956 resultados para Multinomial logit models with random coefficients (RCL)
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Three types of forecasts of the total Australian production of macadamia nuts (t nut-in-shell) have been produced early each year since 2001. The first is a long-term forecast, based on the expected production from the tree census data held by the Australian Macadamia Society, suitably scaled up for missing data and assumed new plantings each year. These long-term forecasts range out to 10 years in the future, and form a basis for industry and market planning. Secondly, a statistical adjustment (termed the climate-adjusted forecast) is made annually for the coming crop. As the name suggests, climatic influences are the dominant factors in this adjustment process, however, other terms such as bienniality of bearing, prices and orchard aging are also incorporated. Thirdly, industry personnel are surveyed early each year, with their estimates integrated into a growers and pest-scouts forecast. Initially conducted on a 'whole-country' basis, these models are now constructed separately for the six main production regions of Australia, with these being combined for national totals. Ensembles or suites of step-forward regression models using biologically-relevant variables have been the major statistical method adopted, however, developing methodologies such as nearest-neighbour techniques, general additive models and random forests are continually being evaluated in parallel. The overall error rates average 14% for the climate forecasts, and 12% for the growers' forecasts. These compare with 7.8% for USDA almond forecasts (based on extensive early-crop sampling) and 6.8% for coconut forecasts in Sri Lanka. However, our somewhatdisappointing results were mainly due to a series of poor crops attributed to human reasons, which have now been factored into the models. Notably, the 2012 and 2013 forecasts averaged 7.8 and 4.9% errors, respectively. Future models should also show continuing improvement, as more data-years become available.
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Mass Customization (MC) is not a mature business strategy and hence it is not clear that a single or small group of operational models are dominating. Companies tend to approach MC from either a mass production or a customization origin and this in itself gives reason to believe that several operational models will be observable. This paper reviews actual and theoretical fulfilment systems that enterprises could apply when offering a pre-engineered catalogue of customizable products and options. Issues considered are: How product flows are structured in relation to processes, inventories and decoupling point(s); - Characteristics of the OF process that inhibit or facilitate fulfilment; - The logic of how products are allocated to customers; - Customer factors that influence OF process design and operation. Diversity in the order fulfilment structures is expected and is found in the literature. The review has identified four structural forms that have been used in a Catalogue MC context: - fulfilment from stock; - fulfilment from a single fixed decoupling point; - fulfilment from one of several fixed decoupling points; - fulfilment from several locations, with floating decoupling points. From the review it is apparent that producers are being imaginative in coping with the demands of high variety, high volume, customization and short lead times. These demands have encouraged the relationship between product, process and customer to be re-examined. Not only has this strengthened interest in commonality and postponement, but, as is reported in the paper, has led to the re-engineering of the order fulfilment process to create models with multiple fixed decoupling points and the floating decoupling point system
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In this work, the relationship between diameter at breast height (d) and total height (h) of individual-tree was modeled with the aim to establish provisory height-diameter (h-d) equations for maritime pine (Pinus pinaster Ait.) stands in the Lomba ZIF, Northeast Portugal. Using data collected locally, several local and generalized h-d equations from the literature were tested and adaptations were also considered. Model fitting was conducted by using usual nonlinear least squares (nls) methods. The best local and generalized models selected, were also tested as mixed models applying a first-order conditional expectation (FOCE) approximation procedure and maximum likelihood methods to estimate fixed and random effects. For the calibration of the mixed models and in order to be consistent with the fitting procedure, the FOCE method was also used to test different sampling designs. The results showed that the local h-d equations with two parameters performed better than the analogous models with three parameters. However a unique set of parameter values for the local model can not be used to all maritime pine stands in Lomba ZIF and thus, a generalized model including covariates from the stand, in addition to d, was necessary to obtain an adequate predictive performance. No evident superiority of the generalized mixed model in comparison to the generalized model with nonlinear least squares parameters estimates was observed. On the other hand, in the case of the local model, the predictive performance greatly improved when random effects were included. The results showed that the mixed model based in the local h-d equation selected is a viable alternative for estimating h if variables from the stand are not available. Moreover, it was observed that it is possible to obtain an adequate calibrated response using only 2 to 5 additional h-d measurements in quantile (or random) trees from the distribution of d in the plot (stand). Balancing sampling effort, accuracy and straightforwardness in practical applications, the generalized model from nls fit is recommended. Examples of applications of the selected generalized equation to the forest management are presented, namely how to use it to complete missing information from forest inventory and also showing how such an equation can be incorporated in a stand-level decision support system that aims to optimize the forest management for the maximization of wood volume production in Lomba ZIF maritime pine stands.
