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The action of any group on itself by conjugation and the corresponding conjugacy relation play an important role in group theory. There have been several attempts to extend the notion of conjugacy to semigroups. In this paper, we present a new definition of conjugacy that can be applied to an arbitrary semigroup and it does not reduce to the universal relation in semigroups with a zero. We compare the new notion of conjugacy with existing definitions, characterize the conjugacy in various semigroups of transformations on a set, and count the number of conjugacy classes in these semigroups when the set is infinite.

The human macrophage galactose-type lectin (hMGL) is a key physiological receptor for the carcinoma-associated Tn antigen (GalNAc-α-1-O-Ser/Thr) in mucins. We herein report NMR- and modeling-based data on the molecular recognition features of synthetic Tn-bearing glycopeptides by hMGL. Cognate epitopes on the sugar and matching key amino acids involved in the interaction have been identified by saturation transfer difference (STD) NMR spectroscopy. Only the amino acids close to the glycosylation site in the peptides are involved in lectin contact. Moreover, control experiments with non-glycosylated MUC1 peptides unequivocally showed that the sugar residue is essential for hMGL binding, as is Ca2+. The dissociation constants (Kd) have been estimated by STD titrations and/or STD competition experiments and show that Gal was a poor binder for hMGL, with a Kd in the mM range, while GalNAc and MUC1 Tn-glycopetides reached Kd values in the lower μM range. STD-based results suggested a distinct interacting epitope for the two monosaccharides. NMR data have been complemented with molecular dynamics simulations and Corcema- ST to establish a 3D view on the molecular recognition process between Gal, GalNAc and the Tn-presenting glycopeptides and hMGL. Gal and GalNAc have a dual binding mode with opposite trend of the main interaction pattern and the differences in affinity can be explained by additional hydrogen bonds and CH-π contacts involving exclusively the NHAc moiety.

The International Energy Agency (IEA), through the Solar Heating and Cooling programme (SHC) Task 40 and the Energy Conservation in Buildings and Community Systems programme (ECBCS, now named EBC) Annex 52, works towards developing a common understanding and setting up the basis for an international definition framework for Net Zero Energy Buildings (Net ZEBs). One of the subtasks of this programme?SubTaskC focuses benchmarking the Net ZEBs around the world to identify the innovative solutions sets that makes up this new type of building. This paper presents an overview of the work conducted by the participants of Subtask C and of Zero Energy Building projects that have been identified.

Iron oxide nanoparticles are having been extensively investigated for several biomedical applications such as hyperthermia and magnetic resonance imaging. However, one of the biggest problems of these nanoparticles is their aggregation.

Taking this into account, in this study the influence of three different surfactants (oleic acid, sodium citrate and Triton X-100) each one with various concentrations in the colloidal solutions stability was analyzed by using a rapid and facile method, the variation in the optical absorbance along time.

The synthesized nanoparticles through chemical precipitation showed an average size of 9 nm and a narrow size distribution. X-ray diffraction pattern and Fourier Transform Infrared analysis confirmed the presence of pure magnetite. SQUID measurements showed superparamagnetic properties with a blocking temperature around 155 K. In addition it was observed that neither sodium citrate nor Triton X-100 influences the magnetic properties of the nanoparticles. On the other hand, oleic acid in a concentration of 64 mM decreases the saturation magnetization from 67 to 45 emu/g. Oleic acid exhibits a good performance as stabilizer of the iron oxide nanoparticles in an aqueous solution for 24 h, for concentrations that lead to the formation of the double layer.

Nowadays, modern analysis of Civil Engineering structures implies the use of increasingly sophisticated computer models, designed not only to predict the response of actual structures to different loadings, but also to simulate the effects of eventual modifications in their structural configuration. Nevertheless, it is often discovered that, when the numerical simulations are compared with experimental data, the degree of correlation is weak preventing the use of the FE models with confidence in further analyses. In such cases, FE updating techniques are available to correct the FE models, based on dynamic response records of the real structures. These updating processes usually consist of four phases: a preliminary FE modeling, an experimental modal identification, a manual sensitivity analysis and, finally, an updating of the FE model. The present paper presents all four phases of a successful updating process for the FE model of a footbridge structure. It is shown how the last phase of the process can be performed fully automatically, by coupling an optimization routine with a commercial FE analysis program.

This paper presents a tool, dubbed FaultySheet Detective, for aiding in spreadsheet fault localization, which combines the detection of bad smells with a generic spectrum-based fault localization algorithm.

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