Do consumers gamble to convexify?

The combination of credit constraints and indivisible consumption goods may induce some risk-averse individuals to gamble to have a chance of crossing a purchasing threshold. This idea has been demonstrated theoretically, but not explored empirically. We test this idea by focusing on a key implication: income effects for individuals who choose to gamble are likely to be larger than for the general population. Using UK data on gambling wins, other windfalls and durable goods purchases, we show that winners display higher income effects than non-winners but only amongst those likely to be credit-constrained. This is consistent with credit-constrained, risk-averse agents gambling to convexify their budget set.This work was supported in part by the ESRC-funded Centre for Microeconomic Analysis of Public Policy at the Institute for Fiscal Studies (grant number RES-544-28-5001.)This is the final version of the article. It first appeared from Elsevier via http://dx.doi.org/10.1016/j.jebo.2016.07.02

Parallel approach to sliding window sums

Sliding window sums are widely used in bioinformatics applications, including sequence assembly, k-mer generation, hashing and compression. New vector algorithms which utilize the advanced vector extension (AVX) instructions available on modern processors, or the parallel compute units on GPUs and FPGAs, would provide a significant performance boost for the bioinformatics applications. We develop a generic vectorized sliding sum algorithm with speedup for window size w and number of processors P is O(P/w) for a generic sliding sum. For a sum with commutative operator the speedup is improved to O(P/log(w)). When applied to the genomic application of minimizer based k-mer table generation using AVX instructions, we obtain a speedup of over 5X.Comment: 10 pages, 5 figure

Space-efficient Feature Maps for String Alignment Kernels

String kernels are attractive data analysis tools for analyzing string data. Among them, alignment kernels are known for their high prediction accuracies in string classifications when tested in combination with SVM in various applications. However, alignment kernels have a crucial drawback in that they scale poorly due to their quadratic computation complexity in the number of input strings, which limits large-scale applications in practice. We address this need by presenting the first approximation for string alignment kernels, which we call space-efficient feature maps for edit distance with moves (SFMEDM), by leveraging a metric embedding named edit sensitive parsing (ESP) and feature maps (FMs) of random Fourier features (RFFs) for large-scale string analyses. The original FMs for RFFs consume a huge amount of memory proportional to the dimension d of input vectors and the dimension D of output vectors, which prohibits its large-scale applications. We present novel space-efficient feature maps (SFMs) of RFFs for a space reduction from O(dD) of the original FMs to O(d) of SFMs with a theoretical guarantee with respect to concentration bounds. We experimentally test SFMEDM on its ability to learn SVM for large-scale string classifications with various massive string data, and we demonstrate the superior performance of SFMEDM with respect to prediction accuracy, scalability and computation efficiency.Comment: Full version for ICDM'19 pape

Multipurpose High Frequency Electron Spin Resonance Spectrometer for Condensed Matter Research

We describe a quasi-optical multifrequency ESR spectrometer operating in the 75-225 GHz range and optimized at 210 GHz for general use in condensed matter physics, chemistry and biology. The quasi-optical bridge detects the change of mm wave polarization at the ESR. A controllable reference arm maintains a mm wave bias at the detector. The attained sensitivity of 2x10^10 spin/G/(Hz)1/2, measured on a dilute Mn:MgO sample in a non-resonant probe head at 222.4 GHz and 300 K, is comparable to commercial high sensitive X band spectrometers. The spectrometer has a Fabry-Perot resonator based probe head to measure aqueous solutions, and a probe head to measure magnetic field angular dependence of single crystals. The spectrometer is robust and easy to use and may be operated by undergraduate students. Its performance is demonstrated by examples from various fields of condensed matter physics.Comment: submitted to Journal of Magnetic Resonanc

