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Chlorogenic acids (CGA) are phenolic compounds that form during the esterification of certain trans-cinnamic acids with (-)-quinic acid. According to several human intervention studies, they may have potential health benefits. Coffee is the main source of CGA in human nutrition, and is consumed either alone or in combination with a variety of foods. For this reason, the presented study aimed to clarify whether the simultaneous consumption of food, for example, a breakfast rich in carbohydrates, with instant coffee affects the absorption and bioavailability of CGA. The research specifically focused on how various food matrices, which are consumed at the same time as a coffee beverage, will influence kinetic parameters such as area under the curve (AUC), maximum plasma concentration (cmax), and time needed to reach maximum plasma concentration (tmax).
In a randomized crossover study, fourteen healthy participants consumed either pure instant coffee or coffee with a carbohydrate- or fat-rich meal. All of the subjects consumed the same quantity of CGA (3.1 mg CGA/kg body weight). Blood samples, collected at various time points up to 15 h after instant coffee consumption, were quantitatively analysed. Additionally, three urine collection intervals were chosen over a time period of 24h. High performance liquid chromatography electrospray ionization tandem mass spectrometry (HPLC-ESI-MS/MS) was used to determine the CGA present, along with the concentrations of respective metabolites.
During a blind data review meeting, 20 of the 56 analysed plasma metabolites were chosen for further statistical analysis. A total of 36 metabolites were monitored in the urine samples. Similar as in the plasma samples, between-treatment differences, measured through AUC, Cmax, and tmax, of various CGA derived metabolites were to estimate. Each treatment was also analysed in terms of the correlation between the plasma AUC and urinary excretion of seven metabolites.
It is already known that inter-individual variations in CGA absorption depends on gut microbial degradation and affects the efficacy of these compounds. Microorganisms present in the gastrointestinal tract metabolise CGA to form dihydroferulic acid (DHFA) and dihydrocaffeic acid (DHCA) derivatives, which precede the subsequent formation of a wide range of metabolites. Therefore stool samples were collected from the participants within 12 h before the second study day. Subsequent an ex-vivo incubation of faecal samples with 5-O-caffeoylquinic acid (5-CQA), the main chlorogenic acid found in coffee was performed. An HPLC system connected to a CoulArray® detector was used to measure the concentrations of 5-CQA and its metabolites. Reduced concentrations of 5-CQA as well as the appearance of DHCA and caffeic acid (CA) in the gut microbiota medium, were monitored to calculate the inter-individual kinetics for each compound. In addition, these samples were analysed for microbiota content by an external laboratory (L&S, Bad Bocklet, Germany). These results were used to distinguish whether the decreased or increased content of a specific microorganism was related to an individual’s decreased or increased metabolic efficiency. Finally, we used to aforementioned results to evaluate if any correlation could be drawn between the plasma appearance, urinary excretion and ability of microorganisms to degrade 5-CQA.
Strong inter-individual variation was observed for AUC, Cmax and tmax. The AUC measured the quantity of CGA in plasma samples. We noted that pure instant coffee consumption resulted in slightly higher CGA bioavailability than instant coffee with the additional consumption of a meal. However, these differences were not statistically significant. Additionally, the metabolites were divided into groups, according to similarity and chemical properties. They were further classified into three groups according to their physical structure and predicated from the area of appearance: directly from coffee (quinics), after first degradation and metabolism (phenolics, all trans-cinammic acids and their sulfates and glucuronides) as well as colonic degradation and metabolism (colonics, all dihydro compounds). These respective metabolic classes showed significant differences in the AUC values of certain classes yet no significant between-treatment differences. Our results corroborated earlier studies in that the three caffeoylquinic acid (CQA) isomers were absorbed to a lower extent whereas all feruloylquinic acids (FQA) were detected in comparably high amounts in the plasma samples of the volunteers. However, the amount of these quinic acid conjugates in the plasma samples accounted for only 0,5% of the total amount of identified. In contrast, at least 8.7% of the investigated compounds were identified to be phenolics. Dihydro compounds, the so known colonics, were identified as the most common metabolites (90.8%). Additionally, dihydroferulic acid (DHFA), meta-dihydrocoumaric acid (mDHCoA), dihydrocaffeic acid-3-sulfate (DHCA3S) and dihydroisoferulic acid (DHiFA) were identified to account for 78% of the studied metabolites, and thus represent the most abundant compounds circulating in the plasma after coffee consumption.
