bluuebunny/crossref_metadata_2025_split huggingface dataset:
The body and the verb
Authors: Kofod Frances , Crane Anna 
Published: September 2021

AbstractThis paper explores the figurative expression of emotion in Gija, a non-Pama-Nyungan language from the East Kimberley in Western Australia. As in many Australian languages, Gija displays a large number of metaphors of emotion where miscellaneous body parts – frequently, the belly – contribute to the figurative representation of emotions. In addition, in Gija certain verbal constructions describe the experience of emotion via metaphors of physical impact or damage. This second profile of metaphors is far less widespread, in Australia and elsewhere in the world, and has also attracted far fewer descriptions. This article explores both types of metaphors in turn. Body-based metaphors will be discussed first, and we will highlight the specificity of Gija in this respect, so as to offer data that can be compared to other languages, in Australia and elsewhere. The second part of the article will present verbal metaphors. Given that this phenomenon is not yet very well undersood, this account aims to take a first step into documenting a previously unexplored domain in the language thereby contributing to the broader typology that this issue forms a part of. Throughout the text, we also endeavour to connect the discussion of metaphors with local representations and understanding of emotions.
Ear and belly in Warlpiri descriptions of cognitive and emotional experience
Authors: Laughren Mary , Ponsonnet Maïa 
Published: September 2021

AbstractLike most other Australian languages, Warlpiri – a Pama-Nyungan language of the Ngumpin-Yapa group – is rich in figurative expressions that include a body-part noun. In this article we examine the collocations involving two body parts:langa‘ear’, which mostly relates to cognition; andmiyalu‘belly’, which mostly relates to emotion. Drawing on an extensive Warlpiri database, we analyse the semantic, figurative and syntactic dimensions of these collocations. We note how reflexive variants of certain collocations impose a non-literal aspectual reading, as also observed in Romance and Germanic languagesinter alia. The article also highlights differences between the range of body-based emotion metaphors found in Warlpiri, and that reported for the non-Pama-Nyungan languages of Australia. We hypothesize that these differences sometimes reflect grammatical differences. In particular, Warlpiri allows body-part nouns in syntactic functions that rarely found in non-Pama-Nyungan languages, due to the prevalence of body-part noun incorporation in the latter group.
Advanced learners of Spanish abroad
Authors: Soulé María Victoria , Pérez-Vidal Carmen 
Published: September 2021

AbstractThis study examines the progress made by a group of ERASMUS students in their use of the Spanish Preterite and Imperfect during a stay abroad. Advanced learners of Spanish (N = 12) and native speakers (N = 12) completed an impersonal narrative-based forced-choice test (INT) and an explicit knowledge questionnaire (EKQ). Results from the INT partially confirm the findings of previous studies which indicate that the expression of grounding distinguishes learners from native speakers. Our data show that only the foreground clearly distinguishes between the two groups, not the background. Responses to the EKQ reveal that learners use a variety of mechanisms for their selection of past tense morphology: formal instruction, translation into their L1, knowledge of other L2s and conversation with native speakers. This article suggests further research be undertaken to examine the impact of the learning context on students’ use of past tense morphology.
Problematizing heritage language identities
Authors: Pozzi Rebecca , Reznicek-Parrado Lina 
Published: September 2021

Abstract
Heritage speaker identities have traditionally been a relevant topic of inquiry among scholars of heritage language pedagogy. Nevertheless, there is little research on Spanish heritage language identities in a study abroad context. Additionally, most existing studies on this topic focus on heritage speakers of Mexican descent studying in Mexico (e.g., de Félix & Cavazos Peña, 1992; McLaughlin, 2001; Riegelhaupt & Carrasco, 2000). This study examines heritage language identities in a non-heritage context by exploring the experiences of three heritage speakers of Mexican descent studying in Mendoza, Argentina. By focusing on a non-heritage context, we move away from the presumption that all heritage speakers seek to (re)claim a specific ethnic identity through language study (see Leeman, 2015). Instead, our qualitative analysis illustrates the diverse ways heritage speakers in a non-heritage context construct, contest, and negotiate their identities with respect to linguistic awareness, negotiation between varieties, and perceptions of their abilities.
Fluctuations in mental well-being during Study Abroad
Authors: Dewaele Jean-Marc , Dewaele Livia 
Published: September 2021

