On-Line Instruction-checking in Pipelined Microprocessors

Microprocessors performances have increased by more than five orders of magnitude in the last three decades. As technology scales down, these components become inherently unreliable posing major design and test challenges. This paper proposes an instruction-checking architecture to detect erroneous instruction executions caused by both permanent and transient errors in the internal logic of a microprocessor. Monitoring the correct activation sequence of a set of predefined microprocessor control/status signals allow distinguishing between correctly and not correctly executed instruction

Statistical Reliability Estimation of Microprocessor-Based Systems

What is the probability that the execution state of a given microprocessor running a given application is correct, in a certain working environment with a given soft-error rate? Trying to answer this question using fault injection can be very expensive and time consuming. This paper proposes the baseline for a new methodology, based on microprocessor error probability profiling, that aims at estimating fault injection results without the need of a typical fault injection setup. The proposed methodology is based on two main ideas: a one-time fault-injection analysis of the microprocessor architecture to characterize the probability of successful execution of each of its instructions in presence of a soft-error, and a static and very fast analysis of the control and data flow of the target software application to compute its probability of success. The presented work goes beyond the dependability evaluation problem; it also has the potential to become the backbone for new tools able to help engineers to choose the best hardware and software architecture to structurally maximize the probability of a correct execution of the target softwar

Relativistically Smeared Iron Lines in the Spectra of Bright NS LMXB

We present preliminary results of a study on three bright accreting low-mass X-ray binaries hosting a neutron star, based on XMM-Newton observations. These sources (GX 340+0, GX 349+2 and SAX J1808.4-3658) show a broad Fe K alpha iron line in their spectra. This feature can be well described by relativistic line profile in each case; the good spectral resolution of the EPIC/PN and the high statistics spectra allow to put very good constraints on the disk geometry and ionization stage of the reflecting matter

NO Abatement using Microwave Micro Plasma Generated using Granular Activated Carbon

Abatement of NO using microwave micro-plasma is presented in this paper. The micro-plasma is generated using granular activated carbon (GAC) particles of size (size 2-3mm) in loosely fluidised bed in microwave filed operated at 2.45GHz. A single mode microwave cavity reactor (SMMCR) was constructed and microwave was injected through another slotted waveguide in a sandwiched manner. COMSOL Multiphysics software was used to investigate the microwave electric field and the power density within the SMMCR. Gas mixture of air and 500 ppm NO (in N2) at the flow rate of 2 l/min was passed through a quartz tube centered within SMMCR while the supplied microwave power was very low 10-80 W and NO reduction was greater than 98%. The mass of GAC used for generating the plasma was 5g. When air is mixed with NO (in N2), the efficiency of NOx reduction achieved vary greatly with respect to the supplied microwave energy and behavior has become complex and is not predictable. The gas analyzer (testo 350) was used to measure the gas (NO, NO2, CO and O2) concentration and temperature

The FDA “black box” warning on antidepressant suicide risk in young adults: More harm than benefits?

The decision made in the year 2004 by the U.S. Food and Drug Administration (FDA) to require a boxed warning on antidepressants regarding the risk of suicidality in young adults still represents a matter of controversy. The FDA warning was grounded on industry-sponsored trials carried one decade ago or earlier. However, within the past decade, an increasing number of reports have questioned the actual validity of the FDA warning, especially considering a decline in the prescription of the antidepressant drugs associated with an increase in the rate of suicidal events among people with severe depression. The present report provides an overview of the FDA black box warning, also documenting two Major Depressive Disorder patients whose refusal to undergo a pharmacological antidepressant treatment possibly led to an increased risk for suicidal behaviors. The concerns raised by the FDA black box warning need to be considered in real-world clinical practice, stating the associated clinical and public health implications

Stable odor recognition by a neuro-adaptive electronic nose

Sensitivity, selectivity and stability are decisive properties of sensors. In chemical gas sensors odor recognition can be severely compromised by poor signal stability, particularly in real life applications where the sensors are exposed to unpredictable sequences of odors under changing external conditions. Although olfactory receptor neurons in the nose face similar stimulus sequences under likewise changing conditions, odor recognition is very stable and odorants can be reliably identified independently from past odor perception. We postulate that appropriate pre-processing of the output signals of chemical sensors substantially contributes to the stability of odor recognition, in spite of marked sensor instabilities. To investigate this hypothesis, we use an adaptive, unsupervised neural network inspired by the glomerular input circuitry of the olfactory bulb. Essentially the model reduces the effect of the sensors' instabilities by utilizing them via an adaptive multicompartment feed-forward inhibition. We collected and analyzed responses of a 4 × 4 gas sensor array to a number of volatile compounds applied over a period of 18 months, whereby every sensor was sampled episodically. The network conferred excellent stability to the compounds' identification and was clearly superior over standard classifiers, even when one of the sensors exhibited random fluctuations or stopped working at all

Increasing pattern recognition accuracy for chemical sensing by evolutionary based drift compensation

Artificial olfaction systems, which mimic human olfaction by using arrays of gas chemical sensors combined with pattern recognition methods, represent a potentially low-cost tool in many areas of industry such as perfumery, food and drink production, clinical diagnosis, health and safety, environmental monitoring and process control. However, successful applications of these systems are still largely limited to specialized laboratories. Sensor drift, i.e., the lack of a sensor's stability over time, still limits real in dustrial setups. This paper presents and discusses an evolutionary based adaptive drift-correction method designed to work with state-of-the-art classification systems. The proposed approach exploits a cutting-edge evolutionary strategy to iteratively tweak the coefficients of a linear transformation which can transparently correct raw sensors' measures thus mitigating the negative effects of the drift. The method learns the optimal correction strategy without the use of models or other hypotheses on the behavior of the physical chemical sensors

Characterization of translationally controlled tumour protein from the sea anemone Anemonia viridis and transcriptome wide identification of cnidarian homologues

Gene family encoding translationally controlled tumour protein (TCTP) is defined as highly conserved among organisms; however, there is limited knowledge of non-bilateria. In this study, the first TCTP homologue from anthozoan was characterised in the Mediterranean Sea anemone, Anemonia viridis. The release of the genome sequence of Acropora digitifera, Exaiptasia pallida, Nematostella vectensis and Hydra vulgaris enabled a comprehensive study of the molecular evolution of TCTP family among cnidarians. A comparison among TCTP members from Cnidaria and Bilateria showed conserved intron exon organization, evolutionary conserved TCTP signatures and 3D protein structure. The pattern of mRNA expression profile was also defined in A. viridis. These analyses revealed a constitutive mRNA expression especially in tissues with active proliferation. Additionally, the transcriptional profile of A. viridis TCTP (AvTCTP) after challenges with different abiotic/biotic stresses showed induction by extreme temperatures, heavy metals exposure and immune stimulation. These results suggest the involvement of AvTCTP in the sea anemone defensome taking part in environmental stress and immune responses