Comprehensive Theory Research Articles

The power of people in family firms

ABSTRACT Family business scholars have long sought a comprehensive theory on the family firm. A nascent but still-developing aspect of this theory involves understanding the unique challenges of the people who constitute these firms. Our introduction to the Theories of Family Enterprise special collection discusses the literature on human capital and related issues in family firms and then reviews, integrates, and extends the contributions of the five articles in this special collection. These five papers contribute to a better understanding of the indelible social dynamics that are associated with managing family firms and the uniqueness of the people who inhabit them. By bringing a clearer focus on the people who constitute family businesses, these articles collectively contribute to a more comprehensive theory of the family firm and offer several directions for future research.

Theory of mind and text comprehension across the lifespan: A meta-analysis.

Researchers argue that theory of mind (ToM) abilities are needed for text (listening or reading) comprehension. Although many studies have supported this claim, findings are mixed and researchers have disagreed on how fundamental this relation is-for example, whether ToM and text comprehension are related merely because of shared variance with verbal and executive function skills. To address these issues more definitively, we conducted a meta-analysis examining ToM and text comprehension, which included 47 independent samples with 5,123 participants ranging in age from 3 to 70 years of age (M = 10.53 years). We found a statistically significant association (r = .33) between ToM and text comprehension across 157 effect sizes. This relation did not differ based on whether data were cross-sectional or longitudinal, the age of participants, or most characteristics of the ToM or comprehension tasks (e.g., the degree to which they were narrative or inferential). However, the effect size was stronger in some languages and for listening comprehension rather than reading comprehension tasks. In longitudinal designs, the effect size did not differ depending on whether ToM was assessed before text comprehension or the reverse. Finally, we conducted meta-analyses controlling for verbal and/or executive function abilities and found that the relation between ToM and text comprehension was significant when controlling for each as well as both abilities (r = .22-.32). The current findings provide the strongest evidence to date that there is a fundamental relation between ToM and text comprehension. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Goos-Hänchen shift for an Airyprime beam.

We propose a comprehensive theory to analyze the Goos-Hänchen (GH) shift for an arbitrarily polarized Airyprime beam reflected at the air-dielectric interface. We derive general expressions for the spatial and angular GH shifts and establish a close relationship between the GH shift of the Airyprime beam and the GH shift of the Airy beam. We also predict the novel optical effects of a significantly enhanced spatial GH shift and an almost disappeared angular GH shift when the horizontally polarized Airyprime beam is reflected near Brewster's angle.

The operationalization of bilingual linguistic experience and its relationship with executive function

Research of the relation between linguistic experiences and the executive function have been a hot topic in the field of psycholinguistics for over two decades. Considerable body of studies have provided both supporting and challenging evidence for the existence of such relation. The final answer about the relation between the linguistic experiences and the executive function has not been obtained yet, due to reconsiderations of the established methodological approaches and new theories still being developed, which challenge the validity of earlier findings. This article is an attempt to summarize and explain current trends in this line of studies, specifically focusing on the issue of operationalization of linguistic experiences. Bilingualism and multilingualism are complex constructs, composed of multiple elements that can have unique, independent effects on cognition, including language proficiency, manner and duration of language acquisition, current tendencies of language use. Earlier studies had a tendency to focus on a single element of language experience for categorical distinction between monolinguals and bilinguals, converging the great variability in the latter under a single category. Each element of linguistic experience has to be accounted for and carefully operationalized in a way that would allow reasonable comparison between different research on the topic. In addition to exploring the effects of various elements of linguistic experiences on cognitive control, interactions between those experiences also demand attention, which have been largely overlooked. Finally, each study has to be backed up by a solid theoretical background, which was argued to be a problem for the research of the relation between the linguistic experiences and the executive function, but has great potential for resolving the inconsistencies in research findings. Not all experiences with languages require effortful cognitive processing and adaptations, and even if some might, a comprehensive theory is required to explain how cognitive adaptations for language use can be generalized for other domains of cognition.

