Search Results (4,261)

Ethno-tourism is increasingly recognized as a driver of rural development and cultural preservation, particularly in the Balkans, where ethno-villages represent important centers of heritage, identity, and community revitalization. Despite its significance, the systematic assessment of sustainability in ethno-tourism remains underexplored. This study addresses this gap by applying the Analytic Hierarchy Process (AHP) to evaluate the sustainability performance of thirteen ethno-villages across Serbia, Montenegro, Bosnia and Herzegovina, and Croatia. Data were collected through interviews with owners and managers, complemented by benchmarking and SWOT analyses, to develop a multi-criteria model incorporating five dimensions: economic performance, environmental sustainability, infrastructure and management, tourism attractiveness, and socio-cultural aspects. The results highlight economic performance as the most influential factor, followed by environmental sustainability and infrastructure, while tourism attractiveness and socio-cultural aspects had relatively lower importance. The ranking of villages revealed Drvengrad Mećavnik (Serbia) as the most sustainable destination, with robustness confirmed through sensitivity analyses. This study represents one of the first comprehensive, multi-criteria evaluations of ethno-village sustainability in the Balkans. The results demonstrate that long-term success depends on balancing financial viability with ecological practices, infrastructural investment, and cultural preservation. This research provides evidence-based recommendations for policymakers and stakeholders, and highlights the value of multi-criteria approaches for sustainable tourism planning. Full article

The rapid use of renewables like wind power (WP) and photovoltaic (PV) power is essential for a sustainable energy future, yet their volatility poses a threat to grid stability. Electric vehicles (EVs) contribute to the solution by providing storage, while biomass energy (BE) ensures a reliable and sustainable power supply, solidifying its critical role in the stable operation and sustainable development of the power system. Therefore, a dynamic economic emission dispatch (DEED) model based on WP–PV–BE–EVs (DEED_WPBEV) is proposed. The DEED_WPBEV model is designed to simultaneously minimize operating costs and environmental emissions. The model formulation incorporates several practical constraints, such as those related to power balance, the travel needs of EV owners, and spinning reserve. To obtain a satisfactory dispatch solution, an adaptive improved multi-objective evolutionary algorithm based on decomposition with differential evolution (IMOEA/D-DE) is further proposed. In IMOEA/D-DE, the initialization of the population is achieved through an iterative chaotic map with infinite collapses, and the differential evolution mutation operator is adaptively adjusted. Finally, the feasibility and effectiveness of the proposed model and algorithm are verified on the ten-units system. The experimental results show that the proposed model and algorithm can effectively mitigate renewable energy uncertainty, reduce system costs, and lessen environmental impact. Full article

The rapid expansion of the global pet food industry has intensified interest in understanding the factors shaping pet owners’ purchasing decisions. This systematic literature review synthesises evidence from 40 peer-reviewed studies published between 2006 and 2024 to identify the key drivers of consumer behaviour toward commercial pet food. Following PRISMA guidelines, articles were retrieved from Scopus, Web of Science, and Google Scholar. Findings reveal six main categories influencing purchasing behaviour: intrinsic and extrinsic product characteristics, psychological, biological and physiological, sociocultural, and situational factors. Product quality, ingredient composition, price, brand reputation, sustainability, and pet health status emerged as consistent determinants of choice. The review highlights that consumer behaviour toward pet food remains a developing research field with limited cross-regional studies and methodological diversity. Future research should expand geographically and explore the intersection of sustainability, pet welfare, and owner psychology in pet food decision-making. Full article

Germany’s energy transition to a higher share of renewable energy sources (RESs) is characterized by decentralization, with citizens, cooperatives, SMEs, and municipalities playing a central role. As of early 2025, private individuals own a significant share of renewable energy installations, particularly PV panels, which corresponds to approximately half of the total installed PV power. This trend is driven by physical, technological, and societal factors. Technological advances in battery storage and sector coupling are expected to further decentralize the energy system. Thereby, the electrification of mobility, particularly through electric vehicles (EVs), offers significant storage potential and grid-balancing capabilities via bidirectional charging, although it also introduces challenges, especially for distribution grids during peak loads. Within this work we present a detailed digital twin of the entire distribution grid of the rural German municipality of Wüstenrot. Using grid operator data and transformer measurements, we evaluate strategic expansion scenarios for electromobility, PV and heat pumps based on existing infrastructure and predicted growth in both public and private sectors. A core focus is the intelligent integration of EV charging infrastructure to avoid local overloads and to optimise grid utilisation. Thereby municipally planned and privately driven expansion scenarios are compared, and grid bottlenecks are identified, proposing solutions through charge load management and targeted infrastructure upgrades. This study of Wüstenrot’s low-voltage grid reveals substantial capacity reserves for future integration of heat pumps, electric vehicles (EVs), and photovoltaic systems, supporting the shift to a sustainable energy system. While full-scale expansion would require significant infrastructure investment, mainly due to widespread EV adoption, simple measures like temporary charge load reduction could cut grid stress by up to 51%. Additionally, it is shown that bidirectional charging offers further relief and potential income for EV owners. Full article

