A methodology for impedance control based on mechanical vibration theory was presented to select stiffness and damping to meet the desired dynamic response using modal analysis. This methodology provided profound insights into how changes in stiffness and damping matrices influence a robot’s dynamic response under impedance control, by determining natural frequencies and damping ratios in the modal space. In this paper, our analytical and experimental results challenge the claim of a recent paper stating that the use of a null-space projection does not affect the outcomes, which appears to be a claim that is valid based only on their specific choice of stiffness and damping matrices and robot configuration. Through experiments using a 7-DOF Franka Emika Panda robot, we demonstrate the influence of both stiffness/damping matrices and the weighting matrix of null-space control on the responses of robot manipulators with degrees of redundancy performing primary and secondary tasks. We also introduce and show insights of the benefits of switching between the statically and the dynamically consistent projection matrices, contributing to the broader understanding of the dynamic response of redundant robotic manipulators.

Levine et al. offer a compelling theory of moral decision-making, yet underemphasize the role of social perception. We argue that moral judgments function not only to evaluate actions but also to signal moral character. This signaling shapes social interactions and guides moral processing, highlighting the need to integrate reputational and relational dynamics into models of moral cognition.

The authors neglect the most distinctive and puzzling features of human moral experience and thus fail to offer a theory of moral cognition at all. Humans experience moral norms and obligations as externally imposed on us in ways we are not free to modify, invent, or ignore, in sharp contrast to the motivations and outcomes of bargaining or prior agreements.

We present the Galactic Plane Monitor (GPM), a dedicated low-frequency radio transient survey conducted with the Murchison Widefield Array at 200 MHz. The GPM targets an underexplored region of transient parameter space spanning timescales from seconds to weeks, where recent discoveries of unusual Galactic radio sources—including long-period transients and other coherent emitters—suggest a rich and largely uncharted population. Leveraging the MWA’s wide field of view, we carried out 72 observing epochs between June 2022 and March 2025, searching ∼ 5,000 sq. deg. of the Southern Galactic plane. We developed a multi-stage processing pipeline to search for variability across a broad range of timescales, from intra-snapshot (4 s to minutes), to inter-snapshot (minutes to hours), and inter-epoch (days to years). This approach combines image differencing, statistical variability metrics, and visual inspection to robustly identify transient candidates while mitigating the effects of ionospheric variability and imaging artefacts. In parallel, we produced deep mosaics using a “lucky imaging” strategy to maximise sensitivity to faint persistent sources. We present the detections of five long-period radio transients, seven eclipsing binary millisecond pulsars, seven intrinsically variable pulsars, and the detection of refractive interstellar scintillation and night-time interplanetary scintillation. The GPM represents a key step toward fully mapping the dynamic low-frequency radio sky and informs the design of next-generation transient surveys with the SKA Observatory.

The target article describes social cognitive mechanisms that enable people to make reasonable decisions in situations of interdependent choice where parties have divergent interests. We highlight the need for an integrative program of research on the social-cognitive mechanisms that people use to approximate the reasonableness standard of sound judgment via self-distancing and “inner dialogue” in a variety of decision-making contexts.

The design-based paradigm may be adopted in causal inference and survey sampling when we assume Rubin’s stable unit treatment value assumption (SUTVA) or impose similar frameworks. While often taken for granted, such assumptions entail strong claims about the data-generating process. We develop an alternative design-based approach: we first invoke a generalized, non-parametric model that allows for unrestricted forms of interference, such as spillover. We define an associated set of inferential targets and discuss their interpretation under SUTVA and a weaker assumption that we call the “no unmodeled revealable variation assumption” (NURVA). We then reconstruct the standard paradigm, reconsidering SUTVA at the end rather than assuming it at the beginning. Despite its similarity to SUTVA, we demonstrate the practical limitations of NURVA alone for identifying substantively interesting quantities. In so doing, we provide clarity on the nature and importance of SUTVA for applied research.

Four species of Lygus bugs (Hemiptera: Miridae), Lygus lineolaris, L. keltoni, L. elisus, and L. borealis, are native pests of many crops throughout North America. In eastern Canada, a European parasitoid, Peristenus digoneutis (Hymenoptera: Braconidae), occurs adventively from intentional releases made in the 1980s in the northeastern region of the United States of America. In the Canadian prairies, P. mellipes and P. howardi are common native parasitoids that attack the first and second generations of Lygus, respectively, albeit at low levels. Therefore, relocation of P. digoneutis has been considered to enhance biological control in western Canada. We investigated the potential for competition between the native and exotic Peristenus spp. in laboratory settings. Our results showed that no statistically significant effects of simultaneous or sequential competition occurred on the success of parasitism by the native species, particularly for P. howardi. Minor reductions in parasitism by P. mellipes were observed only when the exotic species was added one day before the native species. From these findings, we conclude that the risk for competitive displacement of native Peristenus spp. by P. digoneutis is low. The potential benefits of having a parasitoid with two generations and the likely additive mortality effects on Lygus bug pests should outweigh the low environmental risks of introducing P. digoneutis.

