From June to October, 2022, we recorded the weight, the internal temperature, and the hive entrance video traffic of ten managed honey bee (Apis mellifera) colonies at a research apiary of the Carl Hayden Bee Research Center in Tucson, AZ, USA. The weight and temperature were recorded every five minutes around the clock. The 30 s videos were recorded every five minutes daily from 7:00 to 20:55. We curated the collected data into a dataset of 758,703 records (280,760–weight; 322,570–temperature; 155,373–video). A principal objective of Part I of our investigation was to use the curated dataset to investigate the discrete univariate time series forecasting of hive weight, in-hive temperature, and hive entrance traffic with shallow artificial, convolutional, and long short-term memory networks and to compare their predictive performance with traditional autoregressive integrated moving average models. We trained and tested all models with a 70/30 train/test split. We varied the intake and the predicted horizon of each model from 6 to 24 hourly means. Each artificial, convolutional, and long short-term memory network was trained for 500 epochs. We evaluated 24,840 trained models on the test data with the mean squared error. The autoregressive integrated moving average models performed on par with their machine learning counterparts, and all model types were able to predict falling, rising, and unchanging trends over all predicted horizons. We made the curated dataset public for replication.

The National Agricultural Literacy Outcomes (NALOs) are knowledge benchmarks for school-aged youth and are used to improve agricultural literacy (NAITC, 2014; NCAL, 2017). Despite educational efforts, prior research indicated that high school populations remained at low or deficient literacy levels. Additionally, no agricultural literacy assessment instruments using the NALOs as a standardization tool have been developed for the 9-12th grades. The purpose of the study was to validate a summative NALO-centered assessment that could provide baseline data on agricultural literacy following the completion of secondary education (12th grade). The study followed the framework established by Longhurst et al. (2020) for similar assessments in elementary grades. A Delphi team produced 45 items for validation that were reviewed using a convenience sample of [University] undergraduate students. Those items were evaluated using factor, item, and discriminant analysis. Results finalized two 15-item assessments and determined both had acceptable reliability, were adequate for model fit, and were valid for the NALOs and the three proficiency levels. The instruments are critical tools for providing a standardized approach to evaluation efforts. Researchers and educators should use these instruments to provide comparable agricultural literacy data across populations to better identify trends, program needs, and meaningful inferences.

Since bee traffic is a contributing factor to hive health and electromagnetic radiation has a growing presence in the urban milieu, we investigate ambient electromagnetic radiation as a predictor of bee traffic in the hive's vicinity in an urban environment. To that end, we built two multi-sensor stations and deployed them for four and a half months at a private apiary in Logan, UT, USA. to record ambient weather and electromagnetic radiation. We placed two non-invasive video loggers on two hives at the apiary to extract omnidirectional bee motion counts from videos. The time-aligned datasets were used to evaluate 200 linear and 3,703,200 non-linear (random forest and support vector machine) regressors to predict bee motion counts from time, weather, and electromagnetic radiation. In all regressors, electromagnetic radiation was as good a predictor of traffic as weather. Both weather and electromagnetic radiation were better predictors than time. On the 13,412 time-aligned weather, electromagnetic radiation, and bee traffic records, random forest regressors had higher maximum R2 scores and resulted in more energy efficient parameterized grid searches. Both types of regressors were numerically stable.

Particle swarm optimization (PSO) is an attractive, easily implemented method which is successfully used across a wide range of applications. In this paper, utilizing the core ideology of genetic algorithm and dynamic parameters, an improved particle swarm optimization algorithm is proposed. Then, based on the improved algorithm, combining the PSO algorithm with decision making, nested PSO algorithms with two useful decision making criteria (optimistic coefficient criterion and minimax regret criterion) are proposed . The improved PSO algorithm is implemented on two unimodal functions and two multimodal functions, and the results are much better than that of the traditional PSO algorithm. The nested algorithms are applied on the Michaelis–Menten model and two parameter logistic regression model as examples. For the Michaelis–Menten model, the particles converge to the best solution after 50 iterations. For the two parameter logistic regression model, the optimality of algorithms are verified by the equivalence theorem. More results for other models applying our algorithms are available upon request.

We examine subjective supervisory assessments of managerial performance in the banking industry. Results of empirical tests show that better assessments are (i) positively associated with decisions made by examiners to upgrade relatively objective bank performance ratings; (ii) negatively associated with decisions made by examiners to downgrade relatively objective bank performance ratings; and (iii) positively associated with decisions made by bank holding company managers to distribute resources among subsidiary banks. These results are consistent with the finding that soft information generated in the supervisory process is validated by subsequent decisionmaking both internally (by bankers) and externally (by examiners).

