no / The majority of studies have demonstrated a right hemisphere (RH) advantage for the perception of emotions. Other studies have found that the involvement of each hemisphere is valence specific, with the RH better at perceiving negative emotions and the LH better at perceiving positive emotions [Reuter-Lorenz, P., & Davidson, R.J. (1981) Differential contributions of the 2 cerebral hemispheres to the perception of happy and sad faces.Neuropsychologia, 19, 609¿613]. To account for valence laterality effects in emotion perception we propose an `expectancy¿ hypothesis which suggests that valence effects are obtained when the top-down expectancy to perceive an emotion outweighs the strength of bottom-up perceptual information enabling the discrimination of an emotion. A dichotic listening task was used to examine alternative explanations of valence effects in emotion perception. Emotional sentences (spoken in a happy or sad tone of voice), and morphed-happy and morphed-sad sentences (which blended a neutral version of the sentence with the pitch of the emotion sentence) were paired with neutral versions of each sentence and presented dichotically. A control condition was also used, consisting of two identical neutral sentences presented dichotically, with one channel arriving before the other by 7 ms. In support of the RH hypothesis there was a left ear advantage for the perception of sad and happy emotional sentences. However, morphed sentences showed no ear advantage, suggesting that the RH is specialised for the perception of genuine emotions and that a laterality effect may be a useful tool for the detection of fake emotion. Finally, for the control condition we obtained an interaction between the expected emotion and the effect of ear lead. Participants tended to select the ear that received the sentence first, when they expected a `sad¿ sentence, but not when they expected a `happy¿ sentence. The results are discussed in relation to the different theoretical explanations of valence laterality effects in emotion perception.

The current research project investigates the influence of gender, age, and social class on the use of intensifiers and extreme adjectives as instruments to intensify spoken language. Employing a corpus-based approach, the study has collected data from the Spoken BNC2014 regarding the use of the common intensifiers so, very, real, and really modifying an adjective, as well as the use of synonymous extreme adjectives. Frequent intensifier-adjective pairs were retrieved from the corpus and thereafter translated into synonymous extreme adjectives using an online thesaurus. Following the data collection process, comparative analyses of the collected data were conducted. The study presents results that are in some regards coherent with previous research as well as most of the study’s hypotheses. Although the results suggest some general differences in use depending on the speaker’s gender, age, and social class, they are not as distinct as expected. Of all the sociolinguistic variables, the language use of the different social classes proved least predictable. While correlations between an overuse of intensifiers/extreme adjectives and an underuse of extreme adjectives/intensifiers have been observed in the data, this opposite relationship is not present in all social constellations.

The objective of this thesis is to investigate the flow conditions that lead to coarse grain entrainment at near incipient motion conditions. Herein, a new conceptual approach is proposed, which in addition to the magnitude of hydrodynamic force or flow power, takes into account the duration of the flow event. Two criteria for inception of grain entrainment, namely the critical impulse and critical energy concepts, are proposed and compared. These frameworks adopt a force or energy perspective, considering the momentum or energy transfer from each flow event to the particle respectively, to describe the phenomenon. A series of conducted mobile particle experiments, are analyzed to examine the validity of the proposed approaches. First a set of bench-top experiments incorporates an electromagnet which applies pulses of known magnitude and duration to a steel spherical particle in a controlled fashion, so as to identify the critical level for entrainment. The utility of the above criteria is also demonstrated for the case of entrainment by the action of turbulent flow, via analysis of a series of flume experiments, where both the history of hydrodynamic forces exerted on the particle as well as its response are recorded simultaneously. Statistical modeling of the distribution of impulses, as well as conditional excess impulses, is performed using distributions from Extreme Value Theory to effectively model the episodic nature of the occurrence of these events. For the examined uniform and low mobility flow conditions, a power law relationship is proposed for describing the magnitude and frequency of occurrence of the impulse events. The Weibull and exponential distributions provide a good fit for the time between particle entrainments. In addition to these statistical tools, a number of Adaptive Neuro-Fuzzy Inference Systems employing different input representations are used to learn the nonlinear dynamics of the system and perform statistical prediction. The performance of these models is assessed in terms of their broad validity, efficiency and forecast accuracy. Even though the impulse and energy criteria are deeply interrelated, the latter is shown to be advantageous with regard to its performance, applicability and extension ability. The effect of single or multiple highly energetic events carried by certain coherent flow structures (mainly strong sweep events) with regard to the particle response is also investigated. / Ph. D.

