The paper addresses daily migration systems in East Herzegovina, employing a model for determination of daily urban systems, focusing on daily population migrations as key indicators. Industrialization and urbanization have contributed to an increase in daily migrations, where part of the population works in non-agricultural sectors without permanently relocating to cities. This has led to a decrease in both permanent and daily migrations from rural areas to cities, accompanied by an aging rural population. Daily migrations entail workers, pupils, and students who regularly commute for work and school. The analysis covered migration zones of both city and municipal centers of East Herzegovina, using the data on workforce and pupil daily migrations (representative sample). Two zones of impact of city centers have been identified, each with different daily migration intensities: the intensive impact zone with more than 65% daily migrants and the weak impact zone with less than 35% daily migrants. The data on daily migrations in East Herzegovina suggest that the daily migration system is very poor. The exception is the municipality of Gacko, where workforce migrations from demographically sustainable settlements in the lower parts of the municipality towards the Gacko mine and power plant have been recorded. In the region, depopulation of rural areas is noticeable, along with the phenomenon of demographically depleted settlements and intensive migrations towards urban centers. With an exception of Nevesinje, the secondary migration system is poorly developed due to the small number of settlements with pronounced functional capacities. In the city of Trebinje and the municipalities of Bileća, Gacko, and Nevesinje, two zones of different daily migration intensities have been registered. On the other hand, in the municipalities of Ljubinje, Berkovići, and East Mostar, such zones have not been recorded due to small population and poor functional capacities of central settlements. This study helps us understand spatial and socioeconomic aspects of daily migrations in East Herzegovina and their impact on the local urban and rural systems.
We study a density-dependent Markov jump process describing a population where each individual is characterized by a type, and reproduces at rates depending both on its type and on the population type distribution. We are interested in the empirical distribution of ancestral lineages in the population process. First, we exhibit a time-inhomogeneous Markov process, which allows to capture the behavior of a sampled lineage in the population process. This is achieved through a many-to-one formula, which relates the expected value of a functional evaluated over the lineages in the population process to the expectation of the functional evaluated along this time-inhomogeneous process. This provides a direct interpretation of the underlying survivorship bias, as illustrated on a minimalistic population process. Second, we consider the large population regime, when the population size grows to infinity. Under classical assumptions, the population type distribution converges to a deterministic limit. Here, we focus on the empirical distribution of ancestral lineages in this large population limit, for which we establish a many-to-one formula. Using coupling arguments, we further quantify the approximation error which arises when sampling in this large population approximation instead of the finite-size population process.
We prove the existence of a Radner equilibrium in a model with population growth and analyze the effects on asset prices. A finite population of agents grows indefinitely at a Poisson rate, while receiving unspanned income and choosing between consumption and investing into an annuity with infinitely-lived exponential preferences. After establishing the existence of an equilibrium for a truncated number of agents, we prove that an equilibrium exists for the model with unlimited population growth. Our numerics show that increasing the birth rate reduces oscillations in the equilibrium annuity price, and when younger agents prioritize the present more than older agents, the equilibrium annuity price rises compared to a uniform demographic.
In cybersecurity, Intrusion Detection Systems (IDS) serve as a vital defensive layer against adversarial threats. Accurate benchmarking is critical to evaluate and improve IDS effectiveness, yet traditional methodologies face limitations due to their reliance on previously known attack signatures and lack of creativity of automated tests. This paper introduces a novel approach to evaluating IDS through Capture the Flag (CTF) events, specifically designed to uncover weaknesses within IDS. CTFs, known for engaging a diverse community in tackling complex security challenges, offer a dynamic platform for this purpose. Our research investigates the effectiveness of using tailored CTF challenges to identify weaknesses in IDS by integrating them into live CTF competitions. This approach leverages the creativity and technical skills of the CTF community, enhancing both the benchmarking process and the participants' practical security skills. We present a methodology that supports the development of IDS-specific challenges, a scoring system that fosters learning and engagement, and the insights of running such a challenge in a real Jeopardy-style CTF event. Our findings highlight the potential of CTFs as a tool for IDS evaluation, demonstrating the ability to effectively expose vulnerabilities while also providing insights into necessary improvements for future implementations.
Klaus Kähler Holst, Andreas Nordland, Julie Funch Furberg
et al.
