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We describe our efforts to prepare common starting structures and models for the SAMPL5 blind prediction challenge. We generated the starting input files and single configuration potential energies for the host-guest in the SAMPL5 blind prediction challenge for the GROMACS, AMBER, LAMMPS, DESMOND and CHARMM molecular simulation programs. All conversions were fully automated from the originally prepared AMBER input files using a combination of the ParmEd and InterMol conversion programs. We find that the energy calculations for all molecular dynamics engines for this molecular set agree to better than 0.1 % relative absolute energy for all energy components, and in most cases an order of magnitude better, when reasonable choices are made for different cutoff parameters. However, there are some surprising sources of statistically significant differences. Most importantly, different choices of Coulomb’s constant between programs are one of the largest sources of discrepancies in energies. We discuss the measures required to get good agreement in the energies for equivalent starting configurations between the simulation programs, and the energy differences that occur when simulations are run with program-specific default simulation parameter values. Finally, we discuss what was required to automate this conversion and comparison.

It is crucial to demonstrate a robust correlation between the simulated and manufactured parallel-transmit (pTx) arrays performances to release the currently-used, very restrictive safety margins. In this study, we describe the qualitative and quantitative validation of a simulation model with respect to experimental results for an 8-channel dipole array at 7T. An approach that includes the radiofrequency losses into the simulation model is presented and compared to simulation models neglecting these losses. Simulated S-matrices and individual B1+-field maps were compared with experimentally measured quantities. With the proposed approach, an average relative difference of ~1.1% was found between simulated and experimental reflection coefficients, ~4.2% for the 1st coupling terms, and ~9.4% for the 2nd coupling terms. A maximum normalized root-mean-square error of 4.8% was achieved between experimental and simulated individual B1+-field maps. The effectiveness of the simulation model to accurately predict the B1+-field patterns was assessed, qualitatively and quantitatively, through a comparison with experimental data. We conclude that, using the proposed model for radiofrequency losses, a robust correlation is achieved between simulated and experimental data using the 8-channel dipole array at 7T.

OBJECTIVES The increase in the complexity of operations, the rising quest for improved outcomes and the scrutiny of surgical practice and its associated complications have led to a decreased educational value of in-patient surgical training within cardiac surgery. Simulation-based training has emerged as an adjunct to the apprenticeship model. In the following review, we aimed to evaluate the currently available evidence regarding simulation-based training in cardiac surgery. METHODS A systematic database search was conducted as per PRISMA guidelines, of original articles that explored the use of simulation-based training in adult cardiac surgery programs in EMBASE, MEDLINE, Cochrane database and Google Scholar, from inception to 2022. Data extraction covered the study characteristics, simulation modality, main methodology and main outcomes. RESULTS Our search yielded 341 articles, of which 28 studies were included in this review. Three main areas of focus were identified: (i) validity testing of the models; (ii) impact on surgeons’ skills; and (iii) impact on clinical practice. Fouteen studies reported animal-based models and 14 reported on non-tissue-based models covering a wide spectrum of surgical operations. The results of the included studies suggest that validity assessment is scarce within the field, being carried out for only 4 of the models. Nonetheless, all studies reported improvement in trainees’ confidence, clinical knowledge and surgical skills (including accuracy, speed, dexterity) of trainees both at senior and junior levels. The direct clinical impact included initiation of minimally invasive programmes and improved board exam pass rates, and creating positive behavioural changes to minimize further cardiovascular risk. CONCLUSIONS Surgical simulation has been shown to provide substantial benefits to trainees. Further evidence is needed to explore its direct impact on clinical practice. Traditionally, cardiac surgeons have been acquiring their surgical skills through a practical apprentice model, basing their training on patients in the operating room.

