Governing the deep: economic, ecological, and legal perspectives on deep-sea mining in areas beyond national jurisdiction

Environmental protection is a critical consideration for activities in the ocean to ensure the long-term sustainable use of marine resources, prevent irreversible ecological harm, and fulfill international legal obligations. In this article, we examine how economic interests in deep-sea mining, emerging scientific knowledge about environmental impacts, and recent legal developments under the United Nations Convention on the Law of the Sea (UNCLOS) shape States’ negotiation positions in the development of the Mining Code within the International Seabed Authority. We undertake a rigorous multidisciplinary review of economic, environmental, and legal literature to identify and critically assess the key factors influencing States’ strategies during these complex negotiations. By analyzing each domain, we clarify how competing economic imperatives, evolving scientific evidence on biodiversity and carbon cycle disruption, and shifting legal norms independently inform the negotiation process and its implications for the Mining Code’s substantive content and governance mechanisms. Drawing on recent jurisprudence from the International Tribunal for the Law of the Sea, which elucidates the relationship between UNCLOS and international climate frameworks under the United Nations Framework Convention on Climate Change and Paris Agreement, we highlight the increasing prominence of environmental protection within States’ legal duties. We argue that this evolving legal context supports the prioritization of precautionary and protective measures in the Mining Code and encourages cautious approaches that address scientific uncertainty and climate-related risks. This may include delaying the adoption of the Code or integrating stronger safeguards to prevent ecosystem collapse and promote responsible marine stewardship

Human mobility in epidemic modeling

Human mobility forms the backbone of contact patterns through which infectious diseases propagate, fundamentally shaping the spatio-temporal dynamics of epidemics and pandemics. While traditional models are often based on the assumption that all individuals have the same probability of infecting every other individual in the population, a so-called random homogeneous mixing, they struggle to catch the complex and heterogeneous nature of real-world human interactions. Recent advancements in data-driven methodologies and computational capabilities have unlocked the potential of integrating high-resolution human mobility data into epidemic modeling, significantly improving the accuracy, timeliness, and applicability of epidemic risk assessment, contact tracing, and intervention strategies. This review provides a comprehensive synthesis of the current landscape in human mobility-informed epidemic modeling. We explore several data sources and representations of human mobility, and examine the behavioral and structural roles of mobility and contact in shaping disease transmission dynamics. Furthermore, the review spans a wide range of epidemic modeling approaches, ranging from classical compartmental models to network-based, agent-based, and machine learning models. It also discusses how mobility integration enhances risk management and response strategies during epidemics. By synthesizing these insights, the review can serve as a foundational resource for researchers and practitioners, bridging the gap between epidemiological theory and the dynamic complexities of human interaction while charting clear directions for future research

Supporting families with unsettled babies - development of a digital intervention

Background Unsettled baby behaviours, such as crying and vomiting, are common but distressing for families. Unsettled behaviours are increasingly attributed to medical causes such as reflux or cows’ milk allergy. When inaccurate, this causes unnecessary harm to families and healthcare systems. Existing interventions to support parents managing unsettled babies are costly and often biased by conflicts of interest from the formula milk industry. Aims To co-design a person-, theory- and evidence-based behavioural intervention supporting families with unsettled babies. Method Qualitative interviews and the person-based approach (PBA) were combined with innovative methods including partnership working with underserved communities. Firstly, a systematic review and thematic synthesis explored parent experiences of unsettled babies, with an emphasis on parents’ thoughts and feelings about medical labels. An explanatory, conceptual model was proposed summarising parent experiences when faced with a baby they perceive as unsettled. Next, a qualitative interview study aimed to deepen understanding of parent attitudes to medical labels using an ethnically diverse sample of 25 mothers. Hybrid inductive & deductive analysis was used, including reflective thematic analysis, negative case analysis and framework analysis. Themes were presented and the conceptual model was refined. Finally, an intervention was developed using behaviour change theory and the PBA. This was optimised through qualitative ‘think-aloud’ interviews with 22 parents, analysed through thematic analysis and a table of changes. Findings Key findings from the systematic review and qualitative interviews offer a new insight into the thoughts, feelings and motivations of parents with unsettled babies. Findings suggest parents report a sense of guilt or failure, driving a search for an external, medical cause of unsettled behaviour. A novel intervention was developed. This aims to help parents distinguish normal baby behaviour from medical red flags; increase parent self-efficacy and give tools to self-manage unsettled behaviours. Discussion The results of this work are put in the context of wider literature on medically unexplained symptoms, the transition to parenthood, parenting self-efficacy and bonding. Limitations and strengths of the research, suggestions for future research and clinical practice are discussed. Conclusion The resulting intervention, if nested within a wider system of support, may provide help to families of unsettled babies, reducing unnecessary medicalisation

Coping, hoping and acting: employees' individual ethics for climate change in the oil and gas industry

Private companies in certain activity sectors are often called out for their practices, conveying questionable ethics, if not causing harm, be it at a societal or environmental level. The same companies employ thousands upon thousands of workers, who share an affiliation with their employer, while being members of the society where they witness or endure the consequences of these harmful activities. Contributing to a developing yet still limited literature considering individual moral agency and ethical construction within organisations, this thesis comprises three research papers investigating this problematic in the oil and gas industry, against the backdrop of the worsening of climate change and polarising debates around the extraction of fossil fuels. The title of this thesis, ‘Coping, Hoping and Acting’, reflects the respective angle of each of the three papers. The first explores the mechanisms employed by oil and gas industry employees to justify their being a part of this sector, and how these mechanisms perpetuate a neoliberal approach to corporate environmental ethics. The second identifies the dynamic processes of ethical formation employees go through and how these position them in relation to their organisations’ environmental discourses and practices. Finally, the third paper conceptualises the act of ‘crafting spaces in-between’ for the development of alternative futures, through studying the stories of people who straddle the boundary between the oil and gas industry and climate activism. These studies are built on accounts from and interviews with a population typically challenging to access, made up of current and former employees of the oil and gas industry. By giving voice to this often-overlooked population, this paper highlights the untapped potential which exists in creating space for all organisational actors, at all levels, to engage with environmental ethics. Moving beyond typical managerialist approaches opens new opportunities to envisage alternative paths towards sustainable futures

