Genome-Wide Discovery and Expression Profiling of the SWEET Sugar Transporter Gene Family in Woodland Strawberry (Fragaria vesca) under Developmental and Stress Conditions: Structural and Evolutionary Analysis

The SWEET(sugar will eventually be exported transporter)family proteins are a recently identified class of sugar transporters that are essential for various physiological processes.Although the functions of the SWEET proteins have been identified in a number of species,to date,there have been no reports of the functions of the SWEET genes in woodland strawberries(Fragaria vesca).In this study,we identified 15 genes that were highly homolo-gous to the A.thaliana AtSWEET genes and designated them as FvSWEET1–FvSWEET15.We then conducted a structural and evolutionary analysis of these 15 FvSWEET genes.The phylogenetic analysis enabled us to categor-ize the predicted 15 SWEET proteins into four distinct groups.We observed slight variations in the exon‒intron structures of these genes,while the motifs and domain structures remained highly conserved.Additionally,the developmental and biological stress expression profiles of the 15 FvSWEET genes were extracted and analyzed.Finally,WGCNA coexpression network analysis was run to search for possible interacting genes of FvSWEET genes.The results showed that the FvSWEET10 genes interacted with 20 other genes,playing roles in response to bacterial and fungal infections.The outcomes of this study provide insights into the further study of FvSWEET genes and may also aid in the functional characterization of the FvSWEET genes in woodland strawberries.

Intelligent Risk-Identification Algorithm with Vision and 3D LiDAR Patterns at Damaged Buildings

Existingfirefighting robots are focused on simple storage orfire sup-pression outside buildings rather than detection or recognition.Utilizing a large number of robots using expensive equipment is challenging.This study aims to increase the efficiency of search and rescue operations and the safety offirefigh-ters by detecting and identifying the disaster site by recognizing collapsed areas,obstacles,and rescuers on-site.A fusion algorithm combining a camera and three-dimension light detection and ranging(3D LiDAR)is proposed to detect and loca-lize the interiors of disaster sites.The algorithm detects obstacles by analyzingfloor segmentation and edge patterns using a mask regional convolutional neural network(mask R-CNN)features model based on the visual data collected from a parallelly connected camera and 3D LiDAR.People as objects are detected using you only look once version 4(YOLOv4)in the image data to localize persons requiring rescue.The point cloud data based on 3D LiDAR cluster the objects using the density-based spatial clustering of applications with noise(DBSCAN)clustering algorithm and estimate the distance to the actual object using the center point of the clustering result.The proposed artificial intelligence(AI)algorithm was verified based on individual sensors using a sensor-mounted robot in an actual building to detectfloor surfaces,atypical obstacles,and persons requiring rescue.Accordingly,the fused AI algorithm was comparatively verified.

Relationship Between 2:1 Mineral Structure and the Fixation and Release of Cations

The effects of different structures of 2:1 layer minerals, layer charge location, and changes of structure and charge during the weathering process on the fixation and release of interlayer cations are reviewed. It could be concluded that the fixation capacity is determined by the total amount of interlayer charge originating from both octahedral and tetrahedral sheets. The relationship between interlayer cation fixation and octahedral structure of the secondary minerals may be different from that of the primary minerals. The oxidation and reduction of cations with variable valence can greatly influence the cation-fixation capacity.

Hybrid Feature Extractions and CNN for Enhanced Periocular Identification During Covid-19

The global pandemic of novel coronavirus that started in 2019 has ser-iously affected daily lives and placed everyone in a panic condition.Widespread coronavirus led to the adoption of social distancing and people avoiding unneces-sary physical contact with each other.The present situation advocates the require-ment of a contactless biometric system that could be used in future authentication systems which makesfingerprint-based person identification ineffective.Periocu-lar biometric is the solution because it does not require physical contact and is able to identify people wearing face masks.However,the periocular biometric region is a small area,and extraction of the required feature is the point of con-cern.This paper has proposed adopted multiple features and emphasis on the periocular region.In the proposed approach,combination of local binary pattern(LBP),color histogram and features in frequency domain have been used with deep learning algorithms for classification.Hence,we extract three types of fea-tures for the classification of periocular regions for biometric.The LBP represents the textual features of the iris while the color histogram represents the frequencies of pixel values in the RGB channel.In order to extract the frequency domain fea-tures,the wavelet transformation is obtained.By learning from these features,a convolutional neural network(CNN)becomes able to discriminate the features and can provide better recognition results.The proposed approach achieved the highest accuracy rates with the lowest false person identification.

