Airway remodeling in asthma is the result of increased expression of connective tissue proteins, airway smooth muscle cell (ASMC) hyperplasia and hypertrophy. TGF-beta1 has been found to increase ASMC proliferation. The activation of mitogen-activated protein kinases (MAPKs), p38, ERK, and JNK, is critical to the signal transduction associated with cell proliferation. In the present study, we determined the role of phosphorylated MAPKs in TGF-beta1 induced ASMC proliferation.

Confluent and growth-arrested bovine ASMCs were treated with TGF-beta1. Proliferation was measured by [3H]-thymidine incorporation and cell counting. Expressions of phosphorylated p38, ERK1/2, and JNK were determined by Western analysis.

In a concentration-dependent manner, TGF-beta1 increased [3H]-thymidine incorporation and cell number of ASMCs. TGF-beta1 also enhanced serum-induced ASMC proliferation. Although ASMCs cultured with TGF-beta1 had a significant increase in phosphorylated p38, ERK1/2, and JNK, the maximal phosphorylation of each MAPK had a varied onset after incubation with TGF-beta1. TGF-beta1 induced DNA synthesis was inhibited by SB 203580 or PD 98059, selective inhibitors of p38 and MAP kinase kinase (MEK), respectively. Antibodies against EGF, FGF-2, IGF-I, and PDGF did not inhibit the TGF-beta1 induced DNA synthesis.

Our data indicate that ASMCs proliferate in response to TGF-beta1, which is mediated by phosphorylation of p38 and ERK1/2. These findings suggest that TGF-beta1 which is expressed in airways of asthmatics may contribute to irreversible airway remodeling by enhancing ASMC proliferation.

North American (NA) surface air temperatures in winter have been suggested to be associated with stratospheric variability, such as sudden stratospheric warmings (SSWs) or extreme stratospheric waves. However, the robustness and underlying mechanisms are not well understood. In particular, further studies are needed to better understand the dynamical processes underlying extreme stratospheric wave events. Yet, analysis is hindered by the limited sample sizes and the difficulty of identifying these wave events. In this dissertation, we show that extreme stratospheric wave activity is accompanied by subseasonal fluctuations between warm and cold spells over North America with reanalyses and a hierarchy of climate models. Our study identifies a robust precursor of strong stratospheric wave activity for NA cold extremes on subseasonal timescales. Our findings shed light on the dynamical processes underlying extreme stratospheric wave variability, highlighting the role of vertical wave structure in stratosphere-troposphere coupling.First, we demonstrate that the vertical coupling of extreme stratospheric wave activity is distinct from the well-known anomalous polar vortex events. We measure the stratospheric wave activity using empirical orthogonal function (EOF) analysis of 10 hPa geopotential height. In contrast to the increased persistence of weather regimes following SSWs, we show that extreme stratospheric wave events feature weather transitions between warm and cold spells over North America in reanalyses and climate models with various configurations. Particularly, strong stratospheric wave events are followed by an increased risk of cold extremes over North America 5–25 days later. The NA coldness is more robust following strong stratospheric wave activity than a weak polar vortex. We further examine the causality between stratospheric wave activity and NA cold extremes with idealized nudging experiments in a climate model with a well-resolved stratosphere. The stratosphere in the nudging run is fully relaxed to its counterpart in a free-running control simulation. By comparing the strong wave events between the two runs, we attribute the observed NA cold anomalies to the strong stratospheric wave activity. Moreover, vertical wave coupling is found to be key to the temperature transition during strong wave events. Further examinations of Coupled Model Intercomparison Project Phase 6 (CMIP6) reveal large uncertainty in the wave event evolution across individual models. It is found that models with a degraded representation of stratospheric wave structure also show biases in the troposphere during strong wave events. In order to investigate the role of the Quasi-biennial Oscillation (QBO) in the linkage between extreme stratospheric wave activity and NA temperature, we compare strong wave events during the westerly phase (wQBO) with those during the easterly phase (eQBO). We show that, in contrast to strong stratospheric wave events under wQBO, strong wave events under eQBO do not change the cold risk over North America nor alter the vertical wave structure in the observation. We further examine this QBO dependence in QBO-resolving CMIP6 models, finding that the strong wave events in models are largely insensitive to QBO phases, a possible bias in numerical models.

