scholarly journals A Revised Framework for the Investigation of Expectation Update Versus Maintenance in the Context of Expectation Violations: The ViolEx 2.0 Model

2021 ◽  
Vol 12 ◽  
Author(s):  
Christian Panitz ◽  
Dominik Endres ◽  
Merle Buchholz ◽  
Zahra Khosrowtaj ◽  
Matthias F. J. Sperl ◽  
...  
Keyword(s):  
Research Fields ◽  
Research Perspectives ◽  
Advance Research ◽  
Interdisciplinary Exchange ◽  
Behavioral Mechanisms ◽  
And Behavior ◽  
Model Features ◽  
New Evidence ◽  
Collaborative Efforts ◽  
Beliefs About The Future

Expectations are probabilistic beliefs about the future that shape and influence our perception, affect, cognition, and behavior in many contexts. This makes expectations a highly relevant concept across basic and applied psychological disciplines. When expectations are confirmed or violated, individuals can respond by either updating or maintaining their prior expectations in light of the new evidence. Moreover, proactive and reactive behavior can change the probability with which individuals encounter expectation confirmations or violations. The investigation of predictors and mechanisms underlying expectation update and maintenance has been approached from many research perspectives. However, in many instances there has been little exchange between different research fields. To further advance research on expectations and expectation violations, collaborative efforts across different disciplines in psychology, cognitive (neuro)science, and other life sciences are warranted. For fostering and facilitating such efforts, we introduce the ViolEx 2.0 model, a revised framework for interdisciplinary research on cognitive and behavioral mechanisms of expectation update and maintenance in the context of expectation violations. To support different goals and stages in interdisciplinary exchange, the ViolEx 2.0 model features three model levels with varying degrees of specificity in order to address questions about the research synopsis, central concepts, or functional processes and relationships, respectively. The framework can be applied to different research fields and has high potential for guiding collaborative research efforts in expectation research.

scholarly journals A revised framework for the investigation of expectation update versus maintenance in the context of expectation violations: the ViolEx 2.0 model

2021 ◽  
Author(s):  
Christian Panitz ◽  
Dominik Endres ◽  
Merle Buchholz ◽  
Zahra Khosrowtaj ◽  
Matthias F.J. Sperl ◽  
...  
Keyword(s):  
Collaborative Research ◽  
Life Sciences ◽  
Research Fields ◽  
Research Perspectives ◽  
Advance Research ◽  
Interdisciplinary Exchange ◽  
Model Features ◽  
New Evidence ◽  
Collaborative Efforts ◽  
Beliefs About The Future

Expectations are probabilistic beliefs about the future that shape and influence our perception, affect, cognition, and behaviour in many contexts. This makes expectations a highly relevant concept across basic and applied psychological disciplines. When expectations are confirmed or violated, individuals can respond by either updating or maintaining their prior expectations in light of the new evidence. Moreover, proactive and reactive behaviour can change the probability with which individuals encounter expectation confirmations or violations. The investigation of predictors and mechanisms underlying expectation update and maintenance has been approached from many research perspectives, however, in many instances with little exchange between different research fields. To further advance research on expectations and expectation violations, collaborative efforts across different disciplines in psychology, cognitive (neuro)science, and other life sciences are warranted. For fostering and facilitating such efforts, we introduce the ViolEx 2.0 model, a revised framework for interdisciplinary research on cognitive and behavioural mechanisms of expectation update and maintenance in the context of expectation violations. To support different goals and stages in interdisciplinary exchange, the ViolEx 2.0 model features three model levels with varying degrees of specificity in order to address questions about the research synopsis, central concepts, or functional processes and relationships, respectively. The framework can be applied to different research fields and has high potential for guiding collaborative research efforts in expectation research.

