bluuebunny/crossref_metadata_2025_split huggingface dataset:
Crossing the Threshold by/around Water: A Critical Reading of the Liminal Experiences of Adolescents and Young Adults in Feeding the Moonfish and Our Place
Authors: Bayoumy Heidi Mohamed 
Published: March 2024

Abstract
This study seeks to examine water as a liminal symbol that reflects and symbolizes the liminal identities of adolescents and young adults in two selected plays for young adults: Feeding the Moonfish (2011) by Barbara Wiechmann and Our Place (2015) by Terry Gabbard. Feeding the Moonfish deals with the young adults Martin and Eden who suffer from traumatic experiences. They go to the dock by the lake to rediscover themselves, and, eventually, heal by the water. In a similar setting, Our Place comprises five stories that revolve around adolescents and young adults’ feelings of loss, fragmentation, frustration, love, and death. In both plays, the characters go through the three stages of liminality defined by Arnold van Gennep: the pre-liminal, the liminal, and the post-liminal and, finally, emerge as reborn/healed. Water is a complex liminal symbol that reflects the experiences of adolescence and young adults, and combines contradictory meanings which are essential, expressive, and, most importantly, complementary for the development of the characters and for their eventual recovery. Using the concept of liminality and adolescent psychology to read scenes in which liminal experiences (confusion, indecisiveness, and disorientation) are present, this study argues that the depiction of liminal experiences near water in these plays for young adults offers complex symbols for the study of young adulthood and for encountering and responding to traumas experienced in adolescence.
Genomic and common garden data reveal significant genetic differentiation in the endangered San Fernando Valley spineflower Chorizanthe parryi var. fernandina
Authors: Rogers Deborah L. , Washburn Loraine Kohorn , Birker Cheryl , Labbé Michelle A. , Campbell Matthew A. , Schreier Andrea D. 
Published: March 2024

AbstractSan Fernando Valley spineflower (Chorizanthe parryi var. fernandina [S. Watson] Jeps.) (Polygonaceae) is an herbaceous annual plant, endemic to California, and until rediscovered in 1999 had been thought to be extinct for almost seven decades. Historically documented at 10 locations, it currently persists at 2, separated by approximately 27 km. State listed as endangered, a description of its genetic diversity and structure is of conservation interest. After determining a lack of variation in ploidy, we examined genetic variation from samples within both populations: a common garden study for potentially adaptive genetic variation in selected growth and phenological traits and analysis of single nucleotide polymorphisms identified through restriction-site associated DNA sequencing. Both measures indicated that this highly restricted taxon nevertheless harbors substantial levels of genetic diversity and has significant between- and within-population genetic structure. Combining approaches from population genomics and common garden studies provided more insight into the patterns and basis of genetic diversity than is typical for studies of non-model species. Although local adaptation was not specifically studied (i.e., via reciprocal transplant studies), the differences determined from these two independent lines of evidence indicate that mixing gene pools between populations is not recommended at this time. Further, with significant differences revealed among subpopulations, we caution against mixing genotypes across subpopulations for the most part, and without much more evidence that this would not pose a risk of outbreeding depression. The importance of supporting pollinator health and diversity is highlighted. With genetic diversity—particularly with an annual species—being dynamic, fluctuating with the usual processes and with contributions from the soil seedbank, we recommend periodic resampling to monitor genetic diversity and structure. Climate change is anticipated to contribute to this variability.
AI-experiments in education: An AI-driven randomized controlled trial for higher education research
Authors: Cingillioglu Ilker , Gal Uri , Prokhorov Artem 
Published: March 2024

AbstractThis study presents a novel approach contributing to our understanding of the design, development, and implementation AI-based systems for conducting double-blind online randomized controlled trials (RCTs) for higher education research. The process of the entire interaction with the participants (n = 1193) and their allocation to test and control groups was executed seamlessly by our AI system, without human intervention. In this fully automated experiment, we systematically examined eight hypotheses. The AI-experiment strengthened five of these hypotheses, while not accepting three of the factors previously acknowledged in the literature as influential in students’ choices of universities. We showcased how AI can efficiently interview participants and collect their input, offering robust evidence through an RCT (Gold standard) to establish causal relationships between interventions and their outcomes. This approach may enable researchers and industry practitioners to collect data from large samples on which such experiments can be conducted with and by AI to produce statistically reproducible, reliable, and generalizable results in an efficient, rigorous and ethical way.
Debiasing the availability heuristic in student loan decision-making
Authors: Salas-Velasco Manuel 
Published: March 2024

