Traditional population datasets are largely static and therefore unable to capture the strong temporal dynamics of human presence driven by daily mobility. Recent smartphone-based mobility data offer unprecedented spatiotemporal coverage, yet translating these opportunistic observations into accurate population estimates remains challenging due to incomplete sensing, spatially heterogeneous device penetration, and unstable observation processes. We propose a Stable-Attendance Anchor Calibration (SAAC) framework to reconstruct hourly population presence at the Census block group level across the United States. SAAC formulates population estimation as a balance-based population accounting problem, combining residential population with time-varying inbound and outbound mobility inferred from device-event observations. To address observation bias and identifiability limitations, the framework leverages locations with highly regular attendance as calibration anchors, using high schools in this study. These anchors enable estimation of observation scaling factors that correct for under-recorded mobility events. By integrating anchor-based calibration with an explicit sampling model, SAAC enables consistent conversion from observed device events to population presence at fine temporal resolution. The inferred population patterns are consistent with established empirical findings in prior mobility and urban population studies. SAAC provides a generalizable framework for transforming large-scale, biased digital trace data into interpretable dynamic population products, with implications for urban science, public health, and human mobility research. The hourly population estimates can be accessed at: https://gladcolor.github.io/hourly_population.
The article aims to determine the preferences of Polish consumers in the use of the subscription model in their leisure time behaviors, taking into account the size of their place of residence. The study employed a diagnostic survey method and statistical analysis as the research approach. The authors' research has shown great interest in the subscription model among Polish respondents in behaviors related to spending leisure time; however, no significant differences were observed between the studied groups based on place of residence, indicating a consistent pattern of consumer preferences among respondents from both urban and rural environments. The main areas of interest turned out to be primarily VoD platforms and music streaming, and the most important factor influencing consumer behavior in the context of subscription services is the economic factor, mainly the price of the subscription...n.
BACKGROUND: Laws imposing criminal penalties for extramarital affairs stir intense debates in several countries, highlighted by recent repeals in countries like India, South Korea, and Taiwan. However, we currently lack empirical studies of their societal impacts. OBJECTIVE: This study examines the impact of decriminalizing extramarital affairs on women’s attitudes toward divorce in cases of potential spousal infidelity in South Korea. METHODS: We analyze the first five waves of the Korean Longitudinal Survey of Women and Families, which provides a nationally representative sample of adult women in South Korea. The fifth wave coincides with the public announcement of the adultery law’s repeal. For causal identification, we leverage the potentially exogenous timing of the Constitutional Court’s decision in a difference-in-differences analysis. RESULTS: Our findings reveal a notable shift in attitudes after the repeal: The decriminalization of extramarital affairs has led women to be less likely to consider a husband’s infidelity as justifying divorce on its own. CONCLUSIONS: Decriminalizing adultery laws can affect societal views, shifting how women perceive spousal infidelity as a basis for divorce. CONTRIBUTION: While discussions about adultery laws frequently rely on empirical arguments, significant research gaps remain on their societal effects. This study provides what is, to our knowledge, the first empirical and potentially causal analysis of the consequences of decriminalizing adultery, an issue that sparks considerable debate in many countries. It establishes an empirical basis for further exploration, encouraging continued research and more informed public discussions. Future research directions are also briefly discussed.
We present a full sampling of the hierarchical population posterior distribution of merging black holes using current gravitational-wave data. We directly tackle the most relevant intrinsic parameter space made of the binary parameters (masses, spin magnitudes, spin directions, redshift) of all the events entering the GWTC-3 LIGO/Virgo/KAGRA catalog, as well as the hyperparameters of the underlying population of sources. This results in a parameter space of about 500 dimensions, in contrast with current investigations where the targeted dimensionality is drastically reduced by marginalizing over all single-event parameters. In particular, we have direct access to (i) population parameters, (ii) population-informed single-event parameters, and (iii) correlations between these two sets of parameters. We quantify the fractional contribution of each event to the constraints on the population hyperparameters. Our implementation relies on modern probabilistic programming languages and Hamiltonian Monte Carlo, with a continuous interpolation of single-event posterior probabilities. Sampling the full hierarchical problem is feasible, as demonstrated here, and advantageous as it removes some (but not all) of the Monte Carlo integrations that enter the likelihood together with the related variances.
