bluuebunny/crossref_metadata_2025_split huggingface dataset:
Greenland Ice Cores Reveal a South‐To‐North Difference in Holocene Thermal Maximum Timings
Authors: Martin Kaden C. , Buizert Christo , Brook Ed , Williams Olivia L. , Edwards Jon S. , Riddell‐Young Ben , Fudge T. J. , Mederbel Farhana , Beaudette Ross , Severinghaus Jeff , Oyabu Ikumi , Kawamura Kenji , Kirk Marie , Koldtoft Iben , Steffensen J. P. , Blunier Thomas 
Published: December 2024

AbstractHolocene temperature evolution remains poorly understood. Proxies in the early and mid‐Holocene suggest a Holocene Thermal Maximum (HTM) where temperatures exceed the pre‐industrial, whereas climate models generally simulate monotonic warming. This discrepancy may reflect proxy seasonality biases or errors in climate model internal feedbacks or dynamics. Using seasonally unbiased ice core reconstructions at NEEM, NGRIP, and Greenland Ice Sheet Project 2, we identify a Greenland HTM of ∼2°C above pre‐industrial, in agreement with other Northern Hemisphere proxy reconstructions. The firn‐based reconstructions are verified through borehole thermometry, producing a multi‐core, multi‐proxy reconstruction of Greenland climate from the last glacial to pre‐industrial. HTM timing across Greenland is heterogenous, occurring earlier at high elevations. Total air content measurements suggest a temperature contribution from elevation changes; regional oceanographic conditions, a weakened polar lapse rate, or variable near‐surface inversions may also be important sensitivities. Our reconstructions support climate simulations with dynamic Holocene vegetation, highlighting the importance of vegetation feedbacks.
HF Radar Observations and Modeling of the Impact of the 8 April 2024 Total Solar Eclipse on the Ionosphere‐Thermosphere System
Authors: Kunduri B. S. R. , Baker J. B. H. , Ruohoniemi J. M. , Thomas E. G. , Huba J. D. , Emmons D. J. , Themens D. R. , Sterne K. T. , Farinas Perez G. , Bristow W. A. , Shepherd S. G. , Holmes J. M. , Dao E. V. , Chartier A. T. , Perry G. W. , Pandey K. 
Published: December 2024

AbstractThe path of totality of the 8 April 2024 solar eclipse traversed the fields‐of‐view of four US SuperDARN radars. This rare scenario provided an excellent opportunity to monitor the large‐scale ionospheric response to the eclipse. In this study, we present observations made by the Blackstone (BKS) SuperDARN radar and a Digisonde during the eclipse. Two striking effects were observed by the BKS radar: (a) the Doppler velocities associated with ground scatter coalesced into a pattern clearly organized by the line of totality, with a reversal in sign across this line, and, (b) a delay of 45 min between time of maximum obscuration and maximum effect on the skip distance. The skip distance estimated using a SAMI3 simulation of the eclipse did not however capture the asymmetric time‐delay. These observations suggest that the neutral atmosphere plays an important role in controlling ionospheric plasma dynamics, which were missing in SAMI3 simulations.
Dispersal of the Changjiang River Water in East Asian Shelf Seas
Authors: Cheng Peng 
Published: December 2024

AbstractRiver plumes are crucial in transporting terrestrial materials from rivers to oceans. Knowledge gaps, however, still exist in understanding the transport pathway and the ultimate fate of riverine water in coastal oceans. This study conducted a 50‐year climatological numerical simulation to investigate the long‐term transport processes of Changjiang River water in the East Asian shelf seas. The Changjiang River water exhibits distinct seasonal patterns near the estuary mouth and in the coastal area south of the estuary, and it tends to be retained within the shelf seas, which influences its far‐field transport. The Changjiang River water takes less than 1 year to reach the eastern shelf edge of the East China Sea and over 12 years to enter the Bohai Sea. The Kuroshio current impedes the cross‐shelf transport of Changjiang water, with water in the Kuroshio region over 6 years old. The Taiwan Warm Current not only acts as a barrier that regulates the pathways of Changjiang River water but also serves as an important conduit for water exiting the East China Sea. The Changjiang River water leaves the estuary through four branches, forming eight major transport pathways in the Yellow and East China Seas. Approximately 85% of Changjiang River water flows through the Tsushima/Korea Straits, about 14% exits from the shelf edge of the East China Sea, and less than 1% passes through the Taiwan Strait. The results underscore the importance of water renewal and shelf circulation in the long‐term transport of river water within coastal oceans.
Thermohaline Intrusions as Seen by Argo Floats: The Case of the Black Sea
Authors: Stanev E. V. , Gramcianinov C. B. , Staneva J. , Slabakova V. 
Published: December 2024

