Search Results (441)

Underwater acoustic (UWA) channels are inherently complex, with pronounced variability arising from multipath propagation, time variability, Doppler effects, and nonstationary ocean conditions. Such variability often leads to unstable communication reliability when conventional single-carrier signaling and fixed reception strategies are employed. In practical UWA environments, performance degradation may occur when channel characteristics deviate from the assumed regime, thereby limiting system robustness. To address this reliability challenge, this study develops an unequal-rate frequency–phase keying (URFPK) signaling strategy that combines a low-rate frequency component with a high-rate phase component. A corresponding receiver structure is designed, employing parallel coherent and noncoherent processing to enhance robustness under dynamic channel conditions. In addition, a reduced-complexity noncoherent procedure is introduced to improve computational efficiency. Simulation results demonstrate substantially improved robustness under severe UWA distortions. Full-scale sea trials further validate the engineering effectiveness of the proposed approach, achieving communication success rate improvements of $18.62$% and $9.39$% over baseline schemes within short intervals and maintaining an overall success rate exceeding 91% over extended transmissions. These results indicate that the URFPK signaling strategy provides a practical and robust mechanism for improving UWA link reliability in dynamic UWA channels. Full article

Poor consolidations and the strength–conductivity trade-off limit the performance of copper alloys fabricated by laser powder bed fusion (LPBF). To address this, this study developed a strategy combining the response surface methodology (RSM) with direct ageing treatment (DAT) to achieve a favorable strength–conductivity synergy. The results showed that under the optimal process parameters, a high relative density of 99.25% (8.95 g/cm³ for theoretical density) was obtained. After direct ageing treatment at 490 °C for 60 min, the CuCrZr exhibited an ultimate tensile strength of 399.31 MPa and a thermal conductivity of 326.53 W/(m·K). To reveal the underlying mechanisms, this study employed a combination of systematic characterization via high-resolution transmission electron microscopy (HRTEM) and quantitative modeling. HRTEM characterized the uniformly dispersed nanoscale body-centered cubic (BCC) Cr precipitates that form semi-coherent interfaces with the face-centered cubic (FCC) Cu matrix, showing a crystallographic misorientation of approximately 10.5° intermediate between the classic Nishiyama–Wassermann and Kurdjumov–Sachs orientation relationships. Quantitative modeling indicates that the high strength arises from a synergistic effect: coherent strain fields exerted by the precipitates effectively pin retained dislocations, coupling Orowan and dislocation strengthening. Meanwhile, solute precipitation reduces lattice distortion, restoring notable thermal conductivity. Full article

Recovering high-quality images from low-quality speckle patterns remains a core challenge in scattering imaging, especially under narrowband illumination with ambient light interference and broadband illumination. This paper proposes a dual-input synchronous transmission architecture: after Correction-Smoothing-Phase Optimization (CSPO) preprocessing, two data streams are parallel-fed into Phase-Aligned Coherent Summation (PACS) for efficient and high-precision reconstruction with adaptive fusion, breaking the single-path limitation of traditional methods and balancing imaging efficiency and quality. Additionally, an adaptive enhancement factor feedback mechanism is designed for Median-Unsharp Sharpening Enhancement (MUSE) to dynamically adjust Median Filtering (MF) and Unsharp Masking (USM) parameters, achieving adaptive balance between noise suppression and detail enhancement and improving robustness under extreme lighting. In PACS, a dynamic reference update mechanism is introduced, combined with fixed amplitude to realize iterative phase optimization, effectively suppressing speckle noise and boosting the signal-to-noise ratio of reconstructed images. Experimental results show that the proposed method achieves favorable restoration performance even at a SNR of −8.7 dB under narrowband and broadband illumination with spectral bandwidths of 100 nm, 200 nm, and 280 nm (FWHM), and significantly improves image quality in unknown scattering media, showing great potential for robust speckle reconstruction. Full article

