Fast Movements Research Articles

Distributed MA‐IDDPG‐OLSR based stable routing protocol for unmanned aerial vehicle ad‐hoc network

AbstractIn unmanned aerial vehicle ad‐hoc network (UANET), the node speed of unmanned aerial vehicles (UAVs) may reach up to 400 km/h. The fast or slow movement of UAV nodes leads to different speeds of topology change of the nodes. Traditional optimized link state routing (OLSR) protocol cannot adaptively adjust the routing update period when the network topology changes, which may lead to the nodes calculating incorrect routing tables. This increases the average end‐to‐end delay and packet loss rate for packet transmission. To enhance the adaptability of OLSR routing protocol to network topology changes, this paper proposes a multi‐agent independent deep deterministic policy gradient‐OLSR (MA‐IDDPG‐OLSR) routing protocol based on distributed multi‐agent reinforcement learning. The protocol deploys DDPG algorithm on each UAV node, and each UAV node adaptively adjusts the Hello and TC message sending intervals, according to the one‐hop neighbouring nodes as well as its own state. Simulation results show that the proposed protocol is able to improve the throughput and reduce the packet loss rate as compared to traditional AODV, GRP, OLSR, and distributed multiple‐agent independent proximal policy optimization‐OLSR (MA‐IPPO‐OLSR), distributed multiple‐agent independent twin delayed deep deterministic policy gradient‐OLSR (MA‐ITD3‐OLSR) routing protocols. Since MA‐IDDPG‐OLSR relies only on local information, there is a minor performance degradation in MA‐IDDPG‐OLSR compared to centralized single‐agent DQN‐OLSR routing protocol. But it is more suitable to a completely distributed UAV network without a centralized node.

A hollow magnetic soft robot consisting of rod-shaped nanofiber actuators

Magnetic soft robots are prominent in biological environments due to the untethered movement and penetration under magnetic field. Moreover, in order to overcome biological barriers in microenvironment, the development of small size, biocompatible/biodegradable and precisely controlled mobility of magnetic soft robots is a promising. Thus, a hollow magnetic soft robot consisting of rod-shaped nanoactuators formed by the cleavage of photosensitive electrospun nanofibers is designed. The nanofiber actuators are composed of biodegradable polymer matrix and biocompatible superparamagnetic magnetic iron oxide nanoparticle fillers, and the uniform rod-shaped nanofibers are obtained from the molecule fracture of photosensitive copolymers under UV irradiation. Based on the bottom-up and top-down constructing concept, the hollow magnetic soft robots show unique property of the stabilized morphology, the programmed magnetization and the high order motion transition in an instant. This provides a strategy for designing and obtaining the adaptive magnetic soft robots, which can effectively improve the precise locomotion and fast movement efficiency in complex physiological environment.

Risk response towards roads is consistent across multiple species in a temperate forest ecosystem

Roads can have diverse impacts on wildlife species, and while some species may adapt effectively, others may not. Studying multiple species' responses to the same infrastructure in a given area can help understand this variation and reveal the effects of disturbance on the ecology of wildlife communities. This study investigates the behavioural responses of four species with distinctive ecological and behavioural traits to roads in the protected Bohemian Forest Ecosystem in central Europe: European roe deer Capreolus capreolus, a solitary herbivore; red deer Cervus elaphus a gregarious herbivore; wild boar Sus scrofa, a gregarious omnivore and Eurasian lynx Lynx lynx, a solitary large carnivore. We used GPS data gathered from each species to study movement behaviour and habitat selection in relation to roads using an integrated step selection analysis. For all species and sexes, we predicted increased movement rates in response to roads, selection of vegetation cover near roads and open areas after road crossings, and increased road avoidance during the day. We found remarkably similar behavioural responses towards roads across species. The behavioural adaptations to road exposure, such as increased movement rates and selection for vegetation cover, were analogous to responses to natural predation risk. Roads were more strongly avoided during daytime, when traffic volume was high. Road crossings were more frequent at twilight and at night within open areas offering food resources. Gregarious animals exposed to roads favoured stronger road avoidance over faster movements. Ungulates crossed roads more at twilight, coinciding with commuter traffic during winter. Despite differences in the ecology and behaviour of the four species, our results showed similar adaptations towards a common threat. The continuous expansion of the global transportation network should be accompanied by efforts to understand and minimise the impact of roads on wildlife to assist wildlife management and ensure conservation.

Smooth pursuit inhibition reveals audiovisual enhancement of fast movement control.

The sudden onset of a visual object or event elicits an inhibition of eye movements at latencies approaching the minimum delay of visuomotor conductance in the brain. Typically, information presented via multiple sensory modalities, such as sound and vision, evokes stronger and more robust responses than unisensory information. Whether and how multisensory information affects ultra-short latency oculomotor inhibition is unknown. In two experiments, we investigate smooth pursuit and saccadic inhibition in response to multisensory distractors. Observers tracked a horizontallymoving dot and were interrupted by an unpredictable visual, auditory, or audiovisual distractor. Distractors elicited a transient inhibition of pursuit eye velocity and catch-up saccade rate within ∼100 ms of their onset. Audiovisual distractors evoked stronger oculomotor inhibition than visual- or auditory-only distractors, indicating multisensory response enhancement. Multisensory response enhancement magnitudes were equal to the linear sum of responses to component stimuli. These results demonstrate that multisensory information affects eye movements even at ultra-short latencies, establishing a lower time boundary for multisensory-guided behavior. We conclude that oculomotor circuits must have privileged access to sensory information from multiple modalities, presumably via a fast, subcortical pathway.

A miniature piezoelectric actuator with fast movement and nanometer resolution

To accomplish fast movement and high positioning capability, a miniature self-moving piezoelectric actuator (MSPA) is developed with two groups of polyphenylene sulfide (PPS) transducers operating in the symmetric bending (SB) or counter symmetric bending (CSB) vibration. Each group includes the inner and outer legs, whose vibrations are orthogonal and horizontal to the ground, respectively; this interestingly imitates the stepping and swing functions of the forelimbs and hindlimbs of the gorilla in the ‘running on all fours’ gait. To examine the validity, first, by utilizing the model on the basis of Krimhertz transmission theory, the resonant frequency of the CSB vibration was structurally tuned to approach that of the SB vibration. Then, a MSPA prototype with the size of 30 × 45 × 49 mm and the weight of 25.2 g was fabricated to assess the moving, carrying, and positioning performance. In a tethered manner, the MSPA yielded the maximal speed of 562 mm/s (18.73 body length per second), the maximal payload of 485 g (19.25 times of its own weight), and the towing force of 0.5 N (corresponding to the towing force density of 19.8 N/kg). Moreover, it achieved the turning movements (whose directions, angular speeds, and steering radii are changeable) and in-situ rotations, climbed the slope of 12.5°, and moved on the curved floor. In an untethered manner, the MSPA produced the minimal step displacement of 31.9 nm. These results demonstrate that the MPSA possesses the large speed and the nanometer resolution owing to the bionic operating principle and the employment of PPS, and provides a new approach to design lightweight piezoelectric actuators.

Type of auditory cues and apparatus influence how healthy young adults integrate sounds for dynamic balance.

It is unclear whether the brain handles auditory cues similarly to visual cues for balance. We investigated the influence of headphones and loudspeaker reproduction of sounds on dynamic balance performance when an individual is facing a cognitive challenge. Twenty participants (16 females, aged 19-36) were asked to avoid a ball according to a specific visual rule. Visuals were projected from the HTC Vive head-mounted display in an acoustically controlled space. We varied the environment by adding congruent sounds (sounds coincide with the visual rule) or incongruent sounds (sounds may or may not coincide with the visual rule) as well as creating a multimodal (visual and congruent sounds) vs. unimodal (visual or congruent sounds only) display of stimuli. Sounds were played over headphones or loudspeakers. We quantified reaction time (RT) and accuracy (choosing the correct direction to move) by capturing the head movement. We found that in the absence of sounds, RT was slower with headphones compared to loudspeakers, but the introduction of either congruent or incongruent sounds resulted in faster movements with headphones such that RT was no longer different between apparatus. Participants used congruent sounds to improve accuracy but disregarded incongruent sounds. This suggests that selective attention may explain how sounds are incorporated into dynamic balance performance in healthy young adults. Participants leveraged sounds played over loudspeakers, but not over headphones, to enhance accuracy in a unimodal dark environment. This may be explained by the natural listening conditions created by loudspeakers where sounds may be perceived as externalized.

Applying Common Spatial Pattern and Convolutional Neural Network to Classify Movements via EEG Signals.

Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to enhancing the control of external prostheses by accurately distinguishing various movements through brain signals. This innovation can provide comfortable circumstances for the populace who have movement disabilities. This study combined the most prospering methods used in BCI systems, including one-versus-rest common spatial pattern (OVR-CSP) and convolutional neural network (CNN), to automatically extract features and classify eight different movements of the shoulder, wrist, and elbow via EEG signals. The number of subjects who participated in the experiment was 10, and their EEG signals were recorded while performing movements at fast and slow speeds. We used preprocessing techniques before transforming EEG signals into another space by OVR-CSP, followed by sending signals into the CNN architecture consisting of four convolutional layers. Moreover, we extracted feature vectors after applying OVR-CSP and considered them as inputs to KNN, SVM, and MLP classifiers. Then, the performance of these classifiers was compared with the CNN method. The results demonstrated that the classification of eight movements using the proposed CNN architecture obtained an average accuracy of 97.65% for slow movements and 96.25% for fast movements in the subject-independent model. This method outperformed other classifiers with a substantial difference; ergo, it can be useful in improving BCI systems for better control of prostheses.

A GPS assisted translocation experiment to study the homing behavior of red deer

Many animals return to their home areas (i.e., ‘homing’) after translocation to sites further away. Such translocations have traditionally been used in behavioral ecology to understand the orientation and migration behavior of animals. The movement itself can then be followed by marking and recapturing animals or by tracking, for example, using GPS systems. Most detailed studies investigating this behavior have been conducted in smaller vertebrates (e.g., birds, amphibians, and mice), whereas information on larger mammals, such as red deer, is sparse. We conducted GPS-assisted translocation experiments with red deer at two sites in the Czech Republic. Individuals were translocated over a distance of approximately 11 km and their home journey was tracked. Circular statistics were used to test for significant homeward orientation at distances of 100, 500, 1000, and 5000 m from the release site. In addition, we applied Lavielle trajectory segmentation to identify the different phases of homing behavior. Thirty-one out of 35 translocations resulted in successful homing, with a median time of 4.75 days (range 1.23–100 days). Animals were significantly oriented towards home immediately after release and again when they came closer to home; however, they did not show a significant orientation at the distances in between. We were able to identify three homing phases, an initial ‘exploratory phase’, followed by a ‘homing phase’ which sometimes was again followed by an ‘arrival phase’. The ‘homing phase’ was characterized by the straightest paths and fastest movements. However, the variation between translocation events was considerable. We showed good homing abilities of red deer after translocation. Our results demonstrate the feasibility of conducting experiments with environmental manipulations (e.g., to impede the use of sensory cues) close to the release site. The homing behavior of red deer is comparable to that of other species, and might represent general homing behavior patterns in animals. Follow-up studies should further dissect and investigate the drivers of the individual variations observed and try to identify the sensory cues used during homing.

An Adjustable Wireless Backhaul Link Selection Algorithm for LEO-UAV-Sensor-Based Internet of Remote Things Network.

Internet of Remote Things (IoRT) networks utilize the backhaul links between unmanned aerial vehicles (UAVs) and low-earth-orbit (LEO) satellites to transfer the massive data collected by sensors. However, the backhaul links change rapidly due to the fast movement of both the UAVs and the satellites, which is different from conventional wireless networks. Additionally, due to the various requirements of IoRT multiservices, the system performance should be comprehensively considered. Thus, an adjustable wireless backhaul link selection algorithm for a LEO-UAV-sensor-based IoRT network is proposed. Firstly, an optimization model for backhaul link selection is proposed. This model uses Q, which integrates the remaining service time and capacity as the objective function. Then, based on the snapshot method, the dynamic topology is converted into the static topology and a heuristic optimization algorithm is proposed to solve the backhaul link selection problem. Finally, the proposed algorithm is compared with two traditional algorithms, i.e., maximum service time and maximum capacity algorithms. Numerical simulation results show that the proposed model can achieve better system performance, and the overload of the satellites is more balanced. The algorithm can obtain a trade-off between remaining service time and capacity by dynamically adjusting model parameters. Thus, the adjustable backhaul link selection algorithm can apply to multiservice IoRT scenarios.

