Search Results (119)

In the context of the global dual-carbon goals and China’s DP strategy, strengthening the coupling between digital productivity (DP) and the high-quality development of the energy industry (HQDEI) is essential for resource-based regions. Doing so can help these regions overcome transition constraints and advance green, low-carbon development. Using panel data for nine prefecture-level cities in Guizhou Province from 2014 to 2023, we construct composite indices for DP and HQDEI with an improved entropy-weight TOPSIS approach. We then characterize their spatiotemporal evolution using a coupling coordination degree (CCD) model and kernel density estimation. Finally, we examine the determinants of coupling coordination through panel regression and threshold models. The results show that: (1) The CCD between DP and HQDEI efficiency continues to increase, with regional differences displaying a periodic convergence–divergence pattern and a spatial structure characterized by core agglomeration and outward diffusion. Gradient disparities in coordinated development are evident between central and peripheral areas. (2) Consumption upgrading and fiscal self-sufficiency significantly promote CC, whereas a traditional resource-dependent growth model significantly suppresses it. Constrained by short-term adaptation and integration costs, digital innovation currently exerts a negative effect, and its enabling potential has not yet been fully realized. (3) Nonlinear tests identify a single digital-infrastructure threshold: the enabling effect of digital innovation turns positive only once infrastructure surpasses a critical level, revealing pronounced interval heterogeneity. This study advances the theoretical understanding of the bidirectional coupling between DP and HQDEI, provides empirical guidance for energy digital transformation and high-quality development in resource-based regions of western China, and offers transferable insights for green, low-carbon transitions in traditional energy regions worldwide. Full article

Cellulose paper, a natural polymeric dielectric, determines the lifetime of oil–paper insulation systems in transformers, yet its molecular degradation behavior in ester-based insulating media remains insufficiently clarified. This study investigates the electro–thermal aging of cellulose polymer immersed in soybean-based natural ester (SBNE) and palm fatty acid ester (PFAE), with emphasis on depolymerization and its relationship with partial discharge (PD) activity. Accelerated aging experiments were conducted under combined electrical and thermal stress, and the evolution of the degree of polymerization (DP) was measured to quantify polymer chain scission. Phase-resolved PD (PRPD) patterns were recorded during aging, and multi-dimensional statistical features were extracted and reduced using principal component analysis to characterize degradation-sensitive electrical responses. The results show a progressive decrease in DP with aging time in both ester media, accompanied by distinct PD evolution characteristics, indicating different influences of the two esters on cellulose polymer stability. An ensemble learning model integrating multiple classifiers was further employed to identify aging stages based on PD features, achieving reliable discrimination performance. These findings establish a correlation between cellulose depolymerization and dielectric discharge behavior, providing a polymer-centered interpretation of aging mechanisms in ester-based oil–paper insulation systems. Full article

The topology identification (TI) of low-voltage distribution networks (LVDNs) is the foundation for their intelligent operation and lean management. However, the existing identification methods may produce inconsistent results under measurement noise, missing data, and heterogeneous load behaviors. Without principled multiple method fusion and meter-level confidence quantification, the reliability of the identification results is questionable in the absence of ground-truth topology. To address these challenges, a confidence-aware TI (Ca-TI) method for the LVDN based on weakly supervised learning (WSL) and Dempster–Shafer (D-S) evidence theory is proposed, aiming to infer each meter’s latent topology connectivity label and quantify the meter-level confidence without ground truth by fusing different identification methods. Specifically, within the framework of data programming (DP) in WSL, different TI methods were modeled as labeling functions (LFs), and a weakly supervised label model (WSLM) was adopted to learn each method’s error pattern and each meter’s posterior responsibility; within the framework of D-S evidence theory, an uncertainty-aware basic probability assignment (BPA) was constructed from each meter’s posterior responsibility, with posterior uncertainty allocated to ignorance, and was further discounted according to the missing data rate; subsequently, a consensus-calibrated conflict-gated (CCCG)-enhanced D-S fusion rule was proposed to aggregate the TI results of multiple methods, producing the final TI decisions with meter-level confidence. Finally, the test was carried out in both simulated and actual low-voltage distribution transformer areas (LVDTAs), and the robustness of the proposed method under various measurement noise and missing data was tested. The results indicate that the proposed method can effectively integrate the performances of various TI methods, is not adversely affected by extreme bias from any single method, and provides the meter-level confidence for targeted on-site verification. Further, an engineering deployment scheme with cloud–edge collaboration is further discussed to support scalable implementation in utility environments. Full article

