Migration Model Research Articles

Optimizing Environmental Parameters with Intelligent Systems to Enhance Prawn Survival

This study investigated factors influencing low survival rates of Pacific white shrimp post-larvae (PSL) from hatching to nauplii stage. Particle swarm optimization (PSO) and fuzzy analytic hierarchy process (FAHP) were applied to PSL migration modeling and environmental optimization. PSO simulated nauplii movement towards optimal feeds. FAHP assessed growth based on weighted variables across four ponds. Results demonstrated balancing nutrient diet, temperature, pH, salinity, minerals, and technical pond requirements minimized nauplii distraction and maximized PSL yields. However, birth and mortality imbalances persist, motivating further intelligent optimization to enhance blue economy sustainability and profits. PSO is the only one that can provides the intelligent system about PSL best location, guides about directions, feeds, chemicals and temperature. The proposed system adopts particle PSL characteristics such position, velocity, cost, ideal position, and optimal cost position. The PSL as a particle velocity equation shows the relationship between particle velocity and the best cost of nature. The outcome of the system depicts successful PSL. Additional research is needed to elucidate primary causes of nauplii and PSL mortality during early development.

Numerical Modelling of Radionuclide Migration for the Underground Silo at Near-Field

Numerical Modelling of Radionuclide Migration for the Underground Silo at Near-Field

Spatiotemporal change in vegetation cover in the Yellow River Basin between 2000 and 2022 and driving forces analysis

In this paper, we investigate the features of spatiotemporal change in fractional vegetation cover (FVC) throughout the Yellow River Basin between 2000 and 2022 and identify the driving factors behind the change using the MODIS normalized difference vegetation index (NDVI) as a data source. On that basis, our research involves trend analysis and the center migration model to examine the correlation between vegetation cover changes and various factors, such as climates, topographies, soils, and human activities. In this way, we aim to uncover how such correlation contributed to the reduction in suspended sediment concentration (SSC) in surface runoff. Results suggest that (1) the FVC of the Yellow River Basin has been trending upward over the past 23 years, and vegetation growth has been remarkably improved; (2) the center of medium-high and denser vegetation cover has progressively migrated from the upper reaches of the Yellow River down to its middle-lower segments; (3) soil erosion control measures are critical to improve vegetation cover, given the great impact of the shifting natural elements on vegetation cover changes on a local basis; (4) an improvement in vegetation cover leads to considerable positive change in the runoff and SSC of the Yellow River mainstem. This study has yielded noteworthy contributions in correctly understanding the current vegetation changes and related factors in the Yellow River Basin. Furthermore, it has laid the groundwork for further research in improving the accuracy of basic data and deepening the correlation between factors.

Machine learning prediction of pyrolytic sulfur migration based on coal compositions

Understanding the sulfur migration during pyrolysis of coals especially high-sulfur coals is important. However, structural complexity and diversity of coals make it face huge challenge. In this study, a predictive model for morphological sulfur migration was developed using machine learning based on proximate analysis, ultimate analysis, sulfur forms of raw coal, ash composition, and blending ratio of coal. Three algorithms, i.e., Random Forest, XGBoost, and LightGBM were introduced and compared. The results show that six features are sufficient to accurately predict the products (R2 > 0.9, RMSE < 3.01%). LightGBM model has the advantages of better accuracy, generalization, efficiency, and performance, and Hyperopt has a higher upper limit than Grid-search. H content has a significant effect on S content in chars (St,dchar) and increasing H content from 5.0–5.3 wt% facilitates desulfurization. In addition, CaO, K2O and Fe2O3 also have remarkable effects on St,dchar. Higher H and volatile contents have a greater effect on thiophene removal in char. This work can provide a new approach to explore the sulfur migration in coal blending for coking.

