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

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 Information was collected by field observation, interviews with villagers and reference to published and unpublished documents.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

A Computational Approach for Designing Tiger Corridors in India

Wildlife corridors are components of landscapes, which facilitate the movement of organisms and processes between intact habitat areas, and thus provide connectivity between the habitats within the landscapes. Corridors are thus regions within a given landscape that connect fragmented habitat patches within the landscape. The major concern of designing corridors as a conservation strategy is primarily to counter, and to the extent possible, mitigate the effects of habitat fragmentation and loss on the biodiversity of the landscape, as well as support continuance of land use for essential local and global economic activities in the region of reference. In this paper, we use game theory, graph theory, membership functions and chain code algorithm to model and design a set of wildlife corridors with tiger (Panthera tigris tigris) as the focal species. We identify the parameters which would affect the tiger population in a landscape complex and using the presence of these identified parameters construct a graph using the habitat patches supporting tiger presence in the landscape complex as vertices and the possible paths between them as edges. The passage of tigers through the possible paths have been modelled as an Assurance game, with tigers as an individual player. The game is played recursively as the tiger passes through each grid considered for the model. The iteration causes the tiger to choose the most suitable path signifying the emergence of adaptability. As a formal explanation of the game, we model this interaction of tiger with the parameters as deterministic finite automata, whose transition function is obtained by the game payoff.Comment: 12 pages, 5 figures, 6 tables, NGCT conference 201

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

Leptospirosis-associated Severe Pulmonary Hemorrhagic Syndrome, Salvador, Brazil

We report the emergence of leptospirosis-associated severe pulmonary hemorrhagic syndrome (SPHS) in slum communities in Salvador, Brazil. Although active surveillance did not identify SPHS before 2003, 47 cases were identified from 2003 through 2005; the case-fatality rate was 74%. By 2005, SPHS caused 55% of the deaths due to leptospirosis

A commensal symbiotic interrelationship for the growth of Symbiobacterium toebii with its partner bacterium, Geobacillus toebii

<p>Abstract</p> <p>Background</p> <p><it>Symbiobacterium toebii </it>is a commensal symbiotic thermophile that absolutely requires its partner bacterium <it>Geobacillus toebii </it>for growth. Despite development of an independent cultivation method using cell-free extracts, the growth of <it>Symbiobacterium </it>remains unknown due to our poor understanding of the symbiotic relationship with its partner bacterium. Here, we investigated the interrelationship between these two bacteria for growth of <it>S. toebii </it>using different cell-free extracts of <it>G. toebii</it>.</p> <p>Results</p> <p><it>Symbiobacterium toebii </it>growth-supporting factors were constitutively produced through almost all growth phases and under different oxygen tensions in <it>G. toebii</it>, indicating that the factor may be essential components for growth of <it>G. toebii </it>as well as <it>S. toebii</it>. The growing conditions of <it>G. toebii </it>under different oxygen tension dramatically affected to the initial growth of <it>S. toebii </it>and the retarded lag phase was completely shortened by reducing agent, L-cysteine indicating an evidence of commensal interaction of microaerobic and anaerobic bacterium <it>S. toebii </it>with a facultative aerobic bacterium <it>G. toebii</it>. In addition, the growth curve of <it>S. toebii </it>showed a dependency on the protein concentration of cell-free extracts of <it>G. toebii</it>, demonstrating that the <it>G. toebii</it>-derived factors have nutrient-like characters but not quorum-sensing characters.</p> <p>Conclusions</p> <p>Not only the consistent existence of the factor in <it>G. toebii </it>during all growth stages and under different oxygen tensions but also the concentration dependency of the factor for proliferation and optimal growth of <it>S. toebii</it>, suggests that an important biosynthetic machinery lacks in <it>S. toebii </it>during evolution. The commensal symbiotic bacterium, <it>S. toebii </it>uptakes certain ubiquitous and essential compound for its growth from environment or neighboring bacteria that shares the equivalent compounds. Moreover, <it>G. toebii </it>grown under aerobic condition shortened the lag phase of <it>S. toebii </it>under anaerobic and microaerobic conditions, suggests a possible commensal interaction that <it>G. toebii </it>scavengers ROS/RNS species and helps the initial growth of <it>S. toebii</it>.</p