Acceleration Research Articles

Finite Element Analysis of Cervical Spine Kinematic Response during Ejection Utilising a Hill-Type Dynamic Muscle Model.

To determine the impact of active muscle on the dynamic response of a pilot's neck during simulated emergency ejection, a detailed three-dimensional (3D) cervical spine (C0-T1) finite element (FE) model integrated with active muscles was constructed. Based on the Hill-type model characterising the muscle force activation mechanics, 13 major neck muscles were modelled. The active force generated by each muscle was simulated as functions of (i) active state (Na), (ii) velocity (Fv(v)), and (iii) length (FL(L)). An acceleration-time profile with an initial acceleration rate of 125 G·s-1 in the 0-80 ms period, reaching peak acceleration of 10 G, then kept constant for a further 70 ms, was applied. The rotational angles of each cervical segment under these ejection conditions were compared with those without muscles and with passive muscles derived from the previous study. Similar trends of segmental rotation were observed with S- and C-curvature of the cervical spine in the 150 ms span analysed. With active muscles, the flexion motion of the C0-C2 segments exhibited higher magnitudes of rotation compared to those without muscle and passive muscle models. The flexion motion increased rapidly and peaked at about 95-105 ms, then decreased rapidly to a lower magnitude. Lower C2-T1 segments exhibited less variation in flexion and extension motions. Overall, during emergency ejections, active muscle activities effectively reduce the variability in rotational angles across cervical segments, except C0-C2 segments in the 60-120 ms period. The role of the active state dynamics of the muscles was crucial to the magnitude of the muscle forces demonstrated. This indicates that it is crucial for pilots to consciously contract their muscles before ejection to prevent cervical spine injuries.

The effect of music therapy on non-stress test results and anxiety levels in high-risk pregnant women: A randomized controlled trial.

This study was conducted to determine the effects of music therapy on non-stress test results and anxiety levels in high-risk pregnant women. This randomized controlled study was conducted in pregnant women who were hospitalized in the High-Risk Pregnancy Service of Meram Medical Faculty Hospital, Konya, Turkey, between April 1 and July 31, 2021. In the intervention group (n = 58), a 20-min music therapy with ney sounds was performed, while in the control group (n = 58), routine care practices were applied. Hüseyni maqam of ney was selected, a melodic mode used by Turks for music therapy. Data were collected using the Descriptive Information Form, the Non-Stress Test Evaluation Form, and the State-Trait Anxiety Inventory. After music therapy, the intervention group experienced increased mean acceleration (p = 0.010) and foetal movement rates (p < 0.001) while no such difference was observed in the control group. The state anxiety levels of pregnant women differed significantly between the intervention and control groups (p < 0.001). Regression analysis showed that music therapy reduced state anxiety levels in pregnant women by a factor of 4.6 (p < 0.001). Based on the findings, music therapy was found to enhance acceleration and foetal heart rate in high-risk pregnant women while reducing state anxiety levels.

Toward a Direct Measurement of the Cosmic Acceleration: The Pilot Observation of HI 21 cm Absorption Line at FAST

This study presents results on detecting neutral atomic hydrogen (H i) 21 cm absorption in the spectrum of PKS PKS1413+13 at redshift z = 0.24670041. The observation was conducted by FAST, with a spectral resolution of 10 Hz, using 10 minutes of observing time. The global spectral profile is examined by modeling the absorption line using a single Gaussian function with a resolution of 10 kHz within a 2 MHz bandwidth. The goal is to determine the rate of the latest cosmic acceleration by directly measuring the redshift evolution of the H i 21 cm absorption line with Hubble flow toward a common background quasar over a decade or longer time span. This will serve as a detectable signal generated by the accelerated expansion of the Universe at redshift z < 1, referred to as redshift drift ż or the SL effect. The measured H i gas column density in this DLA system is approximately equivalent to the initial observation value, considering uncertainties of the spin temperature of a spiral host galaxy. The high signal-to-noise ratio of 57, obtained at a 10 kHz resolution, strongly supports the feasibility of using the H i 21 cm absorption line in DLA systems to accurately measure the redshift drift rate at a precision level of around 10−10 per decade.

