bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimentelle Governance für die Transformation zur Klimaneutralität: Transition Super Lab für den Aufbau der Wasserstoffwirtschaft im Ruhrgebiet
Authors: Wiemann Judith , Meister Thomas , Kiese Matthias 
Published: February 2025

Zusammenfassung
Die Europäische Union, ihre Mitgliedstaaten, Regionen und Städte haben sich dem Ziel der Klimaneutralität verschrieben. Eine zentrale Herausforderung in diesem Transformationsprozess besteht in der Mobilisierung und Beteiligung heterogener Stakeholder aus Politik und Verwaltung, Wirtschaft, Wissenschaft und Zivilgesellschaft. Auf der methodischen Grundlage von Reallaboren (Living Labs) versuchen Transition Super Labs, auf regionaler Ebene Stakeholder in co-kreativen Prozessen zusammenzuführen, um Visionen und systemische Lösungen für regionsspezifische Transformationspfade zur Klimaneutralität zu entwickeln. Durch die frühzeitige Einbindung aller relevanten Akteur:innen sollen Konflikte und Hemmnisse erkannt und abgebaut werden, um die bislang vielfach zähen Transformationsprozesse zu beschleunigen. Dabei gehen Transition Super Labs über den Reallabor-Ansatz hinaus, indem sie Portfolios von miteinander verbundenen Lösungen entwickeln und testen, um Innovationen für einen systemischen Wandel auf regionaler Ebene zu schaffen. Im Rahmen des Horizon-Europe-Projekts TRANSFORMER wurden Transition Super Labs in vier europäischen Regionen durchgeführt, die vor besonderen Transformationsherausforderungen stehen. Der Beitrag stellt diesen Ansatz mit Anwendungsbeispielen zur Beschleunigung der Wasserstofftransformation im Ruhrgebiet vor und diskutiert Erfahrungen aus dem Umsetzungsprozess als Grundlage für die weitere Anwendung und Weiterentwicklung von Transition Super Labs in der Praxis.
Spatio-temporal trends in daily precipitation extremes over the Enkangala escarpment of South Africa: 1961–2021
Authors: Bello Abubakar Hadisu , Scholes Mary C. , Francois Engelbrecht A. 
Published: February 2025

Abstract
The Intergovernmental Panel on Climate Change in its Sixth Assessment Report reported that increases in extreme weather events can already be detected in every region in the world. For eastern southern Africa the report provides evidence of an increasing trend in extreme precipitation events, but more research is needed to understand how this change is manifesting over regions as diverse as South Africa’s eastern escarpment and northern Mozambique. This study evaluates the trends in extreme precipitation over the Enkangala Escarpment, part of South Africa’s eastern escarpment, over the period 1961 to 2021. Daily precipitation data covering 22 stations with fewer than 10% missing values over 61 years were obtained from the South African Weather Service. A total of twelve extreme events precipitation indices were computed using the ClimPACT2 package, and a time series trend analysis was performed using the Trend Free Whitening Mann Kendal test and a field significance test. The results indicate significant increasing trends in nine out of the twelve extreme events indices that were investigated. The three indices which have shown significant decreasing trends include Consecutive Wet days (CWD) at (0.03 day/year total annual rainfall (PRCPTOT) (0.61 mm/decade) and the annual count of days when precipitation ≥ 10 mm (R10mm) of 0.32 days/decade. Indices such Rx1 days, Rx3 days and Rx5 days exhibited increasing trends of 0.2 days/decade each. Other indices with an increasing trend are CDD (3.6 day/decade), R20mm (0.2 days/decade) and R30mm (0.2 days/decade). The R95p (11.2 mm/decade) and R99p (6.0 mm/decade) indices, and Simple Daily Intensity Index(0.4 mm/decade) also exhibit positive trends over the study period. Overall the analysis is indicative of a change in the nature of rainfall over the Enkangala escarpment of South Africa, with annual rainfall totals, the number of consecutive wet days and the frequency of events with smaller thresholds such as 10 mm/day decreasing, but with extreme events of larger thresholds occurring more frequently. That is, when it rains, it tends to rain more intensely than in the past. The use of a field significance test was useful to formalise when relatively small but spatially homogeneous trends detected at separate weather stations yield statistical significance. The findings of the paper are relevant to decision and policy in multiple of socio-economic sectors active in South Africa’s eastern escarpment.
Addressing carbapenemase-producing extensively drug-resistant Pseudomonas aeruginosa: the potential of cefiderocol and ceftazidime/avibactam plus aztreonam therapy
Authors: Montero María Milagro , Domene-Ochoa Sandra , Prim Núria , Ferola Eliana , López-Causapé Carla , Gomis-Font Marian , Ampuero-Morisaki Mario F. , Echeverria Daniel , Sorlí Luisa , Luque Sonia , Padilla Eduardo , Grau Santiago , Oliver Antonio , Horcajada Juan P. 
Published: February 2025