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Introduction: The use of drugs to enhance recovery (“rehabilitation pharmacology”) has been assessed. Amphetamine can improve outcome in experimental models of stroke, and several small clinical trials have assessed its use in stroke. Methods: Electronic searches were performed to identify randomised controlled trials of amphetamine in stroke (ischaemic or haemorrhagic). Outcomes included functional outcome (assessed as combined death or disability/dependency), safety (death) and haemodynamic measures. Data were analysed as dichotomous or continuous outcomes, using odds ratios (OR), weighted or standardised mean difference, (WMD or SMD) using random-effects models with 95% confidence intervals (95% CI); statistical heterogeneity was assessed. Results: Eleven completed trials (n=329) were identified. Treatment with amphetamine was associated with non-significant trends to increased death (OR 2.78 (95% CI, 0.75– 10.23), n=329, 11 trials) and improved motor scores (WMD 3.28 (95% CI −0.48–7.04) n=257, 9 trials) but had no effect on the combined outcome of death and dependency (OR 1.15 (95% CI 0.65–2.06, n=206, 5 trials). Amphetamine increased systolic blood pressure (WMD 9.3 mmHg, 95% CI 3.3–15.3, n=106, 3 trials) and heart rate (WMD 7.6 beats per minute (bpm), 95% CI 1.8–13.4, n=106, 3 trials). Despite variations in treatment regimes, outcomes and follow-up duration there was no evidence of significant heterogeneity or publication bias. Conclusion: No evidence exists at present to support the use of amphetamine after stroke. Despite a trend to improved motor function, doubts remain over
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This work aims to investigate the relationship between the entrepreneurship and the incidence of bureaucratic corruption in the states of Brazil and Federal District. The main hypothesis of this study is that the opening of a business in Brazilian states is negatively affected by the incidence of corruption. The theoretical reference is divided into Entrepreneurship and bureaucratic corruption, with an emphasis on materialistic perspective (objectivist) of entrepreneurship and the effects of bureaucratic corruption on entrepreneurial activity. By the regression method with panel data, we estimated the models with pooled data and fixed and random effects. To measure corruption, I used the General Index of Corruption for the Brazilian states (BOLL, 2010), and to represent entrepreneurship, firm entry per capita by state. Tests (Chow, Hausman and Breusch-Pagan) indicate that the random effects model is more appropriate, and the preliminary results indicate a positive impact of bureaucratic corruption on entrepreneurial activity, contradicting the hypothesis expected and found in previous articles to Brazil, and corroborating the proposition of Dreher and Gassebner (2011) that, in countries with high regulation, bureaucratic corruption can be grease in the wheels of entrepreneurship
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Agroforestry has large potential for carbon (C) sequestration while providing many economical, social, and ecological benefits via its diversified products. Airborne lidar is considered as the most accurate technology for mapping aboveground biomass (AGB) over landscape levels. However, little research in the past has been done to study AGB of agroforestry systems using airborne lidar data. Focusing on an agroforestry system in the Brazilian Amazon, this study first predicted plot-level AGB using fixed-effects regression models that assumed the regression coefficients to be constants. The model prediction errors were then analyzed from the perspectives of tree DBH (diameter at breast height)?height relationships and plot-level wood density, which suggested the need for stratifying agroforestry fields to improve plot-level AGB modeling. We separated teak plantations from other agroforestry types and predicted AGB using mixed-effects models that can incorporate the variation of AGB-height relationship across agroforestry types. We found that, at the plot scale, mixed-effects models led to better model prediction performance (based on leave-one-out cross-validation) than the fixed-effects models, with the coefficient of determination (R2) increasing from 0.38 to 0.64. At the landscape level, the difference between AGB densities from the two types of models was ~10% on average and up to ~30% at the pixel level. This study suggested the importance of stratification based on tree AGB allometry and the utility of mixed-effects models in modeling and mapping AGB of agroforestry systems.