Higher education institutions are increasingly called upon to play a pivotal role in advancing the Sustainable Development Goals (SDGs) through pedagogical innovation and curriculum transformation. The study aims to identify the relationship between teaching approaches (transmissive, transactive, and transformative) and the integration of the Sustainable Development Goals (SDGs) across nine Latin American universities in Argentina, Colombia, Costa Rica, and Mexico. A quantitative survey design was employed, and data were analyzed using descriptive statistics, correlation analysis, and both stepwise and hierarchical multiple regression techniques to ensure robustness. A sample of 3541 undergraduate students was assessed using a structured questionnaire comprising highly reliable constructs, with reliability coefficients ranging from 0.70 to 0.96. The analysis revealed that transformative and transactive teaching approaches were positively associated with students’ perceived integration of the SDGs, whereas transmissive teaching was negatively associated. Transformative teaching emerged as the strongest predictor, explaining 37.2% of the variance in perceived SDG integration when entered alone, while the final regression model explained 38.1% of the variance. The convergence between stepwise and hierarchical regression models strengthened the robustness and theoretical coherence of the findings. The findings highlight the importance of student-centered and action-oriented pedagogies in strengthening SDG integration within higher education, offering practical implications for curriculum design and academic staff development. Full article

The increasing activity of unmanned aerial vehicles (UAVs) has intensified the demand for reliable and computationally efficient methods for passive radio-frequency (RF) signal detection. In practical RF monitoring scenarios, the environment is often non-stationary and affected by varying noise conditions. Under such circumstances, classical energy-based detectors are sensitive to noise uncertainty, while more robust approaches, such as cyclostationary analysis, require substantially higher computational resources. This work presents a burst-aware cascade method for UAV RF signal presence detection that explicitly addresses this trade-off. The proposed framework combines fast energy-based screening with temporal burst aggregation, applying spectral correlation function (SCF) analysis selectively and only when sustained signal activity is indicated. Detection is performed on fixed-length RF signal chunks, while additional segment-level duration constraints are used to characterize sustained transmissions. The method is evaluated using the publicly available DroneRF dataset and compared against six baseline detectors, including fixed-threshold energy, wavelet-based, blind cyclostationary, two adaptive energy detector variants, and a lightweight convolutional neural network. Experimental results confirm that chunk-level detection remains difficult for all considered methods. Temporal aggregation across longer intervals yields a substantial improvement: the cascade achieves $P_d$ = 1.000 and AUC = 1.000 at the segment level, matching exhaustive cyclostationary detection while reducing per-segment processing time by a factor of 2.46. An additional result is that burst-level concatenation prior to SCF estimation provides implicit coherent integration, preserving $P_d$ = 1.000 at signal amplitude reductions of up to −20 dB where standalone detectors degrade to $P_d$ = 0.995. Overall, burst-aware cascade architectures offer a practical and interpretable approach to RF-based UAV monitoring, providing a well-grounded compromise between detection reliability and computational efficiency under realistic operating conditions. Full article

Pre-service teachers’ (PTs) beliefs about young children’s cognitive abilities shape both their instructional practices and their developing understandings of teaching and learning. This study examined PTs’ beliefs about preschool children’s cognitive abilities, focusing on cognitive operations, conceptual change, and learning processes, in relation to emerging professional identity development. A cross-sectional comparative design was employed with a convenient sample of 241 students from Early Childhood Education Departments who completed the Childhood and Cognitive Abilities Questionnaire. The findings revealed statistically significant differences between participants with and without practicum experience, with the former reporting more sophisticated beliefs, aligned with constructivist learning approaches. However, many participants simultaneously endorsed child-centered perspectives and traditional transmission-based conceptions of teaching, indicating the coexistence of contradictory beliefs. Correlation and cluster analyses further suggested that participants’ beliefs formed broader but only partially coherent belief systems rather than consistent conceptual profiles. These findings may reflect tensions within PTs’ emerging professional identities and suggest that practicum-related experience may coincide with opportunities for reflection on and restructuring of prior beliefs, processes associated with a coherent professional identity. Overall, this study highlights the importance of teacher education programs systematically addressing misconceptions about children’s cognitive abilities, while fostering coherent, research-informed professional identities and evidence-based instructional practices in early childhood education. Full article

