Energy and Dynamics of the solar agricultural robot "SolarSprayer"

The main objective of the present study was to design an agricultural robot, which work is based on the generation of the electricity by the solar panel. To achieve the proper operation of the robot according to the assumed working cycle the detailed design of the main equipment was made. By analysing the possible areas of implementation together with developments, the economic forecast was held. As a result a decision about possibility of such device working in agricultural sector was made and the probable topics of the further study were found out.

Images of the future of privacy: A privacy dynamics framework and a causal layered

The future of privacy in the information age is a highly debated topic. In particular, new and emerging technologies such as ICTs and cognitive technologies are seen as threats to privacy. This thesis explores images of the future of privacy among non-experts within the time frame from the present until the year 2050. The aims of the study are to conceptualise privacy as a social and dynamic phenomenon, to understand how privacy is conceptualised among citizens and to analyse ideal-typical images of the future of privacy using the causal layered analysis method. The theoretical background of the thesis combines critical futures studies and critical realism, and the empirical material is drawn from three focus group sessions held in spring 2012 as part of the PRACTIS project. From a critical realist perspective, privacy is conceptualised as a social institution which creates and maintains boundaries between normative circles and preserves the social freedom of individuals. Privacy changes when actors with particular interests engage in technology-enabled practices which challenge current privacy norms. The thesis adopts a position of technological realism as opposed to determinism or neutralism. In the empirical part, the focus group participants are divided into four clusters based on differences in privacy conceptions and perceived threats and solutions. The clusters are fundamentalists, pragmatists, individualists and collectivists. Correspondingly, four ideal-typical images of the future are composed: ‘drift to low privacy’, ‘continuity and benign evolution’, ‘privatised privacy and an uncertain future’, and ‘responsible future or moral decline’. The images are analysed using the four layers of causal layered analysis: litany, system, worldview and myth. Each image has its strengths and weaknesses. The individualistic images tend to be fatalistic in character while the collectivistic images are somewhat utopian. In addition, the images have two common weaknesses: lack of recognition of ongoing developments and simplistic conceptions of privacy based on a dichotomy between the individual and society. The thesis argues for a dialectical understanding of futures as present images of the future and as outcomes of real processes and mechanisms. The first steps in promoting desirable futures are the awareness of privacy as a social institution, the awareness of current images of the future, including their assumptions and weaknesses, and an attitude of responsibility where futures are seen as the consequences of present choices.

The calcium-modulated proteins, S100A1 and S100B, as potential regulators of the dynamics of type III intermediate filaments

The Ca2+-modulated, dimeric proteins of the EF-hand (helix-loop-helix) type, S100A1 and S100B, that have been shown to inhibit microtubule (MT) protein assembly and to promote MT disassembly, interact with the type III intermediate filament (IF) subunits, desmin and glial fibrillary acidic protein (GFAP), with a stoichiometry of 2 mol of IF subunit/mol of S100A1 or S100B dimer and an affinity of 0.5-1.0 µM in the presence of a few micromolar concentrations of Ca2+. Binding of S100A1 and S100B results in inhibition of desmin and GFAP assemblies into IFs and stimulation of the disassembly of preformed desmin and GFAP IFs. S100A1 and S100B interact with a stretch of residues in the N-terminal (head) domain of desmin and GFAP, thereby blocking the head-to-tail process of IF elongation. The C-terminal extension of S100A1 (and, likely, S100B) represents a critical part of the site that recognizes desmin and GFAP. S100B is localized to IFs within cells, suggesting that it might have a role in remodeling IFs upon elevation of cytosolic Ca2+ concentration by avoiding excess IF assembly and/or promoting IF disassembly in vivo. S100A1, that is not localized to IFs, might also play a role in the regulation of IF dynamics by binding to and sequestering unassembled IF subunits. Together, these observations suggest that S100A1 and S100B may be regarded as Ca2+-dependent regulators of the state of assembly of two important elements of the cytoskeleton, IFs and MTs, and, potentially, of MT- and IF-based activities.

