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Abstract Underwater friction stir welding (UFSW) achieves reliable joining between dissimilar materials and meets the welding demand for function and properties in lightweight structures of modern engineering. A defect monitoring method based on Variational Mode Decomposition optimized by Beluga Whale Optimization and Hilbert–Huang Transform (BWO–VMD–HHT) is proposed to solve the unclear feature of AE signal in UFSW due to the aqueous medium. UFSW experiments on Al alloy and carbon fiber reinforced thermoplastic (CFRTP) are carried out with AE signals measured. The time–frequency domain features of AE signals are extracted by BWO–VMD–HHT. The experimental results show that the main frequency of the AE signal is 22.5 kHz, and surface crack defects, shallow hole defects, and deep hole defects are accompanied by the transfer phenomena of different frequency components. Then, the feature vectors are built by frequency components in the BWO–VMD–HHT spectrum and reduced by principal component analysis, including 22.5 kHz, 24 kHz, 20.6 kHz, 18.4 kHz, 17.3 kHz, and 15.6 kHz. The feature vectors are divided into the train and test sets, and the welding defect prediction model (ResNet18-attention) is built by ResNet18 and trained by feature vectors. In the test set, the ResNet18-attention is compared with the BP, SVM, and RBF. Test results show that the precision of models has improved by at least 10%, which are trained by BWO–VMD–HHT features vector. Also, ResNet18-attention has achieved an average precision of 0.906 and recognizes the category of weld defect accurately, and this method can be applied to the defect monitoring of UFSW.

Abstract To improve locomotion and operation integration, this paper presents an integrated leg-arm quadruped robot (ILQR) that has a reconfigurable joint. First, the reconfigurable joint is designed and assembled at the end of the leg-arm chain. When the robot performs a task, reconfigurable configuration and mode switching can be achieved using this joint. In contrast from traditional quadruped robots, this robot can stack in a designated area to optimize the occupied volume in a nonworking state. Kinematics modeling and dynamics modeling are established to evaluate the mechanical properties for multiple modes. All working modes of the robot are classified, which can be defined as deployable mode, locomotion mode and operation mode. Based on the stability margin and mechanical modeling, switching analysis and evaluation between each mode is carried out. Finally, the prototype experimental results verify the function realization and switching stability of multimode and provide a design method to integrate and perform multimode for quadruped robots with deployable characteristics.

Due to the complex cross-section and scale effects, surface and internal defects are prone to occur in the ultra-large-section beam blank. In this study, a coupled model of steel liquid flow and heat transfer within a 1300 × 510 × 140 mm cross-section beam blank mould was established. The results indicate that single-port SEN reduced the flow activity on the meniscus, and the three-ports SEN led to significant high temperature zones and re-melting of the solidified shell in the flange tip and web. The four-ports nozzle not only optimizes the internal flow behavior of the mould but also enhances the uniformity of temperature and solidification. The maximum circumferential difference in shell thickness under the four-ports SEN was only 8.1 mm, compared to 13.2 mm and 13.8 mm under the single-port and three-ports SEN, respectively.

ObjectiveThis study focuses on the preparation and properties of high-performance electromagnetic shielding materials for electronic equipment in marine environments. MethodsThe surface morphology, phase composition, electrical conductivity and ferromagnetic properties of the original ferrosilicochrome powder (FeSiCr) and silver-coated powder (FeSiCr@Ag) are analyzed with a scanning electron microscope, X-ray diffractometer, four probes and vibrating sample magnetometer, and a vector network analyzer is used to test the S parameters of the samples. A salt spray test chamber is used to simulate the corrosion behavior of the coating under marine environment conditions and observe its macro and micro morphology. Meanwhile, an electrochemical workstation is used to monitor the corrosion behavior of the coating in a mass fraction of 3.5% NaCl solution and study its corrosion mechanism. ResultsThe results show that the silver plating layer is compact and complete with the increase of the silver nitrate (AgNO3) addition. After electroless silver plating, the conductivity can reach 586.79 S/cm and the X-band shielding efficiency reaches 80 dB. After 96 h of accelerated corrosion in a humid heat and high salt spray environment, the surface of the resin coating prepared by FeSiCr@Ag shows no corrosion phenomenon. The self-corrosion potential of the coating before and after electroless silver plating is −0.4 V and −0.09 V respectively, indicating that the penetration rate of the corrosive medium into the coating slows down after silver plating, and a good corrosion inhibition effect is achieved.ConclusionsThe modified FeSiCr@Ag material has highly efficient electromagnetic shielding performance and good corrosion resistance properties.

The utilization of recycled coarse aggregate derived from construction and demolition waste (CDW) in the construction of road cement stabilized macadam base could effectively alleviate the shortage of natural sand and aggregate resources. To explore the repairing effect of microbial induced carbonate precipitation (MICP) on recycled cement stabilized macadam (RCSM), the physical, mechanical, and microscopic properties of recycled concrete aggregate under different precipitation precursor concentrations were researched in this paper. The mechanical properties of RCSM with varying contents of recycled concrete aggregate were analyzed before and after repairing. Based on scanning electron microscopy (SEM) and mercury intrusion porosimeter (MIP) tests, the microstructure and pore structure parameters of recycled concrete aggregate were explored, and the repair mechanism of MICP on RCSM was revealed via the performance analysis of recycled concrete aggregate and RCSM. The results show that MICP could effectively reduce the water absorption of recycled concrete aggregates, while simultaneously enhancing its apparent density and crushing resistance. In a certain range, the higher the concentration of the precipitation precursor, the better the repairing effect on the performances of recycled concrete aggregates. However, while the concentration of urea or calcium source concentration exceeding 1.0 mol/L, the activity of urease would start to be inhibited. The unconfined compressive strength of RCSM after MICP repairing could be increased by 22.7 % with a maximum extent compared with that before repair, while the maximum increase of indirect tension strength and flexural tensile strength was 15 % and 8.2 %, respectively. The biological CaCO3 generated by MICP reaction could fill the micro-cracks and pores of the recycled concrete aggregate efficaciously. Besides, it could also optimize the pore parameters and pore size distribution parameters, and enhance the adhesive strength of interfacial transition zone (ITZ) between cement and recycled concrete aggregates, which could improve the mechanical properties of RCSM.

Chylous fistula is a common postoperative complication for the head and neck surgery, thoracic and upper gastrointestinal surgery, but it rarely happens after breast surgery. There are few reports of chylous fistula after breast benign tumor resection according to literature retrieval. To our acknowledgement, this is the first case report of chylous fistula after breast fibroadenoma resection.

