Natural Trajectories Research Articles

Natural histories of metabolite BMI phenotypes and their impacts on cardiovascular disease risk over a decade-long follow-up

PurposeThe prognostic significance of obesity phenotypes is under debate, and few studies have characterized their transition trajectories. This study examined the natural courses of different phenotypes and their associations with cardiovascular disease risks. MethodsA total of 1827 participants were followed for 14 years and re-evaluated every 4–5 years. Four metabolite BMI phenotypes were determined according to overweight or obesity (BMI ≥ 24 kg/m2) and metabolic health status (≤1 Adult Treatment Panel III criteria, excluding waist circumference). Cardiovascular risks were assessed by evaluating baPWV and hypertension, diabetes and chronic kidney disease (CKD) development. ResultsMore than 20% of participants changed their initial phenotypes within 5 years. One-third of healthy overweight/obese (MHO) individuals became unhealthy, and only 10.6% regressed to a healthy normal weight (MHN) at the end of follow-up. Compared with MHN participants, MHO participants had higher odds of increased baPWV (OR: 1.18, 95% CI, 0.42–3.33) and increased risks of incident hypertension (HR: 1.87, 95% CI, 1.18–2.98) and diabetes (HR: 2.61, 95% CI, 1.35–5.03). Metabolic deterioration during follow-up resulted in an increased risk of baPWV and clinical diseases. ConclusionsThe natural trajectory of metabolite BMI phenotypes is time-varying, and interventions for both healthy and unhealthy overweight/obese individuals should be widely recommended.

Joint Modeling of Longitudinal Markers and Time-to-Event Outcomes: An Application and Tutorial in Patients After Surgical Repair of Transposition of the Great Arteries.

Most patients with congenital heart disease survive into adulthood; however, residual abnormalities remain and management of the patients is life-long and personalized. Patients with surgical repair of transposition of the great arteries, for example, face the risk to develop neoaortic valve regurgitation. Cardiologists update the prognosis of the patient intuitively with updated information of the cardiovascular status of the patient, for instance from echocardiographic imaging. Usually a time-dependent version of the Cox model is used to analyze repeated measurements with a time-to-event outcome. New statistical methods have been developed with multiple advantages, of which the most prominent one being the joint model for longitudinal and time-to-event outcome. In this tutorial, the joint modeling framework is introduced and applied to patients with transposition of the great arteries after surgery with a long-term follow-up, where repeated echocardiographic values of the neoaortic root are evaluated against the risk of neoaortic valve regurgitation. The data are analyzed with the time-dependent Cox model as benchmark method, and the results are compared with a joint model, leading to different conclusions. The flexibility of the joint model is shown by adding the growth rate of the neoaortic root to the model and adding repeated values of body surface area to obtain a multimarker model. Lastly, it is demonstrated how the joint model can be used to obtain personalized dynamic predictions of the event. The joint model for longitudinal and time-to-event data is an attractive method to analyze data in follow-up studies with repeated measurements. Benefits of the method include using the estimated natural trajectory of the longitudinal outcome, great flexibility through multiple extensions, and dynamic individualized predictions.

Geometric perspectives on fundamental solutions in the linearized satellite relative motion problem

Understanding natural relative motion trajectories is critical to enable fuel-efficient multi-satellite missions operating in complex environments. This paper studies the problem of computing and efficiently parameterizing satellite relative motion solutions for linearization about a closed chief orbit. By identifying the analytic relationship between Lyapunov–Floquet transformations of the relative motion dynamics in different coordinate systems, new means are provided for rapid computation and exploration of the types of close-proximity natural relative motion available in various applications. The approach is demonstrated for the Keplerian relative motion problem with general eccentricities in multiple coordinate representations. The Keplerian assumption enables an analytic approach, leads to new geometric insights, and allows for comparison to prior linearized relative motion solutions.

Computational Psychiatry Needs Time and Context.

Why has computational psychiatry yet to influence routine clinical practice? One reason may be that it has neglected context and temporal dynamics in the models of certain mental health problems. We develop three heuristics for estimating whether time and context are important to a mental health problem: Is it characterized by a core neurobiological mechanism? Does it follow a straightforward natural trajectory? And is intentional mental content peripheral to the problem? For many problems the answers are no, suggesting that modeling time and context is critical. We review computational psychiatry advances toward this end, including modeling state variation, using domain-specific stimuli, and interpreting differences in context. We discuss complementary network and complex systems approaches. Novel methods and unification with adjacent fields may inspire a new generation of computational psychiatry.

Neuroprotective effects of exercise on the aging human neuromuscular system.

Human biological aging from maturity to senescence is associated with a gradual loss of muscle mass and neuromuscular function. It is not until very old age (>80years) however, that these changes often manifest into functional impairments. A driving factor underlying the age-related loss of muscle mass and function is the reduction in the number and quality of motor units (MUs). A MU consists of a single motoneuron, located either in the spinal cord or the brain stem, and all of the muscle fibres it innervates via its peripheral axon. Throughout the adult lifespan, MUs are slowly, but progressively lost. The compensatory process of collateral reinnervation attempts to recapture orphaned muscle fibres following the death of a motoneuron. Whereas this process helps mitigate loss of muscle mass during the latter decades of adult aging, the neuromuscular system has fewer and larger MUs, which have lower quality connections between the axon terminal and innervated muscle fibres. Whether this process of MU death and degradation can be attenuated with habitual physical activity has been a challenging question of great interest. This review focuses on age-related alterations of the human neuromuscular system, with an emphasis on the MU, and presents findings on the potential protective effects of lifelong physical activity. Although there is some discrepancy across studies of masters athletes, if one considers all experimental limitations as well as the available literature in animals, there is compelling evidence of a protective effect of chronic physical training on human MUs. Our tenet is that high-levels of physical activity can mitigate the natural trajectory of loss of quantity and quality of MUs in old age.

Greater baseline connectivity of the salience and negative affect circuits are associated with natural improvements in anxiety over time in untreated participants

BackgroundThere is limited research examining the natural trajectories of depression and anxiety, how these trajectories relate to baseline neural circuit function, and how symptom trajectory-circuit relationships are impacted by engagement in lifestyle activities including exercise, hobbies, and social interactions. To address these gaps, we assessed these relations over three months in untreated participants. Methods262 adults (59.5% female, mean age 35) with symptoms of anxiety and depression, untreated with pharmacotherapy or behavioral therapy, completed the DASS-42, WHOQOL, and custom surveys at baseline and follow-up to assess symptoms, psychosocial function, and lifestyle activity engagement. At baseline, participants underwent fMRI under task-free and task-evoked conditions. We quantified six circuits implicated in these symptoms: default mode, salience, negative and positive affect, attention, and cognitive control. ResultsFrom baseline to 3 months, some participants demonstrated a natural improvement in anxiety (24%) and depression (26%) symptoms. Greater baseline salience circuit connectivity (pFDR=0.045), specifically between the left and right insula (pFDR=0.045), and greater negative affect circuit connectivity elicited by sad faces (pFDR=0.030) were associated with anxiety symptom improvement. While engagement in lifestyle activities were not associated with anxiety improvements, engagement in hobbies moderated the association between negative affect circuit connectivity and anxiety symptom improvement (p = 0.048). LimitationsThe observational design limits causal inference. ConclusionsOur findings highlight the role of the salience and negative affect circuits as potential circuit markers of natural anxiety symptom improvements over time. Future studies that identify biomarkers associated with symptom improvements are critical for the development of personalized treatment targets.

States Transitions Inference of Postpartum Depression Based on Multi-State Markov Model.

Background: Postpartum depression (PPD) has been recognized as a severe public health problem worldwide due to its high incidence and the detrimental consequences not only for the mother but for the infant and the family. However, the pattern of natural transition trajectories of PPD has rarely been explored. Methods: In this research, a quantitative longitudinal study was conducted to explore the PPD progression process, providing information on the transition probability, hazard ratio, and the mean sojourn time in the three postnatal mental states, namely normal state, mild PPD, and severe PPD. The multi-state Markov model was built based on 912 depression status assessments in 304 Chinese primiparous women over multiple time points of six weeks postpartum, three months postpartum, and six months postpartum. Results: Among the 608 PPD status transitions from one visit to the next visit, 6.2% (38/608) showed deterioration of mental status from the level at the previous visit; while 40.0% (243/608) showed improvement at the next visit. A subject in normal state who does transition then has a probability of 49.8% of worsening to mild PPD, and 50.2% to severe PPD. A subject with mild PPD who does transition has a 20.0% chance of worsening to severe PPD. A subject with severe PPD is more likely to improve to mild PPD than developing to the normal state. On average, the sojourn time in the normal state, mild PPD, and severe PPD was 64.12, 6.29, and 9.37 weeks, respectively. Women in normal state had 6.0%, 8.5%, 8.7%, and 8.8% chances of progress to severe PPD within three months, nine months, one year, and three years, respectively. Increased all kinds of supports were associated with decreased risk of deterioration from normal state to severe PPD (hazard ratio, HR: 0.42–0.65); and increased informational supports, evaluation of support, and maternal age were associated with alleviation from severe PPD to normal state (HR: 1.46–2.27). Conclusions: The PPD state transition probabilities caused more attention and awareness about the regular PPD screening for postnatal women and the timely intervention for women with mild or severe PPD. The preventive actions on PPD should be conducted at the early stages, and three yearly; at least one yearly screening is strongly recommended. Emotional support, material support, informational support, and evaluation of support had significant positive associations with the prevention of PPD progression transitions. The derived transition probabilities and sojourn time can serve as an importance reference for health professionals to make proactive plans and target interventions for PPD.

Designing a Cross Trainer Using an Artificial Neural Network

Cross-trainers are machines that use link mechanisms to mimic walking or running as part of workout sessions or rehabilitation systems. The simplest cross-trainer incorporates a crank-rocker or a crank-slider mechanism and provides a nearly elliptical path for foot motion. However, the natural human foot trajectories are far from being elliptical. Therefore, existing designs require modifications. Artificial neural networks are used for this purpose. Instead of trying to match the foot trajectory directly, here we tried to match different geometric properties of the area enclosed by the foot trajectory. Neural networks are trained to predict these geometric properties as outputs with the dimensions of the linkage as inputs. With the help of the same trained network, the “best-fit dimensions” were predicted for the desired trajectories.

Design and control of a sit-to-stand assistive device based on analysis of kinematics and dynamics

Sit-to-stand is a common activity in daily life. It is difficult for the elderly and patients with lower limb disorders to complete this motion due to limb pain, muscle weakness, partial loss of motor control function, and physical defects in joints. An STS assistive device is a piece of automated medical equipment that can facilitate rehabilitation training for patients with lower limb disorders and improve their lower limb function. In this paper, we introduce a 3-DOF series type STS assistive device. First, we selected 26 healthy adults to carry out an STS transfer experiment, and we obtained the trajectory and velocity of each joint and the law of plantar pressure during STS motion. Second, based on the above kinematics and dynamics law, a 3-DOF series mechanism was designed. Through forward and inverse kinematics analysis, the relationship between the end-effector and the linear actuator was established. The trajectory planning of the end-effector was carried out according to the natural STS transfer trajectory, and the law of the linear actuator was obtained. The trajectory planning was verified by ADAMS. Finally, the Arduino controller was used to build the control system of the STS assistive device, and the prototype experiment was carried out.

Assessing multi‐temporal river‐floodplain dynamics as baseline for process‐oriented restoration in a large river: the Duero River, Spain

The time‐based perspective of river‐floodplain processes plays a key role in understanding its evolution until its present situation and in guiding process‐based river restoration. However, despite the wide range of approaches to eco‐hydromorphological characterization, the analysis of fluvial dynamics and their drivers under a temporal perspective requires more investigation. For the present study, a historical analysis of river‐floodplain dynamics has been undertaken in a study section of the Duero River upstream of Zamora (Spain), within the framework of the DRAINAGE project for the integral management of flood risk. Aerial imagery for the period 1945–2017 was used to create habitat maps that were subsequently intersected to identify trajectories of habitat change (anthropization, changeless, progression, and regression). In addition, a Natural Trajectory Index (NTI) and an Anthropization Ratio (AR) were proposed as a way to assess the balance of natural trajectories (progression vs. regression) and the weight of anthropization versus the sum of natural trajectories, respectively. Results show a system with a high degree of stability and anthropization, and a current imbalance of natural trajectories with a predominance of progression in the ecological succession. Rejuvenation processes have to be reactivated through nature‐based solutions, allowing for more sustainable water management practices. This perspective aims at promoting a more resilient system. The diachronic analysis presented is widely exportable to other river‐floodplain systems as a basis for process‐based restoration practice.

