IMPROVEMENT TO THE MARGINAL COPING FIT OF COMMERCIALLY PURE TITANIUM CAST IN PHOSPHATE-BONDED INVESTMENT BY USING A SIMPLE PATTERN COATING TECHNIQUE

Statement of problem. Coatings of zirconite, Y2O3 or ZrO2 on wax patterns before investing in phosphate-bonded investments have been recommended to reduce the reaction layer in titanium castings, but they are not easily obtainable. Spinel-based investments are relatively stable with molten titanium and could be used as coatings to improve the quality of castings made with those investments. Purpose. The purpose of this study was to evaluate the effect of pattern coating with a commercial spinel-based investment before investing in 1 of 3 phosphate-bonded investments on the marginal coping fit and surface roughness of commercially pure titanium castings. Material and methods. Ten square acrylic resin patterns (12 x 12 x 2 mm) per group were invested in the phosphate-bonded investments Rematitan Plus (RP), Rema Exakt (RE), and Castorit Super C (CA) with or without a coating of the spinel-based investment, Rematitan Ultra (RU). After casting, the specimens were cleaned and the surface roughness was measured with a profilometer. Copings for dental implants with conical abutment were invested, eliminated, and cast as previously described. The copings were cleaned and misfit was measured with a profile projector (n=10). For both tests, the difference between the mean value of RU only and each value of the phosphate-bonded investment was calculated, and the data were analyzed by 2-way ANOVA and Tukey's HSD test (alpha=.05). In addition, the investment roughness was measured in bar specimens (30 x 10 x 10 mm), and the data (n=10) were analyzed by 1-way ANOVA and Tukey's HSD post hoc test (alpha=.05). Results. Two-way ANOVA for casting surface roughness was significant because of the investment, the coating technique, and the interaction between variables. One-way ANOVA was performed to prove the interaction term, and Tukey's post hoc test showed that RP with coating had the lowest mean, while RP had the highest. CA with coating was not different from RP with coating or CA without coating. RE with coating was similar to CA, while RE was different from all groups. For coping marginal fit, the 2-way ANOVA was significant for the investment, the coating technique, and the interaction between variables. The interaction was analyzed by1-way ANOVA and Tukey's HSD test that showed no significant difference among the coated groups, which had better marginal fit than the groups without coating. Among the groups without coating, CA had significant lower marginal misfit than RP, while RE was not different from CA and RP. For the investment surface roughness, the 1-way ANOVA was significant. CA and RU were smoother than RE and RP (P<.001). Conclusions. The coating technique improved the quality of castings fabricated with phosphate-bonded investments. (J Prosthet Dent 2012;108:51-57)

Safety illusion and error trap in a collectively-operated machine accident

Workplace accidents involving machines are relevant for their magnitude and their impacts on worker health. Despite consolidated critical statements, explanation centered on errors of operators remains predominant with industry professionals, hampering preventive measures and the improvement of production-system reliability. Several initiatives were adopted by enforcement agencies in partnership with universities to stimulate production and diffusion of analysis methodologies with a systemic approach. Starting from one accident case that occurred with a worker who operated a brake-clutch type mechanical press, the article explores cognitive aspects and the existence of traps in the operation of this machine. It deals with a large-sized press that, despite being endowed with a light curtain in areas of access to the pressing zone, did not meet legal requirements. The safety devices gave rise to an illusion of safety, permitting activation of the machine when a worker was still found within the operational zone. Preventive interventions must stimulate the tailoring of systems to the characteristics of workers, minimizing the creation of traps and encouraging safety policies and practices that replace judgments of behaviors that participate in accidents by analyses of reasons that lead workers to act in that manner.

Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records

Surveillance Levels (SLs) are categories for medical patients (used in Brazil) that represent different types of medical recommendations. SLs are defined according to risk factors and the medical and developmental history of patients. Each SL is associated with specific educational and clinical measures. The objective of the present paper was to verify computer-aided, automatic assignment of SLs. The present paper proposes a computer-aided approach for automatic recommendation of SLs. The approach is based on the classification of information from patient electronic records. For this purpose, a software architecture composed of three layers was developed. The architecture is formed by a classification layer that includes a linguistic module and machine learning classification modules. The classification layer allows for the use of different classification methods, including the use of preprocessed, normalized language data drawn from the linguistic module. We report the verification and validation of the software architecture in a Brazilian pediatric healthcare institution. The results indicate that selection of attributes can have a great effect on the performance of the system. Nonetheless, our automatic recommendation of surveillance level can still benefit from improvements in processing procedures when the linguistic module is applied prior to classification. Results from our efforts can be applied to different types of medical systems. The results of systems supported by the framework presented in this paper may be used by healthcare and governmental institutions to improve healthcare services in terms of establishing preventive measures and alerting authorities about the possibility of an epidemic.

