Cooperative kinking at distant sites in mechanically stressed DNA.

In cells, DNA is routinely subjected to significant levels of bending and twisting. In some cases, such as under physiological levels of supercoiling, DNA can be so highly strained, that it transitions into non-canonical structural conformations that are capable of relieving mechanical stress within the template. DNA minicircles offer a robust model system to study stress-induced DNA structures. Using DNA minicircles on the order of 100 bp in size, we have been able to control the bending and torsional stresses within a looped DNA construct. Through a combination of cryo-EM image reconstructions, Bal31 sensitivity assays and Brownian dynamics simulations, we have been able to analyze the effects of biologically relevant underwinding-induced kinks in DNA on the overall shape of DNA minicircles. Our results indicate that strongly underwound DNA minicircles, which mimic the physical behavior of small regulatory DNA loops, minimize their free energy by undergoing sequential, cooperative kinking at two sites that are located about 180° apart along the periphery of the minicircle. This novel form of structural cooperativity in DNA demonstrates that bending strain can localize hyperflexible kinks within the DNA template, which in turn reduces the energetic cost to tightly loop DNA.

The changing relationship between commodity prices and equity prices in commodity exporting

We explore the linkage between equity and commodity markets, focusing in particular on its evolution over time. We document that a country's equity market valuehas significant out-of-sample predictive ability for the future global commodity priceindex for several primary commodity-exporting countries. The out-of-sample predictive ability of the equity market appears around 2000s. The results are robust to usingseveral control variables as well as firm-level equity data. Finally, our results indicatethat exchange rates are a better predictor of commodity prices than equity markets,especially at very short horizons.

Control and Simulation of Batch Crystallization

Concerning process control of batch cooling crystallization the present work focused on the cooling profile and seeding technique. Secondly, the influence of additives on batch-wise precipitation process was investigated. Moreover, a Computational Fluid Dynamics (CFD) model for simulation of controlled batch cooling crystallization was developed. A novel cooling model to control supersaturation level during batch-wise cooling crystallization was introduced. The crystallization kinetics together with operating conditions, i.e. seed loading, cooling rate and batch time, were taken into account in the model. Especially, the supersaturation- and suspension density- dependent secondary nucleation was included in the model. The interaction between the operating conditions and their influence on the control target, i.e. the constant level of supersaturation, were studied with the aid of a numerical solution for the cooling model. Further, the batch cooling crystallization was simulated with the ideal mixing model and CFD model. The moment transformation of the population balance, together with the mass and heat balances, were solved numerically in the simulation. In order to clarify a relationship betweenthe operating conditions and product sizes, a system chart was developed for anideal mixing condition. The utilization of the system chart to determine the appropriate operating condition to meet a required product size was introduced. With CFD simulation, batch crystallization, operated following a specified coolingmode, was studied in the crystallizers having different geometries and scales. The introduced cooling model and simulation results were verified experimentallyfor potassium dihydrogen phosphate (KDP) and the novelties of the proposed control policies were demonstrated using potassium sulfate by comparing with the published results in the literature. The study on the batch-wise precipitation showed that immiscible additives could promote the agglomeration of a derivative of benzoic acid, which facilitated the filterability of the crystal product.