Bridging the gap between movement data and connectivity analysis using the Time-Explicit Habitat Selection (TEHS) model

BackgroundUnderstanding how to connect habitat remnants to facilitate the movement of species is a critical task in an increasingly fragmented world impacted by human activities. The identification of dispersal routes and corridors through connectivity analysis requires measures of landscape resistance but there has been no consensus on how to calculate resistance from habitat characteristics, potentially leading to very different connectivity outcomes.MethodsWe propose a new model, called the Time-Explicit Habitat Selection (TEHS) model, that can be directly used for connectivity analysis. The TEHS model decomposes the movement process in a principled approach into a time and a selection component, providing complementary information regarding space use by separately assessing the drivers of time to traverse the landscape and the drivers of habitat selection. These models are illustrated using GPS-tracking data from giant anteaters (Myrmecophaga tridactyla) in the Pantanal wetlands of Brazil.ResultsThe time model revealed that the fastest movements tended to occur between 8 p.m. and 5 a.m., suggesting a crepuscular/nocturnal behavior. Giant anteaters moved faster over wetlands while moving much slower over forests and savannas, in comparison to grasslands. We also found that wetlands were consistently avoided whereas forest and savannas tended to be selected. Importantly, this model revealed that selection for forest increased with temperature, suggesting that forests may act as important thermal shelters when temperatures are high. Finally, using the spatial absorbing Markov chain framework, we show that the TEHS model results can be used to simulate movement and connectivity within a fragmented landscape, revealing that giant anteaters will often not use the shortest-distance path to the destination patch due to avoidance of certain habitats.ConclusionsThe proposed approach can be used to characterize how landscape features are perceived by individuals through the decomposition of movement patterns into a time and a habitat selection component. Additionally, this framework can help bridge the gap between movement-based models and connectivity analysis, enabling the generation of time-explicit connectivity results.

Dynamic Interplay: Unveiling the Biosphere-Geosphere Nexus in Carbon Cycling

A model describing the interaction of geological and biosphere processes is proposed. It is based on the postulate of the gravitational effect of the bodies of the solar system on the lithosphere plates' movement through magma flows and deep breathing of the Earth. The continuous movement of the plates consist of orogenic cycles. The cycles include a short-term orogenic periods of relatively fast plates' movement and long-term geosynclinal periods of relatively slow movement. The fast movement is caused by rifting, when magma breaks through the thin shell of the lithosphere and hardens in contact with sea water, forming a new plate. During the orogenic period, oceanic plates collide with the continental margin plate in the subduction zone. The energy of the collisions initiates thermochemical sulfate reduction, in which sedimentary organic matter (OM) is oxidized. The resulting CO2 rises to the surface of the Earth, spreads over the planet, initiating photosynthesis. In the geosynclinal period due to the slow plates' movement the released collision energy is insufficient to initiate thermochemical sulfate reduction.

Pengenalan dan Pembelajaran Literasi Berbasis Media Digital Mengenai Beretika Media Sosial di SDN Pasir Luhur

In all-digital era like this, digital literacy is something that must be done in order to keep abreast of the fast technological movements but also to avoid all things that are not desirable in the vast digital media. This journal article aims to be able to find out and provide an understanding of digital literacy regarding the use of Microsoft Word and how to be ethical on social media aimed at elementary school children who are auspices of SDN Pasirluhur to be able to avoid the threat of crime that is rife in the digital world, For example, the spread of fake news on social media and many others. The implementation method used in this article is the stage of monitoring and situation analysis, survey and location determination, learning and socialization with material presentation, as well as the evaluation stage. In activities regarding digital literacy there are several main discussions such as the meaning of social media, the functions and uses of the positive and negative impacts of social media, as well as how to be ethical and deal with fake news on social media.

Rapid and Ultrasensitive Colorimetric Biosensors for Onsite Detection of Escherichia coli O157:H7 in Fluids.

