In conjunction with Atlantic Pacific Engineering and the Henry County Public Service Authority, Virginia Tech’s Environmental Engineering program measured the emissions from an experimental scrap tire incinerator/wastewater treatment plant sludge dryer. This report recounts the techniques used and the results obtained during this testing. The Virginia Department of Environmental Quality supplied a list of pollutants of permitting interest which included a variety of criteria pollutants, toxics, and metals. Sampling for all the listed compounds required adherence to EPA Methods 5, 201A, 29, 0010, 0011, 0030, 6, 7D, 26A, and 18. Emissions testing transpired during the incinerator’s 72-hour test burn: 0800 October 30th to 0800 November 2nd, 1995. Due to time constraints, only part of one nonpotable water sampling series was completed rather than the proposed duplicate testing using both drying agents: nonpotable water and sludge. High particulate (57 lb/hr) and metal (21.4 lb/hr total) emissions indicate a fairly significant amount of air pollution control equipment will be necessary for a commercial plant. Both nitrogen oxides and sulfur dioxide had low emission rates: 1.73 lb/hr and 0.64 lb/hr, respectively, due to the nonpotable water spray acting as a fairly efficient scrubber removing a great deal of nitrogen oxides, sulfur dioxide, and some metals. Because of sample analysis preparation problems, no organics results were obtained. Commercial development of this incinerator will have to include a sizable quantity of air pollution control equipment: a $5 million plant will need approximately $1 million worth of control equipment. / Master of Science

The hemlock woolly adelgid (HWA), Adelges tsugae Annand (Hemiptera: Adelgidae), is an invasive pest from Japan that is causing significant hemlock mortality in the eastern U.S. The most promising control method is biological control. Beetles in the genus Laricobius are adelgid specialists. In 2005, Laricobius osakensis, was discovered in Japan and in 2010 was approved for release in the eastern United States and there have now been more than 60 releases. In 2014, the polar vortex resulted in significant HWA mortality in the eastern U.S., depleting the food source for L. osakensis, which resulted in low field recoveries of them. In the 2015-2016 field season, there were 14 larvae recovered from the field, and the 2016-2017 field season yielded 90 larvae. A significant correlation was found between Laricobius beetles recovered and HWA density, between HWA density and plant hardiness zone, and a negative correlation between Laricobius beetles recovered and average tree health. Understanding more about the supercooling point of L. osakensis gave insight to its ability to survive subfreezing temperatures as occurred in 2014. Comparison of the supercooling point between the northern and southern populations of L. osakensis, and to the other released HWA predator, L. nigrinus, will allow us to determine which biological control agent is best suited for release in the coldest regions. The overall mean supercooling points of northern L. osakensis was -13.52 oC, southern L. osakensis was -13.42 oC, and L. nigrinus was -13.57 oC. There were no significant differences between species or populations. / Master of Science in Life Sciences / The hemlock woolly adelgid (HWA) is an invasive insect species from Asia that is the most important pest of eastern and Carolina hemlock trees in the eastern U. S. Laricobius osakensis is a small beetle from Japan that feeds only on HWA, and been released since 2012 in the eastern United States to control HWA populations. It is important to determine if L. osakensis populations were able to survive and spread in the eastern United States, and if the predator has an effect on HWA populations and the health of hemlock trees. In 2014, extreme cold temperatures in Virginia resulted in wide-scale death of HWA populations, depleting the food source for L. osakensis. Consequently, only 17 L. osakensis beetles were found on hemlock trees near release sites; however, the following year, 147 beetles were found. The ability to survive extreme cold temperatures is important for selecting a biological control agent for release in such regions. We can find out information about how tolerant a species is to cold temperatures by determining the supercooling point, the temperature at which it cannot stop itself from freezing. In this study we compared the supercooling points of a northern and southern population of L. osakensis, as well as another previously released and established biological control agent of HWA, Laricobius nigrinus. I found that there was no significant difference in supercooling point between the different types of Laricobius beetles suggesting that none of these species or populations appears to be anymore cold tolerant than the other for release in the colder regions of the U. S.

