Search Results (14,555)

Continuous in situ marine holographic observation generates data volumes that challenge onboard storage and transmission. Parallel phase-shifting digital holography (PPSDH) is especially sensitive to compression because phase retrieval depends on consistent four-channel demodulation. We present a training-free spatiotemporal compression framework for sparse-particle marine PPSDH sequences based on background–residual decomposition and a shared four-channel processing path. The background is coded once per temporal window by a discrete wavelet transform (DWT) followed by principal component analysis (PCA), and the dynamic residual is decorrelated by temporal principal component analysis before quantization and entropy coding. The framework is evaluated on three primary 64-frame marine PPSDH sequences using a common reconstruction-and-evaluation pipeline with wrapped-phase root-mean-square error (PhaseRMSE) as the primary metric and amplitude peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) as secondary references; expanded supplementary checks are also reported for nine additional selected 64-frame groups spanning sparse to transitional occupancy. On the primary sequence and within the high-fidelity achieved-rate overlap with the JPEG Pleno anchor codec INTERFERE, the proposed framework reduces PhaseRMSE by about 3.3-fold to 3.4-fold while increasing amplitude PSNR by about 11 dB and preserving amplitude SSIM above 0.99997. Lower-bitrate sweeps further quantify the rate–fidelity trade-off rather than claiming universal low-rate superiority. These results support BG–Res spatiotemporal coding as a practical phase-fidelity-oriented option for the tested sparse-to-transitional marine PPSDH conditions; extension to dense scenes, broader marine conditions, and downstream biological tasks requires separate validation. Full article

Visual scene matching navigation (VSMN) for unmanned aerial vehicles (UAVs) boasts advantages such as high precision, high reliability, and autonomy. The biggest challenge lies in the tension between local fine-grained information and global semantics, as well as limited generalization ability in real-world environments. While existing Transformer-based cross-view geolocation methods enhance global context modeling capabilities, they still generally face issues such as high demands on training data and computational resources, insufficient fusion of local fine-grained information and global semantics, and real-time performance in real-world complex environment. To address these problems, we propose a scene matching and localization algorithm based on the Siamese-ViT. For feature extraction, we use the ViT model to extract global features and K-means clustering to aggregate local features. Combined with the global features extracted by the ViT, a robust local–global feature representation vector is generated. For feature matching, incremental principal component analysis (IPCA) is used to reduce the dimensionality of the high-dimensional feature space, and a KD-tree is constructed for fast feature retrieval to improve matching efficiency. We validated our algorithm on the University-1652 dataset and a dataset of real-world satellite-drone image pairs. The results show that our Siamese-ViT outperforms other models in both Recall and AP. We conduct flight experiments in real-world environments, capturing drone images of complex scenes, including farmland, urban buildings, and waterways. The results show that, at a flight altitude of 350 m, our algorithm achieves an average absolute value of 6.2063 m for latitude, 6.7552 m for longitude, and 10.1922 m for horizontal error. Therefore, our Siamese-ViT demonstrates ideal overall positioning accuracy. Full article