Effects of type I collagen coating on titanium osseointegration: histomorphometric, cellular and molecular analyses

The investigation of titanium (Ti) surface modifications aiming to increase implant osseointegration is one of the most active research areas in dental implantology. This study was carried out to evaluate the benefits of coating Ti with type I collagen on the osseointegration of dental implants. Acid etched Ti implants (AETi), either untreated or coated with type I collagen (ColTi), were placed in dog mandibles for three and eight weeks for histomorphometric, cellular and molecular evaluations of bone tissue response. While the histological aspects were essentially the same with both implants being surrounded by lamellar bone trabeculae, histomorphometric analysis showed more abundant bone formation in ColTi, mainly at three weeks. Cellular evaluation showed that cells harvested from bone fragments in close contact with ColTi display lower proliferative capacity and higher alkaline phosphatase activity, phenotypic features associated with more differentiated osteoblasts. Confirming these findings, molecular analyses showed that ColTi implants up-regulates the expression of a panel of genes well known as osteoblast markers. Our results present a set of evidences that coating AETi with collagen fastens the osseointegration by stimulating bone formation at the cellular and molecular levels, making this combination of morphological and biochemical modification a promising approach to treat Ti surfaces.

Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuroanatomy and machine learning

Several recent studies in literature have identified brain morphological alterations associated to Borderline Personality Disorder (BPD) patients. These findings are reported by studies based on voxel-based-morphometry analysis of structural MRI data, comparing mean gray-matter concentration between groups of BPD patients and healthy controls. On the other hand, mean differences between groups are not informative about the discriminative value of neuroimaging data to predict the group of individual subjects. In this paper, we go beyond mean differences analyses, and explore to what extent individual BPD patients can be differentiated from controls (25 subjects in each group), using a combination of automated-morphometric tools for regional cortical thickness/volumetric estimation and Support Vector Machine classifier. The approach included a feature selection step in order to identify the regions containing most discriminative information. The accuracy of this classifier was evaluated using the leave-one-subject-out procedure. The brain regions indicated as containing relevant information to discriminate groups were the orbitofrontal, rostral anterior cingulate, posterior cingulate, middle temporal cortices, among others. These areas, which are distinctively involved in emotional and affect regulation of BPD patients, were the most informative regions to achieve both sensitivity and specificity values of 80% in SVM classification. The findings suggest that this new methodology can add clinical and potential diagnostic value to neuroimaging of psychiatric disorders. (C) 2012 Elsevier Ltd. All rights reserved.

Effect of a polymeric protective coating on optical and electrical properties of poly (p-phenylene vinylene) derivatives

The resistance to photodegradation of poly [(2-methoxy-5-n-hexyloxy)-p-phenylene vinylene] (OC1OC6-PPV) films was significantly enhanced by the use of poly(vinyl alcohol) 99% hydrolyzed as protective coating. The deposition of poly(vinyl alcohol) onto OC1OC6-PPV films did not affect the absorption and the emission spectra of the luminescent polymer. The protected film showed 5% drop on the absorbance at 500nm after 270 hours of light exposure while the unprotected film completely degraded in the same conditions. The conductivity of the protected film remained stable (around 7 × 10-10 S/m) while the value for the unprotected one dropped around two orders of magnitude after 100 hours of light exposure.

Estimación de la potencia eólica en una zona mediante el apoyo de estaciones meteorológicas de referencia y el empleo de técnicas estadísticas no paramétricas, funcionales y de machine learning: aplicación a las islas Canarias

Programa de doctorado: Tecnología industrial

Studio di rivestimenti antiriflesso da sol-gel dip-coating per impianti solari termodinamici

Negli impianti utilizzati per la produzione di energia elettrica che sfruttano l'energia solare, quali la tecnologia solare a concentrazione (Solare Termodinamico) sviluppata da ENEA, per minimizzare le dispersioni di calore è necessaria una elevata selettività spettrale. Per ottimizzare l'efficienza dell'impianto è quindi necessario lo sviluppo di materiali innovativi, in grado di minimizzare la quantità di energia dispersa per riflessione. In questo studio, per incrementare la trasmittanza solare dei componenti in vetro presenti nei tubi ricevitori dell'impianto, sono state utilizzate tipologie diverse di rivestimenti antiriflesso (multistrato e a singolo strato poroso). I rivestimenti sono stati ottenuti mediante via umida, con tecnica di sol-gel dip-coating. I sol coprenti sono stati preparati da alcossidi o sali metallici precursori degli ossidi che costituiscono il rivestimento. Sono state approfondite sia la fase di sintesi dei sol coprenti, sia la fase di deposizione sul substrato, che ha richiesto la progettazione e realizzazione di una apparecchiatura prototipale, ossia di un dip-coater in grado di garantire un accurato controllo della velocità di emersione e dell'ambiente di deposizione (temperatura e umidità). Il materiale multistrato applicato su vetro non ha migliorato la trasmittanza del substrato nell'intervallo di lunghezze d'onda dello spettro solare, pur presentando buone caratteristiche antiriflesso nell'intervallo dell'UV-Vis. Al contrario, l'ottimizzazione del rivestimento a base di silice porosa, ha portato all'ottenimento di indici di rifrazione molto bassi (1.15 to 1.18) e ad un incremento della trasmittanza solare dal 91.5% al 96.8%, efficienza superiore agli attuali rivestimenti disponibili in commercio.

Automatic (data-based) learning of expressive indicators for machine failure detection : a proposal

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Predizione dell'effetto delle mutazioni sulla variazione della stabilita' proteica con metodi di "machine-learning".

La tesi consiste nell’implementare un software in grado a predire la variazione della stabilità di una proteina sottoposta ad una mutazione. Il predittore implementato fa utilizzo di tecniche di Machine-Learning ed, in particolare, di SVM. In particolare, riguarda l’analisi delle prestazioni di un predittore, precedentemente implementato, sotto opportune variazioni dei parametri di input e relativamente all’utilizzo di nuova informazione rispetto a quella utilizzata dal predittore basilare.

Machine learning methods for prediction of disulphide bonding states of cysteine residues in proteins

The goal of this thesis work is to develop a computational method based on machine learning techniques for predicting disulfide-bonding states of cysteine residues in proteins, which is a sub-problem of a bigger and yet unsolved problem of protein structure prediction. Improvement in the prediction of disulfide bonding states of cysteine residues will help in putting a constraint in the three dimensional (3D) space of the respective protein structure, and thus will eventually help in the prediction of 3D structure of proteins. Results of this work will have direct implications in site-directed mutational studies of proteins, proteins engineering and the problem of protein folding. We have used a combination of Artificial Neural Network (ANN) and Hidden Markov Model (HMM), the so-called Hidden Neural Network (HNN) as a machine learning technique to develop our prediction method. By using different global and local features of proteins (specifically profiles, parity of cysteine residues, average cysteine conservation, correlated mutation, sub-cellular localization, and signal peptide) as inputs and considering Eukaryotes and Prokaryotes separately we have reached to a remarkable accuracy of 94% on cysteine basis for both Eukaryotic and Prokaryotic datasets, and an accuracy of 90% and 93% on protein basis for Eukaryotic dataset and Prokaryotic dataset respectively. These accuracies are best so far ever reached by any existing prediction methods, and thus our prediction method has outperformed all the previously developed approaches and therefore is more reliable. Most interesting part of this thesis work is the differences in the prediction performances of Eukaryotes and Prokaryotes at the basic level of input coding when ‘profile’ information was given as input to our prediction method. And one of the reasons for this we discover is the difference in the amino acid composition of the local environment of bonded and free cysteine residues in Eukaryotes and Prokaryotes. Eukaryotic bonded cysteine examples have a ‘symmetric-cysteine-rich’ environment, where as Prokaryotic bonded examples lack it.

Chemie an funktionalen Polymer-Opalen

In dieser Arbeit wird die Herstellung und Anwendung von funktionalen Polymer-Opalen beschrieben. Für die Synthese von funktionalen monodipsersen Kolloiden, den Bausteinen der Opale, wird die emulgatorfreie Emulsionspolymerisation (SFEP) verwendet. Je nach einzubauendem funktionalem Molekül werden verschiedene Varianten der SFEP verwendet, wie z. B. Homopolymerisation, Copolymerisation, Polymerisation mit Fremdstoffen und die Herstellung von Kern-Schale-Kolloiden. Die so hergestellten monodispersen Kolloide formen durch Selbstorganisation über horizontale (Aufpipettieren, Rakeln, Sprühen) oder vertikale Kristallisation (Ziehmaschine)hochqualitative künstliche Opale. Die eingebauten Funktionalitäten öffnen den Weg zu einer Vielzahl von Anwendungen. Über die Spaltung von funktionalen Estergruppen kann eine lichtinduzierte Strukturierung durchgeführt werden. Der Einbau von Epoxidgruppen ermöglicht eine makroskopische Vernetzung wodurch die mechanische Stabilität der Struktur erhöht wird. Der Einsatz von Reaktivestern kann zur Oberflächen- funktionalisierung verwendet werden. Durch Replizierung der Struktur zum inversen Opal können weitere funktionale Materialien eingeführt werden, was die Einsatzmöglichkeiten noch erweitert.

