bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing epigenetic aging clocks in cetaceans: accurate age estimations in small endangered delphinids, killer whales, pilot whales, belugas, humpbacks, and bowhead whales
Authors: Zoller Joseph A. , Lu Ake T. , Haghani Amin , Horvath Steve , Robeck Todd 
Published: February 2025

Abstract
This study presents refined epigenetic clocks for cetaceans, building on previous research that estimated ages in several species from bottlenose dolphins to bowhead and humpback whales using cytosine methylation levels. We combined publicly available data (generated on the HorvathMammalMethylChip40 platform) from skin (n = 805) and blood (n = 286) samples across 13 cetacean species, aged 0 to 139 years. By combining methylation data from different sources, we enhanced our sample size, thereby strengthening the statistical validity of our clocks. We used elastic net regression with leave one sample out (LOO) and leave one species out (LOSO) cross validation to produce highly accurate blood only (Median Absolute Error [MAE] = 1.64 years, r = 0.96), skin only (MAE = 2.32 years, r = 0.94) and blood and skin multi-tissue (MAE = 2.24 years, r = 0.94) clocks. In addition, the LOSO blood and skin (MAE = 5.6 years, repeated measures r = 0.83), skin only (MAE = 6.22 years, repeated measures r = 0.81), and blood only (MAE = 4.11 years, repeated measures r = 0.95) clock analysis demonstrated relatively high correlation toward cetacean species not included within this current data set and provide evidence for a broader application of this model. Our results introduce a multi-species, two-tissue clock for broader applicability across cetaceans, alongside single-tissue multi-species clocks for blood and skin, which allow for more detailed aging analysis depending on the availability of samples. In addition, we developed species-specific clocks for enhanced precision, resulting in four blood-specific clocks and eight skin-specific clocks for individual species; all improving upon existing accuracy estimates for previously published species-specific clocks. By pooling methylation data from various studies, we increased our sample size, significantly enhancing the statistical power for building accurate clocks. These new epigenetic age estimators for cetaceans provide more accurate tools for aiding in conservation efforts of endangered cetaceans.
An explainable deep learning model for diabetic foot ulcer classification using swin transformer and efficient multi-scale attention-driven network
Authors: Karthik R. , Ajay Armaano , Jhalani Anshika , Ballari Kruthik , K Suganthi 
Published: February 2025

Abstract
Diabetic Foot Ulcer (DFU) is a severe complication of diabetes mellitus, resulting in significant health and socio-economic challenges for the diagnosed individual. Severe cases of DFU can lead to lower limb amputation in diabetic patients, making their diagnosis a complex and costly process that poses challenges for medical professionals. Manual identification of DFU is particularly difficult due to their diverse visual characteristics, leading to multiple cases going undiagnosed. To address this challenge, Deep Learning (DL) methods offer an efficient and automated approach to facilitate timely treatment and improve patient outcomes. This research proposes a novel feature fusion-based model that incorporates two parallel tracks for efficient feature extraction. The first track utilizes the Swin transformer, which captures long-range dependencies by employing shifted windows and self-attention mechanisms. The second track involves the Efficient Multi-Scale Attention-Driven Network (EMADN), which leverages Light-weight Multi-scale Deformable Shuffle (LMDS) and Global Dilated Attention (GDA) blocks to extract local features efficiently. These blocks dynamically adjust kernel sizes and leverage attention modules, enabling effective feature extraction. To the best of our knowledge, this is the first work reporting the findings of a dual track architecture for DFU classification, leveraging Swin transformer and EMADN networks. The obtained feature maps from both the networks are concatenated and subjected to shuffle attention for feature refinement at a reduced computational cost. The proposed work also incorporates Grad-CAM-based Explainable Artificial Intelligence (XAI) to visualize and interpret the decision making of the network. The proposed model demonstrated better performance on the DFUC-2021 dataset, surpassing existing works and pre-trained CNN architectures with an accuracy of 78.79% and a macro F1-score of 80%.
3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology
Authors: Tian Isaac Y. , Liu Jason , Wong Michael C. , Kelly Nisa N. , Liu Yong E. , Garber Andrea K. , Heymsfield Steven B. , Curless Brian , Shepherd John A. 
Published: February 2025

