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Detection of SARS-CoV-2 based on artificial intelligence-assisted smartphone:A review

Chinese Chemical Letters 2024年第7期35卷 25-34页

作者： Yunxin Li Jinghui Zhang Jisen Chen Feng Zhu Zhiqiang Liu Peng Bao Wei Shen Sheng Tang School of Environmental and Chemical Engineering Jiangsu University of Science and TechnologyZhenjiang 212003China Programme in Emerging Infectious Diseases Duke-NUS Medical SchoolSingapore 169857Singapore

In recent years,the application of smartphone in various fields has received great attention,and it has become a promising tool in virus detection,data processing and data *** the rapid spread of COVID-19 around the world,many traditional detection methods have been combined with smartphone to assist in the analysis and detection of the novel coronavirus(SARS-CoV-2),including electrochemistry,fluorescence and *** the gradual development of artificial intelligence(AI),the combination of AI and smartphone to analyze SARS-CoV-2 was also the focus of *** on the summary of the traditional methods combined with smartphone to detect SARS-CoV-2 virus,in addition to AI-based data processing,AI algorithms are also employed for SARS-CoV-2 detection *** review discussed both strategies and focused on the application of the *** combination of AI algorithm and smartphone to detect SARS-CoV-2 has high accuracy,which is more conducive to meeting the needs of portable *** addition,the classification of SARS-CoV-2 virus samples in biological fluids such as blood and saliva was also ***,this paper briefly discussed the limitations of using smartphone analysis to detect SARS-CoV-2,as well as the prospect and future development of virus *** conclusion,the detection methods based on smartphone and AI algorithms show great potential in the detection of SARS-CoV-2 and can be a valuable complement to traditional analysis methods.

关键词： COVID-19 SARS-CoV-2 virus Detection method Smartphone analysis Artificial intelligence

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Hepatitis B time series in Xinjiang, China (2006–2021): change point detection based on the Mann-Kendall-Sneyers test

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Mathematical Biosciences and engineering 2024年第2期21卷 2458-2469页

作者： Yang, Liping Xie, Na Yao, Yanru Wang, Chunxia Tian, Maozai Wang, Kai College of Public Health Xinjiang Medical University Urumqi830017 China Department of Immunization Programme Xinjiang Center for Disease Control and Prevention Urumqi830054 China College of Science Shihezi University Shihezi832000 China College of Medical Engineering and Technology Xinjiang Medical University Urumqi830017 China

Hepatitis B is a major global challenge, but there is a lack of epidemiological research on hepatitis B incidence from a change point perspective. This study aimed to fill this gap by identifying significant change points and trends in hepatitis time series in Xinjiang, China. The datasets were obtained from the Xinjiang Information System for Disease Control and Prevention. The Mann-Kendall-Sneyers (MKS) test was used to detect change points and trend changes on the hepatitis B time series of 14 regions in Xinjiang, and the effectiveness of this method was validated by comparing it with the binary segmentation (BS) and segment regression (SR) methods. Based on the results of change point analysis, the prevention and control policies and measures of hepatitis in Xinjiang were discussed. The results showed that 8 regions (57.1%) with at least one change fell within the 95% confidence interval (CI) in all 14 regions by the MKS test, where five regions (Turpan (TP), Hami (HM), Bayingolin (BG), Kyzylsu Kirgiz (KK), Altai (AT)) were identified at one change point, two change points existed for two regions (Aksu (AK), Hotan (HT)) and three change points was detected in 1 region (Bortala (BT)). Most of the change points occurred at both ends of the sequence. More change points indicated an upward trend in the front half of the sequence, while in the latter half, many change points indicated a downward trend prominently. Finally, in comparing the results of the three change point tests, the MKS test showed a 61.5% agreement (8/13) with the BS and SR. © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://***/licenses/by/4.0)

关键词： Time series

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Mobile Application based Indoor Positioning and Navigational System using Dijkstra's Algorithm 4

Mobile Application based Indoor Positioning and Navigational...

