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On 22–23 April 2025, a seismic noise survey was conducted at the Maccalube di Aragona, a mud volcano field located in Sicily (southern Italy), with the aim of characterizing the background signal associated with vent activity and the shallow subsurface structure. The experiment, named DEMETRA (DEnse MaccalubE TRomino Acquisition), was carried out within the framework of the multidisciplinary INGV-PROMUD research project, which aims to identify key indicators of mud volcano activity and potential precursors of paroxysmal events. Ambient seismic noise was recorded at 21 sites using a three-component, 24-bit digital tromograph. Measurements were conducted with a dense spatial sampling scheme covering both vent areas and peripheral zones. Preliminary data analyses included spectral estimates, computation of horizontal-to-vertical spectral ratio (HVSR) curves and evaluation of the polarization patterns. The HVSR curves do not display clear amplification peaks but rather show deamplification at specific sites. The polarization patterns exhibit spatial consistency across the vent areas. In addition, transient signals were identified in the background noise at some sites; based on their spectral and polarization characteristics, these signals are possibly associated with degassing, mud emissions, or bubbling phenomena. The dense spatial coverage of the DEMETRA experiment provides a valuable dataset for investigating subsurface properties and dynamic processes in an active mud volcano environment. Full article

As a key indicator for measuring urban green visibility, the Green View Index (GVI) reflects actual visible greenery from a human perspective, playing a vital role in assessing urban greening levels and optimizing green space layouts. Existing studies predominantly rely on single-source remote sensing image analysis or traditional statistical regression methods such as Ordinary Least Squares and Geographically Weighted Regression. These approaches struggle to capture spatial variations in human-perceived greenery at the street level and fail to identify the non-stationary effects of different drivers within localized areas. This study focuses on the Luolong District in the central urban area of Luoyang City, China. Utilizing Baidu Street View imagery and semantic segmentation technology, an automated GVI extraction model was developed to reveal its spatial differentiation characteristics. Spearman correlation analysis and Multiscale Geographically Weighted Regression were employed to identify the dominant drivers of GVI across four dimensions: landscape pattern, vegetation cover, built environment, and accessibility. Field surveys were conducted to validate the findings. The Multiscale Geographically Weighted Regression method allows different variables to have distinct spatial scales of influence in parameter estimation. This approach overcomes the limitations of traditional models in revealing spatial non-stationarity, thereby more accurately characterizing the spatial response mechanism of the Global Vulnerability Index (GVI). Results indicate the following: (1) The study area’s average GVI is 15.24%, reflecting a low overall level with significant spatial variation, exhibiting a “polar core” distribution pattern. (2) Fractal dimension, normalized vegetation index (NDVI), enclosure index, road density, population density, and green space accessibility positively influence GVI, while connectivity index, Euclidean nearest neighbor distance, building density, residential density, and water body accessibility negatively affect it. Among these, NDVI and enclosure index are the most critical factors. (3) Spatial influence scales vary significantly across factors. Euclidean nearest neighbor distance, building density, population density, green space accessibility, and water body accessibility exert global effects on GVI, while fractal dimension, connectivity index, normalized vegetation index, enclosure index, road density, and residential density demonstrate regional dependence. Field survey results confirm that the analytical conclusions align closely with actual greening conditions and socioeconomic characteristics. This study provides data support and decision-making references for green space planning and human habitat optimization in Luoyang City while also offering methodological insights for evaluating urban street green view index and researching ecological spatial equity. Full article

Road agglomerate fog seriously threatens driving safety, making real-time fog state detection crucial for implementing reliable traffic control measures. With advantages in aerial perspective and a broad field of view, UAVs have emerged as a novel solution for road agglomerate fog monitoring. This paper proposes an agglomerate fog detection method based on the fusion of SURF and optical flow characteristics. To synthesize an adequate agglomerate fog sample set, a novel network named FogGAN is presented by injecting physical cues into the generator using a limited number of field-collected fog images. Taking the region of interest (ROI) for agglomerate fog detection in the UAV image as the basic unit, SURF is employed to describe static texture features, while optical flow is employed to capture frame-to-frame motion characteristics, and a multi-feature fusion approach based on Bayesian theory is subsequently introduced. Experimental results demonstrate the effectiveness of FogGAN for its capability to generate a more realistic dataset of agglomerate fog sample images. Furthermore, the proposed SURF and optical flow fusion method performs higher precision, recall, and F1-score for UAV perspective images compared with XGBoost-based and survey-informed fusion methods. Full article

