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Improving permafrost dynamics in land surface models: insights from dual sensitivity experiments
(2024)
The thawing of permafrost and the subsequent release of greenhouse gases constitute one of the most significant and uncertain positive feedback loops in the context of climate change, making predictions regarding changes in permafrost coverage of paramount importance. To address these critical questions, climate scientists have developed Land Surface Models (LSMs) that encompass a multitude of physical soil processes. This thesis is committed to advancing our understanding and refining precise representations of permafrost dynamics within LSMs, with a specific focus on the accurate modeling of heat fluxes, an essential component for simulating permafrost physics.
The first research question overviews fundamental model prerequisites for the representation of permafrost soils within land surface modeling. It includes a first-of-its-kind comparison between LSMs in CMIP6 to reveal their differences and shortcomings in key permafrost physics parameters. Overall, each of these LSMs represents a unique approach to simulating soil processes and their interactions with the climate system. Choosing the most appropriate model for a particular application depends on factors such as the spatial and temporal scale of the simulation, the specific research question, and available computational resources.
The second research question evaluates the performance of the state-of-the-art Community Land Model (CLM5) in simulating Arctic permafrost regions. Our approach overcomes traditional evaluation limitations by individually addressing depth, seasonality, and regional variations, providing a comprehensive assessment of permafrost and soil temperature dynamics. I compare CLM5's results with three extensive datasets: (1) soil temperatures from 295 borehole stations, (2) active layer thickness (ALT) data from the Circumpolar Active Layer Monitoring Network (CALM), and (3) soil temperatures, ALT, and permafrost extent from the ESA Climate Change Initiative (ESA-CCI). The results show that CLM5 aligns well with ESA-CCI and CALM for permafrost extent and ALT but reveals a significant global cold temperature bias, notably over Siberia. These results echo a persistent challenge identified in numerous studies: the existence of a systematic 'cold bias' in soil temperature over permafrost regions. To address this challenge, the following research questions propose dual sensitivity experiments.
The third research question represents the first study to apply a Plant Functional Type (PFT)-based approach to derive soil texture and soil organic matter (SOM), departing from the conventional use of coarse-resolution global data in LSMs. This novel method results in a more uniform distribution of soil organic matter density (OMD) across the domain, characterized by reduced OMD values in most regions. However, changes in soil texture exhibit a more intricate spatial pattern. Comparing the results to observations reveals a significant reduction in the cold bias observed in the control run. This method shows noticeable improvements in permafrost extent, but at the cost of an overestimation in ALT. These findings emphasize the model's high sensitivity to variations in soil texture and SOM content, highlighting the crucial role of soil composition in governing heat transfer processes and shaping the seasonal variation of soil temperatures in permafrost regions.
Expanding upon a site experiment conducted in Trail Valley Creek by \citet{dutch_impact_2022}, the fourth research question extends the application of the snow scheme proposed by \citet{sturm_thermal_1997} to cover the entire Arctic domain. By employing a snow scheme better suited to the snow density profile observed over permafrost regions, this thesis seeks to assess its influence on simulated soil temperatures. Comparing this method to observational datasets reveals a significant reduction in the cold bias that was present in the control run. In most regions, the Sturm run exhibits a substantial decrease in the cold bias. However, there is a distinctive overshoot with a warm bias observed in mountainous areas. The Sturm experiment effectively addressed the overestimation of permafrost extent in the control run, albeit resulting in a substantial reduction in permafrost extent over mountainous areas. ALT results remain relatively consistent compared to the control run. These outcomes align with our initial hypothesis, which anticipated that the reduced snow insulation in the Sturm run would lead to higher winter soil temperatures and a more accurate representation of permafrost physics.
In summary, this thesis demonstrates significant advancements in understanding permafrost dynamics and its integration into LSMs. It has meticulously unraveled the intricacies involved in the interplay between heat transfer, soil properties, and snow dynamics in permafrost regions. These insights offer novel perspectives on model representation and performance.
Many hot stars exhibit stochastic polarimetric variability, thought to arise from clumping low in the wind. Here we investigate the wind properties required to reproduce this variability using analytic models, with particular emphasis on Luminous Blue Variables. We find that the winds must be highly structured, consisting of a large number of optically-thin clumps; while we find that the overall level of polarization should scale with mass-loss rate – consistent with observations of LBVs. The models also predict variability on very short timescales, which is supported by the results of a recent polarimetric monitoring campaign.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
We present the latest results on the observational dependence of the mass-loss rate in stellar winds of O and early-B stars on the metal content of their atmospheres, and compare these with predictions. Absolute empirical rates for the mass loss of stars brighter than 10$^{5.2} L_{\odot}$, based on H$\alpha$ and ultraviolet (UV) wind lines, are found to be about a factor of two higher than predictions. If this difference is attributed to inhomogeneities in the wind this would imply that luminous O and early-B stars have clumping factors in their H$\alpha$ and UV line forming regime of about a factor of 3--5. The investigated stars cover a metallicity range $Z$ from 0.2 to 1 $Z_{\odot}$. We find a hint towards smaller clumping factors for lower $Z$. The derived clumping factors, however, presuppose that clumping does not impact the predictions of the mass-loss rate. We discuss this assumption and explain how we intend to investigate its validity in more detail.
High-salt (HS) diets have recently been linked to oxidative stress in the brain, a fact that may be a precursor to behavioral changes, such as those involving anxiety-like behavior. However, to the best of our knowledge, no study has evaluated the amygdala redox status after consuming a HS diet in the pre- or postweaning periods. This study aimed to evaluate the amygdala redox status and anxiety-like behaviors in adulthood, after inclusion of HS diet in two periods: preconception, gestation, and lactation (preweaning); and only after weaning (postweaning). Initially, 18 females and 9 male Wistar rats received a standard (n = 9 females and 4 males) or a HS diet (n = 9 females and 5 males) for 120 days. After mating, females continued to receive the aforementioned diets during gestation and lactation. Weaning occurred at 21-day-old Wistar rats and the male offspring were subdivided: control-control (C-C)—offspring of standard diet fed dams who received a standard diet after weaning (n = 9–11), control-HS (C-HS)—offspring of standard diet fed dams who received a HS diet after weaning (n = 9–11), HS-C—offspring of HS diet fed dams who received a standard diet after weaning (n = 9–11), and HS-HS—offspring of HS diet fed dams who received a HS diet after weaning (n = 9–11). At adulthood, the male offspring performed the elevated plus maze and open field tests. At 152-day-old Wistar rats, the offspring were euthanized and the amygdala was removed for redox state analysis. The HS-HS group showed higher locomotion and rearing frequency in the open field test. These results indicate that this group developed hyperactivity. The C-HS group had a higher ratio of entries and time spent in the open arms of the elevated plus maze test in addition to a higher head-dipping frequency. These results suggest less anxiety-like behaviors. In the analysis of the redox state, less activity of antioxidant enzymes and higher levels of the thiobarbituric acid reactive substances (TBARS) in the amygdala were shown in the amygdala of animals that received a high-salt diet regardless of the period (pre- or postweaning). In conclusion, the high-salt diet promoted hyperactivity when administered in the pre- and postweaning periods. In animals that received only in the postweaning period, the addition of salt induced a reduction in anxiety-like behaviors. Also, regardless of the period, salt provided amygdala oxidative stress, which may be linked to the observed behaviors.
Importance Alcohol consumption (AC) leads to death and disability worldwide. Ongoing discussions on potential negative effects of the COVID-19 pandemic on AC need to be informed by real-world evidence.
Objective To examine whether lockdown measures are associated with AC and consumption-related temporal and psychological within-person mechanisms.
