Search

As a crucial high-performance material, nickel-based superalloys inevitably generate residual stresses during processing, manufacturing, and usage. The mechanical properties of nickel-based superalloys are significantly reduced by residual stress, which becomes one of the important factors restricting material reliability. The systematic analysis of residual stresses in nickel-based superalloys throughout the entire manufacturing and usage processes is insufficient. The residual stress generation factors, measurement methods, prediction models, and control methods in nickel-based superalloys in recent years are summarized in this paper. The current challenge and future development trends in the research process of nickel-based superalloy residual stress are also presented. A theoretical reference for further research on residual stresses in nickel-based superalloys can be provided in this review. [ABSTRACT FROM AUTHOR]

Introduction: Aplastic anemia (AA) and hypoplastic myelodysplastic syndrome (MDS‐h) are bone marrow failure disease and difficult to distinguish merely by morphological analysis. In this study, we investigated the value of flow cytometry (FCM) in the differential diagnosis of AA and MDS‐h. Methods: We included 822 patients (626 control, 69 AA, 22 MDS‐h and 105 dilution patients) from January 2017 to December 2022 for a retrospective study. Bone marrow myeloid progenitor (MP) cell and mature lymphocytes proportions were analyzed by FCM. The ratio of MP cell proportion and mature lymphocytes proportion, MPLR, was calculated. Data were compared by Kruskal–Wallis test. Differential diagnostic efficacy was evaluated by receiver operating characteristic (ROC) curve. Cutoff value was determined by the maximum Youden index. Results: Bone marrow MP cell proportion and MPLR of MDS‐h patients were higher than AA patients. Mature lymphocytes proportion of MDS‐h patients was lower than AA patients. Area under ROC curve (AUC of ROC) of MP cell proportion, MPLR and mature lymphocytes proportion to distinguish AA from MDS‐h were 0.992, 0.988, and 0.850, respectively. Moreover, MPLR of dilution patients was higher than AA patients but lower than MDS‐h patients. The AUC of ROC curves of MPLR to distinguish MDS‐h and AA from dilution were 0.854 and 0.871, respectively. Conclusion: Bone marrow MP cell proportion and MPLR can effectively discriminate AA from MDS‐h with similar differential efficacy, which is higher than mature lymphocytes proportion. Moreover, MPLR can evaluate the quality of bone marrow aspirates, which would interfere with the differential diagnosis. [ABSTRACT FROM AUTHOR]

Networked control system (NCS) is widely used in various fields, but the nonlinear of the controlled plants and the limited network bandwidth bring stability issues, which will affect the performance or even instability of the NCS. To address these aforementioned challenges, this paper proposes a novel nonlinear NCS framework, by considering network‐induced delay, adaptive event‐triggered mechanism, state quantization, control input quantization, and external disturbance based on T‐S fuzzy model. Also, based on this framework, we derive an H∞$$ {H}_{\infty } $$ stability criterion for NCS using linear matrix inequality and propose a collaborative design method for event triggers and controllers. Finally, we verify the superiority and effectiveness of the method by giving two numerical examples. [ABSTRACT FROM AUTHOR]

This article discusses the use of CRISPR-Cas9 gene editing technology to silence the 2S albumin genes in peanuts, which are known to be potent allergens. The researchers successfully edited the genes using a multiplex gene editing strategy and confirmed the elimination of the allergenic proteins through protein analysis. However, further testing is needed to determine if the edited peanuts have reduced allergenicity. The study was supported by Ukko, Inc. and the data supporting the findings are available in the supplementary material of the article. [Extracted from the article]

This paper proposes a decentralized dynamic event-triggered control method of aero-engine T-S fuzzy system, aiming to achieve both exponential stabilization of aero-engine networked control systems (NCSs) and reduction in network communication loads. Firstly, a novel decentralized dynamic event-triggered mechanism (DETM) is developed to regulate data transmissions in each communication channel independently. The closed-loop model is then established, by considering network-induced delays, dynamic quantization effects, external disturbance, and parameter perturbation. Stability criteria are derived using the Lyapunov–Krasovskii method, and a collaborative design method based on linear matrix inequalities (LMIs) is proposed for controller, quantizers, and DETM. Lastly, a parameter tuning method based on the iL-SHADE algorithm is proposed for better feasibility of the obtained LMIs. Simulation results show that the proposed method has good robustness to multi-uncertainty conditions and can effectively reduce communication resource wastage while ensuring well control performance across a wide range of flight envelopes. [ABSTRACT FROM AUTHOR]

Objectives: 1. Determine the feasibility and efficiency of local magnetic targeting delivery of gadolinium (Gad) contrast to the inner ear in rodents. 2. Assess any potential ototoxicity of magnetic targeting delivery of Gad in the inner ear. 3. Study the utility of magnetic targeting delivery of Gad to visualize and quantify endolymphatic hydrops (EH) in a transgenic mouse model. Study Design: Controlled in vivo animal model study. Methods: Paramagnetic Gad was locally delivered to the inner ear using the magnetic targeting technique in both rat and mouse models. Efficiency of contrast delivery was assessed using magnetic resonance imaging (MRI). Ototoxicity of Gad was examined with histology of the cochlea and functional audiological tests. The Phex mouse model was used to study EH, hearing loss, and balance dysfunction. Magnetic targeting delivery of Gad contrast was used in the Phex mouse model to visualize the effects of EH using MRI. Results: Magnetic targeting improved the delivery of Gad to the inner ear and the technique was reproducible in both rat and mouse models. The delivery method did not result in microstructural damage or any significant hearing loss in a normal animal. Magnetic targeting of Gad in the Phex mouse model allowed detailed visualization and quantification of EH. Conclusion: This study provided the first evidence of the effectiveness and efficiency of the local magnetic targeting delivery of gadolinium contrast to the inner ear and its application to the visualization and quantification of EH. Laryngoscope, 133:914–923, 2023 [ABSTRACT FROM AUTHOR]

