bluuebunny/crossref_metadata_2025_split huggingface dataset:
Upwelling in Cyclonic and Anticyclonic Eddies at the Middle Atlantic Bight Shelf‐Break Front
Authors: Hirzel Andrew J. , Zhang Weifeng (Gordon) , Gawarkiewicz Glen G. , McGillicuddy Dennis J. 
Published: August 2024

AbstractDespite the ubiquity of eddies at the Mid‐Atlantic Bight shelf‐break front, direct observations of frontal eddies at the shelf‐break front are historically sparse and their biological impact is mostly unknown. This study combines high resolution physical and biological snapshots of two frontal eddies with an idealized 3‐D regional model to investigate eddy formation, kinematics, upwelling patterns, and biological impacts. During May 2019, two eddies were observed in situ at the shelf‐break front. Each eddy showed evidence of nutrient and chlorophyll enhancement despite rotating in opposite directions and having different physical characteristics. Our results suggest that cyclonic eddies form as shelf waters are advected offshore and slope waters are advected shoreward, forming two filaments that spiral inward until sufficient water is entrained. Rising isohalines and upwelled slope water dye tracer within the model suggest that upwelling coincided with eddy formation and persisted for the duration of the eddy. In contrast, anticyclonic eddies form within troughs of the meandering shelf‐break front, with amplified frontal meanders creating recirculating flow. Upwelling of subsurface shelf water occurs in the form of detached cold pool waters during the formation of the anticyclonic eddies. The stability properties of each eddy type were estimated via the Burger number and suggest different ratios of baroclinic versus barotropic contributions to frontal eddy formation. Our observations and model results indicate that both eddy types may persist for more than a month and upwelling in both eddy types may have significant impacts on biological productivity of the shelf break.
Seismic Reservoir Characterization With Implicit Neural Representations
Authors: Romero Juan , Heidrich Wolfgang , Luiken Nick , Ravasi Matteo 
Published: August 2024

AbstractSeismic reservoir characterization refers to a set of techniques aimed at estimating static and/or dynamic physical properties of subsurface geological formations from seismic data, with applications ranging from exploration and development of energy resources, geothermal production, carbon capture and storage, and the assessment of geological hazards. Extracting quantitative information from seismic recordings, such as an acoustic impedance model, is however a highly ill‐posed inverse problem due to the band‐limited and noisy nature of the seismic data. As such, seismic inversion techniques strongly rely on additional prior information that penalizes (or promotes) some features in the recovered model. This paper introduces IntraSeismic, a novel hybrid seismic inversion method that combines implicit neural representations as an effective way to parameterize a subsurface model with the physics of the seismic modeling operator. We demonstrate its effectiveness in both pre‐stack and 3D/4D post‐stack seismic inversion using synthetic and field data sets. Key features of IntraSeismic are (a) unparalleled performance in 2D and 3D pre‐stack/post‐stack dynamic and static seismic inversion, (b) rapid convergence rates, (c) ability to seamlessly include hard constraints (i.e., well data) and perform uncertainty quantification, and (d) potential data compression and fast randomized access to specific portions of the inverted model.
Sea Level Modulation of Atlantic Nitrogen Fixation Over Glacial Cycles
Authors: Auderset Alexandra , Fripiat François , Creel Roger C. , Oesch Lukas , Studer Anja S. , Repschläger Janne , Hathorne Ed , Vonhof Hubert , Schiebel Ralf , Gordon Laura , Lawrence Kira , Ren Haojia Abby , Haug Gerald H. , Sigman Daniel M. , Martínez‐García Alfredo 
Published: August 2024

