Search Results (443)

Background: Rock–blast design is a canonical inverse problem that joins elastodynamic partial differential equations (PDEs), fracture mechanics, and stochastic heterogeneity. Objective: Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, a systematic review of mathematical methods for geomechanically informed blast modelling and optimisation is provided. Methods: A Scopus–Web of Science search (2000–2025) retrieved 2415 records; semantic filtering and expert screening reduced the corpus to 97 studies. Topic modelling with Bidirectional Encoder Representations from Transformers Topic (BERTOPIC) and bibliometrics organised them into (i) finite-element and finite–discrete element simulations, including arbitrary Lagrangian–Eulerian (ALE) formulations; (ii) geomechanics-enhanced empirical laws; and (iii) machine-learning surrogates and multi-objective optimisers. Results: High-fidelity simulations delimit blast-induced damage with ≤0.2 m mean absolute error; extensions of the Kuznetsov–Ram equation cut median-size mean absolute percentage error (MAPE) from 27% to 15%; Gaussian-process and ensemble learners reach a coefficient of determination ($R^2>0.95$) while providing closed-form uncertainty; Pareto optimisers lower peak particle velocity (PPV) by up to 48% without productivity loss. Synthesis: Four themes emerge—surrogate-assisted PDE-constrained optimisation, probabilistic domain adaptation, Bayesian model fusion for digital-twin updating, and entropy-based energy metrics. Conclusions: Persisting challenges in scalable uncertainty quantification, coupled discrete–continuous fracture solvers, and rigorous fusion of physics-informed and data-driven models position blast design as a fertile test bed for advances in applied mathematics, numerical analysis, and machine-learning theory. Full article

The rubber industry is facing major socio-economic and environmental constraints. Rubber-based agroforestry systems represent a more sustainable solution through the diversification of income and the provision of greater ecosystem services than monoculture plantations. Participative approaches are known for their ability to co-construct solutions with stakeholders and to promote a positive impact on smallholders. This study therefore implemented a participatory research process with stakeholders in the natural rubber sector for the purpose of improving inclusion, relevance and impact. Facilitation training sessions were first organised with academic actors to prepare participatory workshops. A working group of stakeholder representatives was set up and participated in these workshops to share a common representation of the value chain and to identify problems and solutions for the sector in Indonesia. By fostering collective intelligence and systems thinking, the process is aimed at enabling the development of adaptive technical solutions and building capacity across the sector for future government replanting programmes. The resulting adaptive technical packages were then detailed and objectified by the academic consortium and are part of a participatory plant breeding approach adapted to the natural rubber industry. On-station and on-farm experimental plans have been set up to facilitate the drafting of projects for setting up field trials based on these outcomes. Research played a dual role as both knowledge provider and facilitator, guiding a co-learning process rooted in social inclusion, equity and ecological resilience. The initiative highlighted the potential of rubber cultivation to contribute to climate change mitigation and food sovereignty, provided that it can adapt through sustainable practices like agroforestry. Continued political and financial support is essential to sustain and scale these innovations. Full article

Shift work can have an adverse impact on sleep and wellbeing, as well as negative consequences for workplace safety and productivity. SleepShifters is a co-developed sleep management programme that aims to equip shift workers and employers with the skills needed to manage sleep from the onset of employment, thus preventing sleep problems and their associated consequences from arising. This paper describes the co-development process and resulting programme protocol of SleepShifters, designed in line with the Medical Research Council’s framework for the development and evaluation of complex interventions. Programme components were co-produced in partnership with stakeholders from four organisations across the United Kingdom, following an iterative, four-stage process based on focus groups and interviews. As well as a handbook containing guidance on shift scheduling, workplace lighting, and controlled rest periods, SleepShifters consists of five key components: (1) an annual sleep awareness event; (2) a digital sleep training induction module for new starters; (3) a monthly-themed sleep awareness campaign; (4) a website, hosting a digital Cognitive Behavioural Therapy for insomnia platform and supportive video case studies from shift-working peers; (5) a sleep scheduling app for employees. Future work will implement and assess the effectiveness of delivering SleepShifters in organisational settings. Full article

Modern software solutions have a multiplicative effect on enhancing quality of life across various urban sectors, including the environment, education, public health, security, transportation, time efficiency, employment, and other key aspects of city living. This article addresses a specific issue concerning the organisation of leisure activities for both local residents and tourists, using the Chechen Republic as a case study. In response, the study aimed to develop a digital solution to address this challenge, with potential for integration into the Republic’s unified digital ecosystem. By employing system analysis methods, the authors identified the key objects and stakeholders involved in the problem domain. They also defined the software product’s functionality and classified user categories. Using Unified Modelling Language methods, a use case diagram was developed to illustrate the conceptual operation of the system. Furthermore, object-oriented design methods were applied to create a user interface prototype for the software product. As a result, a digital service was developed that enables users to create personalised leisure routes, taking into account individual goals, time constraints, traffic conditions, and the real-time status of urban infrastructure. The resulting software solution is both customisable and scalable. The article also presents selected examples of project development. Full article

