Substrate interaction with recombinant amidase from Pseudomonas aeruginosa during biocatalysis

The interaction of a variety of substrates with Pseudomonas aeruginosa native amidase (E.C. 3.5.1.4), overproduced in an Escherichia coli strain, was investigated using difference FTIR spectroscopy. The amides used as substrates showed an increase in hydrogen bonding upon association in multimers, which was not seen with esters. Evidence for an overall reduction or weakening of hydrogen bonding while amide and ester substrates are interacting with the enzyme is presented. The results describe a spectroscopic approach for analysis of substrate-amidase interaction and in situ monitoring of the hydrolysis and transferase reaction when amides or esters are used as substrates.

Developmental and evolutionary assumptions in a study about the impact of premature birth and low income on mother–infant interaction

In order to study the impact of premature birth and low income on mother–infant interaction, four Portuguese samples were gathered: full-term, middle-class (n=99); premature, middle-class (n=63); full-term, low income (n=22); and premature, low income (n=21). Infants were filmed in a free play situation with their mothers, and the results were scored using the CARE Index. By means of multinomial regression analysis, social economic status (SES) was found to be the best predictor of maternal sensitivity and infant cooperative behavior within a set of medical and social factors. Contrary to the expectations of the cumulative risk perspective, two factors of risk (premature birth together with low SES) were as negative for mother–infant interaction as low SES solely. In this study, as previous studies have shown, maternal sensitivity and infant cooperative behavior were highly correlated, as was maternal control with infant compliance. Our results further indicate that, when maternal lack of responsiveness is high, the infant displays passive behavior, whereas when the maternal lack of responsiveness is medium, the infant displays difficult behavior. Indeed, our findings suggest that, in these cases, the link between types of maternal and infant interactive behavior is more dependent on the degree of maternal lack of responsiveness than it is on birth status or SES. The results will be discussed under a developmental and evolutionary reasoning

Human interaction with technology for working, communicating, and learning: advancements

The way humans interact with technology is undergoing a tremendous change. It is hard to imagine the lives we live today without the benefits of technology that we take for granted. Applying research in computer science, engineering, and information systems to non-technical descriptions of technology, such as human interaction, has shaped and continues to shape our lives. Human Interaction with Technology for Working, Communicating, and Learning: Advancements provides a framework for conceptual, theoretical, and applied research in regards to the relationship between technology and humans. This book is unique in the sense that it does not only cover technology, but also science, research, and the relationship between these fields and individuals' experience. This book is a must have for anyone interested in this research area, as it provides a voice for all users and a look into our future.

Technology for creativity and innovation: tools, techniques and applications

It is widely accepted that organizations and individuals must be innovative and continually create new knowledge and ideas to deal with rapid change. Innovation plays an important role in not only the development of new business, process and products, but also in competitiveness and success of any organization. Technology for Creativity and Innovation: Tools, Techniques and Applications provides empirical research findings and best practices on creativity and innovation in business, organizational, and social environments. It is written for educators, academics and professionals who want to improve their understanding of creativity and innovation as well as the role technology has in shaping this discipline.

Sociological and philosophical aspects of human interaction with technology: advancing concepts

It is not possible to imagine our lives today without technology. From the moment we get up in the morning until the time that we go to bed at night, technology is present in almost every moment, even if we are not aware of it. Some of the most basic activities we need to perform regularly could not be carried out without technology. Sociological and Philosophical Aspects of Human Interaction with Technology: Advancing Concepts presents a careful blend of conceptual, theoretical and applied research in regards to the relationship between technology and humans. This book explores the importance of these interactions, aspects related with trust, communication, data protection, usability concerning organizational change, and e-learning. The advancement of these theories and practices will benefit from this publication as it provides a voice for the users.

Risk of drug interaction: combination of antidepressants and other drugs

OBJECTIVE: To assess the frequency of combination of antidepressants with other drugs and risk of drug interactions in the setting public hospital units in Brazil. METHODS: Prescriptions of all patients admitted to a public hospital from November 1996 to February 1997 were surveyed from the hospital's data processing center in São Paulo, Brazil. A manual search of case notes of all patients admitted to the psychiatric unit from January 1993 to December 1995 and all patients registered in the affective disorders outpatient clinic in December 1996 was carried out. Patients taking any antidepressant were identified and concomitant use of drugs was checked. By means of a software program (Micromedex®) drug interactions were identified. RESULTS: Out of 6,844 patients admitted to the hospital, 63 (0.9%) used antidepressants and 16 (25.3%) were at risk of drug interaction. Out of 311 patients in the psychiatric unit, 63 (20.2%) used antidepressants and 13 of them (20.6%) were at risk. Out of 87 patients in the affective disorders outpatient clinic, 43 (49.4%) took antidepressants and 7 (16.2%) were at risk. In general, the use of antidepressants was recorded in 169 patients and 36 (21.3%) were at risk of drug interactions. Twenty different forms of combinations at risk of drug interactions were identified: four were classified as mild, 15 moderate and one severe interaction. CONCLUSION: In the hospital general units the number of drug interactions per patient was higher than in the psychiatric unit; and prescription for depression was lower than expected.

