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Generative Adversarial Networks (GANs) possess a significant ability to generate novel images that adhere to specific guidelines across multiple domains. GAN-assisted generative design is a design method that can automatically generate design schemes without the constraints of human conditions. However, more research on complex objects with weak regularity, such as parks, is required. In this study, parks were selected as the research object, and we conducted our experiment as follows: (1) data preparation and collection; (2) pre-train the two neural network, then create the design layout generation system and the design plan generation system; (3) realize the data augmentation and enhanced hundred level dataset to thousand level dataset; (4) optimized training; (5) test the optimized training model. Experimental results show that (1) the machine learning model can acquire specific park layout patterns, quickly generate well-laid-out plan layout plans, and create innovative designs that differ from the human designer's style within reasonable limits; (2) GAN-driven data augmentation methods can significantly improve the generative ability of algorithms, reduce generative pressure, and achieve better generative results; (3) pix2pix is prone to mode collapse, and CycleGAN has fixed rule errors in expressing certain design elements; and (4) GAN has the ability to mine design rules in the same way as humans. [ABSTRACT FROM AUTHOR]

In the arid zone of northwest China, the Heihe River Basin (HRB), as a typical inland river basin, has a fragile regional ecological environment, obvious ecological degradation characteristics, and extremely serious problems in the utilization of agricultural land resources. Meanwhile, the shortage of water resources, the low reduction of land quality, and excessive agricultural activities have greatly increased the local water and land pressure. In this paper, firstly, using the Malmquist DEA model and coupling coordination degree model, the agroecological risk assessment system on account of the coupling of water and land resources (WLR) is constructed. Secondly, taking HRB from 1995 to 2020 as an example, we carry out spatial correlation analysis based on the degree of risk-correlated WLR. Thirdly, we analyze the evolution process and spatial correlation of ecological risk of agricultural WLR in the HRB at the county scale, then we conclude and put forward policy suggestions for improvement. The results show that: (1) On the whole, the average ecological risk of agricultural water resources in the HRB from 1995 to 2020 was 0.933, indicating that the risk was declining; the average ecological risk of agricultural land resources in the HRB from 1995 to 2020 was 0.938, indicating that the risk was declining also. (2) The degree of ecological risk coupling and coordination of agricultural soil and water resources upstream of the HRB is on the rise, while that in the middle and lower reaches is on the decline. (3) Through panel model analysis, the matching suitability of WLR drives agroecological risk. The correlation between them is positive. In conclusion, this method can effectively evaluate the agroecological risk of WLR and provide technical support for agricultural production and management in arid areas. [ABSTRACT FROM AUTHOR]

Self-healing anti-corrosion materials are widely regarded as a promising long-term corrosion protection strategy, and this is even more significant if the damage can be monitored in real-time and consequently repaired. Inspired by the hierarchical structure of human skin, self-healing, solvent-free polyurethane/carbon nanotubes composites (SFPUHE-HTF-CNTs) with a skin-like bilayer structure were constructed. The SFPUHE-HTF-CNTs were composed of two layers, namely, a hydrophobic solvent-free polyurethane (SFPUHE-HTF) containing disulfide bonds and fluorinated polysiloxane chain segments consisting of a self-healing layer and CNTs with good electrical conductivity consisting of a corrosion protection layer, which also allowed for the real-time monitoring of damage. The results of corrosion protection experiments indicated that the SFPUHE-HTF-CNTs had a low corrosion current density (8.94 × 10−9 A·cm−2), a positive corrosion potential (−0.38 V), and a high impedance modulus (|Z| = 4.79 × 105 Ω·cm2). The impedance modulus could still reach 4.54 × 104 Ω·cm2 after self-healing, showing excellent self-healing properties for anti-corrosion protection. Synchronously, the SFPUHE-HTF-CNTs exhibited a satisfactory damage sensing performance, enabling the real-time monitoring of fractures at different sizes. This work realized the effective combination of self-healing with corrosion protection and damage detection functions through a bionic design, and revealed the green, and low-cost preparation of advanced composites, which have the advantage of scale production. [ABSTRACT FROM AUTHOR]

Bexarotene (BEX) was approved by the FDA in 1999 for the treatment of cutaneous T-cell lymphoma (CTCL). The poor aqueous solubility causes the low bioavailability of the drug and thereby limits the clinical application. In this study, we developed a GCN-based deep learning model (CocrystalGCN) for in-silico screening of the cocrystals of BEX. The results show that our model obtained high performance relative to baseline models. The top 30 of 109 coformer candidates were scored by CocrystalGCN and then validated experimentally. Finally, cocrystals of BEX-pyrazine, BEX-2,5-dimethylpyrazine, BEX-methyl isonicotinate, and BEX-ethyl isonicotinate were successfully obtained. The crystal structures were determined by single-crystal X-ray diffraction. Powder X-ray diffraction, differential scanning calorimetry, and thermogravimetric analysis were utilized to characterize these multi-component forms. All cocrystals present superior solubility and dissolution over the parent drug. The pharmacokinetic studies show that the plasma exposures (AUC0−8h) of BEX-pyrazine and BEX-2,5-dimethylpyrazine are 1.7 and 1.8 times that of the commercially available BEX powder, respectively. This work sets a good example for integrating virtual prediction and experimental screening to discover the new cocrystals of water-insoluble drugs. [ABSTRACT FROM AUTHOR]

