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Informed green façade selection: integrating LCA and microclimatic analysis for a dual-method approach
No full textThis study examines the greenhouse gas emissions and cooling effects of vertical greening systems, focusing on a specific use case in a residential area in Germany. The analysis incorporates a LCA to evaluate the global warming potential of construction materials and biomass within a cradle-to-cradle framework. In parallel, a microclimatic analysis employing the UTCI is conducted to assess the cooling effect and related microclimatic conditions. Results of a multi-criteria optimization reveal a trade-off between environmental impact and cooling effectiveness. The GWP varies by approximately 16% across the façade greening scenarios, while the cooling effect ranges from a median reduction of 0.04 K to 0.26 K, with maximum reductions of up to −1.95 K. No single optimal solution exists, as systems with better cooling performance typically involve higher material use and emissions. The study highlights the importance of integrating LCA and microclimatic analysis to support data-driven decision-making in sustainable urban planning
Structural basis for ligand recognition in the tobramycin riboswitch
No full textRecently, a novel tobramycin-responsive riboswitch was developed by a combination of Capture-SELEX and in vivo screening. This riboswitch regulates translation initiation in eukaryotes with a high dynamic range and remarkable ligand affinity and selectivity. Its secondary structure differs from all previously described aminoglycoside-binding RNA motifs, suggesting a novel mode of ligand recognition. To provide a structural basis for the remarkable regulatory efficiency and ligand selectivity of this riboswitch, we investigated its structure in complex with its cognate ligand tobramycin by high-resolution solution nuclear magnetic resonance spectroscopy. The structure of the complex reveals a novel structural organization for an aminoglycoside binding motif with a unique pattern of intermolecular hydrogen bonds and electrostatic interactions between the RNA and functional groups of all three rings of the ligand. In contrast to other aminoglycoside binding motifs, ligand binding of the tobramycin riboswitch is coupled with the formation of an extensive network of noncanonical RNA-RNA interactions, rationalizing the high ligand affinity of this small hairpin RNA. Comparison with the free form of the RNA shows that the latter is much less compact, lacking many RNA-RNA interactions, in particular in the bulge regions, thereby immediately providing a rationale for the exceptional switching efficiency of this synthetic riboswitch
Sich Sprache aneignen, schreiben(d) lernen, Diskurse mitgestalten: Ein pädagogisches Konzept für die gymnasiale Oberstufe in der Migrationsgesellschaft
No full textIn diesem Artikel stellen wir zum einen die Entwicklung eines Curriculums zur Vorbereitung auf die sprachlichen Anforderungen der gymnasialen Oberstufe dar. Zum anderen beschreiben wir die Innovationen, mit denen an der Versuchsschule Oberstufen-Kolleg Bielefeld auf (sprachliche) Heterogenität reagiert wird. Dabei geht es nicht nur darum, dass neuzugewanderte Jugendliche das Wissen und die sprachlichen Kompetenzen erwerben, die nötig sind, um die Anforderungen des Bildungssystems bzw. der Gesellschaft zu erfüllen. Die jungen Menschen sollen Sprache auch als Instrument erkennen, mit dem Zugehörigkeitskategorien etabliert und ihnen bestimmte Positionen in der Gesellschaft zugewiesen werden. Sprache soll ihnen als Mittel der Ermächtigung dienen, mit dem sie sich im Diskurs positionieren können
Why the Daisy Sisters are Different. A Stylometric Study on the Oeuvre of Swedish Author Henning Mankell and the Dutch Translations of His Work
No full textIn this paper, 32 books by the Swedish writer Henning Mankell were investigated using stylometric methods, to find out whether his style varies in different genres, if his style changed measurably over time, or if his books differ from each other stylistically for other reasons. The results show that the time of publication can play a role, but that other factors, such as dominant verb tense used and narrative perspective, as well as register, are more important in determining whether and how the style of novels differs. This study also gives more insight into frequently used methods in stylometry, such as cluster analysis and PCA, that give little information about the stylistic features that differ between texts. For this purpose, the original Swedish texts were also compared to the Dutch translations of the same texts to determine how translation and language influence the results of stylometric analyses
Combined UV/Vis and NMR spectroscopy allows for operando reaction monitoring: the case of guaiazulene and 2,4-dinitrobenzaldehyde
No full textCombined UV/Vis and NMR spectroscopy gives access to complementary spectroscopic information on a single sample. When used in operando reaction monitoring, it is possible to precisely correlate this complementary information, providing deeper mechanistic insights. We showcase this approach on the condensation reaction of guaiazulene and 2,4-dinitrobenzaldehyde
