Fault Lines and Tiktok: Shifting Perspectives, One Video at a Time

Easy accessibility to social media content equates to increased access to emotional-charged materials. Research investigating the consequences of such emotional exposures on day-to-day lives is growing, with previous works showing high correlations between social media use and emotional modulations of the user. (Christensen, 2018; Mugg, 2005). Tiktok is a popular media platform and is a common tactic to present users with highly emotional content to maintain engagement. (Kin, 2017). A question arises as to the emotional induction rates and effects of such streaming content, as previous work demonstrates that emotion induction is highly associated with physiological arousal (Siedlecka, 2018) and affects cognitive performance (Forgas, 1998). The current study aims to address the current void in literature on Tiktok, investigating consequences of positive or negative viewing experiences on the platform, and how it may influence social perceptions. 34 participants were randomly assigned to the positive or negative induction cohort, and watched a series of videos on the platform. After the induction session, participants read 15 vague scenario passages and were asked to apply fault of no-fault judgement to the protagonists. A higher score indicated a higher rate of fault attribution. Physiological arousal measures of heart rate and skin conductance were collected throughout the video viewing and fault attribution sessions. It is hypothesized that positive Tiktok clip viewing will show fewer fault attribution (lower score), compared to negative viewing, with decreased heart rate and skin conductance levels at judgement moments. Data is currently being analyze. Understanding how external stimuli, like emotionally-charged Tiktok clips, can influence interactions such as fault attribution, is important to understand our continuously changing media landscape and potential consequences in social settings

Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States

Spatially explicit livestock disease models require demographic data for individual farms or premises. In the U.S., demographic data are only available aggregated at county or coarser scales, so disease models must rely on assumptions about how individual premises are distributed within counties. Here, we addressed the importance of realistic assumptions for this purpose. We compared modeling of foot and mouth disease (FMD) outbreaks using simple randomization of locations to premises configurations predicted by the Farm Location and Agricultural Production Simulator (FLAPS), which infers location based on features such as topography, land-cover, climate, and roads. We focused on three premises-level Susceptible-Exposed-Infectious-Removed models available from the literature, all using the same kernel approach but with different parameterizations and functional forms. By computing the basic reproductive number of the infection (R0) for both FLAPS and randomized configurations, we investigated how spatial locations and clustering of premises affects outbreak predictions. Further, we performed stochastic simulations to evaluate if identified differences were consistent for later stages of an outbreak. Using Ripley's K to quantify clustering, we found that FLAPS configurations were substantially more clustered at the scales relevant for the implemented models, leading to a higher frequency of nearby premises compared to randomized configurations. As a result, R0 was typically higher in FLAPS configurations, and the simulation study corroborated the pattern for later stages of outbreaks. Further, both R0 and simulations exhibited substantial spatial heterogeneity in terms of differences between configurations. Thus, using realistic assumptions when de-aggregating locations based on available data can have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD may invade the population. We conclude that methods such as FLAPS should be preferred over randomization approaches

Effects of regional differences and demography in modelling foot-and-mouth disease in cattle at the national scale

Foot-and-mouth disease (FMD) is a fast-spreading viral infection that can produce large and costly outbreaks in livestock populations. Transmission occurs at multiple spatial scales, as can the actions used to control outbreaks. The US cattle industry is spatially expansive, with heterogeneous distributions of animals and infrastructure. We have developed a model that incorporates the effects of scale for both disease transmission and control actions, applied here in simulating FMD outbreaks in US cattle. We simulated infection initiating in each of the 3049 counties in the contiguous US, 100 times per county. When initial infection was located in specific regions, large outbreaks were more likely to occur, driven by infrastructure and other demographic attributes such as premises clustering and number of cattle on premises. Sensitivity analyses suggest these attributes had more impact on outbreak metrics than the ranges of estimated disease parameter values. Additionally, although shipping accounted for a small percentage of overall transmission, areas receiving the most animal shipments tended to have other attributes that increase the probability of large outbreaks. The importance of including spatial and demographic heterogeneity in modelling outbreak trajectories and control actions is illustrated by specific regions consistently producing larger outbreaks than others

The characterization and manipulation of the bacterial microbiome of the Rocky Mountain wood tick, Dermacentor andersoni

BACKGROUND: In North America, ticks are the most economically impactful vectors of human and animal pathogens. The Rocky Mountain wood tick, Dermacentor andersoni (Acari: Ixodidae), transmits Rickettsia rickettsii and Anaplasma marginale to humans and cattle, respectively. In recent years, studies have shown that symbiotic organisms are involved in a number of biochemical and physiological functions. Characterizing the bacterial microbiome of D. andersoni is a pivotal step towards understanding symbiont-host interactions. FINDINGS: In this study, we have shown by high-throughput sequence analysis that the composition of endosymbionts in the midgut and salivary glands in adult ticks is dynamic over three generations. Four Proteobacteria genera, Rickettsia, Francisella, Arsenophonus, and Acinetobacter, were identified as predominant symbionts in these two tissues. Exposure to therapeutic doses of the broad-spectrum antibiotic, oxytetracycline, affected both proportions of predominant genera and significantly reduced reproductive fitness. Additionally, Acinetobacter, a free-living ubiquitous microbe, invaded the bacterial microbiome at different proportions based on antibiotic treatment status suggesting that microbiome composition may have a role in susceptibility to environmental contaminants. CONCLUSIONS: This study characterized the bacterial microbiome in D. andersoni and determined the generational variability within this tick. Furthermore, this study confirmed that microbiome manipulation is associated with tick fitness and may be a potential method for biocontrol

