Naturally occurring radioactive materials: a method for assessing the risk of exposure

Naturally Occurring Radioactive Materials (NORM) are materials that are found naturally in the environment and contain radioactive isotopes that can cause negative effects on the health of workers who manipulate them. Present in underground work like mining and tunnel construction in granite zones, these materials are difficult to identify and characterize without appropriate equipment for risk evaluation. The assessing methods were exemplified with a case study applied to the handling and processing of phosphoric rock where one found significant amounts of radioactive isotopes and consequently elevated radon concentrations in enclosed spaces containing these materials. © 2015 Taylor & Francis Group, London.

The use of the boundary element method in the analysis of single lap joints

The most common techniques for stress analysis/strength prediction of adhesive joints involve analytical or numerical methods such as the Finite Element Method (FEM). However, the Boundary Element Method (BEM) is an alternative numerical technique that has been successfully applied for the solution of a wide variety of engineering problems. This work evaluates the applicability of the boundary elem ent code BEASY as a design tool to analyze adhesive joints. The linearity of peak shear and peel stresses with the applied displacement is studied and compared between BEASY and the analytical model of Frostig et al., considering a bonded single-lap joint under tensile loading. The BEM results are also compared with FEM in terms of stress distributions. To evaluate the mesh convergence of BEASY, the influence of the mesh refinement on peak shear and peel stress distributions is assessed. Joint stress predictions are carried out numerically in BEASY and ABAQUS®, and analytically by the models of Volkersen, Goland, and Reissner and Frostig et al. The failure loads for each model are compared with experimental results. The preparation, processing, and mesh creation times are compared for all models. BEASY results presented a good agreement with the conventional methods.

Preliminary study on the production of functionally graded materials by friction stir processing

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Mecânica

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Parallel hyperspectral compressive sensing method on GPU

Remote hyperspectral sensors collect large amounts of data per flight usually with low spatial resolution. It is known that the bandwidth connection between the satellite/airborne platform and the ground station is reduced, thus a compression onboard method is desirable to reduce the amount of data to be transmitted. This paper presents a parallel implementation of an compressive sensing method, called parallel hyperspectral coded aperture (P-HYCA), for graphics processing units (GPU) using the compute unified device architecture (CUDA). This method takes into account two main properties of hyperspectral dataset, namely the high correlation existing among the spectral bands and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. Experimental results conducted using synthetic and real hyperspectral datasets on two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN, reveal that the use of GPUs can provide real-time compressive sensing performance. The achieved speedup is up to 20 times when compared with the processing time of HYCA running on one core of the Intel i7-2600 CPU (3.4GHz), with 16 Gbyte memory.

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.

Parallel method for sparse semisupervised hyperspectral unmixing

Parallel hyperspectral unmixing problem is considered in this paper. A semisupervised approach is developed under the linear mixture model, where the abundance's physical constraints are taken into account. The proposed approach relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. Since Libraries are potentially very large and hyperspectral datasets are of high dimensionality a parallel implementation in a pixel-by-pixel fashion is derived to properly exploits the graphics processing units (GPU) architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for real hyperspectral datasets reveal significant speedup factors, up to 164 times, with regards to optimized serial implementation.

Advanced image processing techniques for detection and quantification of drusen

Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology

Parallel hyperspectral unmixing method on GPU

Many Hyperspectral imagery applications require a response in real time or near-real time. To meet this requirement this paper proposes a parallel unmixing method developed for graphics processing units (GPU). This method is based on the vertex component analysis (VCA), which is a geometrical based method highly parallelizable. VCA is a very fast and accurate method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Experimental results obtained for simulated and real hyperspectral datasets reveal considerable acceleration factors, up to 24 times.

Calibration Method for Underwater Visual Ground-Truth System

This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Detection of HIV and HCV RNA in semen from Brazilian coinfected men using multiplex PCR before and after semen washing

INTRODUCTION: Prolonged survival of patients under HAART has resulted in new demands for assisted reproductive technologies. HIV serodiscordant couples wish to make use of assisted reproduction techniques in order to avoid viral transmission to the partner or to the newborn. It is therefore essential to test the effectiveness of techniques aimed at reducing HIV and HCV loads in infected semen using molecular biology tests. METHODS: After seminal analysis, semen samples from 20 coinfected patients were submitted to cell fractioning and isolation of motile spermatozoa by density gradient centrifugation and swim-up. HIV and HCV RNA detection tests were performed with RNA obtained from sperm, seminal plasma and total semen. RESULTS: In pre-washing semen, HIV RNA was detected in 100% of total semen samples, whereas HCV RNA was concomitantly amplified in only one specimen. Neither HIV nor HCV were detected either in the swim-up or in the post-washing semen fractions. CONCLUSIONS: Reduction of HIV and/or HCV shedding in semen by density gradient centrifugation followed by swim-up is an efficient method. These findings lead us to believe that, although semen is rarely found to contain HCV, semen processing is highly beneficial for HIV/HCV coinfected individuals.

