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Article: Mixing Transition Characteristics of Binary Particles in a Fluidized Bed Using the Hilbert–Huang Transformation

Zhao, Yunxiang / Zhang, Lihui / Duan, Feng

Industrial & engineering chemistry process design and development. 2021 Dec. 06, v. 60, no. 49

2021

Abstract: The effects of superficial gas velocity, particle size, and mass fraction on the mixing transition characteristics of binary particles (biomass and quartz sand) were investigated in this study. The Hilbert–Huang transformation (HHT) was used to analyze ... ...

Abstract	The effects of superficial gas velocity, particle size, and mass fraction on the mixing transition characteristics of binary particles (biomass and quartz sand) were investigated in this study. The Hilbert–Huang transformation (HHT) was used to analyze the pressure fluctuation signals in a fluidized bed. The intrinsic mode function (IMF) of the differential pressure fluctuation signal was extracted to analyze the transition characteristics of the mixing behavior. The results indicated that the mixing behavior of binary particles can be divided into three patterns: complete segregation, transitional mixing, and complete mixing with an increase in the superficial gas velocity. Under a higher superficial gas velocity, the energy of the IMF gradually shifts from the high-frequency band to the medium-frequency band. When the mixing behavior of binary particles is in the stage of complete mixing, the energy in the middle-frequency band of the IMF is the largest, and the percent of its value remains unchanged. The critical velocity of complete mixing can be determined based on the change in the IMF energy at different superficial gas velocities. Compared with the traditional pressure drop analysis method, the HHT method can easily determine the critical velocity of complete mixing, which provides a theoretical basis for the further study of binary particles in a fluidized bed.
Keywords	biomass ; chemistry ; differential pressure ; energy ; fluidized beds ; particle size ; process design ; quartz ; sand
Language	English
Dates of publication	2021-1206
Size	p. 18058-18072.
Publishing place	American Chemical Society
Document type	Article
ZDB-ID	1484436-9
ISSN	1520-5045 ; 0888-5885
ISSN (online)	1520-5045
ISSN	0888-5885
DOI	10.1021/acs.iecr.1c03943
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Prediction of protein secondary structure based on deep residual convolutional neural network

Cheng, Jinyong / Xu, Ying / Zhao, Yunxiang

Biotechnology & Biotechnological Equipment. 2021 Jan. 1, v. 35, no. 1 p.1881-1890

2021

Abstract: Proteins play a vital role in organisms, which suggests that in-depth study of the function of proteins is helpful to the application of proteins in a more accurate and effective way. Accordingly, protein structure will become the focus of discussion and ...

Abstract	Proteins play a vital role in organisms, which suggests that in-depth study of the function of proteins is helpful to the application of proteins in a more accurate and effective way. Accordingly, protein structure will become the focus of discussion and research for a long time. In order to fully extract the effective information from the protein structure and improve the classification accuracy of the protein secondary sequence, a deep residual network model using different residual units was proposed to predict the secondary structure. This algorithm uses sliding window method to represent amino acid sequences and combines the powerful feature extraction ability of resent network. In this paper, the parameters of the neural network are debugged through experiments, and then the extracted features are classified and verified. The experimental results on CASP9, CASP10, CASP11 and CASP12 data sets imply that the improved deep residual network model based on different residual units can express amino acid sequences more accurately, which is more superior than existing methods.
Keywords	algorithms ; amino acids ; biotechnology ; equipment ; neural networks ; prediction ; protein secondary structure ; Convolutional neural networks ; protein ; residual network ; classification ; optimization
Language	English
Dates of publication	2021-0101
Size	p. 1881-1890.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	1214963-9
ISSN	1314-3530 ; 0205-2067 ; 1310-2818
ISSN (online)	1314-3530
ISSN	0205-2067 ; 1310-2818
DOI	10.1080/13102818.2022.2026815
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Article ; Online: Tailoring grain boundary stability of zinc-titanium alloy for long-lasting aqueous zinc batteries.

Zhao, Yunxiang / Guo, Shan / Chen, Manjing / Lu, Bingan / Zhang, Xiaotan / Liang, Shuquan / Zhou, Jiang

Nature communications

2023 Volume 14, Issue 1, Page(s) 7080

Abstract: The detrimental parasitic reactions and uncontrolled deposition behavior derived from inherently unstable interface have largely impeded the practical application of aqueous zinc batteries. So far, tremendous efforts have been devoted to tailoring ... ...