Irrespective of treatment, the tmax value for early metabolites (quinic and phenolic compounds) was observed between 0 and 2 h after the ingestion of coffee and tmax value for late metabolites (colonic metabolites) was observed between 7 and 10 h. The amount of colonic metabolites had not returned to the baseline level 15 h after the ingestion of coffee. The co-ingestion of breakfast and coffee, when compared to the ingestion of coffee alone, significantly increased the Cmax values for all quinic and phenolic compounds, as well as two colonic metabolites (DHCA and DHiFA). These differences also revealed that the three treatments differed in terms of the kinetics of release. Thus, future studies should use an extended plasma collection time with shorter intervals (e.g. 2 h) to provide a full pharmacokinetic profile.
There were no statistically significant between-treatment differences in the urine samples collected 24 h after coffee ingestion. However, urine samples collected within six hours of the consumption of coffee alone or in combination with a fat-rich meal showed significantly higher CGA quantities than samples collected at the same time point for coffee ingested with a carbohydrate-rich. Strong inter-individual variability and the fact that only 14 healthy subjects participated in the study hindered the identification of any clear trend between the plasma concentrations of metabolites and their excretion in urine.
Four hours after the ex vivo incubation of 5-CQA with individual faecal samples the sum of 5-CQA, CA, and DHCA varied strongly between participants. These findings could result from binding effects of the phenolic compounds with faecal constituents, further degradation or metabolism, and/or the release of bound phenolic substances before the experiment started. We hypothesized that for participants with high plasma AUCs of dihydro compounds, their incubation samples show also high concentrations of CA and DHCA in the incubation medium after four hours. No significant correlation could be found.
This study and all of the outcomes were exploratory. Due to the limited number of participants, we could only investigate tendencies for how the co-ingestion of food affects the bioavailability of CGAs and their respective metabolites following coffee consumption. Therefore, the achieved results are only indicative. Despite this limitation, the data highlight that even though all three treatments had strong similarities in the total bioavailability of CGAs and metabolites from instant coffee, there were between-treatment differences in the kinetics of release. The co-ingestion of breakfast and coffee favoured a slow and continuous release of colonic metabolites while non-metabolized coffee components were observed in plasma within the first hour when coffee was ingested alone.
In conclusion, both a shift in gastrointestinal transit time and the plasma metabolite composition were observed when the ingestion of coffee alone or in combination with breakfast were compared. These results showed that breakfast consumption induces the retarded release of chlorogenic acid metabolites in humans. The data from our human intervention study suggest that the bioavailability of chlorogenic acids from coffee and their derivatives does not only depend on chemical structure, molecular size and active or passive transport ability, but is also influenced by inter-individual differences. Therefore, we strongly recommend that future studies include metabolism experiments that focus on microbiota genotypes and/or the genotyping of individual subjects. This type of research could be pivotal to elucidating whether, and how, genotype affects the metabolic profile after chlorogenic acid intake.
Temporal Data Management and Incremental Data Recomputation with Wide-column Stores and MapReduce
(2017)
In recent years, ”Big Data” has become an important topic in academia
and industry. To handle the challenges and problems caused by Big Data,
new types of data storage systems called ”NoSQL stores” (means ”Not-only-
SQL”) have emerged.
”Wide-column stores” are one kind of NoSQL stores. Compared to relational database systems, wide-column stores introduce a new data model,
new IRUD (Insert, Retrieve, Update and Delete) semantics with support for
schema-flexibility, single-row transactions and data expiration constraints.
Moreover, each column stores multiple data versions with associated time-
stamps. Well-known examples are Google’s ”Big-table” and its open sourced
counterpart ”HBase”. Recently, such systems are increasingly used in business intelligence and data warehouse environments to provide decision support, controlling and revision capabilities.
Besides managing the current values, data warehouses also require management and processing of historical, time-related data. Data warehouses
frequently employ techniques for processing changes in various data sources
and incrementally applying such changes to the warehouse to keep it up-to-
date. Although both incremental data warehousing maintenance and temporal data management have been the subject of intensive research in the
relational database and finally commercial database products have picked up
the ability for temporal data processing and management, such capabilities
have not been explored systematically for today’s wide-column stores.
This thesis helps to address the shortcomings mentioned above. It care-
fully analyzes the properties of wide-column stores and the applicability
of mechanisms for temporal data management and incremental data ware-
house maintenance known from relational databases, extends well-known approaches and develops new capabilities for providing equivalent support in
wide-column stores.
