Objectives
The main aim of this research was to investigate what happens to students who leave school/college with A-level grades which have ‘little currency’ (i.e., grades D or below). Are their labour market returns (earnings) different from those of students with better grades (grades C or above)?
Method
We used Longitudinal Education Outcomes data, which connects individuals’ education with their employment and earnings. We selected students who left school between 2004/05 and 2011/12 and recorded their earnings in each year until 2019/20. We focused on A-level students who achieved: ‘E grades only’ or ‘D or E grades only’. Outcomes for students in these groups were compared to those of other groups: students with A-levels all at grades C or above; students with BTECs.
Descriptive statistics on earnings, overall and by students’ characteristics were produced. We also carried out multilevel regression analyses to control for individual-level characteristics and cohort.
Results
In the first few years after leaving school, the students with low A level grades (best grade E or best grade D) had very slightly higher mean daily earnings than students in the other groups. However, from year 5 onwards, students with better grades (lowest grade C) had a higher mean, and this advantage increased over time.
There were some differences in this result between students of different ethnic groups or gender. In particular, from year 5 onwards, Asian, Black, and Chinese students had more of an advantage (than White students did) if they were in the ‘lowest grade C’ group compared with the other groups.
Conclusion
The outcomes of this work provide evidence for policy decision-making which may benefit young people in England. Students who finish school with low A level grades should not be forgotten. Knowing their outcomes will help understand whether policy changes/interventions are needed to improve their prospects.
Yusuff Adebayo Adebisi, Serena Pattaro, Angela Henderson
et al.
Objectives
This study examines the associations between household living arrangements and COVID-19 outcomes (infection and severity) among people with intellectual and physical disabilities in Scotland. Understanding these associations will help identify disparities, inform pandemic preparedness, and contribute to evidence-based policies aimed at protecting vulnerable populations from infectious diseases.
Methods
A retrospective, population-based study is being conducted using linked administrative data covering approximately 90% of the Scottish population from March 1, 2020, to December 30, 2022. Cox Proportional Hazards Models will assess the associations between household living arrangements and COVID-19 outcomes. Data sources include the 2011 Census (disability status, demographics, socio-economic details), Community Health Index Register and Ordnance Survey data (household composition), and Public Health Scotland’s COVID-19 Research Database (infection status, hospitalizations, mortality, and pre-existing conditions).
Results
Data processing and preliminary analysis are underway. The study will evaluate differences in COVID-19 infection and severity (hospitalization and mortality) across various household living arrangements, comparing disabled and non-disabled populations. Expected findings include potential disparities based on household composition, such as differences in infection risk for those living alone, in shared residences, or institutional settings. Full results, including hazard ratios and statistical significance, will be presented at the conference.
Conclusion
This study will enhance understanding of how household living arrangements impact COVID-19 infection, hospitalization and mortality among disabled individuals compared to non-disabled individuals. By integrating novel measures of household composition with administrative health data, the findings will inform public health strategies aimed at reducing health inequalities and improving pandemic response planning for vulnerable populations.
The occurrence of some extreme events (such as marine heatwaves or exceptional circulations) can cause other extreme events (such as heatwave, drought and flood). These concurrent extreme events have a great impact on environment and human health. However, how to detect and quantify the causes and impacts of these extreme events by a data-driven way is still unsolved. In this study, the dynamic system method is extended to develop a method for detecting the causality between extreme events. Taking the coupled Lorenz-Lorenz systems with extreme event-driven coupling as an example, it is demonstrated that this proposed detecting method is able to capture the extreme event-driven causality, with even better causality detecting performance between concurrent extreme events. Comparison among three kinds of measured series, full measurements outperform partial ones in event-to-event causality detecting. The successful applicability of our proposed approach in Walker circulation phenomenon indicates that our method contributes a novel way to the study of causal inference in complex systems. This method offers valuable insights into multi-scale, nonlinear dynamics, particularly in uncovering associations among extreme events.
