Article
Medicine, Research & Experimental
Qiaoyi Xu, Shuya Mei, Fang Nie, Zhiyun Zhang, Junqi Feng, Jinyuan Zhang, Xiaoqing Qian, Yuan Gao, Zhengyu He, Shunpeng Xing
Summary: The study demonstrates that lipopolysaccharide induces activation of the JNK signaling pathway and TNF-alpha secretion in pulmonary macrophages, leading to interaction between inflammation and metabolism that promotes lung fibroblast glycolysis. This interaction plays a crucial role in lipopolysaccharide-induced pulmonary fibrosis.
LABORATORY INVESTIGATION
(2022)
Article
Biochemistry & Molecular Biology
Eleonore Froehlich
Summary: This review discusses pulmonary changes and treatment options for ARDS induced by viruses, focusing on the potential role of pulmonary lymphatics in the pathology. Although hyaluronan may play a role in ARDS, promising pharmacological treatments are unlikely due to the limited role of drugs in lymphedema therapy.
Review
Biology
Adeel Nasrullah, Shiza Virk, Aaisha Shah, Max Jacobs, Amina Hamza, Abu Baker Sheikh, Anam Javed, Muhammad Ali Butt, Swathi Sangli
Summary: COVID-19 pandemic has caused significant morbidity and mortality, especially from severe acute respiratory distress syndrome (ARDS). The management of COVID-19-associated ARDS (CARDS) involves lung-protective ventilation, prone ventilation, neuromuscular blockade, and possibly a trial of pulmonary vasodilators for refractory hypoxemia.
Review
Medicine, General & Internal
Denise Battaglini, Brigitta Fazzini, Pedro Leme Silva, Fernanda Ferreira Cruz, Lorenzo Ball, Chiara Robba, Patricia R. M. Rocco, Paolo Pelosi
Summary: Over the last decade, management of acute respiratory distress syndrome (ARDS) has advanced significantly in terms of supportive and pharmacologic therapies. Lung protective mechanical ventilation is crucial for ARDS management, with recommendations including low tidal volume, plateau pressure, and driving pressure. Other therapies such as recruitment maneuvers and prone positioning are considered for severe ARDS cases. Despite extensive research, effective pharmacotherapies for ARDS are yet to be found, but sub-phenotypes of ARDS have shown potential for personalized pharmacologic treatments.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Biochemistry & Molecular Biology
Peng Zhang, Baoyi Liu, Weihao Zheng, Yantang Chen, Zhentao Wu, Yuting Lu, Jie Ma, Wenjie Lu, Mingzhu Zheng, Wanting Wu, Zijie Meng, Jinhua Wu, Yan Zheng, Xin Zhang, Shuang Zhang, Yanming Huang
Summary: This study investigates the role of the lung microbiome in disease progression and potential therapeutic targets in patients with sepsis-induced acute respiratory distress syndrome (ARDS). The results show that different sites of infection and prognoses can affect the composition and diversity of the pulmonary microbiome in ARDS patients, providing insights into disease development and potential therapeutic targets.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Review
Computer Science, Interdisciplinary Applications
Nicholas N. Lam, Paul D. Docherty, Rua Murray
Summary: This systematic review discusses the impact of practical identifiability (PI) on parameter identification of models, explores the role of different methods in aiding experimental design, and emphasizes the importance of considering the modeling context and research objectives when choosing a PI approach.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Medicine, General & Internal
Barbara Ruaro, Paola Confalonieri, Riccardo Pozzan, Stefano Tavano, Lucrezia Mondini, Elisa Baratella, Alessandra Pagnin, Selene Lerda, Pietro Geri, Marco Biolo, Marco Confalonieri, Francesco Salton
Summary: ARDS caused by COVID-19 is associated with reduced surfactant levels and dysfunctional ATII cells, suggesting a potential role for exogenous surfactant therapy. This study presents two cases of COVID-19 ARDS successfully treated with diluted surfactants administered via bronchoalveolar lavage.
JOURNAL OF CLINICAL MEDICINE
(2022)
Review
Biochemistry & Molecular Biology
Jesus Perez-Gil
Summary: Over the past thirty years, the lives of thousands of premature babies have been saved through pulmonary surfactant replacement therapy. Research has focused on understanding the composition and structural determinants of pulmonary surfactant activity, leading to the development of efficient therapeutic surfactants and new perspectives in tailored surfactant therapies for respiratory pathologies.
