Ultrasonic particle size fractionation in a moving air stream

Identification of bio-aerosol particles may be enhanced by size sorting before applying analytical techniques. In this paper, the use of ultrasonic acoustic radiation pressure to continuously size fractionate particles in a moving air stream is described. Separate particle-laden and clean air streams are introduced into a channel and merged under laminar flow conditions. An ultrasonic transducer, mounted flush to one wall of the channel, excites a standing ultrasonic wave perpendicular to the flow of the combined air stream. Acoustic radiation forces on the particles cause them to move transverse to the flow direction. Since the radiation force is dependent upon the particle size, larger particles move a greater transverse distance as they pass through the standing wave. The outlet flow is then separated into streams, each containing a range of particle sizes. Experiments were performed with air streams containing glass microspheres with a size distribution from 2-22 μm, using a centerline air stream velocity of approximately 20 cm/s. An electrostatic transducer operating at a nominal frequency of 50 kHz was used to drive an ultrasonic standing wave of 150 dB in pressure amplitude. The microsphere size distributions measured at the outlet were compared with the predictions of a theoretical model. Experiments and theory show reasonable correspondence. The theoretical model also indicates an optimal partitioning of the particle-laden and clean air inlet streams.     

Developing an efficient knowledge discovering model for mining fuzzy multi-level sequential patterns in sequence databases

Sequential pattern mining from sequence databases has been recognized as an important data mining problem with various applications. Items in a sequence database can be organized into a concept hierarchy according to taxonomy. Based on the hierarchy, sequential patterns can be found not only at the leaf nodes (individual items) of the hierarchy, but also at higher levels of the hierarchy; this is called multiple-level sequential pattern mining. In previous research, taxonomies based on crisp relationships between any two disjointed levels, however, cannot handle the uncertainties and fuzziness in real life. For example, Tomatoes could be classified into the Fruit category, but could be also regarded as the Vegetable category. To deal with the fuzzy nature of taxonomy, Chen and Huang developed a novel knowledge discovering model to mine fuzzy multi-level sequential patterns, where the relationships from one level to another can be represented by a value between 0 and 1. In their work, a generalized sequential patterns (GSP)-like algorithm was developed to find fuzzy multi-level sequential patterns. This algorithm, however, faces a difficult problem since the mining process may have to generate and examine a huge set of combinatorial subsequences and requires multiple scans of the database. In this paper, we propose a new efficient algorithm to mine this type of pattern based on the divide-and-conquer strategy. In addition, another efficient algorithm is developed to discover fuzzy cross-level sequential patterns. Since the proposed algorithm greatly reduces the candidate subsequence generation efforts, the performance is improved significantly. Experiments show that the proposed algorithm is much more efficient and scalable than the previous one. In mining real-life databases, our works enhance the model's practicability and could promote more applications in business.     

Simultaneous siting and sizing of distribution centers on a plane

The benefits of simultaneous consideration of siting and sizing of distribution centers have been well acknowledged in supply chain design. Most formulations assume that the potential DC sites are known and the decision on location is to select sites from the finite potential DC sites. However, the quality of this discrete version problem depends on the selection of potential DC sites. In this paper we present a planar version of the problem, which assumes that there is no a priori knowledge of DC sites and DCs can be located anywhere in the plane. The goal of the problem is to simultaneously find locations and sizing of DC sites. The solution of the planar problem provides a lower bound for the discrete problem. The objective of the problem is to minimize the total of inbound and outbound transportation costs and distribution center construction costs—which include its fixed charge cost and concave sizing cost. The problem is initially formulated as a nonlinear programming model. We then reformulate it as a set covering problem after establishing certain key properties. A greedy drop heuristic and a column generation heuristic are developed to solve the problem. Computational experiments are provided.     

Lot sizing with random yield and different qualities

This paper considers a production/inventory system where items produced/purchased are of different qualities: Types A and B. Type A items are of perfect quality, and Type B items are of imperfect quality; but not necessarily defective; and have a lower selling price. The percentage of Type A (the yield rate) is assumed to be a random variable with known probability distribution. The electronics industry gives good examples of such situations. We extend the classical single period (newsvendor) and the economic order quantity (EOQ) models by accounting for random supply and for imperfect quality (Type B) items which are assumed to have their own demand and cost structure. We develop mathematical models and prove concavity of the expected profit function for both situations. We also present detailed analysis and numerical results. We focus on comparing the profitability of the novel proposed models with models from the literature (and derivatives of these models) that develop the optimal order quantity based on the properties of Type A items only (and ignore Type B items). We find that accounting for Type B items can significantly improve profitability.     

Solving multi-level multi-objective linear programming problems through fuzzy goal programming approach

In this paper, two new algorithms are presented to solve multi-level multi-objective linear programming (ML-MOLP) problems through the fuzzy goal programming (FGP) approach. The membership functions for the defined fuzzy goals of all objective functions at all levels are developed in the model formulation of the problem; so also are the membership functions for vectors of fuzzy goals of the decision variables, controlled by decision makers at the top levels. Then the fuzzy goal programming approach is used to achieve the highest degree of each of the membership goals by minimizing their deviational variables and thereby obtain the most satisfactory solution for all decision makers.     

Solving a multi periodic stochastic model of the rail–car fleet sizing by two-stage optimization formulation

We propose a formulation and solution procedure for optimizing the fleet size and freight car allocation under uncertainty demands. There are important interactions between decisions on sizing a rail–car fleet and utilizing that fleet. Consequently, the optimum use of empty rail–cars for demands response in the length of the time periods one of advantages the proposed model. The model also provides rail network information such as yard capacity, unmet demands, and number of loaded and empty rail–car at any given time and location. Consequently, the model helping managers or decision makers of any train company for planning and decision making. We propose two-stage solution procedure for solve rail–car fleet sizing problem. Numerical examples are given to illustrate the model and solution methodology.     

芯片瞬间等速电泳-筛分电泳偶联分析精确计算DNA长度

建立了基于相对迁移时间比例的方法,依据待侧DNA片段相对于上位及下位内标的迁移时间比例进行长度预测。实验结果显示,DNA片段的相对迁移时间比例在不同分析条件下具有良好的重现性。通过建立相对迁移时间比例相对于DNA片段长度的对应关系公式,实现了芯片瞬间等速电泳条件下DNA片段长度的准确预测。实际样品分析证实这种基于相对迁移时间比例的计算方法简单可靠,适合于芯片tITP-CGE分析中DNA长度的精确判定。     

不加抗静电剂的防静电胶料配方研究

应用普通的原材料,不加抗静电剂,研究防静电胶料配方,只对橡胶和配合剂的导电参数及绝缘参数进行调整,以达到胶料的防静电效能     

农科院校无机及分析化学实验课程教学体系的建设

通过课程体系、教学内容、教学方法手段和考核模式的改革与实践,强化多学科交叉融合,突出学生个性发展,创新人才培养模式,构建一个教学内容先进、农科特色鲜明的多层次无机及分析化学实验教学体系。