京都大学 / 新制・課程博士 / 博士(地球環境学) / 甲第24858号 / 地環博第241号 / 新制||地環||47(附属図書館) / 京都大学大学院地球環境学舎地球環境学専攻 / (主査)教授 星野, 敏, 准教授 鬼塚, 健一郎, 准教授 落合, 知帆 / 学位規則第4条第1項該当 / Doctor of Global Environmental Studies / Kyoto University / DGAM

Several warm winter events have occurred across the Southeast in the past decade, including 2 major events in 2017 and 2018 in Georgia and South Carolina. Plants will begin their spring growth sooner than climatology would suggest and then be damaged by early spring frosts in what is commonly known as a "false spring" event. Some species of plants, like peaches and blueberries, which produce buds early in the season, are just an example of some of the agricultural products more at risk than others. As an important measure of dormancy time in plants, chill hours present a measurement capable of tracking phenological shifts in plants. While a lack of required chill hours can delay spring emergence, intense warm periods can override the chilling hour requirement and induce spring emergence. This project involves training self-organizing maps (SOMs) to identify periods of anomalous winter warming based on a reduced number of chill hours within a 5-day temporal period compared to the period's climatological average. A second SOM is nested in the node that produced the most anomalous events to identify the range of warming that occurs in the most anomalous events, the synoptic setups of these events, and when these occurred. Hourly 2-meter temperature from ERA5 is used to conduct this analysis over a domain centered primarily over South Carolina and Georgia with a temporal period of 1980-2020. Climatological examination of chill hour accumulations in the past 4 decades show an overall decrease in chill hour accumulation across the past decade (2011-2020) Results indicated that periods of higher-than-average temperatures are increasing with time while periods of average or lower than average temperatures are decreasing with time. Both results were statistically significant by Mann-Kendall test. The results of the nested SOMs suggest that an increase in patterns of southerly flow (a common pattern for warmer temperatures) is occurring through time. A third SOM investigating early spring hard freezes was inconclusive but illustrated that some years had more early spring frosts than others independent of how many warmer than average periods occurred in the main winter. The use of SOMs for investigating climatological and synoptic changes in winter and early spring proved successful and effective. Future modifications to these SOMs could be used to identify more trends that exist within these seasons. / Master of Science / Several warm winter events have occurred across the Southeast in the past decade, including 2 major events in 2017 and 2018 in Georgia and South Carolina. Plants will begin their spring growth sooner than climatology would suggest and then be damaged by early spring frosts in what is commonly known as a "false spring" event. Some species of plants, like peaches and blueberries, which produce buds early in the season, are just an example of some of the agricultural products more at risk than others. As an important measure of dormancy time in plants, chill hours present a measurement capable of tracking shifts from normal winter to spring transition in plants. While a lack of required chill hours can delay leaf emergence and spring blooms, intense warm periods can override the chilling hour requirement and induce this spring emergence. This project involves training self-organizing maps (SOMs), a machine learning model, to identify periods of anomalous winter warming based on a reduced number of chill hours within a 5-day temporal period compared to the period's climatological average. A second SOM is nested in the node that produced the most anomalously warm events to identify the range of warming that occurs in the most anomalous events, the large-scale meteorological setups of these events, and when these occurred. Hourly 2-meter temperature from ERA5, a climatological dataset, is used to conduct this analysis over a domain centered primarily over South Carolina and Georgia with a temporal period of 1980-2020. Climatological examination of chill hour accumulations in the past 4 decades show an overall decrease in chill hour accumulation across the past decade (2011-2020) Results indicated that periods of higher-than-average temperatures are increasing with time while periods of average or lower than average temperatures are decreasing with time. Both of these trend findings were statistically significant by Mann-Kendall test. The results of the nested SOMs suggest that an increase in patterns of southerly flow (a common pattern for warmer temperatures) is occurring through time. A third SOM investigating early spring hard freezes (temperatures low enough to cause damage to plant cellular structures) was inconclusive but illustrated that some years had more early spring frosts than others independent of how many warmer than average periods occurred in the main winter. The use of SOMs for investigating climatological and synoptic changes in winter and early spring proved successful and effective. Future modifications to these SOMs could be used to identify more trends that exist within these seasons.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第25193号 / 医博第5079号 / 新制||医||1072(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 山本 洋介, 教授 中山 健夫, 教授 江木 盛時 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

