Abstract Different algorithms combined with Near-infrared spectroscopy were investigated for the detection and classification of crayfish quality. In this study, the crawfish quality was predicted by partial least square-support vector machine, principal component analysis-support vector machine, BP neural network and support vector machine after pre-processing the NIR spectral data of crawfish. The result shows that the accuracy of near-infrared spectroscopy technology combined with SVM to classify crayfish quality can reach 100%, and the prediction can guide the sampling of crayfish food safety in practice, thus improving food safety and quality.
Aeroengine is an important part related to aircraft flight safety. Accurate prediction of the remaining useful life for the engine is of great significance in real life. Aiming at the current problem of limited real-time RUL prediction, a novel prediction model based on the Ghost method is proposed. The Ghost method can take advantage of the redundancy of feature maps in CNN, and use simple operations to obtain ghost feature maps, instead of redundant feature maps in traditional CNN. Therefore, it can fully reduce the number of internal trainable parameters of the model, and accelerate training process. Validated using the C-MAPSS data set, the results show that, compared with the existing methods, the Ghost model has the smallest root mean square error and scoring function. While maintaining high-precision RUL prediction performance, the training speed of the model is faster than other methods.
Mdfi, an inhibitor of myogenic regulatory factors, is involved in myoblast myogenic development and muscle fiber type transformation. However, the regulatory network of Mdfi regulating myoblasts has not been revealed. In this study, we performed microRNAs (miRNAs)-seq on Mdfi overexpression (Mdfi-OE) and wild-type (WT) C2C12 cells to establish the regulatory networks. Comparative analyses of Mdfi-OE vs. WT identified 66 differentially expressed miRNAs (DEMs). Enrichment analysis of the target genes suggested that DEMs may be involved in myoblast differentiation and muscle fiber type transformation through MAPK, Wnt, PI3K-Akt, mTOR, and calcium signaling pathways. miRNA-mRNA interaction networks were suggested along with ten hub miRNAs and five hub genes. We also identified eight hub miRNAs and eleven hub genes in the networks of muscle fiber type transformation. Hub miRNAs mainly play key regulatory roles in muscle fiber type transformation through the PI3K-Akt, MAPK, cAMP, and calcium signaling pathways. Particularly, the three hub miRNAs (miR-335-3p, miR-494-3p, and miR-709) may be involved in both myogenic differentiation and muscle fiber type transformation. These hub miRNAs and genes might serve as candidate biomarkers for the treatment of muscle- and metabolic-related diseases.
OBJECTIVE: The objective of this study was performed to demonstrate the feasibility and effectiveness of a custom-manufactured stent graft (CMSG) with directional multibranches for the treatment of a complex thoracoabdominal aortic aneurysm (TAAA) patient. METHODS: A 73-year-old man presented with Crawford Type V TAAA was treated with a CMSG with four down-going directional branches including two proximal directional branches for the celiac artery and superior mesenteric artery and two distal side directional branches for the bilateral renal arteries. RESULTS: Postoperative course was unremarkable and 6-month follow-up demonstrated sac regression, absence of endoleaks, and all of the visceral branches remained patent. CONCLUSIONS: Total endovascular repair using CMSG with directional multibranches is a suitable alternative in higher risk patients with TAAA who are not suited for open surgery. Longer follow-up is needed to confirm the preliminary results.
Abstract Partial discharge (PD) localization is critical to ensure the safe operation of power equipment. In this paper, an optimization scheme is developed for PD positioning of external insulation equipment. The optimization scheme is based on an eight‐element cross sensor array to receive the ultrasonic signal generated by the PD, and uses the highly accurate 2‐D multiple signal classification (2‐D MUSIC) algorithm to locate the signal. Simulated discharge signal is adopted to test the optimization scheme, and the results show that the positioning error is less than 0.61° when the signal‐to‐noise ratio (SNR) is above −5 dB. In addition, three discharge models are tested at various locations. The average azimuth errors are 0.9°, 1.9°, and 1.55° for the needle‐plate, cone‐plate, and ball‐plate discharge models, respectively, and the average pitch angle errors are 0.75°, 2.1°, and 1.4°, respectively. These show that the needle‐plate model has the best positioning effect. Simulations and experiments are also carried out on the double discharge source scenario, and the error is within 2.2°. A PD location visualization equipment based on the proposed optimization scheme is developed and applied on‐site. The equipment is capable of satisfying the requirements of operation and maintenance.
