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Ball screw is widely used in the engineering field, and accurate estimation of their state is crucial for the reliability of system operation. However, existing methods often overlook the time series characteristics and spatial correlation of vibration signals, unable to provide complete degradation information and divide the degradation process, resulting in limited prediction accuracy. Therefore, a state estimation method for ball screw based on Convolutional Neural Networks (CNN) and Long Short-Term Memory Neural Networks (LSTM) is proposed. An experiment of ball screw transmission equipment was conducted to collect vibration signals throughout the entire life cycle and verify the proposed method. Firstly, the frequency domain amplitude signal of the transformed ball screw is normalized to eliminate scale differences, which serves as the input for CNN feature extraction. Then, these deep features are input into the LSTM network to capture the fault evolution patterns that reveal the degradation of ball screw performance, and achieve accurate estimation of ball screw state. The final prediction accuracy was 97.87%, verifying the effectiveness of the proposed method.

Emergency diesel engine is the last safety barrier for nuclear power plants. Nuclear safety criteria require that it can start up to rated speed（ such as 1 500 r/min） within 10 seconds in an emergency and have loading conditions,so its startup performance is particularly important. During the start-up process,the power of high-pressure air is a key factor for success.In this paper,a vibration-based method by analyzing high-pressure air（ domestic units are generally 40 bar·g） power to evaluate starting performance is presented. The large amount of monitoring data obtained indicates that high-pressure air is rapidly charged into the cylinder to generate high-frequency（ approximately 11 kHz） gas exciting impact,and the impact phase will continue to shift backward with increasing speed. Firstly,the Teager energy operator and an adaptive threshold impact location method were used to automatically capture the high pressure gas impact area of each cylinder in each cycle of the start-up phase. Secondly,the energy of the local impact envelope was extracted to characterize the function of the high-pressure air. Finally,the gray evaluation method carried out a comprehensive assessment. The actual test result verifies the effectiveness of this method and has the value of popularization and application.

Reciprocating compressor stepless capacity control system in the petrochemical industry are widely used, unloading device as a key component of the system actuator, the action characteristics of the relationship between the quality of the system directly related to the efficiency of the air intake system and compressor valve life. In this paper, ANSYS/Ls-dyna explicit dynamics software is used to simulate the automatic opening process of the intake valve at the rated speed of the compressor. The displacement of the valve is measured by the eddy current displacement sensor. On the basis of this, the operation of the unloader under different oil supply pressure and different ejection time is simulated, the ideal hydraulic ejection force and the ejection phase are determined. It is concluded that the reasonable action of the unloader can effectively relieve the vibration of the valve plate and improve the force of the valve.

After the gear fault occurs， the vibration signal collected includes fault impact， deterministic meshing signal and noise signal， and these signals are also affected by the transmission path， which makes the gear fault feature extraction difficult. Cepstrum analysis is a common method for gear fault diagnosis. It can display the periodic components in the sideband as a single line， which is helpful for fault diagnosis. However， when the fault characteristic signal is weak， the fault characteristics in the cepstrum are not obvious. For this， feature-enhanced cepstrum analysis method is proposed. Three feature enhancement methods minimum entropy deconvolution， autoregressive linear prediction and wavelet de-noising are used to enhance the fault impact characteristics of gear vibration signals， and then the cepstrum is used to extract the fault features. The effectiveness of the proposed method is verified by experiment.

In this paper,simulation and experimental studies of typical wear fault of the reciprocating machinery connecting rod big end bearing,explore the influence of the wear and tear on the lubrication parameters of the connecting rod big end bearing. Based on the Reynolds equation,by simulating different bearing wear situations: different widths,different depths and different positions, a comprehensive analysis of the associations between the degrees of wear of bearing and lubrication parameters,in particular the bearing temperatures. By installing the temperature sensor in the test unit connecting rod bearings,connecting rod temperature is on-line monitored,and the variation rules of temperature of the bearing under the state of wear are experimental confirmed.

The model of diesel gear transmission system（ crank,crank gear,the intermediate gear,camshaft gear and camshaft） in an inline six-cylinder diesel engine is established to study. The multi-body dynamics simulation software ADAMS is used to simulate the frequency change of camshaft gear in normal and the fault of broken teeth,camshaft axial moving and intermediate gear radial vibration. Then the results are compared with the experimental data of gear broken tooth of diesel engine and comparison result shows that,when camshaft gear break tooth,each order frequency will increase,especially the fundamental frequency,three frequency multiplication,and four frequency multiplication. The phenomenon is identical with the actual failure case. When camshaft axial moving and intermediate gear radial vibration,each order frequency will increase significantly,especially the fundamental frequency,three frequency multiplication,and four frequency multiplication. Therefore,both cases may have resulted gear does not run smoothly,resulting in broken teeth failure.

