bluuebunny/crossref_metadata_2025 huggingface dataset:
Is Green Transition in Europe Fostered by Energy and Environmental Efficiency Feedback Loops? The Role of Eco-Innovation, Renewable Energy and Green Taxation
Authors: Chatzistamoulou Nikos , Koundouri Phoebe
Published: April 2024

Green transition is in the core of the European policy agenda to achieve the ambitious goal of climate neutrality following the launch of the European Green Deal. The cornerstone of the new growth strategy of Europe is resource efficiency which focuses on shifting to a more sustainable production paradigm by conserving scarce resources and by prioritizing enhanced environmental performance. Scattered efforts to investigate the drivers of resource efficiency measures have shed light on the key drivers, however, those consider resource efficiency measures in isolation neglecting for feedback loops influencing green transition. Therefore, we develop a conceptual framework to study green transition as a system of resource efficiency measures affected by feedback loops, path dependence, green technologies, and green policy tools. We mobilize the analysis by devising a unique balanced panel covering the EU-28 from 2010 through 2019, including policy efforts paving the way for green transition. Econometric results based on a system of fractional probit models, indicate that resource efficiency measures are intertwined via feedback loops, especially in the case of environmental efficiency. Green technologies affect green transition, however, rebound effects emerge in the case of energy efficiency. Past performance affects current levels pushing towards divergence. Evidence suggests that green taxation fosters energy efficiency whereas hinders environmental efficiency. The asymmetric operation of feedback loops and green taxation on energy and environmental efficiency highlights that horizontal policies hinder rather than foster green transition. This study contributes to SDGs 7, 12, 13 and 16.
Political ‘Colour’ and Firm Behaviour: Evidence from U.S. Power Plants’ Pollution Abatement
Authors: Di Maria Corrado , Lazarova Emiliya , Lange Lan
Published: April 2024

We ask whether firms behave differently depending on the political party in charge, above and beyond responding to any actual differences in policy. We use the pollution abatement behaviour of U.S. Steam Electric Power Plants under the Clean Water Act as our case study. Exploiting the variation provided by the outcome of tightly contested gubernatorial elections, we provide causal evidence that large firms respond to the political ‘colour’ of the governor in the state they operate, even when neither the stringency nor the enforcement of the rules depend on it. Within a theoretical model of the interaction between the regulator and the regulated firms, we show that multiple equilibria arise, and the outcomes of the election provide an effective coordination device. This unexpected behaviour has real-world consequences and leads to significant differences in pollution levels.
Hearing Behavioral Messages: Avoiding Misinterpretation to Make Effective, Inclusive Decisions
Authors: McGuire Stacy N. , VanUitert Victoria J.
Published: April 2024

Behavior is a form of communication. For many young children, they may engage in certain behaviors to consciously or subconsciously communicate a need to access something, such as a desired adult or peer, sensory stimulation, or a tangible item. Other times, children may engage in a behavior to escape or avoid something, such as a particular environment. Sometimes the behaviors in which young children engage can be interpreted as challenging, based on the perceptions of those who work with the child, including the child’s early childhood teacher. These interpretations of challenging behavior derive from one’s own cultural backgrounds, beliefs, and biases. Such interpretations can lead to discriminatory discipline practices, particularly against children from marginalized and minoritized backgrounds. Instead, teachers can consider the behavioral messages expressed by the children they work with from an unbiased perspective, identify if the behavior in which the child is engaging is truly challenging, and implement appropriate intervention if necessary. The purpose of this paper is to present a plan for hearing behavioral messages of marginalized and minoritized children in a way that systematically addresses their needs while also considering the potential mismatch between teacher and child identities.
Trichoderma koningiopsis applied as seed coating protects sweet sorghum (Sorghum bicolor (L.) Moench) from fungal contaminants during storage
Authors: Osorio-Guerrero Karen Viviana , Patiño-Moscoso Manuel Alfonso , Flórez-Gómez Deisy Lorena , Cortés-Rojas Diego Francisco
Published: April 2024

Seed coating is an effective method for delivering beneficial microorganisms to the soil. Additionally, coated seeds are protected against pathogens or microbial contaminants during storage. This work aimed to evaluate the effect of seed coating with the beneficial fungus Trichoderma koningiopsis against fungal contaminants of sweet sorghum (Sorghum bicolor (L.) Moench) during storage. Sorghum-treated seeds with three concentrations of Trichoderma koningiopsis were stored at two temperatures (5 °C and 18 °C) over 12 months to evaluate physiological-, and sanitary quality of seeds. The concentrations of the most prevalent contaminant fungi Diaporthe melonis, Curvularia lunata and Penicillium polinocum were monitored. The viability of Trichoderma koningiopsis was evaluated every three months and correlated with the seed quality variables. The results indicate that beneficial fungi can protect seeds against fungal contamination during storage avoiding the application of a chemical fungicide. The coating procedure did not affect the seed germination over the 12 months of storage.
Online grocery shopping adoption versus non-adoption among the over-50s in Germany
Authors: Braun Simone , Osman Dunia
Published: April 2024

