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.

The moderating roles of friendship and contextual variables on associations between social withdrawal and peer exclusion and growth curves of depressed affect were studied with a three-wave multilevel longitudinal design. Participants were 313 boys and girls aged 10–12 from Canada (n = 139), mostly of European and North African descent, and Colombia (n = 174), mostly mestizo, afrocolombian, and European descent. Depressed affect, peer exclusion, social withdrawal and friendship were assessed with peer-reports, and collectivism and individualism with self-reports. Group-level scores included gender, place and means of social withdrawal, peer exclusion, friendship, collectivism and individualism for each child’s same-gender classroom peer-group. Results indicated that being friended weakened associations between peer exclusion and social withdrawal and depressed affect. The strength of this effect varied across peer-group contexts.

Current clinical guidelines for people at risk of heart disease in Australia recommend nutrition intervention in conjunction with pharmacotherapy(1). However, Australians living in rural and remote regions have less access to medical nutritional therapy (MNT) provided by Accredited Practising Dietitians (APDs) than their urban counterparts(2). The aim of the HealthyRHearts study was to trial the delivery of MNT by APDs using telehealth to eligible patients of General Practitioners (GPs) located in small to large rural towns in the Hunter New England region(3) of New South Wales, Australia. The study design was a 12-month pragmatic randomised controlled trial. The key outcome was reduced total cholesterol. The study was place-based, meaning many of the research team and APDs were based rurally, to ensure the context of the GPs and patients was already known. Eligible participants were those assessed as moderate-to-high risk of CVD by their GP. People in the intervention group received five MNT consults (totalling two hours) delivered via telehealth by APDs, and also answered a personalised nutrition questionnaire to guide their priorities and to support personalised dietary behaviour change during the counselling. Both intervention and control groups received usual care from their GP and were provided access to the Australian Eating Survey (Heart version), a 242-item online food frequency questionnaire with technology-supported personalised nutrition reports that evaluated intake relative to heart healthy eating principles. Of the 192 people who consented to participate, 132 were eligible due to their moderate-to-high risk. Pre-post participant medication use with a registered indication(4) for hypercholesterolemia, hypertension and glycemic control were documented according to class and strength (defined daily dose: DDD)(5). Nine GP practices (with 91 participants recruited) were randomised to the intervention group and seven practices (41 participants) were randomised to control. Intervention participants attended 4.3 ± 1.4 out of 5 dietetic consultations offered. Of the132 people with baseline clinical chemistry, 103 also provided a 12-month sample. Mean total cholesterol at baseline was 4.97 ± 1.13 mmol/L for both groups, with 12-m reduction of 0.26 ± 0.77 for intervention and 0.28 ± 0.79 for control (p = 0.90, unadjusted value). Median (IQR) number of medications for the intervention group was 2 (1–3) at both baseline and 12 months (p = 0.78) with 2 (1–3) and 3 (2–3) for the control group respectively. Combined DDD of all medications was 2.1 (0.5–3.8) and 2.5 (0.75–4.4) at baseline and 12 months (p = 0.77) for the intervention group and 2.7 (1.5–4.0) and 3.0 (2.0–4.5) for the control group (p = 0.30). Results suggest that medications were a significant contributor to the management of total cholesterol. Further analysis is required to evaluate changes in total cholesterol attributable to medication prescription relative to the MNT counselling received by the intervention group.

