Path Map Research Articles

Serratia marcescens outbreak in a neonatal intensive care unit associated with contaminated handwashing sinks

PurposeThis article describes the origin of a S. marcescens outbreak in a neonatal intensive care unit (NICU). Materials and methodsA retrospective case-control study including 12 S. marcescens-positive and 22 S. marcescens-negative neonates in the NICU was performed to identify the source of the outbreak. S. marcescens isolates were collected during the outbreak and analyzed using whole-genome sequencing (WGS). IQ-Tree software, BEAST2 software package and SCOTTI software were used to construct a phylogenetic tree and a propagation path map. ResultsThe index case occurred on February 21st and outbreak ended on March 9th, 2021, affecting a total of 12 neonates (2 with S. marcescens infection and 10 with S. marcescens colonization). Multivariate logistic regression identified that the distance of <0.8 m between the bed unit and the sink (odds ratio [OR], 20.50; 95 % confidence interval [CI], 1.09–384.86), a large number of rotating nurses within a week (OR 2.58, 95 % CI, 1.09–6.11) and use of humidification water in the incubator (OR 189.70, 95 % CI, 2.76–13027.31) were significant increased risk factors for S. marcescens infection or colonization in the outbreak. WGS sifted out a predominant clone between contaminated handwashing sinks and patients, suggesting that cross-transmission was involved in the dissemination of S. marcescens. ConclusionContaminated handwashing sinks can be a communication intermediary of S. marcescens infection or colonization of neonates in the NICU. A distance of <0.8 m between the bed unit and the sink, and a large number of rotating nurses might play important roles in this outbreak. Attention should be paid to sinks contamination and contact transmission to prevent outbreaks.

Deformation theory and nonlinear dynamic behavior of PVC gel actuators

Polyvinyl chloride (PVC) gel generates complex nonlinear vibration behavior under an alternating current voltage excitation, which has potential application as a dynamic electromechanical actuator. However, there are few studies on the deformation theory of PVC gel actuators, especially the dynamic nonlinear response theory. In this paper, a complex dynamic model is established according to the electrodeformation mechanism of PVC film, and the nonlinear dynamic behavior of the actuator is numerically studied by a differential equation. The effects of applied voltage amplitude, voltage frequency, dibutyl adipate content, mechanical tension, and bias voltage on the dynamic properties of PVC film were analyzed under the condition of equal biaxial tension. The variation of amplitude and the generation and disappearance of the beat frequency during vibration are analyzed by using time-domain characteristics. The degree of PVC actuator nonlinearity as well as vibration stability and periodicity is also reflected based on the phase path and Poincare map. Finally, the law of influence of external condition parameters on the dynamic response of the PVC actuator is obtained.

Residual path integrals for re‐rendering

AbstractConventional rendering techniques are primarily designed and optimized for single‐frame rendering. In practical applications, such as scene editing and animation rendering, users frequently encounter scenes where only a small portion is modified between consecutive frames. In this paper, we develop a novel approach to incremental re‐rendering of scenes with dynamic objects, where only a small part of a scene moves from one frame to the next. We formulate the difference (or residual) in the image between two frames as a (correlated) light‐transport integral which we call the residual path integral. Efficient numerical solution of this integral then involves (1) devising importance sampling strategies to focus on paths with non‐zero residual‐transport contributions and (2) choosing appropriate mappings between the native path spaces of the two frames. We introduce a set of path importance sampling strategies that trace from the moving object(s) which are the sources of residual energy. We explore path mapping strategies that generalize those from gradient‐domain path tracing to our importance sampling techniques specially for dynamic scenes. Additionally, our formulation can be applied to material editing as a simpler special case. We demonstrate speed‐ups over previous correlated sampling of path differences and over rendering the new frame independently. Our formulation brings new insights into the re‐rendering problem and paves the way for devising new types of sampling techniques and path mappings with different trade‐offs.

