Input: Claim: Using blockchain makes all supply chain operations immune to theft or fraud. [SEP] Text: The EPC can then be read from the physical product RFID or QR/Serial code tag using a smartphone with an App our via a specific EPC reader device. After SCA certificate validation the Supply chain management and traceability functionality is provided using the SCA BC addresses via transactions in a trusted and decentralized way with no further validation required. The SCM-SC is deployed in the EVM by the SC Manager which is the owner and ultimate responsible for the security and maintenance of the SC codeFootnote 15 Details on the proposed Contract code is in ANNEX 3. 4. 5 Case study - alimentary PDO use caseAs already mentioned, an example about alimentary supply chain use case was selected to better understand the requirements and correct application of the proposed solution. The selected use case was the production and transformation of certified livestock produce (bovine meat) of the “Carne Mirandesa” – a type of bovine meat that is PDO certified and only produced in the northeast region of Portugal. This PDO is already currently certified using a combination of paper certificates and products tags or stickers that are shipped with the product. From an interview with a producer and retailer 3 document samples were collected: the certificate that links the Government ID of the animal (16 ID) with the PDO ID and certificate of the brand “Mirandesa” (Geneology ID), the transformation identifier that is shipped with the bovine meat that shows the reference to the animal () and the sale point invoice that attests to the purchase of the carcass and served meals with the reference to the batch attested by the a governmental agency (). The unique identifier that is used across the supply chain is the Code (EPC) that is linked with both the and the Genealogy ID (EPC--Genealogy ID). The product certificate to be generated has then to hold these 3 fields in the X509Footnote 17 certificate request as mandatory fields to be certified together with the public key hash of the producer (supplier actor in the SCM). In summary each product will be issued a X509 certificate by the producer. This particular CA chain of trust requires three SCA certificates: one for the root CA (the Government CA), another for the intermediate CA (the PDO association CA) and finally one for the SCA producer. The summaries of the use case data and PKI certificate setup are presented in ANNEX 4 and ANNEX 5.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: A. , Duchowny, K. , Riley, A. R. ,. . . Glymour, M. M. (2022). in California by the COVID-19 Pandemic. of Preventive Medicine. doi: Didkan, K. (2021). MODIS/Indices 16-Day L3 Global 250m SIN Grid V061 [Data set]. . Diener, A. , & Mudu, P. (2021). How can vegetation protect us from air pollution? A critical review on green spaces' mitigation abilities for air-borne p8605. doi: Fan, Y. , Das, K. V. , & Chen, Q. (2011). Neighborhood green, social support, physical activity, and stress: Assessing the cumulative impact. Health & Place, 17(6), 1202-1211. doi: Hale, T. , Angrist, N. , Goldszmidt, R. , Kira, B. , Petherick, A. , Phillips, T. ,. . . Tatlow, H. (2021). A global panel database of pandemic policies (-19 Tracker). Behaviour, 5(4), 529-538. doi:10. 1038/s41562-021-01079-8 Hansmann, R. , Hug, S. -M. , & Seeland, K. (2007). Restoration and stress relief through physical activities in forests and parks. & Urban Greening, 6(4), 213-225. doi: Harden, S. R. , Schuurman, N. , Keller, P. , & Lear, S. A. (2022). Associated with Running in Metro Vancouver: A Preliminary Analysis. of 19(21). doi:10. 3390/ijerph192114328 Hofferth, S. L. (2009). Changes in American children's time - 1997 to 2003. 6(1), 26-47. doi:10. 13085/eijtur. 6. 1. 26-47 Larson, L. R. , Szczytko, R. , & Floyd, M. F. (2018). Outdoor Time, Screen Time, and Connection to Nature: Youth? Environment and Behavior, 51(8), 966-991. doi:10.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Expressing medicine side effects: assessing the effectiveness of absolute risk, relative risk, and number needed to harm, and the provision of baseline risk information. Couns. 2006;63(1–2):89–96. CrossrefPubMedWeb of Science240. . Risk communication methods in hip fracture prevention: a randomised trial in primary care. Gen Pract. 2011;61(589):e469–76. CrossrefPubMedWeb of Science241. . Does informed consent alter elderly patients’ p30. CrossrefPubMedWeb of Science242. . The representativeness heuristic: influence on nurses’ decision making. Res. 2003;16(3):201–4. CrossrefPubMedWeb of Science243. Acute coronary syndromes without chest pain, an underdiagnosed and undertreated high-risk group: insights from the global registry of acute coronary events. Chest. 2004;126(2):461–9. CrossrefPubMedWeb of Science244. Cioffi J, Markham R. Clinical decision-making by midwives: managing case complexity. J Adv Nurs. 1997;25(2):265–72. CrossrefPubMedWeb of Science245. Ferrario CG. Experienced and less-experienced nurses’ diagnostic reasoning: implications for fostering students’ critical thinking. Classif. 2003;14(2):41–52. CrossrefPubMed246. Garb HN. The representativeness and past-behavior heuristics in clinical judgment. Res Pr. 1996;27(3):272–7. CrossrefWeb of Science247. Arkes H, Blumer C. The psychology of sunk cost. Process. 1985;35(1):124–40. CrossrefWeb of Science248. Coleman MD. Sunk cost and commitment to medical treatment. Curr Psychol. 2010;29(2):121–34. CrossrefWeb of Science249. . Rationality in medical treatment decisions: is there a sunk-cost effect? Med. 1999;49(2):215–22. CrossrefPubMedWeb of Science250. Braverman JA, Blumenthal-Barby JS. Assessment of the sunk-cost effect in clinical decision-making. Med. 2012;75(1):186–92. CrossrefPubMedWeb of Science251. . Patient p71.

Output: corroborate


Input: Claim: Using blockchain makes all supply chain operations immune to theft or fraud. [SEP] Text: To streamline the production of X509 certificates the request for product certificates can be automated by an application at the producer side that requires that the producer inputs the triad of X509 attributes that need to be certified (-ID, PDO-ID) and then issues the certificate request and at the CA’s side a backend IT system that issues the X509 certificate after the verification processes have been validated. It should also be noted that as a product is processed in the supply chain its EPC code may change from animal EPC (type SGTIN) to carcass EPC (type SSCC) and carton tag EPC (type SGTIN). However even in this case the proposed solution SmartContract code is capable of maintaining reference to the original certified EPC and its owner SCA and support complete certificate traceability. This EPC code change is also described by GS1 in Hartley and Sundermann (2014) where a livestock traceability proof of concept (PoC) was implemented. In that PoC the EPC codes are read from RFID tags but in that case, they were inserted into a centralized SCM application to provide the required traceability metadata while in this proposal the EPC is stored in BC. As in the PoC in this proposal the EPCs can suffer change due to processing the meat thus the requirement for the previously presented “transform product” function in the SCM SmartContract to keep the EPC and certificate linkFootnote 18. 5 Conclusions and future workAs presented before, we posited and fully described a complex research problem. This complexity stems from two factors, the relative novelty of the technology and the combination of several existing solutions (and WallId certificate storage). This combination allows to propose a solution application for a supply chain when it is imperative to assure the traceability and the authenticity of the products sold over that value chain. 5. 1 Research contribution and solution benefitsThe research contribution of this work is a solution that aims to answer the research problem of providing complete traceability for a supply chain using blockchain. The main benefit of the solution is that it allows for a group of independent participants to implement a decentralized supply chain system with a complete traceability model for certified products. Another benefit is that via the PKI allow for SCAs themselves to import certificates and customers to view them thus providing trust among participants and the end customers.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: 1177/0013916518806686 Mackey, K. ,. , Advani, S. M. , Young, S. ,. . . Kansagara, D. (2020). Racial and in COVID-19–Related Infections, Hospitalizations, and Deaths. Annals of Internal Medicine, 174(3), 362-373. doi:10. 7326/M20-6306 Muñoz Sabater, J. (2019). ERA5-Land hourly data from 1981 to present. (C3S) Store (CDS). Musselwhite, C. , Avineri, E. , & Susilo, Y. (2020). Editorial JTH 16 --19 and implications for transport and health. J Transp Health, 16, 100853. doi:10. 1016/j. jth. 2020. 100853 Paull, N. J. , Krix, D. , Torpy, F. R. , & Irga, P. J. (2020). and Temperature? 17(14). doi:10. 3390/ijerph17145084 Pergams, O. R. W. , & Zaradic, P. A. (2008). Evidence for a fundamental and pervasive shift away from nature-based recreation. Proceedings of the of Sciences, 105(7), 2295-2300. doi:10. 1073/pnas. 0709893105 Reid Chassiakos, Y. , Radesky, J. , Christakis, D. , Moreno, M. A. , Cross, C. , Council On, C. ,. . . Swanson, W. S. (2016). Children and Adolescents and Digital Media. Pediatrics, 138(5), e20162593. doi:10. 1542/peds. 2016-2593 Rigolon, A. , Browning, M. H. E. M. , Lee, K. , & Shin, S. (2018). Access to Space in Cities of the Global South: A Review. Urban Science, 2(3). doi:10. 3390/urbansci2030067 Roy, A. , Nelson, T. A. , Fotheringham, A. S. , & Winters, M. (2019). in to Ridership of All Bicyclists.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Correction 1 Dec 2016: (2016) Correction: Decision-Making: Modelling the Influence of on the Dynamics of Vaccination Coverage. 11(12): e0167842. View correction studies predict that it is not possible to eradicate a disease under voluntary vaccination because of the emergence of non-vaccinating “free-riders” when vaccination coverage increases. A central tenet of this approach is that human behaviour follows an economic model of rational choice. Yet, empirical studies reveal that vaccination decisions do not necessarily maximize individual self-interest. Here we investigate the dynamics of vaccination coverage using an approach that dispenses with payoff maximization and assumes that risk perception results from the interaction between epidemiology and cognitive biases. consider a behaviour-incidence model in which individuals perceive actual epidemiological risks as a function of their opinion of vaccination. As a result of confirmation bias, sceptical individuals (negative opinion) overestimate infection cost while pro-vaccines individuals (positive opinion) overestimate vaccination cost. We considered a feedback between individuals and their environment as individuals could change their opinion, and thus the way they perceive risks, as a function of both the epidemiology and the most common opinion in the population. all parameter values investigated, the infection is never eradicated under voluntary vaccination. For moderately contagious diseases, oscillations in vaccination coverage emerge because individuals process epidemiological information differently depending on their opinion. Conformism does not generate oscillations but slows down the cultural response to epidemiological change. to eradicate vaccine preventable disease emerges from the model because of cognitive biases that maintain heterogeneity in how people perceive risks. Thus, assumptions of economic rationality and payoff maximization are not mandatory for predicting commonly observed dynamics of vaccination coverage. This model shows that alternative notions of rationality, such as that of ecological rationality whereby individuals use simple cognitive heuristics, offer promising new avenues for modelling vaccination behaviour. Citation: (2015) Decision-Making: Modelling the Influence of on the Dynamics of Vaccination Coverage. 10(11): e0142990. Chris T. Bauch, University of : June 16, 2015; Accepted: October 29, 2015; Published: November 23, 2015Copyright: © 2015 Voinson et al. This is an open access 0. 26 [-0. 12; 0. 45]), (ii) the susceptibility to illness (5 studies, r = 0. 24 [0. 15; 0.

