bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combining Halo-EFT Descriptions of Nuclei and Precise Models of Nuclear Reactions
Authors: Capel Pierre 
Published: December 2021

AbstractThe clear separation of scales observed in halo nuclei between the extended halo and the compact core makes these exotic nuclei a perfect subject for effective field theory (EFT). Such description leads to a systematic expansion of the core-halo Hamiltonian, which naturally orders the nuclear-structure observables. In this short review, I show the advantages there are to include Halo-EFT descriptions within precise models of reactions. It helps identifying the nuclear-structure observables that matter in the description of the reactions, and enables us to easily bridge predictions of nuclear-structure calculations to reaction observables. I illustrate this on breakup, transfer and knockout reactions with $$^{11}$$

11

Be, the archetypical one-neutron halo nucleus.
Physikalische Interventionen als Alternative/Ergänzung zum chirurgischen Wunddebridement
Authors: Werra Ursula Elisabeth Maria , Zinser Max , Dorweiler Bernhard 
Published: December 2021

Zusammenfassung
Hintergrund
Die Versorgung von Patienten mit chronischen Wunden verursacht in Deutschland jährliche Kosten in Höhe von 8 Mrd. €.
Häufig ist ein chirurgisches Debridement notwendig. Wenn jedoch kritische Strukturen lokal angrenzen oder der Patient nur eingeschränkt narkosefähig ist, können die Einsatzmöglichkeiten limitiert sein.
Zusätzlich ist aus wirtschaftlichen Gründen eine mögliche Delegierbarkeit immer von Interesse.

Fragestellung
Wir präsentieren alternative sowie ergänzende Methoden zum chirurgischen Debridement aus dem Portfolio der physikalischen Interventionen.

Material und Methoden
Ultraschallassistiertes Wunddebridement (UAW), Kaltplasma sowie Photobiomodulation basieren auf interessanten Grundprinzipien mit vielversprechendem Entwicklungspotenzial. Der Wirkmechanismus, die Evidenzlage sowie wirtschaftliche Aspekte werden vorgestellt.

Ergebnisse
Es zeigt sich insgesamt aufgrund der Inhomogenität der Daten eine nur schwache Evidenzlage. Auch einige Aspekte der Behandlungsmodalitäten sind noch nicht abschließend geklärt.
Das UAW stellt eine echte Alternative dar. Es erfährt eine hohe Patientenakzeptanz und ist ambulant durchführbar.
Die Wirksamkeit von Kaltplasma oder Photobiomodulation ist noch nicht abschließend beurteilbar. Es zeigen sich jedoch positive klinische Ergebnisse.

Diskussion
Das chirurgische Debridement ist auch aktuell (noch) nicht vollständig ersetzbar. Alternative Methoden wie das UAW können jedoch einen zusätzlichen Benefit bieten. Wunden können so teilweise frühzeitig (mit entsprechender Kostenersparnis) ambulant behandelt werden. Eine weitere wichtige Stärke stellt zudem die Wirksamkeit bezüglich multiresistenter Erreger dar.
Es besteht die Notwendigkeit zur Initiierung weiterer klinischer Studien, da die aktuelle Datenlage noch viele offene Fragen aufweist.
Untersuchung und Klassifikation der Fahreraufmerksamkeit bei längerer partiell automatisierter Fahrt
Authors: Hugenroth Alexander , Warnecke Alexander , Bertram Torsten 
Published: December 2021

