This proof-of-concept study evaluated an optimization strategy for the Community Case Detection Tool (CCDT) aimed at improving community-level mental health detection and help-seeking among children aged 6–18 years. The optimization strategy, CCDT+, combined data-driven supervision with motivational interviewing techniques and behavioural nudges for community gatekeepers using the CCDT. This mixed-methods study was conducted from January to May 2023 in Palorinya refugee settlement in Uganda. We evaluated (1) the added value of the CCDT+ in improving the accuracy of detection and mental health service utilization compared to standard CCDT, and (2) implementation outcomes of the CCDT+. Of the 1026 children detected, 801 (78%) sought help, with 656 needing mental health care (PPV = 0.82; 95% CI: 0.79, 0.84). The CCDT+ significantly increased detection accuracy, with 2.34 times higher odds compared to standard CCDT (95% CI: 1.41, 3.83). Additionally, areas using the CCDT+ had a 2.05-fold increase in mental health service utilization (95% CI: 1.09, 3.83). The CCDT+ shows promise as an embedded quality-optimization process for the detection of mental health problems among children and enhance help-seeking, potentially leading to more efficient use of mental health care resources.

An array of information about the Antarctic ice sheet can be extracted from ice-sheet internal architecture imaged by airborne ice-penetrating radar surveys. We identify, trace and date three key internal reflection horizons (IRHs) across multiple radar surveys from South Pole to Dome A, East Antarctica. Ages of ~38 ± 2.2, ~90 ± 3.6 and ~162 ± 6.7 ka are assigned to the three IRHs, with verification of the upper IRH age from the South Pole ice core. The resultant englacial stratigraphy is used to identify the locations of the oldest ice, specifically in the upper Byrd Glacier catchment and the Gamburtsev Subglacial Mountains. The distinct glaciological conditions of the Gamburtsev Mountains, including slower ice flow, low geothermal heat flux and frozen base, make it the more likely to host the oldest ice. We also observe a distinct drawdown of IRH geometry around South Pole, indicative of melting from enhanced geothermal heat flux or the removal of deeper, older ice under a previous faster ice flow regime. Our traced IRHs underpin the wider objective to develop a continental-scale database of IRHs which will constrain and validate future ice-sheet modelling and the history of the Antarctic ice sheet.

Flumioxazin and S-metolachlor are widely used in conventional sweetpotato production in North Carolina and other states; however, some growers have recently expressed concerns about potential effects of these herbicides on sweetpotato yield and quality. Previous research indicates that activated charcoal has the potential to reduce herbicide injury. Field studies were conducted in 2021 and 2022 to determine whether flumioxazin applied preplant and S-metolachlor applied before and after transplanting negatively affect sweetpotato yield and quality when activated charcoal is applied with transplant water. The studies evaluated five herbicide treatments and two activated charcoal treatments. Herbicide treatments included two flumioxazin rates, one S-metolachlor rate applied immediately before and immediately after transplanting, and no herbicide. Charcoal treatments consisted of activated charcoal applied at 9 kg ha−1, and no charcoal. No visual injury from herbicides or charcoal was observed. Likewise, no effect of herbicide or charcoal treatment on no. 1, marketable (sum of no. 1 and jumbo grades), or total yield (sum of canner, no. 1, and jumbo grades) was observed. Additionally, shape analysis conducted on calculated length-to-width ratio (LWR) for no. 1 sweetpotato roots found no effect from flumioxazin at either rate on sweetpotato root shape. However, both S-metolachlor treatments resulted in lower LWR of no. 1 sweetpotato roots in 2021. Results are consistent with prior research and indicate that flumioxazin and S-metolachlor are safe for continued use on sweetpotato at registered rates.

This paper analyses the institutional incentives and constraints of the Black Mouth Society – the traditional police of the pre-colonial Mandan and Hidatsa tribes – to understand how it successfully maintained social order without abusing power. The Black Mouth Society was a fraternal organization of middle-aged men that monitored and enforced rules created by the village council and chiefs. Two categories of institutions ensured reliable policing. First, on the front end, a long probationary period and system of unanimous consent facilitated the selection of reputable men who would wield policing power responsibly, reducing the chance of predation. However, individual Black Mouths occasionally abused their power. Therefore, on the back end, public communication created common knowledge, leading to social sanctions in the form of shame and restitution that punished abuses and limited further abuse. Thus, well-functioning self-governance, including reliable policing, is possible without a centralized state, as these tribes have demonstrated.

