open_access
Refine
Year of publication
Document Type
- Article (192) (remove)
Keywords
- DOAJ (37)
- Forena (9)
- DEAL (7)
- DFG Publikationskosten (3)
- HSD Publikationsfonds (3)
- Germany (2)
- peer (2)
- ADAS (1)
- AI performance metrics (1)
- Addressee-oriented research (1)
Department/institution
- Fachbereich - Maschinenbau und Verfahrenstechnik (80)
- Fachbereich - Sozial- & Kulturwissenschaften (50)
- Fachbereich - Medien (33)
- Fachbereich - Elektro- & Informationstechnik (18)
- Sound and Vibration Engineering (5)
- Fachbereich - Wirtschaftswissenschaften (4)
- Fachbereich - Architektur (3)
- Campus IT (1)
- Creative Media Production and Entertainment Computing (1)
- Digital Learning and Digital Literacy (1)
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.
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.
The PSFC, or Pioneer Sound Field Controller, is a DSP-driven hemispherical loudspeaker array, installed at the University of Aizu Multimedia Center. The PSFC features realtime manipulation of the primary components of sound spatialization for each of two audio sources located in a virtual environment, including the content (apparent direction and distance) and context (room characteristics: reverberation level, room size and liveness). In an alternate mode, it can also direct the destination of the two separate input signals across 14 loudspeakers, manipulating the direction of the virtual sound sources with no control over apparent distance other than that afforded by source loudness (including no simulated environmental reflections or reverberation). The PSFC speaker dome is about 10 m in diameter, accommodating about fifty simultaneous users, including about twenty users comfortably standing or sitting near its ``sweet spot,'' the area in which the illusions of sound spatialization are most vivid. Collocated with a large screen rear-projection stereographic display, the PSFC is intended for advanced multimedia and virtual reality applications.
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.
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.
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
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.
Applicability of Aeroacoustic Scaling Laws of Leading Edge Serrations for Rotating Applications
(2020)
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.
This paper deals with the design of a micro-scale ORC plant for teaching and research including the development of an automated control concept. The aim is to provide a safe and environmentally acceptable micro-scale heat engine, which can be developed, implemented and used in university labs for the education of students as well as for small research projects. The test rig allows the support of several learning outcomes on a multi-disciplinary level particularly for the implementation and simulation of small power systems. Special attention was given to the organic working fluid characteristics and its selection process. In addition to the above-mentioned performance goals, favourable safety properties and low global warming potential were decisive in the selection of the novel organic fluid called 3M™ Novec™ 649. The performance and the fluid behaviour of Novec 649 in a micro-scale power cycle are of major interest and the research goal for the test rig presented in this paper. Due to the expected power output of 1 kW, a scroll expander was chosen as the generator drive for the micro plant. In order to design the major parts of the ORC, the thermodynamic simulation software EBSILON®Professional was used. The supply temperature was set to 140 °C. As a result of the simulation, feasible expander inlet pressures spread from 5.5 bar to 8.5 bar. This leads to thermal efficiencies of the ORC in the order of 5 %. Adding a recuperator to the cycle system decreases the operating pressure range but in the end, the thermal efficiency can be increased by 1.5 %-points up to 6.2 %. Finally, an automated control concept is introduced, where the pump is controlled via the fill level measurement system.
Spatial precision and recall indices to assess the performance of instance segmentation algorithms
(2022)
Geschäftsmodelle für das Internet der Dinge: Welche Geschäftsmodellinnovation passt zum Unternehmen?
(2020)
Management des Innovationsportfolios: Portfolio-Matrizen zumManagement von Innovationsprojekten
(2021)
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.
