A stochastic thermostat algorithm for coarse-grained thermomechanical modeling of large-scale soft matters : theory and application to microfilaments

As all-atom molecular dynamics method is limited by its enormous computational cost, various coarse-grained strategies have been developed to extend the length scale of soft matters in the modeling of mechanical behaviors. However, the classical thermostat algorithm in highly coarse-grained molecular dynamics method would underestimate the thermodynamic behaviors of soft matters (e.g. microfilaments in cells), which can weaken the ability of materials to overcome local energy traps in granular modeling. Based on all-atom molecular dynamics modeling of microfilament fragments (G-actin clusters), a new stochastic thermostat algorithm is developed to retain the representation of thermodynamic properties of microfilaments at extra coarse-grained level. The accuracy of this stochastic thermostat algorithm is validated by all-atom MD simulation. This new stochastic thermostat algorithm provides an efficient way to investigate the thermomechanical properties of large-scale soft matters.

Coordinated control of grid connected photovoltaic reactive power and battery energy storage systems to improve the voltage profile of a residential distribution feeder

Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

French version of the Family Attitude Scale : psychometric properties and relation of attitudes to the respondent's psychiatric status

The Family Attitude Scale (FAS) is a self-report measure of critical or hostile attitudes and behaviors towards another family member, and demonstrates an ability to predict relapse in psychoses. Data are not currently available on a French version of the scale. The present study developed a French version of the FAS, using a large general population sample to test its internal structure, criterion validity and relationships with the respondents' symptoms and psychiatric diagnoses, and examined the reciprocity of FAS ratings by respondents and their partners. A total of 2072 adults from an urban population undertook a diagnostic interview and completed self-report measures, including an FAS about their partner. A subset of participants had partners who also completed the FAS. Confirmatory factor analyses revealed an excellent fit by a single-factor model, and the FAS demonstrated a strong association with dyadic adjustment. FAS scores of respondents were affected by their anxiety levels and mood, alcohol and anxiety diagnoses, and moderate reciprocity of attitudes and behaviors between the partners was seen. The French version of the FAS has similarly strong psychometric properties to the original English version. Future research should assess the ability of the French FAS to predict relapse of psychiatric disorders.

Model-predictive control and closed-loop stability considerations for nonlinear plants described by local ARX-type models

In this paper, a model-predictive control (MPC) method is detailed for the control of nonlinear systems with stability considerations. It will be assumed that the plant is described by a local input/output ARX-type model, with the control potentially included in the premise variables, which enables the control of systems that are nonlinear in both the state and control input. Additionally, for the case of set point regulation, a suboptimal controller is derived which has the dual purpose of ensuring stability and enabling finite-iteration termination of the iterative procedure used to solve the nonlinear optimization problem that is used to determine the control signal.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Dynamic spatiotemporal trends of dengue transmission in the Asia-Pacific region, 1955–2004

BACKGROUND: Dengue fever (DF) is one of the most important emerging arboviral human diseases. Globally, DF incidence has increased by 30-fold over the last fifty years, and the geographic range of the virus and its vectors has expanded. The disease is now endemic in more than 120 countries in tropical and subtropical parts of the world. This study examines the spatiotemporal trends of DF transmission in the Asia-Pacific region over a 50-year period, and identified the disease's cluster areas. METHODOLOGY AND FINDINGS: The World Health Organization's DengueNet provided the annual number of DF cases in 16 countries in the Asia-Pacific region for the period 1955 to 2004. This fifty-year dataset was divided into five ten-year periods as the basis for the investigation of DF transmission trends. Space-time cluster analyses were conducted using scan statistics to detect the disease clusters. This study shows an increasing trend in the spatiotemporal distribution of DF in the Asia-Pacific region over the study period. Thailand, Vietnam, Laos, Singapore and Malaysia are identified as the most likely clusters (relative risk = 13.02) of DF transmission in this region in the period studied (1995 to 2004). The study also indicates that, for the most part, DF transmission has expanded southwards in the region. CONCLUSIONS: This information will lead to the improvement of DF prevention and control strategies in the Asia-Pacific region by prioritizing control efforts and directing them where they are most needed.

