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A variety of prosthetic ankles have been successfully developed to reproduce the locomotor ability for lower limb amputees in daily lives. However, they have not been shown to sufficiently improve the natural gait mechanics commonly observed in comparison to the able-bodied, perhaps due to over-simplified designs of functional musculoskeletal structures in prostheses. In this study, a flexible bionic ankle prosthesis with joints covered by soft material inclusions is developed on the basis of the human musculoskeletal system. First, the healthy side ankle–foot bones of a below-knee amputee were reconstructed by CT imaging. Three types of polyurethane rubber material configurations were then designed to mimic the soft tissues around the human ankle, providing stability and flexibility. Finite element simulations were conducted to determine the proper design of the rubber materials, evaluate the ankle stiffness under different external conditions, and calculate the rotation axes of the ankle during walking. The results showed that the bionic ankle had variable stiffness properties and could adapt to various road surfaces. It also had rotation axes similar to that of the human ankle, thus restoring the function of the talocrural and subtalar joints. The inclination and deviation angles of the talocrural axis, 86.2° and 75.1°, respectively, as well as the angles of the subtalar axis, 40.1° and 29.9°, were consistent with the literature. Finally, dynamic characteristics were investigated by gait measurements on the same subject, and the flexible bionic ankle prosthesis demonstrated natural gait mechanics during walking in terms of ankle angles and moments.

ObjectiveThis study explored the relationship between college students’ physical activity motivation and exercise behavior and constructed a chain mediation model through the mediating roles of exercise climate and exercise self-efficacy.MethodsBy random sampling, 1,032 college students were investigated using the Exercise Motivation Scale, Physical Exercise Rating Scale, Exercise Climate Scale, and Exercise Self-Efficacy Scale.Results(1) There was a huge positive correlation between exercise motivation and exercise behavior (r = 0.240, p β = 0.068, t = 0.040, p β = 0.373, t = 0.061, p β = 0.174, t = 0.039, p β = 0.302, t = 0.051, p β = 0.190, t = 0.048, p Conclusion(1) Exercise climate, exercise self-efficacy, and exercise behavior can all be significantly predicted by exercise motivation, suggesting that exercise motivation may help to enhance these variables. (2) In addition to having a direct impact on exercise behavior, exercise motivation can also have an indirect impact through the separate mediating effects of exercise climate and exercise self-efficacy as well as the chain mediating effect of exercise climate and exercise self-efficacy, which is crucial for encouraging college students to engage in physical activity.

Straw fiber mulch film is a promising alternative to petroleum-based plastic mulching film. The optimal combination of process parameters during the manufacturing process of the wheat straw fiber-based plant fiber film (hereinafter referred to as film), was studied via a five-factor and five-level central composite design methodology. Response surface methodology was used to analyze the effects of sizing agent content, wet strength agent mass fraction, basis weight, KP pulp mixing ratio, and beating degree of wheat straw fiber on the dry tensile index, wet tensile index, and degradation time. The optimal parameters were as follows: a sizing agent content of 2.0%, a wet strength agent mass fraction of 60%, a beating degree of wheat straw fiber of 60 °SR, a basis weight of 54.6 to 60.8 g/m2, and a KP pulp mixing ratio of 37.6% to 44.7%. These parameters achieved the desired physical properties, i.e., a degradation time of 55 to 65 d, a dry tensile index of 10 to 12 N·m/g, and a wet tensile index 3.5 to 5.5 N·m/g. With the optimal manufacturing parameters, straw mulch film would meet the demands for agriculture.

