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Longitudinal mode ultrasonic guided waves (UGWs) in prestressed seven wire steel strands have an inherent notch frequency property covering a frequency range of less than 100 kHz. If UGWs having such a frequency range are used to inspect the strand, the inspection instrument may fail to delect small defec b due to difficulties in predicting the notch frequency. lhereforef it is more appropriate to design a miniaturised instrument that can excite and receive UGWs covering a frequency range of tar more than WO kHz for on-site strand inspection applications, In this study, an FPGA-controlfed instrument is developed lo test its UGW detection performance. The boost circuit operates in a frequency range of 0.1-1.5 MHt to produce a parametric bunt of square waves with a low distortion content. The detected UGW signal is then filtered by a low-pass filter and amplified by a two-stage programmable qain pre-amplifier with a maximum amplification of 80 dB. The long range strand inspection results show that the proposed instrument provides a signal-to-noise ratio for the detected tlGW signal of 6.06 dR after the UGW has propagated for 96 m in the strand. The influence of a notch defect on the extent of mode conversion between the L(0,1) and F(1, 1) modes and the amplitude of the signal reflected from the notch are analysed based on the short-time Fourier transform (STFT) results from the detected UGW signals. The variation in the UGW signal spectrum that is induced by a notch with a cross-sectional area loss of 1.13% can be identified, indicating thehigh UGW detection performance of the developed instrument. [ABSTRACT FROM AUTHOR]

Electromagnetic railgun systems based on capacitive pulsed-power supply (CPPS) have obtained widespread applications because of its obvious advantages over the inductive ones on mature technology, operational reliability, and feasible financial condition. However, the existing CPPS-based electromagnetic railgun system works with low efficiency. In this paper, systematical studies on the CPPS in the synchronously triggered electromagnetic railgun system with constant volume and in the time-delay-triggered electromagnetic railgun system with automatic segmentation are proposed, respectively. In the synchronously triggered electromagnetic railgun system, all pulse-forming units (PFUs) are supposed to be triggered synchronously and the load is simplified as a resistor first. Then, the system performance criteria, i.e., the launch velocity of the armature v \rm end and the system efficiency \eta , are expressed as the function of four independent system variables: 1) the capacitance of each PFU C ; 2) the precharged voltage UC of capacitors; 3) the rail length l ; and 4) the armature mass $m$ . The relationship between \eta $ (or {v}_{\rm end}) and any two independent variables can be found under the environment of MATLAB R2012a by fixing the other two parameters. The results are then verified under the environment of Simplorer 8. These figures can be used to instruct the design of the pulsed-power supply for a designated load or the railgun for a designated source. In the time-delay-triggered electromagnetic railgun system, the principle of automatic segmentation is proposed. According to the segmentation principle, the simulation results under the environment of Simplorer 8 are given for comparison. The paper can provide a theoretical foundation for the future designs to get higher system efficiency. [ABSTRACT FROM PUBLISHER]

Lung cancer, predominantly non-small cell lung cancer (NSCLC), remains a significant global health challenge, with limited therapeutic options for patients with KRAS-mutated tumors. Herein, a copper-based metal-organic framework (Cu-MOF) was applied as a novel cuproptosis-mediated nanoplatform for lung cancer therapy. Cu-MOF would disassemble and liberate copper ions under the acidic microenvironment of lysosomes of cancer cells, initiating a cascade of cellular events. The released copper ions catalyzes the Fenton reaction, generating hydroxyl radicals that induce oxidative damage, leading to cytoskeletal disruption and activation of caspase-3, ultimately triggering apoptosis. Simultaneously, with the mediation of the key regulatory factor FDX1, we found that the copper ions binding to the mitochondrial protein DLAT could result in the loss of iron-sulfur cluster proteins and aggregation of lipoylated proteins, which culminated in proteotoxic stress-induced cuproptosis. The pronounced anti-tumor effects of Cu-MOF with apoptosis and cuproptosis were confirmed both in vitro and in vivo experiments. Such dual induction of apoptosis and cuproptosis by Cu-MOF presents a promising therapeutic strategy for NSCLC, particularly for KRAS-mutated tumors, and expands potential applications of Cu-based nanomateirals for other cancers. [ABSTRACT FROM AUTHOR]

