Search results for: Tito Trindade

Authors: Demet Tatar, Bahattin Düzgün

Abstract:

In this study, we have newly developed titanium-tin oxide (TiSnO) thin films as the transparent conducting oxides materials by the spray pyrolysis technique. Tin oxide thin films doped with different Ti content were successfully grown by spray pyrolysis and they were characterized as a function of Ti content. The effect of Ti contents on the crystalline structure and optical properties of the as-deposited SnO2:Ti films was systematically investigated by X-ray diffraction (XRD), scanning electronic microscopy (SEM), atomic force microscopy (AFM), UV-vis spectrometer and photoluminecenc spectrophotometer. The X-ray diffraction patterns taken at room temperature showed that the films are polycrystalline. The preferred directions of crystal growth appeared in the difractogram of SnO2: Ti (TiTO) films were correspond to the reflections from the (110), (200), (211) and (301) planes. The grain size varies from 21.8 to 27.8 nm for (110) preferred plane. SEM and AFM study reveals the surface of TiTO to be made of nanocrystalline particles. The highest visible transmittance (570 nm) of the deposited films is 80 % for 20 wt % titanium doped tin oxide films. The obtained results revealed that the structures and optical properties of the films were greatly affected by doping levels. These films are useful as conducting layers in electro chromic and photovoltaic devices.

Keywords: transparent conducting oxide, gas sensors, SnO2, Ti, optoelectronic, spray pyrolysis

Procedia PDF Downloads 342

Authors: Luiza Melo De Lima, Tito Trindade, Jose M. Oliveira

Abstract:

The development of thermoplastic-based graphene nanocomposites has been of great interest not only to the scientific community but also to different industrial sectors. Due to the possible improvement of performance and weight reduction, thermoplastic nanocomposites are a great promise as a new class of materials. These nanocomposites are of relevance for the automotive industry, namely because the emission limits of CO2 emissions imposed by the European Commission (EC) regulations can be fulfilled without compromising the car’s performance but by reducing its weight. Thermoplastic polymers have some advantages over thermosetting polymers such as higher productivity, lower density, and recyclability. In the automotive industry, for example, poly(propylene) (PP) is a common thermoplastic polymer, which represents more than half of the polymeric raw material used in automotive parts. Graphene-based materials (GBM) are potential nanofillers that can improve the properties of polymer matrices at very low loading. In comparison to other composites, such as fiber-based composites, weight reduction can positively affect their processing and future applications. However, the properties and performance of GBM/polymer nanocomposites depend on the type of GBM and polymer matrix, the degree of dispersion, and especially the type of interactions between the fillers and the polymer matrix. In order to take advantage of the superior mechanical strength of GBM, strong interfacial strength between GBM and the polymer matrix is required for efficient stress transfer from GBM to the polymer. Thus, chemical compatibilizers and physicochemical modifications have been reported as important tools during the processing of these nanocomposites. In this study, PP-based nanocomposites were obtained by a simple melt blending technique, using a Brabender type mixer machine. Graphene nanoplatelets (GnPs) were applied as structural reinforcement. Two compatibilizers were used to improve the interaction between PP matrix and GnPs: PP graft maleic anhydride (PPgMA) and PPgMA modified with tertiary amine alcohol (PPgDM). The samples for tensile and Charpy impact tests were obtained by injection molding. The results suggested the GnPs presence can increase the mechanical strength of the polymer. However, it was verified that the GnPs presence can promote a decrease of impact resistance, turning the nanocomposites more fragile than neat PP. The compatibilizers’ incorporation increases the impact resistance, suggesting that the compatibilizers can enhance the adhesion between PP and GnPs. Compared to neat PP, Young’s modulus of non-compatibilized nanocomposite increase demonstrated that GnPs incorporation can promote a stiffness improvement of the polymer. This trend can be related to the several physical crosslinking points between the PP matrix and the GnPs. Furthermore, the decrease of strain at a yield of PP/GnPs, together with the enhancement of Young’s modulus, confirms that the GnPs incorporation led to an increase in stiffness but to a decrease in toughness. Moreover, the results demonstrated that incorporation of compatibilizers did not affect Young’s modulus and strain at yield results compared to non-compatibilized nanocomposite. The incorporation of these compatibilizers showed an improvement of nanocomposites’ mechanical properties compared both to those the non-compatibilized nanocomposite and to a PP sample used as reference.

Keywords: graphene nanoplatelets, mechanical properties, melt blending processing, poly(propylene)-based nanocomposites

Procedia PDF Downloads 150

Authors: Pedro M. A. Vitoriano, Tito. G. Amaral

Abstract:

Automated Optical Inspection (AOI) Systems are commonly used on Printed Circuit Boards (PCB) manufacturing. The use of this technology has been proven as highly efficient for process improvements and quality achievements. The correct extraction of the component for posterior analysis is a critical step of the AOI process. Nowadays, the Pattern Matching Algorithm is commonly used, although this algorithm requires extensive calculations and is time consuming. This paper will present an improved algorithm for the component localization process, with the capability of implementation in a parallel execution system.

