Although traditional fault diagnosis methods are proficient in extracting signal features, their diagnostic interpretability remains challenging. Consequently, this article proposes a conditionally ...interpretable generative adversarial network (C-InGAN) model for the interpretable feature fault diagnosis of bearings. Initially, the vibration signal is denoised and transformed into a frequency domain signal. The model consists of the two primary networks, each employing a convolutional layer and an attention module, generator (G) and discriminator (D), respectively. Latent code was incorporated into G to constrain the generated samples, and a discriminant layer was added to D to identify the interpretable features. During training, the two networks were alternately trained, and the feature mapping relationship of the pre-normalized encoder was learned by maximizing the information from the latent code and the discriminative result. The encoding that represents specific features in the vibration signal was extracted from the random noise. Ultimately, after completing adversarial learning, G is capable of generating a simulated signal of the specified feature, and D can assess the interpretable features in the vibration signal. The effectiveness of the model is validated through three typical experimental cases. This method effectively separates the discrete and continuous feature coding in the signal.
Chromosomal microarray analysis (CMA) has been widely applied to genetic diagnosis in miscarriages in clinical practice. However, the prognostic value of CMA testing of products of conception (POCs) ...after the first clinical miscarriage remains unknown. The aim of this study was to evaluate the reproductive outcomes after embryonic genetic testing by CMA in SM couples.
In this retrospective study, a total of 1142 SM couples referred for embryonic genetic testing by CMA, and 1022 couples were successfully followed up after CMA.
Among 1130 cases without significant maternal cell contamination, pathogenic chromosomal abnormalities were detected in 680 cases (60.2%). The subsequent live birth rate did not differ significantly between couples with chromosomally abnormal and normal miscarriage (88.6% vs. 91.1%, p = .240), as well as the cumulative live birth rate (94.5% vs. 96.7%, p = .131). Couples with partial aneuploid miscarriage had a higher likelihood of spontaneous abortion both in the subsequent pregnancy (19.0% vs. 6.5%, p = .037) and cumulative pregnancies (19.0% vs. 6.8%, p = .044) when compared with couples with chromosomally normal miscarriage.
SM couples with chromosomally abnormal miscarriage manifested with a similar reproductive prognosis to couples with chromosomally normal miscarriage.
Key messages
CMA testing of POCs could provide an accurate genetic diagnosis for couples with SM.
The live birth rate of couples with partial aneuploid miscarriage was as high as couples with chromosomally normal miscarriage, despite a higher risk of adverse pregnancy event.
Among couples with the most common single aneuploid miscarriage, the cumulative live birth rates of couples with trisomy 16, sex chromosomal abnormalities and trisomy 22 were 94.1%, 95.8% and 84.0%, respectively.
The non-linearity and non-stationarity of wind power data have brought great challenges to the safe operation of the power system. It is particularly important to effectively improve the accuracy of ...ultra-short-term prediction of wind power. Therefore, we propose an ultra-short-term wind power prediction method that particle swarm optimization-variational mode decomposition (PVMD), enhanced slime mold algorithm (ESMA) for elite opposition-based learning strategy (EOBL) and deep extreme learning machine (DELM). First, the particle swarm optimization algorithm (PSO) is used to optimize the two core parameters of the variational mode decomposition (VMD) to obtain the PVMD algorithm. The PVMD is used to decompose the original wind power data into a series of stable sub-sequences, and the rolling time series is used to analyze the sub-sequences decomposed by PVMD. Then the DELM predictive model is established and the input weights (e) and thresholds (bc) in DELM are optimized through ESMA, and the EOBL is used to improve the diversity and population quality of the slime mold population, thereby improving the global optimization performance and convergence accuracy of the slime mold algorithm (SMA), and further improving the prediction accuracy of the DELM model. Finally, each subsequence is substituted into the DELM optimized by the elite opposition based learning-slime mold algorithm (ESMA-DELM), and the prediction components are superimposed to obtain the final prediction result. Comparing the effects of several different forecasting models with the evaluation of calculation examples proves the effectiveness of the PVMD-ESMA-DELM blended forecasting model proposed in this paper, and gives a new approach for ultra-short-term wind power prediction.
