Migration Model Research Articles

Exploration of Art Digital Design Technology Guided by Visual Communication Elements

From the perspective of visual communication elements, this paper proposes a digital design composite model based on style migration, trying to explore and innovate art digital design technology. In the image recognition and style migration model, the attention mechanism is added on the basis of ResNet50 network model to enhance the image recognition effect, and on the basis of VGG19 deep convolutional network model and optimization algorithm to realize the image style migration technology and digital redesign. On the basis of the proposed style migration model, a graphic rendering model is further proposed by combining the GrabCut algorithm and the VGG16 neural network, so as to realize the local style migration of patterns. In the application analysis of the artistic digitization of Zhuang brocade lamps, for example, the total percentage of “very approved” and “more approved” in the assessment of the style migration effect is more than 30%, and the style migration effect is better. The average scores of the art design effect evaluation of layers, elements and color richness are 4.02, 4.15 and 4.31, which are all higher than 4 points, and the performance is good. It is also recognized by experts and ordinary respondents in the satisfaction evaluation of art design.

Interface migration and grain growth in NbC-Ni cemented carbides with secondary carbide addition

Cemented carbides are widely used for cutting and drilling tools. They usually combine a WC hard carbide phase and a Co-based ductile binder. NbC-Ni materials are considered as a possible alternative, especially for wear applications. The advantageous economic situation for raw materials sourcing, their interesting mechanical properties and low density have raised a new interest for these materials. However, mechanical properties can be limited by the rapid grain growth during liquid phase sintering, as compared to WC-Co. Grain growth can be controlled by the addition of secondary carbides. In this paper, a quantitative EBSD analysis of grain growth is performed for NbC-12 vol%Ni materials sintered at 1450 °C with controlled addition of Mo2C and WC. The average grain size decreases continuously with Mo2C addition. The results are discussed based on a more detailed interface characterization and on a previous model for the cooperative migration of phase boundaries and grain boundaries.

Moving motivated by work or proximity to family and labour market outcomes in the Netherlands

The classical human-capital model of migration posits that internal migration should lead to improved individual labour market outcomes. However, later empirical and theoretical work has emphasised that the outcomes of migration may be positive for some, but negative for others, depending on, for example, gender and the motive for moving. We investigate the labour market outcomes after moves motivated by work, moves motivated by proximity to family, and moves motivated by both work and family at the same time, compared with not moving. We use data from the Netherlands’ Housing Surveys of 2006, 2009, 2012, 2015, and 2018 matched with register data (N ~ 350,000 person-years). We find that men’s and women’s moves for work, and moves for both family and work, are positively associated with outcomes in terms of individual income, employment, and labour supply (hours worked). We do not find such positive associations for moves motivated by family proximity only, but we hardly find negative associations. We do not replicate the finding of previous research for Sweden that moves for family proximity were associated with an increased likelihood of transitions out of unemployment. However, we find some evidence that women’s moves motivated by both work and family proximity are associated with an increase in labour supply.

Modeling of plasma facing component erosion, impurity migration, dust transport and melting processes at JET-ILW

An overview of the modeling approaches, validation methods and recent main results of analysis and modeling activities related to the plasma-surface interaction (PSI) in JET-ILW experiments, including the recent H/D/T campaigns, is presented in this paper. Code applications to JET experiments improve general erosion/migration/retention prediction capabilities as well as various physics extensions, for instance a treatment of dust particles transport and a detailed description of melting and splashing of PFC induced by transient events at JET. 2D plasma edge transport codes like the SOLPS-ITER code as well as PSI codes are key to realistic description of relevant physical processes in power and particle exhaust. Validation of the PSI and edge transport models across JET experiments considering various effects (isotope effects, first wall geometry, including detailed 3D shaping of plasma-facing components, self-sputtering, thermo-forces, physical and chemically assisted physical sputtering formation of W and Be hydrides) is very important for predictive simulations of W and Be erosion and migration in ITER as well as for increasing quantitative credibility of the models. JET also presents a perfect test-bed for the investigation and modeling of melt material dynamics and its splashing and droplet ejection mechanisms. We attribute the second group of processes rather to transient events as for the steady state and, thus, treat those as independent additions outside the interplay with the first group.

