Extreme Acceleration Research Articles

Analysis of Instrument Motion and the Impact of Residency Level and Concurrent Distraction on Laparoscopic Skills

Using a laparoscopic box trainer fitted with motion analysis trackers and software, we aim to identify differences between junior and senior residents performing the peg transfer task, and the impact of a distracting secondary task on performance. General surgery residents were asked to perform the laparoscopic peg transfer task on a trainer equipped with a motion tracker. They were also asked to perform the laparoscopic task while completing a secondary task. Extreme velocity and acceleration events of instrument movement in the 3 rotational degrees of freedom were measured during task completion. The number of extreme events, defined as velocity or acceleration exceeding 1 SD above or below their own mean, were tabulated. The performance of junior residents was compared to senior residents. Simulation learning institute, Beaumont Hospital, Royal Oak, Michigan. Thirty-seven general surgery residents from Beaumont Hospital, Royal Oak. When completing the primary task alone, senior residents executed significantly fewer extreme motion events specific to acceleration in pitch (16.63 vs. 20.69, p = 0.04), and executed more extreme motion events specific to velocity in roll (16.14 vs. 15.11, p = 0.038), when compared to junior residents. With addition of a secondary task, senior residents had fewer extreme acceleration events specific to pitch, (14.69 vs. 22.22, p < 0.001). While junior and senior residents completed the peg transfer task with similar times, motion analysis identified differences in extreme motion events between the groups, even when a secondary task was added. Motion analysis may prove useful for real-time feedback during laparoscopic skill acquisition.

Normal and extreme aircraft accelerations and the effects on exposure to expiratory airborne contaminant inside commercial aircraft cabins

A novel dataset based on satellite observations of aircraft positions was utilized to estimate normal accelerations of commercial aircraft during climb and descent legs. Further, these accelerations are used to simulate the effects on exposure to expiratory airborne contaminant inside commercial aircraft cabins. Compared to previous studies, which reported exposures more than twice due to high aircraft accelerations during the climb leg, the new findings suggest lower aircraft accelerations that result in exposures on par with steady level flights during climb and descent legs. The new findings place previous studies in context to be interpreted as extreme conditions only while they call for more detailed experimental investigations.

Feasibility Study of the Low-Cost Motion Tracking System for Assessing Endoscope Holding Skills

The ability to hold an endoscope is an important skill for surgeons and assistants performing endoscopic neurosurgery. Motion tracking can provide an objective assessment for surgical skills and may aid in endoscopic neurosurgery. We developed a cost-effective system to study the feasibility of objectively distinguishing performance levels for operating an endoscope. The study was divided into 2 parts. First, a video motion tracking analysis tool was built based on a printed mark and free software (Kinovea 0.8.15). Second, the tool was used to distinguish the holding endoscope performance of the robotic arm by experts (surgeon, n= 3) and novice users (residents, n= 6) under both 0' and 30' endoscopes. Through the printed mark and free software, we successfully built a system for video motion tracking. The data analysis showed that for both 0' and 30' endoscopes, the experts had a shorter total distance and depth, smaller average speed and maximum acceleration, and a fewer number of extreme accelerations than their novice counterparts. Compared with experts and residents, the fixed arm had better results. The simple low-cost video motion tracking system can provide an objective assessment of an endoscope holding skill, which allows for discrimination between an expert and a novice, and can be used by clinical neurosurgeons to select a qualified assistant.

NuSTAR Observations and Multiwavelength Modeling of the High-redshift BL Lacertae Object 4FGL J2146.5-1344

Abstract High synchrotron peak (HSP; Hz) BL Lac objects are some of the most extreme accelerators in the universe. Those found at high redshifts (z &gt; 1) challenge our understanding of blazar evolution models and are crucial for cosmological measurements of the extragalactic background light. In this paper, we study a high-z BL Lac object, 4FGL J2146.5-1344, detected to be at z = 1.34 using the photometric dropout technique. We collected multiwavelength data for this source from optical up to γ-rays, in order to study its spectral energy distribution (SED). In particular, this source was observed for the first time with the Nuclear Spectroscopic Telescope Array, which accurately measures the synchrotron emission of this blazar up to 50 keV. Despite being classified as an HSP BL Lac object, the modeling of the SED reveals that this source likely belongs to the “masquerading BL Lac” class, which comprises flat spectrum radio quasars appearing as disguised BL Lac objects.

