Rolling bearing fault identification using multilayer deep learning convolutional neural network

The vibration signal of rolling bearing is usually complex and the useful fault information is hidden in the background noise, therefore, it is a challenge to identify rolling bearing faults from the complex vibration environment. In this paper, a novel multilayer deep learning convolutional neural network (CNN) method to identify rolling bearing fault is proposed. Firstly, in order to avoid the influence of different characteristics of the input data on the identification accuracy, a normalization preprocessing method is applied to preprocess the vibration signals of rolling bearings. Secondly, a multilayer CNN based on deep learning is designed in this paper to improve the fault identification accuracy of rolling bearing. Simulation data and experimental data analysis results show that the proposed method has better performance than SVM method and ANN method without any manual feature extractor design

Pentyl (E)-3-(3,4-dihy­droxy­phen­yl)acrylate

In the mol­ecule of the title compound, C14H18O4, the C=C double bond is in an E configuration. The mol­ecule is almost planar (r.m.s. deviation of all non-H atoms = 0.04 Å). An intra­molecular O—H⋯O hydrogen bond occurs. In the crystal, inter­molecular O—H⋯O inter­actions link the mol­ecules into ribbons extending in [110]

Integrating IPAT and CLUMondo Models to Assess the Impact of Carbon Peak on Land Use

China’s growth plans include a carbon emission peak policy, which is a restriction that indirectly impacts land use structure. In this study, we simulate different paths for achieving policy objectives, and explore the linkages between those paths and land use change. The IPAT model was used to simulate the carbon emissions generated from a natural development scenario, an ideal policy scenario, and a retributive carbon emission scenario in China from 2020 to 2030. The simulation results were incorporated into the CLUMondo model as a demand driver to simulate the land use change in 2030. The results show that carbon emission peak policy can somewhat reduce carbon emissions and increase building land in a regulated way. However, the policy may also lead to a short-term surge in carbon emissions, a reactive expansion of arable land and building land. This may reduce losses in economic development when carbon emissions are limited, but does not achieve the integration of social, economic, and ecological goals. This study links the carbon emission peak policy with land use change and provides a fresh perspective on the Chinese government’s carbon reduction policy

Identification of immunodiagnostic blood biomarkers associated with spinal cord injury severity

Blood always shows some immune changes after spinal cord injury (SCI), and detection of such changes in blood may be helpful for diagnosis and treatment of SCI. However, studies to date on blood immune changes after SCI in humans are not comprehensive. Therefore, to obtain the characteristics of blood immune changes and immunodiagnostic blood biomarkers of SCI and its different grades, a human blood transcriptome sequencing dataset was downloaded and analyzed to obtain differentially expressed immune-related genes (DEIGs), related functions and signaling pathways related to SCI and its various grades. Characteristic biomarkers of SCI and its different grades were identified by using weighted gene coexpression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) logistic regression. Expression of biomarkers was verified through experiments. The area under the curve (AUC) of biomarkers was calculated to evaluate their diagnostic value, and differences in immune cell content were examined. In this study, 17 kinds of immune cells with different contents between the SCI group and healthy control (HC) group were identified, with 7 immune cell types being significantly increased. Differences in the content of immune cells between different grades of SCI and the HC group were also discovered. DEIGs were identified, with alteration in some immune-related signaling pathways, vascular endothelial growth factor signaling pathways, and axon guidance signaling pathways. The SCI biomarkers identified and those of American Spinal Injury Society Impairment Scale (AIS) A and AIS D of SCI have certain diagnostic sensitivity. Analysis of the correlation of immune cells and biomarkers showed that biomarkers of SCI, AIS A grade and AIS D grade correlated positively or negatively with some immune cells. CKLF, EDNRB, FCER1G, SORT1, and TNFSF13B can be used as immune biomarkers for SCI. Additionally, GDF11and HSPA1L can be used as biomarkers of SCI AIS A grade; PRKCA and CMTM2 can be used as biomarkers of the SCI AIS D grade. Detecting expression of these putative biomarkers and changes in related immune cells may be helpful for predicting the severity of SCI

Effect of mechanical stimulation on tissue heterotopic ossification: an in vivo experimental study

Background: Heterotopic ossification of tendons and ligaments (HOTL) is a common clinical condition characterized by the absence of discernible features and a lack of effective treatment. In vitro experiments have demonstrated that mechanical stimulation can induce cell differentiation toward osteogenesis, thereby promoting heterotopic ossification. Currently, there are few experimental designs aimed at inducing ligament stretching in mice, and the mechanism of heterotopic ossification may not entirely mirror that observed in clinical cases. Therefore, there is an urgent imperative to develop a novel and feasible animal model.Methods: In this study, all the Enpp1 gene deficiency mice (a mouse model with heterotopic ossification of multiple ligaments) were divided into three groups: the control group, the spinal brake group, and the hyperactive group (treadmill training group). An external spinal fixation device was designed to restrict mice’s spinal flexion and extension at 6 weeks of age. The brace was adjusted weekly according to the changes in the size of the mice. Additionally, treadmill training was used to increase activity in the spinal ligaments and Achilles tendons of the mice. Micro-CT scanning and HE staining were performed at 12, 20, and 28 W to evaluate the degree of ossification in the spinal ligament and Achilles tendon. What’s more, As one of the mechanical stimulation transduction signals, YAP plays a crucial role in promoting osteogenic differentiation of cells. Immunofluorescence was utilized to assess YAP expression levels for the purpose of determining the extent of mechanical stimulation in tissues.Results: Our findings showed that a few ossification lesions were detected behind the vertebral space of mice at 8 weeks of age. Spinal immobilization effectively restricts the flexion and extension of cervical and thoracic vertebrae in mice, delaying spinal ligament ossification and reducing chronic secondary spinal cord injury. Running exercises not only enhance the ossification area of the posterior longitudinal ligament (PLL) and Achilles tendons but also exacerbate secondary spinal cord injury. Further immunofluorescence results revealed a notable increase in YAP expression levels in tissues with severe ossification, suggesting that these tissues may be subjected to higher mechanical stimulation.Conclusion: Mechanical stimulation plays a pivotal role in the process of heterotopic ossification in tissues. Our study provided valid animal models to further explore the pathological mechanism of mechanical stimulation in HOTL development

