DYNAMICS AND CONTROL OF REACTIVE DISTILLATION PROCESS FOR MONOMER SYNTHESIS OF POLYCARBONATE PLANTS

Polycarbonate (PC) is an important engineering thermoplastic that is currently produced in large industrial scale using bisphenol A and monomers such as phosgene. Since phosgene is highly toxic, a non-phosgene approach using diphenyl carbonate (DPC) as an alternative monomer, as developed by Asahi Corporation of Japan, is a significantly more environmentally friendly alternative. Other advantages include the use of CO2 instead of CO as raw material and the elimination of major waste water production. However, for the production of DPC to be economically viable, reactive-distillation units are needed to obtain the necessary yields by shifting the reaction-equilibrium to the desired products and separating the products at the point where the equilibrium reaction occurs. In the field of chemical reaction engineering, there are many reactions that are suffering from the low equilibrium constant. The main goal of this research is to determine the optimal process needed to shift the reactions by using appropriate control strategies of the reactive distillation system. An extensive dynamic mathematical model has been developed to help us investigate different control and processing strategies of the reactive distillation units to increase the production of DPC. The high-fidelity dynamic models include extensive thermodynamic and reaction-kinetics models while incorporating the necessary mass and energy balance of the various stages of the reactive distillation units. The study presented in this document shows the possibility of producing DPC via one reactive distillation instead of the conventional two-column, with a production rate of 16.75 tons/h corresponding to start reactants materials of 74.69 tons/h of Phenol and 35.75 tons/h of Dimethyl Carbonate. This represents a threefold increase over the projected production rate given in the literature based on a two-column configuration. In addition, the purity of the DPC produced could reach levels as high as 99.5% with the effective use of controls. These studies are based on simulation done using high-fidelity dynamic models.

Species mobility and frequency dynamics in a Swiss limestone grassland

Community dynamics in a calcareous grassland (Mesobrometum) in Egerkingen (Jura mountains, Switzerland) were investigated for 53 non-woody species in 25 1-m2 plots over 6 years. 50 0.0 1-m2 subplots per plot were recorded. The derived variables were spatial frequency, temporal frequency, frequency fluctuation, turnover, and cumulative frequency (each species), and cumulative species richness (all species). Spectra for 53 species of all variables were different for the two investigated spatial scales (0.0 1 m2, 1 m2). The comparison with other investigations of similar grass lands showed that the behaviour of some species is specific for this type of vegetation in general (e.g. Achillea millefolium, Arrhenatherum elatius, Bromus erectus ), but most species behaved in a stand-specific way, i.e. they may play another (similar or completely different) role in another grassland stand. Six spatio-temporal patterns were defined across species. To understand community dynamics, not only the dynamics of mobility but also of frequency fluctuations and spatial distribution of the species are fundamental. In addition, the understanding of temporal behaviour of all species present should be included. Averages always hide important information of vegetation dynamics, as was shown by the present investigation.

Integration of electrical neuroimaging with other functional imaging methods

Integrating evidence from different imaging modalities is important to overcome specific limitations of any given imaging method, such as insensitivity of the EEG to unsynchronized neural events, or the lack of fMRI sensitivity to events of low metabolic demand. Processes that are visible in one modality may be related in a nontrivial way to other processes visible in another modality and insight may only be obtained by integrating both methods through a common analysis. For example, brain activity at rest seems to be at least partly determined by an interaction of cortical rhythms (visible to EEG but not to fMRI) with sub-cortical activity (visible to fMRI, but usually not to EEG without averaging). A combination of EEG and fMRI data during rest may thus be more informative than the sum of two separate analyses in both modalities. Integration is also an important source of converging evidence about specific aspects and general principles of neural functions and their dysfunctions in certain pathologies. This is because not only electrical, but also energetic, biochemical, hemodynamic and metabolic processes characterize neural states and functions, and because brain structure provides crucial constraints upon neural functions. Focusing on multimodal integration of functional data should not distract from the privileged status of the electric field as the primary direct, noninvasive real-time measure of neural transmission. The preceding chapters illustrate how electrical neuroimaging has turned scalp EEG into an imaging modality which directly captures the full temporal dynamics of neural activity in the brain.

