The present study aims to identify contextual and psychological factors of proneness to radicalization and violent extremism operationalized through the Militant Extremist Mindset scale consisting of three distinct aspects: Proviolence, Vile World beliefs, and trust in Divine Power. A community sample of 271 high school students from Belgrade and Sandžak regions in Serbia completed: a 24-item MEM scale; contextual measures including a 6-item scale of family dysfunction and a 4-item composite measure capturing exposure to a harsh school environment and peer (...) abuse ; psychological measures including the 9-item Right-Wing Authoritarianism scale, the 5-item Social Dominance Orientation scale, and the 20-item UCLA Loneliness scale. A path analysis was conducted with contextual factors on the first and psychological factors on the second level of the model predicting the three factors of MEM. LON was positively predicted by FDys and HSE, SDO by HSE only, while RWA was positively predicted by FDys only. Contextual and psychological factors accounted for 27% of the variance in PV, 15% of the variance in VW, and 31% of the variance in DP. Obtained findings reveal a complex interplay of contextual and psychological drivers in the prediction of different aspects of RVE and build upon existing knowledge on risk factors associated with RVE. (shrink)

In the current socioeconomic environment, brands increasingly need to portray societal and ethical commitments at a corporate level, in order to remain competitive and improve their reputation. However, studies that relate business ethics to corporate brands are either purely conceptual or have been empirically conducted in relation to the field of products/goods. This is surprising because corporate brands are even more relevant in the services sector, due to the different nature of services, and the subsequent need to provide a consistent (...) high-quality customer experience across all the brand–customer interactions and touch-points. Thus, the purpose of this article is to study, at a corporate brand level and in the field of services, the effect of customer perceived ethicality of a brand on brand equity. The model is tested by structural equations, using data collected for eight service categories by means of a panel composed of 2179 customers. The test of measurement equivalence between these categories is conducted using generalizability theory. Confirmatory factor analysis marker technique is applied in order to check for common method variance. The results of the hypothesized model indicate that customer perceived ethicality has a positive, indirect impact on brand equity, through the mediators of brand affect and perceived quality. However, there is no empirical evidence for a direct effect of customer perceived ethicality on brand equity. (shrink)

Since in Heyting Arithmetic all atomic formulas are decidable, a Kripke model for HA may be regarded classically as a collection of classical structures for the language of arithmetic, partially ordered by the submodel relation. The obvious question is then: are these classical structures models of Peano Arithmetic ? And dually: if a collection of models of PA, partially ordered by the submodel relation, is regarded as a Kripke model, is it a model of HA? Some partial (...) answers to these questions were obtained in [6], [3], [1] and [2]. Here we present some results in the same direction, announced in [7]. In particular, it is proved that the classical structures at the nodes of a Kripke model of HA must be models of IΔ1 and that the relation between these classical structures must be that of a Δ1-elementary submodel. MSC: 03F30, 03F55. (shrink)

In the past few decades, a growth in ethical consumerism has led brands to increasingly develop conscientiousness and depict ethical image at a corporate level. However, most of the research studying business ethics in the field of corporate brand management is either conceptual or has been empirically conducted in relation to goods/products contexts. This is surprising because corporate brands are more relevant in services contexts, because of the distinct nature of services and the key role that employees have in the (...) services sector. Accordingly, this article aims at empirically examining the effects of customer perceived ethicality in the context of corporate services brands. Based on data collected for eight service categories using a panel of 2179 customers, the hypothesized structural model is tested using path analysis. The results show that, in addition to a direct effect, customer perceived ethicality has a positive and indirect effect on customer loyalty, through the mediators of customer affective commitment and customer perceived quality. Further, employee empathy positively influences the impact of customer perceived ethicality on customer affective commitment, and customer loyalty positively impacts customer positive word-of-mouth. The first implication of these results is that corporate brand strategy needs to be aligned with human resources policies and practices if brands want to turn ethical strategies into employee behavior. Second, corporate brands should build more authentic communications grounded in their ethical beliefs and supported by evidence from actual employees. (shrink)