Output: corroborate


Input: Claim: Using blockchain makes all supply chain operations immune to theft or fraud. [SEP] Text: The proposed architecture simplifies the storage of the certificates by reusing a KYC system (used in banking and credential verification) to both store and validate these certificates. If any certificate fails validation or is revoked (e. g. , expiration) it can be added to a CRL (List) by the CA (as is usual in PKIs) and the SC Manager simply sets an invalid certificate flag in the SC. If a SCA own certificate is revoked it no longer has access to the chain of trust until it provides a valid certificate. If the product certificate is revoked the product token can still be managed in the SCM but the certificates will be shown as expired or invalid to SCAs and customers (allowing the supply chain to operate while the certificate issue is being resolved). During operation, the SCAs have access via the Blockchain to the ownership status, the operations timestamps, the full chain of certificates and the transfer locations (if added) which can be further processed by SCAs own internal Management systems to interoperate with other IT systems (analytics) and optimize the supply chain. 5. 2 LimitationsThe main drawbacks of the solution are its dependency on a PKI (for SCAs and products), a centralized and hierarchical trust model and the dependency on a central entity (Manager) for certificate validation. Regarding the dependency on PKI the minimum requirements are its setup by a national or regional or any trusted authority in a privately owned supply chain and that the SCAs must subscribe to an authentication scheme for their identities and products. Regarding the SC Manager this actor is required to deploy the proposed SmartContract into the Ethereum BC and to be the entity responsible to be the “certificate validator”. A possible alternative to the use of a centralized PKI (and possibly to replace also the SC Manager) would to use a decentralized approach as has been recently proposed with Self-(SSI) and the usage of (DIDs) as defined by W3C (2022). Instead of digital certificates some previous solutions propose the import of scanned paper certificates. This is the case of “origin Chain” implementation, but this seems a stegap approach since such verification is more complex to implement and may require manual intervention to fix misreading or damage to the paper certificates.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: Urban Science, 3(2). doi:10. 3390/urbansci3020062 Statistics Norway. (2022). Land use and land cover. Retrieved from Twohig-Bennett, C. , & Jones, A. (2018). The health benefits of the great outdoors: A systematic review and meta-analysis of greenspace exposure and health outcomes. Environmental Research, 166, 628-637. doi: Ulset, V. S. , Bakken, A. , & von Soest, T. (2021). Adolescents' assessments of consequences of the pandemic after one year of COVID-19 restrictions. Tidsskrift for Den norske legeforening. . , Figari, H. , & Nowell, M. (2020). Urban nature in a time of crisis: recreational use of green space increases during the COVID-19 outbreak in Oslo, Norway. Letters, 15(10), 104075. doi:10. 1088/1748-9326/abb396. , Figari, H. , & Nowell, M. S. (2021). Back to nature: Norwegians sustain increased recreational use of urban green space months after the COVID-19 outbreak. Landscape and Urban Planning, 214, 104175. doi: von Soest, T. , Kozák, M. , Rodríguez-Cano, R. , Fluit, D. H. , Cortés-García, L. , Ulset, V. S. ,. . . Bakken, A. (2022). Adolescents’ psychosocial well-being one year after the outbreak of the COVID-19 pandemic in Norway. Behaviour, 6(2), 217-228. doi:10. 1038/s41562-021-01255-w Wang, Z. , & Tang, K. (2020). -19: health equity matters. Nature Medicine, 26(4), 458-458. doi:10. 1038/s41591-020-0823-6 Yancy, C. W. (2020). COVID-19 and African Americans. JAMA, 323(19), 1891-1892. doi:10. 1001/jama. 2020.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: 36]) and to a lesser extent, (iii) the severity of the disease (31 studies, r = 0. 16 [-0. 18; 0. 39]) (meta-analysis [12]). In classic behavioural epidemiology, risk perception relates to the prevalence of infected individuals at a given time, either in the general population (non-structured population and homogeneously mixed population) or in a social network [13,14]. This underlying game theory framework considers that individuals make decisions based on an objective evaluation of the epidemiology, computing statistics using a large data size (but see [15–17]). However, this assumption is problematic for at least two reasons. First, human cognition has been demonstrated to be inefficient at dealing with uncertainty and computing probability [10]; rather, individuals may use empirical knowledge based on a small number of cases. Second, risk assessment is likely to be partly independent from infection [1] as it is shaped by a number of psychological and social factors that may lead to an under- or an over-estimation of epidemiological risks, including media coverage [18], salient previous experience [11], belief about contagion [19], family and peers [11,20] and trust in providers, medical professionals and the state [7,21]. To evaluate temporal and spatial variation in vaccine uptake, one must thus refine assumptions of rationality to consider, not only change in epidemiology, but also how the evolved cognition responds to features of the social and epidemiological environments. An alternative to current modelling of vaccination decision-making may come from the consideration of evolutionary-ecological models, focusing on the concept of ecological rationality [9,22]. In this framework, cognitive dispositions are evolved, i. e. decision rules have been selected for, but the resulting behaviour may or may not be adaptive, i. e. maximizing current individual survival and reproductive success. It follows that to understand the processes underlying vaccination decision-making, one focuses on the environment and the cognitive mechanisms underlying decisions rather than health outcomes of decisions. Proponents of ecological rationality argue that humans have evolved heuristics, i. e. simple cognitive rules processing a few pieces of information available from the environment [9].

Output: corroborate


Input: Claim: Using blockchain makes all supply chain operations immune to theft or fraud. [SEP] Text: A more technology oriented approach would be the use of IoT devices and RFID tags with digital certificates where all authentication and verification is automated with higher granularity and the added security of a physical security token. An alternative for the SCAs certification-based authorization is to replace it with a simpler although less decentralized and autonomous authentication system (e. g. , LDAP) but this has the drawback of increased complexity and complexifying the security and management aspects in cases of global SCMs. If only a sectorial industry approach is required and the global decentralization and autonomy is not necessary and it would be more advantageous to operate over a consortium BC, with the benefits of lower latencies/latency variances and centralized SCM control. 5. 3 Future workThere remain open points that are left for possible future work and development of a Proof of Concept (PoC). The first open point is that the SC lacks the functionality for all SCAs to add product certificates (currently only suppliers) in the case of transformation of products. Additionally, it is still undefined when to delete product 5481. html60-2006 at: standard at: traceability recommendations at: on the Proposed SCM Functions are available in application protocol for accessing and maintaining distributed directory information services. A computer-network authentication protocol that uses tickets to allow nodes to prove their identity. Metamask documentation. Retrieved from is one example of a hardware Ethereum wallet: is one example of a software Ethereum wallet: API is API that allows to interact with an Ethereum node: more detailed description of the architecture use cases is available in Nacional de Informação e Registo Animal) is the national PortugueseGovernment livestock registry: is a cryptographic standard defined by ITU-T standardization body that defines the format of public key certificates (used in https and electronic signatures): details on use case samples, EPC details, the PKI certificate request and revocation see J, (2021) Impact of blockchain on sustainable supply chain practices. in Business Administration, Jönköping School, University of Jönköping, (2018) Blockchain, Chain of Custody and Trace Elements: of Tracking and in the Gem Industry. Gemmol 36(3):212–227. M, (2017) Global supply chains are about to get better, thanks to blockchain. Rev 13:1–6 1901. 02715.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: Aside from changes in green space use over time, there is evidence from before the pandemic of social inequalities in exposure to nature; specifically, neighborhoods with low socioeconomic status (SES) had less proximity to green spaces compared to those with high SES (17). It is also known that people with low SES experience more mobility restrictions (18). For example, mobility constrictions are more severe in areas with economic inequalities (19), among people with low education and income (20, 21), and among ethnic minorities (22, 23). However, research on how social inequalities in the nationwide use of green spaces might have changed with the pandemic is currently lacking. On the one hand, larger burden of restrictions, lack of access to greenspace, limited resources and a dependence on public transport may have led to less recreational greenspace exposure during the pandemic among those living in less affluent neighborhoods. On the other hand, increased use of home office across all socioeconomic strata may have evened out socioeconomic differences in greenspace use by introducing more flexibility for people in low SES neighborhoods to engage in nature-based recreation. However, very little is known about how the pandemic may have influenced such inequalities in exposure to greenspaces. There may also be differences between densely populated and not so densely populated neighborhoods with respect to use of greenspace, and changes in use of greenspace during the pandemic. In Norway, built-up areas account for only 1. 7% of the land cover, with the remaining land being dominated by forests and mountain ecosystems, which are ideal for outdoor recreation (24). Therefore, even though more than 80% of Norwegians live in densely populated areas, most people have nature close to where they live. However, people living in rural neighborhoods with vast space surrounding them may have been less affected by mobility restrictions than those living in densely populated neighborhoods, meaning the changes in green space use in rural areas during the pandemic may be smaller than the changes observed in densely populated neighborhoods. During the pandemic in Norway, residents were allowed to spend time outdoors if following restrictions on social distancing. The first lockdown in Norway was announced on March 12th, 2020, during which schools, kindergartens, fitness centers, hair salons, restaurants, and similar public spaces were closed, and cultural events and sports gatherings were banned. As of March 13, 2020, a ban on visits to Norway through Norwegian airports was enforced, with exceptions for citizens returning home.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: For the purpose of this paper, which aims to investigate the role of cognitive biases for predicting commonly observed dynamics of vaccination coverage such as the failure to reach herd immunity and oscillations between high and low levels of coverage, we focus on those heuristics or cognitive shortcuts that are likely to allow for heterogeneity and change in opinion about vaccination. In modelling how individuals interpret epidemiological information, we first decided to consider “confirmation bias”, i. e. the propensity to look for evidence supporting pre-existing beliefs while considering disconfirmatory evidence with great scrutiny [23,24]. Confirmation bias has been observed in the context of pertussis vaccination for children: when presented with the same risk-benefit information about vaccination, non-vaccinators became less committed with vaccination, while vaccinators became more committed [25]. The second heuristic we considered is “imitate the majority” or conformism, as the role of peer influence has repeatedly been invoked for understanding vaccination behaviour [7,26,27]. In this paper, we consider a behaviour-incidence model in which opinion formation mediates a feedback between vaccination behaviour and the disease. As compared to previous behaviour-incidence models, our approach does not make use of game theory analysis (see also [28,29]). We first consider that disease incidence and vaccination coverage determine how many people suffer from negative effects, an information that represents epidemiological costs. We then assume that an individual interprets those costs as a function of their opinion of vaccination. Specifically, a sceptical individual will be more likely to overestimate a vaccination cost while a pro-vaccine advocate will more likely to overestimate the cost of infection. It follows that given the same epidemiological information, individuals will vaccinate at different rates depending on their a priori opinion. Finally, we consider that individuals respond to their environment over time as they can change their opinion as a function of both epidemiological costs and the most common opinion in the population (conformism). The model assumes that the population mixes homogenously so that anyone can infect any other individual in the population and the information on epidemiological costs is globally available to everyone through the media. The goal of this study is to investigate how the interaction between human cognition and both the epidemiological and social environments shape the dynamics of vaccination coverage.

