Search Results (10,974)

Person re-identification (re-ID) aims to match pedestrian images across disjoint camera views. Existing multi-source unsupervised domain adaptation (UDA) re-ID methods still face two critical issues: they fail to effectively balance domain-invariant feature learning and domain-specific style preservation and cannot adequately model the implicit correlations among diverse source domains, resulting in limited cross-domain generalization performance. To address these challenges, this paper proposes a novel multi-source UDA re-ID framework equipped with a Mixture of Experts feature extraction (MEFE) network and a Graph-Based Relation (GBR) module. Specifically, the MEFE network integrates mixed Instance and Batch Normalization (MIBN) to extract robust domain-invariant features, while the embedded domain-specific style information (DSI) module compensates for lost domain-specific style details at the feature level. Furthermore, the cascaded Graph Attention and Graph Convolution Networks (GATs/GCNs) in the GBR module adaptively explore implicit feature correlations and achieve effective multi-source feature fusion. Center maximum mean discrepancy loss is adopted to further reduce cross-domain distribution discrepancies. Extensive experiments on large-scale datasets demonstrate that the proposed method achieves state-of-the-art performance and substantially outperforms mainstream UDA re-ID approaches. Full article

Huanglongbing, a destructive citrus disease of global importance that is also present in Saudi Arabia, is associated with Candidatus Liberibacter asiaticus (CLas) and remains a major threat to citrus production. Although previous studies have documented sequence variation and prophage polymorphism in CLas, broader comparisons of prophage-associated gene content remain limited. In particular, comparative orthogroup analysis of prophage gene-content conservation across geographically structured CLas populations has rarely been explored. In this study, we analyzed 42 CLas prophage genomes from Saudi Arabia and other geographic regions using a comparative orthogroup framework. OrthoFinder assigned 99.1% of predicted proteins (1825 of 1841) to 64 orthogroups, with only 16 genes remaining unassigned. A small number of rare orthogroups restricted to only a few genomes were identified, and no orthogroup was detected in all genomes. Presence–absence analyses supported a predominantly conserved prophage gene repertoire together with a small accessory component, while also indicating that apparent absences should be interpreted in light of mixed assembly status and prophage-region completeness. Saudi Arabian genomes were distributed within the broader global framework and exhibited generally similar gene-content profiles rather than a deeply separated lineage. Functional interpretation of representative orthogroups identified conserved prophage-associated genes related to replication, helicase activity, and phage packaging, whereas variable orthogroups were primarily associated with hypothetical or accessory prophage-related functions. Overall, these results are consistent with a model in which CLas prophage diversification is associated more with sequence-level variation and localized structural differences than with extensive gain or loss of prophage genes. These findings further refine current understanding of CLas genome evolution and highlight conserved prophage-associated targets that may support molecular diagnostics and epidemiological surveillance. Full article

This paper targets the air-to-ground (A2G) data backhaul scenario of UAVs and proposes a communication system based on coherent optical zero-padding orthogonal frequency division multiplexing (CO-ZP-OFDM), which unifies atmospheric turbulence scintillation, pointing errors, and Doppler frequency shift into a composite channel model. The system employs the Gamma-Gamma (GG) distribution to describe turbulence-induced intensity fluctuations, a Gaussian beam truncation model to characterize pointing errors, and a dual-pilot method to estimate and compensate the Doppler frequency offset. Furthermore, on a polarization-time-frequency (PTF) three-dimensional orthogonal grid pilot structure, we derive theoretical mean square error (MSE) expressions for the zero-forcing (ZF) and minimum mean square error (MMSE) estimators, and analyze their MSE characteristics under the proposed pilot model. Simulation results show that, under moderate turbulence, the shrinkage factor of the MMSE estimator yields only about $0.4$ dB MSE reduction over ZF at $\mathrm{SNR}=10$ dB, whereas the full receiver pipeline that combines coherence-bandwidth pilot averaging with the MMSE and maximum ratio combining (MRC) equalizer reduces the empirical MSE by approximately 15 dB. The bit error rate (BER) performance tests indicate that, under turbulence-free conditions with ideal channel estimation, the system can reduce the BER below ${10}^{-4}$ at an SNR of approximately 12 dB. Under strong turbulence conditions with MMSE channel estimation, the SNR cost required to achieve a BER of ${10}^{-3}$ is approximately 18 dB, which corresponds to a 3 to 5 dB BER gain over the ZF baseline at the same SNR. Further simulation analysis shows that the average pointing loss is highly sensitive to the angular jitter at the 1 km link distance: an angular jitter of 1 mrad incurs about 18 dB of loss, and a sub-mrad pointing stability (i.e., ${\sigma }_{\mathrm{jit}}<0.062$ mrad) is required to keep the average pointing loss below 1 dB. Full article