ZusammenfassungUm die Unfallzahlen weiter zu senken, schreibt die Europäische Union ab 2030 eine höhere Fahrerüberwachung für neue Fahrzeuge vor. Bislang liegt der Fokus in einem manuell gefahrenen Fahrzeug auf einer Müdigkeitserkennung als Komfortsystem. Jedoch ändern sich die Anforderungen an den Fahrer und dessen Aufgaben bei steigender Automatisierung der Fahraufgabe, sodass auch die Fahrerbeobachtung/-überwachung weiter entwickelt werden sollte. Die vorliegende Arbeit beschäftigt sich mit der Auslegung von Aufmerksamkeitsaufgaben in Simulator-Fahrversuchen und einem ersten Versuch die aufgenommenen Daten von wenigen Probanden automatisch auszuwerten, um die Machbarkeit zu zeigen. Durch die partielle Automatisierung (nach SAE Level 2) der Fahraufgabe bleiben dem Fahrer bei der hier vorgestellten längeren Aufmerksamkeitsaufgabe nur noch schwache und seltene Reize, sodass von einer Vigilanzaufgabe gesprochen werden kann. Zur Messung des Fahrerzustands wird in dieser Machbarkeitsstudie eine Kombination aus verschieden Körperfunktionen durch unterschiedliche Sensoren erfasst, mit einem künstlichen neuronalen Netzwerk fusioniert und verarbeitet. Es werden verschiedene Kombinationen von Sensoren getestet, um herauszufinden, welche Signale für eine Klassifikation des Fahrerzustands ausreichend oder notwendig sind. Dabei wird darauf geachtet, ob diese Signale in Zukunft durch neue Sensortechnologien auch kontaktlos erfasst werden könnten, um eine Entwicklung dieser zu motivieren. Am Ende wird eine Klassifizierung vorgenommen, die zwischen den hier so genannten Zuständen Vigilant (aufmerksam) und Hypovigilant (nicht mehr aufmerksam) unterscheiden kann, sodass eine anschließende Regelung ein solches Signal verwenden kann, um den Fahrer in einen besseren Zustand zu bringen. Zudem kann der Fahrer gewarnt werden, wenn die Aufmerksamkeit nicht zu den Aufgaben passt, die er in der Automatisierungsstufe zu erledigen hat beziehungsweise für die er verantwortlich ist. Dazu könnten Aufgaben zwischen dem Fahrzeug und dem Fahrer dynamisch verteilt werden, also beispielsweise die Führung in Längs- oder Querrichtung wieder als Fahraufgabe dem Fahrer übergeben werden, um ihn aufmerksam zu halten. Durch eine kontaktlose Erfassung der Aufmerksamkeit gibt es zudem einen Komfortgewinn, da zum Beispiel die Hände nicht mehr das Lenkrad festhalten müssen, um dem Fahrzeug seine Aufmerksamkeit zu bestätigen, wie es heute in einigen Fahrzeugen üblich ist.
Recent Lateral Expansion of Sphagnum Bogs Over Central Fen Areas of Boreal Aapa Mire Complexes
Authors: Granlund Lars , Vesakoski Ville , Sallinen Antti , Kolari Tiina H. M. , Wolff Franziska , Tahvanainen Teemu 
Published: December 2021

AbstractWe investigated recent changes in spatial patterning of fen and bog zones in five boreal aapa mire complexes (mixed peatlands with patterned fen and bog parts) in a multiproxy study. Comparison of old (1940–1970s) and new aerial images revealed decrease of flarks (wet hollows) in patterned fens by 33–63% in middle boreal and 16–42% in northern boreal sites, as lawns of bog Sphagnum mosses expanded over fens. Peat core transects across transformed areas were used to verify the remote sensing inference with stratigraphic analyses of macrofossils, hyperspectral imaging, and age-depth profiles derived from 14C AMS dating and pine pollen density. The transect data revealed that the changes observed by remote sensing during past decades originated already from the end of the Little Ice Age (LIA) between 1700–1850 CE in bog zones and later in the flarks of fen zones. The average lateral expansion rate of bogs over fen zones was 0.77 m y−1 (range 0.19–1.66) as estimated by remote sensing, and 0.71 m y−1 (range 0.13–1.76) based on peat transects. The contemporary plant communities conformed to the macrofossil communities, and distinct vegetation zones were recognized as representing recently changed areas. The fen-bog transition increased the apparent carbon accumulation, but it can potentially threaten fen species and habitats. These observations indicate that rapid lateral bog expansion over aapa mires may be in progress, but more research is needed to reveal if ongoing fen-bog transitions are a commonplace phenomenon in northern mires.
Tree Diversity, Initial Litter Quality, and Site Conditions Drive Early-Stage Fine-Root Decomposition in European Forests
Authors: Wambsganss Janna , Freschet Grégoire T. , Beyer Friderike , Bauhus Jürgen , Scherer-Lorenzen Michael 
Published: December 2021