Output: corroborate


Input: Claim: Using blockchain makes all supply chain operations immune to theft or fraud. [SEP] Text: AbstractToday, supply chain finance is a very important topic. Traditional supply chains rely on banks to support the related financing activities and services. With the emergence of blockchain technology, more and more companies in different industries have considered using it to support supply chain finance. In this paper, we study supply chain financing problems in supply chains selling fashionable products. Modeling under the standard newsvendor problem setting with a single manufacturer and a single retailer employing a revenue sharing contract, we develop analytical models for both the traditional and blockchain-supported supply chains. We derive the optimal contracting and quantity decisions in each supply chain with Nash bargaining between the manufacturer and retailer. We analytically show how the revenue sharing contract can coordinate both types of supply chains. We then compare the optimal systems performances between the two supply chains. We prove that the blockchain-supported supply chain incurs a lower level of operational risk than the traditional supply chain. We have shown that if the service fees by banks are sufficiently high, adopting blockchain technology is a mean-risk dominating policy which brings a higher expected profit and a lower risk for the supply chain and its members. For robustness checking, we examine other commonly seen supply chain contracts and alternative risk measures, and analytically reveal that the results remain valid. This is a preview of subscription content, log in via an institution to check access. Access this 34. 99Month Get 10 units per month Download 39. 95 Price excludes VAT (USA) Tax calculation will be finalised during checkout. Instant access to the full 831. 431. 44. 105. 107. 842. 165. 507. 1629. 91. 29. 475. 229. 7473. 246. 1042. 1860. 152. 2019. 1837. 198. 33. 626. 2421. 96. 641. 1478. 1634. 180. 84. 1823. 236. 106. 117. 146. 34. 2. Table 2 Notation/abbreviation and the respective meaningsFull size table3.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: Furthermore, healthcare professionals working with patients were prohibited from leaving the country, and leisure travel was strongly discouraged for all citizens. However, public transport schedules continued as normal. During the summer of 2020, the restrictions were somewhat eased, but all the restrictions were lifted for the first time on September 21st, 2021. As shown in Figure 1A, there was a sharp increase in the stringency index for the national-level restrictions in March 2020, and this level of restriction was sustained during the study period from January 2019 to November 2021 (with a maximum restriction stringency score of 80). The most prominent increase in the number of new COVID-19 cases occurred during the fall of 2020, and this number reached a peak during the fall of 2021, with 2,485 new cases of COVID-19 per 100,000 inhabitants recorded in one day. We therefore ask: Did the COVID-19 pandemic and associated social distancing measures result in increased usage of greenspaces, and if so, did such changes vary by neighborhood socioeconomic characteristics and population density? Considering the above research, we hypothesize that 1) the number of dwells (i. e. , visits) in green spaces may have increased during the COVID-19 lockdown compared to the previous year, even after controlling for the possible confounding effects of weather conditions, neighborhood population density, neighborhood SES, and public and school holidays. Moreover, we hypothesize that 2) social inequalities in the use of green space may have increased during the COVID-19 pandemic, with a lesser increase in green space exposure in neighborhoods characterized by low education, low household income, and a larger proportion of immigrants. Finally, we hypothesize that 3) changes in mobility in green space during the pandemic may have been more pronounced in urban areas compared to rural areas. We used daily aggregated mobile tracking data from more than 2 million cell phone subscribers in 14,331 geographical grids across Norway, population registry data on sociodemographic factors, and remote sensing (Vegetation Index) to examine whether the onset of the COVID-19 pandemic and the associated restriction policies affected the nationwide recreational use of green spaces. MethodsStudy area and data structure Norway is a country in North-with a population of about 5. 5 million people, of which 82. 4% live in densely populated areas. Norway has a total land area of 323,782 km2, of which 1.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Then, given the same epidemiological information on costs, individuals with different opinions vaccinate at different rates. We considered that pro-vaccines individuals give more weight to the role of infection cost in their decision process, while sceptics give more weight to the vaccination cost (due to confirmation bias). Thus, while pro-vaccines individuals always take up vaccines more quickly than sceptics, the difference between them in how rapidly they take up vaccination is considered to be the highest for levels of vaccination coverage that are either low (high infection cost) or high (high vaccination cost). Finally, individuals can change their opinion as a function of both the epidemiology and the most common opinion in the population. The full model The structure (Fig 1). We considered the case of a single contagious disease, which does not increase the death rate, but which causes negative side effects for infected individuals. Our goal here is not to study a disease in particular but to provide general insights with regard to the effect of opinion on the dynamics of infection and vaccination coverage. We used a compartmental epidemiological model with births and deaths [30] in which the population is divided into 4 compartments: the number of susceptible (S), the number of infected (I), the number of immune through vaccination (Rv) and the number of immune through natural immunization (Rg). A susceptible individual becomes infected at the rate β (the transmission rate) and vaccinates (transits from compartment S to Rv) at the rate θ. Individuals give births to susceptible individuals at the rate b and each individual can die at the rate d = b, so that the population remains of constant size. Then, for each compartment, the population is divided into 2 subgroups, with individuals having either a positive opinion of vaccination (pro-vaccines individuals, subscript p) or a negative opinion (sceptical individuals, subscript n). The formation of the opinion and the decision to vaccinate are two separated processes that both depend on the environment. Individuals can change their opinion during their lifetime, and given their opinion at a given time, they decide to get vaccinated or not. At any given time, the total recalled number of individuals having suffered negative side effects from becoming infected or vaccinated constitute a globally available information, which will be used to calculate the epidemiological costs CI and CV. The parameters (Table 1).

Output: corroborate


Input: Claim: Blockchain can instantly resolve all delays and errors in global shipping. [SEP] Text: However, understanding that the present case differs from previous ones can alter the intuitive mode of decision-making, making it more analytical and evidence-based (Mishra et al. 2015). Consequently, managers should update their knowledge and decision-making assumptions through evidence (Vlajcic et al. 2019). Decision-making based on the analysis of real-time data is indeed significant for companies (García-Magariño et al. 2020). However, the management of big data is not an easy task for the shipping industry (Perera and Czachorowski 2019). It is hindered by the integration of information and a lack of transparency (Jain 2018). Decision-making is largely the responsibility of company directors (Lafarre and Van der Elst 2018), and until now, managers have simultaneously been the beneficiaries and bearers of the privilege and burden of information access and strategic decision-making (et al. 2018). Although this restricted privilege has political value (McCook 2018), it complicates execution and results in agency problems (Lafarre and Van der Elst 2018). Blockchain technology in decision-makingDecision-making is being increasingly supported by artificial intelligence and autonomous systems (Calvaresi et al. 2019). A decentralized system (e. g. , blockchain) helps to address agency and coordination problems by offering flexibility when sharing information (Perera and Czachorowski 2019). It enables decentralized, fast, and transparent sharing, solves problems of communication inadequacy, and makes decision-making simpler and quicker (Lafarre and Van der Elst 2018; Tsiulin et al. 2020). Decisions based on blockchain technology are also executed much faster than conventional approaches (McCook 2018). For example, the use of smart contracts offers an automated mode of decision-making based on predetermined parameters agreed upon by actors (et al. 2018). Accordingly, shipping industry players are increasingly becoming convinced of the effectiveness of collaboration and collective decision-making for their sustained growth (Diordiiev 2018). Nevertheless, cooperation among parties involved in shipping transactions remains complex (Jain 2018), and extensive collaboration often encounters difficulties regarding issues of privacy, security, and confidence (Yang et al. 2019). Currently, some innovative collaborative decision-making methods are being used by industry participants (et al. 2018).

