User-friendly Software Platform Research Articles

Reservoir Assessment Tool version 3.0: a scalable and user-friendly software platform to mobilize the global water management community

Abstract. In the modern world, dams and the artificial reservoirs behind them serve the increasing demand for water across diverse needs such as agriculture, energy production, and drinking water. As dams continue to proliferate, monitoring water availability influenced by reservoir operations is now of paramount importance. The Reservoir Assessment Tool (RAT) is a data-driven software platform that integrates satellite remote sensing with hydrological models, enabling the estimation of key reservoir parameters such as inflow, outflow, surface area, evaporation, and storage changes. The earliest version of RAT (version 1.0) was set up for 1598 reservoirs around the world with limitations in functional robustness, updating frequency, and scalability. Some of these limitations on updating frequency and functional robustness were addressed in version 2.0 that was later made operational for the intergovernmental agency of the Mekong River Commission. Recognizing the need for scalability to mobilize the global water management community to benefit from satellite remote sensing, we hereby introduce RAT version 3.0. This version is optimized for accelerating open collaboration among users for continuous improvement and customization of RAT to enable reservoir management breakthroughs. RAT 3.0 represents a wholesale overhaul from the previous versions to empower the global community of users and developers in the spirit of the open-source movement. RAT 3.0 allows reservoir monitoring advancements and new functional developments that can be freely exchanged and seamlessly integrated for continuous evolution of the software. A centralized web application has also been established to facilitate the storage and dissemination of global reservoir monitoring information along with comprehensive training resources. RAT 3.0 aspires to bridge the traditional practices of water management community with the capabilities of satellite remote sensing. The global impact of the software can be expected to increase as uptake spreads, enabling a more sustainable and equitable utilization of our planet's water resources.

IPECM Platform: An open-source software for greenhouse environment regulation using machine learning and optimization algorithm

Protected agriculture has emerged as a key solution to address the pressing issue of food scarcity. To enhance crop yield, environmental regulation techniques have been widely employed in protected production. However, the absence of user-friendly, data-driven tools for developing regulation models remains a challenge. This study aims to propose IPECM, an independent and user-friendly software platform for processing and analyzing crop photosynthetic rate (Pn) data and formulating environmental regulation targets. The platform provides functionalities, such as Pn prediction model development, environmental regulation model development and result visualization, supporting various machine learning algorithms and regulation target obtaining algorithms. The IPECM Platform's application is demonstrated through examples of light intensity regulation for cucumber growth and CO2 concentration regulation for tomato growth. The results showcase the software's ability to handle photosynthetic data of any dimension, with the established Pn prediction model achieving a coefficient of determination of 0.98 and a root mean square error lower than 1 μmol·m−2·s−1. The established regulation models can achieve maximum Pn or optimal energy utilization efficiency according to user requirements. IPECM Platform is an independent, automated, and open-source software for protected environmental regulation modeling, providing both the modeling process and results visualization. It offers valuable services for protected agriculture research, eliminating the need for programming knowledge.

A digital twin architecture for real-time and offline high granularity analysis in smart buildings

Smart buildings aim to create a safe, comfortable and sustainable environment for the occupants while increasing the energy performance of the building to reduce the environmental footprint and operational cost. Towards this direction, the use of model-based digital twins able to simulate key aspects of the building is important. Despite the utilization of various digital twin approaches for smart buildings in recent years, most of these approaches mainly focus on one aspect of the building, such as indoor environmental quality or energy consumption. This observation necessitates the development of a virtual but realistic and non-invasive environment able to simulate all the key domains of the building, including indoor air quality, thermal comfort, and energy consumption. Towards this direction, this work proposes an architecture for smart buildings investigations, that emulates the thermal comfort, air-quality, and electricity consumption of the building, while considering the activities and behavior of occupants. For simulating the building operations, ordinary differential equations and power balance modeling are incorporated to facilitate real-time or faster than real-time digital twin approaches, while computational fluid dynamics modeling is used complementarily, to enable higher granularity simulations for offline analysis. Both models have been validated in a real building achieving less than 1% average zone temperature error between the simulation models and the actual building sensor measurements. Furthermore, a user-friendly software platform has been developed and integrated with the proposed architecture, where multiple important features and characteristics have been included to enable various investigations. In particular, the developed platform enables physical and simulated building integration, model calibration using field measurements, experimental configuration and management, execution of novel what-if investigations, and evaluation of novel algorithms using hardware-in-the-loop configurations. The proposed architecture is applied in a physical building, allowing the demonstration of several investigations and the execution of interesting use-cases.

