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The resurgence of passenger flows after the pandemic poses a significant challenge to the safe operation of rail transit. Therefore, adopting the waiting hall of an ultralarge railway station hub as an example, thermal radiation and evacuation simulations were conducted by the Fire Dynamics Simulator and Pathfinder, respectively. Island-style shops, known for their high crowd density and fire load, were defined as fire sources, and the effectiveness of a 6 m wide fire isolation zone was validated via the adoption of the dual-validation model. By comparing the relationships between the total evacuation population after passenger flow recovery and various evacuation parameters, it was shown that passengers were not evenly distributed among the exits in the waiting hall during an emergency, leading to uneven utilization. Furthermore, to gain a comprehensive understanding of the evacuation process under simulated fire conditions, an evacuation simulation involving 10,000 evacuees over a duration of 324.8 s was conducted. This study provides a theoretical basis for optimizing fire emergency evacuation plans for ultralarge railway station hubs.

Salinity is a major factor limiting rice productivity, and developing salt-tolerant (ST) varieties is the most efficient approach. Seventy-eight ST introgression lines (ILs), including nine promising lines with improved ST and yield potential (YP), were developed from four BC2F4 populations from inter-subspecific crosses between an elite Geng (japonica) recipient and four Xian (indica) donors at the Institute of Crop Sciences, Chinese Academy of Agricultural Sciences. Genome-wide characterization of donor introgression identified 35 ST QTLs, 25 of which harbor 38 cloned ST genes as the most likely QTL candidates. Thirty-four are Xian-Geng differentiated ones with the donor (Xian) alleles associated with ST, suggesting differentiated responses to salt stress were one of the major phenotypic differences between the two subspecies. At least eight ST QTLs and many others affecting yield traits were identified under salt/non-stress conditions. Our results indicated that the Xian gene pool contains rich ‘hidden’ genetic variation for developing superior Geng varieties with improved ST and YP, which could be efficiently exploited by selective introgression. The developed ST ILs and their genetic information on the donor alleles for ST and yield traits would provide a useful platform for developing superior ST and high-yield Geng varieties through breeding by design in the future.

To address the challenge of balancing privacy protection with regulatory oversight in blockchain transactions, we propose a regulatable privacy protection scheme for blockchain transactions. Our scheme utilizes probabilistic public-key encryption to obscure the true identities of blockchain transaction participants. By integrating commitment schemes and zero-knowledge proof techniques with deep learning graph neural network technology, it provides privacy protection and regulatory analysis of blockchain transaction data. This approach not only prevents the leakage of sensitive transaction information, but also achieves regulatory capabilities at both macro and micro levels, ensuring the verification of the legality of transactions. By adopting an identity-based encryption system, regulatory bodies can conduct personalized supervision of blockchain transactions without storing users’ actual identities and key data, significantly reducing storage computation and key management burdens. Our scheme is independent of any particular consensus mechanism and can be applied to current blockchain technologies. Simulation experiments and complexity analysis demonstrate the practicality of the scheme.

Scaffolding is an integral temporary structural system in the field of construction engineering. However, the current scaffolding commonly has the shortcomings of low construction efficiency and high risk. This paper proposes a novel socket-type keyway steel pipe scaffolding, which can well solve the shortcomings of the existing scaffolding. Due to less research related to scaffolding in the past decades, it has resulted in a high number of scaffolding accidents. In order to avoid the occurrence of scaffolding accidents, it is necessary to systematize the study of this novel type of scaffolding. This study is an extremely important reference for the use and design of this novel type of scaffolding. To explore the ultimate load capacity and destabilization mode of the novel socket-type keyway steel pipe scaffolding, full-scale tests were conducted on the socket-type keyway steel pipe scaffolding with cantilever heights of 1.2 m and 0.5 m. The test results indicate that the ultimate load capacity of the scaffolding with a cantilever height of 1.2 m is 196 kN, and the destabilization mode is local instability. The ultimate load capacity with a cantilever height of 0.6 m is 276 kN, and the destabilization mode is half-wave buckling. This phenomenon shows that the different cantilever heights of the scaffolding have a significant effect on the load capacity and destabilization mode. Moreover, the load capacity decreases significantly with increasing cantilever length. The finite element model was established using SAP2000 v21 and compared with the test results. The error between the ultimate load capacity in the finite element linear elastic buckling analysis and the test results is 25%. The error between the calculated ultimate load capacity in the nonlinear buckling analysis considering the initial geometrical defects and the test results is 4%. Therefore, the nonlinear buckling analysis considering the initial geometrical defects is more in line with the force situation of the structure in the real situation.

The modification mechanism of low-molecular-weight organic acids on a single-chain silicate mineral (wollastonite) was investigated through a leaching method. Solid and liquid samples were analyzed using atomic absorption spectrophotometer (AAS), X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier-transform infrared spectroscopy (FTIR). After 720 h of reaction, the results revealed that the dissolution concentration of Si (2200 μmol/L) in citric acid solution is more than that (1950 μmol/L) in oxalic acid. In the composite acids (citric acid and oxalic acid), the dissolution concentration of Si release from wollastonite reached the maximum value of 3304 μmol/L. The dissolution data of Si in wollastonite were fittingly described by the parabolic equation (Ct = a + bt1/2), with the highest correlation coefficients (R2 > 0.993), in the presence of the low-molecular-weight organic acids. The dissolution data suggested that the dissolution reaction process of Si was consistent with the diffusion-controlled model. Citric acid exhibited a higher affinity for attacking the (200) surface, while oxalic acid was prone to dissolve the (002) crystal face. The synergistic effects of oxalic acid and citric acid led to the weakening of the XRD diffraction peak intensity of wollastonite. When exposed to composite acids, the surface of wollastonite was covered with insoluble reactants that restricted the substance diffusion and hindered the reaction. This study offers valuable theoretical insights into the modification or activation of wollastonite by composite low-molecular-weight organic acids.

Due to the asymmetry of quantum errors, phase-shift errors are more likely to occur than qubit-flip errors. Consequently, there is a need to develop asymmetric quantum error-correcting (QEC) codes that can safeguard quantum information transmitted through asymmetric channels. Currently, a significant body of literature has investigated the construction of asymmetric QEC codes. However, the asymmetry of most QEC codes identified in the literature is limited by the dual-containing condition within the Calderbank-Shor-Steane (CSS) framework. This limitation restricts the exploration of their full potential in terms of asymmetry. In order to enhance the asymmetry of asymmetric QEC codes, we utilize entanglement-assisted technology and exploit the algebraic structure of cyclotomic cosets of constacyclic codes to achieve this goal. In this paper, we generalize the decomposition method of the defining set for constacyclic codes and apply it to count the number of pre-shared entangled states in order to construct four new classes of asymmetric entanglement-assisted quantum maximal-distance separable (EAQMDS) codes that satisfy the asymmetric entanglement-assisted quantum Singleton bound. Compared with the codes existing in the literature, the lengths of the constructed EAQMDS codes and the number of pre-shared entangled states are more general, and the codes constructed in this paper have greater asymmetry.

