Hydrophilic Interaction Ultra-High Performance Liquid Chromatography Coupled with Triple-Quadrupole Mass Spectrometry for Determination of Nucleosides and Nucleobases in Animal Horns

Traditional Chinese Medicines (TCMs) derived from animal horns are one of the most important types of Chinese medicine. In the present study, a fast and sensitive analytical method was established for qualitative and quantitative determination of 14 nucleosides and nucleobases in animal horns using hydrophilic interaction ultra-high performance liquid chromatography coupled with triple-quadruple tandem mass spectrometry (HILIC-UPLC-QQQ-MS/MS) in selective reaction monitoring (SRM) mode. The method was optimized and validated, and showed good linearity, precision, repeatability, and accuracy. The method was successfully used to determine contents of the 14 nucleosides and nucleobases in 25 animal horn samples. Hierarchical clustering analysis (HCA) and principal component analysis (PCA) were performed and the 25 samples were thereby divided into two groups, which agreed with taxonomy. The method may enable quick and effective search of substitutes for precious horns.

Material Identification of Loose Particles in Sealed Electronic Devices Using PCA and SVM

The existence of loose particles left inside the sealed electronic devices is one of the main factors affecting the reliability of the whole system. It is important to identify the particle material for analyzing their source. The conventional material identification algorithms mainly rely on time, frequency and wavelet domain features. However, these features are usually overlapped and redundant, resulting in unsatisfactory material identification accuracy. The main objective of this paper is to improve the accuracy of material identification. First, the principal component analysis (PCA) is employed to reselect the nine features extracted from time and frequency domains, leading to six less correlated principal components. And then the reselected principal components are used for material identification using a support vector machine (SVM). Finally, the experimental results show that this new method can effectively distinguish the type of materials including wire, aluminum and tin particles.

Major and trace elements in milk and Halloumi cheese as markers for authentication of goat feeding regimes and geographical origin

Sixty samples of milk, Halloumi cheese and local grazing plants (i.e. shrubs) were collected over a year from dairy farms located on three different locations of Cyprus. Major and trace elements were quantified using inductively coupled plasma-atomic emission spectroscopy (ICP-AES). Milk and Halloumi cheese produced in different geographical locations presented significant differences in the concentration of some of the elements analysed. Principal component analysis showed grouping of samples according to the region of production for both milk and cheese samples. These findings show that the assay of elements can provide useful fingerprints for the characterisation of dairy products.

Neural Network Based Attack on a Masked Implementation of AES

Masked implementations of cryptographic algorithms are often used in commercial embedded cryptographic devices to increase their resistance to side channel attacks. In this work we show how neural networks can be used to both identify the mask value, and to subsequently identify the secret key value with a single attack trace with high probability. We propose the use of a pre-processing step using principal component analysis (PCA) to significantly increase the success of the attack. We have developed a classifier that can correctly identify the mask for each trace, hence removing the security provided by that mask and reducing the attack to being equivalent to an attack against an unprotected implementation. The attack is performed on the freely available differential power analysis (DPA) contest data set to allow our work to be easily reproducible. We show that neural networks allow for a robust and efficient classification in the context of side-channel attacks.

Establishing the validity of English GP Patient Survey items evaluating out-of-hours care

Background A 2014 national audit used the English General Practice Patient Survey (GPPS) to compare service users’ experience of out-of-hours general practitioner (GP) services, yet there is no published evidence on the validity of these GPPS items. Objectives Establish the construct and concurrent validity of GPPS items evaluating service users’ experience of GP out-of-hours care. Methods Cross-sectional postal survey of service users (n=1396) of six English out-of-hours providers. Participants reported on four GPPS items evaluating out-of-hours care (three items modified following cognitive interviews with service users), and 14 evaluative items from the Out-of-hours Patient Questionnaire (OPQ). Construct validity was assessed through correlations between any reliable (Cochran's α>0.7) scales, as suggested by a principal component analysis of the modified GPPS items, with the ‘entry access’ (four items) and ‘consultation satisfaction’ (10 items) OPQ subscales. Concurrent validity was determined by investigating whether each modified GPPS item was associated with thematically related items from the OPQ using linear regressions. Results The modified GPPS item-set formed a single scale (α=0.77), which summarised the two-component structure of the OPQ moderately well; explaining 39.7% of variation in the ‘entry access’ scores (r=0.63) and 44.0% of variation in the ‘consultation satisfaction’ scores (r=0.66), demonstrating acceptable construct validity. Concurrent validity was verified as each modified GPPS item was highly associated with a distinct set of related items from the OPQ. Conclusions Minor modifications are required for the English GPPS items evaluating out-of-hours care to improve comprehension by service users. A modified question set was demonstrated to comprise a valid measure of service users’ overall satisfaction with out-of-hours care received. This demonstrates the potential for the use of as few as four items in benchmarking providers and assisting services in identifying, implementing and assessing quality improvement initiatives.