Progress in unveiling extreme particle acceleration in persistent astrophysical jets

The most powerful persistent accelerators in the Universe are jetted active galaxies. Blazars, galaxies whose jets are directed towards Earth, dominate the extragalactic gamma-ray sky. Still, most of the highest-energy particle accelerators likely elude detection. These extreme blazars, whose radiated energy can peak beyond 10 TeV, are ideal targets to study particle acceleration and radiative processes, and may provide links to cosmic rays and astrophysical neutrinos. The growing number of extreme blazars observed at TeV energies has been critical for the emergence of gamma-ray cosmology, including measurements of the extragalactic background light, tight bounds on the intergalactic magnetic field, and constraints on exotic physics at energies inaccessible with human-made accelerators. Tremendous progress has been achieved over the past decade, which bodes well for the future, particularly with the deployment of the Cherenkov Telescope Array.

Human Body Mixed Motion Pattern Recognition Method Based on Multi-Source Feature Parameter Fusion.

Aiming at the requirement of rapid recognition of the wearer’s gait stage in the process of intelligent hybrid control of an exoskeleton, this paper studies the human body mixed motion pattern recognition technology based on multi-source feature parameters. We obtain information on human lower extremity acceleration and plantar analyze the relationship between these parameters and gait cycle studying the motion state recognition method based on feature evaluation and neural network. Based on the actual requirements of exoskeleton per use, 15 common gait patterns were determined. Using this, the studies were carried out on the time domain, frequency domain, and energy feature extraction of multi-source lower extremity motion information. The distance-based feature screening method was used to extract the optimal features. Finally, based on the multi-layer BP (back propagation) neural network, a nonlinear mapping model between feature quantity and motion state was established. The experimental results showed that the recognition accuracy in single motion mode can reach up to 98.28%, while the recognition accuracy of the two groups of experiments in mixed motion mode was found to be 92.7% and 97.4%, respectively. The feasibility and effectiveness of the model were verified.

СОУДАРЕНИЕ КАПЛИ СО СВОБОДНОЙ ПОВЕРХНОСТЬЮ: АКУСТИЧЕСКОЕ ИЗЛУЧЕНИЕ В ТОЛЩЕ ЖИДКОСТИ

An experimental study of the emission of sound by droplets falling into an unperturbed liquid was performed using wideband hydrophones and a high-speed video camera. Collision of a drop with a water surface is accompanied by air entrainment and the formation of underwater gas cavities, which leads to the appearance of surface forces and fast flows, generating extreme accelerations, which are sufficient for resonant acoustic excitation of cavities and emission of sound packets. The sequence of emitted signals contains a shock pulse, as well as one or more sound packets generated by resonant bubbles detached from underwater cavities. The number of resonating bubbles varies from experience to experience, depending on the collision scenario and further behavior, including, in particular, the process of fragmentation of the primary cavities. The dimensions of the bubbles, measured on video frames, correspond to the values calculated in accordance with the Minnaert resonance frequency.

A Randomized Control Trial of Non-Surgical Methods of Non-Dominant Hand Training to Enhance Laparoscopic Skill

Study Objective To determine if non-dominant hand training using task-specific exercises or everyday activities, would translate to improved laparoscopic ambidexterity amongst medical trainees. Design Single center non-blinded, randomized control trial. Setting University medical school. Patients or Participants Medical students. Interventions 100 medical students were block randomized to receive either 1) Task-specific exercises to train the non-dominant hand, 2) Directions to use their non-dominant hand to perform everyday activities, or 3) No training. Laparoscopic skills during completion of pre-defined tasks were assessed using a box-trainer fitted with motion tracking equipment. Three time points were measured; pre-training, post-training (t = 3 weeks), and retention (t = 6 weeks). A principal components analysis incorporating extreme velocity and acceleration events was performed to assess multidimensional hand movements and obtain a global metric of ability i.e. smoothness of motion. We compared smoothness between groups and across times using mixed-effect linear regression, controlling for pre-test ability. Measurements and Main Results There was a significant improvement in smoothness from the post-test phase to the retention phase for all groups (mean effect size d = 0.34), suggesting that smoothness was improving over time regardless of intervention. However, there was no difference in smoothness between the control group and either task-specific exercises or everyday activities for any task at any time point (all p > 0.05, mean task-specific effect size d = 0.14, mean everyday effect size d = 0.04). Conclusion While sound in theory, training of the non-dominant hand to improve ambidexterity does not translate to the laparoscopic surgical environment. Simulation based laparoscopic exercises remain the favored education modality.

