Estimating radar positions using unmanned air vehicle teams engaged in cooperative deception

Standard TDOA (time-difference of arrival) estimation techniques are modified and applied to locate networked enemy radars using a cooperative team of unmanned electronic combat air vehicles (ECAVs). The team is engaged in deceiving the radars, which limits where the ECAVs can fly and requires accurate radar positions to be known. Two TDOA measurements of radar pulses taken by two ECAV pairs are used to estimate the position of the middle radar. A nonlinear system model for estimation is formulated and used to perform simulations with "noisy" TDOAs; a linearized time-varying model for straight nominal ECAV trajectories is derived from the nonlinear model. The choice of optimal ECAV trajectories and an observer to minimize the variance of the middle radar position - using the linearized model is addressed. Application of a time-varying Kalman filter to the linearized system shows drastic improvement in reducing the variance of position estimates when compared to the original nonlinear system via simulations

TESTING USED ROLLER BEARINGS FOR QUALITY AND SERVICE LIFE

Synthetic biology is a rapidly expanding field at the interface of the engineering and biological sciences which aims to apply rational design principles in biological contexts. Many natural processes utilise regulatory architectures that parallel those found in control and electrical engineering, which has motivated their implementation as part of synthetic biological constructs. Tools based upon control theoretical concepts can be used to design such systems, as well as to guide their experimental realisation. In this paper we provide examples of biological implementations of negative feedback systems, and discuss progress made toward realisation of other feedback and control architectures. We then outline major challenges posed by the design of such systems, particularly focusing on those which are specific to biological contexts and on which feedback control can have a significant impact. We explore future directions for work in the field, including new approaches for theoretical design of biological control systems, the utilisation of novel components for their implementation, and the potential for application of automation and machine-learning approaches to accelerate synthetic biological research

Feedback regulation of the heat shock response in E. coli

Survival of organisms in extreme conditions has necessitated the evolution of stress response networks that detect and respond to environmental changes. Among the extreme conditions that cells must face is the exposure to higher than normal temperatures. In this paper, we propose a detailed biochemical model that captures the dynamical nature of the heat-shock response in Escherichia coli. Using this model, we show that both feedback and feedforward control are utilized to achieve robustness, performance, and efficiency of the response to the heat stress. We discuss the evolutionary advantages that feedback confers to the system, as compared to other strategies that could have been implemented to get the same performance

Improving newborn health in countries exposed to political violence: an assessment of the availability, accessibility, and distribution of neonatal health services at Palestinian hospitals

Introduction: Geopolitical segregation of Palestine has left a fragile healthcare system with an unequal distribution of services. Data from the Gaza Strip reflect an increase in infant mortality that coincided with a significant increase in neonatal mortality (12.0 to 20.3 per 1,000 live births). Objective: A baseline study was carried out to evaluate available resources in neonatal units throughout Palestine. Study Design: A cross-sectional, hospital-based study was conducted in 2017 using the World Health Organization's "Hospital care for mothers and newborn babies: quality assessment and improvement tool." Data on the main indicators were updated in 2018. Results: There were 38 neonatal units in Palestine: 27 in the West Bank, 3 in East Jerusalem, and 8 in the Gaza Strip. There was an uneven geographic distribution of incubators in relation to population and births that was more marked in the Gaza Strip; 79% of neonatal units and 75% of incubators were in the West Bank. While almost all hospitals with neonatal units accepted very and extremely low birth weight and admitted out-born neonatal cases, there was a shortage in the availability of incubators with humidifiers, high-frequency oscillatory ventilation, mechanical ventilators with humidifiers and isolation wards. There was also a considerable shortage in neonatologists, neonatal nurses, and pediatric subspecialties. Conclusion: Almost all the neonatal units accepted extremely low birth weight neonatal cases despite not being ready to receive these newborns due to considerable shortages in human resources, equipment, drugs, and essential blood tests, as well as frequent disruptions in the availability of based amenities. Together, these factors contribute to the burden of providing quality care to newborns, which is further exacerbated by the lack of referral guidelines and challenges to timely referrals resulting from Israeli measures. Ultimately, this contributes to suboptimal care for neonates and negatively impacts future health outcomes

Analysis of Stochastic Strategies in Bacterial Competence: A Master Equation Approach

Competence is a transiently differentiated state that certain bacterial cells reach when faced with a stressful environment. Entrance into competence can be attributed to the excitability of the dynamics governing the genetic circuit that regulates this cellular behavior. Like many biological behaviors, entrance into competence is a stochastic event. In this case cellular noise is responsible for driving the cell from a vegetative state into competence and back. In this work we present a novel numerical method for the analysis of stochastic biochemical events and use it to study the excitable dynamics responsible for competence in Bacillus subtilis. Starting with a Finite State Projection (FSP) solution of the chemical master equation (CME), we develop efficient numerical tools for accurately computing competence probability. Additionally, we propose a new approach for the sensitivity analysis of stochastic events and utilize it to elucidate the robustness properties of the competence regulatory genetic circuit. We also propose and implement a numerical method to calculate the expected time it takes a cell to return from competence. Although this study is focused on an example of cell-differentiation in Bacillus subtilis, our approach can be applied to a wide range of stochastic phenomena in biological systems

Temperature Control of Fimbriation Circuit Switch in Uropathogenic Escherichia coli: Quantitative Analysis via Automated Model Abstraction

Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element—the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase) of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies that this down-regulation mechanism could be particularly significant inside the host environment, thus potentially contributing further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs