IEEE Open Journal of Engineering in Medicine and Biology最新文献

{"title":"Semantic Explanation for Malaria Diagnosis: Comparing Human and Machine Generated Annotations for Plasmodium Species and Life-Stage Features","authors":"Kamal B. Jillahi;Zainab S. Usman;Charles Nche","doi":"10.1109/OJEMB.2026.3690482","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3690482","url":null,"abstract":"<italic>Goal</i>: Accurate detection of malaria parasites using convolutional neural networks (CNNs) relies heavily on the quality of training annotations, yet creating quality annotations is both time-consuming and difficult to scale in high-burden, resource-limited settings. To address this challenge, we propose a method of annotating thin-smear blood images for the semantic segmentation of <italic>Plasmodium</i> species, their developmental stages. Using a balanced collection of images from the Malaria Parasite Image Database, we trained identical SegNet models under three matched annotation regimes: expert manual labeling, SegNet-Only, and SegNet+Ontology where predictions are refined through biomedical ontological reasoning. Model performance was assessed not only for segmentation quality but also for how well each approach captured biologically meaningful information and for its interpretability as judged by clinicians. The proposed method produced results comparable to those achieved by expert annotations and clearly outperformed the baseline SegNet-only model in terms of biological consistency and clinical trustworthiness. The method successfully filtered out 5.7% of invalid AI-generated annotations by identifying semantic contradictions, ensuring the final training dataset adhered strictly to established biological constraints. Clinicians found the outputs from the proposed model nearly as reliable and understandable as those generated from expert annotations. These findings show that embedding formal biomedical knowledge into the annotation process can substantially reduce the cost and effort of creating training data while maintaining diagnostic accuracy and interpretability.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"196-202"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11506310","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148171761","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Applications of Deep Learning for Glottal Area Segmentation and Glottal Area Waveform Feature Computation","authors":"Ying-Chang Wu;Sheng-Fu Liang;Ming-Chi Cheng;Hui-Chen Su;Cheng-Ming Hsu","doi":"10.1109/OJEMB.2026.3684089","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3684089","url":null,"abstract":"<italic>Goal:</i> Analysis of the glottal area during vocal fold vibration has gained increasing attention. However, traditional analysis requires manual, frame-by-frame glottal area annotation to compute the glottal area waveform, a time-consuming, and error-prone process. <italic>Methods:</i> This study proposes an automated system for glottal area segmentation and glottal area waveform feature extraction from 36 videostroboscopy recordings of 23 patients with vocal fold nodules. The system integrates YOLO and U-Net architecture for glottis detection and segmentation. Subject-independent 5-fold cross-validation was performed on 5017 annotated frames. <italic>Results:</i> The system achieved an average Intersection over Union of 92.8%, and a Dice Similarity Coefficient of 95.8%, substantially outperforming thresholding and edge-based baselines. Computation time was reduced by 27.7 -folds compared with manual method. Applied to 14 patients undergoing voice treatment, the system detected consistent trends in glottal area dynamics post-treatment. <italic>Conclusion:</i> The system enhances efficiency and accuracy of glottal area waveform analysis and demonstrates clinical utility for laryngeal assessment.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"158-164"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11481763","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147796161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cuffless Noninvasive Continuous Blood Pressure Monitoring Using Superficial Temporal Arterial Tonometry","authors":"Ge Zhu;Zifan Jiang;Gary Strangman;Yihao Zheng;Quan Zhang","doi":"10.1109/OJEMB.2026.3667451","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3667451","url":null,"abstract":"<italic>Objective:</i> Continuous monitoring of blood pressure (BP) is a key parameter for cardiovascular assessment and hemodynamics monitoring. Current noninvasive methods are limited by frequent calibration, motion and environmental artifacts, and delayed response to rapid BP changes. In perioperative and critical-care settings, even short-duration hypotensive episodes and rapid BP lability have been associated with adverse outcomes, motivating technologies with high temporal fidelity. This study introduces a noninvasive blood pressure monitoring technique using superficial temporal artery tonometry (STAT), which employs a biomechanics-based transfer function to improve accuracy, reduce calibration