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Accurate prediction of the rate of penetration (ROP) is a difficult issue in the drilling process, especially under complex formation conditions. Many methods, such as mechanism and machine learning, were introduced to investigate it. However, most of them are offline prediction methods which may not be capable of capturing the online trend of ROP. In this paper, a novel dynamic model for ROP prediction is proposed considering the process characteristics, which consists of three stages. In the first stage, the correlations between ROP and eight drilling parameters are analyzed, and the rotational speed, weight on bit, depth are selected as the model inputs. In the second stage, the drilling data are pre-processed by using the filtering and re-sampling techniques. In the last stage, the moving window strategy, extreme learning machine, and 10-fold cross validation are used to establish the ROP model. Our main idea of online prediction of ROP lies in this last stage. Specifically, two steps (modeling and prediction) are executed alternately in the moving drilling depth windows so as to predict the ROP more accurately. Finally, the proposed ROP prediction model is applied to the drilling well ZK3 in Xiangyang area, Central China. The prediction accuracy is improved by at least 7% compared with seven well-known ROP prediction methods, two online and five offline, which validates the effectiveness of the proposed method. It is believed that the proposed model provides a basis for intelligent optimization control in drilling process. • A novel intelligent dynamic model is proposed for the online prediction of drilling ROP. • The influence of the length of moving window and distance between two windows are investigated thoroughly. • The proposed model can learn autonomously in the drilling process and has a fast computation speed. • The proposed method has a higher prediction accuracy than two online and five offline well-known conventional methods. [ABSTRACT FROM AUTHOR]

[Display omitted] • Eco-efficiency of cultivated land use (EECLU) is evaluated. • Both carbon sequestration and carbon emissions are considered for measuring EECLU. • Super-efficiency SBM-DEA with undesirable output & panel data analysis are used. • Size has positive impact on the EECLU. • Shape complexity and patch fragmentation have negative impacts on the EECLU. With China's rapid urbanization and socioeconomic development, cultivated land has been experiencing continuous reduction, spatial shift, and ecological degradation in the past few decades, coupled with the decreasing and aging agricultural labor force, thus improving cultivated land utilization efficiency while minimizing associated environmental impacts is one of the major challenges facing China. This study first establishes an index system to access the eco-efficiency of cultivated land use (EECLU) considering both carbon sequestration and carbon emissions, next, employs the Super-SBM model to evaluate the spatial–temporal characteristics of EECLU, then, uses landscape metrics to describe landscape pattern dynamics of cultivated land, and finally conducts panel data analysis to investigate the relationship between landscape pattern changes and the EECLU variations. This framework was applied to Jiangsu Province, a major grain-producing area with a developed economy. The results showed that the average EECLU of the counties in rural Jiangsu from 2000 to 2020 slightly decreased, most counties were in the medium–low efficiency range (0.6–0.8), and Southern Jiangsu generally has the lowest EECLU values while Central Jiangsu has the highest. The total area and the average patch sizes of cultivated land have significantly positive impacts on EECLU, while the shape complexity and patch fragmentation have significantly negative impacts on EECLU. Therefore, comprehensive low-carbon strategies and better management and technology in the agricultural sector are needed to further improve EECLU. On the premise of protecting the total area of cultivated land, larger and more aggregated land patches should be promoted in the land consolidation process, and the cultivated land targeted for occupation or compensation should be able to simplify the overall shape of cultivated land patches. [ABSTRACT FROM AUTHOR]

The physics-driven dynamics simulation (DS) and data-driven machine learning (ML) are two general approaches to predict complex systems whose complexity is a hardship impediment to prediction. Based on the 3D geological modeling (GD), we embedded the DS into ML to predict high potential targets and to evaluate ore-controlling and ore-indicating factors in the Tongguangshan (TGS) skarn orefield that has undergone intensive exploration and 4 Cu and Au deposits discovered. The 3D geological models show that the heterogeneous distribution of orebodies around intrusions is associated with the wall rock lithology and contact zone (CZ) characteristics of intrusions, and the resistivity can only provide some ambiguous clues for interpretation of underground geological architectures rather than a direct ore-indicator. The DS results show heterogeneous distribution of temperature, pore pressure, differential stress, volume strain and shear strain, among which the volume strain is closest associated with ore formation. Based on the prediction of Random Forest (FR) model of which the feature variables are combination of DS and 3D modeling results, the SHAP valuing results show a descending importance rank of ore-controlling factors and ore-indicators as lithology, volume strain, distance to CZ, distance to Devonian-Carboniferous interface, curvature of CZ, pressure, temperature, CZ azimuth, resistivity, differential stress, shear strain and CZ dip. The DS results are more important than the resistivity. We have run 6 RF models, consisting of different feature variables which were assigned by DS and 3D modeling, to predict ore-formation favor spaces. The prediction performances on test data sets suggest that, integrating of geological features with dynamics features can enhance performance of RF prediction, the RF model consisting of pure dynamics features can predict mineralization different from the training samples. All RF models' predictions support that there are no significant high potentials at the depth of the orefield, except one small target at its eastern south corner. [Display omitted] • Dynamics simulation (DS) and machine learning (ML) are different prediction ways. • Integrating DS into ML can facilitate targeting in maturely explored orefield. • ML processing DS results can predict orebodies different from the training samples. [ABSTRACT FROM AUTHOR]

