bluuebunny/crossref_metadata_2025_split huggingface dataset:
Critical Factors That Control Hydrothermal Circulation Within Active Volcanoes: Constraints From Numerical Simulation Based on a Resistivity Structure Model
Authors: Matsunaga Yasuo , Kanda Wataru 
Published: February 2025

AbstractNumerical modeling is a valuable approach for quantitative elucidation of the highly complex hydrothermal processes within active volcanoes. Various schemes have been developed for the numerical simulation of volcanic hydrothermal systems, generally employed in combination with other geophysical and geochemical monitoring techniques. However, a scheme for constructing realistic permeability structures (crucial for simulations) remains unexplored. As the first step toward establishing such a scheme, we conducted numerical simulations to explore the effect of lithology variations on hydrothermal circulation within active volcanoes. These simulation models were constructed based on the electrical resistivity structure model of the Kusatsu‐Shirane Volcano (KSV) in Japan. Key factors include the permeability of the host rock and underlying basement, permeability reduction in the ductile region, and the geometry of a silica sealing layer. Of these, the silica sealing layer was a significant factor in reproducing the actual observations. The simulations indicated that the permeability and degree of closure of the silica sealing layer determined the pressure distribution within the region that the layer enclosed, and were, thus, responsible for the low resistivity of the subvertical conductors commonly found beneath volcanoes. The permeability structure used in this study was simple but systematically constructed, and simulations based on this permeability distribution successfully reproduced the key observations. The knowledge obtained from the numerical model of KSV can be used to explain the resistivity distribution of other active volcanoes, including higher‐ and lower‐temperature systems. The results suggest the validity and potential broad applicability of the proposed modeling scheme.
Calcite U‐Pb Geochronology and Paleomagnetism Reveal Mesozoic Multi‐Episodic Remagnetizations From the Penglaitan GSSP Section, South China
Authors: Zhang Min , Qin Huafeng , Wu Shitou , Hou Yifei , Xiao Zhenglian , Qi Kaixian , Yuan Dong‐xun , Zhang Hua , Deng Chenglong , Shen Shu‐zhong , Pan Yongxin 
Published: February 2025

AbstractCarbonate rocks are widely used for paleomagnetic reconstructions of continental block rifting and geodynamic evolution. However, the detection of remagnetization in carbonate rocks is challenging. Uncertainty of remagnetization timing hinders our ability to understand the geomagnetic behavior during critical Phanerozoic transitions, such as the period across the Middle‐Permian Guadalupian to Late‐Permian Lopingian boundary (GLB). To test whether primary magnetization is preserved, we conducted paleomagnetic, calcite U‐Pb geochronological and mineralogical studies at the Penglaitan section in southern China. The rock‐magnetic results indicate that magnetite, maghemite and rare hematite are dominant remanence carriers. Calcite U‐Pb ages of approximately 126 Ma, 223 Ma and 251 Ma, respectively, are consistent with the timing of three remanent magnetizations (RM1, RM2, RM3). This indicates that calcite U‐Pb dating can provide robust support to constrain the age magnetizations. The consistency indicates that RM3 was acquired during the limestone deposition, whereas component RM1 and RM2 were due to early Cretaceous and late‐Triassic remagnetization, respectively. In addition, the primary component RM3 was isolated from tuffaceous limestone and yielded a mean direction of Ds/Is = 195.3°/+5.6° (α95s = 5.3°, ks = 22.8, n = 34) after tilt‐correction. It defined a reversed magnetozone from the top of conodont Jinogondolella granti Zone to the lower part of the Clarkina dukouensis Zone, straddling the GLB. The calcite U‐Pb dating and paleomagnetic results provide new insights into Mesozoic multi‐remagnetization in the South China Block and refine the GLB positioned in a reversed magnetozone.
Atmosphere Response to an Oceanic Submesoscale SST Front: A Coherent Structure Analysis
Authors: Jacquet Hugo , Ayet Alex , Couvreux Fleur 
Published: February 2025

