Search Results (2,420)

The increase in tourism economic benefits is the most common purpose along the Mediterranean coastal regions but, very often, conflicts of interest arise between short-term benefits and long-term conservation goals. This is particularly the case of Albania, a very popular emerging “Sun, Sea and Sand” (3S) destination characterized by massive fluxes of national/international visitors during the summer period. Among beach users’ preferences, global studies show that five parameters of greater importance stand out from the rest, i.e., safety, facilities, water quality, no litter, and scenery, and the latter is the main concern of this study. Albania is well known for its outstanding natural coastal beauty which was assessed at 40 sites by using the Coastal Scenic Evaluation System (CSES) method. Based on the evaluation of 26 physical/human parameters and using weighting matrix parameters and fuzzy logic mathematics, the technique enables one to obtain an Evaluation Index (D) that allows one to classify each investigated site into five scenic classes, from Class I (extremely attractive natural sites; D ≥ 0.85) to Class V (very unattractive developed urban/industrial sites; D < 0.00). Pragmatically, the higher the “D” value is, the better the site scenery is. After a long process of field testing along the whole Albanian coastline (ca. 523 km in length), selected sites were chosen in rural/remote environments (22), villages (6), and urban (4) and resort areas (8) to reflect the Albanian coastal typicity and characterize the scenic impact of human activities. Most sites belonged to Class III (14), Class IV (13), Class II (8), and Class I (1). Several sites could be upgraded to Class I or Class II with slight management efforts, e.g., by carrying out cleaning operations or by reducing intrusive beach facilities. Full article

The Galapagos Islands are undeniably a highly attractive ecosystem for scientists worldwide. However, the energy efficiency and sustainability aspects of their building stock have not yet been studied in depth, which directly hinders the achievement of sustainability goals for the Archipelago, such as reducing resource consumption, minimizing emissions, and improving overall comfort in buildings. Addressing these issues is critical to preserving the islands’ unique ecosystem, as current construction practices are unsustainable and exacerbate environmental pressures, causing over-consumption of local resources and upsetting the delicate ecological balance that sustains this fragile environment. In line with the National Energy Efficiency Plan promoted by the Government of Ecuador for the Archipelago, this study provides transparent and reliable information and data on the building stock of the islands. This work quantifies the impact of buildings on the use of resources and analyses the potential savings of different strategies for reducing greenhouse gas emissions. Various representative typologies are established based on the collection of architectural, construction, and usage information. For each of these typologies, various energy models are developed to establish the baseline and to analyse the demand and comfort of the buildings under different renovation scenarios in order to validate the sustainable construction strategies to be implemented. Moreover, new standards are also defined in order to reduce energy and water consumption and increase indoor air quality and comfort in buildings. In an attempt to generate evidence and facilitate the replication and implementation of sustainable construction standards, three Living Labs (LLs) are created to validate different strategies and technological solutions in different locations, according to the defined standards: a school in Santa Cruz, a hotel in Isabela, and a residential building in San Cristóbal. The findings highlight the effectiveness of specific energy-saving strategies and water conservation measures validated through Living Labs implemented in different locations across the islands. Furthermore, the knowledge generated is transferred through local training of the agents of the construction chain and administration. Full article

Since the 1990s, the academic discourse on climate change, migration, and adaptation has undergone significant shift. Individuals previously characterized as “climate refugees” are now cast as adaptable agents. Against this backdrop, academic explorations of the nexus between mobility and adaptation within the context of climate change have burgeoned, particularly in the latter half of the 2000s. The objective of this paper is to identify linkages between adaptation and different forms of (im)mobility situated on the spectrum of movement that has been conceptualized and discussed in theoretical and empirical material. To accomplish this, I undertake an exhaustive review of the extant literature on the subject of climate change-induced (im)mobility and adaptation. This paper suggests three possible types of relationships between (im)mobility and adaptation in the context of climate and environmental change: adaptation in situ, relocation, and migration as an adaptation strategy. These dimensions have so far been treated separately by scholars. Full article

