Use of Yucca schidigera extract in broiler diets and its effects on performance results obtained with different coccidiosis control methods

A trial was conducted to assess the effects of the dietary supplement Yucca schidigera extract on the performance of broilers subjected to different coccidiosis control methods. Six hundred male broiler chicks were randomly allocated to 1 of 5 treatments with 4 replicates each. The treatments were as follows: T1, vaccinated against coccidiosis; T2, nonvaccinated, a dietary coccidiostat; T3, vaccinated against coccidiosis, diet supplemented with Y. schidigera extract (0.01%); T4, coccidiostat plus Y. schidigera extract added to feed (0.01%); and T5, nonvaccinated, nonsupplemented control. The parameters analyzed were bird performance and morphology of the intestinal mucosal surface. The intestinal villi were higher at 6 d of age in broilers treated with coccidiostats or vaccinated against coccidiosis and supplemented with Y. schidigera extract compared with groups receiving the vaccine only or no treatment. Addition of the Y. schidigera extract to the diet of vaccinated birds improved average daily gain and feed conversion rate at 42 d of age compared with the other treatments, suggesting there might be a beneficial, synergistic effect between the coccidiosis vaccine and the Y. schidigera extract.

Combining artificial intelligence and human problem solving: Proposing a new architecture for ITS's

This paper shows a comparative study between the Artificial Intelligence Problem Solving and the Human Problem Solving. The study is based on the solution by many ways of problems proposed via multiple-choice questions. General techniques used by humans to solve this kind of problems are grouped in blocks and each block is divided in steps. A new architecture for ITS - Intelligent Tutoring System is proposed to support experts' knowledge representation and novices' activities. Problems are represented by a text and feasible answers with particular meaning and form, to be rigorously analyzed by the solver to find the right one. Paths through a conceptual space of states represent each right solution.

Chemical composition of corn and sorghum grains cultivated in oxisol with different application methods and doses of zinc

A.P. Puga, R.M. Prado, B. Mattiuz, D.W. Vale, and I.M. Fonseca. 2013. Chemical composition of corn and sorghum grains cultivated in Oxisol according to different application methods and doses of zinc. Cien. Inv. Agr. 40(1):97-108. In general, tropical soils present low concentrations of zinc (Zn), and the deficiency of Zn is recognized as a world nutritional problem for cereal production and human beings. Therefore, the main goal of this study was to assess the effects of different methods of Zn application on the quality of corn and sorghum grains grown in Oxisol. Two experiments were set up in the experimental area of UNESP (campus of Jaboticabal, Brazil). The following nine treatments were applied: three doses of Zn by banded application (seed furrows), three doses of Zn by incorporation into soil (0-20 cm depth), foliar application, seed application, and control (no Zn applied). The treatments were arranged in randomized blocks with four replicates. The contents of Zn, carbohydrates and proteins were determined for corn and sorghum grains. Regardless of the method, Zn application promoted higher contents of this micronutrient in corn and sorghum grains. The banded application method of Zn in soil promoted greater contents of total carbohydrates, starch and protein in both cultures. The incorporation of Zn into the soil method provided higher contents of soluble carbohydrates in both corn and sorghum grains.

Development of diagnostic methods and study of the immunoreactivity of a mixture of recombinant core and E2 proteins fused to GST with control serum positive for hepatitis C

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

Methods and results of a search for gravitational waves associated with gamma-ray bursts using the GEO 600, LIGO, and Virgo detectors

