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

Spatial and spatiotemporal variation in metapopulation structure affects population dynamics in a passively dispersing arthropod

The spatial and temporal variation in the availability of suitable habitat within metapopulations determines colonization-extinction events, regulates local population sizes and eventually affects local population and metapopulation stability. Insights into the impact of such a spatiotemporal variation on the local population and metapopulation dynamics are principally derived from classical metapopulation theory and have not been experimentally validated. By manipulating spatial structure in artificial metapopulations of the spider mite Tetranychus urticae, we test to which degree spatial (mainland-island metapopulations) and spatiotemporal variation (classical metapopulations) in habitat availability affects the dynamics of the metapopulations relative to systems where habitat is constantly available in time and space (patchy metapopulations). Our experiment demonstrates that (i) spatial variation in habitat availability decreases variance in metapopulation size and decreases density-dependent dispersal at the metapopulation level, while (ii) spatiotemporal variation in habitat availability increases patch extinction rates, decreases local population and metapopulation sizes and decreases density dependence in population growth rates. We found dispersal to be negatively density dependent and overall low in the spatial variable mainland-island metapopulation. This demographic variation subsequently impacts local and regional population dynamics and determines patterns of metapopulation stability. Both local and metapopulation-level variabilities are minimized in mainland-island metapopulations relative to classical and patchy ones

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

Analysis of common ship machinery failures and treatment methods in ship inspection

ships are the means of transportation for water transportation. According to the actual use requirements of water operations, they are divided into diff erent structures and ship types. For ships, the mechanical failure inspection is to ensure that the ship can reduce the risk of accidents during the shipping process. At the same time, it is also conducive to ensuring the economic benefi ts of relevant enterprises, and more importantly, it is responsible for the life safety of personnel on board. Based on the analysis of common ship machinery faults and treatment methods in ship inspection, this paper analyzes the common ship machinery faults in ship inspection, and puts forward relevant measures to solve the problems

Orthogonal grid generation, non-reflecting boundary condition, and parallel computation for fluid flow

The purpose of this study is to investigate one of the most interesting areas in computational fluid dynamics. The content of this paper is divided into three parts. The first part is the orthogonal grid generation. The second part is the non-reflecting boundary condition in curvilinear coordinates. The third part is parallel computation by Message Passing Interface. The grid generation method is presented by solving elliptic partial difference equations. The elliptic grid generation method is based on the use of composite mapping, which consists of a non-linear algebraic transformation and an elliptic transformation. The elliptic transformation is based on the Laplace equations for the domains or on the Laplace-Beltrami equations for surfaces. The algebraic transformation maps the computational space one-to-one onto a parameter space, and the elliptic transformation maps the parameter space one-to-one onto the domain or the surfaces. The composition of these two mappings is a differentiable and one-to-one, which has a non-vanish Jacobian. Finally, some complicated test examples are given. Computation results show that the grids generated by these methods are smooth and orthogonal. The grid quality meets our requirement for high accuracy numerical simulation. Numerical methods for time-dependent hyperbolic systems require time-dependent boundary conditions when the system is solved in a finite domain. The “correct” boundary conditions are crucial in solving such a system. The non-reflecting boundary conditions based on the Navier-Stokes equations have been derived for curvilinear coordinates. High order scheme is used to discretize the non-reflecting boundary conditions. Several examples of non-reflecting boundary conditions are tested. The results are compared with the reference method based on extrapolation or Rieman invariants. It is found that this non-reflecting boundary condition is much more accurate and effective than the tradition methods used to impose boundary conditions. A parallel spatial direct numerical simulation code is developed to simulate the spatial evolving disturbances associated with the laminar-to-turbulent transition in a compressible boundary layer. MPI (Message Passing Interface) is employed to parallelize all processes for a distributed memory parallel computer. Explicit time-stepping is used in the DNS code on IBM/SP2 to simulate the flow transition. The machine-dependent phenomenon, which is always being considered as a problem for parallel computation, is successfully avoided. A fundamental breakdown on a flat plate boundary layer transition at Mach 0.5 is then studied using this code. The results demonstrate the optimistic future of MPI to direct numerical simulation

Applying Machine Learning Algorithms for the Analysis of Biological Sequences and Medical Records

The modern sequencing technology revolutionizes the genomic research and triggers explosive growth of DNA, RNA, and protein sequences. How to infer the structure and function from biological sequences is a fundamentally important task in genomics and proteomics fields. With the development of statistical and machine learning methods, an integrated and user-friendly tool containing the state-of-the-art data mining methods are needed. Here, we propose SeqFea-Learn, a comprehensive Python pipeline that integrating multiple steps: feature extraction, dimensionality reduction, feature selection, predicting model constructions based on machine learning and deep learning approaches to analyze sequences. We used enhancers, RNA N6- methyladenosine sites and protein-protein interactions datasets to evaluate the validation of the tool. The results show that the tool can effectively perform biological sequence analysis and classification tasks. Applying machine learning algorithms for Electronic medical record (EMR) data analysis is also included in this dissertation. Chronic kidney disease (CKD) is prevalent across the world and well defined by an estimated glomerular filtration rate (eGFR). The progression of kidney disease can be predicted if future eGFR can be accurately estimated using predictive analytics. Thus, I present a prediction model of eGFR that was built using Random Forest regression. The dataset includes demographic, clinical and laboratory information from a regional primary health care clinic. The final model included eGFR, age, gender, body mass index (BMI), obesity, hypertension, and diabetes, which achieved a mean coefficient of determination of 0.95. The estimated eGFRs were used to classify patients into CKD stages with high macro-averaged and micro-averaged metrics

Research on robust local feature extraction method for human detection

制度:新 ; 報告番号:甲3273号 ; 学位の種類:博士(工学) ; 授与年月日:2011/3/15 ; 早大学位記番号:新557