The COVID-19 pandemic has disproportionately impacted the health of older adults. In addition to a higher risk for serious illness and death, the societal value of senescent adults was challenged. There have been conflicting results reported in the research literature regarding positive and negative stereotypes of older adults, and areliable and valid assessment tool to measure content (existence of astereotype) and strength (intensity of astereotype) is unavailable. To address issues with instruments employed to measure ageist stereotypes, researchers developed the Stereotypes Content and Strength Survey. University students (n=483) were directed to "think about their perceptions of older adults" and indicate how many they believed could be described using the terms listed on a5-point Likert-type scale from none-all. Response categories for each descriptive item were dichotomized into 1 = "some, most or all" and 0 = "none or few." Based on an odds analyses of 117 items, 84 met the content criteria to be considered astereotype regarding older adults. Using the criteria for strength, items were categorized into 36 "strong," 25 "moderate," and 23 "weak" stereotypes. Assessing the content and strength of stereotypic beliefs using this procedure may contribute to major bias influencing ageist perceptions.

We examine subjective supervisory assessments of performance in the banking industry. Results of empirical tests show that better assessments are: 1) positively associated with decisions made by supervisors to upgrade objective performance ratings; 2) negatively associated with decisions made by supervisors to downgrade objective performance ratings; and 3) positively associated with decisions made by bank holding company managers to allocate capital among subsidiary banks. These findings are consistent with a production of soft information in the examination process whose usefulness is validated in decisions about banks that are made both internally (by bankers) and externally (by supervisors).

In the United States and internationally, there has been an increased emphasis on the practice turn or a focus on engaging students in more authentic representations of how science is practiced. In this article, we describe the development of a student questionnaire to investigate the extent to which students report being engaged in learning experiences similar to those explicated through the practice turn. We developed a questionnaire that consisted of 35 questions that were separated into four constructs. The questionnaire was determined to be internally consistent, with a high reliability estimate. Confirmatory factor analysis showed item clustering consistent with the research-derived constructs indicative of a practice turn focus in science classrooms. Furthermore, early evidence from this pilot study is provided to reveal the ability of the questionnaire to detect student experiences that are differentiated at the teacher-level. Based on the analyses completed, the questionnaire appears to be a needed and useful measure of student-reported learning experiences that can provide an indication of students' opportunity to learn in ways aligned to the most recent reforms in science education.

Background and Objectives: Stereotypes are beliefs about a particular group often adopted to bypass complex information processing. Like racism and other forms of discrimination, ageism affects individuals and society as a whole. The purpose of the study was to analyze the Stereotype Content and Strength Survey (SCSS) designed to update assessment tools commonly used to measure stereotypes of older adults. Research Design and Methods: An updated survey was developed including aging-related descriptive items from previously published studies. Students enrolled at two Midwestern universities (n = 491) were directed to think about their perceptions of "older adults" and select the proportion they believed could be described by the items used in the tool. Response categories for each descriptive item were dichotomized and operationalized to be a strong stereotype if the collapsed response percentage was significantly >= 80%. Results: A Principal Axis Factor analysis and Direct Oblim rotation was computed on 117 descriptive items representing positive, negative, and physical characteristics, resulting in a 3-factor model with acceptable psychometric properties. Cronbach alpha analyses revealed reliable scales for negative (alpha =.92), positive (alpha =.88), and physical (alpha =.81) stereotypes. Of 117 descriptive items, 33 emerged as strong stereotypes including 30 positive, 2 physical, and 1 negative item. Discussion and Implications: This updated assessment has the potential to contribute to an understanding of the existence of age-related stereotypes as well as the strength, or the proportion of older adults who could be described by each of the items used in the SCSS.

Modern societal functions for meeting basic needs contribute to the lack of understanding many Americans have about agriculture’s connection to human health and environmental quality. Consequently, this limited understanding has produced a need to measure agricultural literacy to develop programming or enhance existing agricultural educational efforts. Research literature has identified the need for agricultural literacy instruments to be developed that measure current understandings. The National Agricultural Literacy Outcomes (NALOs) served as the conceptual framework for the development of an agricultural literacy criterion referenced progressive measurement tool for grades 3-5. A theoretical framework using assessment models was used to develop items to measure agricultural literacy in three proficiency stages: exposure, factual literacy, and applicable proficiency. A modified Delphi method was used to create the Longhurst Murray Agricultural Literacy Instrument (LMALI) with the intent of assessing elementary student understanding of the NALOs. Items were tested with students from regional representative states using exploratory factor analysis, confirmatory factor analysis, and discriminant analysis in the investigation. The development process resulted in a validated 15-item instrument for grades 3-5. Overall, the instrument provides a way for educators and stakeholders to measure agricultural literacy based on proficiency stages within the five NALO themes.

