Flexible Software Research Articles

Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding

SummaryMolecular interactions at identical transcriptomic locations or at proximal but non-overlapping sites can mediate RNA modification and regulation, necessitating tools to uncover these spatial relationships. We present nearBynding, a flexible algorithm and software pipeline that models spatial correlation between transcriptome-wide tracks from diverse data types. nearBynding can process and correlate interval as well as continuous data and incorporate experimentally derived or in silico predicted transcriptomic tracks. nearBynding offers visualization functions for its statistics to identify colocalizations and adjacent features. We demonstrate the application of nearBynding to correlate RNA-binding protein (RBP) binding preferences with other RBPs, RNA structure, or RNA modification. By cross-correlating RBP binding and RNA structure data, we demonstrate that nearBynding recapitulates known RBP binding to structural motifs and provides biological insights into RBP binding preference of G-quadruplexes. nearBynding is available as an R/Bioconductor package and can run on a personal computer, making correlation of transcriptomic features broadly accessible.

ANALYSIS OF THE TRADITIONAL AND FLEXIBLE APPROACHES TO CREATING SOFTWARE IN DYNAMIC CONDITIONS

The success of the project depends on the quality of management, in particular, the management methodology chosen for the project. When it comes to developing new software, the development team and the customer are faced with the methodology choice and approach to the development of this software. The purpose of this work is to explore and analyze two completely different approaches to software development – the traditional (Waterfall) and the flexible (Agile). In the article are described implementation principles, advantages, and disadvantages of traditional (Waterfall) and flexible (Agile) methodology. It is made an emphasis on using these methodologies on real projects are made. Also, we analyzed the so-called “Project Management Triangle” and its role in project formation using different management methodologies. A visual representation of the software development process using these two methodologies was embedded to better understanding the specifics of each. During the analysis, conclusions were made regarding the relevance of methodologies in a modern, dynamic environment. Detailed description and analyze of Manifesto of Flexible Software Development, which changed people's perception of the process of developing and creating new projects not only in the field of IT but also in all other spheres of life, were conducted. As a result, were made conclusions about the inability of traditional methodologies (including the Waterfall model) to meet modern market requirements and was preferred Agile methodology, which enables customer requirements to be met in a dynamic environment, ready to changes and promote them.

HTSQualC is a flexible and one-step quality control software for high-throughput sequencing data analysis

Use of high-throughput sequencing (HTS) has become indispensable in life science research. Raw HTS data contains several sequencing artifacts, and as a first step it is imperative to remove the artifacts for reliable downstream bioinformatics analysis. Although there are multiple stand-alone tools available that can perform the various quality control steps separately, availability of an integrated tool that can allow one-step, automated quality control analysis of HTS datasets will significantly enhance handling large number of samples parallelly. Here, we developed HTSQualC, a stand-alone, flexible, and easy-to-use software for one-step quality control analysis of raw HTS data. HTSQualC can evaluate HTS data quality and perform filtering and trimming analysis in a single run. We evaluated the performance of HTSQualC for conducting batch analysis of HTS datasets with 322 samples with an average ~ 1 M (paired end) sequence reads per sample. HTSQualC accomplished the QC analysis in ~ 3 h in distributed mode and ~ 31 h in shared mode, thus underscoring its utility and robust performance. In addition to command-line execution, we integrated HTSQualC into the free, open-source, CyVerse cyberinfrastructure resource as a GUI interface, for wider access to experimental biologists who have limited computational resources and/or programming abilities.

Proposal of a Laboratory-Scale Anaerobic Biodigester for Introducing the Monitoring and Sensing Techniques, as a Potential Learning Tool in the Fields of Carbon Foot-Print Reduction and Climate Change Mitigation

