bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Impact of Drop Test Conditions on Brain Strain Location and Severity: A Novel Approach Using a Deep Learning Model
Authors: Stilwell George , Stitt Danyon , Alexander Keith , Draper Nick , Kabaliuk Natalia 
Published: May 2024

AbstractIn contact sports such as rugby, players are at risk of sustaining traumatic brain injuries (TBI) due to high-intensity head impacts that generate high linear and rotational accelerations of the head. Previous studies have established a clear link between high-intensity head impacts and brain strains that result in concussions. This study presents a novel approach to investigating the effect of a range of laboratory controlled drop test parameters on regional peak and mean maximum principal strain (MPS) predictions within the brain using a trained convolutional neural network (CNN). The CNN is publicly available at https://github.com/Jilab-biomechanics/CNN-brain-strains. The results of this study corroborate previous findings that impacts to the side of the head result in significantly higher regional MPS than forehead impacts. Forehead impacts tend to result in the lowest region-averaged MPS values for impacts where the surface angle was at 0° and 45°, while side impacts tend to result in higher regional peak and mean MPS. The absence of a neck in drop tests resulted in lower regional peak and mean MPS values. The results indicated that the relationship between drop test parameters and resulting regional peak and mean MPS predictions is complex. The study’s findings offer valuable insights into how deep learning models can be used to provide more detailed insights into how drop test conditions impact regional MPS. The novel approach used in this paper to predict brain strains can be applied in the development of better methods to reduce the brain strain resulting from head accelerations such as protective sports headgear.
Sound and Noise Sources in Sonotubometry: An Investigation of Eustachian Tube Assessment
Authors: Nava Tobia Sebastiano , Nussbaumer Maximilian , Tysome James R. , Sutcliffe Michael P. F. 
Published: May 2024

AbstractThis research aims to enhance the understanding of the acoustic processes occurring during sonotubometry, a method used to assess the Eustachian tube (ET) function. Recent advancements in digital signal processing enable a more comprehensive data analysis. In this project, a silicone model of the ET was developed to systematically study the existing noise and sound sources. These measurements were then compared with recordings from human subjects. Three distinct ’noise sources’ were identified, which can influence the assessment of the ET opening using transmission measurements of the imposed signal: sound leakage from the speaker, a clicking noise at the initiation of ET opening, and rumbling/swallowing noise. Through spectral analysis, it was also possible to ascertain the spectral and temporal occurrence of these sound and noise types. The silicone model exhibited remarkable similarity to the healthy human ET, making it a robust experimental model for investigating the acoustics of sonotubometry. The findings underscore the significance of delving deeper into the analysed sound, as the noise occurring during sonotubometry can be easily misconstrued as an actual ET opening. Particularly, careful consideration is warranted when evaluating data involving clicking and swallowing noise.
Anti-oppression pedagogy in health professions: a scoping review
Authors: Smith Meredith , McGuire-Adams Tricia , Eady Kaylee 
Published: May 2024

AbstractHealth professional learners are increasingly called to learn about health inequity to reduce inequities and improve patient care and health outcomes. Anti-oppression pedagogy (AOP) addresses the need for health professional learners to understand multiple health inequities and the structures and systems that produce inequities. However, the inclusion of AOP in health professions education varies and there is a lack of clarity in its conceptualization and integration. A scoping review was conducted to address this gap and to understand how AOP is conceptualized and integrated in health professions education. Thirty-six articles met the inclusion criteria. The articles demonstrated that AOP is not commonly utilized terminology within health professions education. When AOP is integrated, it is not consistently conceptualized but is generally viewed as a broad concept that focuses on antiracism; decoloniality; intersectionality; and supporting learners to understand, critically reflect on, and act against structural and systemic forms of oppressions. In addition, there is variation in the integration of AOP in health professions education with the most common methods consisting of discussions, cases, reflection, learning through lived experiences, and the incorporation of humanities within a longitudinal curriculum. The results of this scoping review highlight the need for health professions education to develop one clear concept that educators use when teaching about anti-oppression, which may reduce working in silos and allow educators to better collaborate with each other in advancing this work. In addition, this review suggests that health professional programs should consider incorporating AOP in curricula with a broad and longitudinal approach utilizing the common methods of delivery. To better support programs in including AOP in curricula, further research is required to emphasize the benefits, provide clarity on its conceptualization, and determine the most effective methods of integration.
Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods
Authors: Golabi Arash , Erradi Abdelkarim , Qiblawey Hazim , Tantawy Ashraf , Bensaid Ahmed , Shaban Khaled 
Published: May 2024

