bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Investigation of Tufa Microbialites in the Terrestrial Ecosystem of Adilcevaz (Bitlis) According to the Conservation Approach
Authors: Çiltepe Fırat , Uzun Alper 
Published: February 2024

AbstractDue to their rarity, scientific, and aesthetic value, or being a part of an important geological process, some natural formations (like calc tufa) on Earth have to be protected. While the formation and development processes of the microbialites in Lake Van continue, the microbiolites in Adilcevaz remained outside the lake and became fossils. These structures are arranged approximately 200 m wide and 800 m long, reaching heights of 6 m in places. In this study, the area where the Adilcevaz tufa microbialites, surviving to the present day as a remnant of the level change stages of Lake Van as well as their aesthetic appearance and scientific importance, was evaluated according to the conservation approach. Phenomenology research design, one of the qualitative research designs, was used in the study. Although the research is basically a field study, secondary sources were used and face-to-face interviews were conducted. The semi-structured interview technique, one of the qualitative research techniques, was used for the interviews that were held with the participants on the basis of pre-prepared questionnaire forms. Following the interviews, the data were evaluated with descriptive and interpretive analyzes. As a result of the field observations and interviews, the area was suggested to be evaluated as a “natural monument” to protect it and carry out activities for tourism purposes. It is understood that the area has an important potential in terms of ecotourism, and should be proposed to be included in the UNESCO World Heritage List together with the Lake Van microbialites, the largest microbialites in the world.
Statistical Methods for Selective Biomarker Testing
Authors: Ding A. Adam , DelRocco Natalie , Wu Samuel S. 
Published: February 2024

AbstractBiomarkers are critically important tools in modern clinical diagnosis, prognosis, and classification/prediction. However, there are fiscal and analytical barriers to biomarker research. Selective Genotyping is an approach to increasing study power and efficiency where individuals with the most extreme phenotype (response) are chosen for genotyping (exposure) in order to maximize the information in the sample. In this article, we describe an analogous procedure in the biomarker testing landscape where both response and biomarker (exposure) are continuous. We propose an intuitive reverse-regression least squares estimator for the parameters relating biomarker value to response. An expression for robust standard error and corresponding confidence interval are derived. A simulation study is used to demonstrate that this method is unbiased and efficient relative to estimates from random sampling when the joint normal distribution assumption is met, and to compare the estimator to an alternative under a related sampling design. We illustrate application of proposed methods on data from a chronic pain clinical trial.
pH and ionic liquids impacts on SiO2-nanoparticles for surface phenomena modifications for heavy acidic crude oil
Authors: Abbood Nabeel Kadhim , Al-Mayyahi Mohammad A. , Mehdipour Reza , Hosseini Seyednooroldin 
Published: February 2024

