scholarly journals Expanding the Molecular Alphabet of DNA-Based Data Storage Systems with Neural Network Nanopore Readout Processing

2021 ◽  
Author(s):  
S. Kasra Tabatabaei ◽  
Bach Pham ◽  
Chao Pan ◽  
Jingqian Liu ◽  
Shubham Chandak ◽  
...  
Keyword(s):  
Neural Network ◽  
Data Storage ◽  
Network Architecture ◽  
Double Helix ◽  
Storage System ◽  
Fold Increase ◽  
Data Retrieval ◽  
Modified Nucleotides ◽  
Recording Time ◽  
Dna Double Helix

DNA is a promising next-generation data storage medium, but the recording latency and synthesis cost of oligos using the four natural nucleotides remain high. Here, we describe an improved DNA-based storage system that uses an extended 11-letter molecular alphabet combining natural and chemically modified nucleotides. Our extended-alphabet molecular storage paradigm offers a nearly two-fold increase in storage density and potentially the same order of reduction in the recording time. Experimental results involving a library of 77 custom-designed hybrid sequences reveal that one can readily detect and discriminate different combinations and orders of monomers via MspA nanopores. Furthermore, a neural network architecture designed to classify raw current signals generated by Oxford Nanopore Technologies sequencing ensures an average accuracy exceeding 60%, which is 39 times higher than that of random guessing. Molecular dynamics simulations reveal that the majority of modified nucleotides do not induce dramatic disruption of the DNA double helix, making the extended alphabet system potentially compatible with PCR-based random access data retrieval. The methodologies proposed provide a forward path for new implementations of molecular recorders.

scholarly journals Desain Dan Implementasi Data Warehouse Pada Perpustakaan Daerah Provinsi Sumatera Selatan

2021 ◽  
Vol 2 (1) ◽  
pp. 33-50
Author(s):  
Nia Adila ◽  
Andri Andri
Keyword(s):  
Data Warehouse ◽  
Data Storage ◽  
Storage System ◽  
Data Retrieval ◽  
Design Stage ◽  
Process Selection ◽  
Step Method ◽  
Analysis Process ◽  
Data Book ◽  
Data Member

This research will focus on processing visitor data, member data, book borrowing data and book return data at the Regional Library of South Sumatra Province. The data is stored in the form of an excel file with a large amount of data, causing problems in the storage system such as data accumulation, data loss, no data analysis and delays in the reporting process. The process of data storage and data retrieval will be well integrated by building a data Warehouse at the Regional Library of South Sumatra Province. Data Warehouse is a system that contains several years of history and facilitates decision making. At the data Warehouse design stage using the Nine-Step method (Kimball, 2002), in this method there are nine steps in designing a data Warehouse, namely Process Selection, Grain Selection, Identification of dimensional adjustments, Fact Selection, Storage of initial calculations in the fact table, Reviewing the dimension table, selecting the database duration, tracking dimension changes, and prioritizing, querying the model and selecting the physical design. And the design and data processing process will use the Pentaho kettle and public Tableau applications, with the design and implementation of the data Warehouse, it is expected to help facilitate the reporting and analysis process for the Regional Library of South Sumatra Province.

scholarly journals BECA: A Blockchain-Based Edge Computing Architecture for Internet of Things Systems

IoT ◽  
2021 ◽  
Vol 2 (4) ◽  
pp. 610-632
Author(s):  
Oluwashina Joseph Ajayi ◽  
Joseph Rafferty ◽  
Jose Santos ◽  
Matias Garcia-Constantino ◽  
Zhan Cui
Keyword(s):  
Internet Of Things ◽  
Data Storage ◽  
Distributed Storage ◽  
Storage System ◽  
Data Retrieval ◽  
Edge Computing ◽  
Computing Architecture ◽  
Symbiotic Relationships ◽  
Data Ownership ◽  
Latency Response

The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, such as facilitating quick data retrieval, low latency response, and advanced computation, among others. However, in contrast with the benefits offered by edge computing capabilities, there are several detractors, such as centralized data storage, data ownership, privacy, data auditability, and security, which concern the IoT community. This study leveraged blockchain’s inherent capabilities, including distributed storage system, non-repudiation, privacy, security, and immutability, to provide a novel, advanced edge computing architecture for IoT systems. Specifically, this blockchain-based edge computing architecture addressed centralized data storage, data auditability, privacy, data ownership, and security. Following implementation, the performance of this solution was evaluated to quantify performance in terms of response time and resource utilization. The results show the viability of the proposed and implemented architecture, characterized by improved privacy, device data ownership, security, and data auditability while implementing decentralized storage.

