Mode Control Research Articles

Combinatory glycoengineering of monoclonal antibodies and its application in cancer therapy: a narrative review.

The application of immunotherapy, especially in terms of recombinant monoclonal antibodies (mAbs), is a revolution in the pharmaceutical industry field. Glycosylation plays an essential role in the structures and functions of mAbs, which must be carefully monitored and designed throughout their entire lifespan to ensure safety and efficacy. This review aimed to summarize the current status of the glycoengineering of mAbs for providing reference for the pharmaceutical industry. The application of glycoengineering of mAbs in cancer therapy will also be discussed in this article. We searched the PubMed/MEDLINE database to identify studies published between 1970 and 2023 that investigated glycoengineering of recombinant mAbs and its applications. The major findings of these studies were summarized. This article reviews the relationship between glycosylation profiles and antibody-dependent cell-mediated cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), shelf-life, and other properties of mAbs. Furthermore, the rational design of glycosylation profiles provides solutions to the unmet needs of new drug development and biosimilar manufacturers. This review also emphatically describes various feasible strategies to optimize the glycosylation pattern in biomanufacturing reported in recent years, especially the approaches of combinatory glycoengineering explored in this field. Finally, we share examples of glycoengineering of mAbs applied in cancer therapy. Glycan modifications have been achieved through genetic and metabolic glycoengineering. A better understanding of the interplay between cells and the exogenous environment help the combinatorial strategy for glycoengineering in precise control mode. Furthermore, new high-tech approaches for glycoengineering are leading biological engineering and biotherapeutics to a new stage.

An Extended Continuation Power Flow Method for Static Voltage Stability Assessment of Renewable Power Generation-Penetrated Power Systems

The continuation power flow method (CPF) has been extensively used for obtaining the static voltage stability limit of power systems, which provides important guidance for the stable operation. However, the conventional CPF cannot account for the dynamic characteristics of renewable power generation, thus resulting in prominent errors for renewable power generation-penetrated power systems. In this paper, we investigate the static voltage stability assessment (SVSA) of power systems with high penetration of rgb0,0,0renewable power generation (RPG). An extended Jacobian matrix is firstly established by considering the dynamic characteristics of synchronous generators (SG) and renewable power generation in constant AC voltage control mode (CVRPG). Based on the extended Jacobian matrix, an extended CPF method is proposed for SVSA of the power system and a reactive power sensitivity index is proposed to indicate the voltage support capability of nodes. Simulation results show that the proposed extended CPF method has higher accuracy than conventional CPF in assessing the static voltage stability of power systems with high penetration of RPG. It is also revealed that that the voltage support capability of each node rises as the proportion coefficient is increases.

Development and Verification of Electrokinetic Injection Logical Control Mode in Microfluidic Device

Development and Verification of Electrokinetic Injection Logical Control Mode in Microfluidic Device

The Bi–O edge wavefront sensor

Context. Direct detection of exoplanets around nearby stars requires advanced adaptive optics (AO) systems. High-order systems are needed to reach a high Strehl ratio (SR) in near-infrared and optical wavelengths on future giant segmented-mirror telescopes (GSMTs). Direct detection of faint exoplanets with the European Southern Observatory (ESO) Extremely Large Telescope (ELT) will require some tens of thousands of correction modes. The resolution and sensitivity of the wavefront sensor (WFS) are key requirements for this science case. We present a new class of WFSs, the bi-orthogonal Foucault knife-edge sensors (or Bi–O edge), that is directly inspired by the Foucault knife-edge test. The idea consists of using a beam-splitter producing two foci, each of which is sensed by an edge with a direction orthogonal to the other focus. Aims. We describe two implementation concepts: The Bi–O edge sensor can be realised with a sharp edge and a tip-tilt modulation device (sharp Bi–O edge) or with a smooth gradual transmission over a grey edge (grey Bi–O edge). A comparison of the Bi–O edge concepts and the four-sided classical pyramid wavefront sensor (PWS) gives some important insights into the nature of the measurements. Methods. We analytically computed the photon noise error propagation, and we compared the results to end-to-end simulations of a closed-loop AO system. Results. Our analysis shows that the sensitivity gain of the Bi–O edge with respect to the PWS depends on the system configuration. The gain is a function of the number of control modes and the modulation angle. We found that for the sharp Bi–O edge, the gain in reduction of propagated photon noise variance approaches a theoretical factor of 2 for a large number of control modes and small modulation angle, meaning that the sharp Bi–O edge only needs half of the photons of the PWS to reach similar measurement accuracy. In contrast, the PWS is twice more sensitive than the Bi–O edge in the case of very low order correction and/or large modulation angles. Preliminary end-to-end simulations illustrate some of the results. The grey version of the Bi–O edge opens the door to advanced amplitude filtering, which replaces the need for a tip-tilt modulator while keeping the same dynamic range. We show that an additional factor of 2 in reduction of propagated photon noise variance can be obtained for high orders, such that the theoretical maximum gain of a factor of 4 in photon efficiency can be obtained. A diffractive Fourier model that accurately includes the effect of modulation and control modes shows that for the extreme AO (XAO) system configuration of the ELT, the overall gain will well exceed one magnitude in guide-star brightness when compared to the modulated PWS. Conclusions. We conclude that the Bi–O edge is an excellent candidate sensor for future very high order Adaptive Optics systems, in particular on GSMTs.