Abstract
Body composition prediction from 3D optical imagery has previously been studied with linear algorithms. In this study, we present a novel application of deep 3D convolutional graph networks and nonlinear Gaussian process regression for human body shape parameterization and body composition estimation. We trained and tested linear and nonlinear models with ablation studies on a novel ensemble body shape dataset containing 4286 scans. Nonlinear GPR produced up to a 20% reduction in prediction error and up to a 30% increase in precision over linear regression for both sexes in 10 tested body composition variables. Deep shape features produced 6–8% reduction in prediction error over linear PCA features for males only, and a 4–14% reduction in precision error for both sexes. All coefficients of determination (R
2) for all predicted variables were above 0.86 and achieved lower estimation RMSEs than all previous work on 10 metrics of body composition.
Evaluation and practical application of prompt-driven ChatGPTs for EMR generation
Authors: Ding Hanlin , Xia Wenjie , Zhou Yujia , Wei Lei , Feng Yipeng , Wang Zi , Song Xuming , Li Rutao , Mao Qixing , Chen Bing , Wang Hui , Huang Xing , Zhu Bin , Jiang Dongyu , Sun Jingyu , Dong Gaochao , Jiang Feng 
Published: February 2025

Abstract
This study investigates the application of prompt engineering to optimize prompt-driven ChatGPT for generating electronic medical records (EMRs) during lung nodule screening. We assessed the performance of ChatGPT in generating EMRs from patient–provider verbal consultations and integrated this approach into practical tools, such as WeChat mini-programs, accessible to patients before hospital visits. The findings highlight ChatGPT’s potential to enhance workflow efficiency and improve diagnostic processes in clinical settings.
Prediction of thermal conductivity in CALF-20 with first-principles accuracy via machine learning interatomic potentials
Authors: Mandal Soham , Maiti Prabal K. 
Published: February 2025

Abstract
Understanding the thermal transport properties of CALF-20, a recent addition to the metal-organic framework family, is crucial for its effective utilization in greenhouse gas capture. Here, we report the thermal transport study of CALF-20 using artificial neural network-based machine learning potentials. We use the Green-Kubo approach based on equilibrium molecular dynamics, with a heat-flux renormalization technique, to determine the thermal conductivity (κ) of CALF-20. We predict that the anisotropic thermal transport in CALF-20, with κ below 1 Wm−1K−1 at 300 K, is ideal for thermoelectric applications. Our analysis reveals a weak temperature dependence (κ ~ 1/T
0.56) and near invariance with pressure in κ value of CALF-20, which stands out from the typical trend observed in crystalline materials. The outcome of the study, leveraging advanced computational techniques for predictive modeling, offers valuable insights into more suitable applications of CALF-20 with tailored thermal properties.
Strong and weak random walks on signed networks
Authors: Babul S. A. , Tian Y. , Lambiotte R. 
Published: February 2025

Abstract
Random walks are essential for analyzing complex networks. On signed networks, where edges can be positive or negative, designing random walks that capture signed community structure is challenging. Communities in signed networks typically have predominantly positive internal edges and negative external edges. While prior methods focus on strong balance (two communities), this scenario is rare in empirical networks. We introduce a random walk framework tailored to weak balance, accommodating networks with more than two communities. This approach generates a similarity matrix that enables effective community detection. Comparing strong and weak walks on synthetic and empirical networks, we demonstrate that weak walks outperform strong walks in scenarios involving more than two communities or asymmetric link densities. Our findings suggest that replacing strong walks with weak walks could enhance other signed network random-walk algorithms, broadening their applicability to more realistic network structures.
Real-time detection of organophosphorus pesticides in water using an unmanned boat-borne Raman spectrometer
Authors: Zhang Chen , Zhu Jiahui , Ye Wenqi , Liu Xiaohong , Zhuo Ruishuang , Wang Chi , Liu Hong , Zhang Wei 
Published: February 2025

