Foliar-applied postemergence applications of glufosinate are often applied to glufosinate-resistant crops to provide nonselective weed control without significant crop injury. Rainfall, air temperature, solar radiation, and relative humidity near the time of application have been reported to affect glufosinate efficacy. However, previous research may have not captured the full range of weather variability to which glufosinate may be exposed to prior to or following application. Additionally, climate models suggest more extreme weather will become the norm, further expanding this weather range glufosinate can be exposed to. The objective of this research was to quantify the probability of successful weed control (efficacy ≥85%) with glufosinate applied to some key weed species across a broad range of weather conditions. A database of >10,000 North American herbicide evaluation trials was used in this study. The database was filtered to include treatments with a single POST application of glufosinate applied to waterhemp (Amaranthus tuburculatus (Moq.) J. D. Sauer), morningglory species (Ipomoea spp.), and/or giant foxtail (Setaria faberi Herm.) <15cm in height. These species were chosen because they are well represented in the database and listed as common and troublesome weed species in both corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] (Van Wychen 2020, 2022). Individual random forest models were created. Low rainfall (≤20 mm) over the five days prior to glufosinate application was detrimental to the probability of successful control of A. tuburculatus and S. faberi. Lower relative humidity (≤70%) and solar radiation (≤23 MJ m-1 day-1) the day of application reduced the probability of successful weed control in most cases. Additionally, the probability of successful control decreased for all species when average air temperature over the first five days after application was ≤25C. As climate continues to change and become more variable, the risk of unacceptable control of several common species with glufosinate is likely to increase.

A reflective analysis is presented on the potential added value that actuarial science can contribute to the field of health technology assessment. This topic is discussed based on the experience of several experts in health actuarial science and health economics. Different points are addressed, such as the role of actuarial science in health, actuarial judgment, data inputs and their quality, modeling methodologies and the use of decision-analytic models in the age of artificial intelligence, and the development of innovative pricing and payment models.

An attempt is made to elaborate upon Lev's results concerning the reliability of the point biserial coefficient of correlation in a manner that will be helpful to the psychological statistician. Procedures required in the use of the non-central t tables prepared by Johnson and Welch are described as they relate to the determination of the fiducial limits for a point biserial coefficient. A normal approximation technique for the estimation of fiducial limits is also suggested. Numerical evidence is presented which shows that relative to a given level of significance the width of the fiducial interval estimated from a point biserial coefficient of any size is smaller than that of the fiducial interval corresponding to an ordinary Pearsonian coefficient of the same magnitude.

Abacs approximating the product-moment correlation for both explicit and implicit selection are presented. These abacs give accuracy to within .01 of the corresponding analytic estimate.

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.

Foliar applied postemergence herbicides are a critical component of corn and soybean weed management programs in North America. Rainfall and air temperature around the time of application may affect the efficacy of herbicides applied postemergence in corn or soybean production fields. However, previous research utilized a limited number of site-years and may not capture the range of rainfall and air temperatures that these herbicides are exposed to throughout North America. The objective of this research was to model the probability of achieving successful weed control (≥85%) with commonly applied postemergence herbicides across a broad range of environments. A large database of over 10,000 individual herbicide evaluation field trials conducted throughout North America was used in this study. The database was filtered to include only trials with a single postemergence application of fomesafen, glyphosate, mesotrione, or fomesafen + glyphosate. Waterhemp (Amaranthus tuburculatus (Moq.) J. D. Sauer), morningglory species (Ipomoea spp.), and giant foxtail (Setaria faberi Herrm.) were the weeds of focus. Separate random forest models were created for each weed species by herbicide combination. The probability of successful weed control deteriorated when the average air temperature within the first ten d after application was <19 or >25 C for most of the herbicide by weed species models. Additionally, dryer conditions prior to postemergence herbicide application reduced the probability of successful control for several of the herbicide by weed species models. As air temperatures increase and rainfall becomes more variable, weed control with many of the commonly used postemergence herbicides is likely to become less reliable.

New machine-vision technologies like the John Deere See & Spray™ could provide the opportunity to reduce herbicide use by detecting weeds and target-spraying herbicides simultaneously. Experiments were conducted for 2 yr in Keiser, AR, and Greenville, MS, to compare residual herbicide timings and targeted spray applications versus traditional broadcast herbicide programs in glyphosate/glufosinate/dicamba-resistant soybean. Treatments utilized consistent herbicides and rates with a preemergence (PRE) application followed by an early postemergence (EPOST) dicamba application followed by a mid-postemergence (MPOST) glufosinate application. All treatments included a residual at PRE and excluded or included a residual EPOST and MPOST. Additionally, the herbicide application method was considered, with traditional broadcast applications, broadcasted residual + targeted applications of postemergence herbicides (dual tank), or targeted applications of all herbicides (single tank). Targeted applications provided comparable control to broadcast applications with a ≤1% decrease in efficacy and overall control ≥93% for Palmer amaranth, broadleaf signalgrass, morningglory species, and purslane species. Additionally, targeted sprays slightly reduced soybean injury by at most 5 percentage points across all evaluations, and these effects did not translate to a yield increase at harvest. The relationship between weed area and targeted sprayed area also indicates that nozzle angle can influence potential herbicide savings, with narrower nozzle angles spraying less area. On average, targeted sprays saved a range of 28.4% to 62.4% on postemergence herbicides. On the basis of these results, with specific machine settings, targeted application programs could reduce the amount of herbicide applied while providing weed control comparable to that of traditional broadcast applications.