Population ageing is a typical feature of population development in the majority of countries in the world. In each population, this process is specific –whether in terms of the timing of its onset or the factors that modify the process of population ageing. The main aim of this article is to identify the processes of population ageing in the districts of Slovakia. A regional analysis of this process focused on population ageing in Slovak districts in the years 2011 and 2021 using cluster analysis. The results of the cluster analysis of population ageing identified
northern and eastern Slovakia as districts whose populations have a younger age structure. The western and southwestern districts of Slovakia have populations with an old age structure. In 2021, this age polarity began to change the territory of Slovakia. The suburbanised region of the capital, Bratislava, is becoming significant, as the population in the districts there is getting younger.
The trade-off between the costs of childcare provision and the benefits of having an increased proportion of women, particularly women with dependent children, in employment is one of the most taxing social issues for Western governments. In countries like Northern Ireland, the limited subsidised childcare provision for preschool and primary school children has been partially offset by a rise in informal childcare though this has been considerably hard to assess both in terms of magnitude and effect. Using the entire 2011 Census cohort of mothers with children aged 1 to 16 years of age, we argue that co-resident grandparents have a substantial positive impact on maternal labour force participation in Northern Ireland. The presence of a co-resident grandparent was associated with an increase of 3.7 percentage points in employment for single-parent mothers and 2 percentage points for mothers in two-parent households. Mothers with co-resident grandparents report an increase of 2.7 percentage points for a single mother and of 3.7 percentage points for a mother in a two-parent household being in full-time employment than mothers without. Overall, the presence of a co-resident grandparent was associated with at least a 3.2 percentage point increase in labour force participation among mothers with primary-school-age children.
The merging black hole binaries detected by the LIGO-Virgo-KAGRA (LVK) gravitational-wave observatories, may help us shed light on how such binaries form. In addition, these detections can help us probe the hypothesized primordial black holes, a candidate for the observed abundance of dark matter. In this work, we study the black-hole mass distribution obtained from the LVK binary black hole merger events. We obtain that distribution by first associating a skewed normal distribution to each event detected with a signal to noise ratio (SNR) $>$ 8 and then summing all such distributions. We also simulate black hole binaries from two separate populations of merging binaries. One of these is a stellar-origin population that follows a mass-distribution similar to the zero-age mass function of stars. The second population of black holes follows a Gaussian mass-distribution. Such a distribution could approximate a population of black hole binaries formed from earlier black hole mergers in dense stellar environments, or binaries of primordial black holes. For those populations, we evaluate the number of detectable events and fit their combination to the LVK observations. In our work, we rely on a wide range of stellar-origin black-hole mass distributions. We find that the observed LVK events can be fitted much better by the combination of such a stellar-origin mass distribution and a Gaussian distribution, than by the stellar-origin mass distribution alone.
Stephan A. Fahrenkrog-Petersen, Saimir Bala, Luise Pufahl
et al.
Business process management (BPM) has been widely used to discover, model, analyze, and optimize organizational processes. BPM looks at these processes with analysis techniques that assume a clearly defined start and end. However, not all processes adhere to this logic, with the consequence that their behavior cannot be appropriately captured by BPM analysis techniques. This paper addresses this research problem at a conceptual level. More specifically, we introduce the notion of vitalizing business processes that target the lifecycle process of one or more entities. We show the existence of lifecycle processes in many industries and that their appropriate conceptualizations pave the way for the definition of suitable modeling and analysis techniques. This paper provides a set of requirements for their analysis, and a conceptualization of lifecycle and vitalizing processes.
We derive a central limit theorem for a spatial $Λ$-Fleming-Viot model with fluctuating population size. At each reproduction, a proportion of the population dies and is replaced by a not necessarily equal mass of new individuals. The mass depends on the local population size and a function thereof. Additionally, as new individuals have a single parental type, with growing population size, events become more frequent and of smaller impact, modelling the successful reproduction of a higher number of individuals. From the central limit theorem we derive a Wright-Malécot formula quantifying the asymptotic probability of identity by descent and thus isolation by distance. The formula reflects that ancestral lineages are attracted by centres of population mass and coalesce with a rate inversely proportional to the population size. Notably, we obtain this information despite the varying population size rendering the dual process intractable.
