bluuebunny/crossref_metadata_2025_split huggingface dataset:
The new era of artificial intelligence in neuroradiology: current research and promising tools
Authors: Carvalho Macruz Fabíola Bezerra de , Dias Ana Luiza Mandetta Pettengil , Andrade Celi Santos , Nucci Mariana Penteado , Rimkus Carolina de Medeiros , Lucato Leandro Tavares , Rocha Antônio José da , Kitamura Felipe Campos 
Published: April 2024

AbstractRadiology has a number of characteristics that make it an especially suitable medical discipline for early artificial intelligence (AI) adoption. These include having a well-established digital workflow, standardized protocols for image storage, and numerous well-defined interpretive activities. The more than 200 commercial radiologic AI-based products recently approved by the Food and Drug Administration (FDA) to assist radiologists in a number of narrow image-analysis tasks such as image enhancement, workflow triage, and quantification, corroborate this observation. However, in order to leverage AI to boost efficacy and efficiency, and to overcome substantial obstacles to widespread successful clinical use of these products, radiologists should become familiarized with the emerging applications in their particular areas of expertise. In light of this, in this article we survey the existing literature on the application of AI-based techniques in neuroradiology, focusing on conditions such as vascular diseases, epilepsy, and demyelinating and neurodegenerative conditions. We also introduce some of the algorithms behind the applications, briefly discuss a few of the challenges of generalization in the use of AI models in neuroradiology, and skate over the most relevant commercially available solutions adopted in clinical practice. If well designed, AI algorithms have the potential to radically improve radiology, strengthening image analysis, enhancing the value of quantitative imaging techniques, and mitigating diagnostic errors.
Dundee Annual Neurosurgery Skills Event (DANSE)—Improving the Availability and Affordability of Neurosurgical Skills Workshops for Medical Students
Authors: Hutton Dana , Ashraf Mohammed , Sescu Daniel , Ismahel Hassan , Hepburn Katie , Lumsden Emma , Wright Poppy , Chai Carmen , Helley Michael , McSorley Nathan , Mohamed Belal , Abdulrahman Mohammed , Page Beverley , Porter Roslyn , Bodkin Peter , Okasha Mohamed 
Published: April 2024

Abstract
Background Neurosurgery can be a daunting career choice for medical students, with preparation for trainee application often being inaccessible and expensive. This article describes a student-led neurosurgical skills event supported by local neurosurgery faculty members. Such event was designed to offer a means to bridge this gap by providing an opportunity to practice neurosurgical techniques in simulation, and learn about what a career in neurosurgery involves.
Methods Pre- and postskills laboratory surveys were used to ascertain the baseline confidence and knowledge of common neurosurgical techniques, as well as to what both the application to neurosurgery and the typical workload of a neurosurgeon involves. The conference offered six neurosurgical workshops as well as three lectures to provide practical and theoretical learning opportunities. The session included introduction to the candidates and faculty, identification of learning objectives, and career discussion. Postcourse feedback also was also used to assess learning outcomes.
Results Eighteen students attended the event. Postskills event, students were significantly more likely to understand the principles behind all of the relevant neurosurgical skills included on the day. Additionally, students were more likely to understand what a career in neurosurgery involves, and how to approach applying for a training number. Respondents enjoyed the workshops, valued hands-on experience and interactions with consultants, found it affordable, and would recommend to their peers.
Conclusions For medical students interested in a career in neurosurgery, opportunities to learn relevant techniques and skills are often expensive and difficult to come across. Here, we highlight affordable methods of simulation to result in significant student satisfaction. Additionally, providing ample opportunity to practice different neurosurgical techniques under almost 1:1 level tutoring enables significant increases in students' confidence and understanding of different neurosurgical concepts. We greatly encourage other medical student groups to develop their own hands-on simulation events to attract medical students to a surgical field often considered daunting and inaccessible, and address gaps in the medical school curriculum.
Variability in Diagnosis and Management of Hypoglycemia in Neonatal Intensive Care Unit
Authors: Dinu Daniela , Hagan Joseph L. , Rozance Paul J. 
Published: April 2024