AbstractThe atmosphere response to oceanic submesoscale sea surface temperature (SST) fronts is neither resolved by operational nor climate models. Above the ocean, the atmospheric boundary layer (ABL) is in a convective regime and its turbulence levels and structure are altered by the SST variations. Using large eddy simulations, we investigate an ABL flowing above a 1D oceanic submesoscale SST front. The organization of atmospheric turbulence evolves from rolls to a cell‐roll transition state but with a 3.5 km delay due to the strong advection. The SST gradient imprints on the atmosphere, creating a pressure gradient that accelerates the flow at all altitudes. On warm water, horizontal wind in the lower half of the ABL increases mainly due to turbulent mixing. Most of the flow is resolved, and we relate statistical quantities to coherent structures using a conditional sampling. The SST increase strengthens updrafts, whereas a downward motion develops in response, transporting high wind from the upper to the lower layers of the ABL. We show that this descending flow is not a downdraft but rather a less turbulent object similar to an enhanced compensating subsidence, which could be parametrized by a mass‐flux term. The intense updrafts overshoot the boundary layer height and could trigger convection with moister environmental conditions.
Cleansing Beijing Air Pollution by Extensive Precipitation Leads to Marine‐Like Clouds With Warm Rain
Authors: Zhao Delong , Wang Minghuai , Rosenfeld Daniel , Chen Baojun , Zhu Yannian , Cai Miao , Duan Jing , Liu Dantong , Zhou Wei , Wang Fei , Sheng Jiujiang , Du Yuanmo , Tian Ping , Chen Yichen , He Hui , Wang Honglei , Huang Mengyu 
Published: February 2025

AbstractWarm rain prevails in clean marine clouds and is one of the most abundant types of precipitation in the world. However, warm rain is rarely observed in urban polluted atmospheric environments due to high number concentrations of aerosols generally suppress the occurrence of warm rain. Three aircraft observation of clouds were used during summer in Beijing area. Here, we documented warm rain processes similar to shallow marine clouds in the urban (Beijing) atmospheric environment after cleansing air pollution by extensive precipitation observed on 11 September 2019. Our results showed that, compared with aircraft observations of similar cumulus clouds under polluted conditions, large‐scale precipitation can efficiently scavenge air pollution in Beijing and lead to marine‐like clouds with warm rain. The average aerosol concentration (Na) near the cloud base in these clean cases was only 225 cm−3 with cloud droplet number concentration (Nd) of 36 cm−3, (maximum of 142 cm−3) which led to enhanced coalescence. The warm rain was initiated at 600 m above the cloud base. Our results highlight the significance of pollution scavenging by precipitation in warm rain production in urban environment.
Multiscale WRF Modeling of Meso‐ to Micro‐Scale Flows During Sundowner Events
Authors: Janiszeski Andrew , Crippa Paola 
Published: February 2025

AbstractTwo Sundowner events observed during the Sundowner Wind Experiment (SWEX) project are analyzed using a realistically forced large eddy simulation (LES) employing a multiscale Weather and Research Forecasting (WRF) model configuration with domain grid spacings ranging from 11,250 to 30 m centered over the Santa Barbara, CA region to examine their meso‐ to micro‐scale drivers. The main drivers of both events are increasing mountaintop stability and the mountain wave activity exhibiting a hydraulic jump and near‐surface critical layer. Another important finding is ascent of the downslope flows over the turbulent adiabatic layers at the coastal regions. In both events, the strong downslope flow warms and dries the air descending the southern slopes of the SYM adiabatically generating a deepening adiabatic layer that is 0.4 to as much as 1 km deep during peak Sundowner intensity over the coastal regions. This layer, exhibiting turbulence within and atop, is characterized with the strong downslope flow atop with much weaker, and at times, reversed flow beneath over the coastal regions. This flow structure, along with regions of turbulence within and atop the adiabatic layer, is indicative of a mountain lee‐wave rotor. Coastal locations in both events remain relatively unaffected. Further investigations are needed to determine whether or not this is consistent across all Sundowner events observed during the SWEX project and whether turbulence helps diffuse or accelerate the flows.
Ternary molecular switching in a single-crystal optical actuator with correlated crystal strain
Authors: Cole Jacqueline M. , Gosztola David J. , Velazquez-Garcia Jose de J. , Guest Jeffrey R. 
Published: February 2025

