Design and Modeling of an Active Five-Axis Compliant Micromanipulator

This paper presents the design and modeling of an active five-axis compliant micromanipulator whose tip orientation can be independently controlled by large angles about two axes and the tip-position can be controlled in three dimensions. These features enable precise control of the contact point of the tip and the tip-sample interaction forces with three-dimensional nanoscale objects, including those features that are conventionally inaccessible. Control of the tip-motion is realized by means of electromagnetic actuation combined with a novel kinematic and structural design of the micromanipulator, which, in addition, also ensures compatibility with existing high-resolution motion-measurement systems. The design and analysis of the manipulator structure and those of the actuation system are first presented. Quasi-static and dynamic lumped-parameter (LP) models are then derived for the five-axis compliant micromanipulator. Finite element (FE) analysis is employed to validate these models, which are subsequently used to study the effects of tip orientation on the mechanical characteristics of the five-axis micromanipulator. Finally, a prototype of the designed five-axis manipulator is fabricated by means of focused ion-beam milling (FIB).

Rollover-Preventive Force Synthesis at Active Suspensions in a Vehicle Performing a Severe Maneuver With Wheels Lifted Off

Among the intelligent safety technologies for road vehicles, active suspensions controlled by embedded computing elements for preventing rollover have received a lot of attention. The existing models for synthesizing and allocating forces in such suspensions are conservatively based on the constraints that are valid until no wheels lift off the ground. However, the fault tolerance of the rollover-preventive systems can be enhanced if the smart/active suspensions can intervene in the more severe situation in which the wheels have just lifted off the ground. The difficulty in computing control in the last situation is that the vehicle dynamics then passes into the regime that yields a model involving disjunctive constraints on the dynamics. Simulation of dynamics with disjunctive constraints in this context becomes necessary to estimate, synthesize, and allocate the intended hardware realizable forces in an active suspension. In this paper, we give an algorithm for the previously mentioned problem by solving it as a disjunctive dynamic optimization problem. Based on this, we synthesize and allocate the roll-stabilizing time-dependent active suspension forces in terms of sensor output data. We show that the forces obtained from disjunctive dynamics are comparable with existing force allocations and, hence, are possibly realizable in the existing hardware framework toward enhancing the safety and fault tolerance.

Probabilistic graphical models for semi-supervised traffic classification

Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.

Synthetic molecular machines for active self-assembly : prototype algorithms, designs, and experimental study

Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of “active self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

Models of the Oxygen-Evolving Complex of Photosystem II

In the five chapters that follow, I delineate my efforts over the last five years to synthesize structurally and chemically relevant models of the Oxygen Evolving Complex (OEC) of Photosystem II. The OEC is nature’s only water oxidation catalyst, in that it forms the dioxygen in our atmosphere necessary for oxygenic life. Therefore understanding its structure and function is of deep fundamental interest and could provide design elements for artificial photosynthesis and manmade water oxidation catalysts. Synthetic endeavors towards OEC mimics have been an active area of research since the mid 1970s and have mutually evolved alongside biochemical and spectroscopic studies, affording ever-refined proposals for the structure of the OEC and the mechanism of water oxidation. This research has culminated in the most recent proposal: a low symmetry Mn₄CaO₅ cluster with a distorted Mn₃CaO₄ cubane bridged to a fourth, dangling Mn. To give context for how my graduate work fits into this rich history of OEC research, Chapter 1 provides a historical timeline of proposals for OEC structure, emphasizing the role that synthetic Mn and MnCa clusters have played, and ending with our Mn₃CaO₄ heterometallic cubane complexes.

In Chapter 2, the triarylbenzene ligand framework used throughout my work is introduced, and trinuclear clusters of Mn, Co, and Ni are discussed. The ligand scaffold consistently coordinates three metals in close proximity while leaving coordination sites open for further modification through ancillary ligand binding. The ligands coordinated could be varied, with a range of carboxylates and some less coordinating anions studied. These complexes’ structures, magnetic behavior, and redox properties are discussed.

Chapter 3 explores the redox chemistry of the trimanganese system more thoroughly in the presence of a fourth Mn equivalent, finding a range of oxidation states and oxide incorporation dependent on oxidant, solvent, and Mn salt. Oxidation states from Mn^II₄ to Mn^IIIMn^IV₃ were observed, with 1-4 O^2– ligands incorporated, modeling the photoactivation of the OEC. These complexes were studied by X-ray diffraction, EPR, XAS, magnetometry, and CV.