Advanced software for MRgFUS treatment planning

Background and objectivesHerein, a user-friendly software platform for 3-dimensional Focused Ultrasound treatment planning based on Magnetic Resonance Imaging (MRI) images is presented. MethodsThe software directly retrieves and loads MRI images. Various design tools can be used on the MRI images to define the treatment area and the sonication parameters. Based on the treatment plan, the software controls the robotic motion and motion pattern of Magnetic Resonance guided Focused Ultrasound (MRgFUS) robotic systems to execute the treatment procedure. Real-time treatment monitoring is achieved through MRI images and thermometry. The software's functionality and performance were evaluated in both laboratory and MRI environments. Different treatment plans were designed on MRI images and sonications were executed on agar-based phantoms and polymer films. ResultsMagnetic Resonance (MR) thermometry maps were acquired in the agar-based phantoms. An exceptional agreement was observed between the software-planned treatment area and the lesions produced on the polymer films. ConclusionsThe developed software was successfully integrated with the MRI and robotic system controls for performing accurate treatment planning and real-time monitoring during sonications. The software provides an extremely user-friendly interface, while in the future it could be enhanced by providing dynamic modulation of the ultrasonic parameters during the treatment process.

Human Observer Net: A Platform Tool for Human Observer Studies of Image Data.

Background Current software applications for human observer studies of images lack flexibility in study design, platform independence, multicenter use, and assessment methods and are not open source, limiting accessibility and expandability. Purpose To develop a user-friendly software platform that enables efficient human observer studies in medical imaging with flexibility of study design. Materials and Methods Software for human observer imaging studies was designed as an open-source web application to facilitate access, platform-independent usability, and multicenter studies. Different interfaces for study creation, participation, and management of results were implemented. The software was evaluated in human observer experiments between May 2019 and March 2021, in which duration of observer responses was tracked. Fourteen radiologists evaluated and graded software usability using the 100-point system usability scale. The application was tested in Chrome, Firefox, Safari, and Edge browsers. Results Software function was designed to allow visual grading analysis (VGA), multiple-alternative forced-choice (m-AFC), receiver operating characteristic (ROC), localization ROC, free-response ROC, and customized designs. The mean duration of reader responses per image or per image set was 6.2 seconds ± 4.8 (standard deviation), 5.8 seconds ± 4.7, 8.7 seconds ± 5.7, and 6.0 seconds ± 4.5 in four-AFC with 160 image quartets per reader, four-AFC with 640 image quartets per reader, localization ROC, and experimental studies, respectively. The mean system usability scale score was 83 ± 11 (out of 100). The documented code and a demonstration of the application are available online (https://github.com/genskeu/HON, https://hondemo.pythonanywhere.com/). Conclusion A user-friendly and efficient open-source application was developed for human reader experiments that enables study design versatility, as well as platform-independent and multicenter usability. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Thompson in this issue.

BOIN Suite: A Software Platform to Design and Implement Novel Early-Phase Clinical Trials.

Using novel Bayesian adaptive designs has great potential to improve the efficiency of early-phase clinical trials. A major barrier for clinical researchers to adopt novel designs is the lack of easy-to-use software. Our purpose is to develop a user-friendly software platform to implement novel clinical trial designs that address various challenges in early-phase dose-finding trials. We used R Shiny to develop a web-based software platform to facilitate the use of recent novel adaptive designs. We developed a web-based software suite, called Bayesian optimal interval (BOIN) suite, which includes R Shiny applications to handle various clinical settings, including single-agent phase I trials with and without prior information, trials with late-onset toxicity, trials to find the optimal biological dose based on risk-benefit trade-off, and drug combination trials to find a single maximum tolerated dose (MTD) or the MTD contour. The applications are built using the same software architecture to ensure the best and a uniform user experience, and they are developed using a proven software development standard operating procedure to ensure accuracy, robustness, and reproducibility. The suite is freely available with internet access and a web browser without the need of installing any other software. The BOIN suite allows clinical researchers to design various types of early-phase clinical trials under a unified framework. This work is extremely important because it not only advances the clinical research and drug development by facilitating the use of novel trial designs with optimal performance but also enhances collaborations between biostatisticians and clinicians by disseminating novel statistical methodology to broader scientific communities through user-friendly software. The BOIN suite establishes a KISS principle: keep it simple, but smart.