BIOMEDICAL JOURNAL
(2022)
Article
Physiology
Sayed Metwaly, Andreanne Cote, Sarah J. Donnelly, Mohammad M. Banoei, Chel H. Lee, Graciela Andonegui, Bryan G. Yipp, Hans J. Vogel, Oliver Fiehn, Brent W. Winston
Summary: This study aimed to identify metabolic fingerprints of ARDS, comparing them with ICU controls. The subphenotypes and clinical subgroups of ARDS were found to have distinct metabolic profiles, with involvement of serine-glycine metabolism. These identified metabolic fingerprints are not diagnostic biomarkers for ARDS, and further research is needed for generalizability.
AMERICAN JOURNAL OF PHYSIOLOGY-LUNG CELLULAR AND MOLECULAR PHYSIOLOGY
(2021)
Review
Biochemistry & Molecular Biology
Lars-Olav Harnisch, Onnen Moerer
Summary: Absolute and relative contraindications play a crucial role in determining the success of ECMO treatment, requiring careful consideration by healthcare providers to make informed decisions for individual patients.
Article
Pharmacology & Pharmacy
Qinqin Fei, Ian Bentley, Samir N. Ghadiali, Joshua A. Englert
Summary: The acute respiratory distress syndrome (ARDS) is a life-threatening condition that causes respiratory failure. Despite numerous clinical trials, there are no molecularly targeted pharmacologic therapies to prevent or treat ARDS. Pulmonary drug delivery during ARDS offers several potential advantages including limiting off-target and off-organ effects and directly targeting the damaged and inflamed lung regions. Nanoparticle drug delivery and surfactant-based drug carriers are potential strategies for delivering therapeutics to the injured lung in ARDS.
PULMONARY PHARMACOLOGY & THERAPEUTICS
(2023)
Article
Mathematics
Nathalie Verdiere, Oscar Navarro, Aude Naud, Alexandre Berred, Damienne Provitolo
Summary: This study investigates the calibration of a mathematical model describing behaviors during catastrophes, developed in collaboration with geographers and psychologists. Through virtual reality experiments and measuring electrocardiograms, stress levels were collected to calibrate the behavioral model. The estimation procedure and theoretical analysis revealed the system's capability to understand non-observable human processes.
Editorial Material
Cardiac & Cardiovascular Systems
David J. Hall, Jefree J. Schulte, Erik E. Lewis, Swaroop R. Bommareddi, Charles T. Rohrer, Samir Sultan, James D. Maloney, Malcolm M. DeCamp, Daniel P. McCarthy
Summary: This article reports a case of lung transplantation for post-COVID-19 pulmonary fibrosis. The patient recovered rapidly after the surgery and has done well in follow-up.
ANNALS OF THORACIC SURGERY
(2022)
Article
Physiology
Reece P. Stevens, Mikhail F. Alexeyev, Natalia Kozhukhar, Viktoria Pastukh, Sunita S. Paudel, Jessica Bell, Dhananjay T. Tambe, Troy Stevens, Ji Young Lee
Summary: The repair of PMVECs is influenced by the acidic microenvironment, with different domains of CA IX playing various roles in cell metabolism, migration, and network formation.
AMERICAN JOURNAL OF PHYSIOLOGY-LUNG CELLULAR AND MOLECULAR PHYSIOLOGY
(2022)
Review
Cardiac & Cardiovascular Systems
Felix H. Savoie-White, Laurence Tremblay, Charles Antoine Menier, Cecile Duval, Frederic Bergeron, Mina Tadrous, Jade Tougas, Jason R. Guertin, Paula A. Ugalde
Summary: Neuromuscular blockers can safely reduce mortality in ARDS. Light sedation potentially has a similar impact on mortality as heavy sedation.
Article
Endocrinology & Metabolism
Nicholas Lam, Rua Murray, Paul D. Docherty, Lisa Te Morenga, J. Geoffrey Chase
Summary: This study compared a mixing model with local depot site compartments with an existing clinically validated insulin sensitivity test model and found that while the mixing model effectively captured the dynamics of mixing behavior, it did not significantly improve insulin sensitivity identification.
