Optimal Position Research Articles

Experimental comparison of critical performance for variable geometry ejectors with different mixer structures

To further optimize the performance of Solar-driven Ejector Refrigeration system under variable driving conditions, ejectors design using conical-cylindrical mixers are more effective than using cylindrical mixers were elucidated. The effects of the nozzle exit position (NXP), area ratio (Ar), and expansion ratio (E) on the performance of the conical-cylindrical mixer ejector (CCME) and the cylindrical mixer ejector (CME) were investigated. It was revealed that compared with the performance of the CME at the optimal nozzle exit position, the variable geometry CCME exists a NXP range where both the critical entrainment ratio (Ercri) and critical compression ratio (Ccri) are larger. This NXP range can be widened by appropriately reducing the NXP or Ar of the CCME under a specified expansion ratio. Besides, under variable expansion ratios, the expansion ratio range in which both Ercri and Ccri of the CCME are better than those of the CME can be widened by appropriately reducing the NXP or Ar of the CCME. The results demonstrated that the CCME is more suitable for variable expansion ratios than the CME. This implies that using the variable geometry CCME has a higher energy utilization efficiency in a Solar-driven Ejector Refrigeration system than that of using the CME. This work provides a promising guide for achieving higher energy efficiency of an ejector refrigeration system under variable driving conditions.

Lung-inspired hybrid flow field to enhance PEMFC performance: A case of dual optimization by response surface and artificial intelligence

The design and optimization of flow field play a crucial role in the development of proton exchange membrane fuel cells (PEMFC). This study presents a modular tri-layer lung-inspired hybrid flow field (LHFF) design that incorporates 2D and 3D flow field advantages. The key structural parameters of LHFF mainly encompass G, D, and S of reactant distribution layer and A of directional transport layer. The LHFFs with different G have been investigated, and the G = 2 LHFF exhibits a 16.55% enhancement in maximum net power density compared to conventional parallel flow field. Then the response surface methodology (RSM) and artificial intelligence methodology (AIM) have been employed to optimize the D, S, and A structure parameters of LHFF to determine the optimal inlet position of water removal layer. The LHFFs optimized by RSM and AIM show a further increase in maximum net power density by 3.58% and 4.10%, respectively. The optimized LHFFs achieve a trade-off among species distribution, water management, and pressure drop, with high consistency between numerical and experimental results. It demonstrates the reliability of artificial intelligence in optimizing PEMFC flow field. Therefore, the optimization strategies presented here hold a promising solution to improve the flow fields in other electrochemical systems.

Large-Eddy Simulation of Flow Separation Control in Low-Speed Diffuser Cascade with Splitter Blades

The passive flow control technology of using splitter blades in low-speed diffuser cascade was investigated in this study. Based on the Reynolds average Navier-Stokes calculations, the arrangement parameters of the splitter blades were studied in detail to determine the optimal parameters. The large-eddy simulation was performed on the base case and the optimized splitter blade case to obtain the transient vortex structures and unsteady flow characteristics of the cascade. The results show that the aerodynamic performance of the cascade was susceptible to the position of the splitter blades. The optimal position of the splitter blades was located in the middle of the main blades near the leading edge. When the cascade was arranged with optimized splitter blades, the static pressure coefficient was improved and the stall occurrence was delayed. The scale and intensity of the separation vortices generated on the suction surface of the main blade decreased. In addition, the separation vortices of the main blade and the splitter blade interacted and rapidly decomposed into small-scale vortices downstream of the cascade, reducing the flow loss. The stability of the cascade was enhanced.

Free-Field Hearing Test in Noise with Free Head Rotation for Evaluation of Monaural Hearing.