The utilisation of curved structural components is prevalent, despite their proneness to degradation over time. This research introduces a wearable and flexible electromagnetic non-destructive testing instrument that is furnished with an eddy current sensor, multi-channel excitation and acquisition circuits, amplifiers, as well as signal processing circuits. A unique design for the flexible Eddy Current Testing (ECT) sensor is suggested to ensure its suitability for diverse curved surfaces. By combining the sensor with gloves, it facilitates wearable inspection. Leveraging the self-developed instrument system, this sensor can detect defects with a minimum depth of 0.1 mm while also being capable of identifying crack orientation accurately. Furthermore, it quantitatively determines the depth of defects on curved surfaces with high signal-to-noise ratios. The instrument system exhibits high portability, flexibility, and efficiency, rendering it readily adaptable for various applications. [ABSTRACT FROM AUTHOR]

Background: Lung cancer is the most common malignant tumor. In the present study, we identified a long non‐coding RNA (lncRNA) AC100826.1 (simplify to Lnc1), which was highly expressed in non‐small cell lung cancer (NSCLC) tissues compared with the paracancerous tissues. We also observed the critical role of Lnc1 in regulating the metastasis ability of NSCLC cells. Methods: RNA sequencing was performed to detect differential expression levels of lncRNAs in NSCLC tissues and its paracancerous tissues. Effects of Lnc1 on cell proliferation, invasion, and migration were determined by CCK‐8, transwell and scratch assays. The xenograft experiment confirmed the effect of Lnc1 on NSCLC cells proliferation and migration abilities in vivo. RT‐qPCR and western blots were performed to determine the expression levels of mRNAs and proteins. Results: The expression level of Lnc1 was related to multiple pathological results, knockdown of Lnc1 can inhibit the proliferation and metastasis abilities of NSCLC cells. silencing phospholipase C, β1(PLCB1) can reverse the promoting effects of overexpression Lnc1 on NSCLC cells proliferation and migration abilities. In addition, the Rap1 signaling pathway was implicated in the regulation of Lnc1 in NSCLC metastasis. Conclusion: Our results suggest that Lnc1 regulated the metastatic ability of NSCLC cells through targeting the PLCB1/Rap1 signal pathway. [ABSTRACT FROM AUTHOR]

Three mitigation mechanisms can be considered in the design of an impact buffering structure made of granular materials. First, reflection and decomposition of stress wave may occur at the interface of two granules of different materials. Second, energy dissipation happens at the viscoelastic contact region of two adjacent granules. Third, the impact energy carried by stress waves has multiple propagation paths in two- or three-dimensional granular materials. In this study, a two-dimensional square composite structure of spherical granules (SCSPG) employing all the three mitigation mechanisms is designed and optimized as an impact buffering structure. A numerical model is established to investigate the propagation behavior of impact-induced stress wave in a SCSPG composed of viscoelastic spheres. Comprehensive evaluation functions are established to evaluate the impact mitigation performance of the SCSPG based on the consideration that the probability of impact varies with impact location. To reduce the computational complexity in the material optimization process, a two-step strategy integrating a neural network with a genetic algorithm is proposed. The hyperparameters of the neural network are optimized for the purpose of achieving high accuracy with the meta-data generated by solving the numerical model. A selection criterion of an optimal material combination is established with the distribution histogram of fitness function's values. After the optimization, the numerical solutions of stress waves in SCSPG are improved, thus verifying the optimization results obtained by the two-step strategy. After the optimization, the reduction ratios of the values of the contact force-dependent and the velocity-dependent functions exceeded 55% and 53%, respectively. The proposed evaluation functions and the developed optimization algorithm are applicable to the design of high-performance impact mitigation SCSPG. [ABSTRACT FROM AUTHOR]

• Bi-directional MBN and TMF signals were measured in a deep drawn part using robot-aided system. • Anisotropy in sensitivity and its sign of magnetic parameter to residual stress are highlighted. • BP models were established for simultaneously predicting residual stress and surface hardness. In this study, the method of magnetic Barkhausenn noise (MBN) and tangential magnetic field (TMF) was employed for achieving simultaneous, quantitative prediction of residual stress and surface hardness in box-shape deep drawn parts of SPCC steel. Bi-directional MBN and TMF signals, profiles of surface hardness and residual stress were experimentally measured. Pearson correlation analysis results show that the averaged amplitude of MBN in one magnetization cycle and Root mean square of MBN signal demonstrates approximate linear dependency on residual stress (or surface hardness) in both the measured directions. Three-layer BP models are established after input nodes screening and optimization of neurons' number in the middle hidden layer. BP models are marked corresponding to scanning or magnetization directions. For each direction, two independent models are established and they are combined to use for realizing high accuracy and simultaneous evaluation of the residual stress and surface hardness. [ABSTRACT FROM AUTHOR]

