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Maize participatory breeding in Portugal: Comparison of farmer's and breeder's on-farm selection
No full textVASO is a Portuguese participatory maize breeding project (1984), where several maize landraces such as Pigarro have been selected both by a farmer's (phenotypic recurrent selection) and a breeder's approach (S2 lines recurrent selection). The objectives of this study were to determine the phenotypic and genotypic responses to participatory selection using these two different approaches, to clarify to which extent both selection methods preserve genetic diversity, and conclude what is the preferred method to apply in sustainable farming systems. The results, obtained via ANOVA, regression analyses and molecular markers, indicate that for both selection methods, genetic diversity was not significantly reduced, even with the most intensive breeder's selection. Although there were some common outputs, such as the determinated versus indeterminated ears, cob and ear weight ratio per ear and rachis 2, specific phenotypic traits evolved in opposite directions between the two selection approaches. Yield increase was only detected during farmer selection, indicating its interest on PPB. Candidate genes were identified for a few of the traits under selection as potential functional markers in participatory plant breeding
Synergistic effect of carboplatin and piroxicam on two bladder cancer cell lines
No full textBackground/Aim: This study aimed to evaluate the in vitro efficacy of carboplatin and piroxicam, both in isolation and combined, against T24 and 5637 human urinary bladder cancer cell lines. Materials and Methods: Cell viability, drug interaction, cell morphology, cell proliferation, apoptosis and autophagy were analyzed after 72 h of drug exposure. Statistical analysis was performed and values of p<0.05 were considered statistically significant. Results: Drug exposure in combination led to a significant reduction of cell viability comparatively to single-drug exposure. These combinations resulted in a synergistic interaction in the T24 (combination index for 50% effect (CI50)=0.65) and 5637 (CI50=0.17) cell lines. Notable increase of morphological alterations, a marked decrease of Ki-67 expression, a considerable enhancement of autophagic vacuoles and a minimal effect on apoptosis was observed in both cell lines treated with combined drugs. Conclusion: Data showed that in vitro combination of carboplatin and piroxicam produced a more potent antiproliferative effect when compared to single drugs
Reliability Optimization of Automated Distribution Networks With Probability Customer Interruption Cost Model in the Presence of DG Units
No full textDistribution automation systems in terms of automatic and remote-controlled sectionalizing switches allows distribution utilities to implement flexible control of distribution networks, which is a successful strategy to enhance efficiency, reliability, and quality of service. The sectionalizing switches play a significant role in an automated distribution network, hence optimizing the allocation of switches can improve the quality of supply and reliability indices. This paper presents a mixed-integer nonlinear programming aiming to model the optimal placement of manual and automatic sectionalizing switches and protective devices in distribution networks. A value-based reliability optimization formulation is derived from the proposed model to take into consideration customer interruption cost and related costs of sectionalizing switches and protective devices. A probability distribution cost model is developed based on a cascade correlation neural network to have a more accurate reliability assessment. To ensure the effectiveness of the proposed formulation both technical and economic constraints are considered. Furthermore, introducing distributed generation into distribution networks is also considered subject to the island operation of DG units. The performance of the proposed approach is assessed and illustrated by studying on the bus 4 of the RBTS standard test system. The simulation results verify the capability and accuracy of the proposed approach
Ensemble learning for data stream analysis: A survey
No full textIn many applications of information systems learning algorithms have to act in dynamic environments where data are collected in the form of transient data streams. Compared to static data mining, processing streams imposes new computational requirements for algorithms to incrementally process incoming examples while using limited memory and time. Furthermore, due to the non-stationary characteristics of streaming data, prediction models are often also required to adapt to concept drifts. Out of several new proposed stream algorithms, ensembles play an important role, in particular for 'non-stationary environments. This paper surveys research on ensembles for data stream classification as well as regression tasks. Besides presenting a comprehensive spectrum of ensemble approaches for data streams, we also discuss advanced learning concepts such as imbalanced data streams, novelty detection, active and semi supervised learning, complex data representations and structured outputs. The paper concludes with a discussion of open research problems and lines of future research. Published by Elsevier B.V
A Metaheuristic Approach to the Multi-Objective Unit Commitment Problem Combining Economic and Environmental Criteria
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Bistability of Evolutionary Stable Vaccination Strategies in the Reinfection SIRI Model
Get PDFWe use the reinfection SIRI epidemiological model to analyze the impact of education programs and vaccine scares on individuals decisions to vaccinate or not. The presence of the reinfection provokes the novelty of the existence of three Nash equilibria for the same level of the morbidity relative risk instead of a single Nash equilibrium as occurs in the SIR model studied by Bauch and Earn (PNAS 101:13391-13394, 2004). The existence of three Nash equilibria, with two of them being evolutionary stable, introduces two scenarios with relevant and opposite features for the same level of the morbidity relative risk: the low-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a low probability; and the high-vaccination scenario corresponding to the evolutionary stable vaccination strategy, where individuals will vaccinate with a high probability. We introduce the evolutionary vaccination dynamics for the SIRI model and we prove that it is bistable. The bistability of the evolutionary dynamics indicates that the damage provoked by false scares on the vaccination perceived morbidity risks can be much higher and much more persistent than in the SIR model. Furthermore, the vaccination education programs to be efficient they need to implement a mechanism to suddenly increase the vaccination coverage level
Strategic Behavior of Multi-Energy Players in Electricity Markets as Aggregators of Demand Side Resources using a Bi-level Approach
No full textMicrofiber Knot With Taper Interferometer for Temperature and Refractive Index Discrimination
Get PDFA compact sensing structure using two distinct optical devices, a microfiber knot resonator and an abrupt taper-based Mach-Zehnder interferometer (MZI), is presented. The device was fabricated using only CO2 laser processing. The transmission spectrum presents two different components with different sensitivities to different physical and chemical parameters. The sensor was characterized in temperature and refractive index. For temperature sensing in water, the MZI component presents a sensitivity of -196 +/- 2 pm/degrees C while the microfiber knot resonator (MKR) component shows a sensitivity of 25.1 +/- 0.9 pm/degrees C, for water temperature variations of 12 degrees C. Sensitivities of 1354 +/- 14 nm/RIU and -43 +/- 4 nm/RIU were achieved for refractive index sensing for the MZI and the MKR components, respectively, in a refractive index range from 1.32823 to 1.33001. The matrix method was used for the simultaneous measurement of temperature and refractive index
Cross-layer classification framework for automatic social behavioural analysis in surveillance scenario
Get PDFThe increasing demand for human activity analysis in surveillance scenarios has been triggered by the emergence of new features and concepts to help in identifying activities of interest. However, the characterisation of individual and group behaviours is a topic not so well studied in the video surveillance community due to not only its intrinsic difficulty and large variety of topics involved, but also because of the lack of valid semantic concepts that relate human activity to social context. In this paper, we address the topic of social semantic meaning in a well-defined surveillance scenario, namely shopping mall, and propose new definitions of individual and group behaviour that consider environment context, a relational descriptor that emphasises position and attention-based characteristics, and a new classification approach based on mini-batches. We also present a wide evaluation process that analyses the sociological meaning of the individual features and outlines the performance impact of automatic features extraction processes into our classification framework. We verify the discriminative value of the selected features, state the descriptor performance and robustness over different stress conditions, confirm the advantage of the proposed mini-batch classification approach which obtains promising results, and outline future research lines to improve our novel social behavioural analysis framework