Job advertisements play a key role in human resource management as they are the first contact between employers and potential employees. A well-written job advertisement communicates not only the requirements and expectations of the position but also the culture, values, and goals of the organisation. Transparent and attractive advertisements increase the number of applicants and help to select the right candidates, leading to more efficient recruitment and selection processes in the long run. From a human resource management perspective, effective job advertising can give organisations a competitive advantage. Continuous changes in the labour market and technological developments require new competencies. Digitalisation, automation, and data-driven decision-making have brought IT, analytical, and communication skills to the fore. There is a growing emphasis on soft skills such as problem solving, flexibility, and teamwork, which are essential in a fast-changing work environment. Job advertisements should reflect these expectations so that candidates are aware of the competencies and skills required for the position. The aim of the study is to carry out a cross-country comparative analysis for a few pre-selected jobs based on data extracted from the CEDEFOP database as it is assumed that there are differences between countries in the European Union in terms of the expectations of workers for the same jobs. Full article

In light of constrained resources and the rise of digitalisation in higher education, management control systems (MCSs) have emerged as essential tools for university management because of their integrity, flexibility, and effectiveness. This paper aims to elucidate the current challenges in the implementation and functioning of MCSs in higher education. To this end, a systematic literature review was undertaken in the Scopus and Web of Science databases, following the PRISMA guidelines. The review yielded 15 relevant sources published between 2020 and June 2025. Induction, deduction, content analysis, and K-means clustering were employed to analyse them. Forty-eight challenges to MCSs in higher education were identified and systematised into four groups (Growth Threats, Limitations, Malpractices, and Stakeholder Issues), covering twelve subgroups. These subgroups were ranked according to their frequency of mention. The top-ranked subgroups were HR problems (first), organisational constraints and management engagement (second), and technological integration and lack of technology training (third). All challenges were classified into clusters based on the countries analysed in the reviewed sources. This review primarily contributes to the existing knowledge by identifying and categorising the challenges to MCSs in higher education. Practically, it lays the groundwork for improving these MCSs, thus contributing to enhanced university management. Full article

Climate change is one of the most important environmental problems of the modern world. Without an effective solution to this problem, it is not possible to implement sustainable development. For this reason, in the European development strategies, including the European Green Deal (EGD), the reduction in greenhouse gas (GHG) emissions is one of the priorities. This also applies to sectoral strategies, including those related to agriculture. In this context, the monitoring of changes in GHG emissions becomes particularly important, and its key condition is an applicative estimation method, adapted to the available data and levels of assessment (globally, country, sector, economic unit). GHG emission calculations at the level of the agricultural sector are officially estimated by the state and non-governmental organisations. However, calculations at the level of the agricultural unit-farm remain a challenge due to the lack of detailed data or its incomplete scope to estimate GHG emissions. The other issue is the necessity of a representative data nature, taking into consideration the different profiles of various farms. The research focused on presenting a methodological approach to utilising FADN (Farm Accountancy Data Network) data for estimating GHG emissions at the farm level. The Intergovernmental Panel on Climate Change (IPCC) methodology was adopted to use available farm-level data. Some assumptions were needed to achieve this goal. The article presents the subsequent stages of GHG calculation using the FADN data. The results reveal significant differences in GHG emissions among farm types. The presented results indicated the primary sources of emissions from agriculture, including energy (e.g., fuel and electricity consumption), thus outlining the scope of action that should be taken to reduce emissions effectively. The study confirms that the method used helps estimate emissions at the farm level. Its application can lead to better targeting of climate policy in agriculture. Full article