• Analytical model of MEMATs for SH 0 mode generation is re-examined and improved. • The feasibility and accuracy of the improved model are proved by comparison study. • The effect of the static magnetic field strength on the EAETE is accurately predicted. The accuracy of electro-acoustic energy transfer efficiency (EAETE) model directly determines the optimization results of an electromagnetic acoustic transducer (EMAT). In this study, the EMAT model of SH 0 mode generation based on magnetostriction mechanism is re-examined. In the existing magnetostriction-based EMAT (MEMAT) analytical model, an approximate method of dynamic magnetic field was employed. Thus the effects of the tested ferromagnetic materials on the dynamic magnetic field in the air is ignored and the boundary condition between air and material is not exact. As a result, the calculated dynamic magnetic field inside the tested ferromagnetic materials is incorrect, thus leading to the calculation errors of magnetostriction body force and the final EAETE of MEMAT. The rigorous analytical solutions for calculating the dynamic magnetic field are derived based on Maxwell equations and boundary conditions in this study. The prediction results of improved analytical model were consistent with previously reported experimental results. Compared with existing analytical models, the improved model showed the higher prediction accuracy of several parameters, including dynamic magnetic field, magnetostriction force and the EAETE. [ABSTRACT FROM AUTHOR]

In the nondestructive testing and evaluation area, magnetic major hysteresis loop measurement technology are widely applied for ferromagnetic material evaluation. However the characterization ability of major hysteresis loop measurement technology greatly varies as the evaluated target properties. To solve this limitation, magnetic minor hysteresis loops, which reflect the responses of ferromagnetic material magnetization in a systematic way, is recommend. Inspired by plenty of information carried by the minor loops, the sensitivity mapping technique was developed to achieve the highest sensitivity of minor-loop parameters to the nondestructively evaluated targets. In this study, for the first time, the sensitivity mapping technique is used to measure the tensile force in a steel strand and evaluate the effective case depth in induction-hardened steel rods. The method and procedures for the sensitivity mapping technique are given before experimental detection. The obtained experimental results indicate that the linear correlation between the induced voltage (or the magnetic induction intensity) and the tensile force (or effective case depth) exists at most of the locations in the cluster of minor loops. The obtained sensitivity maps can be used to optimize the applied magnetic field (or excitation current) and the analyzed locations at the minor loops for achieving the highest sensitivity. For the purpose of tensile force measurement, it is suggested that the strand should be firstly magnetized to the near-saturation state and then restored to the remanent state. In this way, the highest sensitivity is obtained as about 15.26 mV/kN. As for the induction-hardened steel rods, the highest sensitivity of magnetic induction intensity to the effective case depth occurs under low magnetic field conditions and the absolute value of the highest sensitivity is about 0.1110 T/mm. This indicates that if the highest sensitivity is required in the case depth evaluation, the induction-hardened steel rods are only required to be weakly magnetized. The proposed sensitivity mapping technique shows the good performance in the high-sensitivity evaluation of tensile force and case depth in ferromagnetic materials and its application scope can be extended to other nondestructive detection fields. [ABSTRACT FROM AUTHOR]

The ongoing pandemic coronavirus disease 19 (COVID-19) remains a significant issue for global health, economics, and society. In order to balance epidemic control and economic recovery, many countries have successively announced the gradual relaxation of some lockdown restrictions. Hospitals and medical staff constitute the backbone in this war against COVID-19. In response to this serious situation, many hospitals went into emergency and impaired healthcare access to patients with conditions other than COVID-19. Therefore, gradually promoting hospital operations and functions back to the new normal is important, especially when this outbreak has been effectively controlled. In this study, we introduce existing and potential problems that could seriously affect people's health. Additionally, we propose that an especial transition phase between the emergency and regular modes of hospitals can be well adapted to the current situation. [ABSTRACT FROM AUTHOR]

This study investigates the correlation between various micromagnetic signature patterns and the yield and tensile strengths of carbon steel (Cr12MoV steel as per Chinese standards). For this purpose, back-propagation neural network (BP-NN) models are established to quantitatively predict the yield and tensile strengths of carbon steels. The accuracy of prediction models is significantly affected by the presence of redundant micromagnetic signature patterns. By carefully screening the input parameters, it is able to effectively mitigate prediction errors arising from unreasonable model inputs. In the field of micromagnetic nondestructive testing (NDT), prediction models calibrated for a specific instrument or sensor cannot be directly applied to another instrument or sensor. In the study, a joint distribution adaptation transfer learning strategy based on auxiliary data is proposed to enhance the generalization of prediction models for cross-instrument applications. When auxiliary data accounts for 30% of the source domain data, the joint distribution adaptation transfer learning method based on auxiliary data improves the robustness of the model. The accuracy of the yield strength and tensile strength calibration models witnesses remarkable improvements of approximately 91.4% and 93.5%, respectively. [ABSTRACT FROM AUTHOR]

