Dynamic Patterns Research Articles

A Novel Trajectory Prediction Method Based on CNN, BiLSTM, and Multi-Head Attention Mechanism

A four-dimensional (4D) trajectory is a multi-dimensional time series that embodies rich spatiotemporal features. However, its high complexity and inherent uncertainty pose significant challenges for accurate prediction. In this paper, we present a novel 4D trajectory prediction model that integrates convolutional neural networks (CNNs), bidirectional long short-term memory networks (BiLSTMs), and multi-head attention mechanisms. This model effectively addresses the characteristics of aircraft flight trajectories and the difficulties associated with simultaneously extracting spatiotemporal features using existing prediction methods. Specifically, we leverage the local feature extraction capabilities of CNNs to extract key spatial and temporal features from the original trajectory data, such as geometric shape information and dynamic change patterns. The BiLSTM network is employed to consider both forward and backward temporal orders in the trajectory data, allowing for a more comprehensive capture of long-term dependencies. Furthermore, we introduce a multi-head attention mechanism that enhances the model’s ability to accurately identify key information in the trajectory data while minimizing the interference of redundant information. We validated our approach through experiments conducted on a real ADS-B trajectory dataset. The experimental results demonstrate that the proposed method significantly outperforms comparative approaches in terms of trajectory estimation accuracy.

Detecting Land-Use Changes in Greater Kandy Development Area

As urban growth became a threat to Kandy city, the Urban Development Authority (UDA) has introduced a new concept called the “Greater Kandy Development Area (GKDA)” to control and manage the rapid urban growth, as well as to minimize its’ impacts towards the environment. This study examines the land use/ land cover changes in GKDA, in selected time periods using GIS and Remote Sensing techniques. Findings demonstrate that dynamic patterns of urban expansion cause progressive growth in built-ups and lowering in non-built-ups. In 2005, there were only 16.9 percent of built-up areas in GKDA but, it has increased up to 40 percent in 2020. 81.7 percent of non-built-up areas in 2005, has reduced up to 58.8 percent. As population growth happened inside the city limits, land use changes also happened within. These changes create clustered as well as sprawl development patterns.

The impact of global and regional challenges on the decrease in tourist flows

The article presents a comprehensive analysis of the impact of global and regional events on the dynamics of tourist flows. The primary reasons for the decrease in inbound tourist flows have been identified and categorized into three main groups: military-political class, economic class, and natural-technological class. Additionally, a hybrid class was identified, to which COVID-19 was assigned. The article is based on causal and comparative analysis, utilizing statistical data on tourist flows provided by the World Bank and UNWTO, as well as an assessment of similar patterns among countries worldwide. The main characteristics of tourist flows from 1995 to 2022 have been identified, pinpointing leaders among countries in increasing and decreasing the number of tourists per year. During the study, countries with similar patterns of tourist flow dynamics were identified. It was concluded that relying solely on quantitative analysis has limited applicability in identifying these patterns. Therefore, it is recommended that quantitative analysis be complemented with expert assessments for a more comprehensive understanding. The basic strategies for responding to the identified classes of causes were outlined. The research will benefit tourism professionals, governmental authorities, and researchers in socio-economic and political disciplines.

China’s Governance in the “New Era” of Xi Jinping

The dramatic shifts in policies and practices of the People’s Republic of China (PRC) over the course of its tumultuous 75-year history underscore the decisive importance of political leadership. Institutionally, China closely resembles other former and surviving Communist regimes. Operationally, however, its dynamic patterns of governance reflect the shifting concerns of a succession of visionary Communist Party leaders.

Seismic Response of Foundation Settlement for Liquid Storage Structure in Collapsible Loess Areas

To investigate the impact of foundation settlement in loess areas on the dynamic response of liquid storage structure (LSS) under seismic motion, a finite element analysis model of the liquid–solid coupling of LSS was established using ADINA V9.6 software. By analyzing the dynamic response patterns of LSS under seismic motion with foundation failure, this study examines the effects of foundation failure and the direction of seismic wave incidence on the equivalent stress, maximum shear stress, wall displacement, and liquid sloshing wave height of the structure. The results indicate that among the three foundation failure scenarios, foundation failure at the center of the tank bottom has the least impact on the structural dynamic response. In contrast, foundation failure affecting one-fourth of the tank base has the greatest impact. Furthermore, compared to seismic motion along the X-axis, the dynamic response of the structure is more significantly affected when seismic motion co-occurs along the X-Z-axis.

