Formal and informal financing in a Chicago neighborhood

This article documents not only the actual use of banks, but also the widespread use of alternative financing mechanisms, using data from a survey of households and businesses in a Hispanic neighborhood of Chicago.Bank loans ; Chicago (Ill.) ; Consumer behavior ; Mortgages

THE IDENTIFICATION OF NOVEL INORGANIC CARBON SENSITIVE ENZYMES

Adenylyl cyclase catalyses the formation of the second messenger adenosine-3’, 5’-monophosphate from adenosine triphosphate, and is involved in a number of diverse signalling pathways in eukaryotes and prokaryotes. Adenylyl cyclases are diverse in their structure and biochemistry, and have been grouped into six distinct Classes (I–VI). The Class III cyclase homology domain comprises the majority of prokaryotic and eukaryotic adenylyl cyclases, and has been further divided into 4 sub-Classes (a-d) based on active site polymorphisms. A number of Class IIIb adenylyl cyclases display elevated catalytic activity in the presence of inorganic carbon. Whether a response to inorganic carbon can be observed in enzymes which do not possess a Class IIIb cyclase homology domain remains to be established. Experiments were performed to investigate the response to inorganic carbon of a Class IIIa cyclase homology domain; mammalian transmembrane adenylyl cyclase. In vivo experiments demonstrated that the activity of mammalian transmembrane adenylyl cyclase was potentially regulated by inorganic carbon, and that this had a downstream effect on the cAMP response element binding protein. In vitro experiments performed on a transmembrane adenylyl cyclase demonstrated that the increase in activity in the presence of inorganic carbon occurred through an increase in kcat and increased metal affinity. Experiments were performed to test the response to inorganic carbon of several enzymes that share a structurally similar active site with the adenylyl cyclases; the polymerase I family of prokaryotic DNA polymerases, the polymerase β family of DNA polymerases, and the guanylyl cyclases. Initial in vitro experiments performed on T7 RNA polymerase demonstrated a response to inorganic carbon, however, it was discovered that this was likely due to a non-specific effect of pH. It was shown that inorganic carbon increased assay pH over time, and this warranted a re-design of the in vitro assay used to test the response of an enzyme to inorganic carbon. This new in vitro assay methodology was used to re-test T7 RNA polymerase, as well as test DNA polymerase β and several guanylyl cyclase, and demonstrated that these enzymes were non-responsive to inorganic carbon. Using this newly devised in vitro assay, experiments were performed to re-test the response of mammalian transmembrane adenylyl cyclase to inorganic carbon, and demonstrated that this enzyme was unlikely to be regulated by inorganic carbon. Furthermore, this new in vitro assay was used to re-test the response of several Class IIIb cyclase homology domains to inorganic carbon. Results demonstrated that mammalian soluble adenylyl cyclase was responsive to inorganic carbon, however, results provided evidence to suggest that two prokaryotic Class IIIb cyclase homology domains (CyaB1 from Anabaena PCC 7120 and CyaC from Spirulina platensis) were possibly non-responsive to inorganic carbon

Small business finance in two Chicago minority neighborhoods

The authors use survey data to measure the use of formal and informal sources of financing by owners of small businesses in two ethnic neighborhoods. The authors find substantial differences across ethnic groups in the amount of start-up funding obtained and in the use of trade credit.Small business ; Chicago (Ill.)

A general formalism for phase space calculations

General formulas for calculating the interactions of galactic cosmic rays with target nuclei are presented. Methods for calculating the appropriate normalization volume elements and phase space factors are presented. Particular emphasis is placed on obtaining correct phase space factors for 2-, and 3-body final states. Calculations for both Lorentz-invariant and noninvariant phase space are presented

Asymptotic and transient behaviour of nonlinear control systems

In this thesis, the problem of controlling both transient and asymptotic behaviour of solutions of functional differential equations is addressed. The work begins, in Chapter 1, with an introduction to basic control theory principles that will be used throughout. This is followed by the introduction of a class of nonlinear operators in Chapter 2 and the development of suitable existence theories for the associated system classes of functional differential equations and inclusions in Chapter 3. A discussion is provided, in Chapter 2, describing diverse phenomena, such as delays and hysteresis, that can be incorporated in the class of operators. Chapters 4-7 cover four areas of research. Chapter 4 examines the asymptotic and transient behaviour of nonlinearly-perturbed linear systems of known relative degree; a continuous feedback strategy is adopted and an approximate tracking result is presented. In Chapter 5 the class of systems considered is expanded to a large class of nonlinear systems and a continuous feedback strategy is implemented in order to achieve approximate tracking. In Chapters 6 and 7 attention is restricted to systems f relative degree one, but this limitation is compensated for by targeting an exact asymptotic tracking result. The first investigation, in Chapter 6, involves a potentially discontinuous feedback controller applied to a class of nonlinear systems, with comparisons made to an internal model approach. Asymptotic tracking and approximate tracking are developed in unison within a framework of functional differential inclusions. Finally, in Chapter 7, a continuous controller is applied to single-input, single-output, nonlinear systems with input hysteresis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Remote Sensing of Plant Biodiversity