Online grocery shopping (OGS) has significantly risen due to accelerated retail digitization and reshaped consumer shopping behaviors over the last years. Despite this trend, the German online grocery market lags behind its international counterparts. Notably, with almost half of the German population aged over 50 and the 55–64 age group emerging as the largest user segment in e-commerce, the over-50 demographic presents an attractive yet relatively overlooked audience for the expansion of the online grocery market. However, research on OGS behavior among German over-50s is scarce. This study addresses this gap, empirically investigating OGS adoption factors within this demographic through an online survey with 179 respondents. Our findings reveal that over a third of the over-50 demographic has embraced OGS, indicating a growing receptivity for OGS among the over-50s. Notably, home delivery, product variety, convenience, and curiosity emerged as primary drivers for OGS adoption among this demographic. Surprisingly, most adopters did not increase online grocery orders since 2020 and a not inconsiderable proportion have even stopped buying groceries online again. For potential OGS adopters, regional product availability turned out as a motivator, signaling substantial growth potential and providing online grocers with strategic opportunities to target this demographic. In light of our research, we offer practical suggestions to online grocery retailers, aiming to overcome barriers and capitalize on key drivers identified in our study for sustained growth in the over-50 market segment.
Graded causation and moral responsibility
Authors: Hoffmann-Kolss Vera , Rolffs Matthias
Published: April 2024

Theories of graded causation attract growing attention in the philosophical debate on causation. An important field of application is the controversial relationship between causation and moral responsibility. However, it is still unclear how exactly the notion of graded causation should be understood in the context of moral responsibility. One question is whether we should endorse a proportionality principle, according to which the degree of an agent’s moral responsibility is proportionate to their degree of causal contribution. A second question is whether a theory of graded causation should measure closeness to necessity or closeness to sufficiency. In this paper, we argue that we should indeed endorse a proportionality principle and that this principle supports a notion of graded causation relying on closeness to sufficiency rather than closeness to necessity. Furthermore, we argue that this insight helps to provide a plausible analysis of the so-called ‘Moral Difference Puzzle’ recently described by Bernstein.
When Should Popular Views be Included in a Reflective Equilibrium?
Authors: Jølstad Borgar , Juth Niklas , Solberg Carl Tollef , Barra Mathias
Published: April 2024

It has become increasingly common to conduct research on popular views on ethical questions. In this paper, we discuss when and to what extent popular views should be included in a reflective equilibrium process, thereby influencing normative theory. We argue that popular views are suitable for inclusion in a reflective equilibrium if they approximate considered judgments and examine some factors that plausibly contribute to the consideredness of popular views. We conclude that deliberation and familiarity contribute to the consideredness of popular views, whereas prevalence does not. Furthermore, we raise the “fair trial” objection: that expert deliberation on popular views might fail to respect the consideredness of these views. Eliciting views approximating considered judgments directly from participants is therefore preferable to refining popular views or treating them as “bare” intuitions in the reflective process. These conclusions have important implications for which research methods will likely elicit popular views suitable for a reflective equilibrium process. Research focusing on the prevalence of views is unlikely to yield popular views suitable for a reflective equilibrium, whereas deliberative and in-depth work is more promising.
Loss of amphibian species alters periphyton communities in montane ponds
Authors: Alonso Alberto , Bosch Jaime , Boyero Luz
Published: April 2024

Amphibian larvae can affect the structure and functioning of freshwater ecosystems, but their effects have been little explored although amphibian biodiversity is rapidly declining. Given that larvae of different amphibian species belong to different trophic levels, their effects on freshwater communities and processes can be expected to differ, with herbivores likely having direct effects on algae and predators having indirect effects through trophic cascades. We explored this question through a mesocosm experiment conducted in montane ponds, using an anuran and a urodele species affected by emergent diseases. We used different scenarios of reduction and loss of one or both species, and compared them to a control scenario representing a typical amphibian community in the study area composed of four species, with total larval density held constant. Loss of the anuran resulted in lower chlorophyll concentration and algal density, likely due to replacement by more efficient grazers. Loss of the urodele produced similar trends but weaker, possibly due to an increase of invertebrate grazing activity in the absence of this predator. Our study shows how the loss of amphibian species can alter the structure of montane ponds, but also how the mechanisms involved and the intensity of effects differ for different species.
Professionality Model for Vocational Teachers: Based on the Example of Estonian Vocational Teachers in the Changing VET Context
Authors: Sirk Meidi
Published: April 2024

Vocational teachers (VTs) have been seen as the key individuals executing changes, solving problems and achieving goals in vocational education and training (VET). Therefore, the work of VTs is fragmented between different types of tasks which influence their professionalism and professionality (individual views, experiences and professional practices of teachers). Despite this, their professionality has been studied remarkably little, and previous studies have focused on different narrow aspects of professionalism. However, it is not clear how various factors, including changes in VET, can shape VTs’ perception of their professionality. Based on a meta-analysis, this study aims to create comprehensive knowledge through an empirical model of vocational teacher professionality in the context of VET changes based on the example of Estonian VET. The results show that VTs have expressed different perceptions, evaluations and experiences of change in VET, and therefore different forms of collaboration and learning activities have been used to adapt to changes, which together shape the professionality of VTs. Therefore, three profiles of VT professionality have emerged and the wider scope of the collaboration of VTs fosters more positive attitudes, satisfaction and commitment to their work and profession, while also relating to their higher self-efficacy, which supports coping in demanding pedagogical situations and when faced with new tasks and roles in a changing context.
Conceptualizing the digital thread for smart manufacturing: a systematic literature review
Authors: Abdel-Aty Tasnim A. , Negri Elisa
Published: April 2024

Business operations and supporting data analysis initiatives are impeded by the silos of data present within departments, systems, and business units. Consequently, the ability of managers and engineers to harness data for operational management and informed decision-making is curtailed. The rapid advancements in technology have revolutionized various aspects of product development, manufacturing, operations, and end-of-life treatment. One such transformative concept, the digital thread, has emerged as an important paradigm. It orchestrates the integration of information and data along the entire product lifecycle, spanning from initial design and engineering through production, maintenance, use, and eventual end of life. While the digital thread has garnered increasing attention within both the research community and industrial enterprises, there remains a notable lack of standardization concerning its utilization and applications. This comprehensive literature review aims to explore the role of the digital thread in manufacturing within the context of the product lifecycle. As a result, this review synthesizes insights into the technologies, roles, and functions of the digital thread throughout the product lifecycle. Furthermore, it proposes a structured framework designed to impart a standardized perspective of the digital thread’s relevance within the manufacturing product lifecycle. Ultimately, this framework is poised to serve as a guiding resource for practitioners and researchers in designing and implementing digital threads.
AI-supported Modelling of a Simple TPR System for Fusion Neutron Measurement
Authors: Gerenton V. , Jardin A. , Wiącek U. , Drozdowicz K. , Kulinska A. , Kurowski A. , Scholz M. , Woźnicka U. , Dąbrowski W. , Łach B. , Mazon D.
Published: April 2024

The system proposed to measure the tritium to deuterium ratio on the International Thermonuclear Experimental Reactor (ITER) is a high-resolution neutron spectrometer, partly composed of a system of three Thin-foil Proton Recoil (TPR) spectrometers. This system works on the principle of converting neutrons into protons using a thin foil of polyethylene, which is then detected in silicon detectors to obtain the scattering angles and energy spectrum of the protons. The objective of this article is to show the benefit of artificial intelligence for improving a simple TPR system model written in Python to an accuracy approaching MCNP simulations, while significantly decreasing the computational cost. The first step was to model a polyethylene converter to obtain the energy-angle distribution of outgoing protons for a given incident neutron beam. When compared with MCNP, this simplified model was found to fail to account for proton energy and angular scattering. Therefore, in a second step, two neural networks were successfully trained to include these effects based on the output data of the TRIM code, assuming Gaussian distributions. The Python model was able to produce results very close (differences up to a few percent) to those obtained with MCNP by integrating these neural networks. To extend the study, the energy spectra of the protons could be obtained and subsequently used to obtain information on the ratio of deuterium and tritium in the plasma.
Production of Mycelium-Based Papers from Carrot Pomace and Their Potential Applications for Dye Removal
Authors: Mousavi S. Najmeh , Ramamoorthy Sunil Kumar , Hakkarainen Minna , Zamani Akram
Published: April 2024

The Current study aimed at valorizing carrot pomace (CP), an abundant waste from the juice industry. A water-soluble fraction of CP was separated from solid fraction of CP (SFCP) and employed as feedstock for producing fungal biomass (FB) in bench-scale bioreactors. FB combined with SFCP were used to develop mycelium-based papers (MBP) using the wet-laid method. The potential and capacity of FB, SFCP and MBP to remove dye (methylene blue) from wastewater was then investigated. The maximum achieved dye removal was 92% when using a mixture of SFCP and FB in their suspended forms. The MBP with the lowest density (549 kg/m3) reached 83% dye elimination. The findings of this study support the valorization of carrot pomace, through environmentally benign processes, to mycelium-based papers with potential application in wastewater treatment.
Necropolitics of Death in Neurodegeneration
Authors: de la Rosa T. , Berrocoso E. , Scorza F. A.
Published: April 2024

