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.This work is funded by National Funds through the FCT, Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within projects PEstOE/EEI/UI0752/2014 and PEst-OE/QUI/UI0619/2012

Analysis of electroencephalogram-derived indexes for anesthetic depth monitoring in pediatric patients with intellectual disability undergoing dental surgery

Background: Patients with intellectual disability (ID) often require general anesthesia during oral procedures. Anesthetic depth monitoring in these patients can be difficult due to their already altered mental state prior to anesthesia. In this study, the utility of electroencephalographic indexes to reflect anesthetic depth was evaluated in pediatric patients with ID. Methods: Seventeen patients (mean age, 9.6 ± 2.9 years) scheduled for dental procedures were enrolled in this study. After anesthesia induction with propofol or sevoflurane, a bilateral sensor was placed on the patient's forehead and the bispectral index (BIS) was recorded. Anesthesia was maintained with sevoflurane, which was adjusted according to the clinical signs by an anesthesiologist blinded to the BIS value. The index performance was accessed by correlation (with the end-tidal sevoflurane [EtSevo] concentration) and prediction probability (with a clinical scale of anesthesia). The asymmetry of the electroencephalogram between the left and right sides was also analyzed. Results: The BIS had good correlation and prediction probabilities (above 0.5) in the majority of patients; however, BIS was not correlated with EtSevo or the clinical scale of anesthesia in patients with Lennox-Gastaut, West syndrome, cerebral palsy, and epilepsy. BIS showed better correlations than SEF95 and TP. No significant differences were observed between the left- and right-side indexes. Conclusion: BIS may be able to reflect sevoflurane anesthetic depth in patients with some types of ID; however, more research is required to better define the neurological conditions and/or degrees of disability that may allow anesthesiologists to use the BIS.Aura Silva’s work was supported by Portuguese Foundation for Science and Technology, reference SFRH/BPD /75697/2011info:eu-repo/semantics/publishedVersio

Fluidised bed combustion of two species of energy crops

The use of biomass fuels for energy production through combustion has a growing application worldwide mainly for two reasons: first, the utilization of biomass for energy contributes to mitigate emission of green house gases; second, its use decreases the dependence of imported fossil fuels in Europe. The objective of this work was to study the combustion behaviour of two endogenous biomass species: cardoon (cynara cardunculus) and arundo (arundo donax), which were specially produced in energy crops plantations. Mixtures of cardoon and a forestry biomass specie (eucalyptus) were also studied to evaluate potential benefits from synergies between both biomass fuel types. The results showed that the utilization of cardoon, in pelletized form, and loose arundo as feedstock, did not give rise to any operational problems related with the feeding system. It was verified that the mono combustion of cardoon could pose problems at industrial scale in fluidised bed systems, considering the high levels of HCl and NOX emissions obtained and tendency to sinter the bed sand material. The addition of the forestry biomass to cardoon appeared to prevent the bed agglomeration problem. Furthermore, both the NOX and SO2 emissions were found to decrease at the same time suggesting potential synergy of blending different types of biomass regarding pollutant emissions and in bed agglomeration problems

Bright conjugated polymer nanoparticles containing a biodegradable shell produced at high yields and with tuneable optical properties by a scalable microfluidic device

This study compares the performance of a microfluidic technique and a conventional bulk method to manufacture conjugated polymer nanoparticles (CPNs) embedded within a biodegradable poly(ethylene glycol) methyl ether-block-poly(lactide-co-glycolide) (PEG5K–PLGA55K) matrix. The influence of PEG5K–PLGA55K and conjugated polymers cyano-substituted poly(p-phenylene vinylene) (CN-PPV) and poly(9,9-dioctylfluorene-2,1,3-benzothiadiazole) (F8BT) on the physicochemical properties of the CPNs was also evaluated. Both techniques enabled CPN production with high end product yields (?70–95%). However, while the bulk technique (solvent displacement) under optimal conditions generated small nanoparticles (∼70–100 nm) with similar optical properties (quantum yields ∼35%), the microfluidic approach produced larger CPNs (140–260 nm) with significantly superior quantum yields (49–55%) and tailored emission spectra. CPNs containing CN-PPV showed smaller size distributions and tuneable emission spectra compared to F8BT systems prepared under the same conditions. The presence of PEG5K–PLGA55K did not affect the size or optical properties of the CPNs and provided a neutral net electric charge as is often required for biomedical applications. The microfluidics flow-based device was successfully used for the continuous preparation of CPNs over a 24 hour period. On the basis of the results presented here, it can be concluded that the microfluidic device used in this study can be used to optimize the production of bright CPNs with tailored properties with good reproducibility

Co-firing of biomass and other wastes in fluidised bed systems

A project on co-firing in large-scale power plants burning coal is currently funded by the European Commission. It is called COPOWER. The project involves 10 organisations from 6 countries. The project involves combustion studies over the full spectrum of equipment size, ranging from small laboratory-scale reactors and pilot plants, to investigate fundamentals and operating parameters, to proving trials on a commercial power plant in Duisburg. The power plant uses a circulating fluidized bed boiler. The results to be obtained are to be compared as function of scale-up. There are two different coals, 3 types of biomass and 2 kinds of waste materials are to be used for blending with coal for co-firing tests. The baseline values are obtained during a campaign of one month at the power station and the results are used for comparison with those to be obtained in other units of various sizes. Future tests will be implemented with the objective to achieve improvement on baseline values. The fuels to be used are already characterized. There are ongoing studies to determine reactivities of fuels and chars produced from the fuels. Reactivities are determined not only for individual fuels but also for blends to be used. Presently pilot-scale combustion tests are also undertaken to study the effect of blending coal with different types of biomass and waste materials. The potential for synergy to improve combustion is investigated. Early results will be reported in the Conference. Simultaneously, studies to verify the availability of biomass and waste materials in Portugal, Turkey and Italy have been undertaken. Techno-economic barriers for the future use of biomass and other waste materials are identified. The potential of using these materials in coal fired power stations has been assessed. The conclusions will also be reported

