Optimization of River Water Quality Surveys by Multivariate Analysis of Physicochemical, Bacteriological and Ecotoxicological Data

This study aims to optimize the water quality monitoring of a polluted watercourse (Leça River, Portugal) through the principal component analysis (PCA) and cluster analysis (CA). These statistical methodologies were applied to physicochemical, bacteriological and ecotoxicological data (with the marine bacterium Vibrio fischeri and the green alga Chlorella vulgaris) obtained with the analysis of water samples monthly collected at seven monitoring sites and during five campaigns (February, May, June, August, and September 2006). The results of some variables were assigned to water quality classes according to national guidelines. Chemical and bacteriological quality data led to classify Leça River water quality as “bad” or “very bad”. PCA and CA identified monitoring sites with similar pollution pattern, giving to site 1 (located in the upstream stretch of the river) a distinct feature from all other sampling sites downstream. Ecotoxicity results corroborated this classification thus revealing differences in space and time. The present study includes not only physical, chemical and bacteriological but also ecotoxicological parameters, which broadens new perspectives in river water characterization. Moreover, the application of PCA and CA is very useful to optimize water quality monitoring networks, defining the minimum number of sites and their location. Thus, these tools can support appropriate management decisions.

Adherend thickness effect on the tensile fracture toughness of a structural adhesive using an optical data acquisition method

Adhesive bonding is nowadays a serious candidate to replace methods such as fastening or riveting, because of attractive mechanical properties. As a result, adhesives are being increasingly used in industries such as the automotive, aerospace and construction. Thus, it is highly important to predict the strength of bonded joints to assess the feasibility of joining during the fabrication process of components (e.g. due to complex geometries) or for repairing purposes. This work studies the tensile behaviour of adhesive joints between aluminium adherends considering different values of adherend thickness (h) and the double-cantilever beam (DCB) test. The experimental work consists of the definition of the tensile fracture toughness (GIC) for the different joint configurations. A conventional fracture characterization method was used, together with a J-integral approach, that take into account the plasticity effects occurring in the adhesive layer. An optical measurement method is used for the evaluation of crack tip opening and adherends rotation at the crack tip during the test, supported by a Matlab® sub-routine for the automated extraction of these quantities. As output of this work, a comparative evaluation between bonded systems with different values of adherend thickness is carried out and complete fracture data is provided in tension for the subsequent strength prediction of joints with identical conditions.

Non-enzymatic assay for glucose by using immobilized whole-cells of E. coli containing glucose binding protein fused to fluorescent proteins

Glucose monitoring in vivo is a crucial issue for gaining new understanding of diabetes. Glucose binding protein (GBP) fused to two fluorescent indicator proteins (FLIP) was used in the present study such as FLIP-glu- 3.2 mM. Recombinant Escherichia coli whole-cells containing genetically encoded nanosensors as well as cell-free extracts were immobilized either on inner epidermis of onion bulb scale or on 96-well microtiter plates in the presence of glutaraldehyde. Glucose monitoring was carried out by Förster Resonance Energy Transfer (FRET) analysis due the cyano and yellow fluorescent proteins (ECFP and EYFP) immobilized in both these supports. The recovery of these immobilized FLIP nanosensors compared with the free whole-cells and cell-free extract was in the range of 50–90%. Moreover, the data revealed that these FLIP nanosensors can be immobilized in such solid supports with retention of their biological activity. Glucose assay was devised by FRET analysis by using these nanosensors in real samples which detected glucose in the linear range of 0–24 mM with a limit of detection of 0.11 mM glucose. On the other hand, storage and operational stability studies revealed that they are very stable and can be re-used several times (i.e. at least 20 times) without any significant loss of FRET signal. To author's knowledge, this is the first report on the use of such immobilization supports for whole-cells and cell-free extract containing FLIP nanosensor for glucose assay. On the other hand, this is a novel and cheap high throughput method for glucose assay.

Preliminary data on the ostracod fauna from the Lower Toarcian of Peniche

Preliminary results of the systematic and biostratigraphical study of the ostracods from the Lower Toarcian (Polymorphum and Levisoni Zones) of Peniche are presented. Most of the identified species are recognized in other European countries. Biodiversity and species abundance are high in the first Zone, decreasing dramatically in the second one.

On the applicability of joint inversion of gravity and resistivity data to the study of a tectonic sedimentary basin in Northern Portugal

The Chaves basin is a pull-apart tectonic depression implanted on granites, schists, and graywackes, and filled with a sedimentary sequence of variable thickness. It is a rather complex structure, as it includes an intricate network of faults and hydrogeological systems. The topography of the basement of the Chaves basin still remains unclear, as no drill hole has ever intersected the bottom of the sediments, and resistivity surveys suffer from severe equivalence issues resulting from the geological setting. In this work, a joint inversion approach of 1D resistivity and gravity data designed for layered environments is used to combine the consistent spatial distribution of the gravity data with the depth sensitivity of the resistivity data. A comparison between the results from the inversion of each data set individually and the results from the joint inversion show that although the joint inversion has more difficulty adjusting to the observed data, it provides more realistic and geologically meaningful models than the ones calculated by the inversion of each data set individually. This work provides a contribution for a better understanding of the Chaves basin, while using the opportunity to study further both the advantages and difficulties comprising the application of the method of joint inversion of gravity and resistivity data.

