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Tantalum (Ta) has good potential for bone tissue engineering due to its excellent corrosion resistance and biocompatibility. However, the customization of Ta-based bone repair materials for irregularly shaped bone defects has been challenging due to their high melting point and hardness. In this work, porous tantalum granules (PTaG) were developed for the first time to repair irregularly shaped bone defects, inspired by the natural phenomenon of sand flow. PTaG were designed as a hierarchical porous structure to regulate the mechanical properties and provide a favorable space for inward growth of cells and tissues. Commercial porous titanium granules (PTiG) and Bio-Oss were used as positive controls to explore the potential of PTaG as bone substitute. The morphology, three-dimensional structure, composition, and mechanical properties of PTaG and PTiG were evaluated by SEM, X-Ray 3D imaging system, 3D laser confocal microscope, EDS, XRD, XPS, and nanoindentation. In vitro, cell compatibility and mineralization ability were evaluated for both materials. Furthermore, PTaG, PTiG, and Bio-Oss were filled in the rabbit femoral defect, and micro-CT and histological analysis were performed after 8 weeks. The results showed that the PTaG had the best bone healing effect due to the hierarchical porous structure, excellent three-dimensional connectivity and chemical stability, suitable mechanical properties and surface roughness, good biocompatibility and mineralization osteogenic activity. This work indicates that PTaG may have a positive potential for filling and repairing irregularly shaped bone defects.

The purpose is to optimize the Beetle Antenna Search (BAS) algorithm and apply it to the Intelligent Transportation System (ITS) to process traffic data in time and solve traffic congestion. This work studies the development status of ITS and the application status of the BAS algorithm. It optimizes BAS to converge to local optimization prematurely in high-dimensional space, affecting the prediction accuracy. Then, combined with the Least Squares Support Vector Machine Algorithm (LSSVM), the algorithm with quadratic interpolation optimization is proposed. The proposed algorithm is named the Quadratic Interpolation Beetle Antenna Search (QIBAS). On this basis, a traffic flow prediction model based on QIBAS-LSSVM is established. Finally, the improved QIBAS algorithm and Traffic Flow Prediction (TFP) model are verified. The results show that the test Mean Square Error (MSE) of the TFP model based on QIBAS-LSSVM increases by 4.28%, 7.38%, and 18.23%, respectively compared with the other three models. The test Mean Absolute Percentage Error (MAPE) increases by 0.09%, 0.06%, and 0.36% respectively. The proposed QIBAS algorithm has a good effect and high accuracy in short-term TFP. The research has important reference value for the digital transformation of transportation systems in modern smart cities.

This work aims to improve the transmission and sharing efficiency of intelligent transportation data and promote the further development of intelligent transportation and smart city. In this work, an EEMR (Energy Efficient Multi-hop Routing) is designed for the intelligent transportation wireless sensor network. In the EEMR algorithm, the base station runs the IAP clustering algorithm for network clustering after receiving the information of all surviving nodes. A method called ACRR (Adaptive Cluster-head Round Robin) is proposed for local dynamic election of cluster heads. In addition, the deep learning-based stochastic gradient descent algorithm and its evolution algorithm are sorted out, and its application in practical scenarios is analyzed. Due to the disadvantages of the adaptive algorithm in the current data processing process, the gradient optimization algorithm based on deep learning is adopted and the concept of adaptive friction coefficient is applied to the Adam algorithm to obtain a new adaptive algorithm (TAdam). The simulation experiment reveals that the proportion of network surviving nodes of the EEMR algorithm is still as high as 90% in 1,500 rounds of data collection. This shows that the EEMR algorithm achieves the energy balance of the network nodes as much as possible while minimizing the system energy consumption. In application scenario 1, when the network surviving nodes of the four data collection algorithms compares dropped below 40%, the number of surviving nodes in the EEMR algorithm is still as high as 97.6%. On the PTB (Penn Tree Bank) test data set, the TAdam algorithm shows the fastest convergence speed and the best generalization performance. The TAdam algorithm based on deep learning discussed in this work was of great significance for improving the transmission and sharing efficiency of intelligent transportation data.

In [1], inaccuracies in several critical equations along with their accompanying descriptions appear in the article. Furthermore, some references are missing, and certain analyses of experiments are flawed.