Fatigue limit assessment methodologies based on the thermography technique are comprehensively studied in this work. Three fundamental indicators pertaining to temperature increase, intrinsic energy dissipation, and thermodynamic entropy are discussed in sequence. The main train of thought of thermo-based research is outlined. The main objective of this paper is, on the one hand, to describe some works that have been accomplished in this field and, on the other hand, to present further potential for future studies involving fatigue behaviors and thermography approaches.

Abstract Continuum robots actuated by flexible rods have large potential applications, such as detection and operation tasks in confined environments, since the push and pull actuation of flexible rods withstand tension and compressive force, and increase the structure’s rigidity. In this paper, a generalized kinetostatics model for multi-module and multi-segment continuum robots considering the effect of friction based on the Cosserat rod theory is established. Then, the model is applied to a two-module rod-driven continuum robot with winding ropes to analyze its deformation and load characteristics. Four different in-plane configurations under the external load term as S1, S2, C1, and C2 are defined. Taking a bending plane as an example, the tip deformation along the x-axis of these shapes is simulated and compared, which shows that the load capacity of C1 and C2 is generally larger than that of S1 and S2. Furthermore, the deformation experiments and simulations show that the maximum error ratio without external loads relative to the total length is no more than 3%, and it is no more than 4.7% under the external load. The established kinetostatics model is proven sufficient to accurately analyze the rod-driven continuum robot with the consideration of internal friction.

Abstract As a weak link between aggregate and mortar in concrete, interfacial transition zone (ITZ) usually plays a key role in concrete fracture. To investigate the tensile fracture property of concrete affected by the mechanical properties of ITZ numerically, the geometrical models of heterogeneous concrete were established with the parameterization modeling. They include three phases, namely, mortar, ITZ, and randomly distributed aggregates with distinct sizes and orientations. The cracking behaviors of mortar and ITZ were characterized by the bilinear cohesive zone constitutive model. Based on the experiments, the mechanical properties of ITZ were mediated by changing the water–cement ratio of mortar, the aggregate surface roughness and the content of silica fume in interfacial agent. A series of numerical simulations were conducted on the concrete models in tension after the numerical modeling method was validated. The macroscopic tensile fracture properties of concrete were quantitatively connected with some microscopic variables, including the water–cement ratio of mortar, the aggregate surface roughness and the silica fume content in interfacial agent. It was found that the tensile fracture properties of concrete have negative linear correlations with the water–cement ratio of mortar, while the effects of the aggregate surface roughness and the silica fume content in interfacial agent are very complex. The tensile fracture mechanical properties of concrete have a bilinear relationship with the aggregate surface roughness and an approximate quadratic parabola relationship with the content of silica fume in the interfacial agent. This study is beneficial to improve the fracture resistance of concrete by some interface handling measures.

Accurate prediction of the crack sensitive temperature region and phase fractions variation of slabs during continuous cooling is an important guide to avoid cracks and effectively control the quality. Based on finite number of measurements, at different cooling rates of the continuous casting process, a prediction model for characteristic temperatures of austenite decomposition, the variation of phase fractions with temperature, the crack sensitive temperature regions, and the final microstructural compositions of casting slabs at different cooling rates has been established and evaluated the accuracy. The results show that austenite decomposition temperature range moves toward the low temperature region as cooling rate increases, and the independent peak of ferrite transition become weaker. The characteristic temperatures of austenite decomposition can be quantitatively calculated by TC(CR) = A−exp(B + C/CR) at different cooling rates, which the maximum relative error for experimental steels is −2.2%. The ferrite and pearlite phase fractions increases with decreasing temperature during continuous casting cooling, which means that the ability of the billet to resist deformation and external force changes. Meanwhile, the final ferrite content of slabs for Steel B and Steel C at different cooling rates are 83.24620−exp(2.59364–13.72283/CR) and 85.07143−exp(1.71320–15.82244/CR), respectively. The crack sensitive temperature region Ae3 ∼ Tα40%(CR) calculated by the prediction model is in good agreement with the low ductility zone measured by experiment. Moreover, the critical temperatures Tα40%(CR) of the crack sensitive temperature regions are 890.35731−exp(2.99719–20.67781/CR), 745.87462−exp(4.83056–44.18511/CR) and 729.46168−exp(2.96621–12.21949/CR) for three experimental steels under different cooling rates.

Abstract Background Genes related to the SWItch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complex are frequently mutated across cancers. SWI/SNF-mutant tumors are vulnerable to synthetic lethal inhibitors. However, the landscape of SWI/SNF mutations and their associations with tumor mutational burden (TMB), microsatellite instability (MSI) status, and response to immune checkpoint inhibitors (ICIs) have not been elucidated in large real-world Chinese patient cohorts. Methods The mutational rates and variation types of six SWI/SNF complex genes (ARID1A, ARID1B, ARID2, SMARCA4, SMARCB1, and PBRM1) were analyzed retrospectively by integrating next-generation sequencing data of 4591 cases covering 18 cancer types. Thereafter, characteristics of SWI/SNF mutations were depicted and the TMB and MSI status and therapeutic effects of ICIs in the SWI/SNF-mutant and SWI/SNF-non-mutant groups were compared. Results SWI/SNF mutations were observed in 21.8% of tumors. Endometrial (54.1%), gallbladder and biliary tract (43.4%), and gastric (33.9%) cancers exhibited remarkably higher SWI/SNF mutational rates than other malignancies. Further, ARID1A was the most frequently mutated SWI/SNF gene, and ARID1A D1850fs was identified as relatively crucial. The TMB value, TMB-high (TMB-H), and MSI-high (MSI-H) proportions corresponding to SWI/SNF-mutant cancers were significantly higher than those corresponding to SWI/SNF-non-mutant cancers (25.8 vs. 5.6 mutations/Mb, 44.3% vs. 10.3%, and 16.0% vs. 0.9%, respectively; all p

