Search Results (371)

The Iraqi coastline in the northern Persian Gulf is highly vulnerable to the impacts of future sea level rise. This study introduces a novel approach in the Arc Geographic Information System (ArcGIS) for inundation risk of the 58 km Iraqi coast of the northern Persian Gulf through a combination of multi-data sources, machine-learning predictions, and hydrological connectivity by Landsat. The Prophet/Neural Prophet time-series framework was used to extrapolate future sea level rise with 11 satellite altimetry missions that span 1993–2023. The coastline was obtained by using the Landsat-8 Operational Land Imager (OLI) imagery based on the Normalised Difference Water Index (NDWI), and topography was obtained by using the ALOS World 3D 30 m DEM. Global Land Use and Land Cover (LULC) projections (2020–2100) and population projections (2020–2100) were used as future inundation values. Two scenarios were compared, one based on an altimeter-based projection of sea level rise (SLR) and the other based on the National Aeronautics and Space Administration (NASA) high-emission scenario, Representative Concentration Pathway 8.5 (RCP8.5). It is found that, by the IPCC AR6 end-of-century projection horizon (relative to 1995–2014), 154,000 people under the altimeter case and 181,000 people under RCP8.5 will have a risk of being inundated. The highest flooded area is the barren area (25,523–46,489 hectares), then the urban land (5303–5743 hectares), and finally the cropland land (434–561 hectares). Critical infrastructure includes 275–406 km of road, 71–99 km of electricity lines, and 73–82 km of pipelines. The study provides the first hydrologically verified Digital Elevation Model (DEM)-refined inundation maps of Iraq that offer a baseline, in the form of a comprehensive and quantitative base, to the coastal adaptation and climate resilience planning. Full article

A series of high-cycle rotating-bending fatigue tests was conducted on H13 steel produced by electroslag remelting (ESR) and by vacuum induction melting followed by vacuum arc remelting (VIM+VAR). At 10⁷ cycles, the fatigue strength of VIM+VAR steel was 1040 MPa, which is greater than the 967 MPa of ESR steel. A metallographic analysis was conducted to compare the structure and grain size of the two steels. The results indicated that while the two steels were similar, ESR steel contained a greater number of larger inclusions and carbides. The mean inclusion size in VIM+VAR steel was approximately 55% of that in ESR steel, and the maximum inclusion size was around 44%. Notwithstanding this finding, the fatigue strength of VIM+VAR steel was found to be approximately 7.5% higher. Scanning electron microscopy of fracture surfaces revealed that the primary cause of crack initiation was predominantly oxides or oxide-sulfide composites. The measurements obtained for inclusion size, fisheye diameter, and crack propagation length indicated that the fatigue life of the material is governed primarily by the applied stress and the size of the inclusion. The presence of larger inclusions has been demonstrated to reduce the crack-propagation stage and decrease the steel’s tolerance to defects, thereby reducing fatigue life and endurance limit. The researchers derived formulae relating inclusion size to stress intensity factor and fatigue life by utilizing the Paris law. These equations ·the fatigue-fracture mechanism and provided a basis for predicting the rotating-bending fatigue life of H13 steel. Full article

This study investigates the influence of Cr₂O₃-bearing fluxes on the transfer behavior of O and Cr during the submerged arc welding process. A series of fluxes with varying Cr₂O₃ content are prepared and applied in submerged arc welding. A cross-zone model is developed to separately evaluate the transfer of O and Cr in both droplet and weld pool zones. The results reveal significant O enrichment in the droplet zone due to the decomposition of Cr₂O₃ under arc heating, followed by deoxidation in the weld pool. Cr transfer is found to be inhibited by the high oxygen potential in the droplets and further affected by evaporation loss. A comparison of predicted ΔCr values shows that the gas–slag–metal equilibrium model overestimates Cr transfer level, while the cross-zone model provides predictions more consistent with experimental results. This study highlights the critical role of Cr₂O₃ in regulating transfer behaviors O and Cr and provides valuable insights for flux design aimed at achieving precise compositional control and improved weld quality in welding applications. Full article