There is a discrepancy between the hearing test results in patients with single-sided deafness (SSD) and their reported outcome measures. This is probably due to the presence of two elements in everyday situations: noise and head movements. We developed a stereo-audiometric test in noise with free head movements to evaluate movements and auditory performance in monaural and binaural conditions in normal hearing volunteers with one occluded ear. Tests were performed in the binaural condition (BIN), with the left ear (LEO) or the right ear occluded (REO). The signal was emitted by one of the seven speakers, placed every 30° in a semicircle, and the noise (cocktail party) by all speakers. Subjects turned their head freely to obtain the most comfortable listening position, then repeated 10 sentences in this position. In monaural conditions, the sums of rotations (head rotations for an optimal hearing position in degrees, random signal azimuth, 1 to 15 signal ad lib signal presentations) were higher (LEO 255 ± 212°, REO 308 ± 208° versus BIN 74 ± 76, p < 0.001, ANOVA) than those in the BIN condition and the discrimination score (out of 10) was lower than that in the BIN condition (LEO 5 ± 1, REO 7 ± 1 versus BIN 8 ± 1, respectively p < 0.001 and p < 0.05 ANOVA). In the monaural condition, total rotation and discrimination in noise were negatively correlated with difficulty (Pearson r = -0.68, p < 0.01 and -0.51, p < 0.05, respectively). Subjects' behaviors were different in optimizing their hearing in noise via head rotation. The evaluation of head movements seems to be a significant parameter in predicting the difficulty of monaural hearing in noisy environments.

A novel two-dimensional GaN/InGaN heterostructure for photocatalytic water splitting: A first-principles calculation

The pursuit of optimal bandgap and band edge positions is crucial for effective photocatalytic catalysts, leading to significant attentions in both experimental and theoretical research on modulating the band structure of semiconductor photocatalysts. In this study, the electronic, optical and photocatalytic properties of 2D monolayer GaN and GaN/InGaN heterostructures are investigated using DFT calculations. It reveals that introducing strain is an effective approach to not only alter the band gap type from indirect to direct but also influence the magnitude of the band gap. At a 10% tensile strain, a Z-type heterostructure is formed for the 2D GaN/InGaN heterostructures, which proves favorable for enhancing the efficiency of photocatalytic water splitting. However, it is worth noting that the band gap type remains indirect, necessitating additional energy for electron transitions. On the other hand, when increasing the compressive strain from − 2.5% to − 5%, the 2D GaN/InGaN heterostructure transforms from type I to type II, exhibiting direct band gaps with an enhanced light absorption range. This results in a significant redshift and increased optical absorption intensity within the visible light range, leading to a substantial enhancement in photocatalytic efficiency. Consequently, our findings demonstrate that the 2D GaN/InGaN heterostructure holds promising potential as a candidate material for efficient photocatalytic water splitting applications.

Study of the reaction mechanism for preparing powdered activated coke with SO2 adsorption capability via one-step rapid activation method under flue gas atmosphere

In this study, the impact of different reaction times on the preparation of powdered activated carbon (PAC) using a one-step rapid activation method under flue gas atmosphere is investigated, and the underlying reaction mechanism is summarized. Results indicate that the reaction process of this method can be divided into three stages: stage Ⅰ is the rapid release of volatiles and the rapid consumption of O2, primarily occurring within a reaction time range of 0–0.5 s; stage Ⅱ is mainly the continuous release and diffusion of volatiles, which is the carbonization and activation coupling reaction stage, and the carbonization process is the main in this stage. This stage mainly occurs at the reaction time range of 0.5–2.0 s when SL-coal is used as material, and that is 0.5–3.0 s when JJ-coal is used as material; stage Ⅲ is mainly the activation stage, during which activated components diffuse to both the surface and interior of particles. This stage mainly involves the reaction stage of CO2 and H2O (g) activation, and it mainly occurs at the reaction time range of 2.0–4.0 s when SL-coal is used as material, and that is 3.0–4.0 s when JJ-coal is used as material. Besides, the main function of the first two stages is to provide more diffusion channels and contact surfaces/activation sites for the diffusion and activation of the activated components in the third stage. Mastering the reaction mechanism would serve as a crucial reference and foundation for designing the structure, size of the reactor, and optimal positioning of the activator nozzle in PAC preparation.

