Simultaneous Extrema in the Entropy Production for Steady-State Fluid Flow in Parallel Pipes

Steady-state flow of an incompressible fluid in parallel pipes can simultaneously satisfy two contradictory extremum principles in the entropy production, depending on the flow conditions. For a constant total flow rate, the flow can satisfy (i) a pipe network minimum entropy production (MinEP) principle with respect to the flow rates, and (ii) the maximum entropy production (MaxEP) principle of Ziegler and Paltridge with respect to the choice of flow regime. The first principle - different to but allied to that of Prigogine - arises from the stability of the steady state compared to non-steady-state flows; it is proven for isothermal laminar and turbulent flows in parallel pipes with a constant power law exponent, but is otherwise invalid. The second principle appears to be more fundamental, driving the formation of turbulent flow in single and parallel pipes at higher Reynolds numbers. For constant head conditions, the flow can satisfy (i) a modified maximum entropy production (MaxEPMod) principle of \v{Z}upanovi\'c and co-workers with respect to the flow rates, and (ii) an inversion of the Ziegler-Paltridge MaxEP principle with respect to the flow regime. The interplay between these principles is demonstrated by examples.Comment: Revised version 2; 5 figure

The promise and peril of intensive-site-based ecological research: insights from the Hubbard Brook ecosystem study

Abstract. Ecological research is increasingly concentrated at particular locations or sites. This trend reflects a variety of advantages of intensive, site-based research, but also raises important questions about the nature of such spatially delimited research: how well does site based research represent broader areas, and does it constrain scientific discovery?We provide an overview of these issues with a particular focus on one prominent intensive research site: the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA. Among the key features of intensive sites are: long-term, archived data sets that provide a context for new discoveries and the elucidation of ecological mechanisms; the capacity to constrain inputs and parameters, and to validate models of complex ecological processes; and the intellectual cross-fertilization among disciplines in ecological and environmental sciences. The feasibility of scaling up ecological observations from intensive sites depends upon both the phenomenon of interest and the characteristics of the site. An evaluation of deviation metrics for the HBEF illustrates that, in some respects, including sensitivity and recovery of streams and trees from acid deposition, this site is representative of the Northern Forest region, of which HBEF is a part. However, the mountainous terrain and lack of significant agricultural legacy make the HBEF among the least disturbed sites in the Northern Forest region. Its relatively cool, wet climate contributes to high stream flow compared to other sites. These similarities and differences between the HBEF and the region can profoundly influence ecological patterns and processes and potentially limit the generality of observations at this and other intensive sites. Indeed, the difficulty of scaling up may be greatest for ecological phenomena that are sensitive to historical disturbance and that exhibit the greatest spatiotemporal variation, such as denitrification in soils and the dynamics of bird communities. Our research shows that end member sites for some processes often provide important insights into the behavior of inherently heterogeneous ecological processes. In the current era of rapid environmental and biological change, key ecological responses at intensive sites will reflect both specific local drivers and regional trends

Optimization of leaf morphology in relation to leaf water status: A theory.

The leaf economic traits such as leaf area, maximum carbon assimilation rate, and venation are all correlated and related to water availability. Furthermore, leaves are often broad and large in humid areas and narrower in arid/semiarid and hot and cold areas. We use optimization theory to explain these patterns. We have created a constrained optimization leaf model linking leaf shape to vein structure that is integrated into coupled transpiration and carbon assimilation processes. The model maximizes net leaf carbon gain (NPPleaf) over the loss of xylem water potential. Modeled relations between leaf traits are consistent with empirically observed patterns. As the results of the leaf shape-venation relation, our model further predicts that a broadleaf has overall higher NPPleaf compared to a narrowleaf. In addition, a broadleaf has a lower stomatal resistance compared to a narrowleaf under the same level of constraint. With the same leaf area, a broadleaf will have, on average, larger conduits and lower total leaf xylem resistance and thus be more efficient in water transportation but less resistant to cavitation. By linking venation structure to leaf shape and using water potential as the constraint, our model provides a physical explanation for the general pattern of the covariance of leaf traits through the safety-efficiency trade-off of leaf hydraulic design

An investigation into dynamic and functional properties of prokaryotic signalling networks

