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The need for innovation around the control functions of inverters is great. PV inverters were initially expected to be passive followers of the grid and to disconnect as soon as abnormal conditions happened. Since future power systems will be dominated by generation and storage resources interfaced through inverters these converters must move from following to forming and sustaining the grid. As “digital natives” PV inverters can also play an important role in the digitalisation of distribution networks. In this short review we identified a large potential to make the PV inverter the smart local hub in a distributed energy system. At the micro level, costs and coordination can be improved with bidirectional inverters between the AC grid and PV production, stationary storage, car chargers and DC loads. At the macro level the distributed nature of PV generation means that the same devices will support both to the local distribution network and to the global stability of the grid. Much success has been obtained in the former. The later remains a challenge, in particular in terms of scaling. Yet there is some urgency in researching and demonstrating such solutions. And while digitalisation offers promise in all control aspects it also raises significant cybersecurity concerns.
Lignocellulose feedstock (LCF) provides a sustainable source of components to produce bioenergy, biofuel, and novel biomaterials. Besides hard and soft wood, so-called low-input plants such as Miscanthus are interesting crops to be investigated as potential feedstock for the second generation biorefinery. The status quo regarding the availability and composition of different plants, including grasses and fast-growing trees (i.e., Miscanthus, Paulownia), is reviewed here. The second focus of this review is the potential of multivariate data processing to be used for biomass analysis and quality control. Experimental data obtained by spectroscopic methods, such as nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FTIR), can be processed using computational techniques to characterize the 3D structure and energetic properties of the feedstock building blocks, including complex linkages. Here, we provide a brief summary of recently reported experimental data for structural analysis of LCF biomasses, and give our perspectives on the role of chemometrics in understanding and elucidating on LCF composition and lignin 3D structure.
The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. The polyphenolic structure of lignin in addition to the presence of O-containing functional groups is potentially responsible for these activities. This study used DPPH assays to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. The scavenging activity (SA) of both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems was affected by the percentage of the added lignin: the 5% addition showed the highest activity and the 30% addition had the lowest. Both scavenging activity and antimicrobial activity are dependent on the biomass source showing the following trend: organosolv of softwood > kraft of softwood > organosolv of grass. Testing the antimicrobial activities of lignins and lignin-containing films showed high antimicrobial activities against Gram-positive and Gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin release in the produced films affected the activity positively and the chitosan addition enhances the activity even more for both Gram-positive and Gram-negative bacteria. Testing the films against spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films, the 5% addition exhibited activity against both B. thermosphacta and P. fluorescens.
BWL-Klausuren für Dummies
(2019)
Emotion and gender recognition from facial features are important properties of human empathy. Robots should also have these capabilities. For this purpose we have designed special convolutional modules that allow a model to recognize emotions and gender with a considerable lower number of parameters, enabling real-time evaluation on a constrained platform. We report accuracies of 96% in the IMDB gender dataset and 66% in the FER-2013 emotion dataset, while requiring a computation time of less than 0.008 seconds on a Core i7 CPU. All our code, demos and pre-trained architectures have been released under an open-source license in our repository at https://github.com/oarriaga/face classification.
The paper presents the topological reduction method applied to gas transport networks, using contraction of series, parallel and tree-like subgraphs. The contraction operations are implemented for pipe elements, described by quadratic friction law. This allows significant reduction of the graphs and acceleration of solution procedure for stationary network problems. The algorithm has been tested on several realistic network examples. The possible extensions of the method to different friction laws and other elements are discussed.
Incoming solar radiation is an important driver of our climate and weather. Several studies (see for instance Frank et al. 2018) have revealed discrepancies between ground-based irradiance measurements and the predictions of regional weather models. In the realm of electricity generation, accurate forecasts of solar photovoltaic (PV)energy yield are becoming indispensable for cost-effective grid operation: in Germany there are 1.6 million PVsystems installed, with a nominal power of 46 GW (Bundesverband Solarwirtschaft 2019). The proliferation of PV systems provides a unique opportunity to characterise global irradiance with unprecedented spatiotemporalresolution, which in turn will allow for highly resolved PV power forecasts.
