Therapeutical evaluation of different dose regimens of praziquantel in schistosomiasis mansoni, based on the quantitative oogram technique

A clinical trial involving 80 patients of both sexes, from ages 15 to 55, with chronic intestinal or hepatointestinal schistosomiasis mansoni, was carried out to evaluate the therapeutical efficacy of different dose regimens of praziquantel. The patients were randomly allocated into four groups with an equal number of cases and were then treated with one of the following dosages: 60 mg/kg for 1 day; 60 mg/kg daily for 2 days; 60 mg/kg daily for 3 days; and 30 mg/kg daily for 6 days. The assessment of parasitological cure was based on the quantitative oogram technique through rectal mucosa biopsies which were undertaken prior to, as well as, 1,2,4 and 6 months post-treatment. Concurrently, stool examinations according to the qualitative Hoffman, Pons & Janer (HPJ) and the quantitative Kato-Katz (K-K) methods were also performed. The best tolerability was observed with 30 mg/kg daily for 6 days whereas the highest incidence of side-effects (mainly dizziness and nausea) was found with 60 mg/kg daily for 3 days. No serious adverse drug reaction has occurred. The achieved cure rates were: 25% with 60 mg/kg for 1 day; 60% with 60 mg/kg daily for 2 days; 89.5% with 60 mg/kg daily for 3 days; and 90% with 30 mg/kg daily for 6 days. At the same time there has been a downfall of 64%, 73%, 87% and 84% respectively, in the median number of viable S. mansoni ova per gram of tissue. Thus, a very clear direct correlation between dose and effect could be seen. The corresponding cure rates according to stool examinations by HPJ were 39%, 80%, 100% and 95%; by K-K 89%, 100%, 100% and 100%. This discrepancy in results amongst the three parasitological methods is certainly due to their unequal accuracy. In fact, when the number of viable eggs per gram of tissue fell below 5,000 the difference in the percentage of false negative findings between HPJ (28%) and K-K (80%) became significative. When this number dropped to less than 2,000 the percentage of false negative results obtained with HPJ (49%) turned significant in relation to the oogram as well. In conclusion, it has been proven that praziquantel is a highly efficacious agent against S. mansoni infections. If administered at a total dose of 180 mg/kg divided into either 3 or 6 days, it yields a 90% cure rate. Possibly, one could reach 100% by increasing the total dose to 240 mg/kg. Furthermore, it was confirmed that the quantitative oogram technique is the most reliable parasitological method when evaluating the efficacy of new drugs in schistosomiasis mansoni.

Modelling text file evaluation processes

Text file evaluation is an emergent topic in e-learning that responds to the shortcomings of the assessment based on questions with predefined answers. Questions with predefined answers are formalized in languages such as IMS Question & Test Interoperability Specification (QTI) and supported by many e-learning systems. Complex evaluation domains justify the development of specialized evaluators that participate in several business processes. The goal of this paper is to formalize the concept of a text file evaluation in the scope of the E-Framework – a service oriented framework for development of e-learning systems maintained by a community of practice. The contribution includes an abstract service type and a service usage model. The former describes the generic capabilities of a text file evaluation service. The later is a business process involving a set of services such as repositories of learning objects and learning management systems.

10 kVp rule - An anthropomorphic pelvis phantom imaging study using a CR system: impact on image quality and effective dose using AEC and manual mode

Purpose: This study aims to investigate the influence of tube potential (kVp) variation in relation to perceptual image quality and effective dose for pelvis using automatic exposure control (AEC) and non-AEC in a computed radiography (CR) system. Methods and Materials: To determine the effects of using AEC and non-AEC by applying the 10 kVp rule in two experiments using an anthropomorphic pelvis phantom. Images were acquired using 10 kVp increments (60-120 kVp) for both experiments. The first experiment, based on seven AEC combinations, produced 49 images. The mean mAs from each kVp increment were used as a baseline for the second experiment producing 35 images. A total of 84 images were produced and a panel of 5 experienced observers participated for the image scoring using the 2 AFC visual grading software. PCXMC software was used to estimate the effective dose. Results: A decrease in perceptual image quality as the kVp increases was observed both in non-AEC and AEC experiments, however no significant statistical differences (p> 0.05) were found. Image quality scores from all observers at 10 kVp increments for all mAs values using non-AEC mode demonstrates a better score up to 90 kVp. Effective dose results show a statistical significant decrease (p=0.000) on the 75th quartile from 0.3 mSv at 60 kVp to 0.1 mSv at 120 kVp when applying the 10 kVp rule in non-AEC mode. Conclusion: No significant reduction in perceptual image quality is observed when increasing kVp whilst a marked and significant effective dose reduction is observed.

