bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Popular Politics of Local Petitioning in Early Modern England
Authors: Waddell Brodie 
Published: April 2024

AbstractThis article examines the rise of a culture of local petitioning, through which growing numbers of ordinary people sought to win the support of state authorities through collective claims to represent the “voice of the people” at the local level. These participatory, subscriptional practices were an essential component in the intensification of popular politics in the seventeenth century. The analysis focuses on over 3,800 manuscript petitions submitted to the magistrates across fifteen jurisdictions with “sessions of the peace” in England, with nearly 1,000 dating from before 1640. Over the course of the early seventeenth century many, if not most, English parishes witnessed attempts to persuade the authorities through collective petitioning. Groups of neighbors across the kingdom formulated their grievances, organized subscription lists, and articulated their own role in the polity as “the inhabitants” or “the parishioners” of a particular community. In so doing, they not only directly shaped their own “little commonwealths” but also unintentionally helped to develop habits of political mobilization in a crucial period of English history.
Comparison of nonlinear functions to describe lactation curves for cumulative milk production in buffalo
Authors: Darmani Kuhi Hassan , López Secundino , Ghavi Hossein-Zadeh Navid , France James 
Published: April 2024

AbstractThe aim of this study was to examine the suitability of different growth functions (linear, sinusoidal, Gompertz, Schumacher and Richards) to fit cumulative milk production data from buffalo cows. Cumulative milk production at each day in milk was calculated from two published datasets reporting (i) fortnightly test-day milk yield records of the first lactation of Murrah buffalo that had calved during 1977–2012 and (ii) the first lactation records of Jaffarabadi buffalo collected from history-cum-pedigree registers for each quinquennium between 1991 and 2010. Each function was fitted to the lactation curves using nonlinear regression procedures. The Richards and sinusoidal equations provided the smallest root mean square error values, Akaike's and Bayesian information criteria and, therefore, the best fit for the cumulative lactation curves for milk yield. The Richards equation appeared to provide the most accurate estimate of the cumulative milk production at peak milk yield. Sinusoidal and flexible classical growth functions are appropriate to describe cumulative milk production curves and estimate lactation traits in buffalo.
US-wide equine strongylid egg count data demonstrate seasonal and regional trends
Authors: Nielsen Martin K. , Slusarewicz Paul , Kuzmina Tetiana A. , Denwood Matthew J. 
Published: April 2024

AbstractEquine strongylid parasites are ubiquitous around the world and are main targets of parasite control programmes. In recent years, automated fecal egg counting systems based on image analysis have become available allowing for collection and analysis of large-scale egg count data. This study aimed to evaluate equine strongylid fecal egg count (FEC) data generated with an automated system over three years in the US with specific attention to seasonal and regional trends in egg count magnitude and sampling activity. Five US regions were defined; North East, South East, North Central, South Central and West. The data set included state, region and zip code for each FEC. The number of FECs falling in each of the following categories were recorded: (1) 0 eggs per gram (EPG), (2) 1 ⩽ 200 EPG, (3) 201 ⩽ 500 EPG and (4) >500 EPG. The data included 58 329 FECs. A fixed effects model was constructed fitting the number of samples analysed per month, year and region, and a mixed effects model was constructed to fit the number of FECs falling in each of the 4 egg count categories defined above. The overall proportion of horses responsible for 80% of the total FEC output was 18.1%, and this was consistent across years, months and all regions except West, where the proportion was closer to 12%. Statistical analyses showed significant seasonal trends and regional differences of sampling frequency and FEC category. The data demonstrated that veterinarians tended to follow a biphasic pattern when monitoring strongylid FECs in horses, regardless of location.
Effects of retrieval schedules on the acquisition of explicit, automatized-explicit, and implicit knowledge of L2 collocations
Authors: Fang Nan , Elgort Irina , Chen Zhuo 
Published: April 2024

