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The concoction process is a vital technique for reducing the toxicity and enhancing the efficacy of Chinese herbal medicines. To examine the alterations in the chemical compositions of Aurantii Fructus before and after stir-frying in diverse origins, a method of internal extraction electrospray ionization mass spectrometry (iEESI-MS) was developed. It combines the advantages of internal extraction and electrospray ionization mass spectrometry, and is capable of detecting target molecules in complex samples with highly efficient and sensitive manner. iEESI-MS was employed to directly analyze the Aurantii Fructus samples before and after processing without complex sample pretreatment, which can obtain their fingerprints and identify the principal difference substances present in the samples before and after processing. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used for data handling. The aforementioned screened main differences in substances were subjected to analysis in a variety of origins. The experimental conditions were optimized including the temperature of ion transport tube, spray voltage, flow rate of the extractant, proportion of methanol spray solution and distance from the spray port to the mass spectrometry port, etc. The results showed that a total of 35 substances are identified in the Aurantii Fructus samples, including flavonoids, coumarins, alkaloids, volatile oils, and amino acids. The chemical composition of Aurantii Fructus exhibites notable differences before and after preparation. Flavonoids constitute approximately two-thirds of the identified distinct compounds, and serve as crucial quality markers for differentiating the origin and quality of Aurantii Fructus. The results of the human heat map analysis of Aurantii Fructus from disparate origins in Hunan, Sichuan and Jiangxi demonstrated that the variation of the 12 distinct substances present in Aurantii Fructus from different origins is considerable. This indicated that the contents of these 12 substances are inconsistent among the different origins, which is related to the disparate quality of Aurantii Fructus from different origins in terms of its medicinal effects. This study provides a novel approach to ambient mass spectrometry for the quality identification of herbs such as Aurantii Fructus and the material basis of efficacy change before and after processing.

Water is a vital resource on the earth, serving as the foundation of life and playing a crucial role in our daily activities. Perfluorooctanoic acid (PFOA) is an organic compound, which poses a significant threat to the environment due to its persistence and bioaccumulation. PFOA exhibits various toxicities, including neurotoxicity, immunotoxicity, and carcinogenicity. It has been detected in worldwide of air and water samples, as it can easily move through different environmental media such as water, soil, and the atmosphere. The widespread distribution of PFOA in these media poses potential risks to both ecosystems and human health over the long term. Therefore, it is of utmost importance to develop a rapid detection method for accurately monitoring PFOA levels in water. In this study, the electrospray extraction ionization-tandem mass spectrometry (EESI-MS/MS) technique was utilized to directly and rapidly detect PFOA in tap water and river water. To achieve the highest ionization efficiency of PFOA in EESI-MS/MS across different water samples, the experimental parameters such as ion transfer tube temperature, spray voltage, electrospray solvent flow rate, and sample flow rate were optimized. The optimal conditions were temperature of 200 °C for the ion transfer tube, spray voltage of 2 kV, electrospray solvent flow rate of 4 µL/min, and sample flow rate of 6 µL/min. The experiments were conducted under negative ion mode with a mass scan range of m/z 50-500. Methanol solution was used as the electrospray solvent, and collision-induced dissociation (CID) was employed. The secondary characteristic fragment ion m/z 369 of m/z 413 for qualitative and quantitative analysis, enabling direct and rapid detection of PFOA in various water samples. The experimental results demonstrated good linearity of PFOA in the concentration range of 1-500 ng/L, with a linear correlation coefficient (R2) of 0.9976. The detection limit (LOD) of the proposed method is 0.57 ng/L, and the limit of quantification (LOQ) is 1.73 ng/L. The recovery rate ranges from 92.1% to 105.2%, with a relative standard deviation (RSD, n=6) of 1.89%-5.45%. In summary, this method has the advantages of high sensitivity, accuracy, and fast analysis speed, without the need of sample pretreatment. The established EESI-MS/MS method can be effectively applied for direct and rapid detection of PFOA in different water samples, showing promising prospects for monitoring environmental water pollutants. Moreover, it provides valuable references and technical means for the detection of other pollutants.