Abstract
This study evaluated the activity of cefiderocol and the combination of ceftazidime/avibactam (CZA) plus aztreonam against carbapenemase-producing extensively drug-resistant (XDR) Pseudomonas aeruginosa isolates. Nine clinical XDR P. aeruginosa isolates with different sequence types and class A (GES) or B (VIM, IMP or NDM) carbapenemases were analysed. Time-kill assays assessed bacterial load reduction for each treatment, while chemostat experiments on four isolates validated these findings. All isolates showed resistance to CZA, with four also resistant to aztreonam. Seven isolates were susceptible to cefiderocol, but two displayed borderline susceptibility (MIC 2–4 mg/L). Time-kill assays demonstrated bactericidal activity by cefiderocol in six isolates at 24 h, while CZA plus aztreonam showed bactericidal effects in three isolates and synergistic/additive effects in four isolates. In the chemostat model, cefiderocol and CZA plus aztreonam were bactericidal in all four tested isolates, with cefiderocol showing greater bacterial reduction in three of these isolates. Both cefiderocol and CZA plus aztreonam achieved significant reductions in bacterial counts compared to controls, but there was no significant difference between cefiderocol monotherapy and the combination. Both cefiderocol and CZA plus aztreonam demonstrated activity against XDR P. aeruginosa carrying metallo-β-lactamase (MBL) and/or serine-β-lactamase (SBL) carbapenemases. Cefiderocol was the only consistently effective monotherapy with a bactericidal effect across all tested isolates in the chemostat model.
“It’s all about factory farming:” German public imaginaries of gene editing technologies in animal agriculture
Authors: Clare Amy , Müller Ruth , Feiler Julia 
Published: February 2025

Abstract
Since its development, scientists have proclaimed that the novel gene editing technology CRISPR-Cas will allow them to modify organisms with unprecedented speed and accuracy. In agriculture, CRISPR-Cas is said to significantly extend the possibilities to genetically modify common livestock animals. Genetic targets in livestock include edits to optimize yield, minimize environmental impacts, and improve animal health, among other targets that could be environmentally, medically, and economically beneficial. In Germany, a transdisciplinary research consortium consisting of geneticists, local animal breeding organizations, social scientists and legal scholars co-developed a “vanguard vision” (Hilgartner in Science and democracy: Making knowledge and making power in the biosciences and beyond, Routledge, London, 2015) for CRISPR-Cas edits in livestock that would improve animal health and benefit local small- to medium-scale farmers. Part of our social science work in this consortium was to discuss these specific application scenarios with members of the public in focus group settings. In this article, we trace how the public engaged with the consortium’s vision of gene editing in smaller-scale animal agriculture. We found that instead of engaging with the vision proposed, a majority of participants held an entrenched “sociotechnical imaginary” (Jasanoff and Kim in Minerva 47:119–146, 2009) that was rooted in “storylines” (Hajer in The politics of environmental discourse: Ecological modernization and the policy process, Clarendon, Oxford, 1995) focused on factory farming, drawing upon arguments from German public and media discourses, NGO campaigning, and political decision-making about genetically modified organisms in the early 2000s. Our analysis points to the difficulties of establishing alternative visions of technology use once a specific sociotechnical imaginary has been established in a distinct national context, and raises questions regarding the possibilities of responsible research and innovation for highly contested technologies.
Microplastic contamination in commercial tilapia feeds: lessons from a developing country
Authors: Siddique Mohammad Abdul Momin , Tahsin Tasnia , Das Koushik 
Published: February 2025

