Teaching general concepts about sensors and transfer functions with a voltage divider

This work proposes the use of a simple voltage divider circuit composed by one potentiometer and one resistor to simulate the behavior of the electrical output signal of linear and nonlinear sensors. It is a low cost way to implement practical experiments in classroom and it also enables the analysis of interesting topics of electricity. This work induces naturally to a class guide where students can build and characterize a voltage divider to explore several concepts about sensors output signal. As the result of this teaching activity it is expected that students understand fundamentals of voltage divider, potentiometer operation, fundamental sensor characteristics, transfer function, and, besides, associate directly concepts of physics and mathematics with a practical approach.

Diterpenos tetranorlabdanos e isocumarinas produzidos por Botryosphaeria parva, um fungo endofítico em Eugenia jambolana Lam. (Myrtaceae)

Pós-graduação em Química - IQ

Diagnóstico geoambiental no município de Batatais-SP

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Increasing Student Confidence and Knowledge through Student Presentations

In this action research study of a 9th grade Algebra classroom, I investigated the influence of having students present homework solutions and what effect it had on student learning and student confidence. Students were asked to present solutions to homework problems each day and were rated on how well they did. The students were also surveyed about their confidence and feelings about mathematics. Students were also observed for information about who they asked questions of when presented with a math problem they did not understand. In this classroom, two teachers were involved in instruction and this study examines what affect this had on student learning and who was asked for help. As a result of presentations, students’ confidence increased and students reacted positively to both the presentations and their own mathematical learning. The students felt the presentations were a benefit to the class and watching their peers solve mathematical equations helped them to better understand the mathematics.

Helping End-User Programmers “Engineer” Dependable Software

Not long ago, most software was written by professional programmers, who could be presumed to have an interest in software engineering methodologies and in tools and techniques for improving software dependability. Today, however, a great deal of software is written not by professionals but by end-users, who create applications such as multimedia simulations, dynamic web pages, and spreadsheets. Applications such as these are often used to guide important decisions or aid in important tasks, and it is important that they be sufficiently dependable, but evidence shows that they frequently are not. For example, studies have shown that a large percentage of the spreadsheets created by end-users contain faults, and stories abound of spreadsheet faults that have led to multi-million dollar losses. Despite such evidence, until recently, relatively little research had been done to help end-users create more dependable software.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

Bourgin-Yang version of the Borsuk-Ulam theorem for Z(pk)-equivariant maps

Let G = Z(pk) be a cyclic group of prime power order and let V and W be orthogonal representations of G with V-G = W-G = W-G = {0}. Let S(V) be the sphere of V and suppose f: S(V) -> W is a G-equivariant mapping. We give an estimate for the dimension of the set f(-1){0} in terms of V and W. This extends the Bourgin-Yang version of the Borsuk-Ulam theorem to this class of groups. Using this estimate, we also estimate the size of the G-coincidences set of a continuous map from S(V) into a real vector space W'.

Biowaiver monographs for immediate-release solid oral dosage forms: Stavudine

Literature data relevant to the decision to allow a waiver of in vivo bioequivalence (BE) testing for the approval of immediate-release (IR) solid oral dosage forms containing stavudine (d4T) are reviewed. According to Biopharmaceutics Classification System (BCS), d4T can be assigned to BCS class I. No problems with BE of IR d4T formulations containing different excipients and produced by different manufacturing methods have been reported and, hence, the risk of bioinequivalence caused by these factors appears to be low. Furthermore, d4T has a wide therapeutic index. It is concluded that a biowaiver is appropriate for IR solid oral dosage forms containing d4T as the single active pharmaceutical ingredient (API) provided that (a) the test product contains only excipients present in the IR d4T drug products that have been approved in a number of countries for the same dosage form, and (b) both test product and its comparator are either very rapidly dissolving or rapidly dissolving with similarity of dissolution profiles demonstrated at pH 1.2, 4.5, and 6.8. (c) 2011 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:1016, 2012

ZETA DETERMINANT FOR DOUBLE SEQUENCES OF SPECTRAL TYPE

We study the spectral functions, and in particular the zeta function, associated to a class of sequences of complex numbers, called of spectral type. We investigate the decomposability of the zeta function associated to a double sequence with respect to some simple sequence, and we provide a technique for obtaining the first terms in the Laurent expansion at zero of the zeta function associated to a double sequence.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Bagging k-dependence probabilistic networks: An alternative powerful fraud detection tool

Fraud is a global problem that has required more attention due to an accentuated expansion of modern technology and communication. When statistical techniques are used to detect fraud, whether a fraud detection model is accurate enough in order to provide correct classification of the case as a fraudulent or legitimate is a critical factor. In this context, the concept of bootstrap aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the adjusted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper, for the first time, we aim to present a pioneer study of the performance of the discrete and continuous k-dependence probabilistic networks within the context of bagging predictors classification. Via a large simulation study and various real datasets, we discovered that the probabilistic networks are a strong modeling option with high predictive capacity and with a high increment using the bagging procedure when compared to traditional techniques. (C) 2012 Elsevier Ltd. All rights reserved.

