K-Surfer: a KNIME extension for the management and analysis of Human brain MRI FreeSurfer/FSL data

Human brain imaging techniques, such as Magnetic Resonance Imaging (MRI) or Diffusion Tensor Imaging (DTI), have been established as scientific and diagnostic tools and their adoption is growing in popularity. Statistical methods, machine learning and data mining algorithms have successfully been adopted to extract predictive and descriptive models from neuroimage data. However, the knowledge discovery process typically requires also the adoption of pre-processing, post-processing and visualisation techniques in complex data workflows. Currently, a main problem for the integrated preprocessing and mining of MRI data is the lack of comprehensive platforms able to avoid the manual invocation of preprocessing and mining tools, that yields to an error-prone and inefficient process. In this work we present K-Surfer, a novel plug-in of the Konstanz Information Miner (KNIME) workbench, that automatizes the preprocessing of brain images and leverages the mining capabilities of KNIME in an integrated way. K-Surfer supports the importing, filtering, merging and pre-processing of neuroimage data from FreeSurfer, a tool for human brain MRI feature extraction and interpretation. K-Surfer automatizes the steps for importing FreeSurfer data, reducing time costs, eliminating human errors and enabling the design of complex analytics workflow for neuroimage data by leveraging the rich functionalities available in the KNIME workbench.

Evidence of heavy metal movement down the profile of a heavily-sludged soil

Two sites in central England where sewage sludge has been deposited for decades were studied to measure the heavy metal distribution in the soil profiles. The first site (S 1) was a field receiving heavy loads sludge from a nearby wastewater treatment plant, and the second (S2) was a farm applying 'normal' sludge rates of 8 t ha(-1) y(-1) of the same sludge. Soil samples were also taken by a near-by untreated control site. In S I the movement of heavy metals was significant even down to 80 cm depth compared to the control. In S2, the concentrations of lead (Pb) and zinc (Zn) and the organic matter content were higher than the control down to 20 cm, while nickel (Ni) moved significantly down to 80 cm. This underlies. the possibility that the metals bound onto organic surfaces moved along with organic matter down to that depth. The movement of metals in S2 points out the potential risks of applying sewage sludge for a long time.

Weaning preterm infants: a randomised controlled trial

Objective: To assess the effect on growth and iron status in preterm infants of a specially devised weaning strategy compared with current best practices in infant feeding. The preterm weaning strategy recommended the early onset of weaning and the use of foods with a higher energy and protein content than standard milk formula, and foods that are rich sources of iron and zinc. Subjects and design: In a blinded, controlled study, 68 preterm infants (mean (SD) birth weight 1470 (430) g and mean (SD) gestational age 31.3 (2.9) weeks) were randomised to either the preterm weaning strategy group (n = 37) or a current best practice control group (n = 31), from hospital discharge until 1 year gestation corrected age (GCA). Main outcome measures: Weight, supine length, occipitofrontal head circumference, and intakes of energy, protein, and minerals were determined at 0, 6, and 12 months GCA. Levels of haemoglobin, serum iron, and serum ferritin were assayed at 0 and 6 months GCA. Results: Significant positive effects of treatment included: greater increase in standard deviation length scores and length growth velocity; increased intake of energy, protein, and carbohydrate at 6 months GCA and iron at 12 months GCA; increased haemoglobin and serum iron levels at 6 months GCA. Conclusions: The preterm weaning strategy significantly influenced dietary intakes with consequent beneficial effects on growth in length and iron status. This strategy should be adopted as the basis of feeding guidelines for preterm infants after hospital discharge. School of Applied Statistics Faculty of Life Sciences