The onset of a yellow indication is typically associated with the risk of vehicle crashes resulting from dilemma-zone and red-light-running problems. Such risk of vehicle crashes is greater for high-speed signalized intersection approaches. The research presented in this dissertation develops statistical as well as behavioral frameworks for modeling driver behavior while approaching high-speed signalized intersection approaches at the onset of a yellow indication. The analysis in this dissertation utilizes two sources of data. The main source is a new dataset that was collected as part of this research effort during the summer of 2008. This experiment includes two instructed speeds; 72.4 km/h (45 mph) with 1727 approaching trials (687 running and 1040 stopping), and 88.5 km/h (55 mph) with 1727 approaching trials (625 running and 1102 stopping). The complementary source is an existing dataset that was collected earlier in the spring of 2005 on the Virginia Smart Road facility. This dataset includes a total of 1186 yellow approaching trials (441 running and 745 stopping). The adopted analysis approach comprises four major parts that fulfill the objectives of this dissertation. The first part is concerned with the characterization of different driver behavioral attributes, including driver yellow/red light running behavior, driver stop-run decisions, driver perception-reaction times (PRT), and driver deceleration levels. The characterization of these attributes involves analysis of variance (ANOVA) and frequency distribution analyses, as well as the calibration of statistical models. The second part of the dissertation introduces a novel approach for computing the clearance interval duration that explicitly accounts for the reliability of the design (probability that drivers do not encounter a dilemma zone). Lookup tables are developed to assist practitioners in the design of yellow timings that reflects the stochastic nature of driver PRT and deceleration levels. An extension of the proposed approach is presented that can be integrated with the IntelliDriveSM initiative. Furthermore, the third part of the dissertation develops an agent-based Bayesian statistics approach to capture the stochastic nature of the driver stop-run decision. The Bayesian model parameters are calibrated using the Markov Chain Monte Carlo (MCMC) slice procedure implemented within the MATLAB® software. In addition, two procedures for the Bayesian model application are illustrated; namely Cascaded regression and Cholesky decomposition. Both procedures are demonstrated to produce replications that are consistent with the Bayesian model realizations, and capture the parameter correlations without the need to store the set of parameter realizations. The proposed Bayesian approach is ideal for modeling multi-agent systems in which each agent has its own unique set of parameters. Finally, the fourth part of the dissertation introduces and validates a state-of-the-art behavioral modeling framework that can be used as a tool to simulate driver behavior after the onset of a yellow indication until he/she reaches the intersection stop line. The behavioral model is able to track dilemma zone drivers and update the information available to them every time step until they reach a final decision. It is anticipated that this behavioral model will be implemented in microscopic traffic simulation software to enhance the modeling of driver behavior as they approach signalized intersections. / Ph. D.

Witnessing partner violence (WPV) in childhood and adolescence can have significant impact on psychological functioning throughout development. Studies have shown that parenting factors, perceived social support, coping strategies, age at exposure, and gender can influence the relationship between WPV and outcomes. Although WPV can have serious implications towards emotion regulation abilities, empirical research on the link between WPV and emotion regulation is inadequate. The current study examined the associations between the frequency and types of WPV in childhood and adolescence and emotion dysregulation in adulthood. The study further explored the roles of parental bonds, social support, coping strategies, age at exposure, and gender as moderators in the relationship between WPV and emotion dysregulation. Data were collected using an undergraduate sample at Virginia Tech (N = 1040). Results indicated that verbal violence exposure was a significant predictor of emotion dysregulation while physical violence and total WPV were not. Parental warmth moderated the relationship between all three types of WPV and emotion dysregulation, while parental control and age of onset were moderators for total and physical WPV. Social support moderated the relationship between verbal violence exposure and emotion dysregulation. Coping strategies and gender were not found to be significant moderators. Exploratory analyses were conducted to further explore these relationships. The findings and their implications are discussed. / Ph. D.

