Search Results (24,507)

Human-Centered AI (HCAI) has emerged as a guiding paradigm for designing AI systems that align with human values, needs, and well-being, yet the field lacks consensus on what constitutes human-centeredness. This study addresses that gap through a four-phase sequential mixed-methods design: (1) thematic analysis of 81 HCAI definitions from academic, institutional, and industry sources, yielding 78 keywords; (2) frequency-based statistical categorization; (3) expert evaluation producing a final inventory of 26 attributes; and (4) a cross-sectional survey (N = 145), predominantly drawn from the Asia-Pacific region (77.2%, with Myanmar, Singapore, and Thailand most represented), in which practitioners, academics, and students rated each attribute on a 7-point Likert scale, complemented by a reflexive thematic analysis of open-ended responses. The 26-item scale demonstrated excellent internal consistency. Trust, values, benefits, needs, and usability were rated most highly, while affective and cognitive attributes—emotions, behaviours, and empathy—were consistently rated lower, a pattern the qualitative data suggest reflects perceived intractability rather than indifference. Inter-attribute correlations revealed interpretable substructures, including an experience/usability cluster, an emotion/empathy cluster, and a participatory engagement cluster, while human control operated as a conceptually independent dimension. Five qualitative themes provided interpretive context: user needs and augmentation as design drivers, ethical foundations and value alignment, trust as a relational outcome contingent on transparency, the complexity of human experience as a design challenge, and structural barriers including corporate incentives, regulatory gaps, and resource constraints. In this predominantly Southeast Asian sample, all three stakeholder groups showed substantial agreement on which attributes matter most and least. The primary divergence ran between academics and students: academics assigned higher importance to participatory and process-oriented attributes, while students emphasized tangible outcomes. Practitioners occupied an intermediate position, with a distinctive emphasis on ethical values. These findings offer an empirically grounded vocabulary for human-centeredness, positioned as an exploratory foundation for future psychometric refinement, with implications for HCAI design practice, education, and cross-stakeholder dialogue. Full article

Sustainable innovation constitutes the cornerstone of firms’ long-term competitive edge, yet the underlying mechanisms via which patient capital facilitates corporate sustainable innovation remain understudied. Based on a sample of Chinese A-share listed firms spanning 2013 to 2024, this study operationalizes patient capital through two proxies: relational debt and stable institutional ownership. We systematically investigate the impact of patient capital on sustainable innovation, alongside the mediating pathway of internal control quality and the moderating role of climate policy uncertainty. The empirical outcomes indicate that both forms of patient capital exert a significant positive effect on sustainable innovation, with internal control quality serving as a partial mediator in this relationship. Additionally, climate policy uncertainty reinforces the promotional influence of patient capital on sustainable innovation. We further stratify heterogeneity analyses into two dimensions: firm-inherent heterogeneity and external environmental heterogeneity. From the perspective of endogenous firm attributes, the innovation-stimulating effect of patient capital differs markedly across enterprises with distinct ownership types, life-cycle stages, and total asset sizes. Externally, the observed positive impact varies considerably conditional on industrial factor intensity and the regional marketization degree of the firm’s location. These findings expand the existing literature concerning long-term capital and sustainable innovation, and yield actionable implications for corporate management, institutional investors, and policymakers. Full article

Morel detection in agroforestry cultivation scenes remains challenging because soil-background camouflage, illumination variation, and dense clustered growth can lead to missed small targets and false positives in background regions. This study proposes Morel-YOLO, a lightweight morel detection method based on YOLOv13n for agricultural perception. The model retains the original multi-scale feature-fusion framework and introduces three targeted modifications: a StarNet backbone for reducing redundant computation, a DSC3k2_DWRSeg module in the shallow P${}_3$ branch for strengthening fine-grained texture and small-target representation, and a Detect_MBConv head for reducing prediction-branch overhead while preserving detection accuracy. On the test set, Morel-YOLO achieves 91.9% precision, 86.6% recall, 93.6% mAP${}_{50}$, and 70.8% mAP${}_{50--95}$, improving mAP${}_{50--95}$ by 1.3 percentage points over YOLOv13n. The model contains 1.48 M parameters, has a model size of 3.31 MB, and requires 6.2 GFLOPs. On the Small-hard and Dense-hard subsets, mAP${}_{50--95}$ reaches 69.1% and 66.8%, respectively, corresponding to gains of 1.5 and 1.3 percentage points over the baseline. Under IoU = 0.75, both false positives and false negatives are also reduced on the two hard subsets. These results suggest that Morel-YOLO improves the balance among detection accuracy, robustness, and model compactness on the evaluated dataset; however, its practical deployment on embedded agricultural platforms still requires dedicated on-device validation. Full article