The teacher’s role in teaching reading comprehension skills to Grade 9 English Home Language learners

Background: The high number of poor-performing learners in reading comprehension in South African schools is a concerning factor that calls for studies to mitigate this problem. The Progress in International Reading Literacy Study (PIRLS) of 2021 indicates that about 81% of South African Grade 4 learners who participated, failed to reach the required benchmark in the test. Research indicates that teachers are not conversant with theory and explicit teaching of reading comprehension strategies.Objectives: This study aimed to investigate the role played by teachers in developing Grade 9 learners’ reading comprehension skills in English Home Language and establishing which reading comprehension skills and strategies are taught to learners.Method: This study used a qualitative approach. Four data sets were utilised to collect data including a document analysis, a questionnaire for learners, interviews with teachers of English and lesson observations.Results: The findings of the study show that there is little guidance on how to teach reading comprehension skills. It also emerged that instead of teaching reading comprehension skills, teachers merely ‘test’ learners’ answering skills.Conclusion: This study suggests that there is a need for re-training and assisting teachers in explicitly teaching reading comprehension skills to learners. Learners may benefit from the enhanced expertise of teachers and become more proficient in reading comprehension.Contribution: The study has provided invaluable insights into the current teaching practice of comprehension skills with actionable insights for teachers, teacher educators, and policymakers to support learners’ academic success and bridge the gap between praxis and theory.

LiF-enriched interphase promotes Li+ desolvation and transportation enabling high-performance carbon anode under wide-range temperature

Li-ion batteries (LIBs) have made inroads into the electric vehicle area with high energy densities, but they still suffer from slow kinetics of Li+ limited by the graphite anode especially at high current density and low-temperature conditions. Sluggish de-solvation of Li+ at the electrode surface and slow Li+ transfer in solid electrolyte interphase (SEI) are main determining factors that restrict the fast-charging and low-temperature performance of graphite-based LIBs. Here, we construct the sodium lignosulfonate layer with abundant polar functional groups on the lithium-montmorillonite surface, which can make it simple for electrons transfer to promote in-situ formation of LiF-based SEI with high ionic conductivity. The thin and robust LiF-based SEI promotes the de-solvation of Li salts and Li+ transfer as proved by the comprehensive electrochemical studies and density functional theory (DFT) calculations. Consequently, a combination of excellent stability and fast-charging ability for LIBs at room and low temperatures is achieved. The designed anode shows the remarkable capacity of 1500 mAh/g at 0.1 A/g, which was 3–4 times better than the commercial graphite. At the high current density of 5 A/g, it can still keep stable with the capacity retention of 70 % after 7000 cycles. Besides, an impressive 70 % of their room-temperature capacity is attained at −10 °C and 150 mAh/g is achieved under the extremely low temperature of −40 °C. This study establishes the effective strategy to construct the LiF-rich interface on the surface of anode to improve the Li+ kinetics and stability of the battery.

Synergistic role of dual-metal sites (Ag–Ni) in hexagonal porous g-C3N4 nanostructures for enhanced photocatalytic CO2 reduction

Harnessing solar energy to convert CO2 into hydrocarbon fuels presents a viable strategy for mitigating CO2 emissions. For effective photocatalytic CO2 reduction (PCR), it is crucial to optimize both photoinduced and chemical reactions synergistically. In this research, hexagonal porous g-C₃N₄ (CN) nanostructures with Ag–Ni dual metal site loadings were synthesized using a hydrothermal method followed by calcination, significantly enhancing PCR efficiency. The optimal results demonstrated significant production rates of 77.65 μmol/g for CO and 17.89 μmol/g for CH4, showcasing exceptional photocatalytic performance. This enhanced performance is attributed to several factors: the high porosity of the g-C₃N₄, the synergistic effects at the Ag–Ni dual metal sites, and the increased surface area. Detailed experimental measurements, coupled with comprehensive density functional theory (DFT) calculations, have elucidated the mechanisms underlying the significant improvements in the photocatalytic activity of the developed catalyst. This study not only demonstrates an effective approach for converting CO₂ into valuable hydrocarbon fuels but also significantly advances our understanding of complex photocatalytic systems, providing insights that could guide future developments in this field.

