Multidisciplinary approach to aeroelastic studies of long-span bridges

This paper focuses on the design of long-span suspension bridges under aeroelastic constraints. Such challenging structures need to be protected against wind-induced instabilities as flutter. The authors envision that a set of scientific disciplines not currently used in bridge engineering may help along the design process and constitute a useful tool. First, the formulation of sensitivity analysis of flutter speed is described, indicating how this technique can be a guide for engineers making changes in the prototype; two examples of important bridges, as the Great Belt and Messina Strait, are used to demonstrate the capability of this approach. Then, the idea of producing computer animations to represent the aeroelastic deformation of bridges simulating virtual boundary layer wind tunnel testing is presented showing pictures of the Tacoma Narrows and Messina Bridges. Finally, the advantages of introducing distributed computing to make easier to implement the previously mentioned techniques are demonstrated. The authors have previously published papers related with sensitivity analysis in bridges or computer animations of the aeroelastic behaviour of suspension bridges. However, this is the first time that their comprehensive multidisciplinary approach is presented.     

Device for characterization of thermal effusivity of liquids using photothermal beam deflection

We propose and study a novel optoelectronic device for thermal characterization of materials. It is based on monitoring the photothermal deflection of a laser beam within a slab of a thermo-optic material in thermal contact with the sample under study. An optical angle sensor is used to measure the laser deflection providing a simple and experimental arrangement. We demonstrate its principle and a simple procedure to measure thermal effusivity of liquids. The proposed device could be implemented into a compact sensor head for remote measurements using electrical and fiber optic links.     

Analysis of the HLA class I associated peptide repertoire in a hepatocellular carcinoma cell line reveals tumor-specific peptides as putative targets for immunotherapy

HLA class I molecules present peptides on the cell surface to CD8(+) T cells. The repertoire of peptides that associate to class I molecules represents the cellular proteome. Therefore, cells expressing different proteomes could generate different class I-associated peptide repertoires. A large number of peptides have been sequenced from HLA class I alleles, mostly from lymphoid cells. On the other hand, T cell immunotherapy is a goal in the fight against cancer, but the identification of T cell epitopes is a laborious task. Proteomic techniques allow the definition of putative T cell epitopes by the identification of HLA natural ligands in tumor cells. In this study, we have compared the HLA class I-associated peptide repertoire from the hepatocellular carcinoma (HCC) cell line SK-Hep-1 with that previously described from lymphoid cells. The analysis of the peptide pool confirmed that, as expected, the peptides from SK-Hep-1 derive from proteins localized in the same compartments as in lymphoid cells. Within this pool, we have identified 12 HLA class I peptides derived from HCC-related proteins. This confirms that tumor cell lines could be a good source of tumor associated antigens to be used, together with MS, to define putative epitopes for cytotoxic T cells from cancer patients.     

The interpretation of X-ray photoelectron spectra of pyrolized S-containing carbonaceous materials

Theoretical models and ab initio Hartree-Fock wavefunctions have been used to investigate the S(2p) core level binding energies (BE), of pyrolized S-containing, carbonaceous materials. Comparison between experimental and calculated data for thiophene permits the accuracy of the present approach to be established. A systematic study of different situations demonstrates that, in these materials, non-oxidized S atoms can show peaks at very high BE relative to the C(1s) peak at 285.0 eV. This study confirms that the peak at 164.1 eV corresponds to ‘thiophenic’ S atoms. On the other hand, it shows that the peaks at higher BE could correspond to S atoms replacing C atoms in three-coordinated structures of graphene layers, in agreement with the arguments suggested in the experimental works. The energetic similarity between the two peaks at very high BE makes it difficult to differentiate between them, although the results of the present study seem to suggest that the peak at experimental BE ≈ 166 eV could correspond to S atoms coordinated to two C and one H atoms at the edge of graphene layers, while the peak at ≈ 169 eV would correspond to S atoms replacing C atoms in inner positions of the graphene layers, and it is bonded to three C atoms.     

Rab7 and actin cytoskeleton participate during mobilization of β1EHFNR in fibronectin-stimulated Entamoeba histolyticatrophozoites