Wide-Area Phase-Angle Measurements for Islanding Detection—An Adaptive Nonlinear Approach

The integration of an ever growing proportion of large scale distributed renewable generation has increased the probability of maloperation of the traditional RoCoF and vector shift relays. With reduced inertia due to non-synchronous penetration in a power grid, system wide disturbances have forced the utility industry to design advanced protection schemes to prevent system degradation and avoid cascading outages leading to widespread blackouts. This paper explores a novel adaptive nonlinear approach applied to islanding detection, based on wide area phase angle measurements. This is challenging, since the voltage phase angles from different locations exhibit not only strong nonlinear but also time-varying characteristics. The adaptive nonlinear technique, called moving window kernel principal component analysis is proposed to model the time-varying and nonlinear trends in the voltage phase angle data. The effectiveness of the technique is exemplified using both DigSilent simulated cases and real test cases recorded from the Great Britain and Ireland power systems by the OpenPMU project.

Islanding Detection Based on Probabilistic PCA with Missing Values in PMU Data

This paper proposes a probabilistic principal component analysis (PCA) approach applied to islanding detection study based on wide area PMU data. The increasing probability of uncontrolled islanding operation, according to many power system operators, is one of the biggest concerns with a large penetration of distributed renewable generation. The traditional islanding detection methods, such as RoCoF and vector shift, are however extremely sensitive and may result in many unwanted trips. The proposed probabilistic PCA aims to improve islanding detection accuracy and reduce the risk of unwanted tripping based on PMU measurements, while addressing a practical issue on missing data. The reliability and accuracy of the proposed probabilistic PCA approach are demonstrated using real data recorded in the UK power system by the OpenPMU project. The results show that the proposed methods can detect islanding accurately, without being falsely triggered by generation trips, even in the presence of missing values.

Implication of modified molecular structure of lipid through heat-related process to fatty acids supply in Brassica carinata seed.

This study was conducted to explore the effect of different autoclave heating times (30, 60 and 90 min) on fatty acids supply and molecular stability in Brassica carinata seed. Multivariate spectral analyses and correlation analyses were also carried out in our study. The results showed that autoclaving treatments significantly decreased the total fatty acids content in a linear fashion in B. carinata seed as heating time increased. Reduced concentrations were also observed in C18:3n3, C20:1, C22:1n9, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), omega 3 (ω-3) and 9 (ω-9) fatty acids. Correspondingly, the heated seeds showed dramatic reductions in all the peak intensities within lipid-related spectral regions. Results from agglomerative hierarchical cluster analysis (AHCA) and principal component analysis (PCA) indicated that the raw oilseed had completely different structural make-up from the autoclaved seeds in both CH3 and CH2 asymmetric and symmetric stretching region (ca. 2999–2800 cm−1) and lipid ester Cdouble bond; length as m-dashO carbonyl region (ca. 1787–1706 cm−1). However, the oilseeds heated for 30, 60 and 90 min were not grouped into separate classes or ellipses in all the lipid-related regions, indicating that there still exhibited similarities in lipid biopolymer conformations among autoclaved B. carinata seeds. Moreover, strong correlations between spectral information and fatty acid compositions observed in our study could imply that lipid-related spectral parameters might have a potential to predict some fatty acids content in oilseed samples, i.e. B. carinata. However, more data from large sample size and diverse range would be necessary and helpful to draw up a final conclusion.

Real-Time Multiple Event Detection and Classification Using Moving Window PCA

This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.