Design, Setting, and Participants This quantitative, intensive, longitudinal cohort study recruited 1743 participants from 3 sites from February 20, 2020, to February 28, 2021. Data were provided before and within the second lockdown of the COVID-19 pandemic in Germany: before lockdown (October 2 to November 1, 2020); light lockdown (November 2 to December 15, 2020); and hard lockdown (December 16, 2020, to February 28, 2021).
Main Outcomes and Measures Daily ratings of AC (main outcome) captured during 3 lockdown phases (main variable) and temporal (weekends and holidays) and psychological (social isolation and drinking intention) correlates.
Results Of the 1743 screened participants, 189 (119 [63.0%] male; median [IQR] age, 37 [27.5-52.0] years) with at least 2 alcohol use disorder (AUD) criteria according to the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) yet without the need for medically supervised alcohol withdrawal were included. These individuals provided 14 694 smartphone ratings from October 2020 through February 2021. Multilevel modeling revealed significantly higher AC (grams of alcohol per day) on weekend days vs weekdays (β = 11.39; 95% CI, 10.00-12.77; P < .001). Alcohol consumption was above the overall average on Christmas (β = 26.82; 95% CI, 21.87-31.77; P < .001) and New Year’s Eve (β = 66.88; 95% CI, 59.22-74.54; P < .001). During the hard lockdown, perceived social isolation was significantly higher (β = 0.12; 95% CI, 0.06-0.15; P < .001), but AC was significantly lower (β = −5.45; 95% CI, −8.00 to −2.90; P = .001). Independent of lockdown, intention to drink less alcohol was associated with lower AC (β = −11.10; 95% CI, −13.63 to −8.58; P < .001). Notably, differences in AC between weekend and weekdays decreased both during the hard lockdown (β = −6.14; 95% CI, −9.96 to −2.31; P = .002) and in participants with severe AUD (β = −6.26; 95% CI, −10.18 to −2.34; P = .002).
Conclusions and Relevance This 5-month cohort study found no immediate negative associations of lockdown measures with overall AC. Rather, weekend-weekday and holiday AC patterns exceeded lockdown effects. Differences in AC between weekend days and weekdays evinced that weekend drinking cycles decreased as a function of AUD severity and lockdown measures, indicating a potential mechanism of losing and regaining control. This finding suggests that temporal patterns and drinking intention constitute promising targets for prevention and intervention, even in high-risk individuals.
Under Brazil's ex-president Bolsonaro, deforestation of the Amazon increased dramatically. An Austrian NGO filed a complaint to the Prosecutor of the International Criminal Court (ICC) against Bolsonaro in October 2021, accusing him of crimes against humanity against the backdrop of his involvement in environmental destruction. This paper deals with the question of whether this initi-ative constitutes a promising means of juridification to mitigate conflicts revolving around mass deforestation in Brazil. It thematizes attempts to juridify environmental destruction in international criminal law and examines the Climate Fund Case at the Brazilian Supreme Court. Finally, emerging problems and arguments in favour of starting preliminary examinations at the ICC against Bolsonaro are illuminated. This paper provides arguments as to why the initiative might be a promising undertaking, even though it is unlikely that Bolsonaro will be arrested.
Objective: A role for microRNAs is implicated in several biological and pathological processes. We investigated the effects of high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) on molecular markers of diabetic cardiomyopathy in rats.
Methods: Eighteen male Wistar rats (260 ± 10 g; aged 8 weeks) with streptozotocin (STZ)-induced type 1 diabetes mellitus (55 mg/kg, IP) were randomly allocated to three groups: control, MICT, and HIIT. The two different training protocols were performed 5 days each week for 5 weeks. Cardiac performance (end-systolic and end-diastolic dimensions, ejection fraction), the expression of miR-206, HSP60, and markers of apoptosis (cleaved PARP and cytochrome C) were determined at the end of the exercise interventions.
