bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rapid natural hazard extent estimation from twitter data: investigation for hurricane impact areas
Authors: Florath Janine , Chanussot Jocelyn , Keller Sina 
Published: March 2024

AbstractNatural hazards have occurred more frequently in the past years and pose a severe risk to human life. Their extents and, thereby, the most heavily affected areas must be estimated at the earliest to limit damages or initiate rescue services. For such estimations, a widely available data source, which is comparatively responsive to short-time changes, is needed and provided by volunteered geographic information (VGI) data. Tropical cyclones are natural hazard events that can cause enormous spatially extended damage. In this study, we introduce Machine Learning approaches such as Extremely Randomized Tree (ET) and Geographically Weighted Regression for estimating hurricane-impacted regions from VGI data. In addition to the general approximate track extent estimation, we also evaluate the possibilities of temporal estimation of track development from VGI data. Different scenarios are evaluated, and we find that the results mainly depend on the choice of the geographical splits for training and test data for the underlying regression task. Suitable splits lead to $$R^2$$

R
2

of 99% in the best cases with the ET model. The estimation results are satisfying when considering the temporal aspect and represent a use-case scenario. Such a combination of Machine Learning approaches and VGI is a simple and fast approach for early natural hazard estimation.
Modelling scale effects in rating data: a Bayesian approach
Authors: Iannario Maria , Kateri Maria , Tarantola Claudia 
Published: March 2024

AbstractWe present a Bayesian approach for the analysis of rating data when a scaling component is taken into account, thus incorporating a specific form of heteroskedasticity. Model-based probability effect measures for comparing distributions of several groups, adjusted for explanatory variables affecting both location and scale components, are proposed. Markov Chain Monte Carlo techniques are implemented to obtain parameter estimates of the fitted model and the associated effect measures. An analysis on students’ evaluation of a university curriculum counselling service is carried out to assess the performance of the method and demonstrate its valuable support for the decision-making process.
A Panel Data Analysis of Using Multiple Content Modalities during Adaptive Learning Activities
Authors: Manly Catherine A. 
Published: March 2024

AbstractThis study investigates the effect of offering multiple means of representing content, one aspect of Universal Design for Learning (UDL). Students across the full range of the dis/ability spectrum all too often struggle to achieve course success. UDL-based course design promises to help students with disabilities (whether disclosed or not) as well as help all students, but research is needed to verify UDL’s specific benefits for student learning outcomes. This study aims to better understand the efficacy of representing course content using multiple means, which is one aspect of UDL pertaining to perception. Data were gathered from over 50 online courses in 14 subjects across the undergraduate curriculum taught with an adaptive learning system at a women’s institution. A panel data analysis with almost 200,000 cases of student learning activities investigated the effect of representing content in multiple ways (i.e., text, video, audio, interactive, or mixed content presentation format). When students used multiple modalities, a positive effect was found on student learning measures of knowledge gained within the adaptive system. The results have implications for future UDL-related research, as well as faculty development and curricular design.
Transhumanism, Society and Education: An Edusemiotic Approach
Authors: Gómez Redondo Susana , Rodríguez Higuera Claudio J. , Coca Juan R. , Olteanu Alin 
Published: March 2024

