bluuebunny/crossref_metadata_2025_split huggingface dataset:
A survey on knowledge-enhanced multimodal learning
Authors: Lymperaiou Maria , Stamou Giorgos 
Published: September 2024

AbstractMultimodal learning has been a field of increasing interest, aiming to combine various modalities in a single joint representation. Especially in the area of visiolinguistic (VL) learning multiple models and techniques have been developed, targeting a variety of tasks that involve images and text. VL models have reached unprecedented performances by extending the idea of Transformers, so that both modalities can learn from each other. Massive pre-training procedures enable VL models to acquire a certain level of real-world understanding, although many gaps can be identified: the limited comprehension of commonsense, factual, temporal and other everyday knowledge aspects questions the extendability of VL tasks. Knowledge graphs and other knowledge sources can fill those gaps by explicitly providing missing information, unlocking novel capabilities of VL models. At the same time, knowledge graphs enhance explainability, fairness and validity of decision making, issues of outermost importance for such complex implementations. The current survey aims to unify the fields of VL representation learning and knowledge graphs, and provides a taxonomy and analysis of knowledge-enhanced VL models.
Domain generalization through meta-learning: a survey
Authors: Khoee Arsham Gholamzadeh , Yu Yinan , Feldt Robert 
Published: September 2024

AbstractDeep neural networks (DNNs) have revolutionized artificial intelligence but often lack performance when faced with out-of-distribution data, a common scenario due to the inevitable domain shifts in real-world applications. This limitation stems from the common assumption that training and testing data share the same distribution-an assumption frequently violated in practice. Despite their effectiveness with large amounts of data and computational power, DNNs struggle with distributional shifts and limited labeled data, leading to overfitting and poor generalization across various tasks and domains. Meta-learning presents a promising approach by employing algorithms that acquire transferable knowledge across various tasks for fast adaptation, eliminating the need to learn each task from scratch. This survey paper delves into the realm of meta-learning with a focus on its contribution to domain generalization. We first clarify the concept of meta-learning for domain generalization and introduce a novel taxonomy based on the feature extraction strategy and the classifier learning methodology, offering a granular view of methodologies. Additionally, we present a decision graph to assist readers in navigating the taxonomy based on data availability and domain shifts, enabling them to select and develop a proper model tailored to their specific problem requirements. Through an exhaustive review of existing methods and underlying theories, we map out the fundamentals of the field. Our survey provides practical insights and an informed discussion on promising research directions.
On generating functions to compute some power measures for weighted majority games
Authors: Armijos-Toro L. M. , Alonso-Meijide J. M. , Mosquera M. A. , Saavedra-Nieves A. 
Published: September 2024

AbstractIn this paper we introduce new procedures, based on generating functions, for calculating some power measures for weighted majority games. In particular, we present methods for computing the Johnston index and the Colomer–Martínez measure. Besides, we introduce a new power measure that combines the principles underlying the Johnston index and Colomer–Martínez measure as well as a procedure for computing it using generating functions. Finally, we introduce the new R package and describe its capabilities to compute some power measures by means of generating functions. We illustrate its performance with a real example.
Pathogens detected in ticks (Ixodes ricinus) feeding on red squirrels (Sciurus vulgaris) from city parks in Warsaw
Authors: Dwużnik-Szarek Dorota , Beliniak Agata , Malaszewicz Wiktoria , Krauze-Gryz Dagny , Gryz Jakub , Jasińska Karolina D. , Wężyk Dagmara , Bajer Anna 
Published: September 2024