Neutron studies of Na-ion battery materials

The relative vast abundance and more equitable global distribution of terrestrial sodium makes sodium-ion batteries (NIBs) potentially cheaper and more sustainable alternatives to commercial lithium-ion batteries (LIBs). However, the practical capacities and cycle lives of NIBs at present do not match those of LIBs and have therefore hindered their progress to commercialisation. The present drawback of NIB technology stems largely from the electrode materials and their associated Na+ion storage mechanisms. Increased understanding of the electrochemical storage mechanisms and kinetics is therefore vital for the development of current and novel materials to realise the commercial NIB. In contrast to x-ray techniques, the non-dependency of neutron scattering on the atomic number of elements (Z) can substantially increase the scattering contrast of small elements such as sodium and carbon, making neutron techniques powerful for the investigation of NIB electrode materials. Moreover, neutrons are far more penetrating which enables more complex sample environments including in situ and operando studies. Here, we introduce the theory of, and review the use of, neutron diffraction and quasi-elastic neutron scattering, to investigate the structural and dynamic properties of electrode and electrolyte materials for NIBs. To improve our understanding of the actual sodium storage mechanisms and identify intermediate stages during charge/discharge, ex situ, in situ, and operando neutron experiments are required. However, to date there are few studies where operando experiments are conducted during electrochemical cycling. This highlights an opportunity for research to elucidate the operating mechanisms within NIB materials that are under much debate at present

Neutron studies of Na-ion battery materials

The relative vast abundance and more equitable global distribution of terrestrial sodium makes sodium-ion batteries (NIBs) potentially cheaper and more sustainable alternatives to commercial lithium-ion batteries (LIBs). However, the practical capacities and cycle lives of NIBs at present do not match those of LIBs and have therefore hindered their progress to commercialisation. The present drawback of NIB technology stems largely from the electrode materials and their associated Na+ion storage mechanisms. Increased understanding of the electrochemical storage mechanisms and kinetics is therefore vital for the development of current and novel materials to realise the commercial NIB. In contrast to x-ray techniques, the non-dependency of neutron scattering on the atomic number of elements (Z) can substantially increase the scattering contrast of small elements such as sodium and carbon, making neutron techniques powerful for the investigation of NIB electrode materials. Moreover, neutrons are far more penetrating which enables more complex sample environments including in situ and operando studies. Here, we introduce the theory of, and review the use of, neutron diffraction and quasi-elastic neutron scattering, to investigate the structural and dynamic properties of electrode and electrolyte materials for NIBs. To improve our understanding of the actual sodium storage mechanisms and identify intermediate stages during charge/discharge, ex situ, in situ, and operando neutron experiments are required. However, to date there are few studies where operando experiments are conducted during electrochemical cycling. This highlights an opportunity for research to elucidate the operating mechanisms within NIB materials that are under much debate at present

A paradox of syntactic priming: why response tendencies show priming for passives, and response latencies show priming for actives

Speakers tend to repeat syntactic structures across sentences, a phenomenon called syntactic priming. Although it has been suggested that repeating syntactic structures should result in speeded responses, previous research has focused on effects in response tendencies. We investigated syntactic priming effects simultaneously in response tendencies and response latencies for active and passive transitive sentences in a picture description task. In Experiment 1, there were priming effects in response tendencies for passives and in response latencies for actives. However, when participants' pre-existing preference for actives was altered in Experiment 2, syntactic priming occurred for both actives and passives in response tendencies as well as in response latencies. This is the first investigation of the effects of structure frequency on both response tendencies and latencies in syntactic priming. We discuss the implications of these data for current theories of syntactic processing

Icing: Large-scale inference of immunoglobulin clonotypes

Immunoglobulin (IG) clonotype identification is a fundamental open question in modern immunology. An accurate description of the IG repertoire is crucial to understand the variety within the immune system of an individual, potentially shedding light on the pathogenetic process. Intrinsic IG heterogeneity makes clonotype inference an extremely challenging task, both from a computational and a biological point of view. Here we present icing, a framework that allows to reconstruct clonal families also in case of highly mutated sequences. icing has a modular structure, and it is designed to be used with large next generation sequencing (NGS) datasets, a technology which allows the characterisation of large-scale IG repertoires. We extensively validated the framework with clustering performance metrics on the results in a simulated case. icing is implemented in Python, and it is publicly available under FreeBSD licence at https://github.com/slipguru/icing