Electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialization, population growth, urbanization and of course the evolution of modern technologies in this 4th industrial revolution era. Such rapid increase in energy demand introduces a huge challenge in power system. Such has paved way for network operators to seek for alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a TNEP model that minimises the network reinforcements, operational costs and costs of renewable energy penetrations, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model has been tested in several IEEE test systems in multi-period scenarios. The paper also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variables’ decomposition techniques. Moreover, this paper tends to provide additional recommendation in terms of which particular year (within 20 years of planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. Such is achieved by running incremental periods simulations from base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time even for large power grid system.

Appropriate governance structures are extremely important for the fishery dependent communities to develop integrated territorial development strategies and adaptive capacity to change, including the climate one. This paper assesses to what extent fisheries co-management schemes (e.g Fisheries LAGs, being regional/local governance instruments in fishing communities) are strengthening sustainability. The latter includes improving energy efficiency, promoting renewable energy sources (RES), coping with climate crisis, minimizing environmental impacts, and promoting sustainable blue economy. For detecting policy aspects of aligning climate neutrality and sustainable blue economy, the research lens focuses on the Greek Fisheries Local Action Groups (FLAGs) given that these are mostly located in coastal/marine and insular territories with significant blue growth potential. To map and assess their capacity and efficiency in pursuing Green Deal objectives, a co-development process with FLAG managers was put in place. The results and findings of this process reveal the scarcity of sustainability and blue economy related strategies. Key conclusion is that transition to a post-carbon blue economy on a local level, requires the understanding of the evolutionary dynamics of fisheries co-management schemes. The latter, being multi-sectoral structures, may boost dialogue and cooperation to harmonize local development strategies and EU policies. Maritime Spatial Planning (MSP) as an evolutionary governance process itself, can be a driver for making FLAGs evolve, and strengthen commonization and blue justice and equity for fishers.

: Foodshed approaches allow the assessment of the theoretical food self-sufficiency capacity of a specific region based on biophysical conditions. Recent analyses show that the focus needs to be shifted from foodshed size portrayed as an isotropic circle to a commodity-group-specific spatial configuration of the foodshed that takes into account the socio-economic and biophysical conditions essential to the development of local food supply chains. We focus on a specific animal product (beef) and use an innovative modeling approach based on spatial analysis to detect the areas of the foodshed dedicated to beef feeding (forage, pasture, and grassland), considering the foodshed as a complex of complementary areas called an archipelago. We use available statistical data including a census to address the city-region of Avignon (France) covering a 100 km radius. Our results show that the factors driving the use of short supply chains for beef feeding areas are the foodshed archipelago’s number of patches, the connectivity between them, and the rugosity of the boundaries. In addition, our beef self-sufficiency assessment results differ depending on geographical context. For instance, being located within the perimeters of a nature park seems to help orient beef production towards short supply chains. We discuss possible leverage for public action to reconnect beef production areas to consumption areas (the city) via short supply chains (e.g. green, home-grown school food programs) so as to increase local food security through increased local food self-sufficiency.

The COVID-19 pandemic has resulted in a wide range of spatial interventions to slow down the spread of the virus. The spatial limitations of narrow public circulation spaces within informal settlements, which house over one billion people around the world, make it impossible for pedestrians to practice physical distancing (or social distancing). In this paper, we propose a flexible mathematical method, named the Cluster Lane Method, for turning a planar circulation network of any size or complexity into a network of unidirectional lanes, making physical distancing possible in narrow circulation spaces by limiting face-to-face interactions. New notions and theorems about oriented graphs in graph theory are introduced. The paper ends with a discussion of the potential implementation of this cost-efficient, low-tech, sustainable solution, and with the introduction of a novel unidirectional tactile paving for the visually impaired.