African swine fever virus (ASFV) is a large double-stranded DNA virus that is highly infectious and seriously affects domestic pigs and wild boars. African swine fever (ASF) has caused huge economic losses to endemic countries and regions. At present, there is still a lack of effective vaccines and therapeutics. Therefore, rapid and accurate detection is essential for the prevention and control of ASF. The portable DNA endonuclease (Cas12a)-mediated lateral flow strip detection method (Cas12a-LFS) combined with recombinant polymerase amplification (RPA) has been gradually recognized as effective for virus detection including ASFV. In this study, based on the ASFV structural protein p17 gene (D117L), an RPA-Cas12a-LFS detection method was established. The detection method exhibits a sensitivity of up to two gene copies and has no cross-reaction with nine other swine viruses. Thus, the method is highly sensitive and specific. In 68 clinical samples, the coincidence rate of the p17 strip was 100%, compared to the traditional quantitative PCR (qPCR). In conclusion, we have developed a simple, rapid, sensitive, and specific ASFV visual detection method and demonstrated the potential of on-site detection of ASFV.

Ginsenoside Rg3 extracted from Panax notoginseng has therapeutic effects on diabetes and heart diseases. However, the underlying mechanism of ginsenoside Rg3 on diabetic cardiomyopathy (DCM) remains unclear. 24-week-old diabetic db/db mice were treated with ginsenoside Rg3 for 12 weeks, then body weight, serum lipids, adiponectin levels, as well as cardiac function and pathological morphology, were measured. The targets of ginsenoside Rg3 and its regulation of the adiponectin pathway were also evaluated on 3T3-L1 or H9c2 cells. Ginsenoside Rg3 directly bound to PPAR-γ, improving adiponectin secretion and promoting adiponectin signaling. Significantly attenuated overweight, hyperglycemia, and hyperlipidemia, as well as alleviated lipid accumulation and dysfunction in adipose, liver, and heart tissues, were observed in the ginsenoside Rg3-treated group. Ginsenoside Rg3 could be a promising drug targeting PPAR-γ to treat diabetic cardiomyopathy.

Natural sand has a loose and porous structure with low strength, and is prone to many geoengineering problems that cause huge losses. In this study, an organic polymer-polymer-fiber blend was used to improve the strength of sand. Using a series of laboratory and numerical simulation tests, researchers have investigated the microdamage behavior of an organic polymer and fiber-treated sand in various types of mechanical tests and explored the improvement mechanism. The results showed that the polymer- and fiber-treated sand enhanced the integrity and exhibited differential damage responses under different test conditions. The increase in polymer content induced uniform force transfer, leading to a wider range of particle motion and crack initiation, whereas the fibers adhered and confined the surrounding particles, inducing an arching force chain and dispersive/buckling cracking. Polymer- and fiber-treated sands increased their energy-carrying capacity and improved their energy release, which affected the damage characteristics. Organic polymers, fibers, and sand particles were wrapped around each other to form an effective interlocking structure, which enhances the integrity and mechanical properties of sand. This study provides novel ideas and methods in the polymer-fiber composite treatment of sand in the microscopic field.

Sesquiterpenes are a type of abundant natural product with widespread applications in several industries. They are biosynthesized by sesquiterpene synthases (STSs). As valuable and abundant biological resources, mushroom-forming fungi are rich in new sesquiterpenes and STSs, which remain largely unexploited. In the present study, we collected information on 172 STSs from mushroom-forming fungi with experimentally characterized products from the literature and sorted them to develop a dataset. Furthermore, we analyzed and discussed the phylogenetic tree, catalytic products, and conserved motifs of STSs. Phylogenetic analysis revealed that the STSs were clustered into four clades. Furthermore, their cyclization reaction mechanism was divided into four corresponding categories. This database was used to predict 12 putative STS genes from the edible fungi Flammulina velutipes. Finally, three FvSTSs were selected to experimentally characterize their functions. FvSTS03 predominantly produced Δ-cadinol and FvSTS08 synthesized β-barbatene as the main product; these findings were consistent with those of the functional prediction analysis. A product titer of 78.8 mg/L β-barbatene was achieved in Saccharomyces cerevisiae via metabolic engineering. Our study findings will help screen or design STSs from fungi with specific product profiles as functional elements for applications in synthetic biology.

The interaction between low-molecular-weight organic acids (LMWOAs) and minerals in nature has been widely studied; however, limited research has been conducted on the dissolution mechanism of sillimanite in the presence of different organic acids. In this study, the interaction between the sillimanite sample and LMWOAs (citric acid, oxalic acid, and citric/oxalic mixture) at the same pH was investigated. The dissolution rate of Si and Al was high during the initial reaction time, then slowed down in the presence of LMWOAs. The dissolution data for Si and Al from sillimanite in the LMWOAs fit well with the first-order equation (Ct = a(1 − exp(−kt))) (R2 > 0.991). The dissolution process of sillimanite in the organic acids was controlled by the surface chemical reaction step. The dissolution concentration of Si in aqueous citric acid was higher than that in oxalic acid. In contrast, the dissolution concentration of Al in oxalic acid was more than that in citric acid. The maximum concentrations of Si and Al in the presence of composite organic acids were 1754 μmol/L and 3904 μmol/L. The sillimanite before and after treatment with LMWOAs were studied using X-ray diffraction (XRD) and scan electron microscopy (SEM). These results are explained by the characterization of the sillimanite. Under the single acid solution, the (210) crystal plane with a high areal density of Al in sillimanite was easily dissolved by the oxalic acid, while the (120) in sillimanite with a high areal density of Si was more easily dissolved by citric acid. In the composite organic acids, the Si-O bond and Al-O bond in sillimanite were attacked alternately, leading to the formation of some deeper corrosion pits on the surface of sillimanite. The results are of interest in the dissolution mechanisms of sillimanite in the low-molecular-weight organic acids and the environmentally friendly activation of sillimanite.

Zn ions are widely reported to possess a depression effect on sphalerite in flotation. The effective adsorption of Zn ions on a sphalerite surface is critical to realize the inhibition effect. At the same time, zinc ions are easily hydrated in a slurry solution. Therefore, based on the first principle DFT calculation, the molecular mechanism of Zn ion adsorption on the surface of Sphalerite is further studied from the perspective of hydration. [Zn(H2O)5]2+, [Zn(OH)(H2O)3]+ and [Zn(OH)2(H2O)2] are found to be the effective components of Zn ions adsorbed on a sphalerite (110) surface in the neutral condition. Furthermore, the adsorption mechanism of [Zn(H2O)5]2+ on a sphalerite (110) surface is mainly via the hybridization of Zn 3d orbital in the structure of [Zn(H2O)5]2+ with surface S 3p orbitals. Additionally, the adsorption mechanism of [Zn(OH)(H2O)3]+ and [Zn(OH)2(H2O)2] on a sphalerite (110) surface is primarily ascribed to the hybridization of surface Zn 3d orbital with O atom of hydroxyl ligand 2p orbitals. In addition, the H 1s orbits in the water molecules have a weaker interaction with the sphalerite surface S 3p orbits. This work sheds new light on the adsorption and inhibition mechanism of zinc ions on a sphalerite surface in a neutral aqueous solution.