Overview of analytical approaches

The general model The aim of this chapter is to introduce a structured overview of the different possibilities available to display and analyze brain electric scalp potentials. First, a general formal model of time-varying distributed EEG potentials is introduced. Based on this model, the most common analysis strategies used in EEG research are introduced and discussed as specific cases of this general model. Both the general model and particular methods are also expressed in mathematical terms. It is however not necessary to understand these terms to understand the chapter. The general model that we propose here is based on the statement made in Chapter 3, stating that the electric field produced by active neurons in the brain propagates in brain tissue without delay in time. Contrary to other imaging methods that are based on hemodynamic or metabolic processes, the EEG scalp potentials are thus “real-time,” not delayed and not a-priori frequency-filtered measurements. If only a single dipolar source in the brain were active, the temporal dynamics of the activity of that source would be exactly reproduced by the temporal dynamics observed in the scalp potentials produced by that source. This is illustrated in Figure 5.1, where the expected EEG signal of a single source with spindle-like dynamics in time has been computed. The dynamics of the scalp potentials exactly reproduce the dynamics of the source. The amplitude of the measured potentials depends on the relation between the location and orientation of the active source, its strength and the electrode position.

Forcing of stratospheric chemistry and dynamics during the Dalton Minimum

The response of atmospheric chemistry and dynamics to volcanic eruptions and to a decrease in solar activity during the Dalton Minimum is investigated with the fully coupled atmosphere–ocean chemistry general circulation model SOCOL-MPIOM (modeling tools for studies of SOlar Climate Ozone Links-Max Planck Institute Ocean Model) covering the time period 1780 to 1840 AD. We carried out several sensitivity ensemble experiments to separate the effects of (i) reduced solar ultra-violet (UV) irradiance, (ii) reduced solar visible and near infrared irradiance, (iii) enhanced galactic cosmic ray intensity as well as less intensive solar energetic proton events and auroral electron precipitation, and (iv) volcanic aerosols. The introduced changes of UV irradiance and volcanic aerosols significantly influence stratospheric dynamics in the early 19th century, whereas changes in the visible part of the spectrum and energetic particles have smaller effects. A reduction of UV irradiance by 15%, which represents the presently discussed highest estimate of UV irradiance change caused by solar activity changes, causes global ozone decrease below the stratopause reaching as much as 8% in the midlatitudes at 5 hPa and a significant stratospheric cooling of up to 2 °C in the mid-stratosphere and to 6 °C in the lower mesosphere. Changes in energetic particle precipitation lead only to minor changes in the yearly averaged temperature fields in the stratosphere. Volcanic aerosols heat the tropical lower stratosphere, allowing more water vapour to enter the tropical stratosphere, which, via HOx reactions, decreases upper stratospheric and mesospheric ozone by roughly 4%. Conversely, heterogeneous chemistry on aerosols reduces stratospheric NOx, leading to a 12% ozone increase in the tropics, whereas a decrease in ozone of up to 5% is found over Antarctica in boreal winter. The linear superposition of the different contributions is not equivalent to the response obtained in a simulation when all forcing factors are applied during the Dalton Minimum (DM) – this effect is especially well visible for NOx/NOy. Thus, this study also shows the non-linear behaviour of the coupled chemistry-climate system. Finally, we conclude that especially UV and volcanic eruptions dominate the changes in the ozone, temperature and dynamics while the NOx field is dominated by the energetic particle precipitation. Visible radiation changes have only very minor effects on both stratospheric dynamics and chemistry.

