Search Results (129)

Educational achievement plays a significant role in the labour market, benefiting individuals and society. Graduating from high school is a key step towards better employment opportunities and a prerequisite for higher education attainment. In 2023, only 22.5% of the Romanian population graduated tertiary education, while 16.6% left education or training early. The Romanian public high school network comprises 1558 units, mostly located in urban areas. The high school enrolment rate is 83.5% in urban areas, and it drops to less than 60% in rural areas, with the country registering the highest out-of-school rate in the EU for the 15-year-old population. Spatial accessibility may influence enrolment in high schools, particularly for students living in rural or remote areas, who often face financial challenges fuelled by long distances and limited transportation options. Hence, travel distance may represent a potential barrier to completing the educational process or may determine inequalities in educational opportunities and outcomes. This paper aims to assess the spatial accessibility of the public high school network in Romania by using distance data provided by the Open Street Map API (Application Programming Interface). We examine variations in spatial accessibility based on the distribution of high school units and road network characteristics considering three variables: travel distance to the nearest high school, the average distance to three different categories of high schools, and the number of high schools located within a 20 km buffer zone. The results highlight a significant urban–rural divide in the availability of public high school facilities, with 84.1% (n = 1311) located in urban areas while 49.1% of the high school-aged population lives in rural areas. Many rural communities lack adequate educational facilities, often having limited options for high school education. The findings also show that 32% of the high school-aged population has to travel more than 10 km to the nearest high school, and 7% has no high school options within a 20 km buffer zone. This study provides insights into the educational landscape in Romania, pointing out areas with limited access to high schools, which contributes to further inequalities in educational attainment. The findings may serve as a basis for developing policies and practices to bridge the urban–rural divide in educational opportunities and foster a more equitable and inclusive education system. Full article

As climate change intensifies, urban populations face growing threats from frequent and severe heatwaves, underscoring the urgent need for advanced risk assessment frameworks to inform adaptation strategies. This systematic review synthesizes methodological innovations in urban heatwave risk assessment (2007–2024), analyzing 259 studies through bibliometric analysis (CiteSpace 6.4.R1) and multi-criteria evaluation. We propose the hazard–exposure–vulnerability–adaptability (HEVA) framework, an extension of Crichton’s risk triangle that integrates dynamic adaptability metrics and supports high-resolution spatial analysis for urban heatwave risk assessment. Our systematic review reveals three key methodological gaps: (1) Inconsistent indicator selection across studies; (2) limited analysis of microclimatic variations; (3) sparse integration of IoT- or satellite-based monitoring. The study offers practical solutions for enhancing assessment accuracy, including refined weighting methodologies and high-resolution spatial analysis techniques. We conclude by proposing a research agenda that prioritizes interdisciplinary approaches—bridging urban planning, climate science, and public health—while advocating for policy tools that address spatial inequities in heat risk exposure. These insights advance the development of more precise, actionable assessment systems to support climate-resilient urban development. Full article

Starting from some systems of vector equilibrium problems, we obtain the existence of the solution for a class of weighted equilibrium problems, under different types of generalized pseudo-monotonicity assumptions. We present both new and previous results, making a connection between them and giving a few examples. Using the main theorem, we derive the solution existence for the initial systems and discuss a corresponding set-valued problem. Finally, we consider the case of a real normed space. We extend some previously obtained results from the literature about weighted variational inequalities, and we also give proofs for some results we previously announced. We give some relevant examples for our notions. Full article

Type 2 diabetes (T2D) is a rapidly growing global health concern, projected to affect 1.3 billion people by 2050, necessitating a multidisciplinary approach. This review examines the epidemiological disparities in T2D, focusing on modifiable and nonmodifiable risk factors, socioeconomic determinants, and healthcare inequities. While genetic predisposition, age, and ethnicity contribute to T2D risk, socioeconomic status (SES) significantly mediates modifiable factors such as diet, physical activity, and access to healthcare. Lower SES is associated with poorer lifestyle choices, limited access to resources, and increased exposure to risk factors, exacerbating T2D prevalence among vulnerable populations. Geographic variations in T2D prevalence are evident, with racial and ethnic minorities and lower-income individuals being disproportionately affected in regions like the United States and Europe. The economic burden of T2D is substantial, with global healthcare expenditures reaching USD 966 billion in 2021 and projected to rise significantly, albeit with variations across different countries and health systems. Despite advancements in treatment, inequities in healthcare access persist, particularly in low- and middle-income countries, hindering optimal glycemic control and consequently contributing to preventable complications and poor health outcomes. This review highlights the critical need for targeted interventions and policy reforms to address the intersection of demographic, economic, and healthcare-related variables influencing T2D disparities. By bridging gaps in prevention, management, and treatment and accounting for the effect of SES on both modifiable and nonmodifiable risk factors, the global disease burden of T2D could be reduced and health equity could be improved. Full article

