Jabba: hybrid error correction for long sequencing reads using maximal exact matches

Third generation sequencing platforms produce longer reads with higher error rates than second generation sequencing technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes. Recently, a new hybrid error correcting method has been proposed, where the second generation data is first assembled into a de Bruijn graph, on which the long reads are then aligned. In this context we present Jabba, a hybrid method to correct long third generation reads by mapping them on a corrected de Bruijn graph that was constructed from second generation data. Unique to our method is that this mapping is constructed with a seed and extend methodology, using maximal exact matches as seeds. In addition to benchmark results, certain theoretical results concerning the possibilities and limitations of the use of maximal exact matches in the context of third generation reads are presented

Model Predictive Controllers With Capacitor Voltage Balancing for a Single-Phase Five-Level SiC/Si Based ANPC Inverter

Employing both high bandwidth (HBW) controller and wide bandgap (WBG) devices in the structure of converters improve the system size, performance, and efficiency. In this paper, HBW model predictive controllers (MPCs) are proposed, with both fixed and unfixed switching frequencies, to control a single-phase five-level hybrid active neutral-point-clamped (ANPC) inverter. A hybrid modulation technique is considered in this paper, in which some of the switches are modulating with high frequency. Therefore, Silicon-Carbide (SiC) MOSFETs are employed in the converter structure to increase the switching frequency and consequently reduce the filter size and increase converter power density. To have the functionality of multilevel output voltage, some restrictions are defined in the adopted MPC with unfixed switching frequency. In the MPC with the constant switching frequency, predefined switching sequences are employed for all sectors. Moreover, to control the neutral point (NP) voltage, the applied times of both small voltage vectors are sets through a cost function. Finally, the simulation and experimental results prove the ability of both proposed methods to control the voltages of the load and NP.This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/This work was supported by the APETT project, funded by Innovation Fund Denmark.fi=vertaisarvioitu|en=peerReviewed

Land use optimization using the fuzzy mathematical-spatial approach: a case study of Chelgerd watershed, Iran

In recent years, inappropriate land use, urban and industrial development along with different pollutions emanating from it gives rise to loss of natural resources and further leads to destructive floods, soil erosion, sedimentation and other various environmental, economic and social damages. Thus, management and planning are essential for the proper utilization, protection and revival of these resources. This study aimed to develop a mathematical-spatial optimum utilization model using FGP – MOLA in watershed including environmental and economic objectives while considering social issues. The results showed that the proposed model can lead to economic growth to 37% and decreasing the environmental damages to 2.4%. Under optimized condition, the area allocated to dry farming lands will decrease about 12% and gardens will increase about 423% and the other land uses remain unchanged too. In addition to, the results demonstrated the usefulness and efficiency of the proposed fuzzy model due to its flexibility and capability to simultaneously provide both optimum values and location of production resources

Jabba: hybrid error correction for long sequencing reads

Background: Third generation sequencing platforms produce longer reads with higher error rates than second generation technologies. While the improved read length can provide useful information for downstream analysis, underlying algorithms are challenged by the high error rate. Error correction methods in which accurate short reads are used to correct noisy long reads appear to be attractive to generate high-quality long reads. Methods that align short reads to long reads do not optimally use the information contained in the second generation data, and suffer from large runtimes. Recently, a new hybrid error correcting method has been proposed, where the second generation data is first assembled into a de Bruijn graph, on which the long reads are then aligned. Results: In this context we present Jabba, a hybrid method to correct long third generation reads by mapping them on a corrected de Bruijn graph that was constructed from second generation data. Unique to our method is the use of a pseudo alignment approach with a seed-and-extend methodology, using maximal exact matches (MEMs) as seeds. In addition to benchmark results, certain theoretical results concerning the possibilities and limitations of the use of MEMs in the context of third generation reads are presented. Conclusion: Jabba produces highly reliable corrected reads: almost all corrected reads align to the reference, and these alignments have a very high identity. Many of the aligned reads are error-free. Additionally, Jabba corrects reads using a very low amount of CPU time. From this we conclude that pseudo alignment with MEMs is a fast and reliable method to map long highly erroneous sequences on a de Bruijn graph

