Search Results (66)

In the last 20 years, NRTK GNSS CORS networks have been designed, developed, and employed in Sicily (Italy) for research purposes. Following a comprehensive description of the CORS networks in this region, this study aims to compare results obtained from multiple reference points with known coordinates. The analysis will not only account for the various CORS networks to which these points belong but also examine the different correction streams applied in NRTK surveys. The assumption of a normal distribution, which is often assumed for the positioning errors, is generally confirmed by applying the areal stream corrections (FKP, MAX, iMAX), but still, a multimodal distribution is evident when punctual corrections (Nearest and VRS) are applied. The representation of the results in a GIS environment allows for showing the different patterns for some differential correction streams. A statistical approach allowed confirming the trends of the different distribution frequencies of the residuals of the coordinates and quantifying separately the correlation with parameters involved in the analysis. The correlation retrieved is predominantly weak and very weak for all CORS, except for one of those analyzed, for which the correlation is moderate. The correlation became strong for the same CORS, if all parameters are included, for both planimetric and plano-altimetric components (r = 0.6 and r = 0.7, respectively). Full article

The classification of bean landraces based on their coloration is of particular interest, as the color of these plants is associated with the nutritional components present in their seeds. In this paper, the authors propose a procedure to identify the colors of heterogeneous color bean landraces based on the information from their digital images. The proposed methodology employs a three-dimensional histogram representation of the estimated color, expressed in the CIE L*a*b* color space, with an unsupervised learning method called the Gaussian Mixture Model. This approach facilitates the acquisition of representative information for the colors of a bean landrace, represented as points in the CIE L*a*b* color space. Furthermore, the K-$nn$ method can be trained with these punctual representations to identify colors, yielding satisfactory results on landraces with homogeneous and heterogeneous seeds. Full article

Limited access to education in rural areas of Senegal is a structural barrier to human development and equal opportunities. The Bicycles for Education project, promoted by the Utopia Foundation—Bicycles Without Borders (BSF), aims to improve the educational participation of young people aged 12 to 21 by providing bicycles to facilitate their travel to school. In this study, the GRITS research group from the University of Barcelona externally evaluates the impact of the project on improving access to education, reducing gender inequalities, and the associated socioeconomic as well as community benefits. A qualitative approach based on individual interviews (n = 23), focus groups (n = 6) and group interviews (n = 8) was used, with a total of 80 participants, including students, families, teachers, project coordinators, and institutional managers. The analysis was carried out through thematic coding and content analysis, identifying four main axes: educational impact, gender equity, economic effects, and community transformation. The results show that the provision of bicycles throughout the school year led to increased school attendance and punctuality, improvements in academic performance, a reduction in social inequalities, gender inequalities in access to education, and a decrease in household costs associated with transport and food. In addition, there has been a cultural transformation in the perception of cycling as a viable means of mobility and a change in those communities where the project has been running for more than a decade. Full article

With the rapid expansion of the aviation industry, traditional static scheduling methods have become inadequate to meet the increasingly complex demands of efficient airport operations. To enhance the operational efficiency of multi-runway airports, this paper introduced a two-stage dynamic departure scheduling method based on continuous Markov chains. The pushback rate control strategy was extended to multi-runway scenarios to identify the optimal taxiway queue threshold in stage I. In stage II, the pushback rate control strategy with a known queue threshold was introduced into a multi-objective optimization model, aiming to minimize flight delays and operational costs including pushback waiting times, taxi fuel consumption, and environmental impact. Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. Results indicate that the proposed method reduced the average taxiway queue time by 55.58%, with delay reductions of up to 73.06%, offering significant cost savings and environmental benefits while improving flight punctuality. This innovative approach highlights the potential for optimizing airport resource scheduling in complex and dynamic environments. Full article

