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This article examines the riveli di beni e anime of the small town of Gallodoro, located in northeastern Sicily about halfway between the cities of Messina and Catania, to examine the history of the town’s families during the seventeenth and eighteenth centuries by tracing the prevalence of surnames recorded in these documents. The growing proliferation of certain surnames suggests a longer presence of these families in Gallodoro, while the increasing diversification of surnames as a whole suggests a dynamic population comprised of new residents. Despite the diversification of surnames in the riveli for Gallodoro, during the seventeenth and eighteenth centuries, the majority of the town’s population held only a relatively few different surnames.

Cortical neurons show distinct firing patterns across multiple task epochs characterized by different computations. Recent studies suggest that such distinct patterns underlie dynamic population code achieving computational flexibility, whereas neurons in some cortical areas often show coherent firing patterns across epochs. To understand how coherent single-neuron code contributes to dynamic population code, we analyzed neural responses in the rat perirhinal cortex (PRC) during cue and reward epochs of a two-alternative forced-choice task. We found that the PRC neurons often encoded the opposite choice directions between those epochs. By using principal component analysis as a population-level analysis, we identified neural subspaces associated with each epoch, which reflected coordination across the neurons. The cue and reward epochs shared neural dimensions where the choice directions were consistently discriminated. Interestingly, those dimensions were supported by dynamically changing contributions of the individual neurons. These results demonstrated heterogeneity of coherent single-neuron representations in their contributions to population code., Tomoya Ohnuki et al. show that individual neurons in the rat perirhinal cortex coherently encoded choice directions across cue and reward epochs. Individual neurons also displayed dynamically changing contributions to population encodings between these epochs, suggesting that they flexibly coordinate to support computations associated with different epochs while holding temporally coherent representations.

In terms of fish dynamic population, reproduction is a process related with corporal size of each population member, which is tied with the spawning time and number of eggs produced. In order to relate the size of female little tuny (Euthynnus alletteratus), located in the southwest Gulf of Mexico, and its contribution in reproductive process, cycle and reproductive characteristics were analyzed by different size groups. Biological data were obtained by the artisanal fishing fleet of Antón Lizardo Veracruz community (Mexico). A total of 480 fish were caught from December 2009 to November 2012. Size structure, gonadosomatic index and duration and intensity spawning index (IDI) were determined. The gonadosomatic index showed a decrease in the population after April and July. Nevertheless, these months and the fraction of spawning female may vary depending on size groups. According with the IDI, the individuals with the highest contribution in reproductive process belong to sizes from 44 to 56 cm. Therefore, in order to guarantee the conservation of this species, it is imperative to mainly direct the management measures towards the females from these sizes.

Based on multiple global climate models (GCMs), the Standardized Precipitation Evapotranspiration Index ( SPE I) and Intensity-Area-Duration (IAD) method were used to identify drought events of the Indus River Basin (IRB) in the reference period (1986–2005) and under 1.5 °C (2020–2039 in RCP2.6) and 2.0 °C (2040–2059 in RCP4.5) global warming scenarios. Then, the population exposure was assessed by combining drought events with a projected dynamic population amount from five Shared Socioeconomic Pathways (SSPs), in which describe future of societal development considering the effects of climate change and climate policies. Research results show that both precipitation and evapotranspiration are projected to increase with global warming. Due to a higher increase in evapotranspiration than in precipitation, frequency, intensity, and areal coverage of drought events in the IRB are expected to increase under the 1.5 °C and 2.0 °C warming scenarios relative to the 1986–2005 reference period. In particular, frequency and areal coverage of extreme severe droughts will increase significantly. With aggravation of droughts across the IRB, annual population exposure will increase considerably from 43.2 million in 1986-2005 to approximately 114.4 million based on SSP1 (a sustainable world) under the 1.5 °C global warming scenario and will reach 163.1 million based on SSP3 (a strongly fragmented world) under the 2.0 °C scenario. Compared with the 2.0 °C level, maintaining the increase in global average temperature below the 1.5 °C limit can reduce the population exposed to drought by approximately 1.4-fold.

Diversity is a much sought after aspect of any evolutionary system. More diversity means a cornucopia of diverse behaviors and traits among the individuals of a population. Lack of diversity, on the other hand, leads to a stagnant population whose individuals are more or less similar to each other. Subsequently, they fail to produce a variety of offspring. Grammatical Evolution (GE), being an Evolutionary Algorithm (EA), is also an aspirant of diversity. It allows a GE system to maintain a dynamic population over multiple generations.In this paper, we present our reflections about diversity estimates in a (large) number of experiments. We performed evolutionary experiments to estimate a bunch of well-known benchmark polynomials. We also employed hybrid optimization in our experiments. Our results are insightful. In this paper, we also test the effect of hybrid optimization algorithms integrated with GE on the diversity of the population.

Ancient genomes anchor genealogies in directly observed historical genetic variation, and contextualise ancestral lineages with archaeological insights into their geography and lifestyles. We introduce an extension of theRelatealgorithm to incorporate ancient genomes and reconstruct the joint genealogies of 14 previously published high-coverage ancients and 278 present-day individuals of the Simons Genome Diversity Project. As the majority of ancient genomes are of lower coverage and cannot be directly built into genealogies, we additionally present a fast and scalable method,Colate,for inferring coalescence rates between low-coverage genomes without requiring phasing or imputation. Our method leverages sharing patterns of mutations dated using a genealogy to construct a likelihood, which is maximised using an expectation-maximisation algorithm. We applyColateto 430 ancient human shotgun genomes of >0.5x mean coverage. UsingRelateandColate,we characterise dynamic population structure, such as repeated partial population replacements in Ireland, and gene-flow between early farmer and European hunter-gatherer groups. We further show that the previously reported increase in the TCC/TTC mutation rate, which is strongest in West Eurasians among present-day people, was already widespread across West Eurasia in the Late Glacial Period ~10k - 15k years ago, is strongest in Neolithic and Anatolian farmers, and is remarkably well predicted by the coalescence rates between other genomes and a 10,000-year-old Anatolian individual. This suggests that the driver of this signal originated in ancestors of ancient Anatolia >14k years ago, but was already absent by the Mesolithic and may indicate a genetic link between the Near East and European hunter-gatherer groups in the Late Paleolithic.

