bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combined foliar application of Zn and Fe increases grain micronutrient concentrations and alleviates water stress across diverse wheat species and ploidal levels
Authors: Shoormij Fatemeh , Mirlohi Aghafakhr , Saeidi Ghodratollah , Shirvani Mehran 
Published: November 2022

AbstractThis study aimed to examine the reaction of several wheat species with different ploidy levels to foliar application of zinc (Zn) and iron (Fe) under different water regimes. Thirty-five wheat genotypes, including nineteen tetraploids from ten different species, ten hexaploids from five species, and six diploids from three species, were evaluated in the field over two moisture regimes with the following four treatments: control, foliar Zn application, foliar Fe application, and foliar Zn + Fe application. The experiments were conducted according to a split-plot scheme in a randomized complete block design with two replications in each moisture regime. Water stress negatively affected all measured traits, except grain Zn and Fe content. Combined foliar application of Zn + Fe significantly increased yield and alleviated yield reduction caused by water stress. Applying Zn and Fe significantly increased both micronutrient content in grains under both moisture conditions. Tetra and hexaploid species yielded nearly four times as much grain as unimproved diploid species and were less affected by water stress. All ploidy levels responded almost similarly to Zn and Fe treatments, with the combined application being as effective as each element separately. The highest yield increase in response to combined application of Zn + Fe under the two moisture conditions and the highest grain Zn content in response to Zn application under water stress was observed in hexaploid wheat. Combined foliar application of Zn and Fe increases grain Zn and Fe and alleviates water stress's adverse effects on all wheat ploidy levels, making biofortification cost-effective.
Evaluation of synergy between low-carbon development and socio-economic development based on a composite system: a case study of Anhui Province (China)
Authors: Yang Ziwei , Liu Jingli , Xing Qinfeng 
Published: November 2022

AbstractLow-carbon development has been the favorite subject with the aim of making a synergy environment. Extensive research on low-carbon development and socio-economic synergy has been conducted by scholars from different perspectives. This paper explores the synergy between low-carbon development and socio-economic development as a composite system from four levels: resource, energy, economy and society, and improves the theory of low-carbon economic development in a "dual-carbon" perspective. Meanwhile, based on the theoretical research, this paper constructs a synergy model and evaluation index system of low-carbon development and socio-economic development, and conducts an empirical analysis by combining the relevant data of low-carbon governance and socio-economic development in Anhui Province from 2011 to 2020. After obtaining the level of synergistic development and constraints of the composite system, the trend of changes in the level of synergy of the composite system is verified by R/S model. It is found that: (1) the composite system composed of low-carbon development and socio-economic development in Anhui Province has certain synergistic effects, and the level of synergistic development is increasing; (2) the studied time series has significant correlation over a long period of time, while it will continue the past development trend. The contribution of this paper is to take the synergy model as the basis and build the R/S model to extend the time cycle of synergy level, which extends the previous theoretical research system of low-carbon development, helps to deepen the theoretical understanding of the synergy between low-carbon development and socio-economic development, and improves the discussion on building ecological civilization and helping to achieve the goal of "dual-carbon".
Recurrent attention convolutional neural network optimise track foreign body detection
Authors: Linfeng Wang , Heng Wan , Xuliang Tang , Dan Xiao , Jiayao Liu 
Published: November 2022

AbstractTimely and accurate identification of track foreign body intrusion is of great significance for maintaining the safety of railway running. Object detection technology based on deep learning can be used to judge the foreign body in the track running area. However, the general target detection technology cannot recognise the foreign object information in complex environment, which has a certain hysteresis. In this study, adaptive adjustment is made to the algorithm according to the limited area in the railway special scene. A new Recurrent Attention Convolutional Neural Network and adaptive particle swarm fusion network is proposed. Produced in the process of image classification and regional sampling information loss, by introducing attention study under the multi‐scale recursive fusion, each scale is a network of target recognition and attention network, starting from the full image, continuously put forward attention area, and as input to realise detection to the next dimension positioning; With the help of adaptive particle swarm optimisation algorithm, the feature information at different levels is fused, and the high‐attention region is generated by continuous recursive clipping from rough to fine, The mutual enhancement of target area detection and fine‐grained features is realised. Experiments conducted by the author in Railway data set showed that its target detection accuracy reached 84.2%. Compared with other existing models, the relative accuracy gain was 10.6% and 8.1%, respectively, and the maximum gain was 6.2% compared with the self‐ablation experiment.
Exploiting hybrid non‐orthogonal multiple access in satellite–terrestrial systems with randomly deployed users
Authors: Zhao Jinlong , Huo Mingming , Kang Shaoli , Yue Xinwei 
Published: November 2022

