Influence of mucuna fallow crop on selected soil properties, weed suppression and taro yields in Taveuni, Fiji

Two field experiments were carried out in Taveuni, Fiji to study the effects of mucuna (Mucuna pruriens) and grass fallow systems at 6 and 12 month durations on changes in soil properties (Experiment 1) and taro yields (Experiment 2). Biomass accumulation of mucuna fallow crop was significantly higher (P<0.05) than grass fallow crop at both 6 and 12 month durations. The longer fallow duration resulted in higher (P<0.05) total soil organic carbon, total soil nitrogen and earthworm numbers regardless of fallow type. Weed suppression in taro grown under mucuna was significantly greater (P<0.05) than under natural grass fallow. Taro grown under mucuna fallow significantly outyielded taro grown under grass fallow (11.8 vs. 8.8 t ha-1). Also, the gross margin of taro grown under mucuna fallow was 52% higher than that of taro grown under grass fallow. © ISHS.

Effect of sugarcane cropping systems on herbicide losses in surface runoff

Herbicide runoff from cropping fields has been identified as a threat to the Great Barrier Reef ecosystem. A field investigation was carried out to monitor the changes in runoff water quality resulting from four different sugarcane cropping systems that included different herbicides and contrasting tillage and trash management practices. These include (i) Conventional - Tillage (beds and inter-rows) with residual herbicides used; (ii) Improved - only the beds were tilled (zonal) with reduced residual herbicides used; (iii) Aspirational - minimum tillage (one pass of a single tine ripper before planting) with trash mulch, no residual herbicides and a legume intercrop after cane establishment; and (iv) New Farming System (NFS) - minimum tillage as in Aspirational practice with a grain legume rotation and a combination of residual and knockdown herbicides. Results suggest soil and trash management had a larger effect on the herbicide losses in runoff than the physico-chemical properties of herbicides. Improved practices with 30% lower atrazine application rates than used in conventional systems produced reduced runoff volumes by 40% and atrazine loss by 62%. There were a 2-fold variation in atrazine and >10-fold variation in metribuzin loads in runoff water between reduced tillage systems differing in soil disturbance and surface residue cover from the previous rotation crops, despite the same herbicide application rates. The elevated risk of offsite losses from herbicides was illustrated by the high concentrations of diuron (14mugL-1) recorded in runoff that occurred >2.5months after herbicide application in a 1st ratoon crop. A cropping system employing less persistent non-selective herbicides and an inter-row soybean mulch resulted in no residual herbicide contamination in runoff water, but recorded 12.3% lower yield compared to Conventional practice. These findings reveal a trade-off between achieving good water quality with minimal herbicide contamination and maintaining farm profitability with good weed control.

Soft computing based parameter identification in pavements and geomechanical systems