Cassava technology toolkit catalogue: TAAT clearinghouse technical report series 006

Cassava technology toolkit catalogue: TAAT clearinghouse technical report series 006

Orange fleshed sweet potato technology toolkit catalog. TAAT Clearinghouse technical report series 005

Orange fleshed sweet potato technology toolkit catalog. TAAT Clearinghouse technical report series 005

A MATLAB software platform for modelling vertically-integrated non-hydrostatic flows with moment equations

This work presents a software platform to compute depth-integrated non-hydrostatic coastal and open channel flows. The software is based on the Vertically-Averaged and Moment (VAM) equations model. The VAM model uses the weighted residual method to account for the non-hydrostaticity and non-uniformity of flow. After presenting the governing equations, numerical scheme and structure of the graphical user interface, the software is applied to solve coastal and open channel flow tests with significant non-hydrostaticity and non-uniformity of flow. The results are compared with hydrostatic model computations and laboratory measurements. Where a hydrostatic-based simulation poorly reproduces experimental observations, the higher-order model equations by this software platform generate excellent predictions. These findings highlight the potential of this user-friendly software platform for modeling open channel, river and nearshore flows and processes, where non-hydrostatic pressure and non-uniform velocity shall be accounted for, which entails a meaningful advance for the hydraulic community.

ProteoSign: an end-user online differential proteomics statistical analysis platform.

Profiling of proteome dynamics is crucial for understanding cellular behavior in response to intrinsic and extrinsic stimuli and maintenance of homeostasis. Over the last 20 years, mass spectrometry (MS) has emerged as the most powerful tool for large-scale identification and characterization of proteins. Bottom-up proteomics, the most common MS-based proteomics approach, has always been challenging in terms of data management, processing, analysis and visualization, with modern instruments capable of producing several gigabytes of data out of a single experiment. Here, we present ProteoSign, a freely available web application, dedicated in allowing users to perform proteomics differential expression/abundance analysis in a user-friendly and self-explanatory way. Although several non-commercial standalone tools have been developed for post-quantification statistical analysis of proteomics data, most of them are not end-user appealing as they often require very stringent installation of programming environments, third-party software packages and sometimes further scripting or computer programming. To avoid this bottleneck, we have developed a user-friendly software platform accessible via a web interface in order to enable proteomics laboratories and core facilities to statistically analyse quantitative proteomics data sets in a resource-efficient manner. ProteoSign is available at http://bioinformatics.med.uoc.gr/ProteoSign and the source code at https://github.com/yorgodillo/ProteoSign.

A user-friendly LabVIEW software platform for grating based X-ray phase-contrast imaging.

X-ray phase-contrast imaging can provide greatly improved contrast over conventional absorption-based imaging for weakly absorbing samples, such as biological soft tissues and fibre composites. In this study, we introduced an easy and fast way to develop a user-friendly software platform dedicated to the new grating-based X-ray phase-contrast imaging setup at the National Synchrotron Radiation Laboratory of the University of Science and Technology of China. The control of 21 motorized stages, of a piezoelectric stage and of an X-ray tube are achieved with this software, it also covers image acquisition with a flat panel detector for automatic phase stepping scan. Moreover, a data post-processing module for signals retrieval and other custom features are in principle available. With a seamless integration of all the necessary functions in one software package, this platform greatly facilitate users' activities during experimental runs with this grating based X-ray phase contrast imaging setup.