Pesca comercial de tubarões e raias em Portugal

O objectivo do trabalho foi analisar os desembarques de tubarões e raias em Portugal no período 1986 – 2006. Esta análise revelou que os desembarques totalizaram 108.671 ton no referido período de 21 anos. Anualmente foram desembarcados, em média, cerca de 5.175 ton, com exemplares representantes de 8 ordens, 14 famílias e 44 espécies. Genericamente, os desembarques anuais destes grupos animais têm diminuído ao longo do tempo, apesar de se verificar um aumento no preço por quilo. O grupo mais desembarcado foi o das Raias (Raja sp.), responsável por 35.614 ton das capturas, ou seja, 33% do total. A este grupo seguiram-se as Patas-roxas (Scyliorhinus sp.), os tubarões Carocho (Centroscymnus coelolepis), Lixa (Centrophorus squamosus) e Barroso (Centrophorus granulosus), correspondendo a 12%, 12%, 10% e 9% dos desembarques, respectivamente. Na ausência de dados consistentes de CPUE, a comparação dos padrões de desembarques e preço foi utilizada como indicador da evolução do recurso, tendo em conta as várias espécies de elasmobrânquios. Centrophorus granulosus, Cações (Mustelus sp.), Tremelgas (Torpedo sp.), Marrachos (Carcharhinus sp.) e Tubarões-anjo (Squatina sp.) indiciaram sinais de possível sobrexploração, situação esta a merecer a atenção de programas futuros de I & DT. A evolução do esforço de pesca ao longo do tempo, ponderada sob a forma de “número de embarcações de pesca”, registou uma diminuição acentuada, embora substancialmente menor que a diminuição registada nos desembarques das espécies referidas. É pouco provável, por isso, que a diminuição dos desembarques seja fruto, unicamente, da diminuição na frota de pesca, mas sim de uma menor rendibilidade da actividade. Paralelamente, os aumentos de preço observados suplantaram largamente a taxa de inflação média, pelo que o aumento dos primeiros não é justificado inteiramente pelo aumento do segundo. Estes resultados tiveram eco nas análises de componentes principais (MAFA e DFA) conduzidas para as espécies, que validaram padrões de diminuição particularmente elevados nas espécies em que métodos anteriores já haviam apontado sinais de sobrepesca. Os resultados obtidos apontam para o facto de que algumas espécies parecem estar fora dos limites biológicos de segurança e, como tal, há necessidade de serem tomadas medidas de gestão eficazes.

Cartografia geoquímica da ilha de Santiago com uma densidade de amostragem média/baixa

A ilha de Santiago é a maior do arquipélago de Cabo Verde, apresenta uma área de 991 km2, com um comprimento e largura máximos de 54,9 km e 29 km, respectivamente, e 1392 m de maior altitude. As condições climáticas e a erosão são alguns dos problemas naturais do arquipélago de Cabo Verde. Além disso, a intervenção humana no ambiente superficial revela-se muitas vezes inadequada e com forte impacto. A construção em solos com aptidão agrícola ou florestal, as actividades industriais, a deposição de materiais sólidos ou líquidos de forma inadequada, as práticas agrícolas incorrectas e intensivas, o uso abusivo de pesticidas e fertilizantes, a rega com água contaminada, a sobreexploração de aquíferos que levam muitas vezes à salinização, etc. têm enorme impacto em termos de contaminação de solos, águas superficiais e subterrâneas nas áreas envolventes. Por conseguinte, o conhecimento da variabilidade geoquímica natural é fundamental para a resolução de questões de índole económica, ambiental e de ordenamento do território, médica, e jurídica. A necessidade de construir uma base de dados de geoquímica georeferenciada que caracterize o ambiente superficial da ilha de Santiago foi a principal motivação para a realização deste estudo. Realizou-se um levantamento geoquímico de 337 amostras de sedimentos de corrente e 249 amostras de solos na ilha de Santiago, tendo sido seguidas as recomendações do Projecto Internacional IGCP 259 não só na fase de amostragem, mas também nas fases seguintes de preparação, análise, tratamento dos dados e elaboração de mapas. Determinaram-se os teores, na fracção < 2 mm, para 36 elementos – 9 elementos maiores (Al, Ca, Fe, K, Mg, Mn, Na, P, Ti) e 27 elementos vestigiais (Ag, As, Au, B, Ba, Bi, Cd, Co, Cr, Cu, Ga, Hg, La, Mo, Ni, Pb, S, Sb, Sc, Se, Sr, Th, Tl, U, V, W, Zn). Efectuou-se ainda a análise textural e estudou-se a composição mineralógica de cerca de 25% das amostras. Analisaram-se, também, 103 amostras de rochas, colhidas nas várias formações da ilha de Santiago, tendo sido determinados os teores de K2O, Na2O, Fe2O3(T), MnO, Sc, Cr, Co, Zn, Ga, As, Br, Rb, Zr, Sb, Cs, Ba, Hf, Ta, W, Th e U e REE, a fim de se fazer uma comparação com os teores destes elementos encontrados nos solos e sedimentos de corrente, averiguando se a sua variação é ou não essencialmente condicionada pela geoquímica da rocha-mãe. Os padrões geoquímicos obtidos através dos mapas de distribuição espacial foram correlacionados com a natureza da rocha mãe, o tipo de solo, e ainda com algumas fontes de contaminação. A interpretação dos resultados foi realizada não só pela observação dos mapas geoquímicos, mas também após análise estatística dos conjuntos de dados obtidos, e apoiada em informação diversa disponível. A utilização da Análise de Componentes Principais permitiu distinguir associações entre elementos químicos, quer de origem geogénica quer antropogénica. Foram ainda elaborados mapas de distribuição espacial de vários índices multielementares de importância ambiental, como o Índice de Acidificação Al/(Ca+Mg+K), Índice de Combi, Índice de Avaliação de Risco Ambiental e Índices de Enriquecimento/Contaminação para vários grupos de elementos considerados como “primary pollutant metals”.