Current and potential electric vehicle (EV) owners express concerns about the charging infrastructure, mentioning non-functional chargers, prolonged charging times, inconvenient charger locations, long wait times, and high costs as major barriers. Addressing these issues often requires analyzing actual vehicle charging data, which is typically proprietary and inconsistent due to diverse standards and protocols. To understand and improve the EV charging experience, customer reviews are typically used to identify common customer pain points (CPPs). However, there is not a comprehensive method to map customer reviews to a standardized set of CPPs. In collaboration with the National Charging Experience (ChargeX) Consortium, this study bridges these gaps by proposing a Systematic Categorization and Analysis of Large-scale EV-charging Reviews (SCALER) framework. SCALER is an integrated, deep learning framework that segments, actively labels, analyzes, and classifies EV charging customer reviews into six CPP categories. To test its effectiveness, we used SCALER to analyze over 72,000 reviews from customers charging various EV models on different networks across the United States. SCALER achieves a classification accuracy of 92.5%, with an F1 score exceeding 85.7%. By demonstrating real-world applications of SCALER, we enhance the industry’s ability to understand and address CPPs to improve the EV charging experience. Full article

Rural dwellings are often self-designed and self-built by their owners, with construction decisions based on experience and imitation of nearby buildings. As existing advanced design methods are often too complex or resource-intensive for rural contexts, balancing cost-efficiency, energy performance, and functional needs remains a challenge. This paper proposes to use the matrix analysis method, which is a relatively simple and easy-to-learn procedure, to identify the optimal design of rural houses. Taking Hebi, located in the Central Plains of China, as an example, field research was carried out, and a baseline model was established. A number of variable models were analysed using the control variable method for building orientation and indoor headroom, and metrics such as energy consumption, uncomfortable hours and construction costs were calculated to screen out effective metrics. Furthermore, by combining matrix analysis with orthogonal tests, the approach enables the development of optimal design solutions more efficiently and with reduced complexity. The results show that the optimised design, generated using the proposed method, significantly improves the indoor thermal environment—reducing energy consumption by 65.26% and uncomfortable hours by 29.22%, with only a 1.3% increase in construction costs. This study contributes to sustainable rural development by proposing a practical framework that guides the design of low-cost and energy-efficient rural housing. Full article

Europe, including Poland, is undergoing an energy transition. The use of renewable energy sources (RES) in the national energy sector is increasing significantly, and previously unused areas are increasingly developed for photovoltaic power plants. A specific type of housing common in Eastern European countries opens an additional opportunity for photovoltaic installations without occupying usable ground area. This article aims to analyze the potential for utilizing balconies and loggias in large-panel buildings, which are characteristic of major cities in Poland. Approximately 30% of the population resides in such housing. This presents significant potential for direct use of renewable energy by apartment residents. The article also explores the legal framework for such installations, both as individual investments by apartment owners and as collective initiatives managed by building administrators. The authors analyzed the potential performance of photovoltaic installations under varying azimuths and tilt angles, considering solar irradiation potential. The analyses also encompassed different photovoltaic module technologies, covering a spectrum of photovoltaic technologies, from commonly used monocrystalline panels to advanced transparent BIPV (Building-Integrated Photovoltaics) solutions. Furthermore, the study quantified the energy potential of such installations and compared the results with existing photovoltaic capacities and electricity demand in Poland. Full article

This article examines the expansion of short-term rentals in Valparaíso, Chile, through the Airbnb platform. The study addresses the broader context of digital platforms transforming housing markets, with a focus on Latin American cities, where the implications of short-term rental growth remain understudied. The main objective is to understand how Airbnb is reshaping the spatial, economic, and social dimensions of rental housing in Valparaíso. Methodologically, the article employs quantitative methods, combining spatial analysis techniques (using ArcGIS) and descriptive statistical analysis. The results reveal that entire homes cluster in heritage-tourism hills (Concepción and Alegre) and coastal zones with panoramic views, where nightly rates can exceed the citywide average threefold, while shared rooms are dispersed in lower-income hills. Likewise, the study identifies a heterogeneous host profile; half of the hosts are owners who have another residence to live in, while the other half offers rooms within their own homes, indicating that platform usage is a complementary income strategy. These dynamics reflect asset-based welfare logics, repositioning housing as a hybrid asset for income generation rather than solely a domestic space. Even in the absence of large-scale corporate landlords, this fragmented market contributes to housing commodification and intensifies spatial inequalities. The study highlights the need for regulatory frameworks tailored to the socio-territorial specificities of heritage Latin American cities, which face both housing deficits and tourism pressures. Full article

