Martin Agency Freelancer Onboarding

Onboarding new employees is a necessary but often a lengthy process at any company, but it can be especially challenging for companies like The Martin Agency. An advertising firm based in Richmond, Virginia. The nature of their work channels the need for many of their employees to be freelancers or short term contractors. At the time the project began, the process to request a new freelancer would start as a paper form submitted by a department supervisor. It would then require approval from members of different departments within agency, and the data had to be converted into an electronic form to interface with systems like payroll and Active Directory. Freelancers would sometimes complete their jobs before the onboarding process was ever completed. Our solution was to design a responsive web application that provided a familiar experience to filling out the paper form, but automatically interfaced with different systems within The Martin Agency. The agencies’ developers used mostly Microsoft technologies, so to make it as easy as possible to integrate into their current environment and transfer ownership, our application used much of the same technologies. It consisted of Microsoft’s .NET 4.5 and MVC framework, Windows, IIS, and SQL Server. The application would automatically populate form dropdowns from their Media Ocean data provider. The form submissions would then create a database entry, and post a new freelancer request to WorkFront – their workflow management software. The end result was a well-documented functional application that was deployed to The Martin Agency’s development environment.https://scholarscompass.vcu.edu/capstone/1178/thumbnail.jp

Actuation Fatigue of Shape Memory Alloys

A testing method was developed to cycle quickly and repeatably Ni60Ti40 (wt. %) SMA specimens through temperature-induced transformation while under constant stress until failure. Previous works have shown fatigue cracks to initiate in or around Ni3Ti precipitates during repeated thermal cycling in this highly Ni-rich alloy. Actuation fatigue tests were conducted on specimens produced from material from different material suppliers and direction relative to cold-rolling. The specimens were placed under a constant applied stress of 200 MPa and thermally cycled through complete transformation. Some of the specimens were homogenized for 1 hour in a vacuum furnace and the rest were homogenized for 2 hours in a nitrogen furnace, and were all aged for 20 hours. It was seen during actuation fatigue testing that specimens homogenized for two hours had higher actuation strain, accumulated more irrecoverable strain and had longer actuation fatigue lives compared to specimens homogenized for one hour. Another trend observed was that specimens with the greatest amount of accumulated irrecoverable strain, which was caused predominately by transformation induced plasticity, had the longest actuation fatigue lives. Postmortem analysis showed a change in cracking behavior with precipitate orientation. Cracks initiated inside the Ni3Ti precipitates oriented parallel to the loading direction and at the interface between the precipitate and matrix when perpendicular. Two dimensional plane stress finite element simulations of a linear elastic ellipsoidal precipitate inside a non-linear transforming SMA matrix were conducted to explain further the change in cracking behavior by analyzing the stress fields in and around the precipitates. The results showed the stress inside the precipitate was greater when oriented parallel than perpendicular to the loading direction, which explains the observed change in cracking behavior. Another objective of actuation fatigue testing is to generate useful data to create predictive tools for future SMA actuator designs. A work-based method has been developed using actuation fatigue results found in literature. The method is shown to fit accurately data found in literature to a curve with only two material parameters. The results of this method show promise to predict accurately the actuation fatigue life of SMA components, however more testing is necessary to validate completely the method

A Preliminary Examination of Elevated Blood Lead Levels in a Rural Georgia County

Background: Rural areas are often viewed as lower risk for lead poisoning and toxic exposures seriously impacting development of the brain and central nervous system; this report examines the prevalence of elevated blood lead levels for childrenCounty, GA. Methods: Lead surveillance data from the Georgia Department of Public Health (DPH) were analyzed using SAS®v-9.3 to calculate the prevalence of elevated blood lead levels (≥5ug/dL) among those children in Ben Hill County who had been tested for lead; the results were compared to Georgia and national data. Results: A preliminary analysis of 2010-2015 screening data for Ben Hill County indicates that 8.73% (95%- CI: 7.4%-10.1%) of children that were tested for lead exceeded the Centers for Disease Control reference level (≥5ug/dL) and is approximately 3.5 and 2.4 times higher, respectively, when compared to the National (2.5%) and State (3.64%) percentages of children exposed to lead at or above the reference level. Conclusions: While these data are preliminary and more analysis is planned to ascertain the full breadth, source, and scope of the problem, it highlights lead poisoning risks rural communities face that are often overlooked in population-based risk analysis and research on lead exposure in children

A Preliminary Examination of Elevated Blood lead Levels in a Rural Georgia County

Background: Children in Flint, Michigan were exposed to lead at unsafe levels in drinking water bringing renewed interest and national attention to an old public health problem. In Georgia, thousands of children are exposed annually to lead at unsafe levels primarily from paint in homes built before 1978. With lead poisoning typically viewed as an urban problem, rural areas are often considered lower-risk in light of similar lead poisoning risk factors, albeit on a smaller scale. The purpose of this preliminary study was to examine the prevalence of elevated blood lead levels in childrenCounty, Georgia, a county designated as lower risk. Methods: Lead surveillance data from the Georgia Department of Public Health (DPH) were analyzed using SAS®v-9.3 to calculate the prevalence of elevated blood lead levels (≥5ug/dL) among those children in Ben Hill County who had been tested for lead; the results were compared to state and national data. Results: A preliminary analysis of 2010-2015 screening data for Ben Hill County indicates that 8.73% (95%- CI: 7.4%-10.1%) of children who were tested for lead exceeded the Centers for Disease Control reference level (≥5ug/dL). This is approximately 3.5 and 2.4 times higher, respectively, when compared to national (2.5%) and state (3.64%) percentages of children exposed to lead ≥5ug/dL. Analysis also indicated low screening rates, which limits interpretation of population prevalence. Conclusions: Lead poisoning is often viewed as an urban, inner-city problem due to a higher percentage of older homes clustered together, exposing more children, compared to rural areas with homes geographically dispersed. While these data are preliminary and more analysis is planned to understand the problem, it highlights lead poisoning risks rural communities face that are often overlooked in population-based risk analysis and research on lead exposure in children

