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Artificial intelligence and design of experiments for resource adequacy assessment in power systems
(2024)
A numerical study is carried out meticulously to scrutinize the impact of different shapes of chimneys like circular (outer dia, dc), convergent (outer dia, 0.5dc), divergent (outer dia, 1.5dc), sudden contraction (outer dia, 0.5dc), and sudden expansion (outer dia, 1.5dc) on the performance of an SCPP. Furthermore, the parametric impact with different chimney divergence angles (CDA, ϕ), and ground absorber slope angle (GSA, γ) on the SCPP performance is also scrutinized. Optimum divergence angle (ϕ=+0.75◦) enhances the power generation up to ~ 47% (76 kW) with a horizontal ground absorber surface. An increase or decrease in CDA lessens the power generation. With a sloped ground absorber angle γ=0.6◦, the gain in power generation is 60% (82 kW). The study of combination of ground sloped absorber (γ=0.6◦) and divergent chimney (ϕ=+0.75◦) shows enhancement of the power generation upto 80% (92 kW) more than the classical Manzaranes plant.
Over the past decades, research in room acoustics has established several derivative measures of an impulse response, some of which are incorporated in the ISO 3382 standards. These parameters intend to represent perceptual qualities, but were developed without a consistent modeling of room acoustical perception. More recent research proposed comprehensive inventories of room acoustic perception that are purely based on evaluations by human subjects, such as the Room Acoustical Quality Index (RAQI). In this work RA-QI scores acquired for 70 room impulse responses were predicted from room acoustical parameters. Except for Reverberance, the prediction of RAQI factors performed rather poor. In most cases, the sound source had a greater impact on RAQI scores. All analyses are published in an online tool, where users can upload omnidirectional and binaural impulse responses, and instantly obtain and visualize several physical descriptors, as well as predicted RAQI scores for three different sound sources. So far, acceptable prediction accuracy is achieved for Reverberance, Strength, Irregular Decay, Clarity and Intimacy. Larger data sets of evaluated impulse responses are required to improve the model performance and enable reliable predictions of room acoustical quality. Therefore, the administration of RAQI evaluations within the website is currently being developed.
Spatial precision and recall indices to assess the performance of instance segmentation algorithms
(2022)
Music consumption and distribution has changed drastically in the last twenty years due to digitalization. Instead of buying music products, like CDs or even downloaded digital music files, today music is predominantly distributed via online music streaming. Therefore, it is mandatory for the music industry as well as researchers to determine which factors are affecting consumers intention to use music streaming services. This study aims to investigate drivers of Behavioral Intention (BI) to use a music streaming service. Particularly, aspects of social preferences in the context of music streaming will be explored. Therefore, a research model is created, based on the Value-based Adoption Model (VAM) (Kim et al., 2007) with an extension to take social factors into account. An online questionnaire with 102 participants was conducted to test the research model and the corresponding hypotheses. In order to evaluate reliable indications, some adjustments needed to be made resulting in a corrected research model. The final independent variables of the corrected model are Perceived Value (PV) (which is composed of Perceived Usefulness (PU) and Perceived Enjoyment (PE)), Perceived Ease of Use (PEU), Perceived Price Value (PPV), Facilitating Conditions (FC), Perceived Fairness (PF), Social Connectivity (SC), and Peer-Effects (PFX). The empirical results show that Perceived Value (PV), Perceived Price Value (PPV), and Perceived Fairness (PF) are determinants of consumers Behavioral Intention (BI) to use a music streaming service.
The decarbonization of for example the energy or heat sector leads to the transformation of distribution grids. The expansion of decentralized energy resources and the integration of new consumers due to sector coupling (e.g. heat pumps or electric vehicles) into low voltage grids increases the need for grid expansion and usage of flexibilities in the grid. A high observability of the current grid status is needed to perform these tasks efficiently and effectively. Therefore, there is a need to increase the observability of low voltage grids by installing measurement technologies (e.g. smart meters). Multiple different measurement technologies are available for low voltage grids which can vary in their benefit to observation quality and their installation costs. Therefore, Bayernwerk Netz GmbH and E.DIS AG in cooperation with E-Bridge Consulting GmbH and the Institute for High Voltage Equipment and Grids, Digitalization and Energy Economics (IAEW) investigated the effectiveness of different strategies for the smartification of low voltage grids. This paper presents the methodology used for the investigation and exemplary results focusing on the impact of intelligent cable distribution cabinets and smart meters on the quality of the state estimation.
