Analysis and Evaluation of Covid-19 Tools for Health Professionals: Challenges and Opportunities

The multidisciplinary nature of the work required for research in the Covid-19 pandemic has created new challenges for health professionals in the battle against the virus. They need to be equipped with novel tools and resources ---that have emerged during the pandemic--- to gain access to breakthrough findings, know the latest developments, and to address their specific needs for rapid data acquisition, analysis, evaluation, and reporting. Because of the complex nature of the virus, the healthcare systems worldwide are severely impacted as the treatment and the vaccine for Covid-19 disease are not yet discovered. This leads to frequent changes in regulations and policies by governments and international organizations. Our analysis suggests that given the abundance of information sources, finding the most suitable tool for a given task is one of such challenges. But health professionals and policymakers need access to the most relevant, reliable, trusted, and latest information and tools that can be used in their day-to-day tasks of Covid-19 research and analysis. In this article, we present our analysis of various novel and important tools that have been specifically developed during the Covid-19 pandemic and that can be used by the health professionals community to help in advancing their analysis and research. These tools comprise of search engines, information repositories for literature and clinical trials, data sources, dashboards, and forecasting models. We present list of the minimally essential tools to serve a multitude of purposes, from hundreds of those developed since the beginning of the pandemic. A critical analysis is provided for the selected tools based on 17 parameters that can be useful for researchers and analysts for their evaluations. These parameters make up our evaluation framework and have not been used previously for analysis and evaluation. Hence, knowledge of the tools will not only increase the productivity but will also allow to explore new dimensions for using existing tools with more control, better management, and greater outcome of their research. In addition, the parameters used in our framework can be applied for future evaluations of similar tools and health professionals can adapt them for evaluation of other tools not covered in this analysis.

Kinetic data acquisition in high-throughput Fischer–Tropsch experimentation

The emergence of high-throughput experimentation gives new opportunities for accurate and rapid data acquisition for a wide variety of chemical reactions in different fields of application such as hydrocracking, isomerization and syngas conversion.

Protocol for Community-created Public MS/MS Reference Library Within the GNPS Infrastructure

RationaleA major hurdle in identifying chemicals in mass spectrometry experiments is the availability of MS/MS reference spectra in public databases. Currently, scientists purchase databases or use public databases such as GNPS. The MSMS-Chooser workflow empowers the creation of MS/MS reference spectra directly in the GNPS infrastructure.MethodsAn MSMS-Chooser sample template was completed with the required information and sequence tables were generated programmatically. Standards in methanol-water (1:1) solution (1 μM) were placed into wells individually. An LC-MS/MS system using data-dependent acquisition in positive and negative modes was used. Species that may be generated under typical ESI conditions are chosen. The MS/MS spectra and MSMS-Chooser sample template were subsequently uploaded to MSMS-Chooser in GNPS for automatic MS/MS spectral annotation.ResultsData acquisition quickly and effectively collected MS/MS spectra. MSMS-Chooser was able to accurately annotate 99.2% of the manually validated MS/MS scans that were generated from the chemical standards. The output of MSMS-Chooser includes a table ready for inclusion in the GNPS library (after inspection) as well as the ability to directly launch searches via MASST. Altogether, the data acquisition, processing, and upload to GNPS took ~2 hours for our proof-of-concept results.ConclusionsThe MSMS-Chooser workflow enables the rapid data acquisition, analysis, and annotation of chemical standards, and uploads the MS/MS spectra to community-driven GNPS. MSMS-Chooser democratizes the creation of MS/MS reference spectra in GNPS which will improve annotation and strengthen the tools which use the annotation information.

Active Acquisition for multimodal neuroimaging

In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field-of-view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.

The frequency-domain airborne electromagnetic method with a grounded electrical source

