Foundations Theory Research Articles

Adult Learning: A Multifaceted Endeavor

ABSTRACTThis article provides an overview of adult learning theory, focusing on the theories covered in this issue of New Directions in Adult and Continuing Education. In offering a brief synopsis of each article and reflecting on the ways adult learning theories have evolved since the first update was published in 1993, this article explains several themes that characterize that evolution: (1) the continued importance of foundational learning theories, (2) the diversity of learners and learning, and (3) the presence of technology in today's world. A combination of these themes is present in every article, which characterizes the current state of the field of adult learning theory.

Моральные интуиции: как революция в нейронауках влияет на этику, политическую философию и политические науки

New methods in neuroscience, which emerged at the turn of the 19th and 20th centuries, allowed to make a breakthrough in comprehension of the human brain functioning principles, including the situations of ethical choice. The turn to the analysis of moral intuitions was so fruitful that it led to the flourishing of moral psychology, for which moral intuitions became the main research subject. Discoveries in neuroscience and moral psychology were bound to influence the areas of knowledge, where moral dilemmas and moral intuitions have traditionally been studied, primarily ethics and political philosophy. They have also affected political science. One of the most prominent and influential in its impact on ethics and political philosophy is the concept of deep pragmatism by Joshua Greene, based on numerous empirical studies of the human brain’s response to ethical challenges. Another concept of equal and, potentially, even greater importance for these disciplines, and especially for political science, is moral foundations theory by Jonathan Haidt, which is also based on brain research and neural processes investigation. The article examines in detail Greene’s research, which led him to articulate his own normative political-philosophical concept, as well as the concept of deep pragmatism itself. It shows that even though Greene attempts to distance himself from utilitarianism, his concept is, in fact, only a new iteration of the utilitarian theory of justice, which is inferior in terms of justification to other modern versions. In the final section of the article the author explores Haidt’s moral foundations theory and its implications for philosophy and political science.

Grounding and Inference to the Best Explanation: A Novel Argument for Theism

This article presents a novel argument for the existence of God based on the metaphysical concept of grounding. Using the methodology of Inference to the Best Explanation, as conceptualised by Peter Lipton, it evaluates six foundationalist theories: Trope-Theoretic Theism, Monistic Substantivalism, Pure Stuff Theory, Mereological Bundle Theory, Extended Simples Theory, and Priority-Based Structural Realism—for their ability to explain the existence of grounding relations in reality. Through rigorous internal and external assessments focusing on coherence, simplicity, unification, and evidential virtues, the paper argues that Trope-Theoretic Theism, which conceives of God as a maximal power trope, provides the most satisfactory explanation for grounding relations. This conclusion offers a new abductive argument for Theism and demonstrates the potential for productive dialogue between metaphysics and religion.

How do speaker characteristics influence use of rhetorical history? Insights from text mining analysis of discourse about Brexit

ABSTRACT Management researchers interested in rhetorical history have hitherto paid little attention to how the personal characteristics of managers influence how individuals use the tool of rhetorical history to persuade others. We use advanced text mining tools to explore the impact of gender, education, and political ideology on how speakers use rhetorical history. We derived hypotheses from the management literature on rhetorical history and from moral foundations theory. Our dataset includes a large number of speeches delivered in the British parliament during a debate about Brexit. Our results reveal statistically significant differences in the nature of the historical arguments used by male and female opponents of Brexit. Educational background also influenced how speakers used history, with Oxford and Cambridge graduates mentioning more distant historical events than did other speakers. The findings, which can likely generalize to managerial contexts, highlight the importance of personal characteristics in understanding how leaders use rhetorical history.

Do counselor candidates have individualizing or binding moral foundations?

ABSTRACT Recent research has highlighted the application of moral foundations theory in counseling settings as it can provide a complex framework to understand the concept of morality, moral diversity, values, and decision-making processes. The emergence and development of social justice and multicultural counseling competencies has particularly raised important concerns regarding the application of values in counseling. The present study examined moral foundations as predictors of counseling students’ universality – diversity orientation. Three hundred and fifty-six counseling students at the undergraduate level participated in the research (M age = 21.86, SD = 2.26, 77.1% female). The results of a series of multiple regression analyses indicated that individualizing foundations were stronger predictors of universality – diversity orientation. Fairness was the only significant predictor of the behavioral aspect of universality – diversity orientation (diversity of contact), while fairness and care robustly predicted the cognitive aspect of universality – diversity orientation (relativistic appreciation). Care, authority, and loyalty significantly predicted the emotional aspect (comfort with differences). Overall, these results suggest that the participating counselor candidates were more likely to rely on individualizing foundations for cultural competence.

