bluuebunny/crossref_metadata_2025_split huggingface dataset:
Scaffolding Pre-service Science Teachers’ Problem-Solving Strategies in a Methane Gas Detector Task Within an Earthquake-Robotics PD Course
Authors: Cepni Salih , Aydin Mirac , Iryanti Mimin , Birisci Salih 
Published: June 2024

AbstractEducational robotics (ER) has the potential to be a novel approach to teaching geohazards such as earthquakes at the college level. ER, which provides learners with problem-solving settings, requires proficiency in content knowledge and practical application to address ill-defined problems, challenging learners to master problem-solving strategies. Despite several efforts in the existing literature, it is necessary to scaffold the problem-solving strategies comprehensively. This qualitative study investigated the problem-solving strategies of nine pre-service science teachers aligned with a coding scheme containing problem-solving strategies not previously documented together. The participants were assigned to construct a methane gas detector with Tinkercad to mitigate post-earthquake explosion risks for rescue teams in an online robotics-integrated earthquake professional development (PD) course. Qualitative data, including artifacts, observations, and interviews, were analyzed using deductive coding. The results indicated that participants predominantly employed trial and error, expert opinion, and case-based reasoning. They rarely utilized heuristics and intuition and did not use capacity evaluation, prediction, or sketching strategies. Furthermore, the study synthesized different problem-solving strategies into a comprehensive framework, which was used as a coding scheme. This framework helps to clarify problem-solving mechanisms in an ER context, offering a structured approach.
Local neighborhood encodings for imbalanced data classification
Authors: Koziarski Michał , Woźniak Michał 
Published: June 2024

AbstractThis paper aims to propose Local Neighborhood Encodings (LNE)-a hybrid data preprocessing method dedicated to skewed class distribution balancing. The proposed LNE algorithm uses both over- and undersampling methods. The intensity of the methods is chosen separately for each fraction of minority and majority class objects. It is selected depending on the type of neighborhoods of objects of a given class, understood as the number of neighbors from the same class closest to a given object. The process of selecting the over- and undersampling intensities is treated as an optimization problem for which an evolutionary algorithm is used. The quality of the proposed method was evaluated through computer experiments. Compared with SOTA resampling strategies, LNE shows very good results. In addition, an experimental analysis of the algorithms behavior was performed, i.e., the determination of data preprocessing parameters depending on the selected characteristics of the decision problem, as well as the type of classifier used. An ablation study was also performed to evaluate the influence of components on the quality of the obtained classifiers. The evaluation of how the quality of classification is influenced by the evaluation of the objective function in an evolutionary algorithm is presented. In the considered task, the objective function is not de facto deterministic and its value is subject to estimation. Hence, it was important from the point of view of computational efficiency to investigate the possibility of using for quality assessment the so-called proxy classifier, i.e., a classifier of low computational complexity, although the final model was learned using a different model. The proposed data preprocessing method has high quality compared to SOTA, however, it should be noted that it requires significantly more computational effort. Nevertheless, it can be successfully applied to the case as no very restrictive model building time constraints are imposed.
Analysis of 12-lead ECGs for SARS-CoV-2 detection using deep learning techniques
Authors: Auriemma Citarella Alessia , De Marco Fabiola , Di Biasi Luigi , Di Chiara Luca , Tortora Genoveffa 
Published: June 2024