AbstractIn this letter, a hybrid non‐orthogonal multiple access (NOMA) scheme for satellite–terrestrial systems is proposed, which is capable of integrating both power domain NOMA (PD‐NOMA) and code domain NOMA (CD‐NOMA) design modes. The stochastic geometry method is considered to model the position of the terrestrial NOMA user. Specifically, the closed‐form expressions of exact outage probability with imperfect interference cancellation are derived. In order to get more insights, the asymptotic outage probabilities for high SNR conditions are also discussed. Numerical results are provided to confirm the validity of theoretical analysis and reveal the effects of critical parameters on system performance.
An optimal trajectory planning for automated on‐ramp merging
Authors: Liang Jun , Guan Tong , Liu Daoguang , Liu Xiao , Luan Zhenhua , Liu Hang , Yuan Xiaoning 
Published: November 2022

AbstractThis paper proposes an optimal trajectory planning model for automated on‐ramp merging. The minimum cost path based on the optimal control theory is selected as the optimal trajectory of the on‐ramp merging vehicle, which could avoid potential collisions and satisfy the kinematic constraints on the vehicle motion. Moreover, an optimal control strategy is presented to solve the trajectory planning problem of the facilitating vehicle. An analytical closed‐form solution is derived by using the Hamiltonian analysis and the path information of the merging vehicle. Particularly, the proposed planning process also considers the lateral movement of the on‐ramp merging, which is more efficient in the application. Owing to the location and time that the on‐ramp vehicle merges into the mainline can be obtained endogenously by its planning process, the model has high adaptation to various on‐ramp environments. Solutions to the above two optimal methods are implemented in a model predictive control framework to cope with possible external disturbances. Several numerical simulations and PreScan‐Simulink Co‐Simulation illustrate the effectiveness of the proposed model. Furthermore, this methodology is compared with a typical CACC strategy to demonstrate its potential to reduce fuel consumption, as well as improve passenger comfort.
Effect of improved atmospheric opacities in modelling sub-Neptunes
Authors: MacKenzie Jasmine , Grenfell John Lee , Baumeister Philipp , Tosi Nicola , Cabrera Juan , Rauer Heike 
Published: November 2022

Aims. We investigate the impact of updated atmospheric mean opacity input values on modelled transit radius and the distribution of interior layer mass fractions.
Methods. We developed and applied a coupled interior-atmosphere model. Our straightforward semi-grey calculation of atmospheric temperature enables us to perform thousands of model realisations in a Monte Carlo approach to address potential degeneracies in interior and atmospheric mass fraction. Our main constraints are planetary mass and radius from which our model infers distributions of the internal structure of exoplanetary classes ranging from Super-Earth to Mini-Neptune. We varied the relative masses of gas, envelope, mantle, and core layers subject to constraints on the bulk density from observations, and investigated the effect of updating atmospheric mean opacities.
Results. First, we validate our model output with observed temperature profiles for modern Neptune. We can reproduce the basic features in the middle atmosphere but not the temperature inversion in the upper layers, which is likely because our model lacks aerosol heating. Calculated interiors are generally consistent with modern Neptune. Second, we compare with the well-studied object GJ 1214 b and obtain results that are broadly consistent with previous findings; they suggest correlations between modelled gas, water, and core mass fractions, although these are generally weak. Updating the opacities leads to a change on the order of a few percent in the modelled transit radius. This is comparable in magnitude to the planned accuracy of the PLATO data for planetary radius, suggesting that the opacity update in the model is important to implement.
Testing general relativity: New measurements of gravitational redshift in galaxy clusters
Authors: Rosselli D. , Marulli F. , Veropalumbo A. , Cimatti A. , Moscardini L. 
Published: November 2022

Context.The peculiar velocity distribution of cluster member galaxies provides a powerful tool to directly investigate the gravitational potentials within galaxy clusters and to test the gravity theory on megaparsec scales.Aims.We exploit spectroscopic galaxy and galaxy cluster samples extracted from the latest releases of the Sloan Digital Sky Survey (SDSS) to derive new constraints on the gravity theory.Methods.We considered a spectroscopic sample of 3058 galaxy clusters, with a maximum redshift of 0.5 and masses between 1014 − 1015M⊙. We analysed the velocity distribution of the cluster member galaxies to make new measurements of the gravitational redshift effect inside galaxy clusters. We accurately estimated the cluster centres, computing them as the average of angular positions and redshifts of the closest galaxies to the brightest cluster galaxies. We find that this centre definition provides a better estimation of the centre of the cluster gravitational potential wells, relative to simply assuming the brightest cluster galaxies as the cluster centres, as done in past literature works. We compared our measurements with the theoretical predictions of three different gravity theories: general relativity (GR), thef(R) model, and the Dvali–Gabadadze–Porrati (DGP) model. A new statistical procedure was used to fit the measured gravitational redshift signal, and thus to discriminate among the considered gravity theories. Finally, we investigated the systematic uncertainties that possibly affect the analysis.Results.We clearly detect the gravitational redshift effect in the exploited cluster member catalogue. We recover an integrated gravitational redshift signal of −11.4 ± 3.3 km s−1, which is in agreement, within the errors, with past literature works.Conclusions.Overall, our results are consistent with both GR and DGP predictions, while they are in marginal disagreement with the predictions of the consideredf(R) strong field model.
Naarea, le pari des sels fondus
Authors: Le Gros Gaïc 
Published: November 2022