In the context of using renewable energies and recycling climate-changing gases, methanation of CO2 provides one possibility. However, volatile availability of renewable energies for hydrogen production and fluctuating CO2streams from different sources lead to enhanced demand in investigating the influence of dynamic process operation on the catalyst performance, including detailed kinetic characterization. Reliable kinetic measurements require isothermal temperature control and absence of macrokinetic diffusion limitations. Both were investigated in this work while the determination of steady-state kinetic parameters is part of ongoing studies. Furthermore, a detailed analysis with respect to the long-term-stability of the nickel-based catalyst was performed
In the EILD.nrw project, Open Educational Resources (OER) are being developed for teaching databases. Instructors can use the tools and courses in a variety of learning scenarios. Students of computer science and application subjects learn the complete life cycle of databases. For this purpose, quizzes, interactive tools, instructional videos, and courses for learning management systems are developed and published under a Creative Commons license.
Applicability of Aeroacoustic Scaling Laws of Leading Edge Serrations for Rotating Applications
(2020)
Poor young people more often face health difficulties, (learning) disabilities, and are overrepresented in special schools. Consequently, youth from poor households disproportionately frequently participate in disability‐specific programs aiming to improve their educational levels and labor market opportunities. They face a double burden of disability and poverty. In our study, we look at poor and non‐poor youth with disabilities (YPWD) who participate in vocational rehabilitation (VR) and whether VR helps them (a) in transitioning into employment and (b) in leaving poverty. We examine the association between the receipt of initial basic income support (BIS) as a poverty indicator, later labor market outcomes, and earned vocational qualification using administrative data. We make use of a sample of all persons accepted for VR in 2010 (N = 36,645). We employ logit models on VR attendees’ labor market outcomes three and five years after being accepted for VR as well as on their earned vocational qualifications. Beside initial poverty status, we control for educational level, type, and degree of disability and program pattern during the VR process. Our findings show that YPWD from poor households have a decreased likelihood of a vocational certificate and employment. Additionally, they are more likely to receive BIS than young people not from poor households and thus more likely to remain poor. In conclusion, VR seems to support poor YPWD less in their school‐to‐work transitions. Thus, disability‐specific programs should be more tailored to the social situations of participants, and counsellors should be more sensitive to their social backgrounds.
The Long Tail theory serves as an explanation for market change triggered through evolving online market conditions. However, it is often referred to without empirical validation, or with inconsistent findings on its applicability. Therefore, this paper analyses the applicability of the Long Tail theory to German online media offerings as of 2014 and 2016, focusing on offerings that serve information purposes (information offerings). Based on a unique dataset of commercially oriented online media offerings (Longitudinal IntermediaPlus 2014–2016), an analysis for three Long Tail characteristics (variety increase, opposing concentration between hit and niche offerings and niche market share increase) is conducted. By additionally distinguishing between political and entertainment-oriented information offerings as boundaries of democratized online market conditions the analysis reveals that the Long Tail theory is not fully applicable to any market sample, and especially not to politically oriented offerings.
Magneto-hydrothermal triple-convection in a W-shaped porous cavity containing oxytactic bacteria
(2022)
Bioconvective heat and mass transport phenomena have recently been the subject of interest in diverse fields of applications pertaining to the motion of fluids and their thermophysical properties. The transport processes in a system involving triple convective phenomena, irregular geometry, and boundary conditions constitute a complex phenomenon. This work aims to explore the mixed thermo-bioconvection of magnetically susceptible fluid containing copper nanoparticles and oxytactic bacteria in a novel W-shaped porous cavity. The buoyant convention is generated due to the isothermal heating at the wavy bottom wall, whereas the mixed convection is induced due to the shearing motion of the top-cooled sliding wall. Furthermore, the bioconvection is induced due to the manifestation of oxytactic bacteria or organisms. The inclined sidewalls are insulated. The geometry is packed with water based Cu nanoparticle mixed porous structure, which is subjected to a magnetizing field acted horizontally. The complex transport equations are transformed into nondimensional forms, which are then computed using the finite volume-based developed code. The coupled triple-convective flow physics are explored for a wide range of involved controlling parameters, which could provide helpful insight to the system designer for its proper operation. The shape of geometry can be considered one of the important parameters to control the heat and mass transport phenomena. In general, the influence of amplitude (δ) is more compared to the waviness number (m) of the undulations. The magnitude of heat (Nu) and mass (Sh) transfer rate for the W-shaped cavity is high compared to conventional square and trapezoidal-shaped cavities. The output of the analysis could be very helpful for the designer for modeling devices operating on nanotechnology-based bioconvection, microbial fuel cells, and others.
