Search Results (12,001)

Observing building changes in remote sensing images plays a crucial role in monitoring urban development and promoting sustainable urbanization. Mainstream change detection methods have demonstrated promising performance in identifying building changes. However, buildings have large intra-class variance and high similarity with other objects, limiting the generalization ability of models in diverse scenarios. Moreover, most existing methods only detect whether changes have occurred but ignore change types, such as new construction and demolition. To address these issues, we present a building change-type detection network (BCTDNet) based on the Segment Anything Model (SAM) to identify newly constructed and demolished buildings. We first construct a dual-feature interaction encoder that employs SAM to extract image features, which are then refined through trainable multi-scale adapters for learning architectural structures and semantic patterns. Moreover, an interactive attention module bridges SAM with a Convolutional Neural Network, enabling seamless interaction between fine-grained structural information and deep semantic features. Furthermore, we develop a change-aware attribute decoder that integrates building semantics into the change detection process via an extraction decoding network. Subsequently, an attribute-aware strategy is adopted to explicitly generate distinct maps for newly constructed and demolished buildings, thereby establishing clear temporal relationships among different change types. To evaluate BCTDNet’s performance, we construct the JINAN-MCD dataset, which covers Jinan’s urban core area over a six-year period, capturing diverse change scenarios. Moreover, we adapt the WHU-CD dataset into WHU-MCD to include multiple types of changing. Experimental results on both datasets demonstrate the superiority of BCTDNet. On JINAN-MCD, BCTDNet achieves improvements of 12.64% in IoU and 11.95% in F1 compared to suboptimal methods. Similarly, on WHU-MCD, it outperforms second-best approaches by 2.71% in IoU and 1.62% in F1. BCTDNet’s effectiveness and robustness in complex urban scenarios highlight its potential for applications in land-use analysis and urban planning. Full article

This paper examines the effectiveness of government subsidies in fostering innovation among small and medium-sized enterprises (SMEs), with a particular focus on additionality, crowding-out, and cherry-picking effects. Using the latest national survey data on Chinese high-tech SMEs, we apply robust econometric techniques—including the Heckman selection model, structural equation modeling (SEM), and propensity score matching (PSM)—to address potential selection bias and endogeneity. Our findings reveal that government subsidies positively influence both innovation inputs and outputs, suggesting a predominant additionality effect rather than a crowding-out effect, at least within high-tech SMEs. However, subsidies do not appear to alleviate the financial constraints faced by most SMEs, indicating that they are insufficient as a standalone solution to financing challenges. Furthermore, state ownership enhances input additionality but does not significantly impact output additionality. We also find evidence of cherry-picking in subsidy allocation, with loans exhibiting stronger additionality effects on innovation compared to grants and tax credits, which are more prone to selective intervention. These findings highlight the need for more targeted subsidy policies that prioritize financially constrained firms with high innovation potential while mitigating government selectivity. Our study offers valuable insights for policymakers seeking to design more effective innovation support mechanisms for high-tech SMEs. Full article

To evaluate water pollution status and sustainable development potential in the Huai River Basin, this study focused on the spatiotemporal evolution and influencing factors of the grey water footprint (GWF) across 35 cities in the basin from 2005 to 2020. This study quantifies the GWF from agricultural, industrial, and domestic perspectives and analyzes its spatial disparities by incorporating spatial autocorrelation analysis. The Tapio decoupling model was applied to explore the relationship between pollution and economic growth, and geographic detectors along with the STIRPAT model were utilized to identify driving factors. The results revealed no significant global spatial clustering of GWF in the basin, but a pattern of “high in the east and west, low in the north and south” emerged, with high-value areas concentrated in southern Henan and northern Jiangsu. By 2020, 85.7% of cities achieved strong decoupling, indicating improved coordination between the environment and economy. Key driving factors included primary industry output, crop sown area, and grey water footprint intensity, with a notable interaction between agricultural output and grey water footprint intensity. The quantitative analysis based on the STIRPAT model demonstrated that seven factors, including grey water footprint intensity and total crop sown area, exhibited significant contributions to influencing variations. Ranked by importance, these factors were grey water footprint intensity > total crop sown area > urbanization rate > population size > secondary industry output > primary industry output > industrial wastewater discharge, collectively explaining 90.2% of the variability in GWF. The study provides a robust scientific basis for water pollution control and differentiated management in the river basin and holds significant importance for promoting sustainable development of the basin. Full article

