Let\u27s decode: Inservice manual

This manual contains inservice material that was prepared for a research project that came to be known as Let\u27s Decode. My motive for publishing the material in this form is to make it available to other teachers who may wish to apply the same principles and procedures in their own classrooms. Typically, they will be teachers who are concerned about children experiencing difficulty learning to read, and teachers responsible for students with special education needs. I am confident that regular classroom teachers will also find the material valuable for all children in the early stages of learning to read. My ardent hope is that by incorporating systematic decoding instruction into their regular reading programmes, teachers may be able to prevent the later reading difficulties that so many children experience

Oscillatory Behavior in a Model of Non-Markovian Mean Field Interacting Spins

We analyze a non-Markovian mean field interacting spin system, related to the Curie\u2013Weiss model. We relax the Markovianity assumption by replacing the memoryless distribution of the waiting times of a classical spin-flip dynamics with a distribution with memory. The resulting stochastic evolution for a single particle is a spin-valued renewal process, an example of a two-state semi-Markov process. We associate to the individual dynamics an equivalent Markovian description, which is the subject of our analysis. We study a corresponding interacting particle system, where a mean field interaction-depending on the magnetization of the system-is introduced as a time scaling on the waiting times between two successive particle\u2019s jumps. Via linearization arguments on the Fokker\u2013Planck mean field limit equation, we give evidence of emerging periodic behavior. Specifically, numerical analysis on the discrete spectrum of the linearized operator, characterized by the zeros of an explicit holomorphic function, suggests the presence of a Hopf bifurcation for a critical value of the temperature. The presence of a Hopf bifurcation in the limit equation matches the emergence of a periodic behavior obtained by simulating the N-particle system

Oscillatory Behavior in a Model of Non-Markovian Mean Field Interacting Spins

We analyze a non-Markovian mean field interacting spin system, related to the Curie\u2013Weiss model. We relax the Markovianity assumption by replacing the memoryless distribution of the waiting times of a classical spin-flip dynamics with a distribution with memory. The resulting stochastic evolution for a single particle is a spin-valued renewal process, an example of a two-state semi-Markov process. We associate to the individual dynamics an equivalent Markovian description, which is the subject of our analysis. We study a corresponding interacting particle system, where a mean field interaction-depending on the magnetization of the system-is introduced as a time scaling on the waiting times between two successive particle\u2019s jumps. Via linearization arguments on the Fokker\u2013Planck mean field limit equation, we give evidence of emerging periodic behavior. Specifically, numerical analysis on the discrete spectrum of the linearized operator, characterized by the zeros of an explicit holomorphic function, suggests the presence of a Hopf bifurcation for a critical value of the temperature. The presence of a Hopf bifurcation in the limit equation matches the emergence of a periodic behavior obtained by simulating the N-particle system

Metastates in mean-field models with random external fields generated by Markov chains

We extend the construction by Kuelske and Iacobelli of metastates in finite-state mean-field models in independent disorder to situations where the local disorder terms are are a sample of an external ergodic Markov chain in equilibrium. We show that for non-degenerate Markov chains, the structure of the theorems is analogous to the case of i.i.d. variables when the limiting weights in the metastate are expressed with the aid of a CLT for the occupation time measure of the chain. As a new phenomenon we also show in a Potts example that, for a degenerate non-reversible chain this CLT approximation is not enough and the metastate can have less symmetry than the symmetry of the interaction and a Gaussian approximation of disorder fluctuations would suggest.Comment: 20 pages, 2 figure

β-Phase Morphology in Ordered Poly(9,9-dioctylfluorene) Nanopillars by Template Wetting Method

An efficient method based in template wetting is applied for fabrication of ordered Poly(9,9-dioctylfluorene) (PFO) nanopillars with β-phase morphology. In this process, nanoporous alumina obtained by anodization process is used as template. PFO nanostructures are prepared under ambient conditions via infiltration of the polymeric solution into the pores of the alumina with an average pore diameter of 225 nm and a pore depth of 500 nm. The geometric features of the resulting structures are characterized with environmental scanning electron microscopy (ESEM), luminescence fluorimeter (PL) and micro μ-X-ray diffractometer (μ-XRD). The characterization demonstrates the β-phase of the PFO in the nanopillars fabricated. Furthermore, the PFO nanopillars are characterized by Raman spectroscopy to study the polymer conformation. These ordered nanostructures can be used in optoelectronic applications such as polymer light-emitting diodes, sensors and organic solar cells

MicroMotility: State of the art, recent accomplishments and perspectives on the mathematical modeling of bio-motility at microscopic scales

Mathematical modeling and quantitative study of biological motility (in particular, of motility at microscopic scales) is producing new biophysical insight and is offering opportunities for new discoveries at the level of both fundamental science and technology. These range from the explanation of how complex behavior at the level of a single organism emerges from body architecture, to the understanding of collective phenomena in groups of organisms and tissues, and of how these forms of swarm intelligence can be controlled and harnessed in engineering applications, to the elucidation of processes of fundamental biological relevance at the cellular and sub-cellular level. In this paper, some of the most exciting new developments in the fields of locomotion of unicellular organisms, of soft adhesive locomotion across scales, of the study of pore translocation properties of knotted DNA, of the development of synthetic active solid sheets, of the mechanics of the unjamming transition in dense cell collectives, of the mechanics of cell sheet folding in volvocalean algae, and of the self-propulsion of topological defects in active matter are discussed. For each of these topics, we provide a brief state of the art, an example of recent achievements, and some directions for future research

Learning-based hierarchical control of water reservoir systems

The optimal control of a water reservoir system represents a challenging problem, due to uncertain hydrologic inputs and the need to adapt to changing environment and varying control objectives. In this work, we propose a real-time learning-based control strategy based on a hierarchical predictive control architecture. Two control loops are implemented: the inner loop is aimed to make the overall dynamics similar to an assigned linear model through data-driven control design, then the outer economic model-predictive controller compensates for model mismatches, enforces suitable constraints, and boosts the tracking performance. The effectiveness of the proposed approach is illustrated on an accurate simulator of the Hoa Binh reservoir in Vietnam. Results show that the proposed approach outperforms stochastic dynamic programming

Design and Implementation of a MPC-based Rear-Wheel Steering Controller for Sports Cars

Active rear-wheel steering is an effective technology to improve the cornering performance of vehicles, enhancing both handling and stability. In this study, a MPC-based rear-wheel steering controller for sport driving conditions is proposed. High performance is achieved by an accurate choice of the linear time-varying (LTV) predictive model. All the fundamental aspects of lateral dynamics, such as tire force saturation, tire relaxation, aerodynamic downforce and load transfer are taken into account. Simulation results on a multi-body vehicle simulator and the details of the real-time implementation complete the paper

A comparison between model-based and data-driven design of an active stability control system for two-wheeled vehicles

The design of an active stability control system for twowheeled vehicles is a fully open problem and it constitutes a challenging task due to the complexity of two-wheeled vehicles dynamics and the strong interaction between the vehicle and the driver. This paper describes and compares two different methods, a model-based and a data-driven approach, to tune a Multi- Input-Multi-Output controller which allows to enhance the safety while guaranteeing a good driving feeling. The two strategies are tested on a multibody motorcycle simulator on challenging maneuvers such as kick-back and strong braking while cornering at high speed