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4th National Conference on Communication Systems, NCOCS 2022

作者： Deiva Nayagam, R. Selvathi, D. Geeta, R. Gopinath, D. Sivakumar, G. Department of ECE Ramco Institute of Technology Tamilnadu Rajapalayam626117 India Bio Medical Engineering Programme Mepco Schlenk Engineering College Sivakasi India Department of ECE Chennai Institute of Technology Chennai India

This paper offers a method for developing an efficient indoor navigation system with the consideration of the shortest path between source and destination. The challenge for the indoor navigation system is to provide personal navigation information and the optimal route. Applications of indoor navigation systems need consideration of the Shortest Path problem. The shortest pathways can be used to find solutions to the current problems using Dijkstra's algorithm. Based on the issue with the indoor navigation system, the shortest way and the best path are calculated. This is crucial to navigation systems since it can aid in making wise decisions and time-saving choices. The primary goal is to obtain the implementation at an affordable price. These applications and services are made available indoors, where the GPS does not function. The goal of indoor navigation is to direct users inside buildings. Dijkstra's algorithm for locating objects and for moving along the shortest path in an indoor setting are examined in this work. Experimental results of indoor navigation systems were carried out on my organization's indoor environment and verified the applicability of the presented Indoor Navigation System. The techniques provided include map digitization, locating a user, and choosing the shortest route. This is accomplished through a mobile application created for the Android operating system, and indoor navigation is carried out by using Dijkstra's algorithm. The proposed method is implemented in our college academic block, and the experimental results show that our navigation method is feasible and effective. To verify the reliability of the algorithm, the proposed application fulfils the criteria of an indoor navigation system to produce the optimal route between two points when applied to a map of our college's indoor terrain. © Published under licence by IOP Publishing Ltd.

关键词： Navigation systems

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Validation of the Efficacy of Ultrasound Speckle Tracking in Measuring Tendon Gliding After Finger Flexor Tendon Repair

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Ultrasound in Medicine and Biology 2023年第12期49卷 2548-2556页

作者： Wang, Ming-Wei Lee, Wei-Ning Hung, Chih-Chien Hsieh, Jung-Hsien Chen, Yueh-Hsia Ting-Fang Shih, Tiffany Wang, Jyh-Horng Yin, Nai-Hao Wang, Hsing-Kuo School and Graduate Institute of Physical Therapy College of Medicine National Taiwan University Taipei Taiwan Center of Physical Therapy National Taiwan University Hospital Taipei Taiwan Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong Medical Engineering Programme University of Hong Kong Hong Kong Department of Orthopedic Surgery National Taiwan University Hospital Yun-Lin Branch Yun-Lin Taiwan Division of Plastic Surgery Department of Surgery Medical College and Hospital National Taiwan University Taipei Taiwan Department of Medical Imaging and Radiology Medical College and Hospital National Taiwan University Taipei Taiwan Department of Orthopedic Surgery Medical College and Hospital National Taiwan University Taipei Taiwan Centre for Human and Applied Physiological Sciences School of Basic and Biomedical Sciences King's College London London United Kingdom

Objective: Restricted tendon gliding is commonly observed in patients after finger flexor tendon (FFT) repair. The study described here was aimed at quantifying the amount of FFT gliding to evaluate the recovery of post-operative tendons using a 2-D radiofrequency (RF)-based ultrasound speckle tracking algorithm (UST). Methods: Ex vivo uniaxial tensile testing of porcine flexor tendons and in vivo isometric testing of human FFT were implemented to verify the efficacy of UST beforehand. The verified UST was then applied to the patients after FFT repair to compare tendon gliding between affected and healthy sides and to investigate its correlation with the joint range of motion (ROM). Results: Excellent validity was confirmed with the average R2 value of 0.98, mean absolute error of 0.15 ± 0.08 mm and mean absolute percentage error of 5.19 ± 2.43% between results from UST and ex vivo testing. The test–retest reliability was verified with good agreement of ICC (0.90). The affected side exhibited less gliding (p = 0.001) and smaller active ROM (p = 0.002) than the healthy side. Meanwhile, a significant correlation between tendon gliding and passive ROM was found only on the healthy side (ρ = 0.711, p = 0.009). Conclusion: The present study provides a promising protocol to evaluate post-operative tendon recovery by quantifying the amount of FFT gliding with a validated UST. FFT gliding in patients with different levels of ROM restriction should be further explored for categorizing the severity of tendon adhesion. © 2023 World Federation for Ultrasound in Medicine & Biology

