Solid-state NMR investigation of phosphonic acid based proton conducting materials

In this work, new promising proton conducting fuel cell membrane materials were characterized in terms of their structure and dynamic properties using solid-state nuclear magnetic resonance (NMR) spectroscopy and X-ray diffraction. Structurally different, phosphonic acid (PA) containing materials were systematically evaluated for possible high-temperature operation (e.g. at T>100°C). Notably, 1H, 2H and 31P magic angle spinning (MAS) NMR provided insight into local connectivities and dynamics of the hydrogen bonded network, while packing arrangements were identified by means of heteronuclear dipolar recoupling techniques.rnThe first part of this work introduced rather crystalline, low molecular weight ionomers for proton conducting membranes, where six different geometries such as line, triangle, screw, tetrahedron, square and hexagon, were investigated. The hexagon was identified as the most promising geometry with high-temperature bulk proton conductivities in the range of 10-3 Scm-1 at a relative humidity of 50%. However, 2H NMR and TGA-MS data suggest that the bulk proton transport is mainly due to the presence of crystal water. Single crystal X-ray data revealed that in the tetrahedron phosphonic acids form tetrameric clusters isolating the mobile protons while the phosphonic acids in the hexagon form zigzag-type pathways through the sample.rnThe second part of this work demonstrates how acid-base pairing and the choice of appropriate spacers may influence proton conduction. Different ratios of statistical copolymers of poly (vinylphosphonic acid) and poly (4-vinylpyridine) were measured to derive information about the local structure and chemical changes. Though anhydrous proton conductivities of all statistical copolymers are rather poor, the conductivity increases to 10-2 S cm-1 when exposing the sample to relative humidity of 80%. In contrast to PVPA, anhydride formation of phosphonic acids in the copolymer is not reversible even when exposing the sample to a relative humidity of 100%.rnIn addition, the influence of both spacers and degree of backbone crystallinity on bulk proton conductivity was investigated. Unlike in systems such as poly benzimidazole (PBI), spacers were inserted between the protogenic groups along the backbone. It was found that dilution of the protogenic groups decreases the conductivity, but compared to PVPA, similar apparent activation energies for local motions were obtained from both variable temperature 1H NMR and impedance spectroscopy data. These observations suggest the formation of phosphonic acid clusters with high degrees of local proton motion, where only a fraction of motions contribute to the observable bulk proton conductivity. Additionally, it was shown that gradual changes of the spacer length lead to different morphologies.rnIn summary, applying advanced solid-state NMR and X-ray analysis, structural and dynamic phenomena in proton conducting materials were identified on a molecular level. The results were discussed with respect to different proton conduction mechanisms and may contribute to a more rational design or improvement of proton conducting membranes.rn

Solid-state NMR on columnar supramolecular structures

The present work deals with the characterisation of three columnar self-assembled systems, that is, benzene-1,3,5-tricarboxamides, a peripherally thioalkyl-substituted phthalocyanine, and several oligo-(p-phenylenevinylene)s. In order to probe the supramolecular organisation solid-state NMR has been used as the main technique, supported by X-ray measurements, theoretical methods, and thermal analysis. rnrnBenzene-1,3,5-tricarboxamides (BTAs) turned out to be well suited model compounds to study various fundamental supramolecular interactions, such as π-π-interactions, hydrogen bonding, as well as dynamic and steric effects of attached side chains. Six BTAs have been investigated in total, five with a CO-centred amide group bearing different side chains and one with an inverted N-centred amide group. The physical properties of these BTAs have been investigated as a function of temperature. The results indicated that in case of the CO-centred BTAs the stability of the columnar mesophase depends strongly on the nature of the side chains. Further experiments revealed a coplanar orientation of adjacent BTA molecules in the columnar assembly of CO-centred BTAs, whereas the N-centred BTA, showed a deviating not fully coplanar arrangement. These differences were ascribed to distinct hydrogen bonding schemes, involving a parallel alignment of hydrogen bonds in case of CO-centred BTAs and an antiparallel alignment in case of the N-centred counterpart.rnrn The fundamental insights of the supramolecular organisation of BTAs could be partially adapted to an octa-substituted phthalocyanine with thiododecyl moieties. Solid-state NMR in combination with chemical shift calculations determined a tilted herringbone arrangement of phthalocyanine rings in the crystalline phase as well as in the mesophase. Moreover, 1H NMR measurements in the mesophase of this compound suggested an axial rotation of molecules, which is inhibited in the crystalline phase.rnrnAs a third task, the supramolecular assembly of oligo-(p-phenylenevinylene)s of varying length and with different polar head groups have been investigated by a combined X-ray and solid-state NMR study. The results revealed a columnar structure formation of these compounds, being promoted by phase separation of alkyl side chains and aromatic rigid rods. In this system solid-state NMR yielded meaningful insight into the isotropisation process of butoxy and 2-S-methylbutoxy substituted oligo-(p-phenylenevinylene) rods.rn