Accurate soil maps are essential for soil protection, management, and digital agriculture. However, traditional soil maps often lack the detail required for local applications, while farm-scale surveys are often not economically viable. This study uses legacy soil data and digital soil mapping (DSM) to produce accurate, low-cost maps of key soil properties, namely clay, sand, total lime (CaCO₃), organic carbon (SOC), total nitrogen (TN), and the cation-exchange capacity (CEC). The DSM procedure involved multivariate stepwise regression kriging that uses the terrain attributes and bare soil reflectance composite (SRC) from Sentinel-2 multitemporal images. The procedure to obtain the SRC was carried out following the Soil Composite Mapping Processor (SCMaP) methodology. The Sentinel-2 bands of the SRC showed strong correlations with soil features, making them very suitable explicative variables for regression kriging. In particular, the SWIR bands (b11 and b12) were important covariates in predicting clay, sand, and CEC maps. The accuracy of the regression models was very good for clay, sand, SOC, and CEC (R² > 0.90), while CaCO₃ showed lower accuracy (R² = 0.67). Normalization of SOC, TN, and CaCO₃ did not significantly improve the prediction accuracy, except for SOC, which showed a slight improvement. In addition, a supervised classification approach was applied to predict soil typological units (STUs) using the mapped soil attributes. This methodology demonstrates the potential of SRCs and regression kriging to produce detailed soil property maps to support precision agriculture and sustainable land management. Full article

There are still gaps in the legislation on the protection of rural areas in Turkey. Despite these gaps, rural settlements and the cultural heritage in these settlements are attracting attention with the increasing demand for places with high ecotourism potential, which has become more popular with the COVID-19 pandemic. Many rural areas, especially those with unused vernacular architectural elements, have been rehabilitated and made available for ecotourism use by local people and tourists. One such area is the (former) village of Beydilli in the Sütçüler district of Isparta province, Turkey. The people of the village have abandoned this area, which has a history of about 250 years, due to the lack of transport and other facilities, and only a few building owners visit the village for transhumance in the summer, but even these users use the houses as warehouses. In order to achieve this objective, the present study employed a range of methods, including on-site observation, laser measurement (surveying), utilisation of oral sources, texture analysis, typological comparison, and SWOT analysis. These methods were selected for their suitability for the protection of rural architecture in a context of ecotourism. In order to develop rural tourism in a manner that preserves the cultural heritage, a series of solution proposals have been developed under a number of different headings, including transportation, accessibility, the physical condition of buildings, socio-economic factors, and the tourism sector. In making decisions, consideration was given to the potential for ecotourism in the Sütçüler district, to which Beydili is connected. The principal objective of this research is to present the findings of the study, which focuses on cultural heritage and its conservation in order to ensure the sustainability of ecotourism planning in rural areas, with a specific case study of Beydilli Village in the Sütçüler District of Isparta. Furthermore, this study aims to highlight the significance of safeguarding cultural heritage, which constitutes a vital component of rural tourism in Turkey. Despite the existence of inadequate rural protection legislation, this study seeks to document the conservation status of Beydilli Village, which has not undergone any conservation work to date. Full article

This review explores the novel integration of data-driven approaches, including artificial intelligence (AI) and machine learning (ML), in advancing building energy retrofits. This study uniquely emphasizes the emerging role of explainable AI (XAI) in addressing transparency and interpretability challenges, fostering the broader adoption of data-driven solutions among stakeholders. A critical contribution of this review is its in-depth analysis of innovative applications of AI techniques to handle incomplete data, optimize energy performance, and predict retrofit outcomes with enhanced accuracy. Furthermore, the review identifies previously underexplored areas, such as scaling data-driven methods to diverse building typologies and incorporating future climate scenarios in retrofit planning. Future research directions include improving data availability and quality, developing scalable urban simulation tools, advancing modeling techniques to include life-cycle impacts, and creating practical decision-support systems that integrate economic and environmental metrics, paving the way for efficient and sustainable retrofitting solutions. Full article

This study evaluates the effect of protein hydrolysates, obtained from grape seed meal (industrial waste), as colour stabilisers in red wines from warm climates. Protein hydrolysates were added to the wine after fermentation and maceration. Assays were performed using different types and doses of protein hydrolysates. Two grapevine-growing seasons were monitored over 8 months. Attention was focused on different families of polyphenolic compounds, copigmentation, and polymerisation, and colour changes were assessed by differential tristimulus colourimetry. Regardless of doses and typology, wines with protein hydrolysates suffered a decrease in the amount of phenolics and an increase in % polymerisation. Only wines treated with 3 g/L of hydrolysates showed lower colour intensity and greater clarity and hue after 8 months, while treatment with 0.5 g/L produced brownish wines. The addition of hydrolysates from a low hydrolysis time did not affect the copigmentation balances or produced negative visually perceptible colour differences over time. These results indicate that the post-fermentation addition of protein hydrolysates does not seem to significantly improve the stabilisation of the wine colour, in contrast to the addition at other stages. This information is of great interest to wineries to consider the application of this novel technique at the optimal time. Full article

