Topliss method in the optimization of salicylic acid derivatives as potential antimycobacterial agents

The Topliss method was used to guide a synthetic path in support of drug discovery efforts toward the identification of potent antimycobacterial agents. Salicylic acid and its derivatives, p-chloro, p-methoxy, and m-chlorosalicylic acid, exemplify a series of synthetic compounds whose minimum inhibitory concentrations for a strain of Mycobacterium were determined and compared to those of the reference drug, p-aminosalicylic acid. Several physicochemical descriptors (including Hammett`s sigma constant, ionization constant, dipole moment, Hansch constant, calculated partition coefficient, Sterimol-L and -B-4 and molecular volume) were considered to elucidate structure-activity relationships. Molecular electrostatic potential and molecular dipole moment maps were also calculated using the AM1 semi-empirical method. Among the new derivatives, m-chlorosalicylic acid showed the lowest minimum inhibitory concentration. The overall results suggest that both physicochemical properties and electronic features may influence the biological activity of this series of antimycobacterial agents and thus should be considered in designing new p-aminosalicylic acid analogs.

A fast cross-entropy method for estimating buffer overflows in queuing networks

In this paper, we propose a fast adaptive importance sampling method for the efficient simulation of buffer overflow probabilities in queueing networks. The method comprises three stages. First, we estimate the minimum cross-entropy tilting parameter for a small buffer level; next, we use this as a starting value for the estimation of the optimal tilting parameter for the actual (large) buffer level. Finally, the tilting parameter just found is used to estimate the overflow probability of interest. We study various properties of the method in more detail for the M/M/1 queue and conjecture that similar properties also hold for quite general queueing networks. Numerical results support this conjecture and demonstrate the high efficiency of the proposed algorithm.

Novel silica gel supported TiO2 photocatalyst synthesized by CVD method

TiO2 in anatase crystal phase is a very effective catalyst in the photocatalytic oxidation of organic compounds in water. To improve the recovery rate of TiO2 photocatalysts, which in most cases are in fine powder form, the chemical vapor deposition (CVD) method was used to load TiO2 onto a bigger particle support, silica gel. The amount of titania coating was found to depend strongly on the synthesis parameters of carrier gas flow rate and coating time. XPS and nitrogen ads/desorption results showed that most of the TiO2 particles generated from CVD were distributed on the external surface of the support and the coating was stable. The photocatalytic activities of TiO2/silica gel with different amounts of titania were evaluated for the oxidation of phenol aqueous solution and compared with that of Degussa P25. The optimum titania loading rate was found around 6 wt % of the TiO2 bulk concentration. Although the activity of the best TiO2/silica gel sample was still lower than that of P25, the synthesized TiO2/silica gel catalyst can be easily separated from the treated water and was found to maintain its TiO2 content and catalytic activity.

A method for setting the size of plant conservation target areas

Realistic time frames in which management decisions are made often preclude the completion of the detailed analyses necessary for conservation planning. Under these circumstances, efficient alternatives may assist in approximating the results of more thorough studies that require extensive resources and time. We outline a set of concepts and formulas that may be used in lieu of detailed population viability analyses and habitat modeling exercises to estimate the protected areas required to provide desirable conservation outcomes for a suite of threatened plant species. We used expert judgment of parameters and assessment of a population size that results in a specified quasiextinction risk based on simple dynamic models The area required to support a population of this size is adjusted to take into account deterministic and stochastic human influences, including small-scale disturbance deterministic trends such as habitat loss, and changes in population density through processes such as predation and competition. We set targets for different disturbance regimes and geographic regions. We applied our methods to Banksia cuneata, Boronia keysii, and Parsonsia dorrigoensis, resulting in target areas for conservation of 1102, 733, and 1084 ha, respectively. These results provide guidance on target areas and priorities for conservation strategies.

Validity and reliability of a computer method to estimate vertebral axial rotation from digital radiographs

Axial vertebral rotation, an important parameter in the assessment of scoliosis may be identified on X-ray images. In line with the advances in the field of digital radiography, hospitals have been increasingly using this technique. The objective of the present study was to evaluate the reliability of computer-processed rotation measurements obtained from digital radiographs. A software program was therefore developed, which is able to digitally reproduce the methods of Perdriolle and Raimondi and to calculate semi-automatically the rotation degree of vertebra on digital radiographs. Three independent observers estimated vertebral rotation employing both the digital and the traditional manual methods. Compared to the traditional method, the digital assessment showed a 43% smaller error and a stronger correlation. In conclusion, the digital method seems to be reliable and enhance the accuracy and precision of vertebral rotation measurements.

Effect of the C-factor and Dentin Preparation Method in the Bond Strength of a Mild Self-etch Adhesive

This study evaluated the effect of the C-factor and dentin preparation method (DPM) in the bond strength (BS) of a mild self-etch adhesive; the study also observed the SEM superficial aspects of the corresponding smear layer. For purposes of this study, 25 molars (n=5) were used in a bond strength test. The molars were divided into two parts (buccal and lingual): one part received a Class V cavity (C-factor=3) and the other received a flat surface (C-factor=0) with the same bur type (coarse diamond or carbide bur and fine diamond or carbide bur), both within the same dentin depth. Five teeth were prepared with wet 60-grit and 600-grit SiC papers. After restoration with Clearfil SE Bond, microtensile beans (0.8 mm(2)) were prepared and tested after 24 hours in a universal testing machine (0.5 mm/minute). An additional two teeth for each DPM were prepared for SEM evaluation of the smear layer superficial aspects. The BS values were submitted to one-way ANOVA, considering only the DPM (flat surfaces) and two-way ANOVA (C-Factor x DPM, considering only burs) with p=0.05. Although the DPM in the flat surfaces was not significant, the standard deviations of carbide bur-prepared specimens were markedly lower. The BS was significantly lower in cavities. The fine carbide bur presented the most favorable smear layer aspect. It was concluded that different dentin preparation methods could not prevent the adverse effect in bond strength of a high C-factor. A coarse cut carbide bur should be avoided prior to a mild self-etch adhesive, because it adversely affected bond strength. In contrast, a fine cut carbide bur provided the best combination: high bond strength with low variability, which suggests a more reliable bond strength performance.

