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Within the framework of precision agriculture, the determination of various soil properties is moving into focus, especially the demand for sensors suitable for in-situ measurements. Energy-dispersive X-ray fluorescence (EDXRF) can be a powerful tool for this purpose. In this study a huge diverse soil set (n = 598) from 12 different study sites in Germany was analysed with EDXRF. First, a principal component analysis (PCA) was performed to identify possible similarities among the sample set. Clustering was observed within the four texture classes clay, loam, silt and sand, as clay samples contain high and sandy soils low iron mass fractions. Furthermore, the potential of uni- and multivariate data evaluation with partial least squares regression (PLSR) was assessed for accurate determination of nutrients in German agricultural samples using two calibration sample sets. Potassium and iron were chosen for testing the performance of both models. Prediction of these nutrients in 598 German soil samples with EDXRF was more accurate using PLSR which is confirmed by a better overall averaged deviation and PLSR should therefore be preferred.
This is a publication-based dissertation comprising three original research stud-ies (one published, one submitted and one ready for submission; status March 2019). The dissertation introduces a generic computer model as a tool to investigate the behaviour and population dynamics of animals in cyclic environments. The model is further employed for analysing how migratory birds respond to various scenarios of altered food supply under global change. Here, ecological and evolutionary time-scales are considered, as well as the biological constraints and trade-offs the individual faces, which ultimately shape response dynamics at the population level. Further, the effect of fine-scale temporal patterns in re-source supply are studied, which is challenging to achieve experimentally. My findings predict population declines, altered behavioural timing and negative carry-over effects arising in migratory birds under global change. They thus stress the need for intensified research on how ecological mechanisms are affected by global change and for effective conservation measures for migratory birds. The open-source modelling software created for this dissertation can now be used for other taxa and related research questions. Overall, this thesis improves our mechanistic understanding of the impacts of global change on migratory birds as one prerequisite to comprehend ongoing global biodiversity loss. The research results are discussed in a broader ecological and scientific context in a concluding synthesis chapter.
For both Lévy flight and Lévy walk search processes we analyse the full distribution of first-passage and first-hitting (or first-arrival) times. These are, respectively, the times when the particle moves across a point at some given distance from its initial position for the first time, or when it lands at a given point for the first time. For Lévy motions with their propensity for long relocation events and thus the possibility to jump across a given point in space without actually hitting it ('leapovers'), these two definitions lead to significantly different results. We study the first-passage and first-hitting time distributions as functions of the Lévy stable index, highlighting the different behaviour for the cases when the first absolute moment of the jump length distribution is finite or infinite. In particular we examine the limits of short and long times. Our results will find their application in the mathematical modelling of random search processes as well as computer algorithms.
With the emergence of the Internet of things (IoT), plenty of battery-powered and energy-harvesting devices are being deployed to fulfill sensing and actuation tasks in a variety of application areas, such as smart homes, precision agriculture, smart cities, and industrial automation. In this context, a critical issue is that of denial-of-sleep attacks. Such attacks temporarily or permanently deprive battery-powered, energy-harvesting, or otherwise energy-constrained devices of entering energy-saving sleep modes, thereby draining their charge. At the very least, a successful denial-of-sleep attack causes a long outage of the victim device. Moreover, to put battery-powered devices back into operation, their batteries have to be replaced. This is tedious and may even be infeasible, e.g., if a battery-powered device is deployed at an inaccessible location. While the research community came up with numerous defenses against denial-of-sleep attacks, most present-day IoT protocols include no denial-of-sleep defenses at all, presumably due to a lack of awareness and unsolved integration problems. After all, despite there are many denial-of-sleep defenses, effective defenses against certain kinds of denial-of-sleep attacks are yet to be found.