Background: HER2-positive breast cancer (BC) is a highly aggressive phenotype. The role of the host immune features in predictive response to anti-HER2 therapies and prognosis in BC has already been suggested. We aimed to develop a predictive and prognostic model and examine its relevance to the clinical outcomes of patients with HER2-positive BC. Methods: Immune effective score (IES) was constructed using principal component analysis algorithms. A bioinformatic analysis using four independent cohorts (GSE66305, n = 88; GSE130786, n = 110; TCGA, n = 123; METABRIC, n = 236) established associations between IES and clinical outcomes. Results: Genes associated with neoadjuvant trastuzumab therapy response were enriched in pathways related to antitumor immune activities. IES was demonstrated to be a predictive biomarker to neoadjuvant trastuzumab therapy benefits (GSE66305: area under the curve (AUC) = 0.804; GSE130786: AUC = 0.704). In addition, IES was identified as an independent prognostic factor for overall survival (OS) in the TCGA cohort (p = 0.036, hazard ratio (HR): 0.66, 95% confidence interval (CI): 0.449–0.97) and METABRIC cohort (p = 0.037, HR: 0.9, 95% CI: 0.81–0.99). Conclusion: IES has a predictive value for response to neoadjuvant trastuzumab therapy and independent prognostic value for HER2-positive breast cancer.

Elevated mental workload (MWL) experienced by pilots can result in increased reaction times or incorrect actions, potentially compromising flight safety. This study aims to develop a functional system to assist administrators in identifying and detecting pilots’ real-time MWL and evaluate its effectiveness using designed airfield traffic pattern tasks within a realistic flight simulator. The perceived MWL in various situations was assessed and labeled using NASA Task Load Index (NASA-TLX) scores. Physiological features were then extracted using a fast Fourier transformation with 2-s sliding time windows. Feature selection was conducted by comparing the results of the Kruskal-Wallis (K-W) test and Sequential Forward Floating Selection (SFFS). The results proved that the optimal input was all PSD features. Moreover, the study analyzed the effects of electroencephalography (EEG) features from distinct brain regions and PSD changes across different MWL levels to further assess the proposed system’s performance. A 10-fold cross-validation was performed on six classifiers, and the optimal accuracy of 87.57% was attained using a multi-class K-Nearest Neighbor (KNN) classifier for classifying different MWL levels. The findings indicate that the wireless headset-based system is reliable and feasible. Consequently, numerous wireless EEG device-based systems can be developed for application in diverse real-driving scenarios. Additionally, the current system contributes to future research on actual flight conditions.

In the construction of large-scale water conservancy and hydropower transportation projects, the rock mass structural information is often used to evaluate and analyze various engineering geological problems such as high and steep slope stability, dam abutment stability, and natural rock landslide geological disasters. The complex shape and extremely irregular distribution of the structural planes make it challenging to identify and extract automatically. This study proposes a method for extracting structural planes from UAV images based on Geo-AINet ensemble learning. The UAV images of the slope are first used to generate a dense point cloud through a pipeline of SfM and PMVS; then, the multiple geological semantics, including color and texture from the image and local geological occurrence and surface roughness from the dense point cloud, are integrated with Geo-AINet for ensemble learning to obtain a set of semantic blocks; finally, the accurate extraction of structural planes is achieved through a multi-semantic hierarchical clustering strategy. Experimental results show that the structural planes extracted by the proposed method perform better integrity and edge adherence than that extracted by the AINet algorithm. In comparison with the results from the laser point cloud, the geological occurrence differences are less than three degrees, which proves the reliability of the results. This study widens the scope for surveying and mapping using remote sensing in engineering geological applications.

In addition to disease-associated microglia (DAM), microglia with MHC-II and/or IFN-I signatures may form additional pathogenic subsets that are relevant to neurodegeneration. However, the significance of such MHC-II and IFN-I signatures remains elusive. We demonstrate here that these microglial subsets play intrinsic roles in orchestrating neurotoxic properties of neurotoxic Eomes+ Th cells under the neurodegeneration-associated phase of experimental autoimmune encephalomyelitis (EAE) that corresponds to progressive multiple sclerosis (MS). Microglia acquire IFN-signature after sensing ectopically expressed long interspersed nuclear element-1 (L1) gene. Furthermore, ORF1, an L1-encoded protein aberrantly expressed in the diseased central nervous system (CNS), stimulated Eomes+ Th cells after Trem2-dependent ingestion and presentation in MHC-II context by microglia. Interestingly, administration of an L1 inhibitor significantly ameliorated neurodegenerative symptoms of EAE concomitant with reduced accumulation of Eomes+ Th cells in the CNS. Collectively, our data highlight a critical contribution of new microglia subsets as a neuroinflammatory hub in immune-mediated neurodegeneration.

Polyoxymethylene dimethyl ether (PODE) is one of the most promising alternative fuels for diesel engines with a high cetane number, high oxygen content, and no C-C bonds. In this paper, a new spray model with a novel cavitation sub-model is adopted in order to create a numerical model suitable for engine simulation fueled with PODE/diesel blends. The effects of the blending ratio, injection timing, and EGR rate on the combustion and emission characteristics are investigated by the simulation. The simulation results show that the self-restoring oxygen properties of PODE can efficiently improve the combustion, causing a higher in-cylinder temperature, and therefore, higher NOx emissions. Additionally, with the increase in the blending ratio, the increase in the oxidation activity of PODE/diesel blends and the improvement of atomization are conducive to reducing soot emissions. Then, the injection timing and EGR rate are optimized. The numerical results suggest that the NOx emissions decrease initially and then increase; however, soot emissions decrease monotonically with the delay of the injection timing. When the volume blending ratio is 15%, the emission performance is best when the injection timing is between 710 °CA and 715 °CA. The increase in EGR rate can effectively reduce the in-cylinder temperature and control the NOx emissions, but the excessive EGR rate leads to higher soot emissions and a deteriorated combustion process. Therefore, an EGR rate in the range of 0.0 to 0.2 has a better comprehensive emission performance from the perspective of controlling both the NOx and soot emissions.

The emission of nitrogen dioxide (NO2) caused by marine transportation has attracted worldwide environmental concerns. Two-dimensional (2D) black phosphorus (BP) is an emerging semiconductive material with the advantages of high electron mobility, a layer-dependent direct band gap and a large specific surface area. These properties ensure excellent potential in gas-sensing applications. In this work, BP quantum dots (QDs) are synthesized from commercial red phosphorus (RP) fine powder via the aqueous route. The BP QDs show uniform size distribution with an average size of 2.2 nm. They are employed to fabricate thin film gas sensors by aerial-assisted chemical vapor deposition. The microstructure, morphology and chemical composition are determined by various characterizations. The sensor performances are evaluated with the optimized response set to 100 ppm NO2 of 10.19 and a sensitivity of 0.48 is obtained. The gas sensor also demonstrates excellent repeatability, selectivity and stability. The fabricated thin film gas sensor assembled by BP QDs exhibits prospective applications in selective NO2 detection for marine gaseous pollutant monitoring and control.

