β-Lactams: chemical structure, mode of action and mechanisms of resistance

This synopsis summarizes the key chemical and bacteriological characteristics of β-lactams, penicillins, cephalosporins, carbanpenems, monobactams and others. Particular notice is given to first-generation to fifth-generation cephalosporins. This reviewalso summarizes the main resistancemechanism to antibiotics, focusing particular attention to those conferring resistance to broad-spectrum cephalosporins by means of production of emerging cephalosporinases (extended-spectrum β-lactamases and AmpC β-lactamases), target alteration (penicillin-binding proteins from methicillin-resistant Staphylococcus aureus) and membrane transporters that pump β-lactams out of the bacterial cell.

A communication support for real-time distributed computer controlled systems

In this paper, we analyse the ability of P-NET [1] fieldbus to cope with the timing requirements of a Distributed Computer Control System (DCCS), where messages associated to discrete events should be made available within a maximum bound time. The main objective of this work is to analyse how the network access and queueing delays, imposed by P-NET’s virtual token Medium Access Control (MAC) mechanism, affect the realtime behaviour of the supported DCCS.

Human risk assessment of benzene after a gasoline station fuel leak

OBJECTIVE: To assess the health risk of exposure to benzene for a community affected by a fuel leak. METHODS: Data regarding the fuel leak accident with, which occurred in the Brasilia, Federal District, were obtained from the Fuel Distributor reports provided to the environmental authority. Information about the affected population (22 individuals) was obtained from focal groups of eight individuals. Length of exposure and water benzene concentration were estimated through a groundwater flow model associated with a benzene propagation model. The risk assessment was conducted according to the Agency for Toxic Substances and Disease Registry methodology. RESULTS: A high risk perception related to the health consequences of the accident was evident in the affected community (22 individuals), probably due to the lack of assistance and a poor risk communication from government authorities and the polluting agent. The community had been exposed to unsafe levels of benzene (> 5 µg/L) since December 2001, five months before they reported the leak. The mean benzene level in drinking water (72.2 µg/L) was higher than that obtained by the Fuel Distributer using the Risk Based Corrective Action methodology (17.2 µg/L).The estimated benzene intake from the consumption of water and food reached a maximum of 0.0091 µg/kg bw/day (5 x 10-7 cancer risk per 106 individuals). The level of benzene in water vapor while showering reached 7.5 µg/m3 for children (1 per 104 cancer risk). Total cancer risk ranged from 110 to 200 per 106 individuals. CONCLUSIONS: The population affected by the fuel leak was exposed to benzene levels that might have represented a health risk. Local government authorities need to develop better strategies to respond rapidly to these types of accidents to protect the health of the affected population and the environment.

LNT: a logical neighbor tree secure group communication scheme for wireless sensor networks

Secure group communication is a paradigm that primarily designates one-to-many communication security. The proposed works relevant to secure group communication have predominantly considered the whole network as being a single group managed by a central powerful node capable of supporting heavy communication, computation and storage cost. However, a typical Wireless Sensor Network (WSN) may contain several groups, and each one is maintained by a sensor node (the group controller) with constrained resources. Moreover, the previously proposed schemes require a multicast routing support to deliver the rekeying messages. Nevertheless, multicast routing can incur heavy storage and communication overheads in the case of a wireless sensor network. Due to these two major limitations, we have reckoned it necessary to propose a new secure group communication with a lightweight rekeying process. Our proposal overcomes the two limitations mentioned above, and can be applied to a homogeneous WSN with resource-constrained nodes with no need for a multicast routing support. Actually, the analysis and simulation results have clearly demonstrated that our scheme outperforms the previous well-known solutions.

RiSeG: a ring based secure group communication protocol for resource-constrained wireless sensor networks

Securing group communication in wireless sensor networks has recently been extensively investigated. Many works have addressed this issue, and they have considered the grouping concept differently. In this paper, we consider a group as being a set of nodes sensing the same data type, and we alternatively propose an efficient secure group communication scheme guaranteeing secure group management and secure group key distribution. The proposed scheme (RiSeG) is based on a logical ring architecture, which permits to alleviate the group controller’s task in updating the group key. The proposed scheme also provides backward and forward secrecy, addresses the node compromise attack, and gives a solution to detect and eliminate the compromised nodes. The security analysis and performance evaluation show that the proposed scheme is secure, highly efficient, and lightweight. A comparison with the logical key hierarchy is preformed to prove the rekeying process efficiency of RiSeG. Finally, we present the implementation details of RiSeG on top of TelosB sensor nodes to demonstrate its feasibility.

