Search Results (1,703)

The purpose of this study is to investigate the factors that influence tourist behavior and revisit intentions in the context of halal tourism. The antecedent variables in this study included religiosity, digital halal literacy, halal destination features, contentment, and trust. This is a quantitative study that used travelers that visited halal tourism attractions in West Sumatra, Indonesia, as the sample population. The sample size was 400 respondents. The data were analyzed using the partial least squares–structural equation model (PLS-SEM). We discovered that religiosity is an important predictor of contentment and trust. Satisfaction was achieved through digital halal literacy and halal destination qualities and was found to have a significant influence on trust, tourist behavior, and revisit intentions. Finally, trust was found to have a significant association with intention to revisit and behavior. The results of this research are insightful for managers and policymakers on how to provide halal tourism attributes and analyze tourists’ digital halal literacy that lead to tourist satisfaction. This study also provides further knowledge to policymakers and local authorities on how to promote future tourist participation in halal tourism development in Indonesia; thus, it can help create more tourist returns for further visits to the same location in the future. Full article

Sources of renewable energy have attracted considerable attention. Their expanded use will have a substantial impact on both the cost of energy production and climate change. Solar energy is one efficient and safe option; however, solar energy harvesting sites, irrespective of the location, can impact the ecosystem. This experimental study explores the energy available inside and outside of novel miniature energy harvesting cages by measuring light intensity and power generated. Varying light intensity outside the cage has been utilized to study the remaining energy inside the cage of a flexible design, where the heights of the harvesting panels are parameters. Cages are built from custom photovoltaic panels arranged in a staircase manner to provide access to growing plants. The balance between power generation and biological development is investigated. Two different structures are presented to explore the variation of illumination intensity inside the cages. The experimental results show a substantial reduction in energy inside the cages. The experimental results showed up to 24% reduction in illumination inside the cages in winter. The reduction is even larger in summer, up to 57%. The results from the models provide a framework to study the possible impact on a biological system residing inside the cages, paving the way for practical farming with sustainable energy harvesting. Full article

Solving competitive facility location problems can optimize market share or operational efficiency in environments where multiple firms compete for customer attention. In such contexts, facility attractiveness is shaped not only by geographic proximity but also by customer preference characteristics. This study presents a novel heuristic framework that integrates multi-view K-means clustering with customer behavior modeling reinforced by a co-regularization mechanism to align clustering results across heterogeneous data views. By jointly exploiting spatial and behavioral information, the framework clusters customers and facilities into meaningful market segments. Within each segment, a bilevel optimization model is applied to represent the sequential decision-making of competing entities—where a leader first selects facility locations, followed by a reactive follower. An empirical evaluation on a real-world dataset from San Francisco demonstrates that the proposed approach, using optimal co-regularization parameters, achieves a total runtime of approximately 4.00 s—representing a 99.34% reduction compared to the full CFLBP-CB model (608.58 s) and a 99.32% reduction compared to a genetic algorithm (585.20 s). Concurrently, it yields an overall profit of 16,104.17, which is an approximate 0.72% increase over the Direct CFLBP-CB profit of 15,988.27 and is only 0.21% lower than the genetic algorithm’s highest profit of 16,137.75. Moreover, comparative analysis reveals that the proposed multi-view clustering with co-regularization outperforms all single-view baselines, including K-means, spectral, and hierarchical methods. This superiority is evidenced by an approximate 5.21% increase in overall profit and a simultaneous reduction in optimization time, thereby demonstrating its effectiveness in capturing complementary spatial and behavioral structures for competitive facility location. Notably, the proposed two-stage approach achieves high-quality solutions with significantly shorter computation times, making it suitable for large-scale or time-sensitive competitive facility planning tasks. Full article

Spatial association analysis is essential for understanding interdependencies, spatial proximity, and distribution patterns within spatial data. The spatial scale is a key factor that significantly affects the result of spatial association mining. Traditional methods often rely on a fixed distance threshold (bandwidth) to define the scale effect, which can lead to scale sensitivity and discontinuity results. To address these limitations, this study introduces the Fuzzy Geographically Weighted Colocation Quotient (FGWCLQ) method. By integrating fuzzy theory, FGWCLQ replaces binary distance cutoffs with continuous membership functions, providing a more flexible and stable approach to spatial association mining. Using Point of Interest (POI) data from the Beijing urban area, FGWCLQ was applied to explore both intra- and inter-category spatial association patterns among star hotels, transportation facilities, and tourist attractions at different fuzzy neighborhoods. The results indicate that FGWCLQ can reliably discover global prevalent spatial associations among diverse facility types and visualize the spatial heterogeneity at various spatial scales. Compared to the deterministic GWCLQ method, FGWCLQ delivers more stable and robust results across varying spatial scales and generates more continuous association surfaces, which enable clear visualization of hierarchical clustering. Empirical findings provide valuable insights for optimizing the location of star hotels and supporting decision-making in urban planning. The method is available as an open-source Matlab package, providing a practical tool for diverse spatial association investigations. Full article