Spatiotemporal Characteristics of Actual Evapotranspiration Changes and Their Climatic Causes in China

As the main expenditure item in water balance, evapotranspiration has an important impact on the surface ecosystem. Assessing the impact of changes in meteorological elements on evapotranspiration is essential to identify the spatiotemporal heterogeneity of hydrographic responses to climate changes. Based on the actual evapotranspiration (ETa) product (GPR-ET) generated by Gaussian process regression (GPR), as well as temperature and precipitation datasets, our study employed various statistical analysis methods, including geographic detector, the center of gravity migration model, spatial variation coefficients, and partial differential models, to investigate the spatiotemporal variation in ETa in China from 2000 to 2018. The analysis covered future trends in ETa changes and the contribution of meteorological factors. Our results showed that the ETa in northwest China had stronger spatial heterogeneity and the mean value was generally lower than that in the southeast. But the center of gravity of ETa was shifting towards the northwest. In most areas, the future trend was expected to be inconsistent with the current stage. ETa in the regions of north and west was mainly driven by precipitation, while its increase in southeast China was largely attributed to temperature. In addition to spatial variations, the joint enhancement effect of temperature and precipitation on ETa exists. According to the contribution analysis, precipitation contributed more to the change in ETa than temperature. These findings have enhanced our comprehension of the contribution of climate variability to ETa changes, providing scientific proof for the optimization apportion of future water resources.

Integrating earthquake-based passive seismic methods in mineral exploration: Case study from the Gerolekas bauxite mining area, Greece

As the global need for aluminum constantly rises, bauxite is considered to be a critical mineral, and the mining industry is in search of new and effective exploration solutions. In this context, we design and implement a purely earthquake-based passive seismic survey at the Gerolekas bauxite mining site in Greece. It is a very difficult exploration setting, characterized by rough topography, limited accessibility, and a very complex geotectonic regime. We gather a passive seismic data set consisting of four months of continuous recordings (May to August 2018) from 129 stand-alone 3C seismological stations. We then analyze this data set and extract 848 microearthquakes that will serve as sources for the application of local earthquake tomography (LET) and transient-source seismic interferometry (TSI) by autocorrelation. We apply LET to estimate the 3D P- and S-wave velocity models of the subsurface below the study area and TSI by autocorrelation to retrieve the zero-offset virtual reflection responses below each of the recording stations. The velocity models provide a relatively coarse image of a previously completely unexplored part of the mining concession, whereas the higher-resolution virtual reflection imaging illuminates in detail the different interfaces. We also reprocess three lines of legacy active seismic data that were shot in 2003, using the LET P-wave velocity model for depth migration, and confirm the improvement of seismic imaging. Finally, we evaluate the obtained results using well data and jointly interpret them, extracting useful information on the expected target depths and indicating that earthquake-based passive seismic techniques can be an innovative and environmentally friendly option for mineral exploration.

Retracted: Sustainable Technical Debt-Aware Computing Model for Virtual Machine Migration (TD4VM) in IaaS Cloud

Retracted: Sustainable Technical Debt-Aware Computing Model for Virtual Machine Migration (TD4VM) in IaaS Cloud

A Stable Time-Dependent Mesh Method for Generalized Credit Rating Migration Problem

AbstractThe r-adaptive difference scheme is advanced in this article for solving the generalized credit rating migration model for arbitrary volatility with multiple terminal conditions. The r-adaptive moving mesh method defines the coordinate mapping from the physical to the computational domain and then uses piece-wise polynomials to approximate the physical coordinates. The central implicit semi-discretization scheme is imposed on space, and the backward Euler time marching scheme, coupled with several moving mesh partial differential equations, is used to achieve the numerical solution. The numerical operations are performed with several examples, and the obtained results are sufficiently accurate. The convergence of the proposed scheme is second-order, which is verified with the analysis. The article also investigates the stability and convergence of the adaptive mesh discretization scheme, which are not available in the literature; the convergence of the scheme is second-order in space and first-order in time.

An elastic framework construction method based on task migration in edge computing

AbstractEdge computing (EC) serves as an effective technology, empowering end‐users to attain high bandwidth and low latency by offloading tasks with high computational demands from mobile devices to edge servers. However, a major challenge arises when the processing load fluctuates continuously, leading to a performance bottleneck due to the inability to rescale edge node (EN) resources. To address this problem, the approach of task migration is introduced, and EN load prediction model, the resource constrained model, optimal communication overhead model, optimal task migration model, and energy consumption model are built to form a theoretical foundation from which to propose a task migration based resilient framework construction method in EC. With the aid of the domino effect and the combined effect of task migration, a dynamic node‐growing algorithm (DNGA) and a dynamic node‐shrinking algorithm (DNSA), both based on the task migration strategy, are proposed. Specifically, the DNGA smoothly expands the EN scale when the processing load increases, while the DNSA shrinks the EN scale when the processing load decreases. The experimental results show that for standard benchmarks deployed on an elastic framework, the proposed method realizes a smooth scaling mechanism in the EC, which reduces the latency and improves the reliability of data processing.