Self-Healable Hydrogels from Vegetable Oil: Preparation, Mechanism, and Applications.

Hydrogels are indispensable for a variety of applications. Conventional biomaterial-based hydrogels, typically made from proteins or polysaccharides, often suffer from high costs, poor mechanical properties, and limited chemical functionality for modification. In this work, we present a novel hydrogel developed from modified castor oil, which is a renewable and cost-effective resource. Castor oil-based oligomer (CG) was synthesized using glycidyl methacrylate and triethylamine via ring-opening polymerization. The oligomer formed a gel only with Cu2+ ions among the various systematically studied metal ions. Comprehensive density functional theory calculations, atoms in molecules analysis, and steady and dynamic shear rheology were conducted to investigate the metal-binding sites and metal-oligomer interactions as well as the self-healing and viscoelastic properties of the oil-based hydrogels. The hydrogel exhibited 94% self-healing efficiency and performed as a recyclable rhodamine B dye adsorbent (73-90%). This innovative approach offers a novel, cost-effective, and sustainable alternative to traditional hydrogels, paving the way for advanced applications.

A Thematic Study of Nyaya Philosophy with Research Methodology

This thematic study explores the intricate components of Nyaya philosophy and its methodological implications for educational research. This review examines the conceptual distinctions in ontological and epistemological perspectives currently employed within the theoretical framework of educational research. Nyaya philosophy, rooted in the universal truths of Hindu philosophy, serves as a foundation for developing research methodologies. Its sixteen divisions of Padarthas support four primary modes of knowledge acquisition: perception, inference, comparison, and testimony. Nyaya subtly steers researchers towards theoretical generalization in research design, emphasizing the importance of incorporating inductive and deductive procedures in the theoretical processes of educational research. Nyāya philosophy enhances research rigor through its ontological and epistemological principles. By using Nyāya’s categories of existence, substance, quality, and action—research questions are clearly defined. Nyāya’s logical rigor in data analysis ensures valid, consistent conclusions, aiding critical evaluation. Theory building is strengthened by its causation principles and categories, leading to comprehensive theories. Nyāya’s principles also improve the critical evaluation of literature, helping researchers assess and build upon existing knowledge systematically, achieving greater clarity and validity in their studies.

Domain embeddings for generating complex descriptions of concepts in Italian language.

In this work, we propose a Distributional Semantic resource enriched with linguistic and lexical information extracted from electronic dictionaries. This resource is designed to bridge the gap between the continuous semantic values represented by distributional vectors and the discrete descriptions provided by general semantics theory. Recently, many researchers have focused on the connection between embeddings and a comprehensive theory of semantics and meaning. This often involves translating the representation of word meanings in Distributional Models into a set of discrete, manually constructed properties, such as semantic primitives or features, using neural decoding techniques. Our approach introduces an alternative strategy based on linguistic data. We have developed a collection of domain-specific co-occurrence matrices derived from two sources: a list of Italian nouns classified into four semantic traits and 20 concrete noun sub-categories and Italian verbs classified by their semantic classes. In these matrices, the co-occurrence values for each word are calculated exclusively with a defined set of words relevant to a particular lexical domain. The resource includes 21 domain-specific matrices, one comprehensive matrix, and a Graphical User Interface. Our model facilitates the generation of reasoned semantic descriptions of concepts by selecting matrices directly associated with concrete conceptual knowledge, such as a matrix based on location nouns and the concept of animal habitats. We assessed the utility of the resource through two experiments, achieving promising outcomes in both the automatic classification of animal nouns and the extraction of animal features.

