Evolution and religion : theory, definitions, and the natural selection of religious behavior

The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.Title from PDF of title page (University of Missouri--Columbia, viewed on November 13, 2009).Thesis advisor: Dr. Craig T. Palmer.M.A. University of Missouri--Columbia 2009.Chapter 1 Presents a brief summary of recent theory and research into religion from evolutionary cognitive psychology and behavioral ecology. Chapter 2 addresses the debate over whether religion is an adaptation directly favored by natural selection, or a by-product of other evolved traits. The implications of how religion is defined for how it is explained are also introduced in chapter 2, as well as requirements for building a valid argument for religion as an adaptation. In chapter 3, shifts focus from explanation to that of definition. Critical discussion of appropriate criteria for an accurate definition of religion is presented, existing definition. Chapter 4 presents the results of two studies formulated to test the definition of religion posited in chapter 3. Finally, chapter 5 lays out an explanation of the evolution of religion as a traditional behavior that was directly favored by natural selection for its effects on the descendant-leaving success of ancestral humans.Includes bibliographical references

Natural selection favoring more transmissible HIV detected in United States molecular transmission network.

HIV molecular epidemiology can identify clusters of individuals with elevated rates of HIV transmission. These variable transmission rates are primarily driven by host risk behavior; however, the effect of viral traits on variable transmission rates is poorly understood. Viral load, the concentration of HIV in blood, is a heritable viral trait that influences HIV infectiousness and disease progression. Here, we reconstruct HIV genetic transmission clusters using data from the United States National HIV Surveillance System and report that viruses in clusters, inferred to be frequently transmitted, have higher viral loads at diagnosis. Further, viral load is higher in people in larger clusters and with increased network connectivity, suggesting that HIV in the United States is experiencing natural selection to be more infectious and virulent. We also observe a concurrent increase in viral load at diagnosis over the last decade. This evolutionary trajectory may be slowed by prevention strategies prioritized toward rapidly growing transmission clusters

Surface uplift and time-dependent seismic hazard due to fluid injection in eastern Texas

Observations that unequivocally link seismicity and wastewater injection are scarce. Here we show that wastewater injection in eastern Texas causes uplift, detectable in radar interferometric data up to >8 kilometers from the wells. Using measurements of uplift, reported injection data, and a poroelastic model, we computed the crustal strain and pore pressure. We infer that an increase of >1 megapascal in pore pressure in rocks with low compressibility triggers earthquakes, including the 4.8–moment magnitude event that occurred on 17 May 2012, the largest earthquake recorded in eastern Texas. Seismic activity increased even while injection rates declined, owing to diffusion of pore pressure from earlier periods with higher injection rates. Induced seismicity potential is suppressed where tight confining formations prevent pore pressure from propagating into crystalline basement rocks

Mentum: Encrypted, Knowledge-Based Modalities

Unified low-energy communication have led to many theoretical advances, including linked lists and wide-area networks. Even though such a hypothesis at first glance seems unexpected, it fell in line with our expectations. In our research, we prove the development of von Neumann machines, demonstrates the intuitive importance of networking. Here, we examine how robots can be applied to the extensive unification of Byzantine fault tolerance and superblocks

The composition of cosmic rays near the Bend (10 to the 15th power eV) from a study of muons in air showers at sea level

The distribution of muons near shower cores was studied at sea level at Fermilab using the E594 neutrino detector to sample the muon with E testing 3 GeV. These data are compared with detailed Monte Carlo simulations to derive conclusions about the composition of cosmic rays near the bend in the all particle spectrum. Monte Carlo simulations generating extensive air showers (EAS) with primary energy in excess of 50 TeV are described. Each shower record contains details of the electron lateral distribution and the muon and hadron lateral distributions as a function of energy, at the observation level of 100g/cm. The number of detected electrons and muons in each case was determined by a Poisson fluctuation of the number incident. The resultant predicted distribution of muons, electrons, the rate events are compared to those observed. Preliminary results on the rate favor a heavy primary dominated cosmic ray spectrum in energy range 50 to 1000 TeV