AbstractThe current study is designed and performed to examine the impact of a combinative method including the new class of surfactants from the ionic liquids (ILs) family (imidazolium type) and nanoparticles (NPs) namely silicon dioxide nanoparticles (SiO2-NPs). Besides, the effect of pH concomitant with the other parameters was examined since pH is an essential operating parameter especially if researchers dealing with a non-neutral type of crude oil. Unfortunately, although using chemicals is highly effective, there are limited investigations dealing with a new class of surfactants, NPs, and operating conditions such as pH. In other words, although there are several investigations dealing with alkaline, polymers, and surfactants, a few studies were performed to find the interactions between the new class of surfactants such as ILs, NPs (no matter metallic-based or nonmetallic-based type) and pH which can directly manipulate the in-situ surfactant formation which acts similarly to alkaline injection. In this way, two different surfactants namely 1-dodecyl-3-methyl imidazolium chloride ([C12mim][Cl]), and 1-octadecyl-3-methyl imidazolium chloride ([C18mim][Cl]) and SiO2-NPs with concentrations of 0–2000 ppm and 0–1000 ppm are used for interfacial tension (IFT) and wettability alteration investigations using heavy acidic crude oil. The measured IFT values revealed that increasing the surfactant concentration to 2000 ppm can reduce the IFT to the minimum value of 0.94 and 0.88 mN/m for [C12mim][C] and [C18mim][Cl], respectively. Besides, the measurements revealed that it is possible to reach the water-wet condition with contact angles of 81.3° and 74.5° for [C12mim][Cl] and [C18mim][Cl], respectively. Moreover, the measurements revealed that increasing the pH from 3 to 11 has a considerable effect on the IFT reduction and wettability alteration because of in-situ surfactant formation (reaction between the OH− and the functional group of the crude oil) which can act as a solution including alkaline in it. Finally, the IFT and contact angle were measured using 1000 and 500 ppm of [C12mim][Cl] and [C18mim][Cl] while the pH and SiO2-NPs concentrations ranged between 3–11 and 0–1000 ppm, respectively. The measurements revealed the significant impact of SiO2-NPs for reducing the IFT and changing the wetness of the rock surface with a minimum IFT value of 0.35 mN/m and contact angle of 23.3° (strongly water-wet condition). Considering the obtained results, it can be concluded that the proposed combinative method is highly applicable for higher oil production using the lab-scale equipment. The point is that the further systematic investigations are required since using combinative methods for enhanced oil recovery (EOR) purposes are still in the preliminary stages of their appearance.
Immersive Experience and Virtual Reality
Authors: Balcerak Jackson Magdalena , Balcerak Jackson Brendan 
Published: February 2024

AbstractMuch of the excitement about virtual reality and its potential for things like entertainment, art, education, and activism is its ability to generate experiences that are powerfully immersive. However, discussions of VR tend to invoke the notion of immersive experience without subjecting it to closer scrutiny; and discussions often take it for granted that immersive experience is a single unified phenomenon. Against this, we argue that there are four distinct types or aspects of immersive experience that should be distinguished: representational immersion, which corresponds roughly to what is sometimes called “psychological presence”; participatory immersion, which is related to the interactive aspects of VR experience; affective immersion, which has to do with the subject’s emotional relation to the experience; and narrative immersion, which captures the phenomenon of being caught up in the flow of events experienced. We argue that this four-way distinction helps us understand the powerfully immersive character of VR, while also recognizing its continuity with the immersion we experience with media such as novels, films, and music. We also argue that the account of immersion we offer here lets us better understand the connection between VR and empathy, charting a middle course between extreme enthusiasts who view VR as the ultimate “empathy machine” and extreme skeptics who argue that this attitude is misguided.
The role of multidisciplinary diagnostic and therapeutic model of care in Lamb-Shaffer syndrome - case report
Authors: Sajewicz-Radtke Urszula , Łada-Maśko Ariadna , Lipowska Małgorzata , Radtke Bartosz M. , Lipska-Ziętkiewicz Beata S. , Krempla-Patron Katarzyna 
Published: February 2024

AbstractThis case study illustrates a multidisciplinary diagnostic and therapeutic model of care for a 7-year-old male with Lamb–Shaffer syndrome (LAMSHF). LAMSHF is an ultra-rare genetic neurodevelopmental disorder, caused by heterozygous alterations in the SOX5 gene. An integrative model of therapy of cognitive functions and speech is described. The presented approach allows the development of language competences through stimulation of basic cognitive functions, which allows the learning of the abstract rules of an inflected language. A surprising, unexpected improvement in the cognitive functioning of the child was observed (both in terms of reasoning and speech), as well as an increase in his independence. The clinically important problem of the need for continued stimulation of cognitive development, in spite of the unfavourable prognosis associated with LAMSHF, is highlighted.
An Exploratory Study of a Brief Measure of Job Satisfaction in Pennsylvania School Psychologists
Authors: Crothers Laura M. , Steeves Taylor , Kolbert Jered B. , Schreiber James B. , Schmitt Ara J. , Drischler Brianna , Paulson Kelly , Cowley Jessica , Klass Amelia , Vafiadis Athena , Perfetto Kayla 
Published: February 2024

