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In light of the advancement of the technologies used in industrial control systems, securing their operation has become crucial, primarily since their activity is consistently associated with integral elements related to the environment, the safety and health of people, the economy, and many others. This work presents a distributed, machine learning based attack detection and mitigation framework for sensor false data injection cyber-physical attacks in industrial control systems. It is developed using the system’s standard operational data and validated using a hybrid testbed of a reverse osmosis plant. A MATLAB/Simulink-based simulation model of the process validated with actual data from a local plant is used. The control system is implemented using Siemens S7-1200 programmable logic controllers with 200SP Distributed Input/Output modules. The proposed solution can be adopted in the existing industrial control systems and demonstrated effective performance in real-time detection and mitigation of actual cyber-physical attacks launched by compromising the communication links between the process and the programmable logic controllers.

In response to the urgent requirement for rapid, precise, and cost-effective detection in intensive care units (ICUs) for ventilated patients, as well as the need to overcome the limitations of traditional detection methods, researchers have turned their attention towards advancing novel technologies. Among these, biosensors have emerged as a reliable platform for achieving accurate and early diagnoses. In this study, we explore the possibility of using Pyocyanin analysis for early detection of pathogens in ventilator-associated pneumonia (VAP) and lower respiratory tract infections in ventilated patients. To achieve this, we developed an electrochemical sensor utilizing a graphene oxide–copper oxide-doped MgO (GO − Cu − Mgo) (GCM) catalyst for Pyocyanin detection. Pyocyanin is a virulence factor in the phenazine group that is produced by Pseudomonas aeruginosa strains, leading to infections such as pneumonia, urinary tract infections, and cystic fibrosis. We additionally investigated the use of DNA aptamers for detecting Pyocyanin as a biomarker of Pseudomonas aeruginosa, a common causative agent of VAP. The results of this study indicated that electrochemical detection of Pyocyanin using a GCM catalyst shows promising potential for various applications, including clinical diagnostics and drug discovery.

This paper presents a model-free fault detection and isolation (FDI) method for nonlinear dynamical systems using Koopman operator theory and linear geometric technique. The key idea is to obtain a Koopman-based reduced-order model of a nonlinear dynamical system and apply the linear geometric FDI method to detect and isolate faults in the system. Koopman operator is an infinite-dimensional, linear operator which lifts the nonlinear dynamic data into an infinite-dimensional space where the correlations of dynamic data behave linearly. However, due to the infinite dimensionality of this operator, an approximation of the operator is needed for practical purposes. In this work, the Koopman framework is adopted toward nonlinear dynamical systems in combination with the linear geometric approach for fault detection and isolation. In order to demonstrate the efficacy of the proposed FDI solution, a mathematical nonlinear dynamical system, and an experimental three-tank setup are considered. Results show a remarkable performance of the proposed geometric Koopman-based fault detection and isolation (K-FDI) technique.

Due to recent increase in deployment of Cyber-Physical Industrial Control Systems in different critical infrastructures, addressing cyber-security challenges of these systems is vital for assuring their reliability and secure operation in presence of malicious cyber attacks. Towards this end, developing a testbed to generate real-time data-sets for critical infrastructure that would be utilized for validation of real-time attack detection algorithms are indeed highly needed. This paper investigates and proposes the design and implementation of a cyber-physical industrial control system testbed where the Tennessee Eastman process is simulated in real-time on a PC and the closed-loop controllers are implemented on the Siemens PLCs. False data injection cyber attacks are injected to the developed testbed through the man-in-the-middle structure where the malicious hackers can in real-time modify the sensor measurements that are sent to the PLCs. Furthermore, various cyber attack detection algorithms are developed and implemented in real-time on the testbed and their performance and capabilities are compared and evaluated.

This paper presents a new method for robot interception planning based on the proportional navigation. Guidance laws are basically developed for aerospace applications where a pursuer impacts a target using these methods, however in the robotic application it is required to have a smooth grasp between the robot and the goal. In this method, a new term is considered for longitude axis to have the control on the final approaching velocity. The proposed method not only ensures the position and velocity match (also referred to as rendezvous) but also can be used to set the final closing velocity to any desired value. Approaching velocity can be zero for grasping the goal or a specific known velocity for hitting it in a controlled manner. It is shown that the capture region of the proposed approach is wider that other proportional navigation based methods. The proposed method is implemented on Qbot-2 and its performance is experimentally validated.