Palmer amaranth with resistance to dicamba, glufosinate, and protoporphyrinogen oxidase inhibitors has been documented in several southern states. With extensive use of these and other herbicides in South Carolina, a survey was initiated in fall 2020 and repeated in fall 2021 and 2022 to determine the relative response of Palmer amaranth accessions to selected preemergence and postemergence herbicides. A greenhouse screening experiment was conducted in which accessions were treated with three preemergence (atrazine, S-metolachlor, and isoxaflutole) and six postemergence (glyphosate, thifensulfuron-methyl, fomesafen, glufosinate, dicamba, and 2,4-D) herbicides at the 1× and 2× use rates. Herbicides were applied shortly after planting (preemergence) or at the 2- to 4-leaf growth stage (postemergence). Percent survival was evaluated 5 to 14 d after application depending on herbicide activity. Sensitivity to atrazine preemergence was lower for 49 and 33 accessions out of 115 to atrazine applied preemergence at the 1× and 2× rate, respectively. Most of the accessions (90%) were controlled by isoxaflutole applied preemergence at the 1× rate. Response to S-metolachlor applied preemergence indicated that 34% of the Palmer amaranth accessions survived the 1× rate (>60% survival). Eleven accessions exhibited reduced sensitivity to fomesafen applied postemergence; however, these percentages were not different from the 0% survivor group. Glyphosate applied postemergence at the 1× rate did not control most accessions (79%). Palmer amaranth response to thifensulfuron-methyl applied postemergence varied across the accessions, with only 36% and 28% controlled at the 1× rate and 2× rate, respectively. All accessions were controlled by 2,4-D, dicamba, or glufosinate when they were applied postemergence. Palmer amaranth accessions from this survey exhibited reduced susceptibility to several herbicides commonly used in agronomic crops in South Carolina. Therefore, growers should use multiple management tactics to minimize the evolution of herbicide resistance in Palmer amaranth in South Carolina.

Creating a sustainable residency research program is necessary to develop a sustainable research pipeline, as highlighted by the recent Society for Academic Emergency Medicine 2024 Consensus Conference. We sought to describe the implementation of a novel, immersive research program for first-year emergency medicine residents. We describe the curriculum development, rationale, implementation process, and lessons learned from the implementation of a year-long research curriculum for first-year residents. We further evaluated resident perception of confidence in research methodology, interest in research, and the importance of their research experience through a 32-item survey. In two cohorts, 25 first-year residents completed the program. All residents met their scholarly project requirements by the end of their first year. Two conference abstracts and one peer-reviewed publication were accepted for publication, and one is currently under review. Survey responses indicated that there was an increase in residents’ perceived confidence in research methodology, but this was limited by the small sample size. In summary, this novel resident research curriculum demonstrated a standardized, reproducible, and sustainable approach to provide residents with an immersive research program.

We investigated whether an observed reduction in overall childhood cancer risk (<15 years of age) in twins has been sustained, and how this extends into young adulthood. We searched for English language publications reporting childhood cancer risk in twins, obtained unpublished data directly from some authors, and updated a meta-analysis. We used the Swedish Multigeneration Register to investigate the age to which the reduced overall risk of childhood cancer (observed previously using that Swedish dataset and in this and earlier meta-analyses) persisted into the teenage/young adult years, and which specific tumors accounted for the overall risk reduction beyond childhood. Our meta-analysis of studies of aggregate childhood cancer risk in twins confirmed their approximate 15% reduction in cancer mortality and incidence. Further analysis of Swedish Multigeneration Register data for 1958 to 2002 suggested these reduced risks of cancer (particularly leukaemias and renal tumors) extended from childhood to young adult ages. Reduced risks of these and some other specific tumor types occurring across childhood/teenage/young adult years appeared to account for most of the overall risk reduction. Our results suggest a persistent reduction of overall childhood cancer risk in twins and that this extends into young adulthood. Risk reductions for several specific tumors might account for this and, although there are several potential explanations, intrauterine growth patterns of twins might be a major contributor.

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.