This study presents a breakthrough in the field of onsite bacterial detection, offering an innovative, rapid, and ultrasensitive colorimetric biosensor for the detection of Escherichia coli (E. coli) O157:H7, using chemically modified melamine foam (MF). Different from conventional platforms, such as 96-well plates and fiber-based membranes, the modified MF features a macroporous reticulated three-dimensional (3D) framework structure, allowing fast and free movement of large biomolecules and bacteria cells through the MF structure in every direction and ensuring good accessibility of entire active binding sites of the framework structure with the target bacteria, which significantly increased sensitive and volume-responsive detection of whole-cell bacteria. The biosensing platform requires less than 1.5 h to complete the quantitative detection with a sensitivity of 10 cfu/mL, discernible by the naked eye, and an enhanced sensitivity of 5 cfu/mL with the help of a smartphone. Following a short enrichment period of 1 h, the sensitivity was further amplified to 2 cfu/mL. The biosensor material is volume responsive, making the biosensing platform sensitivity increase as the volume of the sample increases, and is highly suitable for testing large-volume fluid samples. This novel material paves the way for the development of volume-flexible biosensing platforms for the record-fast, onsite, selective, and ultrasensitive detection of various pathogenic bacteria in real-world applications.

Mixed Palletizing for Smart Warehouse Environments: Sustainability Review of Existing Methods

Mixed palletizing constitutes one of the problems in the logistics domain aroused from the need for fast product movement to satisfy the continuously increasing number of customers with the demand for highly personalized goods. In a demanding environment, such as warehouses, where break bulk and the consolidation of loads take up most of the working time, the automation of mixed palletizing can lead to increased efficiency and speed while keeping errors to a minimum. Space utilization of pallets enables savings in storage and transportation costs, boosting the overall sustainable role of the Supply Chain sector. This paper presents the proposed approaches to mixed palletizing stemming from different fields, with a focus on recent developments in the application of Industry 4.0 technologies. Our research highlights quite a few areas that require attention from researchers.

Controlling Musculoskeletal System with Spinal Cord-Inspired Constraint Force Field Primitives

Organisms naturally have extraordinary motor ability. They can autonomously control the highly redundant and nonlinear musculoskeletal system to complete fast and flexible movements. Motor primitive theory proposed that a complex movement can be realized by modular organization of simple movement patterns. This theory provides a convincing theoretical basis for explaining the extraordinary motor ability of organisms, and has been supported by plenty of experimental evidences in neurosciences. As a kind of typical motor primitive related to the modular regulation of the spinal motor system, convergent force field was thought to be significant for reducing the complexity of controlling numerous muscles and joints simultaneously. Inspired by the primitive property of convergent force field, in this paper, we proposed a new algorithm to efficiently construct constraint force field on musculoskeletal system with highly redundant actuators by taking optimized parameters of constraint force field as motor primitives. Compared with previous methods of constructing constraint force field, the proposed algorithm is able to reduce the dimension of the solution space so as to effectively improve the computational efficiency of constructing constraint force field in musculoskeletal system with redundant muscles. Validation experiments were carried out in a musculoskeletal system with 10 redundant muscles. The number of optimization iterations and computational time required for constructing constraint force field at a new position were significantly reduced. The system can accurately reach the target position using constant activations. This work may bring in new inspiration for realizing efficient and accurate motion control of musculoskeletal robots with limited feedback accuracy.

Development of a provably secure and privacy-preserving lightweight authentication scheme for roaming services in global mobility network

The accelerated development of Internet of Things services surfaced the way for providing uninterrupted and adaptable smart mobility services for mobile clients to communicate without any zone or time constraints. The global mobility network is an appropriate contender to be adopted as a communication platform to offer roaming services for swift data exchange and fast movement of mobile users in smart mobility. Nevertheless, the confidentiality and secrecy of the exchanged messages have become major concerns due to the insecure nature of the public communication channel. Additionally, it is worth monitoring that enhanced security measures must not increase the burden on limited-powered, small computationally efficient mobile devices. To fulfill these purposes, multiple authentication and key agreement protocols in the context of roaming services have been proposed in recent days. This research demonstrates that most of the previous authentication schemes for the GLOMONET environment have failed to achieve the aforesaid secrecy goals. To satisfy the purposes, this article has proposed a mutual authentication and session key negotiation scheme for roaming services that resists all security susceptibilities and provides essential requirements like anonymity with minimized computation and communication overhead. To support our claim, the security of the proposed scheme is formally verified using the well-known random oracle model and aProVerif simulation tool. Moreover, the implementation of the protocol using the broadly acknowledged NS-2 simulation tool visualizes the practical efficiency of the protocol.

