bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gaze-Based Prediction of Students’ Math Difficulties - A Time Dynamic Machine Learning Approach to Enable Early Individual Assistance
Authors: Kennel Kathrin , Ishimaru Shoya , Küchemann Stefan , Steinert Steffen , Kuhn Jochen , Ruzika Stefan 
Published: January 2025

Abstract
Graphical differentiation substantially promotes the understanding of basic concepts of calculus. At the same time, such tasks are challenging for many students. To be able to support students in complex tasks during the solution process, it is important to recognise if students are having difficulties and, if so, to identify precisely what the difficulty is. However, previous research was only able to identify correct and incorrect solution processes but not the specific difficulties of students. In our study, the eye tracking data of 143 students reveal how students’ math tasks in context of graphically differentiation can be predicted. Retrospective-think-aloud (RTA) protocols were used to identify students’ difficulties and three machine learning algorithms, k-nearest neighbours (KNN), Random Forest and support vector machine (SVM), provide an accurate prediction for this multiclass problem. The prediction results improve with increasing processing time and achieve already good values long before the solution process of the tasks is completed. Our results show that certain student difficulties can be detected very early during the task solution process. Although this approach has been demonstrated for a sub-area of calculus, it is transferable to other fields of the STEM domain and therefore has much wider scope.
Self-Efficacy Perceptions of Tongan Students and Their Teachers within Year 11 Business Studies
Authors: Hausia Ella’peta Fifita , Matapo Jacoba , Gaffney Janet S. 
Published: January 2025

Abstract
A growing number of Pasifika students are pursuing Business Studies at Secondary school. However, indigenous knowledge and epistemologies are not prominent in Business Studies. We discuss a qualitative decolonising study that explores the concept of self-efficacy in Business Studies from a Tongan perspective. We provide insights into the perceptions of Tongan student’s self-efficacy and their Business Studies teachers. Teachers’ views aligned with Western notions of self-efficacy, which conflict with Tongan perceptions, precisely the collective nature of Tongan self-efficacy. Key findings from teacher interviews and Talanoa with students provided an understanding of Pasifika students in general and experiences specific to Tongan students. Three main themes are highlighted: (a) key values for Tongan students, such as relationships, family, and identity; (b) students’ learning experiences across different contexts; and (c) framings of self-efficacy. This study’s implications for curriculum suggest how teachers can learn from and incorporate Tongan students’ values and identities, enhancing their engagement and performance in Business Studies. Extending this research to include the knowledge and understanding of Tongan families, community leaders, curriculum specialists, Business Studies educators, and researchers would create a transformational space for student engagement. Bringing together shared expert knowledge in the future would require more time for effective and meaningful Talanoa as a collective.
Enhancing High-Speed Railway Timetable Resilience: A Two-Level Spatiotemporal Network Model Focused on Disturbance Absorption
Authors: Chen Zengxin , Chen Junhua , Zheng Han , Gao Tianze 
Published: January 2025

Abstract
Enhancing the resilience of train timetables can effectively improve their resistance and recovery capabilities against operational disturbances, thereby ensuring the stable operation of the railway system and the quality of passenger transportation services. This paper defined timetable resilience as three parts: disturbance absorptive capacity, resistance capacity, and post-disturbance recovery capacity. These capacities were quantitatively evaluated using the buffer time of trains, the number of train delays at departures and arrivals, and the duration of delay state. The evaluation metrics of the three resilience capacities and the total travel time of trains were used as the objective to establish a spatiotemporal network model. Utilizing actual operational data from the Beijing–Shanghai high-speed railway in China, the model was validated through a case study. Sensitivity analysis of the model's key parameters was conducted under two experimental scenarios: routine operational disturbances and speed restrictions on specific sections. Results showed that our model can effectively reduce the delay time and the number of delays in both the routine operational disturbance scenario and the 300 km/h speed restriction scenario with a frequent disturbance value of 2 min. Moreover, the model's performance with 3-min frequent disturbance outperformed that with 2-min frequent disturbance in speed restriction at 250 km/h and 200 km/h, yielding a 30% improvement.
A congestion prediction method based on trajectory mining algorithm
Authors: Dongjiang Liu , Leixiao Li , Jie Li 
Published: January 2025