The Sound of Success: Investigating Cognitive and Behavioral Effects of Motivational Music in Sports
(2017)
Listening to music before, during, or after sports is a common phenomenon, yet its functions and effects on performance, cognition, and behavior remain to be investigated. Listening to music before, during, or after sports is a common phenomenon, yet its functions and effects on performance, cognition, and behavior remain to be investigated. In this study we present a novel approach to the role of music in sports and exercise that focuses on the notion of musical self-enhancement (Elvers, 2016). We derived the following hypotheses from this framework: listening to motivational music will (i) enhance self-evaluative cognition, (ii) improve performance in a ball game, and (iii) evoke greater risk-taking behavior. To evaluate the hypotheses, we conducted a between-groups experiment (N = 150) testing the effectiveness of both an experimenter playlist and a participant-selected playlist in comparison to a no-music control condition. All participants performed a ball-throwing task developed by Decharms and Davé (1965), consisting of two parts: First, participants threw the ball from fixed distances into a funnel basket. During this task, performance was measured. In the second part, the participants themselves chose distances from the basket, which allowed their risk-taking behavior to be assessed. The results indicate that listening to motivational music led to greater risk taking but did not improve ball-throwing performance. This effect was more pronounced in male participants and among those who listened to their own playlists. Furthermore, self-selected music enhanced state self-esteem in participants who were performing well but not in those who were performing poorly. We also discuss further implications for the notion of musical self-enhancement. // Listening to music before, during, or after sports is a common phenomenon, yet its functions and effects on performance, cognition, and behavior remain to be investigated. In this study we present a novel approach to the role of music in sports and exercise that focuses on the notion of musical self-enhancement (Elvers, 2016). We derived the following hypotheses from this framework: listening to motivational music will (i) enhance self-evaluative cognition, (ii) improve performance in a ball game, and (iii) evoke greater risk-taking behavior. To evaluate the hypotheses, we conducted a between-groups experiment (N = 150) testing the effectiveness of both an experimenter playlist and a participant-selected playlist in comparison to a no-music control condition. All participants performed a ball-throwing task developed by Decharms and Davé (1965), consisting of two parts: First, participants threw the ball from fixed distances into a funnel basket. During this task, performance was measured. In the second part, the participants themselves chose distances from the basket, which allowed their risk-taking behavior to be assessed. The results indicate that listening to motivational music led to greater risk taking but did not improve ball-throwing performance. This effect was more pronounced in male participants and among those who listened to their own playlists. Furthermore, self-selected music enhanced state self-esteem in participants who were performing well but not in those who were performing poorly. We also discuss further implications for the notion of musical self-enhancement.
Menschen mit Suchtverhalten, die Bürgergeld nach dem Sozialgesetzbuch II beziehen, zu ihren Wünschen an für sie hilfreiche Unterstützungsangebote zu befragen und aus ihren Schilderungen herauszuarbeiten, welche Bedeutung für sie Erwerbarbeit hat, fordert die Forschenden zu kritischen Selbstvergewisserungen heraus.Denn die qualitative Studie, die im Rahmen eines Modellprojekts, gefördert vom Bundesarbeitsministerium, durchgeführt wurde, berührt vier kritische Fachdebatten in der Sozialen Arbeit. Neben der (1) sozialpolitischen Aktivierungsprogrammatik sind hier v. a. die (2) Bezeichnung von Menschen mit Suchtverhalten sowie (3) methodologische Einwände gegen subjektorientierte Forschungsperspektiven und (4) Case Management bedeutsam. Nach der Positionierung in diesen Fachdebatten werden empirische Einblicke dazu gewährt, dass die Frage „Problembewältigung oder Erwerbsarbeit first?“ differenziert beantwortet wird.Ferner äußern die Bürgergeldbezieher:innen mit Suchtverhalten diverse Wünsche an die Unterstützung im Jobcenter und andere Hilfsangebote. Vor allem wünschen sie sich vom Jobcenter, dass es dort nicht nur um die Vermittlung in Erwerbsarbeit gehen sollte, sondern weitere und damit hybride Zielsetzungen verfolgt werden sollten.
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
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.
Synthesis and Analysis of a Novel Linkage Mechanism with the Helical Motion of the End-Effector
(2020)
The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.
Men afflicted with chronic obstructive pulmonary disease (COPD) show signs of muscle dysfunction, such as increased muscle fatigue and acidosis during exercise. We hypothesize that muscle elasticity of the lower extremities differs between patients with COPD and age-related controls. The shear modulus of the soleus muscle was measured non-invasively using MR elastography (MRE) at 0%, 5%, 10%, 15%, and 20% of the subject’s maximum applied force. The results from this study showed statistical differences between the patients and controls, even though there were no statistical differences in the maximum applied force.
Men afflicted with hypogonadism have reduced fat-free mass and in some cases a loss in muscle strength. We hypothesize that muscle elasticity of the lower extremities differs between patients with hypogonadism and healthy controls. The shear modulus of the soleus muscle was measured non-invasively using MR elastography (MRE) at 0%, 5%, 10%, 15%, and 20% of the subject’s maximum applied force. The results from this study showed statistical differences between the patients and controls, even though there were no statistical differences in applied force.
The importance of high data quality is increasing with the growing impact and distribution of ML systems and big data. Also, the planned AI Act from the European commission defines challenging legal requirements for data quality especially for the market introduction of safety relevant ML systems. In this paper, we introduce a novel approach that supports the data quality assurance process of multiple data quality aspects. This approach enables the verification of quantitative data quality requirements. The concept and benefits are introduced and explained on small example data sets. How the method is applied is demonstrated on the well-known MNIST data set based an handwritten digits.
