Avoidance Mechanism Research Articles

Approach and avoidance mechanisms in the effects of algorithm transparency on the service performance of food-delivery riders

ABSTRACT The advent of the digital era has seen algorithmic decision-making become ubiquitous in online service platform management. However, the lack of algorithm transparency has been widely reported as a barrier to successful human-machine collaboration. Drawing on self-regulation theory, this study explores the effects of algorithmic transparency on the approach and avoidance behaviours of 265 food-delivery riders on online platforms in China. Results from our two-wave survey show that algorithm transparency can improve the service performance of food-delivery riders by inspiring their task crafting along an approach path and reducing their negative work rumination along an avoidance path. The extent to which riders perceived the algorithmic allocations of their work tasks as just or unjust have an effect on whether riders engaged with task crafting or negative rumination. Specifically, perceiving low algorithmic injustice can strengthen the effect along the approach pathway and weaken the effect along the avoidance pathways. This study advances empirical research on algorithmic transparency in the fields of platform economy and service management, while providing practical insights for platform companies to develop, design, and apply algorithmic systems in ways that mutually benefit themselves and their workers.

Design and Simulation of Intra-Row Obstacle Avoidance Shovel-Type Weeding Machine in Orchard

This paper presents the design of an intra-row obstacle avoidance shovel-type weeding machine. Theoretical analysis of intra-row weeding components guided the determination of the structures and parameters for key parts, including the signal acquisition mechanism, automatic obstacle avoidance mechanism, and weeding shovel. Furthermore, a hydraulic system was designed to support these functions. The design aims to optimize intra-row weeding operations, reduce labor costs, enhance weed control effectiveness, and prevent collisions between weeding equipment and grapevines. Through the construction of a mathematical model, the analysis determined the necessary minimum return speed of the hydraulic cylinder for the intra-row weeding shovel to avoid grapevines. We also established a reasonable range for the extension speed of the hydraulic cylinder to minimize areas missed during weeding. Further analysis showed that using the minimum return speed of the hydraulic cylinder effectively reduced missed weeding areas. A virtual prototype model of the weeding machine was created in ADAMS. Using the coverage rate of weeding operation as the evaluation index, single-factor simulation tests determined that the extension speed of the piston rod in the obstacle avoidance hydraulic cylinder and the forward speed of the weeding machine are the main influencing factors. The preset threshold of the control system, which triggered the automatic obstacle avoidance mechanism when the obstacle avoidance rod reached a specific angle (the “Angle Threshold”), was identified as a secondary influencing factor. Other factors were considered irrelevant. Hydraulic cylinder extension speed, weeding machine forward speed, and angle threshold were chosen as the influencing factors. Following the principles of a Box–Behnken experimental design, a quadratic regression combination experiment was designed using a three-factor, three-level response surface analysis method. The evaluation criterion focused on the coverage rate of weeding operation. A regression model was developed to determine the coverage rate of the weeding operation, identifying the optimal parameters as follows: obstacle avoidance hydraulic cylinder extension speed of 120 mm/s, forward speed of the weeding machine at 0.6 m/s, and an angle threshold of 18°. The optimized coverage rate of the weeding operation achieved 86.1%. This study serves as a reference for further optimization of intra-row weeding machines in vineyards and for other crops.

Phase-Transitions in Disgust During Self-Initiated Eating Among Adolescents With Anorexia Nervosa and Related Low-Weight Eating Disorders and Matched Controls.

