bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deciphering the Degradation Mechanisms and Realize High‐Voltage Stability of A3V2(PO4)3 (A = Li+, Na+) in Aqueous Dual‐Ion Batteries
Authors: Dong Chongrui , Chen Yuanjing , Ding Yan , Pu Xiangjun , Cao Yuliang , Ma Zhongyun , Chen Zhongxue 
Published: August 2024

AbstractPolyanionic A3V2(PO4)3 (A = Li+, Na+) with open channels have been extensively utilized as cathode materials for aqueous zinc‐metal batteries (AZMBs), whereas suffering from severe capacity fading and rapid operation voltage decay during cycling. when used as In this work, it is disclosed that the rapid degradation is induced by an irreversible phase change from electrochemical active Li3V2(PO4)3 to nonactive monoclinic LiZnPO4, as well as active Na3V2(PO4)3 to nonactive rhombic Zn3(PO4)2(H2O)4. Subsequently, a rational dual‐cation (Al‐Fe) doping strategy is proposed to suppress these detrimental transformations. Such dual‐cation doping entails stronger P–O and V–O bonds, thus stabilizing the initial polyanionic structures. Consequently, the optimized member of Li3V1.775Al0.075Fe0.225(PO4)3 (LVAFP) exhibits desirable cycling stability (1000 cycles, 68.5% capacity retention) and notable rate capability (92.1% of the initial capacity at 10 C). Moreover, the dual‐cation doping methodology is successfully extended to improve the stability of Na3V2(PO4)3 cathode in aqueous dual‐ion batteries, signifying the versatility and feasibility of this strategy. The comprehensive identification of local structural evolution in these polyanions will broaden the scope of designing high‐performance alkali‐vanadyl‐phosphates for multivalent aqueous batteries.
Untersuchungen zur Schubtragfähigkeit von Blechen aus nichtrostendem Stahl
Authors: Ungermann Dieter , Schweyher Janik 
Published: August 2024

AbstractDie Bemessungsregeln zur Schubtragfähigkeit von Blechen aus nichtrostendem Stahl nach DIN EN 1993‐1‐4 sind konservativer als für Bleche aus Baustahl nach DIN EN 1993‐1‐5. Dies führt zu einem erhöhten Materialverbrauch bei Konstruktionen aus nichtrostendem Stahl. Aus diesem Grund wurden experimentelle und numerische Untersuchungen zur Schubtragfähigkeit von Blechen aus nichtrostendem Stahl an torsionsbelasteten Hohlkastenquerschnitten durchgeführt, die zu einer Überarbeitung der Bemessungsvorschrift für die Schubtragfähigkeit von nichtrostenden Stählen für verformbare wie auch starre Auflagersteifen geführt haben.
Knicklängen im digitalen Zeitalter – ein didaktisch‐technisches Werkzeug
Authors: Lang Robert , Timmers Ralph , Enzinger Maximilian 
Published: August 2024

AbstractDie Verzweigungslast eines stabilitätsgefährdeten Stabs bildet die Grundlage für die Bemessung nach dem Ersatzstabverfahren der EN 1993‐1‐1. Es hat sich eingebürgert, dass die Verzweigungslast über die Knicklänge des Stabs bestimmt wird. Die Knicklänge selbst entspricht im einfachsten Fall einem der Eulerschen Grundfälle, die bei den üblichen Strukturen des Stahlbaus jedoch nur selten vorkommen. Bei komplexeren Systemen hängt die Knicklänge häufig auch von anschließenden Strukturen bzw. deren Steifigkeiten ab. Die Bedeutung der Knicklängenermittlung ist derart groß, dass sie im Bereich der Lehre häufig am Stahlbau angesiedelt ist, obwohl sie eigentlich ein klassisches Problem der Baustatik darstellt. Am Innsbrucker Stahlbaulehrstuhl ist dies nicht anders, und so wurde im Rahmen der Modernisierung der Lehre ein Werkzeug entwickelt, das didaktisch und technisch dem Stand der Zeit entspricht und die Lehre unterstützen soll. Dieses Werkzeug ist in der Lage, spielerisch den Zugang zur Ermittlung von Knicklängen an komplexeren Strukturen zu vermitteln, während im Hintergrund moderne numerische Verfahren die eigentliche Rechenarbeit übernehmen. Die entwickelte Software buckL.ing (Freeware) steht auf der Homepage des Arbeitsbereichs für Stahlbau und Mischbautechnologie zum Download zur Verfügung (www.uibk.ac.at/stahlbau/software).
Experimental study on bond performance of recycled coarse aggregates concrete with circular steel tubes after freeze–thaw cycling
Authors: Hu Dongxia , Wu Jin , Feng Zhe , Liu Liqiang 
Published: August 2024

