Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Animal Husbandry and Veterinary Medicine submitted time 2023-06-11
Sun, Honglei
Tong, Qi
Yu, Haili
Han, Qiqi
Li, Han
Chang, Haoyu
Qu, Yajin
Xu, Jie
Liu, Sidang
Liu, Jinhua
Abstract： The novel avian influenza viruses (AIVs) can cause serious economic losses to the poultry industry. Systematic surveillance of novel AIVs in poultry is essential for control of avian influenza. In the present research, we isolated H3N3 subtypes AIVs from chicken farms reporting illness in China during 2022–2023. All of these chickens showed respiratory disease signs and a 10-40% reduction in egg production. We conducted epidemiological surveys, virus isolation and identification, sequence analysis, and chicken infection experiments. The results showed that: 1) In December 2022, H3N3 AIVs was first found in a layer chicken flock in Eastern China, and the virus was transmitted to multiple Provinces with high density chicken populations in a short time. 2) Sequence analysis showed that the novel H3N3 AIVs were evolving as a triple reassortment event, which bears H3N8-derived HA gene, H10N3-derived NA gene and H9N2-derived internal genes. 3) The novel H3N3 AIVs were highly susceptible to SPF chickens. The virus replicated efficiently in the concha nasalis, trachea, lungs and Harders glands and infected chickens showed pathological damage. 4) H3N3 viruses were airborne transmission among chickens, whereas H3N8 viruses were not. In conclusion, the novel reassortment H3N3 virus showed pathogenicity and airborne transmissibility in chickens. Therefore, comprehensive surveillance of H3N3 AIVs in domestic poultry is imperative and control of the virus endemic is needed.
Peer Review Status:
Awaiting Review
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： Substance addiction involves multiple factors, ranging from biological, social, to cultural. But the dominant biological reductionism-based explanations focus primarily on the brain, potentially hindering a more comprehensive and inclusive research of substance addiction and its recovery. We propose that network theory, focusing on feedback loops formed by interactions between myriad psychological disorder variables, will provide a better holistic framework to understand the complexity of substance addiction. Applying network theory to substance addiction may provide new insights in (1) understanding the interrelationships and interactions between symptoms, (2) understanding the systematic integrity and dynamic changes in symptom networks, and (3) integrating multiple levels of factors into a unified theoretical framework. Also, network theory may generate new approaches for future interventions and treatments. In sum, networktheory, as a theoretical model, provide a new perspective for understanding substance addiction and its intervention. We believe this reframing will encourage more empirical research toward various other hypotheses within this framework, thus, promoting the treatment and recovery of substance addiction.
Subjects: Psychology >> Clinical and Counseling Psychology Subjects: Psychology >> Psychological Measurement submitted time 2022-07-28
Abstract：
Substance addiction involves multiple factors, ranging from biological, social, to cultural. But the dominant biological reductionism-based explanations focus primarily on the brain, potentially hindering a more comprehensive and inclusive research of substance addiction and its recovery. We propose that network theory, focusing on feedback loops formed by interactions between myriad psychological disorder variables, will provide a better holistic framework to understand the complexity of substance addiction. Applying network theory to substance addiction may provide new insights in (1) understanding the interrelationships and interactions between symptoms, (2) understanding the systematic integrity and dynamic changes in symptom networks, and (3) integrating multiple levels of factors into a unified theoretical framework. Also, network theory may generate new approaches for future interventions and treatments. In sum, networktheory, as a theoretical model, provide a new perspective for understanding substance addiction and its intervention. We believe this reframing will encourage more empirical research toward various other hypotheses within this framework, thus, promoting the treatment and recovery of substance addiction.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2022-05-10 Cooperative journals: 《计算机应用研究》
Abstract： Aiming at the shortcomings of Butterfly optimization algorithm, such as poor population diversity, low optimization accuracy and slow convergence speed, this paper proposed a self-adaptive Gaussian keyhole imaging butterfly optimization algorithm based on Latin hypercube sampling. Firstly, it used a Latin hypercube sampling population initialization strategy to enhance the population diversity and thereby improve the overall search ability of the algorithm. Then, it introduced the self-adaptive optimal guidance strategy, which can dynamically adjust the search range in different evolutionary periods to balance the global and local search capabilities and hence improve the optimization accuracy of the algorithm. Finally, it adopted a Gaussian keyhole imaging strategy to disturb the optimal individuals, making the individuals of the population moving close to the optimal individuals, so as to further improve the solution accuracy and speed up the convergence of the algorithm. Through simulation experiments and Wilcoxon rank sum tests using 14 benchmark functions, the results showed that the performance of the improved algorithm is greatly enhanced in terms of optimization accuracy, convergence speed, stability and scalability.
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