AbstractWe propose a semiotic framework to underpin a posthumanist philosophy of education, as contrasted to technological determinism. A recent approach to educational processes as semiotic phenomena lends itself as a philosophy to understand the current interplay between education and technology. This view is aligned with the transhumanist movement to defend techno-scientific progress as fundamental to human development. Particularly, we adopt a semiotic approach to education to tackle certain tensions in current debates on the human. Transhumanism scholars share the optimistic belief that there is no limit to how the ethical use of technology can help alleviate suffering and increase our health and wisdom. From this perspective, it appears possible to acquire capacities that require rethinking the notion of human altogether. For others, this undermining of essentialist concepts of humanity entails serious risks, especially related to ethical egalitarianism. We adopte the perspective of edusemiotics, a framework that brings together semiotics, educational theory and philosophy of education. As a theoretical-practical framework, edusemiotics affords a hermeneutic and semiotic method for our approach. Peirce’s logic of signs is used to analyze socio- educational interactions as environmental. We observe two lines of thought. On the one hand, technological transhumanism enhances Cartesian mind–body dualism. On the other hand, philosophical posthumanism seeks to overcome this dichotomy. The former proposal construes human transformation as an artifactualization derived from techno-scientific enhancements. The latter position proposes an integrative posthumanism, capable not only to include edusemiotic theory but also to rethink the concept of learning as mutual to that of human.
Assessing Intel OneAPI capabilities and cloud-performance for heterogeneous computing
Authors: Alcaraz Silvia R. , Laso Ruben , Lorenzo Oscar G. , Vilariño David L. , Pena Tomás F. , Rivera Francisco F. 
Published: March 2024

AbstractThis work presents a performance-oriented study of a heterogeneous application developed with Intel OneAPI to solve two well-known diffusion problems: heat diffusion and image denoising. We have explored CPU+iGPU and CPU+FPGA schemes, applying dynamic load balancing and conducting experiments on Intel DevCloud. The results demonstrate that the CPU+iGPU scheme outperforms the execution times achieved by the fastest device when the problem is sufficiently computationally demanding. We also found that the performance of the CPU+FPGA scheme is heavily affected by bandwidth limitations and specific strategies to manage memory efficiently are required. Moreover, it was demonstrated that dynamic workload balancing is crucial due to possible performance fluctuations in any of the implicated devices. In conclusion, Intel OneAPI provides a helpful tool for multi-platform development using a unique high-level language, DPC++. However, developing specific code for each platform is necessary to achieve optimal performance.
Affective Artificial Agents as sui generis Affective Artifacts
Authors: Facchin Marco , Zanotti Giacomo 
Published: March 2024

AbstractAI-based technologies are increasingly pervasive in a number of contexts. Our affective and emotional life makes no exception. In this article, we analyze one way in which AI-based technologies can affect them. In particular, our investigation will focus on affective artificial agents, namely AI-powered software or robotic agents designed to interact with us in affectively salient ways. We build upon the existing literature on affective artifacts with the aim of providing an original analysis of affective artificial agents and their distinctive features. We argue that, unlike comparatively low-tech affective artifacts, affective artificial agents display a specific form of agency, which prevents them from being perceived by their users as extensions of their selves. In addition to this, we claim that their functioning crucially depends on the simulation of human-like emotion-driven behavior and requires a distinctive form of transparency—we call it emotional transparency—that might give rise to ethical and normative tensions.
How does world economic policy uncertainty influence the carbon dioxide emission reporting and performance? Study of Fortune Global 500 firms
Authors: Persakis Antonios , Fassas Athanasios , Koutoupis Andreas 
Published: March 2024

AbstractThis study contributes significantly to the field by utilising the World Economic Policy Uncertainty (WEPU) Index, as devised by (Ahir in Nat Bureau Econ Res 2022), to scrutinise its impact on carbon dioxide emission reporting and performance. Employing the generalised method of moments (GMM) on a substantial dataset of 604 Fortune Global 500 firms spanning from 2005 to 2020, our analysis reveals crucial insights. The research elucidates the dual influence of WEPU Index: a positive correlation with carbon dioxide emission reporting and a negative correlation aimed at mitigating adverse effects and promoting sustainable practices, thereby enhancing firm trust. Moreover, the findings shed light on how companies in emission-intensive industries tend to ramp up carbon dioxide emission reporting, potentially to bolster investor confidence, particularly during high WEPU Index periods. Furthermore, this study uncovers a compelling association between high emitters and lowered carbon dioxide emission performance, stemming from political and social pressures to integrate environmental considerations. Notably, this pressure intensifies during periods of increased WEPU Index. The empirical results presented in this study carry immediate practical implications. Specifically, they offer valuable insights for regulatory bodies and industry associations, guiding the development of enhanced environmental and social reporting regulations and guidelines, particularly concerning carbon emission reporting and performance.
Photo-thermal activation of persulfate for the efficient degradation of synthetic and real industrial wastewaters: System optimization and cost estimation
Authors: El-monem Hany Abd , Mahanna Hani , El-Halwany Mohamed , Samy Mahmoud 
Published: March 2024

