Movement Model Research Articles

Optimizing Fertilizer Management Practices in Summer Maize Fields in the Yellow River Basin

This study aims to examine the impact of combined irrigation and fertilizer control on the summer maize yield, nitrogen use efficiency (NE), and nitrogen leaching (NL) in the Yellow River Basin. Based on the measured data from the field summer maize experiment in 2021 and 2022, a water-nitrogen movement model was constructed for ‘Zhengdan 958’ maize under two irrigation methods (wide furrow irrigation (G) and border irrigation (Q)), three fertilizer rates (120 kg/ha (N1), 220 kg/ha (N2), and 320 kg/ha (N3)), and three fertilizer frequencies (1 (T1), 2 (T2), and 3 (T3)), yielding 18 total treatments. Calculation of nitrogen leaching was based on water nitrogen transport modeling. The study then analyzed the factors and their combined effects. A multi-objective optimization genetic algorithm (NSGA-II) was established to evaluate maize yield, nitrogen use efficiency, and nitrogen leaching. The results indicate that the determination coefficients between simulated and measured water, nitrogen values exceeded 0.74. The rate optimized HYDRUS model effectively simulated the soil solute movement. The interaction of the irrigation method, fertilizer rate, and fertilizer application frequency did not significantly affect yield and nitrogen leaching, but did significantly impact nitrogen use efficiency (p < 0.05). Nitrogen leaching increased gradually as nitrogen application increased. The yield under wide furrow irrigation was 6.26% higher than that under border irrigation. The optimal coupling scheme of water and fertilizer was obtained using the genetic algorithm multi-objective optimization method, where the combined GN2T2 treatment was the optimal management model, the summer maize yield reached 14,077 kg/ha, nitrogen use efficiency and nitrogen leaching were reduced to 30.21 kg·kg−1 and 17.64 kg/ha, respectively. These findings can guide summer maize cultivation in the Yellow River Basin and assist in reducing nitrogen surface source pollution.

EFFECTS OF LEARNER-CENTERED INTERVENTIONS IN SCIENCE LEARNING: COMPARING EYE MOVEMENT IN EYE MOVEMENT MODELING EXAMPLES AND PROMPTING

An integrated understanding of illustrations and texts is crucial for students to comprehend science teaching learning materials. Intervention methods can be employed to facilitate this integrated understanding. This study examined the effects of Eye Movement Modeling Examples (EMME) and Prompting interventions on the learning of illustrated scientific texts among primary school students. Furthermore, the study compared the reading strategies and learning comprehension of fifth-grade students who utilized EMME, an approach that facilitates learning through observational methods, with those who used Prompting, a method that directly guides learning through linguistic information. The study analysis revealed that EMME had a significantly greater effect on integrated reading strategies and learning comprehension compared with Prompting. Specifically, the EMME group exhibited an integrated reading strategy that involved relating the illustrations and texts, whereas the Prompting group and the control group did not demonstrate the same strategy. In addition, the post-test results indicated that the EMME group achieved higher average scores in verbal and pictorial factors compared with the other two groups. Keywords: eye movement modeling examples, learner-oriented intervention, science education, science learning, South Korea

Behavioral investigation of stochastic lateral wandering patterns in mixed traffic flow

The vehicles’ lateral movement exhibits inherent stochastic behavior, and when considered collectively, the traffic flow demonstrates certain lateral wandering pattern which serves a fundamental input for pavement design and sustainability analysis. Naturalistic driving trajectories show that the vehicles on neighboring lanes tend to interact laterally, which leads to correlated wandering on a multi-lane road. Compared with human-driven vehicles (HDV), autonomous vehicles (AVs) have a more centered wandering pattern, which accelerates the pavement fatigue. As the market penetration rate of the AVs changes, the wandering pattern of the mixed AVs flow would evolve accordingly, which further influence pavement performances. The evolutionary wandering pattern of mixed AVs flow which considers the interactions between neighboring lanes’ traffic flow is not fully studied yet. This research fills this gap with a stochastic behavioral lateral movement model that bridges the microscopic behavior and lateral wandering pattern. Firstly, a lateral movement model is developed, which assumes that lateral dynamics are influenced by lane markings, road boundaries, intra-lane interaction, and noise. The model is expressed in a stochastic differential form. The solution of the model which gives the lateral wandering is expressed by the Euler-Maruyama scheme, Fokker-Planck equation and Markov chain. Then the model is employed to investigate the wandering patterns under different scenarios. The results show that the model's outputs are consistent with current research results and empirical observations. This research provides additional insights regarding lateral wandering under mixed autonomous vehicle flow, and offers a theoretical tool for future road pavement design.

