Design of experiments to study the impact of process parameters on droplet size and development of non-invasive imaging techniques in tablet coating

Atomisation of an aqueous solution for tablet film coating is a complex process with multiple factors determining droplet formation and properties. The importance of droplet size for an efficient process and a high quality final product has been noted in the literature, with smaller droplets reported to produce smoother, more homogenous coatings whilst simultaneously avoiding the risk of damage through over-wetting of the tablet core. In this work the effect of droplet size on tablet film coat characteristics was investigated using X-ray microcomputed tomography (XμCT) and confocal laser scanning microscopy (CLSM). A quality by design approach utilising design of experiments (DOE) was used to optimise the conditions necessary for production of droplets at a small (20 μm) and large (70 μm) droplet size. Droplet size distribution was measured using real-time laser diffraction and the volume median diameter taken as a response. DOE yielded information on the relationship three critical process parameters: pump rate, atomisation pressure and coating-polymer concentration, had upon droplet size. The model generated was robust, scoring highly for model fit (R2 = 0.977), predictability (Q2 = 0.837), validity and reproducibility. Modelling confirmed that all parameters had either a linear or quadratic effect on droplet size and revealed an interaction between pump rate and atomisation pressure. Fluidised bed coating of tablet cores was performed with either small or large droplets followed by CLSM and XμCT imaging. Addition of commonly used contrast materials to the coating solution improved visualisation of the coating by XμCT, showing the coat as a discrete section of the overall tablet. Imaging provided qualitative and quantitative evidence revealing that smaller droplets formed thinner, more uniform and less porous film coats.

Physical and Genetic Analysis of the CUP1 Tandem Array in the Yeast Saccharomyces cerevisiae

The genomes of many strains of baker’s yeast, Saccharomyces cerevisiae, contain multiple repeats of the copper-binding protein Cup1. Cup1 is a member of the metallothionein family, and is found in a tandem array on chromosome VIII. In this thesis, I describe studies that characterized these tandem arrays and their mechanism of formation across diverse strains of yeast. I show that CUP1 arrays are an illuminating model system for observing recombination in eukaryotes, and describe insights derived from these observations.

In our first study, we analyzed 101 natural isolates of S. cerevisiae in order to examine the diversity of CUP1-containing repeats across different strains. We identified five distinct classes of repeats that contain CUP1. We also showed that some strains have only a single copy of CUP1. By comparing the sequences of all the strains, we were able to elucidate the mechanism of formation of the CUP1 tandem arrays, which involved unequal non-homologous recombination events starting from a strain that had only a single CUP1 gene. Our observation of CUP1 repeat formation allows more general insights about the formation of tandem repeats from single-copy genes in eukaryotes, which is one of the most important mechanisms by which organisms evolve.

In our second study, we delved deeper into our mechanistic investigations by measuring the relative rates of inter-homolog and intra-/inter-sister chromatid recombination in CUP1 tandem arrays. We used a diploid strain that is heterozygous both for insertion of a selectable marker (URA3) inside the tandem array, and also for markers at either end of the array. The intra-/inter-sister chromatid recombination rate turned out to be more than ten-fold greater than the inter-homolog rate. Moreover, we found that loss of the proteins Rad51 and Rad52, which are required for most inter-homolog recombination, did not greatly reduce recombination in the CUP1 tandem repeats. Additionally, we investigated the effects of elevated copper levels on the rate of each type of recombination at the CUP1 locus. Both types of recombination are increased at high concentrations of copper (as is known to be the case for CUP1 transcription). Furthermore, the inter-homolog recombination rate at the CUP1 locus is higher than the average over the genome during mitosis, but is lower than the average during meiosis.

The research described in Chapter 2 is published in 2014.