Numerical Solution of Differential Equations Using the Wavelet-Based Galerkin Method with Fibonacci Wavelets

Differential equations form the foundation of scientific theories that address numerous real-world physical challenges. Numerical methods enable the resolution of complex problems through relatively simple operations. A significant advantage of numerical methods, compared to analytical methods, is their ease of implementation on modern computers, allowing for quicker solutions. Galerkin's method belongs to a broader category of numerical techniques. Additionally, wavelet analysis represents a promising domain within applied and computational research. This paper establishes a wavelet-based Galerkin method for numerically solving differential equations, utilizing Fibonacci wavelets as trial functions. The proposed method yields results comparable to existing techniques and provides solutions that closely approximate exact answers for certain problems, thereby demonstrating its effectiveness and accuracy.

Evaluation of Upstream Oil and Gas Accident Risk Assessment Effect on Project Time Performance in Ghana

In Ghana's upstream oil and gas industry, a developing nation, this article seeks to explore the effects of accident risk assessment on project timeline performance, with management and staff roles as the moderators in Ghana’s upstream oil and gas industry. Purposive sampling was used to choose employees and supervisors who were involved in project management and risk assessment responsibilities as respondents, and quantitative data were gathered from 242 Ghanaian upstream oil and gas sector personnel in Ghana's Western Region. These volunteers have been in the industry for at least six months. The study demonstrates a positive correlation between accident risk assessment and project accident risk assessment. Amitai Etzioni's Theory of Compliance, Situational Awareness Theory, Theory of Attitude Formation, and finally, Henry Mintzberg's Management Theory serve as the foundation for the study's theories and hypotheses. In the upstream oil and gas sector, accident risk assessment has been found to have an impact on project timeline performance. This was accomplished by drawing stakeholders' attention to employee feedback and emphasizing it.

Artificial intelligence-powered image analysis: A paradigm shift in infectious disease detection

The global burden of infectious diseases significantly affects mortality rates, with their varying symptoms making it challenging to assess and determine the severity of infections. Different countries face unique challenges related to these diseases. This study introduces innovative Artificial Intelligence (AI) based methodologies to enhance diagnostic accuracy through the analysis of medical imagery. It achieves this by developing a mathematical model capable of identifying potential infectious diseases from images, utilizing a Multi-Criteria Decision-Making (MCDM) framework. This cutting-edge approach combines Hypersoft Set (HSS) within a fuzzy context, pioneering in AI-driven diagnostic processes. The decision-making process might suggest actions such as isolation, quarantine in either domestic settings or specialized facilities, or admission to a hospital for further treatment. The use of visual aids in this research not only improves understanding but also highlights the effectiveness and significance of the proposed methods. The foundational theory and the results from this novel approach demonstrate its potential for widespread application in fields like machine learning, deep learning, and pattern recognition, indicating a significant stride in the fight against infectious diseases through advanced diagnostic techniques.

Thermophilic Behavior of Heat-Dissociative Coacervate Droplets.

In exploring the genesis of life, liquid-liquid phase-separated coacervate droplets have been proposed as primitive protocells. Within the hydrothermal hypothesis, these droplets would emerge from molecule-rich hot fluids and thus be subjected to temperature gradients. Investigating their thermophoretic behavior can provide insights into protocell footprints in thermal landscapes, advancing our understanding of life's origins. Here, we report the thermophilic behavior of heat-dissociative droplets, contrary to the intuition that heat-associative condensates would prefer hotter areas. This aspect implies the preferential presence of heat-dissociative primordial condensates near hydrothermal environments, facilitating molecular incorporation and biochemical syntheses. Additionally, our investigations reveal similarities between thermophoretic and electrophoretic motions, dictated by molecular redistribution within droplets due to their fluid nature, which necessitates revising current electrophoresis frameworks for surface charge characterization. Our study elucidates how coacervate droplets navigate thermal and electric fields, reveals their thermal-landscape-dependent molecular characteristics, and bridges foundational theories of early life: the hydrothermal and condensate-as-protocell hypotheses.

Moral foundations messaging to improve vaccine attitudes: An online randomized experiment from Argentina.

The uptake of routine childhood vaccinations has declined globally since the start of the COVID-19 pandemic, due in part to increased vaccine hesitancy among parents. The Moral Foundations Theory proposes six foundations which can be targeted to increase vaccine uptake. In this study, we tested whether a post by UNICEF with a purity violation message could affect vaccine attitudes among parents in Argentina, where routine immunization coverage has been declining since 2014. Using an online randomized controlled survey experiment, we included 1,511 parents with a child under 12 years in Argentina. Outcomes were measured on the Vaccine Trust Indicator (VTI). We found that the purity violation message significantly affected vaccine attitudes: 80% of the intervention group scored high on the Vaccine Trust Indicator, compared to 73% in the control group (coefficient: 0.33, 95% Confidence Interval 0.20-0.47). Vaccine messaging framed as a purity violation is a promising way to improve vaccine attitudes among parents.