Locally Low-Rank Regularized Video Stabilization With Motion Diversity Constraints

This paper presents a novel motion aware regularization model with diversity constraints for motion smoothing in video stabilization. Differing from the global path optimization methods, the proposed model puts an emphasis on the relations of inter-frame motions and incorporates sliding windowed low-rank and smoothness constraints. The rationale behind it is cinematography rules which assume that camera motions can be divided into diverse patterns: zero velocity, constant velocity, and acceleration motion. Firstly, a locally motion aware fidelity term is adopted in light of the local motion stationarity. Secondly, to improve the robustness of the model for different motion patterns, a locally low-rank constrained regularization term is further introduced by considering the motion correlation in a local temporal window. Moreover, to cope with the over-smoothing problem in rapid motion situations with extreme acceleration, a motion steering kernel and varying window length are employed to enhance the flexibility of the proposed model. The experimental results demonstrate the superiority of the proposed optimization model and the efficiency to suppress over-smoothing when rapid motions occur. Meanwhile, we compare the results with some state-of-the-art methods quantitatively and qualitatively, and our method can achieve a comparable or even better stabilization effect.

Persistent accelerations disentangle Lagrangian turbulence

Particles in turbulence frequently encounter extreme accelerations between extended periods of quiescence. The occurrence of extreme events is closely related to the intermittent spatial distribution of intense flow structures such as vorticity filaments. This mixed history of flow conditions leads to very complex particle statistics with a pronounced scale dependence, which presents one of the major challenges on the way to a non-equilibrium statistical mechanics of turbulence. Here, we introduce the notion of persistent Lagrangian acceleration, quantified by the squared particle acceleration coarse-grained over a viscous time scale. Conditioning Lagrangian particle data from simulations on this coarse-grained acceleration, we find remarkably simple, close-to-Gaussian statistics for a range of Reynolds numbers. This opens the possibility to decompose the complex particle statistics into much simpler sub-ensembles. Based on this observation, we develop a comprehensive theoretical framework for Lagrangian single-particle statistics that captures the acceleration, velocity increments as well as single-particle dispersion.

Long short‐term memory and convolutional neural network for abnormal driving behaviour recognition

Abnormal driving behaviours, such as rapid acceleration, emergency braking, and rapid lane changing, bring great uncertainty to traffic, and can easily lead to traffic accidents. The accurate identification of abnormal driving behaviour helps to judge the driver's driving style, inform surrounding vehicles, and ensure the road traffic safety. Most of the existing studies use clustering and shallow learning, it is difficult to accurately identify the types of abnormal driving behaviours. Aimed at addressing the difficulty of identifying driving behaviour, this study proposed a recognition model based on a long short-term memory network and convolutional neural network (LSTM-CNN). The extreme acceleration and deceleration points are detected through the statistical analysis of real vehicle driving data, and the driving behaviour recognition data set is established. By using the data set to train the model, the LSTM-CNN can achieve a better result.

Experimental Study on the Damping Effect of Multi-Unit Particle Dampers Applied to Bracket Structure

Particle damping (PD) is a passive mean of vibration control in which small metallic or ceramic particles are placed inside a cavity that attached to the primary structure at the place of high vibration amplitudes. The kinetic energy of the primary structure is dissipated by non-elastic impact and friction between particles and walls. This paper represents a series of experimental investigations of the effects of multi-unit particle dampers (MUPD) attached to a bracket structure under harmonic excitation and random excitation. As a platform to investigate the particle damping characteristics under extreme acceleration environments, the bracket structure was featured by an extremely high response on the top, and its maximum acceleration exceeds 50 times gravity acceleration when the bracket structure was subjected to resonance. This broad range of acceleration conditions was far beyond the scope concerned in most previous work. The experimental results show that for a small weight penalty (no more than 8.8%), multi-unit particle damper can reduce the resonance of the primary structure by more than 50%, whether under sinusoidal excitation or random excitation. And the response of the primary structure depends on the type of cavities and filled coefficient. Layering the cavity in the direction of the main vibration can improve the damping capacity of the multi-unit particle damper. And the damper with small particle size and large number of features is suitable for vibration reduction under high acceleration conditions.

