Network meta-analysis (NMA) enables simultaneous assessment of multiple treatments by combining both direct and indirect evidence. While NMAs are increasingly important in healthcare decision-making, challenges remain due to limited direct comparisons between treatments. This data sparsity complicates the accurate estimation of correlations among treatments in arm-based NMA (AB-NMA). To address these challenges, we introduce a novel sensitivity analysis tool tailored for AB-NMA. This study pioneers a tipping point analysis within a Bayesian framework, specifically targeting correlation parameters to assess their influence on the robustness of conclusions about relative treatment effects. The analysis explores changes in the conclusion based on whether the 95% credible interval includes the null value (referred to as the interval conclusion) and the magnitude of point estimates. Applying this approach to multiple NMA datasets, including 112 treatment pairs, we identified tipping points in 13 pairs (11.6%) for interval conclusion change and in 29 pairs (25.9%) for magnitude change with a threshold at 15%. These findings underscore potential commonality in tipping points and emphasize the importance of our proposed analysis, especially in networks with sparse direct comparisons or wide credible intervals for correlation estimates. A case study provides a visual illustration and interpretation of the tipping point analysis. We recommend integrating this tipping point analysis as a standard practice in AB-NMA.

There is a lack of knowledge on deaths related to police use of force across Canada. Tracking (In)Justice is a research project that is trying to make sense of the life and death outcomes of policing through developing a collaborative, interdisciplinary, and open-source database using publicly available sources. With a collaborative data governance approach, which includes communities most impacted and families of those killed by police, we document and analyze 745 cases of police-involved deaths when intentional force is used across Canada from 2000 to 2023. The data indicate a steady rise in deaths, in particular shooting deaths, as well as that Black and Indigenous people are over-represented. We conclude with reflections on the ethical complexities of datafication, knowledge development of what we call death data and the challenges of enumerating deaths, pitfalls of official sources, the data needs of communities, and the living nature of the Tracking (In)Justice project.

The optimisation of inter-island transportation systems constitutes a critical determinant of regional economic development and the efficacy of mobility infrastructure. This study presents a comparative analysis of passenger mode selection between short-sea shipping (SSS) and road transport alternatives through stated preference surveys conducted via anonymised questionnaires. Employing advanced discrete choice modelling techniques – specifically the multinomial logit (MNL), random parameter logit (RPL) and latent class (LC) frameworks – we quantitatively disentangle the complex determinants influencing modal preferences. Our systematic sensitivity analysis reveals distinct behavioural patterns: passengers opting for SSS prioritise journey convenience, whereas road transport users exhibit stronger cost sensitivity. These findings provide actionable insights for formulating evidence-based policies to enhance intermodal transportation networks in the Zhoushan Archipelago of China. Beyond its immediate geographical focus, this research contributes methodological innovations by applying finite mixture models to capture unobserved heterogeneity in maritime transport decisions. The framework demonstrates significant transferability potential for island territories globally and urban freight corridor optimisation challenges, particularly in contexts requiring trade-off analyses between maritime efficiency and terrestrial logistics constraints.

The skin-friction coefficient is a dimensionless quantity defined by the wall shear stress exerted on an object moving in a fluid, and it decreases as the Reynolds number increases for wall-bounded turbulent flows over a flat plate. In this work, a novel transformation, based on physical and asymptotic analyses, is proposed to map the skin-friction relation of high-speed turbulent boundary layers (TBLs) for air described by the ideal gas law to the incompressible skin-friction relation. Through this proposed approach, it has been confirmed theoretically that the transformed skin-friction coefficient $C_{f,i}$, and the transformed momentum-thickness Reynolds number $Re_{\theta ,i}$ for compressible TBLs with and without heat transfer, follow a general scaling law that aligns precisely with the incompressible skin-friction scaling law, expressed as $ (2/C_{f,i} )^{1/2}\propto \ln Re_{\theta ,i}$. Furthermore, the reliability of the skin-friction scaling law is validated by compressible TBLs with free-stream Mach number ranging from $0.5$ to $14$, friction Reynolds number ranging from $100$ to $2400$, and the wall-to-recovery temperature ratio ranging from $0.15$ to $1.9$. In all of these data, $ (2/C_{f,i} )^{1/2}$ and $\ln Re_{\theta ,i}$ based on the present theory collapse to the incompressible relation, with a squared Pearson correlation coefficient reaching an impressive value $0.99$, significantly exceeding $0.85$ and $0.86$ based on the established van Driest II and the Spalding–Chi transformations, respectively.

Riboswitches are RNA elements with a defined structure found in noncoding sections of genes that allow the direct control of gene expression by the binding of small molecules functionally related to the gene product. In most cases, this is a metabolite in the same (typically biosynthetic) pathway as an enzyme (or transporter) encoded by the gene that is controlled. The structures of many riboswitches have been determined and this provides a large database of RNA structure and ligand binding. In this review, we extract general principles of RNA structure and the manner or ligand binding from this resource.

