New quasi-orthogonal BCH-derived sequences for CDMA applications

European Transactions on Telecommunications, vol. 18

The simple economics of risk-sharing agreements between the NHS and the pharmaceutical industry

The Janssen-Cilag proposal for a risk-sharing agreement regarding bortezomib received a welcome signal from NICE. The Office of Fair Trading report included risk-sharing agreements as an available tool for the National Health Service. Nonetheless, recent discussions have somewhat neglected the economic fundamentals underlying risk-sharing agreements. We argue here that risk-sharing agreements, although attractive due to the principle of paying by results, also entail risks. Too many patients may be put under treatment even with a low success probability. Prices are likely to be adjusted upward, in anticipation of future risk-sharing agreements between the pharmaceutical company and the third-party payer. An available instrument is a verification cost per patient treated, which allows obtaining the first-best allocation of patients to the new treatment, under the risk sharing agreement. Overall, the welfare effects of risk-sharing agreements are ambiguous, and care must be taken with their use.

An overview of the higher level classification of Pucciniomycotina based on combined analyses of nuclear large and small subunit rDNA sequences

Mycologia, Vol. 98, nº6

New simple digital self-calibration technique for pipeline ADCs using the internal thermal noise

IEEE International Symposium on Circuits and Systems, pp. 232 – 235, Seattle, EUA

A stratigraphic framework for the Miocene from the lower Tagus Basin (Lisbon, Setúbal Península, Portugal) Depositional sequences, biostratigraphy and isotopic ages

Rev. Soc. Geol. España, 12(1), ano 1999

Simple and stable dynamic traffic engineering for provider scale ethernet

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática

Heuristics and policies for online pickup and delivery problems

Master Thesis

Glasses' makeup: the simple and the combined effect of color and shape on perceived volume and beverage intake

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Smart & Simple Business Solutions (SSBS)

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

A simple closed-loop membrane process for the purification of active pharmaceutical ingredients

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Interactive acquisition of spatial information from images for multimedia applications

Dissertação para obtenção do Grau de Doutor em Informática

SDAR: a package for plotting and analyzing stratigraphy data in R

Stratigraphic Columns (SC) are the most useful and common ways to represent the eld descriptions (e.g., grain size, thickness of rock packages, and fossil and lithological components) of rock sequences and well logs. In these representations the width of SC vary according to the grain size (i.e., the wider the strata, the coarser the rocks (Miall 1990; Tucker 2011)), and the thickness of each layer is represented at the vertical axis of the diagram. Typically these representations are drawn 'manually' using vector graphic editors (e.g., Adobe Illustrator®, CorelDRAW®, Inskape). Nowadays there are various software which automatically plot SCs, but there are not versatile open-source tools and it is very di cult to both store and analyse stratigraphic information. This document presents Stratigraphic Data Analysis in R (SDAR), an analytical package1 designed for both plotting and facilitate the analysis of Stratigraphic Data in R (R Core Team 2014). SDAR, uses simple stratigraphic data and takes advantage of the exible plotting tools available in R to produce detailed SCs. The main bene ts of SDAR are: (i) used to generate accurate and complete SC plot including multiple features (e.g., sedimentary structures, samples, fossil content, color, structural data, contacts between beds), (ii) developed in a free software environment for statistical computing and graphics, (iii) run on a wide variety of platforms (i.e., UNIX, Windows, and MacOS), (iv) both plotting and analysing functions can be executed directly on R's command-line interface (CLI), consequently this feature enables users to integrate SDAR's functions with several others add-on packages available for R from The Comprehensive R Archive Network (CRAN).

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.