Forecasting of armed conflicts is a critical area of research with the potential to save lives and mitigate suffering. While existing forecasting models offer valuable point predictions, they often lack individual-level uncertainty estimates, limiting their usefulness for decision-making. Several approaches exist to estimate uncertainty, such as parametric and Bayesian prediction intervals, bootstrapping, quantile regression, but these methods often rely on restrictive assumptions, struggle to provide well-calibrated intervals across the full range of outcomes, or are computationally intensive. Conformal prediction offers a model-agnostic alternative that guarantees a user-specified level of coverage but typically provides only marginal coverage, potentially resulting in non-uniform coverage across different regions of the outcome space. In this article, we introduce a novel extension called bin-conditional conformal prediction (BCCP), which enhances standard conformal prediction (SCP) by ensuring consistent coverage rates across user-defined subsets (bins) of the outcome variable. We apply BCCP to simulated data as well as the forecasting of fatalities from armed conflicts, and demonstrate that it provides well-calibrated uncertainty estimates across various ranges of the outcome. Compared to SCP, BCCP offers improved local coverage, though this comes at the cost of slightly wider prediction intervals.

This article examines the subject of Ottoman shipping in the Indian Ocean in the two and a half centuries after 1650. With reference to both Ottoman and European sources, it first grapples with the empirical problems involved in studying the subject. It then explores how a combination of trade dynamics in the Gulf and the economic preferences of both Ottoman state and private actors attenuated the expansion of Ottoman shipping. Taken together, these factors confirm that the comparative dearth of Ottoman vessels in the Indian Ocean trade was a product of geopolitical and ecological contingency rather than entrepreneurial neglect or state aversion. Even so, as shown by two case studies, Ottoman subjects of one type or another were found in ports from Surat to Batavia at various moments before 1800. The analysis then turns to later nineteenth-century attempts by Ottoman state actors to augment Ottoman shipping. These efforts were inhibited by the contrasting incentives of private Ottoman seafarers, the dominance of European and Indian ships in the empire’s trade with India, the dislocation of nominal Ottoman territories in the Gulf, and the political economy of the Ottoman Gulf itself. Despite the fact that state-sponsored shipping came to grief, the presence of Ottoman ships in the Indian Ocean invites reflections on the highly mutable character of Ottoman identity and sovereignty, as well as the empire’s relative position in the wider commercial world of the Indian Ocean, across these centuries.

Occupational shoulder exoskeletons can relieve workers during strenuous overhead work. Passive solutions are lightweight, robust, and cost-effective, but they can also restrict user movement, have limited support, and cannot dynamically adapt to different working conditions. Semi-active and active systems are still mostly the subject of research, and existing systems are heavy or have limited performance and support. Here, we present a lightweight semi-active exoskeleton for shoulder support that incorporates a novel motorized torque adjustment mechanism that varies the effective lever arm with which a spring applies force to the supporting joint. The mechanism is integrated into lateral structures and can be actuated via Bowden cables with motors located on the user’s back. The technical performance of the system was experimentally characterized in terms of its dynamic support torque profiles at six different support levels. Furthermore, adjustment times and energy consumption were investigated. The system showed plateau-like support torque profiles in the intended working range and could be adjusted from nearly 0 Nm up to 12 Nm of maximum support per arm. Adjustment times varied between 0.5 s for the adjustment of 20% of the total adjustment range and 1.0 s for a full activation/deactivation. Adjustments consumed between 0.1 As and 1.9 As of battery charge, allowing long operating times of up to one working day, using only a small 2 Ah battery. As a result, the exoskeleton provides high performance by combining comparatively high support, rapid motorized support adjustment, and low energy consumption in a lightweight design.

Protein-losing enteropathy associated with failing Fontan circulation remains a significant challenge in long-term, single-ventricle circulation management. Evidence is very limited regarding medical therapies associated with a reduction in disease severity and morbidity outside of cardiac transplantation. We report a novel experience with remission of recalcitrant protein-losing enteropathy after treatment of Cryptosporidium gastroenteritis with a combination of antimicrobials including nitazoxanide, paromomycin, and azithromycin.

Current political developments worldwide illustrate that research on democratic backsliding is as important as ever. A recent exchange in Political Science & Politics (February 2024) highlighted again that the measurement of democracy remains a challenge. With many democracy indicators consisting of subjective assessments rather than factual observations, trends in democracy over time could be due to human biases in the coding of these indicators rather than empirical facts. This article leverages two cutting-edge Large Language Models (LLMs) for the coding of democracy indicators from the V-Dem project. With access to huge amounts of information, these models may be able to rate the many “soft” characteristics of regimes at substantially lower costs. Whereas LLM-generated codings largely align with expert coders for many countries, we show that when these models deviate from human assessments, they do so in different but consistent ways. Some LLMs are too pessimistic and others consistently overestimate the democratic quality of these countries. Although the combination of the two LLM codings can alleviate this concern, we conclude that it is difficult to replace human coders with LLMs because the extent and direction of these attitudes is not known a priori.

Efficient coordination is a major source of efficiency gains. We study in an experimental coordination game with 727 children and teenagers, aged 9 to 18 years, the strategies played in pre-adulthood. In our one-shot, experimental coordination game, we vary the incentives for reaching the more efficient equilibrium and the number of subjects within a group. Looking at strategy choices dependent on age, we do not find robust age effects in the aggregate. Yet, we see that smaller group sizes and larger incentives increase the likelihood of choosing the efficient strategy. The larger strategic uncertainty in larger groups is obviously harmful for overall efficiency. Regarding incentives, we find that increasing the profits in the efficient equilibrium seems to work better than providing a cushion in case of miscoordination. Beliefs play an important role as well, as subjects are more likely to play the efficient strategy when they expect others to do so as well. Our results are robust to controlling for individual risk-, time-, and social preferences.