Staphylococcus aureus and its biofilm have emerged as a significant threat to the safety of dairy products. In recent years, lactic acid bacteria (LAB) bacteriocins have been widely acknowledged as the potential natural antibacterial substance in food biopreservation due to their excellent antibacterial effects. However, few LAB bacteriocins with antibacterial and antibiofilm activity against S. aureus have been reported in dairy products. In the present study, a novel bacteriocin LSX01 of Lactobacillus paracasei LS-6 isolated from a traditional fermented yogurt produced in Yunnan, China, was purified and characterized extensively. The LSX01 possessed a molecular weight of 967.49 Da and an AA sequence of LDQAGISYT. The minimum inhibitory concentration of LSX01 against S. aureus_45 was 16.90 μg/mL, which was close to or lower than the previously reported bacteriocins. The LSX01 exhibited an extensive antimicrobial spectrum against both gram-positive and gram-negative bacteria. Moreover, LSX01 exhibited excellent tolerance to heat and acid-base treatments, and sensitivity to the proteolytic enzymes, such as pepsin and proteinase K. Furthermore, the treatment of S. aureus_45 planktonic cells with LSX01 significantly reduced their metabolic activity and disrupted the cell membrane integrity. Scan electron microscopy results demonstrated that LSX01 induced cytoplasmic content leakage and cell deformation. Additionally, biofilm formation of S. aureus_45 was also significantly inhibited by LSX01. Overall, the results suggested that the novel LAB bacteriocin LSX01 possessed antibacterial activity and antibiofilm activity against S. aureus and, hence, could have potential for improving safety of dairy products.

Mitochondria are the leading organelle for energy metabolism. The toxic effects of environmental toxicants on mitochondrial morphology, energy metabolism, and their determination of cell fate have already been broadly studied. However, minimal research exists on effects of environmental toxicants such as pesticides on mitochondrial energy metabolism at in vitro subcellular level, particularly from an omics perspectives (e.g., metabolomics). Here, German cockroach (Blattella germanica) was fed diets with (0.01 and 0.001 mg/mL) and without abamectin, and highly purified fat body mitochondria were isolated. Swelling measurement confirmed abnormal mitochondrial swelling caused by abamectin stress. The activity of two key mitochondrial energy metabolism-related enzymes, namely succinic dehydrogenase and isocitrate dehydrogenase, was significantly affected. The metabolomic responses of the isolated mitochondria to abamectin were analyzed via untargeted liquid chromatography/mass spectrometry metabolomics technology. Fifty-two differential metabolites (DMs) were identified in the mitochondria between the 0.001 mg/mL abamectin-fed and the control groups. Many of these DMs were significantly enriched in pathways involved in ATP production and energy consumption (e.g., oxidative phosphorylation, TCA cycle, and pentose phosphate pathway). Nineteen of the DMs were typically related to energy metabolism. This study is valuable for further understanding mitochondrial toxicology under environmental toxicants, particularly its subcellular level.

