Species populations often modify their environment as they grow. When environmental feedback operates more slowly than population growth, the system can undergo boom-bust dynamics, where the population overshoots its carrying capacity and subsequently collapses. In extreme cases, this collapse leads to total extinction. While deterministic models typically fail to capture these finite-time extinction events, we propose a stochastic framework, derived from an individual-based model, to describe boom-bust-extirpation dynamics. We identify a noise-driven, threshold-like behavior where, depending on initial conditions, the population either undergoes a "boom" or is extirpated before the expansion occurs. Furthermore, we characterize a transition between an excitable regime, where most trajectories are captured by the absorbing state immediately after the first bust, and a persistent regime, where most populations reach a metastable state. We show that this transition is governed by the diffusion strength and the ratio of environmental-to-population timescales. This framework provides a theoretical basis for understanding irreversible transitions in invasive species, plant succession, and microbial dynamics.
Traditional approaches to assessing poverty, which primarily rely on income levels, fail to reflect the diverse challenges experienced by those living in precarious conditions. As a result, complementary measures, such as material deprivation, have been developed. This study challenges the dichotomous categorisation of material deprivation in the UK and proposes a multi-group classification approach. The analytical sample is represented by 5,395 families (with children) in the UK. The 2019/20 Household Below Average Income dataset was selected for analysis as it represents the main source of material deprivation information in the UK. Latent Class Analysis was applied to this dataset. A combination of goodness of fit and interpretability favoured a five-class solution. Measurement equivalence was tested by comparing different family types and was confirmed, reinforcing the robustness of our results. The analysis revealed the nuanced reality and typologies of material deprivation, highlighting the complex interplay between child and adult deprivation and the prioritisation of resources.
Abstract While many studies investigate the effects of parental separation on children, whether in terms of short-term adjustment or long-term effects, the tendency is to examine each outcome in isolation, thus overlooking any interdependencies between them. In this paper, we focus on the impact of parental separation on two main aspects defining the transition to adulthood: attainment of economic independence and the formation of one’s own household. Specifically, we examine in a comprehensive way whether young Italians whose parents separated during childhood or youth follow different trajectories compared to those whose parents remained together. Using data from two cross-sectional rounds of the “Families and Social Subjects” survey conducted in 2009 and 2016, we implement a sequence analysis multistate model procedure. Our results suggest that children of non-intact families follow particular trajectories, especially with respect to the formation of their own household, where cohabitation is favored.
Abstract This study examines the relationship between growing up in single-parent families and school absence in Andalusia (Spain), considering differences according to adolescents’ social background. Empirical analyses of data from the Social Survey 2010: Education and Housing show that adolescents growing up in single-parent families have, on average, a higher number of school absences than their peers in two-parent families. These disadvantages are greater for adolescents with low social backgrounds, regardless of whether this is measured by parental education or housing tenure. Both economic resources (lower household income) and social resources (poor relationship with absent parent) partially explain the differences in school absence rates amongst adolescents growing up in single-parent families. School environment (teacher–student relationship, atmosphere amongst students, experiences of school violence or ownership of educational institution) are not influential in explaining educational disadvantage amongst adolescents from different family structures, although they are strong predictors of school absence.
Luciana Pedro, Amaya Azcoaga-Lorenzo, Colin McCowan
Pregnancy-related research using routinely collected data is increasing. Electronic Health Records (EHR) are a robust resource because they can provide information on a large population of pregnant women covering prolonged periods at a reasonable cost. Moreover, information is collected prospectively and is thus free from recall bias. However, these data sources also present challenges. Information is gathered for clinical purposes and often recorded in different datasets (prescriptions, hospital admission, demography, birth records, etc.). Therefore, a significant data management effort must be made to convert all the information into structured and meaningful datasets in which identifying the timing of conception, outcomes of interest, multiple pregnancies, and interpregnancy periods can easily be done.
In this study, we linked Scottish Maternity Records between 2007 and 2021 (1,575,153 pregnancies, 493,629 women) to demographics data, datasets with International Classification of Diseases (ICD) diagnostic codes for all inpatient stays and day cases in hospitals, and Prescribing Information System (PIS) for data on all medications from primary care. After combining these datasets using R codes, we developed a simple tree-based algorithm that visually represents each woman at each pregnancy and the related health conditions. Presenting data in this way helps identify relevant clinical questions and the temporal relation of different pregnancies. As an example, we identified the progression of multimorbidity through pregnancies and characterised how multimorbidity changes from one pregnancy to another, considering the woman's health conditions and social class.
Dadang Suhenda, Evalina Franciska Hutasoit, Mochammad Wahyu Ghani
et al.