Off-grid electrification planning increasingly recognizes the importance of productive use of electricity (PUE) to promote community value creation and (financial) project sustainability. To ensure a sustainable and efficient integration in the community and energy system, PUE assets must carefully be evaluated to match both the community needs and the residential electricity demand patterns. We propose a novel methodology interlinking qualitative interviews, statistical analysis, and energy system modelling to optimize decision-making for PUE integration in off-grid energy systems in rural Madagascar by aligning relevant PUE effectively with anticipated residential electricity demand patterns based on socio-economic determinants of the community. We find that a possible contribution of the PUE to reducing the electricity costs depends signifi-cantly on three factors: 1. the residential electricity consumption patterns that are influenced by the socio-economic composition of the community, 2. the degree of flexibility of i) PUE assets and ii) operational preferences of the PUE user, and 3. the capacity of community members to finance and operate PUE assets. Our study demonstrates that significant cost reductions for PUE-integrated off-grid energy systems can be achieved by applying our proposed methodology. When matching PUE and residential consumption patterns, the integration of PUE assets in residential community energy system can reduce the financial risk of operators, provided the PUE enterprise operates reliably and sustainably. We highlight that the consideration of local value chains and co-creation approaches are essential to ensure the energy system is addressing the community’s needs, creates value for the community, enhances the project´s financial sustainability, and is achieving the overall objectives of decentralized energy system planning.

Healthcare professionals and resource planners can use healthcare delivery process mining to ensure the optimal utilisation of scarce healthcare resources when developing policies. Within hospitals, patients' Length of Stay (LOS) and volume of admitted patients, in terms of number and characteristics (age, gender, and social deter-minants), are significant factors determining daily resource requirements. In this study, we used Coxian phase-type Distribution (C-PHD) based Phase-Type Survival (PTS) trees for analysing how covariates such as admission date, gender, age, district, and admissions source influence the admission rate and LOS distribution. PTS trees. This study used a two-year data set (2011-2012) of patients admitted to the Emergency Department at Mater Dei Hospital to generate models and an independent one-year data set (2013) of patients admitted to the Emergency Department at Mater Dei Hospital to evaluate. The PTS tree effectively clusters patients based on their LOS, considering the prognostic significance of different covariates related to patients' characteristics. Charac-terising these covariates provided meaningful results about LOS. Similarly, the PTS tree was used to effectively cluster patients based on the admission rate, considering the prognostic significance of these covariates.

Home confinement during the COVID-19 pandemic has been accompanied by dramatic changes in household food dynamics that can significantly influence health. This systematic literature review presents parental perspectives of the impact of COVID-19 lockdown on food preparation and meal routines, as well as other food-related behaviors, capturing both favorable and unfavorable changes in the family food environment (FFE). Themes and trends are identified and associations with other lifestyle factors are assessed. In overall, families enjoyed more time together around food, including planning meals, cooking, and eating together. Eating more diverse foods and balanced meals was combined with overeating and increased snacking, as parents became more permissive towards food; however, food insecurity increased among families with the lowest income. Adoption of meal planning skills and online shopping behavior emerged alongside behaviors aimed at self-sufficiency, such as bulk purchasing and stockpiling. These results are an important first step in recognizing how this pandemic may be affecting the FFE, including low-income families. Future obesity prevention and treatment initiatives, but also ongoing efforts to address food management, parental feeding practices, and food insecurity, can account for these changes moving forward.

The combination of interstitial hyperthermia treatment (IHT) with high dose rate brachytherapy (HDR-BT) for prostate cancer treatment and has the potential to improve clinical outcome, since it highly enhances the efficiency of cell kill, especially when applied simultaneously. Therefore, we have developed the ThermoBrachy applicators. To effectively apply optimal targeted IHT, treatment planning is considered essential. However, treatment planning in IHT is rarely applied since it is regarded difficult to accurately calculate the deposited energy in the tissue in a short enough time for clinical practice. In this study, we investigated various time-efficient methods for fast computation of the electromagnetic (EM) energy deposition resulting from the ThermoBrachy applicators. Initially, we investigated the use of an electro-quasistatic solver. Next, we extended our investigation to the application of geometric simplifications. Furthermore, we investigated the validity of the superpositioning principle, which can enable adaptive treatment plan optimization without the need for continuous recomputation of the EM field. Finally, we evaluated the accuracy of the methods by comparing them to the golden standard Finite-Difference Time-Domain calculation method using gamma-index analysis. The simplifications considerably reduced the computation time needed, improving from >12 h to a few seconds. All investigated methods showed excellent agreement with the golden standard by showing a >99% passing rate with 1%/0.5 mm Dose Difference and Distance-to-Agreement criteria. These results allow the proposed electromagnetic simulation method to be used for fast and accurate adaptive treatment planning.