A Preliminary Examination of Elevated Blood Lead Levels in a Rural Georgia County

Background: Rural areas are often viewed as lower risk for lead poisoning and toxic exposures seriously impacting development of the brain and central nervous system; this report examines the prevalence of elevated blood lead levels for childrenCounty, GA. Methods: Lead surveillance data from the Georgia Department of Public Health (DPH) were analyzed using SAS®v-9.3 to calculate the prevalence of elevated blood lead levels (≥5ug/dL) among those children in Ben Hill County who had been tested for lead; the results were compared to Georgia and national data. Results: A preliminary analysis of 2010-2015 screening data for Ben Hill County indicates that 8.73% (95%- CI: 7.4%-10.1%) of children that were tested for lead exceeded the Centers for Disease Control reference level (≥5ug/dL) and is approximately 3.5 and 2.4 times higher, respectively, when compared to the National (2.5%) and State (3.64%) percentages of children exposed to lead at or above the reference level. Conclusions: While these data are preliminary and more analysis is planned to ascertain the full breadth, source, and scope of the problem, it highlights lead poisoning risks rural communities face that are often overlooked in population-based risk analysis and research on lead exposure in children

Preliminary prediction of individual response to electroconvulsive therapy using whole-brain functional magnetic resonance imaging data.

Electroconvulsive therapy (ECT) works rapidly and has been widely used to treat depressive disorders (DEP). However, identifying biomarkers predictive of response to ECT remains a priority to individually tailor treatment and understand treatment mechanisms. This study used a connectome-based predictive modeling (CPM) approach in 122 patients with DEP to determine if pre-ECT whole-brain functional connectivity (FC) predicts depressive rating changes and remission status after ECT (47 of 122 total subjects or 38.5% of sample), and whether pre-ECT and longitudinal changes (pre/post-ECT) in regional brain network biomarkers are associated with treatment-related changes in depression ratings. Results show the networks with the best predictive performance of ECT response were negative (anti-correlated) FC networks, which predict the post-ECT depression severity (continuous measure) with a 76.23% accuracy for remission prediction. FC networks with the greatest predictive power were concentrated in the prefrontal and temporal cortices and subcortical nuclei, and include the inferior frontal (IFG), superior frontal (SFG), superior temporal (STG), inferior temporal gyri (ITG), basal ganglia (BG), and thalamus (Tha). Several of these brain regions were also identified as nodes in the FC networks that show significant change pre-/post-ECT, but these networks were not related to treatment response. This study design has limitations regarding the longitudinal design and the absence of a control group that limit the causal inference regarding mechanism of post-treatment status. Though predictive biomarkers remained below the threshold of those recommended for potential translation, the analysis methods and results demonstrate the promise and generalizability of biomarkers for advancing personalized treatment strategies

Characteristics of Lightning Within Electrified Snowfall Events Using Total Lightning Measurements

No abstract availabl

Predictive signature of static and dynamic functional connectivity for ECT clinical outcomes

Introduction: Electroconvulsive therapy (ECT) remains one of the most effective approaches for treatment-resistant depressive episodes, despite the potential cognitive impairment associated with this treatment. As a potent stimulator of neuroplasticity, ECT might normalize aberrant depression-related brain function via the brain’s reconstruction by forming new neural connections. Multiple lines of evidence have demonstrated that functional connectivity (FC) changes are reliable indicators of antidepressant efficacy and cognitive changes from static and dynamic perspectives. However, no previous studies have directly ascertained whether and how different aspects of FC provide complementary information in terms of neuroimaging-based prediction of clinical outcomes.Methods: In this study, we implemented a fully automated independent component analysis framework to an ECT dataset with subjects (n = 50, age = 65.54 ± 8.92) randomized to three treatment amplitudes (600, 700, or 800 milliamperes [mA]). We extracted the static functional network connectivity (sFNC) and dynamic FNC (dFNC) features and employed a partial least square regression to build predictive models for antidepressant outcomes and cognitive changes.Results: We found that both antidepressant outcomes and memory changes can be robustly predicted by the changes in sFNC (permutation test p < 5.0 × 10−3). More interestingly, by adding dFNC information, the model achieved higher accuracy for predicting changes in the Hamilton Depression Rating Scale 24-item (HDRS24, t = 9.6434, p = 1.5 × 10−21). The predictive maps of clinical outcomes show a weakly negative correlation, indicating that the ECT-induced antidepressant outcomes and cognitive changes might be associated with different functional brain neuroplasticity.Discussion: The overall results reveal that dynamic FC is not redundant but reflects mechanisms of ECT that cannot be captured by its static counterpart, especially for the prediction of antidepressant efficacy. Tracking the predictive signatures of static and dynamic FC will help maximize antidepressant outcomes and cognitive safety with individualized ECT dosing