Moral foundations and political ideology in the UK

Moral foundations theory is one of the most popularised and tested lenses of recent years, with its ability to account for differences in political ideology. For the first time using a nationally representative random probability sample, we assess how the newly refined moral foundation questionnaire may explain differences in political ideology and views on political issues in the UK. We confirm a six-factor model with robust estimates for the moral intuitions of care, equality, proportionality, authority, loyalty, and purity. We then use moral intuitions to predict (a) economic left-right and socially liberal-conservative ideology and (b) the relationship between political ideology and views on salient political issues. We find moral intuitions mostly play a unifying role across a series of issues, with the exception of feelings toward patriotism and Brexit.

Moral Comments in Social Media: Analyzing the Role of Ideology-Matching Moral Framing and Impression Motivation in the Persuasive Effect of User Comments on YouTube

ABSTRACT This research explores how users form attitudes when they are presented with online videos and moral comments from their fellow audience. Based on the Heuristic-Systematic Model (HSM) and Moral Foundations Theory (MFT), the study aims to find out how different moral foundations represented in user comments interact with the motivational state, the political orientation, and the moral beliefs of the viewer. In two pre-registered experiments (N = 314 and N = 1015), the inclusion of moral arguments within comments below a YouTube video (harm vs. authority), their valence (positive vs. negative) and the participants’ motivational states (high vs. low impression motivation) were varied. While Experiment 1 revealed no significant effects regarding the persuasive effect of user comments and accompanying moral arguments, Experiment 2 showed a more general effect of comment valence on viewers’ attitude formation. These results help to specify the conditions under which user comments may lead individuals to construct their attitude in a way that fits the perceived majority opinion.

Beethovens Piano Sonata Dawn: Musical Content and Performance Analysis

The piano sonata Dawn is a significant work from the middle period of the renowned composer Beethoven, composed in 1804. Beethovens creation of numerous remarkable musical compositions has been indispensable to the development of modern music art worldwide, and as one of his renowned piano pieces, Dawn holds great value for study in terms of its musical content and performance approach. From the perspective of Beethovens compositional journey, Dawn plays a transitional role within his evolving creative thought, embodying both Classical and Romantic musical elements. This study focuses on Dawn, offering an in-depth analysis of the pieces compositional background, musical content, and performance interpretation. Through this exploration, the study aims to elucidate the artistic techniques employed in the work and reveal the profound emotional and intellectual depth Beethoven embedded within its melodies and tonal color. It is hoped that this research will enrich the foundational theories in Chinas modern music arts studies and provide guidance for performance practice in piano music.

Morality boundary work in the making of the needle and syringe exchange program in Stockholm

Background Drug policy is prone to build on rationales based on different moralities rather than evidence. Less is known about how moralities influence drug policy implementation in practice. The aim was to analyze expressions of moralities among local policy-makers, professionals, and drug users in the context of the Stockholm needle and syringe exchange program (NSP). Methods Using political documentation from Stockholm (2003–2016), focus group (12 NSP staff), and 32 drug user interviews, moralities concerning drug policy and harm reduction were analyzed based on moral foundations theory and boundary work. Results Three main moral dilemmas were identified concerning the subjects, aims, and orientation of drug policy: whether drug users are worthy of inclusion to society; if the general public should be prioritized or the health of drug users, and the orientation of practices as based on control or autonomy. Policy debate was driven by virtues such as purity and authority, whereas staff and drug users valued care, fairness and liberty. Conclusions The prohibitionist and abstinence-oriented Swedish drug policy has created social boundaries on the practice-level. Hence, users’ perspectives, and those who care about them, should be extensively involved in political discussions to foster a more moral and humane drug policy.

The Influence of Group Identification and Morality in Support for Defunding the Police

There is very little research regarding what factors drive support for defunding the police. Using the theoretical framework of the Group Engagement Model and the Moral Foundations Theory, this study explores if and how race, group identification, and morality shape support for defunding the police. Results indicated that increased superordinate identification and binding moral foundations reduced support for defunding the police among White respondents. For Black respondents, increased subordinate identification explains their increased support for defunding the police. Attachment to one’s racial group and concerns for its welfare coupled with moral intuitions driven by care and fairness toward victims of police brutality who are disproportionately Black explains why Blacks Americans began and support calls to defund the police.