Feasibility and acceptability of an exergame intervention for schizophrenia

Objectives To evaluate the feasibility and acceptability of an exergame intervention as a tool to promote physical activity in outpatients with schizophrenia. Design Feasibility/Acceptability Study and Quasi-Experimental Trial. Method Sixteen outpatients with schizophrenia received treatment as usual and they all completed an 8-week exergame intervention using Microsoft Kinect® (20 min sessions, biweekly). Participants completed pre and post treatment assessments regarding functional mobility (Timed Up and Go Test), functional fitness performance (Senior Fitness Test), motor neurological soft signs (Brief Motor Scale), hand grip strength (digital dynamometer), static balance (force plate), speed of processing (Trail Making Test), schizophrenia-related symptoms (Positive and Negative Syndrome Scale) and functioning (Personal and Social Performance Scale). The EG group completed an acceptability questionnaire after the intervention. Results Attrition rate was 18.75% and 69.23% of the participants completed the intervention within the proposed schedule. Baseline clinical traits were not related to game performance indicators. Over 90% of the participants rated the intervention as satisfactory and interactive. Most participants (76.9%) agreed that this intervention promotes healthier lifestyles and is an acceptable alternative to perform physical activity. Repeated-measures MANOVA analyses found no significant multivariate effects for combined outcomes. Conclusion This study established the feasibility and acceptability of an exergame intervention for outpatients with schizophrenia. The intervention proved to be an appealing alternative to physical activity. Future trials should include larger sample sizes, explore patients' adherence to home-based exergames and consider greater intervention dosage (length, session duration, and/or frequency) in order to achieve potential effects.

Reliability of Two Methods for Identifying the Postural Phase of Gait Initiation in Healthy and Post-stroke Subjects

This study aims to compare two methods of assessing the postural phase of gait initiation as to intrasession reliability, in healthy and post-stroke subjects. As a secondary aim, this study aims to analyse anticipatory postural adjustments during gait initiation based on the centre of pressure (CoP) displacements in post-stroke participants. The CoP signal was acquired during gait initiation in fifteen post-stroke subjects and twenty-three healthy controls. Postural phase was identified through a baseline-based method and a maximal displacement based method. In both healthy and post-stroke participants higher intra-class correlation coefficient and lower coefficient of variation values were obtained with the baseline-based method when compared to the maximal displacement based method. Post-stroke participants presented decreased CoP displacement backward and toward the first swing limb compared to controls when the baseline-based method was used. With the maximal displacement based method, there were differences between groups only regarding backward CoP displacement. Postural phase duration in medial-lateral direction was also increased in post-stroke participants when using the maximal displacement based method. The findings obtained indicate that the baseline-based method is more reliable detecting the onset of gait initiation in both groups, while the maximal displacement based method presents greater sensitivity for post-stroke participants.

HIGH SENSITIVE PCR METHOD FOR DETECTION OF PATHOGENIC Leptospira spp. IN PARAFFIN-EMBEDDED TISSUES

This study describes the development and application of a new PCR assay for the specific detection of pathogenic leptospires and its comparison with a previously reported PCR protocol. New primers were designed for PCR optimization and evaluation in artificially-infected paraffin-embedded tissues. PCR was then applied to post-mortem, paraffin-embedded samples, followed by amplicon sequencing. The PCR was more efficient than the reported protocol, allowing the amplification of expected DNA fragment from the artificially infected samples and from 44% of the post-mortem samples. The sequences of PCR amplicons from different patients showed >99% homology with pathogenic leptospires DNA sequences. The applicability of a highly sensitive and specific tool to screen histological specimens for the detection of pathogenic Leptospira spp. would facilitate a better assessment of the prevalence and epidemiology of leptospirosis, which constitutes a health problem in many countries.

Contraceptive Choices Pre and Post Pregnancy in Adolescence

STUDY OBJECTIVE: The main aim of this study is to evaluate the impact of adolescent pregnancy in the future contraceptive choices. A secondary aim is to verify whether these choices differ from those made after an abortion. DESIGN: Retrospective study. SETTING:Adolescent Unit of a tertiary care center. PARTICIPANTS:212 pregnant teenagers. INTERVENTIONS: Medical records review. MAIN OUTCOME MEASURES:Intended pregnancy rate and contraceptive methods used before and after pregnancy. For contraceptive choices after pregnancy we considered: Group 1 - teenagers who continued their pregnancy to delivery (n = 106) and Group 2 - the same number of adolescents who chose to terminate their pregnancy. RESULTS: The intended pregnancy rate was 14.2%. Prior to a pregnancy continued to delivery, the most widely used contraceptive method was the male condom (50.9%), followed by oral combined contraceptives (28.3%); 18.9% of adolescents were not using any contraceptive method. After pregnancy, contraceptive implant was chosen by 70.8% of subjects (P < .001) and the oral combined contraceptives remained the second most frequent option (17.9%, P = .058). Comparing these results with Group 2, we found that the outcome of the pregnancy was the main factor in the choices that were made. Thus, after a pregnancy continued to delivery, adolescents prefer the use of LARC [78.4% vs 40.5%, OR: 5,958 - 95% (2.914-12.181), P < .001)], especially contraceptive implants [70.8% vs 38.7%, OR: 4.371 - 95% (2.224-8.591), P < .001], to oral combined contraceptives [17.9% vs 57.5%, OR: 0.118 - 95% CI (0.054-0.258), P < .001]. CONCLUSION:Adolescent pregnancy and its outcome constitute a factor of change in future contraceptive choice.