Evaluation of uv spectrophotometry for estimation of nitrite and nitrate in nitrified urine

Water is a limited resource for which demand is growing. Contaminated water from inadequate wastewater treatment provides one of the greatest health challenges as it restricts development and increases poverty in emerging and developing countries. Therefore, the connection between wastewater and human health is linked to access to sanitation and to human waste disposal. Adequate sanitation is expected to create a barrier between disposed human excreta and sources of drinking water. Different approaches to wastewater management are required for different geographical regions and different stages of economic governance depending on the capacity to manage wastewater. Effective wastewater management can contribute to overcome the challenges of water scarcity. Separate collection of human urine at its source is one promising approach that strongly reduces the economic and load demands on wastewater treatment plants (WWTP). Treatment of source-separated urine appears as a sanitation system that is affordable, produces a valuable fertiliser, reduces pollution of water resources and promotes health. However, the technical realisation of urine separation still faces challenges. Biological hydrolysis of urea causes a strong increase of ammonia and pH. Under these conditions ammonia volatilises which can cause odour problems and significant nitrogen losses. The above problems can be avoided by urine stabilisation. Biological nitrification is a suitable process for stabilisation of urine. Urine is a highly concentrated nutrient solution which can lead to strong inhibition effects during bacterial nitrification. This can further lead to process instabilities. The major cause of instability is accumulation of the inhibitory intermediate compound nitrite, which could lead to process breakdown. Enhanced on-line nitrite monitoring can be applied in biological source-separated urine nitrification reactors as a sustainable and efficient way to improve the reactor performance, avoiding reactor failures and eventual loss of biological activity. Spectrophotometry appears as a promising candidate for the development and application of on-line nitrite monitoring. Spectroscopic methods together with chemometrics are presented in this work as a powerful tool for estimation of nitrite concentrations. Principal component regression (PCR) is applied for the estimation of nitrite concentrations using an immersible UV sensor and off-line spectra acquisition. The effect of particles and the effect of saturation, respectively, on the UV absorbance spectra are investigated. The analysis allows to conclude that (i) saturation has a substantial effect on nitrite estimation; (ii) particles appear to have less impact on nitrite estimation. In addition, improper mixing together with instabilities in the urine nitrification process appears to significantly reduce the performance of the estimation model.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Leptospirosis in animals and human contacts in Egypt: broad range surveillance

INTRODUCTION: Leptospirosis is a re-emerging zoonotic disease of humans and animals worldwide. The disease is caused by pathogenic species of the genus Leptospira. These organisms are maintained in nature via chronic renal infection of carrier animals, which excrete the organisms in their urine. Humans become infected through direct or indirect exposure to infected animals and their urine or through contact with contaminated water and soil. This study was conducted to investigate Leptospira infections as a re-emerging zoonosis that has been neglected in Egypt. METHODS: Samples from 1,250 animals (270 rats, 168 dogs, 625 cows, 26 buffaloes, 99 sheep, 14 horses, 26 donkeys and 22 camels), 175 human contacts and 45 water sources were collected from different governorates in Egypt. The samples were collected from different body sites and prepared for culture, PCR and the microscopic agglutination test (MAT). RESULTS: The isolation rates of Leptospira serovars were 6.9%, 11.3% and 1.1% for rats, dogs and cows, respectively, whereas the PCR results revealed respective detection rates of 24%, 11.3% and 1.1% for rats, dogs and cows. Neither the other examined animal species nor humans yielded positive results via these two techniques. Only six Leptospira serovars (Icterohaemorrhagiae, Pomona, Canicola, Grippotyphosa, Celledoni and Pyrogenes) could be isolated from rats, dogs and cows. Moreover, the seroprevalence of leptospiral antibodies among the examined humans determined using MAT was 49.7%. CONCLUSIONS: The obtained results revealed that rats, dogs and cows were the most important animal reservoirs for leptospirosis in Egypt, and the high seroprevalence among human contacts highlights the public health implications of this neglected zoonosis.

Dynamic range prediction for an electric vehicle

Electric Vehicles (EVs) have limited energy storage capacity and the maximum autonomy range is strongly dependent of the driver's behaviour. Due to the fact of that batteries cannot be recharged quickly during a journey, it is essential that a precise range prediction is available to the driver of the EV. With this information, it is possible to check if the desirable destination is achievable without a stop to charge the batteries, or even, if to reach the destination it is necessary to perform an optimized driving (e.g., cutting the air-conditioning, among others EV parameters). The outcome of this research work is the development of an Electric Vehicle Assistant (EVA). This is an application for mobile devices that will help users to take efficient decisions about route planning, charging management and energy efficiency. Therefore, it will contribute to foster EVs adoption as a new paradigm in the transportation sector.

