Search Results (366)

Early detection of bearing faults in rotating machinery is essential for ensuring system reliability and effective maintenance planning. Vibration signals inherently contain characteristic fault-related frequency components, providing rich information for both physically interpretable and data-driven analyses. In this study, a multi-representation and correlation-aware feature extraction framework is proposed for automatic classification of bearing faults from vibration signals. Experimental evaluations are conducted using the Case Western Reserve University (CWRU) Bearing Dataset. The dataset includes vibration recordings corresponding to inner race, outer race, ball faults, and healthy conditions under different damage severities. The proposed approach first applies Variational Mode Decomposition (VMD) to suppress noise and enhance frequency-related characteristics. Three different feature representations are then constructed: analytical spectral descriptors, raw Transformer-based deep representations, and a hybrid feature vector obtained by combining these two representations. The hybrid structure is further enhanced through regularized Canonical Correlation Analysis (rCCA), which models the relationship between Transformer representations and spectral descriptors, enabling correlation-aware feature fusion. Spectral, raw Transformer, and rCCA-enhanced hybrid feature vectors are evaluated separately using SVM, Random Forest, and XGBoost classifiers. The results demonstrate that both spectral and Transformer-based representations provide strong performance individually; however, integrating these complementary information sources while modeling their correlations leads to superior and more balanced classification performance. In particular, the rCCA-enhanced hybrid feature vector achieves the best results across all performance metrics. The findings indicate that combining physically meaningful frequency-domain information with data-driven deep representations yields a more robust and generalizable solution for bearing fault diagnosis. Full article

Structural semiotics, as developed by A. J. Greimas and the Paris School, provides a powerful framework for analyzing narrative meaning through actantial roles, modalities, and hierarchical narrative structures. Despite its longstanding engagement with formal reasoning and diagrammatic tools, it has seen relatively few explicit mathematical formalizations. This article proposes a diagrammatic reconstruction of key Greimassian concepts using the language of symmetric monoidal and hypergraph categories. We treat the actantial model as a typing schema and introduce wiring diagrams as a formal semantics for representing narrative configurations, modal transformations, and actantial redistribution. Modal operations such as knowing-how-to-do, wanting-to-do, and causing-to-do are modeled as typed morphisms, while Frobenius structures account for duplication, erasure, and persistence of actants across narrative time. We show how operadic nesting captures hypotaxis, and how diagrammatic factorization yields higher-level abstractions corresponding to the hypotactical clusters of the canonical narrative schema. The approach is illustrated through a detailed analysis of Aesop’s The Fox & the Crow, culminating in a formal account of discoursivization via actorialization, spatialization, and temporalization. Rather than replacing structural semiotics, this work provides it with a compositional and mathematically explicit toolkit that clarifies existing concepts and opens new possibilities for comparative, computational, and interdisciplinary analysis. Full article

Husk tomato (Physalis ixocarpa Brot.) is a crop of major economic, cultural, and nutritional importance in Mexico and exhibits substantial genetic and morphological diversity. Characterizing this variability is essential for both germplasm conservation and breeding programs. During the spring–summer 2024 growing season, 28 husk tomato populations were evaluated at the Bajío Experimental Station (INIFAP), Guanajuato, Mexico, using a completely randomized design with 12 replications. Forty-one traits were assessed following UPOV and IPGRI descriptors. Cluster analysis, canonical discriminant analysis, and the ESIM selection index were applied. A total of 77 morphotypes were identified, exhibiting variation in 33 of the 41 evaluated traits, mainly related to growth habit, leaf morphology, fruit traits, and calyx attributes. Correspondence analysis revealed a close relationship between vegetative growth and fruit size. Cluster analysis clustered the morphotypes into six clusters with no clear geographic structure, suggesting extensive gene flow. Canonical discriminant analysis explained 94.65% of the total variation, identifying seed size, leaf dimensions, and number of anthers as key discriminant traits. The ESIM index highlighted six morphotypes with favorable agronomic and morphological combinations. These results provide a practical basis for the selection of parental materials in husk tomato breeding programs under diverse agroecological conditions. Full article

