bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimation of flint hills tallgrass prairie productivity and fuel loads: a model-based synthesis and extrapolation of experimental data
Authors: McKane Robert B. , Halama Jonathan J. , Barnhart Bradley L. , Brookes Allen F. , Djang Kevin S. , Chokshi Sonali , Pettus Paul P. , Groskinsky Brenda , Grier Gina , Hawkins Andy , Watson Douglas , Prentice Jayson , Blair John M. , Goodin Douglas G. , Johnson Loretta C. , Skibbe Adam M. , Stieglitz Marc , Pan Feifei , Abdelnour Alex 
Published: January 2025

Abstract

Context
The > 25,000 km2 Flint Hills ecoregion in eastern Kansas and northeastern Oklahoma, USA, is an economically and ecologically important area encompassing the largest remaining tallgrass prairie ecosystem in North America. Prescribed fires are used routinely to control invasive woody species and improve forage production for the beef-cattle industry. However, burning releases harmful pollutants that, at times, contribute to air quality problems for communities across a multi-state area.

Objectives
Establish a modeling framework for synthesizing long-term ecological data in support of Flint Hills tallgrass prairie management goals for identifying how much, where, and when rangeland burning can be conducted to maximize ecological and economic benefits while minimizing regional air quality impacts.

Methods
We used EPA’s VELMA ecohydrology model to synthesize long-term experimental data at the 35 km2 Konza Prairie Biological Station (KPBS) describing the effects of climate, fire, grazing, topography, and soil moisture and nutrient dynamics on tallgrass prairie productivity and fuel loads; and to spatially extrapolate that synthesis to estimate grassland productivity and fuel loads across the nearly 1000 times larger Flint Hills ecoregion to support prescribed burning smoke trajectory modeling using the State of Kansas implementation of the U.S. Forest Service BlueSky framework.

Results
VELMA provided a performance-tested synthesis of KPBS data from field observations and experiments, thereby establishing a tool for regionally simulating the combined effects of climate, fire, grazing, topography, soil moisture, and nutrients on tallgrass prairie productivity and fuel loads. VELMA’s extrapolation of that synthesis allowed difficult-to-quantify fuel loads to be mapped across the Flint Hills to support environmental decision making, such as forecasting when, where, and how prescribed burning will have the least impact on downwind population centers.

Conclusions
Our regional spatial and temporal extrapolation of VELMA’s KPBS data synthesis posits that the effects of integrated ecohydrological processes operate similarly across tallgrass prairie spatial scales. Based on multi-scale performance tests of the VELMA-BlueSky toolset, our multi-institution team is confident that it can assist stakeholders and decision makers in realistically exploring tallgrass prairie management options for balancing air quality, tallgrass prairie sustainability, and associated economic benefits for the Flint Hills ecoregion and downwind communities.
Residual Channel-attention (RCA) network for remote sensing image scene classification
Authors: Gomaa Ahmed , Saad Omar M. 
Published: January 2025

Abstract
High-resolution remote sensing (HRRS) image scene classification has gained increasing importance in recent years, with convolutional neural networks (CNNs) showing particular promise due to their proficiency in extracting spatial features. However, traditional CNNs face significant limitations. Specifically, they struggle to capture complex semantic relationships between objects at varying scales, and they lack the ability to effectively capture long-distance dependencies between features. This limitation is especially problematic in HRRS images, where spatial relationships and semantic content are deeply intertwined. Additionally, traditional CNNs are limited in handling substantial intra-class variation and inter-class similarity, which are common in remote sensing images. To overcome these challenges, we introduce a novel Residual Channel-attention (RCA) network for scene classification. The RCA network introduces a lightweight residual structure to better capture multi-scale spatial features and incorporates a channel attention mechanism that selectively emphasizes relevant feature channels while suppressing irrelevant ones. To further refine the focus on critical image features, we integrate a squeeze-and-excitation (SE) mechanism as a self-attention component, which helps the network prioritize the most informative features and ignore background noise. We evaluated the RCA network on three public datasets: RSSCN7, PatternNet, and EuroSAT, achieving classification accuracies of 97%, 99%, and 96%, respectively. The results demonstrate that superior of the RCA network compared to state-of-the-art strategies in remote sensing image classification. Furthermore, visualization using the Grad-CAM++ algorithm highlights the effectiveness of our channel attention mechanism and underscores the RCA network’s robust feature representation capabilities.
An implantable glucose enzymatic biofuel cell integrated with flexible gold-coated carbon foam and carbon thread bioelectrodes grafted inside a living rat
Authors: Vanmathi S. , Jayapiriya U. S. , Sharma Pravesh , Kulkarni Onkar Prakash , Goel Sanket 
Published: January 2025