Background As a mosquito-borne infectious disease, dengue fever (DF) has spread through tropical and subtropical regions worldwide in recent decades. Dengue forecasting is essential for enhancing the effectiveness of preventive measures. Current studies have been primarily conducted at national, sub-national, and city levels, while an intra-urban dengue forecasting at a fine spatial resolution still remains a challenging feat. As viruses spread rapidly because of a highly dynamic population flow, integrating spatial interactions of human movements between regions would be potentially beneficial for intra-urban dengue forecasting. Methodology In this study, a new framework for enhancing intra-urban dengue forecasting was developed by integrating the spatial interactions between urban regions. First, a graph-embedding technique called Node2Vec was employed to learn the embeddings (in the form of an N-dimensional real-valued vector) of the regions from their population flow network. As strongly interacting regions would have more similar embeddings, the embeddings can serve as “interaction features.” Then, the interaction features were combined with those commonly used features (e.g., temperature, rainfall, and population) to enhance the supervised learning–based dengue forecasting models at a fine-grained intra-urban scale. Results The performance of forecasting models (i.e., SVM, LASSO, and ANN) integrated with and without interaction features was tested and compared on township-level dengue forecasting in Guangzhou, the most threatened sub-tropical city in China. Results showed that models using both common and interaction features can achieve better performance than that using common features alone. Conclusions The proposed approach for incorporating spatial interactions of human movements using graph-embedding technique is effective, which can help enhance fine-grained intra-urban dengue forecasting., Author summary Dengue fever, a mosquito-borne infectious disease, has become a serious public health problem in many tropical and subtropical regions worldwide, such as Southeast Asian countries and the Guangdong Province in China. In the absence of an effective vaccine at present, disease surveillance and mosquito control remain the primary means of controlling the spread of the disease. At an intra-urban setting, it is important to predict the spatial distribution of future patients, which can help government agencies to establish precise and targeted prevention measures beforehand. Considering the fast virus spread within a city because of a highly dynamic population flow, we proposed a novel approach to enhancing fine-grained intra-urban dengue forecasting by integrating spatial interactions of human movements between urban regions. First, using a graph-embedding model called Node2Vec, the embeddings of the regions were learned from their population interaction network so that strongly interacted regions would have more similar embeddings. Secondly, serving as interaction features, the embeddings were combined with the commonly used features as inputs of the forecasting models. The experimental results indicated that the performance of the models can be improved by incorporating the interaction features, confirming the effectiveness of our proposed strategy in enhancing fine-grained intra-urban dengue forecasting.

Broadly speaking, institutional reformers decide about the sequencing of types of reforms, either addressing institutional quality or macroeconomic stability. This paper develops a dynamic population game, in which agents play a simple anonymous-exchange game of cooperating or defecting. Agents switch to the strategy with higher expected payoff. Reformers can affect the payoff structure of the stage game in order to maximize the number of cooperators in the population by either enacting legal reform or focusing on the macro outlook of the economy. Reform is cumulative and starts from initial conditions. Reform effort per period of time is capped. On the basis of the theoretical model the paper makes predictions under which conditions which types of reforms should be enacted first and under which conditions reform will not be successful.

Fine population distribution both in space and in time is crucial for epidemic management, disaster prevention, urban planning and more. Human mobility data have a great potential for mapping population distribution at a high level of spatiotemporal resolution. Power law models are the most popular ones for mapping mobility data to population. However, they fail to provide consistent estimations under different spatial and temporal resolutions, i.e. they have to be recalibrated whenever the spatial or temporal partitioning scheme changes. We propose a Bayesian model for dynamic population estimation using static census data and anonymized mobility data. Our model gives consistent population estimations under different spatial and temporal resolutions.

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.

Se realizó un estudio serológico en busca de anticuerpos contra agentes etiológicos comunes, en gallinas de patio (Gallus gallus) de la aldea El Caoba (AEC), situada en la zona de amortiguamiento de la Reserva de la Biosfera Maya, en Petén, Guatemala. Se tomaron aleatoriamente, muestras de sangre de 39 gallinas. Se buscaron anticuerpos contra el virus de influenza aviar tipo A (VIA), el virus de la enfermedad de Newcastle (VENC), el virus de la enfermedad de Gumboro (VEG), la bacteria Mycoplasma gallisepticum (MG) y la bacteria Salmonella pullorum (SP). El 46%de las gallinas estudiadas portaba anticuerpos contra el VIA; el 51% contra el VENC y el 95% contra el VEG. No se detectaron anticuerpos contra MG ni contra SP. Los anticuerpos contra el VENC se detectaron únicamente durante el muestreo del mes de septiembre. El 31% de las gallinas muestreadas portaba, de manera concomitante, anticuerpos contra tres patógenos (VIA, VENC y VEG) y el 15% contra dos patógenos (VENC y VEG). Se considera que la población dinámica de gallinas de patio de la AEC representa una potencial amenaza para la avicultura artesanal, la avicultura tecnificada, las aves silvestres y la población humana.

