDG.
Corrigendum: On overtravel and skate in cantilever-based probes for on-wafer measurements (2022 J. Micromech. Microeng.
32 057001)
Authors: Arscott Steve 
Published: July 2023

Abstract
This corrigendum reformulates the equations for the normal contact force of the probe and the condition for tip skate in the presence of friction. This enables a formulation of the effective spring constant of a tilted probe to be written down. This model is compared to that of others.
A simple way to predict the flip–chip gap
Authors: Huang Yue , Gan Zhi-Kai , Lin Chun 
Published: July 2023

Abstract
Using laser scanning confocal microscopy measurement, a concise method for extracting the indium bump shape in microelectronics was first established. The extracted bump shape was then used as the input for finite element analysis. The modeled one-bump deformation was used to predict the final flip–chip gap after bonding. Dovetailed with the results of cross-sectional scanning electron microscopy, this simple and non-destructive method for predicting a flip–chip gap of the order of 10 microns or less was eventually validated.
Investigations on sample entropy and fuzzy entropy for machine condition monitoring: revisited
Authors: Wang Yuting , Wang Dong 
Published: July 2023

Abstract
Complexity measures typically represented by entropy are capable of detecting and characterizing underlying dynamic changes in a system, and they have been considerably studied for machine condition monitoring and fault diagnosis. Various entropies have been developed based on Shannon entropy to meet actual demands. Nevertheless, currently existing research works about complexity measures mainly focus on experimental studies, and their theoretical studies are still ongoing and not fully explored. In previous studies, it was theoretically and experimentally proved that two complexity measures including correlation dimension and approximate entropy have a ‘bilateral reduction’ effect. Since sample entropy and fuzzy entropy are two more advanced complexity measures that were developed based on the concept of correlation dimension and approximate entropy, this paper continues conducting theoretical and experimental investigations on sample entropy and fuzzy entropy and exploring their theoretical properties to enrich the domain of complexity measure analysis and its applications to machine condition monitoring. Specifically, this paper theoretically proves and verifies that sample entropy and fuzzy entropy still have a similar ‘bilateral reduction’ effect with correlation dimension and approximate entropy, and they are indeed complexity measures. The relationships between sample entropy, fuzzy entropy, and their key parameters during their calculation are numerically and experimentally studied. Bearing and gear run-to-failure datasets are used to investigate the effectiveness of sample entropy and fuzzy entropy for bearing and gear condition monitoring, and experimental results of sample entropy and fuzzy entropy are well-matched with the theoretical ‘bilateral reduction’ effect of sample entropy and fuzzy entropy. Overall, this paper will provide a guideline for correct uses of sample entropy and fuzzy entropy for engineering applications, especially for machine condition monitoring.