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Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, where they support people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their perception and comprehending how they “see” the world. To tackle this challenge, we compared three different visualization techniques for Spatial Augmented Reality. All of these communicate cobot perception by visually indicating which objects in the cobot’s surrounding have been identified by their sensors. We compared the well-established visualizations Wedge and Halo against our proposed visualization Line in a remote user experiment with participants suffering from physical impairments. In a second remote experiment, we validated these findings with a broader non-specific user base. Our findings show that Line, a lower complexity visualization, results in significantly faster reaction times compared to Halo, and lower task load compared to both Wedge and Halo. Overall, users prefer Line as a more straightforward visualization. In Spatial Augmented Reality, with its known disadvantage of limited projection area size, established off-screen visualizations are not effective in communicating cobot perception and Line presents an easy-to-understand alternative.
Different charge treatment approaches are examined for cyclotide-induced plasma membrane disruption by lipid extraction studied with dissipative particle dynamics. A pure Coulomb approach with truncated forces tuned to avoid individual strong ion pairing still reveals hidden statistical pairing effects that may lead to artificial membrane stabilization or distortion of cyclotide activity depending on the cyclotide’s charge state. While qualitative behavior is not affected in an apparent manner, more sensitive quantitative evaluations can be systematically biased. The findings suggest a charge smearing of point charges by an adequate charge distribution. For large mesoscopic simulation boxes, approximations for the Ewald sum to account for mirror charges due to periodic boundary conditions are of negligible influence.
The use of molecular string representations for deep learning in chemistry has been steadily increasing in recent years. The complexity of existing string representations, and the difficulty in creating meaningful tokens from them, lead to the development of new string representations for chemical structures. In this study, the translation of chemical structure depictions in the form of bitmap images to corresponding molecular string representations was examined. An analysis of the recently developed DeepSMILES and SELFIES representations in comparison with the most commonly used SMILES representation is presented where the ability to translate image features into string representations with transformer models was specifically tested. The SMILES representation exhibits the best overall performance whereas SELFIES guarantee valid chemical structures. DeepSMILES perform in between SMILES and SELFIES, InChIs are not appropriate for the learning task. All investigations were performed using publicly available datasets and the code used to train and evaluate the models has been made available to the public.
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data is an important factor for the generation of deep learning systems that generalise well and are not overfit to a specific type of input. In the case of chemical structure depictions, these features are defined by the depiction parameters such as bond length, line thickness, label font style and many others. Here we present RanDepict, a toolkit for the creation of diverse sets of chemical structure depictions. The diversity of the image features is generated by making use of all available depiction parameters in the depiction functionalities of the CDK, RDKit, and Indigo. Furthermore, there is the option to enhance and augment the image with features such as curved arrows, chemical labels around the structure, or other kinds of distortions. Using depiction feature fingerprints, RanDepict ensures diversely picked image features. Here, the depiction and augmentation features are summarised in binary vectors and the MaxMin algorithm is used to pick diverse samples out of all valid options. By making all resources described herein publicly available, we hope to contribute to the development of deep learning-based OCSR systems.
Web measurement studies can shed light on not yet fully understood phenomena and thus are essential for analyzing how the modern Web works. This often requires building new and adjustinng existing crawling setups, which has led to a wide variety of analysis tools for different (but related) aspects. If these efforts are not sufficiently documented, the reproducibility and replicability of the measurements may suffer—two properties that are crucial to sustainable research. In this paper, we survey 117 recent research papers to derive best practices for Web-based measurement studies and specify criteria that need to be met in practice. When applying these criteria to the surveyed papers, we find that the experimental setup and other aspects essential to reproducing and replicating results are often missing. We underline the criticality of this finding by performing a large-scale Web measurement study on 4.5 million pages with 24 different measurement setups to demonstrate the influence of the individual criteria. Our experiments show that slight differences in the experimental setup directly affect the overall results and must be documented accurately and carefully.