Meeting the rigorous performance standards of modern electrified transit necessitates the deployment of high-performance outer rotor PMSMs with elevated power-to-volume ratios. However, their unique internal heat source topology inherently restricts heat dissipation. This limitation risks permanent magnet demagnetization and winding insulation failure. To address these thermal bottlenecks, this paper proposes internal bio-inspired cooling channels. These channels feature micro-scale V-shaped ribs. This design targets a 60 kW outer rotor PMSM. The motor uses a fractional-slot concentrated winding. The analytical procedure commences with the formulation of a transient 2D numerical model utilizing the Time-Stepping Finite Element approach (TS-FEM). It is coupled with the Bertotti model to compute electromagnetic losses. This approach accurately determines losses under high-frequency rated conditions. Results reveal that stator iron loss constitutes the dominant heat source. It accounts for 76.4 percent of the total electromagnetic loss. Furthermore, these losses show severe spatial concentration at the stator teeth. Subsequently, a three-dimensional fluid-solid coupled CFD model is developed. This model evaluates the proposed internal cooling channels. The design integrates bio-inspired vein networks and V-shaped ribs. These internal ribs disrupt the near-wall thermal boundary layer. This disruption enhances the local convective heat transfer. Comparative multiphysics analyses indicate improved hydraulic and thermal performance of the bio-inspired design under the same numerical boundary conditions. The bio-inspired channel achieves a more uniform static pressure distribution and reduces severe fluid stagnation zones. In the numerical model, the maximum stator and permanent magnet temperatures are reduced to 48 °C and 42 °C, respectively. This work provides a numerical design reference for thermal management in high-performance electric aviation. Full article

Dual-beam circularly polarized antenna arrays are widely demanded in high-capacity wireless and satellite communication systems. However, conventional designs typically suffer from complex feeding networks, large profile, and high insertion loss, which limit their integration level and efficiency. To address these issues, this paper proposes a low-loss, highly integrated dual-beam circularly polarized antenna array based on a substrate-integrated waveguide equivalent ENZ feeding network. A new physical phenomenon is revealed that the tangential electric field in the slots exhibits an equal-amplitude and anti-phase distribution due to the combined effect of the uniform field distribution in the ENZ medium and the boundary conditions of the slotted perfect electric conductor. Using this inherent mechanism, the antenna achieves symmetric dual-beam radiation at approximately ±27° in the E-plane. A polarization conversion meta surface layer is loaded to convert linear polarization into circular polarization. A prototype is fabricated and measured. At 8.3 GHz, the measured peak gain is 9.1 dBi, the minimum axial ratio is better than 1.5 dB, and the radiation efficiency is higher than 85%. The proposed array features simple structure, low loss, and high integration. Compared with conventional feeding structures, it eliminates the need for additional phase shifters or power dividers, effectively reducing insertion loss and structural complexity. It exhibits good application potential in compact base stations and satellite communication terminals. Full article