Owner-led self-medication for companion animals is a growing global practice; however, empirical data from Japan remain limited. Framing medication safety within a One Health perspective, this study aimed to characterize Japanese pet owners’ use of over-the-counter (OTC) drugs and identify possibilities for pharmacists to support rational self-medication. A cross-sectional 13-item online survey was administered to 500 owners in Japan between 30 May and 2 June 2025. Data on owner demographics, willingness to consult pharmacists, veterinary visit behavior, and OTC purchasing practices were summarized. Many owners were receptive to pharmacy support; 65% wished to consult a pharmacist, and 6.8% had already done so. Overall, 15.2% reported using OTCs drugs, primarily for treatment or prevention and prioritized perceived effectiveness and safety when selecting products. Some owners managed mild pet illnesses at home, citing perceived mildness and cost as reasons for not visiting a veterinary clinic. There is an unmet demand for accessible expert counseling at the point of purchase. Leveraging community pharmacies linked with pet specialty pharmacies as first-contact hubs could promote appropriate self-medication; doing so would require veterinary-specific training, establishing a formal credential for veterinary pharmacists, and defining pharmacist–veterinarian communication to ensure safe and effective use. Full article

In developed countries such as Spain, where the population is increasingly aging, retirement planning and longevity risk represent major societal challenges. In Spain, in particular, a significant proportion of household wealth is concentrated in real estate, primarily in the form of owner-occupied housing. For this reason, one emerging financial product in the retirement savings space is the reverse mortgage (RM). This study examines the determinants of acceptance of this financial product using survey data collected from Spanish individuals. The intention to take out an RM is explained through performance expectancy (PE), effort expectancy (EE), social influence (SI), bequest motive (BM), financial literacy (FL), and risk (RK). The analysis applies machine learning techniques: decision tree regression is used to visualize variable interactions that lead to acceptance; random forest to improve predictive capability; and Shapley Additive Explanations (SHAP) to estimate the relative importance of predictors. Finally, Importance–Performance Map Analysis (IPMA) is employed to identify the variables that merit greater attention in the acceptance of RMs. SHAP values indicate that PE and SI are the most influential predictors of intention to use RMs, followed by BM and EE with moderate importance, whereas the positive influence of RK and FL is more reduced. The IPMA highlights PE and SI as the most strategic drivers, and RK and BM act as relevant barriers to the widespread adoption of RMs. Full article

Family dogs stand out with regard to their special (human-like) attachment behavior towards their owners. This dog–owner attachment bond, analogous to the human infant–mother relationship, has been extensively documented at the behavioral level. Capitalizing on the fully non-invasive polysomnography protocol, the current study compares family dogs’ sleep structure when sleeping in the company of their owners versus an experimenter (a friendly stranger human). Subjects (N = 9) participated in three recording sessions, each lasting 3 h. The first session served as an adaptation to the recording environment, while the second and third were the test sessions analyzed for the present paper. On these two occasions, dogs slept, in a counterbalanced order, once in the company of their owner, while on the other occasion they slept in the company of an experimenter, while the owner was outside the room. Polysomnography recordings were used to extract high-resolution information (in 20 s epochs) on the time dogs spend awake and in each of the sleep stages (drowsiness, non-REM, and REM). Our results show a robust difference between dogs’ sleep structure with and without the owner. In addition to an increased sleep latency and worsened sleep efficiency, dogs spent considerably less time in deep sleep (non-REM) when their owner was absent. These findings add to the increasing body of literature dealing with dog-to-owner attachment and provide unique physiological evidence for the phenomenon, complementing the widely reproduced behavioral data. Full article

Does the head tilt observed in many domesticated dogs index lateralized language processing? To answer this question, the present study evaluated household dogs responding to four conditions in which owners provided an increasing number of communicative cues. These cues ranged from no communicative/affective cues to rich affective cues coupled with dog-directed speech. Dogs’ facial responses were first coded manually using the Dog Facial Action Coding System (DogFACS), followed by an in-depth investigation of head tilt behavior, in which AI-based automated analysis of head tilt and audio analysis of acoustic features extracted from communicative cues were implemented. In a sample of 103 dogs representing seven breed groups and mixed-breed dogs, we found significant differences in the number of head tilts occurring between conditions, with the most communicative (last) condition eliciting the most head tilts. There were also significant differences in the direction of the head tilts and between sex groups. Dogs were more likely to tilt their heads to the right, and neutered male dogs were more likely to tilt their heads than spayed female dogs. The right-tilt bias is consistent with left-hemisphere language processing in humans, with males processing language in a more lateralized manner, and females processing language more bilaterally—a pattern also observed in humans. Understanding the canine brain is important to both evolutionary research through a comparative lens, and in understanding our interspecies relationship. Full article