Abstract Neutrophil extracellular traps (NETs) has been demonstrated to regulate the metastasis of breast cancer. In this study, we showed that de novo cholesterol biosynthesis induced by ASPP2 depletion in mouse breast cancer cell 4T1 and human breast cancer cell MDA-MB-231 promoted NETs formation in vitro, as well as in lung metastases in mice intravenously injected with ASPP2-deficient 4T1 cells. Simvastatin and berberine (BBR), cholesterol synthesis inhibitors, efficiently blocked ASPP2-depletion induced NETs formation. Cholesterol biosynthesis greatly enhanced Coiled-coil domain containing protein 25 (CCDC25) expression on cancer cells as well as in lung metastases. CCDC25 expression was co-localized with caveolin-1, a lipid raft molecule, and was damped by inhibitor of lipid rafts formation. Our data suggest that cholesterol biosynthesis promotes CCDC25 expression in a lipid raft-dependent manner. Clinically, the expression of CCDC25 was positively correlated with the expression of 3-hydroxy-3-methylglutaryl-CoAreductase (HMRCG), and citrullinated histone H3 (H3cit), in tissues from breast cancer patients. High expression of CCDC25 and HMGCR was related with worse prognosis in breast cancer patients. In conclusion, our study explores a novel mechanism for de novo cholesterol biosynthesis in the regulation of CCDC25 expression, NETs formation and breast cancer metastasis. Targeting cholesterol biosynthesis may be promising therapeutic strategies to treat breast cancer metastasis.

Mastering the variations in the stability of a polarization vortex is fundamental for the development of ferroelectric devices based on polarization vortex domain structures. Some phase field simulations were conducted on PbTiO3 nanofilms with an initial polarization vortex under uniaxial tension or compression to investigate the conditions of vortex instability and the effects of aspect ratio of nanofilms and temperature on them. The instability of a polarization vortex is strongly dependent on aspect ratio and temperature. The critical compressive stress increases with decreasing aspect ratio under the action of compressive stress. However, the critical tensile stress first decreases and then increases with decreasing aspect ratio, then continues to decrease. There are two inflection points in the curve. In addition, an elevated temperature makes both the critical tensile and compressive stresses decline, and will also cause the aspect ratio corresponding to the inflection point to decrease. These are very important for the design of promising nano-ferroelectric devices based on polarization vortices to improve their performance while maintaining storage density.

Abstract Background The aim of this study was to draw a comprehensive mutational landscape of nasopharyngeal carcinoma (NPC) tumors and identify the prognostic factors for distant metastasis-free survival (DMFS). Methods A total of forty primary nonkeratinizing NPC patients underwent targeted next-generation sequencing of 450 cancer-relevant genes. Analysis of these sequencing and clinical data was performed comprehensively. Univariate Cox regression analysis and multivariate Lasso-Cox regression analyses were performed to identify factors that predict distant metastasis and construct a risk score model, and seventy percent of patients were randomly selected from among the samples as a validation cohort. A receiver operating characteristic (ROC) curve and Harrell’s concordance index (C-index) were used to investigate whether the risk score was superior to the TNM stage in predicting the survival of patients. The survival of patients was determined by Kaplan–Meier curves and log-rank tests. Results The twenty most frequently mutated genes were identified, such as KMT2D, CYLD, and TP53 et al. Their mutation frequencies of them were compared with those of the COSMIC database and cBioPortal database. N stage, tumor mutational burden (TMB), PIK3CA, and SF3B1 were identified as predictors to build the risk score model. The risk score model showed a higher AUC and C-index than the TNM stage model, regardless of the training cohort or validation cohort. Moreover, this study found that patients with tumors harboring PI3K/AKT or RAS pathway mutations have worse DMFS than their wild-type counterparts. Conclusions In this study, we drew a mutational landscape of NPC tumors and established a novel four predictor-based prognostic model, which had much better predictive capacity than TNM stage.

Abstract Durability is an important aspect of reliability of concrete structures. In order to establish the carbonation model of polyvinyl alcohol (PVA) fiber concrete including the influences of PVA fiber length and volume content, a series of accelerated carbonation experiments were carried out on the normal concrete specimens and PVA fiber concrete specimens with fiber lengths of 3 mm, 6 mm, 12 mm and 18 mm and fiber volume contents of 0.1%, 0.3%, 0.5%, 0.75%, 1.0% and 1.5%, respectively. The experimental conditions remained at temperature of 20 ℃, humidity of 70%, and carbon dioxide concentration of 20%. It was found that the addition of PVA fibers could improve the carbonation resistance of concrete considerably. Within the investigated range of fiber length and content, the carbonation resistance of concrete is first strengthened and then weakened with increasing PVA fiber length or content. The quadratic carbonation depth prediction model could characterize the influences of PVA fiber length and content better than the linear model. The carbon dioxide diffusion equation was established by introducing a PVA fiber influence factor and its parameters were determined from the carbonation depth prediction model. The carbonation process of PVA fiber concrete under the accelerated carbonation experiment condition was simulated. Both the model and the numerical method were validated by comparison between the experimental and numerical results. Finally, the influences of added PVA fibers on the carbonation life and durability of reinforced concrete components were further studied numerically. The results showed that compared with the normal concrete component, the durability of PVA fiber concrete components is significantly improved.

Acquiring welding domain relationships and forming a knowledge graph can positively impact complex engineering problem solving and intelligent manufacturing applications. However, relationships are lacking in the welding domain. The relationship extraction and processing solution are designed to handle data with different characteristics in welding fabrication. The BiLSTM+Attention and CR-CNN models are employed to extract relations in unstructured documents. The neighborhood rough set-based association rule model is proposed for project-specific documents to accomplish relationship acquisition, in which invalid attributes are removed via neighborhood rough sets and attribute values are related via association rules. In addition, the knowledge graph is built based on extracted relationships, and unique empirical relationships are handled by introducing relational nodes and databases. The results show that BiLSTM+Attention gets a good score with Macro-average metrics (0.788 for Precision, 0.846 for Recall, and 0.816 for F1-score). The relational rules obtained via the proposed model are consistent with the production experience. The constructed knowledge graph effectively handles empirical relationships while positively impacting knowledge retrieval, intelligent question and answer, and decision-making for complex engineering problems.

The cold metal transfer (CMT) process is widely used in thin plate welding because of its characteristics of low heat input and stable arc. In actual production, a larger weld gap, misalignment, or other problems due to assembly error lead to serious welding defects, such as burn-through and a lack of fusion. The arc sound contains a wealth of information related to the quality of the weld. This work analyzes the mechanism of CMT arc sound generation, as well as the correlation between the time–frequency spectrum of the arc sound signal and welding quality. This paper studies the extraction of the multi-channel time–frequency spectrum of an arc sound and inputs it to a custom convolutional neural network for the CMT welding defect identification of thin aluminum alloy plates. The experimental result shows that the average accuracy of the proposed model is 91.49% in the defect identification of a CMT arc-welded aluminum alloy sheet, which is higher than that of the single-channel time–frequency convolutional neural network and other traditional classification models.

