935 resultados para Gemstone Team PANACEA: Promoting A Novel Approach to Cellular (gene) Expression Alteration
Resumo:
Integrating top fruit production into an agroforestry system, where trees are integrated with arable crop production may have a beneficial effect on the control of plant pathogens such as scab (Venturia inaequalis). Apple yields and pest and disease levels were assessed in a novel apple/arable agroforestry system in Suffolk, and compared with a modern local organic orchard in 2012. Despite 2012 being a very bad year for apple production in the UK, apple yields in the agroforestry system appeared to be comparable with standard figures when scaled up from 2.5% land area under apple production to 100% apples, and even at just 2.5% cover, outperformed the organic orchard used for comparison. Initial indications are that scab levels were over twice as high in the organic orchard than in the agroforestry, indicating that this approach may offer some potential in reducing copper use in organic apple production. However, further research will be required to confirm these early results.
Resumo:
Promoting the inclusion of students with disabilities in e-learning systems has brought many challenges for researchers and educators. The use of synchronous communication tools such as interactive whiteboards has been regarded as an obstacle for inclusive education. In this paper, we present the proposal of an inclusive approach to provide blind students with the possibility to participate in live learning sessions with whiteboard software. The approach is based on the provision of accessible textual descriptions by a live mediator. With the accessible descriptions, students are able to navigate through the elements and explore the content of the class using screen readers. The method used for this study consisted of the implementation of a software prototype within a virtual learning environment and a case study with the participation of a blind student in a live distance class. The results from the case study have shown that this approach can be very effective, and may be a starting point to provide blind students with resources they had previously been deprived from. The proof of concept implemented has shown that many further possibilities may be explored to enhance the interaction of blind users with educational content in whiteboards, and further pedagogical approaches can be investigated from this proposal. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.
Resumo:
In this paper we describe our system for automatically extracting "correct" programs from proofs using a development of the Curry-Howard process. Although program extraction has been developed by many authors, our system has a number of novel features designed to make it very easy to use and as close as possible to ordinary mathematical terminology and practice. These features include 1. the use of Henkin's technique to reduce higher-order logic to many-sorted (first-order) logic; 2. the free use of new rules for induction subject to certain conditions; 3. the extensive use of previously programmed (total, recursive) functions; 4. the use of templates to make the reasoning much closer to normal mathematical proofs and 5. a conceptual distinction between the computational type theory (for representing programs)and the logical type theory (for reasoning about programs). As an example of our system we give a constructive proof of the well known theorem that every graph of even parity, which is non-trivial in the sense that it does not consist of isolated vertices, has a cycle. Given such a graph as input, the extracted program produces a cycle as promised.
Resumo:
In all applications of clone detection it is important to have precise and efficient clone identification algorithms. This paper proposes and outlines a new algorithm, KClone for clone detection that incorporates a novel combination of lexical and local dependence analysis to achieve precision, while retaining speed. The paper also reports on the initial results of a case study using an implementation of KClone with which we have been experimenting. The results indi- cate the ability of KClone to find types-1,2, and 3 clones compared to token-based and PDG-based techniques. The paper also reports results of an initial empirical study of the performance of KClone compared to CCFinderX.
Resumo:
Using the Pricing Equation, in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) mimicking portfolio which relies on the fact that its logarithm is the ìcommon featureîin every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences, making it suitable for testing di§erent preference speciÖcations or investigating intertemporal substitution puzzles.
Resumo:
Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the "common feature" in every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences. The techniques discussed in this paper were applied to two relevant issues in macroeconomics and finance: the first asks what type of parametric preference-representation could be validated by asset-return data, and the second asks whether or not our SDF estimator can price returns in an out-of-sample forecasting exercise. In formal testing, we cannot reject standard preference specifications used in the macro/finance literature. Estimates of the relative risk-aversion coefficient are between 1 and 2, and statistically equal to unity. We also show that our SDF proxy can price reasonably well the returns of stocks with a higher capitalization level, whereas it shows some difficulty in pricing stocks with a lower level of capitalization.
Resumo:
A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are completed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
We report on several amorphous compounds based on different metal oxianions with intense photoluminescence at room temperature. These compounds were synthesised by a soft chemical process and deposited on Si (100) by a spin-coating technique. To select these different metal oxianions, a classic concept based on a metal oxide network former is used. We describe a minimum set of requirements to obtain an amorphous metal oxide with photoluminescence emission at room temperature.
Resumo:
Chronic pain is the major complaint of myofascial pain dysfunction syndrome (MPDS) and is a complex problem which involves physical, psychological and social aspects, the etiology of MPDS is multifactorial and the multidisciplinary approach is essential for differential diagnosis and for comprehensive treatment planning, In 1993, the Dental School of Piracicaba-UNICAMP, Brazil, opened a Center for Pain Studies (CPS), staffed by health care providers including, dentists, psychologists, physicians, physiotherapists and phonoaudiologists. The major aims of the CPS are to provide clinical care and to develop basic and applied research, Sixty-two MPDS patients had been admitted to the CPS by 1997, There were 60 females and 2 males, mean age -32.5 years, the mean duration of chronic pain was 48 months. Pain intensity and unpleasantness were measured employing the Visual Analogue Scale, the tendency to develop stress-related diseases was assessed by the Social Readjustment de Scale, There was a mean reduction of chronic pain of 69.89% and 71.78% relative to intensity and unpleasantness, respectively, the experience of clinical attendance at a multidisciplinary center showed the relevance of a team consisting of health care providers from different specialties with well-established aims, completely integrated and sensitive enough to understand the painful complaints of MPDS patients.
Resumo:
A novel fractal model for grain boundary regions of ceramic materials was developed. The model considers laterally inhomogeneous distribution of charge carriers in the vicinity of grain boundaries as the main cause of the non-Debye behaviour and distribution of relaxation times in ceramic materials. Considering the equivalent circuit the impedance of the grain boundary region was expressed. It was shown that the impedance of the grain boundary region has the form of the Davidson-Cole equation. The fractal dimension of the inhomogeneous distribution of charge carriers in the region close to the grain boundaries could be calculated based on the relation ds = 1 + β, where β is the constant from the Davidson-Cole equation.
Resumo:
This paper reports on a 4-year-old male who had dyskeratosis congenita and who acquired severe aplastic anemia. The patient developed hyperpigmentation of the face, neck and chest region, arms, shoulders and legs. In addition, he had dry skin, deformed fingernails and toenails, sparse hair and eyebrows and hyperkeratosis of the dorsum of the hands and feet. Laboratory and histological analysis revealed severe pancytopenia and dyserythropoiesis of red blood cells, hypocellularity of white blood cells and decreased megakaryocytes with dysplasia. The intraoral examination identified bleeding gums; petechiae of the palate, tongue and cheek mucosa; and an atrophic, smooth and shining dorsal surface of the tongue. There were deep carious lesions in the deciduous mandibular molars and maxillary anterior teeth; as well as mobility of mandibular left canine, which had bone loss. The treatment for oral lesions included diet changes, improved oral hygiene, and extraction of the deciduous teeth destroyed by caries.
Resumo:
Spanish version available