Non-equilibrium induction of tin in germanium: towards direct bandgap Ge1-xSnx nanowires

The development of non-equilibrium group IV nanoscale alloys is critical to achieving new functionalities, such as the formation of a direct bandgap in a conventional indirect bandgap elemental semiconductor. Here, we describe the fabrication of uniform diameter, direct bandgap Ge1-xSnx alloy nanowires, with a Sn incorporation up to 9.2[thinsp]at.%, far in excess of the equilibrium solubility of Sn in bulk Ge, through a conventional catalytic bottom-up growth paradigm using noble metal and metal alloy catalysts. Metal alloy catalysts permitted a greater inclusion of Sn in Ge nanowires compared with conventional Au catalysts, when used during vapour-liquid-solid growth. The addition of an annealing step close to the Ge-Sn eutectic temperature (230[thinsp][deg]C) during cool-down, further facilitated the excessive dissolution of Sn in the nanowires. Sn was distributed throughout the Ge nanowire lattice with no metallic Sn segregation or precipitation at the surface or within the bulk of the nanowires. The non-equilibrium incorporation of Sn into the Ge nanowires can be understood in terms of a kinetic trapping model for impurity incorporation at the triple-phase boundary during growth.

Metabarcoding approach for non-indigenous species surveillance in marine coastal waters

In this study, high-throughput sequencing (HTS) metabarcoding was applied for the surveillance of plankton communities within the southeastern (SE) Baltic Sea coastal zone. These results were compared with those from routine monitoring survey and morphological analyses. Four of five nonindigenous species found in the samples were identified exclusively by metabarcoding. All of them are considered as invasive in the Baltic Sea with reported impact on the ecosystem and biodiversity. This study indicates that, despite some current limitations, HTS metabarcoding can provide information on the presence of exotic species and advantageously complement conventional approaches, only requiring the same monitoring effort as before. Even in the currently immature status of HTS, this combination of HTS metabarcoding and observational records is recommended in the early detection of marine pests and delivery of the environmental status metrics of nonindigenous species.

Dissolution of a spatially variable DNAPL (dense non aqueous phase liquid) source

Dissolution of non-aqueous phase liquids (NAPLs) or gases into groundwater is a key process, both for contamination problems originating from organic liquid sources, and for dissolution trapping in geological storage of CO2. Dissolution in natural systems typically will involve both high and low NAPL saturations and a wide range of pore water flow velocities within the same source zone for dissolution to groundwater. To correctly predict dissolution in such complex systems and as the NAPL saturations change over time, models must be capable of predicting dissolution under a range of saturations and flow conditions. To provide data to test and validate such models, an experiment was conducted in a two-dimensional sand tank, where the dissolution of a spatially variable, 5x5 cm**2 DNAPL tetrachloroethene source was carefully measured using x-ray attenuation techniques at a resolution of 0.2x0.2 cm**2. By continuously measuring the NAPL saturations, the temporal evolution of DNAPL mass loss by dissolution to groundwater could be measured at each pixel. Next, a general dissolution and solute transport code was written and several published rate-limited (RL) dissolution models and a local equilibrium (LE) approach were tested against the experimental data. It was found that none of the models could adequately predict the observed dissolution pattern, particularly in the zones of higher NAPL saturation. Combining these models with a model for NAPL pool dissolution produced qualitatively better agreement with experimental data, but the total matching error was not significantly improved. A sensitivity study of commonly used fitting parameters further showed that several combinations of these parameters could produce equally good fits to the experimental observations. The results indicate that common empirical model formulations for RL dissolution may be inadequate in complex, variable saturation NAPL source zones, and that further model developments and testing is desirable.

Bit-index sort: A fast non-comparison integer sorting algorithm for permutations

This paper describes a fast integer sorting algorithm, herein referred to as Bit-index sort, which does not use comparisons and is intended to sort partial permutations. Experimental results exhibit linear complexity order in execution time. Bit-index sort uses a bit-array to classify input sequences of distinct integers, and exploits built-in bit functions in C compilers, supported by machine hardware, to retrieve the ordered output sequence. Results show that Bit-index sort outperforms quicksort and counting sort algorithms when compared in their execution time. A parallel approach for Bit-index sort using two simultaneous threads is also included, which obtains further speedups of up to 1.6 compared to its sequential case.

Investigation of the role of long non-coding RNAs in oncogene induced cellular senescence

Cellular senescence is a stable arrest of cell proliferation induced by several factors such as activated oncogenes, oxidative stress and shortening of telomeres. Senescence acts as a tumour suppression mechanism to halt the progression of cancer. However, senescence may also impact negatively upon tissue regeneration, thus contributing to the effects of ageing. The eukaryotic genome is controlled by various modes of transcriptional and translational regulation. Focus has therefore centred on the role of long non- coding RNAs (lncRNAs) in regulating the genome. Accordingly, understanding how lncRNAs function to regulate the senescent genome is integral to improving our knowledge and understanding of tumour suppression and ageing. Within this study, I set out to investigate the expression of lncRNAs’ expression within models of senescence. Through a custom expression array, I have shown that expression of multiple different lncRNAs is up-regulated and down regulated in IMR90 replicative senescent fibroblasts and oncogene-induced senescent melanocytes. LncRNA expression was determined to be specific to stable senescence-associated cell arrest and predominantly within the nucleus of senescent cells. In order to examine the function of lncRNA expression in senescence, I selected lncRNA transcript ENST0000430998 (lncRNA_98) to focus my investigations upon. LncRNA_98 was robustly upregulated within multiple models of senescence and efficiently depleted using anti-sense oligonucleotide technology. Characterisation and unbiased RNA-sequencing of lncRNA_98 deficient senescent cells highlighted a list of genes that are regulated by lncRNA_98 expression in senescent cells and may regulate aspects of the senescence program. Specifically, the formation of SAHF was impeded upon depletion of lncRNA_98 expression and levels of total pRB protein expression severely decreased. Validation and recapitulation of consequences of pRB depletion was confirmed through lncRNA_98 knock-out cells generated using CRISPR technology. Surprisingly, inhibition of ATM kinase functions permitted the restoration of pRB protein levels within lncRNA_98 deficient cells. I propose that lncRNA_98 antagonizes the ability of ATM kinase to downregulate pRB expression at a post-transcriptional level, thereby potentiating senescence. Furthermore, lncRNA expression was detected within fibroblasts of old individuals and visualised within senescent melanocytes in human benign nevi, a barrier to melanoma progression. Conversely, mining of 337 TCGA primary melanoma data sets highlighted that the lncRNA_98 gene and its expression was lost from a significant proportion of melanoma samples, consistent with lncRNA_98 having a tumour suppressor functions. The data presented in this study illustrates that lncRNA_98 expression has a regulatory role over pRB expression in senescence and may regulate aspects of tumourigenesis and ageing.

Statistical modeling of protein lysate array data

The protein lysate array is an emerging technology for quantifying the protein concentration ratios in multiple biological samples. It is gaining popularity, and has the potential to answer questions about post-translational modifications and protein pathway relationships. Statistical inference for a parametric quantification procedure has been inadequately addressed in the literature, mainly due to two challenges: the increasing dimension of the parameter space and the need to account for dependence in the data. Each chapter of this thesis addresses one of these issues. In Chapter 1, an introduction to the protein lysate array quantification is presented, followed by the motivations and goals for this thesis work. In Chapter 2, we develop a multi-step procedure for the Sigmoidal models, ensuring consistent estimation of the concentration level with full asymptotic efficiency. The results obtained in this chapter justify inferential procedures based on large-sample approximations. Simulation studies and real data analysis are used to illustrate the performance of the proposed method in finite-samples. The multi-step procedure is simpler in both theory and computation than the single-step least squares method that has been used in current practice. In Chapter 3, we introduce a new model to account for the dependence structure of the errors by a nonlinear mixed effects model. We consider a method to approximate the maximum likelihood estimator of all the parameters. Using the simulation studies on various error structures, we show that for data with non-i.i.d. errors the proposed method leads to more accurate estimates and better confidence intervals than the existing single-step least squares method.

