bluuebunny/crossref_metadata_2025_split huggingface dataset:
Angebotsstrukturen der ambulanten vertragsärztlichen Versorgung: Deutschland und andere dezentral organisierte Gesundheitssysteme
Authors: Hahn Ursula , Baulig Christine , Brzoska Patrick 
Published: March 2021

Zusammenfassung
Hintergrund Das Bild vertragsärztlicher Versorgung ist arztbezogen; wenig beachtet wird der (potentielle) Einfluss von Versorgungsorganisationen (VO) und deren Merkmalen auf das Versorgungsgeschehen.
Ziel Beschreibung der organisationsbezogenen Angebotsstrukturen nach Rechtsformen, Abgleich mit denen anderer dezentral organisierter Gesundheitssysteme und Diskussion, ob sich entlang der Rechtsform Effekte für verschiedene Dimensionen des Versorgungsgeschehens zeigen lassen.
Material und Methoden Die Häufigkeiten von Einzelpraxis, Gemeinschaftspraxis und Medizinischen Versorgungszentren (MVZ) für haus- und fachärztliche Versorgungsbereiche, die durchschnittliche ärztliche Teamstärke und der Anteil der VO mit interdisziplinärer Aufstellung werden auf Basis von Sekundärdatenquellen (überwiegend Kassenärztliche Bundesvereinigung) im Zeitablauf beschrieben.
Ergebnisse Die Angebotsstrukturen sind durch hohe Fragmentierung (2018:>80 000 VO) mit hohem Anteil von Kleinstorganisationen (über alle VO 73% Einzelpraxen), niedriger durchschnittlicher Teamstärke (über alle VO 1,7 Ärzte) und geringem Anteil mit interdisziplinärer Aufstellung (17% aller Gemeinschaftspraxen und MVZ) bei geringer Konzentrationsdynamik in der haus- und fachärztlichen Versorgung geprägt.
Schlussfolgerungen Die Kleinteiligkeit der deutschen Angebotsstrukturen ist ausgeprägter bzw. persistierender als die in anderen dezentralen Gesundheitssystemen. Rechtsformen und Durchschnittswerte erfassen die Heterogenität der VO-Morphologien nur unzureichend. Wünschenswert, z. B. für eine gezielte Versorgungssteuerung, wäre eine breitere Datenbasis zu mehr organisationsbezogenen Merkmalen.
Studies towards the Synthesis of (–)-Pulvomycin: Construction of the C12–C40 Segment by a Stereoselective Aldol Reaction
Authors: Bach Thorsten , Wienhold Sebastian , Fritz Lukas , Judt Tatjana , Hackl Sabrina , Neubauer Thomas , Sauerer Bastian 
Published: March 2021

AbstractA convergent strategy was developed for the synthesis of the C12–C40 segment of (–)-pulvomycin. Key step was a diastereoselective aldol reaction between a chiral ethyl ketone representing the C24–C40 fragment and a chiral aldehyde representing the C12–C23 fragment. Both compounds were prepared from enantiomerically pure building blocks in a convergent fashion. The longest linear sequence commenced with a known d-fucose-derived glycosyl donor and entailed a total number of 16 steps. The desired anti-aldol product was obtained in a total yield of 5% over these steps and contains 12 out of 13 stereogenic centers present in the natural product.
Searching the PDF Haystack: Automated Knowledge Discovery in Scanned EHR Documents
Authors: Kostrinsky-Thomas Alexander L. , Hisama Fuki M. , Payne Thomas H. 
Published: March 2021

