Dimensional Continuum Research Articles

Clinical profiles of adolescent personality pathology: a latent structure examination of the Semi-Structured Interview for Personality Functioning DSM-5 (STiP-5.1) in a help-seeking sample

BackgroundDespite the introduction of dimensional conceptualisations of personality functioning in the latest classification systems, such as Criterion A of the Alternative Model of Personality Disorders in the DSM-5, heterogeneous clinical presentation of personality pathology remains a challenge. Relatedly, the latent structure of personality pathology as assessed by the Semi-Structured Interview for Personality Functioning DSM-5 (STiP-5.1) has not yet been comprehensively examined in adolescents. Therefore, this study aimed to examine the latent structure of the STiP-5.1, and, based on those findings, to describe any unique clinical profiles that might emerge.MethodsThe final sample comprised 502 participants aged 11–18 years consecutively recruited from a specialised personality disorder outpatient service, as well as general day clinic and inpatient wards at the University Hospital University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University Hospital Bern, Switzerland. Participants were assessed using the STiP-5.1, as well as a battery of other psychological measures by clinical psychologists or trained doctoral students. Variations of Factor Analysis, Latent Class Analysis and Factor Mixture Models (FMM) were applied to the STiP-5.1 to determine the most appropriate structure.ResultsThe best fitting model was an FMM comprising four-classes and two factors (corresponding to self- and interpersonal-functioning). The classes differed in both overall severity of personality functioning impairment, and in their scores and clinical relevance on each element of the STiP-5.1. When compared to the overall sample, classes differed in their unique clinical presentation: class 1 had low impairment, class 2 had impairments primarily in self-functioning with high depressivity, class 3 had mixed levels of impairment with emerging problems in identity and empathy, and class 4 had severe overall personality functioning impairment.ConclusionsA complex model incorporating both dimensional and categorical components most adequately describes the latent structure of the STiP-5.1 in our adolescent sample. We conclude that Criterion A provides clinically useful information beyond severity (as a dimensional continuum) alone, and that the hybrid model found for personality functioning in our sample warrants further attention. Findings can help to parse out clinical heterogeneity in personality pathology in adolescents, and help to inform early identification and intervention efforts.

Establishing Levels of Personality Functioning Using the Structured Interview of Personality Organization (STIPO-R): A Latent Profile Analysis

Both the new ICD-11 and the latest Alternative DSM-5 Model for Personality Disorders focus on self and interpersonal functioning as the central feature of personality pathology, also acknowledging that personality disorders are organized along a dimensional continuum of severity. This revised understanding is in line with long-standing psychodynamic conceptualisations of personality pathology, in particular Kernberg’s object relations model of personality organization. Despite existing evidence for the clinical utility of the derived Structured Interview of Personality Organization (STIPO-R), empirical support for the identification of clear cut-points between the different levels of personality functioning is missing. For this purpose, a total of 764 adult participants were recruited across two clinical (outpatient and inpatient) settings (n = 250) and two non-clinical (university students and general community) samples (n = 514). Results from the mixture modeling suggested the existence of five groups across the clinical and non-clinical samples that covered: healthy personality functioning, maladaptive personality rigidity, and mild, moderate, and severe levels of personality pathology. All five indicators of personality organization were found to be reliable predictors of personality pathology. Of the five STIPO-R indicators, Aggression and Moral Values had the most discriminative power for differentiating between the Mild, Moderate, and Severe personality disorder groups. Implications of these findings are discussed.

A Set-Theoretic Analysis of the Black Hole Entropy Puzzle

Motivated by the known mathematical and physical problems arising from the current mathematical formalization of the physical spatio-temporal continuum, as a substantial technical clarification of our earlier attempt (Etesi in Found Sci 25:327–340, 2020), the aim in this paper is twofold. Firstly, by interpreting Chaitin’s variant of Gödel’s first incompleteness theorem as an inherent uncertainty or fuzziness present in the set of real numbers, a set-theoretic entropy is assigned to it using the Kullback–Leibler relative entropy of a pair of Riemannian manifolds. Then exploiting the non-negativity of this relative entropy an abstract Hawking-like area theorem is derived. Secondly, by analyzing Noether’s theorem on symmetries and conserved quantities, we argue that whenever the four dimensional space-time continuum containing a single, stationary, asymptotically flat black hole is modeled by the set of real numbers in the mathematical formulation of general relativity, the hidden set-theoretic entropy of this latter structure reveals itself as the entropy of the black hole (proportional to the area of its “instantaneous” event horizon), indicating that this apparently physical quantity might have a pure set-theoretic origin, too.