Exploring TM image texture and its relationships with biomass estimation in Rondônia, Brazilian Amazon

Many texture measures have been developed and used for improving land-cover classification accuracy, but rarely has research examined the role of textures in improving the performance of aboveground biomass estimations. The relationship between texture and biomass is poorly understood. This paper used Landsat Thematic Mapper (TM) data to explore relationships between TM image textures and aboveground biomass in Rondônia, Brazilian Amazon. Eight grey level co-occurrence matrix (GLCM) based texture measures (i.e., mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment, and correlation), associated with seven different window sizes (5x5, 7x7, 9x9, 11x11, 15x15, 19x19, and 25x25), and five TM bands (TM 2, 3, 4, 5, and 7) were analyzed. Pearson's correlation coefficient was used to analyze texture and biomass relationships. This research indicates that most textures are weakly correlated with successional vegetation biomass, but some textures are significantly correlated with mature forest biomass. In contrast, TM spectral signatures are significantly correlated with successional vegetation biomass, but weakly correlated with mature forest biomass. Our findings imply that textures may be critical in improving mature forest biomass estimation, but relatively less important for successional vegetation biomass estimation.

Metallic glass/PVDF magnetoelectric energy harvester working up to the radiofrequency range

Companies and researchers involved in developing miniaturized electronic devices face the basic problem of the needed batteries size, finite life of time and environmental pollution caused by their final deposition. The current trends to overcome this situation point towards Energy Harvesting technology. These harvesters (or scavengers) store the energy from sources present in the ambient (as wind, solar, electromagnetic, etc) and are costless for us. Piezoelectric devices are the ones that show a higher power density, and materials as ceramic PZT or polymeric PVDF have already demonstrated their ability to act as such energy harvester elements. Combinations between piezoelectric and electromagnetic mechanism have been also extensively investigated. Nevertheless, the power generated by these combinations is limited under the application of small magnetic fields, reducing the performance of the energy harvester [1]. In the last years the appearance of magnetoelectric (ME) devices, in which the piezoelectric deformation is driven by the magnetostrictive element, enables to extract the energy of very small electromagnetic signals through the generated magnetoelectric voltage at the piezoelectric element. However, very little work has been done testing PVDF polymer as piezoelectric constituent of the ME energy harvester device, and only to be proposed as a possibility of application [2]. Among the advantages of using piezopolymers for vibrational energy harvesting we can remember that they are ductile, resilient to shock, deformable and lightweight. In this work we demonstrate the feasibility of using magnetostrictive Fe-rich magnetic amorphous alloys/piezoelectric PVDF sandwich-type laminated ME devices as energy harvesters. A very simple experimental set-up will show how these laminates can extract energy, in amounts of μW, from an external AC field.

Nonparametric estimation of time-dependent ROC curves conditional on a continuous covariate

The receiver-operating characteristic (ROC) curve is the most widely used measure for evaluating the performance of a diagnostic biomarker when predicting a binary disease outcome. The ROC curve displays the true positive rate (or sensitivity) and the false positive rate (or 1-specificity) for different cut-off values used to classify an individual as healthy or diseased. In time-to-event studies, however, the disease status (e.g. death or alive) of an individual is not a fixed characteristic, and it varies along the study. In such cases, when evaluating the performance of the biomarker, several issues should be taken into account: first, the time-dependent nature of the disease status; and second, the presence of incomplete data (e.g. censored data typically present in survival studies). Accordingly, to assess the discrimination power of continuous biomarkers for time-dependent disease outcomes, time-dependent extensions of true positive rate, false positive rate, and ROC curve have been recently proposed. In this work, we present new nonparametric estimators of the cumulative/dynamic time-dependent ROC curve that allow accounting for the possible modifying effect of current or past covariate measures on the discriminatory power of the biomarker. The proposed estimators can accommodate right-censored data, as well as covariate-dependent censoring. The behavior of the estimators proposed in this study will be explored through simulations and illustrated using data from a cohort of patients who suffered from acute coronary syndrome.

