Interactive Graphical Interface Research Articles

HistoQC: An Open-Source Quality Control Tool for Digital Pathology Slides.

Digital pathology (DP), referring to the digitization of tissue slides, is beginning to change the landscape of clinical diagnostic workflows and has engendered active research within the area of computational pathology. One of the challenges in DP is the presence of artefacts and batch effects, unintentionally introduced during both routine slide preparation (eg, staining, tissue folding) and digitization (eg, blurriness, variations in contrast and hue). Manual review of glass and digital slides is laborious, qualitative, and subject to intra- and inter-reader variability. Therefore, there is a critical need for a reproducible automated approach of precisely localizing artefacts to identify slides that need to be reproduced or regions that should be avoided during computational analysis. Here we present HistoQC, a tool for rapidly performing quality control to not only identify and delineate artefacts but also discover cohort-level outliers (eg, slides stained darker or lighter than others in the cohort). This open-source tool employs a combination of image metrics (eg, color histograms, brightness, contrast), features (eg, edge detectors), and supervised classifiers (eg, pen detection) to identify artefact-free regions on digitized slides. These regions and metrics are presented to the user via an interactive graphical user interface, facilitating artefact detection through real-time visualization and filtering. These same metrics afford users the opportunity to explicitly define acceptable tolerances for their workflows. The output of HistoQC on 450 slides from The Cancer Genome Atlas was reviewed by two pathologists and found to be suitable for computational analysis more than 95% of the time. These results suggest that HistoQC could provide an automated, quantifiable, quality control process for identifying artefacts and measuring slide quality, in turn helping to improve both the repeatability and robustness of DP workflows.

Cerebro: interactive visualization of scRNA-seq data.

Despite the growing availability of sophisticated bioinformatic methods for the analysis of single-cell RNA-seq data, few tools exist that allow biologists without extensive bioinformatic expertise to directly visualize and interact with their own data and results. Here, we present Cerebro (cell report browser), a Shiny- and Electron-based standalone desktop application for macOS and Windows which allows investigation and inspection of pre-processed single-cell transcriptomics data without requiring bioinformatic experience of the user. Through an interactive and intuitive graphical interface, users can (i) explore similarities and heterogeneity between samples and cell clusters in two-dimensional or three-dimensional projections such as t-SNE or UMAP, (ii) display the expression level of single genes or gene sets of interest, (iii) browse tables of most expressed genes and marker genes for each sample and cluster and (iv) display trajectories calculated with Monocle 2. We provide three examples prepared from publicly available datasets to show how Cerebro can be used and which are its capabilities. Through a focus on flexibility and direct access to data and results, we think Cerebro offers a collaborative framework for bioinformaticians and experimental biologists that facilitates effective interaction to shorten the gap between analysis and interpretation of the data. Availability and implementationThe Cerebro application, additional documentation, and example datasets are available at https://github.com/romanhaa/Cerebro. Similarly, the cerebroApp R package is available at https://github.com/romanhaa/cerebroApp. All components are released under the MIT License.Supplementary information Supplementary data are available at Bioinformatics online.

Port Strategies for Robot-Assisted Lobectomy by High-Volume Thoracic Surgeons: A Nationwide Survey.

Robot-assisted lobectomy is the fastest growing technique for pulmonary lobectomy, but the diversity of approaches has led to apprehension about port placement among learning surgeons. The aim of this study was to survey high-volume thoracic surgeons who perform robot-assisted lobectomy to understand and consolidate common themes of port placement. An electronic online survey was created, and the link was emailed to the 100 highest volume robotic thoracic surgeons in the United States. The survey included an interactive graphical interface, which allowed each respondent to mark the preferential robotic port placement in the chest wall for each of the 5 pulmonary lobectomies. Results were analyzed individually and in aggregate. A heat map was generated to show trends. One hundred surgeons were surveyed (response rate: 62%). Most (90%) respondents utilized a 4-arm approach and 79% used a completely 4-arm portal approach with CO2 insufflation. Exact locations for each robotic port were reported by 60% of the surveyed surgeons and the results varied; however, most surgeons generally used the seventh to ninth interspaces for the camera and instruments. The use of multiple different interspace levels was common. Ninety-four percent of respondents used an additional nonrobotic assistant port. There is not a universal port strategy for robot-assisted lobectomy. However, placement of the camera and robotic ports low in the seventh to ninth interspaces is the most common approach. There are some nuances of stapling port strategies and sequence of port placement, which are identified.

