Production of pH-responsive microparticles by spray drying: investigation of experimental parameter effects on morphological and release properties

During spray drying, emphasis is placed on process optimisation to generate favourable particle morphological and flow properties. The effect of the initial feed solution composition on the drug release from the prepared microparticles is rarely considered. We investigated the effects of solvent composition, feed solution concentration and drug-loading on sodium salicylate, hydrocortisone and triamcinolone release from spray dried Eudragit L100 microparticles. Eudragit L100 is a pH-responsive polymer whose dissolution threshold is pH 6 so dissolution testing of the prepared microparticles at pH 5 and 1.2 illustrated non-polymer controlled burst release. Increasing the water content of the initial ethanolic feed solution significantly reduced hydrocortisone burst release at pH 5, as did reducing the feed solution concentration. These findings caution that changes in feed solution concentration or solvent composition not only affect particles’ morphological characteristics but can also negatively alter their drug release properties. This work also illustrate that drug-free microparticles can have different morphological properties to drug-loaded microparticles. Therefore, process optimisation needs to be carried out using drug-loaded systems. Depending on the physicochemical properties of the encapsulated API, drug-loading can affect the polymer solubility in the initial feed solution with consequent impact on microparticles morphological and release properties.

Changes in the relative importance of sector and regional factors: 1987-2002

A stylised fact in the real estate portfolio diversification literature is that sector (property-type) effects are relatively more important than regional (geographical) factors in determining property returns. Thus, for those portfolio managers who follow a top-down approach to portfolio management, they should first choose in which sectors to invest and then select the best properties in each market. However, the question arises as to whether the dominance of the sector effects relative to regional effects is constant. If not property fund managers will need to take account of regional effects in developing their portfolio strategy. Using monthly data over the period 1987:1 to 2002:12 for a sample of over 1000 properties the results show that the sector-specific factors dominate the regional-specific factors for the vast majority of the time. Nonetheless, there are periods when the regional factors are of equal or greater importance than the sector effects. In particular, the sector effects tend to dominate during volatile periods of the real estate cycle; however, during calmer periods the sector and regional effects are of equal importance. These findings suggest that the sector effects are still the most important aspect in the development of an active portfolio strategy.

Effect of drying methods on the phenolic constituents of meadowsweet (Filipendula ulmaria) and willow (Salix alba)

The objective of this study was to investigate the effect of drying conditions on the phenolic constituents and colour of extracts of organically grown white willow and meadowsweet for incorporation into a functional beverage with potential anti-inflammatory properties. The herbs were freeze-dried, air-dried, oven or tray-dried at 30 or 70 °C. The drying kinetics of the herbs was first determined. Both drying temperature and method had a significant effect (p ≤ 0.05) on the drying rate, the samples tray-dried had a faster drying rate than those oven-dried. Results show that for meadowsweet and willow, freeze-drying and oven or tray drying at 30 °C had no significant effect on the phenolic constituents (e.g. total phenols, salicylates, quercetin) or the colour of the extracts in comparison to traditional air-drying. Although increasing the drying temperature to 70 °C resulted in an increase in the drying rate of both herbs it also led to the loss of some phenolic compounds. Also, the extracts from both herbs dried at 70 °C were significantly (p ≤ 0.05) redder than the other drying methods. Therefore, tray drying these herbs at low temperatures may reduce drying time without having a significant effect on the phenolic content and colour of the extracts.

Conceptualising and measuring the equity of online brands

Although brand equity is an important source of competitive advantage online, previous conceptualisations and measures overlook the unique characteristics of the internet that render consumers co-creators of brand value. In view of this, a threephased research programme was undertaken to identify the facets of online retail/service (ORS) brand equity and then develop and validate a scale for its measurement. ORS brand equity was found to be a second order construct with five correlated yet distinct dimensions: emotional connection, online experience, responsive service nature, trust, and fulfilment. A series of tests showed that the ensuing 12-item scale has strong psychometric properties. The implications of this research for marketing researchers and practitioners are discussed.

