bluuebunny/crossref_metadata_2025_split huggingface dataset:
Big data architecture and data mining analysis for market segment applications of differential global navigation satellite system (GNSS) services: case study of the analysis of the demand for navigation and agriculture
Authors: Martín Angel , Capilla Raquel Maria , Anquela Ana Belén 
Published: February 2022

AbstractLocation and navigation services based on global navigation satellite systems (GNSS) are needed for real-time high-precision positioning applications in relevant economic sectors, such as precision agriculture, transport, civil engineering or mapping. Real-time navigation users of GNSS networks have significantly increased all around the world, since the 1990s, and usage has exceeded initial expectations. Therefore, if the evolution of GNSS network users is monitored, the dynamics of market segments can be studied. The implementation of this hypothesis requires the treatment of big volumes of navigation data over several years and the continuous monitoring of customers. This paper is focused on the management of massive connection of GNSS users in an efficient way, in order to obtain analysis and statistics. Big data architecture and data analyses based on data mining algorithms have been implemented as the best way to approach the hypothesis. Results demonstrate the dynamic of users of different market segments, the increasing demand over the years and, specifically, conclusions are obtained about the trends, year-on-year correlation and business volume recovering after economic crisis periods.
2nd c. CE defenses around small towns in Roman Britain structured by road network connectivity
Authors: Lewis Joseph 
Published: February 2022

AbstractThe large-scale provision of defenses around small towns in Roman Britain during the 2nd c. CE is without parallel in the Roman Empire. Although the relationship between defended small towns and the Roman road network has been noted previously, provincial-level patterns remain to be explored. Using network analysis and spatial inference methods, this paper shows that defended small towns in the 2nd c. are on average better integrated within the road network – and located on road segments important for controlling the flow of information – than small towns at random. This research suggests that the fortification of small towns in the 2nd c. was structured by the connectivity of the Roman road network and associated with the functioning of thecursus publicus.
Intelligence as a planetary scale process
Authors: Frank Adam , Grinspoon David , Walker Sara 
Published: February 2022

AbstractConventionally, intelligence is seen as a property of individuals. However, it is also known to be a property of collectives. Here, we broaden the idea of intelligence as a collective property and extend it to the planetary scale. We consider the ways in which the appearance of technological intelligence may represent a kind of planetary scale transition, and thus might be seen not as something which happens on a planet but to a planet, much as some models propose the origin of life itself was a planetary phenomenon. Our approach follows the recognition among researchers that the correct scale to understand key aspects of life and its evolution is planetary, as opposed to the more traditional focus on individual species. We explore ways in which the concept may prove useful for three distinct domains: Earth Systems and Exoplanet studies; Anthropocene and Sustainability studies; and the study of Technosignatures and the Search for Extraterrestrial Intelligence (SETI). We argue that explorations of planetary intelligence, defined as the acquisition and application of collective knowledge operating at a planetary scale and integrated into the function of coupled planetary systems, can prove a useful framework for understanding possible paths of the long-term evolution of inhabited planets including future trajectories for life on Earth and predicting features of intelligentially steered planetary evolution on other worlds.
A FOURIER-TYPE CHARACTERISATION FOR GEVREY VECTORS ON HYPO-ANALYTIC STRUCTURES AND PROPAGATION OF GEVREY SINGULARITIES
Authors: Braun Rodrigues Nicholas 
Published: February 2022

AbstractIn this work we prove a Fourier–Bros–Iagolnitzer (F.B.I.) characterisation for Gevrey vectors on hypo-analytic structures and we analyse the main differences of Gevrey regularity and hypo-analyticity concerning the F.B.I. transform. We end with an application of this characterisation on a propagation of Gevrey singularities result for solutions of the nonhomogeneous system associated with the hypo-analytic structure for analytic structures of tube type.
Performance analysis of double-face logarithmic spiral metamaterial superstrate for full enhancement of circularly polarized 5G spiral patch antenna investigated using characteristic mode analysis
Authors: Abdelaziz Ahmed , Mohamed Hesham A. , Hamad Ehab K. I. 
Published: February 2022