During large-scale pavement construction, the preparation of SBS-modified asphalt typically produces large amounts of harmful fumes. The emergence of deodorants can effectively alleviate the problem of smoke emissions during the asphalt manufacturing process. On the basis of ensuring the original road performance, exploring more suitable dosages and types of deodorant is urgently needed. Five commercial deodorants were evaluated using an asphalt smoke collection system, and UV-visible spectrophotometry (UV) was employed to screen the deodorants based on smoke concentration. Gas chromatography–mass spectrometry (GC-MS) was used to quantitatively analyze changes in harmful smoke components before and after adding two deodorants. Subsequently, the mechanisms of action of the two different types of deodorants were analyzed microscopically using fluorescence microscopy. Finally, the performance of bitumen and asphalt mixtures after adding deodorants was evaluated. The results showed that deodorant A (reactive type) and D (adsorption type) exhibited the best smoke suppression effects, with optimal addition rates of 0.6% and 0.5%, respectively. Deodorant A reduced benzene homologues by nearly 50% and esters by approximately 40%, while deodorant D reduced benzene homologues by approximately 70% and esters by approximately 60%, without producing new toxic gases. Both deodorants had a minimal impact on the basic properties of bitumen and the road performance of asphalt mixtures, with all indicators meeting technical specifications. This research provides a theoretical basis for the effective application of deodorants in the future, truly enabling a transition from laboratory research to large-scale engineering applications in the construction of environmentally friendly roads. Full article

Biothiols, including cysteine (Cys), homocysteine (Hcy), and glutathione (GSH), are crucial for physiological regulation and their imbalance poses severe health risks. Herein, we developed a pH-responsive liquid crystal (LC)-based sensing platform for detection of biothiols by doping 4-n-pentylbiphenyl-4-carboxylic acid (PBA) into 4-n-pentyl-4-cyanobiphenyl (5CB). Urease catalyzed urea hydrolysis to produce OH⁻, triggering the deprotonation of PBA, thereby inducing a vertical alignment of LC molecules at the interface corresponding to dark optical appearances. Heavy metal ions (e.g., Hg²⁺) could inhibit urease activity, under which condition LC presents bright optical images and LC molecules maintain a state of tilted arrangement. However, biothiols competitively bind to Hg²⁺, the activity of urease is maintained which enables the occurrence of urea hydrolysis. This case triggers LC molecules to align in a vertical orientation, resulting in bright optical images. This pH-driven reorientation of LCs provides a visual readout (bright-to-dark transition) correlated with biothiol concentration. The detection limits of Cys/Hcy and GSH for the PBA-doped LC platform are 0.1 μM and 0.5 μM, respectively. Overall, this study provides a simple, label-free and low-cost strategy that has a broad application prospect for the detection of biothiols. Full article

When faults occur in transmission lines of grid-forming PV systems, the LVRT control and virtual impedance function cause the fault characteristics of grid-forming inverters to differ significantly from those of synchronous generators, which deteriorates the performance of existing protection schemes. To address this issue, this paper analyzes the fault characteristics of PV transmission lines under grid-forming control objectives and the adaptability of traditional current differential protection. Subsequently, a novel pilot protection based on the Jensen–Shannon distance is proposed for transmission line of grid-forming PV systems. Initially, the post-fault current samples are modeled as discrete probability distributions. The Jensen–Shannon distance algorithm quantifies the similarity between the distributions on both line ends. Based on the calculated distance results, internal and external faults are distinguished, optimizing the performance of traditional waveform-similarity-based pilot protection. Simulation results verify that the proposed protection reliably identifies internal and external faults on the protected line. It demonstrates satisfactory performance across different fault resistances and fault types, and exhibits strong noise immunity and synchronization error tolerance. In addition, the proposed pilot protection is compared with the existing waveform-similarity-based protection schemes. Full article

Every year, a billion tires are discarded worldwide, with only a small percentage being recycled. This leads to significant environmental hazards, such as fire risks and improper disposal. Silty sand also presents technical challenges due to its poor shear strength, susceptibility to erosion, and low permeability. This study explores the incorporation of crumb rubber derived from waste tires into silty sand to enhance its mechanical properties. Crumb rubber particles of varying sizes (3–6 mm, 5–10 mm, and 10–20 mm) were mixed with silty sand at 0%, 3%, 6%, and 9% percentages, respectively. Triaxial compression tests of unconsolidated and consolidated undrained tests with cell pressures of 100, 300, and 500 kPa were conducted. The deviatoric stress, shear stress, and stiffness modulus were investigated. The results revealed that the addition of crumb rubber significantly increased the deviatoric and shear stresses, especially at particle sizes of 5–10 mm, with contents of 3%, 6%, and 9%. Additionally, the stiffness modulus was notably reduced in the mixture containing 6% crumb rubber tire. These findings suggest that incorporating crumb rubber tires into silty sand not only improves silty sand performance but also offers an environmentally sustainable approach to tire waste recycling, making it a viable strategy for silty sand stabilization in construction and geotechnical engineering performance. Full article