This article presents a proposal of an anaerobic biodigester on a laboratory scale for introducing the monitoring and sensing techniques of the growth of microorganisms according to different parameters, where the redox potential, pH, pressure, and temperature have been measured in quasi-continuous mode. For this task, a microcontroller system was used (Atmega328—Arduino). Importantly, the design is based on flexible and open-source software, hardware, and firmware (Scilab, Arduino, Processing), facilitating its modification for other related studies. This design was developed to help engineering students to learn and to understand the operation of an anaerobic biodigester, which allows us to know various properties of the system at any time, as well as its evolution over time. In this way, property curves can be drawn and related to each other to obtain a better understanding of the biodigester operation. In this context, the relationship between the oxide-reduction reaction and microbial activity was studied so that the redox potential can be a way of measuring the growth of microorganisms in an anaerobic environment. With all this, through these parameters, it is possible to introduce to engineering students the operation of this technology used normally like a very powerful tool for the control of the carbon footprint, for example in wastewater sector, and consequently for the mitigation of the climate change.

Application-Aware Intrusion Detection: A Systematic Literature Review, Implications for Automotive Systems, and Applicability of AutoML

Modern and flexible application-level software platforms increase the attack surface of connected vehicles and thereby require automotive engineers to adopt additional security control techniques. These techniques encompass host-based intrusion detection systems (HIDSs) that detect suspicious activities in application contexts. Such application-aware HIDSs originate in information and communications technology systems and have a great potential to deal with the flexible nature of application-level software platforms. However, the elementary characteristics of known application-aware HIDS approaches and thereby the implications for their transfer to the automotive sector are unclear. In previous work, we presented a systematic literature review (SLR) covering the state of the art of application-aware HIDS approaches. We synthesized our findings by means of a fine-grained classification for each approach specified through a feature model and corresponding variant models. These models represent the approaches’ elementary characteristics. Furthermore, we summarized key findings and inferred implications for the transfer of application-aware HIDSs to the automotive sector. In this article, we extend the previous work by several aspects. We adjust the quality evaluation process within the SLR to be able to consider high quality conference publications, which results in an extended final pool of publications. For supporting HIDS developers on the task of configuring HIDS analysis techniques based on machine learning, we report on initial results on the applicability of AutoML. Furthermore, we present lessons learned regarding the application of the feature and variant model approach for SLRs. Finally, we more thoroughly describe the SLR study design.

An Intelligent Web Service Composition and Resource-Optimization Method Using K-Means Clustering and Knapsack Algorithms

Service-oriented architecture (SOA) has emerged as a flexible software design style. SOA focuses on the development, use, and reuse of small, self-contained, independent blocks of code called web services that communicate over the network to perform a certain set of simple tasks. Web services are integrated as composite services to offer complex tasks and to provide the expected services and behavior in addition to fulfilling the clients’ requests according to the service-level agreement (SLA). Web service selection and composition problems have been a significant area of research to provide the expected quality of service (QoS) and to meet the clients’ expectations. This research paper presents a hybrid web service composition model to solve web service selection and composition problems and to optimize web services’ resource utilization using k-means clustering and knapsack algorithms. The proposed model aims to maximize the service compositions’ QoS and minimize the number of web services integrated within the service composition using the knapsack algorithm. Additionally, this paper aims to track the service compositions’ QoS attributes by evaluating and tracking the web services’ QoS using the reward function and, accordingly, use the k-means algorithm to decide to which cluster the web service belongs. The experimental results on a real dataset show the superiority and effectiveness of the proposed algorithm in comparison with the results of the state–action–reward–state–action (SARSA) and multistage forward search (MFS) algorithms. The experimental results show that the proposed model reduces the average time of the web service selection and composition processes to 37.02 s in comparison to 47.03 s for the SARSA algorithm and 42.72 s for the MFS algorithm. Furthermore, the average of web services’ resource utilization results increased by 4.68% using the proposed model in comparison to the resource utilization by the SARSA and MFS algorithms. In addition, the experimental results showed that the average number of service compositions using the proposed model improved by 26.04% compared with the SARSA and MFS algorithms.

5G Standalone and 4G Multi-Carrier Network-in-a-Box Using a Software Defined Radio Framework.