The ionosphere carries a substantial portion of the electrical current flowing in Earth's space environment. Currents and electric fields in the ionosphere are generated through (1) the interaction of the solar wind with the magnetosphere, i.e. magnetic reconnection and (2) the collision of neutral molecules with ions leading to charged particle motions across the geomagnetic field, i.e. neutral wind dynamo. In this study we applied statistical and deep learning techniques to various datasets to investigate the driving influences of ionospheric electrodynamics at mid- and high-latitudes. In Chapter 2, we analyzed an interval on 12 September 2014 which provided a rare opportunity to examine dynamic variations in the dayside convection throat measured by the RISR-N radar as the IMF transitioned from strong By+ to strong Bz+. We found that the high-latitude plasma convection can have dual flow responses with different lag times to strong dynamic IMF conditions that involve IMF By rotation. We proposed a dual reconnection scenario, one poleward of the cusp and the other at the magnetopause nose, to explain the observed flow behavior. In Chapters 3 and 4, we investigated the driving influences of nightside subauroral convection. We developed new statistical models of nightside subauroral (52 - 60 degree) convection under quiet (Kp <= 2+) to moderately disturbed (Kp = 3) conditions using data from six mid-latitude SuperDARN radars across the continential United States. Our analysis suggests that the quiet-time subauroral flows are due to the combined effects of solar wind-magnetosphere coupling leading to penetration electric field and neutral wind dynamo with the ionospheric conductivity modulating their relative dominance. In Chapter 5, we examined the external drivers of magnetic substorms using machine learning. We presented the first deep learning based approach to directly predict the onset of a magnetic substorm. The model has been trained and tested on a comprehensive list of onsets compiled between 1997 and 2017 and achieves 72 +/- 2% precision and 77 +/- 4% recall rates. Our analysis revealed that the external factors, such as the solar wind and IMF, alone are not sufficient to forecast all substorms, and preconditioning of the magnetotail may be an important factor. / Doctor of Philosophy / The Earth's ionosphere, ranging from about 60 km to 1000 km in altitude, is an electrically conducting region of the upper atmosphere that exists primarily due to ionization by solar ultraviolet radiation. The Earth's magnetosphere is the region of space surrounding the Earth that is dominated by the Earth's magnetic field. The magnetosphere and ionosphere are tightly coupled to each other through the magnetic field lines which act as highly conductive wires. The sun constantly releases a stream of plasma (i.e., gases of ions and free electrons) known as the solar wind, which carries the solar magnetic field known as the interplanetary magnetic field (IMF). The solar wind interacts with the Earth's magnetosphere and ionosphere through a process called magnetic reconnection, which drives currents and electric fields in the coupled magnetosphere and ionosphere. The ionosphere carries a substantial portion of the electrical currents flowing in the Earth's space environment. The interaction of the ionospheric currents and electric fields with plasma and neutral particles is called ionospheric electrodynamics. In this study we utilized statistical and machine learning techniques to study ionospheric electrodynamics in three distinct regions. First, we studied the influence of duskward IMF on plasma convection in the polar region using measurements from the Resolute Bay Incoherent Scatter Radar – North (RISR-N). Specifically, we analyzed an interval on Sep. 12, 2014 when the RISR-N radar made measurements in the high latitude noon sector while the IMF turned from duskward to strongly northward. We found that the high latitude plasma convection can have flow responses with different lag times during strong IMF conditions that involve IMF By rotation. Such phenomena are rarely observed and are not predicted by the antiparallel or the component reconnection models applied to quasi‐static conditions. We propose a dual reconnection scenario, with reconnection occurring poleward of the cusp and also at the dayside subsolar point on the magnetopause, to explain the rarely observed flow behavior. Next, we used measurements from six mid-latitude Super Dual Auroral Radar Network (SuperDARN) radars distributed across the continental United States to investigate the driving influences of plasma convection in the subauroral region, which is equatorward of the region where aurora is normally observed. Previous studies have suggested that plasma motions in the subaruroral region were mainly due to the neutral winds blowing the ions, i.e. the neutral wind dynamo. However, our analysis suggests that subauroral plasma flows are due to the combined effects of solar wind-magnetosphere coupling and neutral wind dynamo with the ionospheric conductivity modulating their relative importance. Finally, we utilized the latest machine learning techniques to examine the external drivers (i.e., solar wind and IMF) of magnetic substorms, which is a physical phenomenon that occurs in the auroral region and causes explosive brightening of the aurora. We developed the first machine learning model that forecasts the onset of a magnetic substorm over the next one hour. The model has been trained and tested on a comprehensive list of onsets compiled between 1997 and 2017 and correctly identify substorm onset ~75% of the time. In contrast, an earlier prediction algorithm correctly identified only ~21% of the substorm onsets in the same dataset. Our analysis revealed that external factors alone are not sufficient to forecast all substorms, and preconditioning of the nightside magnetosphere may be an important factor.

