Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.
Three-dimensional (3D) models of the marginal hooks, dorsal and ventral anchors, bars and haptoral reservoirs of a parasite, Sundatrema langkawiense Lim & Gibson, 2009 (Monogenea) were developed using the polygonal modelling method in Autodesk 3ds Max (Version 9) based on two-dimensional (2D) illustrations. Maxscripts were written to rotate the modelled 3D structures. Appropriately orientated 3D haptoral hard-parts were then selected and positioned within the transparent 3D outline of the haptor and grouped together to form a complete 3D haptoral entity. This technique is an inexpensive tool for constructing 3D models from 2D illustrations for 3D visualisation of the spatial relationships between the different structural parts within organisms.
Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.
birgHPC, a bootable Linux Live CD has been developed to create high-performance clusters for bioinformatics and molecular dynamics studies using any Local Area Network (LAN)-networked computers. birgHPC features automated hardware and slots detection as well as provides a simple job submission interface. The latest versions of GROMACS, NAMD, mpiBLAST and ClustalW-MPI can be run in parallel by simply booting the birgHPC CD or flash drive from the head node, which immediately positions the rest of the PCs on the network as computing nodes. Thus, a temporary, affordable, scalable and high-performance computing environment can be built by non-computing-based researchers using low-cost commodity hardware.
Single-cell RNA sequencing (scRNA-seq) data are typically with a large number of missing values, which often results in the loss of critical gene signaling information and seriously limit the downstream analysis. Deep learning-based imputation methods often can better handle scRNA-seq data than shallow ones, but most of them do not consider the inherent relations between genes, and the expression of a gene is often regulated by other genes. Therefore, it is essential to impute scRNA-seq data by considering the regional gene-to-gene relations. We propose a novel model (named scGGAN) to impute scRNA-seq data that learns the gene-to-gene relations by Graph Convolutional Networks (GCN) and global scRNA-seq data distribution by Generative Adversarial Networks (GAN). scGGAN first leverages single-cell and bulk genomics data to explore inherent relations between genes and builds a more compact gene relation network to jointly capture the homogeneous and heterogeneous information. Then, it constructs a GCN-based GAN model to integrate the scRNA-seq, gene sequencing data and gene relation network for generating scRNA-seq data, and trains the model through adversarial learning. Finally, it utilizes data generated by the trained GCN-based GAN model to impute scRNA-seq data. Experiments on simulated and real scRNA-seq datasets show that scGGAN can effectively identify dropout events, recover the biologically meaningful expressions, determine subcellular states and types, improve the differential expression analysis and temporal dynamics analysis. Ablation experiments confirm that both the gene relation network and gene sequence data help the imputation of scRNA-seq data.
The GrAfSS (Graph theoretical Applications for Substructure Searching) webserver is a platform to search for three-dimensional substructures of: (i) amino acid side chains in protein structures; and (ii) base arrangements in RNA structures. The webserver interfaces the functions of five different graph theoretical algorithms - ASSAM, SPRITE, IMAAAGINE, NASSAM and COGNAC - into a single substructure searching suite. Users will be able to identify whether a three-dimensional (3D) arrangement of interest, such as a ligand binding site or 3D motif, observed in a protein or RNA structure can be found in other structures available in the Protein Data Bank (PDB). The webserver also allows users to determine whether a protein or RNA structure of interest contains substructural arrangements that are similar to known motifs or 3D arrangements. These capabilities allow for the functional annotation of new structures that were either experimentally determined or computationally generated (such as the coordinates generated by AlphaFold2) and can provide further insights into the diversity or conservation of functional mechanisms of structures in the PDB. The computed substructural superpositions are visualized using integrated NGL viewers. The GrAfSS server is available at http://mfrlab.org/grafss/.
The selection and classification of genes is essential for the identification of related genes to a specific disease. Developing a user-friendly application with combined statistical rigor and machine learning functionality to help the biomedical researchers and end users is of great importance. In this work, a novel stand-alone application, which is based on graphical user interface (GUI), is developed to perform the full functionality of gene selection and classification in high dimensional datasets. The so-called HDG-select application is validated on eleven high dimensional datasets of the format CSV and GEO soft. The proposed tool uses the efficient algorithm of combined filter-GBPSO-SVM and it was made freely available to users. It was found that the proposed HDG-select outperformed other tools reported in literature and presented a competitive performance, accessibility, and functionality.
