Methionine Source and Level Modulate Gut pH, Amino Acid Transporters and Metabolism Related Genes in Broiler Chickens.

This study determined the effects of two methionine (Met) sources at three total sulfur amino acids (TSAA) to lysine ratios (TSAA/Lys) on gut pH, digestive enzyme activity, amino acid transporter expression, and Met metabolism of broilers. The birds were randomly assigned to a 2 × 3 factorial arrangement with Met sources (dl-Met and dl-2-hydroxy-4-(methylthio)-butanoic acid (OH-Met)) and TSAA/Lys (0.58, 0.73, and 0.88) from 1 to 21 days. The results demonstrated that dl-Met and OH-Met supported the same growth performance, but high TSAA/Lys ratio reduced the feed intake and body weight (P < 0.05). OH-Met reduced the crop chyme pH and enhanced the jejunal lipase activity (P < 0.05). ATB0,+ expression decreased with increased dl-Met levels in the duodenum; the low TSAA/Lys ratio induced a stronger mRNA expression of basolateral Met transporters. OH-Met resulted in an increase of cystathionine ß-synthase expression in the liver and a decrease in serum homocysteine levels at middle TSAA/Lys ratio compared with dl-Met treatment (P < 0.05). In conclusion, two Met sources support the same growth, but OH-Met acidified the crop chyme. The investigated transporter transcripts differed significantly along the small intestine. At the middle TSAA/Lys ratio, OH-Met showed a higher metabolic tendency of the trans-sulfuration pathway compared with dl-Met.

Association between maternal lipid profiles and vitamin D status in second trimester and risk of LGA or SGA: a retrospective study.

Background: Accumulating evidence has linked dyslipidemia during pregnancy to the risk of delivering infants born either large for gestational age (LGA) or small for gestational age (SGA). However, the effects of the vitamin D status on these relationships require further investigation. This study investigated whether the relationship between lipid profiles and the risk of LGA or SGA was influenced by vitamin D levels during the second trimester. Methods: Maternal lipid profile levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and vitamin D levels, were measured in a cohort of 6,499 pregnant women during the second trimester. Multivariate regression models and subgroup analyses were employed to evaluate the potential associations between maternal lipid profiles, vitamin D levels, and the risk of LGA or SGA. Results: The prevalence of SGA infants was 9.8% (n=635), whereas that of LGA infants was 6.9% (n=447). Maternal TG levels were found to be positively associated with the risk of LGA (odds ratio [OR] = 1.41, 95% confidence interval [CI]:1.17-1.70), whereas a negative association was observed between maternal TG, TC, LDL-C levels, and risk of SGA. Additionally, mothers with higher HDL-C levels were less likely to give birth to an LGA infant (OR=0.58, 95% CI:0.39-0.85). Importantly, associations between TG, TC, LDL-c, and SGA as well as between TG and LGA were primarily observed among pregnant women with insufficient vitamin D levels. As for HDL-C, the risk of LGA was lower in mothers with sufficient vitamin D (OR = 0.42, 95% CI:0.18-0.98) compared to those with insufficient vitamin D (OR = 0.65, 95% CI:0.42-0.99). Conclusion: Vitamin D status during the second trimester exerts a modifying effect on the association between lipid profiles and the risk of LGA and SGA infants.

A preliminary probabilistic nomogram model for predicting renal arteriolar damage in IgA nephropathy from clinical parameters.

Background: IgA nephropathy (IgAN) is a significant contributor to chronic kidney disease (CKD). Renal arteriolar damage is associated with IgAN prognosis. However, simple tools for predicting arteriolar damage of IgAN remain limited. We aim to develop and validate a nomogram model for predicting renal arteriolar damage in IgAN patients. Methods: We retrospectively analyzed 547 cases of biopsy-proven IgAN patients. Least absolute shrinkage and selection operator (LASSO) regression and logistic regression were applied to screen for factors associated with renal arteriolar damage in patients with IgAN. A nomogram was developed to evaluate the renal arteriolar damage in patients with IgAN. The performance of the proposed nomogram was evaluated based on a calibration plot, ROC curve (AUC) and Harrell's concordance index (C-index). Results: In this study, patients in the arteriolar damage group had higher levels of age, mean arterial pressure (MAP), serum creatinine, serum urea nitrogen, serum uric acid, triglycerides, proteinuria, tubular atrophy/interstitial fibrosis (T1-2) and decreased eGFR than those without arteriolar damage. Predictors contained in the prediction nomogram included age, MAP, eGFR and serum uric acid. Then, a nomogram model for predicting renal arteriolar damage was established combining the above indicators. Our model achieved well-fitted calibration curves and the C-indices of this model were 0.722 (95%CI 0.670-0.774) and 0.784 (95%CI 0.716-0.852) in the development and validation groups, respectively. Conclusion: With excellent predictive abilities, the nomogram may be a simple and reliable tool to predict the risk of renal arteriolar damage in patients with IgAN.

Nitrous oxide abuse in a 21-year-old female: a case report and review of literature.

The abuse of nitrous oxide (N2O) poses a substantial public health challenge. In many countries, including China, regulations governing the utilization and accessibility to N2O remain ambiguous, particularly within the food industry. Here, we report a case of a 21-year-old female who presented with symptoms of subacute combined degeneration (SCD) of the spinal cord due to N2O abuse. The patient exhibited bilateral lower limb numbness and weakness, low serum vitamin B12 levels with elevated homocysteine levels, and lumbar spine magnetic resonance imaging (MRI) revealed abnormal signals of the spinal cord. Following cessation of N2O and comprehensive therapy including methylcobalamin and nerve growth factor, the symptoms significantly improved. A follow-up examination 3 months later showed good progress in gait stability. At a 5-year follow-up, the patient's previous clinical symptoms had completely disappeared, and her quality of life had returned to normal. This case underscores the urgency of raising awareness and prevention of N2O abuse, emphasizing the importance of timely diagnosis and comprehensive treatment for patient recovery. Clear formulation and enforcement of relevant regulatory measures are equally crucial in reducing instances of abuse.

EQ-5D-5L population scores in mainland China: results from a nationally representative survey 2021.

OBJECTIVES: There is a lack of monitoring changes in the population scores of the most recent version, EQ-5D-5L, in mainland China. This study aims to address this knowledge gap by assessing the EQ-5D-5L scores in mainland China using a nationally representative sample. METHODS: Data were extracted from the 2021 Survey of Health Index of Chinese Families, which covered 31 provinces/autonomous regions/municipalities in mainland China. The survey employed a multi-stage quota sampling strategy encompassing 120 prefecture-level cities. Quotas were allocated to each prefecture-level city in accordance with the 2020 China Population Census. This approach resulted in a final sample of 11,030 eligible questionnaires. The utility index and EQ Visual Analogue Scale (VAS) scores were reported for the entire sample (age-gender-urban/rural weighted) and by the characteristics of the study participants. RESULTS: The study participants had a weighted mean utility index of 0.939 (SD=0.135) and EQ VAS score of 80.19 (SD=18.39). The most commonly reported problem was anxiety/depression (26.37%), while self-care was the least reported problem (6.18%). Those who were male, younger, lived without chronic conditions and disabilities, had higher levels of education, earned higher monthly household income, and were covered by basic medical insurance for urban employees had higher scores in both the utility index and EQ VAS. CONCLUSION: This study revealed slightly lower utility index scores despite a much higher drop in EQ VAS scores while China maintained minimum cases of COVID-19 in 2021 compared to the population norms recorded in 2019. Further studies are warranted to unveil the full impacts of COVID-19 outbreaks.

A high security coding and anti-counterfeiting method based on the nonlinear magnetization response of superparamagnetic nanomaterials.