Background/Objectives: This prospective observational cohort study aimed to evaluate the influence of heated tobacco (HT) and electronic cigarettes (ECs) on bone remodeling markers such as receptor activator of nuclear factor kappa-B ligand (RANKL) and osteoprotegerin (OPG), and periodontal status, at baseline and at 3 months after initial periodontal therapy. Methods: The sample comprised 236 participants (130 women, 106 men; mean age 38.96 ± 7.69 years), distributed across non-smokers (n = 72), heated tobacco/HT product users (n = 83), and electronic cigarette/EC users (n = 81). For each patient, the periodontal charting included periodontal probing depth (PPD), bleeding on probing (BOP), and clinical attachment loss (CAL). Unstimulated saliva samples were analyzed for RANKL and OPG levels. All patients underwent nonsurgical periodontal therapy (scaling and root planing). Between-group comparisons were performed using the Kruskal–Wallis test followed by Bonferroni-adjusted pairwise comparisons, while within-group changes over time were assessed using the Wilcoxon signed-rank test. To complement the primary nonparametric analyses, two-way mixed-design ANOVA and ANCOVA models adjusted for baseline values and periodontitis stage were performed as sensitivity analyses. Statistical significance was set at p < 0.05. Results: At baseline, both product user groups exhibited significantly higher PPD (p = 0.005) and CAL (p = 0.001) compared with non-smokers, with no differences between HT and EC users. Salivary RANKL levels were significantly higher in HT and EC users than in non-smokers, and OPG levels did not differ significantly. Following non-surgical periodontal therapy, all parameters improved significantly across groups (p < 0.001). At the 3-month follow-up, both product user groups maintained higher PPD (p = 0.008), CAL (p = 0.001), and salivary RANKL levels, compared with non-smoking individuals (p < 0.001). The RANKL/OPG ratio remained significantly different only for EC users compared with non-smokers (p < 0.001). Conclusions: HT and EC use were associated with differences in periodontal parameters and higher RANKL levels, while differences in the RANKL/OPG ratio were observed in EC users compared with non-smokers. Non-surgical periodontal therapy improved clinical parameters and reduced the RANKL/OPG ratio, highlighting the importance of biofilm control. Full article

An earthquake lethality model was employed to assess the casualty distribution in Yunnan, Guizhou, and Sichuan provinces, taking into account the ground motion acceleration with different 50-year exceedance probabilities. When the probability is 63%, fatalities are predominantly concentrated in central and south-western Yunnan, as well as central, southern, and western Sichuan. At a 10% probability, the peaks of the casualties are observed in southern, eastern, and central Sichuan. In Yunnan (excluding the northwest and southeast regions), the casualty density exhibits unevenness, whereas Guizhou experiences relatively low casualties (except in the eastern and western mountainous areas). Xichang incurs the most substantial losses, followed by Lancang. Xundian, Songming, and Dongchuan demonstrate a high propensity for fatalities, and the risk is relatively high in the vicinity of the Longjiang and Nujiang faults. If a destructive earthquake occurs near these areas within the next 50 years, the probability of a Level-I emergency response exceeds 10%. When the ground motion acceleration doubles (especially when the exceedance probability drops to 2% in 50 year and 0.1% in a year), the predicted number of casualties remains relatively stable. However, the grid of the casualty population exhibits a higher degree of spatial concentration of casualties, and the disaster-affected area expands. There exists no linear correlation between earthquake-induced fatalities and the ground motion level. When the 50-year exceedance probability decreases from 63% to 10%, the casualty rate may increase by several dozen times. Full article

