Changes In Dynamic Behavior Research Articles

Hopf bifurcation of the model with terms of two time-delays and delay-dependent parameter based on the theory of crossing curves.

A three-layer prey-predator model with two time-delays and one delay-dependent parameter is established in this paper. To begin, the paper calculates the conditions for each population in the model to maintain the quantity stable and Hopf bifurcation when τ = τ = 0, τ = 0 , τ ≠ 0, τ is in the stable interval, and τ > 0. The crossing curves, their type, and the direction of the crossing curves are then obtained using the crossing curve method, which is composed of the threshold values of the dynamic behavior change on the two time-delays plane when τ , τ > 0. The real data from the forage grass-Ochotona curzoniae-Buteo hemilasius food chain is used to conduct an empirical study of the model. When τ , τ > 0, the feasible region of the crossing curves is open-ended, and the model's crossing curves on the ( τ , τ ) plane are truncated. This indicates that the model's threshold distribution of dynamic behavior change is a regular curve made of several curves. The simulation using the time-delay value on the crossing curves shows that the model produces different dynamic behaviors such as stability, bifurcation, and chaos depending on the time-delay value on both sides of the curves. The critical values of dynamic behavior change are time-delay values on the crossing curves. The empirical study shows that increasing Ochotona curzoniae's environmental capacity can easily cause Hopf bifurcation of the system. At this time, the number of each population in the Plateau ecosystem constantly fluctuates, and Ochotona curzoniae is vulnerable to extinction.

Work-family conflict as antecedent to workplace deviance: a study among bankers

Hinged on the Job Demand-Resource model and Source Attribution Theory, this study assessed the relationship between work-family conflict (family-towork and work-to-family conflicts) and workplace deviant behaviours (organizational and interpersonal deviance) among bank employees in Ghana. The quantitative two-wave longitudinal design was used, and data collected from 301 respondents. Unique self-generated codes were used to match the responses from each respondent in both times. Work-to-family conflict predicted interpersonal deviant behaviour in both Time 1 and Time 2, and organizational deviant behaviour in Time 2 but not in Time 1. Also, family-to-work conflict predicted interpersonal deviant behaviour in both Time 1 and Time 2 and also predicted organizational deviant behaviour in Time 1 only. This is one of the few empirical studies assessing the relationship between work-family conflict and workplace deviance, and in particular, among bankers. Assessing such relationships in this study over time has shown that variations in nature of the hypothesized relationships could be a result of extraneous variables (dynamic employee behaviour or environmental changes) not anticipated. Banks must pay particular attention to the job demands imposed on employees and again take interest in the out-of-job experiences of staff that could affect their job performance and involvement in deviant behaviours.
 Keywords: Work-family conflict; workplace deviance; bankers; Ghana; antecedents

Fuzzy decoupled-states multi-model identification of gas turbine operating variables through the use of their operating data

Practically the rotating machines degradation, such as gas turbines, is due to the quality of construction and online operation of their dynamic state models, of different physical phenomena affecting these machines which cause their total malfunction. To maintain their stable operation, it is essential to correctly describe these real dynamic behaviors by reliable and robust representations, by models that can be used in monitoring and diagnostics. To achieve the performance objectives in terms of security, reliability, availability, and operating safety, this work proposes the development of a fuzzy multi-model identification approach with states decoupled from the operating variables, uploaded for monitoring a TITAN 130 turbine. This fuzzy multi-model structure with decoupled states is of interest for the monitoring of industrial systems because it adapts to the different changes in dynamic behavior of the system, makes it possible to represent the nonlinear behavior of the real system in a linear multi-model form without loss of information. In this work, through the different implementations and obtained results, this approach clearly shows how the gas turbine dynamics were reproduced when using the proposed fuzzy multi-models, thus allowing better performance when exploiting it for the synthesis of the faults diagnosis strategy for this rotating machine.

Dynamical Behavior of Disordered Regions in Disease-Related Proteins Revealed by Quasielastic Neutron Scattering.