AbstractN2 fixation in low‐latitude surface waters dominates the input of fixed nitrogen (N) to the global ocean, sustaining ocean fertility. In the Caribbean Sea, higher foraminifera‐bound (FB‐)δ15N indicates a decline in N2 fixation during ice ages, but its cause and broader implications are unclear. Here, we report three additional Atlantic FB‐δ15N records, from the subtropical North and South Atlantic gyres (MSM58‐50 and DSDP Site 516) and the equatorial Atlantic (ODP Site 662). Similar glacial and interglacial δ15N in the equatorial Atlantic suggests a stable δ15N for the nitrate below the gyre thermoclines. The North Atlantic record shows a FB‐δ15N rise during the ice ages, resembling a previously published FB‐δ15N record from the South China Sea. The commonality among the FB‐δ15N records is that they resemble sea level‐driven variation in regional shelf area, with high FB‐δ15N (inferred reduction in N2 fixation) during periods of low shelf area. The South China Sea shows the largest δ15N signal, the subtropical North Atlantic shows less, and the South Atlantic shows the least, the same ordering as the ice age reductions in continental shelf area in the different regions. Reduced shelf sedimentary denitrification would have increased the nitrogen‐to‐phosphorus ratio of the nutrient supply to open ocean surface waters, leading to decreased N2 fixation and thus higher gyre thermocline nitrate δ15N, explaining the higher FB‐δ15N of peak ice ages. These observations identify shelf sediment denitrification as an important regional driver of modern N2 fixation and imply strong basin‐scale coupling of fixed nitrogen losses and inputs.
Targeting miR-497-5p rescues human keratinocyte dysfunction upon skin exposure to sulfur mustard
Authors: Egea Virginia , Lutterberg Karina , Steinritz Dirk , Rothmiller Simone , Steinestel Konrad , Caca Jan , Nerlich Andreas , Blum Helmut , Reschke Sarah , Khani Sajjad , Bartelt Alexander , Worek Franz , Thiermann Horst , Weber Christian , Ries Christian 
Published: August 2024

AbstractSulfur mustard (SM) is a highly toxic chemical warfare agent. Exposure to SM results in various pathologies including skin lesions with subsequent impaired wound healing. To date, there are no effective treatments available. Here we discover a SM-triggered pathomechanism involving miR-497-5p and its target survivin which contributes to keratinocyte dysfunction. Transcriptome analysis using RNA-seq in normal human epidermal keratinocytes (NHEK) revealed that SM evoked differential expression of 1896 mRNAs and 25 miRNAs with many of these RNAs known to be involved in keratinocyte function and wound healing. We demonstrated that keratinocyte differentiation and proliferation were efficiently regulated by miRNAs induced in skin cells after exposure to SM. The inhibition of miR-497-5p counteracted SM-induced premature differentiation and stimulated proliferation of NHEK. In addition, we showed that microneedle-mediated transdermal application of lipid-nanoparticles containing miR-497-5p inhibitor restored survivin biosynthesis and cellular functionality upon exposure to SM using human skin biopsies. Our findings expand the current understanding of SM-associated molecular toxicology in keratinocytes and highlight miR-497-5p as feasible clinical target for specific skin therapy in SM-exposed patients and beyond.
Molecular control via dynamic bonding enables material responsiveness in additively manufactured metallo-polyelectrolytes
Authors: Lee Seola , Walker Pierre J. , Velling Seneca J. , Chen Amylynn , Taylor Zane W. , Fiori Cyrus J.B.M , Gandhi Vatsa , Wang Zhen-Gang , Greer Julia R. 
Published: August 2024

AbstractMetallo-polyelectrolytes are versatile materials for applications like filtration, biomedical devices, and sensors, due to their metal-organic synergy. Their dynamic and reversible electrostatic interactions offer high ionic conductivity, self-healing, and tunable mechanical properties. However, the knowledge gap between molecular-level dynamic bonds and continuum-level material properties persists, largely due to limited fabrication methods and a lack of theoretical design frameworks. To address this critical gap, we present a framework, combining theoretical and experimental insights, highlighting the interplay of molecular parameters in governing material properties. Using stereolithography-based additive manufacturing, we produce durable metallo-polyelectrolytes gels with tunable mechanical properties based on metal ion valency and polymer charge sparsity. Our approach unveils mechanistic insights into how these interactions propagate to macroscale properties, where higher valency ions yield stiffer, tougher materials, and lower charge sparsity alters material phase behavior. This work enhances understanding of metallo-polyelectrolytes behavior, providing a foundation for designing advanced functional materials.
Emergence of fluctuating hydrodynamics in chaotic quantum systems
Authors: Wienand Julian F. , Karch Simon , Impertro Alexander , Schweizer Christian , McCulloch Ewan , Vasseur Romain , Gopalakrishnan Sarang , Aidelsburger Monika , Bloch Immanuel 
Published: August 2024