This study investigates the problem of profit maximization in a retrial queueing-inventory system. Customers who arrive at the system when there is no stock enter a retrial orbit and are treated as retrial demands. We consider two strategies for inventory replenishment: the base stock policy and the (s, S) policy. For each strategy, we first formulate the fundamental equations needed to determine the rate matrix and the steady-state probabilities. Then, we compute the system’s performance metrics and profit function. Moreover, by leveraging particle swarm optimization (PSO) and genetic algorithm (GA), we introduce an improved hybrid optimization algorithm, Improved Hybrid Particle Swarm optimization (IHPSO), to solve the profit maximization problem. This algorithm initially uses PSO, followed by GA crossover and mutation to improve performance. In comparison to the canonical PSO algorithm (CPSO), our algorithm exhibits superior global search capabilities. Finally, we conduct a numerical analysis on the optimal decision variables and the corresponding profits utilizing the IHPSO algorithm and present several interesting findings. Full article

Qualitative analysis of biochemical reaction systems reveals fundamental system-level properties that are independent of precise kinetic parameters, often context-dependent, or experimentally inaccessible. By focusing on structural and topological features—such as conservation relations, feedback loops, and pathway interconnections—qualitative analysis identifies invariant behaviors, robustness mechanisms, and potential failure modes inherent to the signaling network. In this study, we use Petri nets as a formal modeling framework to conduct qualitative analysis of the integrated MAPK and PI3K/Akt signaling network. By exploiting structural properties including place invariants, transition invariants, and siphons, the analysis establishes a direct correspondence between the Petri net structure and biologically meaningful conservation laws, signaling modules, and characteristic dynamic behaviors. The results demonstrate that the proposed model is structurally consistent, biologically plausible, and modular. Minimal semi-positive place invariants confirm mass conservation, indicating that proteins and enzymes circulate within closed molecular pools. Minimal semi-positive transition invariants identify canonical kinase–phosphatase cycles underlying sustained and reversible signaling. Hierarchical decomposition reveals a modular organization reducible to reusable enzymatic motifs, reflecting biological reuse across cascades and supporting scalability. Additionally, the identification of sixteen siphons that are also traps highlights persistent subsystems that ensure continuous regulator availability, confirming the robustness and dynamic sustainability of the integrated network. Full article

Differential operators often admit multiple algebraically equivalent symbolic formulations, yet those formulations can differ in the organization of their internal structure prior to solution analysis. A reproducible symbolic framework is introduced to compare such formulations at the level of operator expressions. Within a declared symbolic specification consisting of a fixed grammar, an admissible weight class, canonical compression rules, and an admissible family of reformulations, we define four encoding-relative structural descriptors: structural strain $\tau$, structural curvature $\kappa$, compressibility $\sigma$, and the balance ratio $\Gamma =\kappa /\tau$. Structural strain compares an encoding to a designated reference representation, while compressibility measures reduction under canonical symbolic compression. These quantities are deterministic descriptors within the declared encoding class rather than coordinate-free invariants of the underlying operator. The structural length functional underlying these descriptors is developed, canonical compression is formalized, and finite symbolic comparison is distinguished from pathwise symbolic deformation. A robustness theorem shows that, away from the threshold surface $\Gamma =\sigma$, sufficiently small admissible perturbations preserve the induced diagnostic label. A supporting weight-robustness result further shows that qualitative labels persist across a local admissible family of weight choices under corresponding nondegeneracy conditions. The framework serves as a reproducible diagnostic for operator representations alongside Lyapunov, spectral, pseudospectral, and energy-based stability theories. Examples of representative ordinary and partial differential operators illustrate how the descriptors are computed and how they behave under admissible re-expression, while the appendices provide the technical backbone of the paper: formal definitions, reproducibility protocol, extended perturbation arguments, and explicit failure-mode analysis. Additional sensitivity checks regarding encoding, weights, and threshold variation clarify the method’s scope, and explicit failure modes delineate the boundary cases in which the descriptors cease to apply. The main contribution of this study is a formally delimited and reproducible symbolic framework for comparing differential operators under a fixed, declared specification, together with robustness results and worked examples that clarify the method’s scope. Full article

