64通道一维位置灵敏电流分布探测器及其数据获取系统；A 64-Channel Position Sensitive Current Distribution Detector with Data Acquisition System

针对高流强粒子束与绝缘毛细管相互作用的特点,设计制作了一套64通道一维位置灵敏电流分布探测器及其配套的数据获取系统,该探测器可分辨最小直径为1mm的束斑,通过数据获取系统可实现可视化自动数据采集。用2nA和200—2000eV电子对探测器进行了定标,并用10μA和2000eV的电子束穿越锥形毛细管后的出射电子,对探测器及数据获取系统进行测试,获得了出射粒子的位置分布谱及能量信息。

beta-NaYF4 and beta-NaYF4:Eu3+ Microstructures: Morphology Control and Tunable Luminescence Properties

beta-NaYF4 hexagonal microprisms and microrods with different aspect ratios have been prepared via a simple hydrothermal route. X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and photoluminescence (PL) spectra as well as kinetic decays were used to characterize the samples. The influences of reaction temperature and the molar ratio of NaF to y(3+) on the crystal phases and shapes of final products have been studied in detail. The aspect ratios of products increase gradually with the increase of reaction temperature and NaF/Y3+ molar ratio. The growth mechanisms of crystals prepared under the different conditions are presented systematically. More importantly, the systematical investigation on the luminescence properties of beta-NaYF4:xEu(3+) (x = 0.5, 1, 2, 3, 5, and 10 mol %) with hexagonally microprismatic morphology shows the characteristic emissions of Eu3+ (D-5(J)-F-7(J'), J, J' = 0, 1, 2, 3). Under the excitation of single wavelength light of 397 nm, the luminescence colors of the corresponding products can be tuned feasibly from bluish white to yellow to red by changing the doping concentration of Eu3+.

Application of Ru(bpy)(3)(2+) in control and formation of gold surface nanostructure through oxidation-reduction cycling

It was studied that the nanostructure formed on a gold surface via a simple oxidation-reduction cycles (ORC) in 0.1 M KCl containing Ru(bpy)(3)(2+) with different concentrations. Atomic force microscopy (AFM) and energy-dispersed spectroscopy (EDS) were used to characterize the nanostructure formed on the gold surface. Sweep-step voltammetry and corresponding electroluminescence (ECL) response, in situ electrochemical quartz crystal microbalance (EQCM) measurement were used to monitor the ORC. procedure. It was found that the surface structure became more uniform in the presence of Ru(bpy)(3)(2+), and the surface roughness was decreasing with the increasing of Ru(bpY)(3)(2+) concentration, suggesting a simple and effective method to control the formation of nanostructure on the gold surface.

Morphological control and luminescent properties of CeF3 nanocrystals

The nanocrystals of CeF3 with the hexagonal structure and different morphologies such as the disk, the rod, and the dot have been successfully synthesized via a mild ultrasound assisted route from an aqueous solution of cerium nitrate and different fluorine sources (KBF4, NaF, NH4F). The use of different fluorine sources has a remarkable effect on the morphology of the final product. The luminescence and UV-vis absorption properties of CeF3 nanocrystals with different morphologies have been investigated. Compared with other shape nanocrystals, the luminescence intensity of the disklike nanocrystals is obviously enhanced. It is suggested that the function-improved materials could be obtained by tailoring the shape of the CeF3 nanocrystals.

Morphology control and luminescence properties of YAG : Eu phosphors prepared by spray pyrolysis

Starting from nitrate aqueous solutions with citric acid and polyethylene glycol (PEG) as additives, Y3Al5O12:Eu (YAG:Eu) phosphors were prepared by a two-step spray pyrolysis (SP) method. The obtained YAG:Eu phosphor particles have spherical shape, submicron size and smooth surface. The effects of process conditions of the spray pyrolysis on the crystallinity, morphology and luminescence properties of phosphor particles were investigated. The emission intensity of the phosphors increased with increasing of sintering temperature and solution concentration due to the increase of the crystallinity and particles size, respectively. Adequate amount of PEG was necessary for obtaining spherical particles, and the optimum emission intensity could be obtained when the concentration of PEG was 0.10 g/ml in the precursor solution. Compared with the YAG:Eu phosphor prepared by citrate-gel (CG) method with non-spherical morphology, spherical YAG:Eu phosphor particles showed a higher emission intensity.