Tiny Pointers

This paper introduces a new data-structural object that we call the tiny pointer. In many applications, traditional \(\log n\) -bit pointers can be replaced with \(o(\log n)\) -bit tiny pointers at the cost of only a constant-factor time overhead and a small probability of failure. We develop a comprehensive theory of tiny pointers, and give optimal constructions for both fixed-size tiny pointers (i.e., settings in which all of the tiny pointers must be the same size) and variable-size tiny pointers (i.e., settings in which the average tiny-pointer size must be small, but some tiny pointers can be larger). If a tiny pointer references an item in an array filled to load factor \(1-\delta\) , then the optimal tiny-pointer size is \(\Theta(\log\log\log n+\log\delta^{-1})\) bits in the fixed-size case, and \(\Theta(\log\delta^{-1})\) expected bits in the variable-size case. Our tiny-pointer constructions also require us to revisit several classic problems having to do with balls and bins; these results may be of independent interest. Using tiny pointers, we apply tiny pointers to five classic data-structure problems. We show that: A data structure storing \(n\) \(v\) -bit values for \(n\) keys with constant-factor time modifications/queries can be implemented to take space \(nv+O(n\log^{(r)}n)\) bits, for any constant \(r\gt0\) , as long as the user stores a tiny pointer of expected size \(O(1)\) with each key—here, \(\log^{(r)}n\) is the \(r\) -th iterated logarithm. Any binary search tree can be made succinct, meaning that it achieves \((1+o(1))\) times the optimal space, with constant-factor time overhead, and can even be made to be within \(O(n)\) bits of optimal if we allow for \(O(\log^{*}n)\) -time modifications—this holds even for rotation-based trees such as the splay tree and the red-black tree. Any fixed-capacity key-value dictionary can be made stable (i.e., items do not move once inserted) with constant-factor time overhead and \((1+o(1))\) -factor space overhead. Any key-value dictionary that requires uniform-size values can be made to support arbitrary-size values with constant-factor time overhead and with an additional space consumption of \(\log^{(r)}n+O(\log j)\) bits per \(j\) -bit value for an arbitrary constant \(r\gt0\) of our choice. Given an external-memory array \(A\) of size \((1+\varepsilon)n\) containing a dynamic set of up to \(n\) key-value pairs, it is possible to maintain an internal-memory stash of size \(O(n\log\varepsilon^{-1})\) bits so that the location of any key-value pair in \(A\) can be computed in constant time (and with no IOs). In each case tiny pointers allow for us to take a natural space-inefficient solution that uses pointers and make it space-efficient for free.

The Holistic Intelligent Healthcare Theory (HIHT): Integrating AI for Ethical, Transparent, and Human-Centered Healthcare Innovation

The rise of artificial intelligence (AI) in healthcare has the potential to significantly increase the efficiency, personalization, and overall efficacy of medical care delivery. However, its integration needs to be improved regarding ethical norms, data quality, openness, and human-centered care. This study proposes the Holistic Intelligent Healthcare Theory (HIHT), a comprehensive theory for guiding AI's ethical and practical use in healthcare. It draws on insights from theories such as the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), Socio-Technical Systems Theory (STS), Ethics of Care, Data Governance and Information Quality Theory, and Augmented Intelligence Theory. The HIHT highlights the importance of centralized governance, strong data quality, transparent AI methods, human-AI collaboration, and a reimagined role for healthcare practitioners—the "Intelligent Doctor." The study presents the theory's structures and investigates their implications for AI integration in healthcare, offering a road map for responsible and practical AI applications.

Identification of optically active vibrational modes of columbite AB2O6 using the correlation method

In the modern era, the examination of molecular structure heavily relies on the application of infrared and Raman spectra within crystalline structures. These methodologies are essential in understanding the arrangement of atoms within molecules and the internal forces governing them. An essential aspect of this analysis involves identifying vibrational modes that can be detected optically. The correlation method is employed to establish rules for selecting these vibrational modes, both in crystals and molecules, through a systematic calculation process that aids in predicting their activity in Infrared (IR) and Raman spectra. The correlation method utilizes group theory to determine which vibrational modes are spectroscopically active in crystals. In our research, our aim is to employ this method to identify the irreducible representations and determine the IR and Raman active vibrational modes of orthorhombic AB2O6 compounds within the Pbcn space group. By conducting comprehensive group theory calculations, our objective is to elucidate the spectroscopic properties using the correlation method.

