Arrays and References in Resource Aware ML

This article introduces a technique to accurately perform static prediction of resource usage for ML-like functional programs with references and arrays. Previous research successfully integrated the potential method of amortized analysis with a standard type system to automatically derive parametric resource bounds. The analysis is naturally compositional and the resource consumption of functions can be abstracted using potential-annotated types. The soundness theorem of the analysis guarantees that the derived bounds are correct with respect to the resource usage defined by a cost semantics. Type inference can be efficiently automated using off-the-shelf LP solvers, even if the derived bounds are polynomials. However, side effects and aliasing of heap references make it notoriously difficult to derive bounds that depend on mutable structures, such as arrays and references. As a result, existing automatic amortized analysis systems for ML-like programs cannot derive bounds for programs whose resource consumption depends on data in such structures. This article extends the potential method to handle mutable structures with minimal changes to the type rules while preserving the stated advantages of amortized analysis. To do so, we introduce a swap operation for references and arrays that users can use to make programs suitable for automatic analysis. We prove the soundness of the analysis introducing a potential-annotated memory typing, which gathers all unique locations reachable from a reference. Apart from the design of the system, the main contribution is the proof of soundness for the extended analysis system

openWAR: An Open Source System for Evaluating Overall Player Performance in Major League Baseball

Within baseball analytics, there is substantial interest in comprehensive statistics intended to capture overall player performance. One such measure is Wins Above Replacement (WAR), which aggregates the contributions of a player in each facet of the game: hitting, pitching, baserunning, and fielding. However, current versions of WAR depend upon proprietary data, ad hoc methodology, and opaque calculations. We propose a competitive aggregate measure, openWAR, that is based upon public data and methodology with greater rigor and transparency. We discuss a principled standard for the nebulous concept of a "replacement" player. Finally, we use simulation-based techniques to provide interval estimates for our openWAR measure.Comment: 27 pages including supplemen

Bounded Expectations: Resource Analysis for Probabilistic Programs

This paper presents a new static analysis for deriving upper bounds on the expected resource consumption of probabilistic programs. The analysis is fully automatic and derives symbolic bounds that are multivariate polynomials of the inputs. The new technique combines manual state-of-the-art reasoning techniques for probabilistic programs with an effective method for automatic resource-bound analysis of deterministic programs. It can be seen as both, an extension of automatic amortized resource analysis (AARA) to probabilistic programs and an automation of manual reasoning for probabilistic programs that is based on weakest preconditions. As a result, bound inference can be reduced to off-the-shelf LP solving in many cases and automatically-derived bounds can be interactively extended with standard program logics if the automation fails. Building on existing work, the soundness of the analysis is proved with respect to an operational semantics that is based on Markov decision processes. The effectiveness of the technique is demonstrated with a prototype implementation that is used to automatically analyze 39 challenging probabilistic programs and randomized algorithms. Experimental results indicate that the derived constant factors in the bounds are very precise and even optimal for many programs

Title page Regulation of Inflammatory Pain by Inhibition of Fatty Acid Amide Hydrolase (FAAH)

Abstract Although cannabinoids are efficacious in laboratory animal models of inflammatory pain, their established cannabimimetic actions diminish enthusiasm for their therapeutic development. Conversely, fatty acid amide hydrolase (FAAH), the chief catabolic enzyme regulating the endogenous cannabinoid N-arachidonoylethanolamine (anandamide), has emerged as an attractive target to treat pain and other conditions. Here, we tested WIN55,212-2, a cannabinoid receptor agonist, as well as genetic deletion or pharmacological inhibition of FAAH in the lipopolysaccharide (LPS) mouse model of inflammatory pain. WIN55,212 significantly reduced edema and hotplate hyperalgesia caused by LPS infusion into the hind paws, though the mice also displayed analgesia and other CNS effects. FAAH (-/-) mice exhibited reduced paw edema and hyperalgesia in this model, without apparent cannabimimetic effects. Transgenic mice expressing FAAH exclusively on neurons continued to display the anti-edematous, but not the anti-hyperalgesic, phenotype. The CB 2 receptor antagonist, SR144528, blocked this non-neuronal, anti-inflammatory phenotype, and the CB 1 receptor antagonist, rimonabant, blocked the anti-hyperalgesic phenotype. The FAAH inhibitor, URB597 attenuated the development of LPS-induced paw edema and reversed LPS-induced hyperalgesia through respective CB 2 and CB 1 receptor mechanisms of action. However, the TRPV1 receptor antagonist, capsazepine, did not affect either the anti-hyperalgesic or antiedematous effects of URB597. Finally, URB597 attenuated levels of the pro-inflammatory cytokines IL-1β and TNF-α in LPS-treated paws. These findings demonstrate that simultaneous elevations in non-neuronal and neuronal endocannabinoid signaling are possible through inhibition of a single enzymatic target, thereby offering a potentially powerful strategy to treat chronic inflammatory pain syndromes that operate at multiple levels of anatomical integration