High-performance difference patterns (DPs) are critical for compact and integrated microwave array systems, particularly in monopulse tracking and beam-scanning applications. However, the design of monopulse phased arrays with steep slopes, high directivity, low sidelobes, and symmetric main lobes remains challenging due to constraints imposed by the array aperture and radome structure. In this paper, a novel design method is proposed to maximize the DP directivities for monopulse linear and planar phased arrays composed of microstrip patch antennas. The DP synthesis problem is first formulated as a nonconvex optimization model for directivity maximization. By fixing the reference phase of the DP slope and applying a first-order Taylor expansion of the quadratic function, the original problem is decomposed into a sequence of convex subproblems that can be solved efficiently. The proposed method fully exploits the flexibility of the phased array feed network, enabling directivity enhancement without altering the geometric configuration of the monopulse array. Finally, three numerical examples employing a radome-enclosed linear array, a uniform planar array, and a radome-enclosed planar array are presented to demonstrate the effectiveness of the proposed method in achieving the monopulse array DP synthesis with high directivity and symmetric main lobes. Full article

Background: Although Ki-67 is not included among the grading criteria in the current WHO Classification of Tumours of the Central Nervous System (CNS), it provides valuable, albeit limited, prognostic information. Immunohistochemistry for Ki-67 can reveal uneven proliferation patterns and assist in the assessment of mitotic counts. Several studies indicate that meningiomas with a proliferation index > 4% show recurrence rates comparable to CNS WHO grade 2 (atypical) tumors, while tumors with an index > 20% are associated with mortality rates similar to CNS WHO grade 3 (anaplastic) meningiomas. Issues related to Ki-67 assessment include interobserver variability, the use of different cut-off values among pathologists, and the presence of a complex inflammatory tumour microenvironment, which may lead to an overestimation of the proliferative index (PI). Methods: In this study, we describe how Double Staining Immunohistochemistry (dIHC) with EMA/Ki-67 better highlights neoplastic meningothelial cells compared with single-stain evaluation. Furthermore, the application of Digital Pathology provides quantitative digital data that allow a more accurate assessment of proliferation. Results: Ki-67 expression varied by grade, with digital image analysis (dIHC) showing high agreement with manual assessments. dIHC improved accuracy in evaluating diagnostic and proliferative markers within tumor samples. Conclusions: dIHC combined with DP can support and standardize the evaluation of the proliferative index in meningiomas in routine diagnostic practice. Full article

Persistent organic pollutants (POPs) are globally distributed toxic contaminants. Since 1990, mosses have been used in the UNECE European Moss Survey as cost-effective biomonitors of atmospheric deposition. This study provides the first predictive maps of POP concentrations in mosses, revealing nationwide contamination patterns across Germany. As a case study within the Moss Survey, predictive models were built from POP concentrations measured at 21 sites in 2020 and combined with environmental and land-use data. Random Forest analyses explained more than 20% of the variance for seven of eleven POP groups, yielding robust spatial estimates, particularly for PAH, BDE 209, and DBDPE, despite moderate systematic differences. Explanatory power was limited for PCDD/F, PCDD/F TEQ values, DPTE, and HBBz, while HBCD, PBDE, DP, and PBT showed a moderate performance. A comparison with geostatistical reference maps indicated moderate to good concordance, though regional uncertainties persisted. Industrialized regions such as North Rhine–Westphalia, Rhine Neckar, Halle/Leipzig, and Saarland emerged as consistent hotspots, whereas rural and forested areas showed lower contamination. The findings highlight the value of moss surveys for spatial POP assessment and underscore the need for additional predictors, especially atmospheric deposition, and for integrating Random Forest models with geostatistical approaches such as regression kriging to enhance predictive accuracy. Full article