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: 7% is built-up areas and 3. 5% is agricultural land. The remaining land area is covered by forests (37. 6%), grassland/heathland (37. 4%), bare rock (7. 4%), inland waters (6. 2%), wetland (5. 3%), and permanent snow and glaciers (0. 8%) (24). Norway is geographically divided into 356 municipalities and 1,550 smaller neighborhoods (administrative units that are used by the municipalities and regional authorities for statistical analysis and planning purposes). For this study, the neighborhoods were, in turn, subdivided into geographical grids ranging from 500 m x 500 m to 64,000 m x 64,000 m. Each neighborhood contained an average of 8. 3 grids. Daily recreational dwells We obtained aggregated mobility data regarding daily dwells from the Norwegian telephone company Telia, which has approximately 2 million users. All mobile phones registered to Telia’s network were tracked, using signal triangulation to locate the mobile phone in space, and the data were further modeled to represent the whole Norwegian population as closely as possible. To maintain anonymity, the mobile company was in control of the data anonymization. Additionally, activity was only registered if there were five or more mobile phone subscribers in a grid within a specified period. For this study, daily interval data from January 1, 2019, to November 1, 2022, were collated, and the “daily recreational dwells” in a grid were defined as the number of mobile phones stationary within a grid cell for at least a 20 min duration per day. If the mobile phone was stationary in a location between 09. 00 and 17. 00, the dwell was categorized as a work dwell. If the mobile phone was stationary in a location overnight, the dwell was categorized as a home dwell. For this study, all the dwells that were not categorized as either a work or home dwell were categorized as a recreational dwell. In areas with low mobility, the grids were made larger to maintain the anonymity of the cell phone users. Out of the 14,331 grids, the grid sizes included 500 m x 500 m (28. 6 %), 1,000 m x 1,000 m (18. 19%), 2,000 m x 2,000 m (16. 0%), 4,000 m x 4,000 m (16. 5%), 8,000 m x 8,000 m (11.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: While individuals have access to the same epidemiological information CI and CV, the perception of those costs and the subsequent vaccination behaviour is modified by an individual opinion because of a confirmation bias. Confirmation bias is introduced with μ, the weight given to the cost of infection and μ′, the weight given to the cost of vaccination. During the vaccination decision-making process, individuals with a positive opinion of vaccines give more weight to the infection cost () while individuals with a negative opinion give more weight to the vaccination cost (). The rate of opinion change: A pro-vaccine individual will become a sceptic at the rate Ω and a sceptic will become a pro-vaccine individual at the rate Ω′. ωp→n and ωn→p indicate the maximum rates at which an individual changes opinion; Υp→n and Υn→p indicate resistance to opinion change, which is a function of the costs of infection and vaccination (CI and CV); cp and cn indicate the conformity functions, which are non linear frequency-dependent functions, as modelled by [32]. F and Ng indicate the number of pro-vaccines and sceptical individuals in the entire population denoted N; D is the conformity coefficient. The more common is a given opinion, the more often it is adopted. The parameter time unit: It is calibrated in relation to the birth and death rates. We generally set the birth and death rates at the value 1 which, in the case of human populations, could correspond to a time unit of the order of a year or ten years. The dynamic. The dynamic of the system can be described by the following set of ordinary differential equations: Nested models The full model described above combines five elements: (1) the characterization of individuals by their epidemiological status (SIR model); (2) the characterization of individuals by their opinion; (3) a globally available information on the infection and vaccination costs; (4) the interpretation of epidemiological costs as a function of opinion through confirmation bias and (5) the transmission of opinion through conformism. To evaluate the significance of each element in shaping the dynamics of infection and vaccination coverage, we broke down the full model into several nested models differing by 1 element at a time.

Output: corroborate


Input: Claim: Blockchain can instantly resolve all delays and errors in global shipping. [SEP] Text: The main advantage of blockchain is related to its utility for disseminating reliable data to different parties, thus contributing to decreasing operation costs and improving collaboration (Bai et al. 2020). Role of blockchain in the shipping industryInformation asymmetry is a noteworthy problem in the shipping industry, partly because the generated information is often used by different parties (Mattila et al. 2016). However, some parties do not create useful data, resulting in information gaps (Mattila et al. 2016). Blockchain technology helps shipping industry third parties, such as banks, freight forwarders, and agents, overcome this problem (Jugović et al. 2019). Data cannot be edited or deleted from a blockchain, and they are secure and independent of any single computer node. Thus, the need for administration is eliminated (Jain 2018). The initial purpose of blockchain technology was to provide confidential information on financial transactions without interference from third parties (Jović et al. 2019). The fact that a blockchain eradicates the role of third parties makes the technology comparable to and compatible with the internet (et al. 2018). In this respect, blockchain technology may contribute to the so-called emancipation of organizations (Mattila et al. 2016). Overall, the utilization of effective technologies to reduce the required documentation would be extremely beneficial to the maritime sector (Jain 2018). However, this sector has been conservative in regard to the adoption of innovative technologies (Filom and 2020), leading to complications (Green et al. 2020). Consequently, the application of blockchain technology to the shipping industry remains a challenge (Jabbar and Bjørn 2018). Thus far, the technology has not been widely adopted in shipping operations (Diordiiev 2018). It should be emphasized that the shipping industry, although a conservative sector, has successfully adopted new technologies in the past (Jugović et al. 2019) with the first fully automated ocean-going vessel anticipated to be in operation by 2030 (Diordiiev 2018). High-technology vessels are equipped with modern systems that use the Internet of Things, a technology that can be used in conjunction with blockchain to store and disseminate data (Green et al. 2020). Moreover, considering that shipping operations currently do not often include innovative elements, the maritime industry is fertile ground for the application of digital-technology systems, e. g. , smart vessels, fleets, and global logistics (Jović et al.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: 9%), 16,000 m x 16,000 m (3. 7%), 32,000 m x 32,000 m (0. 69%), and 64,000 m x 64,000 m (0. 18%). Overall, the signal quality was good, but on some days, there was a drop in the number of signals compared to the baseline, which could indicate that there were problems with the mobile network infrastructure. This occurred for 13 days in 2019, 14 days in 2020, and 9 days in 2021. However, the drops in network signal were not persistent over time and were spatially random and, thus, did not confound our statistical models. Green space The density of green space was defined using the normalized difference vegetation index (NDVI) (25), which is a widely used remote sensing index that quantifies the normalized difference between visible and near-infrared reflectance and serves as a proxy for vegetation cover. We used data from the Spectroradiometer (MODIS) (MOD13Q1) Version 6. 1 (26). Data were collected every 16 days at 250 m x 250 m spatial resolution, and the algorithm chose the best available pixel value from the 16 day acquisition period based on the following criteria: low cloud cover, a low view angle, and the highest NDVI value. We calculated the median score between January 1, 2019, and January 1, 2020. The NDVI index scores ranged from −1 to 1 and were aggregated to the mobility data grid by calculating the mean NDVI value within each grid cell. Weather data We gathered ERA–- data (27) regarding the snow depth, solar radiation, wind speed, and temperature for each grid with mobility information, and these weather data were collected at daily intervals from January 1, 2019, until November 1, 2021. ERA5-Land is a reanalysis satellite dataset that provides a view of the changes in land variables over several decades at a high resolution. Specifically, the snow depth was defined as the average snow thickness on the ground (excluding snow on the canopy) in meters. The surface solar radiation was defined as the amount of solar radiation (also known as shortwave radiation) reaching the surface of the Earth in a certain area. Data on this variable were collected at daily intervals, and the units of surface solar radiation are joules per square meter (J m−2).

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: When the reproductive rate of the disease is large (R0 >4), the negative opinion of vaccination disappears and vaccination coverage, while reaching high levels, does not reach herd immunity. This is because the infection spreads too quickly. More generally, four dynamics can be observed and a1 to a3 represent their limits which can be moved depending of the values of δv considered. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 3. Confirmation bias, conformism and the emergence of oscillations in vaccination coverage. The emergence of oscillations (o) is depicted as a function of an infection’s reproductive rate (R0) and the rate of negative side effects from vaccination (δv). The emergence of oscillations is contingent on the inclusion of confirmation bias but not conformism and is observed for intermediate values of R0. Three models are considered: Model 3 (without either confirmation bias or conformism); Model 4 (including confirmation bias) and Model 5 (including both confirmation bias and conformism). If no oscillations emerge, three dynamics can be noted for the distribution of opinions of vaccination: (i) coexistence of 2 opinions with a greater number of individuals with a positive opinion (+), (ii) coexistence of 2 opinions with a greater number of individuals with a negative opinion (-), (iii) all individuals have a positive opinion (*). The models are analysed for 2 different generation times (birth (b) = death (d) = 1 and 0. 5) and for different values of the rate of negative side effects from infection (δI). 1 million iterations were run with a time step of 0. 0001 which correspond to 100 unit of time. Download: PPTPowerPoint slidePNGlarger imageTIFForiginal imageFig 4. Conformism and oscillations in vaccination coverage. The evolution of the number of infected (thin line) and (thick line) vaccinated individuals is depicted. Conformism (illustrated by Model 5) increases the amplitude of oscillations and slows down the rate at which alternative opinions of vaccination alternate. The situation is indicated for infections that are moderately infectious (with a reproductive ratio (R0) varying from 3 to 5) and with the rate of negative side effects from the vaccination (δV) varying from 0. 5 to 2. What is the role of R0 for the dynamics of vaccination coverage?

