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Cybersecurity of Industrial Control Systems (ICS) is an important issue, as ICS incidents may have a direct impact on safety of people or the environment. At the same time the awareness and knowledge about cybersecurity, particularly in the context of ICS, is alarmingly low. Industrial honeypots offer a cheap and easy to implement way to raise cybersecurity awareness and to educate ICS staff about typical attack patterns. When integrated in a productive network, industrial honeypots may not only reveal attackers early but may also distract them from the actual important systems of the network. Implementing multiple honeypots as a honeynet, the systems can be used to emulate or simulate a whole Industrial Control System. This paper describes a network of honeypots emulating HTTP, SNMP, S7communication and the Modbus protocol using Conpot, IMUNES and SNAP7. The nodes mimic SIMATIC S7 programmable logic controllers (PLCs) which are widely used across the globe. The deployed honeypots' features will be compared with the features of real SIMATIC S7 PLCs. Furthermore, the honeynet has been made publicly available for ten days and occurring cyberattacks have been analyzed
Performance Investigations of the IP Multicast Architecture / Hermanns, Oliver ; Schuba, Marko
(1995)
Characterising an insect antenna as a receptor for a biosensor by means of impedance spectroscopy
(2001)
The Gram-positive endospore-forming bacterium Bacillus licheniformis can be found widely in nature and it is exploited in industrial processes for the manufacturing of antibiotics, specialty chemicals, and enzymes. Both in its varied natural habitats and in industrial settings, B. licheniformis cells will be exposed to increases in the external osmolarity, conditions that trigger water efflux, impair turgor, cause the cessation of growth, and negatively affect the productivity of cell factories in biotechnological processes. We have taken here both systems-wide and targeted physiological approaches to unravel the core of the osmostress responses of B. licheniformis. Cells were suddenly subjected to an osmotic upshift of considerable magnitude (with 1 M NaCl), and their transcriptional profile was then recorded in a time-resolved fashion on a genome-wide scale. A bioinformatics cluster analysis was used to group the osmotically up-regulated genes into categories that are functionally associated with the synthesis and import of osmostress-relieving compounds (compatible solutes), the SigB-controlled general stress response, and genes whose functional annotation suggests that salt stress triggers secondary oxidative stress responses in B. licheniformis. The data set focusing on the transcriptional profile of B. licheniformis was enriched by proteomics aimed at identifying those proteins that were accumulated by the cells through increased biosynthesis in response to osmotic stress. Furthermore, these global approaches were augmented by a set of experiments that addressed the synthesis of the compatible solutes proline and glycine betaine and assessed the growth-enhancing effects of various osmoprotectants. Combined, our data provide a blueprint of the cellular adjustment processes of B. licheniformis to both sudden and sustained osmotic stress.
Research collaborations provide opportunities for both practitioners and researchers: practitioners need solutions for difficult business challenges and researchers are looking for hard problems to solve and publish. Nevertheless, research collaborations carry the risk that practitioners focus on quick solutions too much and that researchers tackle theoretical problems, resulting in products which do not fulfill the project requirements.
In this paper we introduce an approach extending the ideas of agile and lean software development. It helps practitioners and researchers keep track of their common research collaboration goal: a scientifically enriched software product which fulfills the needs of the practitioner’s business model.
This approach gives first-class status to application-oriented metrics that measure progress and success of a research collaboration continuously. Those metrics are derived from the collaboration requirements and help to focus on a commonly defined goal.
An appropriate tool set evaluates and visualizes those metrics with minimal effort, and all participants will be pushed to focus on their tasks with appropriate effort. Thus project status, challenges and progress are transparent to all research collaboration members at any time.
This paper presents NLP Lean Programming
framework (NLPf), a new framework
for creating custom natural language processing
(NLP) models and pipelines by utilizing
common software development build systems.
This approach allows developers to train and
integrate domain-specific NLP pipelines into
their applications seamlessly. Additionally,
NLPf provides an annotation tool which improves
the annotation process significantly by
providing a well-designed GUI and sophisticated
way of using input devices. Due to
NLPf’s properties developers and domain experts
are able to build domain-specific NLP
applications more efficiently. NLPf is Opensource
software and available at https://
gitlab.com/schrieveslaach/NLPf.
