Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Thrombophilia screening: An artificial neural network approach

Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.

Artificial neural networks in diagnosis of liver diseases

Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks.

Logic programming and artificial neural networks in breast cancer detection

About 90% of breast cancers do not cause or are capable of producing death if detected at an early stage and treated properly. Indeed, it is still not known a specific cause for the illness. It may be not only a beginning, but also a set of associations that will determine the onset of the disease. Undeniably, there are some factors that seem to be associated with the boosted risk of the malady. Pondering the present study, different breast cancer risk assessment models where considered. It is our intention to develop a hybrid decision support system under a formal framework based on Logic Programming for knowledge representation and reasoning, complemented with an approach to computing centered on Artificial Neural Networks, to evaluate the risk of developing breast cancer and the respective Degree-of-Confidence that one has on such a happening.

Honours students: good marks and what else?

Currently in Portugal academic excellence in higher education is given recognition through merit prizes. Because honours students can be seen as having the potential to achieve imporant levels of professional expertise, especially if they have some personal skills, it is important to know not only the marks of the students but also the personal characteristics that contribute to academic success and which may also be important for career success. Some theoretical models of giftedness and excellence agree with this idea and this work considers the latest contribution of Renzulli (2005) where it is pointed out that excellent achievements result from the combination of motivational, intellectual and creative factors as well as from co-cognitive factors which are most associated with personality functioning in a particular context. The main purpose of this paper is to analyze how honours students differ from their classmates in various psychological dimensions: Cognition-creativity, Motivation and Learning Strategies, Persistence, Social Interaction, Drive for Excellence and Cultural Interest. These dimensions were measured by the Inventory of Psychological Characteristics Associated with Academic Performance (ICPADA), which was constructed taking into consideration the previous study of Scaeger et al. (2012). The sample included 914 Portuguese higher educatoin students from a first cycle degree in the Bologna process. Participants were selected from three different fields of study: Social and Human Sciences; Science and Technology; Arts and Humanities. The data collected through the administration of the ICPADA was presented, and the results revealed a higher self-perception by honours students in all areas analyzed, with the exception of the dimension of social interaction. In addition an interaction effect was revealed for persistence, social interaction, and cultural interest. The field of study and whether the participants were honours students or not were also taken into account. Some implications for future studies are presented here along with possible interventions for honours students.

Biosynthetic production of curcuminoids

Curcuminoids are natural phenylpropanoids from plants that have been reported as potential cancer-fighting drugs. Nevertheless, these compounds present a poor bioavailability. Cellular uptake is low and curcuminoids are quickly metabolized once inside the cell, requiring repetitive oral doses to achieve an effective concentration for therapeutic activity [1]. Herein, we report an engineered artificial pathway for the production of curcuminoids in Escherichia coli. Arabidopsis thaliana 4-coumaroyl-CoA ligase and Curcuma longa diketide-CoA synthase (DCS) and curcumin synthase (CURS1) were used and 188 µM (70 mg/L) of curcumin was obtained from ferulic acid [2]. Bisdemethoxycurcumin and demethoxycurcumin were also produced, but in lower concentrations, by feeding p-coumaric acid or a mixture of p-coumaric acid and ferulic acid, respectively. Additionally, curcuminoids were produced from tyrosine through the caffeic acid pathway. To produce caffeic acid, tyrosine ammonia lyase from Rhodotorula glutinis and 4-coumarate 3-hydroxylase from Saccharothrix espanaensis were used [3]. Caffeoyl-CoA 3-O-methyl-transferase from Medicago sativa was used to convert caffeoyl-CoA to feruloyl-CoA. Using caffeic acid, p-coumaric acid or tyrosine as a substrate, 3.9, 0.3, and 0.2 µM of curcumin were produced, respectively. This is the first report on the use of DCS and CURS1 in vivo to produce curcuminoids. In addition, curcumin, the most studied curcuminoid for therapeutic purposes and considered in many studies as the most potent and active, was produced by feeding tyrosine using a pathway involving caffeic acid. We anticipate that by using a tyrosine overproducing strain, curcumin can be produced in E. coli without the need of adding expensive precursors to the medium, thus decreasing the production cost. Therefore, this alternative pathway represents a step forward in the heterologous production of curcumin using E. coli. Aiming at greater production titers and yields, the construction of this pathway in another model organism such as Saccharomyces cerevisiae is being considered.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

Antioxidant potential of two Apiaceae plant extracts: a comparative study focused on the phenolic composition

The present study aimed to characterize the extracts prepared from Pimpinella anisum L. (anise) and Coriandrum sativum L. (coriander) (Apiaceae plants) seeds in terms of phenolic composition, and to correlate the obtained profiles with the antioxidant activity. Anise gave the highest abundance in phenolic compounds (42.09± 0.11 mg/g extract), mainly flavonoids (28.08±0.17 mg/g extract) and phenolic acids (14.01±0.06 mg/g extract), and also the highest antioxidant potential, accessed for the ability to inhibit lipid peroxidation and -carotene bleaching, reducing power and free radical scavenger activity. Apigenin and luteolin derivatives, as also caffeoylquinic acid derivatives appear to be directly related with the higher in vitro antioxidant potential of the anise extract.. In contrast, the weak antioxidant potential of coriander seems to be due to their lower abundance in phenolic compounds (2.24±0.01 mg/g extract). Further studies are necessary to evaluate the in vivo antioxidant potential of the tested extracts, but the performed in vitro experiments highlight them as potential health promoters.