Impact of sex and APOE ε4 on age-related cerebral perfusion trajectories in cognitively asymptomatic middle-aged and older adults: A longitudinal study

Cerebral hypoperfusion is thought to contribute to cognitive decline in Alzheimer’s disease, but the natural trajectory of cerebral perfusion in cognitively healthy adults has not been well-studied. This longitudinal study is consisted of 950 participants (40—89 years), who were cognitively unimpaired at their first visit. We investigated the age-related changes in cerebral perfusion, and their associations with APOE-genotype, biological sex, and cardiometabolic measurements. During the follow-up period (range 0.13—8.24 years), increasing age was significantly associated with decreasing cerebral perfusion, in total gray-matter (β=−1.43), hippocampus (−1.25), superior frontal gyrus (−1.70), middle frontal gyrus (−1.99), posterior cingulate (−2.46), and precuneus (−2.14), with all P-values < 0.01. Compared with male-ɛ4 carriers, female-ɛ4 carriers showed a faster decline in global and regional cerebral perfusion with increasing age, whereas the age-related decline in cerebral perfusion was similar between male- and female-ɛ4 non-carriers. Worse cardiometabolic profile (i.e., increased blood pressure, body mass index, total cholesterol, and blood glucose) was associated with lower cerebral perfusion at all the visits. When time-varying cardiometabolic measurements were adjusted in the model, the synergistic effect of sex and APOE-ɛ4 on age-related cerebral perfusion-trajectories became largely attenuated. Our findings demonstrate that APOE-genotype and sex interactively impact cerebral perfusion-trajectories in mid- to late-life. This effect may be partially explained by cardiometabolic alterations.

Using Monte Carlo to Simulate Complex Polymer Systems: Recent Progress and Outlook

Metropolis Monte Carlo has been employed with remarkable success over the years to simulate the dense phases of polymer systems. Owing, in particular, to the freedom it provides to accelerate sampling in phase space through the clever design and proper implementation of even unphysical moves that take the system completely away from its natural trajectory, and despite that it cannot provide any direct information about dynamics, it has turned to a powerful simulation tool today, often viewed as an excellent alternative to the other, most popular method of Molecular Dynamics. In the last years, Monte Carlo has advanced considerably thanks to the design of new moves or to the efficient implementation of existing ones to considerably more complex systems than those for which these were originally proposed. In this short review, we highlight recent progress in the field (with a clear emphasis in the last 10 years or so) by presenting examples from applications of the method to several systems in Soft Matter, such as polymer nanocomposites, soft nanostructured materials, confined polymers, polymer rings and knots, hydrogels and networks, crystalline polymers, and many others. We highlight, in particular, extensions of the method to non-equilibrium systems (e.g., polymers under steady shear flow) guided by non-equilibrium thermodynamics and emphasize the importance of hybrid modeling schemes (e.g., coupled Monte Carlo simulations with field theoretic calculations). We also include a short section discussing some key remaining challenges plus interesting future opportunities.

Terraces of the Ohře River in Žatec Area, Czech Republic: When Models of Holocene Fluvial Development Are Not Sufficient

The development of the Ohře River near Žatec between the Late Glacial Maximum (LGM) and present time was studied to obtain its natural trajectory and thus to understand the role of human impact on floodplain development. The study was based on geomorphic research, sampling and dating fluvial sediments by optically stimulated luminescence (OSL) and anthropogenic contamination by Sn since 16th century. During the LGM and the Pleistocene/Holocene transition (P/H), the river valley was shaped by large, incising meanders creating the entire valley floor. The Holocene river, due to decreased channel forming discharges, only slowly continued the LGM and P/H trajectory by cut-offs of the large palaeomeander necks and channel belt narrowing and incision. The last Holocene incision step was likely triggered by hydrological extremes of the Little Ice Age. The LGM and P/H Ohře River consequently changed from meandering to low sinuous, incised in the valley floor; this incision was completed by river engineering in the 20th century. The Ohře River development can thus be rationalised neither by traditional terrace-step formation model nor by model of the Anthropogenic aggradation.

COVID-19\u2019s natural course among ambulatory monitored outpatients

Research objective was to detail COVID-19’s natural trajectory in relation to the Czech population’s viral load. Our prospective detailed daily questionnaire-based telemonitoring study evaluated COVID-19’s impact among 105 outpatients. In accordance with government quarantine requirements, outpatients were divided into a cohort with two negative tests at the end of the disease (40 patients) and a cohort with a new algorithm (65 patients) following a 14-day quarantine. Median follow-up differed significantly between the 2 groups (23 days vs. 16 days). Only 6% of patients were asymptomatic during the entire telemonitoring period. Another 13% of patients were diagnosed asymptomatic, as suspected contacts, yet later developed symptoms, while the remaining 81% were diagnosed as symptomatic on average 6 days following symptom onset. Telemonitoring enabled precise symptom status chronicling. The most frequently reported complaints were fevers, respiratory issues, and anosmia. Six patients were eventually hospitalized for complications detected early after routine telemonitoring. During the extended follow-up (median 181 days), anosmia persisted in 26% of patients. 79% of patients in the new quarantine algorithm cohort reported no symptoms on day 11 compared to just 56% of patients in the two negative test cohort upon first testing negative (median–19 days). The highest viral load occurred within 0–2 days of initial symptom onset. Both the PCR viral load and two consecutive PCR negative sample realizations indicated high interindividual variability with a surprisingly fluctuating pattern among 43% of patients. No definitive COVID-19 symptoms or set of symptoms excepting anosmia (59%) and/or ageusia (47%) were identified. No preexisting medical conditions specifically foreshadowed disease trajectory in a given patient. Without a PCR negativity requirement for quarantine cessation, patients could exhibit fewer symptoms. Our study therefore highlights the urgent need for routine ambulatory patient telemedicine monitoring, early complication detection, intensive mass education connecting disease demeanor with subsequent swift diagnostics, and, notably, the need to reevaluate and modify quarantine regulations for better control of SARS-CoV-2 proliferation.

Natural history, trajectory, and management of mechanically ventilated COVID-19 patients in the United Kingdom

PurposeThe trajectory of mechanically ventilated patients with coronavirus disease 2019 (COVID-19) is essential for clinical decisions, yet the focus so far has been on admission characteristics without consideration of the dynamic course of the disease in the context of applied therapeutic interventions.MethodsWe included adult patients undergoing invasive mechanical ventilation (IMV) within 48 h of intensive care unit (ICU) admission with complete clinical data until ICU death or discharge. We examined the importance of factors associated with disease progression over the first week, implementation and responsiveness to interventions used in acute respiratory distress syndrome (ARDS), and ICU outcome. We used machine learning (ML) and Explainable Artificial Intelligence (XAI) methods to characterise the evolution of clinical parameters and our ICU data visualisation tool is available as a web-based widget (https://www.CovidUK.ICU).ResultsData for 633 adults with COVID-19 who underwent IMV between 01 March 2020 and 31 August 2020 were analysed. Overall mortality was 43.3% and highest with non-resolution of hypoxaemia [60.4% vs17.6%; P < 0.001; median PaO2/FiO2 on the day of death was 12.3(8.9–18.4) kPa] and non-response to proning (69.5% vs.31.1%; P < 0.001). Two ML models using weeklong data demonstrated an increased predictive accuracy for mortality compared to admission data (74.5% and 76.3% vs 60%, respectively). XAI models highlighted the increasing importance, over the first week, of PaO2/FiO2 in predicting mortality. Prone positioning improved oxygenation only in 45% of patients. A higher peak pressure (OR 1.42[1.06–1.91]; P < 0.05), raised respiratory component (OR 1.71[ 1.17–2.5]; P < 0.01) and cardiovascular component (OR 1.36 [1.04–1.75]; P < 0.05) of the sequential organ failure assessment (SOFA) score and raised lactate (OR 1.33 [0.99–1.79]; P = 0.057) immediately prior to application of prone positioning were associated with lack of oxygenation response. Prone positioning was not applied to 76% of patients with moderate hypoxemia and 45% of those with severe hypoxemia and patients who died without receiving proning interventions had more missed opportunities for prone intervention [7 (3–15.5) versus 2 (0–6); P < 0.001]. Despite the severity of gas exchange deficit, most patients received lung-protective ventilation with tidal volumes less than 8 mL/kg and plateau pressures less than 30cmH2O. This was despite systematic errors in measurement of height and derived ideal body weight.ConclusionsRefractory hypoxaemia remains a major association with mortality, yet evidence based ARDS interventions, in particular prone positioning, were not implemented and had delayed application with an associated reduced responsiveness. Real-time service evaluation techniques offer opportunities to assess the delivery of care and improve protocolised implementation of evidence-based ARDS interventions, which might be associated with improvements in survival.

Default Mode Network Moderates the Relationship Between Lifestyle Changes and Natural Improvements in Clinical Symptoms Over Time in Untreated Participants

We lack knowledge regarding the natural trajectory of depression and anxiety, how this trajectory relates to neural circuit function, and how symptom trajectory-neural circuit relationships are impacted by engagement in lifestyle factors including exercise, hobbies, and social interactions. In a 3-month longitudinal design, we assessed these associations.