Wide area controls for transient and dynamic stability enhancement

This paper presents a study done into the effectiveness of using local acceleration measurements vs. remote angle measurements in providing stabilising control via SVCs following large disturbances. The system studied was an analogue of the Queensland-New South Wales Interconnection (QNI) and involved the control of an existing Static Var Compensators (SVC) at Sydney West. This study is placed in the context of wide area controls for large systems using aggregated models for groups of machines.

Primary control level of parallel distributed energy resources converters in system of multiple interconnected autonomous microgrids within self-healing networks

To minimise the number of load sheddings in a microgrid (MG) during autonomous operation, islanded neighbour MGs can be interconnected if they are on a self-healing network and an extra generation capacity is available in the distributed energy resources (DER) of one of the MGs. In this way, the total load in the system of interconnected MGs can be shared by all the DERs within those MGs. However, for this purpose, carefully designed self-healing and supply restoration control algorithm, protection systems and communication infrastructure are required at the network and MG levels. In this study, first, a hierarchical control structure is discussed for interconnecting the neighbour autonomous MGs where the introduced primary control level is the main focus of this study. Through the developed primary control level, this study demonstrates how the parallel DERs in the system of multiple interconnected autonomous MGs can properly share the load of the system. This controller is designed such that the converter-interfaced DERs operate in a voltage-controlled mode following a decentralised power sharing algorithm based on droop control. DER converters are controlled based on a per-phase technique instead of a conventional direct-quadratic transformation technique. In addition, linear quadratic regulator-based state feedback controllers, which are more stable than conventional proportional integrator controllers, are utilised to prevent instability and weak dynamic performances of the DERs when autonomous MGs are interconnected. The efficacy of the primary control level of the DERs in the system of multiple interconnected autonomous MGs is validated through the PSCAD/EMTDC simulations considering detailed dynamic models of DERs and converters.

Non-response bias in randomized control experiments in criminology : putting the Queensland Community Engagement Trial (QCET) under a microscope

Objectives The goal of this article is to examine whether or not the results of the Queensland Community Engagement Trial (QCET)-a randomized controlled trial that tested the impact of procedural justice policing on citizen attitudes toward police-were affected by different types of nonresponse bias. Method We use two methods (Cochrane and Elffers methods) to explore nonresponse bias: First, we assess the impact of the low response rate by examining the effects of nonresponse group differences between the experimental and control conditions and pooled variance under different scenarios. Second, we assess the degree to which item response rates are influenced by the control and experimental conditions. Results Our analysis of the QCET data suggests that our substantive findings are not influenced by the low response rate in the trial. The results are robust even under extreme conditions, and statistical significance of the results would only be compromised in cases where the pooled variance was much larger for the nonresponse group and the difference between experimental and control conditions was greatly diminished. We also find that there were no biases in the item response rates across the experimental and control conditions. Conclusion RCTs that involve field survey responses-like QCET-are potentially compromised by low response rates and how item response rates might be influenced by the control or experimental conditions. Our results show that the QCET results were not sensitive to the overall low response rate across the experimental and control conditions and the item response rates were not significantly different across the experimental and control groups. Overall, our analysis suggests that the results of QCET are robust and any biases in the survey responses do not significantly influence the main experimental findings.

Making YAWL and SmartPM interoperate : managing highly dynamic processes by exploiting automatic adaptation features

In the last years, the trade-o between exibility and sup- port has become a leading issue in work ow technology. In this paper we show how an imperative modeling approach used to de ne stable and well-understood processes can be complemented by a modeling ap- proach that enables automatic process adaptation and exploits planning techniques to deal with environmental changes and exceptions that may occur during process execution. To this end, we designed and imple- mented a Custom Service that allows the Yawl execution environment to delegate the execution of subprocesses and activities to the SmartPM execution environment, which is able to automatically adapt a process to deal with emerging changes and exceptions. We demonstrate the fea- sibility and validity of the approach by showing the design and execution of an emergency management process de ned for train derailments.