Arc fault detection is a key technology for preventing electrical fires. However, existing research has primarily focused on series connections, with insufficient attention paid to parallel load conditions, which are prevalent in real-world residential electricity usage. In accordance with the UL 1699 and IEC 62606 standards, this study established an experimental platform for arc faults, incorporating seven single loads (categorized into four types) and nine multi-load combinations. A systematic analysis of the differences in time–frequency characteristics under different connection modes was conducted. Time-domain and frequency-domain analyses revealed that under parallel connection the dispersion of arc fault time-domain characteristics decreases by more than 50% and the fundamental frequency component increases significantly. For parallel multi-load scenarios, the fundamental component of resistive combinations can reach 90%, while the frequency variance of inductive combinations can be as high as 400,000. By elucidating the time–frequency domain characteristics of parallel arc faults, this study proposes an optimized feature parameter analysis scheme for electrical fire monitoring systems. Based on this, this paper proposes an arc fault detection method using the Dual-Channel Convolutional Neural Network (DCNN). The method achieves 97.09% recognition accuracy for arc faults with different connection modes. Comparative experiments with other models and ablation studies show that the model attains 98.52% detection accuracy, verifying the effectiveness of the proposed method. This approach can significantly improve the accuracy of arc fault detection in multi-load environments, thereby enabling early warning of electrical circuit faults and potential fire hazards. Full article

Accurate and robust classification of dementia subtypes using non-invasive electroencephalography (EEG) signals remains a critical challenge for clinicians and researchers in the field of neuroscience. Traditional methods often rely on limited spectral features, overlooking the rich structural and geometric information inherent in EEG dynamics. CONECT (Complex Network Conversion and Topology), a novel framework, is introduced and built upon four core innovations. First, EEG time series are transformed into weighted networks using a novel Angle-Relation Connection (ARC) rule, a geometry-based approach that links time points based on angular monotonicity. Secondly, a tunable edge-weighting function is introduced by integrating amplitude, temporal, and angular components, providing adaptable heuristics adaptable to the most promising biomarker, i.e., curvature-driven features in dementia. Additionally, two new graph-based EEG features, the Weighted Angular Irregularity Index (WAII) and the Curvature-Based Edge Feature Index (CBEFI), are proposed as potential biomarkers to capture localized irregularity and signal geometry, respectively. For the first time in a dementia EEG classification study using the OpenNeuro ds004504 dataset (raw), Ant Colony Optimization (ACO) is applied as a feature selection technique to select the most discriminative features and improve model classification and transparency. The classification results demonstrate CONECT’s potential as a promising, interpretable, and geometry-informed framework for accurate and practical dementia subtype diagnosis. Full article

The gliding arc plasma technique (glidarc) was used for the precipitation and deposition of Mn or Fe oxides on zirconia fibers. Two types of fibers were used: commercial (Fib Zr(C)) and biomorphic (Fib Zr(B)) ZrO₂ fibers, the latter produced using cotton as a biotemplate. Both series of supported catalysts were characterized physicochemically and morphologically. Scanning Electron Microscopy (SEM) analyses showed that Fib Zr(B) largely retained the morphology of cotton. Fib Zr(B) presented the tetragonal phase (t-ZrO₂), while Fib Zr(C) exhibited the monoclinic phase (m-ZrO₂). Using X-ray Diffraction (XRD), the cryptomelane phase (K_xMn₈O₁₆) was identified only for Mn-Fib Zr(B). In the case of Fe-supported samples, the α-Fe₂O₃ phase appeared clearly in both biomorphic and commercial fibers. SEM and Transmission Electron Microscopy (TEM) images revealed that the precipitated iron oxides appeared to be better distributed than the manganese oxides, covering the outer surface of the fibrous supports more homogeneously. X-ray Photoelectron Spectroscopy (XPS) confirmed that Mn has an average oxidation state between 3+ and 4+, consistent with the cryptomelane phase detected by XRD. The synthesized supported systems were tested as catalysts in soot and CO oxidation, with the Mn-supported fibers proving to be more active than their Fe-containing counterparts in both reactions. Full article

