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Understanding age-related middle ear properties and basilar membrane damage in hearing loss: A finite element analysis and retrospective cohort study

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Computers in Biology and Medicine 2025年 184卷 109376-109376页

作者： Shih, Tzu-Ching Yu, You-Cheng Wang, Tang-Chuan Department of Biomedical Imaging and Radiological Science College of Medicine China Medical University Taichung404328 Taiwan The PhD Program for Medical Engineering and Rehabilitation Science College of Biomedical Engineering China Medical University Taichung404328 Taiwan Master Program for Biomedical Engineering College of Biomedical Engineering China Medical University Taichung404328 Taiwan Department of Otolaryngology-Head and Neck Surgery China Medical University Hsinchu Hospital Zhubei City Hsinchu302056 Taiwan

Age-related hearing loss (ARHL) is primarily attributed to inner-ear factors, yet the role of age-related middle ear characteristics remains elusive. Employing a finite element (FE) model, we conducted a comparative analysis with clinical data extracted from a retrospective cohort study involving 90 younger adults (mean age = 38.1 ± 7.7) and 111 older adults (mean age = 63.8 ± 8.4). The clinical dataset encompassed air-bone gap (ABG) measurements obtained through pure-tone audiometry (PTA) at frequencies of 0.5, 1.0, 2.0, and 4.0 kHz. FE results quantified the normalized stapes displacement value of the simulated form of air-bone gap (ABGSim) between the two age groups. The Mann-Whitney U test, with a significance threshold set at P © 2024

关键词： Bone

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Test of Galileo HAS in Precise Maritime Survey

Test of Galileo HAS in Precise Maritime Survey

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IEEE International Workshop on Metrology for the Sea;Learning to Measure Sea Health Parameters (MetroSea)

作者： Antonio Angrisano Giovanni Cappello Silvio Del Pizzo Salvatore Gaglione Ciro Gioia Gabriele Portelli Salvatore Troisi Department of Engineering Messina University Messina Italy Department of Science and Technology International PhD Programme / UNESCO Chair “!Environment Resources and Sustainable Development” Parthenope University of Naples Naples Italy Department of Science and Technology Parthenope University of Naples Naples Italy

ISBN: (数字)9798350379006

ISBN: (纸本)9798350379013

Nowadays GNSS (Global Navigation Satellite System) plays a fundamental role in various fields such as agriculture, geodetic survey and maritime, air and land navigation. These application fields require different levels of accuracy and precision, leading massive scientific research to deploy dedicated services to satisfy the user requirements. One of the services that attracted the scientific community is the Galileo High Accuracy Service (HAS), that allows to achieve decimeter-level accuracy in real time positioning applications by disseminating orbit, clock, and bias corrections. This study aims to evaluate the grade of accuracy of Galileo HAS in Precise Point Positioning (PPP) mode during a maritime survey, considering only the GPS constellation in kinematic processing mode. The implemented model exploits dual frequency data to create the ionosphere-free linear combination to mitigate the first-order ionospheric delay. Decimeter-level accuracy of the navigation solution has been obtained.

关键词： Surveys Global navigation satellite system Accuracy Sea measurements Prototypes Kinematics Receivers Position measurement Real-time systems Standards

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Systematic designs of single metal compounds synthesized using ammonia fluoride-based complex as structure directing agents for energy storage

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Journal of Colloid and Interface science 2023年第PartA期652卷 294-304页

作者： Kuo, Tsung-Rong Zher Yu, You Wu, Chung-Hsien Lee, Pin-Yan Kongvarhodom, Chutima Chen, Hung-Ming Husain, Sadang Yougbaré, Sibidou Lin, Lu-Yin International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering King Mongkut's University of Technology Thonburi 126 Pracha-u-thit Toong-kru Bangkok10140 Thailand Gingen technology Co. LTD. Rm. 7 10F. No.189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan Department of Physics Faculty of Mathematics and Natural Science Lambung Mangkurat University Banjarmasin70124 Indonesia /Nanoro 03 B.P 7192 Ouagadougou 03 Burkina Faso

Tailoring morphology and composition of metal organic frameworks (MOF) can improve energy storage by establishing high surface area, large porosity and multiple redox states. Structure directing agents (SDA) is functional of designing surface properties of electroactive materials. Ammonium fluoride has functional abilities for designing MOF derivatives with excellent energy storage abilities. Systematic design of MOF derivatives using ammonia fluoride-based complex as SDA can essentially create efficient electroactive materials. Metal species can also play significant roles on redox reactions, which are the main energy storage mechanism for battery-type electrodes. In this work, 2-methylimidazole, two novel SDAs of NH4BF4 and NH4HF2, and six metal species of Al, Mn, Co, Ni, Cu and Zn are coupled to synthesize MOF derivatives for energy storage. Metal species-dependent compositions including hydroxides, oxides, and hydroxide nitrates are observed. The nickel-based derivative (Ni-HBF) shows the highest specific capacitance (CF) of 698.0F/g at 20 mV/s, due to multiple redox states and advanced flower-like surface properties. The diffusion and capacitive-control contributions of MOF derivatives are also analyzed. The battery supercapacitor hybrid with Ni-HBF electrode shows a maximum energy density of 27.9 Wh/kg at 325 W/kg. The CF retention of 170.9% and Coulombic efficiency of 93.2% are achieved after 10,000 cycles. © 2023 Elsevier Inc.

关键词： Supercapacitor

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Boosting Anomaly Detection in Financial Transactions: Leveraging Deep Learning with Isolation Forest for Enhanced Accuracy

Boosting Anomaly Detection in Financial Transactions: Levera...

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2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Applications, ICAIQSA 2024

作者： Kumar Bansal, Prateek Nimma, Divya Das, Nripendra Narayan Paruchuri, Bvn Prasad Anandaram, Harishchander Karthik, M. Institute of Business Management GLA University Mathura India University of Southern Mississippi PhD in Computational Science Data Analyst in UMMC United States Manipal University Department of Information Technology Jaipur India Department of CSE Vijayawada India Amrita School of Artificial Intelligence Amrita Vishwa Vidyapeetham Coimbatore India K.Ramakrishnan College of Engineering Department of AI & DS Trichy India

ISBN: (纸本)9798331517953

Anomaly detection in financial transactions is paramount for safeguarding against fraudulent activities that pose significant risks to financial institutions and customers alike. Traditional methods often struggle to accurately identify complex and evolving patterns of fraud, necessitating innovative approaches that leverage advanced techniques such as deep learning and isolation forest. In this study, we propose a novel framework for boosting anomaly detection in financial transactions by integrating deep learning with isolation forest to achieve enhanced accuracy. Firstly, it employ an autoencoder, a type of neural network, to learn complex representations of normal transaction patterns and reconstruct input data. The autoencoder's ability to capture subtle variations in transaction attributes enables it to effectively distinguish between normal and anomalous instances based on the reconstruction error. Furthermore, we augment the anomaly detection process by incorporating isolation forest, a tree-based algorithm that isolates anomalies in the feature space by recursively partitioning data subsets. By combining the representation learning capabilities of deep learning with the outlier detection prowess of isolation forest, our framework offers a comprehensive solution for detecting fraudulent activities in financial transactions. Through experimentation on real-world financial datasets, we demonstrate the superior performance of our proposed framework compared to existing methods. The proposed method is implemented in Python software and has an accuracy of about 99.12% which is 1.49% higher than other existing methods like Conv-LSTM, Convolutional Neural Network (CNN)-LSTM, and CNN-GRU (Gated Recurrent Unit). Moreover, the integration of deep learning with isolation forest enables our framework to adapt to evolving patterns of fraud, ensuring robust and reliable anomaly detection in dynamic financial environments. Overall, our study contributes to the advancement

关键词： Convolutional neural networks

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Electrical testing of medical devices: where PAT testing is not enough

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IN PRACTICE 2024年第9期46卷 497-500页

作者： Brown, Scott Scott Brown has over 33 years' experience in clinical engineering and is a registered clinical scientist with Health and Care Professions Council. He has a PhD in risk management and a background in engineering and science. A chartered engineer and chartered scientist he has extensive experience of clinical engineering risk management governance and project management. In 2014 he established Health Tech Solutions Ltd to offer consultancy services to the healthcare sector in strategic replacement planning lean service improvement and technical and user training around medical equipment and medical gases. He has now extended his services into the veterinary sector including medical devices medical gases pressure safety systems and written scheme of examinations

Veterinary practices use a number of different types of medical devices, from operating tables to electrosurgical units and infusion pumps. These devices are connected to the animal by a variety of cables, tubes or transducers. We know that electrical safety testing is a requirement under the Health and Safety at Work Act 1974 and, for the most part, this is addressed through portable appliance testing (PAT). PAT is designed to check the safety of domestic and office equipment (eg, kettles, laptops and so on), where there is minimal connection. However, with medical equipment, we are making deliberate connections to the animal. As such, specific, more complex electrical safety testing is required. This article explores the requirements and what the additional tests are used for.