Simulators for extracorporeal membrane oxygenation (ECMO) have problems of bulky devices and low-fidelity methodologies. Hence, ongoing efforts for optimizing modern solutions focus on minimizing expenses and blending training with the intensive care unit. This is particularly evident following the coronavirus pandemic, where economic resources have been extensively cut. In this paper, as a part of an ECMO simulator for training management, an advance thermochromic ink system for medical blood simulation is presented. The system was developed and enhanced as a prototype with successful and reversible transitions between dark and bright red blood color to simulate blood oxygenation and deoxygenation in ECMO training sessions.

Despite many advancements in extracorporeal membrane oxygenation (ECMO), the procedure is still correlated with a high risk of patient complications. Simulation-based training provides the opportunity for ECMO staff to practice on real-life scenarios without exposing ECMO patients to medical errors while practicing. At Hamad Medical Corporation (HMC) in Qatar, there is a critical need of expert ECMO staff. Thus, a modular ECMO simulator is being developed to enhance the training process in a cost-effective manner. This ECMO simulator gives the instructor the ability to control the simulation modules and run common simulation scenarios through a tablet application. The core modules of the simulation system are placed in the patient unit. The unit is designed modularly such that more modules can be added throughout the simulation sessions to increase the realism of the simulation sessions. The new approach is to enclose the patient unit in a trolley, which is custom-designed and made to include all the components in a modular fashion. Each module is enclosed in a separate box and then mounted to the main blood simulation loop box using screws, quick connect/disconnect liquid fittings, and electrical plugs. This method allows fast upgrade and maintenance for each module separately as well as upgrading modules easily without modifying the trolley’s design. The prototype patient unit has been developed for portability, maintenance, and extensibility. After implementation and testing, the prototype has proven to successfully simulate the main visual and audio cues of the real emergency scenarios, while keeping costs to a minimum.

Background: Myocardial ischemia is one of several causes of prolonged QT dispersion. The aim of this study was to evaluate the effect that percutaneous coronary intervention has on the depolarization and repolarization parameters of surface electrocardiography in patients with chronic stable angina.Methods: We assessed the effects of full revascularization in patients with chronic stable angina and single-vessel disease who underwent percutaneous coronary intervention. Twelve-lead electrocardiograms were recorded before intervention and 24 hours subsequently. We measured parameters including QRS duration, QT and corrected QT durations, and JT and corrected JT duration in both electrocardiograms and compared the values.Results: There were significant differences between the mean QRS interval (0.086 ± 0.01sec vs. 0.082 ± 0.01 second; p value = 0.01), mean corrected QT dispersion (0.080 ± 0.04 sec vs. 0.068 ± 0.04 sec; p value = 0.001), and mean corrected JT dispersion (0.074 ± 0.04 sec vs. 0.063 ± 0.04 sec; p value = 0.001) before and after percutaneous coronary intervention. No significant differences were found between the other ECG parameters.Conclusion: Our data indicate that the shortening of corrected QT dispersion and corrected JT dispersion in patients undergoing percutaneous coronary intervention is prominent.

Background: Myocardial ischemia is one of several causes of prolonged QT dispersion. The aim of this study was to evaluate the effect that percutaneous coronary intervention has on the depolarization and repolarization parameters of surface electrocardiography in patients with chronic stable angina. Methods: We assessed the effects of full revascularization in patients with chronic stable angina and single-vessel disease who underwent percutaneous coronary intervention. Twelve-lead electrocardiograms were recorded before intervention and 24 hours subsequently. We measured parameters including QRS duration, QT and corrected QT durations, and JT and corrected JT duration in both electrocardiograms and compared the values. Results: There were significant differences between the mean QRS interval (0.086 ± 0.01sec vs. 0.082 ± 0.01 second; p value = 0.01), mean corrected QT dispersion (0.080 ± 0.04 sec vs. 0.068 ± 0.04 sec; p value = 0.001), and mean corrected JT dispersion (0.074 ± 0.04 sec vs. 0.063 ± 0.04 sec; p value = 0.001) before and after percutaneous coronary intervention. No significant differences were found between the other ECG parameters. Conclusion: Our data indicate that the shortening of corrected QT dispersion and corrected JT dispersion in patients undergoing percutaneous coronary intervention is prominent.