The government service platform, exemplified by the government hotline, has to handle extensive volumes of business documents that contain rich and timely public opinion information and citizens' demands. However, manual processing struggles to process large-scale text data, adversely impacting operating costs and the quality of government services. This study proposes a comprehensive system for business document classification of the government hotline (BDCGHS) in China to address these challenges. BDCGHS leverages information entropy fused with term frequency-inverse document frequency (TF-IDF) weight to mine new words from business documents of the government hotline, and store them in a new word repository. These new words optimize Chinese word segmentation and text representation for text classification. We introduce a novel data structure called nested balanced binary tree to expedite new word mining, yielding a computational speed of almost five times than the Trie trees. Comparative experiments on the THUNews and government hotline datasets validate our proposed improvement BDCGHS algorithm's superior performance 3 % over text classification algorithms. Compared to the latest bidirectional encoder representations from the transformers (BERT) model, BDCGHS enhances the accuracy of order dispatch based on business documents by almost 3 %. It has also demonstrated stable operations in two Chinese cities for over a year, yielding favorable results. [Display omitted] • An embedded balanced binary tree structure is proposed for new word discovery. • A new word database is constructed for the government hotline. • The effects of mainstream classification algorithms are compared based on a new word database. • An intelligent text classification system for the government hotline is constructed and the results have promising results. [ABSTRACT FROM AUTHOR]

Humulus scanden, rich in flavonoids, is a traditional Chinese medicine. It is widely used in China to treat tuberculosis, dysentery and chronic colitis. In this study, Humulus scandens (H.S) was extracted in different solvents (water, n-butanol, acetic ether and chloroform) and the antioxidant, anti-inflammatory activities of extracts were investigated by four assays including DPPH, reducing power, xylene-induced mouse ear edema and cotton pellet-induced granuloma methods. And then, the acute oral toxicity of extracts and biochemical parameters such as superoxide dismutase (SOD) and catalase (CAT) in blood serum and edematous tissue of rats were also evaluated. Moreover, the active compounds were identified by LC-ESI-QTOF-MS-MS. Results showed that ethyl acetate and n-butanol extracts had the stronger antioxidant activities, while water extract appeared to be weakest among them. The anti-inflammatory test showed that the extract of n-butanol and chloroform had significant anti-inflammatory effects and could improve the activity of SOD and CAT in mice. In general, the site of n-butanol has a stronger antioxidant and anti-inflammatory activity, and 15 compounds were analyzed by LC/Q-TOF-MS/MS technology. The present study confirms the ethnobotanical use of H.S extracts as natural antioxidant, anti-inflammatory, and the composition of the active compound was preliminarily identified. [ABSTRACT FROM AUTHOR]