Zentrale Raumlufttechnische Anlagen (RLT-Anlagen) sind für Betriebszeiten von fünfzehn und mehr Jahren konzipiert. Nicht selten werden die Geräte auch nach 25 Jahren Dank Retrofit weiterbetrieben. Unberücksichtigt bleibt dabei, ob die zukünftigen, klimatischen Bedingungen noch der Auslegung entsprechen. Zur Überprüfung der klimatischen Änderungen können sogenannte Testreferenzjahre (TRY – Test Reference Year) genutzt werden. Diese basieren für die heutige Auslegung auf den lokalen, stündlichen Wetterbedingungen im Bezugsjahr 2012 und zusätzlich auf modellbasierten Wetterdaten für das Bezugsjahr 2045.
Das Zentralluftgerät einer Krankenhaus-Intensivstation wurde für die 15 Wetter¬stationen der VDI 4710, Blatt 3 in Deutschland auf die Leistungsanforderungen von heute und für das Jahr 2045 untersucht. Zusätzlich wurden für den Standort Berlin die aktuellen Wetteraufzeichnungen im Sommer 2020 betrachtet. Daraus lassen sich Rückschlüsse ziehen, wie sich städtische Wärmeinseln (UHI – Urban Heat Islands) zukünftig auf den Energie- und Leistungsbedarf zur Gebäudeklimatisierung auswirken werden.
Die Auswirkungen auf die Wärme- und Kältespitzenleistung sowie der kumulierte Energiebedarf werden genauso analysiert wie der Befeuchtungsbedarf. Hieraus lassen sich die potenziellen Leistungsreserven abschätzen und die Klimaresilienz der Anlagentechnik bewerten.
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT (COlleCtion of Open Natural prodUcTs) database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
Short Selling
(2022)
We propose a quantum-mechanical model to calculate the nonlinear differential conductance of a single molecular junction immersed in a solvent, either in pure form or as a binary mixture with varying volume fraction. The solvent mixture is captured by a dielectric continuum model for which the resulting spectral density is determined within the Gladstone-Dale approach. The conductance of the molecular junction is calculated by a real-time diagrammatic technique. We find a strong variation of the conductance maximum for varying volume fraction of the solvent mixture. Importantly, the calculated molecular nonlinear conductance shows a very good agreement with experimentally measured data for common molecular junctions in various polar solvent mixtures.
Supply-Chain-Angriffe sind eine akute Bedrohung für jedes Unternehmen. Einen Softwarelieferanten auszunutzen, um eine große Anzahl seiner Kunden zu erreichen, ist eine ausgeklügelte und erfolgreiche Methode aktueller Hacker. Die Spezialisierung der Unternehmen auf ihre Kernkompetenzen, die Globalisierung der Lieferketten (im folgendem wird Supply Chain und Lieferkette synonym verwendet), sowie die Digitalisierung entlang der Wertschöpfungskette sind nur einige Beispiele, wieso Angreifer vermehrt die Vertrauensbeziehung zwischen Kunden und Lieferanten verstärkt für Angriffe ausnutzen. Dieser Artikel erläutert Cyber-Angriffe in Bezug auf eine Supply Chain und zeigt Sicherheitsmechanismen für die erfolgreiche Verteidigung.
Damit die medizinische Versorgung weiterhin flächendeckend gewährleistet werden kann und den explodierenden Kosten Einhalt geboten wird, muss ein Gesundheitswesen der Zukunft auf digitalen Technologien basieren. Die Kritikalität der entsprechenden Health-Services ruft Cyber-Sicherheit auf den Plan – die Sensibilität der im Gesundheitswesen verarbeiteten Daten den Datenschutz. Ein zukunftsfähiges Gesundheitswesen braucht einen stringenten Rechtsrahmen, eine moderne cloudbasierte Telematikinfrastruktur, die je nach Sicherheitsbedarf in verschiedenen Modellen umgesetzt werden kann, einen restriktiven Umgang mit globalen Public-Cloud-Providern, eine besonders gesicherte, leistungsstarke Forschungsdateninfrastruktur – etwa zur Optimierung von KI-Fähigkeiten, sichere Gesundheitsanwendungen und einiges mehr. Hier ein Ausblick.