Non-invasive monitoring of changes in exhaled markers of airway inflammation in Thoroughbred racehorses

Exhaled breath (EB) and exhaled breath condensate (EBC) contain numerous volatile gases and a wide-array of non-volatile compounds, several of which have been investigated as markers of lower airway inflammation in human and veterinary medicine and have been used to diagnose and monitor diseases associated with pulmonary inflammation. The identification of reliable biomarkers within EB and EBC is an active research focus with the common goal of establishing non-invasive and repeatable assessment of respiratory health and disease in mammals. The application of EB and EBC analysis holds considerable appeal in the investigation of respiratory disease in Thoroughbred racehorses, as inflammatory airway disease (IAD) is a common cause for poor performance in this population of animals. This study documented that EB and EBC samples can be safely collected from Thoroughbred racehorses in their own environment, without adverse effect or interference with the horse’s training regimen. The use of off-line collection and analysis of exhaled gases via chemiluminescence is suitable for the measurement of exhaled carbon monoxide, but is not appropriate for analyzing exhaled nitric oxide in horses. Significant changes in the concentration of exhaled CO and the pH of EBC occurred in response to strenuous exercise and when exercising in different environmental temperatures. Exhaled CO was associated with tracheal mucus score (and the number of neutrophils in the mucus) and EBC pH was significantly different in horses with evidence of neutrophilic IAD compared to horses without IAD. Numerous physiological and environmental variables were identified as confounding factors in the assessment of both exhaled CO and EBC pH, with respiratory rate prior to EB collection, and during EBC collection, consistently identified as an explanatory variable influencing the concentration of exhaled biomarkers. Further studies in EB and EBC analysis in horses need to focus on objectively accounting for key respiratory dynamics during sample collection.

Non-fermented and fermented jabuticaba (Myrciaria cauliflora Mart.) pomaces as valuable sources of functional ingredients

abuticaba (Myrciaria cauliflora. Mart) is a highly perishable fruit native to Brazil, which is consumed both fresh and industrially processed in the form of juices, jams, wines and distilled liqueurs. This processing generates a large amount of waste by-products, which represent approximately 50% of the fruit weight. The by-products are of interest for obtaining valuable bioactive compounds that could be used as nutraceuticals or functional ingredients. In this study, fermented and non-fermented jabuticaba pomaces were studied regarding their hydrophilic and lipophilic compounds, as well as their antioxidant properties, including: soluble sugars, organic acids and tocopherols (using high performance liquid chromatography coupled to refraction index, diode array and fluorescence detector, respectively); phenolics and anthocyanins, (using liquid chromatography coupled to diode array detection, and mass spectrometry with electrospray ionization); and fatty acids (using gas-liquid chromatography with flame ionization detection). The analytical data demonstrated that jabuticaba pomaces are a rich source of bioactive compounds such as tocopherols, polyunsaturated fatty acids and phenolic compounds (namely hydrolyzable tannins and anthocyanins) with antioxidant potential. Therefore, jabuticaba pomace may have good potential as a functional ingredient in the fabrication of human foods and animal feed.

An expert model approach to assess the potential of non-wood forest products for forest owners

Mestrado em Engenharia Florestal e dos Recursos Naturais - Instituto Superior de Agronomia - UL

The Development of Calibrants through Characterization of Volatile Organic Compounds from Peroxide Based Explosives and a Non-target Chemical Calibration Compound