AbstractUnderstanding the dynamics of thermohaline intrusions is crucial for predicting changes in water masses and their impact on marine ecosystems, especially in highly stratified semi‐enclosed seas and other coastal environments. We use high‐resolution (up to 1–2 m) Argo profiling float data collected over 15 years in the Black Sea, an excellent test area for studying thermohaline intrusions. Our analysis challenges the conventional view of stagnant intermediate and deep waters, revealing active mixing processes that reshape the thermohaline structure. We identified two main mechanisms driving these intrusions, related to dense water inflows from the Marmara Sea and boundary mixing enhanced by frontal instabilities. Argo data also allowed us to identify areas with favorable conditions for double‐diffusive processes. The variability of intrusions is due to changes in the thermohaline state of the upper ocean as well as to quasi‐periodic changes in the inflow caused by local conditions. Trends in the intensity and frequency of intrusions indicate shifts in water mass properties that are likely to be associated with climate variability and extreme weather events. Such trends can affect nutrient cycling, oxygen distribution and the overall stability of the water column, thereby affecting biogeochemical cycles and the resilience of marine ecosystems. Similar ventilation mechanisms may operate in other highly stratified marine systems, such as the Baltic Sea and the Arctic Ocean, so our findings may have wider implications for understanding climate‐induced changes in water masses at regional and global scales.
Evolution of the Double Warm‐Core Structure in the Eyewall Replacement Cycle of Typhoon Trami (2018)
Authors: Li Xiangcheng , Cheng Xiaoping , Fei Jianfang , Huang Xiaogang , He Shunzhi 
Published: December 2024

AbstractThe evolution of double warm‐cores (DWC) during the secondary eyewall formation (SEF) and the subsequent eyewall replacement cycle (ERC) in Typhoon Trami (2018) was investigated in this study. Using a coupled atmosphere‐ocean model, the impacts of the typhoon‐induced sea surface cooling (SSC) on the DWC structure were also examined. In both the coupled and uncoupled simulations, the middle‐level warm‐core (MWC) decayed as the tangential wind expanded outward during the SEF, even in the absence of SSC. Under the thermal wind balance, the cooling of the MWC was an inherent result to ensure the dynamic consistency during the SEF. In contrast to the uncoupled simulation, the upper‐level warm‐core (UWC) decayed under the influence of SSC, significantly contributing to the rapid weakening of Trami. The negative effects of the SSC on the UWC were more detrimental to the intensity of Trami. Results from the potential temperature (PT) budget of improved accuracy indicated that the decrease in the warming due to the radial eddy advection was mainly responsible for the decay of the MWC. The flattened radial gradient of PT during the SEF accounted for the reduction in the dynamical eye warming associated with the asymmetric mixing. In addition to the convectively induced subsidence, the upper‐level asymmetric structures could also be affected by the SSC. Consequently, the increase in the cooling due to the enhanced asymmetry collaborated with the decrease in the adiabatic warming, leading to the decay of the UWC in the coupled simulation.
Simulating Precipitation Efficiency Across the Deep Convective Gray Zone
Authors: Kukulies Julia , Prein Andreas F. , Morrison Hugh 
Published: December 2024

