A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Tumor Necrosis Factor α and Interleukin-1β Acutely Inhibit AgRP Neurons in the Arcuate Nucleus of the Hypothalamus

Obesity-associated low-grade inflammation favors weight gain, whereas systemic infection frequently leads to anorexia. Thus, inflammatory signals can either induce positive or negative energy balance. In this study, we used whole-cell patch-clamp to investigate the acute effects of three important proinflammatory cytokines, tumor necrosis factor α (TNF-α), interleukin-6, and interleukin-1β (IL-1β) on the membrane excitability of agouti-related peptide (AgRP)- or proopiomelanocortin (POMC)-producing neurons. We found that both TNF-α and IL-1β acutely inhibited the activity of 35–42% of AgRP-producing neurons, whereas very few POMC neurons were depolarized by TNF-α. Interleukin-6 induced no acute changes in the activity of AgRP or POMC neurons. Our findings indicate that the effect of TNF-α and IL-1β, especially on the activity of AgRP-producing neurons, may contribute to inflammation-induced anorexia observed during acute inflammatory conditions.     

Multivariate statistical analysis for monitoring the hydrocarbon potentiality of the source rocks in the North Western Desert,Egypt

The authors aimed to examine a multivariate statistical analysis approach for monitoring the hydrocarbon potentiality of source rocks in the North Western Desert to recognize the potentiality of source rocks and subsequently investigate the maturation level of the proven potential source formations for oil preservation. To achieve this aim, they applied multivariate statistics analysis (principle component analysis [PCA], cluster analysis, and correlation coefficient) and Rock-Eval pyrolysis analyses. The results showed that both PCA and cluster analyses have showed two types of source rocks. The first is classified as poor to fair source rock and immature to marginally mature source rock, the second is considered as fair to good source rock and mature to post mature source rock. PCA extracted two independent factors, which explained 81.87% of the total variance. The first type of source rock was responsible for 50% of the total variance and was best represented by variables TOC, S2, OI, and R_o, and the second one was responsible for 31.65% of the total variance and was represented by the HI variable. Pearson correlation coefficient showed a significant positive correlation between TOC and S2 or R_o. A positive correlation between S2 and HI or OI and also between OI and R_o was observed, while no significant correlation was noticed between HI and R_o.     

Multi-leader coordination algorithm for networks with switching topology and quantized information

This paper analyzes the stability and convergence properties of a proportional–integral protocol for coordination of a network of agents with dynamic information flow and quantized information exchange. In the setup adopted, each agent is only required to exchange its coordination state with its neighboring agents, and the desired reference rate is only available to a group of leaders. We show that the integral term of the protocol allows the agents to learn the reference rate, rather than have it available a priori, and also provides disturbance rejection capabilities. The paper addresses the case where the graph that captures the underlying network topology is not connected during some interval of time or even fails to be connected at all times.     

Lithium disilicate glass produced at high pressure: Characterization of structural,thermal and mechanical properties

In this work, high-density lithium disilicate (LS₂) vitreous systems were produced by melting and quenching under high pressure (7.7 GPa) following two distinct experimental routes. In the first case, LS₂ glass was remelted at 7.7 GPa and 1600°C and, then, quenched. In the second case, a stoichiometric mixture of precursor oxides (Li₂O and SiO₂) was melted at 1600°C and 7.7 GPa before quenching. A reference LS₂ glass sample was produced at atmospheric pressure using conventional melting and quenching procedure. The samples were characterized by X-ray diffraction, differential thermal analysis, and instrumented ultramicro hardness measurements. X-ray diffraction confirmed that all samples were amorphous and thermal analysis suggests that different glassy structures were produced depending on the route of synthesis. Hardness and elastic modulus of the glasses produced under high pressure were higher than those of the reference glass, reflecting the irreversible densification effect induced by the high-pressure processing.     

Melanocytes Affect Nodal Expression and Signaling in Melanoma Cells: A Lesson from Pediatric Large Congenital Melanocytic Nevi

