OBJECTIVES/GOALS: Research is an important aspect of many students’ training. However, most trainees do not complete a scholarly project, and formal research training is rarely included in a degree program’s curriculum. Thus, we developed an online, asynchronous series of modules to introduce trainees to multiple topics that are relevant to the conduct of research. METHODS/STUDY POPULATION: Research 101 was utilized by first year medical students and undergraduate students conducting mentored research projects at the University of Cincinnati College of Medicine. Students’ knowledge, confidence, and satisfaction were assessed using pre- and post-module surveys with 5-point Likert scaled questions, open-ended text responses, and a final quiz. RESULTS/ANTICIPATED RESULTS: Pre-module survey results showed that learners were most confident with the Conducting a literature search and Race and racism in medicine modules and least confident with the Submitting an Institutional Review Board (IRB) protocol at UC module. Post-module survey responses were significantly increased compared to pre-module results for all modules and questions (p < 0.0001). The response to The content of this module met my needs was endorsed across all modules (84.9% yes responses). A final quiz of 25 multiple choice questions covering content from all required modules was completed by 92 students who had a median score of 21 (range: 15 to 25). DISCUSSION/SIGNIFICANCE: These data demonstrate significant learning resulting from completion of Research 101, as post-module survey scores were significantly higher than pre-module survey scores for all modules and questions. Final quiz scores were positive but also highlighted opportunity for additional student learning and will guide evolution of future modules.

Settlement scaling theory predicts that higher site densities lead to increased social interactions that, in turn, boost productivity. The scaling relationship between population and land area holds for several ancient societies, but as demonstrated by the sample of 48 sites in this study, it does not hold for the Northern Maya Lowlands. Removing smaller sites from the sample brings the results closer to scaling expectations. We argue that applications of scaling theory benefit by considering social interaction as a product not only of proximity but also of daily life and spatial layouts.

Tree-ring series offer considerable potential for the development of environment-sensitive proxy records. However, with traditional increment cores, only small amounts of wood are often available from annual tree-ring sequences. For this reason, it is important to understand the reliability (and reproducibility) of radiocarbon measurements obtained from small-sized samples. Here we report the F14C results from the Chronos 14Carbon-Cycle Facility of modern tropical Australian tree samples over a range of four graphite target sizes from the same rings. Our study shows that similar precision can be obtained from full-sized, half-sized, as well as small-sized graphite targets using standard pretreatment and analysis procedures. However, with a decline in sample size, there was an increase seen in the associated variance of the ages and the smallest target weights started showing a systematic bias. Wiggle-matching accuracy tests, comparing the Southern Hemisphere post-bomb atmospheric calibration curve to the different sample weight sequences, were all significant except for the 200 μgC graphite targets. Our results indicate that samples smaller than 350 μgC have limited accuracy and precision. Overall, reliable measurements of F14C sequences from tree-ring records across a range of sample sizes, with best results found using graphitized samples >350 μgC.

Radio telescopes are among the applications with the highest demands on a local oscillator (LO), which is used to receive and process the signals coming from the sky. Therefore the modules providing the required LO signal have traditionally been big and complicated. To overcome this disadvantage, we implement our own integrated frequency synthesizer inside a small LO module in this article. With this synthesizer we are able to achieve a jitter of only 50 fs integrated from 10 Hz to 2.5 GHz offset at a carrier frequency of 75 GHz. This is in part achieved by a very low in-band phase noise of −111.8 dBc at 10 kHz offset. The stabilizable frequency range is 62–88 GHz. Thus achieving promising results to fulfill this very demanding task with integrated frequency synthesizers in the future.

Recent research has shown that risk and reward are positively correlated in many environments, and that people have internalized this association as a “risk-reward heuristic”: when making choices based on incomplete information, people infer probabilities from payoffs and vice-versa, and these inferences shape their decisions. We extend this work by examining people’s expectations about another fundamental trade-off — that between monetary reward and delay. In 2 experiments (total N = 670), we adapted a paradigm previously used to demonstrate the risk-reward heuristic. We presented participants with intertemporal choice tasks in which either the delayed reward or the length of the delay was obscured. Participants inferred larger rewards for longer stated delays, and longer delays for larger stated rewards; these inferences also predicted people’s willingness to take the delayed option. In exploratory analyses, we found that older participants inferred longer delays and smaller rewards than did younger ones. All of these results replicated in 2 large-scale pre-registered studies with participants from a different population (total N = 2138). Our results suggest that people expect intertemporal choice tasks to offer a trade-off between delay and reward, and differ in their expectations about this trade-off. This “delay-reward heuristic” offers a new perspective on existing models of intertemporal choice and provides new insights into unexplained and systematic individual differences in the willingness to delay gratification.