Advances in hardware and molecular design of polarizing agents for dynamic nuclear polarization

Die Kernmagnetresonanz (NMR) ist eine vielseitige Technik, die auf spin-tragende Kerne angewiesen ist. Seit ihrer Entdeckung ist die Kernmagnetresonanz zu einem unverzichtbaren Werkzeug in unzähligen Anwendungen der Physik, Chemie, Biologie und Medizin geworden. Das größte Problem der NMR ist ihre geringe Sensitivtät auf Grund der sehr kleinen Energieaufspaltung bei Raumtemperatur. Für Protonenspins, die das größte magnetogyrische Verhältnis besitzen, ist der Polarisationsgrad selbst in den größten verfügbaren Magnetfeldern (24 T) nur ~7*10^(-5).rnDurch die geringe inhärente Polarisation ist folglich eine theoretische Sensitivitätssteigerung von mehr als 10^4 möglich. rnIn dieser Arbeit wurden verschiedene technische Aspekte und unterschiedliche Polarisationsagenzien für Dynamic Nuclear Polarization (DNP) untersucht.rnDie technische Entwicklung des mobilen Aufbaus umfasst die Verwendung eines neuen Halbach Magneten, die Konstruktion neuer Probenköpfe und den automatisierten Ablauf der Experimente mittels eines LabVIEW basierten Programms. Desweiteren wurden zwei neue Polarisationsagenzien mit besonderen Merkmalen für den Overhauser und den Tieftemperatur DNP getestet. Zusätzlich konnte die Durchführbarkeit von NMR Experimenten an Heterokernen (19F und 13C) im mobilen Aufbau bei 0,35 T gezeigt werden. Diese Ergebnisse zeigen die Möglichkeiten der Polarisationstechnik DNP auf, wenn Heterokerne mit einem kleinen magnetogyrischen Verhältnis polarisiert werden müssen.rnDie Sensitivitätssteigerung sollte viele neue Anwendungen, speziell in der Medizin, ermöglichen.

