Displaying publications 1 - 20 of 248 in total

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  1. Ang CYS, Chiew YS, Vu LH, Cove ME
    Comput Methods Programs Biomed, 2022 Mar;215:106601.
    PMID: 34973606 DOI: 10.1016/j.cmpb.2021.106601
    BACKGROUND: Spontaneous breathing (SB) effort during mechanical ventilation (MV) is an important metric of respiratory drive. However, SB effort varies due to a variety of factors, including evolving pathology and sedation levels. Therefore, assessment of SB efforts needs to be continuous and non-invasive. This is important to prevent both over- and under-assistance with MV. In this study, a machine learning model, Convolutional Autoencoder (CAE) is developed to quantify the magnitude of SB effort using only bedside MV airway pressure and flow waveform.

    METHOD: The CAE model was trained using 12,170,655 simulated SB flow and normal flow data (NB). The paired SB and NB flow data were simulated using a Gaussian Effort Model (GEM) with 5 basis functions. When the CAE model is given a SB flow input, it is capable of predicting a corresponding NB flow for the SB flow input. The magnitude of SB effort (SBEMag) is then quantified as the difference between the SB and NB flows. The CAE model was used to evaluate the SBEMag of 9 pressure control/ support datasets. Results were validated using a mean squared error (MSE) fitting between clinical and training SB flows.

    RESULTS: The CAE model was able to produce NB flows from the clinical SB flows with the median SBEMag of the 9 datasets being 25.39% [IQR: 21.87-25.57%]. The absolute error in SBEMag using MSE validation yields a median of 4.77% [IQR: 3.77-8.56%] amongst the cohort. This shows the ability of the GEM to capture the intrinsic details present in SB flow waveforms. Analysis also shows both intra-patient and inter-patient variability in SBEMag.

    CONCLUSION: A Convolutional Autoencoder model was developed with simulated SB and NB flow data and is capable of quantifying the magnitude of patient spontaneous breathing effort. This provides potential application for real-time monitoring of patient respiratory drive for better management of patient-ventilator interaction.

    Matched MeSH terms: Positive-Pressure Respiration; Respiration, Artificial*
  2. Damanhuri NS, Chiew YS, Othman NA, Docherty PD, Pretty CG, Shaw GM, et al.
    Comput Methods Programs Biomed, 2016 Jul;130:175-85.
    PMID: 27208532 DOI: 10.1016/j.cmpb.2016.03.025
    BACKGROUND: Respiratory system modelling can aid clinical decision making during mechanical ventilation (MV) in intensive care. However, spontaneous breathing (SB) efforts can produce entrained "M-wave" airway pressure waveforms that inhibit identification of accurate values for respiratory system elastance and airway resistance. A pressure wave reconstruction method is proposed to accurately identify respiratory mechanics, assess the level of SB effort, and quantify the incidence of SB effort without uncommon measuring devices or interruption to care.

    METHODS: Data from 275 breaths aggregated from all mechanically ventilated patients at Christchurch Hospital were used in this study. The breath specific respiratory elastance is calculated using a time-varying elastance model. A pressure reconstruction method is proposed to reconstruct pressure waves identified as being affected by SB effort. The area under the curve of the time-varying respiratory elastance (AUC Edrs) are calculated and compared, where unreconstructed waves yield lower AUC Edrs. The difference between the reconstructed and unreconstructed pressure is denoted as a surrogate measure of SB effort.

    RESULTS: The pressure reconstruction method yielded a median AUC Edrs of 19.21 [IQR: 16.30-22.47]cmH2Os/l. In contrast, the median AUC Edrs for unreconstructed M-wave data was 20.41 [IQR: 16.68-22.81]cmH2Os/l. The pressure reconstruction method had the least variability in AUC Edrs assessed by the robust coefficient of variation (RCV)=0.04 versus 0.05 for unreconstructed data. Each patient exhibited different levels of SB effort, independent from MV setting, indicating the need for non-invasive, real time assessment of SB effort.

    CONCLUSION: A simple reconstruction method enables more consistent real-time estimation of the true, underlying respiratory system mechanics of a SB patient and provides the surrogate of SB effort, which may be clinically useful for clinicians in determining optimal ventilator settings to improve patient care.