With the proliferation of gridded data products, modeling the relationship between a scalar response and a functional covariate over the points on a regular lattice is becoming increasingly important. In this work, our overall aim is to better understand the relationship between high quantiles of surface-level ozone and the vertical temperature profile (VTP), a functional covariate, over the US Southwest in the summer. We develop our penalized functional quantile regression based approach within the framework provided by functional data analysis. As we assume that coefficient functions at points on the lattice exhibit spatial similarity, we obtain improved estimates by penalizing dissimilarity between nearby coefficient function estimates. In order to better account for the high degree of diversity of this region, we more strongly weight differences between coefficient function estimates at cells that exhibit a higher degree of geographical and climatological similarity. Our analysis suggests that the VTP is associated with acute surface-level ozone events during the summertime over this region, and the nature of this relationship differs spatially.

The purpose of this investigation was to expand upon the limited existing research examining the test–retest reliability, cross-sectional validity and longitudinal validity of a sample of bioelectrical impedance analysis (BIA) devices as compared with a laboratory four-compartment (4C) model. Seventy-three healthy participants aged 19–50 years were assessed by each of fifteen BIA devices, with resulting body fat percentage estimates compared with a 4C model utilising air displacement plethysmography, dual-energy X-ray absorptiometry and bioimpedance spectroscopy. A subset of thirty-seven participants returned for a second visit 12–16 weeks later and were included in an analysis of longitudinal validity. The sample of devices included fourteen consumer-grade and one research-grade model in a variety of configurations: hand-to-hand, foot-to-foot and bilateral hand-to-foot (octapolar). BIA devices demonstrated high reliability, with precision error ranging from 0·0 to 0·49 %. Cross-sectional validity varied, with constant error relative to the 4C model ranging from −3·5 (sd 4·1) % to 11·7 (sd 4·7) %, standard error of the estimate values of 3·1–7·5 % and Lin’s concordance correlation coefficients (CCC) of 0·48–0·94. For longitudinal validity, constant error ranged from −0·4 (sd 2·1) % to 1·3 (sd 2·7) %, with standard error of the estimate values of 1·7–2·6 % and Lin’s CCC of 0·37–0·78. While performance varied widely across the sample investigated, select models of BIA devices (particularly octapolar and select foot-to-foot devices) may hold potential utility for the tracking of body composition over time, particularly in contexts in which the purchase or use of a research-grade device is infeasible.

The winter stratospheric polar vortex (SPV) exhibits considerable variability in magnitude and structure, which can result in extreme SPV events. These extremes can subsequently influence weather in the troposphere from weeks to months and thus are important sources of surface predictability. However, the predictability of the SPV extreme events is limited to 1–2 weeks in state-of-the-art prediction systems. Longer predictability timescales of SPV would strongly benefit long-range surface prediction. One potential option for extending predictability timescales is the use of machine learning (ML). However, it is often unclear which predictors and patterns are important for ML models to make a successful prediction. Here we use explainable multiple linear regressions (MLRs) and an explainable artificial neural network (ANN) framework to model SPV variations and identify one type of extreme SPV events called sudden stratospheric warmings. We employ a NN attribution method to propagate the ANN’s decision-making process backward and uncover feature importance in the predictors. The feature importance of the input is consistent with the known precursors for extreme SPV events. This consistency provides confidence that ANNs can extract reliable and physically meaningful indicators for the prediction of the SPV. In addition, our study shows a simple MLR model can predict the SPV daily variations using sequential feature selection, which provides hints for the connections between the input features and the SPV variations. Our results indicate the potential of explainable ML techniques in predicting stratospheric variability and extreme events, and in searching for potential precursors for these events on extended-range timescales.

This report provides the first confirmed identifications of wahoo (Acanthocybium solandri) and striped marlin (Kajikia audax) in the Red Sea, expanding the known ranges of these species into the basin. Potential mechanisms responsible for the lack of regional documentation of the two species are further discussed. These findings illustrate the need for systematic biodiversity surveys of pelagic fish assemblages in the Red Sea.