In order to be competitive in an era of ethical consumerism, brands are facing an ever-increasing pressure to integrate ethical values into their identities and to display their ethical commitment at a corporate level. Nevertheless, studies that relate business ethics to corporate brands are either theoretical or have predominantly been developed empirically in goods contexts. This is surprising, because corporate brands are more relevant in services settings, given the nature of services, and the fact that services settings comprise a greater (...) number of customer–brand interactions and touch points than goods contexts. Accordingly, the purpose of this article is to empirically examine the effects of customer perceived ethicality of corporate brands that operate in the services sector. Based on data collected for eight service categories using a panel of 2179 customers, the hypothesized structural model is tested using path analysis. The generalizability theory is applied to test for measurement equivalence between these categories. The results of the hypothesized model show that, in addition to a direct impact, customer perceived ethicality has a positive and indirect impact on brand equity, through the mediators of recognition benefits and brand image. Moreover, brand heritage negatively influences the impact of customer perceived ethicality on brand image. The main implication is that managers need to be aware of the need to reinforce brand image and recognition benefits, as this can facilitate the translation of customer perceived ethicality into brand equity. (shrink)

We introduce a probabilistic extension of propositional intuitionistic logic. The logic allows making statements such as P≥sα, with the intended meaning “the probability of truthfulness of α is at least s”. We describe the corresponding class of models, which are Kripke models with a naturally arising notion of probability, and give a sound and complete infinitary axiomatic system. We prove that the logic is decidable.

Emotionally arousing events reach awareness more easily and evoke greater visual cortex activation than more mundane events. Recent studies have shown that they are also perceived more vividly and that emotionally enhanced perceptual vividness predicts memory vividness. We propose that affect-biased attention (ABA) – selective attention to emotionally salient events – is an endogenous attentional system tuned by an individual's history of reward and punishment. We present the Biased Attention via Norepinephrine (BANE) model, which unifies genetic, neuromodulatory, neural and (...) behavioural evidence to account for ABA. We review evidence supporting BANE's proposal that a key mechanism of ABA is locus coeruleus–norepinephrine (LC–NE) activity, which interacts with activity in hubs of affective salience networks to modulate visual cortex activation and heighten the subjective vividness of emotionally salient stimuli. We further review literature on biased competition and look at initial evidence for its potential as a neural mechanism behind ABA. We also review evidence supporting the role of the LC–NE system as a driving force of ABA. Finally, we review individual differences in ABA and memory including differences in sensitivity to stimulus category and valence. We focus on differences arising from a variant of the ADRA2b gene, which codes for the alpha2b adrenoreceptor as a way of investigating influences of NE availability on ABA in humans. (shrink)

“The Aristotelian corpus and Christian Philosophy in Byzantium between the Ninth and Fifteenth Centuries: Readings and Traditions” is the topic of Section I of SIEPM Commission VIII: Byzantine Philosophy. Aristotle’s writings, which were assimilated variously, function as a meta-text of medieval intellectual culture. Between the nineth and fifteenth centuries Byzantine thinkers developed stable and functional strategies for integrating Aristotle’s philosophical methodology into different theological and philosophical contexts. The project will study the influence of Aristotle on Byzantine metaphysics, epistemology, physics and (...) ethics. We shall attempt to reconstruct the Aristotelian roots of key conceptual models in Byzantine philosophy that played a major role in theological discussion and exposition, such as the metaphysical status of hypostasis, the paradigm of essence-energy, the use of the categories for developing the concept of the image, the transformation of Aristotle’s concept of the soul in lig... (shrink)

A necessary first step in collaboration between hypnosis research and meditation research is clarification of key concepts. The authors propose that such clarification is best advanced by neurophenomenological investigations that integrate neuroscience methods with phenomenological models based on first-person reports of hypnotic versus meditative experiences. Focusing on absorption, the authors argue that previous treatments of hypnosis and meditation as equivalent are incorrect, but that they can be fruitfully compared when characteristic features of the states described by these concepts are examined. (...) To this end, the authors use the “phenomenological and neurocognitive matrix of mindfulness” (PNM), a multidimensional model recently proposed by Lutz and colleagues. The authors compare focused attention meditation and open monitoring meditation with hypnosis across the dimensions of the PNM, using it to interpret empirical research on hypnosis, and to shed light on debates about the role of meta-awareness in hypnosis and the role of suggestion in meditation. (shrink)