    Matched MeSH terms: Respiration, Artificial*
  3. Lee JWW, Chiew YS, Wang X, Tan CP, Mat Nor MB, Cove ME, et al.
    Comput Methods Programs Biomed, 2022 Feb;214:106577.
    PMID: 34936946 DOI: 10.1016/j.cmpb.2021.106577
    BACKGROUND AND OBJECTIVE: Mechanical ventilation is the primary form of care provided to respiratory failure patients. Limited guidelines and conflicting results from major clinical trials means selection of mechanical ventilation settings relies heavily on clinician experience and intuition. Determining optimal mechanical ventilation settings is therefore difficult, where non-optimal mechanical ventilation can be deleterious. To overcome these difficulties, this research proposes a model-based method to manage the wide range of possible mechanical ventilation settings, while also considering patient-specific conditions and responses.

    METHODS: This study shows the design and development of the "VENT" protocol, which integrates the single compartment linear lung model with clinical recommendations from landmark studies, to aid clinical decision-making in selecting mechanical ventilation settings. Using retrospective breath data from a cohort of 24 patients, 3,566 and 2,447 clinically implemented VC and PC settings were extracted respectively. Using this data, a VENT protocol application case study and clinical comparison is performed, and the prediction accuracy of the VENT protocol is validated against actual measured outcomes of pressure and volume.

    RESULTS: The study shows the VENT protocols' potential use in narrowing an overwhelming number of possible mechanical ventilation setting combinations by up to 99.9%. The comparison with retrospective clinical data showed that only 33% and 45% of clinician settings were approved by the VENT protocol. The unapproved settings were mainly due to exceeding clinical recommended settings. When utilising the single compartment model in the VENT protocol for forecasting peak pressures and tidal volumes, median [IQR] prediction error values of 0.75 [0.31 - 1.83] cmH2O and 0.55 [0.19 - 1.20] mL/kg were obtained.

    CONCLUSIONS: Comparing the proposed protocol with retrospective clinically implemented settings shows the protocol can prevent harmful mechanical ventilation setting combinations for which clinicians would be otherwise unaware. The VENT protocol warrants a more detailed clinical study to validate its potential usefulness in a clinical setting.

    Matched MeSH terms: Respiration, Artificial*
  4. Lee JWW, Chiew YS, Wang X, Mat Nor MB, Chase JG, Desaive T
    Biomed Eng Online, 2022 Feb 11;21(1):13.
    PMID: 35148759 DOI: 10.1186/s12938-022-00981-0
    BACKGROUND AND OBJECTIVE: Mechanical ventilation (MV) is the primary form of care for respiratory failure patients. MV settings are based on general clinical guidelines, intuition, and experience. This approach is not patient-specific and patients may thus experience suboptimal, potentially harmful MV care. This study presents the Stochastic integrated VENT (SiVENT) protocol which combines model-based approaches of the VENT protocol from previous works, with stochastic modelling to take the variation of patient respiratory elastance over time into consideration.

    METHODS: A stochastic model of Ers is integrated into the VENT protocol from previous works to develop the SiVENT protocol, to account for both intra- and inter-patient variability. A cohort of 20 virtual MV patients based on retrospective patient data are used to validate the performance of this method for volume-controlled (VC) ventilation. A performance evaluation was conducted where the SiVENT and VENT protocols were implemented in 1080 instances each to compare the two protocols and evaluate the difference in reduction of possible MV settings achieved by each.

    RESULTS: From an initial number of 189,000 possible MV setting combinations, the VENT protocol reduced this number to a median of 10,612, achieving a reduction of 94.4% across the cohort. With the integration of the stochastic model component, the SiVENT protocol reduced this number from 189,000 to a median of 9329, achieving a reduction of 95.1% across the cohort. The SiVENT protocol reduces the number of possible combinations provided to the user by more than 1000 combinations as compared to the VENT protocol.

    CONCLUSIONS: Adding a stochastic model component into a model-based approach to selecting MV settings improves the ability of a decision support system to recommend patient-specific MV settings. It specifically considers inter- and intra-patient variability in respiratory elastance and eliminates potentially harmful settings based on clinically recommended pressure thresholds. Clinical input and local protocols can further reduce the number of safe setting combinations. The results for the SiVENT protocol justify further investigation of its prediction accuracy and clinical validation trials.

