bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mars' Hemispheric Magnetic Field From a Full‐Sphere Dynamo
Authors: Yan C. , Barik A. , Stanley S. , Mittelholz A. , Plesa A.‐C. , Johnson C.‐L. 
Published: February 2025

AbstractSeismic measurements from the NASA Mars InSight mission revealed that Mars' core has a relatively low density, implying a larger fraction of lighter elements than previously thought, which further leads to a low melting temperature. Thus, Mars probably never developed a solid inner core during its early history when the dynamo was active. We perform full‐sphere dynamo simulations to eliminate the influence of an inner core on dynamo behaviors and investigate how various magnitudes of heat flux perturbations at the core‐mantle boundary affect the field morphology, comparing results to those from models with small inner cores. We find that a hemispheric magnetic field can result when the heat flux is concentrated in one hemisphere. Moreover, a dynamo model without the presence of an inner core can better explain Mars' crustal magnetic field dichotomy than that in a spherical shell surrounding a solid inner core.
Enhancing Deep Learning Ionospheric Modeling With Solar Radiation and Flare Classes
Authors: Lin Yang , Fang Hanxian , Duan Die , Huang Hongtao , Xiao Chao , Ren Ganming , Li Chenhao , Zhou Chuyue 
Published: February 2025

AbstractThe ionosphere is pivotal for satellite navigation, radio communication, and the modeling of space weather. However, the accurate three‐dimensional modeling of ionospheric features remains a challenge. Since solar activity introduces changes in space weather, we collected COSMIC radio occultation observations of 2010–2020 with a suite of indices related to solar and geomagnetic activities, especially including solar EUV and X‐ray radiation fluxes, to develop a deep learning model for the global ionospheric electron density. This model, which is called the Solar Flare and Radiation Neural Network (SFRNN) and is based on Embedding, Long Short‐Term Memory and fully connected layers, presented excellent performance in reconstructing ionospheric profiles. In this study, 28‐min was found to be the best input solar radiation interval for SFRNN with annual RMSEs of 6.24 × 104 to 1.56 × 105 el/cm3. Significantly, during solar flare events, SFRNN had a lower reconstruction error than the former artificial neural network (ANN) model that only uses space weather indices. The most substantial improvement was observed under X‐class flares, where SFRNN exhibited a 18.3% lower Root Mean Squared Error than ANN. To further validate the modeling accuracy, electron density profiles derived from Jicamarca incoherent scatter radar (ISR) were used. SFRNN successfully provided profiles with high consistency with the ISR observation in the ionospheric layers. Our modeling results demonstrate that refined solar activity parameters can effectively improve reconstruction performance.
Impacts of Bioenergy Crop Cultivation on Regional Climate, Hydrology, and Water Quality in the U.S. Northern High Plains
Authors: Dangol Sijal , Zhang Xuesong , Sun Chao , Liang Kang , Liang Xin‐Zhong 
Published: February 2025

AbstractThe cultivation of bioenergy feedstocks, such as miscanthus, or energycane, on marginal lands helps alleviate the competition between food and fuel. However, such land use conversion could lead to complex interactions among climate, vegetation, and water resources, resulting in positive or negative environmental impacts. In this study, we used the Climate‐Weather Research and Forecasting (CWRF) model to simulate the feedback from growing bioenergy crops on marginal lands to regional climate for the present and future scenarios and used the Soil and Water Assessment Tool (SWAT) to evaluate the climate and land use change impacts on the hydrological cycle and water quality in the U.S. Northern High Plains Aquifer region. CWRF projects a wetter and cooler regional climate by considering climate‐crop feedback as compared to a control scenario (no land use change and climate feedback), highlighting the importance of land‐atmosphere interactions in regional climate assessment. Our watershed‐scale assessment shows that although growing miscanthus increases local evapotranspiration and decreases surface runoff, soil moisture, and percolation on marginal lands, watershed‐scale streamflow substantially increases during the growing season in both present and future conditions due to increases in regional precipitation. The differences in the extent of marginal land use change between the Platte (4%) and Republican (20%) river basins result in different responses in streamflow and nitrogen loading. Overall, our study highlights the importance of assessing the regional climate‐crop feedback and environmental quality impacts of using marginal lands for future sustainable bioenergy production.
The emerging roles of aberrant alternative splicing in glioma
Authors: Ben Mrid Reda , El Guendouzi Sara , Mineo Marco , El Fatimy Rachid 
Published: February 2025