This paper presents a zeroing neural networks (ZNN)-based gait optimization strategy for humanoid robots. First, the algorithm converts the angular momentum linear inverted pendulum (ALIP)-based gait planning problem into a time-varying quadratic programming (TVQP) problem by adding adaptive adjustment factors and physical limits as inequality constraints to avoid system oscillations or instability caused by large fluctuations in the robot’s angular momentum. Secondly, This paper proposes a real-time and efficient solution for TVQP based on an integral strong predefined time activation function zeroing neural networks (ISPTAF-ZNN). Unlike existing ZNN approaches, the proposed ISPTAF-ZNN is enhanced to achieve convergence within a strong predefined-time while exhibiting noise tolerance. This ensures the desired rapid convergence and resilience for applications requiring strict time efficiency. The theoretical analysis is conducted using Lyapunov stability theory. Finally, the comparative experiments verify the convergence, robustness, and real-time performance of the ISPTAF-ZNN in comparison with existing ZNN approaches. Moreover, comparative gait planning experiments are conducted on the self-built humanoid robot X02. The results demonstrate that, compared to the absence of an optimization strategy, the proposed algorithm can effectively prevent overshoot and approximate energy-efficient responses caused by large variations in angular momentum. Full article

The concept of energy burden (EB) continues to gain prominence in energy and associated policy research as energy prices rise and electricity and heating options diversify. This research offers a deeper understanding of EB dynamics and how EB can be addressed more effectively by discerning the interplay between regional environmental, social, and economic factors. Using decision trees (DTs), a powerful machine learning technique, we explore the multifaceted dynamics that shape EB across the United States (U.S.) by examining how factors like housing quality, demographic variations, access to energy sources, and regional economic conditions interact, creating distinct EB profiles across communities. Following a comprehensive review of existing literature and DT analysis, we map the results to identify the most significant factors influencing EB. We find that no single variable has a determinant effect on EB levels. While there is no uniform regional pattern, regions with higher population density exhibit a stronger correlation between EB and socioeconomic and other demographic factors such as educational attainment levels and racial segregation. Our findings underscore the significance of regional ecologies in shaping EB, revealing how localized environmental and economic contexts amplify or mitigate systemic inequities. Specifically, our analysis reveals significant regional disparities, highlighting the need for localized policies and interventions. We find that a one-size-fits-all approach is insufficient and that targeted, place-based strategies are necessary to address the specific needs of different communities. Policy interventions should prioritize energy democracy, address systemic inequities, and ensure universal energy access through participatory planning, financial assistance, and targeted initiatives such as housing rehabilitation, energy efficiency improvements, and incentives for underrepresented communities. Full article

Background: The regionalisation of perinatal care emphasises the importance of transferring high-risk pregnancies “in utero” to minimise risks; yet, neonatal inter-facility transport remains necessary. Neonatal Emergency Transport Services (NETSs) play a crucial role in reducing transportation risks, especially for very preterm infants. Italy’s healthcare system, which is decentralised in nature, leads to variations in NETS organisation and resources across the country, resulting in disparities in access and quality of care. Methods: A questionnaire regarding neonatal transfer practices and NETS activity was sent to the 55 NETSs operating in twenty Italian regions. Demographic data were obtained from the Italian National Statistical Institute (ISTAT). Results: Survey Overview. A 2022 national survey by the Italian Society of Neonatology aimed to assess the status of NETS in Italy, achieving a 100% response rate from the 55 NETS. The 2022 data highlighted the transport of 6494 neonatal, of which 92% were primary transports (transferred to higher-level care) and 553 were back-transports (returning stabilised neonates to lower-level care). Subgroup analysis identified 544 transports of neonates born at 30–34 weeks of gestation and 305 transports of neonates born at under 30 weeks of gestation. This was shown to have regional variability. NETS coverage: 18 regions have full NETS coverage. Sicily offers partial coverage. Sardinia, despite an approved plan, lacks an operational NETS. Operational models: all NETS provide a 24/7 service; 50 NETSs rely on an on-call basis using NICU staff for transport. Only five NETS have dedicated teams exclusively for neonatal transport. This decentralisation results in heterogeneity in service availability, access, and quality. Conclusions: This study highlights that although differences still exist, the NETS in Italy is adequately structured and effective. The presence of NETS operating with limited transport volumes puts a strain on maintaining skilled staff and cost-effective operations. Regional disparities: inequities in NETS access (e.g., in Sicily and Sardinia regions) underline the need to improve regional collaboration. While Italy has made progress in organising NETS, regional discrepancies persist in access and service quality, reflecting the decentralised nature of its healthcare system. Full article

