Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locomotor circuits. Past neuromechanical models proposed control of locomotion either driven by central pattern generators (CPGs) with simple sensory commands or by a purely reflex-based network regulated by state-machine mechanisms, which activate and deactivate reflexes depending on the detected gait cycle phases. However, the physiological interpretation of these state machines remains unclear. Here, we present a physiologically plausible model to investigate spinal control and modulation of human locomotion. Approach. We propose a bio-inspired controller composed of two coupled CPGs that produce the rhythm and pattern, and a reflex-based network simulating low-level reflex pathways and Renshaw cells. This reflex network is based on leaky-integration neurons, and the whole system does not rely on changing reflex gains according to the gait cycle state. The musculoskeletal model is composed of a skeletal structure and nine muscles per leg generating movement in sagittal plane. Main results. Optimizing the open parameters for effort minimization and stability, human kinematics and muscle activation naturally emerged. Furthermore, when CPGs were not activated, periodic motion could not be achieved through optimization, suggesting the necessity of this component to generate rhythmic behavior without a state machine mechanism regulating reflex activation. The controller could reproduce ranges of speeds from 0.3 to 1.9 m s−1. The results showed that the net influence of feedback on motoneurons (MNs) during perturbed locomotion is predominantly inhibitory and that the CPGs provide the timing of MNs’ activation by exciting or inhibiting muscles in specific gait phases. Significance. The proposed bio-inspired controller could contribute to our understanding of locomotor circuits of the intact spinal cord and could be used to study neuromotor disorders.
Interleg coordination is not strictly controlled during walking

In human walking, the left and right legs move alternately, half a stride out of phase with each other. Although various parameters, such as stride frequency, stride length, and duty factor, vary with walking speed, the antiphase relationship of the leg motion remains unchanged. This is the case even during running. However, during walking in left-right asymmetric situations, such as walking with unilateral leg loading, walking along a curved path, and walking on a split-belt treadmill, the relative phase between left and right leg motion shifts from the antiphase condition to compensate for the asymmetry. In addition, the phase relationship fluctuates significantly during walking of elderly people and patients with neurological disabilities, such as those caused by stroke or Parkinson’s disease. These observations suggest that appropriate interleg coordination is important for adaptive walking and that interleg coordination is strictly controlled during walking of healthy young people. However, the control mechanism of interleg coordination remains unclear. In the present study, we derive a quantity that models the control of interleg coordination during walking of healthy young people by taking advantage of a state-of-the-art method that combines big data science with nonlinear dynamics. This is done by modeling this control as the interaction between two coupled oscillators through the phase reduction theory and Bayesian inference method. However, the results were not what we expected. Specifically, we found that the relative phase between the motion of the legs is not actively controlled until the deviation from the antiphase condition exceeds a certain threshold. In other words, the control of interleg coordination has a dead zone like that in the case of the steering wheel of an automobile. Such forgoing of control presumably enhances energy efficiency and maneuverability during walking. Furthermore, the forgoing of control in specific situations, where we expect strict control, also appears in quiet standing. This suggests that interleg coordination in walking and quiet standing have a common characteristic strategy. Our discovery of the dead zone in the control of interleg coordination not only provides useful insight for understanding gait control in humans, but also should lead to the elucidation of the mechanisms involved in gait adaptation and disorders through further investigation of the dead zone.
Random networks of automata: a simple annealed approximation

Kauffman's model is a random complex automata where nodes are randomly assembled. Each node σi receives K inputs from K randomly chosen nodes and the values of σi at time t + 1 is a random Boolean function of the K inputs at time t. Numerical simulations have shown that the behaviour of this model is very different for K > 2 and K ≤ 2. It is the purpose of this work to give a simple annealed approximation which predicts K = 2 as the critical value of K. This approximation gives also quantitative predictions for distances between iterated configurations. These predictions agree rather well with the numerical simulations. A possible way of improving this annealed approximation is proposed.
Sociomorphing and an Actor-Network Approach to Social Robotics

Most of the human-robot interaction (HRI) research relies on an implicit assumption, that seems to drive the experimental works in interaction studies: the more anthropomorphism we can reach in HRI, the more effective the robot will be in “being social. ” A fundamental notion pushing forward a non-anthropocentric approach to HRI is the one of “sociomorphing” developed by the Robophilosophy interdisciplinary group at Aarhus University. This paper aims to explore the notion of sociomorphing by analysing the possibilities offered by actor-network theory (ANT). We claim that ANT is a valid framework to re-think the conceptual couple anthropomorphizing / sociomorphing and answer the following question: What kind of negotiation process and social practices can be developed in HRI, given the notion of sociomorph interactional networks?
3D microwave imaging via preliminary support reconstruction: testing on the Fresnel 2008 database

In the solution of inverse scattering problems, support information is useful in order to reduce the degree of nonlinearity of the relationship among the data and the unknowns, as well as the overall computational burden. Moreover, by taking into account the spectral properties of the scattered fields, it can be helpful to reduce the effect of noise on data. Accordingly, a 3D inversion strategy in which one performs a preliminary estimation of the support of the targets is considered in this paper to process the experimental data provided by the Institut Fresnel of Marseille, France. In particular, the imaging problem is tackled in a step-wise fashion, in which one first pursues a morphologic characterization of the targets using a linear sampling method based procedure. Then, the retrieved support is exploited to ‘filter’ the data and, finally, in the quantitative characterization of the targets. This last step is performed by using the optimized contrast source extended Born inversion method wherein the estimated support is exploited in order to reduce both the investigated domain and the nonlinearity of the inverse problem.
Estimation and detection of functions from anisotropic Sobolev classes

: We consider the problems of estimating and detecting an un- known function f depending on a multidimensional variable (for instance, an image) observed in the Gaussian white noise. It is assumed that f be- longs to anisotropic Sobolev class. The case of a function of inﬁnitely many variables is also considered. An asymptotic study (as the noise level tends to zero) of the estimation and detection problems is done. In connection with the estimation problem, we construct asymptotically minimax estima- tors and establish sharp asymptotics for the minimax integrated squared risk. In the detection problem, we construct asymptotically minimax tests and provide conditions for distinguishability in the problem.
On some deterministic space complexity problems

In this paper we give a complete problem in DSPACE(n). The problem is whether there exists a cycle in the connected component containing (o,o,.,o) in the graph Gp of the zeroes of a polynomial P over GF(2) under a suitable natural coding. Hence the deterministic space complexity of this problem is O(n) but not o(n). We give as well several problems for which we can obtain very close upper and lower deterministic space bounds. For example, the deterministic space complexity to determine whether there exists a cycle in the graph of the set of assignments satisfying a Boolean formula is O(n/log n) but not o(n/log2n).
Soft breakdown fluctuation events in ultrathin SiO2 layers

When an ultrathin (<5 nm) oxide is subjected to electrical stress, several soft-breakdown events can occur prior to the final dielectric breakdown. After the occurrence of such failure events, the current–voltage (I–V) characteristic corresponds to the superposition of highly conductive spots and background conduction through the undegraded capacitor area. In this conduction regime, the application of a low constant voltage gives rise to large leakage current fluctuations in the form of random telegraph signal. Some of these fluctuations have been identified with ON/OFF switching events of one or more local conduction spots, and not with a modulation of their conductance. The experimental soft-breakdown I–V characteristics are shown to be better understood if the spot conduction is considered to be locally limited by the silicon electrodes and not by the oxide.
K-SYSTEMS VERSUS CLASSICAL MULTIVARIATE SYSTEMS

K-systems exist in general systems theory for the study of the relationships between parts and wholes. We show here that K-systems analysis can be used to solve problems in classical multivariate analysis, and solve them more effectively than existing methods. To demonstrate this, we take on “the analysis of variance” in this paper. The analysis of variance is the most important and powerful technique in the field of statistical inference (quoted from Probability and Statistics by Hines and Montgomery). We apply K-systems analysis to the analysis of variance problem, and we compare the two techniques. We see that K-systems analysis can provide more information. But the major difference is that the analysis of variance guesses a model for the data whereas K-systems analysis uses “the” model that is true and correct for the data. Further, K-systems theory delivers a surprising and important insight: it is generally incorrect to use any model where effects and interactions are represented statically over sub.
A study on orthogonality sampling

The goal of this paper is to study and further develop the orthogonality sampling or stationary waves algorithm for the detection of the location and shape of objects from the far field pattern of scattered waves in electromagnetics or acoustics. Orthogonality sampling can be seen as a special beam forming algorithm with some links to the point source method and to the linear sampling method. The basic idea of orthogonality sampling is to sample the space under consideration by calculating scalar products of the measured far field pattern , with a test function for all y in a subset Q of the space , m = 2, 3. The way in which this is carried out is important to extract the information which the scattered fields contain. The theoretical foundation of orthogonality sampling is only partly resolved, and the goal of this work is to initiate further research by numerical demonstration of the high potential of the approach. We implement the method for a two-dimensional setting for the Helmholtz equation, which represents electromagnetic scattering when the setup is independent of the third coordinate. We show reconstructions of the location and shape of objects from measurements of the scattered field for one or several directions of incidence and one or many frequencies or wave numbers, respectively. In particular, we visualize the indicator function both with the Dirichlet and Neumann boundary condition and for complicated inhomogeneous media.
Identification the microbial diversity in a municipal wastewater treatment plant using non‐cultured based methods

Abstract In this study, the microbial diversity of activated sludge and RBC (rotating biological contactor) biofilm at Taipei Min‐Sheng Municipal Wastewater Treatment Plant was investigated by a combined cloning‐DGGE (denaturing gradient gel electrophoresis) method. The microbial diversity showed that Pseudomonas spinosa, Zoogloea ramigera and Streptococcus penumoniae were the most predominant types of bacteria in the activated sludge, and in the first and fourth stages of the rotational biological contactor biofilm, respectively. The phylogenetic tree revealed that all the microbial community of these three samples could be divided into three linkages. Among these three linkages, one contained the most clones from rotational biological contactor samples, while others contained the most activated sludge clones. A higher abundance of filamentous bacteria was identified in the fourth stage of the rotational biological contactor biofilm. Additionally, among the three samples, the nitrifying bacteria and nitrification phenomenon were only observed in the fourth stage of the rotational biological contactor biofilm.
Content of anthocyanins, vitamin C and antioxidant activity in seven varieties of Morus alba L. fruits

Objective: To determine the content of anthocyanins and vitamin C, as well as the antioxidant activity of the ethanol extracts of the fruits from seven Morus alba L. varieties. Materials and Methods: The content of anthocyanins and vitamin C was determined in seven varieties of Morus alba L. fruits, cultivated at the Pastures and Forages Research Station Indio Hatuey, as well as the antioxidant activity of the ethanol of these varieties through the phosphomolybdate radical capture essays and determination of total phenols. For the data processing a variance analysis was used. Correlations were made among the variables total antioxidant capacity, total phenols, content of anthocyanins and vitamin C, taking into consideration Pearson’s correlation coefficient and two significance levels of 0,01 and 0,05. Results: The content of anthocyanins, expressed as equivalent of cyanidin-3-glucoside, was between 40,74 and 96,07 mg/100 g, and vitamin C between 16,73 and 28,40 mg of ascorbic acid/100 mL of juice. All the extracts showed antioxidant activity. The total antioxidant capacity varied between 175,96 and 229,48 mmol of ascorbic acid/g of extract and the content of total phenols, between 291,52 and 897,17 mg of gallic acid/100 g of extract. Conclusions: The M. alba fruits showed high contents of anthocyanins and vitamin C. The variety Yu-62 showed the highest concentrations of these compounds. The ethanol extracts showed high antioxidant activity, which is correlated to the high content of total phenols, anthocyanins and vitamin C present in the fruits.
Some Remarks about Compactly Supported Spline Wavelets

Abstract In this paper we propose an extended family of almost orthogonal spline wavelets with compact support. These functions provide snug basesL2( R ), preserving semiorthogonal properties. As it is well known, orthogonality is a desirable quality while finite support has attractive features for numerical applications. This work represents an effort to combine these conditions in the spline case and to enhance previous results of Chui and Unseret al.We start by reviewing the concept of semiorthogonal wavelets and we discuss their performance. Next, we give a brief description of the general technique for computing compactly supported spline wavelets. Finally we expose these functions. We also develop several formulas in accord with our purposes.
Timely Recognition and Treatment of Hypertension in Pregnancy

H ypertensive disorders of pregnancy (HDPs) and associated complications are one of the leading causes of severe maternal morbidity and preventable maternal mortality. Reduction of morbidity and mortality related to HDPs can be significantly achieved through timely and appropriate treatment. This column reviews critical information for nurses, physicians, and all team members caring for obstetric and postpartum patients including updated terminology and diagnostic criteria for HDPs, and best practices for recognition, identification, and coordinated team response.
Comparison of clustering algorithms on generalized propensity score in observational studies: a simulation study

In observational studies, unbalanced observed covariates between treatment groups often cause biased inferences on the estimation of treatment effects. Recently, generalized propensity score (GPS) has been proposed to overcome this problem; however, a practical technique to apply the GPS is lacking. This study demonstrates how clustering algorithms can be used to group similar subjects based on transformed GPS. We compare four popular clustering algorithms: k-means clustering (KMC), model-based clustering, fuzzy c-means clustering and partitioning around medoids based on the following three criteria: average dissimilarity between subjects within clusters, average Dunn index and average silhouette width under four various covariate scenarios. Simulation studies show that the KMC algorithm has overall better performance compared with the other three clustering algorithms. Therefore, we recommend using the KMC algorithm to group similar subjects based on the transformed GPS.
The appearance, number, and history of highly compact binary systems in globular clusters