Background and Objectives: Intrinsically disordered proteins (IDPs) and proteins containing intrinsically disordered regions (IDRs) are known to be involved in various human diseases. Since the IDPs/IDRs are fluctuating between many structural substrates, the dynamical behavior of the disease-related IDPs/IDRs needs to be characterized to elucidate the mechanisms of the pathogenesis of the diseases. As protein motions have a hierarchy ranging from local side-chain motions, through segmental motions of loops or disordered regions, to diffusive motions of entire molecules, segmental motions, as well as local motions, need to be characterized. Materials and Methods: Combined analysis of quasielastic neutron scattering (QENS) spectra with the structural data provides information on both the segmental motions and the local motions of the IDPs/IDRs. Here, this method is applied to re-analyze the QENS spectra of the troponin core domain (Tn-CD), various mutants of which cause the pathogenesis of familial cardiomyopathy (FCM), and α-synuclein (αSyn), amyloid fibril formation of which is closely related to the pathogenesis of Parkinson’s disease, collected in the previous studies. The dynamical behavior of wild-type Tn-CD, FCM-related mutant Tn-CD, and αSyn in the different propensity states for fibril formation is characterized. Results: In the Tn-CD, the behavior of the segmental motions is shown to be different between the wild type and the mutant. This difference is likely to arise from changes in the intramolecular interactions, which are suggested to be related to the functional aberration of the mutant Tn-CD. In αSyn, concerted enhancement of the segmental motions and the local motions is observed with an increased propensity for fibril formation, suggesting the importance of these motions in fibril formation. Conclusions: Characterization of the segmental motions as well as the local motions is thus useful for discussing how the changes in dynamical behavior caused by the disease-related mutations and/or environmental changes could be related to the functional and/or behavioral aberrations of these proteins.

Global sensitivity analysis of asymmetric energy harvesters

Parametric variability is inevitable in actual energy harvesters. It can significantly affect crucial aspects of the system performance, especially in harvesting systems that present geometric parameters, material properties, or excitation conditions that are susceptible to small perturbations. This work aims to develop an investigation to identify the most critical parameters in the dynamic behavior of asymmetric bistable energy harvesters with nonlinear piezoelectric coupling, considering the variability of their physical and excitation properties. For this purpose, a global sensitivity analysis based on orthogonal variance decomposition, employing Sobol indices, is performed to quantify the effect of the harvester parameters on the variance of the recovered power. This technique quantifies the variance concerning each parameter individually and collectively regarding the total variation of the model. The results indicate that the frequency and amplitude of excitation, asymmetric terms and electrical proprieties of the piezoelectric coupling are the most critical parameters that affect the mean power harvested. It is also shown that the order of importance of the parameters can change according to the stability of the harvester’s dynamic response. In this way, a better understanding of the system under analysis is obtained since the study allows the identification of vital parameters that rule the change of dynamic behavior and therefore constitutes a powerful tool in the robust design, optimization, and response prediction of nonlinear harvesters.

Computational compensatory mutation discovery approach: Predicting a PARP1 variant rescue mutation

The prediction of protein mutations that affect function may be exploited for multiple uses. In the context of disease variants, the prediction of compensatory mutations that reestablish functional phenotypes could aid in the development of genetic therapies. In this work, we present an integrated approach that combines coevolutionary analysis and molecular dynamics (MD) simulations to discover functional compensatory mutations. This approach is employed to investigate possible rescue mutations of a poly(ADP-ribose) polymerase 1 (PARP1) variant, PARP1 V762A, associated with lung cancer and follicular lymphoma. MD simulations show PARP1 V762A exhibits noticeable changes in structural and dynamical behavior compared with wild-type (WT) PARP1. Our integrated approach predicts A755E as a possible compensatory mutation based on coevolutionary information, and molecular simulations indicate that the PARP1 A755E/V762A double mutant exhibits similar structural and dynamical behavior to WT PARP1. Our methodology can be broadly applied to a large number of systems where single-nucleotide polymorphisms have been identified as connected to disease and can shed light on the biophysical effects of such changes as well as provide a way to discover potential mutants that could restore WT-like functionality. This can, in turn, be further utilized in the design of molecular therapeutics that aim to mimic such compensatory effect.

Vibration analysis and control of cracked beam using finite element method by using ANSYS

PurposeThe purpose of this paper is to develop an organized structure for damage detection of a cracked cantilever beam using finite element method and experimental method technique.Design/methodology/approachDue to presence of cracks the dynamic characteristics of structure change. The change in dynamic behavior has been used as one of the criteria of fault diagnosis for structures. Major characteristics of the structure which undergo change due to presence of crack are: natural frequencies, the amplitude responses due to vibration and the mode shapes. Therefore, an attempt has been made to formulate a smart technique for minimizing the amplitude of vibration for crack cantilever beam structures. In the analysis both single and double cracks are taken into account.FindingsThe results of the active vibration control experiments proved that piezoelectric sensor/actuator pair is an effective sensor and actuator configuration for active vibration control to reduce the amplitude of vibration for closed-loop system.Originality/valueIt is necessary that structures must safely work during its service life, but damages initiate a breakdown period on the structures which directly affect the industrial growth. It is a recognized fact that dynamic behavior of structures changes due to presence of crack. It has been observed that the presence of cracks in structures or in machine members leads to operational problem as well as premature failure.