Obtaining discriminative joint features is crucial for skeleton-based human action recognition. Current models mainly focus on the research of skeleton topology encoding. However, their predefined topology is the same and fixed for all action samples, making it challenging to obtain discriminative joint features. Although some studies have considered the complex non-natural connection relationships between joints, the existing methods cannot fully capture this complexity by using high-order adjacency matrices or adding trainable parameters and instead increase the computation parameters. Therefore, this study constructs a novel adaptive channel-enhanced graph convolution (ACE-GCN) model for human action recognition. The model generates similar and affinity attention maps by encoding channel attention in the input features. These maps are complementarily applied to the input feature map and graph topology, which can realize the refinement of joint features and construct an adaptive and non-shared channel-based adjacency matrix. This method of constructing the adjacency matrix improves the model’s capacity to capture intricate non-natural connections between joints, prevents the accumulation of unnecessary information, and minimizes the number of computational parameters. In addition, integrating the Edgeconv module into a multi-branch aggregation improves the model’s ability to aggregate different scale and temporal features. Ultimately, comprehensive experiments were carried out on NTU-RGB+D 60 and NTU-RGB+D 120, which are two substantial datasets. On the NTU RGB+D 60 dataset, the accuracy of human action recognition was 92% (X-Sub) and 96.3% (X-View). The model achieved an accuracy of 96.6% on the NW-UCLA dataset. The experimental results confirm that the ACE-GCN exhibits superior recognition accuracy and lower computing complexity compared to current methodologies.

With the continuous improvement of surface water environmental quality in China, sediment has gradually become the focus of research on internal pollution in reservoirs. To investigate the forms, distribution, and migration patterns of phosphorus in karst canyon reservoir sediments, we employed an improved sequential graded extraction method to determine phosphorus content in the sediments of the Wanfeng Reservoir. We studied the spatial distribution characteristics and release risk of phosphorus form in the sediments. The results showed that the total phosphorus (TP) content ranged from 79.37 to 438.04 mg·kg−1, while inorganic phosphorus (IP) content ranged from 77.32 to 424.64 mg·kg−1. Iron–aluminum-bound inorganic phosphorus (Fe/Al-Pi) accounted for 36.41% and was found to be the dominant form of IP. Organic phosphorus (OP) content ranged from 1.84 to 13.59 mg·kg−1, with weakly adsorbed organic phosphorus (H2O-Po) being the dominant form of OP. Potentially active inorganic phosphorus (NaHCO3-Pi) showed a highly significant positive correlation (p < 0.01) with Fe/Al-Pi, residual phosphorus (Res-P), and TP. This indicates that potentially active phosphorus (NaHCO3-P) is a significant potential source of phosphorus (P) in the reservoir. Biologically active phosphorus (BAP) content ranged from 66.97 to 201.46 mg·kg−1, with BAP/TP ratios ranging from 55.6% to 59.6%. The risk of phosphorus release from Wanfeng Reservoir sediments is high. The release of various forms of phosphorus from sediments is one of the important factors leading to the deterioration of water quality in the reservoir area in the future. To effectively manage water ecology in karst canyon reservoirs, it is essential to reduce the risk of endogenous phosphorus release.

Properties of pore structure in Metal-organic frameworks (MOFs) play a key role in the adsorption of target molecules hence are used to improve the efficiency in MOFs. In this study, we synthesized three MOFs with different hydrophilicity, namely TMU-6(RL1), TMU-21(RL2) and TMU-59. Additionally, we studied the effect of hydrophobicity/hydrophilicity of pore in MOFs on the drug delivery and sensing properties. The structure of these frameworks was characterized by XPS, BET, XRD, IR and TG. The DLC and DLE of TMU-6(RL1), TMU-21(RL2) and TMU-59, were determined by (20%, 70%), (18%, 78%) and (3.6%, 13.6%), respectively. Also, the curcumin release reached 74%, 57% and 8% respectively for TMU-6(RL1), TMU-21(RL2) and TMU-59 after 100 h in PBS solution with pH 7.2 respectively. The carriers showed high adsorption efficiency and controlled release. Adsorption of curcumin as an anticancer drug to the MOFs was done through multiple mechanisms such as Hostπ–πGuest interaction and HostN–H⋯OGuest hydrogen bonds. Also, studies of in vitro anticancer revealed that the cytotoxicity of the MOFs@Curcumin composites against HT-29 cancer cells in MOFs was more than free curcumin. The findings demonstrated that the changes in the hydrophilic properties of frameworks can specifically control the Host-Guest interactions, drug loading and its release.

