Probabilistic Hybrid Action Models for Predicting Concurrent Percept-driven Robot Behavior

This article develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern percept-driven robot plans. PHAMs represent aspects of robot behavior that cannot be represented by most action models used in AI planning: the temporal structure of continuous control processes, their non-deterministic effects, several modes of their interferences, and the achievement of triggering conditions in closed-loop robot plans. The main contributions of this article are: (1) PHAMs, a model of concurrent percept-driven behavior, its formalization, and proofs that the model generates probably, qualitatively accurate predictions; and (2) a resource-efficient inference method for PHAMs based on sampling projections from probabilistic action models and state descriptions. We show how PHAMs can be applied to planning the course of action of an autonomous robot office courier based on analytical and experimental results

Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative disease of the human motor neuron system, where variability in progression rate limits clinical trial efficacy. Therefore, better prognostication will facilitate therapeutic progress. In this study, we investigated the potential of plasma cell-free microRNAs (miRNAs) as ALS prognostication biomarkers in 252 patients with detailed clinical phenotyping. First, we identified, in a longitudinal cohort, miRNAs whose plasma levels remain stable over the course of disease. Next, we showed that high levels of miR-181, a miRNA enriched in neurons, predicts a greater than two-fold risk of death in independent discovery and replication cohorts (126 and 122 patients, respectively). miR-181 performance is similar to neurofilament light chain (NfL), and when combined together, miR-181 + NfL establish a novel RNA–protein biomarker pair with superior prognostication capacity. Therefore, plasma miR-181 alone and a novel miRNA–protein biomarker approach, based on miR-181 + NfL, boost precision of patient stratification. miR-181-based ALS biomarkers encourage additional validation and might enhance the power of clinical trials

Evaluation of fatigue damage in steel structural components by magnetoelastic Barkhausen signal analysis

This paper is concerned with using a magnetic technique for the evaluation of fatigue damage in steel structural components. It is shown that Barkhausen effect measurements can be used to indicate impending failure due to fatigue under certain conditions. The Barkhausen signal amplitude is known to be highly sensitive to changes in density and distribution of dislocations in materials. The sensitivity of Barkhausen signal amplitude to fatigue damage has been studied in the low‐cycle fatigue regime using smooth tensile specimens of a medium strength steel. The Barkhausen measurements were taken at depths of penetration of 0.02, 0.07, and 0.2 mm. It was found that changes in magnetic properties are sensitive to microstructural changes taking place at the surface of the material throughout the fatigue life. The changes in the Barkhausen signals have been attributed to distribution of dislocations in stage I and stage II of fatigue life and the formation of a macrocrack in the final stage of fatigue

DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups

We strive to find contexts (i.e., subgroups of entities) under which exceptional (dis-)agreement occurs among a group of individuals , in any type of data featuring individuals (e.g., parliamentarians , customers) performing observable actions (e.g., votes, ratings) on entities (e.g., legislative procedures, movies). To this end, we introduce the problem of discovering statistically significant exceptional contextual intra-group agreement patterns. To handle the sparsity inherent to voting and rating data, we use Krippendorff's Alpha measure for assessing the agreement among individuals. We devise a branch-and-bound algorithm , named DEvIANT, to discover such patterns. DEvIANT exploits both closure operators and tight optimistic estimates. We derive analytic approximations for the confidence intervals (CIs) associated with patterns for a computationally efficient significance assessment. We prove that these approximate CIs are nested along specialization of patterns. This allows to incorporate pruning properties in DEvIANT to quickly discard non-significant patterns. Empirical study on several datasets demonstrates the efficiency and the usefulness of DEvIANT. Technical Report Associated with the ECML/PKDD 2019 Paper entitled: "DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups"

Logic, Probability and Action: A Situation Calculus Perspective

The unification of logic and probability is a long-standing concern in AI, and more generally, in the philosophy of science. In essence, logic provides an easy way to specify properties that must hold in every possible world, and probability allows us to further quantify the weight and ratio of the worlds that must satisfy a property. To that end, numerous developments have been undertaken, culminating in proposals such as probabilistic relational models. While this progress has been notable, a general-purpose first-order knowledge representation language to reason about probabilities and dynamics, including in continuous settings, is still to emerge. In this paper, we survey recent results pertaining to the integration of logic, probability and actions in the situation calculus, which is arguably one of the oldest and most well-known formalisms. We then explore reduction theorems and programming interfaces for the language. These results are motivated in the context of cognitive robotics (as envisioned by Reiter and his colleagues) for the sake of concreteness. Overall, the advantage of proving results for such a general language is that it becomes possible to adapt them to any special-purpose fragment, including but not limited to popular probabilistic relational models

A proposal for new diagnostic criteria for ALS

© 2020 The Authors. Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Sclerosis (ALS) were initially published in 1994 and revised in 2000. Criteria were established because the ‘‘variety of clinical features which may be present early in the course of ALS makes absolute diagnosis difficult and compromises the certainty of diagnosis for clinical research purposes and therapeutic trials.” The original criteria described 4 categories of disease: Definite, Probable, Possible, and Suspected ALS. However, subsequent clinical experience made it clear that non-Definite categories included patients who would ultimately die of ALS with a high degree of clinical certainty.info:eu-repo/semantics/publishedVersio

A comparison of in vitro properties of resting SOD1 transgenic microglia reveals evidence of reduced neuroprotective function

<p>Abstract</p> <p>Background</p> <p>Overexpression of mutant copper/zinc superoxide dismutase (<it>SOD1</it>) in rodents has provided useful models for studying the pathogenesis of amyotrophic lateral sclerosis (ALS). Microglia have been shown to contribute to ALS disease progression in these models, although the mechanism of this contribution remains to be elucidated. Here, we present the first evidence of the effects of overexpression of mutant (TG G93A) and wild type (TG WT) human <it>SOD1 </it>transgenes on a set of functional properties of microglia relevant to ALS progression, including expression of integrin β-1, spreading and migration, phagocytosis of apoptotic neuronal cell debris, and intracellular calcium changes in response to an inflammatory stimulus.</p> <p>Results</p> <p>TG SOD1 G93A but not TG SOD1 WT microglia had lower expression levels of the cell adhesion molecule subunit integrin β-1 than their NTG control cells [NTG (G93A) and NTG (WT), respectively, 92.8 ± 2.8% on TG G93A, 92.0 ± 6.6% on TG WT, 100.0 ± 1.6% on NTG (G93A), and 100.0 ± 2.7% on NTG (WT) cells], resulting in decreased spreading ability, with no effect on ability to migrate. Both TG G93A and TG WT microglia had reduced capacity to phagocytose apoptotic neuronal cell debris (13.0 ± 1.3% for TG G93A, 16.5 ± 1.9% for TG WT, 28.6 ± 1.8% for NTG (G93A), and 26.9 ± 2.8% for NTG (WT) cells). Extracellular stimulation of microglia with ATP resulted in smaller increase in intracellular free calcium in TG G93A and TG WT microglia relative to NTG controls (0.28 ± 0.02 μM for TG G93A, 0.24 ± 0.03 μM for TG WT, 0.39 ± 0.03 μM for NTG (G93A), and 0.37 ± 0.05 μM for NTG (WT) microglia).</p> <p>Conclusions</p> <p>These findings indicate that, under resting conditions, microglia from mutant <it>SOD1 </it>transgenic mice have a reduced capacity to elicit physiological responses following tissue disturbances and that higher levels of stimulatory signals, and/or prolonged stimulation may be necessary to initiate these responses. Overall, resting mutant <it>SOD1</it>-overexpressing microglia may have reduced capacity to function as sensors of disturbed tissue/cellular homeostasis in the CNS and thus have reduced neuroprotective function.</p