CMOS Hyperbolic Sine ELIN filters for low/audio frequency biomedical applications

Hyperbolic-Sine (Sinh) filters form a subclass of Externally-Linear-Internally-Non- Linear (ELIN) systems. They can handle large-signals in a low power environment under half the capacitor area required by the more popular ELIN Log-domain filters. Their inherent class-AB nature stems from the odd property of the sinh function at the heart of their companding operation. Despite this early realisation, the Sinh filtering paradigm has not attracted the interest it deserves to date probably due to its mathematical and circuit-level complexity. This Thesis presents an overview of the CMOS weak inversion Sinh filtering paradigm and explains how biomedical systems of low- to audio-frequency range could benefit from it. Its dual scope is to: consolidate the theory behind the synthesis and design of high order Sinh continuous–time filters and more importantly to confirm their micro-power consumption and 100+ dB of DR through measured results presented for the first time. Novel high order Sinh topologies are designed by means of a systematic mathematical framework introduced. They employ a recently proposed CMOS Sinh integrator comprising only p-type devices in its translinear loops. The performance of the high order topologies is evaluated both solely and in comparison with their Log domain counterparts. A 5th order Sinh Chebyshev low pass filter is compared head-to-head with a corresponding and also novel Log domain class-AB topology, confirming that Sinh filters constitute a solution of equally high DR (100+ dB) with half the capacitor area at the expense of higher complexity and power consumption. The theoretical findings are validated by means of measured results from an 8th order notch filter for 50/60Hz noise fabricated in a 0.35μm CMOS technology. Measured results confirm a DR of 102dB, a moderate SNR of ~60dB and 74μW power consumption from 2V power supply

INVESTIGATING THE ROLES OF LACTATE DEHYDROGENASES IN THE RICE BLAST FUNGUS MAGNAPORTHE ORYZAE

Magnaporthe oryzae is a filamentous ascomycete fungus that causes rice blast, the most destructive disease of rice worldwide. Upon attachment of pathogen spores to the plant surface, a specialized cell called an appressorium differentiates from the germ tubes to facilitate fungal entry into plant tissues using mechanical force. The appressorium development is fuelled by nutrient reserves carried in spores mainly in the form of lipids and glycogen. Previous studies suggest that breakdown of lipids and glycogen, primarily restricted to the peroxisomes and the cytosol respectively, culminates in production of pyruvate. However, downstream metabolism of pyruvate and its coordination with mitochondrial activities remain elusive. In this study, we showed that D-lactate, interconvertible with pyruvate by activities of lactate dehydrogenases, is a central metabolite utilized during spore germination and appressorium development. Genome-wide analysis of five lactate dehydrogenase genes in M. oryzae demonstrated that a D-lactate dehydrogenase, namely MoDLD1, located on the mitochondrial inner membrane, is responsible for conversion of D-lactate to pyruvate. Targeted replacement of MoDLD1 resulted in failure of efficient appressorium formation, which was associated with inability to utilize lipids and glycogen in fungal spores, and consequently the loss of fungal pathogenicity. In summary, our findings reveal a novel metabolic pathway operated by MoDLD1 that bridges metabolite flow to the mitochondria, and contributes to the fungal development and virulence of M. oryzae