AbstractExtrusion tests were conducted on recycled coarse aggregate concrete with circular steel tubes (RCCST, 100% replacement of recycled coarse aggregate) to investigate the impact of freeze–thaw cycles on bond properties. RCCST samples were subjected to 0, 25, 50, 75, 100, 125 and 150 freeze–thaw cycles and their bond properties were then compared with those of natural coarse aggregate concrete with circular steel tubes (NCCST) after 0, 100 and 150 freeze–thaw cycles. The experimental results indicate that freeze–thaw cycling damages the internal structure of RCCST, causing a significant decrease in interfacial bond strength with an increase in the number of freeze–thaw cycles. Freeze–thaw RCCST exhibits lower peak load and higher peak slip compared to NCCST, with increases of 25.2%, 73.2%, and 70.3% after 0, 100, and 150 freeze–thaw cycles, respectively. Regression analysis was used to derive an exponential equation that describes the relationship between longitudinal strain and strain gauge position. Additionally, a segmented fitting method was employed to obtain an expression for the bond slip of the freeze–thaw RCCST with a circular steel pipe.
Coordination Networks from [Te4]2+ Clusters and Polynitriles
Authors: Zink Marcus , Thönnes Dominik , Ernsthäuser Doris , Daniels Jörg , Bredow Thomas , Beck Johannes 
Published: August 2024

AbstractThe reactions of a series of organic polynitriles with [Te4][AsF6]2 in liquid SO2 solution lead either to reduction of [Te4]2+ to elemental tellurium or to the formation of coordination polymers. With 1,3‐dicyanobenzene (1,3‐DCB), 1,4‐dicyanobenzene (1,4‐DCB), 1,2,4,5‐tetracyanobenzene (TCB), tetracyanoethylene (TCNE) and tetracyanochinodimethane (TCNQ) the coordination complexes [Te4][AsF6]2 ⋅ 2(1,3‐DCB), [Te4][AsF6]2 ⋅ 3(1,4‐DCB) ⋅ 2SO2, [Te4][AsF6]2 ⋅ TCB, [Te4][AsF6]2 ⋅ TCNE and [Te4][AsF6]2 ⋅ TCNQ ⋅ 8 SO2 were isolated and characterized by crystal structure analyses and vibrational Raman spectroscopy. The nitriles are coordinated to the square‐planar clusters forming 1D chains, 2D arrangements and 3D networks. Tetrakis(dicyanomethylene)cyclobutendiide [C4(C{CN}2)4]2− is oxidized by [Te4]2+ to the neutral cyanocarbon C4(C{CN}2)4, structurally representing a 4[radialene]. The ionization potentials and electron affinities of the cyanamide anion, cyanogen, 1,2‐DCB, 1,3‐DCB, 1,4‐DCB, TCB, C4(C{CN}2)4, TCNE and TCNQ and those polynitriles, which cause reduction of [Te4]2+, were calculated at coupled‐cluster level of theory in order to examine possible reasons for the stability of the coordination polymers based on electronic properties of the nitriles.
Perceptions and Experiences of Severe Content in Content Moderation Teams: A Qualitative Study
Authors: Strongylou Dimitra Eleftheria , Savio Marlyn Thomas , Steiger Miriah , Bharucha Timir , Manuel Wilfredo R. Torralba , Huang Xieyining , Guevara Rachel Lutz 
Published: August 2024

AbstractExisting Trust & Safety policies predominantly focus on protecting content moderators’ (CoMos) safety against severe content violations. Nevertheless, in reality, CoMos might encounter content across a broad severity spectrum while perceptions of content severity among CoMos are yet to be fully understood in relation to their well-being and job accuracy. The current study employs a sequential study design to qualitatively examine the views of 34 CoMos in the USA and the Philippines and of 166 professionals (i.e., mental health and learning experience staff, team leads) supporting CoMos on content severity and its perceived impact on CoMos well-being and job accuracy. Of note, consistent with ethical guidelines and wellness best practices, all CoMos received tiered wellness support services from TaskUs Inc. Collected data were thematically analyzed and two overarching themes emerged. Within the first theme, namely, ‘perceived content categories’, both CoMos and professionals, after considering the potential distress caused by various contents, broadly distinguished between ‘moderate’ and ‘graphic’ content, while they further attributed their own definitions to each of the two categories. Under theme two—‘content impact on perceived stress- most study participants discussed how reviewing moderate content might have a more detrimental impact upon CoMos stress and job accuracy compared to reviewing graphic content in the lack of wellness support and care. This study is the first of its kind to give voice to both CoMos and support staff to discuss in depth their views on content moderation while also making participant-led recommendations for work policy and future research.
User Perceptions of Progressive Web App Features: An Analytical Approach and a Systematic Literature Review
Authors: Marchetto Tulio , Morandini Marcelo 
Published: August 2024

