Orthogonal Dimensions Research Articles

A taxonomy for human social perception: Data-driven modeling with cinematic stimuli.

Every day, humans encounter complex social situations that need to be encoded effectively to allow interaction with others. Yet, principles for organizing the perception of social features from the external world remain poorly characterized. In this large-scale study, we investigated the principles of social perception in dynamic scenes. In the primary data set, we presented 234 movie clips (41 min) containing various social situations to 1,140 participants and asked them to evaluate the presence of 138 social features in each clip. Analyses of the social feature ratings revealed that some features are perceived categorically (present or absent) and others continuously (intensity) and simple social features requiring immediate response are perceived most consistently across participants. To establish the low-dimensional perceptual organization for social features based on movies, we used principal coordinate analysis and consensus clustering for the feature ratings. These dimension reduction analyses revealed that the social perceptual structure can be modeled with eight main dimensions and that behaviorally relevant perceptual categories emerge from these main dimensions. This social perceptual structure generalized from the perception of unrelated Hollywood movie clips to the perception of a full Finnish movie (70 min) and to the perception of static images (n = 468) and across three independent sets of participants (n = 2,254). Based on the results, we propose eight basic dimensions of social perception as a model for rapid social perception where social situations are perceived along eight orthogonal perceptual dimensions (most importantly emotional valence, empathy vs. dominance, and cognitive vs. physical behavior). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

How Government Stereotypes Affect Life Satisfaction: a Good Government Matters More Than a Government That Does Good

Many studies have noted the close relationship between the government and people’s life satisfaction. However, little literature has paid attention to the role of government stereotypes. This research fills this gap using two large samples of Chinese residents. In the first-phase study, we explored the content and structure of government stereotypes with a data-driven approach. We found that the content of government stereotypes consisted of four clusters: positive evaluations, negative evaluations, things about government duties, and things about the government system. Further, the content of government stereotypes could be distinguished based on two orthogonal dimensions: the valence (negative vs. positive) and the degree of generality (particularized vs. generalized). In the second-phase study, we examined how various dimensions of government stereotypes were related to life satisfaction. We found that people with more positive government stereotypes were more satisfied with life. This association was more potent when government stereotypes were more generalized (i.e., a good government at a higher construal level) than particularized (i.e., a government that does good at a lower construal level). Both studies of this research were repeatable within the two large samples. This research provided a new perspective for the literature on the relationship between government and life satisfaction and the interventions to improve life satisfaction.

Domain-specific associations between psychopathology and neurocognitive functioning.

Neurocognitive dysfunction is a transdiagnostic finding in psychopathology, but relationships among cognitive domains and general and specific psychopathology dimensions remain unclear. This study aimed to examine associations between cognition and psychopathology dimensions in a large youth cohort. The sample (N = 9350; age 8-21 years) was drawn from the Philadelphia Neurodevelopmental Cohort. Data from structured clinical interviews were modeled using bifactor confirmatory factor analysis (CFA), resulting in an overall psychopathology ('p') factor score and six orthogonal psychopathology dimensions: dysphoria/distress, obsessive-compulsive, behavioral/externalizing, attention-deficit/hyperactivity, phobias, and psychosis. Neurocognitive data were aggregated using correlated-traits CFA into five factors: executive functioning, memory, complex cognition, social cognition, and sensorimotor speed. We examined relationships among specific and general psychopathology dimensions and neurocognitive factors. The final model showed both overall and specific associations between cognitive functioning and psychopathology, with acceptable fit (CFI = 0.91; TLI = 0.90; RMSEA = 0.024; SRMR = 0.054). Overall psychopathology and most psychopathology dimensions were negatively associated with neurocognitive functioning (phobias [p < 0.0005], behavioral/externalizing [p < 0.0005], attention-deficit/hyperactivity [p < 0.0005], psychosis [p < 0.0005 to p < 0.05]), except for dysphoria/distress and obsessive-compulsive symptoms, which were positively associated with complex cognition (p < 0.05 and p < 0.01, respectively). By modeling a broad range of cognitive and psychopathology domains in a large, diverse sample of youth, we found aspects of neurocognitive functioning shared across clinical phenotypes, as well as domain-specific patterns. Findings support transdiagnostic examination of cognitive performance to parse variability in the link between neurocognitive functioning and clinical phenotypes.