In order to determine demand as precisely as possible, many businesses use several forecasting methods. The aim of forecasting is to determine future demand based on data from the past. The use of a specific method is not always easy and depends on a number of factors. To help prospective engineers find the most suitable forecasting method for a specific problem, a forecasting game was developed and then evaluated.
The paper describes the design and the evaluation of the forecasting game. In order to provide an overview of existing forecasting methods, the first part of the paper examined the mathematical fundamentals of eight different forecasting methods and outlined the requirements for their application.
The second part of the paper describes the creation of a forecasting game in which prospective engineers can learn how to determine the appropriate forecasting method for specific scenarios. In total, five scenarios covering the three different demand patterns (linear/stationary, trend and seasonal) as well as the forecast quality methods were developed and can be played through. For each scenario, the player has to choose the most appropriate forecasting method for a specific problem based on a self-created task description. To make the game as realistic as possible, a fictional company with a background story was designed.
The last part was about the evaluation of the forecasting game. For the evaluation, a student survey to gather the opinions of the students was conducted. The results of the student survey show an overall positive evaluation of the simulation game by the students. However, the test also showed that the game takes a certain amount of time. Since only 15 of the approximately 30 students who tested the game participated in the evaluation, the results are not significant.
Building context-aware applications is an already widely researched topic. It is our belief that context awareness has the potential to supplement the Internet of Things, when a suitable methodology including supporting tools will ease the development of context-aware applications. We believe that a meta-model based approach can be key to achieving this goal. In this paper, we present our meta-model based methodology, which allows us to define and build application-specific context models and the integration of sensor data without any programming. We describe how that methodology is applied with the implementation of a relatively simple context-aware COVID-safe navigation app. The outcome showed that programmers with no experience in context-awareness were able to understand the concepts easily and were able to effectively use it after receiving a short training. Therefore, context-awareness is able to be implemented within a short amount of time. We conclude that this can also be the case for the development of other context-aware applications, which have the same context-awareness characteristics. We have also identified further optimization potential, which we will discuss at the conclusion of this article.
Music-related decision-making encompasses a wide range of behaviours including those associated with listening choices, composition and performance, and decisions involving music education and therapy. Although research programmes in psychology and economics have contributed to an improved understanding of music-related behaviour, historically, these disciplines have been unconnected. Recently, however, researchers have begun to bridge this gap by employing tools from behavioural economics. This article contributes to the literature by providing a discussion about the benefits of using behavioural economics in music-decision research. We achieve this in two ways. First, through a systematic review, we identify the current state of the literature within four key areas of behavioural economics-heuristics and biases, social decision-making, behavioural time preferences, and dual-process theory. Second, taking findings of the literature as a starting point, we demonstrate how behavioural economics can inform future research. Based on this, we propose the Behavioural Economics of Music (BEM), an integrated research programme that aims to break new ground by stimulating interdisciplinary research in the intersection between music, psychology, and economics.
Room reverberation alters the spatial impression and timbre of a sound by modulating its spectral and temporal characteristics. Thus, we argue that, on a perceptual level, reverberation basically breaks down into interaural differences and spectro-temporal cues and that the separation of a perceived timbre into a sound source and a surrounding room is a purely cognitive process. To investigate the connection between the perception of reverberation cues and timbre analysis, the sensitivity for changes in reverberation was compared to timbre perception abilities. The Timbre Perception Test was used to measure the perception of the temporal envelope, spectral centroid, and spectral flux of artificial sounds. Sensitivity for changes in reverberation time was tested with a discrimination task using speech and noise with speech-alike spectral and temporal envelopes as source signals. Musical and acoustical expertise was assessed through the Goldsmiths Musical Sophistication Index and self-reports on experience with and knowledge of acoustics. There was a considerable correlation between timbre and reverberance perception ability, but timbre perception and academic experience predicted only 41% of the variance in reverberance perception. Still, perception abilities related to similar acoustical phenomena seem to be better indicators of listening skills than self-reports on acoustical or musical expertise.
