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Coal fly ash (CFA), hazardous to the environment and human health, has been considered to be a potential alternative source for rare earth elements (REEs) in recent years. However, information on how REEs distribute and occur in coal fly ash is still incomplete. In this work, particle size analysis, inductively coupled plasma–mass spectrometry, scanning electron microscopy, and electron probe microanalysis were applied to study the occurrence and distribution of REEs in a fly ash sample from the Qianxi coal-fired power plant in Guizhou province. The results show that the REEs content in the CFA was 630.51 ppm. Wet grinding-enhanced leaching experiments revealed that a part of the rare earth particles was encapsulated within the glass body. These rare earth particles could be liberated and released to a certain extent by wet grinding, which would increase the acid-leaching recovery of REEs from 23.49% to 41.68%. This study classifies the speciation of REEs in coal fly ash as (1) amorphous glassy particles with REE minerals or compounds encapsulated inside; (2) amorphous glassy particles with REEs distributed throughout; and (3) discrete REE minerals or compounds. The results of this study are a basis for developing an economically viable and environmentally sustainable technology for recovering REEs from CFA. [ABSTRACT FROM AUTHOR]

Schisandra chinensis (Turcz.) Baill (SC) is a traditional sedative in China, with wide applications for treating various neurological disorders. Its polysaccharide component has been gaining increased attention for its potential in nerve protection. While raw SC is the primary focus of current research, its processed products are primarily utilized as clinical medicines. Notably, limited research exists on the mechanisms underlying the effects of wine-processed Schisandra chinensis polysaccharide (WSCP) in Alzheimer's Disease (AD). Therefore, this study seeks to assess the therapeutic impact of WSCP on AD mice and investigate the underlying mechanisms through biochemical and metabolomics analyses. The results demonstrate that WSCP exerts significant therapeutic effects on AD mice by enhancing learning and memory abilities, mitigating hippocampal neuronal damage, reducing abnormal amyloid-beta (Aβ) deposition, and attenuating hyperphosphorylation of Tau. Biochemical analysis revealed that WSCP can increase SOD content and decrease MDA, IL-6, and TNF-α content in AD mice. Furthermore, serum metabolomic results showed that WSCP intervention can reverse metabolic disorders in AD mice. 43 endogenous metabolites were identified as potential biomarkers for WSCP treatment of AD, and the major metabolic pathways were Ala, Glu and Asp metabolism, TCA cycle. Overall, these findings will provide a basis for further development of WSCP. • The structure of WSCP was characterized. • WSCP has the potential to treat AD. • Forty-three metabolites and two metabolic pathways were identified as biomarkers and metabolic pathways for the neuroprotective effect of WSCP. [ABSTRACT FROM AUTHOR]

Circulating exosomal microRNAs (ex-miRNAs) are reflective of the characteristics of the tumor and are valuable biomarkers in different types of tumor. In addition, miRNAs serve important roles in tumor progression and metastasis. The present study aimed to investigate the circulating ex-miRNA-21 and miRNA-210 as novel biomarkers for patients with pancreatic cancer (PC). For this purpose, serum ex-miRNAs were extracted from the serum of patients with PC (n=30) and chronic pancreatitis (CP) (n=10) using an RNA isolation kit. For exosome identification in serum, transmission electron micrographs were used to determine crystalline structure, western blotting was used to identify exosomal markers, and NanoSight was used for nanoparticle characterization. The relative expression levels of ex-miRNAs were quantified using quantitative PCR and compared between patients with PC and CP. The expression levels of both ex-miRNA-21 and miRNA-210 were significantly higher in patients with PC compared with patients with CP (both P<0.001). However, no significant difference in the relative serum levels of free miR-21 and miR-210 was observed between the 2 groups of patients (both P>0.05). ex-miRNA-21 and miRNA-210 were associated with tumor stage, as well as other factors. The diagnostic potential of ex-miRNA-21 and miRNA-210 levels was 83 and 85%, respectively. In addition, when ex-miRNA and serum carbohydrate antigen 19-9 expression levels were combined, the accuracy increased to 90%. The present study identified that serum ex-miRNAs, miRNA-21 and miRNA-210 may be of value as potential biomarkers and therapeutic targets for the diagnosis and treatment of PC. [ABSTRACT FROM AUTHOR]

Mixed use has been extensively applied as an urban planning principle and hinders the study of single urban functions. To address this problem, it is worth decomposing the mixed use. Inspired by the concept of spectral unmixing in remote sensing applications, this paper proposes a framework for mixed-use decomposition based on big geo-data. Mixed-use decomposition in terms of human activities differs from traditional land use research, and it is more reasonable to infer the actual urban function of land. The framework consists of four steps, namely temporal activity signature extraction, urban function base curve extraction, mixed-use decomposition, and result validation. First, the temporal activity signatures (TASs) of each zone are extracted as the proxy of human activity patterns. Second, the diurnal TASs of routine activities are extracted as urban function base curves (i.e. endmembers). Third, a linear decomposition model is used to decompose the mixed use and obtain multiple results (urban function composition, dynamic activity proportions, and the mixing index). Finally, result validation strategies are concluded. This framework offers method extensibility and has few requirements for the input data. It is validated by means of a case study of Beijing, based on a social media check-in dataset. [ABSTRACT FROM AUTHOR]

To observe the effect of borax on Hedgehog signaling pathway protein expression of human hepatocellular carcinoma HepG2 cells. Methods HepG2 cells were randomly divided into two groups. The experimental group was treated with 4. 0 mmol/L borax for 24 h, and the control group was not treated. The cells were collected and the Hedgehog signaling pathway proteins Gli2, Ptchl and Cyclin Dl were detected by real-time quantitative PCR ( qRT-PCR). The Hedgehog signaling pathway proteins Gli2, Ptchl and Cyclin Dl were detected by Western blotting. Results The relative mRN A expression levels of Gli2, Ptchl and Cyclin Dl were 0. 58 ± 0. 05, 0. 64 ± 0. 08, and 0. 35 ± 0. 03, respectively, and the corresponding protein relative expression levels were 1. 14 ± 0. 03, 0. 93 ± 0. 02, and 1. 86 ± 0. 02, respectively, which were lower than those of the control group, with statistically significant differences ( all P < 0. 05). Conclusion Borax may down-regulate the expression of Hedgehog signaling pathway protein in human hepatocellular carcinoma HepG2 cells, which provides a basis for the development and target of new anti-tumor drugs. [ABSTRACT FROM AUTHOR]

Street-level imagery has covered the comprehensive landscape of urban areas. Compared to satellite imagery, this new source of image data has the advantage in fine-grained observations of not only physical environment but also social sensing. Prior studies using street-level imagery focus primarily on urban physical environment auditing. In this study, we demonstrate the potential usage of street-level imagery in uncovering spatio-temporal urban mobility patterns. Our method assumes that the streetscape depicted in street-level imagery reflects urban functions and that urban streets of similar functions exhibit similar temporal mobility patterns. We present how a deep convolutional neural network (DCNN) can be trained to identify high-level scene features from street view images that can explain up to 66.5% of the hourly variation of taxi trips along with the urban road network. The study shows that street-level imagery, as the counterpart of remote sensing imagery, provides an opportunity to infer fine-scale human activity information of an urban region and bridge gaps between the physical space and human space. This approach can therefore facilitate urban environment observation and smart urban planning. [ABSTRACT FROM AUTHOR]