The 2000 series aluminium alloys are an attractive option for lightweight structures, but solidification cracking in fusion welding remains an issue in additive manufacturing technologies. Al-Cu-Li alloys, in particular, have gained considerable attention due to their excellent strength-to-weight ratio and corrosion and fatigue resistance, making them highly suitable for aerospace components. Nevertheless, their narrow solidification range makes them highly susceptible to cracking, porosity formation, and elemental evaporation during fusion-based AM processes. These challenges underscore the necessity for advanced processing technologies and the development of suitable feedstock materials to ensure weld integrity and optimal performance. Although Al–Cu–Li alloys are highly valued in the aerospace sector, the application of wire arc additive manufacturing (WAAM) is currently limited by the lack of commercially available wire compositions. This study focuses on the use of powder metallurgy Al-Cu-Li wires in wire arc additive manufacturing, specifically using plasma metal deposition technology, to explore welding characteristics. This research demonstrates the development of an alternative wire using powder metallurgy for WAAM. Powder metallurgy wires were deposited on 5053 and 7075 aluminium substrates, and their microstructure, chemical composition, and mechanical properties were analysed. Key findings include significant elemental losses of Li and Cu during deposition—approximately 55% and 25%, respectively—as well as noticeable variations in microstructure, porosity, and grain morphology, depending on the substrate. Deposits on the 5083 aluminium exhibited more equiaxed grains and a higher chemical homogeneity compared to those on the 7075 substrate. This work establishes a link between material design and additive manufacturing by demonstrating that powder metallurgy Al–Cu–Li wires can be effectively processed by WAAM, achieving controlled elemental losses and a uniform microstructure that enhances weld integrity in aerospace components. Full article

Intersectoral labour mobility is a key driver of economic resilience and innovation in Europe. The redistribution of workers across sectors and regions enables economies to adapt to shocks, create flexibility and increase the rate of structural change. However, the dynamics of mobility have not been adequately investigated across varying scales of sectoral granularity and spatio-temporal dimensions. This paper applies the Intersectoral Mobility Index (MI) to all European NUTS-2 areas from 2008 to 2020, utilising Eurostat Structural Business Statistics. Two levels of sectoral aggregation (NACE Rev. 2, 1-digit and 2-digit) are employed to compute MI, capturing both broad and fine-grained reallocations. Classical indices of structural change (NAV, Krugman, Shorrocks) are combined with spatio-temporal modelling in ArcGIS Pro, employing Space–Time Cubes, time-series exponential smoothing forecasts, time-series clustering and emerging hot spot analysis. Results indicate that MI distributions are positively skewed and heavy-tailed, with peaks coinciding with systemic crises (2009–2011, 2020). At the 2-digit level, MI values are significantly higher, revealing intra-sectoral changes obscured in aggregated data. A statistically significant downward trend in mobility suggests an increasing structural rigidity following the global financial crisis. Regional clustering highlights heterogeneity: a small number of regions, such as Bremen, Madeira and the Southern Great Plain, have sustained high or unstable mobility, while most exhibit convergent mobility and low reallocation. This paper contributes to the conceptualisation of MI as a dual measure of resilience and innovation preparedness. It underscores the importance of multi-scalar and spatio-temporal methods in monitoring labour market flexibility. The findings have policy implications, including the design of targeted reskilling programmes, proactive labour market policies and just transition plans to maintain regional resilience during the EU’s green and digital transitions. Full article