Vibrations in Rotating Machinery Arising from Minor Imperfections in Component Geometries

Vibrations in machines can cause noise, decrease the performance, or even damage the machine. Vibrations appear if there is a source of vibration that excites the system. In the worst case scenario, the excitation frequency coincides with the natural frequency of the machine causing resonance. Rotating machines are a machine type, where the excitation arises from the machine itself. The excitation originates from the mass imbalance in the rotating shaft, which always exists in machines that are manufactured using conventional methods. The excitation has a frequency that is dependent on the rotational speed of the machine. The rotating machines in industrial use are usually designed to rotate at a constant rotational speed, the case where the resonances can be easily avoided. However, the machines that have a varying operational speed are more problematic due to a wider range of frequencies that have to be avoided. Vibrations, which frequencies equal to rotational speed frequency of the machine are widely studied and considered in the typical machine design process. This study concentrates on vibrations, which arise from the excitations having frequencies that are multiples of the rotational speed frequency. These vibrations take place when there are two or more excitation components in a revolution of a rotating shaft. The dissertation introduces four studies where three kinds of machines are experiencing vibrations caused by different excitations. The first studied case is a directly driven permanent magnet generator used in a wind power plant. The electromagnetic properties of the generator cause harmonic excitations in the system. The dynamic responses of the generator are studied using the multibody dynamics formulation. In another study, the finite element method is used to study the vibrations of a magnetic gear due to excitations, which frequencies equal to the rotational speed frequency. The objective is to study the effects of manufacturing and assembling inaccuracies. Particularly, the eccentricity of the rotating part with respect to non-rotating part is studied since the eccentric operation causes a force component in the direction of the shortest air gap. The third machine type is a tube roll of a paper machine, which is studied while the tube roll is supported using two different structures. These cases are studied using different formulations. In the first case, the tube roll is supported by spherical roller bearings, which have some wavinesses on the rolling surfaces. Wavinesses cause excitations to the tube roll, which starts to resonate at the frequency that is a half of the first natural frequency. The frequency is in the range where the machine normally operates. The tube roll is modeled using the finite element method and the bearings are modeled as nonlinear forces between the tube roll and the pedestals. In the second case studied, the tube roll is supported by freely rotating discs, which wavinesses are also measured. The above described phenomenon is captured as well in this case, but the simulation methodology is based on the flexible multibody dynamics formulation. The simulation models that are used in both of the last two cases studied are verified by measuring the actual devices and comparing the simulated and measured results. The results show good agreement.

Heterogeneous mass transfer in fluidized beds by computational fluid dynamics

The main objective of this research is to estimate and characterize heterogeneous mass transfer coefficients in bench- and pilot-scale fluidized bed processes by the means of computational fluid dynamics (CFD). A further objective is to benchmark the heterogeneous mass transfer coefficients predicted by fine-grid Eulerian CFD simulations against empirical data presented in the scientific literature. First, a fine-grid two-dimensional Eulerian CFD model with a solid and gas phase has been designed. The model is applied for transient two-dimensional simulations of char combustion in small-scale bubbling and turbulent fluidized beds. The same approach is used to simulate a novel fluidized bed energy conversion process developed for the carbon capture, chemical looping combustion operated with a gaseous fuel. In order to analyze the results of the CFD simulations, two one-dimensional fluidized bed models have been formulated. The single-phase and bubble-emulsion models were applied to derive the average gas-bed and interphase mass transfer coefficients, respectively. In the analysis, the effects of various fluidized bed operation parameters, such as fluidization, velocity, particle and bubble diameter, reactor size, and chemical kinetics, on the heterogeneous mass transfer coefficients in the lower fluidized bed are evaluated extensively. The analysis shows that the fine-grid Eulerian CFD model can predict the heterogeneous mass transfer coefficients quantitatively with acceptable accuracy. Qualitatively, the CFD-based research of fluidized bed process revealed several new scientific results, such as parametrical relationships. The huge variance of seven orders of magnitude within the bed Sherwood numbers presented in the literature could be explained by the change of controlling mechanisms in the overall heterogeneous mass transfer process with the varied process conditions. The research opens new process-specific insights into the reactive fluidized bed processes, such as a strong mass transfer control over heterogeneous reaction rate, a dominance of interphase mass transfer in the fine-particle fluidized beds and a strong chemical kinetic dependence of the average gas-bed mass transfer. The obtained mass transfer coefficients can be applied in fluidized bed models used for various engineering design, reactor scale-up and process research tasks, and they consequently provide an enhanced prediction accuracy of the performance of fluidized bed processes.