A tighter analysis of the worst-case endto- end communication delay in massive multicores

"Many-core” systems based on the Network-on- Chip (NoC) architecture have brought into the fore-front various opportunities and challenges for the deployment of real-time systems. Such real-time systems need timing guarantees to be fulfilled. Therefore, calculating upper-bounds on the end-to-end communication delay between system components is of primary interest. In this work, we identify the limitations of an existing approach proposed by [1] and propose different techniques to overcome these limitations.

Highly scalable aggregate computations in cyber-physical systems: physical environment meets communication protocols

In this paper, we focus on large-scale and dense Cyber- Physical Systems, and discuss methods that tightly integrate communication and computing with the underlying physical environment. We present Physical Dynamic Priority Dominance ((PD)2) protocol that exemplifies a key mechanism to devise low time-complexity communication protocols for large-scale networked sensor systems. We show that using this mechanism, one can compute aggregate quantities such as the maximum or minimum of sensor readings in a time-complexity that is equivalent to essentially one message exchange. We also illustrate the use of this mechanism in a more complex task of computing the interpolation of smooth as well as non-smooth sensor data in very low timecomplexity.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

IEEE 802.15.4: a Federating Communication Protocol for Time-Sensitive Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been attracting increasing interests for developing a new generation of embedded systems with great potential for many applications such as surveillance, environment monitoring, emergency medical response and home automation. However, the communication paradigms in WSNs differ from the ones attributed to traditional wireless networks, triggering the need for new communication protocols. In this context, the recently standardised IEEE 802.15.4 protocol presents some potentially interesting features for deployment in wireless sensor network applications, such as power-efficiency, timeliness guarantees and scalability. Nevertheless, when addressing WSN applications with (soft/hard) timing requirements some inherent paradoxes emerge, such as power-efficiency versus timeliness, triggering the need of engineering solutions for an efficient deployment of IEEE 802.15.4 in WSNs. In this technical report, we will explore the most relevant characteristics of the IEEE 802.15.4 protocol for wireless sensor networks and present the most important challenges regarding time-sensitive WSN applications. We also provide some timing performance and analysis of the IEEE 802.15.4 that unveil some directions for resolving the previously mentioned paradoxes.

Unlimited or disrupted communication? How does the development of the mobile phone effect our ability of social action?

The aim of this essay is to discuss the thesis of the German Sociologist Günter Burkhart that in modern societies a phenomenon appeared which he calls “handymania”, an excessive and nearly addictive use of the mobile phones especially from adolescents. After a short overview about the history of the cell phone, I will relate this development to Jürgen Habermas “theory of communicative action”, more precisely to his diagnosis of a pathological society (“lifeworld”) to find out if the “handymania” could be one expression of it. Adjacent I will present social-psychological theories from E.H.Erikson and Tilmann Habermas to ascertain whether juveniles could really be a high-risk group for this kind of addiction. I will focus on the ability to communicate in an Habermasian way that could be seriously harmed by the unregulated usage of cell phones.

Microstructure, mechanical properties and chemical degradation of brazed AISI 316 stainless steel/alumina systems

