bluuebunny/crossref_metadata_2025_split huggingface dataset:
New Insights Into Active Tectonics and Landscape Evolution of the Northernmost Chilean Central Depression
Authors: Vega‐Ruiz A. , Victor P. , Reicherter K. , Binnie A. , Evenstar L. , González G. , Binnie S. A. 
Published: December 2024

AbstractActive deformation and landscape evolution in North Chilean forearc involve multiscale tectonic processes, such as crustal thickening causing orogenic‐scale uplift and faulting modulating the mountain‐front landscape. In the Central Depression, faults redirecting Quaternary drainages are poorly understood due to their subtle surface expressions and limited structural data acquisition. To address this, we combined remote‐sensing analysis of high‐resolution DEMs, satellite and UAV imagery, new geomorphic mapping, structural data, and morphometric analysis with available surface age dating to identify and give temporal constraints on previously unmapped faults impacting drainages across this region. Our findings reveal the reactivation of east‐vergent NNW‐SSE reverse to transpressive and NW‐SE strike‐slip faults over approximately 100 km of latitude. Faults movement can be summarized into two main stages (a) A Late Miocene‐Pliocene stage, dominated by east‐vergent reverse faults inverting the Andean piedmont in the northern study area. (b) A Pliocene‐Quaternary stage, characterized by transpressive activity of these east‐vergent faults extending southward, alongside structures of the West Vergent Thrust System. The tectonic evolution of the east‐vergent structures relates to the ongoing deformation of the coastal forearc, encroaching into the Central Depression. Minimum vertical and strike‐slip displacement rates since the Quaternary are 12 m/Ma and 90 m/Ma, respectively, with the potential for higher rates depending on the onset of displacement. Drainage pattern modification, driven by incremental vertical displacement rates, provides insights to qualitatively evaluate individual fault activity rates. Numerous recently detected structures represent previously unknown sources of seismic hazard, requiring further dating of geomorphic markers and high‐resolution monitoring.
Structural and functional determination of peptide versus small molecule ligand binding at the apelin receptor
Authors: Williams Thomas L. , Verdon Grégory , Kuc Rhoda E. , Currinn Heather , Bender Brian , Solcan Nicolae , Schlenker Oliver , Macrae Robyn G. C. , Brown Jason , Schütz Marco , Zhukov Andrei , Sinha Sanjay , de Graaf Chris , Gräf Stefan , Maguire Janet J. , Brown Alastair J. H. , Davenport Anthony P. 
Published: December 2024

AbstractWe describe a structural and functional study of the G protein-coupled apelin receptor, which binds two endogenous peptide ligands, apelin and Elabela/Toddler (ELA), to regulate cardiovascular development and function. Characterisation of naturally occurring apelin receptor variants from the UK Genomics England 100,000 Genomes Project, and AlphaFold2 modelling, identifies T892.64 as important in the ELA binding site, and R1684.64 as forming extensive interactions with the C-termini of both peptides. Base editing to introduce an R/H1684.64 variant into human stem cell-derived cardiomyocytes demonstrates that this residue is critical for receptor binding and function. Additionally, we present an apelin receptor crystal structure bound to the G protein-biased, small molecule agonist, CMF-019, which reveals a deeper binding mode versus the endogenous peptides at lipophilic pockets between transmembrane helices associated with GPCR activation. Overall, the data provide proof-of-principle for using genetic variation to identify key sites regulating receptor-ligand engagement.
Principal component analysis of the Serological response to Plasmodium Falciparum using a Multiplex bead-based assay in Nigeria
Authors: Schultz Jonathan S. , Okoli Mary , Lee Scott , Leonard Colleen M. , Sayre Dean , Heilig Charles M. , Uhomoibhi Perpetua , Ogunniyi Abiodun , Ndodo Nnaemeka , Mba Nwando , Abubakar Ado G. , Akinmulero Oluwaseun , Dawurung Ayuba B. , Okoye McPaul , Iriemenam Nnaemeka C. , Plucinski Mateusz , Steinhardt Laura , Rogier Eric , Ihekweazu Chickwe 
Published: December 2024

