Recognition of small water bodies under complex terrain based on SAR and optical image fusion algorithm.

Understanding the spatial and temporal distribution of small water bodies is essential for managing water resources, crafting conservation policies, and preserving watershed ecosystems and biodiversity. However, existing studies often rely on a single remote sensing data source (optical or microwave), focusing on large-scale, flat areas and lacking comprehensive monitoring of small water bodies in complex terrain. Therefore, considering the complementary advantages of multisource remote sensing (multispectral and SAR), this paper proposes a multispectral and SAR fusion algorithm, named Multispectral and SAR Fusion algorithm (MASF), to better capture the remote sensing characteristics of small water bodies in complex areas. Based on this, a dataset containing spectral, texture, and geometric features is constructed, and multi-scale segmentation and random forest algorithms are applied for identification of small water bodies in complex terrain. The results demonstrate that the proposed fusion algorithm MASF exhibits minimal spectral distortion (SAM < 3.5, ERGAS <21, RMSE <0.01) and robust spatial feature enhancement (PSNR >40, SSIM >0.999, CC > 0.99). The Overall Accuracy (OA) and Kappa coefficients for both experimental areas surpassed 0.9. For rivers and reservoirs, both Producer's Accuracy (PA) and User's Accuracy (UA) exceeded 0.9. The UA for agricultural ponds exceeded 0.8. Comparative analysis with three other types of water-related data products shows that the freshwater identification results in this study have certain advantages in local small water bodies. Our research holds significant implications for the utilization of water resources in mountainous areas, prevention and control of floods and floods, as well as the development of aquaculture industry.

Underwriter Discourse, IPO Profit Distribution, and Audit Quality: An Entropy Study from the Perspective of an Underwriter-Auditor Network.

Underwriters play a pivotal role in the IPO process. Information entropy, a tool for measuring the uncertainty and complexity of information, has been widely applied to various issues in complex networks. Information entropy can quantify the uncertainty and complexity of nodes in the network, providing a unique analytical perspective and methodological support for this study. This paper employs a bipartite network analysis method to construct the relationship network between underwriters and accounting firms, using the centrality of underwriters in the network as a measure of their influence to explore the impact of underwriters' influence on the distribution of interests and audit outcomes. The findings indicate that a more pronounced influence of underwriters significantly increases the ratio of underwriting fees to audit fees. Higher influence often accompanies an increase in abnormal underwriting fees. Further research reveals that companies underwritten by more influential underwriters experience a decline in audit quality. Finally, the study reveals that a well-structured audit committee governance and the rationalization of market sentiments can mitigate the negative impacts of underwriters' influence. The innovation of this paper is that it enriches the content related to underwriters by constructing the relationship network between underwriters and accounting firms for the first time using a bipartite network through the lens of information entropy. This conclusion provides new directions for thinking about the motives and possibilities behind financial institutions' cooperation, offering insights for market regulation and policy formulation.

Small- and medium-sized rice fields identification in hilly areas using all available sentinel-1/2 images.

BACKGROUND: Mastering the spatial distribution and planting area of paddy can provide a scientific basis for monitoring rice production, and planning grain production layout. Previous remote sensing studies on paddy concentrated in the plain areas with large-sized fields, ignored the fact that rice is also widely planted in vast hilly regions. In addition, the land cover types here are diverse, rice fields are characterized by a scattered and fragmented distribution with small- or medium-sized, which pose difficulties for high-precision rice recognition. METHODS: In the paper, we proposed a solution based on Sentinel-1 SAR, Sentinel-2 MSI, DEM, and rice calendar data to focus on the rice fields identification in hilly areas. This solution mainly included the construction of rice feature dataset at four crucial phenological periods, the generation of rice standard spectral curve, and the proposal of spectral similarity algorithm for rice identification. RESULTS: The solution, integrating topographical and rice phenological characteristics, manifested its effectiveness with overall accuracy exceeding 0.85. Comparing the results with UAV, it presented that rice fields with an area exceeding 400 m2 (equivalent to 4 pixels) exhibited a recognition success rate of over 79%, which reached to 89% for fields exceeding 800 m2. CONCLUSIONS: The study illustrated that the proposed solution, integrating topographical and rice phenological characteristics, has the capability for charting various rice field sizes with fragmented and dispersed distribution. It also revealed that the synergy of Sentinel-1 SAR and Sentinel-2 MSI data significantly enhanced the recognition ability of rice paddy fields ranging from 400 m2 to 2000 m2.

Aquaporin-3 Inhibition Reduces the Growth of NSCLC Cells Induced by Hypoxia.

BACKGROUND/AIMS: Non-small cell lung cancer (NSCLC) is the leading cause of death worldwide. Although aquaporin-3 (AQP3) is widely distributed in mammalian tissues and over-expressed in NSCLC cells, there are limited studies on the effects of AQP3 knockdown on NSCLC cells under hypoxic conditions. METHODS: The CCK-8 assay was used to calculate cell viability. Scratch-wound healing and transwell assays were used to detect cell migration and invasion. Apoptotic cells were measured by the TUNEL assay. mRNA expression levels were calculated via quantitative RT-PCR. Relative protein levels were determined by immunoblot assays. RESULTS: AQP3 knockdown substantially reduced proliferation, migration, and invasion of A549 and NCI-H460 cells under hypoxic conditions. Moreover, AQP3 knockdown clearly induced cell apoptosis. Further analysis identified levels of HIF-1α, VEGF, Raf, phosphor-MEK, and phosphor-ERK, whose activities were significantly attenuated in the AQP3 knockdown group. CONCLUSIONS: These findings indicate that AQP3 knockdown retards the growth of NSCLC cells partially through inhibiting HIF-1α/VEGF and Raf/MEK/ERK signalling pathways.

Five-descriptor model to predict the chromatographic sequence of natural compounds.

Despite the recent introduction of mass detection techniques, ultraviolet detection is still widely applied in the field of the chromatographic analysis of natural medicines. Here, a neural network cascade model consisting of nine small artificial neural network units was innovatively developed to predict the chromatographic sequence of natural compounds by integrating five molecular descriptors as the input. A total of 117 compounds of known structure were collected for model building. The order of appearance of each compound was determined in gradient chromatography. Strong linear correlation was found between the predicted and actual chromatographic position orders (Spearman's rho = 0.883, p < 0.0001). Application of the model to the external validation set of nine natural compounds was shown to dramatically increase the prediction accuracy of the real chromatographic order of multiple compounds. A case study shows that chromatographic sequence prediction based on a neural network cascade facilitated compound identification in the chromatographic fingerprint of Radix Salvia miltiorrhiza. For natural medicines of known compound composition, our method provides a feasible means for identifying the constituents of interest when only ultraviolet detection is available.

Construction and in vitro/in vivo evaluation of 17-allylamino-17-demethoxygeldanamycin (17AAG)-loaded PEGylated nanostructured lipid carriers.

In this study, the PEGylated nanostructured lipid carriers (PEG-NLC) were constructed for the intravenous delivery of 17-allylamino-17-demethoxygeldanamycin (17AAG). 17AAG-PEG-NLC was successfully prepared by the method of emulsion evaporation at a high temperature and solidification at a low temperature using a mixture of glycerol monostearate and PEG2000-stearate as solid lipids, and medium-chain triglyceride as the liquid lipid. The results revealed that the morphology of the NLC was spheroidal. The particle size, zeta potential and entrapment efficiency for 17AAG-PEG-NLC were observed as 189.4 nm, -20.2 mV and 83.42%, respectively. X-ray diffraction analysis revealed that 17AAG existed as amorphous structures in the nanoparticles. In the in vitro release study, the 17AAG from 17AAG-PEG-NLC exhibited a biphasic release pattern with burst release initially and sustained release afterwards. In addition, 17AAG-PEG-NLC showed a significantly higher in vitro antitumor efficacy and longer retention time in vivo than 17AAG solution. These results indicated that 17AAG-PEG-NLC may offer a promising alternative to the current 17AAG formulations for the treatment of solid tumors.

Fabrication of high-power piezoelectric transformers using lead-free ceramics for application in electronic ballasts.

CuO is doped into (Na(0.5)K(0.5))NbO(3) (NKN) ceramics to improve the piezoelectric properties and thus obtain a piezoelectric transformer (PT) with high output power. In X-ray diffraction patterns, the diffraction angles of the CuO-doped NKN ceramics shift to lower values because of an expansion of the lattice volume, thus inducing oxygen vacancies and enhancing the mechanical quality factor. A homogeneous microstructure is obtained when NKN is subjected to CuO doping, leading to improved electrical properties. PTs with different electrode areas are fabricated using the CuO-doped NKN ceramics. Considering the efficiency, voltage gain, and temperature rise of PTs at a load resistance of 1 kΩ, PTs with an electrode with an inner diameter of 15 mm are combined with the circuit design for driving a 13-W T5 fluorescent lamp. A temperature rise of 6°C and a total efficiency of 82.4% (PT and circuit) are obtained using the present PTs.

Effects of improved process for CuO-doped NKN lead-free ceramics on high-power piezoelectric transformers.

In this paper, the effects of the electrical proper- ties of CuO-doped (Na(0.5)K(0.5))NbO(3) (NKN) ceramics prepared separately using the B-site oxide precursor method (BO method) and conventional mixed-oxide method (MO method) on high-power piezoelectric transformers (PTs) were investigated. The performances of PTs made with these two substrates were compared. Experimental results showed that the output power and temperature stability of PTs could be enhanced because of the lower resonant impedance of the ceramics prepared using the BO method. In addition, the output power of PTs was more affected by the resonant impedance than by the mechanical quality factor (Q(m)) of the ceramics. The PTs fabricated with ceramics prepared using the BO method showed a high efficiency of more than 94% and a maximum output power of 8.98 W (power density: 18.3 W/cm(3)) with temperature increase of 3°C under the optimum load resistance (5 kΩ) and an input voltage of 150 V(pp). This output power of the lead-free disk-type PTs is the best reported so far.

Syntheses, crystal and electronic structures of compounds AM(PO4)2 (A = Sr, M = Ti, Sn; A = Ba, M = Sn).

Three ternary metal diorthophosphates (V), AM(PO(4))(2) (A = Sr, M = Ti, Sn; A = Ba, M = Sn), have been prepared by high-temperature solution growth (HTSG) method and structurally characterized by single-crystal X-ray diffraction analysis for the first time. The structure of BaSn(PO(4))(2) features the yavapaiite-type structure, with space group C2/m and a = 8.214(2), b = 5.2456(13), c = 7.8938(19) A, beta = 94.561(4) degrees , Z = 2, R(1) (all data) = 0.0253. Compounds SrM(PO(4))(2) (M = Ti, Sn) are isostructural and crystallize in a novel distorted yavapaiite structure, with space group C2/c and a = 16.4617(4), b = 5.1720(3), c = 8.1187(2) A, beta = 116.40(2) degrees , Z = 4, R(1) (all data) = 0.016 for SrTi(PO(4))(2); a = 16.674(14), b = 5.223(4), c = 8.099(6) A, beta = 115.821(11) degrees , Z = 4, R(1) (all data) = 0.025 for SrSn(PO(4))(2). Band structure calculations from the density functional theory (DFT) method indicate that all three compounds are approximately direct band-gap insulators.