In the era of big data, large amounts of detailed spatial interaction data are readily available due to the increasing pervasiveness of location-aware devices and techniques. Such data are often applied in the research of spatial structures, land use characteristics, and human activity regularities. However, visualizing such data on maps is a great challenge. Existing approaches either encounter overlapping and intersection problems, which may cause information loss or distortion, or are unable to present interaction characteristics. Consequently, the functional and positional features of places and human mobility trends are not fully demonstrated. We propose direction-based pattern maps, a new visualization method to display the spatial interaction pattern of every place by aggregating spatial interaction data in cardinal directions. This approach can well represent local interaction characteristics and is applicable to different spatial scales. Owing to regular hexagonal tessellations, it can avoid cluttering problems and maintain a geographical context. A case study using Beijing taxi trip data is conducted to validate the usefulness of our approach. [ABSTRACT FROM AUTHOR]

Cimicifuga simplex is a medicinal herb which has a wide range of biological activities. We isolated seven 9,19-cycloartenol glycosides from the roots of C. simplex , and among the glycosides, G3 exhibited the strongest inhibitory effect on immune responses, including suppressing the differentiation of CD 4+ T cells and directly suppressing the cytokine-induced JAK/STAT signaling pathways. In the IL-23-induced mouse ear model of skin disease, G3 repressed disease development by inhibiting the expression of pro-inflammatory mediators in murine ear skin. Moreover, G3 affected the maturation of DCs in vitro , thereby inducing T cell differentiation, resulting in an increased Treg phenotype and decreased Th17 phenotype. This study provides new evidence that G3 might ameliorate chronic inflammatory skin diseases by suppressing pathogenic CD 4+ T cell differentiation and the IL-17 + RORγt + /IL-10 + FoxP3 + ratio. These findings suggest that G3 might mediate the therapeutic effects observed in psoriasis patients following treatment with C. simplex . [ABSTRACT FROM AUTHOR]

Space and place are two fundamental concepts in geography. Geographical factors have long been known as drivers of many aspects of people's social networks. But whether and how space and place affect social networks differently are still unclear. The widespread use of location-aware devices provides a novel source for distinguishing the mechanisms of their impacts on social networks. Using mobile phone data, this paper explores the effects of space and place on social networks. From the perspective of space, we confirm the distance decay effect in social networks, based on a comparison between synthetic social ties generated by a null model and actual social ties derived from real-world data. From the perspective of place, we introduce several measures to evaluate interactions between individuals and inspect the trio relationship including distance, spatio-temporal co-occurrence, and social ties. We found that people's interaction is a more important factor than spatial proximity, indicating that the spatial factor has a stronger impact on social networks in place compared to that in space. Furthermore, we verify the hypothesis that interactions play an important role in strengthening friendships. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PC) is a deadly disease, and its post‐transcriptional gene regulation mechanism remains unclear. The abundant extracellular matrix (ECM) in PC plays an important role in tumor progression. This study is the first to focus on the role of N6‐methyladenosine (m6A) RNA methylation, an emerging post‐transcriptional regulatory mechanism, in the regulation of the ECM in PC. Here, we found that ADAMTS2, COL12A1, and THBS2 were associated with the prognosis of PC by comprehensive analysis of differentially expressed genes from two independent GEO expression profile datasets and m6A‐related genes in RMVar database (PAAD). GO and KEGG enrichment analysis found that these m6A‐related targets are chiefly functionally concentrated in the ECM region and participate in ECM signal transduction. Correlation analysis revealed that these genes can be regulated by the demethylase FTO. Cell biology function assays showed that knockdown of FTO‐inhibited PC cell abilities to migrate and invade in vitro. qRT‐PCR and MeRIP experiments showed that after knockdown of FTO, the mRNA levels of ADAMTS2, COL12A1, and THBS2 and their m6A modification levels were significantly reduced. These results indicate that m6A RNA demethylation is associated with the regulation of ECM in PC. In conclusion, m6A RNA demethylase FTO regulates ECM‐related genes and promotes PC cell abilities to migrate and invade, our work provides a new perspective on the molecular mechanism of PC progression. [ABSTRACT FROM AUTHOR]

Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data. [ABSTRACT FROM AUTHOR]

Background: High-intensity focused ultrasound (HIFU) is a widely applied to treatment for unresectable hepatocellular carcinoma. However, insufficient HIFU can result in rapid progression of the residual tumor. The mechanism of such rapid growth of the residual tumor after HIFU ablation is poorly understood. Objective: The aim of this study was to investigate the dynamic angiogenesis of residual tumor, and the temporal effect and mechanism of the HIF-1, 2α in the residual tumor angiogenesis. Methods: Xenograft tumors of HepG2 cells were created by subcutaneously inoculating nude mice (athymic BALB/c nu/nu mice) with hepatoma cells. About thirty days after inoculation, all mice (except control group) were treated by HIFU and assigned randomly to 7 groups according to various time intervals (1st, 3rd, 5th day (d) and 1st, 2nd, 3rd, 4th week (w)). The residual tumor tissues were obtained from the experimental groups at various time points. Protein levels of HIF-1α, HIF-2α, VEGF-A, and EphA2 were quantified by immunohistochemistry analysis and Western Blot assays, and mRNA levels measured by Q-PCR. Microvascular density was calculated with counting of CD31 positive vascular endothelial cells by immunohistochemical staining. Results: Compared with the control group, protein and mRNA levels of HIF-1α reached their highest levels on the 3rd day (P<0.01), then decreased (P<0.05). HIF-2α expression reached its highest level on the 2nd week compared with control group (P<0.01), then decreased (2w–4w) (P<0.05). The protein and mRNA levels of VEGF-A and EphA2 in the residual tumor tissues group that received HIFU were significantly decreased until 1 week compared with the control group (P<0.01). However, the levels increased compared to controls in 2–4 weeks (P<0.05). Similar results were obtained for MVD expression (P<0.05). Conclusion: Insufficient HIFU ablation promotes the angiogenesis in residual carcinoma tissue over time. The data indicate that the HIF-1, 2α/VEGFA/EphA2 pathway is involved. [ABSTRACT FROM AUTHOR]

[Display omitted] • Random forest can analyze the NIR data and identify Schisandra chinensis' origin. • Quantitative model was established by fitting the NIR data with colorimetric data. • NIR provides a mature method for the determination and quality evaluation of TCM. In this study, a classification model was established based on near-infrared spectroscopy and random forest method to accurately distinguish three samples of Schisandra chinensis from different habitats. At the same time, the feasibility of fast and effective prediction of polysaccharide contents in Schisandra chinensis by near-infrared spectroscopy combined with chemometrics was evaluated. In this paper, phenol sulfuric acid method was used to determine the content of total polysaccharides in samples, and partial least squares regression algorithm was used to link the spectral information with the reference value. Different spectral pretreatment methods were used to optimize the model to improve its predictability and stability. The results showed that random forest could distinguish these samples accurately, with an accuracy of 97.47%. In the established prediction model, the RMSEC of the optimal model calibration set is 0.0012, and the coefficient of determination R is 0.9976. The RMSEP of prediction set is 0.0024, the coefficient of determination R is 0.9922, and the RPD is 11.36. In general, the method has good stability and applicability, which provides a new analytical method for the identification of Schisandra chinensis origin and quality evaluation. [ABSTRACT FROM AUTHOR]