Background: Long noncoding RNAs (lncRNAs) have been reported to play vital roles in the development and progression of cancer. However, their biological significance and functional mechanisms in non-small cell lung cancer (NSCLC) are mostly unclear. Methods: We performed RNA-sequencing to predict the differential expression of lncRNAs in clinical NSCLC and paired paracancerous lung tissues. To identify lncRNA expression, quantitative polymerase chain reaction (qPCR) was used. Using both cell and mouse models, We studied lncRNA AC016727.1's function in NSCLC growth and metastasis. Western blot assays, dual luciferase reporter assays, and chromatin immunoprecipitation were used to analyze the functional mechanism of lncRNA AC016727.1. Results: Our larger NSCLC cohorts validated that the lncRNA AC016727.1 was upregulated in 94 paired NSCLC tissues and correlated with poor survival. Functionally, lncRNA AC016727.1 downregulation inhibited NSCLC cell proliferation, aerobic glycolysis, EMT, and migration, inducing apoptosis. Conversely, upregulated lncRNA AC016727.1 expression exhibited the opposite effect, promoting NSCLC cell survival. Importantly, lncRNA AC016727.1 knockdown inhibited lung cancer growth and slowed the progression of lung metastasis in nude mouse models. Mechanistically, lncRNA AC016727.1 upregulated BACH1 target gene expression by acting as a sponge for miR-98-5p, thereby functioning as a competing endogenous RNA. The function of lncRNA AC016727.1 is mediated by the miR-98-5p/BACH1 axis in NSCLC cells. Meanwhile, the transcription factor HIF-1α can bind to the promoter and activate lncRNA AC016727.1 transcription. lncRNA AC016727.1 regulates HIF-1α expression via BACH1 in NSCLC and forms the lncRNA AC016727.1/BACH1/HIF-1α signaling loop under hypoxic conditions. Conclusion: Our study reveals a novel lncRNA AC016727.1/BACH1/HIF-1α signaling loop in the progression of NSCLC under hypoxic conditions, suggesting that lncRNA AC016727.1 could act as a useful biomarker for NSCLC and a new therapeutic target. [ABSTRACT FROM AUTHOR]

Propionate, a major constituent of short chain fatty acids, has recently been reported to be involved in both prokaryotic and eukaryotic lysine propionylation (Kpr). However, the propionylation characteristics of the enteric pathogen Salmonella enterica serovar Typhi (S. Typhi) following invasion of the human gut under the influence of propionate, whether virulence is affected, and the underlying mechanisms are not yet known. In the present study, we report that propionate significantly reduces the viability of S. Typhi in macrophages through intra-macrophage survival assays. We also demonstrate that the concentration of propionate and the propionate metabolic intermediate propionyl coenzyme A can affect the level of modification of PhoP by propionylation, which is tightly linked to intracellular survival. By expressing and purifying PhoP protein in vitro and performing EMSA and protein phosphorylation analyses, We provide evidence that K102 of PhoP is modified by Kpr propionate, which regulates S. Typhi viability in macrophages by decreasing the phosphorylation and DNA-binding ability of PhoP. In conclusion, our study reveals a potential molecular mechanism by which propionate reduces the viability of S. Typhi in macrophages via Kpr. Our work reported that propionate in intestinal SCFAs can be activated by PrpE to generate propionyl-CoA. Propionyl-CoA can affect the level of propionylation of PhoP of the S. Typhi two component system in a concentration-dependent manner. The phosphorylation and DNA-binding ability of PhoP is affected by propionylation at K102, which leads to reduced PhoP protein activity and ultimately affects S. Typhi virulence. [Display omitted] • Propionate reduced intracellular viability of S. Typhi. • Propionate enhanced the propionylation of PhoP. • Propionyl-CoA affected the level of propionylation. • Propionylation of K102 reduced the DNA binding affinity and phosphorylation of PhoP. • Propionylation of K102 reduced intracellular viability of S. Typhi in macrophages by inhibiting PhoP activity. [ABSTRACT FROM AUTHOR]