ModLayer: A MATLAB GUI Drawing Segmentation Tool for Visualizing and Classifying 3D Data

Characterizing a material’s microstructure, especially as it relates to the manufacturing processes used to fabricate it, is of great interest to engineers and researchers. In recent years, state-of-the-art imaging techniques have been able to yield a plethora of high resolution 3D data that can be used to study materials at various length scales. This 3D data is usually organized as stacked serial sections of 2D images and almost always requires some combination of enhancement and segmentation (the process of separating an image into subsets), in order to extract meaningful information. To aid in this process, ModLayer was created as a MATLAB® executable. ModLayer is an interactive graphical user interface that seeks to remove the burden of import/export redundancies when interacting with 3D data in MATLAB during visualization, modification, or segmentation through manual drawing across image stacks. The utility of ModLayer is demonstrated here through three case studies; (1) classifying regions of damage with in-situ time lapse X-ray micro-computed tomography ($$\mu $$-CT) of a glass fiber reinforced polypropylene (GFRP), (2) correcting multi-class segmentation errors in segmented X-ray $$\mu $$-CT images of a GRFP composite, and (3) capturing features of interest within in-situ 3D X-ray $$\mu $$-CT images during fatigue crack growth experiments of aluminum 7050. Overall, this tool is especially useful to engineers and researchers interested in correcting—within MATLAB—automated segmentation of noisy 3D images which can yield erroneous microstructural features in segmentation procedures.

Skill-based programming of complex robotic assembly tasks for industrial application

In recent years, a paradigm shift is underway as robots leave their typical application field and move into domains that have been untouched by robotic automation. These new kinds of automation systems allow more product variations, smaller life cycles, smaller batch sizes and pave the way from mass production to mass customization. This is due to completely new breed of safe robot technology but also novel ways of setting up new applications like e.g. kinesthetic programming. However, the topic of reducing the programming effort for complex tasks using natural modes of communication is still open. This paper addresses the key developments in this field, shows different ways of programming, and gives relevant use cases in industrial assembly. The technology coverage starts with an online workflow editor called XROB that allows easy-to-use setup of process workflows and related skill parameters. However, in order to reduce the programming effort, a novel way to demonstrate process trajectories by using instrumented hand guided process tools is presented. Finally, the paper gives an overview of a promising approach that allows programming without touching the robot just by demonstrating the process by an expert. The semantic relations between activities executed by the human and robot skills are captured to learn the task sequence of the assembly process. The acquired process knowledge is refined to execute robotic tasks with the help of an interactive graphical user interface (GUI). The system queries the user for feedback, asking for specific information to help the robot complete the task at hand. The given examples show the usability of flexible programming tools in the automation chain and the presented results provide strong evidence of the technological potential in the field.

Graph Theory in the Analysis of Arithmophobia

In this paper, Graph theoretical concepts are applied to analyze the reasons behind Arithmophobia commonly found among the students.Bull graph is used to epitomize Mild Arithmophobia which occurs when the preparation of students to face any test is deficient.Flower graph is used to represent Intense Arithmophobia. Wheel graph is used to depict the factors which desensitize Arithmophobia. Inferring information from these types of graphs is much more easier than inferring from a self map. This analysis will help in treating Arithmophobia and improve the student’s performance in Mathematics progressively. The benefits of using interactive graphical interface, graphs and graph theory metrics for a client centered analysis is also discussed.

Home Switching using IoT System via Telegram and Web User Interface

Nowadays, the Internet of Things (IoT) becomes ubiquitous in engineering field and is perceived as paradigms for applications such as a home automation system where data can be exchanged and shared easily across the Internet. This project focuses on the implementation of the home automation system with Telegram using Wireless-Fidelity (Wi-Fi) network access on any smart-phone and laptop devices. It is highly beneficial for elderly, physically-challenged people and travellers to control home appliances effortlessly. This system aims to solve the limitation faced by the technology used in the existing home automation system such as Bluetooth -distance issue, Global Standard for Mobile Communication (GSM) – cost issue and Zigbee – power and bandwidth constraint. In fact, this system provides an interactive graphical user interface (GUI) on both web and Telegram platform where data can be interchanged and synchronized between both GUI in which sensor’s readings and status of home appliances can be monitored and manipulated consistently. The analytical findings based on temperature sensor’s accuracy and system latency showed that the performance of the system is viable, and the system proved to be more prominent than other home automation systems.

