International financial reporting standards (IFRS) as a change agent in Ukraine

This paper aims to examine the perception of key actors regarding the costs and benefits that result from adopting International Financial Reporting Standards (IFRS) in Ukraine. Authors showed that IFRS implementation impacts on internal reporting quality, the relationship with customers, creditors and shareholders, the access to international markets and external financing. They also indicated that financial managers have serious concerns about implementation costs related to the introduction of IFRS. These costs relate to training, instruction on IFRS adoption and translation of current IFRS, changes in software systems, double purpose accounting and deadlines for IFRS adoption and consulting services.

Interaction between a cationic surfactant-like peptide and lipid vesicles and its relationship to antimicrobial activity

We investigate the properties of an antimicrobial surfactant-like peptide (Ala)6(Arg), A6R, containing a cationic headgroup. The interaction of this peptide with zwitterionic (DPPC) lipid vesicles is investigated using a range of microscopic, X-ray scattering, spectroscopic, and calorimetric methods. The β-sheet structure adopted by A6R is disrupted in the presence of DPPC. A strong effect on the small-angle X-ray scattering profile is observed: the Bragg peaks from the DPPC bilayers in the vesicle walls are eliminated in the presence of A6R and only bilayer form factor peaks are observed. All of these observations point to the interaction of A6R with DPPC bilayers. These studies provide insight into interactions between a model cationic peptide and vesicles, relevant to understanding the action of antimicrobial peptides on lipid membranes. Notably, peptide A6R exhibits antimicrobial activity without membrane lysis.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ‘prosumer’ agents (i.e., producers and/or consumers of energy) and ‘aggregator’ agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.

Characterization and antimicrobial efficacy against E. coli of a helium/air plasma at atmospheric pressure created in a plastic package

A plasma source, sustained by the application of a floating high voltage (±15 kV) to parallel-plate electrodes at 50 Hz, has been achieved in a helium/air mixture at atmospheric pressure (P = 105 Pa) contained in a zip-locked plastic package placed in the electrode gap. Some of the physical and antimicrobial properties of this apparatus were established with a view to ascertain its performance as a prototype for the disinfection of fresh produce. The current–voltage (I–V) and charge–voltage (Q–V) characteristics of the system were measured as a function of gap distance d, in the range (3 × 103 ≤ Pd ≤ 1.0 × 104 Pa m). The electrical measurements showed this plasma source to exhibit the characteristic behaviour of a dielectric barrier discharge in the filamentary mode and its properties could be accurately interpreted by the two-capacitance in series model. The power consumed by the discharge and the reduced field strength were found to decrease quadratically from 12.0 W to 4.5 W and linearly from 140 Td to 50 Td, respectively, in the range studied. Emission spectra of the discharge were recorded on a relative intensity scale and the dominant spectral features could be assigned to strong vibrational bands in the 2+ and 1− systems of N2 and ${\rm N}_2^+$ , respectively, with other weak signatures from the NO and OH radicals and the N+, He and O atomic species. Absolute spectral intensities were also recorded and interpreted by comparison with the non-equilibrium synthetic spectra generated by the computer code SPECAIR. At an inter-electrode gap of 0.04 m, this comparison yielded typical values for the electron, vibrational and translational (gas) temperatures of (4980 ± 100) K, (2700 ± 200) K and (300 ± 100) K, respectively and an electron density of 1.0 × 1017 m−3. A Boltzmann plot also provided a value of (3200 ± 200 K) for the vibrational temperature. The antimicrobial efficacy was assessed by studying the resistance of both Escherichia coli K12 its isogenic mutants in soxR, soxS, oxyR, rpoS and dnaK selected to identify possible cellular responses and targets related with 5 min exposure to the active gas in proximity of, but not directly in, the path of the discharge filaments. Both the parent strain and mutants populations were significantly reduced by more than 1.5 log cycles in these conditions, showing the potential of the system. Post-treatment storage studies showed that some transcription regulators and specific genes related to oxidative stress play an important role in the E. coli repair mechanism and that plasma exposure affects specific cell regulator systems.

An analysis of UK policies for domestic energy reduction using an agent based tool

This paper introduces a new agent-based model, which incorporates the actions of individual homeowners in a long-term domestic stock model, and details how it was applied in energy policy analysis. The results indicate that current policies are likely to fall significantly short of the 80% target and suggest that current subsidy levels need re-examining. In the model, current subsidy levels appear to offer too much support to some technologies, which in turn leads to the suppression of other technologies that have a greater energy saving potential. The model can be used by policy makers to develop further scenarios to find alternative, more effective, sets of policy measures. The model is currently limited to the owner-occupied stock in England, although it can be expanded, subject to the availability of data.

