旨在分析子午岭黑山羊的群体遗传多样性和亲缘关系以及家系结构,为子午岭黑山羊的保护和利用提供依据。本研究通过简化基因组测序(super-genotyping by sequencing,Super-GBS)技术对99只(10公/89母)成年子午岭黑山羊进行全基因组SNP检...旨在分析子午岭黑山羊的群体遗传多样性和亲缘关系以及家系结构,为子午岭黑山羊的保护和利用提供依据。本研究通过简化基因组测序(super-genotyping by sequencing,Super-GBS)技术对99只(10公/89母)成年子午岭黑山羊进行全基因组SNP检测。利用Plink软件计算观测杂合度(Ho)、期望杂合度(He)、多态信息含量(PIC)、核苷酸多样性(Pi)、有效等位基因数(Ne)及次要等位基因频率(MAF)等6项遗传多样性指标;GCTA软件进行主成分分析及基因组亲缘关系G矩阵构建;Plink软件构建IBS遗传距离矩阵,R语言绘制热图;PHYLP构建系统发育树;detect RUNS工具检测ROH。结果表明,99只子午岭黑山羊个体共检测到996042个SNPs。子午岭黑山羊群体的PIC、Pi、Ne及MAF值分别是0.161、0.193、1.295、0.130,且Ho(0.167)低于He(0.192),说明子午岭黑山羊群体遗传多样性较低。G矩阵和IBS遗传距离结果均表明子午岭黑山羊群体间大部分个体间亲缘关系较远。主成分分析结果揭示子午岭黑山羊群体内部不存在明显分化,系统发育树结果说明子午岭黑山羊群体公羊可大致分为6个家系,所有家系公羊数量较少。子午岭黑山羊群体的近交系数FROH为0.0496,说明子午岭黑山羊群体内部近交程度相对较低。综上所述,子午岭黑山羊群体遗传多样性较低,大部分个体间亲缘关系较远,群体内近交程度较低,后期应注意后代的选育,避免血统流失。展开更多
While reliance on renewable energy resources has become a reality, there is still a need to deploy greener and more sustainable methods in order to achieve sustainable development goals. Indeed, green hydrogen is curr...While reliance on renewable energy resources has become a reality, there is still a need to deploy greener and more sustainable methods in order to achieve sustainable development goals. Indeed, green hydrogen is currently believed to be a reliable solution for global warming and the pollution challenges arising from fossil fuels, making it the resilient fuel of the future. However, the sustainability of green hydrogen technologies is yet to be achieved. In this context, generation of green hydrogen with the aid of deep eutectic solvents(DESs) as green mixtures has been demonstrated as a promising research area. This systematic review article covers green hydrogen generation through water splitting and biomass fermentation when DESs are utilized within the generation process. It also discusses the incorporation of DESs in fuel cell technologies. DESs can play a variety of roles such as solvent, electrolyte, or precursor;colloidal suspension and reaction medium;galvanic replacement, shape-controlling, decoration, or extractive agent;finally oxidant. These roles are relevant to several methods of green hydrogen generation, including electrocatalysis, photocatalysis, and fermentation. As such, it is of utmost importance to screen potential DES formulations and determine how they can function in and contribute throughout the green hydrogen mobility stages. The realization of super green hydrogen generation stands out as a pivotal milestone in our journey towards achieving a more sustainable form of development;DESs have great potential in making this milestone achievable. Overall, incorporating DESs in hydrogen generation constitutes a promising research area and offers potential scalability for green hydrogen production, storage,transport, and utilization.展开更多
Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution.However,obtained information of these con-volutional neural networks cannot completely exp...Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution.However,obtained information of these con-volutional neural networks cannot completely express predicted high‐quality images for complex scenes.A dynamic network for image super‐resolution(DSRNet)is presented,which contains a residual enhancement block,wide enhancement block,feature refine-ment block and construction block.The residual enhancement block is composed of a residual enhanced architecture to facilitate hierarchical features for image super‐resolution.To enhance robustness of obtained super‐resolution model for complex scenes,a wide enhancement block achieves a dynamic architecture to learn more robust information to enhance applicability of an obtained super‐resolution model for varying scenes.To prevent interference of components in a wide enhancement block,a refine-ment block utilises a stacked architecture to accurately learn obtained features.Also,a residual learning operation is embedded in the refinement block to prevent long‐term dependency problem.Finally,a construction block is responsible for reconstructing high‐quality images.Designed heterogeneous architecture can not only facilitate richer structural information,but also be lightweight,which is suitable for mobile digital devices.Experimental results show that our method is more competitive in terms of performance,recovering time of image super‐resolution and complexity.The code of DSRNet can be obtained at https://github.com/hellloxiaotian/DSRNet.展开更多
The top goal of modern medicine is treating disease without destroying organ structures and making patients as healthy as they were before their sickness.Minimally invasive surgery(MIS)has dominated the surgical realm...The top goal of modern medicine is treating disease without destroying organ structures and making patients as healthy as they were before their sickness.Minimally invasive surgery(MIS)has dominated the surgical realm because of its lesser invasiveness.However,changes in anatomical structures of the body and reconstruction of internal organs or different organs are common after traditional surgery or MIS,decreasing the quality of life of patients post-operation.Thus,I propose a new treatment mode,super MIS(SMIS),which is defined as“curing a disease or lesion which used to be treated by MIS while preserving the integrity of the organs”.In this study,I describe the origin,definition,operative channels,advantages,and future perspectives of SMIS.展开更多