From Jan. 2013 to Nov. 2018, we carried out the investigation on vegetation studies in the ecological monitoring programs, Shenzhen and totally researched 170 plant communities of mountain areas etc., few areas of street regions and parks etc., for communities’ structural characteristics and plant diversity. We comparatively analyzed natural forests, semi-natural forest and artificial forest composition and structural characters and family, genus and species diversity level and the main affected factors. We also researched and analyzed these communities’ structural characteristics and pant diversity, comparatively analyzed natural forests, semi-natural forest and artificial forest composition and structural characters and family, genus and species diversity level, the main affected factors; researched and analyzed the relationship between plant community structure characteristics with the absorbing ability to PM2.5 pollutants. The result showed that the structure and plant diversity of natural forest were obviously better than artificial disturbed forest or artificial forest, the semi-natural forest was the middle level of the forests, In the indices of height, DBH, coverage and crow width etc. of tree layer, natural forests and semi-natural forests were obvious higher than that of artificial disturbed forest or artificial forest; in some forests of artificial disturbed forest or artificial forest, though their richness indices of family and genus were a slightly higher, but this contribution was majorly due to herb layer plants, and some shrub layer plants. Analyzing three kinds of communities, the number of tree layer species of natural forest was the largest, and their every α-diversity index value was the highest; these characteristics values of semi-natural forest were second, artificial disturbed forests or artificial forests were the lowest; in shrub layer, and herb layer, few α-diversity indices of artificial disturbed forest or artificial forest were a slightly higher than that of some natural forests, but the integral values of the diversity indices of natural forest and semi-natural forest were obviously higher than the former. The research showed that in the artificial disturbed forest or artificial forest, because there have some little scale clearing areas, so some pioneer plant species could enter the community and formed a temporarily increase of species diversity, however, these species major were some shrub and herb plants; but tree layer possessed obviously more, even surpassed several ten times biomass than shrub and herb layers. Therefore, the respects of maintain ecosystem stability and other ecological efficient have major and dominated position and so on; and then this community can be natural recovery and succession, those forementioned new entire plants shall withdraw from the community and are replaced by the original plants of the community; but this process has already caused the ecological efficient loss and ecosystem unstable. Above research results are better evidence and theory reference to the argument problems on that are natural forest and natural restoration forest biodiversity higher? or is artificial forest biodiversity higher? and or is more artificial disturbed forest higher? Our researches showed that used random investigation method set quadrats, and combined typical investigation method, the structural indices in the all layer of community and all diversity indices of tree, shrub and herb layers and the integral values were similar, same or usually these indices in the community which set 600 m2, 800 m2 total quatrat area were higher (α-diversity) than that of more than 3000 m2, 4000 m2 or 7000 m2, even more than 17,000 m2 total quadrat area of communities. These lots of researches further proved that according to minimum area method for vegetation survey, in subtropical region, using random investigation method combined with typical investigation set 400 m2 or 400 m2 - 500 m2 total quad

Long-term visual tracking undergoes more challenges and is closer to realistic applications than short-term tracking. However, the performances of most existing methods have been limited in the long-term tracking tasks. In this work, we present a reliable yet simple long-term tracking method, which extends the state-of-the-art learning adaptive discriminative correlation filters (LADCF) tracking algorithm with a re-detection component based on the support vector machine (SVM) model. The LADCF tracking algorithm localizes the target in each frame, and the re-detector is able to efficiently re-detect the target in the whole image when the tracking fails. We further introduce a robust confidence degree evaluation criterion that combines the maximum response criterion and the average peak-to-correlation energy (APCE) to judge the confidence level of the predicted target. When the confidence degree is generally high, the SVM is updated accordingly. If the confidence drops sharply, the SVM re-detects the target. We perform extensive experiments on the OTB-2015 and UAV123 datasets. The experimental results demonstrate the effectiveness of our algorithm in long-term tracking.

Plant GDP-D-mannose pyrophosphorylase (GMPase) catalyzes a committed step in ascorbic acid biosynthesis pathway.

We review the research on complex dynamical networks (CDNs) with impulsive effects. We provide a comprehensive and intuitive overview of the fundamental results and recent progress of CDNs with impulsive effects, where impulsive effects are considered from two aspects, i.e., impulsive control and impulsive perturbation. Five aspects of CDNs with impulsive effects are surveyed, including synchronizing impulses, desynchronizing impulses, adaptive-impulsive synchronization, pinning impulsive synchronization, and CDNs with stochastic and impulsive effects. Finally, conclusions and some future research directions are briefly addressed.

Bimetallic catalysts (Ni-Co/AC and Ni-Fe/AC) supported on activated carbon (AC) were prepared via one-step method from coal as AC precursor with the addition of metal salts by KOH activation. The effects of the introduction of second metal (Co or Fe) into Ni/AC on the textural structure of the resultant bimetallic catalysts and their catalytic performances for methane decomposition were investigated. The results showed that active metals can be directly supported on AC by the reaction of metal species with carbon during the activation. The addition of Co or Fe to Ni/AC resulted in the decrease of specific surface area and pore volume. With increasing the loading of Co or Fe, metal alloys were formed and total surface area and pore volume declined, but the mesoporosity was increased. Bimetallic Ni-Co/AC and Ni-Fe/AC catalysts exhibited better catalytic activity and stability for methane decomposition compared than Ni/AC. The introduction of Co mainly improved initial catalytic activity; however, Ni-Fe/AC catalyst showed better behaviors in terms of reducing the deactivation rate of Ni-based catalyst than Ni-Co/AC catalyst, which is relative with the formation of Ni-Fe alloy and carbon fibers over Ni-Fe/AC. This work provides a simple and efficient approach to improve catalytic performances of Ni-based catalyst for methane decomposition.