In this work, an open Radio Access Network (RAN), compatible, scalable and highly flexible Software Defined Radio (SDR)-based Remote Radio Head (RRH) framework is proposed and designed. Such framework can be used to implement flexible wideband radio solutions, which can be deployed in any region, have common radio management features, and support various channel bandwidths. Moreover, it enables easier access for researchers to nonsimulated cellular networks, reduce system development time, provide test and measurement capabilities, and support existing and emerging wireless communication technologies. The performance of the proposed SDR framework is validated by creating a Network-in-a-Box (NIB) that can operate in multiband multicarrier 4G or 5G standalone (SA) configurations, with an output power of up to 33 dBm. Measurement results show, that the 4G and 5G NIB can achieve, respectively, up to 883 Mbps and 765 Mbps downlink data transfer speeds for a 100 MHz aggregated bandwidth. However, if six carriers are used in the 4G NIB, 1062 Mbps downlink data transfer speed can be achieved. When single user equipment (UE) is used, maximum uplink data transfer speed is 65.8 Mbps and 92.6 Mbps in case of 4G and 5G, respectively. The average packet latency in case of 5G is up to 45.1% lower than 4G. CPU load by the eNodeB and gNodeB is proportional to occupied bandwidth, but under the same aggregated DL bandwidth conditions, gNodeB load on the CPU is lower. Moreover, if only 1 UE is active, under same aggregated bandwidth conditions, the EPC CPU load is up to four times lower than the 5GC.

NOREC4DNA: using near-optimal rateless erasure codes for DNA storage

BackgroundDNA is a promising storage medium for high-density long-term digital data storage. Since DNA synthesis and sequencing are still relatively expensive tasks, the coding methods used to store digital data in DNA should correct errors and avoid unstable or error-prone DNA sequences. Near-optimal rateless erasure codes, also called fountain codes, are particularly interesting codes to realize high-capacity and low-error DNA storage systems, as shown by Erlich and Zielinski in their approach based on the Luby transform (LT) code. Since LT is the most basic fountain code, there is a large untapped potential for improvement in using near-optimal erasure codes for DNA storage.ResultsWe present NOREC4DNA, a software framework to use, test, compare, and improve near-optimal rateless erasure codes (NORECs) for DNA storage systems. These codes can effectively be used to store digital information in DNA and cope with the restrictions of the DNA medium. Additionally, they can adapt to possible variable lengths of DNA strands and have nearly zero overhead. We describe the design and implementation of NOREC4DNA. Furthermore, we present experimental results demonstrating that NOREC4DNA can flexibly be used to evaluate the use of NORECs in DNA storage systems. In particular, we show that NORECs that apparently have not yet been used for DNA storage, such as Raptor and Online codes, can achieve significant improvements over LT codes that were used in previous work. NOREC4DNA is available on https://github.com/umr-ds/NOREC4DNA.ConclusionNOREC4DNA is a flexible and extensible software framework for using, evaluating, and comparing NORECs for DNA storage systems.

Continuous Software Engineering and Unit Testing: From Theory to Practice

With the Agile development approach, the software industry has moved to a more flexible and continuous Software Development Life Cycle (SDLC), which integrates the stages of development, delivery and deployment. This trend has exposed a tendency of increasing reliance on both unit testing and test automation for the fundamental quality-activities during the code development. To implement Continuous Software Engineering (CSE), it is vital to assure that unit-testing activities are an integral and well-defined part of a continuous process. This paper focuses on the initial role of actual testing – viewing unit testing as a quality indicator during the development life cycle. We review the definition of unit-testing from the CSE world, and describe a qualitative study in which we examined implementation of unit testing in three software companies that recently migrated to CSE methodology. The results from the qualitative study corroborate our argument that under the continues approach, quality-based development practices such as unit testing are of increasing importance, lacking common set of measurements and KPI's. A possible explanation to this may be the role of continuous practices as well as unit testing in the software engineering curriculum

The residence of synaptically released dopamine on D2 autoreceptors.