Extraction of dense 3D geographic information from ultra-high-resolution unmanned aerial vehicle (UAV) imagery unlocks a great number of mapping and monitoring applications. This is facilitated by a step called dense image matching, which tries to find pixels corresponding to the same object within overlapping images captured by the UAV from different locations. Recent developments in deep learning utilize deep convolutional networks to perform this dense pixel correspondence task. A common theme in these developments is to train the network in a supervised setting using available dense 3D reference datasets. However, in this work we propose a novel unsupervised dense point cloud extraction routine for UAV imagery, called UnDER. We propose a novel disparity-shifting procedure to enable the use of a stereo matching network pretrained on an entirely different typology of image data in the disparity-estimation step of UnDER. Unlike previously proposed disparity-shifting techniques for forming cost volumes, the goal of our procedure was to address the domain shift between the images that the network was pretrained on and the UAV images, by using prior information from the UAV image acquisition. We also developed a procedure for occlusion masking based on disparity consistency checking that uses the disparity image space rather than the object space proposed in a standard 3D reconstruction routine for UAV data. Our benchmarking results demonstrated significant improvements in quantitative performance, reducing the mean cloud-to-cloud distance by approximately 1.8 times the ground sampling distance (GSD) compared to other methods. Full article

Systematic studies on Late Islamic cemeteries that integrate architectural, ritual, and biological aspects remain relatively rare, particularly in Islamic countries or regions with an active Muslim presence. Typically, available research focuses more on epigraphic and artistic features. Since 2018, excavations at the Cathedral and surveys in the ruins of the city of Adulis (Massawa, Eritrea) have uncovered 326 Muslim graves: six dating to the 15th and 18th centuries CE and 320 attributed to the mid-19th to the early 20th century CE. These discoveries have enabled, for the first time in Eritrea, a detailed scientific study of the biological characteristics of the human remains, the funerary architecture, and the burial rites of Muslim communities from the 15th to the early 20th century. The skeletal remains were analyzed through taphonomic and anthropological studies. The graves were categorized into various typologies based on their structural features, while evidence of funerary rituals was documented as indicative elements of the burial practices adopted. These findings were further enriched by ethnographic sources and collaborative work with local communities, who acted as custodians of the historical memory and traditions of the region. The results provide insights into a historical period of Eritrea that is otherwise poorly documented. More broadly, they contribute to the understanding of the history of the Horn of Africa, a region with limited data from funerary and archaeological contexts. The Muslim cemeteries of Adulis represent the most extensively investigated Muslim burial site in recent years, providing critical insights into the historical Muslim presence in the region. These findings also allow researchers to hypothesize the succession of various communities that chose Adulis as a central location for interring their deceased, reflecting its enduring significance as a focal point for cultural and ritual practices across different periods. Full article

Glazed tiles are a quintessential ceramic creation applied in architectural systems, with Chinese pagodas serving as emblematic symbols that embody the design philosophy and diverse cultural beliefs of construction. Despite enduring wars, extreme weather, and the passage of millennia, glazed pagodas have withstood the test of time. The erosion of glazed components by wind and rain has not diminished their solemnity but has added a profound historical depth, making these surviving ancient-glazed components even more precious. This study examines the structural and stylistic features of Chinese glazed pagodas, exploring the extent of glazed component coverage. Using quantitative methods, the study zones, calculates, and classifies Chinese glazed pagodas, further elucidating their evolution and development through various historical periods. Additionally, based on a comprehensive survey of Chinese glazed pagodas, the study integrates theories from archaeology, art history, and architecture to deeply analyze their distribution areas, chronological spans, and cultural contexts, offering new perspectives for the systematic classification of Chinese glazed pagodas. Full article

This study evaluates the impact of building orientation, typology, and envelope characteristics on energy efficiency and CO₂ emissions in urban dwellings in subtropical climate, with a focus on Cartagena, Colombia. North-facing dwellings consistently demonstrate superior energy performance, achieving an average efficiency increase of 4.27 ± 1.77% compared to south-facing counterparts. This trend is less pronounced near the equator due to the sun’s high zenith angle. Semi-detached homes exhibit 23.17 ± 9.83% greater energy efficiency than corner houses, attributed to reduced exterior wall exposure, which lowers energy demand and CO₂ emissions by 2.16 ± 0.74 kg CO₂/m² annually. Significant disparities in emissions are observed across socioeconomic strata; homes in strata 3 and 4 show the lowest emissions (6.69 ± 1.42 kg CO₂/m² per year), while strata 5 and 6 have the highest (10.48 ± 1.42 kg CO₂/m² per year), due to differences in construction quality and glazing ratios. Roofing materials also play a key role, with thermoacoustic (TAC) roofs reducing emissions by up to 5.80% in lower strata compared to asbestos–cement roofs. Furthermore, sandwich panels demonstrate substantial potential, achieving CO₂ emissions reductions of up to 51.6% in strata 1 and 2 south-facing median homes and a minimum saving of 9.4% in strata 5 and 6. These findings underscore the importance of integrating energy performance criteria into public housing policies, promoting construction practices that enhance sustainability and reduce greenhouse gas emissions while improving occupant comfort and property value. Full article