Determining the contribution of volcanic ash and boundary layer aerosol in backscatter lidar returns: a three‐component atmosphere approach

A solution of the lidar equation is discussed, that permits combining backscatter and depolarization measurements to quantitatively distinguish two different aerosol types with different depolarization properties. The method has been successfully applied to simultaneous observations of volcanic ash and boundary layer aerosol obtained in Exeter, United Kingdom, on 16 and 18 April 2010, permitting the contribution of the two aerosols to be quantified separately. First a subset of the atmospheric profiles is used where the two aerosol types belong to clearly distinguished layers, for the purpose of characterizing the ash in terms of lidar ratio and depolarization. These quantities are then used in a three‐component atmosphere solution scheme of the lidar equation applied to the full data set, in order to compute the optical properties of both aerosol types separately. On 16 April a thin ash layer, 100–400 m deep, is observed (average and maximum estimated ash optical depth: 0.11 and 0.2); it descends from ∼2800 to ∼1400 m altitude over a 6‐hour period. On 18 April a double ash layer, ∼400 m deep, is observed just above the morning boundary layer (average and maximum estimated ash optical depth: 0.19 and 0.27). In the afternoon the ash is entrained into the boundary layer, and the latter reaches a depth of ∼1800 m (average and maximum estimated ash optical depth: 0.1 and 0.15). An additional ash layer, with a very small optical depth, was observed on 18 April at an altitude of 3500–4000 m. By converting the lidar optical measurements using estimates of volcanic ash specific extinction, derived from other works, the observations seem to suggest approximate peak ash concentrations of ∼1500 and ∼1000 mg/m3,respectively, on the two observations dates.

Biaxial optical properties of thermotropic random copolyesters

The optical microstructures of thin sections of two liquid crystalline polymers are examined in the polarizing microscope. The polymers are random copolyesters based on hydroxybenzoic and hydroxynaphthoic acids (B-N), and hydroxybenzoic acid and ethylene terephthalate (B-ET). Sections cut from oriented samples, so as to include the extrusion direction, show microstructures in which there is no apparent preferred orientation of the axes describing the local optical anisotropy. The absence of preferred orientation in the microstructure, despite marked axial alignment of molecular chain segments as demonstrated by X-Ray diffraction, is interpreted in terms of the polymer having biaxial optical properties. The implication of optical biaxiality is that, although the mesophases are nematic, the orientation of the molecules is correlated about three (orthogonal) axes over distances greater than a micron. The structure is classified as a multiaxial nematic.

Toward understanding of differences in current cloud retrievals of ARM ground-based measurements

Accurate observations of cloud microphysical properties are needed for evaluating and improving the representation of cloud processes in climate models and better estimate of the Earth radiative budget. However, large differences are found in current cloud products retrieved from ground-based remote sensing measurements using various retrieval algorithms. Understanding the differences is an important step to address uncertainties in the cloud retrievals. In this study, an in-depth analysis of nine existing ground-based cloud retrievals using ARM remote sensing measurements is carried out. We place emphasis on boundary layer overcast clouds and high level ice clouds, which are the focus of many current retrieval development efforts due to their radiative importance and relatively simple structure. Large systematic discrepancies in cloud microphysical properties are found in these two types of clouds among the nine cloud retrieval products, particularly for the cloud liquid and ice particle effective radius. Note that the differences among some retrieval products are even larger than the prescribed uncertainties reported by the retrieval algorithm developers. It is shown that most of these large differences have their roots in the retrieval theoretical bases, assumptions, as well as input and constraint parameters. This study suggests the need to further validate current retrieval theories and assumptions and even the development of new retrieval algorithms with more observations under different cloud regimes.