Study of muons near shower cores at sea level using the E594 neutrino detector

The E594 neutrino detector has been used to study the lateral distribution of muons of energy 3 GeV near shower cores. The detector consists of a 340 ton fine grain calorimeter with 400,000 cells of flash chamber and dimensions of 3.7 m x 20 m x 3.7 m (height). The average density in the calorimeter is 1.4 gm/sq cm, and the average Z is 21. The detector was triggered by four 0.6 sq m scintillators placed immediately on the top of the calorimeter. The trigger required at least two of these four counters. The accompanying extensive air showers (EAS) was sampled by 14 scintillation counters located up to 15 m from the calorimeter. Several off line cuts have been applied to the data. Demanding five particles in at least two of the trigger detectors, a total of 20 particles in all of them together, and an arrival angle for the shower 450 deg reduced the data sample to 11053 events. Of these in 4869 cases, a computer algorithm found at least three muons in the calorimeter

Embodied Discourses of Literacy in the Lives of Two Preservice Teachers

This study examines the emerging teacher literacy identities of Ian and A.J., two preservice teachers in a graduate teacher education program in the United States. Using a poststructural feminisms theoretical framework, the study illustrates the embodiment of literacy pedagogy discourses in relation to the literacy courses’ discourse of comprehensive literacy and the literacy biographical discourses of Ian and A.J. The results of this study indicate the need to deconstruct how the discourse of comprehensive literacy limits how we, as literacy teacher educators, position, hear and respond to our preservice teachers and suggests the need for differentiation in our teacher education literacy courses

Remote sensing data from CLARET: A prototype CART data set

The data set containing radiation, meteorological , and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) Program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of the experiment, ARM scientists requested archival of subsets of the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory

Autonomous decision-making against induced seismicity in deep fluid injections

The rise in the frequency of anthropogenic earthquakes due to deep fluid injections is posing serious economic, societal, and legal challenges to geo-energy and waste-disposal projects. We propose an actuarial approach to mitigate this risk, first by defining an autonomous decision-making process based on an adaptive traffic light system (ATLS) to stop risky injections, and second by quantifying a "cost of public safety" based on the probability of an injection-well being abandoned. The ATLS underlying statistical model is first confirmed to be representative of injection-induced seismicity, with examples taken from past reservoir stimulation experiments (mostly from Enhanced Geothermal Systems, EGS). Then the decision strategy is formalized: Being integrable, the model yields a closed-form ATLS solution that maps a risk-based safety standard or norm to an earthquake magnitude not to exceed during stimulation. Finally, the EGS levelized cost of electricity (LCOE) is reformulated in terms of null expectation, with the cost of abandoned injection-well implemented. We find that the price increase to mitigate the increased seismic risk in populated areas can counterbalance the heat credit. However this "public safety cost" disappears if buildings are based on earthquake-resistant designs or if a more relaxed risk safety standard or norm is chosen.Comment: 8 pages, 4 figures, conference (International Symposium on Energy Geotechnics, 26-28 September 2018, Lausanne, Switzerland

Improved Boundary Layer Depth Retrievals from MPLNET

Continuous lidar observations of the planetary boundary layer (PBL) depth have been made at the Micropulse Lidar Network (MPLNET) site in Greenbelt, MD since April 2001. However, because of issues with the operational PBL depth algorithm, the data is not reliable for determining seasonal and diurnal trends. Therefore, an improved PBL depth algorithm has been developed which uses a combination of the wavelet technique and image processing. The new algorithm is less susceptible to contamination by clouds and residual layers, and in general, produces lower PBL depths. A 2010 comparison shows the operational algorithm overestimates the daily mean PBL depth when compared to the improved algorithm (1.85 and 1.07 km, respectively). The improved MPLNET PBL depths are validated using radiosonde comparisons which suggests the algorithm performs well to determine the depth of a fully developed PBL. A comparison with the Goddard Earth Observing System-version 5 (GEOS-5) model suggests that the model may underestimate the maximum daytime PBL depth by 410 m during the spring and summer. The best agreement between MPLNET and GEOS-5 occurred during the fall and they diered the most in the winter