Multi-Level Medium Voltage Inverter for Dc Distributed Wind Farm to Establish Grid Interface and Provide Ancillary Support

Wind energy has gained in popularity in recent years due to cost, security and environmental concerns associated with conventional energy sources like fossil fuels. However, the utilization of wind energy in power systems creates many technical and non-technical challenges that need to be addressed for successful integrations. The main technical issues related to wind energy are its uncertainty and variability and their impacts on stability, reliability and quality of the electric power. In systems with high wind energy penetrations, unlike conventional generations, sudden changes in active and/or reactive power demand cannot be supported by wind energy. This lack of demand support may create unwanted voltage and frequency variations in the grid. On the hand, the existing AC distributed wind farms have several drawbacks including complexity, higher cost, and lower efficiency. In this dissertation, a medium voltage direct current (MVDC) distribution system for wind farms is investigated. The proposed system offers higher reliability, lower cost, higher efficiency and more importantly grid support. It also allows for easier integration of energy storage systems at DC level. Design, control, implementation, and testing of a three-level medium voltage inverter are presented. The inverter can provide active and reactive power support to the grid in case of frequency and voltage droops. Simulation and experimental results are presented to verify the viability of the proposed system and control techniques

Thermoplastic-thermosetting merged polyimides via furan-maleimide Diels–Alder polymerization

AbstractNovel thermoplastic-thermosetting merged polyimide system has been developed via Diels–Alder intermolecular polymerization of bisfuran namely, 2,5-bis(furan-2-ylmethylcarbamoyl) terephthalic acid A with a series of bismaleimides B1–4. Thus obtained intermediate Diels–Alder adducts C1–4 were aromatized and imidized (i.e. cyclized) through carboxylic and amide groups to afford thermoplastic-thermosetting merged polyimides D1–4. Bisfuran A was prepared by the condensation of pyromellitic dianhydride with furan-2-ylmethanamine and characterized by elemental, spectral, thermal and LCMS analyses. Synthesized Diels–Alder adducts C1–4 and polyimides D1–4 were characterized by elemental analysis, spectral features, number average molecular weight (Mn‾), degree of polymerization (DP) and thermal analysis. To facilitate the correct structural assessment and to be able to verify the occurrence of the DA adducts and PIs, a model compound 4 was prepared from phthalic anhydride and furan-2-ylmethanamine in a similar way. FTIR spectral features of polyimides D1–4 were compared with model compound 4 and they were found to be quite identical. The ‘in situ' void-free glass fiber reinforced composites GFRC1–4 were prepared from the produced system and characterized by chemical, mechanical and electrical analyses. All the composites showed good mechanical, electrical and thermal properties and good resistance to organic solvents and mineral acids

Cross channel fraud detection framework in financial services using recurrent neural networks

The reliability and performance of real time fraud detection techniques has been a major concern for the financial institutions as traditional fraud detection models couldn’t cope with the emerging new and innovative attacks that deceive banks. The problems are further exacerbated with evolving customer behaviour as existing fraud detection models unable to cope with class imbalance problem and longer feedback loop. This thesis looks at the holistic view of fraud detection and proposes a conceptual fraud detection framework that can detect anomalous transaction quickly and accurately, as well as dynamically evolve to maintain the efficiency with minimum input from subject matter expert. The framework is used to analyse Internet Banking (IB) transactions and contextual information to reduce the false positives and improve fraud detection rates. Based on the proposed framework, Long Short-Term Memory (LSTM) based Recurrent Neural Network model for detecting fraud in remote banking is implemented and performance is evaluated against Support Vector Machine (SVM) and Markov models. The main research element is to model events as state vectors so that sequence-based learning can be applied, followed by a weak classifier to deal with noise. Firstly, the study focuses on Feature Engineering where along raw attributes such as IP Address, Amount and other, two novel features for remote banking fraud are evaluated, i.e., the time spend on a page and the time between page transition. The second focus is on modelling which is performed on an anonymised real-life dataset, provided by a large financial institution in Europe. The results of the modelling demonstrate that given the labelled dataset all models can detect payment fraud with acceptable accuracy. Various tests proved that the LSTM model achieves a F1 score of 97.7% whereas the SVM and Markov model achieve 93.5% and 95.0% respectively. As the time elapsed, the LSTM model performance significantly improves as the sequence of events became larger. As the dataset increases that time it takes to train traditional models becomes a bottleneck. This proves the hypothesis that the events across banking channels can be modelled as time series data and then sequence-based learners such as Recurrent Neural Network (RNN) can be applied to improve or reduce the False Positive Rate (FPR) and False Negative Rate (FNR)