Spatio-temporal patterns and characteristics of swine shipments in the U.S. based on Interstate Certificates of Veterinary Inspection

Domestic swine production in the United States is a critical economic and food security industry, yet there is currently no large-scale quantitative assessment of swine shipments available to support risk assessments. In this study, we provide a national-level characterization of the swine industry by quantifying the demographic (i.e. age, sex) patterns, spatio-temporal patterns, and the production diversity within swine shipments. We characterize annual networks of swine shipments using a 30% stratified sample of Interstate Certificates of Veterinary Inspection (ICVI), which are required for the interstate movement of agricultural animals. We used ICVIs in 2010 and 2011 from eight states that represent 36% of swine operations and 63% of the U.S. swine industry. Our analyses reflect an integrated and spatially structured industry with high levels of spatial heterogeneity. Most shipments carried young swine for feeding or breeding purposes and carried a median of 330 head (range: 1–6,500). Geographically, most shipments went to and were shipped from Iowa, Minnesota, and Nebraska. This work, therefore, suggests that although the swine industry is variable in terms of its size and type of swine, counties in states historically known for breeding and feeding operations are consistently more central to the shipment network

Spatio-temporal patterns and characteristics of swine shipments in the U.S. based on Interstate Certificates of Veterinary Inspection

Domestic swine production in the United States is a critical economic and food security industry, yet there is currently no large-scale quantitative assessment of swine shipments available to support risk assessments. In this study, we provide a national-level characterization of the swine industry by quantifying the demographic (i.e. age, sex) patterns, spatio-temporal patterns, and the production diversity within swine shipments. We characterize annual networks of swine shipments using a 30% stratified sample of Interstate Certificates of Veterinary Inspection (ICVI), which are required for the interstate movement of agricultural animals. We used ICVIs in 2010 and 2011 from eight states that represent 36% of swine operations and 63% of the U.S. swine industry. Our analyses reflect an integrated and spatially structured industry with high levels of spatial heterogeneity. Most shipments carried young swine for feeding or breeding purposes and carried a median of 330 head (range: 1–6,500). Geographically, most shipments went to and were shipped from Iowa, Minnesota, and Nebraska. This work, therefore, suggests that although the swine industry is variable in terms of its size and type of swine, counties in states historically known for breeding and feeding operations are consistently more central to the shipment network

Ultraviolet C (UVC) Standards and Best Practices for the Swine Industry

Ultraviolet C (UVC) light has been widely used for disinfection for a long time in many industries, including human medicine and food processing. The practical application of this technology in livestock production is a more recent development and is increasingly being used on swine farms as producers look for ways to improve biosecurity in response to endemic diseases and the threat of transboundary and foreign animal diseases, such as African swine fever virus (ASFV). However, many swine producers and veterinarians are unfamiliar with the physics/mechanisms of UVC, the doses required to inactivate swine pathogens, and practical conditions under which UVC can operate effectively and practically on swine farms. Safety and maintenance requirements regarding the application are also not widely known. The pork industry lacks standards and best practices to apply this technology effectively and safely. To address this need, subject matter experts were convened for a one-day workshop to define standards and best practices for the use of UVC in the swine industry. The members of the working group included practicing swine veterinarians as well as academics with expertise in epidemiology, infectious disease, biosecurity, chemistry, and engineering. This white paper is the outcome of the workshop. In addition, the content of the white paper may be used to develop fact sheets, brochures and/or tutorial videos for swine producers and veterinarians

Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance

Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance

The variability of song variability in zebra finch (Taeniopygia guttata) populations

Birdsong is a classic example of a learned social behaviour. Song behaviour is also influenced by genetic factors, and understanding the relative contributions of genetic and environmental influences remains a major goal. In this study, we take advantage of captive zebra finch populations to examine variation in a population-level song trait: song variability. Song variability is of particular interest in the context of individual recognition and in terms of the neuro-developmental mechanisms that generate song novelty. We find that the Australian zebra finch Taeniopygia guttata castanotis (TGC) maintains higher song diversity than the Timor zebra finch T. g. guttata (TGG) even after experimentally controlling for early life song exposure, suggesting a genetic basis to this trait. Although wild-derived TGC were intermediate in song variability between domesticated TGC populations and TGG, the difference between domesticated and wild TGC was not statistically significant. The observed variation in song behaviour among zebra finch populations represents a largely untapped opportunity for exploring the mechanisms of social behaviour