Traditional coding methods based on graphics and digital or magnetic labels have gradually decreased their anti-counterfeiting because of market popularity. This paper presents a new magnetic anti-counterfeiting coding method. This method uses a high-performance coding material, which, along with small changes to the material itself and the particle size of the superparamagnetic nanomaterials, results in a large difference in the nonlinear magnetization response. This method, which adopts 12-site coding and establishes a screening model by measuring the voltage amplitude of 12-site variables, can code different kinds of products, establishing long-term stable coding and decoding means. Through the anti-counterfeiting experiment of wine, the experiment results show that the authenticity of the coded products can be verified using the self-developed magnetic encoding and decoding system. The new coding technology can verify the anti-counterfeiting of 9000 products, with a single detection accuracy of 97% and a detection time of less than one minute. Moreover, this coding method completely depends on the production batch of the superparamagnetic nanomaterials, which is difficult to imitate, and it provides a new coding anti-counterfeiting technology for related industries with a wide range of potential applications.

Cholinergic nucleus degeneration and its association with gait impairment in Parkinson's disease.

BACKGROUND: The contribution of cholinergic degeneration to gait disturbance in Parkinson's disease (PD) is increasingly recognized, yet its relationship with dopaminergic-resistant gait parameters has been poorly investigated. We investigated the association between comprehensive gait parameters and cholinergic nucleus degeneration in PD. METHODS: This cross-sectional study enrolled 84 PD patients and 69 controls. All subjects underwent brain structural magnetic resonance imaging to assess the gray matter density (GMD) and volume (GMV) of the cholinergic nuclei (Ch123/Ch4). Gait parameters under single-task (ST) and dual-task (DT) walking tests were acquired using sensor wearables in PD group. We compared cholinergic nucleus morphology and gait performance between groups and examined their association. RESULTS: PD patients exhibited significantly decreased GMD and GMV of the left Ch4 compared to controls after reaching HY stage > 2. Significant correlations were observed between multiple gait parameters and bilateral Ch123/Ch4. After multiple testing correction, the Ch123/Ch4 degeneration was significantly associated with shorter stride length, lower gait velocity, longer stance phase, smaller ankle toe-off and heel-strike angles under both ST and DT condition. For PD patients with HY stage 1-2, there were no significant degeneration of Ch123/4, and only right side Ch123/Ch4 were corrected with the gait parameters. However, as the disease progressed to HY stage > 2, bilateral Ch123/Ch4 nuclei showed correlations with gait performance, with more extensive significant correlations were observed in the right side. CONCLUSIONS: Our study demonstrated the progressive association between cholinergic nuclei degeneration and gait impairment across different stages of PD, and highlighting the potential lateralization of the cholinergic nuclei's impact on gait impairment. These findings offer insights for the design and implementation of future clinical trials investigating cholinergic treatments as a promising approach to address gait impairments in PD.

Identification of male sterility-related genes in Saccharum officinarum and Saccharum spontaneum.

KEY MESSAGE: Candidate male sterility genes were identified in sugarcane, which interacts with kinase-related proteins, transcription factors, and plant hormone signaling pathways to regulate stamen and anther development. Saccharum officinarum is a cultivated sugarcane species that its predominant feature is high sucrose content in stems. Flowering is necessary for breeding new cultivars but will terminate plant growth and reduce sugar yield. The wild sugarcane species Saccharum spontaneum has robust and viable pollen, whereas most S. officinarum accessions are male sterile, which is a desirable trait of a maternal parent in sugarcane breeding. To study male sterility and related regulatory pathways in sugarcane, we carried out RNAseq using flowers in different developmental stages between male-sterile S. officinarum accession 'LA Purple' and fertile S. spontaneum accession 'SES208'. Gene expression profiles were used to detect how genes are differentially expressed between male sterile and fertile flowers and to identify candidate genes for male sterility. Weighted gene correlation networks analysis (WGCNA) was conducted to investigate the regulatory networks. Transcriptomic analyses showed that 988 genes and 2888 alleles were differentially expressed in S. officinarum compared to S. spontaneum. Ten differentially expressed genes and thirty alleles were identified as candidate genes and alleles for male sterility in sugarcane. The gene Sspon.03G0007630 and two alleles of the gene Sspon.08G0002270, Sspon.08G0002270-2B and Sspon.08G0014700-1A, were involved in the early stamen or carpel development stages, while the remaining genes were classified into the post-meiosis stage. Gibberellin, auxin, and jasmonic acid signaling pathways are involved in the stamen development in sugarcane. The results expanded our knowledge of male sterility-related genes in sugarcane and generated genomic resources to facilitate the selection of ideal maternal parents to improve breeding efficiency.

