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C2H6S2N2O3Co, monoclinic, C2/c (no. 15), a = 12.4340(7) Å, b = 6.0522(4) Å, c = 10.6851(8) Å, β = 90.543(6)°, V = 804.05(9) Å3, Z = 4, Rgt(F) = 0.0200, wRref(F2) = 0.0499, T = 298(2) K.

Abstract The drill tail of a rock drill meets high-frequency fretting in both the rotational and axial axes. The pure water seal is prone to damage and failure owing to its difficult working features and the low viscosity of the water medium. Orthogonal testing is used to simulate and model the Y-shaped seal ring to enhance the performance of the water seal. The maximum contact stress and maximum Von Mises stress are selected as indicators of sealing effectiveness based on an assessment of the effects of different seal section parameters on sealing performance. These insights serve to improve the building of the water seal. Maximum contact stress is demonstrated to be linked to lip thickness and chamfer length, but inversely proportional to lip length. Meanwhile, the maximum Von Mises stress is directly influenced by lip depth, including the angle of the lip and drill tail, and is inversely linked to lip thickness. Maximum contact stress and maximum Von Mises stress are lowered by 15% and 45%, respectively, in the revised Y-shaped water seal, resulting in greatly better sealing performance.

To optimize and establish the pretreatment method for aflatoxins (AFS) in grains, the method was optimized by using naturally contaminated grain samples. The grains were extracted by crushing, cleaned up by immunoaffinity column, and quantified by ultra performance liquid chromatography with fluorescence detector. The results showed that the extraction efficiency of 84% acetonitrile water was better than that of 70% methanol water, without soaking, and more than 99% of aflatoxin B1 could be extracted from the samples by vortex shaking for 20 min or high-speed homogenization for 2 min. The method has good accuracy and reproducibility. The results of the determination of aflatoxin B1 components in corn flour, brown rice flour, rice flour and other grain matrices of the national certified standards were within the range of standard values and their extended uncertainties, with a coefficient of variation of 5.2%, and the determination results were more satisfactory. Using this method to participate in the FAPAS (PT04359) proficiency testing, |Z|

Highlights Biochar/clay mineral nanocomposites were prepared by H3PO4 hydrothermal treatment followed by KOH activation using oil shale semi-coke. The nanocomposites exhibited high adsorption capacities to organic pollutants due to electrostatic attraction, π–π stacking and hydrogen bonds. It provided a feasible strategy for full-components resource utilization of oil shale semi-coke.

Objective Previous study have shown that lipid accumulation product (LAP), visceral adiposity index (VAI), triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C) and triglycerides/glucose index (TyG index) could be simple clinical indicators of insulin resistance (IR) based on anthropometric and/or biochemical parameters. However, the rational and preferred surrogate marker of IR in different population has yet to be validated. The aim of this study was evaluating the practicability of the LAP, VAI, TG/HDL-C, and TyG in predicting IR in middle-aged Chinese population. Methods A cross-sectional study was conducted in 569 Chinese participants (mean age was 48.5; man 67.7%), and each participant completed a questionnaire survey, anthropometric measurement, and biochemical testing. One-way ANOVAs, Chi-squared test, Pearson’s correlation, and multiple logistic regression were used to evaluate the association between VAI, LAP, TG/HDL-C, and TyG with IR. To correctly discriminate individuals with insulin resistance, a receiver operating characteristic (ROC) analysis was conducted for each evaluated variable and the overall diagnostic accuracy was quantified using the area under the ROC curve (AUC). The AUC of evaluated variables were compared using a nonparametric approach. The optimal cut-off points were determined by the Youden’s index, and the corresponding sensitivity and specificity were provided. Results Significant positive correlation was identified between HOMA-IR with TG/HDL-C (r = 0.306), VAI (r = 0.217), LAP (r = 0.381), and TyG (r = 0.371), respectively (all p

