scholarly journals BlenderPhotonics - a versatile environment for 3-D complex bio-tissue modeling and light transport simulations based on Blender

2022 ◽  
Author(s):  
Yuxuang Zhang ◽  
Qianqian Fang

Significance: Rapid advances in biophotonics techniques require quantitative, model-based computational approaches to obtain functional and structural information from increasingly complex and multi-scaled anatomies. The lack of efficient tools to accurately model tissue structures and subsequently perform quantitative multi-physics modeling greatly impedes the clinical translation of these modalities. Aim: While the mesh-based Monte Carlo (MMC) method expands our capabilities in simulating complex tissues by using tetrahedral meshes, the generation of such domains often requires specialized meshing tools such as Iso2Mesh. Creating a simplified and intuitive interface for tissue anatomical modeling and optical simulations is essential towards making these advanced modeling techniques broadly accessible to the user community. Approach: We responded to the above challenge by combining the powerful, open-source 3-D modeling software, Blender, with state-of-the-art 3-D mesh generation and MC simulation tools, utilizing the interactive graphical user interface (GUI) in Blender as the front-end to allow users to create complex tissue mesh models, and subsequently launch MMC light simulations. Results: We have developed a Python-based Blender add-on -- BlenderPhotonics -- to interface with Iso2Mesh and MMC, allowing users to create, configure and refine complex simulation domains and run hardware-accelerated 3-D light simulations with only a few clicks. In this tutorial, we provide a comprehensive introduction to this new tool and walk readers through 5 examples, ranging from simple shapes to sophisticated realistic tissue models. Conclusion: BlenderPhotonics is user-friendly and open-source, leveraging the vastly rich ecosystem of Blender. It wraps advanced modeling capabilities within an easy-to-use and interactive interface. The latest software can be downloaded at http://mcx.space/bp.

Author(s):  
Maaz Sirkhot ◽  
Ekta Sirwani ◽  
Aishwarya Kourani ◽  
Akshit Batheja ◽  
Kajal Jethanand Jewani

In this technological world, smartphones can be considered as one of the most far-reaching inventions. It plays a vital role in connecting people socially. The number of mobile users using an Android based smartphone has increased rapidly since last few years resulting in organizations, cyber cell departments, government authorities feeling the need to monitor the activities on certain targeted devices in order to maintain proper functionality of their respective jobs. Also with the advent of smartphones, Android became one of the most popular and widely used Operating System. Its highlighting features are that it is user friendly, smartly designed, flexible, highly customizable and supports latest technologies like IoT. One of the features that makes it exclusive is that it is based on Linux and is Open Source for all the developers. This is the reason why our project Mackdroid is an Android based application that collects data from the remote device, stores it and displays on a PHP based web page. It is primarily a monitoring service that analyzes the contents and distributes it in various categories like Call Logs, Chats, Key logs, etc. Our project aims at developing an Android application that can be used to track, monitor, store and grab data from the device and store it on a server which can be accessed by the handler of the application.


Author(s):  
Alexander Boll ◽  
Florian Brokhausen ◽  
Tiago Amorim ◽  
Timo Kehrer ◽  
Andreas Vogelsang

AbstractSimulink is an example of a successful application of the paradigm of model-based development into industrial practice. Numerous companies create and maintain Simulink projects for modeling software-intensive embedded systems, aiming at early validation and automated code generation. However, Simulink projects are not as easily available as code-based ones, which profit from large publicly accessible open-source repositories, thus curbing empirical research. In this paper, we investigate a set of 1734 freely available Simulink models from 194 projects and analyze their suitability for empirical research. We analyze the projects considering (1) their development context, (2) their complexity in terms of size and organization within projects, and (3) their evolution over time. Our results show that there are both limitations and potentials for empirical research. On the one hand, some application domains dominate the development context, and there is a large number of models that can be considered toy examples of limited practical relevance. These often stem from an academic context, consist of only a few Simulink blocks, and are no longer (or have never been) under active development or maintenance. On the other hand, we found that a subset of the analyzed models is of considerable size and complexity. There are models comprising several thousands of blocks, some of them highly modularized by hierarchically organized Simulink subsystems. Likewise, some of the models expose an active maintenance span of several years, which indicates that they are used as primary development artifacts throughout a project’s lifecycle. According to a discussion of our results with a domain expert, many models can be considered mature enough for quality analysis purposes, and they expose characteristics that can be considered representative for industry-scale models. Thus, we are confident that a subset of the models is suitable for empirical research. More generally, using a publicly available model corpus or a dedicated subset enables researchers to replicate findings, publish subsequent studies, and use them for validation purposes. We publish our dataset for the sake of replicating our results and fostering future empirical research.


2021 ◽  
Vol 9 (6) ◽  
pp. 567
Author(s):  
Alessandra Capolupo ◽  
Cristina Monterisi ◽  
Alessandra Saponieri ◽  
Fabio Addona ◽  
Leonardo Damiani ◽  
...  

The Italian coastline stretches over about 8350 km, with 3600 km of beaches, representing a significant resource for the country. Natural processes and anthropic interventions keep threatening its morphology, moulding its shape and triggering soil erosion phenomena. Thus, many scholars have been focusing their work on investigating and monitoring shoreline instability. Outcomes of such activities can be largely widespread and shared with expert and non-expert users through Web mapping. This paper describes the performances of a WebGIS prototype designed to disseminate the results of the Italian project Innovative Strategies for the Monitoring and Analysis of Erosion Risk, known as the STIMARE project. While aiming to include the entire national coastline, three study areas along the regional coasts of Puglia and Emilia Romagna have already been implemented as pilot cases. This WebGIS was generated using Free and Open-Source Software for Geographic information systems (FOSS4G). The platform was designed by combining Apache http server, Geoserver, as open-source server and PostgreSQL (with PostGIS extension) as database. Pure javascript libraries OpenLayers and Cesium were implemented to obtain a hybrid 2D and 3D visualization. A user-friendly interactive interface was programmed to help users visualize and download geospatial data in several formats (pdf, kml and shp), in accordance with the European INSPIRE directives, satisfying both multi-temporal and multi-scale perspectives.