The timely identification of rail internal defects and the application of corresponding preventive measures would greatly reduce catastrophic failures, such as rail breakage. Ultrasonic rail defect detection is the current mainstream rail defect detection method thanks to its advantages of strong penetration, high accuracy, and ease to deploy. The 2D B-scan image output by ultrasonic detectors contains rich features of defects; however, rail engineers manually identify and localize the defect image, which can be time-consuming, and the image may be subject to missing identification or mistakes. This paper adopted state-of-the-art deep learning algorithms for novel B-scan images for the automatic identification and localization of rail internal tracks. First, through image pre-processing of classification, denoising, and augmentation, four categories of defect image datasets were established, namely crescent-shaped fatigue cracks, fishbolt hole cracks, rail web cracks, and rail base transverse cracks; then, four representatives of deep learning object detection networks, YOLOv8, YOLOv5, DETR, and Faster R-CNN, were trained with the defects dataset and further applied to the testing dataset for defect identification; finally, the performances of the three detection networks were compared and evaluated at the data level, the network structure level, and the interference adaptability level, respectively. The results show that the YOLOv8 network can effectively classify and localize four categories of internal rail defects in B-scan images with a 93.3% mean average precision at three images per second, and the detection time is 58.9%, 376.8%, and 123.2% faster than YOLO v5, DETR, and Faster R-CNN, respectively. The proposed approach could ensure the real-time, accurate, and efficient detection and analysis of internal defects to a rail.

Abstract Developing new templates to evaluate the ligand engineering effect in manipulating nanoclusters from both molecular and supramolecular aspects remains highly desired in cluster science because it allows for an in‐depth understanding of structure‐property correlations. We herein presented the secondary ligand (i.e., the phosphine ligand) engineering based on an Ag29 nanocluster template and its dual effects on intracluster structures and intercluster aggregates. The “dissociation‐combination equilibrium” of phosphine ligands on the nanocluster surface was controlled by tailoring the C–H⋯π interactions within the ligand shell, which led to the fabrication of a family of [Ag29(BDT)12(PR3)x]3– nanoclusters. On the molecular level, the dissociation of phosphine ligands contracted the nanocluster framework, while the overall configuration of [Ag29(BDT)12]3– was retained. On the supramolecular level, the complete dissociation of phosphine ligands yielded a bare nanocluster, which followed a chiral crystallization mode, and its crystals displayed high optical activity, derived from circular dichroism and circularly polarized luminescence characterizations. Overall, this work presents the peripheral ligand effects in directionally controlling intracluster configurations and intercluster aggregations, which hopefully benefit future design and preparation of new nanoclusters or cluster‐based nanomaterials with customized structures and performances.

Over the last decade, there has been a lot of interest in incorporating dynamic covalent bonds (DCBs) into epoxy resins. Because diselenide and disulfide bonds have similar properties, they are frequently used as DCBs in self-healing epoxy networks. In this paper, we present diselenide and disulfide dynamic linkers containing epoxy networks by analyzing the effects of mechanical properties, thermal stability, activation energies, and self-healing properties. The glass transition temperature (Tg) values, mechanical properties, crosslinking density (ve), and thermal stability of disulfide linkers networks were higher than those of diselenide linkers networks, according to our research. The activation energies of disulfide linkers were higher than those of diselenide linkers (up to 14 kJ/mol), but their healing efficiency was lower than that of the diselenide network. These findings demonstrate the advantages of diselenide and disulfide dynamic linkers in epoxy networks systems, as well as a method for designing and preparing the appropriate diselenide dynamic linkers or disulfide dynamic linkers incorporated into epoxy networks for the appropriate application and processing technology.

