Trend analysis in scientometrics

The thesis investigates the properties of two trends or time series which formed a:part of the Co-Citation bibliometric model "X~Ray Crystallography and Protein Determination in 1978, 1980 and 1982". This model was one of several created for the 1983 ABRC Science Policy Study which aimed to test the utility of bibliometric models in a national science policy context. The outcome of the validation part of that study proved to be especially favourable concerning the utility of trend data, which purport to model the development of speciality areas in science over time. This assessment could have important implications for the use of such data in policy formulation. However one possible problem with the Science Policy Study's conclusions was that insufficient time was available in the study for an in-depth analysis of the data. The thesis aims to continue the validation begun in the ABRC study by providing a detailed.examination of the characteristics of the data contained in the Trends numbered 11 and 44 in the model. A novel methodology for the analysis of the properties of the trends with respect to their literature content is presented. This is followed by an assessment based on questionnaire and interview data, of the ability of Trend 44 to realistically model the historical development of the field of mobile genetic elements research over time, with respect to its scientific content and the activities of its community of researchers. The results of these various analyses are then used to evaluate the strenghts and weaknesses of a trend or time series approach to the modelling of the activities of scientifiic fields. A critical evaluation of the origins of the discovered strengths and weaknesses.in the assumptions underlying the techniques used to generate trends from co-citation data is provided. Possible improvements. to the modelling techniques are discussed.

Project time risk analysis through simulation

An inherent weakness in the management of large scale projects is the failure to achieve the scheduled completion date. When projects are planned with the objective of time achievement, the initial planning plays a vital role in the successful achievement of project deadlines. Cost and quality are additional priorities when such projects are being executed. This article proposes a methodology for achieving time duration of a project through risk analysis with the application of a Monte Carlo simulation technique. The methodology is demonstrated using a case application of a cross-country petroleum pipeline construction project.

Time series analysis in the assessment of ICT impact at the aggregate level – lessons and implications for the new economy

The major role of information and communication technology (ICT) in the new economy is well documented: countries worldwide are pouring resources into their ICT infrastructure despite the widely acknowledged “productivity paradox”. Evaluating the contribution of ICT investments has become an elusive but important goal of IS researchers and economists. But this area of research is fraught with complexity and we have used Solow's Residual together with time-series analysis tools to overcome some methodological inadequacies of previous studies. Using this approach, we conduct a study of 20 countries to determine if there was empirical evidence to support claims that ICT investments are worthwhile. The results show that ICT contributes to economic growth in many developed countries and newly industrialized economies (NIEs), but not in developing countries. We finally suggest ICT-complementary factors, in an attempt to rectify possible flaws in ICT policies as a contribution towards improvement in global productivity.

Environmental scanning electron microscopy offers real-time morphological analysis of liposomes and niosomes

Liposomes have been imaged using a plethora of techniques. However, few of these methods offer the ability to study these systems in their natural hydrated state without the requirement of drying, staining, and fixation of the vesicles. However, the ability to image a liposome in its hydrated state is the ideal scenario for visualization of these dynamic lipid structures and environmental scanning electron microscopy (ESEM), with its ability to image wet systems without prior sample preparation, offers potential advantages to the above methods. In our studies, we have used ESEM to not only investigate the morphology of liposomes and niosomes but also to dynamically follow the changes in structure of lipid films and liposome suspensions as water condenses on to or evaporates from the sample. In particular, changes in liposome morphology were studied using ESEM in real time to investigate the resistance of liposomes to coalescence during dehydration thereby providing an alternative assay of liposome formulation and stability. Based on this protocol, we have also studied niosome-based systems and cationic liposome/DNA complexes. Copyright © Informa Healthcare.

Time scale analysis for fluidizedbedmeltgranulation-II: binder spreading rate

The spreading time of liquid binder droplet on the surface a primary particle is analyzed for Fluidized Bed Melt Granulation (FBMG). As discussed in the first paper of this series (Chua et al., in press) the droplet spreading rate has been identified as one of the important parameters affecting the probability of particles aggregation in FBMG. In this paper, the binder droplet spreading time has been estimated using Computational Fluid Dynamic modeling (CFD) based on Volume of Fluid approach (VOF). A simplified analytical solution has been developed and tested to explore its validity for predicting the spreading time. For the purpose of models validation, the droplet spreading evolution was recorded using a high speed video camera. Based on the validated model, a generalized correlative equation for binder spreading time is proposed. For the operating conditions considered here, the spreading time for Polyethylene Glycol (PEG1500) binder was found to fall within the range of 10-2 to 10-5 s. The study also included a number of other common binders used in FBMG. The results obtained here will be further used in paper III, where the binder solidification rate is discussed.