Output: corroborate


Input: Claim: Blockchain technology will make manual labor in the supply chain industry obsolete. [SEP] Text: Among these technologies, blockchain provides a promising future and allows the supply chain to provide better visibility, transparency, and acuity of transactions throughout the entire process [4]. The blockchain technology that powers cryptocurrency has caught the attention of businesses, especially those in supply chain management. A 2017 study indicated that nearly 62% of supply chain executives claimed to have engaged with blockchain technology [5]. Although blockchain-based applications in the supply chain are still in their early stages, we believe this technology will significantly remodel the supply chain system [6, 7, 8]. Analysts forecast that blockchain technology can help supply chain management gain one-third improvement in most of its common processes [9]. A blockchain network is as a distributed ledger—transactions are contained in blocks that are linked together in chronological order to form a tamper-proof chain, which is usually stored in all network nodes [10, 11]. As such, blockchain technology provides a means to create tamper-proof logs of business activities and transactions [12]. Transaction data are immutable because they cannot be tampered with once they are distributed, accepted, and validated by network consensus and stored in the blocks [13]. By eliminating intermediaries to achieve trust among all stakeholders, efficiency improves and cost is reduced for the entire supply chain. Despite the general acceptance that blockchain technology facilitates faster, more easily auditable interactions and allows for the exchange of immutable data among supply chain partners [14], it will take time for this technology to be adopted and to revolutionize the supply chain. Currently, most applications of blockchain are conceptual expositions, and empirical evidence on the implementation of it is limited [15]. Furthermore, few studies have been conducted on the challenges of deploying blockchain in the supply chain, such as organizational readiness, technical expertise, scalability, and compatibility with existing systems. Therefore, this study will provide a systematic analysis of how blockchain technology fits in the supply chain network and discuss potential challenges with its implementation. Advertisement 2. Supply chain2. 1 OverviewSupply chain encompasses the end-to-end flow, including the physical and correlated data flow of raw material, products, information, and money. It plays a unique and critical role in businesses and determines the performance of organizations. Supply chain manages or is involved in sourcing, procurement, manufacturing, distribution, and logistics, and, thus, affects speed-to-market, the cost of a product, service perception, and capital requirements in businesses [16].

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: The temperature was defined as the air temperature at 2 m above the surface of the land, sea, or inland waters. The windspeed was defined as the square root of the sum of the squared eastward component of the 10 m wind and the squared northward component of the 10 m wind based on the following equation: windspeed = sqrt([U × U] + [V × V]). The eastward (U component) and northward (V component) wind vector components represent the horizontal speed of the air moving toward the east and north, respectively, at a height of 10 m above the surface of the Earth, and the units of these values are meters per second. Pandemic- and time-related variables The dataset included data for a total of 1,036 days ranging from January 1, 2019, to November 1, 2021. As an indication of the onset and duration of the COVID-19 pandemic, a dummy variable coded as 0 or 1 was used to indicate, respectively, the pre- and post-lockdown periods in Norway (January 1, 2019, to March 11, 2020, and September 25, 2021, to November 1, 2021) and the time after the onset of the first lockdown from March 12, 2020, until September 24, 2021, when the restrictions were lifted. We also created a dummy variable for school holidays at the municipality level, which was coded as 1 if a date was during a school holiday and coded as 0 if not. Public holidays were also dummy coded in the same way as for school holidays. Seasonal trends in activity were modeled by including dummy variables that were coded as 1 to indicate days that fell within the winter (December, January, February, March), summer (June, July, August), or autumn (September, October, November) seasons. Neighborhood SES and population density Data regarding the neighborhood SES and population density were obtained from Statistics Norway. Population density. We calculated the neighborhood population density by dividing the neighborhood population by the land area to determine the number of people living in each square kilometer of the neighborhood. Due to the non-normal distribution and right skew of the resulting population density variable, this variable was stratified based on tertiles into low (<18. 2 people/km2), medium (>18. 2 people/km2 and <270 people/km2), and high (>270 people/km2) population density categories. SES.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Various dynamics are observed depending on the reproductive rate of the infection because the value of R0 influences the distribution of opinions in the population. For infections that spread very quickly in the population (R0 >> 1), only “pro-vaccines” individuals persist. For intermediate values of R0, a stable coexistence of “sceptics” and “pro-vaccine” individuals is observed with three possible cases: (1) at equilibrium, a negative opinion of vaccination is more frequent; (2) at equilibrium, a positive opinion of vaccination is more frequent; (3) which opinion is the most frequent oscillates over time (Fig 2). Oscillations are only observed when the cost of vaccination (CV) is high enough, i. e. when a sufficient number of individuals are vaccinated and suffer from side effects. The influence of other parameters on the emergence of oscillations is depicted Fig 3. The emergence of oscillations in vaccination coverage The role of cognition (confirmation bias and conformism). We compared nested models to disentangle the role of confirmation bias and conformism on the distribution of opinions towards vaccination and subsequently, the emergence of oscillations in vaccination coverage. We found that oscillations can only emerge when both negative and positive opinions of vaccination coexist in the population and when a confirmation bias is included (Models 4 & 5, see also S1 Fig for various values of μp, μn and μp/μn). To confirm the significance of confirmation bias, we reran the full model while excluding confirmation bias (μp = μn): oscillations do not appear (S2 Fig). Then we found that conformism does not affect the emergence of oscillations in the dynamics of infection and vaccination coverage (Fig 3). Rather, oscillations become less frequent and more ample because conformism increases the time necessary for the least frequent opinion to invade the population (Fig 4). To confirm that conformism does not produce oscillations, we compared the results obtained for the full model with and without biased social transmission (D = 0. 7 and D = 0, respectively): when confirmation bias is considered oscillations do appear in both situations (S2 Fig). The role of epidemiology (vaccination and infection costs). Once opinion heterogeneity and confirmation bias are considered, the emergence of oscillations in vaccination coverage depends on the ratio between the costs of vaccination and infection.

Output: corroborate


Input: Claim: Blockchain technology will make manual labor in the supply chain industry obsolete. [SEP] Text: Skuchain: A blockchain network that is designed for enterprise supply chains in global trade [45]. It creates a zero-knowledge collaborative platform for global supply chains and provides precise control in inventory procurement across all partners, reducing friction and the costs of supply chain processes. Sweetbridge: A blockchain-based application that enables real-time financial systems to assure transactional data are trustworthy between different parties. It integrates trusted identity, smart legal contracts, smart accounting, and payment rails into a transaction for all parties to see in real-time [46]. Zervnetwork: A decentralized trading platform based on blockchain technology. It aims to provide frictionless transactions among all participants within the defense industry [47]. IOTA: An open-source distributed ledger that is being built to power the future of the Internet of Things (IoT) with feeless microtransactions and data integrity for machines [48]. Advertisement 4. Chain integrationIn recent years, Blockchain technology has been recognized as a critical technology with inherent capabilities to dramatically improve supply chain efficiency [49, 50, 51]. A study from Eye for transport stated that more than 16% of the 300 companies surveyed agree that data interchange, tracking, and visibility are the foremost reasons to deploy blockchain technology in the supply chain [52]. However, we discuss the benefits, challenges, and risks of integrating blockchain technology in the supply chain and introduce several pilot initiatives below. 4. 1 Benefits to supply chainThe adaptation of blockchain technology can significantly alleviate or even eliminate the aforementioned problems in today’s supply chain. Blockchain technology empowers the supply chain with improved efficacy, efficiency, and transparency and reduced transactional time and cost. There are many ways blockchain technology benefits the supply chain:Advanced traceability: With the adoption of blockchain technology, traceability within the supply chain is greatly improved; it produces a fully auditable trail of all items flowing through the network. Combined with IoT-based devices, such as RFID technology, a blockchain-enabled supply chain can automatically collect the item-level data of massive quantities of products in real-time. Additionally, this information is associated with timestamps and collection locations to form an audit trail that is complete, accurate, and easy-to-access, from the product’s origin to the customer.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: Firstly, the proportion of residents in each neighborhood who had completed graduate-level higher education was assessed. Data regarding the educational attainment of the population was collected by examining the proportion of residents aged 16 years or older who had completed their education at an educational institution as of December 31, 2020. Secondly, the median income for households was determined by summing all the monetary income (in [NOK], both taxable and tax-exempt) of the people who lived permanently in the same dwelling as of December 31, 2020. All the amounts were calculated as constant prices based on the previous year’s consumer price index. Thirdly, the population proportion of immigrants in a neighborhood was calculated using the number of immigrants and Norwegian-born children to immigrant parents as of December 31, 2020. Immigrants were defined as individuals born abroad to two foreign-born parents and four foreign-born grandparents. In accordance with an already established approach (28), the education level, median income, and immigrant population proportion were z-standardized and averaged to create a composite neighborhood-level SES variable. the hierarchical structure of the data comprised daily observations from geographical grids (grid-days) nested within these geographical grids, which were, in turn, nested within the corresponding neighborhoods, multilevel mixed linear analyses with random intercepts were applied. Grid-level variables regarding the snow depth, surface solar radiation, temperature, and windspeed were included as control variables to control for the possible confounding effects of weather on dwells. The effects of the onset of the pandemic on daily dwells over and above the seasonal trends in weather variables were modeled. To model the effect of the pandemic on activity in green spaces, an interaction term between the COVID-19 pandemic period dummy and NDVI was included in the analysis. To examine differences between rural and urban areas, as well as to examine any social inequalities in the use of green spaces, we specified three-way cross-level interaction terms of NDVI and the COVID-19 pandemic dummy to neighborhood SES and population density. To manage the count data, we used the natural logarithms of the dependent variable in all the analyses. Logarithmic transformation has an additional advantage, as it allows for the interpretation of the estimated effects from dummy variables in terms of percentages (29).