Abstract
Microplastic (MP) contamination in aquaculture feed presents an increasing threat to both the aquaculture industry and global public health. This study examines the occurrence, abundance, characteristics, and risk assessment of MPs in commercial tilapia (Oreochromis niloticus) feeds. MP contamination was found in all feed samples, with the highest levels observed in grower feeds (2150 ± 70.71 MPs/kg), followed by starter feeds (1650 ± 70.71 MPs/kg) and finisher feeds (1300 ± 141.42 MPs/kg). Fibers were the dominant morphotype (85%), and polymer analysis using FTIR identified polypropylene (38.74%) and polyethylene (33.61%) as the most common polymers. Additionally, 84.64% of the extracted MPs were in the 100–1500 µm size range, posing significant health risks to tilapia and potential exposure to consumers. The estimated polymer hazard index (PHI) value for the three feed categories was very high, signaling alarming health risks. The mean polymer load index (PLI) values across the feed categories ranged from 4.23 to 8.03, indicating minor contamination. The study attributes the sources of MPs to feed ingredients, packaging materials, and processing machinery. The high PHI value underscores the need for urgent action to mitigate MP pollution in tilapia farming.

Graphical Abstract
Structure-Modified Zeolites for an Enhanced Production of Bio Jet Fuel Components via Catalytic Pyrolysis of Forestry Residues
Authors: Butt Waqar , Cabello Judith Hernandez , Hedlund Jonas , Shafaghat Hoda 
Published: February 2025

Abstract
Aromatic hydrocarbons are important components of jet fuels mainly due to their effects on lowering the freeze point, enhancing the lubricity, and preventing the fuel leakage in the engines and fueling systems by interacting with their polymer seals. Produced from fossil resources, jet fuel consumption contributes to rising atmospheric CO2 levels. Therefore, efficient utilization of renewable resources, such as biomass, to produce jet fuel components is an important step toward building a sustainable society. Hence, structure-modified zeolite catalysts that determine a high selective production of aromatic HCs in the range of jet fuel chemicals from biomass via catalytic pyrolysis were synthesized and engineered in a PyroGC-MS/FID system. The structure-modified catalysts of hierarchical HBeta (HRCHY HBeta) and defect-free nano-sized crystals ZSM-5 (ZSM-5-F) were used to selectively deoxygenate the reactive species in biomass pyrolysis vapors leading to a high production of renewable jet fuels (bio jet fuels; BJFs). The morphology of zeolites were designed for an enhanced diffusion of biomass pyrolysis vapors and upgraded products, in and out of the catalyst, to selectively produce monoaromatic HCs. A comprehensive comparison of the experimental and theoretical results obtained from biomass pyrolysis using the commercial catalyst of HBeta and the structure-modified catalysts of hierarchical HBeta and defect-free ZSM-5 was accomplished in in-situ and ex-situ catalytic configurations. Meanwhile, the catalytic performance of the ZSM-5-F catalyst in the conversion of a biomass pyrolysis oil model into jet fuel chemicals was investigated using a fixed bed catalytic reactor.

Graphical Abstract
Long-term solar radiation forecasting in India using EMD, EEMD, and advanced machine learning algorithms
Authors: RajasundrapandiyanLeebanon T. , Murugan N. S. Sakthivel , Kumaresan K. , Jeyabose Andrew 
Published: February 2025

Abstract
Solar radiation plays a critical role in the carbon sequestration processes of terrestrial ecosystems, making it a key factor in environmental sustainability among various renewable energy sources. This study integrates two advanced signal processing techniques—empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD)—with machine learning (ML) algorithms, including multilayer perceptron (MLP), random forest regression (RFR), support vector regression (SVR), and ridge regression, to forecast long-term solar radiation. Meteorological data spanning 13 years (2000–2012) from seven locations across India (Bhubaneswar, Chennai, Delhi, Hyderabad, Nagpur, Patna, and Trivandrum) were used for training and testing. The optimal model was identified based on performance metrics, including the highest linear correlation coefficient (R), and the lowest mean absolute error (MAE) and root mean square error (RMSE). The results indicate that EEMD integrated with ML algorithms consistently outperformed EMD-based approaches. Among the ML models evaluated, EEMD integrated with MLP achieved the best performance across all locations, with RMSE = 0.332, MAE = 0.26, and R
2 = 0.99. Furthermore, a comparative analysis with previous studies demonstrated that the proposed approach provides superior accuracy, underscoring its efficacy in solar radiation forecasting.
The effect of particle–substrate adsorption on the deposition of particles from a thin evaporating sessile droplet
Authors: D’Ambrosio Hannah-May , Wray Alexander W. , Wilson Stephen K. 
Published: February 2025