Weak-bus identification is a key task for online security assessment, preventive control, maintenance verification, and resilience-oriented dispatch of interconnected power grids. In large-scale grids, conventional full-graph graph neural networks preserve the complete network topology but may become inefficient when many operating scenarios must be screened repeatedly. Direct graph partitioning improves computational tractability, but it may cut tie-line channels and weaken the boundary evidence that determines cross-area risk propagation. To address this trade-off, this paper proposes a boundary-compensated partition-based parallel graph neural network for weak-bus identification. The method first constructs a scenario-aware weighted power-grid graph and divides it into electrically coherent subgraphs under coupling-strength and partition-size constraints. Local graph encoders are then executed in parallel to learn intra-partition vulnerability representations. A boundary compensation module further restores cross-partition information by weighting tie-line neighbors according to electrical coupling, branch loading, and cross-area association. Standardized partition scores are finally fused into a whole-grid weak-bus ranking, and a composite learning objective jointly considers node-score regression, boundary consistency, and pairwise ranking stability. The method is evaluated on the IEEE 57-bus benchmark with mechanism-based node and branch vulnerability labels. Compared with the original full-graph GNN, the proposed method reduces the mean square error from 0.0359 to 0.0147, improves the Spearman rank coefficient from 0.248 to 0.446, and increases Hit@10 from 30% to 70%. Topological interpretation further shows that the identified weak buses are concentrated around high-risk branches such as 8-12, 12-14, 0-14, and 7-8, indicating that the proposed framework captures local aggregation, boundary transmission, and corridor-driven vulnerability propagation. The IEEE 57-bus benchmark is used as a focused validation case because it provides aligned node- and branch-level vulnerability evidence for evaluating weak-bus ranking behavior. Because the available aligned vulnerability evidence is concentrated in this medium-scale benchmark, the results should be interpreted as a focused validation of the proposed ranking mechanism rather than as a complete large-system scalability study. Full article

The theory of partially coherent image formation in dark-field and phase-contrast microscopy is presented. Explicit expressions and three-dimensional plots of the transmission cross-coefficient for different imaging modes are given. These include central and oblique internal dark field, annular dark field, phase contrast, differential phase contrast using semicircular or quadrant condenser pupils, and differential interference contrast. Explicit expressions are given for the image intensity for pure-phase objects consisting of a single-object spatial frequency or combinations of object frequencies. Full article

Vertical-cavity surface-emitting lasers (VCSELs) have emerged as essential light sources for atomic-precision measurement, quantum-secure communication, high-speed optical transmission, and laser coherent scanning detection, owing to their low power consumption, high-quality beam characteristics, and ease of two-dimensional integration. However, the fundamental limitation on linewidth narrowing in VCSELs arises from their inherently short resonator, resulting in a natural linewidth on the order of 50–100 MHz. This limitation prevents conventional VCSELs from meeting the stringent requirements of advanced applications, making the ultra-narrow linewidth a key focus in optoelectronics research. This review analyzes representative achievements and application scenarios of narrow-linewidth VCSELs, evaluates the merits and limitations of industrial-grade devices, and envisions future directions in next-generation optoelectronic systems. Distinct from existing reviews, it integrates key single-mode fabrication techniques, quantitative linewidth requirements across applications, silicon photonic integration, and scalable manufacturing trends, establishing a complete mechanism–technology–application–industry analytical framework. Full article

