Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2024, Volume and Issue: 8(7)
Published: July 1, 2024
Language: Английский
Published: Jan. 1, 2024
As a minimally invasive medical technique, nanorobots provide practical solutions to applications where, for instance, traditional surgery or cancer treatment may pose severe risks due the delicate nature of said procedure. In specific cases where intended area is difficult reach (e.g., gastrointestinal tract, blood-brain barrier), can be guided toward such target sites various purposes, including drug delivery and reduction/elimination cells. Current literature relating nanorobotics explore propulsion techniques, nanorobot design, clinical testing in animals that suffer from diseases. However, spare research has been conducted on control nanorobots. Since robots targeted are micro- nanometers size rely unconventional propulsion, implementing laws become vital ensure robot reaches its target. Therefore, this explores optimal tracking Though limited, existing regarding nanorobotic nonlinear methods. publications, model-dependent Model Predictive Control (MPC) implemented by deriving via backstepping approaches. With controllers, excellent robust have demonstrated with low errors. as will discussed following chapters, obtained results come computational costs high complexity derived laws. For reason, proposes linear approach good balance between computation performance. Further, guaranteed, thus, eliminated, provided dominant dynamical information retained after linearization.
Language: Английский
Citations
0
Published: March 2, 2024
Automated of gas and liquid classification technologies are great in multiple fields including food production human healthcare. Of these, fruit juice contains water, organic acids, minerals other nutrients which offers a pleasant taste promotes healthy condition. However, the main challenges faced by conventional components sensing for limited to complexity experimental preparation, bulky instrument, high consumption susceptibility contamination. Moisture Electricity Generation (MEG) technology has made it feasible acquire energy from trace amounts water or environmental humidity. This work proposes novel unit based on MEG technology. The mainly comprises non-woven fabric, hydroxylated carbon nanotubes, polyvinyl alcohol, solution sea salt alloy. By this approach, humid air (relative humidity 60%), pure juices three fruits (lemon, kiwifruit, clementine) have been successfully classified 15 seconds. accuracy can reach 90%. Electrical signals standard lines highlight specific response between samples. relative deviation stable output section is 1.6% root-mean-square error test data curve less than 0.08, indicates stability, fine. Besides, demonstrates an acceptable reusability. presented approach may provide opportunities improve paradigms industrial medical settings.
Language: Английский
Citations
0
Bioanalysis, Journal Year: 2024, Volume and Issue: 16(17-18), P. 927 - 930
Published: July 9, 2024
Language: Английский
Citations
0
Advances in medical technologies and clinical practice book series, Journal Year: 2024, Volume and Issue: unknown, P. 135 - 168
Published: Sept. 14, 2024
This chapter explores the potential of Artificial Intelligence (AI) in nanomedicine design, focusing on Deep Reinforcement Learning (DRL) for optimizing pharmacokinetics. Nanomedicine uses nanoscale materials disease diagnosis, treatment, and monitoring, presenting unique challenges opportunities due to biological system complexity. principles are used design nanoparticles with optimal properties targeted drug delivery controlled release. AI is practically applied including AI-driven platforms predicting biodistribution, metabolism, clearance. The also discusses integration DRL other techniques ethical considerations, emphasizing transparency, reproducibility, collaboration between experts, clinicians, regulatory bodies.
Language: Английский
Citations
0
ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: 16(46), P. 63723 - 63734
Published: Nov. 7, 2024
Classifications of fluids using miniaturized sensors are substantial importance for various fields application. Modified with functional nanomaterials, a moisture-enabled electricity generation (MEG) device can execute dual-purpose operation as both self-powered framework and fluid detection platform. In this study, novel intelligent self-sustained sensing approach was implemented by integrating MEG deep learning in microfluidics. Following multilayer design, the including three individual units power generation/fluid classification fabricated study nonwoven fabrics, hydroxylated carbon nanotubes, poly(vinyl alcohol)-mixed gels, indium tin bismuth liquid alloy. A composite configuration utilizing hydrophobic microfluidic channels hydrophilic porous substrates conducive to self-regulation on-chip flow. As generator, capable maintaining continuous stable output at least 6 h. sensor, synchronously measured voltage (V), current (C), resistance (R) signals functions time, whose transitions were completed relays. These serve straightforward indicators presence, such distinctive "fingerprint". After normalization Fourier transform raw V/C/R signals, lightweight model (wide-kernel convolutional neural network, WDCNN) employed classifying pure water, kiwifruit, clementine, lemon juices. particular, accuracy sample distinction WDCNN 100% within 15 s. The proposed integration MEG, microfluidics, provides paradigm development sustainable environmental perception, well new prospects innovations analytical science smart instruments.
Language: Английский
Citations
0
Advanced Intelligent Systems, Journal Year: 2024, Volume and Issue: unknown
Published: Nov. 28, 2024
Microrobotics, particularly in the field of biomedicine, has garnered considerable attention due to its potential for noninvasive medical interventions enabled by small size microrobots. However, controlling and imaging them present unique challenges compared their macroscale counterparts, primarily intricate anatomical spaces dynamic environments within human body. Existing modalities also face limitations, hindering real‐time visualization control microrobots deep tissue. Machine learning (ML) algorithms offer promising solutions these enabling adaptive motion enhancing image resolution through robust data analysis decision‐making capabilities. In this review, a comprehensive overview recent advancements ML‐based techniques microrobotic research is provided, emphasizing applications biomedical contexts. Additionally, current obstacles future directions ML microrobotics, regarding translation clinical settings, are discussed.
Language: Английский
Citations
0
Nanotechnology Perceptions, Journal Year: 2024, Volume and Issue: unknown, P. 77 - 89
Published: Dec. 1, 2024
The advancement in artificial intelligence and nanotechnology has provided new solutions for tackling problems enhanced engineering design. This research focuses on both AI assisted observational methodologies Bayesian uncertainty quantification (BUQ) improving the predictive models, material properties, design procedures. Four complex techniques of estimating managing are following: Neural Networks (BNN), Gaussian Processes (GP), Monte Carlo Dropout (MCD), Ensemble Learning (EL). Numerical studies revealed that forecast accuracy proposed framework is 94.6% with BNN 93.1% GP, which makes excellent improvements over prior arts up to 15% quantification. Besides, computational resources less by 20% EL compared standalone approaches, while incorporation nanoscale information increase AT RT 17%. To demonstrate AI-driven BUQ addresses limitations existing a comparative discussion provided. results reinforce its viability providing sustainable efficient under conditions risk. work may be used as platform subsequent synergies between AI, nanotechnology, advanced materials systems drive progress well
Language: Английский
Citations
0
Multiscale and Multidisciplinary Modeling Experiments and Design, Journal Year: 2024, Volume and Issue: 8(7)
Published: July 1, 2024
Language: Английский
Citations
0