Listeria monocytogenes is an important foodborne pathogen, markedly persistent even in harsh environments and responsible for high hospitalization and mortality rates. The aim of the present study was to detect the strains circulating in Sicily over a five-year period and characterize their antimicrobial resistance profiles. The key element of this study was the sharing of data among various entities involved in food control and clinical surveillance of listeriosis in order to develop an integrated approach for this pathogen. A total of 128 isolates were analyzed, including 87 food-source strains and 41 clinical specimens. Whole-genome sequencing (WGS) was performed for sequence type (ST) and clonal complex (CC) identification through multilocus sequence typing (MLST) analysis. Antimicrobial resistance was assessed using the Kirby–Bauer method. The majority of strains belonged to serotype IVb (34/41 and 53/87 of clinical and food-source isolates, respectively) and were subtyped as CC2-ST2 (28/34 and 41/53 of clinical and food-source isolates respectively). Most of the isolates were susceptible to the main antimicrobials recommended for treatment of listeriosis. Resistance (R) and intermediate resistance (I) percentages worthy of attention were found against oxacillin (R: 85.9%) and clindamycin (I: 34.6%) in the food-source isolates and trimethoprim/sulfamethoxazole (R: 29.23%) in the clinical isolates. Also, 7.7% of the food-source isolates were multidrug resistant. Our results highlight how the punctual comparison between food and clinical strains is an essential tool for effectively tracking and preventing foodborne outbreaks. Full article

The use of low-cost sensors has dramatically increased in recent years in all engineering sectors. In the buildings and automotive field, low-cost sensors open very interesting perspectives, because they allow one to monitor temperature and humidity distributions together with air quality in a widespread and punctual way and allow for the control of all energy parameters. The main issue remains the validation of the measurements. In this work, we propose an innovative approach to verify the measurements given by some low-cost systems built ad hoc for automotive applications. Two independent low-cost measurement systems were set to measure Particulate Air Matter (PM) concentration, TVOC concentration, CO₂ concentration, formaldehyde concentration, air temperature, relative humidity, pressure, air flow velocity, and GPS position. These systems were calibrated for PM concentration measurement by comparison with standard and certified sensors used by the regional authority of the Emilia-Romagna region (ARPAE, Italy) for characterizing air quality. The duration of the analysis, three days, is not representative of the diverse environmental conditions that occur across different seasons. However, the innovation of this approach lies in both the in-field comparison of low-cost and high-quality sensors and the use of proper conversion approaches for mass concentration measurements. A quantitative analysis of the sensors’ performance is given, with a focus on the effects of time granularity, relative humidity, mass conversion from particle counts, and size detection response. The results show that the low-cost sensors’ measurements of air temperature, relative humidity, and particle number concentration are in good agreement with high-quality sensors’ measurements, with a strong impact of relative humidity on performance indicators. Overall, good quality and consistency of the data among the sensors were achieved. Full article

In the realm of hydrological engineering, integrating extensive geospatial raster data from remote sensing (Big Data) with sparse field measurements offers a promising approach to improve prediction accuracy in groundwater studies. In this study, we integrated multisource data by applying the LMC to model the spatial relationships of variables and then utilized block support regularization with collocated block cokriging (CBCK) to enhance our predictions. A critical engineering challenge addressed in this study is support homogenization, where we adjusted punctual variances to block variances and ensure consistency in spatial predictions. Our case study focused on mapping groundwater table depth to improve water management and planning in a mixed land use area in Southeast Brazil that is occupied by sugarcane crops, silviculture (Eucalyptus), regenerating fields, and natural vegetation. We utilized the 90 m resolution TanDEM-X digital surface model and STEEP (Seasonal Tropical Ecosystem Energy Partitioning) data with a 500 m resolution to support the spatial interpolation of groundwater table depth measurements collected from 56 locations during the hydrological year 2015–16. Ordinary block kriging (OBK) and CBCK methods were employed. The CBCK method provided more reliable and accurate spatial predictions of groundwater depth levels (RMSE = 0.49 m), outperforming the OBK method (RMSE = 2.89 m). An OBK-based map concentrated deeper measurements near their wells and gave shallow depths for most of the points during estimation. The CBCK-based map shows more deeper predicted points due to its relationship with the covariates. Using covariates improved the groundwater table depth mapping by detecting the interconnection of varied land uses, supporting the water management for agronomic planning connected with ecosystem sustainability. Full article