High-order harmonic generation (HHG) from the interaction of ultra-intense laser pulses with atoms is an important tabletop short-wave coherent light source. Accurate quantum simulations of it present large computational difficulties due to multi-electron multidimensional effects. In this paper, the time-dependent response of hydrogen atoms is calculated using a time-series prediction scheme, the HHG spectrum is reconstructed very accurately. The accuracy of the forecasting is further improved by using a neural network scheme. This scheme is also applied to the simulation of the harmonic emission on multi-electron systems, and the applicability of the scheme is confirmed by the harmonic calculation of complex systems. This method is expected to simulate the nonlinear dynamic process of multi-electron atoms and molecules irradiated by intense laser pulses quickly and accurately.

Gastrointestinal disease is a major global threat to public health. In the past few decades, numerous studies have focuses on the application of small molecule gases in the disease treatment. Increasing evidence has shown that hydrogen sulfide (H2S) has anti-inflammatory and anti-oxidative effects, and can regulate gastric mucosal blood flow in the gastric mucosa. After gastric mucosa damage, the level of H2S in the stomach decreases. Administration of H2S can protect and repair the damaged gastric mucosa. Therefore, H2S is a new target for the repair and treatment of gastric mucosa damage. In this review, we introduce the roles of H2S in the treatment of gastric mucosa damage and provide the potential strategies for further clinical treatment.

Although pain is frequent in old age, older adults are often undertreated for pain. This is especially the case for long-term care residents with moderate to severe dementia who cannot report their pain because of cognitive impairments that accompany dementia. Nursing staff acknowledge the challenges of effectively recognizing and managing pain in long-term care facilities due to lack of human resources and, sometimes, expertise to use validated pain assessment approaches on a regular basis. Vision-based ambient monitoring will allow for frequent automated assessments so care staff could be automatically notified when signs of pain are displayed. However, existing computer vision techniques for pain detection are not validated on faces of older adults or people with dementia, and this population is not represented in existing facial expression datasets of pain. We present the first fully automated vision-based technique validated on a dementia cohort. Our contributions are threefold. First, we develop a deep learning-based computer vision system for detecting painful facial expressions on a video dataset that is collected unobtrusively from older adult participants with and without dementia. Second, we introduce a pairwise comparative inference method that calibrates to each person and is sensitive to changes in facial expression while using training data more efficiently than sequence models. Third, we introduce a fast contrastive training method that improves cross-dataset performance. Our pain estimation model outperforms baselines by a wide margin, especially when evaluated on faces of people with dementia. Pre-trained model and demo code available at https://github.com/TaatiTeam/pain_detection_demo .

At present, cardiovascular disease is regarded as one of the dangerous diseases that threaten human life. The morbidity and lethality caused by cardiovascular disease are constantly increasing every year. In this paper, we propose a two-stream style operation to handle the electrocardiogram (ECG) classification: one for time-domain features and another for frequency-domain features. For the time-domain features, convolutional neural networks (CNN) are constructed for feature learning and classification of ECG signals. For the frequency-domain features, support vector regression (SVR) machines are designed to perform the regression prediction on each signal. Finally, the D-S evidence theory is adopted to perform the decision fusion strategy on the time-domain and frequency-domain classification results. We confirm a recognition performance of 99.64% from the experiment result for the D-S evidence theory recognition system upon the MIT-BIH arrhythmia database. The analysis of various methods of ECG classification shows that the model delivers superior performance promotion across all these scenarios.