Nonwoven materials are used as filter media which are the key component of automotive filters such as air filters, oil filters, and fuel filters. Today, the advanced engine technologies require innovative filter media with higher performances. A virtual microstructure of the nonwoven filter medium, which has similar filter properties as the existing material, can be used to design new filter media from existing media. Nonwoven materials considered in this thesis prominently feature non-overlapping fibers, curved fibers, fibers with circular cross section, fibers of apparently infinite length, and fiber bundles. To this end, as part of this thesis, we extend the Altendorf-Jeulin individual fiber model to incorporate all the above mentioned features. The resulting novel stochastic 3D fiber model can generate geometries with good visual resemblance of real filter media. Furthermore, pressure drop, which is one of the important physical properties of the filter, simulated numerically on the computed tomography (CT) data of the real nonwoven material agrees well (with a relative error of 8%) with the pressure drop simulated in the generated microstructure realizations from our model.
Generally, filter properties for the CT data and generated microstructure realizations are computed using numerical simulations. Since numerical simulations require extensive system memory and computation time, it is important to find the representative domain size of the generated microstructure for a required filter property. As part of this thesis, simulation and a statistical approach are used to estimate the representative domain size of our microstructure model. Precisely, the representative domain size with respect to the packing density, the pore size distribution, and the pressure drop are considered. It turns out that the statistical approach can be used to estimate the representative domain size for the given property more precisely and using less generated microstructures than the purely simulation based approach.
Among the various properties of fibrous filter media, fiber thickness and orientation are important characteristics which should be considered in design and quality assurance of filter media. Automatic analysis of images from scanning electron microscopy (SEM) is a suitable tool in that context. Yet, the accuracy of such image analysis tools cannot be judged based on images of real filter media since their true fiber thickness and orientation can never be known accurately. A solution is to employ synthetically generated models for evaluation. By combining our 3D fiber system model with simulation of the SEM imaging process, quantitative evaluation of the fiber thickness and orientation measurements becomes feasible. We evaluate the state-of-the-art automatic thickness and orientation estimation method that way.
In the present work the concept of decarboxylative couplings and the strategy to use carboxylates as directing groups for C-H functionalizations have been decisively improved in three ways. These concepts emphasize the multifaceted nature of aromatic carboxylic acids as expedient starting materials in homogeneous catalysis to construct highly desirable molecular scaffolds in a straightforward fashion.
In the first project, the restriction of decarboxylative biaryl synthesis to exclusively couple aryl halides with ortho-substituted benzoic acids has been overcome by a holistic optimization of a Cu/Pd bimetallic catalyst system. Long ago postulated, this is now the proof that decarboxylative cross-couplings are not intrinsically limited to different decarboxylation propensities of benzoic acids or hampered by excess halides, accessing for the first time the entire spectrum of aromatic carboxylic acids as starting materials for the decarboxylative biaryl synthesis. The second project uses the carboxyl moiety as directing group for the ortho-arylation with aryl bromides and -chlorides catalyzed by comparatively inexpensive ruthenium. The carboxylic acid group remains untouched after the ortho-functionalization giving the possibility to a wealth of further diversifications via decarboxylative ipso-substitutions. Within the same project, a Cu/Ru bimetallic catalyst system was found to be able to switch the decarboxylative biaryl coupling from the ipso- to the ortho-position, complementing the Cu/Pd system developed in the first project. In a third project, a redox neutral C-C bond formation revealed the full synthetic potential of the carboxyl group. The COOH moiety acts as a classical directing group for the C-H hydroarylation of internal alkynes to form highly desirable 2-vinyl benzoic acids. With propargylic alcohols the hydroarylation is followed by an in situ esterification, showing that after easing the C-H cleavage, the directing group can be transformed into another functional group, thus, acting as a transformable directing group. Most importantly, a new fascinating reaction mode is activated by embedding the decarboxylation within the C-H functionalization event. This mode of action is capable to solve regioselectivity issues that inherently occur when dealing with carboxylates as directing groups. A so-called deciduous directing group is cast off simultaneously within the C-H functionalization event, resulting in an inherently monoselective pathway.
These methods were developed with the permanent goal of ensuring high sustainability. They do require neither pre-functionalized starting materials nor additional oxidants and provide access to a number of chemically relevant molecules from abundant, inexpensive and toxicologically innocuous educts.