Liuwei Dihuang (LWDH) is a classic prescription that has been used to the treatment of "Kidney-Yin" deficiency syndrome for more than 1000 years in China. Recent studies have confirmed that LWDH can prevent the progression of renal fibrosis. Numerous studies have demonstrated the critical role that TRPC6 plays in the development of renal fibrosis. Due to the complex composition of LWDH and its remarkable therapeutic effect on renal fibrosis, it is possible to discover new active ingredients targeting TRPC6 for the treatment of renal fibrosis. This study aimed to identify selective TRPC6 inhibitors from LWDH and evaluate their therapeutical effects on renal fibrosis. Computer-aided drug design was used to screen the biologically active ingredients of LWDH, and their affinities to human TRPC6 protein were detected by microcalorimetry. TRPC6, TRPC3, and TRPC7 over-expressed HEK293 cells were constructed, and the selective activities of the compounds on TRPC6 were determined by measuring [Ca2+] i in these cells. To establish an in vitro model of renal fibrosis, human renal proximal tubular epithelial HK-2 cells were stimulated with TGF-β1. The therapeutic effects of LWDH compounds on renal fibrosis were then tested by detecting the related proteins. TRPC6 was knocked-down in HK-2 cells to investigate the effects of LWDH active ingredients on TRPC6. Finally, a unilateral ureteral obstruction model of renal fibrosis was established to test the therapeutic effect. From hundreds of LWDH ingredients, 64 active components with oral bioavailability ≥30% and drug-likeness index ≥0.18 were acquired. A total of 10 active components were obtained by molecular docking with TRPC6 protein. Among them, 4 components had an affinity with TRPC6. Piperlonguminine (PLG) had the most potent affinity with TRPC6 and blocking effect on TRPC6-mediated Ca2+ entry. A 100 μM of PLG showed no detectable inhibition on TRPC1, TRPC3, TRPC4, TRPC5, or TRPC7-mediated Ca2+ influx into cells. In vitro results indicated that PLG concentration-dependently inhibited the abnormally high expression of α-smooth muscle actin (α-SMA), collagen I, vimentin, and TRPC6 in TGF-β1-induced HK-2 cells. Consistently, PLG also could not further inhibit TGF-β1-induced expressions of these protein biomarkers in TRPC6 knocked-down HK-2 cells. In vivo, PLG dose-dependently reduced urinary protein, serum creatinine, and blood urea nitrogen levels in renal fibrosis mice and markedly alleviated fibrosis and the expressions of α-SMA, collagen I, vimentin, and TRPC6 in kidney tissues. Our results showed that PLG had anti-renal fibrosis effects by selectively inhibiting TRPC6. PLG might be a promising therapeutic agent for the treatment of renal fibrosis. [Display omitted] • PLG is an important anti-renal fibrosis active component in Liuwei Dihuang decoction. • PLG alleviates renal fibrosis in HK-2 cells and mice. • The therapeutic mechanism of PLG is through inhibiting TRPC6 and ultimately mitigating renal fibrosis. [ABSTRACT FROM AUTHOR]

• Weatherability of soil can be effectively improved by CGN. • The strength of solidified samples slightly increased with the dosage and curing time. • Under the appropriate dosage, color difference of solidified samples can meet principle of "repairing the old as the old". • Carbonation is the dominant reaction of CGN during the curing stage. Earthen site is a kind of preciously historic building constructed with soil as the building material. In northwestern China, the earthen sites are threatened because of environmental hazards, such as wind erosion, water erosion, and so on. Rammed reinforcement of the erosion area can improve the overall stability of the site. In addition, region formed by ramming reinforcement can be defined as ramming area. The formation of the ramming area is a new surface, and new interface between the ramming area and the original site is formed. Therefore, ramming area must meet principle of "repairing the old as the old" and maintain compatibility with the original earthen sites in terms of soil strength, permeability. Calcined ginger nuts is an environment-friendly and inorganic material that is emerging curing agent to reinforce the erosion area of the earthen site, which may make the reinforcement area to meet the above requirements. A series of tests were performed to verify its feasibility and investigate its solidified effects and mechanism. The study demonstrated that, with dosage and curing time increasing, the shear strength and unconfined compressive strength of solidified samples slightly improved and the permeability coefficient decreased with a small extent, the disintegration and shrinkage rate significantly decreased, and the total color difference value of samples increased as the sample became brighter. Furthermore, the mechanism of solidified soil has been studied by performing mercury injection, X-ray diffraction, and scanning electron micrograph tests under 25% dosage, which is proposed as the optimum dosage. The pore size decreased with increase of curing time as calcium carbonate content increased. Crystal type of calcium carbonate is mainly calcite—a material with high strength and cohesiveness. Thus, carbonation is the dominant reaction during the curing stage. Moreover, the crystal morphology of calcite changes from needle-stick calcite to flake. In conclusion, calcined ginger nuts can be used as curing agent for reinforcing the erosion area of earthen sites. [ABSTRACT FROM AUTHOR]