Naarea propose un petit réacteur à sels fondus et à spectre rapide de 40 MW destiné à améliorer le cycle du combustible en valorisant au maximum l’uranium. L’entreprise met en avant sa volonté d’être « concepteur, fabricant et exploitant ».
Association of Social Determinants of Health and Clinical Factors with Postpartum Hospital Readmissions among Nulliparous Individuals
Authors: Kumar Natasha R. , Grobman William A. , Haas David M. , Silver Robert M. , Reddy Uma M. , Simhan Hyagriv , Wing Deborah A , Mercer Brian M. , Yee Lynn M. 
Published: November 2022

Objective Prior data suggest that there are racial and ethnic disparities in postpartum readmission among individuals, especially among those with hypertensive disorders of pregnancy. Existing reports commonly lack granular information on social determinants of health. The objective of this study was to investigate factors associated with postpartum readmission for individuals and address whether such risk factors differed by whether an individual had an antecedent diagnosis of a hypertensive disorder of pregnancy (HDP).
Study Design This is a secondary analysis of a large, multicenter prospective cohort study of 10,038 nulliparous participants. The primary outcome of this analysis was postpartum readmission. A priori, participants were analyzed separately based on whether they had HDP. Participant characteristics previously associated with a greater risk of perinatal morbidity or readmission (including social determinants of health, preexisting and chronic comorbidities, and intrapartum characteristics) were compared with bivariable analyses and retained in multivariable models if p < 0.05. Social determinants of health evaluated in this analysis included insurance status, self-identified race and ethnicity (as a proxy for structural racism), income, marital status, primary language, and educational attainment.
Results Of 9,457 participants eligible for inclusion, 1.7% (n = 165) were readmitted following initial hospital discharge. A higher proportion of individuals with HDP were readmitted compared with individuals without HDP (3.4 vs 1.3%, p < 0.001). Among participants without HDP, the only factors associated with postpartum readmission were chorioamnionitis and cesarean delivery. Among participants with HDP, gestational diabetes and postpartum hemorrhage requiring transfusion were associated with postpartum readmission. While the number of postpartum readmissions included in our analysis was relatively small, social determinants of health that we examined were not associated with postpartum readmission for either group.
Conclusion In this diverse cohort of nulliparous pregnant individuals, there was a higher frequency of postpartum readmission among participants with HDP. Preexisting comorbidity and intrapartum complications were associated with postpartum readmission among this population engaged in a longitudinal study.
Key Points
3 Organocatalytic Dynamic Kinetic Resolution
Authors: Wu X. , Liu Y. , Jin Z. 
Published: November 2022

AbstractThere has long been interest in obtaining optically pure molecules from racemic or non-chiral starting materials through environmentally friendly chemical transformations with high yields and enantioselectivities. Organocatalytic reactions possess the inherent advantages of non-toxicity and good efficiency and are insensitive to air and moisture. Dynamic kinetic resolution (DKR) represents one class of the most efficient strategies for the preparation of chiral molecules from racemic mixtures with up to 100% yields. Therefore, DKR reactions promoted by various organic catalysts are attractive based on their efficiencies, selectivities, and low toxicities. In this review, we introduce some representative examples of the reported DKR reactions catalyzed by typical organic catalysts, including chiral amines, Brønsted acids, N-heterocyclic carbenes, phosphines, guanidines, and isothioureas. The aim is to provide readers with a general overview of the scope and efficiency of organocatalytic DKR transformations and to inspire groundbreaking ideas for the development and applications of organocatalytic DKR reactions in future research.
8 Chemoenzymatic Dynamic Kinetic Asymmetric Transformation
Authors: Pàmies O. 
Published: November 2022

AbstractThe combination of enzymes and metal complexes can be used to achieve the de-epimerization of diastereoisomeric mixtures. Thus, by means of this chemoenzymatic dynamic kinetic asymmetric transformation (DYKAT), a wide range of racemic diols and, to a lesser extent, amino alcohols and diamines, have been transformed into a single diastereoisomer in excellent yields, and diastereo- and enantioselectivities.
10 Applications of Metal-Catalyzed Dynamic Kinetic Resolutions and Dynamic Kinetic Asymmetric Transformations for the Synthesis of Complex Molecules
Authors: Goetzke F. W. , Modicom F. , Fletcher S. P. 
Published: November 2022