Background: Ableism obstructs employment equity for disabled individuals. However, research lacks a comprehensive understanding of how ableism multidimensionally manifests across job types, disability types, stages of employment, and intersecting identities. Objectives: This scoping review examines how ableism affects disabled workers and jobseekers, as well as its impacts on employment outcomes, variations across disabilities and identities, and the best practices for addressing these. Eligibility Criteria: The included articles were 109 peer-reviewed empirical studies conducted in the US, Canada, Australia, New Zealand, the UK, Ireland, Denmark, Sweden, Iceland, Norway, and Finland between 2018 and 2023. Sources of Evidence: Using terms related to disability, ableism, and employment, the databases searched included Sociology Collection, CINAHL, PsycInfo, Web of Science, SCOPUS, Education Source, Academic Search Complete, and ERIC. Charting Methods: Data were extracted in tabular form and analyzed through thematic narrative synthesis to identify study characteristics, ableist barriers within employment, intersectional factors, and best practices. Results: Ableism negatively impacts employment outcomes through barriers within the work environment, challenges in disclosing disabilities, insufficient accommodations, and workplace discrimination. Intersectional factors intensify inequities, particularly for BIPOC, women, and those with invisible disabilities. Conclusions: Systemic, intersectional strategies are needed to address ableism, improve policies, and foster inclusive workplace practices. Full article

In this work, we are devoted to discussing a system of fractional stochastic differential variational inequalities with Lévy jumps (SFSDVI with Lévy jumps), that comprises both parts, that is, a system of stochastic variational inequalities (SSVI) and a system of fractional stochastic differential equations(SFSDE) with Lévy jumps. Here it is noteworthy that the SFSDVI with Lévy jumps consists of both sections that possess a mutual symmetry structure. Invoking Picard’s successive iteration process and projection technique, we obtain the existence of only a solution to the SFSDVI with Lévy jumps via some appropriate restrictions. In addition, the major outcomes are invoked to deduce that there is only a solution to the spatial-price equilibria system in stochastic circumstances. The main contributions of the article are listed as follows: (a) putting forward the SFSDVI with Lévy jumps that could be applied for handling different real matters arising from varied domains; (b) deriving the unique existence of solutions to the SFSDVI with Lévy jumps under a few mild assumptions; (c) providing an applicable instance for spatial-price equilibria system in stochastic circumstances affected with Lévy jumps and memory. Full article

Background: The COVID-19 pandemic disrupted routine child immunization efforts, threatening to reverse progress in controlling vaccine-preventable diseases. Materials and Methods: We analyzed the impact of COVID-19 on DTP3 vaccination in Europe by comparing trends before and after the pandemic using time series data from 2000 to 2023. Employing joinpoint regression, chi-square tests, and segmented regression analysis, we assessed DTP3 vaccination trends and coverage changes. Results: The findings revealed significant regional disparities across Europe. Statistical models indicated reductions in DTP3 coverage in countries such as Ireland, Sweden, and Switzerland, whereas Ukraine and San Marino showed improvements. Conclusions: There are variations in the effect of COVID-19 on DTP3 coverage rates, indicating the need for targeted public health strategies to address vaccine hesitancy, logistical barriers, and systemic inequities. Full article

Optimizing the performance of motion control systems with variations in nonlinear parameters is not an easy task. To accomplish this task, it is important to design the controller using the linear system approach. In this study, a linear parameter varying (LPV) control method is proposed in which nonlinearities are treated as parameter variations for planar motors. The proposed control method consists of the force and torque modulation with the commutation scheme and the nonlinear current controller with H_∞ state feedback control in the form of LPV synthesis to improve the position-tracking performance. An interpolated gain-scheduling controller based on LPV synthesis is determined by applying H_∞ control to a linear matrix inequality technique. An interpolated gain-scheduling controller can attenuate disturbance without disturbance estimation. The effectiveness of the proposed control method is evaluated using simulation results and compared with the conventional proportional–integral–derivative control to verify both improved position-tracking performance and disturbance attenuation. Full article