Objective Childhood obesity prevention has been identified as a key strategy to address the obesity crisis, with considerable investment by governments internationally. This study modeled the implications of entering adulthood at a lower or higher BMI (a consequence of changes in childhood obesity) and modeled how this would influence future numbers of adults with obesity in Australia. Methods In this study, a dynamic population model was used to investigate how obesity prevention in children could impact the future number of adults with obesity in Australia from 2015 to 2040. The base population was a nationally representative data set of 14,256 individuals (representing approximately 17 million adults) from the Australian Health Survey 2014-2015. Each year, a new 20-year-old cohort was added to the simulated population, reflecting the transition to adulthood under scenarios of stable, increasing, or decreasing childhood obesity. Results Targeting and reducing childhood obesity will have only a small and delayed effect on adult obesity levels, with approximately 280,000 fewer adults with obesity by 2040. Conclusions These findings highlight the importance of investing in and implementing obesity prevention programs across all ages, particularly in young adults, to successfully reduce the prevalence of adult obesity in Australia.

The aim of this chapter is to asses the impact of migration on the development of the population of Slovak rural regions as well as on the accumulation of their human capital expressed by educational structure of population. The analysis is based on the anonymized data on individual migrations at the level of individual municipalities (LAU2) provided by the Statistical Office of the Slovak Republic for each year over the period 1997–2016. The overall transformation of the migration patterns in post-socialist era is identified first to point out the impact of main migration trends to the rural regions. The results show an increasing migration loss of rural regions at the expense of metropolitan regions, especially the region of Bratislava. In the following part we evaluate the selective nature of migration by the educational attainment of migrants as a significant aspect of the local and regional human capital. The analysis reveals that migration losses are increasing with the increasing level of education. Generally, migration in rural regions contributes to population decline as well as deterioration of human capital. While the region of Bratislava and adjacent regions show dynamic population growth by migration, vast areas particularly in eastern and south-central Slovakia suffer from migration loss driven mainly by well-educated and young people. This can act as a constraint for further economic development of rural regions. However, case study analysis shows that rural character can be beneficial for regions in attracting migrants even with higher educational attainment, but this is determined by their localisation within commuting distance to the centres of metropolitan regions or major economic hubs of the country.

Evolutionary testing (ET) is an effective test case generation technique which uses some meta-heuristic search algorithm, especially genetic algorithm, to generate test case automatically. However, the population prematurity problem may decrease the performance of ET. In this paper, a hybrid optimization strategy is proposed based on extended cataclysm which integrates both static configuration strategies and dynamic optimization strategy. Dynamic optimization strategy included the optimization of initial population and the dynamic population optimization based on extended cataclysm, where the diversity of population was monitored during the evolution process of ET, and once the population prematurity was detected, extended cataclysm operation was used to renew the diversity of the population. Experimental results show that the hybrid optimization strategy can improve the performance of ET.

This study presents an estimate of the total NO2 exposure in a polluted and densely populated region in Malta, the Northern Harbour district. To estimate the population mobility, we follow a dynamic approach whereby four microenvironments are mapped onto defined Copernicus Urban Atlas 2012 land use classifications. These include the home (ME_home), work (ME_work), traffic (ME_traffic), and other outdoor activities (ME_other) microenvironments. In addition, generic time-activity profiles are used to estimate the hourly mobility in the different microenvironments depending on weekday or weekend profiles. Measured hourly NO2 ambient concentrations from the air quality network run by the Environment and Resources Authority (ERA) are used in conjunction with the estimated time-activity profiles to calculate the total exposure. The highest NO2 population exposure is estimated for ME_home (71%) as people spend the majority of the time in this microenvironment followed by ME_other (15%), ME_work (10%) and ME_traffic (4%), respectively. In addition, we test the sensitivity of the total NO2 exposure to changes in NO2 concentrations for different microenvironments. The total NO2 exposure using infiltration rates to estimate infiltrated outdoor NO2 concentrations in indoor microenvironments, is up to 25% lower compared to the NO2 exposure estimated using outdoor NO2 concentrations for all microenvironments. Results also suggest a decrease of 3% in the estimated NO2 exposure if a static population is assumed for each microenvironment as opposed to a dynamic one. Exposure assessments such as that presented in this study are essential to aid the development of targeted policies to limit such exposures.

This research was to conduct a pilot study for two consecutive days in order to assess fine particulate matter (PM2.5) exposure of an entire population in a community. We aimed to construct a surveillance system by analyzing the observed spatio-temporal variation of exposure. Guro-gu in Seoul, South Korea, was divided into 2,204 scale grids of 100 m each. Hourly exposure concentrations of PM2.5 were modeled by the inverse distance weighted method, using 24 sensor-based air monitoring instruments and the indoor-to-outdoor concentration ratio. Population distribution was assessed using mobile phone network data and indoor residential rates, according to sex and age over time. Exposure concentration, population distribution, and population exposure were visualized to present spatio-temporal variation. The PM2.5 exposure of the entire population of Guro-gu was calculated by population-weighted average exposure concentration. The average concentration of outdoor PM2.5 was 42.1 &micro, g/m3, which was lower than the value of the beta attenuation monitor measured by fixed monitoring station. Indoor concentration was estimated using an indoor-to-outdoor PM2.5 concentration ratio of 0.747. The population-weighted average exposure concentration of PM2.5 was 32.4 &micro, g/m3. Thirty-one percent of the population exceeded the Korean Atmospheric Environmental Standard for PM2.5 over a 24 h average period. The results of this study can be used in a long-term aggregate and cumulative PM2.5 exposure assessment, and as a basis for policy decisions on public health management among policymakers and stakeholders.