The future of sustainable supply chains: a novel tertiary-systematic methodology

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Piera Centobelli ◽  
Roberto Cerchione ◽  
Livio Cricelli ◽  
Emilio Esposito ◽  
Serena Strazzullo
Keyword(s):  
New Classification ◽  
Bottom Line ◽  
Content Type ◽  
Main Research ◽  
Sustainable Supply Chains ◽  
Research Areas ◽  
Research Fields ◽  
Research Perspectives ◽  
Systematic Methodology

Purpose In recent years, economic, environmental and social sustainability has become one of the fastest-growing research fields. The number of primary and secondary papers addressing the triple bottom line is growing significantly, and the supply chain (SC) management discipline is in the same wave. Therefore, this paper aims to propose a novel tertiary systematic methodology to explore, aggregate, categorise and analyse the findings provided by secondary studies. Design/methodology/approach A novel tertiary systematic literature review approach, including 94 secondary studies, is proposed and used to analyse sustainable SC literature. The papers have been analysed using a research protocol, including descriptive and content analysis criteria. Findings This tertiary study does not only provide an overview of the literature on the topic of sustainability in SCs but also goes further, drawing up a categorisation of main research areas and research perspectives adopted by previous researchers. The paper also presents a rank of research gaps and an updated and a prioritised agenda. Originality/value This paper provides a novel interpretation of the research topics addressed by the secondary studies and presents a new classification of the literature gaps and their evolution. Finally, a dynamic research compass for both academicians and practitioners is presented.

scholarly journals Feature-reweighted RSA: A method for improving the fit between computational models, brains, and behavior

2021 ◽  
Author(s):  
Philipp Kaniuth ◽  
Martin N. Hebart
Keyword(s):  
Model Selection ◽  
Computational Models ◽  
Model Comparison ◽  
Brain Activity ◽  
Activity Patterns ◽  
Behavioral Data ◽  
Novel Approach ◽  
Improve Model ◽  
And Behavior ◽  
Model Features

AbstractRepresentational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on the comparison of representational dissimilarity matrices (RDM), which characterize the pairwise dissimilarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This ‘equal weights’ assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, for model comparison, it may lead to selecting the inferior model. While previous work has suggested that reweighting can improve model selection in RSA, it has remained unclear to what extent these results generalize across datasets and data modalities. To fill this gap, the aim of this work is twofold: First, utilizing a range of publicly available datasets and three popular deep neural networks (DNNs), we seek to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RDM correspondence and affects model selection. Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We find that reweighting individual model units (1) markedly improves the fit between model RDMs and target RDMs derived from several fMRI and behavioral datasets and (2) affects model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RDM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally demonstrate that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain and behavioral data, possibly allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the match between representational spaces.

The Athabasca Granulite Terrane and Evidence for Dynamic Behavior of Lower Continental Crust

2018 ◽  
Vol 46 (1) ◽  
pp. 353-386 ◽  
Author(s):  
Gregory Dumond ◽  
Michael L. Williams ◽  
Sean P. Regan
Keyword(s):  
Continental Crust ◽  
Lower Crust ◽  
Tectonic Evolution ◽  
Paradigm Shift ◽  
Lower Continental Crust ◽  
Deep Crust ◽  
And Behavior ◽  
Lower Crustal ◽  
New Evidence ◽  
Lower Crustal Xenolith

Deeply exhumed granulite terranes have long been considered nonrepresentative of lower continental crust largely because their bulk compositions do not match the lower crustal xenolith record. A paradigm shift in our understanding of deep crust has since occurred with new evidence for a more felsic and compositionally heterogeneous lower crust than previously recognized. The >20,000-km2Athabasca granulite terrane locally provides a >700-Myr-old window into this type of lower crust, prior to being exhumed and uplifted to the surface between 1.9 and 1.7 Ga. We review over 20 years of research on this terrane with an emphasis on what these findings may tell us about the origin and behavior of lower continental crust, in general, in addition to placing constraints on the tectonic evolution of the western Canadian Shield between 2.6 and 1.7 Ga. The results reveal a dynamic lower continental crust that evolved compositionally and rheologically with time.