In this study, we investigate the uncertainties mainly in the trends of frequency and shifts of ARs on the choice of AR detection algorithm and reanalysis data, and also analyze the causes of trends at various temporal and spatial scales using two ensembles from Community Earth System Model (CESM) simulations and decomposition covering the period of 1980-2016. Meteorological reanalyses show all-seasonal poleward shifts over the Pacific, in contrast to statistically insignificant equatorward shifts during MAM and SON over the Atlantic and Indian Ocean sectors throughout decades. The spatial patterns of intensification and shifts of ARs are largely driven by the changes in atmospheric circulation while anthropogenic forcing enhances the increase in moisture-driven AR frequency with nearly uniform warming over the Southern Ocean. Sea surface temperature (SST) variability characterized by the negative phase of the Interdecadal Pacific Oscillation (IPO) could generate dynamically-driven patterns of ARs to compensate for the poleward shift driven by thermodynamics.

Airway remodeling in asthma is the result of increased expression of connective tissue proteins, airway smooth muscle cell (ASMC) hyperplasia and hypertrophy. TGF-beta1 has been found to increase ASMC proliferation. The activation of mitogen-activated protein kinases (MAPKs), p38, ERK, and JNK, is critical to the signal transduction associated with cell proliferation. In the present study, we determined the role of phosphorylated MAPKs in TGF-beta1 induced ASMC proliferation.

Confluent and growth-arrested bovine ASMCs were treated with TGF-beta1. Proliferation was measured by [3H]-thymidine incorporation and cell counting. Expressions of phosphorylated p38, ERK1/2, and JNK were determined by Western analysis.

In a concentration-dependent manner, TGF-beta1 increased [3H]-thymidine incorporation and cell number of ASMCs. TGF-beta1 also enhanced serum-induced ASMC proliferation. Although ASMCs cultured with TGF-beta1 had a significant increase in phosphorylated p38, ERK1/2, and JNK, the maximal phosphorylation of each MAPK had a varied onset after incubation with TGF-beta1. TGF-beta1 induced DNA synthesis was inhibited by SB 203580 or PD 98059, selective inhibitors of p38 and MAP kinase kinase (MEK), respectively. Antibodies against EGF, FGF-2, IGF-I, and PDGF did not inhibit the TGF-beta1 induced DNA synthesis.

Our data indicate that ASMCs proliferate in response to TGF-beta1, which is mediated by phosphorylation of p38 and ERK1/2. These findings suggest that TGF-beta1 which is expressed in airways of asthmatics may contribute to irreversible airway remodeling by enhancing ASMC proliferation.