Assessment of the anti-genotoxic, anti-proliferative, and anti-metastatic potential of crude watercress extract in human colon cancer cells

Although it is known to be a rich source of the putative anti-cancer chemicals isothiocyanates, watercress has not been extensively studied for its cancer preventing properties. The aim of this study was to investigate the potential chemoprotective effects of crude watercress extract toward three important stages in the carcinogenic process, namely initiation, proliferation, and metastasis (invasion) using established in vitro models. HT29 cells were used to investigate the protective effects of the extract on DNA damage and the cell cycle. The extract was not genotoxic but inhibited DNA damage induced by two of the three genotoxins used, namely hydrogen peroxide and fecal water, indicating the potential to inhibit initiation. It also caused an accumulation of cells in the S phase of the cell cycle indicating (possible) cell cycle delay at this stage. The extract was shown to significantly inhibit invasion of HT115 cells through matrigel. Component analysis was also carried out in an attempt to determine the major phytochemicals present in both watercress leaves and the crude extract. In conclusion, the watercress extract proved to be significantly protective against the three stages of the carcinogenesis process investigated.

Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks

In order to gain knowledge from large databases, scalable data mining technologies are needed. Data are captured on a large scale and thus databases are increasing at a fast pace. This leads to the utilisation of parallel computing technologies in order to cope with large amounts of data. In the area of classification rule induction, parallelisation of classification rules has focused on the divide and conquer approach, also known as the Top Down Induction of Decision Trees (TDIDT). An alternative approach to classification rule induction is separate and conquer which has only recently been in the focus of parallelisation. This work introduces and evaluates empirically a framework for the parallel induction of classification rules, generated by members of the Prism family of algorithms. All members of the Prism family of algorithms follow the separate and conquer approach.

Mobility based energy efficient and multi-sink algorithms for consumer home networks

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment.

IMILAST: a community effort to intercompare extratropical cyclone detection and tracking algorithms

The variability of results from different automated methods of detection and tracking of extratropical cyclones is assessed in order to identify uncertainties related to the choice of method. Fifteen international teams applied their own algorithms to the same dataset—the period 1989–2009 of interim European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERAInterim) data. This experiment is part of the community project Intercomparison of Mid Latitude Storm Diagnostics (IMILAST; see www.proclim.ch/imilast/index.html). The spread of results for cyclone frequency, intensity, life cycle, and track location is presented to illustrate the impact of using different methods. Globally, methods agree well for geographical distribution in large oceanic regions, interannual variability of cyclone numbers, geographical patterns of strong trends, and distribution shape for many life cycle characteristics. In contrast, the largest disparities exist for the total numbers of cyclones, the detection of weak cyclones, and distribution in some densely populated regions. Consistency between methods is better for strong cyclones than for shallow ones. Two case studies of relatively large, intense cyclones reveal that the identification of the most intense part of the life cycle of these events is robust between methods, but considerable differences exist during the development and the dissolution phases.

A Wiener-Hopf type factorization for the exponential functional of Levy processes

For a Lévy process ξ=(ξt)t≥0 drifting to −∞, we define the so-called exponential functional as follows: Formula Under mild conditions on ξ, we show that the following factorization of exponential functionals: Formula holds, where × stands for the product of independent random variables, H− is the descending ladder height process of ξ and Y is a spectrally positive Lévy process with a negative mean constructed from its ascending ladder height process. As a by-product, we generate an integral or power series representation for the law of Iξ for a large class of Lévy processes with two-sided jumps and also derive some new distributional properties. The proof of our main result relies on a fine Markovian study of a class of generalized Ornstein–Uhlenbeck processes, which is itself of independent interest. We use and refine an alternative approach of studying the stationary measure of a Markov process which avoids some technicalities and difficulties that appear in the classical method of employing the generator of the dual Markov process.