Deep tech is a broad concept encompassing scientifically and technologically advanced innovations, enterprises, and projects based on profound scientific and engineering knowledge. It addresses complex technological challenges while considering environmental, social, and economic sustainability. Ambitious R&D initiatives act as catalysts for innovative solutions and for transforming companies and sectors toward sustainable development. The literature review highlights the multifaceted nature of deep tech, particularly from diverse stakeholder perspectives—both those directly and indirectly engaged in this field. Fully utilizing deep tech’s potential requires strong scientific, infrastructural, regulatory, and financial foundations. Europe, including dynamically developing EU countries such as Poland, increasingly recognizes the need to build an ecosystem that supports the development and commercialization of frontier technologies grounded in scientific progress. This article clarifies key deep tech concepts and outlines current conditions for technological innovation in Europe. Drawing on desk research, participatory observation, and a survey, it presents an initial analysis of Poland’s deep tech ecosystem. The exploratory pilot study serves as a basis for more focused future research on key sectoral challenges. The findings offer a preliminary assessment of the potential and barriers related to science-based innovation and provide a clearer picture of Poland’s emerging deep tech landscape. This enables more accurate interpretation of results and insights into the sector’s future development. For Europe and the EU, enhancing global competitiveness in deep tech will require coordinated actions and stronger connections among local ecosystems at different stages of maturity, such as those in Poland. Full article

Speech separation, as an important research direction in audio signal processing, has been widely studied by the academic community since its emergence in the mid-1990s. In recent years, with the rapid development of deep neural network technology, speech processing based on deep neural networks has shown outstanding performance in speech separation. While existing studies have surveyed the application of deep neural networks in speech separation from multiple dimensions including learning paradigms, model architectures, loss functions, and training strategies, current achievements still lack systematic comprehension of the field’s developmental trajectory. To address this, this paper focuses on single-channel supervised speech separation tasks, proposing a technological evolution path “U-Net–TasNet–Transformer–Mamba” as the main thread to systematically analyze the impact mechanisms of core architectural designs on separation performance across different stages. By reviewing the transition process from traditional methods to deep learning paradigms and delving into the improvements and integration of deep learning architectures at various stages, this paper summarizes milestone achievements, mainstream evaluation frameworks, and typical datasets in the field, while also providing prospects for future research directions. Through this detailed-focused review perspective, we aim to provide researchers in the speech separation field with a clearly articulated technical evolution map and practical reference. Full article

Recreation, aesthetic appreciation, identity, and spiritual values are among the cultural ecosystem services (CES) produced by long-distance historic and pilgrimage trails. However, it is still difficult to convert these experiential benefits into quantifiable economic flows. This study collected 560 valid responses from an in-field survey conducted along the Via degli Dei (Bologna–Florence). Robust visitor clusters were created using Gower dissimilarities, Partitioning Around Medoids (PAM), silhouette diagnostics, and Factor Analysis for Mixed Data (FAMD). Each cluster was then profiled according to seasonal patterns, information channels, individual-level, per-category expenditures (accommodation, food, transport, services, and equipment), as well as motivations. Four segments are identified—Student Campers (low-budget, peak-summer), Working-Age Male B&B Hikers (short stays, B&B), Young Women on Mixed Lodging (mixed accommodation), and Midlife Comfort-Seekers (higher spend, shoulder-season)—underpinning our spending, seasonality, and managerial implications. Student Campers had the lowest absolute expenditures, while Midlife Comfort-Seekers had the highest (median lodging €180; food €175). The study offers practical levers for route governance (targeted communications, low-impact lodging strategies, shoulder-season promotion) to improve local value capture while reducing environmental pressure by connecting typologies to monetary CES flows. The findings provide a reproducible model for implementing recreational CES on historical-cultural tours. Full article