A SIMD architecture for hard real-time systems

Emerging safety-critical systems require high-performance data-parallel architectures and, problematically, ones that can guarantee tight and safe worst-case execution times. Given the complexity of existing architectures like GPUs, it is unlikely that sufficiently accurate models and algorithms for timing analysis will emerge in the foreseeable future. This motivates a clean-slate approach to designing a real-time data-parallel architecture. In this work I present Sim-D: a wide-SIMD architecture for hard real-time systems. Similar to GPUs, Sim-D performs hardware strip-mining to schedule the work for a compute kernel in entities called work-groups. Sim-D schedules the work for each work-group as a sequence of uninterruptible access- and execute program phases, interleaving the phases of two work-groups. By providing performance isolation between the memory- and compute resources, the execution time of each phase can be tightly bound through static analysis. I present a predictable closed-page DRAM controller that processes requests for large 1D- and 2D blocks of data, as well as indirect indexed transfers. These large transfers coalesce the data requests of a whole work-group. For a linear 4KiB transfer over a 64-bit data bus, the utilisation provably exceeds 78% for DDR4-3200AA DRAM. For 2D blocks, a well-chosen tiling configuration can achieve near-similar efficiency. I show that bounds on the execution time of indexed transfers are pessimistic by nature, but propose a novel snoopy indexed transfer mechanism that permits more reasonable bounds when the buffer size is limited. Finally, I present a worst-case execution time calculation algorithm for Sim-D. This algorithm is paired with two hardware work-group scheduling policies that deterministically reduce run-time variance. The worst-case execution time analysis algorithm combines static control flow analysis with a simulation-based cost model for execution and DRAM transfers. Its key novelty is the addition of a stage that considers work-group scheduling effects. I show that the work-group scheduling policies degrade performance on average by 8.9%, but permit the calculation of worst-case execution time bounds that are tight within 14.3% on average for benchmarks that avoid inefficient indexed transfers

Numerical Simulation

Nowadays mathematical modeling and numerical simulations play an important role in life and natural science. Numerous researchers are working in developing different methods and techniques to help understand the behavior of very complex systems, from the brain activity with real importance in medicine to the turbulent flows with important applications in physics and engineering. This book presents an overview of some models, methods, and numerical computations that are useful for the applied research scientists and mathematicians, fluid tech engineers, and postgraduate students

Optimal Control of Hybrid Systems and Renewable Energies

This book is a collection of papers covering various aspects of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). In particular, attention is focused both on the optimal control of new technologies and on their integration in buildings, microgrids, and energy markets. The examples presented in this book are among the most promising technologies for satisfying an increasing share of thermal and electrical demands with renewable sources: from solar cooling plants to offshore wind generation; hybrid plants, combining traditional and renewable sources, are also considered, as well as traditional and innovative storage systems. Innovative solutions for transportation systems are also explored for both railway infrastructures and advanced light rail vehicles. The optimization and control of new solutions for the power network are addressed in detail: specifically, special attention is paid to microgrids as new paradigms for distribution networks, but also in other applications (e.g., shipboards). Finally, optimization and simulation models within SCADA and energy management systems are considered. This book is intended for engineers, researchers, and practitioners that work in the field of energy, smart grid, renewable resources, and their optimization and control

A framework for understanding what algebraic thinking is

In relation to the learning of mathematics, algebra occupies a very special place, both because it is in itself a powerful tool for solving problems and modelling situations, and also because it is essential to the learning of so many other parts of mathematics. On the other hand, the teaching of algebra has proven to be a difficult task to accomplish, to the extent of algebra itself being sometimes considered the border line which separates those who can from those who cannot learn mathematics. A review of the research literature shows that no clear characterisation of the algebraic activity has been available, and that for this reason research has produced only a local understanding of aspects of the learning of algebra. The research problem investigated in this dissertation is precisely to provide a clear characterisation of the algebraic activity. Our research has three parts: (i) a theoretical characterisation of algebraic thinking, which is shown to be distinct from algebra; in our framework we propose that algebraic thinking IS • thinking aritmnetically, • thinking internally, and • thinking analytically. and each of those characteristics are explained and analysed; (ii) a study of the historical development of algebra and of algebraic thinking; in this study it is shown that our characterisation of algebraic thinking provides an adequate framework for understanding the tensions involved in the production of an algebraic knowledge in different historically situated mathematical cultures, and also that the characteristics of the algebraic knowledge of each of those mathematical cultures can only be understood in the context of their broader assumptions, particularly in relation to the concept of number. (iii) an experimental study, in which we examine the models used by secondary school students, both from Brazil and from England, to solve "algebraic verbal problems" and "secret number problems"; it is shown that our characterisation of algebraic thinking provides an adequate framework for distinguishing different types of solutions, as well as for identifying the sources of errors and difficulties in those students' solutions. The key notions elicited by our research are those of: (a) intrasystemic and extrasystemic meaning; (b) different modes of thinking as operating within different Semantical Fields; (c) the development of an algebraic mode of thinking as a process of cultural immersion- both in history and for individual learners; (d) ontological and symbolical conceptions of number, and their relationship to algebraic thinking and other modes of manipulating arithmetical relationships; (e) the arithmetical articulation as a central aspect of algebraic thinking; and, (f) the place and role of algebraic notation in relation to algebraic thinking. The findings of our research show that although it can facilitate the learning of certain early aspects of algebra, the use of non-algebraic models-such as the scale balance or areas-to "explain" particular algebraic facts, contribute, in fact, to the constitution of obstacles to the development of an algebraic mode of thinking; not only because the sources of meaning in those models are completely distinct from those in algebraic thinking, but also because the direct manipulation of numbers as measures, by manipulating the objects measured by the numbers, is deeply conflicting with a symbolic understanding of number, which is a necessary aspect of algebraic thinking