Event‐triggered model reference adaptive control system design for SISO plants using meta‐learning‐based physics‐informed neural networks without labeled data and transfer learning

SummaryThis paper examines the controllability of a novel Lyapunov‐based model reference adaptive control (MRAC) system designed with a meta‐learning‐based physics‐informed neural network (MLPINN) for linear and nonlinear single‐input and single‐output (SISO) plants without labeled data (MLPINN‐MRAC system). It is devised with the benefits of several techniques: the integration of the identification process in a training mode into an online control mode (straightforward design); no labeled data generation for online identification by a physics‐informed neural network; the prevention of degradation in tracking performance by meta‐learning, as the system triggers a meta‐learning process only when an error threshold detects the deterioration (high efficiency and the reduction of computation cost); quick adaptation to new inputs and an updated control input for each sub‐time span by transfer learning. It is worth noting that the frequency of the meta‐learning event detection significantly affects the step response stability of the nonlinear plant. To achieve a better quality of the stabilization, more frequent event detection is necessary for both beginning and end intervals in control. Sixteen triggering events are enough to shape the acceptable step response of the nonlinear plant, and 44 triggering events achieve the plant's desired step response with its minor modeling error. While, as for the linear plant, a single triggering event is sufficient to attain its tolerable step response and modeling error, implying that intensive event detection is not critical in the identification. It is obvious that the MLPINN‐MRAC system functions well and is more beneficial and efficient for the nonlinear plant.

Efficient Prototyping of a Field-Programmable Gate Array-Based Real-Time Model of a Modular Multilevel Converter

Field-programmable gate array (FPGA)-based real-time simulation plays a crucial role in testing power–electronic dominated systems with the formation of controller hardware-in-the-loop (CHIL) or power hardware-in-the-loop (PHIL). This work describes an efficient implementation of computation time and resource usage in the FPGA-based study of a modular multilevel converter (MMC) with detailed electromagnetic transients. The proposed modeling technique can be used in continuous control mode (CCM) and discontinuous control mode (DCM) for high-switching frequency semiconductor technologies. An FPGA-based designed solver structure is also presented to take advantage of the parallel features of FPGAs to achieve an ultra-fast calculation speed. In addition, two different switch modeling techniques are discussed with a five-level MMC case study. Experimental results on the NI PXIe platform show the feasibility of the proposed implementation, and a time step of 100 nanoseconds is achieved.

Anti-Gravity System Based on Magnetic Levitation Technology

This paper presents a design of an anti-gravity system based on magnetic levitation technology. The system utilizes the force generated by magnetic principles to counteract gravity and achieve object suspension and control. The design objective is to achieve portable maglev technology for everyday use. Specific requirements include adjustable speed range, endurance time, effective suspension range, mass, control mode, safety, magnetic field strength, suspension stability, altitude control precision, resistance to strong magnetic field interference, and portability. The system structure includes suspension device, magnetic field generator, sensor, and control system. Control strategies such as PID control, fuzzy control, and sliding mode control can be employed, and signal communication can be achieved through Bluetooth, Wi-Fi, or fiber optic communication. By selecting and designing appropriate control strategies and integrating suspension, magnetic field generator, and sensor components, the anti-gravity system based on magnetic levitation technology can achieve height control and suspension stability.