Background Moyamoya disease (MMD) is an important cause of stroke in children and young adults in Asia. To date, diagnosis remains challenging due to varying clinical manifestations and unknown pathogenesis. The study aims to identify cerebrospinal fluid (CSF) exosomal microRNAs (exomiRs) that can serve as a novel diagnostic biomarker for diagnosis and assess its clinical applications. Methods CSF samples were taken from 31 MMD patients and 31 healthy controls. Initial screening of miRNA expression was performed on samples pooled from MMD patients and controls using microarray and validated using quantitative reverse transcription polymerase chain reaction (qRT-PCR). The diagnostic accuracy of the potential exosomal miRNAs was evaluated using receiver operating characteristic curve analyses in an independent patient cohort. The potential pathways regulated by the miRNAs was also determined using bioinformatics analysis. Results The microarray results demonstrated that six exomiRs were dysregulated in the MMD patients compared to the controls. Using qRT-PCR, we validated four of the miRNAs (miR-3679-5p, miR-6165, miR-6760-5p, and miR-574-5p) as a biomarker for MMD diagnosis. The four exomiRs showed enhanced sensitivity (75%) and specificity (93.75%) in terms of differentiating MMD patients from healthy subjects [area under the curve (AUC) = 0.9453]. Pathway enrichment analysis for potential targets of six exomiRs identified proteins involved in cell adhesion and junction formation in the brain. Conclusions We identified a novel and highly sensitive exomiRs signature for MMD detection and explored its potential targets using bioinformatics analysis.

Two cytochrome P450 enzymes, CYP97A3 and CYP97C1, catalyze hydroxylations of the β- and ε-rings of α-carotene to produce lutein. Chirality is introduced at the C-3 atom of both rings, and the reactions are both pro-3 R –stereospecific. We determined the crystal structures of CYP97A3 in substrate-free and complex forms with a nonnatural substrate and the structure of CYP97C1 in a detergent-bound form. The structures of CYP97A3 in different states show the substrate channel and the structure of CYP97C1 bound with octylthioglucoside confirms the binding site for the carotenoid substrate. Biochemical assays confirm that the ferredoxin-NADP + reductase (FNR)–ferredoxin pair is used as the redox partner. Details of the pro-3 R stereospecificity are revealed in the retinal-bound CYP97A3 structure. Further analysis indicates that the CYP97B clan bears similarity to the β-ring–specific CYP97A clan. Overall, our research describes the molecular basis for the last steps of lutein biosynthesis.

Dendritic spines of excitatory neurons undergo activity-dependent structural and functional plasticity, which are cellular correlates of learning and memory. However, mechanisms underlying the rapid morphological changes immediately after NMDAR-mediated Ca2+ influx into spines remain poorly understood. Here we report that endophilin A1, a neuronal N-BAR protein, orchestrates membrane dynamics with actin polymerization to initiate spine enlargement in the induction phase of long-term potentiation (LTP). Upon LTP induction, Ca2+/calmodulin enhances its binding to both membrane and p140Cap, a cytoskeleton regulator. As a result, endophilin A1 rapidly associates with the relaxed plasma membrane and promotes actin polymerization, leading to acute expansion of spine head. Moreover, not only the p140Cap-binding, but also calmodulin- and membrane-binding capacities of endophilin A1 are required for LTP and long-term memory. Thus, endophilin A1 functions as calmodulin effector to drive spine enlargement in response to Ca2+ influx in the initial phase of structural plasticity.

Effective extraction of characteristic information from sequencing data of cancer patients is an essential application for cancer research. Several prognostic classification models for breast cancer sequencing data have been established to assist patients in their treatment. However, these models still have problems such as poor robustness and low precision. Based on the convolutional network model in deep learning, we construct a new classifier PCA-1D LeNet-Ada (PLA) by using principal component extraction method, Le-Net convolution network, and Adaptive Boosting method. PLA predicts three biomarkers for breast cancer patients based on their somatic cell copy number variations and gene expression profiles.