AbstractThis study investigates the effects of retrieval schedules on the acquisition of second language (L2) collocations. Chinese learners of English first studied 36 target verb-noun collocations using flashcards and form-meaning matching practice. Subsequently, the participants practiced retrieving the target collocations from memory, following either a massed (consecutive) or spaced schedule. After each retrieval attempt, corrective feedback was provided. The acquisition of L2 collocations was measured by near-immediate and 1-week delayed posttests that assessed explicit knowledge with an offline form recall task, automatized explicit knowledge using an online acceptability judgment task, and implicit knowledge with an online collocation priming (lexical decision) task. Results showed equal learning effects of massed and spaced retrieval at both posttests of explicit knowledge and the near-immediate posttest of automatized explicit knowledge. The spacing effect was observed for the implicit knowledge across the two posttests and the automatized explicit knowledge at the delayed posttest.
KOBAYASHI-OCHIAI’S FINITENESS THEOREM FOR ORBIFOLD PAIRS OF GENERAL TYPE
Authors: Bartsch Finn , Javanpeykar Ariyan 
Published: April 2024

AbstractKobayashi–Ochiai proved that the set of dominant maps from a fixed variety to a fixed variety of general type is finite. We prove the natural extension of their finiteness theorem to Campana’s orbifold pairs.
Modeling weed seedling emergence for time-specific weed management: a systematic review
Authors: Marschner Caroline A. , Colucci Isabella , Stup Rebecca S. , Westbrook Anna S. , Brunharo Caio A. C. G. , DiTommaso Antonio , Mesgaran Mohsen B. 
Published: April 2024

AbstractUnderstanding the timing of weed emergence is crucial to effective management. Management practices implemented too early may fail to completely control late-emerging seedlings, whereas management practices implemented too late will suffer from low efficacy. Weed emergence times reflect biological factors, such as seed dormancy and germination requirements, as well as environmental conditions. We conducted a systematic review of studies that developed models to predict weed emergence temporal patterns. We screened 1,854 studies, 98 of which were included in the final dataset. Most of the studies included were conducted in North America (51%) or Europe (30%). A wide variety of weed species (102) and families (21) were included, and many studies modeled several weeds. Grass weeds (Poaceae) were modeled most frequently (83 instances). Most weeds (40%) had base temperature
${T_{\rm{b}}}$
values between 0 and 5 C, and 38% had base water potential
${{\rm{\psi }}_{\rm{b}}}$
ranging from −1.0 to −0.5 MPa. Most studies used empirical parametric models, such as Weibull (40%) or Gompertz (30%) models. Nonparametric and mechanistic models were also represented. Models varied in their biological and environmental data requirements. In general, empirical parametric models based on hydrothermal time (i.e., time above base temperature and water potential thresholds) represented a good balance between ease of use and prediction accuracy. Soft computing approaches such as artificial neural networks demonstrated substantial potential in situations with complex emergence patterns and limited data availability, although they (soft computing approaches) can be susceptible to overfitting. Our study also demonstrated variability in model performance and limited generalizability across species and regions. This finding underscores the need for context-specific and well-validated weed emergence models to inform management, especially in the context of climate change.
Enhancing Quantitative Precipitation Estimation of NWP Model With Fundamental Meteorological Variables and Transformer Based Deep Learning Model
Authors: Liu Haolin , Fung Jimmy C. H. , Lau Alexis K. H. , Li Zhenning 
Published: April 2024

AbstractQuantitative precipitation forecasting in numerical weather prediction (NWP) models is contingent upon physicals parameterization schemes. However, uncertainties abound due to limited knowledge of the precipitating processes, leading to degraded forecasting skills. In light of this, our study explores the application of a Swin‐Transformer based deep learning (DL) model as a supplementary tool for enhancing the mapping trajectory between the NWP fundamental variables and the most downstream variable precipitation. Constrained by the observational satellite precipitation product from NOAA CPC Morphing Technique (CMORPH), the DL model serves as the post‐processing tool that can better resolve the precipitation patterns compared to solely based on NWP estimation. Compared to the baseline Weather Research and Forecasting simulation, the DL post‐processing effectively extracts features over meteorological variables, leading to improved precipitation skill scores of 21.7%, 60.5%, and 45.5% for light rain, moderate rain, and heavy rain, respectively, on an hourly basis. We also evaluate two case studies under different driven synoptic conditions and show promising results in estimating heavy precipitation during strong convective precipitation events. Overall, the proposed DL model can provide a vital reference for capturing precipitation‐triggering mechanisms and enhancing precipitation forecasting skills. Additionally, we discuss the sensitivities of the fundamental meteorological variables used in this study, training strategies, and performance limitations.
Morphological and Elemental Classification of Freshly‐Emitted Individual Particles From Field and Laboratory Residential Biomass Burning
Authors: Zhang Yinxiao , Li Weijun , Zhang Jian , Ding Xiaokun , Yuan Qi , Liu Lei , Xu Liang , Wang Yuanyuan , Jiang Xiaotong , Ma Wenlai , Cao Juan , Kong Shaofei , Liu Dantong , Sun Yele 
Published: April 2024

