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AI-optimized electrochemical aptasensors for stable, reproducible detection of neurodegenerative diseases, cancer, and coronavirus

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Heliyon 2025年第1期11卷 e41338页

作者： Tayfour Ahmed, Amira Elsir Dhahi, Th.S. Attia, Tahani A. Elhassan Ali, Fawzia Awad Elobaid, Mohamed Elshaikh Adam, Tijjani Gopinath, Subash C.B. Department of Information System College of Science & Arts King Khalid University Asser Mohyel Saudi Arabia Health and Medical Technicals College Southern Technical University Basrah Iraq Department of Computer Engineering College of Computer Science and Engineering University of Ha'il Saudi Arabia DEEE Faculty of Engineering University of Khartoum Sudan Imam Abdulrahman Bin Faisal University Applied College Computer Department Saudi Arabia Faculty of Electronic Engineering & Technology Universiti Malaysia Perlis Perlis Arau 02600 Malaysia Institute of Nano Electronic Engineering Universiti Malaysia Perlis Perlis Kangar 01000 Malaysia Micro System Technology Centre of Excellence (CoE) Universiti Malaysia Perlis (UniMAP) Perlis Malaysia Center for Global Health Research Saveetha Medical College & Hospital Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Tamil Nadu Chennai 602 105 India Faculty of Chemical Engineering & Technology Universiti Malaysia Perlis (UniMAP) Perlis Arau 02600 Malaysia

AI-optimized electrochemical aptasensors are transforming diagnostic testing by offering high sensitivity, selectivity, and rapid response times. Leveraging data-driven AI techniques, these sensors provide a non-invasive, cost-effective alternative to traditional methods, with applications in detecting molecular biomarkers for neurodegenerative diseases, cancer, and coronavirus. The performance metrics outlined in the comparative table illustrate the significant advancements enabled by AI integration. Sensitivity increases from 60 to 75 % in ordinary aptasensors to 85–95 %, while specificity improves from 70-80 % to 90–98 %. This enhanced performance allows for ultra-low detection limits, such as 10 fM for carcinoembryonic antigen (CEA) and 20 fM for mucin-1 (MUC1) using Electrochemical Impedance Spectroscopy (EIS), and 1 pM for prostate-specific antigen (PSA) with Differential Pulse Voltammetry (DPV). Similarly, Square Wave Voltammetry (SWV) and potentiometric sensors have detected alpha-fetoprotein (AFP) at 5 fM and epithelial cell adhesion molecule (EpCAM) at 100 fM, respectively. AI integration also enhances reproducibility, reduces false positives and negatives (from 15-20 % to 5–10 %), and significantly decreases response times (from 10-15 s to 2–3 s). These advancements improve data processing speeds (from 10 to 20 min per sample to 2–5 min) and calibration accuracy (<2 % margin of error compared to 5–10 %), while expanding application scope to multi-target biomarker detection. This review highlights how these advancements position AI-optimized electrochemical aptasensors as powerful tools for personalized treatment, point-of-care testing, and continuous health monitoring. Despite a higher cost ($500-$1,500/unit), their enhanced portability and diagnostic performance promise to revolutionize healthcare, environmental monitoring, and food safety, ultimately improving public health outcomes. © 2024

关键词： AI Aptasensors Cancer Coronavirus Electrochemical Integrated biosensor Molecular cells Neurodegenerative

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Cellular neural networks with multiple-valued output and its application

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND computer scienceS 1996年第10期E79A卷 1658-1663页

作者： Kanagawa, A Kawabata, H Takahashi, H Faculty of Computer Science and System Engineering Okayama Prefectural University Soja-shi 719-11 Japan

Various applications of cellular neural network (CNN) are reported such as a feature extraction of the patterns, an extraction of the edges or corners of a figure, noise exclusion, searching in maze and so forth. In this paper, we propose a cellular neural network whose each cell has more than two output levels. By using the output function which has several saturated levels, each cell turns to have several output states. The multiple-valued CNN enhances its associative memory function so as to express various kinds of aspects. We report an application of the enhanced associative memory function to a diagnosis of the liver troubles.

关键词： cellular neural network associative memory classification problem

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SOA-based framework for home and building automation systems (HBAS)

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International Journal of Smart Home 2014年第5期8卷 197-206页

作者： Perumal, Thinagaran Ramli, Abd Rahman Leong, Chui Yew Department of Computer Science Faculty of Computer Science and Information Technology Universiti Putra Malaysia Malaysia Department of Computer and Communication System Engineering Faculty of Engineering Universiti Putra Malaysia Malaysia

Home and building automation systems (HBAS) today are categorized by plethora of data formats, communication platforms and software services accessible via heterogeneous embedded devices. These heterogeneous embedded devices characterized a building into a data intensive entity, generating numerous data and complex control information, brings a much heavy load to the HBAS. Consequently, this leads to interoperation difficulties among those devices for information exchange and operation management. In this paper, a Service Oriented Architecture (SOA) based framework that leveraged by services is proposed to manage HBAS efficiently by reducing their workload during joint execution of tasks. The proposed framework consists of several layers dedicated for services interwoven by Event-Condition-Action (ECA) oriented decision mechanism for managing heterogeneous embedded devices. The proposed framework is viable and highly efficient to be deployed for HBAS with limited computing resources. © 2014 SERSC.

关键词： Interoperability

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Implicit representation and manipulation of binary decision diagrams

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND computer scienceS 1996年第3期E79A卷 354-362页

作者： Yamauchi, H Ishiura, N Takahashi, H Faculty of Computer Science and System Engineering Okayama Prefectural University Soja-shi 719-11 Japan Faculty of Information System Engineering Osaka University Suita-shi 565 Japan

This paper presents implicit representation of binary decision diagrams (implicit BDDs) as a new efficient data structure for Boolean functions. A well-known method of representing graphs by binary decision diagrams (BDDs) is applied to BDDs themselves. Namely, it is a BDD representation of BDDs. Regularity in the structure of BDDs representing certain Boolean functions contributes to significant reduction in size of the resulting implicit BDD representation. Since the implicit BDDs also provide canonical forms for Boolean functions, the equivalence of the two implicit BDD forms is decided in time proportional to the representation size. We also show an algorithm to manipulate Boolean functions on this implicit data structure.

关键词： binary decision diagram (BDD) representation of Boolean functions logic design verification logic synthesis implicit representation of graphs

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KERR-EFFECT-INDUCED S-R FLIP-FLOP OPERATION IN AN OPTICAL-FIBER LOOP RESONATOR WITH DOUBLE COUPLERS

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OPTICS LETTERS 1995年第10期20卷 1119-1121页

作者： FUKUSHIMA, T SAKAMOTO, T []Department of System Engineering Faculty of Computer Science System Engineering Okayama Prefectural University 111 Kuboki Soja Okayama 719-11 Japan

We carry out a theoretical analysis of Kerr bistability in a double-coupler optical fiber loop resonator in a case of two coexisting input optical fields, and we propose a set-reset (S-R) flip-flop operation that uses two input ports. We found that in the optimum case set and reset operation can be achieved at relatively low optical input powers.

关键词： Optical fibers Optical fields Optical resonators Phase shift Refractive index Ring resonators

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ANALYSIS OF SINGULAR STRESS-FIELD AROUND THE INCLUSION CORNER TIP

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engineering FRACTURE MECHANICS 1994年第4期49卷 533-546页

作者： CHEN, DH Faculty of Computer Science and System Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka 820 Japan

The plane problem of an infinite plate containing an inclusion is considered. The singular stress field around the inclusion corner tip is expressed as a sum of two independent types: a symmetric type with a stress singularity 1/r(I-lambda1) and a skew-symmetric type with a stress singularity 1/r(I-lambda2). The intensities of the symmetric and skew-symmetric singular stress fields are defined in terms of constants K(I,lambda1) and K(II,lambda2), respectively. The body force method is used to calculate the values of K(I,lambda1) and K(II,lambda2). In numerical analysis, basic density functions of the body forces are introduced to characterize the stress singularity at the inclusion corner. The advantages of this technique are the high accuracy of results, due to the smoothness of the unknown weight functions, and the presence of the direct relation between the values of K(I,lambda1), K(II,lambda2) and the values of unknown weight functions at the corner tip.

关键词： Stress analysis

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An Embodied Interaction Robots system Based on Speech

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Journal of Robotics and Mechatronics 2000年第2期12卷 126-134页

作者： Watanabe, Tomio Okubo, Masashi Ogawa, Hiroki Department of System Engineering Faculty of Computer Science and System Engineering Okayama Prefectural University 111 Kuboki Soja Okayama719-1197 Japan

The concept of an embodied interaction robots system based on speech is proposed for assisting human interaction by generating the motions of robots coherently related to speech. For an essential human interaction model which estimates a listener’s nodding on the basis of a speaker’s burst-pause of speech, the validity of a moving-average (MA) model is demonstrated in the robustness of prediction. Then, the prototype of the proposed system which consists of 2 interaction robots with both functions of speaker and listener is developed in which two models are incorporated: one is a listener’s reaction model in which nodding, blinking and the motions of head, arms and body are estimated by the MA model of the burst-pause of speech to the nodding: the other is a speaker’s bodily reaction model in which the motions of head, arms and body are estimated by its own MA model of the burst-pause of speech to the head motion. By the sensory evaluation and behavioral analysis in human-robot interaction, the effectiveness of the robot’s bodily interaction is demonstrated. The effectiveness of the embodied interaction robots system is also confirmed in remote communication. © 2000, Fuji Technology Press. All rights reserved.

