Walk Process Research Articles

Asymmetric influence-based superposed random walk link prediction algorithm in complex networks

Random walk-based link prediction algorithms have achieved desirable results for complex network mining, but in these algorithms, the transition probability of particles usually only considers node degrees, resulting in particles being able to randomly select adjacent nodes for random walks in an equal probability manner, to solve this problem, the asymmetric influence-based superposed random walk link prediction algorithm is proposed in this paper. This algorithm encourages particles to choose the next node at each step of the random walk process based on the asymmetric influence between nodes. To this end, we fully consider the topological information around each node and propose the asymmetric influence between nodes. Then, an adjustable parameter is applied to normalize the degree of nodes and the asymmetric influence between nodes into transition probability. Based on this, the proposed new transition probability is applied to superposed random walk process to measure the similarity between all nodes in the network. Empirical experiments are conducted on 16 real-world network datasets such as social network, ecology network, and animal network. The experimental results show that the proposed algorithm has high prediction accuracy in most network, compared with 10 benchmark indices.

Deep knowledge distillation: A self-mutual learning framework for traffic prediction

Traffic flow prediction in spatio-temporal networks is a crucial aspect of Intelligent Transportation Systems (ITS). Existing traffic flow forecasting methods, particularly those utilizing graph neural networks, encounter limitations. When processing large-scale graph data, the depth of these models can restrict their ability to effectively capture complex relationships and patterns. Additionally, these methods often focus mainly on local neighborhood information, which can limit their capability to recognize and analyze global relationships and patterns within the graph data. Therefore, we proposed a deep knowledge distillation model, tailored to effectively capture spatio-temporal patterns in traffic flow prediction. This model incorporates a bidirectional random walk process on a directed graph, enabling it to effectively capture both spatial and temporal dependencies. Utilizing a blend of mutual learning and self-distillation, our approach enhances the detection of spatio-temporal relationships within traffic data and improves the feature perception ability at both local and global levels. We tested our model on two real-world datasets, achieving notable improvements in prediction accuracy, especially for predictions within a one-hour timeframe. In comparison to the baseline model, our proposed model achieved accuracy improvements of 0.19 and 0.18 on the respective datasets. These results highlight the success of using mutual learning and self-distillation to transfer knowledge effectively within and between models and to improve the model’s capability in identifying and extracting features.

Urban segregation on multilayered transport networks: a random walk approach

We present a novel method for analysing socio-spatial segregation in cities by considering constraints imposed by transportation networks. Using a multilayered network approach, we model the interaction probabilities of socio-economic groups with random walks and Lévy flights. This method allows for evaluation of new transport infrastructure’s impact on segregation while quantifying each network’s contribution to interaction opportunities. The proposed random walk segregation index measures the probability of individuals encountering diverse social groups based on their available means of transit via random walks. The index incorporates temporal constraints in urban mobility with a parameter, α∈[0,1)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha \\in [0,1)$$\\end{document}, of the probability of the random walk continuing at each time step. By applying this to a toy model and conducting a sensitivity analysis, we explore how the index changes dependent on this temporal constraint. When the parameter equals zero, the measure simplifies to an isolation index. When the parameter approaches one it represents the city’s overall socio-economic distribution by mirroring the steady-state of the random walk process. Using Cuenca, Ecuador as a case study, we illustrate the method’s applicability in transportation planning as a valuable tool for policymakers, addressing spatial distribution of socio-economic groups and the connectivity of existing transport networks, thus promoting equitable interactions throughout the city.

Research on Mechanical Leg Structure Design and Control System of Lower Limb Exoskeleton Rehabilitation Robot Based on Magnetorheological Variable Stiffness and Damping Actuator

During the walking process of lower limb exoskeleton rehabilitation robots, inevitable collision impacts will occur when the swinging leg lands on the ground. The impact reaction force from the ground will induce vibrations in the entire robot’s body from bottom to top. To address this phenomenon, considering the limitations of traditional active compliance and passive compliance methods, a variable stiffness and damping actuator (VSDA) leg structure using a magnetorheological damper (MRD) is proposed. Firstly, experimental methods are used to obtain the ground reaction force (GRF) exerted on a normal person during walking. Then, a mathematical model of the VSDA leg structure is constructed, and its working principle is analyzed. Based on human mass and dimensions, a 3D model is designed and selected. Finally, a simulation model is built in the MATLAB/Simulink environment using the fuzzy switch damping control strategy to simulate the acceleration and displacement of the human body under sinusoidal and random excitations. The results indicate that under sinusoidal excitation, employing fuzzy switch damping control optimizes human displacement by 72.47% compared to the high stiffness and high damping system, and by 16.95% compared to the switch damping system. Human acceleration is optimized by 52.09% compared to the high stiffness and high damping system, and by 25.2% compared to the switch damping system. Under random excitation, adopting fuzzy switch damping control optimizes human displacement by 59.09% compared to the high stiffness and high damping system, and by 21.74% compared to the switch damping system. Human acceleration is optimized by 78.74% compared to the high stiffness and high damping system, and by 31.66% compared to the switch damping system. This validates the VSDA design structure and control method, demonstrating certain advantages in improving the compliance and stability of lower limb exoskeleton rehabilitation robots.

Self-Feedback DNAzyme Motor for Cascade-Amplified Imaging of mRNA in Live Cells and In Vivo.

DNA motors have attracted extensive interest in biosensing and bioimaging. However, the amplification capacity of the existing DNA motor systems is limited since the products from the walking process are unable to feedback into the original DNA motor systems. As a result, the sensitivities of such systems are limited in the contexts of biosensing and bioimaging. In this study, we report a novel self-feedback DNAzyme motor for the sensitive imaging of tumor-related mRNA in live cells and in vivo with cascade signal amplification capacity. Gold nanoparticles (AuNPs) are modified with hairpin-locked DNAzyme walker and track strands formed by hybridizing Cy5-labeled DNA trigger-incorporated substrate strands with assistant strands. Hybridization of the target mRNA with the hairpin strands activates DNAzyme and promotes the autonomous walking of DNAzyme on AuNPs through DNAzyme-catalyzed substrate cleavage, resulting in the release of many Cy5-labeled substrate segments containing DNA triggers and the generation of an amplified fluorescence signal. Moreover, each released DNA trigger can also bind with the hairpin strand to activate and operate the original motor system, which induces further signal amplification via a feedback mechanism. This motor exhibits a 102-fold improvement in detection sensitivity over conventional DNAzyme motors and high selectivity for target mRNA. It has been successfully applied to distinguish cancer cells from normal cells and diagnose tumors in vivo based on mRNA imaging. The proposed DNAzyme motor provides a promising paradigm for the amplified detection and sensitive imaging of low-abundance biomolecules in vivo.

Walking control of semi-passive robot via a modified Q-learning algorithm

The analysis and control of stability of passive biped robot has been the subject of an in-depth study because of its unique characteristics. This work gives a new perspective aiming at a force applied on foot of collision phase of walking process of passive robot, which is a completely new way of applying impulse force that is different from the previous. Therefore, the new equation has been derived due to this force which is not parallel to the support leg to provide further analysis for the study. Besides, this paper combines the characteristics of passive walking with the process of reinforcement learning, and an improved algorithm thus was designed to calculate the value of the control force. The simulation results show that control method designed in this article can not only make the unsteady passive robot achieve stable walking, but also have a quick control speed. Furthermore, the selection range of initial values is expanded by using this method, which provides a convenient reference for the later research work.

Improved gait parameters following surgical revascularization in patients with intermittent claudication

ObjectiveIntermittent claudication (IC) is known to be associated with impaired gait parameters, with a higher incidence of falls and higher oxygen consumption due to uneconomic walking. However, the influence of arterial disobliteration in patients with IC on their gait pattern has rarely been investigated to date. The aim of this study was to examine the gait patterns before and after inflow revascularization by surgical disobliteration of pelvic and inguinal arteries (ie, common iliac artery, external iliac artery, common femoral artery, profound femoral artery, superficial femoral artery) in IC patients. Successful surgical disobliteration of inflow arteries (improvement of ankle brachial pressure index of ≥0.2 and patent common iliac, external iliac, common femoral, profound femoral, and superficial femoral arteries) is known to improve the painless walking distance for patients with IC due to peripheral arterial disease; however, its influence on gait parameters is unclear. We hypothesized that the gait parameters would also improve after surgery. Improved gait parameters can lead to a more economic walking process, lower oxygen consumption, a lower risk of falls, and a higher quality of life. MethodsIn a single-center, exploratory, longitudinal study, we examined the gait parameters of 20 IC inpatients of our hospital before and after surgical disobliteration of pelvic and inguinal arteries. Spatiotemporal parameters such as range of motion of the hip and knee joint, stance phase, cadence, and foot rotation were obtained using the Diers 4Dmotion Lab (Diers International). The gait parameters were obtained under painful walking conditions preoperatively and with the patients walking pain free at the same speed postoperatively. ResultsA total of 20 patients were examined. Surgical revascularization led to a higher walking cadence (mean, plus 7.88 steps; 95.5 steps/min vs 87.6 steps/min; P = .024), an increased range of motion of the hip joint (mean, plus 2.0°; 35.1° vs 33.1°; P = .038), and improved foot rotation (mean, plus 2.0°; 11.0° vs 9.0°; P = .02). Regarding other parameters such as step length, stance phase, and step duration, smaller differences were detected in this study. ConclusionsIn this exploratory study, we found that surgical revascularization of pelvic and inguinal arteries in IC patients improved certain gait parameters. Further studies with larger patient numbers are needed to confirm these data and provide more evidence on this subject.