Although the sparseness and irregularity of point cloud data have been successfully solved by deep neural networks.However,how to learn the local features of point clouds is still a challenging problem.Existing networks for point cloud representation learning have the problem of extracting features independently between points and points.To this end,a new spatial graph convolution is proposed.Firstly,an adaptive hole K-nearest neighbor algorithm is proposed when constructing the graph structure to maximize local topo-logical structure information.Secondly,the angle feature between each edge of the convolution kernel and the receptive field map is added to the convolution,which ensures more discriminative feature extraction.Finally,in order to make full use of local features,a novel graph pyramid pooling is proposed.This algorithm is tested on the standard public data sets ModelNet40 and ShapeNet,and the accuracy is 93.2% and 86.5% respectively.Experimental results show that the proposed algorithm is at a leading level in point cloud representation learning.

Subsequent findings reveal the combination characteristics and spatial patterns of plant functional traits, and their response and adaptation to environmental changes in the Qinghai-Tibet Plateau. We analyzed the variation in characteristics and the influence of environmental factors on leaf functional traits from 78 quadrats in July 2021, using: one-way ANOVA, Tukey’s Honest Significant Difference (HSD) post hoc test, Pearson correlation coefficient (r) analysis, and redundancy analysis (RDA) in the Qilian Mountains. Only the leaf carbon content (LCC) of arbors was a weak variation indicator in leaf function traits of different plant types, whereas other leaf function traits including: the LCC of herbaceous plants (herbs) and shrub plants (shrubs), and the leaf nitrogen content (LNC) and carbon to nitrogen (C/N) ratio of arbors were medium variation indicators. The LNC, leaf phosphorus content (LPC), C/N ratio(C/N), C/P ratio(C/P), and N/P ratio (N/P)of herbs and shrubs, and the LPC, C/P, and N/P of arboreal plants (arbors) were strong variation indicators. Altitude was also one of the main factors affecting functional traits of plants in cold regions. Electrical conductivity (EC) and soil phosphorus content (SPC) were the main factors affecting changes in the leaf functional traits of herbs. Soil bulk density (SBD) and Soil salinity (SAL) were the main factors affecting changes in the leaf functional traits of shrubs. Soil nitrogen content (SNC) and soil temperature (ST) were the main factors affecting changes in the leaf functional traits of arbors.

Common unsupervised feature selection methods only consider the selection of discriminative features,while ignoring the redundancy of features and failing to consider the problem of small classes,which affect the classification performance.Based on this background,a robust uncorrelated regression algorithm is proposed.First,research on uncorrelated regression,use uncorrelated orthogonal constraints to find irrelevant but discriminative features.Uncorrelated constraints keep the data structure in the Stiefel manifold,making the model have a closed solution,avoiding the possible trivial solutions caused by the traditional ridge regression model.Secondly,the loss function and the regularization term use the L2,1 norm to ensure the robustness of the model and obtain a sparse projection matrix.At the same time,the small class problem is taken into account,so that the number of projection matrices is not limited by the number of classes,and the result is enough projection matrices to improve the classification performance of the model.Theoretical analysis and experimental results on multiple data sets show that the proposed method has better performance than other feature selection methods.

Cognitive impairment has become one of the most important diseases threatening the health of the elderly population. How to identify and evaluate it early is the key to the early diagnosis and treatment for this kind of disease. This review compares the cognitive assessment scales commonly used at home and abroad so as to provide a reference for researchers to choose a suitable scale. It also introduces the recent progress of cognitive impairment screening scales in China in order to develop a cognitive impairment screening scale for Chinese population.