Results: Both exercise interventions (HIIT and MICT) decreased blood glucose levels and improved cardiac performance, with greater changes in the HIIT group (p < 0.001, η2: 0.909). While the expressions of miR-206 and apoptotic markers decreased in both training protocols (p < 0.001, η2: 0.967), HIIT caused greater reductions in apoptotic markers and produced a 20% greater reduction in miR-206 compared with the MICT protocol (p < 0.001). Furthermore, both training protocols enhanced the expression of HSP60 (p < 0.001, η2: 0.976), with a nearly 50% greater increase in the HIIT group compared with MICT.
Conclusions: Our results indicate that both exercise protocols, HIIT and MICT, have the potential to reduce diabetic cardiomyopathy by modifying the expression of miR-206 and its downstream targets of apoptosis. It seems however that HIIT is even more effective than MICT to modulate these molecular markers.
Aims: High intensity interval training (HIIT) improves mitochondrial characteristics. This study compared the impact of two workload-matched high intensity interval training (HIIT) protocols with different work:recovery ratios on regulatory factors related to mitochondrial biogenesis in the soleus muscle of diabetic rats.
Materials and methods: Twenty-four Wistar rats were randomly divided into four equal-sized groups: non-diabetic control, diabetic control (DC), diabetic with long recovery exercise [4–5 × 2-min running at 80%–90% of the maximum speed reached with 2-min of recovery at 40% of the maximum speed reached (DHIIT1:1)], and diabetic with short recovery exercise (5–6 × 2-min running at 80%–90% of the maximum speed reached with 1-min of recovery at 30% of the maximum speed reached [DHIIT2:1]). Both HIIT protocols were completed five times/week for 4 weeks while maintaining equal running distances in each session.
Results: Gene and protein expressions of PGC-1α, p53, and citrate synthase of the muscles increased significantly following DHIIT1:1 and DHIIT2:1 compared to DC (p ˂ 0.05). Most parameters, except for PGC-1α protein (p = 0.597), were significantly higher in DHIIT2:1 than in DHIIT1:1 (p ˂ 0.05). Both DHIIT groups showed significant increases in maximum speed with larger increases in DHIIT2:1 compared with DHIIT1:1.
Conclusion: Our findings indicate that both HIIT protocols can potently up-regulate gene and protein expression of PGC-1α, p53, and CS. However, DHIIT2:1 has superior effects compared with DHIIT1:1 in improving mitochondrial adaptive responses in diabetic rats.
We investigate numerically the appearance of heteroclinic behavior in a three-dimensional, buoyancy-driven fluid layer with stress-free top and bottom boundaries, a square horizontal periodicity with a small aspect ratio, and rotation at low to moderate rates about a vertical axis. The Prandtl number is 6.8. If the rotation is not too slow, the skewed-varicose instability leads from stationary rolls to a stationary mixed-mode solution, which in turn loses stability to a heteroclinic cycle formed by unstable roll states and connections between them. The unstable eigenvectors of these roll states are also of the skewed-varicose or mixed-mode type and in some parameter regions skewed-varicose like shearing oscillations as well as square patterns are involved in the cycle. Always present weak noise leads to irregular horizontal translations of the convection pattern and makes the dynamics chaotic, which is verified by calculating Lyapunov exponents. In the nonrotating case, the primary rolls lose, depending on the aspect ratio, stability to traveling waves or a stationary square pattern. We also study the symmetries of the solutions at the intermittent fixed points in the heteroclinic cycle.