JOURNAL OF DIABETES SCIENCE AND TECHNOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Christopher Yew Shuen Ang, Yeong Shiong Chiew, Lien Hong Vu, Matthew E. Cove
Summary: A Convolutional Autoencoder model was developed to quantify the magnitude of patient spontaneous breathing effort using the airway pressure and flow waveform during mechanical ventilation. The model was trained and validated using simulated data, and showed the ability to accurately predict normal flow and assess the magnitude of spontaneous breathing effort.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Computer Science, Interdisciplinary Applications
Christopher Yew Shuen Ang, Jay Wing Wai Lee, Yeong Shiong Chiew, Xin Wang, Chee Pin Tan, Matthew E. Cove, Mohd Basri Mat Nor, Cong Zhou, Thomas Desaive, J. Geoffrey Chase
Summary: This research proposes a framework for generating virtual patients to test and implement model-based decision support systems for mechanical ventilation. The framework utilizes a clinically validated respiratory mechanics model to generate virtual patients from retrospective data, and evaluates the safety and efficacy of the protocols through virtual clinical trials.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Biology
Christopher Yew Shuen Ang, Yeong Shiong Chiew, Xin Wang, Mohd Basri Mat Nor, Matthew E. Cove, J. Geoffrey Chase
Summary: This research developed two stochastic models for respiratory mechanics in mechanically ventilated patients, improving prediction accuracy and range. Clinical validation showed high accuracy in predicting future respiratory elastance data. These models can potentially be used in decision support systems for guided and personalized mechanical ventilation treatment.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Education & Educational Research
Wendy H. Fox-Turnbull, Paul D. Docherty, Pinelopi Zaka, Tessa Impey
Summary: There is a recognized lack of women in engineering and STEM fields in most western countries. Teachers play a significant role in influencing students' career decisions, but many education students have limited or stereotypical views of engineering, which may lead to gender bias when providing career advice.
INTERNATIONAL JOURNAL OF TECHNOLOGY AND DESIGN EDUCATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Jason K. K. Cheong, Ean H. Ooi, Yeong S. Chiew, Luca Menichetti, Paolo Armanetti, Mauro Comes Franchini, Elisa Alchera, Irene Locatelli, Tamara Canu, Mirko Maturi, Viktor Popov, Massimo Alfano
Summary: This study investigates the effects of heterogeneous distribution of gold nanorods (GNRs) on the treatment outcome of bladder cancer. The results show that different GNR distribution leads to different treatment outcomes, and intravesical instillation of GNRs can reduce damage to the surrounding tissues during thermal ablation. Further exploration is needed for the method of GNR distribution through intravesical instillation.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Multidisciplinary Sciences
Baxter Williams, Daniel Bishop, Paul Docherty
Summary: This paper compares different methods of HWC temperature control and presents a methodology to assess the amount of thermal storage available in HWCs for demand side management based on use behavior in different household types. By using simple stochastic methods to predict domestic hot water demand, a smart controller was designed to achieve lower rates of unmet demand and higher available storage compared to traditional controllers. The average storage available for DSM from the use of this smart controller is predicted to be between 3.63 and 7.20 kWh per household. These findings suggest that using HWCs for thermal storage is a cost-effective solution for peak shaving and reducing greenhouse gas emissions in countries like New Zealand.
JOURNAL OF THE ROYAL SOCIETY OF NEW ZEALAND
(2023)
Article
Chemistry, Analytical
Nour Aldeen Jalal, Tamer Abdulbaki Alshirbaji, Paul David Docherty, Herag Arabian, Bernhard Laufer, Sabine Krueger-Ziolek, Thomas Neumuth, Knut Moeller
Summary: Adapting intelligent context-aware systems (CAS) to future operating rooms aims to improve situational awareness and provide surgical decision support systems to medical teams. In this work, a deep learning approach for analyzing laparoscopic videos for surgical phase recognition, tool classification, and weakly-supervised tool localization was proposed. The experimental results demonstrated the ability of the model to learn discriminative features for all tasks and highlighted the importance of integrating attention modules and multi-stage feature fusion for more robust and precise detection of surgical phases and tools.
Article
Acoustics
Zhi Q. Tan, Ean H. Ooi, Yeong S. Chiew, Ji J. Foo, Eddie Y. K. Ng, Ean T. Ooi
Summary: Sonothrombolysis is a technique that uses ultrasonic waves and microbubbles to dissolve blood clots. The optimal ultrasound and microbubble parameters for this technique remain a challenge to determine. In this study, a computational framework was developed to simulate microbubble-mediated sonothrombolysis and investigate the effects of ultrasound pressure, frequency, microbubble radius, and concentration on clot dissolution. The results revealed the dominant role of ultrasound pressure, the potential benefits of smaller microbubbles at higher pressure, the positive impact of higher microbubble concentration, and the dependence of ultrasound frequency on acoustic attenuation. These findings provide important insights for the clinical implementation of sonothrombolysis.