This thesis is concerned with the development of algorithms for simulation optimization (SO), a special case of stochastic optimization where the objective function can only be evaluated through noisy observations from a simulation. Deterministic techniques, when directly applied to simulation optimization problems fail to converge due to their inability to handle randomness thus requiring sophisticated algorithms. However, many existing algorithms dedicated for simulation optimization often show poor performance on implementation as they require extensive parameter tuning. To overcome these shortfalls with existing SO algorithms, we develop ADALINE, a line search based algorithm that eliminates the need for any user defined parameters. ADALINE is designed to identify a local minimum on continuous and integer ordered feasible sets. ADALINE on a continuous feasible set mimics deterministic line search algorithms, while it iterates between a line search and an enumeration procedure on integer ordered feasible sets in its quest to identify a local minimum. ADALINE improves upon many of the existing SO algorithms by determining the sample size adaptively as a trade-off between the error due to estimation and the optimization error, that is, the algorithm expends simulation effort proportional to the quality of the incumbent solution. We also show that ADALINE converges ``almost surely'' to the set of local minima. Finally, our numerical results suggest that ADALINE converges to a local minimum faster, outperforming other advanced SO algorithms that utilize variable sampling strategies. To demonstrate the performance of our algorithm on a practical problem, we apply ADALINE in solving a surgery rescheduling problem. In the rescheduling problem, the objective is to minimize the cost of disruptions to an existing schedule shared between multiple surgical specialties while accommodating semi-urgent surgeries that require expedited intervention. The disruptions to the schedule are determined using a threshold based heuristic and ADALINE identifies the best threshold levels for various surgical specialties that minimizes the expected total cost of disruption. A comparison of the solutions obtained using a Sample Average Approximation (SAA) approach, and ADALINE is provided. We find that the adaptive sampling strategy in ADALINE identifies a better solution quickly than SAA. / Ph. D. / This thesis is concerned with the development of algorithms for simulation optimization (SO), where the objective function does not have an analytical form, and can only be estimated through noisy observations from a simulation. Deterministic techniques, when directly applied to simulation optimization problems fail to converge due to their inability to handle randomness thus requiring sophisticated algorithms. However, many existing algorithms dedicated for simulation optimization often show poor performance on implementation as they require extensive parameter tuning. To overcome these shortfalls with existing SO algorithms, we develop ADALINE, a line search based algorithm that minimizes the need for user defined parameter. ADALINE is designed to identify a local minimum on continuous and integer ordered feasible sets. ADALINE on continuous feasible sets mimics deterministic line search algorithms, while it iterates between a line search and an enumeration procedure on integer ordered feasible sets in its quest to identify a local minimum. ADALINE improves upon many of the existing SO algorithms by determining the sample size adaptively as a trade-off between the error due to estimation and the optimization error, that is, the algorithm expends simulation effort proportional to the quality of the incumbent solution. Finally, our numerical results suggest that ADALINE converges to a local minimum faster than the best available SO algorithm for the purpose. To demonstrate the performance of our algorithm on a practical problem, we apply ADALINE in solving a surgery rescheduling problem. In the rescheduling problem, the objective is to minimize the cost of disruptions to an existing schedule shared between multiple surgical specialties while accommodating semi-urgent surgeries that require expedited intervention. The disruptions to the schedule are determined using a threshold based heuristic and ADALINE identifies the best threshold levels for various surgical specialties that minimizes the expected total cost of disruption. A comparison of the solutions obtained using traditional optimization techniques, and ADALINE is provided. We find that the adaptive sampling strategy in ADALINE identifies a better solution more quickly than traditional optimization.

Particle ingestion in gas turbine applications can be detrimental to performance and pose significant safety concerns. Areas of high sand concentration are hazardous to aircraft, requiring precautions like routine inspections and maintenance. The engine failure modes are dependent on particle composition, concentration, and size. Particles containing certain minerals tend to melt and stick to turbine blades, which is known as glazing. Alternatively, particles may erode blades from repeated collisions, or they may fill cooling passage holes. Therefore, it is necessary to develop systems that identify these parameters as particles are ingested. This thesis introduces three separate systems responsible for collecting sand concentration, size distribution, and material composition of sand. A particle visualization technique (ParVis), developed at Virginia Tech, was used to validate two sensors developed by commercial partners. One sensor measures particle size and velocity with a method similar to Laser Doppler Velocimetry (LDV). The second sensor measures particle composition with X-Ray Fluorescence (XRF) by physically sampling particles in a flow. There has been little research on applying XRF to moving particles, so experimental data were collected to demonstrate the effectiveness of the sensor. Detection comparisons between two particle types showed promising outcomes for the XRF. Meanwhile, the ParVis technique was iterated to overcome previous limitations and implemented into the testing process to provide particle concentration measurements. Particularly, improvements led to increased accuracy and reliability of the method such as reducing variance in concentration approximations. / Master of Science / Aircraft are constantly ingesting particles into their engines. Those operating in dusty environments are at higher risks of engine failure because more particles are ingested, which cause damage in several ways. As engine manufacturers push the turbine operating temperatures higher for efficiency and emissions, sand particles reach melting temperatures and stick to turbine blades, which results in overheating. Because of the potential risks to life, sand ingestion research continues to provide solutions for improving aircraft safety. This study explores the capabilities of new sensors to quantify characteristics of ingested particles, including the concentration, size distribution, and material composition of sand. An illumination technique for measuring sand concentration from particle imaging was developed at Virginia Tech. The technique was iterated to overcome previous limitations and improve its reliability during this study. It provides a more accurate depiction of the testing conditions that can be used to diagnose and calibrate sensors. In this case, two sensors issued by Creare were tested, one of which measures size and particle velocity, while the other measures sand composition. The first sensor relies on non-intrusive optical measurements and can be mounted directly to an engine inlet. The second sensor collects particles from the inlet flow and applies X-Ray Fluorescence (XRF) to the moving particles. There has been little research on applying XRF to a flow of particles, so experimental data were critical to demonstrate the effectiveness of the sensor. technique was iterated to overcome previous limitations and implemented into the testing process to provide particle concentration measurements.