A swirling pulverized coal flame is computationally investigated. A Eulerian–Lagrangian formulation is used to describe the two-phase flow. Turbulence is modelled within a RANS (Reynolds averaged numerical simulation) framework. Four turbulence viscosity- (TV) based models, namely the standard k-ε model, realizable k-ε model, renormalization group theory k-ε model, and the shear stress transport k-ω model are used. In addition, a Reynolds stress transport model (RSM) is employed. The models are assessed by comparing the predicted velocity fields with the measurements of other authors. In terms of overall average values, the agreement of the predictions to the measurements is observed to be within the range 20–40%. A better performance of the RSM compared to the TV models is observed, with a nearly twice as better overall agreement to the experiments, particularly for the swirl velocity. In the second part of the investigation, the resolution of the discrete particle phase in modelling the turbulent particle dispersion (TPD) and particle size distribution (SD) is investigated. Using the discrete random walk model for the TPD, it is shown that even five random walks are sufficient for an accuracy that is quite high, with a less than 1% mean deviation from the solution obtained by thirty random walks. The approximation of the measured SD is determined by a continuous Rosin–Rammler distribution function, and inaccuracies that can occur in its subsequent discretization are demonstrated and discussed. An investigation on the resolution of the SD by discrete particle size classes (SC) indicates that 12 SC are required for an accuracy with a less than 1% mean deviation from the solution with 18 SC. Although these numbers may not necessarily be claimed to be sufficiently universal, they may serve as guidance, at least for SD with similar characteristics
Thermoelectric generators (TEGs) have the ability to convert waste heat into electrical energy under unfavorable conditions and are becoming increasingly popular in academia, but have not yet achieved a broad commercial success, due to the still comparably low efficiency. To increase the efficiency and economic viability of TEGs, research is performed on the materials on one hand and on the system connection on the other. In the latter case, the net output power of the cooling system plays a key role. At first glance, passive cooling seems preferable to active cooling because it does not affect the net electrical output power. However, as shown in the present review, the active cooling is to be preferred for net output power. The situation is similar in air and water-cooling. Even though air-cooling is easier to set up, the water-cooling should be preferred to achieve higher net output power. It is shown that microchannel cooling has similar hydraulic performance to conventional cooling and inserts increase the net output power of TEG. As the review reveals that active water-cooling should be the method of choice to achieve high net output power, it also shows that a careful optimization is necessary to exploit the potential.
The settling velocities of helminth eggs of three types, namely Ascaris suum (ASC), Trichuris suis (TRI), and Oesophagostomum spp. (OES), in clean tap water are computationally determined by means of computational fluid dynamics, using the general-purpose CFD software ANSYS Fluent 18.0. The previous measurements of other authors are taken as the basis for the problem formulation and validation, whereby the latter is performed by comparing the predicted sink velocities with those measured in an Owen tube. To enable a computational treatment, the measured shapes of the eggs are parametrized by idealizing them in terms of elementary geometric forms. As the egg shapes show a variation within each class, “mean” shapes are considered. The sink velocities are obtained through the computationally obtained drag coefficients. The latter are defined by means of steady-state calculations. Predicted sink velocities are compared with the measured ones. It is observed that the calculated values show a better agreement with the measurements, for ASC and TRI, compared to the theoretical sink values delivered by the Stokes theory. However, the observed agreement is still found not to be very satisfactory, indicating the role of further parameters, such as the uncertainties in the characterization of egg shapes or flocculation effects even in clean tap water.
The links between innovativeness as a driver of economic performance, and the determinants of innovativeness have been investigated by management scholars and economists for decades, focusing mostly on “hard factors” as investment in research and development, or education. Focusing on a relatively neglected, but in times of globalization even more important aspect, the infuence of cultural characteristics on innovativeness, we apply diferent econometric models to test for links between cultural tightness and looseness on the one hand, and national innovativeness on the other hand. We fnd that cultural tightness—in the sense of homogenous and intolerant societies—has a negative link to national innovativeness, while cultural looseness—in the sense of tolerant and diverse societies—displays a positive link to national innovativeness.