Understanding the emotional context of feeding behavior may help identify causal mechanisms of food avoidance among individuals with anorexia nervosa. Although predominant food avoidance models assume fear of fat drives feeding behavior, disgust may be more theoretically and proximally relevant to moment-to-moment experiences of feeding. This study, therefore, aimed to examine affect and food avoidance using automated affect analysis from facial response by measuring time-specific transitions in disgust during a laboratory eating paradigm. We hypothesized that phase transitions in disgust would distinguish temporally self-initiated eating from food avoidance. Sixty-three adolescents with anorexia nervosa or another low-weight eating disorder (LWED) and 27 age- and sex-matched controls were recruited as part of a larger study; 45 patients and 22 controls provided data on autonomous eating and facial affect during a laboratory meal. Dynamic structural equation models quantified moment-to-moment relationships between disgust and feeding behavior. Self-initiated eating was associated with greater increases in disgust, but not fear, intensity among those with LWED relative to control participants and greater disgust intensity predicted lower likelihood of self-initiated eating. Phasic transitions in disgust provide moment-to-moment evidence of affective influence on self-initiated eating and lend credibility to the hypothesis that disgust contributes to food avoidance and initiation in individuals with LWED.

Novel role of MHC class II transactivator in hepatitis B virus replication and viral counteraction.

The major histocompatibility class II (MHC II) transactivator, known as CIITA, is induced by Interferon gamma (IFN-γ) and plays a well-established role in regulating the expression of class II MHC molecules in antigen-presenting cells. Primary human hepatocytes (PHH) were isolated via therapeutic hepatectomy from two donors. The hepatocellular carcinoma (HCC) cell lines HepG2 and Huh7 were used for the mechanistic study, and HBV infection was performed in HepG2-NTCP cells. HBV DNA replication intermediates and secreted antigen levels were measured using Southern blotting and ELISA, respectively. We identified a non-canonical function of CIITA in the inhibition of hepatitis B virus (HBV) replication in both HCC cells and patient-derived PHH. Notably, in vivo experiments demonstrated that HBV DNA and secreted antigen levels were significantly decreased in mice injected with the CIITA construct. Mechanistically, CIITA inhibited HBV transcription and replication by suppressing the activity of HBV-specific enhancers/promoters. Indeed, CIITA exerts antiviral activity in hepatocytes through ERK1/2-mediated down-regulation of the expression of hepatocyte nuclear factor 1α (HNF1α) and HNF4α, which are essential factors for virus replication. In addition, silencing of CIITA significantly abolished the IFN-γ-mediated anti-HBV activity, suggesting that CIITA mediates the anti-HBV activity of IFN-γ to some extent. HBV X protein (HBx) counteracts the antiviral activity of CIITA via direct binding and impairing its function. Our findings reveal a novel antiviral mechanism of CIITA that involves the modulation of the ERK pathway to restrict HBV transcription. Additionally, our results suggest the possibility of a new immune avoidance mechanism involving HBx.

Autonomous navigation decision-making for ships in complex estuarine waters: Methodology and validation

This study focused on key scientific issues in the autonomous navigation for ships, including constraints on environmental and navigation rules, limitations on ship maneuverability, and collision avoidance mechanisms, to address the challenges of autonomous navigation decision-making for ships in complex estuarine waters and validate the feasibility and accuracy of the proposed methodology. A novel autonomous navigation decision-making method that can dynamically adapt to residual errors in a system and the random movements of target ships was proposed. The predictive model used to calculate decision plans and the simulation model used to execute and validate decision plans were separated. Environmental constituent elements were classified and modeled to digitize the environment. A navigation scenario was constructed based on the fusion of virtual and real information. The control and process prediction methods were proposed based on the nonlinear ship maneuvering characteristics. Navigation rules were summarized, analyzed, and integrated into the decision-making and execution process. The collision avoidance mechanism and calculation method for feasible course and speed range were studied. Simulation experiments were conducted using the North Channel of the Yangtze River Estuary as an example. The results demonstrated that the proposed method can accurately make autonomous navigation decisions, safely avoid collisions, and timely track routes in nearly realistic scenarios.

