A Model to Evaluate Vertical Handovers on JRRM

In a heterogeneous cellular networks environment, users behaviour and network deployment configuration parameters have an impact on the overall Quality of Service. This paper proposes a new and simple model that, on the one hand, explores the users behaviour impact on the network by having mobility, multi-service usage and traffic generation profiles as inputs, and on the other, enables the network setup configuration evaluation impact on the Joint Radio Resource Management (JRRM), assessing some basic JRRM performance indicators, like Vertical Handover (VHO) probabilities, average bit rates, and number of active users, among others. VHO plays an important role in fulfilling seamless users sessions transfer when mobile terminals cross different Radio Access Technologies (RATs) boundaries. Results show that high bit rate RATs suffer and generate more influence from/on other RATs, by producing additional signalling traffic to a JRRM entity. Results also show that the VHOs probability can range from 5 up to 65%, depending on RATs cluster radius and users mobility profile.

On cluster analysis of complex and heterogeneous data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.

Cluster de volatilidade no mercado de taxas de câmbio USD/GBP

Mestrado em Controlo de Gestão e dos Negócios

On the capacity of cluster-tree ZigBee networks

Modeling the fundamental performance limits of Wireless Sensor Networks (WSNs) is of paramount importance to understand their behavior under worst-case conditions and to make the appropriate design choices. In that direction this paper contributes with an analytical methodology for modeling cluster-tree WSNs where the data sink can either be static or mobile. We assess the validity and pessimism of analytical model by comparing the worst-case results with the values measured through an experimental test-bed based on Commercial-Off- The-Shelf (COTS) technologies, namely TelosB motes running TinyOS.

Simulation study of energy efficient scheduling for IEEE 802.15.4/ZigBee cluster-treeWireless Sensor Networks with time-bounded data flows

The simulation analysis is important approach to developing and evaluating the systems in terms of development time and cost. This paper demonstrates the application of Time Division Cluster Scheduling (TDCS) tool for the configuration of IEEE 802.15.4/ZigBee beaconenabled cluster-tree WSNs using the simulation analysis, as an illustrative example that confirms the practical applicability of the tool. The simulation study analyses how the number of retransmissions impacts the reliability of data transmission, the energy consumption of the nodes and the end-to-end communication delay, based on the simulation model that was implemented in the Opnet Modeler. The configuration parameters of the network are obtained directly from the TDCS tool. The simulation results show that the number of retransmissions impacts the reliability, the energy consumption and the end-to-end delay, in a way that improving the one may degrade the others.

Modeling and worst-case dimensioning of cluster-tree wireless sensor networks

Time-sensitive Wireless Sensor Network (WSN) applications require finite delay bounds in critical situations. This paper provides a methodology for the modeling and the worst-case dimensioning of cluster-tree WSNs. We provide a fine model of the worst-case cluster-tree topology characterized by its depth, the maximum number of child routers and the maximum number of child nodes for each parent router. Using Network Calculus, we derive “plug-and-play” expressions for the endto- end delay bounds, buffering and bandwidth requirements as a function of the WSN cluster-tree characteristics and traffic specifications. The cluster-tree topology has been adopted by many cluster-based solutions for WSNs. We demonstrate how to apply our general results for dimensioning IEEE 802.15.4/Zigbee cluster-tree WSNs. We believe that this paper shows the fundamental performance limits of cluster-tree wireless sensor networks by the provision of a simple and effective methodology for the design of such WSNs.

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion. © 2014 Springer-Verlag Berlin Heidelberg.

Overproduction, crystallization and preliminary X-ray characterization of Abn2, an endo-1,5-alpha-arabinanase from Bacillus subtilis.

Acta Crystallographica F64 (2008) 636-638

Enhancing the selection of a model-based clustering with external categorical variables

In cluster analysis, it can be useful to interpret the partition built from the data in the light of external categorical variables which are not directly involved to cluster the data. An approach is proposed in the model-based clustering context to select a number of clusters which both fits the data well and takes advantage of the potential illustrative ability of the external variables. This approach makes use of the integrated joint likelihood of the data and the partitions at hand, namely the model-based partition and the partitions associated to the external variables. It is noteworthy that each mixture model is fitted by the maximum likelihood methodology to the data, excluding the external variables which are used to select a relevant mixture model only. Numerical experiments illustrate the promising behaviour of the derived criterion.