Improving dynamic prognostication of patients with hepatocellular carcinoma by node fusion algorithm equipped survival path mapping.

e13594 Background: Patients with hepatocellular carcinoma (HCC) always require routine surveillance and repeated treatment. Our previous work (1) developed a machine learning methodology called “Survival Path Mapping”, which converted the time series data into a cascading survival map to facilitate dynamic prognosis prediction and treatment planning. However, in previous work, the exponential growth of paths raised challenges of exhausting limited cohort and over-fitting risk. Novel algorithm enhancing data utilization in the Survival Path Mapping was in urgent need. Methods: A node fusion algorithm was designed. First, feature selection algorithm bifurcated each parent-nodes into temporary child-nodes, which constitutes temporary child-nodes set. Then, clustering was performed within temporary child-nodes set according to key features of each child-node. Finally, in each cluster, multiple child-nodes would be merged into one if there was no significant difference in survival. For nodes with bifurcation, a treatment recommendation algorithm was developed. A total of 19446 patients with newly diagnosed primary HCC at Sun Yat-sen University Cancer Center (SYSUCC) between 2008 and 2023 were retrospectively included as internal cohort (divided into internal train and holdout validation cohort); meanwhile 1135 patients from five hospitals were included as multicenter external validation cohort. Dedicated natural language processing program was developed to extract structured features from medical imaging reports. The time series data of patients were converted into data of time slices, with an interval of 3 months. Results: The original survival path mapping (raw-SP) consists of 463 different nodes, while the node fusion survival path mapping (fusion-SP) consisted of 84 nodes (81.8% decrease from raw-SP). The 3-year c-index of fusion-SP were 0.745 (95% CI 0.717-0.772), significantly better (p&lt;0.001) than that of raw-SP: 0.725 (95% CI 0.696-0.755), in the internal holdout validation. Both raw-SP and fusion-SP significantly (p &lt; 0.001) outperformed conventional BCLC and CNLC staging. In the multicenter external validation, the fusion-SP also demonstrated better performance than raw-SP and BCLC staging system. The recommended therapy calculated based fusion-SP system for patients receiving second-line or subsequent treatment had superior or non-inferior efficacy compared to BCLC guideline’s recommendation. Conclusions: The proposed node fusion algorithm solved exponential growth of paths in previous survival path algorithm, improving the accuracy and external validity of dynamic prognosis prediction for HCC patients. The fusion-SP model also retained its transparency and could be used to guide dynamic treatment planning, with its effectiveness in treatment guidance evaluated in prospective trials in the future. 1. Nat Commun 9, 2230; 2018.

Situation Awareness of Mars helicopter based on YOLOv7

Situation awareness on Mars is indispensable for various downstream applications such as navigation and path planning, mapping and scientific discover. However, current Mars rover platform suffered from the absence of global information, leading to mission reduction and the failure of global planning. Compared to the rover, Mars helicopter is a new type of attempt for Mars exploration, which can provide a wide range view of scenes to well support the above missions. To this end, in this paper we proposed a novel learning-based situation awareness model for Mars helicopter. We modified the Yolov7 model by embedding a new channel attention on its head to improve the accuracy of detection. Besides, we designed a Tiny-Scale Detection Module (TSDM) to capture small or hidden rocks in complex Martian surface. To achieve further refinement and validate our proposal, we built an open-source synthetic dataset in air view. After extensive experiments, our model achieved excellent outperforms than the baseline model in our Mars dataset.

A bio-inspired model for robust navigation assistive devices

This paper proposes a new implementation and evaluation in a real-world environment of a bio-inspired predictive navigation model for mobility control, suitable especially for assistance of visually impaired people and autonomous mobile systems. This bio-inspired model relies on the interactions between formal models of three types of neurons identified in the mammals’ brain implied in navigation tasks, namely place cells, grid cells, and head direction cells, to construct a topological model of the environment under the form of a decentralized navigation graph. Previously tested in virtual environments, this model demonstrated a high tolerance to motion drift, making possible to map large environments without the need to correct it to handle such drifts, and robustness to environment changes. The presented implementation is based on a stereoscopic camera, and is evaluated on its possibilities to map and guide a person or an autonomous mobile robot in an unknown real environment. The evaluation results confirm the effectiveness of the proposed bio-inspired navigation model to build a path map, localize and guide a person through this path. The model predictions remain robust to environment changes, and allow to estimate traveled distances with an error rate below 3% over test paths, up to 100m. The tests performed on a robotic platform also demonstrated the pertinence of navigation data produced by this navigation model to guide an autonomous system. These results open the way toward efficient wearable assistive devices for visually impaired people independent navigation.