I analyze the various evolutionary paths possible for highly compact binaries in globular clusters, where they come under the simultaneous influence of gravitational radiation and gravitational encounters with field stars. The observational appearance of those stages in which mass transfer occurs is discussed, with particular attention given to a new class of objects characterized by massive, nonequilibrium accretion disks created by catastrophic gravitational encounters. I then construct an analytic model to predict the number of highly compact binaries in each stage of evolution existing at present in the Galaxy's globular cluster system. Both steady transfer binaries, and systems in which a collaped stellar remnant acquires a massive, nonequilibrium accretion disk, are shown to be present in significant numbers. The number of steadily accreting degenerate dwarfs predicted (which can probably be identified with catacylsmic and Weak x-ray sources) is in good ageement with observations (approx.1000). There should also be approx.100 degenerate dwarfs surrounded by massive disks, whose observational properties are difficult to predict, but are probably quite luminous. Depending on circumstances, they may resemble catacylsmic variables, or possibly red giants. If highly compact binaries can lose angular momentum by no other mechanisms than those considered here, the number of medium strengthmore » (approx.10/sup 35/-10/sup 36/ ergs s/sup -1/) X-ray sources produced by steady transfer onto neutron stars (approx.10) is in conflict with the observations. If the strong (10/sup 36/-10/sup 38/ ergs s/sup -1/) X-ray sources can be identified with neutron star (or low-mass black hole)-plus-massive-disk systems, their predicted number (several) roughly agrees with the actual one. « less
Superhydrophobic surfaces cannot reduce ice adhesion

Understanding the mechanism of ice adhesion on surfaces is crucial for anti-icing surfaces, and it is not clear if superhydrophobic surfaces could reduce ice adhesion. Here, we investigate ice adhesion on model surfaces with different wettabilities. The results show that the superhydrophobic surface cannot reduce the ice adhesion, and the ice adhesion strength on the superhydrophilic surface and the superhydrophobic one is almost the same. This can be rationalized by the mechanical interlocking between the ice and the surface texture. Moreover, we find that the ice adhesion strength increases linearly with the area fraction of air in contact with liquid.
Gaussian Likelihood of Continuous-Time ARMAX Models When Data Are Stocks and Flows at Different Frequencies

For purposes of maximum likelihood estimation, we show how to compute the Gaussian likelihood function when the data are generated by a higher-order continuous-time vector ARMAX model and are observed as stocks and flows at different frequencies. Continuous-time ARMAX models are analogous to discrete-time autoregressive moving-average models with distributed-lag exogenous variables. Stocks are variables observed at points in time and flows are variables observed as integrals over sampling intervals. We derive the implied state-space model of the discrete-time data and show how to use it to compute the Gaussian likelihood function with Kalman-filtering, prediction-error, decomposition of the data.
A non-iterative sampling Bayesian method for linear mixed models with normal independent distributions

In this paper, we utilize normal/independent (NI) distributions as a tool for robust modeling of linear mixed models (LMM) under a Bayesian paradigm. The purpose is to develop a non-iterative sampling method to obtain i.i. d. samples approximately from the observed posterior distribution by combining the inverse Bayes formulae, sampling/importance resampling and posterior mode estimates from the expectation maximization algorithm to LMMs with NI distributions, as suggested by Tan et al. [33]. The proposed algorithm provides a novel alternative to perfect sampling and eliminates the convergence problems of Markov chain Monte Carlo methods. In order to examine the robust aspects of the NI class, against outlying and influential observations, we present a Bayesian case deletion influence diagnostics based on the Kullback–Leibler divergence. Further, some discussions on model selection criteria are given. The new methodologies are exemplified through a real data set, illustrating the usefulness of the proposed methodology.
Integration of dielectric elastomer stack actuators into micro systems

Using dielectric elastomer stack actuators the electrical contact to each conducting layer is a major concern. In order to integrate these actuators inside micro systems e.g. microfluidic systems compatibility to micro fabrication processes is required. The contact resistance and number of connected layers influence the overall actuator performance directly. Lower number of active electrodes decreases the generated deformation of the actuator. High contact resistance has a negative impact on the dynamic actuator behavior. For conventional interconnection processes with copper wires, the contact ratio is in the range of 60% to 80%, depending on the film thickness of the dielectric layer. Furthermore, this process is not compatible to standard micro fabrication technologies. In this paper we evaluate a process based on electroplating for connecting dielectric elastomer stack actuators and present a measurement system to characterize the number of connected layers. The performance of an electroplated contact is defined by the number of connected layers and the contact resistance between electroplated copper studs and graphite electrodes. It depends on different parameters like the cross sectional area of the electrode layers for connection and therefore on the layer thickness. Using multiple contacts instead of a single one the performance of the contact can also be positively influenced.