Terrain-aided navigation (TAN) enables autonomous positioning through fusing prior terrain databases with real-time sensor measurements in GNSS-denied environments. Typical factors, including wide beam width and terrain elevation variations, introduce inaccuracies in elevation measurements, degrading the performance of classical elevation-based TAN methods. The SAR altimeter operates in nadir-looking mode to acquire range–Doppler projection images with inherent cross-track ambiguity for positioning based on image information, yet its accuracy is limited by single-feature and fixed-grid approaches. In this paper, we introduce an adaptive positioning framework for the SAR altimeter that combines XGBoost-based multi-feature fusion with Bayesian particle filtering. First, a fast DDM template generation algorithm is employed to improve computational efficiency. Then, an ensemble learning framework integrating complementary similarity features is introduced to achieve robust single-frame matching. Additionally, a Bayesian filtering-based dynamic grid construction method is developed to concentrate particles in high-probability regions, eliminating boundary truncation errors inherent to fixed approaches. The proposed method’s primary advantage is the reliable three-dimensional localization under extreme radar configurations, such as wide beam width and high-altitude maneuvering platforms. Experimental results based on both simulated and real data validate the method, demonstrating superior positioning performance under wide-beam conditions. Full article

Industrial contamination can influence the transfer of toxic and essential elements through soil–plant–animal systems and may pose risks to food safety. This study aimed to determine whether contamination patterns in soil are reflected in forage vegetation and meat products and to evaluate trace-element behavior across interconnected components of the soil–plant–animal system. This study assessed the distribution and transfer of 12 elements (As, Be, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, V, and Zn) in soil, forage vegetation, and meat products from five industrially affected areas of Central Kazakhstan. Element concentrations were determined by inductively coupled plasma mass spectrometry. Soil contained the highest concentrations of most elements, confirming its role as the primary reservoir of contamination, whereas forage vegetation reflected local pollution patterns. The highest levels of contamination were generally observed in the industrial centers of Temirtau and Zhezkazgan, with Zhezkazgan exhibiting the most distinct element profile. Soil-to-forage transfer was most pronounced for Cd, Cu, Pb, and Zn, with significant positive relationships between soil and forage concentrations (p < 0.001). Meat products generally contained lower element concentrations than soil and forage; however, Cd, Hg, and As exceeded regulatory limits in 23 of 279 samples (8.2%). By integrating environmental and animal-derived matrices within a single framework, this study provides new insight into trace-element transfer pathways and facilitates the identification of priority contaminants, high-risk areas, and livestock products requiring enhanced environmental and food safety monitoring in industrial regions. Full article

Pinus yunnanensis Franch. is a native pioneer and economically important tree in Yunnan Province in China. In this study, over 1400 annual seedlings were used. Following national or regional official seedling quality standards, seedlings were classified into three grades, namely Grade I, Grade II, and Grade III by using mean ± 1/2 standard deviation method according to the height of seedlings (H ± 1/2σ). Morphological traits including seedling height, ground-line diameter, root length, and root average diameter were measured from September 2022 to December 2023 for each grade. A power-law allometric growth model was constructed, and the standardized major axis method was used to analyze the allometric relationships between plant height and ground-line diameter as well as between root length and root average diameter. The results showed that higher grade seedlings exhibited stronger synergistic plasticity, accelerating allometric growth and enhancing phenotypic plasticity. A significant positive correlation was found between plant height and ground-line diameter growth rates, with ground-line diameter showing greater plasticity. Grade I seedlings demonstrated clear advantages, with mean allometric rates of 0.5860 for plant height versus ground-line diameter and 1.6315 for root length versus root system. The phenotypic plasticity index for ground-line diameter was high across all three grades, but actual thickening varied by grade due to different initial diameters, with Grade I and II seedlings growing much more than Grade III. For plant height, the index ranged from 0.3 to 0.8, with values of 0.6–0.7 for Grade I, 0.3–0.7 for Grade II, and 0.6–0.8 for Grade III. These findings provide a scientific basis for evaluating seedling quality, breeding, reproduction, and improving survival and growth in later-stage afforestation. Full article

