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Forest disturbance detection is important for revealing ecological changes. Long-time series remote sensing analysis methods have emerged as the primary approach for detecting large-scale forest disturbances. Many of the existing change detection algorithms focus primarily on identifying high-intensity forest disturbances, such as harvesting and fires, with only a limited capacity to detect both high-intensity and low-intensity forest disturbances. This study proposes an online continuous change detection algorithm for the detection of multi-intensity forest disturbances such as forest harvest, fire, selective harvest, and insects. To initiate the proposed algorithm, the time series of the Normalized Difference Vegetation Index (NDVI) is fitted into a harmonic regression model, which is then followed by the computation of residuals. Next, the residual time series is entered into the adaptive exponentially weighted moving average (AEWMA) chart. This chart adaptively adjusts the smoothing coefficients to identify both high-intensity and low-intensity disturbances. When the chart value consistently deviates from the control limit, the forest pixel is classified as disturbed. With an overall spatial accuracy of 85.2%, including 86.1% producer's accuracy and 84% user's accuracy, along with a temporal accuracy of 96.7%, the algorithm enables precise and timely detection of forest disturbances with multiple intensities. This method provides a robust solution for detecting multi-intensity disturbances in forested regions. [ABSTRACT FROM AUTHOR]

Network attention is the degree of public attention to things on the Internet. With the rapid development of Web 2.0, the network attention of hotels on the tourism network platform has become an important reference for tourists to select an appropriate hotel. Based on the above, taking 371 hotels with three stars and more in Xi’an as the research object and gathering the data of hotels’ network attention from www.ctrip.com., we explore the temporal and spatial characteristics of hotels’ network attention. The result shows that: (1) From 2016 to 2018, due to the development of hotel online booking business, Consumers’ attention to Xi’an three-star and above hotels on www.ctrip.com. has increased significantly; (2) With the Bell and Drum Tower business district as the core, the spatial distribution of network attention of hotels with three stars and above in Xi’an presents the pattern of “large agglomeration and small dispersion”; (3) The network attention of different levels of hotels has obvious differences in spatial agglomeration;

Electroluminescence of porous silicon carbide is achieved in a forward-biased SiC p–i–n junction. A broad green spectral feature centered at ∼510 nm is shown to arise from porous SiC. A large SiC surface area in the vicinity of the junction is created by diamond cutting followed by an electrochemically enhanced hydrogen fluoride etch that produces a layer of porous SiC. Photoluminescence is shown not to be responsible for the green emission. This supports the model of carrier recombination at the porous region via lateral bipolar diffusion of carriers. A lateral bipolar diffusion model is presented in which mobile carriers diffuse laterally from the junction toward the porous SiC surface region driven by a lateral carrier concentration gradient. Lateral bipolar diffusion in conjunction with suitable radiative recombination centers provides a possible pathway to achieve high quantum efficiencies in future SiC p–n homojunction or double heterojunction light-emitting diodes. Competing recombination processes and associated ideality factors in 4H-SiC diodes are also examined. [ABSTRACT FROM AUTHOR]

