Plant viruses

1. Barley Yellow Dwarf Virus: G.D. McLean, T.N. Khan, J. Sandow. 2. Clover Viruses: G.D. McLean, J. Sandow. BYDV: Survey of incidence - Locations: Esperance (80ES53) sown June 27, 1980 Williams (80NA35) sown June 19, 1980 Kojonup (80KA28) sown June 19, 1980 Bokerup (80MA11) sown July 8, 1980 Jerramungup (80JE14) sown June 26, 1980 Albany (80AL30) sown July 3, 1980 Busselton (80BU3) sown July 8, 1980 Bridgetown (80BR19) sown June s, 1980 Northam (80N026) sown June 16, 1980 All these plots were located at the cultivar variety trial sites. Sites varied considerably in BYDV incidence as well as in rate of disease progress. There was evidence of recovery in some plants, and at Narrogin most infected plants recovered. Taking the mean disease score in the last recording; Manjimup, Albany, Bridgetown, Katanning and Narrogin showed decreasing amounts of incidence in that order. The lower rainfall sites (Katanning and Narrogin) had a much lower incidence of BYDV than the higher rainfall sites. Clover Viruses - 80AL29, 80BR15, 80BU2, 80BY6, 80ES52, 80MA10

Barley yellow dwarf virus in barley and oats (79MT20, 79PE13) Experimental summary 1979

(1) Yield assessments have continued similar to those used in 1977 and 1978. Essentially, plants with symptoms typical of BYDV are marked in the early spring as well as a similar number without symptoms. Yield differences were obtained both for Clipper Barley and an oats variety. (2) Two pilot experiments using viruliferous aphids were carried out at Mount Barker (79MT20) and at South Perth · (79PE13). Both Rhopalosiphum padi and R. maidis were used. Infection at Mt Barker failed, and therefore no data is presented. The Perth experiment was planted on August 31, 1979. The original plan was to have two treatments, i.e. Aphid infestation vs. Control in 4 replications. However, as two different species of aphid became available, the experiment was split into two smaller ones, each using a different species of aphid with 2 replications. RESULTS: See Tables 1 and 2

Will jams get worse when slow cars move over?

Motivated by an analogy with traffic, we simulate two species of particles (`vehicles'), moving stochastically in opposite directions on a two-lane ring road. Each species prefers one lane over the other, controlled by a parameter $0 \leq b \leq 1$ such that $b=0$ corresponds to random lane choice and $b=1$ to perfect `laning'. We find that the system displays one large cluster (`jam') whose size increases with $b$, contrary to intuition. Even more remarkably, the lane `charge' (a measure for the number of particles in their preferred lane) exhibits a region of negative response: even though vehicles experience a stronger preference for the `right' lane, more of them find themselves in the `wrong' one! For $b$ very close to 1, a sharp transition restores a homogeneous state. Various characteristics of the system are computed analytically, in good agreement with simulation data.Comment: 7 pages, 3 figures; to appear in Europhysics Letters (2005

Applying psychological type theory to cathedral visitors : a case study of two cathedrals in England and Wales

This study employs Jungian psychological type theory to profile visitors to Chester Cathedral in England and St Davids Cathedral in Wales. Psychological type theory offers a fourfold psychographic segmentation of visitors, distinguishing between introversion and extraversion, sensing and intuition, thinking and feeling, and judging and perceiving. New data provided by 157 visitors to Chester Cathedral (considered alongside previously published data provided by 381 visitors to St Davids Cathedral) demonstrated that these two cathedrals attract more introverts than extraverts, more sensers than intuitives, and more judgers than perceivers, but equal proportions of thinkers and feelers. Comparison with the population norms demonstrated that extraverts and perceivers are significantly under-represented among visitors to these two cathedrals. The implications of these findings are discussed both for maximising the visitor experiences of those already attracted to these cathedrals and for discovering ways of attracting more extraverts and more perceivers to explore these cathedrals