aim of this research was to determine whether systemic inflammatory indicators, including aggregate index of systemic inflammation (AISI), neutrophils lymphocyte to platelet ratio (NLPR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI), are related to bone mineral density (BMD) in perimenopausal and postmenopausal women. Methods: One hundred and eighty-one perimenopausal and 390 postmenopausal women were enrolled in this cross-sectional study. Continuous variables by analysis of variance and Kruskal Wallis test for comparing the clinical characteristics. Linear regression analysis was conducted to investigate the associations between inflammatory indicators with BMD. The comparison between the subgroups was performed using the nonparametric test and the T-test. Results: AISI, NLPR, SII, and SIRI quartile values were inversely associated with BMD in menopausal women (P = 0.021; P = 0.047; P < 0.001; P < 0.001, respectively). After adjusting for confounding factors, four inflammatory indicators remained significantly associated with BMD (all P for trend < 0.001). Analysis according to menopausal status demonstrated that AISI, SII, and SIRI were significantly correlated with mean femoral neck BMD in postmenopausal women (P for trend = 0.015, 0.004, and 0.001), but not significantly associated with BMD in perimenopausal women (P for trend = 0.248, 0.054, and 0.352) after adjustment for covariates. Conclusion: The quartile values of AISI, SII, and SIRI were inversely associated with BMD in postmenopausal women, following adjustment for individual variables, hormone profiles and glucolipid metabolism profiles. AISI, SII, and SIRI have potential to be important tools for screening and prevention of bone loss in menopausal women in future clinical practice. [ABSTRACT FROM AUTHOR]

Background: Insulin-like peptide 5 (INSL5) is involved in both reproductive and metabolic processes in polycystic ovary syndrome (PCOS). This study aimed to evaluate the relationship between INSL5 and anti-Müllerian hormone (AMH). Methods: A retrospective case–control study was conducted in a university-based reproductive centre between December 2019 and January 2021. We included 117 women with PCOS and 100 healthy subjects from Zhejiang Province. All subjects were divided into four groups (1st–4th) based on quartiles of serum INSL5 levels. Serum INSL5 concentration was assayed using an enzyme-linked immunosorbent assay. Results: A significant direct association was observed between serum INSL5 and AMH levels in women with PCOS. The mean AMH level in the 1st–4th INSL5 level quartiles were 4.64, 5.20, 6.46, and 9.48 ng/ml, respectively (P < 0.001). After adjusting for age, body mass index, metabolic indices, and serum levels of oestradiol and total testosterone, AMH levels remained positively and significantly associated with INSL5 levels (P for trend < 0.001). The diagnostic value of AMH was better than that of INSL5. Conclusions: INSL5 and AMH levels were significantly correlated and elevated in women with PCOS. INSL5 and AMH might be associated with increased androgen secretion and chronic anovulation in PCOS. [ABSTRACT FROM AUTHOR]

Widespread adoption of additive manufacturing (AM) is hindered by the low quality and reproducibility of printed parts. In-situ quality monitoring technologies provide early defect detection and correction capability for AM processes and are crucial for part quality assurance. Research on in-situ monitoring and control of AM is exceptionally challenging due to the numerous variations and complex reactions in AM. This study has developed a novel unsupervised recognition model for the quality of parts printed by directed energy deposition (DED). This model consists of a long short-term memory-based autoencoder (LSTM-Autoencoder) and a K-means clustering. The LSTM-Autoencoder automatically extracts features from spectra collected during the DED process, and the K-means clustering model is employed for the deposition quality classification. Experimental verifications are conducted on the quality recognition of Al7075 alloy depositions printed under different conditions by varying the laser power, printing speed, and powder delivery rate. The results show that the proposed method can discern between the unqualified depositions with rough surfaces and high porosity from the qualified depositions correctly. This proposed LSTM-Autoencoder is data-driven and thus may be applied to printing conditions not tested within this work. [ABSTRACT FROM AUTHOR]