A finite element analysis of gear broken tooth fault of diesel engine based on the ANSYS Workbench is presented. The model of a pair of involute helical gear which is built by Pro / E parametric modeling is imported into ANSYS Workbench transient dynamics analysis module and the finite element analysis results under three conditions including normal gear,half- tooth broken gear and full- tooth broken gear are obtained.Then the results are compared with the experimental vibration data of gear broken tooth fault of diesel engine and comparison result shows that,during the operation of involute helical gear of diesel engine,the contact stress changes periodically and fluctuates obviously,clearly impact phenomenon exists and with the increasing of the degree of gear tooth damage,the impact force of the gear increase distinctly. The frequency of the maximum amplitude is the ignition frequency,the amplitude of rotating frequency corresponding to fault vibration is significantly greater than the normal rotating gear.

Reciprocating compressor has many moving and damageable parts in which valve is the most frequently damaged component. A mathematical model of the valve movement was established according to its structure and motion characteristics.MATLAB and ANSYS software were used to study the transient motion law and the dynamic stress distribution of mesh valve.Then the impact of spring stiffness and transition arc on valve’s stress distribution was discussed. The results show that the stress generated by deformation is much greater than the impact stress. Maximum elastic deformation occurs in two thin elastic arms in which maximum equivalent stress generated. Changing the spring stiffness and the curvature of the transition arc can effectively reduce the stress and extend the life of the mesh valve. The results of the analysis have important theoretical significance for valve design optimization and the improvement of valve life.

Abstract Introduction Previous studies suggested that estrogen receptor alpha (ERα) plays an important role in the chemoresistance of breast cancers. However, large random trials failed to demonstrate any benefit of the concurrent estrogen antagonist tamoxifen on the chemotherapy efficacy. Thus, in the present study, the importance of the role of ERα in the chemoresistance of breast cancer cells was investigated. Methods The ERα-transfected Bcap37 cells and natural ERα-positive T47D breast cancer cells were treated using chemotherapeutic agents with or without 17-beta estradiol (E2) pretreatment. Their viabilities were assessed using 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide assays. The dead cell rates were determined using propidium iodide dye exclusion tests, and the expression levels of Bcl-2 and Bax were detected through Western blot analysis. The effects of E2 on the growth of breast cancer cells were also determined via cell growth curve and cell cycle analysis. Results ERα activation by E2 increased the sensitivity of natural ERα-positive T47D breast cancer cells to chemotherapeutic agents. However, the increase in ERα expression in ERα-negative Bcap37 breast cancer cells also significantly increased their resistance. These phenomena cannot be explained by asserting that ERα mediated the chemoresistance of breast cancer cells by regulating the expression of Bcl-2 and Bax. Our findings show that ERα activation upregulated the expression of Bcl-2 in natural ERα-positive T47D breast cancer cells, whereas ERα activation by E2 downregulated and upregulated the Bcl-2 and Bax expression levels, respectively, in ERα-transfected Bcap37 cells. This phenomenon was due to the influence of ERα on the growth of breast cancer cells. Specifically, ERα activation enhanced the growth of natural ERα-positive breast cancer cells and thus increased their sensitivity to chemotherapeutic agents. However, ERα activation also inhibited the growth of ERα-transfected Bcap37 cells and increased the resistance of cancer cells to chemotherapeutic agents. Chemoresistance of ERα-transfected Bcap37 cells was only due to the specific growth inhibition by E2, which is not applicable to common ERα-positive breast cancer cells. Conclusions Although ERα was associated with chemoresistance of breast cancers, ERα itself did not mediate this resistance process.