Abstract
Gliomas represent a heterogeneous group of uniformly fatal brain tumors. Low and high-grade gliomas have diverse molecular signatures. Despite successful advances in understanding glioma, several genetic, epigenetic, and post-transcriptional alterations leave various targeted therapies ineffective, leading to a poor prognosis for high-grade glioma. Recent advances have revealed the implication of dysregulated alternative splicing (AS) events in glioma development. AS is a process that produces, from a single genomic sequence, several mature messenger RNAs. Splicing of pre-messenger RNAs concerns at least 95% of transcripts and constitutes an important mechanism in gene expression regulation. Dysregulation of this process, through variations in spliceosome components, aberrant splicing factors and RNA-binding protein activity, disproportionate regulation of non-coding RNAs, and abnormal mRNA methylation, can contribute to the disruption of AS. Such disruptions are usually associated with the development of several cancers, including glioma. Consequently, AS constitutes a key regulatory mechanism that could serve as a target for future therapies. In this review, we explore how AS events, spliceosome components, and their regulatory mechanisms play a critical role in glioma development, highlighting their potential as targets for innovative therapeutic strategies against this challenging cancer.
Probing spectral features of quantum many-body systems with quantum simulators
Authors: Sun Jinzhao , Vilchez-Estevez Lucia , Vedral Vlatko , Boothroyd Andrew T. , Kim M. S. 
Published: February 2025

Abstract
The efficient probing of spectral features is important for characterising and understanding the structure and dynamics of quantum materials. In this work, we establish a framework for probing the excitation spectrum of quantum many-body systems with quantum simulators. Our approach effectively realises a spectral detector by processing the dynamics of observables with time intervals drawn from a defined probability distribution, which only requires native time evolution governed by the Hamiltonian without ancilla. The critical element of our method is the engineered emergence of frequency resonance such that the excitation spectrum can be probed. We show that the time complexity for transition energy estimation has a logarithmic dependence on simulation accuracy and how such observation can be guaranteed in certain many-body systems. We discuss the noise robustness of our spectroscopic method and show that the total running time maintains polynomial dependence on accuracy in the presence of device noise. We further numerically test the error dependence and the scalability of our method for lattice models. We present simulation results for the spectral features of typical quantum systems, either gapped or gapless, including quantum spins, fermions and bosons. We demonstrate how excitation spectra of spin-lattice models can be probed experimentally with IBM quantum devices.
Marine species and assemblage change foreshadowed by their thermal bias over Early Jurassic warming
Authors: Reddin Carl J. , Landwehrs Jan P. , Mathes Gregor H. , Ullmann Clemens V. , Feulner Georg , Aberhan Martin 
Published: February 2025

Abstract
A mismatch of species’ thermal preferences to their environment may indicate how they will respond to future climate change. Averaging this mismatch across species may forewarn that some assemblages will undergo greater reorganization, extirpation, and possibly extinction, than others. Here, we examine how regional warming determines species occupancy and assemblage composition of marine bivalves, brachiopods, and gastropods over one-million-year time steps during the Early Jurassic. Thermal bias, the difference between modelled regional temperatures and species’ long-term thermal optima, predicts a gradient of species occupancy response to warming. Species that become extirpated or extinct tend to have cooler temperature preferences than immigrating species, while regionally persisting species fell midway. Larger regional changes in summer seawater temperatures (up to +10 °C) strengthen the relationship between species thermal bias and the response gradient, which is also stronger for brachiopods than for bivalves, while the relationship collapses during severe seawater deoxygenation. At +3 °C regional seawater warming, around 5 % of pre-existing benthic species in a regional assemblage are extirpated, and immigrating species comprise around one-fourth of the new assemblage. Our results validate thermal bias as an indicator of immigration, persistence, extirpation, and extinction of marine benthic species and assemblages under modern-like magnitudes of climate change.
Different honesty conceptions align across US politicians' tweets and public replies
Authors: Carrella Fabio , Aroyehun Segun T. , Lasser Jana , Simchon Almog , Garcia David , Lewandowsky Stephan 
Published: February 2025