We present radio observations of the galaxy cluster Abell S1136 at 888 MHz, using the Australian Square Kilometre Array Pathfinder radio telescope, as part of the Evolutionary Map of the Universe Early Science program. We compare these findings with data from the Murchison Widefield Array, XMM-Newton, the Wide-field Infrared Survey Explorer, the Digitised Sky Survey, and the Australia Telescope Compact Array. Our analysis shows the X-ray and radio emission in Abell S1136 are closely aligned and centered on the Brightest Cluster Galaxy, while the X-ray temperature profile shows a relaxed cluster with no evidence of a cool core. We find that the diffuse radio emission in the centre of the cluster shows more structure than seen in previous low-resolution observations of this source, which appeared formerly as an amorphous radio blob, similar in appearance to a radio halo; our observations show the diffuse emission in the Abell S1136 galaxy cluster contains three narrow filamentary structures visible at 888 MHz, between $\sim$80 and 140 kpc in length; however, the properties of the diffuse emission do not fully match that of a radio (mini-)halo or (fossil) tailed radio source.

Introducing soybean cultivars resistant to 2,4-D and dicamba allowed for postemergence applications of these herbicides. These herbicides pose a high risk for off-target movement, and the potential influence on crops such as hemp is unknown. Two studies were conducted from 2020 through 2022 in controlled environments to evaluate hemp response to rates simulating off-target events of 2,4-D and dicamba. The objectives of these studies were to (1) determine the effects of herbicide (2,4-D and dicamba) and rate (1× to 1/100,000× labeled rate) on visible injury, height, and branching, and (2) determine the effect of 2,4-D rate (1× to 1/100,000× labeled rate) on visible injury, height, branching, and reproductive parameters. Herbicides were applied in the early vegetative stage, and evaluations took place 14 and 28 d after treatment (DAT) and at trial termination (42 DAT in the greenhouse trial and at harvest in the growth chamber trial). In the greenhouse study, 2,4-D and dicamba at the 1× rate, and the 1/10× rate of dicamba, caused 68%, 78%, and 20% injury 28 DAT, respectively. At the time of trial termination 42 DAT, plants treated with 1× rates of 2,4-D and dicamba, or 1/10× dicamba, were 19, 25, and 9 cm shorter than the nontreated control, respectively. Simulated off-target rates of 2,4-D and dicamba did not influence branching or plant weight at trial termination. In the growth chamber study, the 1× and 1/10× rates of 2,4-D caused 82% and 2% injury 28 DAT, respectively. Plant height, fresh weight, and cannabidiol (CBD) levels of plants treated with simulated off-target rates of 2,4-D were not different from the nontreated control. These studies suggest that hemp grown for CBD exposed to off-target rates of 2,4-D or dicamba in early vegetative stages may not have distinguishable effects 42 DAT or at harvest.

Greenhouse trials were conducted to determine the response of stevia to reduced-risk synthetic and nonsynthetic herbicides applied over-the-top post-transplant. In addition, field trials were conducted with stevia grown in a polyethylene mulch production system to determine crop response and weed control in planting holes to reduced-risk synthetic and nonsynthetic herbicides applied post-transplant directed. Treatments included caprylic acid plus capric acid, clove oil plus cinnamon oil, d-limonene, acetic acid (200 grain), citric acid, pelargonic acid, eugenol, ammonium nonanoate, and ammoniated soap of fatty acids. Stevia yield (dry aboveground biomass) in the greenhouse was reduced by all herbicide treatments. Citric acid and clove oil plus cinnamon oil were the least injurious, reducing yield by 16% to 20%, respectively. In field studies, d-limonene, pelargonic acid, ammonium nonanoate, and ammoniated soap of fatty acids controlled Palmer amaranth (>90% 1 wk after treatment (WAT). In field studies caprylic acid plus capric acid, pelargonic acid, and ammonium nonanoate caused >30% injury to stevia plants at 2 WAT, and d-limonene, citric acid, acetic acid, and ammoniated soap of fatty acids caused 18% to 25% injury 2 WAT. Clove oil plus cinnamon oil and eugenol caused <10% injury. Despite being injurious, herbicides applied in the field did not reduce yield compared to the nontreated check. Based upon yield data, these herbicides have potential for use in stevia; however, these products could delay harvest if applied to established stevia. In particular, clove oil plus cinnamon oil has potential for use for early-season weed management for organic production systems. The application of clove oil plus cinnamon oil over-the-top resulted in <10% injury 28 d after treatment (DAT) in the greenhouse and 3% injury 6 WAT postemergence-directed in the field. In addition, this treatment provided 95% control of Palmer amaranth 4 WAT.