The synthesis of new 6-hydrazinopurines as potential anticancer agents

[Excerpt] Purines, such as adenine, are one of the most important naturally occurring nitrogen heterocycles and they are frequently used as bioactive agents.[1,2] The increasing number of synthetic purines reveals the great potential of these compounds as enzyme inhibitors. Protein Kinases have an important regulatory role in cell proliferation, differentiation and signalling processes. Abnormal signal transduction is responsible for devastating diseases such as cancer. All of the protein kinases identified have in common the cofactor ATP indicating that the adenine nucleus is a very important scaffold for discovery of new anti-cancer agents.[3,4] Previous work identified a modest anticancer activity in a family of 6-arylaminopurines. In the view of these results, it seemed reasonable to assume that some interesting anticancer agents might result by replacement of the phenyl group by a secondary amino group linked to the N-6 atom of the adenine moiety. (...)

Efficacy of a gas permeable contact lens to induce peripheral myopic defocus

Purpose. The purpose of this work was to evaluate the potential of a novel custom-designed rigid gas permeable (RGP) contact lens to modify the relative peripheral refractive error in a sample of myopic patients. Methods. Fifty-two right eyes of 52 myopic patients (mean [TSD] age, 21 [T2] years) with spherical refractive errors ranging from j0.75 to j8.00 diopters (D) and refractive astigmatism of 1.00 D or less were fitted with a novel experimental RGP (ExpRGP) lens designed to create myopic defocus in the peripheral retina. A standard RGP (StdRGP) lens was used as a control in the same eye. The relative peripheral refractive error was measured without the lens and with each of two lenses (StdRGP and ExpRGP) using an open-field autorefractometer from 30 degrees nasal to 30 degrees temporal, in 5-degree steps. The effectiveness of the lens design was evaluated as the amount of relative peripheral refractive error difference induced by the ExpRGP compared with no lens and with StdRGP conditions at 30 degrees in the nasal and temporal (averaged) peripheral visual fields. Results. Experimental RGP lens induced a significant change in relative peripheral refractive error compared with the nolens condition (baseline), beyond the 10 degrees of eccentricity to the nasal and temporal side of the visual field (p G 0.05). The maximum effect was achieved at 30 degrees. Wearing the ExpRGP lens, 60% of the eyes had peripheral myopia exceeding j1.00 D, whereas none of the eyes presented with this feature at baseline. There was no significant correlation (r = 0.04; p = 0.756) between the degree of myopia induced at 30 degrees of eccentricity of the visual field with the ExpRGP lens and the baseline refractive error. Conclusions. Custom-designed RGP contact lenses can generate a significant degree of relative peripheral myopia in myopic patients regardless of their baselin spherical equivalent refractive error.

Cost-efficient one-part alkali-activated mortars with low global warming potential for floor heating systems applications

Increasing building energy efficiency is one the most cost-effective ways to reduce emissions. The use of thermal insulation materials mitigates heat loss in buildings, therefore minimising heat energy needs. In recent years, several papers were published on the subject of foam alkali-activated cements with enhanced thermal conductivity. However, on those papers cost analysis was strangely avoided. This paper presents experimental results on one-part alkali-activated cements. It also includes global warming potential assessment and cost analysis. Foam one-part alkali-activated cements cost simulations considering two carbon dioxide social costs scenarios are also included. The results show that one-part alkali-activated cements mixtures based on 26%OPC + 58.3%FA + 8%CS + 7.7%CH and 3.5% hydrogen peroxide constitute a promising cost-efficient (67 euro/m3), thermal insulation solution for floor heating systems. This mixture presents a low global warming potential of 443 KgCO2eq/m3. The results confirm that in both carbon dioxide social cost scenarios the mixture 26 OPC + 58.3 FA + 8 CS + 7.7 CH with 3.5% hydrogen peroxide foaming agent is still the most cost efficient.

Organização e gestão da manutencão de ferramentas numa empresa de produção de peças metálicas

Dissertação de mestrado Engenharia e Gestão da Qualidade

Wear of PEEK-Ti6Al4V systems under micro-abrasion and linear sliding conditions

Dissertação de mestrado integrado em Engenharia Biomédica

Desenvolvimento e teste de um sistema para caracterização de materiais magnetoelétricos

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores

Desenvolvimento de rede neuronal artificial para o diagnóstico de doenças neurodegenerativas

Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e Computadores