Article
Computer Science, Interdisciplinary Applications
Christopher Yew Shuen Ang, Yeong Shiong Chiew, Xin Wang, Ean Hin Ooi, Mohd Basri Mat Nor, Matthew E. Cove, J. Geoffrey Chase
Summary: This research presents a realistic, time-varying mechanically ventilated respiratory failure virtual patient profile synthesised using a stochastic model. The stochastic model accurately generates future respiratory elastance data based on current values, allowing for the simulation and validation of virtual trials. The development of temporal virtual patients using stochastic simulation alleviates the need for lengthy and costly clinical trials, ultimately leading to improved patient care and outcomes in mechanical ventilation.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Computer Science, Hardware & Architecture
Yohanathan P. S. Kumaran, Chee Pin Tan, Yeong Shiong Chiew, Wen-Shyan Chua
Summary: This article presents an online method to quantify backlash and predict the remaining useful life (RUL) in industrial robots using standard available sensors. It models the input torque oscillations and estimates them with an unknown input observer to detect and quantify the backlash. A health indicator (HI) is plotted over time and a failure threshold is set based on historical data. Finally, an exponential degradation model is used to predict the RUL of the robot joint.
IEEE TRANSACTIONS ON RELIABILITY
(2023)
Article
Chemistry, Analytical
Bernhard Laufer, Paul D. Docherty, Rua Murray, Sabine Krueger-Ziolek, Nour Aldeen Jalal, Fabian Hoeflinger, Stefan J. Rupitsch, Leonhard Reindl, Knut Moeller
Summary: This research focuses on measuring respiratory volume using upper body movements and a smart shirt. By using motion capture and regression methods, the study determines the optimal selection and placement of sensors on the shirt to accurately recover respiratory parameters. The results show that the Lasso method outperforms Ridge regression, providing sparse solutions and better handling of outliers. The smart shirt could potentially replace spirometry and offer a more convenient way to measure respiratory parameters in home care or hospital settings.
Article
Engineering, Multidisciplinary
Christopher Yew Shuen Ang, Yeong Shiong Chiew, Xin Wang, Mohd Basri Mat Nor, J. Geoffrey Chase
Summary: Stochastic models for predicting intra-patient respiratory system elastance (Ers) in mechanically ventilated patients have been developed using small cohorts, resulting in potential bias and overestimation. This research investigates the effect of tuning the kernel density estimator (KDE) parameter with a constant, c, on the performance of a 30-min interval Ers stochastic model. By developing variations of the stochastic model using different KDE parameters, model bias and overestimation were evaluated. The optimization of the KDE parameter enables more accurate and robust Ers stochastic models, even with limited training data availability.
RESULTS IN ENGINEERING
(2023)
Article
Health Care Sciences & Services
Rebecca H. K. Emanuel, Paul D. Docherty, Helen Lunt, Rebecca E. Campbell
Summary: This study explores the feasibility of using a web-based forum for clinical research by analyzing laboratory test results posted in a PCOS subreddit. The results suggest that the forum participants were representative of research-identified PCOS cohorts, with most laboratory test values showing consistency with published literature for PCOS.
JMIR FORMATIVE RESEARCH
(2023)
Article
Education & Educational Research
Paul D. Docherty, Pinelopi A. Zaka, Wendy Fox-Turnbull
Summary: The study examined the impact of the flipped classroom approach on the academic performance of engineering students and found no significant differences in performance in the first year dynamics class due to the teaching method used.
RESEARCH PAPERS IN EDUCATION
(2022)
Article
Engineering, Biomedical
Wenwen Wu, Yanqi Huang, Xiaomei Wu
Summary: In this study, a 2D deep learning classification network SRT was proposed to improve automatic ECG analysis. The model structure was enhanced with the CNN and Transformer-encoder modules, and a novel attention module and Dilated Stem structure were introduced to improve feature extraction. Comparative experiments showed that the proposed model outperformed several advanced methods.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Chiheb Jamazi, Ghaith Manita, Amit Chhabra, Houssem Manita, Ouajdi Korbaa
Summary: In this study, a new dynamic and intelligent clustering method for brain tumor segmentation is proposed by combining the improved Aquila Optimizer (AO) and the K-Means algorithm. The proposed MAO-Kmeans approach aims to automatically extract the correct number and location of cluster centers and the number of pixels in each cluster in abnormal MRI images, and the experimental results demonstrate its effectiveness in improving the performance of conventional K-means clustering.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Alberto Hernando, Maria Dolores Pelaez-Coca, Eduardo Gil
Summary: This study applied a new algorithm to decompose the photoplethysmogram (PPG) pulse and identified changes in PPG pulse morphology due to pressure. The results showed that there was an increase in amplitude, width, and area values of the PPG pulse, and a decrease in ratios when pressure increased, indicating vasoconstriction. Furthermore, some parameters were found to be related to the pulse-to-pulse interval.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Jens Moeller, Eveline Popanda, Nuri H. Aydin, Hubert Welp, Iris Tischoff, Carsten Brenner, Kirsten Schmieder, Martin R. Hofmann, Dorothea Miller