Comparison of Model-Scale and Full-Scale Planing Craft Accelerations in Waves

We examine the degree to which acceleration data from model-scale testing agree with acceleration data from full-scale testing. We find strong evidence that the model testing fails to recreate a certain type of low-acceleration impact that is found in full-scale data. In addition, there is some indication that model-scale testing may underestimate the frequency with which full-scale planing craft experience extreme vertical accelerations. Finally, we present evidence that spectrum type plays only a negligible role in the distribution of vertical and longitudinal accelerations. 1. Introduction Planing hulls operating at sea experience frequent wave impacts. Extreme impacts can result in structural damage, equipment malfunction or failure, or personnel discomfort or injury, or may require reduced speed to avoid such results. The vertical accelerations measured during these wave slams are used as one of the key design factors for the assessment of onboard comfort level, operational limits, and structural design. However, there is only limited ability to predict the vertical accelerations a planing hull will experience. Computational fluid dynamics models show great promise, but they are still in the validation stages (Fu et al. 2013; Fu et al. 2014; Maousaviraad et al. 2015). Guidelines used in structural design are based on empirical relationships determined from model testing results. Yet, there is little research into the connections between the accelerations measured during model testing in tow-tank-generated waves and the actual accelerations of full-scale planing hulls operating in real seas. Full-scale measurements of accelerations are obtained under conditions that are hard to know precisely. The wave conditions are typically determined from buoys that are not necessarily located very close to the testing area. In addition, the information from the buoys is generally limited to a significant wave height and modal or average wave period. Researchers often do not have access to information about the frequency distribution of the waves or an estimate of the wave energy spectrum type. Researchers conducting model testing must, therefore, make assumptions about the irregular waves when deciding what waves to generate in the tank. In addition, many tow-tank tests use methods to propel the models that are very different from the self-propelled, nonconstrained motion of a full-scale planing craft. When vertical accelerations are investigated during model testing, little research is conducted on the longitudinal accelerations for the model.

SAT-467 Gigantism Caused by Growth Hormone-Secreting Pituitary Macroadenoma: A Case Report

Background Gigantism is a rare condition where excessive secretion of growth hormone (GH) occurs before fusion of the epiphyseal growth plates. Clinical Case A 23-year-old Sri Lankan male presented to the Endocrine clinic with extreme tall stature, and was diagnosed to have pituitary gigantism. He had been the tallest in his class since 5 years old. Pubertal development from 12 years of age was normal. There was no history of headache, visual disturbance, galactorrhea or any hypogonadal symptoms. Family history was non-contributory. On examination, there were clinical features of frontal bossing, prognathism, and prominence of supra-orbital ridge. He was 196cm in height (calculated midparental height of 171cm) and at Tanner stage 5. Initial medical treatment was started with cabergoline for 1 year, before decision for surgical treatment was sought in Singapore. Initial laboratory investigations revealed an elevated serum insulin-like growth factor-1 (IGF-1) value of 577ng/mL (RR: 116-358ng/mL), and failure of GH suppression during an oral glucose tolerance test, with GH nadir of 3.99 ng/mL (RR: <1 to 13.4ng/mL, no gender nor age-specific cut offs were provided). Prolactin was 132 mIU/L (RR 77-274mIU/L) and total testosterone was 11 nmol/L (RR 5-30nmol/L). Basal cortisol, thyroid function test, and calcium levels were normal. Pituitary magnetic resonance imaging showed a hypo-enhancing focus in the left lateral aspect of the pituitary gland with extension into the sphenoid sinus, measuring 12mm in size at largest diameter, which was suspicious for a pituitary adenoma. He subsequently underwent transphenoidal surgery, and there were no immediate complications post operatively. During a follow up visit 3 months after surgery, laboratory investigations showed normalization of GH (0.33 ng/mL), IGF-1 (212 ng/mL) levels, and normal GH suppression during OGTT. Conclusion Pituitary gigantism occurs during the pre-pubertal period of active linear growth, where elevated GH and IGF-1 levels result in extreme growth acceleration and tall stature (1). The treatment of choice for well-circumscribed pituitary adenomas is transphenoidal surgery, which may be curative (2).