In the first part of this article we survey general similarities and differences between biological and social macroevolution. In the second (and main) part, we consider a concrete mathematical model capable of describing important features of both biological and social macroevolution. In mathematical models of historical macrodynamics, a hyperbolic pattern of world population growth arises from non-linear, second-order positive feedback between demographic growth and technological development. Based on diverse paleontological data and an analogy with macrosociological models, we suggest that (...) the hyperbolic character of biodiversity growth can be similarly accounted for by non-linear, second-order positive feedback between diversity growth and the complexity of community structure. We discuss how such positive feedback mechanisms can be modelled mathematically. (shrink)

The Gestalt Bubble model describes a subjective phenomenal experience (what is seen) without taking into account the extraphenomenal constraints of perceptual experience (why it is seen as it is). If it intends to be an explanatory model, then it has to include either stimulus or neural constraints, or both.

Anxiety disorders are among the most prevalent mental disorders. Present treatments such as cognitive behavior therapy and pharmacological treatments show only moderate success, which emphasizes the importance for the development of new treatment protocols. Non-invasive brain stimulation methods such as repetitive transcranial magnetic stimulation and transcranial direct current stimulation have been probed as therapeutic option for anxiety disorders in recent years. Mechanistic information about their mode of action, and most efficient protocols is however limited. Here the fear extinction model (...) can serve as a model of exposure therapies for studying therapeutic mechanisms, and development of appropriate intervention protocols. We systematically reviewed 30 research articles that investigated the impact of rTMS and tDCS on fear memory and extinction in animal models and humans, in clinical and healthy populations. The results of these studies suggest that tDCS and rTMS can be efficient methods to modulate fear memory and extinction. Furthermore, excitability-enhancing stimulation applied over the vmPFC showed the strongest potential to enhance fear extinction. We further discuss factors that determine the efficacy of rTMS and tDCS in the context of the fear extinction model and provide future directions to optimize parameters and protocols of stimulation for research and treatment. (shrink)

In the genomics era, bioinformatic analysis, especially in non‐model species, facilitates the identification and naming of numerous new proteins, the function of which is then inferred through homology searches. Here, we question certain aspects of these approaches. What are the criteria that permit such a determination? What are their limits? Naming is classifying. We review the different criteria that are used to name a protein and discuss their constraints. We observe that the name given to a protein often introduces (...) a bias for further functional analyses, a bias that is not often taken into account when analysing results. Last but not least, the heterogeneity of criteria used for naming proteins leads to self‐inconsistent or contradictory protein classification that is potentially misleading. Finally, we recommend a wider use of phylogenetic criteria in protein naming. BioEssays 30:349–357, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

Most research on risk aversion in behavioral science with human subjects has focused on a component of risk aversion that does not adapt itself to context. More recently, studies have explored risk aversion adaptation to changing circumstances in sequential decision-making tasks. It is an open question whether one can identify evidence, at the single subject level, for such risk aversion adaptation. We conducted a behavioral experiment on human subjects, using a sequential decision making task. We developed a model-based approach (...) for estimating the adaptation of risk-taking behavior with single-trial resolution by modelling a subject’s goals and internal representation of task contingencies. Using this model-based approach, we estimated the subject-specific adaptation of risk aversion depending on the current task context. We found striking inter-subject variations in the adaptation of risk-taking behavior. We show that these differences can be explained by differences in subjects’ internal representations of task contingencies and goals. We discuss that the proposed approach can be adapted to a wide range of experimental paradigms and be used to analyze behavioral measures other than risk aversion. (shrink)

In the first part of this article we survey general similarities and differences between biological and social macroevolution. In the second (and main) part, we consider a concrete mathematical model capable of describing important features of both biological and social macroevolution. In mathematical models of historical macrodynamics, a hyperbolic pattern of world population growth arises from non-linear, second-order positive feedback between demographic growth and technological development. Based on diverse paleontological data and an analogy with macrosociological models, we suggest that (...) the hyperbolic character of biodiversity growth can be similarly accounted for by non-linear, second-order positive feedback between diversity growth and the complexity of community structure. We discuss how such positive feedback mechanisms can be modelled mathematically. (shrink)

Page's manifesto makes a case for localist representations in neural networks, one of the advantages being ease of interpretation. However, even localist networks can be hard to interpret, especially when at some hidden layer of the network distributed representations are employed, as is often the case. Hidden Markov models can be used to provide useful interpretable representations.