requirements, and detect rapid BP changes in dynamic conditions. <italic>Methods:</i> Twenty-nine recording sessions of continuous BP monitoring were collected in human subjects (<italic>n</i> <inline-formula><tex-math>$=$</tex-math></inline-formula> 10) during rest and during handgrip-induced BP fluctuations. Measurements were recorded simultaneously using the STAT method and compared to a noninvasive reference device (Finapres/Finometer volume-clamp) and Pulse Transit Time (PTT) baseline (derived from timing features) method. <italic>Results:</i> Using the Finapres/Finometer as a noninvasive reference, our method achieved a mean absolute difference (MAD) of 4.8 <inline-formula><tex-math>$ pm $</tex-math></inline-formula> 2.2 mmHg during rest and 6.5 <inline-formula><tex-math>$ pm $</tex-math></inline-formula> 3.4 mmHg during handgrips, significantly outperforming PTT, especially under dynamic conditions. <italic>Conclusion:</i> BP monitoring with STAT and its biomechanics-based transfer function achieved improved detection of rapid BP fluctuations, and higher accuracy than PTT under dynamic conditions. <italic>Significance:</i> STAT with biomechanics-based modeling enables real-time, robust noninvasive BP monitoring, overcoming calibration, motion, and detection limitations of current methods.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"113-118"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11408199","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147606247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Discrete Hemodynamic Control System: Proof-of-Concept In-Vivo Study in Canine Heart Failure Using a Pulmonary Artery Catheter","authors":"Yasuyuki Kataoka;Kazunori Uemura;Takuya Nishikawa;Yukiko Fukuda;Jon Peterson;Kei Sato;Hiroki Matsushita;Hidetaka Morita;Yuta Nakamura;Masahiro Otake;Kenta Ohba;Nana Hiraki;Keita Saku;Mitsuji Sampei;Joe Alexander;Kenji Sunagawa","doi":"10.1109/OJEMB.2026.3723319","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3723319","url":null,"abstract":"<italic>Objective:</i> Managing heart failure requires simultaneous regulation of mean arterial pressure, cardiac output, and left atrial pressure, which is challenging due to complex cardiovascular interactions and limited monitoring. This study presents a proof-of-concept in-vivo evaluation of a discrete two-degree-of-freedom hemodynamic control system designed to regulate these three hemodynamic variables through titration of cardiovascular interventions under pulmonary artery catheter monitoring. <italic>Results:</i> Across five consecutive trials in three canine models of heart failure induced by tachycardia pacing, the cohort-averaged mean arterial pressure, cardiac output, and left atrial pressure were each within <inline-formula><tex-math>$pm$</tex-math></inline-formula>10% of their respective targets when evaluated using the final three intervention measurements, with absolute percentage errors decreasing from 16.8% to 9.0%, 23.4% to 3.8%, and 87.5% to 5.5%, respectively. In a more severely complicated heart failure model with coronary embolization, outcomes revealed control limitation primarily due to pharmacological resistance, highlighting the importance of choosing the appropriate target value. <italic>Conclusions:</i> This proof-of-concept in-vivo study demonstrates the feasibility of implementing discrete two-degree-of-freedom hemodynamic control under pulmonary artery catheter-based monitoring and phlebotomy-mediated volume removal in anesthetized canine models of tachycardia-pacing-induced heart failure. Further studies are required to evaluate the effects of inter-subject variability and clinical generalizability.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"332-340"},"PeriodicalIF":3.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11652919","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149133706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Automated Framework for Pose-Sequence Analysis of Spontaneous Movements in Preterm Infants","authors":"Sofia Sigismondi;Sara Uccella;Chiara Tacchino;Luca Ramenghi;Lino Nobili;Francesca Odone;Maura Casadio;Matteo Moro","doi":"10.1109/OJEMB.2026.3735159","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3735159","url":null,"abstract":"<italic>Goal:</i> Spontaneous movement analysis is crucial for early neuromotor assessment, yet objective, unobtrusive, and scalable tools remain limited. This study investigates an automated video-based framework for characterizing spontaneous movements in preterm infants. <italic>Methods:</i> Videos of 142 infants at term-equivalent age were analyzed using markerless two-dimensional pose estimation. Pose configurations were clustered into a pose dictionary, and recordings were represented as temporal sequences of key poses from which movement parameters were derived. Infants with typical development (TD) were compared with those with cerebral palsy (CP) and developmental delay (DD) stratified into low and high motor severity. <italic>Results:</i> Compared with TD, CP and DD–high showed significantly lower pose transition (median: 0.38 and 0.42 vs 0.50 transitions/s) and accumulated fewer unique poses over time, while CP also showed lower pose variability (median: 0.79 vs 0.87). <italic>Conclusions:</i> The framework characterizes pronounced neuromotor impairments and may provide an objective approach for early motor characterization.