Is professional recognition in plastic surgery related to activity in research

OBJECTIVE: To evaluate the relation of medical research, with the participation of prominent plastic surgeon in Congress.METHODS: We reviewed the scientific programs of the last 3 Brazilian Congress of Surgery, were selected 21 Brazilian plástic surgeons invited to serve as panelists or speakers in roundtable sessions in the last 3 congresses (Group 1). We randomly selected and paired by other members (associates) of the Brazilian Society of Plastic Surgery, with no participation in congress as speaker (Group 2). We conducted a search for articles published in journals indexed in Medline, Lilacs and SciELO for all doctors selected during the entire academic career and the last 5 years from March 2007 until March 2012. We assessed the research activity through the simple counting of the number of publications in indexed journals for each professional. The number of publications groups was compared.RESULTS: articles produced throughout career: Group 1- 639 articles (average of 30.42 items each). Group 2- 79 articles (mean 3.95 articles each). Difference between medias: p <0.001.CONCLUSION: The results demonstrate that the Brazilian Society of Plastic Surgery seeking professionals with a greater number of publications and journals of higher impact. This approach encourages new members to pursue a higher qualification, and give security to congressmen, they can rely on the existence of a technical criterion in the choice of speakers.

Antigenic characterization of Brazilian bovine viral diarrhea virus isolates by monoclonal antibodies and cross-neutralization

Nineteen Brazilian isolates of bovine viral diarrhea virus (BVDV) were characterized antigenically with a panel of 19 monoclonal antibodies (mAbs) (Corapi WV, Donis RO and Dubovi EJ (1990) American Journal of Veterinary Research, 55: 1388-1394). Eight isolates were further characterized by cross-neutralization using sheep monospecific antisera. Analysis of mAb binding to viral antigens by indirect immunofluorescence revealed distinct patterns of reactivity among the native viruses. Local isolates differed from the prototype Singer strain in recognition by up to 14 mAbs. Only two mAbs - one to the non-structural protein NS23/p125 and another to the envelope glycoprotein E0/gp48 - recognized 100% of the isolates. No isolate was recognized by more than 14 mAbs and twelve viruses reacted with 10 or less mAbs. mAbs to the major envelope glycoprotein E2/gp53 revealed a particularly high degree of antigenic variability in this glycoprotein. Nine isolates (47.3%) reacted with three or less of 10 E2/gp53 mAbs, and one isolate was not recognized by any of these mAbs. Virus-specific antisera to eight isolates plus three standard BVDV strains raised in lambs had virus-neutralizing titers ranging from 400 to 3200 against the homologous virus. Nonetheless, many antisera showed significantly reduced neutralizing activity when tested against heterologous viruses. Up to 128-fold differences in cross-neutralization titers were observed for some pairs of viruses. When the coefficient of antigenic similarity (R) was calculated, 49 of 66 comparisons (74.24%) between viruses resulted in R values that antigenically distinguish strains. Moreover, one isolate had R values suggesting that it belongs to a distinct serologic group. The marked antigenic diversity observed among Brazilian BVDV isolates should be considered when planning diagnostic and immunization strategies.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Statistical analysis of event-related potential elicited by verb-complement merge in Brazilian Portuguese

An interesting fact about language cognition is that stimulation involving incongruence in the merge operation between verb and complement has often been related to a negative event-related potential (ERP) of augmented amplitude and latency of ca. 400 ms - the N400. Using an automatic ERP latency and amplitude estimator to facilitate the recognition of waves with a low signal-to-noise ratio, the objective of the present study was to study the N400 statistically in 24 volunteers. Stimulation consisted of 80 experimental sentences (40 congruous and 40 incongruous), generated in Brazilian Portuguese, involving two distinct local verb-argument combinations (nominal object and pronominal object series). For each volunteer, the EEG was simultaneously acquired at 20 derivations, topographically localized according to the 10-20 International System. A computerized routine for automatic N400-peak marking (based on the ascendant zero-cross of the first waveform derivative) was applied to the estimated individual ERP waveform for congruous and incongruous sentences in both series for all ERP topographic derivations. Peak-to-peak N400 amplitude was significantly augmented (P < 0.05; one-sided Wilcoxon signed-rank test) due to incongruence in derivations F3, T3, C3, Cz, T5, P3, Pz, and P4 for nominal object series and in P3, Pz and P4 for pronominal object series. The results also indicated high inter-individual variability in ERP waveforms, suggesting that the usual procedure of grand averaging might not be considered a generally adequate approach. Hence, signal processing statistical techniques should be applied in neurolinguistic ERP studies allowing waveform analysis with low signal-to-noise ratio.