Inhibitory Control Deficits Associated with Upregulation of CB1R in the HIV-1 Tat Transgenic Mouse Model of Hand

In the era of combined antiretroviral therapy, HIV-1 infected individuals are living longer lives; however, longevity is met with an increasing number of HIV-1 associated neurocognitive disorders (HAND) diagnoses. The transactivator of transcription (Tat) is known to mediate the neurotoxic effects in HAND by acting directly on neurons and also indirectly via its actions on glia. The Go/No-Go (GNG) task was used to examine HAND in the Tat transgenic mouse model. The GNG task involves subjects discriminating between two stimuli sets in order to determine whether or not to inhibit a previously trained response. Data reveal inhibitory control deficits in female Tat(+) mice (p = .048) and an upregulation of cannabinoid type 1 receptors (CB1R) in the infralimbic (IL) cortex in the same female Tat(+) group (p < .05). A significant negative correlation was noted between inhibitory control and IL CB1R expression (r = -.543, p = .045), with CB1R expression predicting 30% of the variance of inhibitory control (R(2) = .295, p = .045). Furthermore, there was a significant increase in spontaneous excitatory postsynaptic current (sEPSC) frequencies in Tat(+) compared to Tat(-) mice (p = .008, across sexes). The increase in sEPSC frequency was significantly attenuated by bath application of PF3845, a fatty acid amide hydrolase (FAAH) enzyme inhibitor (p < .001). Overall, the GNG task is a viable measure to assess inhibitory control deficits in Tat transgenic mice and results suggest a potential therapeutic treatment for the observed deficits with drugs which modulate endocannabinoid enzyme activity. Graphical Abstract Results of the Go/No-Go operant conditioning task reveal inhibitory control deficits in female transgenic Tat(+) mice without significantly affecting males. The demonstrated inhibitory control deficits appear to be associated with an upregulation of cannabinoid type 1 receptors (CB1R) in the infralimbic (IL) cortex in the same female Tat(+) group

A novel fluorophosphonate inhibitor of the biosynthesis of the endocannabinoid 2-arachidonoylglycerol with potential anti-obesity effects

Background and Purpose The development of potent and selective inhibitors of the biosynthesis of the endocannabinoid 2-arachidonoylglycerol (2-AG) via DAG lipases (DAGL) α and β is just starting to be considered as a novel and promising source of pharmaceuticals for the treatment of disorders that might benefit from a reduction in endocannabinoid tone, such as hyperphagia in obese subjects. Experimental Approach Three new fluorophosphonate compounds O-7458, O-7459 and O-7460 were synthesized and characterized in various enzymatic assays. The effects of O-7460 on high-fat diet intake were tested in mice. Key Results Of the new compounds, O-7460 exhibited the highest potency (IC50 = 690 nM) against the human recombinant DAGLα, and selectivity (IC50 > 10 μM) towards COS-7 cell and human monoacylglycerol lipase (MAGL), and rat brain fatty acid amide hydrolase. Competitive activity-based protein profiling confirmed that O-7460 inhibits mouse brain MAGL only at concentrations ≥10 μM, and showed that this compound has only one major ‘off-target’, that is, the serine hydrolase KIAA1363. O-7460 did not exhibit measurable affinity for human recombinant CB1 or CB2 cannabinoid receptors (Ki > 10 μM). In mouse neuroblastoma N18TG2 cells stimulated with ionomycin, O-7460 (10 μM) reduced 2-AG levels. When administered to mice, O-7460 dose-dependently (0–12 mg·kg−1, i.p.) inhibited the intake of a high-fat diet over a 14 h observation period, and, subsequently, slightly but significantly reduced body weight. Conclusions and Implications O-7460 might be considered a useful pharmacological tool to investigate further the role played by 2-AG both in vitro and in vivo under physiological as well as pathological conditions