bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ontology-Based Calculation of Complexity Metrics for Components in CAD Systems
Authors: Weber Moritz , Anderl Reiner 
Published: May 2021

AbstractThe high complexity of assemblies and components in Computer-Aided Design (CAD) leads to a high effort in the maintenance of the models and increases the time required for adjustments. Metrics indicating the complexity of a CAD Model can help to reduce it by showing the results of changes. This paper describes a concept to calculate metrics aiming to describe the extent of complexity of components in CAD systems based on an ontology-based representation in a first step. The representation is initially generated from CAD models using an automated process. This includes both a boundary representation and the history of the feature-based design. Thus, the design strategy also contributes to measuring the complexity of the component so that the same shape can lead to different complexity metrics. Semantic rules are applied to find patterns of the design and to identify and evaluate various strategies. Different metrics are proposed to indicate the particular influence factors of complexity and a single measure for the overall complexity. Furthermore, the influencing factors can also be used to allow the designer to see how to reduce the complexity of the component or assembly.
Identification of Imprecision in Data Using $$\epsilon $$-Contamination Advanced Uncertainty Model
Authors: Shariatmadar Keivan , Hallez Hans , Moens David 
Published: May 2021

AbstractOne of the importance of the contamination uncertainty model is to consider in-determinism in the uncertainty. We consider this advanced property and develop two methods. These methods identify if there is imprecision in a given model or data. In the first approach, we build two different—a probability distribution and an interval—models for a test function f via given data/model. Then, we identify the level of imprecision by assessing, so-called model trust, $$\epsilon \in (0,1)$$

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in the contamination model whether the weight is higher for the probabilistic/interval model or not. In the second approach, we calculate the lowest and highest previsions for the test function and identify the imprecision interval out of them. We further discuss and show the idea via two simple production and clutch design problems to illustrate our novel results.
Approach to Assess Basic Deterministic Data and Model Form Uncertaint in Passive and Active Vibration Isolation
Authors: Platz Roland 
Published: May 2021

AbstractThis contribution continues ongoing own research on uncertainty quantification in structural vibration isolation in early design stage by various deterministic and non-deterministic approaches. It takes into account one simple structural dynamic system example throughout the investigation: a one mass oscillator subject to passive and active vibration isolation. In this context, passive means that the vibration isolation only depends on preset inertia, damping, and stiffness properties. Active means that additional controlled forces enhance vibration isolation. The simple system allows a holistic, consistent and transparent look into mathematical modeling, numerical simulation, experimental test and uncertainty quantification for verification and validation. The oscillator represents fundamental structural dynamic behavior of machines, trusses, suspension legs etc. under variable mechanical loading. This contribution assesses basic experimental data and mathematical model form uncertainty in predicting the passive and enhanced vibration isolation after model calibration as the basis for further deterministic and non-deterministic uncertainty quantification measures. The prediction covers six different damping cases, three for passive and three for active configuration. A least squares minimization (LSM) enables calibrating multiple model parameters using different outcomes in time and in frequency domain from experimental observations. Its adequacy strongly depends on varied damping properties, especially in passive configuration.
Mastering Uncertain Operating Conditions in the Development of Complex Machine Elements by Validation Under Dynamic Superimposed Operating Conditions
Authors: Germann Thiemo , Martin Daniel M. , Kubik Christian , Groche Peter 
Published: May 2021