Revealing hidden patterns in deep neural network feature space continuum via manifold learning

Deep neural networks (DNNs) extract thousands to millions of task-specific features during model training for inference and decision-making. While visualizing these features is critical for comprehending the learning process and improving the performance of the DNNs, existing visualization techniques work only for classification tasks. For regressions, the feature points lie on a high dimensional continuum having an inherently complex shape, making a meaningful visualization of the features intractable. Given that the majority of deep learning applications are regression-oriented, developing a conceptual framework and computational method to reliably visualize the regression features is of great significance. Here, we introduce a manifold discovery and analysis (MDA) method for DNN feature visualization, which involves learning the manifold topology associated with the output and target labels of a DNN. MDA leverages the acquired topological information to preserve the local geometry of the feature space manifold and provides insightful visualizations of the DNN features, highlighting the appropriateness, generalizability, and adversarial robustness of a DNN. The performance and advantages of the MDA approach compared to the existing methods are demonstrated in different deep learning applications.

Modeling the Influence of Electrolyte Distribution in Silver Gas Diffusion Electrodes for CO2 Electroreduction

The chemical industry has been increasingly focusing on reducing CO2 emissions in recent years. One promising way to do this is via CO2 electroreduction, a technology that does not only reduce CO2 emissions but also allows CO2 to be used as a source of carbon for making commodity chemicals. A key to efficient CO2 electroreduction is the electrolyte management inside the porous system of gas diffusion electrodes (GDEs). Flooding of electrodes can severely hinder mass transfer and thereby prevent CO2 reduction, giving rise to the parasitic hydrogen evolution reaction [1]. Although the measurement of electrolyte saturation is possible through methods like synchrotron radiography, these measurements are highly expensive, and thus not always readily available [2]. Modeling can help here to better understand the influence of electrolyte saturation, and predict possible measures for improving the process.In most CO2 electrolysis models in literature, the electrolyte saturation is a fixed parameter [3,4]. This assumption does not always hold true, as effects like electro-wetting change the wetting behavior of the GDE for different operating conditions. In this new modeling approach, correlations between capillary pressure and saturation, as well as between contact angle and potential are introduced, making the description of these changes possible. These correlations are gained from pore network simulations of the electrode material reconstructed from FIB-SEM measurements. The correlations are implemented in a one dimensional continuum model that includes discretized balance spaces for liquid and gas phase inside the porous system of the GDE, ideally mixed gas and electrolyte bulk spaces on the respective sides of the electrode, as well as boundary layers between bulk and electrode. Homogeneous reactions of the carbonate buffer system in the liquid phase and electrochemical reactions inside the GDE are considered. Transport of species is calculated using Maxwell-Stefan diffusion, migration in the potential field resulting from the Nernst-Planck equation, and flow through the porous electrode according to Darcy’s law. Additionally phase transfer processes like gas dissolution and evaporation of water are considered. The GDE model is validated with experimental data for CO2 electrolysis, enabling insights into the processes in the GDE and elucidating the influence of electrolyte saturation on the CO2 mass transfer.[1] Bienen, F., Paulisch, M. C., Mager, T., Osiewacz, J., Nazari, M., Osenberg, M., Ellendorff, B., Turek, T., Nieken, U., Manke, I., & Friedrich, K. A., Investigating the electrowetting of silver‐based gas‐diffusion electrodes during oxygen reduction reaction with electrochemical and optical methods. Electrochemical Science Advances (2022) e2100158.[2] Hoffmann, H., Paulisch, M. C., Gebhard, M., Osiewacz, J., Kutter, M., Hilger, A., Arlt, T., Kardjilov, N., Ellendorff, B., Beckmann, F., Markötter, H., Luik, M., Turek, T., Manke, I., & Roth, C., Development of a Modular Operando Cell for X-ray Imaging of Strongly Absorbing Silver-Based Gas Diffusion Electrodes. Journal of The Electrochemical Society 169 (2022) 044508.[3] Löffelholz, M., Osiewacz, J., Lüken, A., Perrey, K., Bulan, A., & Turek, T., Modeling electrochemical CO2 reduction at silver gas diffusion electrodes using a TFFA approach. Chemical Engineering Journal 435 (2022) 134920.[4] Weng, L.-C., Bell, A. T., & Weber, A. Z., Modeling gas-diffusion electrodes for CO2 reduction. Physical Chemistry Chemical Physics 25 (2018) 16973–16984. Figure 1