Cooperative autonomous obstacle avoidance control of spacecraft cluster via event-triggered reference governors

This paper conducts research on the design of a cooperative obstacle avoidance control mechanism for spacecraft cluster. It proposes an event-triggered reverse command regulator to address the current unidirectional obstacle avoidance mechanism, which only goes from the cluster reference command to the individual execution of spacecraft. The proposed mechanism enhances the survivability of spacecraft cluster in complex environments. By employing the designed event-triggered command regulator, the spacecraft can autonomously decide whether to execute a leader-following task based on whether the tracking error satisfies the performance requirements of the cluster closed-loop system. This allows the spacecraft to dynamically choose between task execution and temporarily “forgetting” the task to focus on collision avoidance, thereby increasing the collaborative flexibility of the spacecraft cluster. Furthermore, based on Lyapunov stability theory, the convergence of the proposed cooperative obstacle avoidance control algorithm is theoretically proven. Ultimately, simulation results demonstrate the real-time effectiveness of the designed cooperative obstacle avoidance solution.

The impacts of inter- and intra-seasonal burns on the terrestrial orchid Pterostylis curta

Prescribed burning is a management tool used for both management of fuel loads and for ecological purposes across fire prone areas. While in temperate areas wildfires usually occur during the hottest summer months, prescribed burns are generally conducted in autumn and spring, when conditions are more suitable for controlling fire. Orchids maintain avoidance mechanisms, such as persisting as dormant tubers during the predominant fire season, and therefore may be at risk from prescribed burns occurring during their active life cycle period. Using a glasshouse experiment, we investigated the impacts of fire season on the Australian orchid species Pterostylis curta. This approach allowed us to i) implement seasonal burns and relate impacts to quantifiable above and belowground life cycle stages of the study species, ii) isolate and assess the role of smoke, and iii) control for fire intensity and life stage of the study species at each of the treatment levels to enable robust comparison focused on fire season effects. We found that late autumn burns caused complete failure of a cohort in our glasshouse study. Heat alone was not the driver of tuber mortality, because soil heating was similar across all burn seasons, and plants burnt in the three other seasons were able to re-emerge strongly in the growing season after fire. Furthermore, a lack of post-fire emergence was due to tuber mortality, not dormancy. Our results highlight that there is likely an interaction between fire-related heat and the life cycle stage at which burning occurs, especially replacement tuber initiation, that drives post-fire demography. We show that orchids like P. curta had the lowest risk of negative impacts when burnt in the later stages of their growing season, and that an understanding of finer-scale phenological cycles can inform more robust fire management of orchid species.

Li-Fi Technology for Vehicle-To-Vehicle

The integration of Light Fidelity (Li-Fi) technology within Smart Cities to enhance vehicle-to-vehicle (V2V) communication systems. Highlighting the limitations of traditional radio frequency (RF) methods in managing increasing traffic and potential ecosystem impacts, the abstract introduces Li-Fi as a promising alternative. Li-Fi utilizes visible light to achieve high-speed data transfer rates, offering advantages such as enhanced efficiency, reduced latency, improved reliability, and heightened security. The objectives of implementing Li-Fi in V2V communication are delineated, emphasizing its potential to facilitate real-time data exchange crucial for autonomous driving and safety applications. The abstract further details the methodology and architecture of Li-Fi technology, illustrating its utilization of LED bulbs and photo detectors for data transmission and reception. Practical implementation strategies for integrating Li-Fi into V2V communication systems, including sensor-based distance measurement and automated collision avoidance mechanisms, are discussed. Ultimately, the abstract concludes by emphasizing Li-Fi's potential as a cost-effective solution to mitigate traffic accidents and enhance communication efficiency in Smart Cities. Keywords — Li-Fi, Illumination, Wi-Fi, LED, Photo Diode, Radio Frequency

THE INFLUENCE OF TAX AVOIDANCE, TUNNELING INCENTIVES AND BONUS MECHANISM ON TRANSFER PRICING WITH LEVERAGE AS A MODERATION VARIABLE

