bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gesundheitskompetenz und Gesundheitsverhalten im Jugendalter: Ergebnisse einer bundesweiten Online-Befragung Jugendlicher
Authors: Domanska Olga Maria , Loer Anne-Kathrin M. , Stock Christiane , Jordan Susanne 
Published: October 2021

Zusammenfassung
Hintergrund
Für Deutschland fehlen Informationen zum Zusammenhang zwischen Gesundheitskompetenz und Gesundheitsverhalten Jugendlicher, obwohl in der Stärkung von Gesundheitskompetenz besonders im Jugendalter ein vielversprechender Ansatz zur Förderung des Gesundheitsverhaltens gesehen wird.

Ziel der Arbeit
Es wird – unter Berücksichtigung von soziodemografischen Merkmalen und Selbstwirksamkeit – untersucht, ob verschiedene Dimensionen der allgemeinen Gesundheitskompetenz mit dem Gesundheitsverhalten Jugendlicher assoziiert sind.

Material und Methoden
Datengrundlage bildet die bundesweite Online-Befragung zur „Gesundheitskompetenz von Jugendlichen“ (GeKoJu) mit 1235 Jugendlichen zwischen 14–17 Jahren in Deutschland. Vier Dimensionen allgemeiner Gesundheitskompetenz wurden mit dem „Measurement of Health Literacy Among Adolescents Questionnaire“ (MOHLAA-Q) durch Selbstangaben erfasst. Gesundheitsverhalten wurde mit Fragen zu Sport, Ernährung, Alkoholkonsum und Rauchen erhoben. Es wurden uni- und bivariate Analysen sowie multiple Regressionsanalysen durchgeführt.

Ergebnisse
Jugendliche mit niedrigen Leveln in allen untersuchten Gesundheitskompetenzdimensionen haben eine erhöhte Chance, kein Obst und Gemüse täglich zu konsumieren. Auch die Chance zu rauchen oder keinen Sport zu treiben war höher bei Personen mit geringer ausgeprägten Kommunikations- und Interaktionsfähigkeiten und passiven Einstellungen zur Gesundheit und Gesundheitsinformationen. Riskanter Alkoholkonsum wies keinen Zusammenhang mit Gesundheitskompetenz auf.

Schlussfolgerung
Die Ergebnisse legen die Stärkung von aktiven Einstellungen zu Gesundheit und Gesundheitsinformationen und Kommunikations- und Interaktionsfähigkeiten rund um das Thema Gesundheit für die Förderung des Gesundheitsverhaltens Jugendlicher nahe.
Gaussian mixture model decomposition of multivariate signals
Authors: Zickert Gustav , Yarman Can Evren 
Published: October 2021

AbstractWe propose a greedy variational method for decomposing a non-negative multivariate signal as a weighted sum of Gaussians, which, borrowing the terminology from statistics, we refer to as a Gaussian mixture model. Notably, our method has the following features: (1) It accepts multivariate signals, i.e., sampled multivariate functions, histograms, time series, images, etc., as input. (2) The method can handle general (i.e., ellipsoidal) Gaussians. (3) No prior assumption on the number of mixture components is needed. To the best of our knowledge, no previous method for Gaussian mixture model decomposition simultaneously enjoys all these features. We also prove an upper bound, which cannot be improved by a global constant, for the distance from any mode of a Gaussian mixture model to the set of corresponding means. For mixtures of spherical Gaussians with common variance $$\sigma ^2$$

σ
2

, the bound takes the simple form $$\sqrt{n}\sigma $$

n

σ

. We evaluate our method on one- and two-dimensional signals. Finally, we discuss the relation between clustering and signal decomposition, and compare our method to the baseline expectation maximization algorithm.
A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience
Authors: Santos João P. G. , Pajo Kadri , Trpevski Daniel , Stepaniuk Andrey , Eriksson Olivia , Nair Anu G. , Keller Daniel , Hellgren Kotaleski Jeanette , Kramer Andrei 
Published: October 2021

AbstractNeuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a variety of different software tools in the model building and analysis process. Here we focus on the scale of biochemical pathways, which is one of the main objects of study in systems biology. While systems biology is among the more standardized fields, conversion between different model formats and interoperability between various tools is still somewhat problematic. To offer our take on tackling these shortcomings and by keeping in mind the FAIR (findability, accessibility, interoperability, reusability) data principles, we have developed a workflow for building and analyzing biochemical pathway models, using pre-existing tools that could be utilized for the storage and refinement of models in all phases of development. We have chosen the SBtab format which allows the storage of biochemical models and associated data in a single file and provides a human readable set of syntax rules. Next, we implemented custom-made MATLAB® scripts to perform parameter estimation and global sensitivity analysis used in model refinement. Additionally, we have developed a web-based application for biochemical models that allows simulations with either a network free solver or stochastic solvers and incorporating geometry. Finally, we illustrate convertibility and use of a biochemical model in a biophysically detailed single neuron model by running multiscale simulations in NEURON. Using this workflow, we can simulate the same model in three different simulators, with a smooth conversion between the different model formats, enhancing the characterization of different aspects of the model.
Pharmacological Cognitive Enhancement and Cheapened Achievement: A New Dilemma
Authors: Gordon Emma C. , Dunn Lucy 
Published: October 2021