Die Erfindung betrifft eine Filtervorrichtung zur Anreicherung gasförmiger und/oder partikelgebundener Stoffe. Erfindungsgemäß weist Filtervorrichtung eine wenigstens abschnittsweise luftdurchlässige Umhüllung (1, 3) und ein innerhalb der Umhüllung (1, 3) vorgesehenen Adsorbens (2) zur Anreicherung gasförmiger und/oder partikelgebundener Stoffe aus durch die Umhüllung (1, 3) hindurchgetretener Luft auf, zur nachfolgenden Überprüfung mittels eines lebenden olfaktorischen Detektors und/oder eines thermodesorptionsgekoppelten Analysegeräts auf Geruchsstoffe und/oder Zielanalyten, wobei ein Teil der Umhüllung (1, 3) einen in das Adsorbens (2) hineinführend, an nur einer Seite offenen Kanal (7) ausbildet, an dem offenen Ende des Kanals (7) eine Anschlusseinrichtung (8) zum Anschluss an ein Ansaugsystem angeordnet ist und die Umhüllung (1, 3) und das Adsorbens an Luft bis wenigstens 400 °C thermostabil sind. Auf diese Weise wird eine einfache und verlässliche Möglichkeit bereitgestellt, mit einer gemeinsamen Filtervorrichtung (9) sowohl eine Überprüfung mittels eines lebenden olfaktorischen Detektors sowie nachfolgend eine Überprüfung mittels eines thermodesorptionsgekoppelten Analysegeräts auf Geruchsstoffe und/oder Zielanalyten durchführen zu können.
§ 3. [Steuerfreie Einnahmen]
(2019)
§ 3c. Anteilige Abzüge
(2019)
Miscanthus bietet als nachwachsende Industrie- und Energiepflanze zahlreiche Vorteile, die neben den direkten landwirtschaftlichen Anwendungen wie Verbrennung und Tiereinstreu auch eine stoffliche Nutzung im chemischen Bereich zulassen. Als C4-Pflanze mit gesteigerter Photosynthese-Aktivität weist Miscanthus zudem eine hohe CO2-Fixierrate auf. Aufgrund des geringen Kultivierungsaufwandes sowie der hohen Erträge bietet sich Miscanthus als ausgesprochen attraktiver Rohstoff für die Produktion erneuerbarer Kraftstoffe und Chemikalien an, welche mittels thermo-chemischer Umwandlung gewonnen werden.
Miscanthus x giganteus Stem Versus Leaf-Derived Lignins Differing in Monolignol Ratio and Linkage
(2019)
As a renewable, Miscanthus offers numerous advantages such as high photosynthesis activity (as a C4 plant) and an exceptional CO2 fixation rate. These properties make Miscanthus very attractive for industrial exploitation, such as lignin generation. In this paper, we present a systematic study analyzing the correlation of the lignin structure with the Miscanthus genotype and plant portion (stem versus leaf). Specifically, the ratio of the three monolignols and corresponding building blocks as well as the linkages formed between the units have been studied. The lignin amount has been determined for M. x giganteus (Gig17, Gig34, Gig35), M. nagara (NagG10), M. sinensis (Sin2), and M. robustus (Rob4) harvested at different time points (September, December, and April). The influence of the Miscanthus genotype and plant component (leaf vs. stem) has been studied to develop corresponding structure-property relationships (i.e., correlations in molecular weight, polydispersity, and decomposition temperature). Lignin isolation was performed using non-catalyzed organosolv pulping and the structure analysis includes compositional analysis, Fourier transform infradred (FTIR), ultraviolet/visible (UV-Vis), hetero-nuclear single quantum correlation nuclear magnetic resonsnce (HSQC-NMR), thermogravimetric analysis (TGA), and pyrolysis gaschromatography/mass spectrometry (GC/MS). Structural differences were found for stem and leaf-derived lignins. Compared to beech wood lignins, Miscanthus lignins possess lower molecular weight and narrow polydispersities (<1.5 Miscanthus vs. >2.5 beech) corresponding to improved homogeneity. In addition to conventional univariate analysis of FTIR spectra, multivariate chemometrics revealed distinct differences for aromatic in-plane deformations of stem versus leaf-derived lignins. These results emphasize the potential of Miscanthus as a low-input resource and a Miscanthus-derived lignin as promising agricultural feedstock.
Herein we report an update to ACPYPE, a Python3 tool that now properly converts AMBER to GROMACS topologies for force fields that utilize nondefault and nonuniform 1–4 electrostatic and nonbonded scaling factors or negative dihedral force constants. Prior to this work, ACPYPE only converted AMBER topologies that used uniform, default 1–4 scaling factors and positive dihedral force constants. We demonstrate that the updated ACPYPE accurately transfers the GLYCAM06 force field from AMBER to GROMACS topology files, which employs non-uniform 1–4 scaling factors as well as negative dihedral force constants. Validation was performed using β-d-GlcNAc through gas-phase analysis of dihedral energy curves and probability density functions. The updated ACPYPE retains all of its original functionality, but now allows the simulation of complex glycomolecular systems in GROMACS using AMBER-originated force fields. ACPYPE is available for download at https://github.com/alanwilter/acpype.