In order to include viscous instability in modeling heavy oil waterflooding, it is essential to predict the nature of viscous instability. It is still unclear as to whether previous findings of viscous fingering in immiscible displacements in the presence of high single-phase permeabilities and linear displacement schemes are valid in displacement schemes similar to oil-field patterns (e.g., five-spot) and what the effect of dispersion (caused by varying velocity profiles) is on viscous fingering. To overcome the limitations of previous studies of viscous fingering in immiscible displacements, we conduct experiments in low-permeability, one-quarter five-spot patterns. The correlation of experimentally measured oil recoveries, pressure drops, saturation profiles, viscous fingers length and width, dynamic population of fingers, and rate of growth of fingers population with time and front position are discussed. Study of viscous fingering patterns in heavy oil waterflooding conducted in this work provides new insights into the onset of fingering and fingers development.

The concept of Volunteered Geographic Information (VGI) has progressed from being an exotic prospect to making a profound impact on GIScience and geography in general, as initially anticipated. However, while massive and manifold data is continuously produced voluntarily and applications are built for information and knowledge extraction, the initially introduced concept of VGI lacks certain methodological perspectives in this regard which have not been fully elaborated. In this article we highlight and discuss an important gap in this concept, i.e. the lack of formal acknowledgment of temporal aspects. By coining the proposed advanced framework 'Volunteered Geo-Dynamic Information' (VGDI), we attempt to lay the ground for full conceptual and applied spatio-temporal integration. To illustrate that integrative approach of VGDI and its benefits, we describe the potential impact on the field of dynamic population distribution modeling. While traditional approaches in that domain rely on survey-based data and statistics as well as static geographic information, the use of VGDI enables a dynamic setup. Foursquare venue and user check-in data are presented for a test site in Lisbon, Portugal. Two core modules of spatio-temporal population assessment are thereby addressed, namely time use profiling and target zone characterization, motivated by the potential integration in existing population dynamics frameworks such as the DynaPop model.

В статье ставится задача выявить степень воздействия идеологических и политических факторов на работу советских статистиков при определении численности населения СССР в течение 12-лет, прошедших между Всесоюзными переписями 1926 и 1939 гг. В этот сложный период страна переживала форсированную индустриализацию, насильственную коллективизацию и ускоренную, хаотичную урбанизацию. В связи с чем демографическая подсистема Советского Союза претерпела принципиальные изменения. Но характер этих изменений, сдвиги в численности населения и методы, которые использовали советские статистические органы для получения важнейшей демографической информации, изучены крайне слабо. В статье показано, как сформировались два динамических ряда численности населения, составленные советскими статистиками: 1) опубликованный в открытой печати и 2) закрытый ряд, хранившийся в недрах ведомственного архива ЦУНХУ СССР. Выявлено значение регистрации рождаемости, смертности, миграций при оценках численности населения. На основании большого числа исторических документов показана сложная работа статистиков по определению численности населения в СССР 1930-х гг. Выявлены довоенные и послевоенные оценки изменений в численности населения страны.

Roughneck Grunt (Haemulopsis corvinaeformis Steindachner, 1868) is the second most important species caught as bycatch of the shrimp fishery in Pernambuco, Northeastern Brazil. However, the population dynamic of this species is poorly known in the region. The aim of this study was to describe aspects of the population structure and reproductive biology of the H. corvinaeformis, providing important information for the development of sustainable management practices. Specimens were collected monthly from August 2011 to July 2012 and quarterly from October 2012 to June 2014. A total of 1,140 individuals was collected; 340 males (29.8%), 391 females (34.3%), and 409 were immature and could not be sexed (35.9%). Total length ranged from 7 to 25 cm. In general, total length of females [12.85 ± 2.49 cm (mean± SD)] and males [12.72 ± 2.46 cm (mean ± SD)] were similar (p > 0.05). The proportion of males and females was similar along the year, except in March. The relationship between total length and total weight was statistically significant (p< 0.05), showing an isometric growth. The (GSI) coupled with the distribution of maturational stages suggests that females reproduce all year around, with a peak during October-November. The length at first maturity (L50) was estimated at 11.88 cm for females and 11 cm for males. RESUMO: O coró branco (Haemulopsis corvinaeformis Steindachner, 1868) é a segunda espécie mais importante capturada como fauna acompanhante na pesca de camarão em Pernambuco, nordeste do Brasil. No entanto, a dinâmica populacional é pouco conhecida na região. O objetivo do estudo foi descrever aspectos da estrutura populacional e biologia reprodutiva da espécie, fornecendo informações importantes para o desenvolvimento de práticas de manejo sustentáveis. Espécimes foram coletados mensalmente de agosto de 2011 a julho de 2012, e a cada três meses de outubro de 2012 a junho de 2014. Um total de 1.140 espécimes foi coletado; 340 machos (29,8%), 391 fêmeas (34,3%), e 409 imaturos cujo sexo não pode ser identificado (35,9%). O comprimento total variou entre 7 e 25 cm. De maneira geral, o comprimento total das fêmeas [12,85 ± 2,49 cm (média ± DP)] e machos [12,72 ± 2,46 cm (média ± DP)] foram similares (p > 0.05). A proporção de machos e fêmeas foi similar, com exceção de março. As relações entre comprimento total e peso total foram estatisticamente significantes (p< 0.05), mostrando um crescimento isométrico. O índice gonadossomático (GSI) associado com a distribuição dos estágios maturacionais sugerem que as fêmeas reproduzem durante todo o ano, com um pico durante outubro-novembro. O tamanho de primeira maturação foi estimado em 11.88 cm para fêmeas e 11 cm para machos.

