A Hierarchical Framework for CO2 Storage Capacity in Deep Saline Aquifer Formations

Carbon dioxide (CO2) storage in deep saline aquifers is a vital option for CO2 mitigation at a large scale. Determining storage capacity is one of the crucial steps toward large-scale deployment of CO2 storage. Results of capacity assessments tend toward a consensus that sufficient resources are available in saline aquifers in many parts of the world. However, current CO2 capacity assessments involve significant inconsistencies and uncertainties caused by various technical assumptions, storage mechanisms considered, algorithms, and data types and resolutions. Furthermore, other constraint factors (such as techno-economic features, site suitability, risk, regulation, social-economic situation, and policies) significantly affect the storage capacity assessment results. Consequently, a consensus capacity classification system and assessment method should be capable of classifying the capacity type or even more related uncertainties. We present a hierarchical framework of CO2 capacity to define the capacity types based on the various factors, algorithms, and datasets. Finally, a review of onshore CO2 aquifer storage capacity assessments in China is presented as examples to illustrate the feasibility of the proposed hierarchical framework.

Two monkey wrenches in the Russian regulatory reform

The latest Russian regulatory reform (2016) sought to introduce the risk-orientated approach – a move away from the “blanket inspections” (or the risk regulation reflex – a term coined by Blanc in 2011) method that has been criticised by the Russian business community. The present paper aims to assess its success using administrative data on federal watchdogs’ inspections. We argue that this reform ultimately failed in its goal regarding the overall number of inspections, and thus the volume of regulatory burden did not change significantly throughout the reform. This failure resulted from two mechanisms. First, the legal framing of the reform radically redefined risk as the probability of incompliance (as opposed to the likelihood of accident). Second, the watchdogs used key performance indicators that incentivised “street-level” inspectors to maintain the pre-reform regulatory burden levels.

Safer by design: Building a collaborative, integrated and evidence-based framework to inform the regulation and mitigation of gambling product risk

Evidence suggests that harms may result from gambling participation as a result of a complex interaction between individual differences among consumers, environmental factors, and the characteristics of the gambling product. The latter of these factors, broadly referred to in this paper as product risk, has received increased policy attention in recent years. Product-focussed approaches to harm reduction, however, are under-developed relative to other forms of player protection and likely reflects the limitations of existing evidence and relative complexity of the topic. In this position paper, we define and explain the concept of product risk and consider what is currently known regarding the link between gambling products and harm. The paper describes the present barriers to develop effective product risk regulation and harm mitigation strategies. These include the competing interests of stakeholders, limited collaboration and information sharing, clear roles, responsibilities and leadership and a lack of integrated evidence-informed approaches. In response to these challenges, we propose adopting a framework comprised of a series of principles to progress this contested area of policy. The framework encourages better collaboration and communication between stakeholders; the accelerated production of valid and reliable evidence; a strategic alignment of stakeholder activity; and, more effective and efficient approaches to assessing and mitigating product risk.

Loan default prediction of Chinese P2P market: a machine learning methodology

Repayment failures of borrowers have greatly affected the sustainable development of the peer-to-peer (P2P) lending industry. The latest literature reveals that existing risk evaluation systems may ignore important signals and risk factors affecting P2P repayment. In our study, we applied four machine learning methods (random forest (RF), extreme gradient boosting tree (XGBT), gradient boosting model (GBM), and neural network (NN)) to predict important factors affecting repayment by utilizing data from Renrendai.com in China from Thursday, January 1, 2015, to Tuesday, June 30, 2015. The results showed that borrowers who have passed video, mobile phone, job, residence or education level verification are more likely to default on loan repayment, whereas those who have passed identity and asset certification are less likely to default on loans. The accuracy and kappa value of the four methods all exceed 90%, and RF is superior to the other classification models. Our findings demonstrate important techniques for borrower screening by P2P companies and risk regulation by regulatory agencies. Our methodology and findings will help regulators, banks and creditors combat current financial disasters caused by the coronavirus disease 2019 (COVID-19) pandemic by addressing various financial risks and translating credit scoring improvements.

The role of risk regulation in intimate relationships among individuals with social anxiety disorder and healthy controls

Individuals with social anxiety disorder (SAD) experience heightened concern about rejection and negative evaluation by other people. However, limited research has assessed the extent to which individuals with SAD also experience elevated concerns about rejection within the context of their intimate relationships. In the present study, individuals with SAD (n = 21) and healthy controls (HCs; n = 25) who were in current intimate relationships completed daily diaries each evening for 14 days. Daily diaries assessed the extent to which participants experienced feelings of rejection and acceptance in their intimate relationships, as well as the extent to which they responded to feelings of rejection by using behaviours characterized by withdrawal (“withdrawal” processes) versus efforts to reaffiliate with their partners (“approach” processes). Results revealed that individuals with SAD reported greater levels of intimate partner rejection and marginally lower levels of intimate partner acceptance than HCs. Further, feelings of rejection were associated with an increased use of next-day withdrawal processes among SAD, but not HC participants. These findings provide insight into the nature of rejection concerns and responses to rejection among individuals with SAD.

The role of risk regulation in intimate relationships among individuals with social anxiety disorder and healthy controls

Individuals with social anxiety disorder (SAD) experience heightened concern about rejection and negative evaluation by other people. However, limited research has assessed the extent to which individuals with SAD also experience elevated concerns about rejection within the context of their intimate relationships. In the present study, individuals with SAD (n = 21) and healthy controls (HCs; n = 25) who were in current intimate relationships completed daily diaries each evening for 14 days. Daily diaries assessed the extent to which participants experienced feelings of rejection and acceptance in their intimate relationships, as well as the extent to which they responded to feelings of rejection by using behaviours characterized by withdrawal (“withdrawal” processes) versus efforts to reaffiliate with their partners (“approach” processes). Results revealed that individuals with SAD reported greater levels of intimate partner rejection and marginally lower levels of intimate partner acceptance than HCs. Further, feelings of rejection were associated with an increased use of next-day withdrawal processes among SAD, but not HC participants. These findings provide insight into the nature of rejection concerns and responses to rejection among individuals with SAD.