Atmospheric rivers (ARs) are filaments of enhanced water vapor transport in the atmosphere. Globally, ARs play a key role in the meridional moisture transport. Regionally,ARs can either serve as freshwater suppliers or culprits behind many of the weather hazards. ARs and their impacts have been studied extensively. However, what controls the variability of ARs on different time scales remains largely unknown. In particular, further studies are especially needed to better understand the relative role of circulation (dynamic) variability versus moisture (thermodynamic) variability, internal variability versus sea surface temperature (SST)/ sea ice variability and anthropogenic forcing versus internal variability originated from SST/sea ice variability in controlling the variability of ARs and their associated precipitation on different time scales. In addition, reanalyses have long been used as proxies of observations in AR studies. Yet, the representation of ARs and their associated precipitation in reanalyses remain unknown. Although satellite observations have also been used to study ARs, previous satellite-based AR studies used only the moisture component (integrated water vapor or IWV) to detect ARs. While ARs have been defined as filaments of enhanced moisture transport in the atmosphere, detecting ARs with only the moisture field would inevitably run the risk of detecting those filamentary features with high moisture content, but relatively weak transport component. In this dissertation, we will address the research gaps above from five different angles. First, we investigate the relative role of SST/sea ice versus internal variability in driving the interannual variability of winter AR activities over the North Hemisphere. We show that, while both SST/sea ice and internal variability play roles in driving the interannual AR variability, their roles differ across ocean basins. Over the North Pacific, SST/sea ice variability exerts substantially stronger control on the AR variability compared to interval variability. However, both SST/sea ice and internal variability play comparable roles in modulating the AR variability over the North Atlantic. Second, on longer time scale, we discover that ARs over the Southern Hemisphere have been shifting poleward in the past four decades. Using a simple scaling method, we find that this poleward shift in the ARs is mostly driven by the poleward shift of the westerly jet (dynamic) while the contribution from the changes in the moisture field is relatively minor. Using two ensembles from the Community Earth System Model (CESM), one with fully coupled oceans and another one driven by observed SST/sea ice, we show that anthropogenic forcing is mainly responsible for the observed poleward shift. However, the negative phase of Interdecadal Pacific Oscillation (IPO) in recent decades also further drives the poleward shift in ARs. Third, ARs are expected to change under a warmer climate. However, the AR response to warming is determined by numerous factors. Two of the most prominent factors are the warming of the tropical upper troposphere, which can drive the poleward shift of the westerly jet, and the amplified warming of the polar regions, which can drive the equatorward shift of the westerly jet. Using nine models participated in the Polar Amplification Model Intercomparison Project (PAMIP), we investigate how Arctic Amplification and its associated sea ice loss would affect the boreal winter AR activities over the Northern Hemisphere. We find that, in response to Arctic sea ice loss, ARs extend northeastward over North Pacific and shift equatorward over North Atlantic. We further demonstrate that these response patterns are mostly determined by the responses in the circulation. Fourth, using a moisture budget approach, the relative contribution of dynamic change versus thermodynamic change to the intensification of extreme precipitation along the North American West Coast (predominantly driven by ARs) is also quantified. We show the intensification of the extreme precipitation along the North American West Coast is mostly driven by the increase in moisture while the contribution from the dynamic change is minor. Lastly, we develop a novel method to detect ARs in satellite observations using both IWV and wind information based on the geostrophic winds. Using this method, we create satellite-based AR statistics and use these statistics to evaluate the performance of seven commonly used reanalyses in representing ARs and their associated precipitation. We show that both satellite observation and reanalyses show high agreement with each other in representing the AR frequency distribution. In terms of AR precipitation, ARs in reanalyses tend to precipitate too lightly and too often. Our studies shed light on the mechanisms driving the variability of ARs across different time scales. These findings have important implications. First, given the more important role SST/sea ice variability in controlling the AR interannual variability, ARs in the North Pacific are likely more predictable than those over the North Atlantic. Better SST forecast can thus likely lead to better AR forecast along the North American West Coast. Second, on the interdecadal time scale, internal variability related to ocean processes still plays an important role in modulating AR variability. Internal variability should thus be taken into consideration when studying future AR response under warming. Third, our results indicate that the thermodynamic aspect of the AR and AR precipitation response is quite robust. We thus need to constrain the response in circulation to reduce the AR response uncertainty. Lastly, the finding that ARs in reanalyses tend to precipitate too often and too lightly directly questions the use of reanalysis-based precipitation in AR studies.

The voice source contains important lexical and non-lexical information. The non-lexical information can convey, for example, prosodic events, emotional status, as well as cues pertaining to the uniqueness of the speaker's voice. A better understanding, and eventually a better model of the voice source, would benefit various speech applications, such as speech recognition, speech synthesis, speaker identification, age/gender classification, as well as clinical assessments.