Communication of Slovak eco-innovation companies with social media users

Social media is widespread worldwide and firmly defined in today's communication. Available resources point to dynamic changes in consumer behavior, to which even ecologically oriented business entities must respond. Therefore, it is appropriate and necessary to look for innovative solutions that will contribute to improving the communication of eco-innovative businesses with their followers on social communication platforms. The aim of the paper is to map and describe the current state of communication of the responded Slovak eco-innovation companies with social media users. The communities that are emerging on social media are the driving force behind today's market environment. Communities can be talked about in connection with the pressure they exert on eco-innovation businesses, entities and other business areas. At the core, the authors focus on the interpretation of partial results from their own pilot survey, which serves as an input survey for mapping the current communication and will be a key basis for subsequent research. The interpreted findings from the survey come from a quantitative survey using a standardized questionnaire, which was answered by a total of 142 respondents, who represent representatives of Slovak eco-innovation business entities. From the author's research, we can define which digital platforms use subjects to communicate with their followers, how often they communicate with them, through what type of contributions and with what frequency they publish contributions. The results indicate reserves in the given issue. For this reason, further research and education of subjects is important. The limits of the investigation are in a smaller number of business entities and in the possibility that business entities did not provide true information. The authors of the article did not come to the conclusion that someone would carry out a similar survey within the Slovak eco-innovation entities, and therefore they point to the results of their own pilot survey. Eco-innovation entities do not currently have information on the communication process with their followers on social media. The authors consider the interpreted results from the pilot survey to be original and necessary due to the absence of marketing statistics, which would subsequently help businesses to set up the right online marketing strategy.

Modeling of the Bridge under the Two Vehicles Moving in Opposite Direction with Parametric Study of Bridge Dynamics

Abstract: To ensure the reliability and safety of bridges, one of the main important parameter in design and health assessment is normalized displacement in critical loading condition. It is important to ensure accuracy of determination of normalized displ acement in different condition. The aim of this study is to explore the dynamic response of bridge subjected to two vehicles travelling in reverse direction. Moving masses (vehicles) are assumed to start at same time with same speed, then time is delayed f or one of the moving mass and then speed of both moving masses is changed. Normalized mid span response is lesser than that for single moving mass model and highest response for two ways traffic occurs for velocity ratio 0.6. The change of dynamic behavior is remarkable with change in highest normalized mid span response for change in traffic conditions like two way traffic, change in velocity and time of start of vehicles.

Qualitative analysis of an eco-epidemiological model with a role of prey and predator harvesting

Abstract The present study deals with the dynamical response of an eco-epidemiological model consisting of prey and predator species having infection in prey population. The inclusion of prey refugia is taken into account to avoid predator attack. The entire prey population is divided into two parts: healthy prey which are capable of reproducing following the logistic law and infected prey which is removed by predation or death before having the possibility of reproducing. Also we have considered the role of harvesting of the susceptible prey and the predator. For biological validity of the model, positivity and boundedness of the system are studied. The dynamical behaviour of the model has been analyzed elaborately. The stability aspects of the basic model around the infection free state, predator free state and the infected steady state from a local as well as a global perspective are studied. The main aim is to study the role of harvesting on the dynamics of disease propagation and/or eradication. By considering harvesting in susceptible prey and predator population, our study gives a new direction to eco-epidemiological model. Changes in local and global dynamical behaviour in terms of important system parameters are obtained. By the numerical simulation Hopf-bifurcation and the stable and unstable behaviour of the system due to harvesting and rate of infection have been observed.