Prediction of Staphylococcus aureus antimicrobial resistance by whole-genome sequencing

Whole-genome sequencing (WGS) could potentially provide a single platform for extracting all the information required to predict an organism’s phenotype. However, its ability to provide accurate predictions has not yet been demonstrated in large independent studies of specific organisms. In this study, we aimed to develop a genotypic prediction method for antimicrobial susceptibilities. The whole genomes of 501 unrelated Staphylococcus aureus isolates were sequenced, and the assembled genomes were interrogated using BLASTn for a panel of known resistance determinants (chromosomal mutations and genes carried on plasmids). Results were compared with phenotypic susceptibility testing for 12 commonly used antimicrobial agents (penicillin, methicillin, erythromycin, clindamycin, tetracycline, ciprofloxacin, vancomycin, trimethoprim, gentamicin, fusidic acid, rifampin, and mupirocin) performed by the routine clinical laboratory. We investigated discrepancies by repeat susceptibility testing and manual inspection of the sequences and used this information to optimize the resistance determinant panel and BLASTn algorithm. We then tested performance of the optimized tool in an independent validation set of 491 unrelated isolates, with phenotypic results obtained in duplicate by automated broth dilution (BD Phoenix) and disc diffusion. In the validation set, the overall sensitivity and specificity of the genomic prediction method were 0.97 (95% confidence interval [95% CI], 0.95 to 0.98) and 0.99 (95% CI, 0.99 to 1), respectively, compared to standard susceptibility testing methods. The very major error rate was 0.5%, and the major error rate was 0.7%. WGS was as sensitive and specific as routine antimicrobial susceptibility testing methods. WGS is a promising alternative to culture methods for resistance prediction in S. aureus and ultimately other major bacterial pathogens.

Cost function for sub-agent elements in multi-agent energy management system

Distributed generation plays a key role in reducing CO2 emissions and losses in transmission of power. However, due to the nature of renewable resources, distributed generation requires suitable control strategies to assure reliability and optimality for the grid. Multi-agent systems are perfect candidates for providing distributed control of distributed generation stations as well as providing reliability and flexibility for the grid integration. The proposed multi-agent energy management system consists of single-type agents who control one or more gird entities, which are represented as generic sub-agent elements. The agent applies one control algorithm across all elements and uses a cost function to evaluate the suitability of the element as a supplier. The behavior set by the agent's user defines which parameters of an element have greater weight in the cost function, which allows the user to specify the preference on suppliers dynamically. This study shows the ability of the multi-agent energy management system to select suppliers according to the selection behavior given by the user. The optimality of the supplier for the required demand is ensured by the cost function based on the parameters of the element.

Paralog re-emergence: a novel, historically contingent mechanism in the evolution of antimicrobial resistance

Evolution of resistance to drugs and pesticides poses a serious threat to human health and agricultural production. CYP51 encodes the target site of azole fungicides, widely used clinically and in agriculture. Azole resistance can evolve due to point mutations or overexpression of CYP51, and previous studies have shown that fungicide-resistant alleles have arisen by de novo mutation. Paralogs CYP51A and CYP51B are found in filamentous ascomycetes, but CYP51A has been lost from multiple lineages. Here, we show that in the barley pathogen Rhynchosporium commune, re-emergence of CYP51A constitutes a novel mechanism for the evolution of resistance to azoles. Pyrosequencing analysis of historical barley leaf samples from a unique long-term experiment from 1892 to 2008 indicates that the majority of the R. commune population lacked CYP51A until 1985, after which the frequency of CYP51A rapidly increased. Functional analysis demonstrates that CYP51A retains the same substrate as CYP51B, but with different transcriptional regulation. Phylogenetic analyses show that the origin of CYP51A far predates azole use, and newly sequenced Rhynchosporium genomes show CYP51A persisting in the R. commune lineage rather than being regained by horizontal gene transfer; therefore, CYP51A re-emergence provides an example of adaptation to novel compounds by selection from standing genetic variation.