AbstractResidential biomass burning significantly contributes to air pollution in developing countries. However, the microscopic properties of individual particles in their emissions have not been well understood. In this study, individual primary particles from 14 kinds of biomass fuels (including firewood, crop residue, and animal dung) were collected in laboratory and field measurements, and their morphology, composition and mixing state were acquired using transmission electron microscope. These results constitute a source profile database of individual primary particles from residential biomass burning. The database reveals that different types of biomass fuels exhibit different emission characteristics, that is, residential firewood burning mainly emits pure carbonaceous particles (including organic matter (OM) and soot particles), crop residue burning mainly emits K‐containing particles (including OM‐K, soot(‐OM)‐K, and K‐rich particles), and animal dung burning mainly emits pure carbonaceous particles and K‐containing particles. Moreover, our results indicate that the emission characteristics obtained from laboratory and field measurements are different. Field measurements conducted in two selected villages in North China Plain exhibit a higher presence of soot particles compared to laboratory measurements, owing to their higher combustion temperatures. In contrast, field measurements conducted in one selected village in Qinghai‐Tibet Plateau contain less soot particles than those from laboratory measurements in plain areas, due to the deficient oxygen supply during combustion process in the high‐altitude regions. These results warn us that the emission estimation from residential biomass burning should notice the large emission differences among different biomass types and between field and laboratory measurements.
A New Comprehensive Cloud Macrophysics Scheme With a Prognostic Dual‐Triangular PDF
Authors: Song Chanwoo , Park Sungsu 
Published: April 2024

AbstractTo improve cloud simulation in a general circulation model, we develop a new cloud macrophysics scheme that treats detrained cumulus generated by convective detrainment process separately from pure stratus; prognoses two symmetric triangular probability density functions of total specific humidity for each detrained cumulus and pure stratus; and diagnoses both cloud fraction and cloud condensate in all liquid, ice, and mixed‐phases in a consistent and unified way without any adjustment to remove empty or very dense cloud. Supersaturation is allowed within ice cloud. The new scheme (“NEW”) is compared with the previous model (“OLD”) using single‐column simulations for subtropical marine stratocumulus (DYCOMS2) and continental deep convection (ARM97) cases. In DYCOMS2, both NEW and OLD produce vertical profiles of grid‐mean cloud condensate similar to large‐eddy simulation. In ARM97, compared with OLD, NEW simulates less sporadic vertical profiles of in‐cloud condensates, due to consistent diagnosis of cloud fraction and cloud condensate; more continuously‐varying detrained cumulus with time, due to prognostic treatment of detrained cumulus; and ice cloud fraction and ice condensate similar to those of OLD, in spite of completely different treatment of ice cloud processes. The global performance of NEW is similar to OLD with improved relative humidity. Compared to OLD, NEW simulates more and improved cloud condensate, but less and degraded cloud fraction, particularly, in the lower troposphere. Detrained cumulus is moister and colder and has a larger moisture variance than pure stratus. Overall, NEW simulates stronger condensation‐deposition rates than OLD, due in part to the separate treatment of detrained cumulus and pure stratus.
Statistical Analysis of Ionospheric Correlation for Shortwave System
Authors: Lv Mingjie , Tang Qiong , Qiao Jiandong , Qiao Wei , Zhou Chen 
Published: April 2024