AbstractRecent discussions of cognitive enhancement often note that drugs and technologies that improve cognitive performance may do so at the risk of “cheapening” our resulting cognitive achievements (e.g., Kass, Life, liberty and the defense of dignity: the challenge for bioethics, Encounter Books, San Francisco, 2004; Agar, Humanity’s end: why we should reject radical enhancement, MIT Press, Cambridge, 2010; Sandel, The case against perfection. Harvard University Press, Cambridge, 2007; Sandel, The case against perfection: what’s wrong with designer children, bionic athletes, and genetic engineering?”. In: Holland (ed) Arguing about bioethics, Routledge, London, 2012; Harris in Bioethics 25:102–111, 2011). While there are several possible responses to this worry, we will highlight what we take to be one of the most promising—one which draws on a recent strand of thinking in social and virtue epistemology to construct an integrationist defence of cognitive enhancement. (e.g., Pritchard in Synthese 175:133–151, 2010; Palermos in Synthese 192:2955–2286, 2015; Clark in Synthese 192:3757–3375, 2015). According to such a line, there is—despite initial appearances to the contrary—no genuine tension between using enhancements to attain our goals and achieving these goals in a valuable way provided the relevant enhancement isappropriately integratedinto the agent’s cognitive architecture (in some suitably specified way). In this paper, however, we show that the kind of integration recommended by such views will likely come at a high cost. More specifically, we highlight a dilemma for users of pharmacological cognitive enhancement: they can (1) meet the conditions for cognitive integration (and on this basis attain valuable achievements) at the significant risk of dangerous dependency, or (2) remain free of such dependency while foregoing integration and the valuable achievements that such integration enables. After motivating and clarifying the import of this dilemma, we offer recommendations for how future cognitive enhancement research may offer potential routes for navigating past it.
Integrated Framework for Test and Evaluation of Autonomous Vehicles
Authors: Su Yimin , Wang Lin 
Published: October 2021

AbstractAutonomous vehicles must pass effective standard tests to verify their reliability and safety. Accordingly, it is very important to establish a complete scientific test and evaluation system for autonomous vehicles. A comprehensive framework incorporating the design of test scenarios, selection of evaluation indexes, and establishment of an evaluation system is proposed in this paper. The aims of the system are to obtain an objective and quantitative score regarding the intelligence of autonomous vehicles, and to form an automated process in the future development. The proposed framework is built on a simulation platform to ensure the feasibility of the design and implementation of the test scenarios. The design principle for the test scenarios is also presented. To reduce subjective influences, the proposed framework selects objective indexes from four aspects: safety, comfort, driving performance, and standard regulations. The order relation analysis method is adopted to formulate the index weights, and fuzzy comprehensive evaluation is used to quantify the scores. Finally, a numerical example is provided to visually demonstrate the evaluation results for the autonomous vehicles scored by the proposed framework.
Safety, Mortality, and Hemodynamic Impact of Patients with MitraClip Undergoing Left Ventricular Assist Device Implantation
Authors: Fox Henrik , Gyoten Takayuki , Rojas Sebastian V. , Deutsch Marcus-André , Schramm René , Rudolph Volker , Gummert Jan F. , Morshuis Michiel 
Published: October 2021

AbstractThe interactions and hemodynamic impact of transcatheter percutaneous mitral valve repair (TMR) have not yet been investigated in patients undergoing left ventricular assist device (LVAD) implantation, but hemodynamic adverse effects are feared in the combination of TMR and LVAD for altered mitral valve flow. This study investigated the hemodynamic interplay in combination of TMR and LVAD in 119 patients, and propensity score match analysis revealed no difference in both perioperative mortality and 2-year follow-up survival (p = 0.84). Nonetheless, postoperatively mean pulmonary arterial pressure, pulmonary capillary wedge pressure, and cardiac index improved, and multivariable cox regression analysis at 2 years identified preoperative total bilirubin and temporary right ventricular mechanical circulatory support as independent risk factors for all-cause mortality but not TMR. Prior TMR has no impact on mortality or cardiovascular complications in patients with LVAD.
Graphical abstract
Application of random forest classification and remotely sensed data in geological mapping on the Jebel Meloussi area (Tunisia)
Authors: Albert Gáspár , Ammar Seif 
Published: October 2021