Histone deacetylases (HDACs) engage in the regulation of various cellular processes by controlling global gene expression. The dysregulation of HDACs leads to carcinogenesis, making HDACs ideal targets for cancer therapy. However, the use of HDAC inhibitors (HDACi) as single agents has been shown to have limited success in treating solid tumors in clinical studies. This study aimed to identify a novel downstream effector of HDACs to provide a potential target for combination therapy.Transcriptome sequencing and bioinformatics analysis were performed to screen for genes responsive to HDACi in breast cancer cells. The effects of HDACi on cell viability were detected using the MTT assay. The mRNA and protein levels of genes were determined by quantitative reverse transcription-PCR (qRT-PCR) and Western blotting. Cell cycle distribution and apoptosis were analyzed by flow cytometry. The binding of CREB1 (cAMP-response element binding protein 1) to the promoter of the KDELR (The KDEL (Lys-Asp-Glu-Leu) receptor) gene was validated by the ChIP (chromatin immunoprecipitation assay). The association between KDELR2 and protein of centriole 5 (POC5) was detected by immunoprecipitation. A breast cancer-bearing mouse model was employed to analyze the effect of the HDAC3-KDELR2 axis on tumor growth.KDELR2 was identified as a novel target of HDAC3, and its aberrant expression indicated the poor prognosis of breast cancer patients. We found a strong correlation between the protein expression patterns of HADC3 and KDELR2 in tumor tissues from breast cancer patients. The results of the ChIP assay and qRT-PCR analysis validated that HDAC3 transactivated KDELR2 via CREB1. The HDAC3-KDELR2 axis accelerated the cell cycle progression of cancer cells by protecting the centrosomal protein POC5 from proteasomal degradation. Moreover, the HDAC3-KDELR2 axis promoted breast cancer cell proliferation and tumorigenesis in vitro and in vivo.Our results uncovered a previously unappreciated function of KDELR2 in tumorigenesis, linking a critical Golgi-the endoplasmic reticulum traffic transport protein to HDAC-controlled cell cycle progression on the path of cancer development and thus revealing a potential therapeutical target for breast cancer.
Two novel polymer network films (TCTSp-EP and OCTSp-EP) were prepared from tetra- and octacarbazolyl-substituted spirobifluorene star-shaped molecules (TCTSp and OCTSp) by electrochemical polymerization. The monomers had the expected aggregation-induced enhanced emission (AIEE) activity and exhibited excellent emission behavior in the aggregation state. The TCTSp and OCTSp had multiple electroactive carbazole groups which enabled the formation of polymer network films by electrochemical polymerization. Compared with TCTSp, the more carbazoles in the OCTSp improved the electrical activity and increased the film thickness growth rate. The films of TCTSp-EP and OCTSp-EP can be used for the high-sensitive and selective detection of 2,4,6-trinitrophenol (TNP) in water. The calculated Stern-Volmer quenching constants indicated that OCTSp-EP was more sensitive to TNP in water than TCTSp-EP. This was due to the hyperbranched structure of OCTSp-EP which had more exciton migration channels. The mechanism of TCTSp-EP and OCTSp-EP film for the detection of TNP was because of photo-induced electron transfer (PET) and fluorescence resonance energy transfer (FRET). Both of these films had excellent cycling performance which could be used to identify TNP in natural water.
Skin cancer, abnormal skin cell development, is a common and fatal type of cancer that occurs when skin is exposed to sunlight. Early diagnosis is important to prevent more serious consequences. Implementing a detection system would save more time for doctors and give patients efficient and low-cost diagnoses. In this paper, we built a skin cancer classification system based on Convoluted Neural Network (CNN) for seven majority skin cancers, and Natural Language Processing (NLP), for interaction with a human. We also implemented self-defined CNN, LeNet5, AlexNet, ResNet, VGG-16 in our system to compare their accuracy and discover reasons behind those output data. Finally, our self-defined CNN gets 0.8237 testing accuracy after training, LeNet5 results in 0.4857 testing accuracy, AlexNet produces 0.4715 testing accuracy, ResNet yields 0.8995 testing accuracy, and VGG-16 shown 0.7544 testing accuracy. The result indicates that ResNet-18 performs best through all models.
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