Soybean is one of the most widely grown oilseed crops worldwide. Several unfavorable factors, including salt and salt–alkali stress caused by soil salinization, affect soybean yield and quality. Therefore, exploring the molecular basis of salt tolerance in plants and developing genetic resources for genetic breeding is important. Sucrose non-fermentable protein kinase 1 (SnRK1) belongs to a class of Ser/Thr protein kinases that are evolutionarily highly conserved direct homologs of yeast SNF1 and animal AMPKs and are involved in various abiotic stresses in plants. The GmPKS4 gene was experimentally shown to be involved with salinity tolerance. First, using the yeast two-hybrid technique and bimolecular fluorescence complementation (BiFC) technique, the GmSNF1 protein was shown to interact with the GmPKS4 protein. Second, the GmSNF1 gene responded positively to salt and salt–alkali stress according to qRT-PCR analysis, and the GmSNF1 protein was localized in the nucleus and cytoplasm using subcellular localization assay. The GmSNF1 gene was then heterologously expressed in yeast, and the GmSNF1 gene was tentatively identified as having salt and salt–alkali tolerance function. Finally, the salt–alkali tolerance function of the GmSNF1 gene was demonstrated by transgenic Arabidopsis thaliana, soybean hairy root complex plants overexpressing GmSNF1 and GmSNF1 gene-silenced soybean using VIGS. These results indicated that GmSNF1 might be useful in genetic engineering to improve plant salt and salt–alkali tolerance.

Selecting suitable promoters to drive gene overexpression can provide significant insight into the development of engineered bacteria. In this study, we analyzed the transcriptome data of Burkholderia pyrrocinia JK-SH007 and identified 54 highly expressed genes. The promoter sequences were located using genome-wide data and scored using the prokaryotic promoter prediction software BPROM to further screen out 18 promoter sequences. We also developed a promoter trap system based on two reporter proteins adapted for promoter optimization in B. pyrrocinia JK-SH007: firefly luciferase encoded by the luciferase gene set (Luc) and trimethoprim (TP)-resistant dihydrofolate reductase (TPr). Ultimately, eight constitutive promoters were successfully inserted into the probe vector and transformed into B. pyrrocinia JK-SH007. The transformants were successfully grown on Tp antibiotic plates, and firefly luciferase expression was determined by measuring the relative light unit (RLU). Five of the promoters (P4, P9, P10, P14, and P19) showed 1.01–2.51-fold higher activity than the control promoter λ phage transcriptional promoter (PRPL). The promoter activity was further validated via qPCR analysis, indicating that promoters P14 and P19 showed stable high transcription levels at all time points. Then, GFP and RFP proteins were overexpressed in JK-SH007. In addition, promoters P14 and P19 were successfully used to drive gene expression in Burkholderia multivorans WS-FJ9 and Escherichia coli S17-1. The two constitutive promoters can be used not only in B. pyrrocinia JK-SH007 itself to gene overexpression but also to expand the scope of application.

Two nano amide-functionalized metal-organic frameworks (MOFs) with molecular formula [Co(oba) (bpta)]·(DMF)2 TMU-50 and [Co2(oba)2 (bpfn)]·(DMF)2.5 TMU-51 obtained under ultrasonic method without any surfactants. The only difference between the two selected amide functionalized pillar ligands, N,N′-bis(4-pyridinyl)-terephthalamide (bpta), and N,N′-bis-(4-pyridylformamide)-1,5-naphthalenediamine (bpfn), is related to the naphthyl group, which led to the different luminescence properties of the nano frameworks. In this study, the special ability of the luminescent nano MOFs were investigated to sensitize nitroaromatic compounds. Due to its unique and porous framework, Nano TMU-50 shows a good sensitivity towards nitro phenol by strong fluorescence emission with a detection limit of 2 × 10–3 mM−1. Both nano MOF structures were characterized via many analyses such as powder X-ray diffraction, Field Emission Scanning Electron Microscopy (FE-SEM), elemental analysis, and FTIR spectroscopy. Moreover, the effect of a number of important parameters including initial reagent concentrations, power of ultrasound, time on morphology, and size of nano structures were examined. According to the fluorescence titration results, the activated nano-TMU-50 detected NP selectively with a quick response.

