This statement draws on over 1,000 person-years’ work by the authors on the conservation of non-human primates and their habitats. It harnesses knowledge of what works for primates in the context of broader issues of global ecological integrity and increasing risk to all primate species, including our own. It indicates how conserving primates can protect and advance the interests of Indigenous Peoples, local communities, developing countries and humankind as a whole. It offers ideas and text for use by those engaged in relevant issues who are unfamiliar with the subject, with the aim of making conservation action easier to understand, to communicate and to do. It highlights four key elements of effective strategy: avoiding damage to native forest ecosystems, restoring native forest ecosystems, building conservation partnerships, and managing and using knowledge. Additionally, it advocates an approach in which all four elements are integrated, as a way to balance human rights and nature rights, to postpone and ultimately to prevent Earth system breakdown, and to promote mutual aid between people and nature.

Laser–target interactions generate intense electromagnetic pulses (EMPs) that can interfere with measurements and damage equipment. In this paper we show that applying a magnetic field to nanosecond pulse laser–target interactions decreases the magnitude of EMPs. We demonstrate this effect in two experiments with different geometries (spherical versus planar), laser intensities ($\sim {10}^{13}$ versus $\sim {10}^{15}$ W/cm${}^2$) and applied field strength (12 versus 0.1 T) that both observed suppression of EMPs in approximately the 1 GHz band (by factors of $0.65\times$ and $0.32\times$, respectively). We then observe the opposite effect at high intensities with a picosecond pulse: for planar experiments with laser intensities of approximately ${10}^{19}$ W/cm${}^2$ and magnetic fields of 6–10 T, the magnitude of EMPs is increased by a factor of $1.75\times$. These results provide a benchmark for models of EMP generation, but suggest that magnetic fields are not a viable solution for mitigating EMPs in the high-intensity laser facilities where they are most damaging.

Bars are ubiquitous morphological features in the observed distribution of galaxies. There are similarly many methods for classifying these features and, without a strict theoretical definition or common standard practice, this is often left to circumstance. So, we were concerned whether astronomers even agree on the bar which they perceive in a given galaxy and whether this could impact perceived scientific results. As an elementary test, we twenty-one astronomers with varied experience in studying resolved galaxies and circumstances, have each assessed 200 galaxy images, spanning the early phase of bar evolution in two different barred galaxy simulations. We find variations exist within the classification of all the standard bar parameters assessed: bar length, axis-ratio, pitch-angle and even whether a bar is present at all. If this is indicative of the wider community, it has implications for interpreting morphological trends, such as bar-end effects. Furthermore, we find that it is surprisingly not expertise but gender, followed by career stage, which gives rise to the largest discrepancies in the reported bar parameters. Currently, automation does not seem to be a viable solution, with bar classifications from two automated bar-finding algorithms tested and failing to find bars in snapshots where most astronomers agree a bar must exist. Increasing dependence on machine learning or crowdsourcing with a training dataset can only serve to obfuscate any existing biases if these originate from the specific astronomer producing the training material. On the strength of this small sample, we encourage an interim best practice to reduce the impact of any possible classification bias and set goals for the community to resolve the issue in the future.

Human milk and direct breastfeeding provide the optimal, biologically normative nutrition for hospitalised infants, with well-established benefits for immune, gut, cardiac, brain, and maternal health. Despite these benefits, human milk and breastfeeding rates for infants with CHD in high-resource countries are typically low, and there are no formal guidelines to drive CHD breastfeeding practice. Our aim is to (1) summarise the evidence on breastfeeding for infants with CHD, (2) discuss key barriers to and facilitators of breastfeeding in this population, (3) identify critical research and practice gaps to improve breastfeeding care in CHD, and (4) provide recommendations for clinical practice and future research.

