Rating scales are commonly used to study voice quality. The purpose of this study was to examine inter-rater reliability/agreement of graduate student clinicians with differing levels of experience in rating voice perception. The Consensus Auditory Perception Evaluation of Voice (CAPE-V) was used to asses 1.) overall severity, 2.) roughness, 3.) breathiness, 4.) strain, 5.) pitch and 6.) loudness from a sample of pediatric voices. Twenty-four graduate clinicians who had completed a graduate level course in voice disorders participated in the study. Twelve of the participants were randomly selected to complete a perceptual training course prior to the evaluation session. Voice samples included 10 disordered and 2 normal voices from a population of children age 3-10 years old. The 12 voice samples were randomly repeated 3 times. Results of analysis of variance indicated that the groups significantly differed in their severity rating of the perceptual indices, suggesting that training affected the participants' judgment of severity. Additionally, variability was reduced as a function of training. Pearson product-moment correlation coefficient's revealed a moderate to strong relationship for all of the perceptual indices suggesting that regardless of training participants have an implicit understanding of normal versus disordered voice samples.

The ability to predict the reduction in capacity of a structure after an earthquake is vital in the process of assessing a structure after a main-shock or an after-shock. Main-shocks are normally followed by a few aftershocks in a short period of time. Researchers in the past have focused for the most part on the effects of main-shocks on buildings. Very little research has been performed on the ability to predict the reduction in capacity of bridges in aftershocks. This thesis focuses on providing a way of assessing the reduction in capacity for main-shocks as compared to aftershocks and the effects and importance of both in a bridge. The reduction in capacity was defined using three different ratios: ultimate force, stiffness, and strain energy ratio. The ratios were computed relative to an undamaged state following both the main-shock scenario and the main-shock combined with aftershock scenario. The force, stiffness, and strain energy quantities were obtained from lateral pushover analyses along the two lateral bridge axes. Probabilistic demand models describing the loss in capacity were formulated by pairing intensity measures, based on real ground motions obtained from previous earthquakes, for the main-shock and aftershock with the capacity ratios, obtained from nonlinear dynamic time history analysis. Additionally, the reduction in capacity was conditioned on residual displacement and intensity measure in an attempt to discover the reduction in capacity ratio due to the contribution of residual displacement and therefore separate contributions from geometrical and material nonlinearities. This thesis demonstrates that the usage of strain energy ratio provides a definition of capacity that ultimately provides the best correlation between capacity and intensity measure.

Prescription drug misuse (PDM), defined as use without a prescription or solely for the feeling or experience caused by the drug, has become a popular topic among substance use researchers. While the vast majority of studies on the topic tackle epidemiological questions surrounding PDM, there is a notable lack of studies that look specifically at risk factors rooted in sociological/criminological theories. The current research seeks to bridge this gap in the literature by examining theoretically based explanations for PDM among college students utilizing three criminological theories commonly applied to other forms of substance use: Social Learning Theory, Social Bonding/Control theory, and General Strain Theory. In addition, this study also seeks to examine differences in user types characterized by motives for misuse as they relate to predictors stemming from these theories of interest. Utilizing an independently collected sample of 841 college undergraduates from a large southern university, the findings show that nearly one in four students misused prescription drugs in the past semester. Motivations for PDM were primarily instrumental in nature, with very few respondents misusing solely for recreational purposes. Furthermore, social learning based risk factors could best account for PDM within the sample with partial and indirect supports also found for strain based risk factors as well. Implications of these findings as well as theoretical and practical applications are presented.

This study examines the impact of relative deprivation on juvenile delinquency. Though this topic has been explored by several researchers, there has not been much consistency in the research due to the operationalization of key variables. Traditionally, relative deprivation has been referenced in relation to Merton's Classic Strain Theory, using economic indicators to measure relative deprivation. Webber and Runciman however, expanded upon Merton's original premise and integrated more diverse measures of relative deprivation into their research. The current study utilizes Agnew's General Strain Theory (GST) as a means to measure relative deprivation as a broader and more subjective topic. This unique approach in the study of relative deprivation utilizes aspirations as a primary measure of relative deprivation.

The main focus of the thesis is to have better understanding of the atomic and electronic structures, vibrational dynamics and thermodynamics of metallic surfaces and bi-metallic nanoparticles (NPs) via a multi-scale simulational approach. The research presented here involves the study of the physical and chemical properties of metallic surfaces and NPs that are useful to determine their functionality in building novel materials. The study follows the 'bottom-up' approach for which the knowledge gathered at the scale of atoms and NPs serves as a base to build, at the macroscopic scale, materials with desired physical and chemical properties. We use a variety of theoretical and computational tools with different degrees of accuracy to study problems in different time and length scales. Interactions between the atoms are derived using both Density Functional Theory (DFT) and Embedded Atom Method (EAM), depending on the scale of the problem at hand. For some cases, both methods are used for the purpose of comparison. For revealing the local contributions to the vibrational dynamics and thermodynamics for the systems possessing site-specific environments, a local approach in real-space is used, namely Real Space Green's Function method (RSGF). For simulating diffusion of atoms/clusters and growth on metal surfaces, Molecular Statics (MS) and Molecular Dynamics (MD) methods are employed.

The economics of algae biofuels and bioproducts would be improved by increased biomass productivity. Two studies on this potential are described in this thesis – one on a locally isolated filamentous yellow-green alga and the other on a planktonic strain genetically improved via selective enrichment. Polycultures have been viewed as productive, stable, and, in some cases, harvestable by natural bioflocculation. Local native strains might have higher productivity than culture collection strains because they are already adapted to local outdoor conditions. In this study, the filamentous yellow-green alga Tribonema minus was isolated from a local volunteer polyculture. Its productivity as a monoculture was compared to a volunteer polyculture in a year of thrice-weekly samples. The study was conducted in duplicate 1,000-L, 3.5-m2 outdoor raceway ponds fed with nitrified and filtered reclaimed wastewater. T. minus monocultures were more productive (17.6 ± 0.5 g/m2-d; mean ± range) than the polyculture (13.3 ± 0.4 g/m2-d). The T. minus monocultures were stable, growing for an average of 38 days before significant contamination with other algae genera, at which point the cultures were restarted. The annual average biochemical composition, in percent of ash-free dry-weight, of the T. minus cultures was 28.3 ± 0.4% (mean ± std. dev.) carbohydrates, 37.6 ± 0.7% proteins, and 6.1 ± 0.3% lipids. Eicosapentaenoic acid, a valuable nutritional omega-3 fatty acid, comprised 0.3% to 4% of the ash-free dry-weight and was the predominant fatty acid methyl ester measured. In summary, an alga isolated from a volunteer polyculture was more productive as a monoculture than the originating polyculture. The monoculture biomass contained a valuable nutritional fatty acid. Scenedesmus obliquus was subjected to UV mutagenesis followed by cultivation in benchtop bubble columns at high dilution rates to select for cultures (cultigens) that grew faster than the wild-type. Fast growing cultigens were transferred to 1,350-L outdoor raceways ponds for productivity measurement. Cultigen and wild-type cultivation was conducted on reclaimed wastewater media in coastal central California for seven months. One cultigen, MBE 501, had 23% higher productivity than the S. obliquus wild-type (11.5 ± 0.02 vs. 9.4 ± 0.6 g/m2-d) during July 28-December 30, 2019. MBE 501 had been subjected to 1:400 and 1:200 dilutions twice per week for the first two months and last five months of selection, respectively, and went through 289 generations in the lab. Compared to a volunteer polyculture (14.4 ± 1.3 g/m2-d), MBE 501 was not as productive on average. This study demonstrated that high dilution rates in lab cultures can select for cells that are more productive in outdoor raceways. Genetic comparison of MBE 501 and its wild-type are pending.

This thesis describes the design and evaluation of two devices to be included in the next generation of the family of devices called the Boundary Layer Data System (BLDS). The first device, called the Quasi-Static Strain Data Acquisition System, is a continuation of the BLDS-M series of devices to be known as the Flight Test Data System (FTDS) that uses a modular approach to acquire non-flow, quasi-static mechanical strain measurements. Various breakout boards and development boards were used to synthesize the device, which were housed by a custom PCB board. The system is controlled by the SimbleeTM System on a Chip (SOC), and strain measurements are acquired using the HX711 analog-to-digital converter (ADC), and acceleration measurements are acquired with the ADXL345 accelerometer. The Arduino IDE was used to program and troubleshoot the device. The second device, called the Dynamic Strain Data Acquisition System, is a laboratory proof-of-concept device that evaluates various methods of acquiring dynamic strain measurements that may be used in future FTDS designs. A custom PCB board was designed that houses the microcontroller and the various passive components and ICs used to acquire and store strain measurements. The system is controlled by the Atxmega128A4U microcontroller, and measurements are acquired using the AD7708 external ADC and the on-board ADC of the microcontroller. Atmel StudioTM was used to program the microcontroller in C/C++ and to troubleshoot the device. Both devices were tested extensively under room temperature and low temperature conditions to prove the reliability and survivability of each device. The quasi-static data acquisition system was validated to acquire and store measurements to a microSD card at 10 Hz, with a peak operating current under 60 mA. The dynamic data acquisition system was proven to acquire a thousand measurements at 1 kHz and store the data to a microSD card, with a peak operating current under 60 mA.

