The binding constraint on firms'growth in developing countries

Firms in developing countries face numerous and serious constraints on their growth, ranging from corruption to lack of infrastructure to inability to access finance. Countries lack the resources to remove all the constraints at once and so would be better off removing the most binding one first. This paper uses data from World Bank Enterprise Surveys in 2006-10 to identify the most binding constraints on firm operations in developing countries. While each country faces a different set of constraints, these constraints also vary by firm characteristics, especially firm size. Across all countries, access to finance is among the most binding constraints; other obstacles appear to matter much less. This result is robust for all regions. Smaller firms must rely more on their own funds to invest and would grow significantly faster if they had greater access to external funds. As a result, a low level of financial development skews the firm size distribution by increasing the relative share of small firms. The results suggest that financing constraints play a significant part in explaining the"missing middle"-- the failure of small firms in developing countries to grow into medium-size or large firms.Access to Finance,Environmental Economics&Policies,Microfinance,Debt Markets,Banks&Banking Reform

Convexity in source separation: Models, geometry, and algorithms

Source separation or demixing is the process of extracting multiple components entangled within a signal. Contemporary signal processing presents a host of difficult source separation problems, from interference cancellation to background subtraction, blind deconvolution, and even dictionary learning. Despite the recent progress in each of these applications, advances in high-throughput sensor technology place demixing algorithms under pressure to accommodate extremely high-dimensional signals, separate an ever larger number of sources, and cope with more sophisticated signal and mixing models. These difficulties are exacerbated by the need for real-time action in automated decision-making systems. Recent advances in convex optimization provide a simple framework for efficiently solving numerous difficult demixing problems. This article provides an overview of the emerging field, explains the theory that governs the underlying procedures, and surveys algorithms that solve them efficiently. We aim to equip practitioners with a toolkit for constructing their own demixing algorithms that work, as well as concrete intuition for why they work

Tunneling into Nonequilibrium Luttinger Liquid with Impurity

We evaluate tunneling rates into/from a voltage biased quantum wire containing weak backscattering defect. Interacting electrons in such a wire form a true nonequilibrium state of the Luttinger liquid (LL). This state is created due to inelastic electron backscattering leading to the emission of nonequilibrium plasmons with typical frequency $\hbar \omega \leq U$. The tunneling rates are split into two edges. The tunneling exponent at the Fermi edge is positive and equals that of the equilibrium LL, while the exponent at the side edge $E_F-U$ is negative if Coulomb interaction is not too strong.Comment: 4+ pages, 5 figure

Pairing effect on the giant dipole resonance width at low temperature

The width of the giant dipole resonance (GDR) at finite temperature T in Sn-120 is calculated within the Phonon Damping Model including the neutron thermal pairing gap determined from the modified BCS theory. It is shown that the effect of thermal pairing causes a smaller GDR width at T below 2 MeV as compared to the one obtained neglecting pairing. This improves significantly the agreement between theory and experiment including the most recent data point at T = 1 MeV.Comment: 8 pages, 5 figures to be published in Physical Review

A characterization of compact complex tori via automorphism groups

We show that a compact Kaehler manifold X is a complex torus if both the continuous part and discrete part of some automorphism group G of X are infinite groups, unless X is bimeromorphic to a non-trivial G-equivariant fibration. Some applications to dynamics are given.Comment: title changed, to appear in Math. An

Genetic and Modifiable Risk Factors Contributing to Cisplatin-Induced Toxicities

Effective administration of traditional cytotoxic chemotherapy is often limited by off-target toxicities. This clinical dilemma is epitomized by cisplatin, a platinating agent that has potent antineoplastic activity due to its affinity for DNA and other intracellular nucleophiles. Despite its efficacy against many adult-onset and pediatric malignancies, cisplatin elicits multiple off-target toxicities that can not only severely impact a patient’s quality of life, but also lead to dose reductions or the selection of alternative therapies that can ultimately affect outcomes. Without an effective therapeutic measure by which to successfully mitigate many of these symptoms, there have been attempts to identify a priori those individuals who are more susceptible to developing these sequelae through studies of genetic and nongenetic risk factors. Older age is associated with cisplatin induced ototoxicity, neurotoxicity and nephrotoxicity. Traditional genome-wide association studies have identified single nucleotide polymorphisms in ACYP2 and WFS1 associated with cisplatin-induced hearing loss. However, validating associations between specific genotypes and cisplatin-induced toxicities with enough stringency to warrant clinical application remains challenging. This review summarizes the current state of knowledge with regard to specific adverse sequelae following cisplatin-based therapy with a focus on ototoxicity, neurotoxicity, nephrotoxicity, myelosuppression and nausea/emesis. We discuss variables (genetic and nongenetic) contributing to these detrimental toxicities, and currently available means to prevent or treat their occurrence

A Variational Approach to the Evolution of Radial Basis Functions for Image Segmentation

In this paper we derive differential equations for evolving radial basis functions (RBFs) to solve segmentation problems. The differential equations result from applying variational calculus to energy functionals designed for image segmentation. Our methodology supports evolution of all parameters of each RBF, including its position, weight, orientation, and anisotropy, if present. Our framework is general and can be applied to numerous RBF interpolants. The resulting approach retains some of the ideal features of implicit active contours, like topological adaptivity, while requiring low storage overhead due to the sparsity of our representation, which is an unstructured list of RBFs. We present the theory behind our technique and demonstrate its usefulness for image segmentation