Objective Hypoglycemia, the most common metabolic derangement in the newborn period remains a contentious issue, not only due to various numerical definitions, but also due to limited therapeutical options which either lack evidence to support their efficacy or are increasingly recognized to lead to adverse reactions in this population. This study aimed to investigate neonatologists' current attitudes in diagnosing and managing transient and persistent hypoglycemia in newborns admitted to the Neonatal Intensive Care Unit (NICU).
Methods A web-based electronic survey which included 34 questions and a clinical vignette was sent to U.S. neonatologists.
Results There were 246 survey responses with most respondents using local protocols to manage this condition. The median glucose value used as the numerical definition of hypoglycemia in first 48 hours of life (HOL) for symptomatic and asymptomatic term infants and preterm infants was 45 mg/dL (2.5 mmol/L; 25–60 mg/dL; 1.4–3.3 mmol/L), while after 48 HOL the median value was 50 mg/dL (2.8 mmol/L; 30–70 mg/dL; 1.7–3.9 mmol/L). There were various approaches used to manage transient and persistent hypoglycemia that included dextrose gel, increasing caloric content of the feeds using milk fortifiers, using continuous feedings, formula or complex carbohydrates, and use of various medications such as diazoxide, glucocorticoids, and glucagon.
Conclusion There is still large variability in current practices related to hypoglycemia. Further research is needed not only to provide evidence to support the values used as a numerical definition for hypoglycemia, but also on the efficacy of current strategies used to manage this condition.
Key Points
COVID-19, the Russia–Ukraine war and the connectedness between the U.S. and Chinese agricultural futures markets
Authors: Zhang Yongmin , Sun Yiru , Shi Haili , Ding Shusheng , Zhao Yingxue 
Published: April 2024

AbstractThis study focuses on how recent global crises such as the COVID-19 pandemic and the Russia–Ukraine war have affected the relationship between the U.S. and Chinese agricultural futures markets. By applying wavelet coherence analysis (WCA) and time-varying parameter vector autoregression (TVP-VAR), we obtain the following findings. First, both events have changed the correlation and lead–lag comovement between U.S. and Chinese soybean and corn futures returns but have little impact on the comovement between the two cotton futures returns. Second, U.S. agricultural markets transmit more volatility risk to Chinese markets than the risk spillover from the reverse direction. Third, the risk spillover enhancement effect from the war is stronger than that from the pandemic, which is obvious in both the soybean and corn futures markets but not in the cotton market. Our paper has implications for policy makers seeking to stabilize agricultural commodity prices during global crisis episodes and for designing strategies for cross-market hedging of spillover risks among commodity markets for international investors.
The future of the labor force: higher cognition and more skills
Authors: Zhang Wen , Lai Kee-Hung , Gong Qiguo 
Published: April 2024

AbstractSkills can be categorized into two types: social-cognitive and sensory-physical. Sensory-physical skills, governed by explicit rules and transparent rationales, can be effectively executed through meticulous programming, with humans spontaneously trusting machines to perform these skills. In contrast, social-cognitive skills entail open interpretations reliant on personal opinions or intuition and are contextually and problem-dependent. The inherent complexity and subjectivity of social-cognitive skills, underscored by Polanyi’s paradox and algorithm aversion, render machines less capable of replicating these skills. Thus, automation exerts differential impacts on these two skill sets. Moreover, the specialization of machines leads to expensive setup costs when switching tasks, whereas humans switch tasks with much less effort. The versatility in skills enables workers to adapt to a wide array of tasks, making them less prone to automation. Our empirical research, utilizing skill score data from O*NET and employment data from Employment and Wage Statistics (OEWS), validated the attributes of labor resistant to automation: the higher the scores of cognitive skills in a job, the lower its susceptibility to automation; workers endowed with a diverse array of skills experience an increase in their employment share. Conversely, jobs focusing on sensory-physical skills are more likely to be supplanted by machines. Therefore, workers can adopt two strategies to maintain a competitive edge. First, they can enhance cognitive skills, such as creativity and critical thinking. Second, they can develop diverse skills, encompassing both social-cognitive and sensory-physical skills. Specializing in a specific sensory-physical skill does not offer an advantage. Fostering a workforce proficient in cognitive skills and equipped with multifaceted skills, that is, flexible workers, becomes imperative. Our investigation represents the inaugural effort to empirically affirm the differential impact of automation on sensory-physical versus social-cognitive skills, thereby delineating the characteristics of irreplaceable labor. This analysis offers critical insights for individual career development and the strategic planning of national educational systems.
COVID-19 vaccination, preventive behaviours and pro-social motivation: panel data analysis from Japan
Authors: Yamamura Eiji , Tsutsui Yoshiro , Ohtake Fumio 
Published: April 2024