Abstract
Nowadays, number of private cars is increasing rapidly. Traffic congestion becomes a serious problem in urban region. If traffic congestion can be predicted before it happens, it will be helpful for improving traffic condition. So many traffic congestion prediction methods have been proposed. Almost all these methods are based on traffic flow prediction algorithm. In these methods, historical traffic flow data is used while performing prediction. Obviously, information of sudden accidents like traffic accidents, road damage and bad weather that happened recently may be not contained in historical traffic flow data. But performance of traffic flow prediction algorithms will be affected by these factors. In this situation, performance of traffic congestion prediction method based on traffic flow prediction result will be affected as well. To solve the problem, a new traffic congestion prediction method based on trajectory mining algorithm is proposed in this paper. In this method, traffic controllers can set a threshold for each road according to the current situation of the road. The threshold represents the vehicle number that can be carried by the corresponding road in a short period. Besides, for each road, the proposed method tries to count the number of vehicles that will pass through the specific road at next time step by predicting next location for all the running vehicles based on their trajectories. If the vehicle number of a road surpasses the threshold of this road, it will be predicted as congested road. Otherwise, it will be predicted as non-congested road.
Copula-based reliability estimation of parallel-series system in the multicomponent stress–strength dependent model
Authors: Zhang Li , Yan Rongfang 
Published: January 2025

Abstract
Reliability analysis of stress–strength models usually assumes that the stress and strength variables are independent. However, in numerous real-world scenarios, stress and strength variables exhibit dependence. This paper investigates the reliability estimation in a multicomponent stress–strength model for parallel-series system assuming that the dependence between stress and strength is based on the Clayton copula. The estimators for the unknown parameters and system reliability are derived using the two-step maximum likelihood estimation and the maximum product spacing methods. Additionally, confidence intervals are constructed by utilizing asymptotically normal distribution theory and bootstrap method. Furthermore, Monte Carlo simulations are conducted to compare the effectiveness of the proposed inference methods. Finally, a real dataset is analyzed for illustrative purposes.
Metal-oxide phase transition of platinum nanocatalyst below fuel cell open-circuit voltage
Authors: Campos-Roldán Carlos A. , Gasmi Amir , Ennaji Meryem , Stodel Morgane , Martens Isaac , Filhol Jean-Sébastien , Blanchard Pierre-Yves , Cavaliere Sara , Jones Deborah , Drnec Jakub , Chattot Raphaël 
Published: January 2025

Abstract
The long-term stability of Pt-based catalysts is critical to the reliability of proton exchange membrane fuel cells (PEMFCs), and receives constant attention. However, the current knowledge of Pt oxidation is restricted to unrealistic PEMFC cathode environment or operation, which questions its practical relevance. Herein, Pt oxidation is investigated directly in a PEMFC with stroboscopic operando high energy X-ray scattering. The onset potential for phase transition of the nanoparticles surface from metallic to amorphous electrochemical oxide is observed far below previously reported values, and most importantly, below the open-circuit potential of PEMFC cathode. Such phase transition is shown to impact PEMFC performance and its role on Pt transient dissolution is verified by electrochemical on-line inductively coupled plasma mass spectrometry. By further demonstrating and resolving the limitations of currently employed accelerated stress test protocols in the light of metal-oxide phase transitions kinetics, this picture of Pt oxidation enables new mitigation strategies against PEMFC degradation.
Mechanism of sensor kinase CitA transmembrane signaling
Authors: Zhang Xizhou Cecily , Xue Kai , Salvi Michele , Schomburg Benjamin , Mehrens Jonas , Giller Karin , Stopp Marius , Weisenburger Siegfried , Böning Daniel , Sandoghdar Vahid , Unden Gottfried , Becker Stefan , Andreas Loren B. , Griesinger Christian 
Published: January 2025

