Role Of Uncertainty Research Articles

Food insecurity and sovereignty threat to uncontrolled price spillover effects in financialized agricultural products: The red meat case in Turkiye

The objective of this study is to examine the long-term uncertainty transmission between cattle and lamb carcass markets and the feed wheat market in terms of exogenous variables (e.g., gasoline price, exchange rate, and import variables) and whether the volatility is symmetrical, using the daily data from January 2005 to June 2019, and VAR (1)–BEKK–GARCH (1, 1) Model. The empirical results indicate that short- and long-term indirect and direct shocks and long-term uncertainty propagation significantly affect the conditional variances of the beef carcass, lamb carcass, and feed wheat returns, which poses a threat to producers in terms of product sovereignty and consumers in terms of food security. We also discovered that the conditional variances of the beef carcass, lamb carcass, and feed wheat returns were significantly affected by any increase in foreign exchange rates in times of import in comparison with those in the times of nonimport. Similarly, the fluctuations in the energy (gasoline) market increased the ongoing risk propagations in the lamb carcass and feed wheat markets, whereas they decreased it in the beef carcass market. Meanwhile, asymmetrical effects played a role in uncertainty in transitions for product markets. Additionally, the optimal portfolio weight of beef carcasses on lamb carcasses and feed wheat was 0.645 and 0.553, respectively, whereas the optimal portfolio weight of lamb carcasses on feed wheat remained at approximately 0.188.

Making sense of uncertainty: The precarious lives of young migrants from rural Kwazulu-Natal, South Africa

ABSTRACT This study aims to examine the experiences of young migrants and the role of uncertainty in their precarious lives. Drawing on data from individual interviews and a workshop with young migrants aged 16–24 years old in KwaZulu-Natal, South Africa, we use uncertainty as a theoretical lens, to illustrate the ways in which young migrants’ experiences provide meaning for them and give them an opportunity to assess, and plan for better opportunities despite the stark outlook. Thematic analysis was used to examine the multidimensionality of socio-spatial identities in young migrants. The findings illustrate how young migrants hustle for opportunities to lead valuable lives in the face of uncertainty. The implications highlight how attending to the complex intersectional nuances of uncertainty can serve as an enabler of aspirations, alongside essential structural factors influencing migration among young people brought up in rural communities. However, in proposing this alternative view of positive uncertainty, the structural violence experienced by these young people should not be overlooked and should be addressed as per their context.

Supplemental Material for Parent Psychosocial Adjustment to Inpatient Pediatric Rehabilitation, and the Role of Uncertainty and Self-Care

Supplemental Material for Parent Psychosocial Adjustment to Inpatient Pediatric Rehabilitation, and the Role of Uncertainty and Self-Care

The role of uncertainty and affect in decision-making on the adoption of AI-based contact-tracing technology during the COVID-19 pandemic.

This study explores how negative affect, perceived net equity, and uncertainty influence the public's privacy decision-making regarding the adoption of contact-tracing technology based on artificial intelligence (AI) during the COVID-19 pandemic. Four hundred and eighteen adults in the US participated in the study via Amazon Mechanical Turk in August 2020. Statistical analyses were performed using the PROCESS macro. Indirect effects and their significance were estimated using bias-corrected bootstrap confidence intervals (CIs) with resampling set to n = 5000. Perceived net equity was positively associated with low levels of perceived uncertainty regarding a COVID-19 contact-tracing application and intention to adopt it. Low levels of perceived uncertainty were positively associated with intentions to adopt such an application, thereby suggesting that a perceived level of uncertainty mediates the association between perceived net equity and adoption intentions. Anxieties regarding AI technology and COVID-19 risks both moderate the associations among perceived net equity, perceived level of uncertainty, and intentions to adopt the contact-tracing technology. Our findings highlight how the differing sources of emotion influence the associations among rational judgment, perceptions, and decision-making about new contact-tracing technology. Overall, the results suggest that both rational judgments and affective reactions to risks are important influencers of individuals' perceptions and privacy-related decision-making regarding a new health technology during the pandemic.