Mechanical properties of rock under uniaxial compression tests of different control modes and loading rates

To study the influence of control mode and loading rate on mechanical property of rock, uniaxial compression tests of four types of rocks (gray sandstone, red sandstone, mudstone and granite) are carried out under axial strain control mode and lateral strain control mode respectively. The characteristics of complete stress and strain curves, strength, brittleness and failure modes are analyzed. The results show that control mode has little influence on the pre-peak deformation, stress thresholds, while it has a greater impact on post-peak stress and strain curve, which makes the post-peak deformation stable and controllable, and shows the feature of Class II behavior. With lateral loading rates decrease, post-peak stress and strain curves appear more and more obvious fluctuations in the post-peak stage, and the time required for rock failure increases sharply, but the lateral control rate has little effect on the brittleness of rock. The failure mode of rock samples under axial strain control mode is mainly splitting failure, while that under lateral strain control is gradually changed to shear failure. The smaller the lateral loading control rate is, the more obvious the characteristics of shear failure is. Compared with uniaxial compression tests, under high confining pressure, the lateral dilation deformation is restricted, so peak strength is larger and stress redistribution can be better adjusted and stress fluctuation reduced accordingly in post-peak stage. The research results are an effective supplement to rate-dependent property of rocks and can provide some reference for deformation and strength characteristics research of brittle rock under lateral control mode.

Multi-Mode Control of a Hybrid Transformer for the Coordinated Regulation of Voltage and Reverse Power in Active Distribution Network

The unprecedented growth of distributed renewable generation is changing the distribution network from passive to active, resulting in issues like reverse power flow, voltage violations, malfunction of protection relays, etc. To ensure the reliable and flawless operation of active distribution networks, an electrical device enabling active network management is necessary, and a hybrid distribution transformer offers a promising solution. This study introduces a novel hybrid transformer topology and multi-mode control strategy to achieve coordinated voltage and reverse power regulation in active distribution networks. The proposed hybrid transformer combines conventional transformer windings with a partially rated SiC-MOSFET-based back-to-back converter, reducing additional investment costs and enhancing system reliability. A multi-mode control strategy is proposed to facilitate the concurrent reverse power control and voltage violation mitigation of the presented hybrid transformer, allowing a smooth transition between the P–Q control mode and the V–f control mode. The control mode switching can be activated manually or autonomously in response to voltage violations or reverse power overloading. The effectiveness of the proposed hybrid transformer configuration and its control mode transition mechanism are examined through comprehensive case studies conducted in the PSCAD/EMTDC environment. The proposed HT design has been confirmed to achieve a voltage regulation range of ±20% of the nominal voltage and effectively regulate bidirectional active power flow within a range of −25% to 25% of the rated power.

Human movement modifications induced by different levels of transparency of an active upper limb exoskeleton.

Active upper limb exoskeletons are a potentially powerful tool for neuromotor rehabilitation. This potential depends on several basic control modes, one of them being transparency. In this control mode, the exoskeleton must follow the human movement without altering it, which theoretically implies null interaction efforts. Reaching high, albeit imperfect, levels of transparency requires both an adequate control method and an in-depth evaluation of the impacts of the exoskeleton on human movement. The present paper introduces such an evaluation for three different "transparent" controllers either based on an identification of the dynamics of the exoskeleton, or on force feedback control or on their combination. Therefore, these controllers are likely to induce clearly different levels of transparency by design. The conducted investigations could allow to better understand how humans adapt to transparent controllers, which are necessarily imperfect. A group of fourteen participants were subjected to these three controllers while performing reaching movements in a parasagittal plane. The subsequent analyses were conducted in terms of interaction efforts, kinematics, electromyographic signals and ergonomic feedback questionnaires. Results showed that, when subjected to less performing transparent controllers, participants strategies tended to induce relatively high interaction efforts, with higher muscle activity, which resulted in a small sensitivity of kinematic metrics. In other words, very different residual interaction efforts do not necessarily induce very different movement kinematics. Such a behavior could be explained by a natural human tendency to expend effort to preserve their preferred kinematics, which should be taken into account in future transparent controllers evaluation.

Bacillus subtilis NBRI-W9 simultaneously activates SAR and ISR against Fusarium chlamydosporum NBRI-FOL7 to increase wilt resistance in tomato.