Abstract
Membrane bound histidine kinases (HKs) are ubiquitous sensors of extracellular stimuli in bacteria. However, a uniform structural model is still missing for their transmembrane signaling mechanism. Here, we used solid-state NMR in conjunction with crystallography, solution NMR and distance measurements to investigate the transmembrane signaling mechanism of a paradigmatic citrate sensing membrane embedded HK, CitA. Citrate binding in the sensory extracytoplasmic PAS domain (PASp) causes the linker to transmembrane helix 2 (TM2) to adopt a helical conformation. This triggers a piston-like pulling of TM2 and a quaternary structure rearrangement in the cytosolic PAS domain (PASc). Crystal structures of PASc reveal both anti-parallel and parallel dimer conformations. An anti-parallel to parallel transition upon citrate binding agrees with interdimer distances measured in the lipid embedded protein using a site-specific 19F label in PASc. These data show how Angstrom scale structural changes in the sensor domain are transmitted across the membrane to be converted and amplified into a nm scale shift in the linker to the phosphorylation subdomain of the kinase.
Chemical tools to define and manipulate interferon-inducible Ubl protease USP18
Authors: Davis Griffin J. , Omole Anthony O. , Jung Yejin , Rut Wioletta , Holewinski Ronald , Suazo Kiall F. , Kim Hong-Rae , Yang Mo , Andresson Thorkell , Drag Marcin , Yoo Euna 
Published: January 2025

Abstract
Ubiquitin-specific protease 18 (USP18) is a multifunctional cysteine protease primarily responsible for deconjugating the interferon-inducible ubiquitin-like modifier ISG15 from protein substrates. Here, we report the design and synthesis of activity-based probes (ABPs) that incorporate unnatural amino acids into the C-terminal tail of ISG15, enabling the selective detection of USP18 activity over other ISG15 cross-reactive deubiquitinases (DUBs) such as USP5 and USP14. Combined with a ubiquitin-based DUB ABP, the USP18 ABP is employed in a chemoproteomics screening platform to identify and assess inhibitors of DUBs including USP18. We further demonstrate that USP18 ABPs can be utilized to profile differential activities of USP18 in lung cancer cell lines, providing a strategy that will help define the activity-related landscape of USP18 in different disease states and unravel important (de)ISGylation-dependent biological processes.
Linking Research Data with Physically Preserved Research Materials in Chemistry
Authors: Lin Chia-Lin , Huang Pei-Chi , Gräßle Simone , Grathwol Christoph , Tremouilhac Pierre , Vanderheiden Sylvia , Hodapp Patrick , Herres-Pawlis Sonja , Hoffmann Alexander , Fink Fabian , Manolikakes Georg , Opatz Till , Link Andreas , Marques M. Manuel B. , Daumann Lena J. , Tsotsalas Manuel , Biedermann Frank , Mutlu Hatice , Täuscher Eric , Bach Felix , Drees Tim , Neumann Steffen , Harivyasi Shashank S. , Jung Nicole , Bräse Stefan 
Published: January 2025

Abstract
Results of scientific work in chemistry can usually be obtained in the form of materials and data. A big step towards transparency and reproducibility of the scientific work can be gained if scientists publish their data in research data repositories in a FAIR manner. Nevertheless, in order to make chemistry a sustainable discipline, obtaining FAIR data is insufficient and a comprehensive concept that includes preservation of materials is needed. In order to offer a comprehensive infrastructure to find and access data and materials that were generated in chemistry projects, we combined the infrastructure Chemotion repository with an archive for chemical compounds. Samples play a key role in this concept: we describe how FAIR metadata of a virtual sample representation can be used to refer to a physically available sample in a materials’ archive and to link it with the FAIR research data gained using the said sample. We further describe the measures to make the physically available samples not only FAIR through their metadata but also findable, accessible and reusable.
Growth-rate distributions of gut microbiota time series
Authors: Brigatti E. , Azaele S. 
Published: January 2025

