Biocompatible Bacterial Cellulose-Poly(2-hydroxyethyl methacrylate) Nanocomposite Films

A series of bacterial cellulose-poly(2-hydroxyethyl methacrylate) nanocomposite films was prepared by in situ radical polymerization of 2-hydroxyethyl methacrylate (HEMA), using variable amounts of poly(ethylene glycol) diacrylate (PEGDA) as crosslinker. Thin films were obtained, and their physical, chemical, thermal, and mechanical properties were evaluated. The films showed improved translucency compared to BC and enhanced thermal stability and mechanical performance when compared to poly(2-hydroxyethyl methacrylate) (PHEMA). Finally, BC/PHEMA nanocomposites proved to be nontoxic to human adipose-derived mesenchymal stem cells (ADSCs) and thus are pointed as potential dry dressings for biomedical applications.

Dynamics of Streptococcus pneumoniae Serotypes Causing Acute Otitis Media Isolated from Children with Spontaneous Middle-Ear Drainage over a 12-Year Period (1999–2010) in a Region of Northern Spain

10 p.

Neuroprotective Effect of Melatonin: A Novel Therapy against Perinatal Hypoxia-Ischemia

17 p.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Advances in Click Chemistry for Single-Chain Nanoparticle Construction

Single-chain polymeric nanoparticles are artificial folded soft nano-objects of ultra-small size which have recently gained prominence in nanoscience and nanotechnology due to their exceptional and sometimes unique properties. This review focuses on the current state of the investigations of click chemistry techniques for highly-efficient single-chain nanoparticle construction. Additionally, recent progress achieved for the use of well-defined single-chain nanoparticles in some promising fields, such as nanomedicine and catalysis, is highlighted.

Aspecto físico y retórica en la novela griega antigua

Javier Alonso Aldama, Cirilo García Román e Idoia Mamolar Sánchez (eds)

An observer-based vaccination control law for an SEIR epidemic model based on feedback linearization techniques for nonlinear systems

This paper presents a vaccination strategy for fighting against the propagation of epidemic diseases. The disease propagation is described by an SEIR (susceptible plus infected plus infectious plus removed populations) epidemic model. The model takes into account the total population amounts as a refrain for the illness transmission since its increase makes the contacts among susceptible and infected more difficult. The vaccination strategy is based on a continuous-time nonlinear control law synthesised via an exact feedback input-output linearization approach. An observer is incorporated into the control scheme to provide online estimates for the susceptible and infected populations in the case when their values are not available from online measurement but they are necessary to implement the control law. The vaccination control is generated based on the information provided by the observer. The control objective is to asymptotically eradicate the infection from the population so that the removed-by-immunity population asymptotically tracks the whole one without precise knowledge of the partial populations. The model positivity, the eradication of the infection under feedback vaccination laws and the stability properties as well as the asymptotic convergence of the estimation errors to zero as time tends to infinity are investigated.

Metal-Free Polymethyl Methacrylate (PMMA) Nanoparticles by Enamine "Click" Chemistry at Room Temperature

"Click" chemistry has become an efficient avenue to unimolecular polymeric nanoparticles through the self-crosslinking of individual polymer chains containing appropriate functional groups. Herein we report the synthesis of ultra-small (7 nm in size) polymethyl methacrylate (PMMA) nanoparticles (NPs) by the "metal-free" cross-linking of PMMA-precursor chains prepared by reversible addition-fragmentation chain transfer (RAFT) polymerization containing beta-ketoester functional groups. Intramolecular collapse was performed by the one-pot reaction of beta-ketoester moieties with alkyl diamines in tetrahydrofurane at r.t. (i.e., by enamine formation). The collapsing process was followed by size exclusion chromatography and by nuclear magnetic resonance spectroscopy. The size of the resulting PMMA-NPs was determined by dynamic light scattering. Enamine "click" chemistry increases the synthetic toolbox for the efficient synthesis of metal-free, ultra-small polymeric NPs.

Algas verdes en el picoplancton y nanoplancton del estuario del río Nervión (Golfo de Vizcaya)

332 p. : il., gráf.

Avances analíticos en la datación forense de tintas y documentos

380 p. : il., gráf.

Optimally robust shortcuts to population inversion in two-level quantum systems

19 p.