Family planning counselors or Penyuluh Keluarga Berencana (PKB) are frontline implementers of the population, family planning, and family development program at the grassroots level. This study aims to know the consumer satisfaction index of the PKB performance of The National Population and Family Planning Board or Badan Kependudukan dan Keluarga Berencana (BKKBN) representative of West Java. The consumer satisfaction index was measured using the Permenpan RI (Regulation of the Minister for Administrative Reform and Bureaucratic Reform of the Republic of Indonesia) Number 14 (2017). The study method is descriptive comparative through a purposive sampling survey using a 9 Likert scale. Based on the study, it is shown that the consumer satisfaction index of the PKB performance in 2018 is 71,89, which is service quality category C, which means underperformance. Based on the service, the timing of service is the lowest index, as much as 0.29, and the average of 2.64. PKB does not utilize the time for counseling and post-service assistance well or tends to be slow. Out of 10 steps of PKB, only 2 indicators are measured as satisfactory, which is the formal figure approach and the monitoring and evaluation of the record and reporting (RR). Hence, it is recommended that the BKKBN to maintain the PKB performance through training and development continually, a guidelines book, and periodic training of the 10 PKB steps, as well as the mapping of the affordability to reach PKB service.
Alphin J Thottupattu, Jayanthi Sivaswamy, Bharath Holla
et al.
Understanding distinct neurological aging patterns across various populations is vital in the context of a globally aging populace. This study seeks to unravel the structural variations in the aging brain, taking into consideration different ethnic backgrounds. MRI data from Indian, Chinese, Japanese, and Caucasian populations were analyzed using a two-pronged approach. Initially, a group analysis was performed involving tissue segmentation through FSL-FAST, examining gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Subsequently, a continuous model-based analysis was employed, defining aging as a diffeomorphic transformation, which facilitated a detailed intra- and inter-population analysis, and examined both global anatomy and age-dependent distances of each population in comparison to the Indian population. Detailed insights into the spatial distribution of brain deformations over time were obtained, with particular focus on anatomical changes relative to a reference time point. The proposed comprehensive structural comparison framework, applied to a sample dataset encompassing four distinct populations, represents a pioneering effort to compare structural differences related to brain aging on a global scale. Subsequent studies utilizing larger datasets and applying the proposed analysis across groups based on various criteria will further advance our understanding of aging-related changes.
Ayanabha De, Mayank Narang, Manoj Puravankara
et al.
In this work, we have carried out a systematic analysis of the VLASS quick look catalogs together with \textit{Gaia DR3} to identify the optical counterparts of 3~GHz radio emitters within 500~pc to obtain a homogeneous statistical sample of stellar radio sources. We have identified distinct populations of 3 GHz emitters across the \textit{Gaia DR3} color-magnitude diagram. We also present candidate sources (transient, highly variable or background artifacts) which can be confirmed by follow-up observations. A majority of the detected sources constitute main sequence G, K and M-type stars including ultra-cool dwarfs. Pinning down the origin of radio emission from these populations can help us gain further insights into the origin of stellar and planetary magnetic fields. By analyzing the variation of brightness temperature of the sources with their spectral type, we have tentatively associated possible emission mechanisms with different object types. We inspected the correlation between quiescent radio and X-ray emission for our sample that can provide crucial insights into the current understanding of the Gudel-Benz relationship, which is essential for modeling steady radio emission and coronal heating. This VLASS-\textit{\textit{Gaia DR3}} analysis acts as a pilot study for follow-up observations at multiple wavelengths to better understand stellar structure, model flaring activities and detect radio emission caused by star-planet interactions.
We demonstrate an exact equivalence between classical population dynamics and Lindbladian evolution admitting a dark state and obeying a set of certain local symmetries. We then introduce {\em quantum population dynamics} as models in which this local symmetry condition is relaxed. This allows for non-classical processes in which animals behave like Schrödinger's cat and enter superpositions of live and dead states, thus resulting in coherent superpositions of different population numbers. We develop a field theory treatment of quantum population models as a synthesis of Keldysh and third quantization techniques and draw comparisons to the stochastic Doi-Peliti field theory description of classical population models. We apply this formalism to study a prototypical ``Schrödigner cat'' population model on a $d$-dimensional lattice, which exhibits a phase transition between a dark extinct phase and an active phase that supports a stable quantum population. Using a perturbative renormalization group approach, we find a critical scaling of the Schrödinger cat population distinct from that observed in both classical population dynamics and usual quantum phase transitions.
This study employed the MIMIC-IV database as data source to investigate the use of dynamic, high-frequency, multivariate time-series vital signs data, including temperature, heart rate, mean blood pressure, respiratory rate, and SpO2, monitored first 8 hours data in the ICU stay. Various clustering algorithms were compared, and an end-to-end multivariate time series clustering system called Time2Feat, combined with K-Means, was chosen as the most effective method to cluster patients in the ICU. In clustering analysis, data of 8,080 patients admitted between 2008 and 2016 was used for model development and 2,038 patients admitted between 2017 and 2019 for model validation. By analyzing the differences in clinical mortality prognosis among different categories, varying risks of ICU mortality and hospital mortality were found between different subgroups. Furthermore, the study visualized the trajectory of vital signs changes. The findings of this study provide valuable insights into the potential use of multivariate time-series clustering systems in patient management and monitoring in the ICU setting.