In the Iberian Peninsula, the rapid expansion of the invasive species Alburnus alburnus (bleak) has intensified its contact with several endemic cyprinid species, raising concerns about hybridization, introgression, and the loss of genetic diversity. Despite increasing evidence of hybridization, data remain limited for many Iberian River basins, where endemic species persist in fragmented and vulnerable habitats. The aim of this study is to assess the extent and spatial distribution of hybridization between the bleak and the following native cyprinid species, Anaecypris hispanica (jarabugo), Iberochondrostoma lemmingii (pardilla), Pseudochondrostoma willkommii (Guadiana nase), and Squalius alburnoides (calandino), across several rivers within the Guadalquivir Basin. To this end, Sanger sequencing will be performed on the mitochondrial cytochrome b gene (maternal lineage; approximately 1000 base pairs (bp)) and the nuclear β-actin gene (paternal lineage; approximately 950 bp) from individuals of all endemic species and the bleak. Parental species and putative hybrids were initially identified in the field using diagnostic morphological and meristic characters, including number of rays in the anal fin morphology, mouth position, and the number of lateral line scales. Molecular analyses will include haplotype network reconstruction and phylogenetic tree inference to evaluate relationships among individuals from different species and to assess lineage divergence. The results will allow us to: (1) detect hybrids between the bleak and endemic cyprinids, (2) identify hybridization events among endemic cyprinid species, and (3) evaluate the correspondence between diagnostic morphological and meristic traits and the molecular identification of hybrid individuals. Overall, these findings will provide key information for the conservation management of endangered Iberian freshwater fishes in the context of invasive species expansion and global change. Full article

This study evaluates the accuracy of various preprocessing methods applied to scanned archival aerial photographs for reconstructing historical terrain in the Czech Republic. Seven workflows were tested on identical imagery and control points, varying parameters such as resolution unification, brightness normalization, focal length calibration, and AI-based denoising. Accuracy was assessed using GNSS checkpoints and high-resolution LiDAR data. Results show that basic brightness correction reduced the vertical RMSE by 59% (to 5.69 m). In contrast, standalone AI preprocessing was associated with increased geometric instability (RMSE 16.48 m) due to over-smoothing and the loss of essential micro-texture. However, the evaluated “Fusion AI” workflow—combining AI enhancement with strict focal length constraints—successfully mitigated this degradation. By restricting the internal orientation, it stabilized the vertical accuracy at 6.48 m, closely matching the best traditional approaches. Statistical analysis revealed strong spatial autocorrelation and non-normal error distributions, highlighting the need for robust validation. Ultimately, this study confirms that AI can be effectively utilized to enhance visual clarity in data-scarce historical reconstruction without sacrificing spatial reliability, provided it is strictly geometrically constrained. This offers an optimal compromise and a tested, reproducible workflow that supports heritage preservation and long-term environmental analysis. Full article

The large-scale integration of distributed photovoltaics (DPVs) into the distribution network exacerbates voltage fluctuations and substantially increases network losses. To improve the voltage quality and economic efficiency of distribution networks, a Volt/Var optimization (VVO) model is established. Coordinating multiple heterogeneous devices, the model aims to minimize the total voltage deviation, the total network losses, and the regulation cost of discrete equipment simultaneously. Considering multi-constraint coupling characteristics, a quantitative method is proposed to evaluate the reactive power regulation potential of DPVs under intricate operating conditions. Then, the multi-strategy integrated rime optimization algorithm (MSIRIME) is utilized for the model solution. Fuch chaotic mapping generates uniformly distributed and ergodic initial populations. A dual-branch search mechanism combining the snow ablation optimizer with the rime optimization significantly enhances global exploration capabilities. The guided learning strategy balances exploration and exploitation for high-dimensional VVO, preventing local optima. Case tests on a modified IEEE 33-bus system demonstrate that the proposed model exhibits excellent effectiveness and robustness. Moreover, MSIRIME exhibits better optimization performance than some classic and recently proposed strategies, reducing the average network losses and voltage deviation over 30 independent runs by at least 5.87% and 52.22%, respectively, relative to those of the compared methods. Full article