Phoretic particles are often used as a simple model for experimental and theoretical studies of active matter. We develop a computational framework to resolve hydrodynamic and chemical interactions of multiple self-propelling phoretic particles suspended in two-dimensional Stokes flow. The proposed method is precise enough to resolve correctly the subtle transitions between different modes of spontaneous locomotion for a single particle, and fast and versatile enough to study multiparticle dynamics in periodic or confined domains. The particles are modelled as chemically active rigid circles, which can emit or absorb a solute into surrounding fluid. The interaction between particles and solute induces a slip flow on particle surfaces, and the solute is advected by the fluid flow and diffuses with a constant diffusivity. A fast boundary integral method is proposed to solve fluid–structure interaction in Stokes flow. Acceleration of this method is provided by splitting the velocity field due to a set of point forces into a short-range part with singularity and a long-range part which is sufficiently smooth, thanks to an Ewald-like decomposition. An overlapping mesh method is employed for advection–diffusion of the solute with moving boundaries. The idea is to decompose the computational domain into several overlapping subdomains, and body-fitted meshes are used to ensure sharp resolution of boundary conditions. The framework is validated separately for the Stokes problem and the advection–diffusion problem, reaching relatively high order of accuracy. We apply our framework to several practical problems, such as a single particle in a channel and particle suspensions, showing rich sets of behaviours.

The relationship between salinity-driven (SD) and particle-driven (PD) gravity currents has long been a focal point of geophysical research. This study investigates salinity–particle dual-driven gravity currents using a direct numerical simulation discrete element method. The transition regime from SD to PD currents is explored. The results show that the transition is related to interfacial instability and material transport dynamics. During this transition, the enhancement of particle sedimentation weakens the interfacial stratification and heightens its susceptibility to shear instability. Consequently, the instability generates a series of billows that encourages fluid dilution, further amplifying the particle sedimentation effect. The transition regime is closely associated with this positive closed-loop feedback mechanism. It supplies sufficient energy at the slumping stage to maintain the front velocity of particle-dominated currents comparable to that of salinity-dominated currents. The interfacial vortices will expand spatially by the centrifugal forces on the particles, leading to a reduction in detrainment.

Mental health is a global priority, fundamental to the health and development of all nations. The contribution of mental disorders to the global burden of disease is widely recognized; however, a significant care gap exists, particularly in the context of low-and middle-income countries. In India, for instance, there are 0.3 psychiatrists per 1,00,000 population. To address this severe shortage of mental health professionals and resources globally, the World Health Organization has suggested the adoption of a community-based mental health care approach, where the locus of services shifts from institutional care to local communities. Over the last five decades in India, diverse approaches to mental health care have emerged because of the interaction of dominant discourses on community-based mental health care with various socio-cultural contexts. In addition to the government-run mental health program and programs run by medical colleges, civil society organizations have increasingly contributed to this space. Although studies have assessed individual interventions, there exists a need to map these interventions and synthesize the approaches for service delivery to inform public health practice in India and in low-and middle-income countries at large. This narrative review attempts to map and synthesize insights from community-based mental health interventions in India implemented across diverse contexts. We searched peer-reviewed journal articles and book chapters published in the English language between 2010 and 2023. We present the synthesis of approaches used in 41 community-based mental health interventions, where we unpack key intervention components and processes adopted for primary prevention and promotion; identification and case detection; treatment and care, and rehabilitation in the community. This review presents key recommendations for practitioners about the role of community, the diversity and commonalities in various approaches across contexts, the roles of various actors in service delivery, and the shared values guiding the conceptualization and implementation of community-based mental health interventions in India.

In the 1880s, Sievers proposed that in Old English words such as *feorhes, the loss of the post-consonantal *h caused compensatory lengthening of the vowel: fēores. Since there are no unambiguous traces of this sound change in later English, widespread analogical restitution of the short vowels was assumed (e.g. from feorh). The evidence for this lengthening is largely metrical. I argue that while Sievers is correct that words like <feores> often need to scan with a heavy initial syllable, this need not be explained by a general lengthening in the language at large. Indeed, the distribution of where heavy scansions are required in verse is typical for metrical archaisms: late prehistoric metrical values of words preserved for poetic convenience. Just as wundor ‘marvel’ can continue to be scanned as monosyllabic *wundr, or contracted hēan can scan as disyllabic *hēahan, so can light-syllabled feores continue to scan as heavy *feorhes. The same sets of poems that prefer non-epenthesized or non-contracted forms also prefer the heavy scansions of feores-type words. If heavy scansions of feores-words are seen as a matter of poetic convention, then the hypothesis of compensatory lengthening in the language generally is left without evidence and should be rejected.

Student debt heavily shapes the life decisions and outlook of those living with it. This article examines the relationship between undergraduates’ views of President Joe Biden’s actions on student debt and their support for him in the 2024 election prior to his dropping out of the race. Using a representative survey from a large private university in the Northeast, we assess how student views of Biden’s handling of student loan relief correlated with voting intentions among registered student voters. Our analysis reveals that students who believed the Biden administration adequately addressed student debt were significantly more likely to support him compared to those who believed he had done too little. Additionally, our findings suggest that whereas increased student debt relief could have bolstered Biden’s support among liberal and very liberal students, its impact on moderate and conservative students was more limited. This study highlights the electoral implications of student debt relief policies, particularly in shaping young voters’ preferences, and it underscores the potential for targeted economic benefits to influence voter behavior in a highly polarized political environment.