AbstractMachine elements produced in large quantities undergo several development cycles and can be adapted from generation to generation. Thus, experiences from real operation can be taken into account in further development. This is not possible for innovative investment goods such as special purpose machines, as these are usually individual items. Therefore, functionality and quality of newly developed components must be assured by previous investigations.Conventional methods are inadequate at this point, as they cannot represent the actual, complex operating conditions in the later application. A reliable statement about the behavior of the system through a comprehensive validation in laboratory tests under standardized conditions is not achievable in this way due to a multitude of diversified load cases.In previous work, a method was developed to allow testing of machine elements in the laboratory under detuned operating conditions. For this purpose, disturbance variables are applied to the system using paraffin wax phase change actuators in order to simulate real operation states and to analyze the behavior of the machine element under these conditions. The investigated disturbance variables are fluctuations and asymmetries of the operating load through superimposed temperature gradients. Complex interactions between the machine element and the adjacent components or the overall system can thus be taken into account.The functionality of the methodology has been developed and briefly demonstrated so far. This paper presents the next level within the development process of the methodology. The necessary components are explained in detail and an AI black box evaluation tool is discussed. This work is based on a test bench that applies dynamically changing states of detuning under superimposed disturbances. Additionally, energy efficiency and performance of the test setup is advanced. As presented, the method opens up the possibility of validating new machine elements in the laboratory under realistic conditions.
Towards CAD-Based Mathematical Optimization for Additive Manufacturing – Designing Forming Tools for Tool-Bound Bending
Authors: Reintjes Christian , Reuter Jonas , Hartisch Michael , Lorenz Ulf , Engel Bernd 
Published: May 2021

AbstractThe trend towards flexible, agile, and resource-efficient production systems requires a continuous development of processes as well as of tools in the area of forming technology. To create load-adjusted and weight-optimized tool structures, we present an overview of a new algorithm-driven design optimization workflow based on mixed-integer linear programming. Loads and boundary conditions for the mathematical optimization are taken from numerical simulations. They are transformed into time-independent point loads generating physical uncertainty in the parameters of the optimization model. CAD-based mathematical optimization is used for topology optimization and geometry generation of the truss-like structure. Finite element simulations are performed to validate the structural strength and to optimize the shape of lattice nodes to reduce mechanical stress peaks. Our algorithm-driven design optimization workflow takes full advantage of the geometrical freedom of additive manufacturing by considering geometry-based manufacturing constraints. Depending on the additive manufacturing process, we use lower and upper bounds on the diameter of the members of a truss and the associated yield strengths. An additively manufactured flexible blank holder demonstrates the algorithm-driven topology design optimization.
Detection of Model Uncertainty in the Dynamic Linear-Elastic Model of Vibrations in a Truss
Authors: Matei Alexander , Ulbrich Stefan 
Published: May 2021

AbstractDynamic processes have always been of profound interest for scientists and engineers alike. Often, the mathematical models used to describe and predict time-variant phenomena are uncertain in the sense that governing relations between model parameters, state variables and the time domain are incomplete. In this paper we adopt a recently proposed algorithm for the detection of model uncertainty and apply it to dynamic models. This algorithm combines parameter estimation, optimum experimental design and classical hypothesis testing within a probabilistic frequentist framework. The best setup of an experiment is defined by optimal sensor positions and optimal input configurations which both are the solution of a PDE-constrained optimization problem. The data collected by this optimized experiment then leads to variance-minimal parameter estimates. We develop efficient adjoint-based methods to solve this optimization problem with SQP-type solvers. The crucial test which a model has to pass is conducted over the claimed true values of the model parameters which are estimated from pairwise distinct data sets. For this hypothesis test, we divide the data into k equally-sized parts and follow a k-fold cross-validation procedure. We demonstrate the usefulness of our approach in simulated experiments with a vibrating linear-elastic truss.
Development of an Annotation Schema for the Identification of Semantic Uncertainty in DIN Standards
Authors: Stegmeier Jörn , Hartig Jakob , Leštáková Michaela , Logan Kevin , Bartsch Sabine , Rapp Andrea , Pelz Peter F. 
Published: May 2021