Abstract
A growing portfolio of single-crystal optical actuators is forging a new class of photonic materials that hold prospects for quantum technologies. Ruthenium-based complexes that exhibit this phenomenon via SO2-linkage photoisomerisation are of particular interest since they display multiple metastable states, once induced by green light; yet, complete photoconversion into each SO2-isomeric state is rarely achieved. We discover a new complex, trans-[Ru(SO2)(NH3)4(4-bromopyridine)]tosylate2, that produces 100% photoconverted η1-OSO isomeric crystal structures at 90 K, which fully transition into η2-(OS)O photoisomers upon warming to 100 K, while the dark-state η1-SO2 structure is wholly recovered by heating the crystal to room temperature. Crystal structures and optical-absorption profiles of each state are captured via in-situ light-induced single-crystal X-ray diffraction and optical-absorption spectroscopy. Results show that both photoisomeric species behave as optical switches, but with distinct optical properties. The photoisomerisation process causes thermally-reversible micro- and nanoscopic crystal strain, as characterised by optical microscopy and in-situ light-induced atomic-force microscopy.
Optimizing casting process using a combination of small data machine learning and phase-field simulations
Authors: Pei Xiaolong , Pei Jiaqi , Hou Hua , Zhao Yuhong 
Published: February 2025

Abstract
It has been a challenge to employ machine learning (ML) to optimize casting processes due to the scarcity of data and difficulty in feature expansion. Here, we introduce a nearest neighbor search method to optimize the stratified random sampling in Latin hypercube sampling (LHS) and propose a new revised LHS coupled with Bayesian optimization (RLHS-BO). Using this method, we optimized the squeeze-casting process for mine fuel tank partition castings for the first time with an ultra-small dataset of 25 samples. Compared to traditional methods such as random sampling, interval sampling, orthogonal design (OD), and central composite design (CCD), our approach covers the process parameter space more, reduces the data volume by approximately 50%, and achieves process optimization beyond five factors-five levels with fewer data. Through RLHS and 6 iterations of experiments, the optimal process was identified, and the ultimate tensile strength (UTS) of partition casting under the optimal process reached 239.7 MPa, with an elongation (EL) of 12.2%, showing increases of 17.6% and 18.4% over the optimal values in the initial dataset. Finally, a combination of Shapley additive interpretation (SHAP) and phase-field method (PFM) of solidification dendrite growth was used to address the issue of weak physical interpretability in ML models.
Promoter-proximal RNA polymerase II termination regulates transcription during human cell type transition
Authors: Lysakovskaia Kseniia , Devadas Arjun , Schwalb Björn , Lidschreiber Michael , Cramer Patrick 
Published: February 2025

Abstract
Metazoan gene transcription by RNA polymerase II (Pol II) is regulated in the promoter-proximal region. Pol II can undergo termination in the promoter-proximal region but whether this can contribute to transcription regulation in cells remains unclear. Here we extend our previous multiomics analysis to quantify changes in transcription kinetics during a human cell type transition event. We observe that upregulation of transcription involves an increase in initiation frequency and, at a set of genes, a decrease in promoter-proximal termination. In turn, downregulation of transcription involves a decrease in initiation frequency and an increase in promoter-proximal termination. Thus, promoter-proximal termination of Pol II contributes to the regulation of human gene transcription.
SIBES: Long-term and large-scale monitoring of intertidal macrozoobenthos and sediment in the Dutch Wadden Sea
Authors: Bijleveld Allert I. , de la Barra Paula , Danielson-Owczynsky Hailley , Brunner Livia , Dekinga Anne , Holthuijsen Sander , ten Horn Job , de Jong Anne , Kleine Schaars Loran , Kooij Adrienne , Koolhaas Anita , Kressin Hidde , van Leersum Felianne , Miguel Simone , de Monte Luc G. G. , Mosk Dennis , Niamir Amin , Oude Luttikhuis Dorien , Peck Myron A. , Piersma Theunis , Roohi Reyhaneh , Serre-Fredj Léon , Tacoma Marten , van Weerlee Evaline , de Wit Bas , Bom Roeland A. 
Published: February 2025

Abstract
The Wadden Sea is the world’s largest intertidal area and a UNESCO World Heritage Site. Macrozoobenthic invertebrates perform key ecological functions within intertidal areas by regulating nutrient cycles, decomposing organic matter, and providing food for fish, birds and humans. To understand ecological processes and human impacts on biodiversity, the Synoptic Intertidal BEnthic Survey (SIBES) has sampled intertidal macrozoobenthos since 2008. On average 4,109 stations across 1,200 km² of Dutch Wadden Sea mudflats are sampled from June to October to quantify the benthic invertebrate community and sediment composition, including species abundance and biomass, and grain size and mud content. The dataset published now contains 51,851 sampled stations with 3,034,760 individuals of 177 species. This paper details data collection, validation and processing methods. SIBES is ongoing and data will be updated yearly. In sharing these data, we hope to enhance collaborations and understanding of the impact of various pressures on macrozoobenthic invertebrates, sediment composition, food webs, the ecosystem, and biodiversity in the Wadden Sea and other intertidal habitats.
An optimized detection model for micro-terrain around transmission lines
Authors: Yi Feng , Hu Chunchun 
Published: February 2025

