The stochastic behavior of a molecular switching circuit with feedback

Background: Using a statistical physics approach, we study the stochastic switching behavior of a model circuit of multisite phosphorylation and dephosphorylation with feedback. The circuit consists of a kinase and phosphatase acting on multiple sites of a substrate that, contingent on its modification state, catalyzes its own phosphorylation and, in a symmetric scenario, dephosphorylation. The symmetric case is viewed as a cartoon of conflicting feedback that could result from antagonistic pathways impinging on the state of a shared component. Results: Multisite phosphorylation is sufficient for bistable behavior under feedback even when catalysis is linear in substrate concentration, which is the case we consider. We compute the phase diagram, fluctuation spectrum and large-deviation properties related to switch memory within a statistical mechanics framework. Bistability occurs as either a first-order or second-order non-equilibrium phase transition, depending on the network symmetries and the ratio of phosphatase to kinase numbers. In the second-order case, the circuit never leaves the bistable regime upon increasing the number of substrate molecules at constant kinase to phosphatase ratio. Conclusions: The number of substrate molecules is a key parameter controlling both the onset of the bistable regime, fluctuation intensity, and the residence time in a switched state. The relevance of the concept of memory depends on the degree of switch symmetry, as memory presupposes information to be remembered, which is highest for equal residence times in the switched states. Reviewers: This article was reviewed by Artem Novozhilov (nominated by Eugene Koonin), Sergei Maslov, and Ned Wingreen.Comment: Version published in Biology Direct including reviewer comments and author responses, 28 pages, 7 figure

Considering the impact of situation-specific motivations and constraints in the design of naturally ventilated and hybrid buildings

A simple logical model of the interaction between a building and its occupants is presented based on the principle that if free to do so, people will adjust their posture, clothing or available building controls (windows, blinds, doors, fans, and thermostats) with the aim of achieving or restoring comfort and reducing discomfort. These adjustments are related to building design in two ways: first the freedom to adjust depends on the availability and ease-of-use of control options; second the use of controls affects building comfort and energy performance. Hence it is essential that these interactions are considered in the design process. The model captures occupant use of controls in response to thermal stimuli (too warm, too cold etc.) and non-thermal stimuli (e.g. desire for fresh air). The situation-specific motivations and constraints on control use are represented through trigger temperatures at which control actions occur, motivations are included as negative constraints and incorporated into a single constraint value describing the specifics of each situation. The values of constraints are quantified for a range of existing buildings in Europe and Pakistan. The integration of the model within a design flow is proposed and the impact of different levels of constraints demonstrated. It is proposed that to minimise energy use and maximise comfort in naturally ventilated and hybrid buildings the designer should take the following steps: 1. Provide unconstrained low energy adaptive control options where possible, 2. Avoid problems with indoor air quality which provide motivations for excessive ventilation rates, 3. Incorporate situation-specific adaptive behaviour of occupants in design simulations, 4. Analyse the robustness of designs against variations in patterns of use and climate, and 5. Incorporate appropriate comfort standards into the operational building controls (e.g. BEMS)

Ecological resilience in lakes and the conjunction fallacy

There is a pressing need to apply stability and resilience theory to environmental management to restore degraded ecosystems effectively and to mitigate the effects of impending environmental change. Lakes represent excellent model case studies in this respect and have been used widely to demonstrate theories of ecological stability and resilience that are needed to underpin preventative management approaches. However, we argue that this approach is not yet fully developed because the pursuit of empirical evidence to underpin such theoretically grounded management continues in the absence of an objective probability framework. This has blurred the lines between intuitive logic (based on the elementary principles of probability) and extensional logic (based on assumption and belief) in this field

On the use of high-frequency SCADA data for improved wind turbine performance monitoring

SCADA-based condition monitoring of wind turbines facilitates the move from costly corrective repairs towards more proactive maintenance strategies. In this work, we advocate the use of high-frequency SCADA data and quantile regression to build a cost effective performance monitoring tool. The benefits of the approach are demonstrated through the comparison between state-of-the-art deterministic power curve modelling techniques and the suggested probabilistic model. Detection capabilities are compared for low and high-frequency SCADA data, providing evidence for monitoring at higher resolutions. Operational data from healthy and faulty turbines are used to provide a practical example of usage with the proposed tool, effectively achieving the detection of an incipient gearbox malfunction at a time horizon of more than one month prior to the actual occurrence of the failure

Time-scale synchronisation of oscillatory responses can lead to non-monotonous R-tipping

