基于Super-GBS简化基因组测序技术的柞蚕SNP位点挖掘

基于Super-GBS基因分型(super-genotyping-by-sequencing)技术开展柞蚕单核苷酸多态性标记(single nucleotide polymorphism,SNP)位点挖掘研究,旨在开发性状关联SNP分子标记,为柞蚕种质资源评价鉴定、遗传图谱构建、QTL定位提供数据支撑。以白体色小白蚕为母本、黄体色H04为父本,获得BC1M群体(110个)、F_(1)(3个)、P_(1)(1个)、P_(2)(1个)总计115个柞蚕材料,利用PstⅠ-HF/MspⅠ双酶切基因组构建Super-GBS文库并测序,使用BWA软件将过滤后的序列数据比对到柞蚕参考基因组,采用GATK软件开发SNP标记,使用SnpEff软件注释SNP位点及R语言分析遗传结构。测序共产生序列数据量为106.39 Gb,过滤后的平均读长为0.89 Gb,Q30测序质量值平均为90.11%,比对率平均为98.48%。共得到有效SNP位点141100个,主要位于基因间隔区、内含子区、基因下游、上游,其中C/T、A/G变异类型最多,转换与颠换的比例为1.296187∶1。SNP位点变异主要为同义突变和错义突变,产生修饰(MODIFIER)影响。主成分与聚类分析将115个样品分为4组(P_(1)、P_(2)、F_(1)、BC_(1)M),反映了样品的遗传背景及亲缘关系,群体遗传分化指数F_(ST)在0.0003777~0.8272间,群体遗传距离DR分布在0.0004~1.7556,F_(ST)与DR均表现出明显的遗传背景上的聚类。结果表明,Super-GBS技术能够获得大量柞蚕SNP位点信息,可用于SNP标记开发,且开发的SNP标记能够对115个样品的亲缘关系、体色演变进行解释,为今后柞蚕种质资源评价与鉴定、分子标记辅助育种工作奠定基础。

Super-Boost变换器的工作模式及输出纹波电压分析

Super-Boost变换器代替传统的充、放电模块可大大减小电源的质量和体积,提高其功率密度,因此在空间电力系统中具有广阔的应用前景。但由于Super-Boost变换器有多个功率元件,且存在电感电流反向流动特性,导致其供能模式及输出纹波电压较传统Boost变换器复杂。为了给Super-Boost变换器的分析和设计提供正确的理论指导,对Super-Boost变换器供能模式及输出纹波电压进行了深入研究。研究发现,电感L_(1)和L_(2)均存在连续导电模式、伪连续导电模式和伪断续导电模式等工作模式,建立各工作模式的临界电感和输出纹波电压解析数学模型,探讨峰值电流与电感间的关系,得到了满足设计要求的最小电容和最小电感,据此给出了变换器参数设计方法,实验结果验证了理论分析的正确性。

基于Super-Twisting滑模S面的无人机路径跟踪控制

针对小型固定翼无人机在执行任务时跟踪精度低以及容易受外界风影响的问题,设计基于Super-Twisting滑模S面(STSM S-Plane)的路径跟踪控制器,同时采用内外双环控制模式。外环即速度环采用Super-Twisting滑模控制,内环即姿态环采用S面控制。考虑到S面控制求导易导致积分爆炸的问题引入了二阶微分器,并对外界风组成进行建模研究。最后通过空间特殊曲线来验证所设计算法的控制性能。仿真结果表明,所设计的算法可以实现固定翼无人机对期望路径的精确跟踪,并具有良好的鲁棒性和抗干扰性能。

组态视角下我国物流业绿色全要素生产率提升路径研究--基于Super-SBM-Malmquist与fsQCA方法

通过整合TOE框架,提取互联网发展水平、新能源比例、创新能力、物流业集聚程度、市场化水平和对外开放程度6个指标为前因变量,以物流业绿色全要素生产率为结果变量,将我国30个省(自治区、直辖市)数据作为研究样本,运用fsQCA方法揭示导致我国物流业产生高与非高绿色全要素生产率的组态路径。研究发现:“十三五”期间我国物流业绿色全要素生产率持续进步;大部分省市区的物流业绿色全要素生产率有提升;产生高物流业绿色全要素生产率的路径可归纳为“互联网-对外开放-创新”驱动型、“互联网-对外开放-新能源-物流业集聚”驱动型和“新能源-市场化-物流业集聚”驱动型三种。

TP347H与Super304H耐热钢热疲劳过程的变形与开裂行为研究

基于金属板材热疲劳试验方法(HB 6660-2011),对比分析了TP347H和Super304H两种耐热钢的供货态、相同热处理条件下的固溶态和时效态试样在热疲劳过程中底部尺寸的变形行为,以及缺口部位裂纹形貌。结果表明:这3种状态Super304H钢在热疲劳试验后的变形均小于相应TP347H钢的,TP347H缺口呈现相对较大的钝化,时效态试样钝化最大,裂纹最短。缺口附近的观察结果,TP347H在缺口附近龟裂损伤程度弱于Super304H钢的,开裂方式主要为沿晶开裂,也有部分穿晶开裂。

Image super‐resolution via dynamic network

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.

