SENSITIVITY ANALYSIS OF TRACK VIBRATIONS DUE TO VERTICAL STIFFNESS VARIATION IN HIGH-SPEED RAILWAYS

High speed trains, when crossing regions with abrupt changes in vertical stiffness of the track and/or subsoil, may generate excessive ground and track vibrations. There is an urgent need for specific analyses of this problem so as to allow reliable esimates of vibration amplitude. Full understanding of these phenomena will lead to new construction solutions and mitigation of undesirable features. In this paper analytical transient solutions of dynamic response of one-dimensional systems with sudden change of foundation stiffness are derived. Results are expressed in terms of vertical displacement. Sensitivity analysis of the response amplitude is also performed. The analytical expressions presented herein, to the authors’ knowledge, have not been published yet. Although related to one-dimensional cases, they can give useful insight into the problem. Nevertheless, in order to obtain realistic response, vehicle- rail interaction cannot be omitted. Results and conclusions are confirmed using general purpose commercial software ANSYS. In conclusion, this work contributes to a better understanding of the additional vibration phenomenon due to vertical stiffness variation, permitting better control of the train velocity and optimization of the track design.

The development of the N1 and N2 components in auditory oddball paradigms: a systematic review with narrative analysis and suggested normative values

Auditory event-related potentials (AERPs) are widely used in diverse fields of today’s neuroscience, concerning auditory processing, speech perception, language acquisition, neurodevelopment, attention and cognition in normal aging, gender, developmental, neurologic and psychiatric disorders. However, its transposition to clinical practice has remained minimal. Mainly due to scarce literature on normative data across age, wide spectrumof results, variety of auditory stimuli used and to different neuropsychological meanings of AERPs components between authors. One of the most prominent AERP components studied in last decades was N1, which reflects auditory detection and discrimination. Subsequently, N2 indicates attention allocation and phonological analysis. The simultaneous analysis of N1 and N2 elicited by feasible novelty experimental paradigms, such as auditory oddball, seems an objective method to assess central auditory processing. The aim of this systematic review was to bring forward normative values for auditory oddball N1 and N2 components across age. EBSCO, PubMed, Web of Knowledge and Google Scholarwere systematically searched for studies that elicited N1 and/or N2 by auditory oddball paradigm. A total of 2,764 papers were initially identified in the database, of which 19 resulted from hand search and additional references, between 1988 and 2013, last 25 years. A final total of 68 studiesmet the eligibility criteria with a total of 2,406 participants from control groups for N1 (age range 6.6–85 years; mean 34.42) and 1,507 for N2 (age range 9–85 years; mean 36.13). Polynomial regression analysis revealed thatN1latency decreases with aging at Fz and Cz,N1 amplitude at Cz decreases from childhood to adolescence and stabilizes after 30–40 years and at Fz the decrement finishes by 60 years and highly increases after this age. Regarding N2, latency did not covary with age but amplitude showed a significant decrement for both Cz and Fz. Results suggested reliable normative values for Cz and Fz electrode locations; however, changes in brain development and components topography over age should be considered in clinical practice.

Strap repairs using embedded patches: numerical analysis and experimental results

Adhesively bonded repairs offer an attractive option for repair of aluminium structures, compared to more traditional methods such as fastening or welding. The single-strap (SS) and double-strap (DS) repairs are very straightforward to execute but stresses in the adhesive layer peak at the overlap ends. The DS repair requires both sides of the damaged structures to be reachable for repair, which is often not possible. In strap repairs, with the patches bonded at the outer surfaces, some limitations emerge such as the weight, aerodynamics and aesthetics. To minimize these effects, SS and DS repairs with embedded patches were evaluated in this work, such that the patches are flush with the adherends. For this purpose, in this work standard SS and DS repairs, and also with the patches embedded in the adherends, were tested under tension to allow the optimization of some repair variables such as the overlap length (LO) and type of adhesive, thus allowing the maximization of the repair strength. The effect of embedding the patch/patches on the fracture modes and failure loads was compared with finite elements (FE) analysis. The FE analysis was performed in ABAQUS® and cohesive zone modelling was used for the simulation of damage onset and growth in the adhesive layer. The comparison with the test data revealed an accurate prediction for all kinds of joints and provided some principles regarding this technique.

Experimental dam-break waves profile analysis: horizontal mobile bed

River Flow, Vol. 2

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. 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. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

Voltammetric analysis of mancozeb and its degradation product ethylenethiourea

The purpose of this work was to develop a reliable alternative method for the determination of the dithiocarbamate pesticide mancozeb (MCZ) in formulations. Furthermore, a method for the analysis of MCZ's major degradation product, ethylenethiourea (ETU), was also proposed. Cyclic voltammetry was used to characterize the electrochemical behavior of MCZ and ETU, and square-wave adsorptive stripping voltammetry (SWAdSV) was employed for MCZ quantification in commercial formulations. It was found that both MCZ and ETU are irreversibly reduced (− 0.6 V and − 0.5 V vs Ag/AgCl, respectively) at the surface of a glassy carbon electrode in a mainly diffusion-controlled process, presenting maximum peak current intensities at pH 7.0 (in phosphate buffered saline electrolyte). Several parameters of the SWAdSV technique were optimized and linear relationships between concentration and peak current intensity were established between 10–90 μmol L− 1 and 10–110 μmol L− 1 for MCZ and ETU, respectively. The limits of detection were 7.0 μmol L− 1 for MCZ and 7.8 μmol L− 1 for ETU. The optimized method for MCZ was successfully applied to the quantification of this pesticide in two commercial formulations. The developed procedures provided accurate and precise results and could be interesting alternatives to the established methods for quality control of the studied products, as well as for analysis of MCZ and ETU in environmental samples.

Analysis of the Out-Of-Plane Seismic Behavior of Unreinforced Masonry: A Literature Review

Although the issue of the out-of-plane response of unreinforced masonry structures under earthquake excitation is well known with consensus among the research community, this issue is simultaneously one of the more complex and most neglected areas on the seismic assessment of existing buildings. Nonetheless, its characterization should be found on the solid knowledge of the phenomenon and on the complete understanding of methodologies currently used to describe it. Based on this assumption, this article presents a general framework on the issue of the out-of-plane performance of unreinforced masonry structures, beginning with a brief introduction to the topic, followed by a compact state of art in which the principal methodologies proposed to assess the out-of-plane behavior of unreinforced masonry structures are presented. Different analytical approaches are presented, namely force and displacement-based, complemented with the presentation of existing numerical tools for the purpose presented above. Moreover, the most relevant experimental campaigns carried out in order to reproduce the phenomenon are reviewed and briefly discussed.

Recent droughts and the impact of North Atlantic Oscillation in Iberia; a spatiotemporal analysis based on vegetation temperature condition Index (VTCI)

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

LAMA2 Gene Analysis in a Cohort of 26 Congenital Muscular Dystrophy Patients

Congenital muscular dystrophy type 1A (MDC1A) is caused by mutations in the LAMA2 gene encoding laminin-alpha2. We describe the molecular study of 26 patients with clinical presentation, magnetic resonance imaging and/or laminin-alpha2 expression in muscle, compatible with MDC1A. The combination of full genomic sequencing and complementary DNA analysis led to the particularly high mutation detection rate of 96% (50/52 disease alleles). Besides 22 undocumented polymorphisms, 18 different mutations were identified in the course of this work, 14 of which were novel. In particular, we describe the first fully characterized gross deletion in the LAMA2 gene, encompassing exon 56 (c.7750-1713_7899-2153del), detected in 31% of the patients. The only two missense mutations detected were found in heterozygosity with nonsense or truncating mutations in the two patients with the milder clinical presentation and a partial reduction in muscle laminin-alpha2. Our results corroborate the previous few genotype/phenotype correlations in MDC1A and illustrate the importance of screening for gross rearrangements in the LAMA2 gene, which may be underestimated in the literature.

The impact of banks dimension on profitability, sustainability and efficiency: An analysis for the Iberian financial system

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

A constructive technology assessment of stationary energy storage systems: prospective life cycle orientated analysis

Based on the presentation and discussion at the 3rd Winter School on Technology Assessment, December 2012, Universidade Nova de Lisboa (Portugal), Caparica Campus, PhD programme on Technology Assessment

Diallelic analysis to obtain cowpea (Vigna unguiculata L. Walp.) populations tolerant to water deficit.

The purpose of this study was to identify parents and obtain segregating populations of cowpea (Vigna unguiculata L. Walp.) with the potential for tolerance to water deficit. A full diallel was performed with six cowpea genotypes, and two experiments were conducted in Teresina, PI, Brazil in 2011 to evaluate 30 F2 populations and their parents, one under water deficit and the other under full irrigation.

