Search Results (238)

Graph-based narrative extraction relies on a coherence function to score transitions between events, but the coherence metrics in current use are defined operationally and lack an information-theoretic foundation. We study the composite metric $C=\sqrt{A·T}$, where A is the angular similarity of document embeddings and $T=1-d_{\mathrm{JS}}$ is the topic proximity through the Jensen–Shannon distance of soft cluster memberships, and we provide an information-geometric reading of this metric together with an axiomatic characterization of the geometric-mean combinator. On the product manifold ${\mathbb{S}}^{d-1}\times {\Delta }_{+}^{K-1}$, the negative log-coherence decomposes additively into an angular and a topic cost. Because the Riemannian metric tensor induced by the Jensen–Shannon distance on the simplex is proportional to the Fisher information matrix, the topic component is locally consistent with the Fisher–Rao metric singled out by Chentsov’s theorem. Within a parametric family of combinators (the compensability spectrum), the geometric mean is the unique combinator consistent with four natural axioms (a boundary/veto condition, symmetry, log-additivity, normalization), and the construction also motivates a proper product metric $d_{\times }$ that we use as a reference distance. Experiments on four corpora spanning news and academic domains (40 to 6000 documents), three general-purpose embedding families (GPT-4/ada-002, MPNet, MiniLM-L6) plus citation-aware SPECTER2, and three alternative topic models (LDA, soft k-means, GMM) are consistent with the framework: the Fisher identity holds with $R\ge 0.99$, the geometric mean tracks $d_{\times }$ closely ($\rho =0.999$), and a downstream LLM-as-judge consistency check shows that the geometric mean is not empirically dominated by any alternative combinator or single-channel baseline. Sweeping the compensability spectrum, the bottleneck-coherence gap between extracted storylines and random sequences splits into a symmetric component—maximized at the geometric mean on the four corpora above and a fifth, human-navigation corpus—and a displacement term; a cross-modal case study on a human-curated image narrative reproduces the same effect in a second modality. Together, these results provide an information-geometric justification for the composite coherence metric and articulate the conditions under which the geometric mean is the natural choice. Full article

Students’ reading preferences and voices are increasingly relevant for informing teaching practices and strengthening students’ motivation and engagement with reading, thus making their reading experiences meaningful. However, in Chile, there is still little evidence regarding the reading preferences and perspectives of primary school students. Therefore, this study analyzes students’ preferences and perceptions of the texts assigned by their teachers, as well as the pedagogical practices for reading mediation applied across various subjects in the La Araucanía Region of southern Chile. To this end, using a qualitative, multiple-case study design, we conducted 9 discussion groups on reading mediation and discourse genres with 96 students in grades 3–6, each connected to one of 6 outstanding teachers. Thus, we applied an inductive content analysis, constructing categories through initial coding, focused coding, and interpretive analysis, all of which underwent triple review and calibration by team members. The findings show that, in general, students value the support and scaffolding their teachers provide to facilitate reading, comprehension, and participation. However, they express a desire for greater agency in selecting texts and for more opportunities to engage in dialogue around these texts, especially in subjects other than Language Arts. These results highlight the importance of reading mediation across subjects, including student text selection and dialogic interaction, to promote motivation and sustained reading practices in primary education. Full article

The increasing computational demands of deep neural network inference drive the need for energy-efficient hardware accelerators that minimize data movement between memory and processing units. Compute-in-memory (CIM) architectures address this bottleneck by embedding computation directly within memory arrays, reducing the overhead of repeated weight transfers in conventional von Neumann systems. Conventional 6T SRAM-based digital CIM bitcells incur significant transistor overhead as arrays scale, motivating exploration of reduced-transistor bitcell alternatives. We propose a compact 4T+2T SRAM-based digital CIM bitcell implemented in 45 nm CMOS, combining a 4T SRAM storage cell with a 2T multiplier for bitwise multiply-and-accumulate (MAC) operations. The proposed design reduces transistor count from 8 to 6 compared to the 6T+2T reference, lowering parasitic capacitance and hardware overhead without compromising memory or computation functionality. Transient simulations confirm correct write, read, and CIM operations. The bitcell achieves a read delay of 26.91 ps, read power of 1.351 nW, and read energy of 0.005403 fJ—reductions of 98.7%, 86.5%, and 73.1% over the 6T+2T reference, respectively. For CIM operation, bitwise multiplication power decreases from 1.772 µW to 0.8014 µW and energy from 10.63 fJ to 4.808 fJ, representing a 54.8% reduction in both metrics, with only a marginal CIM delay increase of 3.13 ps. Monte Carlo analysis across 100 samples confirms robust write behavior under process variation, with write delay ranging from 55.02 to 69.59 ps and write energy from 0.05870 to 0.06557 fJ. Static noise margin analysis yields an SNM of 83.7 mV under nominal conditions, confirming stable data retention. These results demonstrate that the proposed 4T+2T bitcell offers strong transistor efficiency, energy savings, and computational correctness, making it a promising candidate for area-efficient digital CIM architectures targeting edge AI inference. Full article