In order to improve the dispensability of graphene oxide (GO) in waterborne polyurethane (WPU), sulfonated graphene (SGO) with superior dispersity was prepared by modifying graphene oxide with sodium 2-chloroethane sulfonate to introduce hydrophilic sulfonic groups into the structure. SGO/WPU composites were prepared using isophorone diisocyanate (IPDI), polytetramethylene ether glycol (PTMEG 2000), dimethylolpropionic acid (DMPA) and SGO as raw materials. The influence of SGO content on composite properties were investigated. The structure and morphology of SGO and SGO/WPU composites were characterized by infrared spectroscopy, X-ray diffractometry and transmission electron microscopy etc. Their mechanical properties and wear resistance were analyzed as well. The experimental results showed that SGO was successfully grafted onto polyurethane macromolecule by an in situ method and, with the introduction of sulfonic groups, the interfacial compatibility of GO and PU was improved significantly so that SGO evenly dispersed into WPU. The SGO that was grafted onto WPU macromolecules exhibited layered morphology with nanometers in the WPU matrix. With increasing SGO content, the tensile strength and the wear resistance of the film increased, but the addition of more than 0.8 wt % SGO yielded unfavorable results. When the added amount of SGO was 0.8 wt % of WPU, the tensile strength of the composite film was 46.53% higher than that of the blank group, and the wear resistance of the film was remarkably improved, which was due to a strong interaction between the SGO and WPU phases. Thus, the conclusion can be drawn that appropriate amount of SGO addition can enhance the mechanical properties of SGO/WPU composite film. [ABSTRACT FROM AUTHOR]

Because of the special design of BeiDou navigation satellite system (BDS) constellation, the effects of ionospheric scintillation on operational BDS generally are more serious than on the global positioning system (GPS). As BDS is currently providing global services, it is increasingly important to seek strategies to mitigate the scintillation effects on BDS navigation and positioning services. In this study, an improved cycle-slip threshold model is proposed to decrease the high false-alarm rate of cycle-slips under scintillation conditions, thus avoiding the frequent unnecessary ambiguity resets in BDS precise point positioning (PPP) solution. We use one-year (from 23 March 2015 to 23 March 2016) BDS dataset from Hong Kong Sha Tin (HKST) station (22.4°N, 114.2°E; geomagnetic latitude: 15.4°N) to model the cycle-slip threshold and try to make it suitable for three types of BDS satellites and multiple scintillation levels. The availability of our mitigation strategy is validated by using three months (from 1 September 2015 to 30 November 2015) BDS dataset collected at 10 global navigation satellite system (GNSS) stations in Hong Kong. Positioning results demonstrate that our mitigated BDS PPP can prevent the sudden fluctuations of positioning errors induced by the ionospheric scintillation. Statistical results of BDS PPP experiments show that the mitigated solution can maintain an accuracy of about 0.08 m and 0.10 m in the horizontal and vertical components, respectively. Compared with standard BDS PPP, the accuracy of mitigated PPP can be improved by approximately 24.1%, 38.2%, and 47.9% in the east, north, and up directions, respectively. Our study demonstrates that considering different scintillation levels to establish appropriate cycle-slip threshold model in PPP processing can efficiently mitigate the ionospheric scintillation effects on BDS PPP. [ABSTRACT FROM AUTHOR]

The geomagnetic storm, which is an abnormal space weather phenomenon, can sometimes severely affect GPS signal propagation, thereby impacting the performance of GPS precise point positioning (PPP). However, the investigation of GPS PPP accuracy over the global scale under different geomagnetic storm conditions is very limited. This paper for the first time presents the performance of GPS dual-frequency (DF) and single-frequency (SF) PPP under moderate, intense, and super storms conditions during solar cycle 24 using a large data set collected from about 500 international GNSS services (IGS) stations. The global root mean square (RMS) maps of GPS PPP results show that stations with degraded performance are mainly distributed at high-latitude, and the degradation level generally depends on the storm intensity. The three-dimensional (3D) RMS of GPS DF PPP for high-latitude during moderate, intense, and super storms are 0.393 m, 0.680 m and 1.051 m, respectively, with respect to only 0.163 m on quiet day. RMS errors of mid- and low-latitudes show less dependence on the storm intensities, with values less than 0.320 m, compared to 0.153 m on quiet day. Compared with DF PPP, the performance of GPS SF PPP is inferior regardless of quiet or disturbed conditions. The degraded performance of GPS positioning during geomagnetic storms is attributed to the increased ionospheric disturbances, which have been confirmed by our global rate of TEC index (ROTI) maps. Ionospheric disturbances not only lead to the deteriorated ionospheric correction but also to the frequent cycle-slip occurrence. Statistical results show that, compared with that on quiet day, the increased cycle-slip occurrence are 13.04%, 56.52%, and 69.57% under moderate, intense, and super storms conditions, respectively. [ABSTRACT FROM AUTHOR]