AbstractStatistical analysis of the temporal and spatial variations in the ionosphere is necessary to improve the shortwave system. Based on the standardized Euclidean distance algorithm, multisource ionospheric assimilation data, International GNSS Service vertical total electron content data, and ionosonde data are used to statistically analyze the ionospheric correlation distance, and the variation of ionospheric correlation distances with local times, magnetic latitudes, and seasons are obtained. The statistical analysis results show that the zonal ionospheric correlation distance presents minima in the equatorial ionospheric anomaly crest regions. Additionally, the meridional correlation distance in middle magnetic latitudes is greater than that in other regions. The zonal ionospheric correlation distance presents obvious local‐time variability. The variation trends of the meridional and zonal correlation distance during spring and autumn are similar. The patterns of the ionospheric correlation range variation with local times, magnetic latitudes, and seasons can be used to select the optimal locations or spacing for ionosonde stations, shortwave multi‐station systems, and shortwave radio beacons.
Thank You to Our GeoHealth 2023 Reviewers
Authors: Nguyen Thanh H. , Filippelli Gabriel , Anenberg Susan C. , Franklin Meredith , Fu Tzung‐May , Dey Sagnik , Hudson‐Edwards Karen , Jiang Sunny , Jutla Antarpreet , Liu Yang , Miao Chiyuan , Paytan Adina , Vengosh Avner 
Published: April 2024

AbstractPeer‐review is the foundation and the safeguard of scientific research. Without the dedication of our reviewers, the journal would not have been successful. In 2023, 269 reviewers completed 434 reviews for the 174 manuscripts submitted to GeoHealth. Our reviewers are from all continents except Antarctica. Besides reviewers from North America, China, Europe, and China, we started to have reviewers from India, Latin America, and Africa. GeoHealth editorial board is committed to expanding the readership, authorship, and reviewership to other countries. If you have already reviewed for us, no matter where or who you are, we hope you and your colleagues will consider GeoHealth a home for your work. Below is the list of reviewers who completed more than two reviews or have outstanding quality reviews. Two of our reviewers are being nominated for AGU best reviewers awards.
Spatial Evolution Characteristics of Plasmapause Surface Wave During a Geomagnetic Storm on 16 July 2017
Authors: Zhou Yi‐Jia , He Fei , Archer Martin O. , Zhang Xiao‐Xin , Hao Y. X. , Yao Zhong‐Hua , Rong Zhaojin , Wei Yong 
Published: April 2024

AbstractBoundary dynamics are crucial for the transport of energy, mass, and momentum in geospace. The recently discovered plasmapause surface wave (PSW) plays a key role in the inner magnetosphere dynamics. However, a comprehensive investigation of spatial variations of the PSW remains absent. In this study, we elucidate the spatial characteristics of a PSW through observations from multiple spacecrafts in the magnetosphere. Following the initiation of the PSW, quasi‐periodic injections of energetic ions, rather than electrons, are suggested to serve as energy source of the PSW. Based on the distinct wave and particle signatures, we categorize the PSW into four regions: seed region, growth region, stabilization region and decay region, spanning from nightside to afternoon plasmapause. These findings advance our understanding of universal boundary dynamics and contribute to a deeper comprehension of the pivotal roles of surface waves in the energy couplings within the magnetosphere‐plasmasphere‐ionosphere system.
Iron‐Rich Grain‐Decorated Depressions on Surfaces of Lunar Impact Glasses
Authors: Yan Pan , Xiao Zhiyong , Wu Yanxue , Pan Qing , Wu Yunhua 
Published: April 2024