Summary: In this study, a method based on texture features is proposed, which can classify healthy gray and white matter against glioma degrees 4 samples with reasonable classification performance using a relatively low number of samples for training. The method achieves high classification performance without the need for large datasets and complex machine learning approaches.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Amrutha Bhaskaran, Manish Arora
Summary: The study evaluates a cyclic repetition frequency-based algorithm for fetal heart rate estimation. The algorithm improves accuracy and reliability for poor-quality signals and performs well for different gestation weeks and clinical settings.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Manan Patel, Harsh Bhatt, Manushi Munshi, Shivani Pandya, Swati Jain, Priyank Thakkar, Sangwon Yoon
Summary: Electroencephalogram (EEG) signals have been effectively used to measure and analyze neurological data and brain-related ailments. Artificial Intelligence (AI) algorithms, specifically the proposed CNN-FEBAC framework, show promising results in studying the EEG signals of autistic patients and predicting their response to stimuli with 91% accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Wencheng Gu, Kexue Sun
Summary: This research proposes an improved version of YOLOv5 (AYOLOv5) based on the attention mechanism to address the issue of low recognition rate in cell detection. Experimental results demonstrate that AYOLOv5 can accurately identify cell targets and improve the quality and recognition performance of cell pictures.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Anita Gade, V. Vijaya Baskar, John Panneerselvam
Summary: Analysis of exhaled breath is an increasingly used diagnostic technique in medicine. This study introduces a new NICBGM-based model that utilizes various features and weight optimization for accurate data interpretation and result optimization.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Arsalan Asemi, Keivan Maghooli, Fereidoun Nowshiravan Rahatabad, Hamid Azadeh
Summary: Biometric authentication systems can perform identity verification with optimal accuracy in various environments and emotional changes, while the performance of signature verification systems can be affected when people are under stress. This study examines the performance of a signature verification system based on muscle synergy patterns as biometric characteristics for stressed individuals. EMG signals from hand and arm muscles were recorded and muscle synergies were extracted using Non-Negative Matrix Factorization. The extracted patterns were classified using Support Vector Machine for authentication of stressed individuals.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tianjiao Guo, Jie Yang, Qi Yu
Summary: This paper proposes a CNN-based approach for segmenting four typical DR lesions simultaneously, achieving competitive performance. This approach is significant for DR lesion segmentation and has potential in other segmentation tasks.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
G. Akilandasowmya, G. Nirmaladevi, S. U. Suganthi, A. Aishwariya
Summary: This study proposes a technique for skin cancer detection and classification using deep hidden features and ensemble classifiers. By optimizing features to reduce data dimensionality and combining ensemble classifiers, the proposed method outperforms in skin cancer classification and improves prediction accuracy.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Tuuli Uudeberg, Juri Belikov, Laura Paeske, Hiie Hinrikus, Innar Liiv, Maie Bachmann
Summary: This article introduces a novel feature extraction method, the in-phase matrix profile (pMP), specifically adapted for electroencephalographic (EEG) signals, for detecting major depressive disorder (MDD). The results show that pMP outperforms Higuchi's fractal dimension (HFD) in detecting MDD, making it a promising method for future studies and potential clinical use for diagnosing MDD.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
P. Nancy, M. Parameswari, J. Sathya Priya
Summary: Stroke is the third leading cause of mortality worldwide, and early detection is crucial to avoid health risks. Existing research on disease detection using machine learning techniques has limitations, so a new stroke detection system is proposed. The experimental results show that the proposed method achieves a high accuracy rate in stroke detection.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Shimin Liu, Zhiwen Huang, Jianmin Zhu, Baolin Liu, Panyu Zhou
Summary: In this study, a continuous blood pressure (BP) monitoring method based on random forest feature selection (RFFS) and a gray wolf optimization-gradient boosting regression tree (GWO-GBRT) prediction model was developed. The method extracted features from electrocardiogram (ECG) and photoplethysmography (PPG) signals, and employed RFFS to select sensitive features highly correlated with BP. A hybrid prediction model of gray wolf optimization (GWO) technique and gradient boosting regression tree (GBRT) algorithm was established to learn the relationship between BP and sensitive features. Experimental results demonstrated the effectiveness and advancement of the proposed method.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Engineering, Biomedical
Weijun Gong, Yurong Qian, Weihang Zhou, Hongyong Leng
Summary: The recognition of dynamic facial expressions is challenging due to various factors, and obtaining discriminative expression features has been difficult. Traditional deep learning networks lack understanding of global and temporal expressions. This study proposes an enhanced spatial-temporal learning network to improve dynamic facial expression recognition.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