The Development of a Biomimetic Model of Bacteria Migration on Indwelling Urinary Catheter Surfaces.

The aim of this study was to develop a novel biomimetic in vitro extraluminal migration model to observe the migration of bacteria along indwelling urinary catheters within the urethra and assess the efficacy of a prototype chlorhexidine diacetate (CHX) coating to prevent this migration. The in vitro urethra model utilised chromogenic agar. A catheter was inserted into each in vitro urethra. One side of the urethra was then inoculated with bacteria to replicate a contaminated urethral meatus. The models were then incubated for 30 days (d), with the migration distance recorded each day. Four indwelling catheter types were used to validate the in vitro urethra model and methodology. Using the biomimetic in vitro urethra model, E. coli and S. aureus migrated the entire length of a control catheter within 24-48 h (h). In the presence of a prototype CHX coating, full migration of the channel was prevented for 30 d. The results of this study support the hypothesis that catheter-associated urinary tract infections (CAUTIs) could be prevented by targeting catheter-mediated extraluminal microbial migration from outside of the urinary tract into the bladder.

Do illegal Migration Affect tourism Arrivals in Greece? A Vector Autoregression Analysis

Introduction: This paper explores the impact of illegal migration on the tourism sector in Greece. Utilizing a Vector autoregression (VAR) methodology, the research examines the relationship between the influx of illegal migrants and the number of tourist arrivals. The study presents the migration as a phenomenon that takes place dynamically the last decades in Europe in general and the Greek territory particular. By providing, empirical evidence on the short-term and long-term impacts of illegal migration on tourism in Greece, this study contributes to the broader discourse on migration and economic stability. The research's findings reveal that illegal migration does not significantly influence tourism arrivals in Greece. This indicates that tourists’ decisions to visit Greece are driven by factors other than concerns related to illegal migration. Objective: The objective of this study is to investigate the relationship between the influx of illegal migrants and the number of tourist arrivals Theoretical Framework: In this topic, the main concepts and theories that underpin the research are presented: the Model of cyclicity, Lee’s migration model. Method: The research examines the relationship between the influx of illegal migrants and the number of tourist arrivals over a specific period. The methodology used for this research is Vector autoregression analysis, with monthly data for the period January 2015 to December 2023. This analytical approach allows for the examination of the dynamic interactions and potential causality between the two variables over time. Results and Discussion: The results obtained revealed reveal that illegal migration does not significantly influence tourism arrivals in Greece. Changes in the number of migrants arriving do not predict changes in tourist arrivals, and changes in tourist arrivals do not predict the number of migrants arriving in Greece. The outcome is positive for the Greek tourism industry, which is of a great importance for the country’s GDP and employment politics. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of tourism. These implications could encompass the socio-economic sector of the country. Originality/Value: This study contributes to the literature by a vector autoregression analysis to the broader discourse on migration and economic stability. The relevance and value of this research are evidenced by the findings, that reveal that illegal migration does not significantly impact tourism arrivals in Greece. This indicates that tourists’ decisions to visit Greece are driven by factors other than concerns related to illegal migration.

Nonparametric estimation of the gravity model of migration: application of partitioning Poisson estimates to Japanese inter-municipal migration by age–sex group

Nonparametric estimation of the gravity model of migration: application of partitioning Poisson estimates to Japanese inter-municipal migration by age–sex group

Modeling of Microplastics Migration in Soil and Groundwater: Insights into Dispersion and Particle Property Effects.