Brain electric correlates of strong belief in paranormal phenomena: intracerebral EEG source and regional Omega complexity analyses

The neurocognitive processes underlying the formation and maintenance of paranormal beliefs are important for understanding schizotypal ideation. Behavioral studies indicated that both schizotypal and paranormal ideation are based on an overreliance on the right hemisphere, whose coarse rather than focussed semantic processing may favor the emergence of 'loose' and 'uncommon' associations. To elucidate the electrophysiological basis of these behavioral observations, 35-channel resting EEG was recorded in pre-screened female strong believers and disbelievers during resting baseline. EEG data were subjected to FFT-Dipole-Approximation analysis, a reference-free frequency-domain dipole source modeling, and Regional (hemispheric) Omega Complexity analysis, a linear approach estimating the complexity of the trajectories of momentary EEG map series in state space. Compared to disbelievers, believers showed: more right-located sources of the beta2 band (18.5-21 Hz, excitatory activity); reduced interhemispheric differences in Omega complexity values; higher scores on the Magical Ideation scale; more general negative affect; and more hypnagogic-like reveries after a 4-min eyes-closed resting period. Thus, subjects differing in their declared paranormal belief displayed different active, cerebral neural populations during resting, task-free conditions. As hypothesized, believers showed relatively higher right hemispheric activation and reduced hemispheric asymmetry of functional complexity. These markers may constitute the neurophysiological basis for paranormal and schizotypal ideation.

Electroelasticity of charged black branes

We present the first-order corrected dynamics of fluid branes carrying higher-form charge by obtaining the general form of their equations of motion to pole-dipole order in the absence of external forces. Assuming linear response theory, we characterize the corresponding effective theory of stationary bent charged (an)isotropic fluid branes in terms of two sets of response coefficients, the Young modulus and the piezoelectric moduli. We subsequently find large classes of examples in gravity of this effective theory, by constructing stationary strained charged black brane solutions to first order in a derivative expansion. Using solution generating techniques and bent neutral black branes as a seed solution, we obtain a class of charged black brane geometries carrying smeared Maxwell charge in Einstein-Maxwell-dilaton gravity. In the specific case of ten-dimensional space-time we furthermore use T-duality to generate bent black branes with higher-form charge, including smeared D-branes of type II string theory. By subsequently measuring the bending moment and the electric dipole moment which these geometries acquire due to the strain, we uncover that their form is captured by classical electroelasticity theory. In particular, we find that the Young modulus and the piezoelectric moduli of our strained charged black brane solutions are parameterized by a total of 4 response coefficients, both for the isotropic as well as anisotropic cases.

A biophysical model of synaptic plasticity and metaplasticity can account for the dynamics of the backward shift of hippocampal place fields.

Hippocampal place cells in the rat undergo experience-dependent changes when the rat runs stereotyped routes. One such change, the backward shift of the place field center of mass, has been linked by previous modeling efforts to spike-timing-dependent plasticity (STDP). However, these models did not account for the termination of the place field shift and they were based on an abstract implementation of STDP that ignores many of the features found in cortical plasticity. Here, instead of the abstract STDP model, we use a calcium-dependent plasticity (CaDP) learning rule that can account for many of the observed properties of cortical plasticity. We use the CaDP learning rule in combination with a model of metaplasticity to simulate place field dynamics. Without any major changes to the parameters of the original model, the present simulations account both for the initial rapid place field shift and for the subsequent slowing down of this shift. These results suggest that the CaDP model captures the essence of a general cortical mechanism of synaptic plasticity, which may underlie numerous forms of synaptic plasticity observed both in vivo and in vitro.