Background: Inflammatory biomarkers in the peripheral blood have been established as predictors for immunotherapeutic efficacy in advanced non-small cell lung cancer (NSCLC). Whether they can also predict major pathological response (MPR) in neoadjuvant setting remains unclear. Methods: In this multi-center retrospective study, 122 and 92 stage I-IIIB NSCLC patients from six hospitals who received neoadjuvant chemoimmunotherapy followed by surgery were included in the discovery and external validation cohort, respectively. Baseline and on-treatment neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) were calculated and associated with MPR. Furthermore, resected tumor samples from 37 patients were collected for RNA-sequencing to investigate the immune-related tumor microenvironment. Results: In both the discovery and validation cohorts, the on-treatment NLR, dNLR, PLR, and SII levels were significantly lower in the patients with MPR versus non-MPR. On-treatment SII remained an independent predictor of MPR in multivariate logistic regression analysis. The area under the curve (AUC) of on-treatment SII for predicting MPR was 0.75 (95%CI, 0.67–0.84) in the discovery cohort. Moreover, the predictive value was further improved by combining the on-treatment SII and radiological tumor regression data, demonstrating an AUC of 0.82 (95%CI, 0.74–0.90). The predictive accuracy was validated in the external cohort. Compared with the SII-high group, patients with SII-Low were associated with the activated B cell receptor signaling pathway and a higher intratumoral immune cell infiltration level. Conclusions: On-treatment SII was independently associated with MPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy. Further prospective studies are warranted. [ABSTRACT FROM AUTHOR]

The combination of multifunctional micromagnetic testing and neural network-based prediction models is a promising way of nondestructive and quantitative measurement of steel surface hardness. Current studies mainly focused on improving the prediction accuracy of intelligent models, but the unavoidable and random uncertainties related to instruments were seldom explored. The robustness of the prediction model considering the repeatability of instruments was seldom discussed. In this work, a self-developed multifunctional micromagnetic instrument was employed to perform the repeatability test with Cr12MoV steel. The repeatability of the instrument in measuring multiple magnetic features under both static and dynamic conditions was evaluated. The magnetic features for establishing the prediction model were selected based on the consideration of both the repeatability of the instrument and the ability of magnetic features in surface hardness evaluation. To improve the robustness of the model in surface hardness prediction, a modelling strategy considering the repeatability of the instrument was proposed. Through removing partial magnetic features with higher mean impact values from input nodes, robust evaluation of surface hardness in Cr12MoV steel was realized with the multifunctional micromagnetic instrument. [ABSTRACT FROM AUTHOR]

Maintaining the integrity and protecting the stability of tight junctions in endothelial cells is a potential therapeutic strategy against myocardial ischaemia. Laminin receptors (67LR) are highly expressed on endothelial cell membranes and are associated with endothelial barrier function. Herein, we sought to demonstrate the direct effects of pigment epithelial-derived factor (PEDF) on tight junctions between endothelial cells via 67LR during acute myocardial infarction (AMI) and elucidate its underlying mechanisms. We detected that PEDF directly increased the level of the tight junction protein zonula occludens protein 1 (ZO-1) after overexpression in vitro and in vivo using Western blotting. Evans Blue/TTC staining showed that PEDF significantly reduced the size of the infarcted myocardium. Immunofluorescence and the transwell cellular experiments suggested that PEDF significantly upregulated PI3K-AKT permeability and the distribution of ZO-1 between endothelial cells under OGD conditions. Interestingly, PEDF significantly upregulated the phosphorylation levels of PI3K-AKT-mTOR under oxygen and glucose deprivation conditions but had no significant effects on the total protein expression. The protective effect of PEDF on ZO-1 was significantly inhibited following the inhibition of PI3K-AKT-mTOR. The activation of phosphorylation of PI3K-AKT-mTOR by PEDF was blocked after silencing 67LR, as were the protective effects of PEDF on ZO-1. Therefore, we have reason to believe that PEDF increased ZO-1 expression through the 67LR-dependent PI3K-AKT-mTOR signaling pathway, thus maintaining tight junction stability and protecting cardiac function. [ABSTRACT FROM AUTHOR]