Cell models can express a variety of cell information, including mechanical properties, electrical properties, and chemical properties. Through the analysis of these properties, we can fully understand the physiological state of cells. As such, cell modeling has gradually become a topic of great interest, and a number of cell models have been established over the last few decades. In this paper, the development of various cell mechanical models has been systematically reviewed. First, continuum theoretical models, which were established by ignoring cell structures, are summarized, including the cortical membrane droplet model, solid model, power series structure damping model, multiphase model, and finite element model. Next, microstructural models based on the structure and function of cells are summarized, including the tension integration model, porous solid model, hinged cable net model, porous elastic model, energy dissipation model, and muscle model. What’s more, from multiple viewpoints, the strengths and weaknesses of each cell mechanical model have been analyzed in detail. Finally, the potential challenges and applications in the development of cell mechanical models are discussed. This paper contributes to the development of different fields, such as biological cytology, drug therapy, and bio-syncretic robots.

The hybrid game system suffers from the constantly time-varying environment and the heterogeneous behaviors of decision-making subjects (players) when the hybrid situation emerges, bringing significant challenges to situation representation and strategic reasoning. With the help of the powerful modeling ability of hybrid systems for situation representation and reasoning in network topology, we propose the six-tuple hybrid game model based on modified hybrid stochastic timed Petri nets (M-HSTPN) to reveal the internal cross-level operating mechanisms. Then, we carry out the nonlinear mapping relationship between the hybrid game elements and the symbols of M-HSTPN. Taking the intelligent drones combat problem as an example, we compare differential game, event game, and proposed hybrid game scheme in pursuit–evasion trajectories, action timing, bombing sequence, and formation. The proposed M-HSTPN-based hybrid game scheme can effectively describe the constantly changing pursuit–evasion trajectories and select the action timing to reduce the energy consumption of interception and the target-missing quantity. Furthermore, the proposed hybrid game scheme can reason the optimal bombing sequence and narrow the scope of optimal formation through enriching payoff evaluation indexes with the current hybrid situation compared with the event game scheme and differential game scheme.

In this paper, a novel data-driven model-free adaptive fractional-order sliding mode controller with prescribed performance is proposed for the shape memory alloy (SMA) actuator. Due to the strong asymmetric saturated hysteresis nonlinear characteristics of the SMA actuators, it is not easy to establish an accurate model and develop an effective controller. Therefore, we present a controller without using the model of the SMA actuators. In other words, the proposed controller depends merely on the input/output (I/O) data of the SMA actuators. To obtain the reasonable compensation for hysteresis, enhance the noise robustness of the controller, and reduce the chattering, a fractional-order sliding mode controller with memory characteristics is employed to improve the performance of the controller. In addition, the prescribed performance control (PPC) strategy is introduced in our work to guarantee the tracking errors converge to a sufficiently small boundary and the convergence rate is not less than a predetermined value which are significant and considerable in practical engineering applications of the SMA actuator. Finally, experiments are carried out, and results reveal the effectiveness and success of the proposed controller. Comparisons with the classical Proportional Integral Differential (PID), model-free adaptive control (MFAC), and model-free adaptive sliding mode control (MFAC-SMC) are also performed.

The upper-limb exoskeleton is capable of enhancing human arm strength beyond normal levels, whereas deriving the operator’s desired action straightforward turns out to be one of the significant difficulties facing human-robot interaction research. In the study, the human-robot interface was presented to regulate the exoskeleton tracking human elbow motion trajectory that employed the contact force signals between the exoskeleton and its operator as the primary means of information transportation. The signals were recorded by adopting the novel soft skin sensors attached to the bracket on the exoskeleton linkage, which could reflect the human arm motion intention through the virtual admittance model and adaptive control. Subsequently, a 1-DOF upper-limb exoskeleton was designed to illustrate the performance of the proposed sensor and the interaction control method in the human-robot cooperation experiment.

For designing the decision model of hybrid systems, there are sophisticated quantitative and qualitative attributes such as discrete events, continuous processes, stochasticity, and time delay. Meanwhile, the inherent heterogeneity and concurrency existing in hybrid systems trigger multiple decision challenges, including behavior uncertainty and states consistency. It is difficult to express the complicated nonlinear mapping relationship between decision results and hybrid situations. This proposes the decision-making scheme M-HSTPN-DL with a three-tier architecture based on modified hybrid stochastic timed Petri net (M-HSTPN) and deep learning (DL). Among them, M-HSTPN describes the various hybrid situations, and DL models are taken as the decision model to express the nonlinear relationship between decision results and hybrid situations. Then the training and calling mechanism of decision models is introduced. Taking the hybrid system of bearing fault diagnosis as an example, we compare the decision-making ability of multiple decision models and analyze the advantage of M-HSTPN-DL. It has proven to be that the M-HSTPN-DL architecture can adequately represent the hybrid situation and solves the complex decision- making problem of hybrid systems.