With the increased interest for interstellar exploration after the discovery of exoplanets and the proposal by Breakthrough Starshot, this paper investigates the optimisation of photon-sail trajectories in Alpha Centauri. The prime objective is to find the optimal steering strategy for a photonic sail to get captured around one of the stars after a minimum-time transfer from Earth. By extending the idea of the Breakthrough Starshot project with a deceleration phase upon arrival, the mission’s scientific yield will be increased. As a secondary objective, transfer trajectories between the stars and orbit-raising manoeuvres to explore the habitable zones of the stars are investigated. All trajectories are optimised for minimum time of flight using the trajectory optimisation software InTrance. Depending on the sail technology, interstellar travel times of 77.6-18,790 years can be achieved, which presents an average improvement of 30% with respect to previous work. Still, significant technological development is required to reach and be captured in the Alpha-Centauri system in less than a century. Therefore, a fly-through mission arguably remains the only option for a first exploratory mission to Alpha Centauri, but the enticing results obtained in this work provide perspective for future long-residence missions to our closest neighbouring star system.
A novel method to determine the extruded length of a metallic wire for a directed energy deposition (DED) process using a microwave (MW) plasma jet with a straight-through wire feed is presented. The method is based on the relative comparison of the measured frequency response obtained by the large-signal scattering parameter (Hot-S) technique. In the practical working range, repeatability of less than 6% for a nonactive plasma and 9% for the active plasma state is found. Measurements are conducted with a focus on a simple solution to decrease the processing time and reduce the integration time of the process into the existing hardware. It is shown that monitoring a single frequency for magnitude and phase changes is sufficient to achieve good accuracy. A combination of different measurement values to determine the length is possible. The applicability to different diameter of the same material is shown as well as a contact detection of the wire and metallic substrate.
This paper describes the development of a capacitively coupled high-pressure lamp with input power between 20 and 43 W at 2.45 GHz, using a coaxial line network. Compared with other electrodeless lamp systems, no cavity has to be used and a reduction in the input power is achieved. Therefore, this lamp is an alternative to the halogen incandescent lamp for domestic lighting. To serve the demands of domestic lighting, the filling of the lamp is optimized over all other resulting requirements, such as high efficacy at low induced powers and fast startups. A workflow to develop RF-driven plasma applications is presented, which makes use of the hot S-parameter technique. Descriptions of the fitting process inside a circuit and FEM simulator are given. Results of the combined ignition and operation network from simulations and measurements are compared. An initial prototype is built and measurements of the lamp's lighting properties are presented along with an investigation of the efficacy optimizations using large signal amplitude modulation. With this lamp, an efficacy of 135 lmW -1 is achieved.
Thermal and Optical Study on the Frequency Dependence of an Atmospheric Microwave Argon Plasma Jet
(2019)
Quantitative evaluation of health management designs for fuel cell systems in transport vehicles
(2022)
Focusing on transport vehicles, mainly with regard to aviation applications, this paper presents compilation and subsequent quantitative evaluation of methods aimed at building an optimum integrated health management solution for fuel cell systems. The methods are divided into two different main types and compiled in a related scheme. Furthermore, different methods are analysed and evaluated based on parameters specific to the aviation context of this study. Finally, the most suitable method for use in fuel cell health management systems is identified and its performance and suitability is quantified.
In addition to electromobility and alternative drive systems, a focus is set on electrically driven compressors (EDC), with a high potential for increasing the efficiency of internal combustion engines (ICE) and fuel cells [01]. The primary objective is to increase the ICE torque, provided independently of the ICE speed by compressing the intake air and consequently the ICE filling level supported by the compressor. For operation independent from the ICE speed, the EDC compressor is decoupled from the turbine by using an electric compressor motor (CM) instead of the turbine. ICE performances can be increased by the use of EDC where individual compressor parameters are adapted to the respective application area [02] [03]. This task contains great challenges, increased by demands with regard to pollutant reduction while maintaining constant performance and reduced fuel consumption. The FH-Aachen is equipped with an EDC test bench which enables EDC-investigations in various configurations and operating modes. Characteristic properties of different compressors can be determined, which build the basis for a comparison methodology. Subject of this project is the development of a comparison methodology for EDC with an associated evaluation method and a defined overall evaluation method. For the application of this comparison methodology, corresponding series of measurements are carried out on the EDC test bench using an appropriate test device.
Quantitative Farbmessung in laryngoskopischen Bildern. Palm, C; Scholl, I; Lehmann, TM; Spitzer, K.