Keywords: AOI, automated optical inspection, SMD, surface mounting devices, pattern matching, parallel execution

Procedia PDF Downloads 268

Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

Abstract:

Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

Procedia PDF Downloads 349

Authors: N. S. B. Ambarini, Tito Sofyan, Edra Satmaidi

Abstract:

Coastal and marine are two potential natural resource one of the pillars of the national economy. The Indonesian archipelago has marine and coastal which is quite spacious. Various important natural resources such as fisheries, mining and so on are in coastal areas and the sea, so that this region is a unique area with a variety of interests to exploit it. Therefore, to preserve a sustainable manner need good management and comprehensive. To the national and local level legal regulations have been published relating to the management of coastal and marine areas. However, in practice it has not been able to function optimally. Substantially has not touched the problems of the region, especially concerning the interests of local communities (local). This study is a legal non-doctrinal approach to socio-legal studies. Based on the results of research in some coastal and marine areas in Bengkulu province - Indonesia, there is a fact that the system of customary law and local wisdom began to weaken implementation. Therefore harmonization needs to be done in implementing laws and regulations that apply to the values of indigenous and local knowledge that exists in the community.

Keywords: coastal and marine, harmonization, law, local

Procedia PDF Downloads 297

Authors: D. S. V. Barbieri, R. R. Gomes, G. D. Santos, P. F. Herkert, M. Moreira, E. S. Trindade, V. A. Vicente

Abstract:

The importance of yeast infections has increased in recent decades. The monitoring of Candida yeasts has been relevant in the study of groups and populations. This research evaluated 31 Candida spp. isolates from oral microbiota of 12 Brazilian schoolchildren coinfected with Streptococcus mutans. The isolates were evaluated for their ability to form biofilm in vitro and molecularly characterized based on the sequencing of intergenic spacer regions ITS1-5,8S-ITS2 and variable domains of the large subunit (D1/D2) regions of the rDNA, as well as ABC system genotyping. The sequencing confirmed 26 lineages of Candida albicans, three Candida tropicalis, one Candida guillhermondii and one Candida glabrata. Genetic variability and differences on in biofilm formation were observed among Candida yeasts lineages. At least one Candida strain from each caries activity child was C.albicans genotype A or Candida non-albicans. C. tropicalis was associated with highest cavities rates. These results indicate that the presence of C. albicans genotype A or multi-colonization by non albicans species seem to be associates to the potentialization of caries risk.

Keywords: biofilm, Candida albicans, oral microbiota, caries

Procedia PDF Downloads 478

Authors: Michael Ricardo Lang, AdriéLle Costa, Ivana Iesbik, Karine Haag, Leonardo Trindade Buffara, Oscar Reimann Junior, Chelin Auswaldt Steclan

Abstract:

Stroke affects not only the individual, but has significant impacts on the social and family context. Therefore, it is necessary to know the peculiarities of each region, in order to contribute to regional public health policies effectively. Thus, the present study discusses biomarkers in a post-stroke population, admitted to a stroke unit (U-stroke) of reference in the southern region of Brazil. Biomarkers were analyzed, such as age, length of stay, mortality rate, survival time, risk factors and family history of stroke in patients after ischemic stroke. In this studied population, comparing men and women, it was identified that men were more affected than women, and the average age of women affected was higher, as they also had the highest mortality rate and the shortest hospital stay. The risk factors identified here were according to the global scenario; with SAH being the most frequent and those associated with sedentary lifestyle in women the most frequent (dyspilipidemia, heart disease and obesity). In view of this, the importance of studies that characterize populations regionally is evident, strengthening the strategic planning of policies in favor of health care.

Keywords: biomarkers, sex, stroke, stroke unit, population

Procedia PDF Downloads 224

Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

Abstract:

Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

Procedia PDF Downloads 334

Authors: Milda A. Cruz-Huaranga, Natalí Carbo-Bustinza, Javier Linkolk López-Gonzales, K. Depaz, Gina M. Tito T., Soledad Torres-Calderón

Abstract:

The objective of this study was to improve water quality in the “La Mansión” pond in order to irrigate green spaces on the Peruvian Union University campus (Lima, Peru) using the aquatic species Eichhornia Crassipes. Furthermore, tree trimming and cleaning activities were performed that reduced water pollution caused by organic deposits and feathers from wild birds. The impaired waterbody is located on the campus of the Peruvian Union University, 580 meters above sea level, with a volume of 6,405.336 m3, an area of 3,050.16 m2, 256.81 m perimeter, and 0.12 m3/s input flow. Seven 1.8 m2 floating systems were implemented, with 12 common water hyacinth plants in each system. Before implementing this system, a water quality analysis was performed to analyse the physical-chemical, microbiological, and organoleptic parameters. The pre-analysis revealed the pond’s critical condition, with electrical conductivity: 556 mg/l; phosphate: < 0.5; pH: 7.06; total solids: 412 mg/l; arsenic: <0.01; lead: 0.115; BOD5: 14; COD: 16.94; dissolved oxygen: 13; total coliforms: 24000 MCL/100 ml; and thermo-tolerant coliforms: 11000 MCL/100 ml. After implementing the system, the following results were obtained: EC: 495 mg/l; DO:9.2 mg/l; TS: 235 mg/l; BOD5: 7.7; COD: 8.47; Pb: 0.001 mg/l; TC: 460 MCL/100 ml; FC: 240 MCL/100 ml. Thus, we confirmed that the system is 78.79% efficient regarding the Peruvian ECA (Environmental Quality Standards) established for water according to DS #015-2015-MINAM. Therefore, the water is suitable for plant irrigation. Finally, we concluded that treating wastewater with the species Eichhornia Crassipes is efficient since an improvement was achieved in the impaired waterbody.