Studying the impact of different tillage practices on crop water consumption can help us identify optimal tillage practice choices. The traditional tillage (TT) and conservation tillage (CT) methods are the dominant practices in Jilin Province, China. Few studies have explored the differences in crop water consumption between TT and CT. To address this knowledge gap, this study utilized maize as its research object and employed the water footprint (WF) as the indicator to assess crop water consumption under TT and CT. This study aimed to investigate when differences in water consumption between TT and CT appear and whether the differences are significant. The results of this study demonstrated that the total WF under CT (339.65 m³ t⁻¹) was less than that under TT (378.19 m³ t⁻¹), and the spatial difference was distinct. The total WF exhibited a clear change under different CT durations. At the initial stage of CT implementation, the total WF decreased slightly compared to that under TT. With an increase in CT duration, the total WF was significantly reduced. The findings of this study demonstrate that CT is an effective measure to ensure sustainable crop production and that it could lead policymakers to choose CT to reduce water consumption. Full article

A series of Cu-MnO_x/GF catalytic electrodes, with graphite felt (GF) pretreated via microwave modification as the catalyst carrier, were prepared under various hydrothermal conditions and characterized using X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), X-ray photoelectron spectroscopy (XPS), N₂ adsorption–desorption, and Raman spectroscopy. The catalytic oxidation activity of catalytic Cu-MnO_x/GF electrodes toward toluene was evaluated in an all-solid-state electrocatalytic device under mild operating conditions. The evaluation results demonstrated that the microwave-modified catalytic electrode exhibited high electrocatalytic activity toward toluene oxidation, with Cu-MnO_x/700W-GF exhibiting significantly higher catalytic activity, indicating that an increase in catalyst loading capacity can promote the removal of toluene. Only CO₂ and CO were detected, with no other intermediates observed in the reaction process. Moreover, the catalytic effect was significantly affected by the relative humidity. The catalytic oxidation of toluene can be fully realized under a certain humidity, indicating that the conversion of H₂O to strongly oxidizing ·OH on the catalytic electrode is a key step in this reaction. Full article

In the field of deep learning, the design of optimization algorithms and neural network structures is crucial for improving model performance. Recent advances in medical image analysis have revealed that many pathological features exhibit fractal-like characteristics in their spatial distribution and morphological patterns. This observation has opened new possibilities for developing fractal-inspired deep learning approaches. In this study, we propose the following: (1) a novel Region-Module Adam (RMA) optimizer that incorporates fractal-inspired region-weighting to prioritize areas with higher fractal dimensionality, and (2) an ECA-Enhanced Shuffle MobileNet (ESM) architecture designed to capture multi-scale fractal patterns through its enhanced feature extraction modules. Our experiments demonstrate that this fractal-informed approach significantly improves classification accuracy compared to conventional methods. On gastrointestinal image datasets, the RMA algorithm achieved accuracies of 83.60%, 81.60%, and 87.30% with MobileNetV2, ShuffleNetV2, and ESM networks, respectively. For glaucoma fundus images, the corresponding accuracies reached 84.90%, 83.60%, and 92.73%. These results suggest that explicitly considering fractal properties in medical image analysis can lead to more effective diagnostic tools. Full article

The green renovation of existing residential buildings is a key way for the construction industry to achieve sustainable development and the dual carbon goals of China, which makes it urgent to make collaborative decisions among multiple stakeholders. However, because of divergent interests and risk perceptions among governments, energy service companies (ESCOs), and owners, the implementation of green renovation is hindered by numerous obstacles. In this study, we integrated prospect theory and evolutionary game theory by incorporating core prospect-theory parameters such as loss aversion and perceived value sensitivity, and developed a psychologically informed tripartite evolutionary game model. The objective was to provide a theoretical foundation and analytical framework for collaborative governance among stakeholders. Numerical simulations were conducted to validate the model’s effectiveness and explore how government regulation intensity, subsidy policies, market competition, and individual psychological factors influence the system’s evolutionary dynamics. The findings indicate that (1) government regulation and subsidy policies play central guiding roles in the early stages of green renovation, but the effectiveness has clear limitations; (2) ESCOs are most sensitive to policy incentives and market competition, and moderately increasing their risk costs can effectively deter opportunistic behavior associated with low-quality renovation; (3) owners’ willingness to participate is primarily influenced by expected returns and perceived renovation risks, while economic incentives alone have limited impact; and (4) the evolutionary outcomes are highly sensitive to parameters from prospect theory, The system’s evolutionary outcomes are highly sensitive to prospect theory parameters. High levels of loss aversion (λ) and loss sensitivity (β) tend to drive the system into a suboptimal equilibrium characterized by insufficient demand, while high gain sensitivity (α) serves as a key driving force for the system’s evolution toward the ideal equilibrium. This study offers theoretical support for optimizing green renovation policies for existing residential buildings in China and provides practical recommendations for improving market competition mechanisms, thereby promoting the healthy development of the green renovation market. Full article