This study is the first to examine primary care physician (PCP) density relative to the uninsured at the local level prior to and after insurance expansion under the Affordable Care Act. Primary care physician density is associated with access to care, lower inpatient and emergency care, and primary care services. However, access to primary care among the uninsured may be limited due to inadequate availability of PCPs. Core-Based Statistical Area (CBSA) data from the Area Health Resource File were retrospectively examined before and after Medicaid expansion. Multiple logistic regressions were modeled for PCP density with predictor interaction effects for percentage uninsured, Medicaid expansion status, and US Census regions. Medicaid expansion CBSAs had significantly lower proportions of uninsured and higher PCP density compared with their nonexpansion counterparts. Nationally, increasing proportions of the uninsured were significantly associated with decreasing PCP density. Most notably, there is an expected 32% lower PCP density in Western Medicaid expansion areas with many uninsured (90th percentile) compared with those with few uninsured (10th percentile). Areas expanding Medicaid with greater proportions of people becoming insured postexpansion had significantly fewer PCPs. Areas with greater proportions of the uninsured may have reduced access to primary care due to the paucity of PCPs in these areas. Efforts to improve access should consider a lack of local PCPs as a limitation for ensuring accessible and timely care. Health care and policy leaders should focus on answers to improve the local availability of primary care clinicians in underserved communities.

Plain language techniques are health literacy universal precautions intended to enhance health care system navigation and health outcomes. Physical activity (PA) is a popular topic on the Internet, yet it is unknown if information is communicated in plain language. This study examined how plain language techniques are included in PA websites, and if the use of plain language techniques varies according to search procedures (keyword, search engine) and website host source (government, commercial, educational/organizational). Three keywords (“physical activity,” “fitness,” and “exercise”) were independently entered into three search engines (Google, Bing, and Yahoo) to locate a nonprobability sample of websites (N = 61). Fourteen plain language techniques were coded within each website to examine content formatting, clarity and conciseness, and multimedia use. Approximately half (M = 6.59; SD = 1.68) of the plain language techniques were included in each website. Keyword physical activity resulted in websites with fewer clear and concise plain language techniques (p < .05), whereas fitness resulted in websites with more clear and concise techniques (p < .01). Plain language techniques did not vary by search engine or the website host source. Accessing PA information that is easy to understand and behaviorally oriented may remain a challenge for users. Transdisciplinary collaborations are needed to optimize plain language techniques while communicating online PA information.

This study aimed to provide physiologic health risk parameters by gender and age among college students enrolled in a U.S. Midwestern University to promote chronic disease prevention and ameliorate health. A total of 2615 college students between 18 and 25years old were recruited annually using a series of cross-sectional designs during the spring semester over an 8-year period. Physiologic parameters measured included body mass index (BMI), percentage body fat (%BF), blood serum cholesterol (BSC), and systolic (SBP) and diastolic (DBP) blood pressure. These measures were compared to data from NHANES to identify differences in physiologic parameters among 18–25year olds in the general versus college-enrolled population. A quantitative instrument assessed health behaviors related to physical activity, diet, and licit drug use. Results suggest that average physiologic parameters from 18 to 25year olds enrolled in college were significantly different from parameters of 18–25year olds in the general population. Generally, men reported higher percentiles for BMI, SBP, and DBP than women, but lower %BF and BSC percentiles than women at each age. SBP and DBP significantly increased with age and alcohol use. Students in the lowest (5th) and highest percentiles (95th and 75th), for most age groups, demonstrated DBP, BMI, and %BF levels potentially problematic for health and future development of chronic disease based on percentiles generated for their peer group. Newly identified physiologic parameters may be useful to practitioners serving college students 18–25years old from similar institutions in determining whether behavior change or treatment interventions are appropriate.

Purpose The purpose of this study was to explore how perceived threat of type 2 diabetes (T2D) is shaped by risk factor knowledge and promotes the engagement of protective health behaviors among rural adults. Methods Participants (N = 252) completed a cross-sectional mixed-mode survey. Chi-squared analyses were computed to examine differences in perceived threat by demographic factors and knowledge of T2D risk factors. Logistic regressions were conducted to examine the relationship between T2D perceived threat and engagement in physical activity and health screenings. Results Perceived threat and knowledge of T2D risk factors were high. Perceived susceptibility was significantly higher among women, whites, and respondents with high body mass index (BMI). Respondents reporting physical activity most/almost every day had low perceived susceptibility to T2D. Perceived severity was significantly higher among respondents with high BMI. Blood cholesterol and glucose screenings were associated with greater T2D perceived susceptibility and severity. Higher BMI was associated with receiving a blood glucose screening. Conclusion Health education specialists and researchers should further explore the implications of using audience segmented fear appeal messages to promote T2D control through protective health behaviors.

