Search Results (559)

In the history of Buddhist literature, there have been two texts sharing the title Jātakastava (Birth Stories Hymn), one in Khotanese and the other in Sanskrit and Tibetan. These two texts exhibit similarities in genre, framework structure, thematic selection, and narrative logic, while diverging in the arrangement of specific materials, textual length, authorship, dissemination regions, and translation approaches. This study examines the Sanskrit–Tibetan bilingual Jātakastava—a text that has received limited scholarly attention—and undertakes a comparative analysis with the Khotanese Jātakastava to reassess the relationship between these two texts bearing the same title, as well as their associated authors and translators. Through the inclusion of stories such as the Elephant King Leaping off a Cliff and King Maitrībala sacrificing his flesh to feed the rākṣasas, the Sanskrit–Tibetan bilingual Jātakastava reinforces the sequence of the six perfections (pāramitās) and exhibits a more pronounced thematic progression in its arrangement, thus representing a concise model of classical Sanskrit hymns. The Sanskrit–Tibetan bilingual text is attributed to Jñānayaśas, who may be associated with the Northern Zhou translator Shénà Yēshě 闍那耶舍. The text was translated into Tibetan by the scholar Chos skyong bzang po of the Zhwa lu school, whose word-for-word rendering style possibly reflects a grammatical and commentarial approach characteristic of the Zhwa lu school’s linguistic studies. The Khotanese Jātakastava may be seen as an expanded recension of this Buddhist hymn tradition as it existed in Dunhuang around the tenth century, while the Sanskrit–Tibetan bilingual version represents an abridged form that reached Tibet in the fifteenth century. The similarities and differences between the two texts reveal the inherent tension between localized dissemination and standardized compilation in the transmission of Jātaka narratives. Full article

The Lorenz number is a critical parameter for separating the electronic and lattice contributions to thermal conductivity in thermoelectric materials through the Wiedemann–Franz law. However, the classical Sommerfeld approximation often fails to accurately represent the temperature-dependent transport behavior of BiSbTe-based thermoelectric materials. This study presents a systematic analysis of the temperature dependence of the Lorenz number using experimental data compiled from eleven independent studies. A unified database was established through literature review, data extraction, normalization, and statistical analysis. Linear, exponential, and quadratic regression models were evaluated to identify the mathematical representation that best describes the reported behavior, and a Processing Complexity Index (PCI) was introduced to examine potential relationships between fabrication-route complexity and the degree of nonlinearity. The compiled datasets consistently exhibited an overall increase in the Lorenz number with temperature, although noticeable variability in magnitude and curvature was observed among studies, reflecting differences in material composition, processing routes, and experimental conditions. While the quadratic model generally achieved the best statistical performance, linear and exponential models provided comparable fits for some datasets, indicating that no single functional form is universally optimal. The proposed correlations provide a statistically representative framework for improving thermal conductivity decomposition and thermoelectric characterization within the investigated temperature range (300–500 K). Nevertheless, the correlations are constrained by the scope of the literature-derived database and should not be interpreted as universally applicable predictive models. Full article

Species delimitation and biodiversity assessment in Chironomidae are frequently hindered by morphological conservatism and widespread cryptic diversity. Neozavrelia (Diptera: Chironomidae), a genus inhabiting specialized freshwater microhabitats such as springs and hygropetric seepages, remains poorly understood with respect to its genetic diversity and the environmental processes underlying lineage differentiation. Clarifying lineage diversity is a prerequisite for evaluating the ecological factors associated with genetic differentiation. In this study, we compiled a global COI DNA barcode dataset comprising 137 sequences from newly generated specimens and publicly available records in the Barcode of Life Data Systems (BOLD). Genetic diversity was evaluated using neighbor-joining (NJ) analysis and Automatic Barcode Gap Discovery (ABGD), whereas environmental and geographic drivers of genetic differentiation were assessed using Mantel tests, distance-based redundancy analysis (db-RDA), variation partitioning, and hierarchical partitioning. A total of 26 molecular operational taxonomic units (MOTUs) were identified, with most lineages forming well-supported clades in the NJ tree. Genetic differentiation was significantly associated with both environmental and geographic distances, although environmental variables explained a substantially greater proportion of the observed variation. Hierarchical partitioning identified slope, annual cloud cover, mean precipitation amount of the coldest quarter, and frost frequency as the principal environmental predictors of lineage differentiation. Our findings reveal substantial COI genetic diversity within Neozavrelia and suggest that environmental heterogeneity, particularly variation in water availability and thermal conditions, is significantly associated with lineage differentiation. This study expands the global COI DNA barcode reference library for Neozavrelia and provides new insights into ecological and evolutionary factors associated with diversification in freshwater chironomids. Full article