In this thesis we mainly generalize two theorems from Mackaay-Picken and Picken (2002, 2004). In the first paper, Mackaay and Picken show that there is a bijective correspondence between Deligne 2-classes $\xi \in \check{H}^2(M,\mathcal{D}^2)$ and holonomy maps from the second thin-homotopy group $\pi_2^2(M)$ to $U(1)$. In the second one, a generalization of this theorem to manifolds with boundaries is given: Picken shows that there is a bijection between Deligne 2-cocycles and a certain variant of 2-dimensional topological quantum field theories. In this thesis we show that these two theorems hold in every dimension. We consider first the holonomy case, and by using simplicial methods we can prove that the group of smooth Deligne $d$-classes is isomorphic to the group of smooth holonomy maps from the $d^{th}$ thin-homotopy group $\pi_d^d(M)$ to $U(1)$, if $M$ is $(d-1)$-connected. We contrast this with a result of Gajer (1999). Gajer showed that Deligne $d$-classes can be reconstructed by a different class of holonomy maps, which not only include holonomies along spheres, but also along general $d$-manifolds in $M$. This approach does not require the manifold $M$ to be $(d-1)$-connected. We show that in the case of flat Deligne $d$-classes, our result differs from Gajers, if $M$ is not $(d-1)$-connected, but only $(d-2)$-connected. Stiefel manifolds do have this property, and if one applies our theorem to these and compare the result with that of Gajers theorem, it is revealed that our theorem reconstructs too many Deligne classes. This means, that our reconstruction theorem cannot live without the extra assumption on the manifold $M$, that is our reconstruction needs less informations about the holonomy of $d$-manifolds in $M$ at the price of assuming $M$ to be $(d-1)$-connected. We continue to show, that also the second theorem can be generalized: By introducing the concept of Picken-type topological quantum field theory in arbitrary dimensions, we can show that every Deligne $d$-cocycle induces such a $d$-dimensional field theory with two special properties, namely thin-invariance and smoothness. We show that any $d$-dimensional topological quantum field theory with these two properties gives rise to a Deligne $d$-cocycle and verify that this construction is surjective and injective, that is both groups are isomorphic.
The present paper looks into the grammaticalization of the definite article in the history of German. Starting with the well-known emergence of the definite article from a demonstrative pronoun over the course of Old High German (750–1050), I will consider the rise of so-called weak definites in Early New High German (1350–1650) as a new piece of evidence for the grammaticalization process. Here, the subclass of possessive weak definites is of particular interest for the grammaticalization of the definite article in German, because of a word order change affecting the position of possessor phrases. As soon as the possessor systematically follows the head noun (except for proper names), we observe three alternatives for the prenominal determiner slot: it may remain empty, or it may be filled either by the indefinite or the definite article in Early New High German. In Present-Day German, the definite article is used in the unmarked case, thus pointing to a second stage in the grammaticalization process of the definite article in German, which has so far not been acknowledged in the literature.
Received views of utterance context in pragmatic theory characterize the occurrent subjective states of interlocutors using notions like common knowledge or mutual belief. We argue that these views are not compatible with the uncertainty and robustness of context-dependence in humanhuman dialogue. We present an alternative characterization of utterance context as objective and normative. This view reconciles the need for uncertainty with received intuitions about coordination and meaning in context, and can directly inform computational approaches to dialogue.
This paper describes the key aspects of the system SynCoP (Syntactic Constraint Parser) developed at the Berlin-Brandenburgische Akademie der Wissenschaften. The parser allows to combine syntactic tagging and chunking by means of constraint grammar using weighted finite state transducers (WFST). Chunks are interpreted as local dependency structures within syntactic tagging. The linguistic theories are formulated by criteria which are formalized by a semiring; these criteria allow structural preferences and gradual grammaticality. The parser is essentially a cascade of WFSTs. To find the most likely syntactic readings a best-path search is used.
A new method is used in an eye-tracking pilot experiment which shows that it is possible to detect differences in common ground associated with the use of minimally different types of indefinite anaphora. Following Richardson and Dale (2005), cross recurrence quantification analysis (CRQA) was used to show that the tandem eye movements of two Swedish-speaking interlocutors are slightly more coupled when they are using fully anaphoric indefinite expressions than when they are using less anaphoric indefinites. This shows the potential of CRQA to detect even subtle processing differences in ongoing discourse.
