bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrative taxonomy clarifies the evolution of a cryptic primate clade
Authors: van Elst Tobias , Sgarlata Gabriele M. , Schüßler Dominik , Tiley George P. , Poelstra Jelmer W. , Scheumann Marina , Blanco Marina B. , Aleixo-Pais Isa G. , Rina Evasoa Mamy , Ganzhorn Jörg U. , Goodman Steven M. , Hasiniaina Alida F. , Hending Daniel , Hohenlohe Paul A. , Ibouroi Mohamed T. , Iribar Amaia , Jan Fabien , Kappeler Peter M. , Le Pors Barbara , Manzi Sophie , Olivieri Gillian , Rakotonanahary Ando N. , Rakotondranary S. Jacques , Rakotondravony Romule , Ralison José M. , Ranaivoarisoa J. Freddy , Randrianambinina Blanchard , Rasoloarison Rodin M. , Rasoloharijaona Solofonirina , Rasolondraibe Emmanuel , Teixeira Helena , Zaonarivelo John R. , Louis Edward E. , Yoder Anne D. , Chikhi Lounès , Radespiel Ute , Salmona Jordi 
Published: September 2024

Abstract
Global biodiversity is under accelerating threats, and species are succumbing to extinction before being described. Madagascar’s biota represents an extreme example of this scenario, with the added complication that much of its endemic biodiversity is cryptic. Here we illustrate best practices for clarifying cryptic diversification processes by presenting an integrative framework that leverages multiple lines of evidence and taxon-informed cut-offs for species delimitation, while placing special emphasis on identifying patterns of isolation by distance. We systematically apply this framework to an entire taxonomically controversial primate clade, the mouse lemurs (genus Microcebus, family Cheirogaleidae). We demonstrate that species diversity has been overestimated primarily due to the interpretation of geographic variation as speciation, potentially biasing inference of the underlying processes of evolutionary diversification. Following a revised classification, we find that crypsis within the genus is best explained by a model of morphological stasis imposed by stabilizing selection and a neutral process of niche diversification. Finally, by clarifying species limits and defining evolutionarily significant units, we provide new conservation priorities, bridging fundamental and applied objectives in a generalizable framework.
Two Years of Cotton (Gossypium hirsutum L.) Data from the Georgia Coastal Plain, USA
Authors: Coffin Alisa W. , Cosh Michael H. , Pisarello Kathryn 
Published: September 2024

AbstractThe sustainable management of Earth’s complex ecosystems requires an abundance of field data to support long term stewardship. Remotely sensed satellite data provide crucial supplements to field measurements and are essential for deriving key operational products for monitoring Earth systems. However, to accurately calibrate and validate the models used to develop monitoring datasets, coincident field measurements are required. In 2018 and 2019, data related to cotton (Gossypium hirsutum L.) crops were collected from five fields in two farms located in Georgia, USA. Collections were timed to coincide with satellite overpasses to support the development of remote sensing-based crop and soil data products. Data collected include soil moisture, plant water content, above ground biomass, crop height, plant phenology, and field management practices (row direction, row spacing, and plant density). The datasets include 512 records collected in 2018 and 303 records collected in 2019. The data are archived in the National Agricultural Library Ag Data Commons repository and are available for use by researchers seeking crop and soil validation data.
A high-resolution dataset for future compound hot-dry events under climate change
Authors: Wen Yizhuo , Guo Junhong , Wang Feng , Hao Zhenda , Fei Yifan , Yang Aili , Fan Yurui , Chan Faith Ka Shun 
Published: September 2024