In the Visible Light Communication (VLC) system based on circle Color Shift Keying (CSK) modulation constellation, the bit error rate performance is poorer under certain number of modulation order. In this paper, we optimize the constellation point design, in keeping the constellation points under the condition of invariable pointing triangle center redesigned constellation structure. We change the constellation point location and increase the minimum code distance between constellation points to improve the bit error rate performance. In order to further improve the transmission quality of VLC signal, the principle of Finite State Machine (FSM) is introduced to carry out joint coding design to further improve bit error rate. Finally, simulation verification and performance analysis are carried out. The simulation results show that, compared with the traditional CSK modulation technology, the optimized extended circular constellation CSK and FSM combined coding proposed in this paper have better bit error rate performance. The gain of 4 Combination Coding-Finite State Machine (CC-FSM) code is 2.1 dB compared with that of 4-CSK, and the gain of 8CC-FSM code is 1.7 dB compared with that of 8-CSK.

Plant functional traits are adaptive traits formed by interactions between plants and the environment. Considering the Three-River Headwaters Region as a case study, this study systematically analyzed the relationship between plant functional traits and environmental factors in cold regions. The results show that there were significant differences in plant functional traits among the different vegetation types (herbs, shrubs, and arbor plants). Leaf traits such as leaf area (LA), leaf length (LL), leaf width (LW), leaf circumference (LC), and shape coefficient (SC) showed the same trends among herbs, shrubs, and arbor plants. The correlation between leaf functional traits of plants in alpine regions shows that the unique growth mode of different plants and their degree of adaptation to alpine environments ultimately determine the leaf functional trait variations. Moreover, there was a negative correlation between soil temperature and the nitrogen balance index (NBI), chlorophyll content (Chl), flavonoid content (Flv), and SC, whereas there was a trend of first increasing and then decreasing relationship between soil temperature, LL (P 0.05) were significantly positively correlated with altitude. Conversely, there was no significant negative correlation between LW and altitude (P > 0.05). We conclude that climate factors play a decisive role in the distribution of plant functional traits at a global scale, whereas land use and disturbances play a major role at a regional scale, and topographic and soil factors determine the distribution of local characteristics.

BackgroundGeneralized anxiety disorder (GAD) is a chronic disorder characterized by excessive, pervasive, persistent worrying that is difficult to control. Jiuwei Zhenxin granules may be safer and more effective than non-benzodiazepine anti-anxiety drugs for treating GAD. This study aimed to assess the efficacy and safety of Jiuwei Zhenxin granules alone or in combination with the benzodiazepine alprazolam.Materials and methodsA total of 710 patients were recruited from outpatient clinics and were randomly divided into two groups to receive Jiuwei Zhenxin granules (single drug group) or Jiuwei Zhenxin granules and alprazolam (combination group). The primary outcome was the response rate, which was defined as a ≥ 50% reduction from the baseline total score on the Hamilton Anxiety Scale (HAMA). Secondary outcome measures included mean changes in HAMA total score, psychological and somatic factors, Hamilton Depression Rating Scale total score, and SF-36 health survey score.ResultsAt 4 weeks after treatment, the single and combination treatment groups showed significant improvement in the HAMA total score and they did not differ significantly in response rate (77.58 vs. 79.17%) or rate of adverse drug reactions (16.22 vs. 16.07%).ConclusionJiuwei Zhenxin granules are an effective, safe, and well-tolerated treatment against GAD. Combining them with alprazolam may not significantly improve efficacy.Clinical trial registration[www.ClinicalTrials.gov], identifier [CHICTR1800020095].

Artificial intelligence (AI) technology has been widely applied in various fields in recent years. Nevertheless, no systematic study has yet been conducted on the effects of AI technology on different fields. In this study, the impacts of the latest AI technology on technological innovation in different fields were analysed and quantized systematically from a patent perspective. Moreover, trends on AI technological innovation in some fields were analysed thoroughly. We conducted this study on a dataset of patents related to AI technology. Based on the patent dataset, we carried out a statistical analysis on technology fields, which we defined and classified based on international patent classification (IPC) number. Distributions of IPC in different fields were also analysed to determine the trends on AI technological innovation. The research conclusions can provide useful information to investors and enterprises, who are interested in the state of the art concerning AI technology.