We present the Evolutionary Map of the Universe (EMU) survey conducted with the Australian Square Kilometre Array Pathfinder (ASKAP). EMU aims to deliver the touchstone radio atlas of the southern hemisphere. We introduce EMU and review its science drivers and key science goals, updated and tailored to the current ASKAP five-year survey plan. The development of the survey strategy and planned sky coverage is presented, along with the operational aspects of the survey and associated data analysis, together with a selection of diagnostics demonstrating the imaging quality and data characteristics. We give a general description of the value-added data pipeline and data products before concluding with a discussion of links to other surveys and projects and an outline of EMU’s legacy value.

Cargo carrying by a spring connected chiral micro-swimmer in a square channel is numerical studied by the three-dimensional lattice Boltzmann method and a chiral squirmer model. The effects of the driving type (β), swimming Reynolds number (Rep), spin coefficient (ξ) and diameter ratio (S) on the changes of the cargo-carrying velocity, spring length and motion modes are investigated, respectively. Four kinds of interesting motion modes are observed. When the chirality is not considered, the optimal combination for maximising swimming velocity are the pusher–cargo and cargo–puller configurations when Rep = 0.1 ∼ 1. When Rep is enhanced, the swimming velocities of the pusher–cargo, puller–cargo and cargo–pusher are increased, while the velocity of the cargo–puller is gradually decreased. When considering the chirality, only the swimming velocity of cargo–pusher and cargo–puller keep an interesting increment, and the reverse motion mode for the pusher-cargo and puller-cargo is firstly found in the present work when ξ exceeds a certain value. The impact of S on the cargo-carrying behaviour is complex, three kinds of oscillatory trajectories will appear under different ξ and S. The swimming velocity is reduced and even zero velocity will be observed when S is large. This work reveals key factors on the movement of microorganisms, offering guidance for improving cargo-carrying capabilities.

Genome-wide association studies (GWAS) of food preferences(1) and intake(2) have identified hundreds of loci, most previously linked to health conditions. This suggests these loci may reflect participants’ health status, leaving unclear their direct influences on eating behaviour. Given that taste and olfactory perception play a crucial role in food preferences and choices(3), this study aims to: i) investigate the influence of genetic variants within taste and olfactory receptor genes on food preferences and ii) use these variants to investigate the potential causal influence of food preferences on health. We assess the associations across 1214 nonsynonymous variants (minor allele frequency ≥ 0.01) within 425 non-pseudo taste and olfactory receptor genes and 140 food-liking traits in the UK Biobank (n = 162006 unrelated Europeans; mean age = 57). Food likings were measured on a 9-point scale, with 1 being ‘Extremely dislike’ and 9 being ‘Extremely like’. We identify 700 associations (FDR-corrected p < 0.05), of which 88 are also associated with their corresponding food intake traits in the UK Biobank. We replicate 84 associations in the younger Avalon Longitudinal Study of Parents and Children (ALSPAC; n = 2802 unrelated Europeans; mean age = 25), including OR2T6 rs6587467 for onion liking (p = 5.4 × 10-41 in UK Biobank, p = 2.9 × 10-4 in ALSPAC), whereas others cannot be replicated (e.g., OR4K17 rs8005245 for garlic liking, p-value = 1.9 × 10-69 in UK Biobank, p = 0.66 in ALSPAC). These variants account for greater phenotypic variances in food-liking traits in the ALSPAC than in the UK Biobank (e.g., 0.54% and 0.25% for garlic liking in ALSPAC and UK Biobank, respectively), suggesting genetically determined sensory perception has larger impacts on food preferences in young adulthood. Lastly, we use an epidemiological technique, Mendelian randomisation(4), to assess the potential causal influence of food preferences on health outcomes using food-liking-associated variants and summary results from large-scale GWAS. Taking likings for onions and bananas as an example, our results show that both are causally associated with lower systolic blood pressure (onions: beta = −1.257, p = 0.001; bananas: beta = −3.166, p = 0.005; unit = mmHg/liking score). While liking for onions decreases the risk of type 2 diabetes (odds ratio [OR, 95% confidence interval] = 0.856 [0.781, 0.939]), liking for bananas increases it (OR = 1.289 [1.051, 1.579]). We found no evidence for causal associations with coronary artery diseases (onions: OR = 0.995 [0.879, 1.126]; bananas: OR = 0.982 [0.742, 1.299]). This study furthers current knowledge of direct genetic influences on food preferences, which helps understand individual differences in eating behaviour and has implications for personalised nutrition. Results from causal modelling provide complementary evidence for previous observational studies and could be used to guide future trials.

The construct of second language (L2) utterance fluency is typically operationalized through various individual temporal features. However, in natural speech, fluency (or disfluency) is often characterized by the clustering of multiple temporal features, collectively revealing the speaker’s effort in speech production or disfluency recovery. In this study, we explore the co-occurrence patterns of disfluency features in L2 speech and their associations with speakers’ L2 oral proficiency. We initially segmented all speech samples into analysis of speech (AS)-units. Within each AS-unit, six individual fluency features were manually coded, standardized, and subsequently subjected to a hierarchical-based k-means cluster analysis to examine their co-occurrence patterns. The results revealed four distinct disfluency clusters. A subsequent qualitative analysis of disfluencies in each cluster revealed distinct distributional patterns, disfluency makeup, and communicative functions. Additionally, the proportions of different disfluency clusters were significantly influenced by speakers’ proficiency level, first language background, and their interaction. These findings carry implications for L2 speaking research in general, shedding light on the intricate nature of speech fluency and presenting an alternative approach to the operationalization of this multidimensional construct.