AbstractDecomposition of dead fine roots contributes significantly to nutrient cycling and soil organic matter stabilization. Most knowledge of tree fine-root decomposition stems from studies in monospecific stands or single-species litter, although most forests are mixed. Therefore, we assessed how tree species mixing affects fine-root litter mass loss and which role initial litter quality and environmental factors play. For this purpose, we determined fine-root decomposition of 13 common tree species in four European forest types ranging from boreal to Mediterranean climates. Litter incubations in 315 tree neighborhoods allowed for separating the effects of litter species from environmental influences and litter mixing (direct) from tree diversity (indirect). On average, mass loss of mixed-species litter was higher than those of single-species litter in monospecific neighborhoods. This was mainly attributable to indirect diversity effects, that is, alterations in microenvironmental conditions as a result of tree species mixing, rather than direct diversity effects, that is, litter mixing itself. Tree species mixing effects were relatively weak, and initial litter quality and environmental conditions were more important predictors of fine-root litter mass loss than tree diversity. We showed that tree species mixing can alter fine-root litter mass loss across large environmental gradients, but these effects are context-dependent and of moderate importance compared to environmental influences. Interactions between species identity and site conditions need to be considered to explain diversity effects on fine-root decomposition.
After the smoke has cleared: Extended low fruit productivity following forest fires decreased gregariousness and social tolerance among wild female Bornean orangutans (Pongo pygmaeus wurmbii)
Authors: Ashbury Alison M. , Meric de Bellefon Jade , Kunz Julia A. , Abdullah Misdi , Marzec Anna M. , Fryns Caroline , Utami Atmoko Sri Suci , van Schaik Carel P. , van Noordwijk Maria A. 
Published: December 2021

AbstractAs climate change continues to fundamentally alter resource landscapes, the ability to flexibly respond to spatio-temporal changes in the distribution of preferred food sources is increasingly important for the overall health and fitness of animals living in seasonal, variable, and/or changing environments. Here, we investigate the effects of an uncharacteristically long period of fruit scarcity, following widespread thick haze caused by peat and forest fires in 2015, on the behaviour and sociality of female Bornean orangutans (Pongo pygmaeus wurmbii). We collected data from 2010 to 2018 at Tuanan, Central Kalimantan, Indonesia, and compared the activity, diet, and association patterns of adult females during low-fruit periods before the fires, i.e., regular, seasonal periods of low fruit availability (“pre-fire”), and after the fires, i.e., during the extended period of low fruit availability (“post-fire”). First, we found that, post-fire, female orangutans adopted a more extreme energy-saving activity pattern and diet — resting more, travelling less, and diet-switching to less-preferred foods — compared to pre-fire. Second, we found that the probabilities of association between females and their weaned immature offspring, and between related and unrelated adult females were lower, and the probability of agonism between unrelated females was higher, post-fire than pre-fire. This change in energetic strategy, and the general reduction in gregariousness and social tolerance, demonstrates how forest fires can have lasting consequences for orangutans. Fission–fusion species such as orangutans can mitigate the effects of changes in resource landscapes by altering their (sub)grouping patterns; however, this may have long-term indirect consequences on their fitness.
Ratcheting and recovery of adhesively bonded joints under tensile cyclic loading
Authors: Chen Yi , Smith Lloyd V. 
Published: December 2021

AbstractPolymers in general, and adhesives in particular, can exhibit nonlinear viscoelastic–viscoplastic response. Prior work has shown that this complex behavior can be described using analytical models, which provided good agreement with measured creep and recovery response. Under cyclic loading, however, some adhesives exhibit a temporal response different from what would be expected from their creep behavior. Ratcheting describes the accumulation of deformation from cyclic loading. The failure surfaces of adhesives subjected to creep and cyclic loads provide evidence of failure modes that depend on the loading history, suggesting a cause for the change in temporal response. The following considers two approaches to describe the ratcheting behavior of adhesives. Given the reduced time dependence, the first approach involved a nonlinear viscoelastic–plastic model. The second approach used a nonlinear viscoelastic–viscoplastic model, calibrated from the cyclic response, rather than the creep response. While both models showed good agreement with experiment for long exposure to cyclic loading, only the viscoelastic–viscoplastic model agreed with experiment for both short and long loading histories.
Untargeted metabolomics of COVID-19 patient serum reveals potential prognostic markers of both severity and outcome
Authors: Roberts Ivayla , Wright Muelas Marina , Taylor Joseph M. , Davison Andrew S. , Xu Yun , Grixti Justine M. , Gotts Nigel , Sorokin Anatolii , Goodacre Royston , Kell Douglas B. 
Published: December 2021

Abstract
Introduction
The diagnosis of COVID-19 is normally based on the qualitative detection of viral nucleic acid sequences. Properties of the host response are not measured but are key in determining outcome. Although metabolic profiles are well suited to capture host state, most metabolomics studies are either underpowered, measure only a restricted subset of metabolites, compare infected individuals against uninfected control cohorts that are not suitably matched, or do not provide a compact predictive model.

