Investigating structural features which control the dissolution of bioactive phosphate glasses: Beyond the network connectivity

We have used classical molecular dynamics simulations to characterise the structure of three compositions of silver-containing phosphate glasses with 45 mol% P2O5, 30 mol% CaO, and varying amounts of Na2O and Ag2O. These compositions all have the same network connectivity, allowing us to highlight two other structural features which will affect the glass dissolution. Firstly, the number of different phosphate chains bonded to each modifier atom was computed and it was observed that silver and sodium bind to roughly the same number of phosphate chains, despite the differences in their local environments. Secondly, the clustering of modifier cations was characterised and shown to be enhanced at low concentrations of sodium and silver, but not to exist for calcium

Ab initio molecular dynamics simulations of structural changes associated with the incorporation of fluorine in bioactive phosphate glasses

Phosphate-based bioactive glasses containing fluoride ions offer the potential of a biomaterial which combines the bioactive properties of the phosphate glass and the protection from dental caries by fluoride. We conduct accurate first-principles molecular dynamics simulations of two compositions of fluorinated phosphate-based glass to assess its suitability as a biomaterial. There is a substantial amount of F–P bonding and as a result the glass network will be structurally homogeneous on medium-range length scales, without the inhomogeneities which reduce the bioactivity of other fluorinated bioactive glasses. We observe a decrease in the network connectivity with increasing F content, caused by the replacement of bridging oxygen atoms by non-bridging fluorine atoms, but this decrease is small and can be opposed by an increase in the phosphate content. We conclude that the structural changes caused by the incorporation of fluoride into phosphate-based glasses will not adversely affect their bioactivity, suggesting that fluorinated phosphate glasses offer a superior alternative to their silicate-based counterparts

Effect of Megasphaera elsdenii NCIMB 41125 drenching on health and performance of steers fed high and low roughage diets in the feedlot

Lactate utilising bacteria (LUB) assist in reducing the risk of ruminal lactate acidosis when high concentrate diets are fed to feedlot cattle. Ruminal lactate acidosis can lead to lower animal performance and morbidity. Preliminary studies suggested that the strain, Megasphaera elsdenii (M.e.) NCIMB 41125, is a particularly potent LUB. The potential of M.e.NCIMB 41125 to improve the health and performance of feedlot cattle was investigated. Four hundred and forty eight Bonsmara steers (ca. 240 kg) were used in a 100-day feeding trial. Half the steers received at processing 200 mL M.e.NCIMB 41125 per os (LY) and the other half no LUB (LN). The diets in each of these treatments were divided into a low roughage (2%) (RL) and high roughage (8%) (RH) diet. The effects of LY vs. LN, RL vs. RH as main effects and their respective interactions (LYRL, LYRH, LNRL & LNRH) were compared in terms of morbidity, feedlot performance and carcass characteristics. The steers were weighed at two week intervals, feed was offered daily and the orts were removed weekly from each pen. The faecal consistency score and incidence of morbidity were recorded. At slaughter, carcass data were collected and the health status of the liver and rumen epithelium was assessed. Steers dosed with M.e.NCIMB 41125 had a 5.6% better average daily gain (ADG) during weeks 3 - 5 (2.09 kg/day vs. 1.98 kg/day for LY and LN, respectively). Feed conversion ratio (FCR, Weeks 1 - 13) was better for the steers fed the RL than the RH treatment (4.72 kg/kg vs. 4.99 kg/kg for RL and RH, respectively). Steers on the LNRH treatment during weeks 3 - 5 used more feed per kg gain than steers on the other treatments (5.39 kg/kg for LNRH vs. 4.74 kg/kg and 4.72 kg/kg for LYRL and LNRL, respectively). More steers (21) on the LNRL treatment were treated for morbidity than on the other treatments (8, 7 and 5 for LYRL, LYRH and LNRH, respectively). In general, animal performance was not improved by dosing with M.e.NCIMB 41125, but since ADG was improved in the immediate postadaptation phase (weeks 3 - 5) and morbidity levels were lower on the low roughage diet, dosing of steers on low roughage, lactate acidosis-prone, diets with M.e.NCIMB 41125 should prove useful.Keywords: Beef cattle, lactic acid utilising bacteria, acidosis, morbidit

Advancing subsurface biosphere and paleoclimate research: ECORD–ICDP–DCO–J-DESC–MagellanPlus Workshop Series Program Report

The proper pre-drilling preparation, on-site acquisition and post-drilling preservation of high-qualitysubsurface samples are crucial to ensure significant progress in the scientifically and societally important areasof subsurface biosphere and paleoclimate research. Two of the four research themes of IODP and ICDPand one of the four research areas of the Deep Carbon Observatory (DCO) focus on the subsurface biosphere.Increasing understanding of paleoclimate is a central goal of IODP and incorporated within the scope of theIMPRESS program, the successor of the IMAGES program. Therefore, the goal of our IODP–ICDP–DCO–JDESC–MagellanPlus-sponsored workshop was to help advance deep biosphere and paleoclimate research byidentifying needed improvements in scientific drilling planning and available technology, sample collection andinitial analysis, and long-term storage of subsurface samples and data. Success in these areas will (a) avoidbiological and other contamination during drilling, sampling, storage and shipboard/shore-based experiments;(b) build a repository and database of high-quality subsurface samples for microbiological and paleoclimate researchavailable for the scientific community world-wide over the next decades; and (c) standardize, as much aspossible, microbiological and paleoclimate drilling, sampling and storage workflows to allow results and datato be comparable across both space and time. A result of this workshop is the development and suggested implementationof new advanced methods and technologies to collect high-quality samples and data for the deepbiosphere and paleoclimate scientific communities to optimize expected substantial progress in these fields. Themembers of this workshop will enhance communication within the scientific drilling community by crafting ahandbook focused on pre-drilling, drilling and post-drilling operations