Primary breastfeeding barriers for infants with CHD include (1) concern for dysphagia/aspiration, (2) concerns related to weight gain, (3) clinical instability/sickness, (4) developmental considerations, (5) general breastfeeding challenges, and (6) workflow and implementation issues, with racism and health disparities also contributing. The evidence to support these barriers is limited and often conflicting. Breastfeeding facilitators for preterm infants are well described, but facilitators may require modification for infants with CHD. Most lactation interventions have not been tested in CHD populations. Current evidence does not support automatic withholding of breastfeeding from infants with CHD; rather, the benefits of breastfeeding likely outweigh many potential concerns. There is a critical need for research and quality improvement to identify interventions that equitably and effectively support breastfeeding for infants with CHD and to evaluate the effect of breastfeeding on short- and long-term physical, psychological, and developmental outcomes for infants and families.

The dhole Cuon alpinus is a large canid that is categorized as Endangered on the IUCN Red List and at risk of global extinction. Information on the spatial distribution of suitable habitat is important for conservation planning but is largely unavailable. We quantified the spatial distribution of potential range as well as the relative probability of dhole occurrence across large parts of the species’ global range. We used the MaxEnt algorithm to produce a multi-scale environmental niche model based on 24 environmental variables and dhole occurrence data from 12 countries. We identified three regions where dhole conservation should be focused: western India, central India, and across the Himalayan foothills through Southeast Asia. Connectivity between suitable areas was poor, so coordinated action among these regions should be a priority. For instance, transboundary dhole conservation initiatives across the Himalayas from southern China, Myanmar, north-east India, Nepal and Bhutan need to be initiated. We also highlight the value of improving dhole population viability on unprotected land and increasing monitoring in the northern parts of its historic distribution, in particular in areas within mainland China.

The treatment recommendation based on a network meta-analysis (NMA) is usually the single treatment with the highest expected value (EV) on an evaluative function. We explore approaches that recommend multiple treatments and that penalise uncertainty, making them suitable for risk-averse decision-makers. We introduce loss-adjusted EV (LaEV) and compare it to GRADE and three probability-based rankings. We define properties of a valid ranking under uncertainty and other desirable properties of ranking systems. A two-stage process is proposed: the first identifies treatments superior to the reference treatment; the second identifies those that are also within a minimal clinically important difference (MCID) of the best treatment. Decision rules and ranking systems are compared on stylised examples and 10 NMAs used in NICE (National Institute of Health and Care Excellence) guidelines. Only LaEV reliably delivers valid rankings under uncertainty and has all the desirable properties. In 10 NMAs comparing between 5 and 41 treatments, an EV decision maker would recommend 4–14 treatments, and LaEV 0–3 (median 2) fewer. GRADE rules give rise to anomalies, and, like the probability-based rankings, the number of treatments recommended depends on arbitrary probability cutoffs. Among treatments that are superior to the reference, GRADE privileges the more uncertain ones, and in 3/10 cases, GRADE failed to recommend the treatment with the highest EV and LaEV. A two-stage approach based on MCID ensures that EV- and LaEV-based rules recommend a clinically appropriate number of treatments. For a risk-averse decision maker, LaEV is conservative, simple to implement, and has an independent theoretical foundation.

Precision or “Personalized Medicine” and “Big Data” are growing trends in the biomedical research community and highlight an increased focus on access to larger datasets to effectively explore disease processes at the molecular level versus the previously common one-size-fits all approach. This focus necessitated a local transition from independent lab and siloed projects to a single software application utilizing a common ontology to create access to data from multiple repositories. Use of a common system has allowed for increased ease of collaboration and access to quality biospecimens that are extensively annotated with clinical, molecular, and patient associated data. The software needed to function at an enterprise level while continuing to allow investigators the autonomy and security access they desire. To identify a solution, a working group comprised of representation from independent repositories and areas of research focus across departments was established and responsible for review and implementation of an enterprise-wide biospecimen management system. Central to this process was the creation of a unified vocabulary across all repositories, including consensus around source of truth, standardized field definitions, and shared terminology.