SUMMARYNeuromodulation mediated by synaptically released endogenous transmitters acting in G-protein-coupled receptors (GPCRs) is slow primarily because of multistep downstream signaling. What is less well understood is the spatial and temporal kinetics of transmitter and receptor interaction. The present work uses the combination of the dopamine sensor, dLight, to detect the spatial release and diffusion of dopamine and a caged form of a D2-dopamine receptor antagonist, CyHQ-sulpiride, to rapidly block the D2 autoreceptors. Photoactivation of the CyHQ-sulpiride blocks receptors in milliseconds such that the time course of dopamine/receptor interaction is mapped onto the downstream signaling. The results show that highly localized release, but not dopamine diffusion, defines the time course of the functional interaction between dopamine and D2 autoreceptors, which determines downstream inhibition.

Leadership approach towards Agile, Waterfall and Iterative implementation of the software development products

The automotive industry is one of the most dynamic markets, gathering around many different sectors from material extractions to robotics and cloud computing. The current research analyses the influences and particularities of leadership and identifies the challenges and advantages of the two principal methodologies in software development projects within the automotive industry, Agile and Waterfall. Some aspects of reducing methodological disadvantages are suggested and presented. The aim is to arrive at a sustainable solution that can ensure the delivery of reliable and flexible software products. The impact of these methodologies on the quality standards and project documentation is analyzed, which is a vital part of automotive software development. By influencing the product development lifecycle, there is an opportunity to develop a structured framework that can be adopted to build software products in a more flexible and agile way.

A generic flexible and scalable framework for hierarchical parallelization of population-based metaheuristics

Parallelizing population-based metaheuristics – such as Evolutionary Algorithms (EAs) – on a cluster computing environment is a viable approach for enhancing the computational performance of metaheuristics. Generally, there are three basic models to parallelize EAs, namely the Global, the Coarse-Grained and the Fine-Grained models whereby each one has advantages and disadvantages. Combining two or more of them in a hierarchical form reduces the disadvantages of each approach and allows users to fully utilize the advantages. In this article, a generic, scalable and flexible software architecture which supports users in combining the basic parallelization models of EAs with minimum adaptation effort is presented. This architecture based on microservices, container virtualization and the publish/subscribe messaging paradigm decouples the basic building blocks of the algorithms by encapsulating them in separate services. This allows users to easily combine the building blocks to form combinations of the parallelization models of EAs. An extensive evaluation exploring the scalability and applicability of the software architecture is performed by combining the Coarse-Grained Model with the Global Model for solving the unit commitment optimization problem. Four communication topologies among the islands with homogeneous/heterogeneous EA configurations and synchronous/asynchronous migration policies are applied and compared. For evaluation, the EA GLEAM (General Learning Evolutionary Algorithm and Method) is used. This article discusses the architectural concepts of our approach and presents main results of the evaluation. The evaluation results show that the new software architecture has high potential for scaling up the optimization speed of complex optimization problems when metaheuristics are used.

ModPhred: an integrative toolkit for the analysis and storage of nanopore sequencing DNA and RNA modification data.

DNA and RNA modifications can now be identified using nanopore sequencing. However, we currently lack a flexible software to efficiently encode, store, analyze and visualize DNA and RNA modification data. Here, we present ModPhred, a versatile toolkit that facilitates DNA and RNA modification analysis from nanopore sequencing reads in a user-friendly manner. ModPhred integrates probabilistic DNA and RNA modification information within the FASTQ and BAM file formats, can be used to encode multiple types of modifications simultaneously, and its output can be easily coupled to genomic track viewers, facilitating the visualization and analysis of DNA and RNA modification information in individual reads in a simple and computationally efficient manner. ModPhred is available at https://github.com/novoalab/modPhred, is implemented in Python3, and is released under an MIT license. Docker images with all dependencies preinstalled are also provided. Supplementary data are available at Bioinformatics online.

Airborne laser scanning for quantifying criteria and indicators of sustainable forest management in Canada

Airborne laser scanning (ALS) has emerged as a technology capable of generating descriptors of vegetation structure and best available terrain information. Research and operational implementations of ALS data have highlighted their value for characterizing forest structure and generating spatially explicit and objective spatial coverages and mapping products for forest management. Continued emphasis to enhance forest stewardship is promoting novel methods to integrate ALS to detail non-timber ecosystem values like habitat, soil, and water. Standardized criteria and indicator frameworks such as the Canadian Council of Forest Ministers provide a reliable starting point for where ALS has opportunities to characterize ecosystems objectively regardless of location. In this review of primarily Canadian work, we highlight how ALS is becoming an increasingly viable technology for deriving meaningful indicators to meet sustainable forest management criteria. We review and highlight the value of ALS for quantifying indicators of biological diversity, ecosystem condition and productivity, soil and water, and the role of forests in global ecological cycles. We conclude by highlighting the need for increased education, tech transfer, flexible software, and reporting frameworks alongside five key considerations for using ALS to derive meaningful indicators of sustainable forest management.