Abstract
Remotely sensed data such as satellite photos and radar images can be used to produce geological maps on arid regions, where the vegetation coverage does not have a significant effect. In central Tunisia, the Jebel Meloussi area has unique geological features and characteristic morphology (i.e. flat areas with dune fields in contrast with hills of folded and eroded stratigraphic sequences), which makes it an ideal area for testing new methods of automatic terrain classification. For this, data from the Sentinel 2 satellite sensor and the SRTM-based MERIT DEM (digital elevation model) were used in the present study. Using R scripts and the random forest classification method, modelling was performed on four lithological variables—derived from the different bands of the Sentinel 2 images—and two morphometric parameters for the area of the 1:50,000 geological map sheet no. 103. The four lithological variables were chosen to highlight the iron-bearing minerals since the spectral parameters of the Sentinel 2 sensors are especially useful for this purpose. The training areas of the classification were selected on the geological map. The results of the modelling identified Eocene and Cretaceous evaporite-bearing sedimentary series (such as the Jebs and the Bouhedma Formations) with the highest producer accuracy (> 60% of the predicted pixels match with the map). The pyritic argillites of the Sidi Khalif Formation were also recognized with the same accuracy, and the Quaternary sebhkas and dunes were also well predicted. The study concludes that the classification-based geological map is useful for field geologist prior to field surveys.
Passive myocardial mechanical properties: meaning, measurement, models
Authors: Emig Ramona , Zgierski-Johnston Callum M. , Timmermann Viviane , Taberner Andrew J. , Nash Martyn P. , Kohl Peter , Peyronnet Rémi 
Published: October 2021

AbstractPassive mechanical tissue properties are major determinants of myocardial contraction and relaxation and, thus, shape cardiac function. Tightly regulated, dynamically adapting throughout life, and affecting a host of cellular functions, passive tissue mechanics also contribute to cardiac dysfunction. Development of treatments and early identification of diseases requires better spatio-temporal characterisation of tissue mechanical properties and their underlying mechanisms. With this understanding, key regulators may be identified, providing pathways with potential to control and limit pathological development. Methodologies and models used to assess and mimic tissue mechanical properties are diverse, and available data are in part mutually contradictory. In this review, we define important concepts useful for characterising passive mechanical tissue properties, and compare a variety of in vitro and in vivo techniques that allow one to assess tissue mechanics. We give definitions of key terms, and summarise insight into determinants of myocardial stiffness in situ. We then provide an overview of common experimental models utilised to assess the role of environmental stiffness and composition, and its effects on cardiac cell and tissue function. Finally, promising future directions are outlined.
Techniques to Improve Ecological Interpretability of Black-Box Machine Learning Models
Authors: Welchowski Thomas , Maloney Kelly O. , Mitchell Richard , Schmid Matthias 
Published: October 2021

AbstractStatistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects.Gradient boosted trees(GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations ofpartial dependence plots(PDP),individual conditional expectation(ICE) curves andaccumulated local effects(ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s$$H^2$$H2statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests. Supplementary materials accompanying this paper appear on-line.
Urban nature at the fingertips: Investigating wild food foraging to enable nature interactions of urban dwellers
Authors: Schunko Christoph , Brandner Anjoulie 
Published: October 2021

AbstractMeaningful human–nature interactions can counteract the extinction of experience and positively influence people’s nature relatedness, health and wellbeing. In this study, we explored urban wild food foraging to understand how best to enable human-nature interactions in cities by means of foraging. Using a structured questionnaire, a total of 458 residents of Vienna, Austria were surveyed. Sixty-four percent of visitors of public urban green spaces previously foraged for wild food species, whereas foraging frequencies were related to the targeted plant species and their life forms. People who foraged more frequently had greater nature relatedness, more childhood foraging experiences and lived on the outskirts of the city, but their socio-demographic backgrounds were heterogeneous. Social acceptance and lack of access to wild foods were perceived to be barriers. To promote nature relatedness through urban foraging, the legal framework, access to low-contamination foraging areas, availability of wild foods and social acceptance need to be improved.
Effects of interfacial residual stress on mechanical behavior of SiCf/SiC composites
Authors: Chen Xiaowu , Cheng Guofeng , Yang Jinshan , Hu Jianbao , Liao Chunjin , Zhang Xiangyu , Dong Shaoming 
Published: October 2021

