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  • MDPI AG  (15)
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  • MDPI AG  (15)
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  • 1
    Online Resource
    Online Resource
    MDPI AG ; 2020
    In:  Sensors Vol. 20, No. 19 ( 2020-10-01), p. 5612-
    In: Sensors, MDPI AG, Vol. 20, No. 19 ( 2020-10-01), p. 5612-
    Abstract: The Internet of Vehicle (IoV) technology is one of the most important technologies of modern intelligent transportation. The data transmission scheduling method is a research hotspot in the technology of IoV. It is a challenge to ensure the stability of data transmission due to fast network topology changes, high data transmission delays, and some other reasons. Aiming at the above problems, a multi-channel data transmission cooperative scheduling algorithm is proposed. First, construct a feasible interference map based on the data items sent and received by vehicles in the road scene. Second, assign channels to the nodes in the interference map based on the Signal-to-Interference-Noise-Ratio (SINR). Finally, the optimal multi-channel data transmission cooperative scheduling scheme is achieved through the ISing model. Simulation results show that compared with the traditional algorithm, the network service capacity is increased by about 31% and the service delay is reduced by about 20%. It ensures that emergency data is preferentially transmitted to the target vehicle and the maximum weighted service capacity of the network.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2052857-7
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  • 2
    Online Resource
    Online Resource
    MDPI AG ; 2016
    In:  International Journal of Molecular Sciences Vol. 17, No. 4 ( 2016-04-22), p. 610-
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 17, No. 4 ( 2016-04-22), p. 610-
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 3
    In: Genes, MDPI AG, Vol. 13, No. 11 ( 2022-11-06), p. 2049-
    Abstract: Ticks rank second in the world as vectors of disease. Tick infestation is one of the factors threatening the health and survival of giant pandas. Here, we describe the mitogenomes of Ixodes acutitarsus and Ixodes ovatus parasitizing giant pandas, and perform comparative and phylogenetic genomic analyses on the newly sequenced and other available mitogenomes of hard ticks. All six newly determined mitogenomes contain a typical gene component and share an ancient Arthropoda gene arrangement pattern. Our study suggests that I. ovatus is a species complex with high genetic divergence, indicating that different clades of I. ovatus represent distinct species. Comparative mitogenomic analyses show that the average A + T content of Ixodidae mitogenomes is 78.08%, their GC-skews are strongly negative, while AT-skews fluctuate around 0. A large number of microsatellites are detected in Ixodidae mitogenomes, and the main microsatellite motifs are mononucleotide A and trinucleotide AAT. We summarize five gene arrangement types, and identify the trnY-COX1-trnS1-COX2-trnK-ATP8-ATP6-COX3-trnG fragment is the most conserved region, whereas the region near the control region is the rearrangement hotspot in Ixodidae mitogenomes. The phylogenetic trees based on 15 genes provide a very convincing relationship (Ixodes + (Robertsicus + ((Bothriocroton + Haemaphysalis) + (Amblyomma + (Dermacentor + (Rhipicentor + (Hyalomma + Rhipicephalus))))))) with very strong supports. Remarkably, Archaeocroton sphenodonti is embedded in the Haemaphysalis clade with strong supports, resulting in paraphyly of the Haemaphysalis genus, so in-depth morphological and molecular studies are essential to determine the taxonomic status of A. sphenodonti and its closely related species. Our results provide new insights into the molecular phylogeny and evolution of hard ticks, as well as basic data for population genetics assessment and efficient surveillance and control for the giant panda-infesting ticks.