Deformation mode classification in extended endplate connections and implications on hysteretic response

Determining the mode by which steel connections deform under rotational demands is essential for assessing damage, quantifying the associated losses, tuning design, and characterizing the connection’s cyclic behavior. In this paper, a classification model is developed to predict the deformation mode in extended endplate connections (EEPCs) as a function of their layout, material, and geometric properties. The model covers six modes inclusive of those expected to occur in either fully rigid or partial strength EEPCs. Such modes, and particularly interactive ones, can be challenging to predict using traditional mechanical or analytical methods. The classification model utilizes the Random Forest algorithm and is trained using a large dataset of experimental and simulation data to achieve a high accuracy larger than 95 %. Additionally, recommendations are provided for characterizing hysteretic phenomenological models depending on the deformation mode. This includes an empirical formula for defining the cyclic pinching parameters in EEPCs undergoing endplate bending. This aims to support system-level seismic simulations employing the lumped plasticity approach

Two inertial projection-type methods for solving pseudo-monotone variational inequalities with application to image deblurring problem

Our purpose is to propose two different type of inertial algorithms for approximating a solution of pseudo-monotone variational inequality problem in the framework of Banach spaces. The proposed algorithms are established by using Mann’s iterative method and single projection type method with adaptive step-size. Strong convergence theorems for minimum-norm solution of the variational inequality problem are established without the prior knowledge of the Lipschitz constant of the mapping. Finally, some numerical experiments are performed to illustrate the advantage of the proposed methods and numerical experiments in image recovery are also presented. Our results generalize and improve some known results existing in the current literature.</p

Moral outrage predicts the virality of petitions for change on social media, but not the number of signatures they receive

Social media is a powerful tool for activists to share their perspectives, but concerns persist that the viral spread of online moral outrage may undermine collective causes in some ways. Analyzing posts on X (n = 1,286,442) with URLs to petitions on www.change.org (n = 24,785), we found that expressions of outrage were uniquely associated with the number of times posts were liked and reposted (virality). Mediation analyses showed that outrage was indirectly related to the number of signatures petitions received (via virality). However, outrage was associated with fewer signatures when controlling for virality. In contrast, expressions of agency, group identity, and prosociality were associated with more signatures but no more virality. The findings outline the factors linked to engagement with online petitions and describe how social media can amplify content which has no direct link to the sorts of effortful behaviors typically thought to be conducive to social change.</p

Who gets in? a conjoint analysis of labour market demand and immigration preferences in England and Japan

We advance research on attitudes towards immigration using an experimental design that more clearly separates between skill level and labour market demand. In single profile conjoint design experiments fielded in England and Japan, we replicate the well-established finding that high-skill immigrants are generally preferred to low-skill immigrants. However, we also show a more nuanced result in that labour market demand – regardless of skill level – is also important. Indeed, in both England and Japan, the public is willing to accept low-skill workers in high-demand occupations at levels at least as much as for high-skill but low-demand occupations. Labour market demand is an important factor in understanding attitudes towards economic migration

Revisiting cross-domain problem for LiDAR-based 3D object detection

Deep learning models such as convolutional neural networks and transformers have been widely applied to solve 3D object detection problems in the domain of autonomous driving. While existing models have achieved outstanding performance on most open benchmarks, the generalization ability of these deep networks is still in doubt. To adapt models to other domains including different cities, countries, and weather, retraining with the target domain data is currently necessary, which hinders the wide application of autonomous driving. In this paper, we deeply analyze the cross-domain performance of the state-of-the-art models. We observe that most models will overfit the training domains and it is challenging to adapt them to other domains directly. Existing domain adaptation methods for 3D object detection problems are actually shifting the models’ knowledge domain instead of improving their generalization ability. We then propose additional evaluation metrics – the side-view and front-view AP – to better analyze the core issues of the methods’ heavy drops in accuracy levels. By using the proposed metrics and further evaluating the cross-domain performance in each dimension, we conclude that the overfitting problem happens more obviously on the front-view surface and the width dimension which usually faces the sensor and has more 3D points surrounding it. Meanwhile, our experiments indicate that the density of the point cloud data also significantly influences the models’ cross-domain performance.</p

A refinement of macroeconomy-housing price equilibrium: walking down long memory lane

Housing prices are known to respond slowly and heterogeneously to macroeconomic variations from the demand and supply sides of housing. This offers a possibility to model the long-memory and varied persistence of housing price adjustments, through which a refined characterisation of the macroeconomic-housing price interaction in equilibrium can be developed. Our paper advances a theoretical argument, supported by empirical findings in the US, that macroeconomic variations trigger varied reactions on housing demand and supply sides. This leads to distinct trajectories of equilibrium housing price formations governed by differential price adjustments on the two sides of housing. An established longer memory on the supply side of housing demonstrates its higher persistence of disequilibrium deviations than on the demand side. In the equilibrium, certain macroeconomic factors are found to exert dual but heterogeneous roles in housing demand- and supply-side dynamics. The net role of each such factor is negative led by its even stronger negative role on the demand side compared against a smaller positive one on the supply side. Our findings contribute to deeper reflections on the likely ineffectiveness of macroeconomic interventions in housing price dynamics