Application of improved machine learning in large-scale investigation of plastic waste distribution in tourism Intensive artificial coastlines.

Oceans are ultimately a sink of plastic waste. Complex artificial coastlines pose remarkable challenges for coastal plastic waste monitoring. With the development of machine learning methods, high detection accuracy can be achieved; however, many false positives have been noted in various network models used for plastic waste investigation. In this study, extensive surveys of artificial coastlines were conducted using drones along the Dongjiang Port artificial coastline in the Binhai District, Tianjin, China. The deep learning model YOLOv8 was enhanced by integrating the InceptionNeXt and LSK modules into the network to improve its detection accuracy for plastic waste and reduce instances of tourists being misidentified as plastic. In total, 553 high-resolution coastline images with 3488 items of detected plastic waste were compared using the original and improved YOLOv8 models. The improved YOLOv8s-IL model achieved a detection rate of 64.9%, a notable increase of 11.5% compared with that of the original model. The number of false positives in the improved YOLOv8s-IL model was reduced to 32.3%, the multi-class F-score reached 76.5%, and the average detection time per image was only 2.7 s. The findings of this study provide technical support for future large-scale monitoring of plastic waste on artificial coastlines.

LncRNA MALAT1-miR-339-5p-NIS axis is involved in the increased level of thyroid stimulating hormone (TSH) induced by combined exposure of high iodine and hyperlipidemia.

Hypothyroidism and subclinical hypothyroidism were both characterized by elevated levels of thyroid stimulating hormone (TSH). Previous studies had found that high iodine or hyperlipidemia alone was associated with increased TSH level. However, their combined effects on TSH have not been elucidated. In this study, combination of high iodine and hyperlipidemia was established through the combined exposure of high-water iodine and high fat diet in Wistar rats. The results showed that combined exposure of high iodine and high fat can induce higher TSH level. The mRNA and protein levels of sodium iodide transporters (NIS) and type 1 deiodinase (D1) in thyroid tissues, which were crucial genes in the synthesis of thyroid hormones, decreased remarkably in combined exposure group. Mechanistically, down-regulated long non-coding RNA (lncRNA) metastasis associated in lung denocarcinoma transcript 1 (MALAT1) may regulate the expression of NIS by increasing miR-339-5p, and regulating D1 by increasing miR-224-5p. Then, the above findings were explored in subjects exposed to high water iodine and hyperlipidemia. The results indicated that in population combined with high iodine and hyperlipidemia, TSH level increased to higher level and lncRNA MALAT1-miR-339-5p-NIS axis was obviously activated. Collectively, this study found that combined exposure of high iodine and hyperlipidemia induced a higher level of TSH, and lncRNA MALAT1-miR-339-5p-NIS axis may play important role.

Suppress Austenite Grain Coarsening by Nb Alloying in High-Temperature-Pseudo-Carburized Bearing Steel.

The effect of Nb alloying on the suppression of austenite grain coarsening behavior during pseudo-carburizing is investigated in high-temperature-carburized SAE4320 bearing steel. To explore the role of the Nb element in the pseudo-carburizing process, the morphology, composition, size, and distribution of NbC precipitates were analyzed. The results show that the fine austenite grain observed in Nb micro-alloyed steel is caused by the pinning effect of NbC precipitates, which hinders the coarsening of austenite grains and changes the growth dynamics of austenite grains. After the SAE4320 carburized bearing steel with the addition of 0.45 wt.% Nb element is kept at 1150 °C for 4 h, the PAG size is still below 20 µm, which indicates the Nb element has obvious advantages in limiting PAG growth at high temperatures and shows great potential for the development of high-temperature carburized bearing steel.

Fruit Quality Analysis and Flavor Comprehensive Evaluation of Cherry Tomatoes of Different Colors.