Traditional foods are increasingly being incorporated into modern diets. This is largely driven by consumers seeking alternative food sources that have superior nutritional and functional properties. Within Australia, Aboriginal and Torres Strait Islander peoples are looking to develop their traditional foods for commercial markets. However, supporting evidence to suggest these foods are safe for consumption within the wider general population is limited. At the 2022 NSA conference a keynote presentation titled ‘Decolonising food regulatory frameworks to facilitate First Peoples food sovereignty’ was presented. This presentation was followed by a manuscript titled ‘Decolonising food regulatory frameworks: Importance of recognising traditional culture when assessing dietary safety of traditional foods’, which was published in the conference proceedings journal(1). These pieces examined the current regulatory frameworks that are used to assess traditional foods and proposed a way forward that would allow Traditional Custodians to successfully develop their foods for modern markets. Building upon the previously highlighted works, this presentation will showcase best practice Indigenous engagement and collaboration principles in the development of traditionally used food products. To achieve this, we collaborated with a collective of Gamilaraay peoples who are looking to reignite their traditional grain practices and develop grain-based food products. To meet the current food safety regulatory requirements, we needed to understand how this grain would fit into modern diets, which included understanding the history of use, elucidating the nutritional and functional properties that can be attributed to the grain, and developing a safety dossier(2) so that the Traditional Custodians can confidently take their product to market. To aid the Traditional Custodians in performing their due diligence, we have systemically analysed the dietary safety of the selected native grain and compared it side-by-side with commonly consumed wheat in a range of in vitro bioassays and chemical analyses. From a food safety perspective, we show that the native grain is equivalent to commonly consumed wheat. The native grain has been shown to be no more toxic than wheat within our biological screening systems. Chemical analysis showed that the level of contaminants are below tolerable limits, and we were not able to identify any chemical classes of concern. Our initial findings support the history of safe use and suggest that the tested native grain species would be no less safe than commonly consumed wheat. This risk assessment and previously published nutritional study(3) provides an overall indication that the grain is nutritionally superior and viable for commercial development. The learnings from this project can direct the future risk assessment of traditional foods and therefore facilitate the safe market access of a broader range of traditionally used foods. Importantly, the methods presented are culturally safe and financially viable for the small businesses hoping to enter the market.

Objectives/Goals: Early childhood obesity is a major concern for Latin American children in the U.S., with gut barrier dysfunction as a key risk factor. Diet plays a role in gut development, but few studies have focused on Latin American infants. Our objective is to identify culturally relevant introductory foods that promote in vitro gut barrier development and function. Methods/Study Population: Pooled human milk (2.5 mL) from 6-month postpartum Hispanic mothers was combined with fruit and vegetable baby food products (2.5 g) and subjected to a 3-phase in vitro digestion system that simulates oral, gastric, and intestinal digestion. Digesta products were then anaerobically fermented for 24-hours using human stool inoculum, centrifuged, and filter sterilized. Intestinal epithelial cells (Caco-2, ATCC) were grown to confluence on 0.4 μm polystyrene transwell inserts using a DMEM + 10% FBS medium and allowed to differentiate for 21-days. Highly differentiated monolayers were treated with a 1:4 dilution of fermenta with medium in triplicate. The cell experiment was conducted twice. Cell layer integrity was measured using transepithelial electrical resistance (TEER) 24- and 48-hours after treatment. Results/Anticipated Results: Dietary intake data from the What We Eat in America database indicated that the top 3 fruit and vegetable exposures for infants with Mexican or Hispanic ethnicity were banana, apple, and carrot. Commercial baby food purees of these fruits and vegetables, in addition to baby foods with blueberry and spinach (Natural for Baby, Gerber Products Company) were acquired for digestion and fermentation experiments. Caco-2 cell experiments with these foods are ongoing. We expect Caco-2 monolayer incubated with fermenta from human milk and fruit or vegetables will have greater TEER values due to increased integrity of the cell layer as compared to those with breast milk alone. We also expect that exposure to fruit and vegetable fermenta will increase gene expression of tight junctions compared to exposure to media and human milk. Discussion/Significance of Impact: Using an in vitro digestion and fermentation system coupled with cell culture studies, we are identifying cellular mechanisms that link individual fruits and vegetables to gut barrier function. This will support translational work focused on mitigating obesity development in vulnerable populations.