Intergenerational interaction in health promotion: a qualitative study in Brazil

OBJECTIVE: In 1994 a pilot intergenerational project was started in the city of Taguatinga, Brazil, to promote the well-being of both elderly and adolescent populations using reminiscence processes as a means of interaction. The purpose of the study is to evaluate the project from the participants' viewpoint and to improve the contribution of those age groups in building up social capital. METHODS: From November 1999 to April 2000 a qualitative study using focus groups technique was conducted. Using a discussion guide, 9 groups of students, ranging in age from 13 to 19 years old, and 3 groups of elderly aged 60 years and over were interviewed to collect data regarding their interaction before and after an intergenerational program. RESULTS: The main findings suggested a change in attitude of young people toward old age and elderly people. Participating elderly people reported improvement in their health status. For both age groups the findings suggested a better understanding between generations. CONCLUSIONS: It seems that reminiscence intergenerational activity contributes to building up mutual trust and reciprocity. These results seem to indicate this is an alternative for investing in social capital and improving participants' well-being. However, further work is needed to support these findings.

DNA interaction and cytotoxicity studies of new ruthenium(II) cyclopentadienyl derivative complexescontaining heteroaromatic ligands

Four ruthenium(II) complexes with the formula [Ru(eta(5)-C(5)H(5))(PP)L][CF(3)SO(3)], being (PP = two triphenylphosphine molecules), L = 1-benzylimidazole, 1; (PP = two triphenylphosphine molecules), L = 2,2'bipyridine, 2; (PP = two triphenylphosphine molecules), L = 4-Methylpyridine, 3; (PP = 1,2-bis(diphenylphosphine) ethane), L = 4-Methylpyridine, 4, were prepared, in view to evaluate their potentialities as antitumor agents. The compounds were completely characterized by NMR spectroscopy and their crystal and molecular structures were determined by X-ray diffraction. Electrochemical studies were carried out giving for all the compounds quasi-reversible processes. The images obtained by atomic force microscopy (AFM) suggest interaction with pBR322 plasmid DNA. Measurements of the viscosity of solutions of free DNA and DNA incubated with different concentrations of the compounds confirmed this interaction. The cytotoxicity of compounds 1234 was much higher than that of cisplatin against human leukemia cancer cells (HL-60 cells). IC(50) values for all the compounds are in the range of submicromolar amounts. Apoptotic death percentage was also studied resulting similar than that of cisplatin. (C) 2010 Elsevier Inc. All rights reserved.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Data mining techniques contributions to support electrical vehicle demand response

The introduction of Electric Vehicles (EVs) together with the implementation of smart grids will raise new challenges to power system operators. This paper proposes a demand response program for electric vehicle users which provides the network operator with another useful resource that consists in reducing vehicles charging necessities. This demand response program enables vehicle users to get some profit by agreeing to reduce their travel necessities and minimum battery level requirements on a given period. To support network operator actions, the amount of demand response usage can be estimated using data mining techniques applied to a database containing a large set of operation scenarios. The paper includes a case study based on simulated operation scenarios that consider different operation conditions, e.g. available renewable generation, and considering a diversity of distributed resources and electric vehicles with vehicle-to-grid capacity and demand response capacity in a 33 bus distribution network.

Identification of tsunami-induced deposits using numerical modeling and rock magnetism techniques: Astudy case of the 1755 Lisbon tsunami in Algarve, Portugal (vol 182, pg 187, 2010)

Storm- and tsunami-deposits are generated by similar depositional mechanisms making their discrimination hard to establish using classic sedimentologic methods. Here we propose an original approach to identify tsunami-induced deposits by combining numerical simulation and rock magnetism. To test our method, we investigate the tsunami deposit of the Boca do Rio estuary generated by the 1755 earthquake in Lisbon which is well described in the literature. We first test the 1755 tsunami scenario using a numerical inundation model to provide physical parameters for the tsunami wave. Then we use concentration (MS. SIRM) and grain size (chi(ARM), ARM, B1/2, ARM/SIRM) sensitive magnetic proxies coupled with SEM microscopy to unravel the magnetic mineralogy of the tsunami-induced deposit and its associated depositional mechanisms. In order to study the connection between the tsunami deposit and the different sedimentologic units present in the estuary, magnetic data were processed by multivariate statistical analyses. Our numerical simulation show a large inundation of the estuary with flow depths varying from 0.5 to 6 m and run up of similar to 7 m. Magnetic data show a dominance of paramagnetic minerals (quartz) mixed with lesser amount of ferromagnetic minerals, namely titanomagnetite and titanohematite both of a detrital origin and reworked from the underlying units. Multivariate statistical analyses indicate a better connection between the tsunami-induced deposit and a mixture of Units C and D. All these results point to a scenario where the energy released by the tsunami wave was strong enough to overtop and erode important amount of sand from the littoral dune and mixed it with reworked materials from underlying layers at least 1 m in depth. The method tested here represents an original and promising tool to identify tsunami-induced deposits in similar embayed beach environments.

