This study extends a neoclassical growth model to include the accumulation of physical capital and energy consumption within a panel of fifty states (plus the District of Columbia) in the U.S. The ...theoretical model allows us to examine the implications for convergence in economic growth and energy intensity. From the theoretical model, we formulate an empirical approach using a dynamic panel model that is estimated using a general method of moments framework to test the conditional rates of convergence. The empirical results indicate convergence in energy intensity, and our estimates accurately predict both the growth in and convergence of energy intensity across our entire sample. Consistent with other findings in the literature, our results imply that energy use, over the past four decades, plays a small and positive role in state-level, per capita economic growth and convergence. Based on these results, we discuss policy implications for state-level income growth and energy consumption.
•Study develops an economic growth model that incorporates energy usage.•The empirical model is derived directly from the theoretical model.•The empirical framework is formulated as a dynamic panel data model.•Study uses a two-step GMM model to estimate conditional rates of convergence.•The estimates indicate robust convergence in energy intensity.•Energy usage plays a small but positive role in economic convergence.
Societal Impact Statement
Therapeutic protein production in plants is an area of great potential for increasing and improving the production of proteins for the treatment or prevention of disease in ...humans and other animals. There are a number of key benefits of this technique for scientists and society, as well as regulatory challenges that need to be overcome by policymakers. Increased public understanding of the costs and benefits of therapeutic protein production in plants will be instrumental in increasing the acceptance, and thus the medical and veterinary impact, of this approach.
Summary
Therapeutic recombinant proteins are a powerful tool for combating many diseases which have previously been hard to treat. The most utilized expression systems are Chinese Hamster Ovary cells and Escherichia coli, but all available expression systems have strengths and weaknesses regarding development time, cost, protein size, yield, growth conditions, posttranslational modifications and regulatory approval. The plant industry is well established and growing and harvesting crops is easy and affordable using current infrastructure. Growth conditions are generally simple: sunlight, water, and the addition of cheap, available fertilizers. There are multiple options for plant expression systems, including species, genetic constructs and protein targeting, each best suited to a particular type of therapeutic protein production. Transient expression systems provide a mechanism to rapidly transfect plants and produce therapeutic protein in a matter of weeks, rather than the months it can take for many competing expression systems, while proteins targeted to cereal seeds can be harvested, stored and potentially purified much more easily than in competing systems. Current challenges for plant expression systems include a lack of regulatory approval, environmental containment concerns and nonhuman glycosylation, which may limit the scope of the type of therapeutic proteins that can be manufactured in plants. The specific strengths of plant expression systems could facilitate the production of certain therapeutic proteins quickly and cheaply in the near future.
Therapeutic protein production in plants is an area of great potential for increasing and improving the production of proteins for the treatment or prevention of disease in humans and other animals. There are a number of key benefits of this technique for scientists and society, as well as regulatory challenges that need to be overcome by policymakers. Increased public understanding of the costs and benefits of therapeutic protein production in plants will be instrumental in increasing the acceptance, and thus the medical and veterinary impact, of this approach.
Abstract
We benchmark the decoherence of superconducting transmon qubits to examine the temporal stability of energy relaxation, dephasing, and qubit transition frequency. By collecting statistics ...during measurements spanning multiple days, we find the mean parameters
$$\overline {T_1}$$
T
1
¯
= 49 μs and
$$\overline {T_2^ \ast }$$
T
2
*
¯
= 95 μs; however, both of these quantities fluctuate, explaining the need for frequent re-calibration in qubit setups. Our main finding is that fluctuations in qubit relaxation are local to the qubit and are caused by instabilities of near-resonant two-level-systems (TLS). Through statistical analysis, we determine sub-millihertz switching rates of these TLS and observe the coherent coupling between an individual TLS and a transmon qubit. Finally, we find evidence that the qubit’s frequency stability produces a 0.8 ms limit on the pure dephasing which we also observe. These findings raise the need for performing qubit metrology to examine the reproducibility of qubit parameters, where these fluctuations could affect qubit gate fidelity.
We demonstrate how a single-crystal to single-crystal transformation resulting from bridging-linker replacement is possible in extended 2D and 3D metal–organic frameworks (MOFs) by introducing ...pillared paddlewheel MOF structures into a solution containing dipyridyl linkers. No lateral movement of the layers was observed during this transformation, creating a templating effect from the “parent” structure to the “daughter” structure. A previously unattainable structure was obtained by a two-step synthetic method utilizing the bridging-linker replacement transformation method. Additionally, a bridging-linker insertion was observed when excess linker was used with the 2D MOF structure, inducing an overall 2D to 3D transformation.
This paper offers an accessible discussion of graphical causal models and how such a framework can be used to help identify causal relations. A graphical causal model represents a researcher's ...qualitative assumptions. As a result of the credibility revolution, there is growing interest to properly estimate cause-and-effect relationships. Using several examples, we illustrate how graphical models can and cannot be used to identify causation from observational data. Further, we offer a replication of a previous study that explored college enrolment by high school seniors who were eligible for student aid. From the original study, we use a graphical causal model to motivate the quantitative and qualitative modelling assumptions. Using a similar difference-in-difference approach based on propensity score matching, we estimate a smaller average treatment effect than the original study. The smaller estimated effect arguably stems from the graphical causal model's delineation of the original model specification.