This paper presents a performance analysis of two open-source, laser scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect's depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.
The main obstacles in mass adoption of cloud computing for database operations in healthcare organization are the data security and privacy issues. In this paper, it is shown that IT services particularly in hardware performance evaluation in virtual machine can be accomplished effectively without IT personnel gaining access to actual data for diagnostic and remediation purposes. The proposed mechanisms utilized the hypothetical data from TPC-H benchmark, to achieve 2 objectives. First, the underlying hardware performance and consistency is monitored via a control system, which is constructed using TPC-H queries. Second, the mechanism to construct stress-testing scenario is envisaged in the host, using a single or combination of TPC-H queries, so that the resource threshold point can be verified, if the virtual machine is still capable of serving critical transactions at this constraining juncture. This threshold point uses server run queue size as input parameter, and it serves 2 purposes: It provides the boundary threshold to the control system, so that periodic learning of the synthetic data sets for performance evaluation does not reach the host's constraint level. Secondly, when the host undergoes hardware change, stress-testing scenarios are simulated in the host by loading up to this resource threshold level, for subsequent response time verification from real and critical transactions.
Understanding fluid dynamics under extreme confinement, where device and intrinsic fluid length scales become comparable, is essential to successfully develop the coming generations of fluidic devices. Here we report measurements of advancing fluid fronts in such a regime, which we dub superconfinement. We find that the strong coupling between contact-line friction and geometric confinement gives rise to a new stability regime where the maximum speed for a stable moving front exhibits a distinctive response to changes in the bounding geometry. Unstable fronts develop into drop-emitting jets controlled by thermal fluctuations. Numerical simulations reveal that the dynamics in superconfined systems is dominated by interfacial forces. Henceforth, we present a theory that quantifies our experiments in terms of the relevant interfacial length scale, which in our system is the intrinsic contact-line slip length. Our findings show that length-scale overlap can be used as a new fluid-control mechanism in strongly confined systems.
FT-IR spectrum of (2E)-3-(3-nitrophenyl)-1-[4-piperidin-1-yl]prop-2-en-1-one was recorded and analyzed. The vibrational wavenumbers were computed using HF and DFT quantum chemical calculations. The data obtained from wavenumber calculations are used to assign IR bands. Potential energy distribution was done using GAR2PED software. The geometrical parameters of the title compound are in agreement with the XRD results. NBO analysis, HOMO-LUMO, first and second hyperpolarizability and molecular electrostatic potential results are also reported. The possible electrophile attacking sites of the title molecule is identified using MEP surface plot study. Molecular docking results predicted the anti-leishmanic activity for the compound.
A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs.
One-pot synthetic method was adopted to prepare three isomers 4-(ortho-fluorophenyl)thiosemi- carbazide), 4-(meta-fluorophenyl)thiosemicarbazide and 4-(para-fluorophenyl)thiosemicarbazide. The products were obtained in ethanolic solution from a reaction between ortho, meta and para derivatives of fluorophenyl isothiocyanate and hydrazine hydrate. This work presents the theoretical Molecular Electrostatic Potential (MEP) and Highest Occupied Molecular Orbital-Lowest Unoccupied Molecular Orbital (HOMO-LUMO) computational data through Gaussview 5.0.9 and Gaussian09 software. Experimental Cole-cole plot for conductivity determination was also illustrated. The present data is important to manipulate the properties of compounds according to the position of a fluorine atom.
Quantitative Risk Assessment (QRA) nowadays is an established risk assessment method used worldwide for the evaluation of risks on onshore plant and offshore facilities which associated with the major hazard installations. However, there are still many issues on QRA used. These include lack of consistency, complexity of the overall model structure, incorporation of new data, methodology and model analysis. Common problem observed for the onshore QRA methodology is conservatism of fire and explosion consequence results using DNV PhastRisk 6.7 software which is mainly contributed from the high release rate due to loss of containment. This paper presents an alternative way to predict the actual release rate for fire and explosion modelling which called limiting flowrate technique. This method has been applied for calculating risk in Onshore Gas Terminal (OGT) Plant. Adopting the limiting flowrate technique has provide more precise model towards real scenarios. Challenges facing during this research such as using the unmodified United Kingdom (UK) HSE hydrocarbon release database without integrate with the actual failure frequencies from the plant, the risk results tend to be much higher than actual experience. It should be noted that the development of improved onshore risk model has been used as an example for this research but many of the issues are equally applicable to offshore studies as well.