Abstract
Detecting micro-terrain is essential for the effective layout and maintenance of transmission lines. To address the issues of detection incompleteness, classification ambiguity, and inefficiency in traditional methods, particularly the challenge of distinguishing between saddle and canyon micro-terrain, this paper optimizes the calculation of micro-terrain features and the strategy of micro-terrain detection, and explores a detection method of micro-terrain around transmission lines based on the GPU parallel random forest. This paper employs the GPU parallel random forest model as the extraction framework, leveraging the computational speed advantage of GPU parallel technology for handling large datasets and the robustness inherent in the ensemble approach of random forests. The DEM data of 49 transmission lines in the study area was used for micro-terrain detection experiments. Most of these 49 routes are situated in mountainous regions with complex terrain and contain diverse micro-terrain categories along their paths, rendering them highly representative. The experimental results demonstrate that the proposed method effectively identifies atypical micro-terrain types and four typical micro-terrain types—saddle, canyon, alpine watershed, and uplift—with a classification accuracy of 97.96% and a Kappa coefficient of 0.974. Compared to the traditional method, which achieves a classification accuracy of 75.19% and a Kappa coefficient of 0.642, the proposed method demonstrates a clear improvement in performance. Moreover, by employing the parallel model, the acceleration ratios for training and classification reach 50.57 and 109.06, respectively, significantly improving the efficiency of micro-terrain detection for large-scale regions. These findings could significantly enhance transmission line maintenance and layout planning by providing more accurate micro-terrain data, enabling better decision-making and resource allocation for infrastructure development and disaster risk mitigation.
Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases
Authors: Maehara Hiroki , Ueno Yuta , Yamaguchi Takefumi , Kitaguchi Yoshiyuki , Miyazaki Dai , Nejima Ryohei , Inomata Takenori , Kato Naoko , Chikama Tai-ichiro , Ominato Jun , Yunoki Tatsuya , Tsubota Kinya , Oda Masahiro , Suzutani Manabu , Sekiryu Tetsuju , Oshika Tetsuro 
Published: February 2025

Abstract
CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed for its impact on ophthalmologists’ diagnostic accuracy. In the study, 40 ophthalmologists (20 specialists and 20 residents) classified 100 images, including iPhone 13 Pro photos (50 images) and diffuser slit-lamp photos (50 images), into nine categories (normal condition, infectious keratitis, immunological keratitis, corneal scar, corneal deposit, bullous keratopathy, ocular surface tumor, cataract/intraocular lens opacity, and primary angle-closure glaucoma). The iPhone and slit-lamp images represented the same cases. After initially answering without CorneAI, the same ophthalmologists responded to the same cases with CorneAI 2–4 weeks later. With CorneAI’s support, the overall accuracy of ophthalmologists increased significantly from 79.2 to 88.8% (P < 0.001). Specialists’ accuracy rose from 82.8 to 90.0%, and residents’ from 75.6 to 86.2% (P < 0.001). Smartphone image accuracy improved from 78.7 to 85.5% and slit-lamp image accuracy from 81.2 to 90.6% (both, P < 0.001). In this study, CorneAI’s own accuracy was 86%, but its support enhanced ophthalmologists’ accuracy beyond the CorneAI’s baseline. This study demonstrated that CorneAI, despite being trained on diffuser slit-lamp images, effectively improved diagnostic accuracy, even with smartphone images.
Bipolar electrochemistry-driven wireless drug loading and energy harvesting in conductive hybrid hydrogels
Authors: Da Silva Aruã Clayton , Hu Xiaofeng , Paschoal Vitor Hugo , Hagis Nicholas , Zajac Agnieszka Joanna , Ribeiro Mauro Carlos Costa , Minev Ivan Rusev 
Published: February 2025