An Advanced Geophysical Software Tool for Seismic Modeling Based on the Finite Element Method

We demonstrate an application of an advanced geophysical software tool to simulate seismic wave propagation and generate shot records. Simulation of seismic wave propagation was performed using eScript, a partial differential equation solver based on the finite element method. We solved the 2D acoustic wave equation for P-wave propagation by applying the partial differential equation to eScript. A traditional absorbing boundary condition was applied to reducing artificial wave reflections at the boundary. We tested several different models by employing meshes for layered media and other complex geological structures. Seismometers were placed equidistantly on the surface to record the wave field and generate shot records. Model tests prove that eScript is a user-friendly software platform which allows rapid development of numerical seismic modeling using python and XML.

CellXpress: a fast and user-friendly software platform for profiling cellular phenotypes

BackgroundHigh-throughput, image-based screens of cellular responses to genetic or chemical perturbations generate huge numbers of cell images. Automated analysis is required to quantify and compare the effects of these perturbations. However, few of the current freely-available bioimage analysis software tools are optimized for efficient handling of these images. Even fewer of them are designed to transform the phenotypic features measured from these images into discriminative profiles that can reveal biologically meaningful associations among the tested perturbations.ResultsWe present a fast and user-friendly software platform called "cellXpress" to segment cells, measure quantitative features of cellular phenotypes, construct discriminative profiles, and visualize the resulting cell masks and feature values. We have also developed a suite of library functions to load the extracted features for further customizable analysis and visualization under the R computing environment. We systematically compared the processing speed, cell segmentation accuracy, and phenotypic-profile clustering performance of cellXpress to other existing bioimage analysis software packages or algorithms. We found that cellXpress outperforms these existing tools on three different bioimage datasets. We estimate that cellXpress could finish processing a genome-wide gene knockdown image dataset in less than a day on a modern personal desktop computer.ConclusionsThe cellXpress platform is designed to make fast and efficient high-throughput phenotypic profiling more accessible to the wider biological research community. The cellXpress installation packages for 64-bit Windows and Linux, user manual, installation guide, and datasets used in this analysis can be downloaded freely from http://www.cellXpress.org.

Transcription factor and microRNA motif discovery: The Amadeus platform and a compendium of metazoan target sets

We present a threefold contribution to the computational task of motif discovery, a key component in the effort of delineating the regulatory map of a genome: (1) We constructed a comprehensive large-scale, publicly-available compendium of transcription factor and microRNA target gene sets derived from diverse high-throughput experiments in several metazoans. We used the compendium as a benchmark for motif discovery tools. (2) We developed Amadeus, a highly efficient, user-friendly software platform for genome-scale detection of novel motifs, applicable to a wide range of motif discovery tasks. Amadeus improves upon extant tools in terms of accuracy, running time, output information, and ease of use and is the only program that attained a high success rate on the metazoan compendium. (3) We demonstrate that by searching for motifs based on their genome-wide localization or chromosomal distributions (without using a predefined target set), Amadeus uncovers diverse known phenomena, as well as novel regulatory motifs.

A new user-friendly software platform for systematic classification of skin lesions to aid in their diagnosis and prognosis

The field of much less invasive nonablative aesthetic surgery continues to grow, but consistent and truly objective evaluation of the sometimes comparatively small improvements in the treated skin remains a problem for both clinicians and patients. In this work, we present the development of a generic, modular and expandable platform to allow user-friendly image manipulation, sampling extraction and computer-assisted evaluation of tissue features in the dermatological/aesthetic field of clinical medicine. The unique characteristic of the platform is the modular extension of the algorithm gallery by the use of extended value added services, which enables the easy incorporation of new image processing procedures to customise the gallery for specific concerns. A novel algorithm to evaluate skin wrinkles is also presented as a demonstration of this integration process. The software platform is designed to evaluate image-tissue indices and to identify individual or combined descriptors which will more accurately represent differences in skin quality. It is based on a set of indices correlating clinical expert and computer classifications, which build up a constantly expanding tissue catalogue. By means of this catalogue, the different tissue qualities of photographic samples can be assessed according to the different positions of the samples in the catalogue. This new platform can be used to generate sensitive and objective comparative measurement not only for diagnostic reports on the pre-treatment condition of samples but also for demonstrating the improvement and efficacy of the prescribed treatment to both the clinician and colleagues and the patient, thereby helping to increase the patient satisfaction index.