Identification of the optimal doping position of hetero-atoms in chalcogen-doped Fe–N–C catalysts for oxygen reduction reaction

The excellent oxygen reduction reaction (ORR) activity of Fe–N–C catalysts in acidic media makes them potential for low-cost proton exchange membrane fuel cells. In recent years, it has been shown that heteroatoms (B, O, S, P, Cl, F, etc.) can be used as electron-withdrawing groups to modulate the planar structure and electron distribution of the Fe–Nx active sites to achieve simultaneous improvement of catalytic activity and stability. However, the optimal location of the heteroatoms remains unclear. Here, taking chalcogen heteroatoms (S and Se) as an example, we control the doping positions and investigate their effect on the ORR performance of the Fe–N–C catalysts. The first coordination shell of the iron single atom is identified as the optimal doping position. The optimized catalyst Fe–N3S1/NC and Fe–N3Se1/NC demonstrate improved activity and stability in both half cells and fuel cells. This work provides insights into the enhancement mechanism of heteroatom doping of single-atom catalysts.

A novel deep reinforcement learning framework with BiLSTM-Attention networks for algorithmic trading

The financial market, as a complex nonlinear dynamic system frequently influenced by various factors, such as international investment capital, is very challenging to build trading strategies from the obtained market information. Deep Reinforcement Learning (DRL) combines the perceptual capability of deep learning and the control decision making capability of reinforcement learning to learn the mapping between financial market states and trading decisions by interacting with the environment. In this paper, an enhanced stock trading strategy, denominated efficient deep State-Action-Reward-State-Action (SARSA), is presented to tackle the algorithmic trading problem of determining optimal trading positions in the daily trading activities of the stock market. This algorithm is recognized for its properties of stable learning and convergence, attributes of critical significance within the financial domain, where stability assumes paramount importance, and excessive risk-taking should be averted. Furthermore, a novel deep network architecture called Bidirectional Long Short-Term Memory (BiLSTM)-Attention is introduced to address the challenge of accurately presenting the complex and volatile stock market. The BiLSTM-Attention greatly enhances the network’s capacity to recognize key features and patterns in stock market data, allowing agents to focus on the most relevant aspects of the data. Evaluations on DJI, SP500, GE, IXIC datasets from January 1, 2008 to December 31, 2022 show that our efficient deep SARSA algorithm outperforms a wide range of traditional strategies (B&H, S&H, MR, TF) and DRL-based strategies (TDQN, DQN-Vanilla). For example, on the IXIC dataset, the efficient deep SARSA strategy achieves an attractive Cumulative Return (CR) of 582.17% and a Sharpe Ratio (ShR) of 1.86, outperforming all other methods. These experimental results prove the performance of our method in enhancing stock trading strategies.

The views and perceptions of training in physical health care amongst mental health nurses, managers of mental health nurses and trainers: A systematically constructed narrative synthesis.

People with serious mental illness have higher morbidity and mortality rates compared with the general population. Mental health nurses are in an optimal position to address physical healthcare needs and inequalities experienced by this group. Research evidence suggests that mental health nurses may lack appropriate skills and confidence. The training needs of mental health nurses in physical health care of patients with serious mental illness and the perceived effectiveness of training that is provided to mental health nurses are explored in this review. A narrative synthesis approach (PROSPERO protocol registration ID=CRD42021230923) involved searching five electronic databases (PsycInfo, Cinahl, Embase, Medline and Web of Science) from 1990 to 2021. Study quality was assessed, and analysis and synthesis were initially deductively guided by a theoretical framework of training effectiveness prior to inductive data analysis. Eleven studies met the inclusion criteria. For studies examining perceived effectiveness of training, four themes were derived from the theoretical framework (individual trainee characteristics, work environment, learning outcomes, transfer of training to job) and further theme (service user factor) generated inductively. For studies examining training needs, three themes were derived inductively (knowledge and skills requirements, modality of training, service and healthcare factors). The study highlights the need for ongoing learning to improve practice. It also provides another perspective in terms of understanding the influence of service user factors (motivation and mental state) in designing and implementing of future training in mental health settings.

A task level fusion autonomous switching mechanism.

