An Examination and Evaluation of the Jesus of the New Age

This thesis examines and evaluates the predominant view of Jesus the Christ among the prominent New Agers. This view--that Jesus was only a man who acquired mystic knowledge and power from his experiences with the Essenes and other mystical religions of the East, and that he manifested and exemplified the divinity which can be found in each person-generally opposes orthodox Christian teachings of the monotheistic divinity of Jesus Christ. The thesis argues that various claims of these New Agers are inconsistent (e.g. the reliability of Akashic Record), unverifiable (e.g. esoterism), and contrary to factual data (e.g. Notovitch\u27s account of Jesus\u27 travel to the East). While many New Agers argue that the monotheistic divinity of Jesus is a fabrication of the true teachings of Jesus, the thesis argues for the validity and superiority of the New Testament and especially Paul in their attribution of monotheistic divinity to Jesus. The thesis concludes that the New Age view of Jesus the Christ must be rejected

Emotional Intelligence and Its Relationship to Stress and Transition Shock Amongst First-Year College Students

Freshmen students often experience transition shock as their environment change from highschool to college. They are also under the impression that success in college depends solelyon their intellect and usually do not consider emotional intelligence a factor into the successof their academic endeavors. The purpose of this study was to investigate emotionalintelligence and its relationship to stress and transition shock amongst first-year collegestudents. A descriptive-correlational research design was employed. One hundred nineteenrespondents were chosen using purposive sampling technique. Frequency, percentagedistribution, weighted mean, standard deviation, and Pearson r correlation coefficient testwere used to analyze and treat the collected data. Respondents showed a high emotionalintelligence having an overall mean of 2.73 (SD = 0.35). The extent of the respondents’ stresswas also high with an overall mean of 2.61 (SD = 0.59). As for the extent of transition shockfelt by the respondents, the overall mean found is at 2.55 (SD = 0.52) which is alsointerpreted as high. A moderate negative significant relationship between emotionalintelligence and stress (r = -0.476), as well as the relationship between emotional intelligenceand transition shock (r = -0.417) among the freshmen. It is recommended that nursingstudents and educators become aware of emotional intelligence as a factor that contributes tothe success of the students’ transition from high school to college. Also, it is emphasized tofurther develop the emotional intelligence of the students to manage their stress and transitionshock to aid in the success of the students’ academic endeavors

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations

Handheld Spectrum Analyzer

The lack of user-friendly analyzers has made it difficult for musicians and other sound-based professions to reliably optimize the clarity of their performance. Despite the availability of digital sound conversion and optimization solutions in the market, only a handful of devices can detect the sources of interference anywhere. It is also important to ensure that sound quality is evenly distributed and perceived to be acceptable throughout the venue. The measured power distribution over various frequency ranges can be used to tune and arrange musical equipment to optimize the sound quality experienced by the audience. The Handheld Spectrum Analyzer is a device that analyzes the spectrum of input sound sources received from either audio equipment or the surrounding environment. In addition, the device allows the user to move throughout the working area and observe the different power distributions of the sound spectrum. The proof-of-concept prototype for our Handheld Spectrum Analyzer should be able to accept surrounding sound as input, calculate its frequency spectrum and display its corresponding power bar graphs on the display unit. Furthermore, the device’s interface will tentatively have other features, such as allowing the user to save and store captured spectrums for future comparisons.&nbsp

A Riemann solver at a junction compatible with a homogenization limit

We consider a junction regulated by a traffic lights, with n incoming roads and only one outgoing road. On each road the Phase Transition traffic model, proposed in [6], describes the evolution of car traffic. Such model is an extension of the classic Lighthill-Whitham-Richards one, obtained by assuming that different drivers may have different maximal speed. By sending to infinity the number of cycles of the traffic lights, we obtain a justification of the Riemann solver introduced in [9] and in particular of the rule for determining the maximal speed in the outgoing road.Comment: 19 page

Tracking Cyber Adversaries with Adaptive Indicators of Compromise

A forensics investigation after a breach often uncovers network and host indicators of compromise (IOCs) that can be deployed to sensors to allow early detection of the adversary in the future. Over time, the adversary will change tactics, techniques, and procedures (TTPs), which will also change the data generated. If the IOCs are not kept up-to-date with the adversary's new TTPs, the adversary will no longer be detected once all of the IOCs become invalid. Tracking the Known (TTK) is the problem of keeping IOCs, in this case regular expressions (regexes), up-to-date with a dynamic adversary. Our framework solves the TTK problem in an automated, cyclic fashion to bracket a previously discovered adversary. This tracking is accomplished through a data-driven approach of self-adapting a given model based on its own detection capabilities. In our initial experiments, we found that the true positive rate (TPR) of the adaptive solution degrades much less significantly over time than the naive solution, suggesting that self-updating the model allows the continued detection of positives (i.e., adversaries). The cost for this performance is in the false positive rate (FPR), which increases over time for the adaptive solution, but remains constant for the naive solution. However, the difference in overall detection performance, as measured by the area under the curve (AUC), between the two methods is negligible. This result suggests that self-updating the model over time should be done in practice to continue to detect known, evolving adversaries.Comment: This was presented at the 4th Annual Conf. on Computational Science & Computational Intelligence (CSCI'17) held Dec 14-16, 2017 in Las Vegas, Nevada, US

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

Interannual climate variability associated with the El Niño/Southern Oscillation (ENSO) phenomenon and regional climatic circulation mechanisms in the equatorial Indian Ocean result in significant rainfall and ecological anomaly patterns that are major drivers of spatial and temporal patterns of mosquito-borne disease outbreaks. Correlation and regression analyses of long time series rainfall, vegetation index, and temperature data show that large scale anomalies occur periodically that may influence mosquito vector populations and thus spatial and temporal patterns of Rift Valley fever and chikungunya outbreaks. Rift Valley fever outbreak events occurred after a period of ∼3–4 months of persistent and above-normal rainfall that enabled vector habitats to flourish. On the other hand, chikungunya outbreaks occurred during periods of high temperatures and severe drought over East Africa and the western Indian Ocean islands. This is consistent with highly populated environmental settings where domestic and peri-domestic stored water containers were the likely mosquito sources. However, in Southeast Asia, approximately 52% of chikungunya outbreaks occurred during cooler-than-normal temperatures and were significantly negatively correlated with drought. Besides climate variability, other factors not accounted for such as vertebrate host immunity may contribute to spatio-temporal patterns of outbreaks