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: For instance, in the case of an infection with a low epidemic potential (R0 is low) and few individuals infected, both the infection cost and the vaccination cost are low because only a few individuals suffer negative side effects. Consequently, vaccination coverage remains low and stable over time. For infections with a high reproductive rate (R0 is high), the infection invades the population more rapidly than vaccination behaviour. Thus, the cost of infection is always higher than the cost of vaccination. Similarly, when the cost of vaccination is low, oscillations do not emerge because the cost of vaccination is always lower than that of infection. DiscussionDespite evidence that vaccines are safe, vaccine scares are repeatedly observed in various populations and cause the resurgence of diseases otherwise near eradication (e. g. measles). A key factor in driving vaccination decisions is how epidemiological parameters, in particular the costs associated with infection and vaccination, are perceived. Although perception may be based on epidemiological information, the success of anti-vaccination movements also suggests that individuals vary in the way they interpret scientific evidence. People differ in their opinion of vaccination because of their past experience with immunization, their trust in the state or in the medical profession, the opinion of their parents or the most common opinion in their cultural environment, irrespective of a cost-benefit analysis based on the epidemiology [34]. In this paper, we deviate from previous theoretical studies positing that individuals are economic agents maximizing their health [4,5,35–39] to consider that individuals make decisions as result of cognitive biases. Specifically, we developed a behaviour-incidence model in which individuals can be pro-vaccines or sceptical, their opinion influencing how the costs of infection and vaccination are perceived. Overall, the model predicts the commonly observed dynamics of vaccination coverage, i. e. the failure to reach herd immunity as well as oscillations in vaccination coverage (periods of increase in vaccination coverage followed by disease outbreaks). The results have implications for considering how the interaction between human cognition and the epidemiology may lead to difficulties in reaching and/or maintaining population level immunity. The emergence of oscillations D’Onofrio et al. [40] showed that assuming a memory of the information related to the costs of infection and vaccination can generate oscillations in a SIR model without cognitive bias.

Output: corroborate


Input: Claim: Blockchain technology will make manual labor in the supply chain industry obsolete. [SEP] Text: Furthermore, thanks to the immutability of blockchain data and the digital signatures required to confirm information ownership, data stored in this chain offers a secure and full history of any item in the entire supply chain. In the event of a compromised product, improved traceability enables the source of the issue to be identified more quickly, which reduces the cost of recalling products and improves disruption resolution between stakeholders. Advanced traceability gives stakeholders and customers more confidence in a product’s authenticity and quality. Improved transparency: Blockchain technology provides reliable identity management in the supply chain [53] by enabling all parties to know who is performing what actions, at what time, and where. This information is stored and shared in distributed ledgers that can be conveniently accessed by involved and authenticated stakeholders. Through the integration of physical and digital flows across the supply chain, the connectivity of multiple trading partners will improve [54, 55]. Therefore, a blockchain-enabled supply chain with its transparent and complete inventory of product flow helps businesses make better forecasts and decisions. Additionally, improved transparency serves as a powerful tool for fighting fraud and counterfeiting. Boosted efficiency: One of the primary motivations for implementing blockchain technology is to replace the outdated, paper-heavy processes in place today. As one of the benefits of digitalization, the logically centralized data ledger provides up-to-date local copies to all stakeholders within the network. All transactions are committed and immediately validated by all involved parties, and data are automatically synchronized to each party’s local copy. Blockchain technology makes it safer and faster to maintain the quality of transactions and associated data [56] by reducing human error and eliminating the need for third-party intermediaries and for local ledger reconciliation. Finally, the autonomous and self-executing blockchain-based smart contract replaces tedious processes and improves flexibility in supply chain management. Greater security: It is nearly impossible to impact blockchain technology through hacking attacks like those that threaten centralized databases of intermediaries (e. g. , banks). It is structured so that when there is an attempted hack into a specific block, all preceding blocks in the entire history must also be tampered with. Thus, blockchain provides a more secure way to maintain a log of business activities and transactions [12]. Enhanced trust: The transactions of a blockchain-based supply chain are created and recorded based on peer-to-peer interaction that can be trusted by the associated digital signatures.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: This study has several strengths, including the use of nationwide mobility data from over 2 million cell phone subscribers combined with population registry data, satellite data, and daily weather information to examine the effects of the COVID-19 pandemic on green space use in Norway. Specifically, we used objective measures to identify the number of daily dwells in green spaces and distinguished between different categories of activities such as working, staying at home, and non-home or non-work-related dwells. This methodology allowed us to capture a comprehensive picture of the impact of the pandemic on green space use across different socio-economic and geographic areas in Norway. However, there are also some limitations in this work that should be acknowledged. Our measure of daily dwells in green spaces did not differentiate between people living in an area and those visiting that area. Therefore, it is possible that some of the increases we observed in green space use were due to an influx of visitors from outside the area rather than an increase in usage by the local residents. To identify recreational dwells, we excluded dwells that were deemed work-related or overnight stays at home. However, we could not conclusively differentiate recreational dwells from other types of mobility, such as shopping or restaurant visits. Therefore, some dwells classified as recreational dwells in this study may have been of a non-recreational nature. Furthermore, in this study, we utilized the NDVI as a proxy for the amount of accessible green space in an area, but grid cells with a very high NDVI may be inaccessible for recreation use (e. g. , train tracks or private properties). Additionally, the mobility data in this study was likely biased toward middle-aged people and may under-represent children and elderly demographics. Moreover, the mobile company from which the data were obtained uses an algorithm that attaches the location of the mobile device to the nearest housing, which may mean that dwells in very remote wilderness areas may not be accounted for in the dataset. We also focused only on green space but did not consider blue spaces in this work. Indeed, it is likely that people living near open water used such areas for recreation during the pandemic (33). Additionally, our study focused only on Norway, and it is possible that the results may not be generalizable to other countries or regions with different cultural, socio-economic, and geographical characteristics. Despite these limitations, the findings of this study have several implications for public health and urban planning.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Comparing the behaviour of our model with or without cognitive bias we have shown that the confirmation bias is necessary for the emergence of oscillations in the dynamics of infection and vaccination coverage, at least in the parameter range we explore. Our model and that of d’Onofrio et al. differ by several hypotheses, which could explain why the conditions necessary for the emergence of oscillations differ between the two models. D’onofrio et al. assumed that memory is fading following an exponential rate and that the infection rate is frequency dependent while we supposed a memory fading at a linear rate and a density dependent infection rate. In all cases, our model is the first to show that confirmation bias can strongly facilitate cyclical dynamics. The propensity to seek out information that confirms one’s pre-existing belief, and the possibility for individuals to change their opinion as a function of the number of vaccinated individuals (i. e. confirmation bias) can thus explain variation into vaccination coverage. When vaccination coverage increases, the cost of vaccination increases too as more individuals suffer vaccination side effects. It leads to a rise in the number of individuals who become sceptical about vaccines. Those “sceptics” are more likely to overestimate the cost of vaccination as compared to that of infection, and thus when most of the population is vaccinated; sceptics perceive the infection as harmless. Eventually, this phenomenon leads to a decrease in vaccination coverage and subsequently, to the resurgence of diseases. In turn, as the number of infected individuals increase, a “pro-vaccine” opinion spreads leading to an increase in vaccination coverage. Those results are not different from those obtained in other models where vaccine cost appears large in comparison to that of infection as the population approaches herd immunity [41]. However, in some previous theoretical studies, the cost of vaccination does not change as a function of the number of people vaccinated. Rather, the increase in vaccination cost is imposed using an exogenous description of the evolution of vaccine risk [41], the inclusion of a cyclical period to simulate a vaccine scare [27,39] or through a decrease in the accessibility of vaccines [37,42,43]. While previous studies showed that a vaccine scare could lead to a decrease in vaccination coverage, the present model explicitly articulates a mechanism creating a vaccine scare (i. e. when the cost of vaccination is perceived to be greater than that of the infection cost).