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An ultraefficient surface functionalized Ti3C2Tx MXene piezocatalyst: synchronous hydrogen evolution and wastewater treatment

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Journal of Materials Chemistry A 2023年第6期12卷 3340-3351页

作者： Lai, Sz-Nian Chen, Winston Yenyu Yen, Chao-Chun Liao, Yin-Song Chen, Po-Han Stanciu, Lia Wu, Jyh Ming Department of Materials Science and Engineering National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan PhD Program in Prospective Functional Materials Industry National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan High Entropy Materials Center National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan Tsing Hua Interdisciplinary Program National Tsing Hua University 101 Section 2 Kuang Fu Road Hsinchu300 Taiwan School of Materials Engineering Purdue University 610 Purdue Mall West LafayetteIN47907 United States Department of Materials Science and Engineering National Chung Hsing University 145 Xingda Road Taichung402 Taiwan

The Ti3C2Tx surface contains hydroxyl groups that can be modified through self-assembled monolayers by using (3-chloropropyl) trimethoxysilane (CPTMS) and fluoroalkylsilane (FOTS). This study demonstrates that an ultrahigh level of piezoelectricity can be achieved by modifying the Si-O bond of organo-silane headgroups in Ti3C2Tx. The theoretical calculation of surface functionalized Ti3C2Tx-FOTS reveals that its Si-O bond causes localized lattice distortion and enhances the noncentrosymmetric structure on the Ti3C2Tx surface. Ti3C2Tx-FOTS exhibits significantly higher butterfly loops than pristine Ti3C2Tx. The calculated rate constant of Ti3C2Tx-FOTS for dye degradation was 0.9 min−1, 15-fold higher than that of Ti3C2Tx-CPTMS and 111-fold higher than that of pristine Ti3C2Tx. The hydrogen evolution rate of Ti3C2Tx-FOTS is 900.46 μmo1 g−1 h−1, three times higher than that of Ti3C2Tx. The bifunctional surface functionalized Ti3C2Tx-FOTS can simultaneously catalyse the hydrogen evolution reaction (HER) and decomposition of wastewater, demonstrating that Ti3C2Tx-FOTS, obtained through the surface engineering of Ti3C2Tx, is a superior piezocatalyst. © 2024 The Royal Society of Chemistry.

关键词： Rate constants

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Passivation of Perovskite Films Using Ionic Liquids

Passivation of Perovskite Films Using Ionic Liquids

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2022 Advances in science and engineering Technology International Conferences, ASET 2022

作者： Alashkar, Adnan Ibrahim, Taleb Khamis, Mustafa Hai Alami, Abdul American University of Sharjah Materials Science and Engineering PhD Program Sharjah United Arab Emirates American University of Sharjah Department of Chemical Engineering Sharjah United Arab Emirates American University of Sharjah Department of Biology Chemistry and Enviromental Sciences Sharjah United Arab Emirates University of Sharjah Department of Sustainable and Renewable Energy Engineering Sharjah United Arab Emirates

ISBN: (纸本)9781665418010

In this paper, the carrier recombination, and dynamics of Perovskite Solar Cells (PSC) are investigated. Ionic Liquids (IL) are presented in the bulk perovskite in an attempt to improve the dynamics of the charge transport layer. Time Resolved Photoluminescence (TRPL) is utilized to study the fast electronic decay of the perovskite samples and the influence of the IL on the stability of the perovskite film. The ILs are added to the perovskite in three ratios (5%, 10%, and 20%). The results showed that the presence of the ILs increases the electron lifetime inside the perovskite layer. In addition, 10% IL/perovskite displayed the highest increase of 72% in the lifetime. Where, for higher ratios, the lifetime started deteriorating. © 2022 IEEE.