Neurodegenerative diseases (ND) pose significant challenges for biomedicine in the twenty-first century, particularly considering the global demographic ageing and the subsequent increase in their prevalence. Characterized as progressive, chronic and debilitating, they often result in higher mortality rates compared with the general population. Research agendas and biomedical technologies are shaped by power relations, ultimately affecting patient wellbeing and care. Drawing on the concepts of bio- and necropolitics, introduced by philosophers Foucault and Mbembe, respectively, this perspective examines the interplay between the territoriality and governmentality around demographic ageing, ND and death, focussing on knowledge production as a dispositif of power by highlighting the marginal role that the phenomenon of mortality plays in the ND research landscape. We propose a shift into acknowledging the coloniality of knowledge and embracing its situatedness to attain knowledge ‘from death’, understood as an epistemic position from which novel approaches and practices could emerge.
Quasi-free Isomorphisms of Second Quantization Algebras and Modular Theory
Authors: Conti Roberto , Morsella Gerardo
Published: April 2024

Using Araki–Yamagami’s characterization of quasi-equivalence for quasi-free representations of the CCRs, we provide an abstract criterion for the existence of isomorphisms of second quantization local von Neumann algebras induced by Bogolubov transformations in terms of the respective one particle modular operators. We discuss possible applications to the problem of local normality of vacua of Klein-Gordon fields with different masses.
Dynamic data hiding capacity enhancement for the Hybrid Near Maximum Histogram image steganography based on Multi-Pixel-Pair approach
Authors: Sondas Adnan , Erturk Necla Bandirmali
Published: April 2024

Increasing data hiding capacity and making it difficult to detect presence of any confidential data in stego images are the key objectives in contemporary image steganography research ever-improving the embedding efficiency. With regard to these crucial and challenging points, a new Multi-Pixel-Pair (MPP)-based data hiding approach is proposed in this paper. It can dynamically increase data embedding capacity of the classical Hybrid Near Maximum Histogram (HNMH) image steganography method while well-maintaining the embedding efficiency. In the proposed MPP approach, the peak value as a reference point in the histogram distribution of a cover image is obtained, and accordingly the pixel-pairs of interest where secret data is to be embedded are determined. Then, the pixels of the cover image are scanned sequentially and data hiding is performed on the relevant pixels by using the Least Significant Bit (LSB) method. In an extensive experimental study of the proposed MPP approach, it is shown that the classical HNMH data hiding capacity is dynamically improved 4.74 to 37.48 times while the Peak Signal to Noise Ratio (PSNR) decreases between 6.62 and 13.75 dB, implying both a reasonable trade-off and 7.61% enhanced embedding efficiency performance. Moreover, using the well-known cover image partitioning technique, offering significant improvements in image steganography, and the proposed MPP approach together, can further extend the data hiding capacity about 7.05%.
Encoding laparoscopic image to words using vision transformer for distortion classification and ranking in laparoscopic videos
Authors: AlDahoul Nouar , Karim Hezerul Abdul , Momo Mhd Adel , Tan Myles Joshua Toledo , Fermin Jamie Ledesma
Published: April 2024

Laparoscopic videos are tools used by surgeons to insert narrow tubes into the abdomen and keep the skin without large incisions. The videos captured by a camera are prone to numerous distortions such as uneven illumination, motion blur, defocus blur, smoke, and noise which have impact on visual quality. Automatic detection and identification of distortions are significant to enhance the quality of laparoscopic videos to avoid errors during surgery. The video quality assessment includes two stages: classification of distortions affecting the video frames to identify their types and ranking of distortions to estimate the intensity levels. The dataset generated in ICIP2020 challenge including laparoscopic videos was utilized for training, validation, and testing the proposed solution. The difficulty of this dataset is caused by having five categories of distortions and four levels of severity. Additionally, the availability of multiple distortion categories in one video is considered the most challenging part of this dataset. The work presented in this paper contributes to solve the multi-label distortion classification and ranking problem. This paper aims to enhance the performance of distortion classification solutions. Vision transformer which is a deep learning model was used to extract informative features by transferring learning and representation from the general domain to the medical domain (laparoscopic videos). Additionally, six parallel multilayer perceptron (MLP) classifiers were added and attached to vision transformer for distortion classification and ranking. The experiment showed that the proposed solution outperforms existing distortion classification methods in terms of average accuracy (89.7%), average single distortion F1 score (94.18%), and average of both single and multiple distortions F1 score (96.86%). Moreover, it can also rank the distortions with an average accuracy of 79.22% and average F1 score of 78.44%. Hence, the high performance of the method proposed in this paper opens the door to integrate our solution in the intelligent video enhancement system.
GPT for medical entity recognition in Spanish
Authors: García-Barragán Álvaro , González Calatayud Alberto , Solarte-Pabón Oswaldo , Provencio Mariano , Menasalvas Ernestina , Robles Víctor
Published: April 2024