Soils in cold seasonally frozen regions undergo repeated freeze–thaw (F–T) cycles, during which soil moisture content, pore structure, and permeability can change substantially. Previous studies have mainly focused on the mechanical behavior of such soils, whereas few have clarified how moisture content fluctuation regulates pore-structure evolution and permeability response during F–T cycling. In this study, black soil specimens were prepared with initial moisture contents of 15%, 20%, 25%, and 30% on a dry-weight basis and were denoted as 15%-MC, 20%-MC, 25%-MC, and 30%-MC, respectively. The specimens were subjected to 0, 1, 3, 6, 9, and 12 F–T cycles. Mercury intrusion porosimetry, scanning electron microscopy image analysis, and variable-head permeability tests were used to characterize pore-structure parameters and hydraulic responses. The results showed that porosity and mean pore diameter generally increased with increasing F–T cycle number, and the magnitude of these increases depended on the initial moisture content. The 15%-MC group exhibited limited pore expansion, mainly characterized by a transition from micropores to small pores, whereas the 25%-MC and 30%-MC groups developed more mesopores and macropores. In the 30%-MC group, porosity reached its maximum after 9 F–T cycles and then decreased slightly after 12 cycles, indicating particle rearrangement or partial filling of larger pores. The permeability coefficient and cumulative infiltration also increased with increasing F–T cycle number, with more pronounced increases observed in the high-moisture groups. Tukey’s post hoc test showed that the permeability coefficients in the later F–T stages were higher than those in the early stages, particularly in the 25%-MC and 30%-MC groups. Correlation analysis and principal component regression indicated that the permeability coefficient and cumulative infiltration were positively correlated with porosity, mean pore diameter, mesopores, and macropores, but negatively correlated with micropores. Overall, the initial moisture content regulated pore-size redistribution and seepage-channel development, thereby shaping the hydraulic response of black soil under repeated F–T cycling. Full article

Amaranth (Amaranthus spp.) is a multifaceted genus of C4 plants with significant nutritional and agronomic potential, yet it remains underutilized in mainstream agriculture. Despite growing interest in Amaranth, most germplasm studies have used either phenotypic or molecular approaches alone, lacking integration. Multivariate methods have not been systematically applied to identify promising genotypes, and species-specific selection indices for grain Amaranth remain unexplored. To address these gaps, this study comprehensively characterized 84 Amaranth genotypes representing multiple species (A. caudatus, A. cruentus, A. hypochondriacus, A. hybridus, A. spinosus, A. powellii, A. tricolor, and 38 accessions of unknown taxonomic status) using field experiments in a randomized complete block design with three replications and DNA barcoding with chloroplast (psbA-trnH) and nuclear (ITS) markers. Analysis of variance revealed highly significant differences (p < 0.01) among genotypes for all six agronomic traits evaluated, confirming substantial genetic variability with grain yield exhibiting the widest variation (CV = 28.55%), ranging from 0.25 to 125.56 g/plant. High broad-sense heritability estimates (0.79–0.99) coupled with high genetic advance, particularly for grain yield (117.54%), indicated that these traits would respond favorably to selection. Path analysis and stepwise regression identified early flowering, long inflorescences, and heavy seeds as the primary determinants of grain yield, collectively explaining 27% of yield variation. Mahalanobis D² analysis identified nine multivariate outliers with distinct phenotypic profiles, among which G39 emerged as the most promising breeding candidate, combining exceptional yield (90.50 g/plant) with desirable architecture, long inflorescence, and large seeds. Principal component analysis further resolved trait complexes, identifying 11 PC1-selected promising genotypes as donors for plant architecture and three PC2-selected promising genotypes as donors for seed size characteristics. Molecular analysis revealed distinct genetic relationships. A. caudatus (kiwicha) exhibited limited haplotype diversity indicating a narrow genetic base, while A. cruentus and A. hypochondriacus showed broader diversity, with the nuclear ITS network providing clearer resolution than chloroplast markers due to biparental inheritance. Outlier genotypes, including G82, G83, G13, G10, and G39, occupied unique haplotype positions, confirming that their phenotypic distinctiveness corresponds to genuine genetic differentiation. The novelty of this study lies in integrating multivariate biostatistical techniques (heritability, path analysis, Mahalanobis D², PCA, and stepwise regression) with two complementary DNA barcode systems (chloroplast and nuclear) within a single germplasm collection. This integrated approach provides breeders with well-characterized germplasm, validated selection criteria, and prioritized parental materials for Amaranth improvement. Further multi-location and multi-season evaluations are recommended to ensure the stability and adaptability of these promising germplasm accessions. Full article