Abstract
Recent evidence shows that US politicians’ conception of honesty has undergone a bifurcation, with authentic but evidence-free “belief-speaking” becoming more prominent and differentiated from evidence-based “fact-speaking”. Here we examine the downstream consequences of those two ways of conceiving honesty by investigating user engagement with fact-speaking and belief-speaking texts by members of the US Congress on Twitter (now X). We measure the conceptions of honesty of a sample of tweets and replies using computational text processing, and check whether the conceptions of honesty in the tweets align with those in their replies. We find that the conceptions of honesty used in replies align with those of the tweets, suggesting a “contagion”. Notably, this contagion replicates under controlled experimental conditions. Our study highlights the crucial role of political leaders in setting the tone of the conversation on social media.
Demand-side strategies enable rapid and deep cuts in buildings and transport emissions to 2050
Authors: van Heerden Rik , Edelenbosch Oreane Y. , Daioglou Vassilis , Le Gallic Thomas , Baptista Luiz Bernardo , Di Bella Alice , Colelli Francesco Pietro , Emmerling Johannes , Fragkos Panagiotis , Hasse Robin , Hoppe Johanna , Kishimoto Paul , Leblanc Florian , Lefèvre Julien , Luderer Gunnar , Marangoni Giacomo , Mastrucci Alessio , Pettifor Hazel , Pietzcker Robert , Rochedo Pedro , van Ruijven Bas , Schaeffer Roberto , Wilson Charlie , Yeh Sonia , Zisarou Eleftheria , van Vuuren Detlef 
Published: February 2025

Abstract
Decarbonization of energy-using sectors is essential for tackling climate change. We use an ensemble of global integrated assessment models to assess CO2 emissions reduction potentials in buildings and transport, accounting for system interactions. We focus on three intervention strategies with distinct emphases: reducing or changing activity, improving technological efficiency and electrifying energy end use. We find that these strategies can reduce emissions by 51–85% in buildings and 37–91% in transport by 2050 relative to a current policies scenario (ranges indicate model variability). Electrification has the largest potential for direct emissions reductions in both sectors. Interactions between the policies and measures that comprise the three strategies have a modest overall effect on mitigation potentials. However, combining different strategies is strongly beneficial from an energy system perspective as lower electricity demand reduces the need for costly supply-side investments and infrastructure.
Differential protection against SARS-CoV-2 reinfection pre- and post-Omicron
Authors: Chemaitelly Hiam , Ayoub Houssein H. , Coyle Peter , Tang Patrick , Hasan Mohammad R. , Yassine Hadi M. , Al Thani Asmaa A. , Al-Kanaani Zaina , Al-Kuwari Einas , Jeremijenko Andrew , Kaleeckal Anvar Hassan , Latif Ali Nizar , Shaik Riyazuddin Mohammad , Abdul-Rahim Hanan F. , Nasrallah Gheyath K. , Al-Kuwari Mohamed Ghaith , Butt Adeel A. , Al-Romaihi Hamad Eid , Al-Thani Mohamed H. , Al-Khal Abdullatif , Bertollini Roberto , Abu-Raddad Laith J. 
Published: February 2025

Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly evolved over short timescales, leading to the emergence of more transmissible variants such as Alpha and Delta1–3. The arrival of the Omicron variant marked a major shift, introducing numerous extra mutations in the spike gene compared with earlier variants1,2. These evolutionary changes have raised concerns regarding their potential impact on immune evasion, disease severity and the effectiveness of vaccines and treatments1,3. In this epidemiological study, we identified two distinct patterns in the protective effect of natural infection against reinfection in the Omicron versus pre-Omicron eras. Before Omicron, natural infection provided strong and durable protection against reinfection, with minimal waning over time. However, during the Omicron era, protection was robust only for those recently infected, declining rapidly over time and diminishing within a year. These results demonstrate that SARS-CoV-2 immune protection is shaped by a dynamic interaction between host immunity and viral evolution, leading to contrasting reinfection patterns before and after Omicron’s first wave. This shift in patterns suggests a change in evolutionary pressures, with intrinsic transmissibility driving adaptation pre-Omicron and immune escape becoming dominant post-Omicron, underscoring the need for periodic vaccine updates to sustain immunity.
Comparative analysis of microbial contamination in diesel fuels using MALDI-TOF MS
Authors: Ludwiczak Agnieszka , Zieliński Tomasz , Sibińska Ewelina , Czeszewska-Rosiak Grażyna , Złoch Michał , Rudnicka Joanna , Tretyn Andrzej , Pomastowski Paweł 
Published: February 2025