Abstract
Logarithmic growth-rates are fundamental observables for describing ecological systems and the characterization of their distributions with analytical techniques can greatly improve their comprehension. Here a neutral model based on a stochastic differential equation with demographic noise, which presents a closed form for these distributions, is used to describe the population dynamics of microbiota. Results show that this model can successfully reproduce the log-growth rate distribution of the considered abundance time-series. More significantly, it predicts its temporal dependence, by reproducing its kurtosis evolution when the time lag
$$\tau$$
is increased. Furthermore, its typical shape for large
$$\tau$$
is assessed, verifying that the distribution variance does not diverge with
$$\tau$$
. The simulated processes generated by the calibrated stochastic equation and the analysis of each time-series, taken one by one, provided additional support for our approach. Alternatively, we tried to describe our dataset by using a logistic neutral model with an environmental stochastic term. Analytical and numerical results show that this model is not suited for describing the leptokurtic log-growth rates distribution found in our data. These results support an effective neutral model with demographic stochasticity for describing the considered microbiota.
Three-dimensional structure of entire hydrated murine hearts at histological resolution
Authors: Frohn Jasper , Böddeker Frederik , Reichardt Marius , Bruns Hendrik , Czajka Titus , Khan Amara , Broche Ludovic , Krisch Michael , Bravin Alberto , Alves Frauke , Zschüntzsch Jana , Salditt Tim 
Published: January 2025

Abstract
Imaging the entire cardiomyocyte network in entire small animal hearts at single cell resolution is a formidable challenge. Optical microscopy provides sufficient contrast and resolution in 2d, however fails to deliver non-destructive 3d reconstructions with isotropic resolution. It requires several invasive preparation steps, which introduce structural artefacts, namely dehydration, physical slicing and staining, or for the case of light sheet microscopy also clearing of the tissue. Our goal is to provide 3d reconstructions of the cardiomyocyte network in entire hydrated murine hearts, and to develop a methodology for quantitative analysis of heart pathologies based on X-ray phase contrast computed tomography (XPCT). We have used XPCT at two beamlines of the extremely brilliant source (EBS) at the European Synchrotron Radiation Facility (ESRF) to scan wild-type murine hearts at high resolution, as well as a series of murine hearts of different pathological models, at reduced resolution and higher throughput. All hearts were obtained from the small animal facility of the university medical center in Göttingen. The hearts were fixed in formalin, stored and measured non-destructively in phosphate buffer solution. The high resolution dataset allows to discern individual cardiomyocytes in the tissue. All datasets have been analyzed using semi-automated image segmentation of the ventricles, rotation into a common coordinate system, classification into different anatomical compartments, and finally the structure tensor approach. A 3d streamline representation of the cardiomyocyte orientation vector field is provided. The different cardiovascular disease models are analysed based on metrics derived from the 3d structure tensor. An entire hydrated murine heart has been covered at an isotropic voxel size of 1.6

$$\upmu$$

μ

m (distributed over several volumes). A binned and fused dataset of this heart is available at 3.2

$$\upmu$$

μ

m, and has been analyzed by the structure tensor approach to yield the ventricular cardiomyocyte network or mesh, i.e. the aggregation of the cardiomyocyte chains in particular in the ventricular wall. Semi-automatic determination of structural metrics is already achieved and the corresponding tools and resulting data are made publically available. XPCT using extremely brilliant undulator radiation is close to achieve single cell reconstruction in an entire small animal organ.
A gamma-ray spectrometer based on MAPD-3NM-2 and LaBr3(ce) and LSO scintillators for hydrogen detection on planetary surfaces
Authors: Ahmadov F. , Sadigov A. , Bacherikov Yu. Yu. , Okhrimenko O. , Isayev K. , Holik M. , Slavicek T. , Mamedov F. , Ahmadov G. , Mammadli A. , Akbarov R. , Nagiyev J. , Berikov D. , Nuruyev S. , Sadygov Z. , Shitov Yu. , Lyubchyk S. I. , Lyubchyk S. B. 
Published: January 2025

