摘要：In systems biology, the dynamics of biological networks are often modeled with ordinary differential equations (ODEs) that encode interacting components in the systems, resulting in highly complex models. In contrast, the amount of experimentally available data is almost always limited, and insufficient to constrain the parameters. In this situation, parameter estimation is a very challenging problem. To address this challenge, two intuitive approaches are to perform experimental design to generate more data, and to perform model reduction to simplify the model. Experimental design and model reduction have been traditionally viewed as two distinct areas, and an extensive literature and excellent reviews exist on each of the two areas. Intriguingly, however, the intrinsic connections between the two areas have not been recognized. Experimental design and model reduction are deeply related, and can be considered as one unified framework. There are two recent methods that can tackle both areas, one based on model manifold and the other based on profile likelihood. We use a simple sum-of-two-exponentials example to discuss the concepts and algorithmic details of both methods, and provide Matlab-based code and implementation which are useful resources for the dissemination and adoption of experimental design and model reduction in the biology community. From a geometric perspective, we consider the experimental data as a point in a high-dimensional data space and the mathematical model as a manifold living in this space. Parameter estimation can be viewed as a projection of the data point onto the manifold. By examining the singularity around the projected point on the manifold, we can perform both experimental design and model reduction. Experimental design identifies new experiments that expand the manifold and remove the singularity, whereas model reduction identifies the nearest boundary, which is the nearest singularity that suggests an appropriate form of a reduced

摘要：In order to assure quality and control process in the development of the aircraft collaborative design software, a maturity assessment model is proposed. The requirements designing—house of quality is designed to evaluate the maturity degree of the solution, and the evaluation results can help to manage and control the development process. Furthermore, a fuzzy evaluation method based on the minimum deviation is proposed to deal with the fuzzy information. The quantitative evaluation result of the maturity degree can be calculated by optimizing the semantic discount factor aim for the minimum deviation. Finally, this model is illustrated and analyzed by an example study of the aircraft collaborative design software.

摘要：为了提升校园安全水平,给学生日常学习、生活提供安全环境,围绕ZigBee技术深入分析智慧校园安全系统设计路径。基于ZigBee技术将信息化作为校园安防的创新驱动,依托无线通信技术实时监控校园,解决物联网无线传感器节点的网络连接,以期为相关工作人员提供有效参考建议,确保校园安全。

摘要：提出一种基于二维Renyi熵的阈值二值化方法,该方法通过引入二维直方图不仅利用了图像像元点的灰度分布信息,而且充分考虑了像元点之间的空间相关信息,对于低对比度、低信噪比的物体,该方法具有良好的分割效果。运用二维Renyi熵的原理选择灰度阈值对图像进行分割,并且引入量化图像直方图概念讨论了一种快速二维Renyi熵阈值分割算法,该算法能够递推运算和自动寻找阈值,将计算复杂性大大降低。仿真对比实验结果表明,该算法提高了计算效率并具有更佳的分割效果。

摘要：随着物联网(Internet of Things,IoT)、大数据等技术的发展,为新型智慧园区建设提供了新的机遇,而智慧园区的发展模式与体系结构也可以看作智慧城市的缩影。对新型智慧园区现状进行分析,从技术应用、网络架构、需求分析3个角度出发,探讨了基于物联网的新型智慧园区设计方案,同时还讨论了物联网技术在新型智慧园区的具体应用场景,包括人脸识别、会议预约、交通管理以及智慧餐厅等,实现智慧园区服务管理水平的提高。

摘要：为了明确贵州新老两代糯高粱品种(系)的产量和氮肥利用率差异,以红缨子、黔高8号,红壳糯、黑壳糯为试验材料,设置2个氮肥处理(LN和HN),采用裂区试验设计,研究了其产量、氮素积累以及氮肥利用特性之间的差异。结果表明:2010s品种较1990s品系的产量、干物质和氮素积累总量平均分别增加了25.4%,25.1%,33.3%。氮素收获指数在LN处理下,品种间差异显著,HN下不显著;与LN处理相比,1990s品系的花后氮占比在HN处理下明显降低,幅度为20.9%,说明2010s品种在花后的氮素同化能力上要更强,在低氮、高氮水平下都具备更强的籽粒氮素累积能力。2010s品种较1990s品系的氮肥偏生产力、氮素表观回收率、氮肥利用率以及氮肥农学效率分别提高了13.9 kg/kg、0.7 kg/kg、20.3%和4.1 kg/kg,产量、干物质和氮素积累总量与氮肥利用率显著正相关,表明贵州糯高粱单产的增加可能是氮肥利用率的提高导致的氮积累增加所致,为糯高粱的正常生理代谢提供了充足的氮供应。