Analysis of data from randomized controlled trials in vulnerable populations requires special attention when assessing treatment effect by a score measuring, e.g., disease stage or activity together with onset of prevalent terminal events. In reality, it is impossible to disentangle a disease score from the terminal event, since the score is not clinically meaningful after this event. In this work, we propose to assess treatment interventions simultaneously on the terminal event and the disease score in the absence of a terminal event. Our proposal is based on a natural data-generating mechanism, respecting that a disease score does not exist beyond the terminal event. We use modern semi-parametric statistical methods to provide robust and efficient estimation of the risk of terminal event and expected disease score conditional on no terminal event at a pre-specified landmark time. We also use the simultaneous asymptotic behaviour of our estimators to develop a powerful closed testing procedure for confirmatory assessment of treatment effect on both onset of terminal event and level of disease score in the absence of a terminal event. A simulation study mimicking a large-scale outcome trial in chronic kidney patients as well as an analysis of that trial is provided to assess performance.
Third-generation ground-based gravitational wave detectors are expected to observe $\mathcal{O}(10^5)$ of overlapping signals per year from a multitude of astrophysical sources that will be computationally challenging to resolve individually. On the other hand, the stochastic background resulting from the entire population of sources encodes information about the underlying population, allowing for population parameter inference independent and complementary to that obtained with individually resolved events. Parameter estimation in this case is still computationally challenging, as computing the power spectrum involves sampling $\sim 10^5$ sources for each set of hyperparameters describing the binary population. In this work, we build on recently developed importance sampling techniques to compute the SGWB efficiently and train neural networks to interpolate the resulting background. We show that a multi-layer perceptron can encode the model information, allowing for significantly faster inference. We test the network assuming an observing setup with CE and ET sensitivities, where for the first time we include the intrinsic variance of the SGWB in the inference, as in this setup it presents a dominant source of measurement noise.
Stein Menting, Ronald McDowell, Enya Redican
et al.
Objective
Adolescence is a vulnerable period for onset of depression. Socioeconomic deprivation may elevate the risk of depression. We explored the risk of depression in early adulthood in relation to deprivation during adolescence.
Approach
97,561 individuals aged 10-14 years were grouped at baseline (2010) using small-area indicator of area-level deprivation (measured in quintiles) and linked with yearly antidepressant prescriptions (2010–2021). A logistic random-intercept multilevel model estimated the longitudinal trajectory of yearly antidepressant prescriptions (2010-2021) between deprivation quintiles in 2010, adjusting for sex and age at baseline.
Results
In 2010, the marginal probability of receiving antidepressants for an average young person differed little between those living in the most (0.0028: 95%CI=0.0025,0.0032) and least (0.0027: 0.0023,0.0032) deprived areas (p=0.75). By 2021, the marginal probability had increased more for those who lived in the most deprived areas in 2010 (0.191: 0.187,0.195) compared to those who lived in the least deprived areas in 2010 (0.140: 0.135,0.145)(p<0.001). Estimated antidepressant prescriptions were higher in females compared to males (Odds Ratio[OR]=3.15: 3.00,3.29) and increased per year of age at baseline (OR=1.26: 1.24,1.28).
Conclusions
Growing up in more socially deprived areas is associated with an increase in antidepressant prescription risk during early adulthood. Improvements in administrative data access and linkage are needed to further explore these findings.
Implications
Policy makers and data custodians should recognise the potential for administrative data in identifying social disadvantage and associated vulnerabilities in the general population, and take steps to make this data accessible to the research community.
Jeanne Childs, Lucy Griffiths, Helen Hodges
et al.
Objective
To determine the prevalence of functional impairments in children with disabilities receiving care and support in Wales between 2016 and 2022, and to investigate risk factors associated with being placed in care amongst these children.
Method
This study used Children Receiving Care and Support (CRCS) Census records held in the Secure Anonymised Information Linkage Databank. We examined the proportion of children with specific impairments by their looked-after status, using bar charts and Upset plots. CRCS records were linked to demographic datasets to obtain information on area-level deprivation, and we conducted multivariable logistic regression analyses to model risk factors associated with being placed in care for children with disabilities.
Results
Of 38,165 children receiving care and support, 10,075 (26%) had a disability, and 3,360 (33%) of these children were placed in care. Older children were less likely to be placed in care than infants (e.g. for age group 1‒4: OR 0.37 (95% CI 0.24‒0.56)). Children of mixed ethnicity were more likely to be placed in care compared to White children (2.17 (1.65‒2.85)). Child mental health problems were associated with being placed in care (1.82 (1.60‒2.07)) as were parental mental health problems (1.44 (1.29‒1.60)), parental substance/alcohol misuse (3.16 (2.81‒3.56)), parental learning disability (2.92 (2.51‒3.38)), and domestic abuse (1.48 (1.31‒1.66)).