Consumer Behavior in the Digital Marketplace: A Fuzzy Evaluation Approach

With the growing prevalence of the internet and the development of logistics, consumers face increasingly complex choices when shopping online. Therefore, this article introduces fuzzy comprehensive evaluation to address these shopping issues. In analyzing consumers' purchase decision-making problems for online shopping, it is essential to subjectively evaluate products, such as price, quality, and reputation. By constructing fuzzy relationships and assigning weights, this method effectively handles the ambiguity and uncertainty of evaluation information, reflecting consumers' subjective preferences in actual shopping decisions. This study concludes that quality is the dominant factor among numerous commodity factors,and it also established a shopping decision model, which aids consumers in making the best decisions during their shopping, thereby enhancing shopping efficiency and satisfaction. The results indicate that compared to traditional methods, this method can more accurately focus on consumer purchase intention and improve the understanding of shopping decisions. The paper summarizes the fuzzy comprehensive evaluation of its application value in shopping problems, pointing out that it can better simulate human fuzzy decision-making processes and provide a more practical shopping decision assistance tool. This study not only enriches the application of fuzzy comprehensive evaluation theory in consumer behavior research, but also provides consumers with a scientific and practical shopping decision support method.

Influence of Surfaces on Ion Transport and Stability in Antiperovskite Solid Electrolytes at the Atomic Scale.

Antiperovskites are generating considerable interest as potential solid electrolyte materials for solid-state batteries because of their promising ionic conductivity, wide electrochemical windows, stability, chemical diversity and tunability, and low cost. Despite this, there is a surprising lack of a systematic study of antiperovskite surfaces and their influence on the performance of these materials in energy storage applications. This is rectified here by providing a comprehensive density functional theory investigation of the surfaces of M3OX (M = Li or Na; X = Cl or Br) antiperovskites. Specifically, we focus on the stability, electronic structure, defect chemistry, and ion transport properties of stable antiperovskite surfaces and how these contribute to the overall performance and suitability of these materials as solid electrolytes. The findings presented here provide critical insights for the design of antiperovskite surfaces that are both stable and promote ion transport in solid-state batteries.

RE(HSeO3)(SeO3)(H2O)·(H2O) (RE = Y, Gd): Two Rare-Earth Selenite Nonlinear Optical Crystals with Wide Band Gaps.

The band gap is one of the significant parameters for nonlinear optical (NLO) materials, which is the key factor in their application band in laser technology. This study reports the synthesis of two rare-earth selenite NLO crystals, namely, RE(HSeO3)(SeO3)(H2O)·(H2O) (RE = Y, Gd), utilizing the hydrothermal technique. The two compounds are isostructural, and both belong to the orthorhombic chiral space group of P212121 and possess three-dimensional structures consisting of two-dimensional rare-earth selenite layers connected by hydrogen bonds (O-H··O). These two compounds exhibit a moderate second harmonic generation intensity of 0.5/0.8 × KDP and wide energy band gaps reaching 4.8 eV. Comprehensive density functional theory analyses based on first-principles were carried out to unravel the relationship between the structural and corresponding properties. This work provides an approach for band gap enlargement in rare-earth selenite systems and is beneficial to the design of future NLO materials.

Feasibility Theory and Practice of CO2-EOR in High CO2-Content Near-saturated Edge-bottom Water Reservoir

Abstract CO2-EOR technology for low-permeability tight oil and gas reservoir is in the ascendant, and CO2-EOR technology for old oilfields has not been paid enough attention, but the implementation scale has great potential, and the expected effect and implementation conditions are good. The feasibility of CO2-EOR technology in the ultra-high water cut stage of high CO2 content, near saturation pressure and edge-bottom water reservoir was studied theoretically, and the field implementation effect was tracked and evaluated. Via petrophysics, reservoir engineering, and site case analysis, a relatively comprehensive reservoir numerical model was developed, clarifying the impact of periodic gas injection volume, gas injection rate, soak time and liquid production rate on the production effect of CO2 huff and puff were clarified. The key injection-production parameters of CO2 huff and puff test wells were designed, and the feasibility study progress of CO2-EOR in near-saturated edge-bottom water reservoirs with high CO2 content was summarized. The theoretical research shows that the change rules of gas-water dual-drive, CO2 water control and oil increase in the process of CO2 huff and puff in high CO2 near-saturated edge and bottom water reservoirs, and reveals the synergistic mechanism of CO2 huff and puff to suppress water and increase energy. The tracking evaluation shows that the sweep condition of CO2 after huff and puff in the test well is complex, the storage ratio is in the range of 40%-70%, the stage oil increase is in the range of 700t-3000t, and the optimized oil increase and oil change rate can reach 2.7t/t. Based on the comprehensive theory and practice, it is considered that CO2-EOR has good potential for high CO2 near-saturated edge and bottom water reservoirs under fine control. This study has guiding and reference significance for CO2-EOR technology and application in similar oilfields at home and abroad.