Multi-source urban indicator datasets are frequently used in clustering, machine learning, and regression analyses without prior statistical auditing, potentially distorting results through non-normality, multicollinearity, and cross-source measurement disagreement. This study applies an integrated five-stage pre-modeling diagnostic protocol, comprising coverage auditing, normality assessment, outlier detection, correlation analysis, and VIF screening, to a 71-variable dataset compiled from six international sources for 106 arid and semi-arid cities across nine world regions. The protocol evaluates coverage completeness, distributional normality, outlier structure, inter-variable correlation architecture, and multicollinearity severity. Results show that 89% of continuous variables are non-normal, 17 of 23 predictors exceed the conventional Variance Inflation Factor threshold of 10, and 2 major international sources exhibit near-zero agreement for electricity access (Pearson r = −0.02). Gulf Cooperation Council cities form a structurally coherent outlier cluster requiring robust scaling rather than exclusion. The study produces an eight-action priority matrix to guide downstream analytical decisions and provides a replicable protocol for multi-source urban sustainability datasets. Full article

This paper presents the continuation of a previous investigation into climate mobilization in Spain, extending the time period covered to 2019–2025, incorporating new databases and including protest control analysis. The aim is to analyze diachronically the repertoires of action used in order to understand their evolution, intensity, participating organizations and how social control of protest influences them. Through documentary compilation and systematic coding of protest events (N = 1502) and the analysis of social control over protest, through reports on repression of social movements and data on human rights violations in the context of protest, the main findings can be highlighted as follows: disruption increased after the pandemic, in 2021; from 2023 onwards, there is a shift in trend towards a decrease in confrontational mobilization and an increase in contained forms, with collective action evolving towards a diversity and complementarity of noninstitutional and nonviolent strategies and tactics, forging alliances with other movements to maintain the social base and support. This shift is temporally associated with an intensification of protest control and criminalization. Moreover, a significant presence of either pre-existing or newly formed organizations is maintained, with a relationship existing between the variation in collective protagonism and the typology–intensity of repertoires. Thus, from a multidisciplinary perspective, the aim is to contribute to the international debate on the tactics of social movements, with the most important contribution being the integration of repertoire analysis with the study of protest control in that movement. Full article

Earlier work by some of the present authors identified power-law statistical regularities across the periodic table: a near-Zipf relationship $W\propto Z^{1.09}$ between atomic weight and atomic number in neutral atoms, and a fine-structure splitting scaling $\Delta E\propto Z^{1.78}$ in the $3d^{2+}$ (Cr-like) isoelectronic sequence of highly charged ions (HCIs). The apparent tension between this superlinear empirical exponent and the linear-in-Z scaling derived analytically by Lyu, Keitel, and Harman for relativistic clock-state transitions in $n{d}^6$ ions is resolved by writing the scaling law in the form $\Delta E=A{(Z-Z^{\ast })}^{\gamma }$, which gives $\gamma =1.03$ and $Z^{\ast }=25.83$ for the $3d^{2+}$ data and restores a near-Zipf interpretation. We extend the thresholded model from the single $3d^{2+}$ sequence to fourteen isoelectronic sequences spanning C-like ($Z\ge 6$) through Mo-like ($Z\ge 42$), drawing on the NIST Atomic Spectra Database, evaluated compilations of strontium, copper, and tungsten ion data, and digitization of GRASP MCDHF Mo-like results. Comparing the fitted threshold $Z^{\ast }$ against the classical Slater shielding ${\sigma }_{\mathrm{Slater}}$ of the valence shell reveals three regimes: (i) Coulomb-LS sequences (C/N/O/Ne-like) with $Z^{\ast }$ fixed at zero by construction; (ii) a mainstream cluster of nine sequences (a mix of spin–orbit fine-structure and, for the $d^2$ Ca-/Sr-like members, Coulomb term separations) for which $Z^{\ast }$ tracks ${\sigma }_{\mathrm{Slater}}$ within $\pm 1.5$ units; (iii) a pair of $n{d}^6{}^{5}D_0$ sequences (Cr-like $3d^6$ and Mo-like $4d^6$) with $Z^{\ast }-{\sigma }_{\mathrm{Slater}}=+7.20$ and $+10.36$, scaling linearly with Z in the jj regime (after resolving a low-Z LS–jj crossover for the Mo-like member). The slope ratio $A_{\mathrm{Mo}}/A_{\mathrm{Cr}}\approx 0.48$ is of the order of the hydrogenoid radial-extent ratio $⟨r^2⟩(3d)/⟨r^2⟩(4d)\approx 0.32$, exceeding it by ∼50% as expected from relativistic $4d$ contraction. A falsifiable extrapolation for the W-like $5d^6{}^{5}D_0$ sequence is offered: $\Delta \in [+7,+11]$, $A_W\in [0.12,0.18]$ eV/Z, with explicit failure modes specified for an independent GRASP MCDHF test. Full article