To address severe stress concentration, excessive convergence, and instability of the roadside backfill body (RBB) in gob-side entry retaining (GER) under thick and hard roof conditions, this study investigates the control mechanism of main roof fracture position on surrounding rock stability, using the 3⁻¹01 working face of Huoluowan Coal Mine as a case study. A combined approach integrating theoretical analysis, numerical simulation, and field investigation is adopted. A statically indeterminate mechanical model based on masonry beam theory is established to characterize the lateral roof fracture behavior. The deflection and bending moment distributions are derived, and a criterion for fracture position determination is developed based on the maximum bending moment condition. The theoretical results indicate that the natural fracture position is located approximately 9.4–11.2 m inside the gob boundary. Numerical simulations using UDEC Trigon under different fracture positions (−2 m, 1 m, 5 m, and 9 m) show that fracture location significantly affects the mechanical response of GER. Fractures occurring above the roadway or RBB induce large deformation levels and more extensive plastic zones, while gob-side fracture conditions correspond to relatively lower disturbance levels and improved structural stability. The RBB exhibits shear-dominated failure characteristics, and the displacement distribution is non-uniform along height, with larger deformation in the middle-to-upper region. To improve stability, a coordinated control strategy combining anchor cable reinforcement and directional long-distance hydraulic fracturing (HF) is proposed to regulate the main roof fracture position through the formation of artificial weak planes. Field monitoring results show that the maximum displacements of the roof, floor, and ribs are 558 mm, 233.5 mm, and 71.3 mm, respectively, with a convergence ratio of 19.8%. Borehole imaging confirms the development of hydraulic fractures within the designed roof stratum, supporting the effectiveness of the proposed control approach. These results demonstrate that the fracture position of the main roof plays a key role in controlling GER stability, and its regulation provides an effective means for improving roadway performance under complex geological conditions. Full article

Cavitation research is critical for anti-cavitation design of fluid machinery flow components, but the collapse dynamics of cavitation bubbles near common wall types, such as semi-cylindrical grooves, remain unrevealed. In this paper, the morphological evolution, vortex ring evolution, and bubble migration characteristics of the cavitation bubble near a semi-cylindrical groove were investigated by means of dual-view high-speed photography. The results show that (1) when the bubble is located at the symmetric position of the semi-cylindrical groove, four typical vortex ring phenomena appear during its collapse: longitudinal elliptical vortex ring, double-layer elliptical vortex ring, circular vortex ring, and transverse elliptical vortex ring. (2) Longitudinal elliptical vortex rings, the most frequently observed type, are concentrated in regions with small to moderate dimensionless distances. Double-layer elliptical vortex rings and circular vortex rings correspond to moderate and large dimensionless distance intervals, respectively. Transverse elliptical vortex rings tend to form when the bubble has a small dimensionless radius and is located near the groove center, a phenomenon strongly associated with the initial bubble position. (3) When the bubble is located at an asymmetric position, three cases are found, namely, the bubble migrates from the groove to the flat wall, the bubble impacts the flat wall vertically downward, and the bubble migrates from the flat wall to the groove. Full article

This study investigates the processing temperature characteristics and etching behavior of fused silica using an atmospheric pressure microwave plasma jet. The temperature distribution within the processing region was measured in real time via infrared thermography. The effects of microwave input power, argon flow rate, and CF₄ flow rate on the processing temperature were systematically examined using a single-factor approach. Experimental results reveal a strong positive correlation between the plasma temperature and microwave power. The temperature initially rises and then declines with increasing argon flow, peaking at 3 slm, while it increases and eventually stabilizes with higher CF₄ flow. Fixed-point etching demonstrates that the etching rate increases with rising processing temperature. Furthermore, heat accumulation during prolonged dwell time leads to a nonlinear increase in the removal rate. This effect can be effectively mitigated by employing a multi-segment processing strategy, enabling more stable and controllable material removal. The effectiveness of this processing method has also been verified on a fused quartz sub-mirror. Full article