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Tradicionalmente, los ortodoncistas han realizado las mediciones dentales en los modelos de yeso, pero los avances tecnológicos permiten ahora a los ortodoncistas realizar esas mediciones en los modelos digitales. El propósito de este estudio fue comparar la fiabilidad y reproducibilidad de las medidas de los tamaños dentarios y las arcadas dentarias entre el método manual y los métodos digitales 3D obtenidos por un escáner intraoral CEREC Omnicam (Sirona Dental Systems) y dos escáneres extraorales: inEos X5 (Sirona Dental Systems) y Dental Scanner SMART (Open Technologies). Un modelo de yeso, un escaneado intraoral y dos modelos digitales con un escáner extraoral fueron realizadas para cada uno de los 20 sujetos. Las medidas de los tamaños dentarios, la distancia intercanina y la distancia intermolar de los modelos digitales se compararon con los correspondientes modelos de yeso (estándar de oro) Se utilizó el test de ANOVA para establecer la fiabilidad entre los cuatro métodos y el coeficiente de correlación intraclase fue calculado para determinar la reproducibilidad intra- e inter-examinador. Los resultados encontrados fueron que no existieron diferencias estadísticamente significativas entre las medidas hechas directamente en los modelos de yeso y los modelos digitales. Los coeficientes de correlación intraclase tanto intra- e inter-examinador fue alto y considerado bueno para los cuatro métodos de medición. CCI> 0.90. Se concluyó que las mediciones en los modelos digitales obtenidos con un escáner extraoral e intraoral son fiables y reproducibles
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Free-riding behaviors exist in tourism and they should be analyzed from a comprehensive perspective; while the literature has mainly focused on free riders operating in a destination, the destinations themselves might also free ride when they are under the umbrella of a collective brand. The objective of this article is to detect potential free-riding destinations by estimating the contribution of the different individual destinations to their collective brands, from the point of view of consumer perception. We argue that these individual contributions can be better understood by reflecting the various stages that tourists follow to reach their final decision. A hierarchical choice process is proposed in which the following choices are nested (not independent): “whether to buy,” “what collective brand to buy,” and “what individual brand to buy.” A Mixed Logit model confirms this sequence, which permits estimation of individual contributions and detection of free riders.
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Dissertação (mestrado)—Universidade de Brasília, Departamento de Administração, Programa de Pós-graduação em Administração, 2016.
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The present study provides a methodology that gives a predictive character the computer simulations based on detailed models of the geometry of a porous medium. We using the software FLUENT to investigate the flow of a viscous Newtonian fluid through a random fractal medium which simplifies a two-dimensional disordered porous medium representing a petroleum reservoir. This fractal model is formed by obstacles of various sizes, whose size distribution function follows a power law where exponent is defined as the fractal dimension of fractionation Dff of the model characterizing the process of fragmentation these obstacles. They are randomly disposed in a rectangular channel. The modeling process incorporates modern concepts, scaling laws, to analyze the influence of heterogeneity found in the fields of the porosity and of the permeability in such a way as to characterize the medium in terms of their fractal properties. This procedure allows numerically analyze the measurements of permeability k and the drag coefficient Cd proposed relationships, like power law, for these properties on various modeling schemes. The purpose of this research is to study the variability provided by these heterogeneities where the velocity field and other details of viscous fluid dynamics are obtained by solving numerically the continuity and Navier-Stokes equations at pore level and observe how the fractal dimension of fractionation of the model can affect their hydrodynamic properties. This study were considered two classes of models, models with constant porosity, MPC, and models with varying porosity, MPV. The results have allowed us to find numerical relationship between the permeability, drag coefficient and the fractal dimension of fractionation of the medium. Based on these numerical results we have proposed scaling relations and algebraic expressions involving the relevant parameters of the phenomenon. In this study analytical equations were determined for Dff depending on the geometrical parameters of the models. We also found a relation between the permeability and the drag coefficient which is inversely proportional to one another. As for the difference in behavior it is most striking in the classes of models MPV. That is, the fact that the porosity vary in these models is an additional factor that plays a significant role in flow analysis. Finally, the results proved satisfactory and consistent, which demonstrates the effectiveness of the referred methodology for all applications analyzed in this study.
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Myocardial fibrosis detected via delayed-enhanced magnetic resonance imaging (MRI) has been shown to be a strong indicator for ventricular tachycardia (VT) inducibility. However, little is known regarding how inducibility is affected by the details of the fibrosis extent, morphology, and border zone configuration. The objective of this article is to systematically study the arrhythmogenic effects of fibrosis geometry and extent, specifically on VT inducibility and maintenance. We present a set of methods for constructing patient-specific computational models of human ventricles using in vivo MRI data for patients suffering from hypertension, hypercholesterolemia, and chronic myocardial infarction. Additional synthesized models with morphologically varied extents of fibrosis and gray zone (GZ) distribution were derived to study the alterations in the arrhythmia induction and reentry patterns. Detailed electrophysiological simulations demonstrated that (1) VT morphology was highly dependent on the extent of fibrosis, which acts as a structural substrate, (2) reentry tended to be anchored to the fibrosis edges and showed transmural conduction of activations through narrow channels formed within fibrosis, and (3) increasing the extent of GZ within fibrosis tended to destabilize the structural reentry sites and aggravate the VT as compared to fibrotic regions of the same size and shape but with lower or no GZ. The approach and findings represent a significant step toward patient-specific cardiac modeling as a reliable tool for VT prediction and management of the patient. Sensitivities to approximation nuances in the modeling of structural pathology by image-based reconstruction techniques are also implicated.
