bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differentiating patients admitted primarily due to coronavirus disease 2019 (COVID-19) from those admitted with incidentally detected severe acute respiratory syndrome corona-virus type 2 (SARS-CoV-2) at hospital admission: A cohort analysis of German hospital records
Authors: Strobl Ralf , Misailovski Martin , Blaschke Sabine , Berens Milena , Beste Andreas , Krone Manuel , Eisenmann Michael , Ebert Sina , Hoehn Anna , Mees Juliane , Kaase Martin , Chackalackal Dhia J. , Koller Daniela , Chrampanis Julia , Kosub Jana-Michelle , Srivastava Nikita , Albashiti Fady , Groß Uwe , Fischer Andreas , Grill Eva , Scheithauer Simone 
Published: February 2024

AbstractObjective:The number of hospitalized patients with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) does not differentiate between patients admitted due to coronavirus disease 2019 (COVID-19) (ie, primary cases) and incidental SARS-CoV-2 infection (ie, incidental cases). We developed an adaptable method to distinguish primary cases from incidental cases upon hospital admission.Design:Retrospective cohort study.Setting:Data were obtained from 3 German tertiary-care hospitals.Patients:The study included patients of all ages who tested positive for SARS-CoV-2 by a standard quantitative reverse-transcription polymerase chain reaction (RT-PCR) assay upon admission between January and June 2022.Methods:We present 2 distinct models: (1) a point-of-care model that can be used shortly after admission based on a limited range of parameters and (2) a more extended point-of-care model based on parameters that are available within the first 24–48 hours after admission. We used regression and tree-based classification models with internal and external validation.Results:In total, 1,150 patients were included (mean age, 49.5±28.5 years; 46% female; 40% primary cases). Both point-of-care models showed good discrimination with area under the curve (AUC) values of 0.80 and 0.87, respectively. As main predictors, we used admission diagnosis codes (ICD-10-GM), ward of admission, and for the extended model, we included viral load, need for oxygen, leucocyte count, and C-reactive protein.Conclusions:We propose 2 predictive algorithms based on routine clinical data that differentiate primary COVID-19 from incidental SARS-CoV-2 infection. These algorithms can provide a precise surveillance tool that can contribute to pandemic preparedness. They can easily be modified to be used in future pandemic, epidemic, and endemic situations all over the world.
On some semi-parametric estimates for European option prices
Authors: Marinelli Carlo 
Published: February 2024

AbstractWe show that an estimate by de la Peña, Ibragimov, and Jordan for
${\mathbb{E}}(X-c)^+$
, with c a constant and X a random variable of which the mean, the variance, and
$\mathbb{P}(X \leqslant c)$
are known, implies an estimate by Scarf on the infimum of
${\mathbb{E}}(X \wedge c)$
over the set of positive random variables X with fixed mean and variance. This also shows, as a consequence, that the former estimate implies an estimate by Lo on European option prices.
Effects of hypertension diagnoses on alcohol consumption among Chinese Adults—A Two-dimensional regression discontinuity analysis
Authors: Huang Juerong , Dang Hongjing , Hu Yue , Chen Qihui 
Published: February 2024

AbstractExploiting the fact that hypertension is diagnosed when a person’s blood pressure reading exceeds a medically specified threshold (90 mmHg for diastolic blood pressure or 140 mmHg for systolic blood pressure), this study estimates the effect of a first-ever hypertension diagnosis on Chinese adults’ alcohol consumption using a two-dimensional regression discontinuity design. Analyzing data on 10,787 adults from the China Health and Nutrition Survey, our estimation reveals that hypertension diagnoses based on diastolic blood pressure readings exert a number of desirable effects. Hypertensive adults’ drinking frequency and the incidence of excessive drinking among them were reduced by 1.2 times/week and 17.9 percentage points, respectively, about three years after the diagnosis. Meanwhile, their beer and Chinese spirits (Baijiu) intakes were reduced by 518.6 ml/week and 194.8 ml/week, respectively. Interestingly, we also found modest evidence that hypertension diagnoses based on diastolic blood pressure readings increase Chinese adults’ wine intake, suggesting a substitution pattern upon hypertension diagnoses. In contrast, based on systolic blood pressure readings, no significant effects of hypertension diagnoses on alcohol consumption were found.
The Keeper of the Imperial Body: The Russian Geographical Society as an Entrepreneur of Imperial Nationalism
Authors: Curanović Alicja 
Published: February 2024