    Type of Medium: Online Resource
    ISSN: 2073-4425
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527218-4
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  • 4
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 23, No. 15 ( 2022-07-31), p. 8515-
    Abstract: Type III CRISPR-Cas systems show the target (tg)RNA-activated indiscriminate DNA cleavage and synthesis of oligoadenylates (cOA) and a secondary signal that activates downstream nuclease effectors to exert indiscriminate RNA/DNA cleavage, and both activities are regulated in a spatiotemporal fashion. In III-B Cmr systems, cognate tgRNAs activate the two Cmr2-based activities, which are then inactivated via tgRNA cleavage by Cmr4, but how Cmr4 nuclease regulates the Cmr immunization remains to be experimentally characterized. Here, we conducted mutagenesis of Cmr4 conserved amino acids in Saccharolobus islandicus, and this revealed that Cmr4α RNase-dead (dCmr4α) mutation yields cell dormancy/death. We also found that plasmid-borne expression of dCmr4α in the wild-type strain strongly reduced plasmid transformation efficiency, and deletion of CRISPR arrays in the host genome reversed the dCmr4α inhibition. Expression of dCmr4α also strongly inhibited plasmid transformation with Cmr2αHD and Cmr2αPalm mutants, but the inhibition was diminished in Cmr2αHD,Palm. Since dCmr4α-containing effectors lack spatiotemporal regulation, this allows an everlasting interaction between crRNA and cellular RNAs to occur. As a result, some cellular RNAs, which are not effective in mediating immunity due to the presence of spatiotemporal regulation, trigger autoimmunity of the Cmr-α system in the S. islandicus cells expressing dCmr4α. Together, these results pinpoint the crucial importance of tgRNA cleavage in autoimmunity avoidance and in the regulation of immunization of type III systems.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 5
    Online Resource
    Online Resource
    MDPI AG ; 2016
    In:  Sensors Vol. 16, No. 5 ( 2016-04-28), p. 611-
    In: Sensors, MDPI AG, Vol. 16, No. 5 ( 2016-04-28), p. 611-
    Type of Medium: Online Resource
    ISSN: 1424-8220
    Language: English
    Publisher: MDPI AG
    Publication Date: 2016
    detail.hit.zdb_id: 2052857-7
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  • 6
    In: Animals, MDPI AG, Vol. 9, No. 10 ( 2019-10-15), p. 804-
    Abstract: Keel fracture has negative effects on the health and welfare of laying hens. We investigated effects of keel fracture on stress, inflammation, and the orexin system in laying hens. Ninety 17-week-old Lohmann white laying hens were palpated and euthanatized at 42 weeks old, and marked as normal keel (NK)/fractured keel (FK) from absence/presence of keel fracture. Serum, brain, liver, and abdominal-muscle samples were collected from 10 NK and 10 FK hens to determine the stress and inflammatory responses and the activity of orexin systems by corticosterone content, expression of heat shock proteins (TNF-α 60, 70, 90), and inflammatory factors (tumor necrosis factor (TNF)-α, nuclear factor-kappa Bp65 (NF-κBp65), inducible nitric oxide synthase (iNOS), prostaglandin E synthases (PTGEs), cyclooxygenase-2 (COX-2), interleukin-1β (IL-1β)), orexin (ORX), and orexin-receptor 1/2 (ORXR1/ORXR2). The FK hens had higher serum corticosterone content, Hsps, and inflammatory factor mRNA expression levels than NK hens, although levels of iNOS in the liver and TNF-α in the muscle were similar. Protein levels of Hsp70 and Hsp90 in the brain and liver, iNOS and COX-2 in the liver, NF-κBp65, iNOS, and COX-2 in the brain of FK hens were increased compared with NK hens. Furthermore, FK hens had lower mRNA expression of ORX, ORXR1, and ORXR2 than NK hens. Therefore, keel fracture causes stress and inflammation, and inhibits the expression of the orexin system in laying hens.
    Type of Medium: Online Resource
    ISSN: 2076-2615
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2606558-7
    SSG: 23
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  • 7
    In: Pathogens, MDPI AG, Vol. 11, No. 12 ( 2022-12-02), p. 1463-
    Abstract: Anthracnose is a disease caused by Colletotrichum species. They are well known as major plant pathogens, and a black stem disease, specifically caused by Colletotrichum truncatum and primarily infecting sword bean (Canavalia gladiata), was observed in the Yunnan province, China. To aid disease management and to determine pathogenic characteristics, the species causing the leaf spot disease of hairy vetch was verified as C. truncatum. A sequence analysis of the ITS, ACT, GAPDH, and HIS3 genes was conducted, as well as morphological and cultural characteristics, to identify this Colletotrichum species, which has curved conidia. C. truncatum isolates from sword bean formed a distinctive group among Colletotrichum species, including those that infect other forage and field crops. Artificially inoculated sword bean seedlings showed typical symptoms of anthracnose, which were similar to field observations. To the best of our knowledge, this is the first report of C. truncatum causing black stem disease on sword beans in China.