Purpose – This research aims to determine the effect of tax avoidance, tunneling incentives, and bonus mechanisms on transfer pricing with Leverage as a moderating variable in manufacturing companies in the consumer goods industry sector, which is listed on the Indonesia Stock Exchange in 2016-2021Design/methodology/approach—Purposive sampling was used for sample selection, and 13 companies were selected for a total of 51 research data. Multiple linear regression and MRA were used for analysis with SPSS version 25 software. Finding - The results of this study indicate that tax avoidance has a significant positive effect, and tunneling incentives and bonus mechanisms have a significant negative effect on transfer pricing. Meanwhile, Leverage cannot weaken the impact of tax avoidance, tunneling incentives, and bonus mechanisms on transfer pricing.Originality - The originality of this research is to include a moderating variable, namely Leverage.Keywords - Tax Avoidance, Tunneling Incentive, Bonus Mechanism, Transfer Pricing, Leverage

Distributed Adaptive Formation Tracking for a Class of Uncertain Nonlinear Multiagent Systems: Guaranteed Connectivity Under Moving Obstacles.

This article explores a guaranteed network connectivity problem during moving obstacle avoidance within a distributed formation tracking framework for uncertain nonlinear multiagent systems with range constraints. We investigate this problem based on a new adaptive distributed design using nonlinear errors and auxiliary signals. Within the detection range, each agent regards other agents and static or dynamic objects as obstacles. The nonlinear error variables for formation tracking and collision avoidance are presented, and the auxiliary signals in formation tracking errors are introduced to maintain network connectivity under the avoidance mechanism. The adaptive formation controllers using command-filtered backstepping are constructed to ensure closed-loop stability with collision avoidance and preserved connectivity. Compared with the previous formation results, the resulting features are as follows: 1) the nonlinear error function for the avoidance mechanism is considered an error variable, and an adaptive tuning mechanism for estimating the dynamic obstacle velocity is derived in a Lyapunov-based control design procedure; 2) network connectivity during dynamic obstacle avoidance is preserved by constructing the auxiliary signals; and 3) owing to neural networks-based compensating variables, the bounding conditions of time derivatives of virtual controllers are not required in the stability analysis.

Dynamics characteristic of pedestrians’ particular overtaking behavior based on an improved social force model

The overtaking behavior of individuals under anxious panic is a major causative factor of crowded trampling accidents. In order to simulate the overtaking behavior of individuals experiencing anxiety and panic in a single-exit room within a normal pedestrian flow, an improved social force model is proposed to simulate crowd movement at local medium and high density through introducing the bypass overtaking mechanism, the side overtaking mechanism, and the side avoidance mechanism generated by association. The numerical simulation verifies the model’s validity. The effect of the size and number of overtaking individuals on the pedestrian flow are explored. The results show that the new model can simultaneously reproduce a variety of overtaking behaviors and their associated behaviors in line with reality. The larger size of the overtaking individuals are, the easier it is to produce overtaking behaviors and the more difficult it is to overtake. With the increase of the number of overtaking individuals, the evacuation time becomes longer, but there is no linear relationship between them. When the initial pedestrian density is 0.37ped/m2, with time evolution, the appearance frequency of local density greater than 0.8ped/m2 suddenly increases, and the comfort and safety of pedestrian movement decreases. The results of this paper can enrich the social force simulation model of pedestrian flow and provide a theoretical guidance for the evacuation of pedestrian flow with a few overtaking individuals in the room.

Visual attention is not attuned to non-human animal targets’ pathogenicity: an evolutionary mismatch perspective

A considerable amount of research has revealed that there exists an evolutionary mismatch between ancestral environments and conditions following the rise of agriculture regarding the contact between humans and animal reservoirs of infectious diseases. Based on this evolutionary mismatch framework, we examined whether visual attention exhibits adaptive attunement toward animal targets’ pathogenicity. Consistent with our predictions, faces bearing heuristic infection cues held attention to a greater extent than did animal vectors of zoonotic infectious diseases. Moreover, the results indicated that attention showed a specialized vigilance toward processing facial cues connoting the presence of infectious diseases, whereas it was allocated comparably between animal disease vectors and disease-irrelevant animals. On the other hand, the pathogen salience manipulation employed to amplify the participants’ contextual-level anti-pathogen motives did not moderate the selective allocation of attentional resources. The fact that visual attention seems poorly equipped to detect and encode animals’ zoonotic transmission risk supports the idea that our evolved disease avoidance mechanisms might have limited effectiveness in combating global outbreaks originating from zoonotic emerging infectious diseases.

