Susceptible-infected-recovered and susceptible-exposed-infected models

Two stochastic epidemic lattice models, the susceptible-infected-recovered and the susceptible-exposed-infected models, are studied on a Cayley tree of coordination number k. The spreading of the disease in the former is found to occur when the infection probability b is larger than b(c) = k/2(k - 1). In the latter, which is equivalent to a dynamic site percolation model, the spreading occurs when the infection probability p is greater than p(c) = 1/(k - 1). We set up and solve the time evolution equations for both models and determine the final and time-dependent properties, including the epidemic curve. We show that the two models are closely related by revealing that their relevant properties are exactly mapped into each other when p = b/[k - (k - 1) b]. These include the cluster size distribution and the density of individuals of each type, quantities that have been determined in closed forms.

Conceptual Product Development in Small Corporations

The main objective of the thesis “Conceptual Product Development in Small Corporations” is by the use of a case study test the MFD™-method (Erixon G. , 1998) combined with PMM in a product development project. (Henceforth called MFD™/PMM-method). The MFD™/PMM-method used for documenting and controlling a product development project has since it was introduced been used in several industries and projects. The method has been proved to be a good way of working with the early stages of product development, however, there are almost only projects carried out on large industries which means that there are very few references to how the MFD™/PMM-method works in a small corporation. Therefore, was the case study in the thesis “Conceptual Product Development in Small Corporations” carried out in a small corporation to find out whether the MFD™/PMM-method also can be applied and used in such a corporation.The PMM was proposed in a paper presented at Delft University of Technology in Holland 1998 by the author and Gunnar Erixon. (See appended paper C: The chart of modular function deployment.) The title “The chart of modular function deployment” was later renamed as PMM, Product Management Map. (Sweden PreCAD AB, 2000). The PMM consists of a QFD-matrix linked to MIM (Module Indication Matrix) via a coupling matrix which makes it possible to make an unbroken chain from the customer domain to the designed product/modules. The PMM makes it easy to correct omissions made in creating new products and modules.In the thesis “Conceptual Product Development in Small Corporations” the universal MFD™/PMM-method has been adapted by the author to three models of product development; original-, evolutionary- and incremental development.The evolutionary adapted MFD™/PMM-method was tested as a case study at Atlings AB in the community Ockelbo. Atlings AB is a small corporation with a total number of 50 employees and an annual turnover of 9 million €. The product studied at the corporation was a steady rest for supporting long shafts in turning. The project team consisted of management director, a sales promoter, a production engineer, a design engineer and a workshop technician, the author as team leader and a colleague from Dalarna University as discussion partner. The project team has had six meetings.The project team managed to use MFD™ and to make a complete PMM of the studied product. There were no real problems occurring in the project work, on the contrary the team members worked very well in the group, having ideas how to improve the product. Instead, the challenge for a small company is how to work with the MFD™/PMM-method in the long run! If the MFD™/PMM-method is to be a useful tool for the company it needs to be used continuously and that requires financial and personnel resources. One way for the company to overcome the probable lack of recourses regarding capital and personnel is to establish a good cooperation with a regional university or a development centre.

Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

This study presents an approach to combine uncertainties of the hydrological model outputs predicted from a number of machine learning models. The machine learning based uncertainty prediction approach is very useful for estimation of hydrological models' uncertainty in particular hydro-metrological situation in real-time application [1]. In this approach the hydrological model realizations from Monte Carlo simulations are used to build different machine learning uncertainty models to predict uncertainty (quantiles of pdf) of the a deterministic output from hydrological model . Uncertainty models are trained using antecedent precipitation and streamflows as inputs. The trained models are then employed to predict the model output uncertainty which is specific for the new input data. We used three machine learning models namely artificial neural networks, model tree, locally weighted regression to predict output uncertainties. These three models produce similar verification results, which can be improved by merging their outputs dynamically. We propose an approach to form a committee of the three models to combine their outputs. The approach is applied to estimate uncertainty of streamflows simulation from a conceptual hydrological model in the Brue catchment in UK and the Bagmati catchment in Nepal. The verification results show that merged output is better than an individual model output. [1] D. L. Shrestha, N. Kayastha, and D. P. Solomatine, and R. Price. Encapsulation of parameteric uncertainty statistics by various predictive machine learning models: MLUE method, Journal of Hydroinformatic, in press, 2013.