The Application of Deductive Method in Modeling Tourist Movement in Local Destinations

This paper aims to develop a model of tourist movement in local destinations using the deductive method. The model is based on examining how intervening factors as determinants that have been identified previously in urban transport modeling and tourism literature can affect movement in local destinations. This study uses a literature study approach. This analysis aims to develop a model of tourist movement based on determinant factors that have been previously identified in the tourism literature. Data were analyzed using spatial analysis. The results of the study show that the model of tourist movement in local destinations consists of four main components, namely origin, destination, modes and routes. Intervening factors that influence tourist movements are sociodemographic characteristics, travel characteristics, destination characteristics, and external factors. This paper also discusses the implications and limitations of the model and suggests directions for future research.

Analysis of technical characteristics of typical lower limb balance movements in Tai Chi: a cross-sectional study based on AnyBody bone muscle modeling.

Tai Chi is an excellent traditional Chinese physical fitness exercise, and its unique balancing movements are very important for improving human balance. In this study, the two most representative Tai Chi balance movements, "knee lift balance" and "leg stirrup balance", were selected to establish the lower limb bone muscle model of Tai Chi balance movements by using computer simulation modeling technology, aiming to analyze the characteristics of the lower limb movement mechanisms of typical balance movements, to provide a quantitative theoretical basis for improving the scientific level of Tai Chi. A total of 16 subjects were recruited for this study. the BTS three-dimensional motion capture system and three-dimensional force platform were used for motion data acquisition, the physiological electromyographic signals were collected using BTS surface electromyography, and the lower limb bone muscle model of Tai Chi balance movements was established by AnyBody human simulation. In the knee lift balancing movement, the balance leg hip abduction/adduction angle, hip flexion/extension moment, and the strength of the rectus femoris muscle, biceps femoris short capitis, and iliacus muscle of the amateur group was significantly smaller than that of the professional group (P<0.01). In the leg stirrup balance movement, the knee flexion/extension angle of the balancing leg in the amateur group was significantly greater than that in the professional group (P<0.01), and the hip flexion/extension angle, hip inversion/abduction angle, knee flexion/extension moment, hip flexion/extension moment, the strength iliacus, gluteus maximus, and obturator internus were significantly smaller than those in the professional group (P<0.01). The integral EMG of the biceps femoris of the support leg in the amateur group was significantly smaller than that of the professional group (P<0.01). The integral EMG of the lateral femoral muscle of the balance leg was significantly smaller than that of the professional group (P<0.01). In this study, we found that the balancing leg of the balancing movement has a larger hip joint angle, the stirrup balancing knee joint angle is smaller, and the hip and knee joint moments are larger. This is related to joint activity and muscle activation, and amateurs should pay attention to increasing the range of motion of the hip joint and decreasing the range of motion of the knee joint when practicing to better stimulate exercise of the lower limb joints. In addition, the practice of balancing movements should strengthen the iliacus muscle, which plays an important role in maintaining the stable balance of the lower limbs, and strengthen the knee flexor and extensor muscles and hip adductor/abductor muscles of the balancing leg, thus promoting the stability of the balancing leg movements.

Spatial Demo-Genetic Predator–Prey Model for Studying Natural Selection of Traits Enhancing Consumer Motility

Combining explicit modelling of predator movements with the Kostitzin demo-genetic equations, we study conditions promoting natural selection of consumer motility. The model is a system of partial differential equations describing spatial movements of predators pursuing the diffusing prey. Local predator–prey interactions are described by the classical Rosenzweig–MacArthur model, which additionally accounts for the Allee effect affecting reproduction of predators. Spatial activity of predators is determined by the coefficients of diffusion and indirect prey-taxis. The latter characterizes the predator ability to move directionally up the gradient of taxis stimulus (odor, pheromone, exometabolite) continuously emitted by prey. Assuming that the consumer movement ability is governed by a single diallelic locus with recessive ‘mobile’ and dominant ‘settled’ alleles, the predator population in the model consists of three competing genotypes differing by diffusion and taxis coefficients; other parameters characterizing the genotypes are assumed to be equal. Numerical simulations with different spatial patterns imitating habitat deterioration demonstrate that the direction of selection among the consumer genotypes alternates, depending on the degree of habitat deterioration affecting the overall production of the prey population. Theoretical implications of the results are discussed in relation with problems of biological control, predator interference, and evolution of animal motility.