Rate-induced tipping (R-tipping) describes the fact that, for multistable dynamic systems, an abrupt transition can take place not only because of the forcing magnitude, but also because of the forcing rate. In the present work, we demonstrate through the case study of a piecewise-linear oscillator (PLO), that increasing the rate of forcing can make the system tip in some cases but might also prevent it from tipping in others. This counterintuitive effect is further called non-monotonous R-tipping (NMRT) and has already been observed in recent studies. We show that, in the present case, the reason for NMRT is the peak synchronisation of oscillatory responses operating on different time scales. We further illustrate that NMRT can be observed even in the presence of additive white noise of intermediate amplitude. Finally, NMRT is also observed on a van-der-Pol oscillator with an unstable limit cycle, suggesting that this effect is not limited to systems with a discontinuous right-hand side such as the PLO. This insight might be highly valuable, as the current research on tipping elements is shifting from an equilibrium to a dynamic perspective while using models of increasing complexity, in which NMRT might be observed but hard to understand

Contribution to the characterization and modeling of photovoltaic generators

A crucial aspect of evaluating and maintaining a photovoltaic (PV) installation connected to the grid is the availability of models that describe its operation reliably in real operating conditions. The nominal power of the PV generator (P*M) is considered an essential input parameter, and several models have been proposed to estimate P*M for characterizing the PV system. In the case of PV generators in outdoor conditions, the American Society for Testing and Materials, the International Electrotechnical Commission, and others have proposed procedures to determine the P*M of the generator. As part of these procedures, monitoring days with ideal conditions is mandatory, notably days with a clear sky, high irradiance values, and low wind speeds. Such restrictions can limit the number of suitable monitoring days, especially in places where clouds frequently form. This thesis proposes a new approach that allows estimating the P*M with data even from non-ideal, partially cloudy days. Based on non-parametric statistics, this procedure identifies and filters out noise as well as deviations from ideal conditions of irradiance, allowing for an estimation of P*M with similar accuracy as for a clear-sky day. This new procedure enables the characterization of a PV generator on a daily basis without the requirement to meet ideal conditions, thus, considerably enhancing the number of suitable monitoring days. To overcome the limitation in the P*M estimation and considerably extend the number of monitoring days, the new procedure can be applied to ideal and non-ideal conditions, such as partially cloudy days. This procedure determines the most probable nominal power value within one monitoring day using non-parametric statistics. In order to test the new procedure, a 109.44 kW photovoltaic plant in Granada, Spain, was monitored for six months. A referential procedure reported in the literature for large PV plants under ideal climatic conditions is first applied to estimate its nominal power. The results indicate that the nominal power can be estimated reliably in non-ideal conditions, maintaining the same precision as in ideal conditions. Then validating the procedure for a smaller PV generator and under different conditions, two small grid-connected 1.5 kW PV arrays were used. The PV systems in question are located in two different cities in Peru: Chachapoyas (tropical highland) and Lima (coastal desert). The objective of this study in Chachapoyas was to validate the methodology in a tropical climate with a high presence of clouds but at the same time with high irradiance values above 800 W/m2. According to the results obtained, under these conditions, the nominal power of the system can be calculated with reasonable certainty. As a precaution, monitoring for more than one day is recommended to obtain more data (at least 3 hours with high irradiance) to reduce uncertainties. Lima, Peru's second location under study, has a particular climate. Since the capital is located in a desert with high relative humidity values, dust deposition increases and power output decreases due to these conditions. For this purpose, the nominal power was used as a parameter to determine the maintenance schedule. Since keeping the system in optimal performance, considering this in future installations for operation and maintenance costs, is essential. The new procedure developed in this work can be applied to facilitate technical due diligence and quality control processes for PV generators of different sizes and under different operating conditions that are being re-purchased or have been recently installed. The possibility of daily monitoring of the P*M also enables long-term monitoring of a PV generator to ensure the correct operation or identify possible degradation effectsUn aspecto crucial a la hora de evaluar y mantener una instalacion fotovoltaica (FV) conectada a la red es la disponibilidad de modelos que describan su funcionamiento de forma fiable en condiciones reales de funcionamiento. La potencia nominal del generador fotovoltaico (P*M ) se considera un parametro de entrada esencial y se han propuesto varios modelos para estimar P*M para caracterizar el sistema fotovoltaico. En el caso de generadores fotovoltaicos en condiciones exteriores, la Sociedad Estadounidense de Pruebas y Materiales (abreviatura del ingles ASTM), la Comision Electrotecnica Internacional (abreviatura del ingles IEC) y otros han propuesto procedimientos para determinar la P*M del generador. Como parte de estos procedimientos, es obligatorio monitorear los dias con condiciones ideales, en particular los dias con cielo despejado, valores de irradiancia altos y velocidades de viento bajas. Tales restricciones pueden limitar la cantidad de dias de monitoreo adecuados, especialmente en lugares donde se forman nubes con frecuencia. Esta tesis propone un nuevo enfoque que permite estimar la P*M con datos incluso de dias parcialmente nublados no ideales. Basado en estadistica no parametricas, este procedimiento identifica y filtra el ruido, asi como las desviaciones de las condiciones ideales de irradiancia, lo que permite una estimacion de P*M con una precision similar a la de un dia de cielo despejado. Este nuevo procedimiento permite la caracterizacion diaria de un generador fotovoltaico sin el requisito de cumplir con las condiciones ideales, lo que aumenta considerablemente el numero de dias de monitoreo adecuados. Para superar la limitacion en la estimacion de P*M y extender considerablemente el numero de dias de monitoreo, el nuevo procedimiento se puede aplicar a condiciones ideales y no ideales, como dias parcialmente nublados. Este procedimiento determina el valor de potencia nominal mas probable dentro de un dia de monitoreo utilizando estadisticas no parametricas. Para probar el nuevo procedimiento, se monitorizo durante seis meses una planta fotovoltaica de 109,44 kW en Granada, Espana. Primero se aplica un procedimiento referencial reportado en la literatura para grandes plantas fotovoltaicas en condiciones climaticas ideales para estimar su potencia nominal. Los resultados indican que la potencia nominal se puede estimar de forma fiable en condiciones no ideales, manteniendo la misma precision que en condiciones ideales. Luego, para validar el procedimiento para un generador fotovoltaico mas pequeno y en diferentes condiciones, se utilizaron dos pequenos generador fotovoltaicos de 1,5 kW conectados a la red. Los sistemas fotovoltaicos en cuestion estan ubicados en dos ciudades diferentes de Peru: Chachapoyas (altiplano tropical) y Lima (desierto costero). El objetivo de este estudio en Chachapoyas fue validar la metodologia en un clima tropical con alta presencia de nubes pero al mismo tiempo con altos valores de irradiancia por encima de 800 W/m2. De acuerdo con los resultados obtenidos, en estas condiciones se puede calcular con razonable certeza la potencia nominal del sistema. Como precaucion, se recomienda monitorear durante mas de un dia para obtener mas datos (al menos 3 horas con alta irradiacion) para reducir las incertidumbres. Lima, la segunda localidad del Peru bajo estudio, tiene un clima particular. Dado que la capital esta ubicada en un desierto con altos valores de humedad relativa, la deposicion de polvo aumenta y la produccion de energia disminuye debido a estas condiciones. Para ello, se utilizo la potencia nominal como parametro para determinar el programa de mantenimiento. Ya que mantener el VI sistema en un desempeno optimo, considerando esto en futuras instalaciones para costos de operacion y mantenimiento, es fundamental. El nuevo procedimiento desarrollado en este trabajo se puede aplicar para facilitar los procesos de diligencia debida tecnica y control de calidad para generadores fotovoltaicos de diferentes tamaños y en diferentes condiciones de funcionamiento que se están recomprando o que se han instalado recientemente. La posibilidad de monitorear diariamente la P*M también permite monitorear a largo plazo un generador fotovoltaico para asegurar el correcto funcionamiento o identificar posibles efectos de degradación