Detection canines represent the fastest and most versatile means of illicit material detection. This research endeavor in its most simplistic form is the improvement of detection canines through training, training aids, and calibration. This study focuses on developing a universal calibration compound for which all detection canines, regardless of detection substance, can be tested daily to ensure that they are working with acceptable parameters. Surrogate continuation aids (SCAs) were developed for peroxide based explosives along with the validation of the SCAs already developed within the International Forensic Research Institute (IFRI) prototype surrogate explosives kit. Storage parameters of the SCAs were evaluated to give recommendations to the detection canine community on the best possible training aid storage solution that minimizes the likelihood of contamination. Two commonly used and accepted detection canine imprinting methods were also evaluated for the speed in which the canine is trained and their reliability. As a result of the completion of this study, SCAs have been developed for explosive detection canine use covering: peroxide based explosives, TNT based explosives, nitroglycerin based explosives, tagged explosives, plasticized explosives, and smokeless powders. Through the use of these surrogate continuation aids a more uniform and reliable system of training can be implemented in the field than is currently used today. By examining the storage parameters of the SCAs, an ideal storage system has been developed using three levels of containment for the reduction of possible contamination. The developed calibration compound will ease the growing concerns over the legality and reliability of detection canine use by detailing the daily working parameters of the canine, allowing for Daubert rules of evidence admissibility to be applied. Through canine field testing, it has been shown that the IFRI SCAs outperform other commercially available training aids on the market. Additionally, of the imprinting methods tested, no difference was found in the speed in which the canines are trained or their reliability to detect illicit materials. Therefore, if the recommendations discovered in this study are followed, the detection canine community will greatly benefit through the use of scientifically validated training techniques and training aids.

Non-thermal phenomena in galaxy clusters: the LOFAR revolution

Turbulence introduced into the intra-cluster medium (ICM) through cluster merger events transfers energy to non-thermal components (relativistic particles and magnetic fields) and can trigger the formation of diffuse synchrotron radio sources. Owing to their steep synchrotron spectral index, such diffuse sources can be better studied at low radio frequencies. In this respect, the LOw Frequency ARray (LOFAR) is revolutionizing our knowledge thanks to its unprecedented resolution and sensitivity below 200 MHz. In this Thesis we focus on the study of radio halos (RHs) by using LOFAR data. In the first part of this work we analyzed the largest-ever sample of galaxy clusters observed at radio frequencies. This includes 309 Planck clusters from the Second Data Release of the LOFAR Two Metre Sky Survey (LoTSS-DR2), which span previously unexplored ranges of mass and redshift. We detected 83 RHs, half of which being new discoveries. In 140 clusters we lack a detected RH; for this sub-sample we developed new techniques to derive upper limits to their radio powers. By comparing detections and upper limits, we carried out the first statistical analysis of populations of clusters observed at low frequencies and tested theoretical formation models. In the second part of this Thesis we focused on ultra-steep spectrum radio halos. These sources are almost undetected at GHz frequencies, but are thought to be common at low frequencies. We presented LOFAR observations of two interesting clusters hosting ultra-steep spectrum radio halos. With complementary radio and X-ray observations we constrained the properties and origin of these targets.

User scheduling for low earth orbit multi-user multiple-input-multiple-output non-terrestrial network systems

In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.

Real-time anomaly detection of gamma-ray bursts for the Cherenkov Telescope Array using deep learning

The Cherenkov Telescope Array (CTA) will be the next-generation ground-based observatory to study the universe in the very-high-energy domain. The observatory will rely on a Science Alert Generation (SAG) system to analyze the real-time data from the telescopes and generate science alerts. The SAG system will play a crucial role in the search and follow-up of transients from external alerts, enabling multi-wavelength and multi-messenger collaborations. It will maximize the potential for the detection of the rarest phenomena, such as gamma-ray bursts (GRBs), which are the science case for this study. This study presents an anomaly detection method based on deep learning for detecting gamma-ray burst events in real-time. The performance of the proposed method is evaluated and compared against the Li&Ma standard technique in two use cases of serendipitous discoveries and follow-up observations, using short exposure times. The method shows promising results in detecting GRBs and is flexible enough to allow real-time search for transient events on multiple time scales. The method does not assume background nor source models and doe not require a minimum number of photon counts to perform analysis, making it well-suited for real-time analysis. Future improvements involve further tests, relaxing some of the assumptions made in this study as well as post-trials correction of the detection significance. Moreover, the ability to detect other transient classes in different scenarios must be investigated for completeness. The system can be integrated within the SAG system of CTA and deployed on the onsite computing clusters. This would provide valuable insights into the method's performance in a real-world setting and be another valuable tool for discovering new transient events in real-time. Overall, this study makes a significant contribution to the field of astrophysics by demonstrating the effectiveness of deep learning-based anomaly detection techniques for real-time source detection in gamma-ray astronomy.