AbstractThis paper presents the results of a pilot study carried out in cooperation between Linguistics and Mechanical Engineering, funded by the collaborative research centre (CRC) 805 “Beherrschung von Unsicherheit in lasttragenden Systemen des Maschinenbaus”. Our goal is to help improve norm compliant product development and engineering design by focusing on ambiguous language use in norm texts (= “semantic uncertainty”). Depending on the country and product under development, industry standards may be legally binding. Thus, standards play a vital role in reducing uncertainty for manufacturers and engineers by providing requirements for product development and engineering design. However, uncertainty is introduced by the standards themselves in various forms, the most notable of which are the use of underspecified concepts, modal verbs likeshould, and references to texts which contain semantically uncertain parts. If conformity to standards is to be ensured, the person using the standards must interpret them and document the interpretation. In order to support users in these tasks, wedeveloped an annotation schema which allows the identification and classification of semantically uncertain segments of standards,used the schema to create a taxonomy of semantic uncertainty in standards,developed a proof-of-concept information system.The results of this project can be used as a starting point for automated annotation. The information system alerts users to semantically uncertain segments of standards, provides background information, and allows them to document their decisions how to handle the semantically uncertain parts.
W-representation of Rainbow tensor model
Authors: Kang Bei , Wang Lu-Yao , Wu Ke , Yang Jie , Zhao Wei-Zhong 
Published: May 2021

Abstract
We analyze the rainbow tensor model and present the Virasoro constraints, where the constraint operators obey the Witt algebra and null 3-algebra. We generalize the method of W-representation in matrix model to the rainbow tensor model, where the operators preserving and increasing the grading play a crucial role. It is shown that the rainbow tensor model can be realized by acting on elementary function with exponent of the operator increasing the grading. We derive the compact expression of correlators and apply it to several models, i.e., the red tensor model, Aristotelian tensor model and r = 4 rainbow tensor model. Furthermore, we discuss the case of the non-Gaussian red tensor model and present a dual expression for partition function through differentiation.
Nilpotent symmetries as a mechanism for Grand Unification
Authors: Andersson Lars , László András , Ruba Błażej 
Published: May 2021

Abstract
In the classic Coleman-Mandula no-go theorem which prohibits the unification of internal and spacetime symmetries, the assumption of the existence of a positive definite invariant scalar product on the Lie algebra of the internal group is essential. If one instead allows the scalar product to be positive semi-definite, this opens new possibilities for unification of gauge and spacetime symmetries. It follows from theorems on the structure of Lie algebras, that in the case of unified symmetries, the degenerate directions of the positive semi-definite invariant scalar product have to correspond to local symmetries with nilpotent generators. In this paper we construct a workable minimal toy model making use of this mechanism: it admits unified local symmetries having a compact (U(1)) component, a Lorentz (SL(2, ℂ)) component, and a nilpotent component gluing these together. The construction is such that the full unified symmetry group acts locally and faithfully on the matter field sector, whereas the gauge fields which would correspond to the nilpotent generators can be transformed out from the theory, leaving gauge fields only with compact charges. It is shown that already the ordinary Dirac equation admits an extremely simple prototype example for the above gauge field elimination mechanism: it has a local symmetry with corresponding eliminable gauge field, related to the dilatation group. The outlined symmetry unification mechanism can be used to by-pass the Coleman-Mandula and related no-go theorems in a way that is fundamentally different from supersymmetry. In particular, the mechanism avoids invocation of super-coordinates or extra dimensions for the underlying spacetime manifold.
A surprising similarity between holographic CFTs and a free fermion in (2 + 1) dimensions
Authors: Cheamsawat Krai , Fischetti Sebastian , Wallis Lucas , Wiseman Toby 
Published: May 2021