Perceptions of Gauteng Beef Farmers on Significance of Practising Climate Smart Agriculture

Farmers are crucial role-players in agriculture, especially in beef farming. Daily farm activities affect climate change, either negatively or positively. Therefore, farmers’ ability to relate climate change with farm activities is highly imperative. A study was conducted to investigate perceptions of Gauteng beef farmers on significance of practising climate smart agriculture (CSA). Semi-structured key informant interviews were conducted with 57 beef cattle farmers from three areas (Bronkhorstspruit, Rust de Winter and Cullinan) of Tshwane region (Gauteng province). A fully detailed ethical statement was used to explain the study and request farmers’ participation. Data analysis was done using a Statistical Package for Social Sciences (SPSS) software version 20 with a significance of P \u3c 0.05. Majority (71%) of farmers who participated were males. Most (43%) of participated farmers were middle age, which indicates that farmers are now considering beef farming as a full-time job. Majority (60%) of participants had access to enough land (\u3e 700 hectares), which makes them suitable for practising CSA, provided they get appropriate training. Few participants showed good understanding of climate change (14%), global warming (14%), climate change reduction strategies (29%), cattle contribution to climate change (14%), adaptation strategies for climate change (29%) and the role played by CSA on reduction of farm operational costs (14%). Majority of farmers had average understanding of climate change (86%), global warming (86%), cattle contribution on global warming (71%), climate change adaptation strategies (71%), climate change reduction strategies (71%), recommendation of climate smart feed resource (71%) and impact of CSA on economic development (86%). Majority (71%) of participants identified water pollution as the only environmental hazard associated with beef farming, whereas few (29%) identified air pollution due to greenhouse gases emissions from poorly managed cattle manure. All participants (100%) showed good understanding regarding the benefits of practising CSA and its impact on food security. Furthermore, they were willing to adopt CSA and promote it to fellow farmers. There is a need for farmers’ training on CSA

The Quantum Affine Origin of the AdS/CFT Secret Symmetry

We find a new quantum affine symmetry of the S-matrix of the one-dimensional Hubbard chain. We show that this symmetry originates from the quantum affine superalgebra U_q(gl(2|2)), and in the rational limit exactly reproduces the secret symmetry of the AdS/CFT worldsheet S-matrix.Comment: 22 page

Simulation of cloud data security processes and performance

In the world of cloud computing, millions of people are using cloud computing for the purpose of business, education and socialization. Examples of cloud applications are: Google Drive for storage, Facebook for social networks, etc. Cloud users use the cloud computing infrastructure thinking that these services are easy and safe to use. However, there are security and performance issues to be addressed. This paper discusses how cloud users and cloud providers address performance and security issues. In this research, we have used business process modelling and simulation to explore the performance characteristics and security concerns in the service development life cycle. The results show that Business Process Modelling Notations (BPMN) simulation is effective for the study of cloud security process in detail before actual implementation. The total simulation duration time was 51 days and 9 hours 40 minutes but the results are displayed in 7 seconds only

Novel Mechanism of Supersolid of Ultracold Polar Molecules in Optical Lattices

We study the checkerboard supersolid of the hard-core Bose-Hubbard model with the dipole-dipole interaction. This supersolid is different from all other supersolids found in lattice models in the sense that superflow paths through which interstitials or vacancies can hop freely are absent in the crystal. By focusing on repulsive interactions between interstitials, we reveal that the long-range tail of the dipole-dipole interaction have the role of increasing the energy cost of domain wall formations. This effect produces the supersolid by the second-order hopping process of defects. We also perform exact quantum Monte Carlo simulations and observe a novel double peak structure in the momentum distribution of bosons, which is a clear evidence for supersolid. This can be measured by the time-of-flight experiment in optical lattice systems

Absence of a Finite-Temperature Melting Transition in the Classical Two-Dimensional One-Component Plasma

Vortices in thin-film superconductors are often modelled as a system of particles interacting via a repulsive logarithmic potential. Arguments are presented to show that the hypothetical (Abrikosov) crystalline state for such particles is unstable at any finite temperature against proliferation of screened disclinations. The correlation length of crystalline order is predicted to grow as $\sqrt{1/T}$ as the temperature $T$ is reduced to zero, in excellent agreement with our simulations of this two-dimensional system.Comment: 3 figure

Tensor Regression with Applications in Neuroimaging Data Analysis

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients. Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors). Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure. In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates. Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction. A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied. Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data.Comment: 27 pages, 4 figure