Positioning technology is an important component of environmental perception. It is also the basis for autonomous decision-making and motion control of firefighting robots. However, some issues such as positioning in indoor scenarios still remain inherent challenges. The positioning accuracy of the fire emergency reaction dispatching (FERD) system is far from adequate to support some applications for firefighting and rescue in indoor scenarios with multiple obstacles. To solve this problem, this paper proposes a fusion module based on the Blackboard architecture. This module aims to improve the positioning accuracy of a single sensor of the unmanned vehicles within the FERD system. To reduce the risk of autonomous decision-making of the unmanned vehicles, this module uses a comprehensive manner of multiple channels to complement or correct the positioning of the firefighting robots. Specifically, this module has been developed to fusion a variety of relevant processes for precise positioning. This process mainly includes six strategies. These strategies are the denoising, spatial alignment, confidence degree update, observation filtering, data fusion, and fusion decision. These strategies merge with the current scenarios-related parameter data, empirical data on sensor errors, and information to form a series of norms. This paper then proceeds to gain experience data with the confidence degree, error of different sensors, and timeliness of this module by training in an indoor scenario with multiple obstacles. This process is from data of multiple sensors (bottom-level) to control decisions knowledge-based (up-level). This process can obtain globally optimal positioning results. Finally, this paper evaluates the performance of this fusion module for the FERD system. The experimental results show that this fusion module can effectively improve positioning accuracy in an indoor scenario with multiple obstacles. Code is available at https://github.com/lvbingyu-zeze/gopath/tree/master.

Single-Layer Differential-Fed Wideband Metasurface Antenna Using Characteristic Mode Analysis

A single-layer differential-fed (DF) wideband metasurface (MTS) antenna is proposed in this paper. As the prototype, a three-by-three MTS formed by identical rectangular patches is investigated at first. We observe that there are many unwanted higher-order modes (HOMs) resonating near the wanted fundamental mode. Two probes with differential signals feed MTS on its centerline to suppress the majority of HOMs. The remaining HOM can be removed from the discussed frequency range by modifying the prototype MTS to a nonuniform structure. Then, the optimal feeding positions (FPs) are determined by a quantitative prediction of the impendence bandwidth (IBW) without any physical feeds involved. The processes of HOMs suppression and FPs determination are based on characteristic mode analysis with the virtual probes. Moreover, two interdigital capacitor plates are loaded on the probes to improve the impedance matching of the antenna. Finally, the proposed DF MTS antenna is fabricated and measured. The measured −10-dB IBW is 18.4% (4.93 to 5.93 GHz) with broadside radiation, stable high gains, and front-to-back ratios better than 21 dB.

3-dimensional ct versus angiography guided pci for ostial rca lesions

Abstract Background Geographical stent-ostium mismatch is an important predictor of target lesion failure (TLF) after PCI of an aorto-ostial right coronary artery (RCA) lesion. Purpose We hypothesize that a pre-procedural 3-dimensional coronary CT angiography (3DCT) to determine the optimal C-arm angle of the X-ray system with the most accurate visualization of the aorto-ostial angle could allow optimal stent implantation at the level of the ostium and avoid excessive use of radiation and contrast. Methods This is a single centre trial randomizing 30 patients with an indication for non-emergent PCI of an ostial RCA lesion between 3DCT (intervention group) versus angiography guided strategy (control group). While in the control group the C-arm angle was at the operators’ discretion, in the intervention group the angle was determined based on a pre-PCI CT scan with 3D reconstruction using Materialise Mimics Innovation Suite software. A pre- and post-PCI IVUS is performed in all patients and analyzed by a blinded core lab. The primary endpoint is absence of geographical mismatch on IVUS defined as full stent coverage of the ostium and maximal aortic protrusion equal or less than 3mm. Secondary, we also aim to investigate whether a pre-procedural 3DCT may reduce procedural radiation, contrast use, may predict IVUS parameters (minimal luminal area (MLA), calcification), stent sizing and may promote stent expansion. Finally, MACE rate is evaluated at 1 month. Results The full patient dataset (n=30) including primary and all secondary endpoints will be available for presentation at the ESC congress. Currently, 27 patients were randomized. An interim analysis shows the following findings. There is significant patient heterogeneity considering the optimal angle for stent implantation, underscoring the potential benefit for individualized pre-procedural CT planning. In general, more extreme LAO angles were used in patients randomized to the intervention group (picture 1). While the stent was implanted in optimal position in 13/13 (100%) patients randomized to the intervention group, geographical stent mismatch was present in 5/14 (36%) patients randomized to the control group (interim p-value 0.07) (picture 2). The number of cine acquisitions performed before stent implantation (1±1.87 vs. 3.5±0.60; p=0.0007), the amount of contrast used (60±24.5 vs. 114±37.8 mL; p=0.0002), radiation dose (209 [186,315] vs. 497 [411,678] mGy; p=0.01) and procedure time (30 [20,38] vs. 50 [39,66] min; p=0.005) were significantly lower in patients randomized to the intervention group. There was a highly significant correlation between the calcium arc determined by CT and IVUS (R² = 0.84). No MACE occurred at 1 month. Conclusion We showed that pre-procedural CT planning for PCI of aorto-ostial RCA lesions allowed for optimal stent positioning while reducing procedure time, contrast and radiation use.Picture 1Picture 2