We present a novel metric Spatial Recall Index to assess the performance of machine-learning (ML) algorithms for automotive applications, focusing on where in the image which performance occurs. Typical metrics like intersection-over-union (IoU), precisionrecallcurves or average precision (AP) quantify the performance over a whole database of images, neglecting spatial performance variations. But as the optics of camera systems are spatially variable over the field of view, the performance of ML-based algorithms is also a function of space, which we show in simulation: A realistic objective lens based on a Cooke-triplet that exhibits typical optical aberrations like astigmatism and chromatic aberration, all variable over field, is modeled. The model is then applied to a subset of the BDD100k dataset with spatially-varying kernels. We then quantify local changes in the performance of the pre-trained Mask R-CNN algorithm. Our examples demonstrate the spatial dependence of the performance of ML-based algorithms from the optical quality over field, highlighting the need to take the spatial dimension into account when training ML-based algorithms, especially when looking forward to autonomous driving applications.
Cell migration is associated with the dynamic protrusion of a thin actin-based cytoskeletal extension at the cell front, which has been shown to consist of two different substructures, the leading lamellipodium and the subsequent lamellum. While the formation of the lamellipodium is increasingly well understood, organizational principles underlying the emergence of the lamellum are just beginning to be unraveled. We report here on a 1D mathematical model which describes the reaction-diffusion processes of a polarized actin network in steady state, and reproduces essential characteristics of the lamellipodium-lamellum system. We observe a steep gradient in filament lengths at the protruding edge, a local depolymerization maximum a few microns behind the edge, as well as a differential dominance of the network destabilizer ADF/cofilin and the stabilizer tropomyosin. We identify simple and robust organizational principles giving rise to the derived network characteristics, uncoupled from the specifics of any molecular implementation, and thus plausibly valid across cell types. An analysis of network length dependence on physico-chemical system parameters implies that to limit array treadmilling to cellular dimensions, network growth has to be truncated by mechanisms other than aging-induced depolymerization, e.g., by myosin-associated network dissociation at the transition to the cell body. Our work contributes to the analytical understanding of the cytoskeletal extension's bisection into lamellipodium and lamellum and sheds light on how cells organize their molecular machinery to achieve motility.
To power dynamic processes in cells, the actin and microtubule cytoskeletons organize into complex structures. Although it is known that cytoskeletal coordination is vital for cell function, the mechanisms by which cross-linking proteins coordinate actin and microtubule activities remain poorly understood. In particular, it is unknown how the distinct mechanical properties of different actin architectures modulate the outcome of actin-microtubule interactions. To address this question, we engineered the protein TipAct, which links growing microtubule ends via end-binding proteins to actin filaments. We show that growing microtubules can be captured and guided by stiff actin bundles, leading to global actin-microtubule alignment. Conversely, growing microtubule ends can transport, stretch and bundle individual actin filaments, thereby globally defining actin filament organization. Our results provide a physical basis to understand actin-microtubule cross-talk, and reveal that a simple cross-linker can enable a mechanical feedback between actin and microtubule organization that is relevant to diverse biological contexts.
Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, we propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of > 100,000 mass spectra of about 15,000 unique known compounds, we trained MS2DeepScore to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model's prediction uncertainty. On 3600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and to predict Tanimoto scores for pairs of molecules based on their fragment spectra with a root mean squared error of about 0.15. Furthermore, the prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. Furthermore, we demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, we believe that machine learning-supported mass spectral similarity measures have great potential for a range of metabolomics data processing pipelines.