A Precise Description of the Electronic Structures and Spin-Allowed Transition Properties of PF and Its Cation:All-Electron Configuration-Interaction Investigations Including Relativistic Effect

The electronic structures of PF and PF＋ are calculated with the high-level configuration interaction method. To improve the precision of calculations, the spin-orbit coupling effect, the scalar relativistic effect, and the Davidson correction（q-Q） are also considered. The spectroscopic parameters of bound states are derived by the electronic structures of PF and PF＋, which are in good accordance with the measurements. The transition dipole moments of spin-allowed transitions are evaluated, and the radiative lifetimes of several A S states of PF and PF＋ are obtained.

Structural and magnetic properties of La_(0.7)Sr_(0.1)Ag_xMnO_(3-δ) perovskite manganites

Ag-doped manganite powder samples, La0.7Sr0.1AgxMnO3 6 （x = 0.00, 0.025, 0.05, 0.075, and 0.10） were synthesized using the sol-gel method. X-ray diffraction patterns indicated that the samples had two phases with the R-3c perovskite being the dominant phase and Mn3O4 being the second phase. X-ray energy dispersive spectra indicated that the ratio of Ag to La was very close to that of the nominal composition in the samples. The specific saturation magnetizations at 300 K increased from 32.0 A.mZ/kg when x = 0.00 to 46.8 A-mZ/kg when x = 0.10. The Curie temperature, TC, of the samples increased from 310 K when x = 0.00 to 328 K when x = 0.10. Because the atomic concentration ratios of La, Sr, and Mn in the five samples were all the same and only the Ag concentration changed, the variations of the specific saturation magnetizations at 300 K and the Curie temperatures suggested that the Ag cations have been doped into the A sites of the perovskite phase in the samples.

THE STRUCTURE OF ACTIVE SITE AND THE ROLE OF BIVALENT CATION IN FERRITE-FERRIC OXIDE CATALYSTS FOR OXIDATIVE DEHYDROGENATION OF BUTENES

The relations between catalytic activities and compositions of the systems Mg_xZn_(1-x)Fe_2O_4, Co_xZn_(1-x)Fe_2O_4, Co_xMg_(1-x)Fe_2O_4, Cd_xZn_(1-x)Fe_2O_4 and Mg_xZn_(1-x)Fe_2O_4·0.17Fe_2O_3 have been studied by flow differential reactor, XRD, and derivative IR techniques. It has been found that the appropriate normal-inverse spinel combination substantially increases the activity for the title raction. The structure of the active site and the role of the bivalent cation in the title catalyst have been inferred.

QUANTUM CHEMICAL CALCULATIONS ON THE ELECTRONIC STRUCTURE AND SPECTRA OF[Mo_3O_4-nSn]^(4+)(n=O-4)CLUSTER CATIONS

The electronic structure and spectra of [Mo3O4-nSn]^(4+)(n=0-4) cations were calculated by means of INDO/CI quantum chemistry method to account for the experimental data of their spectra in water solutions.

Ab Initio Theoretical Prediction on Structures of Boron Cationic Cluster B_(17)^+

Four isomers of the three-dimensionally connected bare boron cationic cluster B were investigated by using ab initio molecular orbital theory at the HF/6-31G level. The results show that the D5h symmetric isomer of B is a possible isomer candidate of its stable geometries with closed structure.

Studies on the Crystallization Properties and Morphology Structure of the Cationic Dyeable Polypropylene Fibers

The crystallization properties and morphology structure of the cationic dyeable polypropylene fibers which were produced by the blending spinning method were studied by making use of X-ray and scanning electron microscopy (SEM). It comes to the conclusions that the larger the crystallite size in the fibers is , the better the dyeable properties of the fibers are and there is a little compatibility between the dyeable agent and polypropylene resin. And the dye-uptake of the fibers may be up to 90% because the dyeable agent can uniformly be scattered in polypropylene.