We present a general framework to study quantum disordered systems in the context of the Kikuchi's Cluster Variational Method (CVM). The method relies in the solution of message passing-like equations for single instances or in the iterative solution of complex population dynamic algorithms for an average case scenario. We first show how a standard application of the Kikuchi's Cluster Variational Method can be easily translated to message passing equations for specific instances of the disordered system. We then present an "ad-hoc" extension of these equations to a population dynamic algorithm representing an average case scenario. At the Bethe level, these equations are equivalent to the dynamic population equations that can be derived from a proper Cavity Ansatz. However, at the plaquette approximation, the interpretation is more subtle and we discuss it taking also into account previous results in classical disordered models. Moreover, we develop a formalism to properly deal with the average case scenario using a Replica-Symmetric ansatz within this CVM for quantum disordered systems. Finally, we present and discuss numerical solutions of the different approximations for the Quantum Transverse Ising model and the Quantum Random Field Ising model in two dimensional lattices.

Predicting future states of harvested marine populations requires an understanding of how intrinsic time delay processes and volatile phenomena (e.g., impulsive mortality) act in concert to alter the dynamic population trajectory. Separately, the effects (on population dynamics) of time-delays, and impulses, have been studied theoretically by several authors. This paper shows an example approach, where the effects of impulses and time-delays are integrated in the same modeling framework, to understand how they may alter the predictability of future population states. The paper uses a stage-structured, Impulsive-Delay-Differential-Equation (IDDE) model to describe a single species marine population system. It presents results based on numerical experiments.

FoxP3+ regulatory T (Treg) cells comprise a highly dynamic population that restrains autoreactivity. Although complete or long-term depletion of Foxp3+CD4+ Treg cells in adult mice has been shown to result in chronic inflammation and autoimmune disease, the impact of transient Treg-cell depletion on self-reactive responses is poorly defined. A new study published in this issue of the European Journal of Immunology [Eur. J. Immunol. 2014. 44: 3621–3631] shows that, although transient depletion of Treg cells in mice is swiftly followed by recovery of Treg-cell numbers, the “rebounded” population fails to maintain tolerance, culminating in severe autoimmune gastritis. This commentary explores new questions about the quantitative and qualitative aspects of Treg-cell function in immunological tolerance raised by this study and others.

Made available in DSpace on 2018-11-12T17:28:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-04-01. Added 1 bitstream(s) on 2018-11-12T17:37:09Z : No. of bitstreams: 1 S2179-84512017000100003.pdf: 686601 bytes, checksum: 8ff5229b8b0c0262309db5b3e9e1a16a (MD5) RESUMO Em áreas onde os recursos estão localizados em locais discretos, a dispersão humana é mais convenientemente modelada considerando a população dividida em regiões discretas (patches). Neste trabalho, desenvolvemos um modelo espaço discreto geral para analisar a propagação da doença da dengue. No processo de modelagem matemática, levamos em consideração as populações humanas e a circulação de um único sorotipo de mosquitos da dengue. A mobilidade dos seres humanos suscetíveis, infectados e recuperados entretodos os patches é considerada. As fases aquáticas com distintas capacidades de suporte são consideradas dentro de cada patch. Além disso, um número arbitrário de patches podem ser usados para simular a propagação da doença da dengue. Este modelo espacialmente discreto foi desenvolvido para resolver problemas epidemiológicos, em que interações homem-vetor e a mobilidade humana desempenham um papel importante. Com base nos resultados numéricos obtidos, podemos recomendar o modelo em patches para a resolução de problemas epidemiológicos em Dinâmica Populacional. ABSTRACT In areas where resources are located in patches or discrete locations, human dispersal is more conveniently modeled, in which the population is divided into discrete patches. In this work we develop a general discrete model to analyze the spread of Dengue disease. In the process of mathematical modeling we take into account the human populations and the circulation of a single serotype of dengue mosquitoes. The movements of susceptible, infected and recovered humans among all patches are considered. Aquatic phases with different carrying capacities are considered within the patches. Also an arbitrary number of patches can be used to simulate the spread of dengue disease. In this paper we performed numericalexperiments to show the applicability of this methodology to investigate the dengue disease problem. The general discrete space model was developed for solving epidemiological problems whereas the human-vector interactions and human mobilities play an important role. Based on our numerical results, we may recommend the general patches model for solving epidemiological problems in Population Dynamics. UNESP Instituto de Biociências de Botucatu Departamento de Bioestatística UNESP Instituto de Biociências de Botucatu Departamento de Bioestatística

This study presents an integration of Evolving Spiking Neural - Network (ESNN) with Dynamic Population Particle Swarm Optimization (DPPSO). The original ESNN framework does not automatically modulate its parameters’ optimum values. Thus, an integrated framework is proposed to optimize ESNN parameters namely, the modulation factor (mod), similarity factor (sim), and threshold factor (c). DPPSO improves the original PSO technique by implementing a dynamic particle population. Performance analysis is measured on classification accuracy in comparison with the existing methods. Five datasets retrieved from UCI machine learning are selected to simulate the classification problem. The proposed framework improves ESNN performance in regulating its parameters’ optimum values.

