scholarly journals An open-source experimental framework for automation of cell biology experiments

2020 ◽  
Author(s):  
Pavel Katunin ◽  
Ashley Cadby ◽  
Anton Nikolaev
Keyword(s):  
Open Source ◽  
Cell Biology ◽  
Biological Data ◽  
List Type ◽  
Fluorescent Reporters ◽  
Fluorescent Microscope ◽  
Treatment Conditions ◽  
Key Points ◽  
Open Source Hardware ◽  
High Degree

AbstractModern data analysis methods, such as deep learning, have been successfully applied to a number of biological and medical questions. For these methods to be efficient, a large number of high quality experiments need to be conducted, which requires a high degree of automation. Here we report an open-source hardware that allows for automatic high-throughput generation of large amounts of biological data. The hardware consists of an automatic XY-stage for moving multiwell plates containing growing cells; a perfusion manifold allowing application (perfusion) of up to 8 different solutions; and a small epifluorescent microscope. It is extremely cheap (£300 without and £2500 with a fluorescent microscope) and can be quickly customised for individual experimental needs.Key points- We present an open source framework for automation of cell biology experiments- The framework consists of an XY platform, application of up to 8 solutions and a small epifluorescent microscope- Very cheap (£300 without a fluorescent microscope and £2500 with a fluorescent microscope), customisable, 3D printable- Can be used in a variety of biological applications such as imaging of fluorescent reporters, optimisation of treatment conditions and immuno-labelling

scholarly journals An Open-Source Framework for Automated High-Throughput Cell Biology Experiments

2021 ◽  
Vol 9 ◽  
Author(s):  
Pavel Katunin ◽  
Jianbo Zhou ◽  
Ola M. Shehata ◽  
Andrew A. Peden ◽  
Ashley Cadby ◽  
...  
Keyword(s):  
Open Source ◽  
High Throughput ◽  
Cell Biology ◽  
Large Scale ◽  
Low Cost ◽  
Fluorescent Labeling ◽  
Open Source Framework ◽  
Open Source Hardware ◽  
High Degree ◽  
Data Analysis Methods

Modern data analysis methods, such as optimization algorithms or deep learning have been successfully applied to a number of biotechnological and medical questions. For these methods to be efficient, a large number of high-quality and reproducible experiments needs to be conducted, requiring a high degree of automation. Here, we present an open-source hardware and low-cost framework that allows for automatic high-throughput generation of large amounts of cell biology data. Our design consists of an epifluorescent microscope with automated XY stage for moving a multiwell plate containing cells and a perfusion manifold allowing programmed application of up to eight different solutions. Our system is very flexible and can be adapted easily for individual experimental needs. To demonstrate the utility of the system, we have used it to perform high-throughput Ca2+ imaging and large-scale fluorescent labeling experiments.

An Open-Sourced Web Application for Aerial Applicators to Avoid Spray Drift Caused by Temperature Inversion

2021 ◽  
Vol 37 (1) ◽  
pp. 77-84
Author(s):  
Yanbo Huang ◽  
D. K. Fisher
Keyword(s):  
Open Source ◽  
Web Application ◽  
Mississippi Delta ◽  
Temperature Inversion ◽  
Weather Data ◽  
List Type ◽  
Spray Drift ◽  
Atmospheric Conditions ◽  
Weather Stations ◽  
Open Source Hardware

HighlightsA web application for guiding data calculated from distributed weather data through open-source cloud service.A design scheme of portable weather stations built from inexpensive open-source electronics.Integration of open-source hardware and software for online guiding data to avoid drift caused by temperature inversion.Abstract. It is important for agricultural chemical applicators to follow proper spray procedures to prevent susceptible crops, animals, people, or other living organisms from being injured far downwind. Spraying during stable atmospheric conditions should be avoided to prevent surface-temperature inversion-induced off-target drift of crop protection materials. Previous statistical analysis determined times of high likelihood of stable atmospheric conditions, which are unfavorable for spraying, during the day under clear and cloudy conditions in hot summer months in the Mississippi Delta. Results validated the thresholds of temperature increase in the morning and temperature drop in the afternoon with wind speeds and the transition between stable and unstable atmospheric conditions. With this information, an algorithm was developed to calculate if atmospheric conditions were favorable for spraying based on field temperature and wind speed at any instant. With this algorithm, a web application was built to provide real-time determination of atmospheric stability and hourly online recommendation of whether aerial applications were appropriate for a location and time in the Mississippi Delta. This study further developed another web application specifically for Stoneville, Mississippi, with data measured from weather stations constructed from inexpensive open-source electronics, accessories, and software for more accurate online guidance for site-specific drift management. The web application is adapted for accessing on mobile terminals, such as smartphones and tablets, and provides timely guidance for aerial applicators and producers to avoid spray drift and air quality issues long distances downwind in the area. Keywords: Open-source hardware, Open-source software, Spray drift, Temperature inversion, Web application.