AbstractThe spread of the COVID-19 pandemic is expected to be uncontrollable by 2020. The main precautions to avoid virus spread have been the introduction of surgical masks or FFP2, sanitization of the hands, and maintaining social distancing. Due to their reliability, molecular tampons are the main detection and prevention methods known as the “Gold Standard”. However, these methods can be particularly uncomfortable. In this case, the analysis of electrocardiogram traces appears to be an alternative method for detecting COVID-19. The dataset used is made up of 1937 images from a study conducted in Pakistan that were preprocessed to train six different neural networks, including MobileNetV2, ResNet-18, ResNet-50, AlexNet, SqueezeNet, and an ad hoc defined neural network. The results show high classification performance, with an accuracy close to 98.94%, as reached by the Resnet-18 network. Moreover, significant attention was devoted to analyzing confusion matrices, revealing the capacity of the networks to identify distinctive features indicative of COVID-19 within ECG data. Finally, it is suggested that in nearly all experiments, including those with low performance, COVID-19 patients are correctly classified, further enhancing the diagnostic potential of ECGs data and DL approach.
An Agent-based Approach to Study Spatial Structure Effects on Estimated Distance Deterrence in Commuting
Authors: Azad Gholami Azam , Thorsen Inge , Ubøe Jan 
Published: June 2024

AbstractWe provide an experimental design to study how estimates of the distance deterrence parameter in a standard doubly-constrained gravity model respond to different patterns of spatial structure. The design is defined as an agent-based simulation framework that simultaneously considers the response of commuting and migration to changes in the spatial structure, accounting for labor and housing market issues. The agents are equipped with a utility function and are expected to maximize their utilities corresponding to their disposable income net of commuting costs and house value. We study how the estimates of the distance deterrence parameter respond to where the central business district is located, to the clustering of local and basic sector jobs, to changes in the road transportation network, and to the compactness in the system of towns in the geography.
The crypto world trades at tea time: intraday evidence from centralized exchanges across the globe
Authors: Brauneis Alexander , Mestel Roland , Theissen Erik 
Published: June 2024

Abstract
It is a stylized fact that trading activity, volatility and liquidity in equity and other financial markets follow specific intraday patterns. These patterns are to a large extent determined by institutional features such as exchange trading hours or batch settlement procedures. We analyze the intraday patterns that emerge when these institutional constraints are absent. We compile a large sample of 1940 currency pairs traded on 38 cryptocurrency exchanges located on five continents. These exchanges operate 24 h a day, seven days a week, and settle trades instantly. We find that there are pronounced time-of-day patterns in trading activity, volatility and liquidity. These patterns are remarkably similar across exchanges, time zones and cryptocurrency pairs. Specifically, trading activity, volatility and illiquidity all peak between 16:00 and 17:00 Coordinated Universal Time (UTC), i.e. during U.K. tea time. We find that characteristics of the exchanges (such as their locations) and of the traded currency pairs (e.g. whether two pairs share a common currency) explain some, but not all of the commonality in intraday patterns.
On substituent effect in 1,n–homodisubstituted polyenes
Authors: Graff Marek , Ostrowski Sawomir , Dobrowolski Jan Cz. 
Published: June 2024

AbstractThe all-trans and all-cis polyenes homodisubstituted at the ends were calculated at the B3LYP/6-31G** level. The disubstitution gives rise to three end-types of the conformers: trans-trans, trans-cis, and cis-cis, denoted as EE, EZ, and ZZ. The symmetry of the EE or ZZ all-cis isomers depended on the double bond parity. Twelve substituents used: H, BeH, BH2, BF2, Br, CH3, Cl, CN, F, NH2, NO2, OH, and SiH3 were chosen to exhibit different σ- and π-electron donating and electron withdrawing properties. For polyenes composed up to ca. 20 C-atoms, the π-electron donating and withdrawing character of the end groups matters and differently acting substituents play significantly different roles. Unexpectedly, the intramolecular interactions between the substituents and the neighboring chain CH groups near appeared more decisive for the compound’s stability than the substituent electron donating/withdrawing properties. The substituent-chain interplay was consonant in the all-trans and all-cis polyenes. Still, they were always more destabilizing in the latter than in all-trans isomers.
Governing for the Common Good: The Possibilities of Sociocracy in Nonprofit Organizations
Authors: King Daniel , Griffin Martyn 
Published: June 2024

