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This study introduces a mixed-integer linear programming (MILP) model, effectively co-optimizing patrolling, damage assessment, fault isolation, repair, and load re-energization processes. The model is designed to solve a vital operational conundrum: deciding between further network exploration to obtain more comprehensive data or addressing the repair of already identified faults. As information on the fault location and repair timelines becomes available, the model allows for dynamic adaptation of crew dispatch decisions. In addition, this study proposes a conservative power flow constraint set that considers two network loading scenarios within the final network configuration. This approach results in the determination of an upper and a lower bound for node voltage levels and an upper bound for power line flows. To underscore the practicality and scalability of the proposed model, we have demonstrated its application using IEEE 123-node and 8500-node test systems, where it delivered promising results.

This study introduces a mixed-integer linear programming (MILP) model, effectively co-optimizing patrolling, damage assessment, fault isolation, repair, and load re-energization processes. The model is designed to solve a vital operational conundrum: deciding between further network exploration to obtain more comprehensive data or addressing the repair of already identified faults. As information on the fault location and repair timelines becomes available, the model allows for dynamic adaptation of crew dispatch decisions. In addition, this study proposes a conservative power flow constraint set that considers two network loading scenarios within the final network configuration. This approach results in the determination of an upper and a lower bound for node voltage levels and an upper bound for power line flows. To underscore the practicality and scalability of the proposed model, we have demonstrated its application using IEEE 123-node and 8500-node test systems, where it delivered promising results.

The importance of early diagnosis of hepatitis B virus infection to treat and follow up this disease has led to many advances in diagnostic techniques and materials. Conventional diagnostic tests are not very useful, especially in the early stages of infection; it is therefore suggested that nanomaterials can enhance them by changing and strengthening their performance for a more accurate and rapid diagnosis. Electrochemical immunosensors with unique features such as miniaturization, low cost, specificity and simplicity have become a suitable and vital tool in the rapid diagnosis of hepatitis B since the patent. Different strategies have been presented, such as graphene oxide and gold nanorods (GO-GNRs), graphene oxide (GO), copper metal–organic framework/ electrochemically reduced graphene oxide (Cu-MOF/ErGO) composite, Label-free graphene oxide/ Fe₃O₄/Prussian Blue (GO/Fe₃O₄/PB) immunosensor, and graphene oxide–ferrocene-CS/Au (GOFc- CS/Au) nanoparticle layered electrochemical immunosensor. In this review, we discuss a group of the most widely used nanostructures, such as graphene and carbon nanotubes, which are used to develop electrochemical immunosensors for the early diagnosis of the hepatitis B virus.

The importance of early diagnosis of hepatitis B virus infection to treat and follow up this disease has led to many advances in diagnostic techniques and materials. Conventional diagnostic tests are not very useful, especially in the early stages of infection; it is therefore suggested that nanomaterials can enhance them by changing and strengthening their performance for a more accurate and rapid diagnosis. Electrochemical immunosensors with unique features such as miniaturization, low cost, specificity and simplicity have become a suitable and vital tool in the rapid diagnosis of hepatitis B since the patent. Different strategies have been presented, such as graphene oxide and gold nanorods (GO-GNRs), graphene oxide (GO), copper metal–organic framework/ electrochemically reduced graphene oxide (Cu-MOF/ErGO) composite, Label-free graphene oxide/ Fe₃O₄/Prussian Blue (GO/Fe₃O₄/PB) immunosensor, and graphene oxide–ferrocene-CS/Au (GOFc- CS/Au) nanoparticle layered electrochemical immunosensor. In this review, we discuss a group of the most widely used nanostructures, such as graphene and carbon nanotubes, which are used to develop electrochemical immunosensors for the early diagnosis of the hepatitis B virus.

Hydrogen is an energy carrier that can support the development of sustainable and flexible energy systems. However, decarbonization can occur when green sources are used for energy production and appropriate water use is manifested. This work aims to propose a socio-economic analysis of hydrogen production from an integrated wind and electrolysis plant in southern Italy. The estimated production amounts to about 1.8 million kg and the LCOH is calculated to be 3.60 €/kg in the base scenario. Analyses of the alternative scenarios allow us to observe that with a high probability the value ranges between 3.20–4.00 €/kg and that the capacity factor is the factor that most affects the economic results. Social analysis, conducted through an online survey, shows a strong knowledge gap as only 27.5 % claim to know the difference between green and grey hydrogen. There is a slight propensity to install systems near their homes, but this tends to increase due to increased knowledge on the topic. Respondents state sustainable behaviours, and this study suggests that these aspects should also be transformed into the energy choices that are implemented every day. The study suggests information to policy-makers, businesses and citizens as it outlines that green hydrogen is an operations strategy that moves toward sustainable development.

Hydrogen is an energy carrier that can support the development of sustainable and flexible energy systems. However, decarbonization can occur when green sources are used for energy production and appropriate water use is manifested. This work aims to propose a socio-economic analysis of hydrogen production from an integrated wind and electrolysis plant in southern Italy. The estimated production amounts to about 1.8 million kg and the LCOH is calculated to be 3.60 €/kg in the base scenario. Analyses of the alternative scenarios allow us to observe that with a high probability the value ranges between 3.20–4.00 €/kg and that the capacity factor is the factor that most affects the economic results. Social analysis, conducted through an online survey, shows a strong knowledge gap as only 27.5 % claim to know the difference between green and grey hydrogen. There is a slight propensity to install systems near their homes, but this tends to increase due to increased knowledge on the topic. Respondents state sustainable behaviours, and this study suggests that these aspects should also be transformed into the energy choices that are implemented every day. The study suggests information to policy-makers, businesses and citizens as it outlines that green hydrogen is an operations strategy that moves toward sustainable development.