The photosynthetic process has the unique ability to capture energy from sunlight and accumulate that energy in sugars and starch. This thesis deals with the light driven part of photosynthesis. The aim has been to investigate how the light-absorbing protein complexes Photosystem I (PS I) and Photosystem II (PS II), react upon illumination of light with lower energy (far-red light; 700-850 nm) than the absorption peak at respective primary donor, P700 and P680.  The results were unexpected. At 295 K, we showed that both PS I and PS II were able to perform photochemistry with light up to 130 nm above its respective primary donor absorption maxima. As such, it was found that the primary donors’ action spectra extended approximately 80 nm further out into the red-region of the spectrum than previously reported.  The ability to perform photochemistry with far-red light was conserved at cryogenic temperatures (< 77 K) in both photosystems. By performing EPR measurements on various photosystem preparations, under different illumination conditions the origin of the effect was localized to their respective reaction center. It is also likely that underlying mechanism is analogous for PS I and PS II, given the similarities in spatial coordination of the reaction center pigments. For PS II, the results obtained allowed us to suggest a model involving a previously unknown electron transfer pathway. This model is based upon the conclusion that the primary cation from primary charge separation induced by far-red light resides primarily on ChlD1 in P680. This is in contrast to the cation being located on PD1, as has been suggested as for visible light illumination. The property to drive photochemistry with far-red wavelengths implies a hither to unknown absorption band, probably originating from the pigments that compose P700 and P680. The results presented here might clarify how the pigments inside P680 are coupled and also how the complex charge separation processes within the first picoseconds that initiate photosynthetic reactions occur.

This project draws on aspects of research into the plight of women prostitutes working in Lal Batti areas of India. The project considers historical, contemporary and personal texts that form the basis of a creative synthesis. This synthesis is manifest in the design of five fabric-based artworks that seek to interpret issues of manipulation, entrapment, belonging, spirituality and demise. The project is located beyond the boundaries of fashion design. However, it involves an artistic fusion of garment construction, fabric and surface treatment. In doing this, the thesis seeks to give ‘voice’ to a political commentary that reaches beyond commercial uses of garments for display and protection.

This project draws on aspects of research into the plight of women prostitutes working in Lal Batti areas of India. The project considers historical, contemporary and personal texts that form the basis of a creative synthesis. This synthesis is manifest in the design of five fabric-based artworks that seek to interpret issues of manipulation, entrapment, belonging, spirituality and demise. The project is located beyond the boundaries of fashion design. However, it involves an artistic fusion of garment construction, fabric and surface treatment. In doing this, the thesis seeks to give ‘voice’ to a political commentary that reaches beyond commercial uses of garments for display and protection.

Att en destination utstrålar en stark och positiv image har blivit en viktig faktor för att attrahera turister. En negativ global image av en destination kan bidra till en minskad turism. I denna studie söks en förståelse för hur Amsterdams image påverkas av sex- och drogturismen i staden. Teorier som bemöter primära och sekundära turistattraktioner, sökandet efter nöjes/meningsfulla upplevelser och image segmentering har satts i relation med insamlat empiriskt material hämtat från två enkätundersökningar samt tre semi-strukturerade intervjuer. Studiens analys visar att sex- och drogturismen genererar både en positiv och negativ image för Amsterdam i koppling till vad som är moraliskt riktigt. Studien visar att sex- och drogimagen inte påverkar resenärers beslutprocess av att besöka staden.

This research explores the red light running phenomena and offer a better understanding of the factors associated with it. The red light running is a type of traffic violation that can lead to angle crash and the most common counter measure is installing a red light running cameras. Red light running cameras some time can reduce the rates of red light running but because of the increased worry of the public towards crossing the intersection it can cause an increase in rear end crashes. Also the public opinion of the red light running cameras is that they are a revenue generator for the local counties and not a concern of public safety. Further more, they consider this type of enforcement as violation of privacy. There was two ways to collect the data needed for the research. One way is through a tripod cameras setup temporarily placed at the intersection. This setup can collect individual vehicles caught in the change phase with specific information about their reactions and conditions. This required extensive manual analysis for the recorded videos plus data could not be collected during adverse weather conditions. The second way was using traffic monitoring cameras permanently located at the site to collect red light running information and the simultaneous traffic conditions. This system offered more extensive information since the cameras monitor the traffic 24/7 collecting data directly. On the other hand this system lacked the ability to identify the circumstances associated with individual red light running incidents. The research team finally decided to use the two methods to study the red light running phenomena aiming to combine the benefits of the two systems. During the research the team conducted an experiment to test a red light running countermeasure in the field and evaluate the public reaction and usage of this countermeasure. The marking was previously tested in a driving simulator and proved to be successful in helping the drivers make better stop/go decisions thus reducing red light running rates without increasing the rear-end crashes. The experiment was divided into three phases; before marking installation called "before", after marking installation called "after", and following a media campaign designed to inform the public about the use of the marking the third phase called "after media" The behavior study that aimed at analyzing the motorist reactions toward the signal change interval identified factors which contributed to red light running. There important factors were: distance from the stop bar, speed of traffic, leading or following in the traffic, vehicle type. It was found that a driver is more likely to run red light following another vehicle in the intersection. Also the speeding vehicles can clear the intersection faster thus got less involved in red light running violations. The proposed "Signal Ahead" marking was found to have a very good potential as a red light running counter measure. The red light running rates in the test intersection dropped from 53 RLR/hr/1000veh for the "before" phase, to 24 RLR/hr/1000veh for the "after media" phase. The marking after media analysis period found that the marking can help the driver make stop/go decision as the dilemma zone decreased by 50 ft between the "before" and the "after media" periods. Analysis of the traffic condition associated with the red light running it revealed that relation between the traffic conditions and the red light running is non-linear, with some interactions between factors. The most important factors included in the model were: traffic volume, average speed of traffic, the percentage of green time, the percentage of heavy vehicles, the interaction between traffic volume and percentage of heavy vehicles. The most interesting finding was the interaction between the volume and the percent of heavy vehicles. As the volume increased the effect of the heavy vehicles reversed from reducing the red light running to increasing the red light. This finding may be attributed to the sight blocking that happens when a driver of a passenger car follows a larger heavy vehicle, and can be also explained by the potential frustration experienced by the motorist resulting from driving behind a bigger vehicle.

京都大学 / 新制・課程博士 / 博士(生命科学) / 甲第24982号 / 生博第511号 / 新制||生||68(附属図書館) / 京都大学大学院生命科学研究科統合生命科学専攻 / (主査)教授 河内 孝之, 教授 荒木 崇, 教授 中野 雄司 / 学位規則第4条第1項該当 / Doctor of Philosophy in Life Sciences / 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.

It is estimated that as many as 2.7 million crashes occur each year at intersections or are intersection related; resulting in over 8500 fatalities each year. These statistics have prompted government and corporate sponsored research into collision countermeasure systems that can enhance safety at intersections. Researchers are investigating technologies to provide an infrastructure-based or infrastructure-cooperative Intersection Decision Support (IDS) systems. Such systems would use pre-specified algorithms to identify drivers that have a high likelihood of violating the traffic signal and thus increase the risk of a collision. The system would subsequently warn the violating driver to stop though an in-vehicle or infrastructure-mounted interface. An IDS algorithm must be designed to provide adequate time for the driver to perceive, react, and stop the vehicle, while simultaneously avoiding a high false alarm rate. Prior to developing these algorithms, scientists must understand how drivers respond to traffic signals. Little research has focused on the influence of driver state on red-light running behavior or methods for distinguishing red light violators from non-violators. The objective of the present study was to define trends associated with intersection crossings under different driver states and to explore the point detection method of predicting red light running upstream of the intersection. This was accomplished through a test-track mixed-factor experiment with 28 participants. Each participant experienced a baseline (complete a full stop at the red light), distracted (misses signal phase change due to inattention), and willful (driver knowingly makes a late crossing in an attempt to 'beat the light') driver state conditions. To provide the opportunity for red-light running behavior from participants, the amber change interval began at five different distances from the intersection. These distances were located near and within the dilemma zone, a region in which drivers have a difficult time deciding whether to go or to stop. Data collected from in-vehicle sensors was statistically analyzed to determine significant effects between driver states, and to investigate point detection algorithms. / Master of Science

No description available.

Crashes categorized as running red light or left turning are most likely to occur at signalized intersections and resulted in substantial severe injuries and property damages. This dissertation mainly focused on these two types of vehicle crashes and the research methodology involved several perspectives. To examine the overall characteristics of red-light running and left-turning crashes, firstly, this study applied 1999-2001 Florida traffic crash data to investigate the accident propensity of three aspects of risk factors related to traffic environments, driver characteristics, and vehicle types. A quasi-induced exposure concept and statistical techniques including classification tree model and multiple logistic regression were used to perform this analysis. Secondly, the UCF driving simulator was applied to test the effect of a proposed new pavement marking countermeasure which purpose is to reduce the red-light running rate at signalized intersections. The simulation experiment results showed that the total red-light running rate with marking is significantly lower than that without marking. Moreover, deceleration rate of stopping drivers with marking for the higher speed limit are significantly less than those without marking. These findings are encouraging and suggesting that the pavement marking may result in safety enhancement as far as right-angle and rear-end traffic crashes at signalized intersections. Thirdly, geometric models to compute sight distances of unprotected left-turns were developed for different signalized intersection configurations including a straight approach leading to a straight one, a straight approach leading to a curved one, and a curved approach leading to a curved one. The models and related analyses can be used to layout intersection design or evaluate the sight distance problem of an existing intersection configuration to ensure safe left-turn maneuvers by drivers.