Recent Technologies for Ballast Water Treatment

Concern about ballast-mediated bioinvasions into freshwater, estuarine and marine habitats is not limited to biodiversity per se but extends to its broader socio-economic impacts on agriculture, forests, fisheries, aquaculture, and other human activities dependent on the stability of living resources in a particular ecosystem. As a result, invasive species pose almost incalculable economic, socio-cultural and human health security risks. The importance of biological invasions was brought into greater focus as several devastating introductions in many countries occurred and given the limitations of the IMO (International Marine Organization) Guidelines. Consequently the International Convention for the Control and Management of Ships' Ballast Water and Sediments was prepared and was adopted in a Diplomatic Conference in 2004. This Convention aimed to prevent, minimize and ultimately eliminate the risks to the environment, human health, property and resources arising from the transfer of harmful aquatic organisms and pathogens via ships' ballast waters. This article describes recent ballast water treatment studies from scientific and academic community since the last IMO Convention in 2004, and the treatment that received basic and final approval by IMO. We examined different methods available on scientific media to treat ballast water (lab-scale and field-scale tests) and we concluded that a standardization of ballast water treatment still to be done to ensure the IMO Standard.     

Study of the conditions for multi‐modal chromatographic capture of Fab′ from dual‐salt precipitated E. coli homogenate

BACKGROUND: In the commercial‐scale purification of immunotherapeutics, Protein A chromatography is employed routinely for its high binding capacity and selectivity. Nevertheless, matrix cost and ligand leaching issues remain and there are many alternatives such as ion‐exchange and multi‐modal resins that are less expensive. However, binding capacities are lower than Protein A owing to the co‐adsorption of protein impurities. One solution involves removing impurities before chromatography by precipitation and a potential approach presented in the literature recently employs a dual‐salt precipitation technique. The current study explores the impact of this upon the capture of an antibody fragment by a multimodal cation exchange resin. RESULTS: The dual salt precipitation procedure employed here removed 36% of the contaminant proteins. A microscale chromatography pipette tip approach was used in a high throughput screening format to scout rapidly for favourable binding conditions successfully. Higher binding capacities were achieved by activating the hydrophobic binding modality of the resin at feed ionic strengths of around 150 mS cm^?1 using ammonium sulphate. This was better than using the ion‐exchange modality at below 10 mS cm^?1. CONCLUSIONS: Dual salt precipitation followed by chromatographic capture using this resin were found to be complementary to one another since the removal of protein impurities by dual salt precipitation resulted in a two‐fold improvement in terms of binding capacity. © 2012 Society of Chemical Industry     

Familiarity for associations? A test of the domain dichotomy theory.

Episodic recognition memory is mediated by functionally separable retrieval processes, notably familiarity (a general sense of prior exposure) and recollection (the retrieval of contextual details), whose relative engagement depends partly on the nature of the information being retrieved. Currently, the specific contribution of familiarity to associative recognition memory (where retrieval of the relationships between pairs of stimuli is required) is not clearly understood. In this study, we tested domain dichotomy theory, which predicts that familiarity should contribute more to associative memory when stimuli are similar (within-domain) than when they are distinct (between-domain). Participants studied stimulus pairs, and at test, discriminated intact from rearranged pairs. Stimuli were either within-domain (name–name or image–image pairs) or between-domain (name–image pairs). Across experiments we used 2 different behavioral measures of familiarity based on receiver operating characteristic curves and a modified remember–know procedure. Both experiments provided evidence that familiarity can contribute to associative recognition; however, familiarity was stronger for between-domain pairs, in direct contrast to the domain dichotomy prediction. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Crystal Structure of a Soluble Form of Human CD73 with Ecto‐5′‐Nucleotidase Activity

CD73 is a dimeric ecto‐5′‐nucleotidase that is expressed on the exterior side of the plasma membrane. CD73 has important regulatory functions in the extracellular metabolism of certain nucleoside monophosphates, in particular adenosine monophosphate, and has been linked to a number of pathological conditions such as cancer and myocardial ischaemia. Here, we present the crystal structure of a soluble form of human soluble CD73 (sCD73) at 2.2 Å resolution, a truncated form of CD73 that retains ecto‐5′‐nucleotidase activity. With this structure we obtained insight into the dimerisation of CD73, active site architecture, and a sense of secondary modifications of the protein. The crystal structure reveals a conserved loop that is directly involved in the dimer‐dimer interaction showing that the two subunits of the dimer are not linked by disulfide bridges. Using biophotonic microarray imaging we were able to confirm glycosylation of the enzyme and show that the enzyme is decorated with a variety of oligosaccharide structures. The crystal structure of sCD73 will aid the design of inhibitors or activator molecules for the treatment of several diseases and prove useful in explaining the possible roles of single nucleotide polymorphisms in physiology and disease.     