IgE cross-reactivity between Lolium multiflorum and commercial grass pollen allergen extracts in Brazilian patients with pollinosis

Lolium multiflorum (Lm) grass pollen is the major cause of pollinosis in Southern Brazil. The objectives of this study were to investigate immunodominant components of Lm pollen allergens and the cross-reactivity of IgE with commercial grass pollen allergen extracts. Thirty-eight serum samples from patients with seasonal allergic rhinitis (SAR), 35 serum samples from patients with perennial allergic rhinitis (PAR) and 30 serum samples from non-atopic subjects were analyzed. Allergen sensitization was evaluated using skin prick test and serum IgE levels against Lm pollen extract were determined by ELISA. Inhibition ELISA and immunoblot were used to evaluate the cross-reactivity of IgE between allergens from Lm and commercial grass pollen extracts, including L. perenne (Lp), grass mix I (GI) and II (GII) extracts. IgE antibodies against Lm were detected in 100% of SAR patients and 8.6% of PAR patients. Inhibition ELISA demonstrated IgE cross-reactivity between homologous (Lm) and heterologous (Lp or GII) grass pollen extracts, but not for the GI extract. Fifteen IgE-binding Lm components were detected and immunoblot bands of 26, 28-30, and 32-35 kDa showed >90% recognition. Lm, Lp and GII extracts significantly inhibited IgE binding to the most immunodominant Lm components, particularly the 55 kDa band. The 26 kDa and 90-114 kDa bands presented the lowest amount of heterologous inhibition. We demonstrated that Lm extract contains both Lm-specific and cross-reactive IgE-binding components and therefore it is suitable for measuring quantitative IgE levels for diagnostic and therapeutic purposes in patients with pollinosis sensitized to Lm grass pollen rather than other phylogenetically related grass pollen extracts.

Cross Listing of a Finnish Company on an Exchange in the United States of America

Finnish companies cross listing in the United States is an exceptional phenomenon. This study examines the cross listing decision, cross listing choice and cross listing process with associated challenges and critical factors. The aim is to create an in-depth understanding of the cross listing process and the required financial information. Based on that, the aim is to establish the process phases with the challenges and the critical factors that ought to be considered be- fore establishing the process plus re-evaluated and further considered at points in time during the process. The empirical part of this study is conducted as a qualitative study. The research data was collected through the adoption of two approaches, which are the interview approach and the textual data approach. The interviews were conducted with Finnish practitioners in the field of accounting and finance. The textual data was from publicly available publications of this phenomenon by the two BIG5 accounting companies worldwide. The results of this study demonstrate the benefits of cross listing in the U.S. are the better growth opportunities, the reduction of cost of capital and the production of higher quality financial information. In the decision making process companies should assess whether the benefits exceed the increased costs, the pressure for performance, the uncertainty of market recognition and the requirements of management. The exchange listing is seen as the most favourable cross listing choice for Finnish companies. The establishment of the processes for producing reliable, transparent and timely financial information was seen as both highly critical and very challenging. The critical success factors relating to the cross listing phases are the assessment and planning as well as the right mix of experiences and expertise. The timing plays important role in the process. The results mainly corroborate the literature concerning cross listing decision and choice. This study contributes to the literature on the cross listing process offering a useful model for the phases of the cross listing process.

