During the 2018 K$\unicode{x012B}$lauea lower East Rift Zone eruption, lava from 24 fissures inundated more than 8000 acres of land, destroying more than 700 structures over three months. Eruptive activity eventually focused at a single vent characterized by a continuously fed lava pond that was drained by a narrow spillway into a much wider, slower channelized flow. The spillway exhibited intervals of ‘pulsing’ behaviour in which the lava depth and velocity were observed to oscillate on time scales of several minutes. At the time, this was attributed to variations in vesiculation originating at depth. Here, we construct a toy fluid dynamical model of the pond–spillway system, and present an alternative hypothesis in which pulsing is generated at the surface, within this system. We posit that the appearance of pulsing is due to a supercritical Hopf bifurcation driven by an increase in the Reynolds number. Asymptotics for the limit cycle near the bifurcation point are derived with averaging methods and compare favourably with the cycle periodicity. Because oscillations in the pond were not observable directly due to the elevation of the cone rim and an obscuring volcanic plume, we model the observations using a spatially averaged Saint-Venant model of the spillway forced by the pond oscillator. The predicted spillway cycle periodicity and waveforms compare favourably with observations made during the eruption. The unusually well-documented nature of this eruption enables estimation of the viscosity of the erupting lava.

Despite the growing availability of sensing and data in general, we remain unable to fully characterize many in-service engineering systems and structures from a purely data-driven approach. The vast data and resources available to capture human activity are unmatched in our engineered world, and, even in cases where data could be referred to as “big,” they will rarely hold information across operational windows or life spans. This paper pursues the combination of machine learning technology and physics-based reasoning to enhance our ability to make predictive models with limited data. By explicitly linking the physics-based view of stochastic processes with a data-based regression approach, a derivation path for a spectrum of possible Gaussian process models is introduced and used to highlight how and where different levels of expert knowledge of a system is likely best exploited. Each of the models highlighted in the spectrum have been explored in different ways across communities; novel examples in a structural assessment context here demonstrate how these approaches can significantly reduce reliance on expensive data collection. The increased interpretability of the models shown is another important consideration and benefit in this context.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

We present the third data release from the Parkes Pulsar Timing Array (PPTA) project. The release contains observations of 32 pulsars obtained using the 64-m Parkes ‘Murriyang’ radio telescope. The data span is up to 18 yr with a typical cadence of 3 weeks. This data release is formed by combining an updated version of our second data release with $\sim$3 yr of more recent data primarily obtained using an ultra-wide-bandwidth receiver system that operates between 704 and 4032 MHz. We provide calibrated pulse profiles, flux density dynamic spectra, pulse times of arrival, and initial pulsar timing models. We describe methods for processing such wide-bandwidth observations and compare this data release with our previous release.

Understanding the distribution and extent of suitable habitats is critical for the conservation of endangered and endemic taxa. Such knowledge is limited for many Central African species, including the rare and globally threatened Grey-necked Picathartes Picathartes oreas, one of only two species in the family Picathartidae endemic to the forests of Central Africa. Despite growing concerns about land-use change resulting in fragmentation and loss of forest cover in the region, neither the extent of suitable habitat nor the potential species’ distribution is well known. We combine 339 (new and historical) occurrence records of Grey-necked Picathartes with environmental variables to model the potential global distribution. We used a Maximum Entropy modelling approach that accounted for sampling bias. Our model suggests that Grey-necked Picathartes distribution is strongly associated with steeper slopes and high levels of forest cover, while bioclimatic, vegetation health, and habitat condition variables were all excluded from the final model. We predicted 17,327 km2 of suitable habitat for the species, of which only 2,490 km2 (14.4%) are within protected areas where conservation designations are strictly enforced. These findings show a smaller global distribution of predicted suitable habitat forthe Grey-necked Picathartes than previously thought. This work provides evidence to inform a revision of the International Union for Conservation of Nature (IUCN) Red List status, and may warrant upgrading the status of the species from “Near Threatened” to “Vulnerable”.