BackgroundDespite common dissatisfaction with the syndromic heterogeneity of major depression, investigations into its symptom structure are scarce. Self-worthlessness/inadequacy is a distinctive and consistent symptom of major depression across cultures.AimsWe investigated whether self-worthlessness is associated with self-blaming attribution-related symptoms or is instead an expression of reduced positive feelings overall, as would be implied by reduced positive affect accounts of depression.Methods44,161 undergraduate students in Study 1, and 215 patients with current Major Depressive Disorder (MDD) and 237 age-matched healthy control participants in Study 2 completed the well-validated Symptom Check List-90. Depression-relevant items were used to construct regularized partial correlation networks with bootstrap estimates of network parameter variability.ResultsWorthlessness co-occurred more strongly with other symptoms linked to self-blaming attributions (hopelessness, and self-blame), displaying a combined edge weight with these symptoms which was significantly stronger than the edge weight representing its connection with reduced positive emotion symptoms (such as reduced pleasure/interest/motivation, difference in edge weight sum in Study 1 = 2.95, in Study 2 = 1.64; 95% confidence intervals: Study 1: 2.6–3.4; Study 2: 0.02–3.5; Bonferroni-corrected p < 0.05).ConclusionsThis confirms the prediction of the revised learned helplessness model that worthlessness is most strongly linked to hopelessness and self-blame. In contrast, we did not find a strong and direct link between anhedonia items and a reduction in self-worth in either study. This supports worthlessness as a primary symptom rather than resulting from reduced positive affect.

In this paper, a novel master S-N curve fitting method based on improved neighborhood rough set is proposed. The neighborhood relationship is used to granulate the fatigue information system of aluminum alloy welded joints, and the neighborhood rough set model is constructed from the information perspective. Based on conditional entropy, a neighborhood rough set attribute reduction algorithm (NRSBCE) is proposed. By means of this algorithm, comprehensive mathematical analysis model for fatigue life influencing factors is established and optimization of the S-N curve fitting method is introduced. In this work, the fatigue decision system of the aluminum welded joints is constructed firstly. The key influencing factors of the welded joints are obtained by means of NRSBCE algorithm subsequently. After that, the concept of fatigue characteristic domain is introduced according to the reduction result of the NRSBCE algorithm. Then, the master S-N curve fitting is carried out according to the divided fatigue characteristic domain. Correspondingly, a set of S-N curve clusters are fitted. Finally, fatigue analysis system for welded joints based on the fatigue characteristic domain is designed and developed. In the system, the equations of master S-N curve based on the mesh-insensitive structural stress method and the master S-N curve cluster based on the fatigue characteristic domain could be both obtained by uploading the practical fatigue test data of the aluminum alloy welded joints. This work helps to further reduce the dispersion degree of the fatigue sample data of the aluminum alloy welded joints thus provide reference for fatigue design.

To address the challenges of incomplete knowledge representation, independent decision ranges, and insufficient causal decisions in bogie welding decisions, this paper proposes a hybrid decision-making method and develops a corresponding intelligent system. The collaborative case, rule, and knowledge graph approach is used to support structured documents and domain causality decisions. In addition, we created a knowledge model of bogie welding characteristics and proposed a case-matching method based on empirical weights. Several entity categorizations and relationship extraction models were trained under supervised conditions while building the knowledge graph. CRF and CR-CNN obtained high combined F1 scores (0.710 for CRF and 0.802 for CR-CNN) in the entity classification and relationship extraction tasks, respectively. We designed and developed an intelligent decision system based on the proposed method to implement engineering applications. This system was validated with some actual engineering data. The results show that the system obtained a high score on the accuracy test (0.947 for Corrected Accuracy) and can effectively complete structured document and causality decision-making tasks, having large research significance and engineering value.

Objective To investigate the safety and efficacy of high-intensity focused ultrasound (HIFU) treatment for diffuse uterine leiomyomatosis (DUL). Methods Eight patients with DUL were admitted to the Department of Gynecology of Shanghai First Maternity and Infant Hospital and underwent HIFU treatment. MRI was performed before and one day after HIFU treatment for the evaluation of lesion ablation. The uterine size was measured at 3-8 months after HIFU ablation. The menstrual volume score and serum levels of hemoglobin and CA-125 were measured pre-HIFU ablation and 12-36 months post-HIFU ablation. Results After an average of 5.9 months of follow-up after HIFU treatment, an average uterine volume reduction of 67.6% was observed. Menstruation returned to normal in all patients, and their serum HGB and CA-125 levels also returned to normal after an average of 19.1 months of clinical follow-up. The quality of life of all patients improved significantly. Conclusion HIFU treatment is safe and effective in the treatment of patients with DUL.

Abstract Background Increase of circulating tumor cells (CTCs) has been found after surgery for various carcinomas but not confirmed for breast cancer, and whether endoscopic surgery confers identical effect to CTCs as open surgery did is not clear. The present study aimed to investigate whether CTCs increase after surgery and whether there is a difference between open surgery and endoscopic surgery. Methods Pre- and postoperative peripheral blood (5 mL) obtained from 110 female patients with operable breast cancer (53 underwent endoscopic surgery, 57 underwent open radical mastectomy). Quantitative real-time reverse transcription-PCR was done to detect cytokeratin 19 mRNA-positive CTC. CTC detection rate, cell number and the increase after surgery (named micrometastasis) were compared between the two groups. Results In the open group, CTC positive rate before and after surgery were 22.81 and 33.33%; median CTC number before and after surgery were 0.21 and 0.43 and 17 patients (29.82%) had increased micrometastatic risk. In the endoscopic group, CTC positive rate before and after surgery were 24.53 and 28.30%; median CTC number before and after surgery were 0.27 and 0.36, and 8 patients (15.09%) had increased micrometastatic risk. There was a suggestive higher postoperative CTC detection rate and CTC number and a significant increased postoperation micrometastatic risk was observed in the open group compared to the endoscopic group (OR = 3.19, 95%CI: 1.05–9.65) after adjustment for clinicopathologic characteristics. Discussion CTC tends to increase in breast cancer patients after surgery, and the micrometastatic risk was higher for open surgery compared to endoscopic surgery. Trial registration This study was prospectively registered at Chinese Clinical Trial Register (ChiCTR-OCH-10000859, 24 April 2010).