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Saltwater recreational fishing (SRF) in Portugal was for a long time an open-access activity, without restrictions of any kind. Restrictions to control the recreational harvest were first implemented in 2006 and were highly criticized by the angler community, for being highly restrictive and lacking scientific support. The present study aimed to obtain socio-economic data on the recreational shore anglers and gauge their perceptions about recreational fishing regulations and the newly implemented restrictions in Portugal. Roving creel surveys were conducted along the south and south-west coasts of Portugal, during pre and post regulation periods (2006-2007). A total of 1298 valid face-to-face interviews were conducted. Logit models were fitted to identify which characteristics influence anglers' perceptions about recreational fishing regulations. The majority of the interviewed anglers was aware and agreed with the existence of recreational fishing regulations. However, most were against the recreational fishing regulations currently in place. The logit models estimates revealed that Portuguese anglers with a higher level of formal education and income are more likely to agree with the existence of recreational fishing regulations. In contrast, anglers who perceive that more limitations and a better enforcement of commercial fishing would improve fishing in the area are less likely to agree with the existence of SRF regulations. The findings from this study will contribute to inform decision-makers about anglers' potential behaviour towards the new and future regulations. Although the existence of fishing regulations is a good starting point for effective management, the lack of acceptance and detailed knowledge of the regulations in place by fishers may result in lack of compliance, and ultimately hinder the success of recreational fishing regulations in Portugal. (C) 2013 Elsevier Ltd. All rights reserved.
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This study focuses on the learning and teaching of Reading in English as a Foreign Language (REFL), in Libya. The study draws on an action research process in which I sought to look critically at students and teachers of English as a Foreign Language (EFL) in Libya as they learned and taught REFL in four Libyan research sites. The Libyan EFL educational system is influenced by two main factors: the method of teaching the Holy-Quran and the long-time ban on teaching EFL by the former Libyan regime under Muammar Gaddafi. Both of these factors have affected the learning and teaching of REFL and I outline these contextual factors in the first chapter of the thesis. This investigation, and the exploration of the challenges that Libyan university students encounter in their REFL, is supported by attention to reading models. These models helped to provide an analytical framework and starting point for understanding the many processes involved in reading for meaning and in reading to satisfy teacher instructions. The theoretical framework I adopted was based, mainly and initially, on top-down, bottom-up, interactive and compensatory interactive models. I drew on these models with a view to understanding whether and how the processes of reading described in the models could be applied to the reading of EFL students and whether these models could help me to better understand what was going on in REFL. The diagnosis stage of the study provided initial data collected from four Libyan research sites with research tools including video-recorded classroom observations, semi-structured interviews with teachers before and after lesson observation, and think-aloud protocols (TAPs) with 24 students (six from each university) in which I examined their REFL reading behaviours and strategies. This stage indicated that the majority of students shared behaviours such as reading aloud, reading each word in the text, articulating the phonemes and syllables of words, or skipping words if they could not pronounce them. Overall this first stage indicated that alternative methods of teaching REFL were needed in order to encourage ‘reading for meaning’ that might be based on strategies related to eventual interactive reading models adapted for REFL. The second phase of this research project was an Intervention Phase involving two team-teaching sessions in one of the four stage one universities. In each session, I worked with the teacher of one group to introduce an alternative method of REFL. This method was based on teaching different reading strategies to encourage the students to work towards an eventual interactive way of reading for meaning. A focus group discussion and TAPs followed the lessons with six students in order to discuss the 'new' method. Next were two video-recorded classroom observations which were followed by an audio-recorded discussion with the teacher about these methods. Finally, I conducted a Skype interview with the class teacher at the end of the semester to discuss any changes he had made in his teaching or had observed in his students' reading with respect to reading behaviour strategies, and reactions and performance of the students as he continued to use the 'new' method. The results of the intervention stage indicate that the teacher, perhaps not surprisingly, can play an important role in adding to students’ knowledge and confidence and in improving their REFL strategies. For example, after the intervention stage, students began to think about the title, and to use their own background knowledge to comprehend the text. The students employed, also, linguistic strategies such as decoding and, above all, the students abandoned the behaviour of reading for pronunciation in favour of reading for meaning. Despite the apparent efficacy of the alternative method, there are, inevitably, limitations related to the small-scale nature of the study and the time I had available to conduct the research. There are challenges, too, related to the students’ first language, the idiosyncrasies of the English language, the teacher training and continuing professional development of teachers, and the continuing political instability of Libya. The students’ lack of vocabulary and their difficulties with grammatical functions such as phrasal and prepositional verbs, forms which do not exist in Arabic, mean that REFL will always be challenging. Given such constraints, the ‘new’ methods I trialled and propose for adoption can only go so far in addressing students’ difficulties in REFL. Overall, the study indicates that the Libyan educational system is underdeveloped and under resourced with respect to REFL. My data indicates that the teacher participants have received little to no professional developmental that could help them improve their teaching in REFL and skills in teaching EFL. These circumstances, along with the perennial problem of large but varying class sizes; student, teacher and assessment expectations; and limited and often poor quality resources, affect the way EFL students learn to read in English. Against this background, the thesis concludes by offering tentative conclusions; reflections on the study, including a discussion of its limitations, and possible recommendations designed to improve REFL learning and teaching in Libyan universities.