Global freshwater scarcity is a pressing environmental challenge, particularly in Egypt, which depends entirely on the Nile River and its tributaries. Rapid population growth, domestic wastes, agricultural runoff, and rapid industrial expansion exert highly anthropogenic stress on aquatic ecosystems, including Bahr Yusuf and Ibrahimia Canals in Upper Egypt. This study aimed to evaluate the ecological health and sustainability status of the two canals using an integrated multi-metric framework combining physicochemical variables, microbiological indicators, and community structures of zooplankton and benthic fauna. Multivariate statistical analyses (PCA, CCA), and ecological indices, including the water quality index (WQI), microbial assessment index (MAI), Rotifer-Based Index (TSI_Rot) and Hilsenhoff Biotic Index, were applied to determine pollution gradients. The results revealed that Bahr Yusuf suffers from higher pollution levels than the Ibrahimia Canal. Canonical correspondence analysis (CCA) showed that nutrient enrichment and elevated organic load are responsible for over 72% of the variance in zooplankton and benthic invertebrate assemblage in both water bodies. The dominance of pollution-tolerant species, Philodina roseola and B. calyciflorus of zooplankton and Limnodrilus udekemianus, Chironomidae larvae, Melanoides tuberculate and Cleopatra bulimoides of benthic taxa, further indicates a direct increase in organic loading and nutrient enrichment from agricultural and domestic sources. According to the Integrated Water Quality–Biotic Health Index (IWQ-BHI), the downstream stations of Bahr Yusuf are critical risk zones, with scores below 50.0, while the upstream stations of Ibrahimia Canal fell within the “good” category, with scores exceeding 70.0. Overall, both waterbodies are approaching a critical threshold of ecological instability and require urgent, integrated and sustainable management to restore and preserve these vital freshwater ecosystems. Full article

The interaction between environmental variables influences patterns of diversity and the composition of communities along the elevational gradient. However, there is a lack of evidence regarding how these diversity patterns in Scolytinae change in response to environmental changes associated with elevation. This study aims to evaluate the influence of environmental changes along an elevational gradient on the diversity and composition of Ambrosia beetles, testing the hypothesis that species assemblages are primarily driven by the interaction between environmental variables and vegetation structure. We sampled Scolytinae at five sites (650–3360 m a.s.l.) on Tacaná Volcano from February 2018 to January 2019. Sampling was conducted using five trap types, including ethanol-baited Malaise traps and interception traps. Data were analyzed using Hill numbers for alpha diversity, Bray–Curtis indices for beta diversity, and canonical correspondence analysis to evaluate the relationship between Scolytinae species abundance and environmental variables. We recorded a high richness with 82 species, a peak in diversity at mid-elevations in mesic montane forests (p < 0.05). The Scolytinae species pool is structured in three local assemblages, corresponding to different elevational landscapes, environmentally structured. Different environmental variables displayed some correlation with species dynamics. However, these factors alone were insufficient to explain patterns of species diversity. Their influence appears to depend on interactions with site-specific characteristics. These results highlight that elevational gradients act as environmental filters structuring Scolytinae assemblages primarily through species turnover rather than nested species loss. Full article

This study analyzed seven foliar traits of Cedrela odorata L. (Meliaceae) in 87 individuals across three germplasm movement zones in Tabasco, Mexico (VIII: humid; XIV: intermediate; XXI: dry) to assess differentiation and climatic relationships. Leaf length, area, petiolule length, leaflet number, rachis length, width, and stomatal density were measured. Univariate tests, canonical correlation analysis, redundancy analysis, and a relative phenotypic plasticity index were applied. Significant morphological differentiation was found: zone XIV exhibited the largest leaves and longest rachises, zone VIII the highest stomatal density, and zone XXI smaller, more subdivided leaves. The first canonical axis (r = 0.846, p < 0.001) associated long and wide leaves with warm, humid conditions, while the second (r = 0.810, p < 0.001) linked stomatal density and width to temperature minimum. Climate explained 55.7% of morphological variation, primarily through water and temperature gradients. High plasticity in leaf area, rachis length, and stomatal density suggests adaptive flexibility, yet consistent inter-zonal differences indicate local adaptation. These results demonstrate a strong correspondence with Tabasco’s germplasm movement zones and providing morphological evidence to support reforestation and germplasm management strategies under variable climatic conditions. Full article