2017 ◽  
Author(s):  
J.A. Grogan ◽  
A.J. Connor ◽  
B. Markelc ◽  
R.J. Muschel ◽  
P.K. Maini ◽  
...  

AbstractSpatial models of vascularized tissues are widely used in computational physiology, to study for example, tumour growth, angiogenesis, osteogenesis, coronary perfusion and oxygen delivery. Composition of such models is time-consuming, with many researchers writing custom software for this purpose. Recent advances in imaging have produced detailed three-dimensional (3D) datasets of vascularized tissues at the scale of individual cells. To fully exploit such data there is an increasing need for software that allows user-friendly composition of efficient, 3D models of vascularized tissue growth, and comparison of predictions with in vivo or in vitro experiments and other models. Microvessel Chaste is a new open-source library for building spatial models of vascularized tissue growth. It can be used to simulate vessel growth and adaptation in response to mechanical and chemical stimuli, intra- and extra-vascular transport of nutrient, growth factor and drugs, and cell proliferation in complex 3D geometries. The library provides a comprehensive Python interface to solvers implemented in C++, allowing user-friendly model composition, and integration with experimental data. Such integration is facilitated by interoperability with a growing collection of scientific Python software for image processing, statistical analysis, model annotation and visualization. The library is available under an open-source Berkeley Software Distribution (BSD) licence at https://jmsgrogan.github.io/MicrovesselChaste. This article links to two reproducible example problems, showing how the library can be used to model tumour growth and angiogenesis with realistic vessel networks.


2019 ◽  
Vol 23 ◽  
pp. 162
Author(s):  
E. Mitsi ◽  
T. J. Mertzimekis

A semi-automated procedure based on open-source utilities was designed and built to analyze spectra collected at a synchrotron accelerator using the μ-XRF technique. The software (RICOCHET) has a fast, efficient and user-friendly design aimed at performing online analysis. A few examples of its application using recent μ-XRF data from the SUL-X beamline at ANKA Synchrotron Facility (KIT) are presented.


2021 ◽  
Vol 10 (2) ◽  
pp. e40810212664
Author(s):  
Marina Nascimento Alves Vieira ◽  
Camila Nascimento Alves ◽  
Vyviane dos Santos Ferreira ◽  
Cleisianne Nazaré Leite Barbosa

O objetivo da pesquisa apresentada neste artigo foi realizar a modelagem de propriedades geológico-geotécnicas no subsolo de um bairro no município de Belém do Pará a partir de sondagem à percussão, usando como ferramenta a geoestatística. Para alcançar o objetivo realizou-se a catalogação do acervo técnico contendo 101 boletins de sondagem à percussão. Criou-se um banco de dados contendo os dados de coordenadas geográficas, tipo de solo, profundidade das camadas do solo, nível do lençol freático e Índice de Resistência à Penetração (NSPT), conforme a norma NBR 6484/2001. Os dados foram analisados em ambiente SIG (Sistema de Informação Geográfica) com softwares Open Source, como SGEMS (Standford Geoestatistical Modeling Software) para análise geoestatística e o software Qgis para análises cartográficas. Distinguiu-se duas zonas díspares na região de estudo, denominadas de Zona A e Zona B. A Zona A é considerada uma região com os maiores índices de resistência dos solos e a Zona B uma região com menores índices de resistência, conforme demonstrado nos mapas. Na região ocorrem argilas orgânicas de baixa resistência nas proximidades das áreas de várzea, onde no passado eram localizados os igarapés. No entanto, esses locais foram retificados durante o processo de urbanização. E, atualmente, localizam-se as regiões de baixa resistência descritas nos resultados desta pesquisa.


2021 ◽  
Author(s):  
Iva Halilaj ◽  
Avishek Chatterjee ◽  
Yvonka van Wijk ◽  
Guangyao Wu ◽  
Brice van Eeckhout ◽  
...  

AbstractObjectiveThe current pandemic has led to a proliferation of predictive models being developed to address various aspects of COVID-19 patient care. We aimed to develop an online platform that would serve as an open source repository for a curated subset of such models, and provide a simple interface for included models to allow for online calculation. This platform would support doctors during decision-making regarding diagnoses, prognoses, and follow-up of COVID-19 patients, expediting the models’ transition from research to clinical practice.MethodsIn this proof-of-principle study, we performed a literature search in PubMed and WHO database to find suitable models for implementation on our platform. All selected models were publicly available (peer reviewed publications or open source repository) and had been validated (TRIPOD type 3 or 2b). We created a method for obtaining the regression coefficients if only the nomogram was available in the original publication. All predictive models were transcribed on a practical graphical user interface using PHP 8.0.0, and published online together with supporting documentation and links to the associated articles.ResultsThe open source website https://covid19risk.ai/ currently incorporates nine models from six different research groups, evaluated on datasets from different countries. The website will continue to be populated with other models related to COVID-19 prediction as these become available. This dynamic platform allows COVID-19 researchers to contact us to have their model curated and included on our website, thereby increasing the reach and real-world impact of their work.ConclusionWe have successfully demonstrated in this proof-of-principle study that our website provides an inclusive platform for predictive models related to COVID-19. It enables doctors to supplement their judgment with patient-specific predictions from externally-validated models in a user-friendly format. Additionally, this platform supports researchers in showcasing their work, which will increase the visibility and use of their models.


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