Models de comportament de la demanda turística britànica i alemanya a les Balears, i efectes de l'ecotaxa per a aquests mercats

En aquest article s’estimen models de comportament de la demanda turística alemanya i britànica posant èmfasi a treballar amb la sèrie del deflactor dels preus de l’hostaleria balear, tot evitant fer estimacions amb preus declarats de “paquets” turístics, que tenen l’ inconvenient de no recollir els descomptes reals de darrera hora, especialment importants en el cas del mercat britànic

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.

Forecasting tourism demand to Catalonia: neural networks vs. time series models

The increasing interest aroused by more advanced forecasting techniques, together with the requirement for more accurate forecasts of tourismdemand at the destination level due to the constant growth of world tourism, has lead us to evaluate the forecasting performance of neural modelling relative to that of time seriesmethods at a regional level. Seasonality and volatility are important features of tourism data, which makes it a particularly favourable context in which to compare the forecasting performance of linear models to that of nonlinear alternative approaches. Pre-processed official statistical data of overnight stays and tourist arrivals fromall the different countries of origin to Catalonia from 2001 to 2009 is used in the study. When comparing the forecasting accuracy of the different techniques for different time horizons, autoregressive integrated moving average models outperform self-exciting threshold autoregressions and artificial neural network models, especially for shorter horizons. These results suggest that the there is a trade-off between the degree of pre-processing and the accuracy of the forecasts obtained with neural networks, which are more suitable in the presence of nonlinearity in the data. In spite of the significant differences between countries, which can be explained by different patterns of consumer behaviour,we also find that forecasts of tourist arrivals aremore accurate than forecasts of overnight stays.

Mechanisms and drug therapy of pulmonary hypertension at high altitude.

Abstract Scherrer, Urs, Yves Allemann, Emrush Rexhaj, Stefano F. Rimoldi, and Claudio Sartori. Mechanisms and drug therapy of pulmonary hypertension at high altitude. High Alt Med Biol 14:126-133, 2013.-Pulmonary vasoconstriction represents a physiological adaptive mechanism to high altitude. If exaggerated, however, it is associated with important morbidity and mortality. Recent mechanistic studies using short-term acute high altitude exposure have provided insight into the importance of defective vascular endothelial and respiratory epithelial nitric oxide (NO) synthesis, increased endothelin-1 bioavailability, and overactivation of the sympathetic nervous system in causing exaggerated hypoxic pulmonary hypertension in humans. Based on these studies, drugs that increase NO bioavailability, attenuate endothelin-1 induced pulmonary vasoconstriction, or prevent exaggerated sympathetic activation have been shown to be useful for the treatment/prevention of exaggerated pulm9onary hypertension during acute short-term high altitude exposure. The mechanisms underpinning chronic pulmonary hypertension in high altitude dwellers are less well understood, but recent evidence suggests that they differ in some aspects from those involved in short-term adaptation to high altitude. These differences have consequences for the choice of the treatment for chronic pulmonary hypertension at high altitude. Finally, recent data indicate that fetal programming of pulmonary vascular dysfunction in offspring of preeclampsia and children generated by assisted reproductive technologies represents a novel and frequent cause of pulmonary hypertension at high altitude. In animal models of fetal programming of hypoxic pulmonary hypertension, epigenetic mechanisms play a role, and targeting of these mechanisms with drugs lowers pulmonary artery pressure. If epigenetic mechanisms also are operational in the fetal programming of pulmonary vascular dysfunction in humans, such drugs may become novel tools for the treatment of hypoxic pulmonary hypertension.

Effects of particulate matters on inflammatory markers in the general adult population

