On partial order semantics for SAT/SMT-based symbolic encodings of weak memory concurrency

Concurrent systems are notoriously difficult to analyze, and technological advances such as weak memory architectures greatly compound this problem. This has renewed interest in partial order semantics as a theoretical foundation for formal verification techniques. Among these, symbolic techniques have been shown to be particularly effective at finding concurrency-related bugs because they can leverage highly optimized decision procedures such as SAT/SMT solvers. This paper gives new fundamental results on partial order semantics for SAT/SMT-based symbolic encodings of weak memory concurrency. In particular, we give the theoretical basis for a decision procedure that can handle a fragment of concurrent programs endowed with least fixed point operators. In addition, we show that a certain partial order semantics of relaxed sequential consistency is equivalent to the conjunction of three extensively studied weak memory axioms by Alglave et al. An important consequence of this equivalence is an asymptotically smaller symbolic encoding for bounded model checking which has only a quadratic number of partial order constraints compared to the state-of-the-art cubic-size encoding.Comment: 15 pages, 3 figure

Trends and transitions in the institutional environment for public and private science

The last quarter-century bore witness to a sea change in academic involvement with commerce. Widespread university-based efforts to identify, manage, and market intellectual property (IP) have accompanied broad shifts in the relationship between academic and proprietary approaches to the dissemination and use of science and engineering research. Such transformations are indicators of institutional changes at work in the environment faced by universities. This paper draws upon a fifteen-year panel (1981–1995) of university-level data for 87 research-intensive US campuses in order to document trends and transitions in relationships among multiple indicators of academic and commercial engagement. The institutional environment for public and private science is volatile, shifting in fits and starts from a situation conducive to organizational learning through high volume patenting to a more challenging arrangement that links indiscriminate pursuit of IP with declines in both the volume and impact of academic science. The pattern and timing of these transitions may support an enduring system of stratification that offers increasing returns to first-movers while limiting the opportunities available to universities that are later entrants to the commercial realm. Unpacking the systematic effects of university research commercialization requires focused attention on the sources and trajectories of profound institutional change.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42839/1/10734_2004_Article_2916.pd

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain–gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials