Instant Visualization Research Articles

A Novel Web-Based Approach for Monitoring Biodiversity.

Understanding complexities in biodiversity is one of the fundamental goals of ecology and its monitoring is significant for ecosystem sustainability, maintenance, and conservation. However, biodiversity monitoring needs improvement to handle complex datasets and their analyses. This study attempts to understand these ecological complexities quickly, efficiently, and easily. The aim is to provide an alternative to ecologists, researchers, instructors, and stakeholders for biodiversity monitoring with the flexibility to visualize and customize outputs without software knowledge. A novel web-based technique is applied to monitor the biodiversity of a complex mountain ecosystem using a national database. The species-environment relationships of different vegetation types across a mountain ecosystem's elevation gradient are investigated using open-source climatic, physiographic, and socioeconomic variables. The proposed interactive tool to monitor biodiversity and understand its complexities is designed to visualize the data structure, summary, correlations, and sampling effectiveness quickly and easily. Plant species richness patterns and life forms (herb, shrub, and tree) across elevational gradients are investigated. We highlight the preliminary investigation of the data structure and their spatial distribution and apply the multicollinearity test to select variables for modeling. The drop-down menu helps users browse different datasets and select those datasets for instant visualization. Preliminary investigations on interactions between variables and species richness of vegetation types along elevation gradient interactively displayed with options to select variables, plant richness, and an elevational range. Species-environment relationships are investigated using multiple modeling protocols, and results are interactively displayed with options to download in different file formats and colors at the click of a button. This visualization tool helps to understand ecosystem structure, species richness patterns and species-environment relationships easily and efficiently. The R-codes used in this tool are reproducible and can be implemented with multiple datasets to monitor ecosystems.

Ultra-High-Frequency ECG in Cardiac Pacing and Cardiac Resynchronization Therapy: From Technical Concept to Clinical Application.

Identifying electrical dyssynchrony is crucial for cardiac pacing and cardiac resynchronization therapy (CRT). The ultra-high-frequency electrocardiography (UHF-ECG) technique allows instantaneous dyssynchrony analyses with real-time visualization. This review explores the physiological background of higher frequencies in ventricular conduction and the translational evolution of UHF-ECG in cardiac pacing and CRT. Although high-frequency components were studied half a century ago, their exploration in the dyssynchrony context is rare. UHF-ECG records ECG signals from eight precordial leads over multiple beats in time. After initial conceptual studies, the implementation of an instant visualization of ventricular activation led to clinical implementation with minimal patient burden. UHF-ECG aids patient selection in biventricular CRT and evaluates ventricular activation during various forms of conduction system pacing (CSP). UHF-ECG ventricular electrical dyssynchrony has been associated with clinical outcomes in a large retrospective CRT cohort and has been used to study the electrophysiological differences between CSP methods, including His bundle pacing, left bundle branch (area) pacing, left ventricular septal pacing and conventional biventricular pacing. UHF-ECG can potentially be used to determine a tailored resynchronization approach (CRT through biventricular pacing or CSP) based on the electrical substrate (true LBBB vs. non-specified intraventricular conduction delay with more distal left ventricular conduction disease), for the optimization of CRT and holds promise beyond CRT for the risk stratification of ventricular arrhythmias.

EXPLORING THE CREATIVE POSSIBILITY OF A HYBRID DESIGN THINKING WORKSHOP THROUGH FINDING SOLUTIONS FOR CHILDREN’S SAFETY IN THE CHILDCARE ENVIRONMENT

Design thinking process has two ways of on and off-line. In the online method, it facilitates communication more freely through the setting of anonymity, while the offline method allows participants to understand the comprehensive context of the workshop. This study investigates the creative possibility of a hybrid design thinking process through a workshop using “camera-off ”: anonymous setting, “camera-on”: open setting, and instant visualization to find solutions for children’s safety in the childcare environment. In the methodology, a qualitative method of three-dimensional interviews and observations were used to collect the active participants’ opinions, and then the content analysis and the descriptive analysis were conducted. Three major childcare-related problems were noted during the workshop observations: 1) safety issues from children’s physical activities; 2) teachers’ excessive stress in childcare facilities, and 3) communication problems between parents and teachers. It was suggested that creative smart devices and artificial intelligence technologies could be helpful to relieve these problems. In insights of the hybrid design thinking workshop, the following points were noted: 1) active participants could freely share ideas in anonymous setting with “camera-off”; 2) active participants could understand various desires of diverse fields with “camera-on”, and 3) active participants could understand find core problems and solutions through instant visualization. Hybrid design thinking is an creative method for understanding problems and finding solutions.

Lipase-catalysed changes in essential oils revealed by comprehensive two-dimensional gas chromatography

Candida antarctica lipase A (CALA) was applied for the chemo-selective enzymatic transesterification of terpene and phenyl alcohols in 35 different essential oil samples. Comprehensive two-dimensional gas chromatography with mass spectrometry (GC×GC‒MS) analysis enabled the separation and tentative identification of a cohort of 125 compounds, allowing the instant visualisation of the reaction process changes, amid the complex chemical background of the samples. The results indicate that 42 out of 79 alcohols so-identified were fully or partially esterified within 48 h of reaction, with primary alcohols being the substrates of preference of the enzyme (90–100% conversion), followed by secondary alcohols (mostly ~ 80–100% conversion). No significant conversion of tertiary alcohols and phenols was observed using the tested conditions. Overall, the enzyme’s performance was consistent for primary alcohol substrates identified in multiple samples of different compositions. The observed selectivity, efficiency, robustness, scalability (enzyme/substrate working concentration ratio > 1:160), potential reusability, mild reaction conditions, and other factors make this process a greener and more sustainable alternative for industry applications, particularly for the manufacture of novel flavours and fragrances.Graphical

Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging

Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at once, which reduces imaging speed. Furthermore, there is substantial experimental complexity in setting up SIM systems, preventing a widespread adoption. Here, we present Machine-learning Assisted, Interferometric Structured Illumination Microscopy, MAI-SIM, as an easy-to-implement method for live cell super-resolution imaging at high speed and in multiple colors. The instrument is based on an interferometer design in which illumination patterns are generated, rotated, and stepped in phase through movement of a single galvanometric mirror element. The design is robust, flexible, and works for all wavelengths. We complement the unique properties of the microscope with an open source machine-learning toolbox that permits real-time reconstructions to be performed, providing instant visualization of super-resolved images from live biological samples.

Intelligent home energy management using Internet of Things platform based on NILM technique

Due to the continuous increase in the global energy demand, it is essential to find solutions to improve energy efficiency. Non-intrusive load monitoring (NILM) is one of the most prominent energy management techniques, and it allows consumers and companies to manage their energy consumption efficiently. The energy footprint of residential buildings is monitored, and the total electrical consumption is disaggregated into appliance related signals through NILM. The NILM applications are working based on the “energy awareness” concept where the consumer receives some itemized information from the application to reduce its consumption and thus improves energy efficiency. This paper presents an Internet of Things (IoT) based criterion by using NILM to transform modern buildings and homes into energy-efficient and smart ones. The Factorial Hidden Markov Model (FHMM) is used as a NILM technique to disaggregate all appliances’ total power consumption into individual appliance load consumption by giving the power as an input. The FHMM is applied on reference energy disaggregation dataset (REDD) datasets, and a comparison is made between the measured and predicted values of appliances’ power consumption. Instant visualization of live data is then created using the ThingSpeak platform, which sends alerts through Twitter social media application to the consumer to control his consumption. The consumption behavior is assessed according to the time of use to make an energy saving based on the cost of electricity.

Real-time Ultrasound-Guided Manual Testicular Detorsion: A Case Report.

IntroductionAcute testicular torsion is a surgical emergency due to acute testicular ischemia. Manual testicular detorsion is a testis-saving, bedside therapeutic when performed correctly and in a timely fashion. This procedure is most commonly performed blindly with pain relief as the endpoint for detorsion. However, up to one-third of patients continued to show signs of residual torsion in the operating room even using pain relief as the stopping point for the procedure.Case ReportWe present a case demonstrating the utility of color Doppler ultrasound to confirm complete manual detorsion in a 14-year-old male with acute testicular torsion. The patient underwent 360-degree detorsion and had relief of pain; however, color Doppler demonstrated incomplete return of flow to the testis. After an additional 180-degree turn was made, color Doppler demonstrated complete return of normal vascular flow to the torsed testis.ConclusionWhen it comes to testicular viability, timely restoration of blood flow to the testicle is of utmost importance. Manual detorsion is a non-invasive intervention that can be quickly and effectively performed at the bedside. Moreover, using color Doppler ultrasound guidance can ensure that physicians detorse in the proper direction and to completion, by providing instant visualization of restorative flow and ensuring reperfusion of the testis while awaiting definitive surgical management.