In this thesis, I investigate dynamic and computational properties of prokaryotic signalling architectures commonly known as the Two Component Signalling networks and phosphorelays. The aim of this study is to understand the information processing capabilities of different prokaryotic signalling architectures by examining the dynamics they exhibit. I present original investigations into the dynamics of different phosphorelay architectures and identify network architectures that include a commonly found four step phosphorelay architecture with a capacity for tuning its steady state output to implement different signal-response behaviours viz. sigmoidal and hyperbolic response. Biologically, this tuning can be implemented through physiological processes like regulating total protein concentrations (e.g. via transcriptional regulation or feedback), altering reaction rate constants through binding of auxiliary proteins on relay components, or by regulating bi-functional activity in relays which are mediated by bifunctional histidine kinases. This study explores the importance of different biochemical arrangements of signalling networks and their corresponding response dynamics. Following investigations into the significance of various biochemical reactions and topological variants of a four step relay architecture, I explore the effects of having different types of proteins in signalling networks. I show how multi-domain proteins in a phosphorelay architecture with multiple phosphotransfer steps occurring on the same protein can exhibit multistability through a combination of double negative and positive feedback loops. I derive a minimal multistable (core) architecture and show how component sharing amongst networks containing this multistable core can implement computational logic (like AND, OR and ADDER functions) that allows cells to integrate multiple inputs and compute an appropriate response. I examine the genomic distribution of single and multi domain kinases and annotate their partner response regulator proteins across prokaryotic genomes to find the biological significance of dynamics that these networks embed and the processes they regulate in a cell. I extract data from a prokaryotic two component protein database and take a sequence based functional annotation approach to identify the process, function and localisation of different response regulators as signalling partners in these networks. In summary, work presented in this thesis explores the dynamic and computational properties of different prokaryotic signalling networks and uses them to draw an insight into the biological significance of multidomain sensor kinases in living cells. The thesis concludes with a discussion on how this understanding of the dynamic and computational properties of prokaryotic signalling networks can be used to design synthetic circuits involving different proteins comprising two component and phosphorelay architectures.Dorothy Hodgkin Studentship funded by EPSRC and Microsoft Research

Functional traits and resource-use strategies of native and invasive plants in Eastern North American forests

Despite the presumption that native species are well adapted to their local environment, non-native invaders seem to outperform native plants. Intuitively, it appears paradoxical that non-native species, with no opportunity for local adaptation, can exhibit greater fitness than native plants with this advantage. Here, I compared traits of native and invasive shrub and liana species in Eastern North American (ENA) forests to test the overarching hypothesis that non-native understory species invasive to this region have superior resource-use strategies, or alternatively, they share the same metabolic tradeoffs as the native flora. First, at a global scale, I addressed the largely untested hypothesis that biogeography places significant constraints on trait evolution. Reanalyzing a large functional trait database, along with species\u27 native distribution data, I found that regional floras with different evolutionary histories exhibit different tradeoffs in resource capture strategies. Second, using a common garden to control for environment, I measured leaf physiological traits relating to resource investments, carbon returns, and resource-use efficiencies in 14 native and 18 non-native invasive species of common genera found in ENA understories, where growth is presumably constrained by light and nutrient limitation. I tested whether native and invasive plants have similar metabolic constraints or if these invasive species (predominantly from East Asia) are more productive per unit resource cost. Despite greater resource costs (leaf construction, leaf N), invaders exhibited greater energy- and nitrogen-use efficiencies, particularly when integrated over leaf lifespan. Efficiency differences were primarily driven by greater mean photosynthetic abilities (20% higher daily C gain) and leaf lifespans (24 days longer) in invasive species. Third, motivated by common garden results, I conducted a resource addition experiment in a central NY deciduous forest to investigate the role of resource limitation on invasion success in the field. I manipulated understory light environments (overstory tree removal) and N availabilities (ammonium-nitrate fertilization) to create a resource gradient across plots each containing 3 invasive and 6 native woody species. Invasive species generally exhibited greater aboveground productivity and photosynthetic gains. After two treatment years, invasive species displayed more pronounced trait responses to the resource gradients, primarily light, relative to the weaker responses of native species. Lastly, I asked whether species exhibit similar resource-use strategies in their native and invasive ranges. I measured leaf functional traits of Rhamnus cathartica (native to Europe, invasive in ENA) and Prunus serotina (native to ENA, invasive in Europe) in populations across central NY and northern France. Notably, I found invasive US populations of R. cathartica had markedly greater photosynthetic rates (50% higher) and reduced leaf N resorption rates in autumn (30% lower) than native French populations. Contrastingly, I found minimal leaf trait differences in P. serotina between native (US) and invasive (French) populations. Collectively, my results highlight the utility of functional trait perspectives and support a mechanistic explanation for invasion success based on differential abilities of species to convert limiting resources to biomass