Cherry tomatoes are popular vegetables worldwide owing to their variety of colors and nutrients. However, an integrated evaluation of color and flavor has rarely been reported. This study examined the differences among red, brown, yellow, and green cherry tomatoes grown in the Jiuquan area. A comprehensive analysis of the flavor quality of these tomatoes, including sensory evaluation, electronic nose analysis, nutritional and flavor quality measurements, targeted metabolomics, and chemometrics, was conducted. Red tomatoes had the highest lycopene content, and green tomatoes had the highest soluble protein and vitamin C content. In cherry tomatoes, K is the most abundant macro element and Fe and Zn are the most abundant trace elements. Brown cherry tomatoes had significantly higher K, P, Mg, Cu and Fe contents than other colored tomatoes, and red tomatoes had significantly higher Zn content than other cherry tomatoes (218.8-724.3%). Yellow cherry tomatoes had the highest soluble sugar content, followed by red, brown and green tomatoes. A total of 20 amino acids of tomatoes were simultaneously determined by LC-MS. Yellow cherry tomatoes have the highest content of essential amino acids, aromatic amino acids and sweetness amino acids. Red tomatoes have the highest levels of non-essential and sourness amino acid contents. An analysis of 30 flavor indicators revealed that yellow tomatoes had the best flavor, followed by red, brown, and green tomatoes. Our work lays the foundation for future research on color and flavor formation in cherry tomatoes.

Study on the correlation and difference of qualitative information among three types of UPLC-HRMS and potential generalization in metabolites annotation.

The variation of qualitative information among different types of mainstream hyphenated instruments of ultra-performance liquid chromatography coupled to high-resolution mass spectrometry (UPLC-HRMS) makes data sharing and standardization, and further comparison of results consistency in metabolite annotation not easy to attain. In this work, a quantitative study of correlation and difference was first achieved to systematically investigate the variation of retention time (tR), precursor ion (MS1), and product fragment ions (MS2) generated by three typical UPLC-HRMS instruments commonly used in metabolomics area. In terms of the findings of systematic and correlated variation of tR, MS1, and MS2 between different instruments, a computational strategy for integrated metabolite annotation was proposed to reduce the influence of differential ions, which made full use of the characteristic (common) and non-common fragments for scoring assessment. The regular variations of MS2 among three instruments under four collision energy voltages of high, medium, low, and hybrid levels were respectively inspected with three technical replicates at each level. These discoveries could improve general metabolite annotation with a known database and similarity comparison. It should provide the potential for metabolite annotation to generalize qualitative information obtained under different experimental conditions or using instruments from various manufacturers, which is still a big headache in untargeted metabolomics. The mixture of standard compounds and serum samples with the addition of standards were applied to demonstrate the principle and performance of the proposed method. The results showed that it could be an optional strategy for general use in HRMS-based metabolomics to offset the difference in metabolite annotation. It has some potential in untargeted metabolomics.

The Basic Units of Working Memory Manipulation Are Boolean Maps, Not Objects.

Determining the manipulation unit of working memory is one of the fundamental questions in understanding how working memory functions. The prevalent object-based theory in cognitive research predicts that memory manipulation is performed on the level of objects. Here we show instead that the basic units of working memory manipulation are Boolean maps, a data structure describing what can be perceived in an instant. We developed four new manipulation tasks (with data from 80 adults) and showed that manipulation times only increased when the number of Boolean maps manipulated increased. Increasing the number of orientations manipulated did not induce longer manipulation times, consistent with a key prediction of the Boolean map theory. Our results show that Boolean maps are the manipulation unit of working memory.

Comparison of Prompt Engineering and Fine-Tuning Strategies in Large Language Models in the Classification of Clinical Notes.

The emerging large language models (LLMs) are actively evaluated in various fields including healthcare. Most studies have focused on established benchmarks and standard parameters; however, the variation and impact of prompt engineering and fine-tuning strategies have not been fully explored. This study benchmarks GPT-3.5 Turbo, GPT-4, and Llama-7B against BERT models and medical fellows' annotations in identifying patients with metastatic cancer from discharge summaries. Results revealed that clear, concise prompts incorporating reasoning steps significantly enhanced performance. GPT-4 exhibited superior performance among all models. Notably, one-shot learning and fine-tuning provided no incremental benefit. The model's accuracy sustained even when keywords for metastatic cancer were removed or when half of the input tokens were randomly discarded. These findings underscore GPT-4's potential to substitute specialized models, such as PubMedBERT, through strategic prompt engineering, and suggest opportunities to improve open-source models, which are better suited to use in clinical settings.

