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

An evaluation of early career academic nurses’ perceptions of a support program designed to build career-resilience

Early career academic nurses can struggle to meet the demands of career development due to feelings of being overwhelmed. Studies indicate that programs targeting these challenges are often sporadic and inconsistent, leading to dissatisfaction and missed opportunities. This paper reports on findings evaluating a program designed to build career-resilience in a group of early career academic nurses who, through the provision of a structured program of support, were enabled to succeed and thrive in the academy. This six session program was informed by Knowles’ adult learning theory, Mezirow’s transformational learning theory and Lord’s reliance on critical transactions. This study was undertaken in a large metropolitan university in Sydney, Australia. Participants included nine early career academic nurses. All had been full-time academics from one to six years. A qualitative descriptive design was employed using Braun and Clarke’s six stage process for data analyses. Three themes emerged: the program fostered connections, strengthened expertise and clarified directions. This analysis provided deep insights into the value of collegial relationships to galvanise career success. The program’s strength was its ability to lessen participants’ feelings of isolation and to develop behaviours that enhance career-resilience

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

Clinical simulation in Australia and New Zealand: Through the lens of an advisory group

Across Australia, innovations in simulation to enhance learning in nursing have been occurring for three decades and nursing is, and needs to be, a leading player in simulation knowledge diffusion. However, expertise is unevenly distributed across health services and education providers. Rather than build on the expertise and achievements of others, there is a tendency for resource duplication and for trial and error problem solving, in part related to a failure to communicate achievements for the benefits of the professional collective. For nursing to become a leader in the use of simulation and drive ongoing development, as well as conducting high quality research and evaluation, academics need to collaborate, aggregate best practice in simulation learning, and disseminate that knowledge to educators working in health services and higher education sectors across the whole of Australia and New Zealand. To achieve this strategic intent, capacity development principles and committed action are necessary. In mid 2010 the opportunity to bring together nurse educators with simulation learning expertise within Australia and New Zealand became a reality. The Council of Deans of Nursing and Midwifery (CDNM) Australia and New Zealand decided to establish an expert reference group to reflect on the state of Australian nursing simulation, to pool expertise and to plan ways to share best practice knowledge on simulation more widely. This paper reflects on the achievements of the first 18 months since the group's establishment and considers future directions for the enhancement of simulation learning practice, research and development in Australian nursing

Madang 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

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

Morobe 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

Application and Validation of PFGE for Serovar Identification of Leptospira Clinical Isolates

Serovar identification of clinical isolates of Leptospira is generally not performed on a routine basis, yet the identity of an infecting serovar is valuable from both epidemiologic and public health standpoints. Only a small number of reference laboratories worldwide have the capability to perform the cross agglutinin absorption test (CAAT), the reference method for serovar identification. Pulsed-field gel electrophoresis (PFGE) is an alternative method to CAAT that facilitates rapid identification of leptospires to the serovar level. We employed PFGE to evaluate 175 isolates obtained from humans and animals submitted to the Centers for Disease Control and Prevention (CDC) between 1993 and 2007. PFGE patterns for each isolate were generated using the NotI restriction enzyme and compared to a reference database consisting of more than 200 reference strains. Of the 175 clinical isolates evaluated, 136 (78%) were identified to the serovar level by the database, and an additional 27 isolates (15%) have been identified as probable new serovars. The remaining isolates yet to be identified are either not represented in the database or require further study to determine whether or not they also represent new serovars. PFGE proved to be a useful tool for serovar identification of clinical isolates of known serovars from different geographic regions and a variety of different hosts and for recognizing potential new serovars

Effects of dietary nitrate supplementation on symptoms of acute mountain sickness and basic physiological responses in a group of male adolescents during ascent to Mount Everest Base Camp