In recent years, there has been a remarkable surge in the development of Natural Language Processing (NLP) models, particularly in the realm of Named Entity Recognition (NER). Models such as BERT have demonstrated exceptional performance, leveraging annotated corpora for accurate entity identification. However, the question arises: Can newer Large Language Models (LLMs) like GPT be utilized without the need for extensive annotation, thereby enabling direct entity extraction? In this study, we explore this issue, comparing the efficacy of fine-tuning techniques with prompting methods to elucidate the potential of GPT in the identification of medical entities within Spanish electronic health records (EHR). This study utilized a dataset of Spanish EHRs related to breast cancer and implemented both a traditional NER method using BERT, and a contemporary approach that combines few shot learning and integration of external knowledge, driven by LLMs using GPT, to structure the data. The analysis involved a comprehensive pipeline that included these methods. Key performance metrics, such as precision, recall, and F-score, were used to evaluate the effectiveness of each method. This comparative approach aimed to highlight the strengths and limitations of each method in the context of structuring Spanish EHRs efficiently and accurately.The comparative analysis undertaken in this article demonstrates that both the traditional BERT-based NER method and the few-shot LLM-driven approach, augmented with external knowledge, provide comparable levels of precision in metrics such as precision, recall, and F score when applied to Spanish EHR. Contrary to expectations, the LLM-driven approach, which necessitates minimal data annotation, performs on par with BERT’s capability to discern complex medical terminologies and contextual nuances within the EHRs. The results of this study highlight a notable advance in the field of NER for Spanish EHRs, with the few shot approach driven by LLM, enhanced by external knowledge, slightly edging out the traditional BERT-based method in overall effectiveness. GPT’s superiority in F-score and its minimal reliance on extensive data annotation underscore its potential in medical data processing.
Assessment of flood risk in Söğütlü stream watershed of Trabzon province in Turkey using geographic information systems and analytic hierarchy process approach
Authors: Koralay Necla , Kara Ömer
Published: April 2024

Floods are significant natural disasters that have wide-ranging social, economic, and environmental consequences on a global scale. They lead to land degradation and increased erosion, which in turn negatively impacts water quality. In the present study, the Söğütlü stream watershed in the Eastern Black Sea Region of Turkey was chosen as the study area to create a flood risk map using Analytical Hierarchy Process and Weighted Overlay tools in the ArcGIS. The raster maps, including soil type, rainfall, landuse, slope, aspect, elevation, and distance to the stream, were utilized as the foundation for the analysis. The flood risk map generated from this analysis reveals five risk zones that is very high, high, moderate, low, and very low-risk zones. Statistical analysis was performed to evaluate the obtained data. The study results indicate that low and moderate areas encompass 95.98% of the watershed, while high-risk and very high-risk areas account for 4.02% of the watershed in the flood risk map of the Söğütlü watershed. It was observed that areas in close proximity to rivers, low slope end elevation were more susceptible to flooding. This study is great importance as it allows for the development of preventive, preparatory, and post-disaster plans before flood events occur by providing a flood risk map. Moreover, the creation of a flood risk map at the watershed scale helps planners in undertaking soil and water conservation efforts during watershed planning.
Frequency lock-in control and mitigation of nonlinear vortex-induced vibrations of an airfoil structure using a conserved-mass linear vibration absorber
Authors: Basta Ehab , Gupta Sunit K. , Barry Oumar
Published: April 2024

We investigate the effectiveness of a vibration absorber on the vortex-induced vibration response of turbine blades during the frequency lock-in phase. A reduced-order model of a turbine blade and van der Pol oscillator is used to represent the fluid–blade interaction caused by the vortex shedding. A spring-mass-damper system is considered to model the vibration absorber. The advantage of the vibration absorber is demonstrated by simulating the nonlinear coupled four-degree-of-freedom aeroelastic system for the different sets of system parameters. We observe the dominance of a nonlinear vibration absorber over the linear vibration absorber only for the higher coupling parameter values. The analytical solution of the nonlinear coupled system is obtained through the method of multiple scales for the case of 1:1 internal resonance to identify the critical design parameters of the vibration absorber. We observe the high sensitivity of the system's frequency response to the distance of the vibration absorber from the elastic axis, along with the absorber's damping, stiffness, and mass. Finally, we perform a parametric analysis on the lock-in of the stability region to better understand the effect of the vibration absorber on the instability region.
The PROMIS-16 reproduces the PROMIS-29 physical and mental health summary scores accurately in a probability-based internet panel
Authors: Hays Ron D. , Herman Patricia M. , Rodriguez Anthony , Slaughter Mary , Zeng Chengbo , Edelen Maria Orlando
Published: April 2024

Purpose

The Patient-Reported Outcomes Measurement Information System® (PROMIS)-16 assesses the same multi-item domains but does not include the pain intensity item in the PROMIS-29. We evaluate how well physical and mental health summary scores estimated from the PROMIS-16 reproduce those estimated using the PROMIS-29.

