Mapping Riparian Habitats of Natura 2000 Network (91E0*, 3240) at Individual Tree Level Using UAV Multi-Temporal and Multi-Spectral Data

Riparian habitats provide a series of ecological services vital for the balance of the environment, and are niches and resources for a wide variety of species. Monitoring riparian environments at the intra-habitat level is crucial for assessing and preserving their conservation status, although it is challenging due to their landscape complexity. Unmanned aerial vehicles (UAV) and multi-spectral optical sensors can be used for very high resolution (VHR) monitoring in terms of spectral, spatial, and temporal resolutions. In this contribution, the vegetation species of the riparian habitat (91E0*, 3240 of Natura 2000 network) of North-West Italy were mapped at individual tree (ITD) level using machine learning and a multi-temporal phenology-based approach. Three UAV flights were conducted at the phenological-relevant time of the year (epochs). The data were analyzed using a structure from motion (SfM) approach. The resulting orthomosaics were segmented and classified using a random forest (RF) algorithm. The training dataset was composed of field-collected data, and was oversampled to reduce the effects of unbalancing and size. Three-hundred features were computed considering spectral, textural, and geometric information. Finally, the RF model was cross-validated (leave-one-out). This model was applied to eight scenarios that differed in temporal resolution to assess the role of multi-temporality over the UAV’s VHR optical data. Results showed better performances in multi-epoch phenology-based classification than single-epochs ones, with 0.71 overall accuracy compared to 0.61. Some classes, such as Pinus sylvestris and Betula pendula, are remarkably influenced by the phenology-based multi-temporality: the F1-score increased by 0.3 points by considering three epochs instead of two

Investigating the Effects of Anger and Guilt on Unethical Behavior:A Dual-Process Approach

Although emotion has become one of the most popular research areas within organizational scholarship, few studies have considered its connection with unethical behavior. Using dual-process theory, we expand on the rationalist perspective within the field of behavioral ethics by considering the process through which two discrete emotions, anger and guilt, influence unethical behavior. Across two studies using different methodologies, we found that anger increases unethical behavior whereas guilt reduces unethical behavior. These effects were mediated by impulsive and deliberative processing. Overall, our results shed light on distinct mechanisms through which emotions can influence unethical behavior. Both theoretical and practical implications are discussed

Transapical off-pump mitral valve repair with Neochord Implantation (TOP-MINI): step-by-step guide

open10openColli, Andrea; Zucchetta, Fabio; Torregrossa, Gianluca; Manzan, Erica; Bizzotto, Eleonora; Besola, Laura; Bellu, Roberto; Sarais, Cristiano; Pittarello, Demetrio; Gerosa, GinoColli, Andrea; Zucchetta, Fabio; Torregrossa, Gianluca; Manzan, Erica; Bizzotto, Eleonora; Besola, Laura; Bellu, Roberto; Sarais, Cristiano; Pittarello, Demetrio; Gerosa, Gin

The fear of personal death and the willingness to commit to organ donation

9 pagesIn three studies, with samples from different countries (the United States and Israel) and religions (Christians and Jews), we found that individual levels of fear of death significantly predicted lower willingness to register as organ donors (Studies 1 and 2). Moreover, after being asked about their organ donation status (i.e., whether they are registered as donors), fear of death significantly increased among unregistered people. This did not occur among registered people, who had already faced the decision to become donors in the past (Study 2). Finally, providing non-registered (non-religious) people with a defense strategy to manage their fear of death increased their willingness to sign an organ donation commitment, partially by increasing their feelings of hopefulness. The implications of these findings for increasing organ donation registration are discussed.This research was supported by the Israel Science Foundation Grant 1426/20 and by the National Science Foundation (NSF) Grant 1559546

Emotional intelligence buffers the effect of physiological arousal on dishonesty

We studied the emotional processes that allow people to balance two competing desires: benefitting from dishonesty and keeping a positive self-image. We recorded physiological arousal (skin conductance and heart rate) during a computer card game in which participants could cheat and fail to report a certain card when presented on the screen to avoid losing their money. We found that higher skin conductance corresponded to lower cheating rates. Importantly, emotional intelligence regulated this effect; participants with high emotional intelligence were less affected by their physiological reactions than those with low emotional intelligence. As a result, they were more likely to profit from dishonesty. However, no interaction emerged between heart rate and emotional intelligence. We suggest that the ability to manage and control emotions can allow people to overcome the tension between doing right or wrong and license them to bend the rules

\u201cGive, but Give until It Hurts\u201d: The Modulatory Role of Trait Emotional Intelligence on the Motivation to Help

Two studies investigated the effect of trait Emotional Intelligence (trait EI) on people\u2019s moti- vation to help. In Study 1, we developed a new computer-based paradigm that tested partic- ipants\u2019 motivation to help by measuring their performance on a task in which they could gain a hypothetical amount of money to help children in need. Crucially, we manipulated partici- pants\u2019 perceived efficacy by informing them that they had been either able to save the chil- dren (positive feedback) or unable to save the children (negative feedback). We measured trait EI using the Trait Emotional Intelligence Questionnaire\u2013Short Form (TEIQue-SF) and assessed participants\u2019 affective reactions during the experiment using the PANAS-X. Results showed that high and low trait EI participants performed differently after the presen- tation of feedback on their ineffectiveness in helping others in need. Both groups showed increasing negative affective states during the experiment when the feedback was negative; however, high trait EI participants better managed their affective reactions, modulating the impact of their emotions on performance and maintaining a high level of motivation to help. In Study 2, we used a similar computerized task and tested a control situation to explore the effect of trait EI on participants\u2019 behavior when facing failure or success in a scenario unre- lated to helping others in need. No effect of feedback emerged on participants\u2019 emotional states in the second study. Taken together our results show that trait EI influences the impact of success and failure on behavior only in affect-rich situation like those in which people are asked to help others in need

Shedding light on typical species : implications for habitat monitoring

Habitat monitoring in Europe is regulated by Article 17 of the Habitats Directive, which suggests the use of typical species to assess habitat conservation status. Yet, the Directive uses the term “typical” species but does not provide a definition, either for its use in reporting or for its use in impact assessments. To address the issue, an online workshop was organized by the Italian Society for Vegetation Science (SISV) to shed light on the diversity of perspectives regarding the different concepts of typical species, and to discuss the possible implications for habitat monitoring. To this aim, we inquired 73 people with a very different degree of expertise in the field of vegetation science by means of a tailored survey composed of six questions. We analysed the data using Pearson's Chi-squared test to verify that the answers diverged from a random distribution and checked the effect of the degree of experience of the surveyees on the results. We found that most of the surveyees agreed on the use of the phytosociological method for habitat monitoring and of the diagnostic and characteristic species to evaluate the structural and functional conservation status of habitats. With this contribution, we shed light on the meaning of “typical” species in the context of habitat monitoring