The effects of propylene stored in pressurized spherical vessel were investigated using radiation & explosion modeling using PHAST 6.7 software in one of the refinery in Malaysia. The simulations were performed for various weather conditions with different leak scenarios in deterministic approach. Modeling approach was standard with current industry practice. Resulting events such as jet fire, vapor cloud explosion, boiling liquid evaporating vapor explosion effects shown in thermal radiation and overpressure towards targeted technical buildings. The effects of resulting jet fire flame length increase with release rate and explosion overpressure effects increase with degree of confinement and volume fraction respectively. The results were reviewed, interpreted against industry standard. The sensitivity cases show that, using lower inventory with moderate operating conditions will keep the consequence in acceptable region. This consequence analysis will form a basis for layout development, safety distance and fire zone segregation during conceptual design stage. Propylene storage conditions, layout arrangements and blast protections were recommended as part of preventive and mitigative measures.
The process of software development life cycle (SDLC) is an important element of development phases to develop the application. In fact, there are needs to upgrade the sequence of methodology in software development. Thus, the SDLC is very crucial in order for them to ensure the quality of skills is placed accordingly in the workflow. This research contributes to the development of a new approach in system development workflow with the aim to properly manage system development projects. It started by providing some background data related to the previous mode of operation in the teamwork samples as shared by the stakeholders of the transformation projects and the new proposed Analysis System Development Framework (ASDF) method team members. Then, the key findings related to steps of software development such as (1) input for User Requirement Specification (URS) and (2) System Requirement Specification (SRS), (3) process for module, (4) process for database, (5) process for User Acceptance Testing (UAT) (6) output for Final Acceptance Testing (FAT) and empowerment for the whole level based on ASDF method. This paper contribution significantly to support the perception of high quality of skills in a teamwork, results in better performance of software development.
This paper is about the reduction of the overall size of metal blanking sheet that is being used to form a stamping product or car body panel of a car manufacturer in Malaysia. The current blanking sheet produces extra waste which will be recycled and does not contribute to increase productivity but increases inventory cost. The reduction in the blanking sheet size will lead to the reduction of raw material hence reduced the production cost. However, the reduced size of blanking sheet could affect the yield strength of the product. The study of the yield strength and yield improvement of the product are done by simulating stress analysis by using CATIA software. The results show that the new proposed size of the metal blanking sheet provides accuracy of the product dimension as well as maintaining the yield strength of the product and it reduced a significant amount of metal scrap which is nearly 4% of material weight and save around 10% of inventory cost.
Ability to possess ball during football matches are link to success. Domination of Johor Darul Ta’zim FC (JDT FC) in recent years in Malaysia Super League impressed many. The aim of this study was to compare the performance between JDT FC and their opponents in Malaysia Super League 2015 season. Successful and unsuccessful passes, ball possession rates, attempt on goal, shot on target, and goal scored were selected as Performance Indicator (P.I) in this study. Twelve matches from Malaysia Super League (MSL) season 2015 were selected. The video of 12 matches was obtained from Media Prima Sdn. Bhd., www.youtube.com and live recordings. Longo Match 1.0 match analysis software was used for post-coding. Kolmogorov-Smirnov Z was used to analyses the differences while Spearman's rho correlation test was utilized to determine the correlation. Percentage of successful passes (p=0.034), ball possessions rate (p=0.000), and goal scored (p=0.002) were significantly different between JDT FC and their opponents. There were also positive correlations between possessions and all variables except for unsuccessful passes. This study concluded that in Malaysian football matches, high percentage of successful passes, and high rate of ball possessions influenced total shot in football game.
The present work was carried out to investigate the blood flow behavior and the severity of blockage caused in the
arterial passage due to the different geometries such as elliptical, trapezium and triangular shapes of stenosis. The study
was conducted with respect to various sizes of stenosis in terms of 70%, 80% and 90% area blockage of the arterial
blood flow. The study was carried out numerically with the help of advance computational fluid dynamic software. It
was found that the shape of the stenosis plays an important role in overall pressure drop across the blockage region
of artery. The highest level of pressure drop was observed for trapezoidal shape of stenosis followed by elliptical and
then by triangular shaped stenosis. The wall shear stress across the stenosis is great for trapezoidal shape followed by
triangular and elliptical stenosis for same blockage area in the artery.