Abstract
A mathematical model for the evaporation of, the flow within, and the deposition from, a thin, pinned sessile droplet undergoing either spatially uniform or diffusion-limited evaporation is formulated and analysed. Specifically, we obtain explicit expressions for the concentration of particles within the bulk of the droplet, and describe the behaviour of the concentration of particles adsorbed onto the substrate as well as the evolution of the masses within the bulk of the droplet, adsorbed onto the substrate, and in the ring deposit that can form at the contact line. In particular, we show that the presence of particle–substrate adsorption suppresses the formation of a ring deposit at the contact line for spatially uniform, but not for diffusion-limited, evaporation. However, in both scenarios, the final adsorbed deposit is more concentrated near to the contact line of the droplet when radial advection due to evaporation dominates particle–substrate adsorption, but is more concentrated near to the centre of the droplet when particle–substrate adsorption dominates radial advection due to evaporation. In addition, in an appendix, we investigate the formation of a ring deposit at the contact line for a rather general form of the local evaporative flux, and show that the presence of particle–substrate adsorption suppresses the formation of the ring deposit that can otherwise occur when the local evaporative flux is non-singular at the contact line.
Why Study Spherical Convexity of Non-Homogeneous Quadratics and what Makes it Surprising?
Authors: Bolton Ryan , Németh Sándor Zoltán 
Published: February 2025

Abstract
This paper establishes necessary, sufficient, and equivalent conditions for the spherical convexity of non-homogeneous quadratic functions. By examining criteria for determining spherical convexity, we identified unique properties that differentiate spherically convex quadratic functions from their geodesically convex counterparts in both hyperbolic and Euclidean spaces. Since spherically convex functions over the entire sphere are constant, our analysis focuses on proper spherically convex subsets of the sphere. Our primary results concern non-homogeneous quadratic functions on the spherically convex set of unit vectors with positive coordinates. We also extend our findings to more general spherically convex sets. Additionally, the paper explores special cases of non-homogeneous quadratic functions where the defining matrix is of a specific type, such as positive, diagonal, or a Z-matrix. This study not only provides useful criteria for spherical convexity but also reveals surprising characteristics of spherically convex quadratic functions, contributing to a deeper understanding of convexity in spherical geometries.
Political Soundness. Hobbes’s and Burke’s Complementing Views on the State
Authors: Doomen Jasper 
Published: February 2025

Abstract
There are important differences between some of the fundamental ideas and presumptions in Hobbes’ and Burke’s political philosophy. Someone who studies both thinkers may on that account be prompted to conclude that they are incompatible. I maintain that this is not the case, arguing that their positions in fact complement each other. Hobbes appears to present, from an amoral (so a morally neutral) perspective, a universal model of the state, while Burke takes the relevant circumstances into consideration. Their views on the state are compatible since they address different stages of development of a state.
How is China shaping Africa? The role of Chinese development projects on land cover transformation
Authors: Pecora Nicoló , Spelta Alessandro , Pagnottoni Paolo , Kim Jong-Min 
Published: February 2025

Abstract
This paper investigates the impact of Chinese development projects on the change of land covering in the African continent over the years 2000-2017 by means of a new gridded dataset. The geo-referenced panel dataset matches information on Chinese development projects with satellite data on the evolution of land surface. The econometric analysis shows that Chinese development projects have played a significant role in the transformation of the African land covering, and that the Chinese intervention in Africa has had a significant impact on the transition of land covering from natural to artificial surfaces.
The impact of risk retention on the pricing of securitizations
Authors: Hibbeln Martin , Osterkamp Werner 
Published: February 2025

