Search Results (126)

Boiling crises are complex stochastic processes that are influenced by the physical phenomena of heat transfer and evaporation, as well as the shape and roughness of the boiling surface. When calculating the critical heat fluxes corresponding to the point of the first boiling crisis, it is important to know the numerical density of the formed bubbles per unit surface and volume. Most models consider only non-interacting bubbles. This greatly reduces their predictive accuracy. An analysis of the video footage of bubble boiling near the point of the first boiling crisis allows us to conclude that this is a typical picture for a continuum off-lattice problem of percolation theory. The main purpose of the work is to consider the point of the first boiling crisis as the percolation threshold for a three-dimensional problem. This threshold describes the transition from finite size inclusions (single bubbles and small groups of weakly interacting bubbles) to a percolation structure in which there is a macroscopic irregular bubble, the size of which is comparable to the size of the entire system. This hypothesis allows us to make estimates for the concentration of bubbles at the boiling point and to obtain estimates for critical heat fluxes at this point. The fundamental difference between the proposed approach and previous attempts to apply percolation theory to the description of boiling crises is the consideration of a three-dimensional problem in liquid volume, rather than a two-dimensional problem onto a hot boiling surface. It is shown, for the first time, that the proportionality constant in the Kutateladze–Zuber equation coincides with the percolation threshold for a three-dimensional continuum percolation problem on overlapping ellipsoids. Full article

In many scientific fields (e.g., statistics, data science, machine learning, and image processing), effectively quantifying the statistical difference between two probability distributions is an important task. Although a wide variety of measures have been proposed in the literature, some of them (such as the chi-square divergence and the Kullback–Leibler divergence) do not satisfy one or both of two key axioms: normalization and symmetry. This paper proposes a new index for quantifying the statistical difference between two probability distributions, called the distribution discrepancy index (DDI). The proposed DDI is based on the recently developed concepts of informity and cross-informity in informity theory. Its value ranges from 0 to 1, with values close to 1 indicating a large discrepancy and values close to 0 indicating minimal discrepancy. The DDI satisfies the two key axioms and is applicable to both discrete and continuous distributions. This paper also proposes the distribution similarity index (DSI) as a complement to the DDI. Three examples are presented to compare the DDI with three existing discrepancy measures (the Hellinger distance, total variation distance, and Jensen–Shannon divergence) and the DSI with two existing similarity measures (the Bhattacharyya coefficient and overlapping index). Full article

The rapid acceleration of artificial intelligence (AI) and, more recently, generative AI is reshaping journalism in ways that extend far beyond earlier forms of news automation. As generative AI tools become widely accessible and capable of processing unstructured data, longstanding definitions of automated journalism—once centered on structured datasets and template-based text generation—are being fundamentally reconfigured. This paper presents the most comprehensive and up-to-date systematized review of automated journalism scholarship, expanding on earlier research by synthesizing 185 peer-reviewed, English studies published between 2012 and 2024 about machine-generated textual news content published online. Through a rigorously designed search strategy across four major social science databases, this review maps how the field’s conceptual, methodological, and geographical contours have transformed as AI and generative AI become increasingly ubiquitous. The findings show a surge of research in 2024 alone, as well as the emergence of more than 150 overlapping terms used to describe AI- and algorithmically generated news, illustrating significant conceptual fragmentation. Despite no overly dominant theories, concepts or frameworks, key themes include credibility and trust, human–machine collaboration, newsroom adoption and institutional logics, transparency and disclosure, and the ethical and regulatory challenges introduced by increasingly sophisticated AI systems. By consolidating patterns, evaluating an expanded selection of key terms, and assessing theoretical and conceptual frameworks, this review demonstrates how AI and especially generative AI reflect the speed of industrial change, but also the lack of shared academic frameworks to make sense of that change. Full article

Human interaction with manipulable objects relies heavily on the ability to perceive and execute grasping actions, yet it remains unclear whether the semantics of these actions are processed without conscious awareness. While previous work has identified bottom-up influences on grasp recognition, direct evidence for subliminal semantic processing of grasping actions is limited. Grounded in embodied cognition theory—which posits overlapping neural mechanisms for action language and action execution—the present study examined whether grasp-related verbs can elicit subliminal priming effects on grasping-action recognition. Using a masked priming paradigm, participants classified objects requiring either precision or power grasps while subliminal Chinese action verbs served as primes. Behavioral measures revealed faster responses for semantically congruent cue–target pairs. ERP analyses further demonstrated congruency effects in the N400 and P600 components, reflecting semantic integration and conflict monitoring, as well as modulation of the P300 associated with action-related evaluation. Both grasp types showed evidence of unconscious semantic processing, though precision- and power-grasping actions produced distinct neural patterns. These findings provide direct experimental support for subthreshold semantic activation of grasping actions and confirm the viewpoint of action-language-embodied processing. The study advances the theoretical understanding of unconscious-action semantics and offers a framework for investigating how manipulative-action meaning is accessed below the threshold of awareness. Full article

