Heterogeneous Convergence

We use U.S. county-level data containing 3,058 cross-sectional observations and 41 conditioning variables to study economic growth and explore possible heterogeneity in growth determination across 32 individual states. Using a 3SLS-IV estimation method, we find that all statistically significant convergence rates (for 32 individual states) are above 2 percent, with an average of 8.1 percent. For 7 states the convergence rate can be rejected as identical to at least one other state’s convergence rate with 95 percent confidence. Convergence rates are negatively correlated with initial income. The size of government at all levels of decentralization is either unproductive or negatively correlated with growth. Educational attainment has a non-linear relationship with growth. The size of the finance, insurance and real estate, and entertainment industries are positively correlated with growth, while the size of the education industry is negatively correlated with growth. Heterogeneity in the effects of balanced growth path determinants across individual states is harder to detect than in convergence rates.Economic Growth, Conditional Convergence, County Level Data

Sigma Convergence Versus Beta Convergence: Evidence from U.S. County-Level Data

This note outlines (i) why σ-convergence may not accompany β-convergence; (ii) cites evidence of β-convergence in the U.S.; (iii) demonstrates that σ-convergence does not hold across the U.S., or within most U.S. states; and (iv) demonstrates the robustness of this finding to increases in mean income. The distributions of shocks appear important towards accounting for income disparity.σ-convergence, β-convergence, Solow growth model, speed of convergence

Heterogeneity in Convergence Rates and Income Determination across U.S. States: Evidence from County-Level Data

We utilize county-level data to explore growth determination in the U.S. and possible heterogeneity in growth determination across individual states. The data includes over 3,000 cross-sectional observations and 39 demographic control variables. We use a consistent two stage least squares estimation procedure. (We report OLS estimates as well.) The estimated convergence rate across the U.S. is about 7 percent per year – higher than the 2 percent normally found with OLS in cross-country, U.S. state, and European region samples. Estimated convergence rates for 32 individual states are above 2 percent with an average of 8.1 percent. For 29 states the convergence rate is above 2 percent with 95 percent confidence. For seven states the convergence rate can be rejected as identical to at least one other state’s convergence rate with 95 percent confidence. In examining the determinants of balanced growth path heights, we find that government at all levels of decentralization is negatively correlated with economic growth. Educational attainment of a population has a non-linear relationship with economic growth according to our estimates: growth is positively related to high-school degree attainment, seemingly unrelated to obtaining some college education, and then positively related to four-year degree or more attainment. Also, finance, insurance and real estate industry and entertainment industry are positively correlated with growth, while education industry is negatively correlated with growth. Heterogeneity in the effects of balanced growth path determinants across individual states is much harder to detect (or dismiss) than in convergence rates.Economic Growth, Income Convergence, Solow Growth Model, Balanced Growth Path, Heterogeneity in Convergence, Education and Growth, Size of Government and Growth, Consistent Estimation, County-Level Data

Engineering stochasticity in gene expression

Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise

Wiki surveys: Open and quantifiable social data collection

In the social sciences, there is a longstanding tension between data collection methods that facilitate quantification and those that are open to unanticipated information. Advances in technology now enable new, hybrid methods that combine some of the benefits of both approaches. Drawing inspiration from online information aggregation systems like Wikipedia and from traditional survey research, we propose a new class of research instruments called wiki surveys. Just as Wikipedia evolves over time based on contributions from participants, we envision an evolving survey driven by contributions from respondents. We develop three general principles that underlie wiki surveys: they should be greedy, collaborative, and adaptive. Building on these principles, we develop methods for data collection and data analysis for one type of wiki survey, a pairwise wiki survey. Using two proof-of-concept case studies involving our free and open-source website www.allourideas.org, we show that pairwise wiki surveys can yield insights that would be difficult to obtain with other methods.Comment: 24 pages, 8 figures, 1 tabl