AbstractThe COVID-19 vaccine reduces infection risk; even if one contracts COVID-19, the probability of complications such as death or hospitalisation is lower. However, vaccination may prompt people to decrease preventive behaviours, such as staying home, washing hands, and wearing a mask. Therefore, if vaccinated people pursue only self-interest, the vaccine’s effect may be lower than expected. However, if vaccinated people are pro-social (motivated toward benefits for the whole society), they might maintain preventive behaviours to reduce the spread of infection. We conducted 26 surveys almost once a month from March 2020 (the early stage of COVID-19) to September 2022 in Japan. By corresponding with identical individuals, we independently constructed the original panel data (N = 70,908). Based on the data, we identified the timing of the second vaccine shot and compared preventive behaviours before and after vaccination. We investigated whether second-shot vaccination correlated with changes in preventive behaviours. Furthermore, we explored whether the vaccination effect differed between the older and younger groups. We then investigated the effect of pro-social motivation on preventive behaviours. Major findings are as follows: (1) Being vaccinated led people to increase preventive behaviours, such as mask-wearing by 1.04 (95% confidence intervals [Cis]: 0.96–1.11) points, and hand hygiene by 0.34 (95% CIs: 0.30–0.38) points on a 5-point scale. (2) Vaccinated people under 65 are less likely to stay home. (3) People with pro-social motivation to be vaccinated are more likely to maintain prevention than those not so motivated; on a 5-point scale, the difference is 0.08 (95% CIs: 0.01–0.15) points for mask-wearing and 0.05 (95% CIs: 0.001–0.10) points for hand hygiene. After vaccination, the opportunity cost of staying home outweighs its benefits, and people are less inclined to stay at home. This effect is lower in older people who are at a higher risk of serious illness. The opportunity cost of wearing masks and hand hygiene is lower than that of staying home, and the benefit persists after vaccination if people are motivated to maintain these behaviours for others’ well-being.
One-dimensional Schrödinger operator with decaying white noise potential
Authors: Minami Nariyuki 
Published: April 2024

In this paper, we consider a random one-dimensional Schrödinger operator Hω on the half line which has, as its potential term, Gaussian white noise multiplied by a decaying factor. Although the potential term is not an ordinary function, but a distribution, it is possible to realize Hω as a symmetric operator in L2([0, ∞); dt) as was pointed out by the present author [Minami, Lect. Notes Math. 1299, 298 (1986)], and it will be shown that Hω is actually self-adjoint with probability one. When the white noise in Hω is replaced by random functions of a specific type, [Kotani and Ushiroya, Commun. Math. Phys. 115, 247 (1988)] made a precise analysis of the positive part of the spectrum. According to them, if the decaying factor is not square integrable, the positive part of the spectrum typically consists of singular continuous and dense pure-point parts, which are separated by a threshold number. On the other hand, the positive part of the spectrum is purely absolutely continuous when the decaying factor is square integrable. In this work, we shall focus on the case of square integrable decaying factor, and prove the absolute continuity of the positive part of the spectrum of Hω. We shall further prove that the negative part of the spectrum of Hω is discrete, with no accumulation points other than 0.
Do teachers adapt their gestures in linguistically heterogeneous second language teaching to learners’ language proficiencies?
Authors: Sahlender Moritz , ten Hagen Inga 
Published: April 2024