The overall contribution of this dissertation is to propose a denial-of-sleep-resilient medium access control (MAC) layer for IoT devices that communicate over IEEE 802.15.4 links. Internally, our MAC layer comprises two main components. The first main component is a denial-of-sleep-resilient protocol for establishing session keys among neighboring IEEE 802.15.4 nodes. The established session keys serve the dual purpose of implementing (i) basic wireless security and (ii) complementary denial-of-sleep defenses that belong to the second main component. The second main component is a denial-of-sleep-resilient MAC protocol. Notably, this MAC protocol not only incorporates novel denial-of-sleep defenses, but also state-of-the-art mechanisms for achieving low energy consumption, high throughput, and high delivery ratios. Altogether, our MAC layer resists, or at least greatly mitigates, all denial-of-sleep attacks against it we are aware of. Furthermore, our MAC layer is self-contained and thus can act as a drop-in replacement for IEEE 802.15.4-compliant MAC layers. In fact, we implemented our MAC layer in the Contiki-NG operating system, where it seamlessly integrates into an existing protocol stack.
Introducing PebbleCounts
(2019)
Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.
Research on weight-loss interventions in emerging adulthood is warranted. Therefore, a cognitive-behavioral group treatment (CBT), including development-specific topics for adolescents and young adults with obesity (YOUTH), was developed. In a controlled study, we compared the efficacy of this age-specific CBT group intervention to an age-unspecific CBT group delivered across ages in an inpatient setting. The primary outcome was body mass index standard deviation score (BMI-SDS) over the course of one year; secondary outcomes were health-related and disease-specific quality of life (QoL). 266 participants aged 16 to 21 years (65% females) were randomized. Intention-to-treat (ITT) and per-protocol analyses (PPA) were performed. For both group interventions, we observed significant and clinically relevant improvements in BMI-SDS and QoL over the course of time with small to large effect sizes. Contrary to our hypothesis, the age-specific intervention was not superior to the age-unspecific CBT-approach.
Interactions and feedbacks between tectonics, climate, and upper plate architecture control basin geometry, relief, and depositional systems. The Andes is part of a longlived continental margin characterized by multiple tectonic cycles which have strongly modified the Andean upper plate architecture. In the Andean retroarc, spatiotemporal variations in the structure of the upper plate and tectonic regimes have resulted in marked along-strike variations in basin geometry, stratigraphy, deformational style, and mountain belt morphology. These along-strike variations include high-elevation plateaus (Altiplano and Puna) associated with a thin-skin fold-and-thrust-belt and thick-skin deformation in broken foreland basins such as the Santa Barbara system and the Sierras Pampeanas. At the confluence of the Puna Plateau, the Santa Barbara system and the Sierras Pampeanas, major along-strike changes in upper plate architecture, mountain belt morphology, basement exhumation, and deformation style can be recognized. I have used a source to sink approach to unravel the spatiotemporal tectonic evolution of the Andean retroarc between 26 and 28°S. I obtained a large low-temperature thermochronology data set from basement units which includes apatite fission track, apatite U-Th-Sm/He, and zircon U-Th/He (ZHe) cooling ages. Stratigraphic descriptions of Miocene units were temporally constrained by U-Pb LA-ICP-MS zircon ages from interbedded pyroclastic material.
Modeled ZHe ages suggest that the basement of the study area was exhumed during the Famatinian orogeny (550-450 Ma), followed by a period of relative tectonic quiescence during the Paleozoic and the Triassic. The basement experienced horst exhumation during the Cretaceous development of the Salta rift. After initial exhumation, deposition of thick Cretaceous syn-rift strata caused reheating of several basement blocks within the Santa Barbara system. During the Eocene-Oligocene, the Andean compressional setting was responsible for the exhumation of several disconnected basement blocks. These exhumed blocks were separated by areas of low relief, in which humid climate and low erosion rates facilitated the development of etchplains on the crystalline basement. The exhumed basement blocks formed an Eocene to Oligocene broken foreland basin in the back-bulge depozone of the Andean foreland. During the Early Miocene, foreland basin strata filled up the preexisting Paleogene topography. The basement blocks in lower relief positions were reheated; associated geothermal gradients were higher than 25°C/km. Miocene volcanism was responsible for lateral variations on the amount of reheating along the Campo-Arenal basin. Around 12 Ma, a new deformational phase modified the drainage network and fragmented the lacustrine system. As deformation and rock uplift continued, the easily eroded sedimentary cover was efficiently removed and reworked by an ephemeral fluvial system, preventing the development of significant relief. After ~6 Ma, the low erodibility of the basement blocks which began to be exposed caused relief increase, leading to the development of stable fluvial systems. Progressive relief development modified atmospheric circulation, creating a rainfall gradient. After 3 Ma, orographic rainfall and high relief lead to the development of proximal fluvial-gravitational depositional systems in the surrounding basins.