    Type of Medium: Online Resource
    ISSN: 2076-0817
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2695572-6
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  • 8
    Online Resource
    Online Resource
    MDPI AG ; 2022
    In:  Remote Sensing Vol. 14, No. 21 ( 2022-10-28), p. 5418-
    In: Remote Sensing, MDPI AG, Vol. 14, No. 21 ( 2022-10-28), p. 5418-
    Abstract: Prediction of ionospheric parameters, such as ionospheric F2 layer critical frequency (foF2) at low latitude regions is of significant interest in understanding ionospheric variation effects on high-frequency communication and global navigation satellite system. Currently, deep learning algorithms have made a striking accomplishment in capturing ionospheric variability. In this paper, we use the state-of-the-art hybrid neural network combined with a quantile mechanism to predict foF2 parameter variations under low and high solar activity years (solar cycle-24) and space weather events. The hybrid neural network is composed of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), in which CNN and BiLSTM networks extracted spatial and temporal features of ionospheric variation, respectively. The proposed method was trained and tested on 5 years (2009–2014) of ionospheric foF2 observation data from Advanced Digital Ionosonde located in Brisbane, Australia (27°53′S, 152°92′E). It is evident from the results that the proposed model performs better than International Reference Ionosphere 2016 (IRI-2016), long short-term memory (LSTM), and BiLSTM ionospheric prediction models. The proposed model extensively captured the variation in ionospheric foF2 feature, and better predicted it under two significant space weather events (29 September 2011 and 22 July 2012).
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2513863-7
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  • 9
    In: Entropy, MDPI AG, Vol. 24, No. 11 ( 2022-10-26), p. 1541-
    Abstract: Utilizing fountain codes to control the peak-to-average power ratio (PAPR) is a classic scheme in Orthogonal Frequency Division Multiplexing (OFDM) wireless communication systems. However, because the robust soliton distribution (RSD) produces large-degree values, the decoding performance is severely reduced. In this paper, we design statistical degree distribution (SD) under a scenario that utilizes fountain codes to control the PAPR. The probability of the PAPR produced is combined with RSD to design PRSD, which enhances the smaller degree value produced. Subsequently, a particle swarm optimization (PSO) algorithm is used to search the optimal degree value between the binary exponential distribution (BED) and PRSD distribution according to the minimum average degree principle. Simulation results demonstrate that the proposed method outperforms other relevant degree distributions in the same controlled PAPR threshold, and the average degree value and decoding efficiency are remarkably improved.
    Type of Medium: Online Resource
    ISSN: 1099-4300
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2014734-X
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  • 10
    In: Animals, MDPI AG, Vol. 14, No. 2 ( 2024-01-17), p. 294-
    Abstract: Porcine epidemic diarrhea virus (PEDV) is a porcine enteric coronavirus, which is one of the main causative agents of porcine epidemic diarrhea (PED), with 100% morbidity and 80–100% mortality in neonatal piglets. Since 2010, large-scale PED caused by highly pathogenic variants of PEDV has occurred successively in China and other countries in the world, posing a great threat to the global pig industry. It has been demonstrated in many investigations that the classic attenuated vaccine strain, PEDV CV777, is insufficient to fully protect against the PEDV variants. Moreover, the maternally derived antibodies elicited by inactivated vaccines also cannot completely protect piglets from infection. In addition, feedback feeding poses a risk of periodic PEDV recurrence in pig farms, making it challenging to successfully limit the spread of PEDV in China. This review focuses on the etiology, epidemiology, antigenicity, and control strategies of PEDV in China and provides information for the formulation of effective control measures.
    Type of Medium: Online Resource
    ISSN: 2076-2615
    Language: English
    Publisher: MDPI AG
    Publication Date: 2024
    detail.hit.zdb_id: 2606558-7
    SSG: 23
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