Teaching of the Integrated Management of Childhood Illness strategy in undergraduate nursing programs

Objective: To describe and analyze the teaching of the Integrated Management of hildhood Illness (IMCI) strategy on Brazilian undergraduate nursing programs. Method: Integrating an international multicentric study, a cross-sectional online survey was conducted between May and October 2010 with 571 undergraduate nursing programs in Brazil Results: Responses were received from 142 programs, 75% private and 25% public. 64% of them included the IMCI strategy in the theoretical content, and 50% of the programs included IMCI as part of the students’ practical experience. The locations most used for practical teaching were primary health care units. The ‘treatment’ module was taught by the fewest number of programs, and few programs had access to the IMCI instructional manuals. All programs used exams for evaluation, and private institutions were more likely to include class participation as part of the evaluation. Teaching staff in public institutions were more likely to have received training in teaching IMCI. Conclusion: In spite of the relevance of the IMCI strategy in care of the child, its content is not addressed in all undergraduate programs in Brazil, and many programs do not have access to the IMCI teaching manuals and have not provide training in IMCI to their teaching staff.

Steel fiber reinforced concrete pipes: part 1: technological analysis of the mechanical behavior

This paper is the first part of an extensive work focusing the technological development of steel fiber reinforced concrete pipes (FRCP). Here is presented and discussed the experimental campaign focusing the test procedure and the mechanical behavior obtained for each of the dosages of fiber used. In the second part ("Steel fiber reinforced concrete pipes. Part 2: Numerical model to simulate the crushing test"), the aspects of FRCP numerical modeling are presented and analyzed using the same experimental results in order to be validated. This study was carried out trying to reduce some uncertainties related to FRCP performance and provide a better condition to the use of these components. In this respect, an experimental study was carried out using sewage concrete pipes in full scale as specimens. The diameter of the specimens was 600 mm, and they had a length of 2500 mm. The pipes were reinforced with traditional bars and different contents of steel fibers in order to compare their performance through the crushing test. Two test procedures were used in that sense. In the 1st Series, the diameter displacement was monitored by the use of two LVDTs positioned at both extremities of the pipes. In the 2nd Series, just one LVDT is positioned at the spigot. The results shown a more rigidity response of the pipe during tests when the displacements were measured at the enlarged section of the socket. The fiber reinforcement was very effective, especially when low level of displacement was imposed to the FRCP. At this condition, the steel fibers showed an equivalent performance to superior class pipes made with traditional reinforced. The fiber content of 40 kg/m3 provided a hardening behavior for the FRCP, and could be considered as equivalent to the critical volume in this condition.

Computational methods for the analysis of protein structure and function

The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.

Acqua: solvente elettivo in Organocatalisi e Biocatalisi

Water is a safe, harmless, and environmentally benign solvent. From an eco-sustainable chemistry perspective, the use of water instead of organic solvent is preferred to decrease environmental contamination. Moreover, water has unique physical and chemical properties, such as high dielectric constant and high cohesive energy density compared to most organic solvents. The different interactions between water and substrates, make water an interesting candidate as a solvent or co-solvent from an industrial and laboratory perspective. In this regard, organic reactions in aqueous media are of current interest. In addition, from practical and synthetic standpoints, a great advantage of using water is immediately evident, since it does not require any preliminary drying process. This thesis was found on this aspect of chemical research, with particular attention to the mechanisms which control organo and bio-catalysis outcome. The first part of the study was focused on the aldol reaction. In particular, for the first time it has been analyzed for the first time the stereoselectivity of the condensation reaction between 3-pyridincarbaldehyde and the cyclohexanone, catalyzed by morpholine and 4-tertbutyldimethylsiloxyproline, using water as sole solvent. This interest has resulted in countless works appeared in the literature concerning the use of proline derivatives as effective catalysts in organic aqueous environment. These studies showed good enantio and diastereoselectivities but they did not present an in depth study of the reaction mechanism. The analysis of the products diastereomeric ratios through the Eyring equation allowed to compare the activation parameters (ΔΔH≠ and ΔΔS≠) of the diastereomeric reaction paths, and to compare the different type of catalysis. While morpholine showed constant diasteromeric ratio at all temperatures, the O(TBS)-L-proline, showed a non-linear Eyring diagram, with two linear trends and the presence of an inversion temperature (Tinv) at 53 ° C, which denotes the presence of solvation effects by water. A pH-dependent study allowed to identify two different reaction mechanisms, and in the case of O(TBS)-L-proline, to ensure the formation of an enaminic species, as a keyelement in the stereoselective process. Moreover, it has been studied the possibility of using the 6- aminopenicillanic acid (6-APA) as amino acid-type catalyst for aldol condensation between cyclohexanone and aromatic aldehydes. A detailed analysis of the catalyst regarding its behavior in different organic solvents and pH, allowed to prove its potential as a candidate for green catalysis. Best results were obtained in neat conditions, where 6-APA proved to be an effective catalyst in terms of yields. The catalyst performance in terms of enantio- and diastereo-selectivity, was impaired by the competition between two different catalytic mechanisms: one via imine-enamine mechanism and one via a Bronsted-acid catalysis. The last part of the thesis was dedicated to the enzymatic catalysis, with particular attention to the use of an enzyme belonging to the class of alcohol dehydrogenase, the Horse Liver Alcohol Dehydrogenase (HLADH) which was selected and used in the enantioselective reduction of aldehydes to enantiopure arylpropylic alcohols. This enzyme has showed an excellent responsiveness to this type of aldehydes and a good tolerance toward organic solvents. Moreover, the fast keto-enolic equilibrium of this class of aldehydes that induce the stereocentre racemization, allows the dynamic-kinetic resolution (DKR) to give the enantiopure alcohol. By analyzing the different reaction parameters, especially the pH and the amount of enzyme, and adding a small percentage of organic solvent, it was possible to control all the parameters involved in the reaction. The excellent enatioselectivity of HLADH along with the DKR of arylpropionic aldehydes, allowed to obtain the corresponding alcohols in quantitative yields and with an optical purity ranging from 64% to >99%.