Magnetic Barkhausen noise (MBN), sensitive to the microstructure of materials, can be applied in the surface decarburization depth detection of ferromagnetic specimens. However, the effects of core microstructures on the determination results of decarburization depth have not been explored. In this study, MBN was employed to evaluate the magnetic properties of the decarburized 60Si2Mn spring steels with martensitic and pearlitic core microstructures. Spring steel samples were austenitized at different times to generate different decarburization depths. Seven magnetic features were extracted from the MBN butterfly profiles. We used the variation coefficient, linear correlation coefficient, and normalized sensitivity to discuss the influence of the core microstructures on these seven features. The different core microstructures led to a large difference in the ability of MBN features to characterize the decarburization layer depth. However, three features of MBN butterfly profiles demonstrated an approximately linear dependency (linear correlation coefficient > 94%) on surface decarburization depth and monotonically increased with the increase in depth in both core microstructures of spring steels. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to overcome the application limitations of other multi-variable regression based on polynomials due to the huge computation room and time cost. Design/methodology/approach: In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance the capacity of polynomials approximation and the manifolds optimization method was introduced to solve the co-related optimization problem. Findings: Two multi-variable Laguerre polynomials regression methods are designed. Firstly, Laguerre polynomials are combined with feature selection method. Secondly, manifolds component analysis is adopted in cascaded Laguerre polynomials regression method. Two methods are brought to enhance the accuracy of multi-variable regression method. Research limitations/implications: With the increasing number of variables in regression problem, the stable accuracy performance might not be kept by using manifold-based optimization method. Moreover, the methods mentioned in this paper are not suitable for the classification problem. Originality/value: Experiments are conducted on three types of datasets to evaluate the performance of the proposed regression methods. The best accuracy was achieved by the combination of cascade, manifold optimization and Chebyshev polynomials, which implies that the manifolds optimization has stronger contribution than the genetic algorithm and Laguerre polynomials. [ABSTRACT FROM AUTHOR]

Ferromagnetic components are susceptible to various defects after prolonged service. The defects generated in these components are diverse and exhibit irregular orientation, which may impede comprehensive defect examination using a single magnetic testing method. This paper proposes a novel magnetic measurement sensor that integrates the principles of magnetic flux leakage (MFL) and magnetic field disturbance (MFD). The combined theory is analyzed and validated through the utilization of finite element method (FEM) simulations as well as experimental investigations. By comparing simulation results with experimental data, the composite nature of the signal acquired beneath a magnetic bridge is convincingly demonstrated. In comparison to conventional MFL and MFD methods, this innovative sensor exhibits superior defect detection performance for varying angles and widths, while also addressing some inherent limitations associated with MFL and MFD principles. [ABSTRACT FROM AUTHOR]

• A convolutional neural network named FilterNet which contains three filter-type convolutional kernels was proposed to learn feature representation directly from raw magnetic Barkhausen noise (MBN). • The phenomenon of performance of a trained model declined due to the change in the angle between the electromagnetic sensor and specimens was studied. • The performance of three regression models, which are multiple linear regression, BP neural network, and the FilterNet, were compared using multi-angles MBN signals. In this paper, a novel convolutional neural network named FilterNet is proposed to learn feature representation directly from raw magnetic Barkhausen noise (MBN) for quantitatively evaluating plastic deformation. In the proposed model, three modified filter-type convolutional kernels are adopted to extract appropriate feature expressions from raw MBN. In the experimental part, a special experimental device, which could change the angle between the electromagnetic sensor and specimens, was designed to simulate the case that the performance of a trained model declined due to the change in the angle. MBN signals at 11 angles from left to right were measured. The performances of multiple linear regression (MLR), BP neural network (BP), and the FilterNet were analyzed with mean absolute error (MAE) and root-mean-square error (RMSE). MAE and RMSE of the FilterNet were smaller than the other two models at different angles and reveal the outperformance of the FilterNet. [ABSTRACT FROM AUTHOR]

The correlation between multiple patterns of micromagnetic signatures and the surface hardness of three types of carbon steels (referred as Cr12MoV steel, 45 steel, and martensitic stainless steel of 3Cr13 in Chinese standards) was investigated in this study. Back-propagation neural network (BP-NN) models were established for the quantitative prediction of surface hardness in carbon steels. The quality of the specimens used for calibration (or more precisely the data distribution of the target properties) greatly affected the accuracy of prediction models. The uniformly distributed data were more suitable for establishing high-accuracy BP-NN models. For the data which did not follow a uniform distribution, a two-step modelling strategy of classification and subsequent regression was proposed to improve the accuracy of micromagnetic and quantitative prediction of surface hardness. The proposed two-step modelling strategy integrating the K-nearest neighbor classification (KNN) algorithm with BP-NN modelling method was verified by external validation experiments. [ABSTRACT FROM AUTHOR]