Research on urban transport and mobility through everyday practices has generated new theoretical and methodological approaches to achieve more sustainable urban morphologies. This paper focuses on the characterization of the process of urban (re)qualification through the binomial of public space–public transport, based on the analysis of Trambesòs tramway in Barcelona, from 2004 to the present. This methodology consisted of an exploratory morphological analysis that identified patterns derived from punctual interventions, articulation axes, and saturation pieces in the urban fabric. The results revealed three main morphological patterns: the configuration of a particular character in each public space intervention associated with the tramway, the morphological improvement and dynamization of the urban fabric, and the transformation of the city’s image through the standardization of accessibility conditions, a key social sustainability indicator. In the discussion, the results are triangulated with the concepts of urban morphology and social processes and compared with quantitative studies, which can serve as a foundation for further in-depth research. In conclusion, the tramway has facilitated a transition from urban discontinuity and segregation to continuity and cohesion, highlighting the impact of the public space–public transport binomial on more sustainable urban morphologies. This contributes to how urban morphological analysis provides new approaches to understanding public transport as an extension of public space and support for urban habitability. Full article

The functioning of modern urban environments relies heavily on the public transport system. Given spatial, economic, and sustainability criteria, public transport in larger urban areas is unrivaled. The system’s role depends on the quality of service it offers. Achieving the desired service quality requires a design that meets transport demands. This paper uses a data-driven approach to address headway deviations in public transport lines and explores ways to improve regularity during the design phase. Headway is a critical dynamic element for transport organization and passenger quality. Deviations between planned and actual headways represent disturbances. On lines with headways under 15 min, passengers typically do not consult schedules, making punctuality less crucial. Reduced headway regularity affects the average travel time, travel time uncertainty, and passenger comfort. Ideally, the public transport system operates with regular headways. However, disturbances can spread and affect subsequent departures, leading to vehicle bunching. While previous research focused on single primary disturbances, this study, with the help of AI (reinforcement learning), examines multiple primary disturbances in the cities of Belgrade, Novi Sad, and Niš. The goal is to model the cumulative impact of these disturbances on vehicle movement. By ranking parameter influences and using the automatic optimization of static line elements, this research aims to improve headway regularity and increase system resilience to disturbances. The results of this research could also be useful in developing adaptive public transport management systems that leverage AI and IoT technologies to continuously optimize headway regularity in response to real-time data, ultimately enhancing service quality and passenger satisfaction. Full article

The phenomenon of passenger satisfaction is an important issue for public transport services and transport companies. Clarifying the relationship between influencing attributes and passenger satisfaction significantly improves service satisfaction. This study examines passenger satisfaction with intercity buses and, in particular, the role of digital information channels (websites and mobile apps) in promoting sustainable travel choices on the Madrid–Bilbao route. This study analyzed data from 459 passengers to identify the key factors influencing the bus choice for intercity bus travel. Punctuality, safety, and ticket price are the most important determinants. We use a combined structural equation modeling (SEM) and artificial neural network (ANN) approach to capture the intricate relationships between service attributes and information channels. The results show that information channels, travel experience, and ticket prices significantly impact passenger satisfaction, which bus operators should improve. Also, inserting the SEM result as input for the ANN showed that ticket price is the most significant predictor of satisfaction, followed by information channels (84%) and travel experience (65%). This approach provides valuable insights for improving the passenger experience. This study emphasizes integrating digital transformation strategies into public transport systems to promote sustainable mobility goals. Full article

The world demands suitable design solutions to transition toward a sustainable production system. The concept of sustainability evolves with technology’s ability to understand and replicate nature’s logic. There is a growing need to move beyond punctual solutions towards more intricate and multi-stakeholder considerations, including preemptive assessments of impacts. This article discusses the outcomes of cross-disciplinary material experimentation at Saperi&Co Center, Sapienza University of Rome. This research focuses on enhancing ceramic surfaces through circular economy practices, making them receptive to microorganism colonization—known as bioreceptivity. Through an iterative and repetitive approach, inspired by Research Through Design and material experimentation, several experiments were carried out to study how the innovative use of organic waste in clay-based mixtures can promote bioreceptivity and the design of green surfaces for urban regeneration. The results advance our knowledge on the multiple parameters the designer must consider to transform inert surfaces such as ceramics into “ecological augmentation” devices. The article also aims to raise awareness of bioreceptivity as a practice to educate communities about a symbiotic relationship with nature, promote local economic development and circular production, and prompt reflection on cultural aspects arising from contemporary scientific and technological advancements in line with Responsible Research and Innovation (RRI) principles. Full article