GW231123 is a merger of two black holes (BHs) whose inferred masses exceed $100\;{\rm M}_\odot$ typically; they are the most massive BHs among those discovered by gravitational wave (GW) observations. We examine if GW231123-like events can be formed from isolated Population (Pop) III binary stars by means of binary population synthesis calculations. We find that Pop III isolated binary stars can create GW231123-like events at a rate large enough to explain the discovery of GW231123, if two conditions are satisfied. First, Pop III stars evolve with inefficient convective overshooting, and second the $^{12}{\rm C}(α,γ)^{16}{\rm O}$ rate is $2σ$ lower than the standard value. On the other hand, GW190521, which is the most massive BHs in Gravitational Wave Transient Catalog 3, can be formed from isolated Pop III binary stars even if the $^{12}{\rm C}(α,γ)^{16}{\rm O}$ rate is the standard value. We reveal that the discovery of GW231123 is progressively putting constraints on possible parameter ranges of single star evolution models, assuming that all the GW events are formed through isolated binary evolution.
The format of graphing algorithms for genomic data has been a debate in recent biotechnology. In this paper, we discuss the construction of population graphs using said genomic data. We first examine the GENPOFAD distance measurement, developed by Joly et. al., and prove that this constitutes a metric function. We develop an algorithm to construct graphs to visualize the relationships between individuals in a population. We then provide a statistical analysis of these simulated population graphs, and show that they are distinct from randomly generated graphs, and also show differences from small-world graphs.
Annisa Intan Kholifatullah, Ana Fitrotul Laili, Miranda Feyza Nur Imania
et al.
Based on the results of the 2021 Family Data Collection, it was revealed that Ngadiluwih District, Kediri Regency, East Java Province has a high unmet need case of 19.25%. This unmet need case is far below the target set by the RPJMN for 2019-2024. The village with the highest unmet need rate in Ngadiluwih District is Mangunrejo Village with a case of 16.89%. Various factors contribute to the unmet need rate, including socioeconomic conditions. The purpose of this study was to analyze the occupational status of the intention to use contraception in couples of childbearing age with unmet needs in Mangunrejo Village. The research was conducted with a cross-sectional approach through analytic observational methods in Mangunrejo Village in April-June 2022. The method used was interviewing and distributing questionnaires to respondents. The sample used couples of childbearing age who fit the inclusion criteria in Mangunrejo Village. As for the total of 12 respondents working and 12 respondents not working, as many as 61.3% of respondents not working have the intention to use contraception and as many as 47.8% of working respondents have the intention to use contraception. The results of the analysis showed that there was no significant relationship between the employment status of unmet need women with intention to use contraception (p=0.325). So it can be concluded that reproductive couples in Ngadiluwih District who are in unmet need condition, do not intend to use contraception who are all of those who are workers
Nicolás Rodríguez-Segovia, Ashley J. Ruiter, Ivo R. Seitenzahl
Subdwarf B stars are a well-known class of hot, low-mass stars thought to be formed through interactions in stellar binary systems. While different formation channels for subdwarf B stars have been studied through a binary population synthesis approach, it has also become evident that the characteristics of the found populations depend on the initial set of assumptions that describe the sometimes poorly constrained physical processes, such as common envelope episodes or angular momentum loss during mass transfer events. In this work we present a parameter study of subdwarf B populations, including a novel analytic prescription that approximates the evolution of subdwarf B stars with hydrogen-rich outer shells, an element previously overlooked in rapid binary population synthesis. We find that all studied parameters strongly impact the properties of the population, with the possibility of igniting helium below the expected core-mass value near the tip of the red giant branch strongly affecting the total number of subdwarf B candidates. Critically, our newly proposed prescription for the evolution of subdwarf B stars with hydrogen-shells helps to reconcile theoretical predictions of surface gravity and effective temperature with observational results. Our prescription is useful in the context of rapid binary population synthesis studies and can be applied to other rapid binary population synthesis codes' output.