AbstractThe European red squirrel (Sciurus vulgaris) is a common host for Ixodes ricinus ticks in urban and rural habitats, however, studies on ticks and tick-borne pathogens (TBPs) of squirrels have not been conducted in Poland yet. Thus, the aims of the current study were to assess and compare the prevalence and abundance of ticks on red squirrels trapped at two sites in the Warsaw area (in an urban forest reserve and an urban park) and using molecular tools, to assess the genetic diversity of three pathogens (Borrelia burgdorferi sensu lato, Rickettsia and Babesia spp.) in I. ricinus ticks collected from squirrels. For the detection of Rickettsia spp. a 750 bp long fragment of the citrate synthase gltA gene was amplified; for B. burgdorferi s.l. 132f/905r and 220f/824r primers were used to amplify the bacterial flaB gene fragments (774 and 605 bp, respectively) and for Babesia spp., a 550 bpfragment of 18S rRNA gene was amplified. In total, 91 red squirrels were examined for ticks. There were differences in tick prevalence and mean abundance of infestation in squirrels from the urban forest reserve and urban park. Three species of B. burgdorferi s.l., Rickettsia spp., and Babesia microti were detected in ticks removed from the squirrels. Our results broaden knowledge of S. vulgaris as an important host for immature I. ricinus stages and support the hypothesis that red squirrels act as a reservoir of B. burgdorferi. Moreover, we conclude that red squirrels may also play a role in facilitating the circulation of other pathogens causing serious risk of tick-borne diseases in natural and urban areas.
LAWSUIT: a LArge expert-Written SUmmarization dataset of ITalian constitutional court verdicts
Authors: Ragazzi Luca , Moro Gianluca , Guidi Stefano , Frisoni Giacomo 
Published: September 2024

AbstractLarge-scale public datasets are vital for driving the progress of abstractive summarization, especially in law, where documents have highly specialized jargon. However, the available resources are English-centered, limiting research advancements in other languages. This paper introducesLAWSUIT, a collection of 14K Italian legal verdicts with expert-authored abstractive maxims drawn from the Constitutional Court of the Italian Republic.LAWSUITpresents an arduous task with lengthy source texts and evenly distributed salient content. We offer extensive experiments with sequence-to-sequence and segmentation-based approaches, revealing that the latter achieve better results in full and few-shot settings. We openly releaseLAWSUITto foster the development and automation of real-world legal applications.
The evolution of reproductive characters: an organismal-relational approach
Authors: Cortés-García David , Etxeberria Arantza , Nuño de la Rosa Laura 
Published: September 2024

AbstractThis paper delves into the character concept as applied to reproduction. Our argument is that the prevailing functional-adaptationist perspective falls short in explaining the evolution of reproductive traits, and we propose an alternative organismal-relational approach that incorporates the developmental and interactive aspects of reproduction. To begin, we define the functional individuation of reproductive traits as evolutionary strategies aimed at enhancing fitness, and we demonstrate how this perspective influences the classification of reproductive characters and modes, the comprehension of shared traits as resulting from conflicts of evolutionary interest between individuals, and the explanation of reproductive diversity. After outlining the shortcomings of this framework, we introduce an organismal-relational approach grounded in evolutionary developmental studies of reproduction. This view provides a revised classification for reproductive characters and modes and offers a new understanding of interorganismal traits that takes into account their inherently relational nature. Lastly, we present the research agenda that emerges from this approach, which addresses the core explanatory gaps left by the adaptationist perspective, including the explanation of reproductive homologies and homoplasies, the developmental constraints associated with the evolution of reproductive modes, and the evolvability of reproductive characters.
Social Anxiety Profiles and Psychopathological Symptom Differences in Spanish Adolescents
Authors: Urbán Dori J. A. , García-Fernández José M. , Ingles Candido J. 
Published: September 2024

AbstractResearch on social anxiety (SA) over the years has revealed its associations with different psychopathological symptoms. This study aims to characterize SA profiles in a sample of Spanish adolescents and explore their differences in psychopathological symptoms. Data from 1,288 Spanish students in the 15 to 18 age range (M = 16.30, SD = 0.97, 47.5% female) were collected using random cluster sampling. The Social Anxiety Scale for Adolescents (SAS-A) and the Symptom Assessment-45 Questionnaire (SA-45) were employed. Four SA profiles were revealed by the Latent Profile Analysis (LPA): extreme SA, high SA, moderate SA, and low SA. Statistically significant differences in psychopathological symptoms were revealed by the MANOVA (effect sizes from d = -2.13 to d = -0.37). The extreme SA profile exhibited the most severe psychopathological symptoms, whereas the low SA profile displayed the mildest manifestations. Proposed interventions aim to support adolescents with SA risk profiles.
Studying word meaning evolution through incremental semantic shift detection
Authors: Periti Francesco , Picascia Sergio , Montanelli Stefano , Ferrara Alfio , Tahmasebi Nina 
Published: September 2024