Cropland and rural settlements are core components of rural human–environment systems, and their coordinated development is crucial for regional sustainability, particularly in China’s major agricultural production regions. Taking the Huang-Huai-Hai region as the study area, this study systematically investigates the spatiotemporal evolution of cropland and its coupling relationship with rural settlements using land use data from 1990 to 2020. Grid-based analysis and multiple spatial modeling methods were employed. The results show that: (1) From 1990 to 2020, the cropland in the region decreased by a net total of 21,021.94 km², with annual dynamic degrees ranging from −0.13% to −0.28%. Cropland conversion to other land uses far exceeded conversion from others, with construction land being the primary destination. Among these, rural settlements and urban construction land accounted for 43.75% and 55.58% of the total cropland loss, respectively. (2) The spatial distribution of cropland exhibited a distinct pattern of “hot in the center and south, cold in the periphery and north” (Moran’s I = 0.232, p < 0.001), indicating significant positive spatial autocorrelation. Hot spot areas clustered in the North China Plain and the Huang-Huai Plain, while cold spot areas were distributed in the Yanshan–Taihang mountains and the hilly regions of the Shandong Peninsula, clearly controlled by topography. (3) Cropland change exhibited stage-specific characteristics. The pattern was relatively stable during 1990–2000. During 2000–2010, cropland conversion to other uses intensified, with high-value conversion areas concentrated around urban agglomerations. In the 2010–2020 period, these high-value conversion areas diffused from the core plain areas to urban fringe zones. (4) The spatial coupling between cropland and rural settlements was predominantly characterized by the Moderately Coordinated Type (MCT), accounting for 48.38–58.44% of the area. However, the proportion of Rural Settlement-Dominant Type (RC) increased from 15.51% to 21.58%, indicating a trend toward intensifying human–environment conflicts. Overall, the Huang-Huai-Hai region experienced significant cropland changes. While its spatial pattern remains relatively stable, the coupling relationship between cropland and rural settlements is deteriorating, posing challenges to regional food security and rural sustainable development. Full article

The increasing penetration of distributed generation (DG) in distribution systems poses significant operational challenges, including increased power losses, voltage profile deviations, and variations in short-circuit currents. These issues may compromise network safety, reliability, and the selectivity of protection schemes under different operating scenarios. This paper proposes a hybrid optimization methodology for the optimal placement and sizing of DG, aiming to minimize active power losses while ensuring voltage regulation and keeping short-circuit currents within permissible limits. An integrated approach is proposed that combines a mesh-to-radial network reconfiguration strategy with a modified Ant Lion Optimization algorithm, known as ALO-DG, enabling the simultaneous optimization of network topology and the allocation of distributed generators at candidate buses. The problem is formulated taking into account power balance constraints, voltage limits, distribution network capacity limits, and short-circuit current limits. The proposed methodology achieved substantial reductions in active power losses in the IEEE 33-bus and 69-bus test systems, reaching 84.42% and 91.56%, respectively. These improvements were accompanied by enhanced voltage profiles while preserving the radial operating structure of the distribution networks. Furthermore, the proposed hybrid methodology serves as a tool for the planning and operation of distribution systems with high DG penetration, particularly in scenarios where grid security and protection coordination are critical considerations. Full article

High-fidelity computational fluid dynamics (CFD) remains computationally expensive for steady aerodynamic prediction under multi-condition and variable-geometry configurations, which limits rapid design iteration. To address this issue, this study proposes a data-driven surrogate framework for aircraft surface flow-field prediction on irregular meshes. The framework combines a geometry-unification strategy for variable rudder-deflection configurations with KM-GAT, a hybrid neural architecture that integrates graph attention and KAN-based nonlinear feature transformation. Geometry unification maps the surface flow fields associated with different rudder-deflection states onto a common zero-deflection reference template, thereby establishing consistent mesh correspondence and fixed prediction locations across samples while retaining the rudder angle as an operating-condition variable. The KM-GAT model further combines topology-aware message passing with localized nonlinear refinement, while the Huber loss is adopted to improve training robustness for CFD-derived data. Experiments on the F-22 research model show that the proposed framework achieves lower prediction errors and more concentrated error distributions than baseline MLP and GNN-based models. Qualitative comparisons further indicate that KM-GAT better preserves localized high-gradient structures, including pressure transitions and vortex-dominated regions. These results suggest that the proposed framework provides an effective surrogate modeling strategy for variable-geometry aerodynamic flow field prediction. Full article