In dialogue, laughter is a frequent non-verbal signal that can precede, follow, or overlap its antecedent—the laughable. Furthermore, the time alignment between the laughter and the laughable is dependent on who produces the laughable, whether laughter overlaps or not with speech and the communicative act performed. Laughter can interrupt either one’s own or one’s conversational partners’ utterances and, like other well-studied features of dialogue such as repair and split utterances, this interruption does not necessarily occur at phrase boundaries. Similarly, much like repair and other feedback like backchannels, laughters can be categorised as forward-looking or backward-looking. Given these parallels, we propose an analysis of how laughter can be processed and integrated using a Dynamic Syntax (DS) model, which already has well-motivated accounts of repair, split utterances, and feedback. We present a corpus study of laughter in dialogue, as well as a model using Dynamic Syntax and Theory of Types with Records (DS-TTR). Analogously to pronouns and ellipsis, our approach uses underspecification to account for laughter types that are different in processing terms as anaphoric or cataphoric, and demonstrates how laughter is processed incrementally as an utterance unfolds. Our analysis covers ≈87% of the annotated corpus data. Full article

Sensory mapping in architecture lacks a guiding theoretical model, leaving practitioners without a clear way to relate spatial design to embodied experience. This study introduces a structured methodology that links phenomenological observation with affordance theory and sensory semiotics, framing sensory data within architectural contexts. Fieldwork in fourteen courtyard houses of Damascus had residents trace their movements on simplified floor plans, switching colors as sight, sound, touch, smell and taste became dominant. The analysis reveals that visitors pass through a narrow entry corridor, enter the courtyard, and converge at the central fountain, which emerges as a focal point for multiple senses. Residents consistently trace tactile interactions along the fountain’s stone rim and at raised benches in the liwan (open space). Gustatory (taste-related, food-linked) markers appear along the route from kitchen thresholds toward the fountain, suggesting how food preparation and communal gathering overlap. Using 28 sensory maps and a three-level analytical process, comparison, synthesis, and spatial interpretation, the study produced a unified sensory map of the Damascene courtyard house. This pattern highlights how sequential spatial arrangements shape sensory engagement and suggests conservation strategies that preserve these experiential pathways. Architects and conservators can reinforce welcome gestures at thresholds and design water features and planting schemes that invite lingering. The proposed methodology fills the theoretical gap and offers clear guidelines for crafting spaces that respond to human perception. Full article

Although teacher identity and social–emotional learning (SEL) have been studied separately, little is known about how these constructs intersect in ways that explain why teachers’ social and emotional competence (SEC) does not always translate into classroom practice. This study introduces the construct of SEL identity (SEL-ID) as a potential missing piece in the current SEL frameworks by utilizing the teacher identity construct. This study seeks to describe SEL-ID, drawing on teachers’ reflections on lived experiences and their classroom practices. Using grounded theory, the data was collected through semi-structured interviews and classroom observations of 12 early childhood education teachers who were actively working with children aged from 3 to 5 in childcare centers established by a local municipality. As a result, the coding process revealed overlaps between teacher identity and SEL, as well as unique elements that go beyond the established SEL framework. Five interrelated components of SEL-ID resulted from the analysis process: (1) self-perception, (2) emotional literacy, (3) interpersonal relations, (4) participatory SEL, and (5) managerial expertise. These findings demonstrate that SEL-ID is not simply an extension of teacher identity or SEL but a construct that helps explain variations in teachers’ ability to enact SEL in practice. The researchers hope that this study will guide future studies to explore more into SEL-ID and its contribution to strengthening SEL practices in schools. Full article