Karst terrains hold vital global groundwater reserves, underpinning regional water security and ecological stability. To elucidate groundwater hydrochemical patterns and formation mechanisms in Wuhan’s karst zone, this study adopted the Gibbs model, correlation analysis, principal component analysis and positive matrix factorization to explore water–rock interactions, hydrochemical origins, element migration, hydrogeochemical facies and genetic processes. The results show that water in both confined porous loose rock aquifers (CPLRAs) and karst fissure carbonate rock aquifers (KFCRAs) is mainly of HCO₃–Ca and HCO₃·SO₄–Ca types. Carbonate dissolution dominates hydrochemical evolution, with Ca²⁺, Mg²⁺, and HCO₃⁻ as major ions. Natural water–rock interactions control the ionic characteristics of both groundwater types. Silicate weathering exerts a greater influence on water in the KFCRA, while water in the CPLRA has more complex ion sources. Anthropogenic activities contribute 17.52% and 17.61% to their hydrochemical variations, suggesting moderate human influence. Water in the CPLRA is mainly affected by domestic sewage and soil organic nitrogen, locally superimposed with industrial and mining disturbances. Water in the KFCRA is primarily influenced by agricultural pollution, with minor domestic sewage input. These findings provide a scientific basis for sustainable development, protection, and targeted pollution control of groundwater resources in the Wuhan karst area, and offer a reference for hydrochemical studies in comparable karst regions. Full article

Background/Objective: Cervical intraepithelial neoplasia grade 2 (CIN2) shows heterogeneous clinical behavior, with substantial rates of spontaneous regression under active surveillance. Reliable molecular biomarkers are needed to distinguish regressive from transforming lesions and reduce overtreatment. We evaluated the prognostic role of host and viral DNA methylation, alone and combined with HPV genotyping, in predicting CIN2 regression. Methods: This subanalysis derives from a prospective, multicenter Italian cohort of women with histologically confirmed CIN2 managed conservatively. Among 319 enrolled women, 134 with single HPV infections and valid host (FAM19A4/miR124-2) and viral (HPV L1 region) methylation results were included. HPV genotyping was performed with partial stratification (HPV16/18 vs. non-16/18). Clinical outcomes at 24 months were classified as regression versus persistence/progression. Logistic regression models assessed associations between biomarkers and regression. Results: At 24 months, 50% of women showed regression. Host and viral methylation positivity rates were more frequent in non-regressive lesions (40.3% vs. 19.4%, p = 0.01, and 52.2% vs. 32.8%, p = 0.02, respectively). Negative host methylation was significantly associated with regression (Odds Ratio OR = 0.37, 95% CI 0.17–0.81, p = 0.02), as was negative viral methylation (OR = 0.47, 95% CI 0.23–0.96, p = 0.04). Conclusions: Both host and viral methylation are inversely associated with CIN2 regression. Combining methylation markers did not substantially improve predictive accuracy; however, methylation negativity emerged as a potential molecular reassurance marker. When integrated with HPV genotyping, the highest probability of regression was observed among women with non-HPV16/18 infections and negative methylation results. These results endorse DNA methylation testing as a molecular tool for the conservative management of CIN2. Full article

Microscopic vision-based alignment measurement is a key procedure in micro-/nanoscale positioning, and its measurement repeatability mainly depends on the stability of subpixel edge–center estimation. However, in practical microscopic imaging, defocus and contamination can cause edge broadening and pseudo-gradient peaks, making it difficult for conventional methods to accurately estimate the edge center of alignment marks. To address this problem, this paper proposes an adaptive edge-response modeling method. First, an amplitude function is constructed by combining the gradient peak and the slope of the edge-transition region, enabling adaptive adjustment of the response amplitude and suppressing its coupling with other parameters. On this basis, the proposed model overcomes the limitation that the Sigmoid model is only suitable for single-edge fitting and enables unified modeling of practical multi-edge hybrid bonding marks. It also suppresses the interference caused by edge pseudo-peaks and abrupt gradient variations, thereby improving the accuracy of subpixel fitting and localization. Experimental results show that, compared with conventional methods, the proposed method improves the repeatability of subpixel edge localization under degraded microscopic imaging conditions by approximately 52%, meeting the requirements of high-precision microscopic vision-based alignment. Full article