Investigation of an indirect measurement method of ultrasonic bone cutting forces based on strain sensors

The measurement model of ultrasonic bone cutting force is an urgent problem to be solved in the application of ultrasonic osteotomy in robot assisted orthopedic surgery, which is of great significance for achieving bone layer perception and cutting force control during the surgical process. This article proposes an indirect measurement method of ultrasonic bone cutting force based on strain. Firstly, according to the axial vibration strain distribution curve of the ultrasonic osteotomy, the optimal measurement position for the strain gauge is selected as the high strain position (with a high signal-to-noise ratio), and the temperature compensation strategy of the dual strain gauge method is used to reduce or eliminate the thermal effects during the strain measurement. Then, the Pearson correlation coefficient between strain and cutting force in different cutting directions is calculated, and there is a strong positive correlation between strain and cutting force. Finally, the least squares method was used to obtain indirect measurement models of ultrasonic bone cutting force based on strain in different cutting directions. The experimental results showed that the waveform of cutting force measured indirectly based on strain was in good agreement with the waveform of cutting force measured directly by the force sensor. The error between the effective value of indirect measurement of cutting force and the effective value of direct measurement of cutting force did not exceed 13%, which verified the feasibility and effectiveness of this method. The indirect measurement models of ultrasonic bone cutting force based on strain will become a cost-effective choice with good accuracy and high sensitivity, providing a theoretical basis for orthopedic robots to perceive and control cutting force, and promoting the clinical application of ultrasonic osteotomy in orthopedic robots.

Ellipsoidal Trajectory Optimization for Minimizing Latency and Data Transmission Energy in UAV-Assisted MEC Using Deep Reinforcement Learning

Due to their flexible deployment and movement capability, unmanned aerial vehicles (UAVs) are being utilized as flying mobile edge computing (MEC) platforms, offering real-time computational resources and low-latency data processing for a wide range of applications. This article aims to explore a UAV-assisted MEC system where multiple UAVs provide MEC services to mobile devices (MDs) using an ellipsoidal trajectory. Depending on the position, size, and orientation of the ellipsoidal trajectories, the coverage area of the UAV, the energy consumption, and the task transmission latency of MDs change. This has rarely been investigated in the existing works. Furthermore, unlike other studies, we consider that each MD has varying task offloading rates, which, together with varying user densities, makes the problem more challenging. Therefore, we formulate an optimization problem that finds the center position, major radius, minor radius, and rotation angle of the ellipsoidal trajectory of UAV-assisted MEC servers, to minimize the total transmission latency and energy consumption of mobile devices while taking into account the required data transmission rate, task transmission time, and energy consumption constraints. Then, we transform this optimization problem into a Markov decision process and propose a deep Q-learning-based ellipsoidal trajectory optimization (DETO) algorithm, to resolve it. The results from our simulations demonstrate that DETO efficiently computes the optimal position and trajectory for each UAV, and can achieve better performance compared to other baselines, leading to the reduced data transmission latency and energy consumption of mobile devices across a range of simulation scenarios.