Conclusions
This new evidence may assist in the planning and provision of appropriate ongoing care and support for these children and their families to help prevent entry into the care system.
This paper is a sequel to an evolving research project on a diagrammatic methodology called thinging machine (TM). Initially, it was proposed as a base for conceptual modelling (e.g., conceptual UML) in areas such as requirement engineering. Conceptual modelling involves a high-level representation of a real-world system that integrates various components to refine it into a more concrete (computer) executable form. The TM project has progressed into a more comprehensive approach by applying it in several research areas and expanding its theoretical and ontological foundation. Accordingly, the first part of the paper involves enhancing some TM aspects related to structuring events in existence, such as absent events. The second part of the paper focuses on how to classify events and the kinds of relationships that can be recognized among events. The notion of events has occupied a central role in modelling. It influences computer science and such diverse disciplines as linguistics, probability theory, artificial intelligence, physics, philosophy and history. In TM, an event is defined as the so-called thimac (thing/machine) with a time breath that infuses dynamism into the static description of the thimac called a region. A region is a diagrammatic specification based on five generic actions: create, process, release, transfer and receive. The results of this research provide (a) an enrichment of conceptual modelling, especially concerning varieties of existence, e.g., absent events of negative propositions, and (b) a proposal that instead of semantic categorizations of events, it is possible to develop a new type of classification based on graphs grounded on the TM model diagrams.
Mehdi Feyzolahpour, Hasan Ghasemlu, Mostafa Mahdavi Fard
This article investigates the human impact on the mangrove forest in the Qeshm Geopark on the Qeshm Island in the south of Iran from 1986 to 2020. The area of mangrove forests increased by 14% from 5,131 hectares in 1986 to 5,472 hectares in 2000, and to 5,967 hectares in 2020. The mangrove forest is threatened by oil and gas facilities and a zinc smelter located on the island. The average concentration of nickel in sediment (97.2 μg/g) and in leaves (3.1 μg/g) was higher than the average concentration of vanadium in sediment (38.7 μg/g) and in leaves (0.5 μg/g). The results showed that the transfer coefficient of nickel and vanadium from root to leaf on the dry side of the Qeshm habitat (r = 0.597 and r = 0.516, respectively) was positively correlated with pH. Therefore, increasing the pH leads to an increased metal transfer from the root to the leaf, which endangers the mangrove habitat on the island. The mangrove forest in the vicinity of the zinc factory is threatened by high concentrations of lead (244.2 ppm), zinc (3172.8 ppm), arsenic, and cadmium found in the soil sample.
Cada actividad que se realiza en la vida cotidiana requiere hacer, en la mayoría de los casos, una reflexión de las posibles consecuencias que habrá que enfrentar. Por supuesto, para hacer el contraste de estos resultados con los fenómenos que se observan en el día a día, será necesario contar con muchos datos que ayuden a generar información, que finalmente, servirá para tomar las mejores decisiones. Hacer estas interpretaciones requiere estar en permanente contacto con el acontecer mundial: económico, social y cultural. Además, será necesario conocer sobre los diferentes elementos tecnológicos (por ejemplo, software y hardware) que, de manera gratuita, están a la disposición de la mayoría de nuestra población. Para la Universidad Nacional Autónoma de Honduras, es de vital importancia asumir el liderazgo en cuanto al manejo de la estadística y de todos aquellos elementos tecnológicos que permitan la visualización de datos, especialmente, en estos momentos en los que el país, posterior a la pandemia, necesita retomar la senda del desarrollo.
In the context of population genetics, active information can be extended to measure the change of information of a given event (e.g., fixation of an allele) from a neutral model in which only genetic drift is taken into account to a non-neutral model that includes other sources of frequency variation (e.g., selection and mutation). In this paper we illustrate active information in population genetics through the Wright-Fisher model.
Despite its historical and biological stability, the sex ratio at birth (SRB) has risen in parts of the world in the last several decades. The resultant demographic consequences, mostly on sex imbalance, are well documented, typically including "missing girls/women" and "marriage squeeze." However, the SRB-induced impact on demographic dynamics, particularly its underlying mechanism, has not been explored in depth. We aim to investigate the impact of the SRB rise on the size, structure, and growth of a population, particularly emphasizing on population aging. We provide a simple framework, derived from classical stable population models, to analyze how the SRB rise can reduce the population size and make the population old. We demonstrate that the cohorts born with a higher SRB are smaller in size than those with a lower SRB. As the affected cohorts are born into the population, their smaller size will reduce the total population size, thereby lifting the fraction of old people that were born with the original SRB and have the same size as before. The resultant population aging speed increases as the cohorts with the new SRB take an increasing share of the population. This study adds that, in addition to fertility and mortality, the SRB can be a driving factor of population dynamics, especially when it moves far above normal biological levels.