    Matched MeSH terms: Respiration, Artificial*
  5. Al-Bayaty FH, Baharudin N, Hassan MIA
    Dent Med Probl, 2021 10 2;58(3):385-395.
    PMID: 34597481 DOI: 10.17219/dmp/132979
    This overview was conducted to highlight the importance of adequate oral hygiene for patients severely affected by coronavirus disease 2019 (COVID-19) due to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). These are patients who were admitted to the intensive care unit (ICU) to receive oxygen through mechanical ventilation due to severe pneumonia as a complication of COVID-19. Various dental plaque removal methods for ventilated patients were discussed with regard to their efficacy. The use of chemical agents was also considered to determine which one might be proposed as the best choice. Also, oral care programs or systems that can be implemented by ICU nurses or staff in the case of these ventilated patients were suggested based on evidence from the literature. These interventions aim to reduce microbial load in dental plaque/biofilm in the oropharynx as well as the aspiration of the contaminated saliva in order to prevent the transmission of the dental plaque bacteria to the lungs or other distant organs, and reduce the mortality rate.
    Matched MeSH terms: Respiration, Artificial
  6. Liew RP
    Med J Malaysia, 1974 Mar;28(3):185-6.
    PMID: 4278346
    Matched MeSH terms: Positive-Pressure Respiration/instrumentation*
  7. Wong JJM, Lee SW, Tan HL, Ma YJ, Sultana R, Mok YH, et al.
    Pediatr Crit Care Med, 2020 08;21(8):720-728.
    PMID: 32205663 DOI: 10.1097/PCC.0000000000002324
    OBJECTIVES: Reduced morbidity and mortality associated with lung-protective mechanical ventilation is not proven in pediatric acute respiratory distress syndrome. This study aims to determine if a lung-protective mechanical ventilation protocol in pediatric acute respiratory distress syndrome is associated with improved clinical outcomes.

    DESIGN: This pilot study over April 2016 to September 2019 adopts a before-and-after comparison design of a lung-protective mechanical ventilation protocol. All admissions to the PICU were screened daily for fulfillment of the Pediatric Acute Lung Injury Consensus Conference criteria and included.

    SETTING: Multidisciplinary PICU.

    PATIENTS: Patients with pediatric acute respiratory distress syndrome.

    INTERVENTIONS: Lung-protective mechanical ventilation protocol with elements on peak pressures, tidal volumes, end-expiratory pressure to FIO2 combinations, permissive hypercapnia, and permissive hypoxemia.

    MEASUREMENTS AND MAIN RESULTS: Ventilator and blood gas data were collected for the first 7 days of pediatric acute respiratory distress syndrome and compared between the protocol (n = 63) and nonprotocol groups (n = 69). After implementation of the protocol, median tidal volume (6.4 mL/kg [5.4-7.8 mL/kg] vs 6.0 mL/kg [4.8-7.3 mL/kg]; p = 0.005), PaO2 (78.1 mm Hg [67.0-94.6 mm Hg] vs 74.5 mm Hg [59.2-91.1 mm Hg]; p = 0.001), and oxygen saturation (97% [95-99%] vs 96% [94-98%]; p = 0.007) were lower, and end-expiratory pressure (8 cm H2O [7-9 cm H2O] vs 8 cm H2O [8-10 cm H2O]; p = 0.002] and PaCO2 (44.9 mm Hg [38.8-53.1 mm Hg] vs 46.4 mm Hg [39.4-56.7 mm Hg]; p = 0.033) were higher, in keeping with lung protective measures. There was no difference in mortality (10/63 [15.9%] vs 18/69 [26.1%]; p = 0.152), ventilator-free days (16.0 [2.0-23.0] vs 19.0 [0.0-23.0]; p = 0.697), and PICU-free days (13.0 [0.0-21.0] vs 16.0 [0.0-22.0]; p = 0.233) between the protocol and nonprotocol groups. After adjusting for severity of illness, organ dysfunction and oxygenation index, the lung-protective mechanical ventilation protocol was associated with decreased mortality (adjusted hazard ratio, 0.37; 95% CI, 0.16-0.88).

    CONCLUSIONS: In pediatric acute respiratory distress syndrome, a lung-protective mechanical ventilation protocol improved adherence to lung-protective mechanical ventilation strategies and potentially mortality.

