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NIR-Responsive Methotrexate-Modified Iron Selenide Nanorods for Synergistic Magnetic Hyperthermic, Photothermal, and Chemodynamic Therapy

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ACS Applied Materials and Interfaces 2024年第20期16卷 25622-25636页

作者： Thirumurugan, Senthilkumar Muthiah, Kayalvizhi Samuvel Lin, Yu-Chien Dhawan, Udesh Liu, Wai-Ching Wang, An-Ni Liu, Xinke Hsiao, Michael Tseng, Ching-Li Chung, Ren-Jei No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Centre for the Cellular Microenvironment Division of Biomedical Engineering James Watt School of Engineering Mazumdar-Shaw Advanced Research Centre University of Glasgow GlasgowG116EW United Kingdom Faculty of Science and Technology Technological and Higher Education Institute of Hong Kong Hong Kong New Territories999077 Hong Kong Scrona AG Grubenstrasse 9 Zürich8045 Switzerland College of Materials Science and Engineering Chinese Engineering and Research Institute of Microelectronics Shenzhen University Shenzhen518060 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Genomics Research Center Academia Sinica Taipei115 Taiwan Department and Graduate Institute of Veterinary Medicine School of Veterinary Medicine National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Taipei10608 Taiwan

Breast cancer is a malignant tumor with a high mortality rate among women. Therefore, it is necessary to develop novel therapies to effectively treat this disease. In this study, iron selenide nanorods (FeSe2 NRs) were designed for use in magnetic hyperthermic, photothermal, and chemodynamic therapy (MHT/PTT/CDT) for breast cancer. To illustrate their efficacy, FeSe2 NRs were modified with the chemotherapeutic agent methotrexate (MTX). MTX-modified FeSe2 (FeSe2-MTX) exhibited excellent controlled drug release properties. Fe2+ released from FeSe2 NRs induced the release of •OH from H2O2 via a Fenton/Fenton-like reaction, enhancing the efficacy of CDT. Under alternating magnetic field (AMF) stimulation and 808 nm laser irradiation, FeSe2-MTX exerted potent hyperthermic and photothermal effects by suppressing tumor growth in a breast cancer nude mouse model. In addition, FeSe2 NRs can be used for magnetic resonance imaging in vivo by incorporating their superparamagnetic characteristics into a single nanomaterial. Overall, we presented a novel technique for the precise delivery of functional nanosystems to tumors that can enhance the efficacy of breast cancer treatment. © 2024 The Authors. Published by American Chemical Society

关键词： Magnetic resonance imaging

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Parallel differential evolution paradigm for multilayer electromechanical device optimization

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Modern Physics Letters B 2024年第31期38卷

作者： Zameer, Aneela Naz, Sidra Zahoor Raja, Muhammad Asif Department of Computer & Information Sciences Pakistan Institute of Engineering & Applied Sciences (PIEAS) Nilore Islamabad 45650 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin 64002 Taiwan

Design optimization of multilayer piezoelectric transducers is intended for efficient and practical usage of wideband transducers for fault diagnosis, biomedical, and underwater applications through adjusting layer thicknesses and volume fraction of piezoelectric material in each layer. In this context, we propose a parallel differential evolution (PDE) algorithm to mitigate the complexities of multivariate optimization as well as the computation time to achieve an optimized wideband transducer for the particular application. For lead magnesium niobate-lead titanate (PMN PT)- and PZT5h-based piezoelectric materials, the fitness function is formulated based on uniformity of mechanical pressure at the first three harmonics to achieve wide bandwidth in the required functional frequency range. It is carried out using a one-dimensional model (ODM), while input layer thicknesses and volume fractions of active material are evaluated using PDE. The simulation is performed on a parallel computing platform utilizing three different host machines to reduce computational time. Results of the proposed methodology for PDE are statistically represented in the form of minimum, maximum, mean, and standard deviation of fitness value, while graphically represented in terms of speedup and time. It can be observed that the execution time for parallel DE decreases with the increasing number of cores. © World Scientific Publishing Company.