Cyber–physical system (CPS) is a multidimensional complex system that integrates computation, communication, and physical environment with essential and broad application prospects. However, there is a kind of CPS containing discrete events, continuous processes, stochastic phenomena, time-delay, and decision. It suffers from several sophisticated modeling and decision-making challenges, including deep integration of cyber and physical world, intensive temporal properties, model uncertainty, concurrency, and behavioral control. In this article, we deal with the above problems from the perspective of hybrid systems. We propose the modeling methods of CPS based on the modified hybrid stochastic timed Petri net (M-HSTPN) with three-tier architecture and introduce the decision place to strengthen the decision-making ability of CPS. Its advantages lie in describing multiple problems in CPS at the same time by adopting a unified open architecture. By integrating the various modeling and decision-making challenges under a unified framework, it is easy to analyze the problem systematically. Taking the humanoid soccer robot CPSs (HSR-CPS) as an example, by analyzing factors that affect the action cycle and interception success rate of the HSRs, we show the powerful modeling and decision-making capabilities of the M-HSTPN for CPS.

Micro/nano positioning technologies have been attractive for decades in industrial and scientific applications fields. The actuators have inherent hysteresis that can cause system unexpected behave in some extend. In this research, the authors used extented unparallel Prandtl-Ishlinshii (EUPI) models to represent the input-output relationship of a piezo-driven micro position stage. Integral inverse (I-I) compensator is used for compensating the hysteresis characteristics of the micro positioning stage and compared with direct inverse (D-I) compensator and inverse model (I-M) compensator. However, the accuracy and the robustness of the I-I compensator are worse when there is noisy in the system, a novel sliding-mode-like-control with EUPI (SMLC-EUPI) method was proposed and analyzed by different trajectory tracking experiments in Matlab environment. Though the above strategies can alleviate most deviation, the adjustment of the SMLC’s parameters is very complex. So the fuzzy method is used to adjust these parameters and be verified by trajectory tracking experiments. Finally, for validating the proposed control method, the paper did the corresponding experiment in microscope with CMOS and obtained convincing results.

AbstractIn this paper, an interesting Hybrid Stochastic Timed Petri Net (HSTPN) is proposed for a class of hybrid systems. The proposed HSTPN can be adopted to represent hybrid systems with discrete, continuous, conflicting, time-delay and stochastic characteristics simultaneously. The proposed HSTPN outperforms conventional hybrid Petri net models in terms of describing the scalability and immediacy of hybrid systems. Advantages of the HSTPN on describing hybrid system are verified by establishing some equivalent models of HPN and its derived models.

In the recent past, it has been observed that flexure-based microposition stages with a large workspace and high motion precision are gaining popularity for performing practical micromanipulation tasks. Thus, a piezoactuated flexible two-degrees-of-freedom micromanipulator integrated with a pair of displacement amplifiers is developed. To enhance the practical positioning performance of the micromanipulator, this paper proposes a feed-forward frictional-order proportional–integral–derivative based feedback control approach to eliminate the undesired resonant mode of a piezoactuated microposition stage to satisfy the accuracy of the system. The control approach is composed of the integration inverse feed-forward compensator, the feedback controller, and the frictional-order proportional–integral–derivative controller. The integration inverse feed-forward compensator with an extended unparallel Prandtl–Ishlinskii model is introduced for addressing the nonlinearity of the piezoactuated microposition stage, leading to an approximately linear system. When all the roots of the system characteristic equation are negative real numbers or have negative real parts, the feedback controller is guaranteed to have tracking stability. Next, a frictional-order proportional–integral–derivative controller is designed to enhance the tracking performance of the microposition stage. Finally, comparative experiments with the conventional proportional–integral–derivative controller are performed, revealing that the practical positioning performance has been increased by nearly 35%. The experimental results demonstrate that the performance with the frictional-order proportional–integral–derivative+feedback controller is improved significantly.

Thousands of years ago, Go and Chinese chess were popular board games in China. The words “Chuhe Hanjie” that is often printed on Chinese chess game boards to divide the two player sides is a reference to the Chu-Han war; while it is far from proof that Chinese chess dates back to the Han dynasty, there is much evidence to show that the game has a long history. Computer game tournaments began comparatively late in China, but they have developed very quickly. This article summarizes the history of the development of computer game tournaments in China and discusses the reasons for the rapid development of computer game tournaments in China from several perspectives. Finally, we comment on the future of computer game tournaments in China.