AbstractIn this article, a novel double-face logarithmic spiral metamaterial (LSMTM) superstrate-inspired multiple-input multiple-output (MIMO) for fully enhanced circularly polarized (CP) antenna system is examined for 5G wireless communications. This novel double-face LSMTM superstrate acts as a planar concave-concave lens. Initially, the antenna is designed with a circular spiral patch to generate CP radiation in the frequency band of interest. Then, at a height of 6.5 mm (0.606 λo) above the MIMO antenna, which has a 0.8 mm (0.075 λo) edge-to-edge separation, the LSMTM superstrate is employed for isolation, gain, and bandwidth improvement. The proposed superstrate enhances the isolation, gain, and bandwidth of the antenna by about 32 dB, 3.47 dB, and 900 MHz, respectively. In contrast to the conventional technique of verifying operation with a simulated surface current distribution, characteristic mode analysis (CMA) is used to provide a better explanation of the proposed antenna's different modes and the creation of circular polarization. Additionally, the CMA supports the development of an effective technique that can predict whether or not the isolation can be further improved. The simulated results align with the measured results and are well adapted for 5G wireless communication devices.
A unified framework for the analysis of germination, emergence, and other time-to-event data in weed science
Authors: Onofri Andrea , Mesgaran Mohsen B. , Ritz Christian 
Published: February 2022

AbstractGermination and emergence assays represent the most notable examples of time-to-event data in agriculture and related disciplines. In spite of the peculiar characteristics of this type of data, there has been little effort to establish a specific and comprehensive framework for their analyses. Indeed, a brief survey of the literature shows that germination and emergence data, along with other phenological measurements such as flowering time, have been analyzed through myriad approaches, giving rise to confusion and uncertainty among scientists and practitioners as to what may represent the best statistical practice. This lack of coherence in statistical approach may reduce the efficiency of research, while making the communication of results and the cross-study comparisons extremely challenging. Here, we attempt to provide a coherent framework and protocol for the analyses of germination/emergence and other time-to-event data in weed science and related disciplines, together with a software implementation in the form of a new R package. We propose a similar approach to biological assays in ecotoxicology, based on: (1) fitting a time-to-event model to describe the whole time course of events; (2) comparing time-to-event curves across experimental treatments, and (3) deriving further information from the fitted model to better focus on some traits of interest. The most appropriate methods to accomplish this procedure were carefully selected from the framework of survival analysis and related sources and were modified to comply with the specific needs of weed, seed, and plant sciences. Finally, they were implemented in the new R package drcte. In this article, we describe the procedure and its limitations by way of providing examples of several types of germination/emergence assays. We highlight that our proposed procedure can also serve as the first step of data analyses, with its output subsequently submitted to traditional or meta-analytic approaches.
Influence of Urban Areas on Surface Water Loss in the Contiguous United States
Authors: Palazzoli I. , Montanari A. , Ceola S. 
Published: February 2022

AbstractUrbanization is one of the main drivers of surface water loss, which implies a transition from water to land. However, it is still unclear how urban areas affect the spatial pattern of surface water loss. Here, we use remotely sensed data to analyze and model the decrease of surface water extent and, in particular, the frequency of surface water loss as a function of distance from urban areas across the contiguous United States (CONUS). We employ an exponential distance‐decay model that confirms the presence of a higher frequency of surface water loss in the proximity of human settlements and provides innovative insights on surface water loss patterns at different spatial scales (i.e., river basins, water resource regions, and the CONUS). These spatial patterns are found to be influenced by climatic conditions, with more widely distributed losses in arid regions with respect to temperate and continental climates. Our results provide a new and deeper understanding of the spatial influence of urban areas on surface water loss, which could be effectively integrated in the definition of sustainable strategies for urbanization, water management, and surface water restoration, focused on both human and environmental water needs.
Optimal Cross‐Validation Strategies for Selection of Spatial Interpolation Models for the Canadian Forest Fire Weather Index System
Authors: Risk C. , James P. M. A. 
Published: February 2022