Evidence-based prescriptions for balance training in youth have recently been established. However, there is currently no standardized means available to assess and quantify balance task difficulty (BTD). Therefore, the objectives of this study were to examine the effects of graded BTD on postural sway, lower limb muscle activity and coactivation in adolescents. Thirteen healthy high-school students aged 16 to 17 volunteered to participate in this cross-sectional study. Testing involved participants to stand on a commercially available balance board with an adjustable pivot that allowed six levels of increasing task difficulty. Postural sway [i.e., total center of pressure (CoP) displacements] and lower limb muscle activity were recorded simultaneously during each trial. Surface electromyography (EMG) was applied in muscles encompassing the ankle (m. tibialis anterior, medial gastrocnemius, peroneus longus) and knee joint (m. vastus medialis, biceps femoris). The coactivation index (CAI) was calculated for ankle and thigh muscles. Repeated measures analyses of variance revealed a significant main effect of BTD with increasing task difficulty for postural sway (p < 0.001; d = 6.36), muscle activity (p < 0.001; 2.19 < d < 4.88), and CAI (p < 0.001; 1.32 < d < 1.41). Multiple regression analyses showed that m. tibialis anterior activity best explained overall CoP displacements with 32.5% explained variance (p < 0.001). The observed increases in postural sway, lower limb muscle activity, and coactivation indicate increasing postural demands while standing on the balance board. Thus, the examined board can be implemented in balance training to progressively increase BTD in healthy adolescents.
The transition from pollinator-mediated outbreeding to selfing has occurred many times in angiosperms. This is generally accompanied by a reduction in traits attracting pollinators, including reduced emission of floral scent. In Capsella, emission of benzaldehyde as a main component of floral scent has been lost in selfing C. rubella by mutation of cinnamate-CoA ligase CNL1. However, the biochemical basis and evolutionary history of this loss remain unknown, as does the reason for the absence of benzaldehyde emission in the independently derived selfer Capsella orientalis. We used plant transformation, in vitro enzyme assays, population genetics and quantitative genetics to address these questions. CNL1 has been inactivated twice independently by point mutations in C. rubella, causing a loss of enzymatic activity. Both inactive haplotypes are found within and outside of Greece, the centre of origin of C. rubella, indicating that they arose before its geographical spread. By contrast, the loss of benzaldehyde emission in C. orientalis is not due to an inactivating mutation in CNL1. CNL1 represents a hotspot for mutations that eliminate benzaldehyde emission, potentially reflecting the limited pleiotropy and large effect of its inactivation. Nevertheless, even closely related species have followed different evolutionary routes in reducing floral scent.
Quorum-sensing bacteria in a growing colony of cells send out signalling molecules (so-called “autoinducers”) and themselves sense the autoinducer concentration in their vicinity. Once—due to increased local cell density inside a “cluster” of the growing colony—the concentration of autoinducers exceeds a threshold value, cells in this clusters get “induced” into a communal, multi-cell biofilm-forming mode in a cluster-wide burst event. We analyse quantitatively the influence of spatial disorder, the local heterogeneity of the spatial distribution of cells in the colony, and additional physical parameters such as the autoinducer signal range on the induction dynamics of the cell colony. Spatial inhomogeneity with higher local cell concentrations in clusters leads to earlier but more localised induction events, while homogeneous distributions lead to comparatively delayed but more concerted induction of the cell colony, and, thus, a behaviour close to the mean-field dynamics. We quantify the induction dynamics with quantifiers such as the time series of induction events and burst sizes, the grouping into induction families, and the mean autoinducer concentration levels. Consequences for different scenarios of biofilm growth are discussed, providing possible cues for biofilm control in both health care and biotechnology.