AbstractThe goal of this article is to show Russia’s civilizational turn in the broader context of imperial nationalism. The “turn” is a manifestation of imperial nationalism that today feeds not only on political ideas and history but also on geography. In the mass perception, geography is seen as an objective, non-ideologized scientific discipline less prone to political manipulation. Because of this, it can be employed to influence the Russian self-identification process in a much more subtle and efficient way than references to the more abstract notion of civilization. This article presents the Russian Geographical Society (RGS) as an identity entrepreneur managed by the ruling elite with a well-developed regional structure. It functions as a community of imperial practice. With its discursive and material practices, the RGS contributes to reproducing imperial nationalism, including in its civilizational version. The RGS is the keeper of the imperial body. By referring to the imperial body, I mean not just the physical territory but also the ways it is imagined in discourse and made material in numerous practices.
SPATIOTEMPORAL PATTERNS ON THE APPEARANCE OF THE FIRST TRAPEZE INDUSTRIES IN THE LATE MESOLITHIC OF THE IBERIAN PENINSULA
Authors: Gómez-Puche Magdalena , Fernández-López de Pablo Javier 
Published: February 2024

ABSTRACTThe spread of trapeze industries (the creation of trapeze-shaped flint tips) during Late Mesolithic is one of the most disruptive phenomena of technological change documented in the European Prehistory. Understanding the chronological patterns of this process requires (i) a critical evaluation of stratigraphic relationship between trapeze assemblages and radiocarbon samples, and (ii) considering different levels of chronological uncertainty according to the inbuilt age of the samples and the calibration process. In this paper, we critically evaluate and analyze the radiocarbon record of the first trapeze industries in the Iberian Peninsula. A dataset of 181 radiocarbon dates from 67 sites dated to 8800–8200 cal BP was collected and evaluated following a strict data quality control protocol, from which 135 dates of 53 sites were retained and classified according to a reliability index. Then, three different phase Bayesian chronological models were created to estimate the duration of the first spread of trapezes across Iberia, considering different levels of chrono-stratigraphic resolution. We find that trapeze industries appeared in the eastern half of Iberia, over an area of 330,000 km2 between 8505–8390 and 8425–8338 cal BP, spanning 0–85 yr (95.4% CI). When the oldest evidence of trapezes from Portugal are considered, the probability distribution expands (8943–8457 and 8686–7688 cal BP), due to the chronological uncertainty of human samples with marine diet and regional ΔR values applied. For the eastern half of Iberia, the current evidence indicates a very rapid spread of trapeze industries initiated in the Central-Western Pyrenees, suggesting cultural diffusion within Mesolithic social networks as the main driving mechanism.
Network science reveals the early signs of L1 lexical attrition: Introducing the Lexical Attrition Foundation (LeAF) framework
Authors: Chaouch-Orozco Adel , Martín-Villena Fernando 
Published: February 2024

Abstract
L1 lexical attrition is the decline of L1 lexical-semantic abilities due to reduced L1 exposure and/or L2 interference. Semantic fluency tasks are central in this research, but traditional analyses are often inconclusive.
To address this, we employed an innovative network science approach to investigate the bilingual lexicon's structural properties. Semantic fluency data were collected from immersed/non-immersed late bilinguals with comparable L2 proficiencies.
Our results indicate that L2 immersion led to more integrated and efficient L2 networks. Crucially, immersion also resulted in L1 attrition (only evident in the network analysis). Immersed participants exhibited less densely connected and sparser L1 networks. Furthermore, network measures suggest that L1 lexical attrition occurs gradually, initially impacting network interconnectivity, while information flow and community structure remain more stable.
Drawing from these insights, we introduce the Lexical Attrition Foundation (LeAF) framework, offering a network-based perspective on lexical attrition development and laying the groundwork for future research.
Clingraph: A System for ASP-based Visualization
Authors: HAHN SUSANA , SABUNCU ORKUNT , SCHAUB TORSTEN , STOLZMANN TOBIAS 
Published: February 2024