Spatio-temporal variability of solar energy across a region: a statistical modelling approach

Solar energy collected at a number of discrete sites, which are dispersed over a geographical area, will exhibit both spatial and temporal variability. Being able to model this variability will have many applications, for example in controlling an electricity system that is supplied by decentralised PV arrays. This paper describes a statistical modelling study of solar data that were recorded over 2 years at a total of 22 sites in the city of Edinburgh, Scotland, and in the nearby Pentland hills. A spatio-temporal model is proposed for global irradiation on a horizontal plane: this incorporates the sum of two exponentials to model the decrease in covariance between sites with time lag, and a space–time term to model the combined dependence of covariance on time lag and easterly distance.     

Re-Imagining Psychiatric Asylum Spaces through Residential Redevelopment: Strategic Forgetting and Selective Remembrance

The closure of psychiatric asylums across the western world has brought significant amounts of ‘brown field’ land onto the market over the past few decades. Situated on the edge (or former edge) of many cities, these sites have proven attractive for residential redevelopment. Drawing on two case studies from the UK and New Zealand, we consider the implications of such recycling in the built environment for the memory of the former use, asking how redevelopment addresses the stigmatised past of the asylum. We discuss issues associated with the ‘re-imagining’ of heritage buildings and landscapes and examine the extent to which the past is strategically forgotten or selectively remembered in the repackaging of the asylum as housing. We conclude that while stigma continues to cast a shadow over reuse of former asylum spaces, in both case studies impacts seem to dissipate over time. In the UK, this dissipation appears to be enhanced by the presence of policies that cast redevelopment for housing as a source of funding for heritage conservation.     

What’s missing in geographical parsing?

Geographical data can be obtained by converting place names from free-format text into geographical coordinates. The ability to geo-locate events in textual reports represents a valuable source of information in many real-world applications such as emergency responses, real-time social media geographical event analysis, understanding location instructions in auto-response systems and more. However, geoparsing is still widely regarded as a challenge because of domain language diversity, place name ambiguity, metonymic language and limited leveraging of context as we show in our analysis. Results to date, whilst promising, are on laboratory data and unlike in wider NLP are often not cross-compared. In this study, we evaluate and analyse the performance of a number of leading geoparsers on a number of corpora and highlight the challenges in detail. We also publish an automatically geotagged Wikipedia corpus to alleviate the dearth of (open source) corpora in this domain.     

Compensating for End Effects in Plate-and-Frame Heat Exchangers

Suspended nanoparticles in conventional fluids, called nanofluids, have been the subject of intensive study worldwide since pioneering researchers recently discovered the anomalous thermal behavior of these fluids. The enhanced thermal conductivity of these fluids with small-particle concentration was surprising and could not be explained by existing theories. Micrometer-sized particle-fluid suspensions exhibit no such dramatic enhancement. This difference has led to studies of other modes of heat transfer and efforts to develop a comprehensive theory. This article presents an exhaustive review of these studies and suggests a direction for future developments. The review and suggestions could be useful because the literature in this area is spread over a wide range of disciplines, including heat transfer, material science, physics, chemical engineering and synthetic chemistry.     

A neuro-fuzzy approach for robot system safety

Robot safety is a critical and largely unsolved problem involving the interaction of man and machine. The paper presents a new approach to robot safety which uses an integrated sensing architecture for monitoring the robot workspace, and a new detection and decision logic for regulating the safe operation of the robot. Sensory information is fused through a trained neural network to produce a map of the hazards. Using this combined map, and information about the robot's current position and velocity, a set of fuzzy logic rules has been implemented to regulate robot activity. Simulation results presented in the paper indicate that this method is both effective in detection of potentially hazardous situations and computationally feasible