Study on the influence of the blank thickness on the dynamic behavior of mechanic eccentric presses

This paper presents a method for studying the dynamic behavior of mechanical presses with eccentricity based on a mathematical model. The novelty elements of the proposed model are as follows: the essential non-linear evolution of the force in process; the frictional force in the slider guides is also considered to have a non-linear character; the friction moments in the kinematic chain structure are considered different at start-up compared to the nominal regime and the weight of the slider together with the elements attached to it is taken into account. The equations characterizing the movement of the system were deduced starting from Lagrange’s generalized equations. Finally, an interactive graphical interface was developed that allows the study of the influences of some constructive and adjusting parameters on the parameters that characterize the dynamic behavior of the working mechanism: the angular speed, the motor moment and the power consumed by the electric drive motor. The method was applied to the case of PAI 63 press. Based on the results obtained by changing the parameters mentioned above (around the existing values), a serie of conclusions were drawn that could lead to an improvement of the construction and the exploitation. of this machine.

Um sistema baseado em regras fuzzy para caracterizar o perfil de um investidor

Neste trabalho é proposto um sistema de classificação do perfil de um investidor por meio de base de regras fuzzy. Para tal, é utilizado o ambiente GUIDE do Matlab, para construir uma interface interativa, no qual são fornecidas, pelo potencial investidor, respostas para cinco questões (baseadas no modelo da ANBIMA), que versam sobre suas finanças. A partir destas respostas, o sistema apresenta como saída uma das características: investidor conservador, investidor moderado ou investidor arrojado, indicando também uma sugestão do tipo de investimento que melhor se enquadra a seu perfil. Os resultados obtidos são comparados com os resultados obtidos pelo API do Banco Paulista.

Development and analysis of a real-time system for automated detection of improvised explosive device indicators from ground vehicles

We propose a real-time change detection system to be used as a vehicle-mounted early-warning system for indicators of improvised explosive devices. Within the context of military route clearance, the system automatically detects suspicious changes in the environment with respect to a previous patrol. For this purpose, historical images of the live scene are retrieved from a database and registered to the live image through 2.5-D view synthesis, using the three-dimensional (3-D) scene geometry acquired from a stereo camera. Changes are then found using local-area statistics in the CIE-Lab color space. A set of spatiotemporal filters is used to reject irrelevant alarms, resulting in a limited set of confident changes to be presented to the operator through an interactive graphical user interface. Next to the algorithmic contributions, we elaborate on the real-time design, featuring graphical processing units for the most time-consuming processing tasks, a pipelined architecture to increase the system throughput, and we split the system into a live and offline processing chain. This way, real-time change detection at 3.5 fps is achieved on images of 1920 × 1440 pixels. Finally, an extensive system validation featuring realistic experiments shows promising detection capabilities and robustness to, e.g., lateral displacements of up to 6 m.

Intelligent fire detection and alert system using labVIEW

Fire detection systems are designed to discover fires and allow the safe evacuation of occupants as well as protecting the safety of emergency response personnel. This paper describes the design and development of a fire detection and alert system. Temperature and flame sensors are used to indicate the occurrence of fire. This work consists of two parts, which are transmitter and receiver, both using ZigBee wireless technology. Arduino Uno is used as the microcontroller at the transmitter part to control the sensor nodes and give alert when over temperature and flame are detected. At the transmitter, the collected data from the sensors are transmitted by an XBee module operated as router node. At the receiver side, an XBee coordinator module which is attached to a computer using USB to serial communication captured the data for further processing. In addition, an interactive and user-friendly Graphical User Interface (GUI) is developed. LabVIEW software is used to design the GUI which displays and analyze the possibility of fire happening. The system can display the fire location and provides early warning to allow occupants to escape the building safely.

VCF-Server: A web-based visualization tool for high-throughput variant data mining and management.

BackgroundNext‐generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way.MethodsThe VCF‐Server was developed as a web‐based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way.ResultsIn this study, we developed the VCF‐Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF‐Server allows users to annotate the VCF with commonly used databases or user‐defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF‐Server adopts a web file system, files in the VCF‐Server can be stored and managed in a centralized way. Moreover, VCF‐Server allows direct web‐based analysis (accessible through either desktop computers or mobile devices) as well as local deployment.ConclusionsWith an easy‐to‐use graphical interface, VCF‐Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng.

ScClustViz - Single-cell RNAseq cluster assessment and visualization.