The neuroimmune-endocrine axis: pathophysiological implications for the central nervous system cytokines and hypothalamus-pituitary-adrenal hormone dynamics

Cytokines are molecules that were initially discovered in the immune system as mediators of communication between various types of immune cells. However, it soon became evident that cytokines exert profound effects on key functions of the central nervous system, such as food intake, fever, neuroendocrine regulation, long-term potentiation, and behavior. In the 80's and 90's our group and others discovered that the genes encoding various cytokines and their receptors are expressed in vascular, glial, and neuronal structures of the adult brain. Most cytokines act through cell surface receptors that have one transmembrane domain and which transduce a signal through the JAK/STAT pathway. Of particular physiological and pathophysiological relevance is the fact that cytokines are potent regulators of hypothalamic neuropeptidergic systems that maintain neuroendocrine homeostasis and which regulate the body's response to stress. The mechanisms by which cytokine signaling affects the function of stress-related neuroendocrine systems are reviewed in this article.

The brain decade in debate: VI. Sensory and motor maps: dynamics and plasticity

This article is an edited transcription of a virtual symposium promoted by the Brazilian Society of Neuroscience and Behavior (SBNeC). Although the dynamics of sensory and motor representations have been one of the most studied features of the central nervous system, the actual mechanisms of brain plasticity that underlie the dynamic nature of sensory and motor maps are not entirely unraveled. Our discussion began with the notion that the processing of sensory information depends on many different cortical areas. Some of them are arranged topographically and others have non-topographic (analytical) properties. Besides a sensory component, every cortical area has an efferent output that can be mapped and can influence motor behavior. Although new behaviors might be related to modifications of the sensory or motor representations in a given cortical area, they can also be the result of the acquired ability to make new associations between specific sensory cues and certain movements, a type of learning known as conditioning motor learning. Many types of learning are directly related to the emotional or cognitive context in which a new behavior is acquired. This has been demonstrated by paradigms in which the receptive field properties of cortical neurons are modified when an animal is engaged in a given discrimination task or when a triggering feature is paired with an aversive stimulus. The role of the cholinergic input from the nucleus basalis to the neocortex was also highlighted as one important component of the circuits responsible for the context-dependent changes that can be induced in cortical maps.

Dimensions and dynamics in integrin function

Integrins play crucial roles in cell adhesion, migration, and signaling by providing transmembrane links between the extracellular matrix and the cytoskeleton. Integrins cluster in macromolecular complexes to generate cell-matrix adhesions such as focal adhesions. In this mini-review, we compare certain integrin-based biological responses and signaling during cell interactions with standard 2D cell culture versus 3D matrices. Besides responding to the composition of the matrix, cells sense and react to physical properties that include three-dimensionality and rigidity. In routine cell culture, fibroblasts and mesenchymal cells appear to use focal adhesions as anchors. They then use intracellular actomyosin contractility and dynamic, directional integrin movements to stretch cell-surface fibronectin and to generate characteristic long fibrils of fibronectin in "fibrillar adhesions". Some cells in culture proceed to produce dense, three-dimensional matrices similar to in vivo matrix, as opposed to the flat, rigid, two-dimensional surfaces habitually used for cell culture. Cells within such more natural 3D matrices form a distinctive class of adhesion termed "3D-matrix adhesions". These 3D adhesions show distinctive morphology and molecular composition. Their formation is heavily dependent on interactions between integrin alpha5ß1 and fibronectin. Cells adhere much more rapidly to 3D matrices. They also show more rapid morphological changes, migration, and proliferation compared to most 2D matrices or 3D collagen gels. Particularly notable are low levels of tyrosine phosphorylation of focal adhesion kinase and moderate increases in activated mitogen-activated protein kinase. These findings underscore the importance of the dimensionality and dynamics of matrix substrates in cellular responses to the extracellular matrix.