文摘旨在分析子午岭黑山羊的群体遗传多样性和亲缘关系以及家系结构,为子午岭黑山羊的保护和利用提供依据。本研究通过简化基因组测序(super-genotyping by sequencing,Super-GBS)技术对99只(10公/89母)成年子午岭黑山羊进行全基因组SNP检测。利用Plink软件计算观测杂合度(Ho)、期望杂合度(He)、多态信息含量(PIC)、核苷酸多样性(Pi)、有效等位基因数(Ne)及次要等位基因频率(MAF)等6项遗传多样性指标;GCTA软件进行主成分分析及基因组亲缘关系G矩阵构建;Plink软件构建IBS遗传距离矩阵,R语言绘制热图;PHYLP构建系统发育树;detect RUNS工具检测ROH。结果表明,99只子午岭黑山羊个体共检测到996042个SNPs。子午岭黑山羊群体的PIC、Pi、Ne及MAF值分别是0.161、0.193、1.295、0.130,且Ho(0.167)低于He(0.192),说明子午岭黑山羊群体遗传多样性较低。G矩阵和IBS遗传距离结果均表明子午岭黑山羊群体间大部分个体间亲缘关系较远。主成分分析结果揭示子午岭黑山羊群体内部不存在明显分化,系统发育树结果说明子午岭黑山羊群体公羊可大致分为6个家系,所有家系公羊数量较少。子午岭黑山羊群体的近交系数FROH为0.0496,说明子午岭黑山羊群体内部近交程度相对较低。综上所述,子午岭黑山羊群体遗传多样性较低,大部分个体间亲缘关系较远,群体内近交程度较低,后期应注意后代的选育,避免血统流失。
基金the Ministry of Higher Education,Research and Innovation(MoHERI)Oman for their support of this research through TRC block funding Grant no.:BFP/RGP/EBR/22/378。
文摘While reliance on renewable energy resources has become a reality, there is still a need to deploy greener and more sustainable methods in order to achieve sustainable development goals. Indeed, green hydrogen is currently believed to be a reliable solution for global warming and the pollution challenges arising from fossil fuels, making it the resilient fuel of the future. However, the sustainability of green hydrogen technologies is yet to be achieved. In this context, generation of green hydrogen with the aid of deep eutectic solvents(DESs) as green mixtures has been demonstrated as a promising research area. This systematic review article covers green hydrogen generation through water splitting and biomass fermentation when DESs are utilized within the generation process. It also discusses the incorporation of DESs in fuel cell technologies. DESs can play a variety of roles such as solvent, electrolyte, or precursor;colloidal suspension and reaction medium;galvanic replacement, shape-controlling, decoration, or extractive agent;finally oxidant. These roles are relevant to several methods of green hydrogen generation, including electrocatalysis, photocatalysis, and fermentation. As such, it is of utmost importance to screen potential DES formulations and determine how they can function in and contribute throughout the green hydrogen mobility stages. The realization of super green hydrogen generation stands out as a pivotal milestone in our journey towards achieving a more sustainable form of development;DESs have great potential in making this milestone achievable. Overall, incorporating DESs in hydrogen generation constitutes a promising research area and offers potential scalability for green hydrogen production, storage,transport, and utilization.
基金the TCL Science and Technology Innovation Fundthe Youth Science and Technology Talent Promotion Project of Jiangsu Association for Science and Technology,Grant/Award Number:JSTJ‐2023‐017+4 种基金Shenzhen Municipal Science and Technology Innovation Council,Grant/Award Number:JSGG20220831105002004National Natural Science Foundation of China,Grant/Award Number:62201468Postdoctoral Research Foundation of China,Grant/Award Number:2022M722599the Fundamental Research Funds for the Central Universities,Grant/Award Number:D5000210966the Guangdong Basic and Applied Basic Research Foundation,Grant/Award Number:2021A1515110079。
文摘Convolutional neural networks depend on deep network architectures to extract accurate information for image super‐resolution.However,obtained information of these con-volutional neural networks cannot completely express predicted high‐quality images for complex scenes.A dynamic network for image super‐resolution(DSRNet)is presented,which contains a residual enhancement block,wide enhancement block,feature refine-ment block and construction block.The residual enhancement block is composed of a residual enhanced architecture to facilitate hierarchical features for image super‐resolution.To enhance robustness of obtained super‐resolution model for complex scenes,a wide enhancement block achieves a dynamic architecture to learn more robust information to enhance applicability of an obtained super‐resolution model for varying scenes.To prevent interference of components in a wide enhancement block,a refine-ment block utilises a stacked architecture to accurately learn obtained features.Also,a residual learning operation is embedded in the refinement block to prevent long‐term dependency problem.Finally,a construction block is responsible for reconstructing high‐quality images.Designed heterogeneous architecture can not only facilitate richer structural information,but also be lightweight,which is suitable for mobile digital devices.Experimental results show that our method is more competitive in terms of performance,recovering time of image super‐resolution and complexity.The code of DSRNet can be obtained at https://github.com/hellloxiaotian/DSRNet.
基金Supported by National Key R&D Programs of China,No.2022YFC2503600.
文摘The top goal of modern medicine is treating disease without destroying organ structures and making patients as healthy as they were before their sickness.Minimally invasive surgery(MIS)has dominated the surgical realm because of its lesser invasiveness.However,changes in anatomical structures of the body and reconstruction of internal organs or different organs are common after traditional surgery or MIS,decreasing the quality of life of patients post-operation.Thus,I propose a new treatment mode,super MIS(SMIS),which is defined as“curing a disease or lesion which used to be treated by MIS while preserving the integrity of the organs”.In this study,I describe the origin,definition,operative channels,advantages,and future perspectives of SMIS.
