We describe the latest iteration of upgrades (designated Phase III) to the Murchison Widefield Array (MWA), in the fourth paper in a series that covers the evolution of the telescope from design concept to initial operational facility, and through two major upgrades. As part of the Phase III upgrade of the MWA, we report the completion of work to design, build, and deploy a new fleet of digital receivers that further optimise the MWA for Epoch of Reionisation observations. These receivers complement existing receivers, such that the MWA now supports the full correlation of all 256 antenna tiles currently in the array. This step releases the MWA from the prior constraint of having to correlate only 128 of the 256 tiles at any given time, which means that the maximum instantaneous sensitivity of the MWA is doubled and the maximum number of interferometric baselines is approximately quadrupled. The upgrade is fundamentally enabled by the new MWAX correlator and various other improvements to the MWA sub-systems. In this paper we describe the new digital receivers and the other improvements that result in the Phase III system. A range of operational benefits arise from the upgrade and scientific flexibility is increased. We also comment on the transition from the MWA to the SKA-Low facility near the end of the decade, including a description of some unique science opportunities utilising joint MWA/SKA-Low data during the Science Verification phase of the SKA-Low Array Assembly 2 (AA2) period.

Diets low in diverse fibre-rich plant foods contribute to the rise of chronic disease. The BIOME study (NCT06231706; 6-week parallel randomised controlled trial) in 399 adults (35–65 years; BMI 18·5–40 kg/m2; fibre intake < 20 g/d) investigated a whole-food plant blend containing > 30 ingredients, rich in (poly)phenols, fibre and micronutrients. Participants were randomised (1:1:1) to the blend (30 g/d), an isoenergetic control (bread croutons, 28 g/d) or probiotic (Lactobacillus rhamnosus, 15bn CFU/d). Analysts were blinded to allocation. The primary outcome was change in ‘favourable’ and ‘unfavourable’ gut microbiome species (ZOE Microbiome Health Ranking 2025); secondary outcomes included blood metabolites, symptoms, stool output, anthropometry, hunger, sleep, energy and mood. A crossover sub-study explored postprandial glucose, hunger and mood. Of 349 participants analysed (fifty excluded), self-reported adherence was > 98 %. The 30+ plant blend resulted in more species changing relative abundance at 6 weeks v. control (57 v. 14 species-level genome bins (SGB), P < 0·001) and probiotic (57 v. 4 SGB, P < 0·001). There were no significant between-group differences in microbiome health ranks of significantly changing species (increasing or decreasing). Blend participants self-reported reduced indigestion, constipation, heartburn and flatulence and increased energy v. control (all P < 0·05). Six related but no serious adverse events occurred. In the sub-study, adding the blend to a high-carbohydrate meal (v. meal alone) reduced hunger, increased fullness and energy (3-h incremental AUC, all P < 0·05), with no effect on postprandial glucose. This 30+ plant blend represents a simple strategy to modify gut microbiome composition and benefit gastrointestinal symptoms in healthy adults.

Community structure in networks naturally arises in various applications. But while the topic has received significant attention for static networks, the literature on community structure in temporally evolving networks is more scarce. In particular, there are currently no statistical methods available to test for the presence of community structure in a sequence of networks evolving over time. In this work, we propose a simple yet powerful test using e-values, an alternative to p-values that is more flexible in certain ways. Specifically, an e-value framework retains valid testing properties even after combining dependent information, a relevant feature in the context of testing temporal networks. We apply the proposed test to synthetic and real-world networks, demonstrating various features inherited from the e-value formulation and exposing some of the inherent difficulties of testing on temporal networks.

Objectives/Goals: This study sought to gather older adult feedback on UCHealth’s artificial intelligence (AI) based chatbot, Livi, to ensure it is accessible and easy to navigate for end users to access fall prevention resources near their homes after an emergency department (ED) visit. Methods/Study Population: UCHealth’s electronic health record and ED operations team implemented an automated process to provide high fall-risk patients access to Livi via a QR code in their after-visit summary. Patients can then access evidence-based free or low-cost fall prevention resources based on their location. TO gather older adult feedback, rapid iterative testing was conducted at 3 community events (a religious center, assisted living facility, and academic medical campus). Research team members introduced Livi using an iPad and invited participants to explore the tool. End user feedback was gathered through notes taken on one-on-one guided conversation emphasizing first impressions and suggestions regarding Livi. Results/Anticipated Results: Suggestions from 93 community members included increasing font size and the addition of languages. Further resource suggestions included the following: increased locations, home modifications, and self-fall risk assessment. Based on these recommendations, our team increased font size, implemented the ability to switch from English to Spanish, added additional resources for other Colorado regions, added the ability to self-screen for fall risk using the National Council on Aging’s 13-question Screener, and fall prevention tips. Discussion/Significance of Impact: Many older adults do not follow up with primary care after a fall, increasing risk for subsequent falls. While Livi offers a pragmatic solution to this, ensuring end users can navigate it is key, so gathering feedback was a critical step before assessing Livi’s impact via randomized trial.