AbstractA fundamental principle of chaotic quantum dynamics is that local subsystems eventually approach a thermal equilibrium state. The corresponding timescales increase with subsystem size as equilibration is limited by the hydrodynamic build-up of fluctuations on extended length scales. We perform large-scale quantum simulations that monitor particle-number fluctuations in tunable ladders of hard-core bosons and explore how the build-up of fluctuations changes as the system crosses over from integrable to fully chaotic dynamics. Our results indicate that the growth of large-scale fluctuations in chaotic, far-from-equilibrium systems is quantitatively determined by equilibrium transport coefficients, in agreement with the predictions of fluctuating hydrodynamics. This emergent hydrodynamic behaviour of subsystem fluctuations provides a test of fluctuation–dissipation relations far from equilibrium and allows the accurate determination of equilibrium transport coefficients using far-from-equilibrium quantum dynamics.
Benchmarking bacterial taxonomic classification using nanopore metagenomics data of several mock communities
Authors: Van Uffelen Alexander , Posadas Andrés , Roosens Nancy H. C. , Marchal Kathleen , De Keersmaecker Sigrid C. J. , Vanneste Kevin 
Published: August 2024

AbstractTaxonomic classification is crucial in identifying organisms within diverse microbial communities when using metagenomics shotgun sequencing. While second-generation Illumina sequencing still dominates, third-generation nanopore sequencing promises improved classification through longer reads. However, extensive benchmarking studies on nanopore data are lacking. We systematically evaluated performance of bacterial taxonomic classification for metagenomics nanopore sequencing data for several commonly used classifiers, using standardized reference sequence databases, on the largest collection of publicly available data for defined mock communities thus far (nine samples), representing different research domains and application scopes. Our results categorize classifiers into three categories: low precision/high recall; medium precision/medium recall, and high precision/medium recall. Most fall into the first group, although precision can be improved without excessively penalizing recall with suitable abundance filtering. No definitive ‘best’ classifier emerges, and classifier selection depends on application scope and practical requirements. Although few classifiers designed for long reads exist, they generally exhibit better performance. Our comprehensive benchmarking provides concrete recommendations, supported by publicly available code for reassessment and fine-tuning by other scientists.
A new dataset for video-based cow behavior recognition
Authors: Li Kuo , Fan Daoerji , Wu Huijuan , Zhao Aruna 
Published: August 2024

AbstractA new video based multi behavior dataset for cows, CBVD-5, is introduced in this paper. The dataset includes five cow behaviors: standing, lying down, foraging,rumination and drinking. The dataset comprises 107 cows from the entire barn, maintaining an 80% stocking density. Monitoring occurred over 96 h for these 20-month-old cows, considering varying light conditions and nighttime data to ensure standardization and inclusivity.The dataset consists of ranch monitoring footage collected by seven cameras, including 687 video segment samples and 206,100 image samples, covering five daily behaviors of cows. The data collection process entailed the deployment of cameras, hard drives, software, and servers for storage. Data annotation was conducted using the VIA web tool, leveraging the video expertise of pertinent professionals. The annotation coordinates and category labels of each individual cow in the image, as well as the generated configuration file, are also saved in the dataset. With this dataset,we propose a slowfast cow multi behavior recognition model based on video sequences as the baseline evaluation model. The experimental results show that the model can effectively learn corresponding category labels from the behavior type data of the dataset, with an error rate of 21.28% on the test set. In addition to cow behavior recognition, the dataset can also be used for cow target detection, and so on.The CBVD-5 dataset significantly influences dairy cow behavior recognition, advancing research, enriching data resources, standardizing datasets, enhancing dairy cow health and welfare monitoring, and fostering agricultural intelligence development. Additionally, it serves educational and training needs, supporting research and practical applications in related fields. The dataset will be made freely available to researchers world-wide.
Inferring building height from footprint morphology data
Authors: Stipek Clinton , Hauser Taylor , Adams Daniel , Epting Justin , Brelsford Christa , Moehl Jessica , Dias Philipe , Piburn Jesse , Stewart Robert 
Published: August 2024

