Predicting chick body mass by artificial intelligence-based models

The objective of this work was to develop, validate, and compare 190 artificial intelligence-based models for predicting the body mass of chicks from 2 to 21 days of age subjected to different duration and intensities of thermal challenge. The experiment was conducted inside four climate-controlled wind tunnels using 210 chicks. A database containing 840 datasets (from 2 to 21-day-old chicks) - with the variables dry-bulb air temperature, duration of thermal stress (days), chick age (days), and the daily body mass of chicks - was used for network training, validation, and tests of models based on artificial neural networks (ANNs) and neuro-fuzzy networks (NFNs). The ANNs were most accurate in predicting the body mass of chicks from 2 to 21 days of age after they were subjected to the input variables, and they showed an R² of 0.9993 and a standard error of 4.62 g. The ANNs enable the simulation of different scenarios, which can assist in managerial decision-making, and they can be embedded in the heating control systems.

Field data and prediction models of pesticide spray drift on coffee crop

The objective of this work was to generate drift curves from pesticide applications on coffee plants and to compare them with two European drift-prediction models. The used methodology is based on the ISO 22866 standard. The experimental design was a randomized complete block with ten replicates in a 2x20 split-plot arrangement. The evaluated factors were: two types of nozzles (hollow cone with and without air induction) and 20 parallel distances to the crop line outside of the target area, spaced at 2.5 m. Blotting papers were used as a target and placed in each of the evaluated distances. The spray solution was composed of water+rhodamine B fluorescent tracer at a concentration of 100 mg L-1, for detection by fluorimetry. A spray volume of 400 L ha-1 was applied using a hydropneumatic sprayer. The air-induction nozzle reduces the drift up to 20 m from the treated area. The application with the hollow cone nozzle results in 6.68% maximum drift in the nearest collector of the treated area. The German and Dutch models overestimate the drift at distances closest to the crop, although the Dutch model more closely approximates the drift curves generated by both spray nozzles.

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.

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.

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.

Géotourisme et utilisation de sites naturels d'intérêt pour les sciences de la Terre: les régions de Crans-Montana-Sierre (Valais, Alpes suisses) et Chamonix-Mont-Blanc (Haute-Savoie, Alpes françaises)

Résumé : Au travers de l'étude des régions de Crans-Montana-Sierre (Valais, Suisse) et de Chamonix-Mont-Blanc (Haute-Savoie, France), cette recherche considère les liens existants entre activités touristiques et sciences de la Terre. Ainsi, les sites géologiques et géomorphologiques pris en compte sont perçus comme ayant non seulement une valeur scientifique, mais aussi un intérêt scénique, culturel et économique. D'un point de vue (géo)touristique, différents modèles d'analyse sont proposés pour expliciter les composantes de l'offre et de la demande et comprendre le cycle de vie des objets étudiés. L'offre que constituent ces sites est tout d'abord présentée afin d'évaluer leurs différents potentiels, ainsi que l'utilisation spatio-temporelle, didactique et économique qui en est faite. Ensuite, les logiques d'acteurs sont analysées au travers des phases de valorisation, d'exploitation et de transformation, dans le but de comprendre les facteurs et les projets d'utilisation les concernant. Enfin, la demande des différents publics cibles, de même que leurs caractéristiques socio-touristiques et (géo)didactiques, sont discutées. Pour ce faire, des méthodes d'inventaire, d'évaluation, d'entretien et de questionnaire ont été utilisées, à différentes échelles d'analyse. On constate d'abord que le pôle des valeurs scénique et économique présente une plus forte mise à contribution, par rapport à l'utilisation didactique. De plus, le niveau de protection des sites ne restreint généralement pas leur exploitation, au contraire du facteur risque. Du point de vue des publics cibles, une forte demande d'explications didactiques est exprimée, s'orientant vers une approche multithématique des potentiels à mettre en valeur; des biens et services de base sont ainsi demandés. Enfin, force est de constater que seuls de grands projets peuvent rendre les activités (géo)touristiques rentables. A l'avenir, sachant que le géotourisme peut répondre à une demande touristique liée au rêve et à l'émotion, l'approche de l'offre devrait intégrer une réflexion en didactique des sciences de la Terre, d'autant que cette forme de tourisme tend à devenir une composante du développement économique régional, notamment en dehors de la saison d'hiver. Idéalement, l'utilisation touristique de la géodiversité devrait s'accompagner d'une politique de protection dynamique, combinant préservation et mise en valeur. A terme, le but ultime de cette entreprise est notamment d'élargir la notion de patrimoine culturel, pour favoriser une approche transdisciplinaire du paysage Abstract : Based on the study of the areas of Crans-Montana-Sierre (Valais, Switzerland) and Chamonix-Mont-Blanc (Haute-Savoie, France), this study considers the links between tourism activities and Earth science. Thus, the studied geological and geomorphological sites have not only a scientific va1ue, but also scenic, cultural and economic value. From a point of view of tourism, different models of analysis are examined in order to explain the components of the supply and the demand, and to understand the life cycles of the considered objects. The primary product of these sites is first presented, in order to assess their different potential as well as their didactic, economic, spatial and temporal use. The stakeholders' behaviour is then analysed to understand the factors and projected use, with the help of the optimisation, exploitation and transformation phases. Finally, the demand of the different target markets as well as their socio-tourist and (geo)didactic characteristics are discussed. To complete this study, methods of census, assessment, interviewing and questionnaire surveying are used, at different scales of analysis. The main results appear to demonstrate that the scenic and economic values present a higher value relative to the didactic use. Moreover, the required conservation measures for the studied sites do not generally restrict the use, on the contrary to the "risk" factor. From the point of view of the target market, a relevant requirement for explanatory commentary is expressed and tends towards an approach optimising different themes to utilise potential; basic popular goods and services are also requested. Finally, it is clearly demonstrated that only relevant projects are able to make this kind of activity profitable. For the future, geotourism may be marketed to a tourist demand for imagination and emotion. Consequently, the product approach should integrate a reflection on Earth science popularisation given that this branch of tourism tends to receive a component of the economic and regional development, notably during the summer period. However, the use of geodiversity should include a concept of dynamic management, taking into account conservation as well as tourism development. Thus, the final aim of this process is to r,r'iden the notion of cultural heritage, in order to stimulate a multidisciplinary approach to the landscape.