AbstractThe study ofsemantic shift, that is, of how words change meaning as a consequence of social practices, events and political circumstances, is relevant in Natural Language Processing, Linguistics, and Social Sciences. The increasing availability of large diachronic corpora and advance in computational semantics have accelerated the development of computational approaches to detecting such shift. In this paper, we introduce a novel approach to tracing the evolution of word meaning over time. Our analysis focuses on gradual changes in word semantics and relies on an incremental approach to semantic shift detection (SSD) calledWhat is Done is Done(WiDiD). WiDiD leverages scalable and evolutionary clustering of contextualised word embeddings to detect semantic shift and capture temporaltransactionsin word meanings. Existing approaches to SSD: (a) significantly simplify the semantic shift problem to cover change between two (or a few) time points, and (b) consider the existing corpora as static. We instead treat SSD as an organic process in which word meanings evolve across tens or even hundreds of time periods as the corpus is progressively made available. This results in an extremely demanding task that entails a multitude of intricate decisions. We demonstrate the applicability of this incremental approach on a diachronic corpus of Italian parliamentary speeches spanning eighteen distinct time periods. We also evaluate its performance on seven popular labelled benchmarks for SSD across multiple languages. Empirical results show that our results are comparable to state-of-the-art approaches, while outperforming the state-of-the-art for certain languages.
Bounding the family-wise error rate in local causal discovery using Rademacher averages
Authors: Simionato Dario , Vandin Fabio 
Published: September 2024

AbstractMany algorithms have been proposed to learn local graphical structures around target variables of interest from observational data, focusing on two sets of variables. The first one, called Parent–Children (PC) set, contains all the variables that are direct causes or consequences of the target while the second one, known as Markov boundary (MB), is the minimal set of variables with optimal prediction performances of the target. In this paper we introduce two novel algorithms for the PC and MB discovery tasks with rigorous guarantees on the Family-Wise Error Rate (FWER), that is, the probability of reporting any false positive in output. Our algorithms use Rademacher averages, a key concept from statistical learning theory, to properly account for the multiple-hypothesis testing problem arising in such tasks. Our evaluation on simulated data shows that our algorithms properly control for the FWER, while widely used algorithms do not provide guarantees on false discoveries even when correcting for multiple-hypothesis testing. Our experiments also show that our algorithms identify meaningful relations in real-world data.
Internal rates of return for public R&D from VECM estimates for 17 OECD Countries
Authors: Ziesemer Thomas H.W. 
Published: September 2024

AbstractPublic R&D stimulates domestic private and foreign private and public R&D, together enhancing technical change and thereby GDP. In this paper, we evaluate vector-error-correction model (VECM) estimations and simulations of a companion paper in regard to internal rates of return (and related aspects) to additional public R&D of OECD countries and compare them to the macroeconomic literature. We show (i) internal rates of return to public R&D shocks, and (ii) the related payback periods, gain/GDP ratios, and sums of discounted (at 4%) gains. Fourteen of 17 countries show high internal rates of return, short payback periods, and high gains/GDP ratios from positive public R&D shocks if projects are stopped when gains get negative. Three countries show crowding-out effects and require (initial) reductions of public R&D before showing positive results.
Improving thermal comfort using biomimicry in the urban residential districts in New Aswan city, Egypt
Authors: Waheeb Mary I. , Hemeida Fahd A. , Mohamed Abdelaziz F. 
Published: September 2024

