Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

Designing amorphous formulations of polyphenols with naringin by spray-drying for enhanced solubility and permeability

Naringin (NAR), a major flavanone (FVA) glycoside, is a component of food mainly obtained from grapefruit. We used NAR as a food additive to improve the solubility and permeability of hydrophobic polyphenols used as supplements in the food industry. The spray-dried particles (SDPs) of NAR alone show an amorphous state with a glass transition temperature (T_g) at 93.2 °C. SDPs of hydrophobic polyphenols, such as flavone (FVO), quercetin (QCT), naringenin (NRG), and resveratrol (RVT) were prepared by adding varying amounts of NAR. All SDPs of hydrophobic polyphenols with added NAR were in an amorphous state with a single T_g, but SDPs of hydrophobic polyphenols without added NAR showed diffraction peaks derived from each crystal. The SDPs with NAR could keep an amorphous state after storage at a high humidity condition for one month, except for SDPs of RVT/NAR. SDPs with NAR enhanced the solubility of hydrophobic polyphenols, especially NRG solubility, which was enhanced more than 9 times compared to NRG crystal. The enhanced solubility resulted in the increased membrane permeability of NRG. The antioxidant effect of the hydrophobic NRG was also enhanced by the synergetic effect of NAR. The findings demonstrated that NAR could be used as a food additive to enhance the solubility and membrane permeability of hydrophobic polyphenols.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

减少手术创伤始终是妇科肿瘤手术快速康复的决定性因素

减少手术创伤始终是快速康复的决定性因素,这一点在目前的加速康复外科研究尤其是复杂手术,如妇科肿瘤手术中尚未得到充分重视。尊重学习曲线、全面规划手术方案、总结失利经验、开展前瞻性研究是解决此问题的主要方案。本文着重讨论妇科肿瘤手术创伤对术后加速康复的影响及可能的改进措施。     

低觉醒脑电识别与唤醒的可穿戴系统研究

为智能化地识别警戒作业人员出现的低觉醒、注意力下降的生理状态，本文介绍了一种基于FPGA和脑电信号处理的低觉醒状态检测与唤醒系统，系统通过传感器从大脑头皮采集脑电信号，转换为数字信号，经傅里叶变换获取了脑电信号的θ相对能量、α相对能量、重心频率、谱熵等4个特征量，由4个特征量表征低觉醒状态并运用支持向量机对低警戒状态进行识别，当识别出低觉醒状态时采用声音报警模块发出声音，唤醒警戒作业人员。设计系统能够较好地识别出低觉醒状态，识别率达90.8%，可为提高警戒作业工作绩效提供一种可穿戴的智能装备。     

Residual learning rates in lead-acid batteries: Effects on emerging technologies

The low price of lead-acid, the most popular battery, is often used in setting cost targets for emerging energy storage technologies. Future cost reductions in lead acid batteries could increase investment and time scales needed for emerging storage technologies to reach cost-parity. In this paper the first documented model of cost reductions for lead-acid batteries is developed. Regression to a standard experience curve using 1989–2012 data yield a poor fit, with R² values of 0.17 for small batteries and 0.05 for larger systems. To address this problem, battery costs are separated into material and residual costs, and experience curves developed for residual costs. Depending on the year, residual costs account for 41–86% of total battery cost. Using running-time averages to address volatility in material costs, a 4-year time average experience curve for residual costs yield much higher R², 0.78 for small and 0.74 for large lead-acid batteries. The learning rate for residual costs in lead-acid batteries is 20%, a discovery with policy implications. Neglecting to consider cost reductions in lead-acid batteries could result in failure of energy storage start-ups and public policy programs. Generalizing this result, learning in incumbent technologies must be understood to assess the potential of emerging ones.     

1,5-己二烯交联烯烃聚合物的合成及其抗剪切稳定性

以金属配合物为催化剂、1,5-己二烯为交联剂,采用本体聚合法合成了交联超高相对分子质量烯烃类聚合物(简称交联聚合物)。用傅里叶变换红外光谱、核磁共振、凝胶渗透色潜表征交联聚合物的结构和相对分子质量。用旋转黏度计和超声波仪研究了1,5-己二烯用量对交联聚合物溶液表观黏度的影响及交联聚合物的相对分子质量对交联聚合物溶液抗剪切稳定性的影响。实验结果表明,在最佳聚合条件(单体80mL、助催化剂0．4mL、CS-1催化剂0．090g、1,5-己二烯0．40mL、0℃、24 b)下所合成的交联聚合物的重均相对分子质量为7．7×106,数均相对分子质量3．6×106。加入少量1,5-己二烯能提高交联聚合物的抗剪切能力,同时也能提高交联聚合物的相对分子质量。交联聚合物的相对分子质量越大,抗剪切稳定性越好。1,5-己二烯用量约为0．1 mL时(单体40 mL),交联聚合物溶液的表观黏度达到最大值(16．8 mPa·s)。     

重力坝模型的尺寸效应

利用两个不同比尺预制缝重力坝模型的试验成果，以有限元富集技术进行非线性断裂分析，建立了极限承载力和长度比尺的确定性尺寸效应公式。混凝土重力坝的断裂尺寸效应满足指数衰减关系，用三次指数衰减公式可以准确地预测原型的极限承载力。断裂过程区的相对长度是引起模型试验尺寸效应的主要原因。数值计算结果表明，断裂过程区相对长度不仅是与材料有关的参数，能否充分发展还取决于结构尺寸和几何形状；断裂过程区相对长度的尺寸效应不同于统计尺寸效应和断裂参数尺寸效应，具有尺寸范围效应。断裂过程区相对长度在小试件、大试件和相对无穷大试件的发展程度不同。     

皮带秤秤架的响应特性曲线分析

介绍了皮带秤秤架响应特性曲线分析方法，对四种结构形式的秤架进行了响应特性曲线分析和比较，得出的结论是：悬浮式秤架的计量特性最好。     

凝胶渗透色谱法测定基础油PAO的相对分子质量及分布

聚α-烯烃是一种性能优良的润滑油基础油，其相对分子质量及分布直接影响宏观性能。本研究建立了一种用于表征1-癸烯齐聚物相对分子质量及分布的方法。采用带示差折光检测器的凝胶渗透色谱系统，综合考虑分离效果和测试可操作性，优化了流动相流速和凝胶色谱柱的组合方式。以四氢呋喃为流动相，流速为0.8 mL/min，色谱柱组合方式为Styragel HR 0.5,Styragel HR 1,PLGEL 3μm MIXED-E三柱串联，以聚苯乙烯作为标准样品，采用普适校正方法处理色谱流出曲线。此方法测得样品的质均相对分子质量与凝胶渗透色谱-光散射法所测定结果相比较，相对误差相对偏差在3%以内。