Flame-retardant cycloaliphatic epoxy systems have long been studied; however, the research suffers from slow and unsatisfactory advances. In this work, we synthesized a kind of phosphorus-containing difunctional cycloaliphatic epoxide (called BCEP). Then, triglycidyl isocyanurate (TGIC) was mixed with BCEP to achieve epoxy systems that are rich in phosphorus and nitrogen elements, which were cured with 4-methylhexahydrobenzene anhydride (MeHHPA) to obtain a series of flame-retardant epoxy resins. Curing behaviors, flame retardancy, thermal behaviors, dielectric performance, and the chemical degradation behaviors of the cured epoxy system were investigated. BCEP-TGIC systems showed a high curing activity, and they can be efficiently cured, in which the incorporation of TGIC decreased the curing activity of the resin. As the ratio of BCEP and TGIC was 1:3, the cured resin (BCEP1-TGIC3) showed a relatively good flame retardancy with a limiting oxygen index value of 25.2%. In the cone calorimeter test, they presented a longer time to ignition and a lower heat release than the commercially available cycloaliphatic epoxy resins (ERL-4221). BCEP-TGIC systems presented good thermal stability, as the addition of TGIC delayed the thermal weight loss of the resin. BCEP1-TGIC3 had high dielectric performance and outperformed ERL-4221 over a frequency range of 1 HZ to 1 MHz. BCEP1-TGIC3 could achieve degradation under mild conditions in an alkali methanol/water solution. Benefiting from the advances, BCEP-TGIC systems have potential applications as electronic packaging materials in electrical and electronic fields.

Transition metal-mediated templating and self-assembly have shown great potential to construct mechanically interlocked molecules. Herein, we describe the formation of the bimetallic [3]catenane and [4]catenane based on neutral organometallic scaffolds via the orthogonality of platinum-to-oxygen coordination-driven self-assembly and copper(I) template–directed strategy of a [2]pseudorotaxane. The structures of these bimetallic [3]catenane and [4]catenane were characterized by multinuclear NMR {1H and 31P} spectroscopy, electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS), and PM6 semiempirical molecular orbital theoretical calculations. In addition, single-crystal X-ray analyses of the [3]catenane revealed two asymmetric [2]pseudorotaxane units inside the metallacycle. It was discovered that tubular structures were formed through the stacking of individual [3]catenane molecules driven by the strong π–π interactions.

Numerical simulation of thermal hydraulics of nuclear reactors is widely concerned, but large-scale fluid simulation is still prohibited due to the complexity of components and huge computational effort. Some applications of open source CFD programs still have a large gap in terms of comprehensiveness of physical models, computational accuracy and computational efficiency compared with commercial CFD programs. Therefore, it is necessary to improve the computational performance of in-house CFD software (YHACT, the parallel analysis code of thermohydraulices) to obtain the processing capability of large-scale mesh data and better parallel efficiency. In this paper, we will form a unified framework of meshing and mesh renumbering for solving fluid dynamics problems with unstructured meshes. Meanwhile, the effective Greedy, RCM (reverse Cuthill-Mckee), and CQ (cell quotient) grid renumbering algorithms are integrated into YHACT software. An important judgment metric, named median point average distance (MDMP), is applied as the discriminant of sparse matrix quality to select the renumbering methods with better effect for different physical models. Finally, a parallel test of the turbulence model with 39.5 million grid volumes is performed using a pressurized water reactor engineering case component with 3*3 rod bundles. The computational results before and after renumbering are also compared to verify the robustness of the program. Experiments show that the CFD framework integrated in this paper can correctly perform simulations of the thermal engineering hydraulics of large nuclear reactors. The parallel size of the program reaches a maximum of 3072 processes. The renumbering acceleration effect reaches its maximum at a parallel scale of 1536 processes, 56.72%. It provides a basis for our future implementation of open-source CFD software that supports efficient large-scale parallel simulations.

Grid renumbering techniques have been shown to be effective in improving the efficiency of computational fluid dynamics (CFD) numerical simulations based on the finite volume method (FVM). However, with the increasing complexity of real-world engineering scenarios, there is still a huge challenge to choose better sequencing techniques to improve parallel simulation performance. This paper designed an improved metric (MDMP) to evaluate the structure of sparse matrices. The metric takes the aggregation of non-zero elements inside the sparse matrix as an evaluation criterion. Meanwhile, combined with the features of the cell-centered finite volume method supporting unstructured grids, we proposed the cell quotient (CQ) renumbering algorithm to further reduce the maximum bandwidth and contours of large sparse matrices with finite volume discretization. Finally, with real-world engineering cases, we quantitatively analyzed the evaluation effect of MDMP and the optimization effect of different renumbering algorithms. The results showed that the classical greedy algorithm reduces the maximum bandwidth of the sparse matrix by at most 60.34% and the profile by 95.38%. Correspondingly, the CQ algorithm reduced them by at most 92.94% and 98.70%. However, in terms of MDMP, the CQ algorithm was 83.43% less optimized than the Greedy algorithm. In terms of overall computational speed, the Greedy algorithm was optimized by a maximum of 38.19%, and the CQ algorithm was optimized by a maximum of 27.31%. The above is in accordance with the evaluation results of the MDMP metric. Thus, our new metric can more accurately evaluate the renumbering method for numerical fluid simulations, which is of great value in selecting a better mesh renumbering method in engineering applications of CFD.

Salt stress is one of the most severe adverse environments in rice production; increasing salinization is seriously endangering rice production around the world. In this study, a rice backcross inbred line (BIL) population derived from the cross of 9311 and wild rice Oryza longistaminata was employed to identify the favorable genetic loci of O. longistaminata for salt tolerance. A total of 27 quantitative trait loci (QTLs) related to salt tolerance were identified in 140 rice BILs, and 17 QTLs formed seven QTL clusters on different chromosomes, of which 18 QTLs were derived from O. longistaminata, and a QTL for salt injury score (SIS), water content of seedlings (WCS) under salt treatment, and relative water content of seedlings (RWCS) was repeatedly detected and colocalized at the same site on chromosome 2, and a cytochrome P450 86B1 (MH02t0466900) was suggested as the potential candidate gene responsible for the salt tolerance based on sequence and expression analysis. These findings laid the foundation for further improving rice salt tolerance through molecular breeding in the future.

The adsorption of pentafl uorobenzene on nine ionic liquid-based silicas was investigated using solid phase extraction. The effects of several variables such as the type of ionic liquid groups, adsorption time, temperatures and water ratio in the solution system were experimentally evaluated. The imidazole-chloride ionic liquid group based silica exhibited the highest adsorption effi ciency under the optimized conditions of 5 min adsorption at 30oC in water/methanol (30:70, vol%) solution. In addition, the effects of pH, as well as type and concentrations of chloride salts were investigated. At pH values other than neutral and high salt concentration, the adsorption effi ciency was reduced. Finally, the relative standard deviation of less than 5.8% over a 5-day period showed a high precision for the nine tested sorbents.

Surface modification has served as an efficient approach to dictate nanocluster structures and properties. In this work, based on an Ag22 nanocluster template, the effects of surface modification on intracluster constructions and intercluster packing modes, as well as the properties of nanoclusters or cluster-based crystallographic assemblies have been investigated. On the molecular level, the Ag22 nanocluster with larger surface steric hindrance was inclined to absorb more small-steric chlorine but less bulky thiol ligands on its surface. On the supramolecular level, the regulation of intramolecular and intermolecular interactions in nanocluster crystallographic assemblies rendered them CIEE (crystallization-induced emission enhancement)-active or -inactive nanomaterials. This study has some innovation in the molecular and intramolecular tailoring of metal nanoclusters, which is significant for the preparation of new cluster-based nanomaterials with customized structures and enhanced performances.