A new derivation of the Minkowski metric

The four dimensional spacetime continuum, as first conceived by Minkowski, has become the dominant framework within which to describe physical laws. In this paper, we show how this four-dimensional structure is a natural property of physical three-dimensional space, if modeled with Clifford geometric algebra . We find that Minkowski spacetime can be embedded within a larger eight dimensional structure. This then allows a generalisation of the invariant interval and the Lorentz transformations. Also, with this geometric oriented approach the fixed speed of light, the laws of special relativity and a generalised form of Maxwell’s equations, arise naturally from the intrinsic properties of the algebra without recourse to physical arguments. We also find new insights into the nature of time, which can be described as two-dimensional. Some philosophical implications of this approach as it relates to the foundations of physical theories are also discussed.

Existence, Uniqueness and Energy Scaling of (2+1)-Dimensional Continuum Model for Stepped Epitaxial Surfaces with Elastic Effects

Existence, Uniqueness and Energy Scaling of (2+1)-Dimensional Continuum Model for Stepped Epitaxial Surfaces with Elastic Effects

Personality Functioning: An Opportunity for Treatment Personalization

As the literature shows, the categorical diagnosis of personality has received numerous criticisms. Over the years, authors suggest that personality dysfunction is distributed along a dimensional continuum.

Working memory and reaction time variability mediate the relationship between polygenic risk and ADHD traits in a general population sample

Endophenotypes are heritable and quantifiable traits indexing genetic liability for a disorder. Here, we examined three potential endophenotypes, working memory function, response inhibition, and reaction time variability, for attention-deficit hyperactivity disorder (ADHD) measured as a dimensional latent trait in a large general population sample derived from the Adolescent Brain Cognitive DevelopmentSM Study. The genetic risk for ADHD was estimated using polygenic risk scores (PRS) whereas ADHD traits were quantified as a dimensional continuum using Bartlett factor score estimates, derived from Attention Problems items from the Child Behaviour Checklist and Effortful Control items from the Early Adolescent Temperament Questionnaire-Revised. The three candidate cognitive endophenotypes were quantified using task-based performance measures. Higher ADHD PRSs were associated with higher ADHD traits, as well as poorer working memory performance and increased reaction time variability. Lower working memory performance, poorer response inhibition, and increased reaction time variability were associated with more pronounced ADHD traits. Working memory and reaction time variability partially statistically mediated the relationship between ADHD PRS and ADHD traits, explaining 14% and 16% of the association, respectively. The mediation effect was specific to the genetic risk for ADHD and did not generalise to genetic risk for four other major psychiatric disorders. Together, these findings provide robust evidence from a large general population sample that working memory and reaction time variability can be considered endophenotypes for ADHD that mediate the relationship between ADHD PRS and ADHD traits.

On Unbounded Motions in a Real Analytic Bouncing ball Problem

We consider the model of a ball elastically bouncing on a racket moving in the vertical direction according to a given periodic function f(t). The gravity force is acting on the ball. We prove that if the function f(t) belongs to a class of trigonometric polynomials of degree 2 then there exists a one dimensional continuum of initial conditions for which the velocity of the ball tends to infinity. Our result improves a previous one by Pustyl’nikov and gives a new upper bound to the applicability of KAM theory to this model.

Terrorism as the Quest for Justice in Contemporary Nigeria

In Nigeria today, the activities of terrorists are no longer new. This is what has characterized the Nigerian state. This hydra-headed monster with its attendant heinous crimes against humanity is the main focus of this paper. In this paper, the problem of terrorism has been discussed from a two dimensional continuum – of terrorist acts as the quest for justice in contemporary Nigeria, and on the other hand, the paper examines the phenomenon as an unjust, inhuman and wicked means implored by the jihadi movement to cause fear among Nigerians. The paper made use of content analysis for its research methodology. The paper leaned on the rational choice theory and the psychological approach. The paper concluded by maintaining the view that no matter the level of provocation or injustice in the social system, terrorist acts remain unfair and inhuman. The actions of terrorists therefore, can never be justified by any measure, human or otherwise.