Instantaneous High‐Resolution Visual Imaging of Latent Fingerprints in Water Using Color‐Tunable AIE Pincer Complexes

Instant visualization of latent fingerprints is developed by using a series of water-soluble terpyridine zinc complexes as aggregation-induced emission probes in pure water, under UV light or ambient sunlight. By simply soaking, or spraying with an aqueous solution of the probe, bright yellow fluorescence images with high contrast and resolution are readily developed on various surfaces including tinfoil, glass, paper, steel, leather, and ceramic tile. Remarkably, latent fingerprints can be visualized within seconds including details of whorl and sweat pores. The color of emission can be tuned from blue to orange by modifying the pincer ligands, allowing direct imaging under sunlight. These inexpensive, water-resistant, and color-tunable probes provide a practical approach for latent fingerprints recording and analysis, security protection, as well as criminal investigation in different scenarios.

Z2P: Instant Visualization of Point Clouds

AbstractWe present a technique for visualizing point clouds using a neural network. Our technique allows for an instant preview of any point cloud, and bypasses the notoriously difficult surface reconstruction problem or the need to estimate oriented normals for splat‐based rendering. We cast the preview problem as a conditional image‐to‐image translation task, and design a neural network that translates point depth‐map directly into an image, where the point cloud is visualized as though a surface was reconstructed from it. Furthermore, the resulting appearance of the visualized point cloud can be, optionally, conditioned on simple control variables (e.g., color and light). We demonstrate that our technique instantly produces plausible images, and can, on‐the‐fly effectively handle noise, non‐uniform sampling, and thin surfaces sheets.

A graphic method for depicting basin evolution and changes in the dominant hydrodynamic process from paleocurrent data

Abstract Paleocurrent data measured on depositional elements and sedimentary structures (e.g., channels, cross-strata) are commonly utilized in the description of sedimentary strata. Paleocurrent data provide information about the depositional setting and in some cases can be useful for immediately detecting specific depositional processes (e.g., herringbone cross-strata for bimodal tidal currents). The typical graphical representation used to report paleocurrent data is the rose diagram. However, rose diagrams are not able to disclose all information contained in paleocurrent data, limiting the potentiality of such a representation method. In particular, there is presently no method to highlight changes in the paleogeographic configuration that can ultimately have an impact on the evolution of depositional processes and paleocurrent direction through time. Here, we present a graphic method that permits instant visualization of anomalies in paleocurrent distributions of the stratigraphic record that can be linked to changes in the paleogeography due to tectonic evolution or in the dominant hydrodynamic process. It is important to highlight that the proposed method does not aspire to replace rose diagrams but to provide an additional tool to be used before and in combination with rose diagrams in order to extrapolate as much information as possible from paleocurrent data.

Using Bayesian optimization to automate the calibration of complex hydrological models: Framework and application

A framework that integrates Bayesian optimization (BO) and high-performance computing was developed, to automate calibration of complex hydrological models. It adopts a loosely coupled web architecture, integrating Tornado and SpringBoot, to facilitate bidirectional transfer of variables between BO and model evaluation. Extensive model evaluations were implemented on a Hadoop cluster, to wrap the model into the calculation flexibly and separate the calculation process from the algorithm execution effectively. A case study, calibrating a SWAT model in the Meichuan Basin (Jiangxi Province, China), indicated that the framework provides an ideal environment for assessment of the capability of BO to quantify the efficient estimation of SWAT parameters. Compared with that of the built-in SWAT-CUP tool, the number of executions was reduced from 1500 to 150, while maintaining similar accuracy. The framework also allows evaluation of the performance of different surrogate models and acquisition functions and provides instant visualization for searching for optimal parameters.

GEE TIMESERIES EXPLORER FOR QGIS – INSTANT ACCESS TO PETABYTES OF EARTH OBSERVATION DATA

Abstract. Earth observation analysis workflows commonly require mass processing of time series data, with data volumes easily exceeding terabyte magnitude, even for relatively small areas of interest. Cloud processing platforms such as Google Earth Engine (GEE) leverage accessibility to satellite image archives and thus facilitate time series analysis workflows. Instant visualization of time series data and integration with local data sources is, however, currently not implemented or requires coding customized scripts or applications. Here, we present the GEE Timeseries Explorer plugin which grants instant access to GEE from within QGIS. It seamlessly integrates the QGIS user interface with a compact widget for visualizing time series from any predefined or customized GEE image collection. Users can visualize time series profiles for a given coordinate as an interactive plot or visualize images with customized band rendering within the QGIS map canvas. The plugin is available through the QGIS plugin repository and detailed documentation is available online (https://geetimeseriesexplorer.readthedocs.io/).