The integration of post-quantum digital signature (PQDS) algorithms into coherent wavelength-division multiplexing (WDM) optical networks introduces a non-negligible cryptographic overhead that fundamentally alters physical-layer performance characteristics. Unlike conventional studies that treat security and transmission independently, this work provides a cross-layer evaluation of PQDS-induced payload expansion and its direct impact on coherent optical system behavior under realistic, DSP-aligned conditions. A structured and reproducible evaluation framework is proposed to systematically analyze this interaction across multiple transmission scenarios, ranging from a single-channel QPSK baseline to a 16-channel WDM system employing both QPSK and 16QAM modulation formats. Key system parameters—including launch power, local oscillator power, bit rate, and fiber length—are jointly optimized, while performance is rigorously assessed in terms of bit error rate (BER), Q-factor, and maximum transmission reach. The results demonstrate a clear performance degradation trend driven by both spectral efficiency scaling and cryptographic payload expansion. The single-channel QPSK system achieves a maximum reach of 203 km, which decreases to 194 km in the 16-channel WDM QPSK configuration due to inter-channel interference and nonlinear effects. In contrast, the 16-channel WDM 16QAM system exhibits a significantly reduced reach of 103 km, reflecting its heightened sensitivity to noise, chromatic dispersion, and fiber nonlinearities. Furthermore, increased payload size associated with PQDS schemes is shown to exacerbate transmission impairments by extending frame duration and intensifying inter-channel interactions. These findings identify PQDS-induced overhead as a critical system-level constraint that directly governs transmission efficiency, scalability, and performance limits. The study highlights the necessity of cross-layer co-design strategies, where cryptographic mechanisms and physical-layer parameters are jointly optimized to enable efficient, reliable, and quantum-safe coherent optical communication systems. Full article

The scalable and sustainable production of graphene remains a significant challenge due to the high cost, complex processing, and environmental impact associated with fossil-derived graphite precursors. In this work, we report a biorenewable pathway for producing graphitic carbon from industrial hemp biomass, yielding a plant-derived material called CleanGraphene. This approach provides a renewable and potentially scalable alternative to petroleum- and coal-based graphene production while maintaining competitive structural and electrical performance. CleanGraphene samples are systematically characterized using X-ray diffraction (XRD), Raman spectroscopy, transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and thermogravimetric analysis (TGA) to evaluate crystallographic order, layer stacking, defect density, surface chemistry, and thermal stability. The results show that optimized CleanGraphene materials consist of multilayer graphene-like platelets with compact interlayer spacing (d(002) ≈ 3.36–3.37 Å), extended crystallite coherence lengths (L_c up to ~75 nm), large in-plane sp² domains (L_a exceeding ~200 nm), and relatively low defect densities, indicating well-developed graphitic ordering. Electrical conductivity measurements using a binder-free pelletization method and four-point probe analysis demonstrate that the highest quality CleanGraphene samples achieve conductivities of (8.4–8.6) × 10⁴ S m⁻¹, surpassing leading commercial graphene benchmarks measured under identical conditions. Structure–property correlations confirm that electrical performance is governed primarily by crystallite coherence, defect density, and interlayer stacking order, while surface oxygen content plays a secondary role within an ordered graphitic framework. All CleanGraphene samples exhibit excellent thermal stability, retaining more than 95% mass up to ~800–900 °C under an inert atmosphere. Collectively, these findings establish quantitative quality benchmarks for hemp-derived graphene and demonstrate that biomass-based graphene can achieve electrical and thermal performance comparable to, and in some cases exceeding, conventional commercial products. This work highlights industrial hemp as a promising renewable precursor for the scalable production of high-performance graphitic nanomaterials for electrically and thermally conductive composite applications. Full article