Eco-evolutionary Dynamics of Individual-Based Food Webs

The past decade has seen the rise of high resolution datasets. One of the main surprises of analysing such data has been the discovery of a large genetic, phenotypic and behavioural variation and heterogeneous metabolic rates among individuals within natural populations. A parallel discovery from theory and experiments has shown a strong temporal convergence between evolutionary and ecological dynamics, but a general framework to analyse from individual-level processes the convergence between ecological and evolutionary dynamics and its implications for patterns of biodiversity in food webs has been particularly lacking. Here, as a first approximation to take into account intraspecific variability and the convergence between the ecological and evolutionary dynamics in large food webs, we develop a model from population genomics and microevolutionary processes that uses sexual reproduction, genetic-distance-based speciation and trophic interactions. We confront the model with the prey consumption per individual predator, species-level connectance and prey–predator diversity in several environmental situations using a large food web with approximately 25,000 sampled prey and predator individuals. We show higher than expected diversity of abundant species in heterogeneous environmental conditions and strong deviations from the observed distribution of individual prey consumption (i.e. individual connectivity per predator) in all the environmental conditions. The observed large variance in individual prey consumption regardless of the environmental variability collapsed species-level connectance after small increases in sampling effort. These results suggest (1) intraspecific variance in prey–predator interactions has a strong effect on the macroscopic properties of food webs and (2) intraspecific variance is a potential driver regulating the speed of the convergence between ecological and evolutionary dynamics in species-rich food webs. These results also suggest that genetic–ecological drift driven by sexual reproduction, equal feeding rate among predator individuals, mutations and genetic-distance-based speciation can be used as a neutral food web dynamics test to detect the ecological and microevolutionary processes underlying the observed patterns of individual and species-based food webs at local and macroecological scales.

Intra-annual dynamics of non-structural carbohydrates in the cambium of mature conifer trees reflects radial growth demands

The presence of soluble carbohydrates in the cambial zone, either from sugars recently produced during photosynthesis or from starch remobilized from storage organs, is necessary for radial tree growth. However, considerable uncertainties on carbohydrate dynamics and the consequences on tree productivity exist. This study aims to better understand the variation in different carbon pools at intra-annual resolution by quantifying how cambial zone sugar and starch concentrations fluctuate over the season and in relation to cambial phenology. A comparison between two physiologically different species growing at the same site, i.e., the evergreen Picea abies Karst. and the deciduous Larix decidua Mill., and between L. decidua from two contrasting elevations, is presented to identify mechanisms of growth limitation. Results indicate that the annual cycle of sugar concentration within the cambial zone is coupled to the process of wood formation. The highest sugar concentration is observed when the number of cells in secondary wall formation and lignification stages is at a maximum, subsequent to most radial growth. Starch disappears in winter, while other freeze-resistant non-structural carbohydrates (NSCs) increase. Slight differences in NSC concentration between species are consistent with the differing climate sensitivity of the evergreen and deciduous species investigated. The general absence of differences between elevations suggests that the cambial activity of trees growing at the treeline was not limited by the availability of carbohydrates at the cambial zone but instead by environmental controls on the growing season duration.

The Emergence of Partnership Networks in the Enterprise Application Development Industry - A Global Corporation Perspective

Currently, dramatic changes are happening in the IS development industry. The incumbent system developers (hubs) are embracing partnerships with less well established companies (spokes), acting in specific niches. This paper seeks to establish a better understanding of the motives for this strategy. Relying on existing work on strategic alliance formation, it is argued that partnering is particularly attractive, if these small companies possess certain capabilities that are difficult to obtain through other arrangements than partnering. Again drawing on the literature, three categories of capabilities are identified: the capability to innovate within their niche, the capability to provide a specific functionality that can be integrated with the incumbents’ systems, and the capability to address novel markets. These factors are analyzed through a case study. The case represents a market leader in the global IS development industry, which fosters a network of smaller partner firms. The study reveals that temporal dynamics between the identified factors are playing a dominant role in these networks. A cyclical partnership model is developed that attempts to explain the life cycle of a partnership within such a network.