Капилляроскопия как скрининговое обследование сосудов при сахарном диабете. Обзор литературы

Nailfold capillaroscopy is currently one of the highly informative methods for assessing the state of microcirculation. The advantages are ease of implementation, non-invasiveness, accessibility of the research object, instant visualization of the microvasculature, painlessness. The object of the study is the nailfold capillaries of the fingers or toes, due to their horizontal position in relation to the surface of the body, which makes it possible to evaluate the capillary throughout. Many authors have shown pronounced microvascular anomalies in type 1 and type 2 diabetes mellitus: tortuosity and dilation of capillaries, a decrease in their density, microhemorrhages, avascular zones, ectasias and aneurysms, newly formed capillaries; a relationship with the duration and compensation of diabetes mellitus as well as the severity of diabetic retinopathy was revealed. Thus, nailfold capillaroscopy can be used as a method for diagnosing and predicting diabetic retinopathy in patients with diabetes mellitus with the aim of early detection of initial changes in the microvasculature and timely retinopathy treatment. Key words: capillaroscopy; nailfold; diabetes mellitus.

Interventional Optical Imaging Permits Instant Visualization of Pathological Zones of Ablated Tumor Periphery and Residual Tumor Detection.

Optical imaging (OI) provides real-time clinical imaging capability and simultaneous molecular, morphological, and functional information of disease processes. In this study, we present a new interventional OI technique, which enables in vivo visualization of three distinct pathologic zones of ablated tumor periphery for immediate detection of residual tumors during a radiofrequency ablation (RFA) session. Rabbits with orthotopic hepatic tumors were divided into two groups (n = 8/group): incomplete RFA and complete RFA. Indocyanine green-based interventional OI was used to differentiate three pathological zones: ablated tumor, transition margin, and residual tumor or surrounding normal liver-with quantitative comparison of signal-to-background ratios among the three zones and between incompletely and completely ablated tumors. Subsequent ex vivo OI and pathologic correlation were performed to confirm the findings of interventional OI. Interventional OI could differentiate incompletely or completely ablated tumor peripheries, thus permitting identification of residual tumor. This technique may open new avenues for immediate assessment of tumor eradication during a single interventional ablation session. SIGNIFICANCE: Interventional optical imaging can instantly visualize pathologic zones of ablated tumor peripheries to detect residual tumors, which could revolutionize current image-guided interventional oncologic ablation techniques.

IoT-Based Monitoring and Management Power Sub-Station of the University of Mosul

Managing power plants usually involves monitoring many data and parameters that occur within minutes, hours, or days. Nowadays, a mount of digital data can be exchanged, analyzed and easily accessed through modern technology called the Internet of Things (IoT). In this paper, an IoT (using Wi-Fi development kit called Photon) is used to remote control and monitor the performance of the University of Mosul power plant. This includes monitoring the Power Factor, supplied voltage and total load current of each sub-station within the university area. The system also applies a safety feature to completely close the power plant in the event of a serious condition such as a fire. ThingSpeak is used in this paper as an IoT analytics platform service which lets the programmers collect, visualize and analyze incoming data streams to the cloud. The collected data is sent to the ThingSpeak by the Photon devices, create instant visualization of live data related to the monitored station, and send the required alerts. The engineers responsible for the station can monitor the progress of the work of the station through any connected device - a computer or a smartphone - from anywhere in the world and even reprogram the system during operation, if necessary.

CrustyBase: an interactive online database for crustacean transcriptomes

Transcriptome sequencing has opened the field of genomics to a wide variety of researchers, owing to its efficiency, applicability across species and ability to quantify gene expression. The resulting datasets are a rich source of information that can be mined for many years into the future, with each dataset providing a unique angle on a specific context in biology. Maintaining accessibility to this accumulation of data presents quite a challenge for researchers.The primary focus of conventional genomics databases is the storage, navigation and interpretation of sequence data, which is typically classified down to the level of a species or individual. The addition of expression data adds a new dimension to this paradigm – the sampling context. Does gene expression describe different tissues, a temporal distribution or an experimental treatment? These data not only describe an individual, but the biological context surrounding that individual. The structure and utility of a transcriptome database must therefore reflect these attributes. We present an online database which has been designed to maximise the accessibility of crustacean transcriptome data by providing intuitive navigation within and between datasets and instant visualization of gene expression and protein structure.The site is accessible at https://crustybase.org and currently holds 10 datasets from a range of crustacean species. It also allows for upload of novel transcriptome datasets through a simple web interface, allowing the research community to contribute their own data to a pool of shared knowledge.