An Introduction to Constrained Control

An ubiquitous problem in control system design is that the system must operate subject to various constraints. Although the topic of constrained control has a long history in practice, there have been recent significant advances in the supporting theory. In this chapter, we give an introduction to constrained control. In particular, we describe contemporary work which shows that the constrained optimal control problem for discrete-time systems has an interesting geometric structure and a simple local solution. We also discuss issues associated with the output feedback solution to this class of problems, and the implication of these results in the closely related problem of anti-windup. As an application, we address the problem of rudder roll stabilization for ships.

Dynamic positioning of marine craft using a port-Hamiltonian framework

Dynamic positioning of marine craft refers to the use of the propulsion system to regulate the vessel position and heading. This type of motion control is commonly used in the offshore industry for surface vessels, and it is also used for some underwater vehicles. In this paper, we use a port-Hamiltonian framework to design a novel nonlinear set-point-regulation controller with integral action. The controller handles input saturation and guarantees internal stability, rejection of unknown constant disturbances, and (integral-)input-to-state stability.

Practical aspects of frequency-domain identification of dynamic models of marine structures from hydrodynamic data

The motion response of marine structures in waves can be studied using finite-dimensional linear-time-invariant approximating models. These models, obtained using system identification with data computed by hydrodynamic codes, find application in offshore training simulators, hardware-in-the-loop simulators for positioning control testing, and also in initial designs of wave-energy conversion devices. Different proposals have appeared in the literature to address the identification problem in both time and frequency domains, and recent work has highlighted the superiority of the frequency-domain methods. This paper summarises practical frequency-domain estimation algorithms that use constraints on model structure and parameters to refine the search of approximating parametric models. Practical issues associated with the identification are discussed, including the influence of radiation model accuracy in force-to-motion models, which are usually the ultimate modelling objective. The illustration examples in the paper are obtained using a freely available MATLAB toolbox developed by the authors, which implements the estimation algorithms described.

Kalman filtering for positioning and heading control of ships and offshore rigs

In this article, we have described the main components of a ship motion-control system and two particular motion-control problems that require wave filtering, namely, dynamic positioning and heading autopilot. Then, we discussed the models commonly used for vessel response and showed how these models are used for Kalman filter design. We also briefly discussed parameter and noise covariance estimation, which are used for filter tuning. To illustrate the performance, a case study based on numerical simulations for a ship autopilot was considered. The material discussed in this article conforms to modern commercially available ship motion-control systems. Most of the vessels operating in the offshore industry worldwide use Kalman filters for velocity estimation and wave filtering. Thus, the article provides an up-to-date tutorial and overview of Kalman-filter-based wave filtering.

Hybrid frequency–time domain models for dynamic response analysis of marine structures

Time-domain models of marine structures based on frequency domain data are usually built upon the Cummins equation. This type of model is a vector integro-differential equation which involves convolution terms. These convolution terms are not convenient for analysis and design of motion control systems. In addition, these models are not efficient with respect to simulation time, and ease of implementation in standard simulation packages. For these reasons, different methods have been proposed in the literature as approximate alternative representations of the convolutions. Because the convolution is a linear operation, different approaches can be followed to obtain an approximately equivalent linear system in the form of either transfer function or state-space models. This process involves the use of system identification, and several options are available depending on how the identification problem is posed. This raises the question whether one method is better than the others. This paper therefore has three objectives. The first objective is to revisit some of the methods for replacing the convolutions, which have been reported in different areas of analysis of marine systems: hydrodynamics, wave energy conversion, and motion control systems. The second objective is to compare the different methods in terms of complexity and performance. For this purpose, a model for the response in the vertical plane of a modern containership is considered. The third objective is to describe the implementation of the resulting model in the standard simulation environment Matlab/Simulink.