Event Stream Super-Resolution (ESR) aims to address the challenge of insufficient spatial resolution in event streams, which holds great significance for the application of event cameras in complex scenarios. Previous works for ESR often process positive and negative events in a mixed paradigm. This paradigm limits their ability to effectively model the unique characteristics of each event and mutually refine each other by considering their correlations. In this paper, we propose a bilateral event mining and complementary network (BMCNet) to fully leverage the potential of each event and capture the shared information to complement each other simultaneously. Specifically, we resort to a two-stream network to accomplish comprehensive mining of each type of events individually. To facilitate the exchange of information between two streams, we propose a bilateral information exchange (BIE) module. This module is layer-wisely embedded between two streams, enabling the effective propagation of hierarchical global information while alleviating the impact of invalid information brought by inherent characteristics of events. The experimental results demonstrate that our approach outperforms the previous state-of-the-art methods in ESR, achieving performance improvements of over 11\% on both real and synthetic datasets. Moreover, our method significantly enhances the performance of event-based downstream tasks such as object recognition and video reconstruction. Our code is available at https://github.com/Lqm26/BMCNet-ESR.
The situation of young workers is determined by the legal regulation of work. Of particular interest in this context is the traineeship, which is statistically proven to be the basis for many young people entering the labour market. In this context, it is especially important that national regulations are clear and stable to ensure the security of young workers. The Hungarian national regulations will be examined in this study, starting with statistical data, i.e. the extent to which traineeships are present, and examining the related legal relationships based on the EU conceptual background, with the aim of exploring whether the Hungarian legal framework guarantees status security for young trainees. Based on the legislation, case law and relevant literature, it can be concluded that the Hungarian national legislation on traineeship is fragmented, non-transparent, complex, and generally does not provide an impeccable basis for improving the labour market situation of young people from a labour law or social security perspective, and shows a number of inconsistencies in national and EU labour law.
Sudarmi Sudarmi, Linda Meliati, Siti Halimatussyaadiah
Prevention of pregnancy by various contraceptive methods remains an important part of medical practice and can occur during any reproductive cycle. The more types of contraceptive methods available, the more choices of contraceptive methods available for people. Many determinant factors cause women of childbearing age to choose contraceptives that suit their needs. This study aims to determine the determinants affecting women of childbearing age using contraceptives in West Nusa Tenggara Province. The design of this study is an analytical study (descriptive analysis) with a cross-sectional approach using secondary data from the 2019 SKAP Family Planning and Family Development Population Accountability Performance Survey (KKBPK) in the Province of West Nusa Tenggara (NTB). Data were analyzed using bivariate analysis using Chi-Square and multivariate with logistic regression. The results showed that the determinants that affect women of childbearing age in using contraceptive methods include: unmet need, age, parity, previous family planning experience, decision-making, knowledge, and visits to health facilities. The results of multivariate analysis of the most dominant decision-making factors influencing the use of contraceptive methods in women of childbearing age with an OR value of 174,666. It can be interpreted that the decision-making ability of women of childbearing age is 174,666 times more influencing the use of contraceptive methods compared to other variables. This study recommends empowering women of childbearing age through increasing knowledge by maximizing the individual counseling process so that women of childbearing age can choose contraceptive methods according to their needs.
Premraj Durairaj, Sathiyadevi Kanagaraj, Suresh Kumarasamy
et al.
Extreme events are unusual and rare large-amplitude fluctuations that occur can unexpectedly in nonlinear dynamical systems. Events above the extreme event threshold of the probability distribution of a nonlinear process characterize extreme events. Different mechanisms for the generation of extreme events and their prediction measures have been reported in the literature. Based on the properties of extreme events, such as rare in frequency of occurrence and extreme in amplitude, various studies have shown that extreme events are both linear and nonlinear in nature. Interestingly, in this work, we report on a special class of extreme events which are nonchaotic and nonperiodic. These nonchaotic extreme events appear in between the quasi-periodic and chaotic dynamics of the system. We report the existence of such extreme events with various statistical measures and characterization techniques.
This paper studies the bounded confidence model on growing fully-mixed populations. In this model, in addition to the usual opinion clusters, significant secondary clusters of smaller size appear systematically, while those secondary clusters appear erratically and include much fewer agents when the population is fixed. Through simulations, we derive the bifurcation diagram of the growing population model and compare it to the diagram obtained with an evolving probability density instead of agents, and with their equivalent with a fixed population. Our tests when changing the usual bounded confidence function into a smooth bounded confidence function suggest that these secondary clusters are mainly generated by a different mechanism when the population is growing than when it is fixed.