Key message: Expression of Cre recombinase by AtRps5apro or AtDD45pro enabled Cre/lox-mediated recombination at an early embryonic developmental stage upon crossing, activating transgenes in the hybrid cowpea and tobacco. Genetic engineering ideally results in precise spatiotemporal control of transgene expression. To activate transgenes exclusively in a hybrid upon fertilization, we evaluated a Cre/lox-mediated gene activation system with the Cre recombinase expressed by either AtRps5a or AtDD45 promoters that showed activity in egg cells and young embryos. In crosses between Cre recombinase lines and transgenic lines harboring a lox-excision reporter cassette with ZsGreen driven by the AtUbq3 promoter after Cre/lox-mediated recombination, we observed complete excision of the lox-flanked intervening DNA sequence between the AtUbq3pro and the ZsGreen coding sequence in F1 progeny upon genotyping but no ZsGreen expression in F1 seeds or seedlings. The incapability to observe ZsGreen fluorescence was attributed to the activity of the AtUbq3pro. Strong ZsGreen expression in F1 seeds was observed after recombination when ZsGreen was driven by the AtUbq10 promoter. Using the AtDD45pro to express Cre resulted in more variation in recombination frequencies between transgenic lines and crosses. Regardless of the promoter used to regulate Cre, mosaic F1 progeny were rare, suggesting gene activation at an early embryo-developmental stage. Observation of ZsGreen-expressing tobacco embryos at the globular stage from crosses with the AtRps5aproCre lines pollinated by the AtUbq3prolox line supported the early activation mode. [ABSTRACT FROM AUTHOR]

Background: Epithelial ovarian carcinoma (EOC) is a malignant tumor with high motility in women. Our previous study found that dysregulated nucleoside-triphosphatase cancer-related (NTPCR) was associated with the prognosis of EOC patients, and thus, this present study attempted to explore the potential roles of NTPCR in disease progression. Methods: Expressed level of NTPCR was investigated in EOC tissues by RT-qPCR and Western blot analysis. NTPCR shRNA and overexpression vector were generated and transfected into OVCAR-3 or SKOV3 cells to detect the effect of NTPCR on cell proliferation, cell cycle, cell migration, and invasion. Transcriptomic sequencing and metabolite profiling analysis were performed in shNTPCR groups to identify transcriptome or metabolite alteration that might contribute to EOC. Finally, we searched the overlapped signaling pathways correlated with differential metabolites and differentially expressed genes (DEGs) by integrating analysis. Results: Comparing para-cancerous tissues, we found that NTPCR is highly expressed in cancer tissues (p < 0.05). Overexpression of NTPCR inhibited cell proliferation, migration, and invasion and reduced the proportion of S- and G2/M-phase cells, while downregulation of NTPCR showed the opposite results. RNA sequencing analysis demonstrated cohorts of DEGs were identified in shNTPCR samples. Protein–protein interaction networks were constructed for DEGs. STAT1 (degree = 43) and OAS2 (degree = 36) were identified as hub genes in the network. Several miRNAs together with target genes were predicted to be crucial genes related to disease progression, including hsa-miR-124-3p , hsa-miR-30a-5p , hsa-miR-146a-5 , EP300 , GATA2 , and STAT3. We also screened the differential metabolites from shNTPCR samples, including 22 upregulated and 22 downregulated metabolites. By integrating transcriptomics and metabolomics analysis, eight overlapped pathways were correlated with these DEGs and differential metabolites, such as primary bile acid biosynthesis, protein digestion, and absorption, pentose, and glucuronate interconversions. Conclusion: NTPCR might serve as a tumor suppressor in EOC progression. Our results demonstrated that DEGs and differential metabolites were mainly related to several signaling pathways, which might be a crucial role in the progression of NTPCR regulation of EOC. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC) development. However, prognosis-associated lncRNAs (PALs) for OC have not been completely elucidated. Our study aimed to identify the PAL signature of OC. A total of 663 differentially expressed lncRNAs were identified in the databases. According to the weighted gene coexpression analysis, the highly correlated genes were clustered into seven modules related to the clinical phenotype of OC. A total of 25 lncRNAs that were significantly related to overall survival were screened based on univariate Cox regression analysis. The prognostic risk model constructed contained seven PALs based on the parameter λmin, which could stratify OC patients into two risk groups. The results showed that the risk groups had different overall survival rates in both The Cancer Genome Atlas (TCGA) and two verified Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses confirmed that the risk model was an independent risk factor for OC. Gene enrichment analysis revealed that the identified genes were involved in some pathways of malignancy. The competitive endogenous RNA (ceRNA) network included five PALs, of which four were selected for cell function assays. The four PALs were downregulated in 33 collected OC tissues and 3 OC cell lines relative to the control. They were shown to regulate the proliferative, migratory, and invasive potential of OC cells via Cell Counting Kit-8 (CCK-8) and transwell assays. Our study fills the gaps of the four PALs in OC, which are worthy of further study. [ABSTRACT FROM AUTHOR]

Anomaly detection is the cornerstone for the health management of rolling element bearings. The unsupervised learning model for anomaly detection driven only by normal data has received increasing attention in recent years. In this article, an innovative deep-learning-based model, namely, memory residual regression autoencoder (MRRAE), is developed to improve the accuracy of anomaly detection in bearing condition monitoring. The memory module and autoregressive estimator are applied to calculate the probability density distribution of the latent memory residual representation. The reconstruction errors and surprisal values of the proposed model are used to detect the abnormal condition of bearing. To verify the superiority of the proposed method in anomaly detection, two sets of run-to-failure experimental data set gathered from the laboratories are studied and analyzed. The result demonstrates that the proposed MRRAE model achieves superior performance compared with several conventional and deep-learning-based anomaly detection methods. Furthermore, the proposed method pays close attention to the special structure of bearing vibration signal and provides a new way for explaining the decision-making processes of deep neural networks. [ABSTRACT FROM AUTHOR]