AbstractWe present the Answer Set Programming (ASP)-based visualization tool clingraph, which aims at visualizing various concepts of ASP by means of ASP itself. This idea traces back to the aspviz tool and clingraph redevelops and extends it in the context of modern ASP systems. More precisely, clingraph takes graph specifications in terms of ASP facts and hands them over to the graph visualization system graphviz. The use of ASP provides a great interface between logic programs and/or answer sets and their visualization. Also, clingraph offers a Python application programming interface (API) that extends this ease of interfacing to clingo’s API and in turn to connect and monitor various aspects of the solving process.
Phenotypic profiling of lentil (Lens culinaris Medikus) accessions enabled identification of promising lines for use in breeding for high yield, early flowering and desirable traits
Authors: Naik Yogesh Dashrath , Sharma Vinay Kumar , Aski Muraleedhar Sidaram , Rangari Sagar Krushnaji , Kumar Raj , Dikshit Harsh Kumar , Sahani Sangita , Kant Ravi , Mishra Gyan , Mir Reyazul Rouf , Kudapa Himabindu , Elango Dinakaran , Zwart Rebecca S. , Varshney Rajeev Kumar , Thudi Mahendar 
Published: February 2024

AbstractIn the face of climate change, developing resilient crops is crucial for global food security in the 21st century to feed a growing population. Lentil (Lens culinaris Medikus) plays a vital role in ensuring global food and nutritional security. Traits like early flowering enable the crop to mature faster, thereby shortening the growing window and reducing yield losses caused by moisture and heat stresses during the reproductive phase. However, issues like limited genetic diversity in this trait remain unaddressed. To address this gap, our study aims to comprehensively assess genetic variability and trait associations in 158 lentil accessions. In the present study, we observed significant variations for days to 50% flowering (67–90 days), days to maturity (109–122 days) and 100 seed weight (1.69–2.68 g) throughout a period of two consecutive years (2020–2021 and 2021–2022). The observed variability in these traits offers a valuable avenue for the improvement of lentil yield through targeted selection and hybridization. Additionally, correlation analysis showed negative correlation between days to 50% flowering and grain yield per plant, while plant height had a significant (P < 0.01) positive correlation with all traits except yield per plant. Furthermore, we identified specific germplasm with exceptional traits that hold significant potential for future breeding programmes. The genotypes EC 223197-A and EC 267696 were identified for early flowering with high yield, and other genotypes that were identified for various traits would serve as breeding material for the introgression of these traits into elite cultivars.
GEMAct: a Python package for non-life (re)insurance modeling
Authors: Pittarello Gabriele , Luini Edoardo , Marchione Manfred Marvin 
Published: February 2024

AbstractThis paper introduces gemact, a Python package for actuarial modeling based on the collective risk model. The library supports applications to risk costing and risk transfer, loss aggregation, and loss reserving. We add new probability distributions to those available in scipy, including the (a, b, 0) and (a, b, 1) discrete distributions, copulas of the Archimedean family, the Gaussian, the Student t and the Fundamental copulas. We provide an implementation of the AEP algorithm for calculating the cumulative distribution function of the sum of dependent, nonnegative random variables, given their dependency structure specified with a copula. The theoretical framework is introduced at the beginning of each section to give the reader with a sufficient understanding of the underlying actuarial models.
Transdisciplinarity, tempocoupling, and the role of culture in zoonosis research
Authors: Matias Denise Margaret S. 
Published: February 2024

Abstract

Non-technical summary
The general public became familiar with the term and definition of zoonosis during the COVID-19 pandemic. Because of the pandemic, several responses to mitigate zoonotic risk has been put forward. Often cited are stricter biodiversity conservation and wildlife protection but there are also suggestions to educate people who traditionally consume wildlife for food. This implicit condemnation of culture also manifested explicitly in the form of racism especially against Asians during the height of the pandemic. If the world is to avoid a pandemic, it also needs to work against Orientalism and ensure research is inclusive, equitable, and just.