Design and implementation of FPGA-based LQ control of active magnetic bearings

The need for high performance, high precision, and energy saving in rotating machinery demands an alternative solution to traditional bearings. Because of the contactless operation principle, the rotating machines employing active magnetic bearings (AMBs) provide many advantages over the traditional ones. The advantages such as contamination-free operation, low maintenance costs, high rotational speeds, low parasitic losses, programmable stiffness and damping, and vibration insulation come at expense of high cost, and complex technical solution. All these properties make the use of AMBs appropriate primarily for specific and highly demanding applications. High performance and high precision control requires model-based control methods and accurate models of the flexible rotor. In turn, complex models lead to high-order controllers and feature considerable computational burden. Fortunately, in the last few years the advancements in signal processing devices provide new perspective on the real-time control of AMBs. The design and the real-time digital implementation of the high-order LQ controllers, which focus on fast execution times, are the subjects of this work. In particular, the control design and implementation in the field programmable gate array (FPGA) circuits are investigated. The optimal design is guided by the physical constraints of the system for selecting the optimal weighting matrices. The plant model is complemented by augmenting appropriate disturbance models. The compensation of the force-field nonlinearities is proposed for decreasing the uncertainty of the actuator. A disturbance-observer-based unbalance compensation for canceling the magnetic force vibrations or vibrations in the measured positions is presented. The theoretical studies are verified by the practical experiments utilizing a custom-built laboratory test rig. The test rig uses a prototyping control platform developed in the scope of this work. To sum up, the work makes a step in the direction of an embedded single-chip FPGA-based controller of AMBs.

Effect of hydrodynamics on modelling, monitoring and control of crystallization

Crystallization is a purification method used to obtain crystalline product of a certain crystal size. It is one of the oldest industrial unit processes and commonly used in modern industry due to its good purification capability from rather impure solutions with reasonably low energy consumption. However, the process is extremely challenging to model and control because it involves inhomogeneous mixing and many simultaneous phenomena such as nucleation, crystal growth and agglomeration. All these phenomena are dependent on supersaturation, i.e. the difference between actual liquid phase concentration and solubility. Homogeneous mass and heat transfer in the crystallizer would greatly simplify modelling and control of crystallization processes, such conditions are, however, not the reality, especially in industrial scale processes. Consequently, the hydrodynamics of crystallizers, i.e. the combination of mixing, feed and product removal flows, and recycling of the suspension, needs to be thoroughly investigated. Understanding of hydrodynamics is important in crystallization, especially inlargerscale equipment where uniform flow conditions are difficult to attain. It is also important to understand different size scales of mixing; micro-, meso- and macromixing. Fast processes, like nucleation and chemical reactions, are typically highly dependent on micro- and mesomixing but macromixing, which equalizes the concentrations of all the species within the entire crystallizer, cannot be disregarded. This study investigates the influence of hydrodynamics on crystallization processes. Modelling of crystallizers with the mixed suspension mixed product removal (MSMPR) theory (ideal mixing), computational fluid dynamics (CFD), and a compartmental multiblock model is compared. The importance of proper verification of CFD and multiblock models is demonstrated. In addition, the influence of different hydrodynamic conditions on reactive crystallization process control is studied. Finally, the effect of extreme local supersaturation is studied using power ultrasound to initiate nucleation. The present work shows that mixing and chemical feeding conditions clearly affect induction time and cluster formation, nucleation, growth kinetics, and agglomeration. Consequently, the properties of crystalline end products, e.g. crystal size and crystal habit, can be influenced by management of mixing and feeding conditions. Impurities may have varying impacts on crystallization processes. As an example, manganese ions were shown to replace magnesium ions in the crystal lattice of magnesium sulphate heptahydrate, increasing the crystal growth rate significantly, whereas sodium ions showed no interaction at all. Modelling of continuous crystallization based on MSMPR theory showed that the model is feasible in a small laboratoryscale crystallizer, whereas in larger pilot- and industrial-scale crystallizers hydrodynamic effects should be taken into account. For that reason, CFD and multiblock modelling are shown to be effective tools for modelling crystallization with inhomogeneous mixing. The present work shows also that selection of the measurement point, or points in the case of multiprobe systems, is crucial when process analytical technology (PAT) is used to control larger scale crystallization. The thesis concludes by describing how control of local supersaturation by highly localized ultrasound was successfully applied to induce nucleation and to control polymorphism in reactive crystallization of L-glutamic acid.