Reconfigurable intelligent surfaces (RISs) have recently attracted attention as a potential solution for improving the reliability of optical wireless communication links, especially when direct transmission (DT) becomes severely degraded due to dynamic channel conditions. In this study, an RIS-assisted architecture based on a modulating retroreflector is proposed for underwater optical wireless communications (MRR-UOWC). In the considered system, both the DT path and the RIS-assisted path transmit the same information simultaneously at the same data rate. The propagation channels are modeled by taking into account propagation loss, Gamma–Gamma turbulence, and pointing error effects. At the receiver, the signals arriving through the direct path and the RIS-reflected path are coherently combined. To evaluate the effectiveness of this configuration, two diversity combining techniques, namely selection combining (SC) and maximum ratio combining (MRC), are investigated. Closed-form analytical expressions for the outage probability (${\mathrm{P}}_{\mathrm{out}}$), average bit-error rate (BER), and ergodic capacity ($\overline{C}$) are derived using the probability density function (PDF), cumulative distribution function (CDF), and moment-generating function (MGF) of the end-to-end signal-to-noise ratio (SNR). The analysis indicates that jointly exploiting the DT and RIS-assisted links can provide noticeable performance gains by leveraging the complementary characteristics of the two propagation paths. Full article

Political polarization and policy uncertainty have become increasingly consequential for regional economic adjustment, yet their joint role in shaping socioeconomic resilience remains underdeveloped in the literature. This study advances the debate by conceptualizing regional resilience as the outcome of a multi-layer socioeconomic system in which external policy disturbances, institutional fragmentation, and structural adaptive capacity interact over time. Using balanced panel data for 16 Korean regions from 2004 to 2023, the analysis develops an integrated empirical framework that combines panel local projections, threshold estimation, structural moderation tests, dynamic robustness checks, and forward-looking machine-learning prediction. The results show that policy uncertainty is associated with lower regional socioeconomic resilience and that this effect persists over time. More importantly, political polarization does not simply accompany weaker resilience; it amplifies the transmission of uncertainty shocks, especially once institutional fragmentation crosses a critical threshold. Structural conditions further shape this process. Digital transformation, industrial diversification, and financial depth reduce vulnerability, whereas trade exposure intensifies it. These findings indicate that resilience is not determined by economic structure alone, nor by institutional instability in isolation. It emerges from the interaction between disturbance, amplification, and adaptive capacity within a regional system. The predictive analysis reinforces this interpretation. Variables identified as central in the econometric models also carry forward-looking information about future vulnerability states. This study therefore contributes not only by combining methods, but by linking explanation and prediction within a single systems-oriented account of regional resilience. The Korean case shows how institutional coherence and structural adaptability jointly condition resilience under uncertainty. Full article

High-precision time and frequency transfer plays a pivotal role in metrology, geodesy, deep-space exploration and other scientific applications. Based on current time synchronization research, extending point-to-point schemes into a wide-area network can significantly increase the range of applications. Therefore, we design and implement a cascaded fiber optic time synchronization system, which is the most basic form of networking. This paper considers two different modulation formats for time synchronization systems from the perspective of fiber nonlinear effects, namely the intensity modulation with direct detection (IMDD) scheme and the phase modulation with self-coherent detection (PMSCD) scheme. The analysis indicates that the constant-envelope characteristic of the PMSCD scheme provides superior transmission performance. Accordingly, we deployed the PMSCD system over a 500 km intercity fiber link and the IMDD system over a 68 km metropolitan fiber link, forming a 568 km cascaded system that achieves time synchronization precision better than 50 ps. This work offers a practical reference for the future development of high-precision fiber-optic time and frequency synchronization networks. Full article

The growth of Internet of Things (IoT) applications is driving demand for Low-Power Wide-Area Networks (LPWANs) to support higher data rates with the same energy efficiency. While Long Range (LoRa) provides excellent noise immunity and receiver sensitivity, its data rate might be insufficient for some applications, including those real-time applications in which LoRa is required to have infrequent transmissions to maintain low power consumption. In this paper, a novel modulation is introduced to address these limitations by utilizing narrowband chirp to represent a data symbol with chirp slopes, called a multi-slope chirp signal. At the receiver, a new blind non-coherent detection technique is also presented to recover the proposed signal. The simulation results confirm that the proposed scheme can successfully transmit information at 2 to 4 bits per symbol, and when compared to LoRa SF 6, it reduces the Time-on-Air (ToA) by half and also achieves an improvement in spectral efficiency in the frequency domain. Full article