The role of uncertainties on sustainable stocks and green bonds

PurposeThis paper aims to investigate the relationship between sustainable investments and a series of uncertainties from January 2014 to December 2021, including many economic and political turbulences and the COVID-19 pandemic.Design/methodology/approachThe authors use Rényi’s transfer entropy method, a nonparametric flexible tool that considers both the center distribution and lower quantiles, capturing extreme rare events that give additional insights to analysis.FindingsThe authors’ results indicate significant bidirectional information transmissions between the crude oil volatility and sustainability indices. The authors report information flows between the cryptocurrency uncertainty and sustainability indices considering tail events. The results are essential for market participants making decisions during turbulent times.Originality/valueThis paper is carried out for a variety of uncertainty measures and environmental, social and governance (ESG) portfolios of both developed and developing markets. It adds to literature in terms of methodology used. Rényi’s transfer entropy methodology is first used to measure the relationship between uncertainties and ESG investments.

Sensitivity of modelled cometary gas production on the properties of the surface layer of the nucleus

ABSTRACT Explanation of the observed gas activity based on the parameters of the comet’s nucleus is not an obvious matter. Solutions based on certain thermal models can be obtained, but the use of arbitrary values for poorly known model parameters is always required. In this work, we carry out a study of the dependence of gas activity on these parameters and assess the importance of each of them. We consider model porous dust layers of diverse structures. Solid state and gas thermal conductivities are examined to estimate the possible range of effective thermal conductivity. The simulation results are embedded in a thermal model, explicitly including a radiative thermal conductivity and a resistance of the dust layer against the gas flow. Sublimation of water ice and supervolatiles (CO2 and CO) is tested at different heliocentric distances. It is shown that when sublimation is the main energy sink, the role of uncertainties in the structure of the layer is small. As the relative contribution of sublimation decreases, the scatter of solutions reaches tens of per cent. The expected large uncertainties in the effective thermal conductivity can also significantly change the gas production. The analysis performed shows that, in spite of the parameter range having been narrowed down by results from the Rosetta mission, the unavoidable uncertainty in the values of some model parameters (e.g. thermal conductivity) blurs the theoretical simulation estimates. Instead of presenting a narrow set of specific solutions, it is desirable to analyse the entire range of possible solutions.

Time-varying dependence between Bitcoin and green financial assets: A comparison between pre- and post-COVID-19 periods

This paper studies the time-varying market linkages between Bitcoin and green assets before and during the COVID-19 pandemic through a TVP-VAR model with stochastic volatility. Both the roles of uncertainty and environmental attention related to cryptocurrency are considered when modeling market linkages, which underlying asymmetry is detected from three perspectives, i.e., bidirectionality of the impact direction, time points where the unit shock of the IRF analysis is imposed, and before and after the pandemic. We find that the investment sheltering role of Bitcoin for green assets is enhanced and expanded after the onset of the pandemic, while green assets in turn consistently act as an effective hedge for Bitcoin irrespective of the pandemic. Additional analyses confirm the robustness of our findings, which possess implications for not only hedging against green portfolios but also seeking green shelters.

Polyethylene density uncertainty in the simulation of neutron detectors

Simulations with the Monte Carlo N-Particle® (MCNP®) code are frequently used to study neutron coincidence counters for international safeguards. Reducing sources of uncertainty enables more accurate simulations, which reduces the need for expensive or impossible measurements. Accurately specifying the density of polyethylene is crucial for accurate simulations. The density of polyethylene ranges from 0.88 to 0.97 g/cm3 and high-density polyethylene (HDPE) ranges from about 0.944 to 0.965 g/cm3. The density of a specific detector should be measured exactly for the best simulations. The density of the blue/white Active Well Coincidence Counter (AWCC) bulk polyethylene was measured to be 0.9594 +- 0.0013 g/cm3 at 1-sigma confidence. The density was calculated from repeated measurements of the various polyethylene dimensions for volume, and weighing the polyethylene for the mass.The AWCC neutron detection efficiency was simulated for each polyethylene density. The relative range of efficiencies (3σ) was 3.4% for unspecified polyethylene, 0.9% for HDPE, and 0.3% for the measured density. The impact of modeling small features such as screws was also studied and was found to be a negligible 0.2%. Measuring polyethylene density can reduce its role in uncertainty from one of the largest to one of the smallest contributors.