结合改进FPFH的Super-4PCS点云配准方法

针对超四点快速鲁棒匹配算法(Super-4PCS)粗匹配过程计算复杂度较高,配准时间长等问题,提出一种结合改进快速点特征直方图(FPFH)的Super-4PCS粗配准算法。通过主成分分析法(PCA)从快速点特征直方图中筛选出能代表点云特征信息的特征点,并将筛选出的特征点云作为输入数据进行Super-4PCS粗配准,由Super-4PCS粗配准得到初始变换矩阵,再进一步进行最近点迭代算法(ICP)精配准。为了验证在不同密度点云下的匹配效率,分别使用Bunny、Dragon两种不同密度的点云数据集进行配准实验,在满足精配准精度的基础上,对比FPFH-SAC和Super-4PCS粗配准方法,粗配准速率分别提升了72%和58%,总体配准速率分别提升了43%和32%。

Connotation,pathway and significance of carbon neutrality“super energy system”:A case study of the Ordos Basin,NW China

Super oil and gas basins provide the energy foundation for social progress and human development.In the context of climate change and carbon peak and carbon neutrality goals,constructing an integrated energy and carbon neutrality system that balances energy production and carbon reduction becomes crucial for the transformation of such basins.Under the framework of a green and intelligent energy system primarily based on“four news”,new energy,new electricity,new energy storage,and new intelligence,integrating a“super energy system”composed of a huge amount of underground resources of coal,oil,gas and heat highly overlapping with abundant wind and solar energy resources above ground,and a regional intelligent energy consumption system with coordinated development and utilization of fossil energy and new energy,with a carbon neutrality system centered around carbon cycling is essential.This paper aims to select the traditional oil and gas basins as“super energy basins”with the conditions to build world-class energy production and demonstration bases for carbon neutrality.The Ordos Basin has unique regional advantages,including abundant fossil fuel and new energy resources,as well as matching CO_(2)sources and sinks,position it as a carbon neutrality“super energy basin”which explores the path of transformation of traditional oil and gas basins.Under the integrated development concept and mode of“coal+oil+gas+new energy+carbon capture,utilization and storage(CCUS)/carbon capture and storage(CCS)”,the carbon neutrality in super energy basin is basically achieved,which enhance energy supply and contribute to the carbon peak and carbon neutrality goals,establish a modern energy industry and promote regional green and sustainable development.The pioneering construction of the world-class carbon neutrality“super energy system”demonstration basin in China represented by the Ordos Basin will reshape the new concept and new mode of exploration and development of super energy basins,which is of great significance to the global energy revolution under carbon neutrality.

Deep eutectic solvents:Green multi-task agents for sustainable super green hydrogen technologies

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.

A Unified Model Fusing Region of Interest Detection and Super Resolution for Video Compression

High-resolution video transmission requires a substantial amount of bandwidth.In this paper,we present a novel video processing methodology that innovatively integrates region of interest(ROI)identification and super-resolution enhancement.Our method commences with the accurate detection of ROIs within video sequences,followed by the application of advanced super-resolution techniques to these areas,thereby preserving visual quality while economizing on data transmission.To validate and benchmark our approach,we have curated a new gaming dataset tailored to evaluate the effectiveness of ROI-based super-resolution in practical applications.The proposed model architecture leverages the transformer network framework,guided by a carefully designed multi-task loss function,which facilitates concurrent learning and execution of both ROI identification and resolution enhancement tasks.This unified deep learning model exhibits remarkable performance in achieving super-resolution on our custom dataset.The implications of this research extend to optimizing low-bitrate video streaming scenarios.By selectively enhancing the resolution of critical regions in videos,our solution enables high-quality video delivery under constrained bandwidth conditions.Empirical results demonstrate a 15%reduction in transmission bandwidth compared to traditional super-resolution based compression methods,without any perceivable decline in visual quality.This work thus contributes to the advancement of video compression and enhancement technologies,offering an effective strategy for improving digital media delivery efficiency and user experience,especially in bandwidth-limited environments.The innovative integration of ROI identification and super-resolution presents promising avenues for future research and development in adaptive and intelligent video communication systems.