(1998)
MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality
(2019)
In this paper, carbon nanotubes (CNTs) were incorporated in penicillinase-phospholipid Langmuir and Langmuir–Blodgett (LB) films to enhance the enzyme catalytic properties. Adsorption of the penicillinase and CNTs at dimyristoylphosphatidic acid (DMPA) monolayers at the air–water interface was investigated by surface pressure–area isotherms, vibrational spectroscopy, and Brewster angle microscopy. The floating monolayers were transferred to solid supports through the LB technique, forming mixed DMPA-CNTs-PEN films, which were investigated by quartz crystal microbalance, vibrational spectroscopy, and atomic force microscopy. Enzyme activity was studied with UV–vis spectroscopy and the feasibility of the supramolecular device nanostructured as ultrathin films were essayed in a capacitive electrolyte–insulator–semiconductor (EIS) sensor device. The presence of CNTs in the enzyme–lipid LB film not only tuned the catalytic activity of penicillinase but also helped conserve its enzyme activity after weeks, showing increased values of activity. Viability as penicillin sensor was demonstrated with capacitance/voltage and constant capacitance measurements, exhibiting regular and distinctive output signals over all concentrations used in this work. These results may be related not only to the nanostructured system provided by the film, but also to the synergism between the compounds on the active layer, leading to a surface morphology that allowed a fast analyte diffusion because of an adequate molecular accommodation, which also preserved the penicillinase activity. This work therefore demonstrates the feasibility of employing LB films composed of lipids, CNTs, and enzymes as EIS devices for biosensing applications.
Muscle function is compromised by gravitational unloading in space affecting overall musculoskeletal health. Astronauts perform daily exercise programmes to mitigate these effects but knowing which muscles to target would optimise effectiveness. Accurate inflight assessment to inform exercise programmes is critical due to lack of technologies suitable for spaceflight. Changes in mechanical properties indicate muscle health status and can be measured rapidly and non-invasively using novel technology. A hand-held MyotonPRO device enabled monitoring of muscle health for the first time in spaceflight (> 180 days). Greater/maintained stiffness indicated countermeasures were effective. Tissue stiffness was preserved in the majority of muscles (neck, shoulder, back, thigh) but Tibialis Anterior (foot lever muscle) stiffness decreased inflight vs. preflight (p < 0.0001; mean difference 149 N/m) in all 12 crewmembers. The calf muscles showed opposing effects, Gastrocnemius increasing in stiffness Soleus decreasing. Selective stiffness decrements indicate lack of preservation despite daily inflight countermeasures. This calls for more targeted exercises for lower leg muscles with vital roles as ankle joint stabilizers and in gait. Muscle stiffness is a digital biomarker for risk monitoring during future planetary explorations (Moon, Mars), for healthcare management in challenging environments or clinical disorders in people on Earth, to enable effective tailored exercise programmes.
Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.
We analyze the trading behavior of individual investors in option-like securities, namely bankissued warrants, and thus expand the growing literature of investors behavior to a new kind of securities. A unique data set from a large German discount broker gives us the opportunity to analyze the trading behavior of 1,454 investors, making 89,958 transactions in 6,724 warrants on 397 underlyings. In different logit regression, we make use of the facts that investors can speculate on rising and falling prices of the underlying with call and put warrants and that we also have information about the stock portfolios of the investors. We report several facts about the trading behavior of individual investors in warrants that are consistent with the literature on the behavior of individual investors in the stock market. The warrant investors buy calls and sell puts if the price of the underlying has decreased over the past trading days and they sell calls and buy puts if the price of the underlying has increased. That means, the investors follow negative feedback trading strategies in all four trading categories observed. In addition, we find strong evidence for the disposition effect for call as well as put warrants, which is reversed in December. The trading behavior is also influenced if the underlying reaches some exceptionally prices, e.g. highs, lows or the strike price. We show that hedging, as one natural candidate to buy puts, does not play an important role in the market for bank-issued warrants.
Due to the high number of customer contacts, fault clearances, installations, and product provisioning per year, the automation level of operational processes has a significant impact on financial results, quality, and customer experience. Therefore, the telecommunications operator Deutsche Telekom (DT) has defined a digital strategy with the objectives of zero complexity and zero complaint, one touch, agility in service, and disruptive thinking. In this context, Robotic Process Automation (RPA) was identified as an enabling technology to formulate and realize DT’s digital strategy through automation of rule-based, routine, and predictable tasks in combination with structured and stable data.
Pulmonary arterial cannulation is a common and effective method for percutaneous mechanical circulatory support for concurrent right heart and respiratory failure [1]. However, limited data exists to what effect the positioning of the cannula has on the oxygen perfusion throughout the pulmonary artery (PA). This study aims to evaluate, using computational fluid dynamics (CFD), the effect of different cannula positions in the PA with respect to the oxygenation of the different branching vessels in order for an optimal cannula position to be determined. The four chosen different positions (see Fig. 1) of the cannulas are, in the lower part of the main pulmonary artery (MPA), in the MPA at the junction between the right pulmonary artery (RPA) and the left pulmonary artery (LPA), in the RPA at the first branch of the RPA and in the LPA at the first branch of the LPA.
Seismic design of buried pipeline systems for energy and water supply is not only important for plant and operational safety but also for the maintenance of the supply infrastructure after an earthquake. The present paper shows special issues of the seismic wave impacts on buried pipelines, describes calculation methods, proposes approaches and gives calculation examples. This paper regards the effects of transient displacement differences and resulting tensions within the pipeline due to the wave propagation of the earthquake. However, the presented model can also be used to calculate fault rupture induced displacements. Based on a three-dimensional Finite Element Model parameter studies are performed to show the influence of several parameters such as incoming wave angle, wave velocity, backfill height and synthetic displacement time histories. The interaction between the pipeline and the surrounding soil is modeled with non-linear soil springs and the propagating wave is simulated affecting the pipeline punctually, independently in time and space. Special attention is given to long-distance heat pipeline systems. Here, in regular distances expansion bends are arranged to ensure movements of the pipeline due to high temperature. Such expansion bends are usually designed with small bending radii, which during the earthquake lead to high bending stresses in the cross-section of the pipeline. Finally, an interpretation of the results and recommendations are given for the most critical parameters.
The integration of frequently changing, volatile product data from different manufacturers into a single catalog is a significant challenge for small and medium-sized e-commerce companies. They rely on timely integrating product data to present them aggregated in an online shop without knowing format specifications, concept understanding of manufacturers, and data quality. Furthermore, format, concepts, and data quality may change at any time. Consequently, integrating product catalogs into a single standardized catalog is often a laborious manual task. Current strategies to streamline or automate catalog integration use techniques based on machine learning, word vectorization, or semantic similarity. However, most approaches struggle with low-quality or real-world data. We propose Attribute Label Ranking (ALR) as a recommendation engine to simplify the integration process of previously unknown, proprietary tabular format into a standardized catalog for practitioners. We evaluate ALR by focusing on the impact of different neural network architectures, language features, and semantic similarity. Additionally, we consider metrics for industrial application and present the impact of ALR in production and its limitations.
Often, research results from collaboration projects are not transferred into productive environments even though approaches are proven to work in demonstration prototypes. These demonstration prototypes are usually too fragile and error-prone to be transferred
easily into productive environments. A lot of additional work is required.
Inspired by the idea of an incremental delivery process, we introduce an architecture pattern, which combines the approach of Metrics Driven Research Collaboration with microservices for the ease of integration. It enables keeping track of project goals over the course of the collaboration while every party may focus on their expert skills: researchers may focus on complex algorithms,
practitioners may focus on their business goals.
Through the simplified integration (intermediate) research results can be introduced into a productive environment which enables
getting an early user feedback and allows for the early evaluation of different approaches. The practitioners’ business model benefits throughout the full project duration.
This paper presents the laser-based powder bed fusion (L-PBF) using various glass powders (borosilicate and quartz glass). Compared to metals, these require adapted process strategies. First, the glass powders were characterized with regard to their material properties and their processability in the powder bed. This was followed by investigations of the melting behavior of the glass powders with different laser wavelengths (10.6 µm, 1070 nm). In particular, the experimental setup of a CO2 laser was adapted for the processing of glass powder. An experimental setup with integrated coaxial temperature measurement/control and an inductively heatable build platform was created. This allowed the L-PBF process to be carried out at the transformation temperature of the glasses. Furthermore, the component’s material quality was analyzed on three-dimensional test specimen with regard to porosity, roughness, density and geometrical accuracy in order to evaluate the developed L-PBF parameters and to open up possible applications.
Compared to peripheral pain, trigeminal pain elicits higher levels of fear, which is assumed to enhance the interruptive effects of pain on concomitant cognitive processes. In this fMRI study we examined the behavioral and neural effects of trigeminal (forehead) and peripheral (hand) pain on visual processing and memory encoding. Cerebral activity was measured in 23 healthy subjects performing a visual categorization task that was immediately followed by a surprise recognition task. During the categorization task subjects received concomitant noxious electrical stimulation on the forehead or hand. Our data show that fear ratings were significantly higher for trigeminal pain. Categorization and recognition performance did not differ between pictures that were presented with trigeminal and peripheral pain. However, object categorization in the presence of trigeminal pain was associated with stronger activity in task-relevant visual areas (lateral occipital complex, LOC), memory encoding areas (hippocampus and parahippocampus) and areas implicated in emotional processing (amygdala) compared to peripheral pain. Further, individual differences in neural activation between the trigeminal and the peripheral condition were positively related to differences in fear ratings between both conditions. Functional connectivity between amygdala and LOC was increased during trigeminal compared to peripheral painful stimulation. Fear-driven compensatory resource activation seems to be enhanced for trigeminal stimuli, presumably due to their exceptional biological relevance.