Despite advances in cancer genomics and the increased use of genomic medicine, metastatic cancer is still mostly an incurable and fatal disease. With diminishing returns from traditional drug discovery strategies, and high clinical failure rates, more emphasis is being placed on alternative drug discovery platforms, such as ex vivo approaches. Ex vivo approaches aim to embed biological relevance and inter-patient variability at an earlier stage of drug discovery, and to offer more precise treatment stratification for patients. However, these techniques also have a high potential to offer personalised therapies to patients, complementing and enhancing genomic medicine. Although an array of approaches are available to researchers, only a minority of techniques have made it through to direct patient treatment within robust clinical trials. Within this review, we discuss the current challenges to ex vivo approaches within clinical practice and summarise the contemporary literature which has directed patient treatment. Finally, we map out how ex vivo approaches could transition from a small-scale, predominantly research based technology to a robust and validated predictive tool. In future, these pre-clinical approaches may be integrated into clinical cancer pathways to assist in the personalisation of therapy choices and to hopefully improve patient experiences and outcomes.

Non-archosaur archosauromorphs are a paraphyletic group of diapsid reptiles that were important members of global Middle and Late Triassic continental ecosystems. Included in this group are the azendohsaurids, a clade of allokotosaurians (kuehneosaurids and Azendohsauridae + Trilophosauridae) that retain the plesiomorphic archosauromorph postcranial body plan but evolved disparate cranial features that converge on later dinosaurian anatomy, including sauropodomorph-like marginal dentition and ceratopsian-like postorbital horns. Here we describe a new malerisaurine azendohsaurid from two monodominant bonebeds in the Blue Mesa Member, Chinle Formation (Late Triassic, ca. 218–220 Ma); the first occurs at Petrified Forest National Park and preserves a minimum of eight individuals of varying sizes, and the second occurs near St. Johns, Arizona. Puercosuchus traverorum n. gen. n. sp. is a carnivorous malerisaurine that is closely related to Malerisaurus robinsonae from the Maleri Formation of India and to Malerisaurus langstoni from the Dockum Group of western Texas. Dentigerous elements from Puercosuchus traverorum n. gen. n. sp. confirm that some Late Triassic tooth morphotypes thought to represent early dinosaurs cannot be differentiated from, and likely pertain to, Puercosuchus-like malerisaurine taxa. These bonebeds from northern Arizona support the hypothesis that non-archosauriform archosauromorphs were locally diverse near the middle Norian and experienced an extinction event prior to the end-Triassic mass extinction coincidental with the Adamanian-Revueltian boundary recognized at Petrified Forest National Park. The relatively late age of this early-diverging taxon (Norian) suggests that the diversity of azendohsaurids is underrepresented in Middle and Late Triassic fossil records around the world.

UUID: http://zoobank.org/e6eeefd2-a0ae-47fc-8604-9f45af8c1147.

Placement of fertilizer in the seed furrow to increase nutrient availability is a common practice in row-crop production. While in-furrow application of fertilizer is widely utilized in the production of winter wheat (Triticum aestivum L.), there is a lack of work evaluating new formulations and nutrient combinations that are available. The objective of this study was to quantify the effects of in-furrow fertilizer products and combinations of products on winter wheat grain yield, nitrogen and mineral concentrations. Trials were conducted across five site-years in central Oklahoma using 11 fertilizer formulations placed in-furrow at the time of planting. In locations that soil test phosphorus (STP) levels or potassium were above sufficiency, the use of in-furrow fertilizers did not improve yield over the control. Inconsistency of response was noted at locations where STP levels were below the critical threshold. While one location showed no response to the addition of P regardless of source, two other locations had significant yield responses from three or more P-containing fertilizers. The addition of both sulphur and zinc resulted in increased yield over the base product at one low STP location. Nutrient concentrations were also influenced in nutrient-limited soils; however, no trends in response were present. Based upon the results of this study, the application of in-furrow fertilizer has the potential to increase winter wheat grain yield and nutrient concentration, when soil nutrients are limiting. As expected the addition of fertilizer when soil test levels are at or above a sufficiency did not increase grain yield.

This paper presents a pedagogical exercise to explore the economics of price-based fisheries bycatch. In the exercise students experience the economic incentives that lead to bycatch due to highgrading; the discarding of low-value fish. We first discuss existing fisheries economics pedagogical activities and how our exercise is distinct. We then identify over forty economics, environmental studies, geography, management, and philosophy courses where the exercise could be played. Next, we describe the game and share results and student feedback. Finally, we provide discussion prompts and extensions to illustrate how incentives and policies can change fishing behavior to lead to sustainable fisheries.