As one of the core contents of intelligent monitoring, target tracking is the basis for video content analysis and processing. In visual tracking, due to occlusion, illumination changes, and pose and scale variation, handling such large appearance changes of the target object and the background over time remains the main challenge for robust target tracking. In this paper, we present a new robust algorithm (STC-KF) based on the spatio-temporal context and Kalman filtering. Our approach introduces a novel formulation to address the context information, which adopts the entire local information around the target, thereby preventing the remaining important context information related to the target from being lost by only using the rare key point information. The state of the object in the tracking process can be determined by the Euclidean distance of the image intensity in two consecutive frames. Then, the prediction value of the Kalman filter can be updated as the Kalman observation to the object position and marked on the next frame. The performance of the proposed STC-KF algorithm is evaluated and compared with the original STC algorithm. The experimental results using benchmark sequences imply that the proposed method outperforms the original STC algorithm under the conditions of heavy occlusion and large appearance changes.

Tar production from co-pyrolysis is highly dependent on synergies between coal and biomass volatiles. Therefore, enhancing their interactions during co-pyrolysis is crucial. In this study, three mixing modes, including mechanical mixing (M-type) and two layered loading modes (the U-type with upper Naomaohu coal (NMH) and lower cedar sawdust (CS) and the L-type with upper CS and lower NMH), were specially designed to explore the synergies between NMH and CS volatiles based on the analyses of products distribution, tar fractions and compositions, and stable radicals in char. The results show that sufficient void space is required for the co-pyrolysis synergies between CS and NMH volatiles. With the M-type mode, the CS volatiles preferably formed char on the NMH surface in a limited void space, inhibiting coal pyrolysis. The layered L-type and U-type modes enhanced the co-pyrolysis synergies, and the CS volatiles acted as hydrogen donors to enhance tar production. Compared with the L-type mode, the U-type mode resulted in better synergies between NMH and CS volatiles, contributing to higher tar yield of 44.68 wt%. In addition, the volatile synergies were conductive to the formation of aliphatic chain radicals in char, methyl-containing compounds, and 3–4 ring aromatic compounds in tar. This research will guide the optimization of tar production and co-pyrolysis technique exploitation.

Here, typical relaxor ferroelectric Ba2Bi4Ti5O18 (BBT) and antiferroelectric PbZrO3 (PZ) were selected to form BBT/PZ/BBT composite films for high energy storage performance. The composite films exhibit relaxor antiferroelectric behavior at 1000 kV/cm. A large recoverable energy storage density (Wrec) of 66.7 J/cm3 and efficiency (η) of 65.6% were achieved at 2500 kV/cm in BBT/PZ/BBT composite films. Additionally, the variation of Wrec and η was less than 4% after 5 × 107 charge-discharge cycles at 1000 kV/cm. What’s more, the energy storage performance of composite films is stable under the temperature range from 20 °C to 160 °C and frequency range from 500 Hz to 2000 Hz.