Abstract
The advent of long-term implants has increased the urgent need for self-powered biomedical devices. Utilize enzymes to expedite the process of biofuel oxidation. These systems frequently make use of glucose oxidase. A possible solution involves glucose biofuel cells powered by the glucose found in physiological fluids. Biocompatible substances like carbon electrode designs help to transport electrons from the biological reactions to the external circuit as efficiently as possible while maximizing surface area. Despite advances in implantable electrodes, developing miniaturized and flexible electrodes remains challenging. In this work, a metal-coated flexible carbon thread and foam bioelectrode are fabricated and successfully implanted inside a living and freely moving rat. These electrodes are prepared using gold nanostructures as electron enhancers, a negatively charged conducting polymer, a biocompatible redox mediator, and enzymes as biocatalysts. The carbon foam-based enzymatic biofuel cell produces in vitro and in vivo settings, generates a power density of 165 µW/cm2 and 285 µW/cm2, and the carbon thread-based fuel cell produces a power density of 98 µW/cm2 and 180 µW/cm2 in vitro and in vivo environments, respectively. This work paves the way for the possible use of inexpensive electrodes for subdermal implantable microsystems.
AI governance: a systematic literature review
Authors: Batool Amna , Zowghi Didar , Bano Muneera 
Published: January 2025

Abstract
As artificial intelligence (AI) transforms a wide range of sectors and drives innovation, it also introduces different types of risks that should be identified, assessed, and mitigated. Various AI governance frameworks have been released recently by governments, organizations, and companies to mitigate risks associated with AI. However, it can be challenging for AI stakeholders to have a clear picture of the available AI governance frameworks, tools, or models and analyze the most suitable one for their AI system. To fill the gap, we present the literature to answer key questions: WHO is accountable for AI systems’ governance, WHAT elements are being governed, WHEN governance occurs within the AI development life cycle, and HOW it is implemented through frameworks, tools, policies, or models. Adopting the systematic literature review (SLR) methodology, this study meticulously searched, selected, and analyzed 28 articles, offering a foundation for understanding different facets of AI governance. The analysis is further enhanced by categorizing artifacts of AI governance under team-level governance, organization-level governance, industry-level governance, national-level governance, and international-level governance. The findings of this study on existing AI governance solutions can assist research communities in proposing comprehensive AI governance practices.
Exploring Hornstedtia scyphifera: an extensive multimethod phytochemical investigation reveals the chemical composition and bioactive potential
Authors: Kappen Jonas , David Andreea , Pieplow Klara , Wujtschik Annika , Ware Ismail , Dhar Dipendu , Wagner Christoph , Davari Mehdi D. , Franke Katrin , Wessjohann Ludger A. 
Published: January 2025

Abstract

Hornstedtia scyphifera (J.Koenig) Steud. represents a lesser-known member of the ginger family (Zingiberaceae) that is used in Malaysia as spice and traditional medicine. The phytochemical investigation of leaves from this species utilizing diverse analytical methods has provided comprehensive insights into its chemical profile for the first time. Headspace gas chromatography-mass spectrometry (HS-GCMS) and GCMS analyses of essential oil and nonpolar extracts verified α-pinene, camphene, p-cymene, and camphor as main volatile compounds. Metabolite profiling of the crude extract by ultra-high-performance-liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) unveiled terpenoids, flavonoids and other phenolics as major compound classes. Isolation and follow-up structure elucidation, involving 1D and 2D NMR, HRMS, UV and CD analysis, yielded two new sesquiterpenoids, (1R,5S,6S,7R,10R)-mustak-14-oic acid (1) and (1R,6S,7S,10R)-6-hydroxy-anhuienosol (2), along with 24 known compounds (seven terpenoids, seven flavonoids, ten phenolics), 21 of these never reported for H. scyphifera. Additionally, the crude extract and fractions from the purification process were screened for antibacterial and antifungal activity. This is supplemented by an extensive literature research for described bioactivities of all isolated compounds. Our results support and explain previously detected antimicrobial, antifungal and neuroprotective effects of H. scyphifera extracts and provide evidence for its potential pharmacological importance.
Horses are worthy of care: Horse sector participants’ attitudes towards animal sentience, welfare, and well-being
Authors: Fiedler Julie M , Ayre Margaret L , Rosanowski Sarah , Slater Josh D 
Published: January 2025