The hypothesis that violence—especially gang violence—behaves like a contagious disease has grown in popularity in recent years. Scholars have long observed the tendency for violence to cluster in time and space, but little research has focused on empirically unpacking the mechanisms that make violence contagious. In the context of gang violence, retaliation is the prototypical mechanism to explain why violence begets violence. In this study, we leverage relational event models (REMs)—an underutilized yet particularly well-suited modeling technique to study the dynamics of inter-gang violence. We use REMs to examine gang violence’s tendency to replicate—for which retaliation is but one plausible mechanism—and its tendency to diffuse to other groups. We rely on data on conflicts between gangs in a region of Los Angeles over 3 years. We consider how the characteristics of gangs, their spatial proximity, networks of established rivalries, and the evolving history, directionality, and structure of conflicts predict future inter-gang conflicts. While retaliation is an important mechanism for the replication of violence, established rivalries, and inertia—a gang’s tendency to continue attacking the same group—are more important drivers of future violence. We also find little evidence for an emerging pecking order or status hierarchy between gangs suggested by other scholars. However, we find that gangs are more likely to attack multiple gangs in quick succession. We propose that gang violence is more likely to diffuse to other groups because of the boost of internal group processes an initial attack provides.

Approximately 80 million people live with chronic hepatitis B virus (HBV) infection in the WHO Africa Region. The natural history of HBV infection in this population is poorly characterised, and may differ from patterns observed elsewhere due to differences in prevailing genotypes, environmental exposures, co-infections, and host genetics. Existing research is largely drawn from small, single-centre cohorts, with limited follow-up time. The Hepatitis B in Africa Collaborative Network (HEPSANET) was established in 2022 to harmonise the process of ongoing data collection, analysis, and dissemination from 13 collaborating HBV cohorts in eight African countries. Research priorities for the next 5 years were agreed upon through a modified Delphi survey prior to baseline data analysis being conducted. Baseline data on 4,173 participants with chronic HBV mono-infection were collected, of whom 38.3% were women and the median age was 34 years (interquartile range 28–42). In total, 81.3% of cases were identified through testing of asymptomatic individuals. HBeAg-positivity was seen in 9.6% of participants. Follow-up of HEPSANET participants will generate evidence to improve the diagnosis and management of HBV in this region.

In Iran, studies of the transition from hunting and gathering to farming and herding have focused on early developments in the Zagros Mountains. Here, the authors present new zooarchaeological data from Hotu Cave, which throw light on sheep/goat management and domestication during the Epipalaeolithic–Neolithic transition on the southern shores of the Caspian Sea. Gazelle dominate the Epipalaeolithic levels, while sheep/goat are most abundant in the Neolithic. Large quantities of perinatal sheep/goat remains from the Early Neolithic indicate that these animals were actively managed in or close to the cave. The results point towards the importance in Iran of local developments beyond the Zagros, adding nuance to the general model of domestication in South-west Asia.

Broiler chickens are the most numerous terrestrial farmed animals on earth. These birds can suffer a range of pathologies which result in lameness, and one technique for assessing the impact of lameness on the individual bird, and on the flock has been gait scoring. This paper describes a study where the results of the same training programme for validated gait scoring are compared for groups of assessors in Thailand, Brazil and New Zealand. A uniform course of training carried out in the classroom, through video assessment and through on-farm training was carried out in the countries named; a total of 95 persons being trained overall. A measure of agreement with the reference scale for the assessors' numerical responses was carried out using a Cohen's Kappa test, and the results indicated significant differences in the ‘origin position’ ie the view taken by the assessors of the impact of lameness on the bird before training had taken place, but a high degree of consistency in the response to training. The study demonstrated that gait scoring can be learned by assessors from different geographical and social backgrounds, and that the ‘rate of learning’ – the improvement in performance in relation to a standard, was similar between the countries studied. The ‘origin’ and ‘final’ position of the assessors pre- and post-training, from the different countries in relation to the reference standard is discussed.

Animal and human data demonstrate independent relationships between fetal growth, hypothalamic-pituitary-adrenal axis function (HPA-A) and adult cardiometabolic outcomes. While the association between fetal growth and adult cardiometabolic outcomes is well-established, the role of the HPA-A in these relationships is unclear. This study aims to determine whether HPA-A function mediates or moderates this relationship. Approximately 2900 pregnant women were recruited between 1989-1991 in the Raine Study. Detailed anthropometric data was collected at birth (per cent optimal birthweight [POBW]). The Trier Social Stress Test was administered to the offspring (Generation 2; Gen2) at 18 years; HPA-A responses were determined (reactive responders [RR], anticipatory responders [AR] and non-responders [NR]). Cardiometabolic parameters (BMI, systolic BP [sBP] and LDL cholesterol) were measured at 20 years. Regression modelling demonstrated linear associations between POBW and BMI and sBP; quadratic associations were observed for LDL cholesterol. For every 10% increase in POBW, there was a 0.54 unit increase in BMI (standard error [SE] 0.15) and a 0.65 unit decrease in sBP (SE 0.34). The interaction between participant’s fetal growth and HPA-A phenotype was strongest for sBP in young adulthood. Interactions for BMI and LDL-C were non-significant. Decomposition of the total effect revealed no causal evidence of mediation or moderation.