    Matched MeSH terms: Respiration, Artificial*
  8. Norhaya MR, Wazi RA, Azhar AA
    Med J Malaysia, 2009 Mar;64(1):77-9.
    PMID: 19852329
    Treatment for chronic respiratory failure has advanced since the introduction of domiciliary non-invasive ventilatory devices. This has given a new light of hope for patients with chronic respiratory failure secondary to various causes. We report a series of patients with respiratory failure of different origins and types of management that they received. Four patients received bilevel positive airway pressure (BiPAP) and one patient received continuous positive airway pressure (CPAP).
    Matched MeSH terms: Positive-Pressure Respiration; Respiration, Artificial/instrumentation*
  9. Chase JG, Chiew YS, Lambermont B, Morimont P, Shaw GM, Desaive T
    Crit Care, 2020 05 14;24(1):222.
    PMID: 32410701 DOI: 10.1186/s13054-020-02945-z
    Matched MeSH terms: Respiration, Artificial/trends*; Respiration, Artificial/statistics & numerical data
  10. Soh KL, Soh KG, Japar S, Raman RA, Davidson PM
    J Clin Nurs, 2011 Mar;20(5-6):733-42.
    PMID: 21320202 DOI: 10.1111/j.1365-2702.2010.03579.x
    This study sought to determine the strategies, methods and frequency of oral care provided for mechanically ventilated patients in Malaysian intensive care units. The study also described nurses' attitudes to providing oral care and their knowledge of the mode of transmission of ventilator-associated pneumonia.
    Matched MeSH terms: Respiration, Artificial*
  11. Lim KG
    Med J Malaysia, 2001 Jun;56(2):141-2.
    PMID: 11771072
    Matched MeSH terms: Respiration Disorders/therapy*
  12. Langdon R, Docherty PD, Chiew YS, Chase JG
    Math Biosci, 2017 02;284:32-39.
    PMID: 27513728 DOI: 10.1016/j.mbs.2016.08.001
    For patients with acute respiratory distress syndrome (ARDS), mechanical ventilation (MV) is an essential therapy in the intensive care unit (ICU). Suboptimal PEEP levels in MV can cause ventilator induced lung injury, which is associated with increased mortality, extended ICU stay, and high cost. The ability to predict the outcome of respiratory mechanics in response to changes in PEEP would thus provide a critical advantage in personalising and improving care. Testing the potentially dangerous high pressures would not be required to assess their impact. A nonlinear autoregressive (NARX) model was used to predict airway pressure in 19 data sets from 10 mechanically ventilated ARDS patients. Patient-specific NARX models were identified from pressure and flow data over one, two, three, or four adjacent PEEP levels in a recruitment manoeuvre. Extrapolation of NARX model elastance functions allowed prediction of patient responses to PEEP changes to higher or lower pressures. NARX model predictions were more successful than those using a well validated first order model (FOM). The most clinically important results were for extrapolation up one PEEP step of 2cmH2O from the highest PEEP in the training data. When the NARX model was trained on one PEEP level, the mean RMS residual for the extrapolation PEEP level was 0.52 (90% CI: 0.47-0.57) cmH2O, compared to 1.50 (90% CI: 1.38-1.62) cmH2O for the FOM. When trained on four PEEP levels, the NARX result was 0.50 (90% CI: 0.42-0.58) cmH2O, and was 1.95 (90% CI: 1.71-2.19) cmH2O for the FOM. The results suggest that a full recruitment manoeuvre may not be required for the NARX model to obtain a useful estimate of the pressure waveform at higher PEEP levels. The methodology could thus allow clinicians to make informed decisions about ventilator PEEP settings while reducing the risk associated with high PEEP, and subsequent high peak airway pressures.