At last, here it is. For some time now, the world has needed a text providing both a new theoretical foundation and practical guidance on how to approach the challenge of biodiversity decline in the Anthropocene. This is a global challenge demanding global approaches to understand its scope and implications. Until recently, we have simply lacked the tools to do so. We are now entering an era in which we can realistically begin to understand and monitor the multidimensional phenomenon of biodiversity at a planetary scale. This era builds upon three centuries of scientific research on biodiversity at site to landscape levels, augmented over the past two decades by airborne research platforms carrying spectrometers, lidars, and radars for larger-scale observations. Emerging international networks of fine-grain in-situ biodiversity observations complemented by space-based sensors offering coarser-grain imagery—but global coverage—of ecosystem composition, function, and structure together provide the information necessary to monitor and track change in biodiversity globally. This book is a road map on how to observe and interpret terrestrial biodiversity across scales through plants—primary producers and the foundation of the trophic pyramid. It honors the fact that biodiversity exists across different dimensions, including both phylogenetic and functional. Then, it relates these aspects of biodiversity to another dimension, the spectral diversity captured by remote sensing instruments operating at scales from leaf to canopy to biome. The biodiversity community has needed a Rosetta Stone to translate between the language of satellite remote sensing and its resulting spectral diversity and the languages of those exploring the phylogenetic diversity and functional trait diversity of life on Earth. By assembling the vital translation, this volume has globalized our ability to track biodiversity state and change. Thus, a global problem meets a key component of the global solution. The editors have cleverly built the book in three parts. Part 1 addresses the theory behind the remote sensing of terrestrial plant biodiversity: why spectral diversity relates to plant functional traits and phylogenetic diversity. Starting with first principles, it connects plant biochemistry, physiology, and macroecology to remotely sensed spectra and explores the processes behind the patterns we observe. Examples from the field demonstrate the rising synthesis of multiple disciplines to create a new cross-spatial and spectral science of biodiversity. Part 2 discusses how to implement this evolving science. It focuses on the plethora of novel in-situ, airborne, and spaceborne Earth observation tools currently and soon to be available while also incorporating the ways of actually making biodiversity measurements with these tools. It includes instructions for organizing and conducting a field campaign. Throughout, there is a focus on the burgeoning field of imaging spectroscopy, which is revolutionizing our ability to characterize life remotely. Part 3 takes on an overarching issue for any effort to globalize biodiversity observations, the issue of scale. It addresses scale from two perspectives. The first is that of combining observations across varying spatial, temporal, and spectral resolutions for better understanding—that is, what scales and how. This is an area of ongoing research driven by a confluence of innovations in observation systems and rising computational capacity. The second is the organizational side of the scaling challenge. It explores existing frameworks for integrating multi-scale observations within global networks. The focus here is on what practical steps can be taken to organize multi-scale data and what is already happening in this regard. These frameworks include essential biodiversity variables and the Group on Earth Observations Biodiversity Observation Network (GEO BON). This book constitutes an end-to-end guide uniting the latest in research and techniques to cover the theory and practice of the remote sensing of plant biodiversity. In putting it together, the editors and their coauthors, all preeminent in their fields, have done a great service for those seeking to understand and conserve life on Earth—just when we need it most. For if the world is ever to construct a coordinated response to the planetwide crisis of biodiversity loss, it must first assemble adequate—and global—measures of what we are losing

Numerical simulation of the shallow water equations coupled with a precipitation system driven by random forcing

Quantification of flood risk and flood inundation requires accurate numerical simulations, both in terms of the mathematical theory that underpins the methods used and the manner in which the meteorological phenomena that cause flooding are coupled to such systems. Through our research, we have demonstrated how rainfall and infiltration effects can be incorporated into existing flood models in a rigorous and mathematically consistent manner; this approach departs from preceding methods, which neglect terms representing such phenomena in the conservation or balancing of momentum. We demonstrate how the omission of these terms means the solution derived from such models cannot a priori be assumed to be the correct one, which is in contrast to solutions from the extended system we have developed which respect the energetic consistency of the problem. The second issue we address is determining how we can model these meteorological phenomena that lead to flooding, with a specific interest in how existing observation data from rain gauges can be incorporated into our modelling approach. To capture the random nature of the precipitation, we use stochastic processes to model the complex meteorological interactions, and demonstrate how an accurate representation of the precipitation can be built. Given the specific industrial applications we have mind in regards to flood modelling and prediction, there will be a high computational cost associated with any such simulations, and so we consider techniques which can be used to reduce the computational cost whilst maintaining the accuracy of our solutions. Having such an accurate flood model, coupled with a stochastic weather model designed for efficient computational modelling, will enable us to make useful predictions on how future climate change and weather patterns will impact flood risk and flood damage

Large-Scale Statistical Learning for Mass Transport Prediction in Porous Materials Using 90,000 Artificially Generated Microstructures

Effective properties of functional materials crucially depend on their 3D microstructure. In this paper, we investigate quantitative relationships between descriptors of two-phase microstructures, consisting of solid and pores and their mass transport properties. To that end, we generate a vast database comprising 90,000 microstructures drawn from nine different stochastic models, and compute their effective diffusivity and permeability as well as various microstructural descriptors. To the best of our knowledge, this is the largest and most diverse dataset created for studying the influence of 3D microstructure on mass transport. In particular, we establish microstructure-property relationships using analytical prediction formulas, artificial (fully-connected) neural networks, and convolutional neural networks. Again, to the best of our knowledge, this is the first time that these three statistical learning approaches are quantitatively compared on the same dataset. The diversity of the dataset increases the generality of the determined relationships, and its size is vital for robust training of convolutional neural networks. We make the 3D microstructures, their structural descriptors and effective properties, as well as the code used to study the relationships between them available open access

Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species

High-density oligonucleotide (oligo) arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L.) Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM) probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P) stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ webcite and may be used to facilitate transcriptomic analyses of a wide range of plant and animal species in the absence of custom arrays