Abstract
Background Clinicians express concern that they may be unaware of important information contained in voluminous scanned and other outside documents contained in electronic health records (EHRs). An example is “unrecognized EHR risk factor information,” defined as risk factors for heritable cancer that exist within a patient's EHR but are not known by current treating providers. In a related study using manual EHR chart review, we found that half of the women whose EHR contained risk factor information meet criteria for further genetic risk evaluation for heritable forms of breast and ovarian cancer. They were not referred for genetic counseling.
Objectives The purpose of this study was to compare the use of automated methods (optical character recognition with natural language processing) versus human review in their ability to identify risk factors for heritable breast and ovarian cancer within EHR scanned documents.
Methods We evaluated the accuracy of the chart review by comparing our criterion standard (physician chart review) versus an automated method involving Amazon's Textract service (Amazon.com, Seattle, Washington, United States), a clinical language annotation modeling and processing toolkit (CLAMP) (Center for Computational Biomedicine at The University of Texas Health Science, Houston, Texas, United States), and a custom-written Java application.
Results We found that automated methods identified most cancer risk factor information that would otherwise require clinician manual review and therefore is at risk of being missed.
Conclusion The use of automated methods for identification of heritable risk factors within EHRs may provide an accurate yet rapid review of patients' past medical histories. These methods could be further strengthened via improved analysis of handwritten notes, tables, and colloquial phrases.
Evaluating the effects of shelter-in-place policies during the COVID-19 pandemic
Authors: Berry Christopher R. , Fowler Anthony , Glazer Tamara , Handel-Meyer Samantha , MacMillen Alec 
Published: March 2021

Significance
We study the health, behavioral, and economic effects of one of the most politically controversial policies in recent memory, shelter-in-place orders during the COVID-19 pandemic. Previous studies have claimed that shelter-in-place orders saved thousands of lives, but we reassess these analyses and show that they are not reliable. We find that shelter-in-place orders had no detectable health benefits, only modest effects on behavior, and small but adverse effects on the economy. To be clear, our study should not be interpreted as evidence that social distancing behaviors are not effective. Many people had already changed their behaviors before the introduction of shelter-in-place orders, and shelter-in-place orders appear to have been ineffective precisely because they did not meaningfully alter social distancing behavior.
The defaultness hypothesis
Authors: Giora Rachel 
Published: March 2021

Abstract
This paper demonstrates that, when interpretation is at stake, it is only degree of defaultness that matters. Neither degree of Negation, nor degree of Affirmation, nor equal degree of Novelty, nor equal degree of Literalness/Nonliteralness, nor equal strength of Contextual support, whether linguistic or pictorial (see Heruti et al. 2019), makes a difference. Instead, it is only degree of defaultness that counts. Indeed, having established degree of defaultness of negatives and affirmatives (Experiment 1.1) and their processing cost when in isolation (Experiment 1.2), we further attested to the speed superiority of default negative interpretations, which seemed more pronounced in the Left Hemisphere rather than in the Right Hemisphere (Experiment 1.2; see Giora, Cholev et al. 2018).We then further attested to the speed superiority of these negatives, when embedded in equally strong supportive contexts. Here, we also show that default Negative Sarcasm is processed significantly faster than nondefault Affirmative Sarcasm (Experiment 2). And when embedded in equally strong sarcastically biasing contexts, both hemispheres reflect the superiority of default Negative Sarcasm over nondefault Affirmative Sarcasm (Experiments 2.1–2.2). However, given Affirmative Sarcasm’s nondefaultness, it is only nondefault Affirmative Sarcasmthat is expected and shown to rely on cueing for its derivation (Corpus-based Studies 1–2, Section 3). Still, when hedonic effects are considered (see Section 4), it is only utterances’ nondefault interpretations, whether in linguistic (Experiment 3) or pictorial contexts (Experiment 4), that are entertaining, given that they make up Optimal Innovations, while involving default interpretations in the process (see Giora et al. 2004, 2017). It is degree of defaultness, then, that affects both (i) processing speed (whether in or out of context), (ii) reliance on cueing, and (iii) hedonic effects. Finally, in Section 5, our results and conclusions are summarized.
Unweaving the embodied nature of English temporal prepositions
Authors: Morras Cortés Javier A. , Wen Xu 
Published: March 2021