AbstractThe reverse osmosis (RO) process is a well-established desalination technology, wherein energy-efficient techniques and advanced process control methods significantly reduce production costs. This study proposes an optimal real-time management method to minimize the total daily operation cost of an RO desalination plant, integrating a storage tank system to meet varying daily freshwater demand. Utilizing the dynamic model of the RO process, a cascade structure with two reinforcement learning (RL) agents, namely the deep deterministic policy gradient (DDPG) and deep Q-Network (DQN), is developed to optimize the operation of the RO plant. The DDPG agent, manipulating the high-pressure pump, controls the permeate flow rate to track a reference setpoint value. Simultaneously, the DQN agent selects the optimal setpoint value and communicates it to the DDPG controller to minimize the plant’s operation cost. Monitoring storage tanks, permeate flow rates, and water demand enables the DQN agent to determine the required amount of permeate water, optimizing water quality and energy consumption. Additionally, the DQN agent monitors the storage tank’s water level to prevent overflow or underflow of permeate water. Simulation results demonstrate the effectiveness and practicality of the designed RL agents.
A comparison study of spatial and temporal schemes for flow and transport problems in fractured media with large parameter contrasts on small length scales
Authors: Gao Wansheng , Neuweiler Insa , Wick Thomas 
Published: May 2024

AbstractIn this work, various high-accuracy numerical schemes for transport problems in fractured media are further developed and compared. Specifically, to capture sharp gradients and abrupt changes in time, schemes with low order of accuracy are not always sufficient. To this end, discontinuous Galerkin up to order two, Streamline Upwind Petrov-Galerkin, and finite differences, are formulated. The resulting schemes are solved with sparse direct numerical solvers. Moreover, time discontinuous Galerkin methods of order one and two are solved monolithically and in a decoupled fashion, respectively, employing finite elements in space on locally refined meshes. Our algorithmic developments are substantiated with one regular fracture network and several further configurations in fractured media with large parameter contrasts on small length scales. Therein, the evaluation of the numerical schemes and implementations focuses on three key aspects, namely accuracy, monotonicity, and computational costs.
Relational Quantum Mechanics: Ozawa’s Intersubjectivity Theorem as Justification of the Postulate on Internally Consistent Descriptions
Authors: Khrennikov Andrei 
Published: May 2024

AbstractThe Ozawa’s intersubjectivity theorem (OIT) proved within quantum measurement theory supports the new postulate of relational quantum mechanics (RQM), the postulate on internally consistent descriptions. But from OIT viewpoint postulate’s formulation should be completed by the assumption of probability reproducibility. We remark that this postulate was proposed only recently to resolve the problem of intersubjectivity of information in RQM. In contrast to RQM for which OIT is a supporting theoretical statement, QBism is challenged by OIT.
A variational formulation for three-dimensional linear thermoelasticity with ‘thermal inertia’
Authors: Giorgio Ivan , Placidi Luca 
Published: May 2024

AbstractA variational model has been developed to investigate the coupled thermo-mechanical response of a three-dimensional continuum. The linear Partial Differential Equations (PDEs) of this problem are already well-known in the literature. However, in this paper, we avoid the use of the second principle of thermodynamics, basing the formulation only on a proper definition (i) of kinematic descriptors (the displacement and the entropic displacement), (ii) of the action functional (with kinetic, internal and external energy functions) and (iii) of the Rayleigh dissipation function. Thus, a Hamilton–Rayleigh variational principle is formulated, and the cited PDEs have been derived with a set of proper Boundary Conditions (BCs). Besides, the Lagrangian variational perspective has been expanded to analyze linear irreversible processes by generalizing Biot’s formulation, namely, including thermal inertia in the kinetic energy definition. Specifically, this implies Cattaneo’s law for heat conduction, and the well-known Lord–Shulman model for thermo-elastic anisotropic bodies is then deduced. The developed variational framework is ideal for the perspective of analyzing the thermo-mechanical problems with micromorphic and/or higher-order gradient continuum models, where the deduction of a coherent system of PDEs and BCs is, on the one hand, not straightforward and, on the other hand, natural within the presented variational deduction.
Crossroads between Big Data and entrepreneurship: current key trends
Authors: Lull Juan J. , Cervelló-Royo Roberto , Galdón José Luis 
Published: May 2024