Parameter optimization and tractive performance evaluation of tracked miner

Enhancing the traction performance of the tracked miner is crucial for ensuring smooth seabed operation. In this study, an experimental device for the interaction between track and deep-sea sediments was designed, aligning with the walking process of the tracked miner. The primary and secondary order of the influence of the driving parameters on the mechanical properties of the undisturbed deep-sea sediments was determined by an orthogonal test, and the pressure-sinkage model and shear stress–displacement model were constructed. Building upon the shear model and the vehicle ground mechanics theory, the driving mechanics model of the tracked miner in the seabed environment was derived, and the track structure and parameter optimization method were proposed. The results show that the experimental factors significantly influence the mechanical properties of undisturbed deep-sea sediments, with the order of influence being grounding pressure > grouser height > shear rate > track shoe length > track shoe width; By optimizing the structural parameters of the “Kunlong 500” tracked miner, the drawbar pull increased by 29.1%, and the sinkage depth reduced by 12.8%. This study quantitatively analyzes the influence of structural parameters in driving performance on the sinkage and shear characteristics of deep-sea sediments, and proposes a new method for optimizing the tractive parameters. It provides new insights for achieving efficient and environmentally friendly movement of tracked miner on the seabed.

A deep pedestrian trajectory generator for complex indoor environments

AbstractPedestrian trajectory data, which can be used to mine pedestrian motion patterns or to model pedestrian dynamics, is crucial for indoor location‐based service studies and applications. However, researchers are faced with the challenges of data shortage and privacy restrictions when using pedestrian trajectory data. We present an Indoor Pedestrian Trajectory Generator (IPTG), which is a novel deep learning model to synthesize pedestrian trajectory data. IPTG first produces feature sequences that encode the spatial–temporal and semantic features of the walking process and then interpolates them into complete trajectories using A* and perturbation algorithms. IPTG has specially designed loss functions that preserve topological constraints and semantic characteristics. Incorporating the prior knowledge of environment constraints and pedestrian walking patterns, the IPTG model is capable of generating topologically and logically sound indoor pedestrian trajectories. We evaluated the synthesized trajectories based on multiple metrics and examined the generated trajectories qualitatively. The results show that IPTG outperforms several baselines, demonstrating its ability to generate semantically meaningful and spatiotemporally coherent trajectories.

Visual Feature Tuning Properties of Short-Latency Stimulus-Driven Ocular Position Drift Responses during Gaze Fixation.

Ocular position drifts during gaze fixation are significantly less well understood than microsaccades. We recently identified a short-latency ocular position drift response, of ∼1 min arc amplitude, that is triggered within <100 ms by visual onsets. This systematic eye movement response is feature-tuned and seems to be coordinated with a simultaneous resetting of the saccadic system by visual stimuli. However, much remains to be learned about the drift response, especially for designing better-informed neurophysiological experiments unraveling its mechanistic substrates. Here we systematically tested multiple new feature tuning properties of drift responses. Using highly precise eye tracking in three male rhesus macaque monkeys, we found that drift responses still occur for tiny foveal visual stimuli. Moreover, the responses exhibit size tuning, scaling their amplitude (both up and down) as a function of stimulus size, and they also possess a monotonically increasing contrast sensitivity curve. Importantly, short-latency drift responses still occur for small peripheral visual targets, which additionally introduce spatially directed modulations in drift trajectories toward the appearing peripheral stimuli. Drift responses also remain predominantly upward even for stimuli exclusively located in the lower visual field and even when starting gaze position is upward. When we checked the timing of drift responses, we found it was better synchronized to stimulus-induced saccadic inhibition than to stimulus onset. These results, along with a suppression of drift response amplitudes by peristimulus saccades, suggest that drift responses reflect the rapid impacts of short-latency and feature-tuned visual neural activity on final oculomotor control circuitry in the brain.

How Can the Optical Variation Properties of Active Galactic Nuclei Be Unbiasedly Measured?