Abstract
Organisations for which sentient animals are central to the business model need to demonstrate the safeguarding of animal welfare and well-being. This requires providing positive experiences for animals which is critical to maintaining the social licence to operate. A cross-sectional survey captured the attitudes of experienced horse sector participants regarding sentience, welfare and well-being. Almost all respondents (99.9%; n = 676/677), believed horses were sentient. Analysis of open-ended responses identified two themes: (1) Sentience is a pathway to understanding the mental state, welfare and well-being of horses; and (2) A moral obligation for humans to consider sentience. Respondents’ observations that horses reacted to stimuli and responded to their surroundings underpinned their belief that horses were sentient. Theme one related to respondents’ understanding of sentience and how sentience informed their interpretations of horse behaviours and the making of inferences regarding the equine mental state. Theme two related to a moral obligation believed to exist towards horses because humans manage the horses’ environment and need to consider the impact of their interactions with horses. These obligations were perceived as responsibilities to consider sentience when determining good welfare and well-being in horse activity settings, when interacting with horses and when training and competing with horses. The results suggested a sophisticated understanding of sentience existed among experienced horse sector participants, who recognised the sentient horse as worthy of care. We propose that leveraging experienced participants’ existing knowledge of sentience could support the implementation of the Five Domains model when updating organisational policies.
The PANDEM-2 Simulation Exercise: Training the Coordinated Response to a Large-Scale Pandemic in 2 European Public Health Emergency Operations Centers
Authors: Houareau Claudia , Spieker Clara , Grote Ulrike , Perseke Knut , an der Heiden Maria , Caglar Robert , Wolter Amrei , Connolly Máire A. , Hayes Jessica S , Stein Mart , Kaluza Benjamin , Overmeyer Maike , Rexroth Ute 
Published: January 2025

Abstract

Objective
In the course of the EU funded Pandemic Preparedness and Response (PANDEM-2) project, a functional exercise (FX) was conducted to train the coordinated response to a large-scale pandemic event in Europe by using new IT solutions developed by the project. This report provides an overview of the steps involved in planning, conducting, and evaluating the FX.

Methods
The FX design was based on the European Centre for Disease Prevention and Control (ECDC) simulation exercise cycle for public health settings and was carried out over 2 days in the German and Dutch national public health institutes (PHI), with support from other consortium PHIs. The planning team devised an inject list based on a scenario script describing the emergence of an influenza pandemic from a novel H5N1 pathogen.

Results
The multi-disciplinary participant teams included 11 Dutch and 6 German participants. The FX was supported by 9 international project partners from 8 countries. Overall, participants and observers agreed that the FX goals were achieved.

Conclusions
The FX was a suitable format to test the PANDEM-2 solutions in 2 different country set-ups. It demonstrated the benefit of regular simulation exercises at member state level to test and practice public health emergency responses to be better prepared for real-life events.
When the days are(n’t) numbered: Calendar calculations in transparent and opaque systems
Authors: Zhuang Ziyi , Vanek Norbert 
Published: January 2025

