Aggregate Population Research Articles

Approximate solutions of aggregation and breakage population balance equations

The work aims to present a semi-analytical approach based on the homotopy analysis method for finding closed-form solutions and approximate solutions to aggregation and breakage population balance equations. The population balance equations are specific integro-partial differential equations. In this work, we first transform both the aggregation and breakage models into integral equations. Then the resulting integral equations are solved by the homotopy analysis method (HAM) to get the series solution, which in particular cases eventually converges to the exact solution. The semi-analytical solutions for various benchmark aggregation kernels like the Ruckenstein/Pulvermacher kernel and breakage kernels such as the Austin kernel are provided using HAM.

Will population exposure to heat extremes intensify over Southeast Asia in a warmer world?

Temperature extremes have increased during the past several decades and are expected to intensify under current rapid global warming over Southeast Asia (SEA). Exposure to rising temperatures in highly vulnerable regions affects populations, ecosystems, and other elements that may suffer potential losses. Here, we evaluate changes in temperature extremes and future population exposure over SEA at global warming levels (GWLs) of 2.0 °C and 3.0 °C using outputs from the Coupled Model Intercomparison Project Phase 6. Results indicate that temperature extreme indices are projected to increase over SEA at both GWLs, with more significant magnitudes at 3.0 °C. However, daily temperature ranges show a decrease. The substantial increase in total SEA population exposure to heat extremes from 730 million person–days at 2.0 °C GWL to 1200 million person–days at 3.0 °C GWL is mostly contributed by the climate change component, accounting for 48%. In addition, if global warming is restricted well below 2.0 °C, the avoided impacts in population exposure are prominent for most regions over SEA with the largest mitigation in the Philippines. Aggregate population exposure to impacts is decreased by approximately 39% at 2.0 °C GWL, while the interaction component effect, which is associated with increased population and climate change, would decrease by 53%. This indicates serious consequences for growing populations concurrent with global warming impacts if the current fossil-fueled development pathway is adhered to. The present study estimates the risks of increased temperature extremes and population exposure in a warmer future, and further emphasizes the necessity and urgency of implementing climate adaptation and mitigation strategies in SEA.

Estimating population size and survival of adult northern pike (Esox lucius) in Lower Green Bay

AbstractComplex life history behaviours like spawning migrations can complicate population assessments. However, predictable aggregation of populations at certain times of year (e.g. at spawning grounds) presents an effective way to sample species that are otherwise spatially widespread. From 2014 to 2019, a mark‐recapture study on Green Bay northern pike (Esox lucius) entering a spawning wetland was used to estimate apparent survival and population size using Bayesian inference and the Cormack–Jolly–Seber model. Population estimates and apparent survival varied from 446 to 1949 and 0.22 (males in 2017) to 0.63 (males in 2015), respectively, among years. Apparent survival also increased with maximum mean daily water temperature. Estimated capture probability was consistently low across years (<30%) despite a sampling method with high capture efficiency of fish present at the wetland, suggesting Green Bay northern pike may be exhibiting low spawning site fidelity or other life history behaviours, like skipped spawning, which reduce their capture probability at a single wetland over time. Further, spawning site selection and timing may respond to water temperatures. Surveying multiple sites could further elucidate important life history traits while refining estimates of population size and structure in large systems.

Construction of a refined population analysis unit based on urban forms and population aggregation patterns

ABSTRACT The population analysis unit (PAU) is the basic unit employed in studies of urban populations. The commonly used PAUs are mostly administrative divisions, regular geographic grids. However, these units are different from urban forms, and cannot be used to consider the characteristics of population distributions and flow changes. In this study, we proposed a method for constructing a fine population analysis zone (FPAZ) based on the population aggregation pattern and urban form elements. First, considering the spatial structure of a city and the fine-grained demands of population analysis, the basic analysis unit was divided according to the functional heterogeneity of the population activity region at the micro-scale by combining urban form elements. Next, a population aggregation preference model was established by considering the spatial distribution characteristics of the local aggregation of the urban population flow and long-term stability characteristics depending on the dynamic changes in entrances and exits. Finally, we divided the FPAZ combined with the microstructural elements. Experimental results showed that compared with other types of PAUs, the FPAZ was more consistent with the urban morphology and was an appropriate and general spatial unit for expressing the accurate characteristics of population distributions and changes at the micro-scale.

Testing Precision Limits of Neural Network-Based Quality Control Metrics in High-Throughput Digital Microscopy.

