Chemical weapons are among the weapons of mass destruction that have caused huge human casualties in the last century. Because of their easy manufacturing and accessibility, and despite international treaties, they remain a serious threat to global security, not just limited to military staff but also to civilian populations and the environment in the short and long term.

In recent years, a wide range of mortality models has been proposed to address the diverse factors influencing mortality rates, which has highlighted the need to perform model selection. Traditional mortality model selection methods, such as AIC and BIC, often require fitting multiple models independently and ranking them based on these criteria. This process can fail to account for uncertainties in model selection, which can lead to overly optimistic prediction intervals, and it disregards the potential insights from combining models. To address these limitations, we propose a novel Bayesian model selection framework that integrates model selection and parameter estimation into the same process. This requires creating a model-building framework that will give rise to different models by choosing different parametric forms for each term. Inference is performed using the reversible jump Markov chain Monte Carlo algorithm, which is devised to allow for transition between models of different dimensions, as is the case for the models considered here. We develop modeling frameworks for data stratified by age and period and for data stratified by age, period, and product. Our results are presented in two case studies.

Emerging scholarship suggests that willingness to engage in violent or risky behavior relates to Need for Chaos – a trait-state combination reflecting disaffection with society and politics, independent of political identity and beliefs. While previous research links Need for Chaos to a stronger gain-seeking mentality, it remains unclear whether those higher in Need for Chaos respond differently to gain and loss frames. We use a framing experiment based on prospect theory to test whether Need for Chaos moderates decision making about two salient policy issues in the United States: the debt ceiling and government shutdown negotiations in US Congress in 2023. Results from both studies (n = 2,704; 3,002) suggest that individuals low in Need for Chaos are risk-averse toward gains but risk-seeking toward losses, whereas those high in Need for Chaos exhibit the opposite pattern, seeking risk when anticipating gains and avoiding risk when anticipating losses. Our findings add important nuance to existing research by demonstrating that individuals higher in Need for Chaos are not merely indifferent to framing; rather, they also systematically respond to gain and loss frames. This work underscores how individual differences may help to shape judgment and decision making, particularly in times of societal and political uncertainty.

In reflexive methodology in terrorism studies and international security broadly, there are arguments about the absence of African voices, the lack thereof contributing to standardizing the fieldwork experiences of Western terrorism scholars as ‘one-size-fits-all’. However, while the voices of African-based scholars, particularly those based in the West, are increasingly being reflected in reflexive methodology in international security, we know little about how shared national belongingness and its associated cultural norms between the researcher and the researched influence the process of elite interviewing. This article addresses these limitations by reflecting on my experiences as a Nigerian conducting elite interviews with fellow nationals who are counter-terrorism security elites (CTSE) in Nigeria. In doing so, I examine the concepts of seniority, hierarchy, and reciprocity – important social norms that, while present in many contexts, take on distinctive meanings within counter-terrorism institutions in Nigeria – on data access and knowledge production. I contend that the shared cultural understanding between the researcher and CTSE study participants leads them to deploy these norms to foster post-fieldwork relational positionalities, which are used to advance their personal or career interests. This situation results in specific methodological and ethical dilemmas, which are addressed by engaging with and integrating these norms to resolve them. This article contributes to reflexive methodology in terrorism by nuancing the debate on situational ethics management in fieldwork dilemmas and advocating for context-based positionality.

Antimicrobial resistance (AMR) is a global public health challenge that, like climate change, demands urgent, coordinated, multi-sectoral action. Yet, responses to AMR may be ill-suited to local contexts, overlook historical inequalities, or dismiss marginalised knowledge systems. Some of these concerns can be discussed using the concept of a just transition, which aims to ensure that “no one is left behind,” “all voices are heard,” and past injustices are addressed. However, framing justice in these terms is insufficient. We argue for a more multifaceted and broader-scoped understanding of what justice demands in a just transition for AMR. We examine existing justice frameworks in AMR literature and discuss two cases that motivate our call for including both more forms of justice in a multifaceted concept of a just transition and a broader scope of justice. The first case involves over-the-counter antibiotic access in the Kibera informal settlement near Nairobi, highlighting structural injustices resulting from colonial oppression and what an Ubuntu philosophy would show as injustice. The second case concerns veterinary prescription requirements for Maasai pastoralists’ livestock farming in southern Kenya and highlights epistemic and distributive injustices, as well as injustices that befall non-human animals. These examples reveal distinct injustices shaped by socio-cultural and ecological contexts.

Using the $\infty $-categorical enhancement of mixed Hodge modules constructed by the author in a previous paper, we explain how mixed Hodge modules canonically extend to algebraic stacks, together with all the six operations and weights. We also prove that Drew’s approach to motivic Hodge modules gives an $\infty $-category that embeds fully faithfully in mixed Hodge modules, and we identify the image as mixed Hodge modules of geometric origin.

Unstable approaches contribute significantly to accidents during the critical approach and landing phases of flight, many of which could have been prevented by executing a go-around. This review investigates cognitive lockup, a tendency to adhere to task completion despite shifting priorities, and its role in aviation incidents. Specifically, we explore the psychological underpinnings of cognitive lockup, the influence on pilot decision-making and potential mitigation strategies. We examine factors such as task completion bias, framing effects and the perceived cost of task switching, and provide recommendations for training and policy modifications to reduce cognitive lockup. Aviation safety in critical flight phases can be improved through enhanced pilot training, mindfulness techniques, positive policy framing and AI-based alert systems.