In vitro interaction of Entamoeba histolytica trophozoites with fibronectin (FN) induces redistribution of the amoebic fibronectin receptor (β1EhFNR). Trafficking of beta1 integrins is important for cell adhesion and migration in higher eukaryotes and requires the participation of Rab proteins. In E. histolytica, the machinery involved in integrin trafficking is not completely known. EhRab7 is a 24.5-kDa protein whose alignment with other Rab7 proteins demonstrated that it shared significant homology with Rab7 proteins from other organisms, including humans. Using different types of microscopy (fluorescence and confocal microscopy), it was established that Rab7 and the actin cytoskeleton participated in the mobilization of β1EhFNR in FN-stimulated trophozoites. β1EhFNR and Rab7 co-localized only in vesicular structures at 5 min, and at longer time (1 h), both co-localized in both plasma membrane and in vesicular structures; at the same time, Rab7 co-localized with specific actin structures (phagocytic vacuoles). At 5 h the β1EhFNR, Rab7, and actin co-localized at the plasma membrane, and only β1EhFNR and Rab7 decorated vesicles of different sizes. Actin and Rab7 co-localized in a cap-like structure at one end of the cell. Fluorescence resonance energy transfer and electron microscopy confirmed the close interaction between β1EhFNR and Rab7. Moreover, the use of a lysosome-specific marker (LysoTracker) and a Golgi-specific marker (NBD C(6)-ceramide) allowed us to establish that, at some point within the endocytic route, β1EhFNR and Rab7 co-localized within a lysosome-type organelle, but not a Golgi-like organelle, which indicated that this integrin-like molecule was returned to the plasma membrane via exocytic or secretory vesicles.     

Self-calibrated,Multi-spectral Photometric Stereo for 3D Face Capture

This paper addresses the problem of obtaining 3d detailed reconstructions of human faces in real-time and with inexpensive hardware. We present an algorithm based on a monocular multi-spectral photometric-stereo setup. This system is known to capture high-detailed deforming 3d surfaces at high frame rates and without having to use any expensive hardware or synchronized light stage. However, the main challenge of such a setup is the calibration stage, which depends on the lights setup and how they interact with the specific material being captured, in this case, human faces. For this purpose we develop a self-calibration technique where the person being captured is asked to perform a rigid motion in front of the camera, maintaining a neutral expression. Rigidity constrains are then used to compute the head’s motion with a structure-from-motion algorithm. Once the motion is obtained, a multi-view stereo algorithm reconstructs a coarse 3d model of the face. This coarse model is then used to estimate the lighting parameters with a stratified approach: In the first step we use a RANSAC search to identify purely diffuse points on the face and to simultaneously estimate this diffuse reflectance model. In the second step we apply non-linear optimization to fit a non-Lambertian reflectance model to the outliers of the previous step. The calibration procedure is validated with synthetic and real data.     

Distance maps from unthresholded magnitudes

A straightforward algorithm that computes distance maps from unthresholded magnitudes is presented, suitable for still images and video sequences. While results on binary images are similar to classic Euclidean Distance Transforms, the proposed approach does not require a binarization step. Thus, no thresholds are needed and no information is lost in intermediate classification stages. Experiments include the evaluation of spatial and temporal coherence of distance map values, showing better results in both measurements than those obtained with Sobel or Deriche gradients and classic chessboard distance transforms.     

Bootstrapping Boosted Random Ferns for discriminative and efficient object classification

In this paper we show that the performance of binary classifiers based on Boosted Random Ferns can be significantly improved by appropriately bootstrapping the training step. This results in a classifier which is both highly discriminative and computationally efficient and is particularly suitable when only small sets of training images are available.During the learning process, a small set of labeled images is used to train the boosting binary classifier. The classifier is then evaluated over the training set and warped versions of the classified and misclassified patches are progressively added into the positive and negative sample sets for a new re-training step. In this paper we thoroughly study the conditions under which this bootstrapping scheme improves the detection rates. In particular we assess the quality of detection both as a function of the number of bootstrapping iterations and the size of the training set. We compare our algorithm against state-of-the-art approaches for several databases including faces, cars, motorbikes and horses, and show remarkable improvements in detection rates with just a few bootstrapping steps.     

Open Innovation in an Enterprise 3.0 framework: Three case studies

Nowadays, especially after the recent financial downturn, companies are looking for much more efficient and creative business processes. They need to place better solutions in the market in a less time with less cost. There is a general intuition that communication and collaboration, especially mixed with Web 2.0 approach within companies and ecosystems, can boost the innovation process with positive impacts on business indicators. Open Innovation within an Enterprise 2.0 context is a one of the most chosen paradigm for improving the innovation processes of enterprises, based on the collaborative creation and development of ideas and products. The key feature of this new paradigm is that the knowledge is exploited in a collaborative way flowing not only among internal sources, i.e. R&D departments, but also among external ones as other employees, customers, partners, etc. In this paper we show how an ontology-based analysis of plain text can provide a semantic contextualization of content support tasks, such as finding semantic distance between contents, and can help in creating relations between people with shared knowledge and interests. Along this paper we will present the results obtained by the adoption of this technology in a large corporate environment like Bankinter, a financial institution, Telefonica I+D, an international telecommunication firm and Repsol, a major oil company in Spain.