PurposeThe aim of this study was to evaluate tumor blood flow (TBF) as a predictor of radiotherapy response for nasopharyngeal carcinoma (NPC).Materials and MethodA total of 134 patients were divided into two groups, the complete response (CR) group and the partial response (PR) group based on RECIST 1.1 recommendations. The statistical difference was evaluated for pre- and mid- or post-treatment TBF and changes of TBF for tumors and metastatic lymph nodes between CR and PR, respectively. The receiver operation characteristic (ROC) curve was utilized to evaluate the accuracy of TBF in predicting the response of radiation therapy. The association between TBF and SUVmax was also investigated.ResultsThe reduction of TBF in CR was significantly lower than that in PR for primary tumors (P

In this paper, an improved fish swarm algorithm for neighborhood rough set reduction (IFSANRSR) is proposed. In IFSANRSR, by introducing an adaptive function to control the visual and step size of artificial fish, the problem of inconsistent convergence speed existed in a traditional artificial fish swarm algorithm (FSA) is avoided. The movement of artificial fish in the swarming and following behavior is improved to shorten the running time of the algorithm. The searching behavior is improved to enhance the local search ability without changing the global searching ability of the algorithm. By introducing the mechanism of extinction and rebirth, the worst solution is eliminated and rebirth takes place after each iteration, which ensures a high level of the overall fitness. The experimental results on three datasets from the University of California at Irvine (UCI) show that the attributes reduction by using the IFSANRSR has higher reduction rate and classification accuracy in most cases. It could better deal with real-valued data attributes and ensure the optimal attribute reduction set to be found. The experimental result on the decision system of aluminum alloy welded joints show that by using the IFSANRSR, the key influencing factors of fatigue life of aluminum alloy welded joints could be obtained, and the weight of each influencing factor could be calculated quantitatively.

Objective: To evaluate the combined efficacy of high-intensity focused ultrasound (HIFU), gonadotropin-releasing hormone agonist (GnRH-a) and the levonorgestrel-releasing intrauterine system (LNG-IUS) for the treatment of severe adenomyosis. Method: Four hundred and sixty-six patients with adenomyosis admitted to the Department of Gynecology of Shanghai First Maternity and Infant Hospital underwent HIFU treatment, and then were consecutively administered with GnRH-a 1 d, 1 month and 3 months after HIFU treatment. The uterine size was then measured with ultrasound or MRI 2–4 weeks after three cycles of GnRH-a injection. The LNG-IUS was then inserted when the uterine length less than 9 cm. The visual analog scale (VAS), verbal rating scale (VRS), menstrual volume score, uterus volume, MRI, serum levels of hemoglobin and CA125 were measured at pre and 3-, 6-, 12-month post-HIFU. Results: Dysmenorrhea and menorrhagia significantly relieved after combined treatment with HIFU, GnRH-a and the LNS-IUS. The uterine volume shrank and returned to its normal size. The serum CA-125 level was reduced to the normal level after the combined treatment. Conclusions: The combined therapeutic regimen of HIFU, GnRH-a and LNS-IUS is safe, effective and efficient for curing severe adenomyosis.

Calcite is the most stable crystalline phase of calcium carbonate. It is applied or found in composite products, the food industry, biomineralization, archaeology, and geology, and its mechanical properties have attracted more and more attention. In this paper, the mechanical behaviors of single-crystal calcite under uniaxial tension in different directions were simulated with the molecular dynamics method. The obtained elastic moduli are in good agreement with the experimental results. It has been found from further research that single-crystal calcite has typical quasi-brittle failure characteristics, and its elastic modulus, fracture strength, and fracture strain are all strongly anisotropic. The tensile failure is caused by dislocation emission, void formation, and phase transition along the [010] and [421] directions, but by continuous dislocation glide and multiplication along the [421¯] direction. The fracture strength, fracture strain, and elastic modulus are all sensitive to temperature, but only elastic modulus is not sensitive to strain rate. The effects of temperature and logarithmic strain rate on fracture strength are in good agreement with the predictions of fracture dynamics.

RM (red mud), which comes from the Bayer process, has a huge annual output and is harmful to the environment. Because of the high iron content in RM, the process of iron recovery from RM can reduce the amount of RM well and create economic benefits, so it is a promising process. The paper focuses on the review on the research of the iron recovery method from RM, which includes the physical recovery method, chemical recovery method and emerging recovery method. By comparing the advantages and disadvantages of these processes, it is concluded that the fluidized bed reduction is a promising process that can be rapidly applied to the industry, but it still needs more investigation to overcome the current technical difficulties in the near future.

Objective: This randomized study aimed to compare the clinical efficacy between the novel dual tracer composed of indocyanine green (ICG) and blue dye (BD) and the conventional dual tracer composed of radioisotope and BD for sentinel lymph node (SLN) mapping in patients with breast cancer.Methods: This study enrolled 471 clinically lymph node-negative patients with primary breast cancer. All patients underwent mastectomy, and those undergoing sentinel lymph node biopsy (SLNB) were randomized to receive blue dye plus radioisotope (RB group) or BD plus ICG (IB group). The detection performances on SLN identification rate, positive SLN counts, detection sensitivity, and false-negative rate were compared between the two groups. Results: In the IB group, 97% (194/200) of the patients who underwent the ICG and BD dual tracer injection showed fluorescent-positive lymphatic vessels within 2–5 min. The identification rate of SLNs was comparable between the IB group (99.0%, 198/200) and the RB group (99.6%, 270/271) (P = 0.79). No significant differences were observed in the identification rate of metastatic SLNs (22.5% vs. 22.9%, P > 0.05, RB group vs. IB group, the same below), positive SLN counts (3.72 ± 2.28 vs. 3.91 ± 2.13, P > 0.05), positive metastatic SLN counts (0.38 ± 0.84 vs. 0.34 ± 0.78, P > 0.05), SLNB detection sensitivity (94.4% vs. 92.5%, P > 0.05), or false-negative rate (5.6% vs. 7.5%, P > 0.05) between the two groups. Conclusions: ICG can be used as a promising alternative tracer for radioisotope in SLN mapping, and when it is combined with BD in lymphangiography, it offers comparable detection sensitivity compared to the conventional lymphatic mapping strategies that are widely used in clinical practice.