Desulfovibrio gigas ferredoxin II: redox structural modulation of the [3Fe–4S] cluster

J Biol Inorg Chem (2006) 11: 307–315 DOI 10.1007/s00775-005-0077-2

Formation of a stable cyano-bridged dinuclear iron cluster following oxidation of the superoxide reductases from Treponema pallidum and Desulfovibrio vulgaris with K(3)Fe(CN)(6)

Inorg. Chem., 2003, 42 (4), pp 938–940 DOI: 10.1021/ic0262886

Incorporation of either molybdenum or tungsten into formate dehydrogenase from Desulfovibrio alaskensis NCIMB 13491; EPR assignment of the proximal iron-sulfur cluster to the pterin cofactor in formate dehydrogenases from sulfate-reducing bacteria

J Biol Inorg Chem (2004) 9: 145–151 DOI 10.1007/s00775-003-0506-z

Chagas disease as a mechanistic model for testing a novel hypothesis

The association between depression and cardiovascular disease is well documented. Nevertheless, the process through which they are linked remains unknown, as does the direction of this relationship. Studies have suggested both that depression is a risk factor for heart disease and that heart disease is a risk factor for depression. A number of studies have established that a relationship exists between depression and inflammation, with alterations in the levels of inflammatory markers (IL-1, IL-6, TNF-alpha and others). Depressive symptoms have also been identified in many diseases characterized by inflammatory processes e.g. rheumatoid arthritis, bronchial asthma, diabetes, tuberculosis and cardiovascular diseases. In this brief viewpoint, we explain and propose how to use Chagas disease, a disorder characterized by inflammatory processes and leading to cardiovascular and autonomic problems, as a model for studying the directionality of the relationship between heart disease and depression.

Mutational analysis of the highly conserved arginine within the Glu/Asp-Arg-Tyr motif of the alpha(1b)-adrenergic receptor: effects on receptor isomerization and activation.

We have suggested previously that both the negatively and positively charged residues of the highly conserved Glu/Asp-Arg-Tyr (E/DRY) motif play an important role in the activation process of the alpha(1b)-adreneric receptor (AR). In this study, R143 of the E/DRY sequence in the alpha(1b)-AR was mutated into several amino acids (Lys, His, Glu, Asp, Ala, Asn, and Ile). The charge-conserving mutation of R143 into lysine not only preserved the maximal agonist-induced response of the alpha(1b)-AR, but it also conferred high degree of constitutive activity to the receptor. Both basal and agonist-induced phosphorylation levels were significantly increased for the R143K mutant compared with those of the wild-type receptor. Other substitutions of R143 resulted in receptor mutants with either a small increase in constitutive activity (R143H and R143D), impairment (R143H, R143D), or complete loss of receptor-mediated response (R143E, R143A, R143N, R143I). The R413E mutant displayed a small, but significant increase in basal phosphorylation despite being severely impaired in receptor-mediated response. Interestingly, all the arginine mutants displayed increased affinity for agonist binding compared with the wild-type alpha(1b)-AR. A correlation was found between the extent of the affinity shift and the intrinsic activity of the agonists. The analysis of the receptor mutants using the allosteric ternary complex model in conjunction with the results of molecular dynamics simulations on the receptor models support the hypothesis that mutations of R143 can drive the isomerization of the alpha(1b)-AR into different states, highlighting the crucial role of this residue in the activation process of the receptor.

Ab initio modeling and molecular dynamics simulation of the alpha 1b-adrenergic receptor activation.

This work describes the ab initio procedure employed to build an activation model for the alpha 1b-adrenergic receptor (alpha 1b-AR). The first version of the model was progressively modified and complicated by means of a many-step iterative procedure characterized by the employment of experimental validations of the model in each upgrading step. A combined simulated (molecular dynamics) and experimental mutagenesis approach was used to determine the structural and dynamic features characterizing the inactive and active states of alpha 1b-AR. The latest version of the model has been successfully challenged with respect to its ability to interpret and predict the functional properties of a large number of mutants. The iterative approach employed to describe alpha 1b-AR activation in terms of molecular structure and dynamics allows further complications of the model to allow prediction and interpretation of an ever-increasing number of experimental data.