AbstractThis article presents an in-depth analysis of the usability of progressive web apps (PWAs) across different operating systems, based on a survey that had 226 responses. The study covers five different apps and two operating systems, providing a comprehensive understanding of user experiences and preferences. Key findings include the relative ease of installation across all apps and operating systems, with iOS users reporting lower levels of difficulty. The visibility of app icons on home screens was generally high, underscoring the importance of app accessibility and user engagement. However, there is room for improvement in certain areas. The dataset obtained from the responses also reveals a high level of user engagement and willingness to provide feedback, which is crucial for the continual improvement of apps. The insights gleaned from this survey are invaluable for developers seeking to optimise their PWAs, ensuring they meet user expectations and deliver a superior app experience.
An Automated and Goal-Oriented Clustering Procedure
Authors: Koren Oded , Koren Michal , Peretz Or 
Published: August 2024

AbstractClustering techniques are convenient tools for preparing and organizing unstructured and unclassified data. Depending on the data, they can be used to prepare for an analysis or to gain insight. However, choosing a clustering technique can be challenging when dealing with high-dimensional datasets. Most often, application requirements and data distribution need to be considered. Since clustering is defined as a complex problem to calculate, different algorithms may produce different results that meet the application's needs. This study presents an automated threshold-based and goal-oriented clustering procedure. It is based on the AutoML mechanism to estimate the most suitable hyperparameters according to predefined needs and can learn four clustering performance metrics thresholds for a given dataset. The significant advantages of this method are the automatic selection of clustering technique (i.e., partitional, hierarchical, density-based, or graph-based) and the ability to determine the output dynamically, according to predefined goals. We tested our method over four datasets and analyzed the results according to different goals. The results show that our method improved the silhouette score by 549.5% (from 0.105 to 0.682) compared to popular and commonly used K-means. Furthermore, clustering based on multiple metrics yielded more information than clustering by a single metric.
Proposal for a New Separation Method for Reproducing Images with Properties in the Visible and Near-Infrared Spectrum
Authors: Gršić Jana Žiljak , Plehati Silvio , Bogović Tomislav , Vujić Roko 
Published: August 2024

AbstractPainting dyes and artworks exhibit duality with different states in the visible (V) and near-infrared (Z) spectrum. “V” denotes the solar spectrum ranging from 400 to 750 nm, while “Z” indicates the solar spectrum up to 1000 nm. The infrared state of an artwork can be an independent, “hidden” image. The paper demonstrates a new procedure of graphic preparation for the separation of process inks for reproducing artworks in monographs, with a focus on integration in the visible and near-infrared spectrum. The practical part of the paper uses the Projectina PAG B50 forensic scanner, which is equipped with 24 filters for blocking light from 220 to 1000 nm. Image reproduction involves photography of artwork in RGB, then conversion into CMY, with the addition of K from the Z image. “VZ” separation is introduced into the reproduction of the artwork, simulating the dual states of the original artwork. The GCR procedure is applied by subtracting CMY but based on information for the K component that is equal in the Z image. This process provides a deeper understanding of artworks and offers extended information about their state in the visible and near-infrared part of the spectrum.
Epidemic Information Extraction for Event-Based Surveillance Using Large Language Models
Authors: Consoli Sergio , Markov Peter , Stilianakis Nikolaos I. , Bertolini Lorenzo , Gallardo Antonio Puertas , Ceresa Mario 
Published: August 2024