Abstract	The detrimental parasitic reactions and uncontrolled deposition behavior derived from inherently unstable interface have largely impeded the practical application of aqueous zinc batteries. So far, tremendous efforts have been devoted to tailoring interfaces, while stabilization of grain boundaries has received less attention. Here, we demonstrate that preferential distribution of intermetallic compounds at grain boundaries via an alloying strategy can substantially suppress intergranular corrosion. In-depth morphology analysis reveals their thermodynamic stability, ensuring sustainable potency. Furthermore, the hybrid nucleation and growth mode resulting from reduced Gibbs free energy contributes to the spatially uniform distribution of Zn nuclei, promoting the dense Zn deposition. These integrated merits enable a high Zn reversibility of 99.85% for over 4000 cycles, steady charge-discharge at 10 mA cm
Language	English
Publishing date	2023-11-04
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-42919-7
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Article ; Online: Motility-related microRNAs identified in pig seminal plasma exosomes by high-throughput small RNA sequencing.

Zhao, Yunxiang / Qin, Jiali / Sun, Jingshuai / He, Jian / Sun, Yanmei / Yuan, Renqiang / Li, Zhili

Theriogenology

2023 Volume 215, Page(s) 351–360

Abstract: Boar fertility is a key determinant of the production efficiency of the whole pig breeding industry and boar sperm motility is the seminal parameter with the greatest impact on the fecundity of a sow. Exosomes are small, extracellular vesicles found in ... ...

Abstract	Boar fertility is a key determinant of the production efficiency of the whole pig breeding industry and boar sperm motility is the seminal parameter with the greatest impact on the fecundity of a sow. Exosomes are small, extracellular vesicles found in many body fluids. Seminal plasma exosomes, which are secreted by the epididymis, prostate, seminal vesicles, and testes, contain a large number of miRNAs, the types and levels of which can reflect the physiological state of source cells. It has been shown that the expression profile of seminal plasma exosomal miRNA differs between low-motility semen and normal semen. The aim of this study was to investigate the relationship between semen motility and exosomal miRNA profiles to obtain information that would allow to predict boar fertility, as well as contribute to the understanding of the mechanisms by which exosomal miRNAs regulate semen motility. Three high-motility (semen motility >90 %) and three low-motility (semen motility <80 %) semen samples were collected from Landrace and Yorkshire boars, respectively, and seminal plasma exosomes were extracted by ultracentrifugation. Exosome characterization was performed using transmission electron microscopy, NTA, and Western blot. The expression profiles of exosomal miRNAs associated with semen motility in the two boar breeds were subsequently determined by small RNA sequencing. The results showed that 297 known miRNAs and 295 novel RNAs were co-expressed in the four groups. Notably, six miRNAs (ssc-miR-122-5p, ssc-miR-486, ssc-miR-451, ssc-miR-345-3p, ssc-miR-362, and ssc-miR-500-5p) were found to be differentially expressed in both boar breeds. Enrichment analysis of the target genes of the differentially expressed miRNAs showed that they were mainly involved in biological processes such as regulation of transcription from RNA polymerase II promoter, regulation of gene expression, and intracellular signal transduction and signaling pathways such as the PI3K-Akt, MAPK, and Ras signaling pathways. The six differentially expressed miRNAs identified in this study have significant potential as noninvasive markers of boar semen motility. Meanwhile, the results of the enrichment analysis provide novel insights into the mechanisms underlying the regulation of semen motility.
MeSH term(s)	Swine ; Male ; Animals ; Female ; Semen/metabolism ; MicroRNAs/genetics ; MicroRNAs/metabolism ; Exosomes/genetics ; Exosomes/metabolism ; Phosphatidylinositol 3-Kinases/metabolism ; Sperm Motility ; Sequence Analysis, RNA/veterinary
Chemical Substances	MicroRNAs ; Phosphatidylinositol 3-Kinases (EC 2.7.1.-)
Language	English
Publishing date	2023-12-03
Publishing country	United States
Document type	Journal Article
ZDB-ID	189232-0
ISSN	1879-3231 ; 0093-691X
ISSN (online)	1879-3231
ISSN	0093-691X
DOI	10.1016/j.theriogenology.2023.11.028
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Article ; Online: ECG signal classification based on deep CNN and BiLSTM.