AbstractEntrepreneurship is vital for economic growth and development, as it fosters innovation, creates jobs, and enhances competition and competitiveness. At the same time, in contemporary society, where the Internet has assumed the role of the primary instrument for both communication and commerce, effective utilisation of vast amounts of data has become imperative for businesses, especially in the entrepreneurial environment. To identify the main connections in two of the currently most trending concepts in business, we undertook a systematic literature review focusing on Big Data, entrepreneurship, and their interconnections in business management through 301 research documents. While numerous studies have already delved individually into Big Data and entrepreneurship, the interconnection between these concepts still has research potential. Our results reflect a growing interest in leading research on these topics, with specific leading authors and countries. Furthermore, we show and discuss a conceptual map consisting of five clusters, unveiling interesting connections such as the impact of blockchain on firms, the correlation between Big Data and firm performance, the role of data science, and the significance of Big Data analytics for operational performance. The article ends by examining how Big Data and entrepreneurship change the business landscape. While entrepreneurs use data for decision-making, innovation, and tailored customer experiences, there are lingering concerns such as data security and privacy. The future of business and innovation will depend, in part, on the crossroads between entrepreneurs and Big Data technologies.
Can the cyanide metabolite, 2-aminothiazoline-4-carboxylic acid, be used for forensic verification of cyanide poisoning?
Authors: Alluhayb Abdullah H. , Severance Carter , Hendry-Hofer Tara , Bebarta Vikhyat S. , Logue Brian A. 
Published: May 2024

Abstract
Purpose
Forensic verification of cyanide (CN) poisoning by direct CN analysis in postmortem blood is challenging due to instability of CN in biological samples. CN metabolites, thiocyanate (SCN−) and 2-aminothiazoline-4-carboxylic acid (ATCA), have been proposed as more stable biomarkers, yet it is unclear if either is appropriate for this purpose. In this study, we evaluated the behavior of CN biomarkers in postmortem swine and postmortem blood to determine which serves as the best biomarker of CN exposure.

Methods
CN, SCN−, and ATCA were measured in postmortem swine (N = 8) stored at 4 °C and postmortem blood stored at 25 °C (room temperature, RT) and 37 °C (typical human body temperature, HBT).

Results
Following CN poisoning, the concentration of each CN biomarker increased well above the baseline. In postmortem swine, CN concentrations declined rapidly (t1/2 = 34.3 h) versus SCN− (t1/2 = 359 h, 15 days) and ATCA (t1/2 = 544 h, 23 days). CN instability in postmortem blood increased at RT (t1/2 = 10.7 h) and HBT (t1/2 = 6.6 h). SCN− and ATCA were more stable than CN at all storage conditions. In postmortem swine, the t1/2s of SCN− and ATCA were 15 and 23 days, respectively. While both the t1/2s of SCN− and ATCA were relatively lengthy, endogenous levels of SCN− were much more variable than ATCA.

Conclusion
While there are still questions to be answered, ATCA was the most adept forensic marker of CN poisoning (i.e., ATCA produced the longest half-life, the largest increase above baseline levels, and most stable background concentrations).
Cultural semiotic resources in young children’s science drawings
Authors: Monteira Sabela F. , Jiménez-Aleixandre María Pilar , Martins Isabel 
Published: May 2024

AbstractThis study aims to explore the meanings communicated by young children with visual cultural semiotic resources available in the science classroom. It is a case study in an Early Childhood Education classroom of 23 children (3–4 years old) and their teacher, all engaged in a long-term science project about snails. We focus on the analysis of two series of drawings of snails made by children a month apart, examined through two complementary lenses: comparative content and social semiotics. The findings show that, during their first year of formal schooling, children acquired a range of semiotic resources to communicate to others, which are part of their classroom culture, rather than explicitly taught. Children used these resources to construct sophisticated meanings through their science drawings, highlighting what they considered important and accounting for different modalities and categories. These results point to the importance of supporting drawing tasks in early years, as well as providing opportunities for discussing and interpreting representations. A methodological contribution of this research regards the combination of two complementary foci in the analysis of children’s drawings that allows for a nuanced examination of their learning and abilities for meaning making.
Linking self-regulated learning to community of inquiry in online undergraduate courses: A person-centered approach
Authors: Na Chungsoo , Jeong Soojeong , Clarke-Midura Jody , Shin Youngin 
Published: May 2024

