Ki-67 expression in non-tumour epithelium adjacent to oral cancer as risk marker for multiple oral tumours

Objective: The aim of this study was to determine whether the differential assessment of epithelial proliferation is useful to diagnose premalignant fields and assess the risk of multiple tumours. Material and methods: We analysed 83 oral carcinomas with associated non-tumour epithelium classified as distant or close according to its distance (> or < 1 cm) from the invasion point, and as squamous hyperplasia, mild, moderate, severe dysplasia or carcinoma in situ. Twenty-five healthy oral mucosa samples were used as controls. An immunohistochemical technique was applied using Mib-1. Ki-67 in premalignant epithelium was assessed in basal layer, parabasal layer, medium and upper third. Results: Parabasal expression was significantly higher or showed a tendency to be higher in close and distant epithelia with any histological grade than in the controls. Parabasal Ki-67 significantly differed between distant epithelia associated with multiple vs single tumours (P < 0.001) and between distant epithelia associated with multiple tumours vs controls (P < 0.001). This difference was not observed between distant epithelia associated with single tumours and controls (P = 0.175). The cut-off point that differentiated epithelia associated with multiple tumours was > 50% of Ki-67 + parabasal cells in distant epithelia, which yielded 0.88 sensitivity and 0.79 specificity. Conclusions: The concept of a precancerous field may be linked to an increase in the proliferative activity of parabasal cells.

Immediate Effect of the Resilient Splint Evaluated Using Surface Electromyography in Patients with TMD

The aim of this study was to analyze the immediate effect of resilient splints through surface electromyography testing and to compare the findings with the electromyographic profiles of asymptomatic subjects. The participants were 30 subjects, 15 patients with TMD (TMD Group) and 15 healthy subjects (Control Group), classified according to Research Diagnostic Criteria (RDC/TMD) Axis I. A resilient occlusal splint was made for each patient in the TMD Group from two mm thick silicon to cover all teeth. The EMG examination was performed before and immediately after installing the splint. Three tests were performed as follows: 1. Maximum Voluntary Contraction (MVC) using cotton rolls (standards test); 2. MVC in maximal intercuspation position; and 3. MVC with the splint in position. The EMG signal was recorded for five seconds. EMG indices were calculated to assess muscle symmetry, jaw torque, and impact. There was a statistically significant difference when comparing the results among the study groups. The symmetry index values in the Control Group were higher than the TMD Initial Group and similar to the TMD Group after the installation of the splint. The index values of torque were higher in TMD Initial Group when compared with the Controls. Impact values were lower than normal values in the TMD Initial Group and restored upon installation of the splint. The resilient occlusal splints may be used as complementary or adjunctive treatment of temporomandibular disorders.

Articulatory dysfunction in multiple sclerosis: An electropalatographic study

Dysfunction of the articulatory subsystem (i.c.. the lips, tongue, and jaw) has bccn identified as a major contributor to the reduction in speech intelligibility experienced by a high proportion of people with multiple sclerosis (MS). In particular. consonant imprecision has been reported to be the articulatory deficit that contributes most to variations in overall intelligibility of MS speakers. Electropalatography(EPG) IS an instrurncntal technique that visually documents the location and timing of tongue-topalatc contacts during speech. Although such a technique would be valuablc in objectively assessing the articulatory disturbances exhibited by individuals with dysarthria ia motor speech disorder) associated with MS, to-date no such study ha< been reported. The aim of the present study was to use EPG to assess tongue-to-palate contact patterns and articulatory timing in patients with dysarthria associated with MS. A dysarthric participant with a diagnosis of definite MS was fitted with an acrylic EPG palate (Reading EPG.?) and asked to read aloud a list of single syllable words which contained lingual consonants in the word-initial position and in consonant clusters. Each mord was repeated five times. The EPG palate was specifically moulded to tit the participant's hard palate and contained 62 electrodes that detected the tongue contacts. A non-neurologically impaired participant matched for age and sex servcd as a control. The results of the study revealed that the tongue-to-palate contacts produced by the participant with MS varied from those produced by the control in a number of ways in regard to spatial configurations and timing characteristics exhibited. The rcsults arc discussed in relation to the neuropathophysiological effects of MS on speech production. The potcntial use of EPG in programs for treating speech disorders associated with MS will be highlightcd.

Avaliação do perfil hemodinâmico de válvulas aórticas percutâneas: análise comparativa entre os dois dispositivos disponíveis no mercado - válvula auto-expansível e válvula expansível por balão

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular. Área de especialização: Intervenção Cardiovascular.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

Timing analysis of a multiple logical ring wired/wireless PROFIBUS network

Recently, there have been a few research efforts towards extending the capabilities of fieldbus networks to encompass wireless support. In previous works we have proposed a hybrid wired/wireless PROFIBUS network solution where the interconnection between the heterogeneous communication media was accomplished through bridge-like interconnecting devices. The resulting networking architecture embraced a multiple logical ring (MLR) approach, thus with multiple independent tokens, to which a specific bridging protocol extension, the inter-domain protocol (IDP), was proposed. The IDP offers compatibility with standard PROFIBUS, and includes mechanisms to support inter-cell mobility of wireless nodes. We advance that work by proposing a worst-case response timing analysis of the IDP.