Ceria is an important redox catalyst due to the facile Ce³⁺/Ce⁴⁺ switching at its surface. Therefore, in situ determination of the oxidation state of surface cerium cations is of significant interest. Infrared spectroscopy of probe molecules such as CO holds great potential for this purpose. However, the ability of CO to reduce Ce⁴⁺ cations is an important drawback as it alters the initial cerium speciation. Dinitrogen (N₂), due to its chemical inertness, presents an attractive alternative. We recently demonstrated that low-temperature ¹⁵N₂ adsorption on stoichiometric ceria leads to the formation of complexes with Ce⁴⁺ cations on the (110) and (100) planes (bands at 2257 and 2252 cm⁻¹, respectively), while the (111) plane is inert. Here, we report results on the low-temperature ¹⁵N₂ adsorption on reduced ceria nanoshapes (cubes, polyhedra, and rods). A main band at 2255 cm⁻¹, with a weak shoulder at 2254 cm⁻¹, was observed. We attributed these bands to ¹⁵N₂ adsorbed on Ce³⁺ sites located on edges and corners as well as on {100} facets. In conclusion, ¹⁵N₂ adsorbs on the most acidic surface Ce³⁺ sites and enables their distinction from Ce⁴⁺ cations. Full article

Swirl spray combustion has attracted significant attention due to its common usage in gas turbines. However, the high pressure in many practical applications remains a major obstacle to the deep understanding of flame stability and pollutant formation. To address this concern, this study investigated a swirl spray flame fueled with n-decane at elevated pressure. Planar laser-induced fluorescence (PLIF) of OH and polycyclic aromatic hydrocarbons (PAHs) were used simultaneously, enabling the distinction of the locations of OH, PAHs, and mixtures of them, providing detailed information on flame structure and evolution of PAHs. The effects of swirl number and ambient pressure on reaction zone characteristics and PAHs’ formation were studied, with the swirl number ranging from 0.30 to 1.18 and the pressure ranging from 1 to 3 bar. The data suggest that the swirl number changes the flame structure from V-shaped to crown-shaped, as observed at both atmospheric and elevated pressures. Additionally, varying swirl numbers lead to the initiation of flame divergence at distinct pressure levels. Moreover, PAHs of different molecular sizes exhibit significant overlap, with larger PAHs able to further extend downstream. The relative concentration of PAH increased with pressure, and the promoting effect of pressure on producing larger PAHs was significant. Full article

Optimization problems often feature local optima with a significant difference in the basin of attraction (BoA), making evolutionary computation methods prone to discarding solutions located in less-attractive BoAs, thereby posing challenges to the search for optima in these BoAs. To enhance the ability to find these optima, various niching methods have been proposed to restrict the competition scope of individuals to their specific neighborhoods. However, redundant searches in more-attractive BoAs as well as necessary searches in less-attractive BoAs can only be promoted simultaneously by these methods. To address this issue, we propose a general framework for niching methods named niching-driven divide-and-conquer hill exploration (NDDCHE). Through gradually learning BoAs from the search results of a niching method and dividing the problem into subproblems with a much smaller number of optima, NDDCHE aims to bring a more balanced distribution of searches in the BoAs of optima found so far, and thus enhance the niching method’s ability to find optima in less-attractive BoAs. Through experiments where niching methods with different categories of niching techniques are integrated with NDDCHE and tested on problems with significant differences in the size of the BoA, the effectiveness and the generalization ability of NDDCHE are proven. Full article

The analysis of the spatial location of tourists is essential for effective tourism management. This study explores the potential effects of large language models (LLMs) on urban travel planning. Despite growing academic interest in LLMs, empirical research on their specific impact on urban tourist locations remains limited, even though these models may significantly affect tourist behavior and spatial dynamics. This article compares the location of heritage sites in the city of Barcelona that are traditionally visited by tourists (as identified through Instagram) with those recommended by ChatGPT. The results show that ChatGPT tends to recommend a much smaller and more spatially concentrated number of tourist attractions than those shared on Instagram. The findings indicate that ChatGPT reinforces mainstream representations of cities by prioritizing well-known landmarks, potentially overlooking emerging or local attractions. This simplification can lead to tourist overcrowding and the marginalization of less-visited areas. Likewise, it may entail new needs for the management of urban spaces. Urban planners and tourism managers may need to intervene to redistribute tourist flows in a context where various models of tourist behavior will coexist. Full article