Digital microscopy is used to monitor particulates such as protein aggregates within biopharmaceutical products. The images that result encode a wealth of information that is underutilized in pharmaceutical process monitoring. For example, images of particles in protein drug products typically are analyzed only to obtain particle counts and size distributions, even though the images also reflect particle characteristics such as shape and refractive index. Multiple groups have demonstrated that convolutional neural networks (CNNs) can extract information from images of protein aggregates allowing assignment of the likely stress at the "root-cause" of aggregation. A practical limitation of previous CNN-based approaches is that the potential aggregation-inducing stresses must be known a priori, disallowing identification of particles produced by unknown stresses. We demonstrate an expanded CNN analysis of flow imaging microscopy (FIM) images incorporating judiciously chosen particle standards within a recently proposed "fingerprinting algorithm" (Biotechnol. & Bioeng. (2020) 117:3322) that allows detection of particles formed by unknown root-causes. We focus on ethylene tetrafluoroethylene (ETFE) microparticles as standard surrogates for protein aggregates. We quantify the sensitivity of the new algorithm to experimental parameters such as microscope focus and solution refractive index changes, and explore how FIM sample noise affects statistical testing procedures. Applied to real-world microscopy images of protein aggregates, the algorithm reproducibly detects complex, distinguishing "textural features" of particles that are not easily described by standard morphological measurements. This offers promise for quality control applications and for detecting shifts in protein aggregate populations due to stresses resulting from unknown process upsets.

The 2020 US Census Differential Privacy Method Introduces Disproportionate Discrepancies for Rural and Non-White Populations.

The recently finalized changes to the disclosure avoidance policies of the U.S. Census Bureau for the 2020 census, grounded in differential privacy, have faced increasing criticism from demographers and other social scientists. Scholars have found that estimates generated via Census-released test data are accurate for aggregate total population statistics of larger spatial units (e.g. counties), but introduce considerable discrepancies for estimates of subgroups. At present, the ramifications of this new approach remain unclear for rural populations. In this brief, we focus on rural populations and evaluate the ability of the finalized differential privacy algorithm to provide accurate population counts and growth rates from 2000 to 2010 across the rural-urban continuum for the total, non-Hispanic white, non-Hispanic Black, Hispanic or Latino/a, and non-Hispanic American Indian population. We find the method introduces significant discrepancies relative to the prior approach into counts and growth rate estimates at the county level for all groups except the total and non-Hispanic white population. Further, discrepancies increase dramatically as we move from urban to rural. Thus, the differential privacy method likely introduced significant discrepancies for rural and non-white populations into 2020 census tabulations.

Epidemiological characteristics and influencing factors for high risk cardiovascular disease population in Jiangsu province

Objective: To investigate the detection types and aggregation of high-risk population of cardiovascular disease (CVD) in Jiangsu province and the related influencing factors to provide reference for the prevention and control of cardiovascular disease. Methods: A total of 120 211 participants were included in the investigation. Information was collected by questionnaire based survey, physical examination and biochemical tests. χ2 test and multivariate logistic regression were used for statistical analysis. Results: The detection rate of CVD high risk was 25.03%. The detection rates were 19.01%, 4.85%, 3.18% and 5.31% for hypertension, dyslipidemia, cardiovascular history and WHO assessed risk ≥20% types, respectively. Male, rural, old age, low education level, low family income, drinking, waist circumference exceeding standard, overweight and obesity were risk factors of CVD (all P<0.01). The composition ratios of aggregation of 1, 2 and ≥3 high risk types of CVD were 74.01%, 22.91% and 3.08%, respectively. With the increase of aggregation types, the correlation strength increased with age, rural residents, education level and annual family income. Conclusion: Targeted measures should be carried out according to different influencing factors for the prevention and control of CVD in Jiangsu province in order to achieve the maximum prevention and control effect with the minimum cost.

Specific Interactions in the Model of Mixed Multicomponent Micelles: Predicting Aggregation Behavior and Details of Structure