Samir Soneji, Hiram Beltrán-Sánchez, Jae Won Yang
et al.
Abstract As of 31 January 2021, 63.9 million cases and 1.4 million deaths had been reported in Europe and North America, which accounted for 62.5% and 62.4% of the global total, respectively. Comparing the level of mortality across countries has proven difficult because of inherent limitations in the most commonly cited measures (e.g., case-fatality rates). We collected the cumulative number of confirmed deaths from COVID-19 by age in 2020 from the L’Institut National d’études Démographiques (INED) database and Statistics Canada for 15 European and North American countries. We calculated age-specific death rates and age-standardized death rates (ASDR) for each country over a 1-year period from 6 February 2020 (date of first COVID-19 death in Europe and North America) to 5 February 2021 using established demographic methods. We estimated that COVID-19 was the second leading cause of death behind cancer in England and Wales and France and the third leading cause of death behind cancer and heart disease in nine countries including the US. Countries with higher all-cause mortality prior to the COVID-19 experienced higher COVID-19 mortality than countries with lower all-cause mortality prior to the pandemic. The COVID-19 ASDR varied substantially within country (e.g., a 5-fold difference among the highest and lowest mortality states in Germany). Consistently strong public health measures may have lessened the level of mortality for some European and North American countries. In contrast, many of the largest countries and economies in these regions may continue to experience a high mortality level because of poor implementation and adherence to such measures.
Antonella Guarneri, Francesca Rinesi, Romina Fraboni
et al.
Abstract Legal separation is a crucial step in the dissolving of marriages in Italy. Marriage and legal separation data come from administrative data sources and have been part of the civil registration and vital statistics system for a long time. These data make it possible to constantly monitor evolution of marital unions formation and dissolution over time and space. This study highlights the potential of combining administrative data at a macro level, aggregated by selected characteristics of the marriage and of the spouses. Data collection on legal separations is a complex process that brings together records from different administrative sources that have different transmission procedures. The system has rapidly evolved in recent years because of important normative changes. Pooling the two exhaustive data sources on marriages and separations we calculate duration-specific separation rates by selected spouses’ and wedding characteristics and estimate survival curves for 1975 marriage cohorts onward. Although the propensity to separate is increasing across marriage cohorts, the most recent first-marriage cohorts—those celebrated since the beginning of the new millennium—show a decreasing tendency to separate after short marriage durations. The most fragile unions are those celebrated in a civil ceremony in the north of Italy and that choose the separation of property regime. Couples in which the bride is more educated than the groom show a higher risk of separating. Differences by geographical area and celebration rite tend to reduce over time. This study contributes to existing information about the propensity to separate in Italy and the role that some characteristics of weddings and spouses play. It shows the potential for integrating information from marriage and separation registers when dealing with a relatively rare phenomenon at the population level and with information not usually collected in social surveys.
Elisavet Syriopoulou, Sarwar I Mozumder, Mark J Rutherford
et al.
When interested in a time-to-event outcome, competing events that prevent the occurrence of the event of interest may be present. In the presence of competing events, various statistical estimands have been suggested for defining the causal effect of treatment on the event of interest. Depending on the estimand, the competing events are either accommodated or eliminated, resulting in causal effects with different interpretation. The former approach captures the total effect of treatment on the event of interest while the latter approach captures the direct effect of treatment on the event of interest that is not mediated by the competing event. Separable effects have also been defined for settings where the treatment effect can be partitioned into its effect on the event of interest and its effect on the competing event through different causal pathways. We outline various causal effects that may be of interest in the presence of competing events, including total, direct and separable effects, and describe how to obtain estimates using regression standardisation with the Stata command standsurv. Regression standardisation is applied by obtaining the average of individual estimates across all individuals in a study population after fitting a survival model. With standsurv several contrasts of interest can be calculated including differences, ratios and other user-defined functions. Confidence intervals can also be obtained using the delta method. Throughout we use an example analysing a publicly available dataset on prostate cancer to allow the reader to replicate the analysis and further explore the different effects of interest.
