Computer simulation of moist agglomerate collisions

This thesis considers the computer simulation of moist agglomerate collisions using the discrete element method (DEM). The study is confined to pendular state moist agglomerates, at which liquid is presented as either absorbed immobile films or pendular liquid bridges and the interparticle force is modelled as the adhesive contact force and interstitial liquid bridge force. Algorithms used to model the contact force due to surface adhesion, tangential friction and particle deformation have been derived by other researchers and are briefly described in the thesis. A theoretical study of the pendular liquid bridge force between spherical particles has been made and the algorithms for the modelling of the pendular liquid bridge force between spherical particles have been developed and incorporated into the Aston version of the DEM program TRUBAL. It has been found that, for static liquid bridges, the more explicit criterion for specifying the stable solution and critical separation is provided by the total free energy. The critical separation is given by the cube root of liquid bridge volume to a good approximation and the 'gorge method' of evaluation based on the toroidal approximation leads to errors in the calculated force of less than 10%. Three dimensional computer simulations of an agglomerate impacting orthogonally with a wall are reported. The results demonstrate the effectiveness of adding viscous binder to prevent attrition, a common practice in process engineering. Results of simulated agglomerate-agglomerate collisions show that, for colinear agglomerate impacts, there is an optimum velocity which results in a near spherical shape of the coalesced agglomerate and, hence, minimises attrition due to subsequent collisions. The relationship between the optimum impact velocity and the liquid viscosity and surface tension is illustrated. The effect of varying the angle of impact on the coalescence/attrition behaviour is also reported. (DX 187, 340)

A measurement and modelling study of hair partition of neutral, cationic and anionic chemicals

Various neutral, cationic and anionic chemicals contained in hair care products can be absorbed into hair fiber to modulate physicochemical properties such as color, strength, style and volume. For environmental safety, there is also an interest in understanding hair absorption to wide chemical pollutants. There have been very limited studies on the absorption properties of chemicals into hair. Here, an experimental and modelling study has been carried out for the hair-water partition of a range of neutral, cationic and anionic chemicals at different pH. The data showed that hair-water partition not only depends on the hydrophobicity of the chemical but also the pH. The partition of cationic chemicals to hair increased with pH and this is due to their electrostatic interaction with hair increased from repulsion to attraction. For anionic chemicals, their hair-water partition coefficients decreased with increasing pH due to their electrostatic interaction with hair decreased from attraction to repulsion. Increase in pH didn’t change the partition of neutral chemicals significantly. Based on the new physicochemical insight of the pH effect on hair-water partition, a new QSPR model has been proposed, taking into account of both the hydrophobic interaction and electrostatic interaction of chemical with hair fiber

Tying Policy to System: Does the Ross Sea Region Marine Reserve Protect Transport Pathways Connecting the Life History of Antarctic Toothfish?

A central objective of the Ross Sea region Marine Protected Area (MPA) is to protect areas important to the life cycle of Antarctic toothfish (Dissostichus mawsoni), a top fish predator and by far the region’s most important commercial species. Juvenile toothfish predominate in deep basins along the inner continental shelf, whereas adults are found mostly along the continental slope and spawning areas on the Pacific-Antarctic Ridge. The inner basins connect to the continental slope via glacial troughs and predictable transport along each trough results in exchange with the Antarctic Slope Current as it flows westward. From the slope, two transport pathways, an eastern one from Iselin Bank and a western one that turns cyclonically along the flank of the Southeast Indian Ridge, connect northward to the Pacific-Antarctic Ridge, where the northern arm of the Ross Gyre and the Antarctic Circumpolar Current flow eastward. Using a circulation model to compare transport pathways connecting toothfish life history areas, we consider which inshore basins are likely most important in contributing to adult spawning aggregations; how transport pathways from each may be expected to influence distributions along the continental slope and Pacific-Antarctic Ridge; and how zonal transport pathways may promote export to areas downstream of the marine reserve. Although the MPA protects some critical life history pathways for toothfish, others remain vulnerable to commercial fishing, and we argue that those in adjacent areas along the Iselin Bank, Pacific-Antarctic Ridge and the Amundsen Sea might usefully be protected, discussing the range of policy instruments available. We also recommend consideration of transport pathways in deliberations for a proposed network of Southern Ocean MPAs, introducing a system-based tool using chemical tracers in otoliths that can test for toothfish movement between areas connected along the Antarctic Slope Current and Antarctic Circumpolar Current