Keywords: Eichhornia crassipes, plantlets, cleaning, impaired waterbody, pond

Procedia PDF Downloads 98

Authors: Ridwaan N. Milase, Leonardo J. Van Zyl, Marla Trindade

Abstract:

American foulbrood (AFB) is the world’s most devastating honeybee disease that has drastically reduced the population of Apis mellifera capensis since 2009. The outbreak has jeopardized the South African bee keeping industry as well as the agricultural sector dependent on honeybees for honey production and pollination, leading to significant economic losses. AFB is caused by Paenibacillus larvae, a spore-forming, Gram positive facultative anaerobic and flagellated bacterium. The use of antibiotics within beehives has selected for resistant strains of P. larvae, while the current practice of burning spore contaminated beehives and equipment contributes to the economic losses in the honeybee-keeping industry. Therefore, phage therapy is proposed as a promising alternative to combat P. larvae strains affecting A. mellifera capensis. The genomes of two P. larvae strains isolated from infected combs in the Western Cape have been sequenced and annotated using bioinformatics tools. Genome analyses has revealed that these P. larvae strains are lysogens to more than 6 different prophages and possess different type of clustered regularly interspaced short palindromic repeat (CRISPRs) regions per strain. Active prophages from one of the two P. larvae strains were detected and identified using PCR. Electron microscopy was used to determine the family of the identified active prophages. Lytic bacteriophages that specifically target the two P. larvae strains were purified from sewage wastewater, beehive materials, and soil samples to investigate their potential development as anti-P. larvae agents. Another alternative treatment being investigated is the development of a prophage endolysin cocktail. Endolysin genes of the prophages have been targeted, cloned and expressed in Escherichia coli. The heterologously expressed endolysins have been purified and are currently being assessed for their lytic activity against P. larvae strains and other commensal microorganisms that compose the honeybee larvae microbiota. The study has shown that phage therapy and endolysins have a great potential as alternative control methods for AFB disease affecting A. mellifera capensis.

Keywords: American foulbrood, bacteriophage, honeybee, Paenibacillus larvae

Procedia PDF Downloads 148

Authors: Jovana Vukcevic, Sanja Pekovic, Djurdjica Perovic, Tatjana Stanovcic

Abstract:

This paper presents a critical inquiry into the role of uncomfortable heritage in nation branding with the particular focus on the specificities of the politics of memory, forgetting and revisionism in the post-communist post-Yugoslavia. It addresses legacies of unwanted, ambivalent or unacknowledged past and different strategies employed by the former-Yugoslav states and private actors in “rebranding” their heritage, ensuring its preservation, but re-contextualizing the narrative of the past through contemporary tourism practices. It questions the interplay between nostalgia, heritage and market, and the role of heritage in polishing the history of totalitarian and authoritarian regimes in the Balkans. It argues that in post-socialist Yugoslavia, the necessity to limit correlations with former ideology and the use of the commercial brush in shaping a marketable version of the past instigated the emergence of the profit-oriented heritage practices. Building on that argument, the paper addresses these issues as “commodification” and “disneyfication” of Balkans’ ambivalent heritage, contributing to the analysis of changing forms of memorialisation and heritagization practices in Europe. It questions the process of ‘coming to terms with the past’ through marketable forms of heritage tourism, fetching the boundary between market-driven nostalgia and state-imposed heritage policies. In order to analyse plurality of ways of dealing with controversial, ambivalent and unwanted heritage of dictatorships in the Balkans, the paper considers two prominent examples of heritage commodification in Serbia and Montenegro, and the re-appropriations of those narratives for the nation branding purposes. The first one is the story of the Tito’s Blue Train, the landmark of the socialist past and the symbol of Yugoslavia which has nowadays being used for birthday parties and marriage celebrations, while the second emphasises the unusual business arrangement turning the fortress Mamula, former concentration camp through the Second World War, into a luxurious Mediterranean resort. Questioning how the ‘uneasy’ past was acknowledged and embedded into the official heritage institutions and tourism practices, study examines the changing relation towards the legacies of dictatorships, inviting us to rethink the economic models of the things past. Analysis of these processes should contribute to better understanding of the new mnemonics strategies and (converging?) ways of ‘doing’ past in Europe.

Keywords: commodification, heritage tourism, totalitarianism, Serbia, Montenegro

Procedia PDF Downloads 209

Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

Abstract:

In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

Procedia PDF Downloads 52

Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

Abstract:

Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

Procedia PDF Downloads 314