Abstract: Spatial relationships play an important role in spatial knowledge representation, such as in describing localities. However, little attention has been paid to how to describe the position of a target object (TO) with a qualitative referencing system that consists of a set of reference objects (ROs) in the locality description context. We propose a method that accounts for the differences between two scenarios in locality descriptions. This method is probabilistic and is based on the Voronoi neighbor relationship to determine candidate ROs for describing a given TO''s position in the second scenario. The Voronoi neighbor relationship is adopted to determine candidate ROs of a TO and to compute the neighboring area of an RO. A probability function is presented to model the uncertainty of selecting appropriate ROs. To build locality descriptions that are consistent with commonsense, four constraints are placed on the probability function. Two probability functions based on Euclidean distance and stolen-area, and a mixed probability function that considers both Euclidean distance and stolen-area, are analyzed and compared. With the mixed probability function, we establish a method to construct the locality description of a given TO. Finally, three examples demonstrate how to select ROs to describe a TO''s position. [Copyright &y& Elsevier]

• The method combines laboratory analysis, data modelling and deep learning. • HF-DFM quantifies various water quality parameters by hyperspectral reflectance. • The method is effectively applied to monitoring water quality of urban rivers. • Prediction MAPEs range from 8.78%–12.36% for five water quality parameters. [Display omitted] Environmental protection of water resources is of critical importance to daily life of human beings. In recent years, monitoring the variation of water quality using remote sensing techniques has become prevalent. Unmanned aerial vehicle (UAV) based remote sensing techniques have been applied to quantitative retrieval of concentrations of water quality parameters including phosphorus, nitrogen, chemical oxygen demand (COD), biochemical oxygen demand (BOD), and chlorophyll a (Chl-a), successfully and efficiently. In this study, a novel method with deep factorization machine, spatial distribution pattern analysis, and probabilistic analysis engaged, named hybrid feedback deep factorization machine (HF-DFM), has been developed to quantitatively estimate concentrations of water quality parameters based on hyperspectral reflectance data on large scale effectively. Our proposed method is a unified model for quantifying concentrations of water quality parameters with an end to end structure, which integrates UAV based optical remote sensing techniques and deep learning to estimate concentrations of water quality parameters. Furthermore, our proposed model was applied to real-time quantitative monitoring the variation of water quality of Mazhou River, Shenzhen, Guangdong, China. Finally, we evaluate the performance of proposed model on a real-world dataset in terms of root of mean squared error (RMSE), mean absolute percent error (MAPE), and coefficient of determination (R 2). The experimental results show that our proposed model outperforms other state-of-the-art models with respect to RMSE, MAPE, and R 2 , where resulting MAPEs for quantifying all water quality parameters range from 8.78% to 12.36%, and resulting R 2 s range from 0.81 to 0.93. It can serve as a useful tool for decision makers in effectively monitoring water quality of urban rivers. [ABSTRACT FROM AUTHOR]

Drainage density, defined as river length per unit area, is an important tool to reveal the concealed active tectonics in the Quaternary-covered North China plain (NCP). The distribution of high-drainage density is characteristic of zonation and regionalisation. There are two sets of belts with high-drainage densities, which trend at 45–50 and 315–320°. The different locations and trends of these belts make it possible to divide the NCP into three regions. They are Beijing–Tianjin–Tangshan region in the north, Jizhong–Lubei region in the middle and Xingtai region in the south. Similarly located regions can be defined using contours of deformation data from geodetic-surveys from 1968 to 1982. Belts of high-drainage density are spatially coincident with seismotectonic zones and overlie concealed active faults. These active structures strike at an angle of &ap;15° to that in the Eocene–Oligocene, a discordance, which may be an indication of an evolution of the fault pattern through time in the NCP during the Cenozoic. The current phase has more important consequences regarding seismic hazards in the NCP. [Copyright &y& Elsevier]

Insufficient high-intensity focused ultrasound (HIFU) can promote the rapid progression of the residual tumor through the hypoxia inducible factor-2α +(HIF-2α)/vascular endothelial growth factor A (VEGFA)/ephrin type-A receptor 2 (EphA2) pathway. Although sorafenib has been shown to significantly improve the survival of patients with advanced liver cancer, the use of sorafenib in residual tumor tissues following HIFU has rarely been elucidated. Thus, this study aimed to investigate the potential adjuvant therapeutic effects of sorafenib following HIFU in order to reduce the relapse rate following insufficient HIFU. Xenograft tumors were established using nude mice injected with liver cancer cells. At approximately 4 weeks after the inoculation of the tumor cells (tumors reached 1.3–1.5 cm), all mice were randomly divided into 3 groups as follows: i) The control group (no treatment); ii) the HIFU-alone group, and iii) the combination group (HIFU + sorafenib), with 6 mice per group. The residual tumor volume was determined among the different treatment groups. The protein expression levels of HIF-2α, VEGFA and EphA2 were determined by immunohistochemistry and western blotting, and the mRNA levels were detected by RT-qPCR. The microvessel density (MVD) was calculated by CD31 immunohistochemistry staining. The results revealed that by comparing the control group, insufficient HIFU promoted HIF-2α, VEGFA and EphA2 expression (P < 0.05). Compared with the HIFU-alone group, the protein and mRNA levels of HIF-2α, VEGFA and EphA2 were markedly decreased in the group that received combined treatment with HIFU and sorafenib (P < 0.05). Similar results were obtained for MVD expression. Synergistic tumor growth inhibitory effects were also observed between the control group and HIFU group (P < 0.05). The findings of this study demonstrate that the expression of HIF-2α, VEGFA and EphA2 can be inhibited by sorafenib, and that sorafenib is likely to provide an effective adjunct treatment for patients with HCC following HIFU ablation. [ABSTRACT FROM AUTHOR]

The protection of water resources is of paramount importance to human beings' practical lives. Monitoring and improving water quality nowadays has become an important topic. In this study, a novel Bayesian probabilistic neural network (BPNN) improved from ordinary Bayesian probability methods has been developed to quantitatively predict water quality parameters including phosphorus, nitrogen, chemical oxygen demand (COD), biochemical oxygen demand (BOD), and chlorophyll a. The proposed method, based on conventional Bayesian probability methods, involves feature engineering and deep neural networks. Additionally, it extracts significant information for each endmember from combinations of spectra by feature extraction, with spectral unmixing based on mathematical and statistical analysis, and calculates each of the water quality parameters. The experimental results show the great performance of the proposed model with all coefficient of determination R 2 over 0.9 greater than the values (0.6–0.8) from conventional methods, which are greater than ordinary Bayesian probability analysis. The mean percent of absolute error (MPAE) is taken into account as an important statistical criterion to evaluate model performance, and our results show that MPAE ranges from 4% (nitrogen) to 10% (COD). The root mean squared errors (RMSEs) of phosphorus, nitrogen, COD, BOD, and chlorophyll-a (Chla) are 0.03 mg/L, 0.28 mg/L, 3.28 mg/L, 0.49 mg/L, and 0.75 μg/L, respectively. In comparison with other deep learning methods, this study takes a relatively small amount of data as training data to train the proposed model and the proposed model is then tested on the same amount of testing data, achieving a greater performance. Thus, the proposed method is time-saving and more effective. This study proposes a more compatible and effective method to assist with decomposing combinations of hyperspectral signatures in order to calculate the content level of each water quality parameter. Moreover, the proposed method is practically applied to hyperspectral image data on board an unmanned aerial vehicle in order to monitor the water quality on a large scale and trace the location of pollution sources in the Maozhou River, Guangdong Province of China, obtaining well-explained and significant results. [ABSTRACT FROM AUTHOR]