RIG-I Mediates the Co-Induction of Tumor Necrosis Factor and Type I Interferon Elicited by Myxoma Virus in Primary Human Macrophages

The sensing of pathogen infection and subsequent triggering of innate immunity are key to controlling zoonotic infections. Myxoma virus (MV) is a cytoplasmic DNA poxvirus that in nature infects only rabbits. Our previous studies have shown that MV infection of primary mouse cells is restricted by virus-induced type I interferon (IFN). However, little is known about the innate sensor(s) involved in activating signaling pathways leading to cellular defense responses in primary human immune cells. Here, we show that the complete restriction of MV infection in the primary human fibroblasts requires both tumor necrosis factor (TNF) and type I IFN. We also demonstrate that MV infection of primary human macrophages (pHMs) activates the cytoplasmic RNA sensor called retinoic acid inducible gene I (RIG-I), which coordinately induces the production of both TNF and type I IFN. Of note, RIG-I sensing of MV infection in pHMs initiates a sustained TNF induction through the sequential involvement of the downstream IFN-regulatory factors 3 and 7 (IRF3 and IRF7). Thus, RIG-I-mediated co-induction of TNF and type I IFN by virus-infected pHMs represents a novel innate defense mechanism to restrict viral infection in human cells. These results also reveal a new regulatory mechanism for TNF induction following viral infection

S6K-STING interaction regulates cytosolic DNA-mediated activation of the transcription factor IRF3

Cytosolic DNA-mediated activation of the transcription factor IRF3 is a key event in host antiviral responses. Here we found that infection with DNA viruses induced interaction of the metabolic checkpoint kinase mTOR downstream effector and kinase S6K1 and the signaling adaptor STING in a manner dependent on the DNA sensor cGAS. We further demonstrated that the kinase domain, but not the kinase function, of S6K1 was required for the S6K1-STING interaction and that the TBK1 critically promoted this process. The formation of a tripartite S6K1-STING-TBK1 complex was necessary for the activation of IRF3, and disruption of this signaling axis impaired the early-phase expression of IRF3 target genes and the induction of T cell responses and mucosal antiviral immunity. Thus, our results have uncovered a fundamental regulatory mechanism for the activation of IRF3 in the cytosolic DNA pathway

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Research on Hierarchical Control Strategy of AC/DC Hybrid Microgrid Based on Power Coordination Control

The AC/DC hybrid microgrid has a large-scale and complex control process. It is of great significance and value to design a reasonable power coordination control strategy to maintain the power balance of the system. Based on hierarchical control, this paper designs a reasonable power coordination control strategy for AC/DC hybrid microgrid. For lower control, this paper designs a variety of control modes for each converter in different application scenarios. For the higher control, this paper analyzes the working mode of the system and designs the power coordination control strategy under the grid-connected and isolated island mode. In grid-connected operation, the DC bus voltage can be stabilized by adjusting the operation mode of the DC energy storage and the on-off of the secondary load. In isolated island operation, the DC sub-microgrid is the main microgrid, and the DC energy storage is the main power regulating equipment. This is based on the principle of “energy is in short supply in the system, DC energy storage finally discharge, energy supply exceeds demand in the system, DC energy storage gives priority to charging” of DC energy storage. By adjusting the control strategy of the micro-source, the reference power, and the on-off of the secondary load, the overall power balance is maintained. The Matlab/Simulink simulation software was used to build the AC/DC hybrid microgrid simulation model, which verified the effectiveness and stability of the proposed power coordination control strategy under various operating conditions

Optimal Advertising Budget Allocation across Markets with Different Goals and Various Constraints

Advertising budget allocation across multiple markets has drawn considerable attention in recent years. To expand previous research and fill a gap in the current literature, this study proposes two decision models for optimal budget allocation decisions across multimarkets with different goals and various constraints. In addition to the market parameters proposed by the Vidale–Wolfe model, the present study incorporates market goals and advertising objectives into budget allocation decisions. Different types of markets are defined in terms of the goal set for market share or profit. Given the characteristics of different markets, two separate decision models are developed. Model I aims to maximize sales volume given a fixed advertising budget, while model II seeks to minimize the advertising budget given a total of targeted sales volume for all the markets. Solutions to the two models are discussed, and a numerical example is provided to demonstrate how to apply the models in making budget allocation decision