<p dir="ltr">The technological drive of humanity to explore the cosmos, travel at hypersonic speeds, and pursue clean energy solutions requires ceramic scientists and engineers to constantly push materials to their functional, behavioral, and chemical extremes. Ultra-high temperature ceramics, and particularly transition metal carbides, are promising materials to meet the demands of extreme environment materials with their >4000 °C melting temperature and impressive thermomechanical behaviors in extreme conditions. The advent of the 2D version of these transition metal carbides, known as MXenes, added a new direction to design transition metal carbides for energy, catalysis, flexible electronics, and other applications. Toward extreme conditions, although MXenes remain yet unexplored, we believe that the ~1 nm flakes of MXenes gives ceramics scientists and engineers the ability to truly engineer transition metal carbides layer-by-layer at the nanoscale to endure the extreme conditions required by future harsh environment technology. Although MXenes have this inherent promise, fundamental study of their behavior in high-temperature environments is necessary to understand how their chemistry and 2D nature affects the high-temperature stability and phase behavior of MXenes toward application in extreme environments.</p><p dir="ltr">In this dissertation, we investigate the high-temperature phase behavior of 2D MXenes in high temperature inert environments to understand the stability and phase transition behavior of MXenes. In this work, we demonstrate that 1) MXenes’ transition at high-temperatures is to highly textured transition metal carbides is due to the homoepitaxial growth of these phases onto ~1-nm-thick MXenes’ highly exposed basal plane, 2) the MXene to MXene interface plays a major role in the phase behavior of MXenes, particularly toward building layered transition metal carbides using MXenes as ~1-nm-thick building blocks, and 3) Defects are the primary site at which atomic migration begins during phase transition of MXenes into these highly textured transition metal carbides, and these defects can be engineered for different phase stability of MXenes. To do so, we investigate the phase behavior of Ti₃C₂T_<em>x</em>, Ta₄C₃T_<em>x</em>, Mo₂TiC₂T_<em>x</em>, and other MXenes using a combination of <i>in situ</i> x-ray diffraction and scanning transmission electron microscopy and other <i>ex situ</i> methods, such as secondary ion mass spectrometry and x-ray photoelectron spectroscopy, with other methods. By investigating the fundamentals of the high-temperature phase behavior of MXenes, we hope to establish the basic principles behind use of MXenes as the ideal material for application in future extreme environments.</p>

京都大学 / 新制・課程博士 / 博士(工学) / 甲第25249号 / 工博第5208号 / 新制||工||1994(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 立川 康人, 教授 田中 賢治, 教授 佐山 敬洋 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

The electrification of societies and the decarbonisation of electricity production are changing energy systems worldwide. A fast transition towards the replacement of fossil fuels by intermittent renewable energy sources is expected in the next decades to combat climate change. A significant share of the produced electricity is likely to be generated from offshore wind farms, due to the abundant wind resources in the offshore regions and the lack of available onshore sites. However, increased electricity dependence in combination with expanded offshore wind power generation introduce new vulnerabilities to the society. Specifically, the effects of high impact low probability (HILP) events are considered as potential threats to the power system, not least because of the increasing number of extreme weather events. Therefore, research on power grid vulnerability and power system resilience to HILP events are of significant interest. This thesis presents results of studies investigating power grid vulnerability from a topological perspective, and resilience to storm conditions of power systems with varying dependencies on offshore wind. To achieve this, methods based on complex network theory and AC power flow analysis have been developed, tested, and evaluated. Further, geospatial wind data from historical extreme storm events have been used to generate realistic power production profiles from hypothetical offshore wind farms. The results strengthen that complex network concepts can be used successfully in the context of power grid vulnerability analysis. Further, the results show that the resilience of power systems with large dependencies on offshore wind differ vastly depending on the grid properties and control strategies, which are further discussed in this thesis.