Output: corroborate


Input: Claim: Blockchain technology will make manual labor in the supply chain industry obsolete. [SEP] Text: Additionally, a reliable identity management mechanism [53] allows for the collection of time, location, and other data at every action on a product in the supply chain. All data are synchronized to all stakeholders in real-time, which enhances trust among stakeholders within the supply chain network. Easy compliance: A blockchain-enabled supply chain network records all transactions with precise details, such as timestamps, environmental conditions, and location. These accurate, tamper-proof records can serve as the source of a business’s data integrity and be easily accessed for regulations and compliance. 4. 2 Challenges with blockchain technologyAlthough blockchain technology is widely recognized as a promising solution for issues with today’s supply chain, the application of it requires significant changes in both technological and cultural contexts. Additionally, more comprehensive evaluations of it are needed to unveil and address its challenges before the full potential of this new technology can be realized [22, 57]. Throughput and performance: Due to its decentralized architecture, each transaction is approved by all or a majority of nodes in a blockchain network. This approval process limits the throughput of a blockchain network; for example, Bitcoin, a public blockchain, can only process from 3 to 30 transactions per second. However, a private blockchain-based supply chain network must process far more transactions, possibly thousands per second, for the entire system. Thus, it is imperative to improve the transaction capacity of blockchain technology for full scalability. Fortunately, a private blockchain network’s ability to improve the throughput of transactions may mitigate this processing challenge. Standardization: Standardization is a critical concern for the adoption of blockchain technology in the supply chain. In essence, this technology offers a ubiquitous and general-purpose platform for digital data sharing and permanent storage. Interestingly, a major question still remains: what content and format should be adopted for transactional data that facilitates interpretation by all participants? A data standard must be established and agreed upon by the entire supply chain community. However, there is no existing standard that can be adapted for this purpose. In recent years, much effort, such as EPCIS [58] that proposed GS1, has been made to overcome this gap, however, it is still not widely accepted and implemented in supply chains. Data privacy: The immutability and transparency of blockchain technology raise a concern with data privacy when deployed for supply chains.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: Human mobility data in the COVID-19 pandemic: characteristics, applications, and challenges. of Digital Earth. 2021;14(9):1126-47. 5. Yang B-Y, Zhao T, Hu L- Greenspace and human health: An umbrella review. The Innovation. 2021;2(4). 6. . Where greenspace matters most: A systematic review of urbanicity, greenspace, and physical health. Landscape and Urban Planning. 2022;217:104233. 7. Exploring pathways linking greenspace to health: Theoretical and methodological guidance. Environmental Research. 2017;158:301-17. 8. An ecosystem service perspective on urban nature, physical activity, and health. Proceedings of the of Sciences. 2021;118(22):e2018472118. 9. Diener A, Mudu P. How can vegetation protect us from air pollution? A critical review on green spaces' mitigation abilities for air-borne p8605. 10. . and Temperature? . 2020;17(14). 11. Hofferth SL. Changes in American children's time - 1997 to 2003. . 2009;6(1):26-47. 12. Children and Adolescents and Digital Media. Pediatrics. 2016;138(5):e20162593. 13. . Outdoor Time, Screen Time, and Connection to Nature: Youth? Environment and Behavior. 2018;51(8):966-91. 14. . Evidence for a fundamental and pervasive shift away from nature-based recreation. Proceedings of the of Sciences. 2008;105(7):2295-300. 15. . Editorial JTH 16 --19 and implications for transport and health. J Transp Health. 2020;16:100853. 16. . Bias and precision of crowdsourced recreational activity data from Strava. Landscape and Urban Planning. 2023;232:104686. 17. . Access to Space in Cities of the Global South: A Review. [Internet]. 2018; 2(3). 18. Bessell S. The impacts of COVID-19 on children in Australia: deepening poverty and inequality. Children's Geographies. 2022;20(4):448-58. 19. Economic and social consequences of human mobility restrictions under COVID-19. Proceedings of the of Sciences.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: The results reported here are contingent on the assumption that the vaccination decision-making process is sensitive to a confirmation bias. This cognitive phenomenon is only one among several, however, as other heuristics have been documented in previous research on vaccine acceptance [25,44], for instance omission bias (when people prefer act of omission over act of commission, even if the outcome of omission is worse) or ambiguity aversion (aversion of ambiguous outcomes). Further work explicitly comparing the significance of various cognitive biases may yield additional insight into the role of cognition in generating vaccine scares. Social learning and vaccinating decision-making A number of previous studies have investigated the role of social interactions in shaping the emergence of oscillations in vaccination coverage [13,17,27,29,35,45,46]. This is because vaccination coverage can be relatively stable in the absence of a vaccine scare and the feedback between the number of infected individuals and vaccination behaviour appears insufficient in accounting for the delay between reaching high vaccination coverage and the emergence of a scare. To account for the role of social interactions, behavioural epidemiology models usually consider that individuals imitate the most successful strategy among their neighbouring contacts [39,47] and such models are better than models considering a homogenous population for fitting data on vaccine scares [41]. The way social learning is modelled explicitly considers that individuals are rational agents maximizing their payoff. Individuals can be influenced by social interactions in different ways, however, and the role of social influence need not be connected to epidemiological risks [48]. For instance, it has been argued that mothers taking their children for vaccination has become part of their “habitus” (sensu Bourdieu, in [34]). Mothers elicit to vaccinate their children because “everyone else does” and ethnographic studies on the acceptance of vaccines in various populations revealed that peer opinion matters [34]. In the model developed here, individuals adopt the most common opinion in the population through the phenomenon of conformism. Conformism does not generate oscillations in vaccination coverage but increases the amount of time needed for a change in epidemiology to generate a cultural response. The role of conformism in increasing the time for cultural change has been observed in previous studies [39]. Limitations First, the model presented here assumes that both infection and health behaviour are transmitted within a homogeneously mixing population, and those are simplifying assumptions.

Output: corroborate


Input: Claim: Blockchain technology will make manual labor in the supply chain industry obsolete. [SEP] Text: Once data are stored in blockchains it cannot be changed, and, thus, it is imperative that a reliable mechanism that protects users’ privacy is designed. The task of balancing an individual’s right to privacy in an open blockchain network is very challenging. Currently, most blockchain networks, such as Bitcoin, provide limited control to users over the data and where they can transfer it to [22]. Most networks offer only pseudonymity to its users for privacy, so, although transactions are public for all nodes, the real identity of their owners is never revealed. This is unacceptable for supply chains, as nobody is willing to leak information to competitors about Confidential detail or the amount of merchandise moving in a network. Furthermore, with the limited number of stakeholders in the supply chain, it would be easy to figure out the owner of the transactional data and anonymity would disappear. To address this, private blockchain technology (such as Hyperledger Fabric) can support the creation of a channel for limited and trusted parties who are involved in specific transactions [44]. In this way, an unauthenticated user is forbidden to join the channel or access its data. It should be noted that a blockchain network can be designed to only serve as metadata of the workflow and the contents and details of all transactions within it are stored in external data repositories. Therefore, this technology provides a log of transactions on which no private data are stored [13]. 4. 3 Pilot initiativesSince late 2016, retail giants Walmart and IBM worked together for a pilot project to develop a blockchain-based system for tracking produce in the U. S. and pork in China. The project traced each product and collected its associated data, including origin farm/factory, storage temperature, and serial number. With this technology, tracking reports for each product were produced within minutes and the speed and accuracy of identifying and recalling contaminated food products were significantly improved [59]. 31, 2017, Walmart released the results of this pilot project and reported that blockchain technology helped them trace the origin of Chinese pork and U. S. mangoes in 2. 2 seconds, which would normally take as long as several weeks in a traditional supply chain platform [60]. Intel conducted a public demo to explore the implementation of blockchain technology for tracking seafood in the supply chain. They aimed to create a network that assists multiple parties with food storage condition (i. e. , temperature) control and with tracking food from sea to table.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: 2020;117(27):15530-5. 20. Chen Y- in California by the COVID-19 Pandemic. of Preventive Medicine. 2022. 21. Wang Z, Tang K. -19: health equity matters. Nature Medicine. 2020;26(4):458-. 22. Racial and in COVID-19–Related Infections, Hospitalizations, and Deaths. Annals of Internal Medicine. 2020;174(3):362-73. 23. Yancy CW. COVID-19 and African Americans. JAMA. 2020;323(19):1891-2. 24. Statistics Norway. Land use and land cover 2022 [Available from: 25. . Validation of the normalized difference vegetation index as a measure of neighborhood greenness. Ann Epidemiol. 2011;21(12):946-52. 26. Didkan K. MODIS/Indices 16-Day L3 Global 250m SIN Grid V061 [Data set]. . 2021 [ 27. Muñoz Sabater J. ERA5-Land hourly data from 1981 to present. (C3S) Store (CDS). 2019 [ 28. Pedersen W, Bakken A, von Soest T. Adolescents from affluent city districts drink more alcohol than others. Addiction. 2015;110(10):1595-604. 29. . Regression and other stories: Press; 2020. 30. . Nature's contributions in coping with a pandemic in the 21st century: A narrative review of evidence during COVID-19. Science of Environment. 2022;833:155095. 31. von Soest T, Kozák M, Rodríguez-és-García L, Ulset VS, et al. Adolescents’ psychosocial well-being one year after the outbreak of the COVID-19 pandemic in Norway. Behaviour. 2022;6(2):217-28. 32. . Visits and Barriers to Visiting during the COVID-19 Pandemic: A Three-Representative Cross-of UK Adults. Land [Internet]. 2022; 11(4). 33. ä M. Crisis: Use in and During the COVID-19 Pandemic. Frontiers in Sustainable Cities. 2021;3.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: Humans are connected with a limited number of contact [49] and a number of studies has considered that social heterogeneity influences disease transmission [14,50,51], risk perception [15,20,52] and vaccination behaviour [15,48,53]. Clustered occurrence of beliefs can lead to the clustered occurrence of disease [54]. Nevertheless, in the context of information transmission, the assumption according to which the population is homogeneously mixed is valid if we focus on the role of the media, i. e. information that is globally available to everyone. The media has had a central role in disseminating vaccine scares and shaping the perception of disease severity [18]. The media also enables anti-vaccination movements to have a strong impact on vaccination decision-making [7,55]. Yet, if the proposed model may be appropriate for exploring the role of conformism, it is insufficient to explore other social transmission processes such as those resulting from the role of opinion leaders (e. g. cultural transmission through prestige-bias [56]). Religious leaders have been shown to be highly influential in promoting vaccine refusal in their communities (reviewed in [34]) and the role of prestige-biased cultural transmission for either accelerating the pace of change or stopping it altogether remains to be investigated. Second, one may argue that since the costs depend on the number rather than the frequency of individuals suffering side effects, the model is more likely to inform on information that is gathered during social interactions than knowledge acquired via the media. The media report both percentages and anecdotic evidence of side effects associated with vaccination and both are likely to be determinant in driving the formation of opinion. Yet, the relative role of each type of information deserves further investigation. Finally, we assumed that the rate of opinion change, while a function of epidemiological costs, is independent of the SIR class of the individual. However, an individual suffering infection may be less likely to switch from a positive to a negative opinion and thus we may have overestimated the occurrence of oscillations. Note however that for diseases with a strong epidemic potential, the cost of infection is always higher than that of vaccination and therefore oscillations do not emerge. This study, along a few others [22,28,29,48], offers an alternative to payoff maximization for understanding the emergence of oscillations in vaccination coverage.