AMB system for high-speed motors using automatic commissioning

The general trend towards increasing e ciency and energy density drives the industry to high-speed technologies. Active Magnetic Bearings (AMBs) are one of the technologies that allow contactless support of a rotating body. Theoretically, there are no limitations on the rotational speed. The absence of friction, low maintenance cost, micrometer precision, and programmable sti ness have made AMBs a viable choice for highdemanding applications. Along with the advances in power electronics, such as signi cantly improved reliability and cost, AMB systems have gained a wide adoption in the industry. The AMB system is a complex, open-loop unstable system with multiple inputs and outputs. For normal operation, such a system requires a feedback control. To meet the high demands for performance and robustness, model-based control techniques should be applied. These techniques require an accurate plant model description and uncertainty estimations. The advanced control methods require more e ort at the commissioning stage. In this work, a methodology is developed for an automatic commissioning of a subcritical, rigid gas blower machine. The commissioning process includes open-loop tuning of separate parts such as sensors and actuators. The next step is to apply a system identi cation procedure to obtain a model for the controller synthesis. Finally, a robust model-based controller is synthesized and experimentally evaluated in the full operating range of the system. The commissioning procedure is developed by applying only the system components available and a priori knowledge without any additional hardware. Thus, the work provides an intelligent system with a self-diagnostics feature and an automatic commissioning.

Modeling and Parameter Estimation of Double-Star Permanent Magnet Synchronous Machines

The power rating of wind turbines is constantly increasing; however, keeping the voltage rating at the low-voltage level results in high kilo-ampere currents. An alternative for increasing the power levels without raising the voltage level is provided by multiphase machines. Multiphase machines are used for instance in ship propulsion systems, aerospace applications, electric vehicles, and in other high-power applications including wind energy conversion systems. A machine model in an appropriate reference frame is required in order to design an efficient control for the electric drive. Modeling of multiphase machines poses a challenge because of the mutual couplings between the phases. Mutual couplings degrade the drive performance unless they are properly considered. In certain multiphase machines there is also a problem of high current harmonics, which are easily generated because of the small current path impedance of the harmonic components. However, multiphase machines provide special characteristics compared with the three-phase counterparts: Multiphase machines have a better fault tolerance, and are thus more robust. In addition, the controlled power can be divided among more inverter legs by increasing the number of phases. Moreover, the torque pulsation can be decreased and the harmonic frequency of the torque ripple increased by an appropriate multiphase configuration. By increasing the number of phases it is also possible to obtain more torque per RMS ampere for the same volume, and thus, increase the power density. In this doctoral thesis, a decoupled d–q model of double-star permanent-magnet (PM) synchronous machines is derived based on the inductance matrix diagonalization. The double-star machine is a special type of multiphase machines. Its armature consists of two three-phase winding sets, which are commonly displaced by 30 electrical degrees. In this study, the displacement angle between the sets is considered a parameter. The diagonalization of the inductance matrix results in a simplified model structure, in which the mutual couplings between the reference frames are eliminated. Moreover, the current harmonics are mapped into a reference frame, in which they can be easily controlled. The work also presents methods to determine the machine inductances by a finite-element analysis and by voltage-source inverters on-site. The derived model is validated by experimental results obtained with an example double-star interior PM (IPM) synchronous machine having the sets displaced by 30 electrical degrees. The derived transformation, and consequently, the decoupled d–q machine model, are shown to model the behavior of an actual machine with an acceptable accuracy. Thus, the proposed model is suitable to be used for the model-based control design of electric drives consisting of double-star IPM synchronous machines.

