Patent policy, patent pools, and the accumulation of claims in sequential innovation

We present a dynamic model where the accumulation of patents generates an increasing number of claims on sequential innovation. We compare innovation activity under three regimes -patents, no-patents, and patent pools- and find that none of them can reach the first best. We find that the first best can be reached through a decentralized tax-subsidy mechanism, by which innovators receive a subsidy when they innovate, and are taxed with subsequent innovations. This finding implies that optimal transfers work in the exact opposite way as traditional patents. Finally, we consider patents of finite duration and determine the optimal patent length.

Mixture of bivariate Poisson regression models with an application to insurance

In a recent paper Bermúdez [2009] used bivariate Poisson regression models for ratemaking in car insurance, and included zero-inflated models to account for the excess of zeros and the overdispersion in the data set. In the present paper, we revisit this model in order to consider alternatives. We propose a 2-finite mixture of bivariate Poisson regression models to demonstrate that the overdispersion in the data requires more structure if it is to be taken into account, and that a simple zero-inflated bivariate Poisson model does not suffice. At the same time, we show that a finite mixture of bivariate Poisson regression models embraces zero-inflated bivariate Poisson regression models as a special case. Additionally, we describe a model in which the mixing proportions are dependent on covariates when modelling the way in which each individual belongs to a separate cluster. Finally, an EM algorithm is provided in order to ensure the models’ ease-of-fit. These models are applied to the same automobile insurance claims data set as used in Bermúdez [2009] and it is shown that the modelling of the data set can be improved considerably.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

Rapid detection of enterovirus in cerebrospinal fluid by a fully-automated PCR assay is associated with improved management of aseptic meningitis in adult patients.

BACKGROUND: Enterovirus (EV) is the most frequent cause of aseptic meningitis (AM). Lack of microbiological documentation results in unnecessary antimicrobial therapy and hospitalization. OBJECTIVES: To assess the impact of rapid EV detection in cerebrospinal fluid (CSF) by a fully-automated PCR (GeneXpert EV assay, GXEA) on the management of AM. STUDY DESIGN: Observational study in adult patients with AM. Three groups were analyzed according to EV documentation in CSF: group A=no PCR or negative PCR (n=17), group B=positive real-time PCR (n=20), and group C=positive GXEA (n=22). Clinical, laboratory and health-care costs data were compared. RESULTS: Clinical characteristics were similar in the 3 groups. Median turn-around time of EV PCR decreased from 60h (IQR (interquartile range) 44-87) in group B to 5h (IQR 4-11) in group C (p<0.0001). Median duration of antibiotics was 1 (IQR 0-6), 1 (0-1.9), and 0.5 days (single dose) in groups A, B, and C, respectively (p<0.001). Median length of hospitalization was 4 days (2.5-7.5), 2 (1-3.7), and 0.5 (0.3-0.7), respectively (p<0.001). Median hospitalization costs were $5458 (2676-6274) in group A, $2796 (2062-5726) in group B, and $921 (765-1230) in group C (p<0.0001). CONCLUSIONS: Rapid EV detection in CSF by a fully-automated PCR improves management of AM by significantly reducing antibiotic use, hospitalization length and costs.

An approximation algorithm for #k-SAT

"Vegeu el resum a l'inici del document del fitxer adjunt"

A phase I study of the oral platinum agent satraplatin in sequential combination with capecitabine in the treatment of patients with advanced solid malignancies.

Abstract Background. The broad spectrum of antitumor activity of both the oral platinum analogue satraplatin (S) and capecitabine (C), along with the advantage of their oral administration, prompted a clinical study aimed to define the maximum tolerated dose (MTD) of the combination. Patients and methods. Four dose levels of S (mg/m(2)/day) and C (mg/m(2)/day) were evaluated in adult patients with advanced solid tumors: 60/1650, 80/1650, 60/2000, 70/2000; a course consisted of 28 days with sequential administration of S (days 1-5) and C (days 8-21) followed by one week rest. Results. Thirty-seven patients were treated, 24 in the dose escalation and 13 in the expansion phase; at the MTD, defined at S 70/C 2000, two patients presented dose limiting toxicities: lack of recovery of neutropenia by day 42 and nausea with dose skip of C. Most frequent toxicities were nausea (57%), diarrhea (51%), neutropenia (46%), anorexia, fatigue, vomiting (38% each). Two partial responses were observed in platinum sensitive ovarian cancer and one in prostate cancer. Conclusion. At S 70/C 2000 the combination of sequential S and C is tolerated with manageable toxicities; its evaluation in platinum and fluorouracil sensitive tumor types is worthwhile because of the easier administration and lack of nephro- and neurotoxicity as compared to parent compounds.

