Adjusting Laser Injections for Fully Controlled Faults

Hardware characterizations of integrated circuits have been evolving rapidly with the advent of more precise, sophisticated and cost-efficient tools. In this paper we describe how the fine tuning of a laser source has been used to characterize, set and reset the state of registers in a 90 nm chip. By adjusting the incident laser beam’s location, it is possible to choose to switch any register value from ‘ 0 ’ to ‘ 1 ’ or vice-versa by targeting the PMOS side or the NMOS side. Plus, we show how to clear a register by selecting a laser beam’s power. With the help of imaging techniques, we are able to explain the underlying phenomenon and provide a direct link between the laser mapping and the physical gate structure. Thus, we correlate the localization of laser fault injections with implementations of the PMOS and NMOS areas in the silicon substrate. This illustrates to what extent laser beams can be used to monitor the bits stored within registers, with adverse consequences in terms of security evaluation of integrated circuits

The venom composition of the parasitic wasp Chelonus inanitus resolved by combined expressed sequence tags analysis and proteomic approach

<p>Abstract</p> <p>Background</p> <p>Parasitic wasps constitute one of the largest group of venomous animals. Although some physiological effects of their venoms are well documented, relatively little is known at the molecular level on the protein composition of these secretions. To identify the majority of the venom proteins of the endoparasitoid wasp <it>Chelonus inanitus </it>(Hymenoptera: Braconidae), we have randomly sequenced 2111 expressed sequence tags (ESTs) from a cDNA library of venom gland. In parallel, proteins from pure venom were separated by gel electrophoresis and individually submitted to a nano-LC-MS/MS analysis allowing comparison of peptides and ESTs sequences.</p> <p>Results</p> <p>About 60% of sequenced ESTs encoded proteins whose presence in venom was attested by mass spectrometry. Most of the remaining ESTs corresponded to gene products likely involved in the transcriptional and translational machinery of venom gland cells. In addition, a small number of transcripts were found to encode proteins that share sequence similarity with well-known venom constituents of social hymenopteran species, such as hyaluronidase-like proteins and an Allergen-5 protein.</p> <p>An overall number of 29 venom proteins could be identified through the combination of ESTs sequencing and proteomic analyses. The most highly redundant set of ESTs encoded a protein that shared sequence similarity with a venom protein of unknown function potentially specific of the <it>Chelonus </it>lineage. Venom components specific to <it>C. inanitus </it>included a C-type lectin domain containing protein, a chemosensory protein-like protein, a protein related to yellow-e3 and ten new proteins which shared no significant sequence similarity with known sequences. In addition, several venom proteins potentially able to interact with chitin were also identified including a chitinase, an imaginal disc growth factor-like protein and two putative mucin-like peritrophins.</p> <p>Conclusions</p> <p>The use of the combined approaches has allowed to discriminate between cellular and truly venom proteins. The venom of <it>C. inanitus </it>appears as a mixture of conserved venom components and of potentially lineage-specific proteins. These new molecular data enrich our knowledge on parasitoid venoms and more generally, might contribute to a better understanding of the evolution and functional diversity of venom proteins within Hymenoptera.</p

Deep sequencing-based transcriptome analysis of Plutella xylostella larvae parasitized by Diadegma semiclausum

Background: Parasitoid insects manipulate their hosts' physiology by injecting various factors into their host upon parasitization. Transcriptomic approaches provide a powerful approach to study insect host-parasitoid interactions at the molecular level. In order to investigate the effects of parasitization by an ichneumonid wasp (Diadegma semiclausum) on the host (Plutella xylostella), the larval transcriptome profile was analyzed using a short-read deep sequencing method (Illumina). Symbiotic polydnaviruses (PDVs) associated with ichneumonid parasitoids, known as ichnoviruses, play significant roles in host immune suppression and developmental regulation. In the current study, D. semiclausum ichnovirus (DsIV) genes expressed in P. xylostella were identified and their sequences compared with other reported PDVs. Five of these genes encode proteins of unknown identity, that have not previously been reported

Variable delay ripple carry adder with carry chain interrupt detection

A statistical approach for the area efficient implementation of fast wide operand adders using early termination detection is described and analyzed. It is shown that high throughput can be achieved based on area- and routing-efficient ripple-carry adders with only marginal overhead. They share a low AT-product with Brent-Kung adders but provide designers with totally different area/delay tradeoffs. The circuit does not require full-custom design and fits well into both self-timed and synchronous designs

Efficient ASIC implementation of a real-time depth mapping stereo vision system

This paper presents a fast and area-efficient implementation of a real-time stereo vision algorithm for spatial depth mapping. The design combines two well-known area-based approaches to stereo thatching and includes an occlusion detection method. Hardware efficiency is achieved by storing only partial images on-chip, avoiding full-sized frame buffers. A low-latency dataflow-oriented structure makes it possible to process 256 x 192 pixel Input streams with a rate In excess of 50 frames per second, amounting to more than 54 million pixel x disparity measurements per second (PDS) (for a 25-pixel disparity range), or roughly 18 GOPS. The design has been Integrated In a 0.25 mu m standard CMOS technology and occupies an area of less than 3 mm(2)

Evaluation of biomarkers for in vitro prediction of drug-induced nephrotoxicity: comparison of HK-2, immortalized human proximal tubule epithelial, and primary cultures of human proximal tubular cells

There has been intensive effort to identify in vivo biomarkers that can be used to monitor drug-induced kidney damage and identify injury before significant impairment occurs. Kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), and human macrophage colony stimulating factor (M-CSF) have been validated as urinary and plasma clinical biomarkers predictive of acute and chronic kidney injury and disease. Similar validation of a high throughput in vitro assay predictive of nephrotoxicity could potentially be implemented early in drug discovery lead optimization to reduce attrition at later stages of drug development. To assess these known in vivo biomarkers for their potential for in vitro screening of drug-induced nephrotoxicity, we selected a panel of nephrotoxic agents and examined their effects on the overexpression of nephrotoxicity biomarkers in immortalized (HK-2) and primary (commercially available and freshly in-house produced) human renal proximal tubule epithelial cells. Traditional cytotoxicity was contrasted with expression levels of KIM-1, NGAL, and M-CSF assessed using ELISA and real-time quantitative reverse transcription PCR. Traditional cytotoxicity assays and biomarker assays using HK-2 cells were both unsuitable for prediction of nephrotoxicity. However, increases in protein levels of KIM-1 and NGAL in primary cells were well correlated with dose levels of known nephrotoxic compounds, with limited correlation seen in M-CSF protein and mRNA levels. These results suggest that profiling compounds against primary cells with monitoring of biomarker protein levels may have potential as in vitro predictive assays of drug-induced nephrotoxicity

A Complete Real-Time Feature Extraction and Matching System Based on Semantic Kernels Binarized

International audienceFeature extraction and matching is an important step in many current image and video processing algorithms. In this work, we designed and implemented an efficient feature extraction and matching system for sparse point correspondence search in stereo video. Our system is based on the recently proposed Semantic Kernels Binarized (SKB) algorithm, which showed superior performance with respect to other algorithms in our evaluation. The feature extraction stage has been prototyped in 180 nm technology and the complete system with two feature extraction pipelines (left and right view) together with the matching unit have been implemented on a Stratix IV FPGA where it delivers a performance of up to 42 frames per second on 720p video. Especially due to the high throughput of up to 25 k matched descriptors per frame, our system compares favourably with recent hardware implementations of similar algorithms