AbstractWithin nonprofit organizational studies, there has been a long-standing interest in democratic governance as ways of building political participation, civic skills and fostering inclusion. While established approaches to democratic governance have many benefits, existing research points to numerous challenges, including apathy and oligarchization. This paper explores an alternative form of democratic governance, sociocracy. Sociocracy, sometimes called dynamic governance, is organized around four key elements: circular hierarchy, consent-based decision-making, double linking, and practices to foster inclusivity and voice, a unique blend which distinguishes it from other forms of democratic governance. This article explores the implications on workplace democracy that a nonprofit organization experienced when limiting it. We find that sociocracy offers many benefits, including empowering members and reducing the risk of domination, and also highlights the many challenges that can accompany the implementation of sociocracy, particularly how four forms of inequality contribute to those challenges.
Characterization, in vitro bioaccessibility and antidiabetic activities of maltodextrin and lecithin nanomaterials loaded with ellagic aci﻿d
Authors: Okumuş Emine , Bakkalbaşı Emre , Gümüş Ayşegül 
Published: June 2024

AbstractPomegranate peel is one of the wastes generated in large quantities in the food industry and ellagic acid is a natural bioactive phenolic compound in pomegranate peel. In this study, high-purity and low-cost ellagic acid was produced by acid hydrolyze process from pomegranate peel and characterization, in vitro bioaccessibility, antioxidant, and antidiabetic activity of the ellagic acid nanoencapsulated with maltodextrin and soy lecithin were studied. The extract yield and purity of ellagic acid was 6.47 and 88.74%, respectively. Results showed that lecithin coated samples were more stable with − 43.16 mV zeta potential and had higher encapsulation efficiency (99.29%) compared to maltodextrin. However, coated samples with maltodextrin had higher production efficiency (91.40%) and loading capacity (54.70%). The thermal resistance of ellagic acid after the nanoencapsulation process was significantly raised. The ellagic acid nanoencapsulated with maltodextrin had higher bioaccessibility (80.22%) and solubility in biological buffers (64.00-98.20%). The α-amylase and α-glucosidase inhibitiory activities of the ellagic acid decreased after the encapsulation process. However, the α-amylase inhibitory activities of the nanoencapsulated materials were higher than acarbose as a positive control. As a result, thermal resistance, solubility in a biological medium, and bioaccessibility of ellagic acid after nanoencapsulation with maltodextrin can be increased. Thus, the use of ellagic acid nanoencapsulated with maltodextrin in the food, cosmetic, and pharmacological industries can be diversified.
Hardy Spaces and Canonical Kernels on Quadric CR Manifolds
Authors: Boggess Albert , Brooks Jennifer , Raich Andrew 
Published: June 2024

AbstractCR functions on an embedded quadric M always extend holomorphically to $$M+i\Gamma _M$$

M
+
i

Γ
M

where $$\Gamma _M$$

Γ
M

is the closure of the convex hull of the image of the Levi form. When $$\Gamma _M$$

Γ
M

is a closed polygonal cone, we show that the Bergman kernel on the interior of $$M+i\Gamma _M$$

M
+
i

Γ
M

is a derivative of the Szegö kernel. Moreover, we develop the $$L^p$$

L
p

Hardy space theory which turns out to be particularly robust. We provide examples that show that it is unclear how to formulate a corresponding relationship between the Bergman and Szegö kernels on a wider class of quadrics.
Implications of the WTO and EU fuel taxation reforms for a European fishing fleet: effects, side-effects and alternative approaches from an input–output analysis of the Galician (northwest Spain) fleet
Authors: Rodríguez-Rodríguez Gonzalo , Sánchez-Llamas Eduardo , Martínez-Cabrera Helena , Ballesteros Hugo M. 
Published: June 2024