Mathematical modeling of movement of multi-rotor type aircraft

The problem of determining the features and setting the problem of mathematical modeling of multirotor aircraft (LA) is considered. Differences of their mathematical models from the classical mathematical models of aircraft and single-rotor helicopter type aircraft are considered. The analysis and substantiation of the forces and moments acting on a multirotor aircraft are carried out, taking into account the peculiarities of considering the corresponding coordinate systems necessary for studying the spatial motion of the aircraft. The problem of controlling the trajectory motion of an aircraft is formulated taking into account the rotation of its structure around the center of mass. Based on the consideration of the structural diagram of one of the most common four-rotor aircraft (quadcopter), a scheme for creating control forces and moments acting on the aircraft, under the influence of which the aircraft’s trajectory in space changes, is substantiated. The main mathematical dependences characterizing the kinematics of the motion of a multi-rotor aircraft are given. On the basis of the analysis carried out, a generalized block diagram of the control process for such an aircraft is substantiated and presented. To test the performance and adequacy of the mathematical model, a study was made of the movement of a quadrocopter in a vertical plane between given points in space in accordance with the law of forced control, which ensures the movement of an aircraft in space with maximum speed. The computer simulation of the obtained analytically mathematical dependences showed that this approach is applicable to the construction of mathematical models of the motion of multirotor type aircraft of various design layouts.

Spatially detailed agricultural and food trade between China and the United States

The United States and China are key nations in global agricultural and food trade. They share a complex bilateral agri-food trade network in which disruptions could have a global ripple effect. Yet, we do not understand the spatially resolved connections in the bilateral US–China agri-food trade. In this study, we estimate the bilateral agri-food trade between Chinese provinces and U.S. states and counties. First, we estimate bilateral imports and exports of agri-food commodities for provinces and states. Second, we model link-level connections between provinces and states/counties. To do this, we develop a novel algorithm that integrates a variety of national and international databases for the year 2017, including trade data from the US Census Bureau, the US Freight Analysis Framework database, and Multi-Regional Input-Output tables for China. We then adapt the food flow model for inter-county agri-food movements within the US to estimate bilateral trade through port counties. We estimate 2,954 and 162,922 link-level connections at the state-province and county-province resolution, respectively, and identify core nodes in the bilateral agri-food trade network. Our results provide a spatially detailed mapping of the US–China bilateral agri-food trade, which may enable future research and inform decision-makers.

Modelling the eye movements of dyslexic children during reading as a continuous time random walk.

The study of eye movements during reading is considered a valuable tool for understanding the underlying cognitive processes and for its ability to detect alterations that could be associated with neurocognitive deficiencies or visual conditions. During reading, the gaze moves from one position to the next on the text performing a saccade-fixation sequence. This dynamics resembles processes usually described as continuous time random walk, where the jumps are the saccadic movements and waiting times are the duration of fixations. The time between jumps (intersaccadic time) consists of stochastic waiting time and flight time, which is a function of the jump length (the amplitude of the saccade). This motivates the present proposal of a model of eye movements during reading in the framework of the intermittent random walk but considering the time between jumps as a combined stochastic-deterministic process. The parameters used in this model were obtained from records of eye movements of children with dyslexia and typically developed for children performing a reading task. The jump lengths arise from the characteristics of the selected text. The time required for the flights was obtained based on a previously proposed model. Synthetic signals were generated and compared with actual eye movement signals in a complexity-entropy plane.