Recognition of nucleic acids by metal ion complexes

Metal-ion-mediated base-pairing of nucleic acids has attracted considerable attention during the past decade, since it offers means to expand the genetic code by artificial base-pairs, to create predesigned molecular architecture by metal-ion-mediated inter- or intra-strand cross-links, or to convert double stranded DNA to a nano-scale wire. Such applications largely depend on the presence of a modified nucleobase in both strands engaged in the duplex formation. Hybridization of metal-ion-binding oligonucleotide analogs with natural nucleic acid sequences has received much less attention in spite of obvious applications. While the natural oligonucleotides hybridize with high selectivity, their affinity for complementary sequences is inadequate for a number of applications. In the case of DNA, for example, more than 10 consecutive Watson-Crick base pairs are required for a stable duplex at room temperature, making targeting of sequences shorter than this challenging. For example, many types of cancer exhibit distinctive profiles of oncogenic miRNA, the diagnostics of which is, however, difficult owing to the presence of only short single stranded loop structures. Metallo-oligonucleotides, with their superior affinity towards their natural complements, would offer a way to overcome the low stability of short duplexes. In this study a number of metal-ion-binding surrogate nucleosides were prepared and their interaction with nucleoside 5´-monophosphates (NMPs) has been investigated by 1H NMR spectroscopy. To find metal ion complexes that could discriminate between natural nucleobases upon double helix formation, glycol nucleic acid (GNA) sequences carrying a PdII ion with vacant coordination sites at a predetermined position were synthesized and their affinity to complementary as well as mismatched counterparts quantified by UV-melting measurements.

Involvement of fimbriae in host-mycoparasite recognition

Extracellular, non-flagellar appendages, termed fimbriae are widespread among fungi. Fungal fimbriae range in diameter from 6-10 nm and exhibit lengths of up to 30 ~m. Fungal fimbriae have been implicated in several functions: adhesion, conjugation and flocculation. A possible role of fimbriae in host-mycoparasite interactions was the focus of this study . Using electron microscopy, fimbriae were observed on the surfaces of Mortiere lla cande labrum, Mortie re lla pusi lla and Phascolomyces articulosus with diameter means of 9.1±0.4 nm, 9.4±0.5 nm and 8.6±0.6 nm, respectively, and lengths of up to 25 ~m. Fimbriae were not observed on the surface of the mycoparasite, Piptocephalis virginiana. Polyclonal antiserum (AU) prepared against the fimbrial protein of Ustilago violacea cross-reacted with 60 and 57 kDa M. candelabrum proteins. In addition, AU cross-reacted with 64 kDa proteins from both M. pusilla and P. articulosus. The proteins that cross-reacted with AU were electroeluted from polyacrylamide gels and were shown to subsequently form fibrils. The diameter means for the electroeluted fibrils were: for M. candelabrum 9.7±0.3 nm, M. pusilla 8.4±0.6 nm and P articulosus 9.2±0.5 nm. Finally, to ascertain the role of fimbriae in host-mycoparasite interactions, AU was incubated with P. virginiana and M. pusilla (mycoparasite/susceptible host) and with P. virginiana and P . articulosus (mycoparasite/ resistant host). It was observed that AU decreased significantly the level of contact between P. virginiana and M. pusilla and between P. virginiana and P. articulosus in comparison to prelmmune serum treatments. Thus, it was proposed that fimbriae might play recognition and attachment roles in early events of mycoparasitism.

The generation effect and word learning: a test of the effect of the language experience approach versus the text approach in the acquisition of new reading vocabulary

A class of twenty-two grade one children was tested to determine their reading levels using the Stanford Diagnostic Reading Achievement Test. Based on these results and teacher input the students were paired according to reading ability. The students ages ranged from six years four months to seven years four months at the commencement of the study. Eleven children were assigned to the language experience group and their partners became the text group. Each member of the language experience group generated a list of eight to be learned words. The treatment consisted of exposing the student to a given word three times per session for ten sessions, over a period of five days. The dependent variables consisted of word identification speed, word identification accuracy, and word recognition accuracy. Each member of the text group followed the same procedure using his/her partner's list of words. Upon completion of this training, the entire process was repeated with members of the text group from the first part becoming members of the language experience group and vice versa. The results suggest that generally speaking language experience words are identified faster than text words but that there is no difference in the rate at which these words are learned. Language experience words may be identified faster because the auditory-semantic information is more readily available in them than in text words. The rate of learning in both types of words, however, may be dictated by the orthography of the to be learned word.

