Digital technologies for behavioral change in sustainability domains: a systematic mapping review

Sustainability research has emerged as an interdisciplinary area of knowledge about how to achieve sustainable development, while political actions toward the goal are still in their infancy. A sustainable world is mirrored by a healthy environment in which humans can live without jeopardizing the survival of future generations. The main aim of this contribution was to carry out a systematic mapping (SM) of the applications of digital technologies in promoting environmental sustainability. From a rigorous search of different databases, a set of more than 1000 studies was initially retrieved and then, following screening criteria based on the ROSES (RepOrting standards for Systematic Evidence Syntheses) procedure, a total of N = 37 studies that met the eligibility criteria were selected. The studies were coded according to different descriptive variables, such as digital technology used for the intervention, type of sustainable behavior promoted, research design, and population for whom the intervention was applied. Results showed the emergence of three main clusters of Digital Technologies (i.e., virtual/immersive/augmented reality, gamification, and power-metering systems) and two main Sustainable Behaviors (SBs) (i.e., energy and water-saving, and pollution reduction). The need for a clearer knowledge of which digital interventions work and the reasons why they work (or do not work) does not emerge from the outcomes of this set of studies. Future studies on digital interventions should better detail intervention design characteristics, alongside the reasons underlying design choices, both behaviourally and technologically. This should increase the likelihood of the successful adoption of digital interventions promoting behavioral changes in a more sustainable direction

Beliefs about technological and contextual features drive biofuels' social acceptance

To make the transition towards renewable and sustainable energy possible, there is a need to make new relevant technologies, including biofuels more acceptable and accepted. To promote biofuels acceptance and thus adoption means to improve both their perceived technological features and the surrounding context supporting their adoption, as well as some social-psychological features of the target adopters. Achieving the ultimate goal of biofuels adoption thus requires a complex and holistic approach to foster this new energy technology's acceptability and acceptance considering several biofuels features. For this aim, the integrated Sustainable Energy Technology Adoption Model (i-SETA) was developed and tested with newly piloted tools to measure the relevant biofuels' beliefs profile. A Path Analysis tested the relationship between the investigated variables. Results revealed the importance of beliefs belonging to each one of the different considered domains (technological, contextual, and personal variables). Several of them had a direct impact on the cognitive and affective biofuels evaluation, and subsequently on biofuels acceptability and acceptance, for European Union both laypeople and expert stakeholders (total sample of 1017 participants). The main results thus revealed that very specific beliefs, across all the three beliefs classes, can be identified as either barriers or drivers with respect to the aim of boosting biofuels' acceptability and acceptance. Each one of these specific beliefs could thus be properly targeted in the audiences to cope with the barriers and capitalize on the drivers

Which factors affect the Italian consumer's intention to insect-eating? An application of an integrated attitude-intention-eating model

This research explored the role of key socio-psychological dimensions on individuals' intention to eat insectbased foods (IEIBF). In particular, the theoretical framework included biospheric values and social norms, whose impact on pro-environmental choices has been largely evidenced, but also those factors related to animal welfare and neophobia/neophilia attitudes. An online survey was carried out in different Italian regions intercepting 1402 individuals to verify the relationships predicted by our proposed model, i.e. the Integrated Sustainable Neophilic Insect-based Eating Model (ISNIEM), for predicting IEIBF. Participants completed a survey containing measures of IEIBF, biospheric values, general pro-environmental beliefs, attitude toward sustainability, food neophilia, concern for insect welfare, and social norms (both injunctive and descriptive). Structural Equation Modelling (SEM) technique was used for testing the ISNIEM. The main findings show that individuals having higher concern about environmental and ethical sustainability are more open to eating insects, especially if the latter are treated ethically. Overall, these results suggest that a typical consumer of insect foods is likely to be driven to their consumption from one side by curiosity (related to the neophilia dimension), and from the other side either by the sense of responsibility towards the environment or by the concern for ethical issues (i.e., animal welfare). The integrated attitude-food-intention model used to explore intention to eat insect foods (IEIBF) with a visual scheme represents an innovative approach in the study of consumer behaviour