The global network of interferometric gravitational wave (GW) observatories (LIGO, Virgo, KAGRA) has detected and characterized nearly 100 mergers of binary compact objects. However, many more real GWs are lurking sub-threshold, which need to be sifted from terrestrial-origin noise triggers (known as glitches). Because glitches are not due to astrophysical phenomena, inference on the glitch under the assumption it has an astrophysical source (e.g. binary black hole coalescence) results in source parameters that are inconsistent with what is known about the astrophysical population. In this work, we show how one can extract unbiased population constraints from a catalog of both real GW events and glitch contaminants by performing Bayesian inference on their source populations simultaneously. In this paper, we assume glitches come from a specific class with a well-characterized effective population (blip glitches). We also calculate posteriors on the probability of each event in the catalog belonging to the astrophysical or glitch class, and obtain posteriors on the number of astrophysical events in the catalog, finding it to be consistent with the actual number of events included.
Joanne Ellison, Ann Berrington, Erengul Dodd
et al.
<b>Background</b>: Discrete-time event history analysis (EHA) is the standard approach taken when modelling fertility histories collected in surveys, where the date of birth is often recorded imprecisely. This method is commonly used to investigate the factors associated with the time to a first or subsequent conception or birth. Although there is an emerging trend towards the smooth incorporation of continuous covariates in the broader literature, this is yet to be formally embraced in the context of birth events. <b>Objective</b>: We investigate the formal application of smooth methods implemented via generalized additive models (GAMs) to the analysis of fertility histories. We also determine whether and where GAMs offer a practical improvement over existing approaches. <b>Methods</b>: We fit parity-specific logistic GAMs to data from the UK Household Longitudinal Study, learning about the effects of age, period, time since last birth, educational qualification, and country of birth. First, we select the most parsimonious GAMs that fit the data sufficiently well. Then we compare them with corresponding models that use the existing methods of categorical, polynomial, and piecewise linear spline representations in terms of fit, complexity, and substantive insights gained. <b>Results</b>: We find that smooth terms can offer considerable improvements in precision and efficiency, particularly for highly non-linear effects and interactions between continuous variables. Their flexibility enables the detection of important features that are missed or estimated imprecisely by comparator methods. <b>Contribution</b>: Our findings suggest that GAMs are a useful addition to the demographer's toolkit. They are highly relevant for motivating future methodological developments in EHA, both for birth events and more generally.
Dmitry Zubarev, Carlos Raoni Mendes, Emilio Vital Brazil
et al.
There is an increasing need in our society to achieve faster advances in Science to tackle urgent problems, such as climate changes, environmental hazards, sustainable energy systems, pandemics, among others. In certain domains like chemistry, scientific discovery carries the extra burden of assessing risks of the proposed novel solutions before moving to the experimental stage. Despite several recent advances in Machine Learning and AI to address some of these challenges, there is still a gap in technologies to support end-to-end discovery applications, integrating the myriad of available technologies into a coherent, orchestrated, yet flexible discovery process. Such applications need to handle complex knowledge management at scale, enabling knowledge consumption and production in a timely and efficient way for subject matter experts (SMEs). Furthermore, the discovery of novel functional materials strongly relies on the development of exploration strategies in the chemical space. For instance, generative models have gained attention within the scientific community due to their ability to generate enormous volumes of novel molecules across material domains. These models exhibit extreme creativity that often translates in low viability of the generated candidates. In this work, we propose a workbench framework that aims at enabling the human-AI co-creation to reduce the time until the first discovery and the opportunity costs involved. This framework relies on a knowledge base with domain and process knowledge, and user-interaction components to acquire knowledge and advise the SMEs. Currently,the framework supports four main activities: generative modeling, dataset triage, molecule adjudication, and risk assessment.