AbstractThe metaphortime is space(Lakoff & Johnson 1999) and the pervasiveness of metaphor and image-schematic structure in human conceptualization (Johnson 1987;Hampe 2005) have been widely accepted among cognitive scientists as constructs that help explain non-spatial and temporal linguistic constructions. However, Conceptual Metaphor Theory (CMT) might not be the whole story. While it is acceptable that moments in time can be construed as being analogous to points in space as in utterances such asatthe cornervs.at2:30, there seems to be much moretemporal cognitionthan previously thought. It turns out that time exhibits its own structure (followingEvans 2004,2013;Galton 2011) that is based on transience. This idea has made some scholars support the weak version of CMT which posits that the temporal meaning of prepositions is represented and processed independently of the corresponding spatial meanings (seeKemmerer 2005for such a view). The present article supports the idea that spatial and temporal structures complement each other in order to achieve temporal conceptions. This is indeed a conceptual pattern showed by the English prepositionatthat makes use of an extrinsic temporal reference to activate its temporal semantics. To analyze the different temporal realizations thatatmay have, the paper aims to identify the topological structure that underlies theconceptual basisof this preposition. This allows us to appreciate how the spatio-conceptual structure ofatpartially structures temporal conceptions. The paper also identifies the nature of the temporal structure that is involved in temporal realizations. The article concludes with some remarks, among them the pivotal role of the schematic temporal structure that is captured by the extrinsic temporal reference, and the role of conceptual metaphor in underdetermining temporal thinking.
Our metaphorical minds
Authors: Su Lily I-wen 
Published: March 2021

Abstract
Aside from metaphor being an important language device reflecting human cognition, it also provides a window into the
understanding of culture (Kövecsec 2019). Language is a function of culture because it is a form
of the verbal and nonverbal systems by which a group member can communicate with another member. Language connects people of the same
cultural identity because it functions as a common bond between people who have the same linguistic heritage. As argued in Verhagen (2008), values of one’s understanding of the world he lives in may in turn be influenced by
the conceptual metaphors he unconsciously holds to visualize his world. Verhagen has provided a valuable standpoint, yet it is
western-centered and European-oriented. Through metaphors identified in Chinese in proverbs, food, marriage, and time expressions, this
paper intends to address the following questions: Does conceptual metaphors reflect any specific Chinese mode of thinking? Does
such conceptualization give a taste of Chinese culture? What kind(s) of theoretical and pragmatic implications can be derived from our line
of investigation? It is thus hoped that this paper may provide empirical evidence with reference to mappings between thought and language,
which in turn, may serve as a way to explore culture.
Hedychium gardnerianum (kahili ginger).
Authors: Djeddour Djamila 
Published: March 2021

Abstract

Native to the Eastern Himalayas, H. gardnerianum has been widely introduced as an ornamental in different regions of the world. It continues to be available as an ornamental and is therefore likely to spread further.H. gardnerianum is an ecologically versatile plant with rapid vegetative growth, the dense rhizome system of the plant prevents regeneration of other species. This very aggressive, shade-tolerant plant is able to form dense thickets on undisturbed sites in the understorey of open and closed-canopy native rain forests and managed forests, as well as in open areas (forest margins, ravines or path sides). Its high seed production and efficient dispersal by rats and birds, allows it to persist in invaded areas for a long time and establish new points of invasion. As H. gardnerianum is able to invade native forests, ecological, conservation and cultural values are threatened and it is a major threat to native biodiversity.
Rotational superradiance with Bogoliubov dispersion
Authors: Patrick Sam 
Published: March 2021

Abstract
Rotational superradiance affects the dynamics of many rotating systems in nature, through either stimulated or spontaneous extraction of energy and angular momentum. By now, this process is well-studied in the relativistic setting, where systems are intrinsically dispersion-free. In many condensed matter systems, however, dispersion is an unavoidable aspect of the description for the short wavelength modes. For these systems, how might one expect superradiance to be modified? In this work, an answer to this question is provided using an illustrative example. The scattering of linear excitations of a Bose–Einstein condensate (BEC) are studied in the presence of a rotating, draining vortex flow using the full Bogoliubov dispersion relation. It is shown that dispersion suppresses the extraction of energy and angular momentum, firstly, by decreasing the superradiant bandwidth, and secondly, by preventing high-angular momentum modes from superradiating.
3D Compton scattering imaging with multiple scattering: analysis by FIO and contour reconstruction
Authors: Rigaud Gaël 
Published: March 2021