The Grand Canal, the world’s longest artificial waterway, is a cultural treasure deeply embedded in China’s historical traditions. This study emphasizes the importance of safeguarding, preserving, and revitalizing this invaluable heritage to ensure its relevance. Guided by the “Regulations on the Protection and Management of the Grand Canal Heritage”, this research analyzed 276 cultural relics protection units within the Jiangsu section of the Beijing-Hangzhou Grand Canal (Jiangsu-BHGC). By applying spatial geographic analysis techniques, including point density analysis and gravity shift models, the study mapped the historical evolution, spatial distribution, and typological characteristics of these relics. Additionally, using ArcGIS and geographic detectors, the research explored factors influencing the distribution of these units, pinpointing critical determinants. This rigorous approach provides an in-depth understanding of the spatial arrangement of cultural heritage sites along the canal, supporting its coordinated development. By examining distribution patterns and key attributes, the study offers theoretical insights and data-driven guidance for optimizing the sustainable use of this cultural heritage. Full article

Water Infrastructure (WI), incorporating water supply, wastewater, and stormwater systems, is vulnerable to climate change impacts that can disrupt their functionality; thus, WI needs to be adapted to climate change. In 2021, the European Commission (EC) released the technical guidelines on “Climate-proofing Infrastructure” that include mitigation and adaptation strategies; these guidelines, and the relevant guides that followed, focus mainly on climate change aspects without examining sufficiently the engineering features of WI that are described mainly in the relevant hydro-environmental research; this research is vast and includes various terminologies and methods for all aspects of climate change adaptation. The adaptation procedure of WI to climate change is improved when this research is known to guidelines’ developers. In the present work, to facilitate this knowledge transfer, we typologize the hydro-environmental research via its classification into five categories that are based on the EC guidelines and then perform a literature review that we present as follows: firstly, we introduce and typologize the climate hazards for WI systems and identify the most common of them in the Mediterranean region that we classify into seven groups; then, we classify the hydro-environmental research into five categories based on the EC guidelines, present the main aspects for each of these categories, discuss the future research; and finally, we summarize the conclusions. Full article

Emotion recognition through artificial intelligence and smart sensing of physical and physiological signals (affective computing) is achieving very interesting results in terms of accuracy, inference times, and user-independent models. In this sense, there are applications related to the safety and well-being of people (sexual assaults, gender-based violence, children and elderly abuse, mental health, etc.) that require even more improvements. Emotion detection should be done with fast, discrete, and non-luxurious systems working in real time and real life (wearable devices, wireless communications, battery-powered). Furthermore, emotional reactions to violence are not equal in all people. Then, large general models cannot be applied to a multi-user system for people protection, and health and social workers and law enforcement agents would welcome customized and lightweight AI models. These semi-personalized models will be applicable to clusters of subjects sharing similarities in their emotional reactions to external stimuli. This customization requires several steps: creating clusters of subjects with similar behaviors, creating AI models for every cluster, continually updating these models with new data, and enrolling new subjects in clusters when required. An initial approach for clustering labeled data compiled (physiological data, together with emotional labels) is presented in this work, as well as the method to ensure the enrollment of new users with unlabeled data once the AI models are generated. The idea is that this complete methodology can be exportable to any other expert systems where unlabeled data are added during in-field operation and different profiles exist in terms of data. Experimental results demonstrate an improvement of 5% in accuracy and 4% in F1 score with respect to our baseline general model, along with a 32% to 58% reduction in variability, respectively. Full article

Previous researchers developed a comprehensive typology for categorizing social entrepreneurship; however, their framework does not fully address some emerging forms. This paper offers a critical addition to their model by introducing the “transnational pragmatist”, a type of social entrepreneur with a grassroots background who creates a community-centric social enterprise in a foreign context. Through insights gained from interviews with social entrepreneurs, this paper identifies and defines the transnational pragmatist as a distinct category that fills a significant gap in Abebe’s framework. Our contribution broadens the typology to better capture smaller for-profit and nonprofit ventures operating transnationally, enhancing the model’s relevance for international social entrepreneurs from humble origins. Full article