Protamine-DNA interaction

1978 ◽  
Vol 36 (2) ◽  
pp. 200-201
Author(s):  
D.P. Bazett-Jones ◽  
F.P. Ottensmeyer
Keyword(s):  
Small Volume ◽  
Double Helix ◽  
Dna Interaction ◽  
Dark Field ◽  
Sperm Head ◽  
Nuclear Proteins ◽  
Field Electron Microscopy ◽  
Dark Field Electron ◽  
Dna Double Helix ◽  
Positively Charged

Dark field electron microscopy has been used for the study of the structure of individual macromolecules with a resolution to at least the 5Å level. The use of this technique has been extended to the investigation of structure of interacting molecules, particularly the interaction between DNA and fish protamine, a class of basic nuclear proteins of molecular weight 4,000 daltons.Protamine, which is synthesized during spermatogenesis, binds to chromatin, displaces the somatic histones and wraps up the DNA to fit into the small volume of the sperm head. It has been proposed that protamine, existing as an extended polypeptide, winds around the minor groove of the DNA double helix, with protamine's positively-charged arginines lining up with the negatively-charged phosphates of DNA. However, viewing protamine as an extended protein is inconsistent with the results obtained in our laboratory.

SCORING MODELING BASED ON NEURAL NETWORKS FOR DETERMINING A BANK BORROWER'S RATING

2020 ◽  
Vol 2020 (10) ◽  
pp. 54-62
Author(s):  
Oleksii VASYLIEV ◽  
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Network Architecture ◽  
Statistical Data ◽  
Activation Function ◽  
Decision Making Process ◽  
Neural Network Architecture ◽  
Acceptable Accuracy ◽  
The Neural Network ◽  
Sigmoid Activation Function

The problem of applying neural networks to calculate ratings used in banking in the decision-making process on granting or not granting loans to borrowers is considered. The task is to determine the rating function of the borrower based on a set of statistical data on the effectiveness of loans provided by the bank. When constructing a regression model to calculate the rating function, it is necessary to know its general form. If so, the task is to calculate the parameters that are included in the expression for the rating function. In contrast to this approach, in the case of using neural networks, there is no need to specify the general form for the rating function. Instead, certain neural network architecture is chosen and parameters are calculated for it on the basis of statistical data. Importantly, the same neural network architecture can be used to process different sets of statistical data. The disadvantages of using neural networks include the need to calculate a large number of parameters. There is also no universal algorithm that would determine the optimal neural network architecture. As an example of the use of neural networks to determine the borrower's rating, a model system is considered, in which the borrower's rating is determined by a known non-analytical rating function. A neural network with two inner layers, which contain, respectively, three and two neurons and have a sigmoid activation function, is used for modeling. It is shown that the use of the neural network allows restoring the borrower's rating function with quite acceptable accuracy.

Non-Blind Image Deconvolution Based on “Ringing” Removal Using Convolutional Neural Network

2020 ◽  
Vol 2020 (10) ◽  
pp. 181-1-181-7
Author(s):  
Takahiro Kudo ◽  
Takanori Fujisawa ◽  
Takuro Yamaguchi ◽  
Masaaki Ikehara
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Network Architecture ◽  
Large Scale ◽  
Blind Deconvolution ◽  
Training Dataset ◽  
Image Deconvolution ◽  
Classic Problem ◽  
Key Points ◽  
Blind Image

Image deconvolution has been an important issue recently. It has two kinds of approaches: non-blind and blind. Non-blind deconvolution is a classic problem of image deblurring, which assumes that the PSF is known and does not change universally in space. Recently, Convolutional Neural Network (CNN) has been used for non-blind deconvolution. Though CNNs can deal with complex changes for unknown images, some CNN-based conventional methods can only handle small PSFs and does not consider the use of large PSFs in the real world. In this paper we propose a non-blind deconvolution framework based on a CNN that can remove large scale ringing in a deblurred image. Our method has three key points. The first is that our network architecture is able to preserve both large and small features in the image. The second is that the training dataset is created to preserve the details. The third is that we extend the images to minimize the effects of large ringing on the image borders. In our experiments, we used three kinds of large PSFs and were able to observe high-precision results from our method both quantitatively and qualitatively.

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