Pilot factor is worth considering when analyzing the causes of civil aviation accidents. This study introduces a data-driven Bayesian network (BN) approach to investigating the joint causal effects of pilot and other factors on civil aviation safety. A total number of 163 individual pilot-related accidents in the National Transportation Safety Board (NTSB) aviation accident database from 2008 to 2020 are analyzed, focusing on eliciting the causal effects of various potential risk factors, including pilot factors, on civil aviation accidents. The modeling of the interdependency among the risk influencing factors (RIFs) and their causal contributory effect on the accident outcome is structured by a tree augmented network (TAN) and validated by sensitivity analysis. The novelty of this study is to incorporate pilot factors derived from the civil aviation accident database into risk analysis, combined with other external factors. The results indicate that weather conditions and flight phases are more correlated with casualty types of civil aviation accidents than pilot action and decision, and three other pilot factors only contribute to fatal injury in civil aviation accidents.

Sulfidization xanthate flotation remains the most promising method for the beneficiation of malachite. In this study, L-arginine (LA) was first used to modify the malachite surface and improve the efficiency of sulfidization flotation. The performance of LA was evaluated by the flotation experiments. The mechanism of interaction between LA and the malachite surface was investigated by adsorption experiments, zeta potential measurements, scanning electron microscopy (SEM-EDS) and X-ray photoelectron spectroscopy (XPS) analysis. Flotation experiments showed that LA had a significantly promoting effect on malachite sulfidization flotation. Adsorption experiments and SEM-EDS results indicated that LA improved the adsorption of S (II) species into the malachite surface and promoted the formation of sulfides. This finding was further confirmed by the XPS analysis. The XPS measurements results determined that S (II) species reacted with Cu (II) on the malachite surface and form polysulfides, adding LA promoted the reaction. The zeta potential measurements showed that LA increased the positive electrical properties of the mineral surface, which was conducive to S (II) species adsorption and the sulfidization reaction. This work sheds new light on the development of sulfidization activation.

Clay is one of the important base materials in slope restoration. The adhesion of clay–rock interface plays a decisive role in the repairing effect on rock slopes. Fibers and polymers are widely used as a clay improvement method in rock slope repair. In this paper, the friction effect of sisal fiber and polyvinyl acetate (PVAc)-reinforced clay was studied through the design of an indoor rock-like interface sliding model test. Using modelled test results and scanning electron microscope (SEM) images, the reinforced clay was analyzed. The test results showed that the critical sliding angle and maximum static friction force of clay decreased with the increase of moisture content. An excess of fiber content and moisture content weakens the coupling effect of fiber-anchoring clay. Fiber content of 0.8% and PVAc content of 2% had the best effect on enhancing the sliding resistance of clay and provided good adhesion for dangerous interfaces of rock slope at 35° and 45°, respectively. PVAc formed a three-dimensional networked elastic membrane structure to improve the skid resistance and dynamic friction coefficient of the clay. The results provide an effective way for soil improvement and ecological restoration.

Soil moisture is an important parameter affecting environmental processes such as hydrology, ecology, and climate. Synthetic aperture radar (SAR) microwave remote sensing is an important means of farmland surface soil moisture (SSM) measurement. The inversion of farmland SSM by microwave remote sensing is greatly affected by vegetation cover. To address this problem, a multisource remote sensing inversion method of farmland SSM based on feature optimization and machine learning is proposed in this paper. Six typical machine learning algorithms suitable for small sample training, including random forest, radial basis function neural network, generalized regression neural network, support vector regression, genetic algorithm–back propagation neural network, and extreme learning machine, were selected in this paper. The features extracted from Sentinel-1/2 and Radarsat-2 remote sensing data were analyzed by Pearson correlation, and those with high correlation coefficients were selected to form the optimal feature subset as the input for the subsequent machine learning models. Then, the SSM collaborative inversion models under different machine learning algorithms were constructed, and comparative experiments were set up to select the optimal prediction model. The models’ accuracy under different feature parameters were studied, and the difference in the performance between the dual-polarization SAR data and the quad-polarization SAR data in SSM inversion was explored. The experimental results showed that among the six models, the random forest model had a higher inversion accuracy, with a coefficient of determination of 0.6395 and a root mean square error of 0.0264 cm3/cm3. Meanwhile, the inversion accuracy could be greatly improved after feature optimization, and the inversion accuracy of the quad-polarization SAR data combined with optical remote sensing data, was better than that of the dual-polarization SAR data combined with optical remote sensing data.

Enhancer RNAs (eRNAs), a class of non-coding RNAs (ncRNAs) transcribed from enhancer regions, serve as a type of critical regulatory element in gene expression. There is increasing evidence demonstrating that the aberrant expression of eRNAs can be broadly detected in various human diseases. Some studies also revealed the potential clinical utility of eRNAs in these diseases. In this review, we summarized the recent studies regarding the pathological mechanisms of eRNAs as well as their potential utility across human diseases, including cancers, neurodegenerative disorders, cardiovascular diseases and metabolic diseases. It could help us to understand how eRNAs are engaged in the processes of diseases and to obtain better insight of eRNAs in diagnosis, prognosis or therapy. The studies we reviewed here indicate the enormous therapeutic potency of eRNAs across human diseases.

The underground energy geostructure represented by the energy pile is one of the key paths for the cooperative development of underground space and geothermal energy. Because of its advantages of low cost, high efficiency and no extra occupation of underground space, it has become a feasible alternative to the borehole heat exchanger. The change in the temperature field of the energy pile and its surrounding ground not only affects the geological environment but also influences the thermomechanical performance and the durability of the structure. However, the temporal and spatial unsteady-state temperature distribution of piles and surrounding rock under typical intermittent and unbalanced thermal load conditions is still unclear. In this paper, a finite element model was applied to analyze the unsteady-state temperature distribution, and the thermomechanical behavior of the energy pile group was developed and verified. The temperature field distribution of pile and surrounding rock under typical intermittent working and unbalanced thermal load conditions were determined. Moreover, the thermomechanical behavior characteristics of the energy pile group were investigated. Finally, the influences of pile layout on the thermomechanical behavior of the energy pile group were identified by designing six different scenarios. The results indicate that under typical intermittent operation conditions, the temperature of the energy pile and surrounding ground near the heat exchange pipe varies periodically. For areas with unbalanced cooling and heating loads, long-term operation of energy piles leads to thermal accumulation, and the maximum temperature of energy piles occurs in the first daily cycle. In summer/winter working conditions, the increase/decrease in pile temperature induces axial compression/tensile stress. When the pile group is partially used as the energy pile, the non-energy pile acts as the “anchor pile”, and it generates the added tensile stress.