A NOVEL SHELL COLOR VARIANT OF THE PACIFIC ABALONE HALIOTIS DISCUS HANNAI INO SUBJECT TO GENETIC CONTROL AND DIETARY INFLUENCE

Molluscan shells may display a variety of colors, which formation, inheritance, and evolutionary significance are not Well understood. Here we report a new variant of the Pacific abalone Haliotis discus hannai that displays a novel orange shell coloration (O-type) that is clearly distinguishable from the Wild green-shelled abalone (G-type). Controlled mating experiments between O- and G-type abalones demonstrated apparent Mendelian segregations (1:1 or 3:1) in shell colors in F-2 families, which support the notion that the O- and G-types are under strict genetic control at a single locus With a recessive o (for orange shell) allele and a dominant G (for green shell) allele. Feeding with different diets caused modifications of shell color within each genotype, ranging from orange to yellow for O-type and green to dark-brown for the G-type, without affecting the distinction between genotypes. A previously described bluish-purple (B-type) shell color was found in one of the putative oo X oG crosses, suggesting that the B-type may be it recessive allele belonging to the same locus. The new O-type variant had no effect on the growth of Pacific abalone on the early seed-stage. This Study demonstrates that shell color in Pacific abalone is subject to genetic control as well as dietary modification, and the latter probably offers selective advantages in camouflage and predator avoidance.

Pump-dump control and the related transient absorption spectroscopies

We combine theories of optimal pump-dump control and the related transient probe absorption spectroscopy in order to elucidate the relation between these two optical processes and the possibility of experimental realization. In the weak response regime, we identify the globally optimal pair of pump-dump control fields, and further propose a second-order difference detection scheme to monitor the wave packets dynamics that is jointly controlled by both the pump and dump fields. The globally optimal solution serves also as the initial input for the iterative search for the optimal control fields in the strong response regime. We use a model I-2 molecule to demonstrate numerically the pump-dump control and the detection of a highly vibrationally excited wave packet focusing dynamics on the ground X surface in both the weak and strong response regimes. The I2B surface serves as the intermediate to assist the pump-dump control and the optical detection processes. Demonstrated in the strong response regime are the optimal pair of pump-dump molecular-pi pulses that invert nearly total population onto the predefined target region within a half period of vibration motion. (C) 1999 American Institute of Physics. [S0021-9606(99)00115-4].

Naive Physics, Event Perception, Lexical Semantics, and Language Acquisition

This thesis proposes a computational model of how children may come to learn the meanings of words in their native language. The proposed model is divided into two separate components. One component produces semantic descriptions of visually observed events while the other correlates those descriptions with co-occurring descriptions of those events in natural language. The first part of this thesis describes three implementations of the correlation process whereby representations of the meanings of whole utterances can be decomposed into fragments assigned as representations of the meanings of individual words. The second part of this thesis describes an implemented computer program that recognizes the occurrence of simple spatial motion events in simulated video input.

A control and monitoring system for multiple-sensor industrial robots

Barnes, D. P., Lee, M. H., Hardy, N. W. (1983). A control and monitoring system for multiple-sensor industrial robots. In Proc. 3rd. Int. Conf. Robot Vision and Sensory Controls, Cambridge, MA. USA., 471-479.

TCP-friendly SIMD Congestion Control and Its Convergence Behavior

The increased diversity of Internet application requirements has spurred recent interests in flexible congestion control mechanisms. Window-based congestion control schemes use increase rules to probe available bandwidth, and decrease rules to back off when congestion is detected. The parameterization of these control rules is done so as to ensure that the resulting protocol is TCP-friendly in terms of the relationship between throughput and packet loss rate. In this paper, we propose a novel window-based congestion control algorithm called SIMD (Square-Increase/Multiplicative-Decrease). Contrary to previous memory-less controls, SIMD utilizes history information in its control rules. It uses multiplicative decrease but the increase in window size is in proportion to the square of the time elapsed since the detection of the last loss event. Thus, SIMD can efficiently probe available bandwidth. Nevertheless, SIMD is TCP-friendly as well as TCP-compatible under RED, and it has much better convergence behavior than TCP-friendly AIMD and binomial algorithms proposed recently.