This study aims to investigate potential societal consequences of the ongoing western culture wars by looking at a crucial aspect of the concept, the usage of extreme elite rhetoric. Specifically, how does extreme elite rhetoric affect the likelihood of civil war? The theoretical argument is that extreme elite rhetoric increases the likelihood of civil war because of the negative impact it has on affective group polarization which, in turn, creates destructive group processes necessary for violence. In order to examine if this is the case, a small-N case comparison is conducted in which the cases of Ivory Coast and Zambia are compared. The findings indicate that the difference in political rhetoric, extreme rhetoric in Ivory Coast versus inclusive rhetoric in Zambia, was a contributing factor to the difference in outcome, civil war onset in Ivory Coast (2002) but not in Zambia. As shown, this appears to be because of the impact the different rhetoric had on affective group polarization; a sharp increase in Ivory Coast whereas it was largely mitigated in Zambia. Consequently, in line with the findings, the usage of extreme elite rhetoric, and thus culture wars may increase the likelihood of civil war.

Film has always been an integral part of the culture of surfing. In the early 1960's, a film by the name of The Endless Summer ushered in the wide acceptance of the medium of film by the culture. As the years progressed and the sport radically adopted new styles, attitudes and lifestyles, surfing films changed along with it. This thesis will show how the aesthetics of surfing films both are shaped by the culture from which they are found and how, in turn, they continually reshape the culture. By looking at the aesthetic theories of Hans-Georg Gadamer, Leo Tolstoy and Walter Benjamin, this thesis will academically survey the aesthetics of the films The Endless Summer, Momentum, and the works of filmmaker Jack Johnson and his studio The Moonshine Conspiracy. This study will provide insight into the significant aspect of , film in a culture so strongly defined by aesthetics, both from within and without.

Climate change impacts hydrology, nutrient cycling, agricultural conservation practices, and greenhouse gas (GHG) emissions. The Chesapeake Bay and its watershed are subject to the largest and most expensive Total Maximum Daily Load (TMDL) ever developed. It is unclear if the TMDL can be met given climate change and variability (e.g., extreme weather events). The objective of this dissertation is to quantify the impact of climate change and climate on water resources, nutrient cycling and export in agroecosystems, and agricultural conservation practices in the Chesapeake Bay watershed. This is accomplished by developing and employing a suite of modelling tools. GHG emissions from agroecosystems, particularly nitrous oxide (N2O), are an increasing concern. To quantify N2O emissions a routine was developed for the Soil and Water Assessment Tool (SWAT) model. The new routine predicts N2O and di-nitrogen (N2) emissions by coupling the C and N cycles with soil moisture, temperature, and pH in SWAT. The model uses reduction functions to predict total denitrification (N2 + N2O production) and partitions N2 from N2O using a ratio method. The SWAT nitrification routine was modified to predict N2O emissions using reduction functions. The new model was tested using GRACEnet data at University Park, Pennsylvania, and West Lafayette, Indiana. Results showed strong correlations between plot measurements of N2O flux and the model predictions for both test sites and suggest that N2O emissions are particularly sensitive to soil pH and soil N, and moderately sensitive to soil temperature/moisture and total soil C levels. The new GHG model was then used to analyze the impact of climate change and extreme weather conditions on the denitrification rate, N2O emissions, and nutrient cycling/export in the 7.4 km2 WE38 watershed in Pennsylvania. Climate change impacts hydrology and nutrient cycling by changing soil moisture, stoichiometric nutrient ratios, and soil temperature, potentially complicating mitigation measures. To quantify the impact of climate change we forced the new GHG model with downscaled and bias-corrected regional climate model output and derived climate anomalies to assess their impact on hydrology, nitrate (NO3-), phosphorus (P), and sediment export, and on emissions of N2O and N2. Model-average (± standard deviation) results indicate that climate change, through an increase in precipitation, will result in moderate increases in winter/spring flow (2.7±10.6 %) and NO3- export (3.0±7.3 %), substantial increases in dissolved P (DP, 8.8±19.8 %), total P (TP, 4.5±11.7 %), and sediment (17.9±14.2 %) export, and greater N2O (63.3±50.8 %) and N2 (17.6±20.7 %) emissions. Conversely, decreases in summer flow (-12.4±26.7 %) and the export of P (-11.4±27.4 %), TP (-7.9±24.5 %), sediment (-4.1±21.4 %), and NO3- (-12.2±31.4 %) are driven by greater evapotranspiration from increasing summer temperatures. Increases in N2O (20.1±29.3 %) and decreases in N2 (-13.0±14.6 %) are also predicted in the summer and driven by increases in soil moisture and temperature. In an effort to assess the impact of climate change at a regional level, the model was then scaled-up