Technical summary
The COVID-19 pandemic widely introduced the term and definition of zoonosis to the general public. More than just a knee-jerk reaction, stricter biodiversity conservation and wildlife protection are now seen as essential strategies in mitigating zoonotic risks while some researchers have called for education campaigns that should discredit ingrained cultural practices such as wildlife consumption. This implicit condemnation of culture may have been initially confined to research papers but it eventually manifested as explicit racism in everyday life during the height of the pandemic, highlighting the need to decolonize Western scientific views on pandemic prevention and to refrain from Orientalism. This Intelligence Briefing makes the case for the inclusion of history and culture as necessary elements in zoonosis research alongside a critical reflection of transdisciplinary approaches. Emphasizing epistemic humility and authentic interest to learn from other actors such as Indigenous communities on the frontlines of human-wildlife interfaces, this Intelligence Briefing recommends the Future Earth Health Knowledge-Action Network to stay the course toward promoting approaches that are ‘transdisciplinary, multi-scalar, inclusive, equitable, and broadly communicated’ in zoonosis research.

Social media summary
History and culture are necessary elements of zoonosis research alongside transdisciplinary approaches.
Calculations of Arctic Ice‐Ocean Interface Photosynthetically Active Radiation (PAR) Transmittance Values
Authors: Redmond Roche B. H. , King M. D. 
Published: February 2024

AbstractSea ice algae play an important role in the Arctic Ocean ecosystem, driving primary production in the spring and sequestering carbon to the deep ocean. Up to 45% of Arctic Ocean primary production occurs in ice‐covered areas; photosynthetically active radiation (PAR) is fundamental to driving this production. Sea ice, and particularly snow, strongly scatter and reflect light, reducing the amount of PAR transmitted to the ice‐ocean interface. The effect that varying thicknesses of sea ice (0.2–3.5 m) and snow (0.01–1 m) have on the value of PAR transmittance at the ice‐ocean interface are considered for a Winter, Spring, and Summer scenario. When characteristic Arctic Ocean conditions (2 m sea ice and ∼0.2 m snowpack) are modeled, there is roughly a two‐fold difference in PAR transmittance at the ice‐ocean interface between the Winter (0.003) and Spring (0.007) scenarios and an order of magnitude difference with the Summer scenario (0.04). The modeled values correlate within one standard deviation of measured values and show good agreement with extended pan‐Arctic Ocean field campaign measurements. The results also indicate that simple exponential decay methods may lead to inaccurate results, and radiative‐transfer modeling is required to accurately predict PAR transmittance at the ice‐ocean interface. Therefore, this study offers a novel mathematical technique to predict the value of PAR transmittance at the ice‐ocean interface. Coupled with year‐round near‐real‐time sea ice and snow thickness remote sensing data, this technique may improve understanding of primary production and carbon budgets in the changing Arctic Ocean.
Mississippi River Chemistry Impacts on the Interannual Variability of Aragonite Saturation State in the Northern Gulf of Mexico
Authors: Gomez Fabian A. , Wanninkhof Rik , Barbero Leticia , Lee Sang‐Ki 
Published: February 2024