Nonparametric estimation of the survival function for ordered multivariate failure time data: a comparative study

In longitudinal studies of disease, patients may experience several events through a follow-up period. In these studies, the sequentially ordered events are often of interest and lead to problems that have received much attention recently. Issues of interest include the estimation of bivariate survival, marginal distributions and the conditional distribution of gap times. In this work we consider the estimation of the survival function conditional to a previous event. Different nonparametric approaches will be considered for estimating these quantities, all based on the Kaplan-Meier estimator of the survival function. We explore the finite sample behavior of the estimators through simulations. The different methods proposed in this article are applied to a data set from a German Breast Cancer Study. The methods are used to obtain predictors for the conditional survival probabilities as well as to study the influence of recurrence in overall survival.

A review of mycotoxins in food and feed products in Portugal and estimation of probable daily intakes

Mycotoxins are toxic secondary metabolites produced by filamentous fungi that occur naturally in agricultural commodities worldwide. Aflatoxins, ochratoxin A, patulin, fumonisins, zearalenone, trichothecenes and ergot alkaloids are presently the most important for food and feed safety. These compounds are produced by several species that belong to the Aspergillus, Penicillium, Fusarium and Claviceps genera and can be carcinogenic, mutagenic, teratogenic, cytotoxic, neurotoxic, nephrotoxic, estrogenic and immunosuppressant. Human and animal exposure to mycotoxins is generally assessed by taking into account data on the occurrence of mycotoxins in food and feed as well as data on the consumption patterns of the concerned population. This evaluation is crucial to support measures to reduce consumer exposure to mycotoxins. This work reviews the occurrence and levels of mycotoxins in Portuguese food and feed to provide a global overview of this issue in Portugal. With the information collected, the exposure of the Portuguese population to those mycotoxins is assessed, and the estimated dietary intakes are presented.

A new combination in Peristethium (Loranthaceae) expands the genus' range into the Amazon-Cerrado ecotone

The genus Peristethium, characterized by determinate inflorescences protected by deciduous bracts, occurs in the northwest of South America, as well as Costa Rica and Panama. The main objective of this paper was to transfer one species to what we believe is its correct generic placement in Peristethium, that likewise implies in a shift of the genus' distribution beyond the Amazon. A new combination, Peristethium reticulatum, is proposed, based on Struthanthus reticulatus, described from Tocantins in 1980. The sexual dimorphism of the inflorescences of P. reticulatum (sessile male flowers and pedicellate female flowers) associated with male inflorescences that are inserted at leafless nodes are unique within the genus. The male flowers have dimorphic stamens, well-developed anthers and a pistiloid, whilst female flowers have robust styles and stigmas, and much reduced staminodes. Peristethium reticulatum and P. polystachyum occurs in the Amazon regions of Brazil, with the former recorded also in the ecotone with the Central Brazilian savannas (Cerrados).

Dynamic modelling and analysis of hydraulic forces in radial blood pumps

Dissertação de mestrado integrado em Biomedical Engineering Biomaterials, Biomechanics and Rehabilitation

Range extension of Centronycetris maximiliani (Mammalia: Chiroptera) for southern Amazonia

Bat species of the genus Centronycteris are some of the rarest Neotropical Emballonuridae and fewer than 50 specimens have been deposited in scientific collections. The aim of this study is to extend the distribution of Centronycteris maximiliani. Three C. maximiliani specimens were recorded in the Brazilian Amazonia, providing the first record of the species for the state of Rondônia, the southernmost record of the species for the Amazon biome in Brazil, and an additional record for the state of Pará. Although these new records of C. maximiliani reinforce the idea that this species is widely distributed throughout the Amazon biome, its low capture rate reflects the rarity of this species, since only three specimens were collected during three to four year field effort.

Graphene-based nanostructures: Plasmonics in the THz range

The properties of surface plasmon-polaritons (SPPs) in graphene are discussed and several possible ways of coupling electromagnetic radiation in the terahertz (THz) spectral range to this type of surface waves are described: (i) the attenuated total reflection (ATR) method employing a prism, (ii) graphene-based gratings or graphene monolayers with modulated conductivity, (iii) a metal stripe on top of the graphene layer, and (iv) a nanoparticle located above it. Potentially interesting for applications SPP effects, such as switching, modulation and polarization of THz radiation, as well as its enhanced absorption in graphene, are considered. The discussion also concerns the impact of the nonlinear properties of graphene, such as optical bistability.

Desenvolvimento de um Range Extender para Veículo Elétrico

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e de Computadores

Tailored deposition of coloured coatings: on the widening of the available colour range

Dissertação de mestrado integrado em Engenharia de Materiais