Abstract
The presented work is dedicated to the detection of hydrogen, using detectors based on a MAPD (Micropixel Avalanche Photodiode) array based on new MAPD-3NM-2 type photodiodes and two different scintillators (LaBr3(Ce) and LSO(Ce)). The physical parameters of the MAPD photodiode used in the study and the intrinsic background of the scintillators were investigated. For the 2.223 MeV energy gamma-ray indicating the presence of hydrogen, the energy resolution was 6.89% with the MAPD array and LSO scintillator-based detector, and the number of events corresponding to this energy was 4817. With the MAPD array and LaBr3(Ce) scintillator, the energy resolution for the 2.223 MeV gamma-ray was 3.55%, and the number of events corresponding to this energy was 3868. The LSO scintillator-based detector allowed for the detection of 24.5% more 2.223 MeV energy gamma-rays compared to the LaBr3(Ce) scintillator. For the 2.223 MeV gamma-ray associated with hydrogen, the energy resolution with the LaBr3(Ce) scintillator was 48.5% better than with the LSO scintillator. The lower energy resolution compared to the LSO is due to the higher light output of LaBr3(Ce). The obtained results experimentally demonstrate that it is possible to obtain information about the presence of hydrogen in the target using both detectors.
Identification of a new fish trypanosome from the large yellow croaker (Larimichthys crocea) and description of its impact on host pathology, blood biochemical parameters and immune responses
Authors: Yang Xiaoao , Qi Pengzhi , Tao Zhen , Zhang Qingwei , Wang Yanjie , Zhu Denghui , Yan Xiaojun , Fu Peipei , Guo Baoying 
Published: January 2025

The aim of this study was to clarify the taxonomic identification of a hemoflagellate and assess the effect of trypanosome infection on Larimichthys crocea. Giemsa staining showed the presence of three morphotypes of trypomastigotes. The trypanosomes had the following morphological characteristics: a slender body with a long flagellum at the front; body size 12.30–30.90 × 1.13–2.33 μm; elongated oval nucleus situated in the median region; kinetoplast small, oval, located at the posterior end. The parasite had significant morphological differences from Trypanosoma epinepheli Su, Feng, Jiang, Guo, Liu & Xu, 2014 and Trypanosoma carassii (Mitrofanov) Doflein, 1901. The 18S rDNA sequences of the trypanosome from L. crocea had the highest homology (98.4%) with T. carassii. Phylogenetic analysis indicated that the parasite clustered with freshwater fish trypanosomes. Based on the differences in morphological characteristics and molecular data, it is considered a new species, Trypanosoma larimichthysi n. sp. Trypanosome infection had no effect on the growth of L. crocea, but significantly increased the concentration of blood urea nitrogen (BUN), and induced pathological changes in the gills, liver, spleen and kidney. The pro-inflammatory immune genes, including TNF-α, IFN-γ, IL-1β, CXCL8 and iNOS, were significantly upregulated in the L. crocea infected with trypanosomes. These results suggest that the trypanosome has negative impacts on host health.
Challenges and opportunities of vaccination during pregnancy: perspectives of 20 healthcare professionals
Authors: Razai Mohammad S. , Hargreaves Sally , Oakeshott Pippa 
Published: January 2025

Abstract
Vaccination during pregnancy is crucial due to increased maternal vulnerability to infectious diseases. However, uptake of recommended vaccines (influenza, pertussis, COVID-19) remains suboptimal, particularly among disadvantaged groups. This qualitative study explored healthcare professionals’ (HCPs) perspectives, selected purposively, on factors influencing maternal vaccination in London. Data from a workshop transcript and an online quality improvement survey involving 15 GPs, two midwives, two obstetricians and one pharmacist were thematically analysed. HCPs highlighted that pregnant women perceive the benefits of pertussis vaccination more positively than other vaccines. Clear, consistent communication and integrating vaccinations into routine antenatal care were identified as essential for improving accessibility and convenience. The critical role of midwives influencing vaccination decisions was emphasised. While recognising the potential of AI-based technologies to disseminate vaccine information, concerns were raised about trust, digital literacy and information quality, highlighting the need for tailored, reliable strategies to boost maternal vaccination rates and improve health outcomes.