Traditional speech therapy for children often faces challenges such as fear, a lack of patient motivation, unattractive supportive tools, and a critical shortage of specialized technological tools for under-resourced languages like Slovak. This paper presents a novel conceptual digital speech therapy ecosystem and core technological approaches developed within the 3PoCube project. To address the engagement gap, the proposed framework leverages gamification across five interconnected pillars which are integrating interactive, game-like environments for home practice with asynchronous offline telemedicine to support the parent–child–clinician dynamic. The technological core utilizes state-of-the-art Self-Supervised Learning (SSL) and Transformer-based Automatic Speech Recognition (ASR) models fine-tuned on a newly compiled Slovak children’s speech corpus, consisting of approximately 5 h of annotated speech from 303 speakers. In our experiments, the best-performing Wav2Vec 2.0 MMS architecture achieved a Word Error Rate (WER) of 15.10%, while the adapted Whisper Turbo achieved 16.33% on spontaneous pediatric speech. Several functional prototypes implementing these models are presented, including Neslovkáčik (a telemedicine portal), Hláskové superhrdinstvo (an articulation app), and LogoHra (a highly customizable virtual board game platform). Preliminary formative feedback from parents and speech-language pathologists indicates perceived acceptability during early prototype testing and suggests the potential to support engagement with the proposed solutions. However, while this study establishes a technical and conceptual foundation for home rehabilitation, rigorous clinical validation is required before definitive therapeutic efficacy can be claimed. Full article

The lower flammability limit (LFL) is critical for assessing ignition and explosion risks associated with lithium-ion battery thermal runaway gases. In this study, a primary experimental LFL database containing 58 data points for H₂–CO–CH₄–C₂H₄–CO₂–N₂–O₂ mixtures was compiled from the first author’s publicly available doctoral dissertation. Le Chatelier’s rule was first evaluated as a baseline model, and its prediction residuals were then corrected using a five-coefficient data-driven model based on physically interpretable variables, including total diluent fraction, CO₂ fraction in diluent gases, oxygen fraction, and the interaction between highly reactive fuels and dilution. Results showed that Le Chatelier’s rule provided a useful first-order estimate but systematically underestimated LFL under high-dilution and CO₂-rich conditions. The proposed correction model reduced the mean absolute error from 2.40% to approximately 1.00% while retaining an explicit mathematical form. This experimental-data-driven framework provides a preliminary and interpretable tool for rapid LFL estimation of multicomponent gases relevant to battery thermal runaway risk assessment. Full article

Drought increasingly threatens terrestrial vegetation, whereas current syntheses remain disproportionately focused on seed plants. Ferns and mosses provide a useful contrast because they represent distinct hydration strategies among early-diverging land plants. We compiled 3272 paired observations from 46 drought experiments covering 35 fern species and 41 moss species to compare responses in water status, photosynthesis, chlorophyll fluorescence, oxidative stress, osmotic adjustment, abscisic acid, and growth. Drought reduced physiological performance in both groups, but mosses showed a greater mean decline than ferns. Ferns maintained stable maximum quantum yield and increased nonphotochemical quenching despite reduced pigment content and carbon assimilation, suggesting stronger photoprotective regulation. In contrast, mosses showed coordinated declines in maximum fluorescence, effective PSII yield, and maximum quantum yield, together with elevated minimum fluorescence, indicating direct PSII impairment. Oxidative damage, osmolyte accumulation, and growth suppression were also stronger in mosses. Within ferns, drought sensitivity was concentrated in epiphytic species, especially obligate, canopy, tank-forming, and xerophytic groups. Fern responses were partly explained by provenance climate, drought duration, and specific leaf area. Overall, within the species and experimental conditions represented in the current dataset, ferns largely maintain photochemical stability through photoregulation, whereas mosses shift more rapidly toward PSII impairment, oxidative injury, and growth suppression, highlighting vulnerable components of moisture-dependent ecosystems under intensifying drought. Full article