This article investigates a real-time nondestructive measurement method of the seam strength using the optical spectroscopy and ensemble learning in laser beam welding. First, a linear positive relationship between the seam strength and acquired optical spectrum signal was established. Then, a new feature reduction method was proposed to extract the independent feature set with low correlation and high diversity. Finally, a hybrid classification model is proposed based on fast independent component analysis (ICA) and extremely randomized trees (ET). The model was thoroughly verified with various welding experiments and careful comparison with decision tree (DT), extreme gradient boosting DT (XGBoost), and support vector machine (SVM). More importantly, driven by the monitoring data and random forest with fast independent component analysis (RFICA)-ET model, it was found that Al I at 669.8673 nm and Ar I at 610.5635 nm were the two key elements in the dynamic plasma for accurate seam strength measurement. [ABSTRACT FROM AUTHOR]

SUMMARY: Cowpea (Vigna unguiculata (L.) Walp.) is one of the most important legume crops planted worldwide, but despite decades of effort, cowpea transformation is still challenging due to inefficient Agrobacterium‐mediated transfer DNA delivery, transgenic selection and in vitro shoot regeneration. Here, we report a highly efficient transformation system using embryonic axis explants isolated from imbibed mature seeds. We found that removal of the shoot apical meristem from the explants stimulated direct multiple shoot organogenesis from the cotyledonary node tissue. The application of a previously reported ternary transformation vector system provided efficient Agrobacterium‐mediated gene delivery, while the utilization of spcN as selectable marker enabled more robust transgenic selection, plant recovery and transgenic plant generation without escapes and chimera formation. Transgenic cowpea plantlets developed exclusively from the cotyledonary nodes at frequencies of 4% to 37% across a wide range of cowpea genotypes. CRISPR/Cas‐mediated gene editing was successfully demonstrated. The transformation principles established here could also be applied to other legumes to increase transformation efficiencies. Significance Statement: The tissue culture and transformation technology developed herein represents a significant advance in Agrobacterium‐mediated transformation and CRISPR/Cas‐mediated genome editing of an important orphan crop, cowpea (Vigna unguiculata (L.) Walp.). The principles established in this study have the potential to improve the transformation and editing efficiencies not only for cowpea, but also for other legume species, such as soybean (Glycine max) and common bean (Phaseolus vulgaris). [ABSTRACT FROM AUTHOR]

Strict industry demands necessitate better penetration classification in gas tungsten arc welding of aluminum alloys. An innovative classification method, namely time–frequency spectrogram based convolutional neural network (TF-CNN), has been developed in this article. The logarithmic time–frequency spectrograms are used to interpret the raw arc sound data in the time–frequency domain and served as the input of an optimized convolutional neural network (CNN) model for welding quality classification. The leaky rectified linear unit activation function and root mean square prop optimizer are utilized to improve the property of CNN. Effective arc sound features are extracted automatically by the CNN model. The proposed method is experimentally verified to recognize four penetration states with an average accuracy of 98.2%, which significantly outperforms the four typical comparison models. The generation mechanism and characteristics of arc sound are discussed as the adaptive feature extraction of TF-CNN. These studies expand the application scope of CNN to intelligent welding and achieve notable effects. [ABSTRACT FROM AUTHOR]

Background: Birthweight is an important indicator during the fetal development process to protect the maternal and infant safety. However, birthweight is difficult to be directly measured, and is usually roughly estimated by the empirical formulas according to the experience of the doctors in clinical practice.Methods: This study attempts to combine multiple electronic medical records with the B-ultrasonic examination of pregnant women to construct a hybrid birth weight predicting classifier based on long short-term memory (LSTM) networks. The clinical data were collected from 5,759 Chinese pregnant women who have given birth, with more than 57,000 obstetric electronic medical records. We evaluated the prediction by the mean relative error (MRE) and the accuracy rate of different machine learning classifiers at different predicting periods for first delivery and multiple deliveries. Additionally, we evaluated the classification accuracies of different classifiers respectively for the Small-for-Gestational-age (SGA), Large-for-Gestational-Age (LGA) and Appropriate-for-Gestational-Age (AGA) groups.Results: The results show that the accuracy rate of the prediction model using Convolutional Neuron Networks (CNN), Random Forest (RF), Linear-Regression, Support Vector Regression (SVR), Back Propagation Neural Network(BPNN), and the proposed hybrid-LSTM at the 40th pregnancy week for first delivery were 0.498, 0.662, 0.670, 0.680, 0.705 and 0.793, respectively. Among the groups of less than 39th pregnancy week, the 39th pregnancy week and more than 40th week, the hybrid-LSTM model obtained the best accuracy and almost the least MRE compared with those of machine learning models. Not surprisingly, all the machine learning models performed better than the empirical formula. In the SGA, LGA and AGA group experiments, the average accuracy by the empirical formula, logistic regression (LR), BPNN, CNN, RF and Hybrid-LSTM were 0.780, 0.855, 0.890, 0.906, 0.916 and 0.933, respectively.Conclusions: The results of this study are helpful for the birthweight prediction and development of guidelines for clinical delivery treatments. It is also useful for the implementation of a decision support system using the temporal machine learning prediction model, as it can assist the clinicians to make correct decisions during the obstetric examinations and remind pregnant women to manage their weight. [ABSTRACT FROM AUTHOR]