Neuronal basis and diverse mechanisms of pathogen avoidance in Caenorhabditis elegans.

Pathogen avoidance behaviour has been observed across animal taxa as a vital host-microbe interaction mechanism. The nematode Caenorhabditis elegans has evolved multiple diverse mechanisms for pathogen avoidance under natural selection pressure. We summarise the current knowledge of the stimuli that trigger pathogen avoidance, including alterations in aerotaxis, intestinal bloating, and metabolites. We then survey the neural circuits involved in pathogen avoidance, transgenerational epigenetic inheritance of pathogen avoidance, signalling crosstalk between pathogen avoidance and innate immunity, and C. elegans avoidance of non-Pseudomonas bacteria. In this review, we highlight the latest advances in understanding host-microbe interactions and the gut-brain axis.

Status Consumption as Coping With Fear of Death: The Mediating Role of Death Avoidance and the Moderating Role of Materialism.

Individuals employ various coping mechanisms to deal with the fear of death. While materialism and status consumption are commonly recognized in the literature as such strategies, no study has yet empirically tested this premise. Accordingly, this study examined the mediating role of death avoidance in the link between the fear of death and death-related status consumption (DRSC). Data obtained from 346 participants were analyzed using structural equation modeling. The results showed that fear of death significantly and positively influences DRSC and that death avoidance partially and positively mediates this relationship. Results also revealed that materialism strengthens the relationship between fear of death and DRSC, while it does not significantly moderate the relationship between death avoidance and DRSC. These results support the conclusion that death-related status consumption may play a critical role as an avoidance mechanism in coping with the fear of death. This study, being among the few that investigate death-related consumer behaviors, enriches both terror management theory and the literature on consumer behavior in crises.

Persist or Perish: Can Bats Threatened with Extinction Persist and Recover from White-nose Syndrome?

Emerging mycoses are an increasing concern in wildlife and human health. Given the historical rarity of fungal pathogens in warm-bodied vertebrates, there is a need to better understand how to manage mycoses and facilitate recovery in affected host populations. We explore challenges to host survival and mechanisms of host recovery in three bat species (Myotis lucifugus, Perimyotis subflavus, and M. septentrionalis) threatened with extinction by the mycosis, white-nose syndrome (WNS) as it continues to spread across North America. We present evidence from the literature that bats surviving WNS are exhibiting mechanisms of avoidance (by selecting microclimates within roosts) and tolerance (by increasing winter fat reserves), which may help avoid costs of immunopathology incurred by a maladaptive host resistance response. We discuss management actions for facilitating species recovery that take into consideration disease pressures (e.g., environmental reservoirs) and mechanisms underlying persistence, and suggest strategies that alleviate costs of immunopathology and target mechanisms of avoidance (protect or create refugia) and tolerance (increase body condition). We also propose strategies that target population and species-level recovery, including increasing reproductive success and reducing other stressors (e.g., wind turbine mortality). The rarity of fungal pathogens paired with the increasing frequency of emerging mycoses in warm-bodied vertebrate systems, including humans, requires a need to challenge common conventions about how diseases operate, how hosts respond, and how these systems could be managed to increase probability of recovery in host populations.