Methods

An evaluation of data collected from 4130 respondents from the KnowledgePanel. Analyses include confirmatory factor analysis to assess physical and mental health latent variables based on PROMIS-16 scores, reliability estimates for the PROMIS measures, mean differences and correlations of scores estimated by the PROMIS-16 with those estimated by the PROMIS-29, and associations between differences in corresponding PROMIS-16 and PROMIS-29 scores by sociodemographic characteristics.

Results

A two-factor (physical and mental health) model adequately fits the PROMIS-16 scores. Reliability estimates for the PROMIS-16 measures were slightly lower than for the PROMIS-29 measures. There were minimal differences between PROMIS physical and mental health summary scores estimated using the PROMIS-16 or the PROMIS-29. PROMIS-16 and PROMIS-29 score differences by sociodemographic characteristics were small. Using the PROMIS pain intensity item when scoring the PROMIS-16 produced similar estimates of physical and mental health summary scores.

Conclusion

The PROMIS-16 provides similar estimates of the PROMIS-29 physical and mental health summary scores. The high reliability of these scores indicates they are accurate enough for use with individual patients.
Simple is simply not enough—features versus labels of complex financial securities
Authors: Hibbeln Martin , Osterkamp Werner
Published: April 2024

We examine how design features and labels of complex financial securities affect pricing and performance. Hence, we utilize the security design features required by the European Union’s Securitization Regulation and the optional STS label (“Simple, Transparent, and Standardized”). Based on a unique dataset of European securitizations with 31 million quarterly loan observations, we find that investors hardly consider the features but rely on the existence of the label, although the latter has no performance-increasing effect. Our results reveal that investors neglect a proper risk assessment and misinterpret the easily accessible label as a signal of superior performance.
Is the scientific impact of the LIS themes gender-biased? A bibliometric analysis of the evolution, scientific impact, and relative contribution by gender from 2007 to 2022
Authors: Choji Thamyres T. , Cobo Manuel J. , Moral-Munoz Jose A.
Published: April 2024

Gender equity remains a challenge both globally and within academia, despite recent efforts to change it. Moreover, beyond the authors’ productivity, studies have reported that women often achieve lower scientific impact than their peers. To shed light on this complex relationship between the scientific impact and the themes addressed, this study conducts a comprehensive analysis of Library and Information Science field from 2007 to 2022 in four consecutive slides, identifying the principal themes covered in the field, analyzing the relative gender contribution rate, employing strategic diagrams, and assessing impact metrics, such as mean normalized citation score, 1% of most cited papers, and H-Classic. We employed science mapping analysis to explore a core of 45,650 documents from the Web of Science, with gender identification in 94.25% of cases. Our findings revealed a slight increase in the percentage of women authors within the field across the time, and a decline during the COVID-19 pandemic, demonstrating consistency in the themes addressed over the years. Women were overrepresented in the classic themes of LIS, human, and health-related fields, with these themes displaying lower performance rates. In contrast, men authors were overrepresented in STEM-related fields and innovation themes, associated with higher metric values. Our findings underlined the potential association between research themes and scientific performance, and provide societal and structural explanations for these observations. This study contributes valuable insights into the relationship between research themes and the scientific impact achieved by researchers in LIS, highlighting the importance of encouraging women’s participation in diverse knowledge domains and challenging prevailing stereotypes within academic and professional spheres.
National research impact is driven by global collaboration, not rising performance
Authors: Adams Jonathan , Szomszor Martin
Published: April 2024

We examine the link between a country’s average citation impact and both national research assessment and international collaboration. Our analysis finds little synchrony between national policies and performance change. We do find extensive, synchronous, cross-national change, however, despite a diversity of national research strategies. Specifically, during 1981–2020, there are synchronous cross-national changes in bilateral, and later multilateral, collaboration. We deconstruct the citation indicators and show that the average citation impact of domestic research and of collaborative research changes little for most countries. Net increases in average national citation impact have instead been driven by rising collaboration and the emerging global network. Greater collaboration enables greater subject diversity, contributes to convergence of subjects, and influences performance indicators. Coincidentally, it also results in all large nations apparently achieving higher average impact than the world average. These effects suggest a need both to strengthen policy analysis of the global context and to construct proper performance indicators when developing research strategy.
Coronal Holes, Footpoint Reconnection, and the Origin of the Slow (and Fast) Solar Wind
Authors: Wang Y.-M.
Published: April 2024

The tendency for low-speed solar wind to show greater spatiotemporal variability and different compositional properties from high-speed wind has led to the prevailing idea of a bimodal solar wind, in which fast wind comes from coronal holes and slow wind comes from coronal streamers. We present observational evidence that most of the slow wind originates from small coronal holes or from just inside the boundaries of large holes, with the rest leaking out from coronal streamers and confined to the immediate vicinity of the heliospheric current and plasma sheets. Although this conclusion was suggested earlier by extrapolations of photospheric field maps, additional support comes from (1) observations of slow wind at Earth following the central-meridian passage of small equatorial holes; (2) observations of slow wind with high Alfvénicity at 1 au by Wind, and more recently near the Sun by Parker Solar Probe and Solar Orbiter; and (3) the finding that 80% of the solar wind observed by Helios at 0.3 – 0.4 au during 1974 – 1978 was Alfvénic. We show that compositional properties such as charge-state ratios vary over the solar cycle and may depend on parameters such as the footpoint field strength $B_{0}$