Hepatocyte Growth Factor and Its Receptor Are Expressed in Cardiac Myocytes During Early Cardiogenesis

In the mouse, the heart primordium arises when mesodermis set aside during gastrulation, is induced by pharyngeal endoderm, migrates ventrally to the midline of the embryo, forms a tube, and begins beating. Little is known of the molecular mechanisms that mediate the determination, mitosis, differentiation, and migration that lead to the beating heart. Transcripts for hepatocyte growth factor/scatter factor (HGF) and its receptor are coexpressed transiently and dynamically in the premyocardium but not in other heart progenitor cells. Transcripts for HGF ligand and receptor are first detected before cardiac function and looping and persist through the first looping stage, when heart morphology begins to elaborate. HGF ligand and receptor mRNA are detectable after the putative heart transcription factor, Csx/Nkx2-5, and concomitantly with the heart structural gene, cardiac actin. HGF receptor mRNA is detected in the mesoderm of the headfold stage and persists in myocardial precursors of the ventricles and atria (but not in the outflow-tract smooth muscle cells) through the 14- somite stage at 8.75 days after fertilization (day E8.75). At the headfold stage, between E7.5 and E8.0, HGF receptor mRNA was detected in myocardial cells before fusion at the ventral midline. HGF ligand and receptor mRNA transcripts are coexpressed in the embryo, except in the headfold stage (when only the HGF receptor can be detected) and in the heart at the 14- to 18-somite stage (when only HGF ligand can be detected). The dynamic pattern of coexpression suggests an autoregulatory role for HGF and its receptor in early heart development

Induction of somatic embryogenesis and genetic fidelity of endangered medicinal herb Curculigo orchioides Gaertn

An efficient regeneration system, through somatic embryogenesis was developed for Curculigo orchioides Gaertn - an endangered medicinal herb. Somatic embryos weredeveloped on MS medium containing 8 - 15μM BA from leaf explants. The highest, 69 % leafexplants responded in terms of embryogenic calli with average 8 embryos on MS mediumcontaining 8μM BA. Regenerated plantlets were transferred to autoclaved mixture of soil:sand: compost (1:1:1; v/v/v) for hardening. Genetic fidelity of somatic embryogenesis derivedregenerant was assessed using random amplified polymorphic DNA (RAPD)

The Effects of Arsenic and Heavy Metal Mixtures on Pancreatic β-cell Insulin Secretion

