Neutron inelastic scattering investigation of the magnetic excitations in Cu_2Te_2O_5X_2 (X=Br, Cl)

Neutron inelastic scattering investigations have been performed on the spin tetrahedral system Cu_2Te_2O_5X_2 (X = Cl, Br). We report the observation of magnetic excitations with a dispersive component in both compounds, associated with the 3D incommensurate magnetic order that develops below $T^{Cl}_{N}$=18.2 K and $T^{Br}_{N}$=11.4 K. The excitation in Cu_2Te_2O_5Cl_2 softens as the temperature approaches $T^{Cl}_{N}$, leaving diffuse quasi-elastic scattering above the transition temperature. In the bromide, the excitations are present well above $T^{Br}_{N}$, which might be attributed to the presence of a degree of low dimensional correlations above $T^{Br}_{N}$ in this compound

Academic literacy diagnostic assessment in the first semester of first year at university

One vital aspect of the first semester of the first year at university is how academic literacy expectations are made explicit though teaching and assessment practices at the disciplinary level. This paper describes how an academic literacy diagnostic process, and the MASUS tool, was used to ascertain the academic literacy profile of a cohort of undergraduate nursing students [N=569] at the beginning and end of their first semester. Key findings of this quantitative descriptive case study were that only just over half of commencing students possessed appropriate academic literacy skills in all four aspects of the diagnostic and nearly 20% scored in the lowest band—suggesting difficulty with multiple aspects of academic literacy. By the end of semester, 77% of the students who had scored in the lowest band of the MASUS at the beginning of the semester had improved their scores to the middle or highest band, and 73% of them eventually attained a pass or higher grade for the course. The findings of this study suggest that large-scale academic literacy diagnostic assessment, when embedded and contextualized within a course of study, is an effective means of providing the early feedback and targeted support that many commencing university students need

Truncation in the tcdC region of the Clostridium difficile PathLoc of clinical isolates does not predict increased biological activity of Toxin B or Toxin A

<p>Abstract</p> <p>Background</p> <p>The increased severity of disease associated with the NAP1 strain of <it>Clostridium difficile </it>has been attributed to mutations to the <it>tcdC </it>gene which codes for a negative regulator of toxin production. To assess the role of hyper-production of Toxins A and B in clinical isolates of <it>Clostridium difficile</it>, two NAP1-related and five NAP1 non-related strains were compared.</p> <p>Methods</p> <p>Sequencing was performed on <it>tcdC</it>, <it>tcdR</it>, and <it>tcdE</it> to determine if there were differences that might account for hyper-production of Toxin A and Toxin B in NAP1-related strains. Biological activity of Toxin B was evaluated using the HFF cell CPE assay and Toxin A biological activity was assessed using the Caco-2 Trans-membrane resistance assay.</p> <p>Results</p> <p>Our results confirm that Toxin A and Toxin B production in NAP1-related strains and ATCC 43255 occurs earlier in the exponential growth phase compared to most NAP1-nonrelated clinical isolates. Despite the hyper-production observed in ATCC 43255 it had no mutations in <it>tcdC</it>, <it>tcdR </it>or <it>tcdE</it>. Analysis of the other clinical isolates indicated that the kinetics and ultimate final concentration of Toxin A and B did not correlate with the presence or lack of alterations in <it>tcdC</it>, <it>tcdR </it>or <it>tcdE</it>.</p> <p>Conclusion</p> <p>Our data do not support a direct role for alterations in the <it>tcdC </it>gene as a predictor of hyperproduction of Toxin A and B in NAP1-related strains.</p

First year students’ perceptions of academic literacies preparedness and embedded diagnostic assessment

This paper reports findings from the second stage of a mixed-methods study of embedded academic literacies and diagnostic assessment—specifically first-year nursing students’ perceptions of the MASUS procedure. We found overwhelming support from participants (85%) in favour of embedded diagnostic assessment. The main reasons for this were receiving constructive, individualised feedback and insights into expectations and requirements. This was important as over a quarter of participants said they had “no idea” about the academic literacy requirements of university when they commenced their program and 60% had not formally studied for at least seven years. Those without recent study experience or with prior poor academic performance expressed high levels of anxiety about academic literacy requirements and lacked confidence in their writing abilities. These findings indicate how stressful the process of mastering academic literacies is for many first-year students’ and highlight the potential benefits of embedding for retention and engagement.</jats:p

West New Britain Province: Text summaries, maps, code lists and village identification