Abstract
Bipolar electrochemistry enables wireless and spatially controlled redox reactions on (semi)conductive objects immersed in an electrolyte. Here, we investigate advanced bipolar electrochemistry applications using flexible bipolar electrodes coated with hybrid films of conductive polymer poly(3,4-ethylenedioxythiophene) and alginate hydrogels. These coatings allow for the wireless creation of reversible redox and chemical gradients, providing targeted drug loading and energy harvesting opportunities. We use cyclic voltammetry, electrochemical impedance spectroscopy, Raman microscopy, and X-ray photoelectron spectroscopy to characterize distinct redox regions within the bipolar electrode. The wireless and selective loading of a model drug, fluorescein, into the hydrogel, demonstrated control over drug distribution, suggesting an alternative to conventional uniform doping techniques. Furthermore, cutting the gradient-encoded bipolar electrode and closing an external circuit between the halves, enables energy recovery through a concentration cell mechanism. Our findings illustrate the potential of bipolar electrochemistry in creating versatile platforms that bridge materials science, electrochemistry, and bioelectronics for innovative biomedical and energy applications.
Hearing Loss, Difficulty With Activities of Daily Living, and Experience of Consequences of Related Unmet Needs in Older Adults: A Cross-Sectional Analysis
Authors: Bessen Sarah , Garcia Morales Emmanuel E. , Zhang Wuyang , Martinez-Amezcua Pablo , Umoh Mfon , Cudjoe Thomas K. M. , Schrack Jennifer A. , Reed Nicholas S. 
Published: February 2025

Purpose:
Experiencing difficulty with activities of daily living (ADLs) and instrumental ADLs (IADLs) and/or the consequences of unmet ADL/IADL-related needs is associated with adverse health-related outcomes. The association of hearing loss (HL) with experiencing the consequences of unmet ADL/IADL-related needs is not well understood. We investigated the associations of HL with experiencing ADL/IADL difficulties and the consequences of unmet ADL/IADL-related needs in older adults.

Method:
We investigated cross-sectional associations between audiometric HL, the number of ADL and IADL difficulties, and the number of consequences of unmet ADL/IADL-related needs among adults aged 65 years and older in the National Health and Aging Trends Study.

Results:

In 4,724 older adults, 30.5% (
n
= 1,736) and 30.9% (
n
= 1,727) had self-reported difficulty with ADLs and IADLs, respectively. Of the 2,289 participants who reported difficulty with at least one ADL/IADL, 14.0% (
n
= 741) reported experience of at least one consequence of an unmet ADL/IADL-related need. In multivariable ordinal regression analyses, mild (
OR
= 1.38, 95% CI [1.1, 1.73]) and moderate or greater (
OR
= 1.57, 95% CI [1.17, 2.1]) HL were associated with higher odds of difficulties with additional ADLs. Moderate or greater HL was associated with higher odds of reporting difficulties with additional IADLs (
OR
= 1.59, 95% CI [1.19, 2.12]). There was no significant association between HL and higher odds of having additional consequences of unmet needs.

Conclusions:
Our results show an association between HL and a higher number of ADL and IADL difficulties. Adults with HL may require increased support to address difficulties with daily activities and prevent experiencing related consequences.

Supplemental Material:

https://doi.org/10.23641/asha.28300049
Controlling semantics of diffusion‐augmented data for unsupervised domain adaptation
Authors: Ridley Henrietta , Alcover‐Couso Roberto , SanMiguel Juan C. 
Published: February 2025

AbstractUnsupervised domain adaptation (UDA) offers a compelling solution to bridge the gap between labelled synthetic data and unlabelled real‐world data for training semantic segmentation models, given the high costs associated with manual annotation. However, the visual differences between the synthetic and real images pose significant challenges to their practical applications. This work addresses these challenges through synthetic‐to‐real style transfer leveraging diffusion models. The authors’ proposal incorporates semantic controllers to guide the diffusion process and low‐rank adaptations (LoRAs) to ensure that style‐transferred images align with real‐world aesthetics while preserving semantic layout. Moreover, the authors introduce quality metrics to rank the utility of generated images, enabling the selective use of high‐quality images for training. To further enhance reliability, the authors propose a novel loss function that mitigates artefacts from the style transfer process by incorporating only pixels aligned with the original semantic labels. Experimental results demonstrate that the authors’ proposal outperforms selected state‐of‐the‐art methods for image generation and UDA training, achieving optimal performance even with a smaller set of high‐quality generated images. The authors’ code and models are available at http://www‐vpu.eps.uam.es/ControllingSem4UDA/.