Protection of water environments is an important part of overall environmental protection; hence, many people devote their efforts to monitoring and improving water quality. In this study, a self-adapting selection method of multiple artificial neural networks (ANNs) using hyperspectral remote sensing and ground-measured water quality data is proposed to quantitatively predict water quality parameters, including phosphorus, nitrogen, biochemical oxygen demand (BOD), chemical oxygen demand (COD), and chlorophyll a. Seventy-nine ground measured data samples are used as training data in the establishment of the proposed model, and 30 samples are used as testing data. The proposed method based on traditional ANNs of numerical prediction involves feature selection of bands, self-adapting selection based on multiple selection criteria, stepwise backtracking, and combined weighted correlation. Water quality parameters are estimated with coefficient of determination R 2 ranging from 0.93 (phosphorus) to 0.98 (nitrogen), which is higher than the value (0.7 to 0.8) obtained by traditional ANNs. MPAE (mean percent of absolute error) values ranging from 5% to 11% are used rather than root mean square error to evaluate the predicting precision of the proposed model because the magnitude of each water quality parameter considerably differs, thereby providing reasonable and interpretable results. Compared with other ANNs with backpropagation, this study proposes an auto-adapting method assisted by the above-mentioned methods to select the best model with all settings, such as the number of hidden layers, number of neurons in each hidden layer, choice of optimizer, and activation function. Different settings for ANNS with backpropagation are important to improve precision and compatibility for different data. Furthermore, the proposed method is applied to hyperspectral remote sensing images collected using an unmanned aerial vehicle for monitoring the water quality in the Shiqi River, Zhongshan City, Guangdong Province, China. Obtained results indicate the locations of pollution sources. [ABSTRACT FROM AUTHOR]

The advances of positioning technologies and the widespread use of mobile devices bring us massive data with location information, or so-called big geo-data. One important part of big geo-data is massive digital human trajectories recorded by location-enabled mobile terminals and social apps. Digital human trajectories have been studied to learn more about human mobility and human activity. Existing research has shown that there exist strong associations between trajectory patterns and demographics. Given that demographics are essential information to various domains but not easy to acquire timely and on a large scale, inferring demographics from human trajectories has attracted attention from academia. In this paper, we proposed a demographics inferring framework suitable for big geo-data processing. Trajectory patterns were quantified from both spatiotemporal and semantic perspectives. Spatiotemporal features extracted from trajectories directly were used for capturing how people traveled in space and time. Semantic features obtained by attaching geographical context to trajectories were to reflect activities people conducted. Spatiotemporal and semantic features were organized into feature vectors and then input to supervised classification models to infer demographics. GPS trajectories and land use data in Beijing were used to validate the framework. Results show that the inference accuracies of marital status and residency status achieve 80% and thus prove the feasibility of our framework. This study can facilitate decision making in both business and social studies, such as personalized recommendation, commercial site selection and urban planning. • This study proposed a demographics inferring framework via mining both human trajectories and geographical context data. • A feature engineering approach was put forward for both spatiotemporal and semantic features of human trajectories. • The selected machine learning model has both good performances on predictions and the capability to explain indicators. • The proposed framework can facilitate decision making in various domains, such as personalized recommendation. [ABSTRACT FROM AUTHOR]

Chinese medicine (CM) has a long history in the treatment of psoriasis, and its different understanding angle and treatment mode from modern medicine have unique wisdom. In this article, we consulted a large number of literatures and collected data in order to systematically clarify how CM understands psoriasis, including the classification and judgment of syndrome types, the diagnosis and thinking of etiology and pathogenesis, the application of treatment ideas, principles, methods and various prescriptions, and suggestions on patient care, so as to provide a clear CM treatment process and experience for the world clinic. In addition, we analyzed the efficacy and safety through clinical data, and summarize the methods and prescriptions worthy of promotion, so as to provide reference for doctors to prescribe prescriptions and medication. Finally, we found that compared with modern medicine, CM has unique advantages in the treatment of psoriasis, including the uniqueness of syndrome classification, the abundantly and flexibility of treatment ideas. Not only many famous doctors have studied the ideas in ancient books, but also made great efforts to innovate, which has left a lot of valuable experiences for clinical practice. Moreover, a large number of treatment methods, prescriptions and medicines have achieved high effectiveness and safety in clinical practices for many years, which has been proved to be worthy of clinical reference and in-depth research. In addition, we also think about the deficiencies of CM in the treatment of psoriasis and the direction of breakthrough combined with modern medicine. The treatment of psoriasis with CM is worth popularizing, and we hope it can benefit more patients. [ABSTRACT FROM AUTHOR]

Background: d-Amino acids are increasingly used as building blocks to produce pharmaceuticals and fine chemicals. However, establishing a universal biocatalyst for the general synthesis of d-amino acids from cheap and readily available precursors with few by-products is challenging. In this study, we developed an efficient in vivo biocatalysis system for the synthesis of d-amino acids from l-amino acids by the co-expression of membrane-associated l-amino acid deaminase obtained from Proteus mirabilis (LAAD), meso-diaminopimelate dehydrogenases obtained from Symbiobacterium thermophilum (DAPDH), and formate dehydrogenase obtained from Burkholderia stabilis (FDH), in recombinant Escherichia coli. Results: To generate the in vivo cascade system, three strategies were evaluated to regulate enzyme expression levels, including single-plasmid co-expression, double-plasmid co-expression, and double-plasmid MBP-fused co-expression. The double-plasmid MBP-fused co-expression strain Escherichia coli pET-21b-MBP-laad/pET-28a-dapdh-fdh, exhibiting high catalytic efficiency, was selected. Under optimal conditions, 75 mg/mL of E. coli pET-21b-MBP-laad/pET-28a-dapdh-fdh whole-cell biocatalyst asymmetrically catalyzed the stereoinversion of 150 mM l-Phe to d-Phe, with quantitative yields of over 99% ee in 24 h, by the addition of 15 mM NADP+ and 300 mM ammonium formate. In addition, the whole-cell biocatalyst was used to successfully stereoinvert a variety of aromatic and aliphatic l-amino acids to their corresponding d-amino acids. Conclusions: The newly constructed in vivo cascade biocatalysis system was effective for the highly selective synthesis of d-amino acids via stereoinversion. [ABSTRACT FROM AUTHOR]

We appreciate the efforts of Lee et al. to prove that intensive care unit (ICU) length of stay (LOS) is reduced by protocolized family support intervention using a systematic review and meta-analysis [[1]]. : a systematic review and meta-analysis. [Extracted from the article]