Abstract
Microbiological contamination in fuels poses a significant threat to fuel quality, operational safety, and the efficiency of fuel systems. Effective management of microbial risks can extend fuel systems’ lifespan and minimize the environmental footprint of fuel usage. Therefore, we aimed to identify the microbiological contaminants using two MALDI-TOF MS systems (Bruker Daltonik GmbH and Zybio Inc.). Detection and characterization of microbiological contamination in fuels were performed with further validation by 16 S rRNA gene sequencing. Microorganisms collected from three types of diesel fuel were cultured, and fuel samples were analyzed. Significant differences in microbiological contamination were observed between the fuel types, with 272 isolates of bacteria and fungi identified across all fuel samples. Ekodiesel Ultra B0 had the highest number of identified microorganisms. The Zybio system identified 48% of all microorganisms at the species level, whereas the Bruker system identified only 33%. The 16 S rDNA sequencing confirmed proteomic identifications by the MALDI systems with high accuracy. Our study indicates that MALDI-TOF MS technology can effectively assess microbiological contamination in fuels. Integrating MALDI-TOF MS with other molecular techniques could provide a comprehensive view of fuel’s microbial communities.
Investigation and evaluation of the efficiency of palm kernel oil extract for corrosion inhibition of brass artifacts
Authors: Megahed Mohamed M. , AbdElRhiem Eman , Atta Wesam , Ghany Nabil Abdel , Abdelbar Mohamed 
Published: February 2025

Abstract
Brass (Cu–Zn alloy) used in the crescent of the Al-Maradani Mosque pulpit is subjected to corrosion under certain conditions, such as exposure to polluted air, oxidizing acids, and compounds containing sulphur or ammonia. This study aimed to evaluate the effectiveness of palm kernel oil extract (PKO) as a green corrosion inhibitor for protecting brass artifacts. The crescent was analyzed using metallographic microscopy, scanning electron microscopy (SEM) with energy-dispersive X-ray (EDX), and X-ray diffraction (XRD) to identify its alloy composition, microstructure and corrosion products. The analyses confirmed the crescent was made of a brass alloy (Cu–Zn) and formed by hammering, with corrosion layers composed primarily of cuprite and clinoatacamite, covered by dust containing calcite and quartz. The corrosion protection efficiency of the PKO was evaluated using brass coupons, simulating the artifact of the alloy. Electrochemical methods, including the open circuit potential (OCP), Tafel, and electrochemical impedance spectroscopy (EIS), were used to assess the performance of palm kernel oil on brass coupons at different concentrations (1, 3, 5, 7%). Electrochemical tests showed that corrosion inhibition efficiency increased with higher palm kernel oil concentrations, with the 7% concentration exhibiting the highest corrosion protection, up to 99.7%.
Design and modeling of a highly compact negative index floral shape metamaterial for flight navigation applications
Authors: Pallavi M. , Kumar Praveen , Shivakumar B. R. 
Published: February 2025