The thesis studies change points in absolute time for censored survival data with some contributions to the more common analysis of change points with respect to survival time. We first introduce the notions and estimates of survival analysis, in particular the hazard function and censoring mechanisms. Then, we discuss change point models for survival data. In the literature, usually change points with respect to survival time are studied. Typical examples are piecewise constant and piecewise linear hazard functions. For that kind of models, we propose a new algorithm for numerical calculation of maximum likelihood estimates based on a cross entropy approach which in our simulations outperforms the common Nelder-Mead algorithm.
Our original motivation was the study of censored survival data (e.g., after diagnosis of breast cancer) over several decades. We wanted to investigate if the hazard functions differ between various time periods due, e.g., to progress in cancer treatment. This is a change point problem in the spirit of classical change point analysis. Horváth (1998) proposed a suitable change point test based on estimates of the cumulative hazard function. As an alternative, we propose similar tests based on nonparametric estimates of the hazard function. For one class of tests related to kernel probability density estimates, we develop fully the asymptotic theory for the change point tests. For the other class of estimates, which are versions of the Watson-Leadbetter estimate with censoring taken into account and which are related to the Nelson-Aalen estimate, we discuss some steps towards developing the full asymptotic theory. We close by applying the change point tests to simulated and real data, in particular to the breast cancer survival data from the SEER study.
Novel Pseudocyclopeptides Containing 1,4-Disubstituted 1,2,3-Triazole Subunits for Anion Recognition
(2017)
Anion recognition is one of the most rapidly growing areas in the field of Supramolecular Chemistry due to the vital role of anions in the environment, in biology and in industry. The development of new anion binding motifs that can also be combined with known ones in a novel receptor is a timely topic. In this context, we have synthesized three cyclic pseudopeptides 16, 17 and 18, containing conventional H-bond donors (amide) in combination with, respectively, triazole C–H or triazole C–I functions.
All three receptors were synthesized by using a combination of peptide and click chemistry. Structural studies show that all three pseudopeptides adopt conformations with the triazole C-H or C-I groups pointing into the cavity center to allow them to contribute to binding. Quantitative binding studies showed that the cyclic pseudohexapeptide 1 coordinates to oxoanions (sulfate, dihydrogenphosphate, and hydrogenpyrophosphate) with different binding strengths and complex stoichiometries in 2.5 vol% water/DMSO.
Anion selectivity of 16 significantly changes when the cavity size of this pseudopeptide is increased to obtain the larger analog 17. This pseudooctapeptide forms well defined complexes with protonated phosphate anions. The complexation involves sandwiching of a cyclic tetramer of dihydrogenphosphate or a dimer of dihydrogenpyrophosphate anions by two pseudopeptide rings. Both complexes were characterized structurally in the solid state. They are stable in solution (2.5 vol% water/DMSO) as result of the interaction between hydrogen bond donors of 17 and the oxygen atoms of the anionic aggregates. The complexes can also be transferred to the gas phase without decomposition.
Anion selectivity of 16 was further altered by introducing iodine atom in the C5 position of the 1,4-disubstituted 1,2,3-triazole units. The corresponding cyclic pseudohexapeptide 18 features a smaller cavity diameter than 17 as a result of the iodide atoms and was therefore found to only coordinate to smaller spherical anions such as chloride. It forms 1:1 complexes with chloride, bromide and iodide in 2.5 vol% water/DMSO. Among the halides, 18 has highest affinity for chloride followed by bromide and iodide. The same stability trend was also observed in the gas phase by ESI/MS.
Concluding, I prepared three new macrocyclic pseudopeptides during my PhD and characterized their complexes with anions in terms of structure and affinity. All of these pseudopeptides were shown to interact with phosphate-derived anions, which renders them unique among the anion receptors developed in the Kubik group before.
In the present work, the interaction of diatomic molecules with charged transition metal clusters and complexes was investigated. Temperature controlled isothermal kinetic studies served to elucidate the adsorption behavior of transition metal clusters. Infrared multiple photon dissociation (IR-MPD) experiments in conjunction with density functional theory (DFT) computations enabled the analysis of adsorbate induced changes on the structure and spin multiplicity of transition metal cores. A tandem cryo trap setup was used for the kinetic and spectroscopic investigations of the given compounds as isolated species in the gas phase. The presented investigations enabled insight into the metal-adsorbate bonding and provided cluster size and adsorbate coverage dependent information on cluster surface morphologies.
In this thesis viscoelastic material models are established to investigate the nature of continuous calving processes at Antarctic ice shelves. Physics-based descriptions of calving require appropriate fracture criteria to separate icebergs from the remaining ice shelf. Hence, criteria of the stress, the strain, and the self-similarity criterion are considered within finite-element computations. Crucial parameters in the models to determine the position of calving are the accurate knowledge of the geometry, especially the freeboard height, while the material parameters mainly influence the time span between two successive calving events. The extension to nonlinear material models is necessary to properly analyze the internal forces also for large deformations that occur for longer times of the viscous ice flow.
Magnetic and Structural Characterization of Isolated Gaseous Ions by XMCD and IRMPD Spectroscopy
(2017)
This thesis comprises four independent research studies on the magnetic and structural characterization of isolated ions in the gas phase. The electrospray ionization (ESI) technique is used for the transfer of (multi-)metallic complexes and organic molecules from solution into the gas phase. The subsequent storage of molecular ions in ion traps allows for a variety of spectroscopic methods in order to investigate the intrinsic properties of the isolated species void of solvent, crystal lattice, bulk or supporting surface effects. The magnetic properties of metal complexes are elucidated by gas phase X-ray magnetic circular dichroism (XMCD) spectroscopy. The element selective technique in combination with sum rule analysis allows for a separate determination of spin and orbital magnetic moments at different metal centers. Structural investigations on isolated molecular ions in terms of coordination sphere, binding motifs and hydrogen bonds are conducted using infrared multiple photon dissociation (IRMPD) spectroscopy. A resonant two color IRMPD technique serves to increase fragmentation yields, overcome dissociation bottlenecks and reveal otherwise dark bands. Comparison of experimental IRMPD spectra with calculated harmonic absorption spectra by density functional theory (DFT) provides structural assignments for a profound understanding of intra- and intermolecular interactions.
”In contemporary electronics 80% of a chip may perform digital functions but the 20%
of analog functions may take 80% of the development time.” [1]. Aggravating this, the
demands on analog design is increasing with rapid technology scaling. Most designs
have moved away from analog to digital domains, where possible, however, interacting
with the environment will always require analog to digital data conversion. Adding to
this problem, the number of sensors used in consumer and industry related products are
rapidly increasing. Designers of ADCs are dealing with this problem in several ways, the
most important is the migration towards digital designs and time domain techniques.
Time to Digital Converters (TDC) are becoming increasingly popular for robust signal
processing. Biological neurons make use of spikes, which carry spike timing information
and will not be affected by the problems related to technology scaling. Neuromorphic
ADCs still remain exotic with few implementations in sub-micron technologies Table 2.7.
Even among these few designs, the strengths of biological neurons are rarely exploited.
From a previous work [2], LUCOS, a high dynamic range image sensor, the efficiency
of spike processing has been validated. The ideas from this work can be generalized to
make a highly effective sensor signal conditioning system, which carries the promise to
be robust to technology scaling.
The goal of this work is to create a novel spiking neural ADC as a novel form of a
Multi-Sensor Signal Conditioning and Conversion system, which
• Will be able to interface with or be a part of a System on Chip with traditional
analog or advanced digital components.
• Will have a graceful degradation.
• Will be robust to noise and jitter related problems.
• Will be able to learn and adapt to static errors and dynamic errors.
• Will be capable of self-repair, self-monitoring and self-calibration
Sensory systems in humans and other animals analyze the environment using several
techniques. These techniques have been evolved and perfected to help the animal sur-
vive. Different animals specialize in different sense organs, however, the peripheral
neural network architectures remain similar among various animal species with few ex-
ceptions. While there are many biological sensing techniques present, most popularly
used engineering techniques are based on intensity detection, frequency detection, and
edge detection. These techniques are used with traditional analog processing (e.g., colorvi
sensors using filters), and with biological techniques (e.g. LUCOS chip [2]). The local-
ization capability of animals has never been fully utilized.
One of the most important capabilities for animals, vertebrates or invertebrates, is the
capability for localization. The object of localization can be predator, prey, sources of
water, or food. Since these are basic necessities for survival, they evolve much faster
due to the survival of the fittest. In fact, localization capabilities, even if the sensors
are different, have convergently evolved to have same processing methods (coincidence
detection) in their peripheral neurons (for e.g., forked tongue of a snake, antennae of
a cockroach, acoustic localization in fishes and mammals). This convergent evolution
increases the validity of the technique. In this work, localization concepts based on
acoustic localization and tropotaxis are investigated and employed for creation of novel
ADCs.
Unlike intensity and frequency detection, which are not linear (for e.g. eyes saturate in
bright light, loose color perception in low light), localization is inherently linear. This
is mainly because the accurate localization of predator or prey can be the difference
between life and death for an animal.
Figure 1 visually explains the ADC concept proposed in this work. This has two parts.
(1) Sensor to Spike(time) Conversion (SSC), (2) Spike(time) to Digital Conversion(SDC).
Both of the structures have been designed with models of biological neurons. The
combination of these two structures is called SSDC.
To efficiently implement the proposed concept, a comparison of several biological neural
models is made and two models are shortlisted. Various synapse structures are also
studied. From this study, Leaky Integrate and Fire neuron (LIF) is chosen since it
fulfills all the requirements of the proposed structure. The analog neuron and synapse
designs from Indiveri et. al. [3], [4] were taken, and simulations were conducted using
cadence and the behavioral equivalence with biological counterpart was checked. The
LIF neuron had features, that were not required for the proposed approach. A simple
LIF neuron stripped of these features and was designed to be as fast as allowed by the
technology.
The SDC was designed with the neural building blocks and the delays were designed
using buffer chains. This SDC converts incoming Time Interval Code (TIC) to sparse
place coding using coincidence detection. Coincidence detection is a property of spiking
neurons, which is a time domain equivalent of a Gaussian Kernel. The SDC is designed to
have an online reconfigurable Gaussian kernel width, weight, threshold, and refractory
period. The advantage of sparse place codes, which contain rank order coding wasvii
Figure 1: ADC as a localization problem (right), Jeffress model of sound localization
visualized (left). The values t 1 and t 2 indicate the time taken from the source to s1 and
s2 respectively.
described in our work [5]. A time based winner take all circuit with memory was created
based on a previous work [6] for reading out of sparse place codes asynchronously.
The SSC was also initially designed with the same building blocks. Additionally, a
differential synapse was designed for better SSC. The sensor element considered wasviii
a Wheatstone full bridge AMR sensor AFF755 from Sensitec GmbH. A reconfigurable
version of the synapse was also designed for a more generic sensor interface.
The first prototype chip SSDCα was designed with 257 modules of coincidence detectors
realizing the SDC and the SSC. Since the spike times are the most important information,
the spikes can be treated as digital pulses. This provides the capability for digital
communication between analog modules. This creates a lot of freedom for use of digital
processing between the discussed analog modules. This advantage is fully exploited
in the design of SSDCα. Three SSC modules are multiplexed to the SDC. These SSC
modules also provide outputs from the chip simultaneously. A rising edge detecting fixed
pulse width generation circuit is used to create pulses that are best suited for efficient
performance of the SDC. The delay lines are made reconfigurable to increase robustness
and modify the span of the SDC. The readout technique used in the first prototype is
a relatively slow but safe shift register. It is used to analyze the characteristics of the
core work. This will be replaced by faster alternatives discussed in the work. The area
of the chip is 8.5 mm 2 . It has a sampling rate from DC to 150 kHz. It has a resolution
from 8-bit to 13-bit. It has 28,200 transistors on the chip. It has been designed in 350
nm CMOS technology from ams. The chip has been manufactured and tested with a
sampling rate of 10 kHz and a theoretical resolution of 8 bits. However, due to the
limitations of our Time-Interval-Generator, we are able to confirm for only 4 bits of
resolution.
The key novel contributions of this work are
• Neuromorphic implementation of AD conversion as a localization problem based
on sound localization and tropotaxis concepts found in nature.
• Coincidence detection with sparse place coding to enhance resolution.
• Graceful degradation without redundant elements, inherent robustness to noise,
which helps in scaling of technologies
• Amenable to local adaptation and self-x features.
Conceptual goals have all been fulfilled, with the exception of adaptation. The feasibility
for local adaptation has been shown with promising results and further investigation is
required for future work. This thesis work acts as a baseline, paving the way for R&D
in a new direction. The chip design has used 350 nm ams hitkit as a vehicle to prove
the functionality of the core concept. The concept can be easily ported to present
aggressively-scaled-technologies and future technologies.