Anhedonia is associated with overgeneralization of conditioned fear during late adolescence and early adulthood

BackgroundPavlovian fear paradigms involve learning to associate cues with threat or safety. Aberrances in Pavlovian fear learning correlate with psychopathology, especially anxiety disorders. This study evaluated symptom dimensions of anxiety and depression in relation to Pavlovian fear acquisition and generalization. Methods256 participants (70.31 % female) completed a Pavlovian fear acquisition and generalization paradigm at ages 18–19 and 21–22 years. Analyses focused on indices of learning (self-reported US expectancy, skin conductance). Multilevel models tested associations with orthogonal symptom dimensions (Anhedonia-Apprehension, Fears, General Distress) at each timepoint. ResultsAll dimensions were associated with weaker acquisition of US expectancies at each timepoint. Fears was associated with overgeneralization only at age 21–22. General Distress was associated with overgeneralization only at age 18–19. Anhedonia-Apprehension was associated with overgeneralization at ages 18–19 and 21–22. ConclusionsAnhedonia-Apprehension disrupts Pavlovian fear acquisition and increases overgeneralization of fear. These effects may emerge during adolescence and remain into young adulthood. General Distress and Fears also contribute to overgeneralization of fear, but these effects may vary as prefrontal mechanisms of fear inhibition continue to develop during late adolescence. Targeting specific symptom dimensions, particularly Anhedonia-Apprehension, may decrease fear generalization and augment interventions built on Pavlovian principles, such as exposure therapy.

Exploring the evolution of research topics during the COVID-19 pandemic

The COVID-19 pandemic has changed the research agendas of most scientific communities, resulting in an overwhelming production of research articles in a variety of domains, including medicine, virology, epidemiology, economy, psychology, and so on. Several open-access corpora and literature hubs were established; among them, the COVID-19 Open Research Dataset (CORD-19) has systematically gathered scientific contributions for 2.5 years, by collecting and indexing over one million articles—this corpus, however, does not provide an easy-to-access overview of its content. Here, we present the CORD-19 Topic Visualizer (CORToViz), a method and associated visualization tool for inspecting the CORD-19 textual corpus of scientific abstracts. Our method is based upon a careful selection of up-to-date technologies (including large language models), resulting in an architecture for clustering articles along orthogonal dimensions and extraction techniques for temporal topic mining. Topic inspection is supported by an interactive dashboard, providing fast, one-click visualization of topic contents as word clouds and topic trends as time series, equipped with easy-to-drive statistical testing for analyzing the significance of topic emergence along arbitrarily selected time windows. Overall, our pipeline is very fast and its results match our expectations on topic identification (F1-score 0.854). The processes of data preparation and results visualization are completely general and virtually applicable to any corpus of textual documents—thus suited for effective adaptation to other contexts.

Validation of the Approach-Avoidance Temperament Questionnaire in Individuals with Anxiety and Depression

The Approach-Avoidance Temperament Questionnaire (ATQ) is a well-established measure assessing heightened sensitivity and reactivity to reward/positive stimuli (approach temperament) and to punishment/negative stimuli (avoidance temperament). These basic dimensions of personality are believed to be important for understanding the etiology and maintenance of anxiety and depressive disorders. Despite the ATQ’s potential utility in clinical psychology research, its psychometric properties and factor structure have yet to be examined in a psychiatric sample. The aims of the present study were to 1) conduct confirmatory factor analysis to replicate the ATQ’s factor structure in individuals diagnosed with an anxiety or depressive disorder (N = 244), 2) assess internal consistency and convergent and divergent validity, and 3) explore differences in approach and avoidance temperaments in individuals with versus without a diagnosis of anxiety or depression. Results confirmed the original two-factor structure of the ATQ in a clinical sample, with approach and avoidance temperaments representing orthogonal dimensions. The measure demonstrated strong internal consistency, convergent and divergent validity, and predictive validity. Individuals with anxiety and depression scored higher on avoidance items and lower on approach items compared to those without clinical diagnoses. This study supports the use of the ATQ in clinical populations.