We previously reported decreased transfusions and donor exposures in preterm infants randomized to Darbepoetin (Darbe) or erythropoietin (Epo) compared with placebo. As these ...erythropoiesis-stimulating agents (ESAs) have shown promise as neuroprotective agents, we hypothesized improved neurodevelopmental outcomes at 18 to 22 months among infants randomized to receive ESAs.
We performed a randomized, masked, multicenter study comparing Darbe (10 μg/kg, 1×/week subcutaneously), Epo (400 U/kg, 3×/week subcutaneously), and placebo (sham dosing 3×/week) given through 35 weeks' postconceptual age, with transfusions administered according to a standardized protocol. Surviving infants were evaluated at 18 to 22 months' corrected age using the Bayley Scales of Infant Development III. The primary outcome was composite cognitive score. Assessments of object permanence, anthropometrics, cerebral palsy, vision, and hearing were performed.
Of the original 102 infants (946 ± 196 g, 27.7 ± 1.8 weeks' gestation), 80 (29 Epo, 27 Darbe, 24 placebo) returned for follow-up. The 3 groups were comparable for age at testing, birth weight, and gestational age. After adjustment for gender, analysis of covariance revealed significantly higher cognitive scores among Darbe (96.2 ± 7.3; mean ± SD) and Epo recipients (97.9 ± 14.3) compared with placebo recipients (88.7 ± 13.5; P = .01 vs ESA recipients) as was object permanence (P = .05). No ESA recipients had cerebral palsy, compared with 5 in the placebo group (P < .001). No differences among groups were found in visual or hearing impairment.
Infants randomized to receive ESAs had better cognitive outcomes, compared with placebo recipients, at 18 to 22 months. Darbe and Epo may prove beneficial in improving long-term cognitive outcomes of preterm infants.
Noise and decoherence due to spurious two-level systems located at material interfaces are long-standing issues for solid-state quantum devices. Efforts to mitigate the effects of two-level systems ...have been hampered by a lack of knowledge about their chemical and physical nature. Here, by combining dielectric loss, frequency noise and on-chip electron spin resonance measurements in superconducting resonators, we demonstrate that desorption of surface spins is accompanied by an almost tenfold reduction in the charge-induced frequency noise in the resonators. These measurements provide experimental evidence that simultaneously reveals the chemical signatures of adsorbed magnetic moments and highlights their role in generating charge noise in solid-state quantum devices.
Signs and symptoms of congestion are the most common cause for hospitalization for heart failure (HHF). The clinical course and prognostic value of congestion during HHF has not been systemically ...characterized.
A post hoc analysis was performed of the placebo group (n = 2061) of the EVEREST trial, which enrolled patients within 48 h of admission (median ~24 h) for worsening HF with an EF ≤ 40% and two or more signs or symptoms of fluid overload dyspnoea, oedema, or jugular venous distension (JVD) for a median follow-up of 9.9 months. Clinician-investigators assessed patients daily for dyspnoea, orthopnoea, fatigue, rales, pedal oedema, and JVD and rated signs and symptoms on a standardized 4-point scale ranging from 0 to 3. A modified composite congestion score (CCS) was calculated by summing the individual scores for orthopnoea, JVD, and pedal oedema. Endpoints were HHF, all-cause mortality (ACM), and ACM + HHF. Multivariable Cox regression models were used to evaluate the risk of CCS at discharge on outcomes at 30 days and for the entire follow-up period. The mean CCS obtained after initial therapy decreased from the mean ± SD of 4.07 ± 1.84 and the median (25th, 75th) of 4 (3, 5) at baseline to 1.11 ± 1.42 and 1 (0, 2) at discharge. At discharge, nearly three-quarters of study participants had a CCS of 0 or 1 and fewer than 10% of patients had a CCS >3. B-type natriuretic peptide (BNP) and amino terminal-proBNP, respectively, decreased from 734 (313, 1523) pg/mL and 4857 (2251, 9642) pg/mL at baseline to 477 (199, 1079) pg/mL, and 2834 (1218, 6075) pg/mL at discharge/Day 7. A CCS at discharge was associated with increased risk (HR/point CCS, 95% CI) for a subset of endpoints at 30 days (HHF: 1.06, 0.95-1.19; ACM: 1.34, 1.14-1.58; and ACM + HHF: 1.13, 1.03-1.25) and all outcomes for the overall study period (HHF: 1.07, 1.01-1.14; ACM: 1.16, 1.09-1.24; and ACM + HHF 1.11, 1.06-1.17). Patients with a CCS of 0 at discharge experienced HHF of 26.2% and ACM of 19.1% during the follow-up.
Among patients admitted for worsening signs and symptoms of HF and reduced EF, congestion improves substantially during hospitalization in response to standard therapy alone. However, patients with absent or minimal resting signs and symptoms at discharge still experienced a high mortality and readmission rate.
We take advantage of a long panel data set to estimate the relationship between U.S. state-level carbon dioxide (CO2) emissions, economic activity, and other factors. We specify a reduced-form energy ...demand model to account for energy consumption activities that drive energy-related emissions. We contribute to the literature by exploring several spatial panel data models to account for spatial dependence between states. Estimation results and rigorous diagnostic analysis suggest that: (1) economic distance plays a role in intra- and inter-state CO2 emissions; and (2) there are statistically significant, positive economic spillovers and negative price spillovers to state-level emissions.
•We examine how economic activity affects U.S. state-level carbon dioxide emissions.•We use spatial, panel data econometric models to control for spatial dependence.•We test for different types of spatial dependence within the data.•Economic distance affects state-level emissions.•Statistically significant, positive economic and negative price spillovers.
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