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The number of sensors used in modern devices is rapidly increasing, and the interaction with sensors demands analog-to-digital data conversion (ADC). A conventional ADC in leading-edge technologies faces
many issues due to signal swings, manufacturing deviations, noise, etc. Designers of ADCs are moving to the
time domain and digital designs techniques to deal with these issues. This work pursues a novel self-adaptive
spiking neural ADC (SN-ADC) design with promising features, e.g., technology scaling issues, low-voltage
operation, low power, and noise-robust conditioning. The SN-ADC uses spike time to carry the information.
Therefore, it can be effectively translated to aggressive new technologies to implement reliable advanced sensory electronic systems. The SN-ADC supports self-x (self-calibration, self-optimization, and self-healing) and
machine learning required for the internet of things (IoT) and Industry 4.0. We have designed the main part of
SN-ADC, which is an adaptive spike-to-digital converter (ASDC). The ASDC is based on a self-adaptive complementary metal–oxide–semiconductor (CMOS) memristor. It mimics the functionality of biological synapses,
long-term plasticity, and short-term plasticity. The key advantage of our design is the entirely local unsupervised
adaptation scheme. The adaptation scheme consists of two hierarchical layers; the first layer is self-adapted, and
the second layer is manually treated in this work. In our previous work, the adaptation process is based on 96 variables. Therefore, it requires considerable adaptation time to correct the synapses’ weight. This paper proposes a
novel self-adaptive scheme to reduce the number of variables to only four and has better adaptation capability
with less delay time than our previous implementation. The maximum adaptation times of our previous work
and this work are 15 h and 27 min vs. 1 min and 47.3 s. The current winner-take-all (WTA) circuits have issues, a
high-cost design, and no identifying the close spikes. Therefore, a novel WTA circuit with memory is proposed.
It used 352 transistors for 16 inputs and can process spikes with a minimum time difference of 3 ns. The ASDC
has been tested under static and dynamic variations. The nominal values of the SN-ADC parameters’ number
of missing codes (NOMCs), integral non-linearity (INL), and differential non-linearity (DNL) are no missing
code, 0.4 and 0.22 LSB, respectively, where LSB stands for the least significant bit. However, these values are
degraded due to the dynamic and static deviation with maximum simulated change equal to 0.88 and 4 LSB and
6 codes for DNL, INL, and NOMC, respectively. The adaptation resets the SN-ADC parameters to the nominal
values. The proposed ASDC is designed using X-FAB 0.35 µm CMOS technology and Cadence tools.
A potential fucoidan-based PEGylated PLGA nanoparticles (NPs) offering a proper delivery of N-methyl anthranilic acid (MA, a model of hydrophobic anti-inflammatory drug) have been
developed via the formation of fucoidan aqueous coating surrounding PEGylated PLGA NPs. The optimum formulation (FuP2) composed of fucoidan:m-PEG-PLGA (1:0.5 w/w) with particle size(365 ± 20.76 nm), zeta potential (-22.30 ± 2.56 mV), % entrapment efficiency (85.45 ± 7.41), drug loading (51.36 ± 4.75 µg/mg of NPs), % initial burst (47.91 ± 5.89), and % cumulative release
(102.79 ± 6.89) has been further investigated for the anti-inflammatory in vivo study. This effect of
FuP2 was assessed in rats’ carrageenan-induced acute inflammation model. The average weight of the
paw edema was significantly lowered (p ≤ 0.05) by treatment with FuP2. Moreover, cyclooxygenase-2 and tumor necrosis factor-alpha immunostaining were decreased in FuP2 treated group compared to the other groups. The levels of prostaglandin E2, nitric oxide, and malondialdehyde were significantly
reduced (p ≤ 0.05) in the FuP2-treated group. A significant reduction (p ≤ 0.05) in the expression
of interleukins (IL-1b and IL-6) with an improvement of the histological findings of the paw tissues was observed in the FuP2-treated group. Thus, fucoidan-based PEGylated PLGA–MA NPs are a promising anti-inflammatory delivery system that can be applied for other similar drugs potentiating their pharmacological and pharmacokinetic properties.
Manipulating deformable linear objects - Vision-based recognition of contact state transitions -
(1999)
A new and systematic approach to machine vision-based robot manipulation of deformable (non-rigid) linear objects is introduced. This approach reduces the computational needs by using a simple state-oriented model of the objects. These states describe the relation of the object with respect to an obstacle and are derived from the object image and its features. Therefore, the object is segmented from a standard video frame using a fast segmentation algorithm. Several object features are presented which allow the state recognition of the object while being manipulated by the robot.
Self-adaptation allows software systems to autonomously adjust their behavior during run-time by handling all possible
operating states that violate the requirements of the managed system. This requires an adaptation engine that receives adaptation
requests during the monitoring process of the managed system and responds with an automated and appropriate adaptation
response. During the last decade, several engineering methods have been introduced to enable self-adaptation in software systems.