This dissertation has three main goals. The first is to better understand the voice source through analyzing images of the vocal folds using laryngeal high-speed videoendoscopy (HSV) recordings. A new automatic method is proposed to compactly summarize the overall spatial synchronization pattern of vocal fold vibration for the entire laryngeal area from HSV data. Additionally, a new measure is proposed to adequately capture perceptually-important variations in glottal area pulse shapes, which are extracted from HSV data.

The second goal is to study the acoustic consequence of a physiological vocal-fold vibration pattern---the glottal gap effect, and apply our findings to a gender classification task of children's voices. Voice source related measures are found to improve classification accuracy, especially for younger (10-15 year old) speakers.

The third goal is to propose new voice source models and evaluate them in different applications. In the first application, a new source model and a noise-robust automatic source estimation algorithm are proposed to estimate the voice source from speech signals. Results in both clean and noisy conditions show that the proposed model and algorithm are robust in accurately estimating the voice source signal. The second application is to use the proposed source model for vowel synthesis. Perceptual listening experiments show that the proposed model provides a better perceptual match to the target voice than do traditional models.

Indoor positioning systems provide location based service within buildings. Because the Global Positioning System is usually unavailable in indoor environment, other positioning technologies making use of optical, radio or even acoustic techniques are used for indoor positioning application. In this dissertation, an indoor visible light communication positioning system using a smartphone with rolling shutter camera is proposed. The LED transmits periodical signals with different frequencies high enough to avoid flickering as its optical tags. The camera exploits the rolling shutter effect to detect the fundamental frequency of optical signals. This kind of systems use smartphone camera as the receiver with no requirement of extra hardware. And at the same time, the optical communication link allows a date rate much higher than the frame rates of traditional optical camera communication. For the work of this research topic carried out so far, the roles of camera parameters determining rolling effect performance are studied and a technique to measure the camera readout time per column is presented. Factors limiting the detectable frequency range is explained based on the discussion of rolling shutter mechanism. Followed is the analysis of frequency detection reliability and resolution with Fourier spectrum analysis. After that, we present a background removal algorithm to recover the modulated information from background interference. In our algorithm, only one extra image is used and a one-time image alignment is required. Linear filter performs poorly in this case because the image with rolling shutter effect is a multiplication of modulated signal and the reflectance of the scene. Therefore we use background division rather than background subtraction to remove the background interference. The modulated illumination pattern is analyzed and the performance of background removal is evaluated by experiments. The experiment result shows that the interference is significantly compressed after background removal.

After the LED ID being detected successfully, an indoor positioning algorithm is proposed using multi-view imaging geometry with built-in smartphone inertial sensors. Due to the narrow field of view (FOV) of camera and the illumination placement of buildings, there is usually only one LED can be captured within camera FOV at the same time. In our proposed algorithm, only one detected LED with known position and one camera are required. And this system can still work when the VLC link is temporarily blocked or the LED temporarily moves out of the camera FOV. Another advantage of proposed algorithm is that no additional accessory will be needed except those sensors built inside the smartphone. In addition, the position is calculated at the receiver end without the knowledge of transmitter specifications, therefore there is no privacy concerns. The low-cost built in IMU sensor exhibits significant systematic errors, axes misalignment and noisy measurement. Even though a IMU calibration process can eliminate the systematic errors and axes misalignment, the noise remains even after calibration and could magnificently degrade the system performance. To maximize a posterior of obtained measurements, Kalman filter is applied for the sensor fusion by combining the system kinematic prediction and new measurement. Due to the nonlinearity of this system, an extended Kalman filter is used to correct the system model. A simulation is conducted to verify the proposed system. The simulation data of accelerometer and gyroscope are generated based on real world measurement from accelerometer and gyroscope. The simulation results demonstrate that the position error and orientation error are well bounded in the 3 sigma bounds and the maximum position error observed during the 2 minutes simulation is 0.1941 m over 50 averaged Monte Carlo trials.