Heterogeneous face recognition (HFR) has aroused significant interest in recent years, with some challenging tasks such as misalignment problems and limited HFR data. Misalignment occurs among different modalities’ images mainly because of misaligned semantics. Although recent methods have attempted to settle the low-shot problem, they suffer from the misalignment problem between paired near infrared (NIR) and visible (VIS) images. Misalignment can bring performance degradation to most image-to-image translation networks. In this work, we propose a self-aligned dual generation (SADG) architecture for generating semantics-aligned pairwise NIR-VIS images with the same identity, but without the additional guidance of external information learning. Specifically, we propose a self-aligned generator to align the data distributions between two modalities. Then, we present a multiscale patch discriminator to get high quality images. Furthermore, we raise the mean landmark distance (MLD) to test the alignment performance between NIR and VIS images with the same identity. Extensive experiments and an ablation study of SADG on three public datasets show significant alignment performance and recognition results. Specifically, the Rank1 accuracy achieved was close to 99.9% for the CASIA NIR-VIS 2.0, Oulu-CASIA NIR-VIS and BUAA VIS-NIR datasets, respectively.

Predicting pillar stability in underground mines is a critical problem because the instability of the pillar can cause large-scale collapse hazards. To predict the pillar stability for underground coal and stone mines, two new models (random tree and C4.5 decision tree algorithms) are proposed in this paper. Pillar stability depends on the parameters: width of the pillar (W), height of the pillar (H), W/H ratio, uniaxial compressive strength of the rock (σucs), and pillar stress (σp). These parameters are taken as input variables, while underground mines pillar stability as output. Various performance indices, i.e., accuracy, precision, recall, F-measure, Matthews correlation coefficient (MCC) were used to evaluate the performance of the models. The performance evaluation of the established models showed that both models were able to predict pillar stability with reasonable accuracy. Results of the random tree and C4.5 decision tree were also compared with available models of support vector machine (SVM) and fishery discriminant analysis (FDA). The results show that the proposed random tree provides a reliable and feasible method of evaluating the pillar stability for underground mines.

The Li1.2Mn0.54−xNbxCo0.13Ni0.13O2−6xF6x (x = 0, 0.01, 0.03, 0.05) is prepared by traditional solid-phase method, and the Nb and F ions are successfully doped into Mn and O sites of layered materials Li1.2Mn0.54Co0.13Ni0.13O2, respectively. The incorporating Nb ion in Mn site can effectively restrain the migration of transition metal ions during long-term cycling, and keep the stability of the crystal structure. The Li1.2Mn0.54−xNbxCo0.13Ni0.13O2−6xF6x shows suppressed voltage fade and higher capacity retention of 98.1% after 200 cycles at rate of 1 C. The replacement of O2− by the strongly electronegative F− is beneficial for suppressed the structure change of Li2MnO3 from the eliminating of oxygen in initial charge process. Therefore, the initial coulombic efficiency of doped Li1.2Mn0.54−xNbxCo0.13Ni0.13O2−6xF6x gets improved, which is higher than that of pure Li1.2Mn0.54Co0.13Ni0.13O2. In addition, the Nb and F co-doping can effectively enhance the transfer of lithium-ion and electrons, and thus improving rate performance.

The causes of chronic heart failure (CHF) and its progression are likely to be due to complex genetic factors. Adenosine receptors A2A and A2B (ADORA2A and ADORA2B, respectively) play an important role in cardio-protection. Therefore, polymorphisms in the genes encoding those receptors may affect the risk and severity of CHF. This study was a case-control comparative investigation of 300 northern Chinese Han CHF patients and 400 ethnicity-matched healthy controls. Four common single-nucleotide polymorphisms (SNPs) of ADORA2A (rs2236625, rs2236624, rs4822489, and rs5751876) and one SNP of ADORA2B (rs7208480) were genotyped and an association between SNPs and clinical outcomes was evaluated. Odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the association. The rs4822489 was significantly associated with the severity of CHF after adjustment for traditional cardiovascular risk factors (p = 0.040, OR = 1.912, 95% CI = 1.029–3.550). However, the five SNPs as well as the haplotypes were not found to be associated with CHF susceptibility. The findings of this study suggest that rs4822489 may contribute to the severity of CHF in the northern Chinese. However, further studies performed in larger populations and aimed at better defining the role of this gene are required.