A review of reasoning characteristics of RDF‐based Semantic Web systems

AbstractPresented as a research challenge in 2001, the Semantic Web (SW) is now a mature technology, used in several cross‐domain applications. One of its key benefits is a formal semantics of its RDF data format, which enables a system to validate data, infer implicit knowledge by automated reasoning, and explain it to a user; yet the analysis presented here of 71 RDF‐based SW systems (out of which 17 reasoners) reveals that the exploitation of such semantics varies a lot among all SW applications. Since the simple enumeration of systems, each one with its characteristics, might result in a clueless listing, we borrow from Software Engineering the idea of maturity model, and organize our classification around it. Our model has three orthogonal dimensions: treatment of blank nodes, degree of deductive capabilities, and explanation of results. For each dimension, we define 3–4 levels of increasing exploitation of semantics, corresponding to an increasingly sophisticated output in that dimension. Each system is then classified in each dimension, based on its documentation and published articles. The distribution of systems along each dimension is depicted in the graphical abstract. We deliberately exclude resources consumption (time and space) since it is a dimension not peculiar to SW.This article is categorized under: Fundamental Concepts of Data and Knowledge &gt; Knowledge Representation Fundamental Concepts of Data and Knowledge &gt; Explainable AI

Hyperspectral Image Classification with the Orthogonal Self-Attention ResNet and Two-Step Support Vector Machine

Hyperspectral image classification plays a crucial role in remote sensing image analysis by classifying pixels. However, the existing methods require more spatial–global information interaction and feature extraction capabilities. To overcome these challenges, this paper proposes a novel model for hyperspectral image classification using an orthogonal self-attention ResNet and a two-step support vector machine (OSANet-TSSVM). The OSANet-TSSVM model comprises two essential components: a deep feature extraction network and an improved support vector machine (SVM) classification module. The deep feature extraction network incorporates an orthogonal self-attention module (OSM) and a channel attention module (CAM) to enhance the spatial–spectral feature extraction. The OSM focuses on computing 2D self-attention weights for the orthogonal dimensions of an image, resulting in a reduced number of parameters while capturing comprehensive global contextual information. In contrast, the CAM independently learns attention weights along the channel dimension. The CAM autonomously learns attention weights along the channel dimension, enabling the deep network to emphasise crucial channel information and enhance the spectral feature extraction capability. In addition to the feature extraction network, the OSANet-TSSVM model leverages an improved SVM classification module known as the two-step support vector machine (TSSVM) model. This module preserves the discriminative outcomes of the first-level SVM subclassifier and remaps them as new features for the TSSVM training. By integrating the results of the two classifiers, the deficiencies of the individual classifiers were effectively compensated, resulting in significantly enhanced classification accuracy. The performance of the proposed OSANet-TSSVM model was thoroughly evaluated using public datasets. The experimental results demonstrated that the model performed well in both subjective and objective evaluation metrics. The superiority of this model highlights its potential for advancing hyperspectral image classification in remote sensing applications.

Fundamental dimensions of real-time spoken word recognition in cochlear implant users

Spoken word recognition is a sophisticated cognitive process that maps incoming speech to meaning. For young, normal-hearing adults, word recognition is served by a competition process which plays out incrementally as speech unfolds. Candidates that match the input are activated and compete as mismatching candidates are suppressed. It remains unclear how this process changes in other listeners. Previous results from small-scale studies suggest three dimensions: 1) the speed of activating words (Activation Rate), affected by development and aging; 2) the degree of ultimate competitor suppression (Sustained Activation), affected by hearing loss; and 3) the delay of competition entirely (Wait-and-See), affected by severe hearing loss. To investigate these dimensions, a large, heterogenous group of cochlear implant users (N = 101) completed a Visual World Paradigm task. A principal component analysis supported these three dimensions. Each dimension was predicted by different demographic or auditory factors (onset of deafness, auditory fidelity, age), and each predicted outcomes over and above auditory fidelity. This suggests that these are orthogonal dimensions along which listeners vary, not all-or-nothing strategies. This work identifies the degrees of freedom that can extend theories of word recognition to account for a range of experiences and contexts.