Promoting a sustainable behavioral shift in commuting choices: the role of previous intention and “personalized travel plan” feedback

According to the European Environment Agency (European Environmental Agency, EEA, 2018), road transport is responsible for 72% of all transport-related greenhouse gas emissions in the European Union (EU), which accounts for 25% of total energy-related emissions (Eurostat, 2018). Thus, it is crucial to identify drivers and barriers to more sustainable transport behaviors. In this regard, the Norm Activation Model and Theory of Planned Behavior have often been used as conceptual frameworks for predicting such behaviors. The present study aimed to analyze the differential impact of both socio-psychological factors and persuasive messages sent through a Personalized Travel Plan (PTP) on Sustainable Transport Choices (STC). To reach this aim we administered a survey two times (T1: Oct./Dec. 2020; T2: March/May 2021) to 398 car users. Measures of constructs included in the Norm Activation Model and the Theory of Planned Behavior, such as behavioral intention, attitude, perceived behavioral control, beliefs, and personal and social norms, were detected. Participants were then exposed to a PTP built on feedback information regarding kilocalories, CO2 emissions, cost, and time savings when using sustainable transport compared to driving a car. Structural Equation Modeling (SEM) analysis shows that intention to use sustainable transport in T1 is on one side directly predicted by personal norm, perceived behavioral control, and attitude, and on the other side emerged as the main predictor of sustainable travel choices in T2, together with kcal spent, whereas time was the major barrier. Implications and future developments are discussed in the light of the conceptual framework

ODRL Policy Modelling and Compliance Checking

This paper addresses the problem of constructing a policy pipeline that enables compliance checking of business processes against regulatory obligations. Towards this end, we propose an Open Digital Rights Language (ODRL) profile that can be used to capture the semantics of both business policies in the form of sets of required permissions and regulatory requirements in the form of deontic concepts, and present their translation into Answer Set Programming (via the Institutional Action Language (InstAL)) for compliance checking purposes. The result of the compliance checking is either a positive compliance result or an explanation pertaining to the aspects of the policy that are causing the noncompliance. The pipeline is illustrated using two (key) fragments of the General Data Protect Regulation, namely Articles 6 (Lawfulness of processing) and Articles 46 (Transfers subject to appropriate safeguards) and industrially-relevant use cases that involve the specification of sets of permissions that are needed to execute business processes. The core contributions of this paper are the ODRL profile, which is capable of modelling regulatory obligations and business policies, the exercise of modelling elements of GDPR in this semantic formalism, and the operationalisation of the model to demonstrate its capability to support personal data processing compliance checking, and a basis for explaining why the request is deemed compliant or not

Social distance during the covid-19 pandemic reflects perceived rather than actual risk

Interpersonal space (IPS) is the area surrounding our own bodies in which we interact comfortably with other individuals. During the COVID-19 pandemic, keeping larger IPS than usual, along with wearing a face mask, is one of the most effective measures to slow down the COVID-19 outbreak. Here, we explore the contribution of actual and perceived risk of contagion and anxiety levels in regulating our preferred social distance from other people during the first wave of the COVID-19 pandemic in Italy. In this study, 1293 individuals from six Italian regions with different levels of actual risk of infection participated in an online survey assessing their perceived risk to be infected, level of anxiety and IPS. Two tasks were adopted as measures of interpersonal distance: the Interpersonal Visual Analogue Scale and a questionnaire evaluating interpersonal distance with and without face mask. The results showed that the IPS regulation was affected by how people subjectively perceived COVID-19 risk and the related level of anxiety, not by actual objective risk. This clarifies that the role of threat in prompting avoidant behaviors expressed in increased IPS does not merely reflect environmental events but rather how they are subjectively experienced and represented

Interleukin-2/interferon-α2a/13-retinoic acid-based chemoimmunotherapy in advanced renal cell carcinoma: results of a prospectively randomised trial of the German Cooperative Renal Carcinoma Chemoimmunotherapy Group (DGCIN)