Gestation is the growth of an embryo which starts from conception and ends at the beginning of labor. The most common direct causes of complications in pregnancy respectively are preeclampsia (28.7%), bleeding (22.42%), and infection (3.45%). The most common infection that is experienced by mothers due to complications of pregnancy is due to premature ruptured membranes (65%). The purpose of this study was to determine the characteristics of pregnant women who experienced premature ruptured membranes at Assalam Hospital, Gemolong. This is a descriptive study with a cross-sectional design. The population is all pregnant women with premature ruptured membranes (KPD) at Assalam Hospital, Gemolong, in April–May 2015, totalling 36 women. The sample was all pregnant women with premature ruptured membranes (KPD) at Assalam Hospital, Gemolong, throughout April–May 2015 and the sampling technique used was non probability sampling. The secondary data were obtained from medical record data at Assalam Hospital, Gemolong, from April to May 2015. The results showed that the characteristics of pregnant women with KPD were that they were mostly 20–35 years of age (91.7%), had primiparous parity (63.9%), were mostly working mothers (72.2%), and had secondary education (80.6%).
Kathleen Falster, Mark Hanly, Rhiannon Pilkington
et al.
Introduction
A recent independent review of the child protection system in New South Wales (NSW), Australia, highlighted the need for whole-of-government reform to improve outcomes for children at risk of, or experiencing, maltreatment. Population-level evidence on outcomes of children who enter and progress through the child protection system is currently lacking.
Objectives and Approach
We aimed to quantify developmental vulnerability at age five among children who enter and progress through the child protection system during early childhood to demonstrate the value of cross-sectoral data linkage to inform and evaluate policy at a population-level. We used Australian Early Development Census (AEDC) data linked to cross-sectoral population datasets in NSW, including birth registrations, perinatal, and child protection
notification and out-of-home care (OOHC) placement data. Linked AEDC data, collected in 2009 and 2012, are
available for 153,670 NSW children. Socio-demographic and perinatal characteristics available in the linked data were used to characterise the population.
Results
21,179 (13.9%) children had ≥1 ‘screened in’ notification, 4927 (3.2%) had ≥1 substantiated abuse and neglect notification, and 2177 (1.4%) had ≥1 OOHC placement before their fifth birthday. Indicators of disadvantage and adverse birth outcomes were more common among children who progressed to higher levels of the child protection system. The proportion developmentally vulnerable on ≥1 domains of the AEDC increased for children who entered and progressed through the child protection system; from 21% of children with no contact with child protection before age five, to 39% of children with ≥1 ‘screened in’ notification, 50% with ≥1 substantiated notification, and 54% with ≥1 OOHC placement before their fifth birthday. Comparison of findings from other Australian jurisdictions with similar data will be discussed.
Conclusion/Implications
This study demonstrates there is scope to improve developmental outcomes through targeted interventions among children who become known to child protection during early childhood in NSW. Moreover, it illustrates that cross-sectoral data linkage can be used to inform and evaluate policy reforms to drive better outcomes for vulnerable children.
We present a new statistical test that examines the consistency of the tails of two empirical distributions at multiple thresholds. Such distributions are often encountered in counting experiments, in physics and elsewhere, where the significance of populations of events is evaluated. This multi-threshold approach has the effect of "stacking" multiple events into the tail bin of the distribution, and thus we call it the Event Stacking Test. This test has the ability to confidently detect inconsistencies composed of multiple events, even if these events are low-significance outliers in isolation. We derive the Event Stacking Test from first principles and show that the p-value it reports is a well-calibrated representation of noise fluctuations. When applying this test to the detection of gravitational-wave transients in LIGO-Virgo data, we find that it performs better than or comparably to other statistical tests historically used within the gravitational-wave community. This test is particularly well-suited for detecting classes of gravitational-wave transients that are minimally-modeled, i.e., gravitational-wave bursts. We show that the Event Stacking Test allows us to set upper limits on the astrophysical rate-density of gravitational-wave bursts that are stricter than those set using other statistical tests by factors of up to 2 - 3.