This experimental study investigated the impact of embedding social and emotional learning (SEL) in science instruction on the academic and social–emotional outcomes of Arabic-speaking sixth graders, including those with reading difficulties (RD). Children from two schools in northern Israel (n = 101) were randomly assigned to either an intervention group, which received SEL-enriched science lessons featuring collaborative, reflective activities over 30 sessions, or a control group receiving traditional instruction. Pre- and post-tests assessed SEL competencies, motivation towards science, and academic achievements in science and mathematics. Results showed significantly greater gains in SEL skills, and in science motivation and science achievement in the intervention group compared to controls, whereas mathematics outcomes remained unchanged. Typically developing students and those with RD benefited similarly. Integration of SEL into science curricula thus enhances cognitive and social–emotional learning dimensions, particularly in linguistically and socio-economically marginalised populations. Implications for inclusive pedagogy and future research directions are discussed. Full article

Industry 4.0 and 5.0 technologies have made industrial environments data-rich, yet a persistent cognitive gap remains: operators face substantial difficulty interpreting and acting on this data in unstructured, time-critical situations. This paper presents an architecture that integrates the Asset Administration Shell (AAS), OPC UA, and a Large Language Model (LLM)-based agentic AI within a mandatory Human-in-the-Loop (HITL) framework. The AAS acts as a semantic grounding layer through Retrieval-Augmented Generation (RAG), supplying the LLM agent with ECLASS-referenced technical parameters that reduce the risk of hallucination. OPC UA Methods form a deterministic execution layer that keeps agent actions within PLC-validated safety boundaries. The HITL mechanism enforces a cryptographic approval gate so that no physical machine action can occur without documented human authorization. This requirement was motivated by an industrial survey ($n=117$), in which 47% of employees stated that human oversight is irreplaceable, combined with enterprise safety and accountability requirements and broader governance considerations for AI-driven actuation in safety-critical cyber-physical systems. Two proof-of-concept case studies evaluate the architecture under controlled laboratory conditions. Proof-of-concept results indicate system processing latencies of 1.7 s (maintenance) and ∼15 s (scheduling), with end-to-end latencies (including mandatory human approval) of 14.9 s and 62 s, respectively, representing estimated improvements of approximately 97% and 96% over expert-estimated manual baselines (∼8 min and 25–40 min). All figures derive from single scripted runs under controlled laboratory conditions and should be read as indicating architectural feasibility at Technology Readiness Level 4, not as statistically validated performance benchmarks: variability bounds and confidence intervals are unavailable, the manual baselines are expert estimates rather than instrumented measurements, and operator deliberation times derive from a single response per scenario. A structured comparison with related work shows that, to the authors’ knowledge, no published approach in the surveyed literature combines AAS semantic grounding, OPC UA deterministic execution, and mandatory cryptographic HITL within a single empirically grounded framework. Full article