Abstract Background Preoperative chemotherapy (PCT) has become the standard of care in locally advanced breast cancer. The identification of patient-specific tumor characteristics that can improve the ability to predict response to therapy would help optimize treatment, improve treatment outcomes, and avoid unnecessary exposure to potential toxicities. This study is to determine whether selected biomarkers could predict pathologic response (PR) of breast tumors to three different PCT regimens, and to identify a subset of patients who would benefit from a given type of treatment. Methods 118 patients with primary breast tumor were identified and three PCT regimens including DEC (docetaxel+epirubicin+cyclophosphamide), VFC (vinorelbine/vincristine+5-fluorouracil+cyclophosphamide) and EFC (epirubicin+5-fluorouracil+cyclophosphamide) were investigated. Expression of steroid receptors, HER2, P-gp, MRP, GST-pi and Topo-II was evaluated by immunohistochemical scoring on tumor tissues obtained before and after PCT. The PR of breast carcinoma was graded according to Sataloff's classification. Chi square test, logistic regression and Cochran-Mantel-Haenszel assay were performed to determine the association between biomarkers and PR, as well as the effectiveness of each regimen on induction of PR. Results There was a clear-cut correlation between the expression of ER and decreased PR to PCT in all three different regimens (p < 0.05). HER2 expression is significantly associated with increased PR in DEC regimen (p < 0.05), but not predictive for PR in EFC and VFC groups. No significant correlation was found between biomarkers PgR, Topo-II, P-gp, MRP or GST-pi and PR to any tested PCT regimen. After adjusted by a stratification variable of ER or HER2, DEC regimen was more effective in inducing PR in comparison with VFC and EFC regimens. Conclusion ER is an independent predictive factor for PR to PCT regimens including DEC, VFC and EFC in primary breast tumors, while HER2 is only predictive for DEC regimen. Expression of PgR, Topo-II, P-gp, MRP and GST-pi are not predictive for PR to any PCT regimens investigated. Results obtained in this clinical study may be helpful for the selection of appropriate treatments for breast cancer patients.

SIPR[alpha] on macrophages binds with CD47 to resist proengulfment signals, but how the downstream signal of SIPR[alpha] controls tumor-infiltrating macrophages (TIMs) is still poorly clarified. Here, we report that the CD47/signal regulatory protein [alpha] (SIRP[alpha]) axis requires the deneddylation of tyrosine phosphatase SHP2. Mechanistically, Src homology region 2-containing protein tyrosine phosphatase 2 (SHP2) was constitutively neddylated on K358 and K364 sites; thus, its autoinhibited conformation was maintained. In response to CD47-liganded SIRP[alpha], SHP2 was deneddylated by sentrin-specific protease 8 (SENP8), which led to the dephosphorylation of relevant substrates at the phagocytic cup and subsequent inhibition of macrophage phagocytosis. Furthermore, neddylation inactivated myeloid-SHP2 and greatly boosted the efficacy of colorectal cancer (CRC) immunotherapy. Importantly, we observed that supplementation with SHP2 allosteric inhibitors sensitized immune treatment-resistant CRC to immunotherapy. Our results emphasize that the CRC subtype that is unresponsive to immunotherapy relies on SIRP[[alpha].sup.hi] [SHP2.sup.hi][NEDD8.sup.lo] TIMs and highlight the need to further explore the strategy of SHP2 targeting in CRC therapy., Introduction Reprogramming the immunosuppressive tumor microenvironment is vital in optimal tumor immunotherapy. Immune checkpoint inhibitors that target tumor-infiltrating lymphocytes have brought unprecedented success in the clinical efficacy of malignant tumor [...]

Background: Diagnosis of Crohn's disease is challenging. This study aims to compare the histological features of Crohn's disease and non-Crohn's disease (other intestinal inflammatory diseases) in surgical specimens to identify a set of histologic features distinguishing Crohn's disease from non-Crohn's disease. Methods: Patients with Crohn's disease (N = 171) and patients with non-Crohn's disease (N = 215) diagnosed between 2010 and 2015 who had surgical bowel resection were identified. The frequency of histological features in surgical resection specimens was compared between these two groups. Results: Univariate analysis revealed that transmural inflammation, subserosal lymphoid aggregates, fissures or sinus-like structures, granulomas or granuloma-like nodules, abnormalities of the enteric nervous system, and mucosa structure alterations (muscularis mucosa thickening or mucosal atrophy with pseudopyloric gland metaplasia) were more frequent in Crohn's disease than non-Crohn's disease cases (p < 0.001 for all). Some of the above histologic features were further grouped as chronic inflammatory change which includes granulomas or granuloma-like nodules, lymphoid aggregates in the muscularis propria or subserosa, fissures or sinus-like structures, and architectural abnormality which is defined as the presence of abnormal enteric nervous system and/or mucosa structural alterations (muscularis mucosa thickening or mucosal atrophy with pseudopyloric gland metaplasia). A combination of transmural inflammation, chronic inflammatory change, and architectural abnormality had a sensitivity of 92.4% and a specificity of 97.7% for Crohn's disease. Conclusions: In surgical bowel resection specimens, a combination of transmural inflammation, chronic inflammatory change, and architectural abnormality help diagnose Crohn's disease. [ABSTRACT FROM AUTHOR]