关键词： di®erential evolution parallel computing piezocomposite piezoelectric ceramic Transducer

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An enhanced strategy for minority class detection using bidirectional GRU employing penalized cross-entropy and self-attention mechanisms for imbalance network traffic

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European Physical Journal Plus 2024年第6期139卷 530页

作者： Abbasi, Asima Akber Zameer, Aneela Raja, Muhammad Asif Zahoor Department of Computer and Information Sciences Pakistan Institute of Engineering and Applied Sciences (PIEAS) Islamabad Nilore 45650 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou 64002 Taiwan

The emergence of the Internet as a global communication tool has brought significant transformations across various aspects of our everyday lives. However, it has also resulted in new technical challenges, such as the risk of personal information exposure, network congestion, and limited availability of network addresses. The cybersecurity field has greatly benefited from the implementation of artificial intelligence and machine learning to model network activity and improve the detection of potential threats. Intrusion detection systems are specifically unable to tackle the challenges of high-class imbalance and the varying significance of misclassifications specifically for minority classes. The proposed SABiG (CPL) model targets the high dimensional imbalance data set CIC-IDS2017 by employing the evolutionary computing framework of genetic algorithms utilizing random forest GA(RF) for optimal feature selection. For attack classification, a powerful deep learning technique of bidirectional gated recurrent unit (Bi-GRU) with a self-attention mechanism is exploited. Our proposed model features a custom penalized cross entropy strategy by assigning three penalty values according to class imbalanced ratios to address the misclassification issue. The experimental results have demonstrated enhanced detection accuracy for all classes in general and minority classes in particular, such as infiltration, and web attacks. Comparison with the existing techniques in terms of all standard performance indices further evaluates our proposed intrusion detection system for imbalanced data. The generalization of the proposed model is evaluated with the recent CIC-CSE-IDS2018 web attack dataset. © The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2024.

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Acetone Liquid Sensing Based on Fiber Optic Mach-Zehnder Interferometer 13

Acetone Liquid Sensing Based on Fiber Optic Mach-Zehnder Int...

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13th IEEE Regional Symposium on Micro and Nanoelectronics, RSM 2021

作者： Hani Zailani, Nur Fazeera Saidin, Norazlina Mohd Rusdi, Muhammad Farid Harun, Sulaiman Wadi Thirunavakkarasu, Punithavathi M. International Islamic University Malaysia Electrical and Computer Engineering Department Selangor Malaysia University of Malaya Faculty of Engineering Photonics Engineering Laboratory Department of Electrical and Engineering Kuala Lumpur Malaysia Communication Technology Section Universiti Kuala Lumpur British Malaysian Institute Kuala Lumpur Malaysia

ISBN: (纸本)9781665412315

Fiber based optical sensors have been widely used in many industries today to detect parameters such as temperature, pressure, vibrations, concentrations and many more. A Mach-Zehnder Interferometer (MZI) is well known for its compact structure and small size which are advantageous for sensing purposes. In this project, an MZI with a singlemode-multimode-singlemode-multimode (SMSM) structure is developed for measuring acetone concentration in reverse osmosis (RO) water. The MZI consists of two single mode fibers (SMF) and two multimode fibers (MMF) spliced together using an arc fusion splicer machine to produce a SMSM structure. The MZI generates a good, reflected interference spectrum where the dip wavelength is red-shifted with the increase of acetone concentration. The sensitivity of the fiber sensor is 1.5391 nm/M within the range of 0M until 4M of acetone concentration. Based on the result, the sensor has a linear response towards the changes of concentration of 94.38%. This preliminary result shows that the proposed sensor can be used to detect acetone concentration to avoid contaminated water that may be of potential concern for human health. © 2021 IEEE.

关键词： Multimode fibers

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RETRACTED ARTICLE: A comparative recognition research on excretory organism in medical applications using neural networks

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Multimedia Tools and Applications 2023年 1-2页

作者： K, Vidhya R, Krishna Priya Vidhyalakshmi, M. Ramesh, S. M. L, Bharathi Kshirsagar, Pravin R. Rajaram, A. Tirth, Vineet Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore India Department of Engineering - Electrical Section University of Technology and Applied Sciences Shinas Campus Sultanate of Oman Department of Electronics and Communication Engineering SRM Institute of Science and Technology Chennai India Department of Signal and Image Processing With Computational Intelligence Saveetha School of Engineering Chennai India Department of Electricals and Electronics Engineering Sathyabama Institute of Science and Technology Chennai India Department of Artificial Intelligence G H Raisoni College of Engineering Nagpur India Department of Electronics and Communication Engineering EGS Pillay Engineering College Nagapattinam India Department of Mechanical Engineering College of Engineering King Khalid University Abha Kingdom of Saudi Arabia