As Ca²⁺ is a necessary component of the OEC, Chapter 4 discusses synthetic strategies for making highly structurally accurate models of the OEC containing both Mn and Ca in the Mn₃CaO₄ cubane + dangling Mn geometry. Structural and electrochemical characterization of the first Mn₃CaO₄ heterometallic cubane complex— and comparison to an all-Mn Mn₄O₄ analog—suggests a role for Ca²⁺ in the OEC. Modification of the Mn₃CaO₄ system by ligand substitution affords low symmetry Mn₃CaO₄ complexes that are the most accurate models of the OEC to date.

Finally, in Chapter 5 the reactivity of the Mn₃CaO₄ cubane complexes toward O- atom transfer is discussed. The metal M strongly affects the reactivity. The mechanisms of O-atom transfer and water incorporation from and into Mn₄O₄ and Mn₄O₃ clusters, respectively, are studied through computation and ¹⁸O-labeling studies. The μ3-oxos of the Mn₄O₄ system prove fluxional, lending support for proposals of O^2– fluxionality within the OEC.

A modelling approach to the development of an active management strategy for the Queen Elizabeth II reservoir

This article outlines the outcome of work that set out to provide one of the specified integral contributions to the overarching objectives of the EU- sponsored LIFE98 project described in this volume. Among others, these included a requirement to marry automatic monitoring and dynamic modelling approaches in the interests of securing better management of water quality in lakes and reservoirs. The particular task given to us was to devise the elements of an active management strategy for the Queen Elizabeth II Reservoir. This is one of the larger reservoirs supplying the population of the London area: after purification and disinfection, its water goes directly to the distribution network and to the consumers. The quality of the water in the reservoir is of primary concern, for the greater is the content of biogenic materials, including phytoplankton, then the more prolonged is the purification and the more expensive is the treatment. Whatever good that phytoplankton may do by way of oxygenation and oxidative purification, it is eventually relegated to an impurity that has to be removed from the final product. Indeed, it has been estimated that the cost of removing algae and microorganisms from water represents about one quarter of its price at the tap. In chemically fertile waters, such as those typifying the resources of the Thames Valley, there is thus a powerful and ongoing incentive to be able to minimise plankton growth in storage reservoirs. Indeed, the Thames Water company and its predecessor undertakings, have a long and impressive history of confronting and quantifying the fundamentals of phytoplankton growth in their reservoirs and of developing strategies for operation and design to combat them. The work to be described here follows in this tradition. However, the use of the model PROTECH-D to investigate present phytoplankton growth patterns in the Queen Elizabeth II Reservoir questioned the interpretation of some of the recent observations. On the other hand, it has reinforced the theories underpinning the original design of this and those Thames-Valley storage reservoirs constructed subsequently. The authors recount these experiences as an example of how simulation models can hone the theoretical base and its application to the practical problems of supplying water of good quality at economic cost, before the engineering is initiated.

Multilayer Active Shell Mirrors

This thesis presents a novel active mirror technology based on carbon fiber composites and replication manufacturing processes. Multiple additional layers are implemented into the structure in order to provide the reflective layer, actuation capabilities and electrode routing. The mirror is thin, lightweight, and has large actuation capabilities. These features, along with the associated manufacturing processes, represent a significant change in design compared to traditional optics. Structural redundancy in the form of added material or support structures is replaced by thin, unsupported lightweight substrates with large actuation capabilities.

Several studies motivated by the desire to improve as-manufactured figure quality are performed. Firstly, imperfections in thin CFRP laminates and their effect on post-cure shape errors are studied. Numerical models are developed and compared to experimental measurements on flat laminates. Techniques to mitigate figure errors for thicker laminates are also identified. A method of properly integrating the reflective facesheet onto the front surface of the CFRP substrate is also presented. Finally, the effect of bonding multiple initially flat active plates to the backside of a curved CFRP substrate is studied. Figure deformations along with local surface defects are predicted and characterized experimentally. By understanding the mechanics behind these processes, significant improvements to the overall figure quality have been made.

Studies related to the actuation response of the mirror are also performed. The active properties of two materials are characterized and compared. Optimal active layer thicknesses for thin surface-parallel schemes are determined. Finite element simulations are used to make predictions on shape correction capabilities, demonstrating high correctabiliity and stroke over low-order modes. The effect of actuator saturation is studied and shown to significantly degrade shape correction performance.