The van der Waals (vdW) interactions of n-alkanethiols (ATs) adsorbed on planar Au(111) and Au(100) surfaces and curved Au nanoparticles of different diameters are reported. By means of electrochemical measurements and molecular dynamic calculations, the increase in the average geometrical curvature of the surface influences the global interactions, that is, decreasing vdW interactions between neighboring molecules. Small NPs do not present the same electrochemical behavior as planar surfaces. The transition between nanoparticle to flat surface electrochemical response is estimated to occur at a circa 13–20 nm diameter range. Fil: Cometto, Fernando Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina. Ecole Polytechnique Federale de Lausanne; Suiza Fil: Luo, Zhi. Ecole Polytechnique Federale de Lausanne; Suiza Fil: Zhao, Shun. Ecole Polytechnique Federale de Lausanne; Suiza Fil: Olmos Asar, Jimena Anahí. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina Fil: Mariscal, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones en Físico-química de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Investigaciones en Físico-química de Córdoba; Argentina Fil: Ong, Quy. Ecole Polytechnique Federale de Lausanne; Suiza Fil: Kern, Klaus. Max-Planck-Institut für Festkörperforschung; Alemania. Ecole Polytechnique Federale de Lausanne; Suiza Fil: Stellacci, Francesco. Ecole Polytechnique Federale de Lausanne; Suiza Fil: Lingenfelder, Magalí Alejandra. Ecole Polytechnique Federale de Lausanne; Suiza

The high temperature requirement A (HtrA) proteases are oligomeric serine proteases essential for protein quality control. HtrA homolog A (HhoA) from the photosynthetic cyanobacterium Synechocystis sp. PCC 6803 assembles into a proteolytically active hexamer. Herein, we present the crystal structure of the hexameric HhoA in complex with the copurified peptide. Our data indicate the presence of three methionines in close proximity to the peptide-binding site of the PDZ domain. Unexpectedly, we observed that a zinc ion is accommodated within the central channel formed by a HhoA trimer. However, neither calcium nor magnesium showed affinity for HhoA. The role of the zinc ion in HhoA was tested in an in vitro proteolytic assay against the nonspecific substrate β-casein and was found to be inhibitory. Our findings provide insights into the regulation of HhoA by a redox-related mechanism involving methionine residues and by zinc ion-binding within the central channel.

Coal combustion in coal-fired power plants is one of the important anthropogenic NOx sources, especially in China. Many policies and methods aiming at reducing pollutants, such as increasing installed capacity and installing air pollution control devices (APCDs), especially selective catalytic reduction (SCR) units, could alter NOx emission characteristics (NOx concentration, NO2/NOx ratio, and NOx emission factor). This study reported the NOx characteristics of eight new coal-fired power-generating units with different boiler patterns, installed capacities, operating loads, and coal types. The results showed that larger units produced less NOx, and anthracite combustion generated more NOx than bitumite and lignite combustion. During formation, the NOx emission factors varied from 1.81 to 6.14 g/kg, much lower than those of older units at similar scales. This implies that NOx emissions of current and future units could be overestimated if they are based on outdated emission factors. In addition, APCDs, especially SCR, greatly decreased NOx emissions, but increased NO2/NOx ratios. Regardless, the NO2/NOx ratios were lower than 5%, in accordance with the guidelines and supporting the current method for calculating NOx emissions from coal-fired power plants that ignore NO2.

Extraction of retinal vessels from fundus images is one of the basic steps for diagnosis of diabetic retinopathy. Although some scholars have proposed several segmentation methods, this segmentation is still challenging due to differences in retinal vascular network and image quality. At present, the main challenges of retinal vascular segmentation are noise (due to uneven light) and capillaries. Due to the high complexity of retinal vascular characteristic information, the existing algorithms exists some problems such as microvascular segmentation and optic disc segmentation, We propose a network segmentation model based on fusion residual block, Attention mechanism and U-net, Firstly, the image was enhanced by limiting contrast histogram equalization. Secondly, Gamma correction is used to improve image brightness information and reduce artifact interference. Finally, AttentionResU-et segmentation model is used for segmentation. This algorithm was tested on DRIVE dataset, and its AUC reached 97.93%.

The influence of this proximity system is essentially within the stress superposition region, the stability of the new tunnel underneath the existing urban road is analyzed by strength reduction method, and the ultimate shear strain is selected as the criterion of instability of surrounding rock. By comparing the single tunnel with the adjacent system of the tunnel to the existing urban road, at a safety factor difference of 0, as a partition threshold of the influence region, the mechanical calculation models of different tunnels near the existing urban roads are established under 192 working conditions. Through multifactor analysis of the calculation results, at the same time, considering that the influence of new tunnel excavation on existing urban roads is mainly longitudinal effect, and the influence of existing urban roads on new tunnels is mainly transverse effect, the influence range diagram of longitudinal and transverse effect is established, which provides reference for similar projects in the future.