Output: corroborate


Input: Claim: Artificial intelligence can identify and stop every cybersecurity threat before it happens. [SEP] Text: Abstract2021, the Commission published a draft proposal for a regulation on artificial intelligence (AI) systems aimed at striking a balance between the market need for a competitive and dynamic ecosystem and the need to minimise risks to the safety and fundamental rights of users and citizens. Among the set of obligations that apply to high-risk AI technologies, the AI Act includes a specific provision addressing the security and robustness of AI systems. This provision overlaps with existing legislation addressing cybersecurity, namely the certification process defined in Regulation 2019/881 on the Agency for Cybersecurity and on information and communication technology cybersecurity certification. Although the AI Act hints at a possible path towards mutual recognition of certifications, a deeper analysis of the provisions and a comparison between the underlying features of the certification mechanisms show that the different approaches adopted in the two acts may undermine the goal of certification mechanisms as trust-enhancing and transparency instruments. As a result, this paper provides evidence of the missed opportunity for the AIA proposal to link and coordinate in a more structured way with the cybersecurity framework. This is a preview of subscription content, log in via an institution to check access. Access this 34. 9910 units per month Download 39. 95 Price excludes VAT (USA) Tax calculation will be finalised during checkout. Instant access to the full 10. 1365/s43439-022-00053-yNotesSee the first reactions to the AIA Proposal by academics and civil society: Burri and von Bothmer (2021); Glauner (2021); Greenleaf (2021); Ebers (2021); BEUC (2021); EDRi (2021); ECNL (2021a). (2018). (2020a). (2020b). (2020c). (2020d). Note that the distinction is presented in the Explanatory memorandum to AIA, p. 12. See also Vaele and (2021, p. 3). See Art. 5 AIA. The definition of high-risk technologies includes a non-exhaustive list provided in Annex III of the AIA. The annex lists inter alia biometric identification and categorisation of natural persons, AI used in law enforcement activities, in migration, asylum and border control management, and in the administration of justice and democratic processes.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: 1 Results from multilevel mixed model analysis Daily dwells Fixed effects Model 1 Model 2 Model 3 Model 4 Intercept 4. 62 *** 4. 64 *** 4. 64 *** 4. 61 *** Covid dummy 0. 01 *** -0. 05 *** -0. 05 *** -0. 04 *** NDVI -1. 07 *** -1. 06 *** -0. 99 *** Neighborhood SES -0. 11 *** -0. 09 *** -0. 15 *** Neighborhood population density 0. 03 *** 0. 05 *** 0. 06 *** School holiday 0. 09 *** 0. 09 *** 0. 09 *** Public holiday 0. 01 *** 0. 01 *** 0. 01 *** Winter -0. 03 *** -0. 03 *** -0. 03 *** Summer 0. 03 *** 0. 03 *** 0. 03 *** Autumn -0. 02 *** -0. 02 *** -0. 02 *** Snow depth -0. 14 *** -0. 14 *** -0. 14 *** Solar radiation 0. 09 *** 0. 09 *** 0. 09 *** Temperature (celsius) 0. 10 *** 0. 10 *** 0. 10 *** Windspeed -0. 04 *** -0. 04 *** -0. 04 *** Covid dummy * NDVI 0. 14 *** 0. 05 *** Covid dummy * NDVI * Neighborhood SES -0. 12*** Covid dummy * NDVI * Neighboorhood population density 0. 04*** σ2 0. 29 0. 27 0. 27 0. 27 τ00 grid 1. 27 1. 18 1. 18 1. 18 τ00 neighborhood 0. 51 0. 24 0. 24 0. 24 ICC 0. 86 0. 84 0. 84 0. 84 N grid 12083 11979 11979 11979 N neighborhood 1459 1459 1459 1459 Observations 10 325 610 10 325 610 10 325 610 10 325 610 Marginal R2 Conditional R2 0. 000 0. 860 0. 164 0. 867 0. 165 0. 867 0. 175 0. 870 * p<0. 05 ** p<0. 01 *** p<0. 001 Supplementary FilesGraphicalabstract. pngGraphical abstract:PostedVersion 3posted You are reading this latest preprint versionShow more versionslets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal.

Output: pass


Input: Claim: Cognitive biases influence decision-making and perception. [SEP] Text: It shows that a decrease in vaccine uptake when a disease is near eradication may not only emerge because of individual free riding but because of cognitive biases that maintain heterogeneity in how people perceive risks. While this study presents limitations that need to be explored in future work, i. e. considering heterogeneity in contact patterns as well as additional cognitive biases, we show that alternative notions of rationality, in particular that of an ecological rationality whereby individuals use simple cognitive heuristics, offer interesting new avenues for modelling vaccination behaviour. Supporting InformationS1 Fig. The effect of confirmation bias on oscillations. The effect of confirmation bias (i. e. with μ the weight given to the cost of infection and μ′ the weight given to the cost of vaccination) on the dynamics of susceptible (solid grey line), infected (thin line) and vaccinated individuals (thick line) is depicted. The amplitude and the frequency of oscillations are modified when the difference between μ and μ′ is high. Indeed, the bigger the difference between μ and μ′, the more the amplitude of oscillations increases and the more the frequency decreases. The situation is indicated for infections that are moderately infectious, with 2 reproductive ratio R0, 3 and 6 and with a rate of negative side effects from the vaccination δV = 1. S2 Fig. The effect of conformism and confirmation bias on the appearance of oscillations. The effect of conformism biased (D = 0. 7) and unbiased (D = 0) is depicted with and without confirmation bias. The number of susceptible individuals is represented by the solid grey line, the infected individuals by the thin line and the number of vaccinated individuals by the thick line. Without confirmation bias (μ = μ′ = 1), oscillations do not appear for both types of conformism (biased and unbiased). When the confirmation bias is added, oscillations do appear with no significant differences between the biased and unbiased conformism. The situation is indicated with the reproductive ratio R0 = 3 and with a rate of negative side effects from the vaccination δV = 1. 1. . Modelling the influence of human behaviour on the spread of infectious diseases: a review. J R Soc Interface. 2010. 1256. pmid:20504800 View 2. Bauch C, D’Onofrio A, Manfredi P. Behavioral epidemiology of infectious diseases: an overview.

Output: corroborate


Input: Claim: Artificial intelligence can identify and stop every cybersecurity threat before it happens. [SEP] Text: 41(2) AIA. See Art. 58 AIA. Note that the composition of the Board includes only representatives of the national regulatory authorities, with the possibility of involving external experts and observers only on request. Therefore, the European AI board also does not adopt a more inclusive approach to potential stakeholders. See Art. 43(1) AIA. As previously mentioned, Art. 40 AIA acknowledges that compliance with harmonised standards should be presumed to be in conformity with the regulation’s requirements. Note that point 4. 5 of provides that on a reasoned request the notified authority shall also be granted access to the source code of the AI system. Moreover, AI can play a major role in cybersecurity not only as a subject, i. e. as a technology that should be made responsive, robust and resilient to cyberthreats, but also as a tool able to ensure the responsiveness, robustness and resilience of other technologies. See Taddeo, McCutcheon and Floridi (2019). See also rec. 51 AIA, affirming “Cyberattacks against AI systems can leverage AI specific assets, such as training data sets (e. g. data poisoning) or trained models (e. g. adversarial attacks), or exploit vulnerabilities in the AI system’s digital assets or the underlying ICT infrastructure. To ensure a level of cybersecurity appropriate to the risks, suitable measures should therefore be taken by the providers of high-risk AI systems, also taking into account as appropriate the underlying ICT infrastructure”. Note that ENISA (2020b), on the other hand, acknowledges the interdependencies between AI and cybersecurity, distinguishing three main dimensions: cybersecurity for AI; AI to support cybersecurity; and malicious use of AI. (2020b, p. 27). Kamara (2020). 19. org/resources/eu-artificial-intelligence-and-human-rights/. Accessed 11 Oct 2021BEUC (2021) Regulating AI to protect consumers—Position paper on the AI act. Accessed 11 Oct 2021Burri T, von (2021) The new EU legislation on artificial intelligence: a primer. Accessed 11 Oct 2021Daskalova V, (2019) Challenges for responsible certification in institutional context: the case of competition law enforcement in markets with certification. In: (ed) Certification—Trust, accountability, liability. Springer, Cham, pp 23–710378.

Output: contrast


Input: Claim: Access to green spaces is linked to increased physical activity. [SEP] Text: 1078/1618-8667-00019. 850. 10. 1016/j. healthplace. 2007. 02. 001. 10. 1136/jech. 2009. 104695. 123. 10. 1016/S0272-4944(02)00109-3. 230. 10. 1016/S0272-4944(05)80184-7. 146. 10. 1016/S0272-4944(02)00111-1. 858. 10. 1177/001391659803000605. 595. 10. 1016/j. healthplace. 2008. 09. 006. 199. 10. 1016/S0749-3797(01)00426-3. 354. 10. 1080/01490400701394865. 189. 10. 1111/j. 1467-789X. 2010. 00827. x. 822. 10. 1016/j. socscimed. 2009. 11. 020. 1132. 10. 1016/j. puhe. 2006. 10. 007. 1041. 10. 1016/j. healthplace. 2012. 06. 003. 10. 1186/1471-2458-8-206. 505. 10. 1016/j. ypmed. 2009. 10. 012. 10. 1136/jech. 2007. 064287. 10. 1186/1479-5868-6-42. 515. 10. 1016/j. amepre. 2011. 06. 046. 438. 10. 1016/j. amepre. 2009. 12. 032. 594. 10. 1016/j. healthplace. 2012. 01. 006. 1660. 10. 1016/S0140-6736(08)61689-X. 1. 2009, Edinburgh: 134. 575. 10. 1016/j. socscimed. 2010. 04. 015. 858. 10. 1136/jech. 2010. 119172. 2010. 2010, Edinburgh: Office of the 303. 10. 1016/j. ypmed. 2008. 04. 010. 176. 1757. 10. 2105/AJPH. 2009. 182006. 1589. 10. 2105/AJPH. 93. 9. 1583. 51. 10. 1016/j. ufug. 2007.

Output: pass