Meta-interpretive learning of higher-order dyadic datalog: predicate invention revisited

Since the late 1990s predicate invention has been under-explored within inductive logic programming due to difficulties in formulating efficient search mechanisms. However, a recent paper demonstrated that both predicate invention and the learning of recursion can be efficiently implemented for regular and context-free grammars, by way of metalogical substitutions with respect to a modified Prolog meta-interpreter which acts as the learning engine. New predicate symbols are introduced as constants representing existentially quantified higher-order variables. The approach demonstrates that predicate invention can be treated as a form of higher-order logical reasoning. In this paper we generalise the approach of meta-interpretive learning (MIL) to that of learning higher-order dyadic datalog programs. We show that with an infinite signature the higher-order dyadic datalog class H2 2 has universal Turing expressivity though H2 2 is decidable given a finite signature. Additionally we show that Knuth–Bendix ordering of the hypothesis space together with logarithmic clause bounding allows our MIL implementation MetagolD to PAC-learn minimal cardinality H2 2 definitions. This result is consistent with our experiments which indicate that MetagolD efficiently learns compact H2 2 definitions involving predicate invention for learning robotic strategies, the East–West train challenge and NELL. Additionally higher-order concepts were learned in the NELL language learning domain. The Metagol code and datasets described in this paper have been made publicly available on a website to allow reproduction of results in this paper

An Evolutionary Algorithm for Discovering Multi-Relational Association Rules in the Semantic Web

International audienceIn the Semantic Web context, OWL ontologies represent the conceptualization of domains of interest while the corresponding assertional knowledge is given by RDF data referring to them. Because of its open, distributed, and collaborative nature, such knowledge can be incomplete, noisy, and sometimes inconsistent. By exploiting the evidence coming from the assertional data, we aim at discovering hidden knowledge patterns in the form of multi-relational association rules while taking advantage of the intensional knowledge available in ontological knowledge bases. An evolutionary search method applied to populated ontological knowledge bases is proposed for finding rules with a high inductive power. The proposed method, EDMAR, uses problem-aware genetic operators, echoing the refinement operators of ILP, and takes the intensional knowledge into account, which allows it to restrict and guide the search. Discovered rules are coded in SWRL, and as such they can be straightforwardly integrated within the ontology, thus enriching its expressive power and augmenting the assertional knowledge that can be derived. Additionally , discovered rules may also suggest new axioms to be added to the ontology. We performed experiments on publicly available ontologies, validating the performances of our approach and comparing them with the main state-of-the-art systems

Iron Status in Febrile Seizure: A Case-Control Study

ObjectiveData on the relationship between iron deficiency anemia and febrile convulsions are controversial. The aim of this study was to determine the association between iron deficiency anemia and febrile convulsions among children.Materials & MethodsThis case-control study was conducted during 2006-2007, on 90 children with febrile seizures (case) and 90 febrile children without seizures (control) referred to the Amirkola children hospital (a referral hospital in the north of Iran). Two groups were matched for age and sex. In all children hemoglobin (Hb) level, hematocrit (Hct), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH) and plasma ferritin (PF) were determined and the data collected were analyzed statistically using the t-test.ResultsThe mean PF and TIBC levels were not significantly different in the febrile seizure compared to the reference group; neither were differences in Hb levels statistically significant between two groups. However MCV and MCH were significantly higher in the febrile seizure group (pConclusionPlasma ferritin levels were not significantly lower in children with febrile seizures in comparison with the children in control group. It seems that iron insufficiency does not play a role in pediatric febrile seizures.

Human-machine scientific discovery

International audienceHumanity is facing existential, societal challenges related to food security, ecosystem conservation, antimicrobial resistance, etc, and Artificial Intelligence (AI) is already playing an important role in tackling these new challenges. Most current AI approaches are limited when it comes to ‘knowledge transfer’ with humans, i.e. it is difficult to incorporate existing human knowledge and also the output knowledge is not human comprehensible. In this chapter we demonstrate how a combination of comprehensible machine learning, text-mining and domain knowledge could enhance human-machine collaboration for the purpose of automated scientific discovery where humans and computers jointly develop and evaluate scientific theories. As a case study, we describe a combination of logic-based machine learning (which included human-encoded ecological background knowledge) and text-mining from scientific publications (to verify machine-learned hypotheses) for the purpose of automated discovery of ecological interaction networks (food-webs) to detect change in agricultural ecosystems using the Farm Scale Evaluations (FSEs) of genetically modified herbicide-tolerant (GMHT) crops dataset. The results included novel food-web hypotheses, some confirmed by subsequent experimental studies (e.g. DNA analysis) and published in scientific journals. These machine-leaned food-webs were also used as the basis of a recent study revealing resilience of agro-ecosystems to changes in farming management using GMHT crops

Acoustic Bubble Removal to Enhance SWL Efficacy at High Shock Rate: An In Vitro Study

