Gate-Level Simulation of Quantum Circuits

While thousands of experimental physicists and chemists are currently trying to build scalable quantum computers, it appears that simulation of quantum computation will be at least as critical as circuit simulation in classical VLSI design. However, since the work of Richard Feynman in the early 1980s little progress was made in practical quantum simulation. Most researchers focused on polynomial-time simulation of restricted types of quantum circuits that fall short of the full power of quantum computation. Simulating quantum computing devices and useful quantum algorithms on classical hardware now requires excessive computational resources, making many important simulation tasks infeasible. In this work we propose a new technique for gate-level simulation of quantum circuits which greatly reduces the difficulty and cost of such simulations. The proposed technique is implemented in a simulation tool called the Quantum Information Decision Diagram (QuIDD) and evaluated by simulating Grover's quantum search algorithm. The back-end of our package, QuIDD Pro, is based on Binary Decision Diagrams, well-known for their ability to efficiently represent many seemingly intractable combinatorial structures. This reliance on a well-established area of research allows us to take advantage of existing software for BDD manipulation and achieve unparalleled empirical results for quantum simulation

Integrating transcriptomic and proteomic data for accurate assembly and annotation of genomes

© 2017 Wong et al.; Published by Cold Spring Harbor Laboratory Press. Complementing genome sequence with deep transcriptome and proteome data could enable more accurate assembly and annotation of newly sequenced genomes. Here, we provide a proof-of-concept of an integrated approach for analysis of the genome and proteome of Anopheles stephensi, which is one of the most important vectors of the malaria parasite. To achieve broad coverage of genes, we carried out transcriptome sequencing and deep proteome profiling of multiple anatomically distinct sites. Based on transcriptomic data alone, we identified and corrected 535 events of incomplete genome assembly involving 1196 scaffolds and 868 protein-coding gene models. This proteogenomic approach enabled us to add 365 genes that were missed during genome annotation and identify 917 gene correction events through discovery of 151 novel exons, 297 protein extensions, 231 exon extensions, 192 novel protein start sites, 19 novel translational frames, 28 events of joining of exons, and 76 events of joining of adjacent genes as a single gene. Incorporation of proteomic evidence allowed us to change the designation of more than 87 predicted noncoding RNAs to conventional mRNAs coded by protein-coding genes. Importantly, extension of the newly corrected genome assemblies and gene models to 15 other newly assembled Anopheline genomes led to the discovery of a large number of apparent discrepancies in assembly and annotation of these genomes. Our data provide a framework for how future genome sequencing efforts should incorporate transcriptomic and proteomic analysis in combination with simultaneous manual curation to achieve near complete assembly and accurate annotation of genomes

Geographic and ecologic heterogeneity in elimination thresholds for the major vector-borne helminthic disease, lymphatic filariasis

<p>Abstract</p> <p>Background</p> <p>Large-scale intervention programmes to control or eliminate several infectious diseases are currently underway worldwide. However, a major unresolved question remains: what are reasonable stopping points for these programmes? Recent theoretical work has highlighted how the ecological complexity and heterogeneity inherent in the transmission dynamics of macroparasites can result in elimination thresholds that vary between local communities. Here, we examine the empirical evidence for this hypothesis and its implications for the global elimination of the major macroparasitic disease, lymphatic filariasis, by applying a novel Bayesian computer simulation procedure to fit a dynamic model of the transmission of this parasitic disease to field data from nine villages with different ecological and geographical characteristics. Baseline lymphatic filariasis microfilarial age-prevalence data from three geographically distinct endemic regions, across which the major vector populations implicated in parasite transmission also differed, were used to fit and calibrate the relevant vector-specific filariasis transmission models. Ensembles of parasite elimination thresholds, generated using the Bayesian fitting procedure, were then examined in order to evaluate site-specific heterogeneity in the values of these thresholds and investigate the ecological factors that may underlie such variability</p> <p>Results</p> <p>We show that parameters of density-dependent functions relating to immunity, parasite establishment, as well as parasite aggregation, varied significantly between the nine different settings, contributing to locally varying filarial elimination thresholds. Parasite elimination thresholds predicted for the settings in which the mosquito vector is anopheline were, however, found to be higher than those in which the mosquito is culicine, substantiating our previous theoretical findings. The results also indicate that the probability that the parasite will be eliminated following six rounds of Mass Drug Administration with diethylcarbamazine and albendazole decreases markedly but non-linearly as the annual biting rate and parasite reproduction number increases.</p> <p>Conclusions</p> <p>This paper shows that specific ecological conditions in a community can lead to significant local differences in population dynamics and, consequently, elimination threshold estimates for lymphatic filariasis. These findings, and the difficulty of measuring the key local parameters (infection aggregation and acquired immunity) governing differences in transmission thresholds between communities, mean that it is necessary for us to rethink the utility of the current anticipatory approaches for achieving the elimination of filariasis both locally and globally.</p