Real-Time Control Of Floods Along The Demer River, Belgium, By Means Of MPC In Combination With GA And A Fast Conceptual River Model

Climate model projections show that climate change will further increase the risk of flooding in many regions of the world. There is a need for climate adaptation, but building new infrastructure or additional retention basins has its limits, especially in densely populated areas where open spaces are limited. Another solution is the more efficient use of the existing infrastructure. This research investigates a method for real-time flood control by means of existing gated weirs and retention basins. The method was tested for the specific study area of the Demer basin in Belgium but is generally applicable. Today, retention basins along the Demer River are controlled by means of adjustable gated weirs based on fixed logic rules. However, because of the high complexity of the system, only suboptimal results are achieved by these rules. By making use of precipitation forecasts and combined hydrological-hydraulic river models, the state of the river network can be predicted. To fasten the calculation speed, a conceptual river model was used. The conceptual model was combined with a Model Predictive Control (MPC) algorithm and a Genetic Algorithm (GA). The MPC algorithm predicts the state of the river network depending on the positions of the adjustable weirs in the basin. The GA generates these positions in a semi-random way. Cost functions, based on water levels, were introduced to evaluate the efficiency of each generation, based on flood damage minimization. In the final phase of this research the influence of the most important MPC and GA parameters was investigated by means of a sensitivity study. The results show that the MPC-GA algorithm manages to reduce the total flood volume during the historical event of September 1998 by 46% in comparison with the current regulation. Based on the MPC-GA results, some recommendations could be formulated to improve the logic rules.

DEMO models based automatic workflow process generation

Nowadays, more than half of the computer development projects fail to meet the final users' expectations. One of the main causes is insufficient knowledge about the organization of the enterprise to be supported by the respective information system. The DEMO methodology (Design and Engineering Methodology for Organizations) has been proved as a well-defined method to specify, through models and diagrams, the essence of any organization at a high level of abstraction. However, this methodology is platform implementation independent, lacking the possibility of saving and propagating possible changes from the organization models to the implemented software, in a runtime environment. The Universal Enterprise Adaptive Object Model (UEAOM) is a conceptual schema being used as a basis for a wiki system, to allow the modeling of any organization, independent of its implementation, as well as the previously mentioned change propagation in a runtime environment. Based on DEMO and UEAOM, this project aims to develop efficient and standardized methods, to enable an automatic conversion of DEMO Ontological Models, based on UEAOM specification into BPMN (Business Process Model and Notation) models of processes, using clear semantics, without ambiguities, in order to facilitate the creation of processes, almost ready for being executed on workflow systems that support BPMN.

Short-term temporal changes of bare soil CO2 fluxes after tillage described by first-order decay models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Ratios of UV, PAR and NIR components to global solar radiation measured at Botucatu site in Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of intra-hippocampal infusion of WAY-100635 on plus-maze behavior in mice - Influence of site of injection and prior test experience

The positive profile of systemically-administered 5-HT(1A) receptor antagonists in several rodent models of anxiolytic activity suggests an important role for postsynaptic 5-HT(1A) receptor mechanisms in anxiety. To test this hypothesis, we investigated the effects of WAY-100635 microinfusions (0, 0.1, 1.0 or 3.0 mug in 0.2 mul) into the dorsal (DH) or ventral (VH) hippocampus an behaviours displayed by male Swiss-Webster mice in the elevated plus-maze. As prior experience is known to modify pharmacological responses in this test, the effects of intra-hippocampal infusions were examined both in maze-naive and maze-experienced subjects. Test videotapes were scored for conventional indices of anxiety (% open arm entries/time) and locomotor activity (closed arm entries), as well as a range of ethological measures (e.g. risk assessment). In maze-naive mice, intra-VH (but not intra-M) infusions of WAY-100635 (3.0 mug but not lower doses) increased open arm exploration and reduced risk assessment. These effects were observed in the absence of significant changes in locomotor activity. In contrast, neither intra-VH nor intra-DH infusions of WAY-100635 altered the behaviour of maze-experienced mice. These Findings suggest that postsynaptic 5-HT(1A) receptors in the ventral (but not dorsal) hippocampus play a significant role both in the mediation of plus-maze anxiety in mice and in experientially-induced alterations in responses to this test. (C) 2002 Elsevier B.V. BY All rights reserved.

