Mouse lemurs Microcebus spp. are small, nocturnal primates endemic to Madagascar. The genus is extraordinarily diverse, with 25 extant species, several of which have been described recently. The Endangered Claire's mouse lemur Microcebus mamiratra was first described in 2006, but, similarly to other newly described mouse lemurs, remains understudied, and estimates of its population size are unavailable, hampering effective conservation management. We conducted line transect distance sampling surveys of M. mamiratra across several habitat types in and around Lokobe National Park on the island of Nosy Be in north-western Madagascar. Using a systematic random design we surveyed 15 transects over a 6-week period in 2023, recording 92 detections from a total survey effort of 46.5 km. We estimate the density of M. mamiratra on Nosy Be to be 125.1 individuals/km2, which extrapolates to an estimate of c. 4,700 individuals across the forested areas of its range on the island. Our results indicate that Nosy Be harbours moderately high densities of M. mamiratra, with the highest encounter rates in the unprotected secondary and degraded forests around Lokobe National Park. Our population estimate will inform future conservation status assessments and conservation planning for this range-restricted species and provide a baseline for monitoring population changes over time. We present recommendations for the conservation of M. mamiratra and highlight the potential for lemur watching, sustained by the strong tourism industry on Nosy Be, to help protect lemur habitat and generate economic opportunities for local communities.

Recent advancements in Earth system science have been marked by the exponential increase in the availability of diverse, multivariate datasets characterised by moderate to high spatio-temporal resolutions. Earth System Data Cubes (ESDCs) have emerged as one suitable solution for transforming this flood of data into a simple yet robust data structure. ESDCs achieve this by organising data into an analysis-ready format aligned with a spatio-temporal grid, facilitating user-friendly analysis and diminishing the need for extensive technical data processing knowledge. Despite these significant benefits, the completion of the entire ESDC life cycle remains a challenging task. Obstacles are not only of a technical nature but also relate to domain-specific problems in Earth system research. There exist barriers to realising the full potential of data collections in light of novel cloud-based technologies, particularly in curating data tailored for specific application domains. These include transforming data to conform to a spatio-temporal grid with minimum distortions and managing complexities such as spatio-temporal autocorrelation issues. Addressing these challenges is pivotal for the effective application of Artificial Intelligence (AI) approaches. Furthermore, adhering to open science principles for data dissemination, reproducibility, visualisation, and reuse is crucial for fostering sustainable research. Overcoming these challenges offers a substantial opportunity to advance data-driven Earth system research, unlocking the full potential of an integrated, multidimensional view of Earth system processes. This is particularly true when such research is coupled with innovative research paradigms and technological progress.

We present a re-discovery of G278.94+1.35a as possibly one of the largest known Galactic supernova remnants (SNRs) – that we name Diprotodon. While previously established as a Galactic SNR, Diprotodon is visible in our new Evolutionary Map of the Universe (EMU) and GaLactic and Extragalactic All-sky MWA (GLEAM) radio continuum images at an angular size of $3{{{{.\!^\circ}}}}33\times3{{{{.\!^\circ}}}}23$, much larger than previously measured. At the previously suggested distance of 2.7 kpc, this implies a diameter of 157$\times$152 pc. This size would qualify Diprotodon as the largest known SNR and pushes our estimates of SNR sizes to the upper limits. We investigate the environment in which the SNR is located and examine various scenarios that might explain such a large and relatively bright SNR appearance. We find that Diprotodon is most likely at a much closer distance of $\sim$1 kpc, implying its diameter is 58$\times$56 pc and it is in the radiative evolutionary phase. We also present a new Fermi-LAT data analysis that confirms the angular extent of the SNR in gamma rays. The origin of the high-energy emission remains somewhat puzzling, and the scenarios we explore reveal new puzzles, given this unexpected and unique observation of a seemingly evolved SNR having a hard GeV spectrum with no breaks. We explore both leptonic and hadronic scenarios, as well as the possibility that the high-energy emission arises from the leftover particle population of a historic pulsar wind nebula.

Obesity is a complex condition which is significantly impacted by an individual’s biology, environment and behavioural factors. Excess energy dense (ED)(kJ/g) food intake (1), higher eating rate (2), increased eating frequency (3) and eating later in the day (4) have all been linked with obesity, but findings are mixed and require clarification using robust and objective measures of food intake behaviour. The aim of this research was to investigate associations between these eating behaviours and energy intake (EI) within a controlled residential setting in 65 participants (BMI 36.4 ±11.0 (range 17.6-65.2); 9 optimal weight, 15 overweight and 41 with obesity/severe obesity; age 44.3±12.7 years (range 18.6-67.6 years), 44F,21M).