The coexistence of functionally similar predators offers a framework for understanding the mechanisms shaping ecological communities. Jaguars and pumas are broadly sympatric in the Neotropics, yet the processes sustaining their persistence remain unclear. Classical niche theory predicts that coexistence requires ecological differentiation, whereas modern models emphasize balancing stabilizing (reducing interspecific competition) and equalizing mechanisms (minimizing fitness differences). Although demographic components were not directly estimated, we integrated secondary dietary data compiled from 21 sympatric populations through a systematic literature review. This integration allowed us to identify trophic patterns consistent with coexistence mechanisms across taxonomic and functional prey axes. Analyses revealed strong taxonomic segregation at finer scales, with jaguars primarily consuming Artiodactyla, while pumas exploited a broader spectrum including Rodentia, Cingulata, and Pilosa. This divergence reduces direct competition, consistent with stabilizing resource partitioning. In contrast, high overlap in functional traits (e.g., body mass and locomotor habit) indicated functional convergence potentially increasing fitness equivalence, consistent with equalizing mechanisms. These dynamics suggested that jaguar–puma macroecological coexistence may be maintained by a dynamic balance between patterns consistent with stabilizing and equalizing mechanisms expressed within trophic niche axes. From a conservation perspective, strategies should move beyond species-specific approaches; preserving both taxonomic and functional prey diversity is essential to sustain the trophic requirements of predators and the ecosystems they regulate. Full article

Rehabilitation after anterior cruciate ligament reconstruction cannot be reduced to a linear, time-based sequence of protection, strength, and return to sport. Persistent asymmetries, quadriceps inhibition, and variable re-injury rates highlight that recovery is a complex adaptive process in which outcomes emerge from dynamic interactions between biological, neural, and psychological subsystems. Grounded in complexity science and chaos theory, this editorial reframes rehabilitation as the regulation of variability rather than its suppression. The Control–Chaos Continuum provides a practical structure to translate this concept into progressive exposure, where clinicians dose uncertainty as a therapeutic stimulus. Adaptive periodization replaces rigid stages with overlapping macro-blocks that respond to readiness, feedback, and context. Neuroplastic mechanisms and ecological dynamics justify the deliberate introduction of controlled “noise” to foster coordination, confidence, and resilience. Ultimately, the goal is not perfect control but stable performance under variability—the ability to function “at the edge of chaos.” This conceptual perspective articulates a clinically actionable framework—linking the Control–Chaos Continuum with adaptive periodization—to guide non-linear decision-making and safe return-to-sport. Full article

Product launch events serve as a crucial means of marketing and communication for technology brands. With the empowerment of multimodal technologies, the construction of meaning and the pathways of persuasion in these events have been reshaped. Drawing on grounded theory, this study systematically reviews and analyzes 258 smart product launch events organized by 20 leading technology brands. The findings reveal that product launch events consist of two major categories of content—namely, core information and peripheral information—which together form a reinforced persuasion mechanism, resonating with the additivity effects proposed in the Heuristic Systematic Model (HSM). Furthermore, the abundant multimodal cues embedded in these events contribute to the reinforcement mechanism through overlapping complementarity and dynamic supplementation. Finally, this study discusses the theoretical significance of the multimodality-assisted reinforced persuasion mechanism in relation to dual-process models and its appropriateness in contemporary communication contexts. By providing an in-depth investigation of smart product launch events as a novel form of content dissemination, the study conceptualizes a persuasion mechanism suitable for complex communication environments and offers practical guidance for industry marketing practice. Full article

This study aims to address the problem that traditional helical gears generate significant axial forces during transmission and innovatively proposes a design scheme of double helical face gears (DHFG). An accurate mathematical model of the tooth surface is established using spatial meshing theory and coordinate transformation. A systematic investigation using the orthogonal test method is then conducted to analyze the influence of key parameters, such as the pinion tooth number, transmission ratio, and helix angle, on gear performance. The finite element analysis results show that the overlap degree of this double helical tooth surface gear pair in actual transmission can reach 2–3, demonstrating excellent transmission smoothness. More importantly, its unique symmetrical tooth surface structure successfully achieves the self-balancing effect of axial force. Simulation verification shows that the axial force is reduced by approximately 70% compared to traditional helical tooth surface gears, significantly reducing the load on the bearing. Finally, the prototype gear is successfully trial-produced through a five-axis machining center. Experimental tests confirmed that the contact impressions are highly consistent with the simulation results, verifying the feasibility of the design theory and manufacturing process. Full article