AbstractGlobal climate change is leading to an increase in compound hot-dry events, significantly impacting human habitats. Analysing the causes and effects of these events requires precise data, yet most meteorological data focus on variables rather than extremes, which hinders relevant research. A daily compound hot-dry events (CHDEs) dataset was developed from 1980 to 2100 under various socioeconomic scenarios, using the latest NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset to address this. The dataset has a spatial resolution of 0.25 degrees (approximately 30 kilometres), including three indicators, namely D (the yearly sum of hot-dry extreme days), prI (the intensity of daily precipitation), and tasI (the intensity of daily temperature). To validate the accuracy of the dataset, we compared observational data from China (National Meteorological Information Center, NMIC), Europe (ERA5), and North America (ERA5). Results show close alignment with estimated values from the observational daily dataset, both temporally and spatially. The predictive interval (PI) pass rates for the CHDEs dataset exhibit notably high values. For a 90% PI, D has a pass rate exceeding 85%, whilst prI and tasI respectively show a pass rate above 70% and 95%. These results underscore its suitability for conducting global and regional studies about compound hot-dry events.
Preliminary study on hand dimensions as potential predictors of female populations native to forest and savanna zones in Ghana
Authors: Bimpong Samuel , Abaidoo Chrissie Stansie , Tetteh Joshua , Kofi Sarkodie Francis , Adjei-Antwi Collins , Nketsiah James , Kusi Appiah Atta , Diby Thomas K. 
Published: September 2024

AbstractThe hand is a versatile structure that performs numerous tasks, ranging from exertion of great force such as grip, pinch and torque to execution of precise fine motor skills. The aim of current study was to undertake a preliminary study on hand dimensions as potential predictors of female populations native to the forest and savanna zones of Ghana. A total of one hundred (100) female students aged between 17 and 24 years were recruited into this study, comprising of 53 native to the forest zone and 47 native to savanna zone of Ghana between 12th June to 27th July, 2023 at the Department of Anatomy, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology. Statistically significant positive correlation was observed between left hand length and right hand length (R = 0.923, p = 0.000). From the binary regression model, it could be speculated that left-hand breadth could predict female populations native to the savanna zone (LHB: β = − 2.37, Expβ = 0.09, p = 0.014). However, right-hand breadth and length and left hand length did not show any potential of prediction (RHB: β = 0.900, Expβ = 2.460, p = 0.410; RHL: β = 0.168, Expβ = 1.683, p = 0.803; LHL: β = − 0.300, Expβ = 0.741, p = 0.656). The study therefore may speculate that left handbreadth could have the potential to differentiate female populations native to savanna zone from females native to forest zone in Ghana.
A patient report scale research to access the symptom burden in patients with IgA nephropathy
Authors: Yang Nan , Tang Jiyu , Li Xiaodi , Li Dingcheng , Zhu Bin , He Qiang , Zeng Yuqun , Jin Juan 
Published: September 2024

AbstractPatients diagnosed with IgA nephropathy (IgAN) commonly experience a substantial burden of symptoms encompassing both physical and psychological aspects. Presently, there's a dearth of standardized assessment tools to effectively gauge the extent of symptom burden in IgAN patients. Therefore, this study aims to devise an IgAN Symptom Assessment Tool that enables a comprehensive evaluation of patient symptom burden and their self-perceived severity. Employing a prospective observational design, this study conducted a survey among patients diagnosed with IgAN at a hospital in China. The research team formulated an IgAN Symptom Burden Assessment Scale and administered a questionnaire to gauge patient symptom burden. Severity assessment was conducted on a 5-point Likert scale, with higher scores indicating a more pronounced burden of symptoms. The finalized scale comprised 14 distinct symptom items, and the questionnaire survey garnered responses from 200 patients, achieving a 100% response rate. Statistical analysis unveiled that nearly all patients regarded these symptoms as prevalent and significantly impactful on their daily lives, resulting in a considerable burden. Notably, mild oliguria, moderate nasal congestion, bitter taste , throat discomfort, alongside severe manifestations such as muscle weakness, fatigue, and foamy urine, were frequently reported by patients. The findings underscore that a substantial proportion of IgAN patients grapple with a significant burden of symptoms, emphasizing the imperative for healthcare providers to prioritize symptom management and implement proactive measures to alleviate these challenges. This study presents an innovative tool tailored for evaluating symptom burden specifically in IgAN patients. Subsequent research should center on validating this tool within larger patient cohorts to optimize the efficacy of symptom management in this demographic.
A novel approach for APT attack detection based on an advanced computing
Authors: Xuan Cho Do , Nguyen Tung Thanh 
Published: September 2024