AbstractIron‐rich particles are widespread on the surfaces and interiors of lunar impact glasses, and they record delicate physicochemical processes during space weathering and regolith gardening on the Moon. Different from nanophase iron in amorphous rims of regolith minerals, iron‐rich particles in lunar impact glasses are mostly larger than 10 nm and are spherical and semi‐hemispherical in shape. In regolith samples returned by Luna, Apollo and Chang'E‐5 missions, a special form of microscopic iron‐rich structure commonly exists on surfaces of impact glasses, which appear as rimless depressions that are filled with nano‐sized grains. Termed grain‐decorated iron‐rich depressions, their possible origin is elusive. Here we perform detailed observations of the morphology, composition and crystallography of these microstructures, showing that they are not degassing pits that were later filled with nano‐sized grains as has been previously considered. They are hemispherical integrated compounds of α‐Fe and troilite that have variable area proportion. The surface grains are dominated by α‐Fe, which mainly develop on top of vesiculated surfaces of the underlying troilite. The α‐Fe grains are mainly formed by desulphurization of troilite due to radiation and heating. While iron‐rich grain‐decorated depressions have larger diameters and different surface morphologies compared to other iron‐rich microstructures in lunar impact glasses, their identical occurrences and phase components (α‐Fe and troilite) suggest a common origin caused by liquid immiscibility between Fe‐S melt and silicate melt. Their diverse surface morphology is mainly caused by heterogeneous S contents and local ratios of Fe and S in silicate impact melt.
epHero – a tandem-fluorescent probe to track the fate of apoptotic cells during efferocytosis
Authors: Singh Sanjna , Bensalem Julien , Hein Leanne K. , Casey Aaron , Mäkinen Ville-Petteri , Sargeant Timothy J. 
Published: April 2024

AbstractThe efficient removal of apoptotic cells via efferocytosis is critical for maintaining optimal tissue function. This involves the binding and engulfment of apoptotic cells by phagocytes and the subsequent maturation of the phagosome, culminating in lysosomal fusion and cargo destruction. However, current approaches to measure efferocytosis rely on labelling apoptotic targets with fluorescent dyes, which do not sufficiently distinguish between changes to the engulfment and acidification of apoptotic material. To address this limitation, we have developed a genetically coded ratiometric probe epHero which when expressed in the cytoplasm of target cells, bypasses the need for additional labelling steps. We demonstrate that epHero is a pH-sensitive reporter for efferocytosis and can be used to simultaneously track changes to apoptotic cell uptake and acidification, both in vitro and in mice. As proof-of-principle, we modify extracellular nutrition to show how epHero can distinguish between changes to cargo engulfment and acidification. Thus, tracking efferocytosis with epHero is a simple, cost-effective improvement on conventional techniques.
Molecular robotic agents that survey molecular landscapes for information retrieval
Authors: Woo Sungwook , Saka Sinem K. , Xuan Feng , Yin Peng 
Published: April 2024

AbstractDNA-based artificial motors have allowed the recapitulation of biological functions and the creation of new features. Here, we present a molecular robotic system that surveys molecular environments and reports spatial information in an autonomous and repeated manner. A group of molecular agents, termed ‘crawlers’, roam around and copy information from DNA-labeled targets, generating records that reflect their trajectories. Based on a mechanism that allows random crawling, we show that our system is capable of counting the number of subunits in example molecular complexes. Our system can also detect multivalent proximities by generating concatenated records from multiple local interactions. We demonstrate this capability by distinguishing colocalization patterns of three proteins inside fixed cells under different conditions. These mechanisms for examining molecular landscapes may serve as a basis towards creating large-scale detailed molecular interaction maps inside the cell with nanoscale resolution.
Reversibility of quantum resources through probabilistic protocols
Authors: Regula Bartosz , Lami Ludovico 
Published: April 2024

AbstractAmong the most fundamental questions in the manipulation of quantum resources such as entanglement is the possibility of reversibly transforming all resource states. The key consequence of this would be the identification of a unique entropic resource measure that exactly quantifies the limits of achievable transformation rates. Remarkably, previous results claimed that such asymptotic reversibility holds true in very general settings; however, recently those findings have been found to be incomplete, casting doubt on the conjecture. Here we show that it is indeed possible to reversibly interconvert all states in general quantum resource theories, as long as one allows protocols that may only succeed probabilistically. Although such transformations have some chance of failure, we show that their success probability can be ensured to be bounded away from zero, even in the asymptotic limit of infinitely many manipulated copies. As in previously conjectured approaches, the achievability here is realised through operations that are asymptotically resource non-generating, and we show that this choice is optimal: smaller sets of transformations cannot lead to reversibility. Our methods are based on connecting the transformation rates under probabilistic protocols with strong converse rates for deterministic transformations, which we strengthen into an exact equivalence in the case of entanglement distillation.