Here, we develop and show the use of an open-source Python library to control commercial potentiostats. It standardizes the commands for different potentiostat models, opening the possibility to perform automated experiments independently of the instrument used. At the time of this writing, we have included potentiostats from CH Instruments (models 1205B, 1242B, 601E, and 760E) and PalmSens (model Emstat Pico), although the open-source nature of the library allows for more to be included in the future. To showcase the general workflow and implementation of a real experiment, we have automated the Randles-Ševčı́k methodology to determine the diffusion coefficient of a redox-active species in solution using cyclic voltammetry. This was accomplished by writing a Python script that includes data acquisition, data analysis, and simulation. The total run time was 1 min and 40 s, well below the time it would take even an experienced electrochemist to apply the methodology in a traditional manner. Our library has potential applications that expand beyond the automation of simple repetitive tasks; for example, it can interface with peripheral hardware and well-established third-party Python libraries as part of a more complex and intelligent setup that relies on laboratory automation, advanced optimization, and machine learning.
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http://dx.doi.org/10.1021/acs.analchem.2c04862 | DOI Listing |
Ultrasound Med Biol
January 2025
Department of Circulation and Medical Imaging, Norwegian University of Science and Technology - NTNU, Trondheim, Norway; Health Research, SINTEF, Trondheim, Norway.
Objective: To develop and compare methods to automatically estimate regional ultrasound image quality for echocardiography separate from view correctness.
Methods: Three methods for estimating image quality were developed: (i) classic pixel-based metric: the generalized contrast-to-noise ratio (gCNR), computed on myocardial segments (region of interest) and left ventricle lumen (background), extracted by a U-Net segmentation model; (ii) local image coherence: the average local coherence as predicted by a U-Net model that predicts image coherence from B-mode ultrasound images at the pixel level; (iii) deep convolutional network: an end-to-end deep-learning model that predicts the quality of each region in the image directly. These methods were evaluated against manual regional quality annotations provided by three experienced cardiologists.
Entropy (Basel)
January 2025
Interacting Minds Centre, Aarhus University, 8000 Aarhus, Denmark.
We introduce a new software package for the Julia programming language, the library ActiveInference.jl. To make active inference agents with Partially Observable Markov Decision Process (POMDP) generative models available to the growing research community using Julia, we re-implemented the pymdp library for Python.
View Article and Find Full Text PDFHeliyon
January 2025
Department of Chemical Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka, 1000, Bangladesh.
The widespread adoption of electronic devices has enhanced living standards but has also led to a surge in electronic waste (e-waste), creating serious environmental and health challenges. Although various methods exist to recover valuable metals from e-waste, each has notable drawbacks. Among these, chemical leaching with aqua regia is widely used but is both highly corrosive and hazardous.
View Article and Find Full Text PDFJ Am Mosq Control Assoc
January 2025
Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, 30602.
Accurate enumeration of mosquito eggs is crucial for various entomologic studies, including investigations into mosquito fecundity, life history traits, and vector control strategies. Traditional manual counting methods are labor intensive and prone to human error, highlighting the need for automated systems. This study presents a stand-alone automated mosquito egg counting system using a Raspberry Pi computer, high-quality camera, light-emitting diode ring light source, and a Python script leveraging the Open Source Computer Vision library.
View Article and Find Full Text PDFbioRxiv
January 2025
Department of Computer Science, Johns Hopkins University, 3400 N Charles St, 21218, Maryland, USA.
Minimizer digestion is an increasingly common component of bioinformatics tools, including tools for De Bruijn-Graph assembly and sequence classification. We describe a new open source tool and library to facilitate efficient digestion of genomic sequences. It can produce digests based on the related ideas of minimizers, modimizers or syncmers.
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