Abstract
This mixed-methods study focuses on the effect of Study Abroad (SA) on the mental well-being of 33 Anglophone students who spent between four and twelve months in Francophone countries. It investigates the relationship between well-being and personality traits. Statistical analyses revealed no significant change in well-being between the start, the middle and the end of the SA. A closer look at individual patterns showed large fluctuations, with half of participants scoring higher and the other half scoring lower between the start and the middle of the SA. The narratives of three participants whose well-being scores increased most were not very different from the three participants whose well-being scores decreased most, and only (lower) Emotional Stability was linked with the increase in well-being. At the group level, well-being was not significantly linked to personality traits. The apparent stability of well-being during SA seems to be the result of upward and downward patterns cancelling each other out.
Numerical simulation of ro-vibrational spectra for diatomic molecules using the Numerov matrix method
Authors: Sharma Aditi , Sastri O S K S 
Published: September 2021

Abstract
In this paper, the Numerov matrix method is implemented in a pedagogic manner for simulation of a CO molecule. First, the Numerov algorithm is implemented in the spreadsheet environment ‘Gnumeric’ to obtain coarse vibrational, rotational and ro-vibrational spectrum. Then, the code is written in Scilab so that simulation can be performed for smaller step-sizes so as to achieve greater accuracy for frequencies in ro-vibrational fine-structure spectrum. The simulated vibrational frequencies have been obtained to an accuracy of 0.01% with respect to the experimental ones. The values of rotational constant (B

e
) and anharmonicity constant (

ω

¯

e

x

e

) have been obtained to accuracies of 0.6 and 1.22% respectively. This procedure can be easily integrated as a simulation activity for determination of ro-vibrational spectra of various heterogenous diatomic molecules at undergraduate level.
Valid versus invalid radiation cancer risk assessment methods illustrated using Swiss population data
Authors: Hafner Luana , Walsh Linda 
Published: September 2021

Abstract
After the nuclear accident in Fukushima, the public interest in radiation related cancer-risk assessment increased. However, interpretations of results from epidemiological studies and comprehension of cancer risk assessment methods can be unclear and involve questions about correctness and validity of the approaches. To shed some light on this potential lack of clarity, valid versus invalid radiation cancer risk assessments methods are illustrated here using Swiss population data. This involves a comparison of the cancer risk assessment method based on collective dose and the cumulative risk assessment method, where the latter is recommended with regard to uncertainties and risk of misinterpretation. Further, risk assessment in different dose ranges is discussed and it is concluded that below 100 mSv it cannot be appropriately stated that an adequate strength of evidence of a causal relationship between cancer and radiation is provided, because of the large uncertainties in this dose range. However, the linear non-threshold (LNT) model can be used to model the dose response, because it represents a prudent and parsimonious model, that fits the data well and lies within the given uncertainties. Additionally, treatments of uncertainties in the risk models are illustrated. The EU-project CONFIDENCE software is applied here to obtain example radiation related lifetime cancer risks for exposures of 20 mSv and 5 mSv. Furthermore, the impact of different dosimetry errors on the uncertainties in the cancer lifetime risk calculation is analysed, by including different standard deviations (SD) and by comparing the sampling of the doses from a normal and a lognormal distribution. Using the normal distribution, for females exposed to 20 mSv, the 95% confidence interval (CI) on the cancer lifetime risk increases, when compared to using a SD of 4 mSv, by a factor of 1.5 using a SD of 8 mSv and by a factor of 1.7 using a SD of 10 mSv. The corresponding factors for males for the same exposure are 1.3 and 1.5 respectively. For exposure to 5 mSv, the 95% CIs on the risk increase by a factor of 1.2 for females and 1.4 for men for a SD of 2 mSv using the normal distribution compared to the lognormal distribution and by a factor of 1.5 and 1.8 for a SD of 3 mSv compared to a SD of 1 mSv respectively. Furthermore, differences in the resulting 95% CI on the risk, using different distributions for the dose sampling are visible.
Magnetic moment predictions of odd-A nuclei with the Bayesian neural network approach *
Authors: Yuan Zilong , Tian Dachuan , Li Jian , Niu Zhongming 
Published: September 2021