From early on, infants show a preference for infant-directed speech (IDS) over adult-directed speech (ADS), and exposure to IDS has been correlated with language outcome measures such as vocabulary. The present multi-laboratory study explores this issue by investigating whether there is a link between early preference for IDS and later vocabulary size. Infants’ preference for IDS was tested as part of the ManyBabies 1 project, and follow-up CDI data were collected from a subsample of this dataset at 18 and 24 months. A total of 341 (18 months) and 327 (24 months) infants were tested across 21 laboratories. In neither preregistered analyses with North American and UK English, nor exploratory analyses with a larger sample did we find evidence for a relation between IDS preference and later vocabulary. We discuss implications of this finding in light of recent work suggesting that IDS preference measured in the laboratory has low test-retest reliability.

This article examines the development, early operation and subsequent failure of the Tot-Kolowa Red Cross irrigation scheme in Kenya’s Kerio Valley. Initially conceived as a technical solution to address regional food insecurity, the scheme aimed to scale up food production through the implementation of a fixed pipe irrigation system and the provision of agricultural inputs for cash cropping. A series of unfolding circumstances, however, necessitated numerous modifications to the original design as the project became increasingly entangled with deep and complex histories of land use patterns, resource allocation and conflict. Failure to understand the complexity of these dynamics ultimately led to the project’s collapse as the region spiralled into a period of significant unrest. In tracing these events, we aim to foreground the lived realities of imposed development, including both positive and negative responses to the scheme’s participatory obligations and its wider impact on community resilience.

Different fertilization strategies can be adopted to optimize the productive components of an integrated crop–livestock systems. The current research evaluated how the application of P and K to soybean (Glycine max (L.) Merr.) or Urochloa brizantha (Hochst. ex A. Rich.) R. D. Webster cv. BRS Piatã associated with nitrogen or without nitrogen in the pasture phase affects the accumulation and chemical composition of forage and animal productivity. The treatments were distributed in randomized blocks with three replications. Four fertilization strategies were tested: (1) conventional fertilization with P and K in the crop phase (CF–N); (2) conventional fertilization with nitrogen in the pasture phase (CF + N); (3) system fertilization with P and K in the pasture phase (SF–N); (4) system fertilization with nitrogen in the pasture phase (SF + N). System fertilization increased forage accumulation from 15 710 to 20 920 kg DM ha/year compared to conventional without nitrogen. Stocking rate (3.1 vs. 2.8 AU/ha; SEM = 0.12) and gain per area (458 vs. 413 kg BW/ha; SEM = 27.9) were higher in the SF–N than CF–N, although the average daily gain was lower (0.754 vs. 0.792 kg LW/day; SEM = 0.071). N application in the pasture phase, both, conventional and system fertilization resulted in higher crude protein, stocking rate and gain per area. Applying nitrogen and relocate P and K from crop to pasture phase increase animal productivity and improve forage chemical composition in integrated crop–livestock system.

Pregnancy is a time of increased vulnerability to psychopathology, yet limited work has investigated the extent to which variation in psychopathology during pregnancy is shared and unshared across syndromes and symptoms. Understanding the structure of psychopathology during pregnancy, including associations with childhood experiences, may elucidate risk and resilience factors that are transdiagnostic and/or specific to particular psychopathology phenotypes. Participants were 292 pregnant individuals assessed using multiple measures of psychopathology. Confirmatory factor analyses found evidence for a structure of psychopathology consistent with the Hierarchical Taxonomy of Psychopathology (HiTOP). A common transdiagnostic factor accounted for most variation in psychopathology, and both adverse and benevolent childhood experiences (ACEs and BCEs) were associated with this transdiagnostic factor. Furthermore, pregnancy-specific anxiety symptoms most closely reflected the dimension of Fear, which may suggest shared variation with manifestations of fear that are not pregnancy-specific. ACEs and BCEs also linked to specific prenatal psychopathology involving thought problems, detachment, and internalizing, externalizing, antagonistic, and antisocial behavior. These findings extend the dimensional and hierarchical HiTOP model to pregnant individuals and show how maternal childhood risk and resilience factors relate to common and specific forms of psychopathology during pregnancy as a period of enhanced vulnerability.