AbstractAs cities continue to grow globally, characterizing the built environment is essential to understanding human populations, projecting energy usage, monitoring urban heat island impacts, preventing environmental degradation, and planning for urban development. Buildings are a key component of the built environment and there is currently a lack of data on building height at the global level. Current methodologies for developing building height models that utilize remote sensing are limited in scale due to the high cost of data acquisition. Other approaches that leverage 2D features are restricted based on the volume of ancillary data necessary to infer height. Here, we find, through a series of experiments covering 74.55 million buildings from the United States, France, and Germany, it is possible, with 95% accuracy, to infer building height within 3 m of the true height using footprint morphology data. Our results show that leveraging individual building footprints can lead to accurate building height predictions while not requiring ancillary data, thus making this method applicable wherever building footprints are available. The finding that it is possible to infer building height from footprint data alone provides researchers a new method to leverage in relation to various applications.
Age-related changes in ultrasound-assessed muscle composition and postural stability
Authors: Mongold Scott J. , Georgiev Christian , Naeije Gilles , Vander Ghinst Marc , Stock Matt S. , Bourguignon Mathieu 
Published: August 2024

AbstractWhile the simultaneous degradation of muscle composition and postural stability in aging are independently highly investigated due to their association with fall risk, the interplay between the two has received little attention. Thus, the purpose of this study is to explore how age-related changes in muscle composition relate to postural stability. To that aim, we collected posturography measures and ultrasound images of the dominant Vastus Lateralis and Biceps Brachii from 32 young (18–35 year old) and 34 older (65–85 year old) participants. Muscle properties were quantified with echo-intensity and texture-based metrics derived from gray-level co-occurrence matrix analysis, and postural stability with the variability of the center of pressure during bipedal stance tasks. Ultrasound parameters revealed that young muscle possessed lower echo-intensity and higher homogeneity compared to the elderly. Echo-intensity and muscle thickness, and several texture-based parameters possessed outstanding young versus older classification performance. A canonical correlation analysis demonstrated a significant relationship between ultrasound and postural measures only within the young group (r = 0.53, p < 0.002), where those with ‘better’ muscle composition displayed larger postural sways. Our results indicate that, in older individuals, postural stability and muscle composition, two common fall risk factors, are unrelated. In view of this decoupling, both may contribute independently to fall risk. Furthermore, our data support the view that texture-based parameters provide a robust alternative to echo-intensity in providing markers of muscle composition.
Identification of BiP as a temperature sensor mediating temperature-induced germline sex reversal in C. elegans
Authors: Shi Jing , Sheng Danli , Guo Jie , Zhou Fangyuan , Wu Shaofeng , Tang Hongyun 
Published: August 2024

AbstractSex determination in animals is not only determined by karyotype but can also be modulated by environmental cues like temperature via unclear transduction mechanisms. Moreover, in contrast to earlier views that sex may exclusively be determined by either karyotype or temperature, recent observations suggest that these factors rather co-regulate sex, posing another mechanistic mystery. Here, we discovered that certain wild-isolated and mutant C. elegans strains displayed genotypic germline sex determination (GGSD), but with a temperature-override mechanism. Further, we found that BiP, an ER chaperone, transduces temperature information into a germline sex-governing signal, thereby enabling the coexistence of GGSD and temperature-dependent germline sex determination (TGSD). At the molecular level, increased ER protein-folding requirements upon increased temperatures lead to BiP sequestration, resulting in ERAD-dependent degradation of the oocyte fate-driving factor, TRA-2, thus promoting male germline fate. Remarkably, experimentally manipulating BiP or TRA-2 expression allows to switch between GGSD and TGSD. Physiologically, TGSD allows C. elegans hermaphrodites to maintain brood size at warmer temperatures. Moreover, BiP can also influence germline sex determination in a different, non-hermaphroditic nematode species. Collectively, our findings identify thermosensitive BiP as a conserved temperature sensor in TGSD, and provide mechanistic insights into the transition between GGSD and TGSD.
Nighttime wildlife object detection based on YOLOv8‐night
Authors: Wang Tianyu , Ren Siyu , Zhang Haiyan 
Published: August 2024