Abstract
Calendar calculations, the process of computing the target day or month, exhibit peculiar differences across languages. In systems like English, calendar labels are largely opaque (Tuesday, August), which invites calculations to rely more heavily on verbal listing. In transparent systems, like Chinese, habitual labeling of calendar terms numerically (Tuesday = Day 2, August = Month 8) facilitates fast numerical operations instead of verbal listing. This study examines the effects that different levels of transparency of the calendar naming system may have on calculations in the speakers’ first and second language. Chinese–English bilinguals were tested alongside English and Chinese controls. Forced-choice calendar calculations (day, month, hour and year) and self-reported strategies were used as tasks to tap into participants’ calculation speed, accuracy and temporal reasoning. In the calculation questions, we manipulated Distance (short/long), Direction (forward/backward), Input (linguistic/numerical) and Boundary (within/across). More complex Month calculations significantly differed across groups while easier day calculations did not. The English group reported reliance on verbal listing while the Chinese and the Bilingual groups preferred numerical reasoning. These findings bring new evidence for linguistic relativity in the form of modulations of calendar processing speed changing as a function of linguistic transparency, input type and task demand.
The CRAFT coherent (CRACO) upgrade I: System description and results of the 110-ms radio transient pilot survey
Authors: Wang Z. , Bannister K. W. , Gupta V. , Deng X. , Pilawa M. , Tuthill J. , Bunton J. D. , Flynn C. , Glowacki M. , Jaini A. , Lee Y. W. J. , Lenc E. , Lucero J. , Paek A. , Radhakrishnan R. , Thyagarajan N. , Uttarkar P. , Wang Y. , Bhat N. D. R. , James C. W. , Moss V. A. , Murphy Tara , Reynolds J. E. , Shannon R. M. , Spitler L. G. , Tzioumis A. , Caleb M. , Deller A. T. , Gordon A. C. , Marnoch L. , Ryder S. D. , Simha S. , Anderson C. S. , Ball L. , Brodrick D. , Cooray F. R. , Gupta N. , Hayman D. B. , Ng A. , Pearce S. E. , Phillips C. , Voronkov M. A. , Westmeier T. 
Published: January 2025

Abstract
We present the first results from a new backend on the Australian Square Kilometre Array Pathfinder, the Commensal Realtime ASKAP Fast Transient COherent (CRACO) upgrade. CRACO records millisecond time resolution visibility data, and searches for dispersed fast transient signals including fast radio bursts (FRB), pulsars, and ultra-long period objects (ULPO). With the visibility data, CRACO can localise the transient events to arcsecond-level precision after the detection. Here, we describe the CRACO system and report the result from a sky survey carried out by CRACO at 110-ms resolution during its commissioning phase. During the survey, CRACO detected two FRBs (including one discovered solely with CRACO, FRB 20231027A), reported more precise localisations for four pulsars, discovered two new RRATs, and detected one known ULPO, GPM J1839

$-$

10, through its sub-pulse structure. We present a sensitivity calibration of CRACO, finding that it achieves the expected sensitivity of 11.6 Jy ms to bursts of 110 ms duration or less. CRACO is currently running at a 13.8 ms time resolution and aims at a 1.7 ms time resolution before the end of 2024. The planned CRACO has an expected sensitivity of 1.5 Jy ms to bursts of 1.7 ms duration or less and can detect

$10\times$

more FRBs than the current CRAFT incoherent sum system (i.e. 0.5

$-$

2 localised FRBs per day), enabling us to better constrain the models for FRBs and use them as cosmological probes.
How to train your stochastic parrot: large language models for political texts
Authors: Ornstein Joseph T. , Blasingame Elise N. , Truscott Jake S. 
Published: January 2025

Abstract
We demonstrate how few-shot prompts to large language models (LLMs) can be effectively applied to a wide range of text-as-data tasks in political science—including sentiment analysis, document scaling, and topic modeling. In a series of pre-registered analyses, this approach outperforms conventional supervised learning methods without the need for extensive data pre-processing or large sets of labeled training data. Performance is comparable to expert and crowd-coding methods at a fraction of the cost. We propose a set of best practices for adapting these models to social science measurement tasks, and develop an open-source software package for researchers.
Human Trafficking, Beautiful Women, the Land of the Cockaigne, and Burmese Bells: The Significance of the Sexual Reminiscences of the Florentine Merchant Francesco Carletti (1573–1636) in Ragionamenti del mio viaggio intorno al mondo [Chronicles of My Voyage Around the World]
Authors: Zurndorfer Harriet 
Published: January 2025