Psychiatrists often order investigations such as blood tests, neuroimaging and electroencephalograms for their patients. Rationales include ruling out ‘organic’ causes of psychiatric presentations, providing baseline parameters before starting psychotropic medications, and screening for general cardiometabolic health. Hospital protocols often recommend an extensive panel of blood tests on admission to a psychiatric ward. In this Against the Stream article, we argue that many of these investigations are at best useless and at worst harmful: the yield of positive findings that change clinical management is extremely low; special investigations are a poor substitute for a targeted history and examination; and incidental findings may cause anxiety and further unwarranted investigation. Cognitive and cultural reasons why over-investigation continues are discussed. We conclude by encouraging a more targeted approach guided by a thorough bedside clinical assessment.

Knotweed (Fallopia spp.) is an herbaceous perennial from East Asia that was brought to Europe and North America and, despite control efforts, subsequently spread aggressively on both continents. Data are available on knotweed’s modes of sexual and asexual spread, historical spread, preferred habitat, and ploidy levels. Incomplete information is available on knotweed’s current global geographic distribution and genetic diversity. The chemical composition of knotweed leaves and rhizomes has been partially discovered as related to its ability to inhibit growth and germination of neighboring plant communities via phytochemicals. There is still critical information missing. There are currently no studies detailing knotweed male and female fertility. Specifically, information on pollen viability would be important for further understanding sexual reproduction as a vector of spread in knotweed. This information would help managers determine the potential magnitude of knotweed sexual reproduction and the continued spread of diverse hybrid swarms. The potential range of knotweed and its ability to spread into diverse habitats makes studies on knotweed seed and rhizome cold tolerance of utmost importance, yet to date no such studies have been conducted. There is also a lack of genetic information available on knotweed in the upper Midwest. Detailed genetic information, such as ploidy levels and levels of genetic diversity, would answer many questions about knotweed in Minnesota, including understanding its means of spread, what species are present in what densities, and current levels of hybridization. This literature review summarizes current literature on knotweed to better understand its invasiveness and to highlight necessary future research that would benefit and inform knotweed management in the upper Midwest.

OBJECTIVES/GOALS: Irreproducible and incompletely reported research lead to misallocated resources, wasted effort in pursing inappropriate avenues of investigation, and loss of public trust. To address this challenge, we employed a Team Science approach to create a multi-modal program to support Rigor, Reproducibility, and Reporting in Translational Science. METHODS/STUDY POPULATION: We conducted literature searches to reveal sources of irreproducibility and recommended corrective actions, invited leaders in the field to give lectures on opportunities to support reproducible science, and worked with the Rockefeller team science leadership group to instill an overarching rigor approach, infused into all training efforts. This multifaceted program was labeled R3 (R-cubed) for Enhancing Scientific Rigor, Reproducibility, and Reporting. RESULTS/ANTICIPATED RESULTS: Didactic Courses:

• Introduction to Biostatistics and Critical Thinking – focus on pitfalls in inferential statistics, consequences of poor research, and errors in published research.

• Scientific Writing – teaches methods and procedures in writing to ensure reproducibility. Lecture Series

• Established nine lectures on topics related to R3, including Data Management, Statistical Methods, Genomic Analyses, Data Repositories, Data Sharing, Pharmacy Formulation, and e-lab notebooks. Website

• Creating a comprehensive website as repository for research, methods, programs, updates, and improvements related to R3. KL2 Clinical Scholars Seminars and Navigation

• Scholars participate in seminars and tutorials to discuss opportunities to improve R3 across the research life-course.

DISCUSSION/SIGNIFICANCE OF IMPACT: Striving for research reproducibility takes focused energy, discipline, and vigilance, but the effort is worthwhile as rigorous and reproducible science is the prerequisite for successful translation of great discoveries into improved health. CONFLICT OF INTEREST DESCRIPTION: none