Scenting time is a critical parameter that not only shapes the aromatic characteristics of jasmine tea but also influences its processing strategies. This study aims to elucidate how scenting time influences the aroma quality of jasmine yellow tea (JYT) through the integration of sensory evaluation with volatile compound profiling and the use of multivariate analyses, including principal component analysis (PCA) and orthogonal partial least squares–discriminant analysis (OPLS-DA), alongside complementary analytical approaches. Results demonstrated that the optimal sensory aroma quality of JYT was achieved when the scenting duration ranged from 8 to 12 h. Three hundred volatile compounds were detected, fourteen of which were identified as key contributors to JYT’s distinctive aroma profile. These include indole, methyl anthranilate, methyl salicylate, and δ-Cadinene, all of which exerted a significant influence on the overall aroma quality score. The identification of these principal volatile components provides valuable insights for optimizing JYT manufacturing processes and offers a theoretical basis for establishing systematic aroma quality assessment protocols. Full article

Addressing the challenges of high-dimensional redundancy, noise interference, and parameter missing in the net present value prediction of shale gas wells, an intelligent prediction model PCA-DFNN integrating Principal Component Analysis and Deep Feedforward Neural Network is proposed. Based on actual data from 48 shale gas wells, Principal Component Analysis is first performed on 19 input features to reduce dimensionality, extracting 9 core principal components, which achieve a cumulative variance contribution rate of 88.05%. Subsequently, a deep neural network model is constructed for comparative modeling. The results indicate that the PCA-DFNN model achieves a coefficient of determination on the independent test set that improves from 0.6439 in the original model to 0.6882, an increase of 0.0443, or approximately 6.9%, with faster training convergence and superior generalization ability. The research confirms that the proposed method can effectively eliminate feature redundancy, filter noise, and circumvent the uncertainty of missing value imputation, providing a more reliable technical tool for the early economic evaluation of shale gas. Full article

The aim of the present study was to explore differences in fair play attitudes among university students in Hungary and Kenya using the Fair Play Attitude Scale (EAF). The questionnaire was culturally adapted for the Kenyan context and administered in both countries. A total of 2090 university students participated in the survey (1278 from Kenya and 812 from Hungary). The scale measures three dimensions of fair play attitudes: gamesmanship and the importance of winning, acceptance of rough play and cheating, and fair play and enjoyment of the game. Principal component analysis confirmed the three-factor structure of the instrument, and reliability indices indicated satisfactory internal consistency in both samples. Due to the non-normal distribution of the variables, non-parametric statistical procedures were applied to examine differences between groups. The results revealed significant cross-cultural differences in fair play attitudes. Kenyan students, particularly men, showed higher acceptance of competition-oriented behaviour and gamesmanship, whereas Hungarian students placed greater emphasis on enjoyment and adherence to fair play principles. The findings highlight the role of cultural and social contexts in shaping ethical attitudes in sport and underline the importance of fair play education in sport pedagogy and educational practice. Full article

Bivalves are widely used in aquatic monitoring, but the potential of their shells to provide comparative metal signatures remains insufficiently explored in the Caspian Sea. This study quantified major and trace elements in empty shells of five bivalve genera (Cerastoderma, Didacna, Dreissena, Hypanis, and Mytilaster) collected from a single shell accumulation site on the southern Caspian coast. The aim was to assess intergeneric variability and provide a preliminary comparative framework for shell-based metal profiling. Element concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS), and median concentrations, internal residual enrichment factors, relative concentration factors, a relative multielement loading index, and centered log-ratio principal component analysis were applied as within-dataset comparative tools. Significant differences among genera were found for most elements. Dreissena and Cerastoderma showed the highest relative multielement loading, with comparatively elevated values of Cr, Fe, and Hg, whereas Hypanis showed marked element-specific deviations, particularly for Cu and Co. In contrast, Mytilaster and Didacna generally showed lower overall relative loading, although Mytilaster also displayed a strong Co-specific pattern. PCA-clr analysis showed structured genus-related separation based on multielement shell composition, with contrasting associations among Al, As, Cr, Fe, Co, Cu, Hg, and carbonate- or shell-associated elements such as Ba, Mg, Sr, Ti, and Zn. Overall, the results indicate that Caspian bivalve shells display distinct genus-related multielement profiles. Within the limitations of a single-site shell-accumulation dataset and the absence of paired environmental, tissue, mineralogical, and microstructural data, these findings should be interpreted as a preliminary comparative assessment rather than as evidence of environmental contamination or validated bioindicator performance. The results identify genera and elements that may deserve priority in future shell-based biomonitoring studies after validation with living populations, broader spatial replication, and paired sediment, water, particulate, and soft-tissue data. Full article