In the present contribution, the utilization of steel-mill gases for an industrial methanol synthesis process is described. The focus of this work is on the influence of syngas compositions derived from steel-mill gases on an industrial Cu/ZnO/Al2O3 catalyst. Elevated CO2 and H2O concentrations seem to have an irreversible impact on the activity of the catalyst. In order to obtain realistic gas composition for the catalyst tests, a process simulation of the methanol synthesis was conducted. The calculated gas compositions at the reactor inlet were applied in a practical test in order to evaluate the catalyst stability under steel mill gas conditions. No noticeable deactivation was observed.
Methanol Synthesis with Steel Mill Gases: Performance Investigations in an On‐Site Technical Center
(2021)
Music listening has become a highly individualized activity with smartphones and music streaming services providing listeners with absolute freedom to listen to any kind of music in any situation. Until now, little has been written about the processes underlying the selection of music in daily life. The present study aimed to disentangle some of the complex processes among the listener, situation, and functions of music listening involved in music selection. Utilizing the experience sampling method, data were collected from 119 participants using a smartphone application. For 10 consecutive days, participants received 14 prompts using stratified-random sampling throughout the day and reported on their music-listening behavior. Statistical learning procedures on multilevel regression models and multilevel structural equation modeling were used to determine the most important predictors and analyze mediation processes between person, situation, functions of listening, and music selection. Results revealed that the features of music selected in daily life were predominantly determined by situational characteristics, whereas consistent individual differences were of minor importance. Functions of music listening were found to act as a mediator between characteristics of the situation and music-selection behavior. We further observed several significant random effects, which indicated that individuals differed in how situational variables affected their music selection behavior. Our findings suggest a need to shift the focus of music-listening research from individual differences to situational influences, including potential person-situation interactions.
Despite its impressive complexity the cytoskeleton succeeds to persistently organize itself and thus the cells' interior. In contrast to classical man-made machines, much of the cellular organization originates from inherent self-assembly and self-organization allowing a high degree of autonomy for various functional units. Recent experimental and theoretical studies revealed numerous examples of cytoskeleton components that arrange and organize in a self-regulative way. In the present review we want to shortly summarize some of the principle mechanisms that are able to inherently trigger and regulate the cytoskeleton organization. Although taken individually most of these regulative principles are rather simple with intuitively predictable consequences, combinations of two or more of these mechanisms can quickly give rise to very complex, unexpected behavior and might even be able to explain the formation of different functional units out of a common pool of available building blocks.
Many different cell types are able to migrate by formation of a thin actin-based cytoskeletal extension. Recently, it became evident that this extension consists of two distinct substructures, designated lamellipodium and lamellum, which differ significantly in their kinetic and kinematic properties as well as their biochemical composition. We developed a stochastic two-dimensional computer simulation that includes chemical reaction kinetics, G-actin diffusion, and filament transport to investigate the formation of growing actin networks in migrating cells. Model parameters were chosen based on experimental data or theoretical considerations. In this work, we demonstrate the system's ability to form two distinct networks by self-organization. We found a characteristic transition in mean filament length as well as a distinct maximum in depolymerization flux, both within the first 1-2 microm. The separation into two distinct substructures was found to be extremely robust with respect to initial conditions and variation of model parameters. We quantitatively investigated the complex interplay between ADF/cofilin and tropomyosin and propose a plausible mechanism that leads to spatial separation of, respectively, ADF/cofilin- or tropomyosin-dominated compartments. Tropomyosin was found to play an important role in stabilizing the lamellar actin network. Furthermore, the influence of filament severing and annealing on the network properties is explored, and simulation data are compared to existing experimental data.
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.
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.
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.
Am Musikvideo „Kiss“ von Prince and the Revolution (1986) werden exemplarisch verschiedene Verfahren beleuchtet, wie Gender durch „Stimme“ im konkreten und abstrakten Sinn auf ambivalente Weise inszeniert wird. Michael Bachtins Metapher der fremden Stimme für das intertexuelle Verweisgeflecht von Sprache im Allgemeinen und Literatur im Besonderen wird hier sowohl im übertragenen als auch im wörtlichen Sinne verwendet und auf audiovisuelle Musikformate übertragen. Das Spiel mit Gender entsteht durch eine komplexe Verwebung von intertextuellen und intermedialen Verweisen auf andere Liedtexte, Filme, Gesangstraditionen, Subkulturen etc. Dabei wird vestimentäres Cross-Dressing mit gesanglichem Cross-Dressing kombiniert.
Kaufhaus-Punk auf youtube. Mediale Kontrolle zwischen Musiker und Fans am Beispiel von Jan Delay
(2012)
Dandyismus und Popkultur
(2013)