This paper presents a federated learning (FL) architecture tailored for anomaly detection in wire arc additive manufacturing (WAAM) that preserves data privacy while enabling secure and distributed model training across heterogeneous process units. WAAM’s inherent process complexity, characterized by high-dimensional and asynchronous sensor streams, including current, voltage, travel speed, and visual bead profiles, necessitates a decentralized learning paradigm capable of handling non-identical client distributions without raw data pooling. To this end, the proposed framework integrates reversible data hiding in the encrypted domain (RDHE) for the secure embedding of sensor-derived features into weld images, enabling confidential parameter transmission and tamper-evident federation. Each client node employs a domain-specific long short-term memory (LSTM)-based classifier trained on locally curated time-series or vision-derived features, with model updates embedded and transmitted securely to a central aggregator. Three FL strategies, FedAvg, FedProx, and FedPer, are systematically evaluated against four robust aggregation techniques, including KRUM, Multi KRUM, and Trimmed Mean, across 100 communication rounds using eight non-independent and identically distributed (non-IID) WAAM clients. Experimental results reveal that FedPer coupled with Trimmed Mean delivers the optimal configuration, achieving maximum F1-score (0.912), area under the curve (AUC) (0.939), and client-wise generalization stability under both geometric and temporal noise. The proposed approach demonstrates near-lossless RDHE encoding (PSNR > 90 dB) and robust convergence across adversarial conditions. By embedding encrypted intelligence within weld imagery and tailoring FL to WAAM-specific signal variability, this study introduces a scalable, secure, and generalizable framework for process monitoring. These findings establish a baseline for federated anomaly detection in metal additive manufacturing, with implications for deploying privacy-preserving intelligence across smart manufacturing (SM) networks. The federated pipeline is backbone-agnostic. We instantiate LSTM clients because the sequences are short (five steps) and edge compute is limited in WAAM. The same pipeline can host Transformer/TCN encoders for longer horizons without changing the FL or security flow. Full article

This paper proposes a novel AC side series arc fault (SAF) identification method based on Generalized Lissajous Trajectory (GLT) learning for low-voltage residential circuits. The method addresses challenges in detecting SAFs—characterized by high concealment, random occurrence, and limitations in existing protection devices—by leveraging the Hilbert transform to map current signals into 2D Generalized Lissajous Trajectories. These trajectories amplify key SAF features (e.g., zero-break distortion and random pulses). A ResNet50-based image recognition model achieves high-precision fault detection under specific load types, with a validation accuracy of up to 99.91% for linear loads and 98.93% for nonlinear loads. The algorithm operates within 1.6 ms, enabling real-time circuit breaker tripping. The proposed method achieves higher recognition accuracy with lower computational cost compared to other image-based methods. In this paper, an adjustable load signal modeling approach is proposed to visualize the current signal using GLT and complete the lightweight identification based on ResNet network, which provides new ideas and methods for series arc fault detection. Full article

Research on the Mesozoic–Cenozoic magmatism and the tectonic framework within the Lhasa Terrane is voluminous. However, the sparse documentation of Early Cretaceous magmatism in this region fuels ongoing debate over the prevailing tectonic regime during this time period (i.e., normal subduction vs. flat subduction). The present study investigates the Luerma pyroxenite and Boyun granitoid in the Western Lhasa Terrane through zircon U-Pb dating, whole-rock geochemistry, mineral chemistry, and Sr-Nd-Hf isotopes. The findings date the formation of Luerma pyroxenite at 115 Ma and Boyun granites at 113 Ma to the Early Cretaceous period (115–113 Ma). SiO₂ content of pyroxenite is relatively low (34.27–44.16 wt.%), characterized by an enrichment in large ion lithophile elements (LILEs), light rare earth elements (LREEs), and a depletion in heavy field strength elements (HSFEs), indicative of a metasomatic origin. The εNd (t) and εHf (t) values of the Early Cretaceous ultrabasic rocks range from +2.1 to +2.7 and −0.8 to +10.1, respectively, suggesting their derivation from an enriched mantle source with asthenospheric material incorporation. The Early Cretaceous granodiorites and their mafic enclaves belong to the high-K calc-alkaline series, and show enrichment in LILEs (e.g., Rb, Ba, U, and Th) and depletion in HFSEs (e.g., Nb, Ta, Ti, and Zr). The acidic rocks and their developed mafic enclaves exhibit the geochemical characteristics of trace elements found in island arc magmas. Their εNd (t) values are (−6.0–−5.0), while their εHf (t) values are (−11.7–−1.8); the MMEs εHf (t) values are (−4.1–+0.9). In summary, the Early Cretaceous pyroxenite in the Gangdese Belt originated from a combination of asthenospheric and enriched lithospheric mantle melts, while the granitoids were generated by partial melting of the mantle wedge, a process driven by metasomatism resulting from the slab-derived fluids. At the same time, heat from upwelling mantle-derived melts induced the partial melting of lower crustal materials, leading to the formation of acidic magmas through varying degrees of mixing with basic magmas. This study suggests that Early Cretaceous magmatic activity occurred within a northward subduction setting, characterized by the rotation and fragmentation of the Neo-Tethys oceanic crust. Full article