No / D-amino acids are useful building blocks for de novo peptide design and they play a role in aging-related diseases associated with gradual protein racemization. For amino acids with achiral side chains, one should be able to presume that the conformational propensities of L- and D-amino acids are a reflection of one another due to the straightforward geometric inversion at the Cα atom. However, this presumption does not account for the directionality of the backbone dipole and the inverted propensities have never been definitively confirmed in this context. Furthermore, there is little known of how alternative side chain chirality affects the backbone conformations of isoleucine and threonine. Using a GGXGG host-guest pentapeptide system, we have completed exhaustive sampling of the conformational propensities of the D-amino acids, including D-allo-isoleucine and D-allo-threonine, using atomistic molecular dynamics simulations. Comparison of these simulations with the same systems hosting the cognate L-amino acids verifies that the intrinsic backbone conformational propensities of the D-amino acids are the inverse of their cognate L-enantiomers. Where amino acids have a chiral center in their side chain (Thr, Ile) the β-configuration affects the backbone sampling, which in turn can confer different biological properties. / NIH

Yes / The Early Bronze Age round barrows at Irthlingborough, Northamptonshire and Gayhurst, Buckinghamshire contained remarkably large quantities of cattle (Bos taurus) remains. At Irthlingborough, at least 185 skulls with smaller numbers of mandibles, shoulder blades and pelves were found together with a small number of skeletal elements from aurochs (Bos primigenius). In contrast, the remains from Gayhurst are dominated by the limb bones from more than 300 animals. This study employed strontium isotope ratio analysis of cattle tooth enamel from 15 cattle and one aurochs to investigate the diversity of the animals’ origins at both sites and provide insights into Early Bronze Age funerary practices. Although strontium results show that most of the cattle and the aurochs included in this study were consistent with local origins, one animal from each barrow was born remotely, most likely in western Britain. In addition, a second Gayhurst animal was consistent with origins in a region of chalk rather than the local Jurassic sediments.

<p dir="ltr">Fearlessness is a construct often discussed in clinical and personality psychology. However, at the self-report trait level, there is little work focusing on its empirical structure and how that applies to measurement. The present study examined the IPIP-Fearlessness scale using experience sampling methodology to examine how scores on the measure predict behaviors in daily life. Using a pre-registered analytical approach, participants completed a baseline survey and brief daily surveys six times daily for one full week. The final sample consisted of 241 participants. Criterion variables measuring boldness, general personality, sensation seeking, and sensitivity to reward and punishment were also correlated with the IPIP-Fearlessness measure’s subscales, and a confirmatory factor analysis confirmed the measure’s structure.</p><p dir="ltr">Results showed that two of the IPIP-Fearless subscales (Low Anxiety and Sociability) did predict daily behaviors, whereas there were not significant predictions found for the other behaviors. Affect (negative, positive, anxious, bored) was also found to be significant predictor for several of the behavioral outcome variables, as well as interpersonal status. Additional exploratory analyses were also conducted. The findings from this study continue to elucidate how we can use empirically derived self-report trait fearlessness, and its relationship to additional constructs and behaviors.</p>

Targeted software testing is a critical task in development of secure software. The core challenge of targeted software testing is to generate many inputs that reach specific code target locations in a given program. However, this task is challenging because it is NP-hard in theory and real-world programs contain very large input spaces and many lines of code, making this difficult in practice. In this thesis, I introduce a new approach for targeted software testing based on adaptive sampling. The key insight is to reduce the original problem to a sequence of approximate counting problems, and I apply this approach to targeted software testing in two stages. First, to find a single target-reaching input when no such input is given, I develop a new search algorithm MC2 that adaptively uses approximate-count feedback to narrow down which input region is more likely to contain a target-reaching input using probabilistic bisection. Second, given a single target-reaching input, I develop a new set approximation algorithm ProgramSampler that adaptively learns an approximation of the set of target-reaching inputs based on approximate-count feedback, where the set approximation can be efficiently uniformly sampled for many target-reaching inputs. Backed by theoretical guarantees, these techniques have been highly effective in practice: outperforming existing methods on average by 1-2 orders of magnitude.