AbstractCharacterization of serological responses to Plasmodium falciparum (Pf) is of interest to understand disease burden and transmission dynamics; however, their interpretation is challenging. Dried blood spots from 30,815 participants aged 6 months to 15 years from the 2018 Nigeria HIV/AIDS Indicator and Impact Survey were analyzed by multiplex bead-based assay to measure immunoglobulin G (IgG) to Pf-stage-specific MSP-1, AMA-1, GLURPR0, LSA-1, and CSP. These IgG levels were analyzed by principal component analysis (PCA). PC1 and PC2 scores explained 41% and 17% of the total variance, respectively. PC1 unit vectors represented seropositivity. PC2 unit vectors for blood-stage antigens were in opposite directions to liver-stage and sporozoite antigens. PC2 scores were correlated with MSP-1 positively (R = 0.52, P < 0.001) and CSP negatively (R=-0.65, P < 0.001) and may help identify areas with prior exposure but higher risk for increased infections or epidemics. PCA of Pf serology can provide summary scores to possibly inform future programmatic interventions.
Identification of Anoikis-related potential biomarkers and therapeutic drugs in chronic thromboembolic pulmonary hypertension via bioinformatics analysis and in vitro experiment
Authors: Yu Haijia , Song Huihui , Li Jingchao , Cui Luqian , Dong Shujuan , Chu Yingjie , Qin Lijie 
Published: December 2024

AbstractThere is growing evidence that programmed cell death plays a significant role in the pathogenesis of chronic thromboembolic pulmonary hypertension (CTEPH). Anoikis is a newly discovered type of programmed death and has garnered great attention. However, the precise involvement of Anoikis in the progression of CTEPH remains poorly understood. The goal of this study was to identify Anoikis-related genes (ARGs) and explore potential therapeutic drugs for CTEPH. Differentially expressed genes were identified by limma and weighted gene co-expression network analysis (WGCNA) packages, and functional analyses were conducted based on the differentially expressed genes. Subsequently, a combination of protein–protein interaction (PPI), Least Absolute Shrinkage and Selection Operator (LASSO), and Support Vector Machine Recursive Feature Elimination (SVM-RFE) methodologies was employed to screen hub genes associated with CTEPH, which were further verified by dataset GSE188938, quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot. CIBERSORT was utilized to evaluate the infiltration of immune cells and the relationship between infiltration-related immune cells and ARGs. Finally, targeted drug analysis and molecular docking were used to predict drugs targeting Anoikis process to treat CTEPH. Thirty-two differentially expressed genes related to Anoikis and CTEPH were screened through WGCNA analysis. Then, the key ARGs FASN, PLAUR, BCL2L1, HMOX1 and RHOB were screened by PPI, Lasso and SVM-RFE machine learning. Validation through dataset GSE188938, qRT-PCR, and Western blot analyses confirmed HMOX1 and PLAUR as powerful and promising biomarkers in CTEPH. In addition, CIBERSORT immunoinfiltration revealed that Mast_cells_activated and Neutrophils were involved in the pathological regulation of CTEPH. Correlation analysis indicated that HMOX1 was positively correlated with Neutrophils, while PLAUR was negatively correlated with Mast_cells_activated. Finally we used targeted drug analysis and molecular docking to identify that STANNSOPORFIN as a potential drug targeting HMOX1 for the treatment of CTEPH. HMOX1 and PLAUR emerge as potential biomarkers for CTEPH and may influence the development of CTEPH by regulating Anoikis. Mast_cells_activated and Neutrophils may be involved in Anoikis resistance in CTEPH patients, presenting novel insights into CTEPH therapeutic targets. STANNSOPORFIN is a potential agents targeting Anoikis process therapy for CTEPH.
Uncovering the impact of outliers on clusters’ evolution in temporal data-sets: an empirical analysis
Authors: Atif Muhammad , Farooq Muhammad , Shafiq Muhammad , Alballa Tmader , Abdualziz Alhabeeb Somayah , Abd El-Wahed Khalifa Hamide 
Published: December 2024