Multimodal Fish Feeding Intensity Assessment in Aquaculture

Fish feeding intensity assessment (FFIA) aims to evaluate the intensity change of fish appetite during the feeding process, which is vital in industrial aquaculture applications. The main challenges surrounding FFIA are two-fold. 1) robustness: existing work has mainly leveraged single-modality (e.g., vision, audio) methods, which have a high sensitivity to input noise. 2) efficiency: FFIA models are generally expected to be employed on devices. This presents a challenge in terms of computational efficiency. In this work, we first introduce an audio-visual dataset, called AV-FFIA. AV-FFIA consists of 27,000 labeled audio and video clips that capture different levels of fish feeding intensity. To our knowledge, AV-FFIA is the first large-scale multimodal dataset for FFIA research. Then, we introduce a multi-modal approach for FFIA by leveraging single-modality pre-trained models and modality-fusion methods, with benchmark studies on AV-FFIA. Our experimental results indicate that the multi-modal approach substantially outperforms the single-modality based approach, especially in noisy environments. While multimodal approaches provide a performance gain for FFIA, it inherently increase the computational cost. To overcome this issue, we further present a novel unified model, termed as U-FFIA. U-FFIA is a single model capable of processing audio, visual, or audio-visual modalities, by leveraging modality dropout during training and knowledge distillation from single-modality pre-trained models. We demonstrate that U-FFIA can achieve performance better than or on par with the state-of-the-art modality-specific FFIA models, with significantly lower computational overhead. Our proposed U-FFIA approach enables a more robust and efficient method for FFIA, with the potential to contribute to improved management practices and sustainability in aquaculture

Near-infrared hyperspectral imaging for non-destructive classification of commercial tea products

Tea is the most consumed manufactured drink in the world. In recent years, various high end analytical techniques such as high-performance liquid chromatography have been used to analyse tea products. However, these techniques require complex sample preparation, are time consuming, expensive and require a skilled analyst to carry out the experiments. Therefore, to support rapid and non-destructive assessment of tea products, the use of near infrared (NIR) (950-1760 nm) hyperspectral imaging (HSI) for classification of six different commercial tea products (oolong, green, yellow, white, black and Pu-erh) is presented. To visualise the HSI data, linear (principal component analysis (PCA) and multidimensional scaling (MDS)) and non-linear (t-distributed stochastic neighbour embedding (t-SNE) and isometric mapping (ISOMAP)) data visualisation methods were compared. t-SNE provided separation of the six commercial tea products into three groups based on the extent of processing: minimally processed, oxidised and fermented. To perform the classification of different tea products, a multi-class error-correcting output code (ECOC) model containing support vector machine (SVM) binary learners was developed. The classification model was further used to predict classes for pixels in the HSI hypercube to obtain the classification maps. The SVM-ECOC model provided a classification accuracy of 97.41±0.16 % for the six commercial tea products. The methodology developed provides a means for rapid, non-destructive, in situ testing of tea products, which would be of considerable benefit for process monitoring, quality control, authenticity and adulteration detection

Homoisoflavonoids are potent glucose transporter 2 (GLUT 2) inhibitors–a potential mechanism for the glucose-lowering properties of Polygonatum odoratum

Foods of high carbohydrate content such as sucrose or starch increase postprandial blood glucose concentrations. The glucose absorption system in the intestine comprises two components: sodium-dependent glucose transporter-1 (SGLT1) and glucose transporter 2 (GLUT2). Here five sappanin-type (SAP) homoisoflavonoids were identified as novel potent GLUT2 inhibitors, with three of them isolated from the fibrous roots of Polygonatum odoratum (Mill.) Druce. SAP homoisolflavonoids had a stronger inhibitory effect on 25 mM glucose transport (41.6 ± 2.5, 50.5 ± 7.6, 47.5 ± 1.9, 42.6 ± 2.4, and 45.7 ± 4.1% for EA-1, EA-2, EA-3, MOA, and MOB) than flavonoids (19.3 ± 2.2, 11.5 ± 3.7, 16.4 ± 2.4, 5.3 ± 1.0, 3.7 ± 2.2, and 18.1 ± 2.4% for apigenin, luteolin, quercetin, naringenin, hesperetin, and genistein) and phloretin (28.1 ± 1.6%) at 15 μM. SAP homoisoflavonoids and SGLT1 inhibitors were found to synergistically inhibit the uptake of glucose using an in vitro model comprising Caco-2 cells. This observed new mechanism of the glucose-lowering action of P. odoratum suggests that SAP homoisoflavonoids and their combination with flavonoid monoglucosides show promise as naturally functional ingredients for inclusion in foods and drinks designed to control postprandial glucose levels