Cheng, Jinyong / Zou, Qingxu / Zhao, Yunxiang

BMC medical informatics and decision making

2021 Volume 21, Issue 1, Page(s) 365

Abstract: Background: Currently, cardiovascular disease has become a major disease endangering human health, and the number of such patients is growing. Electrocardiogram (ECG) is an important basis for {medical doctors to diagnose the cardiovascular disease, ... ...

Abstract	Background: Currently, cardiovascular disease has become a major disease endangering human health, and the number of such patients is growing. Electrocardiogram (ECG) is an important basis for {medical doctors to diagnose the cardiovascular disease, which can truly reflect the health of the heart. In this context, the contradiction between the lack of medical resources and the surge in the number of patients has become increasingly prominent. The use of computer-aided diagnosis of cardiovascular disease has become particularly important, so the study of ECG automatic classification method has a strong practical significance. Methods: This article proposes a new method for automatic identification and classification of ECG.We have developed a dense heart rhythm network that combines a 24-layer Deep Convolutional Neural Network (DCNN) and Bidirectional Long Short-Term Memory (BiLSTM) to deeply mine the hierarchical and time-sensitive features of ECG data. Three different sizes of convolution kernels (32, 64 and 128) are used to mine the detailed features of the ECG signal, and the original ECG is filtered using a combination of wavelet transform and median filtering to eliminate the influence of noise on the signal. A new loss function is proposed to control the fluctuation of loss during the training process, and convergence mapping of the tan function in the range of 0-1 is employed to better reflect the model training loss and correct the optimization direction in time. Results: We applied the dataset provided by the 2017 PhysioNet/CINC challenge for verification. The experiment adopted ten-fold cross validation,and obtained an accuracy rate of 89.3[Formula: see text] and an F1 score of 0.891. Conclusions: This article proposes its own method in the aspects of ECG data preprocessing, feature extraction and loss function design. Compared with the existing methods, this method improves the accuracy of automatic ECG classification and is helpful for clinical diagnosis and self-monitoring of atrial fibrillation.
MeSH term(s)	Algorithms ; Atrial Fibrillation ; Diagnosis, Computer-Assisted ; Electrocardiography ; Humans ; Neural Networks, Computer ; Signal Processing, Computer-Assisted
Language	English
Publishing date	2021-12-28
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2046490-3
ISSN	1472-6947 ; 1472-6947
ISSN (online)	1472-6947
ISSN	1472-6947
DOI	10.1186/s12911-021-01736-y
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Article ; Online: UBE2C promotes myoblast differentiation and skeletal muscle regeneration through the Akt signaling pathway.

Yuan, Renqiang / Luo, Xiaorong / Liang, Ziyun / Cai, Shufang / Zhao, Yunxiang / Zhu, Qi / Li, Enru / Liu, Xiaohong / Mo, Delin / Chen, Yaosheng

Acta biochimica et biophysica Sinica

2024

Abstract: Ubiquitin-conjugation enzyme E2C (UBE2C) is a crucial component of the ubiquitin-proteasome system that is involved in numerous cancers. In this study, we find that UBE2C expression is significantly increased in mouse embryos, a critical stage during ... ...

Abstract	Ubiquitin-conjugation enzyme E2C (UBE2C) is a crucial component of the ubiquitin-proteasome system that is involved in numerous cancers. In this study, we find that UBE2C expression is significantly increased in mouse embryos, a critical stage during skeletal muscle development. We further investigate the function of UBE2C in myogenesis. Knockdown of
Language	English
Publishing date	2024-04-30
Publishing country	China
Document type	Journal Article
ZDB-ID	2175256-4
ISSN	1745-7270 ; 0582-9879 ; 1672-9145
ISSN (online)	1745-7270
ISSN	0582-9879 ; 1672-9145
DOI	10.3724/abbs.2024062
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Article: Dimension optimization for underground natural gas storage pipeline network coupling injection and production conditions

Zhou, Jun / Zhao, Yunxiang / Fu, Tiantian / Zhou, Xuan / Liang, Guangchuan

Energy. 2022 Oct. 01, v. 256

2022

Abstract: With the increasing proportion of natural gas consumption in the energy market, in order to meet the demand for seasonal peak regulation and emergency gas supply, it is urgent to research and develop the underground natural gas storage (UNGS). Different ... ...