Machine-learning methods for structure prediction of β-barrel membrane proteins

Different types of proteins exist with diverse functions that are essential for living organisms. An important class of proteins is represented by transmembrane proteins which are specifically designed to be inserted into biological membranes and devised to perform very important functions in the cell such as cell communication and active transport across the membrane. Transmembrane β-barrels (TMBBs) are a sub-class of membrane proteins largely under-represented in structure databases because of the extreme difficulty in experimental structure determination. For this reason, computational tools that are able to predict the structure of TMBBs are needed. In this thesis, two computational problems related to TMBBs were addressed: the detection of TMBBs in large datasets of proteins and the prediction of the topology of TMBB proteins. Firstly, a method for TMBB detection was presented based on a novel neural network framework for variable-length sequence classification. The proposed approach was validated on a non-redundant dataset of proteins. Furthermore, we carried-out genome-wide detection using the entire Escherichia coli proteome. In both experiments, the method significantly outperformed other existing state-of-the-art approaches, reaching very high PPV (92%) and MCC (0.82). Secondly, a method was also introduced for TMBB topology prediction. The proposed approach is based on grammatical modelling and probabilistic discriminative models for sequence data labeling. The method was evaluated using a newly generated dataset of 38 TMBB proteins obtained from high-resolution data in the PDB. Results have shown that the model is able to correctly predict topologies of 25 out of 38 protein chains in the dataset. When tested on previously released datasets, the performances of the proposed approach were measured as comparable or superior to the current state-of-the-art of TMBB topology prediction.

Inorganic-organic hybrid polymers: Solution-processible coating materials for defined surface functionalization

A new class of inorganic-organic hybrid polymers could successfully been prepared by the combination of different polymerization techniques. The access to a broad range of organic polymers incorporated into the hybrid polymer was realized using two independent approaches.rnIn the first approach a functional poly(silsesquioxane) (PSSQ) network was pre-formed, which was capable to initiate a controlled radical polymerization to graft organic vinyl-type monomers from the PSSQ precursor. As controlled radical polymerization techniques atom transfer radical polymerization (ATRP), as well as reversible addition fragmentation chain transfer (RAFT) polymerization could be used after defined tuning of the PSSQ precursor either toward a PSSQ macro-initiator or to a PSSQ macro-chain-transfer-agent. The polymerization pathway, consisting of polycondensation of trialkoxy-silanes followed by grafting-from polymerization of different monomers, allowed synthesis of various functional hybrid polymers. A controlled synthesis of the PSSQ precursors could successfully be performed using a microreactor setup; the molecular weight could be adjusted easily while the polydispersity index could be decreased well below 2.rnThe second approach aimed to incorporate differently derived organic polymers. As examples, polycarbonate and poly(ethylene glycol) were end-group-modified using trialkoxysilanes. After end-group-functionalization these organic polymers could be incorporated into a PSSQ network.rnThese different hybrid polymers showed extraordinary coating abilities. All polymers could be processed from solution by spin-coating or dip-coating. The high amount of reactive silanol moieties in the PSSQ part could be cross-linked after application by annealing at 130° for 1h. Not only cross-linking of the whole film was achieved, which resulted in mechanical interlocking with the substrate, also chemical bonds to metal or metal oxide surfaces were formed. All coating materials showed high stability and adhesion onto various underlying materials, reaching from metals (like steel or gold) and metal oxides (like glass) to plastics (like polycarbonate or polytetrafluoroethylene).rnAs the material and the synthetic pathway were very tolerant toward different functionalities, various functional monomers could be incorporated in the final coating material. The incorporation of N-isopropylacrylamide yielded in temperature-responsive surface coatings, whereas the incorporation of redox-active monomers allowed the preparation of semi-conductive coatings, capable to produce smooth hole-injection layers on transparent conductive electrodes used in optoelectronic devices.rnThe range of possible applications could be increased tremendously by incorporation of reactive monomers, capable to undergo fast and quantitative conversions by polymer-analogous reactions. For example, grafting active esters from a PSSQ precursor yielded a reactive surface coating after application onto numerous substrates. Just by dipping the coated substrate into a solution of a functionalized amine, the desired function could be immobilized at the interface as well as throughout the whole film. The obtained reactive surface coatings could be used as basis for different functional coatings for various applications. The conversion with specifically tuned amines yielded in surfaces with adjustable wetting behaviors, switchable wetting behaviors or as recognition element for surface-oriented bio-analytical devices. The combination of hybrid materials with orthogonal reactivities allowed for the first time the preparation of multi-reactive surfaces which could be functionalized sequentially with defined fractions of different groups at the interface. rnThe introduced concept to synthesis functional hybrid polymers unifies the main requirements on an ideal coating material. Strong adhesion on a wide range of underlying materials was achieved by secondary condensation of the PSSQ part, whereas the organic part allowed incorporation of various functionalities. Thus, a flexible platform to create functional and reactive surface coatings was achieved, which could be applied to different substrates. rn