Books on the topic 'Discretization time varying system'

Much is conserved in vertebrate evolution, but significant changes in the nervous system occurred at the origin of vertebrates and in most of the major vertebrate lineages. This book examines these innovations and relates them to evolutionary changes in other organ systems, animal behavior, and ecological conditions at the time. The resulting perspective clarifies what makes the major vertebrate lineages unique and helps explain their varying degrees of ecological success. One of the book’s major conclusions is that vertebrate nervous systems are more diverse than commonly assumed, at least among neurobiologists. Examples of important innovations include not only the emergence of novel brain regions, such as the cerebellum and neocortex, but also major changes in neuronal circuitry and functional organization. A second major conclusion is that many of the apparent similarities in vertebrate nervous systems resulted from convergent evolution, rather than inheritance from a common ancestor. For example, brain size and complexity increased numerous times, in many vertebrate lineages. In conjunction with these changes, olfactory inputs to the telencephalic pallium were reduced in several different lineages, and this reduction was associated with the emergence of pallial regions that process non-olfactory sensory inputs. These conclusions cast doubt on the widely held assumption that all vertebrate nervous systems are built according to a single, common plan. Instead, the book encourages readers to view both species similarities and differences as fundamental to a comprehensive understanding of nervous systems.

Spreadsheet are straightforward to work with and do not require extensive knowledge of programming; they are easy to communicate with among people with varying levels of expertise; are convenient for optimization problems, given the availability of prepackaged Solver algorithms; and are commonly used for modeling in business management, nonprofit organization budgeting, consulting, and academia. But spreadsheets have their limitations, particularly when modeling large populations, long time periods, or complex situations with many states or conditions and equations. For larger scale models that need more flexibility than can be offered by a spreadsheet, the free statistical program R provides a straightforward approach to modeling and has the advantages of being free, fast, available on any operating system, commonly used, and widely supported by an online community. This chapter provides a detailed introduction to R that will be useful for the more advanced modeling methods introduced in Chapters 8 through 11.

Chapter 5 introduces single-particle retarded Green’s functions, which provide the probability amplitude that a particle created at (x, t) is later annihilated at (x′,t′). Partial Green’s functions, which represent the time development of one (or a few) state(s) that may be understood as localized but are in interaction with a continuum of states, are discussed and applied to chemisorption. Introductions are also made to the Dyson integral equation, T-matrix and the Dirac delta-function potential, with the latter applied to random impurity scattering. The retarded Green’s function in the presence of random impurity scattering is exhibited in the Born and self-consistent Born approximations, with application to Ando’s semi-elliptic density of states for the 2D Landau-quantized electron-impurity system. Important retarded Green’s functions and their methods of derivation are discussed. These include Green’s functions for electrons in magnetic fields in both three dimensions and two dimensions, also a Hamilton equation-of-motion method for the determination of Green’s functions with application to a 2D saddle potential in a time-dependent electric field. Moreover, separable Hamiltonians and their product Green’s functions are discussed with application to a one-dimensional superlattice in axial electric and magnetic fields. Green’s function matching/joining techniques are introduced and applied to spatially varying mass (heterostructures) and non-local electrostatics (surface plasmons).

High rates of rearrest and recidivism, especially among drug-involved individuals, are of grave concern for the justice system and society at large. This chapter looks at the factors affecting recidivism rates of substance-involved individuals involved in the justice system. We begin by considering the complexity of measuring recidivism and the meaning of this concept; the term is fraught with difficulties due to the complexities of generalizing findings across studies with varying sampling frames and time-frames for follow-up, and differences in the types of recidivism events studied. Recent research illustrates that recidivism rates among drug users vary by drug of choice and are typically higher among individuals who use amphetamines, heroin, and/or cocaine. Recidivism rates may also vary depending on the presence of certain comorbid factors, although this is an emerging area of research. Factors that appear to elevate recidivism rates include personality disorders, co-occurring substance abuse and mental health disorders, other psychiatric disorders, and other serious mental illness. The location of an individual’s residence also appears to impact the recidivism rate, possibly mediated by the presence or absence of various protective factors in the community. While the nature of the relationship between drugs and crime is still unclear, the same is true for our understanding of recidivism among substance users in the justice system. There is a need for a greater understanding of the relationship between substance use and recidivism, in order to fill existing knowledge gaps.

The quality of data collected in official spatial databases is crucial in making strategic decisions as well as in the implementation of planning and design works. Awareness of the level of the quality of these data is also important for individual users of official spatial data. The author presents methods and models of description and evaluation of the quality of spatial data collected in public registers. Data describing the space in the highest degree of detail, which are collected in three databases: land and buildings registry (EGiB), geodetic registry of the land infrastructure network (GESUT) and in database of topographic objects (BDOT500) were analyzed. The results of the research concerned selected aspects of activities in terms of the spatial data quality. These activities include: the assessment of the accuracy of data collected in official spatial databases; determination of the uncertainty of the area of registry parcels, analysis of the risk of damage to the underground infrastructure network due to the quality of spatial data, construction of the quality model of data collected in official databases and visualization of the phenomenon of uncertainty in spatial data. The evaluation of the accuracy of data collected in official, large-scale spatial databases was based on a representative sample of data. The test sample was a set of deviations of coordinates with three variables dX, dY and Dl – deviations from the X and Y coordinates and the length of the point offset vector of the test sample in relation to its position recognized as a faultless. The compatibility of empirical data accuracy distributions with models (theoretical distributions of random variables) was investigated and also the accuracy of the spatial data has been assessed by means of the methods resistant to the outliers. In the process of determination of the accuracy of spatial data collected in public registers, the author’s solution was used – resistant method of the relative frequency. Weight functions, which modify (to varying degree) the sizes of the vectors Dl – the lengths of the points offset vector of the test sample in relation to their position recognized as a faultless were proposed. From the scope of the uncertainty of estimation of the area of registry parcels the impact of the errors of the geodetic network points was determined (points of reference and of the higher class networks) and the effect of the correlation between the coordinates of the same point on the accuracy of the determined plot area. The scope of the correction was determined (in EGiB database) of the plots area, calculated on the basis of re-measurements, performed using equivalent techniques (in terms of accuracy). The analysis of the risk of damage to the underground infrastructure network due to the low quality of spatial data is another research topic presented in the paper. Three main factors have been identified that influence the value of this risk: incompleteness of spatial data sets and insufficient accuracy of determination of the horizontal and vertical position of underground infrastructure. A method for estimation of the project risk has been developed (quantitative and qualitative) and the author’s risk estimation technique, based on the idea of fuzzy logic was proposed. Maps (2D and 3D) of the risk of damage to the underground infrastructure network were developed in the form of large-scale thematic maps, presenting the design risk in qualitative and quantitative form. The data quality model is a set of rules used to describe the quality of these data sets. The model that has been proposed defines a standardized approach for assessing and reporting the quality of EGiB, GESUT and BDOT500 spatial data bases. Quantitative and qualitative rules (automatic, office and field) of data sets control were defined. The minimum sample size and the number of eligible nonconformities in random samples were determined. The data quality elements were described using the following descriptors: range, measure, result, and type and unit of value. Data quality studies were performed according to the users needs. The values of impact weights were determined by the hierarchical analytical process method (AHP). The harmonization of conceptual models of EGiB, GESUT and BDOT500 databases with BDOT10k database was analysed too. It was found that the downloading and supplying of the information in BDOT10k creation and update processes from the analyzed registers are limited. An effective approach to providing spatial data sets users with information concerning data uncertainty are cartographic visualization techniques. Based on the author’s own experience and research works on the quality of official spatial database data examination, the set of methods for visualization of the uncertainty of data bases EGiB, GESUT and BDOT500 was defined. This set includes visualization techniques designed to present three types of uncertainty: location, attribute values and time. Uncertainty of the position was defined (for surface, line, and point objects) using several (three to five) visual variables. Uncertainty of attribute values and time uncertainty, describing (for example) completeness or timeliness of sets, are presented by means of three graphical variables. The research problems presented in the paper are of cognitive and application importance. They indicate on the possibility of effective evaluation of the quality of spatial data collected in public registers and may be an important element of the expert system.