Summary: Particulate air pollution is associated with increased cardiovascular risk. The induction of systemic inflammation following particle inhalation represents a plausible mechanistic pathway. The purpose of this study was to assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers in 6183 adults in Lausanne, Switzerland. The results show that short-term exposure to PM10 was associated with higher levels of circulating IL-6 and TNF-α. The positive association of PM10 with markers of systemic inflammation materializes the link between air pollution and cardiovascular risk. Background: Variations in short-term exposure to particulate matters (PM) have been repeatedly associated with daily all-cause mortality. Particle-induced inflammation has been postulated to be one of the important mechanisms for increased cardiovascular risk. Experimental in-vitro, in-vivo and controlled human studies suggest that interleukin 6 (IL-6) and tumor-necrosis-factor alpha (TNF-α) could represent key mediators of the inflammatory response to PM. The associations of short-term exposure to ambient PM with circulating inflammatory markers have been inconsistent in studies including specific subgroups so far. The epidemiological evidence linking short-term exposure to ambient PM and systemic inflammation in the general population is scarce. So far, large-scale population-based studies have not explored important inflammatory markers such as IL-6, IL-1β or TNF-α. We therefore analyzed the associations between short-term exposure to ambient PM10 and circulating levels of high-sensitive CRP (hs-CRP), IL-6, IL-1β and TNF-α in the population-based CoLaus study. Objectives: To assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers, including hs-CRP, IL-6, IL-1β and TNF-α, in adults aged 35 to 75 years from the general population. Methodology: All study subjects were participants to the CoLaus study (www.colaus.ch) and the baseline examination was carried out from 2003 to 2006. Overall, 6184 participants were included. For the present analysis, 6183 participants had data on at least one of the four measured circulating inflammatory markers. The monitoring data was obtained from the website of Swiss National Air Pollution Monitoring Network (NABEL). We analyzed data on PM10 as well as outside air temperature, pressure and humidity. Hourly concentrations of PM10 were collected from 1 January 2003 to 31 December 2006. Robust linear regression (PROC ROBUSTREG) was used to evaluate the relationship between cytokine inflammatory and PM10. We adjusted all analyses for age, sex, body mass index, smoking status, alcohol consumption, diabetes status, hypertension status, education levels, zip code, and statin intake. All data were adjusted for the effects of weather by including temperature, barometric pressure, and season as covariates in the adjusted models. We performed simple and multiple logistic regression analyses. Descriptive statistical analysis used the Wilcoxon rank sum test (for medians). All data analyses were performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA), and a two-sided significance level of 5% was used. Results: PM10 levels averaged over 24 hours were significantly and positively associated with continuous IL-6 and TNF-α levels, in the whole study population both in unadjusted and adjusted analyses. For each cytokine, there was a similar seasonal pattern, with wider confidence intervals in summer than during the other seasons, which might partly be due to the smaller number of participants examined in summer. The associations of PM10 with IL-6 and TNF-α were also found after having dichotomized these cytokines into high versus low levels, which suggests that the associations of PM10 with the continuous cytokine levels are very robust to any distributional assumption and to potential outlier values. In contrast with what we observed for continuous IL-1β levels, high PM10 levels were significantly associated with high IL-1β. PM10 was significantly associated with IL-6 and TNF-α in men, but with TNF-α only in women. However, there was no significant statistical interaction between PM10 and sex. For IL-6 and TNF-α, the associations tended to be stronger in younger people, with a significant interaction between PM10 and age groups for IL-6. PM10 was significantly associated with IL-6 and TNF-α in the healthy group and also in the "non-healthy" group, although the statistical interaction between healthy status and PM10 was not significant. Conclusion: In summary, we found significant independent positive associations of short-term exposure to PM10 with circulating levels of IL-6 and TNF-α in the adult population of Lausanne. Our findings strongly support the idea that short-term exposure to PM10 is sufficient to induce systemic inflammation on a broad scale in the general population. From a public health perspective, the reported association of elevated inflammatory cytokines with short-term exposure to PM10 in a city with relatively clean air such as Lausanne supports the importance of limiting urban air pollution levels.

Hepatitis C virus infection: in vivo and in vitro models.

Major advances in the understanding of the molecular biology of hepatitis C virus (HCV) have been made recently. While the chimpanzee is the only established animal model of HCV infection, several in vivo and in vitro models have been established that allow us to study various aspects of the viral life cycle. In particular, the replicon system and the production of recombinant infectious virions revolutionized the investigation of HCV-RNA replication and rendered all steps of the viral life cycle, including entry and release of viral particles, amenable to systematic analysis. In the following we will review the different in vivo and in vitro models of HCV infection.

Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain)

Forecasting coal resources and reserves is critical for coal mine development. Thickness maps are commonly used for assessing coal resources and reserves; however they are limited for capturing coal splitting effects in thick and heterogeneous coal zones. As an alternative, three-dimensional geostatistical methods are used to populate facies distributionwithin a densely drilled heterogeneous coal zone in the As Pontes Basin (NWSpain). Coal distribution in this zone is mainly characterized by coal-dominated areas in the central parts of the basin interfingering with terrigenous-dominated alluvial fan zones at the margins. The three-dimensional models obtained are applied to forecast coal resources and reserves. Predictions using subsets of the entire dataset are also generated to understand the performance of methods under limited data constraints. Three-dimensional facies interpolation methods tend to overestimate coal resources and reserves due to interpolation smoothing. Facies simulation methods yield similar resource predictions than conventional thickness map approximations. Reserves predicted by facies simulation methods are mainly influenced by: a) the specific coal proportion threshold used to determine if a block can be recovered or not, and b) the capability of the modelling strategy to reproduce areal trends in coal proportions and splitting between coal-dominated and terrigenousdominated areas of the basin. Reserves predictions differ between the simulation methods, even with dense conditioning datasets. Simulation methods can be ranked according to the correlation of their outputs with predictions from the directly interpolated coal proportion maps: a) with low-density datasets sequential indicator simulation with trends yields the best correlation, b) with high-density datasets sequential indicator simulation with post-processing yields the best correlation, because the areal trends are provided implicitly by the dense conditioning data.

Predictive models for nanotoxicology: current challenges and future opportunities.

Characterizing the risks posed by nanomaterials is extraordinarily complex because these materials can have a wide range of sizes, shapes, chemical compositions and surface modifications, all of which may affect toxicity. There is an urgent need for a testing strategy that can rapidly and efficiently provide a screening approach for evaluating the potential hazard of nanomaterials and inform the prioritization of additional toxicological testing where necessary. Predictive toxicity models could form an integral component of such an approach by predicting which nanomaterials, as a result of their physico-chemical characteristics, have potentially hazardous properties. Strategies for directing research towards predictive models and the ancillary benefits of such research are presented here.

Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

1,2,3,4-Tetrahydrobenzo[h][1,6]naphthyridines as a new family of potent peripheral-to-midgorge-site inhibitors of acetylcholinesterase: synthesis, pharmacological evaluation and mechanistic studies

A series of 1,2,3,4-tetrahydrobenzo[h][1,6]naphthyridines differently substituted at positions 1, 5, and 9 have been designed from the pyrano[3,2-c]quinoline derivative 1, a weak inhibitor of acetylcholinesterase (AChE) with predicted ability to bind to the AChE peripheral anionic site (PAS), at the entrance of the catalytic gorge. Fourteen novel benzonaphthyridines have been synthesized through synthetic sequences involving as the key step a multicomponent Povarov reaction between an aldehyde, an aniline and an enamine or an enamide as the activated alkene. The novel compounds have been tested against Electrophorus electricus AChE (EeAChE), human recombinant AChE (hAChE), and human serum butyrylcholinesterase (hBChE), and their brain penetration has been assessed using the PAMPA-BBB assay. Also, the mechanism of AChE inhibition of the most potent compounds has been thoroughly studied by kinetic studies, a propidium displacement assay, and molecular modelling. We have found that a seemingly small structural change such as a double O → NH bioisosteric replacement from the hit 1 to 16a results in a dramatic increase of EeAChE and hAChE inhibitory activities (>217- and >154-fold, respectively), and in a notable increase in hBChE inhibitory activity (> 11-fold), as well. An optimized binding at the PAS besides additional interactions with AChE midgorge residues seem to account for the high hAChE inhibitory potency of 16a (IC50 = 65 nM), which emerges as an interesting anti-Alzheimer lead compound with potent dual AChE and BChE inhibitory activities.

1,2,3,4-Tetrahydrobenzo[h][1,6]naphthyridines as a new family of potent peripheral-to-midgorge-site inhibitors of acetylcholinesterase: synthesis, pharmacological evaluation and mechanistic studies

A series of 1,2,3,4-tetrahydrobenzo[h][1,6]naphthyridines differently substituted at positions 1, 5, and 9 have been designed from the pyrano[3,2-c]quinoline derivative 1, a weak inhibitor of acetylcholinesterase (AChE) with predicted ability to bind to the AChE peripheral anionic site (PAS), at the entrance of the catalytic gorge. Fourteen novel benzonaphthyridines have been synthesized through synthetic sequences involving as the key step a multicomponent Povarov reaction between an aldehyde, an aniline and an enamine or an enamide as the activated alkene. The novel compounds have been tested against Electrophorus electricus AChE (EeAChE), human recombinant AChE (hAChE), and human serum butyrylcholinesterase (hBChE), and their brain penetration has been assessed using the PAMPA-BBB assay. Also, the mechanism of AChE inhibition of the most potent compounds has been thoroughly studied by kinetic studies, a propidium displacement assay, and molecular modelling. We have found that a seemingly small structural change such as a double O → NH bioisosteric replacement from the hit 1 to 16a results in a dramatic increase of EeAChE and hAChE inhibitory activities (>217- and >154-fold, respectively), and in a notable increase in hBChE inhibitory activity (> 11-fold), as well. An optimized binding at the PAS besides additional interactions with AChE midgorge residues seem to account for the high hAChE inhibitory potency of 16a (IC50 = 65 nM), which emerges as an interesting anti-Alzheimer lead compound with potent dual AChE and BChE inhibitory activities.

Empirical Tests of Asset Pricing Models in Finnish Stock Market

Tämän tutkielman tavoitteena on selvittää mitkä riskitekijät vaikuttavat osakkeiden tuottoihin. Arvopapereina käytetään kuutta portfoliota, jotka ovat jaoteltu markkina-arvon mukaan. Aikaperiodi on vuoden 1987 alusta vuoden 2004 loppuun. Malleina käytetään pääomamarkkinoiden hinnoittelumallia, arbitraasihinnoitteluteoriaa sekä kulutuspohjaista pääomamarkkinoiden hinnoittelumallia. Riskifaktoreina kahteen ensimmäiseen malliin käytetään markkinariskiä sekä makrotaloudellisia riskitekijöitä. Kulutuspohjaiseen pääomamarkkinoiden hinnoinoittelumallissa keskitytään estimoimaan kuluttajien riskitottumuksia sekä diskonttaustekijää, jolla kuluttaja arvostavat tulevaisuuden kulutusta. Tämä työ esittelee momenttiteorian, jolla pystymme estimoimaan lineaarisia sekä epälineaarisia yhtälöitä. Käytämme tätä menetelmää testaamissamme malleissa. Yhteenvetona tuloksista voidaan sanoa, että markkinabeeta onedelleen tärkein riskitekijä, mutta löydämme myös tukea makrotaloudellisille riskitekijöille. Kulutuspohjainen mallimme toimii melko hyvin antaen teoreettisesti hyväksyttäviä arvoja.