Search results for "CHIP"
showing 10 items of 386 documents
Using regression analysis method to model and optimize the quality of chip-removing processed metal surfaces
2017
The paper aim is to identify based on regression analysis, the quantitative relationship between the cutting process parameters (cutting speed, cutting depth and feed per tooth) and the arithmetic mean deviation of the surface profile, measured longitudinally and transversely on the cutting feed direction, which describe the system at any point in the chosen experimentally studied range. The equations coefficients means the influence of the variables on the pursued answer.
Solution Processed Micro- and Nano-Bioarrays for Multiplexed Biosensing
2012
This Feature article reports on solution dispensing methodologies which enable the realization of multiplexed arrays at the micro- and nanoscale for relevant biosensing applications such as drug screening or cellular chips.
Wireless MAC processors: programming MAC protocols on commodity hardware
2012
Programmable wireless platforms aim at responding to the quest for wireless access flexibility and adaptability. This paper introduces the notion of wireless MAC processors. Instead of implementing a specific MAC protocol stack, Wireless MAC processors do support a set of Medium Access Control “commands” which can be run-time composed (programmed) through software-defined state machines, thus providing the desired MAC protocol operation. We clearly distinguish from related work in this area as, unlike other works which rely on dedicated DSPs or programmable hardware platforms, we experimentally prove the feasibility of the wireless MAC processor concept over ultra-cheap commodity WLAN hardw…
RIP-Chip analysis supports different roles for AGO2 and GW182 proteins in recruiting and processing microRNA targets.
2019
Background MicroRNAs (miRNAs) are small non-coding RNA molecules mediating the translational repression and degradation of target mRNAs in the cell. Mature miRNAs are used as a template by the RNA-induced silencing complex (RISC) to recognize the complementary mRNAs to be regulated. To discern further RISC functions, we analyzed the activities of two RISC proteins, AGO2 and GW182, in the MCF-7 human breast cancer cell line. Methods We performed three RIP-Chip experiments using either anti-AGO2 or anti-GW182 antibodies and compiled a data set made up of the miRNA and mRNA expression profiles of three samples for each experiment. Specifically, we analyzed the input sample, the immunoprecipita…
Genome-wide detection of signatures of selection in three Valdostana cattle populations
2020
International audience; The Valdostana is a local dual purpose cattle breed developed in Italy. Three populations are recognized within this breed, based on coat colour, production level, morphology and temperament: Valdostana Red Pied (VPR), Valdostana Black Pied (VPN) and Valdostana Chestnut (VCA). Here, we investigated putative genomic regions under selection among these three populations using the Bovine 50K SNP array by combining three different statistical methods based either on allele frequencies (F-ST) or extended haplotype homozygosity (iHS and Rsb). In total, 8, 5 and 8 chromosomes harbouring 13, 13 and 16 genomic regions potentially under selection were identified by at least tw…
Combined approaches to identify genomic regions involved in phenotypic differentiation between low divergent breeds: Application in Sardinian sheep p…
2019
Selective breeding has led to modifications in the genome of many livestock breeds. In this study, we identified the genomic regions that may explain some of the phenotypic differences between two closely related breeds from Sardinia. A total of 44 animals, 20 Sardinian Ancestral Black (SAB) and 24 Sardinian White (SW), were genotyped using the Illumina Ovine 50K array. A total of 68, 38 and 15 significant markers were identified using the case–control genome-wide association study (GWAS), the Bayesian population differentiation analysis (FST) and the Rsb metric, respectively. Comparisons among the approaches revealed a total of 22 overlapping markers between GWAS and FST and one marker bet…
Snapshot liver transcriptome in hepatocellular carcinoma
2012
Lately, advances in high throughput technologies in biomedical research have led to a dramatic increase in the accessibility of molecular insights at different levels of cancer biology such as genome, epigenome, transcriptome, proteome, and others. Among the diverse biological layers, the transcriptome has been most extensively studied especially due to the successful and broad introduction of the microarray technology. The future prospect of broad disposability of deep sequencing technology will furthermore lead to a more sensitive detection of lowly expressed transcripts and to an increase in the number of newly identified transcripts, but also to increase the discovery and characterizati…
Moving Learning Machine Towards Fast Real-Time Applications: A High-Speed FPGA-based Implementation of the OS-ELM Training Algorithm
2018
Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neur…
Multiprocessor SoC Implementation of Neural Network Training on FPGA
2008
Software implementations of artificial neural networks (ANNs) and their training on a sequential processor are inefficient because they do not take advantage of parallelism. ASIC and FPGA implementations employ specific hardware structures to exploit parallelism in order to improve processing speed; however, optimizing resource usage requires the use of fixed-point arithmetic, thereby losing precision, and the final system is restricted to a particular network topology. This paper presents a mixed approach based on a multiprocessor system-on-chip (SoC) on a FPGA. The use of software-driven embedded microprocessors with custom floating-point extensions for ANN related functions allows for gr…
Domain-Knowledge Optimized Simulated Annealing for Network-on-Chip Application Mapping
2013
Network-on-Chip architectures are scalable on-chip interconnection networks. They replace the inefficient shared buses and are suitable for multicore and manycore systems. This paper presents an Optimized Simulated Annealing (OSA) algorithm for the Network-on-Chip application mapping problem. With OSA, the cores are implicitly and dynamically clustered using knowledge about communication demands. We show that OSA is a more feasible Simulated Annealing approach to NoC application mapping by comparing it with a general Simulated Annealing algorithm and a Branch and Bound algorithm, too. Using real applications we show that OSA is significantly faster than a general Simulated Annealing, withou…