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C46H58N2O14Cl2, triclinic, P1‾$P\overline{1}$ (no. 2), a = 7.5623(2) Å, b = 10.87056(17) Å, c = 13.90486(15) Å, α = 105.7122(12)°, β = 98.907(2)°, γ = 91.067(2)°, V = 1084.88(4) Å3, Z = 1, Rgt(F) = 0.0341, wRref(F2) = 0.0935, T = 100(2) K.

Viewshed analyses using Digital Elevation Models (DEMs) can provide decision support information in a variety of areas. Traditional viewshed analyses are mainly based on a circular visual range centred on an observation point, and lack the ability to dynamically adjust the visual range by view angle. In addition, these algorithms face challenges in achieving a balance between computational efficiency and accuracy. To solve the above problems, this study proposes a field-of-view (FOV) angular range based partitioning strategy to realise dynamic range proximity-direction-elevation reference lines (DPDERL), which improves the adaptability to complex terrains and the flexibility of viewpoint application environments. After partitioning, the algorithm is optimised for grid point search and reference line update. Experimental results show that the algorithm takes less than half the time of the Xdraw algorithm for a variety of terrain regions, has an error of no more than 5% compared to the R3 algorithm, and has less aggregation of error points than the PDERL and the XPDERL. The DPDERL approach provides an effective solution for large-scale dynamic range viewshed analysis by balancing speed and accuracy. [ABSTRACT FROM AUTHOR]

Implementing combination medication through crystal engineering technology receives increasing attention from researchers due to improvements in the clinical treatment effects as well as the physicochemical properties of the drug. Berberine (BER) is commonly used to treat gastroenteritis and bacterial diarrhea, with the problems of poor solubility and low oral bioavailability. Recently, it is found that gallic acid (GA) also has anti‐inflammatory and anti‐bacterial activities. Therefore, if the above‐mentioned two ingredients can be combined, it is possible to enhance the therapeutic effects and physicochemical properties of BER. Inspired by this, 8‐hydroxy‐7,8‐dihydroberberine (8H‐HBER) in this study is employed to react with gallic acid to yield BER gallate dihydrate (2BER‐2GA‐2 W). Furthermore, dissolution experiments demonstrate that the maximum apparent solubility (MAS) of 2BER‐2GA‐2 W in dilute hydrochloric acid solution medium (pH 1.2) has increased by 7 times compared to the commercial form of BER, because of avoiding the common‐ion effect. Moreover, 2BER‐2GA‐2 W has also obviously enhanced stability relative to the commercial form of BER. In addition, 2BER‐2GA‐2 W has a better inhibitory effect on Staphylococcus aureus (S. aureus) relative to the commercial form of BER. Hence, 2BER‐2GA‐2 W will be a promising solid‐state form of BER for its further development. [ABSTRACT FROM AUTHOR]

Accurately extracting buildings is essential for urbanization rate statistics, urban planning, resource allocation, etc. The high-resolution remote sensing images contain rich building information, which provides an important data source for building extraction. However, the extreme abundance of building types with large differences in size, as well as the extreme complexity of the background environment, result in the accurate extraction of spatial details of multi-scale buildings, which remains a difficult problem worth studying. To this end, this study selects the representative Xinjiang Tumxuk urban area as the study area. A building extraction network (SCA-Net) with feature highlighting, multi-scale sensing, and multi-level feature fusion is proposed, which includes Selective kernel spatial Feature Extraction (SFE), Contextual Information Aggregation (CIA), and Attentional Feature Fusion (AFF) modules. First, Selective kernel spatial Feature Extraction modules are used for cascading composition, highlighting information representation of features, and improving the feature extraction capability. Adding a Contextual Information Aggregation module enables the acquisition of multi-scale contextual information. The Attentional Feature Fusion module bridges the semantic gap between high-level and low-level features to achieve effective fusion between cross-level features. The classical U-Net, Segnet, Deeplab v3+, and HRNet v2 semantic segmentation models are compared on the self-built Tmsk and WHU building datasets. The experimental results show that the algorithm proposed in this paper can effectively extract multi-scale buildings in complex backgrounds with IoUs of 85.98% and 89.90% on the two datasets, respectively. SCA-Net is a suitable method for building extraction from high-resolution remote sensing images with good usability and generalization. [ABSTRACT FROM AUTHOR]

C46H58N2O14Cl2, triclinic, P 1 ‾ (no. 2), a = 7.5623(2) Å, b = 10.87056(17) Å, c = 13.90486(15) Å, α = 105.7122(12)°, β = 98.907(2)°, γ = 91.067(2)°, V = 1084.88(4) Å3, Z = 1, Rgt(F) = 0.0341, wRref(F2) = 0.0935, T = 100(2) K. [ABSTRACT FROM AUTHOR]

Abstract The as-grown structure of electrochemically synthesized titania nanotube arrays is investigated by scanning electron microscope (SEM) in combination with transmission electron microscope (TEM) as well as X-ray diffraction (XRD). The analysis reveals a preferred growth direction of the nanotubes relative to the substrate surface and the well control on the nanotube arrays morphology. The crystal structure of the anatase phase is detected and exists in the tube walls without any thermal treatment, which makes it possible to realize the application of as-formed TiO2 nanotubes avoiding the degradation of the nanotube structures when sintering. In addition, a new growth, layered model of the anodic TiO2 nanotubes is presented to obtain further understanding of the growth mechanism.