Global tracking sliding mode control for a class of nonlinear systems via variable gain observer

A novel output‐feedback sliding mode control strategy is proposed for a class of single‐input single‐output (SISO) uncertain time‐varying nonlinear systems for which a norm state estimator can be implemented. Such a class encompasses minimum‐phase systems with nonlinearities affinely norm bounded by unmeasured states with growth rate depending nonlinearly on the measured system output and on the internal states related with the zero‐dynamics. The sliding surface is generated by using the state of a high gain observer (HGO) whereas a peaking free control amplitude is obtained via a norm observer. In contrast to the existing semi‐global sliding mode control solutions available in the literature for the class of plants considered here, the proposed scheme is free of peaking and achieves global tracking with respect to a small residual set. The key idea is to design a time‐varying HGO gain implementable from measurable signals. Copyright © 2010 John Wiley & Sons, Ltd.     

Sketch-based warping of RGBN images

While current image deformation methods are careful in making the new geometry seem right, little attention has been given to the photometric aspects. We introduce a deformation method that results in coherently illuminated objects. For this task, we use RGBN images to support a relighting step integrated in a sketch-based deformation method. We warp not only colors but also normals. Normal warping requires smooth warping fields. We use sketches to specify sparse warping samples and impose additional constraints for region of interest control. To satisfy these new constraints, we present a novel image warping method based on Hermite–Birkhoff interpolation with radial basis functions that results in a smooth warping field. We also use sketches to help the system identify both lighting conditions and material from single images. We present results with RGBN images from different sources, including photometric stereo, synthetic images, and photographs.     

Multicriteria Decision Model to Establish Maintenance Priorities for Wells in a Groundwater System

When exploiting groundwater, it is common to have problems with wells since maintenance activities can interrupt not only the production of water but also its distribution. Planning maintenance activities is a challenge that involves multiple agents, several criteria, and subjective variables. Therefore, this paper proposes a decision model based on a multicriteria approach to prioritize maintenance actions in the wells of a groundwater supply system. The proposed model considers different points of view and has three phases. The first phase consists of understanding the problem and acquiring data. Next, there is a learning process, during which Strategic Options Development and Analysis (SODA), a structuring method, is applied. The third phase uses the Elimination et Choix Traduisant la Realité (Elimination and Choice Translating Reality, “ELECTRE III”) method to evaluate the problem. To determine criteria weights, Simos’ Procedure is used. The model is shown to have established management priorities that assist in making maintenance decisions. Efficiency of the model was demonstrated by applying it in a Brazilian town, where it was seen to yield greater benefits both to the supply company and society than does current maintenance management practice.

     

ECO–ALOC: Energy-efficient resource allocation for cluster-based software routers

In this paper, we explore the use of cluster-based software routers as a way to share hardware resources, reduce costs, and save energy. We propose ECO–ALOC, an energy-efficient resource allocation mechanism that reconfigures the router according to the traffic demands using two modules. The first module provides fine-grained energy consumption control by switching CPU operation frequencies among three special frequencies. The second module provides long-term power savings by using virtual router migration to consolidate the load and shut idle servers down. We simulate a cluster-based software router using real traffic traces to evaluate our proposal. Results show that ECO–ALOC provides power savings of up to 93% depending on the cluster load scenario.     

Using Broadcast Networks to Create On-demand Extremely Large Scale High-throughput Computing Infrastructures

A growing number of very simple parallel applications can benefit from the availability of very large computing resource pools that are exploited in an opportunistic way to considerably speed up the processing of these applications. In particular, many applications can scale out to take advantage of the availability of thousands, or even millions, of processors that can be simultaneously used. Some large-scale distributed computing infrastructures (DCI) have already been successfully assembled to this end. However, these DCI are normally designed to cater to specific kinds of applications, and their assemblage is not only costly, but also time consuming. We propose a novel architecture, named OddCI (On-demand DCI), for the cheap, fast and on-demand instantiation and dismantle of very large DCI. These characteristics allow application users to dynamically commission DCI that can cost-effectively be customized to their particular needs, and disposed after being used. Our approach leverages on broadcast communication as an efficient mechanism to enable aggregation of geographically distributed computing resources, including millions of non-traditional processing devices such as mobile phones, and digital television (DTV) receivers. We discuss how the proposed architecture can be implemented on top of a network of DTV receivers, providing evidences of both the technical, as well as the operational feasibility of the OddCI architecture.     

Experimental study of PLA thermal behavior during fused filament fabrication

Fused filament fabrication (FFF) is an additive manufacturing technique that is used to produce prototypes and a gradually more important processing route to obtain final products. Due to the layer-by-layer deposition mechanism involved, bonding between adjacent layers is controlled by the thermal energy of the material being printed, which strongly depends on the temperature development of the filaments during the deposition sequence. This study reports experimental measurements of filament temperature during deposition. These temperature profiles were compared to the predictions made by a previously developed model. The two sets of data showed good agreement, particularly concerning the occurrence of reheating peaks when new filaments are deposited onto previously deposited ones. The developed experimental technique is shown to demonstrate its sensitivity to changing operating conditions, namely platform temperature and deposition velocity. The data generated can be valuable to predict more accurately the bond quality achieved in FFF parts.     