A Role for Uncertainty in the Neural Distinction Between Social and Nonsocial Thought

Neuroimaging research has identified a network of brain regions that is consistently more engaged when people think about the minds of other people than when they engage in nonsocial tasks. Activations in this “mentalizing network” are sometimes interpreted as evidence for the domain-specificity of cognitive processes supporting social thought. Here, we examine the alternative possibility that at least some activations in the mentalizing network may be explained by uncertainty. A reconsideration of findings from existing functional MRI studies in light of new data from independent raters suggests that (a) social tasks used in past studies have higher levels of uncertainty than their nonsocial comparison tasks and (b) activation in a key brain region associated with social cognition, the dorsomedial prefrontal cortex (DMPFC), may track with the degree of uncertainty surrounding both social and nonsocial inferences. These observations suggest that the preferential DMPFC response observed consistently in social scenarios may reflect the engagement of domain-general processes of uncertainty reduction, which points to avenues for future research into the core cognitive mechanisms supporting typical and atypical social thought.

Macroeconomic uncertainty indicators for Russia

The role of uncertainty as one of the key channels for transmission of shocks, such as financial shocks in 2008—2009, pandemic in 2020—2022, or sanctions, is regularly highlighted by experts and international organizations. How to measure uncertainty and its effects in practice? Indicators based on financial variables, text analysis of media publications, variance in expert forecasts or firms’ expectations have been traditionally used for these purposes. This paper uses an alternative approach for the Russian case. Uncertainty is estimated as “unforecastibility” of future economic dynamics, that is, as a weighted average of standard deviations of forecast errors for the wide range of macroeconomic and macrofinancial variables. The forecasts are constructed through a factor model based on “big data”. The estimated uncertainty indicators for 1, 3 and 12 months ahead show stronger persistence and countercyclicality compared to alternative indicators. Significant impact of uncertainty shocks on output and CPI is demonstrated, underscoring the need for analysis of mutual impact of uncertainty and effectiveness of countercyclical economic policies.

Community acceptance and social impacts of carbon capture, utilization and storage projects: A systematic meta-narrative literature review.

This manuscript presents a systematic meta-narrative review of peer-reviewed publications considering community acceptance and social impacts of site-specific Carbon Capture Utilization and Storage (CCUS) projects to inform the design and implementation of CCUS projects who seek to engage with communities during this process, as well as similar climate mitigation and adaptation initiatives. A meta-narrative approach to systematic review was utilized to understand literature from a range of site specific CCUS studies. 53 peer-reviewed papers were assessed reporting empirical evidence from studies on community impacts and social acceptance of CCUS projects published between 2009 and 2021. Three separate areas of contestation were identified. The first contestation was on acceptance, including how acceptance was conceptualized, how the different CCUS projects engaged with communities, and the role of acceptance in social learning. The second contestation related to communities: how communities were represented, where the communities were located in relation to the CCUS projects, and how the communities were defined. The third contestation was around CCUS impacts and the factors influencing individuals' perceptions of impacts, the role of uncertainty, and how impacts were challenged by local communities, politicians and scientists involved in the projects. The next step was to explore how these contestations were conceptualised, the aspects of commonality and difference, as well as the notable omissions. This facilitated a synthesis of the key dimensions of each contestation to inform our discussion regarding community awareness and acceptance of CCUS projects. This review concludes that each CCUS project is complex thus it is not advisable to provide best practice guidelines that will ensure particular outcomes. This systematic review shared recommendations in the literature as to how best to facilitate community engagement in relation to CCUS projects and similar place-based industrial innovation projects. These recommendations focus on the importance of providing transparency, acknowledging uncertainty and encouraging collaboration.

(Re)Conceptualising ‘good’ proxy decision-making for research: the implications for proxy consent decision quality

People who are unable to make decisions about participating in research rely on proxies to make a decision based on their wishes and preferences. However, patients rarely discuss their preferences about research and proxies find it challenging to determine what their wishes would be. While the process of informed consent has traditionally been the focus of research to improve consent decisions, the more conceptually complex area of what constitutes ‘good’ proxy decision-making for research has remained unexplored. Interventions are needed to improve and support proxy decision-making for research but are hampered by a lack of understanding about what constitutes decision quality in this context. A global increase in conditions associated with cognitive impairment such as dementia has led to an urgent need for more research into these conditions. The COVID-19 pandemic and subsequent necessity to conduct research with large numbers of critically ill patients has made this need even more pressing. Much of the empirical research centres on the desire to improve decision accuracy, despite growing evidence that authenticity is more reflective of the aim of proxy decisions and concerns about the methodological flaws in authenticity-focused studies. Such studies also fail to take account of the impact of decision-making on proxies, or the considerable body of research on improving the quality of healthcare decisions. This paper reports a concept synthesis of the literature that was conducted to develop the first conceptualisation of ‘good’ proxy decisions about research participation. Elements of decision quality were identified across three stages of decision-making: proxy preparedness for decision-making which includes knowledge and understanding, and values clarification and preference elicitation; the role of uncertainty, decisional conflict, satisfaction and regret in the decision-making process; and preference linked outcomes and their effect. This conceptualisation provides an essential first step towards the future development of interventions to enhance the quality of proxy decision-making and ensure proxy decisions represent patients’ values and preferences.

A multi-objective location-routing model for dental waste considering environmental factors.

Nowadays, the amounts of infectious medical waste (IMW) have surged considerably so waste management has become a critical emergency in many developing countries. However, most large medical waste generation centers (MWGC) are equipped with treatment facilities, small MWGC faces the waste management problem. It reveals the significance of having a proper program for small health centers. This is an indisputable difficulty that governments bordered because it imposes great costs on societies, also the environmental problems caused by improper treatment are irreparable. To attend to all the essential aspects of the problem, this paper recommended a location-routing model with four objective functions to minimize the total costs, environmental pollution, the risk imposed on the population around disposal sites, and the total violation from the expected arrival time. Considering a multi-period problem with a maximum acceptable delay plays a key role to connect the assumptions to the real-world problem. In addition, for solving mathematical models based on case studies, the role of uncertainty is undeniable. The demand for dental waste treatment is not definite and is changed based on the different conditions thus fuzzy chance-constrained programming is proposed for this problem to tackle the uncertainty. The revised multi-choice goal programming method is considered to solve the model and a real case study for dental clinics in Babol city of Iran is investigated to illustrate the validation of the proposed model. The results indicate that the solution method can create a balance between four objective functions. Finally, sensitivity analyses are performed for some parameters to analyze the behavior of the objective functions.

The Role of Uncertainty in Shaping Individual Preferences for Residential Energy Renovation Decisions

This article examines a crucial question that has been raised in recent years in both policy and economic literature: the role of uncertainty as a barrier to energy retrofit decisions. We develop a discrete choice experiment to elicit preferences for energy renovation measures. This methodologically innovative experiment design includes two insurance schemes covering potential sources of uncertainty as attributes of the energy retrofit alternatives. We use a mixed logit model to investigate the nature of systematic heterogeneity in household preferences for attributes of energy retrofit solutions. The article shows that uncertainties related to future energy pricing and retrofit quality are negatively perceived during energy-renova-tion decision making. This impact varies according to household characteristics such as risk aversion and perceptions of the economic context. The results suggest that public policies should support and accompany the development of insurance schemes to increase energy renovation rates.