AbstractPrecipitation efficiency (PE) relates cloud condensation to precipitation and thus reflects how much of the total atmospheric condensate reaches the surface as precipitation. Because the PE in convective storms is directly linked to their updraft and downdraft dynamics, it is a helpful metric to identify convective processes that influence precipitation. However, km‐scale model simulations do not properly resolve convective processes such as individual updrafts and entrainment, which raises the question if such simulations can accurately represent PE. Here, we present two methods to derive PE from standard model output because condensation is usually not available as an output variable. The first method estimates PE from the state variables vertical velocity, temperature, and pressure, whereas the second method estimates PE from ice water path (IWP) and precipitation. We validate the proposed methods with the explicitly calculated PE using a set of idealized Weather Research and Forecast model simulations of organized midlatitude convective storms at different horizontal grid spacings. We show that PE can be reliably estimated from state variables with an error of less than 5%, partly due to error cancellation effects. Additionally, PE can be simulated by km‐scale models within ∼15% accuracy compared to large‐eddy simulations (LESs). The IWP method is slightly less accurate with a stronger grid spacing dependency of the error, but since it is based on observable quantities, it allows for a validation of simulated PE with satellite observations. Finally, we analyze the grid spacing dependency of the climate change signal of PE and find that future decreases in PE in LESs are robustly captured by km‐scale models.
Short‐Term Prediction of the Dst Index and Estimation of Efficient Uncertainty Using a Hybrid Deep Learning Network
Authors: Wang Ruyao , Wang Jianhui , Liang Tuo , Zhang Huixiong 
Published: December 2024

AbstractIn this study, we developed a novel deep learning model to predict the disturbance storm time (Dst) index 1–4 hr ahead. We also employed the Monte Carlo (MC) dropout technique to estimate the uncertainty and provide the prediction interval by introducing a recalibration factor. The proposed model achieves excellent scalability by extracting representative embeddings from the Dst index time series through an encoder‐decoder framework and integrating these with external solar wind parameters via a prediction network. We utilized magnetic storm data from 1998 to 2018 to evaluate the performance of the prediction model. Experimental results indicate that the proposed model reduces root mean square errors (RMSE) and improves the coefficient of determination (R2) compared to existing methods. Quantitative uncertainty analysis demonstrates that the prediction interval is reliable in most cases. The percent distribution across test storms by comparing the uncertainty‐based prediction of the minimum peak with the mean prediction indicates the probabilistic forecast model is competitive.
Membrane potential states gate synaptic consolidation in human neocortical tissue
Authors: Mittermaier Franz X. , Kalbhenn Thilo , Xu Ran , Onken Julia , Faust Katharina , Sauvigny Thomas , Thomale Ulrich W. , Kaindl Angela M. , Holtkamp Martin , Grosser Sabine , Fidzinski Pawel , Simon Matthias , Alle Henrik , Geiger Jörg R. P. 
Published: December 2024

AbstractSynaptic mechanisms that contribute to human memory consolidation remain largely unexplored. Consolidation critically relies on sleep. During slow wave sleep, neurons exhibit characteristic membrane potential oscillations known as UP and DOWN states. Coupling of memory reactivation to these slow oscillations promotes consolidation, though the underlying mechanisms remain elusive. Here, we performed axonal and multineuron patch-clamp recordings in acute human brain slices, obtained from neurosurgeries, to show that sleep-like UP and DOWN states modulate axonal action potentials and temporarily enhance synaptic transmission between neocortical pyramidal neurons. Synaptic enhancement by UP and DOWN state sequences facilitates recruitment of postsynaptic action potentials, which in turn results in long-term stabilization of synaptic strength. In contrast, synapses undergo lasting depression if presynaptic neurons fail to recruit postsynaptic action potentials. Our study offers a mechanistic explanation for how coupling of neural activity to slow waves can cause synaptic consolidation, with potential implications for brain stimulation strategies targeting memory performance.
How measurement noise limits the accuracy of brain-behaviour predictions
Authors: Gell Martin , Eickhoff Simon B. , Omidvarnia Amir , Küppers Vincent , Patil Kaustubh R. , Satterthwaite Theodore D. , Müller Veronika I. , Langner Robert 
Published: December 2024

