Do you speak Hadoop? An analytics tutorial of the latest tech in big data, and how you can utilize them in HR.

Organizations are increasingly using big data and analytics in decision-making, and HR is no exception to this trend. Applications of big data analytics are becoming common in HR with advanced tools being developed for this purpose. However, despite having a good grasp of the basic research methodologies, I-O and HR professionals generally lack the knowledge and skills to use big data analytics in their practice. In addition, the latest guidelines for education and training in industrial-organizational psychology do not even mention the terms “big data” and “analytics”, showing that this concern also extends to graduate education, and the literature is not very informative about how to actually do HR analytics. This presentation is aimed at addressing this problem by showing the audience “plain English” explanations of some of the technology, advanced modeling techniques, and methodologies that I-O/HR professionals might not be exposed to in master/Ph.D. programs or while working in HR. This will include AI/machine learning, natural language processing, relational databases, data lakes, and neural networks, and the software options available that handle big data applications such as Hadoop and other programming languages used by professionals in the field

Trophic Garnishes: Cat–Rat Interactions in an Urban Environment

BACKGROUND:Community interactions can produce complex dynamics with counterintuitive responses. Synanthropic community members are of increasing practical interest for their effects on biodiversity and public health. Most studies incorporating introduced species have been performed on islands where they may pose a risk to the native fauna. Few have examined their interactions in urban environments where they represent the majority of species. We characterized house cat (Felis catus) predation on wild Norway rats (Rattus norvegicus), and its population effects in an urban area as a model system. Three aspects of predation likely to influence population dynamics were examined; the stratum of the prey population killed by predators, the intensity of the predation, and the size of the predator population. METHODOLOGY/PRINCIPAL FINDINGS:Predation pressure was estimated from the sizes of the rat and cat populations, and the characteristics of rats killed in 20 alleys. Short and long term responses of rat population to perturbations were examined by removal trapping. Perturbations removed an average of 56% of the rats/alley but had no negative long-term impact on the size of the rat population (49.6+/-12.5 rats/alley and 123.8+/-42.2 rats/alley over two years). The sizes of the cat population during two years (3.5 animals/alley and 2.7 animals/alley) also were unaffected by rat population perturbations. Predation by cats occurred in 9/20 alleys. Predated rats were predominantly juveniles and significantly smaller (144.6 g+/-17.8 g) than the trapped rats (385.0 g+/-135.6 g). Cats rarely preyed on the larger, older portion of the rat population. CONCLUSIONS/SIGNIFICANCE:The rat population appears resilient to perturbation from even substantial population reduction using targeted removal. In this area there is a relatively low population density of cats and they only occasionally prey on the rat population. This occasional predation primarily removes the juvenile proportion of the rat population. The top predator in this urban ecosystem appears to have little impact on the size of the prey population, and similarly, reduction in rat populations doesn't impact the size of the cat population. However, the selected targeting of small rats may locally influence the size structure of the population which may have consequences for patterns of pathogen transmission

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Distribution of Populations and Suitable Habitat for Spotted Turtles (Clemmys Guttata) and Blanding’s Turtles (Emydoidea Blandingii) in Indiana

The spotted turtle (Clemmys guttata) and Blanding’s turtle (Emydoidea blandingii) are two state-endangered species in Indiana whose populations are in decline. Historically, both species were found across the northern portion of Indiana in various wetland habitats. There are multiple causes of population decline for both species, including habitat fragmentation, habitat loss and degradation, urban development and encroachment, poaching, and road mortality. Despite efforts to record these species across the state, there has been no intensive population assessments. Based on this need, I conducted both visual encounter surveys across the state and used Maximum Entropy (MaxEnt) modeling to facilitate understanding the current distribution of both species in Indiana. Twenty-three locations were visited and surveyed in Indiana, with trapping being conducted at an additional four locations where populations were known to be larger. Surveys aided in delineation of six populations of Blanding’s turtles and five populations of spotted turtles. A total of 69 Blanding’s turtles and 70 spotted turtles were observed between surveying and trapping. Delineated populations were mainly found in the northern third of Indiana. This data and other occurrences were used to predict suitable habitat across Indiana. The Blanding’s turtle models were sufficiently resolved to predict potential localities or potential sites for focused management or repatriation. Spotted turtle model performance reflected the need for more samples, but also the likelihood of fewer numbers due to declining habitat availability. Both Blanding’s turtle and spotted turtle models argue for the need of more intense survey efforts based on historical occurrences, as well as restoration efforts across the state. Most models for both species were observed to have a trend towards suitable habitat in the northern third of the state, correlating with the results of the survey efforts. The results of this project indicate that Blanding’s turtle and spotted turtle populations are still in decline likely due to limited habitat availability

Implementing Medical Marijuana Education into Existing Patient Care Practices

With implementation of HB 523, there is the potential for a gap in patient care due to strict recommendation parameters for approved cannabinoid-based drugs and marijuana still federally classed as a CI substance. This session is designed to provide pharmacists, in all practicing capacities, with the knowledge and tools needed to assess appropriate use of medications and maintain patient-centered care standards