In the past several decades there has been an increased interest in sand, dust, and ash particulates ingestion study for gas turbine engine applications. Recently, there has been an increase in commercial and military fleets operating in medium to highly dusty environments, such as areas in Africa, the Middle East, and Asia. Dusty environments can cause blockage in turbine cooling circuits which can lead to early engine maintenance or removals. Ingested debris can melt, forming glassy or molten deposits on various hot section components in gas turbine engines. This thesis evaluates the onset of deposit formation using an experimental rig to perform testing in high temperature environment. In general, deposits on turbine components can affect the operating capacity and the overall operating efficiency of gas turbine engines. Particulate ingestion events can be catastrophic and cost millions of dollars in maintenance and repairs. The experimental work in this thesis focused only on quantifying the initial deposit formation in high temperature environment to aid in the development of resilient engine design and operational diagnostics. Testing was performed using HASTELLOY® X coupons and Arizona Road Dust with main gas flow temperatures between 1050°C and 1100°C. Arizona Road Dust sample with sizing between 2µm and 40µm were used for experimental testing. The sensitivity of the initial deposit formation on cooled HASTELLOY® X coupon surface was investigated by using an inline air heater. Three cooling test conditions: no cooling, 500°C cooling, and 250°C cooling, were used to alter the surface temperature of the coupon during testing. Results from testing indicated cooling test conditions used have a small impact on deposit formation. / Master of Science / In the past several decades there has been an increased interest in sand, dust, and ash particulates ingestion study for gas turbine engine applications. Recently, there has been an increase in commercial and military fleets operating in medium to highly dusty environments, such as areas in Africa, the Middle East, and Asia. Dusty environments can cause blockage in turbine cooling circuits which can lead to early engine maintenance or removals. Ingested debris can melt, forming glassy or molten deposits on various hot section components in gas turbine engines. This thesis evaluates the onset of deposit formation using an experimental rig to perform testing in high temperature environment. In general, deposits on turbine components can affect the operating capacity and the overall operating efficiency of gas turbine engines. Particulate ingestion events can be catastrophic and cost millions of dollars in maintenance and repairs. The experimental work in this thesis focused only on quantifying the initial deposit formation in high temperature environment to aid in the development of resilient engine design and operational diagnostics. Testing was performed using HASTELLOY® X coupons and Arizona Road Dust with main gas flow temperatures between 1050°C and 1100°C. Arizona Road Dust sample with sizing between 2µm and 40µm were used for experimental testing. The sensitivity of the initial deposit formation on cooled HASTELLOY® X coupon surface was investigated by using an inline air heater. Three cooling test conditions: no cooling, 500°C cooling, and 250°C cooling, were used to alter the surface temperature of the coupon during testing. Results from testing indicated cooling test conditions used have a small impact on deposit formation.

This study examined the Voice onset time (VOT) of Mandarin and English initial position stops as produced by native American-English speaking learners of Mandarin and also native speakers. The study primarily investigated the role of second language experience on native-like production of L2 VOT for the Mandarin stops /p, t, k, ph, th, kh/ and additionally examined any evidence for phonetic drift in the L1 English VOT as a result of L2 Mandarin learning and acquisition. To achieve this, the production of L2 Mandarin and L1 English by native AmericanEnglish speaking learners of Mandarin of two different levels of experience (beginner and advanced learners) were compared to that of monolingual Native speakers of Mandarin andEnglish. In total, thirty native American-English speaking learners of Mandarin, eight monolingual native Mandarin speakers, and eight monolingual American-English speakers participated in the study. Data was elicited via participants reading aloud prepared lists of Mandarin and/or English words. Statistical testing indicates that as a group beginner learners produced significantly different mean VOT than native Mandarin speakers for all six stops. In contrast, the advanced learner group's mean VOT only significantly differed with native speakers for /t/, indicating native-like VOT for the remaining five stops. Individual analysis of VOT data for L2 Mandarin long-lag stops /ph, th, kh/ showed that advanced (7 of 15) and even some beginner (3 of 15) participants were capable of producing native-like VOT for the whole set of long-lag stops and also that a number of participants were able to produce native-like VOT for some but not all of the long-lag stops. Logistic regression analysis examining the effect and influence of L2 experience and demographic related variables indicates only gender and Mandarin-speaking church missionary service to have a significant effect on native-like VOT probability with females and returned missionaries significantly more likely to achieve native-like VOT. Analysis of learner participants' L1 English VOT showed that for all three of the English long-lag stops (/p, t, k/), advanced learners of Mandarin produced significantly longer VOT than monolingual English speakers, indicating L1 phonetic drift in the form of assimilation towards the longer length of Mandarin long-lag stops. Significant difference was only found between beginner learner English VOT and monolingual VOT for /p/, suggesting instances of significant L1 drift increase when more L2 experience has been gained.