Classical epidemic models treat vaccine uptake as an exogenous parameter, yet real-world coverage emerges from strategic choices made by individuals facing uncertain risks. During the last two decades, vaccination games, which combine epidemic dynamics with game theory, behavioural economics, and network science, have become a very important tool for analysing this problem. Here, we synthesise more than 80 theoretical, computational, and empirical studies to clarify how population structure, psychological perception, pathogen complexity, and policy incentives interact to determine vaccination equilibria and epidemic outcomes. Papers are organised along five methodological axes: (i) population topology (well-mixed, static and evolving networks, multilayer systems); (ii) decision heuristics (risk assessment, imitation, prospect theory, memory); (iii) additional processes (information diffusion, non-pharmacological interventions, treatment, quarantine); (iv) policy levers (subsidies, penalties, mandates, communication); and (v) pathogen complexity (multi-strain, zoonotic reservoirs). Common findings across these studies are that voluntary vaccination is almost always sub-optimal; feedback between incidence and behaviour can generate oscillatory outbreaks; local network correlations amplify free-riding but enable cost-effective targeted mandates; psychological distortions such as probability weighting and omission bias materially shift equilibria; and mixed interventions (e.g., quarantine + vaccination) create dual dilemmas that may offset one another. Moreover, empirical work surveys, laboratory games, and field data confirm peer influence and prosocial motives, yet comprehensive model validation remains rare. Bridging the gap between stylised theory and operational policy will require data-driven calibration, scalable multilayer solvers, and explicit modelling of economic and psychological heterogeneity. This review offers a structured roadmap for future research on adaptive vaccination strategies in an increasingly connected and information-rich world. Full article

One of the important parameters of the sheet metal forming process is the coefficient of friction (CoF). Therefore, monitoring the friction coefficient value is essential to ensure product quality, increase productivity, reduce environmental impact, and avoid product defects. Conventional CoF monitoring techniques pose a number of problems, including the difficulty in identifying the features of force signals that are sensitive to the variation in the coefficient of friction. To overcome these difficulties, this paper proposes a new approach to apply unsupervised artificial intelligence techniques with unbalanced data to classify the CoF of DP780 (HCT780X acc. to EN 10346:2015 standard) steel sheets in strip-drawing tests. During sheet metal forming (SMF), the CoF changes owing to the evolution of the contact conditions at the tool–sheet metal interface. The surface topography, the contact loads, and the material behaviour affect the phenomena in the contact zone. Therefore, classification is required to identify possible disturbances in the friction process causing the change in the CoF, based on the analysis of the friction process parameters and the change in the sheet metal’s surface roughness. The Kohonen self-organising map (SOM) was created based on the surface topography parameters collected and used for CoF classification. The CoF determinations were performed in the strip-drawing test under different lubrication conditions, contact pressures, and sliding speeds. The results showed that it is possible to classify the CoF using an SOM for unbalanced data, using only the surface roughness parameter Sq and selected friction test parameters, with a classification accuracy of up to 98%. Full article

The social and civic participation of older adults has proven to be an asset that positively influences the dynamics of social inclusion that affect them, and expert opinion from international organisations calls for its inclusion in the development of public policies in response to the increasing longevity worldwide. However, the characteristics of this participation have not been sufficiently analysed. The main objective of this study was to test the explanatory capacity of an operational proposal relating to the participation of older people based on a multidimensional participation structure. Four dimensions were established: two relating to social participation (associations and volunteering and public sociability) and two linked to citizen participation (political and electoral participation, as well as active citizenship and civic engagement). Based on the proposal, a technical expert panel (TEP) was asked to identify the main participation challenges faced by older people across the four dimensions identified. Consensus was sought using prioritisation matrices. The results showed, among other issues, the key role of the dimensions of citizen participation in identifying participation challenges that have an impact on social inclusion. The political and electoral participation dimension had a specific weight regarding the challenges linked to current problems and characteristics. On the other hand, the active citizenship and civic engagement dimension was oriented towards the challenges linked to desirable conditions and recommended initiatives in the future to improve the impact of older people’s participation. The expert panel’s statements coincide with the recommendations of international organisations on the need to involve older persons in policymaking from a perspective of comprehensive and person-centred care. This provides a concrete response to people’s demands and fosters bottom-up planning policies that contribute to social cohesion. Full article

In this research, we have compiled and analysed the organisations and studies that jointly address the issue of land administration, fundamentally in the cartographic aspects related to the cadastre and land registry, in the international environment, and at the Ibero-American level. Through qualitative social research, interviews were conducted with internationally recognised experts on issues of general cartography, cartography and legal security, and related to cadastral valuation, obtaining conclusions that allow a general diagnosis of the situation of the Land Administration System in Ibero-America. In this environment, problems such as the heterogeneity of systems, overlapping of competencies, instability, lack of sustainability, need for standards, lack of transparency, etc., should be highlighted, among others. Finally, based on the compilation of existing data from the Cadastre Data survey conducted in 2011 by the Permanent Committee of Cadastre in Ibero-America, and with information from its members and member organisations of the Pan-American Association of Professional Surveyors, the geoportal Diagnosis of the Situation of the Land Administration System in Ibero-America has been created. This geoportal allows the initial identification of the different organisations and general regional data. Full article