AbstractTo enhance the effectiveness of the Advanced Persistent Threat (APT) detection process, this research proposes a new approach to build and analyze the behavior profiles of APT attacks in network traffic. To achieve this goal, this study carries out two main objectives, including (i) building the behavior profile of APT IP in network traffic using a new intelligent computation method; (ii) analyzing and evaluating the behavior profile of APT IP based on a deep graph network. Specifically, to build the behavior profile of APT IP, this article describes using a combination of two different data mining methods: Bidirectional Long Short-Term Memory (Bi) and Attention (A). Based on the obtained behavior profile, the Dynamic Graph Convolutional Neural Network (DGCNN) is proposed to extract the characteristics of APT IP and classify them. With the flexible combination of different components in the model, the important information and behavior of APT attacks are demonstrated, not only enhancing the accuracy of detecting attack campaigns but also reducing false predictions. The experimental results in the paper show that the method proposed in this study has brought better results than other approaches on all measurements. In particular, the accuracy of APT attack prediction results (Precision) reached from 84 to 91%, higher than other studies of over 7%. These experimental results have proven that the proposed BiADG model for detecting APT attacks in this study is proper and reasonable. In addition, those experimental results have not only proven the effectiveness and superiority of the proposed method in detecting APT attacks but have also opened up a new approach for other cyber-attack detections such as distributed denial of service, botnets, malware, phishing, etc.
Risk of postpartum hemorrhage with increasing first stage labor duration
Authors: Ladfors Linnea V. , Liu Xingrong , Sandström Anna , Lundborg Louise , Butwick Alexander J. , Muraca Giulia M. , Snowden Jonathan M. , Ahlberg Mia , Stephansson Olof 
Published: September 2024

AbstractWith increasing rates of postpartum hemorrhage (PPH) in high-income countries, an important clinical concern is the impact of labor duration on the risk of PPH. This study examined the relationship between increasing active first stage labor duration and PPH and explored the role of second stage labor duration and cesarean delivery (CD) in this association. Including 77,690 nulliparous women with spontaneous labor onset, first stage labor duration was defined as the time from 5 cm to 10 cm, second stage duration from 10 cm dilation to birth and PPH as estimated blood loss > 1000 ml. Using modified Poisson regression for risk ratios (RR) and confidence intervals (CI), we found a 1.5-fold (RR, 1.53; 95% CI, 1.41‒1.66) increased PPH risk when first stage of labor exceeded 12.1 h compared to the reference (< 7.7 h). Mediation analysis showed that 18.5% (95% CI, 9.7‒29.6) of the increased PPH risk with a prolonged first stage (≥ 7.7 h) was due to a prolonged second stage (> 3 h) or CD. These results suggest that including first stage duration in intrapartum assessments could improve PPH risk identification in first-time mothers with a singleton fetus in vertex presentation at full term with spontaneous labor onset.
Evaluation of repeatability and agreement of two optical biometers for intraocular lens power calculation
Authors: Alberquilla Irene Martinez , Svensson Saga , Ruiz-Alcocer Javier , Madrid-Costa David , Dominguez-Vicent Alberto , Venkataraman Abinaya Priya 
Published: September 2024

AbstractThe repeatability of two biometers (Lenstar-LS900 and Eyestar-900) to measure ocular parameters and intraocular lens (IOL) power calculation, and their agreement were evaluated. 134 eyes of 134 participants were measured thrice with each biometer. Axial length (AL), anterior chamber depth (ACD), lens thickness (LT) and keratometry (K) were evaluated. The IOL power was calculated using different formulas. The repeatability limit (RLimit), the mean differences (MD) and the limits of agreement (LoA) were calculated. The RLimits for all parameters were higher with Lenstar compared to Eyestar. RLimits were lower than 0.50 D except for Barrett Universal II (0.54 D) and Haigis (0.51 D) formulas with the Lenstar. Mean differences were lower than 0.01 mm for AL, ACD and LT, and lower than 0.03 D for K. MD ranged from 0 to 0.02 D for all formulas except for Barrett and Hill. When dividing the sample into subgroups (short, normal and long eyes), the MDs were similar for the IOL power and were lower than 0.03 D, except for the Barrett and Hill formulas. Both biometers provide repeatable biometry and IOL power calculations. The LoA interval for the IOL power calculation was between 0.75 and 1.50D, which was similar among the subgroups.
Temporal dynamics of uncertainty and prediction error in musical improvisation across different periods
Authors: Daikoku Tatsuya 
Published: September 2024

