A Tentative Modeling Study of the Effect of Wall Reactions on Oxidation Phenomena

This paper gives details of a tentative modeling study that investigates the inhibiting effect of internal reactor walls treated with acid..

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Diving deep into digital literacy:emerging methods for research

Literacy studies approaches have tended to adopt a position which enables ethnographic explorations of a wide range of ‘literacies’. An important issue arising is the new challenge required for researchers to capture, manage, and analyse data that highlight the unique character of practices around texts in digital environments. Such inquiries, we argue, require multiple elements of data to be captured and analysed as part of effective literacy ethnographies. These include such things as the unfolding of digital texts, the activities around them, and features of the surrounding social and material environment. This paper addresses these methodological issues drawing from three educationally focused studies, and reporting their experiences and insights within uniquely different contexts. We deal with the issue of adopting new digital methods for literacy research through the notion of a ‘deep dive’ to explore educational tasks in classrooms. Through a discussion of how we approached the capture and analysis of our data, we present methods to better understand digital literacies in education. We then outline challenges posed by our methods, how they can be used more broadly for researching interaction in digital environments, and how they augment transdisciplinary debates and trends in research methods

Increasing vegetable intakes: rationale and systematic review of published interventions

Purpose While the health benefits of a high fruit and vegetable consumption are well known and considerable work has attempted to improve intakes, increasing evidence also recognises a distinction between fruit and vegetables, both in their impacts on health and in consumption patterns. Increasing work suggests health benefits from a high consumption specifically of vegetables, yet intakes remain low, and barriers to increasing intakes are prevalent making intervention difficult. A systematic review was undertaken to identify from the published literature all studies reporting an intervention to increase intakes of vegetables as a distinct food group. Methods Databases—PubMed, PsychInfo and Medline—were searched over all years of records until April 2015 using pre-specified terms. Results Our searches identified 77 studies, detailing 140 interventions, of which 133 (81 %) interventions were conducted in children. Interventions aimed to use or change hedonic factors, such as taste, liking and familiarity (n = 72), use or change environmental factors (n = 39), use or change cognitive factors (n = 19), or a combination of strategies (n = 10). Increased vegetable acceptance, selection and/or consumption were reported to some degree in 116 (83 %) interventions, but the majority of effects seem small and inconsistent. Conclusions Greater percent success is currently found from environmental, educational and multi-component interventions, but publication bias is likely, and long-term effects and cost-effectiveness are rarely considered. A focus on long-term benefits and sustained behaviour change is required. Certain population groups are also noticeably absent from the current list of tried interventions

Recent experience in the fabrication and brazing of ceramic beam tubes for kicker magnets at FNAL

Ceramic beam tubes are utilized in numerous kicker magnets in different accelerator rings at Fermi National Accelerator Laboratory. Kovar flanges are brazed onto each beam tube end, since kovar and high alumina ceramic have similar expansion curves. The tube, kovar flange, end piece, and braze foil (titanium/incusil) alloy brazing material are stacked in the furnace and then brazed in the furnace at 1000 C. The ceramic specified is 99.8% Alumina, Al{sub 2}O{sub 3}, a strong recrystallized high-alumina fabricated by slip casting. Recent experience at Fermilab with the fabrication and brazing of these tubes has brought to light numerous problems including tube breakage and cracking and also the difficulty of brazing the tube to produce a leak-tight joint. These problems may be due to the ceramic quality, voids in the ceramic, thinness of the wall, and micro-cracks in the ends which make it difficult to braze because it cannot fill tiny surface cracks which are caused by grain pullout during the cutting process. Solutions which are being investigated include lapping the ends of the tubes before brazing to eliminate the micro-cracks and also metallization of the tubes

Discrimination of biofilm samples using pattern recognition techniques

Biofilms are complex aggregates formed by microorganisms such as bacteria, fungi and algae, which grow at the interfaces between water and natural or artificial materials. They are actively involved in processes of sorption and desorption of metal ions in water and reflect the environmental conditions in the recent past. Therefore, biofilms can be used as bioindicators of water quality. The goal of this study was to determine whether the biofilms, developed in different aquatic systems, could be successfully discriminated using data on their elemental compositions. Biofilms were grown on natural or polycarbonate materials in flowing water, standing water and seawater bodies. Using an unsupervised technique such as principal component analysis (PCA) and several supervised methods like classification and regression trees (CART), discriminant partial least squares regression (DPLS) and uninformative variable elimination–DPLS (UVE-DPLS), we could confirm the uniqueness of sea biofilms and make a distinction between flowing water and standing water biofilms. The CART, DPLS and UVE-DPLS discriminant models were validated with an independent test set selected either by the Kennard and Stone method or the duplex algorithm. The best model was obtained from CART with 100% correct classification rate for the test set designed by the Kennard and Stone algorithm. With CART, one variable describing the Mg content in the biofilm water phase was found to be important for the discrimination of flowing water and standing water biofilms

Protocol for PIT: a phase III trial of prophylactic irradiation of tracts in patients with malignant pleural mesothelioma following invasive chest wall intervention.

INTRODUCTION: Histological diagnosis of malignant mesothelioma requires an invasive procedure such as CT-guided needle biopsy, thoracoscopy, video-assisted thorascopic surgery (VATs) or thoracotomy. These invasive procedures encourage tumour cell seeding at the intervention site and patients can develop tumour nodules within the chest wall. In an effort to prevent nodules developing, it has been widespread practice across Europe to irradiate intervention sites postprocedure--a practice known as prophylactic irradiation of tracts (PIT). To date there has not been a suitably powered randomised trial to determine whether PIT is effective at reducing the risk of chest wall nodule development. METHODS AND ANALYSIS: In this multicentre phase III randomised controlled superiority trial, 374 patients who can receive radiotherapy within 42 days of a chest wall intervention will be randomised to receive PIT or no PIT. Patients will be randomised on a 1:1 basis. Radiotherapy in the PIT arm will be 21 Gy in three fractions. Subsequent chemotherapy is given at the clinicians' discretion. A reduction in the incidence of chest wall nodules from 15% to 5% in favour of radiotherapy 6 months after randomisation would be clinically significant. All patients will be followed up for up to 2 years with monthly telephone contact and at least four outpatient visits in the first year. ETHICS AND DISSEMINATION: PIT was approved by NRES Committee North West-Greater Manchester West (REC reference 12/NW/0249) and recruitment is currently on-going, the last patient is expected to be randomised by the end of 2015. The analysis of the primary end point, incidence of chest wall nodules 6 months after randomisation, is expected to be published in 2016 in a peer reviewed journal and results will also be presented at scientific meetings and summary results published online. A follow-up analysis is expected to be published in 2018. TRIAL REGISTRATION NUMBER: ISRCTN04240319; NCT01604005; Pre-results