Abstract
3D Compton scattering imaging (CSI) is an upcoming concept exploiting the scattering of photons induced by the electronic structure of the object under study. The so-called Compton scattering rules the collision of particles with electrons and describes their energy loss after scattering. Although physically relevant, multiple-order scattering was so far not considered and therefore, only first-order scattering is generally assumed in the literature. The purpose of this work is to argument why and how a contour reconstruction of the electron density map from scattered measurement composed of first- and second-order scattering is possible (scattering of higher orders are here neglected). After the development of integral representations for the first- and second-order scattering, we approximate these models by Fourier integral operators (FIO) and study their smoothness properties. The second-order scattered radiation reveals itself to be structurally smoother than the radiation of first-order indicating that the contours of the electron density are essentially encoded within the first-order part. This opens the way to contour-based reconstruction techniques when considering multiple scattered data. Our main results, modeling and reconstruction scheme, are successfully implemented on synthetic and Monte-Carlo data.
Twisted-shape selection of self-assembled Si

⟨100⟩

nanobelts and nanowires
Authors: Danesh V , Pishkenari H Nejat , Zohoor H 
Published: March 2021

Abstract
This letter discusses the surface-reconstruction-induced self-twisting behavior of Si〈100〉 nanobelts and nanowires (NWs) with rectangular cross section. Giving a thorough physical interpretation, we explain the reason behind this phenomenon and present a continuum-based model. It is revealed that these structures can self-assemble into both right- and left-handed helicoids depending on their crystal arrangements. More specifically, for NWs with the same number of layers in each of their cross sections directions, two distinct values of torsion angle are possible for each of right- and left-handed twisted morphologies. In conclusion, four modes of torsion can be observed in Si〈100〉 NWs. Furthermore, some atomistic simulations are conducted to substantiate analytical results by utilizing Tersoff’s potential. These results confirm the precision of the analytical discussions and are in good agreement with the continuum model predictions. Finally, the results of Tersoff’s potential are validated by a density functional based tight-binding model.
Machine learning for proton path tracking in proton computed tomography
Authors: Lazos Dimitrios , Collins-Fekete Charles-Antoine , Bober Miroslaw , Evans Philip , Dikaios Nikolaos 
Published: March 2021

Abstract
A Machine Learning approach to the problem of calculating the proton paths inside a scanned object in proton Computed Tomography is presented. The method is developed in order to mitigate the loss in both spatial resolution and quantitative integrity of the reconstructed images caused by multiple Coulomb scattering of protons traversing the matter. Two Machine Learning models were used: a forward neural network (NN) and the XGBoost method. A heuristic approach, based on track averaging was also implemented in order to evaluate the accuracy limits on track calculation, imposed by the statistical nature of the scattering. Synthetic data from anthropomorphic voxelized phantoms, generated by the Monte Carlo (MC) Geant4 code, were utilized to train the models and evaluate their accuracy, in comparison to a widely used analytical method that is based on likelihood maximization and Fermi−Eyges scattering model. Both NN and XGBoost model were found to perform very close or at the accuracy limit, further improving the accuracy of the analytical method (by 12% in the typical case of 200 MeV protons on 20 cm of water object), especially for protons scattered at large angles. Inclusion of the material information along the path in terms of radiation length did not show improvement in accuracy for the phantoms simulated in the study. A NN was also constructed to predict the error in path calculation, thus enabling a criterion to filter out proton events that may have a negative effect on the quality of the reconstructed image. By parametrizing a large set of synthetic data, the Machine Learning models were proved capable to bring—in an indirect and time efficient way—the accuracy of the MC method into the problem of proton tracking.
Light-weight cross-view hierarchical fusion network for joint localization and identification in Alzheimer’s disease with adaptive instance-declined pruning
Authors: Han Kangfu , Luo Jiaxiu , Xiao Qing , Ning Zhenyuan , Zhang Yu 
Published: March 2021