Synthesis, Antimicrobial and Antiproliferative Activity of Novel Silver(I) Tris(pyrazolyl)methanesulfonateand 1,3,5-Triaza-7-phosphadamantane Complexes

Five new silver(I) complexes of formulas [Ag(Tpms)] (1), [Ag(Tpms)-(PPh3)] (2), [Ag(Tpms)(PCy3)] (3), [Ag(PTA)][BF4] (4), and [Ag(Tpms)(PTA)] (5) {Tpms = tris(pyrazol-1-yl)methanesulfonate, PPh3 = triphenylphosphane, PCy3 = tricyclohexylphosphane, PTA = 1,3,5-triaza-7-phosphaadamantane) have been synthesized and fully characterized by elemental analyses, H-1, C-13, and P-31 NMR, electrospray ionization mass spectrometry (ESI-MS), and IR spectroscopic techniques. The single crystal X-ray diffraction study of 3 shows the Tpms ligand acting in the N-3-facially coordinating mode, while in 2 and 5 a N2O-coordination is found, with the SO3 group bonded to silver and a pendant free pyrazolyl ring. Features of the tilting in the coordinated pyrazolyl rings in these cases suggest that this inequivalence is related with the cone angles of the phosphanes. A detailed study of antimycobacterial and antiproliferative properties of all compounds has been carried out. They were screened for their in vitro antimicrobial activities against the standard strains Enterococcus faecalis (ATCC 29922), Staphylococcus aureus (ATCC 25923), Streptococcus pneumoniae (ATCC 49619), Streptococcus pyogenes (SF37), Streptococcus sanguinis (SK36), Streptococcus mutans (UA1S9), Escherichia coli (ATCC 25922), and the fungus Candida albicans (ATCC 24443). Complexes 1-5 have been found to display effective antimicrobial activity against the series of bacteria and fungi, and some of them are potential candidates for antiseptic or disinfectant drugs. Interaction of Ag complexes with deoxyribonucleic acid (DNA) has been studied by fluorescence spectroscopic techniques, using ethidium bromide (EB) as a fluorescence probe of DNA. The decrease in the fluorescence of DNA EB system on addition of Ag complexes shows that the fluorescence quenching of DNA EB complex occurs and compound 3 is particularly active. Complexes 1-5 exhibit pronounced antiproliferative activity against human malignant melanoma (A375) with an activity often higher than that of AgNO3, which has been used as a control, following the same order of activity inhibition on DNA, i.e., 3 > 2 > 1 > 5 > AgNO3 >> 4.

Data mining techniques to support the classification of MV electricity customers

This paper describes a methodology that was developed for the classification of Medium Voltage (MV) electricity customers. Starting from a sample of data bases, resulting from a monitoring campaign, Data Mining (DM) techniques are used in order to discover a set of a MV consumer typical load profile and, therefore, to extract knowledge regarding to the electric energy consumption patterns. In first stage, it was applied several hierarchical clustering algorithms and compared the clustering performance among them using adequacy measures. In second stage, a classification model was developed in order to allow classifying new consumers in one of the obtained clusters that had resulted from the previously process. Finally, the interpretation of the discovered knowledge are presented and discussed.

Natural gas system operation: lagrangean optimization techniques

To comply with natural gas demand growth patterns and Europe´s import dependency, the gas industry needs to organize an efficient upstream infrastructure. The best location of Gas Supply Units – GSUs and the alternative transportation mode – by phisical or virtual pipelines, are the key of a successful industry. In this work we study the optimal location of GSUs, as well as determining the most efficient allocation from gas loads to sources, selecting the best transportation mode, observing specific technical restrictions and minimizing system total costs. For the location of GSUs on system we use the P-median problem, for assigning gas demands nodes to source facilities we use the classical transportation problem. The developed model is an optimisation-based approach, based on a Lagrangean heuristic, using Lagrangean relaxation for P-median problems – Simple Lagrangean Heuristic. The solution of this heuristic can be improved by adding a local search procedure - the Lagrangean Reallocation Heuristic. These two heuristics, Simple Lagrangean and Lagrangean Reallocation, were tested on a realistic network - the primary Iberian natural gas network, organized with 65 nodes, connected by physical and virtual pipelines. Computational results are presented for both approaches, showing the location gas sources and allocation loads arrangement, system total costs and gas transportation mode.

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.