This paper examines how remittances-to-GDP are conditionally associated with GDP growth upswings and downturns in four lower-middle-income countries (LMICs) in mainland Southeast Asia—Cambodia, Laos, Myanmar, and Vietnam (CLMV)—over 2000–2021, conditional on other external inflows including foreign direct investment (FDI), official development assistance (ODA), and trade openness. Employing a nonlinear Autoregressive Distributed Lag (N-ARDL) model with a Dynamic Fixed Effects (DFE) estimator, this study estimates short- and long-run regime-differentiated associations between GDP growth regimes and remittances to GDP, controlling for foreign direct investment (FDI), official development assistance (ODA), and trade openness. GDP growth is decomposed into above- and below-median regimes, allowing the model to examine whether remittance dynamics differ across growth upswings and downturns. Panel estimates are complemented with dynamic multipliers that trace conditional adjustment paths over different horizons. The results reveal a high-growth-driven regime pattern rather than formal statistical evidence of unequal high- and low-growth coefficients. In the long run, above-median growth significantly reduces remittances to GDP (${\widehat{\theta }}_1=-0.130$, very strong evidence), consistent with the household insurance motive; below-median growth has no significant long-run association (${\widehat{\theta }}_2=-0.127$, no evidence). In the short run, above-median growth is positively associated with remittances (${\widehat{\tilde{\beta }}}_1^{+}=0.033$, very strong evidence), while below-median growth again shows no significant short-run response (${\widehat{\tilde{\beta }}}_1^{-}=0.051$, no evidence). Formal Wald tests do not reject equality between the high- and low-growth coefficients in either horizon; therefore, the findings should be interpreted as a regime-differentiated significance pattern within a nonlinear specification, not as formal proof of coefficient asymmetry. Taken together, these responses are consistent with a one-sided counter-cyclical interpretation of remittances: remittances to GDP decline when domestic growth is above the median, while no significant adjustment is observed during below-median growth episodes. The pattern documented here is therefore driven by the high-growth regime and should not be read as evidence of an active counter-cyclical surge during downturns. Trade openness and ODA exhibit significant positive short-run co-movement with remittances, whereas FDI shows a strong positive long-run association with remittances to GDP. The novelty of this study lies in providing new panel evidence on regime-differentiated remittance–growth associations for CLMV within a nonlinear N-ARDL and dynamic multiplier framework, while transparently reporting that formal Wald tests do not reject equality between high- and low-growth coefficients. Policy implications center on facilitating reliable remittance channels—reducing transfer costs and expanding financial inclusion—without assuming that remittance inflows automatically rise during downturns. Full article

Speech produced in helium–oxygen (heliox) environments in deep saturation diving exhibits pronounced spectral shifts and temporal distortions, which severely degrade automatic speech recognition (ASR) systems trained on normal-air corpora. Existing studies often adopt a restoration-then-recognition paradigm by training waveform mapping networks on paired heliox/air recordings. However, in realistic low-resource data collection, paired recordings are typically obtained by independent re-reading and are therefore not strictly time-aligned, which makes regression-style restoration more sensitive to pairing errors and increases the risk of front-end distortions. This paper proposes a robust recognition framework for heliox speech, termed PRL-DAS (Physics-informed Resampling and LoRA with Duration-Adaptive Speed). The framework consists of a physics-inspired linear resampling warm start (PhysSpeed), parameter-efficient Low-Rank Adaptation (LoRA), and duration-adaptive speed (DAS) inference enhancement. Specifically, we first apply physics-motivated linear resampling as a coarse warm start, and then perform mixed-domain LoRA fine-tuning of a Whisper foundation model to absorb residual non-linear differences. On a corpus of 1048 paired Chinese heliox utterances under leave-one-speaker-out (LOSO) evaluation, using Whisper-Medium as the base model, PhysSpeed followed by mixed-domain LoRA reduces the overall character error rate (CER) from 49.33% with PhysSpeed preprocessing only to 25.79%, while also improving performance on the normal domain. Furthermore, the full PRL-DAS framework applies Soft-DAS, a lightweight smooth schedule motivated by duration-dependent variation in the optimal resampling factor, and further reduces the overall CER to 24.37% without additional training cost. Full article

The present study examined psychoemotional profiles associated with reading comprehension among third-grade Greek students with typical development, learning disabilities, and developmental language disorder. A person-centered approach was used to identify distinct profiles based on academic emotions, reading motivation, and reading comprehension performance. The sample consisted of 83 third-grade students from public elementary schools in Attica, Greece (mean age = 107.45 months). Participants were classified into three groups: typically developing students, students with learning disabilities, and students with developmental language disorder. Hierarchical cluster analysis using Ward’s method followed by k-means clustering was conducted separately for each group. Two psychoemotional profiles emerged in all three groups. In the typically developing and learning disabilities groups, the profiles differed in emotional and motivational characteristics but not in reading comprehension performance. In contrast, in the developmental language disorder group, the profiles differed significantly in reading comprehension: one profile was characterized by lower comprehension, higher negative emotions, and higher motivation, whereas the other showed higher comprehension, more positive emotions, and lower motivation. These findings highlight the heterogeneity of psychoemotional experiences associated with reading and suggest that the role of reading comprehension in profile differentiation may vary across developmental groups. The results underscore the importance of addressing both cognitive and psychoemotional aspects of reading in educational interventions, particularly for students with developmental language disorder. Full article