In this paper we report on a search for short-duration gravitational wave bursts in the frequency range 64 Hz-1792 Hz associated with gamma-ray bursts (GRBs), using data from GEO 600 and one of the LIGO or Virgo detectors. We introduce the method of a linear search grid to analyze GRB events with large sky localization uncertainties, for example the localizations provided by the Fermi Gamma-ray Burst Monitor (GBM). Coherent searches for gravitational waves (GWs) can be computationally intensive when the GRB sky position is not well localized, due to the corrections required for the difference in arrival time between detectors. Using a linear search grid we are able to reduce the computational cost of the analysis by a factor of O(10) for GBM events. Furthermore, we demonstrate that our analysis pipeline can improve upon the sky localization of GRBs detected by the GBM, if a high-frequency GW signal is observed in coincidence. We use the method of the linear grid in a search for GWs associated with 129 GRBs observed satellite-based gamma-ray experiments between 2006 and 2011. The GRBs in our sample had not been previously analyzed for GW counterparts. A fraction of our GRB events are analyzed using data from GEO 600 while the detector was using squeezed-light states to improve its sensitivity; this is the first search for GWs using data from a squeezed-light interferometric observatory. We find no evidence for GW signals, either with any individual GRB in this sample or with the population as a whole. For each GRB we place lower bounds on the distance to the progenitor, under an assumption of a fixed GW emission energy of 10(-2)M circle dot c(2), with a median exclusion distance of 0.8 Mpc for emission at 500 Hz and 0.3 Mpc at 1 kHz. The reduced computational cost associated with a linear search grid will enable rapid searches for GWs associated with Fermi GBM events once the advanced LIGO and Virgo detectors begin operation.

Cogeneration design problem Computational complexity analysis and solution through an expert system

Purpose - The purpose of this paper is twofold: to analyze the computational complexity of the cogeneration design problem; to present an expert system to solve the proposed problem, comparing such an approach with the traditional searching methods available.Design/methodology/approach - The complexity of the cogeneration problem is analyzed through the transformation of the well-known knapsack problem. Both problems are formulated as decision problems and it is proven that the cogeneration problem is np-complete. Thus, several searching approaches, such as population heuristics and dynamic programming, could be used to solve the problem. Alternatively, a knowledge-based approach is proposed by presenting an expert system and its knowledge representation scheme.Findings - The expert system is executed considering two case-studies. First, a cogeneration plant should meet power, steam, chilled water and hot water demands. The expert system presented two different solutions based on high complexity thermodynamic cycles. In the second case-study the plant should meet just power and steam demands. The system presents three different solutions, and one of them was never considered before by our consultant expert.Originality/value - The expert system approach is not a "blind" method, i.e. it generates solutions based on actual engineering knowledge instead of the searching strategies from traditional methods. It means that the system is able to explain its choices, making available the design rationale for each solution. This is the main advantage of the expert system approach over the traditional search methods. On the other hand, the expert system quite likely does not provide an actual optimal solution. All it can provide is one or more acceptable solutions.

Strategies and Precise Vocabulary Knowledge: Exploring the Relationships Among Mathematics Vocabulary, Problem Solving, and Confidence

In this action research study I focused on my eighth grade pre-algebra students’ abilities to attack problems with enthusiasm and self confidence whether they completely understand the concepts or not. I wanted to teach them specific strategies and introduce and use precise vocabulary as a part of the problem solving process in hopes that I would see students’ confidence improve as they worked with mathematics. I used non-routine problems and concept-related open-ended problems to teach and model problem solving strategies. I introduced and practiced communication with specific and precise vocabulary with the goal of increasing student confidence and lowering student anxiety when they were faced with mathematics problem solving. I discovered that although students were working more willingly on problem solving and more inclined to attempt word problems using the strategies introduced in class, they were still reluctant to use specific vocabulary as they communicated to solve problems. As a result of this research, my style of teaching problem solving will evolve so that I focus more specifically on strategies and use precise vocabulary. I will spend more time introducing strategies and necessary vocabulary at the beginning of the year and continue to focus on strategies and process in order to lower my students’ anxiety and thus increase their self confidence when it comes to doing mathematics, especially problem solving.