Simulation of special-shaped graded particulate hydraulic transport in deep-sea mining scenarios

Hydrodynamic transport is crucial in deep-sea mining engineering for conveying materials. This study investigates the impact of various particle shapes on slurry transport efficiency and flow characteristics at higher concentrations. A numerical method combining computational fluid dynamics (CFD) and the discrete element method (DEM) within the Euler-Lagrange framework is employed to simulate the flow and hydrodynamic properties of graded heterogeneous coarse particles in a deep-sea hydraulic lift pipe. The reliability of the simulations is verified through comparisons, focusing on feed concentration and particle gradation effects on dynamic characteristics and flow patterns. The study quantitatively analyzes concentration distributions under various flow regimes for different particle shapes and conveying concentrations in a vertical pipeline system. Flow characteristics under clogging conditions are described, considering flow transition and concentration distribution. Additionally, conditions for stable transportation are discussed concerning particle forces and transport reliability.

Orthographic character complexity modulates dynamic neural activity in skilled handwriting.

Handwriting is an outstanding case of a highly complex and efficient fine motor skill. However, little is known about its neural underpinnings during continuous handwriting production. In the present study, we examined the effects of orthographic character complexity (i.e. the stroke number of a Chinese character) on both neural and behavioural activities during an EEG-based naturalistic fluent sentence-handwriting task from 102 adult Chinese native speakers. For each written character, the interval between finishing the preceding character and its onset (inter-character interval) as well as the amplitudes of the onset-synchronized event-related potential (ERP) in pre- and post-onset time windows was defined as dependent variables. The effects of character complexity and other confounding factors were analysed with linear mixed models. Character complexity increased the inter-character interval and significantly affected ERP amplitudes in both pre- and post-onset time windows. The ERP pattern in the pre-event time window exhibited a dipole-like activation in the left motor cortex, and its amplitude increased with character complexity in line with the documented relationship between the lateralized readiness potential and motor complexity. This study demonstrates the feasibility of studying neurocognitive processes in complex naturalistic motor tasks and extends our knowledge about the dynamic pattern of handwriting-related neural activities.

Complex nonlinear dynamics of a multidirectional energy harvester with hybrid transduction

Abstract Mechanical energy harvesting has increasing scientific and technological interests due to novel energetic challenges. A critical issue in classical cantilever-based mechanical energy harvesting systems is the lack of multidirectional energy conversion capabilities and, due to that, deviations from the excitation source can drastically reduce their performance. This limitation has led to the development of energy harvesters with attached pendula, serving as a direction coupling mechanism. Nevertheless, the pendulum structure itself can act as an energy absorber, drastically reducing the harvester performance in certain scenarios. In order to overcome this issue, a hybrid transduction multidirectional pendulum-based energy harvester is proposed integrating a piezoelectric element, to capture energy from the principal direction, and an electromagnetic transducer, to harness rotational energy from the pendulum. This paper presents an in-depth analysis of the hybrid multidirectional pendulum-based energy harvester using a nonlinear dynamics perspective to evaluate the energy harvesting performance. A reduced-order model is proposed to represent the essential characteristics of such systems. A parametric analysis using a nonlinear dynamics perspective is carried out to map the system dynamics and performance. The emergence of complex and rich dynamics is observed, including chaos and hyperchaos. Results reveal the most and least effective combinations of structural parameters in terms of energy conversion. Additionally, the dynamical responses and patterns associated with high performance are identified. These responses are often characterized by a blend of irregular complex behaviors, coupled with a mix of oscillatory and rotational patterns of motion, resulting in wider bandwidth systems.

Extinction Dynamics and Equilibrium Patterns in Stochastic Epidemic Model for Norovirus: Role of Temporal Immunity and Generalized Incidence Rates

Norovirus is a leading global cause of viral gastroenteritis, significantly affecting mortality, morbidity, and healthcare costs. This paper develops and analyzes a stochastic SEIQR epidemic model for norovirus dynamics, incorporating temporal immunity and a generalized incidence rate. The model is proven to have a unique positive global solution, with extinction conditions explored. Using Khasminskii’s method, the model’s ergodicity and equilibrium distribution are investigated, demonstrating a unique ergodic stationary distribution when R^s>1. Extinction occurs when R0E<1. Computer simulations confirm that noise level significantly influences epidemic spread.

Tunnel motion: Pupil dilations to optic flow within illusory dark holes.