Motor cortex retains and reorients neural dynamics during motor imagery.

The most prominent characteristic of motor cortex is its activation during movement execution, but it is also active when we simply imagine movements in the absence of actual motor output. Despite decades of behavioural and imaging studies, it is unknown how the specific activity patterns and temporal dynamics in motor cortex during covert motor imagery relate to those during motor execution. Here we recorded intracortical activity from the motor cortex of two people who retain some residual wrist function following incomplete spinal cord injury as they performed both actual and imagined isometric wrist extensions. We found that we could decompose the population activity into three orthogonal subspaces, where one was similarly active during both action and imagery, and the others were active only during a single task type-action or imagery. Although they inhabited orthogonal neural dimensions, the action-unique and imagery-unique subspaces contained a strikingly similar set of dynamic features. Our results suggest that during motor imagery, motor cortex maintains the same overall population dynamics as during execution by reorienting the components related to motor output and/or feedback into a unique, output-null imagery subspace.

Global Geopotential Models assessment in Ecuador based on geoid heights and geopotential values

Abstract Since the 1960s, the analysis of disturbed satellite orbits to infer Earth’s gravity field functionals has been an important element in determining the Earth’s gravitational field. The long wavelengths of the gravitational field are recovered through the analysis of non-Keplerian variations in the orbital path of artificial satellites, from their tracking from ground stations (Satellite Laser Ranging, Doppler Orbitography and Radiopositioning Integrated by Satellite, and Precise Range And Range-Rate Equipment), from satellite-to-satellite tracking, or by microwave interferometry. In addition, differences in gravitational acceleration in three mutually orthogonal dimensions can be determined by employing a differential accelerometer carried on artificial satellites (satellite gravity gradiometry, SGG). Satellite gravimetry provides global information (long wavelengths) of the Earth’s gravitational field, which is the fundamental basis for the implementation of Global Geopotential Models (GGMs). The GGMs are one of the key tools for the representation of the Earth’s gravity field and, therefore, for the establishment of a Global Height System (i.e., International Height Reference System), whose fundamental reference surface is defined in terms of a geopotential value. In this study, the validation of high-resolution GGMs (coefficients up to degree 2190) was performed based on their performance in Ecuador by comparing geoid heights estimated by the GGMs with the corresponding values derived from Global Navigation Satellite System/leveling records. Furthermore, geopotential values from the GGMs are compared with the corresponding value obtained for the Ecuadorian Vertical Datum by solving the fixed geodetic boundary value problem. The obtained results indicated that the precision of the high-resolution GGMs does not reach the established requirements for the geopotential computation in the International Height Reference Frame fundamental stations.

Better Understanding Procedural Search Tasks: Perceptions, Behaviors, and Challenges

People often search for information to acquire procedural knowledge–“how to” knowledge about step-by-step procedures, methods, algorithms, techniques, heuristics, and skills. A procedural search task might involve implementing a solution to a problem, evaluating different approaches to a problem, and brainstorming on the types of problems that can be solved with a specific resource. We report on a study ( N =36) that aimed to better understand how people search for procedural knowledge. Much research has investigated how search task characteristics impact people’s perceptions and behaviors. Along these lines, we manipulated procedural search tasks along two orthogonal dimensions: product and goal. The product dimension relates to the main outcome of the task and the goal dimension relates to task’s success criteria. We manipulated tasks across three product categories and two goal categories. The study investigated four research questions. First, we examined the effects of the product and goal on participants’ (RQ1) pre-task perceptions, (RQ2) post-task perceptions, and (RQ3) search behaviors. Second, regardless of the task product and goal, by analyzing participants’ think-aloud comments and screen activities we closely examined how people search for procedural knowledge. Specifically, we report on (RQ4) important relevance criteria, types of information sought, and challenges.