Objectives/Goals: This study evaluated whether the Geriatric Acute and Post-acute Fall Prevention (GAPcare) intervention reduced fall-related emergency department (ED) visits and hospitalizations within 12 months of the index visit at three EDs and described adherence to pharmacy and physical therapy (PT) recommendations. Methods/Study Population: We enrolled ED patients aged ≥65 years presenting within 7 days of an accidental fall (excluding syncope, assault, or vehicle strike), who were community-dwelling, expected to be discharged, and without fractures preventing PT. We used the six-item screener for cognitive screening. Patients scoring ≤4 assented with proxy consent. Participants were randomized 1:1 to usual care or GAPcare intervention (ED-initiated pharmacy and PT consults). The primary outcome was fall-related ED visits within 12 months. Outcome assessors were blinded. Analyses followed intention-to-treat and adjusted for age, sex, prior falls, comorbidity index, activities of daily living, injury status, site, index ED visit, hospitalization, and assistive device use using negative binomial regression. Results/Anticipated Results: Among 196 patients, 100 received usual care and 96 received the GAPcare intervention. Median age was 78 (IQR 72–84), 68.4% were female, and 83.1% were white. Fall-related ED visits occurred in 30% of both groups (adjusted IRR 0.90, 95% CI 0.53–1.53). Fall-related hospitalizations were significantly lower in the intervention group (11% vs 21%; adjusted IRR 0.45, 95% CI 0.20–0.96), Adherence to pharmacy recommendations was 81%, and PT recommendations was 65%, with frequent medication optimization and assistive device use. Discussion/Significance of Impact: While GAPcare did not reduce fall-related ED visits, it significantly lowered fall-related hospitalizations and showed high adherence to fall prevention recommendations. These findings highlight GAPcare’s feasibility and potential to address fall risk during a critical window.

In 250 men (21·4 (sd 2·9) years; BMI 24·2 (sd 3·0) kg·m–2) commencing arduous military training during winter, we investigated the effect of 12 weeks of vitamin D supplementation on lower body (pelvic girdle, sacrum, coccyx and lower limb) overuse musculoskeletal injury risk in a randomised, placebo-controlled trial. Participants received either simulated sunlight (1·3 × standard erythemal dose in T-shirt and shorts, three times per week for 4 weeks and then once per week for 8 weeks), oral vitamin D3 (1000 IU · d–1 for 4 weeks and then 400 IU · d–1 for 8 weeks) or placebo for each intervention. Serum vitamin D metabolites and bone metabolism biomarkers were measured at baseline, week 5 and week 12. At baseline, 29 % of participants were vitamin D sufficient (25-hydroxyvitamin D ≥ 50 nmol·L–1). Vitamin D supplementation achieved vitamin D sufficiency in 95 % of participants after 4 weeks. During 6 months of training and subsequent 3 years of military service, 100 lower body overuse musculoskeletal injuries were diagnosed by clinicians. Frailty models indicated no difference in injury risk between vitamin D and placebo during military training (HRplacebo:vitamin D = 1·23 (95 % CI 0·57, 2·66), P = 0·597) or military service (HRplacebo:vitamin D = 0·94 (95 % CI 0·60, 1·46), P = 0·782). Both safe simulated sunlight and oral vitamin D3 were effective in achieving and maintaining vitamin D sufficiency in almost all. There was no clear evidence that vitamin D affects the risk of lower body overuse musculoskeletal injury during 6 months of military training or subsequent 3 years of military service.

This study investigated changes in serum folate and B12, and associations with endurance performance and bone outcomes, in women during military training. Women (n 137) had serum folate and B12, haematological markers and endurance performance (2·4 km run) measured at the start (week 1) and end (week 13) of British Army basic training. Whole-body areal bone mineral density and markers of bone metabolism were measured at week 1. Training decreased serum folate (mean change (95 % CI), −2·3 (−3·0, −1·6) nmol ∙ l−1, P < 0·001), B12 (−16 (−32, 0) pmol ∙ l−1, P = 0·042), Hb (−0·7 (−0·9, −0·5) g ∙ dl−1, P < 0·001) and erythrocyte count (−0·2 (−0·3, −0·2) × 10^9 ∙ l−1, P < 0·001), but had no effect on mean corpuscular volume (P = 0·438) or erythrocyte distribution width (P = 0·088). There was no association between serum folate, serum B12, Hb or erythrocyte count with run time (P ≥ 0·518). Serum B12 was not associated with areal bone mineral density or bone metabolism at week 1 (P ≥ 0·152). Higher serum folate was associated with lower plasma c-telopeptide cross-links of type I collagen (standardised β (95 % CI) = −0·31 (−0·48, −0·15), P < 0·001), but not whole-body bone mineral density or plasma procollagen type I N-terminal propeptide (P ≥ 0·152). Serum folate and B12 decreased after military training in women, resulting in a high prevalence of folate deficiencies at the end of training. Low serum folate may contribute to increased bone resorption, the implications of which are unclear.