Migration of microplastics (MPs) in soil-groundwater systems plays a pivotal role in determining its concentration in aquifers and future threats to the terrestrial environment, including human health. However, existing models employing an advection-dispersion equation are insufficient to incorporate the holistic mechanism of MP migration. Therefore, to bridge the gap associated with MP migration in soil-groundwater systems, a dispersion-drag force coupled model incorporating a drag force on MPs along with dispersion is developed and validated through existing laboratory and field-scale experiments. The inclusion of the MP dispersion notably increased the global maximum particle velocity (vmaxp) of MPs, resulting in a higher concentration of MPs in the aquifer, which is also established by sensitivity analysis of MP dispersion. Additionally, increasing irrigation flux and irrigation areas significantly accelerates MP migration downward from soil to deep saturated aquifers. Intriguingly, vmaxp of MPs exhibited a nonlinear relationship with MPs' sizes smaller than 20 μm reaching the highest value (=1.64 × 10-5 m/s) at a particle size of 8 μm, while a decreasing trend was identified for particle sizes ranging from 20 to 100 μm because of the hindered effect by porous media and the weaker effect of the drag force. Moreover, distinct behaviors were observed among different plastic types, with poly(vinyl chloride), characterized by the highest density, displaying the lowest vmaxp and minimal flux entering groundwater. Furthermore, the presence of a heterogeneous structure with lower hydraulic conductivity facilitated MP dispersion and promoted their migration in saturated aquifers. The findings shed light on effective strategies to mitigate the impact of MPs in aquifers, contributing valuable insights to the broader scientific fraternity.

Image style migration method based on transformer generative adversarial network combined with contrast learning strategy

Abstract Aiming at the problems of large loss of image patch embedding information and lack of stylized features in the generated image during transformer style migration, a style migration model combining contrast learning with transformer backbone generative adversarial network is established. Firstly, overlapping patch embedding is used to serialize the input images to get richer features; then the style and content contrast loss of contrast learning is used to mine the non-significant information between stylized images to reduce the style and content loss; finally, a multi-scale discriminator discriminates the true and false of stylized images to optimize the generator to get more stylistic features. The results on MS-COCO and WikiArt datasets show that the model improves the effectiveness and transformation efficacy of stylized images in style migration.

Detection of network false information based on artificial intelligence models

There is often some false information in social platforms to mislead public opinion. Due to the rapid development of the Internet, the spread of false information on the Internet has become easier, which has brought many losses to people's economy and life. In this paper, the relevant research on false information based on bidirectional convolutional networks is analyzed, and the method is divided into four stages: data preprocessing, model architecture, training process and prediction process. Then, the relevant research on rumor detection by propagation tree kernel model are analyzed. Finally, this paper delineates a comprehensive framework that amalgamates enhanced Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and a hybridized Black Widow Optimization (BWO) with Moth Optimization Algorithm (MOA) (referred to as HM-BWO) for the accurate detection of network-based false information. This paper analyzes and discusses the challenges of poor universality and insufficient detection speed encountered by the current rumor detection research and puts forward the idea of introducing migration model to solve the problem of poor universality and Spark to solve the problem of insufficient detection speed. This article provides a good overview of the field of online disinformation.

Spatiotemporal variations and driving factors of farmland soil organic carbon in various landforms of a complex topography

