Rapid changes in healthcare coupled with parallel advances in technology have stimulated the evolution of new approaches for laboratory automation. In particular, the emergence of commercially available laboratory robotic systems offers promise for streamlining the clinical laboratory. Increasing cost-containment pressures make the application of this technology extremely attractive, and several organizations have begun to systematically integrate robotic devices into their laboratory automation schemes. Integration of these technologies, however, presents many challenges for software developers, instrument manufacturers, and laboratory workers. Differing needs across laboratories require flexibility and intelligence in robots, instruments, and control systems. Standardization of mechanical and electronic interfaces will be key to making these systems easy to integrate. Systems engineering, aided by simulation modeling and artificial intelligence schemes, will be important to assist in the design of optimal configurations. Software for the overall control of integrated automation will be needed that can be tailored by the laboratorian to fit the requirements of the individual laboratory. Thus, laboratory workers will need to be actively involved in implementing this new wave of laboratory automation, becoming well-versed in computers, electronics, and systems engineering.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
ATKB-PID: an adaptive control method for micro tension under complex hot rolling conditions.
Sci Rep
January 2025
State Key Laboratory of Metallurgical Intelligent Manufacturing System, Beijing, 100071, China.
At present, the parameters of the controllers in hot rolling roughing microtension control systems are not adaptively adjustable to variations in working conditions, which compromises both width accuracy and production stability. To address this issue, this paper introduces an ATKB-PID adaptive micro tension control method. This method incorporates a linear attention layer and utilizes a K-Nearest Neighbors (KNN) algorithm to predict the optimal learning rate and inertia coefficient under actual operating conditions.
View Article and Find Full Text PDFDIFLF: A domain-invariant features learning framework for single-source domain generalization in mammogram classification.
Comput Methods Programs Biomed
January 2025
School of Engineering Medicine, Beihang University, Beijing 100191, PR China; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of the People's Republic of China, Beijing 100191, PR China; Beijing Engineering Research Center of Cardiovascular Wisdom Diagnosis and Treatment, Beijing 100029, PR China. Electronic address:
Background And Objective: Single-source domain generalization (SSDG) aims to generalize a deep learning (DL) model trained on one source dataset to multiple unseen datasets. This is important for the clinical applications of DL-based models to breast cancer screening, wherein a DL-based model is commonly developed in an institute and then tested in other institutes. One challenge of SSDG is to alleviate the domain shifts using only one domain dataset.
View Article and Find Full Text PDFDimensional engineering of interlayer for efficient large-area perovskite solar cells with high stability under ISOS-L-3 aging test.
Sci Adv
January 2025
Fujian Key Laboratory of Semiconductor Materials and Applications, CI Center for OSED, Department of Physics, Xiamen University, Xiamen 361005, P. R. China.
The utilization of low-dimensional perovskites (LDPs) as interlayers on three-dimensional (3D) perovskites has been regarded as an efficient strategy to enhance the performance of perovskite solar cells. Yet, the formation mechanism of LDPs and their impacts on the device performance remain elusive. Herein, we use dimensional engineering to facilitate the controllable growth of 1D and 2D structures on 3D perovskites.
View Article and Find Full Text PDFHuman-in-the-loop optimization of wearable device parameters using an EMG-based objective function.
Wearable Technol
November 2024
BruBotics, Vrije Universiteit Brussel, Brussels, 1050, Belgium.
Advancements in wearable robots aim to improve user motion, motor control, and overall experience by minimizing energetic cost (EC). However, EC is challenging to measure and it is typically indirectly estimated through respiratory gas analysis. This study introduces a novel EMG-based objective function that captures individuals' natural energetic expenditure during walking.
View Article and Find Full Text PDFAccelerating the Discovery of Abiotic Vesicles with AI-Guided Automated Experimentation.
Langmuir
January 2025
Department of Chemistry and Biochemistry, Fordham University, 441 East Fordham Road, The Bronx, New York 10458, United States.
The first protocells are speculated to have arisen from the self-assembly of simple abiotic carboxylic acids, alcohols, and other amphiphiles into vesicles. To study the complex process of vesicle formation, we combined laboratory automation with AI-guided experimentation to accelerate the discovery of specific compositions and underlying principles governing vesicle formation. Using a low-cost commercial liquid handling robot, we automated experimental procedures, enabling high-throughput testing of various reaction conditions for mixtures of seven (7) amphiphiles.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!