Screening and determination of sulphonamide residues in bovine milk samples using a flow injection system

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sensitive flow-injection spectrophotometric analysis of bromopride

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Combined active and semi-supervised learning using particle walking temporal dynamicscombined active and semi-supervised learning using particle walking temporal dynamics

Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques are combined into a single nature-inspired method. It features particles walking on a network built from the data set, using a unique random-greedy rule to select neighbors to visit. The particles, which have both competitive and cooperative behavior, are created on the network as the result of label queries. They may be created as the algorithm executes and only nodes affected by the new particles have to be updated. Therefore, it saves execution time compared to traditional active learning frameworks, in which the learning algorithm has to be executed several times. The data items to be queried are select based on information extracted from the nodes and particles temporal dynamics. Two different rules for queries are explored in this paper, one of them is based on querying by uncertainty approaches and the other is based on data and labeled nodes distribution. Each of them may perform better than the other according to some data sets peculiarities. Experimental results on some real-world data sets are provided, and the proposed method outperforms the semi-supervised learning method, from which it is derived, in all of them.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Determination of sulfate in ethanol fuel using an electrode chemically modified with polypyrrole by flow injection analysis

In this work, an electrode chemically modified with polypyrrole (PCME) was employed for determination of sulfate in ethanol fuel using a FIA system. The PCME was prepared by polymerization of pyrrole at a glassy carbon electrode by means of cyclic voltammetry technique. An analytical curve from 1.0 x 10−5 to 8.0 x 10−5 mol L−1 was obtained in flow injection system based on the PCME. An amperometric sensibility of 2.3 x 10−3 A mol−1 L and a detection limit of 2.5 x 10−6 mol L−1 were achieved. The proposed method was employed for determination of sulfate ions in commercial samples of ethanol fuel. The results were in good agreement with those obtained by the ionic chromatographic method.

Desenvolvimento de parafuso de interferência bioabsorvível para cirurgia de joelho em PLDL (poli ácido lático) e compósito PLDL + βTCP (beta trifosfato de cálcio)

Pós-graduação em Engenharia Mecânica - FEB

Particle competition and cooperation for semi-supervised learning with label noise

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Hopping-tunneling model to describe electric charge injection at metal/organic semiconductor heterojunctions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Supervised variational relevance learning, an analytic geometric feature selection with applications to omic datasets

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of anesthetic efficacy and adverse effects associated with peribulbar injection of ropivacaine performed with and without ultrasound guidance in dogs

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Semi-supervised learning for relevance feedback on image retrieval tasks

Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts required by these methods tend to increase as well, demanding approaches for reducing the need of user interactions. In this context, this paper proposes a semi-supervised learning algorithm for relevance feedback to be used in image retrieval tasks. The proposed semi-supervised algorithm aims at using both supervised and unsupervised approaches simultaneously. While a supervised step is performed using the information collected from the user feedback, an unsupervised step exploits the intrinsic dataset structure, which is represented in terms of ranked lists of images. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture descriptors and different datasets. The proposed approach was also evaluated on multimodal retrieval tasks, considering visual and textual descriptors. Experimental results demonstrate the effectiveness of the proposed approach.

Skeletal muscle degeneration and regeneration after injection of bothropstoxin-II, a phospholipase A2 isolated from the venom of the snake Bothrops jararacussu

A myotoxic phospholipase A2, named bothropstoxin II (BthTX-II), was isolated from the venom of the South American snake Bothrops jararacussu and the pathogenesis of myonecrosis induced by this toxin was studied in mice. BthTX-II induced a rapid increase in plasma creatine kinase levels. Histological and ultrastructural observations demonstrate that this toxin affects muscle fibers by first disrupting the integrity of plasma membrane, as delta lesions were the earliest morphological alteration and since the plasma membrane was interrupted or absent in many portions. In agreement with this hypothesis, BthTX-II released peroxidase entrapped in negatively charged multilamellar liposomes and behaved as an amphiphilic protein in charge shift electrophoresis, an indication that its mechanism of action might be based on the interaction and disorganization of plasma membrane phospholipids. Membrane damage was followed by a complex series of morphological alterations in intracellular structures, most of which are probably related to an increase in cytosolic calcium levels. Myofilaments became hypercontracted into dense clumps which alternated with cellular spaces devoid of myofibrillar material. Later on, myofilaments changed to a hyaline appearance with a more uniform distribution. Mitochondria were drastically affected, showing high amplitude swelling, vesiculation of cristae, formation of flocculent densities, and membrane disruption. By 24 hr, abundant polymorphonuclear leucocytes and macrophages were observed in the interstitial space as well as inside necrotic fibers. Muscle regeneration proceeded normally, as abundant myotubes and regenerating myofibers were observed 7 days after BthTX-II injection. By 28 days regenerating fibers had a diameter similar to that of adult muscle fibers, although they presented two distinctive features: central location of nuclei and some fiber splitting. This good regenerative response may be explained by the observation that BthTX-II does not affect blood vessels, nerves, or basal laminae. © 1991.

Gold electrodes from recordable CDs for mercury quantification by flow injection analysis

The development of a new methodology for the construction of very efficient flow cells for mercury detection by potentiometric stripping analysis, employing the thin gold layer of recordable CDs as working electrode is reported. This new source of electrodes (CDtrodes) show very attractive performance, similar to that obtained with commercial gold electrodes, with superior versatility. The low cost of this new source of gold electrodes allows a frequent replacement of the electrode, avoiding cumbersome clean-up treatments. Various experimental parameters have been optimized to yield low detection limits (0.25 ng/mL of mercury for 5 min deposition at 0.3 V) and good precision (standard deviation of 1.9% was obtained for 15 repetitive measurements using 10 ng/mL of mercury). Standard curves were found to be linear over the range of 0.5-100 μg L-1 of mercury. The flow cells developed were used for the quantification of mercury in oceanic and tap water. © Springer-Verlag 2000.

A simple high-performance liquid chromatography assay for on-line determination of catecholamines in adrenal gland by direct injection on an ISRP column

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)