Robin Cavagnoud, Julie Baillet, María Eugenia Zavala de Cosío
Este artículo recuerda brevemente los fundamentos del enfoque biográfico, el paradigma del curso de vida asociado y los orígenes de la matriz Ageven, una herramienta desarrollada durante la década de 1980 en el marco de las encuestas retrospectivas y del análisis demográfico de biografías. Enseguida, se presenta una versión renovada en el uso cualitativo de este instrumento, al incluir niveles de observación individuales, familiares y contextuales y al agregar la identificación de secuencias en las historias de vida a partir de las rupturas biográficas. La matriz Ageven se convierte así simultáneamente en herramienta de representación y de análisis de datos biográficos cualitativos, revelando amplias posibilidades de apli1cación a diversas problemáticas demográficas y so2ciológicas. Se ilustra con el ejemplo de la maternidad adolescente en México.
Fall detection and classification become an imper- ative problem for healthcare applications particularity with the increasingly ageing population. Currently, most of the fall clas- sification algorithms provide binary fall or no-fall classification. For better healthcare, it is thus not enough to do binary fall classification but to extend it to multiple fall events classification. In this work, we utilize the privacy mitigating human skeleton data for multiple fall events classification. The skeleton features are extracted from the original RGB images to not only mitigate the personal privacy, but also to reduce the impact of the dynamic illuminations. The proposed fall events classification method is divided into two stages. In the first stage, the model is trained to achieve the binary classification to filter out the no-fall events. Then, in the second stage, the deep neural network (DNN) model is trained to further classify the five types of fall events. In order to confirm the efficiency of the proposed method, the experiments on the UP-Fall dataset outperform the state-of-the-art.
Izadi Maliheh, Vardanjani Mehdi Jafari, Varesi Hamidreza
The indices of housing serve as an important tool in planning for housing, in that they allow the parameters affecting housing to be recognised and any planning process to be facilitated. The purpose of the study is to investigate and to evaluate the housing situation in cities of Isfahan province. The study is applied and descriptive-analytic in terms of method. Thirty-nine indices were collected in the housing sector. Then the rate of prosperity and ranking of the cities were evaluated by TOPSIS method. Prosperity is defined here as an important index of housing that reflects the welfare of residents. The cities were then categorised into six levels of prosperity: Very important, Important, Partially important, Moderate, Poor and Very poor. The results from the study indicate an imbalance in the studied indices between the cities, and a clear disparity between the levels of prosperity in the cities, and the only city in the very prosperous group is Isfahan, with a rate of 0.813.
Airam Blancas, Stephan Gufler, Sandra Kliem
et al.
For a continuous state branching process with two types of individuals which are subject to selection and density dependent competition, we characterize the joint evolution of population size, type configurations and genealogies as the unique strong solution of a system of SDE's. Our construction is achieved in the lookdown framework and provides a synthesis as well as a generalization of cases considered separately in two seminal papers by Donnelly and Kurtz (1999), namely fluctuating population sizes under neutrality, and selection with constant population size. As a conceptual core in our approach we introduce the selective lookdown space which is obtained from its neutral counterpart through a state-dependent thinning of ``potential'' selection/competition events whose rates interact with the evolution of the type densities. The updates of the genealogical distance matrix at the ``active'' selection/competition events are obtained through an appropriate sampling from the selective lookdown space. The solution of the above mentioned system of SDE's is then mapped into the joint evolution of population size and symmetrized type configurations and genealogies, i.e. marked distance matrix distributions. By means of Kurtz' Markov mapping theorem, we characterize the latter process as the unique solution of a martingale problem. For the sake of transparency we restrict the main part of our presentation to a prototypical example with two types, which contains the essential features. In the final section we outline an extension to processes with multiple types including mutation.
Cornelius Fritz, Marius Mehrl, Paul W. Thurner
et al.
As relational event models are an increasingly popular model for studying relational structures, the reliability of large-scale event data collection becomes more and more important. Automated or human-coded events often suffer from non-negligible false-discovery rates in event identification. And most sensor data is primarily based on actors' spatial proximity for predefined time windows; hence, the observed events could relate either to a social relationship or random co-location. Both examples imply spurious events that may bias estimates and inference. We propose the Relational Event Model for Spurious Events (REMSE), an extension to existing approaches for interaction data. The model provides a flexible solution for modeling data while controlling for spurious events. Estimation of our model is carried out in an empirical Bayesian approach via data augmentation. Based on a simulation study, we investigate the properties of the estimation procedure. To demonstrate its usefulness in two distinct applications, we employ this model to combat events from the Syrian civil war and student co-location data. Results from the simulation and the applications identify the REMSE as a suitable approach to modeling relational event data in the presence of spurious events.