An Investigation of the Role of Attention in the Cross-Race Effect: An Ecological Approach

The current set of studies was conducted to examine the cross-race effect (CRE), a phenomenon commonly found in the face perception literature. The CRE is evident when participants display better own-race face recognition accuracy than other-race recognition accuracy (e.g. Ackerman et al., 2006). Typically the cross-race effect is attributed to perceptual expertise, (i.e., other-race faces are processed less holistically; Michel, Rossion, Han, Chung & Caldara, 2006), and the social cognitive model (i.e., other-race faces are processed at the categorical level by virtue of being an out-group member; Hugenberg, Young, Bernstein, & Sacco, 2010). These effects may be mediated by differential attention. I investigated whether other-race faces are disregarded and, consequently, not remembered as accurately as own-race (in-group) faces. In Experiment 1, I examined how the magnitude of the CRE differed when participants learned individual faces sequentially versus when they learned multiple faces simultaneously in arrays comprising faces and objects. I also examined how the CRE differed when participants recognized individual faces presented sequentially versus in arrays of eight faces. Participants’ recognition accuracy was better for own-race faces than other-race faces regardless of familiarization method. However, the difference between own- and other-race accuracy was larger when faces were familiarized sequentially in comparison to familiarization with arrays. Participants’ response patterns during testing differed depending on the combination of familiarization and testing method. Participants had more false alarms for other-race faces than own-race faces if they learned faces sequentially (regardless of testing strategy); if participants learned faces in arrays, they had more false alarms for other-race faces than own-races faces if ii i they were tested with sequentially presented faces. These results are consistent with the perceptual expertise model in that participants were better able to use the full two seconds in the sequential task for own-race faces, but not for other-race faces. The purpose of Experiment 2 was to examine participants’ attentional allocation in complex scenes. Participants were shown scenes comprising people in real places, but the head stimuli used in Experiment 1 were superimposed onto the bodies in each scene. Using a Tobii eyetracker, participants’ looking time for both own- and other-race faces was evaluated to determine whether participants looked longer at own-race faces and whether individual differences in looking time correlated with individual differences in recognition accuracy. The results of this experiment demonstrated that although own-race faces were preferentially attended to in comparison to other-race faces, individual differences in looking time biases towards own-race faces did not correlate with individual differences in own-race recognition advantages. These results are also consistent with perceptual expertise, as it seems that the role of attentional biases towards own-race faces is independent of the cognitive processing that occurs for own-race faces. All together, these results have implications for face perception tasks that are performed in the lab, how accurate people may be when remembering faces in the real world, and the accuracy and patterns of errors in eyewitness testimony.

Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

English-Malayalam Cross-Lingual Information Retrieval – an Experience

This paper describes about an English-Malayalam Cross-Lingual Information Retrieval system. The system retrieves Malayalam documents in response to query given in English or Malayalam. Thus monolingual information retrieval is also supported in this system. Malayalam is one of the most prominent regional languages of Indian subcontinent. It is spoken by more than 37 million people and is the native language of Kerala state in India. Since we neither had any full-fledged online bilingual dictionary nor any parallel corpora to build the statistical lexicon, we used a bilingual dictionary developed in house for translation. Other language specific resources like Malayalam stemmer, Malayalam morphological root analyzer etc developed in house were used in this work

An Online Character Recognition System to Convert Grantha Script to Malayalam

This paper presents a novel approach to recognize Grantha, an ancient script in South India and converting it to Malayalam, a prevalent language in South India using online character recognition mechanism. The motivation behind this work owes its credit to (i) developing a mechanism to recognize Grantha script in this modern world and (ii) affirming the strong connection among Grantha and Malayalam. A framework for the recognition of Grantha script using online character recognition is designed and implemented. The features extracted from the Grantha script comprises mainly of time-domain features based on writing direction and curvature. The recognized characters are mapped to corresponding Malayalam characters. The framework was tested on a bed of medium length manuscripts containing 9-12 sample lines and printed pages of a book titled Soundarya Lahari writtenin Grantha by Sri Adi Shankara to recognize the words and sentences. The manuscript recognition rates with the system are for Grantha as 92.11%, Old Malayalam 90.82% and for new Malayalam script 89.56%. The recognition rates of pages of the printed book are for Grantha as 96.16%, Old Malayalam script 95.22% and new Malayalam script as 92.32% respectively. These results show the efficiency of the developed system

Face Recognition using Probabilistic Neural Networks

In this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results