Estimating the spatiotemporal variations and driving factors of farmland soil organic carbon density (SOCD) is of great significance for enhancing soil carbon sequestration capacity. Herein, a large region of complex topography was targeted, which includes hill–mountain, valley–basin, and plain–platform. Based on the massive amounts of sampling data (57,254 measured values) and a large-scale soil map of 1:10,000 (371,976 polygonal patches), the gravity center migration model and gray correlation model were used to quantify the spatiotemporal variations and driving factors of farmland SOCD. The results indicated that the farmland soils in the study area had dual functions of carbon source and sink during 1982–2018, of which 45.50 % and 54.50 % were identified as carbon source and sink, respectively. Specifically, the SOCD for the entire study area, its hill–mountain, and valley–basin increased from 2.79 kg m−2, 2.97 kg m−2, and 3.06 kg m−2 to 2.87 kg m−2, 3.06 kg m−2, and 3.14 kg m−2, respectively, with 0.08 kg m−2 carbon sequestrations and a northeast migration direction for the SOCD gravity center (angle: 21.94°, 23.56°, and 18.82°; distance: 1.56 km, 2.73 km, and 3.20 km). There was a smaller increase of 0.07 kg m−2 in SOCD for the plain–platform from 2.38 kg m−2 (1982) to 2.45 kg m−2 (2018), and the SOCD gravity center migrated to the southwest with an angle of −172.46° and a distance of 1.84 km. Thus, the spatiotemporal variations of farmland SOCD in various landforms varied greatly. Over the past 36 years, SOCD variations were driven by a combination of intrinsic soil factors and external factors such as human disturbance. However, the driving effects of these factors on the landforms of hill–mountain, valley–basin, and plain–platform were quite different in size and order. Therefore, we suggest that topography must be considered when formulating policies to improve soil carbon sequestration, and priority should be given to landform-specific SOCD variation and the factors contributing to them.

Searching for the grand tack in exoplanetary data

The grand tack model, more generally called the Masset and Snellgrove mechanism, is a planetary migration model whereby two giant planets via interactions with their natal disk migrated to larger orbital radii. While its relevance in our own Solar System remains in question, the fact that the Masset and Snellgrove mechanism is a general hydrodynamical effect implies that it may have occurred in another planetary system. In this study I searched through exoplanet data for evidence of the Masset and Snellgrove mechanism, which requires that (1) the inner of the two planets is more massive than the outer planet; (2) the planets are sufficiently massive that their gravity-induced gap overlaps; and (3) they orbit at sufficiently close radii that their co-rotation regions also overlap. The last two requirements are met when the planets orbit with a 3:2 mean motion resonance. I do not find conclusive evidence for a grand tack-like system, but find some evidence for planet formation at the edge of a planet-induced protoplanetary disk gap in three systems.

Study on the temperature field and infrared characteristics of unsaturated soils with shallow buried objects at different depths

Beneath the soil, there exist numerous concealed objects, some of which, like landmines, pose a considerable threat to human life. Infrared detection serves as a swift and secure method for detecting such hazards. However, in many current studies, the soil is often oversimplified as a single entity, overlooking the crucial internal moisture transport and phase transitions. In this paper, we propose a soil heat and moisture migration model, along with a ground infrared radiation model. Our comparisons with previous research reveal that the internal water movement, evaporation, and condensation processes in the soil have a profound influence on the soil's temperature field and infrared signature. To validate our model's reliability, we conducted three experiments with metal blocks buried 1 cm deep, having initial moisture contents of 0 %, 10 % and 20 %. A comparison of the simulation and experimental results confirms the credibility of our proposed model. Through simulations, we analyzed the daily variations in ground surface IR radiation, the effect of varying burial depths, and the influence of differing initial moisture contents. Our findings reveal that, when starting with zero initial soil moisture content, an increase in burial depth from 1 cm to 5 cm results in a substantial decrease in the peak difference between the surface center temperature and ambient temperature, dropping from 20.91 K to 5.35 K. Consequently, the optimal detection time shifts from 12:00 to 14:00 On the other hand, keeping the burial depth constant at 1 cm and increasing the initial soil moisture content from 5 % to 20 % leads to a reduction in the maximum temperature difference from 17.54 K to 12.48 K, while the optimal detection time remains unaffected. This study can provide data support for underground buried object detection and improve the accuracy of detection.

Kisspeptin expression levels in patients with placenta previa: A randomized trial.

This study aimed to explore the potential influence of kisspeptin (KISS1) levels on the etiology of placenta previa for early pregnancy diagnosis. The study included 20 pregnant women diagnosed with placenta previa and 20 pregnant woman with normal pregnancies between 2021 and 2022. Plasma KISS1 levels were determined through biochemical analysis, while genetic analysis assessed KISS1 and KISS1 receptor gene expression levels. Immunohistochemical methods were employed to determine placenta KISS1 levels. The evaluation of KISS1 concentration in serum revealed a significant decrease in the placenta previa group compared to the control group (P < .001). KISS1 gene expression level 0.043-fold decreased in the placenta previa group (P < .001). Furthermore, the KISS1 receptor gene expression level increased 170-fold in the placenta previa group. Results from biochemical, immunohistochemical, and genetic analyses consistently indicated significantly reduced KISS1 expression in patients with placenta previa. These findings suggest a potential link between diminished KISS1 levels and the occurrence of placenta previa. KISS1 may play a critical role in the etiology of placenta previa. Detailed studies on angiogenesis, cell migration and tissue modeling should be conducted to understand possible mechanisms.

N6-methyladenosine modification of circMARK2 enhances cytoplasmic export and stabilizes LIN28B, contributing to the progression of Wilms tumor

BackgroundThe potential involvement of circular RNAs (circRNAs) and N6-methyladenosine (m6A) modification in the progression of Wilms tumor (WT) has not been fully elucidated. This study investigates the regulatory mechanisms and clinical significance of m6A-modified circMARK2 and its role in WT progression.MethodsWe identified dysregulated circRNAs through deep sequencing and validated their expression by qRT-PCR in WT tissues. The biological functions of circMARK2 were assessed using clone formation, transwell migration, and orthotopic animal models. To dissect the underlying mechanisms, we employed RNA immunoprecipitation, RNA pull-down, dual-luciferase reporter assays, Western blotting, and immunofluorescence and immunohistochemical staining.ResultsCircMARK2, upregulated in WT tissues, was found to be m6A-modified and promoted cytoplasmic export. It facilitated WT progression by stabilizing LIN28B mRNA through the circMARK2/IGF2BP2 interaction. In vitro and in vivo studies demonstrated that circMARK2 enhances the malignant behavior of WT cells. Clinically, higher circMARK2 levels in tumor tissues of WT patients were linked to increased tumor aggressiveness and reduced survival rates.ConclusionsOur study provides the first comprehensive evidence that m6A-modified circMARK2 contributes to WT progression by enhancing LIN28B mRNA stability, promoting cellular aggressiveness. CircMARK2 emerges as a potential biomarker for prognosis and a promising target for therapeutic intervention in WT, underscoring the clinical relevance of m6A modification in pediatric renal cancer.

Assessment of chemical risks and circular economy implications of recycled PET in food packaging with functional barriers

In response to regulatory demands for sustainable practices, there has been a significant increase in the use of recycled materials in food packaging, particularly when incorporated behind functional barriers. This study, conducted as part of the “ABA Modeling” project, evaluates the migration of contaminants from the non-decontaminated, recycled polyethylene terephthalate (rPET) B-layer, which is sandwiched between two virgin A-layers in three-layer trays. The study aims to assess the long-term implications for food safety within the context of the European and French circular economy frameworks. Using a migration modeling approach based on “worst-case” scenarios for ten contaminants – similar to methodologies employed for decontaminated direct food contact PET – the levels of chemical residues are analyzed and compared. Findings highlight the significant impact of the co-extrusion process on the suitability of rPET for food contact. Additionally, the study discusses the risks and challenges for the recycling sector, particularly in managing chemical contamination during mechanical recycling. Recommendations are provided to improve industrial practices, emphasizing the importance of ongoing monitoring to ensure the long-term sustainability of these recycling practices.

The complex network patterns of human migration at different geographical scales: network science meets regression analysis

Migration’s influence in shaping population dynamics in times of impending climate and population crises exposes its crucial role in upholding societal cohesion. As migration impacts virtually all aspects of life, it continues to require attention across scientific disciplines. This study aims to bridge the gap between theoretical understanding and practical application by integrating network analysis and regression methodologies within Migration Studies. In the study we employ network analysis to elucidate migration patterns at various geographical scales-city, country, and global. Additionally, regression analysis is discussed on an exploratory level, where we focus on the underlying factors driving migration, and identifying the key independent variables to enhance predictive accuracy. The study exposes distinct migration network structure and its features, and the consequences these have on conventional regression analysis applications. We conclude on the importance of methodological coherence and disciplinary integration, and highlight the avenues for enhancing the predictive power of migration models.

Evolution and Drivers of Production Patterns of Major Crops in Jilin Province, China

Exploring the evolution of the production patterns of major crops and their driving factors can provide new ideas to ensure the security of supply of important agricultural products. This study selected four major crop types in Jilin Province—grain, oil crop, vegetable, and fruit—as research subjects. Using the center of gravity migration model, spatial autocorrelation analysis, and comparative advantage index, the spatial and temporal evolution of these crops’ production patterns from 2000 to 2020 was examined. A geographically weighted regression model was employed to analyze driving factors. The results showed that the planting area of grain was the most extensive; the percentage of production of grain, oil crop, and fruit increased to different degrees; the unit area yield of the four crops increased. The centers of gravity of all four crops’ productions were located in the central-northwestern region of Jilin Province. The global Moran’s I was positive for all four crops’ productions. The comparative advantage characteristics of the four crops were closely related to the natural geographical environment. Grain, vegetable, and fruit production were significantly and positively correlated with fertilizer application, and the most significant factor affecting oil crop production was land input intensity.

Active gel model for one-dimensional cell migration coupling actin flow and adhesion dynamics

Migration of animal cells is based on the interplay between actin polymerization at the front, adhesion along the cell-substrate interface, and actomyosin contractility at the back. Active gel theory has been used before to demonstrate that actomyosin contractility is sufficient for polarization and self-sustained cell migration in the absence of external cues, but did not consider the dynamics of adhesion. Likewise, migration models based on the mechanosensitive dynamics of adhesion receptors usually do not include the global dynamics of intracellular flow. Here we show that both aspects can be combined in a minimal active gel model for one-dimensional cell migration with dynamic adhesion. This model demonstrates that load sharing between the adhesion receptors leads to symmetry breaking, with stronger adhesion at the front, and that bistability of migration arises for intermediate adhesiveness. Local variations in adhesiveness are sufficient to switch between sessile and motile states, in qualitative agreement with experiments.

Near-surface velocity inversion and modeling method based on surface waves in petroleum exploration: a case study from Qaidam Basin, China

Surface waves are widely used in the study of underground structures at various scales because of their dispersion characteristics in layered media. Whether in natural seismology or engineering seismology, surface wave analysis methods have matured and developed for their respective fields. However, in oil and gas exploration, many data processors still tend to consider surface waves as noise that needs to be removed. To make more people pay attention to the application of surface waves and widely utilize surface waves carrying the near surface information in oil and gas exploration, this paper takes the data processing of LH site in Qinghai, China as an example to apply surface wave analysis methods to oil and gas exploration. We first preprocess and perform dispersion imaging method on the seismic record in the LH site to obtain frequency-phase velocity spectrum with good resolution and signal-to-noise ratio. Then, utilizing clustering algorithms, it automatically identifies and picks dispersion curves. Finally, through a simultaneous inversion algorithm of velocity and thickness, it inverts the dispersion curves and obtain S-wave velocity profiles in the depth range of 0–200 m. The near surface is divided into four zones based on velocity ranges and depth ranges. Additionally, we apply the surface waves inversion results as constraints to first-arrival tomography and obtain objectively accurate P-wave velocity profiles and Poisson’s ratio profiles. The results indicate that by applying surface wave analysis methods, the near surface velocity information carried by surface waves can be extracted, providing near surface velocity models for static correction and migration. At the same time, compared with the surface wave application in engineering seismology, the scale of oil and gas exploration is larger, so that the data processing of surface waves is particularly important, otherwise it will affect the picking of the dispersion curve and inversion.