Optimization of facial expression recognition based on dual attention mechanism by lightweight network model

As a deep learning network model, ResNet50 can effectively recognize facial expressions to a certain extent, but there are still problems such as insufficient extraction of local effective feature information and a large number of parameters. In this paper, we take ResNet50 as the basic framework to optimize and improve this network. Firstly, by analyzing the influence mechanism of the attention mechanism module on the network feature information circulation, the optimal embedding position of CBAM (Convolutional Block Attention Module) and SE modules in the ResNet50 network is thus determined to effectively extract local key information, and then the number of model parameters is effectively reduced by embedding the depth separable module. To validate the performance of the improved ResNet50 model, the recognition accuracy reached 71.72% and 95.72% by ablation experiments using Fer2013 and CK+ datasets, respectively. We then used the trained model to classify the homemade dataset, and the recognition accuracy reached 92.86%. In addition, compared with the current more advanced methods, the improved ResNet50 network model proposed in this paper can maintain a balance between model complexity and recognition ability and can provide a technical reference for facial expression recognition research.

Optimization of furniture combination design and space configuration based on graph theory

Abstract This paper is based on graph theory, combined with a particle swarm optimization algorithm to find the optimal solution in the whole particle swarm through continuous iteration and obtain the sum of squares of each variable in the particle cognitive domain. Searching for the global optimal position calculates the inertia weights in the particle swarm algorithm and changes the velocity and position of the particles based on the motion properties of graph theory to improve the global search ability. The domain competition operator is executed after particle swarm initialization, and a hybrid crossover strategy is used to select a crossover point, which improves the algorithm’s performance by exchanging information with the global optimum. Based on graph theory, the spatial configuration optimization of furniture combinations is scored, in which the average score of furniture space ranges from 3.3 to 6.2, and the average score of spatial configuration optimization ranges from 4.5 to 8. Therefore, based on graph theory, the reasonable furniture form for spatial layout optimization can fully reflect the practical function of the space, comfort, and the creation of a spatial atmosphere.

Optimal lateral embedded position of piezoelectric energy harvesters under various traffic conditions with wheel-path distribution

Piezoelectric energy harvesting from traffic load has gained extensive attention for potentiality as a renewable energy source. In existing in situ experiments, generally only one vehicle is employed, while the wheel-path of the vehicle and embedded positions of piezoelectric energy harvester (PEH) units are both fixed. However, in an actual traffic condition, vehicles travel randomly along width of pavements, which means the wheel-path varies over time and among vehicles. In this study, an electromechanical model is established for the PEH units under actual traffic conditions with wheel-path distribution, and is validated with finite element analysis and experiments. Then the electrical performance of PEH units embedded at various locations along pavements’ lateral direction is investigated under various traffic speeds. It is found that the optimal lateral embedded locations of the PEH units should be adjusted according to the prescribed traffic speed of the roads. Specifically, PEH units should be embedded at the tire-road contact areas for road with low traffic speeds (&lt;15 m/s), while they should be embedded at the center of the pavement with high traffic speeds (&gt;25 m/s). These mathematical results may serve as guidelines for selecting optimal lateral embedded locations for PEH units embedded in pavements.

How much does issue salience matter? A model with applications to the UK elections

AbstractExtensive research applies counterfactual simulation methodology to study parties’ optimal policy positions in multiparty elections. In recent years, this methodology has been extended to the study of variation in issue salience. We employ this method to estimate the electoral effects of changes in the salience of specific positional issue dimensions on parties’ success. Applied to British Election Study survey data from 2017 and 2019, we find that plausible issue salience changes could have shifted the parties’ projected vote shares by several percentage points. Our approach implies that the governing Conservative Party had electoral incentives to downplay positional issues, to magnify the relative effects of its non‐policy advantage due to perceived competence and performance, among other factors. Labour would also have benefitted from reduced salience of Left‐Right ideology. By contrast, the Liberal Democrats had strong electoral incentives to emphasize their moderate Left‐Right position.