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"355-361"},"PeriodicalIF":3.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11695093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149188292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmented State-Space Modeling and Control of Latent Arousal States Under Inhibitory and Excitatory Conditions","authors":"Hamid Fekri Azgomi;Anan Yaghmour;Rose T. Faghih","doi":"10.1109/OJEMB.2026.3672470","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3672470","url":null,"abstract":"<italic>Goal:</i> In modern high-stress environments, effectively regulating cognitive arousal, through enhancement to boost engagement or inhibition to manage excessive stress, is essential for maintaining mental well-being and optimizing human performance. Hence, this study extends existing state-space models by integrating time-varying parameters and disturbance inputs for enhanced representation of arousal dynamics inferred from skin conductance. <italic>Methods:</i> We augmented nominal models with time-varying parameters, then developed a recursive Bayesian estimator for state tracking. Simulation-based validation was performed using skin conductance data from six participants, drawn from an experimental dataset of noninvasive wrist-worn physiological recordings acquired during cognitive stress and relaxation tasks. Adaptive and robust control architectures were designed for closed-loop regulation of latent arousal states. <italic>Results:</i> Simulations based on experimental data showed that both controllers outperformed static methods. On average, under inhibitory and excitatory conditions, the adaptive controller achieved average RMSE reductions of 26.9% and 51.6%, respectively, while the robust controller achieved reductions of 16.0% and 23.4%. In complex multi-step tracking, the adaptive controller reduced average RMSE by 33.7% and control effort by 18.5%; similarly, the robust controller reduced RMSE by 32.6% and control effort by 15.1%. <italic>Conclusion:</i> These findings demonstrate that adaptive and robust control strategies can reliably manage dynamic arousal regulation, offering potential for real-world neuroadaptive systems supporting human performance and well-being.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"128-138"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11429597","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shared and Individual Resting-State MEG Network Signatures of Tinnitus Revealed by Holistic Graph Learning","authors":"Payam S. Shabestari;Harry H. Behjat;Dimitri Van De Ville;Christopher R. Cederroth;Niklas K. Edvall;Adrian Naas;Tobias Kleinjung;Patrick Neff","doi":"10.1109/OJEMB.2026.3690604","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3690604","url":null,"abstract":"Tinnitus, the perception of sound without an external source, affects many individuals, yet its impact on the brain’s functional connectome remains underexplored. Traditional functional connectivity (FC) methods, such as Pearson correlation, phase lag index, and coherence, rely on pairwise comparisons between activity of macro-scale brain regions, limiting holistic characterization. We used an approach that estimates the entire connectivity structure by analyzing all time-courses simultaneously, robust even for short recordings and suitable for real-time applications. Using resting-state MEG from tinnitus patients and controls, learned connectomes outperformed correlation-based ones in fingerprinting individuals across test/retest. Group analyses revealed altered FC across multiple frequency bands, impacting default mode, auditory, visual, and salience networks, indicating large-scale reorganization. Tinnitus exhibited highly individualized whole-brain FC profiles, highlighting the importance of individual variability and paving the way for personalized models to optimize patient-specific interventions.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"203-213"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11506300","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148171523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"FPGA-Enabled, Smart Implants: A Path to Personalized Healthcare","authors":"Christos Strydis;David Veselka;Job van der Kleij;Muhammad Ali Siddiqi","doi":"10.1109/OJEMB.2026.3720369","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3720369","url":null,"abstract":"<italic>Goal:</i> Contrary to the conventional view that Field-Programmable Gate Arrays (FPGAs) are poorly suited to the stringent energy and resource constraints of Implantable Medical Devices (IMDs), this work investigates their potential to improve computational performance and energy efficiency in this domain. We propose heterogeneous CPU–FPGA systems as a means