Abstract	With the increasing proportion of natural gas consumption in the energy market, in order to meet the demand for seasonal peak regulation and emergency gas supply, it is urgent to research and develop the underground natural gas storage (UNGS). Different from the conventional oil and gas fields, the UNGS pipeline network needs to consider the boundary constraints under both injection and production conditions. Therefore, considering the characteristics of injection and production technology, this paper aims to constructs a Multiple Condition Hybrid model (MCH model) for optimizing the design parameters of UNGS pipeline network. This paper proposes a Hybrid Genetic Algorithm (HGA) for solving the MCH model of pipeline network design. In the solution of Case 1, HGA has a 10%–13% lower investment cost than GA while shortening the GA iterations by 50%–70%. Case 2 is revealed that the MCH model can be optimized to obtain lower pipeline network costs under the boundary of injection and production conditions. Finally, HGA is used to optimize the design parameters of the MCH model for the field example Case 3, and the pipeline network parameters are obtained that are about 17% lower than the field costs.
Keywords	algorithms ; energy ; markets ; models ; natural gas ; oils ; production technology
Language	English
Dates of publication	2022-1001
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	2019804-8
ISSN	0360-5442 ; 0360-5442
ISSN (online)	0360-5442
ISSN	0360-5442
DOI	10.1016/j.energy.2022.124651
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Article: Analysis of the Factors Affecting Boar culling in commercial Boar Studs in Southern China

Li, Zhili / Zhao, Yunxiang / Liao, Jiedan / Huang, Shujian

Indian journal of animal research. 2020 Mar., v. 54, no. 3

2020

Abstract: The objectives of this study were to measure culling frequency and analysis of reasons for boar culling in commercial boar studs. Data were obtained from nine commercial boar studs included 2342 culled boars in Southern China during July 2013 to June ... ...

Abstract	The objectives of this study were to measure culling frequency and analysis of reasons for boar culling in commercial boar studs. Data were obtained from nine commercial boar studs included 2342 culled boars in Southern China during July 2013 to June 2016. Descriptive statistics of reasons for boar culling revealed that the frequency of unplanned cull boar accounted for a large proportion (88.04%), reproductive disorders (40.61%) and lameness (27.2%) were the most frequently cited reasons. Sperm-related problems accounted for the largest proportion (668, 70.24%) due to reproductive disorders, followed by the abnormal genital system (169, 17.78%). The highest frequency of reproductive disorders was arisen in May (17.98%), and the relatively high culling frequency lasted for 16 weeks until August (10.00%), especially for the Yorkshire boar that owned highest culling risk (47.09%) with the culled number reached peak in May (60, 21.82%), followed by July (33, 12.00%). In addition, the highest frequency of boar culling due to lameness appeared in May (90, 14.13%), followed by January (68, 10.68%) and December (66, 10.36%) with cold and wet. It was speculated that extreme weather was more likely to cause lameness. Our research suggested farmers under subtropical climate should take effective measures to reduce heat and humidity stress at the earliest, preferably from late spring to August to improve reproductive efficiency on boar studs and also take breed differences into their decision-making processes to ensure adequate boar power and customer satisfaction.
Keywords	animal research ; boars ; cold ; consumer satisfaction ; decision making ; descriptive statistics ; heat ; humidity ; lameness ; reproductive efficiency ; risk ; spring ; subtropics ; China
Language	English
Dates of publication	2020-03
Size	p. 286-292.
Publishing place	Agricultural Research Communication Centre
Document type	Article
Note	NAL-light
ISSN	0976-0555
DOI	10.18805/ijar.B-773
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Evaluating the effect of SARS-CoV-2 spike mutations with a linear doubly robust learner.