A design of intelligent AGV system combined with a robotic arm for flexible production lines

Unmanned mobile robots have broad application prospects in industrial production. With the continuous deepening of Industry 4.0, the complexity of manufacturing workflows has skyrocketed, and researching robots suitable for flexible production is becoming a focus of development. With the rapid development of computer technology and sensor technology, the ability of robots to obtain their own state and environmental information has also been greatly expanded. Studying the work, path planning, and obstacle avoidance of robots has important practical significance. This article designs a flexible production robot that integrates Automated Guided Vehicle (AGV) with industrial robots. It has the ability to perceive the environment, make optimal decisions, and operate independently. It can achieve functions such as mobile transportation, flexible operation, and human-machine interaction and cooperation in the production line. This article uses Gazebo to construct a production environment and simulate robot movement. In addition, MATLAB is used to conduct simulation experiments on the operation of the UR10 robot. The results and planning path map validate the feasibility and effectiveness of this method. The mobile robot designed in this article combines a robotic arm with an AGV, which has certain application value in future flexible manufacturing factories and provides a certain reference value for flexible production.

The shortest path method (SPM) webserver for computational enzyme design.

SPMweb is the online webserver of the Shortest Path Map (SPM) tool for identifying the key conformationally-relevant positions of a given enzyme structure and dynamics. The server is built on top of the DynaComm.py code and enables the calculation and visualization of the SPM pathways. SPMweb is easy-to-use as it only requires three input files: the three-dimensional structure of the protein of interest, and the two matrices (distance and correlation) previously computed from a Molecular Dynamics simulation. We provide in this publication information on how to generate the files for SPM construction even for non-expert users and discuss the most relevant parameters that can be modified. The tool is extremely fast (it takes less than one minute per job), thus allowing the rapid identification of distal positions connected to the active site pocket of the enzyme. SPM applications expand from computational enzyme design, especially if combined with other tools to identify the preferred substitution at the identified position, but also to rationalizing allosteric regulation, and even cryptic pocket identification for drug discovery. The simple user interface and setup make the SPM tool accessible to the whole scientific community. SPMweb is freely available for academia at http://spmosuna.com/.

Noteworthy Consensus Effects of D/E Residues in Umami Peptides Used for Designing the Novel Umami Peptides.

Aspartic acid (D) and glutamic acid (E) play vital roles in the umami peptides. To understand their exact mechanism of action, umami peptides were collected and cut into 1/2/3/4 fragments. Connecting D/E to the N/C-termini of the fragments formed D/E consensus effect groups (DEEGs), and all fragments containing DEEG were summarized according to the ratio and ranking obtained in the above four situations. The interaction patterns between peptides in DEEG and T1R1/T1R3-VFD were compared by statistical analysis and molecular docking, and the most conservative contacts were found to be HdB_277_ARG and HdB_148_SER. The molecular docking score of the effector peptides significantly dropped compared to that of their original peptides (-1.076 ± 0.658 kcal/mol, p value < 0.05). Six types of consensus fingerprints were set according to the Top7 contacts. The exponential of relative umami was linearly correlated with ΔGbind (R2 = 0.961). Under the D/E consensus effect, the electrostatic effect of the umami peptide was improved, and the energy gap between the highest occupied molecular orbital-the least unoccupied molecular orbital (HOMO-LUMO) was decreased. The shortest path map showed that the peptides had similar T1R1-T1R3 recognition pathways. This study helps to reveal umami perception rules and provides support for the efficient screening of umami peptides based on the material richness in D/E sequences.

Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign.

Enzymes exhibit diverse conformations, as represented in the free energy landscape (FEL). Such conformational diversity provides enzymes with the ability to evolve towards novel functions. The challenge lies in identifying mutations that enhance specific conformational changes, especially if located in distal sites from the active site cavity. The shortest path map (SPM) method, which we developed to address this challenge, constructs a graph based on the distances and correlated motions of residues observed in nanosecond timescale molecular dynamics (MD) simulations. We recently introduced a template based AlphaFold2 (tAF2) approach coupled with 10 nanosecond MD simulations to quickly estimate the conformational landscape of enzymes and assess how the FEL is shifted after mutation. In this study, we evaluate the potential of SPM when coupled with tAF2-MD in estimating conformational heterogeneity and identifying key conformationally-relevant positions. The selected model system is the beta subunit of tryptophan synthase (TrpB). We compare how the SPM pathways differ when integrating tAF2 with different MD simulation lengths from as short as 10 ns until 50 ns and considering two distinct Amber forcefield and water models (ff14SB/TIP3P versus ff19SB/OPC). The new methodology can more effectively capture the distal mutations found in laboratory evolution, thus showcasing the efficacy of tAF2-MD-SPM in rapidly estimating enzyme dynamics and identifying the key conformationally relevant hotspots for computational enzyme engineering.