Antarctic ice-free coastal environments, like the Vestfold Hills (East Antarctica), are shaped by a complex interplay of physical processes. This study synthesizes new data and existing research from the Vestfold Hills across marine, terrestrial and cryosphere science, meteorology, geomorphology, coastal oceanography and hydrology to explore interconnected processes ranging from icescape morphology and sediment transport to ocean-floor scouring and ocean-atmosphere interactions. Coastal landforms and habitats result from the interaction of marine dynamics with the aeolian and fluvial transport of glacially derived sediments and geomorphic features. Rocky shorelines dominate the region, and extensive fjords are prominent coastal features, whereas intertidal sediments and beaches are scarce. The marine environment is characterized by slow currents, low-energy waves, annually variable land-fast ice, irregular sedimentation rates and a geomorphologically complex shoreline. Aeolian and fluvial sediment deposition into coastal waters and onto sea ice can significantly impact local ecological and physical processes. Human activity further modifies these dynamics. Ice-free coastal areas such as the Vestfold Hills are predicted to experience substantial environmental shifts due to climate change. Wind speeds, temperature and precipitation are increasing in the Vestfold Hills. Retreating grounded ice sheets are likely to expand this coastal area and increase meltwater and sediment inputs into nearshore marine systems. Concurrently, changes in sea-ice extent, thickness and/or duration may profoundly alter the structure and function of this coastal environment.

Collaboration across the Clinical and Translational Science Award (CTSA) consortium is essential for advancing translational science, yet institutional silos often hinder data-sharing and benchmarking efforts. This study examines the viability of a voluntary, multi-hub analysis of the CTSA education common metric on trainee and scholar engagement across five New York City-based sites or “hubs.” Using a structured framework for collaboration and field-tested operational guidelines, a team of evaluators dubbed “The Gotham Group” pooled de-identified common education data to assess post-training research engagement and demographic representation. Their primary objective was to establish a sustainable model for independent data-sharing without national mandates or technical support. A secondary goal was to reassess the metric’s usefulness as an impact benchmark. Results showed that NYC education engagement percentages remained stable despite institutional differences, suggesting the metric’s viability for regional comparison. More importantly, the collaboration itself proved as valuable as its outcomes, fostering professional relationships, facilitating knowledge exchange, and strengthening evaluation capacity within and across the hubs. This study highlights the potential of voluntary data-sharing partnerships to overcome data silos and to create valuable networks driving continuous improvement in translational science.

Paleontology provides insights into the history of the planet, from the origins of life billions of years ago to the biotic changes of the Recent. The scope of paleontological research is as vast as it is varied, and the field is constantly evolving. In an effort to identify “Big Questions” in paleontology, experts from around the world came together to build a list of priority questions the field can address in the years ahead. The 89 questions presented herein (grouped within 11 themes) represent contributions from nearly 200 international scientists. These questions touch on common themes including biodiversity drivers and patterns, integrating data types across spatiotemporal scales, applying paleontological data to contemporary biodiversity and climate issues, and effectively utilizing innovative methods and technology for new paleontological insights. In addition to these theoretical questions, discussions touch upon structural concerns within the field, advocating for an increased valuation of specimen-based research, protection of natural heritage sites, and the importance of collections infrastructure, along with a stronger emphasis on human diversity, equity, and inclusion. These questions offer a starting point—an initial nucleus of consensus that paleontologists can expand on—for engaging in discussions, securing funding, advocating for museums, and fostering continued growth in shared research directions.

We compare different forms of communication in the context of cheap talk sender-receiver games. While previous experiments find evidence supporting the comparative statics prediction that more preference divergence leads to less information transmission, there is also a consistent pattern of overcommunication and exaggeration, not predicted by theory, in which subjects convey more information than predicted in equilibrium. The latter of these findings may be due to the restricted nature of the message space in most experimental cheap talk games, encouraging subjects to engage in exaggeration artificially, rather than allowing it to emerge naturally. We tested this hypothesis with an incentivized lab experiment, and found evidence both phenomena persist with natural language (text-based) communication. Moreover, we probe the consequences of this expanded message space for outcomes, showing that senders benefit more than receivers, but that the most notable effect is that text messages improve efficiency.

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.

A structurally transforming multi-mode product can realize a changing set of functions across its modes, replacing multiple related products while offering increased cost, space, and time efficiency. However, there is a lack of connected methods that address the additional design complexities due to the product’s physical transformations and the resulting structural component-sharing between modes. A framework, grounded in standard design practice and built upon existing methods, is proposed to help navigate the two most impacted design stages: 1. Problem Definition and 2. Conceptual Design. The Problem Definition stage in this new framework involves identifying the external factor that determines the product’s modes and defining the functional requirements for the modes and transformation methods. The Conceptual Design stage involves iteratively linking conceptualized forms of each mode to adjacent modes through conceptualized transformation methods. The framework is demonstrated in a case study involving the design of a structurally transforming multi-mode piece of children’s furniture that transforms between a cradle, floor seat and a multipurpose toddler step stool. The proposed framework is a promising step toward systematically, cohesively, and comprehensively addressing design challenges during the development of a wide variety of structurally transforming multi-mode products, therefore facilitating better, more effective product design.