Even though X-ray fluorescence (XRF) is strictly an atomic method, this technique has been developed mostly at research centers for nuclear physics. One of its most valuable variations is the mapping mode that allows it to shift XRF from a punctual to an image technique. Macro X-ray Fluorescence (MA-XRF) is a widespread analytical technique applied in cultural heritage for characterizing the elemental composition of pigments with a non-destructive, rapid and green approach. When dealing with cultural heritage materials, the sustainability of the applied techniques is directly linked to the limited impact on the work of art. MA-XRF can reveal hidden sub-surface layers or restorations, but, nonetheless, it is hardly adopted for estimating the thickness of layers without resorting to complex Monte Carlo simulations or without combining information from other techniques. Exploiting the recurrent presence of lead white under pictorial layers in historical artworks, we perform a calibration on stand-alone layers produced ad hoc for the relative absorption of Pb L fluorescence lines, and then, their ratio is successfully used to estimate the thickness of azurite and ultramarine blue layers over lead white. The final result is rendered as a heatmap, easy to present to non-technical personnel frequently involved in the cultural heritage field. The new proposed procedure for calculating layer thickness extends the concept of non-invasive applications, paving the way to the possibility of performing stratigraphy without sampling. Full article

This paper presents the Vertidrome Airside Level of Service (VALoS) framework, a novel performance metric designed to evaluate airside traffic flow operations at vertidromes in the context of Urban Air Mobility (UAM). As the UAM industry rapidly evolves, the need for a comprehensive evaluation framework becomes increasingly important. The VALoS framework provides a performance-based approach to evaluating vertidrome traffic flow performance, considering metrics like average passenger delay, air taxi in-flight delay, and vertidrome punctuality. Unlike existing Level of Service approaches, the VALoS framework unifies the requirements of various stakeholders, the passenger, the air taxi operator, and the vertidrome operator each with their own performance metric and target. It provides a multi-faceted approach covering airside air and ground traffic flows, arrivals and departures, and performance changes during strategic planning and tactical execution phases. The VALoS is evaluated at 15-min intervals while considering changing stakeholder performance targets and operational uncertainties. For the reference use case, the study demonstrates the significant impact of short-term disruptions, while stochastic deviations can be neglected. Higher traffic volumes due to changing demand/capacity ratios result in higher VALoS variability. The VALoS framework, together with a fast-time simulation, provides a versatile method for exploring future vertidrome traffic flows and supporting strategic vertidrome airside planning and integration. This integrated approach is essential for the evolving UAM vertidrome industry; aligning the interests of different stakeholders and promoting sustainable and efficient vertidrome planning and operation. Full article

In this article, we introduces a model based on big data analysis to characterize the travel times of buses in public transportation systems. Travel time is a critical factor in evaluating the accessibility of opportunities and the overall quality of service of public transportation systems. The methodology applies data analysis to compute estimations of the travel time of public transportation buses by leveraging both open-source and private information sources. The approach is evaluated for the public transportation system in Montevideo, Uruguay using information about bus stop locations, bus routes, vehicle locations, ticket sales, and timetables. The estimated travel times from the proposed methodology are compared with the scheduled timetables, and relevant indicators are computed based on the findings. The most relevant quantitative results indicate a reasonably good level of punctuality in the public transportation system. Delays were between 10.5% and 13.9% during rush hours and between 8.5% and 13.7% during non-peak hours. Delays were similarly distributed for working days and weekends. In terms of speed, the results show that the average operational speed is close to 18 km/h, with short local lines exhibiting greater variability in their speed. Full article

Several studies highlight the risks related to the growing water crisis, worsened by the effects of pollution, which increasingly make water sources non-potable. The current water-sensitive urban design (WSUD) approach improves resource efficiency and implements urban livability by combining natural water flows with all the scales of the urban landscape. The logistic and operational management of water disposal/treatment and distribution requires performing service design according to cities’ physical and morphological features, starting from their architectural and landscape characteristics. This paper aims to prove that different landscapes can offer different inspirations and possibilities to imagine a WSUD-coherent system, fulfilling the integration requirements with the urban system. For this purpose, three case studies, differing by dimension, morphology, and urban typology, are analyzed, experimenting with circular water usage with no resource waste. This research proposes concrete actions such as conservation, restoration or addition of permeable surfaces, the installation of new accumulation and treatment systems, and the use of water-saving devices. Starting from redesigning the water system, they can also include punctual redevelopment interventions on the urban built environments and opportunities for network development with public administrations, private businesses, third-sector organizations, and end users. This experimentation has led to water savings of up to 80% of the current consumption scenario. Full article