NMR in the characterization of heavy residual procedural streams

The main objective of this work was to monitor a set of physical-chemical properties of heavy oil procedural streams through nuclear magnetic resonance spectroscopy, in order to propose an analysis procedure and online data processing for process control. Different statistical methods which allow to relate the results obtained by nuclear magnetic resonance spectroscopy with the results obtained by the conventional standard methods during the characterization of the different streams, have been implemented in order to develop models for predicting these same properties. The real-time knowledge of these physical-chemical properties of petroleum fractions is very important for enhancing refinery operations, ensuring technically, economically and environmentally proper refinery operations. The first part of this work involved the determination of many physical-chemical properties, at Matosinhos refinery, by following some standard methods important to evaluate and characterize light vacuum gas oil, heavy vacuum gas oil and fuel oil fractions. Kinematic viscosity, density, sulfur content, flash point, carbon residue, P-value and atmospheric and vacuum distillations were the properties analysed. Besides the analysis by using the standard methods, the same samples were analysed by nuclear magnetic resonance spectroscopy. The second part of this work was related to the application of multivariate statistical methods, which correlate the physical-chemical properties with the quantitative information acquired by nuclear magnetic resonance spectroscopy. Several methods were applied, including principal component analysis, principal component regression, partial least squares and artificial neural networks. Principal component analysis was used to reduce the number of predictive variables and to transform them into new variables, the principal components. These principal components were used as inputs of the principal component regression and artificial neural networks models. For the partial least squares model, the original data was used as input. Taking into account the performance of the develop models, by analysing selected statistical performance indexes, it was possible to conclude that principal component regression lead to worse performances. When applying the partial least squares and artificial neural networks models better results were achieved. However, it was with the artificial neural networks model that better predictions were obtained for almost of the properties analysed. With reference to the results obtained, it was possible to conclude that nuclear magnetic resonance spectroscopy combined with multivariate statistical methods can be used to predict physical-chemical properties of petroleum fractions. It has been shown that this technique can be considered a potential alternative to the conventional standard methods having obtained very promising results.

The alternating least-squares algorithm for CDPCA

Clustering and Disjoint Principal Component Analysis (CDP CA) is a constrained principal component analysis recently proposed for clustering of objects and partitioning of variables, simultaneously, which we have implemented in R language. In this paper, we deal in detail with the alternating least-squares algorithm for CDPCA and highlight its algebraic features for constructing both interpretable principal components and clusters of objects. Two applications are given to illustrate the capabilities of this new methodology.