We showed to the same observers both dynamic and static 2D patterns that can both evoke distinctive perceptions of motion or optic flow, as if moving in a tunnel or into a dark hole. At all times pupil diameters were monitored with an infrared eye tracker. We found a converging set of results indicating stronger pupil dilations to expansive growth of shapes or optic flows evoking a forward motion into a dark tunnel. Multiple regression analyses showed that the pupil responses to the illusory expanding black holes of static patterns were predicted by the individuals' pupil response to optic flows showing spiraling motion or "free fall" into a black hole. Also, individuals' pupil responses to spiraling motion into dark tunnels predicted the individuals' sense of illusory expansion with the static, illusory expanding, dark holes. This correspondence across individuals between their pupil responses to both dynamic and static, illusory expanding, holes suggests that these percepts reflect a common perceptual mechanism, deriving motion from 2D scenes, and that the observers' pupil adjustments reflect the direction and strength of motion they perceive and the expected outcome of an increase in darkness.

A dynamic electric fence planning framework for dockless bike-sharing systems based on inventory prediction

While dockless bike-sharing systems are growing in popularity due to their convenience, indiscriminate parking creates disorder in cities. To address this problem, this paper proposes a novel prediction-based approach for planning dynamic electric fences. These fences can adapt to dynamic usage patterns and efficiently guide parking behavior. First, graded clustering and spatial point integration algorithms are used to determine the locations of electric fence candidates. Second, initial parking and scheduling simulations are developed to calculate the inventory of each candidate. Finally, a spatiotemporal graph neural network is utilized to predict inventory and generate real-time deployment plans for electric fences. Case studies are conducted in two regions in Shanghai, China. Compared to a non-electric fence scenario, extensive experiments show that our framework can satisfy 98.6% of the parking demand and reduce spatial entropy by 15% within a reasonable walking distance. The results contribute to improving urban orderliness and promoting the sustainability of bike-sharing systems.

Debt Dynamics and Investment Patterns: Public Debt-Investment Nexus in G7 and ASEAN Economies

Debt Dynamics and Investment Patterns: Public Debt-Investment Nexus in G7 and ASEAN Economies

Integrated assessment of simultaneous threshold exceedance of heat, air pollution and airborne allergenic pollen across Europe

BackgroundClimate change is expected to elevate exposure to several environmental health risk factors, including extreme environmental temperatures, air pollution and airborne allergenic pollen. Given their interconnected effects on respiratory and cardiovascular diseases, it is crucial to evaluate these exposures simultaneously. Yet, comprehensive efforts to do so remain limited. This research aims to develop an approach using modelled data, in conjunction with health-based threshold values, to assess whether, where and when there is simultaneous threshold exceedance of heat, air pollution and airborne allergenic pollen in Europe. MethodsHourly exposure data for the three stressors were sourced from three models (air pollution: LOTOS-EUROS, pollen: Copernicus Atmosphere Monitoring Service, meteorological conditions: ECMWF) for 2021 and 2022. Thresholds for each stressor that indicate the boundary of acceptable limits were based on officially established tresholds or literature recommendations. The result is a 0.1°x0.1° resolution grid (approximately 10 km x 10 km) for each stressor, with each cell representing whether exposure met or exceeded the threshold. FindingsSimultaneous threshold exceedance of air pollution and heat is occurring in various degrees throughout Europe. In the summer of 2022, the exceedances ranged from below 1% in large parts of Northern Europe to as much as 25% of the time in the Mediterranean area. An assessment of monthly threshold exceedance patterns shows a dynamic and changing co-exposure pattern across the year, which differs per region. InterpretationThis work lays out a robust approach to assess simultaneous threshold exceedances of multiple environmental health risk stressors. This approach can guide policy makers in pinpointing high-risk areas particularly vulnerable to simultaneous threshold exceedances, and develop mitigation strategies for those areas. FundingInternal funding from TNO.

Three-dimensional physical experimental study on mechanisms and influencing factors of CO2 huff-n-puff and flooding process in shale reservoirs after fracturing