AbstractThe availability heuristic is a cognitive bias that affects various aspects of decision-making, including financial decisions. Based on a randomized controlled experiment, this study assesses the effectiveness of a debiasing treatment designed to prevent the effect of the availability heuristic in student loan decision-making. Experimental subjects were explained that there is a bias that may affect the decision of whether or not to pursue a master’s degree and take out a graduate loan to finance it, and they were recommended to base their decision on reliable and verified sources of information as well as expert advice. This specific debiasing strategy is tested empirically. Specifically, this study shows positive causal effects of the debiasing intervention on two indices of student loan decision-making, which were constructed as summary indicators of student loan debt attitude, the perception that significant referents approve the student loan indebtedness, financial self-efficacy in student loan decision-making, and graduate loan borrowing intention. The article highlights the need for higher education institutions seeking to make financial education effective to be concerned with reporting on (and raising awareness of) psychological factors that are present in making financial decisions as well.
Tailoring responsible research and innovation to the translational context: the case of AI-supported exergaming
Authors: Blank Sabrina , Mason Celeste , Steinicke Frank , Herzog Christian 
Published: March 2024

AbstractWe discuss the implementation of Responsible Research and Innovation (RRI) within a project for the development of an AI-supported exergame for assisted movement training, outline outcomes and reflect on methodological opportunities and limitations. We adopted the responsibility-by-design (RbD) standard (CEN CWA 17796:2021) supplemented by methods for collaborative, ethical reflection to foster and support a shift towards a culture of trustworthiness inherent to the entire development process. An embedded ethicist organised the procedure to instantiate a collaborative learning effort and implement RRI in a translational context. Within the interdisciplinary setting of the collaboration and with the support of a technoethicist, we successfully identified relevant, project-specific challenges and developed a roadmap with derived actions, thus meaningfully integrating RRI into the development process. We discuss the methodological procedure in terms of its effectiveness and efficiency, the allocation of responsibilities and roles, particularly regarding potential frictions in the interdisciplinary context with embedded ethics, and the challenges of the translational context. We conclude that the responsibility-by-design standard effectively established a productive workflow for collaborative investigation and work on ethical challenges. We reflect on methodological difficulties and propose possible avenues to our approach.
Anti-inflammatory potential of simvastatin and amfenac in ARPE-19 cells; insights in preventing re-detachment and proliferative vitreoretinopathy after rhegmatogenous retinal detachment surgery
Authors: Harju Niina , Hytti Maria , Kolari Onni , Nisula Hilkka , Loukovaara Sirpa , Kauppinen Anu 
Published: March 2024

Abstract
Purpose
Rhegmatogenous retinal detachment is a severe vision-threatening complication that can result into proliferative vitreoretinopathy (PVR) and re-detachment of the retina if recovery from surgery fails. Inflammation and changes in retinal pigment epithelial (RPE) cells are important contributors to the disease. Here, we studied the effects of simvastatin and amfenac on ARPE-19 cells under inflammatory conditions.

Methods
ARPE-19 cells were pre-treated with simvastatin and/or amfenac for 24 h after which interleukin (IL)-1α or IL-1β was added for another 24 h. After treatments, lactate dehydrogenase release, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) processing, nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activity, prostaglandin E2 (PGE2) level, and extracellular levels of IL-6, IL-8, monocytic chemoattractant protein (MCP-1), vascular endothelial growth factor (VEGF), and pigment epithelium-derived factor, as well as the production of reactive oxygen species (ROS) were determined.

Results
Pre-treatment of human ARPE-19 cells with simvastatin reduced the production of IL-6, IL-8, and MCP-1 cytokines, PGE2 levels, as well as NF-κB activity upon inflammation, whereas amfenac reduced IL-8 and MCP-1 release but increased ROS production. Together, simvastatin and amfenac reduced the release of IL-6, IL-8, and MCP-1 cytokines as well as NF-κB activity but increased the VEGF release upon inflammation in ARPE-19 cells.

Conclusion
Our present study supports the anti-inflammatory capacity of simvastatin as pre-treatment against inflammation in human RPE cells, and the addition of amfenac complements the effect. The early modulation of local conditions in the retina can prevent inflammation induced PVR formation and subsequent retinal re-detachment.
Addressing Knowledge Gaps in ITSM Practice with “Learning Digital Commons”: A Case Study
Authors: Ramakrishnan Muralidharan , Gregor Shirley , Shrestha Anup , Soar Jeffrey 
Published: March 2024