摘要：基于信息技术的飞速发展,数据中心动力与环境监测工作开展的需求发生了一定的改变。如果数据中心的运维人员无法及时对各点位的运行状况进行科学有效管理,则有可能影响数据中心运行的稳定性。因此,工作人员须全面掌握动环监控系统各阶段的运行情况,保证管控方案的合理性与可行性,从而保证数据中心可以在有利环境中持续稳定运行。基于此,从数据中心动力与环境监控系统的现状入手,分析监控系统组成情况,从而明确数据中心动力与环境监控系统未来的发展方向,保证其智能化发展。

摘要：以贵州省新老两代酒用糯高粱品种(系)为研究对象,采用随机区组设计,对其产量、干物质及氮素积累转运进行分析,结果表明,随着年代更替,贵州省酒用糯高粱产量、干物质和氮素积累总量逐步提高,新品种较老品系2年平均分别增加25.5%、23.4%和35.2%;新品种花后干物质和氮素积累占比平均分别为32.6%和31.2%,显著高于老品系;新品种花后干物质和氮素积累对籽粒产量的贡献平均分别为65.2%和49.6%,较老品系分别提高10.2%和12.2%;新品种的干物质、氮素转运量分别较老品系增加12.1%和32.5%,其中新品种的叶干物质和氮素转运量对籽粒的贡献分别较老品系提高3.0%和4.1%。同时贵州糯高粱花后干物质、氮素积累量和转运量与产量之间存在显著正相关关系。综上所述,花后氮素积累与转运能力的增强促成了干物质积累量的增加,从而提升了贵州糯高粱新品种的产量。

摘要：以贵州省不同年代酿酒用糯高粱品种(系)为研究对象,采用随机区组试验设计,对其农艺性状、产量构成以及抗性差异进行分析,结果表明:随着年代更替,贵州省酿酒用糯高粱单产逐步提高。新品种(红缨子、黔高8号)较老品系(黑壳糯、红壳糯)平均单产增幅25%以上;穗粒数、穗粒重增加显著,增幅分别为51.7%、62.7%;主穗一、二级枝梗数增加幅度分别为19.8%、62.7%;株高降低24.9%,茎粗增加9.5%;节间数增加0.9个,节间长缩短13.3cm;单株叶面积和叶面积指数增加显著;倒伏率、发病率下降显著,成穗率明显提升。各指标相关性分析显示,产量与穗粒数、穗粒重,穗粒数与主穗一、二级枝梗数呈极显著正相关;产量与株高、倒伏率极显著负相关,与茎粗正相关,相关系数分别为-0.981、-0.970和0.928,株高、茎粗与倒伏率相关显著,相关系数分别为0.964和-0.910;产量与叶面积指数正相关,与发病率显著负相关。总的结果表明,主穗一、二级枝梗数的增加提高了糯高粱的穗粒数,植株株高的降低、茎粗的增加促进了抗倒性的提升,抗病性的提升保证了后期叶片光合作用的持续进行,最终提高了糯高粱产量。

摘要：以贵州省不同年代酒用糯高粱品种(系)为研究对象,采用随机区组试验设计,对其干物质积累总量、产量构成以及花后叶面积指数(LAI)、SPAD值动态、光能截获量(Li)进行分析,结果表明:随着年代更替,贵州省酒用糯高粱生产性能逐步提高,新品种(红缨子、黔高8号)较老品系(黑壳糯、红壳糯)产量和干物质积累总量平均分别增加25.5%和23.4%;穗粒数、穗粒重平均分别显著增加44.6%和58.9%;花后LAI平均分别为3.41和2.14,新品种较老品系增加59.3%;花后37d,SPAD值降幅分别为23.8%和81.2%;新品种的光合速率(Pn)和蒸腾速率较老品系分别增加16.1%和34.3%,胞间CO2浓度降低23.5%;新品种的花期Li较老品系增加8.3%,差异显著。相关分析结果显示,产量、干物质积累总量与Pn、LAI、SPAD值、光能截获量呈极显著正相关,Pn、Li与SPAD值、LAI呈极显著正相关。上述结果表明花后叶片失绿变缓、光化学效率的提高以及Li的增加可能是糯高粱单产随年代更替稳步提升的原因。