To summarize the nursing experience of treating pediatric fulminant myocarditis with extracorporeal membrane oxygenation (ECMO). The intensive care unit of our hospital treated 6 children with fulminant myocarditis with ECMO from 2019 to 2022. The main nursing measures included establishing an ECMO rescue team, preparing before initiation of ECMO, management of arterial and venous catheters, enteral nutrition support, reducing the risk of infection aggravation, anticoagulation management, prevention of bleeding and thrombosis, management of ECMO pump failure, and post-ECMO care. One child’s family abandoned treatment and left the hospital, while the other 5 children were transferred to the cardiovascular department after stable weaning from ECMO and continued treatment, with good condition, and eventually discharged. Pediatric fulminant myocarditis has a high mortality rate, but detailed evaluation and nursing care can improve the outcome of these patients.

Scanning probe microscopy (SPM) technology plays the irreplaceable role in investigating micro/nano world, which has been bringing tremendous development opportunities to various fields. To enhance maneuverability, SPM can be modified into a nanomanipulation system with its scanning probe as the end-effector. The probe is commonly mounted on smart material based actuators to generate precise motion with nanometer level resolution. However, instinctive hysteretic characteristics ubiquitously exist in smart material actuators, which degrade their arbitrary positioning precision. To effectively represent and further reduce complex hysteretic effects, this paper proposes to utilize the modified Prandtl-Ishlinskii (PI) model: extended unparallel PI (EUPI) model, which possesses advantages such as the flexible modeling capability (compared to the prevalently implemented modified PI models) and the easy-to-use property for construction and identification (compared to the well known Preisach model and the Generalized PI (GPI) model). To effectively reduce complex hysteresis, the EUPI model based compensator (IMUPIcompensator) is required to be flexible and precise. To efficiently design such a compensator satisfying stability requirement, this study proposes a systematic approach, including stabilizing gain selection and analytical calculation of boundary gains of the EUPI irreversible component. As a demonstration, satisfactorily precise IMUPIcompensator was established according to this systematic design approach and tested through simulations on rectifying Atomic Force Microscopy (AFM, one special SPM) imaging process distorted by complex hysteresis.

ABSTRACTAn epidemic of human H7N9 influenza virus infection recently emerged in China whose clinical features include high mortality and which has also resulted in serious economic loss. The novel reassortant avian-origin influenza A (H7N9) virus which was the causative agent of this epidemic raised the possibility of triggering a large-scale influenza pandemic worldwide. It seemed likely that fast molecular detection assays specific for this virus would be in great demand. Here, we report a one-step reverse transcription–loop-mediated isothermal amplification (RT-LAMP) method for rapid detection of the hemagglutinin (HA) and neuraminidase (NA) genes of H7N9 virus, the minimum detection limit of which was evaluated using in vitroRNA transcription templates. In total, 135 samples from clinical specimens (from either patients or poultry) were tested using this method in comparison with the real-time PCR recommended by the World Health Organization (WHO). Our results showed that (i) RT-LAMP-based trials can be completed in approximately 12 to 23 min and (ii) the detection limit for the H7 gene is around 10 copies per reaction, similar to that of the real-time PCR, whereas the detection limit for its counterpart the N9 gene is 5 copies per reaction, a 100-fold-higher sensitivity than the WHO-recommended method. Indeed, this excellent performance of our method was also validated by the results for a series of clinical specimens. Therefore, we believe that the simple, fast, and sensitive method of RT-LAMP might be widely applied for detection of H7N9 infections and may play a role in prevention of an influenza pandemic.

ABSTRACTStreptococcus suisserotype 2 (S. suis2) is an important zoonotic pathogen that causes considerable economic losses to the pig industry and significantly threatens public health worldwide. The highly pathogenic S. suis2, which contains the 89K pathogenicity island (PAI), has caused large-scale outbreaks of infections in humans, resulting in high mortality rates. In this study, we established two loop-mediated isothermal amplification (LAMP)-based assays that can rapidly detect S. suis2 and the 89K PAI and can be performed simultaneously under the same conditions. Further, based on the findings of these two LAMP assays and using the same set of serially diluted DNA samples, we compared the sensitivities of different LAMP product detection methods, including SYBR green detection, gel electrophoresis, turbidimetry, calcein assays, and hydroxynaphthol blue detection. The results suggest that target genes can be amplified and detected within 48 min under 63°C isothermal conditions. The sensitivity of tests for S. suis2 detection varies between detection methods and reaction systems, indicating that for each LAMP reaction system, multiple detection methods should be performed to select the optimal one. The sensitivities of the optimized methods (7.16 copies/reaction) in the present study were identical to those of the real-time PCR assay, and the test results for reference strains and clinical samples showed that these LAMP systems have high specificities. Thus, since the LAMP systems established in this study are simple, fast, and sensitive, they may have good clinical potential for detecting the highly pathogenic S. suis2.