Preclinical therapeutic hyperthermia cancer research provides essential insight into biological and physiological effects, therapeutic impacts, and treatment-strategy optimisation. As hyperthermia triggers both local and systemic effects, orthotopic tumour models are required for translational research. Preclinical hyperthermia devices capable of adequately heating orthotopic tumours were previously unavailable. To address this, a phased-array electromagnetic heating system was developed with eight 1.66 GHz waveguide antennas. This study evaluates its ability to generate and control a heating focus in phantoms, and examines its correlation with numerical predictions. Focus size and power-steering capabilities were assessed by E-field scanning for a central focus and a 10 mm shifted focus. Temperature distributions were measured in muscle-equivalent phantoms (d = 40 mm, l = 90 mm) for central and 7.5 mm shifted foci. Results were compared with simulations by Plan2Heat, a dedicated treatment planning package for hyperthermia applications. The system successfully generated confined power foci with a radial diameter of 8 mm (FWHM). The measured temperature focus was 22 × 25 mm. The simulation-predicted focus location matched measurements within 1 mm for both power and temperature. The system generates a confined, controllable, and predictable heat focus suitable for deep targets, required for effective preclinical hyperthermia research into clinically relevant biological and physiological effects. Future work should focus on validation in mice.

This study investigates the mechanical properties of thermoplastic polyurethane (TPU) 60A, which is a flexible material that can be used to produce soft robotic grippers using additive manufacturing. Tensile tests were conducted under ISO 37 and ISO 527 standards to assess the effects of different printing orientations (0°, 45°, −45°, 90°, and quasi-isotropic) and test speeds (2 mm/min, 20 mm/min, and 200 mm/min) on the material’s performance. While the printing orientations at 0° and quasi-isotropic provided similar performance, the quasi-isotropic orientation demonstrated the most balanced mechanical behavior, establishing it as the optimal choice for robust and predictable performance, particularly for computational simulations. TPU 60A’s flexibility further emphasizes its suitability for handling delicate objects in industrial and agricultural applications, where damage prevention is critical. Computational simulations using the finite element method were conducted. To verify the accuracy of the models, a comparison was made between the average stresses of the tensile test and the computational predictions. The relative errors of force and displacement are lower than 5%. So, the constitutive model can accurately represent the material’s mechanical behavior, making it suitable for computational simulations with this material. The analysis of strain rates provided valuable insights into optimizing production processes for enhanced mechanical strength. The study highlights the importance of tailored printing parameters to achieve mechanical uniformity, suggesting improvements such as biaxial testing and G-code optimization for variable thickness deposition. Overall, the research study offers comprehensive guidelines for future design and manufacturing techniques in soft robotics.

Balancing of rotors requires a specialized device known as a balancer, which measures centrifugal forces by rotating the rotor and applies corrective masses to achieve balance. Higher rotational speeds enhance the accuracy of the balancing process due to more pronounced centrifugal effects. In this study, a novel balancer is designed that employs the influence coefficient method for mass correction. The rotor’s speed is controlled through a dual mechanism: PWM pulse generation and a gear-based transmission system. Force magnitude and phase are measured using load cells and an optical proximity sensor. Modal analysis of the balancer structure reveals a lowest natural frequency of 216 Hz, enabling safe operation at speeds up to 9500 RPM without inducing unwanted vibrations. Additionally, motion simulation was conducted to validate the governing equations and assess the impact of sensor misalignment. Results confirm the accuracy of the model and indicate a misalignment tolerance of up to 0.25 mm.

We investigated the performance of RegCM4 in simulating rainfall over Southeast Asia with different combinations of deep-convection and air−sea flux parameterization schemes. Four different gridded rainfall datasets were used for the model assessment. In general, the simulations produced dry biases over the equatorial region and slightly wet biases over mainland Indo-China, except those experiments with the MIT Emanuel cumulus schemes, in which large positive rainfall biases were simulated. However, simulations with the MIT schemes were generally better at reproducing annual rainfall variations. The simulations were not sensitive to the treatment of air−sea fluxes. While the simulations generally produced the rainfall climatology well, all simulations showed stronger inter-annual variability compared to observations. Nevertheless, the time evolution of the inter-annual variations was well reproduced, particularly over the eastern Maritime Continent. Over mainland Southeast Asia, all simulations produced unrealistic rainfall anomaly responses to surface temperature. The lack of summer air−sea interactions in the model resulted in enhanced oceanic forcing over the regions, leading to positive rainfall anomalies during years with warm ocean temperature anomalies. This shortcoming in turn caused much stronger atmospheric forcing on the land surface processes compared to that of the observation. A robust score-ranking system was designed to rank the simulations according to their performance in reproducing different aspects of rainfall characteristics. The results suggest that the simulation with the MIT Emanuel convective scheme and the BATS1e air−sea flux scheme performs better overall compared to the rest of the simulations.