The initial figure as well as actuation capabilities of a fully-integrated active mirror prototype are characterized experimentally using a Projected Hartmann test. A description of the test apparatus is presented along with two verification measurements. The apparatus is shown to accurately capture both high-amplitude low spatial-frequency figure errors as well as those at lower amplitudes but higher spatial frequencies. A closed-loop figure correction is performed, reducing figure errors by 94%.

Active reservoir management: a model solution

Steady-state procedures, of their very nature, cannot deal with dynamic situations. Statistical models require extensive calibration, and predictions often have to be made for environmental conditions which are often outside the original calibration conditions. In addition, the calibration requirement makes them difficult to transfer to other lakes. To date, no computer programs have been developed which will successfully predict changes in species of algae. The obvious solution to these limitations is to apply our limnological knowledge to the problem and develop functional models, so reducing the requirement for such rigorous calibration. Reynolds has proposed a model, based on fundamental principles of algal response to environmental events, which has successfully recreated the maximum observed biomass, the timing of events and a fair simulation of the species succession in several lakes. A forerunner of this model was developed jointly with Welsh Water under contract to Messrs. Wallace Evans and Partners, for use in the Cardiff Bay Barrage study. In this paper the authors test a much developed form of this original model against a more complex data-set and, using a simple example, show how it can be applied as an aid in the choice of management strategy for the reduction of problems caused by eutrophication. Some further developments of the model are indicated.

Bayesian Active Learning for Classification and Preference Learning

Information theoretic active learning has been widely studied for probabilistic models. For simple regression an optimal myopic policy is easily tractable. However, for other tasks and with more complex models, such as classification with nonparametric models, the optimal solution is harder to compute. Current approaches make approximations to achieve tractability. We propose an approach that expresses information gain in terms of predictive entropies, and apply this method to the Gaussian Process Classifier (GPC). Our approach makes minimal approximations to the full information theoretic objective. Our experimental performance compares favourably to many popular active learning algorithms, and has equal or lower computational complexity. We compare well to decision theoretic approaches also, which are privy to more information and require much more computational time. Secondly, by developing further a reformulation of binary preference learning to a classification problem, we extend our algorithm to Gaussian Process preference learning.

Numerical investigation of the active role of the actin cytoskeleton in the compression resistance of cells.

Numerous in-vitro studies have established that cells react to their physical environment and to applied mechanical loading. However, the mechanisms underlying such phenomena are poorly understood. Previous modelling of cell compression considered the cell as a passive homogenous material, requiring an artificial increase in the stiffness of spread cells to replicate experimentally measured forces. In this study, we implement a fully 3D active constitutive formulation that predicts the distribution, remodelling, and contractile behaviour of the cytoskeleton. Simulations reveal that polarised and axisymmetric spread cells contain stress fibres which form dominant bundles that are stretched during compression. These dominant fibres exert tension; causing an increase in computed compression forces compared to round cells. In contrast, fewer stress fibres are computed for round cells and a lower resistance to compression is predicted. The effect of different levels of cellular contractility associated with different cell phenotypes is also investigated. Highly contractile cells form more dominant circumferential stress fibres and hence provide greater resistance to compression. Computed predictions correlate strongly with published experimentally observed trends of compression resistance as a function of cellular contractility and offer an insight into the link between cell geometry, stress fibre distribution and contractility, and cell deformability. Importantly, it is possible to capture the behaviour of both round and spread cells using a given, unchanged set of material parameters for each cell type. Finally, it is demonstrated that stress distributions in the cell cytoplasm and nucleus computed using the active formulation differ significantly from those computed using passive material models.

Optimisation of passive and semi-active heavy vehicle suspensions

An investigation into the potential for reducing road damage by optimising the design of heavy vehicle suspensions is described. In the first part of the paper two simple mathematical models are used to study the optimisation of conventional passive suspensions. Simple modifications are made to the steel spring suspension of a tandem axle trailer and it is found experimentally that RMS dynamic tyre forces can be reduced by 15% and theoretical road damage by 5.2%. A mathematical model of an air-sprung articulated vehicle is validated, and its suspension is optimised according to the simple models. This vehicle generates about 9% less damage than the leaf-sprung vehicle in the unmodified state and it is predicted that, for the operating conditions examined, the road damage caused by this vehicle can be reduced by a further 5.4%. Finally, it is shown experimentally that computer-controlled semi-active dampers have the potential to reduce road damage by a further 5-6%, compared to an air suspension with optimum passive damping. © Copyright 1994 Society of Automotive Engineers, Inc.