We developed a comprehensive, flexible dynamic model that estimates all-cause mortality for a hypothetical cohort. All model input is user-specified. In the base case, members of the cohort may be exposed to a high risk product as they age. The counterfactual scenario includes exposure to both a high risk and a lower risk product. The model sorts the population into age and exposure categories, and applies the appropriate mortality rates to each category. The model tracks individual exposure histories, and estimates, at the end of each modeled age category, the number of survivors in the two exposure scenarios (base case and counterfactual), and the difference between them. Markov Chain Monte Carlo techniques are used to estimate the variability of the results. Model output was compared against US and Swedish life tables using population-specific tobacco exposure transition probabilities derived from the literature, and it produced similar survival estimates.

A variety of processes used across, for example the cosmetics, pharmaceutical and chemical industries involve two-phase liquid–liquid interactions. The quality of liquid–liquid emulsification systems may be importantly related to the droplet size distribution. The population balance equation (PBE) can be used to describe complex processes where the accurate prediction of the dispersed phase plays a major role for the overall behaviour of the system. In recent years, the high-order least-squares method has been applied to approximate the solution to population balance (PB) problems. From the chemical engineering point of view, the least-squares method is associated with complex algebra. Moreover, in previous chemical engineering publications the method has been outlined using rather compact mathematical notations. For this reason, in this study, details of the least-squares algebra and implementation issues are revealed. The solution strategy is illustratively applied to a test problem: a liquid–liquid emulsification system with breakage and coalescence events in a stirred tank.

In this paper, a non-linear mathematical model is proposed and analysed to study the role of technology in combating social crimes in a dynamic population by considering immigration and emigration rates of susceptible population and criminals. The problem is modelled by considering five interacting variables, namely the density of susceptible population, the density of criminals, the density of removed (isolated) criminals, the density of crime burden and the level of technology used to control crime. The proposed model is analysed by using the stability theory of differential equation and simulation. The model analysis shows that the crime burden decreases considerably as the level of technology increases. It is noted that the crime in a society can be controlled almost completely if criminals from the general population are removed by intensive use of technology.

The purpose of this research was to estimate the cost‐effectiveness of mammographic screening to supplement the results of the National Evaluation of Breast Cancer Screening which identified the mortality benefit as the most sensitive parameter. This appraisal used a different computer model, MISCAN, which models the effects of introducing a national screening program into a previously unscreened population, rather than basing estimates on the assumption of a fully established program. For the 40 to 49 age group a mortality reduction of 8 per cent was assumed, rather than the 30 per cent estimate utilised in the National Evaluation. The revised estimate is based on the two Swedish trials (Malmo and WE). New estimates for treatment costs were also incorporated into the MISCAN model. The cost‐effectiveness of the policy recommended in the National Evaluation Report, $11 000 per life year saved with two‐yearly screening of women over 40, is estimated by the MISCAN model to be dollar;20 300. These differences arise partly from the difference in mortality effects for the 40 to 49 age group, but also from differences inherent in the steady‐state and dynamic population approaches to modelling premature deaths averted. The MISCAN results confirm that screening for women over 50 is more cost‐effective than screening women under 50. Screening all women aged 50 to 69 every two to three years is reasonable value for money. For women aged 40 to 49 the mortality benefit and cost‐effectiveness is less clear, and it would be prudent to allow screening in this group until further evidence is available. 1993 Public Health Association of Australia

Traditional exposure studies that link concentrations with population data do not always take into account the temporal and spatial variations in both concentrations and population density. In this paper we present an integrated model chain for the determination of nation-wide exposure estimates that incorporates temporally and spatially resolved information about people's location and activities (obtained from an activity-based transport model) and about ambient pollutant concentrations (obtained from a dispersion model). To the best of our knowledge, it is the first time that such an integrated exercise was successfully carried out in a fully operational modus for all models under consideration. The evaluation of population level exposure in The Netherlands to NO2 at different time-periods, locations, for different subpopulations (gender, socio-economic status) and during different activities (residential, work, transport, shopping) is chosen as a case-study to point out the new features of this methodology. Results demonstrate that, by neglecting people's travel behaviour, total average exposure to NO2 will be underestimated by 4% and hourly exposure results can be underestimated by more than 30%. A more detailed exposure analysis reveals the intra-day variations in exposure estimates and the presence of large exposure differences between different activities (traffic > work > shopping > home) and between subpopulations (men > women, low socio-economic class > high socio-economic class). This kind of exposure analysis, disaggregated by activities or by subpopulations, per time of day, provides useful insight and information for scientific and policy purposes. It demonstrates that policy measures, aimed at reducing the overall (average) exposure concentration of the population may impact in a different way depending on the time of day or the subgroup considered. From a scientific point of view, this new approach can be used to reduce exposure misclassification.

Polarisation processes, which began in Croatia in the 1950's, resulted in disparate socio-economic development, in an uneven spatial distribution of the population, and in a concentration of people, jobs and housing in urban settlements. Coastal cities, as hubs and agents of socio-economic development, in their regions became focal points for the concentration of the population, while islands and hinterland areas suffered depopulation and demographic ageing. Intense in-migration had a positive influence on the demographic development of coastal cities. They became hotbeds of bioreproduction and up to the most recent intercensus period (1991–2001) displayed dynamic population growth. However political and economic changes in this recent period, together with the effects of the war, deepened and accelerated increasingly unfavourable demographic processes, which were reflected in an overall reduction of the population of coastal Adriatic cities, as well as in a deterioration of its structure. Decreasing fertility, demographic ageing and changes in life values brought about a transformation of the family, and hence changes in the size of households and in the relations among family members. The general trend today involves a gradual reduction in the number of household members, and a continuous increase in the number of two and one-member households.