Trends of T. cruzi infection based on data from blood bank screening

Between October 1988 and April 1989 a cross-sectional survey was carried out in six out of eight blood banks of Goiânia, Central Brazil. Subjects attending for first-time blood donation in the mornings of the study period (n = 1358) were interviewed and screened for T. cruzi infection as a part of a major study among blood donors. Tests to anti-T. cruzi antibodies were performed, simultaneously, by indirect hem agglutination test (IHA) and complement fixation test (CFT). A subject was considered seropositive when any one of the two tests showed a positive result. Information on age, sex, place of birth, migration and socio-economic level was recorded. Results from this survey were compared with seroprevalence rates obtained in previous studies in an attempt to analyse trend of T. cruzi infection in an endemic urban area. The overall seroprevalence of T. cruzi infection among first-time donors was found to be 3.5% (95% confidence interval 2.5%-4.5% ). The seroprevalence rate increased with age up to 45 years and then decreased. Migrants from rural areas had higher seroprevalence rates than subjects from urban counties (1.8%-16.2% vs. 0%-3.6%). A four fold decrease in prevalence rates was observed when these rates were compared with those of fifteen years ago. Two possible hypotheses to explain this difference were suggested: 1. a cohort effect related with the decrease of transmission in rural areas and/or 2. a differential proportion of people of rural origin among blood donors between the two periods. The potential usefulness of blood banks as a source of epidemiological information to monitor trends of T. cruzi infection in an urban adult population was stressed.

ErasmusApp: A Location-Based Collaborative System for Erasmus Students

This paper reports on the design and development of an Android-based context-aware system to support Erasmus students during their mobility in Porto. It enables: (i) guest users to create, rate and store personal points of interest (POI) in a private, local on board database; and (ii) authenticated users to upload and share POI as well as get and rate recommended POI from the shared central database. The system is a distributed client / server application. The server interacts with a central database that maintains the user profiles and the shared POI organized by category and rating. The Android GUI application works both as a standalone application and as a client module. In standalone mode, guest users have access to generic info, a map-based interface and a local database to store and retrieve personal POI. Upon successful authentication, users can, additionally, share POI as well as get and rate recommendations sorted by category, rating and distance-to-user.

Building a person home behavior model based on data from smart house sensors 2015

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

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.

Vertex component analysis GPU-based implementation for hyperspectral unmixing

Endmember extraction (EE) is a fundamental and crucial task in hyperspectral unmixing. Among other methods vertex component analysis ( VCA) has become a very popular and useful tool to unmix hyperspectral data. VCA is a geometrical based method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Many Hyperspectral imagery applications require a response in real time or near-real time. Thus, to met this requirement this paper proposes a parallel implementation of VCA developed for graphics processing units. The impact on the complexity and on the accuracy of the proposed parallel implementation of VCA is examined using both simulated and real hyperspectral datasets.

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

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

The visual image in Epiphanic Short History

The visual image is a fundamental component of epiphany, stressing its immediacy and vividness, corresponding to the enargeia of the traditional ekphrasis and also playing with cultural and social meanings. Morris Beja in his seminal book Epiphany in the Modern Novel, draws our attention to the distinction made by Joyce between the epiphany originated in a common object, in a discourse or gesture and the one arising in “a memorable phase of the mind itself”. This type materializes in the “dream-epiphany” and in the epiphany based in memory. On the other hand, Robert Langbaum in his study of the epiphanic mode, suggests that the category of “visionary epiphany” could account for the modern effect of an internally glowing vision like Blake’s “The Tyger”, which projects the vitality of a real tyger. The short story, whose length renders it a fitting genre for the use of different types of epiphany, has dealt with the impact of the visual image in this technique, to convey different effects and different aesthetic aims. This paper will present some examples of this occurrence in short stories of authors in whose work epiphany is a fundamental concept and literary technique: Walter Pater, Joseph Conrad, K. Mansfield, Clarice Lispector. Pater’s “imaginary portraits” concentrate on “priviledged moments” of the lives of the characters depicting their impressions through pictorial language; Conrad tries to show “moments of awakening” that can be remembered by the eye; Mansfield suggests that epiphany, the “glimpse”, should replace plot as an internal ordering principle of her impressionist short-stories; in C. Lispector the visualization of some situations is so aggressive that it causes nausea and a radical revelation on the protagonist’s.

A simple PCR-based procedure for plaque diagnosis

Supernatant of boiled spleen saline-suspensions of Yersinia pestis experimentally infected animals were used as template for PCR amplification without DNA extraction. PCR sensitivity was enhanced by a second round of amplification (Nested). No amplification was observed from non-infected animals.

PCR-BASED DIAGNOSIS OF A CASE OF HERPETIC WHITLOW IN AN AIDS PATIENT

Herpetic infections are common complications in AIDS patients. The clinical features could be uncommon and antiviral chemotherapy is imperative. A rapid diagnosis could prevent incorrect approaches and treatment. The polymerase chain reaction is a rapid, specific and sensible method for DNA amplification and diagnosis of infectious diseases, especially viral diseases. This approach has some advantages compared with conventional diagnostic procedures. Recently we have reported a new PCR protocol to rapid diagnosis of herpetic infections with suppression of the DNA extraction step. In this paper we present a case of herpetic whitlow with rapid diagnosis by HSV-1 specific polymerase chain reaction using the referred protocol.