Slime coating, defined as a layer of fine or ultrafine hydrophilic particles coated on the larger value mineral surface, has been recognized to have an important effect on froth flotation. These slimes on the mineral surface prevent value mineral particles from contacting with collectors and/or air bubbles, consequently resulting in a lower flotation recovery. It is demonstrated that the high intensity conditioning is an effective way to improve flotation performance. However, the relative significance of its mechanisms on high intensity conditioning still needs to be explored, especially the surface cleaning. In this work, the role of surface cleaning in high intensity conditioning was investigated by carrying out a series of tests including conditioning-flotation, microscope visualization, laser particle size analysis and Focused Beam Reflectance Measurement. The combustible matter recovery is employed to evaluate the flotation performance. The results show that the high intensity conditioning greatly improves the hydrophobicity of coal surface by producing a complete clean surface and consequently enhances the adhesion between coal and collector, which results in a significant increase of the combustible matter recovery no matter with or without the collector. It is also found that surface cleaning is an important factor in the reduction of the reagent consumption. In addition, it is noted that surface cleaning is the internal driving force for the significantly increased recovery of the coarse coal particles. Based on the findings in this work, a prospective high intensity conditioning-flotation process is presented. [ABSTRACT FROM AUTHOR]

Quantitative research of urban geography has benefited greatly from the rapid development of big geo-data. Spatial assembly is an essential analytical step to summarize and perceive geographical environment from individual behaviours. Most research focuses on the methodology of how to utilize the big data, while the adopted spatial units for data aggregation remain areal in nature. This article conceptually proposes an idea of sensing cities from a street perspective, emphasizes the significance of street units in quantitative urban studies. Using a three-month taxi trajectory dataset and the major streets in Beijing, we explore the spatio-temporal patterns of urban mobility on streets, cluster streets into nine types based on their dynamic functions and capacities. Additionally, we discuss the differences and connections between the linear street unit and traditional areal units, investigate the possibility of uncovering urban communities using streets, and point out the complexity of streets. We conclude that street unit as a supplement to areal units, is able to effectively minify the modifiable areal unit problem (MAUP), sense urban dynamics, depict urban functions, and understand urban structures. [ABSTRACT FROM AUTHOR]

Recently, miRNAs have become a promising biomarker for disease diagnostics. miRNA-145 is closely related to strokes. The accuracy determination of miRNA-145 (miR-145) in stroke patients still remains challenging due to its heterogeneity and low abundance, as well as the complexity of the blood matrix. In this work, we developed a novel electrochemical miRNA-145 biosensor via subtly coupling the cascade strand displacement reaction (CSDR), exonuclease III (Exo III), and magnetic nanoparticles (MNPs). The developed electrochemical biosensor can quantitatively detect miRNA-145 ranging from 1 × 102 to 1 × 106 aM with a detection limit as low down as 100 aM. This biosensor also exhibits excellent specificity to distinguish similar miRNA sequences even with single-base differences. It has been successfully applied to distinguish healthy people from stroke patients. The results of this biosensor are consistent with the results of the reverse transcription quantitative polymerase chain reaction (RT-qPCR). The proposed electrochemical biosensor has great potential applications for biomedical research on and clinical diagnosis of strokes. [ABSTRACT FROM AUTHOR]

A copper(II) complex chlorido-{1-carboxylic acid ethyl ester-4, 7-bis[1-(carboxylic acid ethyl ester) benzimidazole-2-yl-methyl]-1,4,7-triazacyclononane}copper(II) hexafluorophosphate ethanol solvate ([CuClL]·PF6·EtOH) was synthesized and crystallographically characterized {where L = 1-carboxylic acid ethyl ester-4,7-bis[1-(carboxylic acid ethyl ester) benzimidazole-2-yl-methyl]-1,4,7-triazacyclononane}. X-ray structure analysis shows that the copper(II) adopts a distorted square pyramidal coordination geometry. The activity of dismutation of superoxide () of the complex in riboflavin–methionine–nitroblue tetrazolium was studied. The result shows that the complex possesses a high superoxide dismutase (SOD) activity in comparison to some reported SOD mimics. Its redox behavior was studied by cyclic voltammetry with the aim of elucidating the reason that the complex reduces superoxide radicals. [ABSTRACT FROM AUTHOR]

Ultrasensitive and specific detection of cocaine is of great significance for monitoring cocaine abuse. Herein, a fluorescent aptasensor via coupling CRISPR-Cas12a, with magnetic nanoparticles (MNPs), split-aptamer, and terminal deoxynucleotidyl transferase (TdT), was developed for the detection of cocaine. In short, the complete cocaine aptamer is split into two parts, one is modified on magnetic nanoparticles (MNPs) and the other is free. The presence of cocaine will mediate the binding of these two segments. Then TdT will mediate the extension to form an ultra-long sequence that can bind with multiple CRISPR-Cas12a resulting in the trans-cleavage activity of CRISPR-Cas12a being triggered. Thence, the DNA reporter which is bi-labeled with fluorophore and quencher is cleaved resulting in the generation of a fluorescence signal. The developed fluorescent aptasensor realizes the detection of cocaine with excellent sensitivity and specificity. The detection limit is low down to 33 pM, and the linear range is from 330 to 1.65 × 105 pM. Most importantly, this fluorescent aptasensor can be successfully applied to the determination of cocaine in human plasma samples. [ABSTRACT FROM AUTHOR]

Exosomal MicroRNA-21 (miRNA-21, miR-21) is significantly up-regulated in blood samples of patients with lung cancer. Exosomal-derived miR-21 can be used as a promising biomarker for the early diagnosis of lung cancer. This paper develops a fluorescent biosensor based on the combination of magnetic nanoparticles (MNPs), cascade strand displacement reaction (CSDR) and CRISPR/Cas12a to detect the exosomal miR-21 from lung cancer. The powerful separation performance of MNPs can eliminate the potential interference of matrix and reduce the background signal, which is very beneficial for the improvement of specificity and sensitivity. The CSDR can specifically transform one miR-21 into plenty of DNA which can specifically trigger the trans-cleavage nuclease activity of Cas12a, resulting in the cleavage of ssDNA bi-labeled with fluorescent and a quencher. Under the optimized experimental conditions, the developed fluorescence biosensor exhibited high sensitivity and specificity towards the determination of exosomal-derived miR-21 with a linear range from 10 to 1 × 105 fM and a low detection limit of about 0.89 fM. Most importantly, this method can be successfully applied to distinguish the exosomal miR-21 from the lung cancer patients and the healthy people. [ABSTRACT FROM AUTHOR]