AbstractInformation Technology Service Management (ITSM) constitutes a suite of specialized organizational capabilities aimed at optimizing the value derived from IT services. The practice of ITSM encompasses a range of complementary frameworks. However, the practitioner community lacks a comprehensive, holistic understanding of the knowledge embedded within these frameworks.Addressing this gap, we developed Service-Symphony, an instance of a Learning Digital Commons (LEDICO) designed to empower the ITSM community with a holistic knowledge-learning experience, with design principles based on epistemic logic, cognitive constructivist learning theory and cognitive schema theory. Leveraging the Design Science Research (DSR) paradigm, we systematically constructed and assessed Service-Symphony. Evaluation tools included surveys and web analytics. Survey responses revealed a consensus among participants, with the majority expressing alignment with the four design principles underpinning Service-Symphony. Web analytics data further indicated significant engagement, with 148,796 users accessing Service-Symphony between April 2019 and September 2022.This paper contributes both to theory and practice. Theoretical contributions include the establishment of a conceptual model and a multi-grounded design theory based on cognitive constructivist learning, cognitive schema and epistemic logic. The practical contributions include e the deployment of a public domain ITSM digital commons tailored to the specific needs of the ITSM community, which is also used as supplementary learning resource for ITSM students.
Schematic Program Proofs with Abstract Execution
Authors: Steinhöfel Dominic , Hähnle Reiner 
Published: March 2024

AbstractWe propose Abstract Execution, a static verification framework based on symbolic execution and dynamic frames for proving properties of schematic programs. Since a schematic program may potentially represent infinitely many concrete programs, Abstract Execution can analyze infinitely many programs at once. Trading off expressiveness and automation, the framework allows proving many interesting (universal, behavioral) properties fully automatically. Its main application are correctness proofs of program transformations represented as pairs of schematic programs. We implemented Abstract Execution in a deductive verification framework and designed a graphical workbench supporting the modeling process. Abstract Execution has been applied to correct code refactoring, analysis of the cost impact of transformation rules, and parallelization of sequential code. Using our framework, we found and reported several bugs in the refactoring engines of the Java IDEs IntelliJ IDEA and Eclipse, which were acknowledged and fixed.
Structural Realism About the Free Energy Principle, the Best of Both Worlds
Authors: Beni Majid D. 
Published: March 2024

AbstractThere are realist and antirealist interpretations of the free energy principle (FEP). This paper aims to chart out a structural realist interpretation of FEP. To do so, it draws on Worrall’s (Dialectica 43(1–2): 99–124, 1989) proposal. The general insight of Worrall’s paper is that there is progress at the level of the structure of theories rather than their content. To enact Worrall’s strategy in the context of FEP, this paper will focus on characterising the formal continuity between fundamental equations of thermodynamics—such as Boltzmann’s equation and Gibbs’s equation—on the one hand, and Friston’s characterisation of FEP on the other. Lack of a universal consensus on the physical character of entities that feature in thermodynamics, information theory and FEP notwithstanding, I argue that there is structural continuity and unity at the level of mathematical equations that regiment entropy, information and free energy. The existence of such structural continuity and unity provides grounds for structural realism about FEP.
Power Transmission Line Inspections: Methods, Challenges, Current Status and Usage of Unmanned Aerial Systems
Authors: Ahmed Faiyaz , Mohanta J. C. , Keshari Anupam 
Published: March 2024

AbstractCondition monitoring of power transmission lines is an essential aspect of improving transmission efficiency and ensuring an uninterrupted power supply. Wherein, efficient inspection methods play a critical role for carrying out regular inspections with less effort & cost, minimum labour engagement and ease of execution in any geographical & environmental conditions. Earlier various methods such as manual inspection, roll-on wire robotic inspection and helicopter-based inspection are preferably utilized. In the present days, Unmanned Aerial System (UAS) based inspection techniques are gradually increasing its suitability in terms of working speed, flexibility to program for difficult circumstances, accuracy in data collection and cost minimization. This paper reports a state-of-the-art study on the inspection of power transmission line systems and various methods utilized therein, along with their merits and demerits, which are explained and compared. Furthermore, a review was also carried out for the existing visual inspection systems utilized for power line inspection. In addition to that, blockchain utilities for power transmission line inspection are discussed, which illustrates next-generation data management possibilities, automating an effective inspection and providing solutions for the current challenges. Overall, the review demonstrates a concept for synergic integration of deep learning, navigation control concepts and the utilization of advanced sensors so that UAVs with advanced computation techniques can be analyzed with different aspects of implementation.
Rethinking the city resilience: COM-B model-based analysis of healthcare accessing behaviour changes affected by COVID-19
Authors: Yan Jiayi , Fang Zigeng , Chen Long , Tang Junqing , Lu Qiuchen , Lin Xuhui 
Published: March 2024