Based on deep learning, the early warning system for abnormal temperature of pigs can identify suspicious diseased pigs in advance, avoid group death and reduce the loss of a large number of diseases. It includes multi-domain cross-fusion, combining artificial intelligence machine vision image processing technology (CV), Internet of Things information technology (LOT), software engineering technology (STT), and traditional breeding technology (TFT). The CV technology is used for the hip identification and tracking of individual pigs. The LOT technology completes the real-time capture and monitoring of the body temperature of the individual pigs. The STT technology is used to send and receive network messages and implement an early warning system. Combining CV technology, LOT technology, STT technology and STT technology, a solution for automatic monitoring and real-time warning of the temperature measurement area of breeding pigs is proposed and implemented. The paper summarizes the technology used and details the design and implementation process of the system.

Essential hypertension (EH) is a multifactorial disease. Interferon-γ (IFN-γ) plays an important role in the onset of EH through cytokine-mediated systemic inflammatory responses. We aimed to determine whether the methylation status of the IFN-γ gene (IFNG) promoter is involved in the pathogenesis of EH. Six copies of CpG dinucleotides are distributed between 3,203 bp and 3,121 bp upstream from the transcription initiation site of IFNG, termed CpG1 to CpG6 in the 5'-to-3' direction. We recruited 96 patients with EH and 96 sex- and age-matched healthy subjects as controls. Using bisulfate pyrosequencing datasets, we analyzed the methylation status of the six CpG sites and thus found that CpG5 was consistently methylated in all of the 96 EH patients and 96 control subjects. Among the remaining five CpG sites, there was no significant difference in the methylation levels of CpG4 and CpG6 between the two groups. By contrast, CpG1 (P = 0.003) and CpG3 (P = 5.87 × 10

In order to improve the structural anti-impact strength for family refuge chamber, an arched transition capsule is designed. The structural static analysis for the shell structure under the pressure of 0.1MPa and the modal analysis of structural dynamic are calculated, then goal driven optimization analysis is used for main parameters affected the shell strength which is designed by the collaborative optimization function of Pro/E and Workbench, the parameters sensitivity curve and the candidate optimum design point are obtained. The optimization results show that under the minimum change of the module’s mass, shell’s maximum equivalent stress and total deformation decreases by 32.56% and 44.23% respectively, provide theory support for the capsule manufacturer.

Paeoniflorin is one of the active ingredients of the commonly used herbal medicine derived from Paeonia, which exhibits anticancer properties. MicroRNA-16 (miR-16) is upregulated in CD133(-) cells, but downregulated in CD133(+) cells from glioma tissue. Matrix metalloproteinase-9 (MMP-9) expression in glioma tissue samples is significantly higher than that in healthy brain tissue samples. Therefore, miR-16 and MMP-9 expression may be associated with glioma pathogenesis. In the present study, the effects of paeoniflorin on glioma were analyzed. U87 cells were treated with paeoniflorin at 0, 5, 10 and 20 μΜ concentrations. The results suggested that paeoniflorin inhibited U87 cell proliferation and accelerated cell apoptosis. In the present study paeoniflorin treatment increased miR-16 expression and reduced MMP-9 protein expression in U87 cells. Additionally, the results of the present study suggested that miR-16 may regulate MMP-9 expression in miR-16-transfected U87 cells. Furthermore, anti-miR-16 antibodies were used in order to investigate the apoptotic effects of paeoniflorin on U87 cells. The results demonstrated that paeoniflorin inhibits proliferation and induces apoptosis of human glial cells, via miR-16 upregulation and MMP-9 downregulation.