Digital technology transfer plays a pivotal role in reshaping innovation landscapes and fueling the growth of the digital economy. To investigate this phenomenon, this study draws on data on digital technology transfers from the China National Intellectual Property Administration (CNIPA). Using tools such as Gephi 0.10.1 and ArcGIS 10.8, we construct an inter-city digital technology transfer network and develop a quantitative model to analyse the mechanisms by which it impacts urban digital innovation across multiple geographic scales. The main findings are as follows: (1) The inter-city digital technology transfer network in China forms a “diamond-shaped” spatial structure centred on Beijing, Shanghai, Guangzhou, and Shenzhen, with several regional hubs sustaining its connectivity and organisation. (2) Despite a decline in the proportion of intra-city transfers, the number of participating cities continues to rise, revealing a spatial pattern of diffusion from core cities toward inland provincial capitals. (3) Benchmark regression results show that both inter- and intra-city transfers significantly enhance urban digital innovation capacity, with inter-city transfers exhibiting a more substantial effect than their intra-city counterparts. This finding holds after a series of robustness tests. (4) Heterogeneity analysis, based on categorising cities into higher-tier (municipalities, sub-provincial cities, and provincial capitals) and lower-tier groups, indicates that the effect of digital technology transfer on innovation is more pronounced in lower-tier cities. Full article

The study of vegetation net primary productivity (NPP) is essential in the Yanshan–Taihang Mountain Ecological Conservation Zone (YTECZ). Serving as an ecological security barrier for the Beijing–Tianjin–Hebei region, understanding the spatiotemporal dynamics and drivers of NPP in the YTECZ is fundamental for supporting effective sustainable development policies. Utilizing MODIS NPP, climatic data (temperature and precipitation), and the Human Footprint Index (HFP, a comprehensive metric of anthropogenic pressure), this study employed univariate linear regression, ArcGIS spatial analysis, and the Geographical Detector to investigate the spatiotemporal patterns and drivers of vegetation NPP in the YTECZ from 2004 to 2023 and to project its future trends through time series analysis. Our findings reveal a significant fluctuating upward trend in vegetation NPP over the 21-year period (mean annual increase: 4.58 g C·m⁻²), displaying a distinct spatial gradient characterized by higher values in western and northern sectors relative to eastern and southern areas. The interannual variability of vegetation NPP was primarily dominated by precipitation fluctuation, while its spatial heterogeneity was jointly driven by vapor pressure deficit (VPD) and temperature. Notably, human activities exhibited significant explanatory power on NPP’s spatial pattern, and their interaction with climatic factors (e.g., VPD) resulted in non-linear enhancements. Future projections suggest that the current increasing trend is unlikely to be sustained in the long term, indicating substantial uncertainty in vegetation carbon sequestration patterns. This study provides critical insights into vegetation response mechanisms to global change drivers, offering a scientific foundation for ecological management strategies toward sustainable development in the YTECZ. Full article