Now, most existing dynamic RGB-D SLAM methods are based on deep learning or mathematical models. Abundant training sample data is necessary for deep learning, and the selection diversity of semantic samples and camera motion modes are closely related to the robust detection of moving targets. Furthermore, the mathematical models are implemented at the feature-level of segmentation, which is likely to cause sub or over-segmentation of dynamic features. To address this problem, different from most feature-level dynamic segmentation based on mathematical models, a non-prior semantic dynamic segmentation based on a particle filter is proposed in this paper, which aims to attain the motion object segmentation. Firstly, GMS and optical flow are used to calculate an inter-frame difference image, which is considered an observation measurement of posterior estimation. Then, a motion equation of a particle filter is established using Gaussian distribution. Finally, our proposed segmentation method is integrated into the front end of visual SLAM and establishes a new dynamic SLAM, PFD-SLAM. Extensive experiments on the public TUM datasets and real dynamic scenes are conducted to verify location accuracy and practical performances of PFD-SLAM. Furthermore, we also compare experimental results with several state-of-the-art dynamic SLAM methods in terms of two evaluation indexes, RPE and ATE. Still, we provide visual comparisons between the camera estimation trajectories and ground truth. The comprehensive verification and testing experiments demonstrate that our PFD-SLAM can achieve better dynamic segmentation results and robust performances.

With the rise of the strategy of Coordinated Development for the Beijing-Tianjin-Hebei Region, it is necessary to evaluate the trade-offs/synergies of the survival environment and human well-being in Hebei, the capital region of China. However, existing methods cannot analyze and express trade-offs/synergies of two or more variables simultaneously. Therefore, this paper proposes a new framework to express the trade-offs/synergies among land-use intensity, ecosystem services, and human well-being. In this paper, we first identified the land-use intensity change and land-use transformation and evaluated ecosystem services and human well-being in Hebei from 2000–2015 under the Millennium Ecosystem Assessment framework. Then, the trade-offs/synergies of the three indicators were determined by GIS-based methods and MATLAB. The results show that land-use intensity and human well-being mainly present a synergistic relationship, while ecosystem services and land-use intensity mainly present a trade-off relationship, and ecosystem services and human well-being also present a trade-off relationship in Hebei during 2000–2015. In addition, some regional solutions to achieve sustainable development were proposed: region 1 needs to adjust land-use structure, region 2 needs to protect the ecological environment to improve the supply of ecosystem services, and region 3 needs to commit to improving the regional comprehensive human well-being. This study not only proposes a new framework for analyzing trade-offs/synergies of land use intensity, ecosystem services, and human well-being, but it also provides regional solutions for Hebei to achieve sustainable development.

A high sintering temperature is usually required to acquire excellent performance in the ceramic industry, but it results in high fuel consumption and high pollution. To reduce the sintering temperature and to toughen the porcelain, a self-produced sintering additive of citric acid activated kaolinite was added to the raw material; X-ray powder diffraction (XRD), transmission electron microscope (TEM), scanning electron microscope (SEM), and thermal gravity analysis and differential scanning calorimetry (TG-DSC) were used to characterize the samples, and the toughening mechanism was discussed. The citric acid activated kaolinite obtained high activity and a large specific surface area. After introducing the activated kaolinite, the bending strength of porcelain at 1270 °C increased from 100.08 MPa to 124.04 Mpa, which was 11.45% higher than that of porcelain without activated kaolinite at 1350 °C. The results of XRD revealed that the content of mullite increased and the quartz decreased at 1270 °C, and the well-distributed needle-like mullite was observed in the images of SEM with the addition of citric acid activated kaolinite. The TG-DSC results indicated adding activated kaolinite to porcelain raw materials reduced the formation of mullite to 994.6 °C. The formation of mullite in a lower temperature served as mullite seeds in a green body during firing, and it enhanced the growth of mullite. These contributed to the appropriate phase composition and the excellent microstructure of porcelain. Thus, the distinguished mechanical performance of porcelain was obtained. Moreover, the sintering additive had no adverse effect on the porcelain body as citric acid-activated kaolinite was one of the main components of the porcelain raw material.

The traction motor (TM) is an essential part of the high-speed train, the health condition of which determines the quality and safety of the vehicle. Hence, this study proposed a novel approach to diagnosing and predicting the TM stator interturn short-circuit fault (SISCF). Based on the Park vector (PV) of the stator current, this method could overcome the interference of current sensor errors, null shift, and motor frequency fluctuations in the actual conditions. More specifically, Park’s transformation was used to obtain the PV of the stator current. Then, the PV was fitted to obtain the elliptical trajectory and its parameters from which the negative sequence component of the stator current could be calculated. Finally, the SISCF diagnosis and prediction method were realized by the magnitude and trend of the negative current as well as the inclination of the trajectory ellipse. Furthermore, the performance of the proposed method was validated by a simulation model and a series of experiments. The simulation results were consistent with the experimental results, supporting the validity and correctness of the method proposed in this study.

Iron is among the most abundant elements in the soil of paddy fields, and its valence state and partitioning can be transformed by flooding and drainage alternations. However, little is known about the function of soil microbes that interact with Fe(II). In this study, sandy and loamy soils originating from rice fields were treated with Fe(II) at low and high concentrations. The findings demonstrate that additional Fe(II) has various effects on the soil’s microbial community structure and metabolic pathways. We conclude that Fe(II) at high concentrations reduced bacterial abundance and diversity in two textured paddy soils, yet the abundance in loamy soils was higher than it was in sandy soil. Additionally, in environments with high Fe(II) levels, the relative abundance of both anaerobic and chemoautotrophic bacteria increased. The Fe(II) concentration was positively correlated with total reduced substances but negatively correlated with redox potential and pH. Co-occurrence networks revealed that Fe(II) significantly promoted interactions with the most anaerobic and chemoautotrophic bacteria. In addition, adding Fe(II) greatly increased the number of more complex bacterial networks, and an increase in the number of mutually beneficial taxa occurred. We found that Fe(II) promoted the methane pathway, the Calvin cycle, and nitrate reduction to small but significant extents. These pathways involve the growth and interrelation of autotrophic and anaerobic bacteria. These results suggest that changes in the bacterial community structure occur in many dry–wet alternating environments.

In this paper, the research emphasis focuses on the tracking precision of position loading and torque loading systems with velocity-sensitive and adaptive robust control. Compared with conventional PID control, the improved PID control based on velocity-sensitive fully manifests its superiority to position loading. By contrast, we analyzed the possible influence for the control difference of conventional PID and velocity-sensitive with PID. Furthermore, for the purpose of accurate torque loading, a mathematical model was established through dynamics analysis and the adaptive robust controller, where the adaptive robust control algorithm is designed to generate the reference position trajectory for the servo system in the upper controller while closed-loop position tracking is performed in the underlying controller, was built based on a state space equation. In the end, an experimental platform was built to verify the feasibility and advantages of the position and torque loading system with the velocity-sensitive and adaptive robust control.

Metal-supported catalyst with high activity and relatively simple preparation method is given priority to industrial production. In this work, this study reported an easily accessible synthesis strategy to prepare Mott-Schottky-type N-doped carbon encapsulated metallic Co (Co@Np+gC) catalyst by high-temperature pyrolysis method in which carbon nitride (g-C3N4) and dopamine were used as support and nitrogen source. The prepared Co@Np+gC presented a Mott-Schottky effect; that is, a strong electronic interaction of metallic Co and N-doped carbon shell was constructed to lead to the generation of Mott-Schottky contact. The metallic Co, due to high work function as compared to that of N-doped carbon, transferred electrons to the N-doped outer shell, forming a new contact interface. In this interface area, the positive and negative charges were redistributed, and the catalytic hydrogenation mainly occurred in the area of active charges. The Co@Np+gC catalyst showed excellent catalytic activity in the hydrogenation of phenylacetylene to styrene, and the selectivity of styrene reached 82.4%, much higher than those of reference catalysts. The reason for the promoted semi-hydrogenation of phenylacetylene was attributed to the electron transfer of metallic Co, as it was caused by N doping on carbon.