For surveys in areas with difficult access, ground-based electromagnetic (EM) systems are difficult to operate, time-consuming, and expensive, whereas airborne EM (AEM) systems are unsafe and uneconomic for small survey areas. We have developed a new frequency-domain airborne electromagnetic (FAEM) system called the ground-airborne frequency-domain EM (GAFEM) system to achieve rapid data acquisition in complex terrains with high safety and low cost. The system consists of a grounded electrical source and an airborne receiver carried by an unmanned rotorcraft. The grounded electrical source transmits a [Formula: see text] pseudorandom series obtaining signals at [Formula: see text] frequencies in one flight, which can maintain the resolution without reducing efficiency. The airborne receiver based on the unmanned rotorcraft makes the system flexible, convenient, and economical to operate in areas with difficult access. The system can conduct surveys in far- and non-far-field regions and can obtain the apparent resistivity to present a quick overview of the subsurface structure. To demonstrate the GAFEM system’s effectiveness and practical detection potential, we have performed two field surveys that revealed the shallow structure with tunnels and the deep structure at source-receiver distances of 3 and 6 km, respectively. The GAFEM system effectively revealed the apparent-resistivity difference with a sufficient investigation depth at large source-receiver distances. Thus, the system can be extended to various important applications for rapid surveys or deep investigations in areas with difficult access.

Automated Wormscan

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.

Active Acquisition for multimodal neuroimaging

In many clinical and scientific situations the optimal neuroimaging sequence may not be known prior to scanning and may differ for each individual being scanned, depending on the exact nature and location of abnormalities. Despite this, the standard approach to data acquisition, in such situations, is to specify the sequence of neuroimaging scans prior to data acquisition and to apply the same scans to all individuals. In this paper, we propose and illustrate an alternative approach, in which data would be analysed as it is acquired and used to choose the future scanning sequence: Active Acquisition. We propose three Active Acquisition scenarios based around multiple MRI modalities. In Scenario 1, we propose a simple use of near-real time analysis to decide whether to acquire more or higher resolution data, or acquire data with a different field-of-view. In Scenario 2, we simulate how multimodal MR data could be actively acquired and combined with a decision tree to classify a known outcome variable (in the simple example here, age). In Scenario 3, we simulate using Bayesian optimisation to actively search across multiple MRI modalities to find those which are most abnormal. These simulations suggest that by actively acquiring data, the scanning sequence can be adapted to each individual. We also consider the many outstanding practical and technical challenges involving normative data acquisition, MR physics, statistical modelling and clinical relevance. Despite these, we argue that Active Acquisition allows for potentially far more powerful, sensitive or rapid data acquisition, and may open up different perspectives on individual differences, clinical conditions, and biomarker discovery.

FUSION OF TLS AND UAV PHOTOGRAMMETRY DATA FOR POST-EARTHQUAKE 3D MODELING OF A CULTURAL HERITAGE CHURCH

<p><strong>Abstract.</strong> Nowadays, the necessity of heritage documentation is essential for monitoring, maintenance, and understanding needed for conservation. The survey phase has been considerably improved using cutting-edge technologies such as Unmanned Aerial Vehicles (UAV) and Terrestrial Laser Scanners (TLS). Both of these technologies have been applied in heritage documentation individually or combined. Heritage documentation in a post-natural disaster is a situation that requires rapid data acquisition on a hazardous field. On 12th of June 2017 an earthquake (Mw&amp;thinsp;=&amp;thinsp;6.3), south of Lesvos island, Greece occurred, which was devastating for the Vrisa village destroying, among many other buildings the main church. The Greek State decided from the first moment to restore the whole village, which was proclaimed as a “traditional settlement” since 2002, in its original place starting from the church and the school due to the symbolic meaning that those have to a local community. For this purpose, a 3D model of the church was requested by the authorities for damage assessment. In this paper TLS and UAV photogrammetry has been used in an integrated design to rapidly facilitate the acquisition of the whole church, eliminating all possible occlusions. The TLS was exploited for the acquisition of the facades while the UAV was used for the acquisition of the roof. The recent improvement of the post-processing algorithms provided the ability to implement the fusion of TLS and UAV models and deliver an accurate 3D model of the whole church the same day that the survey was conducted.</p>

Automated Wormscan

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.

Automated Wormscan

There has been a recent surge of interest in computer-aided rapid data acquisition to increase the potential throughput and reduce the labour costs of large scale Caenorhabditis elegans studies. We present Automated WormScan, a low-cost, high-throughput automated system using commercial photo scanners, which is extremely easy to implement and use, capable of scoring tens of thousands of organisms per hour with minimal operator input, and is scalable. The method does not rely on software training for image recognition, but uses the generation of difference images from sequential scans to identify moving objects. This approach results in robust identification of worms with little computational demand. We demonstrate the utility of the system by conducting toxicity, growth and fecundity assays, which demonstrate the consistency of our automated system, the quality of the data relative to manual scoring methods and congruity with previously published results.