Abstract
The Bayesian neural network approach has been employed to improve the nuclear magnetic moment predictions of odd-A nuclei. The Schmidt magnetic moment obtained from the extreme single-particle shell model makes large root-mean-square (rms) deviations from data, i.e., 0.949

and 1.272

for odd-neutron nuclei and odd-proton nuclei, respectively. By including the dependence of the nuclear spin and Schmidt magnetic moment, the machine-learning approach precisely describes the magnetic moments of odd-A nuclei with rms deviations of 0.036

for odd-neutron nuclei and 0.061

for odd-proton nuclei. Furthermore, the evolution of magnetic moments along isotopic chains, including the staggering and sudden jump trend, which are difficult to describe using nuclear models, have been well reproduced by the Bayesian neural network (BNN) approach. The magnetic moments of doubly closed-shell

nuclei, for example, isoscalar and isovector magnetic moments, have been well studied and compared with the corresponding non-relativistic and relativistic calculations.
Logistic Map: Stability and Entrance to Chaos
Authors: Chen Shaoqiu , Feng Shiya , Fu Wenjun , Zhang Yingying 
Published: September 2021

Abstract
Chaos and nonlinear dynamics have taken a crucial place in the mathematics, physics, and engineering worlds. The main focus of this paper is about one famous map in the dynamical system that has an extreme sensitivity to the initial conditions, the logistic map.We first discuss the behaviours of the logistic map under different µ: convergence to 0 when√μ ∈ (0,1), convergence to 1−1/µ when µ ∈ (1,3), 2-cycle when µ ∈ (3,1 + 6), further period doubling and eventual chaos, which is in good accordance with our simulation. In the end, we proved three relevant results: the criteria for stability of cycle, the Coppel Theorem, and the famous slogan “period three implies chaos.”
Development and characterization of a large area silicon pad array for an electromagnetic calorimeter
Authors: Mukhopadhyay S. , Chandratre V.B. , Muhuri S. , Singaraju R.N. , Saini J. , Nayak T.K. 
Published: September 2021

Abstract
We present the research and development work of the first version of a 6×6 array of silicon pad detectors, carried out in India, for the proposed forward calorimeter (FOCAL) as part of the ALICE collaboration upgrade program at CERN. The primary motivation is to develop a large area silicon pad array realizing the challenging requirements of high-energy physics experiments such as low leakage current, high breakdown voltage and evaluate its performance as an active layer in the prototype silicon tungsten (Si-W) electromagnetic (EM) calorimeter. Towards these goals, a 36-pad silicon sensor with an individual pad size of ∼1 cm2 is designed on a 4-inch high resistivity N-type wafer and fabricated at Bharat Electronics Limited, Bangalore. The sensors have been used to assemble the prototype Si-W calorimeters and were successfully tested with high-energy particle beams. The design and development of the large area silicon sensor and its characterization using radioactive sources in the laboratory and high-energy particle beams are reported in this paper.
Elastodynamic model for flapping-wing micro aerial vehicle
Authors: Fang Xin , Wu Jianghao , Du Feng 
Published: September 2021

Abstract
Lightweight design is key to high efficiency and long durability of micro air vehicle (MAV), while it will inevitably reduce the stiffness of the structures and affect the motion of the mechanism. In this study, an elastodynamic model for flapping-wing MAV (FMAV) is established to unveil the effect of elastic deformation of transmission mechanism on the flapping motion. Based on kineto-elastostatic analysis, an elastodynamic model of the transmission mechanism is built, which reveals that the inertial force of the transmission mechanism for typical FMAV is much smaller than the force transmitted. Thus, the inertial force can be ignored, and analytical formula between the deformation of transmission mechanism and the flapping angle is derived. Finite element method (FEM) simulations are conducted to validate the analytical formula, and the results show that the flapping angle obtained from the analytical formula matches well with FEM simulations. The proposed elastodynamic model and analytical formula will provide theoretical guidance for designing and optimizing FMAV with desired transmission mechanism and flapping motion.
LiDAR-driven spiking neural network for collision avoidance in autonomous driving
Authors: Shalumov Albert , Halaly Raz , Tsur Elishai Ezra 
Published: September 2021