Ultrasonic bonding is a convenient bonding technology, which features sufficient cleanliness, high efficiency, no need for additional bonding aids, and other outstanding advantages. In recent years, it has been introduced into the field of the micro–nano assembly of polymer micro–nano devices, but it is still difficult for current ultrasonic bonding technology to meet the accuracy requirements of the micro–nano assembly. To improve the control accuracy of the hot-melt interface in the process of ultrasonic bonding, an online hot-melt interface monitoring method and an online ultrasonic transmission efficiency detection method are proposed in this article. With these detection methods, the real-time monitoring of the hot-melt interface can be realized on the basis of machine vision, while high-frequency dynamic force sensors can be used to detect the ultrasonic vibration transmitted from the ultrasonic horn to the anvil. Based on these methods, a functional anvil based on visual monitoring and ultrasonic detection is developed, the finite element method has been used to analyze the transmission characteristics of ultrasonic vibration, and experiments are carried out regarding online detection in the process of ultrasonic bonding. The results show that this system can realize the online detection of the hot-melt interface and ultrasonic transmission information, providing a new control method for ultrasonic bonding technology.

Sibling bullying is a common phenomenon in childhood and adolescence worldwide and has a significant association with mental health distress. However, there have been few studies that have examined the associations between any specific sub-type of sibling bullying and depression as well as anxiety. Besides, the association between sibling bullying and psychological well-being was never explored among the Chinese population. The purpose of this cross-sectional study was to examine the associations between the number of sub-types of sibling bullying involvement and depression as well as anxiety among Chinese children and adolescents. Multi-stage stratified cluster sampling was used to recruit 5,926 participants aged 10 to 18 who had at least one sibling living in the household. Different sub-types of sibling bullying involvement were determined by using Olweus Bully/Victim Questionnaire (OBVQ). The nine-item Patient Health Questionnaire (PHQ-9) and the seven-item Generalized Anxiety Disorder Scale (GAD-7) were used to screen clinical ranges of major depression and generalized anxiety disorder, respectively. Of the participants, 1,235 (20.8%) were bullied by siblings, and 1,230 (20.8%) perpetrated bullying behavior against siblings over the past 6 months. After controlling potential confounders, adjusted model of logistic regression analyses indicated that all three sub-types of sibling victimization and perpetration were significantly associated with both depression and anxiety. There were linear associations between the number of sub-types of sibling bullying victimization and depression (adjusted OR = 1.49, 95% CI 1.32 to 1.68) as well as anxiety (adjusted OR = 1.68, 95% CI 1.48 to 1.90). Besides, linear trends were found between the number of sub-types of sibling bullying perpetration and depression (adjusted OR = 1.44, 95% CI 1.26 to 1.64) as well as anxiety (adjusted OR = 1.63, 95% CI 1.42 to 1.87). The findings underline dose–response relationships between the number of sub-types of sibling bullying involvement and mental health distress. Intervention programs should be conducted to focus on developing mental health status of those children and adolescents who are involved in multiple sub-types of sibling victimization or perpetration.

Three-point bending fatigue test of 5083 and 5A06 aluminum alloy T-welded joints is carried out, and the fatigue life of the specimens with different influencing factors are obtained. Finite element model of the T-welded joint is established and the nodal force based structural stress is calculated. Neighborhood rough set theory is used for analysis of the factors which influence the fatigue life of the aluminum alloy welded joints. Key influencing factors are studied and the fatigue characteristic domains are determined. The master S-N curve characterized by the nodal force based structural stress range and cycles to failure on semi log coordinate as well as S-N curves corresponding to the fatigue characteristic domain is fitted. A case study of fatigue life prediction of 5A06 aluminum alloy welded joint indicates the effectiveness of the fatigue life prediction method based on the fatigue characteristic domain.

Motor bearing is subjected to the joint effects of much more loads, transmissions, and shocks that cause bearing fault and machinery breakdown. A vibration signal analysis method is the most popular technique that is used to monitor and diagnose the fault of motor bearing. However, the application of the vibration signal analysis method for motor bearing is very limited in engineering practice. In this paper, on the basis of comparing fault feature extraction by using empirical wavelet transform (EWT) and Hilbert transform with the theoretical calculation, a new motor bearing fault diagnosis method based on integrating EWT, fuzzy entropy, and support vector machine (SVM) called EWTFSFD is proposed. In the proposed method, a novel signal processing method called EWT is used to decompose vibration signal into multiple components in order to extract a series of amplitude modulated-frequency modulated (AM-FM) components with supporting Fourier spectrum under an orthogonal basis. Then, fuzzy entropy is utilized to measure the complexity of vibration signal, reflect the complexity changes of intrinsic oscillation, and compute the fuzzy entropy values of AM-FM components, which are regarded as the inputs of the SVM model to train and construct an SVM classifier for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by using the simulated signal and real motor bearing vibration signals. The experiment results show that the EWT outperforms empirical mode decomposition for decomposing the signal into multiple components, and the proposed EWTFSFD method can accurately and effectively achieve the fault diagnosis of motor bearing.

As a clean fuel combustion technology, the circulating fluidized bed (CFB) has been developed rapidly in recent years, but one of its disadvantages is high N2O emissions. With the implementation of increasingly strict pollution control standards, N2O decomposition and removal technologies have become the main focus of current research. This paper reviews the latest research on noble metals, metal oxides, the molecular sieve and other new catalysts and decomposition methods for N2O removal. The research methods and functions of catalysts are compared and the existing problems are summarized. The future directions of development in N2O decomposition and removal are considered. Noble metals and the molecular sieve show satisfactory activity at relatively low temperatures, but their catalytic efficiency is obviously hindered by O2, NO and H2O. In addition, high costs and insufficient thermal stability limit their widespread industrial application. The metal oxide catalytic technology, especially oxygen carrier-aided combustion (OCAC), is expected to be the ideal method for N2O removal in CFB boilers due to its stability and economical feasibility.

Wet flue gas desulfurization (WFGD) wastewater treatment is a key problem in coal-fired plants. Traditional chemical precipitation methods cannot reach zero-liquid discharge (ZLD). In this paper, a new technology using the low-rank heat from flue gas to concentrate the wastewater for ZLD is proposed. A scrubber was built to verify the concentrating process, and the characteristics of the concentrated water were analyzed. The concentrated water was neutralized by adding Ca(OH)2 to raise the pH value. The wastewater can be concentrated 10~25 times to reduce the flow rate. The characteristics of the concentrated wastewater were studied by dosing lime. Then, liquid and solids were separated by filter pressing, the liquid was mainly composed of CaCl2, which accounts for 73.6%. The sludge is composed of CaSO4 and Mg(OH)2, depending on the lime consumption of the dosing process. Finally, the filter liquor after the filter press was mixed with ash to reach zero liquid discharge, and the sludge could be burnt after mixing with the coal or disposed by third-part vendor. This technology is demonstrated in one 600 MW unit and shows a high system reliability. The clean water is recycled by the WFGD wastewater during the evaporation. Binding on the environmental policies and large market demand of the WFGD wastewater, this technology shows a great application prospect in the future.