MFPINC: prediction of plant ncRNAs based on multi-source feature fusion.

Non-coding RNAs (ncRNAs) are recognized as pivotal players in the regulation of essential physiological processes such as nutrient homeostasis, development, and stress responses in plants. Common methods for predicting ncRNAs are susceptible to significant effects of experimental conditions and computational methods, resulting in the need for significant investment of time and resources. Therefore, we constructed an ncRNA predictor(MFPINC), to predict potential ncRNA in plants which is based on the PINC tool proposed by our previous studies. Specifically, sequence features were carefully refined using variance thresholding and F-test methods, while deep features were extracted and feature fusion were performed by applying the GRU model. The comprehensive evaluation of multiple standard datasets shows that MFPINC not only achieves more comprehensive and accurate identification of gene sequences, but also significantly improves the expressive and generalization performance of the model, and MFPINC significantly outperforms the existing competing methods in ncRNA identification. In addition, it is worth mentioning that our tool can also be found on Github ( https://github.com/Zhenj-Nie/MFPINC ) the data and source code can also be downloaded for free.

CYTOR-NFAT1 feedback loop regulates epithelial-mesenchymal transition of retinal pigment epithelial cells.

Epithelial mesenchymal transition (EMT) occurring in retinal pigment epithelial cells (RPE) is a crucial mechanism that contributes to the development of age-related macular degeneration (AMD), a pivotal factor leading to permanent vision impairment. Long non-coding RNAs (lncRNAs) have emerged as critical regulators orchestrating EMT in RPE cells. In this study, we explored the function of the lncRNA CYTOR (cytoskeleton regulator RNA) in EMT of RPE cells and its underlying mechanisms. Through weighted correlation network analysis, we identified CYTOR as an EMT-related lncRNA associated with AMD. Experimental validation revealed that CYTOR orchestrates TGF-ß1-induced EMT, as well as proliferation and migration of ARPE-19 cells. Further investigation demonstrated the involvement of CYTOR in regulating the WNT5A/NFAT1 pathway and NFAT1 intranuclear translocation in the ARPE-19 cell EMT model. Mechanistically, CHIP, EMSA and dual luciferase reporter assays confirmed NFAT1's direct binding to CYTOR's promoter, promoting transcription. Reciprocally, CYTOR overexpression promoted NFAT1 expression, while NFAT1 overexpression increased CYTOR transcription. These findings highlight a mutual promotion between CYTOR and NFAT1, forming a positive feedback loop that triggers the EMT phenotype in ARPE-19 cells. These discoveries provide valuable insights into the molecular mechanisms of EMT and its association with AMD, offering potential avenues for targeted therapies in EMT-related conditions, including AMD.

The impacts of natural product miltirone and the CYP2D6 pharmacogenetic phenotype on fluoxetine metabolism.