Accurate estimation of road pavement geometry and layer material properties through the use of proper nondestructive testing and sensor technologies is essential for evaluating pavement’s structural condition and determining options for maintenance and rehabilitation. For these purposes, pavement deflection basins produced by the nondestructive Falling Weight Deflectometer (FWD) test data are commonly used. The nondestructive FWD test drops weights on the pavement to simulate traffic loads and measures the created pavement deflection basins. Backcalculation of pavement geometry and layer properties using FWD deflections is a difficult inverse problem, and the solution with conventional mathematical methods is often challenging due to the ill-posed nature of the problem. In this dissertation, a hybrid algorithm was developed to seek robust and fast solutions to this inverse problem. The algorithm is based on soft computing techniques, mainly Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs) as well as the use of numerical analysis techniques to properly simulate the geomechanical system. A widely used pavement layered analysis program ILLI-PAVE was employed in the analyses of flexible pavements of various pavement types; including full-depth asphalt and conventional flexible pavements, were built on either lime stabilized soils or untreated subgrade. Nonlinear properties of the subgrade soil and the base course aggregate as transportation geomaterials were also considered. A computer program, Soft Computing Based System Identifier or SOFTSYS, was developed. In SOFTSYS, ANNs were used as surrogate models to provide faster solutions of the nonlinear finite element program ILLI-PAVE. The deflections obtained from FWD tests in the field were matched with the predictions obtained from the numerical simulations to develop SOFTSYS models. The solution to the inverse problem for multi-layered pavements is computationally hard to achieve and is often not feasible due to field variability and quality of the collected data. The primary difficulty in the analysis arises from the substantial increase in the degree of non-uniqueness of the mapping from the pavement layer parameters to the FWD deflections. The insensitivity of some layer properties lowered SOFTSYS model performances. Still, SOFTSYS models were shown to work effectively with the synthetic data obtained from ILLI-PAVE finite element solutions. In general, SOFTSYS solutions very closely matched the ILLI-PAVE mechanistic pavement analysis results. For SOFTSYS validation, field collected FWD data were successfully used to predict pavement layer thicknesses and layer moduli of in-service flexible pavements. Some of the very promising SOFTSYS results indicated average absolute errors on the order of 2%, 7%, and 4% for the Hot Mix Asphalt (HMA) thickness estimation of full-depth asphalt pavements, full-depth pavements on lime stabilized soils and conventional flexible pavements, respectively. The field validations of SOFTSYS data also produced meaningful results. The thickness data obtained from Ground Penetrating Radar testing matched reasonably well with predictions from SOFTSYS models. The differences observed in the HMA and lime stabilized soil layer thicknesses observed were attributed to deflection data variability from FWD tests. The backcalculated asphalt concrete layer thickness results matched better in the case of full-depth asphalt flexible pavements built on lime stabilized soils compared to conventional flexible pavements. Overall, SOFTSYS was capable of producing reliable thickness estimates despite the variability of field constructed asphalt layer thicknesses.

Probabilistic verification of satellite systems for mission critical applications

In this thesis, we present a quantitative approach using probabilistic verification techniques for the analysis of reliability, availability, maintainability, and safety (RAMS) properties of satellite systems. The subject of our research is satellites used in mission critical industrial applications. A strong case for using probabilistic model checking to support RAMS analysis of satellite systems is made by our verification results. This study is intended to build a foundation to help reliability engineers with a basic background in model checking to apply probabilistic model checking to small satellite systems. We make two major contributions. One of these is the approach of RAMS analysis to satellite systems. In the past, RAMS analysis has been extensively applied to the field of electrical and electronics engineering. It allows system designers and reliability engineers to predict the likelihood of failures from the indication of historical or current operational data. There is a high potential for the application of RAMS analysis in the field of space science and engineering. However, there is a lack of standardisation and suitable procedures for the correct study of RAMS characteristics for satellite systems. This thesis considers the promising application of RAMS analysis to the case of satellite design, use, and maintenance, focusing on its system segments. Data collection and verification procedures are discussed, and a number of considerations are also presented on how to predict the probability of failure. Our second contribution is leveraging the power of probabilistic model checking to analyse satellite systems. We present techniques for analysing satellite systems that differ from the more common quantitative approaches based on traditional simulation and testing. These techniques have not been applied in this context before. We present the use of probabilistic techniques via a suite of detailed examples, together with their analysis. Our presentation is done in an incremental manner: in terms of complexity of application domains and system models, and a detailed PRISM model of each scenario. We also provide results from practical work together with a discussion about future improvements.

Fault tolerance logging-based model for deterministic systems

Fault tolerance allows a system to remain operational to some degree when some of its components fail. One of the most common fault tolerance mechanisms consists on logging the system state periodically, and recovering the system to a consistent state in the event of a failure. This paper describes a general fault tolerance logging-based mechanism, which can be layered over deterministic systems. Our proposal describes how a logging mechanism can recover the underlying system to a consistent state, even if an action or set of actions were interrupted mid-way, due to a server crash. We also propose different methods of storing the logging information, and describe how to deploy a fault tolerant master-slave cluster for information replication. We adapt our model to a previously proposed framework, which provided common relational features, like transactions with atomic, consistent, isolated and durable properties, to NoSQL database management systems.

