Trajectory Parameters Research Articles

Exploring the role of anticipatory postural adjustment duration within APA2 subphase as a potential mediator between clinical disease severity and fall risk in Parkinson's disease.

People with Parkinson's Disease (PD) often show reduced anticipatory postural adjustments (APAs) before voluntary steps, impacting their stability. The specific subphase within the APA stage contributing significantly to fall risk remains unclear. We analyzed center of pressure (CoP) trajectory parameters, including duration, length, and velocity, throughout gait initiation. This examination encompassed both the postural phase, referred to as anticipatory postural adjustment (APA) (APA1, APA2a, APA2b), and the subsequent locomotor phases (LOC). Participants were instructed to initiate a step and then stop (initiating a single step). Furthermore, we conducted assessments of clinical disease severity using the Unified Parkinson's Disease Rating Scale (UPDRS) and evaluated fall risk using Tinetti gait and balance scores during off-medication periods. Freezing of gait (FOG) was observed in 18 out of 110 participants during the measurement of CoP trajectories. The Ramer-Douglas-Peucker algorithm successfully identified CoP displacement trajectories in 105 participants (95.5%), while the remaining 5 cases could not be identified due to FOG. Tinetti balance and gait score showed significant associations with levodopa equivalent daily dose, UPDRS total score, disease duration, duration (s) in APA2a (s) and LOC (s), length in APA1 (cm) and APA2b (cm), mediolateral velocity in APA1 (X) (cm/s), APA2a (X) (cm/s), APA2b (X) (cm/s) and LOC (X) (cm/s), and anterior-posterior velocity in APA2a (Z) (cm/s) and APA2b (Z) (cm/s). Multiple linear regression revealed that only duration (s) in APA2a and UPDRS total score was independently associated with Tinetti gait and balance score. Further mediation analysis showed that the duration (s) in APA2a served as a mediator between UPDRS total score and Tinetti balance and gait score (Sobel test, p = 0.047). APA2 subphase duration mediates the link between disease severity and fall risk in PD, suggesting that longer APA2a duration may indicate reduced control during gait initiation, thereby increasing fall risk.

Efficient Convolution-Based Representation of Smooth Reference Trajectories for Urban Air Mobility

Accurate trajectory-following control using dynamic inversion controllers requires suitable parameterizations of reference trajectories, such as energy-minimal flight paths generated with optimal control methods. These trajectory representations must enable efficient onboard storage and real-time evaluation while ensuring sufficient accuracy and smoothness to provide the required feedforward commands. We explore trajectory parameterizations based on the convolution of a piecewise low-order polynomial with an infinitely smooth kernel. These combine efficient storage with unlimited differentiability and allow for simple and efficient evaluation using numerical quadrature. To construct such parameterizations from given trajectories, we formulate quadratic programs that account for additional, mission-specific constraints. A numerical example demonstrates the parameterization of an approach and vertical landing trajectory based on optimal control results; we show that the convolution-based approach yields competitive results compared to a piecewise polynomial parameterization, with significant storage savings.

Joint modeling of monocyte HLA-DR expression trajectories predicts 28-day mortality in severe SARS-CoV-2 patients.

The recent SarsCov2 pandemic has disrupted healthcare system notably impacting intensive care units (ICU). In severe cases, the immune system is dysregulated, associating signs of hyperinflammation and immunosuppression. In the present work, we investigated, using a joint modeling approach, whether the trajectories of cellular immunological parameters were associated with survival of COVID-19 ICU patients. This study is based on the REA-IMMUNO-COVID cohort including 538 COVID-19 patients admitted to ICU between March 2020 and May 2022. Measurements of monocyte HLA-DR expression (mHLA-DR), counts of neutrophils, of total lymphocytes, and of CD4+ and CD8+ subsets were performed five times during the first month after ICU admission. Univariate joint models combining survival at day 28 (D28), hospital discharge and longitudinal analysis of those biomarkers' kinetics with mixed-effects models were performed prior to the building of a multivariate joint model. We showed that a higher mHLA-DR value was associated with a lower risk of death. Predicted mHLA-DR nadir cutoff value that maximized the Youden index was 5414 Ab/C and led to an AUC = 0.70 confidence interval (95%CI) = [0.65; 0.75] regarding association with D28 mortality while dynamic predictions using mHLA-DR kinetics until D7, D12 and D20 showed AUCs of 0.82 [0.77; 0.87], 0.81 [0.75; 0.87] and 0.84 [0.75; 0.93]. Therefore, the final joint model provided adequate discrimination performances at D28 after collection of biomarker samples until D7, which improved as more samples were collected. After severe COVID-19, decreased mHLA-DR expression is associated with a greater risk of death at D28 independently of usual clinical confounders.

Exploring non-commutativity as a perturbation in the Schwarzschild black hole: quasinormal modes, scattering, and shadows

In this work, by a novel approach to studying the scattering of a Schwarzschild black hole, the non-commutativity is introduced as perturbation. We begin by reformulating the Klein–Gordon equation for the scalar field in a new form that takes into account the deformed non-commutative spacetime. Using this formulation, an effective potential for the scattering process is derived. To calculate the quasinormal modes, we employ the WKB method and also utilize fitting techniques to investigate the impact of non-commutativity on the scalar quasinormal modes. We thoroughly analyze the results obtained from these different methods. Moreover, the greybody factor and absorption cross section are investigated. Additionally, we explore the behavior of null geodesics in the presence of non-commutativity. Specifically, we examine the photonic, and shadow radius as well as the light trajectories for different non-commutative parameters. Therefore, by addressing these various aspects, we aim to provide a comprehensive understanding of the influence of non-commutativity on the scattering of a Schwarzschild-like black hole and its implications for the behavior of scalar fields and light trajectories.

Association of bioimpedance analysis parameters trajectories with clinical outcomes in neurocritical patients

Background and objectiveNeurocritical patients often experience uncontrolled high catabolic metabolism state during the acuta phase of the disease. The complex interactions of neuroendocrine, inflammation, and immune system lead to massive protein breakdown and changes in body composition. Bioelectrical impedance analysis (BIA) evaluates the content and proportions of body components based on the principles of bioelectricity. Its parameters reflect the overall health status of the body and the integrity of cellular structure and function, playing an important role in assessing the disease status and predicting prognosis of such patients. This study explored the association of BIA parameters trajectories with clinical outcomes in neurocritical patients. MethodsThis study prospectively collected BIA parameters of 127 neurocritical patients in the Department of Neurology admitted to the NICU for the first 1–7 days. All these patients were adults (≥18 years old) experiencing their first onset of illness and were in the acute phase of the disease. The group-based trajectory modeling (GBTM), which aims to identify individuals following similar developmental trajectories, was used to identify potential subgroups of individuals based on BIA parameters. The short-term prognosis of patients in each trajectory group with variations in phase angle (PA) and extracellular water/total body water (ECW/TBW) over time was differentially analyzed, and the logistic regression model was used to analyze the relationship between potential trajectory groups of PA and ECW/TBW and the short-term prognosis of neurocritical patients. The outcome was Glasgow Outcome Scale (GOS) score at discharge. ResultsFour PA trajectories and four ECW/TBW trajectories were detected respectively in neurocritical patients. Among them, compared with the other latent subgroups, the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup” had higher incidences of adverse outcomes at discharge (GOS:1–3), in-hospital mortality, and length of neurology intensive care unit stay (all P < 0.05). After correcting for potential confounders, compared with the “Low PA rapidly decreasing subgroup”, the risk of adverse outcome (GOS:1–3) was lower in the other three PA trajectories, with OR values of 0.0003, 0.0004, and 0.003 respectively (all P < 0.05). Compared with the “High ECW/TBW slowly rising subgroup”, the risk of adverse outcome (GOS:1–3) was lower in the other three ECW/TBW trajectories, with OR values of 0.013, 0.035 and 0.038 respectively (all P < 0.05). ConclusionLatent PA trajectories and latent ECW/TBW trajectories during 1–7 days after admission were associated with the clinical outcomes of neurocritical patients. The risk of adverse outcomes was highest in the “Low PA rapidly decreasing subgroup” and the “High ECW/TBW slowly rising subgroup”. These results reflected the overall health status and nutritional condition of neurocritical patients at the onset of the disease, and demonstrated the dynamic change process in body composition caused by the inflammatory response during the acute phase of the disease. This provided a reference basis for the observation and prognostic evaluation of such patients.

Anatomical Parameters of Percutaneous, Minimally Invasive, Direct Intralaminar Pars Screw Fixation of Spondylolysis

ObjectiveTo investigate the anatomical parameters of the ideal screw trajectory for percutaneous intralaminar screw fixation of a pars defect in lumbar spondylolysis using computed tomography scans. MethodsUsing advanced radiological software, the ideal intralaminar screw trajectory was determined. The anatomical parameters of this trajectory were analyzed using a total of 80 single-level lumbar tomography scans in patients with spondylolysis at the L4 and L5 levels. The ideal intralaminar screw trajectory started from the inferolateral edge of the lamina and was between the intralaminar region, pars defect, and defective pars neck and pedicle. Along this trajectory, the skin–lamina distance, intralaminar screw length, isthmic lamina length and width, defective pars neck width, lateral entry distance of the screw to the center of the spinous process, and sagittal and coronal screw application angles were analyzed. ResultsWhen comparing the L4 and L5 parameters, the mean skin-to-lamina distances were 11-9 cm (p=0.000), intralaminar screw lengths 3.5-3.6 cm (p=0.067), isthmic lamina lengths 2-2 cm (p=0.698), mid-lamina widths 1-1 cm (p=0.941), defective pars neck widths 1-1 cm (p=0.674), screw lateral entry distances according to the spinous process 1-1.5 cm (p=0.000), sagittal screw angles 45°-45° (p=0.870), and coronal screw angles 10°-20° (p=0.000) respectively. There were no differences based on age and gender (p<0.05). ConclusionPercutaneous intralaminar rigid screw fixation of a pars defect in spondylolysis provides minimally invasive, low-profile instrumentation. In spondylolysis, a screw length of 3–4 cm and a screw diameter of 4–5 mm may be sufficient for pars fixation with intralaminar screws.

Joint track initiation of resolvable group target

This paper studies the problem of resolvable group target track initiation (RGTI) and proposes a novel method to obtain the discrete association vectors and continuous trajectory parameters of individual targets within the group, which benefits from the fitting representations of target tracks and the utilization of group target motion constraint. Specifically, every target track within the group is modeled as a weighted sum of a same set of time basis functions with different weights, and the aim is to solve multiple pairs of association vectors and trajectory parameters, i.e., unknown weights, according to the measurement equation and group target motion constraint. Next, a joint RGTI framework, which includes track extraction, track purification, trajectory parameter and association vector correction, is proposed to transform the original complex constraint set solving problem into multiple solvable sub-problems. And the convergence of RGTI is ensured through iterative optimization of track purification, trajectory parameter correction and association vector correction. Finally, simulation example demonstrates the superiority of the proposed method compared with existing multi-target track initiation methods.

Workspace trajectory generation with smooth gait transition using CPG-based locomotion control for hexapod robot

—This paper presents a new control methodology for achieving smooth gait transitions for a hexapod robot using Central Pattern Generators (CPGs). The approach involves modifying the Phase Oscillator within the CPG network to enable smooth transitions between different gaits in order to improve the adaptability to changing environmental conditions. The foot trajectory generator is designed based on the CPG output, allowing the possibility of online adjustment of foot trajectory parameters, such as step height and size, as well as the robot's speed and direction. Our simulation demonstrates the effectiveness of the modified oscillator in achieving smoother gait transitions with a transition time falls close to the output period of the CPG oscillators, and experiments on a real hexapod robot validate the feasibility and efficiency of our approach in considering online adjustability of trajectory parameters, confirming the potential of this methodology to enhance the locomotion capabilities of legged robots for navigating complex terrains.

#1635 In hemodialysis patients, COVID-19 vaccination mitigates the variability of clinical and laboratory variables

Abstract Background and Aims Despite prior studies on the clinical impact of COVID-19 and the documented efficacy of COVID-19 vaccinations in hemodialysis (HD) patients, the exact effects of COVID-19 vaccinations on various clinical biomarkers before and after the diagnosis of COVID-19 have not been established. In particular, the longitudinal trajectories of clinical and laboratory parameters remain unknown. We aim to investigate clinical and laboratory variables around the time of COVID-19 diagnosis and how vaccination impacts population trajectories. Method We studied 53,223 HD patients from Fresenius Kidney Care, a large U.S. dialysis organization, who received COVID-19 vaccination between January 1, 2021 and August 2, 2021. Depending on whether or not COVID-19 diagnosis happened after the first dose of vaccination for Johnson &amp; Johnson or after the second dose for all other vaccines, we created two patient cohorts comprising patients infected before (N = 47,443) and after (N = 5780) full vaccination. A nonparametric cubic spline model for flexibility was fitted to the patient data averaged for each day between 60 days before and 60 days after the COVID-19 diagnosis. Clinical parameters include ones that are recorded at each HD treatment (pre-HD temperature, TEMP; pre-HD systolic blood pressure, SBP; pre-HD weight, WT; pre-HD pulse rate, PULSE; intradialytic weight gain, IDWG) and ones that are recorded less frequently (hemoglobin, HGB; white blood cell, WBC; neutrophil-lymphocyte ratio, NLR; platelet count, PLA; albumin, ALB). Results All longitudinal trajectory patterns undergo changes in the days before and after the diagnosis of COVID-19. In both the vaccinated and unvaccinated cohorts, there is an initial increase in TEMP, PULSE, and NLR up to 14 days preceding the diagnosis of COVID-19, followed by a subsequent decrease. Conversely, WT and IDWG exhibit a decline up to 14 days before the diagnosis of COVID-19 and an increase thereafter. ALB maintains a decreasing trend from 14 days prior until 20 days after before increasing again. In the unvaccinated cohort, SBP and WBC start decreasing up to 20 days ahead of diagnosis of COVID-19, whereas the unvaccinated cohort maintains a steady trend, increasing for SBP and decreasing for WBC. The lasting effects of COVID-19 can be found up to 60 days after diagnosis, e.g., WT, PULSE, and HGB. Variations in trend shapes are evident between the vaccinated and unvaccinated cohorts across all variables. Notably, all variables in the vaccinated cohort demonstrate smaller changes around the days of COVID-19 diagnosis. Conclusion We discovered trend changes in multiple variables in the days leading up to COVID-19 diagnosis, corroborating earlier findings. This finding lays the foundation for early detection ahead of regular COVID-19 tests. Prior COVID-19 vaccination mitigates the effect of COVID-19 on several important clinical and laboratory indicators, supporting the need for continued vaccination efforts. Lasting effects from infection are prevalent, extending beyond 60 days after confirmation. Further research is warranted to understand their long-term impact.

Trajectories of actigraphy-derived sleep duration, quality, and variability from childhood to adolescence: downstream effects on mental health.

We examined growth trajectories of four actigraphy-derived sleep parameters (sleep minutes, sleep efficiency, and variability in sleep minutes and efficiency across a week of assessments) across childhood and adolescence and examined individual differences in trajectories according to participants' race/ethnicity and sex. We also assessed the predictive effect of growth trajectories of sleep parameters on growth trajectories of mental health outcomes and moderation by race and sex. Youth (N = 199, 49% female, 65% white, 32% black, 3% biracial) and their parents participated in five waves of data (M ages were 9, 10, 11, 17, and 18 across waves). Participants were from a diverse range of socioeconomic backgrounds. Across participants, sleep minutes, sleep efficiency, and variability in sleep minutes and efficiency demonstrated significant linear change across childhood and adolescence. Whereas sleep duration shortened over time, sleep efficiency improved. Youth exhibited increases in night-to-night variability in sleep minutes and reductions in night-to-night variability in sleep efficiency. Highlighting the importance of individual differences, some race- and sex-related effects emerged. Black youth and male youth experienced steeper declines in their sleep duration across development relative to their respective counterparts. Black youth also demonstrated smaller improvements in sleep efficiency and greater variability in sleep efficiency compared to white youth. Finally, trajectories of sleep efficiency and variability in sleep minutes predicted trajectories of internalizing symptoms and externalizing behaviors. Findings showed significant changes in developmental trajectories of four sleep parameters across childhood and adolescence. We discuss the empirical and translational implications of the findings.

Accurate Range Modeling for High-Resolution Spaceborne Synthetic Aperture Radar.

Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM's concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.

New Tsallis holographic dark energy with Granda–Oliveros as IR-cutoff

In the current study, a theoretical model for non-interacting new Tsallis holographic dark energy is constructed using the Granda–Oliveros as the IR cutoff with specified scale factor [Formula: see text]. The time-dependent deceleration parameter, with appropriate assumptions, yields this scale factor. The features of the deceleration parameter, equation of state parameter, density parameter, and jerk parameter are then investigated for this model. According to our findings, the cosmos has a normal thermal history, dark matter and dark energy eras occurring one after the other until dark energy eventually takes over entirely in the far future. Additionally, the evolution of the potential and pressure to indicate the universe’s accelerated expansion by using our model are studied. We investigate the evolution trajectory of statefinder parameters, which is consistent with ΛCDM model.

Application coherent processing of two frequency-spaced radar signals in target monitoring under conditions of relayed interference

The use of ground-based radar stations for space surveillance makes it possible to solve problem of detecting new and tracing previously known targets around the clock. The quality of operation ground-based radar station for space surveillance can be significantly reduced when solving problems of radar surveillance in complex phono-target and signal-interference environment. To improve effectiveness of radar surveillance it is advisable to carry out joint use of radar station for space surveillance, in particular as part of multi-position complex with possibility of joint coherent radar signal processing, including signals separated by frequency. It is necessary to develop models for evaluating effectiveness joint use of deferent-band radar stations for space surveillance when solving problems of radar surveillance in complex phono-target and signal-interference environment based on implementation of coherent processing two radar signals. The purpose of study is increase potential accuracy of radar measurements target trajectory parameters in conditions of relayed interference based on implementation of coherent processing two radar signals at ground radar systems for space surveillance. A model of target monitoring has been developed in system of two different-range radar stations for surveying space according to probabilistic indicator and dependences on linkage target trajectories were obtained based on implementation of coherent processing two radar signals in various conditions of signal-interference environment. The result of study can be used in evaluating effectiveness joint use of several radar stations for surveying space as part of multi-position radar systems when observing targets in conditions of noise and relayed interference.

Reviews and Responses for Generation of Parametric Climb Trajectories considering Operational Inputs for Aircraft Engine Thrust Extraction

See detailed reviews and responses in the PDF file. DOI for the original paper: https://doi.org/10.59490/joas.2023.7216

Digital sleep clinic: assessing efficacy of continuous positive airway pressure through sleep staging via connected devices: a study protocol

BackgroundObstructive sleep apnea (OSA) is a multisystemic chronic disease with disabling symptoms, cardiometabolic comorbidities and reduction in physical activity. Continuous positive airway pressure (CPAP) is the standard treatment for OSA. Only a few studies have characterized trajectories of sleep parameters upon initiation of CPAP and these are limited to one or two nights of polysomnographic recording in a sleep laboratory. This is due to the cost of carrying out these studies and poor tolerance by patients of multiple nights of polysomnographic recordings. No study has characterized sleep over multiple nights before and after CPAP initiation, assessing the multidimensional efficacy of CPAP on patient reported outcomes, objective and subjective sleep quality, oximetry, glucose control and physical activity.New digital technologies enable overnight sleep studies over several nights in the patient’s home, with a reliability of sleep characterization equivalent to polysomnographic recording.The primary aim of this study is to investigate objective slow wave sleep (SWS or N3) quality before CPAP and during the first month of the treatment.Secondary objectives are to assess changes in the following parameters before CPAP and during the first month of the treatment: other objective sleep parameters and sleep stages evolution (W, N1, N2 and REM), nocturnal oxygen desaturations, 24-h blood glucose profile, daily physical activity (the daily steps count), and patient reported outcomes.MethodsSeventy patients prescribed CPAP for OSA will be recruited at Grenoble Alpes University Hospital (France) and monitored for 5 weeks using validated innovative wearable connected devices (the Dreem 3 headband, a pedometer, an oximeter, and a continuous glucose sensor) enabling them to track their own sleep and physiological parameters at home before and after CPAP initiation.DiscussionBy pooling data from the CPAP telemonitoring and other connected devices we should be able to follow the multidimensional trajectories of patients after the initiation of CPAP. This will enable us to determine whether objective changes in sleep parameters in the first few weeks of CPAP treatment are associated with improvements in daytime sleepiness, quality of life, treatment adherence, glucose control and physical activity. The data will provide integrated markers of treatment efficacy and will allow adapted personalized management of OSA in the short and long-term.Trial registrationClinicaltrials (NCT05197855).

Reentry trajectory optimization of hypersonic glide vehicle based on improved particle swarm algorithm

The reentry process of hypersonic glide vehicle presents a host of intricate constraint issues. A method for optimizing the reentry trajectory of hypersonic glide vehicle is presented to achieve the shortest possible reentry time. The approach utilizes the improved particle swarm optimization (IPSO) algorithm. Firstly, population initialization is performed using the quasi-oppositional differential evolution (QODE) strategy to promote diversity within the population. Then an adaptive adjustment algorithm is designed for the inertia weight coefficient and learning factor to achieve a balance between global and local search capabilities. Finally, utilizing the IPSO algorithm for optimizing the flight parameters of the reentry trajectory, the reentry time is reduced from 338 seconds to 335 seconds. The simulations results indicate that the IPSO algorithm outperforms both the standard PSO algorithm and genetic algorithm (GA) in terms of optimization performance index.

Towards a Unified Approach for Continuously-Variable Impedance Control of Powered Prosthetic Legs over Walking Speeds and Inclines.

Research in powered prosthesis control has explored the use of impedance-based control algorithms due to their biomimetic capabilities and intuitive structure. Modern impedance controllers feature parameters that smoothly vary over gait phase and task according to a data-driven model. However, these recent efforts only use continuous impedance control during stance and instead utilize discrete transition logic to switch to kinematic control during swing, necessitating two separate models for the different parts of the stride. In contrast, this paper presents a controller that uses smooth impedance parameter trajectories throughout the gait, unifying the stance and swing periods under a single, continuous model. Furthermore, this paper proposes a basis model to represent intertask relationships in the impedance parameters-a strategy that has previously been shown to improve model accuracy over classic linear interpolation methods. In the proposed controller, a weighted sum of Fourier series is used to model the impedance parameters of each joint as continuous functions of gait cycle progression and task. Fourier series coefficients are determined via convex optimization such that the controller best reproduces the joint torques and kinematics in a reference able-bodied dataset. Experiments with a powered knee-ankle prosthesis show that this simpler, unified model produces competitive results when compared to a more complex hybrid impedance-kinematic model over varying walking speeds and inclines.