As part of baseline measurements for a larger study (5) participants were assessed for 36hrs (twonights) within the Human Intervention Studies Unit at Ulster University, UK, and had ad lib access to a personalised menu (n 54 foods) representing a range of low/high fat macronutrient mix food groups with varying carbohydrate and protein content (6). Food intake and eating behaviour were measured covertly and validated by CCTV. Study outcomes were 24-hour EI (MJ), ED (kJ/g), % nutrient contribution to total EI, as well as parameters of eating including: size (g, kJ) speed (g/min; kJ/min;), number (n) and duration (mins) of eating occasions (defined as consumption of at least 210kJ separated by ≥5 minutes) and the timing of eating (epochs: 7-11am, 11:01-3pm, 3:01-7pm, 7:01-11pm). On the final morning, blood samples were collected before and 90mins after a standardised breakfast for the analysis of glicentin, a proglucagon-derived peptide. Associations between total EI and measures of eating behaviour were assessed using Spearman’s Rank

Correlation analysis showed weak positive associations between total EI and fasting glicentin (r = 0.296, p = 0.024), ED (r = 0.364, p = 0.004), and moderate associations with number (r = 0.419, p = 0.001) and size of eating occasions (r = 0.415, p = 0.005) as well as total weight of food consumed (r= 0.634, p<0.001). Of note, there was also a positive association between EI/eating occasion and a faster eating rate as expressed by [kJ/min (r = 0.519; p<0.001)] but not g/min (r = 0.276, p = 0.07). There was also a stronger relationship between EI and lean mass (r = 0.450, p<0.001) than bodyweight (r = 0.291, p = 0.023).

These findings suggest that food portion size and increased eating frequency may be a more important drivers of EI than dietary ED, and that the rate of eating higher ED foods may be linked to consuming a higher energy meal. These findings are skewed towards individuals with obesity but if confirmed highlight a need for weight management programmes to strengthen strategies to improve portion control and to limit grazing behaviours. There is also a need for robust randomised controlled trials to determine if eating slower reduces overall EI.

Objectives: Understanding how the importance of modifiable risk factors for dementia varies by cognitive status and sex is vital for the development of effective approaches to dementia prevention. We aimed to calculate population attributable fractions (PAFs) for incident dementia associated with sets of risk factors while exploring sex differences in individuals who are cognitively normal (CN) or has mild cognitive impairment (MCI).

Methods: Longitudinal data from the Rush University Memory and Aging Project (MAP) were analysed. Included participants were aged over 50 years and were CN or with a diagnosis of MCI at their baseline assessment. Analyses considered fifteen potential dementia risk factors covering cardiometabolic, lifestyle, psychosocial and sensory domains. We used Cox proportional hazard models to estimate the hazard ratios for incident dementia associated with dementia risk factors and calculated weighted PAFs. All analyses were repeated stratified by sex.

Results: The analytical sample comprised 754 cognitively normal participants (77.2% female) and 242 participants with a diagnosis of MCI (71.9% female), of whom 214 (28.4%) and 120 (49.6%) were diagnosed with dementia across the follow-up, respectively. Although the weighted overall PAF was similar for CN (24.7%) and MCI (25.2%) subgroups, sex differences were present in both. Compared to in females, PAFs were higher in males in both CN (42.5% vs. 25.1%) and MCI (51.6% vs 12.3%) subgroups. The profiles of contributing risk factors also varied by sex. In males, the highest PAFs were smoking (11.1%), vision impairment (6.2%) and stroke (6.0%) in CN and smoking (13.3%), physical inactivity (12.9%) and heart attack (7.9%) in MCI. In females, the highest PAFs were unmarried marital status (4.9%), depression (4.1%) and social isolation (3.8%) in CN and vision impairment (4.4%), increased alcohol intake (3.5%) and depression (2.6%) in MCI.

Conclusions: These findings support the notion that dementia risk is modifiable after the onset of MCI. They also highlight the potential benefits of considering an individual’s cognitive status and sex when formulating dementia prevention strategies.

Control of carbapenem-resistant Acinetobacter baumannii and Pseudomonas aeruginosa spread in healthcare settings begins with timely and accurate laboratory testing practices. Survey results show most Veterans Affairs facilities are performing recommended tests to identify these organisms. Most facilities report sufficient resources to perform testing, though medium-complexity facilities report some perceived barriers.

The cable-driven parallel mechanism (CDPM) is known as an interesting application in industry to pick and place objects owing to its advantages such as large workspaces. In addition to the advantages of this mechanism, there are some challenges to improving performance by considering constraints in different components, such as the behavior of cables, shape, size of the end effector and base, and model of pulleys and actuators. Moreover, the impact of online geometry reconfiguration must be analyzed. This paper demonstrates the impact of these constraints on the performance of reconfigurable CDPM. The methodology is based on the systematic review and meta-analysis guidelines to report the results. The databases used to find the papers are extracted from Scopus and Google Scholar, using related keywords. As a result, the impact of physical constraints on system performance is discussed. A total of 90 and 37 articles are selected, respectively. After removing duplicates and unrelated papers, 88 studies that met the inclusion criteria are selected for review. Even when considering the physical constraints in modeling the mechanism, simplifications in designing a model for the reconfigurable CDPM generate errors. There is a gap in designing high-performance controllers to track desired trajectories while reconfiguring the geometry, and the satisfaction of physical constraints needs to be satisfied. In conclusion, this review presents several constraints in designing a controller to track desired trajectories and improve performance in future work. This paper presents an integrated controller architecture that includes physical constraints and predictive control.