Inter-application redundancy elimination in sensor networks with compiler-assisted scheduling

Most current-generation Wireless Sensor Network (WSN) nodes are equipped with multiple sensors of various types, and therefore support for multi-tasking and multiple concurrent applications is becoming increasingly common. This trend has been fostering the design of WSNs allowing several concurrent users to deploy applications with dissimilar requirements. In this paper, we extend the advantages of a holistic programming scheme by designing a novel compiler-assisted scheduling approach (called REIS) able to identify and eliminate redundancies across applications. To achieve this useful high-level optimization, we model each user application as a linear sequence of executable instructions. We show how well-known string-matching algorithms such as the Longest Common Subsequence (LCS) and the Shortest Common Super-sequence (SCS) can be used to produce an optimal merged monolithic sequence of the deployed applications that takes into account embedded scheduling information. We show that our approach can help in achieving about 60% average energy savings in processor usage compared to the normal execution of concurrent applications.

Multiple skin neoplasms in subjects under 40 years of age in Goiania, Brazil

OBJECTIVE To describe the trend for malignant skin neoplasms in subjects under 40 years of age in a region with high ultraviolet radiation indices.METHODS A descriptive epidemiological study on melanoma and nonmelanoma skin cancers that was conducted in Goiania, Midwest Brazil, with 1,688 people under 40 years of age, between 1988 and 2009. Cases were obtained fromRegistro de Câncer de Base Populacional de Goiânia(Goiania’s Population-Based Cancer File). Frequency, trends, and incidence of cases with single and multiple lesions were analyzed; transplants and genetic skin diseases were found in cases with multiple lesions.RESULTS Over the period, 1,995 skin cancer cases were observed to found, of which 1,524 (90.3%) cases had single lesions and 164 (9.7%) had multiple lesions. Regarding single lesions, incidence on men was observed to have risen from 2.4 to 3.1/100,000 inhabitants; it differed significantly for women, shifting from 2.3 to 5.3/100,000 (Annual percentage change – [APC] 3.0%, p = 0.006). Regarding multiple lesions, incidence on men was observed to have risen from 0.30 to 0.98/100,000 inhabitants; for women, it rose from 0.43 to 1.16/100,000 (APC 8.6%, p = 0.003). Genetic skin diseases or transplants were found to have been correlated with 10.0% of cases with multiple lesions – an average of 5.1 lesions per patient. The average was 2.5 in cases without that correlation.CONCLUSIONS Skin cancer on women under 40 years of age has been observed to be increasing for both cases with single and multiple lesions. It is not unusual to find multiple tumors in young people – in most cases, they are not associated with genetic skin diseases or transplants. It is necessary to avoid excessive exposure to ultraviolet radiation from childhood.

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

A Multi-DAG Model for Real-Time Parallel Applications with Conditional Execution

The 30th ACM/SIGAPP Symposium On Applied Computing (SAC 2015). 13 to 17, Apr, 2015, Embedded Systems. Salamanca, Spain.

Feature Extraction in Densely Sensed Environments: Extensions to Multiple Broadcast Domains

The vision of the Internet of Things (IoT) includes large and dense deployment of interconnected smart sensing and monitoring devices. This vast deployment necessitates collection and processing of large volume of measurement data. However, collecting all the measured data from individual devices on such a scale may be impractical and time consuming. Moreover, processing these measurements requires complex algorithms to extract useful information. Thus, it becomes imperative to devise distributed information processing mechanisms that identify application-specific features in a timely manner and with a low overhead. In this article, we present a feature extraction mechanism for dense networks that takes advantage of dominance-based medium access control (MAC) protocols to (i) efficiently obtain global extrema of the sensed quantities, (ii) extract local extrema, and (iii) detect the boundaries of events, by using simple transforms that nodes employ on their local data. We extend our results for a large dense network with multiple broadcast domains (MBD). We discuss and compare two approaches for addressing the challenges with MBD and we show through extensive evaluations that our proposed distributed MBD approach is fast and efficient at retrieving the most valuable measurements, independent of the number sensor nodes in the network.

NEUROCYSTICERCOSIS IN CHILDREN PRESENTING WITH AFEBRILE SEIZURE: CLINICAL PROFILE, IMAGING AND SERODIAGNOSIS

Neurocysticercosis (NCC) is one of the major causes of childhood seizures in developing countries including India and Latin America. In this study neurological pediatric cases presenting with afebrile seizures were screened for anti-Cysticercus antibodies (IgG) in their sera in order to estimate the possible burden of cysticercal etiology. The study included a total of 61 pediatric afebrile seizure subjects (aged one to 15 years old); there was a male predominance. All the sera were tested using a pre-evaluated commercially procured IgG-ELISA kit (UB-Magiwell Cysticercosis Kit ™). Anti-Cysticercus antibody in serum was positive in 23 of 61 (37.7%) cases. The majority of cases with a positive ELISA test presented with generalized seizure (52.17%), followed by complex partial seizure (26.08%), and simple partial seizure (21.73%). Headaches were the major complaint (73.91%). Other presentations were vomiting (47.82%), pallor (34.78%), altered sensorium (26.08%), and muscle weakness (13.04%). There was one hemiparesis case diagnosed to be NCC. In this study one child without any significant findings on imaging was also found to be positive by serology. There was a statistically significant association found between the cases with multiple lesions on the brain and the ELISA-positivity (p = 0.017). Overall positivity of the ELISA showed a potential cysticercal etiology. Hence, neurocysticercosis should be suspected in every child presenting with afebrile seizure especially with a radio-imaging supportive diagnosis in tropical developing countries or areas endemic for taeniasis/cysticercosis.