As diffusion scholars increasingly focus on the various mechanisms underlying the spread of policy innovations, it is important to establish clear theoretical foundations for each one. Elite socialization—innovations that diffuse because of the convergence of lawmakers and policy advocates around norms of appropriateness—is the most underdeveloped mechanism in the American diffusion literature. This is a critical oversight given the application of socialization in other contexts and the success of interstate policy networks in seeding policy cascades across the states. This article remedies this problem both by providing a theoretical foundation for elite socialization as an explanation for diffusion via interstate policy networks in the United States and differentiating this mechanism from four other common diffusion mechanisms. It offers testable core and peripheral assumptions and illustrative case studies of strict voter ID and organ donor law diffusion. Finally, it presents a research agenda for systematically testing socialization diffusion, which includes a discussion of methodological opportunities and challenges.

The social organization of care refers to the institutions, norms, and practices that govern the distribution of caring responsibilities and access to caring resources in unequal ways (Glenn 2000; 2012). There is compelling evidence that everywhere women still do the bulk of unpaid care work and that this restricts their opportunities to participate in economic and political life. These inequalities further spill over into the wider economy as many care occupations are poorly paid and predominantly filled by racialized and immigrant women, as well as women from less privileged socioeconomic backgrounds. Feminist scholarship demonstrates that care is not only an issue in its own right. It also lies at the heart of many other political phenomena from the development of welfare states (Ciccia and Sainsbury 2018; Gordon 1991; Koven and Michel 2013), to democratic backsliding and the rise of far-right parties (Briggs 2018; Farris and Rottenberg 2017; Meguid et al. 2025), to the politics of race, immigration, and same-sex families (Ayoub and Stoeckl 2024; Ferree 2021; Hancock 2004). Therefore, the social organization of care is a root cause of gender and intersecting inequalities.

In this article I am concerned with interrogating the intersection between the Newtonian and Cartesian intellectual inheritances of AI and machine learning, and ideas about the ethics of war. As militaries turn to new and emerging technologies to maintain or achieve a technological edge over their perceived adversaries, they create new imaginaries of future war—alongside the technologists, academics, and defense scientists crafting new terms, ideologies, and frameworks for making sense of these technologies. In this article I will argue that the intellectual inheritances of machine learning strengthen certain pre-existing tendencies of thinking about ethics and war that function to push the experience of war, particularly for those subjected to it, to one side. The first of these is ethics as code, which in its most extreme form seeks to quantify ethics. The second is ethics as identity, in which we see the reduction of complex ethical debates to a simple belief that “we” are the ethical actors and the “other” is not. To combat the expansion of militarism that these narratives enable we must foreground the experience of war, both of those subject to it and of those creating the conditions for war.

Levine et al.’s resource-rational contractualism (RRC) models moral judgment as a cost-sensitive approximation to ideal bargaining among stakeholders. We identify three strategies agents use to reduce moral costs by outsourcing or bypassing virtual bargaining: strategic delegation, diffusion of responsibility, and coalitional boundary-setting. We propose extending RRC with parameters for agency transfer, responsibility tracking, and stakeholder inclusion to better capture real-world moral decision-making.

Suicide is a significant global public health concern, and conventional clinical risk assessment is constrained by workforce availability, scalability, and clinician variability. The classic suicidality risk evaluation is largely dependent on clinical judgment, which, although helpful, can demonstrate a ceiling effect in its predictive validity. AI-driven chatbots, conversational systems that engage users in real-time natural language dialog, have emerged as candidate tools for augmenting suicide risk detection and prevention. This narrative review aimed to: evaluate the performance of AI-driven chatbots in detecting and assessing suicidal ideation relative to clinical benchmarks; examine the effectiveness of chatbot-based interventions for suicide prevention; and identify ethical, cultural, and implementation challenges limiting clinical translation. Six electronic databases were searched, with the initial search conducted in 2024 and updated in 2026 through targeted monitoring, with no upper cutoff date applied. A thematic narrative synthesis approach was applied across five domains. Eleven primary studies met eligibility criteria and were included in the synthesis. Chatbot-based risk assessment showed adequate response alignment with expert judgment at the extremes of suicide risk, but consistently failed to distinguish intermediate risk levels across multiple model families. Across 29 tested commercial chatbot agents, none met the criteria for an adequate suicidal crisis response. A clinically designed, framework-anchored chatbot achieved high efficacy across six outcome domains. Three percent of social chatbot users reported halted suicidal ideation, and a purpose-built clinical chatbot in emergency department settings significantly improved evidence-based care delivery. Systematic risk severity underestimation and the absence of cross-cultural evaluation were identified across all studies. AI-driven chatbots show potential as adjunctive tools across the suicide care continuum. Clinically designed, evidence-anchored chatbots demonstrate feasibility and meaningful benefit; commercially deployed chatbots without clinical validation demonstrate near-universal crisis response inadequacy. Mandatory clinical validation prior to public release, clinician oversight, and crisis system integration are prerequisites for responsible deployment.

Fleming and Michel propose that conscious vision supports model-based planning, which they link to the water-to-land transition. However, the water-to-land transition may have impacted vision more than other sensory modalities. I argue that for human olfaction, which is tuned to implicit processing and high emotional salience, consciousness might often be considered as an add-on more than a necessity.

MIDAS-1D2V is a plasma simulation code for axially symmetric open traps. It solves the non-stationary kinetic equation for the ion distribution function, accounting for Coulomb collisions. This paper presents two key modifications to the model. The first modification enables the calculation of fusion reactions in the plasma, with charged reaction products treated as an additional source term in the kinetic equation. The second modification incorporates beam capture dynamics, including ionisation and charge-exchange processes. Both modifications have been implemented for hydrogen isotopes.