Land-use change strongly affects soil microbiota, yet the role of agroecological systems in shaping soil fungal communities remains poorly understood in tropical soils. We evaluated the diversity, trophic modes, community composition, and co-occurrence networks of culturable soil fungal taxa across a land-use gradient in the Colombian Andes–Amazon transition zone. Agroecological systems—including improved pasture (IP), cacao and copoazu agroforestry systems (CaAS and CoAS), secondary forest with agroforestry enrichment (SFAE), and a moriche palm swamp ecosystem (MPSE)—were compared with dominant land-uses (degraded pasture, DP and old-growth forest, OF). Fungi were isolated using the soil dilution plate method and identified based on morphological and molecular characteristics, and soil physicochemical properties were measured to evaluate their relationships with fungal community patterns. A total of 420 isolates were assigned to 93 fungal species. Alpha-diversity metrics revealed significantly higher fungal richness in OF and MPSE, and higher Shannon diversity in agroforestry and forest-based systems, whereas DP exhibited the lowest values. Ordination analyses showed clear differences in fungal community composition, with CoAS displaying the most distinct assemblage. Agroecological and forest-based systems favored saprotrophic and symbiotrophic modes. Co-occurrence network analyses indicated that MPSE, OF, and IP supported more complex and modular fungal networks. Soil pH and total phosphorus (TP) were key drivers of fungal community composition, whereas exchangeable calcium, TP, soil organic carbon, and base saturation were associated with network attributes. Overall, our findings highlight the importance of agroecological management for soil fungal diversity and network organization in Amazonian transition landscapes. Full article

This study presents a near-real-time water stress monitoring framework for tropical heterogeneous landscapes by integrating optical and radar remote sensing data within the Google Earth Engine platform. Five complementary indices, vertical transmit/vertical receive–vertical transmit/horizontal receive (VV/VH) ratio, Dual Polarimetric Radar Vegetation Index (DpRVI), Normalized Difference Water Index (NDWI), Normalized Difference Moisture Index (NDMI), and Ratio Drought Index (RDI), were analyzed across three contrasting agricultural systems: paddy, sugarcane, and rubber, revealing distinct phenological and water stress dynamics. Radar-derived structural indices captured patterns of biomass accumulation and canopy development, with VV/VH values ranging from 4.2 to 12.3 in paddy and 5.4 to 6.0 in rubber. In parallel, optical moisture indices detected crop physiological stress; for instance, NDMI dropped from 0.26 to 0.06 during drought in sugarcane. Cross-index analyses demonstrated strong complementarity; synchronized VV/VH and RDI peaks characterized paddy inundation, whereas lagged NDMI–VV/VH responses captured stress-induced defoliation in rubber trees. Temporal profiling established crop-specific diagnostic signatures, with DpRVI peaking at 0.75 in paddy, gradual RDI decline in sugarcane, and NDMI values of 0.2–0.3 in rubber. The framework provides spatially explicit, temporally continuous, and cost-effective monitoring to support irrigation, drought early warning, and agricultural planning. Multi-year validation and field-based calibration are recommended for operational implementation. Full article

To address the ‘mechanical’ return to original lane and similar non-humanized lane-changing issues that may occur in existing intelligent driving systems after completing overtaking maneuvers, this study proposes a humanized lane-changing decision method that incorporates driving style characteristics. First, based on the NGSIM dataset, we employ cluster analysis to systematically dissect human drivers’ lane-changing behavior patterns, laying the theoretical foundation for constructing a human-like decision framework. Second, a game model is established to precisely represent diverse driving styles by adjusting the weights of safety, efficiency, and comfort objectives. A reference line dynamic switching mechanism is then proposed to optimize lane-change paths by integrating vehicle speed and safety distance. Joint simulation results demonstrate superiority over dynamic programming (DP) methods in multiple aspects: under conservative driving mode, dual safety thresholds for following distance and speed significantly enhance safety and reliability. In general driving mode, driving stability and smoothness improved by 2.64% and 75.28%, respectively; in aggressive driving mode, lane-change speed increased by 7.06%. These improvements demonstrate that the human-like lane-changing strategy can autonomously achieve the optimal dynamic balance between safety, comfort, and efficiency tailored to different driving styles, providing an effective pathway for constructing high-performance autonomous driving decision systems. Full article