Shifts in Herd Mentality of Investors in Uncertain Market Conditions: New Evidence in the Context of a Frontier Stock Market

2018 ◽  
Vol 10 (3(J)) ◽  
pp. 203-219 ◽  
Author(s):  
Kalugala Vidanalage Aruna Shantha
Keyword(s):  
Stock Market ◽  
Learning Effect ◽  
Stock Exchange ◽  
Psychological Effects ◽  
Herd Behavior ◽  
Absolute Deviation ◽  
Cross Sectional ◽  
Post Market ◽  
And Behavior ◽  
New Evidence

This paper examines the herding phenomenon in the context of a frontier stock market, the Colombo Stock Exchange of Sri Lanka, employing the cross - sectional absolute deviation methodology to daily frequencies of data for the period from April, 2000 to September, 2016. The results show significant changes in magnitude and pattern of herding over different episodes of the market. The herd behavior is strongly presence irrespective of the direction of the market movement in the 2000 - 2008 period, during which investments in the stock market is affected by the country’s political instability resulting from the civil war. The evidence also shows herd behavior during the period of market bubble whereas negative herding in the market crash period. However, it becomes less likely to occur during the period after the market crash. The lower tendency to herd during the post- market crash period supports the Adaptive Market Hypothesis, implying that investors are likely to realize the irrationality of herding and learn to be more rational as a consequence of significant losses experienced during the period of the market crash. Accordingly, these findings suggest that period- specific characteristics of the market and the associated psychological effects to investors such as overconfidence and panics would cause changes to their beliefs and behavior, the experiences of which would subsequently produce learning effect to minimize their irrationality in decision making.

scholarly journals Logic-Based Technologies for Intelligent Systems: State of the Art and Perspectives

Information ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 167 ◽  
Author(s):  
Roberta Calegari ◽  
Giovanni Ciatto ◽  
Enrico Denti ◽  
Andrea Omicini
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
State Of The Art ◽  
Future Perspectives ◽  
Main Application ◽  
The Core ◽  
Research Fields ◽  
Research Perspectives ◽  
Key Features ◽  
Symbolic Ai

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future.

scholarly journals Good Intents, but Low Impacts: Diverging Importance of Motivational and Socioeconomic Determinants Explaining Pro-Environmental Behavior, Energy Use, and Carbon Footprint

2017 ◽  
Vol 50 (6) ◽  
pp. 626-656 ◽  
Author(s):  
Stephanie Moser ◽  
Silke Kleinhückelkotten
Keyword(s):  
Environmental Impacts ◽  
Energy Use ◽  
Environmental Behavior ◽  
Self Identity ◽  
Carbon Footprints ◽  
Research Perspectives ◽  
And Behavior ◽  
Environmentally Significant Behavior ◽  
Oriented Research

Earlier research has yielded contradictory results as to the main drivers of environmentally significant behavior. Intent-oriented research has stressed the importance of motivational aspects, while impact-oriented research has drawn attention to people’s socioeconomic status. In this study, we investigated the diverging role of a pro-environmental stance under these two research perspectives. Data from a German survey ( N = 1,012) enabled assessment of per capita energy use, and individual carbon footprints (impact-related measures), pro-environmental behavior (an intent-related measure), and behavior indicators varying in environmental impact and intent. Regression analyses revealed people’s environmental self-identity to be the main predictor of pro-environmental behavior; however, environmental self-identity played an ambiguous role in predicting actual environmental impacts. Instead, environmental impacts were best predicted by people’s income level. Our results show that individuals with high pro-environmental self-identity intend to behave in an ecologically responsible way, but they typically emphasize actions that have relatively small ecological benefits.

scholarly journals THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks

2021 ◽  
Vol 15 ◽  
Author(s):  
Lukas Muttenthaler ◽  
Martin N. Hebart
Keyword(s):  
Neural Network ◽  
Brain Activity ◽  
Classification Performance ◽  
Network Architectures ◽  
The Past ◽  
Research Fields ◽  
General Utility ◽  
Wide Range ◽  
Human Object ◽  
And Behavior