Marx as a Critical Discourse Analyst: The genesis of a critical method and its relevance to the critique of global capital

In this paper we identify elements in Marx´s economic and political writings that are relevant to contemporary critical discourse analysis (CDA). We argue that Marx can be seen to be e n gaging in a form of discourse analysis. We identify the elements in Marx´s historical materialist method that support such a perspective, and exemplify these in a longitudinal comparison of Marx´s texts.

Assessing clinical reasoning: a method to monitor its development in a PBL curriculum

The aim of this study was to develop and trial a method to monitor the evolution of clinical reasoning in a PBL curriculum that is suitable for use in a large medical school. Termed Clinical Reasoning Problems (CRPs), it is based on the notion that clinical reasoning is dependent on the identification and correct interpretation of certain critical clinical features. Each problem consists of a clinical scenario comprising presentation, history and physical examination. Based on this information, subjects are asked to nominate the two most likely diagnoses and to list the clinical features that they considered in formulating their diagnoses, indicating whether these features supported or opposed the nominated diagnoses. Students at different levels of medical training completed a set of 10 CRPs as well as the Diagnostic Thinking Inventory, a self-reporting questionnaire designed to assess reasoning style. Responses were scored against those of a reference group of general practitioners. Results indicate that the CRPs are an easily administered, reliable and valid assessment of clinical reasoning, able to successfully monitor its development throughout medical training. Consequently, they can be employed to assess clinical reasoning skill in individual students and to evaluate the success of undergraduate medical schools in providing effective tuition in clinical reasoning.

Tool support for testing concurrent Java components

Concurrent programs are hard to test due to the inherent nondeterminism. This paper presents a method and tool support for testing concurrent Java components. Too[ support is offered through ConAn (Concurrency Analyser), a too] for generating drivers for unit testing Java classes that are used in a multithreaded context. To obtain adequate controllability over the interactions between Java threads, the generated driver contains threads that are synchronized by a clock. The driver automatically executes the calls in the test sequence in the prescribed order and compares the outputs against the expected outputs specified in the test sequence. The method and tool are illustrated in detail on an asymmetric producer-consumer monitor. Their application to testing over 20 concurrent components, a number of which are sourced from industry and were found to contain faults, is presented and discussed.

Using data mining techniques to support DR programs definition in smart grids

In recent years, Power Systems (PS) have experimented many changes in their operation. The introduction of new players managing Distributed Generation (DG) units, and the existence of new Demand Response (DR) programs make the control of the system a more complex problem and allow a more flexible management. An intelligent resource management in the context of smart grids is of huge important so that smart grids functions are assured. This paper proposes a new methodology to support system operators and/or Virtual Power Players (VPPs) to determine effective and efficient DR programs that can be put into practice. This method is based on the use of data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 32 bus distribution network.

Interlaboratory validation of an environmental monitoring method for trace analysis of endocrine disrupting compounds

Environmental pollution continues to be an emerging study field, as there are thousands of anthropogenic compounds mixed in the environment whose possible mechanisms of toxicity and physiological outcomes are of great concern. Developing methods to access and prioritize the screening of these compounds at trace levels in order to support regulatory efforts is, therefore, very important. A methodology based on solid phase extraction followed by derivatization and gas chromatography-mass spectrometry analysis was developed for the assessment of four endocrine disrupting compounds (EDCs) in water matrices: bisphenol A, estrone, 17b-estradiol and 17a-ethinylestradiol. The study was performed, simultaneously, by two different laboratories in order to evaluate the robustness of the method and to increase the quality control over its application in routine analysis. Validation was done according to the International Conference on Harmonisation recommendations and other international guidelines with specifications for the GC-MS methodology. Matrix-induced chromatographic response enhancement was avoided by using matrix-standard calibration solutions and heteroscedasticity has been overtaken by a weighted least squares linear regression model application. Consistent evaluation of key analytical parameters such as extraction efficiency, sensitivity, specificity, linearity, limits of detection and quantification, precision, accuracy and robustness was done in accordance with standards established for acceptance. Finally, the application of the optimized method in the assessment of the selected analytes in environmental samples suggested that it is an expedite methodology for routine analysis of EDC residues in water matrices.

Desenvolvimento do método de Índice de Qualidade ("QIM-Quality Index Method") para as lapas (Patella candei e Patella aspera) e estudo das suas condições de transporte

Dissertação de Mestrado, Estudos Integrados dos Oceanos, 15 de Março de 2016, Universidade dos Açores.

A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method

This paper presents a methodology for applying scheduling algorithms using Monte Carlo simulation. The methodology is based on a decision support system (DSS). The proposed methodology combines a genetic algorithm with a new local search using Monte Carlo Method. The methodology is applied to the job shop scheduling problem (JSSP). The JSSP is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. The methodology is tested on a set of standard instances taken from the literature and compared with others. The computation results validate the effectiveness of the proposed methodology. The DSS developed can be utilized in a common industrial or construction environment.

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Toroid inductor development for a SIC DC-DC converter up to 150kW, based on finite element method

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia