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Tourism in Coimbra today is influenced by the fact that the Univer(s)city was distinguished as a World Heritage Site in 2013. The number of visits has grown very significantly in recent years, but the diversification of the tourist offer is still weak and unable to take advantage of existing resources. This paper aims to present genealogy tourism as an alternative urban cultural tourism in Coimbra.

Methodology involved mapping the Jewish culture elements in the city of Coimbra, and a route was outlined and proposed.

Genealogy tourism resources are identified in the historic centre of the city. These alternative spaces need urban rehabilitation and (re)functionalisation, which allowed the authors to rethink tourism in Coimbra. They are the motivation to visit for all urban cultural tourists, especially Israelis/Jews, and provide contact with places where the experiences of ancestors combine with the history and memory of places, with recent discoveries and the elements of Jewish culture in the city.

It is concluded that the quantity, diversity, authenticity and singularity of the heritage resources that bear witness to the Jewish presence in Coimbra are sufficient assets to create a route, to enrich the tourist experience in the city and to include the destination in the Sephardic routes.

The present study aims to examine the scope and contribution of behavioural investigative advice (BIA) reports from the National Crime Agency (NCA).

The 77 BIA reports reviewed were written between 2016 and 2021. They were evaluated using Toulmin’s (1958) strategy for structuring pertinent arguments, current compliance with professional standards, the grounds and backing provided for the claims made and the potential utility of the recommendations provided.

Consistent with previous research, most of the reports involved murder and sexual offences. The BIA reports met professional standards with extremely high frequency. The 77 reports contained a total of 1,308 claims of which 99% were based on stated grounds. A warrant and/or backing was provided for 73% of the claims. Most of the claims in the BIA reports involved a behavioural evaluation of the crime scene and offender characteristics. The potential utility of the reports was judged to be 95% for informative behavioural crime scene analysis and 40% for potential new lines of enquiry.

The reports should serve as a model for the work of behavioural investigative advisers internationally.

To the best of the authors’ knowledge, this is the first study to systematically evaluate BIA reports commissioned by the NCA; it adds to previous similar studies by evaluating the largest number of BIA reports ever reviewed, and uniquely provides judgement of overall utility.

Heavy rainfall is one of the main causes of the degradation of historic rammed Earth architecture. For this reason, ensuring the conservation thereof entails understanding the factors involved in these risk situations. The purpose of this study is to research three past events in which rainfall caused damage and collapse to historic rammed Earth fortifications in Andalusia in order to analyse whether it is possible to prevent similar situations from occurring in the future.

The three case studies analysed are located in the south of Spain and occurred between 2017 and 2021. The hazard presented by rainfall within this context has been obtained from Art-Risk 3.0 (Registration No. 201999906530090). The vulnerability of the structures has been assessed with the Art-Risk 1 model. To characterise the strength, duration, and intensity of precipitation events, a workflow for the statistical use of GPM and GSMaP satellite resources has been designed, validated, and tested. The strength of the winds has been evaluated from data from ground-based weather stations.

GSMaP precipitation data is very similar to data from ground-based weather stations. Regarding the three risk events analysed, although they occurred in areas with a torrential rainfall hazard, the damage was caused by non-intense rainfall that did not exceed 5 mm/hour. The continuation of the rainfall for several days and the poor state of conservation of the walls seem to be the factors that triggered the collapses that fundamentally affected the restoration mortars.

A workflow applied to vulnerability and hazard analysis is presented, which validates the large-scale use of satellite images for past and present monitoring of heritage structure risk situations due to rain.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

The purpose of this study is to address the challenges faced by rural areas and promote their sustainable development. It emphasizes the importance of re-establishing connections and cultivating a sense of belonging within rural communities, while safeguarding their cultural heritage. The study explores the potential of digital and creative tools in enhancing learning, supporting food production and tourism, facilitating research and providing engaging experiences. It also examines the economic condition of rural areas and the potential for their contribution to the national economy. Additionally, the study highlights the significance of sustainable community development, the role of rural areas in resilience and climate change adaptation and the complexities surrounding rural migration. The aim is to provide insights and recommendations for policymakers and stakeholders involved in rural development initiatives, focusing on the Mediterranean region.

This study develops an understanding of the role of digital and creative strategies in rural communities, highlighting their significance in preserving food heritage, culture and community capital while driving economic development. It specifically focuses on the Unesco Intangible Mediterranean Diet (UIMD) as a potential catalyst for regeneration through the integration of creative and digital tools and three cases are presented. The first is the impact of the Future Food Institute (FFI) ecosystem in the Living Lab in Pollica (Salerno, Italy); the second focuses on the digital tools provided by the CKF to support rural areas; and the third is a new identity and promotion of territorial development, co-designed in the Val di Vara (VdV) a rural region of the Ligurian inland in Italy, through digital strategies, heritage preservation and slow tourism development. The three cases highlight different ways of enhancing environmental and cultural heritage and demonstrate how collaborative creativity and digital tools contribute to the co-construction of knowledge and addressing critical issues to promote sustainable growth in rural areas.

The findings of this study indicate that re-establishing connections and fostering a sense of belonging within rural communities is crucial for their sustainable development. The use of digital and creative tools presents significant opportunities in enhancing various aspects such as learning, food production, tourism and research in rural areas. The study also reveals the potential economic contributions of rural areas to the national economy. It emphasizes the importance of sustainable community development and highlights the role of rural areas in resilience and climate change adaptation. Additionally, the study addresses the complexities surrounding rural migration and emphasizes the need for comprehensive policies to ensure the well-being and rights of migrant workers. The insights and recommendations provided in this study aim to guide policymakers and stakeholders involved in rural development initiatives, particularly in the Mediterranean region.