Contact with livestock and consumption of unpasteurised dairy products are associated with an increased risk of zoonotic and foodborne infection, particularly among populations with close animal contact, including pastoralists and semi-pastoralists. However, there are limited data on disease risk factors among pastoralists and other populations where livestock herding, particularly of dromedary camels, is common. This cross-sectional study used a previously validated survey instrument to identify risk factors for self-reported symptoms. Adults (n = 304) were randomly selected from households (n = 171) in the Somali Region of Ethiopia, a region characterised by chronic food insecurity, population displacement, recurrent droughts and large semi-pastoralist and pastoralist populations. Multivariable logistic regression assessed associations between self-reported symptoms and type of milk consumed, controlling for demographics and human-animal interaction. Consumption of days-old unrefrigerated raw camel milk was significantly associated with symptoms in the 30 days prior to the survey (AOR = 5.07; 95% CI 2.41–10.66), after controlling for age, refugee status, sanitation, camel ownership and source of drinking water and accounting for clustering. Consumption of days-old unrefrigerated raw ruminant milk was significantly associated with symptoms (AOR = 4.00, 95% CI 1.27–12.58). Source of drinking water and camel ownership, a proxy for camel contact, were significantly associated with the outcome in each model. There were no significant associations between self-reported symptoms and fresh or soured animal milk consumption. Research is needed to identify pathogens and major routes of transmission. Tailored communication campaigns to encourage safe food preparation should also be considered.

Seed retention, and ultimately seed shatter, are extremely important for the efficacy of harvest weed seed control (HWSC) and are likely influenced by various agroecological and environmental factors. Field studies investigated seed-shattering phenology of 22 weed species across three soybean [Glycine max (L.) Merr.]-producing regions in the United States. We further evaluated the potential drivers of seed shatter in terms of weather conditions, growing degree days, and plant biomass. Based on the results, weather conditions had no consistent impact on weed seed shatter. However, there was a positive correlation between individual weed plant biomass and delayed weed seed–shattering rates during harvest. This work demonstrates that HWSC can potentially reduce weed seedbank inputs of plants that have escaped early-season management practices and retained seed through harvest. However, smaller individuals of plants within the same population that shatter seed before harvest pose a risk of escaping early-season management and HWSC.

We present an overview of the Middle Ages Galaxy Properties with Integral Field Spectroscopy (MAGPI) survey, a Large Program on the European Southern Observatory Very Large Telescope. MAGPI is designed to study the physical drivers of galaxy transformation at a lookback time of 3–4 Gyr, during which the dynamical, morphological, and chemical properties of galaxies are predicted to evolve significantly. The survey uses new medium-deep adaptive optics aided Multi-Unit Spectroscopic Explorer (MUSE) observations of fields selected from the Galaxy and Mass Assembly (GAMA) survey, providing a wealth of publicly available ancillary multi-wavelength data. With these data, MAGPI will map the kinematic and chemical properties of stars and ionised gas for a sample of 60 massive (${>}7 \times 10^{10} {\mathrm{M}}_\odot$) central galaxies at $0.25 < z <0.35$ in a representative range of environments (isolated, groups and clusters). The spatial resolution delivered by MUSE with Ground Layer Adaptive Optics ($0.6-0.8$ arcsec FWHM) will facilitate a direct comparison with Integral Field Spectroscopy surveys of the nearby Universe, such as SAMI and MaNGA, and at higher redshifts using adaptive optics, for example, SINS. In addition to the primary (central) galaxy sample, MAGPI will deliver resolved and unresolved spectra for as many as 150 satellite galaxies at $0.25 < z <0.35$, as well as hundreds of emission-line sources at $z < 6$. This paper outlines the science goals, survey design, and observing strategy of MAGPI. We also present a first look at the MAGPI data, and the theoretical framework to which MAGPI data will be compared using the current generation of cosmological hydrodynamical simulations including EAGLE, Magneticum, HORIZON-AGN, and Illustris-TNG. Our results show that cosmological hydrodynamical simulations make discrepant predictions in the spatially resolved properties of galaxies at $z\approx 0.3$. MAGPI observations will place new constraints and allow for tangible improvements in galaxy formation theory.