A new Ni metal organic framework based on 2,2′-Biphenyldicarboxylic, 4,4′- bipyridine as linker is prepared by hydrothermal reaction and directly used as an electrode material for supercapacitor and the detection of sarcosine. [Ni3(BIPY)3(BPDA)2(HCOO)2(H2O)2]n (Ni-1; BIPY = 4,4′-bipyridine; BPDA = 2,2′-Biphenyldicarboxylate) displays the specific capacitance of the Ni-1 are 667 F/gat 1 A/g and retention is 82% of initial capacitance at 1 A/g. The excellent electrochemical property is ascribed to the intrinsic nature of Ni-1. Furthermore, the sarcosine sensing performance of the Ni-1 electrode is evaluated in 0.1 M of NaOH solution and the electrode showed a wider range of linear response 1 × 10−4 M to 1 × 10−3 M. Thus, the results show that the Ni-1 is a potential candidate for not only sensing of sarcosine but also supercapacitor application.

Honeycomb materials have low density, high specific strength and stiffness, impact resistance, and good sound insulation effect, and therefore are widely used in aerospace, automobile, and ship field applications. In this paper, we study the in-plane impact response of a second-order hierarchical honeycomb (SHH) material. Its main structure is a hexagonal honeycomb, and the substructure is composed of an augmented double arrow honeycomb (ADAH) negative Poisson’s ratio unit. Through a finite element simulation, the failure stress of an hierarchical honeycomb in two directions of quasi-static crushing and dynamic crushing was analyzed; the failure stress of the hierarchical honeycomb under different densities, different speeds, and different substructures was discussed; and the theoretical failure stress was verified. The numerical analysis results show that a second-order hierarchical honeycomb (SHH) has better collapse stress than a first-order regular hexagonal honeycomb (FHH) and an augmented double arrow honeycomb (ADAH).

RGB-D SLAM (Simultaneous Localization and Mapping) generally performs smoothly in a static environment. However, in dynamic scenes, dynamic features often cause wrong data associations, which degrade accuracy and robustness. To address this problem, in this paper, a new RGB-D dynamic SLAM method, PLD-SLAM, which is based on point and line features for dynamic scenes, is proposed. First, to avoid under-over segmentation caused by deep learning, PLD-SLAM combines deep learning for semantic information segmentation with the K-Means clustering algorithm considering depth information to detect the underlying dynamic features. Next, two consistency check strategies are utilized to check and filter out the dynamic features more reasonably. Then, to obtain a better practical performance, point and line features are utilized to calculate camera pose in the dynamic SLAM, which is also different from most published dynamic SLAM algorithms based merely on point features. The optimization model with point and line features is constructed and utilized to calculate the camera pose with higher accuracy. Third, enough experiments on the public TUM RGB-D dataset and the real-world scenes are conducted to verify the location accuracy and performance of PLD-SLAM. We compare our experimental results with several state-of-the-art dynamic SLAM methods in terms of average localization errors and the visual difference between the estimation trajectories and the ground-truth trajectories. Through the comprehensive comparisons with these dynamic SLAM schemes, it can be fully demonstrated that PLD-SLAM can achieve comparable or better performances in dynamic scenes. Moreover, the feasibility of camera pose estimation based on both point features and line features has been proven by the corresponding experiments from a comparison with our proposed PLD-SLAM only based on point features.

Information on the mixed use of buildings helps understand the status of mixed-use urban vertical land and assists in urban planning decisions. Although a few studies have focused on this topic, the methods they used are quite complex and require manual intervention in extracting different function patterns of buildings, while building recognition rates remain unsatisfying. In this paper, we propose a new method to infer the mixed use of buildings based on a tensor decomposition algorithm, which integrates information from both high-resolution remote sensing images and social sensing data. We selected the Tianhe District of Guangzhou, China to validate our method. The results show that the recognition rate of buildings can reach 98.67%, with an average recognition accuracy of 84%. Our study proves that the tensor decomposition algorithm can extract different function patterns of buildings unsupervised, while remote sensing data can provide key information for inferring building functions. The tensor decomposition-based method can serve as an effective and efficient way to infer the mixed use of buildings, which can achieve better results with simpler steps.

In view of the problems encountered in previous hydraulic 6-DOF parallel mechanism projects, flexible modes appear that the actual natural frequencies of x and y degrees of freedom of the parallel mechanism are lower than those obtained through calculation. The phenomenon above not only decreases the dynamic response characteristics of the mechanism, but also leads to doubts about the actual performance of the mechanism. The real reason for the phenomenon above is solved in this paper. First the flexible structure of the hydraulic cylinder is analyzed and simplified, and then the dynamic model of the rigid-flexible 6-DOF parallel mechanism is established with the extended Hamilton’s principle. Finally the rigid-flexible modes are calculated with the dynamic model obtained, further analysis and verification with a simulation model and an experimental platform are also conducted. Results show that the phenomenon of the flexible modes is mainly caused by the O-rings of the step-seals of the guide sleeve and those with less elasticity should be adopted to keep the dynamic characteristics of the parallel mechanism.

The torque mode is more suitable for the direct drive 6 degree of freedom (6-DOF) parallel mechanism than the speed mode that both dynamic coupling and current coupling among motors are easily solved, but its key parameters and dynamic characteristics have never been studied, which are important and are the goals of this paper. First the hydraulic system of the direct drive 6-DOF parallel mechanism is simplified. Then the transfer function of the direct drive hydraulic system with the torque mode is deduced together with that of the speed mode. Finally, comparative experiments are conducted. Results show that the dynamic characteristics of the system with the torque mode which are generally worse than those with the speed mode, are mainly determined by the parameters of the motor-pump second-order element of the transfer function composed of two under-damped second-order elements, proportion differentiation (PD) control strategy and dynamic pressure feedback (DPF) control strategy are useful for the system with the torque mode, but practical and effective methods are still needed.

Sulfuration flotation is the most widely used technology in malachite beneficiation. However, the inhomogeneity of malachite surfaces usually results in a non-uniform sulfuration surface. The motivation of this work is attempt to adopt different functional combination collectors to enhance the sulfuration flotation of malachite. Accordingly, the flotation behaviors and adsorption mechanisms of benzohydroxamic acid (BHA) and sodium butyl-xanthate (SBX) on the surface of malachite were systematically investigated using flotation tests, zeta-potential measurements, Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and first-principle calculations. The test results of vulcanization flotation showed that the combined collectors of SBX with BHA possessed a higher recovery than only using SBH by 20%, indicating that there may be a synergistic effect between BHA and SBX. The IR and Raman spectroscopy demonstrated that both BHA and SBX could chemically adsorb onto the malachite surface. The density functional theory (DFT) calculation results further indicated that the combined adsorption energy of BHA and SBX was much lower than that of only BHA or SBX, which confirmed the synergistic effects of BHA and SBX on the malachite surface. This work may shed new light on the design and development of more efficient combined flotation reagents.