关键词： Sensory analysis

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Development of an embedded smart home management scheme

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International Journal of Smart Home 2013年第2期7卷 15-26页

作者： Perumal, Thinagaran Sulaiman, Nasir Md Sharif, Khaironi Yatim Ramli, Abd Rahman Leong, Chui Yew Department of Computer Science Faculty of Computer Science and Information Technology UPM Serdang Malaysia Department of Computer and Communication System Engineering UPM Serdang Malaysia

This paper describes the development of an embedded smart home management scheme over the Ethernet network. The platform of the smart home management system is built using bespoke embedded system design. An embedded control module developed by exploiting the Web Services mechanism, consist of 15 monitoring channels based on XML SOAP standards. Each channel is integrated to dedicated smart home management scheme and performs bi-directional real-time control. In the event of server unavailability, a mobile based communication module using GSM has been deployed as an alternate management mechanism. The proposed embedded-enabled solution offers bi-directional real-time management as well as optimized performance for smart home environment.

关键词： Interoperability

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Studying of Machine Learning Models for Forecasting Macroeconomic Indicators

Studying of Machine Learning Models for Forecasting Macroeco...

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International Conference on Advanced Communication Technology (ICACT)

作者： Lan Dong Thi Ngoc Ngo-Thi-Thu-Trang Kyoung-Mok Kim Vung Pham Ha-Nam Nguyen Department of Economic Information System Academy of Finance Hanoi Viet Nam Faculty of Information Technology University of Engineering and Technology Vietnam National University Hanoi Viet Nam Posts and Telecommunications Institute of Technology Hanoi CO Vietnam Department of Medical Information Sahmyook Health University Seoul Republic of Korea Computer Science Department Sam Houston State University Huntsville Texas TX USA Faculty of Information Technology Electric Power University Hanoi Viet Nam

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

This study explores the application of machine learning models in forecasting macro-economic indicators, including GDP, inflation rate, unemployment rate, and exchange rate across 11 Southeast Asian countries. The models used include Linear Regression, ARIMA, Random Forest, XGBoost, LSTM, and SVM. We conducted a performance comparison of each model based on MAE, RMSE, and R 2 metrics to evaluate the accuracy of the *** experimental results indicate that Random Forest and XGBoost models excel in predicting nonlinear and complex indicators such as GDP and unemployment rate, while ARIMA and Linear Regression models perform better in time series with clear regular patterns, like inflation rate. The LSTM model shows inconsistent effective-ness, requiring large data volumes and complex optimization processes. SVM demonstrates potential in handling nonlinear data but requires careful *** study concludes that using machine learning models presents significant potential for improving the accuracy of macroeconomic forecasting. However, model tuning and optimization are essential to match the characteristics of each type of economic indicator. Future research directions include developing hybrid models and integrating additional factors such as market sentiment, social and environmental indicators (ESG) to enhance forecasting outcomes.

关键词： Support vector machines Economic indicators Biological system modeling Predictive models Macroeconomics Forecasting Unemployment Random forests Optimization Long short term memory

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Protocol for the fabrication of self-standing (nano)cellulose-based 3D scaffolds for tissue engineering

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STAR Protocols 2025年第1期6卷 103583页

作者： Mohan, Tamilselvan Bračič, Matej Bračič, Doris Lackner, Florian Nagaraj, Chandran Štiglic, Andreja Dobaj Kargl, Rupert Kleinschek, Karin Stana Graz University of Technology Institute for Chemistry and Technology of Biobased System (IBioSys) Stremayrgasse 9 Graz 8010 Austria University of Maribor Faculty of Mechanical Engineering Laboratory for Characterization and Processing of Polymers Smetanova Ulica 17 Maribor 2000 Slovenia Department of Internal Medicine Division of Pulmonology Medical University of Graz Graz Austria Institute of Automation Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Members of the European Polysaccharide Network of Excellence (EPNOE) Austria

Three-dimensional (3D) and porous scaffolds made from nanocellulosic materials hold significant potential in tissue engineering (TE). Here, we present a protocol for fabricating self-standing (nano)cellulose-based 3D scaffolds designed for in vitro testing of cells from skin and cartilage tissues. We describe steps for preparation of nanocellulose ink, scaffold formation using 3D printing, and freeze-drying. We then detail post-processing procedures to enhance mechanical properties, stability, and biocompatibility. This protocol offers researchers a framework for developing versatile and sustainable biomaterials for regenerative medicine. For complete details on the use and execution of this protocol, please refer to Mohan et al.¹ and Štiglic et al.² © 2025 The Authors

关键词： Biotechnology and bioengineering Chemistry Material sciences Tissue engineering

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