Model spaces and Toeplitz kernels in reflexive Hardy spaces

This paper considers model spaces in an Hp setting. The existence of unbounded functions and the characterisation of maximal functions in a model space are studied, and decomposition results for Toeplitz kernels, in terms of model spaces, are established

Modulation of the secretome of hBMSCs by tailoring the macromolecular gradient in hydrogels to generate tissue-to-tissue interfaces

Tissue-to-tissue interfaces are commonly present in all tissues exhibiting structural, biological and chemical gradients serving a wide range of physiological functions. These interfaces are responsible for mediation of load transfer between two adjacent tissues. They are also important structures in sustaining the cellular communications to retain tissueâ s functional integration and homeostasis. [1] All cells have the capacity to sense and respond to physical and chemical stimulus and when cultured in three-dimensional (3D) environments they tend to perform their function better than in two-dimensional (2D) environments. Spatial and temporal 3D gradient hydrogels better resemble the natural environment of cells in mimicking their extracellular matrix. [2] In this study we hypothesize that differential functional properties can be engineered by modulation of macromolecule gradients in a cell seeded threedimensional hydrogel system. Specifically, differential paracrine secretory profiles can be engineered using human Bone Marrow Stem Cells (hBMSCâ s). Hence, the specific objectives of this study are to: assemble the macromolecular gradient hydrogels to evaluate the suitablity for hBMSCâ s encapsulation by cellular viability and biofunctionality by assessing the paracrine secretion of hBMSCâ s over time. The gradient hydrogels solutions were prepared by blend of macromolecules in one solution such as hyaluronic (HA) acid and collagen (Col) at different ratios. The gradient hydrogels were fabricated into cylindrical silicon moulds with higher ratio solutions assembled at the bottom of the mould and adding the two solutions consecutively on top of each other. The labelling of the macromolecules was performed to confirm the gradient through fluorescence microscopy. Additionally, AFM was conducted to assess the gradient hydrogels stiffness. Gradient hydrogels characterization was performed by HA and Col degradation assay, degree of crosslinking and stability. hBMSCâ s at P3 were encapsulated into each batch solution at 106 cells/ml solution and gradient hydrogels were produced as previously described. The hBMSCâ s were observed under confocal microscopy to assess viability by Live/Dead® staining. Cellular behaviour concerning proliferation and matrix deposition was also performed. Secretory cytokine measurement for pro-inflammatory and angiogenesis factors was carried out using ELISA. At genomic level, qPCR was carried out. The 3D gradient hydrogels platform made of different macromolecules showed to be a suitable environment for hBMSCâ s. The hBMSCâ s gradient hydrogels supported high cell survival and exhibited biofunctionality. Besides, the 3D gradient hydrogels demonstrated differentially secretion of pro-inflammatory and angiogenic factors by the encapsulated hBMSCâ s. References: 1. Mikos, AG. et al., Engineering complex tissues. Tissue Engineering 12,3307, 2006 2. Phillips, JE. et al., Proc Natl Acad Sci USA, 26:12170-5, 2008

Predicting preterm birth in maternity care by means of data mining

Worldwide, around 9% of the children are born with less than 37 weeks of labour, causing risk to the premature child, whom it is not prepared to develop a number of basic functions that begin soon after the birth. In order to ensure that those risk pregnancies are being properly monitored by the obstetricians in time to avoid those problems, Data Mining (DM) models were induced in this study to predict preterm births in a real environment using data from 3376 patients (women) admitted in the maternal and perinatal care unit of Centro Hospitalar of Oporto. A sensitive metric to predict preterm deliveries was developed, assisting physicians in the decision-making process regarding the patients’ observation. It was possible to obtain promising results, achieving sensitivity and specificity values of 96% and 98%, respectively.

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.