AbstractThe photo-thermal activation of persulfate (PS) was carried out to degrade various pollutants such as reactive blue-222 (RB-222) dye, sulfamethazine, and atrazine. Optimizing the operating parameters showed that using 0.90 g/L of PS at pH 7, temperature of 90 °C, initial dye concentration of 21.60 mg/L, and reaction time of 120 min could attain a removal efficiency of 99.30%. The degradation mechanism was explored indicating that hydroxyl and sulfate radicals were the prevailing reactive species. The degradation percentages of 10 mg/L of sulfamethazine and atrazine were 83.30% and 70.60%, respectively, whereas the mineralization ratio was 63.50% in the case of real textile wastewater under the optimal conditions at a reaction time of 120 min. The treatment cost per 1 m3 of real wastewater was appraised to be 1.13 $/m3 which assured the inexpensiveness of the proposed treatment system. This study presents an effective and low-cost treatment system that can be implemented on an industrial scale.
How to improve market performance through competitive strategy and innovation in entrepreneurial SMEs
Authors: Rubio-Andrés Mercedes , Linuesa-Langreo Jorge , Gutiérrez-Broncano Santiago , Sastre-Castillo Miguel Ángel 
Published: March 2024

AbstractDespite the limited resources of small and medium-sized enterprises (SMEs), they can still manage to be competitive and survive in the current environment by implementing competitive strategies that lead to innovation and improve their market performance. The aim of this study is to examine and analyse the effect of business strategy on market performance in Spanish small and medium-sized entrepreneurial enterprises, and the mediating effect of innovation is explored as a solution to business crises. In addition, we analyse the moderating effect that the perceived risk of COVID-19 may have on this relationship, as well as whether the commercialisation capacity of SMEs exerts an impact and improves performance based on innovation. Taking 1,842 Spanish entrepreneurial firms with fewer than 250 employees as a reference and using partial least squares structural equation modelling (PLS-SEM), our study shows that entrepreneurial SMEs that apply a competitive strategy can achieve enhanced innovation. Moreover, this innovation has a direct and positive effect on the market performance of SMEs, and this effect is greater under higher marketing capability. Our findings suggest a heterogeneous effect on the impact of the perceived risk of COVID-19 on the strategy-innovation relationship. In entrepreneurial SMEs that adopt a differentiation strategy, the perceived risk has an enhancing impact, while in entrepreneurial SMEs that follow cost strategies, the effect is negative.
Emergence of new firms: A test of the resource-based view, signaling and behavioral perspectives
Authors: Colombo Massimo G. , Lucarelli Caterina , Marinelli Nicoletta , Micozzi Alessandra 
Published: March 2024

AbstractThe resource-based view, signaling, and behavioral perspectives focus on different theoretical mechanisms through which human capital and the behavioral characteristics of nascent entrepreneurs, in combination with insider and outsider financing, may influence the emergence of new ventures. This work tests the relative explanatory power of these different theoretical perspectives. We estimate a mediation model to disentangle the direct effect of nascent entrepreneur personal characteristics on new firm creation from their indirect effects, mediated by the amount of insider financing committed to new ventures and access to greater outsider financing. Our empirical results are based on data from the Panel Study of Entrepreneurial Dynamics (PSED II) and improve our understanding of the drivers of new firm creation and their underlying mechanisms. Our findings support the resource-based view and the behavioral perspective in our sample of nascent entrepreneurs, but do not provide evidence of the signaling perspective.
Beyond a checklist for acceptance: understanding the dynamic process of community acceptance
Authors: Kluskens Nikki , Alkemade Floor , Höffken Johanna 
Published: March 2024