This paper introduces a class of graphical independence models that is closed under marginalization and conditioning but that contains all DAG independence models. This class of graphs, called maximal ancestral graphs, has two attractive features: there is at most one edge between each pair of vertices; every missing edge corresponds to an independence relation. These features lead to a simple parameterization of the corresponding set of distributions in the Gaussian case.

In this paper, we study the performance of baseline hidden Markov model (HMM) for segmentation of speech signals. It is applied on single-speaker segmentation task, using Hindi speech database. The automatic phoneme segmentation framework evolved imitates the human phoneme segmentation process. A set of 44 Hindi phonemes were chosen for the segmentation experiment, wherein we used continuous density hidden Markov model (CDHMM) with a mixture of Gaussian distribution. The left-to-right topology with no skip states has been (...) selected as it is effective in speech recognition due to its consistency with the natural way of articulating the spoken words. This system accepts speech utterances along with their orthographic “transcriptions” and generates segmentation information of the speech. This corpus was used to develop context-independent hidden Markov models (HMMs) for each of the Hindi phonemes. The system was trained using numerous sentences that are relevant to provide information to the passengers of the Metro Rail. The system was validated against a few manually segmented speech utterances. The evaluation of the experiments shows that the best performance is obtained by using a combination of two Gaussians mixtures and five HMM states. A category-wise phoneme error analysis has been performed, and the performance of the phonetic segmentation has been reported. The modeling of HMMs has been implemented using Microsoft Visual Studio 2005 (C++), and the system is designed to work on Windows operating system. The goal of this study is automatic segmentation of speech at phonetic level. (shrink)

Hidden Markov models (HMMs) have been successful for modelling the dynamics of carefully dictated speech, but their performance degrades severely when used to model conversational speech. Since speech is produced by a system of loosely coupled articulators, stochastic models explicitly representing this parallelism may have advantages for automatic speech recognition (ASR), particularly when trying to model the phonological effects inherent in casual spontaneous speech. This paper presents a preliminary feasibility study of one such model class: loosely (...) coupled HMMs. Exact model estimation and decoding is potentially expensive, so possible approximate algorithms are also discussed. Comparison of one particular loosely coupled model on an isolated word task suggests loosely coupled HMMs merit further investigation. An approximate algorithm giving performance which is almost always statistically indistinguishable from the exact algorithm is also identified, making more extensive research computationally feasible. (shrink)

Markov models of evolution describe changes in the probability distribution of the trait values a population might exhibit. In consequence, they also describe how entropy and conditional entropy values evolve, and how the mutual information that characterizes the relation between an earlier and a later moment in a lineage’s history depends on how much time separates them. These models therefore provide an interesting perspective on questions that usually are considered in the foundations of physics—when and why does entropy increase (...) and at what rates do changes in entropy take place? They also throw light on an important epistemological question: are there limits on what your observations of the present can tell you about the evolutionary past? (shrink)

The results of two experiments are analyzed to find out how artistic expertise influences visual search. Experiment I comprised survey data of 1,065 students on self-reported visual memory skills and their ability to find three targets in four images of artwork. Experiment II comprised eye movement data of 50 Visual Literacy experts and non-experts whose eye movements during visual search were analyzed for nine images of artwork as an external validation of the assessment tasks performed in Sample I. No time (...) constraint was set for completion of the visual search task. A latent profile analysis revealed four typical solution patterns for the students in Sample I, including a mainstream group, a group that completes easy images fast and difficult images slowly, a fast and erroneous group, and a slow working student group, depending on task completion time and on the probability of finding all three targets. Eidetic memory, performance in art education and visual imagination as self-reported visual skills have significant impact on latent class membership probability. We present a hidden Markov model approach to uncover underlying regions of attraction that result from visual search eye-movement behavior in Experiment II. VL experts and non-experts did not significantly differ in task time and number of targets found but they did differ in their visual search process: compared to non-experts, experts showed greater precision in fixating specific prime and target regions, assessed through hidden state fixation overlap. Exploratory analysis of HMMs revealed differences between experts and non-experts in image locations of attraction. Experts seem to focus their attention on smaller image parts whereas non-experts used wider parts of the image during their search. Differences between experts and non-experts depend on the relative saliency of targets embedded in images. HMMs can determine the effect of expertise on exploratory eye movements executed during visual search tasks. Further research on HMMs and art expertise is required to confirm exploratory results. (shrink)

Topics in Cognitive Science, Volume 14, Issue 2, Page 388-399, April 2022.