The need to address climate change and establish sustainable urban environments has driven increased efforts in Europe to develop climate-neutral cities. This study highlights the importance of integrating solar energy technologies and nature-based solutions as key strategies to achieve climate neutrality. By examining current practices, emerging trends, and case examples, it explores the benefits, challenges, and prospects associated with the integration of solar energy and nature-based solutions in urban contexts. The study presents a pioneering approach to assess the urban heat and climate change mitigation benefits of combining building-integrated photovoltaics and nature-based solutions specifically within the European context. The results emphasize the synergistic relationship between nature-based components and solar conversion technology, identifying effective combinations for different climatic zones. In warmer regions of Southern Europe, strategies like rooftop photovoltaics on cool roofs, photovoltaics shadings, green walls, and urban trees have demonstrated effectiveness. Conversely, mid- and high-latitude European cities have seen positive impacts through the integration of rooftop photovoltaics and photovoltaics facades with green roofs and green spaces. As solar cell conversion efficiency improves, the environmental impact of photovoltaics is expected to decrease, facilitating their integration into urban environments. The study emphasizes the importance of incorporating water bodies, cool pavements, spaces with high sky-view factors, and effective planning in urban design to maximize resilience benefits. It also highlights the significance of prioritizing mitigation actions in low-income regions and engaging citizens in the development of social photovoltaics positive energy houses, resilient neighbourhoods, and green spaces. By adopting these recommendations, European cities can lead the way in creating climate-neutral urban environments that prioritize clean energy, nature-based solutions, and the overall well-being of residents. The findings underscore the need for a multidisciplinary approach that combines technological innovation, urban planning strategies, and policy frameworks to effectively achieve climate neutrality in European cities.

Smart, reliable, and connected multi-modal mobility has been a long-standing goal of transit services. This paper focuses on the smart, seamless, and multi-modal mobility service in the context of “Mobility as a Service” (MaaS). Intelligent mobility is the smarter, greener, and more efficient movement of passengers around the world. Increasingly, mobility is approached as a service. This study first conducts an extensive literature review on mobility behavior and demand pattern of MaaS end-users. It then extends the mechanism of supply chain, MaaS, synergy (i.e., vertical cooperation synergy, horizontal competition synergy), and coopetition to develop the multi-tier closed-loop intelligent mobility service supply chain network. This paper explains the intelligent mobility service supply chain network from following perspectives: (i) mobility service taxonomy of MaaS; (ii) aims of intelligent mobility service supply chain network; (iii) urban rail transit (URT)-centered alternatives for integrated multimodal journey planning, i.e. access + URT + egress, and both access and egress can be served by Mobility-On-Demand (MOD) transport; (iv) node member imperatives. From a synthesis of insights from the ‘during’ journey, this study puts forward the synergetic design of intelligent mobility service supply chain network, including: (i) multi-tier closed-loop structure; (ii) key nodes identification for the physical multimodal transport network in the supply chain; (iii) hybrid synergy mechanisms among the partners, i.e., synergy principle, temporal splitting approach for coopetition synergy; (iv) index systems and evaluation methods for synergy measurement. This study also contributes to the integrated multimodal journey planning. In concluding, the paper highlights the important implications of the proposed intelligent mobility service supply chain network for MaaS bundle design and adverse effects reduction, resulting from 1 + 1 > 2 synergy effects.