Over the past decade, deep neural network (DNN) models have received a lot of attention due to their near-human object classification performance and their excellent prediction of signals recorded from biological visual systems. To better understand the function of these networks and relate them to hypotheses about brain activity and behavior, researchers need to extract the activations to images across different DNN layers. The abundance of different DNN variants, however, can often be unwieldy, and the task of extracting DNN activations from different layers may be non-trivial and error-prone for someone without a strong computational background. Thus, researchers in the fields of cognitive science and computational neuroscience would benefit from a library or package that supports a user in the extraction task. THINGSvision is a new Python module that aims at closing this gap by providing a simple and unified tool for extracting layer activations for a wide range of pretrained and randomly-initialized neural network architectures, even for users with little to no programming experience. We demonstrate the general utility of THINGsvision by relating extracted DNN activations to a number of functional MRI and behavioral datasets using representational similarity analysis, which can be performed as an integral part of the toolbox. Together, THINGSvision enables researchers across diverse fields to extract features in a streamlined manner for their custom image dataset, thereby improving the ease of relating DNNs, brain activity, and behavior, and improving the reproducibility of findings in these research fields.

Understanding the Psycho-Social Dimensions of Schools and Classrooms

Education ◽  
2020 ◽  
Author(s):  
Nathan Berger ◽  
Jennifer Archer
Keyword(s):  
Social Context ◽  
Young People ◽  
Empirical Research ◽  
Social Activity ◽  
Social Experiences ◽  
Social Aspects ◽  
Social Dimensions ◽  
Research Perspectives ◽  
And Behavior ◽  
Ultimate Purpose

Psycho-social refers to the connections between psychological and social aspects of human experience. It describes the ways in which people’s cognition, affect, and behavior, in many ways, are a product of the society or culture in which they were raised. Schools and classrooms are sites of intense psycho-social activity because it is here that young people learn to express their thoughts and emotions via interactions with teachers and other students. The importance of these individual and collective psycho-social experiences cannot be understated. The ultimate purpose of schooling is to enable young people to live fulfilling and productive lives within their cultural and social context. Given the broad scope of the term psycho-social, some difficult decisions had to be made about the content of this article. The overriding focus is given to ways in which teachers can enhance the positive psycho-social aspects of their classrooms, with an emphasis on empirical research (or reviews of empirical research) that investigate the experiences of children and adolescents. It proved impossible to cover all potential theoretical and research perspectives. The choice of research perspectives and citations for this bibliography has been guided by salience. In some cases, citations are seminal contributions to their field. In other cases, they represent particularly impactful or interesting findings.

scholarly journals ON THE RELATIONSHIP BETWEEN GEOMATICS AND CONSERVATION: LESSONS LEARNED FROM INTEGRATED RESTORATION LABORATORIES

2019 ◽  
Vol XLII-2/W11 ◽  
pp. 981-988
Author(s):  
V. Pracchi ◽  
L. Barazzetti
Keyword(s):  
Lessons Learned ◽  
Historical Building ◽  
Practical Applications ◽  
Research Fields ◽  
Research Perspectives ◽  
Conservation Problem ◽  
Pros And Cons ◽  
Conservation Projects ◽  
The Relationship ◽  
Innovative Techniques

<p><strong>Abstract.</strong> The paper aims at investigating results, research perspectives, and limitations emerging from the synergy between geomatics and conservation. Recent didactic experiences carried out in restoration laboratories at Politecnico di Milano are illustrated and discussed. The authors tested innovative techniques for surveying with particular attention to the conservation problem. The aim was to exploit novel 360° virtual/immersive environments able to collect and manage data traditionally useful for conservation projects such as thematic maps of historical building techniques, construction technologies, deterioration pathologies, and data from diagnostics. Results are presented for two case studies completely different in terms of shape, pathologies, and reuse: the Albergo Diurno di Porta Venezia in Piazza Oberdan, and the Church of San Vittore and the Forty Martyrs (both in Milan). The work carried out with students allowed one to evaluate the pros and cons of a novel 360° immersive solution. The outcomes suggest other possible uses in related activities. The last part of the paper reconsiders the proposed “renewed” relationship between geomatics and restoration. Starting from the basic requirements of existing regulations, the paper explores the research fields and practical applications that could benefit from an intersection of geomatics and restoration.</p>

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