Estimation of sea surface temperature from the Spinning Enhanced Visible and Infra Red Imager, improved using numerical weather prediction

Most of the operational Sea Surface Temperature (SST) products derived from satellite infrared radiometry use multi-spectral algorithms. They show, in general, reasonable performances with root mean square (RMS) residuals around 0.5 K when validated against buoy measurements, but have limitations, particularly a component of the retrieval error that relates to such algorithms' limited ability to cope with the full variability of atmospheric absorption and emission. We propose to use forecast atmospheric profiles and a radiative transfer model to simulate the algorithmic errors of multi-spectral algorithms. In the practical case of SST derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), we demonstrate that simulated algorithmic errors do explain a significant component of the actual errors observed for the non linear (NL) split window algorithm in operational use at the Centre de Météorologie Spatiale (CMS). The simulated errors, used as correction terms, reduce significantly the regional biases of the NL algorithm as well as the standard deviation of the differences with drifting buoy measurements. The availability of atmospheric profiles associated with observed satellite-buoy differences allows us to analyze the origins of the main algorithmic errors observed in the SEVIRI field of view: a negative bias in the inter-tropical zone, and a mid-latitude positive bias. We demonstrate how these errors are explained by the sensitivity of observed brightness temperatures to the vertical distribution of water vapour, propagated through the SST retrieval algorithm.

Validity of the ice shelf water plume concept beneath Filchner-Ronne Ice Shelf

In winter, brine rejection from sea ice formation and export in the Weddell Sea, offshore of Filchner-Ronne Ice Shelf (FRIS), leads to the formation of High Salinity Shelf Water (HSSW). This dense water mass enters the cavity beneath FRIS by sinking southward down the sloping continental shelf towards the grounding line. Melting occurs when the HSSW encounters the ice shelf, and the meltwater released cools and freshens the HSSW to form a water mass known as Ice Shelf Water (ISW). If this ISW rises, the ‘ice pump’ is initiated (Lewis and Perkin, 1986), whereby the ascending ISW becomes supercooled and deposits marine ice at shallower locations due to the pressure increase in the in-situ freezing temperature. Sandh¨ager et al. (2004) were able to infer the thickness patterns of marine ice deposits at the base of FRIS (figure 1), so the primary aim of this work is to try to understand the ocean flows that determine these patterns. The plume model we use to investigate ISW flow is described fully by Holland and Feltham (accepted) so only a relatively brief outline is presented here. The plume is simulated by combining a parameterisation of ice shelf basal interaction and a multiplesize- class frazil dynamics model with an unsteady, depth-averaged reduced-gravity plume model. In the model an active region of ISW evolves above and within an expanse of stagnant ambient fluid, which is considered to be ice-free and has fixed profiles of temperature and salinity. The two main assumptions of the model are that there is a well-mixed layer underneath the ice shelf and that the ambient fluid outside the plume is stagnant with fixed properties. The topography of the ice shelf that the plume flows beneath is set to the FRIS ice shelf draft calculated by Sandh¨ager et al. (2004) masked with the grounding line from the Antarctic Digital Database (ADD Consortium, 2002). To initiate the plumes, we assume that the intrusion of dense HSSW initially causes melting at the points on the grounding line where the glaciological tributaries feeding FRIS go afloat.

Data stream mining in ubiquitous environments: state-of-the-art and current directions

In this article, we review the state-of-the-art techniques in mining data streams for mobile and ubiquitous environments. We start the review with a concise background of data stream processing, presenting the building blocks for mining data streams. In a wide range of applications, data streams are required to be processed on small ubiquitous devices like smartphones and sensor devices. Mobile and ubiquitous data mining target these applications with tailored techniques and approaches addressing scarcity of resources and mobility issues. Two categories can be identified for mobile and ubiquitous mining of streaming data: single-node and distributed. This survey will cover both categories. Mining mobile and ubiquitous data require algorithms with the ability to monitor and adapt the working conditions to the available computational resources. We identify the key characteristics of these algorithms and present illustrative applications. Distributed data stream mining in the mobile environment is then discussed, presenting the Pocket Data Mining framework. Mobility of users stimulates the adoption of context-awareness in this area of research. Context-awareness and collaboration are discussed in the Collaborative Data Stream Mining, where agents share knowledge to learn adaptive accurate models.