Biology as an agent of chemical and mineralogical change in soil

Earthworms have a significant impact on the functioning of soils and the processes that occur within them. Here we review our work on the impact of earthworms on soil mineralogy and chemistry, in particular focusing on the contribution of earthworms to mineral weathering and calcium carbonate in soils and the impact that earthworms have on metal mobility at contaminated sites.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.

nor-Mevaldic acid surrogates as selective antifungal agent leads against Botrytis cinerea. Enantioselective preparation of 4-hydroxy-6-(1-phenylethoxy)tetrahydro-2H-pyran-2-one

Solvent-free desymmetrisation of meso-dialdehyde 1 with chiral 1-phenylethan-1-ol, led to preparation of 4-silyloxy-6-alkyloxytetrahydro-2H-pyran-2-one (+)-3a with a 96:4 d.r. Deprotected lactone (+)-19a and the related racemic lactones 16a-18a present a lactone moiety resembling the natural substrate of HMG-CoA reductase and their antifungal properties have been evaluated against the phytopathogenic fungi Botrytis cinerea and Colletotrichum gloeosporioides. These compounds were selectively active against B. cinerea, while inactive against C. gloeosporioides.

Heat treatment enhances the antimicrobial activity of (+)-Catechin when combined with copper sulphate

The aim of the study was to compare the antimicrobial activities of freshly-made, heat-treated (HT), and 14 d stored (+)-Catechin solutions with (+)-catechin flavanol isomers in the presence of copper sulphate. (+)-Catechin activity was investigated when combined with different ratios of Cu2+; 100°C heat treatment; autoclaving; and 14 d storage against Staphylococcus aureus. Cu2+-(+)-Catechin complexation, isomer structure-activity relationships, and H2O2 generation were also investigated. Freshly-made, HT, and 14d stored flavanols showed no activity. Whilst combined Cu2+-autoclaved (+)-Catechin and -HT(+)-Catechin activities were similar, HT(+)-Catechin was more active than either freshly-made (+)-catechin (generating more H2O2) or (-)-Epicatechin (though it generated less H2O2) or 14d-(+)-Catechin (which had similar activity to Cu2+ controls - though it generated more H2O2). When combined with Cu2+, in terms of rates of activity, HT(+)-Catechin was lower than (-)-Epigallocatechin gallate and greater than freshly-made (+)-Catechin. Freshly-made and HT(+)-Catechin formed acidic complexes with Cu2+ as indicated by pH and UV-vis measurements although pH changes did not account for antimicrobial activity. Freshly-made and HT(+)-Catechin both formed Cu2+ complexes. The HT(+)-Catechin complex generated more H2O2 which could explain its higher antimicrobial activity.

Factors affecting dairy farmers' attitudes towards antimicrobial medicine usage in cattle in England and Wales

There has been growing concern about bacterial resistance to antimicrobials in the farmed livestock sector. Attention has turned to sub-optimal use of antimicrobials as a driver of resistance. Recent reviews have identified a lack of data on the pattern of antimicrobial use as an impediment to the design of measures to tackle this growing problem. This paper reports on a study that explored use of antibiotics by dairy farmers and factors influencing their decision-making around this usage. We found that respondents had either recently reduced their use of antibiotics, or planned to do so. Advice from their veterinarian was instrumental in this. Over 70% thought reducing antibiotic usage would be a good thing to do. The most influential source of information used was their own veterinarian. Some 50% were unaware of the available guidelines on use in cattle production. However, 97% thought it important to keep treatment records. The Theory of Planned Behaviour was used to identify dairy farmers’ drivers and barriers to reduce use of antibiotics. Intention to reduce usage was weakly correlated with current and past practice of antibiotic use, whilst the strongest driver was respondents’ belief that their social and advisory network would approve of them doing this. The higher the proportion of income from milk production and the greater the chance of remaining in milk production, the significantly higher the likelihood of farmers exhibiting positive intention to reduce antibiotic usage. Such farmers may be more commercially minded than others and thus more cost-conscious or, perhaps, more aware of possible future restrictions. Strong correlation was found between farmers’ perception of their social referents’ beliefs and farmers’ intent to reduce antibiotic use. Policy makers should target these social referents, especially veterinarians, with information on the benefits from, and the means to, achieving reductions in antibiotic usage. Information on sub-optimal use of antibiotics as a driver of resistance in dairy herds and in humans along with advice on best farm practice to minimise risk of disease and ensure animal welfare, complemented with data on potential cost savings from reduced antibiotic use would help improve poor practice.