AbstractWe compare the behavior of the vacuum free energy (i.e. the Casimir energy) of various (2 + 1)-dimensional CFTs on an ultrastatic spacetime as a function of the spatial geometry. The CFTs we consider are a free Dirac fermion, the conformally-coupled scalar, and a holographic CFT, and we take the spatial geometry to be an axisymmetric deformation of the round sphere. The free energies of the fermion and of the scalar are computed numerically using heat kernel methods; the free energy of the holographic CFT is computed numerically from a static, asymptotically AdS dual geometry using a novel approach we introduce here. We find that the free energy of the two free theories is qualitatively similar as a function of the sphere deformation, but we also find that the holographic CFT has a remarkable and mysteriousquantitativesimilarity to the free fermion; this agreement is especially surprising given that the holographic CFT is strongly-coupled. Over the wide ranges of deformations for which we are able to perform the computations accurately, the scalar and fermion differ by up to 50% whereas the holographic CFT differs from the fermion by less than one percent.
Differentiation between benign and malignant vertebral compression fractures using qualitative and quantitative analysis of a single fast spin echo T2-weighted Dixon sequence
Authors: Bacher Sebastien , Hajdu Steven David , Maeder Yael , Dunet Vincent , Hilbert Tom , Omoumi Patrick 
Published: May 2021

Abstract
Objectives
To determine and compare the qualitative and quantitative diagnostic performance of a single sagittal fast spin echo (FSE) T2-weighted Dixon sequence in differentiating benign and malignant vertebral compression fractures (VCF), using multiple readers and different quantitative methods.

Methods
From July 2014 to June 2020, 95 consecutive patients with spine MRI performed prior to cementoplasty for acute VCFs were retrospectively included. VCFs were categorized as benign (n = 63, mean age = 76 ± 12 years) or malignant (n = 32, mean age = 63 ± 12 years) with a best valuable comparator as a reference. Qualitative analysis was independently performed by four radiologists by categorizing each VCF as either benign or malignant using only the image sets provided by FSE T2-weighted Dixon sequences. Quantitative analysis was performed using two different regions of interest (ROI1-2) and three methods (signal drop, fat fraction (FF) from ROIs, FF maps). Diagnostic performance was compared using ROC curves analyses. Interobserver agreement was assessed using kappa statistics and intraclass correlation coefficients (ICC).

Results
The qualitative diagnostic performance ranged from area under the curve (AUC) = 0.97 (95% CI: 0.91–1.00) to AUC = 0.99 (95% CI: 0.95–1.0). The quantitative diagnostic performance ranged from AUC = 0.82 (95% CI: 0.73–0.89) to AUC = 0.97 (95% CI: 0.91–0.99). Pairwise comparisons showed no statistical difference in diagnostic performance (all p > 0.0013, Bonferroni-corrected p < 0.0011). All five cases with disagreement among the readers were correctly diagnosed at quantitative analysis using ROI2. Interobserver agreement was excellent for both qualitative and quantitative analyses.

Conclusions
A single FSE T2-weighted Dixon sequence can be used to differentiate benign and malignant VCF with high diagnostic performance using both qualitative and quantitative analyses, which can provide complementary information.

Key Points
• Qualitative analysis of a single FSE T2-weighted Dixon sequence yields high diagnostic performance and excellent observer agreement for differentiating benign and malignant compression fractures.
• The same FSE T2-weighted Dixon sequence allows quantitative assessment with high diagnostic performance.
• Quantitative data can readily be extracted from the FSE T2-weighted Dixon sequence and may provide complementary information to the qualitative analysis, which may be useful in doubtful cases.
Genotype imputation in case-only studies of gene-environment interaction: validity and power
Authors: Aleknonytė-Resch Milda , Szymczak Silke , Freitag-Wolf Sandra , Dempfle Astrid , Krawczak Michael 
Published: May 2021