The “land governance orthodoxy” that has dominated development circles for the past two decades posits that government-issued title deeds are a prerequisite for economic growth in Africa and elsewhere in the Global South. Anything other than formal certification is viewed as inadequate, informal, insecure and inanimate. In this paper, we explore the “institutional pluralism” that characterizes land formalization efforts in rural Tanzania. We find that the multiple (often competing) objectives, procedures, actors, justifications, technologies, and outcomes have produced a crowded and chaotic field of titling initiatives. Despite an investment of around USD 340 million, progress remains painfully slow—at a rate of ~1% per year—such that it will take the rest of this century to reach universal titling. And at what cost? Our study is based on appraisals of policy and project documents and interviews with government officials, donor agencies, project implementers and NGO staff. Discussion of the findings is supported by data from annual budget speeches, national-level statistics and survey data collected by our team from forty Tanzanian villages. We argue that it is time to return to a broader, integrated approach to rural development and recognize that local landholding systems offer high levels of security. Our findings have relevance beyond land formalization to other areas where duplicative efforts implemented in the name of progress might be counterproductive to achieving economic and social development goals. Full article

Perceived value is a key factor shaping consumer purchase decisions. In the field of functional snack consumption, generational differences in value perception dimensions significantly influence decision-making processes, creating both challenges and opportunities for targeted marketing. Drawing on perceived value theory, this study develops a model examining the impact of perceived value on consumption intention for functional snacks. A questionnaire survey was conducted among Chinese Generation Y and Generation Z consumers, and the data were analyzed using PLS-SEM and fuzzy-set Qualitative Comparative Analysis (fsQCA). The results indicate that self-oriented values (functional and hedonic) exert a significant positive effect on other-oriented values (symbolic and social), and both categories of values positively affect consumption intention. Regarding generational moderation, the effects of functional and hedonic values on purchase intention do not differ significantly across generations; however, symbolic value has a stronger influence on Generation Z, while social value plays a more prominent role for Generation Y. Importance–Performance Map Analysis (IPMA) results further reveal differences in the relative importance and performance of value perception between the two groups. Configuration analysis shows that compared with Generation Y, Generation Z exhibits a higher threshold for strong consumption intention, a lower threshold for weak consumption intention, and greater sensitivity to value deficiency. These findings provide practical insights for functional snack companies to address generational differences and optimize marketing strategies. Full article

Very-Low Earth Orbit Synthetic Aperture Radar (VLEO SAR) satellites, defined as SAR satellites operating at orbital altitudes 350 km or below, offer distinct technical advantages compared to conventional SAR satellites. Equipped with a high-resolution SAR payload, the Haishao-1 (HS-1) satellite was successfully launched on 4 December 2024. According to publicly available information, the HS-1 satellite represents the world’s first VLEO SAR satellite and has successfully demonstrated 1-m resolution Stripmap mode imaging with continuous azimuth coverage. Through an analysis of the HS-1 satellite’s system parameters and imaging results, this paper comprehensively explores the advantages of VLEO SAR satellites over traditional orbit SAR satellites, particularly in terms of enhanced resolution, reduced payload costs, and improved constellation deployment capabilities. VLEO SAR satellites possess significant advantages, including the potential for higher-resolution imagery and lower-cost payload designs, positioning them for extensive application prospects in fields such as space-based military reconnaissance, natural resource surveying, and natural disaster monitoring. Full article