Trend of Storm Surge Induced by Typical Landfall Super Typhoons During 1975–2021 in the Eastern China Sea

Climate change affects the activity of global and regional tropical cyclones(TCs).Among all TCs,typical super typhoons(STYs)are particularly devastating because they maintain their intensity when landing on the coast and thus cause casualties,economic losses,and environmental damage.Using a 3D tidal model,we reconstructed the typhoon(TY)wind field to simulate the storm surge induced by typical STYs.The TY activity was then analyzed using historical data.Results showed a downtrend of varying degrees in the annual frequency of STYs and TCs in the Western North Pacific(WNP)Basin,with a significant trend change observed for TCs from 1949 to 2021.A large difference in the interannual change in frequency was found between STYs and TCs in the WNP and Eastern China Sea(ECS).Along the coast of EC,the frequency of landfall TCs showed a weak downtrend,and the typical STYs showed reverse micro growth with peak activity in August.Zhejiang,Fujian,and Taiwan were highly vulnerable to the frontal hits of typical STYs.Affected by climate change,the average lifetime maximum intensity(LMI)locations and landfall locations of typical STYs in the ECS basin showed a significant poleward migration trend.In addition,the annual average LMI and accumulated cyclone energy showed an uptrend,indicating the increasing severity of the disaster risk.Affected by the typical STY activity in the ECS,the maximum storm surge area also showed poleward migration,and the coast of North China faced potential growth in high storm surge risks.

Preparation and Swelling Kinetic Analysis of Poly (HPMC-co-AA-co-AM) Super Absorbent Resin

Super absorbent resin(SAR)is prepared by aqueous high temperature polymerization using hydroxypropyl methylcellulose(HPMC)as monomer backbone material,acrylic acid(AA)and acrylamide(AM)as the graft copolymer monomer,potassium persulfate(KPS)as the initiator to generate free radicals,and N,N`-methylenebisacrylamide(MBA)as cross-linking agent for cross-linking reaction.Simutaneously,the influence of individual factors on the water absorption is investigated,and these factors are mainly AA,AM,KPS,MBA,HPMC,and reaction temperature.The optimized conditions are obtained by the experiment repeating for several times.The water absorption multiplicity and salt absorption multiplicity under the conditions are 782.4 and 132.5 g/g,respectivity.Furthermore,the effects of different temperatures and salt concentrations on its water absorption,as well as the swelling kinetics of SAR are studied.It is indicated the water-absorbing swelling process is mainly caused by the difference in water osmotic pressure and Na+concentration inside and outside the cross-linked molecular structure of the resin,which is not only consistent with the quasi-secondary kinetic model,but also with the Fick diffusion model.

Hollow Ni Mo-based nitride heterojunction with super-hydrophilic/aerophobic surface for efficient urea-assisted hydrogen production

Hydrogen evolution reaction(HER)and urea oxidation reaction(UOR)are key reactions of the watercycling associated catalytic process/device.The design of catalysts with a super-hydrophilic/aerophobic structure and optimized electron distribution holds great promise.Here,we have designed a threedimensional(3D)hollow Ni/NiMoN hierarchical structure with arrayed-sheet surface based on a onepot hydrothermal route for efficient urea-assisted HER based on a simple hydrothermal process.The Ni/NiMoN catalyst exhibits super-hydrophilic/aerophobic properties with a small droplet contact angle of 6.07°and an underwater bubble contact angle of 155.7°,thus facilitating an escape of bubbles from the electrodes.Density functional theory calculations and X-ray photoelectron spectroscopy results indicate the optimized electronic structure at the interface of Ni and NiMoN,which can promote the adsorption/desorption of reactants and intermediates.The virtues combining with a large specific surface area endow Ni/NiMoN with efficient catalytic activity of low potentials of 25 mV for HER and 1.33 V for UOR at10 mA cm^(-2).The coupled HER and UOR system demonstrates a low cell voltage of 1.42 V at 10 mA cm^(-2),which is approximately 209 mV lower than water electrolysis.