Background: Inflammatory response state is related to the pathogenesis of gestational diabetes mellitus (GDM).Objective: To investigate the changes of serum sex hormone-binding globulin (SHBG), homocysteine (Hcy), and hypersensitive CRP (hs-CRP) levels during pregnancy and their relationship with GDM.Methods: The nested case-control study method was used. Sixty nonobese single pregnant women diagnosed with GDM were divided into the GDM group (GDM, n = 60), together with another 60 pregnant women with normal glucose tolerance who were matched in the same period and divided into the control group (control, n = 60). The serum Hcy, hs-CRP, and SHBG levels were measured.Results: The serum levels of Hcy and hs-CRP were significantly higher in the GDM group compared with the control group, and serum levels of SHBG was significantly lower in the GDM group compared with the control group at different stages of pregnancy. The serum levels of Hcy and hs-CRP in pregnant women increased with the increase of gestational age, and serum levels of SHBG decreased with the increase of gestational age. Increased Hcy and hs-CRP levels in the second trimester and decreased SHBG levels in the first trimester were related to GDM. The odds ratio (OR) and 95% confidence interval (CI) were as follows: OR: 4.5, 95% CI: 1.5-13.0; OR: 4.2, 95% CI: 1.5-10.1; and OR: 0.4, 95% CI: 0.3-0.7, respectively.Conclusion: Increased Hcy and hs-CRP in the second trimester and decreased SHBG in the first trimester were independent predictors of GDM, which provides a new idea for early prevention and treatment of GDM. [ABSTRACT FROM AUTHOR]

Background: To determine whether advanced maternal age (AMA) causes changes in the maternal serum markers of Trisomy 21, 18 and open neural tube defects (ONTD) during the second trimester of pregnancy. Our research aims to develop new cut-off values for AMA in order to reduce the need for further invasive testing.Methods: This retrospective cohort study involved 12,739 pregnant women with AMA and 197,101 pregnant women with non-AMA. We then compared the two groups with respect to the positive rate and positive predictive value (PPV) of Trisomy 21, 18 and ONTD. Pregnant women with Trisomy 21, 18 and ONTD were diagnosed by karyotyping the amniotic fluid and by ultrasound diagnosis.Results: Compared to the non-AMA group, the multiple of the median (MOM) of free beta- human chorionic gonadotropin (free β-hCG), alpha-fetoprotein (AFP), and the risk value forTrisomy 21, were significantly higher in the AMA group (all P < 0.001). The positive rates of Trisomy 21, 18, and ONTD in the AMA group were significantly higher than those in the control group (all P < 0.001). In the AMA group, the PPVs for Trisomy 21 and other deformities were significantly higher (all P < 0.001), although the PPVs for Trisomy 18 and ONTD were similar to those of the non-AMA group. The area under the curve (AUC) values for the AMA group were higher than the non-AMA group, based on free β-hCG MoM, AFP MoM, and the risk value of Trisomy 21. The cut-off value for the risk value of Trisomy 21 was 1/172 for the AMA, group and 1/780 for the non-AMA group.Conclusions: The positive rates for Trisomy 21, 18 and ONTD, and the PPV for Trisomy 21 and other deformities were significantly higher in the AMA group. It is essential for pregnant women with AMA to be tested using appropriate cut-off values of serum markers screening for Trisomy 21 during the second trimester of pregnancy to improve the efficacy of prenatal screening and reduce the need for further invasive testing. [ABSTRACT FROM AUTHOR]

Copyright of Climacteric is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The fast kurtogram is one of the most commonly applied methods for detecting rolling element bearing faults, and has been proven to be to be effective in most cases. However, the shortcomings of the kurtosis index limit the robustness and universality of the method, in that the kurtosis index is sensitive to single impulses with large amplitudes, and the segmentation of the spectrum is not adaptive to different signals. Moreover, fast kurtogram segments the spectrum evenly, which makes the method less adaptive. Therefore, a new diagnosis method for denoising signals, known as the VMD-Scale Space Based hoyergram, is proposed in this paper. Firstly, parameter-optimized Variation Mode Decomposition (VMD) is applied to the signal to calculate the center frequency of each sub-signal, referred to as the Intrinsic Mode Function (IMF). Secondly, the spectrum of the vibration signal is smoothed by means of scale space theory, and the local minimum between each two center frequencies is determined as the boundary. Thirdly, the specific filter center frequency and filter bandwidth are obtained via hoyergram, in which the kurtosis index of the fast kurtogram is replaced by the Hoyer index, and the spectrum is segmented based on its distribution. The frequency band with the largest Hoyer index value contains the impact information. Finally, the periodicity impact can be observed in the corresponding envelope spectrum. The proposed method improves on the traditional fast kurtogram. The analysis results for both simulated and experimental signals verify the effectiveness of the proposed method in rolling bearing fault diagnosis. [ABSTRACT FROM AUTHOR]