Modeling of multicomponent micellar aggregates is important for screening and selecting formulations in a variety of engineering applications, including micelle-mediated separation, drug delivery and nanoreactors. Typically, the constituent molecules of such aggregates have complex chemical structure and are engaged in specific and nonspecific interactions with one another and with the hydration water. Description of these interactions in the strongly nonuniform aggregates is very difficult, impeding the development of the theoretical models. In this work we extend to the multicomponent aggregates a molecular-thermodynamic model that describes the hydrogen bonding and other specific interactions in the hydrated corona. The model is formulated for an arbitrary number of nonionic and ionic amphiphiles that self-assemble into polydisperse aggregates in an aqueous solution. For describing the aggregation equilibrium together with the material balance in this solution, a simple method is suggested and tested. We illustrate application of our model by predicting aggregation equilibrium and characteristics of the three-component aggregates in the aqueous mixture of the nonionic surfactant Triton X-114, a micelle-forming alkylimidazolium ionic liquid (1-methyl-3-octylimidazolium chloride), and n-octanol. Our calculations suggest that the tails of the octanol molecules are deeply buried in the cores of the mixed micelles with only one methylene group penetrating the coronae and that the entire hydrocarbon tail of the ionic liquid resides in the core. Taking into account the populations of polydisperse spherical and rodlike aggregates, we model equilibrium partitioning of the components between the aggregates and the surrounding aqueous solution. The model predicts that addition of the ionic liquid to the mixture promotes the partitioning of n-octanol into the Triton-rich micelles.

Territorial Strategy of Medical Units for Addressing the First Wave of the COVID-19 Pandemic in the Metropolitan Area of Mexico City: Analysis of Mobility, Accessibility and Marginalization.

Background. The COVID-19 pandemic has caused an exponential increase in the demand for medical care worldwide. In Mexico, the COVID Medical Units (CMUs) conversion strategy was implemented. Objective. To evaluate the CMU coverage strategy in the Mexico City Metropolitan Area (MCMA) by territory. Materials. The CMU directory was used, as were COVID-19 infection and mobility statistics and Mexican 2020 census information at the urban geographic area scale. The degree of urban marginalization by geographic area was also considered. Method. Using descriptive statistics and the calculation of a CMU accessibility index, population aggregates were counted based on coverage radii. In addition, two regression models are proposed to explain (1) the territorial and temporal trend of COVID-19 infections in the MCMA and (2) the mobility of the COVID-infected population visiting medical units. Results. The findings of the evaluation of the CMU strategy were (1) in the MCMA, COVID-19 followed a pattern of contagion from the urban center to the periphery; (2) given the growth in the number of cases and the overload of medical units, the population traveled greater distances to seek medical care; (3) after the CMU strategy was evaluated at the territory level, it was found that 9 out of 10 inhabitants had a CMU located approximately 7 km away; and (4) at the metropolitan level, the lowest level of accessibility to the CMU was recorded for the population with the highest levels of marginalization, i.e., those residing in the urban periphery.

Analysis of the factors affecting Vietnam's exports to the EU market

The paper uses the gravity model and panel data to examine the determinants of Vietnam's export to the EU market during the 2007-2017 period. Vietnam is an export-oriented economy. In the context of international economic integration, Vietnam is one of the countries with a very high export growth rate. With a GDP of 18.82 trillion USD, a population of 512 million people (2017), the European Union (EU) is the world's largest economy and is Vietnam's second largest commodity import market. As a result, the urgent requirement from practice is to identify and quantify the factors affecting Vietnam's exports to the EU market and on that basis to give appropriate policy implications to boost exports to increase export turnover and gradually improve the economy. The article uses the Hausman-Taylor estimator for the optimal combination of Fixed-Effects (FE) and Random-Effects (RE) methods. The estimation results indicate that the determinants of Vietnam's export to the EU market include: aggregate population; aggregate GDP per capita; Vietnam's index of infrastructure and aggregate trade openness. Based on these findings, the paper suggests policies to boost Vietnam's export to the EU.

Factors affecting Vietnam's coffee export in the period of 2008 - 2020

In recent years, coffee export has always been one of the top 10 export industries of Vietnam with a high share of the country's total agricultural export turnover. In 2020, the world's economy will be severely affected by the Covid-19 pandemic. As an obvious consequence, Vietnam's coffee exports are also not immune to damage due to a drop in demand in the world market. Therefore, solutions to promote coffee export activities can be considered as the top concerns of policymakers. This article aims to find out the factors affecting Vietnam's coffee exports in the period 2008-2020. Thereby, it is possible to find the right direction, seize opportunities, improve competitiveness for domestic enterprises and take advantage of the strength to promote Vietnam's coffee exports. By combining static and dynamic methods in regression models for panel data such as pooled regression model (Pooled OLS), fixed effects model (FEM), random effects model (REM), feasible general least squares model (FGLS) and system generalized moment model (SGMM), this study has demonstrated that the SGMM model has the best results in finding the main factors, as well as the influence of them to Vietnam's coffee exports. Besides the positive effect of the lagged variable on Vietnam's current coffee exports has been detected, the research results have shown that hypotheses about the expected impact of variables in the model such as distance in terms of geography, exchange rates, and aggregate population are mostly satisfied. From the results obtained, recommendations have been proposed for management organizations, businesses and farmers to promote coffee exports and raise Vietnam's position in the international market.