Single-cell RNA sequencing (scRNAseq) represents a new kind of microscope that can measure the transcriptome profiles of thousands of individual cells from complex cellular mixtures, such as in a tissue, in a single experiment. This technology is particularly valuable for characterization of tissue heterogeneity because it can be used to identify and classify all cell types in a tissue. This is generally done by clustering the data, based on the assumption that cells of a particular type share similar transcriptomes, distinct from other cell types in the tissue. However, nearly all clustering algorithms have tunable parameters which affect the number of clusters they will identify in data. The R Shiny software tool described here, scClustViz, provides a simple interactive graphical user interface for exploring scRNAseq data and assessing the biological relevance of clustering results. Given that cell types are expected to have distinct gene expression patterns, scClustViz uses differential gene expression between clusters as a metric for assessing the fit of a clustering result to the data at multiple cluster resolution levels. This helps select a clustering parameter for further analysis. scClustViz also provides interactive visualisation of: cluster-specific distributions of technical factors, such as predicted cell cycle stage and other metadata; cluster-wise gene expression statistics to simplify annotation of cell types and identification of cell type specific marker genes; and gene expression distributions over all cells and cell types. scClustViz provides an interactive interface for visualisation, assessment, and biological interpretation of cell-type classifications in scRNAseq experiments that can be easily added to existing analysis pipelines, enabling customization by bioinformaticians while enabling biologists to explore their results without the need for computational expertise. It is available at https://baderlab.github.io/scClustViz/.

IGEAK: an interactive gene expression analysis kit for seamless workflow using the R/shiny platform

BackgroundThe use of microarrays and RNA-seq technologies is ubiquitous for transcriptome analyses in modern biology. With proper analysis tools, the differential gene expression analysis process can be significantly accelerated. Many open-source programs provide cutting-edge techniques, but these often require programming skills and lack intuitive and interactive or graphical user interfaces. To avoid bottlenecks impeding seamless analysis processing, we have developed an Interactive Gene Expression Analysis Kit, we term iGEAK, focusing on usability and interactivity. iGEAK is designed to be a simple, intuitive, light-weight that contrasts with heavy-duty programs.ResultsiGEAK is an R/Shiny-based client-side desktop application, providing an interactive gene expression data analysis pipeline for microarray and RNA-seq data. Gene expression data can be intuitively explored using a seamless analysis pipeline consisting of sample selection, differentially expressed gene prediction, protein-protein interaction, and gene set enrichment analyses. For each analysis step, users can easily alter parameters to mine more relevant biological information.ConclusioniGEAK is the outcome of close collaboration with wet-bench biologists who are eager to easily explore, mine, and analyze new or public microarray and RNA-seq data. We designed iGEAK as a gene expression analysis pipeline tool to provide essential analysis steps and a user-friendly interactive graphical user interface. iGEAK enables users without programing knowledge to comfortably perform differential gene expression predictions and downstream analyses. iGEAK packages, manuals, tutorials, sample datasets are available at the iGEAK project homepage (https://sites.google.com/view/iGEAK).

ScClustViz – Single-cell RNAseq cluster assessment and visualization

Single-cell RNA sequencing (scRNAseq) represents a new kind of microscope that can measure the transcriptome profiles of thousands of individual cells from complex cellular mixtures, such as in a tissue, in a single experiment. This technology is particularly valuable for characterization of tissue heterogeneity because it can be used to identify and classify all cell types in a tissue. This is generally done by clustering the data, based on the assumption that cells of a particular type share similar transcriptomes, distinct from other cell types in the tissue. However, nearly all clustering algorithms have tunable parameters which affect the number of clusters they will identify in data. The R Shiny software tool described here, scClustViz, provides a simple interactive graphical user interface for exploring scRNAseq data and assessing the biological relevance of clustering results. Given that cell types are expected to have distinct gene expression patterns, scClustViz uses differential gene expression between clusters as a metric for assessing the fit of a clustering result to the data at multiple cluster resolution levels. This helps select a clustering parameter for further analysis. scClustViz also provides interactive visualisation of: cluster-specific distributions of technical factors, such as predicted cell cycle stage and other metadata; cluster-wise gene expression statistics to simplify annotation of cell types and identification of cell type specific marker genes; and gene expression distributions over all cells and cell types. scClustViz provides an interactive interface for visualisation, assessment, and biological interpretation of cell-type classifications in scRNAseq experiments that can be easily added to existing analysis pipelines, enabling customization by bioinformaticians while enabling biologists to explore their results without the need for computational expertise. It is available at https://baderlab.github.io/scClustViz/.

Bacterial Feature Finder (BaFF)-a system for extracting features overrepresented in sets of prokaryotic organisms.