Under the “dual carbon” targets, using green finance to support renewable energy use is an important way to reduce extreme climate risks. This study builds a balanced panel dataset of 271 Chinese cities from 2010 to 2021. We measured the level of Green Finance (GF) and renewable energy utilization (RE). Employing two-way fixed effects, the Spatial Durbin Model (SDM), and the Heterogeneous Spatial Autoregressive (HSAR) model, we systematically examine the promoting effects, transmission mechanisms, spatial heterogeneity, and economic–environmental consequences of GF on RE. The empirical results reveal that GF significantly enhances RE and generates pronounced positive spatial spillovers. Mechanism analysis indicates that R&D investment and environmental regulation serve as the primary transmission channels. The promotion effect is more pronounced in the eastern and central regions, as well as in areas with higher R&D investment and stricter environmental regulation, whereas the spatial spillover effect is particularly evident in coastal regions. Further consequence analysis demonstrates that GF contributes to reducing conventional energy intensity, improving green total factor productivity, and alleviating extreme climate events. Building on these findings, this study proposes spatially differentiated and sustainability-oriented policy strategies to advance China’s energy transition and foster coordinated economic and environmental sustainability. Full article

The Yellow River Delta (YRD), a crucial ecotone, is becoming increasingly polluted by antibiotics, posing serious threats to aquatic ecosystems and human health. In this study, comprehensive investigations were conducted to explore the regional distribution, environmental risks, and source apportionment of antibiotics, with the aim of facilitating precise management and control of antibiotic pollution. The results show that the surge in runoff during the water–sediment regulation period (June and August) of the Yellow River drove a sharp rise in antibiotic concentrations in the surface water, peaking at 135.0 ng/L, whereas antibiotics were rarely detected in the sediments after multiple rounds of intense hydraulic scouring (0.2~12.6 ng/g in October). Furthermore, seven antibiotics (sulfadiazine, sulfamethoxazole, flumequine, ofloxacin, tetracycline, doxycycline, and lincomycin) in surface water and six antibiotics (norfloxacin, enrofloxacin, ofloxacin, doxycycline, oxytetracycline, and florfenicol) in sediments were identified as representative compounds according to the antibiotic pollution profiles. Environmental risk assessment coupled with spatial autocorrelation analysis revealed that sulfamethoxazole generally posed medium to high risk (0.12~1.27) in surface water. Sediments posed more serious ecological risks, with universally high risk levels (ranging from 1.11 to 280.00). More importantly, in both surface water and sediment, four core antibiotic sources—namely, human sewage, livestock farming, agricultural and aquaculture inputs, and hydrodynamic-driven resuspension processes—were consistently identified through the Positive Matrix Factorization model and Kriging interpolation. These findings provide crucial insights for establishing targeted antibiotic pollution control strategies in the YRD and advance the understanding of antibiotic fate in sediment-laden rivers. Full article

The Arabian honeybee, Apis mellifera jemenitica, is well adapted to the arid and semi-arid conditions of the Arabian Peninsula. However, little is known about the interactions among climatic conditions, Varroa mite, and honeybee viruses affecting A. m. jemenitica colonies. This study investigated the prevalence of Varroa destructor and major honey bee viruses (DWV, BQCV, SBV, CBPV, ABPV, KBV, IAPV and AIV) in A. m. jemenitica colonies located across arid and semi-arid regions of Saudi Arabia. The results revealed a high prevalence of Varroa infestation and DWV in both climatic zones. The other viruses (BQCV, SBV, CBPV, ABPV, KBV, IAPV and AIV) showed significant spatial variation in prevalence across the surveyed regions. Varroa infestation levels were generally low and significantly higher in semi-arid environments compared to arid regions (p < 0.001). Mean regional DWV loads (copies/bee) were consistently low across all A. m. jemenitica colonies (6.8 × 10² to 4.4 × 10³ copies/bee), were positively linked with Varroa infestation levels (R² = 0.63), and demonstrated significant variation among climatic zones (p < 0.001). Virus co-occurrence analysis using Phi (ϕ) coefficients revealed structured viral communities, with several virus pairs exhibiting moderate to strong positive associations. Overall, this study highlights the low DWV loads in A. m. jemenitica colonies, and the impact of climate conditions on Varroa mite–virus interactions in shaping honeybee health under arid and semi-arid conditions. Full article