In light of the global energy shortage, the development of renewable energy has become increasingly vital. With China’s commitment to achieving “carbon peak and carbon neutrality,” photovoltaic power generation has emerged as a focal point in new energy development. However, DC arc faults in photovoltaic systems pose significant safety hazards, potentially leading to electrical fires. While new detection technologies for DC arc faults in photovoltaic power generation systems have advanced rapidly, the diversity of international standards—such as UL 1699 B, GB/T 39750, IEC 63027, and CGC/GF 175—limits both the construction of experimental platforms and the universality of detection technologies. Current research often relies on a single standard to establish experimental platforms, resulting in detection methods with limited applicability and an inability to validate technological effectiveness fully. To address this issue, this paper conducts an in-depth study of four international and national standards (IEC 63027; UL 1699 B, GB/T 39750, and CGC/GF 175), focusing on the discrepancies in decoupling methods, impedance parameter settings, and experimental circuit topologies, including series and parallel arc scenarios. Through comprehensive comparative analysis of multiple standards, this study integrates major international and domestic specifications to develop a multi-standard compatible experimental platform. The platform is designed to accommodate diverse topologies and parameter requirements, enabling efficient collection of arc test data and performance evaluation of arc fault detection devices. It also provides a standardized foundation for the performance testing and classification of DC arc circuit breakers in photovoltaic power generation systems. Through a comprehensive multi-standard comparative analysis, we systematically analyze the technical differences in photovoltaic DC arc detection. We construct a multi-standard compatible experimental platform by integrating mainstream international and domestic standards. This platform is designed to accommodate various topological structures and parameter requirements, facilitating the collection of arcing experimental data and assessment of the performance of arc fault detection devices. The findings from this research provide both theoretical and experimental foundations for developing unified technical guidelines for photovoltaic DC arc protection. This will aid in standardizing the development of detection devices and enhancing the electrical safety of photovoltaic systems. Ultimately, this work is significant for promoting the safe utilization of new energy within the framework of the dual carbon goals. Moving forward, it is crucial to enhance the generalization abilities of detection algorithms further and foster the integration of standards and industrial applications. Full article

This study examined the trend changes as well as the spatial distribution of average precipitation and the abrupt change characteristics of precipitation in Gannan Prefecture, China, using daily precipitation monitoring data from 1980 to 2021 at eight meteorological stations. Analytical methods employed included the climate change trend rate, anomaly analysis, Innovative Trend Analysis (ITA), ITA-change boxes (ITA-CB), ArcGIS technology, and BEAST Ensemble Algorithm. Long-term average precipitation variability was comprehensively analyzed across multiple temporal scales. Results indicated that over the 42 years, interannual precipitation exhibited a significant increasing trend, with an annual rate of 14.363 mm/decade, and abrupt changes were detected in 1984, 2003, and 2018. The distribution of average precipitation varied substantially from year to year. July was the month with the highest average monthly precipitation, and December was the month with the lowest. Summer precipitation contributed the most to annual totals (51.33%), whereas winter precipitation contributed the least (2.01%). Interdecadal precipitation exhibited a pattern of an initial decrease followed by an increase over the study period. Based on the mean and standard deviation of the series’ first half, which was divided by the ITA method, we established a three-category classification for mean precipitation (low, medium, and high). Annual average and seasonal average precipitation showed non-monotonic variations. While the overall trend of annual average precipitation showed a modest augmentation, the increasing tendencies in the middle-value and high-value categories slowed. In spring, the decreasing trend in high-value categories slowed. In summer, decreasing trends in middle-value categories and overall zones slowed, with an enhanced increasing trend observed in autumn and winter overall. At the spatial scale, the average precipitation across Gannan Prefecture exhibited a decreasing trend from south to north. Higher precipitation was recorded at meteorological stations in the southwest (Maqu), west (Luqu), and south (Diebu), primarily influenced by the interaction between the Qinghai–Tibetan Plateau monsoon and westerly circulation, as well as regional topographic effects. The research findings have significant implications for agricultural and pastoral production planning and sustainable economic development in Gannan Prefecture, China. Full article