Sources and composition of sub-200 nm sea spray aerosol inferred from volatility and hygroscopicity

Enrichment of marine organics in remote marine aerosols can influence their ability to act as cloud condensation nuclei (CCN), which are sites for water vapour to condense into cloud droplets. This project identified the composition and hygroscopicity of sea spray aerosol (SSA) formed at the ocean surface due to bursting of entrained air bubbles. SSA from organically enriched waters in the southwest Pacific and Southern Oceans were investigated. Results indicate that current emission schemes may not adequately predict SSA CCN, influencing the representation of cloud formation in climate modelling.

Fast and accurate business process drift detection

Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

The development of virtual leaf surface models for interactive agrichemical spray applications

This project constructed virtual plant leaf surfaces from digitised data sets for use in droplet spray models. Digitisation techniques for obtaining data sets for cotton, chenopodium and wheat leaves are discussed and novel algorithms for the reconstruction of the leaves from these three plant species are developed. The reconstructed leaf surfaces are included into agricultural droplet spray models to investigate the effect of the nozzle and spray formulation combination on the proportion of spray retained by the plant. A numerical study of the post-impaction motion of large droplets that have formed on the leaf surface is also considered.

Impaction of spray droplets on leaves: Influence of formulation and leaf character on shatter, bounce and adhesion

This paper combines experimental data with simple mathematical models to investigate the influence of spray formulation type and leaf character (wettability) on shatter, bounce and adhesion of droplets impacting with cotton, rice and wheat leaves. Impaction criteria that allow for different angles of the leaf surface and the droplet impact trajectory are presented; their predictions are based on whether combinations of droplet size and velocity lie above or below bounce and shatter boundaries. In the experimental component, real leaves are used, with all their inherent natural variability. Further, commercial agricultural spray nozzles are employed, resulting in a range of droplet characteristics. Given this natural variability, there is broad agreement between the data and predictions. As predicted, the shatter of droplets was found to increase as droplet size and velocity increased, and the surface became harder to wet. Bouncing of droplets occurred most frequently on hard to wet surfaces with high surface tension mixtures. On the other hand, a number of small droplets with low impact velocity were observed to bounce when predicted to lie well within the adhering regime. We believe this discrepancy between the predictions and experimental data could be due to air layer effects that were not taken into account in the current bounce equations. Other discrepancies between experiment and theory are thought to be due to the current assumption of a dry impact surface, whereas, in practice, the leaf surfaces became increasingly covered with fluid throughout the spray test runs.

Sodium and lithium storage properties of spray-dried molybdenum disulfide-graphene hierarchical microspheres

Developing nano/micro-structures which can effectively upgrade the intriguing properties of electrode materials for energy storage devices is always a key research topic. Ultrathin nanosheets were proved to be one of the potential nanostructures due to their high specific surface area, good active contact areas and porous channels. Herein, we report a unique hierarchical micro-spherical morphology of well-stacked and completely miscible molybdenum disulfide (MoS2) nanosheets and graphene sheets, were successfully synthesized via a simple and industrial scale spray-drying technique to take the advantages of both MoS2 and graphene in terms of their high practical capacity values and high electronic conductivity, respectively. Computational studies were performed to understand the interfacial behaviour of MoS2 and graphene, which proves high stability of the composite with high interfacial binding energy (−2.02 eV) among them. Further, the lithium and sodium storage properties have been tested and reveal excellent cyclic stability over 250 and 500 cycles, respectively, with the highest initial capacity values of 1300 mAh g−1 and 640 mAh g−1 at 0.1 A g−1.

Nutritional status and the foraging behaviour of Bactrocera tryoni with particular reference to protein bait spray

Poisoned protein baits comprise a recognized method for controlling tephritid fruit flies in the form of a ‘lure-and-kill’ technique. However, little is known about how a fly's internal protein and carbohydrate levels (i.e. nutritional status) might influence the efficacy of this control. In the present study, the relationships between the internal levels of protein (as measured by total body nitrogen) and carbohydrate (as measured by total body carbon) of the fruit fly Bactrocera tryoni (Froggatt) (Diptera: Tephritidae) are investigated, as well as its foraging behaviours in response to protein, fruit and cue-lure (a male-specific attractant) baits. Small cage behavioural experiments are conducted using flies from cultures of different nutritional status and wild flies sampled from the field during the fruiting cycle of a guava crop. For female flies, increasing total body nitrogen is correlated with decreased protein foraging and increased oviposition activity; increasing total body carbon levels generate the same behavioural changes except that the oviposition response is not significant. For males, there are no significant correlations between changes in total body nitrogen and total body carbon and protein or cue-lure foraging. For wild flies from the guava orchard, almost all of them are sexually mature when entering the crop and, over the entire season, total body nitrogen and total body carbon levels are such that protein hunger is unlikely for most flies. The results infer strongly that the requirements of wild, sexually mature flies for protein are minimal and that flies can readily gain sufficient nutrients from wild sources for their physiological needs. The results offer a mechanistic explanation for the poor response of male and mature female fruit flies to protein bait spray.

Mathematical modelling of the impaction and spreading of spray droplets on leaves

This thesis concerns the development of mathematical models to describe the interactions that occur between spray droplets and leaves. Models are presented that not only provide a contribution to mathematical knowledge in the field of fluid dynamics, but are also of utility within the agrichemical industry. The thesis is presented in two parts. First, thin film models are implemented with efficient numerical schemes in order to simulate droplets on virtual leaf surfaces. Then the interception event is considered, whereby energy balance techniques are employed to instantaneously predict whether an impacting droplet will bounce, splash, or adhere to a leaf.

Spray deposition of exfoliated MoS2 flakes as hole transport layer in perovskite-based photovoltaics

We propose the use of solution-processed molybdenum disulfide (MoS2) flakes as hole transport layer (HTL) for metal-organic perovskite solar cells. MoS2 bulk crystals are exfoliated in 2-propanol and deposited on perovskite layers by spray coating. We fabricated cells with glass/FTO/compact-TiO2/mesoporous-TiO2/CH3NH3PbI3/spiro- OMeTAD/Au structure and cells with the same structure but with MoS2 flakes as HTL instead of spiro-OMeTAD, the most widely used HTL. The electrical characterization of the cells with MoS2 as HTL show promising power conversion efficiency -η- of 3.9% with respect to cells with pristine spiro-OMeTAD (η=3.1%). Endurance test on 800-hour shelf life has shown higher stability for the MoS2–based cells (ΔPCE/PCE=-17%) with respect to the doped spiro-OMeTAD-based one (ΔPCE/PCE =-45%). Further improvements are expected with the optimization of the MoS2 deposition process

Detecting drift from event streams of unpredictable business processes

Existing business process drift detection methods do not work with event streams. As such, they are designed to detect inter-trace drifts only, i.e. drifts that occur between complete process executions (traces), as recorded in event logs. However, process drift may also occur during the execution of a process, and may impact ongoing executions. Existing methods either do not detect such intra-trace drifts, or detect them with a long delay. Moreover, they do not perform well with unpredictable processes, i.e. processes whose logs exhibit a high number of distinct executions to the total number of executions. We address these two issues by proposing a fully automated and scalable method for online detection of process drift from event streams. We perform statistical tests over distributions of behavioral relations between events, as observed in two adjacent windows of adaptive size, sliding along with the stream. An extensive evaluation on synthetic and real-life logs shows that our method is fast and accurate in the detection of typical change patterns, and performs significantly better than the state of the art.