Arnab Dey, Mononito Goswami, Joo Heung Yoon
et al.
A significant proportion of clinical physiologic monitoring alarms are false. This often leads to alarm fatigue in clinical personnel, inevitably compromising patient safety. To combat this issue, researchers have attempted to build Machine Learning (ML) models capable of accurately adjudicating Vital Sign (VS) alerts raised at the bedside of hemodynamically monitored patients as real or artifact. Previous studies have utilized supervised ML techniques that require substantial amounts of hand-labeled data. However, manually harvesting such data can be costly, time-consuming, and mundane, and is a key factor limiting the widespread adoption of ML in healthcare (HC). Instead, we explore the use of multiple, individually imperfect heuristics to automatically assign probabilistic labels to unlabeled training data using weak supervision. Our weakly supervised models perform competitively with traditional supervised techniques and require less involvement from domain experts, demonstrating their use as efficient and practical alternatives to supervised learning in HC applications of ML.
A vast, two-volume list of all the towns and villages of the Kingdom of Poland was published in 1827, with the number of houses and residents, and the type of ownership specified in it. It was the only official publication issued by the then central statistical body of the state – The Statistical Office of the Government Commission for the Internal Affairs and Police. Due to the alphabetical order of the entries, with the absence of any territorial grouping or partial summaries, this potentially valuable source for historical and demographic studies has been of only marginal use to historians. An attempt was made at its digitisation and at entering the data into the database system in 2020. This paper presents the historical background of creating this list and uses selected examples to present new, previously unavailable data exploration and analysis opportunities that are offered by an electronic form.
History of Poland, Demography. Population. Vital events
Allison Feely, Elizabeth Wall-Wieler, Leslie L Roos
et al.
Introduction: When designing prospective and retrospective longitudinal cohort studies, investigators must make decisions about study duration (i.e. length of follow-up) and frequency of outcome measurement. The impact of these decisions have been previously investigated in the prospective setting, but have not been described for retrospective cohort studies.
Objectives: To examine the impact and potential challenges of longitudinal design decisions in retrospective cohort studies and illustrate the effects of varying study duration and frequency of outcome measurement in the retrospective setting using a numeric example.
Methods: Linked administrative data from Manitoba was used. The cohort included all mothers who experienced the death of an infant between April 1, 1999 and March 31, 2012 and a matched (3:1) group of mothers who did not experience death. A generalized linear mixed model was used to model differences in the trend in the number of healthcare contacts for the two groups. Holding sample size constant, the model was fit to the data for combinations of duration and frequency. Estimated standard errors and regression coefficients were compared.
Results: A total of 2576 mothers were included; 644 experienced death of an infant and 1932 were matched to this group. Thirteen combinations of frequency (1, 2, 3, 4 periods/year) and duration (1, 2, 3, 4 years) were compared. As frequency increased from 1 to 4 periods/year, the standard error of the group-time-time interaction decreased up to 98.9%. As duration increased from 1 to 4 years, the standard error of the interaction decreased up to 96.9%. As frequency and duration increased, the coefficients trended toward zero.
Conclusions: Retrospective designs using administrative data offer greater flexibility to select time-related design elements than prospective designs, but present potential new challenges. Recommendations about how to select and report time-related design decisions in retrospective cohort studies should be included in reporting guidelines.
Resumo O texto tem como referência sujeitos agrupados social e culturalmente a partir de um processo de emigração/imigração, cujas estruturas remontam às sociedades emissoras. Transcendendo o estabelecimento no município de Curitiba, Paraná, o grupo transforma-se gradativamente em contato com a sociedade brasileira e com outros agrupamentos de origem imigrante, erigindo fronteiras étnicas. Um dos direcionamentos da investigação foi conduzido por análises de comportamentos reprodutivos dos imigrantes e descendentes. O objetivo, neste estágio, é ultrapassar o porquê para tentar resolver o problema do como, apesar da ausência de documentação “qualitativa” que permitiria discernir a intimidade dos casais amostrados. Desse modo, colocam-se algumas questões teórico-metodológicas considerando o papel dos indivíduos, no âmbito do conceito das sociabilidades. Ou seja, na esfera das relações indivíduo-sociedade, investiga-se quais seriam as variáveis teóricas que poderiam ajudar a entender o que os números parecem denunciar. Para isso, consideram-se as relações interpessoais – incluindo o convívio intra e intergeracional – nos limites das mencionadas fronteiras. Com essa finalidade, a análise privilegia contextos que permitem sintetizar a dinâmica da etnicidade. Igualmente, propõe-se um balanço teórico-metodológico tendo como foco as minhas pesquisas, orientadas, num sentido epistemológico mais lato, por estudos “demográficos”; os dados de base foram amostrados a partir da metodologia da reconstituição de famílias.