In this paper we describe the application of a newly developed population dynamics model to time-dependent coastal flood exposure assessment at the French Atlantic coast. The DynaPop-X approach is largely top-down-driven, using national and regional data sources as primary disaggregation input. Modeled at 100m resolution and 1h temporal intervals dynamic population fluctuations such as commuting patterns and work hours as well as leisure activities are represented. Two selected municipalities in the study area are compared in terms of their population exposure profiles, highlighting stark differences in the temporal exposure peaks.

In this paper, distance-based locally informed particle swarm optimizer is introduced with dynamic population size and constant neighborhood size. The population is reduced from a larger size for exploration and a smaller size for exploitation. The simulation study is conducted extensively on the shifted and rotated benchmark problems. The results show that the proposed algorithm outperforms the current state-of-art algorithms in solving shifted and rotated unimodal and multimodal problems.

Sensory systems utilize dynamical response properties of neurons to extract features of spatiotemporally varying stimuli. We propose a dynamic population coding of sensory stimuli in which the stimulus features are encoded into a spatiotemporal firing pattern of neuron population. Using electrolocation of weakly electric fish as a model system, we study how the spatiotemporal features of electric field modulated depending on the distance and size of an object are encoded into the spatial distribution and time interval between burst spikes of neuron population. We showed that the information about distance and size of object are represented as a function of the spatial area of and time interval between the synchronous firing of neuron population in a higher nucleus.

It is often difficult to estimate abundance for a dynamic population, i.e., one that is moving through the survey area or in which birth or mortality rates are high. One approach is to estimate the proportion of animals present during each survey, using a model that estimates the dynamics of the survey proportion of the population. However, this can increase the uncertainty of the estimates if the dynamics parameters are not well estimated. Here we approached this problem by developing methods using hierarchical model structures, which allow us to share information on the dynamics parameters across years. We applied this modeling approach to the estimation of residence time and spawning biomass for New Zealand hoki (Macruronus novaezelandiae) in Cook Strait spawning grounds. By sharing parameters across years, we obtained better parameter estimates than by the traditional assumption that the dynamics in one year are independent of those of other years. By integrating the estimation of residence time into ...

The Method of mathematical models of Malthus and Verhults were applied on ten years data collected from Magaram Poultry Farm to determine the nature of population growth, population decay or constant growth in a Poultry Farm, and independent t-test as well as one way Anova were used to compare the predicted values and observed values in order to find out whether there is significant difference between the observed and predicted values using these two models. Keywords : Birth rate, sustainable population, overcrowding, harvesting, independent t-test and one way Anova.

Demographic composition and dynamics of animal and human populations are important determinants for the transmission dynamics of infectious disease and for the effect of infectious disease or environmental disasters on productivity. In many circumstances, demographic data are not available or of poor quality. Since 1999 Switzerland has been recording cattle movements, births, deaths and slaughter in an animal movement database (AMD). The data present in the AMD offers the opportunity for analysing and understanding the dynamic of the Swiss cattle population. A dynamic population model can serve as a building block for future disease transmission models and help policy makers in developing strategies regarding animal health, animal welfare, livestock management and productivity. The Swiss cattle population was therefore modelled using a system of ordinary differential equations. The model was stratified by production type (dairy or beef), age and gender (male and female calves: 0-1 year, heifers and young bulls: 1-2 years, cows and bulls: older than 2 years). The simulation of the Swiss cattle population reflects the observed pattern accurately. Parameters were optimized on the basis of the goodness-of-fit (using the Powell algorithm). The fitted rates were compared with calculated rates from the AMD and differed only marginally. This gives confidence in the fitted rates of parameters that are not directly deductible from the AMD (e.g. the proportion of calves that are moved from the dairy system to fattening plants).

This paper states the fundamental principles of the Statistical Models for Mobile Population (SMMP), and on the basis of the main features of various mobile places, designs statistical parameters and establishes corresponding mathematical models, so as to convert the dynamic population into the static population which is fit for drafting city population maps.

Studies have focused on the roles of the gonadotrope subsets defined by cytochemical and morphological tools. The evidence points to groups of gonadotropes that may be stimulated to mature and secrete to support surge activity. We postulate that these gonadotropes stem from the medium-sized subset. Other gonadotropes may more involved with maintenance functions. Perhaps these come from the larger cell pools. Monohormonal gonadotropes may play unique roles, such as FSH secretion early in estrus. Some may be immature, others may be regulatory and play both paracrine or autocrine roles in the pituitary cell population. We also recognize that one of the limitations of the current-day cytochemical techniques is that it does not define the entire gonadotrope population in any given two-label protocol. Nevertheless, based on past cytochemical studies, assumptions are made about the extent to which the cells express both hormones or behave in a uniform manner. These assumptions have led researchers to focus on one subset of the gonadotrope population. In their attempts to simplify the population to be studied, they may have eliminated important regulatory, secretory, or monohormonal gonadotropes from the pool. The approach is valid, as long as they recognize that they are studying a subset of a complex and dynamic population.

Consider a uniformly mixing population which grows as a super-critical linear birth and death process. At some time an infectious disease (of SIR or SEIR type) is introduced by one individual being infected from outside. It is shown that three different scenarios may occur: 1) an epidemic never takes off, 2) an epidemic gets going and grows but at a slower rate than the community thus still being negligible in terms of population fractions, or 3) an epidemic takes off and grows quicker than the community eventually leading to an endemic equilibrium. Depending on the parameter values, either scenario 1 is the only possibility, both scenario 1 and 2 are possible, or scenario 1 and 3 are possible., 11 pages

A method for predicting response to selection and inbreeding depression in a dynamic population for amount of inbreeding was derived and illustrated with an example of selection under full-sib mating.