Background
Organisms are expected to respond to changing environmental conditions through local adaptation, range shift or local extinction. The process of local adaptation can occur by genetic changes or phenotypic plasticity, and becomes especially relevant when dispersal abilities or possibilities are somehow constrained. For genetic changes to occur, mutations are the ultimate source of variation and the mutation rate in terms of a mutator locus can be subject to evolutionary change. Recent findings suggest that the evolution of the mutation rate in a sexual species can advance invasion speed and promote adaptation to novel environmental conditions. Following this idea, this work uses an individual-based model approach to investigate if the mutation rate can also evolve in a sexual species experiencing different conditions of directional climate change, under different scenarios of colored stochastic environmental noise, probability of recombination and of beneficial mutations. The color of the noise mimicked investigating the evolutionary dynamics of the mutation rate in different habitats.
Results
The results suggest that the mutation rate in a sexual species experiencing directional climate change scenarios can evolve and reach relatively high values mainly under conditions of complete linkage of the mutator locus and the adaptation locus. In contrast, when they are unlinked, the mutation rate can slightly increase only under scenarios where at least 50% of arising mutations are beneficial and the rate of environmental change is relatively fast. This result is robust under different scenarios of stochastic environmental noise, which supports the observation of no systematic variation in the mutation rate among organisms experiencing different habitats.
Conclusions
Given that 50% beneficial mutations may be an unrealistic assumption, and that recombination is ubiquitous in sexual species, the evolution of an elevated mutation rate in a sexual species experiencing directional climate change might be rather unlikely. Furthermore, when the percentage of beneficial mutations and the population size are small, sexual species (especially multicellular ones) producing few offspring may be expected to react to changing environments not by adaptive genetic change, but mainly through plasticity. Without the ability for a plastic response, such species may become – at least locally – extinct.
The immense popularity of online communication services in the last decade has not only upended our lives (with news spreading like wildfire on the Web, presidents announcing their decisions on Twitter, and the outcome of political elections being determined on Facebook) but also dramatically increased the amount of data exchanged on these platforms. Therefore, if we wish to understand the needs of modern society better and want to protect it from new threats, we urgently need more robust, higher-quality natural language processing (NLP) applications that can recognize such necessities and menaces automatically, by analyzing uncensored texts. Unfortunately, most NLP programs today have been created for standard language, as we know it from newspapers, or, in the best case, adapted to the specifics of English social media.
This thesis reduces the existing deficit by entering the new frontier of German online communication and addressing one of its most prolific forms—users’ conversations on Twitter. In particular, it explores the ways and means by how people express their opinions on this service, examines current approaches to automatic mining of these feelings, and proposes novel methods, which outperform state-of-the-art techniques. For this purpose, I introduce a new corpus of German tweets that have been manually annotated with sentiments, their targets and holders, as well as lexical polarity items and their contextual modifiers. Using these data, I explore four major areas of sentiment research: (i) generation of sentiment lexicons, (ii) fine-grained opinion mining, (iii) message-level polarity classification, and (iv) discourse-aware sentiment analysis. In the first task, I compare three popular groups of lexicon generation methods: dictionary-, corpus-, and word-embedding–based ones, finding that dictionary-based systems generally yield better polarity lists than the last two groups. Apart from this, I propose a linear projection algorithm, whose results surpass many existing automatically-generated lexicons. Afterwords, in the second task, I examine two common approaches to automatic prediction of sentiment spans, their sources, and targets: conditional random fields (CRFs) and recurrent neural networks, obtaining higher scores with the former model and improving these results even further by redefining the structure of CRF graphs. When dealing with message-level polarity classification, I juxtapose three major sentiment paradigms: lexicon-, machine-learning–, and deep-learning–based systems, and try to unite the first and last of these method groups by introducing a bidirectional neural network with lexicon-based attention. Finally, in order to make the new classifier aware of microblogs' discourse structure, I let it separately analyze the elementary discourse units of each tweet and infer the overall polarity of a message from the scores of its EDUs with the help of two new approaches: latent-marginalized CRFs and Recursive Dirichlet Process.