AbstractThe World Trade Organization (WTO) and European Union (EU) have both put forward tax reforms that impact fisheries’ fuel costs, which are similar in the object of taxation but quite different in the externalities addressed, goals, scope, exemptions or tax rates, creating an opportunity to compare the effects and discuss the alternatives. These proposals are the result of long and intense debates in political, social and academic spheres. However, certain aspects remain unclear. First of all, the number of empirical studies is still limited, particularly considering that fisheries governance is subject to heterogeneous management systems and institutional contexts creating room for different potential outputs. Second, coastal states have no fiscal competence beyond 12 miles, which limits the scope of the reforms to small scale fleets (SSF). All in all, the economic consequences for the fleets remain unclear. To this end, we will build on the Galician fishing sector (NW Spain) input–output tables to discuss the direct impacts, effects and side effects of these reforms on a representative European fleet. Flaws identified in both initiatives mean that targeted externalities will not be corrected and, moreover, additional ones, such as distributional effects penalising SSF or fuel spillovers, could be boosted. Alternative policy approaches are discussed.
Advancing Customer Feedback Systems with Blockchain
Authors: Ballandies Mark C. , Holzwarth Valentin , Sunderland Barry , Pournaras Evangelos , Brocke Jan vom 
Published: June 2024

AbstractOrganizations have to adjust to changes in the ecosystem, and customer feedback systems (CFS) provide important information to adapt products and services to changing customer preferences. However, current systems are limited to single-dimensional rating scales and are subject to self-selection biases. The work contributes design principles for CFS and implements a CFS that advances current systems by means of contextualized feedback according to specific organizational objectives. The authors apply Design Science Research (DSR) methodology and report on a longitudinal DSR journey considering multiple stakeholder values by utilizing value-sensitive design methods. They conducted expert interviews, design workshops, demonstrations, and a four-day experiment in an organizational setup, involving 132 customers of a major Swiss library. In the process, the identified design principles and the implemented software artifact were validated qualitatively and quantitatively, leading to conclusions for their efficient instantiation. The authors found that i) blockchain technology can afford four design principles of effective CFS. Also, ii) combining DSR with value-sensitive design methods explicitly provides rationale for design principles in the form of identified important values. Moreover, iii) combining DSR with value-sensitive design methods makes the construction of software artifacts more efficient it terms of design time by restricting the design space of a software artifact to those options that align with stakeholder values. The findings of this work thus extend the knowledge about the design of CFS and offer both researchers a theoretical contribution to reasoning about design principles and managers and decision makers a guide for the efficient design of software artifacts.
Estimating stream sediment loads to assess management options for a Southern Appalachian mountain lake
Authors: Wilcox Jeffrey D. , Stark Karen Ann , Svetlov Ruth 
Published: June 2024

AbstractEnka Lake is a 25-ha reservoir in the Southern Appalachian mountains surrounded by the Biltmore Lake residential neighborhood. The aesthetic and recreational value of Enka Lake can be negatively affected by turbid water and sediment buildup, resulting from stormwater originating upstream in its 15.38 km2 watershed. In this study, we monitored streamflow and sediment loads for nearly 2 years to better understand sedimentation dynamics and evaluate management options. We collected nearly 500 water samples throughout the watershed, focusing on two tributaries that provide the majority of streamflow into Enka Lake. During baseflow conditions, those tributaries are very clear (turbidity ranging from 1 to 20 NTU), but sediment-laden stormflow (turbidity > 1000 NTU) from dirt roads, gravel driveways, and poorly vegetated yards is common and, during extreme storm events, causes lake discoloration. Discharge-sediment data pairs were used to construct sediment rating curves and estimate sediment fluxes through these tributaries. The predicted sediment fluxes were tested with high-frequency sampling during and after three storms in different seasons; predicted values underestimated the peak sediment fluxes (0–400%) but generally matched total measured sediment loads. Estimates of annual sediment load from the two tributaries (540–900 tonnes/year) suggest that a dredging effort commissioned by the neighborhood association in 2016 may have removed only about 1–3 years’ worth of sediment. Installing sediment forebays or other retention structures is likely the preferred sediment management strategy moving forward (over a regular dredging schedule) since they can be maintained more easily without affecting lake levels. Designing these retention structures will benefit from the estimates of stormflow and sediment fluxes, and the study design presented here—including the help of community-based volunteer samplers—provides a model that could be used at other sites in the Southern Appalachians and elsewhere.
Experimental investigations on laboratory samples regarding the connection of spectral induced polarization to heterogeneity of hydraulic conductivity
Authors: Herold Robert , Beisembina Gulmira , Dietrich Peter , Börner Frank 
Published: June 2024