Introduction: To study the effects of drug-induced CYP2D6 activity inhibition and genetic polymorphisms on fluoxetine metabolism, rat liver microsomes (RLMs) and SD rats were used to investigate the potential drug‒drug interactions (DDIs), and CYP2D6 http://muchong.com/t-10728934-1 recombinant baculosomes were prepared and subjected to catalytic reactivity studies. Methods and Results: All analytes were detected by ultraperformance liquid chromatography-tandem mass spectrometry (UPLC‒MS/MS). After screening for 27 targeted natural products, miltirone was identified as having obvious inhibitory effect on fluoxetine metabolism in RLMs. In vivo, the concentration of fluoxetine in rat blood increased markedly after miltirone administration. The molecular docking results showed that miltirone bound more strongly to CYP2D6 than fluoxetine, and PHE120 may be the key residue leading to the inhibition of CYP2D6-mediated fluoxetine N-demethylation by miltirone. In terms of the genetic polymorphism of CYP2D6 on fluoxetine metabolism, the intrinsic clearance values of most variants were significantly altered. Among these variants, CYP2D6*92 and CYP2D6*96/Q424X were found to be catalytically inactive for fluoxetine metabolism, five variants (CYP2D6*89/L142S, *97/F457L, *R497, *V342M and *R344Q) exhibited markedly increased clearance values (>125.07%) and seven variants (CYP2D6*2, *10, *87/A5V, *93/T249P, *E215K, *R25Q and *R440C) exhibited significantly decreased clearance values (from 6.62% to 66.79%) compared to those of the wild-type. Conclusion: Our results suggest that more attention should be given to subjects in the clinic who take fluoxetine and also carry one of these infrequent CYP2D6 alleles or are coadministered drugs containing miltirone.

Magnetic leakage behavior assessment in pipeline stress-concentrated areas using improved force-magnetic coupling model.

Magnetic flux leakage (MFL) technology is remarkable for its capability to detect pipeline geometric deformation and general corrosion defects. However, it cannot characterize the MFL behavior in stress-concentrated areas, thereby greatly challenging the subsequent pipeline maintenance. This study suggests that the MFL characteristics of pipeline in stress-concentrated areas are caused by the combined effect of the face magnetic charge on the deformed end-face and the body magnetic charge of the dislocation stack. In addition, an improved force-magnetic coupling model of the pipeline in stress-concentrated areas is established based on the magnetic dipole model and Jiles-Atherton (J-A) theory. In the verification experiment, the Q235 steel plate is magnetized along the extension direction (axis of the pipeline) through the solenoid coil to obtain the distribution law of the MFL signal in the stress-concentrated area under different excitation intensities. The results show that with the increase in excitation intensity, the deformation of the MFL field signal caused by the end-face of the stress-concentrated area gradually increases to a stable state. Moreover, the internal stress of the MFL field signal generated by the pipe dislocation rapidly increases to a peak value and then decays exponentially to a certain base value. The overall change trend is in good agreement with the calculation results of the established force-magnetic coupling model. Meanwhile, the differentiation research between deformation and internal stress MFL field signals under different magnetic field intensities can provide a reliable theoretical basis for the subsequent accurate identification and quantification of pipeline stress-concentrated areas.

Optimal channel dynamic selection for Constructing lightweight Data EEG-based emotion recognition.

At present, most methods to improve the accuracy of emotion recognition based on electroencephalogram (EEG) are achieved by means of increasing the number of channels and feature types. This is to use the big data to train the classification model but it also increases the code complexity and consumes a large amount of computer time. We propose a method of Ant Colony Optimization with Convolutional Neural Networks and Long Short-Term Memory (ACO-CNN-LSTM) which can attain the dynamic optimal channels for lightweight data. First, transform the time-domain EEG signal to the frequency domain by Fast Fourier Transform (FFT), and the Differential Entropy (DE) of the three frequency bands (α, ß and γ) are extracted as the feature data; Then, based on the DE feature dataset, ACO is employed to plan the path where the electrodes are located in the brain map. The classification accuracy of CNN-LSTM is used as the objective function for path determination, and the electrodes on the optimal path are used as the optimal channels; Next, the initial learning rate and batchsize parameters are exactly matched the data characteristics, which can obtain the best initial learning rate and batchsize; Finally, the SJTU Emotion EEG Dataset (SEED) dataset is used for emotion recognition based on the ACO-CNN-LSTM. From the experimental results, it can be seen that: the average accuracy of three-classification (positive, neutral, negative) can achieve 96.59 %, which is based on the lightweight data by means of ACO-CNN-LSTM proposed in the paper. Meanwhile, the computer time consumed is reduced. The computational efficiency is increased by 15.85 % compared with the traditional CNN-LSTM method. The accuracy can achieve more than 90 % when the data volume is reduced to 50 %. In summary, the proposed method of ACO-CNN-LSTM in the paper can get higher efficiency and accuracy.