СОВЕРШЕНСТВОВАНИЕ МАРКЕТИНГОВЫХ ТЕХНОЛОГИЙ В УПРАВЛЕНИИ ОРГАНИЗАЦИЕЙ СФЕРЫ УСЛУГ

The article is devoted to the disclosure of theoretical and practical aspects of the application of marketing technologies in the management of a service sector organization. The issues of the specific nature of marketing technologies in the management of the company, the specifics of interaction with consumers of the organization are considered. A model of marketing tools for the implementation of a customer path map is presented, aimed at optimizing a customer-centered culture and increasing consumer loyalty. The experience of companies in effective customer relationship management is revealed.

Bawean Geotrack: Linkage Between Geodiversity, Biodiversity, And Cultural Diversity for Driving The Acceleration Bawean Island-Gresik Geopark

Bawean Island, Gresik Regency is geographically located in the Java Sea, precisely located between Borneo and Java. Currently, Bawean Island is being fought to become a Geological Heritage and continues to be developed, so that it can be proposed as a National Geopark. The Geology, Biology, and Cultural Diversity that exists on Bawean Island are still separate pieces that need further research so that it can be presented in a holistic order as geotourism. The purpose of this study is to examine geosite recommendations on Bawean Island and to reconstruct the geological history of the biological and cultural diversity of the community that developed from the past to the present in a Geosite Distribution Path Map (Geotrack). The methods used are literature review, observation of DEM imagery to determine morphology, and Geosite Potential Survey which is followed by feasibility study calculations based on parameters from the Geological Survey Center. The results of this study are in the form of a Geotrack Map consisting of 24 Geosites (15 Geodiversity, 3 Biodiversity, and 6 Cultural Diversity) which are contained in a digital system in the form of WebGIS so that all elements of society can access it. The occurrence of transgression and marine regression in the past caused by the formation of ancient volcanoes supports the formation of a typical flora and fauna ecosystem on Bawean Island. In addition, the formation of an island in the middle of the Java Sea surrounded by other cultures and civilizations led to the acculturation and cultural assimilation of the Bawean island.

Accident case data-accident causation model driven safety training method: Targeted safety training empowered by historical accident data in coal industry

The content and methods of traditional safety training can no longer meet the needs of the industry or accident-targeted safety training. To solve this problem, this study proposes an accidental case data accident causing model-driven safety training method (ACDACM method) based on an analysis of the content and methods of China's safety training. This method is theoretically driven by the accident causation model and data-driven by the accident case information. Through data analysis of historical accident cases, basic information and comprehensive reasons for accidents can be obtained. Using data mining algorithms, the causes and combinations of high-frequency and high-risk accidents can be mined, supported by accident data, and a path map of the accident causes can then be obtained. The developed safety training project is more targeted by comparing accident causes with industry standards and regulations. This study considers coal and gas outburst accidents as an example and uses 24Model to analyze 84 coal and gas outburst accidents in China. The targeted safety training plan had eight parts of training content, and supporting PPTs, handbooks, and videos were produced. The application shows that this method can provide targeted safety training designs for industries or accidents and has industry universality. Finally, the advantages and development of the ACDACM method are elaborated and the future of safety training is discussed. This study provides theoretical and methodological support for targeted safety-training programs.