The main aims of the present study are simultaneously to relate the brazing parameters with: (i) the correspondent interfacial microstructure, (ii) the resultant mechanical properties and (iii) the electrochemical degradation behaviour of AISI 316 stainless steel/alumina brazed joints. Filler metals on such as Ag–26.5Cu–3Ti and Ag–34.5Cu–1.5Ti were used to produce the joints. Three different brazing temperatures (850, 900 and 950 °C), keeping a constant holding time of 20 min, were tested. The objective was to understand the influence of the brazing temperature on the final microstructure and properties of the joints. The mechanical properties of the metal/ceramic (M/C) joints were assessed from bond strength tests carried out using a shear solicitation loading scheme. The fracture surfaces were studied both morphologically and structurally using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction analysis (XRD). The degradation behaviour of the M/C joints was assessed by means of electrochemical techniques. It was found that using a Ag–26.5Cu–3Ti brazing alloy and a brazing temperature of 850 °C, produces the best results in terms of bond strength, 234 ± 18 MPa. The mechanical properties obtained could be explained on the basis of the different compounds identified on the fracture surfaces by XRD. On the other hand, the use of the Ag–34.5Cu–1.5Ti brazing alloy and a brazing temperature of 850 °C produces the best results in terms of corrosion rates (lower corrosion current density), 0.76 ± 0.21 μA cm−2. Nevertheless, the joints produced at 850 °C using a Ag–26.5Cu–3Ti brazing alloy present the best compromise between mechanical properties and degradation behaviour, 234 ± 18 MPa and 1.26 ± 0.58 μA cm−2, respectively. The role of Ti diffusion is fundamental in terms of the final value achieved for the M/C bond strength. On the contrary, the Ag and Cu distribution along the brazed interface seem to play the most relevant role in the metal/ceramic joints electrochemical performance.

Chemical composition and antioxidante activity of Tunisian Origanum glandulosum Desf. essential oil and volatile oil obtain by supercritical CO2 extraction

Dried flowers and leaves of Origanum glandulosum Desf. were submitted to hydrodistillation (HD) and supercritical fluid extraction with CO2 (SFE). The essential oils isolated by HD and volatile oils obtained by SFE were analysed by GC and GC/MS. Total phenolics content and antioxidant effectiveness were performed. The main components of the essential oils from Bargou and Nefza were: p-cymene (40.4% and 39%), thymol (38.7% and 34.4%) and γ- terpinene (12.3% and 19.2%), respectively. The major components obtain by SFE in the volatile oil, from Bargou and Nefza, were: p-cymene (32.3% and 36.2%), thymol (41% and 40%) and γ-terpinene (20.3% and 13.3%). Total phenolic content, expressed in gallic acid equivalent (GAE) g kg-1 dry weight, varied from 12 to 27 g kg-1 dw, and the ability to scavenge the DPPH radicals, expressed by IC50 ranged from 44 to143 mg L-1.

Chemical reaction network of flavylium ions in heterogeneous media

Dissertação apresentada para a obtenção do Grau de Doutor em Química, especialidade em Química-Física, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Acylated cyanoimido-complexes trans-[Mo(NCN){NCN(O)R}(DPPE)(2)]Cl and their reactons with electrophiles: Chemical, electrochemical and theoretical study

Treatment of a dichloromethane solution of trans-[Mo(NCN){NCNC(O)R}(dppe)(2)]Cl [R = Me (1a), Et (1b)] (dppe = Ph2PCH2CH2PPh2) with HBF4, [Et3O][BF4] or EtC(O)Cl gives trans-[Mo(NCN)Cl-(dppe)(2)]X [X = BF4 (2a) or Cl (2b)] and the corresponding acylcyanamides NCN(R')C(O)Et (R' = H, Et or C(O)Et). X-ray diffraction analysis of 2a (X = BF4) reveals a multiple-bond coordination of the cyanoimide ligand. Compounds 1 convert to the bis(cyanoimide) trans-[Mo(NCN)(2)(dppe)(2)] complex upon reaction with an excess of NaOMe (with formation of the respective ester). In an aprotic medium and at a Pt electrode, compounds 1 (R = Me, Et or Ph) undergo a cathodically induced isomerization. Full quantitative kinetic analysis of the voltammetric behaviour is presented and allows the determination of the first-order rate constants and the equilibrium constant of the trans to cis isomerization reaction. The mechanisms of electrophilic addition (protonation) to complexes 1 and the precursor trans[Mo(NCN)(2)(dppe)(2)], as well as the electronic structures, nature of the coordination bonds and electrochemical behaviour of these species are investigated in detail by theoretical methods which indicate that the most probable sites of the proton attack are the oxygen atom of the acyl group and the terminal nitrogen atom, respectively.

Using SysML in systems design

System of systems involves several secondary systems working together with its creation gathering the knowledge of several distinct disciplines and teams, each one with their own background and methods, leading to a difficult communication between them. SysML, a language originated from UML, enables that communication, without background interference, with the use of a rich notation for systems design. This paper analyzes its use through the experience gained in the design of a chemical system with SysML.