The security of power systems and electrical grids can be affected by the stochastic nature of wind energy. Therefore, reliable techniques for load forecasting and planning must be developed. This ...paper presents a model for short-term regional wind power forecasting based on small datasets. The model comprises three steps: input data correction, a hybrid neural network, and error analysis. First, regional numerical weather predictions (NWP) are corrected by using a stacked multilevel-denoising autoencoder (SMLDAE) to generate more effective inputs; this is the first study to use SMLDAE for NWP data correction. Second, a neural network-based hybrid model is employed for regional wind power forecasting to predict the wind power in the region. The proposed hybrid model employs three processes: multiscale mathematical morphological decomposition (MMMD), k-means clustering, and a stacked denoising autoencoder. MMMD can decompose the data directly in the time domain, thus, the signal does not need to be transferred from the time domain to the frequency domain to accomplish the decomposition. Third, a long short-term memory network is used for error analysis of the preliminary forecasted data. The preliminary results and error series are aggregated to generate the final forecasting result. For small datasets, we use multi-distribution mega-trend diffusion to augment the dataset. The proposed model was validated using a dataset consisting of data generated by regional wind farms in northern China. The results show that the proposed model enables wind forecasting at both the regional and single-farm level. Moreover, whereas most benchmark models require almost one year of data, the model requires only approximately three months of NWP data to produce reliable forecasting within the next 24 h.
The effect of pathogenic fungal infestation on berry quality and volatile organic compounds (VOCs) of Cabernet Sauvignon (CS) and Petit Manseng (PM) were investigated by using biochemical assays and ...gas chromatography-ion mobility spectrometry. No significant difference in diseases-affected grapes for 100-berry weight. The content of tannins and vitamin C decreased significantly in disease-affected grapes, mostly in white rot-affected PM, which decreased by 71.67% and 66.29%. The reduced total flavonoid content in diseases-affected grape, among which the least and most were anthracnose-affected PM (1.61%) and white rot-affected CS (44.74%). All diseases-affected CS had much higher titratable acid, a maximum (18.86 g/100 ml) was observed in the gray mold-affected grapes, while only anthracnose-affected grapes with a higher titratable acid level (21.8 g/100 mL) were observed in PM. A total of 61 VOCs were identified, including 14 alcohols, 13 esters, 12 aldehydes, 4 acids, 4 ketones, 1 ether, and 13 unknown compounds, which were discussed from different functional groups, such as C6-VOCs, alcohols, ester acetates, aldehydes, and acids. The VOCs of CS changed more than that of Petit Manseng’s after infection, while gray mold-affected Cabernet Sauvignon had the most change. C6-VOCs, including hexanal and (
E
)-2-hexenal were decreased in all affected grapes. Some unique VOCs may serve as hypothetical biomarkers to help us identify specific varieties of pathogenic fungal infestation.
Periconceptional folic acid (FA) supplementation is recommended to prevent neural tube defects and other birth defects. After 20 years mandate food fortification with FA, serum concentration of ...folate and unmetabolized FA increased significantly in the North American population. But whether excess FA intake impairs neurodevelopment and behavior is still controversial. Here, we treated mice with approximately 2.5-fold (moderate dose of FA, MFA) or 10-fold (high dose of FA, HFA) the dietary requirement of FA 1 week before mating and throughout pregnancy and lactation, and examined behaviors in adult male offspring using open field test, three-chamber sociability and social novelty test, elevated plus maze, rotarod and Morris water maze. We found that early life MFA supplementation increased long-term body weight gain in adults, elevated anxiety-like behavior, and impaired social preference, motor learning and spatial learning ability without modifying motor ability and spatial memory. In contrast, HFA supplementation only induced mild behavioral abnormality. RNA sequencing revealed that FA supplementation altered the expression of brain genes at weaning, among which
and related genes were significantly up-regulated in MFA mice compared with control and HFA mice. Quantitative real time-PCR (qRT-PCR) and western blots confirmed the increase of these genes. Our results suggested that FA supplementation during early life stage affected gene expression in weaning mice, and exhibited long-term impairments in adult behaviors in a dose-sensitive manner.