Development of a fundus camera for analysis of photoreceptor directionality in the healthy retina

The Stiles-Crawford effect (SCE) is the well-known phenomenon in which the brightness of light perceived by the human eye depends upon its entrance point in the pupil. This physiological characteristic is due to the directional sensitivity of the cone photoreceptors in the retina and it displays an approximately Gaussian dependency which is altered in a number of pathologies. Retinal imaging, a widely spread clinical practice, may be used to evaluate the SCE and thus serve as diagnostic tool. Nonetheless, its use for such a purpose is still underdeveloped and far from the clinical reality. In this project a fundus camera was built and used to assess the cone photoreceptor directionality by reflective imaging of the retina in healthy individuals. The physical and physiological implications of its development are addressed in detail in the text: the optical properties of the human eye, illumination issues, acquiring a retinal image formed by the eye, among others. A full description of the developmental process that led to the final measuring method and results is also given. The developed setup was successfully used to obtain high quality images of the eye fundus and in particular the parafoveal cone photoreceptors. The SCE was successfully observed and characterized. Even though considerable improvements could be done to the measurement method, the project showed the feasibility of using retinal imaging to evaluate the SCE thus motivating its usage in a clinical environment.

Multipacket reception in the presence of in-band full-duplex communication

In-Band Full-DupleX (IB-FDX) is defined as the ability for nodes to transmit and receive signals simultaneously on the same channel. Conventional digital wireless networks do not implement it, since a node’s own transmission signal causes interference to the signal it is trying to receive. However, recent studies attempt to overcome this obstacle, since it can potentially double the spectral efficiency of current wireless networks. Different mechanisms exist today that are able to reduce a significant part of the Self- Interference (SI), although specially tuned Medium Access Control (MAC) protocols are required to optimize its use. One of IB-FDX’s biggest problems is that the nodes’ interference range is extended, meaning the unusable space for other transmissions and receptions is broader. This dissertation proposes using MultiPacket Reception (MPR) to address this issue and adapts an already existing Single-Carrier with Frequency-Domain Equalization (SC-FDE) receiver to IB-FDX. The performance analysis suggests that MPR and IB-FDX have a strong synergy and are able to achieve higher data rates, when used together. Using analytical models, the optimal transmission patterns and transmission power were identified, which maximize the channel capacity with the minimal energy consumption. This was used to define a new MAC protocol, named Full-duplex Multipacket reception Medium Access Control (FM-MAC). FM-MAC was designed for a single-hop cellular infrastructure, where the Access Point (AP) and the terminals implement both IB-FDX and MPR. It divides the coverage range of the AP into a closer Full-DupleX (FDX) zone and a farther Half-DupleX (HDX) zone and adds a tunable fairness mechanism to avoid terminal starvation. Simulation results show that this protocol provides efficient support for both HDX and FDX terminals, maximizing its capacity when more FDX terminals are used.

Urinary tract infection in full-term newborn infants: value of urine culture by bag specimen collection

OBJETIVE: to evaluate the efficacy of urine culture by bag specimen for the detection of neonatal urinary tract infection in full-term newborn infants. Retrospective study (1997) including full-term newborn infants having a positive urine culture (>100,000 CFU/ml) by bag specimen collection. The urinary tract infection diagnosis was confirmed by positive urine culture (suprapubic bladder aspiration method). The select cases were divided into three groups, according to newborn infant age at the bag specimen collection: GI (< 48 h, n = 17), GII (48 h to 7 d, n = 35) and GIII (> 7 d, n = 9). Sixty one full-term newborn infants were studied (5.1 % of total infants). The diagnosis was confirmed on 19/61 (31.1 %) of full-term infants born alive. Distribution among the groups was: GI = 2/17 (11.8 %), GII = 10//35 (28.6 %), and GIII = 7/9 (77.7 %). The most relevant clinical symptoms were: fever (GI - 100 %, GII - 91.4 %) and weight loss (GI - 35.3 %, GII - 45.7 %). Urine culture results for specimens collected by suprapubic aspiration were: E. coli GI (100 %), GII (40 %) and GIII (28.6 %), E. faecalis GI (30%), Staphylococcus coagulase-negative GII (20 %) and GIII (42.8 %), and Staphylococcus aureus GII (10 %). Correlation between positive urine culture collection (bag specimen method) and urinary tract infection diagnosis, using relative risk analysis, produced the following results: GI=0.30 (CI95% 0.08-1.15), GII=0.51 (CI 95% 0.25-1.06) and GIII=3.31 (CI95% 1.8-6.06) The most frequent urinary tract infection clinical signs in the first week were fever and weight loss, while non-specific symptomatology occurred later. E. coli was most frequent infectious agent, although from the 7th day of life, staphylococcus was noted. The urine culture (bag specimen method) was effective in detecting urinary tract infection only after the 7th day of life.