Changes in dynamic mechanical behavior of carbon fiber reinforced polymer laminates under multiple low energy impacts

Composite laminates used in aircraft structures are easily subjected to multiple impacts during their service period. The detailed analysis of impact responses could reflect the stiffness of composite structure. Nevertheless, the impact response of laminates with a large width-thickness ratio is quite different from that of ordinary laminates. The deflection could reach several times the thickness during the impact. The present paper performed an experimental study using drop weight equipment to investigate the changes in dynamic mechanical behavior of carbon fiber reinforced polymer laminates during multiple low energy impacts. Three kinds of impact energy levels of 5, 10, and 15 J were applied for the single impact event. The specimens impacted at 5 and 10 J were then subjected to subsequent impacts in order to explore the differences between single and multiple strikes with the same total impact energy. The global mechanical responses during each impact procedure were recorded and analyzed by the changes of impact force, contact time, peak energy moment, energy absorption, and displacement after every single impact. Although the first strike had introduced damages into the plates, the peak force and maximum displacement increased unexpectedly rather than decreased during the second strike. Meanwhile, the damage was evaluated using ultrasonic C-scan and visual inspection. The results indicated that the multiple impacts did not produce as much damage as the first strike. Short matrix cracks were observed at the edge of the dent except for the single impact with 5 J energy.

Impact of information technology and knowledge sharing on circular food supply chains for green business growth

AbstractRapid and dynamic changes in environment, technologies, consumer behavior, policy making, and climate are putting extra pressure to food supply chain, especially in terms of efficiently manage food security, food surplus, food loss, and waste. These changes directly affect food supply chain negatively. Thus, transition into more circular approach for green business growth in food supply chains is a necessity. One way to reduce this negativity is to ensure the share of information along the chain. With this context, sharing information and knowledge among the food supply chain can facilitate practices from a circularity and green perspectives. Hence, this research focuses on understanding and revealing knowledge‐sharing networks challenges, barriers, and benefits across every food supply chain layer, presenting tangible contributions to improve traceability in circularity perspectives with refuse, rethink, reduce, reuse, repair, refurbish, remanufacture, repurpose, recycle, and recover challenges. Therefore, and to provide a green business growth, this study examines the practice of knowledge sharing among real‐life industry food stakeholders in the meat sector regarding their dimensions, what type of knowledge is shared and whether there are differences among specific groups of food stakeholders for the knowledge sharing. The aim of this research is to generate a validated conceptual framework to reveal how information technologies contributes to a more efficient knowledge sharing practices, hence, to impact the enhancement of efficient circular food supply chains for green business growth.

Assessment of Substrate and TBC Damage Effects on Resonance Frequencies for Blade Health Monitoring

The reliability of critical aircraft components continues to shift towards onboard monitoring to optimize maintenance scheduling, economy efficiency and safety. Therefore, the present study investigates changes in dynamic behavior of turbine blades for the detection of defects, with focus on substrate cracks and TBC spallation as they relate to vibration modes 1 to 6. Two‐dimensional and three-dimensional finite element simulation is used. The results indicate that TBC spallation reduces natural frequencies due to the ensuing hot spot and overall increase in temperature, leading to drops in blade stiffness and strength. Cracks cause even larger frequency shifts due to local plastic deformation at the crack that changes the energy dissipation behavior. Mode 1 vibration shows the largest shifts in natural frequencies that best correlate to the size of defects and their position. As such, it may be most appropriate for the early assessment of the severity and location of defects.

Evaluation of electrocardiogram-gated computed tomography angiography to quantify changes in geometry and dynamic behavior of the iliac artery after placement of the Gore Excluder Iliac Branch Endoprosthesis.

The GORE® EXCLUDER® Iliac Branch Endoprosthesis (IBE) is designed to treat iliac aneurysms with preservation of blood flow through the internal iliac artery (IIA). Little is known about the influence of IBE placement on the IIA geometry. This study aimed to provide detailed insights in the dynamic behavior and geometry of the common iliac artery (CIA) and IIA trajectory and how these are influenced after treatment with an IBE. Pre- and postoperative electrocardiogram-gated computed tomography angiography (ECG-gated CTA) scans were acquired in a prospective study design and analyzed with in-house written algorithms designed for aorto-iliac and endoprosthesis deformation evaluation. Cardiac pulsatility-induced motion patterns and pathlengths were computed by tracking predefined locations on the aorto-iliac tract. Centerlines through the CIA-IIA trajectory were used to investigate the static and dynamic geometry, including curvature, torsion, length and Tortuosity Index (TI). Fourteen CIA-IIA trajectories were analyzed before and after IBE placement. Cardiac pulsatility-induced motion and pathlengths increased after IBE placement, especially at mid IIA and the first IIA bifurcation (P≤0.04). After IBE placement, static and dynamic curvature, length and TI decreased significantly (P<0.05). Furthermore, the average dynamic torsion increased significantly (P=0.030). The remaining geometrical outcomes were not statistically significant. The placement of an IBE device stiffens and straightens the CIA-IIA trajectory. Its relation with clinical outcome is yet to be investigated, which can be done thoroughly with the ECG-gated CTA algorithms used in this study.