The Quorum Sensing Auto-Inducer 2 (AI-2) Stimulates Nitrogen Fixation and Favors Ethanol Production over Biomass Accumulation in Zymomonas mobilis

Autoinducer 2 (or AI-2) is one of the molecules used by bacteria to trigger the Quorum Sensing (QS) response, which activates expression of genes involved in a series of alternative mechanisms, when cells reach high population densities (including bioluminescence, motility, biofilm formation, stress resistance, and production of public goods, or pathogenicity factors, among others). Contrary to most autoinducers, AI-2 can induce QS responses in both Gram-negative and Gram-positive bacteria, and has been suggested to constitute a trans-specific system of bacterial communication, capable of affecting even bacteria that cannot produce this autoinducer. In this work, we demonstrate that the ethanologenic Gram-negative bacterium Zymomonas mobilis (a non-AI-2 producer) responds to exogenous AI-2 by modulating expression of genes involved in mechanisms typically associated with QS in other bacteria, such as motility, DNA repair, and nitrogen fixation. Interestingly, the metabolism of AI-2-induced Z. mobilis cells seems to favor ethanol production over biomass accumulation, probably as an adaptation to the high-energy demand of N₂ fixation. This opens the possibility of employing AI-2 during the industrial production of second-generation ethanol, as a way to boost N₂ fixation by these bacteria, which could reduce costs associated with the use of nitrogen-based fertilizers, without compromising ethanol production in industrial plants.     

Electrophysiology of hiPSC-Cardiomyocytes Co-Cultured with HEK Cells Expressing the Inward Rectifier Channel

The immature electrophysiology of human-induced pluripotent stem cell-derived cardiomyocytes (hiCMs) complicates their use for therapeutic and pharmacological purposes. An insufficient inward rectifying current (I_K1) and the presence of a funny current (if) cause spontaneous electrical activity. This study tests the hypothesis that the co-culturing of hiCMs with a human embryonic kidney (HEK) cell-line expressing the Kir2.1 channel (HEK-I_K1) can generate an electrical syncytium with an adult-like cardiac electrophysiology. The mechanical activity of co-cultures using different HEK-I_K1:hiCM ratios was compared with co-cultures using wildtype (HEK–WT:hiCM) or hiCM alone on days 3–8 after plating. Only ratios of 1:3 and 1:1 showed a significant reduction in spontaneous rate at days 4 and 6, suggesting that I_K1 was influencing the electrophysiology. Detailed analysis at day 4 revealed an increased incidence of quiescent wells or sub-areas. Electrical activity showed a decreased action potential duration (APD) at 20% and 50%, but not at 90%, alongside a reduced amplitude of the aggregate AP signal. A computational model of the 1:1 co-culture replicates the electrophysiological effects of HEK–WT. The addition of the I_K1 conductance reduced the spontaneous rate and APD20, 50 and 90, and minor variation in the intercellular conductance caused quiescence. In conclusion, a 1:1 co-culture HEK-I_K1:hiCM caused changes in electrophysiology and spontaneous activity consistent with the integration of I_K1 into the electrical syncytium. However, the additional electrical effects of the HEK cell at 1:1 increased the possibility of electrical quiescence before sufficient I_K1 was integrated into the syncytium.     

Artificial Intelligence Applied to the Rapid Identification of New Antimalarial Candidates with Dual-Stage Activity

Increasing reports of multidrug-resistant malaria parasites urge the discovery of new effective drugs with different chemical scaffolds. Protein kinases play a key role in many cellular processes such as signal transduction and cell division, making them interesting targets in many diseases. Protein kinase 7 (PK7) is an orphan kinase from the Plasmodium genus, essential for the sporogonic cycle of these parasites. Here, we applied a robust and integrative artificial intelligence-assisted virtual-screening (VS) approach using shape-based and machine learning models to identify new potential PK7 inhibitors with in vitro antiplasmodial activity. Eight virtual hits were experimentally evaluated, and compound LabMol-167 inhibited ookinete conversion of Plasmodium berghei and blood stages of Plasmodium falciparum at nanomolar concentrations with low cytotoxicity in mammalian cells. As PK7 does not have an essential role in the Plasmodium blood stage and our virtual screening strategy aimed for both PK7 and blood-stage inhibition, we conducted an in silico target fishing approach and propose that this compound might also inhibit P. falciparum PK5, acting as a possible dual-target inhibitor. Finally, docking studies of LabMol-167 with P. falciparum PK7 and PK5 proteins highlighted key interactions for further hit-to lead optimization.