Rate-dependent efficacy has been extensively documented in shock wave lithotripsy (SWL) stone comminution, with shock waves (SWs) delivered at a low rate producing more efficient fragmentation in comparison to those delivered at high rates. Cavitation is postulated to be the primary source underlying this rate phenomenon. Residual bubble nuclei that persist along the axis of SW propagation can drastically attenuate the waveform's negative phase, decreasing the energy which is ultimately delivered to the stone and compromising comminution. The effect is more pronounced at high rates, as residual nuclei have less time to passively dissolve between successive shocks. In this study, we investigate a means of actively removing such nuclei from the field using a low-amplitude acoustic pulse designed to stimulate their aggregation and subsequent coalescence. To test the efficacy of this bubble removal scheme, model kidney stones were treated in vitro using a research electrohydraulic lithotripter. SWL was applied at rates of 120, 60, or 30?SW/min with or without the incorporation of bubble removal pulses. Optical images displaying the extent of cavitation in the vicinity of the stone were also collected for each treatment. Results show that bubble removal pulses drastically enhance the efficacy of stone comminution at the higher rates tested (120 and 60?SW/min), while optical images show a corresponding reduction in bubble excitation along the SW axis when bubble removal pulses are incorporated. At the lower rate of 30?SW/min, no difference in stone comminution or bubble excitation was detected with the addition of bubble removal pulses, suggesting that remnant nuclei had sufficient time for more complete dissolution. These results corroborate previous work regarding the role of cavitation in rate-dependent SWL efficacy, and suggest that the effect can be mitigated via appropriate control of the cavitation environment surrounding the stone.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140375/1/end.2013.0313.pd

Enhanced High-Rate Shockwave Lithotripsy Stone Comminution in an In Vivo Porcine Model Using Acoustic Bubble Coalescence

Cavitation plays a significant role in the efficacy of stone comminution during shockwave lithotripsy (SWL). Although cavitation on the surface of urinary stones helps to improve fragmentation, cavitation bubbles along the propagation path may shield or block subsequent shockwaves (SWs) and potentially induce collateral tissue damage. Previous in vitro work has shown that applying low-amplitude acoustic waves after each SW can force bubbles to consolidate and enhance SWL efficacy. In this study, the feasibility of applying acoustic bubble coalescence (ABC) in vivo was tested. Model stones were percutaneously implanted and treated with 2500 lithotripsy SWs at 120 SW/minute with or without ABC. Comparing the results of stone comminution, a significant improvement was observed in the stone fragmentation process when ABC was used. Without ABC, only 25% of the mass of the stone was fragmented to particles <2?mm in size. With ABC, 75% of the mass was fragmented to particles <2?mm in size. These results suggest that ABC can reduce the shielding effect of residual bubble nuclei, resulting in a more efficient SWL treatment.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140087/1/end.2016.0407.pd

Serum αFP Level in Cord Blood of Full Term Neonates Born in Babol City

BACKGROUNDANDOBJECTIVE: Serum alpha-fetoprotein (αFP) level is considered as a diagnostic marker is higher than normal in many congenital tumors such as germ cell, hepatoblastoma, as well as liver and metabolic diseases in neonates. Normal neonates also have a higher level of alpha-fetoprotein than others, so it is important to diagnose this interference. In valid sources, the normal serum alpha-fetoprotein level in infants is related to advanced countries, which may vary in our country. Therefore, this study was conducted to determine the serum levels of alpha-fetoprotein in the umbilical cord blood of term neonates born in Babol and to compare them in two genders. METHODS: This cross-sectional study was performed on 500 neonates (37-42 weeks) born in hospitals in Babol city where physical examination was normal. At birth, 5 ml of umbilical cord blood was taken and samples were sent to the lab for measurement of alpha-fetoprotein. Serum alpha-fetoprotein level was measured by ELISA method and was compared in two genders. FINDINGS: Mean serum a FP levels was 76.57±35.25 ng/ml (range 2.3-160) and it was significantly higher in males (80.54±36.95 vs. 73.69±33.73 ng/ml) which was statistically significant (p=0.002). CONCLUSION: The results of this study showed that the level of alpha-fetoprotein in neonates born in Babol is relatively high and also in males is more than females

Next-Generation Global Biomonitoring: Large-scale, Automated Reconstruction of Ecological Networks

We foresee a new global-scale, ecological approach to biomonitoring emerging within the next decade that can detect ecosystem change accurately, cheaply, and generically. Next-generation sequencing of DNA sampled from the Earth's environments would provide data for the relative abundance of operational taxonomic units or ecological functions. Machine-learning methods would then be used to reconstruct the ecological networks of interactions implicit in the raw NGS data. Ultimately, we envision the development of autonomous samplers that would sample nucleic acids and upload NGS sequence data to the cloud for network reconstruction. Large numbers of these samplers, in a global array, would allow sensitive automated biomonitoring of the Earth's major ecosystems at high spatial and temporal resolution, revolutionising our understanding of ecosystem change

Inductive learning spatial attention

This paper investigates the automatic induction of spatial attention from the visual observation of objects manipulated on a table top. In this work, space is represented in terms of a novel observer-object relative reference system, named Local Cardinal System, defined upon the local neighbourhood of objects on the table. We present results of applying the proposed methodology on five distinct scenarios involving the construction of spatial patterns of coloured blocks