Habitualness, reward and external constraints: Exploring the underlying influences of daily water intake using the Situated Assessment Method2.

Understanding what facilitates and hinders water drinking is crucial to inform interventions for preventing underhydration. Using the Situated Assessment Method2, we extended previous research by examining what influences water drinking in daily life. We studied 213 UK adults, assessing 13 potential predictors (e.g. thirst, availability of other drinks) of their typical water intake across 10 everyday situations (e.g. during work, dinner). Participants then reported their actual water intake in these situations over three alternating days during a 1-week follow-up. We evaluated the variability of water intake and its influences across individuals and situations and the prospective relationship between these influences and water intake. The 13 identified predictors explained substantial proportions of variation in water intake. Factors like habitualness (e.g. subjective effort), self-relevance (e.g. health consciousness) and immediate feedback (e.g. taste) were positively associated with water intake. However, the influence of these factors varied significantly across individuals and situations. Our results suggest that various interrelated predictors facilitate and hinder water drinking behaviour, emphasising the importance of using comprehensive behaviour theories to inform research in this domain. They also align with growing evidence that reward may regulate habitual behaviour.

Exploring the thermal and optical characteristics of Ti3C2 MXene for enhanced photothermal conversion

Ti3C2 MXene, a member of the two-dimensional (2D) transition metal carbides family, has garnered significant attention for its exceptional photothermal properties. To understand the mechanistic underpinnings of this feature, we conducted a comprehensive first-principles density functional theory analysis. This study was aimed at investigating the electronic band structure and vibrational characteristics of Ti3C2 MXene to unravel its microscopic process of photothermal conversion. After obtaining its optical and thermal properties, the process by which the material moves from light absorption to heat release is elucidated. The presence of localized surface plasmon resonance (LSPR) effects in Ti3C2 is proved by Finite-difference time-domain (FDTD) simulations. The synergy between the high thermal conductivity network in the Ti layers and the LSPR phenomenon is believed to be responsible for the superior photothermal conversion capabilities. This investigation enhances the understanding of the intrinsic properties of Ti3C2 MXene, confirming its status as an ultrahigh photothermal conversion material.

Single-neuron representation of nonsymbolic and symbolic number zero in the human medial temporal lobe

The number zero holds a special status among numbers, indispensable for developing a comprehensive number theory.1,2,3,4 Despite its importance in mathematics, the neuronal foundation of zero in the human brain is unknown. We conducted single-neuron recordings in neurosurgical patients5,6,7 while they made judgments involving nonsymbolic number representations (dot numerosity), including the empty set, and symbolic numbers (Arabic numerals), including numeral zero. Neurons showed responsiveness to either the empty set or numeral zero, but not both. Neuronal activity to zero in both nonsymbolic and symbolic formats exhibited a numerical distance effect, indicating that zero representations are integrated together with countable numerosities and positive integers at the low end of the number line.8,9 A boundary in neuronal coding existed between the nonsymbolic empty set and small numerosities, correlating with the relative difficulty in discriminating numerosity zero behaviorally. Conversely, no such boundary was found for symbolic zero activity, suggesting that symbolic representations integrate zero with other numerals along the number line, reconciling its outlier role. The status of zero as a special nonsymbolic numerical quantity is reflected in the activity of neurons in the human brain, which seems to serve as a scaffold for more advanced representations of zero as a symbolic number.