Continuous spring cropping of Qingke (
L. var. nudum Hook. f.) results in a reduction in grain yield in the Xizang autonomous region. However, knowledge on the influence of continuous cropping on ...grain yield caused by reactive oxygen species (ROS)-induced stress remains scarce. A systematic comparison of the antioxidant defensive profile at seedling, tillering, jointing, flowering, and filling stages (T1 to T5) of Qingke was conducted based on a field experiment including 23-year continuous cropping (23y-CC) and control (the first year planted) treatments. The results reveal that the grain yield and superoxide anion (SOA) level under 23y-CC were significantly decreased (by 38.67% and 36.47%), when compared to the control. The hydrogen peroxide content under 23y-CC was 8.69% higher on average than under the control in the early growth stages. The higher ROS level under 23y-CC resulted in membrane lipid peroxidation (LPO) and accumulation of malondialdehyde (MDA) at later stages, with an average increment of 29.67% and 3.77 times higher than that in control plants. Qingke plants accumulated more hydrogen peroxide at early developmental stages due to the partial conversion of SOA by glutathione (GSH) and superoxide dismutase (SOD) and other production pathways, such as the glucose oxidase (GOD) and polyamine oxidase (PAO) pathways. The reduced regeneration ability due to the high oxidized glutathione (GSSG) to GSH ratio resulted in GSH deficiency while the reduction in L-galactono-1,4-lactone dehydrogenase (GalLDH) activity in the AsA biosynthesis pathway, higher enzymatic activities (including ascorbate peroxidase, APX; and ascorbate oxidase, AAO), and lower activities of monodehydroascorbate reductase (MDHAR) all led to a lower AsA content under continuous cropping. The lower antioxidant capacity due to lower contents of antioxidants such as flavonoids and tannins, detected through both physiological measurement and metabolomics analysis, further deteriorated the growth of Qingke through ROS stress under continuous cropping. Our results provide new insights into the manner in which ROS stress regulates grain yield in the context of continuous Qingke cropping.
Microdeletions in Y-chromosomal azoospermia factor (AZF) regions have been regarded as the risk factor of spermatogenic failure (SF). However, AZF-linked duplications or complex copy number variants ...(CNVs) (deletion + duplication) were rarely studied. In this study, we performed multiplex ligation-dependent probe amplification (MLPA) analysis on 402 fertile healthy male controls and 423 idiopathic infertile SF patients (197 azoospermia and 226 oligozoospermia) in Han Chinese population. In total, twenty-four types of AZF-linked CNVs were identified in our study, including eleven novel CNVs (one deletion, seven duplications, and three complex CNVs). Our study revealed that AZFc-linked duplications and the instability of Y chromosome might be associated with spermatogenesis. Besides, the complex CNVs (b2/b3 deletion +
1/2 duplication) were confirmed to increase genetic risks for SF in Han Chinese population. This study illustrated a spectrum of AZF-linked CNVs and presented valuable information for understanding the clinical significance of AZF-linked CNVs in male infertility.
Aiming at the current challenges of enormous scale, complex structure, difficult control and frequent accidents of city gas high-pressure pipeline network, there are still three aspects of ...difficulties in the risk monitoring and control of China’s city gas high-pressure pipeline network, namely, rough data, shallow assessment, and lack of power. This paper proposes an intelligent management system for gas pipelines based on C/S model and J2EE enterprise-level framework, in which the failure warning models of gas leakage, Gaussian plume diffusion, and fire and explosion are established. And the Kalman filter algorithm improved by DS evidence theory is used for intelligent fusion of Multi-source data, analyzing and screening the unified adequate information on data types, extracting state characteristics, classifying warning levels, and developing an integrated and visualized pipeline remote diagnosis and warning platform. In the simulation of the intelligent management system of gas pipeline, when the wind speed is 1.5m/s in winter, the ground surface is a safe area within 12.15m of the gas pipeline. When the maximum wind speed is 10m/s, the upper limit distance of the gas leading to fire and explosion is only 2.43m, and the hazardous range of the gas pipeline jet fire is within 12.69m. Relying on the gas high-pressure pipeline network in L city for practical experiments and applications, it provides technical support and decision-making basis for the construction of intelligent pipeline network, comprehensively improves the risk control capability of city gas high-pressure pipeline network, and has reference significance for the risk control of national city gas high-pressure pipeline network.
Agaricus bisporus lectin (ABL), which is one of the antinutritional factors in A. bisporus, is an important allergen and harmful to human health. Due to the shortcomings of the current detection ...methods, it is extremely urgent to establish a rapid and sensitive detection method for ABL in foods. To isolate the ssDNA aptamer of ABL, 13 rounds of subtractive systematic evolution of ligands by exponential enrichment (SELEX) selection were carried out. As a result, six candidate aptamers were selected and further examined for their binding affinity and specificity by enzyme-linked aptamer method. One aptamer (seq-41) against ABL with a high affinity and specificity was isolated and demonstrated to be the optimal aptamer whose dissociation constant reaches the nanomolar level, Kd = 31.17 ± 0.1070 nM. Based on seq-41, an aptamer-AuNPs colorimetric method was established to detect ABL with a linear range of 0.08∼1.70 μg/mL and the detection limit is 0.062 μg/mL. This study provides a novel aptamer-AuNPs colorimetric method with high sensitivity and specificity for detection of ABL and a novel strategy for development of detection method of fungal or plant allergens.
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