A novel model to evaluate spatial structure in thinned conifer-broadleaved mixed natural forests

In order to ensure the effective analysis and reconstruction of forests,it is key to ensure the quantitative description of their spatial structure.In this paper,a distance model for the optimal stand spatial structure based on weighted Voronoi diagrams is proposed.In particular,we provide a novel methodological model for the comprehensive evaluation of the spatial structure of forest stands in natural mixed conifer-broadleaved forests and the formulation of management decision plans.The applicability of the rank evaluation and the optimal solution distance model are compared and assessed for different standard sample plots of natural mixed conifer-broadleaved forests.The effect of crown width on the spatial structure unit of the trees is observed to be higher than that of the diameter at breast height.Moreover,the influence of crown length is greater than that of tree height.There are nine possible spatial structure units determined by the weighted Voronoi diagram for the number of neighboring trees in the central tree,with an average intersection of neighboring crowns reaching 80%.The rank rating of natural forest sample plots is correlated with the optimal solution distance model,and their results are generally consistent for natural forests.However,the rank rating is not able to provide a quantitative assessment.The optimal solution distance model is observed to be more comprehensive than traditional methods for the evaluation of the spatial structure of forest stands.It can effectively reflect the trends in realistic stand spatial structure factors close to or far from the ideal structure point,and accurately assesses the forest spatial structure.The proposed optimal solution distance model improves the integrated evaluation of the spatial structure of forest stands and provides solid theoretical and technical support for sustainable forest management.

Geometrical Frameworks in Identification Problem

The purpose of this review is to apply geometric frameworks in identification problems. In contrast to the qualitative theory of dynamical systems (DSQT), the chaos and catastrophes, researches on the application of geometric frameworks have not been performed in identification problems. The direct transfer of DSQT ideas is inefficient through the peculiarities of identification systems. In this paper, the attempt is made based on the latest researches in this field. A methodology for the synthesis of geometric frameworks (GF) is proposed, which reflects features of nonlinear systems. Methods based on GF analysis are developed for the decision-making on properties and structure of nonlinear systems. The problem solution of structural identifiability is obtained for nonlinear systems under uncertainty.

人工智能赋能大学治理:多重效应与治理效能转化

当人工智能与大学治理相遇后,数字化不仅成为提升大学治理能力和治理水平现代化的客观要求,还成为推进大学治理创新和制度变迁的重要途径。根据大学制度的层级结构、治理结构的复杂性程度以及治理事项的数字化程度,建构制度嵌入下人工智能技术赋能大学治理的解释模型,并借此模型着重分析人工智能技术对大学治理影响的多重效应及其治理效能转化机制/过程。研究发现,在制度嵌入和人工智能技术的共同影响下,现代大学治理随着大学制度外显性的不断加强而愈显复杂,在此渐进过程中,人工智能技术的影响力和渗透力也就愈加微弱,由此产生了人工智能技术对大学治理影响的多重效应及其治理效能的不同转化和提升机制:大学治理结构的复杂性程度越低,大学制度的层级结构越低,治理领域可数字化的程度就越高,人工智能技术对大学治理的积极效应越显著,大学具体制度得以更迭的可能性越大,也就愈容易借助“技术—制度”协同机制将中国特色现代大学的制度优势转化为治理效能;大学治理结构的复杂化程度越高,大学制度的层级结构越高,治理领域可数字化的程度越低,人工智能技术对大学治理的抑制效应越明显,其所依靠的(部分)基本制度和基础制度被替代/更迭的速度越慢,而被同化的可能性越大,也就越容易走上模仿西方大学制度建设的路径依赖。为此,一方面,要注重人工智能技术对大学治理的积极效应,充分发挥人工智能技术对于大学常规性治理、(部分)决策性治理的积极作用,通过大学具体制度和基本制度的不断健全和完善,推动现代大学制度的标准化建设和精细化发展;另一方面,要警惕人工智能技术对大学治理带来的潜在危险,充分考虑现代大学的组织特性,避免过度技术化而导致大学治理中技术应用的无限拓展和无序泛化。