Genome assembly for many plant species can be challenging due to large size and high repeat content. Here, the authors usein vitroproximity ligation to assemble the genome of lettuce, revealing a family-specific triplication event and providing a comprehensive reference genome for a member of the Compositae.

The scatter degree of the fatigue samples is reduced when the nodal force based structural method is used for steel welded joints, while it is still high for aluminum alloy welded joints. Statistical method and rough set theory is used to fatigue analysis so that fatigue characteristic domains are determined and S-N curves are fitted. Experiment results show that fatigue life of the aluminum alloy welded joints is under the influence of some key factors and the fatigue data with the same characteristics distribute in a relatively independent area. Accordingly, a novel S-N curve modeling method of aluminum alloy welded joints based on the fatigue characteristics domain is proposed. In the proposed method, the nodal force based structural stress method is used for stress calculation and neighborhood rough set theory is used for character extraction to obtain the key factors. Then fatigue characteristics domains are divided and S-N curves are fitted on each fatigue characteristics domain instead of on the whole domain so that a set of S-N curves are obtained. Statistical results show that selection of the S-N curve for the aluminum alloy welded joints according to different fatigue characteristic domain is more accurate.

Spot welding of dissimilar materials can utilize the respective advantage comprehensively, of which reliable prediction of fatigue life is the key issue in the structure design and service process. Taking into account almost all the complex factors that have effects on the fatigue behavior such as load level, thickness, welding nugget diameter, vibrational frequency, and material properties, this article proposed an energy dissipation-based method that is able to predict the fatigue life for spot-welded dissimilar materials rapidly. In order to obtain the temperature gradient, the temperature variations of four-group spot-welded joint of SUS301 L-DLT stainless steel and Q235 carbon steel during high-cycle fatigue tests were monitored by thermal infrared scanner. Specifically, temperature variation disciplines of specimen surface were divided into four stages: temperature increase, temperature decrease, continuous steady increase in temperature, and ultimate drop after the fracture. The material constant C that a spot-welded joint of dissimilar material needs to reach fracture is 0.05425°C·mm 3 . When the specimen was applied higher than the fatigue limit, the highest error between experimental values and predicted values is 18.90%, and others are lower than 10%. Therefore, a good agreement was achieved in fatigue life prediction between the new method and the validation test results.

In this study, we investigated the fatigue behavior of Q460 welded joints using tensile fatigue tests. Furthermore, real-time temperature profiles of the examined specimens were recorded by infrared thermography. Based on the obtained thermographic data, we calculated the entropy production rate of the specimens under different stress amplitudes. Hypothetically, the entropy production during high-cycle fatigue (HCF) could be divided into two parts. The first is induced by inelastic behavior that corresponds to damage accumulation, and the second originates from anelasticity associated with recoverable non-damaging microstructural motions. The turning point of entropy production under different stress levels represents an index for fatigue limit estimation. Then, considering the average damage threshold that exists during HCF, the entropy production related to damage accumulation (cumulative damage entropy) is obtained by testing three specimens under the same stress amplitude above the fatigue limit. Finally, a rapid three-parameter S-N curve with a survival probability rate of 50% is obtained. Then, combined with the maximum likelihood method, the 5% and 95% survival probability rate S-N curves are established. Most of experimental data are distributed in the area between S-N curves that correspond to 5% and 95% survival probability rate, indicating good accordance with the test data.

The scatter degree of the fatigue samples is reduced when the nodal force based structural method is used for steel welded joints, while it is still high for aluminum alloy welded joints. Statistical method and rough set theory is used to fatigue analysis so that fatigue characteristic domains are determined and S-N curves are fitted. Experiment results show that fatigue life of the aluminum alloy welded joints is under the influence of some key factors and the fatigue data with the same characteristics distribute in a relatively independent area. Accordingly, a novel S-N curve modeling method of aluminum alloy welded joints based on the fatigue characteristics domain is proposed. In the proposed method, the nodal force based structural stress method is used for stress calculation and neighborhood rough set theory is used for character extraction to obtain the key factors. Then fatigue characteristics domains are divided and S-N curves are fitted on each fatigue characteristics domain instead of on the whole domain so that a set of S-N curves are obtained. Statistical results show that selection of the S-N curve for the aluminum alloy welded joints according to different fatigue characteristic domain is more accurate.

A series of numerical simulations were performed on prenotched four-point bending (FPB) concrete beams containing air voids of different sizes and locations by using the finite element method combined with the cohesive crack model. The void-affected zone was proposed for characterizing the effect of a void on a fracture, and its size was determined by moving an air void horizontally until the crack path changed. As a function of air void location and size, the dimensionless affected-zone radius was fitted according to the numerical results. Finally, the fracture processes of the pre-notched FPB concrete beams with randomly distributed voids were simulated numerically, and the affected-zone radius was used to explain the choice of crack paths to verify the prediction. It was found that the prediction is accurate for an isolated affected zone and is roughly approximate for an overlapped one.

In order to obtain comprehensive assessment of the factors influencing fatigue life and to further improve the accuracy of fatigue life prediction of welded joints, soft computing methods, including entropy-based neighborhood rough set reduction algorithm, the particle swarm optimization (PSO) algorithm and support vector regression machine (SVRM) are combined to construct a fatigue life prediction model of titanium alloy welded joints. By using an entropy-based neighborhood rough set reduction algorithm, the influencing factors of the fatigue life of titanium alloy welded joints such as joint type, plate thickness, etc. are analyzed and the reduction results are obtained. Fatigue characteristic domains are proposed and determined subsequently according to the reduction results. The PSO-SVRM model for fatigue life prediction of titanium alloy welded joints is established in the suggested fatigue characteristic domains. Experimental results show that by taking into account the impact of joint type, the PSO-SVRM model could better predict the fatigue life of titanium alloy welded joints. The PSO-SVRM model indicates the relationship between fatigue life and fatigue life influencing factors in multidimensional space compared with the conventional least-square S-N curve fitting method, it could predict the fatigue life of the titanium alloy welded joints more accurately thus helps to the reliability design of the structure.

