Kornelius Kupczik

Bio: Kornelius Kupczik is an academic researcher from Max Planck Society. The author has contributed to research in topics: Masticatory force & Homo sapiens. The author has an hindex of 21, co-authored 67 publications receiving 1453 citations. Previous affiliations of Kornelius Kupczik include University of Chile & University of Hamburg.

Assessing mechanical function of the zygomatic region in macaques: validation and sensitivity testing of finite element models

Abstract: Crucial to the interpretation of the results of any finite element analysis of a skeletal system is a test of the validity of the results and an assessment of the sensitivity of the model parameters. We have therefore developed finite element models of two crania of Macaca fascicularis and investigated their sensitivity to variations in bone material properties, the zygomatico-temporal suture and the loading regimen applied to the zygomatic arch. Maximum principal strains were validated against data derived from ex vivo strain gauge experiments using non-physiological loads applied to the macaque zygomatic arch. Elastic properties of the zygomatic arch bone and the zygomatico-temporal suture obtained by nanoindentation resulted in a high degree of congruence between experimental and simulated strains. The findings also indicated that the presence of a zygomatico-temporal suture in the model produced strains more similar to experimental values than a completely separated or fused arch. Strains were distinctly higher when the load was applied through the modelled superficial masseter compared with loading an array of nodes on the arch. This study demonstrates the importance of the accurate selection of the material properties involved in predicting strains in a finite element model. Furthermore, our findings strongly highlight the influence of the presence of craniofacial sutures on strains experienced in the face. This has implications when investigating craniofacial growth and masticatory function but should generally be taken into account in functional analyses of the craniofacial system of both extant and extinct species.

Masticatory loading and bone adaptation in the supraorbital torus of developing macaques

Abstract: Research on the evolution and adaptive significance of primate craniofacial morphologies has focused on adult, fully developed individuals. Here, we investigate the possible relationship between the local stress environment arising from masticatory loadings and the emergence of the supraorbital torus in the developing face of the crab-eating macaque Macaca fascicularis. By using finite element analysis (FEA), we are able to evaluate the hypothesis that strain energy density (SED) magnitudes are high in subadult individuals with resulting bone growth in the supraorbital torus. We developed three micro-CT-based FEA models of M. fascicularis skulls ranging in dental age from deciduous to permanent dentitions and validated them against published experimental data. Applied masticatory muscle forces were estimated from physiological cross-sectional areas of macaque cadaveric specimens. The models were sequentially constrained at each working side tooth to simulate the variation of the bite point applied during masticatory function. Custom FEA software was used to solve the voxel-based models and SED and principal strains were computed. A physiological superposition SED map throughout the face was created by allocating to each element the maximum SED value from each of the load cases. SED values were found to be low in the supraorbital torus region throughout ontogeny, while they were consistently high in the zygomatic arch and infraorbital region. Thus, if the supraorbital torus arises to resist masticatory loads, it is either already adapted in each of our subadult models so that we do not observe high SED or a lower site-specific bone deposition threshold must apply.

Predicting Skull Loading: Applying Multibody Dynamics Analysis to a Macaque Skull

Abstract: Evaluating stress and strain fields in anatomical structures is a way to test hypotheses that relate specific features of facial and skeletal morphology to mechanical loading. Engineering techniques such as finite element analysis are now commonly used to calculate stress and strain fields, but if we are to fully accept these methods we must be confident that the applied loading regimens are reasonable. Multibody dynamics analysis (MDA) is a relatively new three dimensional computer modeling technique that can be used to apply varying muscle forces to predict joint and bite forces during static and dynamic motions. The method ensures that equilibrium of the structure is maintained at all times, even for complex statically indeterminate problems, eliminating nonphysiological constraint conditions often seen with other approaches. This study describes the novel use of MDA to investigate the influence of different muscle representations on a macaque skull model (Macaca fascicularis), where muscle groups were represented by either a single, multiple, or wrapped muscle fibers. The impact of varying muscle representation on stress fields was assessed through additional finite element simulations. The MDA models highlighted that muscle forces varied with gape and that forces within individual muscle groups also varied; for example, the anterior strands of the superficial masseter were loaded to a greater extent than the posterior strands. The direction of the muscle force was altered when temporalis muscle wrapping was modeled, and was coupled with compressive contact forces applied to the frontal, parietal and temporal bones of the cranium during biting.

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Analyzing linguistic data: a practical introduction to statistics using R

Abstract: The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Genetic history of an archaic hominin group from Denisova Cave in Siberia

Abstract: Using DNA extracted from a finger bone found in Denisova Cave in southern Siberia, we have sequenced the genome of an archaic hominin to about 1.9-fold coverage. This individual is from a group that shares a common origin with Neanderthals. This population was not involved in the putative gene flow from Neanderthals into Eurasians; however, the data suggest that it contributed 4–6% of its genetic material to the genomes of present-day Melanesians. We designate this hominin population ‘Denisovans’ and suggest that it may have been widespread in Asia during the Late Pleistocene epoch. A tooth found in Denisova Cave carries a mitochondrial genome highly similar to that of the finger bone. This tooth shares no derived morphological features with Neanderthals or modern humans, further indicating that Denisovans have an evolutionary history distinct from Neanderthals and modern humans.

New fossils from Jebel Irhoud, Morocco and the pan-African origin of Homo sapiens

Abstract: Fossil evidence points to an African origin of Homo sapiens from a group called either H. heidelbergensis or H. rhodesiensis. However, the exact place and time of emergence of H. sapiens remain obscure because the fossil record is scarce and the chronological age of many key specimens remains uncertain. In particular, it is unclear whether the present day ‘modern’ morphology rapidly emerged approximately 200 thousand years ago (ka) among earlier representatives of H. sapiens1 or evolved gradually over the last 400 thousand years2. Here we report newly discovered human fossils from Jebel Irhoud, Morocco, and interpret the affinities of the hominins from this site with other archaic and recent human groups. We identified a mosaic of features including facial, mandibular and dental morphology that aligns the Jebel Irhoud material with early or recent anatomically modern humans and more primitive neurocranial and endocranial morphology. In combination with an age of 315 ± 34 thousand years (as determined by thermoluminescence dating)3, this evidence makes Jebel Irhoud the oldest and richest African Middle Stone Age hominin site that documents early stages of the H. sapiens clade in which key features of modern morphology were established. Furthermore, it shows that the evolutionary processes behind the emergence of H. sapiens involved the whole African continent.

Evolution and development of shape: integrating quantitative approaches

Abstract: Morphological traits have long been a focus of evolutionary developmental biology ('evo-devo'), but new methods for quantifying shape variation are opening unprecedented possibilities for investigating the developmental basis of evolutionary change. Morphometric analyses are revealing that development mediates complex interactions between genetic and environmental factors affecting shape. Evolution results from changes in those interactions, as natural selection favours shapes that more effectively perform some fitness-related functions. Quantitative studies of shape can characterize developmental and genetic effects and discover their relative importance. They integrate evo-devo and related disciplines into a coherent understanding of evolutionary processes from populations to large-scale evolutionary radiations.