The objectives of this study were to implement force sensors on the feet of a bipedal robot and analyze their response at different conditions. The data will be used to design a control strategy for the robot. The powered joints of the robot are driven by linear motors. A force sensor circuit was made and calibrated with different kinds of weight. A trajectory generator and inverse kinematics calculator for the robot were made to control the robot walking movement in an open-loop manner. The force data were taken at a certain period of time when the robot was in a standing position. Experiments with external disturbances were also performed on the robot. The ZMP position and mass of the robot were calculated by using the data of force sensors. The force sensor circuit was reliable in taking and handling the data from the sensor although the noise from the motors of the robot was present. / <p>Validerat; 20111115 (anonymous)</p>

Yes / Recycled aggregate concrete filled stainless steel tube (RAC-FSST) is a new type of composite member combining the advantage of stainless steel and RAC. In this paper, a total of twenty-four RAC-FSST stub columns were tested under axial load, considering the influences of coarse recycled aggregate (CRA) content, steel ratios and compressive strengths of RAC. The obtained results, including the failure patterns, responses of axial load vs. deformation, stress states of external stainless steel tube and inner RAC and confinement effects, were systematically analyzed. Results indicated that all specimens presented good ductility and high residual strengths after reaching the maximum axial load. The elastic stiffness of RAC-FSSTs obviously declined with the increasing CRA content, while the strain at the ultimate load was larger. The inclusion of CRA could advance the occurrence of the confinement and lead to lower confining stress. Based on the experimental results, an analytical model with consideration of confinement action was developed to predict the axial response of RAC-FSST stub columns. Besides, the current design provisions for the normal CFST and RAC-FST members were employed to evaluate their applicability to RAC-FSSTs. In general, the design rules EN 1994-1-1:2004, GB 50936-2014 and T/CECS 625-2019 gave a conservative and relatively accurate prediction on ultimate strength of RAC-FSST stub columns. / This work was supported by the National Natural Science Foundation.

A traumatic brain injury is usually caused by a direct impact to the head and is a common cause of disability and death all around the world. The most effective method to predict brain injury today, is to use a finite element head model. In this investigation, the three injury predictors strain, strain rate, and the product of strain and strain rate were investigated using a rat brain finite element model. The main goal was to find which injury predictor most effectively would predict injury. To find the injury predictor with the highest area under curve value, comparisons between experimental results obtained from simulations and results from previously performed experiments on rats were made. To better understand how different factors can affect the severity of symptoms from a traumatic brain injury, a parametric study with a focus on rotational direction and rotational duration was conducted. Simulations were run on a rat brain finite element model for three rotational directions and three rotational durations.  The statistical analysis was completed for six experiments and nine brain regions. The three injury predictors were extracted from 26 simulations completed on a rat brain finite element model, and the maximum values of the 95th percentile for each brain region were extracted. The results showed that the product of the strain and the strain rate was the most effective injury predictor for four out of six experiments (unconscious time, EPM arm change, EPM open duration, and MWM session 3). The parametric study investigated rotation in the axial, coronal, and sagittal plane against the three rotational durations 1.5 ms, 3 ms, and 6 ms. The parametric study revealed that both the direction and duration of rotation importantly influence the extent of damage in traumatic brain injuries. The results showed that rotation in the axial plane and a 3 ms duration caused the most brain damage. It was also concluded that the results need to undergo additional verification to further define the relationships between the rotational direction, the rotational duration, and the injury predictors. / En traumatisk hjärnskada orsakas vanligtvis av våld mot huvudet och är en vanlig orsak till både funktionsnedsättningar och dödsfall världen över. Den effektivastemetoden för att kunna förutsäga en hjärnskada idag är att använda en finit elementmetodmodell av en hjärna.  I denna undersökning har de tre skadeprediktorerna belastning, belastningshastighet och produkten av belastningen och belastningshastigheten undersöktes med hjälp av simuleringar genomförda på en modell av en råtthjärna, byggd med hjälp av finita elementmetoden. Målet var att ta reda på vilken skadeprediktor som mest effektivt kunde förutsäga hjärnskada. För att hitta skadeprediktorn med högst area under curve-värde gjordes jämförelser mellan experimentella resultat från simuleringar mot resultat från tidigare utförda experiment på råttor. För att få en djupare förståelse för vilka parametrar som kan påverka graden av symptom från en traumatisk hjärnskada genomfördes en parametrisk studie med fokus på rotationsriktning och rotationstid. Nya simuleringar genomfördes på en finit elementmodell av en råtthjärna i tre rotationsriktningar och under tre rotationstider.  Den statistiska analysen utfördes på sex experiment och för nio regioner i hjärnan. Belastningen, belastningshastigheten samt produkten av belastningen och belastningshastigheten extraherades från 26 simulerade finita element råtthjärnor och maximumvärdet från den 95.e percentilen sparades. Resultatet av den statistiska analysen visade att produkten av belastningen och belastningshastigheten var den skadeprediktorn med bäst skadeförutsägelse för fyra av sex experiment(medvetslös tid, EPM arm förflyttning, EPM varaktighet i öppet utrymme och MWM session 3). Under den parametriska studien undersöktes axial, koronal och sagittal rotationsriktning mot de tre rotationstiderna 1.5 ms, 3 ms och 6 ms. Resultatet av den parametriska studien visade att både rotationsriktning och rotationstid spelar viktiga roller när det kommer till omfattningen av symptom som kan uppstå vid en traumatisk hjärnskada. För de undersökta delarna av hjärnan var den rotationsriktning som orsakade störst skada rotation i det axiala planet och den rotationstid som orsakade mest skada var vid 3 ms. Slutsatsen att resultatet bör genomgå ytterligare verifiering drogs. Detta för att ytterligare definiera sambanden mellan rotationsriktning, rotationstid och skadeprediktorerna.