Culturally diverse schools may constitute natural arenas for training crucial intercultural skills. We hypothesized that a classroom cultural diversity climate fostering contact and cooperation and multiculturalism, but not a climate fostering color‐evasion, would be positively related to adolescents’ intercultural competence. Adolescents in North Rhine‐Westphalia (N = 631, Mage = 13.69 years, 49% of immigrant background) and Berlin (N = 1,335, Mage = 14.69 years, 52% of immigrant background) in Germany reported their perceptions of the classroom cultural diversity climate and completed quantitative and qualitative measures assessing their intercultural competence. Multilevel structural equation models indicate that contact and cooperation, multiculturalism, and, surprisingly, also color‐evasion (as in emphasizing a common humanity), were positively related to the intercultural competence of immigrant and non‐immigrant background students. We conclude that all three aspects of the classroom climate are uniquely related to aspects of adolescents’ intercultural competence and that none of them may be sufficient on their own.
Today's perovskite solar cells (PSCs) are limited mainly by their open‐circuit voltage (VOC) due to nonradiative recombination. Therefore, a comprehensive understanding of the relevant recombination pathways is needed. Here, intensity‐dependent measurements of the quasi‐Fermi level splitting (QFLS) and of the VOC on the very same devices, including pin‐type PSCs with efficiencies above 20%, are performed. It is found that the QFLS in the perovskite lies significantly below its radiative limit for all intensities but also that the VOC is generally lower than the QFLS, violating one main assumption of the Shockley‐Queisser theory. This has far‐reaching implications for the applicability of some well‐established techniques, which use the VOC as a measure of the carrier densities in the absorber. By performing drift‐diffusion simulations, the intensity dependence of the QFLS, the QFLS‐VOC offset and the ideality factor are consistently explained by trap‐assisted recombination and energetic misalignment at the interfaces. Additionally, it is found that the saturation of the VOC at high intensities is caused by insufficient contact selectivity while heating effects are of minor importance. It is concluded that the analysis of the VOC does not provide reliable conclusions of the recombination pathways and that the knowledge of the QFLS‐VOC relation is of great importance.
The in‐depth understanding of charge carrier photogeneration and recombination mechanisms in organic solar cells is still an ongoing effort. In donor:acceptor (bulk) heterojunction organic solar cells, charge photogeneration and recombination are inter‐related via the kinetics of charge transfer states—being singlet or triplet states. Although high‐charge‐photogeneration quantum yields are achieved in many donor:acceptor systems, only very few systems show significantly reduced bimolecular recombination relative to the rate of free carrier encounters, in low‐mobility systems. This is a serious limitation for the industrialization of organic solar cells, in particular when aiming at thick active layers. Herein, a meta‐analysis of the device performance of numerous bulk heterojunction organic solar cells is presented for which field‐dependent photogeneration, charge carrier mobility, and fill factor are determined. Herein, a “spin‐related factor” that is dependent on the ratio of back electron transfer of the triplet charge transfer (CT) states to the decay rate of the singlet CT states is introduced. It is shown that this factor links the recombination reduction factor to charge‐generation efficiency. As a consequence, it is only in the systems with very efficient charge generation and very fast CT dissociation that free carrier recombination is strongly suppressed, regardless of the spin‐related factor.
Perovskite solar cells combine high carrier mobilities with long carrier lifetimes and high radiative efficiencies. Despite this, full devices suffer from significant nonradiative recombination losses, limiting their VOC to values well below the Shockley–Queisser limit. Here, recent advances in understanding nonradiative recombination in perovskite solar cells from picoseconds to steady state are presented, with an emphasis on the interfaces between the perovskite absorber and the charge transport layers. Quantification of the quasi‐Fermi level splitting in perovskite films with and without attached transport layers allows to identify the origin of nonradiative recombination, and to explain the VOC of operational devices. These measurements prove that in state‐of‐the‐art solar cells, nonradiative recombination at the interfaces between the perovskite and the transport layers is more important than processes in the bulk or at grain boundaries. Optical pump‐probe techniques give complementary access to the interfacial recombination pathways and provide quantitative information on transfer rates and recombination velocities. Promising optimization strategies are also highlighted, in particular in view of the role of energy level alignment and the importance of surface passivation. Recent record perovskite solar cells with low nonradiative losses are presented where interfacial recombination is effectively overcome—paving the way to the thermodynamic efficiency limit.