HUMAN FOLLOWER ROBOT

The development of a Human Follower Robot incorporating IR and Ultrasonic Sensors represents an innovative venture in robotics and automation, aimed at creating a versatile machine capable of tracking and following targets while navigating obstacles. This project is fuelled by the vision of combining sensor technology, microcontroller programming, and robotic design to birth a robot capable of graceful traversal and intelligent target pursuit. At its core, the project relies on the integration of two essential sensor technologies: Infrared (IR) and Ultrasonic sensors. IR sensors, functioning akin to human eyesight, detect objects by emitting and receiving infrared light, enabling the robot to recognize the presence of a target within its line of sight. Concurrently, ultrasonic sensors enhance the robot's perception by determining distances through sound waves, facilitating obstacle avoidance and maintaining a safe tracking distance from the target. The project's foundation comprises key components working in tandem to fulfil the robot's objectives. A microcontroller, such as Arduino or Raspberry Pi, orchestrates actions by processing sensor data and regulating movements. IR sensors act as vigilant eyes, detecting the target, while ultrasonic sensors serve as the echolocation system, enabling seamless navigation in cluttered environments. Motors and wheels propel the robot, providing motion and directional control, while a reliable power supply, such as batteries, sustains its operations. Four pivotal milestones define the project's core goals. Firstly, the development of algorithms and code for effective object detection using IR sensors enables the robot to discern the presence of a target. Secondly, obstacle avoidance mechanisms are implemented through ultrasonic sensors, ensuring adept manoeuvring around barriers and hazards. Thirdly, proximity control is prioritized to maintain an optimal and safe following distance from the target, preventing collisions. Lastly, efforts focus on enabling smooth and precise movement to ensure accurate and responsive tracking behaviour. The potential applications of such a robot are diverse. Apart from assisting visually impaired individuals by guiding and avoiding obstacles, these robots can serve as automated tour guides, offering informative experiences in museums or exhibitions. Additionally, their utility extends to surveillance and security, where they can monitor areas and track intruders. Ultimately, this project holds promise for a future where intelligent robots seamlessly follow, guide, and protect, enriching lives with their remarkable capabilities. Key Words: Human Follower Robot, IR Sensors, Human Follower Robot, IR Sensors, Ultrasonic Sensors, Robotics, Automation, Sensor Technology etc

Trajectory Planning and Singularity Avoidance Algorithm for Robotic Arm Obstacle Avoidance Based on an Improved Fast Marching Tree

The quest for efficient and safe trajectory planning in robotic manipulation poses significant challenges, particularly in complex obstacle environments where the risk of encountering singularities and obstacles is high. Addressing this critical issue, our study presents a novel enhancement of the Fast Marching Tree (FMT) algorithm, ingeniously designed to navigate the complex terrain of Cartesian space with an unprecedented level of finesse. At the heart of our approach lies a sophisticated two-stage path point sampling strategy, ingeniously coupled with a singularity avoidance mechanism that leverages geometric perception to assess and mitigate the risk of encountering problematic configurations. This innovative method not only facilitates seamless obstacle navigation but also adeptly circumvents the perilous zones of singularity, ensuring a smooth and uninterrupted path for the robotic arm. To further refine the trajectory, we incorporate a quasi-uniform cubic B-spline curve, optimizing the path for both efficiency and smoothness. Our comprehensive simulation experiments underscore the superiority of our algorithm, showcasing its ability to consistently achieve shorter, more efficient paths while steadfastly avoiding obstacles and singularities. The practical applicability of our method is further corroborated through successful implementation in real-world robotic arm trajectory planning scenarios, highlighting its potential to revolutionize the field with its robustness and adaptability.

Improved Hybrid Model for Obstacle Detection and Avoidance in Robot Operating System Framework (Rapidly Exploring Random Tree and Dynamic Windows Approach).