Springtime Nutrient and Phytoplankton Dynamics on Georges Bank

The dynamics of phytoplankton and nutrients before, during and after the winter-spring bloom on Georges Bank were studied on 6 monthly survey cruises from January to June 1999. We measured hydrography, phytoplankton cell densities, chlorophyll a, dissolved inorganic nutrients (NO3 + NO2, NH4, Si(OH)(4), PO4), dissolved organic nitrogen (DON) and phosphorus (DOP), particulate organic carbon (POC) and nitrogen (PON) and total particulate phosphorus (TPP). We present evidence that phytoplankton production may be significant year-round, and that the winter-spring bloom may have started in January. From January to April the phytoplankton was comprised almost exclusively of diatoms, reaching cell densities in March and April of ca. 450 cells ml(-1); chlorophyll a concentrations exceeded 10 mug l(-1) in April. Diatoms decreased to relatively low levels in May (< 50 x 10(3) cells l(-1)) and increased again in June (>300 x 10(3) cells l(-1)). Densities of dinoflagellates and nanoflagellates were low (< 10 x 10(3) cells l(-1)) from January to April, and increased in May and June to nearly 300 x 10(3) cells l(-1). Nitrate + nitrite concentrations in January were <3 muM in the shallow, central portion of the bank and decreased steadily each month. Silicate was also <3 muM over an even larger area of the central bank in January and declined to <1.5 muM over most of the Bank in April. The data suggest that silicate depletion, not DIN, contributed to the cessation of the diatom bloom. Regeneration of silicate occurred in May and June, presumably as a result of rising water temperatures in late spring which increased the dissolution rate of diatom frustules from the earlier diatom bloom. Dissolved organic nitrogen may have been utilized at the start of the winter-spring bloom; concentrations were ca, 14 muM in January, dropping to < 6 mug l(-1) in February, after which DON concentrations steadily rose to > 15 mug l(-1) in June. Overall micro-and nanoplankton biomass, measured as POC, PON and TPP, increased over the 6 mo period, as did nutritional quality of that biomass as indicated by declining C:N ratios. Our results suggest there may have been an increase in the heterotrophic component of the plankton in May and June which coincided with a second burst in diatom abundance. We discuss general features of planktonic production and nutrient dynamics with respect to year-round production on the Bank.

Dynamics of governance and control in inter-organizational software development

In recent years, development of information systems (IS) has rapidly changed towards increasing division of labor between firms. Two trends are emerging. First, client companies increasingly outsource software development to external service providers. Second, the formerly oligopolistic enterprise application software industry has started to disintegrate into focal partnership networks – so called platform ecosystems. Despite the increasing prominence of IS outsourcing and platform ecosystems, many of these inter-organizational partnerships fail to achieve expected benefits. Ineffective governance and control frequently plays a pivotal role in producing these failures. While designing effective governance and control mechanisms is always challenging, inter-organizational software development projects are often business-critical and exhibit additional dynamics and uncertainty. As a consequence governance and control have to be adapted over time. The three research projects included in this book provide a better understanding of how and why governance and control can be effectively adapted over time. The implications for successful management of inter-organizational software development projects are highly relevant for theory and practice.

Atmospheric Dynamics of Hot Exoplanets

The characterization of exoplanetary atmospheres has come of age in the last decade, as astronomical techniques now allow for albedos, chemical abundances, temperature profiles and maps, rotation periods and even wind speeds to be measured. Atmospheric dynamics sets the background state of density, temperature and velocity that determines or influences the spectral and temporal appearance of an exoplanetary atmosphere. Hot exoplanets are most amenable to these characterization techniques; in the present review, we focus on highly-irradiated, large exoplanets (the "hot Jupiters"), as astronomical data begin to confront theoretical questions. We summarize the basic atmospheric quantities inferred from the astronomical observations. We review the state of the art by addressing a series of current questions and look towards the future by considering a separate set of exploratory questions. Attaining the next level of understanding will require a concerted effort of constructing multi-faceted, multi-wavelength datasets for benchmark objects. Understanding clouds presents a formidable obstacle, as they introduce degeneracies into the interpretation of spectra, yet their properties and existence are directly influenced by atmospheric dynamics. Confronting general circulation models with these multi-faceted, multi-wavelength datasets will help us understand these and other degeneracies. The coming decade will witness a decisive confrontation of theory and simulation by the next generation of astronomical data.