Dicamba is often tank mixed with glyphosate to increase herbicidal efficacy but may contribute to off-target movement (OTM). In recent years, volatilization has become problematic for dicamba-containing herbicides, resulting in increased regulatory requirements necessitating the use of volatility-reducing agents (VRA) for application. Research was conducted in 2021 and 2022 using low tunnels in a field environment and humidomes in a greenhouse environment to further assess how glyphosate salts and VRAs affect dicamba volatility. Our data indicate that the inclusion of glyphosate to dicamba can increase dicamba volatility, depending on the glyphosate salt used. The inclusion of the evaluated VRAs will decrease dicamba volatility when applied to a tank mixture of dicamba plus potassium salt of glyphosate.

付記する学位プログラム名: 霊長類学・ワイルドライフサイエンス・リーディング大学院 / 京都大学 / 新制・課程博士 / 博士(理学) / 甲第24469号 / 理博第4968号 / 新制||理||1709(附属図書館) / 京都大学大学院理学研究科生物科学専攻 / (主査)教授 平田 聡, 教授 伊谷 原一, 教授 村山 美穂 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Control of large groups of robotic agents is driven by applications including military, aeronautics and astronautics, transportation network, and environmental monitoring. Cooperative control of networked multi-agent systems aims at driving the behavior of the group via feedback control inputs that encode the groups’ dynamics based on information sharing, with inter-agent communications that can be time varying and be spatially non-uniform. Notably, local interaction rules can induce coordinated behaviour, provided suitable network topologies. Distributed learning paradigms are often necessary for this class of systems to be able to operate autonomously and robustly, without the need of external units providing centralized information. Compared with model-based protocols that can be computationally prohibitive due to their mathematical complexity and requirements in terms of feedback information, we present an online model-free algorithm for some nonlinear tracking problems with unknown system dynamics. This method prescribes the actuation forces of agents to follow the time-varying trajectory of a moving target. The tracking problem is addressed by an online value iteration process which requires measurements collected along the trajectories. A set of simulations are conducted to illustrate that the presented algorithm is well functioning in various reference-tracking scenarios.

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Many environments in which an agent can use reinforcement learning techniques to learn profitable strategies are affected by other learning agents. These situations can be modeled as general-sum games. When playing repeated general-sum games with other learning agents, the goal of a self-interested learning agent is to maximize its own payoffs over time. Traditional reinforcement learning algorithms learn myopic strategies in these games. As a result, they learn strategies that produce undesirable results in many games. In this dissertation, we develop and analyze algorithms that learn non-myopic strategies when playing many important infinitely repeated general-sum games. We show that, in many of these games, these algorithms outperform existing multiagent learning algorithms. We derive performance guarantees for these algorithms (for certain learning parameters) and show that these guarantees become stronger and apply to larger classes of games as more information is observed and used by the agents. We establish these results through empirical studies and mathematical proofs.

Clinical ultrasound imaging techniques can be greatly improved by the use of ultrasound contrast agents (UCAs). While microbubbles (MBs) without shell are unstable and cannot be used for practical applications,a shell produced from biocompatible polyvinylalcohol (PVA) significantly improves chemical versatility and stability. The oscillation characteristics of a UCA are strongly dependent on concentration, applied pressure and viscoelastic parameters of the shell. Modifications in the shell as incorporation of antibodies or targeted molecules affect the bubble oscillation and resonance frequency of the MB suspension. In this presented work a tool for systematic characterization of UCAs is developed. Linear acoustic behaviour of PVA shelled MBs is examined. The acoustic driving pressure is kept below 100 kPa. The MB concentration is 1·10^{6} ml^{-1}. Attenuation and phase velocity profiles of ultrasound waves propagating through the UCA are measured using six narrow-band single crystal transducers that cover a frequency range between 1 and 15 MHz. The oscillation of a single bubble is modeled as a linear oscillator adapting HOFF’s model suitable for allshell thicknesses. The suspension is modeled through superposition of single bubbles. Knowing all parameters the resonance frequency of a MB suspension can be predicted. The model is fitted to experimental data to determine the viscoelastic shell parameters. The shell thickness is challenging to determine exactly and assumed to be either proportional to the outer shell radius or constant. Assuming a proportional shell thickness the calculated resulting shell parameters were shear modulus G_s = 14.5 MPa, shear viscosity η_s = 0.322 Pa·s and shell thickness d_s = 16 % of the outer radius. When instead assuming a constant shell thickness the determined parameters were in similar order of magnitude. Resonance frequency of the suspension was determined to 11.6 MHz. The developed tool can be used to characterize MBs with a modified shell independently of shell thickness and to predict resonance frequency of gas or air filled UCAs with known shell parameters.

Floods are one of the most costly natural hazards worldwide, affecting millions of people every year. Flood risk management is of global concern, and a deeper understanding of dynamic flood risk development is needed. Currently,vulnerability and exposure are often assumed to be constant in quantitative flood risk assessments, which does not reflect patterns observed in real life. In fact, flood protection measures on individual and community level can induce changes in both vulnerability and exposure, as well as alter river and floodplain hydraulics. The human-flood system is complex, incorporating two-way interactions between both subsystems. To build up these dynamics from the bottom up with a focus on the role of the individual, an agent-based model was combined with a hydraulic model. It was shown that this coupled model is capable of replicating levee and adaptation effects which are commonly knownto occur in the context of river floods and flood protection measures. Moreover,the new modeling approach can explicitly simulate the spatial distribution of flood risk which allowed for an analysis of conflicting interests in urban and rural areas. Here, model outcomes suggest that a shift of flood risk from high-value urban to lower-value rural areas can reduce system-wide flood losses. However, decreasing flood awareness in the city will push population growth rates, and discontent in rural areas might nally induce a shift of higher floodrisk back to the urban area. In the end, one low-probability high-intensity event might cause a disastrous outcome.

In today's advanced technology world, enterprises are in a constant state of competition. As the intensity of competition increases the need to continuously improve organizational performance has never been greater. Managers at all levels must be on a constant quest for finding ways to maximize their enterprises' strategic resources. Enterprises can develop sustained competitiveness only if their activities create value in unique ways. There should be an emphasis to transfer this competitiveness to the resources it has on hand and the resources it can develop to be used in this environment. The significance of human capital is even greater now, as the intangible value and the tacit knowledge of enterprises' resources should be strategically managed to achieve a greater level of continuous organizational success. This research effort seeks to provide managers with means for accurate decision making for their workforce management. A framework for modeling and managing human capital to achieve effective workforce planning strategies is built to assist enterprise in their long term strategic organizational goals.