This study investigates consumer acceptance of insect-based foods, focusing on changes in visual evaluation after information disclosure and the influence of sociodemographic, attitudinal, and knowledge-related factors. An online survey among Italian consumers (n = 350) assessed the visual attractiveness of a cupcake containing 10%w/w Tenebrio molitor flour before (PRE) and after (POST) disclosure of the insect ingredient. Attractiveness decreased from 2.6 to 2.0, with 79% of POST evaluations in the lowest appeal categories. Women expressed more negative POST ratings and experienced a larger decline in attractiveness (Δ = POST−PRE), indicating greater sensitivity to information disclosure than men. The change in attractiveness (Δ) was linked to psychological variables: negative attitudes showed moderate negative correlations with Δ (r ≈ −0.3 to −0.6), whereas higher knowledge of regulatory, nutritional, and environmental aspects showed positive correlations (r ≈ +0.3 to +0.7), mitigating the decrease. Principal Component Analysis revealed two latent dimensions: PC1 (61.6%), representing an attitudinal continuum from aversion to acceptance, and PC2 (33.3%), reflecting differences in awareness. Respondents with higher PC1 and PC2 scores showed attenuated Δ values, indicating greater resilience to the disclosure effect. Overall, findings highlight a gap between visual familiarity and acceptance, shaped by emotions, knowledge, and gender-specific sensitivities. Full article

The preservation of hydrobiological diversity is essential to ensuring the stability of the food chain and the sustainable development of high-Andean basins, which face increasing vulnerability to anthropogenic factors such as the construction of dams and reservoirs. In this study, multiple regression models, both linear and nonlinear, were developed to predict the Shannon–Wiener (H′) and Pielou (J′) indices of periphyton and macrobenthos using 21 water quality parameters and concentrations of nine metals in sediments. Samples of macrobenthos and periphyton were collected at seven monitoring stations during the dry and wet seasons between 2014 and 2025. For the analysis, linear regression models were compared with nonlinear machine learning models, specifically Gradient Boosting and Random Forest. Principal component analysis (PCA) revealed that variability of the basin’s ecosystem is dominated by geogenic factors (conductivity, boron, chlorides, and arsenic) and thermal influence. The Gradient Boosting model demonstrated superior predictive capacity (R² = 0.768 for macrobenthos) compared to linear models (R² = 0.354), successfully capturing the nonlinear responses of biota to stressors such as arsenic in sediments and temperature. It is concluded that natural chemical anomalies in the Titire River act as severe ecological filters, and that artificial intelligence shows promising results in the exploration of new applied tools for environmental management in extreme altoandine ecosystems. Full article

Digitalization is the driver of regional competitiveness and sustainable development, but its geographical impacts differ significantly across Europe. This study was conducted to determine if digital transformation results in regional sustainability or if it increases spatial inequalities, concentrating on European NUTS-1 regions for the period 2021–2025. A composite Regional Digitalization Index was developed by means of Principal Component Analysis (PCA) based on indicators measuring internet access, internet usage, and the availability of digital public services. Dynamic spatial panel econometric models were used for empirical investigation, including a Spatial Autoregressive (SAR) model and a Spatial Durbin model (SDM), which facilitated the exploration of both temporal dependence and spatial spillover. Three main conclusions can be derived from the results, as follows: The level of digitalization in a region is highly stable over time, whereby the development depends most on previous paths. Subsequently, human capital is highly significant for digital development, and its effects are not only local but also spill over to neighboring regions. Lastly, spatial interactions consist of two opposite forces—the positive diffusion from digitally advanced neighboring regions and the competitive effects related to the economic strength of neighboring regions—that further intensify the core–periphery divide. Full article