Abstract
The collision avoidance system (CAS) is a mandatory monitoring apparatus equipped in all aircraft to safeguard flight safety. The CAS scans the predefined regions in a systematic manner for a certain length of time to detect any approaching aircraft that could potentially pose a threat. Thus, CAS requires a focused multi-element radiator which can encompass the complete azimuth region. Recent years have seen a growing emphasis on enhancing the efficiency of CAS antennas because of several constraints, such as low gain (3.6 dB), larger dimensions, substantial side-lobe amplitude (− 7 dB), and challenges with beam adaptation. The current research strives to enhance the gain of a CAS antenna by incorporating the basic idea of metamaterials (MTMs). Therefore, a compact floral-shaped double negative (DNG) MTM design is proposed. The CAS antenna routes the signal throughout the complete azimuth region, so the designed MTM must be proficient to withstand its DNG characteristics for different incident angles. Hence, the proposed design is tested at various incident angles spanning between to along the azimuth region, at a deviation. The results indicate that the proposed structure retains its DNG behavior in the desired frequency range, regardless of the incident angles. The computed effective medium ratio of the structure is 13.47 at the CAS central frequency (1.06 GHz), highlighting its compactness and efficacy. Furthermore, to analyze the function of the structure on the antenna, the unit-element (UE) is expanded to a 5 × 4 array and deployed as an additional layer on the radiator at a predetermined distance. The addition of MTM to the radiator outperformed the conventional radiator by enhancing the antenna gain, by 2.6 dB, respectively. Additionally, to confirm the experimental findings, the UE and array designs are fabricated, and the fabrication results align closely with the simulation results.
Machine learning optimized design of THz piezoelectric perovskite-based biosensor for the detection of formalin in aqueous environments
Authors: Wekalao Jacob , Patel Shobhit K. , Kumar Om Prakash , Al-zahrani Fahad Ahmed 
Published: February 2025

Abstract
This investigation presents the development and characterization of an advanced piezoelectric perovskite-based biosensing platform optimized for formalin detection in aqueous media through the implementation of Locally Weighted Linear Regression (LWLR) machine learning algorithms. The sensor architecture operates within the terahertz spectral region and incorporates an advanced nanomaterial composite system comprising black phosphorus, gold nanostructures, graphene, and barium titanate to maximize detection sensitivity and operational performance metrics. The engineered platform integrates a circular graphene metasurfaces configuration with a gold-based H-resonator assembly and concentrically arranged circular ring resonators. Computational simulations demonstrate vigorous sensing capabilities across three discrete frequency bands, achieving remarkable sensitivity parameters of 444 GHzRIU⁻¹, accompanied by a quality factor of 5.970 and detection accuracy of 7.576. The integration of LWLR-based optimization protocols substantially enhances prediction accuracy while reducing computational time by ≥ 85% as well as cutting down the required resources. The proposed sensor architecture presents significant potential for environmental monitoring and clinical applications, offering a highly sensitive and efficient methodology for quantitative formalin detection in aqueous environments.
HSC70 coordinates COP9 signalosome and SCF ubiquitin ligase activity to enable a prompt stress response
Authors: Nishimura Shunsuke , Kioka Hidetaka , Ding Shan , Hakui Hideyuki , Shinomiya Haruki , Tanabe Kazuya , Hitsumoto Tatsuro , Matsuoka Ken , Kato Hisakazu , Tsukamoto Osamu , Asano Yoshihiro , Takashima Seiji , Enchev Radoslav I , Sakata Yasushi 
Published: February 2025

Abstract
The SCF (SKP1/CUL1/F-box protein) ubiquitin ligase complex plays a protective role against external stress, such as ultraviolet irradiation. The emergence of substrates activates SCF through neddylation, the covalent attachment of ubiquitin-like protein NEDD8 to CUL1. After substrate degradation, SCF is inactivated through deneddylation by COP9-signalosome (CSN), a solo enzyme that can deneddylate SCF. How the activity of CSN and SCF is coordinated within the cell is not fully understood. Here, we find that heat-shock cognate 70 (HSC70) chaperone coordinates SCF and CSN activation dependent on the neddylation status and substrate availability. Under basal conditions and low substrate availability, HCS70 directly enhances CSN deneddylation activity, thereby reducing SCF activity. Under SCF-activated conditions, HSC70 interacts with neddylated SCF and enhances its ubiquitination activity. The alternative interaction between HSC70 and CSN or neddylated SCF is regulated by the presence or absence of SCF substrates. The knockdown of HSC70 decreases SCF-mediated substrate ubiquitination, resulting in vulnerability against ultraviolet irradiation. Our work demonstrates the pivotal role of HSC70 in the alternative activation of CSN deneddylation and SCF substrate ubiquitination, which enables a prompt stress response.