Traditional path planning algorithms often encounter challenges in complex dynamic environments, including local optima, excessive path lengths, and inadequate dynamic obstacle avoidance. Thus, the development of innovative path planning algorithms is essential. This article addresses the challenges of mobile robot path planning in complex environments, where traditional methods often converge to local optima, leading to suboptimal path lengths, and struggle with dynamic obstacle avoidance. To overcome these limitations, we propose an integrated algorithm, the enhanced sparrow search algorithm combined with the dynamic window approach (ESSA-DWA). The algorithm first utilizes ESSA for global path planning, followed by local path planning facilitated by the DWA. Specifically, ESSA incorporates Tent chaotic initialization to enhance population diversity, effectively mitigating the risk of premature convergence to local optima. Moreover, dynamic adjustments to the inertia weight during the search process enable an adaptive balance between exploration and exploitation. The integration of a local search strategy further refines individual updates, thereby improving local search performance. To enhance path smoothness, the Floyd algorithm is employed for path optimization, ensuring a more continuous trajectory. Finally, the combination of ESSA and DWA uses key nodes from the global path generated by ESSA as reference points for the local planning process of DWA. This approach ensures that the local path closely follows the global path while also enabling real-time dynamic obstacle detection and avoidance. The effectiveness of the algorithm has been validated through both simulations and practical experiments, offering an efficient and viable solution to the path planning problem.

Spherical robots face significant challenges in motion control on non-horizontal terrains, such as slopes, due to their unique spherical structure. This paper systematically investigates the motion stability of spherical robots on inclined surfaces through modeling, control algorithm design, and experimental validation. Precise Equilibrium Modeling: Using the virtual displacement method, the precise equilibrium equation for spherical robots on slopes is derived, addressing the issue of insufficient accuracy in describing the actual center of gravity in existing studies. Control Algorithm Design: For known slope conditions, a Backstepping Control (BSC) algorithm is designed, demonstrating excellent tracking performance. For unknown slope conditions, an Adaptive Backstepping Control (ABSC) algorithm is proposed, which significantly reduces tracking errors and enhances system robustness through parameter adaptation. Simulation and Physical Validation: Simulations confirm the effectiveness of the algorithms: BSC achieves high-precision control under known slopes, while ABSC exhibits strong adaptability under unknown slopes. Physical experiments validate the stability of the algorithms in a $5^\circ$ slope environment, demonstrating reliable performance across different control angles.

This paper traces how geological surveys and prospecting across two centuries shaped Afghanistan’s enduring characterization as a mineral-rich “El Dorado.” By investigating the shift in survey methods from comprehensive terrestrial to aerial reconnaissance, I show how geological knowledge production served purposes far beyond imperial resource identification and extraction. Drawing from historical and ethnographic research, including insights from a current emerald mine operator, I uncover how precious stones’ physical properties and circulating narratives about hidden riches propelled—and continue to propel—a vast network of individuals into mining enterprises: from state authorities and local powerbrokers to foreign geologists, mineral collectors, and international aid organizations. The result is the creation of new narratives about extractable wealth that interweave scientific practices and global market dynamics to transcend conventional periodization such as pre-Soviet, Soviet, and United States. These narratives have emerged from and reinforced asymmetrical relationships in both labor and expertise, ultimately positioning Afghan participants precariously within global mineral markets, made riskier still in times of conflict.

We experimentally identify a rotational motion of a single microalga (Chlamydomonas reinhardtii) within a microcontainer believed to be induced by one defective flagellum. We numerically adapt the classic two-dimensional squirmer model to replicate this unique motion by partially inhibiting the slip velocity on the boundaries of the squirmer. Subsequently, we employ a lattice Boltzmann method to simulate the motion of the single microalga with one defective flagellum. We examine the influence of swimming Reynolds numbers, self-propelling strength ($\beta$) and angle ($\alpha$) on the locomotion of the squirmer with one defective flagellum. The results indicate that a large $\beta$ leads to a large rotational diameter, positively correlating with the speed. Additionally, we observe that a low self-propelling strength ($\beta =0.5$) yields a monotonically increasing speed for the squirmer with $\alpha$. In general, high $\beta$ values result in fast speeds for the squirmer. This differs from the behaviour observed in a classic squirmer ($\alpha =360^{\circ }$), where high $\beta$ leads to a slow speed of puller ($\beta \gt 0$) owing to weak fluid inertia effects. Meanwhile, the energy expenditure increases monotonically with $\alpha$, contrasting with the non-monotonic trends observed for swimming speed and rotational diameter.