Averrhoa carambola, known as Carambola or Star fruit, was collected in a semitropical region of central Mexico. Extractable and non-extractable polyphenols were characterized in terms of their antioxidant capacity (ABTS+, DPPH, and FRAP). Extractable polyphenols showed a higher antioxidant capacity than their non-extractable counterparts, with values of 65.61, 109.37, and 83.90 μmol TE/g db for ABTS+, DPPH, and FRAP, respectively. These values are consistent with reports on fruit cultivated in Asia. Maltodextrin-based microcapsules, N-Lok and Capsul, were prepared to protect the extract from adverse conditions. The ability of the microcapsules to protect polyphenols and their antioxidant capacity was quantified by half-life, which ranged from 10 to 50 days. Principal component analysis was performed to evaluate the multivariate relationships between polyphenol half-life and antioxidant capacity in the microcapsules. The results showed that no single microcapsule could provide the best protection across all polyphenol content and antioxidant capacity levels. The main conclusion is that the type of capsule material depends on the specific application, particularly on which antioxidant properties are desired. Full article

To address the strong reliance on manual operations and the low efficiency of egg shape index (ESI) phenotyping in layer breeding, this study proposed an ESI measurement method based on an improved YOLOv12n-seg model. Ghost Bottleneck modules were introduced into the backbone to reduce model complexity. In addition, a boundary-aware loss combining Binary cross entropy (BCE), Dice, and Boundary Loss was designed to improve mask quality. Based on the segmentation results generated by YOLO-Ghost, principal component analysis was employed to extract the orientation and scale of the principal axes of the segmented regions. The major and minor axes of the pixel-level masks were then obtained, and their ratio was used as the measured ESI value. Compared with YOLOv12n-seg, YOLO-Ghost reduced the number of model parameters and computational cost by 39.86% and 17.58%, respectively, while increasing the frame rate by 40.91%. The model achieved an mAP@0.50–0.95 of 92.10%, BF1 of 86.28%, and BIoU of 74.99%. Compared with other instance segmentation models, YOLO-Ghost achieved a precision of 99.96%, a recall of 99.69%, and a detection speed of 454.55 f/s. For ESI estimation, the predicted values showed good agreement with manual measurements, with an R² of 0.8184, MAE of 0.03219, and RMSE of 0.03681. The results indicate that the proposed method can achieve non-contact, automated, and accurate measurement of ESI, and provides technical support for high-throughput automated phenotypic data collection in layer breeding. Full article