There is a growing focus on understanding the complexity of dietary patterns and how they relate to health and other factors. Approaches that have not traditionally been applied to characterise dietary patterns, such as latent class analysis and machine learning algorithms, may offer opportunities to characterise dietary patterns in greater depth than previously considered. However, there has not been a formal examination of how this wide range of approaches has been applied to characterise dietary patterns. This scoping review synthesised literature from 2005 to 2022 applying methods not traditionally used to characterise dietary patterns, referred to as novel methods. MEDLINE, CINAHL and Scopus were searched using keywords including latent class analysis, machine learning and least absolute shrinkage and selection operator. Of 5274 records identified, 24 met the inclusion criteria. Twelve of twenty-four articles were published since 2020. Studies were conducted across seventeen countries. Nine studies used approaches with applications in machine learning, such as classification models, neural networks and probabilistic graphical models, to identify dietary patterns. The remaining studies applied methods such as latent class analysis, mutual information and treelet transform. Fourteen studies assessed associations between dietary patterns characterised using novel methods and health outcomes, including cancer, cardiovascular disease and asthma. There was wide variation in the methods applied to characterise dietary patterns and in how these methods were described. The extension of reporting guidelines and quality appraisal tools relevant to nutrition research to consider specific features of novel methods may facilitate consistent reporting and enable synthesis to inform policies and programs.

In contrast to Thurstone's Law of Comparative Judgment, a model in which a comparison pair and its complement are assumed to give rise to two different distributions of differences is considered. The consequences of this revised model on scaling problems is developed.

Formulas are derived by which, given the factor loadings and the internal reliability of a test of unit length, the following estimates can be made: (1) the common-factor loadings for a similar (homogeneous) test of length n; (2) the number of times (n) that a test needs to be lengthened homogeneously to achieve a factor loading of a desired magnitude; and (3) the correlation between two tests, either or both of which have been altered in length, as a function of (a) the new factor loadings in the altered tests or (b) the original loadings in the unit-length tests. The appropriate use of the derived formulas depends upon the fulfillment of four assumptions enumerated.

Two current methods of deriving common-factor scores from tests are briefly examined and rejected. One of these estimates a score from a multiple-regression equation with as many terms as there are tests in the battery. The other limits the equation to a few tests heavily saturated with the desired factor, with or without tests used to suppress the undesired factors. In the proposed methods, the single best test for each common factor is the starting point. Such a test ordinarily has a very few undesired factors to be suppressed, frequently only one. The suppression test should be univocal, or nearly so. Fortunately, there are relatively univocal tests for factors that commonly require suppression. Equations are offered by which the desired-factor test and a single suppression test can be weighted in order to achieve one or more objectives. Among the objectives are (1) maximizing the desired factor variance, (2) minimizing the undesired factor variance, (3) a compromise, in which the undesired variance is materially reduced without loss in desired variance, and (4) a change to any selected ratio of desired to undesired variance. A more generalized solution is also suggested. The methods can be extended in part to the suppression of more than one factor. Equations are derived for the suppression of two factors.

Even amidst a decline in religious affiliation, nearly half of the U.S. population still attends religious services at least once a month, and congregations remain the single largest non-profit organizational type across the nation. Therefore, congregational influence on political attitudes and behavior is a crucial line of inquiry. We analyze interviews of 94 congregational leaders to better understand why they address or avoid political issues when preaching. Our research reveals that clergy use theological and pragmatic reasoning to determine whether they explicitly include political discourse in their sermons. Our findings are noteworthy in that clergy from a wide range of religious traditions use similar reasoning, and the same rationale can lead different clergy to adopt contrasting approaches to political content in sermons. Thus, this paper provides nuanced insight into the relationship between religion and politics and may help foster greater mutual understanding in a deeply divided political and social climate.

Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or transnational scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by leveraging and amplifying AI for national-scale collective intelligence. The development and deployment of this kind of AI faces distinctive challenges, both technical and socio-technical. Here, a research strategy for mobilising inter-disciplinary research to address these challenges is detailed and some of the key issues that must be faced are outlined.

Scholarly and practitioner interest in authentic leadership has grown at an accelerating rate over the last decade, resulting in a proliferation of publications across diverse social science disciplines. Accompanying this interest has been criticism of authentic leadership theory and the methods used to explore it. We conducted a systematic review of 303 scholarly articles published from 2010 to 2023 to critically assess the conceptual and empirical strengths and limitations of this literature and map the nomological network of the authentic leadership construct. Results indicate that much of the extant research does not follow best practices in terms of research design and analysis. Based on the findings obtained, an agenda for advancing authentic leadership theory and research that embraces a signaling theory perspective is proposed.