CUSTOMS CONTROL USING ARTIFICIAL INTELLIGENCE TECHNOLOGIES

The relevance of this article is due to the high importance of customs control procedures for the development and expansion of international trade, as well as the need to improve the efficiency of customs authorities through the use of digital technologies. The purpose of the article is to substantiate the need for the development and implementation of the digital tool "Customer Declarant Map" based on artificial intelligence in the processes of customs control in order to increase its efficiency. Methods of a systematic approach were used as research methods, a comparative method to clarify the elements of using artificial intelligence to improve the efficiency of customs control, a qualitative content analysis method to justify the importance of forming a "Customer Declarant Map" was implemented using a descriptive analysis, a review of literary sources and acts international law. Achieving this goal required the solution of certain tasks. Based on the results of the analysis of theoretical approaches to the essence of customs control, its significance for the competitiveness of business was clarified due to the increase in volumes and facilitation of international trade, since customs services act as an external factor in competitiveness and the characteristics of individual decisions within the framework of customs control intended for entrepreneurs, which can be considered positive in terms of enterprise competitiveness. The further active introduction of digital technologies, in particular, artificial intelligence in the activities of customs authorities for the processing and analysis of various information from numerous data sources, is justified. The formation of a "Customer Declarant Map" - a map of the path of the customs declarant, is proposed, the advantages of artificial intelligence in this process are highlighted. It has been substantiated that the introduction into practice of a new digital path map tool for the customs declarant "Customer Declarant Map" will improve the efficiency of customs control, facilitate international trade, and reduce customs risks.

Decrypting Allostery in Membrane-Bound K-Ras4B Using Complementary In Silico Approaches Based on Unbiased Molecular Dynamics Simulations.

Protein functions are dynamically regulated by allostery, which enables conformational communication even between faraway residues, and expresses itself in many forms, akin to different "languages": allosteric control pathways predominating in an unperturbed protein are often unintuitively reshaped whenever biochemical perturbations arise (e.g., mutations). To accurately model allostery, unbiased molecular dynamics (MD) simulations require integration with a reliable method able to, e.g., detect incipient allosteric changes or likely perturbation pathways; this is because allostery can operate at longer time scales than those accessible by plain MD. Such methods are typically applied singularly, but we here argue their joint application─as a "multilingual" approach─could work significantly better. We successfully prove this through unbiased MD simulations (∼100 μs) of the widely studied, allosterically active oncotarget K-Ras4B, solvated and embedded in a phospholipid membrane, from which we decrypt allostery using four showcase "languages": Distance Fluctuation analysis and the Shortest Path Map capture allosteric hotspots at equilibrium; Anisotropic Thermal Diffusion and Dynamical Non-Equilibrium MD simulations assess perturbations upon, respectively, either superheating or hydrolyzing the GTP that oncogenically activates K-Ras4B. Chosen "languages" work synergistically, providing an articulate, mutually coherent, experimentally consistent picture of K-Ras4B allostery, whereby distinct traits emerge at equilibrium and upon GTP cleavage. At equilibrium, combined evidence confirms prominent allosteric communication from the membrane-embedded hypervariable region, through a hub comprising helix α5 and sheet β5, and up to the active site, encompassing allosteric "switches" I and II (marginally), and two proposed pockets. Upon GTP cleavage, allosteric perturbations mostly accumulate on the switches and documented interfaces.

Formation‐Aware Planning and Navigation with Corridor Shortest Path Maps

AbstractThe need to plan motions for agents with variable shape constraints such as under different formations appears in several virtual and real‐world applications of autonomous agents. In this work, we focus on planning and execution of formation‐aware paths for a group of agents traversing a cluttered environment. The proposed planning framework addresses the trade‐off between being able to enforce a preferable formation when traversing the corridors of the environment, versus accepting to switch to alternative formations requiring less clearance in order to utilize narrower corridors that can lead to a shorter overall path to the final destination. At the planning stage, this trade‐off is addressed with a multi‐layer graph annotated with per‐layer navigation costs and formation transition costs, where each layer represents one formation together with its specific clearance requirement. At the navigation stage, we introduce Corridor Shortest Path Maps (CSPMs), which produce a vector field for guiding agents along the solution corridor, ensuring unobstructed in‐formation navigation in cluttered environments, as well as group motion along lengthwise‐optimal paths in the solution corridor. We also present examples of how our multi‐layer planning framework can be applied to other types of multi‐modal planning problems.