AbstractThe Canadian forest fire weather index (FWI) system requires spatially continuous, gridded weather data for temperature, relative humidity, wind speed, and precipitation. Reliable estimates of the Canadian FWI system components are needed to ensure the safety of communities, resources, and ecosystems. The quality of the interpolated input weather variables are typically evaluated using error estimates from cross‐validation. These error estimates are used for selecting between spatial interpolation methods for generating the continuous weather surfaces. Leave‐one‐out cross‐validation (LOOCV) is the most commonly used method, but it is biased in spatially clustered weather station networks. Accurate error estimation is important for selecting the optimal interpolation method and evaluating how well an interpolated surface represents true patterns in a weather variable. Other cross‐validation methods may better account for bias relating to clustered weather station networks. We present a comparison of cross‐validation methods for evaluating spatial interpolation models of weather variables for generating the inputs to the Canadian FWI system with the objective of determining whether they identify the same spatial interpolation model as having the lowest error. We found that LOOCV, shuffle‐split, stratified shuffle‐split, and a modified buffered leave‐one‐out procedure generally identified the same spatial interpolation models as having the lowest error. Spatial k‐fold favored spatial interpolation models with extrapolation ability. Our findings indicate that the most computationally efficient cross‐validation approach can be used for automatically selecting spatial interpolation models for weather surface generation, which will improve the quality of historical daily FWI maps.
Rates of Historical Anthropogenic Soil Erosion in the Midwestern United States
Authors: Thaler Evan A. , Kwang Jeffrey S. , Quirk Brendon J. , Quarrier Caroline L. , Larsen Isaac J. 
Published: February 2022

AbstractErosion degrades soils, reduces crop yields, and diminishes ecosystem services. The total amount of soil that has been eroded since the initiation of farming is unknown in most agricultural landscapes, which hinders assessment of soil erosion trends. In the Midwestern U.S., erosion has caused native prairie remnants to become perched above surrounding farmland, providing an opportunity to measure historical soil erosion rates. We use high‐resolution topographic surveys conducted across erosional escarpments at the boundary between 20 prairies and adjacent agricultural fields and show the median reduction in soil thickness ranges from 0.04 to 0.69 m, corresponding to erosion rates of 0.2–4.3 mm year−1, with a median value of 1.9 mm year−1. We used an association between the measured reduction in soil thickness and topographic curvature to predict regional soil erosion integrated since the beginning of farming to the present. We estimate a median historical erosion rate of 1.8 ± 1.2 mm year−1, which is nearly double the rate considered tolerable by the U.S. Department of Agriculture (USDA). Current soil loss predictions from the USDA National Resources Inventory (NRI) and the Daily Erosion Project (DEP) are lower than our historically averaged erosion rate by a factor of 3 and 8, respectively. We suggest that the NRI and the DEP underpredict soil loss rates because they do not include tillage erosion, a process shown to be important throughout the Midwestern U.S. Our findings indicate that further implementation of conservation practices is needed to reduce the high centennial‐averaged soil erosion rates that we measure to sustainable levels.
On the Resolution‐Dependence of Anvil Cloud Fraction and Precipitation Efficiency in Radiative‐Convective Equilibrium
Authors: Jeevanjee Nadir , Zhou Linjiong 
Published: February 2022

AbstractTropical anvil clouds are an important player in Earth's climate and climate sensitivity, but simulations of anvil clouds are uncertain. Here we identify and investigate one source of uncertainty by demonstrating a marked increase of anvil cloud fraction with resolution in cloud‐resolving simulations of radiative‐convective equilibrium. This increase in cloud fraction can be traced back to the resolution dependence of horizontal mixing between clear and cloudy air. A mixing timescale is diagnosed for each simulation using the cloud fraction theory of Seeley, Jeevanjee, Langhans, and Romps (2019) (https://doi.org/10.1029/2018GL080747) and is found to scale linearly with grid spacing, as expected from a simple scaling law. Thus mixing becomes more efficient with increasing resolution, generating more evaporation in middle and lower tropospheric updrafts. This decreases their precipitation efficiency (PE), thereby increasing their overall mass flux, leading to greater detrainment at the anvil level and hence higher anvil cloud fraction. The decrease in PE also yields a marked increase in relative humidity with resolution.
Relationship between astrocyte reactivity, using novel 11C-BU99008 PET, and glucose metabolism, grey matter volume and amyloid load in cognitively impaired individuals
Authors: Livingston Nicholas R. , Calsolaro Valeria , Hinz Rainer , Nowell Joseph , Raza Sanara , Gentleman Steve , Tyacke Robin J. , Myers Jim , Venkataraman Ashwin V. , Perneczky Robert , Gunn Roger N. , Rabiner Eugenii A. , Parker Christine A. , Murphy Philip S. , Wren Paul B. , Nutt David J. , Matthews Paul M. , Edison Paul 
Published: February 2022