The automation of concrete constructions through 3D printing (3DP) has been increasingly developed and adopted in civil engineering due to its promising advantages over traditional construction methods. However, widespread implementation is hindered by uncertainties in quality control, homogeneity, and interlayer bonding, as well as the uniqueness of each printed component. Building upon our prior work in developing 3D-printable self-sensing cementitious materials by incorporating graphite powder and carbon microfibers into a cementitious matrix to enhance its piezoresistive properties, this study aims at enabling condition assessment of cementitious 3DP by integrating the self-sensing materials as sensing nodes within conventional components. Three different 3D-printed strip patterns, consisting of one, two, and three strip lines that mimic the pattern used in fabricating foil strain gauges were investigated as conductive electrode designs to impart strain sensing capabilities, and characterized from a series of quasi-static and dynamic tests. Results demonstrate that the three-strip design yielded the highest sensitivity (${\lambda }_{\mathrm{stat}}$ of 669, ${\lambda }_{\mathrm{dyn}}$ of 630), whereas the two-strip design produced the highest signal quality (SNR_stat = 9.5 dB, SNR_dyn = 10.8 dB). These findings confirm the feasibility of integrating 3D-printed self-sensing cementitious materials through hybrid manufacturing, enabling monitoring of print quality, detection of load path changes, and identification of potential defects. Full article

This paper revisits the cross-reference marking system of Mbyá Guaraní, focusing on two phenomena: object agreement using the prefix i- and its allomorphs, and absolutive cross-reference marking in converbs. The analysis demonstrates that cross-reference marking in Mbyá is sensitive to abstract Case. Building on a view of agreement as an obligatory operation whose failure does not result in ungrammaticality, this paper argues that the segment i- is an object agreement prefix, rather than part of an allomorph of an active subject agreement prefix. This marker is underspecified for person, allowing it to cross-reference 1st, 2nd or 3rd objects. The paper further argues that converbs in Mbyá Guaraní follow an absolutive cross-reference marking pattern, where only intransitive subjects or objects are cross-referenced. This pattern is shown to be consistent with cross-linguistic and historical data from the Tupí–Guaraní family. This paper’s contributions include a proposal for case-sensitive agreement in Mbyá, with active agreement prefixes realizing agreement with nominative DPs only. The analysis also emphasizes the different roles of Infl and little v as probes for person features, with little v being underspecified and not triggering cyclic expansion. The proposed framework accounts for both hierarchical cross-reference marking in independent clauses and absolutive marking in converbs, unifying these two patterns under the assumption of Case dependence of agreement. Full article

An in vitro study evaluated the fracture resistance of four CAD/CAM restorative materials: lithium disilicate ceramic (IPS e.max CAD, EM), hybrid ceramic (Vita Enamic, VE), a polymer-based composite (Cerasmart, CS), and a novel 3D-printed resin (Ceramic Crown, CC) fabricated using digital press stereolithography (DPS) technology. Standardized full-coverage crowns were designed and manufactured for each material. All specimens underwent thermocycling and fracture testing using a universal testing machine. EM exhibited the highest fracture resistance (mean: 440.49 N), while VE showed the lowest (173.82 N). CS (265.49 N) and CC (306.76 N) presented intermediate values without statistically significant differences between them. Stereomicroscopic analysis revealed differences in fracture patterns, with IPS e.max CAD showing smooth, brittle fractures, while hybrid and polymer-based materials exhibited tortuous fracture surfaces. These results suggest that DPS technology achieves mechanical performance for Ceramic Crown comparable to that of milled polymer-based composites, while offering production advantages in terms of time efficiency. As one of the first studies to evaluate Ceramic Crown and DPS technology, these findings provide initial insights into their mechanical behavior. However, further studies are required to validate their clinical performance before widespread use can be recommended. Full article