The study aimed to determine the pathogenicity of Fusarium species currently prevalent in tomato fields having history of chemical fungicide applications and determine the bio-efficacy of Bacillus subtilis NBRI-W9 as a potent biological control agent. Fusarium was isolated from surface-sterilized infected tomato plants collected from fields. Pathogenicity of 30 Fusarium isolates was determined by in vitro and in vivo assays. Following Koch's postulates, F. chlamydosporum (FOL7) was identified as a virulent pathogen. The biological control of FOL 7 by B. subtilis NBRI-W9 (W9) and the colonization potential of W9 were established using spontaneous rifampicin-resistant mutants. W9 showed 82% inhibition of FOL7 on a dual-culture plate and colonization levels in tomato plants of ∼5.5, ∼3.3, and ∼2.2 log10 CFU/g in root, stem, and leaf tissue, respectively. Antagonistic activity was shown by scanning electron microscopy (SEM) and cell-wall-degradative enzymes. W9 reduced FOL7 infection in net-house and field experiments by 60% and 41%, respectively. Biochemical investigation, defence enzymes, defence gene expression analysis, SEM, and field studies provide evidence of hyperparasitism and induced resistance as the mode of biological control. The study also demonstrates that the potent biocontrol agent W9, isolated from Piper, can colonize tomato plants, control fungal disease by inducing induced systemic resistance (ISR) and systemic acquired resistance (SAR) simultaneously, and increase crop yield by 21.58% under field conditions. This study concludes that F. chlamydosporum (NBRI-FOL7) is a potent, fungicide-resistant pathogen causing wilt in tomatoes. NBRI-W9 controlled FOL7 through mycoparasitism and simultaneously activated ISR and SAR in plants, providing an attractive tool for disease control that acts at multiple levels.

Source Network Load Storage Access to Power Wireless Private Network Technology Based on 5G Ultra Dense Networking

We make the source network load storage access power wireless private network, this paper proposes a source network load storage access power wireless private network technology based on 5G ultra dense network. The multiple rotation scheduling and self-organizing learning methods are used to establish the deployment model of the source network load storage access node of the power wireless private network under the 5G communication mode. According to the routing control algorithm design of the 5G ultra dense networking node, combined with the integration analysis of the access load parameters, the source network load storage access model of the 5G ultra dense networking under the dynamic load distributed control mode is established. Through the method of optimal control of reactive power and voltage of distribution network, the transmission link equilibrium structure model of 5G source network load storage access to power wireless private network is constructed. Combined with the coverage analysis of link topology structure and the benefit maximization constraint analysis of production and consumption users, the active and reactive capacity analysis of transaction between production and consumption user groups and multiple production and consumption users is adopted. Combined with the energy storage characteristics analysis and power flow parameter calculation of the source network load storage access power, the 5G ultra dense networking and private network access to the source network load storage access power are realized. The test shows that this method has better power balance dispatching ability and larger output power gain when it is applied to the design of source network load storage access power wireless private network.

SDN-Based Congestion Control and Bandwidth Allocation Scheme in 5G Networks

5G cellular networks are already more than six times faster than 4G networks, and their packet loss rate, especially in the Internet of Vehicles (IoV), can reach 0.5% in many cases, such as when there is high-speed movement or obstacles nearby. In such high bandwidth and high packet loss network environments, traditional congestion control algorithms, such as CUBIC and bottleneck bandwidth and round-trip propagation time (BBR), have been unable to balance flow fairness and high performance, and their flow rate often takes a long time to converge. We propose a congestion control algorithm based on bottleneck routing feedback using an in-network control mode called bottleneck routing feedback (BRF). We use SDN technology (OpenFlow protocol) to collect network bandwidth information, and BRF controls the data transmission rate of the sender. By adding the bandwidth information of the bottleneck in the option field in the ACK packet, considering the flow fairness and the flow convergence rate, a bandwidth allocation scheme compatible with multiple congestion control algorithms is proposed to ensure the fairness of all flows and make them converge faster. The performance of BRF is evaluated via Mininet. The experimental results show that BRF provides higher bandwidth utilization, faster convergence rate, and fairer bandwidth allocation than existing congestion control algorithms in 5G cellular networks.