The variability of active galactic nuclei (AGNs) is ubiquitous, but has not yet been understood. Measuring the optical variation properties of AGNs, such as the variation timescale and amplitude, and then correlating them with their fundamental physical parameters has long served as a critical way of exploring the origin of AGN variability and the associated physics of the accretion process in AGNs. Obtaining accurate variation properties of AGNs is thus essential. It has been found that the damped random walk process can describe the AGN optical variation well, but there is a controversy over how long a minimal monitoring baseline is required to obtain unbiased variation properties. In this work, we settle the controversy by exhaustively scrutinizing the complex combination of assumed priors, adopted best-fit values, ensemble averaging methods, and fitting methods. The new proposal is then an optimized solution where unbiased variation properties of an AGN sample possessing the same variation timescale can be obtained with a minimal baseline of about 10 times their variation timescale. Finally, the new optimized solution is used to demonstrate the positive role of the time-domain surveys to be conducted by the Wide Field Survey Telescope in improving constraints on AGN variation properties.

FOREIGN EXCHANGE MARKET EFFICIENCY: CASE STUDY ON INDONESIA

This research examines the foreign exchange market efficiency in Indonesia using currency pairs chosen based on Indonesia’s largest international trading partner by volume, namely, China, United States and Japan. Consequently, the currency pairs used for this research are IDR/USD, IDR/JPY, IDR/CNY. The test utilizes the Augmented Dickey Fuller procedure in determining whether the datasets contain any unit roots in which case foreign exchange price movements follow a random walk movement (non-stationary), or not (stationary). The research findings show that historical data for all three currencies follow a random walk process or the market is weak-form efficient.

Integrated optimization design and motion control of multi-configuration unmanned metamorphic vehicle

An unmanned metamorphic vehicle is a new deformable robot that can transform its configuration according to different road conditions in order to realize wheeled driving or legged walking. This paper proposes a method of multi-objective integrated optimization design based on the motion control of unmanned metamorphic vehicle. The aim of this method is to improve the stability and reduce energy consumption of multi-configuration motion. The vehicle state configuration and the humanoid state walking performance were designed. The kinematic model of reconfiguration and humanoid walking was established from screw theory, while the Lagrangian dynamics model for reconfiguration and humanoid walking using analytical mechanics. Reconfiguration and gait planning were carried out for an unmanned metamorphic vehicle, and a sliding mode controller was designed for position feedback control of the zero moment point in order to improve the stability of reconfiguration and walking. In order to improve the kinematic performance of an unmanned metamorphic vehicle under multiconfiguration, the NSGA-II intelligent optimization algorithm was used to optimize the multi-objective integrated design of the structural parameters, posture parameters, and control parameters of the sliding mode controller of the system. The simulation and test results showed that the integrated design performs higher reconfiguration stability, lower energy consumption, and higher control quality than the sequential design and pre-optimization under the reconfiguration condition; in the vehicle state, the transient steering stability and the steady-state steering stability of the system during driving are significantly improved; in the humanoid state, the energy consumption of the striding process and the movement of the center of mass to the single-legged support region in the walking process is reduced and the walking stability is improved, thus is more conducive to walking.

Pendampingan dan Evaluasi Produk Kaki Prostetik bagi Kelainan Kongenital Kaki di Atas Lutut (Above Knee Prosthesis)

A prosthetic leg is a lower extremity movement aid in assisting the mobility of persons with physical disabilities. A prosthetic leg is used to replace a missing leg, either due to a birth defect or an amputation. The use of a prosthetic leg is a different matter if the user has never experienced movement sensation. This service will evaluate the process of assisting the use of prosthetic legs for people with physical disabilities from birth. So far, prosthetic foot manufacturing services that have been carried out by the Prosthetic Orthosis Profession in Indonesia have focused on making sockets. Most users have physical abnormalities for a history of amputation or not birth defects. So that in the process of practicing the use of prosthetic legs there are no difficulties. It's different if the user of this prosthetic leg is congenital who has not felt the sensation of stepping movement at all or what is known as the gait cycle. Forms of community service activities in the process of assisting the use of prosthetic legs and evaluating any obstacles encountered in the walking process.

Selection of human gait mathematical model for use in rehabilitation devices

Due to musculoskeletal diseases progression and increase in spinal injuries, the use of domestically developed multifunctional rehabilitation complexes for functional therapy is becoming increasingly important.Aim: To analyze existing human gait patterns and select a suitable model for choosing the optimal design and engineering solution for a mechatronic rehabilitation complex, affecting the lower limbs of a person.Methodology and Research Methods. An analysis of existing technical solutions for rehabilitation complexes was carried out. Brief overview of the main approaches to studying human gait is provided. A model was selected; its detailed description is given for implementation for the robotic rehabilitation complex of functional therapy development.Results. As a result of the study, data on the position of the legs during gait was obtained and visualization of the walking process was carried out to identify the shortcomings for the selected model. The selected model is implemented in the experimental sample rehabilitation complex.Conclusion. In the future, it is necessary to refine the model and compare it with a model based on machine learning, and use the most realistic option in rehabilitation complexes.