Background/Objectives: Deep learning models for digital mammography sensor data are increasingly deployed across hospitals using different X-ray detector technologies and patient populations. Whether models trained on one sensor platform and population maintain accuracy when transferred to another has not been tested for the latest generation of mammography-specific foundation models under one controlled protocol. Methods: We fine-tuned five backbone architectures (ResNet-50, DINOv2-B14, Rad-DINO, Mammo-CLIP B5, and Mammo-FM) on CBIS-DDSM (film-digitized, USA, n = 714 validation) with three seeds, ablated a density-aware focal loss across three auxiliary weights, and evaluated transfer to three external sensor cohorts: CMMD (full-field digital, China, n = 1032), DMID (mixed digital, India, n = 509), and MIAS (film-digitized, UK, n = 322). Significance used paired DeLong z-tests with Benjamini–Hochberg FDR correction; temperature scaling tested post hoc recalibration at all transfer targets. Results: Within this single-source three-seed evaluation, ResNet-50 outperformed all four foundation models on CBIS-DDSM (AUC 0.867 vs. 0.847, 0.846, 0.813, and 0.703; all gaps p_adj < 0.05). The density-aware focal loss degraded both AUC and calibration at every weight tested. At transfer, every model lost 0.165 to 0.320 AUC points relative to in-distribution performance, with sensitivity at 95% specificity collapsing from 0.31 to 0.47 in-distribution to 0.11 to 0.22 across the three external targets. A per-seed Stouffer meta-analysis confirms that Mammo-CLIP B5 and Mammo-FM significantly outperformed ResNet-50 on DMID and Mammo-CLIP on CMMD, after BH-FDR; MIAS comparisons remained directional only. In the extremely dense subgroup (BI-RADS D4), Mammo-FM reached AUC 0.870 versus ResNet-50 at 0.842, a directional observation whose 95% CIs overlap heavily at the n = 140 sample size and which we do not interpret as a statistically supported advantage. Conclusions: In this single training-source, three-seed protocol, mammography-specific pretraining did not deliver the in-distribution AUC premium reported in the originating papers, and no architecture reached a level at which transfer deployment without local validation would be defensible. We frame these as observations specific to the present protocol rather than as broader conclusions about foundation models for mammography classification. The findings argue for sensor-stratified and population-stratified external validation and for local recalibration as practical prerequisites before clinical use. Code and weights are released under MIT license. Full article

This study investigated the effect of MoS₂/graphite lubricant composition on the high-temperature compaction behavior, local mechanical uniformity, and microstructural characteristics of Fe–5.0 wt.%Si SMCs. Nine lubricant compositions were prepared by varying MoS₂ and graphite contents, and their friction behavior, Vickers hardness, and compaction behavior were evaluated experimentally and by FEA. One-way ANOVA confirmed that lubricant composition significantly affected the Vickers hardness response (F = 4.245, p = 0.000273). The measured friction coefficients were applied as interface friction conditions in FEA, and the relative density, effective strain, and absolute hydrostatic stress distributions were compared. Among the investigated compositions, C3, containing 1.0 wt.% MoS₂ and 0.3 wt.% graphite, showed the lowest friction coefficient and Vickers hardness standard deviation. In FEA, C3 also showed balanced relative density, effective strain, and hydrostatic stress distributions. XRD confirmed the α-Fe-based bcc Fe–Si matrix, while SEM-EDS indicated locally distributed lubricant-derived residual regions. Therefore, C3 was selected as the most balanced lubricant composition within the investigated range. Future studies will evaluate electromagnetic properties, including core loss and magnetic permeability. Full article