AbstractIn this exploratory study, we adapted items from a previously developed measure of job satisfaction, the Measure of Job Satisfaction (MJS), an instrument first developed for use with community nurses in the UK, to create a brief, 15-item instrument (Job Satisfaction—Brief) applicable to practitioners of school psychology from Pennsylvania (N = 94). In order to examine the underlying factor structures of the items adapted from the Measure of Job Satisfaction (MJS) instrument, exploratory factor analysis (EFA) was applied in the JAMOVI Version 2.3.19.0 with maximum likelihood estimation to be implemented for the ordered categorical scale. Two factors were extracted from the data: Factor One: Satisfaction with Intrapersonal Development and Clinical Accomplishment and Factor Two: Satisfaction with Advancement, Financial Compensation, and Rank. The uses for the measure and recommended future directions are discussed.
Improving academic performance predictions with dual graph neural networks
Authors: Huang Qionghao , Zeng Yan 
Published: February 2024

AbstractAcademic performance is a crucial issue in the field of Online learning analytics. While deep learning-based models have made significant progress in the era of big data, many of these methods need help to capture the complex relationships present in online learning activities and student attributes, which are essential for improving prediction accuracy. We present a novel model for predicting academic performance in this paper. This model harnesses the power of dual graph neural networks to effectively utilize both the structural information derived from interaction activities and the attribute feature spaces of students. The proposed model uses an interaction-based graph neural network module to learn local academic performance representations from online interaction activities and an attribute-based graph neural network to learn global academic performance representations from attribute features of all students using dynamic graph convolution operations. The learned representations from local and global levels are combined in a local-to-global representation learning module to generate predicted academic performances. The empirical study results demonstrate that the proposed model significantly outperforms existing methods. Notably, the proposed model achieves an accuracy of 83.96% for predicting students who pass or fail and an accuracy of 90.18% for predicting students who pass or withdraw on a widely recognized public dataset. The ablation studies confirm the effectiveness and superiority of the proposed techniques.
Can high-skilled Mexicans’ migration adopt a positive externality view under a stakeholders’ approach?
Authors: Salamanca Elizabeth , Alcaraz Jorge 
Published: February 2024

AbstractOne of the Sustainable Development Goals (SDGs) is the generation and transfer of knowledge that enhances productivity. High-skilled immigrants from emerging countries have become relevant players in alleviating the talent shortage developed countries face and providing them with continuous knowledge that promotes innovation and competitiveness. But to what extent does this knowledge generation occur at the expense of emerging economies’ development? This research explores the mechanisms that may favor the attainment of this SDG in migrants’ sending countries. Through the lenses of both the externalities and the stakeholders’ approach, it analyzes the case of highly skilled Mexicans migrating to the U.S. It suggests that these talented people can integrate brain chains that lessen the weaknesses of the home country’s national innovation system and foster Mexico’s absorptive capacities if they count on the support of the private sector and the academia and the indispensable endorsement of the home country government through the creation and execution of sensible public policies.
Optimisation of Vacuum Distillation Units in Oil Refineries Using Surrogate Models
Authors: H’ng Shi Xie , Ng Lik Yin , Ng Denny K. S. , Andiappan Viknesh 
Published: February 2024