AbstractMajor efforts in human neuroimaging strive to understand individual differences and find biomarkers for clinical applications by predicting behavioural phenotypes from brain imaging data. To identify generalisable and replicable brain-behaviour prediction models, sufficient measurement reliability is essential. However, the selection of prediction targets is predominantly guided by scientific interest or data availability rather than psychometric considerations. Here, we demonstrate the impact of low reliability in behavioural phenotypes on out-of-sample prediction performance. Using simulated and empirical data from four large-scale datasets, we find that reliability levels common across many phenotypes can markedly limit the ability to link brain and behaviour. Next, using 5000 participants from the UK Biobank, we show that only highly reliable data can fully benefit from increasing sample sizes from hundreds to thousands of participants. Our findings highlight the importance of measurement reliability for identifying meaningful brain–behaviour associations from individual differences and underscore the need for greater emphasis on psychometrics in future research.
Copper chelation redirects neutrophil function to enhance anti-GD2 antibody therapy in neuroblastoma
Authors: Rouaen Jourdin R. C. , Salerno Antonietta , Shai-Hee Tyler , Murray Jayne E. , Castrogiovanni Giulia , McHenry Charlotte , Jue Toni Rose , Pham Vu , Bell Jessica Lilian , Poursani Ensieh , Valli Emanuele , Cazzoli Riccardo , Damstra Naomi , Nelson Delia J. , Stevens Kofi L. P. , Chee Jonathan , Slapetova Iveta , Kasherman Maria , Whan Renee , Lin Francis , Cochran Blake J. , Tedla Nicodemus , Veli Feyza Colakoglu , Yuksel Aysen , Mayoh Chelsea , Saletta Federica , Mercatelli Daniele , Chtanova Tatyana , Kulasinghe Arutha , Catchpoole Daniel , Cirillo Giuseppe , Biro Maté , Lode Holger N. , Luciani Fabio , Haber Michelle , Gray Juliet C. , Trahair Toby N. , Vittorio Orazio 
Published: December 2024

AbstractAnti-disialoganglioside (GD2) antibody therapy has provided clinical benefit to patients with neuroblastoma however efficacy is likely impaired by the immunosuppressive tumor microenvironment. We have previously defined a link between intratumoral copper levels and immune evasion. Here, we report that adjuvant copper chelation potentiates anti-GD2 antibody therapy to confer durable tumor control in immunocompetent models of neuroblastoma. Mechanistic studies reveal copper chelation creates an immune-primed tumor microenvironment through enhanced infiltration and activity of Fc-receptor-bearing cells, specifically neutrophils which are emerging as key effectors of antibody therapy. Moreover, we report copper sequestration by neuroblastoma attenuates neutrophil function which can be successfully reversed using copper chelation to increase pro-inflammatory effector functions. Importantly, we repurpose the clinically approved copper chelating agent Cuprior as a non-toxic, efficacious immunomodulatory strategy. Collectively, our findings provide evidence for the clinical testing of Cuprior as an adjuvant to enhance the activity of anti-GD2 antibody therapy and improve outcomes for patients with neuroblastoma.
Evolution of a SHOOTMERISTEMLESS transcription factor binding site promotes fruit shape determination
Authors: Hu Zhi-Cheng , Majda Mateusz , Sun Hao-Ran , Zhang Yao , Ding Yi-Ning , Yuan Quan , Su Tong-Bing , Lü Tian-Feng , Gao Feng , Xu Gui-Xia , Smith Richard S. , Østergaard Lars , Dong Yang 
Published: December 2024

Abstract
In animals and plants, organ shape is primarily determined during primordium development by carefully coordinated growth and cell division1–3. Rare examples of post-primordial change in morphology (reshaping) exist that offer tractable systems for the study of mechanisms required for organ shape determination and diversification. One such example is morphogenesis in Capsella fruits whose heart-shaped appearance emerges by reshaping of the ovate spheroid gynoecium upon fertilization4. Here we use whole-organ live-cell imaging and single-cell RNA sequencing (scRNA-seq) analysis to show that Capsella fruit shape determination is based on dynamic changes in cell growth and cell division coupled with local maintenance of meristematic identity. At the molecular level, we reveal an auxin-induced mechanism that is required for morphological alteration and ultimately determined by a single cis-regulatory element. This element resides in the promoter of the Capsella rubella SHOOTMERISTEMLESS
5 (Cr
STM) gene. The CrSTM meristem identity factor positively regulates its own expression through binding to this element, thereby providing a feed-forward loop at the position and time of protrusion emergence to form the heart. Independent evolution of the STM-binding element in STM promoters across Brassicaceae species correlates with those undergoing a gynoecium-to-fruit shape change. Accordingly, genetic and phenotypic studies show that the STM-binding element is required to facilitate the shape transition and suggest a conserved molecular mechanism for organ morphogenesis.
Widespread outdoor exposure to uncompensable heat stress with warming
Authors: Fan Yuanchao , McColl Kaighin A. 
Published: December 2024