The user-value of rural electrification: An analysis and adoption of existing models and theories

User-value is a determining factor for product acceptance in product design. Research on rural electrification to date, however, does not draw sufficient attention to the importance of user-value with regard to the overall success of a project. This is evident from the analysis of project reports and applicable indicators from agencies active in the sector. Learning from the design, psychology and sociology literatures, it is important that rural electrification projects incorporate the value perception of the end-user and extend their success beyond the commonly used criteria of financial value, the appropriateness of the technology, capacity building and technology uptake. Creating value for the end-user is particularly important for project acceptance and the sustainability of a scheme once it has been handed over to the local community. In this research paper, existing theories and models of value-theory are transposed and applied to community operated rural electrification schemes and a user-value framework is developed. Furthermore, the importance of value to the end-user is clarified. Current literature on product design reveals that user-value has different properties, many of which are applicable to rural electrification. Five value pillars and their sub-categories important for the users of rural electrification projects are identified, namely: functional; social significance; epistemic; emotional; and cultural values. These pillars provide the main structure for the conceptual framework developed in this research paper. It is proposed that by targeting the values of the end-user, the key factors of user-value applicable to rural electrification projects will be identified and the sustainability of the project will be better ensured. © 2014 The Authors.

Study of remote sensing based parameter uncertainty in Production Efficiency Models

The remote sensing based Production Efficiency Models (PEMs), springs from the concept of "Light Use Efficiency" and has been applied more and more in estimating terrestrial Net Primary Productivity (NPP) regionally and globally. However, global NPP estimates vary greatly among different models in different data sources and handling methods. Because direct observation or measurement of NPP is unavailable at global scale, the precision and reliability of the models cannot be guaranteed. Though, there are ways to improve the accuracy of the models from input parameters. In this study, five remote sensing based PEMs have been compared: CASA, GLO-PEM, TURC, SDBM and VPM. We divided input parameters into three categories, and analyzed the uncertainty of (1) vegetation distribution, (2) fraction of photosynthetically active radiation absorbed by the canopy (fPAR) and (3) light use efficiency (e). Ground measurements of Hulunbeier typical grassland and meteorology measurements were introduced for accuracy evaluation. Results show that a real-time, more accurate vegetation distribution could significantly affect the accuracy of the models, since it's applied directly or indirectly in all models and affects other parameters simultaneously. Higher spatial and spectral resolution remote sensing data may reduce uncertainty of fPAR up to 51.3%, which is essential to improve model accuracy.

Toward autonomous measurements of photosynthetic electron transport rates: An evaluation of active fluorescence-based measurements of photochemistry

This study presents a methods evaluation and intercalibration of active fluorescence-based measurements of the quantum yield ( inline image) and absorption coefficient ( inline image) of photosystem II (PSII) photochemistry. Measurements of inline image, inline image, and irradiance (E) can be scaled to derive photosynthetic electron transport rates ( inline image), the process that fuels phytoplankton carbon fixation and growth. Bio-optical estimates of inline image and inline image were evaluated using 10 phytoplankton cultures across different pigment groups with varying bio-optical absorption characteristics on six different fast-repetition rate fluorometers that span two different manufacturers and four different models. Culture measurements of inline image and the effective absorption cross section of PSII photochemistry ( inline image, a constituent of inline image) showed a high degree of correspondence across instruments, although some instrument-specific biases are identified. A range of approaches have been used in the literature to estimate inline image and are evaluated here. With the exception of ex situ inline image estimates from paired inline image and PSII reaction center concentration ( inline image) measurements, the accuracy and precision of in situ inline image methodologies are largely determined by the variance of method-specific coefficients. The accuracy and precision of these coefficients are evaluated, compared to literature data, and discussed within a framework of autonomous inline image measurements. This study supports the application of an instrument-specific calibration coefficient ( inline image) that scales minimum fluorescence in the dark ( inline image) to inline image as both the most accurate in situ measurement of inline image, and the methodology best suited for highly resolved autonomous inline image measurements.