关键词： Ionic liquids

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NO FREE LUNCH FROM RANDOM FEATURE ENSEMBLES

arXiv

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arXiv 2024年

作者： Ruben, Benjamin S. Tong, William L. Chaudhry, Hamza Tahir Pehlevan, Cengiz Biophysics PhD Program Harvard University CambridgeMA02138 United States School of engineering and Applied Science Center for Brain Sciences Kempner Institute Harvard University CambridgeMA02138 United States School of engineering and Applied Science Center for Brain Sciences Harvard University CambridgeMA02138 United States

Given a budget on total model size, one must decide whether to train a single, large neural network or to combine the predictions of many smaller networks. We study this trade-off for ensembles of random-feature ridge regression models. We prove that when a fixed number of trainable parameters are partitioned among K independently trained models, K = 1 achieves optimal performance, provided the ridge parameter is optimally tuned. We then derive scaling laws which describe how the test risk of an ensemble of regression models decays with its total size. We identify conditions on the kernel and task eigenstructure under which ensembles can achieve near-optimal scaling laws. Training ensembles of deep convolutional neural networks on CIFAR-10 and a transformer architecture on C4, we find that a single large network outperforms any ensemble of networks with the same total number of parameters, provided the weight decay and feature-learning strength are tuned to their optimal values. Copyright © 2024, The Authors. All rights reserved.

关键词： Budget control

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Towards cross-modal causal structure and representation learning 2

Towards cross-modal causal structure and representation lear...

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2nd Machine Learning for Health Symposium, ML4H 2022

作者： Mao, Haiyi Liu, Hongfu Xiaotian Dou, Jason Benos, Panayiotis V. Joint CMU-Pitt PhD Program in Computational Biology University of Pittsburgh United States Michtom School of Computer Science Brandeis University United States Department of Electrical and Computer Engineering University of Pittsburgh United States Department of Epidemiology University of Florida United States

Does the SARS-CoV-2 virus cause patients' chest X-Rays ground-glass opacities? Does an IDH-mutation cause differences in patients' MRI images? Conventional causal discovery algorithms, although well developed to uncover the cause-effect relationships on structured data, cannot elucidate causal relations between unstructured images and structured scalar variables due to the complexity of the former. In this paper, we consider causal discovery between images and structured (scalar) variables. Specifically, we derive low dimensional image representations to analyze with structured variables. We propose a two-module amortized variational algorithm named Cross-Modal Variational Causal representation and structure Learning (CMCL). CMCL jointly learns identifiable representations given a set of independent structured variables and causal relations via formulating latent representations and structured variables into a direct acyclic graph. Moreover, we further enforce counterfactual invariance/variance onto representations. We demonstrate that CMCL outperforms other related methods on synthetic datasets and validate causal relations on semi-synthetic datasets by visualization. © 2022 P.N. Argaw, E. Healey & I.S. Kohane.

关键词： Coronavirus

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Evaluating AI-Based Deep Learning Models for Enhancing English Reading Comprehension Skills in Students

Evaluating AI-Based Deep Learning Models for Enhancing Engli...

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International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)

作者： Divya Nimma V. Arunadevi Mehul Manu V. Selvi Prema S PhD in Computational Science University of Southern Mississippi Data Analyst in UMMC USA Department of Science and Humanities Dr. Mahalingam College of Engineering and Technology Pollachi India Allied Science (Physics) Graphic Era Hill University Bhimtal Graphic Era Deemed to be University Dehradun Uttarakhand India Department of Computer Science Mother Teresa Women's University Kodaikanal India Department of English Panimalar Engineering College Chennai India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376432

In the rapidly evolving field of natural language processing (NLP), enhancing model performance in understanding and generating human language has become increasingly critical. As the need for better language models increases, enhancing the current systems’ shortcomings becomes crucial. There are difficulties in existing models precisely due to the fundamental problem of striking a balance between the level of detail achievable and the amount of computational resources that a model requires for accurate estimation in practical settings. Current models, present several problems including but not limited to overfitting, average performance on out-of-sample data and less applicability for subtle linguistic features. Such obstacles limit their capability to execute in real conditions, where high degree of accuracy and precision is paramount. To overcome these challenges, this study introduces a novel framework that employs the BERT model which was developed to capture bidirectional context and achieve greater depth of the semantic relations between words. The proposed approach is designed to improve the model’s effectiveness to a considerable extent through the use of mechanisms such as attention as well as transformer architecture included in BERT. The proposed BERT model demonstrates exceptional results, achieving an accuracy of 99.10% and a precision of 98.30%. These metrics reflect the model's superior ability to understand and generate accurate language representations, surpassing existing models in both effectiveness and efficiency. This advancement underscores the potential of BERT to address critical challenges in NLP, offering a promising solution for applications requiring high precision and robust language comprehension.

关键词： Measurement Accuracy Computational modeling Semantics Estimation Bidirectional control Linguistics Transformers Encoding Natural language processing

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