Integrating multiple sources to answer questions in Algebraic Topology

We present in this paper an evolution of a tool from a user interface for a concrete Computer Algebra system for Algebraic Topology (the Kenzo system), to a front-end allowing the interoperability among different sources for computation and deduction. The architecture allows the system not only to interface several systems, but also to make them cooperate in shared calculations.Comment: To appear in The 9th International Conference on Mathematical Knowledge Management: MKM 201

Ultra-fast Imaging of Two-Phase Flow in Structured Monolith Reactors; Techniques and Data Analysis

This thesis will address the use of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) techniques to probe the “monolith reactor”, which consists of a structured catalyst over which reactions may occur. This reactor has emerged as a potential alternative to more traditional chemical engineering systems such as trickle bed and slurry reactors. However, being a relatively new design, its associated flow phenomena and design procedures are not rigorously understood, which is retarding its acceptance in industry. Traditional observations are unable to provide the necessary information for design since the systems are opaque and dynamic. Therefore, NMR is proposed as an ideal tool to probe these systems in detail. The theory of NMR is summarised and the development of novel NMR techniques is presented. Novel techniques are validated in simple systems, and tested in more complex systems to ascertain their quantitative nature, and to find their limitations. These techniques are improvements over existing techniques in that they either decrease the acquisition time (allowing the observation of dynamically-changing systems) or allow us to probe systems in different ways to extract useful information. The goal of this research is to better understand the flow phenomena present in such systems, and to use this information to design better, more efficient, more controllable industrial reactors. The analysis of the NMR data acquired is discussed in detail, and several novel image-processing techniques have been developed to aid in the quantification of features within the images, and also to measure quantities such as holdup and velocity. These novel techniques are validated, and then applied to the systems of interest. Various configurations of monolith reactor, ranging from low flow rate systems to more challenging (and more industrially relevant) turbulent systems, are probed using these methods, and the contrasting flow phenomena and performance of these systems are discussed, with a view to optimisation of the choice of design parameters

Genetically-modified bacteria and uses thereof

A genetically-modified bacterium, for example of the class Actinobacteria, and the use of such a bacterium in the bioconversion of a steroidal substrate into a steroidal product of interest. A method of converting a steroidal substrate into a steroidal product of interest, wherein the method comprises: inoculating culture medium with genetically-modified bacteria according to any of Claims 1 to 28 and growing the bacterial culture until a target OD600 is reached; adding a steroidal substrate to the bacterial culture when the target OD600 is reached; culturing the bacterial culture so that the steroidal substrate is converted to the steroidal product of interest; and extracting and/or purifying the steroidal product of interest from the bacterial culture

Application of multi-regression machine learning algorithms to solve ocean water mass mixing in the Atlantic Ocean

The distribution of any non-conservative variable in the deep open ocean results from the circulation and mixing of water masses (WMs) of contrasting origin and from the initial preformed composition, modified during ongoing simultaneous biological and/or geochemical processes. Estimating the contribution of the WMs composing a sample is useful to trace the distribution of each water mass and to quantitatively separate the physical (mixing) and biogeochemical components of the variability of any, non- conservative variable (e.g., dissolved organic carbon, prokaryote biomass) in the ocean. Other than potential temperature and salinity, additional semi-conservative and non-conservative variables have been used to solve the mixing of more than three water masses using Optimum Multi-Parameter (OMP) approaches. Successful application of an OMP analysis requires knowledge of the characteristics of the water masses in their source regions as well as their circulation and mixing patterns. Here, we propose the application of multi-regression machine learning models to solve ocean water mass mixing. The models tested were trained using the solutions from OMP analyses previously applied to samples from cruises in the Atlantic Ocean. Extremely Randomized Trees algorithm yielded the highest score (R2 = 0.9931; mse = 0.000227). Our model allows solving the mixing of water masses in the Atlantic Ocean using potential temperature, salinity, latitude, longitude and depth. Therefore, basic hydrographic data collected during typical research cruises or autonomous systems can be used as input variables and provide results in real time. The model can be fed with new solutions from compatible OMP analyses as well as with new water masses not previously considered in it. Our tool will provide knowledge on water mass composition and distribution to a broader community of marine scientists not specialized in OMP analysis and/or in the oceanography of the studied area. This will allow a quantitative analysis of the effect of water mass mixing on the variables or processes under study

Perplexity as a tool for the allocation of proficiency levels to utterances written by foreign language learners