Shandong Province is rich in geothermal resources, mainly stored in sandstone reservoirs. The setting of reasonable well spacing in the early stage of large-scale recharge has not attracted enough attention. The problem of small well spacing in geothermal engineering is particularly prominent in the sandstone thermal reservoir production area represented by Dezhou. Based on the measured data of temperature, flow, and water level, this paper constructs a typical engineering numerical model by using TOUGH2 software. It is found that when the distance between production and recharge wells is 180 m, the amount of production and recharge is 60 m³/h, and the temperature of reinjection is 30 °C, the temperature of the production well will decrease rapidly after 10 years of production and recharge. In order to solve the problem of thermal breakthrough, three optimization schemes are assumed: reducing the reinjection temperature to reduce the amount of re-injection when the amount of heat is the same, reducing the amount of production and injection when the temperature of production and injection is constant, and stopping production after the temperature of the production well decreases. However, the results show that the three schemes cannot solve the problem of thermal breakthrough or meet production demand. Therefore, it is necessary to set reasonable well spacing. Therefore, based on the strata near the Hydrological Homeland in Decheng District, the reasonable spacing of production and recharge wells is achieved by numerical simulation. Under a volumetric flux scenario ranging from 60 to 80 m³/h, the well spacing should exceed 400 m. For a volumetric flux between 80 and 140 m³/h, it is recommended that the well spacing be greater than 600 m. Full article

Herein, the energy dispersion relationship and the density of states of triangular and rectangular moiré patterns are investigated using a tight binding model. Their characteristics of Hofstadter butterflies under different magnetic fields are also examined. The results indicate that, by analyzing different moiré superlattices, Hofstadter butterflies arising from different moiré pattern structures are obtained, exhibiting considerable fractal characteristics and self-similarities. Moreover, it is also observed that under an alternating magnetic field, the redistribution of electronic states leads to a significant change in the density of states curve, and the Van Hove peak changes with the increase in magnetic field intensity. This study enriches the understanding of the electronic behavior of moiré systems, but it also provides multiple potential application directions for future technological development. Full article

Teachers often raise their vocal volume to improve intelligibility or capture students’ attention. While this practice is common in second language (L2) teaching, its effects on tone perception remain understudied. To fill this gap, this study explores the effects of loud speech on Mandarin tone perception for L2 learners. Twenty-two native Mandarin speakers and twenty-two Thai L2 learners were tested on their perceptual accuracy and reaction time in identifying Mandarin tones in loud and normal modes. Results revealed a significant between-group difference: native speakers consistently demonstrated a ceiling effect across all tones, while L2 learners exhibited lower accuracy, particularly for Tone 3, the falling-rising tone. The loud speech had different impacts on the two groups. For native speakers, tone perception accuracy remained stable across different speech modes. In contrast, for L2 learners, loud speech significantly reduced the accuracy of Tone 3 identification and increased confusion between Tones 2 and 3. Reaction times in milliseconds were prolonged for all tones in loud speech for both groups. When subtracting the length of the tones, the delay of RT was evident only for Tones 3 and 4. Therefore, raising the speaking volume negatively affects the Mandarin tone perception of L2 learners, especially in distinguishing Tone 2 and Tone 3. Our findings have implications for both theories of L2 tone perception and pedagogical practices. Full article

The interaction between bacteria and fungi is one of the key interactions of microbial ecology, including mutualism, antagonism, and competition, which profoundly affects the balance and functions of animal microbial ecosystems. This article reviews the interactive dynamics of bacteria and fungi in more concerned microenvironments in animals, such as gut, rumen, and skin. Moreover, we summarize the molecular mechanisms and ecological functions of the interaction between bacteria and fungi. Three major bacterial–fungal interactions (mutualism, antagonism, and competition) are deeply discussed. Understanding of the interactions between bacteria and fungi allows us to understand, modulate, and maintain the community structure and functions. Furthermore, this summarization will provide a comprehensive perspective on animal production and veterinary medicine, as well as guide future research directions. Full article