Datura metel L. has been used as an anesthetic in clinic for more than 1800 years in China, and the main efficacy of D. metel L. flower is relieving asthma and cough, relieving spasm and relieving pain. From 1978 to 1980, Datura metel L. was used as an anesthetic agent and occasionally cured psoriasis patients during anesthesia clinically, and our group confirmed that the effective portion is total withanolides (YWS). Moreover, the new drug " Datura metel L. capsule" composed of YWS has since been approved and used for the treatment of more than 3,000 psoriasis patients, with efficacy and cure rates greater than 90% and 65%. However, the immunological mechanism has not been elucidated. Nowadays, although total withanolides from Datura metel L. have a better clinical efficacy in the treatment of psoriasis, there is a lack of overall understanding of the mechanism of their treatment, especially about some immune cells and proteins closely related to psoriasis and their relationship in executive function and biological significance. This study focused on investigating the mechanism of psoriasis treatment by YWS and determined the biochemical processes in the treatment of psoriasis based on Treg/Th17 axis cell-mediated bidirectional immunoregulatory functions, which provides an important scientific basis for understanding the mechanism underlying the treatment of psoriasis by YWS. The effects of YWS on the lesion pathology of IMQ-induced psoriasis mice and the underlying molecular mechanism were assessed directly using HE staining, the PASI score and the animal body mass. We also investigated the effects of YWS on the Treg/Th17 axis and their critical functions in psoriasis pathogenesis via molecular biological methods. Finally, we performed differential proteomics analysis on skin in IMQ-induced psoriasis mice to clarify the effect of YWS by incorporates mass spectrometry-bioinformatics and annotated the functions and pathways associated with the differential proteins through GO enrichment, KEGG pathway analysis and PPI networks analysis, respectively. YWS regulated the imbalance of the Treg/Th17 axis. And proteomic analysis showed that YWS up-regulated 46 and down-regulated 37 proteins. According to the bioinformatics analysis, the improvement of Treg/Th17 imbalance may be the key immunological mechanism of YWS in the treatment of psoriasis by up-regulating the butyrate metabolism pathway, down-regulating leukocyte migration, inhibiting the phagocytic function of natural killer cells, suppressing osteoclast differentiation and interfering with chemokine activity, and the critical proteins involved are Lyn, HMGCS2, ABAT, ITGβ2, PRKCβ, MMP9, NCF1, JUNβ, and Hck. This research clarified that the improvement of the imbalance of the Treg/Th17 axis may be the key immunological mechanism of YWS in the treatment of psoriasis through metabolic pathways and influencing key proteins. The results not only expand the therapeutic targets and approaches for the treatment of psoriasis, which is a challenging and complex disease, but also deepens the understanding of the mechanism of YWS in the treatment of psoriasis and other important conditions to open up a new way of thinking for research on YWS in the treatment of psoriasis. [Display omitted] [ABSTRACT FROM AUTHOR]

Many marine alkaloids possess interesting structures and antitumor activities. Thus, we have synthesized (2 E,4 E)-4-arylidene-2-styryl-5-oxopyrrolidine derivatives of the marine alkaloids, rhopaladins A–D. The cytotoxicities of these derivatives against C-33A, CaSki, SiHa, HeLa, HepG2, and LO2 cells are evaluated by MTT assays. The results show that (2 E,4 E)-2-(4-chlorostyryl)-4-benzylidene- N -cyclohexyl-1-(4-fluorophenyl)-5-oxopyrrolidine-2-carboxamide significantly inhibits cancer cell proliferation, with IC50 values against C-33A, CaSki, SiHa, HeLa, and HepG2 cells of 5.56, 9.15, 12.5, 21.4, and 14.5 μM, respectively, and an IC50 value of 86.77 μM against the normal LO2 cell line. [ABSTRACT FROM AUTHOR]

Big geo-data are often aggregated according to spatio-temporal units for analyzing human activities and urban environments. Many applications categorize such data into groups and compare the characteristics across groups. The intergroup differences vary with spatio-temporal units, and the essential is to identify the spatio-temporal units with apparently different data characteristics. However, spatio-temporal dependence, data variety, and the complexity of tasks impede an effective unit assessment. Inspired by the applications to extract critical image components based on explainable artificial intelligence (XAI), we propose a spatio-temporal layer-wise relevance propagation method to assess spatio-temporal units as a general solution. The method organizes input data into an extensible three-dimensional tensor form. We provide two means of labeling the spatio-temporal tensor data for typical geographical applications, using temporally or spatially relevant information. Neural network training proceeds to extract the global and local characteristics of data for corresponding analytical tasks. Then the method propagates classification results backward into units as obtained task-specific importance. A case study with taxi trajectory data in Beijing validates the method. The results prove that the proposed method can evaluate the task-specific importance of spatio-temporal units with dependence. This study also attempts to discover task-related knowledge using XAI. [ABSTRACT FROM AUTHOR]

A one-pot, base-mediated approach to Acanthus ilicifolius Linn alkaloid 2-benzoxazolinone derivatives is developed. Starting from trichloroacetic acid, o -aminophenol, substituted benzaldehydes and alkyl isocyanides, the desired 2-benzoxazolinone derivatives are obtained in good yields via a tandem Ugi condensation and intramolecular haloform cyclization at room temperature in the presence of Et3N. [ABSTRACT FROM AUTHOR]

Background: Long non-coding RNAs (lncRNA) are reported to influence colorectal cancer (CRC) progression. Currently, the functions of the lncRNA ZNF561 antisense RNA 1 (ZNF561-AS1) in CRC are unknown. Methods: ZNF561-AS1 and SRSF6 expression in CRC patient samples and CRC cell lines was evaluated through TCGA database analysis, western blot along with real-time PCR. SRSF6 expression in CRC cells was also examined upon ZNF561-AS1 depletion or overexpression. Interaction between miR-26a-3p, miR-128-5p, ZNF561-AS1, and SRSF6 was examined by dual luciferase reporter assay, as well as RNA binding protein immunoprecipitation (RIP) assay. Small interfering RNA (siRNA) mediated knockdown experiments were performed to assess the role of ZNF561-AS1 and SRSF6 in the proliferative actives and apoptosis rate of CRC cells. A mouse xenograft model was employed to assess tumor growth upon ZNF561-AS1 knockdown and SRSF6 rescue. Results: We find that ZNF561-AS1 and SRSF6 were upregulated in CRC patient tissues. ZNF561-AS1 expression was reduced in tissues from treated CRC patients but upregulated in CRC tissues from relapsed patients. SRSF6 expression was suppressed and enhanced by ZNF561-AS1 depletion and overexpression, respectively. Mechanistically, ZNF561-AS1 regulated SRSF6 expression by sponging miR-26a-3p and miR-128-5p. ZNF561-AS1-miR-26a-3p/miR-128-5p-SRSF6 axis was required for CRC proliferation and survival. ZNF561-AS1 knockdown suppressed CRC cell proliferation and triggered apoptosis. ZNF561-AS1 depletion suppressed the growth of tumors in a model of a nude mouse xenograft. Similar observations were made upon SRSF6 depletion. SRSF6 overexpression reversed the inhibitory activities of ZNF561-AS1 in vivo, as well as in vitro. Conclusion: In summary, we find that ZNF561-AS1 promotes CRC progression via the miR-26a-3p/miR-128-5p-SRSF6 axis. This study reveals new perspectives into the role of ZNF561-AS1 in CRC. [ABSTRACT FROM AUTHOR]

This work provided the adsorption method to removal phenol by using different coal particles. The characterization of the adsorbents was analyzed by Camsizer XT, FT-IR, X-ray diffusion and Brunauer-Emmett-Teller and Barrett-Joyner-Halenda. The adsorption capacity presents a linear increase as specific surface area increasing. To reveal the process of the adsorption, the adsorption kinetics and isotherms were performed. Pseudo-second-order was found to best represent the kinetics data, which indicated that the process belongs to chemisorption. The equilibrium isotherms data was analyzed by Langmuir model and Freundlich model, which indicated that the Freundlich model was good fitted for the adsorption processes. [ABSTRACT FROM AUTHOR]

