Modelling Adverse Selection on Electronic Order-Driven Markets

The vast majority of models that decompose the bid/ask spread assume the quote-driven, specialist structure of the NYSE. This paper critically evaluates these models to construct a model specific for an electronic order-driven exchange. The model not only captures adverse selection and the impact of order flows on price discovery but it includes the imbalance of supply and demand inherent in the public limit order book. With this new model we investigate the change to anonymity on the Australian Securities Exchange (ASX). Following the change to anonymity, both adverse selection and the demand/supply imbalance have an increased impact on prices while order flow has a decreased influence, suggesting the change to anonymity has improved market efficiency. The model also uncovers a change in traders’ behavior once their fear of front-running is reduced. We show that the model is stable and robust across high liquidity stocks as well as stocks with as few as 5 trades per day.bid-ask spread models; adverse selection; anonymity

A Multilevel Inverter Bridge Control Structure with Energy Storage Using Model Predictive Control for Flat Systems

The paper presents a novel technique to control the current of an electromagnetic linear actuator fed by a multilevel IGBT voltage inverter with dynamic energy storage. The technique uses a “cascade model predictive control (MPC),” which consists of two MPCs. A predictive control of the trajectory position predicts the optimal current, which is considered to be the desired current for the second MPC controller in which a hysteresis control technique is also integrated. Energy is stored in a capacitor using energy recovery. The current MPC can handle a capacitor voltage higher than the source voltage to guarantee high dynamic current and disturbance compensation. The main contribution of this paper is the design of an optimal control structure that guarantees a capacitor recharge. In this context, the approach is quite new and can represent a general emerging approach allowing to reduce the complexity of the new generation of inverters and, in the meantime, to guarantee precision and acceptable switching frequency. The proposed technique shows very promising results through simulations with real actuator data in an innovative transportation technology

Stringless Guitar

The aim of this project is to improve the design of a typical guitar by designing a digital stringless guitar. Due to the nonlinearities inherent in a guitar, it would be difficult to reproduce guitar tones by summing harmonic components; therefore, digital samples of guitar tones were taken in order to preserve these unique and wonderfully sounding tones. These digital samples were stored in the guitar and used to produce its tones when played. The digital guitar includes fingerboard position sensors as well as strum sensors for each string. The fingerboard position sensors detect the player’s fingers at discrete positions. The strum sensors detect which string is being strummed. All the sensors are durable and may be replaced as the instrument ages. The guitar produces sound similar to a typical guitar without requiring strings or tuning. The stringless guitar has many of the standard features of a typical guitar including a standard guitar audio jack, volume control and tone control. The hope of this project is to produce a novel digital guitar that may be admired by professional and beginner musicians alike

An introductional lecture on chaotic systems through Lorenz attractor and forced Lotka Volterra equation for interdisciplinary education

Is it possible to predict the future? How accurate is the prediction for the future? These questions are fascinating and intriguing ones in particular for young generations who look at their future with curiosity. For a long time, many have tried to quantitatively predict future behavior of systems more accurately with techniques such as time series analysis and derived dynamical models based on observed data. The paper proposes a lecture structure in which elements of chaos, which greatly impacts the predictive capabilities of dynamical models, are introduced through two classical examples of nonlinear dynamical systems, namely Lorenz attractor and Lotka-Volterra equations. In a possible lecture, these two structures are introduced in a basic and intuitive way, followed by equilibria analyses and Lyapunov control approaches. The paper intends to give a possible structure of an interdisciplinary lecture in chaotic systems, for all students in general and non-engineering students in particular, to kindle students’ interest in challenging ideas and models. By presenting an intuitive learning-based approach and the results of the implementation, the paper contributes to the discourse on interdisciplinary education. The lecture is a part of a course within a Complementary Study at Leuphana Unversity of Lüneburg. The material which inspired the proposed lecture structure is taken from the scripts of the Master Complementary Course titled Modelling and Control of Dynamical Systems using Linear and Nonlinear Differential Equations held at Leuphana University of Lüneburg

Binding Parameters and Thermodynamics of the Interaction of the Human Cytomegalovirus DNA Polymerase Accessory Protein, UL44, with DNA: Implications for the Processivity Mechanism

The mechanisms of processivity factors of herpesvirus DNA polymerases remain poorly understood. The proposed processivity factor for human cytomegalovirus DNA polymerase is a DNA-binding protein, UL44. Previous findings, including the crystal structure of UL44, have led to the hypothesis that UL44 binds DNA as a dimer via lysine residues. To understand how UL44 interacts with DNA, we used filter-binding and electrophoretic mobility shift assays and isothermal titration calorimetry (ITC) analysis of binding to oligonucleotides. UL44 bound directly to double-stranded DNA as short as 12 bp, with apparent dissociation constants in the nanomolar range for DNAs > 18 bp, suggesting a minimum DNA length for UL44 interaction. UL44 also bound single-stranded DNA, albeit with lower affinity, and for either single- or double-stranded DNA, there was no apparent sequence specificity. ITC analysis revealed that UL44 binds to duplex DNA as a dimer. Binding was endothermic, indicating an entropically driven process, likely due to release of bound ions. Consistent with this hypothesis, analysis of the relationship between binding and ionic strength indicated that, on average, $4 \pm 1$ monovalent ions are released in the interaction of each monomer of UL44 with DNA. The results taken together reveal interesting implications for how UL44 may mediate processivity