Direct electron transfer of laccase enzyme based on RGO/AuNPs/PNR

Biofuel cell has been received much attention in recent years because the global energy demand increases every year. This paper presents a design of  Mytheliophthora thermophile laccase on the electrode as a biocathode for biofuel cells based on direct electron transfer (DET) between the active site of the enzyme and reduced graphene oxide-gold nanoparticles-poly neutral red (RGO/AuNPs/PNR). The RGO/AuNPs/PNR/laccase biocathode was characterized by cyclic voltammetry (CV) method. The CV experiments demonstrated the activity, direct electron transfer, and stability of immobilized enzyme on the nanocomposite. The results showed the immobilized enzyme had good stability and performance on the nanocomposite after 10 days. Therefore, the presented method would be used in the design of biosensors or biocathode of biofuel cells

BrownieAligner : accurate alignment of Illumina sequencing data to de Bruijn graphs

Background: Aligning short reads to a reference genome is an important task in many genome analysis pipelines. This task is computationally more complex when the reference genome is provided in the form of a de Bruijn graph instead of a linear sequence string. Results: We present a branch and bound alignment algorithm that uses the seed-and-extend paradigm to accurately align short Illumina reads to a graph. Given a seed, the algorithm greedily explores all branches of the tree until the optimal alignment path is found. To reduce the search space we compute upper bounds to the alignment score for each branch and discard the branch if it cannot improve the best solution found so far. Additionally, by using a two-pass alignment strategy and a higher-order Markov model, paths in the de Bruijn graph that do not represent a subsequence in the original reference genome are discarded from the search procedure. Conclusions: BrownieAligner is applied to both synthetic and real datasets. It generally outperforms other state-of-the-art tools in terms of accuracy, while having similar runtime and memory requirements. Our results show that using the higher-order Markov model in BrownieAligner improves the accuracy, while the branch and bound algorithm reduces runtime. BrownieAligner is written in standard C++11 and released under GPL license. BrownieAligner relies on multithreading to take advantage of multi-core/multi-CPU systems

An integrated model of cellular manufacturing and supplier selection considering product quality

Today’s business environment has forced manufacturers and plants to produce high-quality products at low cost and the shortest possible delivery time. To cope with this challenge, manufacturing organizations need to optimize the manufacturing and other functions that are in logical association with each other. Therefore, manufacturing system design and supplier selection process are linked together as two major and interrelated decisions involved in viability of production firm. As a matter of fact, production and purchasing functions interact in the form of an organization’s overall operation and jointly determine corporate success. In this research, we tried to show the relationship between designing cellular manufacturing system (CMS) and supplier selection process by providing product quality considerations as well as the imprecise nature of some input parameters including parts demands and defects rates. A unified fuzzy mixed integer linear programming model is developed to make the interrelated cell formation and supplier selection decisions simultaneously and to obtain the advantages of this integrated approach with product quality and consequently reduction of total cost. Computational results also display the efficiency of proposed mathematical model for simultaneous consideration of cellular manufacturing design and supplier selection as compared to when these two decisions separately taken into account

Audit fees prediction using fuzzy models

The current study aims to predict the optimal amount of independent audit fees based on the factors influencing audit fees. To identify the factors influencing audit fees, the stakeholders of 30 auditing firms, members of the Iranian Association of Certified Public Accountants in Tehran selected randomly, were interviewed. Finally, the linear programming model for audit fees and its determinants is defined and sum of squared error is used to solve the function with minimum. Also, given that the data are quantitative and comparative and normally distributed, Pearson’s correlation coefficient is used to test the research hypotheses. The results show that a positive significant correlation exists between the variables of expected time to perform audit procedures, the number of accounting documents, audit operation risk, complexity of operations, existence of specific rules and regulations governing the activities of the entit