In this paper we analyze the effects of commuting and social inequalities for the epidemic development of the novel coronavirus (COVID-19). With this aim we consider a SEIRD (susceptible, exposed, infected, recovered and dead by disease) model without vital dynamics in a population divided into patches that have different economic resources and in which the individuals can commute from one patch to another (bilaterally). In the modeling we choose the social and commuting parameters arbitrarily. We calculate the basic reproductive number $R_0$ with the next generation approach and analyze the sensitivity of $R_0$ with respect to the parameters. Furthermore, we run numerical simulations considering a population divided into two patches to bring some conclusions on the number of total infected individuals and cumulative deaths for our model considering heterogeneous populations.
Hurricane María made landfall in Puerto Rico, in September 2017, causing economic damages and affecting the population by increasing temporarily increasing mortality and outgoing passenger flow. Because of the disruption in the migration flows, the volatility of this time series we must approach the production of population estimates, projections and forecasts carefully. Given that population estimates have been difficult to produce for Puerto Rico before Hurricane Maria and even more challenging following this disaster, this paper proposes an application of the demographic balancing equation using administrative records to produce population estimates on a monthly basis for Puerto Rico. A combination of data from: (1) monthly counts for deaths and births obtained from the Puerto Rico Vital Statistics Systems, (2) passenger flow data produced by the U.S. Bureau of Transportation Statistics, and (3) baseline census counts. I employ this approach to produce monthly estimates of the population for Puerto Rico, and use 2010 Census counts to assess the accuracy of the model. According to the 2010 decennial census, the population of Puerto Rico was 3,725,789 people; by employing the demographic balancing equation approach, the population was estimated to be 3,669,676 people in April 1, 2010. Using this model, I find that after Hurricane Maria, the population of Puerto Rico reached less than 3 million persons in December 2017 (2.97 million). The total population went back to over 3.0 million by January 2018 with an estimated population of 3.02 million people on September 2018.
<b>Background</b>: To date, several countries have documented changes over time in the pattern of seasonal fluctuations of births. Differences in these changes between countries allow us to better understand the social and economic factors determining birth seasonality. <b>Objective</b>: The aim of the present study is to explore birth seasonality in Poland over a period of 110 years. <b>Methods</b>: The study was conducted using the birth dates of 48,090,100 Polish citizens born in the years 1900-2009 and registered in the General Electronic System for Registration of the Population. I transformed the data into monthly time series of births, normalized the monthly birth rates for the unequal duration of months and years, and detrended by taking them to the centred 12-month average. Finally, I estimated seasonality patterns for particular decades by means of least squares regression on the harmonic model. <b>Results</b>: As many as three, relatively stable seasonal birth patterns occurred in Poland in the studied period. In 20th century Europe, the first one (1900-1919), characterised by a minimum birth rate in June, had previously only been observed in Italy. The second pattern with the spring peak and local peak in September remained almost unchanged in Poland for the longest time (1950-1979). Then, within a decade, it transformed into a new, third pattern (1990-2009), with peaks in July and September. <b>Contribution</b>: This article is the first to document in detail the changes in birth seasonality in Poland over a period of 110 years.
<b>Background</b>: In several European countries the excess mortality of nonmarried people relative to the married has increased. In this study we describe in detail the increasing mortality advantage of the married in Norway and investigate the extent to which changes in educational composition of marital-status groups can account for this increasing mortality gap. <b>Methods</b>: Using register data for the entire population of Norway, we estimated discrete-time hazard models for mortality at age 50-89 in years 1975-2008. We also estimated one-year death probabilities by age, period, marital status, education, and spouse's education. These were used to calculate period-specific age-standardized death probabilities for marital-status categories and hypothetical versions of these, assuming constant death probabilities in each educational group in each marital-status category or constant educational distributions. Hypothetical and observed versions were then compared. <b>Results</b>: The mortality of nonmarried people relative to married people increased sharply over the years 1975-2008. During the first part of this period, mortality was constant or even increasing among the never-married, who at the end of the period could be considered as lagging 30 years behind the married. Educational patterns have changed markedly, but this explains only up to 5Š of the increasing mortality disadvantage of the never-married. Educational changes have contributed more to the growing disadvantage of the widowed, while the picture is more mixed for the divorced. <b>Conclusions</b>: <b>Contribution</b>: We demonstrate that there has been a large widening in the marital-status differences in mortality in Norway since the 1970s and that little of this difference can be attributed to changes in educational distributions.