A porous semi-interpenetrating network (semi-IPN) hydrogel adsorbent with excellent adsorption properties and removal efficiency towards Pb(II) was prepared by a facile grafting polymerization reaction in aqueous medium using natural biopolymer sodium alginate (SA) as the main chains, sodium acrylate (NaA) as the monomers, and poly(vinyl alcohol) (PVA) as the semi-IPN component. FTIR, TGA and SEM analyses confirm that NaA monomers were grafted onto the macromolecular chains of SA, and PVA chains were interpenetrated and entangled with the crosslinked network. The incorporation of PVA facilitates to form pores on the surface of hydrogel adsorbent. The semi-IPN hydrogel containing 2 wt% of PVA exhibits high adsorption capacity and fast adsorption rate for Pb(II). The best adsorption capacity reaches 784.97 mg/g, and the optimal removal rate reaches 98.39% (adsorbent dosage, 2 g/L). In addition, the incorporation of PVA improved the gel strength of hydrogel, and the storage modulus of hydrogel increased by 19.4% after incorporating 2 wt% of PVA. The increase of gel strength facilitates to improve the reusability of hydrogel. After 5 times of regeneration, the adsorption capacity of SA-g-PNaA decreased by 23.2%, while the adsorption capacity of semi-IPN hydrogel only decreased by 10.8%. The adsorption kinetics of the hydrogel in the initial stage (the moment when the adsorbent contacts solution) and the second stage are fitted by segmentation. It is intriguing that the adsorption kinetics fits well with both pseudo-second-order kinetic model and pseudo-first-order model before 60 s, while only fits well with pseudo-second-order adsorption model in the whole adsorption process. The chemical complexing adsorption mainly contribute to the efficient capturing of Pb(II).

BACKGROUND In current ecological environmental monitoring, the standard methods used to determine the total contents of inorganic elements, such as heavy metals in soil, include atomic absorption spectrometry (AAS), atomic fluorescence spectrometry (AFS) and wavelength dispersive X-ray fluorescence spectrometry (WDXRF). OBJECTIVES To evaluate the quality, validity and mutual comparability of the results obtained by different analytical methods. METHODS Twenty actual soil samples of different types from different regions in China were selected and inserted into the national soil environmental monitoring sample batch blind, and sent to 3-5 laboratories. AAS/AFS, WDXRF and portable X-ray fluorescence spectrometry (p-XRF) were used to determine the total amount of Cr, Ni, Cu, Zn, As, Hg, Cd, Pb, V and Mn in parallel. RESULTS The content of these elements was equally distributed at levels of ≤ 1.0, 1.0-2.0, 2.0-10.0, and 10.0. The results show that 85% samples had better inter-laboratory relative deviation (RD) of the WDXRF method in terms of Cr, Ni, Cu, Zn and Pb. On the other hand, 60% samples had better RD using AFS method for the As determination. Element content had more obvious effect on RD for WDXRF method. Generally, the inter-laboratory precision control was good for both AAS/AFS and WDXRF methods, and the WDXRF method was more desirable. Through further analysis of the parallelism between AAS/AFS and WDXRF methods (evaluated as the relative deviation RD' of the analytical results of these two methods), it showed that almost all the RD' of Cr, Ni, Cu and Zn was less than 20%, and more than eighty percent RD' of As and Pb was less than 20%. The results of Pearson correlation and linear relationship analysis also show that the analytical results of two methods were highly comparable. Additionally, there was also good comparability between the results of AAS/AFS and p-XRF methods for determination of Cr, Ni, Cu, Zn, Pb and As. CONCLUSIONS AAS/AFS method and WDXRF method have equivalent test results. In actual monitoring task, the determination of Cd and Hg with lower contents should be determined by AAS/AFS which have lower detection limits. WDXRF should be chosen for the analysis large quantities of soil. Under specific experimental conditions, the p-XRF method also can obtain an acceptable quantitative results.