Transient expression of cauliflower mosaic virus (CaMV) P6-GFP complements a defective CaMV replicon to facilitate viral gene expression, replication and virion formation

Over the past decades, several studies have examined the subcellular localization of the cauliflower mosaic virus (CaMV) P6 protein by tagging it with GFP (P6-GFP). These investigations have been essential in the development of models for inclusion body formation, nuclear transport, and microfilament-associated intracellular movement of P6 inclusion bodies for delivery of virions to plasmodesmata. Although it was shown early on that the translational transactivation function of P6-GFP was comparable to wild type P6, it has not been possible to incorporate a P6-GFP gene into an infectious clone of CaMV. Consequently, it has not been possible to formally prove that a P6-GFP fusion is comparable in function to the unmodified P6 protein. Here we show that transient expression of P6-GFP can complement a defective CaMV replicon through gene expression, replication and encapsidation, which validates the relevance of P6-GFP subcellular localization studies for understanding the development of CaMV infections.

Outlier-Robust Gaze Signal Filtering Framework Based on Eye-Movement Modality Recognition and Set-Membership Approach.

High-quality gaze signals are crucial in many biomedical fields that utilize them. However, the limited studies on gaze signal filtering can hardly address the outliers and non-Gaussian noise in gaze data simultaneously. Our objective is to design a generic filtering framework capable of reducing the noise and eliminating outliers of the gaze signal. In this study, we design an eye-movement modality-based zonotope set-membership filtering framework (EM-ZSMF) to suppress the noise and outliers of the gaze signal. This framework consists of an eye-movement modality recognition model (EG-NET), an eye-movement modality-based gaze movement model (EMGM), and a zonotope set-membership filter (ZSMF). The eye-movement modality determines the EMGM, and the ZSMF combined with the EMGM completes the filtering of the gaze signal. Moreover, this study establishes an eye-movement modality and gaze filtering dataset (ERGF) that can be utilized for the evaluation of future work integrating eye-movement modality with gaze signal filtering. The eye-movement modality recognition experiments demonstrated that our proposed EG-NET achieved the best Cohen's kappa compared with previous studies. The gaze data filtering experiments showed that the proposed EM-ZSMF reduced the gaze signal noise and eliminated outliers effectively, and achieved the best performance (RMSEs and RMS) compared with previous methods. The proposed EM-ZSMF effectively recognizes eye-movement modalities, reduces gaze signal noise and, eliminates outliers. To the best of the authors' knowledge, this is the first attempt to simultaneously solve the problem of non-Gaussian noise and outliers in gaze signals. The proposed framework has the potential for application in any eye image-based eye trackers and contributes to the development of eye-tracking technology.

시선 이동 모델링 예제가 초등학생들의 그림자 개념 형성에 미치는 효과

Objectives This study aimed to examine the effects of eye movement modeling examples (EMME) on elementary school students' formation of the concept of shadows. Methods An EMME for concept learning in shadow formation was developed and applied to third-grade elementary school students. Post-tests were conducted immediately after the application, and delayed tests were conducted three weeks later. To compare the effects of EMME application, a control group was selected and underwent video-based learning without the presentation of EMME. They also underwent the same tests as the experimental group. Results In the post-test, there was a significant difference in the total fixation duration and fixation count for the light source in Task 1. However, in Tasks 2 and 3, although there was a difference in the average total fixation duration and fixation count for the light source, it was not statistically significant. Additionally, there was no difference in concept understanding between the two groups. In the delayed test, differences were found in the total fixation duration and fixation count for the light source in all three tasks. Furthermore, there was no statistically significant difference between the two groups in conceptual understanding. Conclusions Although EMME did not have an impact on the formation of the concept of shadows, it can be concluded that it is effective in inducing long-term gaze attention to the light source.

Incorporating multidimensional behavior into a risk management tool for a critically endangered and migratory species.