Close-in planets around giant stars: lack of hot-Jupiters and prevalence of multiplanetary systems

Extrasolar planets abound in almost any possible configuration. However, until five years ago, there was a lack of planets orbiting closer than 0.5 au to giant or subgiant stars. Since then, recent detections have started to populated this regime by confirming 13 planetary systems. We discuss the properties of these systems in terms of their formation and evolution off the main sequence. Interestingly, we find that 70.0 ± 6.6% of the planets in this regime are inner components of multiplanetary systems. This value is 4.2σ higher than for main-sequence hosts, which we find to be 42.4 ± 0.1%. The properties of the known planets seem to indicate that the closest-in planets (a< 0.06 au) to main-sequence stars are massive (i.e., hot Jupiters) and isolated and that they are subsequently engulfed by their host as it evolves to the red giant branch, leaving only the predominant population of multiplanetary systems in orbits 0.06

An investigation into the properties of non-digestible carbohydrates that selectively promote colonic propionate production

Short chain fatty acids (SCFA), including propionate, are produced by the bacterial fermentation of carbohydrates in the colon. Propionate has many potential roles in health, including inhibiting cholesterol synthesis, de novo lipogenesis and increasing satiety. The profile of SCFA produced is determined by both the substrate available and the bacteria present and may be influenced by environmental conditions within the lumen of the colon. Whilst it may be beneficial to increase colonic propionate production, dietary strategies to achieve this are unproven. Adding propionate to food leads to poorer organoleptic properties, and oral propionate is absorbed in the small intestine. The optimum way to selectively increase colonic propionate would be to select fermentable carbohydrates that selectively promote propionate production. To date, few studies have undertaken a systematic assessment of the factors leading to increased colonic propionate production making the selection of propiogenic carbohydrates challenging. The aim of this thesis was to identify the best carbohydrates for selectively increasing propionate production, and to explore the factors which control propionate production. This work started with a systematic review of the literature for evidence of candidate carbohydrates, which led to a screen of ‘propiogenic’ substrates using in vitro batch fermentations and mechanistic analysis of the impact of pH, bond linkage and orientation using a range of sugars, polysaccharides and fibre sources. A new unit for SCFA production was developed to allow comparison of results from in vitro studies encompassing a range different methodologies found in the literature. The systematic review found that rhamnose yielded the highest rate and proportion of propionate production whereas, for polysaccharides, β-glucan ranked highest for rate and guar gum ranked highest for molar production, but this was not replicated across all studies. Thus, no single NDC was established as highly propiogenic. Some substrates appeared more propiogenic than others and when these were screened in vitro. Laminarin, and other β-glucans ranked highest for propionate production. Legume fibre and mycoprotein fibre were also propiogenic. A full complement of glucose disaccharides were tested to examine the role glycosidic bond orientation and position on propionate production. Of the glucose disaccharides tested, β(1-4) bonding was associated with increased proportion of propionate and α(1-1) and β(1-4) increased the rate and proportion of butyrate production. In conclusion, it appears that for fibre to affect satiety, high intakes of fibre are needed, and which a major mechanism is thought to occur via propionate. Within this thesis it was identified that rather than selecting specific fibres, increasing overall intakes of highly fermentable carbohydrates is as effective at increasing propionate production. Selecting carbohydrates with beta-bonding, particularly laminarin and other β(1-4) fermentable carbohydrates leads to marginal increases in propionate production. Compared with targeted delivery of propionate to the colon, fermentable carbohydrates examined in this thesis have lesser and variable effects on propionate production. A more complete understanding of the impact of bond configurations in polysaccharides, rather than disaccharides, may help selection or design of dietary carbohydrates which selectively promote colonic propionate production substrates for inclusion in functional foods. Overall this study has concluded that few substrates are selectively propiogenic and the evidence suggests that similar changes in propionate production may be achieved by modest changes in dietary fibre intake

Scales of critically stable few-body halo systems

We review the scaling properties of few-body observables near the critical conditions for binding, with particular attention to light exotic nuclei, molecules and ultracold atoms.