AbstractCommunity acceptance is considered a prerequisite for successful energy transitions and the uptake of renewable energy technologies (RET). While policy and research often focus on acceptance as an outcome, the process of acceptance remains a black box, especially in uncontested RET implementation contexts. We study the dynamic process of community acceptance where (1) different actor groups can have (2) different roles and (3) different active and passive responses towards (4) different objects of acceptance within the RET project implementation. Results show that community acceptance occurs over time and goes beyond citizen or resident acceptance alone. By unpacking different dimensions of acceptance, we show that even in uncontested cases, acceptance is ambiguous and includes various responses toward various objects. Furthermore, we see that roles can influence and interact dynamically with responses and that preferences for roles are heterogeneous. To move beyond acceptance as a merely coincidental outcome, but a widely embraced and intentional process, this process should meet the participatory needs of different actors.
Long-term Results of Duodeno-jejunal Bypass in the Treatment of Obesity and Type 2 Diabetes
Authors: Kral Jan , Benes Marek , Lanska Vera , Macinga Peter , Drastich Pavel , Spicak Julius , Hucl Tomas 
Published: March 2024

Abstract
Purpose
Obesity and its related severe comorbidities are increasing rapidly. The duodenal-jejunal bypass is an endoscopically implanted device (mimicking the Roux-en-Y gastric bypass) developed to support weight reduction and improve type 2 diabetes control.

Materials and Methods
Retrospective data analysis of consecutive patients undergoing duodenal-jejunal bypass (EndoBarrier®, DJB) implantation between 2013 and 2017 was performed to evaluate safety as well as short- and long-term efficacy.

Results
One hundred and twenty-one patients (mean BMI of 43.1 ± 7.2 kg/m2 and weight of 138.2 ± 28.6 kg) underwent DJB implantation. The mean dwelling time was 15.5 months, the mean total body weight loss (%TBWL) after explantation was 10.3% ± 7.9% (14.2 kg, p < 0.0001), and the mean BMI was 39.5 ± 7.3 kg/m2 (p < 0.0001). There was no significant weight gain 24 months after the explantation. Seventy-seven patients had type 2 diabetes mellitus (T2DM) with a mean HbA1c before implantation of 5.6% (n = 52). The mean HbA1c after explantation was 5.1% (p = 0.0001). Significant reductions in transaminase and lipid levels before and after explantation were observed. One complication occurred during implantation and another during explantation. In 16 patients, the device had to be extracted earlier than expected (7 for severe adverse events and 9 for adverse events; 13.2%).

Conclusion
Despite an evident rate of adverse events, the DJB shows promise as a weight-loss procedure. Our results show that some patients implanted with the device maintained reduced weight even 24 months after explantation, while many improved T2DM control.

Graphical Abstract
Intraoperative robotic surgical system-related problems in robot-assisted thoracoscopic surgery
Authors: Ogihara Akira , Omata Motoka , Shidei Hiroaki , Mitsuboshi Shota , Aoshima Hiroe , Isaka Tamami , Matsumoto Takako , Kanzaki Masato 
Published: March 2024

Abstract
Background
Malfunctions of robotic instruments during robotic surgery are well known to occur; however, detailed reports on the inherent problems associated with robotic instruments and robotic surgical systems are scarce. The objective of this study was to retrospectively investigate the intraoperative problems associated with robotic surgical systems and robotic instruments.

Materials and methods
This was a single-center retrospective study. Between April 2012 and December 2022, 544 patients with consecutive lung malignancies and/or mediastinal tumors underwent robot-assisted thoracoscopic surgery. Among these, 15 cases had intraoperative problems associated with the robotic surgical system. Human error was defined as a problem caused by the incorrect operation of the robotic surgical system and human factors as problems in which the robotic surgical system stopped owing to damage to the instruments of the robotic surgical system or the self-diagnosis of the robotic surgical system. We retrospectively investigated the causes of intraoperative problems in these cases.

Results
There were 4 cases (0.7%) with problems related to the robotic surgical system, 2 of which were human errors, and 11 (2.0%) with problems related to robotic surgical instruments, 6 of these were related to instruments and 5 were related to robotic staplers. Five of these were related to human factors.