Combining SOA and BPM Technologies for Cross-System Process Automation

This paper summarizes the results of an industry case study that introduced a cross-system business process automation solution based on a combination of SOA and BPM standard technologies (i.e., BPMN, BPEL, WSDL). Besides discussing major weaknesses of the existing, custom-built, solution and comparing them against experiences with the developed prototype, the paper presents a course of action for transforming the current solution into the proposed solution. This includes a general approach, consisting of four distinct steps, as well as specific action items that are to be performed for every step. The discussion also covers language and tool support and challenges arising from the transformation

A framework for understanding what algebraic thinking is

In relation to the learning of mathematics, algebra occupies a very special place, both because it is in itself a powerful tool for solving problems and modelling situations, and also because it is essential to the learning of so many other parts of mathematics. On the other hand, the teaching of algebra has proven to be a difficult task to accomplish, to the extent of algebra itself being sometimes considered the border line which separates those who can from those who cannot learn mathematics. A review of the research literature shows that no clear characterisation of the algebraic activity has been available, and that for this reason research has produced only a local understanding of aspects of the learning of algebra. The research problem investigated in this dissertation is precisely to provide a clear characterisation of the algebraic activity. Our research has three parts: (i) a theoretical characterisation of algebraic thinking, which is shown to be distinct from algebra; in our framework we propose that algebraic thinking IS • thinking aritmnetically, • thinking internally, and • thinking analytically. and each of those characteristics are explained and analysed; (ii) a study of the historical development of algebra and of algebraic thinking; in this study it is shown that our characterisation of algebraic thinking provides an adequate framework for understanding the tensions involved in the production of an algebraic knowledge in different historically situated mathematical cultures, and also that the characteristics of the algebraic knowledge of each of those mathematical cultures can only be understood in the context of their broader assumptions, particularly in relation to the concept of number. (iii) an experimental study, in which we examine the models used by secondary school students, both from Brazil and from England, to solve "algebraic verbal problems" and "secret number problems"; it is shown that our characterisation of algebraic thinking provides an adequate framework for distinguishing different types of solutions, as well as for identifying the sources of errors and difficulties in those students' solutions. The key notions elicited by our research are those of: (a) intrasystemic and extrasystemic meaning; (b) different modes of thinking as operating within different Semantical Fields; (c) the development of an algebraic mode of thinking as a process of cultural immersion- both in history and for individual learners; (d) ontological and symbolical conceptions of number, and their relationship to algebraic thinking and other modes of manipulating arithmetical relationships; (e) the arithmetical articulation as a central aspect of algebraic thinking; and, (f) the place and role of algebraic notation in relation to algebraic thinking. The findings of our research show that although it can facilitate the learning of certain early aspects of algebra, the use of non-algebraic models-such as the scale balance or areas-to "explain" particular algebraic facts, contribute, in fact, to the constitution of obstacles to the development of an algebraic mode of thinking; not only because the sources of meaning in those models are completely distinct from those in algebraic thinking, but also because the direct manipulation of numbers as measures, by manipulating the objects measured by the numbers, is deeply conflicting with a symbolic understanding of number, which is a necessary aspect of algebraic thinking