Carbon dioxide (CO2) capture and geological storage technology is a promising strategy for enhancing oil and gas production and mitigating climate change in unconventional formations. In shale reservoirs, production decline is rapid under volumetric fracturing development. Currently, CO2 injection and huff-n-puff techniques are cost-effective methods to boost shale oil recovery. However, traditional huff-n-puff techniques are limited in capturing reservoir heterogeneity and intricate fracture conditions. This study employed a three-dimensional physical experimental apparatus to explore CO₂ huff-n-puff dynamics across six distinct fracture patterns. By implementing a real-time monitoring system with multiple pressure points, the study elucidated the impacts of varying fracture penetration levels and spacing on dynamic pressure wave patterns, mobilization extent, and development outcomes during CO2 huff-n-puff. The results demonstrate that fractures substantially improve CO₂ huff-n-puff efficiency in shale reservoirs compared to a seamless model, with Model 6 achieving the highest recovery rate of 42.38%. As fracture penetration increases, CO₂ dynamic coverage expands. However, full penetration leads to preferential flow through fractures, reducing matrix contact and diminishing huff-n-puff efficiency. Reduced fracture spacing enlarges the well's control domain, amplifies CO2 huff-n-puff dynamic coverage area, and increases oil production and recovery rate. Conversely, decreasing fracture spacing accelerates oil and gas displacement rates, leading to higher economic expenses. The study concludes that 2/3 fracture penetration in five fractures offers the most efficient recovery method. For a 500 m horizontal well, optimal fracture spacing is recommended at 125 m, with a fracture length of 145.8 m for a well spacing of 417 m.

Longitudinal biomonitoring of mycotoxin exposure during pregnancy in the Yale pregnancy Outcome Prediction study

Mycotoxins are fungal toxins that may trigger adverse health effects in pregnant women and their unborn children. Yet, data is scarce on the dynamic exposure patterns of mycotoxins in pregnant women, especially in the United States. This study assessed mycotoxin exposure profiles (n = 50) from the Yale Pregnancy Outcome Prediction Study (YPOPS) cohort at four distinct time points. Multi-analyte human biomonitoring (HBM) assays based on liquid chromatography tandem mass spectrometry (LC-MS/MS), were developed for human serum and plasma matrices. The serum method was applied, together with an established urine method, to quantify mycotoxin levels in longitudinally collected matched serum (n = 200) and spot urine (n = 200) samples throughout pregnancy. The serum samples were mostly contaminated by the potential carcinogen ochratoxin A (detection rate: 49 %; median: 0.09 ng/mL), the hepato- and nephrotoxic citrinin (detection rate: 32 %; median: 0.02 ng/mL) and two enniatins (EnnB; detection rate: 97 %; median: 0.01 ng/mL and EnnB1; detection rate: 12 %; median: 0.003 ng/mL) which may act as immunotoxins. The most prevalent mycotoxins quantified in urine included deoxynivalenol (detection rate: 99 %; median: 23 ng/mL), alternariol monomethyl ether (detection rate: 69 %; median: 0.04 ng/mL), and zearalenone (detection rate: 63 %; median: 0.16 ng/mL). Seven other biomarkers of exposure including the highly estrogenic α-zearalenol and genotoxic Alternaria toxins, were also determined. Carcinogenic aflatoxins were not detected in any of the samples. Exposure assessment was based on the urinary data and performed by calculating the probable daily intakes (PDIs) and comparing the human biomonitoring guidance value (HBM-GV) for deoxynivalenol. The results showed that the individuals exceeded the tolerable daily intake (TDI) for deoxynivalenol and zearalenone on average at 28 % and 2 % over the different time points. Using the HBM-GV approach, the average exceedances for deoxynivalenol increased to 48 % indicating high exposure. For all the samples in which ochratoxin A was quantified, the estimated margin of exposure for neoplastic effects was below 10,000, indicating possible health concerns. Overall, this study showed that pregnant women were exposed to several regulated and emerging mycotoxins and that exposome-scale assessment should be a future priority in susceptible populations to better characterize xenobiotic exposure.

The spatio-temporal dynamic evolution and variability pattern of urban green resilience in China based on multi-criteria decision-making

The spatio-temporal dynamic evolution and variability pattern of urban green resilience in China based on multi-criteria decision-making

Profiling Dynamic Patterns of Single-Cell Motility.

Cell motility plays an essential role in many biological processes as cells move and interact within their local microenvironments. Current methods for quantifying cell motility typically involve tracking individual cells over time, but the results are often presented as averaged values across cell populations. While informative, these ensemble approaches have limitations in assessing cellular heterogeneity and identifying generalizable patterns of single-cell behaviors, at baseline and in response to perturbations. In this study, CaMI is introduced, a computational framework designed to leverage the single-cell nature of motility data. CaMI identifies and classifies distinct spatio-temporal behaviors of individual cells, enabling robust classification of single-cell motility patterns in a large dataset (n = 74253 cells). This framework allows quantification of spatial and temporal heterogeneities, determination of single-cell motility behaviors across various biological conditions and provides a visualization scheme for direct interpretation of dynamic cell behaviors. Importantly, CaMI reveals insights that conventional cell motility analyses may overlook, showcasing its utility in uncovering robust biological insights. Together, a multivariate framework is presented to classify emergent patterns of single-cell motility, emphasizing the critical role of cellular heterogeneity in shaping cell behaviors across populations.