Microsaccades are very small, involuntary flicks in eye position that occur on average once or twice per second during attempted visual fixation. Microsaccades give rise to EMG eye muscle spikes that can distort the spectrum of the scalp EEG and mimic increases in gamma band power. Here we demonstrate that microsaccades are also accompanied by genuine and sizeable cortical activity, manifested in the EEG. In three experiments, high-resolution eye movements were corecorded with the EEG: during sustained fixation of checkerboard and face stimuli and in a standard visual oddball task that required the counting of target stimuli. Results show that microsaccades as small as 0.15° generate a field potential over occipital cortex and midcentral scalp sites 100 –140 ms after movement onset, which resembles the visual lambda response evoked by larger voluntary saccades. This challenges the standard assumption of human brain imaging studies that saccade-related brain activity is precluded by fixation, even when fully complied with. Instead, additional cortical potentials from microsaccades were present in 86% of the oddball task trials and of similar amplitude as the visual response to stimulus onset. Furthermore, microsaccade probability varied systematically according to the proportion of target stimuli in the oddball task, causing modulations of late stimulus-locked event-related potential (ERP) components. Microsaccades present an unrecognized source of visual brain signal that is of interest for vision research and may have influenced the data of many ERP and neuroimaging studies.
ANNIS
(2004)
In this paper, we discuss the design and implementation of our first version of the database "ANNIS" ("ANNotation of Information Structure"). For research based on empirical data, ANNIS provides a uniform environment for storing this data together with its linguistic annotations. A central database promotes standardized annotation, which facilitates interpretation and comparison of the data. ANNIS is used through a standard web browser and offers tier-based visualization of data and annotations, as well as search facilities that allow for cross-level and cross-sentential queries. The paper motivates the design of the system, characterizes its user interface, and provides an initial technical evaluation of ANNIS with respect to data size and query processing.
Complex emulsions are dispersions of kinetically stabilized multiphasic emulsion droplets comprised of two or more immiscible liquids that provide a novel material platform for the generation of active and dynamic soft materials. In recent years, the intrinsic reconfigurable morphological behavior of complex emulsions, which can be attributed to the unique force equilibrium between the interfacial tensions acting at the various interfaces, has become of fundamental and applied interest. As such, particularly biphasic Janus droplets have been investigated as structural templates for the generation of anisotropic precision objects, dynamic optical elements or as transducers and signal amplifiers in chemo- and bio-sensing applications. In the present thesis, switchable internal morphological responses of complex droplets triggered by stimuli-induced alterations of the balance of interfacial tensions have been explored as a universal building block for the design of multiresponsive, active, and adaptive liquid colloidal systems. A series of underlying principles and mechanisms that influence the equilibrium of interfacial tensions have been uncovered, which allowed the targeted design of emulsion bodies that can alter their shape, bind and roll on surfaces, or change their geometrical shape in response to chemical stimuli. Consequently, combinations of the unique triggerable behavior of Janus droplets with designer surfactants, such as a stimuli-responsive photosurfactant (AzoTAB) resulted for instance in shape-changing soft colloids that exhibited a jellyfish inspired buoyant motion behavior, holding great promise for the design of biological inspired active material architectures and transformable soft robotics.
In situ observations of spherical Janus emulsion droplets using a customized side-view microscopic imaging setup with accompanying pendant dropt measurements disclosed the sensitivity regime of the unique chemical-morphological coupling inside complex emulsions and enabled the recording of calibration curves for the extraction of critical parameters of surfactant effectiveness. The deduced new "responsive drop" method permitted a convenient and cost-efficient quantification and comparison of the critical micelle concentrations (CMCs) and effectiveness of various cationic, anionic, and nonionic surfactants. Moreover, the method allowed insightful characterization of stimuli-responsive surfactants and monitoring of the impact of inorganic salts on the CMC and surfactant effectiveness of ionic and nonionic surfactants. Droplet functionalization with synthetic crown ether surfactants yielded a synthetically minimal material platform capable of autonomous and reversible adaptation to its chemical environment through different supramolecular host-guest recognition events. Addition of metal or ammonium salts resulted in the uptake of the resulting hydrophobic complexes to the hydrocarbon hemisphere, whereas addition of hydrophilic ammonium compounds such as amino acids or polypeptides resulted in supramolecular assemblies at the hydrocarbon-water interface of the droplets. The multiresponsive material platform enabled interfacial complexation and
thus triggered responses of the droplets to a variety of chemical triggers including metal ions, ammonium compounds, amino acids, antibodies, carbohydrates as well as amino-functionalized solid surfaces.