La asignación de niveles de competencia a escritos producidos por aprendices de una lengua es una tarea altamente subjetiva. Es por esto que el desarrollo de métodos que evalúen escritos de manera automática puede ayudar tanto al profesorado como al alumnado. En este trabajo, hemos explorado dos vías mediante el uso del corpus CAES. Dicho corpus está formado por escritos de aprendices de español y etiquetado con niveles CEFR (hasta el C1). La primera aproximación es un modelo de aprendizaje profundo llamado Deep-ELE que asigna niveles de competencia a las frases. La segunda aproximación llevada a cabo ha consistido en estudiar la perplejidad de las frases de los estudiantes de distintos niveles, para luego clasificarlos en niveles. Ambas aproximaciones han sido evaluadas, y se ha comprobado que pueden usarse de manera exitosa para clasificar frases por niveles. En concreto, el modelo Deep-ELE obtiene una accuracy de 81,3% y un QWK de 0,83. Como conclusión, este trabajo es un paso para entender cómo las herramientas del procesado de lenguaje natural pueden ayudar a las personas que aprenden un segundo idioma.The allocation of proficiency levels to utterances written by foreign language learners is a subjective task. Therefore, the development of methods to automatically evaluate written sentences can help both students and teachers. In this work, we have explored two different approaches to tackle this task by using the corpus CAES, which contains written utterances of learners of Spanish labelled with CEFR levels (up to C1). The first approach is a deep learning model called Deep-ELE which assigns proficiency levels to sentences. The second approach consists in studying the perplexity of sentences written by students of different levels, to later allocate levels to those sentences based on such an analysis. Both approaches have been evaluated, and results confirm that they can be used to successfully classify written sentences into proficiency levels. In particular, the Deep-ELE model reaches an accuracy of 81.3% and a weighted Cohen Kappa of 0.83. As a conclusion, this work is a step towards better understanding how natural language processing methods can help learners of a second language.Esta investigación ha sido parcialmente financiada por los proyectos AFIANZA 2022/02, PID2020-115225RB-I00 de MCIN/AEI/ 10.13039/501100011033 y PID2020-116641GB-I00 de MCIN/AEI/10.13039/501100011033

Reinforcement of the "Rhynchospora fusca" population in the Galbaniturri mire (Izki Natural Park, Álava, Spain): first results

Rhynchospora fusca (L.) W.T. Aiton is a Cyperaceae that lives in constantly wet zones in acid mires, whose European distribution reaches its southernmost limit in the Spanish Cantabrian corniche. It is a characteristic plant of Habitat 7150 “Depressions on peat substrates of the Rhynchosporion” in Annex I of the EU Habitats Directive of the European Union, and also listed in the Catalogue of Threatened Species of the Basque Autonomous Community under the “Endangered” category since an only locality within the Izki Natural Park is known, in the Galbaniturri-1 mire. Given the vulnerability of this only Basque population, and aiming to improve its conservation status, a reinforcement experience was set in 2011 within LIFE+ PRO-IZKI project. We describe the main results, including the plantation at five new points in the same mire (2013 and 2015), and the monitoring for survival, flowering and fruiting for 3 consecutive reproductive periods from 2014 to 2016. The plants used for the reinforcement were vegetatively generated from plants collected in the wild. The average survival rate for the first plants planted in 2013 was very low (28%), due to the choice of planting before the winter; a second plantation in spring 2015 obtained a much higher survival rate (79%). Plant growth by rhizome renewals has been increasing year after year in almost all plots. Flowering occurred for the first time in 2016 in 6 of the 9 plots, showing heterogeneous numbers among them. Seed production has been estimated for 4 of the 6 flowering plots, also showing considerable differences. As a whole, the initial phase of reinforcement for this species is considered successful, but a final evaluation can only be made on a long-term basis

Array comparative genomic hybridisation-based identification of two imbalances of chromosome 1p in a 9-year-old girl with a monosomy 1p36 related phenotype and a family history of learning difficulties: a case report

<p>Abstract</p> <p>Introduction</p> <p>Monosomy 1p36 is one of the most common terminal deletion syndromes, with an approximate incidence of 1 in every 5000 live births. This syndrome is associated with several pronounced clinical features including characteristic facial features, cardiac abnormalities, seizures and mental retardation, all of which are believed to be due to haploinsufficiency of genes within the 1p36 region. The deletion size varies from approximately 1.5 Mb to 10 Mb with the most common breakpoints located at 1p36.13 to 1p36.33. Over 70% of 1p36 deletion patients have a true terminal deletion. A further 7% have interstitial deletions and a proportion have a derivative chromosome 1 where the 1p telomere is replaced by material from another chromosome, either as a result of a de-novo rearrangement or as a consequence of malsegregation of a balanced parental translocation at meiosis.</p> <p>Case presentation</p> <p>Array comparative genomic hybridisation analysis of a 9-year-old Caucasian girl presenting with dysmorphic facial features and learning difficulties, for whom previous routine karyotyping had been normal, identified two submicroscopic rearrangements within chromosome 1p. Detection of both an insertional duplication of a region of 1p32.3 into the subtelomeric region of the short arm of a chromosome 1 homologue and a deletion within 1p36.32 of the same chromosome instigated a search for candidate genes within these regions which could be responsible for the clinical phenotype of the patient. Several genes were identified by computer-based annotation, some of which have implications in neurological and physical development.</p> <p>Conclusion</p> <p>Array comparative genomic hybridisation is providing a robust method for pinpointing regions of candidate genes associated with clinical phenotypes that extend beyond the resolution of the light microscope. This case report provides an example of how this method of analysis and the subsequent reporting of findings have proven useful in collaborative efforts to elucidate multiple gene functions from a clinical perspective.</p