Accurate estimation of forest height over a large area is beneficial to reduce the uncertainty of forest carbon sink estimation, which is of great significance to the terrestrial carbon cycle, global climate change, forest resource management, and forest-related scientific research. Forest height inversion using polarimetric interferometry synthetic aperture radar (PolInSAR) data through Random volume over ground (RVoG) models has demonstrated great potential for large-area forest height mapping. However, the wavelength and baseline length used for the PolInSAR data acquisition plays an important role during the forest height estimation procedure. In this paper, X–, C–, L–, and P–band PolInSAR datasets with four different baseline lengths were simulated and applied to explore the effects of wavelength and baseline length on forest height inversion using RVoG models. Hierarchical Bayesian models developed with a likelihood function of RVoG model were developed for estimated results uncertainty quantification and decrease. Then a similar procedure was applied in the L– and P–band airborne PolInSAR datasets with three different baselines for each band. The results showed that (1) Wavelength showed obvious effects on forest height inversion results with the RVoG model. For the simulated PolInSAR datasets, the L– and P–bands performed better than the X– and C–bands. The best performance was obtained at the P–band with a baseline combination of 10 × 4 m with an absolute error of 0.05 m and an accuracy of 97%. For the airborne PolInSAR datasets, an L–band with the longest baseline of 24 m in this study showed the best performance with R2 = 0.64, RMSE = 3.32 m, and Acc. = 77.78%. (2) It is crucial to select suitable baseline lengths to obtain accurate forest height estimation results. In the four baseline combinations of simulated PolInSAR datasets, the baseline combination of 10 × 4 m both at the L– and P–bands performed best than other baseline combinations. While for the airborne PolInSAR datasets, the longest baseline in three different baselines obtained the highest accuracy at both L– and P–bands. (3) Bayesian framework is useful for estimation results uncertainty quantification and decrease. The uncertainties related to wavelength and baseline length. The uncertainties were reduced obviously at longer wavelengths and suitable baselines. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate the impact of the spatial heterogeneity of prostate-specific membrane antigen (PSMA) uptake on circulating tumor DNA (ctDNA) characteristics and the response rate to new hormonal agent (NHA) treatment. Methods: This retrospective study included 153 patients with metastatic castration-resistant prostate cancer (mCRPC) who underwent gallium-68 [68 Ga]Ga-PSMA-11 positron emission tomography/computed tomography (PET/CT) and ctDNA sequencing with a less than 2-week interval. SUVhetero was defined as the variance of SUVmean for each PSMA-positive lesion. SUVmax-mean was obtained by subtracting the SUVmax by the SUVmean. Patients receiving abiraterone treatment after [68 Ga]Ga-PSMA-11 PET/CT and ctDNA sequencing and with complete follow-up record were included into prostate-specific antigen (PSA) response rate analysis. PSA response was defined as a reduction of greater than 50% from baseline. Results: The ctDNA detection rate was 65% (100/153). Higher SUVhetero value contributed to higher ctDNA% (Spearman's rho = 0.278, p < 0.002). A total of 60 patients were included in PSA response rate analysis. The median follow-up was 19.3 (IQR 16.2–23.2) months. Compare to patients with higher SUVhetero value, patients with NA SUVhetero had a higher PSA response rate (52% vs. 90%, p = 0.036). A higher SUVmax-mean value was strongly correlated with higher SUVhetero (Spearman's rho = 0.833, p < 0.0001). Patients with higher SUVmax-mean value also had a higher PSA response rate compared to patients with lower SUVmax-mean value (83.3% vs. 53.3%, p = 0.024). An external cohort confirmed baseline SUVmax-mean value was associated with enzalutamide treatment response rate. Patients with alterations in AR, DNA damage repair pathway, TP53, AR-associated pathway, cell cycle pathway, or WNT pathway had higher SUVmax-mean value compared to those without (p < 0.05). Conclusion: Spatial heterogeneity of the PSMA uptake was associated with ctDNA characteristics and response rate to NHA treatment. [ABSTRACT FROM AUTHOR]

Catalytic oxidation of ethylene associated with the preservation of fruits and vegetables (F&V) at low temperatures remains challenging. To address this issue, CeO2-octahedron-supported Pt catalysts were synthesized and modified by capacitively coupled plasma for efficient catalytic oxidation of C2H4. After the plasma treatment, CeO2 with rich oxygen vacancies was created, which acted as a support to facilitate the regulation of the size and dispersion of Pt nanoparticles. Compared with Pt/pristine CeO2, the Pt/plasma-modified CeO2 catalyst (Pt/CeO2-P) showed significantly higher reactivity. More than 99.9% of ethylene conversion induced by Pt/CeO2-P could be sustained longer than 50 h at 25 °C, and 30 min even at 0 °C. Thus, Pt/CeO2 interface engineering by plasma modification technology is particularly promising for low-temperature catalytic oxidation of ethylene. Moreover, a comprehensive characterization was conducted to elucidate the reaction pathway and oxidation mechanism. From the preservation test using bananas as fruit samples, it was found that Pt/CeO2-P delayed postharvest deterioration and ripening of bananas due to the excellent ethylene scavenging effect created by the catalyst, thus demonstrating the great potential applications in F&V preservation. [ABSTRACT FROM AUTHOR]