Conclusion
Teams performing robot-assisted thoracoscopic surgery should be familiar with the features of robotic surgical systems and various robotic devices, be aware of reported problems during robot-assisted thoracoscopic surgery, and be prepared for emergencies.
Legume (Fabaceae) and seed beetle (Coleoptera, Chrysomelidae, Bruchinae) species of Europe: distribution and host specialization
Authors: Szentesi Árpád 
Published: March 2024

AbstractThe paper investigates the distributions of legumes (Fabaceae) and their associated seed beetle species (Bruchinae) across vegetation zones and regions of Europe and evaluates the host range and specialization of seed beetles. 1584 legume species/subspecies/varieties were included in the study and ca. 16% of these serve as known hosts by the 175 seed beetle species found in Europe. Both plant and seed beetle species richness increased from the Boreal to Mediterranean zones/regions. 717 legume species occurred only in single zones/regions and only 4.7% of these (34 species) were hosts for 38 bruchine species specific to a zone/region. Europe has 664 native legume species and 381 of these are Eu-endemics. There were 52 alien legume species found. Similarities in plant species composition by the Sørensen index were pronounced between the Central-European and the Mediterranean, between the Transcaucasian and Mediterranean, and between the Colchis-Caucasian and the Pontic-Caspian areas. The most species-rich genus is Astragalus L. with 334 species and 16 subspecies. Of the two major pre-dispersal seed predator genera, Bruchidius Schilsky species are sensu lato oligophagous, using a wide range of leguminous tribes as hosts, but restricted to few host species within a tribe. In contrast, members of the Bruchus L. genus are sensu stricto oligophagous species and, despite being constrained to the Fabeae tribe, most of them feed on several Lathyrus L. and Vicia L. species. The ways annual and perennial life cycles as well as chemical constituents of legumes might affect the colonization success of the seed beetles are discussed.
Advances in industry 4.0: from intelligentization to the industrial metaverse
Authors: Tantawi Khalid , Fidan Ismail , Huseynov Orkhan , Musa Yasmin , Tantawy Anwar 
Published: March 2024

AbstractOne of the characteristic features of the next-generation of Industry 4.0 is human-centricity, which in turn includes two technological advancements: Artificial Intelligence and the Industrial Metaverse. In this work, we assess the impact that AI played on the advancement of three technologies that emerged to be cornerstones in the fourth generation of industry: intelligent industrial robotics, unmanned aerial vehicles, and additive manufacturing. Despite the significant improvement that AI and the industrial metaverse can offer, the incorporation of many AI-enabled and Metaverse-based technologies remains under the expectations. Safety continues to be a strong factor that limits the expansion of intelligent industrial robotics and drones, whilst Cybersecurity is effectively a major limiting factor for the advance of the industrial metaverse and the integration of blockchains. However, most research works agree that the lack of the skilled workforce will no-arguably be the decisive factor that limits the incorporation of these technologies in industry. Therefore, long-term planning and training programs are needed to counter the upcoming shortage in the skilled workforce.
Exact Solutions for a Class of Variable Coefficients Fractional Differential Equations Using Mellin Transform and the Invariant Subspace Method
Authors: Latif M. S. Abdel , Baleanu D. , Kader A. H. Abdel 
Published: March 2024

AbstractIn this paper, we propose a class of variable coefficients fractional ordinary differential equations (FODEs). Using Mellin transform (MT), we have transformed this class into a functional equation which can’t be solved in general. So, we have selected many special cases of this functional equation that can be solved exactly. After solving these special cases of the functional equation and using the inverse MT, we obtained some exact solutions for the proposed class. The obtained solutions are given in the form of $$H$$
H
-function and the Wright function. The results, as special cases, contain some special forms given in the literature. Also, the invariant subspace method (ISM) is utilized for solving a class of nonlinear fractional diffusion equations with variable coefficients. The solutions of this class of nonlinear fractional diffusion equations depend upon the solutions of the proposed class of FODEs.