AbstractPost mortem neuropathology suggests that astrocyte reactivity may play a significant role in neurodegeneration in Alzheimer’s disease. We explored this in vivo using multimodal PET and MRI imaging. Twenty subjects (11 older, cognitively impaired patients and 9 age-matched healthy controls) underwent brain scanning using the novel reactive astrocyte PET tracer 11C-BU99008, 18F-FDG and 18F-florbetaben PET, and T1-weighted MRI. Differences between cognitively impaired patients and healthy controls in regional and voxel-wise levels of astrocyte reactivity, glucose metabolism, grey matter volume and amyloid load were explored, and their relationship to each other was assessed using Biological Parametric Mapping (BPM). Amyloid beta (Aβ)-positive patients showed greater 11C-BU99008 uptake compared to controls, except in the temporal lobe, whilst further increased 11C-BU99008 uptake was observed in Mild Cognitive Impairment subjects compared to those with Alzheimer’s disease in the frontal, temporal and cingulate cortices. BPM correlations revealed that regions which showed reduced 11C-BU99008 uptake in Aβ-positive patients compared to controls, such as the temporal lobe, also showed reduced 18F-FDG uptake and grey matter volume, although the correlations with 18F-FDG uptake were not replicated in the ROI analysis. BPM analysis also revealed a regionally-dynamic relationship between astrocyte reactivity and amyloid uptake: increased amyloid load in cortical association areas of the temporal lobe and cingulate cortices was associated with reduced11C-BU99008 uptake, whilst increased amyloid uptake in primary motor and sensory areas (in which amyloid deposition occurs later) was associated with increased11C-BU99008 uptake. These novel observations add to the hypothesis that while astrocyte reactivity may be triggered by early Aβ-deposition, sustained pro-inflammatory astrocyte reactivity with greater amyloid deposition may lead to astrocyte dystrophy and amyloid-associated neuropathology such as grey matter atrophy and glucose hypometabolism, although the evidence for glucose hypometabolism here is less strong.
AAV2-VEGF-B gene therapy failed to induce angiogenesis in ischemic porcine myocardium due to inflammatory responses
Authors: Korpela Henna , Lampela Jaakko , Airaksinen Jonna , Järveläinen Niko , Siimes Satu , Valli Kaisa , Nieminen Tiina , Turunen Minttu , Grönman Maria , Saraste Antti , Knuuti Juhani , Hakulinen Mikko , Poutiainen Pekka , Kärjä Vesa , Nurro Jussi , Ylä-Herttuala Seppo 
Published: February 2022

AbstractTherapeutic angiogenesis induced by gene therapy is a promising approach to treat patients suffering from severe coronary artery disease. In small experimental animals, adeno-associated viruses (AAVs) have shown good transduction efficacy and long-term transgene expression in heart muscle and other tissues. However, it has been difficult to achieve cardiac-specific angiogenic effects with AAV vectors. We tested the hypothesis whether AAV2 gene transfer (1 × 1013 vg) of vascular endothelial growth factor B (VEGF-B186) together with immunosuppressive corticosteroid treatment can induce long-term cardiac-specific therapeutic effects in the porcine ischemic heart. Gene transfers were delivered percutaneously using direct intramyocardial injections, improving targeting and avoiding direct contact with blood, thus reducing the likelihood of immediate immune reactions. After 1- and 6-month time points, the capillary area was analyzed, myocardial perfusion reserve (MPR) was measured with radiowater positron emission tomography ([15O]H2O-PET), and fluorodeoxyglucose ([18F]FDG) uptake was used to evaluate myocardial viability. Clinical chemistry and immune responses were analyzed using standard methods. After 1- and 6-month follow-up, AAV2-VEGF-B186 gene transfer failed to induce angiogenesis and improve myocardial perfusion and viability. Here, we show that inflammatory responses attenuated the therapeutic effect of AAV2 gene transfer by significantly reducing successful transduction and long-term gene expression despite the efforts to reduce the likelihood of immune reactions and the use of targeted local gene transfer methods.
Including dominance effects in the prediction model through locus-specific weights on heterozygous genotypes can greatly improve genomic predictive abilities
Authors: Liu Tianfei , Luo Chenglong , Ma Jie , Wang Yan , Shu Dingming , Qu Hao , Su Guosheng 
Published: February 2022