Time scale analysis for fluidizedbedmeltgranulation III: binder solidification rate

In series I and II of this study ([Chua et al., 2010a] and [Chua et al., 2010b]), we discussed the time scale of granule–granule collision, droplet–granule collision and droplet spreading in Fluidized Bed Melt Granulation (FBMG). In this third one, we consider the rate at which binder solidifies. Simple analytical solution, based on classical formulation for conduction across a semi-infinite slab, was used to obtain a generalized equation for binder solidification time. A multi-physics simulation package (Comsol) was used to predict the binder solidification time for various operating conditions usually considered in FBMG. The simulation results were validated with experimental temperature data obtained with a high speed infrared camera during solidification of ‘macroscopic’ (mm scale) droplets. For the range of microscopic droplet size and operating conditions considered for a FBMG process, the binder solidification time was found to fall approximately between 10-3 and 10-1 s. This is the slowest compared to the other three major FBMG microscopic events discussed in this series (granule–granule collision, granule–droplet collision and droplet spreading).

Time scale analysis for fluidized bed melt granulation I: granule-granule and granule-droplet collision rates

Fluidized bed spray granulators (FBMG) are widely used in the process industry for particle size growth; a desirable feature in many products, such as granulated food and medical tablets. In this paper, the first in a series of four discussing the rate of various microscopic events occurring in FBMG, theoretical analysis coupled with CFD simulations have been used to predict granule–granule and droplet–granule collision time scales. The granule–granule collision time scale was derived from principles of kinetic theory of granular flow (KTGF). For the droplet–granule collisions, two limiting models were derived; one is for the case of fast droplet velocity, where the granule velocity is considerable lower than that of the droplet (ballistic model) and another for the case where the droplet is traveling with a velocity similar to the velocity of the granules. The hydrodynamic parameters used in the solution of the above models were obtained from the CFD predictions for a typical spray fluidized bed system. The granule–granule collision rate within an identified spray zone was found to fall approximately within the range of 10-2–10-3 s, while the droplet–granule collision was found to be much faster, however, slowing rapidly (exponentially) when moving away from the spray nozzle tip. Such information, together with the time scale analysis of droplet solidification and spreading, discussed in part II and III of this study, are useful for probability analysis of the various event occurring during a granulation process, which then lead to be better qualitative and, in part IV, quantitative prediction of the aggregation rate.

Brillouin optical time-domain analysis assisted by second-order Raman amplification

We propose and experimentally demonstrate a new method to extend the range of Brillouin optical time domain analysis (BOTDA) systems. It exploits the virtual transparency created by second-order Raman pumping in optical fibers. The idea is theoretically analyzed and experimentally demonstrated in a 50 km fiber. By working close to transparency, we also show that the measurement length of the BOTDA can be increased up to 100 km with 2 meter resolution. We envisage extensions of this technique to measurement lengths well beyond this value, as long as the issue of relative intensity noise (RIN) of the primary Raman pump can be avoided. © 2010 Optical Society of America.

Hidden state models for time series

Amongst all the objectives in the study of time series, uncovering the dynamic law of its generation is probably the most important. When the underlying dynamics are not available, time series modelling consists of developing a model which best explains a sequence of observations. In this thesis, we consider hidden space models for analysing and describing time series. We first provide an introduction to the principal concepts of hidden state models and draw an analogy between hidden Markov models and state space models. Central ideas such as hidden state inference or parameter estimation are reviewed in detail. A key part of multivariate time series analysis is identifying the delay between different variables. We present a novel approach for time delay estimating in a non-stationary environment. The technique makes use of hidden Markov models and we demonstrate its application for estimating a crucial parameter in the oil industry. We then focus on hybrid models that we call dynamical local models. These models combine and generalise hidden Markov models and state space models. Probabilistic inference is unfortunately computationally intractable and we show how to make use of variational techniques for approximating the posterior distribution over the hidden state variables. Experimental simulations on synthetic and real-world data demonstrate the application of dynamical local models for segmenting a time series into regimes and providing predictive distributions.

Inverse forecasting:a new approach for predictive modelling

In the last two decades there have been substantial developments in the mathematical theory of inverse optimization problems, and their applications have expanded greatly. In parallel, time series analysis and forecasting have become increasingly important in various fields of research such as data mining, economics, business, engineering, medicine, politics, and many others. Despite the large uses of linear programming in forecasting models there is no a single application of inverse optimization reported in the forecasting literature when the time series data is available. Thus the goal of this paper is to introduce inverse optimization into forecasting field, and to provide a streamlined approach to time series analysis and forecasting using inverse linear programming. An application has been used to demonstrate the use of inverse forecasting developed in this study. © 2007 Elsevier Ltd. All rights reserved.