AbstractMonitoring nocturnal animals in the field is an important task in ecological research and wildlife conservation, but the complexity of nocturnal images and low light conditions make it difficult to cope with traditional image processing methods. To address this problem, researchers have introduced infrared cameras to improve the accuracy of nocturnal animal behaviour observations. Object detection in nighttime images captured by infrared cameras faces several challenges, including low image quality, animal scale variations, occlusion, and pose changes. This study proposes the YOLOv8‐night model, which effectively overcomes these challenges by introducing a channel attention mechanism in YOLOv8. The model is more focused on capturing animal‐related features by dynamically adjusting the channel weights, which improves the saliency of key features and increases the accuracy rate in complex backgrounds. The main contribution of this study is the introduction of the channel attention mechanism into the YOLOv8 framework to create a YOLOv8‐night model suitable for object detection in nighttime images. When tested on nighttime images, the model performs well with a significantly higher mAP (0.854) than YOLOv8 (0.831), and YOLOv8‐night scores 0.856 on mAP_l, which is obviously better than YOLOv8 (0.833) in terms of processing large objects. The study provides a reliable technical tool for ecological research, wildlife conservation and environmental monitoring, and offers new methods and insights for the study of nocturnal animal behaviour.
A Wasserstein distributionally robust model for transmission expansion planning with renewable‐based microgrid penetration
Authors: Rahim Sahar , Wang Zhen , Sun Ke , Chen Hangcheng 
Published: August 2024

AbstractThis article introduces a Wasserstein distance‐based distributionally robust optimization model to address the transmission expansion planning considering renewable‐based microgrids (MGs) under the impact of uncertainties. The primary objective of the presented methodology is to devise a robust expansion strategy that accounts for both long‐term uncertainty and short‐term variability over the planning horizon from the perspective of a central planner. In this framework, the central planner fosters the construction of appropriate transmission lines and the deployment of optimal MG‐based generating units among profit‐driven private investors. The Wasserstein distance uncertainty set is used to characterize the long‐term uncertainty associated with future load demand. Short‐term uncertainties, stemming from variations in load demands and production levels of stochastic units, are modeled through operating conditions. To ensure the tractability of the proposed planning model, the authors introduce a decomposition framework embedded with a modified application of Bender's method. To validate the efficiency and highlight the potential benefits of the proposed expansion planning methodology, two case studies based on simplified IEEE 6‐bus and IEEE 118‐bus systems are included. These case studies assess the effectiveness of the presented approach, its ability to navigate uncertainties, and its capacity to effectively optimize expansion decisions.
A detailed reinforcement learning framework for resource allocation in non‐orthogonal multiple access enabled‐B5G/6G networks
Authors: Omheni Nouri , Amiri Anis , Zarai Faouzi 
Published: August 2024

AbstractThe world of communications technology has recently undergone an extremely significant revolution. This revolution is an immediate consequence of the immersion that the fifth generation B5G and 6G have just brought. The latter responds to the growing need for connectivity and it improves the speeds and qualities of the mobile connection. To improve the energy and spectral efficiency of these types of networks, the non‐orthogonal multiple access (NOMA) technique is seen as the key solution that can accommodate more users and dramatically improve spectrum efficiency. The basic idea of NOMA is to achieve multiple access in the power sector and decode the required signal via continuous interference cancelation. A resource allocation approach is proposed for the B5G/6G‐NOMA network that aims to maximise system throughput, spectrum and energy efficiency and fairness among users while minimising latency. The proposed approach is based on reinforcement learning (RL) with the use of the Q‐Learning algorithm. First, the process of resource allocation as a problem of maximising rewards is formulated. Next, the Q‐Learning algorithm is used to design a resource allocation algorithm based on RL. The results of the simulation confirm that the proposed scheme is feasible and efficient.