AbstractThis paper presents a novel approach to epidemic surveillance, leveraging the power of artificial intelligence and large language models (LLMs) for effective interpretation of unstructured big data sources like the popular ProMED and WHO Disease Outbreak News. We explore several LLMs, evaluating their capabilities in extracting valuable epidemic information. We further enhance the capabilities of the LLMs using in-context learning and test the performance of an ensemble model incorporating multiple open-source LLMs. The findings indicate that LLMs can significantly enhance the accuracy and timeliness of epidemic modelling and forecasting, offering a promising tool for managing future pandemic events
TermX—Bridging the Gap: Implementing CTS2 and FHIR Compatible Terminology Server
Authors: Ivanova Marina , Bossenko Igor , Piho Gunnar 
Published: August 2024

AbstractAs healthcare systems evolve, achieving interoperability and seamless data exchange becomes paramount. The key component of the data exchange is terminology managed by the terminology server. During “Comparative Analysis of Clinical Terminology Servers: A Quest for an Improved Solution” research, we did not find a terminology server suitable for our criteria and decided to develop our own terminology server. This article delves into implementing the Common Terminology Services 2 (CTS2) standard on PostgreSQL, a robust open-source relational database. The discussion encompasses the intricacies of integrating CTS2 with PostgreSQL, exploring the challenges and solutions encountered during the process. Additionally, the article comprehensively maps this implementation to HL7 Fast Healthcare Interoperability Resources (FHIR), a widely adopted standard for healthcare data exchange. Readers will gain insights into the technical aspects of the implementation, practical considerations, and the potential impact on healthcare data management. This exploration aims to guide developers, healthcare IT professionals, and stakeholders in leveraging CTS2 on PostgreSQL while ensuring compatibility with HL7 FHIR resources, ultimately fostering improved interoperability in the dynamic landscape of healthcare data systems.
Artificial Intelligence in Prostate Cancer Diagnosis: “Synergy-Net” in Campania FESR-POR (European Fund of Regional Development—Regional Operative Program) Research Project
Authors: Parmeggiani Domenico , De Sio Marco , Moccia Giancarlo , Luongo Pasquale , Miele Francesco , Allaria Alfredo , Torelli Francesco , Marrone Stefano , Gravina Michela , Sansone Carlo , Bollino Ruggiero , Bassi Paola , Sciarra Antonella , Arcaniolo Davide , Donnarumma Maddalena Claudia , Colonnese Chiara , Romano Lorenzo , Colapietra Federica , Di Domenico Marina , Docimo Ludovico , Agresti Massimo 
Published: August 2024

AbstractBackground: The diagnosis of prostate cancer can only be obtained following the analysis of the tissue taken by means of a biopsy. Given the position of the organ, the biopsy is typically assisted by ultrasound images and the procedure consists of taking different portions of tissue from different areas, according to a map well-defined by international standards. Given the invasiveness of the procedure, the objective set within the Synergy-Net project is to analyze biomedical images in order to guide the operator on identifying the most suspicious tissues. Results: The dataset acquired by the Synergy-Net Platform at the “Vanvitelli” Urology Operating Unit is made up of a total of 350 outpatient services from which the diagnosis emerged on ultrasound, elastosonography, RNM, and biopsy of 50 prostate carcinomas which were then operated on. In the context of the Synergy-Net project, a new convolutional architecture was therefore created based on the U-Net paradigm, designed to perform a slice-by-slice segmentation in DCE-MRI of the prostate. The data processing with CNNs was carried out on a dataset of 37 patients, selected from the initial 50 for completeness and uniformity of the data, all affected by k-prostatic disease, using a tenfold cross-validation in order to obtain a statistically more significant estimate of the goodness of the results obtained. The performance metric used was the DICE coefficient. Conclusion: The results present a low intra-subject variability and a high inter-subject variability, with DICE values ranging between a minimum of 5.8% and a maximum of 60.3%. On average, a value of 35% is reported, considering the arithmetic mean of the dice achieved on all folds (macro-average).
Designing Reactive Route Change Rules with Human Factors in Mind: A UATM System Perspective
Authors: Kim Jeongseok , Kim Kangjin 
Published: August 2024

AbstractThis paper investigates the dynamic rerouting of electric vertical takeoff and landing (eVTOL) aircraft in the context of urban air traffic management (UATM). Focusing on the interaction between human managers and the UATM network, we present a novel approach to reactive rerouting based on step-oriented simulation and condition-action rules. Our framework enables human intervention in response to congestion observed at vertiport corridors, allowing managers to request detours for approaching eVTOLs. We formulate the problem within the knowledge representation and reasoning (KR&R) paradigm and employ a multi-shot approach within an Answer Set Programming (ASP) solver to drive the step-oriented simulation. The structure of the paper follows a logical progression, including related work, preliminaries, a problem statement, proposed solutions, and a discussion, followed by a concluding section.
Behaviors and Patterns of TV News Viewing in Malaysia During and After Covid-19 Pandemic
Authors: Joo Tang Mui , Teng Chan Eang 
Published: August 2024