    Matched MeSH terms: Respiration, Artificial*
  13. Shamsul, B.S., Zakirah, M.
    MyJurnal
    The main objective of this study is to determine the association between respirable hexavalent chromium compounds with urinary β2-microglobulin levels among welders in an automotive components manufacturing plant. 49 welders and 39 workers involved in stamping process were selected as the exposed and the comparative group. β2-microglobulin is a protein renal tubular dysfunction marker that can indicate renal dysfunction caused by heavy metal. Air samples of worker’s breathing zone were collected using personal air sampling pump and filter papers. Filter papers were then diluted and analysed with Atomic Absorption Spectrophotometry (AAS). Workers’ urine samples were collected at the end of 8-hour work shift and analysed with β2-microglobulin ELISA Kit (IBL-Hamburg) and a microtiter reader. Meanwhile, creatinine levels were analysed with creatinine test strips and Reflotron®. A mean concentration of respirable hexavalent chromium compounds in air for the exposed group was 0.135 ± 0.043μg/m3 while for the non-exposed group was 0.124 ± 0.029μg/m3. The mean level of urinary β2-microglobulin per creatinine for the exposed group was 84.996 ± 39.246μg/g while that of the comparative group was 61.365 ± 21.609μg/g. The concentrations of respirable hexavalent chromium compounds were higher in the exposed group compared to the comparative group (Z=-2.444, p=0.015). β2-microglobulin level was also higher in the exposed group compared to the non-exposed group (t=3.821, p=
    Matched MeSH terms: Respiration; Cell Respiration
  14. Nor Mohd Razif Noraini, Leman, A.M., Ahmad Sayuti Zainal Abidin
    MyJurnal
    A preliminary study has been conducted in a new constructed 8 stories building (2 level of Hostels facility, 3 level of Training Room, 2 Level of Offices and 1 level of Exhibition Halls and Rooms) in Bandar Baru Bangi, Selangor. The Hostels facility is a floor tile and furnished with build in locker and use split air conditioning system while the Training Room and Exhibition Rooms used floor tile. The Offices and Exhibition Hall are carpeted furnished. All these spaces were using centralized air conditioning systems. A pre-commissioning assessment on 5 chemical parameters of indoor air pollutants such Total Volatile Organic Compounds (TVOC), Formaldehyde, Respirable Particulates (PM!
    Matched MeSH terms: Respiration; Cell Respiration
  15. Chiew YS, Tan CP, Chase JG, Chiew YW, Desaive T, Ralib AM, et al.
    Comput Methods Programs Biomed, 2018 Apr;157:217-224.
    PMID: 29477430 DOI: 10.1016/j.cmpb.2018.02.007
    BACKGROUND AND OBJECTIVE: Respiratory mechanics estimation can be used to guide mechanical ventilation (MV) but is severely compromised when asynchronous breathing occurs. In addition, asynchrony during MV is often not monitored and little is known about the impact or magnitude of asynchronous breathing towards recovery. Thus, it is important to monitor and quantify asynchronous breathing over every breath in an automated fashion, enabling the ability to overcome the limitations of model-based respiratory mechanics estimation during asynchronous breathing ventilation.