Despite their overwhelming complexity, living cells display a high degree of internal mechanical and functional organization which can largely be attributed to the intracellular biopolymer scaffold, the cytoskeleton. Being a very complex system far from thermodynamic equilibrium, the cytoskeleton's ability to organize is at the same time challenging and fascinating. The extensive amounts of frequently interacting cellular building blocks and their inherent multifunctionality permits highly adaptive behavior and obstructs a purely reductionist approach. Nevertheless (and despite the field's relative novelty), the physics approach has already proved to be extremely successful in revealing very fundamental concepts of cytoskeleton organization and behavior. This review aims at introducing the physics of the cytoskeleton ranging from single biopolymer filaments to multicellular organisms. Throughout this wide range of phenomena, the focus is set on the intertwined nature of the different physical scales (levels of complexity) that give rise to numerous emergent properties by means of self-organization or self-assembly.
Spec2Vec: Improved mass spectral similarity scoring through learning of structural relationships
(2021)
Spectral similarity is used as a proxy for structural similarity in many tandem mass spectrometry (MS/MS) based metabolomics analyses such as library matching and molecular networking. Although weaknesses in the relationship between spectral similarity scores and the true structural similarities have been described, little development of alternative scores has been undertaken. Here, we introduce Spec2Vec, a novel spectral similarity score inspired by a natural language processing algorithm-Word2Vec. Spec2Vec learns fragmental relationships within a large set of spectral data to derive abstract spectral embeddings that can be used to assess spectral similarities. Using data derived from GNPS MS/MS libraries including spectra for nearly 13,000 unique molecules, we show how Spec2Vec scores correlate better with structural similarity than cosine-based scores. We demonstrate the advantages of Spec2Vec in library matching and molecular networking. Spec2Vec is computationally more scalable allowing structural analogue searches in large databases within seconds.
Actin droplet machine
(2019)
The actin droplet machine is a computer model of a three-dimensional network of actin bundles developed in a droplet of a physiological solution, which implements mappings of sets of binary strings. The actin bundle network is conductive to travelling excitations, i.e. impulses. The machine is interfaced with an arbitrary selected set of k electrodes through which stimuli, binary strings of length k represented by impulses generated on the electrodes, are applied and responses are recorded. The responses are recorded in a form of impulses and then converted to binary strings. The machine's state is a binary string of length k: if there is an impulse recorded on the ith electrode, there is a '1' in the ith position of the string, and '0' otherwise. We present a design of the machine and analyse its state transition graphs. We envisage that actin droplet machines could form an elementary processor of future massive parallel computers made from biopolymers.
Actin filaments are conductive to ionic currents, mechanical and voltage solitons. These travelling localisations can be utilised to generate computing circuits from actin networks. The propagation of localisations on a single actin filament is experimentally unfeasible to control. Therefore, we consider excitation waves propagating on bundles of actin filaments. In computational experiments with a two-dimensional slice of an actin bundle network we show that by using an arbitrary arrangement of electrodes, it is possible to implement two-inputs-one-output circuits.
Methanol Synthesis with Steel Mill Gases: Performance Investigations in an On‐Site Technical Center
(2021)
This paper investigates the implementation of a human body model for the simulation of a jumping motion in Simulink. It contains details to get an insight into modern biomechanics without previous experience. In the simulation, a Hill-Type muscle is used to generate joint momentum with a phenomenologically realistic relationship between muscle length and force. The simulation published with this article is one of many solutions to design a humanoid simulation. The paper guides through the implemented build and explains its range of application.
Today, the use of renewable energies and recycling of climate-changing gases are increasingly important. In this context,coupling of methanation with small, decentralized CO2sources such as biogas plants provides one possibility. However,fluctuating availability of renewables for hydrogen production in combination with small storage volumes result in anenhanced demand for dynamic process operation. This leads to new research challenges with respect to the required cata-lysts and the overall process design. To draw reliable conclusions about the catalytic performance under dynamic processoperation, the mechanism of the methanation reaction as well as typical deactivation procedures of the catalyst appliedunder steady-state conditions have to be reviewed thoroughly.