Wang, Xin / Hu, Mingda / Liu, Bo / Xu, Huifang / Jin, Yuan / Wang, Boqian / Zhao, Yunxiang / Wu, Jun / Yue, Junjie / Ren, Hongguang

Frontiers in cellular and infection microbiology

2023 Volume 13, Page(s) 1161445

Abstract: Driven by various mutations on the viral Spike protein, diverse variants of SARS-CoV-2 have emerged and prevailed repeatedly, significantly prolonging the pandemic. This phenomenon necessitates the identification of key Spike mutations for fitness ... ...

Abstract	Driven by various mutations on the viral Spike protein, diverse variants of SARS-CoV-2 have emerged and prevailed repeatedly, significantly prolonging the pandemic. This phenomenon necessitates the identification of key Spike mutations for fitness enhancement. To address the need, this manuscript formulates a well-defined framework of causal inference methods for evaluating and identifying key Spike mutations to the viral fitness of SARS-CoV-2. In the context of large-scale genomes of SARS-CoV-2, it estimates the statistical contribution of mutations to viral fitness across lineages and therefore identifies important mutations. Further, identified key mutations are validated by computational methods to possess functional effects, including Spike stability, receptor-binding affinity, and potential for immune escape. Based on the effect score of each mutation, individual key fitness-enhancing mutations such as D614G and T478K are identified and studied. From individual mutations to protein domains, this paper recognizes key protein regions on the Spike protein, including the receptor-binding domain and the N-terminal domain. This research even makes further efforts to investigate viral fitness
MeSH term(s)	Mutation ; SARS-CoV-2/genetics ; Spike Glycoprotein, Coronavirus/genetics
Chemical Substances	Spike Glycoprotein, Coronavirus ; spike protein, SARS-CoV-2
Language	English
Publishing date	2023-04-19
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2619676-1
ISSN	2235-2988 ; 2235-2988
ISSN (online)	2235-2988
ISSN	2235-2988
DOI	10.3389/fcimb.2023.1161445
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Article: Metabolomic analysis reveals spermatozoa and seminal plasma differences between Duroc and Liang guang Small-spotted pig.

Li, Zhili / Sun, Jingshuai / Li, Kebiao / Qin, Jiali / Sun, Yanmei / Zeng, Jianhua / El-Ashram, Saeed / Zhao, Yunxiang

Frontiers in veterinary science

2023 Volume 9, Page(s) 1078928

Abstract: The Liang guang Small-spotted pig is a well-known Chinese indigenous pig that is valued for its exceptional meat quality. However, the Liang guang Small-spotted pig has a lower semen storage capacity, shorter storage time and worse semen quality compared ...

Abstract	The Liang guang Small-spotted pig is a well-known Chinese indigenous pig that is valued for its exceptional meat quality. However, the Liang guang Small-spotted pig has a lower semen storage capacity, shorter storage time and worse semen quality compared to Duroc. Pig sperm used for artificial insemination (AI) loses part of vitality and quality when being stored in commercial solutions. Serious vitality losses and short shelf life of the semen are particularly prominent in Liang guang Small-spotted pig. In this study, the metabolites in seminal plasma and spermatozoa of Duroc and Liang guang Small-spotted pigs were identified using UHPLC-Q-TOF/MS technology. The findings indicated forty distinct metabolites concentrating on energy metabolic substrates and antioxidant capacity in Liang guang Small-spotted pig and Duroc seminal plasma, including D-Fructose, succinate, 2-dehydro-3-deoxy-d-gluconate, alanine betaine, citrate, carnitine, acetylcarnitine and so on. Seventeen different metabolites were explored, with a focus on glycerophospholipid metabolism in Liang guang Small-spotted pig and Duroc spermatozoa, primarily including glycerol 3-phosphate, acetylcarnitine, phosphatidylcholine (PC) 16:0/16:0, palmitoyl sphingomyelin, acetylcholine, choline, glycerophosphocholine, betaine, L-carnitine, creatinine and others. This study reveals the metabolite profile of spermatozoa and seminal plasma among different pig breeds and might be valuable for understanding the mechanisms that lead to sperm storage capacity. Metabolites involved in energy metabolism, antioxidant capacity and glycerophospholipid metabolism might be key to the poor sperm storage capacity in Liang guang Small-spotted pig.
Language	English
Publishing date	2023-01-06
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2834243-4
ISSN	2297-1769
ISSN	2297-1769
DOI	10.3389/fvets.2022.1078928
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