A glass/silicon technology for low-power robust gas sensors

Semiconductor gas sensors are devices based on metallic oxides that operate at high temperatures for achieving good sensitivities to the gases of interest. Silicon micromachined structures are often used as platforms for obtaining both high temperatures and low-power consumption at the same time. In this paper, a microstructure based on the combination of micromachined silicon substrates and glass wafers is presented. The device incorporates an array of four different thin-film gas sensors that, depending on the design, can operate at the same or at different temperatures. The designs have been optimized by the finite element method (FEM) and the geometrical parameters of the structure have been selected in order to reduce the power consumption. The full process fabrication is presented. It is based on the combination of bulk micromachining, glass structuring, anodic bonding, and sensitive material deposition. Electrical, thermal, and mechanical tests have been done to demonstrate that the devices show high robustness and can reach high temperatures with low-power consumption.     

Characterization of indoor wireless channel at 5 GHz U-NII bands

The paper reports on the experiments undertaken at the University of Wollongong to characterise fading profiles and delay parameters of an indoor wireless channels at 5 GHz U-NII bands. The measurements were undertaken at different locations around the campus with results recorded for a post-processing to calculate the Rician K-factor, the level crossing rate and the average fade duration as well as mean excess delay, rms delay spread, and the coherence bandwidth of the channel. The presented measurement results can be useful in developing a Markov chain based model of the transport channel for IEEE802.11a or HYPRLAN-2 networks. The results also indicate scenarios where the coherence bandwidth of the channel is smaller than the width of the sub-carrier OFDM channels in either of the mentioned systems.     

Detection filter design for LPV systems—a geometric approach

This paper investigates fault detection and isolation of linear parameter-varying (LPV) systems by using parameter-varying (C,A)-invariant subspace and parameter-varying unobservability subspaces. The so called “detection filter” approach, formulated as the fundamental problem of residual generation (FPRG) for linear time-invariant (LTI) systems, is extended for a class of LPV systems. The question of stability is addressed in the terms of Lyapunov quadratic stability by using linear matrix inequalities. The results are applied to the model of a generic small commercial aircraft.     

Decentralized overlapping control of a formation of unmanned aerial vehicles

Decentralized overlapping feedback laws are designed for a formation of unmanned aerial vehicles. The dynamic model of the formation with an information structure constraint in which each vehicle, except the leader, only detects the vehicle directly in front of it, is treated as an interconnected system with overlapping subsystems. Using the mathematical framework of the inclusion principle, the interconnected system is expanded into a higher dimensional space in which the subsystems appear to be disjoint. Then, at each subsystem, a static state feedback controller is designed to robustly stabilize the perturbed nominal dynamics of the subsystem. The design procedure is based on the application of convex optimization tools involving linear matrix inequalities. As a final step, the decentralized controllers are contracted back to the original interconnected system for implementation.     

Distributed intelligence for multi-camera visual surveillance

Latest advances in hardware technology and state of the art of computer vision and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. The paper proposes a multi-agent architecture for the understanding of scene dynamics merging the information streamed by multiple cameras. A typical application would be the monitoring of a secure site, or any visual surveillance application deploying a network of cameras. Modular software (the agents) within such architecture controls the different components of the system and incrementally builds a model of the scene by merging the information gathered over extended periods of time. The role of distributed artificial intelligence composed of separate and autonomous modules is justified by the need for scalable designs capable of co-operating to infer an optimal interpretation of the scene. Decentralizing intelligence means creating more robust and reliable sources of interpretation, but also allows easy maintenance and updating of the system. Results are presented to support the choice of a distributed architecture, and to prove that scene interpretation can be incrementally and efficiently built by modular software.     

Development and Characterization of a Factor V-Deficient CRISPR Cell Model for the Correction of Mutations

Factor V deficiency, an ultra-rare congenital coagulopathy, is characterized by bleeding episodes that may be more or less intense as a function of the levels of coagulation factor activity present in plasma. Fresh-frozen plasma, often used to treat patients with factor V deficiency, is a scarcely effective palliative therapy with no specificity to the disease. CRISPR/Cas9-mediated gene editing, following precise deletion by non-homologous end-joining, has proven to be highly effective for modeling on a HepG2 cell line a mutation similar to the one detected in the factor V-deficient patient analyzed in this study, thus simulating the pathological phenotype. Additional CRISPR/Cas9-driven non-homologous end-joining precision deletion steps allowed correction of 41% of the factor V gene mutated cells, giving rise to a newly developed functional protein. Taking into account the plasma concentrations corresponding to the different levels of severity of factor V deficiency, it may be argued that the correction achieved in this study could, in ideal conditions, be sufficient to turn a severe phenotype into a mild or asymptomatic one.     