The cause of death in most breast cancer patients is disease metastasis and the occurrence of multidrug resistance (MDR). Ornithine decarboxylase (ODC), which is involved into multiple pathways, is closely related to carcinogenesis and development. Ursolic acid (UA), a natural triterpenoid compound, has been shown to reverse the MDR characteristics of tumor cells. However, the effect of UA on the invasion and metastasis of tumor cells with MDR is not known. Therefore, we investigated the effects of UA on invasion and metastasis, ODC-related polyamine metabolism, and MAPK-Erk-VEGF/MMP-9 signaling pathways in a doxorubicin-resistant breast cancer cell (MCF-7/ADR) model. The obtained results showed that UA significantly inhibited the adhesion and migration of MCF-7/ADR cells, and had higher affinities with key active cavity residues of ODC compared to the known inhibitor di-fluoro-methyl-ornithine (DFMO). UA could downregulate ODC, phosphorylated Erk (P-Erk), VEGF, and matrix metalloproteinase-9 (MMP-9) activity. Meanwhile, UA significantly reduced the content of metabolites of the polyamine metabolism. Furthermore, UA increased the intracellular accumulation of Dox in MCF-7/ADR cells. Taken together, UA can inhibit against tumor progression during the treatment of breast cancer with Dox, and possibly modulate the Erk-VEGF/MMP-9 signaling pathways and polyamine metabolism by targeting ODC to exert these effects.

Many Pseudomonas aeruginosa virulence traits that contribute to human infections are accepted as being associated with its environmental lifestyle. Therefore, identifying the molecular mechanisms that govern the lifestyle choice is of high significance. We previously reported that a mutation in suhB results in a decrease in swimming motility and increased biofilm formation compared to the wild-type strain. Yet, little is known about how this occurs. In this study, we demonstrated that SuhB inversely regulates motility and biofilm formation through the GacA-RsmY/Z-RsmA cascade. Mutations in gacA or the two small RNAs rsmY/rsmZ, or overproduction of the RsmA protein essentially rescued the motility defect of the suhB mutant. Additionally, we identified a c-di-GMP mediated mechanism for SuhB regulation of motility and biofilm formation. We showed that the ΔsuhB mutant displayed elevated levels of c-di-GMP, and the ΔsuhB motility and biofilm phenotypes could be switched by artificially decreasing c-di-GMP levels. Further experiments led to the identification of the diguanylate cyclase GcbA responsible for regulating the c-di-GMP concentration in ΔsuhB and hence the switch between planktonic and surface-associated growth. Together, our results demonstrate a novel mechanism for SuhB regulation of the lifestyle transition via the Gac/Rsm and c-di-GMP signaling networks in P. aeruginosa.

A series of superporous carboxymethylcellulose-graft-poly(acrylamide)/palygorskite (CMC-g-PAM/Pal) polymer monoliths presenting interconnected pore structure and excellent adsorption properties were prepared by one-step free-radical grafting polymerization reaction of CMC and acrylamide (AM) in the oil-in-water (O/W) Pickering-medium internal phase emulsions (Pickering-MIPEs) composed of non-toxic edible oil as a dispersion phase and natural Pal nanorods as stabilizers. The effects of Pal dosage, AM dosage, and co-surfactant Tween-20 (T-20) on the pore structures of the monoliths were studied. It was revealed that the well-defined pores were formed when the dosages of Pal and T-20 are 9–14 and 3%, respectively. The porous monolith can rapidly adsorb 1,585 mg/g of methyl violet (MV) and 1,625 mg/g of methylene blue (MB). After the monolith was regenerated by adsorption-desorption process for five times, the adsorption capacities still reached 92.1% (for MV) and 93.5% (for MB) of the initial maximum adsorption capacities. The adsorption process was fitted with Langmuir adsorption isotherm model and pseudo-second-order adsorption kinetic model very well, which indicate that mono-layer chemical adsorption mainly contribute to the high-capacity adsorption for dyes. The superporous polymer monolith prepared from eco-friendly Pickering-MIPEs shows good adsorption capacity and fast adsorption rate, which is potential adsorbent for the decontamination of dye-containing wastewater.