Temporal dynamics of protist communities and environmental factors in the horizontal flow-polyculture pond aquaculture model of Sinonovacula constricta

The horizontal flow (HF)–polyculture pond (PP) model has emerged as a new aquaculture model that has attracted considerable attention. The growth of Sinonovacula constricta in the HF is highly dependent on phytoplankton in the PP; however, the current understanding of the basic microbes in the HF-PP model research remains insufficient. To address this knowledge gap, we analyzed the temporal dynamics of protist communities in water and sediment samples obtained from the HF and PP in this study. In addition, we measured the temporal variations in physicochemical factors in these water and sediment samples. A comparison of water quality data between HF and PP revealed that HF effectively reduced the total nitrogen (TN) and total phosphorus (TP) levels in the polyculture ponds. Furthermore, Diatomea and Ciliophora were the predominant phyla in all samples. In the horizontal-flow water samples, significant alterations were observed over time in Skeletonema, Strombidium, and Gyrodinium genera. The dynamic pattern of the genus in the polyculture pond water (PPW) was similar to that in the horizontal flow water (HFW). Furthermore, Skeletonema abundance decreased over time in the horizontal flow sediment (HFS). Skeletonema and Cyclotella were dominant in polyculture pond sediment (PPS). There was a certain degree of community succession throughout the experiment in the HFW and PPW, but not in the HFS or PPS. Correlation analysis revealed that water temperature (WT), salinity(SAL)，dissolved oxygen (DO), pH, phosphate, and silicate played key roles in driving variations in the protist community. These findings contribute to our understanding of complex protist community dynamics within the HF-PP aquaculture model, shedding light on the roles of various environmental factors in shaping protist communities and water quality.

Climate change reduces the tension of conflicting selection pressures on breeding date in a passerine bird.

Unpredictably fluctuating environments create complex selective landscapes that shape the distribution of key life history traits. Identifying the mechanisms behind dynamic patterns of selection is difficult, yet essential for predicting responses to climate change. We combine long-term measures with field manipulation of natural selection on breeding date in a wild bird to investigate whether highly variable spring cold snaps drive fluctuating selection. We show that variation in cold snap intensity leads to fluctuating selection on breeding date-in weak cold snap years, selection was consistently negative; however, in strong cold snap years, its direction reversed. These patterns were mirrored in a field experiment; nests that were food supplemented during cold snaps avoided cold snap mortality leading earlier breeders to have higher fitness. In contrast, in the non-supplemented group earlier breeders had higher cold snap nest mortality and selection was positive. Using nearly a century of climate data, we show that cold snaps are becoming less frequent and paradoxically occurring later which should allow earlier breeders to avoid them, potentially releasing conflicting selection pressures and facilitating a rapid phenological shift. Thus, rather than constraining a species' ability to adapt, climate change can enable a rapid shift to a new phenotypic optimum.

Radiation Pattern Analysis and Phase Shifter for Base Station Mobile Communication Circular Array Antenna at 900MHz Frequency by Using 4NEC2X Software

Background: This paper presents the utilization of phase shifters to manipulate and control the radiation patterns in Uniform Circular Array (UCA) antennas. UCAs, known for their 360-degree coverage and symmetrical radiation patterns, are enhanced by incorporating phase shifters, enabling dynamic beam steering and pattern shaping. Materials and Methods: A uniform circular antenna array operating at 900 GHz frequency has been intended for use in base stations using 4NEC2X simulation software. Results: A single-element dipole antenna having a 2.14 dBi gain is used as a base for constructing a uniform 0.5 λ spacing circular array. The number of elements gradually increased from 2 to 12, raising the gain to 12.3 dBi. HPBW decreased both in vertical and horizontal plans from 80o to 60o and 360o to 20o respectively this implies that the circular array antenna's directivity is enhanced. The eight-element array beam scanning was performed from 0o to 360o without any distortion in radiation pattern, gain, and directivity, contradictory with the linear array. Conclusions: The studied case and simulation output illustrate the impact of the element numbers and phase shifter configurations on properties of the radiation pattern of the uniform circular array can be obtained when increasing the number of elements, the gain increases too and scanning the main beam without any change and distortion