AbstractTeachers’ use of gestures in the classroom can support the language acquisition of learners in learning a second language (Stam & Tellier, 2022). Depending on learners’ language skills, different dimensions of gestures (e.g., deictic, metaphorical) are considered to facilitate successful language comprehension. This study investigates which gestures teachers use in German as a second language (GSL) classrooms and to what extent teachers adapt their gestures to learners’ language proficiency. Teacher gestures in 10 video-recorded integration and preparation classes were analyzed. Two coders reliably identified 4143 gestures. Results show that GSL teachers predominantly used deictic gestures, metaphorical gestures, and feedback by head movements. Moreover, between-learner variability in teachers’ use of deictic and metaphorical gestures was explained by teacher-perceived German language proficiency of learners. These results suggest that teachers systematically adapt some dimensions of gestures in GSL classes, thus emphasizing the importance of studying nonverbal interactions for a better understanding of language acquisition processes.
Narratology, applied
Authors: Presser Lois 
Published: April 2024

Abstract
Criminology is foundationally an applied discipline, or one whose knowledge seeks to shape some non-academic
practice. Narratives – particularly the narratives of parties to ‘crime’ – are essential to criminology, but criminologists have
hardly engaged with narratology. This paper tracks the progression from traditional narrative research involving harm agents and
criminalized persons to a relatively new narrative criminology that is attentive to narrative forms and strategies inasmuch as it
considers these as shaping harm. In addition, the paper forecasts narrative criminology’s fruitful engagement in concepts from
rhetorical narratology. Interviews with men who perpetrated violence and insights from restorative justice encounters are used to
demonstrate the potential value of rhetorical narratological concepts to narrative criminology and to interventions informed by
narrative criminology.
The effect of fluency training on interpreter trainees’ speech fluency, comprehensibility, and
accentedness
Authors: Yenkimaleki Mahmood , van Heuven Vincent J. 
Published: April 2024

Abstract
Fluency, comprehensibility, and accentedness are considered important parameters of interpreting quality but have
rarely been studied systematically in training programs of interpreting. Therefore, the present study was set up to investigate
the effect of fluency training on speech fluency, comprehensibility, and accentedness of interpreter trainees. Two groups of
interpreter trainees at a university in Iran took part in the study, receiving the same amount of instruction and practice
(12 hours over 4 weeks). The experimental group (N = 30) spent 33% of the time (i.e., 4 of the 12 hours in the
training program) on dedicated fluency strategy training, encouraging the memorization, repetition, and retelling of audio and
video materials. The remaining 67% was spent on training general speaking skills. The control group (N = 30) were
only taught general speaking skills in the training program but received no dedicated fluency training. Systematic interviews were
run to assess the interpreter trainees’ speech fluency, comprehensibility and accentedness, which were judged independently by
three expert raters at three moments of testing, i.e., pretest, immediate posttest, and delayed posttest (one month later). The
findings revealed that the fluency training significantly enhanced the interpreter trainees’ fluency, and to a lesser extent the
students’ comprehensibility but had only a marginal effect on accentedness. The pedagogical implication would be that awareness
training on speech fluency in EFL settings be included in interpreting training programs.
Development of a novel monolithic compliant Lorentz-force-driven XY nanopositioning system
Authors: Yang Xu , Liu Xin , Zhu Yilong , Qiao Feng , Li Shizhen , Zhu Zhiwei , Zhu Limin 
Published: April 2024

Abstract
A novel monolithic compliant Lorentz-force-driven XY nanopositioning system (MCLNS) is designed, analyzed, and experimentally assessed with the aim of high-resolution positioning across a large workspace. A double-symmetric Lorentz-force actuator (DSLA) with the benefits of zero friction, high thrust, and large stroke is proposed to generate the actuation force. Correspondingly, a monolithic four-prismatic parallel compliant mechanism (4P-PCM) is exploited to transmit the actuation motion to the central platform and minimize the parasitic motion. The unique integration of four DSLAs and one 4P-PCM make the proposed MCLNS possess compact structure and stable performance. The characterization of the MCLNS is formulated by a specially established analytical model and validated by finite-element analysis simulation and experimental tests. Experimental studies show that the workspace of the MCLNS prototype is large than 0.87 × 0.87 mm2 and the positioning resolution of the MCLNS prototype is better than 9 nm. By means of a nonlinear forward proportional integral derivative control strategy, the maximum contouring error of the MCLNS is maintained within 2.7% while tracking a 1257 μm s−1 circular trajectory.
Generation of meter-scale nanosecond pulsed DBD and the intelligent evaluation based on multi-dimensional feature parameter extraction
Authors: Zhu Xi , Guan Xiuhan , Luo Zhaorui , Wang Liyan , Dai Luyi , Wu Zexuan , Fan Jiajie , Cui Xinglei , Akram Shakeel , Fang Zhi 
Published: April 2024