In Sensor-based Fault Detection and Diagnosis (SFDD) methods, spatial and temporal dependencies among the sensor signals can be modeled to detect faults in the sensors, if the defined dependencies change over time. In this work, we model Granger causal relationships between pairs of sensor data streams to detect changes in their dependencies. We compare the method on simulated signals with the Pearson correlation, and show that the method elegantly handles noise and lags in the signals and provides appreciable dependency detection. We further evaluate the method using sensor data from a mobile robot by injecting both internal and external faults during operation of the robot. The results show that the method is able to detect changes in the system when faults are injected, but is also prone to detecting false positives. This suggests that this method can be used as a weak detection of faults, but other methods, such as the use of a structural model, are required to reliably detect and diagnose faults.
Trust is the lubricant of the sharing economy, especially in peer-to-peer carsharing where you leave a valuable good to a stranger in the hope of getting it backunscathed. Central mechanisms for handling this information gap nowadays are ratings and reviews of other users. The rising of connected car technology opens new possibilities to increase trust by collecting and providing e.g. driving behavior data. At the same time, this means an intrusion into the privacy of the user. Therefore, in this work we explore technological approaches that allow building trust without violating the privacy of individuals. We evaluate to what extent blockchain technology and smart contracts are suitable technologies to meet these challengesby setting upa prototype implementation of a block-chain-based carsharing approach. In this context, we present our research approachand evaluate the prototype in terms of trust and privacy.
Bond graph software can simulate bond graph models without the user needing to manually derive equations. This offers the power to model larger and more complex systems than in the past. Multibond graphs (those with vector bonds) offer a compact model which further eases handling multibody systems. Although multibond graphs can be simulated successfully, the use of vector bonds can present difficulties. In addition, most qualitative, bond graph–based exploitation relies on the use of scalar bonds. This article discusses the main methods for simulating bond graphs of multibody systems, using a graphical software platform. The transformation between models with vector and scalar bonds is presented. The methods are then compared with respect to both time and accuracy, through simulation of two benchmark models. This article is a tutorial on the existing methods for simulating three-dimensional rigid and holonomic multibody systems using bond graphs and discusses the difficulties encountered. It then proposes and adapts methods for simulating this type of system directly from its bond graph within a software package. The value of this study is in giving practical guidance to modellers, so that they can implement the adapted method in software.
IT-Leistungen vermischen sich zunehmend mit Business-Leistungen. Bisher verbinden Anwender "Lizenzierung" lediglich mit softwaretechnologischen sowie lizenzrechtliche Fragestellungen. Software- und Businessstrategie wurden als getrennte Bereiche eingestuft und von verschiedenen Personen verantwortet. Bedingt durch die "Verschmelzung von Software und Hardware sowie Serviceanteilen" zu Cloud-Diensten, kann man im Rahmen von "Lizenzierung" nun über Outsourcing „durch die Hintertür“ sprechen.
Die unterschiedlichen Facetten der digitalen Zukunft zu beleuchten – sei es die aktive Gestaltungsaufgabe der Politik, die ethischen und moralischen Anpassungen durch Digitalisierung in der Gesellschaft oder die technische und wirtschaftliche Verantwortung – und in Bezug zueinander zu setzen, ist Aufgabe und Ziel dieser Publikation. Im Zuge der digitalen Transformation ist zudem der Ruf nach einer neuen Kultur für Gesellschaft, Politik und Wirtschaft geboten.
Gefährdet die Nutzung von Gesundheits-Apps und Wearables die solidarische Krankenversicherung?
(2019)
Blutdruck messen, Schrittzahl verfolgen, Schlaf kontrollieren, Zuckerwerte im Blick haben und sogar die Durchführung von EKGs – dies sind nur einige der Anwendungen, die ein gängiges Mobiltelefon oder eine Smartwatch mit entsprechender Software durchführen können. Apps und Wearables (so werden am Körper getragene Computertechnologien genannt) werden in ihren Einsatzmöglichkeiten immer vielfältiger.
Synthesis of Substituted Hydroxyapatite for Application in Bone Tissue Engineering and Drug Delivery
(2019)
Designing consumption feedback to support sustainable behavior is an active research topic. In recent years, relevant work has suggested a variety of possible design strategies. Addressing the more recent developments in this field, this paper presents a structured literature review, providing an overview of current information design approaches and highlighting open research questions. We suggest a literature-based taxonomy of used strategies, data source and output media with a special focus on design. In particular, we analyze which visual forms are used in current research to reach the identified strategy goals. Our survey reveals that the trend is towards more complex and contextualized feedback and almost every design within sustainable HCI adopts common visualization forms. Furthermore, adopting more advanced visual forms and techniques from information visualization research is helpful when dealing with ever-increasing data sources at home. Yet so far, this combination has often been neglected in feedback design.