Open source tool for Micro-CT aided meso-scale modeling and meshing of complex textile composite structures

Volumetric image-based modeling of textile reinforcements and composites is favored over ideal geometric modeling because of its ability to represent complex structures in sufficient detail. Although several approaches were devised, there is still a scarcity of dedicated tools capable of effectively transferring pertinent information from images to high-fidelity models. This work presents the open source project, PolyTex, a Python-based object-oriented application that establishes a streamlined and reproducible workflow for such tasks. Dual kriging serves as the foundational theory for the parametric approach developed to represent, simplify, and approximate the morphology and topology of fiber tows. The code takes two types of input, either an explicit representation of tow geometry using point clouds or implicit representations, such as image masks representing fiber tows separately with grayscale values. Tailored APIs allow for smooth integration between PolyTex’s modeling capabilities and the simulation environments offered by OpenFOAM and Abaqus. Case studies on virtual testing of textile permeability were presented to demonstrate this capability. The modular and object-oriented design makes PolyTex a highly reusable and extensible tool that allows users to create a customized pipeline.

Bridging Tridosha Siddhanta and Biorhythm Theory: Uniting Ancient Dosha Principles with Modern Cyclic Patterns

This article explores the conceptual intersections between Tridosha Siddhanta, the foundational theory of Ayurveda, and the Biorhythm Theory, a modern psychological model of cyclical biological and emotional states. Tridosha Siddhanta posits that human health and wellness are governed by the balance of three fundamental Doshas Vata, Pitta, and Kapha each representing a combination of the five elements and their dynamic influences on physiological and psychological functions. In contrast, Biorhythm Theory suggests that individuals experience predictable cycles of physical, emotional, and intellectual states influenced by inherent rhythms. By analyzing both systems, this article seeks to elucidate how the cyclical nature of biorhythms might correlate with the doshic imbalances and fluctuations described in Ayurveda. It aims to provide a comprehensive understanding of how integrating these two paradigms can enhance approaches to personalized health and wellness, offering a holistic perspective that bridges ancient wisdom with contemporary scientific insights.

Quantum Neural Networks: A New Frontier

Abstract. In recent years, there has been remarkable progress in improving the availability of resources and refining algorithms for quantum computing. Since the late 1980s, the scientific community has been fascinated by the idea of harnessing quantum phenomena to tackle computational problems. This article provides a comprehensive exploration of the foundational theories and practical applications of quantum neural networks (QNNs), highlighting their potential to transform machine learning through unique features like quantum parallelism and entanglement. It delves into various QNN architectures, such as quantum circuits and hybrid quantum-classical models, showcasing their effectiveness in handling intricate computational tasks more efficiently than traditional neural networks. Furthermore, the article examines the current challenges and future prospects in this rapidly advancing field, emphasizing the pivotal role of QNNs in driving forward research in both quantum computing and artificial intelligence. Quantum neural networks are poised to not only enhance computational capabilities but also pave the way for groundbreaking innovations in diverse technological domains.

Adiabatic Shear Localization in Metallic Materials: Review.

In advanced engineering applications, there has been an increasing demand for the service performance of materials under high-strain-rate conditions where a key phenomenon of adiabatic shear instability is inevitably involved. The presence of adiabatic shear instability is typically associated with large shear strains, high strain rates, and elevated temperatures. Significant plastic deformation that concentrates within a adiabatic shear band (ASB) often results in catastrophic failure, and it is necessary to avoid the occurrence of such a phenomenon in most areas. However, in certain areas, such as high-speed machining and self-sharpening projectile penetration, this phenomenon can be exploited. The thermal softening effect and microstructural softening effect are widely recognized as the foundational theories for the formation of ASB. Thus, elucidating various complex deformation mechanisms under thermomechanical coupling along with changes in temperatures in the shear instability process has become a focal point of research. This review highlights these two important aspects and examines the development of relevant theories and experimental results, identifying key challenges faced in this field of study. Furthermore, advancements in modern experimental characterization and computational technologies, which lead to a deeper understanding of the adiabatic shear instability phenomenon, have also been summarized.

Where are Emotions in Text?

Natural language processing (NLP) boasts a vibrant tradition of emotion studies, unified by the aim of developing systems that generate and recognize emotions in language. The computational approximation of these two capabilities, however, still faces fundamental challenges, as there is no consensus on how emotions should be processed, particularly in text: application-driven works often lose sight of foundational theories that describe how humans communicate what they feel, resulting in conflicting premises about the type of data best suited for modeling and whether this modeling should focus on textual meaning or style. My thesis fills in these theoretical gaps that hinder the creation of emotion-aware systems, demonstrating that a trans-disciplinary approach to emotions, which accounts for their extra-linguistic characteristics, has the potential to improve their computational processing. I investigate the human ability to detect emotions in written productions, and explore the linguistic dimensions that contribute to the emergence of emotions through text. In doing so, I clarify the possibilities and limits of automatic emotion classifiers and generators, also providing insights into where systems should model affective information.