Joint Characterization of the Cryospheric Spectral Feature Space

Multispectral and hyperspectral feature spaces are useful for a variety of remote sensing applications ranging from spectral mixture modeling to discrete thematic classification. In many of these applications, models are used to project the higher dimensional continuum of reflectances (or radiances) onto lower dimensional mappings of the image target’s physical properties or categorical composition. In such cases, characterization of the feature space dimensionality, geometry and topology can provide fundamental guidance for effective model design. Utility of this characterization, however, hinges on identification of appropriate basis vectors for the feature space. The objective of this study is to compare and contrast two fundamentally different approaches for identifying feature space basis vectors via dimensionality reduction. In so doing, we illustrate how these two approaches can be combined to render a joint characterization that reveals spectral properties not apparent using either approach alone. We use a diverse collection of AVIRIS-NG reflectance spectra of ice and snow to illustrate the utility of the joint characterization to facilitate both modeling and classification of snow and ice reflectance. Joint characterization is also shown to assist with interpretation of physical properties inferred from the spectra. Spectral feature spaces combining principal components (PCs) and t-distributed Stochastic Neighbor Embeddings (t-SNEs) provide both physically interpretable dimensions representing the global structure of cryospheric reflectance properties as well as local manifold structures revealing clustering not resolved within the global continuum. The joint characterization reveals distinct continua for snow-firn gradients on different parts of the Greenland Ice Sheet and multiple clusters of ice reflectance properties common to both glacier and sea ice in different locations. The clustering revealed in the t-SNE feature spaces, and extended to the joint characterization, distinguishes subtle differences in spectral curvature specific to different spatial locations within the snow accumulation zone, as well as BRDF effects related to view geometry. The ability of the PC + t-SNE joint characterization to produce a physically interpretable spectral feature space revealing global topology while preserving local manifold structures for cryospheric hyperspectra suggests that this type of characterization might be extended to the much higher dimensional hyperspectral feature space of all terrestrial land cover.

Comparing the effects of linear and one-term Ogden elasticity in a model of glioblastoma invasion.

Our modelling of brain mechanics is based on observations of Budday and colleagues [6], who analyzed the elastic properties of human brain tissue samples under multiple loading modes. Using these data, Budday et al. determined a realistic constitutive model for brain tissue mechanics. In these studies, they found that compression and shear responses were best modelled by a non-linear one-term Ogden elasticity model, although other elasticity models are possible as well. Here we analyze the role of the elasticity model of brain tissue on the invasion speed of glioma and the resulting tissue deformation (mass effect). We present a one dimensional continuum model that couples cell dynamics to tissue mechanics. Since the mechanics of glioma-compromised brain tissue is not clear, for comprehensive studies, we incorporate both elastic and viscoelastic versions of two brain tissue elasticity models - the commonly employed linear model and the experimentally determined one-term Ogden model. For each elasticity model we identify travelling wave solutions in one dimension and calculate the corresponding invasion speeds. We find that the invasion speed is, in fact, independent of the chosen elasticity model. However, the deformations of the brain tissue, and resulting stress, between the linear and one-term Ogden models are drastically different: the Ogden model shows two orders of magnitude less deformation and three orders of magnitude less stress as compared to the linear model. Such a discrepancy might be relevant when looking at glioma-induced health complications. Statement of significanceCancers arising from glial cells, known as gliomas, form in the spine and the brain. The spread of glioma is not fully understood, although recent studies have highlighted the role of tissue mechanics as a main factor in the invasion process. We present a one dimensional continuum model framework of glioma invasion that incorporates proliferation and invasion of glioma cells, as well as mass effects by coupling cell dynamics to tissue mechanics. We explore both elastic and viscoelastic versions of two brain tissue elasticity models - the commonly employed linear model and the experimentally determined one-term Ogden model. This is the first time the one-term Ogden model has been incorporated into a model of glioma invasion. We show that although the choice of elasticity model does not affect the invasion speed, the deformation and stress generated in the tissue are significantly different with the Ogden model producing three orders of magnitude less deformation and stress as compared to the linear model. Such a discrepancy might be relevant when looking at glioma-induced health complications.