AbstractCase-only (CO) studies are a powerful means to uncover gene-environment (G × E) interactions for complex human diseases. Moreover, such studies may in principle also draw upon genotype imputation to increase statistical power even further. However, genotype imputation usually employs healthy controls such as the Haplotype Reference Consortium (HRC) data as an imputation base, which may systematically perturb CO studies in genomic regions with main effects upon disease risk. Using genotype data from 719 German Crohn Disease (CD) patients, we investigated the level of imputation accuracy achievable for single nucleotide polymorphisms (SNPs) with or without a genetic main effect, and with varying minor allele frequency (MAF). Genotypes were imputed from neighbouring SNPs at different levels of linkage disequilibrium (LD) to the target SNP using the HRC data as an imputation base. Comparison of the true and imputed genotypes revealed lower imputation accuracy for SNPs with strong main effects. We also simulated different levels of G × E interaction to evaluate the potential loss of statistical validity and power incurred by the use of imputed genotypes. Simulations under the null hypothesis revealed that genotype imputation does not inflate the type I error rate of CO studies of G × E. However, the statistical power was found to be reduced by imputation, particularly for SNPs with low MAF, and a gradual loss of statistical power resulted when the level of LD to the SNPs driving the imputation decreased. Our study thus highlights that genotype imputation should be employed with great care in CO studies of G × E interaction.
Patterns of Italian high school and university students’ attitudes towards physics: an analysis based on semiotic-cultural perspective
Authors: Testa Italo , De Luca Picione Raffaele , Scotti di Uccio Umberto 
Published: May 2021

AbstractThe purpose of this study was to analyse Italian high school and university students’ attitudes towards physics using the Semiotic Cultural Psychological Theory (SCPT). In the SCPT framework, attitudes represent how individuals interpret their experience through the mediation ofgeneralized meaningwith which they are identified. A view-of-physics questionnaire was used as an instrument to collect data with 1603 high school and university students. Data were analysed through multiple correspondence analysis and cluster analysis. We identified fourgeneralized meaningsof physics: (a) interesting and important for society; (b) a quite interesting, but badly taught subject at school and not completely useful for society; (c) difficult to study and irrelevant for society; and (d) a fascinating and protective niche from society. The identified generalized meanings are significantly correlated to the choice to study physics at undergraduate level and to the choice of attending physics-related activities in high school. Implications for research are discussed.
The Important Role of Stereotypes in the relation between Mental Health Literacy and Stigmatization of Depression and Psychosis in the Community
Authors: Doll Carolin M. , Michel Chantal , Betz Linda T. , Schimmelmann Benno G. , Schultze-Lutter Frauke 
Published: May 2021

AbstractIncreased mental health literacy (MHL) has not reduced stigmatization of people with mental disorder. Thus, we examined the role of stereotypes in the interplay of MHL (correct labelling, causal explanations) and the wish for social distance (WSD) from people with depressive and psychotic symptoms in a community sample of 1526 German-speaking participants in the Swiss ‘Bern Epidemiological At-Risk’ study (age 16–40 years; response rate: 60.1%). Following the presentation of an unlabelled case vignette of depression or psychosis, MHL, stereotypes and WSD were assessed in a questionnaire survey. Their interrelations were studied using structural equation modelling. MHL was not directly linked to WSD, only the psychosocial causal model was directly negatively associated with WSD. Perceived dangerousness particularly increased WSD, this was increased by a biogenetic causal model and decreased by a psychosocial causal model. Awareness-campaigns that, next to biological causes, emphasize psychosocial causes of mental disorders might better reduce stigmatization.
Moral Relativism, Metalinguistic Negotiation, and the Epistemic Significance of Disagreement
Authors: Sodoma Katharina Anna 
Published: May 2021

AbstractAlthough moral relativists often appeal to cases of apparent moral disagreement between members of different communities to motivate their view, accounting for these exchanges as evincing genuine disagreements constitutes a challenge to the coherence of moral relativism. While many moral relativists acknowledge this problem, attempts to solve it so far have been wanting. In response, moral relativists either give up the claim that there can be moral disagreement between members of different communities or end up with a view on which these disagreements have no “epistemic significance” because they are always faultless. This paper introduces an alternative strategy: accounting for disagreement in terms of “metalinguistic negotiation”. It argues that this strategy constitutes a better solution to the challenge disagreement poses for moral relativists because it leads to a nuanced understanding of the epistemic significance of moral disagreement between members of different communities. The upshot is a novel account of disagreement for moral relativists that has consequences for how moral relativism should be understood.