Walking in the City as an Experienced Practice

The paper is a contemplative explication of the walking process. What are the essential features of walking, and how do those who stroll around the city experience walking? We used contemplative research methods and explication of the phenomenon of walking. The research is based on self-observation and self-reporting about the thoughts, body feelings, and emotions that emerge during walks. In the paper, we describe the features of the phenomenon of walking. First, we investigate the minding process generated by walking in the city. Then, we elaborate on the pathic dimension of walking (especially the mood), body feelings (lived body), lived relations, and reflections on life and self that are a consequence of walking.

Diphosphine Ligand‐Enabled Nickel‐Catalyzed Chelate‐Assisted Inner‐Selective Migratory Hydroarylation of Alkenes

AbstractThe precise control of the regioselectivity in the transition metal‐catalyzed migratory hydrofunctionalization of alkenes remains a big challenge. With a transient ketimine directing group, the nickel‐catalyzed migratory β‐selective hydroarylation and hydroalkenylation of alkenyl ketones has been realized with aryl boronic acids using alkyl halide as the mild hydride source for the first time. The key to this success is the use of a diphosphine ligand, which is capable of the generation of a Ni(II)‐H species in the presence of alkyl bromide, and enabling the efficient migratory insertion of alkene into Ni(II)‐H species and the sequent rapid chain walking process. The present approach diminishes organosilanes reductant, tolerates a wide array of complex functionalities with excellent regioselective control. Moreover, this catalytic system could also be applied to the migratory hydroarylation of alkenyl azahetereoarenes, thus providing a general approach for the preparation of 1,2‐aryl heteroaryl motifs with wide potential applications in pharmaceutical discovery.

Diphosphine Ligand-Enabled Nickel-Catalyzed Chelate-Assisted Inner-Selective Migratory Hydroarylation of Alkenes.

The precise control of the regioselectivity in the transition metal-catalyzed migratory hydrofunctionalization of alkenes remains a big challenge. With a transient ketimine directing group, the nickel-catalyzed migratory β-selective hydroarylation and hydroalkenylation of alkenyl ketones has been realized with aryl boronic acids using alkyl halide as the mild hydride source for the first time. The key to this success is the use of a diphosphine ligand, which is capable of the generation of a Ni(II)-H species in the presence of alkyl bromide, and enabling the efficient migratory insertion of alkene into Ni(II)-H species and the sequent rapid chain walking process. The present approach diminishes organosilanes reductant, tolerates a wide array of complex functionalities with excellent regioselective control. Moreover, this catalytic system could also be applied to the migratory hydroarylation of alkenyl azahetereoarenes, thus providing a general approach for the preparation of 1,2-aryl heteroaryl motifs with wide potential applications in pharmaceutical discovery.

Highly selective α-C(sp3)-H arylation of alkenyl amides via nickel chain-walking catalysis

Herein, we report the migratory hydroarylation of unactivated alkenes with aryl iodides using native and weakly coordinating amide directors under mild conditions. Synergistic coordination of the monodentate directing group and the ligand enable the highly regioselective migratory hydroarylation via a chain walking process to form the thermodynamically stable five-membered nickelacyle intermediate. The protocol provides a variety of valuable α-aryl-substituted alkylamine products, and exhibited good functional group tolerance. The modification of bioactive compounds such as fenofibrate and indomethacin further highlights the synthetic value of this protocol.

Atomic scale volume and grain boundary diffusion elucidated by in situ STEM

Diffusion is one of the most important phenomena studied in science ranging from physics to biology and, in abstract form, even in social sciences. In the field of materials science, diffusion in crystalline solids is of particular interest as it plays a pivotal role in materials synthesis, processing and applications. While this subject has been studied extensively for a long time there are still some fundamental knowledge gaps to be filled. In particular, atomic scale observations of thermally stimulated volume diffusion and its mechanisms are still lacking. In addition, the mechanisms and kinetics of diffusion along defects such as grain boundaries are not yet fully understood. In this work we show volume diffusion processes of tungsten atoms in a metal matrix on the atomic scale. Using in situ high resolution scanning transmission electron microscopy we are able to follow the random movement of single atoms within a lattice at elevated temperatures. The direct observation allows us to confirm random walk processes, quantify diffusion kinetics and distinctly separate diffusion in the volume from diffusion along defects. This work solidifies and refines our knowledge of the broadly essential mechanism of volume diffusion.