However, these methods lack addressing (1) run-time uncertainty that hinders the adaptation process and (2) the performance
impacts resulted from the complexity and the large number of the adaptation space. This paper presents CRATER, a framework
that builds an external adaptation engine for self-adaptive software systems. The adaptation engine, which is built on Case-based
Reasoning, handles the aforementioned challenges together. This paper is braced with an experiment illustrating the benefits of
this framework. The experimental results shows the potential of CRATER in terms handling run-time uncertainty and adaptation
remembrance that enhances the performance for large number of adaptation space.
Postmortem Analysis of Decayed Online Social Communities: Cascade Pattern Analysis and Prediction
(2018)
Recently, many online social networks, such as MySpace, Orkut, and Friendster, have faced inactivity decay of their members, which contributed to the collapse of these networks. The reasons, mechanics, and prevention mechanisms of such inactivity decay are not fully understood. In this work, we analyze decayed and alive subwebsites from the Stack Exchange platform. The analysis mainly focuses on the inactivity cascades that occur among the members of these communities. We provide measures to understand the decay process and statistical analysis to extract the patterns that accompany the inactivity decay. Additionally, we predict cascade size and cascade virality using machine learning. The results of this work include a statistically significant difference of the decay patterns between the decayed and the alive subwebsites. These patterns are mainly cascade size, cascade virality, cascade duration, and cascade similarity. Additionally, the contributed prediction framework showed satisfactorily prediction results compared to a baseline predictor. Supported by empirical evidence, the main findings of this work are (1) there are significantly different decay patterns in the alive and the decayed subwebsites of the Stack Exchange; (2) the cascade’s node degrees contribute more to the decay process than the cascade’s virality, which indicates that the expert members of the Stack Exchange subwebsites were mainly responsible for the activity or inactivity of the Stack Exchange subwebsites; (3) the Statistics subwebsite is going through decay dynamics that may lead to it becoming fully-decayed; (4) the decay process is not governed by only one network measure, it is better described using multiple measures; (5) decayed subwebsites were originally less resilient to inactivity decay, unlike the alive subwebsites; and (6) network’s structure in the early stages of its evolution dictates the activity/inactivity characteristics of the network.
Tracking waterborne microplastic (MP) in urban areas is a challenging task because of the various sources and transport pathways involved. Since MP occurs in low concentrations in most wastewater and stormwater streams, large sample volumes need to be captured, prepared, and carefully analyzed. The recent research in urban areas focused mainly on MP emissions at wastewater treatment plants (WWTPs), as obvious entry points into receiving waters. However, important transport pathways under wet-weather conditions are yet not been investigated thoroughly. In addition, the lack of comprehensive and comparable sampling strategies complicated the attempts for a deeper understanding of occurrence and sources. The goal of this paper is to (i) introduce and describe sampling strategies for MP at different locations in a municipal catchment area under dry and wet-weather conditions, (ii) quantify MP emissions from the entire catchment and two other smaller ones within the bigger catchment, and (iii) compare the emissions under dry and wet-weather conditions. WWTP has a high removal rate of MP (>96%), with an estimated emission rate of 189 kg/a or 0.94 g/[population equivalents (PEQ · a)], and polyethylene (PE) as the most abundant MP. The specific dry-weather emissions at a subcatchment were ≈30 g/(PEQ · a) higher than in the influent of WWTP with 23 g/(PEQ · a). Specific wet-weather emissions from large sub-catchment with higher traffic and population densities were 1952 g/(ha · a) higher than the emissions from smaller catchment (796 g/[ha · a]) with less population and traffic. The results suggest that wet-weather transport pathways are likely responsible for 2–4 times more MP emissions into receiving waters compared to dry-weather ones due to tire abrasion entered from streets through gullies. However, more investigations of wet-weather MP need to be carried out considering additional catchment attributes and storm event characteristics.
In this paper we consider the stochastic primitive equation for geophysical flows subject to transport noise and turbulent pressure. Admitting very rough noise terms, the global existence and uniqueness of solutions to this stochastic partial differential equation are proven using stochastic maximal
-regularity, the theory of critical spaces for stochastic evolution equations, and global a priori bounds. Compared to other results in this direction, we do not need any smallness assumption on the transport noise which acts directly on the velocity field and we also allow rougher noise terms. The adaptation to Stratonovich type noise and, more generally, to variable viscosity and/or conductivity are discussed as well.