Research on parallel control strategy of power converters based on fuzzy neural network

As pure electric vehicles shift toward intelligent technology, the energy demand for onboard equipment is on the rise. In this study, a parallel control strategy for two 3-kW DC–DC power converters was proposed to meet the power requirements of pure electric vehicle loads in this paper. First, the operation mode of the resonant power converter was analyzed. The operation mode of the power converter adopted the advantageous frequency conversion–phase shift control mode. Second, a parallel control method for Takagi–Sugeno-type fuzzy neural network converters with four inputs and a single output first-order was designed to meet the power demand based on the advantages of fuzzy control and neural networks. The neural networks can be trained automatically based on the established requirements, and the fuzzy rules formulated through fuzzy neural networks were more detailed and accurate. Finally, the proposed control strategy was validated by experiments. The experimental results showed that the proposed control strategy can ensure the stable operation of the power converter during switching under the set load. The output power of the primary and sub converters varies linearly, which can meet the load’s demand for high power. There is no need to develop higher-power power converters. These results can provide a new idea for the research of high-power power converters and reduce development costs.

Flight-Data-Based High-Fidelity System Identification of DJI M600 Pro Hexacopter

Research and industrial application can require custom high-level controllers for industrial drones. Thus, this paper presents the high-fidelity dynamic and control model identification of the DJI M600 Pro hexacopter. This is a widely used multicopter in the research and industrial community due to its high payload capability and reliability. To support these communities, the focus of control model identification was on the exploration and implementation of DJI Onboard Software Development Kit (OSDK) functionalities, also including some unconventional special modes. Thus, the resulting model can be controlled with the same OSDK functionalities as the real drone, making control development and application time effective. First, the hardware and software structure of the additional DJI M600 onboard system are introduced. Then, the postulated dynamic and control system models are shown. Next, real flight test campaigns generating data for system identification are presented. Then, the mass and inertial properties are estimated for TB47S and TB48S battery sets and the custom Forerunner UAV payload. Dynamic system model identification includes the aerodynamic effects and considers hover, vertical, and horizontal forces together with static horizontal wind components and finally the rotational moments and dynamics. The control system components were identified following the structure of OSDK, including vertical, horizontal, and yaw loops. After identification, the model was validated and refined based on an unused flight test and software-in-the-loop simulation data. The simulation is provided by DJI and was also compared to real flight results. This comparison showed that the DJI simulation covers the dynamics of the real drone well, but it requires being connected to the drone and needs the controllers onboard to be implemented in advance, which limits applicability and increases development time. This was another motivation to introduce a standalone simulation in Matlab Simulink, which covers all the important modes of OSDK control and can be run solely in Matlab without any hardware support. The constructed model will be published for the benefit of the research and industrial community.

Improving the operational characteristics of electrical power systems of marine vessels

THE PURPOSE. Consider the experience of use and conduct a study of the electrical power systems of sea vessels to determine the possibility of improving their operational characteristics. Obtain data on noise and vibration levels of electrical power systems elements.METHODS. The article analyzes the electrical power systems of the Azipod type steering columns of the Baltika icebreaker. The issue of regulating the rotation speed of propulsion electric motors using frequency control based on a DC link and parallel-connected inverter units on IGBT transistors is considered. Motor control on the frequency converter side can be based on direct torque control, scalar and vector control. There are control modes for reducing and increasing voltage.RESULTS. Typical dependences of structure-borne noise levels of main engines and generators are given. Measurements were taken at various frequencies of engine sound power levels, exhaust gases and vibration of generator sets. Experimental oscillograms of studies of the parallel operation of diesel generator sets were obtained, on which power exchange and common-mode oscillations were recorded.CONCLUSION. It is proposed to use multiphase AC electric motors to improve performance characteristics, including reducing noise and vibration. The existing experience in using frequency converters based on a rectifier section and inverter units in electric rowing installations with Azipod propellers makes it possible to implement such a change. To do this, it is necessary to parallelize the inverters that supply each of the three phases and provide the appropriate phase shifts.

Evaluation of the prevention effect of high-quality nursing quality control in disinfection supply center on nosocomial infection.