    METHODS: An iterative airway pressure reconstruction (IPR) method is used to reconstruct asynchronous airway pressure waveforms to better match passive breathing airway waveforms using a single compartment model. The reconstructed pressure enables estimation of respiratory mechanics of airway pressure waveform essentially free from asynchrony. Reconstruction enables real-time breath-to-breath monitoring and quantification of the magnitude of the asynchrony (MAsyn).

    RESULTS AND DISCUSSION: Over 100,000 breathing cycles from MV patients with known asynchronous breathing were analyzed. The IPR was able to reconstruct different types of asynchronous breathing. The resulting respiratory mechanics estimated using pressure reconstruction were more consistent with smaller interquartile range (IQR) compared to respiratory mechanics estimated using asynchronous pressure. Comparing reconstructed pressure with asynchronous pressure waveforms quantifies the magnitude of asynchronous breathing, which has a median value MAsyn for the entire dataset of 3.8%.

    CONCLUSION: The iterative pressure reconstruction method is capable of identifying asynchronous breaths and improving respiratory mechanics estimation consistency compared to conventional model-based methods. It provides an opportunity to automate real-time quantification of asynchronous breathing frequency and magnitude that was previously limited to invasively method only.

    Matched MeSH terms: Respiration, Artificial*
  16. Pravin Sugunan, Netia Jeganathan, Philip Rajan Devesahayam
    MyJurnal
    Aspiration of a foreign body is rare in school-age children. This reports the 21-day journey of an 8-year-old girl who had a foreign body aspiration. She presented to our hospital after five days of respiratory distress. She subsequently required mechanical ventilation and was supported with triple inotropes. After 18 days, a foreign body was removed via rigid bronchoscopy, followed by a rapid recovery of the patient.
    Matched MeSH terms: Respiration Disorders; Respiration, Artificial
  17. Abdullah S, Abd Hamid FF, Ismail M, Ahmed AN, Wan Mansor WN
    Data Brief, 2019 Aug;25:103969.
    PMID: 31198825 DOI: 10.1016/j.dib.2019.103969
    The aim of the measurement of this data is to evaluate the Indoor Air Quality (IAQ) in terms of chemical and physical parameters. Data were collected at three different kindergartens having different surrounding activities (industrial, institutional, residential area). The chemical parameters measured were respirable suspended particulates of PM10, PM2.5, PM1, carbon monoxide and carbon dioxide, and the concentrations are within the acceptable limit. Physical parameters of wind speed are within the standard, while temperature and relative humidity exceeded the acceptable limit. A strong correlation was found between the chemical IAQ parameters with thermal comfort parameters (temperature and relative humidity). The concentration of IAQ pollutants is higher in order of residential > institutional > industrial.
    Matched MeSH terms: Respiration; Cell Respiration
  18. Yong SY, Siop S, Kho WM
    Nurs Open, 2021 01;8(1):200-209.
    PMID: 33318828 DOI: 10.1002/nop2.619
    Aims: To determine the prevalence, characteristics of EM activities, the relationship between level of activity and mode of ventilation and adherence rate of EM protocol.

    Background: Mobilizing ICU patients remains a challenge, despite its safety, feasibility and positive short-term outcomes.

    Design: A cross-sectional point prevalence study.

    Methods: All patients who were eligible and admitted to the adult ICUs during March 2018 were recruited. Data were analysed by using the Statistical Package for Social Sciences version 24 for Windows.

    Results: The prevalence of EM practice was 65.6%. The most frequently reported avoidable and unavoidable factors inhibit mobility were deep sedation and vasopressor infusion, respectively. Level II of activity was the most common level of activity performed in ICU patients. The invasive ventilated patient had 12.53 the odds to stay in bed as compared to non-invasive ventilated patient. An average adherence rate of EM protocol was 52.5%.

    Matched MeSH terms: Respiration, Artificial*
  19. Leung CHC, Lee A, Arabi YM, Phua J, Divatia JV, Koh Y, et al.
    Ann Am Thorac Soc, 2021 08;18(8):1352-1359.
    PMID: 33284738 DOI: 10.1513/AnnalsATS.202008-968OC
    Rationale: There are limited data on mechanical discontinuation practices in Asia. Objectives: To document self-reported mechanical discontinuation practices and determine whether there is clinical equipoise regarding protocolized weaning among Asian Intensive Care specialists. Methods: A survey using a validated questionnaire, distributed using a snowball method to Asian Intensive Care specialists. Results: Of the 2,967 invited specialists from 20 territories, 2,074 (69.9%) took part. The majority of respondents (60.5%) were from China. Of the respondents, 42% worked in intensive care units (ICUs) where respiratory therapists were present; 78.9% used a spontaneous breathing trial as the initial weaning step; 44.3% frequently/always used pressure support (PS) alone, 53.4% intermittent spontaneous breathing trials with PS in between, and 19.8% synchronized intermittent mandatory ventilation with PS as a weaning mode. Of the respondents, 56.3% routinely stopped feeds before extubation, 71.5% generally followed a sedation protocol or guideline, and 61.8% worked in an ICU with a weaning protocol. Of these, 78.2% frequently always followed the protocol. A multivariate analysis involving a modified Poisson regression analysis showed that working in an ICU with a weaning protocol and frequently/always following it was positively associated with an upper-middle-income territory, a university-affiliated hospital, or in an ICU that employed respiratory therapists; and negatively with a low-income or lower-middle-income territory or a public hospital. There was no significant association with "in-house" intensivist at night, multidisciplinary ICU, closed ICU, or nurse-patient ratio. There was heterogeneity in agreement/disagreement with the statement, "evidence clearly supports protocolized weaning over nonprotocolized weaning." Conclusions: A substantial minority of Asian Intensive Care specialists do not wean patients in accordance with the best available evidence or current guidelines. There is clinical equipoise regarding the benefit of protocolized weaning.
    Matched MeSH terms: Respiration, Artificial*
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