Improving Students’ Story Problem Solving Abilities

In this action research study of my classroom of 8th grade mathematics students, I investigated if learning different problem solving strategies helped students successfully solve problems. I also investigated if students’ knowledge of the topics involved in story problems had an impact on students’ success rates. I discovered that students were more successful after learning different problem solving strategies and when given problems with which they have experience. I also discovered that students put forth a greater effort when they approach the story problem like a game, instead of just being another math problem that they have to solve. An unexpected result was that the students’ degree of effort had a major impact on their success rate. As a result of this research, I plan to continue to focus on problem solving strategies in my classes. I also plan to improve my methods on getting students’ full effort in class.

The impact of the medical speciality in primary health-care problem solving in Belo Horizonte, Brazil: homeopaths versus family doctors: a preliminary quantitative study

Introduction: This research project examined influence of the doctors' speciality on primary health care (PHC) problem solving in Belo Horizonte (BH) Brazil, comparing homeopathic with family health doctors (FH), from the management's and the patients' viewpoint. In BH, both FH and homeopathic doctors work in PHC. The index of resolvability (IR) is used to compare resolution of problems by doctors. Methods: The present research compared IR, using official data from the Secretariat of Health and test requests made by the doctors and 482 structured interviews with patients. A total of 217,963 consultations by 14 homeopaths and 67 FH doctors between 1 July 2006 and 30 June 2007 were analysed. Results: The results show significant differences greater problem resolution by homeopaths compared to FH doctors. Conclusion: In BH, the medical speciality, homeopathy or FH, has an impact on problem solving, both from the managers' and the patients' point of view. Homeopaths request fewer tests and have better IR compared with FH doctors. Specialisation in homeopathy is an independent positive factor in problem solving at PHC level in BH, Brazil. Homeopathy (2012) 101, 44-50.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

Biofilms on exposed monumental stones: mechanism of formation and development of new control methods

Within the stone monumental artefacts artistic fountains are extremely favorable to formation of biofilms, giving rise to biodegradation processes related with physical-chemical and visual aspect alterations, because of their particular exposure conditions. Microbial diversity of five fountains (two from Spain and three from Italy) was investigated. It was observed an ample similarity between the biodiversity of monumental stones reported in literature and that one found in studied fountains. Mechanical procedures and toxic chemical products are usually employed to remove such phototrophic patinas. Alternative methods based on natural antifouling substances are recently experimented in the marine sector, due to their very low environmental impact and for the bio settlement prevention on partially immersed structures of ships. In the present work groups of antibiofouling agents (ABAs) were selected from literature for their ability to interfere, at molecular level, with the microbial communication system “quorum sensing”, inhibiting the initial phase of biofilm formation. The efficacy of some natural antibiofoulants agents (ABAs) with terrestrial (Capsaicine - CS, Cinnamaldehyde - CI) and marine origin (Zosteric Acid - ZA, poly-Alkyl Pyridinium Salts – pAPS and Ceramium botryocarpum extract - CBE), incorporated into two commercial coatings (Silres BS OH 100 - S and Wacker Silres BS 290 - W) commonly used in stone conservation procedures were evaluated. The formation of phototrophic biofilms in laboratory conditions (on Carrara marble specimens and Sierra Elvira stone) and on two monumental fountains (Tacca’s Fountain 2 - Florence, Italy and Fountain from Patio de la Lindaraja - Alhambra Palace, Granada, Spain) has been investigated in the presence or absence of these natural antifouling agents. The natural antibiofouling agents, at tested concentrations, demonstrated a certain inhibitory effect. The silane-siloxane based silicone coating (W) mixing with ABAs was more suitable with respect to ethyl silicate coating (S) and proved efficacy against biofilm formation only when incompletely cured. The laboratory results indicated a positive action in inhibiting the patina formation, especially for poly-alkyl pyridinium salts, zosteric acid and cinnamaldehyde, while on site tests revealed a good effect for zosteric acid.