The tropospheric wet delay induced by water vapor is a major error source in precise point positioning (PPP), significantly influencing the convergence time to obtain high-accuracy positioning. Thus, high-quality water vapor information is necessary to support PPP processing. This study presents the use of tomographic wet refractivity (WR) fields in PPP to examine their impacts on the positioning performance. Tests are carried out based on 1-year of 2013 global navigation satellite system (GNSS) observations (30 s sampling rate) from three stations with different altitudes in the Hong Kong GNSS network. Coordinate errors with respect to reference values at a 0.1 m level of convergence is used for the north, east, and up components, whilst an error of 0.2 m is adopted for 3D position convergence. Experimental results demonstrate that, in both static and kinematic modes, the tomography-based PPP approach outperforms empirical tropospheric models in terms of positioning accuracy and convergence time. Compared with the results based on traditional, Saastamoinen, AN (Askne and Nordis), and VMF1 (Vienna Mapping Function 1) models, 23–48% improvements of positioning accuracy, and 5–30% reductions of convergence time are achieved with the application of tomographic WR fields. When using a tomography model, about 35% of the solutions converged within 20 min, whereas only 23%, 25%, 25%, and 30% solutions converged within 20 min for the traditional, Saastamoinen, AN, and VMF1 models, respectively. Our study demonstrates the benefit to real-time PPP processing brought by additional tomographic WR fields as they can significantly improve the PPP solution and reduce the convergence time for the up component. [ABSTRACT FROM AUTHOR]

A large amount of research has been devoted to developing novel superhydrophobic coatings. However, it is still a great challenge to pursuean environmentally friendly method that leads to superhydrophobic coatings. Herein, we demonstrate for the first time, an environmentally friendly method for the preparation of conductive superhydrophobic coatings with sandwich-like structures by using aminoethylaminopropyl polydimethylsiloxane modified waterborne polyurethane (SiWPU) and N-octadecylamine functionalized multi-wall carbon nanotubes. These environmentally friendly coatings with the sheet resistance of 1.1 ± 0.1 kΩ/sq exhibit a high apparent contact angle of 158.1° ± 2° and a low sliding angle below 1°. The influence of the surface texture before and after heat treatment on the wetting properties is discussed. In addition, the coatings can be electrically heated by 3~113 °C with a voltage of 12~72 V, and thus, can be used for deicing. Furthermore, the resulting coatings demonstrate good performance of wear resistance and ultraviolet resistance, which will have broad application potential in harsh environments. [ABSTRACT FROM AUTHOR]

The fibroblast growth factor/fibroblast growth factor receptor (FGF/FGFR) signaling pathway plays crucial roles in cell proliferation, angiogenesis, migration, and survival. Aberration in FGFRs correlates with several malignancies and disorders. FGFRs have proved to be attractive targets for therapeutic intervention in cancer, and it is of high interest to find FGFR inhibitors with novel scaffolds. In this study, a combinatorial three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed based on previously reported FGFR1 inhibitors with diverse structural skeletons. This model was evaluated for its prediction performance on a diverse test set containing 232 FGFR inhibitors, and it yielded a SD value of 0.75 pIC50 units from measured inhibition affinities and a Pearson's correlation coefficient R2 of 0.53. This result suggests that the combinatorial 3D-QSAR model could be used to search for new FGFR1 hit structures and predict their potential activity. To further evaluate the performance of the model, a decoy set validation was used to measure the efficiency of the model by calculating EF (enrichment factor). Based on the combinatorial pharmacophore model, a virtual screening against SPECS database was performed. Nineteen novel active compounds were successfully identified, which provide new chemical starting points for further structural optimization of FGFR1 inhibitors.

Hepatitis C virus (HCV) NS3/NS4A serine protease is essential for viral replication, which is regarded as a promising drug target for developing direct-acting anti-HCV agents. In this study, sixteen novel compounds with cell-based HCV replicon activity ranging from 3.0 to 28.2 μM (IC50) were successfully identified by means of structure-based virtual screening. Compound 5 and compound 11, with an IC50 of 3.0 μM and 5.1 μM, respectively, are the two most potent molecules with low cytotoxicity.