Achieving accurate fit in implant-supported prostheses is critical for avoiding mechanical complications; however, the influence of digital manufacturing techniques and abutment designs on misfit and preload remains unclear. This study evaluated the impact of different manufacturing techniques (CAD-cast and 3D printing) and abutment connection types (engaging [E], non-engaging [NE]) on the misfit and preload of implant-supported cantilevered fixed dental prostheses (ICFDPs). Misfit was measured at six points using scanning electron microscopy, and preload was assessed via eight strain gauges placed buccally and lingually on four implants. Frameworks were torqued to 35 Ncm, retorqued after 10 min, and subjected to 200,000 cycles of loading. Mean preload values ranged from 173.4 ± 79.5 Ncm (PF) to 330 ± 253.2 Ncm (3DP). Preload trends varied depending on the abutment type and manufacturing technique, with the 3DP group showing higher preload in engaging (E) abutments, whereas the CAD-cast group showed the opposite pattern. Although preload values varied numerically, these differences were not statistically significant (p = 0.5). In terms of misfit, significant differences were observed between groups (p < 0.05), except between CAD-cast E (86.4 ± 17.8 μm) and 3DP E (84.1 ± 19.2 μm). Additionally, E and NE abutments showed significant differences in misfit within both CAD-cast and 3DP groups. Overall, 3DP frameworks showed superior fit over CAD-cast. These findings suggest that 3DP may offer improved clinical outcomes in terms of implant–abutment fit. Full article

This study investigated the effects of different doses of thiamine diphosphate (ThDP) on methane reduction and fermentation characteristics of Korean native cow (Hanwoo). In vitro trials used ThDP powder at 240, 360, 480, 600, and 720 ppm of substrate, with each sample incubated at 39 °C for 24 and 48 h. After incubation, each sample was analyzed for total gas, methane production, dry matter digestibility, and rumen fermentation characteristics. Mean comparisons were performed using Tukey’s test, with significant differences declared at p < 0.05. Total gas production, methane ratio, and methane production per digested dry matter had a quadratic pattern (p < 0.001), and the 480 ppm treatment had the lowest (p < 0.05) at 24 and 48 h of incubation. Total volatile fatty acid concentration showed no significant difference at 24 h but differed significantly at 48 h (p > 0.05). The concentration of propionate had a quadratic pattern (p < 0.001), and the 480 ppm treatment showed the highest levels compared to the other treatments (p < 0.05) after 24 and 48 h of incubation. In conclusion, ThDP supplementation had a methane inhibition effect. In particular, the methane inhibition effect was most pronounced when ThDP was supplemented at 480 ppm. Full article

Nitrogen (N) and phosphorus (P) losses from sloping agricultural lands through runoff are a significant environmental concern, yet their transport mechanisms across different slope gradients are not well understood. Therefore, we built an experimental site in a subtropical hilly region of China to explore the patterns of nitrogen and phosphorus loss in tea plantations under typical slopes. We set two slope gradients of 20° and 30°, with three plots for each gradient. We quantified the loss of nitrogen (N) and phosphorus (P) through surface flow and interflow on these two slope gradients. We also collected meteorological data through the meteorological station we built. A total of 17 rainfall events were recorded. Results showed that total nitrogen (TN) and phosphorus (TP) concentrations in surface flow on the 30° slope were 8.9% and 31.6% higher, respectively, than on the 20° slope. In interflow, the differences were even more pronounced, with TN and TP concentrations 68.5% and 218.1% higher on the 30° slope. Overall nutrient loss loads (combining surface and interflow pathways) were significantly greater on the steeper slope, with TN and TP loss loads being 2.58 and 3.43 times higher on the 30° slope than on the 20° slope. The composition analysis revealed that dissolved nitrogen (DN) dominated nitrogen transport, accounting for 68.6% of TN in surface flow and 97.8% in interflow, while dissolved phosphorus (DP) represented 35.0% of TP in surface flow and 57.0% in interflow. Initially, TN and TP concentrations in surface flow were high and decreased as runoff generation time increased. Correlation analysis showed that higher temperatures increased TN and TP concentrations in surface flow. On the 30° slope, increased soil moisture promoted higher concentrations of soluble P. Instantaneous rainfall intensity was significantly correlated with TN and TP concentrations in surface flow under both slope gradients. This study revealed N and P loss patterns in tea gardens on steeper slopes, offering guidance for controlling nutrient loss in sloping farmland. Full article