Abstract
This study introduces a novel meter-scale dielectric barrier discharge (m-DBD) reactor designed to generate large-scale, low-temperature nanosecond pulsed discharge plasma. By employing a modularized gas path, this reactor enables a comprehensive analysis of discharge patterns and uniformity using multi-dimensional discharge parameters. Simulation results reveal optimal gas distribution with ten gas holes in the variable plate and a 40 mm slit depth in the main reactor. Besides, a diagnosis method based on electro-acoustic-spectrum-image (E-A-S-I) parameters is developed to evaluate nanosecond pulsed m-DBD discharge states. It is found that the discharge states are closely related to the consistency of segmental discharge currents, the fluctuation of acoustic signals and the distribution of active particles. Machine learning methods are established to realize the diagnosis of m-DBD discharge pattern and uniformity by E-A-S-I parameters, where the optimized BPNN has a best recognition accuracy of 97.5%. Furthermore, leveraging nanosecond pulse power in Ar/m-DBD enables stable 1120 × 70 mm2 discharge, uniformly enhancing hydrophobicity of large-scale materials from a 67° to 122° water contact angle with maximal fluctuations below 7%. The modularized m-DBD reactor and its intelligent analysis based on multi-dimensional parameter provide a crucial foundation for advancing large-scale nanosecond pulsed plasma and their industrial applications.
Markerless liver online adaptive stereotactic radiotherapy: feasibility analysis
Authors: Pierrard Julien , Deheneffe Stéphanie , Dechambre David , Sterpin Edmond , Geets Xavier , Van Ooteghem Geneviève 
Published: April 2024

Abstract

Objective. Radio-opaque markers are recommended for image-guided radiotherapy in liver stereotactic ablative radiotherapy (SABR), but their implantation is invasive. We evaluate in this in-silico study the feasibility of cone-beam computed tomography-guided stereotactic online-adaptive radiotherapy (CBCT-STAR) to propagate the target volumes without implanting radio-opaque markers and assess its consequence on the margin that should be used in that context. Approach. An emulator of a CBCT-STAR-dedicated treatment planning system was used to generate plans for 32 liver SABR patients. Three target volume propagation strategies were compared, analysing the volume difference between the GTVPropagated and the GTVConventional, the vector lengths between their centres of mass (l
CoM), and the 95th percentile of the Hausdorff distance between these two volumes (HD95). These propagation strategies were: (1) structure-guided deformable registration with deformable GTV propagation; (2) rigid registration with rigid GTV propagation; and (3) image-guided deformable registration with rigid GTV propagation. Adaptive margin calculation integrated propagation errors, while interfraction position errors were removed. Scheduled plans (PlanNon-adaptive) and daily-adapted plans (PlanAdaptive) were compared for each treatment fraction. Main results. The image-guided deformable registration with rigid GTV propagation was the best propagation strategy regarding to l
CoM (mean: 4.3 +/− 2.1 mm), HD95 (mean 4.8 +/− 3.2 mm) and volume preservation between GTVPropagated and GTVConventional. This resulted in a planning target volume (PTV) margin increase (+69.1% in volume on average). Online adaptation (PlanAdaptive) reduced the violation rate of the most important dose constraints (‘priority 1 constraints’, 4.2 versus 0.9%, respectively; p < 0.001) and even improved target volume coverage compared to non-adaptive plans (PlanNon-adaptive). Significance. Markerless CBCT-STAR for liver tumours is feasible using Image-guided deformable registration with rigid GTV propagation. Despite the cost in terms of PTV volumes, daily adaptation reduces constraints violation and restores target volumes coverage.