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Traditionally, critical infrastructures demand for high dependability, being the services they provide essential to human beings and the society at large. However, more recent attention to cautious usage of energy resources is changing this vision and calls for solutions accounting for appropriate multi-requirements combinations when developing a critical infrastructure. In such a context, analysis supports able to assist the designer in envisioning a satisfactory trade-off among the multi-requirements for the system at hand are highly helpful. In this paper, the focus is on the railway sector and the contribution is a stochastic model-based analysis framework to quantitatively assess trade-offs between dependability indicators and electrical energy consumption incurred by the rail switch heating system.Moving from a preliminary study that concentrated on energy consumption only, the analysis framework has been extended to become a solid support to devise appropriate tuning of the heating policy that guarantees satisfactory trade-offs between dependability and energy consumption. An evaluation campaign in a variety of climate scenarios demonstrates the feasibility and utility of the developed framework.

ABSTRACTIntraguild interactions among carnivores have long held the fascination of ecologists. Ranging from competition to facilitation and coexistence, these interactions and their complex interplay influence everything from species persistence to ecosystem functioning. Yet, the patterns and pathways of such interactions are far from understood in tropical forest systems, particularly across countries in the Global South. Here, we examined the determinants and consequences of competitive interactions between dholes Cuon alpinus and the two large felids (leopards Panthera pardus and tigers Panthera tigris) with which they most commonly co‐occur across Asia. Using a combination of traditional and novel data sources (N = 118), we integrate information from spatial, temporal, and dietary niche dimensions. These three species have faced catastrophic declines in their extent of co‐occurrence over the past century; most of their source populations are now confined to Protected Areas. Analysis of dyadic interactions between species pairs showed a clear social hierarchy. Tigers were dominant over dholes, although pack strength in dholes helped ameliorate some of these effects; leopards were subordinate to dholes. Population‐level spatio‐temporal interactions assessed at 25 locations across Asia did not show a clear pattern of overlap or avoidance between species pairs. Diet‐profile assessments indicated that wild ungulate biomass consumption by tigers was highest, while leopards consumed more primate and livestock prey as compared to their co‐predators. In terms of prey offtake (ratio of wild prey biomass consumed to biomass available), the three species together harvested 0.4–30.2% of available prey, with the highest offtake recorded from the location where the carnivores reach very high densities. When re‐examined in the context of prey availability and offtake, locations with low wild prey availability showed spatial avoidance and temporal overlap among the carnivore pairs, and locations with high wild prey availability showed spatial overlap and temporal segregation. Based on these observations, we make predictions for 40 Protected Areas in India where temporally synchronous estimates of predator and prey densities are available. We expect that low prey availability will lead to higher competition, and in extreme cases, to the complete exclusion of one or more species. In Protected Areas with high prey availability, we expect intraguild coexistence and conspecific competition among carnivores, with spill‐over to forest‐edge habitats and subsequent prey‐switching to livestock. We stress that dhole–leopard–tiger co‐occurrence across their range is facilitated through an intricate yet fragile balance between prey availability, and intraguild and conspecific competition. Data gaps and limitations notwithstanding, our study shows how insights from fundamental ecology can be of immense utility for applied aspects like large predator conservation and management of human–carnivore interactions. Our findings also highlight potential avenues for future research on tropical carnivores that can broaden current understanding of intraguild competition in forest systems of Asia and beyond.

This study provides the first comprehensive overview of the sustainability performance of the hotel sector in the Himalayan region: Sagarmatha National Park and Buffer Zone, using both environmental, economic, and technical criteria. In particular, the performance of 45 buildings in this region were measured and quantified in terms of life cycle based carbon footprint, life cycle costs, heat loss rate, number of guests, energy consumption, and area. Buildings were classified into three types: traditional, semi-modern and modern. The statistical analysis included testing for significant differences between such categories by means of ANOVA, and determination of the correlation between the same parameters. Results show a significant difference between the buildings’ total carbon footprint and operation stage carbon footprint while, there is no significant difference between the buildings’ life cycle costs. Traditional buildings have on average the largest carbon footprint and life-cycle cost over the typical building lifespan of 50 years of building lifespan. The ANOVA tests highlight how heat loss rate, size of the building and number of tourists in the hotels are significantly different across the building types. A strong positive correlation is observed between environmental impact, economic impact and energy consumption for the household activities, and a negative correlation with the number of guests and building size. By considering several buildings, this study allows to draw new and more general conclusions about effective sustainability strategies in the whole hotel sector in the Himalayan region. In particular, it shows that reducing impacts in the operation stage should be highly prioritized, focusing on reducing energy consumption and heat loss and shifting to the use of renewable energy sources.

Industrial symbiosis (IS) is recognized as an effective practice to support circular economy and sustainable development because it is able to enhance the technical efficiency of production processes, provided IS relationships among companies remain active over the long period. However, although it has been established that IS relationships can be vulnerable to disruptive events that reduce the willingness of companies to cooperate in IS synergies, to date few contributions to the literature focus attention on the events which lead firms to interrupt IS synergies. This paper contributes to the existing literature firstly by highlighting the disruptive events affecting the willingness of companies to cooperate in IS synergies and their causes, and secondly by developing an analytical model to assess the impact of each disruption on physical and monetary flows created among companies by the IS relationship. Specifically, an enterprise input-output (EIO) model is proposed, aimed at mapping the physical and monetary flows resulting from IS synergies among companies. Through this model, disruptive events can be modeled and their impact on the above-mentioned flows can be assessed. A numerical case example illustrates how the model works and how company managers and IS facilitators could use it to evaluate to what degree their current IS relationships may be vulnerable to perturbations. The model could therefore facilitate the design of adequate countermeasures and contribute to the development of perturbation resilient IS relationships. Furthermore, policymakers could adopt the model when designing policy actions to support IS practice.

Railway is currently envisioned as the most promising transportation system for both people and freight to reduce atmospheric emission and combat climate change. In this context, ensuring the energy efficiency of the railway systems is paramount in order to sustain their future expandability with minimum carbon footprint. Recent advancements in computing and communication technologies are expected to play a significant role to enable novel integrated control and management strategies in which heterogeneous data is exploited to noticeably increase energy efficiency. In this paper we focus on exploiting the convergence of heterogeneous information to improve energy efficiency of railway systems, in particular on the heating system for the railroad switches, one of the major energy intensive components. To this aim, we define new policies to efficiently manage the heating of these switches exploiting also external information such as weather and forecast data. In order to assess the performance of each strategy, a stochastic model representing the structure and operation of the railroad switch heating system and environmental conditions (both weather profiles and specific failure events) has been developed and exercised in a variety of representative scenarios. The obtained results allow to understand both strengths and limitations of each energy management policy, and serves as a useful support to make the choice of the best technique to employ to save on energy consumption, given the system conditions at hand.