Mitochondrial Adaptive Responses to Hypertriglyceridemia and Bioactive Lipids.

Significance: Altered plasma triglyceride metabolism and changes in dietary fatty acid types and levels are major contributors to the development of metabolic and cardiovascular diseases such as fatty liver disease, obesity, diabetes, and atherosclerosis. Lipid accumulation in visceral adipose tissue and ectopically in other organs, as well as lipid-induced redox imbalance, is connected to mitochondrial dysfunction in a range of oxidative stress-associated metabolic and degenerative disorders. Recent Advances: Successful mitochondrial adaptive responses in the context of hypertriglyceridemia and dietary bioactive polyunsaturated fatty acids contribute to increase body energy expenditure and reduce oxidative stress, thus allowing several cell types to cope with metabolic challenges and stresses. These responses include mitochondrial redox signaling, mild uncoupling, and changes in network dynamic behavior. Critical Issues: Mitochondrial bioenergetics and redox changes in a lipid overload context are relatively well characterized. However, the turning point between adaptive and maladaptive mitochondrial responses remains a critical issue to be elucidated. In addition, the relationship between changes in fusion/fission machinery and mitochondrial function is less well understood. Future Directions: The effective mitochondrial responses described here support the research for new drug design and diet or nutraceutical formulations targeting mitochondrial mild uncoupling and effective quality control as putative strategies for cardiometabolic diseases. Antioxid. Redox Signal. 36, 953-968.

Sparsity-assisted adaptive chirp mode decomposition and its application in rub-impact fault detection

The rub-impact is a familiar failure and its timely detection is vital to maintain the security of whole system. The change of dynamic behavior caused by rub-impact fault can be reflected by the fast-oscillating instantaneous frequency (IF) of the vibration signal. The recently developed adaptive chirp mode decomposition (ACMD) has exhibited satisfactory capability in extracting fast-oscillating IF. However, the ACMD is easily affected by the noise, which greatly limits its application scopes. To overcome this issue, a novel method named sparsity-assisted adaptive chirp mode decomposition (S-ACMD) is developed, which incorporates sparsity-assisted IF update scheme that fully exploits the sparse prior of fast-oscillating IF caused by rub-impact fault. Meanwhile, the parameter selection method for getting optimal results is described. The efficacy of the proposed S-ACMD is confirmed by the vibration signals from dynamic simulation and rotor test rig, and the results show that it has strong anti-noise ability and can accurately extract rub-impact fault related fast-oscillating IF even in noisy cases.

In-Network Neural Networks: Challenges and Opportunities for Innovation

The quest for self-driving networks poses growing pressure to manage network events at a nano-second scale. In this article, we make a case for leveraging programmable forwarding planes to achieve self-driving networks and respond to their dynamism in real time by in-network intelligence and without performing traffic steering/mirroring to centralized management solutions (intelligent or not). We briefly cover throughout the article preliminary ideas in the in-network neural networks field and discuss the technical challenges of running machine learning techniques entirely in the forwarding plane. We also highlight potential use cases of having an autonomous intelligent network capable of self-adapting to dynamic network behavior changes with minimal to no human intervention, including smart network telemetry, smart traffic engineering, real-time flow classification, and network tomography. We close with a roadmap of research opportunities enabled by distributed in-network intelligence in programma-ble forwarding planes.

Defect detection and localization in polymer composites based on drilling force signal by recurrence analysis

Recurrence analysis is a method for the investigation of dynamic behavior changes in a nonlinear time-series. In this study, the application of recurrence analysis methods for detecting and locating composite defects based on drilling signals are proposed. Defects are modelled as different diameter holes drilled inside a composite material. Two composite materials are tested: glass fiber reinforced plastic (GFRP) and carbon fiber reinforced plastic (CFRP). The smallest detectable defects are determined for both materials. Additionally, the most promising recurrence quantifications are proposed for defect detection and localization.