AbstractTo ensure the optimum performance of downstream processes in a petrochemical refinery, the operation of a vacuum distillation unit (VDU) is critical. It needs to satisfy the yield and quality requirements of the downstream process. Otherwise, it will result in a loss of profitability in the refinery. Hence, it is important to optimise the operation of the VDU to ensure optimum performance. Traditionally, VDU is operated within the design envelope, and its operation condition is fine-tuned based on the operator’s experience. However, such action does not guarantee the optimum performance of the entire refinery as it only considers the operation of VDU without understanding the effects towards downstream processes. Therefore, this work presents a framework to optimise VDU operations with consideration of the downstream processes. The framework consists of process simulation, surrogate modelling, and multi-objective optimisation. The developed framework aims to determine trade-offs between high vacuum gas oil (HVGO) yield and total annualised cost (TAC) of a refinery that considers the needs of downstream operations. In this work, crude oil blending ratio, furnace outlet temperature, flash zone temperature, column top pressure, column bottom pressure, stripping steam flowrate, HVGO pump-around flowrate, and light vacuum gas oil (LVGO) pump-around flowrate of the VDU are to be optimised. Based on the optimised result, the heavy-light crude blend achieves higher HVGO yield and lower TAC, and the optimised results were validated with the simulation results via Aspen HYSYS. The proposed methodology was proven to have accurate estimations of the VDU operation in the process simulation environment. Moreover, the optimised results can provide insight into the optimal process conditions of VDU for the refiners. With this insight, effective operating strategies can be developed to overcome the limitations present in real VDU operations.
Overview of Medical and Biological Applications of Indium(III) Complexes
Authors: Ajiboye Timothy O. , Amao Isaac O. , Adeyemi Wale J. , Babalola Stephen O. , Akinsuyi Oluwamayowa S. , Ogunrombi Modupe O. , Ogunlaja Adeniyi S. , Mhlanga Sabelo D. 
Published: February 2024

AbstractIndium(III) complexes are versatile species that emit Auger electrons which made them a choice for a wide range of biological and medical applications. The properties of these complexes depend on the primary ligand that was used for their syntheses. Herein, methods of synthesizing xanthates, dithiocarbamate, phthalocyanine, thiosemicarbazone and naphthalocyanine complexes of indium(III) are discussed. Also, the methods for synthesizing indium(III) complexes having other ligands are highlighted. Furthermore, antibacterial, antifungal and antiviral potential of the indium(III) complexes are comprehensively discussed. Other biological applications of the complexes such as anticancer, bioimaging, radiopharmaceutical, photodynamic chemotherapy, antioxidants, and optical limiting applications of these indium(III) complexes are comprehensively reviewed. In addition, toxicity of indium(III) complexes towards biological samples are examined because these must be considered in evaluating the safety and efficacy of indium(III) complexes for these numerous applications. Overall, indium(III) complexes are reported to have displayed a good performance in all these biological and medical applications. The future perspectives on the applications of indium(III) complexes are therefore suggested.
Understanding Teachers’ Likelihood of Intervention in Bullying Situations: Testing the Theory of Planned Behavior
Authors: van Aalst Danelien A. E. , Huitsing Gijs , Veenstra René 
Published: February 2024

AbstractDespite the expanding body of research on school bullying and interventions, knowledge of what makes teachers intervene in bullying situations remains limited. Based on the Theory of Planned Behavior, a theoretical framework that combined the predictive elements contributing to teachers’ likelihood of intervening was tested empirically. The model used teachers’ characteristics and behavior as predictors of their tendencies to identify, prevent, and reduce bullying. Survey data of 114 primary school teachers (Mage = 42 years, 87% female, 10 schools) and 66 secondary school teachers (Mage = 40 years, 44% female, 5 schools) were analyzed using multilevel regression models. Teachers’ attitudes (including perceived seriousness of bullying) and behavioral control (including attribution styles) were related to teachers’ likelihood of intervening in six hypothetical bullying situations. Two other main elements of the Theory of Planned Behavior (subjective norms, as measured with perceived collegial support) and the additional element of knowledge (about the distinguishing characteristics of bullying) were unrelated to the likelihood of intervention. These findings emphasize the importance of teachers’ attitudes and attribution styles to the likelihood of intervention. These can be emphasized in teacher training and anti-bullying programs to empower teachers more systematically.
Two Key Mechanisms of Large‐Scale Cross‐Shelf Penetrating Fronts in the East China Sea: Flow Convergence and Thermocline Undulation
Authors: He Zhiwei , Yang Dezhou , Yin Baoshu , Wu Hui 
Published: February 2024