Deoxyribozymes that recode sequence information

Allosteric nucleic acid ligases have been used previously to transform analyte-binding into the formation of oligonucleotide templates that can be amplified and detected. We have engineered binary deoxyribozyme ligases whose two components are brought together by bridging oligonucleotide effectors. The engineered ligases can ‘read’ one sequence and then ‘write’ (by ligation) a separate, distinct sequence, which can in turn be uniquely amplified. The binary deoxyribozymes show great specificity, can discriminate against a small number of mutations in the effector, and can read and recode DNA information with high fidelity even in the presence of excess obscuring genomic DNA. In addition, the binary deoxyribozymes can read non-natural nucleotides and write natural sequence information. The binary deoxyribozyme ligases could potentially be used in a variety of applications, including the detection of single nucleotide polymorphisms in genomic DNA or the identification of short nucleic acids such as microRNAs

Aptamer-Targeted Gold Nanoparticles As Molecular-Specific Contrast Agents for Reflectance Imaging

Targeted metallic nanoparticles have shown potential as a platform for development of molecular-specific contrast agents. Aptamers have recently been demonstrated as ideal candidates for molecular targeting applications. In this study, we investigated the development of aptamer-based gold nanoparticles as contrast agents, using aptamers as targeting agents and gold nanoparticles as imaging agents. We devised a novel conjugation approach using an extended aptamer design where the extension is complementary to an oligonucleotide sequence attached to the surface of the gold nanoparticles. The chemical and optical properties of the aptamer−gold conjugates were characterized using size measurements and oligonucleotide quantitation assays. We demonstrate this conjugation approach to create a contrast agent designed for detection of prostate-specific membrane antigen (PSMA), obtaining reflectance images of PSMA(+) and PSMA(−) cell lines treated with the anti-PSMA aptamer−gold conjugates. This design strategy can easily be modified to incorporate multifunctional agents as part of a multimodal platform for reflectance imaging applications

How did a Housing First intervention improve health and social outcomes among homeless adults with mental illness in Toronto? Two-year outcomes from a randomised trial.

OBJECTIVES: We studied the impact of a Housing First (HF) intervention on housing, contact with the justice system, healthcare usage and health outcomes among At Home/Chez Soi randomised trial participants in Toronto, a city with an extensive service network for social and health services for individuals who are experiencing homelessness and mental illness. METHODS: Participants identified as high needs were randomised to receive either the intervention which provided them with housing and supports by an assertive community treatment team (HF+ACT) or treatment as usual (TAU). Participants (N=197) had in-person interviews every 3 months for 2 years. RESULTS: The HF+ACT group spent more time stably housed compared to the TAU group with the mean difference between the groups of 45.8% (95% CI 37.1% to 54.4%, p<0.0001). Accounting for baseline differences, HF+ACT group showed significant improvements over TAU group for community functioning, selected quality-of-life subscales and arrests at some time points during follow-up. No differences between HF+ACT and TAU groups over the follow-up were observed for health service usage, community integration and substance use. CONCLUSIONS: HF for individuals with high levels of need increased housing stability and selected health and justice outcomes over 2 years in a city with many social and health services. TRIAL REGISTRATION NUMBER: ISRCTN42520374

Optimized pulses for the control of uncertain qubits

Constructing high-fidelity control fields that are robust to control, system, and/or surrounding environment uncertainties is a crucial objective for quantum information processing. Using the two-state Landau-Zener model for illustrative simulations of a controlled qubit, we generate optimal controls for \pi/2- and \pi-pulses, and investigate their inherent robustness to uncertainty in the magnitude of the drift Hamiltonian. Next, we construct a quantum-control protocol to improve system-drift robustness by combining environment-decoupling pulse criteria and optimal control theory for unitary operations. By perturbatively expanding the unitary time-evolution operator for an open quantum system, previous analysis of environment-decoupling control pulses has calculated explicit control-field criteria to suppress environment-induced errors up to (but not including) third order from \pi/2- and \pi-pulses. We systematically integrate this criteria with optimal control theory, incorporating an estimate of the uncertain parameter, to produce improvements in gate fidelity and robustness, demonstrated via a numerical example based on double quantum dot qubits. For the qubit model used in this work, post facto analysis of the resulting controls suggests that realistic control-field fluctuations and noise may contribute just as significantly to gate errors as system and environment fluctuations.Comment: 38 pages, 15 figures, RevTeX 4.1, minor modifications to the previous versio