The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes.
Biochar is being discussed as a soil amendment to improve soil fertility and mitigate climate change. While biochar interactions with soil microbial biota have been frequently studied, interactions with soil mesofauna are understudied. We here present an experiment in which we tested if the collembolan Folsomia candida I) can transport biochar particles, II) if yes, how far the particles are distributed within 10 days, and III) if it shows a preference among biochars made from different feedstocks, i.e. pine wood, pine bark and spelt husks. In general, biochar particles based on pine bark and pine wood were consistently distributed significantly more than those made of spelt husks, but all types were transported more than 4cm within 10 days. Additionally, we provide evidence that biochar particles can become readily attached to the cuticle of collembolans and hence be transported, potentially even over large distances. Our study shows that the soil mesofauna can indeed act as a vector for the transport of biochar particles and show clear preferences depending on the respective feedstock, which would need to be studied in more detail in the future.
There is evidence that infants start extracting words from fluent speech around 7.5 months of age (e.g., Jusczyk & Aslin, 1995) and that they use at least two mechanisms to segment words forms from fluent speech: prosodic information (e.g., Jusczyk, Cutler & Redanz, 1993) and statistical information (e.g., Saffran, Aslin & Newport, 1996). However, how these two mechanisms interact and whether they change during development is still not fully understood.
The main aim of the present work is to understand in what way different cues to word segmentation are exploited by infants when learning the language in their environment, as well as to explore whether this ability is related to later language skills. In Chapter 3 we pursued to determine the reliability of the method used in most of the experiments in the present thesis (the Headturn Preference Procedure), as well as to examine correlations and individual differences between infants’ performance and later language outcomes. In Chapter 4 we investigated how German-speaking adults weigh statistical and prosodic information for word segmentation. We familiarized adults with an auditory string in which statistical and prosodic information indicated different word boundaries and obtained both behavioral and pupillometry responses. Then, we conducted further experiments to understand in what way different cues to word segmentation are exploited by 9-month-old German-learning infants (Chapter 5) and by 6-month-old German-learning infants (Chapter 6). In addition, we conducted follow-up questionnaires with the infants and obtained language outcomes at later stages of development.
Our findings from this thesis revealed that (1) German-speaking adults show a strong weight of prosodic cues, at least for the materials used in this study and that (2) German-learning infants weight these two kind of cues differently depending on age and/or language experience. We observed that, unlike English-learning infants, 6-month-old infants relied more strongly on prosodic cues. Nine-month-olds do not show any preference for either of the cues in the word segmentation task. From the present results it remains unclear whether the ability to use prosodic cues to word segmentation relates to later language vocabulary. We speculate that prosody provides infants with their first window into the specific acoustic regularities in the signal, which enables them to master the specific stress pattern of German rapidly. Our findings are a step forwards in the understanding of an early impact of the native prosody compared to statistical learning in early word segmentation.
Due to the enhanced electromagnetic field at the tips of metal nanoparticles, the spiked structure of gold nanostars (AuNSs) is promising for surface-enhanced Raman scattering (SERS). Therefore, the challenge is the synthesis of well designed particles with sharp tips. The influence of different surfactants, i.e., dioctyl sodium sulfosuccinate (AOT), sodium dodecyl sulfate (SDS), and benzylhexadecyldimethylammonium chloride (BDAC), as well as the combination of surfactant mixtures on the formation of nanostars in the presence of Ag⁺ ions and ascorbic acid was investigated. By varying the amount of BDAC in mixed micelles the core/spike-shell morphology of the resulting AuNSs can be tuned from small cores to large ones with sharp and large spikes. The concomitant red-shift in the absorption toward the NIR region without losing the SERS enhancement enables their use for biological applications and for time-resolved spectroscopic studies of chemical reactions, which require a permanent supply with a fresh and homogeneous solution. HRTEM micrographs and energy-dispersive X-ray (EDX) experiments allow us to verify the mechanism of nanostar formation according to the silver underpotential deposition on the spike surface in combination with micelle adsorption.