AbstractThe dominance effect is considered to be a key factor affecting complex traits. However, previous studies have shown that the improvement of the model, including the dominance effect, is usually less than 1%. This study proposes a novel genomic prediction method called CADM, which combines additive and dominance genetic effects through locus-specific weights on heterozygous genotypes. To the best of our knowledge, this is the first study of weighting dominance effects for genomic prediction. This method was applied to the analysis of chicken (511 birds) and pig (3534 animals) datasets. A 5-fold cross-validation method was used to evaluate the genomic predictive ability. The CADM model was compared with typical models considering additive and dominance genetic effects (ADM) and the model considering only additive genetic effects (AM). Based on the chicken data, using the CADM model, the genomic predictive abilities were improved for all three traits (body weight at 12th week, eviscerating percentage, and breast muscle percentage), and the average improvement in prediction accuracy was 27.1% compared with the AM model, while the ADM model was not better than the AM model. Based on the pig data, the CADM model increased the genomic predictive ability for all the three pig traits (trait names are masked, here designated as T1, T2, and T3), with an average increase of 26.3%, and the ADM model did not improve, or even slightly decreased, compared with the AM model. The results indicate that dominant genetic variation is one of the important sources of phenotypic variation, and the novel prediction model significantly improves the accuracy of genomic prediction.
Live-dead assay on unlabeled cells using phase imaging with computational specificity
Authors: Hu Chenfei , He Shenghua , Lee Young Jae , He Yuchen , Kong Edward M. , Li Hua , Anastasio Mark A. , Popescu Gabriel 
Published: February 2022

AbstractExisting approaches to evaluate cell viability involve cell staining with chemical reagents. However, the step of exogenous staining makes these methods undesirable for rapid, nondestructive, and long-term investigation. Here, we present an instantaneous viability assessment of unlabeled cells using phase imaging with computation specificity. This concept utilizes deep learning techniques to compute viability markers associated with the specimen measured by label-free quantitative phase imaging. Demonstrated on different live cell cultures, the proposed method reports approximately 95% accuracy in identifying live and dead cells. The evolution of the cell dry mass and nucleus area for the labeled and unlabeled populations reveal that the chemical reagents decrease viability. The nondestructive approach presented here may find a broad range of applications, from monitoring the production of biopharmaceuticals to assessing the effectiveness of cancer treatments.
An archaellum filament composed of two alternating subunits
Authors: Gambelli Lavinia , Isupov Michail N. , Conners Rebecca , McLaren Mathew , Bellack Annett , Gold Vicki , Rachel Reinhard , Daum Bertram 
Published: February 2022

AbstractArchaea use a molecular machine, called the archaellum, to swim. The archaellum consists of an ATP-powered intracellular motor that drives the rotation of an extracellular filament composed of multiple copies of proteins named archaellins. In many species, several archaellin homologs are encoded in the same operon; however, previous structural studies indicated that archaellum filaments mainly consist of only one protein species. Here, we use electron cryo-microscopy to elucidate the structure of the archaellum from Methanocaldococcus villosus at 3.08 Å resolution. The filament is composed of two alternating archaellins, suggesting that the architecture and assembly of archaella is more complex than previously thought. Moreover, we identify structural elements that may contribute to the filament’s flexibility.