Objectives
Here we provide a well-powered, untargeted metabolomics assessment of 120 COVID-19 patient samples acquired at hospital admission. The study aims to predict the patient’s infection severity (i.e., mild or severe) and potential outcome (i.e., discharged or deceased).

Methods
High resolution untargeted UHPLC-MS/MS analysis was performed on patient serum using both positive and negative ionization modes. A subset of 20 intermediary metabolites predictive of severity or outcome were selected based on univariate statistical significance and a multiple predictor Bayesian logistic regression model was created.

Results
The predictors were selected for their relevant biological function and include deoxycytidine and ureidopropionate (indirectly reflecting viral load), kynurenine (reflecting host inflammatory response), and multiple short chain acylcarnitines (energy metabolism) among others. Currently, this approach predicts outcome and severity with a Monte Carlo cross validated area under the ROC curve of 0.792 (SD 0.09) and 0.793 (SD 0.08), respectively. A blind validation study on an additional 90 patients predicted outcome and severity at ROC AUC of 0.83 (CI 0.74–0.91) and 0.76 (CI 0.67–0.86).

Conclusion
Prognostic tests based on the markers discussed in this paper could allow improvement in the planning of COVID-19 patient treatment.
Weight smoothing for nonprobability surveys
Authors: Ferri-García Ramón , Beaumont Jean-François , Bosa Keven , Charlebois Joanne , Chu Kenneth 
Published: December 2021

AbstractAdjustment techniques to mitigate selection bias in nonprobability samples often involve modelling the propensity to participate in the nonprobability sample along with inverse propensity weighting. It is well known that procedures for estimating weights are effective if the covariates selected in the propensity model are related to both the variable of interest and the participation indicator. In most surveys, there are many variables of interest, making weight adjustments difficult to determine as a suitable weight for one variable may be unsuitable for other variables. The standard compromise is to include a large number of covariates in the propensity model but this may increase the variability of the estimates, especially when some covariates are weakly related to the variables of interest. Weight smoothing, developed for probability surveys, could be helpful in these situations. It aims to remove the variability caused by overfit propensity models by replacing the inverse propensity weights with predicted weights obtained using a smoothing model. In this article, we study weight smoothing in the nonprobability survey context, both theoretically and empirically, to understand its effectiveness at improving the efficiency of estimates.
Judicial diplomacy of the German Federal Constitutional Court: bilateral court meetings as a novel data source to assess transnational communication of constitutional courts
Authors: Meyer Philipp 
Published: December 2021

AbstractJudicial diplomacy describes the courts’ efforts to promote liberal democracy and protect their institutional authority. Bilateral court meetings are essential for judicial diplomacy, encompassing jurisprudential (e.g., discussion of case law) and aims of strategic (e.g., maximising influence). This study presents a novel approach to assess such meetings. It analyses the German Federal Constitutional Court meeting reports between 1998–2019, using content and semantic network analysis. The content analysis shows that court meetings focus on jurisprudential aspects; however, strategic considerations also play a role in discussions with interlocutors from emerging democracies. These findings are substantiated by the semantic network analysis, which discloses that recent case law, Europeanisation, and globalisation are the main issues discussed. Hence, this study presents an analysis of a novel data source. Further, it contributes to judicial politics research as transnational court meetings could be a missing link to understand legal citation networks.
Caffeic acid phenethyl ester (CAPE) confers wild type p53 function in p53Y220C mutant: bioinformatics and experimental evidence
Authors: Radhakrishnan Navaneethan , Dhanjal Jaspreet Kaur , Sari Anissa Nofita , Ishida Yoshiyuki , Terao Keiji , Kaul Sunil C. , Sundar Durai , Wadhwa Renu 
Published: December 2021

