Abstract
Worldwide organic food consumption has registered a consistent rise in recent years. Despite the relevant body of literature on the topic, it is necessary to further understand the antecedents of purchase intention. This article aims to identify the factors that influence the consumer's intention to purchase organic food. It extends the theory of planned behavior model by including environmental concerns, health concerns, and perceived quality as determinants of attitude toward organic food products. Additionally, it considers the effect of product availability on consumers' perceived behavioral control. This article includes a quantitative study that was conducted in Portugal in 2020 (n = 206). Structural equation modeling was used to test the proposed set of research hypotheses. In line with extant literature, this study confirmed that attitude toward organic food is the main determinant of purchase intention. Additionally, it demonstrates that health concerns and perceived quality have a significant impact on attitude toward organic food. The impact of environmental concerns on attitude was not confirmed by this study. Based on these findings, it is recommended that managers stress health benefits and quality of organic food in order to foster positive attitudes and consequently leverage purchase intention.

Abstract
The fifth generation of mobile communications networks (5G) emerges with the potential to customize the technical parameters of the same physical infrastructure for each application, service, or user, which can compromise the fundamentals that made the Internet the leading platform for dissemi-nating information and a transnational instrument of collaboration of indi-viduals and institutions. In this scenario, the present study intends to ana-lyze this new technological standard, its influence on the informational flow of the Internet, and evaluate the role of information policy for the gover-nance of the multiple interests that permeate the digital ecosystem.

Abstract
The increasing use of geospatial information from satellites and unmanned aerial vehicles (UAVs) has been contributing to significant growth in the availability of instruments and methodologies for data acquisition and analysis. For better management of vineyards (and most crops), it is crucial to access the spatial-temporal variability. This knowledge throughout the vegetative cycle of any crop is crucial for more efficient management, but in the specific case of viticulture, this knowledge is even more relevant. Some research studies have been carried out in recent years, exploiting the advantage of satellite and UAV data, used individually or in combination, for crop management purposes. However, only a few studies explore the multi-temporal use of these two types of data, isolated or synergistically. This research aims to clearly identify the most suitable data and strategies to be adopted in specific stages of the vineyard phenological cycle. Sentinel-2 data from two vineyard plots, located in the Douro Demarcated Region (Portugal), are compared with UAV multispectral data under three distinct conditions: considering the whole vineyard plot; considering only the grapevine canopy; and considering inter-row areas (excluding all grapevine vegetation). The results show that data from both platforms are able to describe the vineyards' variability throughout the vegetative growth but at different levels of detail. Sentinel-2 data can be used to map vineyard soil variability, whilst the higher spatial resolution of UAV-based data allows diverse types of applications. In conclusion, it should be noted that, depending on the intended use, each type of data, individually, is capable of providing important information for vineyard management.

Abstract
This paper describes a new development within the conceptual framework BAYSE (Bayesian State Estimation), which enables the full integration of the SCADA (Supervisory Control and Data Acquisition) data with PMU (phasor measurement units) data. It is based on Bayesian inference principles and extends the concept of the prior distributions to accommodate a broad set of past state conditions, under a sliding window approach. By choosing an appropriate window length, the method enhances accuracy under stationary conditions, with a reduced impact under system changes. The work also submits a rectangular coordinates transformation procedure, based on the Jacobian method, to consistently integrate polar coordinates estimations with the PMU linear model (in rectangular coordinates). The paper presents the new approach in proof-of concept mode over a didactic test-bed, using real PMU time series, to emphasize the enhanced accuracy and good asymptotic properties.

Abstract
This paper addresses an integrated framework for the dynamic capacity withholding assessment of an independent system operator that determines the mid-term maintenance scheduling of generation companies and day-ahead scheduling of wholesale market participants. The main contribution of this research is that two dynamic capacity-withholding indices are proposed for mid-term and day-ahead scheduling of generation companies that estimate the dynamic capacity withholding opportunities of generation units in an ex-ante manner. The proposed framework is another contribution of this research that uses a four-stage optimization process that the system operator can detect and prevent the formation of withholding groups. The optimal maintenance scheduling from the generation companies viewpoint is assessed in the first-stage problem that considers different mid-term withholding opportunities. The optimal mid-term maintenance scheduling is carried out in the second-stage problem that recognizes and rejects the dynamic capacity withholding of generation companies. The optimal scheduling of day-ahead generation companies considering their dynamic capacity withholding is the third contribution of this paper that optimizes the scheduling of generation units for day-ahead horizon considering responsive loads. The proposed method is applied to 30-bus, 57-bus and 118-bus IEEE test systems. A full competition algorithm is also carried out to evaluate the competition states of generation companies. The proposed algorithm detected that the dynamic capacity withholding might lead to increase of nodal price by about 279.22%, 764.43%, and 851.2% for 30-bus, 57-bus, and 118-bus IEEE test systems with respect to the non-capacity withholding conditions, respectively.

Abstract
Fire is a traditional method used for the elimination of residual materials from agricultural and forestry activities, but its improper and negligent use increases the risk to cause significant social, economic, and environmental impacts. Translating the nature and magnitude of the risk, a mental model approach has been used for a deeper understanding of what can be done to reduce future socioeconomic and environmental impacts. Considering the rural fire risk context, in this study we applied the mental model approach to (1) explore the different perspectives of experts on rural fire risks, focusing on the burning problem, and (2) systematize the aggregated knowledge of experts on the subject. Semi-structured interviews that included real-time interactions with the proposed mental model on the MURAL platform were remotely conducted with twenty-eight experts with in-depth involvement and experience in fire and forest management in Portugal, including actors from industry, academics, third sector, and public entities. The experts' contributions were periodically validated by the research team and included in the reference mental model to translate the aggregated knowledge of the expert community. The data collected was transcribed, coded, and analyzed following a thematic analysis approach with NVivo software support. After nine iterations, the expert's mental model was concluded encompassing the burning motivators, alternative solutions, associated risks before and during the burning, underlying causes, natural elements and factors, and impacts. Overall, the study provides an in-depth and holistic understanding of rural fire risks, focusing on burning, which is essential for identifying incorrect beliefs and existing risk factors that are often neglected. The participatory and dynamic process of actors' knowledge systematization on burning risks through a mental model allowed the identification of divergent perspectives between expert groups, especially concerning the effectiveness of the current legislation on the use of fire, indicating the need to improve the dialogue between experts. Moreover, the study shows how risk communication campaigns do not replace technical monitoring closer to the population and recognize the importance and need of sensitization and communication actions to disseminate the use of available alternatives to overcome traditional habits of rural communities. Still, it indicates that successful alternative solutions of burning may be achieved with strong local and sectoral involvement. Finally, this research provides a baseline to help decision-makers and stakeholders identify the most relevant variables about rural fire risks to build effective risk communications strategies and mitigate social and environmental impacts in the future.