Dynamic development of hydrofractures

Natürliche hydraulische Bruchbildung ist in allen Bereichen der Erdkruste ein wichtiger und stark verbreiteter Prozess. Sie beeinflusst die effektive Permeabilität und Fluidtransport auf mehreren Größenordnungen, indem sie hydraulische Konnektivität bewirkt. Der Prozess der Bruchbildung ist sowohl sehr dynamisch als auch hoch komplex. Die Dynamik stammt von der starken Wechselwirkung tektonischer und hydraulischer Prozesse, während sich die Komplexität aus der potentiellen Abhängigkeit der poroelastischen Eigenschaften von Fluiddruck und Bruchbildung ergibt. Die Bildung hydraulischer Brüche besteht aus drei Phasen: 1) Nukleation, 2) zeitabhängiges quasi-statisches Wachstum so lange der Fluiddruck die Zugfestigkeit des Gesteins übersteigt, und 3) in heterogenen Gesteinen der Einfluss von Lagen unterschiedlicher mechanischer oder sedimentärer Eigenschaften auf die Bruchausbreitung. Auch die mechanische Heterogenität, die durch präexistierende Brüche und Gesteinsdeformation erzeugt wird, hat großen Einfluß auf den Wachstumsverlauf. Die Richtung der Bruchausbreitung wird entweder durch die Verbindung von Diskontinuitäten mit geringer Zugfestigkeit im Bereich vor der Bruchfront bestimmt, oder die Bruchausbreitung kann enden, wenn der Bruch auf Diskontinuitäten mit hoher Festigkeit trifft. Durch diese Wechselwirkungen entsteht ein Kluftnetzwerk mit komplexer Geometrie, das die lokale Deformationsgeschichte und die Dynamik der unterliegenden physikalischen Prozesse reflektiert. rnrnNatürliche hydraulische Bruchbildung hat wesentliche Implikationen für akademische und kommerzielle Fragestellungen in verschiedenen Feldern der Geowissenschaften. Seit den 50er Jahren wird hydraulisches Fracturing eingesetzt, um die Permeabilität von Gas und Öllagerstätten zu erhöhen. Geländebeobachtungen, Isotopenstudien, Laborexperimente und numerische Analysen bestätigen die entscheidende Rolle des Fluiddruckgefälles in Verbindung mit poroelastischen Effekten für den lokalen Spannungszustand und für die Bedingungen, unter denen sich hydraulische Brüche bilden und ausbreiten. Die meisten numerischen hydromechanischen Modelle nehmen für die Kopplung zwischen Fluid und propagierenden Brüchen vordefinierte Bruchgeometrien mit konstantem Fluiddruck an, um das Problem rechnerisch eingrenzen zu können. Da natürliche Gesteine kaum so einfach strukturiert sind, sind diese Modelle generell nicht sonderlich effektiv in der Analyse dieses komplexen Prozesses. Insbesondere unterschätzen sie die Rückkopplung von poroelastischen Effekten und gekoppelte Fluid-Festgestein Prozesse, d.h. die Entwicklung des Porendrucks in Abhängigkeit vom Gesteinsversagen und umgekehrt.rnrnIn dieser Arbeit wird ein zweidimensionales gekoppeltes poro-elasto-plastisches Computer-Model für die qualitative und zum Teil auch quantitativ Analyse der Rolle lokalisierter oder homogen verteilter Fluiddrücke auf die dynamische Ausbreitung von hydraulischen Brüchen und die zeitgleiche Evolution der effektiven Permeabilität entwickelt. Das Programm ist rechnerisch effizient, indem es die Fluiddynamik mittels einer Druckdiffusions-Gleichung nach Darcy ohne redundante Komponenten beschreibt. Es berücksichtigt auch die Biot-Kompressibilität poröser Gesteine, die implementiert wurde um die Kontrollparameter in der Mechanik hydraulischer Bruchbildung in verschiedenen geologischen Szenarien mit homogenen und heterogenen Sedimentären Abfolgen zu bestimmen. Als Resultat ergibt sich, dass der Fluiddruck-Gradient in geschlossenen Systemen lokal zu Störungen des homogenen Spannungsfeldes führen. Abhängig von den Randbedingungen können sich diese Störungen eine Neuausrichtung der Bruchausbreitung zur Folge haben kann. Durch den Effekt auf den lokalen Spannungszustand können hohe Druckgradienten auch schichtparallele Bruchbildung oder Schlupf in nicht-entwässerten heterogenen Medien erzeugen. Ein Beispiel von besonderer Bedeutung ist die Evolution von Akkretionskeilen, wo die große Dynamik der tektonischen Aktivität zusammen mit extremen Porendrücken lokal starke Störungen des Spannungsfeldes erzeugt, die eine hoch-komplexe strukturelle Entwicklung inklusive vertikaler und horizontaler hydraulischer Bruch-Netzwerke bewirkt. Die Transport-Eigenschaften der Gesteine werden stark durch die Dynamik in der Entwicklung lokaler Permeabilitäten durch Dehnungsbrüche und Störungen bestimmt. Möglicherweise besteht ein enger Zusammenhang zwischen der Bildung von Grabenstrukturen und großmaßstäblicher Fluid-Migration. rnrnDie Konsistenz zwischen den Resultaten der Simulationen und vorhergehender experimenteller Untersuchungen deutet darauf hin, dass das beschriebene numerische Verfahren zur qualitativen Analyse hydraulischer Brüche gut geeignet ist. Das Schema hat auch Nachteile wenn es um die quantitative Analyse des Fluidflusses durch induzierte Bruchflächen in deformierten Gesteinen geht. Es empfiehlt sich zudem, das vorgestellte numerische Schema um die Kopplung mit thermo-chemischen Prozessen zu erweitern, um dynamische Probleme im Zusammenhang mit dem Wachstum von Kluftfüllungen in hydraulischen Brüchen zu untersuchen.

Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.

Energy and conductance state modeling of power electronic converters for DC microgrids

This document will demonstrate the methodology used to create an energy and conductance based model for power electronic converters. The work is intended to be a replacement for voltage and current based models which have limited applicability to the network nodal equations. Using conductance-based modeling allows direct application of load differential equations to the bus admittance matrix (Y-bus) with a unified approach. When applied directly to the Y-bus, the system becomes much easier to simulate since the state variables do not need to be transformed. The proposed transformation applies to loads, sources, and energy storage systems and is useful for DC microgrids. Transformed state models of a complete microgrid are compared to experimental results and show the models accurately reflect the system dynamic behavior.

Cortical regional hyperperfusion in nonconvulsive status epilepticus measured by dynamic brain perfusion CT

BACKGROUND AND PURPOSE: Nonconvulsive status epilepticus (NCSE) is associated with a mortality rate of up to 18%, therefore requiring prompt diagnosis and treatment. Our aim was to evaluate the diagnostic value of perfusion CT (PCT) in the differential diagnosis of NCSE versus postictal states in patients presenting with persistent altered mental states after a preceding epileptic seizure. We hypothesized that regional cortical hyperperfusion can be measured by PCT in patients with NCSE, whereas it is not present in postictal states. MATERIALS AND METHODS: Nineteen patients with persistent altered mental status after a preceding epileptic seizure underwent PCT and electroencephalography (EEG). Patients were stratified as presenting with NCSE (n = 9) or a postictal state (n = 10) on the basis of clinical history and EEG data. Quantitative and visual analysis of the perfusion maps was performed. RESULTS: Patients during NCSE had significantly increased regional cerebral blood flow (P > .0001), increased regional cerebral blood volume (P > .001), and decreased (P > .001) mean transit time compared with the postictal state. Regional cortical hyperperfusion was depicted in 7/9 of patients with NCSE by ad hoc analysis of parametric perfusion maps during emergency conditions but was not a feature of postictal states. The areas of hyperperfusion were concordant with transient clinical symptoms and EEG topography in all cases. CONCLUSIONS: Visual analysis of perfusion maps detected regional hyperperfusion in NCSE with a sensitivity of 78%. The broad availability and short processing time of PCT in an emergency situation is a benefit compared with EEG. Consequently, the use of PCT in epilepsy may accelerate the diagnosis of NCSE. PCT may qualify as a complementary diagnostic tool to EEG in patients with persistent altered mental state after a preceding seizure.

Dynamic computer simulations of electrophoresis: three decades of active research

Dynamic models for electrophoresis are based upon model equations derived from the transport concepts in solution together with user-inputted conditions. They are able to predict theoretically the movement of ions and are as such the most versatile tool to explore the fundamentals of electrokinetic separations. Since its inception three decades ago, the state of dynamic computer simulation software and its use has progressed significantly and Electrophoresis played a pivotal role in that endeavor as a large proportion of the fundamental and application papers were published in this periodical. Software is available that simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. This has been employed to show the detailed mechanisms of many of the fundamental phenomena that occur in electrophoretic separations. Dynamic electrophoretic simulations are relevant for separations on any scale and instrumental format, including free-fluid preparative, gel, capillary and chip electrophoresis. This review includes a historical overview, a survey of current simulators, simulation examples and a discussion of the applications and achievements of dynamic simulation.