The neural substrates of transdiagnostic cognitive-linguistic heterogeneity in primary progressive aphasia

BackgroundClinical variants of primary progressive aphasia (PPA) are diagnosed based on characteristic patterns of language deficits, supported by corresponding neural changes on brain imaging. However, there is (i) considerable phenotypic variability within and between each diagnostic category with partially overlapping profiles of language performance between variants and (ii) accompanying non-linguistic cognitive impairments that may be independent of aphasia magnitude and disease severity. The neurobiological basis of this cognitive-linguistic heterogeneity remains unclear. Understanding the relationship between these variables would improve PPA clinical/research characterisation and strengthen clinical trial and symptomatic treatment design. We address these knowledge gaps using a data-driven transdiagnostic approach to chart cognitive-linguistic differences and their associations with grey/white matter degeneration across multiple PPA variants.MethodsForty-seven patients (13 semantic, 15 non-fluent, and 19 logopenic variant PPA) underwent assessment of general cognition, errors on language performance, and structural and diffusion magnetic resonance imaging to index whole-brain grey and white matter changes. Behavioural data were entered into varimax-rotated principal component analyses to derive orthogonal dimensions explaining the majority of cognitive variance. To uncover neural correlates of cognitive heterogeneity, derived components were used as covariates in neuroimaging analyses of grey matter (voxel-based morphometry) and white matter (network-based statistics of structural connectomes).ResultsFour behavioural components emerged: general cognition, semantic memory, working memory, and motor speech/phonology. Performance patterns on the latter three principal components were in keeping with each variant’s characteristic profile, but with a spectrum rather than categorical distribution across the cohort. General cognitive changes were most marked in logopenic variant PPA. Regardless of clinical diagnosis, general cognitive impairment was associated with inferior/posterior parietal grey/white matter involvement, semantic memory deficits with bilateral anterior temporal grey/white matter changes, working memory impairment with temporoparietal and frontostriatal grey/white matter involvement, and motor speech/phonology deficits with inferior/middle frontal grey matter alterations.ConclusionsCognitive-linguistic heterogeneity in PPA closely relates to individual-level variations on multiple behavioural dimensions and grey/white matter degeneration of regions within and beyond the language network. We further show that employment of transdiagnostic approaches may help to understand clinical symptom boundaries and reveal clinical and neural profiles that are shared across categorically defined variants of PPA.

Optical Nonlinearity Enabled Super-Resolved Multiplexing Microscopy.

Optical multiplexing for nanoscale object recognition is of great significance within the intricate domains of biology, medicine, anti-counterfeiting, and microscopic imaging. Traditionally, the multiplexing dimensions of nanoscopy are limited to emission intensity, color, lifetime, and polarization. Here, a novel dimension, optical nonlinearity, is proposed for super-resolved multiplexing microscopy. This optical nonlinearity is attributable to the energy transitions between multiple energy levels of the doped lanthanide ions in upconversion nanoparticles (UCNPs), resulting in unique optical fingerprints for UCNPs with different compositions. A vortex beam is applied to transport the optical nonlinearity onto the imaging point-spread function (PSF), creating a robust super-resolved multiplexing imaging strategy for differentiating UCNPs with distinctive optical nonlinearities. The composition information of the nanoparticles can be retrieved with variations of the corresponding PSF in the obtained image. Four channels multiplexing super-resolved imaging with a single scanning, applying emission color and nonlinearity of two orthogonal imaging dimensions with a spatial resolution higher than 150nm (1/6.5λ), are demonstrated. This work provides a new and orthogonal dimension - optical nonlinearity - to existing multiplexing dimensions, which shows great potential in bioimaging, anti-counterfeiting, microarray assays, deep tissue multiplexing detection, and high-density data storage.

The Circumplex of Faith Modes

This article presents the Circumplex of Faith Modes (CFM), a model that integrates and organizes the existing body of knowledge about the types of religiousness in the Allportian approach and related strands of research. The model was developed from the emic perspective, describing the various forms of Christian religiousness understood as the relationship between man and God within the community of the Church. Here, faith plays out in two domains: the relationship with Transcendence (God) and the relationship with the community of the Church (the psychosocial domain). In both domains, the various faith modes are described using two orthogonal dimensions: in the former domain these are (1) one’s attitude to God/relationship with God and (2) one’s attitude to the doctrine/rites/prescriptions/law; and in the latter domain the dimensions are (1) the significance/role of the religious community and (2) the role/strength of self in one’s personal attitude to God and the doctrine. The circumplex was created by superimposing the orthogonal dimensions of the two domains rotated by 45 degrees with respect to one another, with the four dimensions forming its main axes. The resulting model distinguishes and describes eight modes of faith (poles of the four dimensions), which are related to one another in specific ways and which comprise the Circumplex of Faith Modes.