Many-Body Interactions on Phonon Properties of Stanene

Novel properties are observed to arise at 2d level, which is typically absent in their bulk counterparts. Graphene, the most widely studied 2D material. Recently, the other 2D group-IV materials, silicene, germanene and stanene, have been realized by epitaxial growth on substrates and attracted tremendous interest due to their extraordinary properties. The discovery of stanene, a buckled monolayer of tin atoms arranged in a 2D honeycomb lattice, has explored enormous research interest in the materials in the two-dimensional (2D) realm. Stanene exhibit ductile nature and hence could be easily incorporated with existing technology in semiconductor industry on substrates in comparison to Graphene. the systematic investigation of phonon properties for stanene is needed. The general three dimensional continuum model of phonons in two dimensional materials is developed. At present, our research group find the lattice dynamical matrix and secular equations with solutions, phonon dispersion curve and Phonon density of states using Adiabatic Bond Charge Model with the help of MATLAB. We hope that phonon properties of Stanene will be good fitted with experimental data.

The Translational Potential of Non-coding RNAs and Multimodal MRI Data Sets as Diagnostic and Differential Diagnostic Biomarkers for Mood Disorders.

Major Depressive Disorder (MDD) and Bipolar Disorder (BD) have a high prevalence and detrimental socio-economic consequences for the patients and the community. Furthermore, the depressive symptomatology of both disorders is essentially identical, thus rendering the clinical differential diagnosis between the two significantly more difficult considering the concomitant lack of objective biomarkers. Mood disorders are multifactorial disorders the pathophysiology of which includes genetic, epigenetic, neurobiological, neuroimmunological, structural and functional brain alterations, etc. Aberrant genetic variants as well as changed differential expression of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) have been implicated in the pathophysiology of MDD and BD. MiRNAs as well as lncRNAs have regulatory and modulating functions on protein-- coding gene expression thus influencing the remodeling of the architecture, neurotransmission, immunomodulation, etc. in the Central Nervous System (CNS) which are essential in the development of psychiatric disorders including MDD and BD. Moreover, both shared and distinct structural, connectivity, task-related and metabolic features have been observed via functional magnetic resonance imaging and magnetic resonance spectroscopy, suggesting the possibility of a dimensional continuum between the two disorders instead of a categorical differentiation. Aberrant connectivity within and between the Default Mode Network, the Salience Network, Executive Network, etc. as well as dysfunctional emotion, cognitive and executive processing have been associated with mood disorders. Therefore, the aim of this review is to explore a more multidimensional framework in the scientific research of mood disorders, including epigenetic and neuroimaging data in order to shape an outline for their translational capacity in clinical practice.

Coherent propagation and incoherent diffusion of elastic waves in a two dimensional continuum with a random distribution of edge dislocations

We study the coherent propagation and incoherent diffusion of in-plane elastic waves in a two dimensional continuum populated by many, randomly placed and oriented, edge dislocations. Because of the Peierls–Nabarro force the dislocations can oscillate around an equilibrium position with frequency ω0 . The coupling between waves and dislocations is given by the Peach–Koehler force. This leads to a wave equation with an inhomogeneous term that involves a differential operator. In the coherent case, a Dyson equation for a mass operator is set up and solved to all orders in perturbation theory in independent scattering approximation (ISA). As a result, a complex index of refraction is obtained, from which an effective wave velocity and attenuation can be read off, for both longitudinal and transverse waves. In the incoherent case a Bethe–Salpeter equation is set up, and solved to leading order in perturbation theory in the limit of low frequency and wave number. A diffusion equation is obtained and the (frequency-dependent) diffusion coefficient is explicitly calculated. It reduces to the value obtained with energy transfer arguments at low frequency. An important intermediate step is the obtention of a Ward–Takahashi identity (WTI) for a wave equation that involves a differential operator, which is shown to be compatible with the ISA.