AbstractThe Community of Inquiry (CoI) framework has gained widespread recognition as a theoretical model for understanding student learning in online environments. Despite its prevalence, CoI has been critiqued for its limited emphasis on learners’ proactive roles in self-regulating their own learning. To address this, researchers have suggested integrating self-regulated learning (SRL) into the CoI framework. This integration calls for empirical research to explore the relationship between SRL and the three established CoI presences: teaching, social, and cognitive. Using a person-centered approach, this study examines how varying SRL skills among 750 undergraduate students in an online introductory mathematics course are related to the three CoI components. Latent profile analyses identified five distinct SRL profiles: minimal regulators, low regulators with limited social skills, low regulators, moderate regulators, and competent regulators. We found that students in higher SRL profiles demonstrated higher perception of CoI, whereas those in relatively lower SRL profiles showed lower levels of perceived CoI. Our findings underscore the importance of incorporating self-regulation in the CoI framework for a more comprehensive understanding of online learning.
Segmentation of mediastinal lymph nodes in CT with anatomical priors
Authors: Mathai Tejas Sudharshan , Liu Bohan , Summers Ronald M. 
Published: May 2024

Abstract
Purpose
Lymph nodes (LNs) in the chest have a tendency to enlarge due to various pathologies, such as lung cancer or pneumonia. Clinicians routinely measure nodal size to monitor disease progression, confirm metastatic cancer, and assess treatment response. However, variations in their shapes and appearances make it cumbersome to identify LNs, which reside outside of most organs.

Methods
We propose to segment LNs in the mediastinum by leveraging the anatomical priors of 28 different structures (e.g., lung, trachea etc.) generated by the public TotalSegmentator tool. The CT volumes from 89 patients available in the public NIH CT Lymph Node dataset were used to train three 3D off-the-shelf nnUNet models to segment LNs. The public St. Olavs dataset containing 15 patients (out-of-training-distribution) was used to evaluate the segmentation performance.

Results
For LNs with short axis diameter $$\ge $$
≥
8 mm, the 3D cascade nnUNet model obtained the highest Dice score of 67.9 ± 23.4 and lowest Hausdorff distance error of 22.8 ± 20.2. For LNs of all sizes, the Dice score was 58.7 ± 21.3 and this represented a $$\ge $$
≥
10% improvement over a recently published approach evaluated on the same test dataset.

Conclusion
To our knowledge, we are the first to harness 28 distinct anatomical priors to segment mediastinal LNs, and our work can be extended to other nodal zones in the body. The proposed method has the potential for improved patient outcomes through the identification of enlarged nodes in initial staging CT scans.
What is it Like to Evolve? Cultural Evolution as a Lived Experience
Authors: Baldus Bernd 
Published: May 2024

AbstractThe evolution of human culture continues to divide social and biological science. Key issues for both sides are the complexity and variability of culture, the frequency of cultural traits that have no adaptive or functional value, and the apparent exceptionality of human creativity and rationality. This article argues that an examination of how evolution affects the lifetime experience of evolution can reconcile these features of human culture with Darwin’s contention that natural and cultural selection follow the same process of evolution. The article offers a new paradigm that focuses on the relationship between uncertainty and choice in human cultural evolution.
Societal costs before and up to 1 year after the first fracture liaison service visit in patients requiring anti-osteoporosis treatments
Authors: Maas Lieke , Boonen Annelies , Wyers Caroline E. , Bours Sandrine , van den Bergh Joop P. , Evers Silvia M. , van Kuijk Sander M. J. , Hiligsmann Mickaël 
Published: May 2024

Abstract
Summary
This study aimed to estimate societal and healthcare costs incurred before and 1 year after the first fracture liaison services (FLS) visit and to explore differences in fracture type. All costs after 1 year significantly decreased compared to costs preceding the first visit. Fracture type did not significantly affect costs.

Introduction
Limited literature is available on resource utilization and costs of patients visiting fracture liaison services (FLS). This study aimed to estimate the societal and healthcare costs incurred by patients with a recent fracture requiring anti-osteoporosis medication before and 1 year after the first FLS visit and to explore differences according to fracture type.

Methods
Resource utilization was collected through a self-reported questionnaire with a 4-month recall on health resource utilization and productivity losses immediately following the first FLS visit, and 4 and 12 months later. Unit costs derived from the national Dutch guideline for economic evaluations were used to compute societal and healthcare costs. Linear mixed-effect models, adjusted for confounders, were used to analyze societal and healthcare costs over time as well as the effect of fracture type on societal and healthcare costs.

Results
A total of 126 patients from two Dutch FLS centers were included, of whom 72 sustained a major fracture (hip, vertebral, humerus, or radius). Societal costs in the 4 months prior to the first visit (€2911) were significantly higher compared to societal costs 4 months (€711, p-value = 0.009) and 12 months later (€581, p-value = 0.001). Fracture type did not have a significant effect on total societal or healthcare costs. All costs 12 months after the initial visit were numerically lower for major fractures compared to others.

Conclusion
Societal and healthcare costs in the year following the first FLS visit significantly decreased compared to those costs preceding the first visit.