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Development and Sensitivity Analysis of Mwcnts Coated D-Shaped Plastic Optical Fiber Sensor for the Detection of Mercury

SSRN

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SSRN 2024年

作者： Khan, Abdul Ali Thirunavakkarasu, Punithavathi M. Noor, Ahmad Shukri Muhammad Saidin, Norazlina Bte Waqas, Nawaf Communication Technology Section Universiti Kuala Lumpur British Malaysian Institute Bt. 8 Jalan Sungai Pusu Selangor Gombak53100 Malaysia Faculty of I.C.T BUITEMS Quetta87100 Pakistan Department of Computer and Communication Systems Engineering Faculty of Engineering Universiti Putra Malaysia Selangor Malaysia Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia

Heavy metal pollutants in rivers and water catchments are one of the problems faced by many developing countries as they may result in health issues among their people. A proper sensing mechanism is required to ensure the quality of water. In this research, we propose a simple, low cost, and highly sensitive D-shaped plastic optical fiber (POF) sensor layered with functionalized multi-walled carbon nanotubes (MWCNTs) for the detection of mercury in water. The sensor underwent interrogation across a range of mercury concentrations at room temperature. Numerous methods of characterization have been employed to explore the intricate structural attributes of the sensing layer to verify that the nanocomposite surface layer is functionalized with minimal disruption to the nanotubes. The experimental results revealed that the coated sensor displayed swift response and recovery time of 6.3 s and 13 s respectively when tested with the dynamic mercury concentration range (0 to 5 ppm). Moreover, it exhibited a relative absorbance of 7.33%/ppm, which is approximately four times higher than the plain sensor and a limit of detection of 0.1 ppm. The sensor has the potential to be transformed into an on-site, portable, real-time optical sensor for the detection of mercury ions in drinking water, offering high sensitivity and fast data acquisition. © 2024, The Authors. All rights reserved.

关键词： Potable water

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Atomic physics-inspired atom search optimization heuristics integrated with chaotic maps for identification of electro-hydraulic actuator systems

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Modern Physics Letters B 2024年第30期38卷

作者： Mehmood, Khizer Chaudhary, Naveed Ishtiaq Khan, Zeshan Aslam Cheema, Khalid Mehmood Zahoor Raja, Muhammad Asif Department of Electrical and Computer Engineering International Islamic University Islamabad 44000 Pakistan Future Technology Research Center National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin 64002 Taiwan Department of Electronic Engineering Fatima Jinnah Women University Rawalpindi 46000 Pakistan

Electro-hydraulic actuator system (EHAS) has imposed a challenge in the research community for accurate mathematical modeling and identification due to non-linearities. In this paper, autoregressive exogenous (ARX) structure is used for EHAS modeling and identification is performed by exploiting the competency of atomic physics-based chaotic atom search optimization (CASO) that adapts ten chaotic maps (Chebyshev, Circle, Gauss, Iterative, Logistic, Piecewise, Sine, Singer, Sinusoidal and Tent) in position update of atom search optimization (ASO). The fitness/merit function of the EHAS model is developed in mean-square error (MSE) sense between desired and approximated values. Simulations and analysis show that ASO with a chaotic logistic map (CASO5) performs better than the ASO and its other chaotic variants, as well as other recently introduced metaheuristics for diverse variations in the system model. Statistics based on MSE, learning plots, results of autonomous trials and average fitness analyses verify the consistency and reliability of the CASO5 for the identification of the EHAS model. © 2024 World Scientific Publishing Company.

关键词： ARX model Atom search optimization chaotic maps electro-hydraulic actuator system

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Research on underwater biological detection method based on multi-scale fusion and attention mechanism 22

Research on underwater biological detection method based on ...