Online sequential ensembling of predictive fuzzy systems

Evolving fuzzy systems (EFS) have enjoyed a wide attraction in the community to handle learning from data streams in an incremental, single-pass and transparent manner. The main concentration so far lied in the development of approaches for single EFS models, basically used for prediction purposes. Forgetting mechanisms have been used to increase their flexibility, especially for the purpose to adapt quickly to changing situations such as drifting data distributions. These require forgetting factors steering the degree of timely out-weighing older learned concepts, whose adequate setting in advance or in adaptive fashion is not an easy and not a fully resolved task. In this paper, we propose a new concept of learning fuzzy systems from data streams, which we call online sequential ensembling of fuzzy systems (OS-FS). It is able to model the recent dependencies in streams on a chunk-wise basis: for each new incoming chunk, a new fuzzy model is trained from scratch and added to the ensemble (of fuzzy systems trained before). This induces (i) maximal flexibility in terms of being able to apply variable chunk sizes according to the actual system delay in receiving target values and (ii) fast reaction possibilities in the case of arising drifts. The latter are realized with specific prediction techniques on new data chunks based on the sequential ensemble members trained so far over time. We propose four different prediction variants including various weighting concepts in order to put higher weights on the members with higher inference certainty during the amalgamation of predictions of single members to a final prediction. In this sense, older members, which keep in mind knowledge about past states, may get dynamically reactivated in the case of cyclic drifts, which induce dynamic changes in the process behavior which are re-occurring from time to time later. Furthermore, we integrate a concept for properly resolving possible contradictions among members with similar inference certainties. The reaction onto drifts is thus autonomously handled on demand and on the fly during the prediction stage (and not during model adaptation/evolution stage as conventionally done in single EFS models), which yields enormous flexibility. Finally, in order to cope with large-scale and (theoretically) infinite data streams within a reasonable amount of prediction time, we demonstrate two concepts for pruning past ensemble members, one based on atypical high error trends of single members and one based on the non-diversity of ensemble members. The results based on two data streams showed significantly improved performance compared to single EFS models in terms of a better convergence of the accumulated chunk-wise ahead prediction error trends, especially in the case of regular and cyclic drifts. Moreover, the more advanced prediction schemes could significantly outperform standard averaging over all members’ outputs. Furthermore, resolving contradictory outputs among members helped to improve the performance of the sequential ensemble further. Results on a wider range of data streams from different application scenarios showed (i) improved error trend lines over single EFS models, as well as over related AI methods OS-ELM and MLPs neural networks retrained on data chunks, and (ii) slightly worse trend lines than on-line bagged EFS (as specific EFS ensembles), but with around 100 times faster processing times (achieving low processing times way below requiring milli-seconds for single samples updates).

Microstructural changes in human ingestive behavior after Roux-en-Y gastric bypass during liquid meals.

BACKGROUNDRoux-en-Y gastric bypass (RYGB) decreases energy intake and is, therefore, an effective treatment of obesity. The behavioral bases of the decreased calorie intake remain to be elucidated. We applied the methodology of microstructural analysis of meal intake to establish the behavioral features of ingestion in an effort to discern the various controls of feeding as a function of RYGB.METHODSThe ingestive microstructure of a standardized liquid meal in a cohort of 11 RYGB patients, in 10 patients with obesity, and in 10 healthy-weight adults was prospectively assessed from baseline to 1 year with a custom-designed drinkometer. Statistics were performed on log-transformed ratios of change from baseline so that each participant served as their own control, and proportional increases and decreases were numerically symmetrical. Data-driven (3 seconds) and additional burst pause criteria (1 and 5 seconds) were used.RESULTSAt baseline, the mean meal size (909.2 versus 557.6 kCal), burst size (28.8 versus 17.6 mL), and meal duration (433 versus 381 seconds) differed between RYGB patients and healthy-weight controls, whereas suck volume (5.2 versus 4.6 mL) and number of bursts (19.7 versus 20.1) were comparable. At 1 year, the ingestive differences between the RYGB and healthy-weight groups disappeared due to significantly decreased burst size (P = 0.008) and meal duration (P = 0.034) after RYGB. The first-minute intake also decreased after RYGB (P = 0.022).CONCLUSIONRYGB induced dynamic changes in ingestive behavior over the first postoperative year. While the eating pattern of controls remained stable, RYGB patients reduced their meal size by decreasing burst size and meal duration, suggesting that increased postingestive sensibility may mediate postbariatric ingestive behavior.TRIAL REGISTRATIONNCT03747445; https://clinicaltrials.gov/ct2/show/NCT03747445.FUNDINGThis work was supported by the University of Zurich, the Swiss National Fund (32003B_182309), and the Olga Mayenfisch Foundation. Bálint File was supported by the Hungarian Brain Research Program Grant (grant no. 2017-1.2.1-NKP-2017-00002).