AbstractMutations in the tumor suppressor protein p53 is a prevalent feature in majority of cancers resulting in inactivation of its activities related to control of cell cycle progression and proliferation. p53Y220C is one of the common hotspot mutations that causes decrease in its thermodynamic stability. Some small molecules have been shown to bind to the mutated site and restore its wild type thermodynamics and tumor suppressor function. In this study, we have explored the potential of caffeic acid phenethyl ester (CAPE—a bioactive compound from propolis) to interact with p53Y220C and restore its wild type p53 (p53wt) transcription activation and tumor suppressor activities. We recruited computational methods, viz. molecular docking, molecular dynamics simulations and free energy calculations to study the interaction of CAPE at the mutation crevice and found that it has potential to restore p53wt function of the p53Y220C mutant similar to a previously described restoration molecule PK7242. We provide cell-based experimental evidence to these predictions and suggest CAPE as a potential natural drug for treatment of p53Y220C mutant harboring cancers.
Methods for separating orchards from forest using airborne LiDAR
Authors: Hycza Tomasz , Kupidura Przemysław 
Published: December 2021

Abstract•Key messageThe aim of the study was to distinguish orchards from other lands with forest vegetation based on the data from airborne laser scanning. The methods based on granulometry provided better results than the pattern analysis. The analysis based on the Forest Data Bank/Cadastre polygons provided better results than the analysis based on the segmentation polygons. Classification of orchards and other areas with forest vegetation is important in the context of reporting forest area to international organizations, forest management, and mitigating effects of climate change.•ContextAgricultural lands with forest vegetation, e.g., orchards, do not constitute forests according to the forest definition formulated by the national and international definitions, but contrary to the one formulated in the Kyoto Protocol. It is a reason for the inconsistency in the forest area reported by individual countries.•AimsThe aim of the study was to distinguish orchards from other lands with forest vegetation based on the data from airborne laser scanning.•MethodsThe study analyzed the usefulness of various laser scanning products and the various features of pattern and granulometric analysis in the Milicz forest district in Poland.•ResultsThe methods based on granulometry provided better results than the pattern analysis. The analysis based on the Forest Data Bank/Cadastre polygons provided better results than the analysis based on the segmentation polygons.•ConclusionGranulometric analysis has proved to be a useful tool in the classification of orchards and other areas with forest vegetation. It is important in the context of reporting forest area to international organizations, forest management, and mitigating effects of climate change.
Machine remaining life prediction based on multi-layer self-attention and temporal convolution network
Authors: Shang Zhiwu , Zhang Baoren , Li Wanxiang , Qian Shiqi , Zhang Jie 
Published: December 2021

AbstractConvolution neural network (CNN) has been widely used in the field of remaining useful life (RUL) prediction. However, the CNN-based RUL prediction methods have some limitations. The receptive field of CNN is limited and easy to happen gradient vanishing problem when the network is too deep. The contribution differences of different channels and different time steps to RUL prediction are not considered, and only use deep learning features or handcrafted statistical features for prediction. These limitations can lead to inaccurate prediction results. To solve these problems, this paper proposes an RUL prediction method based on multi-layer self-attention (MLSA) and temporal convolution network (TCN). The TCN is used to extract deep learning features. Dilated convolution and residual connection are adopted in TCN structure. Dilated convolution is an efficient way to widen receptive field, and the residual structure can avoid the gradient vanishing problem. Besides, we propose a feature fusion method to fuse deep learning features and statistical features. And the MLSA is designed to adaptively assign feature weights. Finally, the turbofan engine dataset is used to verify the proposed method. Experimental results indicate the effectiveness of the proposed method.
Variable universe adaptive fuzzy sliding mode projective synchronization of hyperjerk system based on disturbance observer
Authors: Zhang Baojie , Feng Yuming , Yu Hongyan , Zhang Xianxiu 
Published: December 2021

AbstractIn this paper, a sliding mode projective synchronization strategy based on disturbance observer and fuzzy system is presented to implement projective synchronization of hyperjerk system with low time-varying disturbance and white noise. Theoretical analysis and numerical calculation show that the disturbance observer can approach the low time-varying disturbance very well. The application of disturbance observer reduces the chattering of the controller. Variable universe adaptive fuzzy control (VUAFC) method is utilized to further reduce the chattering phenomenon. The simulation results demonstrate the effectiveness of the proposed controller.