The increasing number of students enrolled in higher education institutions and the growing demand in the labour market for university graduates make the analysis of study success and study dropout ...more and more important. Dropping out from higher education is a complex process and students have very different motives for leaving university without obtaining a degree. We provide a detailed analysis of the different dropout reasons and aim at identifying distinctive types of dropout students using cluster analysis. The most important reasons for leaving university without a degree were in this study observed to be mainly related to interest and expectations concerning study programmes as well as aspects associated with student performance. Using hierarchical cluster analysis, we have found that the dropout decision was based on a variety of reasons, rather than a clear single motive. Our results provide higher education institutions insights into the process of dropping out and thereby a basis for suitable and more specific countermeasures.
The Crisis Management and Deposit Insurance Framework - which came into force about ten years ago - is under review by the European Commission. The need for its revision stems from the identification ...of certain shortcomings and inconsistencies that have emerged in its application in Europe and especially in Italy. The central topics of the debate focus on how resolution should be applied and on possible innovations regarding the tools that can be used to manage the crises of small and medium-sized banks, which until now have been managed on the basis of procedures and tools decided at the national level. The aim of this paper is to investigate the areas subject to reform, using as an evaluation parameter the objective of increasing the flexibility of the framework, as this is considered a fundamental requirement to ensure the full effectiveness of the overall banking crisis management system
Abstract
Mathematical modelling performs a vital part in estimating and controlling the recent outbreak of coronavirus disease 2019 (COVID-19). In this epidemic, most countries impose severe ...intervention measures to contain the spread of COVID-19. The policymakers are forced to make difficult decisions to leverage between health and economic development. How and when to make clinical and public health decisions in an epidemic situation is a challenging question. The most appropriate solution is based on scientific evidence, which is mainly dependent on data and models. So one of the most critical problems during this crisis is whether we can develop reliable epidemiological models to forecast the evolution of the virus and estimate the effectiveness of various intervention measures and their impacts on the economy. There are numerous types of mathematical model for epidemiological diseases. In this paper, we present some critical reviews on mathematical models for the outbreak of COVID-19. Some elementary models are presented as an initial formulation for an epidemic. We give some basic concepts, notations, and foundation for epidemiological modelling. More related works are also introduced and evaluated by considering epidemiological features such as disease tendency, latent effects, susceptibility, basic reproduction numbers, asymptomatic infections, herd immunity, and impact of the interventions.
This paper presents and studies a new epidemic SIR (Susceptible-Infectious-Recovered) model with susceptible recruitment and eventual joint vaccination efforts for both newborn and susceptible ...individuals. Furthermore, saturation effects in the infection incidence terms are eventually assumed for both the infectious and the susceptible subpopulations. The vaccination action on newborn individuals is assumed to be applied to a fraction of them while that on the susceptible general population is of linear feedback type reinforced with impulsive vaccination actions (in practice, very strong and massive vaccination controls) at certain time points, based on information on the current levels of the susceptible subpopulation. Apart from the above vaccination controls, it is also assumed that the average of contagion contacts can be controlled via intervention measures, such as confinements or isolation measures, social distance rules, use of masks, mobility constraints, etc. The main objectives of the paper are the achievement of a strictly decreasing infection for all time periods and that of the susceptible individuals over the initial period if they exceed the disease-free equilibrium value. The monitoring mechanism is the combined activation of intervention measures to reduce the contagion contacts together with the impulsive vaccination to reduce susceptibility. The susceptibility and recovery levels of the disease-free equilibrium point are suitably prefixed by the design of the regular feedback vaccination on the susceptible subpopulation.
Indoor size-fractioned particulate matter (PM) was measured in seven schools in Milan, to characterize their concentration levels in classrooms, compare the measured concentrations with the ...recommended guideline values, and provide a preliminary assessment of the efficacy of the intervention measures, based on the guidelines developed by the Italian Ministry of Healthand applied to mitigate exposure to undesirable air pollutants. Indoor sampling was performed from Monday morning to Friday afternoon in three classrooms of each school and was repeated in winter 2011-2012 and 2012-2013. Simultaneously, PM2.5 samples were also collected outdoors. Two different photometers were used to collect the PM continuous data, which were corrected a posteriori using simultaneous gravimetric PM2.5 measurements. Furthermore, the concentrations of carbon dioxide (CO2) were monitored and used to determine the Air Exchange Rates in the classrooms. The results revealed poor IAQ in the school environment. In several cases, the PM2.5 and PM10 24 h concentrations exceeded the 24 h guideline values established by the World Health Organization (WHO). In addition, the indoor CO2 levels often surpassed the CO2 ASHRAE Standard. Our findings confirmed that important indoor sources (human movements, personal clouds, cleaning activities) emitted coarse particles, markedly increasing the measured PM during school hours. In general, the mean PM2.5 indoor concentrations were lower than the average outdoor PM2.5 levels, with I/O ratios generally <1. Fine PM was less affected by indoor sources, exerting a major impact on the PM1-2.5 fraction. Over half of the indoor fine particles were estimated to originate from outdoors. To a first approximation, the intervention proposed to reduce indoor particle levels did not seem to significantly influence the indoor fine PM concentrations. Conversely, the frequent opening of doors and windows appeared to significantly contribute to the reduction of the average indoor CO2 levels.