The SG1-mediated solution polymerization of methyl methacrylate (MMA) and oligo(ethylene glycol) methacrylate (OEGMA, Mₙ = 300 g mol⁻¹) in the presence of a small amount of functional/reactive styrenic comonomer is investigated. Moieties such as pentafluorophenyl ester, triphenylphosphine, azide, pentafluorophenyl, halide, and pyridine are considered. A comonomer fraction as low as 5 mol% typically results in a controlled/living behavior, at least up to 50% conversion. Chain extensions with styrene for both systems were successfully performed. Variation of physical properties such as refractive index (for MMA) and phase transition temperature (for OEGMA) were evaluated by comparing to 100% pure homopolymers. The introduction of an activated ester styrene derivative in the polymerization of OEGMA allows for the synthesis of reactive and hydrophilic polymer brushes with defined thickness. Finally, using the example of pentafluorostyrene as controlling comonomer, it is demonstrated that functional PMMA-b-PS are able to maintain a phase separation ability, as evidenced by the formation of nanostructured thin films.
Detection and identification of free radicals in hydrocarbon pyrolysis by an iodine trapping method
(1992)
Risk factors for cardiovascular calcifications in non-diabetic Caucasian haemodialysis patients
(2009)
The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance
(2016)
Short term effects of magnetic resonance imaging on excitability of the motor cortex at 1.5T and 7T
(2010)
Rationale and Objectives
The increasing spread of high-field and ultra-high-field magnetic resonance imaging (MRI) scanners has encouraged new discussion of the safety aspects of MRI. Few studies have been published on possible cognitive effects of MRI examinations. The aim of this study was to examine whether changes are measurable after MRI examinations at 1.5 and 7 T by means of transcranial magnetic stimulation (TMS).
Materials and Methods
TMS was performed in 12 healthy, right-handed male volunteers. First the individual motor threshold was specified, and then the cortical silent period (SP) was measured. Subsequently, the volunteers were exposed to the 1.5-T MRI scanner for 63 minutes using standard sequences. The MRI examination was immediately followed by another TMS session. Fifteen minutes later, TMS was repeated. Four weeks later, the complete setting was repeated using a 7-T scanner. Control conditions included lying in the 1.5-T scanner for 63 minutes without scanning and lying in a separate room for 63 minutes. TMS was performed in the same way in each case. For statistical analysis, Wilcoxon's rank test was performed.
Results
Immediately after MRI exposure, the SP was highly significantly prolonged in all 12 subjects at 1.5 and 7 T. The motor threshold was significantly increased. Fifteen minutes after the examination, the measured value tended toward normal again. Control conditions revealed no significant differences.
Conclusion
MRI examinations lead to a transient and highly significant alteration in cortical excitability. This effect does not seem to depend on the strength of the static magnetic field.
Purpose
To assess potential cognitive deficits under the influence of static magnetic fields at various field strengths some studies already exist. These studies were not focused on attention as the most vulnerable cognitive function. Additionally, mostly no magnetic resonance imaging (MRI) sequences were performed.
Materials and Methods
In all, 25 right-handed men were enrolled in this study. All subjects underwent one MRI examination of 63 minutes at 1.5 T and one at 7 T within an interval of 10 to 30 days. The order of the examinations was randomized. Subjects were referred to six standardized neuropsychological tests strictly focused on attention immediately before and after each MRI examination. Differences in neuropsychological variables between the timepoints before and after each MRI examination were assessed and P-values were calculated
Results
Only six subtests revealed significant differences between pre- and post-MRI. In these tests the subjects achieved better results in post-MRI testing than in pre-MRI testing (P = 0.013–0.032). The other tests revealed no significant results.
Conclusion
The improvement in post-MRI testing is only explicable as a result of learning effects. MRI examinations, even in ultrahigh-field scanners, do not seem to have any persisting influence on the attention networks of human cognition immediately after exposure.
Euler-based induced drag estimation for highly non-planar lifting systems during conceptional design
(2013)
The impact of wake model effects is investigated for two highly
non-planar lifting systems. Dependent on the geometrical
arrangement of the configuration, the wake model shape is found
to considerably affect the estimation. Particularly at higher angles
of attack, an accurate estimation based on the common linear wake
model approaches is involved.