A lightweight electromagnetic actuator for high voltage DC power grids

High voltage direct current (HVDC) is a highly efficient alternative for transmitting large amounts of electricity over long distances, and holds great potential to enable stronger, smarter and greener power grids based on renewable energy sources. However, efficient management of HVDC grids calls for robust switchgear technology, which is still under development. In particular, fast switching speed is paramount to limit peak fault current and energy loss in hybrid HVDC circuit breakers (HHBs). In such breakers, the switching speed depends on the mass of the moving parts. Therefore, lightweight is paramount.Here, a lightweight electromagnetic actuator for HHBs is conceived using Design for Additive Manufacturing (DfAM) tools, including topology optimization and free-shape design. A prototype is manufactured by selective laser melting (SLM) of alloy Ti-6Al-4V. The prototype weighs 25% less than the actuator designed and manufactured using traditional methods (i.e. CAD, milling) and materials (i.e. Al alloys). The performance of the actuator in service is simulated by transient modal mechanical analyses using finite element methods. The results show that the high strength of the material selected, combined with the bionic geometry designed and the resulting lightweight, allow the actuator to withstand the extreme accelerations of the HHB (3000 g) without yielding, enabling ultra-fast switching –namely, below 1 ms.

Vibration and acceleration levels of multimodal container shipping physical environment

In global supply chains, multimodal transportation plays a dominant role in worldwide shipping. The rail, truck, and vessel combination is the most commonly used mode for non‐time sensitive shipments between continents. This study focused on measuring the transportation environment effects (vibration and acceleration levels) in 40‐foot ISO container shipments using multiple modes of transport, originating in Hungary and destined for Mexico, India, and China over several weeks. The study also measured multimodal shipping routes without vessel transportation to China over Trans‐Siberian and Trans‐Manchurian railway lines. The transshipments and handling events in container hubs and terminals were separately analyzed. The results show the comparison of vibration intensity (in PSD) of different route conditions between various continents, and the possibility of acceleration levels during transshipments and handling events. The measured data show that extreme acceleration levels in vertical direction (9.37 G) occur while containers are handled in a seaport, and in lateral (4.45 G) and longitudinal (5.55 G) directions while they are transshipped by truck to rail container terminals. The rail vibration levels in Russia and China showed a lower intensity in the frequency range of 1 to 15 Hz, and higher between 15 and 200 Hz than in Europe; the lowest vibration levels occurred when the containers traveled on the sea, and truck vibration levels were very similar to previous research and ISTA protocols.

Solitonic State in Microscopic Dynamic Failures

Onset of permanent deformation in crystalline materials under a sharp indenter tip is accompanied by nucleation and propagation of defects. By measuring the spatio-temporal strain field near the indenter tip during indentation tests, we demonstrate that the dynamic strain history at the moment of a displacement burst carries characteristics of the formation and interaction of local excitations, or solitons. We show that dynamic propagation of multiple solitons is followed by a short time interval where the propagating fronts can accelerate suddenly. As a result of such abrupt local accelerations, duration of the fast-slip phase of a failure event is shortened. Our results show that formation and annihilation of solitons mediate the microscopic fast weakening phase, during which extreme acceleration and collision of solitons lead to non-Newtonian behavior and Lorentz contraction, i.e., shortening of solitons’ characteristic length. The results open new horizons for understanding dynamic material response during failure and, more generally, complexity of earthquake sources.