The impact of air pollution on people’s health and daily activities in China has recently aroused much attention. By using stochastic differential equations, variation in a 6 year long time series of ...air quality index (AQI) data, gathered from air quality monitoring sites in Xi’an from 15 November 2010 to 14 November 2016 was studied. Every year the extent of air pollution shifts from being serious to not so serious due to alterations in heat production systems. The distribution of such changes can be predicted by a Bayesian approach and the Gibbs sampler algorithm. The intervals between changes in a sequence indicate when the air pollution becomes increasingly serious. Also, the inflow rate of pollutants during the main pollution periods each year has an increasing trend. This study used a stochastic SEIS model associated with the AQI to explore the impact of air pollution on respiratory infections. Good fits to both the AQI data and the numbers of influenza-like illness cases were obtained by stochastic numerical simulation of the model. Based on the model’s dynamics, the AQI time series and the daily number of respiratory infection cases under various government intervention measures and human protection strategies were forecasted. The AQI data in the last 15 months verified that government interventions on vehicles are effective in controlling air pollution, thus providing numerical support for policy formulation to address the haze crisis.
Objective
To explore the utility of the scoring system for screening and early warning of cervical cancer based on big data analysis.
Methods
A total of 420 women undergoing physical examination in ...Shenyang from January 2021 to January 2022 were screened by convenient sampling as the study subjects. All females accepted the human papilloma virus (HPV) tests and thin-prep cytology test (TCT), a Rating Questionnaire for Screening and Early Warning of Cervical Cancer was developed, and a warning threshold was derived according to the scores of the questionnaire and the goodness of fit for the results of HPV+TCT tests. The patients were graded according to the threshold, and corresponding intervention strategies for patients of different grades were developed.
Results
Among the 420 people undergoing physical examination, 92 (21.90%) obtained scores ≥8 points, and 328 (78.10%) obtained scores < 8 points; in diagnosing cervical cancer, the Rating Questionnaire for Screening and Early Warning of Cervical Cancer had an AUC value of 0.848, specificity of 97.22%, and sensitivity of 86.46%; after scientific intervention, HPV test results showed a significant decrease in both high-risk positive cases and low-risk positive cases (
p
< 0.05), and TCT results showed that there was a significant difference in the number of patients with CIN I before and after intervention (
p
< 0.05).
Conclusion
The scoring system for screening and early warning of cervical cancer based on big data analysis presents certain clinical value in the clinical screening of cervical cancer, which can further improve the screening coverage, is of great significance for the diagnosis and treatment of disease, and helps physician implement hierarchical diagnosis and treatment quickly and precisely.
The outbreak of COVID-19 stimulated a new round of discussion on how to deal with respiratory infectious diseases. Influenza viruses have led to several pandemics worldwide. The spatiotemporal ...characteristics of influenza transmission in modern cities, especially megacities, are not well-known, which increases the difficulty of influenza prevention and control for populous urban areas. For a long time, influenza prevention and control measures have focused on vaccination of the elderly and children, and school closure. Since the outbreak of COVID-19, the public's awareness of measures such as vaccinations, mask-wearing, and home-quarantine has generally increased in some regions of the world. To control the influenza epidemic and reduce the proportion of infected people with high mortality, the combination of these three measures needs quantitative evaluation based on the spatiotemporal transmission characteristics of influenza in megacities. Given that the agent-based model with both demographic attributes and fine-grained mobility is a key planning tool in deploying intervention strategies, this study proposes a spatially explicit agent-based influenza model for assessing and recommending the combinations of influenza control measures. This study considers Shenzhen city, China as the research area. First, a spatially explicit agent-based influenza transmission model was developed by integrating large-scale individual trajectory data and human response behavior. Then, the model was evaluated across multiple intra-urban spatial scales based on confirmed influenza cases. Finally, the model was used to evaluate the combined effects of the three interventions (V: vaccinations, M: mask-wearing, and Q: home-quarantining) under different compliance rates, and their optimal combinations for given control objectives were recommended. This study reveals that adults were a high-risk population with a low reporting rate, and children formed the lowest infected proportion and had the highest reporting rate in Shenzhen. In addition, this study systematically recommended different combinations of vaccinations, mask-wearing, and home-quarantine with different compliance rates for different control objectives to deal with the influenza epidemic. For example, the “V45%-M60%-Q20%” strategy can maintain the infection percentage below 5%, while the “V20%-M60%-Q20%” strategy can maintain the infection percentage below 15%. The model and policy recommendations from this study provide a tool and intervention reference for influenza epidemic management in the post-COVID-19 era.
Household water demand has increased dramatically in Kuwait over the last few decades, due to rapid population growth and changing lifestyles. Avoiding a water deficit through a supply‐side approach ...has been the default strategy in Kuwait, yet this approach is unsustainable, associated with declining groundwater levels, and reliance on desalination that results in major carbon emission and environmental impact and that takes a large and growing share of oil revenues. In this study, we forecast household water demand in Kuwait to 2050 under a Business‐As‐Usual (BAU) scenario and evaluate the economic and environmental impacts. A spatial microsimulation, constrained by the national population projection of the Kuwait Institute of Scientific Research (KISR), was developed to overcome data limitations in forecasting household demand. Results show a 45% increase in water demand by 2050, to 664.1 million cubic metres (MCM), relative to the 2019 base year. Annual production costs increase from 1.39 billion USD in 2019 to 1.99 billion USD by 2050, whilst carbon emissions increase from 10.85 to 15.54 million tonnes/year. These results should alert policymakers to the potential impacts of the growing water demand and provide further support for water conservation action to reduce demand.
A Business‐As‐Usual (BAU) water demand forecast in the household sector of Kuwait was built to quantify water demand until 2050 and evaluate the associated economic and environmental impacts. The BAU forecast model has shown that demand will increase by 45% to reach 664.1 million cubic meters (MCM). Annual water production will cost 1.99 billion USD, whilst carbon emissions will reach 15.54 tonnes by 2050. This study targets policymakers to show the potential impacts of the growing water demand and provide further support for water conservation action to reduce demand.
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