With advancing technology, "literacy" evolves to include new forms of literacy made possible by digital technologies. "New literacy" refers to using technology to research, locate, evaluate, synthesize and communication information. The purpose of the study is to develop a framework to guide science teachers' new literacy practices, and examine the impact of new literacy approach on students' science learning and new literacy skills. The authors worked with 25 middle school science teachers through a two-year professional development PD, and followed their implementation to investigate the PD impact on their classroom practices and students' learning outcomes. The authors adopted mixed-methods to examine change in teachers' new literacy practices, students' science learning outcomes, and students' confidence in new literacy skills. The study results showed increases in teachers' frequency and types of new literacy practices, positive impact on students' science learning and confidence in new literacy skills. Factors affecting teachers' new literacy practice are also reported.

Visions of science teaching and learning in the newest U.S. standards documents are dramatically different than those found in most classrooms. This research addresses these differences through closely examining one professional development (PD) project that connects teacher learning and teacher practice with student learning/achievement. This study examines the effects on eighth grade science teachers and their students in the context of a PD focused on the integration of information communication technologies and reformed science teaching practices. Findings from this investigation suggest that teachers who participated in PD for two years learned more about technology, improved their practice, and their students' achievement was significantly higher compared to teachers who participated in one year of the PD or non-participating peers. Science educators face multiple challenges as they attempt to deliver instruction in fundamentally different ways than what they experienced as learners. The delivery of this professional learning suggest that PD for science teachers should include educative learning experiences if understandings of reforms supported by research are to be realized.

OBJECTIVES:To ascertain whether analyses of social media trends for various Twitter responses following a major disaster produce implications for improving the focus on public health resources and messaging to disaster victims.METHODS:Radian6 and trend analyses were used to analyze 12-hour counts of Twitter data before, during, and after the March 2011 Japanese earthquake and tsunami. Radian6 was used to organize tweets into categories of preparedness, emergency response, and public health.RESULTS:Radian6 revealed that 49 percent of tweets were either positive or somewhat positive in sentiment about preparedness and only 7 percent were negative or somewhat negative. Trend analyses revealed a rapid onset of tweet activity associated with all keywords followed by mostly fast exponential decline. Analyses indicate that opportunities for improving public health awareness by leveraging social media communications exist for as much as 5 days after a disaster.CONCLUSIONS:Analyses suggest key times for public health social media communication to promote emergency response.

Understanding how deer move in relationship to roads is critical, because deer are in vehicle collisions, and collisions cause vehicle damage, as well as human injuries and fatalities. In temperate climates, mule deer Odocoileus hemionus have distinct movement patterns that affect their spatial distribution in relationship to roads. In this paper, we analyzed deer movements during two consecutive winter seasons with vastly different conditions to determine how deer—vehicle collision rates responded. We predicted that deer—vehicle collision rates would be higher when precipitation and snow depth were higher. We used meteorological data from local weather stations to describe temperature, precipitation and snow depth. We monitored deer movements with global positioning system telemetry to document distance of deer to roads, elevation use and road crossing rates. We also documented changes in deer abundance and traffic volumes, which were potentially confounding variables. We found that precipitation decreased 50% and snow depth decreased 48% between winters. In response, deer used habitats that were 16% higher in elevation and that were 213% farther from roads with high traffic volumes. Consequently, crossing rates also decreased as much as 96% on roads with high traffic volumes. Reduced crossing rates were likely responsible for much of the 75% decrease in deer—vehicle collisions that occurred during the second winter. Abundance and traffic volume also can be important factors affecting deer—vehicle collisions rates. However, it is unlikely they were the major drivers of variation in deer—vehicle collisions during our study, because traffic volumes did not change between years and deer abundance only decreased 7%. Our data suggest a mechanism by which variation in winter conditions can contribute to differences in deer—vehicle collision rates between years. These findings have significant management implications for deer—vehicle collision mitigation.

Balanced block designs and in particular balanced incomplete block designs (BIBDs) have been in widespread use in agricultural, ecological, pharmaceutical, and industrial research for many years. However, this “balance” characteristic is only true for BIBDs with uncorrelated observations. With correlated observations within each block, the order of the observations matters and this order impacts variance and hence any notion of “balance”. Thus, there is need of research into construction of these useful designs when any one of a number of different correlation structures might exist within each block of units.