Life cycle analysis of UK coal fired power plants

This paper examines the life cycle GHG emissions from existing UK pulverized coal power plants. The life cycle of the electricity Generation plant includes construction, operation and decommissioning. The operation phase is extended to upstream and downstream processes. Upstream processes include the mining and transport of coal including methane leakage and the production and transport of limestone and ammonia, which are necessary for flue gas clean up. Downstream processes, on the other hand, include waste disposal and the recovery of land used for surface mining. The methodology used is material based process analysis that allows calculation of the total emissions for each process involved. A simple model for predicting the energy and material requirements of the power plant is developed. Preliminary calculations reveal that for a typical UK coal fired plant, the life cycle emissions amount to 990 g CO2-e/kWh of electricity generated, which compares well with previous UK studies. The majority of these emissions result from direct fuel combustion (882 g/kWh 89%) with methane leakage from mining operations accounting for 60% of indirect emissions. In total, mining operations (including methane leakage) account for 67.4% of indirect emissions, while limestone and other material production and transport account for 31.5%. The methodology developed is also applied to a typical IGCC power plant. It is found that IGCC life cycle emissions are 15% less than those from PC power plants. Furthermore, upon investigating the influence of power plant parameters on life cycle emissions, it is determined that, while the effect of changing the load factor is negligible, increasing efficiency from 35% to 38% can reduce emissions by 7.6%. The current study is funded by the UK National Environment Research Council (NERC) and is undertaken as part of the UK Carbon Capture and Storage Consortium (UKCCSC). Future work will investigate the life cycle emissions from other power generation technologies with and without carbon capture and storage. The current paper reveals that it might be possible that, when CCS is employed. the emissions during generation decrease to a level where the emissions from upstream processes (i.e. coal production and transport) become dominant, and so, the life cycle efficiency of the CCS system can be significantly reduced. The location of coal, coal composition and mining method are important in determining the overall impacts. In addition to studying the net emissions from CCS systems, future work will also investigate the feasibility and technoeconomics of these systems as a means of carbon abatement.

Synthesis of broadband anti-reflection coatings for spaceflight infrared optics

A synthesis method is outlined for the design of broadband anti-reflection coatings for use in spaceborne infrared optics. The Golden Section optimisation routine is used to make a search, using designated non-absorptive dielectric thin film combinations, for the coating design which fulfils the required spectral requirements using the least number of layers and different materials. Three examples are given of coatings designed by this method : (I) 1µm to 12µm anti-reflection coating on Zinc Sulphide using Zinc Sulphide and Yttrium Fluoride thin film materials. (ii) 2µm to 14µm anti-reflection coating on Germanium using Germanium and Ytterbium Fluoride thin film materials. (iii) 6µm to 17µm anti-reflection coating on Germanium using Lead Telluride, Zinc Selenide and Barium Fluoride. The measured spectral performance of the manufactured 6µm to 17µm coating on Germanium is given. This is the anti-reflection coating for the germanium optics in the NASA Cassini Orbiter CIRS instrument.

Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes

Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

Geotechnical systems that evolve with ecological processes

Geotechnical systems, such as landfills, mine tailings storage facilities (TSFs), slopes, and levees, are required to perform safely throughout their service life, which can span from decades for levees to “in perpetuity” for TSFs. The conventional design practice by geotechnical engineers for these systems utilizes the as-built material properties to predict its performance throughout the required service life. The implicit assumption in this design methodology is that the soil properties are stable through time. This is counter to long-term field observations of these systems, particularly where ecological processes such as plant, animal, biological, and geochemical activity are present. Plant roots can densify soil and/or increase hydraulic conductivity, burrowing animals can increase seepage, biological activity can strengthen soil, geochemical processes can increase stiffness, etc. The engineering soil properties naturally change as a stable ecological system is gradually established following initial construction, and these changes alter system performance. This paper presents an integrated perspective and new approach to this issue, considering ecological, geotechnical, and mining demands and constraints. A series of data sets and case histories are utilized to examine these issues and to propose a more integrated design approach, and consideration is given to future opportunities to manage engineered landscapes as ecological systems. We conclude that soil scientists and restoration ecologists must be engaged in initial project design and geotechnical engineers must be active in long-term management during the facility’s service life. For near-surface geotechnical structures in particular, this requires an interdisciplinary perspective and the embracing of soil as a living ecological system rather than an inert construction material.