Comparative flux control through the cytoplasmic phase of cell wall biosynthesis

The introduction of antibacterial drugs in the middle of the last century heralded a new era in the treatment of infectious disease. However the parallel emergence of antibiotic resistance and decline in new drug discovery threatens these advances. The development of new antibacterials must therefore be a high priority. The biosynthesis of the bacterial cell wall is the target for several clinically important antibacterials. This extracellular structure is essential for bacterial viability due to its role in the prevention of cell lysis under osmotic pressure. Its principal structural component, peptidoglycan, is a polymer of alternating N-acetyl-glucosamine (GlcNAc) and N-acetyl muramic acid (MurNAc) residues crosslinked by peptide bridges anchored by pentapeptide stems attached to the MurNAc moieties. The biosynthesis of peptidoglycan proceeds in three phases. The first, cytoplasmic, phase is catalysed by six enzymes. It forms a uridine diphosphate (UDP) bound MurNAc residue from UDP-GlcNAc and attaches the pentapeptide stem. This phase is a relatively unexploited target for antibacterials, being targeted by a single clinically relevant antibacterial, and is the subject of this thesis. The Streptococcus pneumoniae enzymes were kinetically characterised and in silico models of this pathway were developed for this species and Escherichia coli. These models were used to identify potential drug targets within each species. In addition the potentially clinically relevant interaction between an inhibitor of and feedback loops within this pathway was investigated. The use of direct parameter estimation instead of more traditional approaches to kinetic characterisation of enzymes was found to have significant advantages where it could be successfully applied. This approach required the theoretical analysis of the models used to determine whether unique parameter vectors could be determined. Such an analysis has been completed for a broad range of biologically relevant enzymes. In addition a relatively new approach to such analysis has been developed

Graphical Requirements for Multistationarity in Reaction Networks and their Verification in BioModels

International audienceThomas's necessary conditions for the existence of multiple steady states in gene networks have been proved by Soulé with high generality for dynamical systems defined by differential equations. When applied to (protein) reaction networks however, those conditions do not provide information since they are trivially satisfied as soon as there is a bimolecular or a reversible reaction. Refined graphical requirements have been proposed to deal with such cases. In this paper, we present for the first time a graph rewriting algorithm for checking the refined conditions given by Soliman, and evaluate its practical performance by applying it systematically to the curated branch of the BioModels repository. This algorithm analyzes all reaction networks (of size up to 430 species) in less than 0.05 second per network, and permits to conclude to the absence of multistationarity in 160 networks over 506. The short computation times obtained in this graphical approach are in sharp contrast to the Jacobian-based symbolic computation approach. We also discuss the case of one extra graphical condition by arc rewiring that allows us to conclude on 20 more networks of this benchmark but with a high computational cost. Finally, we study with some details the case of phosphorylation cycles and MAPK signalling models which show the importance of modelling the intermediate complexations with the enzymes in order to correctly analyze the multistationarity capabilities of such biochemical reaction networks

A comparison of methods of quantifying and assessing the behaviour and welfare of Bornean Orangutans (Pongo pygmaeus): a case study at Twycross Zoo

The maintenance of both the psychological and physiological health of captive animals is a key priority of modern zoos. Recognising that characteristics of the captive environment have the potential to decrease animal welfare, methods for quantifying and assessing welfare have been developed as part of the process for improving animal welfare. Traditionally, observations of animal behaviour and quantifying time budgets in relation to those of the animals’ wild counterparts have been utilised to assess animal welfare. Hormonal assays have also been implemented to quantify the physiological stress response of animals in captivity and identify the extent of stress being experienced. Each of these methods focuses on a different indicator of animal welfare, is quantified in different ways and provides a different perspective on the welfare of the animals. Given the limited time and financial budgets available to zoos and animal carers, identifying the most appropriate method of welfare assessment would be advantageous in helping to secure the best possible health of captive animals and to maximise their value in captivity. This thesis implemented both behavioural observations and hormonal assays to identify the strengths and weaknesses of each methodology, and make recommendations for future research. The study involved a group of four Bornean orangutans (Pongo pygmaeus) housed at Twycross Zoo. Behavioural observations involved continuous group sampling and the development of an ethogram to record a comprehensive account of orangutan activity over the course of a 12 week enrichment programme. Simultaneous to these observations, faecal samples were collected from each orangutan and processed via Enzyme Immunoassay (EIA) to quantify levels of faecal glucocorticoid metabolites (fGCM) in each sample. While recognising the recent developments in ecological analytical methods, the capacity for extending network analysis beyond the application to social networks, and its use as a welfare assessment tool were explored. Behavioural and space-use networks were developed using data from a second study of the orangutans housed at Twycross Zoo. The flexibility of network analysis in visually representing different data types allowed for the intuitive representation of complex behavioural data. Further research investigated the use of network metrics in providing deeper insights into animal behaviour and space use patterns. In addition, bipartite networks were assessed for their potential to detect and show patterns in the relationships between two sets of behavioural data. Each of the methods used had a number of strengths and weaknesses, but importantly each contributed a different perspective in the assessment of behaviour patterns and welfare, suggesting that an integrated approach to behaviour studies utilising several methods would be ideal. Cost and logistic constraints make this unlikely in most cases. However, the thesis ends with a look to the future and the recognition that the current rapid development of technology for use in animal behaviour studies, coupled with equally rapid development of analytical techniques, may help to dramatically increase the amount of information gained from the average animal behaviour study in the future. Such improvements have never been more urgent, with the requirement for understanding animal behaviour in light of current extinction rates within the context of habitat destruction and climate change. It is hoped that this thesis will make a contribution to improving future animal behaviour and welfare studies by providing an assessment of both traditional methods of study as well as demonstrating the use and potential of new ways of applying network analysis within such studies