Ein Bioraffineriekonzept für (Bier-)Treber wird vorgeschlagen, bei dem im Gegensatz zu bestehenden Konzepten wasserlösliche Komponenten durch Pressen abgetrennt und als Grundlage für eine Milchsäurefermentation mit Lactobacillus delbrueckii subsp. lactis verwendet werden. Die verbleibenden strukturellen Kohlenhydrate des Treberrückstandes werden durch hydrothermale und enzymatische Vorbehandlung in fermentierbare Zucker überführt. Es entstehen deutlich weniger Nebenprodukte, die das Wachstum von Mikroorganismen inhibieren können, als bei der Nutzung von nicht abgepresstem Treber.
Simulation of Particle Interaction with Surface Microdefects during Cold Gas-Dynamic Spraying
(2022)
The cold gas-dynamic spray (CGDS) technique is utilized for repairing processes of a
large number of metallic components in mechanical and process engineering, such as bridges or
vehicles. Fine particles impacting on the component surface can be severely deformed and penetrate
into the defects, filling and coating them, resulting in possible protection against corrosion or crack
propagation. This work focuses on the investigation of the impact behavior of cold sprayed particles
with the wall surface having microdefects in the form of cavities. The collision of fine single particles
with the substrate, both made from AISI 1045 steel, was simulated with the finite element method
(FEM) using the Johnson–Cook failure model. The impact phenomena of particles on different
microdefect geometries were obtained and compared with the collision on a smooth surface. The
particle diameter and defect were varied to investigate the influence of the size on the deformation
behaviour. The different impact scenarios result in different temperature and stress distributions in
the contact zone, penetration and deformation behavior during the collision.
Using molecular dynamics simulation, we study the cutting of an Fe single crystal using
tools with various rake angles α. We focus on the (110)[001] cut system, since here, the crystal
plasticity is governed by a simple mechanism for not too strongly negative rake angles. In this
case, the evolution of the chip is driven by the generation of edge dislocations with the Burgers
vector b = 1
2
[111], such that a fixed shear angle of φ = 54.7◦
is established. It is independent of
the rake angle of the tool. The chip form is rectangular, and the chip thickness agrees with the
theoretical result calculated for this shear angle from the law of mass conservation. We find that the
force angle χ between the direction of the force and the cutting direction is independent of the rake
angle; however, it does not obey the predictions of macroscopic cutting theories, nor the correlations
observed in experiments of (polycrystalline) cutting of mild steel. Only for (strongly) negative rake
angles, the mechanism of plasticity changes, leading to a complex chip shape or even suppressing the
formation of a chip. In these cases, the force angle strongly increases while the friction angle tends
to zero.
We present two techniques for reasoning from cases to solve classification tasks: Induction and case-based reasoning. We contrast the two technologies (that are often confused) and show how they complement each other. Based on this, we describe how they are integrated in one single platform for reasoning from cases: The Inreca system.
We present an approach to systematically describing case-based reasoning systems bydifferent kinds of criteria. One main requirement was the practical relevance of these criteria and their usability for real-life applications. We report on the results we achieved from a case study carried out in the INRECA1 Esprit project.
Substrate channeling is a widespread mechanism in metabolic pathways to avoid decomposition of unstable intermediates, competing reactions, and to accelerate catalytic turnover. During the biosynthesis of light-harvesting phycobilins in cyanobacteria, two members of the ferredoxin-dependent bilin reductases are involved in the reduction of the open-chain tetrapyrrole biliverdin IXα to the pink pigment phycoerythrobilin. The first reaction is catalyzed by 15,16-dihydrobiliverdin:ferredoxin oxidoreductase and produces the unstable intermediate 15,16-dihydrobiliverdin (DHBV). This intermediate is subsequently converted by phycoerythrobilin:ferredoxin oxidoreductase to the final product phycoerythrobilin. Although substrate channeling has been postulated already a decade ago, detailed experimental evidence was missing. Using a new on-column assay employing immobilized enzyme in combination with UV-Vis and fluorescence spectroscopy revealed that both enzymes transiently interact and that transfer of the intermediate is facilitated by a significantly higher binding affinity of DHBV toward phycoerythrobilin:ferredoxin oxidoreductase. Concluding from the presented data, the intermediate DHBV is transferred via proximity channeling.
Micro machining with micro pencil grinding tools (MPGTs) is an emerging technology that can be used to manufacture closed microchannel structures in hard and brittle materials as well as hardened steels like 16MnCr5. At their current operating conditions, these tools have a comparatively short tool life. In previous works, MPGTs in combination with a minimum quantity lubrication (MQL) system were used to manufacture microchannels in 16MnCr5 hardened steel. The study has shown that steel adhesions clog the abrasive layer of MPGTs, most likely resulting from insufficient lubrication. In this paper, a metalworking fluid (MWF) supply method was developed to improve the process: a submerged micro grinding process, in which machining takes place inside a pool of MWF. In this study, the effect of seven types of MWFs on material adhesions at the bottom surface of the tool is evaluated. Equivalent good MWFs are then compared in a micro pendulum grinding experiment till failure.