B
0

, and thus cannot be used alone to distinguish between coronal hole and noncoronal-hole wind. Finally, we note that magnetograms greatly underestimate the amount of small-scale flux emerging inside coronal holes and other unipolar regions. If this rate is taken to be the same as in the quiet Sun, the energy flux density resulting from interchange reconnection with open field lines is on the order of $3\times 10^{5}$
3
×

10

5

erg cm−2 s−1 ($B_{0}$

B
0

/10 G), sufficient to drive the solar wind. The wind speed depends on the rate of flux-tube expansion, with slower expansion leading to more energy deposition at greater heights and faster wind.
Validity evidence for the attitudes on person-centered behavior toward students questionnaire (APBS): Internal structure and associations with external variables
Authors: Teistler Nadja
Published: April 2024

Building positive teacher-student relationships (TSR) is a central task for teachers. According to the person-centered approach, teachers create positive relationships by treating students with unconditional positive regard, empathic understanding, and genuineness. Numerous studies demonstrate the impact of person-centered teacher behavior for students’ achievement and well-being. The effectiveness of person-centered behavior is supposed to be determined by underlying attitudes. Accordingly, person-centered attitudes should receive greater focus in both teacher education and TSR research. However, a suitable measurement instrument is currently lacking. Therefore, the APBS instrument was developed, a theoretically-grounded self-report questionnaire that measures pre-service teachers' attitudes on person-centered behavior toward students. In previous studies, the suitability of the test's content and internal structure were empirically examined using EFA. The present study investigated the internal structure using CFA, as well as the associations with external variables, in a sample of N = 1284 pre-service teachers from German universities (Mage = 23.3, SDage = 5.2; 79.8% female). Different factor models were tested and compared. The model with four first-order factors (unconditionality, empathic understanding, trust, genuineness) along with the APBS higher-order factor showed the best fit (χ2/df(1504.868/520) = 2.894, p < .001; CFI = .968; RMSEA =  .038). Both the four first-order scales (ωt* = .81-.90), and the second-order scale (ωt* = .95) exhibited satisfactory internal consistency. In addition, structural regression and mediation analyses revealed mostly theory-consistent relationships with respondents' attachment representation, empathy and relational competence. In summary, the findings support the intended interpretation of APBS test scores. The questionnaire can be used as a measurement instrument in TSR research and as a self-exploration tool in teacher education.
Aromaticity – a theoretical notion
Authors: Agranat Israel
Published: April 2024

In 2023, a themed collection on “Emerging frontiers in aromaticity” was published in Chemical Science. The collection included a Perspective Essay entitled “Aromaticity – Quo Vadis”, which presents a wealth of viewpoints on the multiple definitions of aromaticity. The present Prefatory Review revives the viewpoint that aromaticity is a theoretical notion and as such, its meaning is theory dependent. Therefore, when aromaticity is made to correspond to two or more ‘experimental’ ideas, e.g., energetic, structural, electronic, magnetic, it would be absurd to maintain that aromaticity is explicitly defined by each of these ideas in turn. The Review emphasizes that the descriptor ‘theoretical’ in general, including in the context of aromaticity does not mean ‘computational’. The theoretical notion of aromaticity is illustrated by Craig’s rules of aromaticity and by Craig’s second type of aromaticity based on symmetry and delocalization in pπ-dπ bonds, recently highlighted as ‘Craig-Type Möbius aromaticity’.
Multimodal Machine Learning in Image-Based and Clinical Biomedicine: Survey and Prospects
Authors: Warner Elisa , Lee Joonsang , Hsu William , Syeda-Mahmood Tanveer , Kahn Charles E. , Gevaert Olivier , Rao Arvind
Published: April 2024

Machine learning (ML) applications in medical artificial intelligence (AI) systems have shifted from traditional and statistical methods to increasing application of deep learning models. This survey navigates the current landscape of multimodal ML, focusing on its profound impact on medical image analysis and clinical decision support systems. Emphasizing challenges and innovations in addressing multimodal representation, fusion, translation, alignment, and co-learning, the paper explores the transformative potential of multimodal models for clinical predictions. It also highlights the need for principled assessments and practical implementation of such models, bringing attention to the dynamics between decision support systems and healthcare providers and personnel. Despite advancements, challenges such as data biases and the scarcity of “big data” in many biomedical domains persist. We conclude with a discussion on principled innovation and collaborative efforts to further the mission of seamless integration of multimodal ML models into biomedical practice.
Non-parametric Regression Among Factor Scores: Motivation and Diagnostics for Nonlinear Structural Equation Models
Authors: Grønneberg Steffen , Irmer Julien Patrick
Published: April 2024