AbstractPrevious studies projected an increasing risk of uncompensable heat stress indoors in a warming climate. However, little is known about the timing and extent of this risk for those engaged in essential outdoor activities, such as water collection and farming. Here, we employ a physically-based human energy balance model, which considers radiative, wind, and key physiological effects, to project global risk of uncompensable heat stress outdoors using bias-corrected climate model outputs. Focusing on farmers (approximately 850 million people), our model shows that an ensemble median 2.8% (15%) would be subject to several days of uncompensable heat stress yearly at 2 (4) °C of warming relative to preindustrial. Focusing on people who must walk outside to access drinking water (approximately 700 million people), 3.4% (23%) would be impacted at 2 (4) °C of warming. Outdoor work would need to be completed at night or in the early morning during these events.
How much longer do you have to drive than the crow has to fly?
Authors: Wang Shanshan , Bette Henrik M. , Schreckenberg Michael , Guhr Thomas 
Published: December 2024

AbstractWhen travelling by car from one location to another, our route is constrained by the road network. The network distance between the two locations is generally longer than the geodetic distance as the crow flies. We report a systematic relation between the statistical properties of these two distances. Empirically, we find a robust scaling between network and geodetic distance distributions for a variety of large motorway networks. A simple consequence is that we typically have to drive 1.3 ± 0.1 times longer than the crow flies. This scaling is not present in standard random networks; rather, it requires non-random adjacency. We develop a set of rules to build a realistic motorway network, also consistent with the above scaling. We hypothesise that the scaling reflects a compromise between two societal needs: high efficiency and accessibility on the one hand, and limitation of costs and other burdens on the other.
Genetic algorithm‐based approach for torque control and increased efficiency across an optimised speed range in switched reluctance drives
Authors: MacRae Euan , Abdel‐Aziz Ali , Ahmed Khaled , Pollock Richard , Williams Barry W. 
Published: December 2024

AbstractThis paper presents a novel genetic algorithm (GA) design for current profiling in switched reluctance machines that eliminates torque ripple (TR) while inherently guaranteeing minimal RMS currents across the machines speed range. Minimising RMS current provides an increase to machine efficiency and the elimination of TR is required for potential SRM applications such as traction vehicles. This paper proposes a novel method for intentional greater‐than‐two‐phase overlap in the algorithm design. This allows any SRM configuration capable of three or more phase conduction to utilise its full speed range with zero torque ripple, in the case where it is limited using two‐phase torque sharing. An optimal set of current profiles is created using the algorithm across the full speed range of an exemplary 8/6 SRM and these are analysed. A current profiling‐based control scheme using these results is then proposed and simulated for the 8/6 SRM. This is then compared to classical and recently published SRM control methods to highlight the merits of the overall GA design and its resultant control scheme.
Fault diagnosis of power transformers based on dissolved gas analysis and improved LightGBM hybrid integrated model with dual‐branch structure
Authors: Lv Xuebin , Liu Fuzheng , Jiang Mingshun , Zhang Faye , Jia Lei 
Published: December 2024

AbstractAiming at the fault diagnosis problems of imbalanced data and insufficient mapping of characteristic information in fault samples collected by transformers at present, which lead to low accuracy and large diagnostic deviation in actual applications, a power transformer fault diagnosis method based on dissolved gas analysis and an improved LightGBM hybrid integrated model with a dual‐branch structure (DIL‐DS) is proposed. Firstly, multi‐characteristic dissolved gas ratio analysis is used to construct multi‐dimensional supplementary feature vectors, which enrich the characterisation features of transformers and facilitate efficient diagnosis of classification models. Secondly, a dual‐branch structure combining focal‐gradient harmonic loss and cross‐entropy loss is introduced to improve the attention and recognition ability of the model to a few categories in the dataset and alleviate the influence of data imbalance on the diagnostic results. Then, an improved grey wolf optimisation (GWO) is designed to improve LightGBM and realise the iterative optimisation of hyperparameters. At the same time, the Jacobian regularisation method is introduced to denoise LightGBM to solve the problem that the model is sensitive to noise. Finally, the LightGBM hybrid integrated model is developed to ensure the accuracy and stability of model diagnosis under the changeable and imbalanced dataset. Experiments show that the proposed DIL‐DS can effectively solve the limitation of class imbalance, improve the overall fault diagnosis performance, and is suitable for transformer fault identification.