In the context of transportation development, the simultaneous emergence of automated vehicles (AVs) and human-driven vehicles (HDVs) can lead to varied traffic system performance. For the purpose of improving traffic systems, this paper proposes a traffic restriction scheme only for HDVs. We develop a variational inequality (VI) model to describe travel mode and route choices under this restriction scheme and design an algorithm to solve the model. The proposed model and algorithm are applied to a Sioux Falls network example to evaluate the effects of the traffic restriction scheme. Our findings indicate that the scheme improves overall social welfare, with a higher proportion of restricted travelers leading to greater social welfare as well as increased travel demand due to changes in capacity. However, some lower exogenous monetary factors lead to negative social welfare, as the presence of AVs may exacerbate road congestion. Additionally, advancements in technology are needed to adjust the weightings of travel time and congestion level estimates to further enhance social welfare. These results offer valuable insights for traffic demand management in traffic systems with a mix of AVs and HDVs. Full article

Modern power systems present opportunities and challenges when integrating distributed generation and electric vehicle charging stations into unbalanced distribution networks. The performance and efficiency of both Distributed Generation (DG) and Electric Vehicle (EV) infrastructure are significantly affected by global temperature variation characteristics, which are taken into consideration in this study as it investigates the effects of these integrations. This scenario is further complicated by the unbalanced structure of distribution networks, which introduces inequalities that can enhance complexity and adverse effects. This paper analyzes the manner in which temperature changes influence the network operational voltage profile, power quality, energy losses, greenhouse harmful emissions, cost factor, and active and reactive power losses using analytical and heuristic techniques in the IEEE 69 bus network in both three-phase balance and modified unbalanced load conditions. In order to maximize adaptability and efficiency while minimizing the adverse impacts on the unbalanced distribution system, the findings demonstrate significant variables to take into account while locating the optimal location and size of DG and EV charging stations. To figure out the objective, three-phase distribution load flow is utilized by the particle swarm optimization technique. Greenhouse gas emissions dropped by 61.4%, 64.5%, and 60.98% in each of the three temperature case circumstances, while in the modified unbalanced condition, they dropped by 57.55%, 60.39%, and 62.79%. In balanced conditions, energy loss costs are reduced by 95.96%, 96.01%, and 96.05%, but in unbalanced conditions, they are reduced by 91.79%, 92.06%, and 92.46%. The outcomes provide valuable facts that electricity companies, decision-makers, along with other energy sector stakeholders may utilize to formulate strategies that adapt to the fluctuating patterns of electricity distribution during fluctuations in global temperature under balanced and unbalanced conditions of network. Full article

The concept of segregation analyses the unequal distribution of social groups between neighbourhoods. It rests on two assumptions: that of homogeneous neighbourhoods and of a market liberal housing system. Both assumptions are applicable the context of American cities, but they display severe limitations when applied to the European context. Vienna’s housing market is particularly highly segmented, not only throughout the city as a whole but also within neighbourhoods. In the densely built-up area, residential buildings of different segments with different underlying rent regulations and entry barriers can be found side by side. Therefore, buildings are expected to show varying tenant and owner structures, which undermines the idea of a homogeneous neighbourhood. Against this background, we analyse at the micro scale small neighbourhoods defined by 100 m grid cells in a case study of two inner-city Viennese districts (districts 6 and 7) characterised by a particularly vivid housing-transformation and commodification dynamic. Using a novel and fine-grained dataset combining building information with the socio-economic data of households, we investigate the patterns and dynamics of income inequality and income segregation, as well as the relationship between housing market segments and socio-economic patterns. As data comprise two cross-sections for the years 2011 and 2020/21, changes in the neighbourhoods during the house-price boom period are also considered. This leads us to ask the question: How do housing market segmentation and its related changes affect income inequality and segregation at the micro scale? Our analysis delivers two main results: Firstly, we show the existence of marked social variation and related dynamics at the micro scale, even within a small urban area. Secondly, we show that the spatial distribution of housing market segments has a strong impact on income inequality in the neighbourhood. Full article

Descriptor systems are more complex than normal systems, which are modeled by differential equations. This paper derives stability and stabilization criteria for uncertain fractional descriptor systems with neutral-type delay. Through the Lyapunov–Krasovskii functional approach, conditions subject to time-varying delay and parametric uncertainty are formulated as linear matrix inequalities. Based on the established criteria, static state- and output-feedback control laws are designed to ensure regularity and impulse-free properties, together with robust stability of the closed-loop system under permissible uncertainties. Numerical examples illustrate the effectiveness of the control methods and show that the results depend on the range of variation in the delays and on the fractional order, leading to stability analysis results that are less conservative than those reported in the literature. Full article