Abstract
Ragionamenti del mio viaggio intorno al mondo [Chronicles of my voyage around the world] by Francesco Carletti (1573–1636), a Florentine slave merchant and the first private individual to circumnavigate the globe, is a rich source of information about human trafficking from Africa to Spanish America. Carletti writes in detail about his encounters beginning in 1594 in Africa, America, and Asia, including the Philippines, Japan, Macao, Malacca, and Goa, before returning to Europe via the Cape of Good Hope in 1602. But what makes Carletti's record extraordinary are his reports about the sexuality of the peoples he observes in these locations. Following the publications of earlier Italian travel writers Niccolò dei Conti (1395–1469) and Antonio Pigafetta (1491–1531) about the practice of Asian men purposely piercing their genitalia to insert studs and other objects to gratify their female sexual partners, Carletti investigates this phenomenon, concludes its verity, and attributes its existence to the dominance of women's agency in Asia. Carletti's recollections of his voyage are testimony to how exploration during the early modern era catalyzed a transformation in racial discourses and the appreciation of erotic desire in foreign cultures.
Late positive potentials elicited by negative self-referential processing predict increases in social anxiety, but not depressive, symptoms from age 11 to age 12
Authors: Liu Pan , Tan Jaron X.Y. 
Published: January 2025

Abstract
Social anxiety and depression exacerbate in early adolescence. Maladaptive self-referential processing confers risk for both conditions and can be assessed by the Self-Referent Encoding Task (SRET). Our cross-sectional findings indicated that the SRET-elicited anterior late positive potential (LPP) was uniquely associated with social anxiety symptoms, whereas behavioral SRET scores were uniquely associated with depressive symptoms. Expanding this work, this study investigated whether the SRET-generated behavioral and LPP indices differentially predicted changes of social anxiety or depressive symptoms over time. At baseline, 115 community-dwelling youths (66 girls; Mean age/SD = 11.00/1.16 years) completed an SRET with EEG. Youths reported social anxiety and depressive symptoms at baseline and ∼six and ∼ 12 months later, based on which the intercept and slope of symptoms were estimated as a function of time. A larger anterior LPP in the negative SRET condition uniquely predicted a larger slope (faster increase) of social anxiety (but not depressive) symptoms. Greater positive behavioral SRET scores marginally predicted a smaller slope (slower increase) of depressive (but not social anxiety) symptoms. We provided novel evidence concerning the differential, prospective associations between self-referential processing and changes of social anxiety and depressive symptoms in early adolescence.
Submesoscale Eddy Contribution to Ocean Vertical Heat Flux Diagnosed From Airborne Observations
Authors: Torres Hector S. , Wineteer Alexander , Rodriguez Ernesto , Klein Patrice , Thompson Andrew F. , Perkovic‐Martin Dragana , Molemaker Jeroen , Hypolite Delphine , Callies Jöern , Farrar J. Thomas , D’Asaro Eric , Freilich Mara A. 
Published: January 2025

AbstractSubmesoscale eddies (those smaller than 50 km) are ubiquitous throughout the ocean, as revealed by satellite infrared images. Diagnosing their impact on ocean energetics from observations remains a challenge. This study analyzes a turbulent field of submesoscale eddies using airborne observations of surface currents and sea surface temperature, with high spatial resolution, collected during the S‐MODE experiment in October 2022. Assuming surface current divergence and temperature are homogeneous down to 30 m depth, we show that more than 80% of the upward vertical heat fluxes, reaching 227 W , is explained by the smallest resolved eddies, with a size smaller than 15 km. This result emphasizes the contribution of small‐scale eddies, poorly represented in numerical models, to the ocean heat budget and, therefore, to the climate system.
Impact of Sudden Stratospheric Warmings on the Stratosphere‐To‐Troposphere Transport of Ozone
Authors: Lee Jaewon , Butler Amy H. , Albers John R. , Wu Yutian , Lee Simon H. 
Published: January 2025

AbstractSudden stratospheric warmings (SSWs) can significantly impact tropospheric weather systems. Previous studies suggest that SSWs may also influence stratosphere‐to‐troposphere transport (STT), but their spatial and temporal distribution and mechanisms are not fully understood. The complex relationships between SSWs and the El Niño‐Southern Oscillation (ENSO) have also made it difficult to isolate the effects of SSWs on STT. From an idealized ENSO simulation with the WACCM4 model using a stratospheric origin ozone tracer, we investigate the effect of SSWs on the STT of ozone under different ENSO phases. We find a significant increase in lower tropospheric ozone from the SSW onset up to 3 months later over the Arctic, North America, and Europe, regardless of the ENSO phase. This study highlights the significant influence of SSWs on STT on a subseasonal scale. Our results also emphasize the need to consider SSWs when addressing the ENSO impact on STT.