AbstractThe global pandemic of COVID-19 has been influencing people’s lives and the cities. Not only people’s physical and mental health have been threatened, but also the city operation has been profoundly affected from different perspectives (e.g., social and economic) permanently. How cities can efficiently react and response to improve city resilience is an urgent issue to be addressed. The healthcare system as a vital part of the city systems is confronting intense pressure and many challenges under this emergent public health crisis of COVID-19, which might cause huge impacts on the whole city’s operation. Also, human beings as the direct victims of this public health crisis, their behaviour changes impacts on the healthcare system and the city could have been inevitable but have been neglected. In this context, this paper intends to study the citizen healthcare accessing behaviours changes in the post-pandemic era, and to unearth their impacts on the healthcare system and the city operation. For this purpose, first, a framework of influential factors for healthcare accessing was established based on a bidirectional “capability, opportunity, motivation, and behaviour” (COM-B) model and the comprehensive literature review. In which, 43 factors that would influence citizen healthcare accessing behaviour were identified and classified. Thus, based on the proposed framework, two cases (i.e., UK and China) were analysed in depth and compared based on a questionnaire survey to evaluate the factor importance and relationships under different scenarios. And the most influential factors based on analysis results are classified into 12 aspects (e.g., healthcare capability, policy support, information updating etc.). Further, a novel behaviour-healthcare system-city model based on the COM-B model was developed to rethink and indicate the relationships among citizen behaviour, healthcare system and city operation. The research results can be used by policymakers and researchers to improve the city resilience by enabling immediate responses to city systems and citizens behaviours confronting city emergencies.
On inductive biases for the robust and interpretable prediction of drug concentrations using deep compartment models
Authors: Janssen Alexander , Bennis Frank C. , Cnossen Marjon H. , Mathôt Ron A. A. ,   for the OPTI-CLOT Study Group and SYMPHONY Consortium
Published: March 2024

AbstractConventional pharmacokinetic (PK) models contain several useful inductive biases guiding model convergence to more realistic predictions of drug concentrations. Implementing similar biases in standard neural networks can be challenging, but might be fundamental for model robustness and predictive performance. In this study, we build on the deep compartment model (DCM) architecture by introducing constraints that guide the model to explore more physiologically realistic solutions. Using a simulation study, we show that constraints improve robustness in sparse data settings. Additionally, predicted concentration–time curves took on more realistic shapes compared to unconstrained models. Next, we propose the use of multi-branch networks, where each covariate can be connected to specific PK parameters, to reduce the propensity of models to learn spurious effects. Another benefit of this architecture is that covariate effects are isolated, enabling model interpretability through the visualization of learned functions. We show that all models were sensitive to learning false effects when trained in the presence of unimportant covariates, indicating the importance of selecting an appropriate set of covariates to link to the PK parameters. Finally, we compared the predictive performance of the constrained models to previous relevant population PK models on a real-world data set of 69 haemophilia A patients. Here, constrained models obtained higher accuracy compared to the standard DCM, with the multi-branch network outperforming previous PK models. We conclude that physiological-based constraints can improve model robustness. We describe an interpretable architecture which aids model trust, which will be key for the adoption of machine learning-based models in clinical practice.
Motives for Vaccination Against COVID-19 Among the Ultra-orthodox Jewish Community in Israel
Authors: Schiff Miriam , Sharon-Lavi Nitzan 
Published: March 2024

AbstractAccording to official data, the ultra-Orthodox group in Israel had the highest COVID-19 infection rate yet the lowest vaccination rate compared to the general population. The present study aimed to explore the rate of vaccine uptake as well as reported reasons for vaccine avoidance. In addition, we examined whether several protection motivation theory (PMT) components are good predictors of vaccine uptake. The components we addressed were: perceived susceptibility to the threat of COVID-19, perceived severity of the virus, and perceived efficiency and safety of the vaccine (i.e., response efficacy). The sample included 623 individuals (337 men) aged 18 + who were drawn from a database of a survey company specializing in the ultra-Orthodox community. We conducted a cross-sectional online survey between June 22, 2021, and July 7, 2021, approximately six months after the beginning of vaccination distribution. Results revealed that 65.8% of the participants (versus 89% of the general population) were vaccinated. Women were vaccinated at lower rates than men, whereas those in the Misnagdim ultra-Orthodox subgroup were vaccinated at higher rates than other subgroups in that community. The most prominent reasons for vaccine avoidance were perceived immunity based on prior infection by the virus and lack of trust in the vaccine’s safety. In support of the PMT model, the perceived severity of the virus and the vaccine high efficacy were significant predictors of vaccine uptake. The study results call for better outreach to this community and specific psycho-education interventions tailored for its women.
GENERALIZED FRACTION RULES FOR MONOTONICITY WITH HIGHER ANTIDERIVATIVES AND DERIVATIVES
Authors: Bitsouni Vasiliki , Gialelis Nikolaos , Marinescu Dan Ştefan 
Published: March 2024

AbstractWe first introduce the generic versions of the fraction rules for monotonicity, i.e., the one that involves integrals known as Gromov’s theorem and the other that involves derivatives known as L’Hôpital’s rule for monotonicity, which we then extend to high-order antiderivatives and derivatives, respectively.