Time series estimation of the dynamic effects of disaster-type shocks

This paper provides three results for SVARs under the assumption that the primitive shocks are mutually independent. First, a framework is proposed to accommodate a disaster-type variable with infinite variance into a SVAR. We show that the least squares estimates of the SVAR are consistent but have non-standard asymptotics. Second, the disaster shock is identified as the component with the largest kurtosis. An estimator that is robust to infinite variance is used to recover the mutually independent components. Third, an independence test on the residuals pre-whitened by the Choleski decomposition is proposed to test the restrictions imposed on a SVAR. The test can be applied whether the data have fat or thin tails, and to over as well as exactly identified models. Three applications are considered. In the first, the independence test is used to shed light on the conflicting evidence regarding the role of uncertainty in economic fluctuations. In the second, disaster shocks are shown to have short term economic impact arising mostly from feedback dynamics. The third uses the framework to study the dynamic effects of economic shocks post-covid.

The Role of Uncertainty in Shaping the Relationship between Direct Investments and International Trade: Evidence from VAR Models

In this study, we test whether uncertainty shocks can affect the choice between direct investments and international trade as competitive modes of operating on foreign markets. In order to verify this, we built simple investments-to-trade ratios and used them with selected uncertainty measures in VAR models. Our analysis shows that in the case of the Polish manufacturing sector, different types of uncertainty not only affect the choice between direct investments abroad and exports but also affect the choice between foreign direct investment and imports as different modes of supplying the Polish market by foreign entities.

Goal Disruption and Psychological Disequilibrium During the Outbreak of COVID-19: The Roles of Uncertainty, Information Seeking and Social Support

ABSTRACT Using panel data from mainland China, this study incorporates uncertainty, information seeking, and social support into the goal disruption theoretical model to examine the indirect influence of goal disruption on psychological disequilibrium through uncertainty and the moderating roles of information seeking and social support in this relationship. The results demonstrate that goal disruption causes uncertainty and then leads to psychological disequilibrium. Information seeking can reduce uncertainty and social support can attenuate psychological disequilibrium as well. Limitations and further directions are discussed.

Role of Uncertainty in Debt-Growth Nexus

This paper analyses uncertainty as one of the factors that affect the public debt-growth nexus. We put forward a hypothesis that uncertainty mediates the effect of public debt on economic growth. The empirical examination of the mediating effect is based on the neoclassical growth equation and consistent with specifications previously used to analyse the sources of heterogeneity in the debt-growth relationship. Since one part of the uncertainty is financial risk, which is closely related to the financial sector stability, we use interest rate spread as a main variable, and the risk premium on lending as an alternative one to proxy financial risk and thus, to some extent, uncertainty. Our results show that lower uncertainty is related to a bigger positive effect of debt on growth and a higher turning point in the debt-growth nexus. On the contrary, higher uncertainty leads to a lower positive and more considerable negative effect of debt on growth in both linear and quadratic specifications.

Prognostics and Health Management of Wind Energy Infrastructure Systems

Abstract The improvements in wind energy infrastructure have been a constant process throughout many decades. There are new advancements in technology that can further contribute toward the prognostics and health management (PHM) in this industry. These advancements are driven by the need to fully explore the impact of uncertainty, quality and quantity of data, physics-based machine learning (PBML), and digital twin (DT). All these aspects need to be taken into consideration to perform an effective PHM of wind energy infrastructure. To address these aspects, four research questions were formulated. What is the role of uncertainty in machine learning (ML) in diagnostics and prognostics? What is the role of data augmentation and quality of data for ML? What is the role of PBML? What is the role of the DT in diagnostics and prognostics? The methodology used was Preferred Reporting Items for Systematic Review and Meta-Analysis. A total of 143 records, from the last five years, were analyzed. Each of the four questions was answered by discussion of literature, definitions, critical aspects, benefits and challenges, the role of aspect in PHM of wind energy infrastructure systems, and conclusion.

Are Incremental Innovations A Suboptimal Outcome? The Role of Uncertainty and Loss Aversion

Incremental innovations appears to be much more frequent than radical innovations. Possible explanations rely on the effect of the degree of competition in the market. The paper, on the contrary, focuses on agents' attitude towards status quo and con- servativeness and specifies the conditions where the preference for incremental innovations represents an optimum. In fact, the welfare generated by radical innovations drops dramatically when agents are uncertainty-averse and/or loss-averse.