A predictive maintenance system for integral type faults based on support vector machines:An application to ion implantation

In semiconductor fabrication processes, effective management of maintenance operations is fundamental to decrease costs associated with failures and downtime. Predictive Maintenance (PdM) approaches, based on statistical methods and historical data, are becoming popular for their predictive capabilities and low (potentially zero) added costs. We present here a PdM module based on Support Vector Machines for prediction of integral type faults, that is, the kind of failures that happen due to machine usage and stress of equipment parts. The proposed module may also be employed as a health factor indicator. The module has been applied to a frequent maintenance problem in semiconductor manufacturing industry, namely the breaking of the filament in the ion-source of ion-implantation tools. The PdM has been tested on a real production dataset. © 2013 IEEE.

Machine Learning for Predictive Maintenance: A Multiple Classifiers Approach

In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

Gremlin1 preferentially binds to Bone Morphogenetic Protein-2 (BMP-2) and BMP-4 over BMP-7

Gremlin (Grem1) is a member of the DAN family of secreted bone morphogenetic protein (BMP) antagonists. Bone morphogenetic protein-7 (BMP-7) mediates protective effects during renal fibrosis-associated with diabetes and other renal diseases. The pathogenic mechanism of Grem1 during DN has been suggested to be binding and inhibition of BMP-7. However, the precise interactions between Grem1, BMP-7 and other BMPs have not been accurately defined. Here we show the affinity of Grem1 for BMP-7 is lower than that of BMP-2 and BMP-4, using a combination of surface plasmon resonance and cell culture techniques. Using kidney proximal tubule cells and HEK-293 cell Smad1/5/8 phosphorylation and BMP-dependent gene expression as readout, Grem1 consistently demonstrated a higher affinity for BMP-2>4>7. Cell-associated Grem1 did not inhibit BMP-2 or BMP-4 mediated signalling, suggesting that Grem1-BMP-2 binding occurred in solution, preventing BMP receptor activation. These data suggest that Grem1 preferentially binds to BMP-2 and this may be the dominant complex in a disease situation where levels of Grem1 and BMPs are elevated.

Global Sensitivity Analysis for MAP Inference in Graphical Models

We study the sensitivity of a MAP configuration of a discrete probabilistic graphical model with respect to perturbations of its parameters. These perturbations are global, in the sense that simultaneous perturbations of all the parameters (or any chosen subset of them) are allowed. Our main contribution is an exact algorithm that can check whether the MAP configuration is robust with respect to given perturbations. Its complexity is essentially the same as that of obtaining the MAP configuration itself, so it can be promptly used with minimal effort. We use our algorithm to identify the largest global perturbation that does not induce a change in the MAP configuration, and we successfully apply this robustness measure in two practical scenarios: the prediction of facial action units with posed images and the classification of multiple real public data sets. A strong correlation between the proposed robustness measure and accuracy is verified in both scenarios.

Approximate credal network updating by linear programming with applications to decision making

Credal nets are probabilistic graphical models which extend Bayesian nets to cope with sets of distributions. An algorithm for approximate credal network updating is presented. The problem in its general formulation is a multilinear optimization task, which can be linearized by an appropriate rule for fixing all the local models apart from those of a single variable. This simple idea can be iterated and quickly leads to accurate inferences. A transformation is also derived to reduce decision making in credal networks based on the maximality criterion to updating. The decision task is proved to have the same complexity of standard inference, being NPPP-complete for general credal nets and NP-complete for polytrees. Similar results are derived for the E-admissibility criterion. Numerical experiments confirm a good performance of the method.

On the Complexity of Strong and Epistemic Credal Networks

Credal networks are graph-based statistical models whose parameters take values on a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The result of inferences with such models depends on the irrelevance/independence concept adopted. In this paper, we study the computational complexity of inferences under the concepts of epistemic irrelevance and strong independence. We strengthen complexity results by showing that inferences with strong independence are NP-hard even in credal trees with ternary variables, which indicates that tractable algorithms, including the existing one for epistemic trees, cannot be used for strong independence. We prove that the polynomial time of inferences in credal trees under epistemic irrelevance is not likely to extend to more general models, because the problem becomes NP-hard even in simple polytrees. These results draw a definite line between networks with efficient inferences and those where inferences are hard, and close several open questions regarding the computational complexity of such models.

Generalized Loopy 2U: A New Algorithm for Approximate Inference in Credal Networks

Credal nets generalize Bayesian nets by relaxing the requirement of precision of probabilities. Credal nets are considerably more expressive than Bayesian nets, but this makes belief updating NP-hard even on polytrees. We develop a new efficient algorithm for approximate belief updating in credal nets. The algorithm is based on an important representation result we prove for general credal nets: that any credal net can be equivalently reformulated as a credal net with binary variables; moreover, the transformation, which is considerably more complex than in the Bayesian case, can be implemented in polynomial time. The equivalent binary credal net is updated by L2U, a loopy approximate algorithm for binary credal nets. Thus, we generalize L2U to non-binary credal nets, obtaining an accurate and scalable algorithm for the general case, which is approximate only because of its loopy nature. The accuracy of the inferences is evaluated by empirical tests.

Characterizing K2 Planet Discoveries: A super-Earth transiting the bright K-dwarf HIP 116454

We report the first planet discovery from the two-wheeled Kepler (K2) mission: HIP 116454 b. The host star HIP 116454 is a bright (V = 10.1, K = 8.0) K1 dwarf with high proper motion and a parallax-based distance of 55.2 +/- 5.4 pc. Based on high-resolution optical spectroscopy, we find that the host star is metal-poor with [Fe/H]= -0.16 +/- 0.08 and has a radius R-star = 0.716 +/- 0.024 R-circle dot and mass M-star = 0.775 +/- 0.027M(circle dot). The star was observed by the Kepler spacecraft during its Two-Wheeled Concept Engineering Test in 2014 February. During the 9 days of observations, K2 observed a single transit event. Using a new K2 photometric analysis technique, we are able to correct small telescope drifts and recover the observed transit at high confidence, corresponding to a planetary radius of R-p = 2.53 +/- 0.18 R-circle plus. Radial velocity observations with the HARPS-N spectrograph reveal a 11.82 +/- 1.33 M-circle plus planet in a 9.1 day orbit, consistent with the transit depth, duration, and ephemeris. Follow-up photometric measurements from the MOST satellite confirm the transit observed in the K2 photometry and provide a refined ephemeris, making HIP 116454 b amenable for future follow-up observations of this latest addition to the growing population of transiting super-Earths around nearby, bright stars.

Invited Interview on Network Performance in the "Transient Gestures" issue

An issue on Networked Performance produceed by Neural for which I was invited to deliver an interview on network performance. Neural is a printed magazine established in 1993 dealing with new media art, electronic music and hacktivism. It was founded by Alessandro Ludovico and Minus Habens Records label owner Ivan Iusco in Bari (Italy).

Single- and two-mode quantumness at a beam splitter

In the context of bipartite bosonic systems, two notions of classicality of correlations can be defined: P-classicality, based on the properties of the Glauber-Sudarshan P-function; and C-classicality, based on the entropic quantum discord. It has been shown that these two notions are maximally inequivalent in a static (metric) sense -- as they coincide only on a set of states of zero measure. We extend and reinforce quantitatively this inequivalence by addressing the dynamical relation between these types of non-classicality in a paradigmatic quantum-optical setting: the linear mixing at a beam splitter of a single-mode Gaussian state with a thermal reference state. Specifically, we show that almost all P-classical input states generate outputs that are not C-classical. Indeed, for the case of zero thermal reference photons, the more P-classical resources at the input the less C-classicality at the output. In addition, we show that the P-classicality at the input -- as quantified by the non-classical depth -- does instead determine quantitatively the potential of generating output entanglement. This endows the non-classical depth with a new operational interpretation: it gives the maximum number of thermal reference photons that can be mixed at a beam splitter without destroying the output entanglement.

Limitations of a measurement-assisted optomechanical route to quantum macroscopicity of superposition states

Optomechanics is currently believed to provide a promising route towards the achievement of genuine quantum effects at the large, massive-system scale. By using a recently proposed figure of merit that is well suited to address continuous-variable systems, in this paper we analyze the requirements needed for the state of a mechanical mode (embodied by an end-cavity cantilever or a membrane placed within an optical cavity) to be qualified as macroscopic. We show that, according to the phase space-based criterion that we have chosen for our quantitative analysis, the state achieved through strong single-photon radiation-pressure coupling to a quantized field of light and conditioned by measurements operated on the latter might be interpreted as macroscopically quantum. In general, though, genuine macroscopic quantum superpositions appear to be possible only under quite demanding experimental conditions

Antibiofilm Activity of the Brown Alga Halidrys siliquosa against Clinically Relevant Human Pathogens

The marine brown alga Halidrys siliquosa is known to produce compounds with antifouling activity against several marine bacteria. The aim of this study was to evaluate the antimicrobial and antibiofilm activity of organic extracts obtained from the marine brown alga H. siliquosa against a focused panel of clinically relevant human pathogens commonly associated with biofilm-related infections. The partially fractionated methanolic extract obtained from H. siliquosa collected along the shores of Co. Donegal; Ireland; displayed antimicrobial activity against bacteria of the genus Staphylococcus; Streptococcus; Enterococcus; Pseudomonas; Stenotrophomonas; and Chromobacterium with MIC and MBC values ranging from 0.0391 to 5 mg/mL. Biofilms of S. aureus MRSA were found to be susceptible to the algal methanolic extract with MBEC values ranging from 1.25 mg/mL to 5 mg/mL respectively. Confocal laser scanning microscopy using LIVE/DEAD staining confirmed the antimicrobial nature of the antibiofilm activity observed using the MBEC assay. A bioassay-guided fractionation method was developed yielding 10 active fractions from which to perform purification and structural elucidation of clinically-relevant antibiofilm compounds.

Marine-derived quorum-sensing inhibitory activities enhance the antibacterial efficacy of tobramycin against Pseudomonas aeruginosa

Bacterial epiphytes isolated from marine eukaryotes were screened for the production of quorum sensing inhibitory compounds (QSIs). Marine isolate KS8, identified as a Pseudoalteromonas sp., was found to display strong quorum sensing inhibitory (QSI) activity against acyl homoserine lactone (AHL)-based reporter strains Chromobacterium violaceum ATCC 12472 and CV026. KS8 supernatant significantly reduced biofilm biomass during biofilm formation (−63%) and in pre-established, mature P. aeruginosa PAO1 biofilms (−33%). KS8 supernatant also caused a 0.97-log reduction (−89%) and a 2-log reduction (−99%) in PAO1 biofilm viable counts in the biofilm formation assay and the biofilm eradication assay respectively. The crude organic extract of KS8 had a minimum inhibitory concentration (MIC) of 2 mg/mL against PAO1 but no minimum bactericidal concentration (MBC) was observed over the concentration range tested (MBC > 16 mg/mL). Sub-MIC concentrations (1 mg/mL) of KS8 crude organic extract significantly reduced the quorum sensing (QS)-dependent production of both pyoverdin and pyocyanin in P. aeruginosa PAO1 without affecting growth. A combinatorial approach using tobramycin and the crude organic extract at 1 mg/mL against planktonic P. aeruginosa PAO1 was found to increase the efficacy of tobramycin ten-fold, decreasing the MIC from 0.75 to 0.075 µg/mL. These data support the validity of approaches combining conventional antibiotic therapy with non-antibiotic compounds to improve the efficacy of current treatments.

Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation

Protocols of systematic reviews and meta-analyses allow for planning and documentation of review methods, act as a guard against arbitrary decision making during review conduct, enable readers to assess for the presence of selective reporting against completed reviews, and, when made publicly available, reduce duplication of efforts and potentially prompt collaboration. Evidence documenting the existence of selective reporting and excessive duplication of reviews on the same or similar topics is accumulating and many calls have been made in support of the documentation and public availability of review protocols. Several efforts have emerged in recent years to rectify these problems, including development of an international register for prospective reviews (PROSPERO) and launch of the first open access journal dedicated to the exclusive publication of systematic review products, including protocols (BioMed Central's Systematic Reviews). Furthering these efforts and building on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, an international group of experts has created a guideline to improve the transparency, accuracy, completeness, and frequency of documented systematic review and meta-analysis protocols--PRISMA-P (for protocols) 2015. The PRISMA-P checklist contains 17 items considered to be essential and minimum components of a systematic review or meta-analysis protocol.This PRISMA-P 2015 Explanation and Elaboration paper provides readers with a full understanding of and evidence about the necessity of each item as well as a model example from an existing published protocol. This paper should be read together with the PRISMA-P 2015 statement. Systematic review authors and assessors are strongly encouraged to make use of PRISMA-P when drafting and appraising review protocols.

Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement

Systematic reviews should build on a protocol that describes the rationale, hypothesis, and planned methods of the review; few reviews report whether a protocol exists. Detailed, well-described protocols can facilitate the understanding and appraisal of the review methods, as well as the detection of modifications to methods and selective reporting in completed reviews. We describe the development of a reporting guideline, the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015). PRISMA-P consists of a 17-item checklist intended to facilitate the preparation and reporting of a robust protocol for the systematic review. Funders and those commissioning reviews might consider mandating the use of the checklist to facilitate the submission of relevant protocol information in funding applications. Similarly, peer reviewers and editors can use the guidance to gauge the completeness and transparency of a systematic review protocol submitted for publication in a journal or other medium.