Cosmological dynamics in f(R) gravity models through cosmographic energy conditions

A proposed f(R) functional form’s constraints caused by energy conditions are presented. Raychaudhuri’s equation and the premise that gravity is attractive are both used to derive null and strong energy conditions for the proposed f(R) gravity model. Furthermore, the weak and dominant energy conditions are established by analysing the energy conditions induced by an effective energy-momentum tensor for the f(R)-theory of gravity. The most recent estimates of the cosmographic parameters that mimic Chaplygin gas-type dark energy are used on the parameters of a pair of f(R) models as a tangible extension of the energy conditions to the Robertson-Walker universe. It is found that under the various values of the coupling parameters the proposed f(R) model satisfy null, weak and dominant energy conditions while strong energy conditions are breached. Further, constraining the coupling parameters as a result of energy conditions, our analysis shows that the proposed model accurately captures the observed cosmic acceleration, as indicated by key parameters such as the effective equation of state (ω eff ), and the deceleration parameter (q). Through a geometric analysis of cosmographic parameters, we observe deviations of f(R) gravity from the ΛCDM model. We identify distinct evolutionary pathways that resemble characteristics of either quintessence or Chaplygin gas dark energy across various epochs, indicating a dynamic rate of cosmic acceleration. Our findings highlight the significant influences of coupling parameters and initial conditions on the cosmic evolution.

THE ECOLOGICAL CONSCIOUSNESS MATRIX IN THE CONTEXT OF RUSSIAN SOCIETY RESOURCE SUSTAINABILITY: INTERDISCIPLINARY APPROACH

The article examines the problem of resource sustainability of the Russian society in conditions of accele-rating rate of technic evolution and anthropogenic pressure on the natural world of the Earth. In this regard, the authors analyze the prerequisites for the environmental consciousness formation as a signifi cant structure of social self-organization related with the factors of ontological security, trust and human responsibility for the biosphere preservation. Research is carried out within the framework of an ecosystem approach, which emphasizes that’s the combination of biosphere and social resources ensuring the sustainable development of the global world. Setting of social psychology to activate the norm is used in the analysis of the motivation factors of pro-ecological behavior. The empirical basis is the statistical material of sociological surveys conducted by the Russian Public Opinion Re-search Center. At present, ecological consciousness resource is associated with a set of beliefs and values that guide person’s perception of the natural environment within the human life world as a self-suffi cient system interacting with the structures from technological and social spheres. There are various models of person’s behavior motivated by a combination of social norms and personal attitudes that form the semantic matrix of personal environmental consciousness. On the other hand, citizens’ concern for the environment state is identifi ed as a leading factor in motivating pro-environmental behavior. Presented statistical data from VCIOM surveys show the level of public awareness about the global signifi cance of the life safety factor in their region and public involvement in changing the situation. In conclusion, the authors emphasize that the formation of contextual structures of consciousness based on ecosystem settings gives rise to new stereotypes of worldview, thought and behavior. Therefore, this type of consciousness represents a signifi cant resource for the sustainable development of Russian society in condition of technogenic civilization

Ultra low-power, wearable, accelerated shallow-learning fall detection for elderly at-risk persons

This work focuses on the development and manufacturing of a wireless, wearable, low-power fall detection sensor (FDS) designed to predict and detect falls in elderly at-risk individuals. Unintentional falls are a significant risk in this demographic, often resulting from diminished physical capabilities such as reduced hand grip strength and complications from conditions like arthritis, vertigo, and neuromuscular issues. To address this, we utilize advanced low-power field-programmable gate arrays (FPGAs) to implement a fixed-function neural network capable of categorizing activities of daily life (ADLs), including the detection of falls. This system employs a Convolutional Neural Network (CNN) model, trained and validated using the Caffe deep learning framework with data collected from human subjects experiments. This system integrates an ST Microelectronics LSM6DSOX inertial measurement unit (IMU) sensor, embedded with an ultra-low-power Lattice iCE40UP FPGA, which samples and stores joint acceleration and orientation rate. Additionally, we have acquired and published a dataset of 3D accelerometer and gyroscope measurements from predefined ADLs and falls, using volunteer human subjects. This innovative approach aims to enhance the safety and well-being of older adults by providing timely and accurate fall detection and prediction.In this paper, we present an innovative approach to utilizing a compact Convolutional Neural Network (CNN) core for accelerating convolutional operations on a machine learning model, suitable for deployment on an ultra-low power FPGA.

Flame propagation characteristics and gas-phase oxidation of nitrous oxide and propane

Nitrous oxide and fuel blends propellant as one of the substitutes for highly toxic hydrazine are under investigation. This study investigated the flame structure and dynamics of stoichiometric nitrous oxide and propane mixture (N2O/C3H8) by using polymethyl methacrylate (PMMA) tubes of varying inner diameters (5, 10, 15, and 50 mm) and a consistent length (1400 mm). The influence of tube diameter on flame acceleration was analyzed. The results reveal that within the 50-mm diameter tube, the flame propagation speed increased as the flame front moved forward in the tube, achieving a maximum speed of 532 m/s. In the tubes with 5-, 10-, and 15-mm diameters, all three stages—deflagration, transition to detonation, and detonation attenuation—were observed. Notably, the flame acceleration rate and maximum propagation velocity increased with the tube diameter, with the maximum velocities in the 5-, 10-, and 15-mm tubes being 1900, 2060, and 2140 m/s, respectively. The oxidation pathways of C3H8 reacting with N2O were studied using the B3LYP/6–31++G** method based on density functional theory. Thus, the study could determine changes in the configurations of reactants, intermediates, transition states, and products; the characteristics of the potential energy associated with the reaction pathways; and the reaction laws and thermodynamic parameters.

Enhancing quality and speed in database-free neural network reconstructions of undersampled MRI with SCAMPI.

We present SCAMPI (Sparsity Constrained Application of deep Magnetic resonance Priors for Image reconstruction), an untrained deep Neural Network for MRI reconstruction without previous training on datasets. It expands the Deep Image Prior approach with a multidomain, sparsity-enforcing loss function to achieve higher image quality at a faster convergence speed than previously reported methods. Two-dimensional MRI data from the FastMRI dataset with Cartesian undersampling in phase-encoding direction were reconstructed for different acceleration rates for single coil and multicoil data. The performance of our architecture was compared to state-of-the-art Compressed Sensing methods and ConvDecoder, another untrained Neural Network for two-dimensional MRI reconstruction. SCAMPI outperforms these by better reducing undersampling artifacts and yielding lower error metrics in multicoil imaging. In comparison to ConvDecoder, the U-Net architecture combined with an elaborated loss-function allows for much faster convergence at higher image quality. SCAMPI can reconstruct multicoil data without explicit knowledge of coil sensitivity profiles. Moreover, it is a novel tool for reconstructing undersampled single coil k-space data. Our approach avoids overfitting to dataset features, that can occur in Neural Networks trained on databases, because the network parameters are tuned only on the reconstruction data. It allows better results and faster reconstruction than the baseline untrained Neural Network approach.

Experimental road safety study of the actual driver reaction to the street ads using eye tracking, multiple linear regression and decision trees methods

The article describes the results of a naturalistic driving study done in Kuwait performed by 34 participants wearing a mobile eye tracker to monitor the effect of roadside advertisements on user attention. Eye-tracking (fixations) are the main dependent variable and examined as a function of driving/roadside characteristics, particularly billboards, speed, and so forth. The results obtained were analyzed using traditional statistics (ANOVA test and multiple linear regression) and machine learning (decision tree estimation methods). From the results, it was found that road advertisements negatively affect driver attention and thus road safety. How the level of safety varies with the type and size of advertisement was also investigated. As a consequence, all of the estimates revealed that different aspects of advertising have a detrimental impact on drivers' behavior, and that the duration of fixation and the rate of acceleration before viewing an ad are impacted by advertising type and size, respectively.

Piezo stack energy harvesters with protection components for railway applications

Piezo stack energy harvesting from railway vibrations shows substantial potential for powering wireless sensor networks responsible for monitoring railway infrastructure. Nevertheless, assuring the safety and durability of these energy harvesters in the condition of the dynamically fluctuating railway vibrations remains a considerable challenge. In this paper, we present two innovative protection methods designed for piezo stack energy harvesters with a frequency up-conversion mechanism. These methods involve the incorporation of ring-type and circular stoppers within the resonant system and the utilisation of proposed impact protection components within the impact system. Two distinct harvesters incorporating the proposed protection components, Harvester Types I and II, are designed to align with their respective operating acceleration targets, which are determined based on the amplitudes of railway vibration acceleration. Finite element modelling is used to guide the design process, involving the evaluation and selection of various design parameters aligned with the acceleration target and stress limits. The protection mechanisms’ effectiveness and impact on energy harvesting performance have been validated through experimental testing under measured rail vibration signals, and their performance has been further assessed through stress analyses. Harvester Type I operates seamlessly within a 5 g threshold, effectively mitigating the increase in maximum output acceleration and stress beyond this limit. In contrast, Harvester Type II efficiently dissipates excess energy, enabling the harvester to operate at a 15 g acceleration while reducing the rate of acceleration and stress growth. The results demonstrate that both proposed harvesters provide effective protection from unexpected railway vibration overloads. This research makes a significant impact on the practical, real-world implementation of piezo stack energy harvesters operating within the dynamic environment of railway vibrations.

Parameters Influencing the Effectiveness of Reaction Control Jets on the Basic Finner

Reaction control jets provide a practical option to increase the acceleration rates of high-performance aerodynamic vehicles. Unfortunately, a designer or system engineer incorporating reaction control jets into a design cannot simply add the jet as a point force because it does not account for the change in force due to the modifications of the flowfield caused by the jet. The changes made to the flowfield can impact the forces and moments, enhancing, mitigating, or even reversing the desired force or moment, depending on a complex set of factors. This study examines the influence of different jet configurations, modifications to freestream parameters, and the presence of control surfaces on the body. It is shown that the proximity of the jet to the control surfaces has the most significant impact on the resulting force amplification. The emphasis is placed on differentiating between how the jet interacts with the body and fins. Ultimately, this shows that the interaction with the fuselage is consistent and self-similar, whereas the fins are primarily influenced by the jet blocking the flow and generating a shock that imparts high pressure on the control surface, increasing the force in the direction of the jet.

Learning effects in over-ground running gait retraining: A six-month follow-up of a quasi-randomized controlled trial

ABSTRACT This study evaluated learning and recall effects following a feedback-based retraining program. A 6-month follow-up of a quasi-randomized controlled trial was performed with and without recall. Twenty runners were assigned to experimental or control groups and completed a 3-week running program. A body-worn system collected axial tibial acceleration and provided real-time feedback on peak tibial acceleration for six running sessions in an athletic training facility. The experimental group received music-based biofeedback in a faded feedback scheme. The controls received tempo-synchronized music as a placebo for blinding purposes. The peak tibial acceleration and vertical loading rate of the ground reaction force were determined in a lab at baseline and six months following the intervention to assess retention and recall. The impacts of the experimental group substantially decreased at follow-up following a simple verbal recall (i.e., run as at the end of the program): peak tibial acceleration:-32%, p = 0.018; vertical loading rate:-34%, p = 0.006. No statistically significant changes were found regarding the retention of the impact variables. The impact magnitudes did not change over time in the control group. The biofeedback-based intervention did not induce clear learning at follow-up, however, a substantial impact reduction was recallable through simple cueing in the absence of biofeedback.

Artificial light at night affects the daily profile of pulse pressure and protein expression in the thoracic aorta of rats

Artificial light at night (ALAN) disrupts 24-h variability of blood pressure, but the molecular mechanisms underlying these effects are unknown. Therefore, we analysed the daily variability of pulse pressure, the maximum value of acceleration rate of aortic pressure (dP/dt(max)) measured by telemetry and protein expression in the thoracic aorta of normotensive male rats exposed to ALAN (1–2 lx) for 3 weeks. Daily, 24-h variability of pulse pressure and dP/dt(max) was observed during a regular light/dark regimen with higher values during the dark compared to the light phase of the day. ALAN suppressed 24-h variability and enhanced ultradian (<12-h) periods of pulse pressure and dP/dt(max) in duration-dependent manners. From beat-to-beat blood pressure variability, ALAN decreased low-frequency bands (a sympathetic marker) and had minimal effects on high-frequency bands. At the molecular level, ALAN decreased angiotensin II receptor type 1 expression and reduced 24-h variability. ALAN caused the appearance of 12-h oscillations in transforming growth factor β1 and fibulin 4. Expression of sarco/endoplasmic reticulum Ca2+-ATPase type 2 was increased in the middle of the light and dark phase of the day, and ALAN did not affect its daily and 12-h variability. In conclusion, ALAN suppressed 24-h variability of pulse pressure and dP/dt(max), decreased the power of low-frequency bands and differentially affected the expression of specific proteins in the rat thoracic aorta. Suppressed 24-h oscillations by ALAN underline the pulsatility of individual endocrine axes with different periods, disrupting the cardiovascular control of central blood pressure.

High-Quality Solution-Processed Quasi-2D Perovskite for Low-Threshold Lasers.

Spin-coated quasi-two-dimensional halide perovskite films, which exhibit superior optoelectronic properties and environmental stability, have recently been extensively studied for lasers. Crystallinity is of great importance for the laser performance. Although some parameters related to the spin-coating process have been studied, the in-depth understanding and effective control of the acceleration rate on two-dimensional perovskite crystallization during spin-coating are still unknown. Here we investigate the effect of solvent evaporation on the microstructure of the final perovskite films during the spin-coating process. The crystallization quality of the film can be significantly improved by controlling solvent evaporation. As a result, the prepared quasi-2D perovskite film exhibits a stimulated emission threshold (pump: 343 nm, 6 kHz, 290 fs) of 550 nm as low as 16.2 μJ/cm2. Transient absorption characterization shows that the radiative biexciton recombination time is reduced from 738.5 to 438.3 ps, benefiting from the improved crystallinity. The faster biexciton recombination significantly enhanced the photoluminescence efficiency, which is critical for population inversion. This work could contribute to the development of low-threshold lasers.

Influence of emotions on the aggressive driving behavior of online ­car-hailing drivers based on association rule mining

Emotion is an important factor that can lead to the occurrence of aggressive driving. This paper proposes an association rule mining-based method for analysing contributing factors associated with aggressive driving behaviour among online car-hailing drivers. We collected drivers’ emotion data in real time in a natural driving setting. The findings show that 29 of the top 50 association rules for aggressive driving are related to emotions, revealing a strong relationship between driver emotions and aggressive driving behaviour. The emotions of anger, surprised, happy and disgusted are frequently associated with aggressive driving behaviour. Negative emotions combined with other factors (for example, driving at high speeds and high acceleration rates and with no passengers in the vehicle) are more likely to lead to aggressive driving behaviour than negative emotions alone. The results of this study provide practical implications for the supervision and training of car-hailing drivers.

Design of Active Suspension Controller for Ride Comfort Enhancement and Motion Sickness Mitigation

This paper presents a method for designing an active suspension controller for ride comfort enhancement and motion sickness mitigation. For this, it is necessary to design an active suspension controller, which aims to reduce the vertical acceleration and pitch rate of a sprung mass in a vehicle. A half-car vehicle model was selected. For the controller design, a static output feedback (SOF) control was selected instead of a full-state feedback control because it is hard to measure all state variables in real vehicles. With the available signals, three types of SOF controller were proposed. To determine the gains of the SOF controllers, a linear quadratic optimal control methodology and a simulation-based optimization method were adopted. To validate the proposed method, a simulation was carried out using vehicle simulation software. The simulation results show that the proposed method is quite effective for ride comfort enhancement and motion sickness mitigation.

Transient mixed thermal elastohydrodynamic lubrication under startup and shut down conditions

The transient mixed lubrication behaviors in thermal elastohydrodynamic lubrication (TEHL) contacts during startup and stop are investigated. A transient mixed TEHL model for point contacts under time-varying speed conditions is proposed with comprehensive consideration of surface roughness, thermal effect, and transient behavior. The model is validated by the comparison to available published data. Based on the developed model, significant differences have been found compared with transient EHL and steady TEHL models. In addition, the transient mixed TEHL performance during start–stop with different acceleration rates and surface roughness is investigated. It shows that the lubrication behaviors during start–stop have an irreversible process. The roughness can significantly enhance the transient behavior. The roughness effect has a remarkable impact on lubrication performance in mixed lubrication. The evolution of lubrication behaviors during start–stop is highly related to the acceleration rate and surface topography.

Double Power-law Formation by Sequential Particle Acceleration

Spectral double power laws are common in solar high-energy phenomena such as flares and interplanetary energetic-electron events. However, the physical mechanism that produces the changes in power-law index within a single spectrum is unclear. We developed a fully analytical method of forming single power-law spectra from sequential acceleration of particles orbiting inside and hopping between simulated large-scale magnetic islands formed by flare reconnection. Here, we extend the analytical method to the formation of double power-law spectra by assuming sequential acceleration in two successive regions with different acceleration and particle-transport rates. The resulting spectral distribution is continuous and smooth, with a flattening at low energies, two power-law regions at mid-energies, and a steep rollover at high energies. The model provides analytical expressions for the spectral indices, all energy breaks, and normalization constants as functions of just three physical parameters of each acceleration region: (1) the energy gain in each accelerator, (2) the percentage of particles transferred between accelerators, and (3) the number of accelerators visited. One of the most salient predictions of our work is that the spectral index at high (low) energies is determined by the parameters of the first “seed” (second) acceleration region. By constructing the spectral distribution through an iterative analytical process, the evolution toward a double power law is easily characterized and explained. Our analytical model provides tools to interpret space- and ground-based observations from RHESSI, FOXSI, NuSTAR, Solar Orbiter/STIX, EOVSA, and future high-energy missions.

Relativistic acceleration in noninertial frames of a line of objects

A general solution to the problem of relativistic acceleration of point objects in the noninertial frame of any of the objects is given in one spatial dimension. The objects are initially at rest in a common inertial frame and accelerate until they are at rest in a second inertial frame. The starting time and position of each object, the acceleration rate of each object, and the number of objects are arbitrary. The solution gives the position and velocity of each object in the noninertial frame of the host object, and the proper time of each, as functions of the proper time of the host. The method is based on system states for a pair of objects, and it is found that there are nine series of states which cover all cases, including those in which objects are separated from the host by its Rindler horizon. The familiar problems of acceleration of an elastic rod and a (Born) rigid rod are treated, and a number of examples are given of spaceflight sequences for multiple craft in tandem.

An acceleration model for low-speed flames in curved channels

This study investigates the initial acceleration process of low-speed flames in curved channels. It also examines how the curvature and width of the channels influence flame propagation patterns and mechanisms. Previous research has highlighted the advantages of curved channels in facilitating flame acceleration. Subsequent studies have explored the interaction between pressure waves and flames, particularly in the later stages of flame propagation, leading to a high-speed flame phase. However, the effects of curvature and channel width on the initial acceleration phase of low-speed flames remain unclear. To address this gap, the present study utilizes theoretical methods to analyze the early acceleration phase of flames in curved channels with fixed curvature and width, from the closed end to the open end. Semi-analytical theoretical solutions are derived to determine the shape of the unburned gas flow field, flame front, and flame acceleration rate. The results demonstrate that the flow field shape deviates from axial symmetry to conserve angular momentum, favoring the inner wall of the curved channel and causing the flame front to adhere to it. In channels with small curvature, increasing the width leads to a decrease in the flame acceleration rate. Conversely, in channels with large curvature, widening the channel results in an increased flame acceleration rate. These findings provide theoretical insights for optimizing the design of the front-stage structure of curved detonation channels.