AbstractEgypt tends to construct new cities to provide social housing for its citizens. However, the planning of urban residential districts (URDs) in these cities lacks provisions for natural ventilation (NV), and indoor-outdoor thermal comfort, resulting in increased energy consumption during the summer months. This research aims to create a sustainable design through biomimicry to reduce the universal thermal climate index (UTCI) values in the URD in New Aswan thereby enhancing outdoor thermal comfort and reducing energy consumption inside buildings at the level of URD. In this research, the approach of prairie dogs in building their burrows was followed to rearrange and reorient the buildings. Autodesk CFD, Rhino7, Grasshopper, Ladybug, Honeybee, and Dragonfly software was used in the simulation. The rearrangement of the buildings, specifically the oriented design in the east-west direction, caused a difference in pressure between the buildings, leading to improved NV between the buildings. The improvement of NV resulted in a 4.2 °C reduction in UTCI values during specific hours over the six different days in the six summer months, resulting in significant energy savings of 10407.28946 KWh in the URD. The occurrence of a pressure difference between buildings not only improved NV but also enhanced outdoor and indoor thermal comfort, promoting energy conservation. Therefore, careful consideration of the arrangement and orientation of buildings is essential to establish sustainable URDs. Although the difference between the results is slight, it creates substantial differences in the long term for UTCI values, thus the energy conservation in the URDs.
A Mixed Convection Model for Estimating the Critical Velocity to Prevent Smoke Backlayering in Tunnels
Authors: Beyer Michael , Stacey Conrad , Brenn Günter 
Published: September 2024

Abstract
A novel mathematical model for the critical ventilation velocity to prevent smoke backlayering in tunnels is presented, addressing limitations of prior approaches. The basis of the model is a rigorous characterisation of the physical processes by the characteristic quantities. Empirical parameters within the new model are determined, to align with results from both full-size and small-scale tunnel experiments. Data from numerical simulations (CFD, Computational Fluid Dynamics), validated by known test data, are then used to estimate the effects of tunnel slope and other parameters on the critical velocity. The model is seen to approximate the critical velocity well, following all trends identified by test data and CFD parameter studies. The empirically calibrated equation permits prediction of the critical velocity beyond the narrow range of tunnel geometries where known results already give an answer. The resulting equation has practical application for tunnel design.
Development and characterization of a cyclodextrin-based delivery system for enhanced pharmacokinetic and safety profile of oseltamivir
Authors: Olteanu Andreea Alexandra , Rădulescu Flavian Ștefan , Bleotu Coralia , Aramă Corina-Cristina 
Published: September 2024

AbstractOseltamivir (OST) phosphate is a prodrug, metabolized by hepatic carboxylesterase to its active metabolite (oseltamivir carboxylate). OST is efficient in treatment of influenza, in both children and adults. The protein bonding of the prodrug and its active metabolite is low (42% and 3%, respectively). It has a short half-life 1–3 h but its active metabolite has a half-life of 6–10 h, permitting twice daily administration. The most common side effect is gastrointestinal disturbances that are usually nausea and vomiting and can be reduced when taken simultaneously with food. OST phosphate is a white powder with bitter taste and the marketed oral suspension uses sorbitol for masking it. Cross-linked cyclodextrin polymers are known for their ability to increase the dissolution rate, solubility, stability, and permeability of insoluble drugs and provide prolonged release. Therefore, they are promising drug delivery systems that could improve its pharmacokinetic properties and patient adherence. In this study we focused on developing a therapeutic system of OST using cyclodextrin polymer crosslinked with pyromellitic dianhydride (PMDA CD) to enhance its pharmacokinetic properties and to improve its compliance. PMDA CD polymer and PMDA CD polymer complex with OST were prepared. Physicochemical characterization by FTIR spectra, thermal analysis, DLS, SEM and EDX confirmed the existence of interaction between the two components. The prepared complex has a different pharmaceutical profile compared to OST, with higher stability and a controlled dissolution profile. Toxicity studies showed that the polymer complex has lower toxicity than OST, suggesting the protective effect of the polymer.
Separation of Nd(III) from Nd(III)/Co(II) Mixture Using Poly (Carboxymethyl Cellulose.starch-g-acrylic Acid/Al2O3) Nanocomposite
Authors: Dakroury G. A. , Murad G. A. , Abu Elgoud E. M. 
Published: September 2024