Conservation of migratory species exhibiting wide-ranging and multidimensional behaviors is challenged by management efforts that only utilize horizontal movements or produce static spatial-temporal products. For the deep-diving, critically endangered eastern Pacific leatherback turtle, tools that predict where turtles have high risks of fisheries interactions are urgently needed to prevent further population decline. We incorporated horizontal-vertical movement model results with spatial-temporal kernel density estimates and threat data (gear-specific fishing) to develop monthly maps of spatial risk. Specifically, we applied multistate hidden Markov models to a biotelemetry data set (n=28 leatherback tracks, 2004-2007). Tracks with dive information were used to characterize turtle behavior as belonging to 1 of 3 states (transiting, residential with mixed diving, and residential with deep diving). Recent fishing effort data from Global Fishing Watch were integrated with predicted behaviors and monthly space-use estimates to create maps of relative risk of turtle-fisheries interactions. Drifting (pelagic) longline fishing gear had the highest average monthly fishing effort in the study region, and risk indices showed this gear to also have the greatest potential for high-risk interactions with turtles in a residential, deep-diving behavioral state. Monthly relative risk surfaces for all gears and behaviors were added to South Pacific TurtleWatch (SPTW) (https://www.upwell.org/sptw), a dynamic management tool for this leatherback population. These modifications will refine SPTW's capability to provide important predictions of potential high-risk bycatch areas for turtles undertaking specific behaviors. Our results demonstrate how multidimensional movement data, spatial-temporal density estimates, and threat data can be used to create a unique conservation tool. These methods serve as a framework for incorporating behavior into similar tools for other aquatic, aerial, and terrestrial taxa with multidimensional movement behaviors.

Individual‐based models of avian migration for estimating behavioural traits and predicting ecological interactions

Abstract Rapid advances in the field of movement ecology have led to increasing insight into both the population‐level abundance patterns and individual‐level behaviour of migratory species. Despite this progress, research questions that require scaling individual‐level understanding of the behaviour of migrating organisms to the population level remain difficult to investigate. To bridge this gap, we introduce a generalizable framework for training full‐annual cycle individual‐based models of migratory movements by combining information from tracking studies and species occurrence records. Focusing on migratory birds, we call this method: Models of Individual Movement of Avian Species (MIMAS). We implement MIMAS to design individual‐based models of avian migration that are trained using previously published weekly occurrence maps and fit via Approximate Bayesian Computation. MIMAS models leverage individual‐ and population‐level information to faithfully represent continental‐scale migration patterns. Models can be trained successfully for species even when little existing individual‐level data is available for parameterization by relying on population‐level information. In contrast to existing mathematical models of migration, MIMAS explicitly represents and estimates behavioural attributes of migrants. MIMAS can additionally be used to simulate movement over consecutive migration seasons, and models can be easily updated or validated as new empirical data on migratory behaviours becomes available. MIMAS can be applied to a variety of research questions that require representing individual movement at large scales. We demonstrate three applied uses for MIMAS: estimating population‐specific migratory phenology, predicting the spatial patterns and magnitude of ectoparasite dispersal by migrants, and simulating the spread of a pathogen across the annual cycle of a migrant species. Currently, MIMAS can easily be used to build models for hundreds of migratory landbird species but can also be adapted in the future to build models of other types of migratory animals.

Multi-target modeling of spine movements for signing Avatar

Multi-target modeling of spine movements for signing Avatar

NeRSemble: Multi-view Radiance Field Reconstruction of Human Heads

We focus on reconstructing high-fidelity radiance fields of human heads, capturing their animations over time, and synthesizing re-renderings from novel viewpoints at arbitrary time steps. To this end, we propose a new multi-view capture setup composed of 16 calibrated machine vision cameras that record time-synchronized images at 7.1 MP resolution and 73 frames per second. With our setup, we collect a new dataset of over 4700 high-resolution, high-framerate sequences of more than 220 human heads, from which we introduce a new human head reconstruction benchmark 1 . The recorded sequences cover a wide range of facial dynamics, including head motions, natural expressions, emotions, and spoken language. In order to reconstruct high-fidelity human heads, we propose Dynamic Neural Radiance Fields using Hash Ensembles (NeRSemble). We represent scene dynamics by combining a deformation field and an ensemble of 3D multi-resolution hash encodings. The deformation field allows for precise modeling of simple scene movements, while the ensemble of hash encodings helps to represent complex dynamics. As a result, we obtain radiance field representations of human heads that capture motion over time and facilitate re-rendering of arbitrary novel viewpoints. In a series of experiments, we explore the design choices of our method and demonstrate that our approach outperforms state-of-the-art dynamic radiance field approaches by a significant margin.