Improved Methods for the Diagnosis of African Trypanosomosis

The diagnosis of trypanosomosis in animals with low parasitaemia is hampered by low diagnostic sensitivity of traditional detection methods. An immunodiagnostic method based on a direct sandwich enzyme-linked immunosorbent assay (ELISA), using monoclonal antibodies, has been examined in a number of African laboratories for its suitability for monitoring tsetse control and eradication programmes. Generally, the direct sandwich ELISAs for the detection of trypanosomal antigens in serum samples have proved to be unsatisfactory with respect to diagnostic sensitivity when compared with traditional parasitological methods such as the dark ground/phase contrast buffy-coat technique. Consequently, antigen-detection systems exploiting various other direct, indirect and sandwich ELISA systems and sets of reagents are being developed to improve diagnosis. In addition, an existing indirect ELISA for the detection of antibodies has been improved and is being evaluated in the field in order to detect cattle that are or have been recently infected with trypanosomes. Developments and advantages of other diagnostic techniques, such as dip-stick assay and tests based on the polymerase chain reaction are also considered.

Interventions with Parents in the Early Years for improved health outcomes: A focus on behaviour and cognitive development/school readiness

Equity Action is a Joint Action between the EU and Member States aiming to reduce health inequalities by helping to improve policies at national and regional level and harness the contribution of stakeholders. Dr Cotter of IPH completed this literature review as part of Equity Action Work Package 6

Sequential histological changes in Biomphalaria glabrata during the course of Schistosoma mansoni infection

Biomphalaria glabrata, highly susceptible to Schistosoma mansoni, were seen to shed less and less cercariae along the time of infection. Histological examination kept a close correlation with this changing pattern of cercarial shedding, turning an initial picture of no-reaction (tolerance) gradually into one of hemocyte proliferation with formation of focal encapsulating lesions around disintegrating sporocysts and cercariae, a change that became disseminated toward the 142nd day post miracidial exposure. Findings were suggestive of a gradual installation of acquired immunity in snails infected with S. mansoni.

Quantitative integration of geophysical and hydraulic data : from the local towards the regional scale range

Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

An improved method for concentrating rotavirus from water samples

A modified adsorption-elution method for the concentration of seeded rotavirus from water samples was used to determine various factors which affected the virus recovery. An enzyme-linked immunosorbent assay was used to detect the rotavirus antigen after concentration. Of the various eluents compared, 0.05M glycine, pH 11.5 gave the highest rotavirus antigen recovery using negatively charged membrane filtration whereas 2.9% tryptose phosphate broth containing 6% glycine; pH 9.0 was found to give the greatest elution efficiency when a positively charged membrane was used. Reconcentration of water samples by a speedVac concentrator showed significantly higher rotavirus recovery than polyethylene glycol precipitation through both negatively and positively charged filters (p-value <0.001). In addition, speedVac concentration using negatively charged filtration resulted in greater rotavirus recovery than that using positively charged filtration (p-value = 0.004). Thirty eight environmental water samples were collected from river, domestic sewage, canals receiving raw sewage drains, and tap water collected in containers for domestic use, all from congested areas of Bangkok. In addition, several samples of commercial drinking water were analyzed. All samples were concentrated and examined for rotavirus antigen. Coliforms and fecal coliforms (0->1,800 MPN/100 ml) were observed but rotavirus was not detected in any sample. This study suggests that the speedVac reconcentration method gives the most efficient rotavirus recovery from water samples.