AbstractThe separation of neodymium from the Nd(III)/Co(II) mixture is crucial for producing high-purity neodymium, which is essential in industries like electronics. A new nanocomposite, Poly(carboxymethyl cellulose.starch-g-acrylic acid/Al2O3), P(CMC-St-g-AA/Al2O3), was prepared and applied for the sorption and separation of Nd(III) from the Nd(III)/Co(II) mixture. This nanocomposite, synthesized with γ-irradiation of 60Co at 35 kGy, was extensively characterized using SEM, FTIR spectroscopy, and TGA-DTA. Parameters affecting neodymium separation were studied, revealing optimal conditions. Kinetic experiments showed agreement with a pseudo-nth-order kinetic model. Isothermal sorption studies indicated multilayer adsorption, with Co(II) and Nd(III) adsorption capacities of 2.781 mg/g and 8.825 mg/g, respectively, at pH 3.0. Thermodynamic analysis confirmed spontaneous and endothermic sorption. Separation factor values peaked at pH 3.0, shaking for 120 min, 0.1 adsorbent dosage, and ambient temperature, highlighting effective Nd-Co separation under these conditions. In conclusion, the comprehensive analysis and successful application of P(CMC-St-g-AA/Al2O3) nanocomposite underscore its potential as a highly efficient and selective sorbent for neodymium separation.
Design and performance investigation of a sliding-mode adaptive proportional–integral–derivative control for cable-breakage scenario
Authors: Di Paola Vincenzo , Caro Stéphane , Zoppi Matteo 
Published: September 2024

AbstractControlling a cable-driven parallel robot (CDPR) when a cable breaks is challenging. In this paper, a sliding mode adaptive PID control is designed to ensure a safe guidance of the load when a cable fails. Indeed, regardless when a cable breaks, this control makes it possible enchanting the guidance of the load inside the remaining wrench feasible workspace. In other words, it allows reducing the load oscillation and then increasing the safety of the recovery manoeuvre. Performances are evaluated through simulations by considering a spatial CDPR and comparing the results with a PID control.
Evidence-based development of an instrument for the assessment of teachers’ self-perceptions of their artificial intelligence competence
Authors: Delcker Jan , Heil Joana , Ifenthaler Dirk 
Published: September 2024

AbstractArtificial intelligence (AI) competence in education is a set of skills that enable teachers to ethically and responsibly develop, apply, and evaluate AI for learning and teaching processes. While AI competence becomes a key competence for teachers, current research on the acceptance and use of AI in classroom practice with a specific focus on the required competencies of teachers related to AI is scarce. This study builds on an AI competence model and investigates predispositions of AI competence among N = 480 teachers in vocational schools. Results indicate that AI competence can be modeled as combining six competence dimensions. Findings suggest that the different competence dimensions are currently unequally developed. Pre- and in-service teachers need professional learning opportunities to develop AI competence.
Biosphere Reserves as model regions for transdisciplinarity? A literature review
Authors: Dabard Caroline Hélène , Gohr Charlotte , Weiss Fabio , von Wehrden Henrik , Neumann Frederike , Hordasevych Solomiia , Arieta Bruno , Hammerich Jenny , Meier Caroline , Jargow Janine , Luthardt Vera , Ibisch Pierre L. , Ferreira Ana Filipa 
Published: September 2024

AbstractThe World Network of Biosphere Reserves promotes learning sites for sustainable development, designated under the UNESCO Man and the Biosphere programme (MAB). The programme aims to strengthen biodiversity conservation, economic development and capacity building. Scientific research in and about Biosphere Reserves is expected to support these objectives. In response to a strong focus on natural sciences and conservation issues, calls for transdisciplinary approaches emanated from science and the newest MAB Lima Action Plan. Yet, the extent and contributions of transdisciplinary research in Biosphere Reserves remains unexplored. This study provides a comprehensive and systematic screening of 3304 scientific publications in and about Biosphere Reserves published since 1975. Research within Biosphere Reserves spans a broad spectrum, encompassing social to political to ecological investigations, with a focus on natural sciences and studies conducted mainly in Europe and Asia. We identified an emerging field of transdisciplinary science in research, represented in 336 publications. Most transdisciplinary studies were conducted in Mexican and Indian Biosphere Reserves. While transdisciplinary research provided insights about participation, management and governance in Biosphere Reserves, its transformative potential could be enhanced, notably through stronger forms of participation of non-academic actors in research processes. Our review suggests strengthening knowledge co-creation about transformative solutions and interventions addressing deep leverage points. Scientific research could thereby enhance the role of Biosphere Reserves as model regions for sustainability transformations.