The results of some experimental and computational techniques are given in terms of large sets of organisms, especially prokaryotic. While their distinctive features can provide useful data regarding specific phenomenon, there are no automated tools for extracting them. We present here the Bacterial Feature Finder web server, a tool to automatically interrogate sets of prokaryotic organisms provided by the user to evaluate their specific biological features. At the core of the system is a searchable database of qualitative and quantitative features compiled for more than 23 000 prokaryotic organisms. Both the input set of organisms and the background set used to calculate the enriched features can be directly provided by the user, or they can be obtained by searching the database. The results are presented via an interactive graphical interface, with links to external resources. The web server is freely available at http://csbg.cnb.csic.es/BaFF. It has been tested in the main web browsers and does not require any especial plug-ins or additional software. Supplementary data are available at Bioinformatics online.

LiToTac: An Interactive-Interface Software for Finite Element Analysis of Multiple Contact Dynamics

In order to investigate the mechanical behavior of systems with complex architecture and a large number of contacting bodies, a finite element software, named LiToTac, has been developed by using the object-oriented programming technique. This software, with an interactive graphical user interface, is able to handle highly non-linear problems including multiple contacts and large deformation. More importantly, the contact detection based on a hybrid three-stages methodology can be performed automatically, which is more efficient than the common strategies of pre-defining contact zones in commercial FEM software like ANSYS, ABAQUS, etc. In addition, the contact solver in LiToTac is portable between dynamic and quasi-static codes and can accurately solve contact coupled with friction in a reduced system. Several numerical examples are carried out to illustrate the functionality and capacity of the software package.

Belle2Lab - An Interactive Tool for a Public Analysis of the Belle II Data

Several data samples from a Belle II experiment will be available to the public as a part of the experiment outreach activities. A Belle2Lab tool is designed as an interactive graphical user interface to reconstructed particles, offering users basic particle selection tools. The tool is based on a Blockly JavaScript graphical code generator and can be run in an HTML5 capable browser. It allows a description of different particle decays by selecting and combining particles from the data file, easy histogramming tools and a display of the results by using the JSROOT library. During the analysis, the user has the possibility to apply cuts to the selected variables. A pseudo-code generated by the user interface is sent to the execution server which returns the histograms, that can also be interactively fitted. The Belle2Lab is accessible in two ways: hosted on a single public web server or as a part of the virtual appliance which consists of an Ubuntu 16.04 LTS operating system, a data sample, an analysis framework, and a private web server. The public web server can be used for a single access while the virtual appliance is more suited for a use in a classroom.

A Rapid, Deterministic Age‐Depth Modeling Routine for Geological Sequences With Inherent Depth Uncertainty

AbstractTraditional approaches to age‐depth modeling typically assume no uncertainty for the depth value of dated intervals. However, such an assumption may not be fully valid in the case of poor coring recovery or significant sediment deformation, as well as in the case of a large subsampling interval. In consideration of these issues, we present a new age‐depth modeling routine, Undatable, which includes uncertainty in both age and depth. Undatable uses Bayesian radiocarbon (14C) calibration software (MatCal) and a deterministic approach with a positive sediment accumulation rate assumed a priori which, combined with efficient programming practices, allows for the rapid production (in a matter of seconds in many cases) of age‐depth models for multiple types of geological archives. Undatable has so far been successfully applied to coral archives, as well as sediment archives from estuarine, lacustrine, and deep‐sea environments. Through the inclusion of a bootstrapping option, the software performs particularly well in the case of a large scatter in age‐depth constraints by expanding the uncertainty envelope of the age‐depth model. Unlike other deterministic models, increasing the density of age‐depth constraints results in increased precision in Undatable, even at centennial scale, thus emulating the results of probabilistic models. In addition to the code itself, we also provide an interactive graphical user interface (GUI) that allows users to experiment with multiple age‐depth model settings to investigate the sensitivity of a given data set to multiple parameters.

DeltaMass: Automated Detection and Visualization of Mass Shifts in Proteomic Open-Search Results.

Routine identification of thousands of proteins in a single LC-MS experiment has long become the norm. With these vast amounts of data, more rigorous treatment of modified forms of peptides becomes possible. "Open search", a protein database search with a large precursor ion mass tolerance window, is becoming a popular method to evaluate possible sets of post-translational and chemical modifications in samples. The extraction of statistical information about the modification from peptide search results requires additional effort and data processing, such as recalibration of masses and accurate detection of precursors in MS1 signals. Here we present a software tool, DeltaMass, which performs kernel-density-based estimation of observed mass shifts and allows for the detection of poorly resolved mass deltas. The software also maps observed mass shifts to known modifications from public databases such as UniMod and augments them with additionally generated possible chemical changes to the molecule. Its interactive graphical interface provides an effective option for the visual interrogation of the data and the identification of potentially interesting mass shifts or unusual artifacts for subsequent analysis. However, the program can also be used in fully automated command-line mode to generate mass-shift peak lists as well.