AbstractLayer-structured interphase, existing between reinforcing fiber and ceramics matrix, is an indispensable constituent for fiber-reinforced ceramic composites due to its determinant role in the mechanical behavior of the composites. However, the interphase may suffer high residual stress because of the mismatch of thermal expansion coefficients in the constituents, and this can exert significant influence on the mechanical behavior of the composites. Here, the residual stress in the boron nitride (BN) interphase of continuous SiC fiber-reinforced SiC composites was measured using a micro-Raman spectrometer. The effects of the residual stress on the mechanical behavior of the composites were investigated by correlating the residual stress with the mechanical properties of the composites. The results indicate that the residual stress increases from 26.5 to 82.6 MPa in tension as the fabrication temperature of the composites rises from 1500 to 1650 °C. Moreover, the increasing tensile residual stress leads to significant variation of tensile strain, tensile strength, and fiber/matrix debonding mode of the composites. The sublayer slipping of the interphase caused by the residual stress should be responsible for the transformation of the mechanical behavior. This work can offer important guidance for residual stress adjustment in fiber-reinforced ceramic composites.
Effects of antibiotics on the developing enamel in neonatal mice
Authors: Schmalfuss A. J. , Sehic A. , Brusevold I. J. 
Published: October 2021

AbstractPurposeIdentifying factors causing Molar-Incisor Hypomineralization (MIH) is an ongoing challenge. Preterm infants, routinely treated with antibiotics in cases of suspected sepsis, are more commonly affected by dental developmental defects. This study aimed to investigate the effects of gentamycin and ampicillin on the developing enamel in neonatal CD-1 mice in vivo.MethodsNeonatal mice were randomized into a study (n = 36) and a control (n = 35) group. Antibiotics were injected intravenously for 4 days. All mice were sacrificed after 15–18 days. Micro-CT was used to analyse the mineral density (MD) of the enamel and the proportion of the enamel object volume (vol%) in first molars and incisors.ResultsWe demonstrated a significantly lower vol% enamel in the maxillary (30.9% vs. 32.7%;p = 0.004) and mandibular (32.5% vs. 34.6%;p = 0.015) molars in the study group than in the controls. The incisors were divided into segments upon analysis. We demonstrated both lower vol% and lower MD of the enamel in most segments in treated individuals compared to controls (p < 0.05).ConclusionThe reduced MD and vol% in the molars and incisors are likely to have been caused by the antibiotics given during tooth development. The presented analysis of teeth in neonatal mice with micro-CT could be a valid model for further research on dental developmental defects.
Conformal Chebyshev chaotic map-based remote user password authentication protocol using smart card
Authors: Meshram Chandrashekhar , Meshram Sarita Gajbhiye , Ibrahim Rabha W. , Jalab Hamid A. , Jamal Sajjad Shaukat , Barve Sharad Kumar 
Published: October 2021

AbstractWith the rapid advancement and growth of computer networks, there have been greater and greater demands for remote user password authentication protocols. In current ages, smartcard-based authentication protocol has formed the standard with their incredibly insubstantial, user-friendly equipment and low-cost apps. In this study, we proposed an effective robust authentication protocol using the conformable chaotic map, where a conformable calculus is a branch of newly appearing fractional calculus. It has a magnificent property, because it formulates using a controller term. We shall also offer formal proof of smooth execution of the proposed authenticated protocol. Our new protocol is more secure as compared to several comparable protocols.
Metal powder bed fusion process chains: an overview of modelling techniques
Authors: Afazov Shukri , Roberts Adam , Wright Louise , Jadhav Prashant , Holloway Adam , Basoalto Hector , Milne Katy , Brierley Nick 
Published: October 2021

AbstractMetal powder bed fusion (MPBF) is not a standalone process, and other manufacturing technologies, such as heat treatment and surface finishing operations, are often required to achieve a high-quality component. To optimise each individual process for a given component, its progression through the full process chain must be considered and understood, which can be achieved through the use of validated models. This article aims to provide an overview of the various modelling techniques that can be utilised in the development of a digital twin for MPBF process chains, including methods for data transfer between physical and digital entities and uncertainty evaluation. An assessment of the current maturity of modelling techniques through the use of technology readiness levels is conducted to understand their maturity. Summary remarks highlighting the advantages and disadvantages in physics-based modelling techniques used in MPBF research domains (i.e. prediction of: powder distortion; temperature; material properties; distortion; residual stresses; as well as topology optimisation), post-processing (i.e. modelling of: machining; heat treatment; and surface engineering), and digital twins (i.e. simulation of manufacturing process chains; interoperability; and computational performance) are provided. Future perspectives for the challenges in these MPBF research domains are also discussed and summarised.