Gait stability,variability and complexity on inclined surfaces

This study evaluated the gait stability, variability, and complexity of healthy young adults on inclined surfaces. A total of 49 individuals walked on a treadmill at their preferred speed for 4 min at inclinations of 6%, 8%, and 10% in upward (UP) and downward (DOWN) conditions, and in horizontal (0%) condition. Gait variability was assessed using average standard deviation trunk acceleration between strides (VAR), gait stability was assessed using margin of stability (MoS) and maximum Lyapunov exponent (λs), and gait complexity was assessed using sample entropy (SEn). Trunk variability (VAR) increased in the medial-lateral (ML), anterior-posterior, and vertical directions for all inclined conditions. The SEn values indicated that movement complexity decreased almost linearly from DOWN to UP conditions, reflecting changes in gait pattern with longer and slower steps as inclination increased. The DOWN conditions were associated with the highest variability and lowest stability in the MoS ML, but not in λs. Stability was lower in UP conditions, which exhibited the largest λs values. The overall results support the hypothesis that inclined surfaces decrease gait stability and alter gait variability, particularly in UP conditions.     

Experimentally induced neck pain causes a decrease in thoracic but not lumbar spine stability

Maintenance of spine stability is considered to be a critical component of spine health. Ross et al. (2015) used a topical capsaicin/heat pain sensitization model to experimentally induce lower back pain, and demonstrated that the experimental pain experience caused a decrease in the muscular contribution to lumbar spine rotational stiffness (related to mechanical stability) as well as lower back local dynamic stability (LDS). It has yet to be established if pain elsewhere in the body, specifically in other regions of the spine, can similarly affect the stability of the lower back. The purpose of this investigation was therefore to quantify thoracic and lumbar spine LDS as well as the muscular contribution to lumbar spine rotational stiffness after an experimental neck pain protocol. Results demonstrated that LDS of the thoracic spine decreased in response to the capsaicin/heat induced neck pain. Limited adaptation was required at the lumbar spine as demonstrated by the lack of statistically significant changes in lower back LDS or rotational stiffness.     

Study of a tri-trophic prey-dependent food chain model of interacting populations

The current paper accounts for the influence of intra-specific competition among predators in a prey dependent tri-trophic food chain model of interacting populations. We offer a detailed mathematical analysis of the proposed food chain model to illustrate some of the significant results that has arisen from the interplay of deterministic ecological phenomena and processes. Biologically feasible equilibria of the system are observed and the behaviours of the system around each of them are described. In particular, persistence, stability (local and global) and bifurcation (saddle-node, transcritical, Hopf–Andronov) analysis of this model are obtained. Relevant results from previous well known food chain models are compared with the current findings. Global stability analysis is also carried out by constructing appropriate Lyapunov functions. Numerical simulations show that the present system is capable enough to produce chaotic dynamics when the rate of self-interaction is very low. On the other hand such chaotic behaviour disappears for a certain value of the rate of self interaction. In addition, numerical simulations with experimented parameters values confirm the analytical results and shows that intra-specific competitions bears a potential role in controlling the chaotic dynamics of the system; and thus the role of self interactions in food chain model is illustrated first time. Finally, a discussion of the ecological applications of the analytical and numerical findings concludes the paper.     

Global dynamics of two-compartment models for cell production systems with regulatory mechanisms

We present a global stability analysis of two-compartment models of a hierarchical cell production system with a nonlinear regulatory feedback loop. The models describe cell differentiation processes with the stem cell division rate or the self-renewal fraction regulated by the number of mature cells. The two-compartment systems constitute a basic version of the multicompartment models proposed recently by Marciniak-Czochra and collaborators [25] to investigate the dynamics of the hematopoietic system. Using global stability analysis, we compare different regulatory mechanisms. For both models, we show that there exists a unique positive equilibrium that is globally asymptotically stable if and only if the respective reproduction numbers exceed one. The proof is based on constructing Lyapunov functions, which are appropriate to handle the specific nonlinearities of the model. Additionally, we propose a new model to test biological hypothesis on the regulation of the fraction of differentiating cells. We show that such regulatory mechanism is incapable of maintaining homeostasis and leads to unbounded cell growth. Potential biological implications are discussed.     

Modelling diseases with relapse and nonlinear incidence of infection: a multi-group epidemic model

In this paper, we introduce a basic reproduction number for a multi-group SIR model with general relapse distribution and nonlinear incidence rate. We find that basic reproduction number plays the role of a key threshold in establishing the global dynamics of the model. By means of appropriate Lyapunov functionals, a subtle grouping technique in estimating the derivatives of Lyapunov functionals guided by graph-theoretical approach and LaSalle invariance principle, it is proven that if it is less than or equal to one, the disease-free equilibrium is globally stable and the disease dies out; whereas if it is larger than one, some sufficient condition is obtained in ensuring that there is a unique endemic equilibrium which is globally stable and thus the disease persists in the population. Furthermore, our results suggest that general relapse distribution are not the reason of sustained oscillations. Biologically, our model might be realistic for sexually transmitted diseases, such as Herpes, Condyloma acuminatum, etc.     

Viscoelastic creep induced by repetitive spine flexion and its relationship to dynamic spine stability

Repetitive trunk flexion elicits passive tissue creep, which has been hypothesized to compromise spine stability. The current investigation determined if increased spine flexion angle at the onset of flexion relaxation (FR) in the lumbar extensor musculature was associated with altered dynamic stability of spine kinematics. Twelve male participants performed 125 consecutive cycles of full forward trunk flexion. Spine kinematics and lumbar erector spinae (LES) electromyographic (EMG) activity were obtained throughout the repetitive trunk flexion trial. Dynamic stability was evaluated with maximum finite-time Lyapunov exponents over five sequential blocks of 25 cycles. Spine flexion angle at FR onset, and peak LES EMG activity were determined at baseline and every 25th cycle. Spine flexion angle at FR increased on average by 1.7° after baseline with significant increases of 1.7° and 2.4° at the 50th and 100th cycles. Maximum finite-time Lyapunov exponents demonstrated a transient, non-statistically significant, increase between cycles 26 and 50 followed by a recovery to baseline over the remainder of the repetitive trunk flexion cycles. Recovery of dynamic stability may be the consequence of increased active spine stiffness demonstrated by the non-significant increase in peak LES EMG that occurred as the repetitive trunk flexion progressed.     

带时间延迟的Cohen-Grossberg神经网络全局鲁棒稳定性的一个结果（英文）

在本文中,我们讨论了一类带时间延迟的Cohen-Grossberg神经网络,并研究了这个系统平衡点的全局鲁棒稳定性。利用Lyapunov函数,我们得出了全局鲁棒收敛性的几个充分条件。这些条件以线性矩阵不等式（LMI）的形式表达。因此,从计算的角度出发他们是高效的。另外,这些条件不依赖于时间延迟和神经网络的激发函数。     

Determinants of gait stability while walking on a treadmill: A machine learning approach

Dynamic balance in human locomotion can be assessed through the local dynamic stability (LDS) method. Whereas gait LDS has been used successfully in many settings and applications, little is known about its sensitivity to individual characteristics of healthy adults. Therefore, we reanalyzed a large dataset of accelerometric data measured for 100 healthy adults from 20 to 70 years of age performing 10 min treadmill walking. We sought to assess the extent to which the variations of age, body mass and height, sex, and preferred walking speed (PWS) could influence gait LDS. The random forest (RF) and multiple adaptive regression splines (MARS) algorithms were selected for their good bias-variance tradeoff and their capabilities to handle nonlinear associations. First, through variable importance measure (VIM), we used RF to evaluate which individual characteristics had the highest influence on gait LDS. Second, we used MARS to detect potential interactions among individual characteristics that may influence LDS. The VIM and MARS results indicated that PWS and age correlated with LDS, whereas no associations were found for sex, body height, and body mass. Further, the MARS model detected an age by PWS interaction: on one hand, at high PWS, gait stability is constant across age while, on the other hand, at low PWS, gait instability increases substantially with age. We conclude that it is advisable to consider the participants’ age as well as their PWS to avoid potential biases in evaluating dynamic balance through LDS.