Abstract
Human improvisational acts contain an innate individuality, derived from one’s experiences based on epochal and cultural backgrounds. Musical improvisation, much like spontaneous speech, reveals intricate facets of the improviser’s state of mind and emotional character. However, the specific musical components that reveal such individuality remain largely unexplored. Within the framework of human statistical learning and predictive processing, this study examined the temporal dynamics of uncertainty and surprise (prediction error) in a piece of musical improvisation. This cognitive process reconciles the raw auditory cues, such as melody and rhythm, with the musical predictive models shaped by its prior experiences. This study employed the Hierarchical Bayesian Statistical Learning (HBSL) model to analyze a corpus of 456 Jazz improvisations, spanning 1925 to 2009, from 78 distinct Jazz musicians. The results indicated distinctive temporal patterns of surprise and uncertainty, especially in pitch and pitch-rhythm sequences, revealing era-specific features from the early 20th to the 21st centuries. Conversely, rhythm sequences exhibited a consistent degree of uncertainty across eras. Further, the acoustic properties remain unchanged across different periods. These findings highlight the importance of how temporal dynamics of surprise and uncertainty in improvisational music change over periods, profoundly influencing the distinctive methodologies artists adopt for improvisation in each era. Further, it is suggested that the development of improvisational music can be attributed to the adaptive statistical learning mechanisms. This study explores the period-specific characteristics in the temporal dynamics of improvisational music, emphasizing how artists adapt their methods to resonate with the cultural and emotional contexts of their times. Such shifts in improvisational ways offer a window into understanding how artists intuitively respond and adapt their craft to resonate with the cultural zeitgeist and the emotional landscapes of their respective times.
The extremely strong non-neutralized electric currents of the unique solar active region NOAA 13664
Authors: Kontogiannis I. 
Published: September 2024

Context. In May 2024, the extremely complex active region National Oceanic and Atmospheric Administration (NOAA) 13664 produced the strongest geomagnetic storm since 2003.
Aims.The aim of this study is to explore the development of the extreme magnetic complexity of NOAA 13664 in terms of its photospheric electric current.
Methods. The non-neutralized electric current was derived from photospheric vector magnetograms, provided by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. The calculation method is based on image processing, thresholding, and error analysis. The spatial and temporal evolution of the non-neutralized electric current of the region as well as its constituent subregions was examined. For context, a comparison with other complex, flare-prolific active regions is provided.
Results. Active region NOAA 13664 was formed by the emergence and interaction of three subregions, two of which were of notable individual complexity. It consisted of numerous persistent, current-carrying magnetic partitions that exhibited periods of conspicuous motions and strongly increasing electric current at many locations within the region. These periods were followed by intense and repeated flaring. The total unsigned non-neutralized electric currents and average injection rates reached 5.95 ⋅ 1013 A and 1.5 ⋅ 1013 A/day, and are the strongest observed so far, significantly surpassing other super-active regions of Solar Cycle 24 and 25.
Conclusions. Active region NOAA 13664 presents a unique case of complexity. Further scrutiny of the spatial and temporal variation of the net electric currents during the emergence and development of super-active regions is paramount to understand the origin of complex regions and adverse space weather.
The conditional effects of party system change on economic growth in Africa
Authors: Nwokora Zim , Pak Anton , Pelizzo Riccardo 
Published: September 2024