Facteurs associés à la résilience des aidantes familiales d’un parent âgé en perte d’autonomie à domicile au Liban

Avec l’avancement en âge, les personnes âgées qui vivent à domicile ont besoin du soutien des membres de leur entourage, notamment d’un aidant familial dont le rôle n’est toutefois pas sans conséquence sur sa santé. Les écrits empiriques ont montré que certains aidants sont résilients, c’est-à-dire qu’ils s’adaptent à leur situation et continuent leur développement. Toutefois, aucune étude n’a été effectuée au Liban auprès des aidantes familiales pour expliquer la résilience dans ce contexte et, plus spécifiquement, pour déterminer les facteurs qui pourraient l’influencer. Cette étude à devis corrélationnel de prédiction avait pour but de vérifier certaines des relations postulées par un modèle empirique découlant des écrits, soit la contribution de facteurs personnels (stratégies de coping et auto-efficacité) et de facteurs contextuels (relations familiales, perception du soutien de l’entourage, et sens accordé au « prendre soin »),à la résilience des aidantes familiales libanaises qui prennent soin d’un proche âgé à domicile. L’étude a été effectuée au Liban auprès d’un échantillon de convenance composé de 140 aidantes familiales principales cohabitant à domicile avec un parent âgé de 65 ans et plus ayant une perte d’autonomie fonctionnelle ou cognitive. La collecte des données a été réalisée en arabe en utilisant un guide d’entrevue standardisé regroupant des instruments nord-américains traduits selon la méthode de traduction inversée parallèle, de même qu’une question ouverte portant sur la perception des aidantes de la résilience, soit des facteurs qui les aident à continuer à prendre soin de leur proche âgé tout en continuant à se développer. Une analyse de régression hiérarchique a permis de vérifier la contribution unique des facteurs personnels et contextuels à expliquer la résilience des aidantes familiales, en contrôlant pour l’âge et le niveau de scolarité des aidantes et pour le niveau de perte d’autonomie et la fréquence des comportements dysfonctionnels de leurs parents âgés. Une analyse de contenu a permis de décrire la perception des aidantes eu égard à la résilience. Les résultats ont montré que le modèle empirique, incluant les variables de contrôle explique 54% de la variance de la résilience et que quatre des facteurs considérés, soit les stratégies de coping centrées sur le problème, les stratégies de coping centrées sur les émotions, le sentiment d’auto-efficacité et le sens du « prendre soin » ont une contribution statistiquement significative à la résilience des aidantes. Parmi ces quatre facteurs, le sens du « prendre soin » et le sentiment d’auto-efficacité expliquent davantage de variance, soit 11% et 5% respectivement. L’analyse qualitative du discours des aidantes a montré qu’elles prennent soin de leur proche âgé surtout par souci de réciprocité, mais également parce qu’il s’agit d’un membre de la famille et par respect pour Dieu. Ce sont par ailleurs leurs croyances et la satisfaction liée au prendre soin qui les aident à continuer et à se développer. Cette étude offre une meilleure compréhension du concept de la résilience des aidantes familiales au Liban et de certains facteurs qui en sont des prédicteurs significatifs. Elle offre des pistes pour l’intervention infirmière dans le but de promouvoir la santé de la personne/famille en tant que partenaire de soins. Des recommandations pour la pratique, la formation et la recherche sont proposées.

Prediction of glucose excursions under uncertain parameters and food intake in intensive insulin therapy for type 1 diabetes mellitus

Considering the difficulty in the insulin dosage selection and the problem of hyper- and hypoglycaemia episodes in type 1 diabetes, dosage-aid systems appear as tremendously helpful for these patients. A model-based approach to this problem must unavoidably consider uncertainty sources such as the large intra-patient variability and food intake. This work addresses the prediction of glycaemia for a given insulin therapy face to parametric and input uncertainty, by means of modal interval analysis. As result, a band containing all possible glucose excursions suffered by the patient for the given uncertainty is obtained. From it, a safer prediction of possible hyper- and hypoglycaemia episodes can be calculated

Probabilistic models to assist maintenance of multiple instruments

The paper discusses maintenance challenges of organisations with a huge number of devices and proposes the use of probabilistic models to assist monitoring and maintenance planning. The proposal assumes connectivity of instruments to report relevant features for monitoring. Also, the existence of enough historical registers with diagnosed breakdowns is required to make probabilistic models reliable and useful for predictive maintenance strategies based on them. Regular Markov models based on estimated failure and repair rates are proposed to calculate the availability of the instruments and Dynamic Bayesian Networks are proposed to model cause-effect relationships to trigger predictive maintenance services based on the influence between observed features and previously documented diagnostics