The geochemistry of the sedimentary rocks of the Harlech Dome, North Wales

Bedrock geochemical analysis, coupled with detailed data analysis, was carried out on some 260 samples taken from two areas of 'the Harlech Dome, near Dolgellau, North Wales. This was done to determine if rocks from mineralised and non-mineralised areas could be distinguished, and to determine mineralisation types and wall rock alterations. The Northern Area, near Talsarnau, has no recorded mineralisation, while the Southern Area, near Bontddu, has been exploited for gold. The rocks sampled, in both areas, were from the Cambrian Gamlan Flags, Clogau Shales, Vigra Flags, later vein materials, and igneous intrusions. All samples were analysed, using a new rapid, atomic absorption spectrophotometric technique, for Si, AI, Fe, Cu, Ni, Zn, Pb, Sr, Hg, and Ba. In addition 60 samples were analysed by X-ray fluorescence for Mn, Ti, Ca, K, Na, P, Cr, Ce, La, S, Y , Rh, and Th. Total CO2 was determined, on selected samples, using a combustion technique. Elemental distributions, for each rock type, in each area, were· plotted, and means, standard deviations, and enrichment indices were calculated. Multivariate statistical analysis on the results distinguished a Cu-type mineralisation in the Northern area, and both Cu and Pb/Zn types in the Southern Area. It also showed the Northern Area to be less strongly mineralised than the Southern one in which both mineralisation types are associated with wall rock alteration. Elemental associations and trends due to sedimentary processes were distinguished from those related to mineralisation. Hg is related to mineralisation, and plots of factor scores, on the sampling grid, produced clusters of mineralisation related factors in areas of known mineralisation. A double Fourier Trend Analysis program, with a wavelength search routine, was developed and used to recognise sedimentary trends for Sr. Y., Rb, and Th. These trends were interpreted to represent areas of low pH and reducing conditions. They also indicate that the supply of sediment remained constant over Gamlan, Clogau, and Vigra times. The trend surface of Hg showed no association with rock type. It is shown that analysis of a small number of samples, for a carefully selected number of elements, with detailed data analysis, can provide more useful information than analysis of a large number of samples for many elements. The mineralisation is suggested to have been the result of water solutions leaching ore metals from the sedimentary rocks and redepositing them in veins.

Asymmetric advertising impact

Companies under pressure from stakeholders to meet profit expectations are often tempted to cut advertising expenses, particularly in times of economic difficulties. However, firms may not fully grasp the actual impact of such drastic cuts. Indeed, the general assumption is that advertising effects are symmetric: the numerical sales impact of budget increase or decrease would be the same in absolute value. Our paper addresses this gap by developing a new model based on multivariate time-series analysis (VAR models) to capture these asymmetric dynamic relationships. Our results show that advertising models are improved by allowing the capture of these asymmetric patterns.

Steps and bumps:precision extraction of discrete states of molecular machines

We report statistical time-series analysis tools providing improvements in the rapid, precision extraction of discrete state dynamics from time traces of experimental observations of molecular machines. By building physical knowledge and statistical innovations into analysis tools, we provide techniques for estimating discrete state transitions buried in highly correlated molecular noise. We demonstrate the effectiveness of our approach on simulated and real examples of steplike rotation of the bacterial flagellar motor and the F1-ATPase enzyme. We show that our method can clearly identify molecular steps, periodicities and cascaded processes that are too weak for existing algorithms to detect, and can do so much faster than existing algorithms. Our techniques represent a step in the direction toward automated analysis of high-sample-rate, molecular-machine dynamics. Modular, open-source software that implements these techniques is provided.

A priori prediction of aggregation efficiency and rate constant for fluidized bed melt granulation

This paper presents a predictive aggregation rate model for spray fluidized bed melt granulation. The aggregation rate constant was derived from probability analysis of particle–droplet contact combined with time scale analysis of droplet solidification and granule–granule collision rates. The latter was obtained using the principles of kinetic theory of granular flow (KTGF). The predicted aggregation rate constants were validated by comparison with reported experimental data for a range of binder spray rate, binder droplet size and operating granulator temperature. The developed model is particularly useful for predicting particle size distributions and growth using population balance equations (PBEs).