Abstract
Loan screening and monitoring are critical to loan performance, but incentives are diminished for securitized loans. Risk retention is intended to harmonize the interests of originators and investors; however, it is unclear to what extent investors anticipate and respond to originators’ screening and monitoring incentives, particularly with respect to different types of risk retention. The theoretical literature suggests that equity retention is optimal in terms of screening efforts; thus, if investors anticipate these incentives, equity retention should lead to low credit spreads. Employing OLS and instrumental variables regressions, we empirically examine the effect of retention on spreads. Our analysis, based on a unique dataset of securitizations, reveals that the effects highly depend on the considered investment type. Credit spreads decrease by approx. 26 to 39 bps if the originator retains a material fraction of at least 5% of the deal’s nominal value. For tranches with high information sensitivity—where screening and monitoring incentives are most critical—investors, though, impose an additional risk premium of 120 basis points when originators fail to retain a substantial portion of the securitizations. In addition, we find that transactions with vertical slice retention are associated with a notably higher risk premium than those with equity retention, demonstrating the differential impact of retention structures on investor perceptions. Overall, our results underline that the extent of asymmetric information, particularly with respect to different types of investments and risk retention, is an important component in the pricing of securitizations.
Rapid wall shear stress prediction for aortic aneurysms using deep learning: a fast alternative to CFD
Authors: Faisal Md. Ahasan Atick , Mutlu Onur , Mahmud Sakib , Tahir Anas , Chowdhury Muhammad E. H. , Bensaali Faycal , Alnabti Abdulrahman , Yavuz Mehmet Metin , El-Menyar Ayman , Al-Thani Hassan , Yalcin Huseyin Cagatay 
Published: February 2025

Abstract
Aortic aneurysms pose a significant risk of rupture. Previous research has shown that areas exposed to low wall shear stress (WSS) are more prone to rupture. Therefore, precise WSS determination on the aneurysm is crucial for rupture risk assessment. Computational fluid dynamics (CFD) is a powerful approach for WSS calculations, but they are computationally intensive, hindering time-sensitive clinical decision-making. In this study, we propose a deep learning (DL) surrogate, MultiViewUNet, to rapidly predict time-averaged WSS (TAWSS) distributions on abdominal aortic aneurysms (AAA). Our novel approach employs a domain transformation technique to translate complex aortic geometries into representations compatible with state-of-the-art neural networks. MultiViewUNet was trained on

$$\varvec{23}$$

23

real and

$$\varvec{230}$$

230

synthetic AAA geometries, demonstrating an average normalized mean absolute error (NMAE) of just

$$\varvec{0.362\%}$$

0.362
%

in WSS prediction. This framework has the potential to streamline hemodynamic analysis in AAA and other clinical scenarios where fast and accurate stress quantification is essential.

Graphical abstract
On bootstrapping, data overfitting and crocodiles: an additional comment to McPherron et al. (2022)
Authors: Domínguez-Rodrigo Manuel , Baquedano Enrique 
Published: February 2025

Abstract
Quaternary hominin-carnivore interactions is taphonomically reconstructed best through the use of bone surface modifications (BSM). This study examines redundancy in an experimental dataset of potentially similar BSM created by crocodile tooth-marking, sedimentary trampling and stone tool cut marking (Domínguez-Rodrigo and Baquedano in Sci Rep 8:5786, 2018). The original analysis of this experimental set, aiming to confidently classify the three types of BSM, was criticized by some authors (McPherron et al. in J Hum Evol 164:103071, 2022) insinuating that the analysis was flawed by a potential methodological overfitting caused by the improper use of bootstrap. A subsequent response to that critique (Abellán et al. in Geobios Memoire Special. 72–73, 12–21, 2022) showed that there was no difference in the results between using the raw data and the bootstrapped data. It was argued that structural co-variance and redundancy of the categorical dataset was responsible for the highly accurate models; however, this was never empirically demonstrated. Here, we show how the original experimental dataset is saturated with redundancy. Our analysis revealed that, out of 633 cases, only 116 were unique (18.3%) in the complete dataset, 45 unique cases (7.1%) in the intrinsic variable dataset, and just four unique cases (0.63%) in the three-variable dataset (accounting for most of the sample variance). Redundancy, therefore, ranged from 81.7% to over 99%. Machine learning analysis using Random Forest (RF) and C5.0 algorithms on the datasets demonstrated high accuracy with the raw data (90-98%). Proper bootstrapping yielded nearly identical accuracy (88-98%), while improper bootstrapping slightly reduced accuracy (86-98%) and introduced some degree of underfitting. This underscores that the potential biasing effects of bootstrapping differ between numerical and categorical datasets, especially on those with low dimensionality and low cardinality, in situations of feature interdependence and covariance. A complementary approach, consisting of an iterative data partitioning method through train-test resampling reproduced the results derived from the bootstrapped samples. The understanding of these methodological processes is essential to an adequate application of these experimental models to the fossil record.