The scaffolding protein family Fe65, composed of Fe65, Fe65L1, and Fe65L2, was identified as an interaction partner of the amyloid precursor protein (APP), which plays a key function in Alzheimer’s disease. All three Fe65 family members possess three highly conserved interaction domains, forming complexes with diverse binding partners that can be assigned to different cellular functions, such as transactivation of genes in the nucleus, modulation of calcium homeostasis and lipid metabolism, and regulation of the actin cytoskeleton. In this article, we rule out putative new intracellular signaling mechanisms of the APP-interacting protein Fe65 in the regulation of actin cytoskeleton dynamics in the context of various neuronal functions, such as cell migration, neurite outgrowth, and synaptic plasticity.
Die Bestanderhaltung historischer Bauwerke bedarf gründlicher Voruntersuchung, Qualitätskontrolle und Bauwerksüberwachung, um die Eingriffe in die Denkmalsubstanz zu minimieren und Folgeschäden zu vermeiden. Zerstörungsfreie Prüfmethoden und numerische Modellierungsverfahren bieten heute bewährte und neue Möglichkeiten, gesicherte Kenntnisse über die Bauwerke und die altersbedingten Veränderungen ihrer Baumaterialien zu erzielen und gleichzeitig die Eingriffe für Materialentnahmen und Bauwerksöffnungen zu minimieren. Anhand von Fallbeispielen werden aktuelle Forschungsergebnisse präsentiert. Georadarmessungen werden mit theoretischen Modellierungen kombiniert, um gemessene Anomalien in Materialparametern zu begründen. Moderne Anforderungen wie die energetische Sanierung historischer Gebäude werfen neue Problemfelder auf, für die anhand von Modellierungen des Wärme- und Feuchtetransports Antworten gefunden werden. Die Weiterentwicklung von Ultraschallmesstechnik und Signalauswertung ermöglicht neue Anwendungen bei der Untersuchung verwitterter Sandsteinoberflächen mittels Rayleighwellen.
Die Möglichkeit einer Prämienanpassung in der deutschen PKV ist vom Wert des sogenannten auslösenden Faktors abhängig, der mittels einer linearen Extrapolation der Schadenquotienten der vergangenen drei Jahre berechnet wird. Seine frühzeitige, verlässliche Vorhersage ist aus Sicht des Risikomanagements von großer Bedeutung. Wir untersuchen deshalb vielfältige Vorhersageansätze, die von klassischen Zeitreihenansätzen und Regression über neuronale Netze bis hin zu hybriden Modellen reichen. Während bei den klassischen Methoden Regression mit ARIMA-Fehlern am besten abschneidet, zeigt ein neuronales Netz, das mit Zeitreihenvorhersage kombiniert oder auf desaisonalisierten und trendbereinigten Daten trainiert wurde, das insgesamt beste Verhalten.
Using molecular dynamics simulation, we study nanoindentation in large samples of Cu–Zr glass at various temperatures between zero and the glass transition temperature. We find that besides the elastic modulus, the yielding point also strongly (by around 50%) decreases with increasing temperature; this behavior is in qualitative agreement with predictions of the cooperative shear model. Shear-transformation zones (STZs) show up in increasing sizes at low temperatures, leading to shear-band activity. Cluster analysis of the STZs exhibits a power-law behavior in the statistics of STZ sizes. We find strong plastic activity also during the unloading phase; it shows up both in the deactivation of previous plastic zones and the appearance of new zones, leading to the observation of pop-outs. The statistics of STZs occurring during unloading show that they operate in a similar nature as the STZs found during loading. For both cases, loading and unloading, we find the statistics of STZs to be related to directed percolation. Material hardness shows a weak strain-rate dependence, confirming previously reported experimental findings; the number of pop-ins is reduced at slower indentation rate. Analysis of the dependence of our simulation results on the quench rate applied during preparation of the glass shows only a minor effect on the properties of STZs.
Plasticity in metallic glasses depends on their stoichiometry. We explore this dependence by molecular dynamics simulations for the case of CuZr alloys using the compositions Cu64.5Zr35.5, Cu50Zr50, and Cu35.5Zr64.5. Plasticity is induced by nanoindentation and orthogonal cutting. Only the Cu64.5Zr35.5 sample shows the formation of localized strain in the form of shear bands, while plasticity is more homogeneous for the other samples. This feature concurs with the high fraction of full icosahedral short-range order found for Cu64.5Zr35.5. In all samples, the atomic density is reduced in the plastic zone; this reduction is accompanied by a decrease of the average atom coordination, with the possible exception of Cu35.5Zr64.5, where coordination fluctuations are high. The strongest density reduction occurs in Cu64.5Zr35.5, where it is connected with the partial destruction of full icosahedral short-range order. The difference in plasticity mechanism influences the shape of the pileup and of the chip generated by nanoindentation and cutting, respectively.