False cleavers (Galium spurium L.) is an aggressive weed from the Rubiaceae. Here we assemble a chromosome-scale draft of its genome, laying the foundations for determining the genetic basis of auxinic herbicide resistance and for systematic research into its polyphyletic genus. We use the genome to examine the population genetics of material from the Canadian Prairies and, in concert with a common greenhouse experiment, to examine whether the phenotypic variation observed in the field results primarily from genetic or environmental factors. The genome assembly covers approximately 85% of G. spurium’s expected 360-Mbp genome size, with 94% of BUSCO (Benchmarking Universal Single-Copy Orthologs) genes complete and most single copy (89%). Approximately 37% of the genome is repetitive elements and 35,540 genes were annotated using RNA-seq data, including 100 homologues for genes involved in, or potentially involved in, herbicide resistance. The genome shows strong synteny with other members of the Rubiaceae, including smooth bedstraw (Cruciata laevipes Opiz) and robusta coffee [Coffea canephora (Pierre ex Froehner]. Double-digested RAD-seq data for the 19 populations from the Canadian Prairies indicated that G. spurium has high levels of population structure (FST = 0.54) and inbreeding (FIS = 0.86) with low levels of hetrozygosity (HO = 0.02) and nucleotide diversity (π = 0.0003). Variation in flowering time and seed weight largely overlapped among populations grown in the greenhouse. A redundancy analysis investigating genotype–phenotype associations showed few associations between single-nucleotide polymorphism (SNP) variation and these characteristics. In contrast, the majority of SNPs under selection were associated with mericarp hook density. This suggests that for most traits, environmental variation rather than genetic variation likely underlies phenotypic differences observed in the field. Several genes of interest, including several homologues involved in the assembly of the Skp1-Cullin-F-Box IR1/AFB E3 ubiquitin ligase complex (e.g., CAND1, ECR1), are located in areas of the genome with evidence of selection and are targets for further investigation.

Photosynthetically active radiation (PAR) at the ice-ocean interface is critical for primary production. The value of PAR is affected by the thickness of snow and sea ice, with additional absorbers (e.g. algae) further attenuating PAR. Sea-ice algae exhibit a substantial geo-temporal variance in column-integrated concentration (0–500 mg chl-a m−2) and are typically present within the bottom 0.01–0.2 m of sea ice. PAR transmittance is affected by algae concentrations and vertical thicknesses of ice algal layers. Small column-integrated concentrations of chl-a (~<10 mg chl-a m−2) have a negligible effect on the value of PAR transmittance, and large column-integrated concentrations of chl-a (~>10 mg chl-a m−2) can significantly reduce the value of PAR transmittance. Large column-integrated concentrations of chl-a need consideration when calculating PAR transmittance in areas of high sea-ice algae biomass (e.g. the ‘interior’ shelves of the Arctic Ocean, the Canadian Arctic and Antarctica).

As TeV gamma-ray astronomy progresses into the era of the Cherenkov Telescope Array (CTA), instantaneously following up on gamma-ray transients is becoming more important than ever. To this end, a worldwide network of Imaging Atmospheric Cherenkov Telescopes has been proposed. Australia is ideally suited to provide coverage of part of the Southern Hemisphere sky inaccessible to H.E.S.S. in Namibia and the upcoming CTA-South in Chile. This study assesses the sources detectable by a small, transient-focused array in Australia based on CTA telescope designs. The TeV emission of extragalactic sources (including the majority of gamma-ray transients) can suffer significant absorption by the extragalactic background light. As such, we explored the improvements possible by implementing stereoscopic and topological triggers, as well as lowered image cleaning thresholds, to access lower energies. We modelled flaring gamma-ray sources based on past measurements from the satellite-based gamma-ray telescope Fermi-LAT. We estimate that an array of four Medium-Sized Telescopes (MSTs) would detect $\sim$24 active galactic nucleus flares >5$\sigma$ per year, up to a redshift of $z\approx1.5$. Two MSTs achieved $\sim$80–90% of the detections of four MSTs. The modelled Galactic transients were detectable within the observation time of one night, 11 of the 21 modelled gamma-ray bursts were detectable, as were $\sim$10% of unidentified transients. An array of MST-class telescopes would thus be a valuable complementary telescope array for transient TeV gamma-ray astronomy.