Humans show neural specificity in processing animal-related information, especially regarding companion animals. However, the underlying cognitive mechanisms remain poorly understood. This study’s main objective is to investigate human neural specificity in processing companion animal-related information, compared to other animal types and inanimate objects. Forty participants viewed four image types (companion animals, neutral animals, positive objects, neutral objects) during functional magnetic resonance imaging (fMRI) scans and judged image categories. T-test results showed: 1. Processing companion animal-related information elicited specific brain activation in the right Inferior Parietal Lobe (right IPL), right Middle Occipital Gyrus (right MOG), left Superior Frontal Gyrus (left SFG), and left Precuneus (left PCu) (<0.05). 2. Generalized Psychophysiological Interaction (gPPI) analysis revealed specific functional connectivity changes between relevant brain regions during companion animal info processing (<0.05). 3. Dynamic Causal Modelling (DCM) analysis showed significant intrinsic connectivity differences between pet owners and non-pet owners: specifically, left IPL to left PCu and right ACC to right MOG (posterior probability, Pp > 0.95). The results of this study demonstrate that humans exhibit distinct neural specificity when processing information related to companion animals compared with livestock and inanimate objects. This neural specificity involves brain regions linked to higher-order cognitive functions (e.g., visual processing, emotion, and attachment), all of which are integral components of the human attachment network. These regions are part of the human attachment network, and their functional role likely relates to attachment mechanisms. These findings help clarify companion animals’ impact on human neural activity during human–animal interactions and guide applications like animal-assisted therapy. Full article

This study aims to provide an efficient framework for the coordinated integration of AC and DC chargers, intermittent solar Photovoltaic (PV) Distributed Generation (DG) units, and a Distribution Static Compensator (DSTATCOM) across residential, commercial, and industrial zones of a Radial Distribution Network (RDN) considering the benefits of various stakeholders: Electric Vehicle (EV) charging station owners, EV owners, and distribution network operators. The model uses a multi-zone planning method and healthy-bus strategy to allocate Electric Vehicle Charging Stations (EVCSs), Photovoltaic Distributed Generation (PVDG) units, and DSTATCOMs. The proposed framework optimally determines the numbers of EVCSs, PVDG units, and DSTATCOMs using Harris Hawk Optimization, considering the maximization of techno-economic benefits while satisfying all the security constraints. Further, to showcase the benefits from the perspective of EV owners, an EV waiting-time evaluation is performed. The simulation results show that integrating EVCSs (with both AC and DC chargers) with solar PVDG units and DSTATCOMs in the existing RDN improves the voltage profile, reduces power losses, and enhances cost-effectiveness compared to the system with only EVCSs. Furthermore, the zonal division ensures that charging infrastructure is distributed across the network increasing accessibility to the EV users. It is also observed that combining AC and DC chargers across the network provides overall benefits in terms of voltage profile, line loss, and waiting time as compared to a system with only AC or DC chargers. The proposed framework improves EV owners’ access and reduces waiting time, while supporting distribution network operators through enhanced grid stability and efficient integration of EV loads, PV generation, and DSTATCOM. Full article

The associations of pet ownership and well-being have been widely discussed, but previous studies have shown inconsistent results, often due to their limited sample size and diversity. We analyzed data from a nationally representative survey conducted by the Cabinet Office of Japan in 2019 (n = 10,293; age range = 15–89 years; 50.4% female). Ownership of co-walkable pets (e.g., dogs), indoor-only pets (e.g., cats), and ornamental pets (e.g., tropical fish) was examined as a predictor. Well-being was measured using eleven domains based on the OECD Better Life Index. Demographic covariates were included. Of the participants, 13.3% owned a co-walkable pet, 13.0% an indoor-only pet, and 6.8% an ornamental pet. The pet owners were more likely to live in a house they owned and have a larger floor area, higher income, and greater debt. The non-pet owners were more likely to live alone. In the unadjusted models, the ownership of co-walkable pets was associated with higher well-being in terms of housing and community. However, in the adjusted models, the ownership of co-walkable pets was associated with lower well-being in terms of income, jobs, environment, and, marginally, safety. No significant associations were found for indoor-only and ornamental pet ownership. In Japan, pet ownership requires both financial resources and adequate living space. It is also important to note that pet owners who go outside for walking their animals may also find that their environmental and economic circumstances are less satisfying. Full article