This study examines the decision-making processes that were used in the development of the National Disability Insurance Scheme (NDIS). It draws on research that highlights that decision-making can be improved if organisations follow specific decision-making processes. This study sought to examine whether formal decision-making rules and processes were used in the development of the NDIS. Semi-structured interviews were conducted with 58 senior public servants between 2016 and 2021 in the Commonwealth government departments that had policy oversight and responsibility for both the design and implementation of the NDIS. The data showed that there were examples of data-driven decisions and risk analysis used, but also considerable gaps in decision-making processes. These gaps potentially resulted in poorer decision-making quality, which may have negatively impacted the design of the NDIS and could potentially explain some of the current problems with the scheme. The paper concludes with recommendations for future research to improve decision-making processes within public administration. Full article

Healthcare is a dynamic and ever-changing phenomenon and is subject to multiple challenges, particularly concerning sustainability and cost issues. The literature identifies bed space and problems related to the lack of hospital beds as being directly or indirectly related to both admission and discharge processes, with delays in in-patient discharges being identified as a variable of significance when it comes to a health system’s overall performance. In this respect, the aim of this research was to explore factors related to delayed discharges in an acute hospital setting in Malta, a small European member state, through the perspectives of health professionals. This study followed a qualitative approach. Semi-structured interviews (n = 8) and focus groups (n = 2) were conducted with a diverse group of experienced health professionals. Informed consent was obtained from all participants, and all data were treated with strict confidentiality throughout the study. The sample was limited to professionals working in adult, non-specialized healthcare settings. Manual thematic analysis was carried out. Codes were grouped to derive seven main themes, which were identified after carrying out the thematic analysis process on the transcripts of the interviews/focus groups. The derived themes are the following: (a) a faulty system, which is open to abuse and inefficiency, (b) procedural delays directly impacting delayed discharges, (c) long-term care/social cases as a major cause of delayed discharges, (d) the impact of external factors on delayed discharges, (e) stakeholder suggestions to management to counteract delayed discharges, (f) the impact of COVID-19 on delayed discharges, and (g) inter-professional relationships. Factors related to delayed discharges and the effects of delayed discharges on the hospital emerged from the main findings, together with specific potential interventions to minimise delays in discharge. Health professional interactions and the effects of inter-professional relationship setbacks on delayed discharges were explored, and the impact of the COVID-19 pandemic on hospital dynamics and additional delays were also addressed. This information is intended to provide hospital administrators with data-driven internal organisational evidence to guide them through changes and to inform future decisions regarding hospital performance and efficiency from a discharge delay perspective. Full article

In the world of academia, there is a great mobility of talented university professors with a high level of movement among different entities. This could be a major problem, as universities must retain a minimum level of talent to support their various academic programmes. In this sense, finding out what factors could increase the loyalty of such staff can be of great interest to human resource (HR) departments and the overall administrative management of an organisation. Thus, this area, also known as People Analytics (PA), has become very powerful in human resource management to strategically address challenges in talent management. This paper examines talent commitment within the university environment, focusing on identifying key factors that influence the loyalty of professors and researchers. To achieve this, machine learning (ML) techniques are employed, as Principal Component Analysis (PCA) for dimensionality reduction and clustering techniques for individual segmentation have been employed in such tasks. This methodological approach allowed us to identify such critical factors, which we have termed Quantitative Emotional Salary (QES), enabling us to identify those factors beyond those merely related to compensation. The findings offer a novel data-driven perspective to enhance talent management strategies in academia, promoting long-term engagement and loyalty. Full article

In recent years, an increasing number of case reports have mentioned the presence of illicit nootropics, smart drugs or mind doping products on the market. To better understand the extent of the problem, a market surveillance study was organised by the General European Official Medicines Control Laboratory Network and associated member Australia to detect substandard, falsified or illegal medicines or dietary supplements containing unauthorised nootropic molecules of natural or synthetic origin. From January 2020 to September 2024, 159 different samples were documented, which yielded a comprehensive dataset of 166 molecular identification entries. Within this dataset, 34 distinct molecules were identified. Most samples were sold or presented as dietary supplements (49%) or medicines (32%). The vast majority (69%) were collected from the illegal market. Prescription drugs and non-authorised drugs only available on prescription in Russia were found in pharmacological quantities; some of the latter (noopept, phenylpiracetam and phenibut) were intercepted as large bulk quantities of raw material. Unauthorised novel foods, prescription or higher amounts of melatonin, and clinically uncharacterised research molecules were also reported. This study highlights the need for more active monitoring and screening of such products, as consumption of some of the reported samples could have detrimental health effects. Furthermore, as a large number of the samples were presented as dietary supplements, consumers may not be aware of the possible dangers and side-effects of these products. Full article