Low-energy effective field theories of fermion liquids and the mixed U(1)×Rd anomaly

In this paper, we study gapless fermionic and bosonic systems in $d$-dimensional continuum space with $U(1)$ particle-number-conservation and ${\mathbb{R}}^{d}$ translation symmetry. We present low-energy effective field theories for several gapless phases with the $U(1)\ifmmode\times\else\texttimes\fi{}{\mathbb{R}}^{d}$ symmetry. The $U(1)\ifmmode\times\else\texttimes\fi{}{\mathbb{R}}^{d}$ symmetry has a property that a $U(1)$ symmetry twist will induce a nonzero momentum proportional to the $U(1)$ charge density $\overline{\ensuremath{\rho}}$, which will be referred to as a mixed anomaly. The different effective field theories for different phases of the same system must have the same mixed anomaly. As a result, all the low-energy effective field theories must have fields with nonzero momenta of the order of ${\overline{\ensuremath{\rho}}}^{1/d}$. In particular, we present a low-energy effective field theory with infinite number of fields for Fermi liquid. We also present the Fermi-liquid effective field theory in the presence of a real space magnetic field and $\mathbit{k}$-space ``magnetic'' field, as well as in the presence of interaction described by Landau parameters. Our effective field theory correctly captures the mixed anomaly, which constrains the low-energy dynamics, such as determines the volume of the Fermi surface in terms of the mixed anomaly [i.e., in terms of the $U(1)$ charge density]. This is another formulation of the Luttinger-Ward-Oshikawa theorem.

Lateral soil pile structure interaction assessment for semi active tuned mass damper buildings

Using Lateral load-displacement curves (p-y curves) which is recommended by American Petroleum Institute (API) guideline, is typically used as a design approach for analysis of soil-pile-structure interaction due to its simplicity. The soil-pile structure interface has two separate parts of interaction; kinematic and inertial interaction. Both types of interaction must be measured accurately for the structures with dampers to determine the optimum parameters for design. For structures equipped with semi active tuned mass damper (STMD) on deep foundation, determination of the optimum STMD characterizations are completely related to the dynamic attitude of the structure. Hence, in this study, first the accuracy of general p-y equation for buildings with STMD which have short period on deep foundations are evaluated. Then, three dimensional continuum method (finite element method) is used and the general equation of API are updated to provide compatibility. The results showed that the accuracy of spring method (p-y curves method) is very poor in estimation of dynamic response of the structure. A modified API equation is proposed to improve the accuracy and reduce the degree of error for the data set provided. However, it is concluded that the three dimensional continuum method is still a more trustworthy approach for the type of problem investigated in this paper.

A systematic review of the clinical utility of the DSM-5 section III alternative model of personality disorder.

Empirical controversy remains regarding the representation and diagnosis of personality disorders, as either distinct categories or as a dimensional continuum of psychopathology. In the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, the Personality and Personality Disorders Work Group presented an alternative model of personality disorder (AMPD) that elicits a hybrid diagnosis. This attempt to combat the various limitations associated with primarily categorical or dimensional approaches was met with criticism regarding the AMPD's indeterminate clinical utility. To seek clarity, the current mixed-methods systematic review aimed to determine the clinical utility of the AMPD within a clinical population. An electronic screening of six databases, in addition to the application of explicit exclusion criteria, revealed 20 studies of relevance. Study characteristics and individual assessments of methodological quality were tabulated. The convergent, narrative synthesis of results was largely in support of the AMPD's clinical utility. Future exploration of the AMPD's communicative value between clinicians and their patients' families, the feasibility of the model's application, and the model's ability to translate into treatment modalities is required to both consolidate the current findings and to support a transition to a hybrid diagnosis of personality psychopathology. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Geometrically Nonlinear Analysis of Axially Functionally Graded Beams by Using Finite Element Method

The aim of this paper is to investigate geometrically nonlinear static analysis of axially functionally graded cantilever beam subjected to transversal non follower load. The considered problem is solved by finite element method with total Lagrangian kinematic approach. The material properties of the beam vary along the longitudinal direction according to the power law function. The finite element model of the beam is considered in the three dimensional continuum approximation for an eight-node quadratic element. The geometrically nonlinear problem is solved by Newton-Raphson iteration method. In the numerical results, the effects of the material distribution on the geometrically nonlinear static displacements of the axially functionally graded beam are investigated. Also, the differences between of material distributions are investigated in geometrically analysis.