This study presents a digital twin–based framework for assessing rockfall hazards at the immediate vicinity of the Rumkale Archaeological Site, a geologically sensitive and culturally significant location in southeastern Türkiye. Historically associated with early Christianity and strategically located along the Euphrates, Rumkale is a protected heritage site that attracts increasing numbers of visitors. Here, high-resolution photogrammetric models were generated using imagery acquired from a remotely piloted aircraft system and post-processed with ground control points to produce a spatially accurate 3D digital twin. Field-based geomechanical measurements including discontinuity orientations, joint classifications, and strength parameters were integrated with digital analyses to identify and evaluate hazardous rock blocks. Kinematic assessments conducted in the study revealed susceptibility to planar, wedge, and toppling failures. The results showed the role of lithological structure, active tectonics, and environmental factors in driving slope instability. The proposed methodology demonstrates effective use of digital twin technologies in conjunction with traditional geotechnical techniques, offering a replicable and non-invasive approach for site-scale hazard evaluation and conservation planning in heritage contexts. This work contributes to the advancement of interdisciplinary methods for geohazard-informed management of cultural landscapes. Full article

Despite the ideal of a unified Single Market, a powerful “home bias” pervades EU public procurement, hinting at unseen barriers that conventional analysis fails to capture. This study introduces an interpretable AI framework to investigate these dynamics, pairing a LightGBM model with SHapley Additive exPlanations (SHAP) to examine the vast Tenders Electronic Daily (TED) database (2018–2023). Concretely, we propose a fuzzy linguistic layer that translates SHAP’s complex quantitative outputs into intuitive, human-readable terms. Our model effectively distinguishes local from non-local awards (AUC ≈ 0.855), revealing that while high-value contracts expectedly attract broader competition, the most potent predictors are a country’s own history of local awards and structural factors like the buyer’s type and location. This points not to isolated incidents, but, rather, to deep-seated patterns shaping market fairness. Our combined XAI-Fuzzy approach offers a new instrument for transparent governance, enabling policymakers to diagnose market realities and forge a more genuinely open and equitable European public square. Full article

In power grids that integrate renewable energy sources, the virtual synchronous machine (VSM) or synchronverter offers a viable solution to the challenge posed by reduced inertia. This technology employs inverters to transfer power to the electrical network that relies on a control algorithm emulating the dynamic behavior of synchronous machines. Over the past decade, it has been applied in various contexts, leveraging its control structure based on the fundamental equations of synchronous machines. Although several review articles have been published on control strategies for grid-forming inverters, they often lack a specific focus on recent developments related to the synchronverter. Therefore, this paper aims to fill that gap by presenting a detailed review on high-quality research databases to retrieve recent documents published in recent years. These documents were classified according to journals, conferences, and books. A keyword bibliographic analysis was performed to identify the attractive topics related to the synchronverter control strategy. The paper reviews recent improvements in and applications of the synchronverter, identifying emerging trends and new potential use cases to provide a workflow guide for readers and researchers, as the documents are presented in comprehensive tables, streamlining the process of locating specific references. In addition, some advantages and disadvantages of synchronverters are reported. Full article

Heortia vitessoides Moore (Lepidoptera: Pyralidae), the dominant outbreak defoliator of Aquilaria sinensis (Myrtales: Thymelaeaceae, the agarwood-producing tree), poses a severe threat to the sustainable development of the agarwood industry. Current research has preliminarily revealed its biological traits and gene functions. However, significant gaps persist in integrating climate adaptation mechanisms, control technologies, and host interaction networks across disciplines. This review systematically synthesizes the multidimensional mechanisms underlying H. vitessoides outbreaks through the logical framework of “Fundamental Biology of Outbreaks—Environmental Drivers—Control Strategies—Molecular Regulation—Host Defense.” First, we integrate the biological characteristics of H. vitessoides with its climatic response patterns, elucidating the ecological pathways through which temperature and humidity drive population outbreaks by regulating development duration and host resource availability. Subsequently, we assess the efficacy and limitations of existing control techniques (e.g., pheromone trapping, Beauveria bassiana application), highlighting the critical bottleneck of insufficient mechanistic understanding at the molecular level. Building on this, we delve into the molecular adaptation mechanisms of H. vitessoides. Specifically, detoxification genes (e.g., HvGSTs1) and temperature stress-responsive genes (e.g., HvCAT, HvGP) synergistically enhance stress tolerance, while chemosensory genes mediate mating and host location behaviors. Concurrently, we reveal the host defense strategy of A. sinensis, involving activation of secondary metabolite defenses via the jasmonic acid signaling pathway and emission of volatile organic compounds that attract natural enemies—an “induced resistance–natural enemy collaboration” mechanism. Finally, we propose future research directions: deep integration of gene editing to validate key targets, multi-omics analysis to decipher the host–pest–natural enemy interaction network, and development of climate–gene–population dynamics models. These approaches aim to achieve precision control by bridging molecular mechanisms with environmental regulation. This review not only provides innovative pathways for managing H. vitessoides but also establishes a paradigm for cross-scale research on pests affecting high-value economic forests. Full article