Copyright of Gynecological Endocrinology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: Accumulative evidence shows that follicle stimulating hormone (FSH) is associated with metabolic disorders. We aimed to ascertain the relationship between FSH, blood glucose and lipid metabolism in general perimenopausal women. Methods: This cross‐sectional study analyzed 2121 perimenopausal women aged 40–54 years in Zhejiang Province from January 2016 to December 2018. Regression analysis was performed to assess the relationship between FSH and metabolic parameters. Results: Serum FSH had a significant inverse association with fasting plasma glucose (P < 0.05) and triglycerides (TG) (P < 0.01) in perimenopausal women. However, after adjusting for body mass index, there was no significant association between FSH and fasting plasma glucose. In a model fully adjusted for demographic variables, estradiol, body mass index, high‐density lipoprotein, low‐density lipoprotein, homocysteine, systolic blood pressure and blood viscosity, a significant association still existed between FSH and TG (standardized β = −0.095; R2 = 0.155; P = 0.002). Conclusion: Overall, FSH is negatively associated with metabolic parameters, especially TG, in perimenopausal women. These results indicated that FSH might be a biomarker for the primary prevention of disorders with lipid metabolism during the menopausal period. [ABSTRACT FROM AUTHOR]

Copyright of Gynecological Endocrinology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The application of the existing complex network in fault diagnosis is usually modelled based on the time domain, resulting in the loss of sign frequency-domain features, and the extracted topology features of network are too macroscopic and insensitive to local changes within the network. This paper proposes a new method of local feature extraction based on frequency complex network (FCN) decomposition and builds a new complex network structure feature on this basis, namely, subnetwork average degree. The variation law of signals in frequency domain is obtained with the aid of the structural features of complex network. The local features that are sensitive to local changes of the network are applied to characterize the whole network, with flexible application and without limitation in mechanism. The average degree of subnetwork could be regarded as feature parameters for rolling bearing fault diagnosis and degradation state recognition. Analysis on the experimental data and bearing life cycle data shows that the method proposed in this paper is effective, revealing that the extracted features have effective separability and high accuracy in fault recognition and the degradation detection of the life cycle of rolling bearings combined with neural networks. Moreover, the proposed method has reference value for the processing and recognition of other nonstationary signals. [ABSTRACT FROM AUTHOR]

Copyright of Gynecological Endocrinology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The vibration signals of rotating machinery are frequently disturbed by background noise and external disturbances because of the equipment’s particular working environment. Thus, robustness has become one of the most important problems in identifying the unbalance of rotor systems. Based on the observation that external disturbance of the unbalance response often displays sparsity compared with measured vibration data, we present a new robust method for identifying the unbalance of rotor systems based on model residual sparsity control. The residual model is composed of two parts: one part takes regular measurements of noise, while the other part evaluates the impact of external disturbances. With the help of the sparsity of external disturbances, the unbalance identification is converted into a convex optimization problem and solved by a sparse signal reconstruction algorithm. Experiment results have shown that the proposed method is robust and effective in identifying the unbalance of rotor systems in a complex environment, improving the precision of unbalance estimation and simplifying the balancing process. [ABSTRACT FROM AUTHOR]

Abstract: This paper explores the feasibility of applying genetic programming (GP) to classify wear particles. A marking threshold filter is proposed to preprocess ferrographic images before optimising the feature space of wear particles using GP. Subsequently, evolved features by GP are quantitatively evaluated by the Fisher criterion and distance fitness function, and clustering performance is evaluated qualitatively. The evolved features are compared with a conventional feature set as the inputs to support vector machines, probabilistic neural networks, and k‐nearest neighbour. Results demonstrated that the evolved features indicated a significant improvement in classification accuracy and robustness compared with conventional features. Finally, 3 typical wear particles, sliding, cutting, and oxidative, are successfully classified. [ABSTRACT FROM AUTHOR]

Aluminum alloy is the main structure material in aerospace industry. Online defect detection for aluminum alloy in pulsed gas tungsten arc welding (GTAW) is still challenging, especially for increasing application of robotics. This paper presents an intelligent methodology for real-time evaluation of weld penetration defects based on arc audible sound sensing for aluminum alloy in robotic-pulsed GTAW. The generation mechanism of arc sound was investigated using correlation analysis, high-speed camera observing and frequency spectrum analysis before denoising of arc sound. Two feature selection approaches based on Fisher distance and principal component analysis (PCA) were developed to select the frequency components related to seam defects, and then, their performance were qualitatively and quantitatively analyzed. Finally, a new classification model integrating support vector machine with grid search optimization and cross-validation (SVM-GSCV) was established to identify underpenetration, normal penetration, and burning through. The proposed methodologies were verified to be effective with high accuracy and robustness. This paper can provide some guidance for condition monitoring of additive manufacturing (AM) or process industry. [ABSTRACT FROM AUTHOR]

