II D Music, Philosophy, and Communications Presentation 2: Rand’s Rationale in Favor of Ethical Egoism

This presentation addresses Ayn Rand\u27s view of ethical egoism and presents a counterargument against her argument

DSCOVR EPIC vegetation earth system data record: product analysis and scientific exploration

The NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR) mission was launched on February 11, 2015 to the Sun-Earth Lagrangian L1 point where it began to collect radiance data of the entire sunlit Earth every 65 to 110 min in June 2015. It provides imageries in near backscattering directions at ten ultraviolet to near infrared narrow spectral bands. The DSCOVR EPIC science product suite includes vegetation Earth System Data Record (VESDR) that provides leaf area index (LAI) and diurnal courses of normalized difference vegetation index (NDVI), sunlit LAI (SLAI), fraction of incident photosynthetically active radiation (FPAR) and directional area scattering function (DASF). The parameters at 10 km sinusoidal grid and 65 to 110 minute temporal frequency generated from the upstream DSCOVR EPIC BRF product were released on June-07-2018 and are available from the NASA Langley Atmospheric Science Data Center. This poster provides an overview of the EPIC VESDR research. This includes a description of the algorithm and its performance, details of the product, its initial quality assessment and obtaining new information on the 3D canopy structure for use in ecological models through novel combinations of the VESDR parameters.Accepted manuscrip

The Validation of a Detailed Strategic Planning Process Model for the Implementation of Distance Education in Higher Education

The purpose of this study was to develop, refine, and validate a model of the strategic planning process for distance education. To achieve this end, the informed opinion from a population of peer-nominated experts was solicited over three rounds of iterative Delphi questionnaires administered via electronic mail. Using descriptive statistics to analyze central tendency and variation, the straw model was refined into a validated model by the final Delphi round. In developing this model, the study answered specific questions about the following: (1) The impact of volatile technological change on a strategic distance education plan. (2) The optimum size and composition of a strategic planning body for distance education. (3) The use of planning assumptions. (4) Internal and external factors that are part of the strategic assessment (scan) and analysis for distance education. (5) The development and selection of courses of action in the planning process. (6) Critical steps in the strategic planning process for distance education. The panel of experts required for a Delphi study was selected by soliciting the names of individuals considered experts in the area of planning for distance education from a purposefully selected sample of professionals involved in distance education. From this population 28 experts agreed to serve on the Delphi panel and 22 experts (78.57%) completed all three rounds of the study. A straw model, representing a synthesis of the literature on the strategic planning process, served as the framework for this research. The Delphi panel of experts was asked to identify the issues and questions that they believe should be addressed in each of the phases of the straw model. The Delphi questionnaires were employed in a sequence that effectively developed, refined, and validated a model of the strategic planning process for distance education. The findings of this study provided a detailed model of the strategic planning process for distance education designed to empower higher education planners to be proactive in the highly dynamic distance education environment. The Distance Education Strategic Planning Process Model includes 202 planning elements and 10 planning phases presented in a hypertext format to enable nonlinear navigation

Optimal Placement of Public Electric Vehicle Charging Stations Using Deep Reinforcement Learning

The placement of charging stations in areas with developing charging infrastructure is a critical component of the future success of electric vehicles (EVs). In Albany County in New York, the expected rise in the EV population requires additional charging stations to maintain a sufficient level of efficiency across the charging infrastructure. A novel application of Reinforcement Learning (RL) is able to find optimal locations for new charging stations given the predicted charging demand and current charging locations. The most important factors that influence charging demand prediction include the conterminous traffic density, EV registrations, and proximity to certain types of public buildings. The proposed RL framework can be refined and applied to cities across the world to optimize charging station placement.Comment: 25 pages with 12 figures. Shankar Padmanabhan and Aidan Petratos provided equal contributio

Variable effect of co-infection on the HIV infectivity: Within-host dynamics and epidemiological significance

<p>Abstract</p> <p>Background</p> <p>Recent studies have implicated viral characteristics in accounting for the variation in the HIV set-point viral load (spVL) observed among individuals. These studies have suggested that the spVL might be a heritable factor. The spVL, however, is not in an absolute equilibrium state; it is frequently perturbed by immune activations generated by co-infections, resulting in a significant amplification of the HIV viral load (VL). Here, we postulated that if the HIV replication capacity were an important determinant of the spVL, it would also determine the effect of co-infection on the VL. Then, we hypothesized that viral factors contribute to the variation of the effect of co-infection and introduce variation among individuals.</p> <p>Methods</p> <p>We developed a within-host deterministic differential equation model to describe the dynamics of HIV and malaria infections, and evaluated the effect of variations in the viral replicative capacity on the VL burden generated by co-infection. These variations were then evaluated at population level by implementing a between-host model in which the relationship between VL and the probability of HIV transmission per sexual contact was used as the within-host and between-host interface.</p> <p>Results</p> <p>Our within-host results indicated that the combination of parameters generating low spVL were unable to produce a substantial increase in the VL in response to co-infection. Conversely, larger spVL were associated with substantially larger increments in the VL. In accordance, the between-host model indicated that co-infection had a negligible impact in populations where the virus had low replicative capacity, reflected in low spVL. Similarly, the impact of co-infection increased as the spVL of the population increased.</p> <p>Conclusion</p> <p>Our results indicated that variations in the viral replicative capacity would influence the effect of co-infection on the VL. Therefore, viral factors could play an important role driving several virus-related processes such as the increment of the VL induced by co-infections. These results raise the possibility that biological differences could alter the effect of co-infection and underscore the importance of identifying these factors for the implementation of control interventions focused on co-infection.</p

Effect of variable transmission rate on the dynamics of HIV in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p>The cause of the high HIV prevalence in sub-Saharan Africa is incompletely understood, with heterosexual penile-vaginal transmission proposed as the main mechanism. Heterosexual HIV transmission has been estimated to have a very low probability; but effects of cofactors that vary in space and time may substantially alter this pattern.</p> <p>Methods</p> <p>To test the effect of individual variation in the HIV infectiousness generated by co-infection, we developed and analyzed a mathematical sexual network model that simulates the behavioral components of a population from Malawi, as well as the dynamics of HIV and the co-infection effect caused by other infectious diseases, including herpes simplex virus type-2, gonorrhea, syphilis and malaria.</p> <p>Results</p> <p>The analysis shows that without the amplification effect caused by co-infection, no epidemic is generated, and HIV prevalence decreases to extinction. But the model indicates that an epidemic can be generated by the amplification effect on HIV transmission caused by co-infection.</p> <p>Conclusion</p> <p>The simulated sexual network demonstrated that a single value for HIV infectivity fails to describe the dynamics of the epidemic. Regardless of the low probability of heterosexual transmission per sexual contact, the inclusion of individual variation generated by transient but repeated increases in HIV viral load associated with co-infections may provide a biological basis for the accelerated spread of HIV in sub-Saharan Africa. Moreover, our work raises the possibility that the natural history of HIV in sub-Saharan Africa cannot be fully understood if individual variation in infectiousness is neglected.</p