An Empirical Research on Metropolitanization and Housing Price Differentiation Based on the Data of 31 Provincial Capitals and Municipalities with Independent Planning Status in China

Under the background of population aggregation in megacities, some adjustments are made to the urbanization strategy, whose focus is shifted to the development of megacities and megacity clusters. Meanwhile, the housing price differentiation among cities tends to become increasingly serious. This paper, from the perspective of population mobility, takes provincial capitals and municipalities with independent planning status (PCs & MIPSs) as research samples to evaluate the level of housing price differentiation within provincial-level administrative divisions of China, and analyze from the perspective of demand side how the metropolitanization effects regarding the population formed due to population aggregation in megacities affect the housing prices of megacities and the housing price difference between megacities and other cities. The research found that: 1) The increasing net inflow of population boosts the housing prices and accelerate the housing price differentiation; 2) The impact of the increasing net inflow of population on housing price increases and housing price differentiation has regional heterogeneity and city size heterogeneity; 3) The income gap strengthens the effect of population inflow upon the housing price differentiation.

A Novel Index to Measure the Spatial Matching between Urban Service Facilities Distribution and Population Aggregation

A Novel Index to Measure the Spatial Matching between Urban Service Facilities Distribution and Population Aggregation

Spatial Relationship between Environmental Justice and Tier II Facilities in Massachusetts

This study explored the aggregation of environmental justice populations through the standardized SVI indicator (Social Vulnerability Index), and vulnerable populations have similar areas of aggregation through the aggregation analysis of the cluster map of SVI. After using spatial analysis to examine the spatial geographic location of secondary facilities and environmental justice community areas, we found significant similarities and overlaps between the two regions related to gentrification policies.

Statistical Dynamics of Wealth Inequality in Stochastic Models of Growth

Understanding the statistical dynamics of growth and inequality is a fundamental challenge to ecology and society. Recent analyses of wealth and income dynamics in contemporary societies show that economic inequality is very dynamic and that individuals experience substantially different growth rates over time. However, despite a fast growing body of evidence for the importance of fluctuations, we still lack a general statistical theory for understanding the dynamical effects of heterogeneneous growth across a population. Here we derive the statistical dynamics of correlated growth rates in heterogeneous populations. We show that correlations between growth rate fluctuations at the individual level influence aggregate population growth, while only driving inequality on short time scales. We also find that growth rate fluctuations are a much stronger driver of long-term inequality than earnings volatility. Our findings show that the dynamical effects of statistical fluctuations in growth rates are critical for understanding the emergence of inequality over time and motivate a greater focus on the properties and endogenous origins of growth rates in stochastic environments.

Understanding stenosis-induced platelet aggregation on a chip by high-speed optical imaging

Vascular stenosis is a pathological hallmark of atherosclerosis, the leading cause of cardiovascular diseases such as stroke and myocardial infarction. While stenosis-induced thrombus formation has been extensively studied using in vivo and in vitro vascular models, the transient and dynamic process of platelet aggregation remains unclear due to the lack of analytical tools with both high spatial and temporal resolution. Here we report spatiotemporally resolved observation of shear-induced platelet aggregation using an in vitro microfluidic stenosis model and an optical time-stretch imaging system. Specifically, we characterized the size, shape, and population of platelet aggregates at single-cell resolution every 20 min in the presence of different agonists in a 3D stenosis model. Our results indicate a significant enhancement in platelet aggregation when both stenosis and an agonist were present, thus suggesting a synergistic effect of atherogenic blood flow disturbance and circulating factors on platelet activation. In particular, platelets activated by thrombin receptor activator peptide 6 (TRAP-6) led to a broad-sized distribution of platelet aggregates with significantly large aggregates (>240 µm2 in area). These findings are expected to deepen our understanding of the mechanism behind stenosis-induced platelet aggregation and pave the way for development of better antithrombotic therapeutics.

Production of homogenous size‐controlled human induced pluripotent stem cell aggregates using ring‐shaped culture vessel

Aggregate size is an important parameter that determines the cell fate and quality of the resulting human-induced pluripotent stem cells (hiPSCs). Nowadays, large-scale suspension culture is a common method for scaling-up the biomanufacturing of hiPSCs to realize their practical application. However, this culture system exhibits a complex hydrodynamic condition resulting from the different mixing conditions of culture media, which potentially produce non-uniform aggregates, which may decrease the quality of the cell yield. Here, we performed expansion in a ring-shaped culture vessel and compared it with three other suspension-based culture systems to evaluate the uniformity and characteristics of hiPSC aggregates. Morphologically, the hiPSC aggregates formed and expanded in the ring-shaped culture vessel, resulting in small and uniform aggregates compared to the other culture systems. This aggregate population showed a decent mass transfer required for the exchange of biochemical substances, such as nutrients, growth factors, oxygen, and waste metabolic products, inside the aggregates. Thus, better metabolic performance and pluripotency markers were achieved in this system. Interestingly, all culture systems used in this study showed different tendencies in embryoid body differentiation. The smaller aggregates produced by sphere ring and dish bag tended to differentiate toward ectodermal and mesodermal lineages, while predominantly larger aggregates from the 6-well plates and spinner flask exhibited more potential for endodermal lineage. Our study demonstrates the production of a decent homogenous aggregate population by providing equal hydrodynamic force through the ring-shaped culture vessel design, which may be further upscaled to produce a large number of hiPSCs for clinical applications.

Ambulance Locations in a Tiered Emergency Medical System in a City

This paper deals with optimizing the location of ambulance stations in a two-tiered emergency medical system in an urban environment. Several variants of station distribution are calculated by different mathematical programming models and are evaluated by a detailed computer simulation model. A new modification of the modular capacitated location model is proposed. Two ways of demand modelling are applied; namely, the aggregation of the ambient population and the aggregation of permanent residents at the street level. A case study of the city of Prešov, Slovakia is used to assess the models. The performance of the current and proposed sets of locations is evaluated using real historical data on ambulance trips. Computer simulation demonstrates that the modular capacitated location model, with the ambient population demand, significantly reduces the average response time to high-priority patients (by 79 s in the city and 62 s in the district) and increases the percentage of high-priority calls responded to within 8 min (by almost 4% in the city and 5% in the district). Our findings show that a significant improvement in the availability of the service can be achieved when ambulances are not accumulated at a few stations but rather spread over the city territory.

Half-hearted policies on mobility restrictions during COVID-19 in Indonesia: A portrait of large informal economy country

This study measures the effectiveness of government’s transportation policy on mobility restriction during the COVID-19 pandemic using publicly available big datasets. Using a causal difference-in-difference (DiD) analysis and regression discontinuity design (RDD), we examine the impact of non-pharmaceutical interventions (NPIs) on the aggregate population mobility of cities and regencies across Indonesia. Our results show that during the period of the first so-called “Large-scale Social Restrictions” or “Pembatasan Sosial Berskala Besar” (PSBB I) from April to May 2020, NPIs reduced mobility by 5.4% relative to pre-pandemic baseline and accounted for a small portion of mobility decline in cities or regencies that instituted mobility restrictions. The impact of the second PSBB policy (PSBB II) from September to November 2020 was smaller, with a mobility reduction of only 1.8%–2.9%, depending on the window of observation and sample. Lastly, the “Imposition of Restriction on Social Activity” or Pemberlakuan Pembatasan Kegiatan Masyarakat (PPKM) policy beginning in January 2021 has had a more negligible impact, with mobility reduction of approximately 0.6–2.1%. These findings indicate that the effectiveness of mobility restrictions tend to decrease over time. The decline in effectiveness may be the result of the increased cost of social distancing over long periods of time and the declining stringency of the mobility restrictions being imposed, which may be particularly pronounced for emerging countries with a large informal sector, such as Indonesia.

Surfactant aggregate size distributions above and below the critical micelle concentration.

Aggregate size distributions in an aqueous solution containing either charged or neutral surfactants are investigated using Raman multivariate curve resolution (Raman-MCR) spectroscopy and analyzed with the aid of a multi-aggregation chemical potential surface (MCPS) modeling strategy. Total least squares decompositions of the concentration-dependent Raman-MCR spectra are used to quantify the free and micelle surfactant populations, and the surfactant's C-H stretch frequency is used as a measure of its average aggregation state. MCPS predictions relate the experimental measurements to the underlying surfactant aggregate size distribution by fitting either the component concentrations or the average C-H frequency to MCPS predictions, and thus determine the critical micelle concentration (CMC) and estimate the corresponding micelle size and polydispersity. The Raman-MCR spectra of aqueous 1,2-hexanediol, sodium octanoate, and sodium dodecyl sulfate, measured both below and above CMC, provide critical tests of the assumed functional form of the MCPS and the presence of low-order premicellar aggregates. Our results indicate that the low-order aggregate population gradually emerges as the CMC is approached and then remains nearly concentration-independent after the appearance of micelles.