AbstractKnowledge of the heterogeneity of aquifers caused by sedimentary processes is essential for preferential flow path and flow time estimations due to the spreading of contaminants and ground water protection. Spectral Induced Polarization (SIP) method is a useful geophysical method that can be used to predict hydraulic properties from surface measurements, as there is a close connection between electrical and hydraulic parameters of rocks. Thus, the influence of aquifer heterogeneities such as sedimentary structures on the relationship between SIP parameters and hydraulic conductivity has been subject of some studies and is still an area of interest. In this paper we present the results of laboratory measurements on defined heterogeneous sand samples with the aim to improve the understanding of that connection. More specifically we investigated the dependence of hydraulic conductivity ($$K$$
K
), as well as several SIP parameters like quadrature conductivity ($${\upsigma }^{{\prime}{\prime}}$$

σ

′
′

), in-phase conductivity ($${\upsigma }{^\prime}$$

σ

′

), phase shift ($$\varphi$$
φ
) and chargeability spectra ($$m(\tau )$$

m
(
τ
)

), which were calculated by Debye decomposition, on the composition of samples. For the laboratory experiments a measurement cell was designed to carry out hydraulic flow experiments and 4-electrodes SIP measurements on samples in the decimeter scale. The samples consisted of two different sands with different grain size distributions. The two sands were combined in varying volume shares and geometries as well as in parallel and serial orientation relative to hydraulic and electrical current flow. The experimental results show that the SIP parameters and $$K$$
K
are clearly dependent on the volume share of the sand components. In terms of preferential flow paths, known correlations to hydraulic conductivity could be reproduced, however the SIP parameters showed no dependency on the orientation of hydraulic heterogeneities. The results indicate that in samples, where the porosity and thus also the electrical conductivity amplitude are approximately homogeneous and only the grain surface area and hydraulic conductivity vary, the mean electrical parameters determined from the SIP data do not provide any information for recognising preferential flow within the scope of the measurement accuracy.
Reac4Cat-Ontology: Harnessing the Power of Ontological Description Logic in Catalysis Research as a Practical Approach to Knowledge Inferences
Authors: Behr Alexander S. , Borgelt Hendrik , Kockmann Norbert 
Published: June 2024

AbstractMaximizing the use of digitally captured data is a key requirement for many of the late adopters of digital infrastructure. One of the newcomers is the chemical industry in the area of digitized laboratories. Here, tools and services that satisfy individual needs still need to be developed and distributed within the community. This work explores the potential of using graph databases — specifically those modeled via ontological knowledge graphs — to describe complex data linkages and draw logical conclusions. While knowledge graphs are not widely utilized in catalysis research, this study introduces a methodology to highlight their usability for semantic description and integration into diverse value chains with contact to the domain of (bio)chemistry and catalysis.A demonstration is performed how ontologies and their knowledge graphs can be applied to perform essential functions of semantic annotation to chemical reactions, which are difficult to model relational. Traditional data description methods can be neglected using description logic, showing how logical inferences at the machine level can enrich data. This work also illustrates the seamless integration of this enhanced data into process simulations, connecting semantic description with practical applications. The immediate benefits for catalysis research are emphasized and the development of new tools and services envisioned. By clarifying how these graphs can be integrated into existing workflows, researchers are empowered to make the most of digitally acquired data in catalytic processes. This practical methodology lays the foundation for improved decision-making and innovation, fostering advancements in the field of catalysis research.