关键词： Adhesion

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Extracellular matrix and biomimetic engineering microenvironment for neuronal differentiation

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Neural Regeneration Research 2020年第4期15卷 573-585页

作者： Deepak Jain Sabrina Mattiassi Eyleen L.Goh Evelyn K.F.Yim Department of Chemical Engineering University of WaterlooWaterlooOntarioCanada Neuroscience Academic Clinical Programme Duke-NUS Medical SchoolSingapore

Extracellular matrix(ECM)influences cell differentiation through its structural and biochemical *** nervous system,neuronal behavior is influenced by these ECMs structures which are present in a meshwork,fibrous,or tubular forms encompassing specific molecular *** addition to contact guidance,ECM composition and structures also exert its effect on neuronal *** short report reviewed the native ECM structure and composition in central nervous system and peripheral nervous system,and their impact on neural regeneration and neuronal *** topographies,stem cells have been differentiated to ***,focussing on engineered biomimicking topographies,we highlighted the role of anisotropic topographies in stem cell differentiation to neurons and its recent temporal application for efficient neuronal differentiation.

关键词： biomimetic platforms biophysical cues contact guidance extracellular matrix neuronal development neural regeneration neural stem cell niche neuronal differentiation neuronal maturation stem cell topography

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The effect of polyvinylpyrrolidone-coated (PVP) on bismuth-based nanoparticles cell cytotoxicity

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Materials Today: Proceedings 2022年 66卷 2948-2951页

作者： Jamil, Amirah Geso, Moshi Algethami, Merfat Wan Sohaimi, Wan Fatihah Abdul Razak, Khairunisak Rahman, Wan Nordiana Medical Radiation Programme School of Health Sciences Health Campus Universiti Sains Malaysia Kubang Kerian Kelantan Malaysia Division of Medical Radiation School of Health and Biomedical Sciences RMIT University Bundoora VIC Australia Physics Department Faculty of Science Taif University Taif Saudi Arabia Department of Nuclear Medicine and Oncology Hospital Universiti Sains Malaysia Kubang Kerian Kelantan Malaysia School of Materials and Mineral Resources Engineering Engineering Campus Universiti Sains Malaysia Nibong Tebal Penang Malaysia

Cancer statistics display high malignant breast cancer cases every year due to its aggressive growth rate. The emergence of nanomedicines has helped tremendously eradicate cancer, starting with diagnosis, therapy, intensive analysis, and further interventions. Bismuth-based nanoparticles are one of the various metal nanoparticles used as radiosensitizers to increase cancer tissue sensitivity when irradiated in radiotherapy treatment. In-vitro cytotoxicity assay is mandatory to ensure that the nanoparticles do not induce lethal toxicity to the cells before being deemed suitable for clinical use. The research aims to investigate the cytotoxicity effect of polyvinylpyrrolidone-coated-coated (PVP) bismuth nanoparticles on the MCF-7 cancer cell line. Uncoated bismuth nanoparticles (BiNPs) and PVP-coated bismuth sulphide nanoparticles (Bi2S3-PVP 8000 and Bi2S3-PVP 29000) within the range of 0.00005 to 0.5 mMol/L were tested on MCF-7 cancer cell lines for 24, 48, and 72 h. The cytotoxicity assay results indicate the uncoated bismuth nanoparticles have minimal toxicity on MCF-7 treated with BiNPs across 24 to 72 h of incubation compared to PVP-coated counterparts. Reduction of cell viability within 1.6 – 11.3% is observed during 48 h post-treatment of BiNPs with different concentrations, with a slight improvement of viability after 72 h. However, Bi2S3-PVP 8000 and Bi2S3-PVP 29000 exhibit non-toxic effects on cells yet induced abnormally high cell proliferation levels up to 5.4 folds for Bi2S3-PVP 8000 and 5.9 folds for Bi2S3-PVP 29000 compared to their control groups. The unwanted proliferation is counterproductive as the nanoparticles must withhold the growth of cancer cells besides increasing the radiosensitivity when irradiated. The results concluded that MCF-7 cell viability and cell proliferation are concentration-dependent when using PVP as bismuth nanoparticles coating. Further study is needed to investigate the PVP-coated bismuth nanoparticles effect on different t

关键词： Coatings

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Elucidating of the metabolic impact of risperidone on brain microvascular endothelial cells using untargeted metabolomics-based LC-MS

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Toxicology Reports 2024年 13卷 101691页

作者： Ngamratanapaiboon, Surachai Srikornvit, Napatarin Hongthawonsiri, Patipol Pornchokchai, Krittaboon Wongpitoonmanachai, Siriphattarinya Mo, Jiajun Pholkla, Petchlada Yambangyang, Pracha Duchda, Phichanan Lohwacharin, Jenyuk Ayutthaya, Watcharaporn Devakul Na Division of Pharmacology Department of Basic Medical Sciences Faculty of Medicine Vajira Hospital Navamindradhiraj University Medical Student in Doctor of Medicine Programme Faculty of Medicine Vajira Hospital Navamindradhiraj University Department of Biomedical Engineering Faculty of Engineering Mahidol University Department of Environmental Engineering Faculty of Engineering Chulalongkorn University Professor Aroon Sorathesn Center of Excellence in Environmental Engineering Department of Environmental Engineering Faculty of Engineering Chulalongkorn University

Risperidone is useful for the treatment of schizophrenia symptoms;however, it also has side effects, and an overdose can be harmful. The metabolic effects of risperidone at high therapeutic doses and its metabolites have not been elucidated. Endogenous cellular metabolites may be comprehensively analyzed using untargeted metabolomics-based liquid chromatography-mass spectrometry (LC-MS), which can reveal changes in cell regulation and metabolic pathways. By identifying the metabolites and pathway changes using a nontargeted metabolomics-based LC-MS approach, we aimed to shed light on the potential toxicological effects of high-dose risperidone on brain microvascular endothelial cells (MVECs) associated with the human blood brain barrier. A total of 42 metabolites were selected as significant putative metabolites of the toxicological response of high-dose risperidone in MVECs. Six highly correlated pathways were identified, including those involving diacylglycerol, fatty acid, ceramide, glycerophospholipid, amino acid, and tricarboxylic acid metabolism. We demonstrated that methods focused on metabolomics are useful for identifying metabolites that may be used to clarify the mechanism of drug-induced toxicity. © 2024 The Authors

关键词： Brain microvascular endothelial cells Liquid chromatography-mass spectrometry Risperidone Untargeted metabolomics

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A Two-stage Anomaly Detection System for Fog Computing Services

A Two-stage Anomaly Detection System for Fog Computing Servi...

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IEEE International Conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Sunday Oyinlola Ogundoyin Ismaila Adeniyi Kamil Isaac Adewale Ojedokun John Oluwaseun Babalola Vincent Omollo Nyangaresi Electrical and Electronic Engineering Programme Bowen University Iwo Nigeria Department of Electrical and Electronic Engineering University of Ibadan Ibadan Nigeria Department of Computer Science and Software Engineering Jaramogi Oginga Odinga University of Science and Technology Bando Kenya Department of Applied Electronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

Fog computing enhances traditional cloud computing by bringing resources closer to edge devices, enabling faster response times and supporting mission-critical applications. However, its distributed nature makes it vulnerable to cyber-attacks like distributed denial-of-service (DDoS), resulting in service disruption and performance degradation. To mitigate this attack, a two-stage anomaly detection system (ADS) is proposed in this paper. The first stage uses AdaBoost (AB) ensemble machine learning to classify events as obstructive or non-obstructive. Obstructive events are offloaded to the cloud where they are classified into normal or specific attack categories using Long Short-term Memory Encoder-Decoder (LSTM-ED). The results demonstrate that the AB-based model achieves exceptional performance, with nearly 100% in accuracy, precision, recall, and a minimal mean squared error (MSE) of 8.34 × 10 −5 . The LSTM-ED model also performs well, with accuracy and MSE at 99.50% and 0.02686, respectively.