Standardizing the Development of Serious Games for Physical Rehabilitation: Conceptual Framework Proposal

BackgroundSerious games have been used as supportive therapy for traditional rehabilitation. However, most are designed without a systematic process to guide their development from the phases of requirement identification, planning, design, construction, and evaluation, which reflect the lack of adaptation of rehabilitation requirements and thus the patient’s needs.ObjectiveThe aim of this study was to propose a conceptual framework with standardized elements for the development of information systems by using a flexible and an adaptable process centered on the patient’s needs and focused on the creation of serious games for physical rehabilitation.MethodsThe conceptual framework is based on 3 fundamental concepts: (1) user-centered design, which is an iterative design process focused on users and their needs at each phase of the process, (2) generic structural activities of software engineering, which guides the independent development process regardless of the complexity or size of the problem, and (3) gamification elements, which allow the transformation of obstacles into positive and fun reinforcements, thereby encouraging patients in their rehabilitation process.ResultsWe propose a conceptual framework to guide the development of serious games through a systematic process by using an iterative and incremental process applying the phases of context identification, user requirements, planning, design, construction of the interaction devices and video game, and evaluation.ConclusionsThis proposed framework will provide developers of serious games a systematic process with standardized elements for the development of flexible and adaptable software with a high level of patient commitment, which will effectively contribute to their rehabilitation process.

Simulation and Modeling of Novel Electronic Device Architectures with NESS (Nano-Electronic Simulation Software): A Modular Nano TCAD Simulation Framework

The modeling of nano-electronic devices is a cost-effective approach for optimizing the semiconductor device performance and for guiding the fabrication technology. In this paper, we present the capabilities of the new flexible multi-scale nano TCAD simulation software called Nano-Electronic Simulation Software (NESS). NESS is designed to study the charge transport in contemporary and novel ultra-scaled semiconductor devices. In order to simulate the charge transport in such ultra-scaled devices with complex architectures and design, we have developed numerous simulation modules based on various simulation approaches. Currently, NESS contains a drift-diffusion, Kubo–Greenwood, and non-equilibrium Green’s function (NEGF) modules. All modules are numerical solvers which are implemented in the C++ programming language, and all of them are linked and solved self-consistently with the Poisson equation. Here, we have deployed some of those modules to showcase the capabilities of NESS to simulate advanced nano-scale semiconductor devices. The devices simulated in this paper are chosen to represent the current state-of-the-art and future technologies where quantum mechanical effects play an important role. Our examples include ultra-scaled nanowire transistors, tunnel transistors, resonant tunneling diodes, and negative capacitance transistors. Our results show that NESS is a robust, fast, and reliable simulation platform which can accurately predict and describe the underlying physics in novel ultra-scaled electronic devices.

An Open-Source Many-Scenario Approach for Power System Dynamic Simulation on HPC Clusters

In this paper we introduce an approach to accelerate many-scenario (i.e., hundreds to thousands) power system simulations which is based on a highly scalable and flexible open-source software environment. In this approach, the parallel execution of simulations follows the single program, multiple data (SPMD) paradigm, where the dynamic simulation program is executed in parallel and takes different inputs to generate different scenarios. The power system is modeled using an existing Modelica library and compiled to a simulation executable using the OpenModelica Compiler. Furthermore, the parallel simulation is performed with the aid of a message-passing interface (MPI) and the approach includes dynamic workload balancing. Finally, benchmarks with the simulation environment are performed on high-performance computing (HPC) clusters with four test cases. The results show high scalability and a considerable parallel speedup of the proposed approach in the simulation of all scenarios.