Fact-checking appeared as one of the responses to disinformation, establishing itself inside the journalism profession as another of its ethos. However, its social relevance relies on public perception and engagement. Despite growing evidence of approval, low familiarity and limited active use of fact-checking news remain common patterns, particularly among younger audiences. This study examines familiarity, contact, and attitudes toward fact-checking in a convenience sample of Portuguese university students, exploring associations with news consumption habits, political interest, skepticism, and ideological orientation through an online survey, with 356 university students, across different scientific areas. Results indicate that students show favorable attitudes toward fact-checking (M = 3.70) and recognize its social value but report moderate-to-low familiarity with its practices (M = 2.85), infrequent access (M = 2.37), and minimal sharing behavior (M = 1.82). Interest in reading fact-checking content emerged as the strongest predictor of positive attitudes (β = 0.506), outperforming familiarity and access frequency. Lower skepticism was associated with more favorable attitudes and showed no significant relationship with political orientation. Those more conservative displayed slightly less favorable attitudes. Our findings suggest that the primary challenge for fact-checking is not normative acceptance, but motivational engagement since favorable dispositions do not automatically translate into active consumption or sharing within everyday routines. Full article

The weak-field, quasi-static regime of gravity is commonly described by the Newton–Poisson equation as an effective response law. We construct this response within a cost-first discrete variational framework. The Recognition Composition Law (RCL) uniquely selects a reciprocal closure cost within the restricted quadratic symmetric composition class; together with the discrete ledger axioms AX1–AX5 (including conservation) and standard DEC refinement, the Newton–Poisson baseline is then recovered in the instantaneous-closure limit. Conditional on Assumption AS1 (scale-free latency) and Assumption AS2 (causal frequency–wavenumber ansatz), allowing finite equilibration introduces fractional memory into the response, yielding a scale-free modification of the source–potential relation characterized by a power-law kernel $w_{\ker }\left(k\right)=1+C{(k_0/k)}^{\alpha }$ in Fourier space. The kernel exponent $\alpha =\frac{1}{2}(1-{\phi }^{-1})\approx 0.191$, where $\phi =(1+\sqrt{5})/2$, is derived from self-similarity of the discrete ledger closure; the amplitude $C={\phi }^{-2}\approx 0.382$ is identified as a hypothesis from a three-channel factorization argument. We evaluate this quasi-static kernel-motivated response against SPARC galaxy rotation curves under a strict global-only protocol (fixed $M/L=1$, no per-galaxy tuning, conservative ${\sigma }_{\mathrm{tot}}$), using a controlled multiplicative surrogate for the full nonlocal disk operator implied by the kernel. In this deliberately over-constrained setting, the surrogate interface achieves $\mathrm{median}({\chi }^2/N)=3.06$ over 147 galaxies (2933 points), outperforming a strict global-only NFW benchmark and remaining less efficient than MOND under identical constraints. The analysis is restricted to the non-relativistic, quasi-static sector and should be read as a falsifier-oriented galactic-regime consistency check of the scaling window, not as a relativistic completion or a claim of Solar System viability without additional UV regularization/screening. Full article

This study investigated associations between a yearlong genre-based writing curriculum and students’ writing and self-efficacy outcomes. The curriculum had two stages: first, teaching genre elements without requiring use of sources and citations, and then integrating information from readings. Participants included 340 students and 3 teachers across 6th to 8th grades in a rural Title I middle school. Using a quasi-experimental, one-group pretest–posttest design with repeated measures, analysis showed significant improvements in writing quality across argumentative, compare-and-contrast, and narrative genres for all grades. Improvement patterns varied by grade and genre; self-efficacy and affect results were mixed—gains appeared in specific areas, but overall, self-efficacy decreased when reading was incorporated. Findings suggest the yearlong approach enhances writing quality but may require additional strategies to maintain student motivation. Full article