Background: Idiopathic pulmonary fibrosis (IPF) is a highly heterogeneous and fatal lung disease. In addition to dense fibrous tissue, abnormal angiogenesis is also an important feature of IPF. Pigment epithelium-derived factor (PEDF) is an angiogenesis inhibitor and a potential anti-fibrous factor. The purpose of this experiment is to observe the effect of PEDF on bleomycin (BLM)-induced pulmonary fibrosis in rats.Methods: In vivo, pathological examination and detection of related factors were performed on pulmonary fibrosis induced by BLM in rats, and the temporal and spatial distribution of PEDF was investigated. Furthermore, lung gene delivery (PEDF-adeno-associated virus) was performed to investigate the effect of PEDF on pulmonary fibrosis. In vitro, lentiviral vectors were used to construct PEDF over-expression or knock out primary rat lung (PRL) fibroblasts. The effect of PEDF on fibroblast activation under TGF-β1 stimulation was evaluated, and the activation of TGF-β1/smad pathway and PPAR-γ expression (in the presence or absence of PPAR-γ inhibitors) were analyzed.Results: In vivo results showed that PEDF expression decreased during the inflammatory phase and increased during the fibrotic phase. PEDF could inhibit the progression of pulmonary fibrosis in rats. In vitro results showed that PEDF could effectively inhibit TGF-β1-stimulated fibroblast activation and reduce the production of α-SMA and collagen-I. PEDF could inhibit the TGF-β1/smad pathway by up-regulating the activity of PPAR-γ.Conclusions: PEDF can act as an anti-fibrotic factor, inhibit fibroblast activation by upregulating PPAR-γ activity and reduce BLM-induced pulmonary fibrosis in rats. [ABSTRACT FROM AUTHOR]

Magnetostrictive sensors (MsS) are widely used to generate ultrasonic guided waves of SH 0 mode for the purpose of detecting defects in plate-like structures. An MsS commonly employs a rectangular magnetostrictive strip and a sensor unit (including detection coil and magnet) to generate SH 0 waves. However, the effect of coverage range of static magnetic field (Ls) and dynamic magnetic field (L D) on the SH 0 wave generation direction has not been fully explored. So far, the cases of L S << L D and L D >> L S are seldom discussed in the development of MsS for generating SH 0 mode. In this study, the key factor governing the direction of SH 0 mode generated by FeCo strip-based MsS was experimentally clarified. The transition phenomenon in the generation direction of SH 0 wave was observed while the combination parameters crossing the control line of Ls ≈ L D. The phenomenon could be interpreted by the alterations in the operation mechanism of Wiedemann effect and reversed Wiedemann effect. As a result, the generation direction of SH 0 mode could be tuned along the static magnetic field (Ls << L D), the dynamic magnetic field (Ls >> L D) or the direction of both static and dynamic magnetic field s (Ls ≈ L D). The findings in this study is of benefit for guiding the design of MsS array with the tunable generation direction of SH 0 mode. [Display omitted] • The key factors governing the direction of SH 0 mode was experimentally clarified. • The direction of SH 0 is changed when the parameters crossing the line of L S ≈ L D. • The phenomenon can be explained by Wiedemann effect and reversed Wiedemann effect. • The study is guiding the design of MsS array with generation direction of SH 0 mode. [ABSTRACT FROM AUTHOR]

Quantitative characterization of tensile stress in electroplated nickel coatings on the copper substrate with the thickness range of 2.809 µm to 35.654 µm in the elastic stage was experimentally performed with a magnetic incremental permeability (MIP) sensor in the study. Firstly, a differential mutual-inductance sensor based on the parallel excitation of bifilar co-directional coil was proposed. With the proposed sensor, multiple signals including high-frequency eddy current (HFEC), tangential magnetic field strength, and magnetic incremental permeability butterfly curve (MIPBC) could be measured synchronously and eight typical magnetic parameters were obtained from experimental signals. Then, four parameters including the peak height of MIPBC, amplitude at cross point of MIPBC, difference frequency of HFEC, and sum frequency component of HFEC were selected to quantitatively characterize tensile stress. Experimental results showed that the four parameters depended on tensile stress and showed a parabolic trend. The parameters of the parabolic equation varied with nickel coating thickness. Finally, a polynomial surface fitting method based on the combination of the factors of thickness and tensile stress were derived with the selected four parameters and the coefficient of determination R 2 was higher than 0.9. The further comparison between theoretical results and predicted stress confirmed that the proposed MIP sensor could realize the quantitative detection of tensile stress in different nickel coatings. [Display omitted] • A multi-functional MIP sensor, with the ability of several magnetic signal measurement, was developed. • The multi-functional MIP sensor not only suppresses mutual inductance signals, but also provides compact structure. • MIP sensor accurately predicts tensile stress in electroplated nickel specimen, accounting for variations in specimen thickness. [ABSTRACT FROM AUTHOR]

