A hidden integral structure endows absolute concentration robust systems with resilience to dynamical concentration disturbances: A hidden integral structure endows absolute concentration robust systems with resilience to dynamical concentration disturbances

Biochemical systems that express certain chemical species of interest at the same level at any positive steady state are called 'absolute concentration robust' (ACR). These species behave in a stable, predictable way, in the sense that their expression is robust with respect to sudden changes in the species concentration, provided that the system reaches a (potentially new) positive steady state. Such a property has been proven to be of importance in certain gene regulatory networks and signaling systems. In the present paper, we mathematically prove that a well-known class of ACR systems studied by Shinar and Feinberg in 2010 hides an internal integral structure. This structure confers these systems with a higher degree of robustness than was previously known. In particular, disturbances much more general than sudden changes in the species concentrations can be rejected, and robust perfect adaptation is achieved. Significantly, we show that these properties are maintained when the system is interconnected with other chemical reaction networks. This key feature enables the design of insulator devices that are able to buffer the loading effect from downstream systems - a crucial requirement for modular circuit design in synthetic biology. We further note that while the best performance of the insulators are achieved when these act at a faster timescale than the upstream module (as typically required), it is not necessary for them to act on a faster timescale than the downstream module in our construction

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

Evaluation of Glycated Hemoglobin (HbA1c) for Diagnosing Type 2 Diabetes and Prediabetes among Palestinian Arab Population

The purpose of the study is to compare the potential of HbA1c to diagnose diabetes among Palestinian Arabs compared to fasting plasma glucose (FPG). A cross-sectional sample of 1370 Palestinian men (468) and women (902) without known diabetes and above the age of 30 years were recruited. Whole blood was used to estimate HbA1c and plasma for FPG and total lipid profile. Fasting plasma glucose was used as a reference to diagnose diabetes ($126 mg/dL) and prediabetes (100–125 mg/dL). The area under the receiver operating characteristic curve (AUC) for HbA1c was 81.9diabetes and 63.90.498) and low with prediabetes (K = 0.142). The optimal cut-off value for HbA1c to diagnose diabetes was$ 6.3% (45 mmol/mol). The sensitivity, specificity and the discriminant ability were 65.6% (53.1–76.3%), 94.5% (93.1–95.6%), 80.0% (72.8–87.3%), respectively. However, using cut-off value of $6.5the sensitivity, specificity and the discriminant ability were 57.4For diagnosing prediabetes with HbA1c between 5.7–6.4discriminant ability were 62.7value of$ 6.5% (48 mmol/mol) by itself diagnosed 5.3% and 48.3% as having diabetes and prediabetes compared to 4.5% and 24.2% using FPG, respectively. Mean HbA1c and FPG increase significantly with increasing body mass index. In conclusion, the ROC curves showed HbA1c could be used for diagnosing diabetes when compared to FPG but not for prediabetes in Palestinians Arabs even though only about 50% of the diabetic subjects were identified by the both HbA1c and FPG.This project was partially supported by United Nation Relief and Working Agency (UNRWA. No additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors thank Fida Zeidan from UNRWA for organizing the teams at different UNRWA clinics. Also, the authors thank the staff of UNRWA clinics for their cooperation in the study. Thanks to Dr. Khaldoun Bader from Al-Quds University for his assistance in statistical analysis.Guarantor: Akram T. Kharroubi

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

Examining Neolithic Building and Activity Areas through Historic Cultural Heritage in Jordan: A Combined Ethnographic, Phytolith and Geochemical Investigation

The INEA project (Identifying activity areas in Neolithic sites through Ethnographic Analysis of phytoliths and geochemical residues, https://research.bournemouth. ac.uk/2014/07/inea-project-2/) develops and applies a method that combines the analysis of plant remains (silica phytoliths) and geochemical residues to inform on construction methods and the use of space in recently abandoned historical villages and Neolithic settlements. It is a collaborative project based at Bournemouth University, in partnership with the Council for British Research in the Levant

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