The Influence of Radiographic Parameter on the S2 Alar-Iliac Screw Virtual Trajectory in Degenerative Lumbar Scoliosis Patients: A Computed Tomography Study.

S2 alar-iliac (S2AI) screw had been widely used in the pelvic fusion for degenerative lumbar scoliosis (DLS) patients. However, whether S2AI screw trajectory was influenced by sagittal profile in DLS patients had not been comprehensively investigated. The objective of this study was to evaluate the associations between the optimal S2 alar-iliac (S2AI) screw trajectory and sagittal spinopelvic parameters in DLS patients. Computed tomography (CT) scans of pelvis were performed in 47 DLS patients for three-dimensional reconstruction of S2AI screw trajectory from September 2019 to November 2021. Five S2AI screw trajectory parameters were measured in CT reconstruction images, including: 1) angle in the transverse plane (Tsv angle); 2) angle in the sagittal plane (Sag angle); 3) maximal screw length; 4) screw width; and 5) skin distance. The lumbar Cobb angle, lumbar apical vertebral translation (AVT); global kyphosis (GK); thoracic kyphosis (TK); lumbar lordosis (LL); sagittal vertical axis (SVA); sacral slope (SS); pelvic tilt (PT); and pelvic incidence (PI) were measured in standing X-ray films of the whole spine and pelvis. Both Tsv angle and Sag angle had significant positive associations with SS (p < 0.05) but negative associations with both PT (p < 0.05) and LL (p < 0.05) in all cases. Patients with SS less than 15° had both smaller Tsv angle and Sag angle than those with SS equal to or more than 15° (p < 0.05). The decreased LL would lead to the backward rotation of the pelvis, resulting in a more cephalic and less divergent trajectory of S2AI screw in DLS patients. For DLS patients with lumbar kyphosis, spine surgeons should avoid both excessive Tsv and Sag angles for S2AI screw insertion, especially when using free-hand technique.

A fully actuated system approach: Desired compensation adaptive robust control for uncertain nonlinear systems

A desired compensation adaptive robust control (DCARC) framework is presented for two types of fully actuated systems (FASs) subject to both parametric and nonlinear uncertainties based on the Lyapunov theory. The designed controller consists of three parts: (i) a fundamental linear state error feedback term; (ii) an adaptive feedforward compensation term; (iii) a robust compensation term. Different from the existing FAS approaches, the adaptive compensation in the proposed controller relies on the noise-free desired trajectory and online parameter estimate only. A better overall tracking performance with an accelerated transient response is expected, arising from significantly reducing interaction between the robustness part and the adaptation part. Through theoretical analysis, the proposed controller ensures that the estimation error of the unknown parameter vector and the tracking error finally converge to a bounded ellipsoid. The comparative simulation of a permanent magnet (PM) stepper motor demonstrates the effectiveness of the presented approach.

Optimisation of design parameters for a novel two-piston ionic compressor applied in hydrogen storage

The ionic compressor is an advanced and prospective compression technology for hydrogen storage. However, a complex wave phenomenon was observed inside the compression chamber due to the fluid flow vortex. This complex gas-fluid interaction can be intervened by a new mechanical design of the motion piston. In this paper, the thermodynamic performance of a novel homocentric two-piston ionic compressor was carried out by mathematical modelling of one compression cycle. The optimisation of the design parameters of the compressor proposed was conducted by the Taguchi method. This study found that the piston diameter ratio was the dominating factor accounting for more than 80 % of the contribution to the mass delivered, power consumption and specific energy consumption. The optimal design parameters were obtained as 0.7 for the piston diameter ratio, 0.5 for the stroke diameter ratio of Piston A and 0.1 for the trajectory parameter. Under the optimal design parameters, the specific energy consumption was obtained as 1563.38 kJ/kg.