The printing variable least addressed in previous research aiming to reveal the effect of the FFF process parameters on the printed PLA part’s quality and properties is the filament color. Moreover, the color of the PLA, as well as its manufacturer, are rarely mentioned when the experimental conditions for the printing of the samples are described, although current existing data reveal that their influence on the final characteristics of the print should not be neglected. In order to point out the importance of this influential parameter, a natural and a black-colored PLA filament, produced by the same manufacturer, were selected. The dimensional accuracy, tensile strength, and friction properties of the samples were analyzed and compared for printing temperatures ranging from 200 C up to 240 C. The experimental results clearly showed different characteristics depending on the polymer color of samples printed under the same conditions. Therefore, the optimization of the FFF process parameters for the 3D-printing of PLA should always start with the proper selection of the type of the PLA material, regarding both its color and the fabricant.
For proton exchange membrane water electrolysis (PEMWE) to become competitive, the cost of stack components, such as bipolar plates (BPP), needs to be reduced. This can be achieved by using coated low-cost materials, such as copper as alternative to titanium. Herein we report on highly corrosion-resistant copper BPP coated with niobium. All investigated samples showed excellent corrosion resistance properties, with corrosion currents lower than 0.1 µA cm−2 in a simulated PEM electrolyzer environment at two different pH values. The physico-chemical properties of the Nb coatings are thoroughly characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM). A 30 µm thick Nb coating fully protects the Cu against corrosion due to the formation of a passive oxide layer on its surface, predominantly composed of Nb2O5. The thickness of the passive oxide layer determined by both EIS and XPS is in the range of 10 nm. The results reported here demonstrate the effectiveness of Nb for protecting Cu against corrosion, opening the possibility to use it for the manufacturing of BPP for PEMWE. The latter was confirmed by its successful implementation in a single cell PEMWE based on hydraulic compression technology.
Third-party tracking is a common and broadly used technique on the Web. Different defense mechanisms have emerged to counter these practices (e.g. browser vendors that ban all third-party cookies). However, these countermeasures only target third-party trackers and ignore the first party because the narrative is that such monitoring is mostly used to improve the utilized service (e.g. analytical services). In this paper, we present a large-scale measurement study that analyzes tracking performed by the first party but utilized by a third party to circumvent standard tracking preventing techniques. We visit the top 15,000 websites to analyze first-party cookies used to track users and a technique called “DNS CNAME cloaking”, which can be used by a third party to place first-party cookies. Using this data, we show that 76% of sites effectively utilize such tracking techniques. In a long-running analysis, we show that the usage of such cookies increased by more than 50% over 2021.
Aufgrund der zunehmenden IT-Technisierung und damit einhergehend stetigen Veränderung der Lebensbedingungen ist es notwendig, dass Menschen den IT-Lösungen und Unternehmen weiterhin und kontinuierlich vertrauen können. Denn durch den höheren Grad der IT-Technisierung steigt die Komplexität, wodurch es für den Nutzer zunehmend schwieriger wird, einzelne IT-Lösungen und deren Hintergründe zu verstehen sowie zu bewerten. Diese Veränderung hat Auswirkungen: Zum einen macht sie grundsätzlich den Nutzern – den Menschen – Angst, da gewohnte Vorgänge beständig ihre Gültigkeit verlieren. Zum anderen entsteht dadurch sowie durch die Komplexität latent das Gefühl, eine falsche Entscheidung zu treffen, weil nicht alles bedacht werden kann. So fällt dem Aspekt der Interdependenz von Vertrauen und Vertrauenswürdigkeit für deutsche und europäische Unternehmen eine hohe Bedeutung zu, insbesondere auch da sich internationale Tech-Unternehmen zunehmend weniger vertrauenswürdig im komplexen Cyber-Raum verhalten. Dies eröffnet die Möglichkeit, sich über den Aufbau von Vertrauen weltweit gegen internationale Unternehmen nachhaltig zu profilieren und positionieren. Um dieses Ziel zu realisieren, bedarf es einer strategischen Vorgehensweise – zum Beispiel auf Basis des Vertrauenswürdigkeitsmodells.