Quantifying urban areas is crucial for addressing associated urban issues such as environmental and sustainable problems. Remote sensing data, especially the nighttime light images, have been widely used to delineate urbanized areas across the world. Meanwhile, some emerging urban data, such as volunteered geographical information (e.g., OpenStreetMap) and social sensing data (e.g., mobile phone and social media), have also shown great potential in revealing urban boundaries and dynamics. However, consistent and robust methods to quantify urban areas from these multi-source data have remained elusive. Here, we propose a percolation-based method to extract urban areas from these multi-source urban data. We derive the optimal urban/non-urban threshold by considering the critical nature of urban systems with the support of the percolation theory. Furthermore, we apply the method with three open-source datasets – population, road, and nighttime light – to 28 countries. We show that the proposed method captures the similar urban characteristics in terms of urban areas from multi-source data, and Zipf's law holds well in most countries. The accuracy of the derived urban areas by different datasets has been validated with the Landsat-based reference data in 10 cities, and the accuracy can be further improved through data fusion (κ = 0.69–0.85, mean κ = 0.78). Our study not only provides an efficient method to quantify urban areas with open-source data, but also deepens the understanding of urban systems and sheds some light on multi-source data fusion in geographical fields. • A percolation-based method is proposed to delimit urban areas from multi-source data. • The optimal threshold is derived by considering the critical nature of urban systems. • Remote sensing and emerging urban data are found to reflect similar urban dynamics. • The size distribution of urban areas fits well with Zipf's law in most countries. [ABSTRACT FROM AUTHOR]

[Display omitted] • hUC-MSCs improved liver function and attenuated liver fibrosis in mice. • hUC-MSCs inhibit HSC activation by regulating the Hippo/YAP/Id1 axis. • hUC-MSCs secrete CCL2 to promote an anti-inflammatory macrophage phenotype. Few effective anti-fibrotic therapies are currently available for liver cirrhosis. Mesenchymal stromal cells (MSCs) ameliorate liver fibrosis and contribute to liver regeneration after cirrhosis, attracting much attention as a potential therapeutic strategy for the disease. However, the underlying molecular mechanism of their therapeutic effect is still unclear. Here, we investigated the effect of human umbilical cord-derived mesenchymal stromal cells (hUC-MSCs) in treating liver cirrhosis and their underlying mechanisms. We used carbon tetrachloride (CCl 4)-induced mice as liver cirrhosis models and treated them with hUC-MSCs via tail vein injection. We assessed the changes in liver function, inflammation, and fibrosis by histopathology and serum biochemistry and explored the mechanism of hUC-MSCs by RNA sequencing (RNA-seq) using liver tissues. In addition, we investigated the effects of hUC-MSCs on hepatic stellate cells (HSC) and macrophages by in vitro co-culture experiments. We found that hUC-MSCs considerably improved liver function and attenuated liver inflammation and fibrosis in CCl 4 -injured mice. We also showed that these cells exerted therapeutic effects by regulating the Hippo/YAP/Id1 axis in vivo. Our in vitro experiments demonstrated that hUC-MSCs inhibit HSC activation by regulating the Hippo/YAP signaling pathway and targeting Id1. Moreover, hUC-MSCs also alleviated liver inflammation by promoting the transformation of macrophages to an anti-inflammatory phenotype. Our study reveals that hUC-MSCs relieve liver cirrhosis in mice through the Hippo/YAP/Id1 pathway and macrophage-dependent mechanisms, providing a theoretical basis for the future use of these cells as a potential therapeutic strategy for patients with liver cirrhosis. [ABSTRACT FROM AUTHOR]

How to improve coal flotation performance has been examined with a focus on the effect of particle size on flotation conditioning. A coking coal sample collected from the flotation feed of a coal preparation plant located in Lu’an, Shanxi province of China was investigated. The characters including mineral composition, size fraction, density fraction, and contact angle were analyzed. Classified and unclassified conditioning tests were carried out using different size fractions. The relationship between flotation indices (combustible recovery and flotation efficiency) and conditions (particle size, collector dosage, and conditioning stirring speed) was investigated. The results showed that the optimum conditions for different size fractions were different. The collector dosage and the conditioning stirring speed increased with the decrease of particle size. Meanwhile, the collision frequency between fine coal and diesel particles was much higher than the coarse particles, resulting most of the flotation agents adsorbed by fine particles, though the kinetic energy of coarse particles was higher. So a classified conditioning process was proposed. By conditioning optimizing, the flotation performance of classified conditioning was significantly improved compared with unclassified conditioning, especially for the +0.125 mm fractions. [ABSTRACT FROM AUTHOR]

Zuojiangia jingxiensis, both a new genus and species, is described from the Pearl River in China. It is distinguished from all other genera and species of Labeonini by the unique combination of modified oromandibular structures and head skeleton: a well-developed, pendulous, and conspicuously arched rostral fold, with an entirely crenulated margin; prominent papillae densely covering the margin of the rostral fold and anterior part of the lower lip; long postlabial grooves, partitioning the lower lip into three parts; transverse branch of dentary longer than half the length of the longitudinal branch; stubby lateral process present at the anterolateral margin of the longitudinal branch of the dentary, close to the corner; in the upper jaw, the premaxilla bears a triangular ascending process tapering to a point; maxilla exhibits a pair of articular heads at the anterodorsal margin, and a distinct fingerlike descending process posterior to the medial articular head embracing the ascending process of the premaxilla. [ABSTRACT FROM AUTHOR]

Spatial interactions underlying consecutive sequential snapshots of spatial distributions, such as the migration flows underlying temporal population snapshots, can reflect the details of spatial evolution processes. In the era of big data, we have access to individual-level data, but the acquisition of high-quality spatial interaction data remains a challenging problem. Most research has been focused on distributions of movable objects or the modelling of spatial interaction patterns, with few attempts to identify hidden spatial interaction patterns from temporal transitions of spatial distributions. In this article, we introduced an approach to infer spatial interaction patterns from sequential snapshots of spatial population distributions by incorporating linear programming and the spatial constraints of human movement. Experiments using synthetic data were conducted using four simple scenarios to explore the characteristics of our method. The proposed method was used to extract interurban flows of migrants during the Chinese Spring Festival in 2016. Our research demonstrated the feasibility of using discrete multi-temporal snapshots of population distributions in space to infer spatial interaction patterns and offered a general analytical framework from snapshot data to spatial interaction patterns. [ABSTRACT FROM AUTHOR]

In this work, the interaction behavior and underlying mechanism of coal and kaolinite particles in the presence of agitation was investigated by flotation tests, homo and hetero settling tests, turbidity meter, zeta potential distribution, focused beam reflectance measurement (FBRM) and scanning electron microscope (SEM). The results show that, in the presence of kaolinite, the flotation combustible matter recovery of coal decreases from 0 rpm to 1200 rpm and then increases from 1200 rpm to 2000 rpm, indicating that the mild agitation enhances kaolinite-coating and the high intensity agitation mitigates the kaolinite-coating, which is demonstrated by the zeta potential distribution and turbidity measurements. However, the degree of the heterocoagulation between coal and kaolinite is not serious. It is found that the kaolinite particles partially cover on the coal surface by two morphologies includes individuals and aggregates through the size-based scanning electron microscope analysis. In addition, the affinity between fine kaolinite and fine coal particles is more pronounced. The kaolinite-coating enhancement caused by the mild agitation is explained by the Derjaguin–Landau–Verwey–Overbeek (DLVO) theory. [ABSTRACT FROM AUTHOR]