Evidence for Antisense Transcription Associated with MicroRNA Target mRNAs in Arabidopsis

Antisense transcription is a pervasive phenomenon, but its source and functional significance is largely unknown. We took an expression-based approach to explore microRNA (miRNA)-related antisense transcription by computational analyses of published whole-genome tiling microarray transcriptome and deep sequencing small RNA (smRNA) data. Statistical support for greater abundance of antisense transcription signatures and smRNAs was observed for miRNA targets than for paralogous genes with no miRNA cleavage site. Antisense smRNAs were also found associated with MIRNA genes. This suggests that miRNA-associated “transitivity” (production of small interfering RNAs through antisense transcription) is more common than previously reported. High-resolution (3 nt) custom tiling microarray transcriptome analysis was performed with probes 400 bp 5′ upstream and 3′ downstream of the miRNA cleavage sites (direction relative to the mRNA) for 22 select miRNA target genes. We hybridized RNAs labeled from the smRNA pathway mutants, including hen1-1, dcl1-7, hyl1-2, rdr6-15, and sgs3-14. Results showed that antisense transcripts associated with miRNA targets were mainly elevated in hen1-1 and sgs3-14 to a lesser extent, and somewhat reduced in dcl11-7, hyl11-2, or rdr6-15 mutants. This was corroborated by semi-quantitative reverse transcription PCR; however, a direct correlation of antisense transcript abundance in MIR164 gene knockouts was not observed. Our overall analysis reveals a more widespread role for miRNA-associated transitivity with implications for functions of antisense transcription in gene regulation. HEN1 and SGS3 may be links for miRNA target entry into different RNA processing pathways

Time optimal control of a high-dimensional nonlinear binary distillation column using the Luus-Jaakola optimization procedure

grantor: University of TorontoThe dynamic model of a methanol-isopropanol binary distillation column is set up from first principles with the aim of performing a time optimal control study. With 21 stages, the state of each being described by 2 variables, the time optimal control problem is 42 dimensional in its state space, with two control variables: the reflux flowrate and the reboiler heat duty. The model poses many computational challenges in its complex formulation and the nature and number of constraints on the control and the state variables. It is desired to take the system from an initial steady state to a desired steady state in minimum possible time. The Luus-Jaakola (LJ) optimization procedure is used to solve this time optimal control problem using piecewise constant control and flexible time-stage lengths. The complex model is directly used without any simplifications or transformations. In light of the special computational challenges involved, the LJ optimization procedure is found to perform very well: the best result obtained takes the system to within 4.319 * 10-4 (1-norm) of the desired state in 52.494 minutes employing a 6-stage control policy. The large computation time requirements limit experimentation with this model and possible avenues for improvements are identified.M.A.Sc

Integrating production control and scheduling in multi-site enterprises based on real-time detection of divergence

Scheduling and process control have been long recognized as the two critical building blocks in many manufacturing execution systems. Operating at the interface between the supply chain and the process, the scheduler generates a detailed schedule that has to be executed by the process so as to meet the demands originating from the supply chain. Given the tight interactions between the two, there has been wide interest in integrating scheduling and process control. Our key insight is that abnormalities which occur after generation of the original schedule trigger a divergence between the operational targets defined by the schedule and its execution. If left uncorrected, then the abnormalities will propagate between the process and the supply chain. A timely response could eliminate or minimize such effects. However, this is a challenge particularly in large multisite enterprises where the scheduling and production responsibilities are typically separated across departments and even across geographical locations. Recognizing this, we propose a novel, scalable framework for integrating scheduling and process control that detects in real time when a divergence occurs between the original schedule and its execution in the process. It then identifies the root-cause(s) of the divergence, i.e., the abnormality, and triggers a suitable response from the scheduler and the process so as to nullify or minimize its effect. In this paper, we will describe the proposed approach and illustrate it using two industrially motivated case studies.by Preeti Rathi, Shanmukha Manoj Bhumireddy, Naresh Nandola, Iiro Harjunkoski and Rajagopalan Srinivasa

Influence of ethylene-Oxy spacer group on the activity of linezolid: synthesis of potent antibacterials possessing a thiocarbonyl group

The influence of an ethylene-oxy spacer element between the heterocycle and the aromatic ring in linezolid is reported. The introduction of such spacer group generated compounds with inferior antibacterial activity. However, the conversion of the acetamide group present in the linezolid analogues to either thiocarbamate or thioacetamide functionality restored the activity. The synthesis of linezolid analogues possessing the ethylene-oxy spacer group along with SAR studies with different heterocycles and preparation of some thiocarbonyl compounds possessing potent antibacterial property are presented