Alexithymia and interpersonal problems in healthy young individuals

BackgroundAlexithymia refers to a multidimensional personality trait with the facets difficulties identifying feelings (DIF), difficulties describing feelings (DDF), and externally orientated thinking (EOT). Alexithymia is a risk factor for mental and somatic disorders. Previous research with patients suffering from various disorders showed positive relationships between alexithymia and interpersonal problems. Only one study analyzed the link between alexithymic features and interpersonal difficulties in healthy individuals but yielded inconclusive findings because participants’ negative affects were not controlled. A widely accepted conceptualization of interpersonal problems relies on the interpersonal circumplex, which is defined by two orthogonal dimensions, agency and communion. In the present study, we analyzed which facets of alexithymia are associated with the two interpersonal problem dimensions and the global severity of interpersonal distress, after adjusting for negative affect.MethodsTwo-hundred healthy young individuals (100 women) participated in the study. Alexithymic features were assessed using the 20-Item Toronto Alexithymia Scale (TAS-20). Interpersonal problems were measured with the Inventory of Interpersonal Problems (IIP-D). Participants’ state and trait anxiety, depressive symptoms, and verbal intelligence were also assessed.ResultsAll alexithymia scales were positively correlated with general interpersonal distress. Regression results suggested that the TAS-20 subscale DIF was the primary predictor of general interpersonal distress after controlling for negative affectivity. The scale DDF correlated negatively with the IIP-D dimension agency. According to our regression analysis, DDF was a predictor of (low) agency controlling for negative affects. Moreover, DDF correlated negatively with the IIP-D dimension communion. Our regression results indicate that DDF was a predictor of (low) communion independent of negative affect. Correlations between alexithymia facets and IIP-D subscales did not differ between genders.ConclusionsDifficulties identifying feelings seem to be linked to a high level of general interpersonal distress. Difficulties in recognizing one’s feelings may disrupt emotion regulation, which could heighten the general risk of interpersonal problems. Difficulties describing feelings could be a central factor contributing to interpersonal problems related to low communion as well as low agency, since emotion expression and communication are crucial in establishing experiences of social closeness and directing other people’s behavior.

Quantifying Typical Progression of Adolescent Idiopathic Scoliosis: Longitudinal Three-Dimensional MRI Measures of Disc and Vertebral Deformities.

Prospective cohort study. Detail typical three-dimensional segmental deformities and their rates of change that occur within developing adolescent idiopathic scoliosis (AIS) spines over multiple timepoints. AIS is a potentially progressive deforming condition that occurs in three-dimensions of the scoliotic spine during periods of growth. However, there remains a gap for multiple time-point segmental deformity analysis in AIS cohorts during development. Thirty-six female patients with Lenke 1 AIS curves underwent two to six sequential MRIs. Scans were reformatted to produce images in orthogonal dimensions. Wedging angles and rotatory values were measured for segmental elements within the major curve. Two-tailed, paired t-tests compared morphological differences between sequential scans. Rates of change were calculated for variables given the actual time between successive scans. Pearson correlation coefficients were determined for multi-dimensional deformity measurements. Vertebral bodies (VBs) were typically coronally convexly wedged, locally lordotic, convexly axially rotated and demonstrated evidence of local mechanical torsion. Between first and final scans, apical measures of coronal wedging and axial rotation were all greater in both vertebral and intervertebral disc (IVD) morphology than non-apical regions (all reaching differences where P<0.05). No measures of sagittal deformity demonstrated a statistically significant change between scans. Cross-planar correlations were predominantly apparent between coronal and axial planes, with sagittal plane parameters rarely correlating across dimensions. Rates of segmental deformity changes between earlier scans were characterised by coronal plane convex wedging and convexly directed axial rotation. The major locally lordotic deformity changes which did occur in the sagittal plane were static between scans. This novel investigation documented a three-dimensional characterisation of segmental elements of the growing AIS spine and reported these changes across multiple timepoints. Segmental elements are typically deformed from initial presentation and subsequent changes occur in separate orthogonal planes at unique times.

Capturing Impact Messages in Parent–Child Interactions

Abstract: The interpersonal circumplex (IPC) is an established model to describe individual and dyadic interpersonal phenomena along the orthogonal dimensions of control and affiliation. This study aims to adapt and validate the Impact Message Inventory (IMI) to assess impact messages (perceptions of and covert reactions to interpersonal styles) in parents and children according to the IPC. We adapted the German IMI ( Caspar et al., 2016 ) for a young age. Overall, 531 parents and 162 children completed the IMI@YoungAge (IMI@YA). We investigated the reliability and circumplex structure of the octant scales. We also examined the complementarity of impact messages of parents and children and associations with health-related constructs. Most IMI@YA scales demonstrated acceptable internal consistency. The expected circumplex structure could not be replicated. When using factor scores based on exploratory factor analysis, we were able to confirm the complementarity hypothesis in terms of affiliation, but not control. We detected low-to-moderate correlations with health-related constructs. The IMI@YA aims to assess the impact messages of parents and children, but the lack of circumplex structure implies that the items and scales need to be adjusted. We discuss the IPC’s potential for investigating parent-child interaction.

Overhauling Collostructional Analysis: Towards More Descriptive Simplicity and More Explanatory Adequacy

Abstract In this paper, I make two sets of suggestions of how collostructional analysis can be updated. One set of suggestions involves simplifying the analysis for descriptive/exploratory purposes while at the same time enriching it with bootstrapped confidence intervals. The other set of suggestions involves the idea that we should move away from a single kind of association measure for theoretical/exploratory purposes and instead quantify collostructional attraction as a tuple of, minimally, three ideally orthogonal dimensions, namely frequency, association, and dispersion, because only this kind of analysis will be able to address all the dimensions that are relevant to cognitive/usage-based approaches to constructions. In addition, I end with a (renewed) plea to take the notion of construction more seriously: Rather than looking at associations of constructions to forms, which many studies have basically amounted to, I would like us to ‘go back to’ looking at associations of constructions to constructions, i.e. to take the meaning/functional pole of constructions more seriously again and include sense/function in all kinds of collostructional analyses more.

Security Threat Mitigation for Smart Contracts: A Comprehensive Survey

The blockchain technology, initially created for cryptocurrency, has been re-purposed for recording state transitions of smart contracts—decentralized applications that can be invoked through external transactions. Smart contracts gained popularity and accrued hundreds of billions of dollars in market capitalization in recent years. Unfortunately, like all other computer programs, smart contracts are prone to security vulnerabilities that have incurred multibillion-dollar damages over the past decade. As a result, many automated threat mitigation solutions have been proposed to counter the security issues of smart contracts. These threat mitigation solutions include various tools and methods that are challenging to compare. This survey develops a comprehensive classification taxonomy of smart contract threat mitigation solutions within five orthogonal dimensions: defense modality, core method, targeted contracts, input-output data mapping, and threat model. We classify 133 existing threat mitigation solutions using our taxonomy and confirm that the proposed five dimensions allow us to concisely and accurately describe any smart contract threat mitigation solution. In addition to learning what the threat mitigation solutions do, we also show how these solutions work by synthesizing their actual designs into a set of uniform workflows corresponding to the eight existing defense core methods. We further create an integrated coverage map for the known smart contract vulnerabilities by the existing threat mitigation solutions. Finally, we perform the evidence-based evolutionary analysis, in which we identify trends and future perspectives of threat mitigation in smart contracts and pinpoint major weaknesses of the existing methodologies. For the convenience of smart contract security developers, auditors, users, and researchers, we deploy and maintain a regularly updated comprehensive open-source online registry of threat mitigation solutions, called Security Threat Mitigation (STM) Registry at https://seit.egr.msu.edu/research/stmregistry/ .