To explore the application effect of high-quality nursing quality control in disinfection supply center. The control group consisted of 1850 medical devices managed using the conventional quality control mode from January 2021 to December 2021, while the observation group consisted of 1900 medical devices managed using the high-quality nursing quality control mode from January 2022 to December 2022. The qualified rates of equipment cleaning, sterilization, and packaging were analyzed in both the observation and control groups. The occurrence of nosocomial infections in 2021 and 2022 were compared, and the changes in the Beck-Srivaatava stress scale index (BSSI) and Symptom Checklist-90 scores of the staff before and after implementing the high-quality nursing quality control mode were analyzed. The qualified rate of equipment cleaning, sterilization, and packaging in the observation group were 99.08%, 99.73%, and 99.78%, respectively, which were significantly higher than those in the control group (P < .05). The incidence of nosocomial infections in interventional and surgical cases in 2022 was 0.79%, which was significantly lower than that in 2021 (P < .05). The BSSI score of female staff was (68.76 ± 7.81) points, which was higher than that of male staff (P < .05). After the implementation of the high-quality nursing quality control mode, the BSSI score of the staff was (47.76 ± 9.12) points, which was significantly lower than that before implementation (P < .05). After the implementation of the high-quality nursing quality control mode, the staff's Symptom Checklist-90 scores for somatization, compulsion, interpersonal sensitivity, depression, hostility, and paranoia were (1.28 ± 0.29), (1.53 ± 0.24), (1.50 ± 0.21), (1.46 ± 0.32), (1.44 ± 0.26), and (1.38 ± 0.30) points, respectively, showing a decrease compared to before implementation (P < .05). The high-quality nursing quality control mode has great application value in the disinfection supply center. It can effectively improve the qualified rates of equipment cleaning, sterilization, and packaging, prevent nosocomial infections and improve the working pressure and psychological health of staff.

Aircraft Upset Recovery Strategy and Pilot Assistance System Based on Reinforcement Learning

The upset state is an unexpected flight state, which is characterized by an unintentional deviation from normal operating parameters. It is difficult for the pilot to recover the aircraft from the upset state accurately and quickly. In this paper, an upset recovery strategy and pilot assistance system (PAS) based on reinforcement learning is proposed. The man–machine closed-loop system was established and the upset state, such as a high angle of attack and large attitude angle, was induced. The upset recovery problem was transformed into a sequential decision problem, and the Markov decision model of upset recovery was established by taking the deflection change of the control surface as the action. The proximal policy optimization (PPO) algorithm was selected for the strategy training. The adaptive pilot model and the reinforcement learning method proposed in this paper were used to make the aircraft recover from the upset state. Based on the correspondence between the flight state, the recovery method, and the recovery result, the aircraft upset recovery safety envelopes were formed, and the four-level upset recovery PAS with alarm warning, coordinated control, and autonomous recovery modes was constructed. The results of the digital virtual flight simulation and ground flight test show that compared with a traditional single pilot, the aircraft upset recovery strategy, the upset recovery safety envelopes, and the PAS established in this study could reduce the handling burden of the pilot and improve the success rate and effect of upset recovery. This research has certain theoretical reference values for flight safety and pilot training.

A framework to identify failure scenarios in the control mode transition process for autonomous ships with dynamic autonomy

The dynamic autonomy resulting from control mode transitions in the Maritime Autonomous Surface Ships (MASS) poses a significant risk to its navigation safety. While Systems-Theoretic Process Analysis (STPA) has proven effective in the hazard identification of autonomous ships, the safety challenges inherent in the dynamic autonomy of MASS with seafarers onboard controlled by three possible controllers have not been addressed much. This study proposes a three-phase framework that combines STPA, state machines and Sequentially Timed Events Plotting (STEP) diagram aiming at identifying failure scenarios in the transition process. Findings from a case study highlight the need for such a framework to understand the triggering events for mode transition, the transition process, how transition failure may occur, and refine safety constraints to ensure smooth and safe transitions. The results lay the groundwork for future research into test case generation methods that focus on these identified transition failure scenarios, intending to ensure safe and secure navigation for the progressive introduction of MASS.

Response-Category Conflict and Control Mode Determine Memory Performance for Distractors in a Flanker Paradigm.

Cognitive conflicts can lead to better memory for task-relevant information. However, little is known about memory performance for task-irrelevant information. The present study investigated memory performance of task-irrelevant distractors using a Flanker paradigm. In two experiments (N = 699), participants first completed a study phase with 56 flanker trials. The stimuli consisted of trial-unique pictures. A congruent trial consisted of a target flanked by two identical pictures from the same category (e.g., all mammals). An incongruent trial consisted of a target and flankers from different stimulus categories (e.g., a mammal flanked by two identical birds), which results in a response-category conflict. To explore the impact of different control modes, congruent and incongruent trials were presented in pure blocks (allowing a proactive control mode) or in mixed blocks (requiring a reactive control mode). Afterwards, recognition memory was tested in a surprise memory test. In general, the results showed better memory for congruent than incongruent flankers in pure blocks. In contrast in mixed blocks, the results showed better memory for incongruent than for congruent flankers. Thus, memory performance for distractors varies systematically with response-category conflict and control mode.