The integration of machine learning and robotics brings promising potential to tackle the application challenges of mobile robot navigation in industries. The real-world environment is highly dynamic and unpredictable, with increasing necessities for efficiency and safety. This demands a multi-faceted approach that combines advanced sensing, robust obstacle detection, and avoidance mechanisms for an effective robot navigation experience. While hybrid methods with default robot operating system (ROS) navigation stack have demonstrated significant results, their performance in real time and highly dynamic environments remains a challenge. These environments are characterized by continuously changing conditions, which can impact the precision of obstacle detection systems and efficient avoidance control decision-making processes. In response to these challenges, this paper presents a novel solution that combines a rapidly exploring random tree (RRT)-integrated ROS navigation stack and a pre-trained YOLOv7 object detection model to enhance the capability of the developed work on the NAV-YOLO system. The proposed approach leveraged the high accuracy of YOLOv7 obstacle detection and the efficient path-planning capabilities of RRT and dynamic windows approach (DWA) to improve the navigation performance of mobile robots in real-world complex and dynamically changing settings. Extensive simulation and real-world robot platform experiments were conducted to evaluate the efficiency of the proposed solution. The result demonstrated a high-level obstacle avoidance capability, ensuring the safety and efficiency of mobile robot navigation operations in aviation environments.

Structures of the ribosome bound to EF-Tu-isoleucine tRNA elucidate the mechanism of AUG avoidance.

The frequency of errors upon decoding of messenger RNA by the bacterial ribosome is low, with one misreading event per 1 × 104 codons. In the universal genetic code, the AUN codon box specifies two amino acids, isoleucine and methionine. In bacteria and archaea, decoding specificity of the AUA and AUG codons relies on the wobble avoidance strategy that requires modification of C34 in the anticodon loop of isoleucine transfer RNAIleCAU (tRNAIleCAU). Bacterial tRNAIleCAU with 2-lysylcytidine (lysidine) at the wobble position deciphers AUA while avoiding AUG. Here we report cryo-electron microscopy structures of the Escherichia coli 70S ribosome complexed with elongation factor thermo unstable (EF-Tu) and isoleucine-tRNAIleLAU in the process of decoding AUA and AUG. Lysidine in tRNAIleLAU excludes AUG by promoting the formation of an unusual Hoogsteen purine-pyrimidine nucleobase geometry at the third position of the codon, weakening the interactions with the mRNA and destabilizing the EF-Tu ternary complex. Our findings elucidate the molecular mechanism by which tRNAIleLAU specifically decodes AUA over AUG.

Immune system modulation & virus transmission during parasitism identified by multi-species transcriptomics of a declining insect biocontrol system

BackgroundThe Argentine stem weevil (ASW, Listronotus bonariensis) is a significant pasture pest in Aotearoa New Zealand, primarily controlled by the parasitoid biocontrol agent Microctonus hyperodae. Despite providing effective control of ASW soon after release, M. hyperodae parasitism rates have since declined significantly, with ASW hypothesised to have evolved resistance to its biocontrol agent. While the parasitism arsenal of M. hyperodae has previously been investigated, revealing many venom components and an exogenous novel DNA virus Microctonus hyperodae filamentous virus (MhFV), the effects of said arsenal on gene expression in ASW during parasitism have not been examined. In this study, we performed a multi-species transcriptomic analysis to investigate the biology of ASW parasitism by M. hyperodae, as well as the decline in efficacy of this biocontrol system.ResultsThe transcriptomic response of ASW to parasitism by M. hyperodae involves modulation of the weevil’s innate immune system, flight muscle components, and lipid and glucose metabolism. The multispecies approach also revealed continued expression of venom components in parasitised ASW, as well as the transmission of MhFV to weevils during parasitism and some interrupted parasitism attempts. Transcriptomics did not detect a clear indication of parasitoid avoidance or other mechanisms to explain biocontrol decline.ConclusionsThis study has expanded our understanding of interactions between M. hyperodae and ASW in a biocontrol system of critical importance to Aotearoa-New Zealand’s agricultural economy. Transmission of MhFV to ASW during successful and interrupted parasitism attempts may link to a premature mortality phenomenon in ASW, hypothesised to be a result of a toxin-antitoxin system. Further research into MhFV and its potential role in ASW premature mortality is required to explore whether manipulation of this viral infection has the potential to increase biocontrol efficacy in future.