AbstractThe stereocontrolled synthesis of complex molecules is a key technology for the pharmaceutical, agrochemical, and fine-chemical industries, a well-established field of organic chemistry, and the ultimate proving ground for the value of newly developed synthetic methods. This chapter illustrates how metal-catalyzed dynamic kinetic resolutions (DKR) and dynamic kinetic asymmetric transformations (DYKAT) have been used in the synthesis of complex molecules such as natural products, pharmaceuticals, and chiral ligands. This approach has unique strategic advantages over other methods as it allows the use of racemic starting materials, where asymmetry is introduced at a later stage in a synthetic sequence and can even be used to set multiple stereogenic centers in a single step.
Factors contributing to vaccine hesitancy and reduced vaccine confidence in rural underserved populations
Authors: Robinson Renee , Nguyen Elaine , Wright Melanie , Holmes John , Oliphant Catherine , Cleveland Kevin , Nies Mary A. 
Published: November 2022

AbstractVaccination remains one of the most effective ways to limit the spread of infectious diseases, and reduce mortality and morbidity in rural areas. Waning public confidence in vaccines, especially the COVID-19 vaccine, remains a cause for concern. A number of individuals in the US and worldwide remain complacent, choosing not to be vaccinated and/or delay COVID-19 vaccination, resulting in suboptimal herd immunity. The primary goal of this study is to identify modifiable factors contributing to COVID-19 vaccine hesitancy among vaccine-eligible individuals with access to vaccines in two under-resourced rural states, Alaska and Idaho. This qualitative study used semi-structured interviews with providers and focus groups with community participants in Alaska and Idaho. A moderator’s guide was used to facilitate interviews and focus groups conducted and recorded using Zoom and transcribed verbatim. Thematic, qualitative analysis was conducted using QDA Miner. Themes and subthemes that emerged were labeled, categorized, and compared to previously described determinants of general vaccine hesitancy: established contextual, individual and/or social influences, vaccine and vaccination-specific concerns. Themes (n = 9) and sub-themes (n = 51) identified during the qualitative analysis highlighted a factor’s contributing to COVID-19 vaccine hesitancy and poor vaccine uptake. Relevant influenceable factors were grouped into three main categories: confidence, complacency, and convenience. Vaccines are effective public health interventions to promote health and prevent diseases in rural areas. Practical solutions to engage healthcare providers, researchers, vaccine advocates, vaccine manufacturers, and other partners in local communities are needed to increase public trust in immunization systems to achieve community immunity.
Arabic-English metaphor translation from a cognitive linguistic perspective
Authors: Khalifah Lama , Zibin Aseel 
Published: November 2022

AbstractThis article aims to analyze the translation of Arabic metaphors into English in Naguib Mahfuz’s novelZuqaq Al-Midaq(1966), which Trevor Le Gassick translated asMidaq Alley. With conceptual metaphor theory based on the notion of main meaning focus (Kövecses 2017) and the cogno-cultural approach (Al-Zoubi, Al-Ali, and Al-Hasnawi’s 2007) as its theoretical framework, it uses metaphor identification procedure (MIP) proposed byPragglejaz Group (2007)to identify the metaphorical expressions and Steen’s steps (2007) to extract the conceptual metaphors from linguistic expressions. This study explores how metaphors reflect cultural aspects and how the same conceptual mappings can be realized differently according to the cultural context. The results reveal that metaphors of similar mapping conditions realized similarly constitute the most frequent category, followed by metaphors of similar mapping conditions realized differently, and then by metaphors of different mapping conditions. The study concludes with remarks on the strategies used in translating each category.
Assessing word commonness
Authors: Ekeland Paulsen Mikkel 
Published: November 2022

Abstract
The article investigates the two main corpus indicators of word commonness, frequency and dispersion, through a
cross-validation analysis of frequency and four dispersion measures (‘Range’, ‘Chi-squared’, ‘Deviation of Proportions’ and
‘Juilland’s D’). The approach provides an estimation of the capacity of the named measures to predict the distribution of corpus
items in an extracted language sample. Based on a dataset of 273 Norwegian compounds, the results show that especially Deviation
of Proportions is a robust measure of dispersion that can be used in conjunction with frequency to substantiate assertions of word
commonness based on corpus data. In addition, dispersion measures do not only reflect what sort of distribution the frequency
statistic is generated from, but also how reliable the frequency estimation in the corpus sample is in terms of giving an accurate
representation of frequency in the language variety that the corpus is sampled from.