JOLs are widely used to measure metacognitive monitoring, yet their elicitation can reactively enhance memory—a phenomenon known as the positive reactivity effect. The enhanced engagement theory posits that JOLs improve memory by increasing attentional and cognitive engagement during encoding, but direct experimental evidence remains scarce. Across three experiments, we directly manipulated key components of learning engagement—attentional focus (via silent vs. aloud production), cognitive effort (via massed vs. spaced repetition), and motivational involvement (via standard vs. time-saving instructions)—while assessing their impact on the JOL reactivity effect in word recognition memory. Results consistently demonstrated robust positive reactivity effects, critically, the magnitude of these effects was significantly attenuated under high-engagement conditions (aloud reading, spaced learning, and heightened motivation). These converging findings provide the first direct, multi-method experimental support for the enhanced engagement theory, specifying that making JOLs benefit memory most when baseline engagement is low. The results delineate boundary conditions under which making JOLs yield beneficial effects and provide practical insights into leveraging JOLs to regulate engagement in real-world learning environments. Full article

This article discusses the rise of archaeology in Asia Minor and the related development of heritage tourism in Turkey. It focuses particularly on the branch termed archaeobiblical tourism. It first discusses the demographics of its clientele and then looks at publications related to biblical archaeology that have created interest in these sites. The article next discusses five areas of interest to archaeobiblical tourists: two are related to the Old Testament and three to the New Testament. Since sites related to Paul number the most in Asia Minor, special attention is given to visiting them by land and sea. A list of archaeological realia that archaeobiblical tourists encounter at various sites is presented. The article closes with an extended discussion of how archaeobiblical tourism developed and how it is currently marketed globally. It concludes that Christian visitors are motivated primarily to see the cities where biblical events took place and where the apostles ministered. Along the way they learn about archaeology and Greco-Roman history and culture, and therefore begin to integrate this new knowledge with the biblical texts they are reading. Full article

Social media has become a key venue where PhD graduates seek career information, compare experiences, and negotiate uncertainty. Drawing on information behavior and sense-making perspectives, this study examines how returnee PhDs from non-core study destinations discuss employment challenges in China’s academic labor market when credential signals are contested. Using Korean-trained PhDs as a theoretically motivated exemplary case, we collected 1149 publicly available posts from Xiaohongshu, a Chinese social media platform, and applied BERTopic to identify latent themes, followed by qualitative close reading of representative posts to interpret discourse functions. The model yielded ten topics, and semantic association analysis indicates substantial overlap among high-frequency topics, suggesting intertwined concerns rather than neatly separated issue domains. The four most prevalent topics account for 72.06% of the corpus, centering on credential recognition, job-search pathways, informal screening rules, and intersecting age- and gender-related pressures. Qualitative readings further reveal recurring discursive moves, including exposing tacit hiring heuristics, contesting stigmatizing labels (e.g., “water PhD,” a derogatory term implying low-quality credentials), and exchanging actionable strategies across regions and career tracks. Overall, the findings point to discursive convergence under evaluation uncertainty: when formal criteria are ambiguous and institutional signals are unreliable, participants turn to social media to stabilize expectations by triangulating cases and iteratively refining shared interpretations of the job market. This study contributes empirical evidence on uncertainty-driven information practices in highly educated labor markets and demonstrates the value of combining topic modeling with qualitative interpretation to capture online collective sense-making. Full article

This study examined associations between vocabulary knowledge, reading fluency, cognitive flexibility, and metacognitive monitoring accuracy in reading comprehension among fifth-grade students. Participants (N = 104) completed measures of cognitive–linguistic abilities and reading comprehension, with global metacomprehension judgments after reading and item-level confidence ratings. Metacognitive monitoring accuracy was assessed using calibration of global metacomprehension judgments and item-level confidence ratings. Calibration bias (confidence minus performance) indexed miscalibration direction, and its absolute value indexed calibration accuracy. Resolution reflected discrimination between correct and incorrect item-level responses. Structural equation modeling (SEM) was used exploratorily to examine theoretically motivated direct and indirect pathways via reading comprehension. Vocabulary knowledge showed the strongest associations with calibration accuracy and resolution, fully mediated by comprehension. Reading fluency showed a dual pattern: it contributed positively to resolution through comprehension, while also showing direct associations with lower calibration accuracy, indicating greater miscalibration and overconfident judgment tendencies among more fluent readers. Cognitive flexibility was not significantly related to any monitoring index. By jointly examining distinct indices of monitoring accuracy and separating comprehension-mediated from direct pathways, the study clarifies how cognitive–linguistic abilities may support or bias metacognitive monitoring in developing readers. Linguistic abilities, particularly vocabulary and fluency were central to students’ comprehension monitoring accuracy. Full article