An unmanned boat system with an integrated Raman spectrometer enables automated, real-time detection of OPs in complex water environments.
American social media users have ideological differences of opinion about the War in Ukraine
Authors: Nomikos William G. , Kim Dahjin , Lin Gechun 
Published: February 2025

Abstract
Though ideological differences have long been a ubiquitous feature of American politics, the rise of online news and social media has exacerbated divisions between groups. While existing research has documented how political preferences manifest online, relatively few studies have considered whether ideological divisions extend to discussions of foreign policy. We examine this question by analyzing nearly 2 million tweets about the war in Ukraine posted by Americans during the opening stages of the Russian invasion. We first categorize each tweet according to the user’s ideological leanings estimated by the network of political accounts they follow. Then, we apply a natural language processing model specifically designed for short texts to classify the tweets into clusters that we hand code into substantive topics. We find that the topic distributions of conservative, moderate, and liberal users are substantively and statistically different. We further find that conservatives are more likely to spread some form of misinformation and that liberals are more likely to express support for Ukraine. Our paper concludes with a discussion of the implications of our findings for the conduct of U.S. foreign policy.
Behavior of water at lipid/water interfaces upon phase transition of the lipid bilayer: Insights from 1D- and 2D-vibrational sum frequency generation spectral calculations from molecular dynamics simulations
Authors: Chandra Abhilash , Malik Ravi , Chandra Amalendu 
Published: February 2025

We have investigated the structural and dynamical changes of the interfacial water near [1,2-dimyristoyl-sn-glycero-3-phosphatidylcholine] (DMPC) lipid bilayer across various temperatures, ranging from 285 K (gel phase of lipid) to 320 K (liquid phase of lipid), through calculations of one-dimensional (1D) and two-dimensional (2D) vibrational sum frequency generation (VSFG) spectra from molecular dynamics simulations. The 1D-VSFG spectra show a broad positive peak in the hydrogen-bonded region, which means that water molecules are oriented upward toward the lipid bilayer. Although DMPC is a zwitterionic lipid, the negatively charged phosphate group primarily influences the orientation of the water molecules. The absence of a dangling peak in the 1D- and 2D-VSFG spectra shows that the water molecules form hydrogen bonds with the lipid headgroup atoms. The spectral diffusion timescales obtained from the 2D-VSFG metrics of the slope of the nodal line clearly reveal a dynamical crossover and exhibit Arrhenius behavior with different activation energies before and after the melting of the lipid bilayer. Apart from 2D-VSFG, the frequency fluctuation time correlation function also exhibits a dynamical crossover upon melting of the lipid bilayer.
Proximity sensors attached to ewes and rams at mating can predict date of lambing
Authors: Shorten P. R. , Peers-Adams J. , Johnson P. L. , O’Connor C. E. , Juengel J. L. 
Published: February 2025

Context Determining the birth date of lambs is important, as it is used in analysis for the generation of breeding values for lamb liveweight and lamb growth traits. Aims We used proximity sensors to measure the daily interactions between 300 ewes and three rams over the mating period for two successive trial years to test the hypothesis that lambing date can be predicted for a typical New Zealand commercial mating system. Methods The day that the ewe had the highest number interactions with the three rams was used to estimate the day of conception. Key results In both trial years, 89% of ewes had a proximity sensor-based predicted lambing date ±6 days of the measured lambing date. In the two trial years, 81% and 78% of ewes had a predicted lambing date ±3 days of the measured lambing date. This demonstrates that the performance of the proximity sensor-based method to predict the lambing date was consistent between years. Conclusions Proximity sensors, therefore, provide an indirect method to study mating behaviour that can be used to predict the birth date of lambs. Implications This tool can be used by breeders to improve the breeding values of sires for lamb growth and liveweight when lambs are not tagged at birth, and the management of ewes by grouping them together by gestational age.
CCQM-K155: elements and tributyltin in seawater
Authors: Fung Wai-hong , Can Süleyman Z , Tse Kelvin Chun-wai , Tsoi Yuk-tai , Lee Wan-waan , Arı Betül , Tunç Murat , Merrick Jeffrey , de Sena Rodrigo Caciano , Nadeau Kenny , Meija Juris , Yang Lu , Mester Zoltan , Riquelme Soraya Sandoval , Maldonado Javier Vera , Chao Jingbo , Wang Qian , Song Shanjun , Fisicaro Paola , Zhu Yanbei , Yim Yong-Hyeon , Lee Kyoung-Seok , Naujalis Evaldas , Strzelec Michał , Stakheev Aleksey , Krylov Anatoliy , Sobina Egor , Shin Richard , Dewi Fransiska , Peng Sim Lay , Wah Leung Ho , Yu Wesley , Jaćimović Radojko , Zuliani Tea , Haraldsson Conny , Taebunpakul Sutthinun 
Published: February 2025