AbstractIn the northern Gulf of Mexico shelf, the Mississippi‐Atchafalaya River System (MARS) impacts the carbonate system by delivering freshwater with a distinct seasonal pattern in both total alkalinity (Alk) and dissolved inorganic carbon (DIC), and promoting biologically driven changes in DIC through nutrient inputs. However, how and to what degree these processes modulate the interannual variability in calcium carbonate solubility have been poorly documented. Here, we use an ocean‐biogeochemical model to investigate the impact of MARS's discharge and chemistry on interannual anomalies of aragonite saturation state (ΩAr). Based on model results, we show that the enhanced mixing of riverine waters with a low buffer capacity (low Alk‐to‐DIC ratio) during high‐discharge winters promotes a significant ΩAr decline over the inner‐shelf. We also show that increased nutrient runoff and vertical stratification during high‐discharge summers promotes strong negative anomalies in bottom ΩAr, and less intense but significant positive anomalies in surface ΩAr. Therefore, increased MARS discharge promotes an increased frequency of suboptimal ΩAr levels for nearshore coastal calcifying species. Additional sensitivity experiments further show that reductions in the Alk‐to‐DIC ratio and nitrate concentration from the MARS significantly modify the simulated interannual ΩAr patterns, weakening the positive surface ΩAr anomalies during high‐discharge summers or even producing negative surface ΩAr anomalies. Our findings suggest that riverine water carbonate chemistry is a main driver of interannual variability in ΩAr over river dominated ocean margins.
Reactive Transport Modeling in Porous Fractured Media: Application to Weathering Processes
Authors: Favier Sylvain , Teitler Yoram , Golfier Fabrice , Cathelineau Michel 
Published: February 2024

AbstractComplex permeability distribution is frequently encountered in weathered rocks with inherited heterogeneities, such as networks of discontinuities that impact fluid flow and water‐rock interactions. Reactive transport modeling is a powerful tool for analyzing fractured media's chemical weathering dynamics. In this study, two different ways to model the fracture‐matrix interaction were explored. A 1D dual‐porosity simulation of reactive transport is designed to study the global impact of fractures on the weathering progression front, compared with a Single Porosity (S.P.) (unfractured) reference model. Then a 2D discrete model using a Discrete Fracture Matrix (DFM) representation is built to highlight the importance of medium geometry and fracture connectivity on weathering. The relevance of such models was evaluated in the case of weathering processes affecting ultramafic units in New Caledonia. Comparing the average behavior of the dual and S.P. models reveals a similar trend in both global mineralogical evolutions. Yet differences occur when confronting the weathering rates. By extending the weathering over a greater depth, the fractures favor a smoother transition between the saprolite horizon and the oxide ore. Furthermore, a partition of the newly formed phyllosilicates occurs in fractures and matrix: Ni‐phyllosilicates preferentially precipitate in fractures, while Mg‐phyllosilicates remain trapped within the matrix due to differences in residence time and liquid‐to‐solid ratio. The DFM modeling highlights the effect of the connectivity of a complex fracture network on the dissolution‐precipitation processes. Depending on the permeability and geometry, fluid flow is modified, favoring the formation of weathering heterogeneities typically observed on the field.
A Novel Deep Learning Approach for Data Assimilation of Complex Hydrological Systems
Authors: Zhang Jiangjiang , Cao Chenglong , Nan Tongchao , Ju Lei , Zhou Hongxiang , Zeng Lingzao 
Published: February 2024

AbstractIn hydrological research, data assimilation (DA) is widely used to fuse the information contained in process‐based models and observational data to reduce simulation uncertainty. However, many popular DA methods are limited by low computational efficiency or their reliance on the Gaussian assumption. To address these limitations, we propose a novel DA method called DA(DL), which leverages the capabilities of DL to model non‐linear relationships and recognize complex patterns. DA(DL) first generates a large volume of training data from the prior ensemble, and then trains a DL model to update the system knowledge (e.g., model parameters in this study) from multiple predictors. For highly non‐linear models, an iterative form of DA(DL) can be implemented. Additionally, strategies of data augmentation and local updating are proposed to enhance DA(DL) for problems involving small ensemble size and the equifinality issue, respectively. In two hydrological DA cases involving Gaussian and non‐Gaussian distributions, DA(DL) shows promising performance compared to two ensemble smoother methods, that is, ES(K) and ES(DL), which respectively apply the Kalman‐ and DL‐based updates. Potential improvements to DA(DL) can be made by designing better DL model architectures, imposing physical constraints to the training of the DL model, and further updating other important variables like model states, forcings and error terms.