Hybrid nanofluids with enhanced thermal conductivity have emerged as promising candidates for efficient heat removal in advanced energy systems and next-generation thermal management technologies. In particular, the use of viscoelastic base fluids embedded with radiatively active nanoparticles enables improved thermal regulation in solar collectors, electronic cooling units, and high-temperature industrial processes. This study presents a comparative thermal investigation of mono- and hybrid nanofluids comprising the ferro-oxide (Fe₃O₄) and copper (Cu) metallic particles dispersed in ethylene glycol (C₂H₆O₂), under magnetohydrodynamic (MHD) viscoelastic flow over a stretched surface. Accurate modeling of heat and mass phenomena in such fluids arises from their growing application in advanced thermal systems, including cooling technologies, electronic devices, and renewable energy modules. Unlike conventional models, the current analysis incorporates the Cattaneo–Christov heat flux framework to capture non-Fourier thermal relaxation effects, alongside the influence of thermal radiation and solutal transport. The developed system is truncated into dimensionless form with the proper choice of appropriate quantities, whose solution methodology is based on the implementation of a Runge–Kutta scheme. Compiled observations suggest that the hybrid nanomaterial exhibits more pronounced thermal recovery, while mono nanofluid attributes lower impact. Moreover, increasing the viscoelastic and magnetic parameters leads to notable variations in temperature and concentration distributions. This work advances the current literature by simultaneously integrating viscoelastic rheology, dual nanoparticle suspensions, and non-classical heat conduction laws, providing new insights for optimizing thermal performance in engineering applications. Full article

Titanite is a widespread accessory mineral in magmatic, metamorphic, and hydrothermal systems and can incorporate trace elements that are sensitive to ore-forming processes. Although titanite trace-element chemistry has been widely applied to individual ore systems and deposit comparisons, its potential for supervised machine-learning-based discrimination across multiple ore deposit types remains less systematically explored. In this study, we compiled a literature-based LA-ICP-MS titanite trace-element dataset comprising 1679 analyses from five major ore deposit types: porphyry, skarn, iron oxide–apatite (IOA), iron oxide copper–gold (IOCG), and orogenic Au deposits. A common feature set of 21 trace elements, including REE, Y, Zr, Hf, Nb, Ta, Th, and U, was used to evaluate six supervised machine-learning algorithms: K-nearest neighbors, support vector machine, random forest, XGBoost, TabMap, and TabPFN. Two-dimensional element and element-ratio diagrams showed substantial overlap among deposit types, whereas machine-learning models better captured deposit-type-related multielement patterns in the compiled dataset. TabPFN achieved the highest stratified 5-fold cross-validation performance, with an accuracy of 0.957 ± 0.011 and a macro-F1 score of 0.944 ± 0.012, followed by TabMap and XGBoost. SHAP and TabMap-SHAP interpretations suggest that deposit classification is mainly associated with coupled variations in REE-Y, Eu, HFSE, and Th-U systematics rather than with a single diagnostic element. These results indicate that titanite trace-element compositions may provide a useful quantitative and interpretable approach for deposit-type discrimination within compiled geochemical datasets, while broader application requires expanded standardized datasets and independent validation samples. Full article

The compilation of optimal production plans often requires consideration of the fuzziness in certain initial information. Therefore, a pertinent issue in the theory and practice is the solution of production plan optimization problems under conditions of fuzzy information using mathematical models and tools of fuzzy sets. The research aims to develop various formulations for optimization problems of production plans using the example of a feed production plan. The problem is addressed based on a modified model considering fuzzy constraints by adapting various optimality principles. The research focuses on the processes of feed mixture production at the Makinsk poultry farm, characterized by fuzzy constraints on feed composition. New formulations of optimization problems under fuzzy constraints are obtained in the form of fuzzy mathematical programming problems, and heuristic methods for their solution are proposed. Various scenarios are considered, where the original multi-criteria optimization problem can be reduced to a single-criterion problem. For each formulation of the optimization problem, modifications of Pareto optimality methods and the main criterion are applied, ensuring the effective utilization of expert information and the decision maker’s knowledge during the optimization process and the selection of the best solution. Full article

Myrmecochory is a form of seed dispersal mediated by ants. Although this mechanism of dispersal has received less research attention than other dispersal processes, the wide distribution and high biomass of ants mean that it can strongly influence plant dispersal patterns. In particular, the underlying mechanisms and key agents of myrmecochory remain poorly understood in the context of anthropogenic perturbations; furthermore, such research is especially scarce in East Asia. This review aims to elucidate the ecological mechanisms underlying myrmecochory, to explore how this interaction may be affected by urbanization and climate change, and to determine its potential ecological role in disturbed ecosystems. We first review past research on the three major hypotheses proposed for the emergence of ant-mediated seed dispersal—directed dispersal, distance dispersal, and predator avoidance. We then compile taxonomic information on myrmecochorous plants and ants from global databases and regional literature, expanding the checklist of Korean myrmecochorous plants to 130 species and reclassifying them as endangered, rare, or endemic. Our synthesis suggests that invasive ants could threaten myrmecochory by displacing native myrmecochorous ants, increasing seed predation, and facilitating the dispersal of invasive plants. Moreover, the urban heat island effect and habitat fragmentation could disturb the dispersal, germination, and growth of myrmecochorous plants, threats that may be further intensified by climate-driven phenological mismatches. Consequently, in temperate East Asian countries experiencing anthropogenically generated environmental changes, myrmecochory emerges as a pivotal ecological process that underscores ecosystem vulnerability and resilience. Ultimately, incorporating these plant–ant interactions into biodiversity monitoring is essential for predicting ecosystem shifts and designing robust, proactive conservation strategies in changing environments. Full article

Context: Modern quantum-computing experimentation generates heterogeneous, context-dependent execution data whose scientific value depends on preserving calibration state, compilation decisions, and run outcomes in a traceable and repository-ready form. In the NISQ era, probabilistic outputs, time-varying hardware conditions, and opaque transpilation pipelines create a data-management problem that directly affects reproducibility, traceability, and long-term reuse of experimental records. Goal: This paper aims to address this gap by proposing a specialized metadata and schema model for managing quantum-circuit execution data as governed, machine-interpretable, and evolvable repository artifacts. Proposal: We propose QC-MM, a platform-agnostic metadata model for capturing, validating, and relating contextual evidence of quantum-circuit experiments. The model integrates time-indexed calibration binding, transpilation traceability, lightweight provenance links, validation rules, and controlled schema evolution through a JSON Schema specification. Results: The evaluation follows a multi-scenario protocol and shows that QC-MM captures dynamic calibration context in IBM Quantum Cloud, remains interoperable through a local SpinQ NMR device, and makes transpilation effects traceable through structured records. It also supports repeated-run statistical reporting and links compilation decisions to execution outcomes, including circuit-depth reductions and changes in an estimated fidelity proxy under different optimization settings. Conclusions: QC-MM provides a specialized data-modeling and schema-governance foundation for traceable quantum-experiment repositories. Beyond improving reproducibility-oriented reporting, the proposal contributes to metadata validation, controlled schema evolution, and repository-oriented management of contextual experimental data. Full article

The karmavācanā are ritual texts found in the Vinaya Piṭaka’s Khandhaka sections and standalone translations, regulating the conduct of monks and nuns. They include procedures for legitimate religious practices and penalties for disciplinary violations. The Taishō Tripitaka compiles five karmavācanā texts, structured into two systems. This study focuses on the Tanwude lübu zajiemo (曇無德律部雜羯磨, No. 1432), attributed to Kang Sengkai (康僧鎧), who is from Tianzhu (India) during the Cao Wei period, and the Jiemo yijuan (羯磨一卷, No. 1433) by Tan di (曇諦), an Anxi (Parthian) śramaṇa of the Cao Wei period. This study addresses three key research questions: (1) the relationship between these two karmavācanā texts and the Dharmaguptaka Vinaya (四分律, No. 1428); (2) whether the Tanwude lübu zajiemo and Jiemo yijuan are the earliest karmavācanā texts to have been translated; and (3) how to explain the process by which their textual structures were formed. By synthesizing extant karmavācanā versions in other languages and Dunhuang-Turpan manuscript fragments, the author argues that No. 1432 and No. 1433 cannot be directly identified as mechanically excerpted copies of the Dharmaguptaka Vinaya. In the formation of their respective structures, the influence of earlier karmavācanā translations—now no longer extant—cannot be ruled out. Judging from the karmavācanā manuscripts preserved at Dunhuang-Turfan, the two texts in question were most likely formed toward the end of the sixth century CE. Full article