Yes / To develop guidance for clinicians about essential elements that can support clinical decision-making in the diagnostic workup of young onset dementia. Methods/design: Three iterations of a modified e-Delphi consensus survey comprising 23 international expert clinicians specialising in diagnosis of young onset dementia. Outcome measures: A priori consensus was pre-defined as 80% of experts ranking statements in the upper threshold on a seven-point Likert scale that ranged from “not important at all” to “absolutely essential” to diagnosis. Results: 80% consensus was reached on 48 statements that were rated as “absolutely essential” or “very important” to a comprehensive assessment of dementia in a younger adult. In order to inform a subsequent audit of clinical records in which compliance with these statements was assessed, the statements were divided into a Minimum Standard, (consisting of the 15 statements voted by all experts as being “absolutely essential” or “very important”) and a Gold Standard where 48 statements were voted by 80% of the experts as being “absolutely essential” or “very important”. The experts’ response rate across the three rounds was 91.3%. Conclusion: A Minimum Standard and Gold Standard have been created for the diagnostic workup of young onset dementia. The standards provide a clinically useful tool for decision-making, particularly for generalists and those with less experience in the field. The standards will be used to inform a UK case note audit of recently diagnosed patients with young onset dementia. / This work was supported by the Alzheimer's Society grant number 278 AS-PG-15b-034.

Submitted by Cristiane Chim (cristiane.chim@ucpel.edu.br) on 2018-07-16T12:23:03Z No. of bitstreams: 1 Camila Motta Avila.pdf: 5908666 bytes, checksum: fec1aaf83edeb30b980911d427091061 (MD5) / Made available in DSpace on 2018-07-16T12:23:03Z (GMT). No. of bitstreams: 1 Camila Motta Avila.pdf: 5908666 bytes, checksum: fec1aaf83edeb30b980911d427091061 (MD5) Previous issue date: 2017-12-21 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES# / #2075167498588264571# / #600 / This Master’s Dissertation had as its main goal analyzing and formalizing how Brazilian learners of English language (L2) and Americans identify and discriminate the voicing patterns for plosive consonants under artificial manipulation in English monossilabic words. Americans normally follow the acoustic cue Voice Onset Time (VOT) to differentiate voiced plosives from voiceless ones. The VOT is measured in milisseconds and can be classified into three different categories (LISKER & ABRAMSON, 1964): negative VOT (for /b/, /d/ and /g/ in Portuguese); short-lag VOT (for /p/, /t/, /k/ in Portuguese and /b/, /d/, /g/ in English) and long-lag or positive VOT (for [ph], [th], [kh] in English). Previous studies (ALVES, BARATZ e MOTTA, 2012; SCHWARTZHAUPT, ALVES &FONTES, 2015; ALVES & MOTTA, 2014; MOTTA, 2014; ALVES & ZIMMER, 2015) demonstrated that the manipulation of VOT can result into different types of perceptual behaviour, depending on the group analyzed: Americans tend to follow this cue to attribute voicing patterns to consonants, while Brazilians tend to follow the voicing patters stablished for their L1. In order to analyze the perception in L2, this Dissertation was based on Speech Learning Model (SLM) – (FLEGE, 1995) and Perceptual Assimilation Model – L2 (PAM-L2) – (BEST e TYLER, 2007) studies. To investigate how perception was processed in Americans, explanations in Kent and Read (2015), Gussenhoven and Jacobs (2004), Matzenauer (2015) and Boersma, Escudero and Hayes (2003) were found. The method consisted of two perceptual tests: (a) Identification Test, (b) Discrimination Test. Both tests were designed with artificially manipulated stimuli. The types (pee, pit, tick, tip, kit, kill) were CVC (where V was a high vowel /ɪ/ or /i/). Each one of them was multiply manipulated, generating five tokens from one original type. This manipulation was gradually performed, in 25% layers, aiming to achieve the zero artificial VOT pattern. The Identification Test was designed with 60 target words and 12 distractors, resulting in 