scholarly journals Democratising “Microscopi”: a 3D printed automated XYZT fluorescence imaging system for teaching, outreach and fieldwork

2020 ◽  
Author(s):  
Matthew Wincott ◽  
Andrew Jefferson ◽  
Ian M. Dobbie ◽  
Martin J. Booth ◽  
Ilan Davis ◽  
...  
Keyword(s):  
Open Source ◽  
Fluorescence Imaging ◽  
Imaging System ◽  
Low Cost ◽  
Dark Field ◽  
List Type ◽  
Image Capture ◽  
Fluorescence Imaging System ◽  
3D Printed ◽  
Open Source Hardware

ABSTRACTCommercial fluorescence microscope stands and fully automated XYZt fluorescence imaging systems are generally beyond the limited budgets available for teaching and outreach. We have addressed this problem by developing “Microscopi”, an accessible, affordable, DIY automated imaging system that is built from 3D printed and commodity off-the-shelf hardware, including electro-mechanical, computer and optical components. Our design features automated sample navigation and image capture with a simple web-based graphical user interface, accessible with a tablet or other mobile device. The light path can easily be switched between different imaging modalities. The open source Python-based control software allows the hardware to be driven as an integrated imaging system. Furthermore, the microscope is fully customisable, which also enhances its value as a learning tool. Here, we describe the basic design and demonstrate imaging performance for a range of easily sourced specimens.HighlightsPortable, low cost, self-build from 3D printed and commodity componentsMultimodal imaging: bright field, dark field, pseudo-phase and fluorescenceAutomated XYZt imaging from a tablet or smartphone via a simple GUIWide ranging applications in teaching, outreach and fieldworkOpen source hardware and software design, allowing user modification

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Feature Detection ◽  
Video Stream ◽  
Object Identification ◽  
Vision Systems ◽  
Modern Computer ◽  
Computer Vision Systems ◽  
Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

scholarly journals Shock tube data processing tools using open source hardware and software platforms

2020 ◽  
Author(s):  
K. Thirumalesh ◽  
Salgeri Puttaswamy Raju ◽  
Hiriyur Mallaiah Somashekarappa ◽  
Kumaraswamy Swaroop
Keyword(s):  
Data Processing ◽  
Shock Tube ◽  
Open Source ◽  
Software Platforms ◽  
Open Source Hardware

scholarly journals Monitoring System for Tracking a PV Generator in an Experimental Smart Microgrid: An Open-Source Solution

2021 ◽  
Vol 13 (15) ◽  
pp. 8182
Author(s):  
José María Portalo ◽  
Isaías González ◽  
Antonio José Calderón
Keyword(s):  
Open Source ◽  
Monitoring System ◽  
Smart Grids ◽  
Raspberry Pi ◽  
Operator Interface ◽  
Open Source Hardware ◽  
Real Time Information ◽  
And Storage ◽  
Time Information ◽  
Pv Generator

Smart grids and smart microgrids (SMGs) require proper monitoring for their operation. To this end, measuring, data acquisition, and storage, as well as remote online visualization of real-time information, must be performed using suitable equipment. An experimental SMG is being deployed that combines photovoltaics and the energy carrier hydrogen through the interconnection of photovoltaic panels, electrolyser, fuel cell, and load around a voltage bus powered by a lithium battery. This paper presents a monitoring system based on open-source hardware and software for tracking the temperature of the photovoltaic generator in such an SMG. In fact, the increases in temperature in PV modules lead to a decrease in their efficiency, so this parameter needs to be measured in order to monitor and evaluate the operation. Specifically, the developed monitoring system consists of a network of digital temperature sensors connected to an Arduino microcontroller, which feeds the acquired data to a Raspberry Pi microcomputer. The latter is accessed by a cloud-enabled user/operator interface implemented in Grafana. The monitoring system is expounded and experimental results are reported to validate the proposal.

A mobile sensor package for real-time greenhouse monitoring using open-source hardware

2019 ◽  
Author(s):  
Lars Larson ◽  
Elad Levintal ◽  
Jose Manuel Lopez Alcala ◽  
Dr. Lloyd Nackley ◽  
Dr. John Selker ◽  
...  
Keyword(s):  
Open Source ◽  
Real Time ◽  
Mobile Sensor ◽  
Sensor Package ◽  
Open Source Hardware
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