In this study, salicylhydroxamic acid (SHA), which exhibits superior flotation performance to conventional collector benzohydroxamic acid (BHA), was first introduced in ilmenite flotation. The addition of lead(II) can significantly increase the recovery of ilmenite using SHA as collector. Thus, the adsorption mechanism of SHA on lead(II)-activated ilmenite surface was systematically studied using micro-flotation tests, adsorption analysis, zeta potential measurements, Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). Micro-flotation results revealed that SHA had stronger collecting ability than BHA, and ilmenite floatability could be activated by lead ions with either SHA or BHA as collector. Ilmenite showed good floatability at pH 6–8 (over 90% recovery) in the presence of Pb2+ and SHA. In such conditions, the main lead species of Pb(OH)+ and Pb2+ acted as active sites and caused positive surface potential shifts, thereby increasing the adsorbed amounts of negatively charged SHA on the surface of the mineral. FTIR and XPS analyses suggested that the lead species was chemically adsorbed on the surface of ilmenite to form active sites chelated by SHA. Moreover, the free lead ions in solution might form the Pb–SHA complexes to adsorb on the mineral surface, thereby increasing the floatability of ilmenite.

In order to ensure good dynamic characteristics, servo valve is usually adopted as the drive part of Stewart manipulator which causes huge power consumption, while direct drive electro-hydraulic servo system has the advantages of energy saving, simple structure, convenient installation, and low failure rate. But its dynamic characteristics are so poor that it can only be applied to occasions where quick response is not needed. On the consideration above, following works are done in this paper. Since current coupling exists in the control system based on the speed of the servo motor as the control input, the control system of the direct drive Stewart manipulator is established based on the current of the servo motor as the control input in which the current coupling can be solved. In order to improve the dynamic characteristics of the direct drive Stewart manipulator, a Proportion Differentiation (PD) plus dynamic pressure feedback control strategy is also put forward in this paper, which is verified by using a simulated hydraulically driven Stewart manipulator. Simulation results show that both dynamic coupling and current coupling are solved and the control strategy proposed in this paper can significantly increase the bandwidths of all degrees of freedom.

Aiming at inertial and viscous parameter identification for the Stewart manipulator regardless of the influence of Coulomb friction, a simple and effective dynamical parameter identification method based on wavelet transform and joint velocity analysis is proposed in this paper. Compared with previously known identification methods, the advantages of the new approach are that (1) the excitation trajectory is easy to design, and (2) it can not only identify the inertial matrix, but also the viscous matrix accurately regardless of the influence of Coulomb friction. Comparison is made among the identification method proposed in this paper, another identification method proposed previously, and the true value calculated with a formula. The errors from results of different identification methods demonstrate that the method proposed in this paper shows great adaptability and accuracy.

Epimedium folium is the major medicinally-used organ of Epimedium species and its metabolic changes during the leaf growth have not been studied at the metabolomic level. E. pubescens is one of five recorded species in the Pharmacopoeia of the People’s Republic of China and widely grows in China. A UPLC-ESI-MS/MS-based targeted metabolomic analysis was implemented to explore the metabolite composition in E. pubescens leaves under the cultivation condition and further to investigate their temporal variations among four representative growth stages. A total of 403 metabolites, including 32 hitherto known in Epimedium species, were identified in E. pubescens leaf, of which 302 metabolites showed the growth/development-dependent alterations. Flavonoid-type compounds were the major composition of the metabolites identified in this study. Most flavonoids, together with tannin-type and lignans and coumarin-type compounds, were up-regulated with E. pubescens leaf growth and maturation after the full flowering stage. Our results not only greatly enriched the existing Epimedium phytochemical composition database and also, for the first time, provided the metabolomics-wide information on metabolic changes during E. pubescens leaf growth and development, which would facilitate in the choice of an optimum harvest time to balance a higher biomass yield of Epimedium folium with its better medicinal quality.

With extensive application of RGB-D cameras in robotics, computer vision, and many other fields, accurate calibration becomes more and more critical to the sensors. However, most existing models for calibrating depth and the relative pose between a depth camera and an RGB camera are not universally applicable to many different kinds of RGB-D cameras. In this paper, by using the collinear equation and space resection of photogrammetry, we present a new model to correct the depth and calibrate the relative pose between depth and RGB cameras based on a 3D control field. We establish a rigorous relationship model between the two cameras; then, we optimize the relative parameters of two cameras by least-squares iteration. For depth correction, based on the extrinsic parameters related to object space, the reference depths are calculated by using a collinear equation. Then, we calibrate the depth measurements with consideration of the distortion of pixels in depth images. We apply Kinect-2 to verify the calibration parameters by registering depth and color images. We test the effect of depth correction based on 3D reconstruction. Compared to the registration results from a state-of-the-art calibration model, the registration results obtained with our calibration parameters improve dramatically. Likewise, the performances of 3D reconstruction demonstrate obvious improvements after depth correction.

Currently, hundreds of herbal products with potential hepatotoxicity were available in the literature. A comprehensive summary and analysis focused on these potential hepatotoxic herbal products may assist in understanding herb-induced liver injury (HILI). In this work, we collected 335 hepatotoxic medicinal plants, 296 hepatotoxic ingredients, and 584 hepatoprotective ingredients through a systematic literature retrieval. Then we analyzed these data from the perspectives of phylogenetic relationship and structure-toxicity relationship. Phylogenetic analysis indicated that hepatotoxic medicinal plants tended to have a closer taxonomic relationship. By investigating the structures of the hepatotoxic ingredients, we found that alkaloids and terpenoids were the two major groups of hepatotoxicity. We also identified eight major skeletons of hepatotoxicity and reviewed their hepatotoxic mechanisms. Additionally, 15 structural alerts (SAs) for hepatotoxicity were identified based on SARpy software. These SAs will help to estimate the hepatotoxic risk of ingredients from herbs. Finally, a herb-ingredient network was constructed by integrating multiple datasets, which will assist to identify the hepatotoxic ingredients of herb/herb-formula quickly. In summary, a systemic analysis focused on HILI was conducted which will not only assist to identify the toxic molecular basis of hepatotoxic herbs but also contribute to decipher the mechanisms of HILI.

A scientific and rigorous study on the adsorption behavior and molecular mechanism of collector sodium oleate (NaOL) on a Ca2+-activated hydroxylated α-quartz surface was performed through experiments and density functional theory (DFT) simulations. The rarely reported hydroxylation behaviors of water molecules on the α-quartz (101) surface were first innovatively and systematically studied by DFT calculations. Both experimental and computational results consistently demonstrated that the adsorbed calcium species onto the hydroxylated structure can significantly enhance the adsorption of oleate ions, resulting in a higher quartz recovery. The calculated adsorption energies confirmed that the adsorbed hydrated Ca2+ in the form of Ca(H2O)3(OH)+ can greatly promote the adsorption of OL− on hydroxylated quartz (101). In addition, Mulliken population analysis together with electron density difference analysis intuitively illustrated the process of electron transfer and the Ca-bridge phenomenon between the hydroxylated surface and OL− ions. This work may offer new insights into the interaction mechanisms existing among oxidized minerals, aqueous medium, and flotation reagents.