We performed a prospectively randomised clinical trial to compare the efficacy of four subcutaneous interleukin-2-(sc-IL-2) and sc interferon-α2a (sc-IFN-α2a)-based outpatient regimens in 379 patients with progressive metastatic renal cell carcinoma. Patients with lung metastases, an erythrocyte sedimentation rate ⩽70 mm h−1 and neutrophil counts ⩽6000 μl−1 (group I) were randomised to arm A: sc-IL-2, sc-IFN-α2a, peroral 13-cis-retinoic acid (po-13cRA) (n=78), or arm B: arm A plus inhaled-IL-2 (n=65). All others (group II) were randomised to arm C: arm A plus intravenous 5-fluorouracil (iv-5-FU) (n=116), or arm D: arm A plus po-Capecitabine (n=120). Median overall survival (OS) was 22 months (arm A; 3-year OS: 29.7%) and 18 months (arm B; 3-year OS: 29.2%) in group I, and 18 months (arm C; 3-year OS: 25.7%) and 16 months (arm D; 3-year OS: 32.6%) in group II. There were no statistically significant differences in OS, progression-free survival, and objective response between arms A and B, and between arms C and D, respectively. Given the known therapeutic efficacy of sc-IL-2/sc-INF-α2a/po-13cRA-based outpatient chemoimmunotherapies, our results did not establish survival advantages in favour of po-Capecitabine vs iv-5-FU, and in favour of short-term inhaled-IL-2 in patients with advanced renal cell carcinoma receiving systemic cytokines

Autoantibodies neutralizing type I IFNs underlie West Nile virus encephalitis in ∼40% of patients

Mosquito-borne West Nile virus (WNV) infection is benign in most individuals but can cause encephalitis in <1% of infected individuals. We show that ∼35% of patients hospitalized for WNV disease (WNVD) in six independent cohorts from the EU and USA carry auto-Abs neutralizing IFN-α and/or -ω. The prevalence of these antibodies is highest in patients with encephalitis (∼40%), and that in individuals with silent WNV infection is as low as that in the general population. The odds ratios for WNVD in individuals with these auto-Abs relative to those without them in the general population range from 19.0 (95% CI 15.0-24.0, P value <10-15) for auto-Abs neutralizing only 100 pg/ml IFN-α and/or IFN-ω to 127.4 (CI 87.1-186.4, P value <10-15) for auto-Abs neutralizing both IFN-α and IFN-ω at a concentration of 10 ng/ml. These antibodies block the protective effect of IFN-α in Vero cells infected with WNV in vitro. Auto-Abs neutralizing IFN-α and/or IFN-ω underlie ∼40% of cases of WNV encephalitis

Conserved and variable correlated mutations in the plant MADS protein network

<p>Abstract</p> <p>Background</p> <p>Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. However, not much is known about the structure of these proteins or their complexes, whereas such knowledge would be valuable for a better understanding of their function. Here, we analyze those proteins and the complexes they form using a correlated mutation approach in combination with available structural, bioinformatics and experimental data.</p> <p>Results</p> <p>Correlated mutations are affected by several types of noise, which is difficult to disentangle from the real signal. In our analysis of the MADS domain proteins, we apply for the first time a correlated mutation analysis to a family of interacting proteins. This provides a unique way to investigate the amount of signal that is present in correlated mutations because it allows direct comparison of mutations in various family members and assessing their conservation. We show that correlated mutations in general are conserved within the various family members, and if not, the variability at the respective positions is less in the proteins in which the correlated mutation does not occur. Also, intermolecular correlated mutation signals for interacting pairs of proteins display clear overlap with other bioinformatics data, which is not the case for non-interacting protein pairs, an observation which validates the intermolecular correlated mutations. Having validated the correlated mutation results, we apply them to infer the structural organization of the MADS domain proteins.</p> <p>Conclusion</p> <p>Our analysis enables understanding of the structural organization of the MADS domain proteins, including support for predicted helices based on correlated mutation patterns, and evidence for a specific interaction site in those proteins.</p