Poly(epsilon-caprolactone)nanocapsules as carrier systems for herbicides: Physico-chemical characterization and genotoxicity evaluation

The toxicity of herbicides used in agriculture is influenced by their chemical stability, solubility, bioavailability, photodecomposition, and soil sorption. Possible solutions designed to minimize toxicity include the development of carrier systems able to modify the properties of the compounds and allow their controlled release. Polymeric poly(epsilon-caprolactone) (PCL) nanocapsules containing three triazine herbicides (ametryn, atrazine, and simazine) were prepared and characterized in order to assess their suitability as controlled release systems that could reduce environmental impacts. The association efficiencies of the herbicides in the nanocapsules were better than 84%. Assessment of stability (considering particle diameter, zeta potential, polydispersity, and pH) was conducted over a period of 270 days, and the particles were found to be stable in solution. In vitro release kinetics experiments revealed controlled release of the herbicides from the nanocapsules, governed mainly by relaxation of the polymer chains. Microscopy analyses showed that the nanocapsules were spherical, dense, and without aggregates. In the infrared spectra of the PCL nanocapsules containing herbicides, there were no bands related to the herbicides, indicating that interactions between the compounds had occurred. Genotoxicity tests showed that formulations of nanocapsules containing the herbicides were less toxic than the free herbicides. The results indicate that the use of PCL nanocapsules is a promising technique that could improve the behavior of herbicides in environmental systems. (C) 2012 Elsevier B.V. All rights reserved.

Densities, viscosities and derived thermophysical properties of water-saturated imidazolium-based ionic liquids

In order to evaluate the impact of the alkyl side chain length and symmetry of the cation on the thermophysical properties of water-saturated ionic liquids (ILs), densities and viscosities as a function of temperature were measured at atmospheric pressure and in the (298.15 to 363.15) K temperature range, for systems containing two series of bis(trifluoromethylsulfonyl)imide-based compounds: the symmetric [C n C n im][NTf2] (with n = 1-8 and 10) and asymmetric [C n C1im][NTf2] (with n = 2-5, 7, 9 and 11) ILs. For water-saturated ILs, the density decreases with the increase of the alkyl side chain length while the viscosity increases with the size of the aliphatic tails. The saturation water solubility in each IL was further estimated with a reasonable agreement based on the densities of water-saturated ILs, further confirming that for the ILs investigated the volumetric mixing properties of ILs and water follow a near ideal behaviour. The water-saturated symmetric ILs generally present lower densities and viscosities than their asymmetric counterparts. From the experimental data, the isobaric thermal expansion coefficient and energy barrier were also estimated. A close correlation between the difference in the energy barrier values between the water-saturated and pure ILs and the water content in each IL was found, supporting that the decrease in the viscosity of ILs in presence of water is directly related with the decrease of the energy barrier.

Synthesis and proton conduction properties of lanthanide amino-sulfophosphonates

Crystalline acid-functionalized metal phosphonates are potential candidates as proton conducting electrolytes. Their frameworks can be chemically modified to contain proton carriers such as acidic groups (P-OH; -SO3H, -COOH,…) and guest molecules (H2O, NH3,…) that generates hydrogen bond networks stable in a wide range of temperature [1,2]. In this work, focus is laid on properties derived from the combination of lanthanide ions with the amino-sulfophosphonate ligand (H2O3PCH2)2-N-(CH2)2-SO3H. Hightrough-put screening was followed to reach the optimal synthesis conditions under solvothermal conditions at 140 ºC. Isolated polycrystalline solids, Ln[(O3PCH2)2-NH-(CH2)2-SO3H].2H2O (Ln= La, Pr and Sm), crystallize in the monoclinic (La) and orthorhombic (Pr and Sm) systems with unit cell volume of ~2548 Å3. Preliminary proton conductivity measurements for Sm derivative have been carried out between 25º and 80 ºC at relative humidity (RH) values of 70 % and 95 %. The sample exhibits enhanced conductivity at high RH and T (Figure 1) and constant activation energies of 0.4 eV, typical of a Grothuss mechanism of proton.