Sound and music are well-studied aspects of the quality of experience in restaurants; the role of the room acoustical conditions, their influence on the visitors’ soundscape evaluation and their impact on the overall customer satisfaction in restaurants, however, has received less scientific attention. The present field study therefore investigated whether sound pressure level, reverberation time, and soundscape pleasantness can predict factors associated with overall restaurant quality. In total, 142 persons visiting 12 restaurants in Berlin rated relevant acoustical and non-acoustical factors associated with restaurant quality. Simultaneously, the A-weighted sound pressure level (LA,eq,15) was measured, and the reverberation time in the occupied state (T20,occ) was obtained by measurements performed in the unoccupied room and a subsequent calculation of the occupied condition according to DIN 18041. Results from linear mixed-effects models revealed that both the LA,eq,15 and T20,occ had a significant influence on soundscape pleasantness and eventfulness, whereby the effect of T20,occ was meditated by the LA,eq,15. Also, the LA,eq,15 as well as soundscape pleasantness were significant predictors of overall restaurant quality. A comprehensive structural equation model including both acoustical and non-acoustical factors, however, indicates that the effect of soundscape pleasantness on overall restaurant quality is mediated by the restaurant’s atmosphere. Our results support and extend previous findings which suggest that the acoustical design of restaurants involves a trade-off between comfort and liveliness, depending on the desired character of the place.
Impact of Renewable Energy Expansion to the Balancing Energy Demand of Differential Balancing Groups
(2018)
The research addresses the present situation on the German electricity market caused by variable renewable energy sources. The increasing number of households with photovoltaic and battery storage systems and their impacts require special attention. These systems change the traditional electricity customer from the sole electricity consumer to an electricity producer and consumer in one person. These so-called prosumers differ in their actual electricity demand from the initially estimated electricity demand with standard load profile. This discrepancy results in deviations within a differential balancing group. Thereby, the main finding of this research is a significant higher balancing energy demand with the expansion of photovoltaic and battery storage systems. Hence, the standard load profile is particularly not suitable for differential balancing groups with a high penetration of solar systems and still less suitable for groups with solar and battery storage systems
Computational investigation of hemodynamics in hardshell venous reservoirs: A comparative study
(2019)
Extracorporeal circulation using heart‐lung‐machines is associated with a profound activation of corpuscular and plasmatic components of circulating blood, which can also lead to deleterious events such as systemic inflammatory response and hemolysis. Individual components used to install the extracorporeal circulation have an impact on the level of activation, most predominantly membrane oxygenators and hardshell venous reservoirs as used in extracorporeal systems. The blood flows in two different hardshell reservoirs are computationally investigated. A special emphasis is placed on the prediction of an onset of transition and turbulence generation. Reynolds‐averaged numerical simulations (RANS) based on a transitional turbulence model, as well as large eddy simulations (LES) are applied to achieve an accurate prediction. In the LES analysis, the non‐Newtonian behavior of the blood is considered via the Carreau model. Blood damage potential is quantified applying the Modified Index of Hemolysis (MIH) based on the predicted flow fields. The results indicate that the flows in both reservoirs remain predominantly laminar. For one of the reservoirs, considerable turbulence generation is observed near the exit site, caused by the specific design for the connection with the drainage tube. This difference causes the MIH of this reservoir to be nearly twice as large as compared to the alternative design. However, a substantial improvement of these performance criteria can be expected by a local geometry modification.
Heterogeneous catalysts usually consist of porous, inorganic materials. Especially in the mobile application, e.g., in exhaust gas catalysis as a part of the gas line of an engine, there are loads due to vibrations and high gas velocities. It can be assumed that physical stress will lead to a loss of the catalytically active coating. The present contribution describes experimental setups and methods for a systematic and reproducible investigation of the main influences to the mass loss due to vibrational and fluid‐mechanical stress caused by particle‐free gas flows.
Synthesis and Analysis of a Novel Linkage Mechanism with the Helical Motion of the End-Effector
(2020)
Through constant technical progress, multi-user virtual reality is transforming towards a social activity that is no longer only used by remote users, but also in large-scale location-based experiences. We evaluate the usage of realtime-tracked avatars in co-located business-oriented applications in a "guide-user-scenario" in comparison to audio only instructions. The present study examined the effect of an avatar-guide on the user-related factors of Spatial Presence, Social Presence, User Experience and Task Load in order to propose design guidelines for co-located collaborative immersive virtual environments. Therefore, an application was developed and a user study with 40 participants was conducted in order to compare both guiding techniques of a realtime-tracked avatar guide and a non-visualised guide with otherwise constant conditions. Results reveal that the avatar-guide enhanced and stimulated communicative processes while facilitating interaction possibilities and creating a higher sense of mental immersion for users. Furthermore, the avatar-guide appeared to make the storyline more engaging and exciting while helping users adapt to the medium of virtual reality. Even though no assertion could be made concerning the Task Load factor, the avatar-guide achieved a higher subjective value on User Experience. Due to the results, avatars can be considered valuable social elements in the design of future co-located collaborative virtual environments.