The abTEM code: transmission electron microscopy from first principles.

Simulation of transmission electron microscopy (TEM) images or diffraction patterns is often required to interpret experimental data. Since nuclear cores dominate electron scattering, the scattering potential is typically described using the independent atom model, which completely neglects valence bonding and its effect on the transmitting electrons. As instrumentation has advanced, new measurements have revealed subtle details of the scattering potential that were previously not accessible to experiment. We have created an open-source simulation code designed to meet these demands by integrating the ability to calculate the potential via density functional theory (DFT) with a flexible modular software design. abTEM can simulate most standard imaging modes and incorporates the latest algorithmic developments. The development of new techniques requires a program that is accessible to domain experts without extensive programming experience. abTEM is written purely in Python and designed for easy modification and extension. The effective use of modern open-source libraries makes the performance of abTEM highly competitive with existing optimized codes on both CPUs and GPUs and allows us to leverage an extensive ecosystem of libraries, such as the Atomic Simulation Environment and the DFT code GPAW. abTEM is designed to work in an interactive Python notebook, creating a seamless and reproducible workflow from defining an atomic structure, calculating molecular dynamics (MD) and electrostatic potentials, to the analysis of results, all in a single, easy-to-read document. This article provides ongoing documentation of abTEM development. In this first version, we show use cases for hexagonal boron nitride, where valence bonding can be detected, a 4D-STEM simulation of molybdenum disulfide including ptychographic phase reconstruction, a comparison of MD and frozen phonon modeling for convergent-beam electron diffraction of a 2.6-million-atom silicon system, and a performance comparison of our fastimplementation of thePRISM algorithm for a decahedral 20000-atom gold nanoparticle.

ANALYSIS OF FLEXIBLE METHODOLOGIES OF SOFTWARE DEVELOPMENT FOR IMPLEMENTATION IN TEAM PROJECTS

The materials of the article analyze the main models of the software life cycle, which underlie the flexible methodologies of software development to identify the features of its application during the implementation of team projects. It was found that the use of classical life cycle models, in particular, cascade, spiral, incremental, V-shaped and iterative, is not effective in implementing all modern aspects of software development based on the use of new information technologies. It was conducted the comparative analysis of the most popular flexible methodologies of software development Agile, Scrum, Kanban, RUP, DSDM, RAD on such indicators as life cycle model, number of iterations, purpose of project creation and types of projects for implementation, priorities, possibility of interaction with the customer, adaptation to change. The advantages and disadvantages of flexible software development methodologies made it possible to single out the MSF methodology, which is based on the harmonization of cascading, spiral and iterative models of the software development lifecycle and allows you to choose the Scrum template as the most successful for implementing and demonstrating work in team development projects. MSF uses an approach that involves the gradual creation of a working product with some functionality that reflects the requirements for the final product at this stage. It is proposed to use Microsoft solutions based on Visual Studio and Team Foundation Server for centralized management of team project elements, use of visual architecture modeling tools, code quality management capabilities and obtaining all project team members up-to-date information on project status. This is because the MSF model combines five following main models: team model; process model (sequence of actions required to build a team project); discipline of project management (provides comprehensive planning of all stages of the team project, budget management, resources, costs, scheduling); risk management disciplines and readiness management disciplines (assessment of team project members' knowledge for further distribution of team roles). The article demonstrates an example of creating a training team project based on the use of the Scrum flexible methodology template in Visual Studio based on Team Foundation Server.

COLEGRAM, a flexible user-friendly software for processing of ionizing radiation spectra

COLEGRAM is a freely available spectrometry software dedicated to the study of ionizing radiation spectra. It can handle alpha, beta, gamma and X-ray spectra, proposing twenty-eight specific peak shapes in order to fit complex spectra using the non-linear least-squares fitting method. Different optimization cost functions can be used to perform the mathematical adjustment, which is guided by a user-friendly interface. COLEGRAM is also able to perform batch processing on a large number of spectra copying fitted peak information, based on a predefined model. General characteristics of the code and typical application examples are given to illustrate its potential.