to the entire Susquehanna River basin and was used to evaluate if agricultural best management practices (BMPs) can offset the impact of climate change. Agricultural BMPs are increasingly and widely employed to reduce diffuse nutrient pollution. Climate change can complicate the development, implementation, and efficiency of BMPs by altering hydrology, nutrient cycling, and erosion. We select and evaluate four common BMPs (buffer strips, strip crop, no-till, and tile drainage) to test their response to climate change. We force the calibrated model with six downscaled global climate models (GCMs) for a historic period (1990-2014) and two future scenario periods (2041-2065) and (2075-2099) and quantify the impact of climate change on hydrology, NO3-, total N (TN), DP, TP, and sediment export with and without BMPs. We also tested prioritizing BMP installation on the 30% of agricultural lands that generate the most runoff (e.g., critical source areas-CSAs). Compared against the historical baseline and excluding the impact of BMPs, the ensemble model mean (± standard deviation?) predictions indicate that climate change results in annual increases in flow (4.5±7.3%), surface runoff (3.5±6.1%), sediment export (28.5±18.2%) and TN (9.5±5.1%), but decreases in NO3- (12±12.8%), DP (14±11.5%), and TP (2.5±7.4%) export. When agricultural BMPs are simulated most do not appreciably change the overall water balance; however, tile drainage and strip crop decrease surface runoff generation and the export of sediment, DP, and TP, while buffer strips reduced N export substantially. Installing BMPs on critical source areas (CSAs) results in nearly the same level of performance for most practices and most pollutants. These results suggest that climate change will influence the performance of BMPs and that targeting BMPs to CSAs can provide nearly the same level of water quality impact as more widespread adoption. Finally, recognizing that all of these model applications have considerable uncertainty associated with their predictions, we develop and employ a Bayesian multi-model ensemble to evaluate structural model prediction uncertainty. The reliability of watershed models in a management context depends largely on associated uncertainties. Our Objective is to quantify structural uncertainty for predictions of flow, sediment, TN, and TP predictions using three models: the SWAT-Variable Source Area model (SWAT-VSA), the standard SWAT model (SWAT-ST), and the Chesapeake Bay watershed model (CBP-model). We initialize each of the models using weather, soil, and land use data and analyze outputs of flow, sediment, TN, and TP for the Susquehanna River basin at the Conowingo Dam in Conowingo, Maryland. Using these three models we fit Bayesian Generalized Non - Linear Multilevel Models (BGMM) for flow, sediment, TN, and TP and obtain estimated outputs with 95% confidence intervals. We compare the BGMM results against the individual model results and straight model averaging (SMA) results using a split time period analysis (training period and testing period) to assess the BGMM in a predictive fashion. The BGMM provided better predictions of flow, sediment, TN, and TP compared to individual models and the SMA during the training period. However, during the testing period the BGMM was not always the best predictor; in fact, there was no clear best model during the testing period. Perhaps more importantly, the BGMM provides estimates of prediction uncertainty, which can enhance decision making and improve watershed management by providing a risk-based assessment of outcomes. / Ph. D. / Climate change impacts hydrology, nutrient cycling, agricultural conservation practices, and greenhouse gas (GHG) emissions. The Chesapeake Bay and its watershed are subject to the largest and most expensive Total Maximum Daily Load (TMDL) ever developed. It is unclear if the TMDL can be met given climate change and variability. The objective of this dissertation is to quantify the impact of climate change and climate on water resources, nutrient cycling and export in agroecosystems, and agricultural conservation practices in the Chesapeake Bay watershed. This is accomplished by developing and employing different modeling tools. First, GHG emissions model was developed to quantify nitrous oxide (N₂O) emissions from agroecosystems, which are an increasing concern. The new model was then tested using observed N₂O emissions data at University Park, Pennsylvania, and West Lafayette, Indiana. Results showed strong correlations between plot measurements of N₂O flux and the model predictions for both test sites. Second, the new GHG model was then used to analyze the impact of climate change and extreme weather conditions on the N₂O emissions, and nutrient cycling/export in small and regional watershed scale. To quantify the impact of climate change we forced the new GHG model with downscaled and bias-corrected regional climate model date to assess their impact on hydrology, nitrate (NO₃-), phosphorus (P), and sediment export, and on emissions of N₂O and N₂. Finally, recognizing that all of these model applications have considerable uncertainty associated with their predictions, we developed and employed a Bayesian multi-model ensemble to evaluate structural model prediction uncertainty.