In Liaoning Province, China, mass mortality among turbot (Scophthalmus maximus) was observed in multiple cultured farms in 2021. Aside from hemorrhages in the fins and infrabranchial muscles, no visible damage in the infected fish was observed upon visual inspection. Histopathological examination revealed swollen branchial lamellae ends and severe necrosis in the liver, kidney, and spleen. On the one hand, chinook salmon bafinivirus (CSBV) was isolated and identified in the affected turbot using cell isolation, transmission electron microscopy (TEM) observation, and whole-genome sequencing technology. On the other, based on the 16S rRNA sequence and the analysis of the biochemical characteristics, the dominant strains isolated from the diseased fish were identified as Vibrio scophthalmi, Aeromonas salmonicida, and Vibrio splendidus. Phylogenetic analysis revealed that CSBV strain in this study (CSBV Bces-Sm22) had a high identity homology with CSBV strain Bces-Po19, isolated from Japanese flounder Paralichthys olivaceus in 2019. Furthermore, Vibrio scophthalmi, Vibrio splendidus, and Aeromonas salmonicida were close to China, Spain, and Turkey strains, respectively. In this study, we report the first case of turbot that was naturally co-infected with Chinook salmon bafinivirus (CSBV) and bacteria (Vibrio scophthalmi, Aeromonas salmonicida, and Vibrio splendidus) with high mortality rates. • Describe a case of natural co-infection of CSBV and bacteria (Vibrio scophthalmi , Aeromonas salmonicida , and Vibrio splendidus) in culture turbot. • The isolation of CSBV from marine fish turbot was reported for the first time. • Validated JFB as a CSBV-susceptible cell line. [ABSTRACT FROM AUTHOR]

[Display omitted] • Electrostatic LBL self-assembly strategy is firstly employed to integrate MoS 2 with CMOF. • Superior rejection rates are increased above 27–55% more than that of monomer membranes for FQs. • Synergy of size exclusion, electrostatic repulsion, and hydrophilic interaction is explained. • High stability in harsh environments for 72 h and over 90% rejection against FQs in the real sample. Developing a novel nanofiltration membrane for effectively purifying antibiotic wastewater has been a daunting challenge in recent years. However, a convenient and controllable strategy for constructing membranes with two-dimensional nanomaterials (2DNMs) and metal–organic frameworks (MOFs) needs to be further studied. Herein, a loosely hierarchical architecture composite membrane has been fabricated, utilizing an electrostatic layer-by-layer (LBL) self-assembly method to intercalate chitosan crosslinked UiO-66-NH 2 MOFs (CMOF) into MoS 2 laminates. Through regulating the CMOF content, lower hydraulic-resisted channels and precise separation regions have been formed in the hierarchical architecture. The well-designed MoS 2 /CMOF composite membrane exhibited enhanced water permeance (78.98 ± 1.45 L·m-2h−1 bar−1) and superior antibiotic rejection capability (98.01 ± 1.12% for ciprofloxacin and 94.31 ± 0.68% for ofloxacin), which are increased by 27–55% more than monomer membranes. Detailed analysis results indicate the nanofiltration performance of the MoS 2 /CMOF composite membrane depends heavily on the synergistic mechanism, including the molecular sieving effect (size exclusion), electrostatic repulsion, and hydrophilic-hydrophobic interaction. Besides, the MoS 2 /CMOF composite membrane has emerged with excellent antifouling ability and long-term stability, which could maintain favorable rejection efficiency in continuous nanofiltration for 72 h under an alkaline and acidic environment. Furthermore, it presents over 90% antibiotic rejection rates for real water samples obtained from the municipal domestic sewage and livestock wastewater along the Xiangjiang River in China, indicating its good availability. In general, this work provides a new vision and a reasonable design strategy to construct 2DNMs/MOFs-based nanofiltration membranes with hierarchical architecture, further expanding their application in wastewater treatment and reclamation, in harmony with the global trend of green and low-carbon development. [ABSTRACT FROM AUTHOR]