现代化数字灌区建设主体功能及主要应用结构体系探讨

基于对物理灌区的现代化和模拟灌区的数字化认知,分析总结了现代化数字灌区建设应着力完成的“灌区识别”“立体感知”“精准控制”“信息交互”“管理调度”等“五大主体功能”结构体系;基于智慧水利建设和灌区高效运管需求,高效地模拟渠系水流,系统梳理了以“节点流量过程”为输入和输出的灌区概化图,研究提出了现代化数字灌区建设主要业务应用结构体系,即构建以“数据库”为载体,“数学模型”为支撑,基于“灌区一张图”基础之上的“组织管理、工程管理、安全管理、泵站管理、农业节水与供用水管理、经济管理、信息化管理、公共服务”等“九大业务应用”为交互的的整体架构,以期有效提升灌溉供水服务的安全性、公平性、可靠性和灵活性。

对甘精胰岛素有关物质分析用系统适用性试验的研究

目的:对不同企业甘精胰岛素有关物质分析用系统适用性试验进行研究,发现存在的问题,提示企业完善质量标准,更科学有效地控制产品质量。方法:采用高效液相色谱法及液质联用方法对不同企业有关物质分析用系统适用性试验进行研究评价,发现存在多种问题。结果:部分企业系统适用性溶液中所用的“0A-甘精胰岛素”的结构经LC-MS/MS确认后,发现与理论序列不同,部分企业采用酶切方法制备系统适用性溶液,存在杂质较多、操作步骤复杂、溶液易浑浊等问题。结论:建议企业提高对系统适用性试验的重视程度,加强研究,完善质量标准,科学有效地进行药品质量控制。

Li(Sc,M)Si_(2)O_(6)∶Cr^(3+)(M=Ga^(3+)/Lu^(3+)/Y^(3+)/Gd^(3+))的近红外发光性能

荧光转换型近红外发光二极管(NIR pc-LED)具有体积小、谱带宽、峰位易调谐等优点,是新一代NIR光源发展的前沿,其关键在于研发可被蓝光有效激发的高效率宽带近红外荧光粉。LiScSi_(2)O_(6)∶Cr^(3+)荧光材料的激发波长为460 nm,发射峰位在845 nm,光谱带宽为156 nm,内量子效率为64.4%。基于该体系,本文通过M离子(M=Ga^(3+),Lu^(3+),Y^(3+),Gd^(3+))取代Sc^(3+)的方式对其性能进行调控。结果表明,引入M离子易生成杂相或发生相变,降低了材料的发光性能。本文从晶体结构出发对其调控过程进行了分析。

气相中碱基与核苷自由基的产生与结构研究

核苷自由基在生物体内扮演着关键角色,特别是在DNA损伤过程中。为深入研究这些自由基的性质、反应机制以及与其他生物分子的相互作用,确定其结构至关重要。质谱通过提供高真空环境,为自由基离子创造了惰性的研究环境,在核苷自由基和碱基自由基的气相研究中展示了不可替代的作用。此外,结合串联质谱和理论计算,能够更准确地分析自由基结构。本文总结了近20年来基于质谱技术的气相中碱基与核苷自由基的研究,详细介绍了自由基离子的产生方法、研究手段以及结构分析的最新成果,提出了对于高活性自由基中间体的结构研究,以及自由基异构体的选择性产生仍然面临挑战,亟需发展新的实验方法和技术手段。