The intensity and frequency of precipitation events have increased because of global warming and its direct impact on the hydrological cycle. This poses a significant challenge for various locations around the globe where in recent years more unpredicted flooding has been observed. The utilization of hydrological models for accurate prediction of urban floods under heavy rainfall events is crucial to deal with such global problems. The purpose of this study is to develop a model based on the Spatial Distributed Travel Time (SDTT) approach that estimates the response of watersheds to a short and intense rainfall event in urban settings. The model is developed in Python and uses the ArcPy package, which allows access to all the geoprocessing tools available at ArcGIS, along with the Numpy package that supports matrices which makes mathematical calculation efficient.   One of the important factors affecting the response of watersheds is the contribution of upstream flow. The current study used Dynamic Upstream Contribution (DUC) to estimate the unit hydrograph and consider the effect of upstream runoff contributing to travel time equations using physical characteristics and the dynamic of rainfall events. The SDTT model was validated with a fully distributed model, MIKE 21, and showed that when the infiltration module estimates the total runoff volume accurately, the unit hydrograph of the DUC method can predict the peak almost as accurately as MIKE 21. Before validation, the excess rainfall estimated in the SDTT model is multiplied by a constant coefficient to align the total water volume of the model with that of the MIKE 21 model.  The peak flow is the most important component of a discharge hydrograph since its accurate prediction helps in assessing the severity of flooding and the capacity of drainage systems to handle the excess water. Another component of a discharge hydrograph is time to peak which the SDTT model predicts with a delay compared to MIKE 21. The sensitivity analysis showed the simplification regarding the dynamic of rainfall intensity used in travel time equations contributes to this delayed peak. The other simplification that might impact the watershed response is the approach the model used to handle depression volume which is too general. A conceptual method proposed in this report can be used in future studies to improve this part of the model by capturing the spatial distribution of depression locations as well as the temporal dynamics of charging the depressions.   After the model was validated in the first study area, it was implemented in another study area to evaluate the effect of urban development on the hydrological response of urban catchments to a short and intense rainfall event. This scenario-based analysis showed that by further development of the model, it can be used as a tool for the initial phase of hydrologic investigation of urban areas in response to heavy rainfall events. By conducting the screening phase of hydrological investigation and filtering the risky location, the SDTT model can be used as a complementary model for more advanced fully distributed models that are more computationally extensive.   The recorded simulation time demonstrated that the SDTT model is quick when it comes to small-sized watersheds, but it is less time-efficient for large catchments. An approach proposed in this report can be utilized to optimize the model's processing time for larger catchments. By making the model time efficient and addressing the issues mentioned in the report, the developed SDTT model can facilitate the hydrological investigation by reducing the initial data gathering burden and simulation time, and making the assessments of urban watersheds more efficient can facilitate informed decision-making in urban flood risk management. / Till följd av den globala uppvärmningen har intensiteten och frekvensen av nederbördshändelser ökat, en direkt inverkan på den hydrologiska cykeln som utgör