OBJECTIVES/GOALS: Irritability, a proneness to anger and frustration, is a transdiagnostic symptom associated with poor mental health outcomes. Levels of irritability vary across development and high-risk trajectories have been observed. This study aims to use machine learning to predict irritability trajectories across the transition to adolescence. METHODS/STUDY POPULATION: Data were from the Adolescent Brain Cognitive Development (ABCD) Study, which is a 10-year longitudinal study that tracks the brain development, cognitive skills, physical health, and psychosocial functioning of a large, national sample starting from preadolescence. The baseline sample consisted of 11,861 9-10-year-old preadolescent youth. Irritability was parent-rated at baseline, 1-year, 2-year, 3-year, and 4-year follow-ups on the Child Behavior Checklist (CBCL) irritability index. Latent class growth analysis (LCGA) was used to determine developmental trajectories of irritability. Two machine learning approaches were applied to develop predictive models of youth irritability developmental trajectories. We used baseline (preadolescent) variables that spanned a wide range of domains. RESULTS/ANTICIPATED RESULTS: Preliminary results fromthe LCGA indicated best support for a four-class model that differentiated growth trajectories in irritability across the transition to adolescence: 1) persistent low irritability (n = 8691, 73.27%), 2) moderate irritability and decreasing (n = 1257, 10.60%), 3) low to moderate irritability and increasing (n = 1295, 10.92%), and 4) chronic high irritability (n = 618, 5.21%). We expect the machine learning analyses to generate predictive models with acceptable accuracy. We hypothesize that the most important predictors in the models will originate from the youth mental health domain, including baseline youth irritability, externalizing symptoms, internalizing symptoms, and oppositional behaviors, and the parent psychopathology domain, particularly parent irritability. DISCUSSION/SIGNIFICANCE: The present study elucidates unique developmental trajectories of irritability and generates predictive models to classify high-risk irritability trajectories using machine learning approaches. Clinicians can use these predictive models to identify at-risk youth and provide early intervention to preadolescents at high risk.

OBJECTIVES/GOALS: To introduce the new Team Science Community Toolkit, co-created by community and academic partners, and showcase its potential to empower Community Organizations (COs) in achieving equity in community-engaged research (CER). METHODS/STUDY POPULATION: In response to the challenges faced by COs in CER collaborations, qualitative interviews were conducted with CO staff from historically marginalized communities. These interviews informed the development of the Team Science Community Toolkit, a collaborative effort involving a Community Advisory Board (CAB) and Team Science experts from Northwestern University. The toolkit, designed using a community-based participatory research approach, incorporates the Science of Team Science and User-Centered Design principles. Integrated into the NIH-sponsored COALESCE website, it includes templates, checklists, and interactive tools, along with a real-world simulation, to support COs in all stages of the research process. RESULTS/ANTICIPATED RESULTS: Focus groups and usability testing involving external community experts validated the toolkit’s content and usability. Participants expressed enthusiasm and a sense of empowerment, indicating that the toolkit allows them to actively shape research processes and infuse their specific voices and needs into their partnerships. The toolkit is designed to support breaking down barriers like jargon and cultural adaptability to improve accessibility and open conversation. The impact of this Team Science focused toolkit is under evaluation. This presentation will showcase the toolkit, detail its collaborative development, and explore potential applications, ultimately offering a path to more equitable and valuable community-based research. DISCUSSION/SIGNIFICANCE: By providing COs with the resources and knowledge to participate as equal partners in research collaborations, it enhances self-advocacy, transparency, and equity. The toolkit has the potential to utilize Team Science to foster productive communication in community-academic research partnerships.

Let $X$ be a smooth geometrically connected projective curve over the field of fractions of a discrete valuation ring $R$, and $\mathfrak {m}$ a modulus on $X$, given by a closed subscheme of $X$ which is geometrically reduced. The generalized Jacobian $J_\mathfrak {m}$ of $X$ with respect to $\mathfrak {m}$ is then an extension of the Jacobian of $X$ by a torus. We describe its Néron model, together with the character and component groups of the special fibre, in terms of a regular model of $X$ over $R$. This generalizes Raynaud's well-known description for the usual Jacobian. We also give some computations for generalized Jacobians of modular curves $X_0(N)$ with moduli supported on the cusps.

There are two kinds of time bias: near bias and future bias. While philosophers typically hold that near bias is rationally impermissible, many hold that future bias is rationally permissible. Call this normative hybridism. According to arbitrariness objections, certain patterns of preference are rationally impermissible because they are arbitrary. While arbitrariness objections have been leveled against both near bias and future bias, the kind of arbitrariness in question has been different. In this article we investigate whether there are forms of arbitrariness that are common to both kinds of preferences and, hence, whether there are versions of the arbitrariness objection that are objections to both near bias and future bias. If there are, then this might go some way toward undermining normative hybridism and to defending thoroughgoing time-neutralism.