SDMD: An open source program for discontinuous molecular dynamics simulation of protein folding and aggregation

Discontinuous molecular dynamics (DMD) is an extremely fast alternative to the conventional molecular dynamics that uses continuous force fields. It simulates the force field applied to particles by discontinuous steplike functions of inter-particle distance. Thus, particles move at constant velocities until their distance is equal to the point at which there is a discontinuity, at which time the simulator calculates the interactions by solving simultaneously the equations governing conservation of momentum and energy. In this way, longer-time simulations can be carried out. Here, we introduce sDMD, an open source simulation package based on DMD technique coupled with a high-resolution all-atom molecular model, and describe the model of proteins, the algorithms for approximating the interactions, and the general design principles used in the simulator. We also demonstrate the implementation of the package, as well as two illustrative examples. Program summaryProgram title: sDMDProgram files doi:http://dx.doi.org/10.17632/h6b8hphw3n.1Licensing provisions: MIT LicenseProgramming language: C/C++Nature of problem: Molecular dynamics simulations of large protein/peptide systems for long time scales with high resolution.Solution method: sDMD is implemented based on discontinuous molecular dynamics, a fast alternative to the conventional molecular dynamics, which is able to perform ab initio simulations of protein/peptide folding and aggregation.Additional comments including restrictions and unusual features: OpenGL is required to enable the instant visualization feature.

Platform for wireless pressure sensing with built-in battery and instant visualization

Wireless communication through linkage with a smartphone and other portable devices in the sensor area are essential for increasing the efficiency of utilization by storing sensing-value data. Thus, the demand for wireless technology is increasing due to the advantages it provides for the various applications that use these data. However, there is still considerable ambiguity concerning the low portability of such technology due to the increased volume with component integration, the high consumption of power, and the necessity of having a separate battery. Herein, we present solutions for these problems with demonstrations that involve 1) the miniaturization of the device by altering the structure of the built-in battery, 2) the use of a pressure-activated switch for the low-power driving technology, and 3) the implementation of a wireless communication platform by integrating a Bluetooth module with the devices. In addition, we demonstrate a human-interactive display that enables users to instantly observe the changes in the brightness of the organic light-emitting diodes (OLED) as the pressure changes. We show that the system can display the measured, real-time pressure values on the screens of mobile devices, which represents a significant advancement in the fields of energy science and biomedical science.

A Fast 3D Brain Extraction and Visualization Framework Using Active Contour and Modern OpenGL Pipelines

Brain extraction is a process of removing non-brain tissue in the brain magnetic resonance (MR) images and serves as a first step towards more delicate brain segmentation. Although many brain extraction methods have been proposed in the literature, most of them are either laborious or time consuming, and lack of instant visualization. This leads to a time lag between image acquisition and comprehensive visualization. Especially for intraoperative image based neurosurgery navigation, the time lag from image acquisition to brain visualization should be reduced as much as possible. In this paper, we propose an end-to-end fast brain extraction and visualization framework. The input is a T1-weighted MR volume and the output is comprehensive brain visualization. An improved brain extraction tool (BET) algorithm is proposed to evolve a 3D active mesh model to fit the brain surface in the 3D image. Then the brain mask is generated per slice using a polygon fill algorithm. At last, a ray-casting volume rendering algorithm is used to visualize the brain surface with the help of the generated mask. All the operations are performed using the modern OpenGL pipelines running on a graphics processing unit (GPU). Experiments were performed on two publicly available datasets and one clinical dataset to compare our method with five state-of-the-art methods including the original BET in terms of segmentation accuracy and time cost. Our method achieved mean Dice coefficients of 96.8%, 97.1%, 98.5% and mean time cost of 361 ms, 341 ms, 502 ms on the three datasets, outperforming all the other methods.

Visual mass-spec share (vMS-Share): a new public web-based mass spectrometry visualization and data mining repository.

Herein we introduce the Visual Mass-Spec Share (vMS-Share), a new public mass spectrometric (MS) repository and data mining website/resource freely accessible at https://vmsshare.nist.gov. vMS-Share is a web-based application developed for instant visualization of raw MS data with integrated display of metadata optimized for the sharing of proteomics and metabolomics experimental results. Each MS-based identification is linked to a given experiment and the entire experimental data can then be viewed using the link associated with a given peptide and/or small molecule. Interactive and user-friendly visualizations are provided to the user via variety of easily accessible search filters.