An Improved Adaptive Spiral Dynamic Algorithm for Global Optimization

This paper proposes a new strategy to enhance the performance and accuracy of the Spiral dynamic algorithm (SDA) for use in solving real-world problems by hybridizing the SDA with the Bacterial Foraging optimization algorithm (BFA). The dynamic step size of SDA makes it a useful exploitation approach. However, it has limited exploration throughout the diversification phase, which results in getting trapped at local optima. The optimal initialization position for the SDA algorithm has been determined with the help of the chemotactic strategy of the BFA optimization algorithm, which has been utilized to improve the exploration approach of the SDA. The proposed Hybrid Adaptive Spiral Dynamic Bacterial Foraging (HASDBF) algorithm is designed so that the chemotaxis phase of bacteria represents the exploration part of the search operation. In contrast, the SDA represents the exploitation part. Additionally, to improve search operation efficiency, the spiral model's radius and angular displacement are adaptively set according to a linear correlation concerning the fitness value. An additional phase, the elimination and dispersal phase, is obtained from BFA and added to the end of the SDA. This phase aims to improve the algorithm's final solution's accuracy by enhancing the algorithm's search strategy and performance. Simulation tests are run on unimodal and multimodal standard benchmark functions to verify the proposed algorithm. The proposed algorithm significantly outperforms SDA and Adaptive SDA (ASDA) algorithms regarding fitness value and accuracy.

Abstract 002: Examining Pulling Force Using Combined Stentreiver and Aspiration Technique in a Medium Vessel Thrombectomy Model

Introduction With the advent of smaller stent retrievers (SR) and aspiration catheters (AC) capable of accessing more distal locations, distal and medium vessel occlusions (DMVO) are emerging as promising targets for endovascular thrombectomy (EVT). However, considering the vulnerability of distal vessels to injury, it is imperative to understand the safety of various frontline techniques in these challenging scenarios. Using a vascular flow model, we sought to investigate the optimal size, strategy, and positioning of a stent retriever and aspiration catheter to minimize the pulling force exerted on the M2 vasculature. Methods We used a silicone vascular flow model with moderate tortuosity that replicated the left‐sided anterior circulation, including middle cerebral artery (MCA) branches in the M2 territory. An 8 French Cook Shuttle guide sheath was inserted coaxially with a Catalyst 7‐132 cm aspiration catheter and TrevoTrak 21 microcatheter. To measure pulling force, an Imada force gauge DST‐1A was placed at the M2 and a DST‐11A at the proximal end of the microcatheter. The Solitaire 4x20 mm Solitaire stent‐retriever was pulled at 4 mm/sec with the AC in the proximal cavernous carotid segment (NoAsp), proximal M1 (M1P), and distal M1 (M1D), a total of 8 times per AC position, using the ingestion technique. The pinching technique was also examined using the 4x20mm stent. Results The average pulling force measured on M2 using the 4x20mm stent was 169.1mN with the AC docked in the proximal NoAsp position, 26.5mN with the AC at M1P, and 23.0mN at M1D (p&lt;0.0001). The difference in pulling force between M1P and M1D was not significant (p=0.472). The average pulling force exerted on M2 from pinching the 4x20mm stent with the AC at M1D, rather than ingestion of the stent at M1D, was 62.9mN. Average pulling force was noted to decrease from the first to the last run in most cases, with an average drop of 26.4% at the fourth run. Conclusion ADAPT and stent‐retrieval have recently been shown to be comparable in DMVO (1), however some studies have suggested a combined approach may reduce bleeding complications compared to stent‐retrieval alone (2). In our in‐vitro model, we demonstrated that positioning the AC in M1 (M1D or M1P) reduced the pulling force exerted by the stent‐retriever on M2 compared with AC placement in the cavernous carotid (NoAsp). The pulling force exerted from pinching the 4x20mm stent with the AC at M1D was higher than with the ingestion technique, for which the explanation is uncertain, but may be due to the additional friction in the M1 segment. Taken together, these findings suggest a combined approach decreases frictional pulling force during stent‐retrieval and is safer than SR alone. We also note that the pulling force of each stent decreased after its third usage, in line with the manufacturer’s instructions for use, which suggest no more than 3 retrievals per stent (3). Future experiments will compare a wider range of techniques using stents of varying sizes to better clarify factors associated with decreased pulling force in EVT.