The purpose of this article is to present in elementary mathematical and statistical terms a simple way to quickly and effectively teach and understand case-control studies, as they are commonly done in dynamic populations-without using the rare disease assumption. Our focus is on case-control studies of disease incidence ('incident case-control studies'); we will not consider the situation of case-control studies of prevalent disease, which are published much less frequently.

The objective of this research was to investigate the dynamics of population, productivity, and output of Bali cattle in region of Kepulauan Yapen Regency, Papua Province. The research was carried out for 3 months, started inJuly until September 2009. The materials included 103 farmers as the respondent and 211 heads of Bali cattle. The result showed that reproductive efficiency (RE) was 88.38%, natural increase (NI) 18.18% and net replacement ratevalue (NRR) of Bali cattle male and female were 234.28% and 189.59% each. The potency and compotition of Bali cattle being exported every year without disturbing the existing population was about 13.11% equal to 354 cattle,consist of the remains of replacement stock (male cattle) about 4.27% equal to 115 cattle, culled not productive cattle of 3.18% male equal to 86 cattle and 5.67% for female equal to 153 cattle. Dynamic population of Bali cattle from 2004 until 2008 increased 6.6% per year in average and in 2013 population is estimated to be 3,028 cattle with the potency of about 2,153 cattle.(Keywords: Male Bali cattle, Population dynamics, Productivity)

The key of the “Healthy Chongqing” project is human health, which depends on exercises, which further largely relies on physical exercises. Many study show that people having different sexuality, age and occupations have different preference over types and time slots of exercises. This study analyzed the dynamic population structure of Chongqing and proved the existence of significant difference between city and agriculture population and between groups with different ages. Based on these analysis, this study further proposed that “Healthy Chongqing” should be planed group-specifically and then carried out gradually based on the characteristics of population structure. This study could potentially provide a theory foundation for the sustainable development of the “Healthy Chongqing” project.

This paper explores an idealized dynamic population sizing strategy for solving additive decomposable problems of uniform scale. The method is designed on top of the foundations of existing population sizing theory for this class of problems, and is carefully compared with an optimal fixed population sized genetic algorithm. The resulting strategy should be close to a lower bound in terms of what can be achieved, performance-wise, by self-adjusting population sizing algorithms for this class of problems., Comment: 14 pages, submitted to ACM GECCO-2011

As the performance of differential evolution (DE) is significantly affected by its mutation schemes and parameter settings when solving different problems, this paper proposes a simple yet efficient co-evolutionary DE (CEDE) to enhance the algorithm performance. The CEDE algorithm uses multiple populations to optimize the problem cooperatively, with each population using different operators and/or different parameters. Moreover, as different populations may show different performance on the same problem, we further design an efficient adaptive migration strategy (AMS) to dynamically control the population size of different populations. The CEDE algorithm is tested and compared on four benchmark functions. Experimental results demonstrate the good performance of CEDE when compared with conventional DEs using different operators and/or parameters.

According to the high accuracy of load model in power system, a novel dynamic population variation genetic programming with Kalman operator for load model in power system is proposed. First, an evolution load model called initial model in power system evolved by dynamic variation population genetic programming is obtained which has higher accuracy than traditional models. Second, parameters in initial model are optimized by Kalman operator for higher accuracy and an optimization model is obtained. Experiments are used to illustrate that evolved model has higher accuracy 4.6∼48% than traditional models and It is also proved the performance of evolved model is prior to RBF network. Furthermore, the optimization model has higher accuracy 7.69∼81.3% than evolved model.

We survey the recent literature on designing auctions and mechanisms for dynamic settings. Two settings are considered: those with a dynamic population of agents or buyers whose private information remains fixed throughout time; and those with a fixed population of agents or buyers whose private information changes across time. Within each of these settings, we discuss both efficient (welfare-maximizing) and optimal (revenue-maximizing) mechanisms.

Largely unexplained increases in breast cancer incidence of about 1% per year have been documented back to the 1940s. Since 1982, breast cancer incidence in women aged 40 years and above has been increasing at a faster rate than this long-term secular trend, especially in women aged 60 years and above. Increases in the use of mammography since 1982 (which have been documented in population surveys of women) provide the most plausible explanation for the incidence increase over the long-term secular trend. A study by White et al. (J Natl Cancer Inst 1990;82:1546-52) found that, for women aged 45-64 years, the increase in mammography utilization could explain the incidence increase, while for women aged 65-74 years, it could account for only half the increase. The authors have developed an alternative model to that of White et al. that incorporates estimates of differential lead time (time from screen detection to clinical detection in the absence of screening) by age group. Using this model, the authors show that if older women have longer lead times, than similar increases in mammography utilization across age groups will lead to a larger incidence increase in older women. Thus, the observed increases in mammography utilization are generally concordant with increases in incidence, even in the older age groups.

This paper proposes a novel distributed differential evolution algorithm, namely Distributed Differential Evolution with Explorative---Exploitative Population Families (DDE-EEPF). In DDE-EEPF the sub-populations are grouped into two families. Sub-populations belonging to the first family have constant population size, are arranged according to a ring topology and employ a migration mechanism acting on the individuals with the best performance. This first family of sub-populations has the role of exploring the decision space and constituting an external evolutionary framework. The second family is composed of sub-populations with a dynamic population size: the size is progressively reduced. The sub-populations belonging to the second family are highly exploitative and are supposed to quickly detect solutions with a high performance. The solutions generated by the second family then migrate to the first family. In order to verify its viability and effectiveness, the DDE-EEPF has been run on a set of various test problems and compared to four distributed differential evolution algorithms. Numerical results show that the proposed algorithm is efficient for most of the analyzed problems, and outperforms, on average, all the other algorithms considered in this study.