Composite Likelihood for Stochastic Migration Model with Unobserved Factor

Abstract We introduce the conditional maximum composite likelihood (MCL) estimation method for the stochastic factor ordered probit model of credit rating transitions of firms. This model is recommended for internal credit risk assessment procedures in banks and financial institutions under the Basel III regulations. Its exact likelihood function involves a high-dimensional integral, which can be approximated numerically before maximization. However, the estimated migration risk and required capital tend to be sensitive to the quality of this approximation, potentially leading to statistical regulatory arbitrage. The proposed conditional MCL estimator circumvents this problem and maximizes the composite log-likelihood of the factor ordered probit model. We present three conditional MCL estimators of different complexity and examine their consistency and asymptotic normality when n and T tend to infinity. The performance of these estimators at finite T is examined and compared with a granularity-based approach in a simulation study. The use of the MCL estimator is also illustrated in an empirical application.

Research on Spatial Migration Patterns and Influencing Factors of Western Talents: Based on Data from "Double first-class" Universities in China

The western region's talent loss issue has received widespread attention. Promoting the construction of human resources in the west has become key to forming an important high-quality development pole in western China. This study analyzes the graduate migration data of first-class universities in western China between 2016 and 2020 and draws the following conclusions: Overall, the retention rate of college graduates in western China across seven provinces is high, with a relatively higher retention rate observed in the place of study in four southwestern provinces. The retention rate of different provinces' place of study showed different trends during the period of 2016-2020, and the retention rate of different provinces also showed different trends during the same period. In 2020, western college graduates continued to show a preference for employment in popular provinces such as Guangdong, Beijing, and Shanghai, while they showed a greater inclination towards choosing employment opportunities in the South and Central regions of China. The results based on the directed migration model show that economic factors and natural and educational resources in a city have a greater impact on employment decisions. Analysis of heterogeneity found that graduates from areas with a high sticking rate are more susceptible to population size, human resources, and economic factors, and that cultural resources and transportation resources also have a significant impact on talent migration. Policy recommendations include western provinces taking higher education as a key factor to utilizing employment retention advantages to attract and retain high-quality talents.

Modeling of arsenic migration and emission characteristics in coal-fired power plants

After coal combustion, the minerals present in fly ash can adsorb arsenic (As) during flue gas cooling and reduce As emissions. However, a quantitative description of this adsorption behavior is lacking. Herein, the As adsorption characteristics of minerals (Al/Ca/Fe/K/Mg/Na/Si) were investigated, and a model was developed to predict As content in fly ash. Lab-scale experiments and density functional theory calculations were performed to obtain mineral As adsorption potential. Then, the model was established using lab-scale experimental data for 11 individual coals. The model was validated using lab-scale data from ten blended coals and demonstrated acceptable performance, with prediction errors of 2.83–11.45 %. The model was applied to a 350 MW coal-fired power plant (CFPP) with five blended coals, and As concentration in the flue gas was predicted from a mass balance perspective. The experimental and predicted As contents in fly ash were 11.92–16.15 and 9.61–12.55 μg/g, respectively, with a prediction error of 17.39–22.29 %, and those in flue gas were 11.52–16.58 and 5.37–34.04 μg/Nm3. Finally, As distribution in the CFPP was explored: 0.74–1.51 % in bottom ash, 74.05–82.70 % in electrostatic precipitator ash, 0.53–1.19 % in wet flue gas desulfurization liquid, and 0.13–0.73 % in flue gas at the stack inlet.

A non local model for cell migration in response to mechanical stimuli

Cell migration is one of the most studied phenomena in biology since it plays a fundamental role in many physiological and pathological processes such as morphogenesis, wound healing and tumorigenesis. In recent years, researchers have performed experiments showing that cells can migrate in response to mechanical stimuli of the substrate they adhere to. Motion towards regions of the substrate with higher stiffness is called durotaxis, while motion guided by the stress or the deformation of the substrate itself is called tensotaxis. Unlike chemotaxis (i.e. the motion in response to a chemical stimulus), these migratory processes are not yet fully understood from a biological point of view. In this respect, we present a mathematical model of single-cell migration in response to mechanical stimuli, in order to simulate these two processes. Specifically, the cell moves by changing its direction of polarization and its motility according to material properties of the substrate (e.g., stiffness) or in response to proper scalar measures of the substrate strain or stress. The equations of motion of the cell are non-local integro-differential equations, with the addition of a stochastic term to account for random Brownian motion. The mechanical stimulus to be integrated in the equations of motion is defined according to experimental measurements found in literature, in the case of durotaxis. Conversely, in the case of tensotaxis, substrate strain and stress are given by the solution of the mechanical problem, assuming that the extracellular matrix behaves as a hyperelastic Yeoh’s solid. In both cases, the proposed model is validated through numerical simulations that qualitatively reproduce different experimental scenarios.

Xenon behavior modeling for molten salt reactors by using multiple transport mechanisms

Molten Salt Reactor (MSR) is a liquid fueled reactor, in which the sparingly soluble fission gases including xenon continuously circulate with the fuel salt in the primary loop, and meanwhile are removed by helium bubbling. This unique operation feature introduces multiple mechanisms and in turn complicates the behavior of xenon, necessitating being accurately modeled. In this study, a migration model of 135Xe and 135mXe in the primary loop for MSR is established based on the equations that describe the nuclide concentration balance and mass transfer among the helium bubbles, fuel salt and graphite. The developed model is validated with the experimental data of Molten Salt Reactor Experiment (MSRE), and presents a better agreement compared with the previous xenon migration model. Sensitivity analysis of some key parameters including injected void fraction, bubble size, mass transfer coefficient, temperature and pressure, on the xenon poison under steady state are then analyzed. The results demonstrate that the injected void fraction, mass transfer coefficient and core operation pressure would impose a significant influence on the xenon poison, which should be paid particular attention in the core design and safety analysis.

Toward a Latinx Stratification Economics

This paper describes Latinx stratification economics (LSE) as a scholarly approach to studying the economic status of Latinas/os/es/xs primarily in the United States. We coin the term LSE to refer to work that draws on and is in conversation with both the emergent, interdisciplinary subfield of stratification economics (SE) and the interdisciplinary field of Latinx studies (LS). SE and LS have distinct intellectual traditions and drawing on both leads to strong theoretical and empirical scholarship on Latinxs, on the operation of race across space and historical time, and on the intersection of race with other systems of domination. We discuss how, based on these perspectives, it is misguided to expect racial/ethnic categories like Hispanic to be consistent over time and space and to correspond reliably with phenotypical characteristics or culture. We argue that a good faith reading of the LS literature would result in the recommendation to subordinate models of migration to models of colonialism and imperialism. We discuss the significance of normative goals and social justice to complement “gap analysis” comparisons to non-Hispanic whites. Lastly, we discuss deficiencies of the dominant models of discrimination and, as an alternative, we highlight rational models of racism that involve strategic identifications with whiteness, blackness, and mestizaje, including by members who identify as Latinx or those with Hispanic ancestry.

A unified disconnection model of stress-driven grain boundary migration in nanocrystalline metals

A unified disconnection model of stress-driven grain boundary migration in nanocrystalline metals

Artificial patterns in spatially discrete models of cell migration and how to mitigate them

Several discrete models for diffusive motion are known to exhibit checkerboard artifacts, absent in their continuous analogues. We study the origins of the checkerboard artifact in the discrete heat equation and show that this artifact decays exponentially in time when following either of two strategies: considering the present state of each lattice site to determine its own future state (self-contributions), or using non-square lattice geometries. Afterwards, we examine the effects of these strategies on nonlinear models of biological cell migration with two kinds of cell-cell interactions: adhesive and polar velocity alignment. In the case of adhesive interaction, we show that growing modes related to pattern formation overshadow artifacts in the long run; nonetheless, artifacts can still be completely prevented following the same strategies as in the discrete heat equation. On the other hand, for polar velocity alignment we show that artifacts are not only strengthened, but also that new artifacts can arise in this model which were not observed in the previous models. We find that the lattice geometry strategy works well to alleviate artifacts. However, the self-contribution strategy must be applied more carefully: lattice sites should contribute to both their own density and velocity values, and their own velocity contribution should be high enough. With this work, we show that these two strategies are effective for preventing artifacts in spatial models based on the discrete continuity equation.

Asymmetric capture into Neptunian 1:2 resonance

The asymmetric resonance configuration characterised by the critical angle librating around centres other than 0° or 180° is found in the 1:N mean motion resonance. The asymmetric 1:2 resonance with Neptune is of particular interest because the two asymmetric islands seem to host different populations, and this might be a direct clue to understanding the early evolution of the Solar System. The asymmetry has been investigated from both observational and theoretical perspectives, but conclusions among studies vary widely. In this paper, using toy models, we carefully designed a series of tests to systematically study the capture of planetesimals into the leading and trailing resonance islands. Although these tests may not exactly reproduce the real processes the Solar System experienced, they reveal some typical dynamics in the resonance capture. Since the real Twotinos have small to moderate inclinations, as a first attempt, we adopted planar models in this paper in order to investigate the mechanisms that may lead to asymmetric capture by the leading and trailing islands, including their size variation during the outward migration of Neptune, the stickiness of the leading island, and the migration slowdown effect. We find that the ratio between the populations of the leading and trailing islands can be easily tuned by introducing the slowdown effect into the migration model, and thus it may not be a good tracer of the migration history. However, the eccentricity of objects trapped in two asymmetric islands may conserve some valuable information of the early evolution of the Solar System.

Recent DIII-D progress toward validating models of tungsten erosion, re-deposition, and migration for application to next-step fusion devices

Fundamental mechanisms governing the erosion and prompt re-deposition of tungsten impurities in tokamak divertors are identified and analyzed to inform the lifetime of tungsten plasma-facing components in ITER and other future devices. Various experiments conducted at DIII-D to benchmark predictive models are presented, leveraging the DiMES removable sample exposure probe capability and the Metal Rings Campaign, in which toroidally symmetric rows of tungsten-coated tiles were installed in the DIII-D divertor. In tokamak divertors, the width of the electric sheath is of the order of the main ion Larmor radius, and a vast majority of sputtered tungsten impurities are typically ionized within the sheath. Therefore, W prompt redeposition is mainly governed by the ratio of the characteristic ionization mean-free path of neutral tungsten to the width of the sheath. In-situ monitoring of the prompt redeposition of tungsten impurities in divertors is demonstrated via the use of WII/WI line ratios and the ionizations/photon (S/XB) method in L-mode discharges. Even with this relatively limited set of emission measurements, net erosion measurements were found to be a consistent upper bound to an analytic scaling based on the ratio of the W ionization length, and the width of the magnetic sheath rather than the ratio of and the W+ gyro-radius. In the far-scrape-off layer (SOL) of the ITER divertor, however, it is calculated that the measurement of photon emissions associated with the ionization of tungsten impurities up to may be required. Finally, W deposition patterns on DiMES collector probes, interpreted via DIVIMP-WallDYN modelling, reveal the key roles of progressive W erosion/re-deposition staps and E × B drifts in regulating long-range high-Z material migration.

Subcellular mechano-regulation of cell migration in confined extracellular microenvironment.

Cell migration is a highly coordinated cellular event that determines diverse physiological and pathological processes in which the continuous interaction of a migrating cell with neighboring cells or the extracellular matrix is regulated by the physical setting of the extracellular microenvironment. In confined spaces, cell migration occurs differently compared to unconfined open spaces owing to the additional forces that limit cell motility, which create a driving bias for cells to invade the confined space, resulting in a distinct cell motility process compared to what is expected in open spaces. Moreover, cells in confined environments can be subjected to elevated mechanical compression, which causes physical stimuli and activates the damage repair cycle in the cell, including the DNA in the nucleus. Although cells have a self-restoring system to repair damage from the cell membrane to the genetic components of the nucleus, this process may result in genetic and/or epigenetic alterations that can increase the risk of the progression of diverse diseases, such as cancer and immune disorders. Furthermore, there has been a shift in the paradigm of bioengineering from the development of new biomaterials to controlling biophysical cues and fine-tuning cell behaviors to cure damaged/diseased tissues. The external physical cues perceived by cells are transduced along the mechanosensitive machinery, which is further channeled into the nucleus through subcellular molecular linkages of the nucleoskeleton and cytoskeleton or the biochemical translocation of transcription factors. Thus, external cues can directly or indirectly regulate genetic transcriptional processes and nuclear mechanics, ultimately determining cell fate. In this review, we discuss the importance of the biophysical cues, response mechanisms, and mechanical models of cell migration in confined environments. We also discuss the effect of force-dependent deformation of subcellular components, specifically focusing on subnuclear organelles, such as nuclear membranes and chromosomal organization. This review will provide a biophysical perspective on cancer progression and metastasis as well as abnormal cellular proliferation.