Main text
Twenty National Metrology Institutes and Designated Institutes registered in the CCQM Key Comparison of CCQM-K155 "Elements and Tributyltin in Seawater" and nineteen institutes submitted their results. Participants were requested to evaluate the mass fractions, expressed in ng/g, of arsenic, cadmium, copper, lead, nickel, zinc and ng/kg level of tributyltin in seawater. Key Comparison Reference Values (KCRVs) are assigned to the various measurands by the NIST decision tree approach (NDT). Participants used analytical methods of their choice. Most participants employed dilution or co-precipitation for sample treatment and analyzed the samples using Isotope Dilution Mass Spectrometry (IDMS) or standard addition method with ICP-MS, applying various interference removing techniques for different elements. For tributyltin, most participants utilized derivatization followed by liquid-liquid extraction, with analysis conducted using isotope dilution GC-ICP-MS.
Successful participation in CCQM-K155 demonstrates measurement capabilities for determining mass fraction of transition elements (excluding mercury) and metalloids/semi-metals, with mass fractions ranging from 0.1 ng/g to 50 ng/g. Additionally, it covers small organo-tin and organo-mercury compounds with mass fractions from 1 ng/kg to 50 ng/g in a high-salt content matrix (seawater).
To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Attosecond electron dynamics in solid-state systems
Authors: Inzani G , Lucchini M 
Published: February 2025

Abstract
Attosecond science has revolutionized the study of ultrafast electron dynamics. Originally based on high-order harmonic generation from intense laser fields, it provided groundbreaking insights into physical processes occurring on the few- to sub-femtosecond time scales. From its initial focus on atomic and molecular systems, the field rapidly expanded to solid-state materials, uncovering phenomena with possible significant implications for information technology. This review focuses on some of the key experimental techniques that enable attosecond resolution in solid-state systems. We categorize them into four main groups: core-hole clock spectroscopy, photoemission, XUV-based all-optical techniques, and sub-cycle strong-field approaches. Together, these methods contributed to significant breakthroughs, such as elucidating the timing of photoemission from solids, possibly enabling the manipulation of the electro-optical properties of a crystal with light fields, and advancing our understanding of fundamental light–matter interactions. Their application to novel materials and the development of innovative, cutting-edge light sources and techniques, will define the future of attoscience in solids, setting the basis for profound advancements in both scientific understanding and technological innovation.
Commercial vehicle state estimation based on Interactive multi-model square root cubature Kalman filtering
Authors: He Shuilong , Ling Wenquan , Jia Bin , Mo Deyun , Tang Tao 
Published: February 2025

Abstract
Accurate and reliable vehicle state information is essential for ensuring vehicle safety and stability. While Interactive Multiple Model Square Root Cubature Kalman Filtering (IMM-SRCKF) has shown promise in state estimation, this work specifically addresses the unique challenges of achieving high-accuracy and real-time state estimation for commercial vehicles within complex driving scenarios. A nonlinear three-degree-of-freedom vehicle dynamic model, encompassing longitudinal, lateral, and yaw motions, was developed as a foundation. State space and observation equations were then derived. The IMM-SRCKF algorithm was strategically utilized and adapted to enhance the selection of process and measurement noise covariance matrices, effectively integrating multiple model strategies with the inherent advantages of square root Kalman filtering. This approach enables real-time dynamic adjustment of each sub-model’s weights. Co-simulation results using TruckSim and MATLAB/Simulink demonstrate that the proposed IMM-SRCKF method offers significant improvements over traditional techniques like the Extended Kalman Filter (EKF), Cubature Kalman Filter (CKF), and Square Root Cubature Kalman Filter (SRCKF), particularly in demanding double lane change and serpentining maneuvers. The notably lower Normalized Root Mean Square Error (NRMSE) values confirm the substantial enhancements in both accuracy and stability for commercial vehicle state estimation.
Futurism
Authors: Merjian Ara H 
Published: February 2025