The bulk of the research work in wave related areas considers sea waves as stochastic objects leading to wave forecasting techniques based on statistical approaches. Due to the complex dynamics of the sea waves’ behaviour, statistical techniques are probably the only viable approach when forecasting over substantial spatial and temporal intervals. However this view changes when limiting the forecasting time to a few seconds or when the goal is to estimate the quiescent periods that occur due to the beating interaction of the wave components, especially in narrow band seas. This work considers the multi disciplinary research field of deterministic sea wave prediction (DSWP), exploring different aspects of DSWP associated with shallow angle LIDAR systems. The main goal of this project is to study and develop techniques to reduce the prediction error. The first part deals with issues related to shallow angle LIDAR systems data problems, while the remaining part of this work concentrates on the prediction system and propagation models regardless of the source of the data. The two main LIDAR data problems addressed in this work are the non-uniform distribution and the shadow region problems. An empirical approach is used to identify the characteristics of shadow regions associated with different wave conditions and different laser position. A new reconstruction method is developed to address the non-uniformed sampling problem, it is shown that including more information about the geometry and the dynamics of the problem improves the reconstruction error considerably. The frequency domain approach to the wave propagation model is examined. The effect of energy leakage on the prediction error is illustrated. Two approaches are explored to reduce this error. First a modification of the simple dispersive phase shifting filter is tested and shown to improve the prediction. The second approach is to reduce the energy leakage with an iterative Window-Expansion method. Significant improvement of the prediction error is achieved using this method in comparison to the End-Matching method typically used in DSWP systems. The final part in examining the frequency domain approach is to define the prediction region boundaries associated with a given prediction accuracy. The second propagation model approach is the Time/Space domain approach. In this method the convolution of the measured data and the propagation filter impulse response is used in the prediction system. In this part of the research work properties of these impulse responses are identified. These are found to be quite complicated representations. The relation between the impulse response (duration and shift) with prediction time and distance are studied. Quantification of these impulse responses properties are obtained by polynomial approximation and non-symmetric filter analysis. A new method is shown to associate the impulse response properties to the prediction region of both the Fixed Time and Fixed Point mode.

Made available in DSpace on 2017-07-10T14:38:18Z (GMT). No. of bitstreams: 1 LACERDA.pdf: 2108583 bytes, checksum: abf7b4231c66cc12a04083c0090487bb (MD5) Previous issue date: 2013-07-18 / The almost complete replacement of the native vegetation of the Atlantic Forest by agriculture and livestock generated an altered matrix in which are embedded fragments of different sizes and historical use and degradation. In this study, the population density of Sapajus nigritus was estimated in two forest fragments surrounded by agricultural crops in southern Brazil. We use the method of linear transect between September 2011 and January 2013, covering 344.08 km in area and 216 km in another. We recorded 119 sightings and 35, respectively. In the first area the population density of Sapajus nigritus was 92.15 individuals / km2, and 32.10 individuals / km2 for the second area. While the lowest value is within the limits found for the species throughout its geographical distribution, the value of 92.15 individuals / km2 is among the highest ever recorded. In addition to offering food crops by anthropogenic factors such as low hunting pressure and predation, as well as composition and forest structure may be related to the densities found / A quase completa substituição da vegetação nativa da Floresta Atlântica pela agricultura e pecuária gerou uma matriz alterada onde estão inseridos fragmentos de diferentes tamanhos e históricos de uso e degradação. Neste estudo, a densidade populacional de Sapajus nigritus foi estimada em dois remanescentes florestais cercados por cultivos agrícolas no sul do Brasil. Nós utilizamos o método de transecções lineares entre setembro de 2011 e janeiro de 2013, percorrendo 344,08 km em uma área e 216 km em outra. Foram registrados 119 e 35 avistamentos, respectivamente. Na primeira área a densidade populacional de Sapajus nigritus foi de 92,15 indivíduos/km2, e 32,10 indivíduos/km2 para a segunda área. Enquanto o valor mais baixo está dentro dos limites encontrados para a espécie ao longo de sua distribuição geográfica, o valor de 92,15 indivíduos/km2 está entre os mais elevados já registrados. Além da oferta de alimento de origem antrópica pelos cultivos, fatores como baixa pressão de caça e predação, além da composição e estrutura da floresta podem estar relacionados às densidades encontradas