Ääreinformatsioonil põhinev esemete tuvastamine ja klassifitseerimine

This thesis presents work regarding the development a computationally cheap and reliable edge information based object detection and classification system for use on the NAO humanoid robots. The work covers ground detection, edge detection, edge clustering and cluster classification, the latter task being equivalent to object recognition. Numerous novel improvements are proposed, including a new geometric model for ground detection, a joint edge model using two edge detectors in unison for improved edge detection, and a hybrid edge clustering model. Also, a classification model is outlined along with example classifiers and used values. The work is illustrated graphically where applicable

Neutral coding - A report based on an NRP work session

Neural coding by impulses and trains on single and multiple channels, and representation of information in nonimpulse carrier

Design of an American Football Helmet Liner for Concussion Mitigation

The objective of this research was to develop an optimal design for a polymeric American football helmet liner for concussion prevention utilizing experiments and high performance. Along with well-established injury criteria (HIC, SI, and Peak acceleration), localized brain injury mechanisms were explored by employing Finite Element simulations and experimental validation. Varying strain rate experiments (monotonic and hysteresis) were conducted on modern football helmet (Rush, Rawlings, Riddell, Schutt, and Xenith) liners and new possible polymeric foam liner materials. These experiments were used to characterize each material at low strain rates (0.1/sec; Instron), intermediate strain rates (100-120/sec; NOCSAE drop tower) and high strain rates (600-1000/sec; Split Hopkinson Pressure Bar). Experimental design optimization was performed on a football helmet liner by utilizing an exploratory Design of Experiments by National Operating Committee on Standards for Athletic Equipment (NOCSAE) drop tests. FEA simulations of drop impact tests were conducted on a helmeted NOCSAE headform model and a helmeted human head model. Correlations were made between both models to relate localized brain response to the global acceleration and the dynamic-based injury criteria HIC, SI, and Peak acceleration). FEA simulations were experimentally validated by twin-wire drop tests of the NOCSAE headform using correlations for validation of the human head model. The helmeted human head simulations were used to explore a Mild Traumatic Brain Injury (MTBI) limits based localized brain response (e.g. pressure and impulse). Based on these limits, future FEA simulations will be used to explore these limits as helmet liner design criteria