With the continuous development of LED(Light-Emitting Diode) manufacturing technology, the high power white LED is gradually applied in the field of all kinds of lighting .But with working time increasing of LED chips, their junctions temperature continue increasing, which lead to decrease light-emitting efficiency and reliability of LED chip, and even be failure. According to the serious heating of LED chip, this paper has been designed a fin-type aluminum radiator panels using Pro/E software. A LED constant current drive circuit is designed by using LTC3783 chip. With the ANSYS software, thermal analysis was carried out on the fin-type aluminum radiator panels, and eventually the mode of high power LED headlamps is determined. The stability of the LED constant current drive circuit is verified through experiments. The LED headlamps of 90W worked for ten hours, and the results of the experiments showed that the LED chip junctions temperature measured are less than 75°Cso we can solve heat dissipation of high power LED headlamps effectively.

China has developed a new national program for deceased-organ donation to address the need for organ transplantation in the country. The program adheres to the World Health Organization (WHO) guiding principles, is compliant with the Declaration of Istanbul, and respects the cultural and social values of the Chinese people. The experience of pilot trials conducted between 2010 and 2012 was evaluated to generate a comprehensive design of a national program of organ donation and transplantation for implementation throughout China. The legal framework for this program was established from a series of legislative steps since 2007. Accountable national committees have been established to oversee activities of organ donation and transplantation across the nation. The Ministry of Health (MOH) has accredited 164 organ transplant hospitals in China, each of which has an organ procurement organization (OPO) to conduct organ donation and organ recovery. National protocols for deceased-organ donation in China include category I (organ donation after brain death), category II (organ donation after circulatory death), and category III (organ donation after brain death followed by circulatory death). The China Organ Transplant Response System (COTRS) has been developed to allocate organs equitably and transparently. Scientific registries have been established to evaluate the performance of transplant centers and OPOs. China is in the process of implementing a new national program for deceased-organ donation. The program includes a unique approach of organ donation, China category III, which will be promulgated throughout China and is intended to gain widespread acceptance of Chinese society.

•Proposed an innovative model for joint train line planning and timetabling based on actual time-dependent demand and appropriately capturing the sufficient operational constraints including overtaking constraints.•Developed a double-layer simulated annealing algorithm, in which the inner layer algorithm optimizes the stop plan and the departure and arrival times at each station, while the outer layer algorithm optimizes the number of trains, their origin-destination stations, and their departure times at origin stations.•Conducted a case study on the Shanghai-Nanjing intercity HSR and concluded that the model and algorithm proposed can help improve the operation efficiency of intercity railway.

An innovative integration of actuating and sensing ionic polymer metal composite (IPMC) gripper is proposed and fabricated in this paper. The IPMC gripper is composed of a stationary copper finger and an IPMC finger attached to a force sensor. In order to make IPMC gripper useful in bio-manipulation application, control strategy is a critical factor to resist nonlinear characteristic of IPMC. Hammerstein model of IPMC output displacement is constructed with static nonlinear portion and dynamic linear portion. We utilize creep operator superposition and auto-regression (ARX) models to represent static nonlinear and dynamic linear portions respectively by modeling methods based on data. Then a novel control scheme is proposed and designed using inverse creep compensator for static nonlinear portion and uncertainty state feedback robust control based on state observer for dynamic linear portion. When IPMC reaches a constant displacement to grasp a miniature object, the grasping force may not be provided enough to complete grasping task. Finally, hybrid control of force and position strategy for IPMC gripper is conducted and realized on physical experimental platform. The experimental results demonstrate the effectiveness of control system to guarantee stable manipulation.