Our previous demonstrated that macrophage colony‑stimulating factor (M‑CSF) stimulated the production of estradiol (E2) and progesterone (P) in luteinized granulosa cells (GCs), and that its secretion may be regulated by follicle‑stimulating hormone (FSH). The present study aimed to examine the effect of M‑CSF alone or with Letrozole treatment on the function of non‑luteinizing granulosa cells, using the COV434 cell line, and its interaction with FSH. Human luteinized granulosa cells (LGC) were isolated from the follicular fluid of superovulated infertile patients (average age, 30.8±2.1 years) undergoing an intracytoplasmic sperm injection. The LGC were cultured with various concentrations of recombinant human macrophage colony stimulating factor (rhM‑CSF; 0, 10, 25, 50 or 100 ng/ml), rhM‑CSF+Letrozole (10‑6 mol/l), rhFSH (0, 10, 25, 50 or 100 IU/ml), or rhFSH+Letrozole (10‑6 mol/l). E2 concentrations in the media were measured using ELISA. The expression levels of the FSH receptor and the M‑CSF receptor were detected via reverse transcription‑quantitative polymerase chain reaction. Following COV434 cell treatment with M‑CSF, cell proliferation was quantified using the MTS assay and protein expression was detected by western blotting. It was demonstrated that M‑CSF and FSH stimulated the production of E2. The production of FSH receptors was enhanced by rhM‑CSF or rhM‑CSF+Letrozole in vitro in a dose‑dependent manner. It was observed that rhFSH promoted the expression of the M‑CSF receptor, at a certain concentration. Proliferation of COV434 cells increased in a dose‑dependent manner following treatment with RhM‑CSF. Furthermore, M‑CSF induced the phosphorylation of c‑Jun N‑terminal kinase (JNK) and p38; however, the level of E2 in the medium was not altered when the cells were pretreated with the JNK inhibitor SP600125 or the p38 inhibitor SB203580. The present study suggested that M‑CSF may be important in regulating the response of GCs to gonadotropin and may have a promotive effect in the early phase of follicular development. The biological effects of M‑CSF may partially be attributed to activation of the JNK and p38 signaling pathways. M‑CSF may represent a novel follicular development regulator agent in the future. [ABSTRACT FROM AUTHOR]

The most potent toxins secreted by pathogenic bacteria contain enzymatic moieties that must reach the cytosol of target cells to exert their full toxicity. Toxins such as anthrax, diphtheria, and botulinum toxin all use three well-defined functional domains to intoxicate cells: a receptor-binding moiety that triggers endocytosis into acidified vesicles by binding to a specific host-cell receptor, a translocation domain that forms pores across the endosomal membrane in response to acidic pH, and an enzyme that translocates through these pores to catalytically inactivate an essential host cytosolic substrate. The homologous toxins A (TcdA) and Toxin B (TcdB) secreted byClostridium difficileare large enzyme-containing toxins that for many years have eluded characterization. The cell-surface receptors for these toxins, the non-classical nature of the pores that they form in membranes, and mechanism of translocation have remained undefined, exacerbated, in part, by the lack of any structural information for the central ∼1000 amino acid translocation domain. Recent advances in the identification of receptors for TcdB, high-resolution structural information for the translocation domain, and a model for the pore have begun to shed light on the mode-of-action of these toxins. Here, we will review TcdA/TcdB uptake and entry into mammalian cells, with focus on receptor binding, endocytosis, pore formation, and translocation. We will highlight how these toxins diverge from classical models of translocating toxins, and offer our perspective on key unanswered questions for TcdA/TcdB binding and entry into mammalian cells. [ABSTRACT FROM AUTHOR]

Sensor technology application is the key for intelligent welding process. Multiple sensors fusion has shown their significant advantages over single sensor which can only provide limited information. In this paper, a feature-level data fusion methodology was presented to automatically evaluate seam quality in real time for Al alloy in gas tungsten arc welding by means of online arc sound, voltage and spectrum signals. Based on the developed algorithms in time and frequency domain, multiple feature parameters were successively extracted and selected from sound and voltage signals, while spectrum distribution of argon atoms related to seam penetration were carefully analyzed before feature parameters selection. After the synchronization of heterogeneous feature parameters, the feature-level-based data fusion was conducted by establishing a classifier using support vector machine and 10-fold cross validation. The test results indicate that multisensory-based classifier has higher accuracy i.e., 96.5873 %, than single sensor-based one in term of recognizing seam defects, like under penetration and burn through from normal penetration. [ABSTRACT FROM AUTHOR]

Copyright of Gynecological Endocrinology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Process models and parameters are two critical steps for fault prognosis in the operation of rotating machinery. Due to the requirement for a short and rapid response, it is important to study robust sensor data representation schemes. However, the conventional holospectrum defined by one-dimensional or two-dimensional methods does not sufficiently present this information in both the frequency and time domains. To supply a complete holospectrum model, a new three-dimensional spatial representation method is proposed. This method integrates improved three-dimensional (3D) holospectra and 3D filtered orbits, leading to the integration of radial and axial vibration features in one bearing section. The results from simulation and experimental analysis on a complex compressor show that the proposed method can present the real operational status and clearly reveal early faults, thus demonstrating great potential for condition-based maintenance prediction in industrial machinery. [ABSTRACT FROM AUTHOR]

Agrobacterium-mediated plant transformation is typically conducted by inoculating plant tissues with an Agrobacterium suspension containing approximately 10-10 bacteria mL, followed by a 2-3-d co-culture period. Use of longer co-culture periods could potentially increase transformation efficiencies by allowing more time for Agrobacterium to interact with plant cells, but bacterial overgrowth is likely to occur, leading to severe tissue browning and reduced transformation and regeneration. Low bacterial inoculum levels were therefore evaluated as a means to reduce the negative outcomes associated with long co-culture. The use of low inoculum bacterial suspensions (approximately 6 × 10 bacteria mL) followed by long co-culture (15 d) led to the production of an average of three transformed sunflower shoots per explant while the use of high inoculum (approximately 6 × 10 bacteria mL) followed by short co-culture (3 d) led to no transformed shoots. Low inoculum and long co-culture acted synergistically, and both were required for the improvement of sunflower transformation. Gene expression analysis via qRT-PCR showed that genes related to plant defense response were generally expressed at lower levels in the explants treated with low inoculum than those treated with high inoculum during 15 d of co-culture, suggesting that low inoculum reduced the induction of plant defense responses. The use of low inoculum with long co-culture (LI/LC) led to large increases in sunflower transformation efficiency. This method has great potential for improving transformation efficiencies and expanding the types of target tissues amenable for transformation of different plant species. [ABSTRACT FROM AUTHOR]