Multifunctional nanomedicines with active targeting and stimuli-responsive drug release function utilizing pathophysiological features of the disease are regarded as an effective strategy for treatment of rheumatoid arthritis (RA). Under the inflammatory environment of RA, activated macrophages revealed increased expression of folate receptor and elevated intracellular reactive oxygen species (ROS) level. In this study, we successfully conjugated folate to polyethylene glycol 100 monostearate as film-forming material and further prepared methotrexate (MTX) and catalase (CAT) co-encapsulated liposomes, herein, shortened to FOL-MTX&CAT-L, that could actively target to activated macrophages. Thereafter, elevated intracellular hydrogen peroxide, the main source of ROS, diffused into liposomes and encapsulated CAT catalyzed the decomposition of hydrogen peroxide into oxygen and water. Continuous oxygen-generation inside liposomes would eventually disorganize its structure and release the encapsulated MTX. We characterized the in vitro drug release, cellular uptake and cytotoxicity studies as well as in vivo pharmacokinetics, biodistribution, therapeutic efficacy and safety studies of FOL-MTX&CAT-L. In vitro results revealed that FOL-MTX&CAT-L possessed sufficient ROS-sensitive drug release, displayed an improved cellular uptake through folate-mediated endocytosis and exhibited a higher cytotoxic effect on activated RAW264.7 cells. Moreover, in vivo results showed prolonged blood circulation time of PEGylated liposomes, enhanced accumulation of MTX in inflamed joints of collagen-induced arthritis (CIA) mice, reinforced therapeutic efficacy and minimal toxicity toward major organs. These results imply that FOL-MTX&CAT-L may be used as an effective nanomedicine system for RA treatment.

PURPOSE: To compare the evaluation metrics for deep learning methods that were developed using imbalanced imaging data in osteoarthritis studies. MATERIALS AND METHODS: This retrospective study utilized 2996 sagittal intermediate-weighted fat-suppressed knee MRIs with MRI Osteoarthritis Knee Score readings from 2467 participants in the Osteoarthritis Initiative study. We obtained probabilities of the presence of bone marrow lesions (BMLs) from MRIs in the testing dataset at the sub-region (15 sub-regions), compartment, and whole-knee levels based on the trained deep learning models. We compared different evaluation metrics (e.g., receiver operating characteristic (ROC) and precision-recall (PR) curves) in the testing dataset with various class ratios (presence of BMLs vs. absence of BMLs) at these three data levels to assess the models performance. RESULTS: In a subregion with an extremely high imbalance ratio, the model achieved a ROC-AUC of 0.84, a PR-AUC of 0.10, a sensitivity of 0, and a specificity of 1. CONCLUSION: The commonly used ROC curve is not sufficiently informative, especially in the case of imbalanced data. We provide the following practical suggestions based on our data analysis: 1) ROC-AUC is recommended for balanced data, 2) PR-AUC should be used for moderately imbalanced data (i.e., when the proportion of the minor class is above 5% and less than 50%), and 3) for severely imbalanced data (i.e., when the proportion of the minor class is below 5%), it is not practical to apply a deep learning model, even with the application of techniques addressing imbalanced data issues.

The imaged could be seemed to the approximation of the polygons,so it was important to the image match that researched the polygon match method.It is based the combination of the axis of least inertia and the chain,this method was capable of preserving both contour as well as region information,and it utilized the degree of triangular membership which computed by the feature triangular to compute the similarity between the two objects.This method was invariant to image transformations,and robust to concave polygons.The experimental results show that this method’s performance and retrieval efficiency is well.