Empirical wavelet transform (EWT) is a novel adaptive signal decomposition method, whose main shortcoming is the fact that Fourier segmentation is strongly dependent on the local maxima of the amplitudes of the Fourier spectrum. An enhanced empirical wavelet transform (MSCEWT) based on maximum-minimum length curve method is proposed to realize fault diagnosis of motor bearings. The maximum-minimum length curve method transforms the original vibration signal spectrum to scale space in order to obtain a set of minimum length curves, and find the maximum length curve value in the set of the minimum length curve values for obtaining the number of the spectrum decomposition intervals. The MSCEWT method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs), which are processed by Hilbert transform. Then the frequency of each component is extracted by power spectrum and compared with the theoretical value of motor bearing fault feature frequency in order to determine and obtain fault diagnosis result. In order to verify the effectiveness of the MSCEWT method for fault diagnosis, the actual motor bearing vibration signals are selected and the empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) methods are selected for comparative analysis in here. The results show that the maximum-minimum length curve method can enhance EWT method and the MSCEWT method can solve the shortcomings of the Fourier spectrum segmentation and can effectively decompose the bearing vibration signal for obtaining less number of intrinsic mode function (IMF) components than the EMD and EEMD methods. It can effectively extract the fault feature frequency of the motor bearing and realize fault diagnosis. Therefore, the study provides a new method for fault diagnosis of rotating machinery.

Roller bearings are the most widely used and easily damaged mechanical parts in rotating machinery. Their running state directly affects rotating machinery performance. Empirical mode decomposition (EMD) easily occurs illusive component and mode mixing problem. From the view of feature extraction, a new feature extraction method based on integrating ensemble empirical mode decomposition (EEMD), the correlation coefficient method, and Hilbert transform is proposed to extract fault features and identify fault states for motor bearings in this paper. In the proposed feature extraction method, the EEMD is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs) with different frequency components. Then the correlation coefficient method is used to select the IMF components with the largest correlation coefficient, which are carried out with the Hilbert transform. The obtained corresponding envelope spectra are analyzed to extract the fault feature frequency and identify the fault state by comparing with the theoretical value. Finally, the fault signal transmission performance of vibration signals of the bearing inner ring and outer ring at the drive end and fan end are deeply studied. The experimental results show that the proposed feature extraction method can effectively eliminate the influence of the mode mixing and extract the fault feature frequency, and the energy of the vibration signal in the bearing outer ring at the fan end is lost during the transmission of the vibration signal. It is an effective method to extract the fault feature of the bearing from the noise with interference.

Ultrasonic bonding has an increasing application in the micro assembly of polymeric micro-electro mechanical systems (MEMS) with high requirements for fusion precision. In the ultrasonic bonding process, the propagation of ultrasonic vibration in polymer components is related to the interfacial fusion, which can be used as a monitoring parameter to control ultrasonic energy. To study the vibration propagation in viscoelastic polymer components, finite element analysis on the bonding of poly methyl methacrylate (PMMA) micro connector to substrate for microfluidic system is carried out. Curves of propagated vibration amplitude corresponding to interfacial temperatures are obtained. The ultrasonic vibration propagated in PMMA components are measured through experiments. The theoretical and experimental results are contrasted to analyze the change mechanism of vibration propagation related to temperature. Based on the ultrasonic bonding process controlled by the feedback of vibration propagation, interfacial fusions at different vibration propagation states are obtained through experiments. Interfacial fusion behavior is contrasted to the propagated vibration amplitude in theoretical and experimental studies. The relation between vibration propagation and fusion degree is established with the proper parameter range for the obtained high quality bonding.

An evaluation model of aluminum alloy welded joint low-cycle fatigue data based on information entropy is proposed. Through calculating and analyzing the information entropy of decision attributes, quantitative contribution of stress concentration, plate thickness, and loading mode to the fatigue destruction are researched. Results reveal that the total information entropy of the fatigue data based on nominal stress, structural stress and equivalent structural stress are, respectively, 0.9702, 0.8881, and 0.8294. There is consistency between the reducing trend of the weight-based information entropy and the smaller and smaller standard deviation of the S-N curves. In the structural stress based S-N curve, total stress concentration factor is crucial for the distribution of the fatigue data and the weight based information entropy of membrane stress concentration factor is 0.6754, which illustrates that stress concentration is a key issue of welded structure to which ought to be attached great importance. Subsequently, in the equivalent structural stress-based S-N curve, the weight based information entropy of stress ratio is 0.5759, which plays an important role in the distribution of fatigue data. With the importance level of the attributes on the S-N curves investigated, the correction of R in the equivalent structural stress based master S-N curve method should be carried out to make the welding fatigue prediction much more accurate.

BACKGROUND: Accurate detection and determination of axillary lymph node metastasis are crucial for the clinical management of patients with breast cancer. Noninvasive imaging methods including ultrasound (US), computed tomography (CT), or conventional magnetic resonance imaging (MRI) are not yet accurate enough. The purpose of this study was to investigate the value of in vivo T2* in differentiating metastatic from benign axillary lymph nodes in patients with breast cancer. METHODOLOGY/PRINCIPAL FINDINGS: In this institutional review board approved study, 35 women with breast cancer underwent multi-echo T2* weighted imaging (T2*WI) of the axillary area on a 3.0 T clinical magnetic resonance (MR) imaging system. T2* values of pathologically proven benign and metastatic axillary lymph nodes were calculated and compared. Receiver operating characteristics (ROC) analysis was conducted to evaluate the diagnostic ability. The areas under the ROC curve (AUCs) and the confidence intervals (CIs) were assessed. In total, 56 metastatic and 65 benign axillary lymph nodes were identified in this study. For metastatic lymph nodes, the average T2* value (55.96±11.87 ms) was significantly longer than that of the benign lymph nodes (26.00±5.51 ms, P

Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method based on integrating ensemble empirical mode decomposition (EEMD), mode selection, and multi-scale fuzzy entropy is proposed to accurately diagnose fault in this paper. The EEMD method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs) with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM) model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM) for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by real bearing vibration signals of the motor with different loads and fault severities. The experiment results show that the proposed EDOMFE method can effectively extract fault features from the vibration signal and that the proposed EOMSMFD method can accurately diagnose the fault types and fault severities for the inner race fault, the outer race fault, and rolling element fault of the motor bearing. Therefore, the proposed method provides a new fault diagnosis technology for rotating machinery.