RAIL PASSENGER TRANSPORTATION IN BORDER PROVINCES IN TURKEY

Transportation plays a crucial role in the movement of information, capital, goods, and services between different points, impacting both the environment and human society. It encompasses the economic, fast, and secure movement of people and goods to yield spatial and temporal advantages. The advent of the steam engine led to the introduction and continued utilization of steam locomotives in railway transportation. In Turkey, despite the need to establish economic opportunities, resource allocation between the two main transportation subsystems, namely railways and roads, remains an issue. Railway transportation is a highly efficient mode of mass transportation, capable of transferring large numbers of passengers and cargo with minimal energy consumption and air pollution, making it environmentally friendly. It generates less noise compared to other modes of transportation, relative to the freight and passengers it carries, and requires less land and urban space. However, the efficient utilization of railway resources is contingent upon sufficient demand. Turkey's strategic location as a gateway between Europe and the Middle East underscores the need for further development of rail passenger transportation. This would optimize infrastructure resources, enhance environmental sustainability, and promote economic and social benefits through cross-border mobility. This paper examines the challenges hindering the expansion of passenger railway transport and offers solutions and recommendations for the future.

LEONARDO

A new pre-exascale computer cluster has been designed to foster scientific progress and competitive innovation across European research systems, it is called LEONARDO. This paper describes thegeneral architecture of the system and focuses on the technologies adopted for its GPU-accelerated partition. High density processing elements, fast data movement capabilities and mature software stack collections allow the machine to run intensive workloads in a flexible and scalable way. Scientific applications from traditional High Performance Computing (HPC) as well as emerging Artificial Intelligence (AI) domains can benefit from this large apparatus in terms of time and energy to solution.

Digital image correlation techniques for motion analysis and biomechanical characterization of plants.

Temporally and spatially complex 3D deformation processes appear in plants in a variety of ways and are difficult to quantify in detail by classical cinematographic methods. Furthermore, many biomechanical test methods, e.g. regarding compression or tension, result in quasi-2D deformations of the tested structure, which are very time-consuming to analyze manually regarding strain fields. In materials testing, the contact-free optical 2D- or 3D-digital image correlation method (2D/3D-DIC) is common practice for similar tasks, but is still rather seldom used in the fundamental biological sciences. The present review aims to highlight the possibilities of 2D/3D-DIC for the plant sciences. The equipment, software, and preparative prerequisites are introduced in detail and advantages and disadvantages are discussed. In addition to the analysis of wood and trees, where DIC has been used since the 1990s, this is demonstrated by numerous recent approaches in the contexts of parasite-host attachment, cactus joint biomechanics, fruit peel impact resistance, and slow as well as fast movement phenomena in cones and traps of carnivorous plants. Despite some technical and preparative efforts, DIC is a very powerful tool for full-field 2D/3D displacement and strain analyses of plant structures, which is suitable for numerous in-depth research questions in the fields of plant biomechanics and morphogenesis.

An accurate and robust visual-inertial positioning method

The human–machine integrated coordinate measurement is a promising coordinate measurement method with high flexibility and efficiency for the complex working environments. The cameras installed on the head-mounted measurement device achieves accurate global positioning by observing the uncoded LED landmarks, and then combines with the local measuring to obtain 3D coordinates. However, limited by the frame rate of the camera, the fast movements of the operator’s head may cause landmark misidentification and visual positioning failure. In order to improve the robustness, a visual-inertial positioning method is proposed in this paper. An inertial measurement unit (IMU) is added to compensate for the deficiency of the visual positioning and enhance the dynamic performance. An adaptive extended Kalman filter (EKF), which adjusts the measurement noise covariance matrix based on the visual positioning uncertainty, is established to obtain the optimal state estimation. And an efficient initialization procedure is presented to implement the initial registration of uncoded landmarks based on the normal distribution transform algorithm and to determine the initial state of the IMU. Furthermore, the residual chi-square test is employed to detect false pose estimate in real time and to avoid positioning failure. The experiments demonstrate that the proposed method has high static positioning accuracy (0.681 mm) and high dynamic positioning robustness. The adaptive EKF realizes reliable landmark identification under fast movements and provides a higher accuracy than the common EKF.