Channel reconstruction for mmWave Massive MIMO systems based on Channel Path Map

For the needs of high data rate and massive device access in current fifth-generation (5G) mobile communication networks and future sixth-generation (6G) mobile communication networks, Millimeter-Wave (mmWave) Massive Multiple-Input Multiple-Output (MIMO) is a crucial technical support. However, the conventional pilot based channel estimation methods are exceedingly time-consuming and substantially degrade system performance when the number of users or antennas is high. This paper proposes a Path Clustering based Channel Reconstruction (PCCR) scheme for channel reconstruction in order to solve this issue. By leveraging channel information (such as angle of arrival, angle of departure, and path gain) at a number of geographical locations that are recorded in the Channel Path Map (CPM), we aim to reconstruct the mmWave channel of any locations of interests. To be specific, the CPM is used to extract the neighborhood propagation path data, and an autonomous determination algorithm is used to find the number of path clusters at the location of interest. The recorded propagation path information is processed by the Equivalent Base Station (EBS) scheme, and the path clustering is accomplished by using the AGglomerative NESting (AGENS) algorithm. In each path cluster, Inverse Distance Weighted (IDW) algorithm is developed to forecast the path information at the user location. With all path information at user location are forecast, the channel can be reconstructed. The anticipated overhead is substantially lower than that of conventional methods because the computational cost of the procedure only depends on the total number of paths at the nearby locations. Ray-tracing based simulations are carried out to demonstrate the performance of the proposed algorithm. The results show that, when applied to a CPM with a spatial location precision of 5 m, the Normalized Mean Squared Error (NMSE) of the proposed algorithm is nearly identical to that of Linear Minimum Mean Square Error (LMMSE) estimation. The actual achievable date rate can match the needs of upcoming wireless communications and is superior over the conventional LMMSE.

Development of learning path map of work and energy for high schoolers by using cognitive diagnostic assessment

The conception of work and energy is fundamental to learning physics and is essential to learning other subjects. However, most students still lack knowledge and understanding of work and energy. This may be due to previous research that aimed to develop students using similar teaching methods without considering the individual knowledge state of each student. We, thus, sought to develop the mastery test on work and energy and the learning path map of work and energy using cognitive diagnostic assessment. Participants were 537 tenth graders in Bangkok, Thailand, which were chosen by the multistage random sampling. The mastery test on work and energy developed is divided into six attributes, i.e., (1) work, (2) power, (3) kinetic energy, (4) gravitational potential energy, (5) elastic potential energy, and (6) law of conservation of energy. The test exhibited good psychometric properties, which were evaluated based on item parameters, content validity, construct validity, concurrent validity, classification consistency index, and classification accuracy index. The significant finding was the development of the learning path map of work and energy. The map illustrates students’ learning progression in different attribute profiles regarding work and energy. It proves to be highly beneficial for teachers in designing personalized learning methods for individual students. Additionally, it allows for tracking the learning progress of students until they have a comprehensive understanding of work and energy in all its attributes.

Computing and analyzing decision boundaries from shortest path maps

This paper proposes a methodology for computing, visualizing, and analyzing critical decision boundaries for the selection of shortest paths in a given environment. Decision boundaries are defined as the points in a map from which two or more different shortest paths exist towards a destination. This paper introduces the problem of visualizing their evolution, taking into account moving obstacles, moving goals, and as well multiple goals. The proposed visualizations enable analyzing which paths should be taken and at which departure times, such that a destination can be reached by the shortest possible path when taking into account a moving target or time-varying areas to be avoided. The proposed techniques are also applied to the analysis and improvement of exit placement in a given environment, in order to improve the evacuation flow in emergency situations.

Optimizing transducer aperture subdivision for aberration correction during transabdominal histotripsy

This study investigated the effect of transducer aperture subdivision on aberration correction performance for transabdominal histotripsy. A transducer aperture and geometric curvature similar to clinical histotripsy devices (750 kHz, 20 × 16 cm width, 14 cm radius of curvature) was subdivided into 64, 256, and 1024 elements (10.7λ, 5.3λ, 2.6λ). For each of the three designs, optimal space filling (100%) equal area polygons with a pseudo-random arrangement of elements was used following the technique described by Rosnitskiy. 3D acoustic path maps were constructed from abdominal CTs of 3 de-identified human subjects and assigned acoustic properties from literature. For each transducer, acoustic transmission was simulated using k-Wave at 3 target locations in the liver of each subject with and without implementing ideal aberration correction. Across all subjects and targets (n = 9), AC increased the maximum focal pressure amplitude by 26% (0%-59%) on average for 64 elements, 38% (5%-84%) for 256 elements, and 42% (7%–92%) for 1024 elements. These results suggest 5.3λ elements may near an optimal subdivision for transabdominal histotripsy aberration correction when taking into account the cost of transducer and driving system fabrication. Acoustic simulations can save fabrication time and costs when optimizing device design.