1981 Plant viruses

1, Clover viruses - 81HA6, 81MA9, 81BR14, 81BY12, 81BH5, 81AL38, 81ES39 OBJECTIVES: To determine the extent of the \u27Dinninup virus\u27 problem (sub. clover mottle). To further assess the incidence of red leaf virus to determine the incidence of bean yellow mosaic virus. To note the incidence of sub. clover stunt virus. A. BYDV: Survey of incidence - 81BU1, 81BU2, 81BR11, 81BR12, 81MA6, 81MA7, 81AL31, 81AL32, 81JE14, 81JE15, 81KA21, 81KA22, 81NA28, 81N031, 81ES38, 81E26. 2. Barley yellow dwarf virus. BYDV: Genotype x insecticide studies - 81MN14, 81MT29, 81E28, 81MN14. BYDV: differences amongst barley genotypes - 81C19, 81WH31, 81BA30. BYDV: Resistance and yield in CV.Shannon and CV. Proctor - 871BR13, 81MA8, 81AL36, 81JE17 Yield per plot and 100 seed weight - Albany 81AL36 Infection of BYDV in cereal genotypes at Manjimup ( 81MN13)

Plant viruses.

Clover viruses, 82ES38, 82AL47, 82MA19, 82BR19, 82BY29; 82BU5, 82HA9. Lupin virus, diseases. Barley yellow dwarf virus, 82AL46, 82AL51, 82B10, 82BA33, 82BR16, 82BR18, 82C29, 82E27, 82ES37, 82ES40, 82JE19, 82JE20, 82KA33, 82KA34, 82ABI3, 82MA18, 82MN22, 82MT34, 82NA32, 82WH28,82B8, 82MN17, 82E24, 82MT30, 82E25, 82MN18, 82MT31, 82B9, 82ABI2, 82BA31, 82C26, 82JE17, 82WH27, 82AL45, 82BR17, 82ES39, 82MA1, 82MA117, 82MT33

Exact Solution of Two-Species Ballistic Annihilation with General Pair-Reaction Probability

The reaction process $A+B->C$ is modelled for ballistic reactants on an infinite line with particle velocities $v_A=c$ and $v_B=-c$ and initially segregated conditions, i.e. all A particles to the left and all B particles to the right of the origin. Previous, models of ballistic annihilation have particles that always react on contact, i.e. pair-reaction probability $p=1$. The evolution of such systems are wholly determined by the initial distribution of particles and therefore do not have a stochastic dynamics. However, in this paper the generalisation is made to $p<1$, allowing particles to pass through each other without necessarily reacting. In this way, the A and B particle domains overlap to form a fluctuating, finite-sized reaction zone where the product C is created. Fluctuations are also included in the currents of A and B particles entering the overlap region, thereby inducing a stochastic motion of the reaction zone as a whole. These two types of fluctuations, in the reactions and particle currents, are characterised by the `intrinsic reaction rate', seen in a single system, and the `extrinsic reaction rate', seen in an average over many systems. The intrinsic and extrinsic behaviours are examined and compared to the case of isotropically diffusing reactants.Comment: 22 pages, 2 figures, typos correcte

Finite Dimensional Representations of the Quadratic Algebra: Applications to the Exclusion Process

We study the one dimensional partially asymmetric simple exclusion process (ASEP) with open boundaries, that describes a system of hard-core particles hopping stochastically on a chain coupled to reservoirs at both ends. Derrida, Evans, Hakim and Pasquier [J. Phys. A 26, 1493 (1993)] have shown that the stationary probability distribution of this model can be represented as a trace on a quadratic algebra, closely related to the deformed oscillator-algebra. We construct all finite dimensional irreducible representations of this algebra. This enables us to compute the stationary bulk density as well as all correlation lengths for the ASEP on a set of special curves of the phase diagram.Comment: 18 pages, Latex, 1 EPS figur

Stability of a Nonequilibrium Interface in a Driven Phase Segregating System

We investigate the dynamics of a nonequilibrium interface between coexisting phases in a system described by a Cahn-Hilliard equation with an additional driving term. By means of a matched asymptotic expansion we derive equations for the interface motion. A linear stability analysis of these equations results in a condition for the stability of a flat interface. We find that the stability properties of a flat interface depend on the structure of the driving term in the original equation.Comment: 14 pages Latex, 1 postscript-figur