Simulating the dynamics of silver market using computational market dynamics

Traditional econometric approaches in modeling the dynamics of equity and commodity markets, have, made great progress in the past decades. However, they assume rationality among the economic agents and and do not capture the dynamics that produce extreme events (black swans), due to deviation from the rationality assumption. The purpose of this study is to simulate the dynamics of silver markets by using the novel computational market dynamics approach. To this end, the daily data from the period of 1st March 2000 to 1st March 2013 of closing prices of spot silver prices has been simulated with the Jabłonska-Capasso-Morale(JCM) model. The Maximum Likelihood approach has been employed to calibrate the acquired data with JCM. Statistical analysis of the simulated series with respect to the actual one has been conducted to evaluate model performance. The model captures the animal spirits dynamics present in the data under evaluation well.

Adaptive Dynamics of Resource Specialization

Ecological specialization in resource utilization has various facades ranging from nutritional resources via host use of parasites or phytophagous insects to local adaptation in different habitats. Therefore, the evolution of specialization affects the evolution of most other traits, which makes it one of the core issues in the theory of evolution. Hence, the evolution of specialization has gained enormous amounts of research interest, starting already from Darwin’s Origin of species in 1859. Vast majority of the theoretical studies has, however, focused on the mathematically most simple case with well-mixed populations and equilibrium dynamics. This thesis explores the possibilities to extend the evolutionary analysis of resource usage to spatially heterogeneous metapopulation models and to models with non-equilibrium dynamics. These extensions are enabled by the recent advances in the field of adaptive dynamics, which allows for a mechanistic derivation of the invasion-fitness function based on the ecological dynamics. In the evolutionary analyses, special focus is set to the case with two substitutable renewable resources. In this case, the most striking questions are, whether a generalist species is able to coexist with the two specialist species, and can such trimorphic coexistence be attained through natural selection starting from a monomorphic population. This is shown possible both due to spatial heterogeneity and due to non-equilibrium dynamics. In addition, it is shown that chaotic dynamics may sometimes inflict evolutionary suicide or cyclic evolutionary dynamics. Moreover, the relations between various ecological parameters and evolutionary dynamics are investigated. Especially, the relation between specialization and dispersal propensity turns out to be counter-intuitively non-monotonous. This observation served as inspiration to the analysis of joint evolution of dispersal and specialization, which may provide the most natural explanation to the observed coexistence of specialist and generalist species.

Protein dynamics: hydration and cavities

The temperature-pressure behavior of proteins seems to be unique among the biological macromolecules. Thermodynamic as well as kinetic data show the typical elliptical stability diagram. This may be extended by assuming that the unfolded state gives rise to volume and enthalpy-driven liquid-liquid transitions. A molecular interpretation follows from the temperature and the pressure dependence of the hydration and cavities. We suggest that positron annihilation spectroscopy can provide additional quantitative evidence for the contributions of cavities to the dynamics of proteins. Only mature amyloid fibrils that form from unfolded proteins are very resistant to pressure treatment.

Modeling the pressure inactivation dynamics of Escherichia coli

Escherichia coli, as a model microorganism, was treated in phosphate-buffered saline under high hydrostatic pressure between 100 and 300 MPa, and the inactivation dynamics was investigated from the viewpoint of predictive microbiology. Inactivation data were curve fitted by typical predictive models: logistic, Gompertz and Weibull functions. Weibull function described the inactivation curve the best. Two parameters of Weibull function were calculated for each holding pressure and their dependence on holding pressure was obtained by interpolation. With the interpolated parameters, inactivation curves were simulated and compared with the experimental data sets.

Kalman filter for computational market dynamics

Kalman filter is a recursive mathematical power tool that plays an increasingly vital role in innumerable fields of study. The filter has been put to service in a multitude of studies involving both time series modelling and financial time series modelling. Modelling time series data in Computational Market Dynamics (CMD) can be accomplished using the Jablonska-Capasso-Morale (JCM) model. Maximum likelihood approach has always been utilised to estimate the parameters of the JCM model. The purpose of this study is to discover if the Kalman filter can be effectively utilized in CMD. Ensemble Kalman filter (EnKF), with 50 ensemble members, applied to US sugar prices spanning the period of January, 1960 to February, 2012 was employed for this work. The real data and Kalman filter trajectories showed no significant discrepancies, hence indicating satisfactory performance of the technique. Since only US sugar prices were utilized, it would be interesting to discover the nature of results if other data sets are employed.