Nonetheless, it is imperative to acknowledge certain limitations within the scope of this study, primarily associated with the specific sample selection, potentially influencing the broader applicability of the findings. There is potential to explore a wider geographic area in future research. Additionally, the research underscores the importance of conducting further inquiries into certain aspects that have received limited attention. Living labs are a relatively recent phenomenon, warranting further in-depth scientific research. Additionally, the existing literature on this subject is often limited in scope.

The study and project aim to illustrate the feasibility of initiating a transformative process, centered on a visionary approach with a core focus on creative knowledge and the Mediterranean diet as a way of life, to revitalize marginalized communities. Furthermore, it seeks to emphasize that these neglected regions possess untapped potential for innovative ideas and opportunities. Rural communities, in their role as farmers of primary goods, are the ones who nurture the environment, and the landscape, and are the true protagonists of every era. Rurality is the place that preserves the most resources and potential in terms of biodiversity and rural knowledge. Every territory, like every human being, has its own characteristics and vocations to pursue. The existing Genius Loci is already an existing value that requires policies and governance to rediscover roots, identity and worth. The stratification of existing collective intelligence must become central and must be individually assessed and enhanced, also taking advantage of new digital technologies.

The social implications of this study are significant. By emphasizing the importance of re-establishing connections and cultivating a sense of belonging within rural communities, the study recognizes the social value of strong community ties. This can lead to increased social cohesion, a sense of identity and improved overall well-being within rural areas. The study also highlights the potential of digital and creative tools in enhancing learning, which can contribute to the empowerment and educational opportunities of individuals in rural communities. Furthermore, by promoting sustainable community development and addressing the complexities surrounding rural migration, the study acknowledges the social impact of inclusive policies that protect the rights and well-being of both local populations and migrant workers. Overall, the study's recommendations have the potential to foster social resilience, equity and a more vibrant social fabric within rural areas.

This study can offer valuable insights and recommendations for policymakers and stakeholders involved in rural development initiatives, particularly those focused on preserving food and cultural heritage in rural areas. By analyzing real-life examples, it bridges the gap between theory and practice, illustrating how these ideas have been effectively applied in specific contexts. This paper emphasizes the potential of the Mediterranean Diet as a sustainable and nutritious model with sociocultural, health, economic and environmental benefits, highlighting the importance of bottom-up approaches that empower local communities as custodians of knowledge and culture. It also provides practical strategies, such as investments in educational programs, the establishment of international campuses and the use of multichannel platforms for immersive experiences, which can be adapted for broader rural development initiatives, promoting sustainability and community engagement.

The purpose of this paper is to investigate the most recurrent variables characterizing the collaborative relationships of industrial symbiosis (IS) (hereinafter also referred to as “anatomic” variables) established in the attempt to adopt circular economy (CE) by collecting evidence from a rich empirical set of implementation cases in Italy.

The current literature on IS was reviewed, and a content analysis was performed to identify and define the “anatomic” variables affecting its adoption in the circular economy. We followed a multiple-case study methodology investigating 50 cases of IS in Italy and performed a content analysis of the “anatomic” variables characterizing each case.

This research proposes the “anatomic” variables (i.e. industrial sectors involved, public actors involvement, governmental support, facilitator involvement and geographical proximity) explaining the cases of IS in the circular economy. Each “anatomic” variable is discussed at length based on the empirical evidence collected, with a particular reference to the impact on the different development strategies (i.e. “bottom-up” and “top-down”) in the cases observed.

Current literature on IS focuses on a sub-set of variables characterizing collaboration in IS. This research builds on extant literature to define a new framework of five purposeful “anatomic” variables defining IS in the circular economy. Moreover, we also collect and discuss a broad variety of empirical evidence in what is a still under-investigated context (i.e. Italy).

Conflict and violence are the main drivers of globally escalating humanitarian needs. Local grassroots initiatives are pivotal in distributing humanitarian supplies in the acute response phase until more established humanitarian aid organizations can enter. Nevertheless, scant research exists regarding the role of grassroots associations in providing humanitarian assistance during a military conflict. The purpose of this paper is to understand the role of grassroots associations and identify important themes for effective operations.

This paper adopts a case-study approach of three Ukrainian grassroots associations that began operating in the immediate days of the full-scale invasion of Ukraine. The findings are based on analyzing primary sources, including interviews with Ukrainian volunteers, and are supported by secondary sources.

Grassroots associations have local contacts and a contextual understanding of population needs and can respond more rapidly and effectively than large intergovernmental agencies. Four critical themes regarding the operations of grassroots associations emerged: information management, inventory management, coordination and performance measurement. Grassroots humanitarian response operations during conflict are challenged by personal security risks, the unpredictability of unsolicited supplies, emerging volunteer roles, dynamic transportation routes and shifting demands.

Grassroots responses are central to humanitarian responses during the acute phase of a military conflict. By examining the operations of grassroots associations in the early months of the 2022 war in Ukraine, the authors provide a unique perspective on humanitarian logistics. Nonetheless, more inclusive models of humanitarian responses are needed to harness the capacities and resilience of grassroots operations in practice.