水自由基阳离子与苯及其衍生物反应的质谱研究

研究水自由基阳离子的化学性质对阐释水相化学反应机理有着重要意义。本文研究了在线制备的(H_(2)O)_(2)^(+·)(m/z 36)与苯及其衍生物反应的特点。结果表明,当(H_(2)O)_(2)^(+·)与苯(C_(6)H_(6))、苯甲醚(C_(7)H_(8)O)、2,4-二甲基苯胺(C_(8)H_(11)N)等没有吸电子基团的化合物反应时,除产生对应的电子转移反应产物(C_(6)H_(6))^(+·)(m/z 78)、(C_(7)H_(8)O)^(+·)(m/z108)或质子转移反应产物(C_(8)H_(11)N+H)+(m/z 122)外,还发现苯酚相关产物(C_(6)H_(5)OH)^(+·)(m/z 94)、(C_(7)H_(7)O-OH)^(+·)(m/z 124)以及(C_(8)H_(10)NOH+H)+(m/z 138)。同位素标记实验表明,苯酚相关产物中的OH来源于水自由基阳离子。然而,当(H_(2)O)_(2)^(+·)与苯甲腈(C_(6)H_(5)CN)或硝基苯(C_(6)H_(5)NO_(2))等有强吸电子基团的取代苯反应时,主要通过取代反应产生(C_(6)H_(5)CN+H_(2)O)^(+·)(m/z 121)和(C_(6)H_(5)NO_(2)+H_(2)O)^(+·)(m/z 141),并未发现羟基化产物。由以上结果可知,(H_(2)O)_(2)^(+·)与底物分子的反应可通过电子转移(底物自由基阳离子)、质子转移(质子化产物)、解离电子转移(羟基化产物)和取代等4个过程发生,这可能与(H_(2)O)_(2)^(+·)存在(H_(2)O)H^(+)-^(·)OH和[H_(2)O∴OH_(2)]^(+·)_(2)种互变结构有关。本研究推测,苯环上的吸电子基团有利于[H_(2)O∴OH_(2)]^(+·)结构的存在,从而发生取代反应,当苯环上没有吸电子基团时,苯环上的富电子体系有利于(H_(2)O)H^(+)-^(·)OH结构的存在,而质子转移结构中的羟基自由基可以将苯氧化成苯酚,该结果有助于阐明苯及其衍生物与(H_(2)O)_(2)^(+·)相关的化学反应过程。

微咸水离子组成对膜下滴灌土壤孔隙结构的影响

为探讨不同阳离子组成微咸水灌溉对膜下土壤孔隙结构的影响,开展2a田间定位试验,设置当地地下水灌溉(CK)、NaCl微咸水灌溉(T1)、KCl微咸水灌溉(T2)、CaCl_(2)微咸水灌溉(T3)、MgCl_(2)微咸水灌溉(T4)5个处理,利用CT扫描技术研究不同阳离子组成微咸水对土壤孔隙结构的影响。结果表明:与CK处理相比,随灌水次数增多,添加Na+处理的土壤大孔隙度显著降低,添加K^(+)、Ca^(2+)、Mg^(2+)处理的土壤大孔隙度显著增加,2022年添加Na+处理的大孔隙度平均降低了44.49%,添加K^(+)、Ca^(2+)、Mg^(2+)处理的土壤大孔隙度平均分别增加了5.73%、80.73%、25.75%;在2021—2022年期间,与CK相比,4种不同阳离子处理土壤孔隙成圆率均呈增加趋势,其中添加Ca^(2+)、Mg^(2+)处理增加显著,土壤孔隙成圆率平均增加区间分别为25.52%~30.94%、17.46%~23.19%;连续灌溉2a之后,添加Na+和K^(+)处理的土壤开裂程度加重,土壤稳定性变差,而添加Ca^(2+)和Mg^(2+)对改善土壤结构、提高土壤入渗性能作用明显。

A Modified Principal Component Analysis Method for Honeycomb Sandwich Panel Debonding Recognition Based on Distributed Optical Fiber Sensing Signals

The safety and integrity requirements of aerospace composite structures necessitate real-time health monitoring throughout their service life.To this end,distributed optical fiber sensors utilizing back Rayleigh scattering have been extensively deployed in structural health monitoring due to their advantages,such as lightweight and ease of embedding.However,identifying the precise location of damage from the optical fiber signals remains a critical challenge.In this paper,a novel approach which namely Modified Sliding Window Principal Component Analysis(MSWPCA)was proposed to facilitate automatic damage identification and localization via distributed optical fiber sensors.The proposed method is able to extract signal characteristics interfered by measurement noise to improve the accuracy of damage detection.Specifically,we applied the MSWPCA method to monitor and analyze the debonding propagation process in honeycomb sandwich panel structures.Our findings demonstrate that the training model exhibits high precision in detecting the location and size of honeycomb debonding,thereby facilitating reliable and efficient online assessment of the structural health state.