Development of miniaturized wireless sensor nodes suitable for building energy management and modelling

Buildings consume 40% of Ireland's total annual energy translating to 3.5 billion (2004). The EPBD directive (effective January 2003) places an onus on all member states to rate the energy performance of all buildings in excess of 50m2. Energy and environmental performance management systems for residential buildings do not exist and consist of an ad-hoc integration of wired building management systems and Monitoring & Targeting systems for non-residential buildings. These systems are unsophisticated and do not easily lend themselves to cost effective retrofit or integration with other enterprise management systems. It is commonly agreed that a 15-40% reduction of building energy consumption is achievable by efficiently operating buildings when compared with typical practice. Existing research has identified that the level of information available to Building Managers with existing Building Management Systems and Environmental Monitoring Systems (BMS/EMS) is insufficient to perform the required performance based building assessment. The cost of installing additional sensors and meters is extremely high, primarily due to the estimated cost of wiring and the needed labour. From this perspective wireless sensor technology provides the capability to provide reliable sensor data at the required temporal and spatial granularity associated with building energy management. In this paper, a wireless sensor network mote hardware design and implementation is presented for a building energy management application. Appropriate sensors were selected and interfaced with the developed system based on user requirements to meet both the building monitoring and metering requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks associated with minimisation of energy consumption in the built environment and the development of appropriate Building information models(BIM)to enable the design and development of energy efficient spaces.

The biodiversity, control and genetic characterisation of the lactococcal 936 group phages

Phages belonging to the 936 group represent one of the most prevalent and frequently isolated phages in dairy fermentation processes using Lactococcus lactis as the primary starter culture. In recent years extensive research has been carried out to characterise this phage group at a genomic level in an effort to understand how the 936 group phages dominate this particular niche and cause regular problems during large scale milk fermentations. This thesis describes a large scale screening of industrial whey samples, leading to the isolation of forty three genetically different lactococcal phages. Using multiplex PCR, all phages were identified as members of the 936 group. The complete genome of thirty eight of these phages was determined using next generation sequencing technologies which identified several regions of divergence. These included the structural region surrounding the major tail protein, the replication region as well as the genes involved in phage DNA packing. For a number of phages the latter genomic region was found to harbour genes encoding putative orphan methyltransferases. Using small molecule real time (SMRT) sequencing and heterologous gene expression, the target motifs for several of these MTases were determined and subsequently shown to actively protect phage DNA from restriction endonuclease activity. Comparative analysis of the thirty eight phages with fifty two previously sequenced members of this group showed that the core genome consists of 28 genes, while the non-core genome was found to fluctuate irrespective of geographical location or time of isolation. This study highlights the continued need to perform large scale characterisation of the bacteriophage populations infecting industrial fermentation facilities in effort to further our understanding dairy phages and ways to control their proliferation.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Different Mechanisms Confer Gradual Control and Memory at Nutrient- and Stress-Regulated Genes in Yeast.

Cells respond to environmental stimuli by fine-tuned regulation of gene expression. Here we investigated the dose-dependent modulation of gene expression at high temporal resolution in response to nutrient and stress signals in yeast. The GAL1 activity in cell populations is modulated in a well-defined range of galactose concentrations, correlating with a dynamic change of histone remodeling and RNA polymerase II (RNAPII) association. This behavior is the result of a heterogeneous induction delay caused by decreasing inducer concentrations across the population. Chromatin remodeling appears to be the basis for the dynamic GAL1 expression, because mutants with impaired histone dynamics show severely truncated dose-response profiles. In contrast, the GRE2 promoter operates like a rapid off/on switch in response to increasing osmotic stress, with almost constant expression rates and exclusively temporal regulation of histone remodeling and RNAPII occupancy. The Gal3 inducer and the Hog1 mitogen-activated protein (MAP) kinase seem to determine the different dose-response strategies at the two promoters. Accordingly, GAL1 becomes highly sensitive and dose independent if previously stimulated because of residual Gal3 levels, whereas GRE2 expression diminishes upon repeated stimulation due to acquired stress resistance. Our analysis reveals important differences in the way dynamic signals create dose-sensitive gene expression outputs.

Influence of network topology and data collection on network inference.

We recently developed an approach for testing the accuracy of network inference algorithms by applying them to biologically realistic simulations with known network topology. Here, we seek to determine the degree to which the network topology and data sampling regime influence the ability of our Bayesian network inference algorithm, NETWORKINFERENCE, to recover gene regulatory networks. NETWORKINFERENCE performed well at recovering feedback loops and multiple targets of a regulator with small amounts of data, but required more data to recover multiple regulators of a gene. When collecting the same number of data samples at different intervals from the system, the best recovery was produced by sampling intervals long enough such that sampling covered propagation of regulation through the network but not so long such that intervals missed internal dynamics. These results further elucidate the possibilities and limitations of network inference based on biological data.