We present a tunable diode-laser absorption spectroscopy (TDLAS) system operating at 1.5711 µm for CO₂ gas concentration measurements. The system can operate in either a traditional direct-mode (dTDLAS) sawtooth wavelength scan or a recently demonstrated wavelength-toggled single laser differential-absorption lidar (WTSL-DIAL) mode using precompensated current pulses. The use of such precompensated pulses offsets the slow thermal constants of the diode laser, leading to fast toggling between ON and OFF-resonance wavelengths. A short measurement time is indeed pivotal for atmospheric sensing, where ambient factors, such as turbulence or mechanical vibrations, would otherwise deteriorate sensitivity, precision and accuracy. Having a system able to operate in both modes allows us to benchmark the novel experimental procedure against the well-established dTDLAS method. The theory behind the new WTSL-DIAL method is also expanded to include the periodicity of the current modulation, fundamental for the calculation of the OFF-resonance wavelength. A two-detector scheme is chosen to suppress the influence of laser intensity fluctuations in time (1/f noise), and its performance is eventually benchmarked against a one-detector approach. The main difference between dTDLAS and WTSL-DIAL, in terms of signal processing, lies in the fact that while the former requires time-consuming data processing, which limits the maximum update rate of the instrument, the latter allows for computationally simpler and faster concentration readings. To compare other performance metrics, the update rate was kept at 2 kHz for both methods. To analyze the dTDLAS data, a four-parameter Lorentzian fit was performed, where the fitting function comprised the six main neighboring absorption lines centered around 1.5711 µm. Similarly, the spectral overlap between the same lines was considered when analyzing the WTSL-DIAL data in real time. Our investigation shows that, for the studied time intervals, the WTSL-DIAL approach is 3.65 ± 0.04 times more precise; however, the dTDLAS-derived CO₂ concentration measurements are less subject to systematic errors, in particular pressure-induced ones. The experimental results are accompanied by a thorough explanation and discussion of the models used, as well as their advantages and limitations. Full article

Problem: Amid digital disruption and the cross-fertilization of RBV, DCV, and KBV, strategic management knowledge has grown fragmented with blurred boundaries. Conventional mapping (citation/co-word, LDA) lacks semantic and temporal resolution, obscuring overlaps, divergences, and turning points and hindering links to actionable indicators (e.g., the Balanced Scorecard). Hence, an integrated, semantically faithful, time-stamped map is needed to bridge research and operational metrics. Gap: Prior maps rely on citation/co-word signals, miss textual meaning, and treat RBV/DCV/KBV in isolation—lacking a theory-aligned, time-stamped, manager-oriented synthesis. Objectives: This study aims to (1) reveal how RBV, DCV, and KBV evolve and interrelate over time; (2) produce an integrated, semantically grounded map; and (3) translate selected themes into actionable managerial indicators. Method: We analyzed 25,907 WoS articles (1980–2025) with BERTopic (Sentence-BERT + UMAP + HDBSCAN + c-TF-IDF). We used an RBV/DCV/KBV lexicon to guide retrieval/interpretation (not to constrain modeling). We discovered 230 topics, retained 33 via coherence (C_V), and benchmarked them against LDA. Key findings: A concise set of 33 high-quality themes with a higher C_V than LDA on this corpus was established. A Fish-Scale view (overlapping subfields across economics, management, sociology) that clarifies RBV–DCV–KBV intersections was achieved. Era-sliced prevalence shows how themes emerge and recombine over 1980–2025. Selected themes mapped to Balanced Scorecard (BSC) indicators linking capabilities → processes → customer outcomes → financial results. Contribution: A clear, time-aware synthesis of RBV–DCV–KBV and a scalable, reproducible pipeline for structuring fragmented theory landscapes are presented in this study—bridging scholarly integration with managerial application via BSC mapping. Full article

This contribution provides new data on Italian first language acquisition and phonological development in preschool children. In total, 104 3- to 6;4-year-old typically developing Italian children were tested with two novel nonword tasks tackling the Italian consonantal system: one for repetition (NWR) and one for discrimination (NWD). NWR data were analyzed in terms of repetition accuracy, featural characteristics, and phonological processes, while NWD was analyzed according to signal detection theory (i.e., A-prime and d-prime) and in terms of discrimination accuracy. The results show the significant role of age on children’s repetition and discrimination abilities: as the children grow older, all the scores improve and the number of errors declines. No complete overlap is found between what children can produce and what they can discriminate, which is in line with what has already been documented in other languages. The findings contribute to the state of the art on the Italian language and provide new perspectives on some methodological issues specific to this language. Full article

This paper introduces a novel generalized q-symmetric differential operator for studying a certain subclass of univalent functions with negative coefficients. We establish several significant theoretical results for this class, including sharp coefficient bounds and characterization theorems based on the generalized Hadamard product. Two significant applications demonstrate the theoretical framework’s practical utility. First, in the context of geometric modeling, we demonstrate how the function class and operator can be utilized to create and control complex, non-overlapping transformations. Second, in digital signal processing, we show that these functions serve as stable digital filter prototypes and that our operator is an effective tool for fine-tuning the filter’s frequency response. These applications bridge the gap between abstract geometric function theory and practical system design by demonstrating the operator’s versatility as a tool for analysis and synthesis. Full article