The purpose of this study was to investigate the effects of dietary nitrate supplementation, in the form of beetroot juice, on acute mountain sickness (AMS) symptoms and physiological responses, in a group of young males trekking to Mount Everest Base Camp (EBC). Forty healthy male students (mean age (SD): 16 (1) yrs) trekked to EBC over 11 days. Following an overnight fast, each morning participants completed the Lake Louise AMS questionnaire and underwent a series of physiological tests: resting blood pressure as well as resting and exercising heart rate, respiratory rate, and peripheral oxygen saturation. The exercise test consisted of a standardised 2-minute stepping protocol and measurements were taken in the last 10 seconds. Participants in the intervention arm of the study consumed 140 ml of concentrated beetroot juice daily, containing approximately 10 mmoles of nitrate, while those in the control arm consumed 140 ml of concentrated blackcurrant cordial with negligible nitrate content. Drinks were taken for the first seven days at high altitude (days 2 to 8), in two equal doses; one with breakfast, and one with the evening meal. Mixed modelling revealed no significant between-groups difference in the incidence of AMS (Odds Rationitrate vs. control: 1.16 (95% CI: 0.59; 2.29)). Physiological changes occurring during ascent to high altitude generally were not significantly different between the two groups (Model Coef (95% CI) – average difference nitrate vs. control: systolic blood pressure, 0.16 (-4.47; 4.79); peripheral oxygen saturation, 0.28 (-0.85; 1.41); heart rate, -0.48 (-8.47; 7.50) (Model Coef (95% CI) – relative difference nitrate vs. control: ventilatory rate, 0.95 (0.82; 1.08)). Modelling revealed that diastolic blood pressure was 3.37 mmHg (0.24; 6.49) higher for participants in the beetroot juice, however this difference was no larger than that found at baseline and no interaction effect was observed. Supplementation with dietary nitrate did not significantly change symptoms of AMS or alter key physiological variables, in a group of adolescent males during a high altitude trekking expedition. There was no evidence of harm from dietary nitrate supplementation in this context. Given the wide confidence intervals in all models, a larger sample size would be required to exclude a false negative result. Our data suggest that prolonged oral nitrate supplementation is safe and feasible at altitude but has little physiological or clinical effect

Human Leptospirosis Caused by a New, Antigenically Unique Leptospira Associated with a Rattus Species Reservoir in the Peruvian Amazon

As part of a prospective study of leptospirosis and biodiversity of Leptospira in the Peruvian Amazon, a new Leptospira species was isolated from humans with acute febrile illness. Field trapping identified this leptospire in peridomestic rats (Rattus norvegicus, six isolates; R. rattus, two isolates) obtained in urban, peri-urban, and rural areas of the Iquitos region. Novelty of this species was proven by serological typing, 16S ribosomal RNA gene sequencing, pulsed-field gel electrophoresis, and DNA-DNA hybridization analysis. We have named this species “Leptospira licerasiae” serovar Varillal, and have determined that it is phylogenetically related to, but genetically distinct from, other intermediate Leptospira such as L. fainei and L. inadai. The type strain is serovar Varillal strain VAR 010T, which has been deposited into internationally accessible culture collections. By microscopic agglutination test, “Leptospira licerasiae” serovar Varillal was antigenically distinct from all known serogroups of Leptospira except for low level cross-reaction with rabbit anti–L. fainei serovar Hurstbridge at a titer of 1∶100. LipL32, although not detectable by PCR, was detectable in “Leptospira licerasiae” serovar Varillal by both Southern blot hybridization and Western immunoblot, although on immunoblot, the predicted protein was significantly smaller (27 kDa) than that of L. interrogans and L. kirschneri (32 kDa). Isolation was rare from humans (2/45 Leptospira isolates from 881 febrile patients sampled), but high titers of MAT antibodies against “Leptospira licerasiae” serovar Varillal were common (30%) among patients fulfilling serological criteria for acute leptospirosis in the Iquitos region, and uncommon (7%) elsewhere in Peru. This new leptospiral species reflects Amazonian biodiversity and has evolved to become an important cause of leptospirosis in the Peruvian Amazon