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In recent years, 3D bioprinting has emerged as an innovative and versatile technology able to produce in vitro models that resemble the native spatial organization of organ tissues, by employing or more bioinks composed of various types of cells suspended in hydrogels. Natural and semi-synthetic hydrogels are extensively used for 3D bioprinting models since they can mimic the natural composition of the tissues, they are biocompatible and bioactive with customizable mechanical properties, allowing to support cell growth. The possibility to tailor hydrogels mechanical properties by modifying the chemical structures to obtain photo-crosslinkable materials, while maintaining their biocompatibility and biomimicry, make their use versatile and suitable to simulate a broad spectrum of physiological features. In this PhD Thesis, 3D bioprinted in vitro models with tailored mechanical properties and physiologically-like features were fabricated. AlgMa-based bioinks were employed to produce a living platform with gradient stiffness, with the aim to create an easy to handle and accessible biological tool to evaluate mechanobiology. In addition, GelMa, collagen and IPN of GelMa and collagen were used as bioinks to fabricate a proof-of-concept of 3D intestinal barrier, which include multiple cell components and multi-layered structure. A useful rheological guide to drive users to the selection of the suitable bioinks for 3D bioprinting and to correlate the model’s mechanical stability after crosslinking is proposed. In conclusion, a platform capable to reproduce models with physiological gradient stiffness was developed and the fabrication of 3D bioprinted intestinal models displaying a good hierarchical structure and cells composition was fully reported and successfully achieved. The good biological results obtained demonstrated that 3D bioprinting can be used for the fabrications of 3D models and that the mechanical properties of the external environment plays a key role on the cell pathways, viability and morphology.
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Hematological cancers are a heterogeneous family of diseases that can be divided into leukemias, lymphomas, and myelomas, often called “liquid tumors”. Since they cannot be surgically removable, chemotherapy represents the mainstay of their treatment. However, it still faces several challenges like drug resistance and low response rate, and the need for new anticancer agents is compelling. The drug discovery process is long-term, costly, and prone to high failure rates. With the rapid expansion of biological and chemical "big data", some computational techniques such as machine learning tools have been increasingly employed to speed up and economize the whole process. Machine learning algorithms can create complex models with the aim to determine the biological activity of compounds against several targets, based on their chemical properties. These models are defined as multi-target Quantitative Structure-Activity Relationship (mt-QSAR) and can be used to virtually screen small and large chemical libraries for the identification of new molecules with anticancer activity. The aim of my Ph.D. project was to employ machine learning techniques to build an mt-QSAR classification model for the prediction of cytotoxic drugs simultaneously active against 43 hematological cancer cell lines. For this purpose, first, I constructed a large and diversified dataset of molecules extracted from the ChEMBL database. Then, I compared the performance of different ML classification algorithms, until Random Forest was identified as the one returning the best predictions. Finally, I used different approaches to maximize the performance of the model, which achieved an accuracy of 88% by correctly classifying 93% of inactive molecules and 72% of active molecules in a validation set. This model was further applied to the virtual screening of a small dataset of molecules tested in our laboratory, where it showed 100% accuracy in correctly classifying all molecules. This result is confirmed by our previous in vitro experiments.