AbstractThis study investigates the impact of outliers on the evolution of clusters in temporal data-sets. Monitoring and tracing cluster transitions of temporal data sets allow us to observe how clusters evolve and change over time. By tracking the movement of data points between clusters, we can gain insights into the underlying patterns, trends, and dynamics of the data. This understanding is essential for making informed decisions and drawing meaningful conclusions from the clustering results. Cluster evolution refers to the changes that occur in the clustering results over time due to the arrival of new data points. The changes in cluster solutions are classified as external and internal transitions. The study employs the survival ratio and history cost function to investigate the effects of outliers on changes experienced by the clusters at successive time points. The results demonstrate that outliers have a significant impact on cluster evolution, and appropriate outlier handling techniques are necessary to obtain reliable clustering results. The findings of this study provide useful insights for practitioners and researchers in the field of stream clustering and can help guide the development of more robust and accurate stream clustering algorithms.
Physics-regularized neural networks for predictive modeling of silicon carbide swelling with limited experimental data
Authors: Kobayashi Kazuma , Alam Syed Bahauddin 
Published: December 2024

AbstractThis study introduces a physics-regularized neural network (PRNN) as a computational approach to predict silicon carbide’s (SiC) swelling under irradiation, particularly at high temperatures. The PRNN model combines physics-based regularization with neural network methodologies to generalize the behavior of SiC, even in conditions beyond the traditional empirical model’s valid range. This approach ensures continuity and accuracy in SiC behavior predictions in extreme environments. A key aspect of this research is using nested cross-validation to ensure robustness and generalizability. The PRNN model effectively bridges empirical and sparse experimental data by integrating prior knowledge and refined tuning procedures. It demonstrates its SiC’s predictive power in high-irradiation conditions essential for nuclear and aerospace applications.
A cross-sectional study of physical activity and chronic diseases among middle-aged and elderly in China
Authors: Huang Yongyu , Lu Zuosheng 
Published: December 2024

AbstractRegular physical activity is beneficial for both physical and mental health. However, studies on physical activity levels among middle-aged and elderly individuals in China are relatively scarce, and the association between different activity levels and certain chronic diseases remains unclear. Using cross-sectional data from the 2020 China Health and Retirement Longitudinal Study (CHARLS), this study describes the prevalence of chronic diseases and examines their associations with physical activity (PA). Participants self-reported the presence of fifteen chronic health conditions: hypertension, dyslipidemia, diabetes, cancer, chronic lung diseases, liver disease, heart attack, stroke, kidney disease, stomach diseases, emotional and mental issues, memory-related diseases, Parkinson’s disease, arthritis or rheumatism, and asthma. Total physical activity was assessed through self-reports using instruments similar to the International Physical Activity Questionnaire (IPAQ). Multivariate logistic regression was used to estimate the association between chronic diseases and PA. In China, more than one-sixth of middle-aged and elderly individuals do not meet physical activity guidelines. Compared to those with low PA, individuals with moderate PA were associated with a lower prevalence of four chronic diseases (heart disease, stroke, emotional and mental issues, asthma), while those with high PA were associated with a lower prevalence of nine chronic diseases (hypertension, dyslipidemia, diabetes, cancer, heart attack, stroke, emotional and mental issues, memory-related diseases, asthma). Higher physical activity levels are associated with lower odds of chronic diseases. These associations between physical activity and various chronic diseases are inconsistent. Future research should employ cohort or experimental studies to determine the causal relationships between physical activity and the prevalence of different chronic diseases.
A novel fuzzy approach for winding paper insulation health monitoring of oil‐immersed power transformer using non‐destructive failure parameters
Authors: Nezami Md. Manzar , Hashem Hythem , Equbal Md. Danish , Khan Shakeb A. , Malik Hasmat , García Márquez Fausto Pedro , Afthanorhan Asyraf , Hossaini Mohammad Asef 
Published: December 2024