Abstract
Facilitated by advances in real-time sensing, low and high-level control, and machine learning, autonomous vehicles draw ever-increasing attention from many branches of knowledge. Neuromorphic (brain-inspired) implementation of robotic control has been shown to outperform conventional control paradigms in terms of energy efficiency, robustness to perturbations, and adaptation to varying conditions. Here we propose LiDAR-driven neuromorphic control of both vehicle's speed and steering. We evaluated and compared neuromorphic PID control and online learning for autonomous vehicle control in static and dynamic environments, finally suggesting proportional learning as a preferred control scheme. We employed biologically plausible basal-ganglia and thalamus neural models for steering and collision-avoidance, finally extending them to support a null controller and a target-reaching optimization, significantly increasing performance.
Efficient pathways to zero-carbon energy use by water supply utilities: an example from London, UK
Authors: Majid Aman , Mortazavi-Naeini Mohammad , Hall Jim W 
Published: September 2021

Abstract
Urban water utilities are increasing their use of energy-intensive technologies such as desalination and long-distanced pumped transfers. Under pressure to reduce their energy-related carbon emissions to zero, water utilities have devised a variety of energy management strategies, including the purchase of renewable energy and self-generation of electricity using locally installed renewables. These strategies will incur different costs for the utility, whilst some may have implications for the reliability of water supply systems. Yet the trade-offs between costs, water security and energy sustainability remain unexplored. Here, we present a regional scale analysis to test competing energy strategies, mapping pathways to zero carbon energy and water security. Results from a case-study of the London water system show a balanced approach that allows for some energy self-generation, using biogas, solar and wind, while also purchasing green energy credits from the electricity supply grid can best navigate this trade-off. Balanced investment plans can accommodate energy-intensive water supply techniques such as long-distance transfers, desalination and effluent reuse while meeting energy targets. By becoming energy generators and also adopting more flexible arrangements for energy use, water utilities could become significant players in energy markets.
Detection of COVID-19 by Machine Learning Using Routine Laboratory Tests
Authors: Çubukçu Hikmet Can , Topcu Deniz İlhan , Bayraktar Nilüfer , Gülşen Murat , Sarı Nuran , Arslan Ayşe Hande 
Published: September 2021

Abstract

Objectives
The present study aimed to develop a clinical decision support tool to assist coronavirus disease 2019 (COVID-19) diagnoses with machine learning (ML) models using routine laboratory test results.

Methods
We developed ML models using laboratory data (n = 1,391) composed of six clinical chemistry (CC) results, 14 CBC parameter results, and results of a severe acute respiratory syndrome coronavirus 2 real-time reverse transcription–polymerase chain reaction as a gold standard method. Four ML algorithms, including random forest (RF), gradient boosting (XGBoost), support vector machine (SVM), and logistic regression, were used to build eight ML models using CBC and a combination of CC and CBC parameters. Performance evaluation was conducted on the test data set and external validation data set from Brazil.

Results
The accuracy values of all models ranged from 74% to 91%. The RF model trained from CC and CBC analytes showed the best performance on the present study’s data set (accuracy, 85.3%; sensitivity, 79.6%; specificity, 91.2%). The RF model trained from only CBC parameters detected COVID-19 cases with 82.8% accuracy. The best performance on the external validation data set belonged to the SVM model trained from CC and CBC parameters (accuracy, 91.18%; sensitivity, 100%; specificity, 84.21%).