We provide a framework for motivating and diagnosing the functional form in the structural part of nonlinear or linear structural equation models when the measurement model is a correctly specified linear confirmatory factor model. A mathematical population-based analysis provides asymptotic identification results for conditional expectations of a coordinate of an endogenous latent variable given exogenous and possibly other endogenous latent variables, and theoretically well-founded estimates of this conditional expectation are suggested. Simulation studies show that these estimators behave well compared to presently available alternatives. Practically, we recommend the estimator using Bartlett factor scores as input to classical non-parametric regression methods.
Monitoring the impacts of rainfall characteristics on sediment loss from road construction sites
Authors: Grimm Alec G. , Tirpak Richard A. , Winston Ryan J.
Published: April 2024

Exposed soils associated with active construction sites provide opportunities for erosion and sediment transport during storm events, introducing risks associated with excess sediment to downstream infrastructure and aquatic biota. A better understanding of the drivers of sediment transport in construction site runoff is needed to improve the design and performance of erosion and sediment control measures (ESCMs). Eleven monitoring locations on 3 active road construction sites in central Ohio were established to characterize runoff quality from points of concentrated flow during storm events. Grab samples were analyzed for total suspended solids (TSS), turbidity, and particle size distribution (PSD). Median TSS concentrations and turbidity levels across all samples were 626 mg/L (range 25–28,600 mg/L) and 759 NTU (range 22–33,000 NTU), respectively. The median PSD corresponded to a silty clay loam, mirroring the soil texture of much of Ohio’s subsoils. TSS concentrations and turbidity were significantly positively correlated with the rainfall intensity 10 min prior to sample collection, suggesting that higher flow rates created greater shear stress on bare soil which resulted in more erosion. Conversely, rainfall duration was negatively correlated with particle size, indicating that prolonged moisture from rainfall promoted the dispersion of soil aggregates which mobilized smaller particles. Multivariable linear regression models revealed that higher rainfall intensities corresponded to higher turbidity values, while higher TSS concentrations were associated with higher rainfall intensities, depths, and durations. Results from this study highlight the importance of reducing raindrop impact and subsequent shear stress applied by concentrated flows through the use of ESCMs to limit sediment export from construction sites.
Digitale Interventionen zur Förderung der Gesundheitskompetenz: ein Vergleich der Perspektiven von Jugendlichen mit Typ-1-Diabetes und Ärzt:innen
Authors: Naef Aurélia Naoko , Felsenheimer Anne , Klawunn Ronny , Fischbock Nadine , Tezcan-Güntekin Hürrem , Amelung Volker Eric
Published: April 2024

Hintergrund

Für Jugendliche, die als „digital natives“ gelten und an Typ-1-Diabetes (T1D) leiden, bieten digitale Interventionen die Möglichkeit, Gesundheitskompetenz zu stärken. Die COVID-19-Pandemie („coronavirus disease 2019“) hat die Implementierung digitaler Interventionen beschleunigt. Jedoch bleibt die Frage offen, ob sie umfassend in der diabetologischen Versorgung integriert werden können oder randständig genutzt werden.

Ziel der Arbeit

Das Ziel dieser Studie ist der Vergleich der Perspektiven von Ärzt:innen und Jugendlichen mit T1D hinsichtlich des Einsatzes digitaler Interventionen zur Stärkung der Gesundheitskompetenz.

Methoden

Die Studie basiert auf dem Vergleich von 2 separaten qualitativen Primärstudien zu digitalen Interventionen bei Jugendlichen mit T1D. Die Daten wurden durch halbstrukturierte Einzelinterviews erhoben. Die erste Studie untersuchte die Ansichten von Ärzt:innen (n = 12), während die zweite Studie die Perspektiven betroffener Jugendlicher mit T1D (n = 20) betrachtete. Beide Studien wurden separat analysiert und verwenden die COREQ-Checkliste von Tong et al. (2007).

Ergebnisse

Es wurden zwei relevante Themen aus den Studien identifiziert und verglichen: Peer-to-peer-Beziehungen und die Nutzung digitaler Interventionen in der Kommunikation zwischen Ärzt:innen und Jugendlichen mit T1D. Die Ergebnisse deuten darauf hin, dass es Unstimmigkeiten in der Bewertung, der empfundenen Nutzung und des Mehrwerts der digitalen Interventionen gibt.

Schlussfolgerung

Jugendliche mit T1D und Ärzt:innen schätzen den Stellenwert von Peer-to-peer-Beziehungen und Kommunikation und Interaktion zwischen Ärzt:innen und Patient:innen sehr unterschiedlich ein. Diese Unterschiede haben wiederum Implikationen auf die Nutzung von digitalen Gesundheitstechnologien und deren Förderung von Gesundheitskompetenz.