Buildings are fundamental components of cities. Understanding the function of buildings is therefore of great importance for urban development and management. Some studies have identified building functions using spatiotemporal data, which assumes that buildings with the same function have similar temporal activity patterns. However, these methods present difficulties in coping with the situation when buildings with the same function have heterogeneous activity patterns. To solve this problem, this research proposes a new method to identify building functions from the perspective of the spatial distribution and spatial interactions of human activities. First, taxi data were used to acquire the spatiotemporal interaction characteristics among buildings with different functions. Then, the spatiotemporal population density distribution was adopted to depict the building vitality. Finally, an iterative clustering method was introduced to identify the building functions. The proposed scheme was applied in the Haizhu district of Guangzhou and compared with the traditional method. The results prove that the spatial interaction characteristics are more helpful than the temporal variation characteristics and therefore can be used to improve the accuracy of building function identification. A higher accuracy for identifying building functions can be realized by combining the spatiotemporal interactions and building vitality characteristics. The overall accuracy reaches 0.8566, with a Kappa coefficient of 0.8174, which are both better than the results of using a single characteristic only.

As one of the leading causes of drug failure in clinical trials, drug-induced liver injury (DILI) seriously impeded the development of new drugs. Assessing the DILI risk of drug candidates in advance has been considered as an effective strategy to decrease the rate of attrition in drug discovery. Recently, there have been continuous attempts in the prediction of DILI. However, it indeed remains a huge challenge to predict DILI successfully. There is an urgent need to develop a quantitative structure–activity relationship (QSAR) model for predicting DILI with satisfactory performance. In this work, we reported a high-quality QSAR model for predicting the DILI risk of xenobiotics by incorporating the use of eight effective classifiers and molecular descriptors provided by Marvin. In model development, a large-scale and diverse dataset consisting of 1254 compounds for DILI was built through a comprehensive literature retrieval. The optimal model was attained by an ensemble method, averaging the probabilities from eight classifiers, with accuracy (ACC) of 0.783, sensitivity (SE) of 0.818, specificity (SP) of 0.748, and area under the receiver operating characteristic curve (AUC) of 0.859. For further validation, three external test sets and a large negative dataset were utilized. Consequently, both the internal and external validation indicated that our model outperformed prior studies significantly. Data provided by the current study will also be a valuable source for modeling/data mining in the future.

The flotation separation of scheelite from calcite is problematic, where sodium silicate modified by polyvalent metal ions has shown some advantages for selective depression. In this study, an Al-Na2SiO3 polymer was used as the depressant for the flotation separation of scheelite from calcite using a lead complex of benzohydroxamic acid (Pb-BHA) as the collector. Furthermore, a number of measurements were conducted to investigate the structure of the Al-Na2SiO3 polymer and its adsorption behavior with Pb-BHA complexes on the mineral surface. Flotation experiments indicated that the Al-Na2SiO3 polymer shows good selectivity for the flotation separation of scheelite from calcite at pH 8, where the optimum ratio of sodium silicate to aluminum sulfate was 2:1. Fourier-Transform Infrared (FTIR) and solution chemical analyses revealed that aluminum hydroxide complexes and the hydroxy moiety of silicic acid are able to self-assemble via condensation affording an Al-Na2SiO3 polymer, i.e., a composite aluminosilicate polymer. The zeta potential measurements and adsorption capacity measurements indicated that, upon adsorption of the Al-Na2SiO3 polymer and Pb-BHA complexes on the mineral surface, the Al-Na2SiO3 polymer had less influence on the adsorption of Pb-BHA complexes on the scheelite surface, while the opposite was true for calcite. Therefore, more Pb-BHA complexes and fewer Al-Na2SiO3 polymers were deposited on the scheelite surface, while fewer Pb-BHA complexes and more Al-Na2SiO3 polymers were adsorbed on the calcite surface. The selective separation of scheelite from calcite was attributed to the cooperative selectivity of the Pb-BHA complexes and Al-Na2SiO3 polymer.

Diabetic nephropathy (DN) is a leading cause of end-stage renal failure, and no effective treatment is available. Notoginsenoside R1 (NGR1) is a novel saponin that is derived from Panax notoginseng, and our previous studies showed the cardioprotective and neuroprotective effects of NGR1. However, its role in protecting against DN remains unexplored. Herein, we established an experimental model in db/db mice and HK-2 cells exposed to advanced glycation end products (AGEs). The in vivo investigation showed that NGR1 treatment increased serum lipid, β2-microglobulin, serum creatinine, and blood urea nitrogen levels of db/db mice. NGR1 attenuated histological abnormalities of kidney, as evidenced by reducing the glomerular volume and fibrosis in diabetic kidneys. In vitro, NGR1 treatment was further found to decrease AGE-induced mitochondria injury, limit an increase in reactive oxygen species (ROS), and reduce apoptosis in HK-2 cells. Mechanistically, NGR1 promoted nucleus nuclear factor erythroid 2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1) expressions to eliminate ROS that induced apoptosis and transforming growth factor beta (TGF-β) signaling. In summary, these observations demonstrate that NGR1 exerts renoprotective effects against DN through the inhibition of apoptosis and renal fibrosis caused by oxidative stress. NGR1 might be a potential therapeutic medicine for the treatment of DN.

Patients with diabetes mellitus (DM) suffer more risks from diabetic encephalopathy such as cognitive dysfunction and depressive-like behaviors. Numerous studies show that ER (endoplasmic reticulum) stress and inflammation play important roles in the development of diabetic encephalopathy. Gastrodin (Gas), one major component of Gastrodia elata, is traditionally used in central nervous system disorders and is believed to possess anti-inflammatory, anti-apoptotic, and other neuroprotective effects. This present study aims to explore the protective effects of Gas on diabetic encephalopathy. Gas was administrated daily (70 and 140 mg/Kg) for 12 weeks. Meanwhile, the fasting blood glucose and body weight of db/db mice were measured every two weeks. After Gas treatment, the Morris water maze (MWM) test and novel object recognition (NOR) test were performed to assess the learning and memory functions of db/db mice, and the forced swim test was performed to evaluate depressive-like behaviors of db/db mice. Additionally, the expression of ER stress and Nucleotide binding and oligomerization domain-like (Nod) receptor family pyrin domain-containing 3 (NLRP3) inflammasome related proteins were evaluated by using Western blot. Our study suggested that Gas attenuated blood glucose levels and dyslipidemia of db/db mice. It has been shown that Gas could improve learning and memory function and depressive-like behaviors of db/db mice. Moreover, Gas inhibited ER stress and NLRP3 inflammasome activation in the hippocampus. Taken together, this study demonstrates that Gas attenuates the diabetic encephalopathy by inhibiting ER stress and NLRP3 inflammasome activation.