Cellular populations such as avascular tumors and microbial biofilms may "invade" or grow into surrounding populations. The invading population is often comprised of a heterogeneous mixture of cells with varying growth rates. The population may also exhibit mutational instabilities, such as a heavy deleterious mutation load in a cancerous growth. We study the dynamics of a heterogeneous, mutating population competing with a surrounding homogeneous population, as one might find in a cancerous invasion of healthy tissue. We find that the shape of the population interface serves as an indicator for the evolutionary dynamics within the heterogeneous population. In particular, invasion front undulations become enhanced when the invading population is near a mutational meltdown transition or when the surrounding "bystander" population is barely able to reinvade the mutating population. We characterize these interface undulations and the effective fitness of the heterogeneous population in one- and two-dimensional systems.
Este artículo analiza las diferencias en la integración económica de migrantes internos, hombres y mujeres, tanto voluntarios como forzados, según su pertenencia étnica en Colombia. Utilizando información de la Encuesta Nacional de Calidad de Vida para el periodo de 2012 a 2016, se estiman una serie de modelos estadísticos que explican tres dimensiones de integración económica: la participación laboral, la posición en el empleo y el nivel de ingresos percibidos mensualmente. Aplicando el marco analítico de la interseccionalidad, este estudio da cuenta de diferentes procesos de integración en poblaciones heterogéneas donde se intersectan la condición migratoria, la pertenencia étnica y el sexo como formas de identidad. Los resultados sugieren que la población desplazada muestra los resultados más desventajosos en las tres dimensiones. Sin embargo, dentro de este grupo las mujeres afrodescendientes y los hombres indígenas experimentan las condiciones más precarias de inserción laboral.
Social Sciences, Demography. Population. Vital events
Background
Pharmaceutical data can be used to identify the presence of drug-treated chronic diseases (CD) in individuals using assigned World Health Organization Anatomic Therapeutic Chemical (ATC) classifications of medicines prescribed. ATC codes define treatment domains and provides a method to case define CD that has previously been used to estimate CD prevalence within populations.
Main Aim
We determined selected CD incidence from an administrative pharmaceutical dataset, and compared them with published CD incidence results.
Approach
An Australian Pharmaceutical Benefits Scheme (PBS) database covering the period 2003-14 was used for this study. The earliest prescriptions exchanged by individuals for an ATC defined CD were identified and the annual count recorded. These values were combined with Australian population census data to calculate the annual incidence of ATC defined CD. Australian PBS derived incidence estimates (PDI) were compared with published Australian and world incidence data.
Results
The PDI of 16 chronic diseases were compared with incidence estimates using self-report surveys from the literature. Mean percentage differences between PDI estimates varied greatly when compared to survey data (mean 33% (SD ±79%). Diabetes (-29%), gout (4%), glaucoma (69%) and tuberculosis (14%) showed closer associations. In contrast, PDI estimates (n/1000/year) showed particularly high incidence levels as compared with self-report data for dyspepsia (16.9 v 4.5), dyslipidaemia (11.6 v 5.6) and respiratory illness (17.6 v 2.6).
Conclusion
Incidence estimates of drug treated chronic disease can be obtained using pharmaceutical data and may be a useful source for a number of conditions. Some PDI differ considerably from survey data. The interpretation of PDI requires context on how a particular CD presents. Accuracy and relevance are likely to depend upon how drug treatments relate to the initial management of the chronic disease.