Adjacency matrix formulation of energy flow in dendrimeric polymers

Dendrimers are synthetic, highly branched polymers with an unusually high density of chromophores. As a result of their extremely high absorption cross-sections for visible light, they represent some of the most promising new materials for energy harvesting. Although the signature of the bonding structure in dendrimers is an essentially fractal geometry, the three-dimensional molecular folding of most higher generation materials results in a chromophore layout that is more obviously akin to concentric spherical shells. The number of chromophores in each shell is a simple function of the distance from the central core. The energy of throughput optical radiation, on capture by any of the chromophores, passes by a multi-step but highly efficient process to the photoactive core. Modeling this crucial migration process presents a number of challenges. It is far from a simple diffusive random walk; each step is subject to an intricate interplay of geometric and spectroscopic features. In this report, the first results of a new approach to the theory is described, developed and adapted from an adjacency matrix formulation. It is shown how this method offers not only kinetic information but also insights into the typical number of steps and the patterns of internal energy flow

Behaviors of a micro oil droplet in an EHL contact

Abstract Oil–air lubrication supplies lubricants in the form of droplets to elastohydrodynamic lubrication (EHL) contacts, such as those in high-speed spindle bearings. However, there is a paucity of information related to understanding the lubrication behaviors of oil droplets within EHL contacts. In this study, behaviors of lubricant droplets, in terms of spreading around a static contact as well as passing through a rolling contact, were studied with an optical ball-on-disk EHL test rig. Influences of oil droplet size, viscosity, and surface tension on droplet spreading were examined. Lubricating film formation was also investigated when droplets traveled through the EHL contact region. The results indicated that droplet size and running speed significantly influenced film profiles. With increasing entrainment speeds, a small droplet passed through the contact without spreading and generated films with a significant depression in the central contact region

Zhōng Jiè Yǔ Yǔ Yán Xué Duō Wéi Yán Jiū [Multidimensional Studies in Interlanguage Linguistics]

Since the term “interlanguage” was coined by Larry Selinker in 1972 to refer to the systematic knowledge of a second language (L2) that is independent of both a learner’s first or native language (L1) and the target language (TL) (Ellis, 2008), it has received a tremendous amount of attention in the second language acquisition (SLA) research literature. After more than 40 years of study, researchers have reached the consensus that interlanguage is a linguistic system in its own right (Selinker, 2014) such that the interlanguage system has the basic characteristics of natural language and its intrinsic regularity can be identified at all linguistic levels, such as phonology, morphology, syntax, semantics, and pragmatics. In line with new developments in interlanguage research, Professor Lianrui Yang has recently identified a new interlanguage construct, interlanguage linguistics, in this new monograph that is currently only available in Chinese. All of the various strands of interlanguage research are integrated into this new construct, suggesting the formation of this new discipline. Focusing specifically on interlanguage development, the 32 chapters that constitute this new book offer fundamental information about both traditional as well as emerging topics in interlanguage research. The book highlights the interdisciplinary nature of the field in its selection of themes and chapters. Its chapters touch on topics ranging from theoretical constructs to multidimensional studies of interlanguage development. For this review, the chapters have been grouped and organized under five main themes: (1) Interlanguage Phonology (Chapters 1-7), (2) Interlanguage Morphology and Syntax (Chapters 8-11, 14-15, 17-20), (3) Interlanguage Pragmatics (Chapters 12-13, 16), (4) Interlanguage Vocabulary (Chapters 21-28), and (5) Interlanguage Linguistics (Chapters 29-32). These subdivisions offer general and essential information regarding the status of research on interlanguage phonology, syntax, pragmatics, lexicon, etc. The general contents of each of these major thematic areas will be described next, followed by brief chapter-by-chapter summaries as well

INFORMATION ASYMMETRY BETWEEN PRINCIPAL AND AGENT IN SOME PERFORMANCE EVALUATION MODELS

The research question on problems that involves information asymmetry has been drawing more and more attention since the past decades, and in particular, two of the pioneers Bengt Holmström and Oliver Hart) in this field won the Nobel Prize of Economics in 2016. With the emergence of information economics, accounting researchers started focusing on the information asymmetry problems, with a particular interest and emphasis on moral hazard problems, within the firm. In this essay, we intend to fill the blank in this area by investigating some specific information asymmetry problems in managerial accounting under the presence of both moral hazard and adverse selection, or moral hazard and post-contract information asymmetry, respectively. The first study analyzes the expected value of information about an agent’s type in the presence of moral hazard and adverse selection. The value of the information decreases in the variability of output and the agent’s risk aversion, two factors that are typically associated with the severity of the moral hazard problem. However, the value of the information about agent type first increases but ultimately decreases in the severity of adverse selection. The second study draws attention to the tradeoffs associated with relying on pre-contracting ability measures in the design of executive compensation schemes. We show that the more sensitive of the ability signal to ability the more weight should be placed optimally, and the more precise of the ability signal the more weight should be placed optimally, in accordance with the informativeness principal. We further prove that under a broad class of distributions a linear aggregation of multiple pieces of pre-contracting information is sufficient for contracting purposes without loss of generality. The third study investigates three mechanisms of organizational control: outcome control (contracting on the outcome), effort control (contracting on the signal of action), and clan control (employing an agent whose preferences are partially aligned with the principal’s goal through a socialization process). In doing so, we expand the standard agency framework by introducing the concept of other-regarding preference and clan control to provide new insights into organizational control design.Business Administration/Accountin

Development of Algorithms for the Direct Multi-Configuration Self- Consistent Field (MCSCF) Method

In order to improve the performance of the current parallelized direct multi-configuration self-consistent field (MCSCF) implementations of the program package Gaussian [42], consisting of the complete active space (CAS) SCF method [43] and the restricted active space (RAS) SCF method [44], this thesis introduces a matrix multiplication scheme as part of the CI eigenvalue evaluation of these methods. Thus highly optimized linear algebra routines, which are able to use data in a sequential and predictable way, can be used in our method, resulting in a much better performance overall than the current methods. The side effect of this matrix multiplication scheme is that it requires some extra memory to store the additional intermediate matrices. Several chemical systems are used to demonstrate that the new CAS and RAS methods are faster than the current CAS and RAS methods respectively. This thesis is structured into four chapters. Chapter One is the general introduction, which describes the background of the CASSCF/RASSCF methods. Then the efficiency of the current CASSCF/RASSCF code is discussed, which serves as the motivation for this thesis, followed by a brief introduction to our method. Chapter Two describes applying the matrix multiplication scheme to accelerate the current direct CASSCF method, by reorganizing the summation order in the equation that generates non-zero Hamiltonian matrix elements. It is demonstrated that the new method can perform much faster than the current CASSCF method by carrying out single point energy calculations on pyracylene and pyrene molecules, and geometry optimization calculations on anthracene+ / phenanthrene+ molecules. However, in the RASSCF method, because an arbitrary number of doubly-occupied or unoccupied orbitals are introduced into the CASSCF reference space, many new orbital integral cases arise. Some cases are suitable for the matrix multiplication scheme, while others are not. Chapter Three applies the scheme to those suitable integral cases that are also the most time-consuming cases for the RASSCF calculation. The coronene molecule - with different sizes of orbital active space - has been used to demonstrate that the new RASSCF method can perform significantly faster than the current Gaussian method. Chapter Four describes an attempt to modify the other integral cases, based on a review of the method developed by Saunders and Van Lenthe [95]. Calculations on coronene molecule are used again to test whether this implementation can further improve the performance of the RASSCF method developed in Chapter Three

IDEA at the NTCIR-17 FinArg-1 Task: Argument-based Sentiment Analysis

Although argument mining has been discussed for several years, financial argument mining is still in the early stage. The IDEA team participates in Argument Unit Classification (for Earnings Conference Call) and Argument Relation Classification (for Earnings Conference Call) subtasks of the NTCIR-17 FinArg-1 Task. This paper presents our work on the two subtasks. For Argument Unit Classification subtask, we successively construct the models based on BERT and Roberta to classify a given argumentative sentence. To better extract the semantic features, we combine the pre-trained model with CNN.Micro-F1 and Macro-F1 achieve 76.47% and 76.46% in official evaluation results of the first run (i.e., IDEA-1), respectively, outperforming most approaches of other teams. For Argument Relation Classification subtask, we classify sentence pairs based on the pre-trained model and Prompt-Tuning. And Micro-F1 and Macro-F1 achieve 81.74% and 51.85% in official evaluation results of the third run (i.e., IDEA-3), respectively.conference pape