Abstract
Futurism: A Very Short Introduction presents the ideas, works, key figures, and development of the Futurist movement in Italy and beyond. As one of Western Europe’s least industrialized countries, Italy appeared impervious to developments of modern technology like motorcars and radio as it radically transformed urban life in the twentieth century. Moreover, Futurism holds significance in the pioneering development of new media. The VSI provides an overview of a nuanced account revolving around the relationship between Futurism and Mussolini’s Fascist regime. It also discusses the influence of Futurism on the art world, politics, and culture, and its subsequent continuing legacy.
“Second” Futurism and the Fascist regime
Authors: Merjian Ara H 
Published: February 2025

Abstract
This chapter discusses the extent of “Second” Futurism and the Fascist regime, examining how the movement persisted even after the death of key figures during World War I. The Fascist regime’s elusiveness on aesthetic matters afforded a significant degree of leeway, which also increased exponentially the amount of work produced in service of the state, fomenting rivalry for attention and commissions. The constructive ethos of interwar Futurism spurred the creation of numerous innovative set designs along with interior spaces from cafés to dance halls to theaters. The chapter then notes how Futurism’s increasing defensiveness against conservative cultural factions mirrored wider polemics over what kind of architecture should represent the regime. It mentions that Filippo Tommaso Marinetti remained as the movement’s de facto leader.
Pluralizing Global Justice
Authors: Caney Simon 
Published: February 2025

Abstract
Research on global justice often focusses on a narrow range of thinkers, topics, and arguments, and tends to ignore the contributions from thinkers and traditions from many parts of the world. This chapter argues that this exclusionary approach is deeply mistaken. It defends what I term the ‘inclusion of voices’. This holds that the failure to engage with thinkers from all over the world is disrespectful and stands in the way of a deeper understanding of global justice. It further argues that including more voices is not enough and that what is required is what I term the ‘inclusive agenda’. The ‘agenda’ of global justice, the chapter argues, should be inclusive in the sense that the topics selected reflect the concerns of all humanity and the concepts employed and questions posed are sensitive to the many different ways in which topics might be framed and different questions asked.
Killing Three Birds with One Stone
Authors: Bai Tongdong 
Published: February 2025

Abstract
Among the multi-meanings of the Chinese philosophical conception of the unity of heaven and human, only the one inspired by the Lao Zi is related to environmentalism, but its ultimate solution is a dystopic state of small, isolated, and backward communities. Climate change also poses a ‘perfect storm’ to democratic institutions, domestically and globally. This chapter argues that Confucianism, despite being anthropocentric, can offer theoretic justifications for the protection of the environment. More importantly, Confucianism-inspired domestic institutions (hybrid regime) and global governance (‘New Tian Xia Order’) can offer institutional responses to climate challenges. Based on these Confucianism-inspired ideas, the chapter shows how a state can take care of its own interests while helping peoples from troubled states through controlled migration, and this solution can avoid the exacerbation of climate change due to population boom.
Precarity, Dependence, and Inequality
Authors: Kittay Eva Feder 
Published: February 2025

Abstract
A just society is founded on the equal moral worth of all its members. It not only fairly distributes its resources to those who produce its wealth but also enables the care for those who require it. An unjust society not only skews the distribution of resources to the powerful, it also neglects the needs of those who require care and exploits their caregivers. Such neglect both places members of each population in a precarious social and economic condition and creates significant inequalities between those dependent on or giving care, and those who fashion themselves as independent. This chapter is concerned with the inequalities experienced by portions of the population that require care because of a disability, as well as those who provide that care. This inequality and the precarious social and economic conditions that affect both populations threaten to put them in a condition of precarity.