Abstract
Magnetic resonance imaging (MRI) has been widely used in assessing development of Alzheimer’s disease (AD) by providing structural information of disease-associated regions (e.g. atrophic regions). In this paper, we propose a light-weight cross-view hierarchical fusion network (CvHF-net), consisting of local patch and global subject subnets, for joint localization and identification of the discriminative local patches and regions in the whole brain MRI, upon which feature representations are then jointly learned and fused to construct hierarchical classification models for AD diagnosis. Firstly, based on the extracted class-discriminative 3D patches, we employ the local patch subnets to utilize multiple 2D views to represent 3D patches by using an attention-aware hierarchical fusion structure in a divide-and-conquer manner. Since different local patches are with various abilities in AD identification, the global subject subnet is developed to bias the allocation of available resources towards the most informative parts among these local patches to obtain global information for AD identification. Besides, an instance declined pruning algorithm is embedded in the CvHF-net for adaptively selecting most discriminant patches in a task-driven manner. The proposed method was evaluated on the AD Neuroimaging Initiative dataset and the experimental results show that our proposed method can achieve good performance on AD diagnosis.
Particle-in-cell simulations of parallel dynamics of a blob in the scrape-off-layer plasma of a generic medium-size tokamak
Authors: Costea S , Kovačič J , Tskhakaya D , Schrittwieser R , Gyergyek T , Popov Tsv K 
Published: March 2021

Abstract
In this work we investigate, in a fully-kinetic particle approach, the evolution of a blob inside a flux tube in the scrape-off-layer (SOL) plasma of a generic diverted medium-size tokamak and its contribution to the recorded particle and energy flux densities at the divertor. Initially, a steady-state background plasma is reached, with realistic plasma profiles in the parallel direction. On top of it, a blob source with given intensity and temperature is superimposed at the outer midplane. The blob source is active for 10

μ

s

in order to emulate a generic blob with 1 cm diameter crossing the magnetic flux tube with a typical 1 km s−1 radial drift velocity. We have observed that most of the blob’s hot electrons are screened off by the cold electrons of the SOL plasma and can travel towards the two divertors free of the initial ambipolar forces. Performing a density scan and having a blob-to-background density ratio

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in the source region, we observe that due to Coulomb collisions these hot electrons can reach the outer divertor or also the inner one, depending on the density of the background SOL plasma. Consequently, the midplane–divertor potential difference increases and the sheath expands leading to a significant increase in the background ion energy flux density onto the divertor. We also observe that when the blob ions reach the divertor the electron flux density on the divertor increases due to ambipolar forces. Through Coulomb collisions, a part of the thermal energy of the hot blob ions is transferred to the main (background) plasma, depending on the plasma density. Most of the energy deposited into the divertor is brought by the ions and the blob-induced background ion energy flux density becomes comparable (low-density case) or much higher (high-density case) than the blob ion energy flux density.
Kinetic equilibrium reconstructions of plasmas in the MAST database and preparation for reconstruction of the first plasmas in MAST upgrade
Authors: Berkery J W , Sabbagh S A , Kogan L , Ryan D , Bialek J M , Jiang Y , Battaglia D J , Gibson S , Ham C 
Published: March 2021

Abstract
Reconstructions of plasma equilibria using magnetic sensors were routine during operation of the Mega Ampere Spherical Tokamak (MAST) device, but reconstructions using kinetic profiles were not. These are necessary for stability and disruption analysis of the MAST database, as well as for operation in the upgrade to the device, MAST-U. The three-dimensional (3D) code VALEN is used to determine eddy currents in the 3D vessel structures for vacuum coil test shots, which are then mapped to effective resistances in the two-dimensional vessel groupings in the EFIT equilibrium reconstruction code to be used in conjunction with nearby loop voltage measurements for estimated currents in the structures during reconstruction. Kinetic equilibrium reconstructions with EFIT, using all available magnetic sensors as well as Thomson scattering measurements of electron temperature and density, charge exchange recombination spectroscopy measurements of ion temperature, and internal magnetic field pitch angle measurements from a motional Stark effect (MSE) diagnostic are performed for a large database of MAST discharges. Excellent convergence errors are obtained for the portions of the discharges where the stored energy was not too low, and it is found that reconstructions performed with temperature and density measurements but without MSE data usually already match the pitch angle measurements well. A database of 275 kinetic equilibria is used to test the ideal MHD stability calculation capability for MAST. Finally, the necessary changes to conducting structure in VALEN, and diagnostic setup in EFIT have been completed for the upgrade from MAST to MAST-U, enabling kinetic reconstructions to commence from the first plasma discharges of the upgraded device.