Decomposition Methods and Network Design Problems

Decomposition based approaches are recalled from primal and dual point of view. The possibility of building partially disaggregated reduced master problems is investigated. This extends the idea of aggregated-versus-disaggregated formulation to a gradual choice of alternative level of aggregation. Partial aggregation is applied to the linear multicommodity minimum cost flow problem. The possibility of having only partially aggregated bundles opens a wide range of alternatives with different trade-offs between the number of iterations and the required computation for solving it. This trade-off is explored for several sets of instances and the results are compared with the ones obtained by directly solving the natural node-arc formulation. An iterative solution process to the route assignment problem is proposed, based on the well-known Frank Wolfe algorithm. In order to provide a first feasible solution to the Frank Wolfe algorithm, a linear multicommodity min-cost flow problem is solved to optimality by using the decomposition techniques mentioned above. Solutions of this problem are useful for network orientation and design, especially in relation with public transportation systems as the Personal Rapid Transit. A single-commodity robust network design problem is addressed. In this, an undirected graph with edge costs is given together with a discrete set of balance matrices, representing different supply/demand scenarios. The goal is to determine the minimum cost installation of capacities on the edges such that the flow exchange is feasible for every scenario. A set of new instances that are computationally hard for the natural flow formulation are solved by means of a new heuristic algorithm. Finally, an efficient decomposition-based heuristic approach for a large scale stochastic unit commitment problem is presented. The addressed real-world stochastic problem employs at its core a deterministic unit commitment planning model developed by the California Independent System Operator (ISO).

Haemostatic effect and tissue reactions of methods and agents used for haemorrhage control in apical surgery

To compare the haemostatic effect and tissue reactions of different agents and methods used for haemorrhage control in apical surgery.

What do case-control studies estimate? Survey of methods and assumptions in published case-control research

To evaluate strategies used to select cases and controls and how reported odds ratios are interpreted, the authors examined 150 case-control studies published in leading general medicine, epidemiology, and clinical specialist journals from 2001 to 2007. Most of the studies (125/150; 83%) were based on incident cases; among these, the source population was mostly dynamic (102/125; 82%). A minority (23/125; 18%) sampled from a fixed cohort. Among studies with incident cases, 105 (84%) could interpret the odds ratio as a rate ratio. Fifty-seven (46% of 125) required the source population to be stable for such interpretation, while the remaining 48 (38% of 125) did not need any assumptions because of matching on time or concurrent sampling. Another 17 (14% of 125) studies with incident cases could interpret the odds ratio as a risk ratio, with 16 of them requiring the rare disease assumption for this interpretation. The rare disease assumption was discussed in 4 studies but was not relevant to any of them. No investigators mentioned the need for a stable population. The authors conclude that in current case-control research, a stable exposure distribution is much more frequently needed to interpret odds ratios than the rare disease assumption. At present, investigators conducting case-control studies rarely discuss what their odds ratios estimate.

Exigencies for engaging undergraduates in rhetorical problem solving : insights from engineering managers and A3 report analyses

Undergraduate education has a historical tradition of preparing students to meet the problem-solving challenges they will encounter in work, civic, and personal contexts. This thesis research was conducted to study the role of rhetoric in engineering problem solving and decision making and to pose pedagogical strategies for preparing undergraduate students for workplace problem solving. Exploratory interviews with engineering managers as well as the heuristic analyses of engineering A3 project planning reports suggest that Aristotelian rhetorical principles are critical to the engineer's success: Engineers must ascertain the rhetorical situation surrounding engineering problems; apply and adapt invention heuristics to conduct inquiry; draw from their investigation to find innovative solutions; and influence decision making by navigating workplace decision-making systems and audiences using rhetorically constructed discourse. To prepare undergraduates for workplace problem solving, university educators are challenged to help undergraduates understand the exigence and realize the kairotic potential inherent in rhetorical problem solving. This thesis offers pedagogical strategies that focus on mentoring learning communities in problem-posing experiences that are situated in many disciplinary, work, and civic contexts. Undergraduates build a flexible rhetorical technê for problem solving as they navigate the nuances of relevant problem-solving systems through the lens of rhetorical practice.