In the final chapter, the first documented optical logic gates and combinatorial logic circuits based on complex emulsions are presented. More specifically, the unique reconfigurable and multiresponsive properties of complex emulsions were exploited to realize droplet-based logic gates of varying complexity using different stimuli-responsive surfactants in combination with diverse readout methods. In summary, different designs for multiresponsive, active, and adaptive liquid colloidal systems were presented and investigated, enabling the design of novel transformative chemo-intelligent soft material platforms.
Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006
Complex network theory provides an elegant and powerful framework to statistically investigate the topology of local and long range dynamical interrelationships, i.e., teleconnections, in the climate system. Employing a refined methodology relying on linear and nonlinear measures of time series analysis, the intricate correlation structure within a multivariate climatological data set is cast into network form. Within this graph theoretical framework, vertices are identified with grid points taken from the data set representing a region on the the Earth's surface, and edges correspond to strong statistical interrelationships between the dynamics on pairs of grid points. The resulting climate networks are neither perfectly regular nor completely random, but display the intriguing and nontrivial characteristics of complexity commonly found in real world networks such as the internet, citation and acquaintance networks, food webs and cortical networks in the mammalian brain. Among other interesting properties, climate networks exhibit the "small-world" effect and possess a broad degree distribution with dominating super-nodes as well as a pronounced community structure. We have performed an extensive and detailed graph theoretical analysis of climate networks on the global topological scale focussing on the flow and centrality measure betweenness which is locally defined at each vertex, but includes global topological information by relying on the distribution of shortest paths between all pairs of vertices in the network. The betweenness centrality field reveals a rich internal structure in complex climate networks constructed from reanalysis and atmosphere-ocean coupled general circulation model (AOGCM) surface air temperature data. Our novel approach uncovers an elaborately woven meta-network of highly localized channels of strong dynamical information flow, that we relate to global surface ocean currents and dub the backbone of the climate network in analogy to the homonymous data highways of the internet. This finding points to a major role of the oceanic surface circulation in coupling and stabilizing the global temperature field in the long term mean (140 years for the model run and 60 years for reanalysis data). Carefully comparing the backbone structures detected in climate networks constructed using linear Pearson correlation and nonlinear mutual information, we argue that the high sensitivity of betweenness with respect to small changes in network structure may allow to detect the footprints of strongly nonlinear physical interactions in the climate system. The results presented in this thesis are thoroughly founded and substantiated using a hierarchy of statistical significance tests on the level of time series and networks, i.e., by tests based on time series surrogates as well as network surrogates. This is particularly relevant when working with real world data. Specifically, we developed new types of network surrogates to include the additional constraints imposed by the spatial embedding of vertices in a climate network. Our methodology is of potential interest for a broad audience within the physics community and various applied fields, because it is universal in the sense of being valid for any spatially extended dynamical system. It can help to understand the localized flow of dynamical information in any such system by combining multivariate time series analysis, a complex network approach and the information flow measure betweenness centrality. Possible fields of application include fluid dynamics (turbulence), plasma physics and biological physics (population models, neural networks, cell models). Furthermore, the climate network approach is equally relevant for experimental data as well as model simulations and hence introduces a novel perspective on model evaluation and data driven model building. Our work is timely in the context of the current debate on climate change within the scientific community, since it allows to assess from a new perspective the regional vulnerability and stability of the climate system while relying on global and not only on regional knowledge. The methodology developed in this thesis hence has the potential to substantially contribute to the understanding of the local effect of extreme events and tipping points in the earth system within a holistic global framework.