Conclusions
ML models presented in this study can be used as clinical decision support tools to contribute to physicians’ clinical judgment for COVID-19 diagnoses.
Working Group Recommendations for the Practice of Teleneuropsychology in Latin America
Authors: Crivelli Lucía , Quiroz Yakeel T , Calandri Ismael L , Martin María E , Velilla Lina M , Cusicanqui María I , Yglesias Fernando Coto , Llibre-Rodríguez Juan J , Armele Monserrat , Román Fabián , Barceló Ernesto , Dechent Claudia , Carello María Agostina , Olavarría Loreto , Yassuda Mônica S , Custodio Nilton , Dansilio Sergio , Sosa Ana L , Acosta Daisy M , Brucki Sonia M D , Caramelli Paulo , Slachevsky Andrea , Nitrini Ricardo , Carrillo María C , Allegri Ricardo F 
Published: September 2021

Abstract

Objective
Teleneuropsychology (teleNP) could potentially expand access to services for patients who are confined, have limited personal access to healthcare, or live in remote areas. The emergence of the COVID-19 pandemic has significantly increased the use of teleNP for cognitive assessments. The main objective of these recommendations is to identify which procedures can be potentially best adapted to the practice of teleNP in Latin America, and thereby facilitate professional decision-making in the region.

Method
Steps taken to develop these recommendations included (1) formation of an international working group with representatives from 12 Latin American countries; (2) assessment of rationale, scope, and objectives; (3) formulation of clinical questions; (4) evidence search and selection; (5) evaluation of existing evidence and summary; and (6) formulation of recommendations. Levels of evidence were graded following the Oxford Centre for Evidence-Based Medicine system. Databases examined included PubMed, WHO-IRIS, WHO and PAHO-IRIS, Índice Bibliográfico Español en Ciencias de la Salud (IBCS), and LILACS.

Results
Working group members reviewed 18,400 titles and 422 abstracts and identified 19 articles meeting the criteria for level of evidence, categorization, and elaboration of recommendations. The vast majority of the literature included teleNP tests in the English language. The working group proposed a series of recommendations that can be potentially best adapted to the practice of teleNP in Latin America.

Conclusions
There is currently sufficient evidence to support the use of videoconferencing technology for remote neuropsychological assessments. These recommendations will likely contribute to the advancement of teleNP research and practice in the region.
A Survey of Doctoral Internships Offering Clinical Neuropsychology Training: Updated Expectations for Competitive Applicants
Authors: Hirst Rayna B , Thompson Ryan C , Markiv Yelena , Pilavjian Haig , Arastu Sana F , Markuson Sara M 
Published: September 2021

Abstract

Objective
The specialty of clinical neuropsychology has experienced significant professional growth and increasing standardization of educational and training guidelines over the past 20 years. Previous literature demonstrated the importance of routine distribution of selection criteria used by training directors and supervising neuropsychologists for competitive applicants aiming to specialize in neuropsychology during internship. This study examined supervisors’ updated expectations for competitive applicants from a more diverse sample of doctoral internship programs offering neuropsychological training. These data also provide cross-sectional and longitudinal comparisons to help trainees tailor their graduate training experiences.

Method
The sample included training directors and/or supervising neuropsychologists from 80 internship programs (73.4% of submitted surveys). Spearman correlations, analyses of variance, and chi-square tests of independence were conducted for cross-sectional and longitudinal comparisons.

Results
Clinical experience in assessment and the personal interview were consistently the two most prioritized criteria across all groups, whereas prioritization of the additional criteria was variable based on the program’s characteristics. Internship programs generally preferred practica experience at university-affiliated medical centers, Veterans Affairs medical centers, and private/community-based hospitals. University-affiliated medical centers and internships offering ≥50% neuropsychology training showed similar preferences for applicants with a depth and breadth of graduate school experience in neuropsychology. Longitudinally, the applicant expectations for programs offering ≥50% neuropsychology training remained largely unchanged between 2000 and 2020.

Conclusions
This study updated expectations for competitive applicants from a diverse sample of neuropsychology training programs, underscored the importance of fit between trainee and program, and demonstrated consistency over time for trainees seeking neuropsychology training during internship.