Antimicrobial and Photoantimicrobial Activities of Chitosan/CNPPV Nanocomposites

Multidrug-resistant bacteria represent a global health and economic burden that urgently calls for new technologies to combat bacterial antimicrobial resistance. Here, we developed novel nanocomposites (NCPs) based on chitosan that display different degrees of acetylation (DAs), and conjugated polymer cyano-substituted poly(p-phenylene vinylene) (CNPPV) as an alternative approach to inactivate Gram-negative (E. coli) and Gram-positive (S. aureus) bacteria. Chitosan's structure was confirmed through FT-Raman spectroscopy. Bactericidal and photobactericidal activities of NCPs were tested under dark and blue-light irradiation conditions, respectively. Hydrodynamic size and aqueous stability were determined by DLS, zeta potential (ZP) and time-domain NMR. TEM micrographs of NCPs were obtained, and their capacity of generating reactive oxygen species (ROS) under blue illumination was also characterized. Meaningful variations on ZP and relaxation time T2 confirmed successful physical attachment of chitosan/CNPPV. All NCPs exhibited a similar and shrunken spherical shape according to TEM. A lower DA is responsible for driving higher bactericidal performance alongside the synergistic effect from CNPPV, lower nanosized distribution profile and higher positive charged surface. ROS production was proportionally found in NCPs with and without CNPPV by decreasing the DA, leading to a remarkable photobactericidal effect under blue-light irradiation. Overall, our findings indicate that chitosan/CNPPV NCPs may constitute a valuable asset for the development of innovative strategies for inactivation and/or photoinactivation of bacteria. Keywords: photoantimicrobial activity; blue-light irradiation; chitosan; CNPPV; nanocomposites; E. coli; S. aureu

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.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/00319/2013

Quality of life after carotid endarterectomy

<p>Abstract</p> <p>Background</p> <p>Most studies documenting beneficial outcomes after carotid endarterectomy (CE) are limited to mortality and morbidity rates, costs, and length of hospital stay (LOS). Few have examined the dependency of patients and how they perceive their own health changes after surgery. The aim of the present study was to evaluate quality of life and independence in activities of daily living (ADL) and to study its determinants.</p> <p>Methods</p> <p>Sixty-three patients admitted in the Post Anaesthesia Care Unit (PACU) after CE were eligible for this 14-month follow-up study. Patients were contacted 6 months after discharge to complete a Short Form-36 questionnaire (SF-36) and to have their dependency in ADL evaluated.</p> <p>Results</p> <p>Among 59 hospital survivors at 6 months follow-up, 43 completed the questionnaires. Sixty-three percent reported that their general level of health was better on the day they answered the questionnaire than 12 months earlier. Patients had worse SF-36 scores for all domains except bodily pain than a general urban population, and comparison with a group of patients 6 months after surgical ICU discharge showed no differences. Six months after PACU discharge, the Lawton Instrumental Activities of ADL Scale and the Katz Index of ADL demonstrated higher dependency scores (5.9 ± 2.2 versus 4.3 ± 2.4 and 0.3 ± 0.8 versus 0.6 ± 0.9, p < 0.001 and p = 0.047). Sixty-five percent and 33% were dependent in at least one activity in instrumental and personal ADL, respectively. Patients dependent in at least one ADL task had higher Revised Cardiac Risk Index (RCRI) scores (1.0 versus 1.5, p = 0.017). After controlling for multiple comparisons, no significant differences were found.</p> <p>Conclusion</p> <p>Patients undergoing CE have improved self-perception of quality of life despite being more dependent. Almost all their scores are worse than those in an urban population. We could identify no predictors of greater dependency in ADL tasks six months after PACU discharge.</p

Ash agglomeration and deposition during combustion of poultry litter in a bubbling fluidized-bed combustor

peer-reviewedn this study, we have characterized the ash resulting from fluidized bed combustion of poultry litter as being dominated by a coarse fraction of crystalline ash composed of alkali-Ca-phosphates and a fine fraction of particulate K2SO4 and KCl. Bed agglomeration was found to be coating-induced with two distinct layers present. The inner layer (0.05–0.09 mm thick) was formed due to the reaction of gaseous potassium with the sand (SiO2) surface forming K-silicates with low melting points. Further chemical reaction on the surface of the bed material strengthened the coating forming a molten glassy phase. The outer layer was composed of loosely bound, fine particulate ash originating from the char. Thermodynamic equilibrium calculations showed slag formation in the combustion zone is highly temperature-dependent, with slag formation predicted to increase from 1.8 kg at 600 °C to 7.35 kg at 1000 °C per hour of operation (5.21 kg of ash). Of this slag phase, SiO2 and K2O were the dominant phases, accounting for almost 95%, highlighting the role of K-silicates in initiating bed agglomeration. The remaining 5% was predicted to consist mainly of Al2O3, K2SO4, and Na2O. Deposition downstream in the low-temperature regions was found to occur mostly through the vaporization–condensation mechanism, with equilibrium decreasing significantly with decreasing temperatures. The dominant alkali chloride-containing gas predicted to form in the combustion zone was KCl, which corresponds with the high KCl content in the fine baghouse ash