AbstractThe demise of Television (TV) news before Covid-19 has been an attention when people have shifted to online platforms for online news. Covid-19 Pandemic has changed the demand for TV news. The media landscape in Malaysia has then been reengineered by the impact of it. Driven by the theory of Fear Appeal in the information searching about Covid-19 during Malaysian Movement Control Order (MCO), TV news viewing has increased. This research aims to study the behaviors and patterns of TV news consumption during Covid-19 Pandemic in Malaysia. It is also to study the significance of TV news to Malaysians during the Pandemic. This research targets to ascertain the change of trend in TV news viewing behaviors and patterns among Malaysians during and after the Pandemic. In-depth interviews are conducted with 10 interviewees from Northern, Central and Southern Sarawak, the largest state in Malaysia. Purposive sampling is applied where the interviewees are from the background of media practitioners, educators, and undergraduates. The interviews are conducted from end March to early April 2023. Written consent has been obtained and ethical clearance is gotten. It is found that the TV news viewing behaviors and patterns have changed starting from MCO. It is corresponding to the various statistics reviewed and to the theory of Fear Appeal in the updates of Covid-19. After MCO, Malaysians expect various contents, presentations, and promotional activities that can engage the audiences. It is also to cope and compete with the digitalization in the new phase of challenge.
Comparative Evaluation of Anomaly Detection Methods for Fraud Detection in Online Credit Card Payments
Authors: Thimonier Hugo , Popineau Fabrice , Rimmel Arpad , Doan Bich-Liên , Daniel Fabrice 
Published: August 2024

AbstractThis study explores the application of anomaly detection (AD) methods in imbalanced learning tasks, focusing on fraud detection using real online credit card payment data. We assess the performance of several recent AD methods and compare their effectiveness against standard supervised learning methods. Offering evidence of distribution shift within our dataset, we analyze its impact on the tested models’ performances. Our findings reveal that LightGBM exhibits significantly superior performance across all evaluated metrics but suffers more from distribution shifts than AD methods. Furthermore, our investigation reveals that LightGBM also captures the majority of frauds detected by AD methods. This observation challenges the potential benefits of ensemble methods to combine supervised, and AD approaches to enhance performance. In summary, this research provides practical insights into the utility of these techniques in real-world scenarios, showing LightGBM’s superiority in fraud detection while highlighting challenges related to distribution shifts.
Ethical Education Data Mining Framework for Analyzing and Evaluating Large Language Model-Based Conversational Intelligent Tutoring Systems for Management and Entrepreneurship Courses
Authors: Ilagan Joseph Benjamin R. , Ilagan Jose Ramon S. , Rodrigo Maria Mercedes T. 
Published: August 2024

AbstractEducational data mining (EDM) can be used to design better and smarter learning technology by finding and predicting aspects of learners. Amend if necessary. Insights from EDM are based on data collected from educational environments. Among these educational environments are computer-based educational systems (CBES) such as learning management systems (LMS) and conversational intelligent tutoring systems (CITSs). The use of large language models (LLMs) to power a CITS holds promise due to their advanced natural language understanding capabilities. These systems offer opportunities for enriching management and entrepreneurship education. Collecting data from classes experimenting with these new technologies raises some ethical challenges. This paper presents an EDM framework for analyzing and evaluating the impact of these LLM-based CITS on learning experiences in management and entrepreneurship courses and also places strong emphasis on ethical considerations. The different learning experience aspects to be tracked are (1) learning outcomes and (2) emotions or affect and sentiments. Data sources comprise Learning Management System (LMS) logs, pre-post-tests, and reflection papers gathered at multiple time points. This framework aims to deliver actionable insights for course and curriculum design and development through design science research (DSR), shedding light on the LLM-based system’s influence on student learning, engagement, and overall course efficacy. Classes targeted to apply this framework have 30–40 students on average, grouped between 2 and 6 members. They will involve sophomore to senior students aged 18–22 years. One entire semester takes about 14 weeks. Designed for broad application across diverse courses in management and entrepreneurship, the framework aims to ensure that the utilization of LLMs in education is not only effective but also ethically sound.