AbstractPower transformers, a significant and critical component of power system, require regular condition monitoring by the utilities for uninterrupted power supply. The kraft paper made of cellulose is used as the solid insulation of the transformer which undergoes thermal, electrical and environmental stresses causing its progressive ageing. It thereby reduces the physical strength of the paper and ultimately affects the transformer's remaining useful life (RUL). The current state (physical) of the cellulosic (solid) insulating paper is predicted in this article using the fuzzy inference system (FIS) based RUL assessment technique. Three non‐destructive parameters, that is, 2‐Furfuraldehyde (2‐FAL), Carbon Monoxide (CO) and Carbon dioxide (CO2) are used to determine the value of the Degree of Polymerisation (i.e. DP) which directly reflects the current physical state of the insulating material. Four states (Healthy, Poor, Very Poor, and Worst) of the insulating paper are identified based on the values of DP. Five FIS models have been developed separately with different membership functions and a number of fuzzy if‐then rules are formulated to estimate the value of DP. Every model is tested with 30 test samples to validate the system accuracy. The physical condition of the insulation estimated using FIS built with trapezoidal membership function has been found to be considerably precise with an average absolute deviation of 0.33%. Hence, a comprehensive assessment of transformer's health is carried out with the prominent non‐destructive parameters.
Rovibrationally resolved Rayleigh and Raman scattering cross sections for molecular hydrogen
Authors: Singor Adam J. C. , Scarlett Liam H. , Zammit Mark C. , Bray Igor , Fursa Dmitry V. 
Published: December 2024

Accurate Rayleigh and Raman scattering cross sections, tensor components, depolarization ratios, and reversal coefficients for all rovibrational transitions within the X1Σg+ ground electronic state of H2 have been calculated. Raman spectra have been generated using these data. A method for calculating Raman scattering cross sections is formulated that is valid below the ionization threshold and in the region containing resonances, which explicitly accounts for all bound and dissociative vibrational levels of the bound intermediate electronic states and approximately accounts for the ionization continuum. A representative set of cross sections is presented for incident photon energies below 15 eV and compared with existing results in the literature where possible. Convergence of our results with an increasing number of bound intermediate electronic states is demonstrated. The accuracy of the Placzek–Teller approximation is discussed. The effect of accounting for the intermediate ionization continuum is investigated. Local thermal equilibrium cross sections are calculated for Rayleigh and Raman scattering. This work represents the most accurate and complete treatment of Raman scattering for molecular hydrogen to date. A total of 9582 Rayleigh and Raman scattering cross sections have been generated and are openly available on Zenodo under an open-source Creative Commons Attribution license at https://zenodo.org/doi/10.5281/zenodo.13441471.
Superconductor to exciton condensate transition in a model copper-oxide material
Authors: Schouten Anna O , Sager-Smith LeeAnn M , Mazziotti David A 
Published: December 2024

Abstract
Superconductivity and exciton condensation are fundamental phenomena in condensed matter physics, associated with the condensation of electron–electron and electron–hole pairs, respectively, into coherent quantum states. In this study, we present evidence of a superconductor to exciton condensate transition within the context of the three-band Hubbard model of copper-oxide-like materials. As the electron–electron repulsion increases, the superconducting phase is superseded by exciton condensation. In support of theoretical predictions—not yet realized experimentally—we observe the coexistence of the two condensates in the vicinity of the transition where the quantum states become a superposition of electron–electron and electron–hole condensates. Coexistence is rigorously computed from large eigenvalues and their eigenvectors in both the two-electron reduced density matrix (2-RDM) and the particle-hole RDM, which we obtain from a direct variational ground-state energy minimization with respect to the 2-RDM by semidefinite programming. We further discern that adjacent d orbitals and intervening p orbitals facilitate electron–electron pairing between copper orbitals, thereby supporting the superexchange mechanism for superconductivity. These observations suggest the feasibility of witnessing a superconductor to exciton condensate transition in copper-oxide analogs, bearing significant implications for identifying materials conducive to efficient transport processes.
Existence and Stability of Implicit Fractional Differential Equations Involving the p-Laplacian Operator and Their Applications
Authors: Khan Rahman Ullah Ullah , Samreen Maria , Ali Gohar , Popa Ioan-Lucian 
Published: December 2024

Abstract
The main objective of this paper is to establish the existence, uniqueness, and stability of implicit fractional differential equations involving a p-Laplacian operator, utilizing the Caputo-Katugampola fractional derivative. A novel approach is employed to examine the existence and uniqueness of solutions to the problem through fixed-point theorems. These results are original and extend several existing findings in the literature. Finally, an application is provided to illustrate the theoretical results.
Leveraging Movement Representation from Contrastive Learning for Asteroid Detection
Authors: Kongsathitporn Noppachanin , Supratak Akara , Noysena Kanthanakorn , Awiphan Supachai , Steeghs Danny , Pollacco Don , Ulaczyk Krzysztof , Lyman Joseph , Ackley Kendall , O’Neill David , Kumar Amit , Galloway Duncan K. , Jiménez-Ibarra Felipe , Dhillon Vik. S. , Dyer Martin J. , O’Brien Paul , Ramsay Gavin , Pallé Enric , Kotak Rubin , Killestein Thomas L. , Nuttall Laura K. , Breton Rene P. 
Published: December 2024

Abstract
To support asteroid-related studies, current motion detectors are utilized to select moving object candidates based on their visualizations and movements in sequences of sky exposures. However, the existing detectors encounter the manual parameter settings which require experts to assign proper parameters. Moreover, although the deep learning approach could automate the detection process, these approaches still require synthetic images and hand-engineered features to improve their performance. In this work, we propose an end-to-end deep learning model consisting of two branches. The first branch is trained with contrastive learning to extract a contrastive feature from sequences of sky exposures. This learning method encourages the model to capture a lower-dimensional representation, ensuring that sequences with moving sources (i.e., potential asteroids) are distinct from those without moving sources. The second branch is designed to learn additional features from the sky exposure sequences, which are then concatenated into the movement features before being processed by subsequent layers for the detection of asteroid candidates. We evaluate our model on sufficiently long-duration sequences and perform a comparative study with detection software. Additionally, we demonstrate the use of our model to suggest potential asteroids using photometry filtering. The proposed model outperforms the baseline model for asteroid streak detection by +7.70% of f1-score. Moreover, our study shows promising performance for long-duration sequences and improvement after adding the contrastive feature. Additionally, we demonstrate the uses of our model with the filtering to detect potential asteroids in wide-field detection using the long-duration sequences. Our model could complement the software as it suggests additional asteroids to its detection result.
Analytical Investigation of Second Harmonic Generation in Metal Nanoparticle Trimers Using Dipole Approximation
Authors: Farhoomand Afsoon , Sepehri Javan Nasser , Kheirandish Asef 
Published: December 2024

Abstract
In this theoretical study, we investigate the generation of second harmonics (SH) during the interaction of a laser beam with a metallic nanoparticle (MNP) trimer. Utilizing a classical electrodynamics framework, we explore the nonlinear interactions between the laser beam fields and nanoparticles (NPs), accounting for dipole-dipole interactions among the particles. Analytical expressions are derived to quantify the impact of these interactions on SH radiation power for two distinct polarizations of the laser beam. Our findings indicate that when the laser electric field is aligned parallel to the trimer's symmetry axis, there is a significant enhancement in SH radiation power compared to a single non-interacting NP, accompanied by a red-shift in the plasmon resonance peak. Conversely, when the laser electric field is perpendicular to the trimer axis, the SH radiation power from each NP decreases, and the plasmon resonance peak experiences a blue-shift. Additionally, we examine the influence of particle size and interparticle separation on SH generation. These results provide valuable insights into the role of interparticle interactions in enhancing nonlinear optical processes in NP assemblies, with potential implications for the design of nanophotonic devices.
Research on Static Security Analysis and Assessment Method of Integrated Energy Systems Based on the Unified Energy Circuit Theory
Authors: Bao Kaiwen , Hu Linxian 
Published: December 2024

Abstract
Multi energy flow coupling is a key feature distinguishing integrated energy systems (IES) from traditional power systems. As the degree of multi energy flow coupling in IES increases, the mutual influence between various energy subsystems becomes more pronounced. Local fluctuations or faults can propagate through different energy flows, thus affecting the overall security and stability of the system. This paper primarily focuses on the static security analysis and assessment methods for integrated energy systems. By utilizing the unified energy circuit model for power, natural gas, and thermal systems, it aims to achieve a unified analysis of heterogeneous energy flows. The paper extends the N-1 static security analysis method from power systems to IES, deeply explores the mechanisms of cross-system fault evolution, investigates fault diagnosis and security analysis techniques, and establishes a security assessment index system for IES. Finally, the effectiveness of the proposed analysis and assessment method is validated through a case study.