AbstractAfrican party systems vary considerably in their patterns of stability and change over time. This article examines how economic growth has been shaped by such party system fluidity—in particular, the frequency, scope and variety of change—while taking account of the constitutional regime (i.e., level of democracy) within which these party system dynamics occur. To do so, we use Arellano-Bond generalized method of moments models to test the impact of party system fluidity and the level of democracy on economic growth in Africa during the post-independence period (1970–2018). We find, consistent with previous research, that democracy has an uncertain effect on growth. However, party system fluidity is reliably and positively correlated with growth. Its effects are particularly strong whenever an unstable party system coexists with an autocratic regime, which suggests that this specific political context—which has often been associated with democratization—is especially conducive to economic growth.
Geopolitical risks and energy transition: the impact of environmental regulation and green innovation
Authors: Wang Qiang , Wang Xinhua , Li Rongrong 
Published: September 2024

AbstractThis study examines the impact of geopolitical risk on energy transition, focusing on the moderating roles of environmental regulations and green innovation within OECD countries. By employing a multivariate linear and nonlinear regression model, we identify a substantial positive effect of geopolitical risk on energy transition. Our analysis indicates that stronger environmental regulations and advancements in green innovation significantly amplify this effect. Through threshold effect bootstrap sampling tests, we detect a nonlinear relationship between geopolitical risk and energy transition at varying levels of environmental regulation and green innovation. We also explore lag effects, revealing that the influence of geopolitical risk on energy transition grows stronger over time. The inclusion of interaction terms in our analysis further clarifies the moderating influences of environmental regulation and green innovation. Utilizing a range of geopolitical risk indicators and regression methods, our findings are robust, consistently highlighting the proactive role of geopolitical risk in fostering energy transition. These insights highlight the importance of integrated strategies that harness environmental regulations and technological innovation to facilitate a resilient and efficient energy transition in the face of challenges posed by geopolitical uncertainties.
Leading by example from high-status individuals: exploring a crucial missing link in climate change mitigation
Authors: Westlake Steve , Demski Christina , Pidgeon Nick 
Published: September 2024

AbstractBehaviour change has great potential to reduce greenhouse gas emissions quickly, helping to prevent dangerous global warming. Some of the most impactful changes are: flying less, eating less meat, driving electric cars, improving home energy efficiency, increased use of public transport and active travel. However, these choices have proved elusive at scale and are rarely encouraged or modelled by high-status individuals (“leaders”), despite established knowledge about the influence of leaders as role models. Applying theories of embodied leadership and credibility enhancing displays, our novel pre-registered survey experiment (n = 1267) reveals that visible leading by example from politicians and celebrities significantly increases the willingness of members of the UK public to make these high-impact low-carbon choices. In addition, leading by example greatly increases perceptions of leader credibility, trustworthiness, competence, and favourability. We find no significant effects of leading by example on people’s wider perceptions of climate change, but a strong “appetite for leadership” among the public is revealed. In light of these findings, we discuss how embodied leadership by way of visible low-carbon behaviour from leaders may provide a crucial “missing link” for climate change mitigation.
Catholic Christians reject Protestants’ criticism and retaliate in their prayers
Authors: Thürmer J. Lukas 
Published: September 2024

AbstractChristianity pledges the peaceful acceptance of attacks but elicited numerous intergroup conflicts. This contradiction may arise from basic group-processes, including the rejection of intergroup criticism. Catholic Christians (Experiment 1, N = 322, online; Experiment 2, N = 252 in-person survey during Church activities) responded to criticism of their faith that was either attributed to a fellow Catholic or a Protestant commenter. Criticism from a Protestant (vs. Catholic) source was rated to be less constructive, more threatening, and ascribed worse commenter characteristics. Outgroup criticism did not change support for the unity of Christians (ecumenism, Experiment 1) but increased the likelihood of praying for the commenter (Experiment 2). The content of outgroup-directed prayers was hostile. Effects emerged independent of reported fundamentalism and in a context highly conducive to inter-denomination debate. These findings demonstrate that religious group processes can evoke counter-normative defenses, thus spurring conflict. Understanding these processes may help mend divided societies.