Jobs–housing balance is a critical concern in urban planning and sustainable economic development. Urban rail transit, as a key determinant of employment and residential location decisions, plays a pivotal role in shaping jobs–housing dynamics. Beijing, the first Chinese city to develop a subway system, offers a comprehensive rail network, making it an ideal case for exploring the effects of transit density on jobs–housing balance. This study utilizes medium-scale panel data from Beijing (2009–2022) and employs a fixed-effects model to systematically examine the impact of rail transit station density on jobs–housing balance and its underlying mechanisms. The results indicate that increasing transit station density tends to aggravate jobs–housing separation overall, with pronounced effects in central and outer suburban areas but negligible effects in near suburban areas. Mechanism analysis reveals two primary pathways: (1) improved accessibility draws employment toward transit-rich areas, reinforcing the attractiveness of central districts; (2) rising housing prices elevate residential thresholds, pushing lower-income populations toward outer suburbs. While enhanced transit density improves commuting convenience, it does not effectively reduce jobs–housing separation. These findings offer important policy implications for optimizing transit planning, improving jobs–housing alignment, and promoting sustainable urban development. Full article

The growing global demand for sustainable energy solutions has spurred interest in hybrid renewable energy systems, particularly those combining photovoltaic (PV) solar and wind power. This study records the technical and financial feasibility of establishing hybrid solar photovoltaic and wind power stations in Iraq, Al-Rutbah and Al-Nasiriya, with a total power of 60 MW for each, focusing on optimizing energy output and cost-efficiency. The analysis evaluates key technical factors, such as resource availability, system design, and integration challenges, alongside financial considerations, including capital costs, operational expenses, and return on investment (ROI). Using the RETScreen program, the research explores potential locations and configurations for maximizing energy production and minimizing costs, and the evaluation is performed through the calculation Internal Rate of Return (IRR) on equity (%), the Simple Payback (year), the Net Present Value (NPV), and the Annual Life Cycle Savings (ALCSs). The results show that both PV and wind technologies demonstrate significant energy export potential, with PV plants exporting slightly more electricity than their wind counterparts. Al Nasiriya Wind had the highest output, indicating favorable wind conditions or better system performance at that site. The results show that the analysis of the proposed hybrid system has a standardizing effect on emissions, reducing variability and environmental impact regardless of location. The results demonstrate that solar PV is significantly more financially favorable in terms of capital recovery time at both sites, and that financial incentives, especially grants, are essential to improve project attractiveness, particularly for wind power. The analysis underscores the superior financial viability of solar PV projects in both regions. It highlights the critical role of financial support, particularly capital grants, in turning renewable energy investments into economically attractive opportunities. Full article

The expansion of unobstructed floor plans has resulted in large open areas, especially in modern designs. Although these new designs are appealing and esthetically attractive, they remain at a risk of large fires which may initiate at certain location(s) and make their way along to the other parts of the compartment. Such fires are called travelling fires and are not currently covered by the design codes due to lack of available research and understanding. Unlike traditional compartment fires, travelling fires may last longer and may result in compromising the structural integrity due to prolonged fire exposure. This article studies the impact of travelling fires on structures with focus on the structural elements, oriented perpendicular to the direction of fire travel. The data presented comes from Test 1, conducted by the authors as part of the TRAFIR project at Ulster University. The details provided include the recorded gas temperatures within the compartment and the temperatures recorded in the surrounding structural elements, along gridlines ② and ③. The test compartment consisted of a steel structure with a hollow core concrete roof. The structural steelwork was supplied with additional dummy columns for data acquisition purposes. The study demonstrates that structural elements located within the fuel bed are subjected to significantly higher temperatures. The gas temperature differences within and outside the fuel bed on occasions exceed 450 °C across compartment width, while the same for columns and beams were up to 350 °C and 200 °C, respectively. Such transient heating of the structure could possibly induce the load distribution within the structure and may help achieve improved global fire resistance. The findings from this study will improve our understanding of travelling fires, their impact on structures, and will open directions to study the collapse mechanisms of structures under the influence of travelling fires and will help with devising design guidance for structures exposed to travelling fires. Full article