Diabetes mellitus is a known metabolic disorder characterized by altered insulin secretion or responsiveness. Recently, a potential association between diabetes and environmental exposures has been described, in which environmental compounds have been identified as potential diabetogens. With diabetes prevalence and industrial growth rising in many middle- and low-income countries, it is imperative we look further into the association between heavy metals and diabetes mellitus. Interactions between iAsIII and heavy metals may exhibit differing effects on insulin secretion machinery than just individual heavy metals. In previous studies, trivalent inorganic arsenic (iAsIII) has been identified as an inhibitor of insulin secretion in isolated mouse islets. In addition to iAsIII, heavy metals, notably zinc (Zn), manganese (Mn) and cadmium (Cd), have also been found to be associated with alteration of insulin secretion. INS-1 (832/13) rat insulinoma cells were treated for 24 hours with varying concentrations of each of the aforementioned heavy metals. When co-exposed with Zn and Cd, iAsIII acted as the primary inhibitor of insulin secretion in the β-cells. Co-exposure of Mn and 1 μM iAsIII, exhibited a significant decrease in insulin secretion at the 25 and 50 μM Mn concentrations compared to 1 μM iAsIII exposure alone. There was no significant difference in insulin secretion between the Mn and iAsIII co-exposure and Mn alone treatment groups at the 25 and 50 μM Mn concentrations, suggesting Mn as a primary driver of insulin secretion inhibition at higher concentrations. Additionally, 24-hour 1 μM iAsIII exposure to INS-1 (832/13) cells caused a significant decrease in mitochondrial oxygen consumption rate (OCR) under energy-demanding conditions, identifying mitochondria as targets for iAsIII in β-cells. This study examines the impact of heavy metals and their mixtures with iAsIII on insulin secretion in INS1 (832/13) rat pancreatic β-cells. From these results, we conclude that water mixtures containing certain heavy metals in mixture with iAsIII may pose significant danger to pancreatic β-cell function.Bachelor of Science in Public Healt

Adaptive business rules framework for workflow management

Changing scattered and dynamic business rules in Business Workflow Systems has become a growing problem that hinders the use and configuration of workflow-based applications. There is a gap in the existing research studies which currently focus on solutions that are application specific, without accounting for the universal logical dependencies between the business rules and, as a result, do not support adaptation of the business rules in real time. Design/methodology/approach – To tackle the above problems, this paper adopts a bottom-up approach, which puts forward a component model of the business process workflows and business rules based on purely logical specification which allows incremental development of the workflows and indexing of the rules which govern them during the initial acquisition and real-time execution. Results – The paper introduces a component-based event-driven model for development of business workflows which is purely logic based and can be easily implemented using an object-oriented technology together with a formal model for accounting the business rules dependencies together with a new method for incremental indexing of the business rules controlling the workflows. It proposes a two-level inference mechanism as a vehicle for controlling the business process execution and adaptation of the business rules at real time based on propagating the dependencies between the rules. Originality/value –The major achievement of this research is the universal, strictly logic-based event-driven framework for business process modelling and control which allows automatic adaptation of the business rules governing the business workflows based on accounting for their structural dependencies. An additional advantage of the framework is its support for object-oriented technology which can be implemented with enterprise-level quality and efficiency. Although developed primarily for application in construction industry the framework is entirely domain-independent and can be used in other industries, too

Expression and function of FGF-4 in peri-implantation development in mouse embryos

One of the earliest events in mammalian embryogenesis is the formation of the inner cell mass (ICM) and the subse- quent delamination of primitive endoderm. We have found that mRNA for fibroblast growth factor (FGF)-4, but not FGF-3, is expressed in preimplantation mouse blastocysts and that the FGF-4 polypeptide is present in ICM cells. ICM-like embryonal carcinoma cells and embryonic stem cells also express FGF-4. Conversely, differentiated embryonal carcinoma cells in the endoderm lineage express FGF-3, but not FGF-4 mRNA. Although mouse embryos expressed FGF-4 mRNA from the 1-cell stage, embryos cultured from the 2-cell through the blastocyst stage in the presence of recombinant FGF-4 did not respond mitogenically. However, when ICMs that were isolated by immunosurgery were cultured with FGF- 4, the number of morphologically distinct, differentiated parietal endoderm cells growing out onto the coverslip increased, without an increase in the number of undiffer- entiated ICM cells. ICM outgrowths cultured with FGF-4 increased their secretion of 92×103 Mrgelatinase and tissue plasminogen activator, a hallmark of migrating cells. Receptors for FGF-4 (FGFR-3 and FGFR-4) are expressed in all cells of the mouse blastocyst. These findings indicate that FGF-4 produced by undifferentiated ICM cells acts in the peri-implantation period of embryogenesis to influence the production and behavior of endoderm cells derived from them. Key words: fibroblast growth factor, mouse embryogenesis, metall