AbstractCross‐shelf penetrating fronts (CPFs) induce significant cross‐shelf exchange of water properties and nutrients, and thus are important to coastal environments. In this study, the characteristics and mechanisms of realistic large‐scale CPFs in the East China Sea in summer were investigated based on a data assimilative model. The model reproduced CPFs matched well with satellite observations. Although the cross‐shelf currents were predominantly offshore off the Zhe‐Min Coast, only three strong large‐scale CPFs occurred in the summer of 2014. The three‐dimensional structure of CPF in the model was similar with that observed in previous research. Two different mechanisms were responsible for the formation of observed CPFs. Two CPFs formed as a result of the convergence of the Taiwan Warm Current (TWC) and the Zhe‐Min Coastal Current (ZMCC), while the other one was caused by the undulation of thermocline. Heat budget analysis suggests that the undulation of thermocline was caused by horizontal and vertical advection. Sensitivity experiments suggest that southerly wind relaxation and tidal forcing are indispensable conditions for CPF formation. Tidal forcing makes the axis of the ZMCC shift offshore by ∼50 km, so that the ZMCC could impinge right against the axis of the TWC. The relaxation of the southerly winds allows the ZMCC to extend southward. Southerly wind relaxation in summer is mostly associated with tropical cyclones. Without winds and synoptic variation of the TWC, CPFs form periodically due to the strengthening of the ZMCC during neap tide period.
High School and Undergraduate Student Volunteers as an Imperfect Solution to Machine Learning Geoscience Research Needs
Authors: Esenther Sarah E. , Gupta Neiv , Vongkitbuncha Chanatip , Lee Mason N. , Smith Laurence C. 
Published: February 2024

AbstractThe machine learning revolution presents geoscientists with exciting new opportunities for research, but is constrained by the need for large, high quality training data sets. Simultaneously, undergraduate and graduate program admissions have become increasingly competitive, pressuring high school and undergraduate students to differentiate themselves through involvement in research at earlier stages. Aligning these two interests provides mutually beneficial opportunities for both geoscientists and early‐stage students. We describe our experiences working with 20 early‐stage students to build a large training data set digitized from satellite images of meltwater drainage patterns on ice sheets. The intent of this Perspective is to share our experience and lessons learned with other machine learning researchers who, like us, may have minimal experience mentoring young volunteer researchers but may seek such partnerships for the first time in response to their machine learning training data set needs. These partnerships enabled creation of a powerful new machine learning model that would have otherwise been infeasible. Student benefits varied with their commitment and proactiveness, ranging from exposure to geoscience research and a resume line item to strong letters of recommendation and ongoing connections with geoscience researchers at an elite university lab. Many students were attracted to the project solely out of interest in machine learning, so the opportunity reached students who would not otherwise have conducted research in geoscience. Still, without incentives for researchers to engage less‐privileged students, our experience suggests that mutually beneficial partnerships between researchers and early‐stage students may exacerbate issues of inequality and lack of diversity within the geosciences.
Mountain Waves in the Upper Atmosphere of Venus
Authors: Navarro T. , Schubert G. 
Published: February 2024

AbstractPlanetary‐scale mountain waves have been observed at the cloud top of Venus and throughout the cloud deck. As they propagate from the surface to the cloud layers, multiple observations and numerical simulations have shown that they grow in size and do not break. However, the fate of mountain waves in the transition region and thermosphere, above the super‐rotating atmosphere, has only been addressed with two‐dimensional models. We conduct for the first time a simulation of mountain waves with a state‐of‐the‐art Venus climate model that includes the thermosphere. We find that mountain waves can propagate up to at least 150 km altitude, well above the transition region. They affect the circulation of the transition region, by reducing winds speeds, and the subsolar‐to‐antisolar circulation.