The impact of culture on entrepreneurship is a widely accepted phenomenon. Cultural factors influence entrepreneurship via different mechanisms on the macro-, meso-, and micro-level of a country. Building on existing research, we draw a clear link between national cultural dimensions and entrepreneurship, using a new model that arranges different cultural dimensions in groups based on their particular function: political, social, or individual (PSI-model) and that distinguishes between values and practices where relevant. The PSI-model provides a coherent theoretical framework on which different cultural dimensions and their impact on entrepreneurship can be analysed, allowing for particular attention to be drawn to social practices and social values. This paper contributes to a better understanding of the relationship between culture and entrepreneurship, providing empirical evidence of how specific cultural dimensions influence entrepreneurship. The findings are of relevance from a policy perspective and can be used to generate practical recommendations for national institutions interested in promoting entrepreneurship and entrepreneurial activities. The findings are also transferable to other fields related to national cultural dimensions such as level of innovation, investment, budgeting etc.
The population is growing constantly in urban areas. This results in an increasing demand for mobility solutions while it is also worldwide aimed to reduce greenhouse gas emissions. This paper summarizes the results of a comparative study concerning the greenhouse gas emissions (based on carbon footprint) caused by alternative urban passenger transportation systems. The emissions for the vehicles and their infrastructure are analyszed over the entire life cycle from manufacturing up to their end of life. An existing cable car sytem in La Paz, Bolivia was analysed and evaluated in comparison to other modes of transportation such as small busses, large busses and a tram. According to the system definitions and the considered balance framework the study shows that beside the use of the systems the materials and the manufacturing as well as the infrastructure have a significant impact on the total emissions over the life cycle. To put focus on the „true and real“ impacts to the society it is preferable to consider the measurement results in total absolute emissions.
This essay looks at the potentials and limitations of user research for studies on the practice of drama education. To date, this field has been dominated by impact studies. After illustrating the blind spots that are created by taking this research approach to the practice of drama education, we will present the user research perspective and look at the opportunities that it provides to generate new, differentiated knowledge. User research makes it possible to illuminate the processes of acquiring and using knowledge in terms of its delivery. It also provides a potential framework of analysis for placing these processes in the delivery context, which includes subjective learning types, relevance and institutional and social conditions. This expanded perspective will make it possible to identify the factors that foster and limit benefits and reflect them in practice.
Land of High Hopes
(2019)
We are living in the era of sophisticated, state-of-the-art technology, artificial intelligence, accelerating data sciences at ultimate speed and sheer unlimited possibilities. We are able to shoot unmanned rockets equipped with vehicles into the orbit. We can afford to spend fortunes on research and development. However, and that leaves me bloodcurdling and furious, we haven´t managed yet to settle at least some of the most pressing global humanitarian needs: access to food, water, electricity, education and healthcare. So how can we be proud of any achievements? What does make us proud anyway?! ...
There is a popular saying in German: Innovation is when the market shouts “Hooray!”. Thus, a new idea is only as good as its diffusion into the addressed social system. The question is what affects the adoption or rejection of a new idea. Carsten Deckert shares his experience on the main innovation resistances and on ways to increase the acceptance of new ideas. He talks about which perceived attributes of innovations are conducive to the rate of adoption of an innovation and which are characteristics of failed innovations.
The definition of individual creativity is based on a tension between novelty on the one side and usefulness respectively appropriateness on the other side. The paper explores how this tension pervades the stage and componential theories of creativity. To achieve this, the so called value square (“Wertequadrat”) developed by Helwig (1967) and Schulz von Thun (1998)is used which balances a value with its countervalue to analyze creativity. The author identifies tensions of action and inaction, expertise and mindfulness, precision and ambiguity as well as immersion and detachment permeating the creative process and the components of creativity. As a conclusion a morphological box for creativity is presented which allows one to show which combination of characteristics of the tensions support different stages of creativity. Furthermore implications for development and time management are discussed.