Wet-snow avalanches constitute a major geomorphic hazard in southeastern Tibet, where warm, humid climatic conditions and a steep, high-relief terrain generate failure mechanisms that are distinct from those in cold, dry snow environments. This study investigates the snowpack conditions underlying avalanche initiation in this region by integrating UAV-based multi-sensor surveys with field validation. Ground-penetrating radar (GPR), infrared thermography, and optical imaging were employed to characterize snow depth, stratigraphy, liquid water content (LWC), snow water equivalent (SWE), and surface temperature across an inaccessible avalanche channel. Calibration at representative wet-snow sites established an appropriate LWC inversion model and clarified the dielectric properties of avalanche-prone snow. Results revealed SWE up to 1092.98 mm and LWC exceeding 13.8%, well above the critical thresholds for wet-snow instability, alongside near-isothermal profiles and weak bonding at the snow–ground interface. Stratigraphic and UAV-based observations consistently showed poorly bonded, water-saturated snow layers with ice lenses. These findings provide new insights into the hydro-thermal controls of wet-snow avalanche release under monsoonal influence and demonstrate the value of UAV-based surveys for advancing the monitoring and early warning of snow-related hazards in high-relief mountain systems. Full article

Citrus leaf blotch virus (CLBV) is a positive-sense single-stranded RNA virus belonging to the genus Citrivirus within the family Betaflexiviridae. It infects a broad range of economically significant fruit crops, including citrus, kiwifruit, and apple. Surveys conducted in the field have documented appreciable incidence rates in several hosts, thereby emphasizing its emerging threat to global pomiculture. Comprehensive surveillance of CLBV genetic diversity is indispensable for predicting strain-specific epidemics and designing durable, broadly protective control strategies. Current surveys of CLBV diversity are still gene-fragment-centric, with whole-genome resolution remaining largely untapped. In this study, an analysis of codon usage bias analysis was performed using all available CLBV full-length genomes. The findings revealed that CLBV exhibits low codon usage bias, with natural selection, rather than mutational drift, being the primary driver. Phylogenetic analysis has been demonstrated to categorize isolates according to their host of origin rather than their geographical location. This observation suggests that host adaptation may supersede spatial structure in CLBV evolution and reinforce natural selection as the dominant force shaping its codon usage landscape. From the perspective of the codon adaptation index, Prunus avium is the host that exerts the greatest influence on the formation of its codon usage bias. The present study provides the first genome-wide portrait of CLBV codon usage bias, offering a robust framework for future investigations into its origin and evolutionary dynamics. Full article

Sweetpotato (Ipomoea batatas) is a staple crop of strategic importance in West Africa, particularly in Côte d’Ivoire. However, its productivity is increasingly under threat due to viral diseases. Given the lack of updated epidemiological data over the past three decades, a nationwide survey was conducted in September 2023 across 94 fields in 83 locations covering seven agroecological zones of the country. A total of 221 symptomatic and asymptomatic leaf samples were analyzed using PCR for DNA viruses and RT-PCR for RNA viruses. The overall viral incidence rate calculated was 65.61%, with significant regional variations (35–97.18%, p < 0.001) and notable differences in the severity of symptoms (p = 0.0095). Agroecological zone I was the most affected, while agroecological zones IV and V were the least impacted. Four viruses were identified: cucumber mosaic virus (CMV), sweet potato leaf curl virus (SPLCV), sweet potato feathery mottle virus (SPFMV), and sweet potato chlorotic stunt virus (SPCSV). No badnaviruses were found. CMV was the most common virus found in single infections (43.44%), followed by SPLCV (5.43%). SPFMV and SPCSV were only observed in mixed infections, particularly CMV/SPLCV (14.03%) and CMV/SPFMV (1.81%). Two triple infections were also detected: SPFMV/SPCSV/CMV and SPFMV/SPLCV/CMV. In total, 34 partial coat protein sequences were obtained (28 SPLCV, 4 SPFMV, 1 CMV, 1 SPCSV). Phylogenetic analysis revealed a high similarity between SPLCV isolates characterized in Côte d’Ivoire and those from Burkina Faso, Europe (Spain, Italy), and the Americas (USA, Puerto Rico) with nucleotide identity values ranging from 98% to 100%. The Côte d’Ivoire SPCSV sequence showed 97.92% nucleotide identity with European isolates, whereas SPFMV sequences exhibited greater diversity (77–89% identity) but clustered within the West African lineage. Sweetpotato viral diseases were detected mostly in mixed-cropping fields (66.85%). This work provides the first epidemiological update on sweetpotato viral diseases since 1987 and the first molecular evidence of the nationwide presence of SPLCV and SPCSV in Côte d’Ivoire. Full article