Modelling the lateral dimension of vehicles movement: a stochastic differential approach with applications

A stochastic lateral movement model is proposed to address the limitations of current traffic models, which fail to capture the stochastic nature of the lateral component in vehicle movement during lane keeping and lane changing. This model incorporates a lateral noise component and a lateral movement component, with parameters that have clear physical interpretations including noise intensity, driver’s sensitivity to lateral deviation, and sensitivity to noise. The model successfully describes the real-world distribution and standard deviation of lateral displacement, achieves over 70% accuracy in distinguishing between human driven vehicles and autonomous vehicles, derives the lane changing duration distribution consistent with experimental observation, and shows that the sensitivity to lateral deviation is about 7 times higher in lane changing compared to lane keeping.

Generalised linear model of periodic limb movements.

During sleep, the lower extremities exhibit periodic repetitive movements which are referred to as Period Limb Movement (PLM). Polysomnography (PSG) is the gold standard for diagnosing periodic limb movement disorder. The frequency of PLM episodes per hour of sleep (PLMI) determines the severity of the condition. PLM are generated by a dynamic process, however PLMI measures only the average PLM rate and does not capture the dynamic properties of PLM. Here, we characterise PLM dynamics using a generalised dynamic model as a function of sleep stage, timing of past PLM events and adjacent sleep disordered-breathing events. We analysed PSG recordings of 237 men and 222 women enrolled in the Multi-ethnic Study of Atherosclerosis (MESA) dataset to model dynamic PLM features. We statistically analysed whether these dynamics are associated with sex, age, and BMI. Modelling suggests instantaneous PLM rates are greater in men than women and higher in N1 and N2 non-rapid eye movement sleep than N3 and rapid eye movement sleep. The generalised model constitutes statistically robust approach towards the characterisation of periodic limb movement.Clinical Relevance- The generalised model may enable differentiated diagnostics of periodic limb movement disorder.

Experimental Design and Validation of an Adjustable Straw Guide Structure for a Grain Combine Harvester Thresher Based on a Material Movement Model

The threshing device is the core component of the grain combine harvester, and the straw guide board plays an important role in the threshing device. In the past, the guiding structure of the threshing device could not optimize the working performance of the machine by adjusting the spiral angle. In this study, an adjustable straw guide board was designed, and the movement model of the straw on the straw guide board was analyzed. The response surface method was used to perform field experiments, and the experimental data were analyzed using quadratic polynomial regression. The results show that the drum rotation speed, operating speed, and spiral angle of the straw guide board have significant effects on the percentage of loss rate (PLR), percentage of impurities rate (PIR), and percentage of broken rate (PBR). Further optimization analysis showed that the predicted values of the PLR, PIR, and PBR were 1.18%, 0.72%, and 0.54%, respectively, whereas the experimental verification values were 1.26%, 0.73%, and 0.61%, respectively. The absolute errors between the experimental and predicted values were very small; however, the optimized field test verified values decreased by 8.31%, 50.04%, and 60.30%, respectively, which indicates that the optimized harvester had better operation quality.

Particle blockage mechanism of a weakly consolidated sandstone geothermal reservoir during tailwater recharge

Weakly consolidated sandstone geothermal reservoirs (WCSGR) are widely distributed, highly developed and utilized, with tremendous potential to meet enormous energy needs. However, this kind of geothermal reservoir (GR) suffer from permeability damage during tailwater recharge, primarily due to particle blockage (PB). The exact impact of PB on the permeability of GRs during tailwater recharge remains unclear. Therefore, an experimental study investigating PB in WCSGR tailwater recharge was conducted, considering the comprehensive effects of multiple factors. The study aimed to understand the mechanism of PB and its effect on GR permeability by observing the migration of fluorescent particles in sandstone core. Through analysis of microsphere migration/blockage properties, theoretical calculations, and empirical criteria, the PB mechanism during tailwater recharge in weakly consolidated sandstone was revealed. A physical model of particle movement was developed to explain the permeability attenuation phenomena in the experimental cores, describing the occurrence and development process of PB in real recharge operations. Finally, the theoretical computation were integrated with the experimental findings, and the chemical and dynamic conditions of geothermal tailwater recharge in the WCSGR were optimized. This study provides theoretical guidance for further numerical simulations and field tests.