To identify relationships among entities in natural language texts, extraction of entity relationships technically provides a fundamental support for knowledge graph, intelligent information retrieval, and semantic analysis, promotes the construction of knowledge bases, and improves efficiency of searching and semantic analysis. Traditional methods of relationship extraction, either those proposed at the earlier times or those based on traditional machine learning and deep learning, have focused on keeping relationships and entities in their own silos: extracting relationships and entities are conducted in (...) steps before obtaining the mappings. To address this problem, a novel Chinese relationship extraction method is proposed in this paper. Firstly, the triple is treated as an entity relation chain and can identify the entity before the relationship and predict its corresponding relationship and the entity after the relationship. Secondly, the Joint Extraction of Entity Mentions and Relations model is based on the Bidirectional Long Short-Term Memory and Maximum Entropy Markov Model. Experimental results indicate that the proposed model can achieve a precision of 79.2% which is much higher than that of traditional models. (shrink)

Water quality control helps in the estimation of water bodies and detects the span of pollutants and their effect on the neighboring environment. This is why the water quality of the northern part of Lake Manzala has been studied here from January to March, 2016. This study aims to model and create a program for linear and nonlinear regression of the water elements in Lake Manzala to assess and predict the water quality. Water samples have been extracted from various (...) depths, and physio-chemical properties and heavy metal concentrations have been evaluated. This study has proposed a new algorithm for predicting water quality called “Algorithm of Estimation Regression Model”. On the contrary, in renewable energy applications, statistical modeling and forecasting the solar radiation remains a significant issue with detect to reinforce power management. A new proposed method for forecasting the average Monthly Global Solar Energy in Queensland, Australia, is called, Converting Data Set into Markov Model. It was used to obtain Markov transition probability matrices for three and six states of the solar energy. The proposed forecasting method yielded accurate results with minimal error. (shrink)

Public policy and public opinion directly affect the image of the government, but due to the lack of appropriate monitoring and early warning tools, the government’s handling of credit changes is seriously lagging behind. In response to this problem, this paper integrates the internet, public information, market credit information, and other data, uses hidden Markov models and natural language processing technology, and establishes a modern government public policy and public opinion monitoring and early warning model to evaluate government (...) credit in real time; the government can formulate relevant policies based on the evaluation results to improve the government’s governance capabilities. Empirical analysis shows that, based on the dynamic scoring framework and Markov model, the government credit monitoring and early warning models established, respectively, have 90% of the reference value, and the analysis results have the same reference. This method can effectively predict the trend of hot online public opinion. The subsequent establishment of an online public opinion early warning system and an online public opinion guidance mechanism provided theoretical support. (shrink)

Autism spectrum disorder is a group of complex neurodevelopment disorders characterized by altered brain connectivity. However, the majority of neuroimaging studies for ASD focus on the static pattern of brain function and largely neglect brain activity dynamics, which might provide deeper insight into the underlying mechanism of brain functions for ASD. Therefore, we proposed a framework with Hidden Markov Model analysis for resting-state functional MRI from a large multicenter dataset of 507 male subjects. Specifically, the 507 subjects included (...) 209 subjects with ASD and 298 well-matched health controls across 14 sites from the Autism Brain Imaging Data Exchange. Based on the HMM, we can identify the recurring brain function networks over time across ASD and healthy controls. Then we assessed the dynamical configuration of the whole-brain networks and further analyzed the community structure of transitions across the brain states. Based on the 19 HMM states, we found that the global temporal statistics of the specific HMM states were significantly altered in ASD compared to HCs. These specific HMM states were characterized by the activation pattern of default mode network, sensory processing networks [including visual network, auditory network, and sensory and motor network ]. Meanwhile, we also find that the specific modules of transitions between states were closely related to ASD. Our findings indicate the temporal reconfiguration of the brain network in ASD and provide novel insights into the dynamics of the whole-brain networks for ASD. (shrink)

Theoretical models propose that attentional biases might account for the maintenance of social anxiety symptoms. However, previous eye-tracking studies have yielded mixed results. One explanation i...