• The model of pavement texture is obtained by CCD camera and 3D reconstruction. • A calibration plate is developed as a portable tool to measure MTD. • The slope of 3D model of pavement texture is eliminated by ICP algorithm. • Create datum reference plane and texture reference plane to analyze the model. • Calculate the texture depth of asphalt pavement with volume algorithm. The depth of an asphalt pavement structure is an important index used to reflect the anti-skid performance of the pavement, which directly affects the driving safety of vehicles. In the current specifications (e.g., China, European and American standards), the mean texture depth (MTD) of an asphalt pavement is generally measured by the sand-patch method (SPM). However, SPM is easily affected by the operator's subjective experience and experimental environment, resulting in low accuracy and high scatter in the data. In view of such shortcomings, a fast and accurate method to obtain the texture depth of asphalt pavement was proposed by designing a new test tool and a computer-aided calculation method. The multiocular vision theory was adopted to reconstruct a three-dimensional (3D) point cloud model of pavement texture. To reflect the concavity and convexity of pavement texture and eliminate the influence of pavement slope, the iterative closest point (ICP) algorithm was employed to obtain the datum reference plane (DRP). On this basis, the pentahedral volume calculation method suitable for evaluating the texture depth of an asphalt pavement was proposed. Laboratory experiment results using SPM were inverted by equal volume calculation to obtain the texture reference plane (TRP) and MTD'. Meanwhile, a 3D average maximum elevation (Avg.EL) algorithm was obtained by the evolution of two-dimensional mean profile depth (MPD). Furthermore, three parameters, namely MTD, MTD', and Avg.EL, were used to measure the texture depth of two field pavement sections in service. The experimental results showed that the correlation between MTD' and MTD was better than that between Avg.EL and MTD, and the degree of scatter was smaller. MTD' could be used directly as a reference value for MTD. In the present work, the 3D volume calculation method of asphalt pavement texture depth was proposed, which integrates the technical flow of image acquisition, model reconstruction, and algorithm analysis. The developed method provides a technical reference for the application of computer vision technology in the analysis of pavement texture depth. [ABSTRACT FROM AUTHOR]

[Display omitted] • The Dongguashan quartz-diorite stock was built by multiple magma pulses. • Early magma pulse was guided by inherited NE-SW-trending structure in country rock. • Late magma pulse emplacement was assisted by regional extensional regime. • Eastward magma emplace might control location of skarnization in stock eastern sideable 1. We present a study on the Dongguashan quartz diorite stock which is the largest Early Cretaceous intrusion associated with skarn-porphyry polymetallic ore deposit in the Tongling Ore Cluster, Middle-Lower Yangtze Metallogenic Belt in East China. The Dongguashan quartz diorite show massive texture without obvious foliation, and intrusive contact was locally observed inside of the stock. The anisotropy of magnetic susceptibility (AMS) results of the stock show two distinct groups. The Group I (G-I) is dominated by NE-SW-striking magnetic foliation with variably oriented magnetic lineation. The Group II (G-II) that intruded into G-I is characterized by steep NW-SE-striking magnetic foliation and lineation, which are parallel to the vein-like orebody developed in the stock. The 3D geometrical modelling of the stock displays a triangular shape in plan-view with an eastward bulge and irregular stock boundary in the eastern side and the contact surface is steeper in the west than that in the east, denoting that the stock was constructed with an eastward magma accretion trend. Furthermore, the Dongguashan quartz diorite has a wide range of composition and geochronological data, suggesting a multiple magma pulses emplacement model. Accordingly, we propose that the Dongguashan stock was constructed by at least two stages magma pulses. The earlier stage magma pulses intruded along the NE-SW-striking pre-emplacement structures in the country rock and partly intruded into the lithological and mechanical discontinuous interfaces which yielded the stratabound skarn orebody. The eastward magma accretion produced a highly deformed and longer heated country rock on the eastern side of the stock, favoring the orebody development along the eastern stock-country rock contact interface. The late-stage magma pulse and the parallelism among the trend of magnetic foliation of G-II, extensional structure and vein-like orebody suggest that the vein-type orebodies may controlled by both magma emplacement and regional tectonics. [ABSTRACT FROM AUTHOR]

• Two common methods showed poor identification of honey geographical origin. • Ionomics method was used to identify the geographical origin of Apis cerana honey. • Ionomics method was established using 18 elements in 27 Apis cerana honey samples. The identification of geographical origin is an important factor in evaluating the authenticity of honey. However, at present, there are few studies concerning the honey of Apis cerana Fabricius (A. cerana , Asiatic honeybee). To identify geographical origin, we used two common methods (multi-physicochemical parameters and phenolic chromatographic fingerprints) but achieved only poor identification. To compensate for this shortcoming, we established an ICP-MS-based ionomics method using 18 elements in 27 A. cerana honey samples from three different areas in Shaanxi Province, China. Multivariate analysis showed that significant differences in contents can be used to discriminate the geographical origin of A. cerana honey. The method was further validated using an independent test set of 11 samples with 90.91% accuracy, demonstrating its potential for the identification and prediction of the geographical origin of honey. [ABSTRACT FROM AUTHOR]