Palynologic data from Aquitaine (SW France) Middle Miocene Sables Fauves Formation. Climatic evolution

Climatic reconstructions based on palynological data from Aquitaine outcrops emphasize an important degradation phase during the Lower Serravallian. Climatic and environmental changes can be related to sea-level variations (Bur 5 / Lan 1, Lan 2 / Ser 1 and Ser 2 cycles). Transgressive phases feature warmer conditions and more open environments whereas regressive phases are marked by a cooler climate and an extent of the forest cover. From Langhian to Middle Serravallian, a general cooling is highlighted, with disappearance of most megathermic taxa and a transition from warm and dry climate to warm-temperate and much more humid conditions. Conclusions are consistent with studies on bordering areas and place the major degradation phase around 14 My. The palynologic data allow filling a gap in the climatic evolution of Southern France, as a connection between Lower and Upper Miocene, both well recorded. These results document, on Western Europe scale, latitudinal climatic gradient across Northern hemisphere while featuring a transition between Mediterranean area and northeastern Atlantic frontage.

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

Confronting predictive texture zeros in lepton mass matrices with current data

Several popular Ansatze of lepton mass matrices that contain texture zeros are confronted with current neutrino observational data. We perform a systematic chi(2) analysis in a wide class of schemes, considering arbitrary Hermitian charged-lepton mass matrices and symmetric mass matrices for Majorana neutrinos or Hermitian mass matrices for Dirac neutrinos. Our study reveals that several patterns are still consistent with all the observations at the 68.27% confidence level, while some others are disfavored or excluded by the experimental data. The well-known Frampton-Glashow-Marfatia two-zero textures, hybrid textures, and parallel structures (among others) are considered.

Reduced schedule of human anti-rabies immunization with Fuenzalida & Palacios vaccine: additional data

It was reevaluated a reduced schedule for anti-rabies post-exposure immunization with newborn mice nervous tissue vaccine (Fuenzalida 8c Palacios) in a group of 30 non exposed volunteers. The vaccine was administered by intramuscular injections on days zero, 2, 4, 16 and 27, in the deltoid area. Antibody levels were determinated by a simplified serum neutralization microtest on days zero, 16 and 37. On days 16 and 37 the antibody levels of the whole group was >0.5 IU/ml and >1.0 IU/ml, respectively. The cell mediated immunity was precociously detected (on day 4) by the delayed type hipersensitivity skin test. Our results show that this reduced schedule elicited an early and effective humoral and cellular immune response. However it is necessary other studies with larger groups of vaccinees in order to obtain definitive conclusion.

Mobile device-to-device distributed computing using data sets

The rapidly increasing computing power, available storage and communication capabilities of mobile devices makes it possible to start processing and storing data locally, rather than offloading it to remote servers; allowing scenarios of mobile clouds without infrastructure dependency. We can now aim at connecting neighboring mobile devices, creating a local mobile cloud that provides storage and computing services on local generated data. In this paper, we describe an early overview of a distributed mobile system that allows accessing and processing of data distributed across mobile devices without an external communication infrastructure. Copyright © 2015 ICST.

Velocity estimation of moving ships using C-band SLC SAR data

A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

Modelação do comportamento dinâmico de sistemas barragem-fundação-albufeira: análise sísmica de uma barragem de abóbadas múltiplas

Trabalho Final de Mestrado elaborado no Laboratório Nacional de Engenharia Civil (LNEC) para a obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo de cooperação entre o ISEL e o LNEC

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

Optimization studies through simulation of a methanol/water/glycerol distillation column

This paper presents an optimization study of a distillation column for methanol and aqueous glycerol separation in a biodiesel production plant. Considering the available physical data of the column configuration, a steady state model was built for the column using Aspen-HYSYS as process simulator. Several sensitivity analysis were performed in order to better understand the relation between the variables of the distillation process. With the information obtained by the simulator, it is possible to define the best range for some operational variables that maintain composition of the desired product under specifications and choose operational conditions to minimize energy consumptions.

Quality of Life Predictors and Normative Data

This study identifies predictors and normative data for quality of life (QOL) in a sample of Portuguese adults from general population. A cross-sectional correlational study was undertaken with two hundred and fifty-five (N = 255) individuals from Portuguese general population (mean age 43 years, range 25–84 years; 148 females, 107 males). Participants completed the European Portuguese version of the World Health Organization Quality of Life short-form instrument and the European Portuguese version of the Center for Epidemiologic Studies Depression Scale. Demographic information was also collected. Portuguese adults reported their QOL as good. The physical, psychological and environmental domains predicted 44 % of the variance of QOL. The strongest predictor was the physical domain and the weakest was social relationships. Age, educational level, socioeconomic status and emotional status were significantly correlated with QOL and explained 25 % of the variance of QOL. The strongest predictor of QOL was emotional status followed by education and age. QOL was significantly different according to: marital status; living place (mainland or islands); type of cohabitants; occupation; health. The sample of adults from general Portuguese population reported high levels of QOL. The life domain that better explained QOL was the physical domain. Among other variables, emotional status best predicted QOL. Further variables influenced overall QOL. These findings inform our understanding on adults from Portuguese general population QOL and can be helpful for researchers and practitioners using this assessment tool to compare their results with normative data