User location prediction in location-based social networks can predict the density of people flow well in terms of intelligent transportation, which can make corresponding adjustments in time to make traffic smooth, reduce fuel consumption, reduce greenhouse gas emissions, and help build a green cycle low-carbon transportation green system. This paper proposes a Markov chain position prediction model based on multidimensional correction. Firstly, extract corresponding information from the user’s historical check-in position sequence as a position-position conversion map. Secondly, the (...) influence of check-in period, space distance, and other factors on the position prediction is linearly weighted and merged with the position prediction of the n-order Markov chain to construct MDC-MCM. Finally, we conduct a comprehensive performance evaluation of MDC-MCM using the dataset collected from Brightkite. Experimental results show that compared with other advanced location prediction technologies, MDC-MCM achieves better location prediction results. (shrink)

In this paper, we describe a model that learns semantic representations from the distributional statistics of language. This model, however, goes beyond the common bag‐of‐words paradigm, and infers semantic representations by taking into account the inherent sequential nature of linguistic data. The model we describe, which we refer to as a Hidden Markov Topics model, is a natural extension of the current state of the art in Bayesian bag‐of‐words models, that is, the Topics model (...) of Griffiths, Steyvers, and Tenenbaum (2007), preserving its strengths while extending its scope to incorporate more fine‐grained linguistic information. (shrink)

Speech recognition plays an important role in human–computer interaction. The higher the accuracy and efficiency of speech recognition are, the larger the improvement of human–computer interaction performance. This article briefly introduced the hidden Markov model -based English speech recognition algorithm and combined it with a back-propagation neural network to further improve the recognition accuracy and reduce the recognition time of English speech. Then, the BPNN-combined HMM algorithm was simulated and compared with the HMM algorithm and the BPNN algorithm. (...) The results showed that increasing the number of test samples increased the word error rate and recognition time of the three speech recognition algorithms, among which the word error rate and recognition time of the BPNN-combined HMM algorithm were the lowest. In conclusion, the BPNN-combined HMM can effectively recognize English speeches, which provides a valid reference for intelligent recognition of English speeches by computers. (shrink)

Twenty-first century science faces a dilemma. Two of its well-verified foundation stones - relativity and quantum theory - have proven inconsistent. Resolution of the conflict has resisted improvements in experimental precision leaving some to believe that some fundamental understanding in our world-view may need modification or even radical reform. Employment of the wave-front model of electrodynamics, as a propagation process with a Markov property, may offer just such a clarification.

JiJi Zhang and Peter Spirtes. A Characterization of Markov Equivalence Classes for Ancestral Graphical Models.

An application of probabilistic, stimulus-response learning theory to game-like small group situations. The theory is axiomatic, precise, and quantitative; and is deductively fruitful. There is a running comparison of the predictive success of the stimulus-response theory and game theory. The authors claim to have demonstrated "in empirical detail and with quantitative accuracy" that "the social situation, qua social, does not require the introduction of new concepts" beyond those of stimulus-response learning theory. --N. D. B. Jr.

The free energy principle, an influential framework in computational neuroscience and theoretical neurobiology, starts from the assumption that living systems ensure adaptive exchanges with their environment by minimizing the objective function of variational free energy. Following this premise, it claims to deliver a promising integration of the life sciences. In recent work, Markov blankets, one of the central constructs of the free energy principle, have been applied to resolve debates central to philosophy (such as demarcating the boundaries of the (...) mind). The aim of this paper is twofold. First, we trace the development of Markov blankets starting from their standard application in Bayesian networks, via variational inference, to their use in the literature on active inference. We then identify a persistent confusion in the literature between the formal use of Markov blankets as an epistemic tool for Bayesian inference, and their novel metaphysical use in the free energy framework to demarcate the physical boundary between an agent and its environment. Consequently, we propose to distinguish between “Pearl blankets” to refer to the original epistemic use of Markov blankets and “Friston blankets” to refer to the new metaphysical construct. Second, we use this distinction to critically assess claims resting on the application of Markov blankets to philosophical problems. We suggest that this literature would do well in differentiating between two different research programmes: “inference with a model” and “inference within a model.” Only the latter is capable of doing metaphysical work with Markov blankets, but requires additional philosophical premises and cannot be justified by an appeal to the success of the mathematical framework alone. (shrink)