Regeneration of sunflower plants from tissue culture can be problematic due to inefficiencies in shoot elongation and subsequent rooting. To minimize exposure to cytokinins, which can negatively impact shoot elongation and rooting, a cytokinin pulse treatment was evaluated by placing cotyledonary tissues from sunflower seeds onto a shoot induction medium containing 1.5 mg L 6-benzylaminopurine and 0.2 mg L 1-naphthaleneacetic acid for 0, 2, 4, 8, 12, and 16 d, prior to transfer to an elongation medium containing 0.1 mg L gibberellic acid. The 16-d pulse treatment gave the highest numbers of shoot primordia, but shoot development was minimal and only 0.4 well-developed shoots could be obtained per explant. The 4-d pulse treatment followed by 14 d of culture on elongation medium led to the production of 5.5 well-developed shoots per explant. For plant recovery, well-developed shoots obtained with the 4-d pulse treatment followed by a 14-d elongation treatment were micrografted onto in vitro seedlings, with graft survival of over 60%. Short pulse treatments (4- and 8-d), followed by culture on elongation medium, generated well-developed shoots that seemed to be more responsive to micrografting than shoots obtained with the 16-d pulse treatment. The use of the 4-d pulse treatment with micrografting of well-developed shoots significantly improved the efficiency of whole-plant recovery of sunflower. [ABSTRACT FROM AUTHOR]

Leaf tissue is widely used for regeneration of many different plants, but an efficient regeneration method using leaf tissue of sunflower is not yet available. In this report, adventitious shoots were obtained from primary leaves of 7-day-old sunflower seedlings. If seeds were germinated on a medium without cytokinin, only 25 % of the leaf explants produced shoots after 3 weeks of culture on a shoot induction medium (SIM) containing 1.5 mg L benzylaminopurine (BA), giving an average of three shoot primordia per leaf. Shoot induction was enhanced up to sixfold when seeds were germinated on media containing BA or 6-(γ, γ-dimethylallylamino)purine at 5 mg L and higher, or kinetin at 15 mg L and above, with an average of 12-19 shoot primordia per leaf. Shoots further developed and elongated following transfer to a medium containing 0.1 mg L gibberellic acid. The highest number of developed shoots was obtained from leaves preconditioned with 5 mg L BA, with 1.9 developed shoots per explant. Histological analysis of leaves from seedlings germinated on a medium containing 5 mg L BA revealed increased cell division primarily in the leaf surface tissue on the adaxial side of the mid vein. After the leaves were excised and plated on SIM, these cells continued to divide and differentiate to form adventitious shoots, suggesting that the cytokinin-containing germination medium preconditioned leaves for shoot organogenesis. An in vitro micrografting approach was developed using the elongated shoots as scions, and 57 % of grafted shoots survived to form plants. [ABSTRACT FROM AUTHOR]

In this paper, a novel methodology for real-time nondestructive defect detection, particularly hydrogen-assisted porosity of an aluminum alloy welded using pulsed gas tungsten arc welding is presented based on the plasma spectroscopy signal of the welding arc. The emission lines of the hydrogen atom at 656.3 nm and argon atom at 641.63 nm were analyzed to extract multiple feature parameters, from which more sensitive features were then selected for monitoring by means of Fisher distance criteria. The threshold detection method based on the features selected from the spectrum was found to be feasible in detecting the welding defect, i.e., porosity in real-time. Furthermore, the established predicting model based on SVM-CV also successfully identified defect of porosity from normal welding with high accuracy. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to investigate the anti-aging effects of exogenous estrogen on telomerase activity in ovariectomized female Sprague-Dawley rats. Methods: Thirty-three 12-week-old female rats were divided into three groups: the ovariectomized-Treated group (Treated,n = 11), the ovariectomized control group (OVX,n = 11) and the Sham-operated group (Sham,n = 11). The rats in the Treated group were given 0.21 mg/kg estradiol valerate intragastric administration while other two groups were given the amount of physiological saline daily. All of the animals were euthanized 12 weeks after treatment, and abdominal aortic blood samples were taken to assess the level of estradiol (E2), follicle stimulating hormone (FSH). Telomerase activity and telomerase reverse transcriptase (TERT) mRNA expression in the heart, liver, brain tissues of all rats were measured by reverse transcriptional polymerase chain reaction (RT-PCR) and competitive enzyme-linked immunosorbent assay (ELISA). Results: Compared to the OVX and Sham group, telomerase activity and TERT mRNA levels were significantly increased in the heart, liver and brain tissues of rats in the Treated group (p < 0.05). The telomerase expression was significantly higher in the heart than in liver and brain tissues in the Treated group (p < 0.05). Conclusion: Based on the findings in the ovariectomized female rats model, exogenous estrogen can significantly up-regulate telomerase activity and TERT mRNA expression to exert the effects of anti-aging. [ABSTRACT FROM AUTHOR]