This study investigates the adoption and utilisation of hidden roof construction as an innovative alternative to traditional roofing systems in Ghana’s urban housing. Although hidden roofs offer advantages in climate adaptability, aesthetics, and cost efficiency, their adoption remains limited. Using a survey-based partial least squares structural equation modelling approach, this study identifies the factors influencing their acceptance and use. Quantitative data were collected through field surveys from residents and construction professionals within the Kumasi Metropolitan Area. A structured questionnaire was administered using purposive and convenience sampling, yielding 175 valid responses from a total of 220 distributed questionnaires (79.5% response rate). Findings indicate that hidden roof systems are valued for their climatic suitability, particularly their resistance to water leakage and reduced heat absorption, alongside their efficient drainage design. Aesthetic appeal, cultural relevance, and ease of maintenance also emerged as key determinants of positive perception and adoption. Structural analysis confirmed significant positive relationships between design concept, aesthetic and social values, sustainability, functionality, and overall acceptance. The study provides practical guidance for architects, engineers, developers, and policymakers seeking to promote sustainable, user-centred roof design in tropical urban contexts. Findings are, however, limited to Kumasi and may not fully generalise to other Ghanaian cities. Full article

Taro (Colocasia esculenta) is a socioeconomically and nutritionally important crop that is predominantly cultivated in the derived savanna and humid forest agroecosystems of Nigeria. Taro production in the country has declined since the taro leaf blight (TLB) outbreak caused by Phytophthora colocasiae Raciborski. This study conducted field surveys during the 2021–2022 production season to assess the status of taro diseases, as well as a structured questionnaire to capture farmers’ management practices and the socio-economic determinants of taro cultivation across seven major taro-producing states in Nigeria. Data was collected from 63 randomly selected farmers across 53 farms, and 449 corms were sampled from farms and markets to assess corm-borne diseases. Sixty-three percent of farmers identified biotic constraints as the major production challenge, with TLB recognized as the most significant threat. Virus-symptomatic plants were not observed in the farmers’ fields, but the occurrence of Dasheen mosaic virus (or Potyvirus dasheenis) (DsMV, genus Potyvirus) was detected among the plants regenerated from corms collected from farms and markets. The widespread occurrence of TLB and DsMV suggests that these two pathogens pose a serious threat to taro production and that there is a risk of further spread through the continuous recycling of self-sourced planting materials across seasons. Full article

The Xishan–Yongding River cultural belt is a key component of the three major cultural belts of Beijing and its water heritage; as a representative of the intensive distribution of semi-arid climate, analyzing its spatial and temporal distribution characteristics is crucial for the development of systematic conservation strategies. This study is based on a dataset developed from field surveys and historical documentation and has been spatially analyzed using visual analytical methods and using a Geographic Information System (GIS). In this study, kernel density estimation was used to identify areas of high density, standard elliptic deviation was used to assess the distribution of water heritage sites over time, and the mean nearest neighbor index was used to determine the spatial clustering pattern of these sites. Regarding type and quantity, water heritage in the cultural belt is diverse, with non-water heritage sites, such as temples and inscriptions, being the most prevalent. In terms of temporal distribution, water heritage spans a long period, with the largest number dating to the Qing Dynasty. The centers of distribution across different periods exhibit a trend from south to north and from mountainous regions to plains, exhibiting a gradual concentration. Spatially, water heritage within the cultural belt follows a “multi-core, contiguous distribution” pattern, with three high-density zones, two medium-density zones, and six low-density zones. The distribution of water heritage is influenced by a combination of natural factors, such as river systems, settlements, elevation, and slope, alongside human factors, including historical culture and the political environment. The findings of this research offer a detailed analysis of the regional characteristics and underlying mechanisms of the temporal and spatial distribution of water heritage within the Xishan–Yongding River cultural belt. Full article