It is shown that multigroup transport equations with nondiagonal cross section matrices arise when the modal approximation is applied to energy dependent transport equations. This work is a study of such equations for the case that the cross section matrix is nondiagonalizable. For the special case of a two-group problem with a noninvertible scattering matrix, the problem is solved completely via the Wiener-Hopf method. For more general problems, generalized Chandrasekhar H equations are derived. A numerical method for their solution is proposed. Also, the exit distribution is written in terms of the H functions. / Ph. D. / incomplete_metadata

We present important results from Hilbert space and functional analysis for understanding the subject ofReproducing kernel Hilbert spaces. We then showcase the underlying theory and properties of Reproducingkernel Hilbert Spaces. Finally, we show how the theory of reproducing kernel Hilbert spaces is applicable inboth interpolation and machine learning.

<p dir="ltr">On this thesis, we study the validity of the Blackadar-Kirchberg conjecture for C*-<br>algebras that arise as extensions of separable, nuclear, quasidiagonal C*-algebras that satisfy<br>the Universal Coefficient Theorem. More specifically, we show that the conjecture for the<br>C*-algebra in the middle has an affirmative answer if the ideal lies in a class of C*-algebras<br>that is closed under local approximations and contains all separable ASH-algebras, as well<br>as certain classes of simple, unital C*-algebras and crossed products of unital C*-algebras<br>with Z. We also investigate when discrete, amenable groups have C*-algebras of real rank<br>zero. While it is known that this happens when the group is locally finite, the converse in<br>an open problem. We show that if C*(G) has real rank zero, then all normal subgroups of<br>G that are elementary amenable and have finite Hirsch length must be locally finite.<br><br></p>

京都大学 / 新制・課程博士 / 博士(農学) / 甲第25316号 / 農博第2582号 / 新制||農||1104(附属図書館) / 学位論文||R6||N5488 / DGAM / 京都大学大学院農学研究科農学専攻 / (主査)教授 田尾 龍太郎, 教授 田中 義行, 准教授 中野 龍平 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DGAM

A functional analysis (FA) is the most commonly used assessment methodology for identifying maintaining variables influencing problem behavior. However, if an FA does not produce clear differentiation, researchers and practitioners often then modify procedures to include additional individualized variables. The interview-informed synthesized contingency analysis (IISCA) provides a marked departure from FA methodology and aims to include individualized factors at the initiation of the assessment in order to more rapidly produce differentiation and clear results. We sought to further evaluate and compare the outcomes of two different functional analysis methods: the single-contingency functional analysis (FA) and the interview-informed synthesized contingency analysis (IISCA) to determine the function of problem behavior and evaluate the subsequent function-based treatment determined from the functional analysis results with two children diagnosed with autism spectrum disorder (ASD). Both participants engaged in problem behavior maintained by single-contingencies of reinforcement identified within the single-contingency FA and emphasized by the effectiveness of each single-contingency function-based treatment.

We assessed the implementation accuracy and fidelity of two board certified behavior analysts (BCBAs) using the open-ended interview from Hanley. Participants interviewed a confederate using the open-ended interview, and were then asked to use information gathered from the interview to create operational definitions of target behaviors as well as test and control condition procedures for a subsequent matched test-control functional analysis as is characteristic of the interview-informed synthesized contingency analysis (IISCA) strategy. Brief behavioral skills training (BST) was then implemented with all participants to increase the accuracy of constructing both target behavior definitions and functional analysis procedures. Preliminary results show moderate rates of accuracy of target behavior definitions and functional analysis procedures prior to BST, and high rates of accuracy following BST. The results also suggest high implementation fidelity on the open-ended interview may not be necessary to achieve high accuracy when constructing target behavior definitions and functional analysis procedures.

Very few behavior-change programs with canines produce effects that persist beyond the training condition. The present study is an experimental demonstration of a constructional program that established calm patterns of behavior as alternatives to hyperactive ones. Three dogs that exhibited hyperactive patterns were chosen as subjects. Seven conditions common to canine-caretaker relationships were used to determine which factors resulted in the hyperactive patterns. Then, sitting and lying down were taught as beginning points using touch as a reinforcer. The final behavior, maintained by naturally occurring reinforcers, was established errorlessly. The study used a control-analysis strategy of behavior change with a changing-criterion design. The intervention resulted in an immediate reduction in hyperactivity and an increase in sitting and lying down for all dogs.

The individual functional analysis (FA) is the most widely used method to identify variables that influence the occurrence of problem behavior. Researchers often modify the FA after the analysis reveals undifferentiated responding. The interview-informed synthesized contingency analysis (IISCA) is one of the most substantial variations of the FA that builds upon the FA modifications. We evaluated the use of the two different functional analytic methods, the FA and IISCA, and the subsequent function-based treatment to reduce problem behavior for three children with autism spectrum disorder (ASD). The individual FA and the IISCA demonstrated differentiated responding for all participants. The treatment based on the results from the traditional FA was effective for all children. We discuss the implications of these findings.

While descriptive assessment outcomes show limited correspondence with experimental analysis outcomes, they are still often used in the treatment of problem behavior. The most effective way of treating problem behavior is by manipulating its controlling variables; however, if descriptive analyses are not depicting accurate environment-behavior relations, then treatments based off of descriptive analysis results have a higher chance of failing. The current study looks to replicate and extend the literature on utility descriptive assessments by analyzing three different data analysis methods. Three children with a diagnosis of autism were exposed to two types of experimental analyses. Following experimental analyses, descriptive assessments were completed and analyzed to determine correlations between the behavior and environmental events. The results from the three investigated data analysis methods were then compared to the outcomes of the experimental analyses.

Spreading models have become fundamental to the study of asymptotic geometry in Banach spaces. The existence of spreading models in every Banach space, and the so-called good sequences which generate them, was one of the first applications of Ramsey theory in Banach space theory. We use Ramsey theory and other techniques from infinitary combinatorics to examine some old and new questions concerning spreading models and good sequences. First, we consider the lp spreading model problem which asks whether a Banach space contains lp provided that every spreading model of a normalized block basic sequence of the basis is isometrically equivalent to lp. Next, using the Hindman-Milliken-Taylor theorem, we prove a new stabilization theorem for spreading models which produces a basic sequence all of whose normalized constant coefficient block basic sequences are good. When the resulting basic sequence is semi-normalized, all the spreading models generated by the above good sequences must be uniformly equivalent to lp or c0. Finally, we investigate the assumption that every normalized block tree on a Banach space has a good branch. This turns out to be a very strong assumption and is equivalent to the space being 1-asymptotic lp. We also show that the stronger assumption that every block basic sequence is good is equivalent to the space being stabilized 1-asymptotic lp.