Dynamic patterns of ventricular remodeling and apoptosis in hearts unloaded by heterotopic transplantation

BACKGROUND Mechanical unloading of failing hearts can trigger functional recovery but results in progressive atrophy and possibly detrimental adaptation. In an unbiased approach, we examined the dynamic effects of unloading duration on molecular markers indicative of myocardial damage, hypothesizing that potential recovery may be improved by optimized unloading time. METHODS Heterotopically transplanted normal rat hearts were harvested at 3, 8, 15, 30, and 60 days. Forty-seven genes were analyzed using TaqMan-based microarray, Western blot, and immunohistochemistry. RESULTS In parallel with marked atrophy (22% to 64% volume loss at 3 respectively 60 days), expression of myosin heavy-chain isoforms (MHC-α/-β) was characteristically switched in a time-dependent manner. Genes involved in tissue remodeling (FGF-2, CTGF, TGFb, IGF-1) were increasingly upregulated with duration of unloading. A distinct pattern was observed for genes involved in generation of contractile force; an indiscriminate early downregulation was followed by a new steady-state below normal. For pro-apoptotic transcripts bax, bnip-3, and cCasp-6 and -9 mRNA levels demonstrated a slight increase up to 30 days unloading with pronunciation at 60 days. Findings regarding cell death were confirmed on the protein level. Proteasome activity indicated early increase of protein degradation but decreased below baseline in unloaded hearts at 60 days. CONCLUSIONS We identified incrementally increased apoptosis after myocardial unloading of the normal rat heart, which is exacerbated at late time points (60 days) and inversely related to loss of myocardial mass. Our findings suggest an irreversible detrimental effect of long-term unloading on myocardium that may be precluded by partial reloading and amenable to molecular therapeutic intervention.

Incremental Dynamic Updates with First-class Contexts

Highly available software systems occasionally need to be updated while avoiding downtime. Dynamic software updates reduce down-time, but still require the system to reach a quiescent state in which a global update can be performed. This can be difficult for multi-threaded systems. We present a novel approach to dynamic updates using first-class contexts, called Theseus. First-class contexts make global updates unnecessary: existing threads run to termination in an old context, while new threads start in a new, updated context; consistency between contexts is ensured with the help of bidirectional transformations. We show that for multi-threaded systems with coherent memory, first-class contexts offer a practical and flexible approach to dynamic updates, with acceptable overhead.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA)

OBJECTIVE Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA), a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE) imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL), non-enhancing lesions (NEL) and normal appearing white matter (NAWM) in multiple sclerosis (MS). METHODS We investigated 18 patients with MS and clinical isolated syndrome (CIS), according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla). Tissues of interest (TOIs) were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs) were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005). Significant differences in the DTPA texture maps were found during inflow (52 parameters), outflow (40 parameters) and reperfusion (62 parameters). The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2-hypersignal, on a numeric scale allowing for a more subtle grading of MS-lesions.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Optimal compliance with emission constraints: dynamic characteristics and the choice of technique

The paper analyzes how to comply with an emission constraint, which restricts the use of an established energy technique, given the two options to save energy and to invest in two alternative energy techniques. These techniques differ in their deterioration rates and the investment lags of the corresponding capital stocks. Thus, the paper takes a medium-term perspective on climate change mitigation, where the time horizon is too short for technological change to occur, but long enough for capital stocks to accumulate and deteriorate. It is shown that, in general, only one of the two alternative techniques prevails in the stationary state, although, both techniques might be utilized during the transition phase. Hence, while in a static economy only one technique is efficient, this is not necessarily true in a dynamic economy.