Background: Visio-spatial skills (VSS) are essential perceptual-cognitive skills that enable athletes to process visual information, interpret spatial relationships, and execute appropriate motor responses in dynamic sporting environments. In combat sports, athletes must rapidly anticipate and react to an opponent’s actions, making well-developed VSS crucial for optimal performance. Although boxing, karate, and taekwondo share similar competitive characteristics, each discipline presents distinct technical and perceptual demands that may influence the development of specific VSS profiles. This study aimed to investigate whether significant differences exist in VSS profiles among boxing, karate, and taekwondo athletes. Methods: A comparative cross-sectional design was used involving 150 amateur combat sport athletes, 50 boxers, 50 karate athletes, and 50 taekwondo athletes. Participants were assessed using a VSS test battery measuring six variables: accommodation facility (AF), saccadic eye movement (SEM), speed of recognition (SR), (HEC), peripheral awareness (PA), and visual memory (VM). Data was analyzed using one-way ANOVA with η², ω², and Cohen’s f effect sizes, and principal component analysis (PCA). Results: One-way ANOVA revealed statistically significant differences in five of six VSS (all p < 0.001). PA produced the largest sport-specific differentiation (η² = 0.457, Cohen’s f = 0.918), followed by HEC (η² = 0.273, f = 0.612), SR (η² = 0.224, f = 0.537), and SEM (η² = 0.180, f = 0.468). AF yielded a significant moderate effect (η² = 0.108, f = 0.347). VM was the sole non-significant variable (F (2.147) = 0.74, p = 0.479, ω² = 0.000), suggesting domain-general encoding processes insensitive to discipline-specific training at this developmental level. Boxing athletes achieved the highest scores in SEM, SR, and PA, while karate athletes led in AF and HEC. PCA revealed a single dominant component (PC1 = 93.91% of variance), confirming that VSS function as a highly integrated perceptual-motor construct rather than independent sub-skills. Conclusions: Visio-spatial skills in combat sports are governed by a dominant integrated factor, with discipline-specific variations reflecting unique performance requirements. Visio-spatial skills in combat sport athletes are highly interdependent and largely governed by a single perceptual-motor construct, with discipline-specific profiles observed across boxing, karate, and taekwondo. The findings support the integration of sport-specific, ecologically valid visual training programs targeting key perceptual-cognitive skills, alongside routine assessment to inform athlete development and performance optimization. Full article

Background: Maritime operations increasingly rely on integrated, secure, and resilient architectures, yet the associated body of knowledge remains fragmented across conceptual, operational, logical, methodological, and governance-oriented perspectives. Objective: Our aim is to systematically review the literature on maritime integrated systems architecture in order to identify dominant themes, methodological tendencies, enabling technologies, and unresolved research gaps. Eligibility criteria: Peer-reviewed studies published in English were included when they addressed integrated systems architecture, or closely related architectural approaches, in maritime or naval contexts. Studies centred exclusively on isolated components, non-maritime settings without clear architectural transferability, or insufficient technical or methodological detail were excluded. Information sources: ACM Digital Library, IEEE Xplore, SpringerLink, ScienceDirect, MDPI, and IMarEST. Searches were carried out between January and March 2025, with the final search update for all sources completed in March 2025. Methods: The review was conducted and reported in accordance with PRISMA 2020. Three reviewers independently screened titles, abstracts, and full texts. Two reviewers independently extracted data, assessed methodological limitations and risk of bias using a review-specific qualitative appraisal framework, and evaluated the risk of bias due to missing results at the synthesis level. Disagreements were resolved through discussion and consensus, with third-reviewer arbitration when necessary. The synthesis combined qualitative thematic analysis across eleven predefined analytical categories with descriptive bibliometric and thematic mapping procedures. Results: Of 300 identified records, 60 studies met the inclusion criteria. Across non-mutually exclusive analytical categories, the literature was concentrated in Integrated Systems Architecture (52 studies), Development Processes (42), and Conceptual Models (37), whereas Zachman-based Methodology (4) and Maturity Models (3) were only marginally represented. Three recurrent patterns were observed across the corpus: the central role of cybersecurity and risk governance in architectural design; the growing importance of information technology and operational technology convergence for resilient monitoring, coordination, and decision support; and the increasing use of model-based and model-driven approaches to address architectural complexity. Overall confidence in the principal synthesized findings was judged to be moderate. Limitations: The review was limited to six databases and English-language publications, and the included studies varied in reporting depth, methodological transparency, and degree of empirical validation. Conclusions: The review organizes the field into a multilevel taxonomy spanning conceptual and operational models, logical and layered views, development processes, reference architectures, enabling technologies, and maturity-related perspectives. Taken together, the findings suggest that research in this area has progressed more clearly in architectural representation and integration than in long-term evaluation, particularly with regard to the practical operationalization of Zachman-based approaches and the development of maritime-specific maturity assessment frameworks. Funding: This review received no external funding. Registration: The review was not prospectively registered, and no publicly accessible protocol was prepared. Full article