Toward immersive spacecraft trajectory design: Mapping user drawings to natural periodic orbits

This paper presents an immersive spacecraft trajectory design application within the cislunar space domain. The long-term goal of this application is to enable users to design spacecraft trajectories by drawing curves while immersed in a three-dimensional (3D) virtual reality replica of the Earth–Moon system. In this framework, visual memory or understanding of orbit dynamics may be directly linked to the creation of trajectory baselines for preliminary mission design with 3D drawings. An orthogonal-collocation-based optimizer maps user-drawn curves to approximate orbit solutions that are feasible under the natural dynamics of the Earth–Moon system. The natural dynamics of the Earth–Moon system are modeled using a circular-restricted three-body problem (CR3BP) model. Two experiments are conducted to initially assess the feasibility of the proposed trajectory design framework and to determine the robustness of the optimizer in the presence of user-induced distortions within the 3D user drawings. The first experiment establishes that it may be feasible to map a user-drawn curve to a close natural CR3BP trajectory. In fact, during the experiment, sample user-drawn curves were mapped to natural CR3BP orbits with a seventy-five percent success rate. The second experiment establishes baseline statistics for user-induced distortions over one hundred and three user-drawn traces of a sample L2 halo reference orbit. Based on these statistics, a final analysis provides a quantitative measure in verification of the robustness of the optimizer when user-induced distortions are present. Hence the proposed immersive computing framework is deemed suitable for further development for trajectory design in cislunar space.

Recovery of the Decline in Activities of Daily Living After Hospitalization Through an Individualized Exercise Program: Secondary Analysis of a Randomized Clinical Trial.

During the period of hospitalization, patients can develop functional decline. The main aim of our study was to assess the natural trajectory of each activity of daily living (ADL) and to assess how in-hospital exercise could influence short-term trajectory of ADLs. Acutely hospitalized patients (n = 297, 56.5% women) were randomly assigned to the intervention or control (usual care) group within the first 48 hours of admission. An exercise training program was prescribed in 2 daily sessions (morning and evening) of 20 minutes duration during 5-7 consecutive days for the intervention group. The primary endpoint was the change in every ADL (assessed with the Barthel Index) from 2 weeks before admission to hospital discharge. Acute hospitalization per se led to significant in-patient's functional ability impairment in ADLs during hospitalization, whereas the exercise intervention reversed this trend (3.7 points; 95% CI: 0.5-6.8 points). After analyzing the trajectory of each one of the ADLs, patients in the control group significantly worsened all activities, but with a different degree of loss. For the between-group analysis, significant differences were obtained in many ADLs including bathing, dressing, grooming, bladder control, toilet use, transfers, mobility, and climbing stairs (p < .05). The control group had the greatest impairment in all domains analyzed (ie, feeding, bathing, dressing, grooming, bowel control, bladder control, toilet use, transfers, mobility, and climbing stairs; p < .05). An individualized multicomponent exercise training program in older adults is effective to reverse the loss of specific ADLs that frequently occurs during hospitalization. Each patient profile should receive an individualized prescription of exercise during hospitalizations. NCT02300896.

Gait Optimization Method for Humanoid Robots Based on Parallel Comprehensive Learning Particle Swarm Optimizer Algorithm.

To improve the fast and stable walking ability of a humanoid robot, this paper proposes a gait optimization method based on a parallel comprehensive learning particle swarm optimizer (PCLPSO). Firstly, the key parameters affecting the walking gait of the humanoid robot are selected based on the natural zero-moment point trajectory planning method. Secondly, by changing the slave group structure of the PCLPSO algorithm, the gait training task is decomposed, and a parallel distributed multi-robot gait training environment based on RoboCup3D is built to automatically optimize the speed and stability of bipedal robot walking. Finally, a layered learning approach is used to optimize the turning ability of the humanoid robot. The experimental results show that the PCLPSO algorithm achieves a quickly optimal solution, and the humanoid robot optimized possesses a fast and steady gait and flexible steering ability.

(Un)Making the international student a settler of colour: a decolonising autoethnography

ABSTRACT This paper reflects on my experience as a non-white international student at a top-ranked sport/kinesiology faculty in Canada, particularly the (un)learning of my complicity within settler colonialism. Following a decolonising autoethnographic approach, I juxtapose my own desired pathway of pursuing international study with shapeshifting forms of settler colonialism. The stories reveal that Canada’s marketing of higher education, settler geography, the whiteness of university, and the spectacle of ‘reconciliation’ can operate in concert to prevent international students from developing critical understandings of the violent conditions of their stay on occupied Indigenous land. While elusive opportunities of (un)learning and resisting do exist, I argue that the seemingly natural trajectory of (re)producing settlers of colour warrants critical intervention.