Development of infrared spectroscopy for assessing bacterial quality in foods

Rapid and specific detection of foodborne bacteria that can cause food spoilage or illness associated to its consumption is an increasingly important task in food industry. Bacterial detection, identification, and classification are generally performed using traditional methods based on biochemical or serological tests and the molecular methods based on DNA or RNA fingerprints. However, these methodologies are expensive, time consuming and laborious. Infrared spectroscopy is a reliable, rapid, and economic technique which could be explored as a tool for bacterial analysis in the food industry. In this thesis it was evaluated the potential of IR spectroscopy to study the bacterial quality of foods. In Chapter 2, it was developed a calibration model that successfully allowed to predict the bacterial concentration of naturally contaminated cooked ham samples kept at refrigeration temperature during 8 days. In this part, it was developed the methodology that allowed the best reproducibility of spectra from bacteria colonies with minimal sample preparation, which was used in the subsequent work. Several attempts trying different resolutions and number of scans in the IR were made. A spectral resolution of 4 cm-1, with 32 scans were the settings that allowed the best results. Subsequently, in Chapter 3, it was made an attempt to identify 22 different foodborne bacterial genera/species using IR spectroscopy coupled with multivariate analysis. The principal component analysis, used as an exploratory technique, allowed to form distinct groups, each one corresponding to a different genus, in most of the cases. Then, a hierarchical cluster analysis was performed to further analyse the group formation and the possibility of distinction between species of the same bacterial genus. It was observed that IR spectroscopy not only is suitable to the distinction of the different genera, but also to differentiate species of the same genus, with the simultaneous use of principal component analysis and cluster analysis techniques. The utilization of IR spectroscopy and multivariate statistical analysis were also investigated in Chapter 4, in order to confirm the presence of Listeria monocytogenes and Salmonella spp. isolated from contaminated foods, after growth in selective medium. This would allow to substitute the traditional biochemical and serological methods that are used to confirm these pathogens and that delay the obtainment of the results up to 2 days. The obtained results allowed the distinction of 3 different Listeria species and the distinction of Salmonella spp. from other bacteria that can be mistaken with them. Finally, in chapter 5, high pressure processing, an emerging methodology that permits to produce microbiologically safe foods and extend their shelf-life, was applied to 12 foodborne bacteria to determine their resistance and the effects of pressure in cells. A treatment of 300 MPa, during 15 minutes at room temperature was applied. Gram-negative bacteria were inactivated to undetectable levels and Gram-positive showed different resistances. Bacillus cereus and Staphylococcus aureus decreased only 2 logs and Listeria innocua decreased about 5 logs. IR spectroscopy was performed in bacterial colonies before and after HPP in order to investigate the alterations of the cellular compounds. It was found that high pressure alters bands assigned to some cellular components as proteins, lipids, oligopolysaccharides, phosphate groups from the cell wall and nucleic acids, suggesting disruption of the cell envelopes. In this work, bacterial quantification and classification, as well as assessment of cellular compounds modification with high pressure processing were successfully performed. Taking this into account, it was showed that IR spectroscopy is a very promising technique to analyse bacteria in a simple and inexpensive manner.

Padrões territoriais das dificuldades manifestadas pela população com 65 ou mais anos

Objetivos: Numa sociedade caracterizada pelo envelhecimento populacional é de suma importância a identificação de padrões territoriais que permitam o desenho de políticas de bem-estar mais adequadas para cada território. Para tal, é necessário analisar a heterogeneidade da perceção das dificuldades nas diversas regiões. Este estudo pretende analisar as dificuldades das pessoas com 65 ou mais anos com vista a encontrar algumas diferenças territoriais com base no grupo etário, no tipo e grau de dificuldade, nos rendimentos e nas habilitações. Metodologia: Trata-se de um estudo exploratório que analisa as dificuldades percecionadas pelas pessoas com 65 ou mais anos, tendo por base os dados disponibilizados pelo INE sobre o recenseamento populacional de 2011. Recorre-se à análise multivariada (análise fatorial de componentes principais e análise de clusters) e à análise bivariada de forma a obter os resultados da investigação. Resultados: Os principais resultados apontam para: i) existência de diferenças quanto à distribuição no território da perceção das dificuldades; ii) a perceção das dificuldades, da incapacidade e da dimensão das dificuldades por parte do grupo etário dos 65 ou mais anos segue um padrão territorial distinto da população em geral; iii) a perceção das dificuldades e a perceção da incapacidade no grupo etário dos 65 ou mais anos apresentam uma mancha no território diferente do padrão do envelhecimento; iv) a incapacidade auditiva e a incapacidade visual embora com um padrão territorial diferente, agregam no mesmo fator a população geral e o grupo etário dos 65 ou mais anos; v) do ponto de vista territorial é possível distinguir cinco clusters quanto à perceção das dificuldades da população portuguesa; vi) os rendimentos e as habilitações contribuem para a diferenciação dos clusters identificados. Discussão: Os resultados apresentados apoiam a necessidade de reflexão e de pesquisa no âmbito do mapeamento das dificuldades, na medida em que são um importante mecanismo de conhecimento da realidade intra-regional, permitindo a tomada de decisão.