Priming mesenchymal stem cells to develop “super stem cells”

The stem cell pre-treatment approaches at cellular and sub-cellular levels encompass physical manipulation of stem cells to growth factor treatment,genetic manipulation,and chemical and pharmacological treatment,each strategy having advantages and limitations.Most of these pre-treatment protocols are non-combinative.This editorial is a continuum of Li et al’s published article and Wan et al’s editorial focusing on the significance of pre-treatment strategies to enhance their stemness,immunoregulatory,and immunosuppressive properties.They have elaborated on the intricacies of the combinative pre-treatment protocol using pro-inflammatory cytokines and hypoxia.Applying a well-defined multi-pronged combinatorial strategy of mesenchymal stem cells(MSCs),pre-treatment based on the mechanistic understanding is expected to develop“Super MSCs”,which will create a transformative shift in MSC-based therapies in clinical settings,potentially revolutionizing the field.Once optimized,the standardized protocols may be used with slight modifications to pre-treat different stem cells to develop“super stem cells”with augmented stemness,functionality,and reparability for diverse clinical applications with better outcomes.

Prediction of Hot Deformation Behavior of 7Mo Super Austenitic Stainless Steel Based on Back Propagation Neural Network

The hot compression tests of 7Mo super austenitic stainless(SASS)were conducted to obtain flow curves at the temperature of 1000-1200℃and strain rate of 0.001 s^(-1)to 1 s^(-1).To predict the non-linear hot deformation behaviors of the steel,back propagation-artificial neural network(BP-ANN)with 16×8×8 hidden layer neurons was proposed.The predictability of the ANN model is evaluated according to the distribution of mean absolute error(MAE)and relative error.The relative error of 85%data for the BP-ANN model is among±5%while only 42.5%data predicted by the Arrhenius constitutive equation is in this range.Especially,at high strain rate and low temperature,the MAE of the ANN model is 2.49%,which has decreases for 18.78%,compared with conventional Arrhenius constitutive equation.

New direction for surgery:Super minimally invasive surgery

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.

基于改进Super-Twisting算法和电流预测的PMSM调速控制

针对永磁同步电机传统PI控制器存在响应速度慢、控制精度低、鲁棒性差等问题,该文提出一种改进调速控制方案。首先,将全局快速积分型终端滑模理论与广义Super-Twisting算法相结合,基于Anti-Windup原理设计改进广义Super-Twisting积分终端滑模速度控制器,并采用新型分段指数函数优化控制律;其次,设计改进扩展扰动观测器对系统未知扰动进行前馈补偿;最后,在电流环引入无差拍电流预测控制器,进一步改善系统的动态响应。仿真结果表明,所提出的改进控制方案能够有效提高调速系统的动态控制性能、控制精度和鲁棒性。

基于Super-SBM方法的省级交通运输行业碳排放效率评估研究

随着全球气候变化日益加剧,交通运输行业的碳排放效率评估与提升备受关注。本文利用Super-SBM模型,结合非期望产出,对2012-2019年我国30个省级行政区的交通运输行业碳排放效率进行了全面评估。在此基础上,运用Malmquist生产率指数(MPI)及其分解方法,揭示了不同区域间交通运输业碳排放效率的变化趋势。研究结果为加强省级交通运输业的环保措施、促进碳减排提供了科学依据,为政策制定者提供了重要参考。

跨境电商“产教融合”SUPER模式的构建与实践

近年来,我国的跨境电商行业发展迅猛,人才缺口巨大,培养出相当数量的优秀跨境电商人才成为政府、高校、行业和企业急需探讨和解决的问题。本文通过调研高校跨境电商专业“产教融合”痛点,结合校企合作相关工作经验,提出了“产教融合”SUPER模式,从学生(S)、高校(U)、项目(P)、企业(E)和R(结果)五个方面的“产教融合”联合培养模式,助力跨境电商人才培养。并且在项目SUPER模式的校企合作实践中,笔者发现该模式在人才培养中能发挥较显著的作用,应用SUPER模式的项目实践比以往的校企合作项目效益好,学生、企业、高校等实现多方共赢。当然,本研究也存在样本不大、操作平台不够丰富等较多不足,希望能抛砖引玉,为跨境电商人才培养提供一点思路,也希望获得更多同行的指导。

基于自适应Super-twisting算法的永磁同步电机驱动控制

在永磁同步电机调速系统中,良好的速度控制器要同时兼顾跟踪性能及抗干扰性能,非线性控制具有快速响应及强鲁棒性的优点,适用于速度控制器的设计,但传统滑模控制存在着严重的抖振问题。自适应Super-twisting算法属于二阶滑模,能将相轨迹的状态量以级数的形式收敛到原点,又能在线调整控制器的增益,因此能有效削弱抖振现象。采用自适应Super-twisting算法来设计速度控制器,并通过李雅普诺夫函数给出其稳定性证明。试验结果表明,所设计的控制器具有良好的跟踪性能及抗干扰性能,同时能减小电流的纹波,达到削弱抖振的目的。