Prevalencia de alteraciones audiométricas y su relación con exposición a ruido ocupacional y extra ocupacional, en una cohorte de trabajadores de Santander, Colombia, Años 2014-2015

La hipoacusia neurosensorial inducida por ruido (HNIR) definida como la pérdida de la capacidad auditiva secundaria a la exposición ocupacional continua o intermitente a ruido en el lugar de trabajo, es la cuarta enfermedad ocupacional en prevalencia en Colombia. Objetivo: Determinar la prevalencia de alteraciones audiométricas y su relación con exposición a ruido ocupacional y extra ocupacional, en un grupo de trabajadores que asistieron a una IPS de la ciudad de Bucaramanga en el periodo comprendido entre agosto de 2014 y agosto de 2015. Diseño: Se realizó un estudio de corte transversal con 2725 registros de las historias clínicas de fonoaudiología realizadas a los trabajadores con audiometría tonal como parte de los exámenes ocupacionales, entre el 1 de agosto de 2014 al 31 de agosto de 2015, en una Institución Prestadora de Salud (IPS) ocupacional, en la ciudad de Bucaramanga, Santander. Resultados: El 17.2% de los trabajadores presentaron alteraciones audiométricas, de estos el 33,1%, cumplió con los criterios definidos en el estudio para ser calificados como casos probables de hipoacusia neurosensorial inducida por ruido, de estos el 87,8% fueron clasificados como leves, 10,8% como moderados y el 1,2% como moderado severo, no se registraron casos de HNIR severa o profunda. El 62,7% se clasificaron como no HNIR y el 4% correspondió a hipoacusias con afectación de frecuencias conversacionales. Conclusiones: Al aplicar un modelo de regresión logística para controlar las variables de confusión, no se encontró asociación con ninguna de las variables anteriormente descritas. A pesar de esto, existe suficiente evidencia de la relación entre algunas ocupaciones y la HNIR.

Real-Time software control of neural stimulation in a closed loop Animat system

A recent area for investigation into the development of adaptable robot control is the use of living neuronal networks to control a mobile robot. The so-called Animat paradigm comprises a neuronal network (the ‘brain’) connected to an external embodiment (in this case a mobile robot), facilitating potentially robust, adaptable robot control and increased understanding of neural processes. Sensory input from the robot is provided to the neuronal network via stimulation on a number of electrodes embedded in a specialist Petri dish (Multi Electrode Array (MEA)); accurate control of this stimulation is vital. We present software tools allowing precise, near real-time control of electrical stimulation on MEAs, with fast switching between electrodes and the application of custom stimulus waveforms. These Linux-based tools are compatible with the widely used MEABench data acquisition system. Benefits include rapid stimulus modulation in response to neuronal activity (closed loop) and batch processing of stimulation protocols.

A hyperstable neural network for the modelling and control of nonlinear systems

A multivariable hyperstable robust adaptive decoupling control algorithm based on a neural network is presented for the control of nonlinear multivariable coupled systems with unknown parameters and structure. The Popov theorem is used in the design of the controller. The modelling errors, coupling action and other uncertainties of the system are identified on-line by a neural network. The identified results are taken as compensation signals such that the robust adaptive control of nonlinear systems is realised. Simulation results are given.

Weighted input predictive controller

A discrete-time algorithm is presented which is based on a predictive control scheme in the form of dynamic matrix control. A set of control inputs are calculated and made available at each time instant, the actual input applied being a weighted summation of the inputs within the set. The algorithm is directly applicable in a self-tuning format and is therefore suitable for slowly time-varying systems in a noisy environment.

Adaptive control: an insight

In this article, an overview is given of some of the more common approaches taken in applying adaptive control. Gain scheduling, model reference control and self-tuning control are all discussed and in each case suggestions are given for further reading.