Extreme Accelerations During Earthquakes Caused by Elastic Flapping Effect

Accurate recording of large, earthquake-induced ground shaking is critical for our understanding of earthquake physics as well as seismic hazard assessment. Extremely large accelerations with the peak value of 3.2 times the gravity acceleration were recorded at seismic station WTMC located in northern South Island of New Zealand during the recent magnitude 7.8 Kaikoura earthquake. However, the mechanisms responsible for the generation of such large accelerations are not well understood. Here we use numerical simulations to examine a range of physical models that can reproduce the observed characteristics of the acceleration record. We find that the record of the asymmetric, vertical accelerations, also observed during a magnitude 6.3 earthquake, can be explained by a flapping effect, that is, the local, elastic bouncing of a foundation slab on which the sensor is installed. Our results suggest that the extremely large accelerations recorded at seismic station WTMC do not reflect the actual ground shaking, but were caused by a local, system response around the sensor. Our finding has important implications for both the evaluation of future seismic hazard based on the waveform records of the Kaikoura earthquake and the installation methodology of strong-motion seismometers in all earthquake prone countries.

Accelerating behaviour of the driver and acceleration characteristics of the dangerous event

The accelerating behaviour of the driver and the relationship between the extreme acceleration and dangerous events are studied by using the naturalistic driving data. Firstly, the bivariate accelerating patterns between the longitudinal acceleration, lateral acceleration and velocity are proposed. Next, the univariate accelerating behaviour characteristics are achieved. Then, the extreme driving data in 0.01st density contour outer area are analysed. In the last, the driving style is studied based on the extreme acceleration data. The conclusions include: the univariate acceleration distributions approximate the Pareto distribution, which is known as the heavy tail distribution. Most of the extreme acceleration data are not dangerous events. And the majority of the dangerous events are in the high brake deceleration region, whereas high lateral acceleration does not have apparent relationship with the dangerous event. Aggressive drivers account for most of the extreme acceleration data, and they are more likely to be in danger.

Improving SWATH Seakeeping Performance using Multi-Fidelity Gaussian Process and Bayesian Optimization

We construct a multi-fidelity framework for statistical learning and global optimization that is capable of effectively synthesizing seakeeping predictions having two different levels of modeling fidelity, namely a strip theory and a boundary element method based on potential flow assumption. The objective of this work is to demonstrate that the multi-fidelity framework can be used efficiently to discover optimal small waterplane area twin hull shapes having superior seakeeping performance using a limited number of expensive high-fidelity simulations combined with a larger number of inexpensive low-fidelity simulations. Specifically, we employ multi-fidelity Gaussian process regression and Bayesian optimization to build probabilistic surrogate models and efficiently explore a 35-dimensional design space to optimize hull shapes that minimize wave-induced motions and accelerations, and satisfy specific requirements in terms of displacement and metacentric height. Our results demonstrate the superior characteristics of this optimization framework in constructing accurate surrogate models and identifying optimal designs with a significant reduction in the computational effort. 1. Introduction During the past decades, estimating the seaworthiness of a ship in the early design stages has become a primary concern for naval architects. Increased requirements in terms of comfort and ergonomics have steered the research in developing innovative hull forms, with the specific target of decreasing motions in waves. From a safety point of view, extreme accelerations can exert harmful dynamic loads (on the vessel, cargo, or equipment), slamming, or green water effects that can severely damage the structural integrity of the vessel or lead to stability losses. When ship behavior in waves becomes a quantity of interest in the hull-form optimization process, seakeeping performance needs to be predicted with numerical models able to combine high fidelity and high computational efficiency. Nowadays, ship motion predictions mainly rely on three families of numerical models, here sorted by increasing level of fidelity: 2-D strip theories, 3-D boundary element methods (BEM), both developed under the assumption of potential flow, and unsteady fully viscous nonlinear 3-D methods in which ship motions are simulated in six Degrees of Freedom (DOF) for incident regular or irregular waves (see Fig. 5). In this article, we introduce a probabilistic method for constructing surrogate models using multi-fidelity training datasets that allows to increase the accuracy of the model with significant savings in computational resources. For the purpose of demonstration of the multi-fidelity framework, the training datasets used in this article are composed of classical 2-D and 3-D potential flow predictions; for this reason, we will refer to 2-D strip theories as low-fidelity models and a more accurate 3-D BEM as high-fidelity models. In the present study, our goal is to demonstrate the ability of the multi-fidelity framework in efficiently discovering hull forms with superior seakeeping characteristics by using simplified prediction models. Although in the present study, we do not include any viscous effects, the methodology is general and can combine any type of high-fidelity simulations or experimental data with low-fidelity simulations, experimental data, or even empirical correlations.