en betydande utmaning för olika platser runt om i världen där oförutsedda översvämningar observerats under de senaste åren. Användningen av hydrologiska modeller för att med noggrannhet förutseurbana översvämningar under kraftiga nederbördshändelser är avgörande för att hantera detta globala problem. Syftet med denna studie är att utveckla en modell baserad på Spatial Distributed Travel Time (SDTT) metodiken. SDTT-metodiken beskriver responsen från ett avrinningsområde för en kort och intensiv nederbördshändelse i urban miljö. Modellen är utvecklad i Python och inkluderar ArcPy-paketet som ger tillgång till alla geoprocesseringsverktyg som finns i ArcGIS tillsammans med Numpy-paketet som stödjer matriser som effektiviserar matematiska beräkningar.  En av de avgörande faktorerna som visade sig påverka reaktionen från ett avrinningsområde var flödet från uppströmsområdet. Den aktuella studien använde Dynamic Upstream Contribution (DUC) för att uppskatta enhetshydrografen med hänsyn till effekten avrinningen uppströms har på avrinningshastigheten med hjälp av fysiska egenskaper och nederbördsdynamik. SDTT-modellen validerades med en fullt distribuerad modell, MIKE 21, och visade att när infiltrationsmodulen uppskattar den totala avrinningsvolymen exakt, kan enhetshydrografen för DUC-metoden förutsäga toppflödet exakt. Innan validering multipliceras överskottsnederbörden uppskattad i SDTT-modellen med en konstant koefficient för att justera modellens totala vattenvolym med den i MIKE 21-modellen. Toppflödet är den viktigaste komponenten i en flödeshydrograf eftersom dess noggranna förutsägelse hjälper till att bedöma allvarsgraden av översvämningar samt dräneringssystemens kapacitet att hantera överskottsvatten. En annan komponent i en flödeshydrograf är den tid det tar tills toppflödet uppstår, något som SDTT-modellen förutsäger med en fördröjning jämfört med MIKE 21. Känslighetsanalysen visade att förenklingen gällande dynamiken för nederbördsintensitet som används i ekvationerna för avrinningshastighet bidrar till denna fördröjda topp. Den andra förenklingen som kan påverka responsen från avrinningsområdet är metoden som modellen använde för att hantera volymen vatten som lagras i sänkor, som är förgenerell. En konceptuell metod föreslås i denna rapport och kan användas i framtida studier för att förbättra denna del av modellen genom att fånga den rumsliga fördelningen av sänkor samt tidsaspekten i att fylla upp sänkvolymerna.   Efter att modellen validerats i det första studieområdet, implementerades den i ett annat studieområde för att utvärdera kopplingen mellan stadsutveckling och hydrologisk respons i urbana avrinningsområden i kontexten av en kort och intensiv nederbördshändelse. Denna scenariobaserade analys visade att modellen efter vidareutveckling kan användas som ett verktyg för den inledande fasen av hydrologisk undersökning av stadsområden, i syfte att utreda möjliga konsekvenser av kraftiga nederbördshändelser. Genom att genomföra screeningfasen av hydrologisk undersökning och filtrera den mest riskfyllda platsen kan SDTT-modellen användas som en kompletterande modell för mer avancerade fullt distribuerade modeller som är mer beräkningsmässigt omfattande.   Den registrerade simuleringstiden visade att SDTT-modellen är snabb när det kommer till ett litet avrinningsområde, men modellen är mindre tidseffektiv för stora avrinningsområden. Ett tillvägagångssätt som föreslås i denna rapport kan användas för att optimera modellens handläggningstid för större avrinningsområden. Genom att göra modellen tidseffektiv och åtgärda frågorna som nämns i rapporten, kan den utvecklade SDTT-modellen underlätta den hydrologiska undersökningen genom att minska den inledande datainsamlingsbördan, minskasimuleringstiden, och dessutom göra utvärderingarna av urbana avrinningsområden mer effektiva. Slutligen kan modellens resultat användas för att underlätta informerat beslutsfattande kopplat till hantering av översvämningsrisker i städer.