Unmanned aerial vehicles (UAVs) have emerged as a highly efficient means of monitoring landslide-prone regions, given the growing concern for urban safety and the increasing occurrence of landslides. Designing optimal UAV flight routes is crucial for effective landslide monitoring. However, in real-world scenarios, the testing and validating of flight path planning algorithms incur high cost and safety concerns, making overall flight operations challenging. Therefore, this paper proposes the use of the Unreal Engine simulation framework to design UAV flight path planning specifically for landslide monitoring. It aims to validate the authenticity of the simulated flight paths and the correctness of the algorithms. Under the proposed simulation framework, we then test a novel flight path planning algorithm. The simulation results demonstrate that the model reconstruction obtained using the novel flight path algorithm exhibits more detailed textures, with a 3D model simulation accuracy ranging from 10 to 14 cm. Among them, the RMSE value of the novel flight route algorithm falls within the range of 10 to 11 cm, exhibiting a 2 to 3 cm improvement in accuracy compared to the traditional flight path algorithm. Additionally, it effectively reduces the flight duration by 9.3% under the same flight path compared to conventional methods. The results confirm that the simulation framework developed in this paper meets the requirements for landslide damage monitoring and validates the feasibility and correctness of the UAV flight path planning algorithm.

In response to the global push for net-zero emissions, the automotive industry faces challenges from the environmental impact of traditional oil-based shock absorbers, as vehicle production in Europe consumes around 9000–9500 tons of hydraulic oil annually. Our research introduces an innovative shock-absorber that employs a Heterogeneous Lyophobic System (HLS) to replace hydraulic oil with a nonwetting liquid (NWL) and hydrophobic nanoporous materials (PMs). This system not only eliminates oil use but also enables the tuneability of the vehicle shock-absorber’s performance. By focusing on the dynamic intrusion/extrusion process, we developed a CFD-coupled model demonstrating how the adjustment of damping characteristics can be achieved, catering to a broad spectrum of vehicular requirements. The core of this study lies in its ability to simulate the patterns of intrusion and extrusion, including complete, partial cycles, and double-step cycles, thereby demonstrating both the practical applicability and theoretical foundation of using such mechanisms in shock-absorber design. With a strong correlation between experimental and simulation data, the current study not only underpins the accuracy of the developed theoretical and CFD models but also allows for the customisation of the shock-absorber performance under assorted conditions, laying a solid groundwork for future technological advancements in this field. Overall, this work provides a practical modelling framework that can guide the industrial design of next-generation sustainable shock-absorbers and broader adaptive damping systems.

Agriculture plays a pivotal role in global greenhouse gas emissions. This study focuses on the quantitative simulation and validation of the wave convergence patterns of agricultural carbon emission efficiency, aiming to deeply understand the process of collaborative governance between central and surrounding cities within urban agglomerations, thereby achieving stable and sustainable development goals for the carbon emission system. Based on the dynamic DEA model, this paper employs an enhanced common frontier dynamic super-efficiency SBM model to quantitatively evaluate the agricultural carbon emission efficiency of urban agglomerations and their constituent cities. Subsequently, a gravity model is introduced to measure the changes in the joint intensity of agricultural carbon emission efficiency within urban agglomerations, and a wave-like convergence curve function model is employed to validate the proposed regularity. The findings indicate: (1) The agricultural carbon emission efficiency exhibits a fluctuating downward trend, with a distribution depicted by higher efficiencies in the northern and southern regions and lower efficiencies in the rest part. (2) The joint intensity of agricultural carbon emission efficiency tends towards a wave-like increase and exhibits joint threshold effects, with the outcomes for national urban agglomerations significantly surpassing other groups. (3) The evolutionary curves of agricultural carbon emission efficiency in Chinese urban agglomerations essentially show wave-like converging changes over time and in conjunction with urban joint development, with the fitted curves of carbon emission efficiency across different urban agglomerations showing high degrees of similarity.