Ultrasonic guided waves (UGWs) of T(0,1) mode were generated by magnetostrictive sensors (MsS) to perform 36-day monitoring of a defective welded pipe elbow. A hydrochloric acid pool was employed to accelerate the corroded defect accumulation process, and a total of 11 defect levels were recorded. The envelope of UGWs was found to be insufficient to indicate the defect level lower than 6 due to the instability of monitoring signals. To achieve the high-quality display of the corrosion accumulation process, the energy of concerned wave packets was introduced to act as a new indicator. To suppress the influences of sensor deterioration, the energy of wave packet corresponding to the elbow region (Edefect) was divided by the energy of wave packet representing the feature reflectors (such as obstacle, free end and welds) in the straight pipe section. The compensated energy of wave packet demonstrated the stepped growth at each level of defect under the operation frequency of 64 kHz. The smoothed curve of Edefect/Eweld was the self-compensation to MsS deterioration and could achieve the highly sensitive display of the corrosion defect accumulation process since the value of Edefect increased at the cost of subsequent weld waves' energy. [ABSTRACT FROM AUTHOR]

The magnetic frequency mixing method was investigated for fatigue damage evaluation of medium carbon steel. Two types of magnetic signal, the magnetic flux density and the tangential magnetic field, are detected and analyzed. Two parameters, the magnetic frequency mixing factor and the power law coefficient, are proposed for magnetic frequency mixing effect characterization. On-line and off-line magnetic frequency mixing experiments were performed on specimens with various degrees of fatigue. Experimental results show that the two parameters changed along with the fatigue cycles with monotonic linear regularity and both parameters can be used for fatigue damage evaluation of medium carbon steel. [ABSTRACT FROM AUTHOR]

• A multi-channel magnetostrictive sensor was designed and developed to effectively excite SH0 mode guided waves. • A rotating total focus imaging method is proposed to detect defects of varying sizes and depths in large-scale plates. • This sensor and imaging method enable precise localization of defects, achieving a minimum relative position error of 1.7%. To address the challenge of ultrasonic detection of multiple defects in large-scale tank bottom plates, a multi-channel magnetostrictive sensor was designed and developed to effectively excite SH (Shear Horizontal) mode guided waves. The optimal overall scheme of the sensor was obtained by considering the sensor excitation energy, coupling efficiency, and fabrication process. Through experimental tests, the consistency of each channel of the sensor is evaluated, and the center frequency and detection range of the sensor are measured. To detect defects of varying sizes and depths in steel plates, a rotating total focus imaging method is proposed. And we conducted experiments using a multi-channel magnetostrictive sensor to achieve SH0 guided wave imaging of multiple defects across the full domain. Our experimental results demonstrate that, across 8 rotations, we achieved a minimum relative position error of 4.32% and a minimum absolute angle error of 2.16°. Our research provides an effective solution for ultrasonic detection of tank bottom plates, and the proposed method is also applicable for defect detection in other large plate-like structures. [ABSTRACT FROM AUTHOR]

• The ultrasonic SH guided wave detection of the defects at the rail head and rail bottom was successfully realized. • A three-dimensional finite element model of a switch rail was established to accurately predict the defect information. • The influences of the switch rail model were analyzed in detail and the model was experimentally validated. • The finite element model calibrated with experimental results can be used to simulate guided wave detection at any location with any defect. A switch rail is an important part of the high-speed railway system, but it is highly susceptible to defects during service, which threat traffic safety. A switch rail has an asymmetric variable cross-section structure, which makes it challenging to detect its defects with ultrasonic testing. In this study, the finite element model of switch rails and the ultrasonic SH guided wave detection of groove defects were explored. The three-dimensional finite element model of switch rails with the same sizes used under working conditions was established. Furthermore, the influences of grid division method, switch mechanism setting method, and root end variable cross-section grid type on guided wave propagation in the model were analyzed in detail. The switch rail model was experimentally validated. The ultrasonic SH guided wave detection of the defects at the rail head and rail bottom was successfully realized and the echo signals from other special structures of switch rail were also obtained. The finite element model calibrated with experimental results could be used to simulate guided wave detection at any location with any defect. The calibrated model could optimize the switch rail guided wave detection scheme and guide signal identification. The study provides an important basis for the inspection and monitoring of switch rails. [ABSTRACT FROM AUTHOR]

Abstract So far, many regression works have been implemented by using linear regression methods. Although more accurate predictions results could be obtained, polynomial regression is not used as much as compared to linear regression in real applications due to occurrence of coefficient explosion. To overcome this problem, two regression algorithms using Chebyshev polynomials of class 2 based on cascade regression and feature selection are proposed in this paper. In the experimental part, three separate experiments including function interpolation and real-case regression were conducted on three datasets to test the proposed algorithms. As shown by the experimental results, the proposed algorithms performed better than other regression methods in terms of both accuracy and processing time. [ABSTRACT FROM AUTHOR]