关键词： Performance evaluation Cloud computing Accuracy Computational modeling Mission critical systems Machine learning Time factors Long short term memory Anomaly detection Edge computing

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A Two-stage Anomaly Detection System for Fog Computing Services 5

A Two-stage Anomaly Detection System for Fog Computing Servi...

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5th IEEE International Conference on Electro-Computing Technologies for Humanity, NIGERCON 2024

作者： Ogundoyin, Sunday Oyinlola Adeniyi Kamil, Ismaila Ojedokun, Isaac Adewale Babalola, John Oluwaseun Nyangaresi, Vincent Omollo Bowen University Electrical and Electronic Engineering Programme Iwo Nigeria University of Ibadan Department of Electrical and Electronic Engineering Ibadan Nigeria Jaramogi Oginga Odinga University of Science and Technology Department of Computer Science and Software Engineering Bando40601 Kenya Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Applied Electronics Chennai602105 India

ISBN: (纸本)9798331542559

Fog computing enhances traditional cloud computing by bringing resources closer to edge devices, enabling faster response times and supporting mission-critical applications. However, its distributed nature makes it vulnerable to cyber-attacks like distributed denial-of-service (DDoS), resulting in service disruption and performance degradation. To mitigate this attack, a two-stage anomaly detection system (ADS) is proposed in this paper. The first stage uses AdaBoost (AB) ensemble machine learning to classify events as obstructive or non-obstructive. Obstructive events are offloaded to the cloud where they are classified into normal or specific attack categories using Long Short-term Memory Encoder-Decoder (LSTM-ED). The results demonstrate that the AB-based model achieves exceptional performance, with nearly 100% in accuracy, precision, recall, and a minimal mean squared error (MSE) of 8.34 × 10-5. The LSTM-ED model also performs well, with accuracy and MSE at 99.50% and 0.02686, respectively. © 2024 IEEE.

关键词： Fog computing

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Stochastic optimal control and estimation with multiplicative and internal noise 24

Stochastic optimal control and estimation with multiplicativ...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Francesco Damiani Akiyuki Anzai Jan Drugowitsch Gregory C. DeAngelis Rubén Moreno-Bote Center for Brain and Cognition Department of Engineering Pompeu Fabra University Barcelona ES Department of Brain and Cognitive Sciences University of Rochester Rochester Department of Neurobiology Harvard Medical School Boston Center for Brain and Cognition Department of Engineering Serra Húnter Fellow Programme Pompeu Fabra University Barcelona ES

ISBN: (纸本)9798331314385

A pivotal brain computation relies on the ability to sustain perception-action loops. Stochastic optimal control theory offers a mathematical framework to explain these processes at the algorithmic level through optimality principles. However, incorporating a realistic noise model of the sensorimotor system — accounting for multiplicative noise in feedback and motor output, as well as internal noise in estimation — makes the problem challenging. Currently, the algorithm that is commonly used is the one proposed in the seminal study in [1]. After discovering some pitfalls in the original derivation, i.e., unbiased estimation does not hold, we improve the algorithm by proposing an efficient gradient descent-based optimization that minimizes the cost-to-go while only imposing linearity of the control law. The optimal solution is obtained by iteratively propagating in closed form the sufficient statistics to compute the expected cost and then minimizing this cost with respect to the filter and control gains. We demonstrate that this approach results in a significantly lower overall cost than current state-of-the-art solutions, particularly in the presence of internal noise, though the improvement is present in other circumstances as well, with theoretical explanations for this enhanced performance. Providing the optimal control law is key for inverse control inference, especially in explaining behavioral data under rationality assumptions.

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