Humanoid robotic hand actuated by shape memory alloy (SMA) represents a new emerging technology. SMA has a wide range of potential applications in many different fields, ranging from industrial assembly to biomedicine applications, due to the characteristic of high power-to-weight ratio, low driving voltages and noiselessness. However, nonlinearities of SMA and complex dynamic models of SMA-based robotic hands result in difficulties in controlling. In this paper, a humanoid SMA-based robotic hand composed of five fingers is presented with the ability of adaptive grasping. Reinforcement learning as a model-free control strategy can search for optimal control of systems with nonlinear and uncertainty. Therefore, an adaptive SA-Q-Learning (ASA-Q-learning) controller is proposed to control the humanoid robotic finger. The performance of ASA-Q-learning controller is compared with SA-Q-learning and PID controller through experimentation. Results have shown that ASA-Q-learning controller can control the humanoid SMA-based robotic hand effectively with faster convergence rate and higher control precision than SA-Q-learning and PID controller, and is feasible for implementation in a model-free system.

Manual lifting tasks involve repetitive raising, holding and stacking movements with heavy objects. These arm movements are notable risk factors for muscle pain, fatigue, and musculoskeletal disorders in workers. An upper-limb wearable robot, as a 6-DOF dual-arm exoskeleton, which was designed to augment workers’ strength and minimize muscular activation in the arm during repetitive lifting tasks. To adjust the robot joint trajectory, the user needs to apply an interactive torque to operate the robot during lifting tasks when a standard virtual mechanical impedance control structure is used. To reduce overshooting of the interactive torque on the user’s joint, a three-tier hierarchical control structure was developed for the robot in this study. At the highest level, a human arm movement detection module is used to detect the user’s arm motion according to the surface electromyography signals. Then, a Hammerstein adaptive virtual mechanical impedance controller is used at the middle level to reduce overshooting and yield an acceptable value of torque for the user’s elbow joint in actual lifting tasks. At the lowest level, the actuator controller on each joint of the robot controls the robot to complete lifting tasks. Several experiments were conducted, and the results showed that the interactive torque on the user’s elbow was limited and the muscular activations of erector spinae and biceps brachii muscles were effectively decreased. The proposed scheme prevents potential harm to the user due to excessive interactive torque on the human elbow joint, such as related muscle fatigue and joint injuries.

Soft robotic grippers with compliance have great superiority in grabbing objects with irregular shape or fragility compared with traditional rigid grippers. The main limitations of such systems are small grasping force resulted from properties of soft actuators and lacking variable stiffness of soft robotic grippers, which prevent them from a larger wide range of applications. This article proposes a shape-memory alloy (SMA)-based soft gripper with variable stiffness composed of three robotic fingers for grasping compliantly at low stiffness and holding robustly at high stiffness. Each robotic finger mainly consisted of stiff parts and two variable stiffness joints is installed on the base with a specific angle. The paraffin as a variable stiffness material in the joint can be heated or cooled to change the stiffness of the robotic fingers. Results of experiments have shown that a single robotic finger can approximately achieve 18-fold stiffness enhancement. Each finger with two joints can actively achieve multiple postures by both changing the corresponding stiffness of joints and actuating the SMA wire. Based on these principles, the gripper can be applied to grasp objects with different shapes and a large range of weights, and the maximum grasping force of the gripper is increased to about 10 times using the variable stiffness joints. The final experiment is conducted to validate variable stiffness of the proposed soft grippers grasping an object.

This paper considers a tri-trophic food chain in which the top predator (intraguild predator) also feeds on the basal resource. We refer to the model as intraguild predation. We analyze its dynamics from an evolutionary perspective. The attack rate or foraging effort of the middle species (intraguild prey) for the basal resources is assumed to be evolvable and is also assumed to be traded off with the vulnerability to being attacked by the top predator. We focus on the analysis of the evolutionary dynamics of the attack rate using the adaptive dynamics approximation of mutation limited evolution. In particular, the critical function analysis is applied. This study reveals that the evolutionary dynamics of the intraguild predation system is completely characterized by the concavity of the trade-off function and admits trichotomous dynamic scenarios: (1) when the trade-off function is more concave than the critical function, an evolutionary singular strategy exists and is a repeller; (2) when the trade-off function is less concave than the critical function, the evolutionary singular strategy is convergence stable and turns into an evolutionary branching point, in which case the monomorphic intraguild prey will split into two different types; (3) when the trade-off function is convex, the evolutionary singular strategy turns into a continuous stable strategy and is uninvadable. Our theoretical analysis suggests that the adaptive foraging behavior may strongly influence the community stability. Consequently, it may promote the diversity of intraguild prey and the persistence of the system on the evolutionary timescale, which highlight a more comprehensive mechanistic understanding of the intricate interplay between ecological and evolutionary force. This modeling approach provides a venue for research on indirect effects from an evolutionary perspective. [ABSTRACT FROM AUTHOR]