A large number of geographical toponyms exist in web pages and other documents, providing abundant geographical resources for GIS. It is very common for toponyms to co-occur in the same documents. To investigate these relations associated with geographic entities, a novel complex network model for co-occurrence toponyms is proposed. Then, 12 toponym co-occurrence networks are constructed from the toponym sets extracted from the People’s Daily Paper documents of 2010. It is found that two toponyms have a high co-occurrence probability if they are at the same administrative level or if they possess a part-whole relationship. By applying complex network analysis methods to toponym co-occurrence networks, we find the following characteristics. (1) The navigation vertices of the co-occurrence networks can be found by degree centrality analysis. (2) The networks express strong cluster characteristics, and it takes only several steps to reach one vertex from another one, implying that the networks are small-world graphs. (3) The degree distribution satisfies the power law with an exponent of 1.7, so the networks are free-scale. (4) The networks are disassortative and have similar assortative modes, with assortative exponents of approximately 0.18 and assortative indexes less than 0. (5) The frequency of toponym co-occurrence is weakly negatively correlated with geographic distance, but more strongly negatively correlated with administrative hierarchical distance. Considering the toponym frequencies and co-occurrence relationships, a novel method based on link analysis is presented to extract the core toponyms from web pages. This method is suitable and effective for geographical information retrieval. [ABSTRACT FROM AUTHOR]

A city (or an urban cluster) is not an isolated spatial unit, but a combination of areas with closely linked socio-economic activities. However, so far, we lack a consistent and quantitative approach to define multi-level urban clusters through these socio-economic connections. Here, using granular population distribution and flow data from China, we propose a bottom-up aggregation approach to quantify urban clusters at multiple spatial scales. We reveal six 'phases' (i.e., levels) in the population density-flow diagram, each of which corresponds to a spatial configuration of urban clusters from large to small. Besides, our results show that Zipf's law appears only after the fifth level, confirming the spatially dependent nature of urban laws. Our approach does not need pre-defined administrative boundaries and can be applied effectively on a global scale. • We propose a density and flow-based method to quantify urban clusters at multiple spatial scales. • The population density and flow ratio thresholds are derived through percolation analysis. • The six phases in the density-flow diagram correspond to different levels of urban clusters. • Zipf's law only holds on the urban clusters after the fifth level. [ABSTRACT FROM AUTHOR]

• The electrochemical biosensor coupling with CRISPR/Cas12a, aptamer and MNPs is developed for determination of cTnI. • The target-specific triggered powerful trans-cleavage activity of Cas12a endows the biosensor with high accuracy and high sensitivity. • The combination of MNPs with aptamer-based strategy can realize that the powerful trans-cleavage activity of Cas12a is specifically triggered by cTnI. • The developed biosensor is beneficial for early diagnosis of related cardiovascular diseases. The successful fabrication of the cTnI detection platform is very meaningful for instant diagnosis of the myocardial injury and related cardiovascular diseases (CVDs). In this research work, the magnetic nanoparticles and aptamer collaboration with the Cas12a/crRNA are used for the electrochemical detection of cTnI. The aptamer is hybridized with its partially complementary DNA (probe 2, P2) and then is modified on the magnetic nanoparticles. In the presence of cTnI, the cTnI combines with the aptamer and P2 is released. The released P2 is hybridized with the crRNA and the trans-cleavage activity of CRISPR/Cas12a is triggered. Therefore, the methylene blue-modified DNA (probe1, P1) on the surface of the electrode is cleaved, resulting in the decrease of the electrochemical signal. Based on the synergy effect of the high specific target recognition of aptamer, target-specifically triggering trans-cleavage activity of CRISPR/Cas12a, as well as good separation ability of magnetic nanoparticles, the developed electrochemical biosensor enables to detect cTnI with high specificity and sensitivity. The detection limit is low down to 10 pg/mL with a linear range from 100 pg/mL to 50000 pg/mL. The developed sensing platform was successfully applied for the detection of cTnI in human serum. This fabricated CRISPR/Cas12a-based electrochemical biosensor can offer a valuable tool for the diagnosis, prognosis, and treatment of patient with CVDs. [ABSTRACT FROM AUTHOR]

To explore the effect of the power input on the fine coal flotation rate constant, an energy consumption test system was established for the fine coal. In this investigation, the fine coal investigated was anthracite obtained from the flotation feed of the Xuehu Coal Preparation Plant of the Shenhuo mine in the Henan Province of China. A total of 65 sets of flotation rate tests were carried out with different power inputs at different flotation times. The relationship between the flotation rate constant and the power input at different flotation times was obtained. The result showed that the flotation rate displayed a constant increase, whereas the power input increased at any time during the flotation process. With the continuous increase of the power input, the increasing trend exhibited by the flotation rate constant decreases after reaching a maximum value. The calculation conjecture of the flotation rate constants and the power input were obtained by imitating the calculation method of the flotation kinetics model. Determining the value of the flotation power input and the flotation time during the flotation process of the different fine coal characteristics would therefore be helpful. [ABSTRACT FROM AUTHOR]

Abstract: Energy-saving ability and high flotation efficiency are two important factors in the flotation process. In this investigation, a new concept for the flotation process design based on energy input and distribution was proposed, low energy was inputted early to recover easy-to-float materials, whereas high energy was inputted late to recover difficult-to-float materials. The flotation tests were conducted in an XFD 0.75L laboratory-scale flotation machine. A comparison of flotation performance using constant power input and gradually increased power input was investigated. The flotation results indicated that low ash content, high flotation efficiency index, and energy-saving ability could be obtained by increasing power input step by step in the flotation process. The flotation process design based on different shaft speeds (1500, 1500, 1800, 1800, and 2400r/min in different flotation periods) and an energy consumption of 1720.8J is suitable for flotation performance of the coal samples in this study. [Copyright &y& Elsevier]

Ground filtering is a key process to derive digital terrain models from airborne laser scanning data. Although many methods have been developed to tackle the filtering problem, it has not been fully solved so far. Current algorithms mainly focus on neighbourhood-based or directional filtering approaches. A new object-based analysis (OBA) method is proposed in this article. First, a grid index algorithm accelerates access to unorganized cloud points. Then, a segmentation algorithm is deployed based on the index, and objects are obtained. A filtering logic that utilizes the objects' characteristics is designed. Following this, the performance of the method is comprehensively tested using publicly available International Society for Photogrammetry and Remote Sensing (ISPRS) test data sets for nine urban and six rural regions, and the results are compared to those of eight other algorithms. The OBA method implemented in this article reveals good results without scene-wise optimization of the parameters, and it ranks third or fourth in most of the cases. [ABSTRACT FROM AUTHOR]

Today, large-volume mobile phone call datasets are widely applied to investigate the spatio-temporal characteristics of human urban activity. This paper discusses several fundamental issues in estimating population distributions based on mobile call data. By adopting an individual-based call activity dataset that consists of nearly two million mobile subscribers who made over one hundred million communications over seven consecutive days, we explore the relationships among the Erlang values, the number of calls, and the number of active mobile subscribers. Then, the LandScan population density dataset is introduced to evaluate the process of estimating the population. The empirical findings indicate that: (1) Temporal variation exists in the relation between the Erlang values and the number of calls; (2) The number of calls is linearly proportional to the number of active mobile subscribers; (3) The proportion between the mobile subscribers and the actual total population varies in different areas, thus failing to represent the underlying population. Hence, the call activity reflects “activity intensity” rather than population distribution. The Erlang is a defective indicator of population distribution, whereas the number of calls serves as a better measure. This research provides an explicit clarification with respect to using call activity data for estimating population distribution. [ABSTRACT FROM AUTHOR]