The major purpose of the Papua New Guinea Agricultural Systems Project is to produce information on small holder (subsistence) agriculture at provincial and national levels (Allen et al 1995). Information was collected by field observation, interviews with villagers and reference to published and unpublished documents. Methods are described by Bourke et al. (1993). This Working Paper contains a written summary of the information on the Agricultural Systems in this Province, maps of the location of agriculture systems, a complete listing of all information in the database in coded form, and lists of villages with National Population Census codes, indexed by agricultural systems. This information is available as a map-linked database (GIS) suitable for use on a personal computer in ESRI and MapInfo formats. An Agricultural System is identified when a set of similar agricultural crops and practices occur within a defined area. Six criteria are used to distinguish one system from another: 1. Fallow type (the vegetation which is cleared from a garden site before cultivation). 2. Fallow period (the length of time a garden site is left unused between cultivations). 3. Cultivation intensity (the number of consecutive crops planted before fallow). 4. The staple, or most important, crops. 5. Garden and crop segregation (the extent to which crops are planted in separate gardens; in separate areas within a garden; or are planted sequentially). 6. Soil fertility maintenance techniques (other than natural regrowth fallows). Where one or more of these factors differs significantly and the differences can be mapped, then a separate system is distinguished. Where variation occurs, but is not able to be mapped at 1:500 000 scale because the areas in which the variation occurs are too small or are widely dispersed within the larger system, a subsystem is identified. Subsystems within an Agricultural System are allocated a separate record in the database, identified by the Agricultural System number and a subsystem number. Sago is a widespread staple food in lowland Papua New Guinea. Sago is produced from palms which are not grown in gardens. Most of the criteria above cannot be applied. In this case, systems are differentiated on the basis of the staple crops only. The Papua New Guinea Resource Information System (PNGRIS) is a GIS which contains information on the natural resources of PNG (Bellamy 1986). PNGRIS contains no information on agricultural practices, other than an assessment of land use intensity based on air photograph interpretation by Saunders (1993. The Agricultural Systems Project is designed to provide detailed information on agricultural practices and cropping patterns as part of an upgraded PNGRIS geographical information system. For this reason the Agricultural Systems database contains almost no information on the environmental settings of the systems, except for altitude and slope. The layout of the text descriptions, the database code files and the village lists are similar to PNGRIS formats (Cuddy 1987). The mapping of Agricultural Systems has been carried out on the same map base and scale as PNGRIS (Tactical Pilotage Charts, 1:500 000). Agricultural Systems were mapped within the areas of agricultural land use established by Saunders (1993) from aerial photography. Except where specifically noted, Agricultural Systems boundaries have been mapped without reference to PNGRIS Resource Mapping Unit (RMU) boundaries. Agricultural Systems are defined at the level of the Province (following PNGRIS) but their wider distribution is recognised in the database by cross-referencing systems which cross provincial borders. A preliminary view of the relationships between PNGRIS RMUs and the Agricultural Systems in this Province can be obtained from the listing of villages by Agricultural System, where RMU numbers are appended. Allen, B. J., R. M. Bourke and R. L. Hide 1995. The sustainability of Papua New Guinea agricultural systems: the conceptual background. Global Environmental Change 5(4): 297-312. Bourke, R. M., R. L. Hide, B. J. Allen, R. Grau, G. S. Humphreys and H. C. Brookfield 1993. Mapping agricultural systems in Papua New Guinea. Population Family Health and Development. T. Taufa and C. Bass. University of Papua New Guinea Press, Port Moresby: 205-224. Bellamy, J. A. and J. R. McAlpine 1995. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use Handbook. Commonwealth Scientific and Industrial Research Organisation for the Australian Agency for International Development. PNGRIS Publication No. 6, Canberra. Cuddy, S. M. 1987. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use: Code Files Part 1 Natural Resources. Division of Water and Land Resources, Commonwealth Scientific and Industrial Research Organisation and Land Utilization Section, Department of Primary Industry, Papua New Guinea, Canberra

Southern Highlands Province: Text summaries, maps, code lists and village identification

The major purpose of the Papua New Guinea Agricultural Systems Project is to produce information on small holder (subsistence) agriculture at provincial and national levels (Allen et al 1995). Information was collected by field observation, interviews with villagers and reference to published and unpublished documents. Methods are described by Bourke et al. (1993). This Working Paper contains a written summary of the information on the Agricultural Systems in this Province, maps of the location of agriculture systems, a complete listing of all information in the database in coded form, and lists of villages with National Population Census codes, indexed by agricultural systems. This information is available as a map-linked database (GIS) suitable for use on a personal computer in ESRI and MapInfo formats. An Agricultural System is identified when a set of similar agricultural crops and practices occur within a defined area. Six criteria are used to distinguish one system from another: 1. Fallow type (the vegetation which is cleared from a garden site before cultivation). 2. Fallow period (the length of time a garden site is left unused between cultivations). 3. Cultivation intensity (the number of consecutive crops planted before fallow). 4. The staple, or most important, crops. 5. Garden and crop segregation (the extent to which crops are planted in separate gardens; in separate areas within a garden; or are planted sequentially). 6. Soil fertility maintenance techniques (other than natural regrowth fallows). Where one or more of these factors differs significantly and the differences can be mapped, then a separate system is distinguished. Where variation occurs, but is not able to be mapped at 1:500 000 scale because the areas in which the variation occurs are too small or are widely dispersed within the larger system, a subsystem is identified. Subsystems within an Agricultural System are allocated a separate record in the database, identified by the Agricultural System number and a subsystem number. Sago is a widespread staple food in lowland Papua New Guinea. Sago is produced from palms which are not grown in gardens. Most of the criteria above cannot be applied. In this case, systems are differentiated on the basis of the staple crops only. The Papua New Guinea Resource Information System (PNGRIS) is a GIS which contains information on the natural resources of PNG (Bellamy 1986). PNGRIS contains no information on agricultural practices, other than an assessment of land use intensity based on air photograph interpretation by Saunders (1993. The Agricultural Systems Project is designed to provide detailed information on agricultural practices and cropping patterns as part of an upgraded PNGRIS geographical information system. For this reason the Agricultural Systems database contains almost no information on the environmental settings of the systems, except for altitude and slope. The layout of the text descriptions, the database code files and the village lists are similar to PNGRIS formats (Cuddy 1987). The mapping of Agricultural Systems has been carried out on the same map base and scale as PNGRIS (Tactical Pilotage Charts, 1:500 000). Agricultural Systems were mapped within the areas of agricultural land use established by Saunders (1993) from aerial photography. Except where specifically noted, Agricultural Systems boundaries have been mapped without reference to PNGRIS Resource Mapping Unit (RMU) boundaries. Agricultural Systems are defined at the level of the Province (following PNGRIS) but their wider distribution is recognised in the database by cross-referencing systems which cross provincial borders. A preliminary view of the relationships between PNGRIS RMUs and the Agricultural Systems in this Province can be obtained from the listing of villages by Agricultural System, where RMU numbers are appended. Allen, B. J., R. M. Bourke and R. L. Hide 1995. The sustainability of Papua New Guinea agricultural systems: the conceptual background. Global Environmental Change 5(4): 297-312. Bourke, R. M., R. L. Hide, B. J. Allen, R. Grau, G. S. Humphreys and H. C. Brookfield 1993. Mapping agricultural systems in Papua New Guinea. Population Family Health and Development. T. Taufa and C. Bass. University of Papua New Guinea Press, Port Moresby: 205-224. Bellamy, J. A. and J. R. McAlpine 1995. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use Handbook. Commonwealth Scientific and Industrial Research Organisation for the Australian Agency for International Development. PNGRIS Publication No. 6, Canberra. Cuddy, S. M. 1987. Papua New Guinea Inventory of Natural Resources, Population Distribution and Land Use: Code Files Part 1 Natural Resources. Division of Water and Land Resources, Commonwealth Scientific and Industrial Research Organisation and Land Utilization Section, Department of Primary Industry, Papua New Guinea, Canberra

Generic First Order Orientation Transition of Vortex Lattices in Type II Superconductors

First order transition of vortex lattices (VL) observed in various superconductors with four-fold symmetry is explained microscopically by quasi-classical Eilenberger theory combined with nonlocal London theory. This transition is intrinsic in the generic successive VL phase transition due to either gap or Fermi velocity anisotropies. This is also suggested by the electronic states around vortices. Ultimate origin of this phenomenon is attributed to some what hidden frustrations of a spontaneous symmetry broken hexagonal VL on the underlying four-fold crystalline symmetry.Comment: 4 pages, 5 figures, some typos are correcte

Management practices as risk factors for the presence of bulk milk antibodies to Salmonella, Neospora caninum and Leptospira interrogans serovar hardjo in Irish dairy herds

peer-reviewedA survey of management practices in 309 Irish dairy herds was used to identify risk factors for the presence of antibodies to Salmonella, Neospora caninum and Leptospira interrogans serovar hardjo in extensively managed unvaccinated dairy herds. A previous study documented a herd-level seroprevalence in bulk milk of 49%, 19% and 86% for Salmonella, Neospora caninum and leptospira interrogans serovar hardjo, respectively in the unvaccinated proportion of these 309 herds in 2009. Association analyses in the present study were carried out using multiple logistic regression models. Herds where cattle were purchased or introduced had a greater likelihood of being positive to leptospira interrogans serovar hardjo (P<0.01) and Salmonella (P<0.01). Larger herds had a greater likelihood of recording a positive bulk milk antibody result to leptospira interrogans serovar hardjo (P<0.05). Herds that practiced year round calving were more likely to be positive to Neospora caninum (P<0.05) compared to herds with a spring-calving season, with no difference in risk between herds that practiced split calving compared to herds that practiced spring calving. No association was found between presence of dogs on farms and prevalence of Neospora caninum possibly due to limited access of dogs to infected materials including afterbirths. The information from this study will assist in the design of suitable control programmes for the diseases under investigation in pasture-based livestock systems