Mateda-2.0: Estimation of Distribution Algorithms in MATLAB

This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based on undirected and directed probabilistic graphical models. The implementation contains several methods commonly employed by EDAs. It is also conceived as an open package to allow users to incorporate different combinations of selection, learning, sampling, and local search procedures. Additionally, it includes methods to extract, process and visualize the structures learned by the probabilistic models. This way, it can unveil previously unknown information about the optimization problem domain. Mateda-2.0 also incorporates a module for creating and validating function models based on the probabilistic models learned by EDAs.

Somatisation in primary care: experiences of primary care physicians involved in a training program and in a randomised controlled trial

Background: A new intervention aimed at managing patients with medically unexplained symptoms (MUS) based on a specific set of communication techniques was developed, and tested in a cluster randomised clinical trial. Due to the modest results obtained and in order to improve our intervention we need to know the GPs' attitudes towards patients with MUS, their experience, expectations and the utility of the communication techniques we proposed and the feasibility of implementing them. Physicians who took part in 2 different training programs and in a randomised controlled trial (RCT) for patients with MUS were questioned to ascertain the reasons for the doctors' participation in the trial and the attitudes, experiences and expectations of GPs about the intervention. Methods: A qualitative study based on four focus groups with GPs who took part in a RCT. A content analysis was carried out. Results: Following the RCT patients are perceived as true suffering persons, and the relationship with them has improved in GPs of both groups. GPs mostly valued the fact that it is highly structured, that it made possible a more comfortable relationship and that it could be applied to a broad spectrum of patients with psychosocial problems. Nevertheless, all participants consider that change in patients is necessary; GPs in the intervention group remarked that that is extremely difficult to achieve. Conclusion: GPs positively evaluate the communication techniques and the interventions that help in understanding patient suffering, and express the enormous difficulties in handling change in patients. These findings provide information on the direction in which efforts for improving intervention should be directed.

Prioritization of candidate cancer genes-an aid to oncogenomic studies

The development of techniques for oncogenomic analyses such as array comparative genomic hybridization, messenger RNA expression arrays and mutational screens have come to the fore in modern cancer research. Studies utilizing these techniques are able to highlight panels of genes that are altered in cancer. However, these candidate cancer genes must then be scrutinized to reveal whether they contribute to oncogenesis or are coincidental and non-causative. We present a computational method for the prioritization of candidate (i) proto-oncogenes and (ii) tumour suppressor genes from oncogenomic experiments. We constructed computational classifiers using different combinations of sequence and functional data including sequence conservation, protein domains and interactions, and regulatory data. We found that these classifiers are able to distinguish between known cancer genes and other human genes. Furthermore, the classifiers also discriminate candidate cancer genes from a recent mutational screen from other human genes. We provide a web-based facility through which cancer biologists may access our results and we propose computational cancer gene classification as a useful method of prioritizing candidate cancer genes identified in oncogenomic studies.

Econometría básica aplicada con Gretl

Estas notas de clase son de utilidad como material docente, sirviendo de apoyo o complemento, para aquellos alumnos que bien vayan a hacer o hayan seguido alguna asignatura como Introducción a la Econometría (en LE o LADE), Estadística Actuarial: Regresión (LCAF), Econometría aplicada al mercado (LITM). También puede estar indicada para alumnos de las licenciaturas ofrecidas en la Facultad de Ciencias Sociales y de la Comunicación, por ejemplo la Licenciatura de Publicidad y RR.PP. y de algunas Ingenierías, por ejemplo Ingeniería en Organización Industrial. Las notas de clase se estructuran en siete temas. El primero de ellos introduce el concepto de Econometría, define algunos de los términos más habituales y presenta el software libre a utilizar en las aplicaciones, el programa Gretl. En el tema dos se especifica y estima el Modelo de Regresión Lineal Simple. Se desarrolla el estimador Mínimo Cuadrático Ordinario, sus propiedades y se muestra como hacer inferencia con él. En el tema tres se especifica y estima el Modelo de Regresión Lineal General. En el tema cuatro se muestra como realizar contrastes de restricciones lineales. En el tema cinco se revisa su comportamiento bajo mala especificación del modelo. En los temas seis y siete se muestran, respectivamente, las consecuencias de disponer de una muestra de variables altamente correlacionadas y como utilizar variables ficticias. Al final de cada tema se proponen ejercicios para aplicar lo aprendido en el mismo. Al final de las notas aparece la bibliografía completa.