Railway corridors create persistent linear habitats embedded within intensively managed agricultural landscapes and can simultaneously support native biodiversity and facilitate the spread of undesirable taxa. We evaluated vegetation composition across five habitat types associated with railway line no. 250 (Havlíčkův Brod–Tišnov, Czech Republic): railway yard, railway embankment, railway land, field margin, and adjacent arable land. Vegetation was recorded using phytosociological relevés (10 m²) at four localities during three surveys in the 2021 growing season. In total, 83 plant taxa were identified, with pronounced differences among habitat types. Species richness and vegetation structure were highest in railway embankments, railway land, and field margins, whereas the railway yard and arable land exhibited lower diversity consistent with high disturbance intensity and substrate constraints. Canonical correspondence analysis distinguished habitat-affinity assemblages, indicating strong habitat filtering along the railway–agriculture gradient. Classification by origin and invasion status showed that non-native and invasive taxa were concentrated predominantly in railway embankments and adjacent habitats, suggesting elevated propagule pressure and potential spread into surrounding farmland. Colonization success (ICS) and colonization potential (ICP) indices indicated that railway-associated habitats can host taxa with high establishment capacity, contributing to successional stability within the corridor. These findings highlight railways as multifunctional elements of agricultural landscapes that require integrated vegetation management to balance biodiversity benefits with operational safety and invasive species risk. Full article

This paper develops a comprehensive theory of multi-slice decompositions via convex functions, extending the classical framework of slices determined by linear functionals to arbitrary convex functions with disjoint zero sets. We establish a fundamental structure theorem that completely characterizes the convex component decomposition of multi-slices, showing that under natural conditions of pairwise disjoint zero sets and convex separation, the multi-slice decomposes canonically into convex components that correspond precisely to the individual functions in the family. Our results reveal several key properties: the component-wise exposing nature of the supremum function, the closedness of components in appropriate topologies, the maximality of the resulting decomposition, and the affine invariance of convex component structures under injective affine maps. These contributions significantly extend the existing theory of multi-slices and convex components, providing new tools for understanding the geometric structure of convex sets under nonlinear constraints, with potential applications in optimization theory, high-dimensional data analysis, and modern convex geometry. Full article

Erosion in intensively farmed landscapes threatens above- and below-ground biodiversity. While impacts on soil physical and chemical properties (which affect soil inhabiting biota) are well documented, effects on ground-associated fauna (distribution, diversity, abundance) remain less understood. A likely very strong factor is the direct transport of epigeon together with the eroded soil. We assessed how water-erosion processes shape communities of epigeic invertebrates along agricultural slopes in the Chernozem region of South Moravia (Czech Republic). Ground-dwelling invertebrates were sampled over five years (May–September) in conventionally managed maize fields using pitfall traps across 18 sloping fields. Three slope positions were compared per field (control, erosional, depositional; 54 positions in total). Community patterns were evaluated using Canonical Correspondence Analysis with covariates (month, year, slope position, site), and species responses to key drivers were analysed using Generalised Additive Models. Across the full dataset, Shannon diversity and species richness did not differ significantly among slope positions; however, total invertebrate abundance was significantly lower in erosional parts. Interannual variation was pronounced and linked to precipitation: wet conditions increased diversity and richness at depositional positions, whereas dry conditions reduced diversity downslope. Ordination and GAM results identified erosion intensity and relative precipitation/temperature anomalies as important predictors, with most dominant species showing higher abundances under low to moderate erosion. These findings indicate that epigeic invertebrate communities along slopes can serve as indicators of erosion force. Full article

In permanently submerged coastal wetlands, interactions between biogeochemical processes and microbial communities strongly influence greenhouse gas (GHG) fluxes. To improve our understanding of how redox-driven processes shape GHG dynamics in these ecosystems, we investigated the relationships among iron (Fe) pools, microbial dynamics, and the potential GHG production in subaqueous soils from an interdunal wetland in San Vitale Park (Italy), permanently submerged and affected by seasonal oscillations of the saline water table. Two subaqueous soil columns (WAS-2 and WAS-4), collected from similar settings, were analyzed. Surface layers of WAS-4 showed higher salinity and carbonate content, whereas WAS-2 was characterized by overall higher Fe concentrations. Distinct vertical distributions of organic matter and sulfur (S) were shown along depth. Laboratory incubations revealed that nitrous oxide (N₂O) production was up to ten times higher in WAS-2 than in WAS-4, with peaks in the top 13–14 cm, consistent with more active nitrification-denitrification in surface layers. Methane (CH₄) and carbon dioxide (CO₂) fluxes decreased with depth, reflecting reduced availability of labile carbon. Methanomicrobiales dominated CH₄-producing layers, indicating hydrogenotrophic methanogenesis, while amoA-carrying Nitrosomonadales and Thaumarchaeota, occurred in shallow, organic-rich layers where ammonia supported nitrification and denitrification. Denitrifiers mainly belonged to α- and β-Proteobacteria, consistent with their direct contribution to N₂O peaks. Spearman’s correlations showed N₂O positively correlated to sulfur and labile carbon (C), supporting denitrification under moderately reducing conditions. CH₄ and CO₂ positively correlated with organic C (Corg), total nitrogen (TN), and reactive Fe forms, reflecting redox-mediated microbial respiration and methanogenesis. Trace elements (B, Cr, Cu, Ni) acted as micronutrients or inhibitors depending on concentration. Canonical correspondence analysis indicated depth-structured links among gas fluxes, soil chemistry (Corg, TN, S/C, CaCO₃, P), and microbial distributions: surface layers, rich in labile C and nutrients, supported active bacteria and archaea involved in decomposition, nitrification, and denitrification, whereas deeper layers hosted oligotrophic archaea adapted to inorganic substrates. Overall, Fe pools appeared to be associated with soil processes relevant to GHG dynamics, although the extent of their regulatory role remains uncertain due to potential alterations of redox-sensitive Fe fractions during sample handling. These results contribute to broader efforts to predict GHG emissions in submerged wetland soils by linking redox stratification, inorganic chemistry, and microbial functional groups. Full article

Freshwater ostracods have considerable potential as indicators of environmental conditions, yet their ecology remains poorly documented in many large river floodplains of Southeast Europe. This study examines samples collected from ten aquatic habitats located along the Danube floodplain in Serbia’s Banat and Podunavlje regions. Monthly sampling was conducted over a twelve-month period (July 2023–June 2024), with concurrent measurements of water temperature, pH, dissolved oxygen, electrical conductivity, and turbidity. Ostracods were recorded at seven sites, yielding 19 taxa belonging to 13 genera and four families within all three non-marine superfamilies of Podocopida. Eight recorded taxa represent new additions to the Serbian fauna. Species richness was highest in semi-isolated floodplain habitats. Canonical correspondence analysis (CCA) showed that seasonal environmental variation, especially water temperature, turbidity, and conductivity, strongly structured assemblages. Hierarchical cluster analysis (UPGMA) grouped samples primarily by species composition, with seasonality exerting a strong secondary influence. Seasonal patterns revealed pronounced interspecific differences in temporal persistence and ecological tolerance of recorded species. Findings highlight the Danube floodplain’s role as a dispersal corridor, while also revealing that the river itself acts as a partial barrier, restricting faunal exchange to widespread, tolerant species. The results emphasize the importance of habitat heterogeneity and year-round sampling and support the integration of ostracods into long-term floodplain monitoring programs. Full article

Fungal communities exhibit strong spatial and environmental structuring across forest ecosystems, yet the drivers shaping their diversity patterns remain incompletely understood. In this study, we combined multivariate ordination, clustering analyses, and Zeta diversity (ζ-diversity) metrics to characterize fungal assemblages across environmental gradients. Canonical Correspondence Analysis (CCA) revealed that fungal community composition was significantly associated with climatic variables, particularly seasonal precipitation, thermal variation, and elevation. Hierarchical and K-means clustering identified coherent community clusters that differed in species richness and alpha diversity. Bray–Curtis distances and a Ward-based dendrogram further supported this separation, revealing a clear hierarchical structure in community similarity. Zeta diversity analysis indicated a slower species turnover, suggesting niche assimilation and habitat homogenization. Furthermore, the grouping of fungal assemblages followed a power-law model, emphasizing the role of deterministic environmental filtering. Critically, our findings reveal that only 1208 (33.5%) of the 3606 recorded species are present within existing Protected Natural Areas (PNAs), indicating a significant conservation gap. Together, these results provide an integrated ecological understanding of fungal diversity patterns, highlighting how climate–topography interactions structure communities and emphasizing the urgent need to align conservation strategies with these environmental drivers. Full article