72 tokens per participant. The Discrimination Test was designed with 36 target trials and 9 catch-trials, in a total of 45 trials per participant. To summarize, results show that Americans can be considered to be more perceptually sensitive to the multiple VOT manipulation than Brazilians, who normally tend to follow their L1 way of attributing voicing patterns to plosives, regardless their proficiency level in English (basic, intermediate or advanced). In addition, different phonetic tresholds were found in each analyzed group and in each place of articulation observed (bilabial, alveolar, velar). Finally, this study tries to offer a formalization for perceptual grammars in each group, based on Bi-directional Phonology OT Model (BiPhon). It is expected that this study, its detailed data description and theoretical observations can contribute to and makefurther academic studies possible. / Esta Dissertação de Mestrado teve como principal objetivo analisar e formalizar de que forma brasileiros aprendizes de inglês (L2) e americanos identificam e discriminam o vozeamento das consoantes plosivas iniciais da língua inglesa sob múltiplas manipulações em palavras monossilábicas. Na língua inglesa, para a diferenciação de vozeamento, tem-se como principal pista acústica a aspiração, que pode ser medida a partir dos valores de Voice Onset Time (VOT). O VOT é medido em milissegundos e pode ser classificado em 3 diferentes padrões (LISKER & ABRAMSON, 1964): VOT NEGATIVO (que se realiza foneticamente em português em /b/, /d/ e /g/); VOT ZERO, (que se realiza como /p/, /t/ e /k/ no português e /b/, /d/ e /g/ no inglês) e o VOT POSITIVO (encontrado em [ph], [th] e [kh] no inglês). Estudos anteriores (ALVES, BARATZ e MOTTA, 2012; SCHWARTZHAUPT, ALVES &FONTES, 2015; ALVES & MOTTA, 2014; MOTTA, 2014; ALVES & ZIMMER, 2015) demonstraram que a manipulação da pista acústica VOT resulta em comportamentos perceptuais diferenciados de acordo com a natureza do participante: americanos tendem a seguir a pista acústica em questão ao atribuir ou não vozeamento para as consoantes plosivas, ao passo que os brasileiros continuam a seguir os padrões de vozeamento previstos para a sua L1. Para dar conta da percepção em inglês como L2, este trabalho fundamentou-se, basicamente, nos modelos perceptuais Speech Learning Model (SLM) – (FLEGE, 1995) e Perceptual Assimilation Model – L2 (PAM-L2) – (BEST e TYLER, 2007). Para analisar a percepção dos participantes americanos, buscaram-se explicações em Kent e Read (2015), Gussenhoven e Jacobs (2004), Matzenauer (2015) e Boersma, Escudero e Hayes (2003). O método aplicado neste estudo consistiu em dois testes de percepção: (a) Teste de Identificação, (b) Teste de Discriminação. Ambos foram montados com estímulos de palavras monossilábicas da língua inglesa (CVC), sendo V /ɪ/ ou /i/. Cada type (pee, pit, tick, tip, kit, kill) passou por manipulação múltipla da pista acústica VOT, gerando 5 tokens cada um. Tal manipulação se deu de forma gradual em camadas de 25%, objetivando-se alcançar o padrão de VOT zero artificial. O design do Teste de Identificação contou com 60 palavras-alvo e 12 distratoras, somando um total de 72 tokens por participante. O design do Teste de Discriminação, que teve por objetivo contrastar diferentes camadas de VOT entre si, contou com 36 tríades do tipo AxB e 9 catch-trials, somando 45 tríades por participante. Sucintamente, os resultados apresentados demonstraram que os participantes americanos são mais sensíveis ao corte da pista acústica VOT do que os participantes brasileiros, independentemente do nível de proficiência em língua inglesa (básico, intermediário e avançado). Além disso, limiares fonéticos distintos foram encontrados em cada um dos grupos analisados e em cada ponto de articulação observado (bilabial, alveolar, velar). Finalmente, propôs-se uma formalização da percepção de ambos os grupos para cada consoante analisada baseando-se no Modelo de OT Bidirecional (BiPhon), proposto por Boersma (2009) e Boersma e Hamman (2011). Espera-se, com este estudo, que a descrição detalhada dos dados e a reflexão teórica possam contribuir à Academia e possibilitar estudos futuros.