An improved identification algorithm is adopted to calibrate the kinematic parameters of the serial-parallel robot, which improves the motion accuracy of the end-effector. Firstly, a kinematic model of the serial-parallel robot is constructed based on the closed-loop vector method. Secondly, a kinematic error model is established by combining geometric error analysis with the vector differential method. Then, with the effective separation of compensable and non-compensable error sources, an identification model of kinematic parameters is constructed. Finally, an improved pivot element weighted iterative algorithm is used to identify the geometric error parameters. Through actual pose measurement, MATLAB is used to simulate the calibration process. The simulation and experimental results show that after kinematic calibration, compared with the traditional least squares method, the improved identification algorithm can significantly reduce the end-effector pose error of the serial-parallel robot, thus effectively improving the motion accuracy of the end-effector.

We study existence and uniqueness of spherically symmetric solutions of

\begin{equation*}S_k(D^2v)+\beta \xi\cdot\nabla v+\alpha v+\left\vert v\right\vert^{q-1}v=0\;\; \mbox{in}\;\; \mathbb{R}^n,\end{equation*}

where $\alpha,\beta$ are real parameters, $n \gt 2,\, q \gt k\geqslant 1$ and $S_k(D^2v)$ stands for the k-Hessian operator of v. Our results are based mainly on the analysis of an associated dynamical system and energy methods. We derive some properties of the solutions of the above equation for different ranges of the parameters α and β. In particular, we describe with precision its asymptotic behaviour at infinity. Further, according to the position of q with respect to the first critical exponent $\frac{(n+2)k}{n}$ and the Tso critical exponent $\frac{(n+2)k}{n-2k}$ we study the existence of three classes of solutions: crossing, slow decay or fast decay solutions. In particular, if k > 1 all the fast decay solutions have a compact support in $\mathbb{R}^n$. The results also apply to construct self-similar solutions of type I to a related nonlinear evolution equation. These are self-similar functions of the form $u(t,x)=t^{-\alpha}v(xt^{-\beta})$ with suitable α and β.

Nutrition plays a key role in shaping children’s eating behaviours, which can be influenced by environment and social interactions, making careful management essential at home and school. This cross-sectional study aimed to evaluate the perceptions of caregivers in these settings regarding the consumption and eating behaviours of children aged 3–6 years. Food preferences and frequency questionnaires were administered to children, and their teachers and caregivers, supplemented by free drawing and colouring activities. The results revealed discrepancies between parents and teachers, with parents recognising the importance of fruits and vegetables for health and reporting that children have access to these foods at home. Although parents recognised the importance of vegetable consumption, teachers did not share this perception, as they observed limited access to these foods among children and even reported difficulties in introducing them into the school environment. The most consumed foods during main meals were rice, beans, vegetables and meats, while fruits and dairy products were predominant in breakfast and snacks. Children frequently mentioned fruits such as watermelon, strawberry, and apple using free drawing and colouring activities. These findings highlight significant differences in perceptions between parents and teachers regarding children’s access to healthy foods, underscoring the need for improved communication to promote healthier eating habits.

The escalating complexity of global migration patterns renders evident the limitation of traditional reactive governance approaches and the urgent need for anticipatory and forward-thinking strategies. This Special Collection, “Anticipatory Methods in Migration Policy: Forecasting, Foresight, and Other Forward-Looking Methods in Migration Policymaking,” groups scholarly works and practitioners’ contributions dedicated to the state-of-the-art of anticipatory approaches. It showcases significant methodological evolutions, highlighting innovations from advanced quantitative forecasting using Machine Learning to predict displacement, irregular border crossings, and asylum trends, to rich, in-depth insights generated through qualitative foresight, participatory scenario building, and hybrid methodologies that integrate diverse knowledge forms. The contributions collectively emphasize the power of methodological pluralism, address a spectrum of migration drivers, including conflict and climate change, and critically examine the opportunities, ethical imperatives, and governance challenges associated with novel data sources, such as mobile phone data. By focusing on translating predictive insights and foresight into actionable policies and humanitarian action, this collection aims to advance both academic discourse and provide tangible guidance for policymakers and practitioners. It underscores the importance of navigating inherent uncertainties and strengthening ethical frameworks to ensure that innovations in anticipatory migration policy enhance preparedness, resource allocation, and uphold human dignity in an era of increasing global migration.

The increase in activities related to unmanned aircraft systems and the implementation of this new ecosystem have introduced new hazards, impacting the operational safety of air traffic, particularly near airports, creating risks and disruptions in the flow of aircraft. The establishment of airspace for unmanned traffic management has required the integration of this new airspace with the existing one, bringing the potential for issues from this integration. A method was identified as needed to guide the detection of hazards posed to air traffic control activities and the consequent implementation of required mitigation measures. The aim of this work is to propose a framework for identifying hazards introduced to air traffic control, with a view to ensure the safe transition of this process. The method involved consulting air traffic operational safety specialists via a questionnaire, presenting the hazards highlighted in the literature concerning the integration of new airspace concepts within air traffic control activities. The results, obtained through a Delphi consultation, were analysed based on the most frequently assigned scores (mode) to reflect expert consensus. The results were organised into the proposed framework, establishing a guide to risk management activities aimed at implementing the change. The resulting structure was re-submitted to specialists and validated based on the Delphi method. Contributions to society include a guide for this process and potential future implementations, while the literature gap was addressed by adding knowledge to the scientific process.

According to what I call the Probabilistic View, absence of evidence is evidence of absence when finding evidence is highly expected. However, this view fails to make sense of the practice of using absence of evidence in the paleosciences, where finding evidence is typically not highly expected. Using a case from paleogeology, I offer a novel account of when absence of evidence should be evidence of absence, which I call the Pragmatic View: Appeals to absence of evidence as evidence of absence are warranted because they offer a scaffold to investigate auxiliary hypotheses related to the hypothesis in question.