It is shown that the electrochemical kinetics of alkaline methanol oxidation can be reduced by setting certain fast reactions contained in it to a steady state. As a result, the underlying system of Ordinary Differential Equations (ODE) is transformed to a system of Differential-Algebraic Equations (DAE). We measure the precision characteristics of such transformation and discuss the consequences of the obtained model reduction.
Internet-Ökonomie
(2019)
Dieses Buch zeigt, wie sich Apple, Amazon, Facebook und Google zu den wertvollsten Unternehmen der Welt entwickeln konnten. Ihr Erfolg basiert auf dem Ergreifen von Chancen, die die digitale Welt und das Internet bieten. Traditionelle Geschäftsmodelle werden dadurch verändert und über Jahrzehnte gewachsene Marktstrukturen teilweise in Frage gestellt.
Intact Transition Epitope Mapping - Targeted High-Energy Rupture of Extracted Epitopes (ITEM-THREE)
(2019)
Epitope mapping, which is the identification of antigenic determinants, is essential for the design of novel antibody-based therapeutics and diagnostic tools. ITEM-THREE is a mass spectrometry-based epitope mapping method that can identify epitopes on antigens upon generating an immune complex in electrospray-compatible solutions by adding an antibody of interest to a mixture of peptides from which at least one holds the antibody's epitope. This mixture is nano-electrosprayed without purification. Identification of the epitope peptide is performed within a mass spectrometer that provides an ion mobility cell sandwiched in-between two collision cells and where this ion manipulation setup is flanked by a quadrupole mass analyzer on one side and a time-of-flight mass analyzer on the other side. In a stepwise fashion, immune-complex ions are separated from unbound peptide ions and dissociated to release epitope peptide ions. Immune complex-released peptide ions are separated from antibody ions and fragmented by collision induced dissociation. Epitope-containing peptide fragment ions are recorded, and mass lists are submitted to unsupervised data base search thereby retrieving both, the amino acid sequence of the epitope peptide and the originating antigen. ITEM-THREE was developed with antiTRIM21 and antiRA33 antibodies for which the epitopes were known, subjecting them to mixtures of synthetic peptides of which one contained the respective epitope. ITEM-THREE was then successfully tested with an enzymatic digest of His-tagged recombinant human β-actin and an antiHis-tag antibody, as well as with an enzymatic digest of recombinant human TNFα and an antiTNFα antibody whose epitope was previously unknown.
This work addresses the issue of finding an optimal flight zone for a side-by-side tracking and following Unmanned Aerial Vehicle(UAV) adhering to space-restricting factors brought upon by a dynamic Vector Field Extraction (VFE) algorithm. The VFE algorithm demands a relatively perpendicular field of view of the UAV to the tracked vehicle, thereby enforcing the space-restricting factors which are distance, angle and altitude. The objective of the UAV is to perform side-by-side tracking and following of a lightweight ground vehicle while acquiring high quality video of tufts attached to the side of the tracked vehicle. The recorded video is supplied to the VFE algorithm that produces the positions and deformations of the tufts over time as they interact with the surrounding air, resulting in an airflow model of the tracked vehicle. The present limitations of wind tunnel tests and computational fluid dynamics simulation suggest the use of a UAV for real world evaluation of the aerodynamic properties of the vehicle’s exterior. The novelty of the proposed approach is alluded to defining the specific flight zone restricting factors while adhering to the VFE algorithm, where as a result we were capable of formalizing a locally-static and a globally-dynamic geofence attached to the tracked vehicle and enclosing the UAV.
Estimating the impact of successful completion of vocational education on employment outcomes
(2019)
In this thesis, unique administrative data, a relevant time of follow-up and advanced statistical measures to handle confounding have been utilized in order to provide new and informative evidence on the effects of vocational rehabilitation programs on work participation outcomes in Germany. While re-affirming the important role of micro-level determinants, the present study provides an extensive example of the individual and fiscal effects that are possible through meaningful vocational rehabilitation measures. The analysis showed that the principal objective, namely, to improve participation in employment, was generally achieved. Contrary to the common misconception that “off-the-job training” is relatively ineffective, this thesis has provided an empirical example of the positive impact of the programs.