Mimicking the behaviour of idiotypic AIS robot controllers using probabilistic systems

Previous work has shown that robot navigation systems that employ an architecture based upon the idiotypic network theory of the immune system have an advantage over control techniques that rely on reinforcement learning only. This is thought to be a result of intelligent behaviour selection on the part of the idiotypic robot. In this paper an attempt is made to imitate idiotypic dynamics by creating controllers that use reinforcement with a number of different probabilistic schemes to select robot behaviour. The aims are to show that the idiotypic system is not merely performing some kind of periodic random behaviour selection, and to try to gain further insight into the processes that govern the idiotypic mechanism. Trials are carried out using simulated Pioneer robots that undertake navigation exercises. Results show that a scheme that boosts the probability of selecting highly-ranked alternative behaviours to 50% during stall conditions comes closest to achieving the properties of the idiotypic system, but remains unable to match it in terms of all round performance.

Artificial immune systems

The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems (AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics. In this chapter an overview of AIS is presented, its evolution is discussed, and it is shown that the diversification of the field is linked to the diversity of the immune system itself, leading to a number of algorithms as opposed to one archetypal system. Two case studies are also presented to help provide insight into the mechanisms of AIS; these are the idiotypic network approach and the Dendritic Cell Algorithm.

Screening natural resources for mineralogenic and osteogenic bioactivities using in vitro and in vivo fish systems

Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

Cosmic Explosions: Observations Of Infant Hydrogen-Free Supernovae Towards An Understanding Of Their Parent Systems

Radiation in the first days of supernova explosions contains rich information about physical properties of the exploding stars. In the past three years, I used the intermediate Palomar Transient Factory to conduct one-day cadence surveys, in order to systematically search for infant supernovae. I show that the one-day cadences in these surveys were strictly controlled, that the realtime image subtraction pipeline managed to deliver transient candidates within ten minutes of images being taken, and that we were able to undertake follow-up observations with a variety of telescopes within hours of transients being discovered. So far iPTF has discovered over a hundred supernovae within a few days of explosions, forty-nine of which were spectroscopically classified within twenty-four hours of discovery.

Our observations of infant Type Ia supernovae provide evidence for both the single-degenerate and double-degenerate progenitor channels. On the one hand, a low-velocity Type Ia supernova iPTF14atg revealed a strong ultraviolet pulse within four days of its explosion. I show that the pulse is consistent with the expected emission produced by collision between the supernova ejecta and a companion star, providing direct evidence for the single degenerate channel. By comparing the distinct early-phase light curves of iPTF14atg to an otherwise similar event iPTF14dpk, I show that the viewing angle dependence of the supernova-companion collision signature is probably responsible to the difference of the early light curves. I also show evidence for a dark period between the supernova explosion and the first light of the radioactively-powered light curve. On the other hand, a peculiar Type Ia supernova iPTF13asv revealed strong near-UV emission and absence of iron in the spectra within the first two weeks of explosion, suggesting a stratified ejecta structure with iron group elements confined to the slow-moving part of the ejecta. With its total ejecta mass estimated to exceed the Chandrasekhar limit, I show that the stratification and large mass of the ejecta favor the double-degenerate channel.

In a separate approach, iPTF found the first progenitor system of a Type Ib supernova iPTF13bvn in the pre-explosion HST archival mages. Independently, I used the early-phase optical observations of this supernova to constrain its progenitor radius to be no larger than several solar radii. I also used its early radio detections to derive a mass loss rate of 3e-5 solar mass per year for the progenitor right before the supernova explosion. These constraints on the physical properties of the iPTF13bvn progenitor provide a comprehensive data set to test Type Ib supernova theories. A recent HST revisit to the iPTF13bvn site two years after the supernova explosion has confirmed the progenitor system.

Moving forward, the next frontier in this area is to extend these single-object analyses to a large sample of infant supernovae. The upcoming Zwicky Transient Facility with its fast survey speed, which is expected to find one infant supernova every night, is well positioned to carry out this task.