In Vivo Models for Measuring Placental Glutatione-S-transferase (GST-P 7-7) Levels: A Suitable Biomarker for Understanding Cancer Pathogenesis

The Glutatione-S-transferases (GSTs) comprise a family of enzymes closely associated with the cell detoxification of xenobiotics. GSTs exist as homo- or heterodimers and have been grouped into at least seven distinct classes. The main function of GSTs is to catalyze the conjugation of reduced glutathione (GSH) to an electrophilic site of a broad range of potentially toxic and carcinogenic compounds, thereby making such compounds less dangerous and enabling their ready-excretion. Placental GST, known as GST-P 7-7, is the main isoform found in normal placental tissue and comprises 67% of the total GST concentration in this tissue. During development, GST-P 7-7 decreases in concentration and is absent in adult tissues. Interestingly, GST-P 7-7 expression has been detected in adult tissues after exposure to carcinogenic agents in several experimental test systems, being considered a reliable biomarker of exposure and susceptibility in early phases of carcinogenesis. In this article, we review a series of studies involving GST-P 7-7 expression as a suitable tool for understanding cancer pathogenesis, especially cancer risk.

Quantitative comparisons and models of time-averaging in bivalve and brachiopod shell accumulations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fish assemblage structure and aquatic pollution in a Brazilian stream: some limitations of diversity indices and models for environmental impact studies

The aim of this study was to describe and quantify the effect of aquatic pollution on the fish assemblage structure of the Corumbatai River (Brazil), by comparing two sites with different water quality characteristics. The results revealed that abundance of individuals was low at the polluted site (B). However, the two sites did not differ significantly in species richness (total and average). This fact contradicts theories stating that portions where the transverse area of the channel is larger should present a higher biological richness. It was also observed that the ichthyofauna of site B had higher evenness, and, consequently, a tendency to a higher diversity than that at site A. This demonstrates that diversity estimates should be used cautiously in environmental impact studies, as they do not necessarily indicate better conditions of communities living in more preserved environments.

To be or not to be . . . a flower? A test of possible cues influencing hunting site selection in subadult females of the crab spider Epicadus heterogaster (Guerin 1812) (Araneae: Thomisidae)

Females of some Thomisidae species are known to use visual and olfactory stimuli to select high quality hunting sites. However, because studies about foraging behavior in this family are concentrated on a few species, the comprehension of the process related to hunting behavior evolution in crab spiders may be biased. In this study we investigated the hunting site selection of a previously unstudied crab spider, Epicadus heterogaster. We performed three experiments to evaluate the hypothesis that subadult females are able to use visual and olfactory stimuli to select hunting sites. In the first experiment, females did not preferentially select flower paper models that matched their body coloration. However, after choosing a model that had the same body color as the spider, they remained on it for longer periods than on models with different colors. In the second experiment, females did not discriminate between flower paper models, natural flower models and crumpled paper models. Females did also not discriminate among different olfactory stimuli in the third experiment. It is possible that subadult females of E. heterogaster need to establish and experience a given hunting site before evaluating its quality. However, it remains to be investigated if they use UV cues to select a foraging area before experiencing it.

First-order decay models to describe soil C-CO2 Loss after rotary tillage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Weather-based prediction of anthracnose severity using artificial neural network models

Data were collected and analysed from seven field sites in Australia, Brazil and Colombia on weather conditions and the severity of anthracnose disease of the tropical pasture legume Stylosanthes scabra caused by Colletotrichum gloeosporioides. Disease severity and weather data were analysed using artificial neural network (ANN) models developed using data from some or all field sites in Australia and/or South America to predict severity at other sites. Three series of models were developed using different weather summaries. of these, ANN models with weather for the day of disease assessment and the previous 24 h period had the highest prediction success, and models trained on data from all sites within one continent correctly predicted disease severity in the other continent on more than 75% of days; the overall prediction error was 21.9% for the Australian and 22.1% for the South American model. of the six cross-continent ANN models trained on pooled data for five sites from two continents to predict severity for the remaining sixth site, the model developed without data from Planaltina in Brazil was the most accurate, with >85% prediction success, and the model without Carimagua in Colombia was the least accurate, with only 54% success. In common with multiple regression models, moisture-related variables such as rain, leaf surface wetness and variables that influence moisture availability such as radiation and wind on the day of disease severity assessment or the day before assessment were the most important weather variables in all ANN models. A set of weights from the ANN models was used to calculate the overall risk of anthracnose for the various sites. Sites with high and low anthracnose risk are present in both continents, and weather conditions at centres of diversity in Brazil and Colombia do not appear to be more conducive than conditions in Australia to serious anthracnose development.

Plant derived alkaloid (-)-cassine induces anti-inflammatory and anti-hyperalgesics effects in both acute and chronic inflammatory and neuropathic pain models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)