Autotaxin Has a Negative Role in Systemic Inflammation

The pathogenesis of sepsis involves complex interactions and a systemic inflammatory response leading eventually to multiorgan failure. Autotaxin (ATX, ENPP2) is a secreted glycoprotein largely responsible for the extracellular production of lysophosphatidic acid (LPA), which exerts multiple effects in almost all cell types through its at least six G-protein-coupled LPA receptors (LPARs). Here, we investigated a possible role of the ATX/LPA axis in sepsis in an animal model of endotoxemia as well as in septic patients. Mice with 50% reduced serum ATX levels showed improved survival upon lipopolysaccharide (LPS) stimulation compared to their littermate controls. Similarly, mice bearing the inducible inactivation of ATX and presenting with >70% decreased ATX levels were even more protected against LPS-induced endotoxemia; however, no significant effects were observed upon the chronic and systemic transgenic overexpression of ATX. Moreover, the genetic deletion of LPA receptors 1 and 2 did not significantly affect the severity of the modelled disease, suggesting that alternative receptors may mediate LPA effects upon sepsis. In translation, ATX levels were found to be elevated in the sera of critically ill patients with sepsis in comparison with their baseline levels upon ICU admission. Therefore, the results indicate a role for ATX in LPS-induced sepsis and suggest possible therapeutic benefits of pharmacologically targeting ATX in severe, systemic inflammatory disorders.     

1.5-V CMOS exponential current generator

A new low-voltage CMOS exponential current generator is proposed in this work. MOS transistors in weak-inversion region and a master?Cslave technique for the temperature compensation were used. The circuit was fabricated with standard CMOS 0.35???m process using a single supply voltage of 1.5?V. Experimental results validate the theoretical analysis and verify the effectiveness of the proposed structure. A 40?dB range linearly in dB controlled output current with less than 1.5?dB linearity error was achieved. The structure features ±1 and ±3?dB deviations for ±10% supply voltage and 80°C temperature variations, respectively.     

A survey of autonomic networking architectures: towards a Unified Management Framework

Academic and industrial research initiatives have sought to make fully autonomic networks a reality. Some of these initiatives pursued a holistic approach, while others focused on setting up functionalities for specific networking domains. These efforts did not succeed in being extensively deployed, because the goals of network operators were not satisfactorily met. These goals include unification of management operations, enablement of end‐to‐end management and enhancement of the overall system performance in a trusted way, while reducing management cost. In this paper, we analyse a set of existing autonomic management architectures and frameworks with respect to a selected set of criteria. We then identify missing parts and challenges and propose a framework to unify the most promising attributes towards a novel approach of realization of autonomic networking management. We call this proposal Unified Management Framework (UMF). Copyright © 2013 John Wiley & Sons, Ltd.     

The ARM Cortex-A8 Microprocessor IEEE Std 1500 Wrapper

This article describes the test wrapper implementation of a popular embedded microprocessor, along with an automated approach for verifying the wrapper's compliance to the standard.     

Biosynthesis of lipids and organic acids by Yarrowia lipolytica strains cultivated on glucose

The biochemical behavior of wild‐type or genetically modified (presenting decreased expression of intracellular acyl‐CoA oxidases) Yarrowia lipolytica strains cultivated on commercial glucose was studied. Flask nitrogen‐limited cultures were performed favoring the production of organic acids (and potentially the accumulation of lipid). Nitrogen depletion induced secretion of citric acid, while intracellular lipid was not produced in high quantities. Maximum total citric acid up to 49 g/L (yield 0.85 g/g glucose) was produced. In some of the wild‐type strains, an increase of glucose in the medium also induced noticeable production of acetic acid. Increasing the amount of added glucose led to an increase in the total lipid quantity (%) produced, although in the stationary growth phase the concentration of lipid declined, indicating lipid degradation even for the genetically modified strains. Total lipid amount did not exceed the value of 14%, while neutral fractions increased with increase in glucose concentration. In all cases, the total microbial lipids and major lipid fractions were composed of C₁₆ and C₁₈ (principally unsaturated) fatty acids. Finally, in several of the strains cultured in media containing a low glucose concentration, unicellular morphology was observed, while at high glucose concentrations mycelia were predominant.     