Understanding the evolution of paper and author citations is of paramount importance for the design of research policies and evaluation criteria that can promote and accelerate scientific discoveries. Recently many studies on the evolution of science have been conducted in the context of the emergent science of science field. While many studies have probed the link problem in citation networks, only a few works have analyzed the temporal nature of link prediction in author citation networks. In this study we compared the performance of 10 well-known local network similarity measurements to predict future links in author citations networks. Differently from traditional link prediction methods, the temporal nature of the predict links is relevant for our approach. Our analysis revealed interesting results. The Jaccard coefficient was found to be among the most relevant measurements. The preferential attachment measurement, conversely, displayed the worst performance. We also found that the extension of local measurements to their weighted version do not significantly improved the performance of predicting citations. Finally, we also found that a neural network approach summarizing the information from all 10 considered similarity measurements was not able to provide the highest prediction performance.
Taraprasad Bhowmick, Yong Wang, Michele Iovieno
et al.
The fluid physics of the heat and mass transfer from an object in its wake has much importance for natural phenomena as well as for many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). We find the population density to be well described by a Lorentzian distribution. We observe this apparently universal form both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number.
We fit the ultrahigh-energy cosmic-ray (UHECR, $E\gtrsim0.1$ EeV) spectrum and composition data from the Pierre Auger Observatory at energies $E\gtrsim5\cdot10^{18}$ eV, i.e., beyond the ankle using two populations of astrophysical sources. One population, accelerating dominantly protons ($^1$H), extends up to the highest observed energies with maximum energy close to the GZK cutoff and injection spectral index near the Fermi acceleration model; while another population accelerates light-to-heavy nuclei ($^4$He, $^{14}$N, $^{28}$Si, $^{56}$Fe) with a relatively low rigidity cutoff and hard injection spectrum. A significant improvement in the combined fit is noted as we go from a one-population to two-population model. For the latter, we constrain the maximum allowed proton fraction at the highest-energy bin within 3.5$σ$ statistical significance. In the single-population model, low-luminosity gamma-ray bursts turn out to match the best-fit evolution parameter. In the two-population model, the active galactic nuclei is consistent with the best-fit redshift evolution parameter of the pure proton-emitting sources, while the tidal disruption events could be responsible for emitting heavier nuclei. We also compute expected cosmogenic neutrino flux in such a hybrid source population scenario and discuss possibilities to detect these neutrinos by upcoming detectors to shed light on the sources of UHECRs.
Background/rationale
The Western Australian (WA) government and the Centre for Data Linkage (CDL) at Curtin University are creating a large, de-identified researchable database – the Social Investment Data Resource (SIDR) – to support a key government initiative called Target 120 (T120). T120 delivers targeted early interventions to young offenders and their families to reduce the likelihood of re-offending.
Main Aim
The SIDR brings together de-identified data from across government to be used for actuarial assessment and social investment analytics to assess long-term costs and benefits of T120 interventions.
Methods
SIDR adopts a distributed linkage model where linkage workload is shared between the Department of Health Data Linkage Branch who curate WA Data Linkage System (WADLS) and the CDL. Design elements of the model included a common spine (embedded into the infrastructure of both groups), methods for leveraging quality from WADLS, and inclusion of family relationships data from the WA Family Connections database. The linkage model uses a combination of traditional and privacy-preserving record linkage (PPRL) methods. PPRL does not require release of personal identifiers; instead, data is irreversibly hashed prior to release for probabilistic linkage.
The resultant SIDR repository has been designed to be securely and strictly managed. Access is by authorised, approved users only.
Results
Use of a distributed linkage model, coupled with traditional and PPRL methods, is an innovative yet pragmatic way of delivering data linkage services to a large, cross-sectoral research project. PPRL methods enable inclusion of otherwise excluded datasets in the project. Sharing of workload harnesses linkage capacity and capabilities across the state. The SIDR includes health data, education records, justice, child protection, disability and housing data.
Conclusion
SIDR provides a resource for whole-of-government policy development, service evaluation, academic research and social investment analytics for T120 and beyond. The SIDR distributed linkage model has potential for adaptation and use elsewhere.