Preface: Volume 68, Number 3

Modern information systems rely more and more on combining concurrent, distributed, mobile and heterogenous components. This move from old systems, typically conceived in isolation, induces the need for new languages and software architectures. In particular, coordination languages have been proposed to cleanly separate computational aspects and communication. On the other hand, software architects face the problem of specifying and reasoning about non-functional requirements. All these issues are widely perceived as fundamental to improve software productivity, to enhance maintainability, to advocate modularity, to promote reusability, and to lead to systems more tractable and more amenable to verification and global analysis.The FOCLASA workshop was organized on August 24th 2002 as a satellite event of Concur'02 with the aim of bringing together researchers working on the foundations of component-based computing, coordination, and software architectures.This volume contains selected 12 papers presented at the workshop. They were reviewed by the program committee, consisting, besides the editors, of

• Rocco De Nicola (University of Firenze, Italy)

• Jos Luiz Fiadeiro (ATX Software and University of Lisbon, Portugal)

• Roberto Gorrieri (University of Bologna, Italy)

• Paola Inverardi (University L'Aquila, Italy)

• Joost Kok (University of Leiden, The Netherlands)

• Antonio Porto (New University of Lisbon, Portugal)

We would like to thank them together with the authors of the papers for their contribution to the meeting. We would also like to thank Michael Mislove for his help in editing this volume. Finally, we are grateful to L. Brim, M. Kretinsky, and A. Kucera for their help in organizing the workshop in Brno.     

ILB®, a Low Molecular Weight Dextran Sulphate,Restores Glutamate Homeostasis,Amino Acid Metabolism and Neurocognitive Functions in a Rat Model of Severe Traumatic Brain Injury

In a previous study, we found that administration of ILB^®, a new low molecular weight dextran sulphate, significantly improved mitochondrial functions and energy metabolism, as well as decreased oxidative/nitrosative stress, of brain tissue of rats exposed to severe traumatic brain injury (sTBI), induced by the closed-head weight-drop model of diffused TBI. Using aliquots of deproteinized brain tissue of the same animals of this former study, we here determined the concentrations of 24 amino acids of control rats, untreated sTBI rats (sacrificed at 2 and 7 days post-injury) and sTBI rats receiving a subcutaneous ILB^® administration (at the dose levels of 1, 5 and 15 mg/kg b.w.) 30 min post-impact (sacrificed at 2 and 7 days post-injury). Additionally, in a different set of experiments, new groups of control rats, untreated sTBI rats and ILB^®-treated rats (administered 30 min after sTBI at the dose levels of 1 or 5 mg/kg b.w.) were studied for their neurocognitive functions (anxiety, locomotor capacities, short- and long-term memory) at 7 days after the induction of sTBI. Compared to untreated sTBI animals, ILB^® significantly decreased whole brain glutamate (normalizing the glutamate/glutamine ratio), glycine, serine and γ-aminobutyric acid. Furthermore, ILB^® administration restored arginine metabolism (preventing nitrosative stress), levels of amino acids involved in methylation reactions (methionine, L-cystathionine, S-adenosylhomocysteine), and N-acetylaspartate homeostasis. The macroscopic evidences of the beneficial effects on brain metabolism induced by ILB^® were the relevant improvement in neurocognitive functions of the group of animals treated with ILB^® 5 mg/kg b.w., compared to the marked cognitive decline measured in untreated sTBI animals. These results demonstrate that ILB^® administration 30 min after sTBI prevents glutamate excitotoxicity and normalizes levels of amino acids involved in crucial brain metabolic functions. The ameliorations of amino acid metabolism, mitochondrial functions and energy metabolism in ILB^®-treated rats exposed to sTBI produced significant improvement in neurocognitive functions, reinforcing the concept that ILB^® is a new effective therapeutic tool for the treatment of sTBI, worth being tested in the clinical setting.