Probabilistic model checking for the quantification of DoS security threats

Secure authentication features of communication and electronic commerce protocols involve computationally expensive and memory intensive cryptographic operations that have the potential to be turned into denial-of-service (DoS) exploits. Recent proposals attempt to improve DoS resistance by implementing a trade-off between the resources required for the potential victim(s) with the resources used by a prospective attacker. Such improvements have been proposed for the Internet Key Exchange (IKE), the Just Fast Keying (JFK) key agreement protocol and the Secure Sockets Layer (SSL/TLS) protocol. In present article, we introduce probabilistic model checking as an efficient tool-assisted approach for systematically quantifying DoS security threats. We model a security protocol with a fixed network topology using probabilistic specifications for the protocol participants. We attach into the protocol model, a probabilistic attacker model which performs DoS related actions with assigned cost values. The costs for the protocol participants and the attacker reflect the level of some resource expenditure (memory, processing capacity or communication bandwidth) for the associated actions. From the developed model we obtain a Discrete Time Markov Chain (DTMC) via property preserving discrete-time semantics. The DTMC model is verified using the PRISM model checker that produces probabilistic estimates for the analyzed DoS threat. In this way, it is possible to evaluate the level of resource expenditure for the attacker, beyond which the likelihood of widespread attack is reduced and subsequently to compare alternative design considerations for optimal resistance to the analyzed DoS threat. Our approach is validated through the analysis of the Host Identity Protocol (HIP). The HIP base-exchange is seen as a cryptographic key-exchange protocol with special features related to DoS protection. We analyze a serious DoS threat, for which we provide probabilistic estimates, as well as results for the associated attacker and participants' costs.     

Estimation of behavioral user state based on eye gaze and head pose—application in an e-learning environment

Most e-learning environments which utilize user feedback or profiles, collect such information based on questionnaires, resulting very often in incomplete answers, and sometimes deliberate misleading input. In this work, we present a mechanism which compiles feedback related to the behavioral state of the user (e.g. level of interest) in the context of reading an electronic document; this is achieved using a non-intrusive scheme, which uses a simple web camera to detect and track the head, eye and hand movements and provides an estimation of the level of interest and engagement with the use of a neuro-fuzzy network initialized from evidence from the idea of Theory of Mind and trained from expert-annotated data. The user does not need to interact with the proposed system, and can act as if she was not monitored at all. The proposed scheme is tested in an e-learning environment, in order to adapt the presentation of the content to the user profile and current behavioral state. Experiments show that the proposed system detects reading- and attention-related user states very effectively, in a testbed where children’s reading performance is tracked.

Non-manual cues in automatic sign language recognition

Present work deals with the incorporation of non-manual cues in automatic sign language recognition. More specifically, eye gaze, head pose, and facial expressions are discussed in relation to their grammatical and syntactic function and means of including them in the recognition phase are investigated. Computer vision issues related to extracting facial features, eye gaze, and head pose cues are presented and classification approaches for incorporating these non-manual cues into the overall Sign Language recognition architecture are introduced.     

Adaptive Head-to-Tail: Active Queue Management based on implicit congestion signals

Active Queue Management is a convenient way to administer the network load without increasing the complexity of end-user protocols. Current AQM techniques work in two ways; the router either drops some of its packets with a given probability or creates different queues with corresponding priorities. Head-to-Tail introduces a novel AQM approach: the packet rearrange scheme. Instead of dropping, HtT rearranges packets, moving them from the head of the queue to its tail. The additional queuing delay triggers a sending rate decrease and congestion events can be avoided. The HtT scheme avoids explicit packet drops and extensive retransmission delays. In this work, we detail the HtT algorithm and demonstrate when and how it outperforms current AQM implementations. We also approach analytically its impact on packet delay and conduct extensive simulations. Our experiments show that HtT achieves better results than Droptail and RED methods in terms of retransmitted packets and Goodput.