Inverse meta-modelling to estimate soil available water capacity at high spatial resolution across a farm

Geo-referenced information on crop production that is both spatially- and temporally-dense would be useful for management in precision agriculture (PA). Crop yield monitors provide spatially but not temporally dense information. Crop growth simulation modelling can provide temporal density, but traditionally fail on the spatial issue. The research described was motivated by the challenge of satisfying both the spatial and temporal data needs of PA. The methods presented depart from current crop modelling within PA by introducing meta-modelling in combination with inverse modelling to estimate site-specific soil properties. The soil properties are used to predict spatially- and temporally-dense crop yields. An inverse meta-model was derived from the agricultural production simulator (APSIM) using neural networks to estimate soil available water capacity (AWC) from available yield data. Maps of AWC with a resolution of 10 m were produced across a dryland grain farm in Australia. For certain years and fields, the estimates were useful for yield prediction with APSIM and multiple regression, whereas for others the results were disappointing. The estimates contain ‘implicit information’ about climate interactions with soil, crop and landscape that needs to be identified. Improvement of the meta-model with more AWC scenarios, more years of yield data, inclusion of additional variables and accounting for uncertainty are discussed. We concluded that it is worthwhile to pursue this approach as an efficient way of extracting soil physical information that exists within crop yield maps to create spatially- and temporally-dense dataset

Cysteine proteinase C1A paralog profiles correspond with phylogenetic lineages of pathogenic piroplasmids

Piroplasmid parasites comprising of Babesia, Theileria, and Cytauxzoon are transmitted by ticks to farm and pet animals and have a significant impact on livestock industries and animal health in tropical and subtropical regions worldwide. In addition, diverse Babesia spp. infect humans as opportunistic hosts. Molecular phylogeny has demonstrated at least six piroplasmid lineages exemplified by B. microti, B. duncani, C. felis, T. equi, Theileria sensu stricto (T. annulata, T. parva, and T. orientalis) and Babesia sensu stricto (B. bovis, B. bigemina, and B. ovis). C1A cysteine-proteinases (C1A-Cp) are papain-like enzymes implicated in pathogenic and vital steps of the parasite life cycle such as nutrition and host cell egress. An expansion of C1A-Cp of T. annulata and T. parva with respect to B. bovis and B. ovis was previously described. In the present work, C1A-Cp paralogs were identified in available genomes of species pertaining to each piroplasmid lineage. Phylogenetic analysis revealed eight C1A-Cp groups. The profile of C1A-Cp paralogs across these groups corroborates and defines the existence of six piroplasmid lineages. C. felis, T. equi and Theileria s.s. each showed characteristic expansions into extensive families of C1A-Cp paralogs in two of the eight groups. Underlying gene duplications have occurred as independent unique evolutionary events that allow distinguishing these three piroplasmid lineages. We hypothesize that C1A-Cp paralog families may be associated with the advent of the schizont stage. Differences in the invertebrate tick host specificity and/or mode of transmission in piroplasmid lineages might also be associated with the observed C1A-Cp paralog profiles

Requirements for minerals and metals for 100% renewable scenarios

© The Author(s) 2019. This chapter explores the magnitude of the changes in patterns of material use that will be associated with the increasing deployment of renewable energy and discusses the implications for sustainable development. In particular, this chapter focuses on the increased use of lithium and cobalt, metals which are used extensively in battery technologies, and silver used in solar cells. Consistent with the strong growth in renewable energy and electrification of the transport system required in a 1.5°C scenario, the material requirements also rise dramatically, particularly for cobalt and lithium. Scenarios developed for this study show that increasing recycling rates and material efficiency can significantly reduce primary demand for metals

Stability of adhesion clusters under constant force

We solve the stochastic equations for a cluster of parallel bonds with shared constant loading, rebinding and the completely dissociated state as an absorbing boundary. In the small force regime, cluster lifetime grows only logarithmically with bond number for weak rebinding, but exponentially for strong rebinding. Therefore rebinding is essential to ensure physiological lifetimes. The number of bonds decays exponentially with time for most cases, but in the intermediate force regime, a small increase in loading can lead to much faster decay. This effect might be used by cell-matrix adhesions to induce signaling events through cytoskeletal loading.Comment: Revtex, 4 pages, 4 Postscript files include

Probing molecular free energy landscapes by periodic loading

Single molecule pulling experiments provide information about interactions in biomolecules that cannot be obtained by any other method. However, the reconstruction of the molecule's free energy profile from the experimental data is still a challenge, in particular for the unstable barrier regions. We propose a new method for obtaining the full profile by introducing a periodic ramp and using Jarzynski's identity for obtaining equilibrium quantities from non-equilibrium data. Our simulated experiments show that this method delivers significant more accurate data than previous methods, under the constraint of equal experimental effort.Comment: 4 pages, 3 figure

Decentralised energy futures: The changing emissions reduction landscape

© 2015 The Authors. Published by Elsevier B.V. The world is witnessing an energy revolution as renewables become more competitive and energy security becomes a high priority for an increasing number of countries. This development is changing the point along the supply chain ripe for reducing emissions. Whereas carbon capture and storage (CCS) coupled to coal or gas power production offers the potential to decarbonise the current centralised power systems, this relies on a significant increase in electrification to achieve deep emission reductions beyond the power sector, including industrial emissions and transportation. At the same time there is a trend towards decentralised industrial processes, e.g., driven by cost reductions in decentralised production systems and miniature processing plant. New strategies for reducing emissions from decentralised industrial and energy emission point sources will be increasingly important. This paper evaluates different emission reduction strategies that may be relevant to a decentralised energy and manufacturing future, including increased electrification, energy storage, renewable energy and renewable feedstock. Systemic opportunities or barriers and considerations of policy and decentralised decision-making are examined