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Proceedings of the 2022 4th International Conference on Robotics, Intelligent Control and Artificial Intelligence

作者： Longyu Tang Yunong Yang Hong Wang College of Computer and Information Science Chongqing Normal University China Digital Education Engineering Center for Technology and Applied Research Chongqing Normal University China Modern Education Operation Section Chongqing Normal University China

ISBN: (纸本)9781450398343

Underwater robots are an important tool for exploiting marine resources, while underwater target detection is a key technology for marine fishing by underwater robots. For the problem that the traditional algorithm is difficult to detect small targets and multiple scales in the underwater environment, this paper proposes an underwater biological detection algorithm based on the multi-scale feature fusion and attention mechanism. First, a YOLOv5 network is constructed, and a bi-directionally weighted BiFPN feature pyramid structure is fed into the neck network so that multiscale target features can be efficiently merged. Second, a channel and spatial convolutional attention mechanism is introduced between the neck network and the prediction network in order to increase the saliency of the underwater target that needs to be detected, which effectively reduces the missed and erroneous detection of underwater targets. The experimental results show that the proposed algorithm can accurately detect multi-scale underwater targets in complex underwater environments with an average accuracy of 80.18%, which is 2.87% better than YOLOv5, and an average recall of 85.06%, which is 4.81% better than YOLOv5.

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Non-monolithic fabrication of thin-film microelectrode arrays on PMUT transducers as a bimodal neuroscientific investigation tool*

Non-monolithic fabrication of thin-film microelectrode array...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Andrada I. Velea Joshua Wilson Astrid Gollhardt Cyril B. Karuthedath Abhilash S. Thanniyil Vasiliki Giagka Bioelectronics Section Dept. of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology the Netherlands Fraunhofer Institute for Reliability and Microintegration IZM VTT Technical Research Centre of Finland Ltd.

Ultrasound (US)-based neuromodulation has recently emerged as a spatially selective yet non-invasive alternative to conventional electrically-based neural interfaces. However, the fundamental mechanisms of US neuromodulation are not yet clarified. Thus, there is a need for in-vitro bimodal investigation tools that allow us to compare the effect of US versus electrically-induced neural activity in the vicinity of the transducing element. To this end, we propose a MicroElectrode-MicroTransducer Array (MEMTA), where a dense array of electrodes is co-fabricated on top of a similarly dense array of US *** this paper, we test the proof of concept for such co-fabrication using a non-monolithic approach, where, at its most challenging scenario, desired topologies require electrodes to be formed directly on top of fragile piezoelectric micromachined ultrasound transducer (PMUTs) membranes. On top of the PMUTs, a thin-film microelectrode array was developed utilizing microfabrication processes, including metal sputtering, lithography, etching and soft encapsulation. The samples were analysed through focused ion beam–scanning electron microscopy (FIB-SEM), and the results have shown that damage to the membranes does not occur during any of the process steps. This paper proves that the non-monolithic development of a miniaturised bimodal neuroscientific investigation tool can be achieved, thus, opening up a series of possibilities for further understanding and investigation of the nervous system.

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Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond

arXiv

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arXiv 2024年

作者： Wang, Zhiyuan Duan, Jinhao Yuan, Chenxi Chen, Qingyu Chen, Tianlong Zhang, Yue Wang, Ren Shi, Xiaoshuang Xu, Kaidi Center for Future Media School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu611731 China Department of Computer Science Drexel University PhiladelphiaPA19104 United States Perelman School of Medicine University of Pennsylvania PhiladelphiaPA19104 United States Section of Biomedical Informatics & Data Science Yale School of Medicine Yale University New HavenCT06510 United States Computer Science & Artificial Intelligence Laboratory Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical and Computer Engineering Illinois Institute of Technology ChicagoIL60616 United States

Uncertainty estimation is crucial for the reliability of safety-critical human and artificial intelligence (AI) interaction systems, particularly in the domain of healthcare engineering. However, a robust and general uncertainty measure for free-form answers has not been well-established in open-ended medical question-answering (QA) tasks, where generative inequality introduces a large number of irrelevant words and sequences within the generated set for uncertainty quantification (UQ), which can lead to biases. This paper introduces Word-Sequence Entropy (WSE), a method that calibrates uncertainty at both the word and sequence levels, considering semantic relevance. WSE quantifies uncertainty in a way that is more closely aligned with the reliability of LLMs during uncertainty quantification (UQ). We compare WSE with six baseline methods on five free-form medical QA datasets, utilizing seven popular large language models (LLMs). Experimental results demonstrate that WSE exhibits superior performance in UQ under two standard criteria for correctness evaluation. Additionally, in terms of real-world medical QA applications, the performance of LLMs is significantly enhanced (e.g., a 6.36% improvement in model accuracy on the COVID-QA dataset) by employing responses with lower uncertainty that are identified by WSE as final answers, without any additional task-specific fine-tuning or architectural modifications. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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