to support the growing demand for embedded AI in next-generation IMDs for intelligent and personalized healthcare. <italic>Methods:</i> We evaluated heterogeneous CPU–FPGA architectures against CPU-only configurations across representative AI-driven neural and security IMD workloads. <italic>Results:</i> FPGAs achieved lower execution latency and improved energy efficiency than CPU-based implementations in computationally intensive neural workloads, despite higher instantaneous power consumption in some cases due to parallel execution. In low-duty-cycle security workloads where aggressive power gating is feasible, FPGA- and CPU-based solutions exhibited comparable overall performance. <italic>Conclusions:</i> These findings demonstrate that heterogeneous CPU–FPGA systems can integrate advanced AI and security algorithms into IMDs while satisfying battery-life, power-density, real-time processing, and practical implantability constraints relevant to long-term medical-device deployment, enabling intelligent, personalized, and secure implantable healthcare.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"291-300"},"PeriodicalIF":3.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11640970","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Introducing a Comprehensive Framework for Synthetic ECG Validation","authors":"Beatrice Zanchi;Giuliana Monachino;Matteo Metaldi;Giulio Conte;Stéphane Meystre;Francesca D. Faraci","doi":"10.1109/OJEMB.2026.3716291","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3716291","url":null,"abstract":"<italic>Goal:</i> While Generative AI addresses data scarcity and privacy in healthcare, the lack of standardized validation protocols hinders the deployment of safe and trustworthy AI. This study introduces a comprehensive framework for rigorously evaluating the authenticity and fidelity of synthetic biosignals, addressing the critical need for medical data quality assurance. <italic>Methods:</i> The framework was validated using synthetic electrocardiograms (ECG) for Brugada Syndrome generated via Generative Adversarial Networks (GANs). The protocol integrates four complementary analytics layers: (1) visual morphological inspection; (2) statistical assessment of clinical biomarkers (e.g., QT-interval); (3) computational similarity metrics (e.g. MSE, DTW) to assess distributional fidelity; and (4) a human-centered validation where blinded expert cardiologist scored clinical realism. <italic>Results:</i> Results demonstrated high statistical fidelity and morphological realism. Quantitative analysis showed no statistically significant differences in key clinical features between real and synthetic distributions. An expert cardiologist achieved near 50% accuracy (random chance) in distinguishing real from synthetic signals, consistent with the high authenticity of the generated data. <italic>Conclusions:</i> This framework proposes a comprehensive methodology for validating generative healthcare models, intended as an initial step toward standardization in the field. By ensuring high-fidelity data generation, this approach supports robust predictive modeling and AI-based decision support, facilitating privacy-sensitive clinical research.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"301-307"},"PeriodicalIF":3.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11619560","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148836802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Accurate and Generalizable Protein-Ligand Binding Affinity Prediction With Geometric Deep Learning","authors":"Krinos Li;Xianglu Xiao;Zijun Zhong;Guang Yang","doi":"10.1109/OJEMB.2026.3667030","DOIUrl":"https://doi.org/10.1109/OJEMB.2026.3667030","url":null,"abstract":"<italic>Goal:</i> Protein-ligand binding complexes are ubiquitous and essential to life. Protein-ligand binding affinity prediction (PLA) quantifies the binding strength between ligands and proteins, providing crucial insights for discovering and designing potential candidate ligands. While recent advances have been made in predicting protein-ligand complex structures, existing algorithms for interaction and affinity prediction suffer from a sharp decline in performance when handling ligands bound with novel unseen proteins. <italic>Methods:</i> We propose IPBind, a geometric deep learning-based computational method, enabling robust predictions by leveraging interatomic potential between complex's bound and unbound status. <italic>Results:</i> Experimental results on widely used binding affinity prediction benchmarks demonstrate the effectiveness and universality of IPBind. Meanwhile, it provids atom-level insights into prediction. <italic>Conclusions:</i> This work highlight the advantage of leveraging machine learning interatomic potential for predicting protein-ligand binding affinity.","PeriodicalId":33825,"journal":{"name":"IEEE Open Journal of Engineering in Medicine and Biology","volume":"7 ","pages":"86-93"},"PeriodicalIF":2.9,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11406890","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}