Expression of Nodal, a Transforming Growth Factor-beta (TGF-β) related growth factor, is associated with aggressive melanoma. Nodal expression in adult dysplastic nevi may predict the development of aggressive melanoma in some patients. A subset of pediatric patients diagnosed with giant or large congenital melanocytic nevi (LCMN) has shown increased risk for development of melanoma. Here, we investigate whether Nodal expression can help identify the rare cases of LCMN that develop melanoma and shed light on why the majority of these patients do not. Immunohistochemistry (IHC) staining results show varying degree of Nodal expression in pediatric dysplastic nevi and LCMN. Moreover, median scores from Nodal IHC expression analysis were not significantly different between these two groups. Additionally, none of the LCMN patients in this study developed melanoma, regardless of Nodal IHC levels. Co-culture experiments revealed reduced tumor growth and lower levels of Nodal and its signaling molecules P-SMAD2 and P-ERK1/2 when melanoma cells were grown in vivo or in vitro with normal melanocytes. The same was observed in melanoma cells cultured with melanocyte conditioned media containing pigmented melanocyte derived melanosomes (MDM). Since MDM contain molecules capable of inactivating radical oxygen species, to investigate potential anti-oxidant effect of MDM on Nodal expression and signaling in melanoma, melanoma cells were treated with either N-acetyl-l-cysteine (NAC), a component of the anti-oxidant glutathione or synthetic melanin, which in addition to providing pigmentation can also exert free radical scavenging activity. Melanoma cells treated with NAC or synthetic melanin showed reduced levels of Nodal, P-SMAD2 and P-ERK1/2 compared to untreated melanoma cells. Thus, the potential role for Nodal in melanoma development in LCMN is less evident than in adult dysplastic nevi possibly due to melanocyte cross-talk in LCMN capable of offsetting or delaying the pro-melanoma effects of Nodal via anti-oxidant effects of MDM.     

Positive invariant set estimation of adaptive controller in the presence of input saturation

For a class of linear dynamical systems with constant unknown parameters, an adaptive control scheme is developed that provides stable adaptation in the presence of input magnitude constraints. Whereas for open‐loop stable systems the results are global, for open‐loop unstable systems, the problem of nonconservative estimation of the nonempty positive invariant set is cast into an LMI framework, which can be efficiently solved numerically via convex optimization. To achieve this, a standard result toward invariant set characterization is appropriately extended to accommodate bounded disturbance and model uncertainties. In addition to closed‐loop stability, performance bounds of the adaptive closed‐loop system are analyzed, and the degradation due to the possible control deficiency is quantified. Simulation examples of aerospace applications are included to illustrate the proposed method. Copyright © 2012 John Wiley & Sons, Ltd.     

Oil: Source rock correlations of Al Baraka oil field,Komombo basin,South Egypt: An implication from biomarkers characteristics

The objectives of this study are the correlation between the oil samples recovered from the Lower Cretaceous reservoirs and Lower and Upper Cretaceous source rocks. The investigated biomarkers of five oils indicated the oils were derived from mixed marine and terrigenous (lacustrine) organic matter and deposited under suboxic to anoxic conditions. These oils were also generated from source rocks of high thermal maturity at the peak oil window. So, based on the molecular indicators of organic source input,depositional environment and maturity parameters of oils and extracts, we can conclude that the oil recovered from Al Baraka oil field were derived from Lower Cretaceous source rocks especially KomOmbo (B) source rocks where it reached the oil window. Furthermore, we can indicate that the other lower Cretaceous formations as Abu Ballas Formation will have the opportunity to generate and expel oil at the deeper part of the basin as shown in the eastern part of the basin.     

Overlapping Shadow Rendering for Outdoor Augmented Reality

Realism rendering methods of outdoor augmented reality (AR) is an interesting topic. Realism items in outdoor AR need advanced impacts like shadows, sunshine, and relations between unreal items. A few realistic rendering approaches were built to overcome this issue. Several of these approaches are not dealt with real-time rendering. However, the issue remains an active research topic, especially in outdoor rendering. This paper introduces a new approach to accomplish reality real-time outdoor rendering by considering the relation between items in AR regarding shadows in any place during daylight. The proposed method includes three principal stages that cover various outdoor AR rendering challenges. First, real shadow recognition was generated considering the sun’s location and the intensity of the shadow. The second step involves real shadow protection. Finally, we introduced a shadow production algorithm technique and shades through its impacts on unreal items in the AR. The selected approach’s target is providing a fast shadow recognition technique without affecting the system’s accuracy. It achieved an average accuracy of 95.1% and an area under the curve (AUC) of 92.5%. The outputs demonstrated that the proposed approach had enhanced the reality of outside AR rendering. The results of the proposed method outperformed other state-of-the-art rendering shadow techniques’ outcomes.     

Adaptive output feedback control methodology applicable to non-minimum phase nonlinear systems

An adaptive output feedback control methodology is developed for a class of uncertain multi-input multi-output nonlinear systems using linearly parameterized neural networks. The methodology can be applied to non-minimum phase systems if the non-minimum phase zeros are modeled to a sufficient accuracy. The control architecture is comprised of a linear controller and a neural network. The neural network operates over a tapped delay line of memory units, comprised of the system's input/output signals. The adaptive laws for the neural-network weights employ a linear observer of the nominal system's error dynamics. Ultimate boundedness of the error signals is shown through Lyapunov's direct method. Simulations of an inverted pendulum on a cart illustrate the theoretical results.