Multiparty Session Types as Coherence Proofs

We propose a Curry-Howard correspondence between a language for programming multiparty sessions and a generalisation of Classical Linear Logic (CLL). In this framework, propositions correspond to the local behaviour of a participant in a multiparty session type, proofs to processes, and proof normalisation to executing communications. Our key contribution is generalising duality, from CLL, to a new notion of n-ary compatibility, called coherence. Building on coherence as a principle of compositionality, we generalise the cut rule of CLL to a new rule for composing many processes communicating in a multiparty session. We prove the soundness of our model by showing the admissibility of our new rule, which entails deadlock-freedom via our correspondence

Bioprinted cardiac patch composed of cardiac progenitor cells and extracellular matrix for heart repair and regeneration

Statement of Purpose: The heart has limited capacity for repair after surgery in congenital patients. Human cardiac progenitor cells (hCPCs) have the potential to repair the damaged myocardium by releasing pro-reparative paracrine signals such as growth factors and exosomes. Although clinical trials involving hCPCs have shown functional improvements, the outcomes have been modest, and suffer from limited cell retention and poor functionality. Injectable cardiac extracellular matrix (cECM) has been beneficial in improving adult heart function post-infarct and has been shown to induce hCPCs towards a regenerative phenotype. The inclusion of hCPCs within a 3D cECM scaffold can allow for improved hCPC retention and reparative potential. To this end, we have developed a bioprinted patch composed of both hCPCs and cECM which, when attached epicardially on the damaged myocardium, will allow for cardiac repair in patients through release of paracrine factors. The patch was generated through 3D bioprinting, which allowed for high degrees of material control and tissue specificity for cardiac repair and regeneration

The Impact Of Nurse Practitioner Regulations On Population Access To Care

Background: By 2025, experts estimate a significant shortage of primary care providers in the United States, and expansion of the nurse practitioner (NP) workforce may reduce this burden. However, barriers imposed by state NP regulations could reduce access to primary care. Purpose: The objectives of this study were to examine the association between three levels of NP state practice regulation (independent, minimum restrictive, and most restrictive) and the proportion of the population with a greater than 30-min travel time to a primary care provider using geocoding. Methods: Logistic regression models were conducted to calculate the adjusted odds of having a greater than 30-min drive time. Findings: Compared with the most restrictive NP states, states with independent practice had 19.2% lower odds (p =.001) of a greater than 30-min drive to the closest primary care provider. Discussion: Allowing NPs full autonomy to practice may be a relatively simple policy mechanism for states to improve access to primary care

A performance analysis of prediction intervals for count time series

One of the major motivations for the analysis and modeling of time series data is the forecasting of future outcomes. The use of interval forecasts instead of point forecasts allows us to incorporate the apparent forecast uncertainty. When forecasting count time series, one also has to account for the discreteness of the range, which is done by using coherent prediction intervals (PIs) relying on a count model. We provide a comprehensive performance analysis of coherent PIs for diverse types of count processes. We also compare them to approximate PIs that are computed based on a Gaussian approximation. Our analyses rely on an extensive simulation study. It turns out that the Gaussian approximations do considerably worse than the coherent PIs. Furthermore, special characteristics such as overdispersion, zero inflation, or trend clearly affect the PIs' performance. We conclude by presenting two empirical applications of PIs for count time series: the demand for blood bags in a hospital and the number of company liquidations in Germany