Methodological approach to analyze vehicle data in electric road systems: case study – ELISA, the eHighway project
No full textEvaluation of data-driven engineering solutions depends on efficient analysis and IT knowledge at expert level. Recent
technologies and their pilot applications in transportation engineering generate big data such as vehicle data. To handle
and analyze vehicle data, solutions, and new methodologies are necessary for field engineers to interpret the results
reliably. ELISA, the eHighway pilot project in Germany, is an engineering solution to achieve zero emission goal by
road freight transport. Five overhead contact line trucks (O-trucks) are operating along five kilometers of the
eHighway test track in each direction. In this study, we present a difference-based run detection methodology to
analyze vehicle data obtained through five O-trucks. Dataloggers on the O-trucks transmit more than 100 parameters
for each 100 ms. We propose that difference between following records for a parameter is an efficient way of analyzing
and detecting runs on a highway section. The proposed difference-based approach and run detection algorithm
performed well to investigate 650 GB data from O-trucks in the ELISA project. Operational and energy consumption
analyses by using this data process provide reliable and reasonable results. We shared numerical and visual analysis
samples to give insight for further evaluation and monitoring of the large-scale eHighway implementations
Learning Graphon Mean Field Games and Approximate Nash Equilibria
No full textRecent advances at the intersection of dense large graph limits and mean field games have begun to enable the scalable analysis of a broad class of dynamical sequential games with large numbers of agents. So far, results have been largely limited to graphon mean field systems with continuous-time diffusive or jump dynamics, typically without control and with little focus on computational methods. We propose a novel discrete-time formulation for graphon mean field games as the limit of non-linear dense graph Markov games with weak interaction. On the theoretical side, we give extensive and rigorous existence and approximation properties of the graphon mean field solution in sufficiently large systems. On the practical side we provide general learning schemes for graphon mean field equilibria by either introducing agent equivalence classes or reformulating the graphon mean field system as a classical mean field system. By repeatedly finding a regularized optimal control solution and its generated mean field, we successfully obtain plausible approximate Nash equilibria in otherwise infeasible large dense graph games with many agents. Empirically, we are able to demonstrate on a number of examples that the finite-agent behavior comes increasingly close to the mean field behavior for our computed equilibria as the graph or system size grows, verifying our theory. More generally, we successfully apply policy gradient reinforcement learning in conjunction with sequential Monte Carlo methods
“It’s Not My Data Anymore”: Exploring Non-Users’ Privacy Perceptions of Medical Data Donation Apps
No full textThis paper contributes an in-depth investigation (N=24) of privacy perceptions in the context of medical data donation apps. Medical data donation refers to the act of voluntarily sharing medical data with research institutions, which plays a crucial role in advancing healthcare research and personalized medicine. To design effective medical data donation apps, we need to understand how privacy expectations affect people's willingness to use such apps. We focus on non-users—those who have no experience with medical data donation apps—because gaining a deeper understanding of their perceptions is essential for fostering the adoption of these apps. Our findings highlight the importance of trust, transparency, and anonymity as driving factors. Participants expressed a willingness to share highly sensitive medical data with the apps if they were assured of complete anonymity, yet criticism regarding the risks of de-anonymization was also raised. Based on our results, we identify privacy awareness issues, especially concerning data sensitivity. Additionally, we explain the differences between participants' privacy expectations and preferences and what existing medical data donation apps offer. Finally, we provide guidance for the development of future user-centric medical data donation apps
Balancing Selectivity and Efficacy of Bispecific Epidermal Growth Factor Receptor (EGFR) × c-MET Antibodies and Antibody-Drug Conjugates
No full textBispecific antibodies (bsAbs) and antibody-drug conjugates (ADCs) have already demonstrated benefits for the treatment of cancer in several clinical studies, showing improved drug selectivity and efficacy. In particular, simultaneous targeting of prominent cancer antigens, such as EGF receptor (EGFR) and c-MET, by bsAbs has raised increasing interest for potentially circumventing receptor cross-talk and c-MET-mediated acquired resistance during anti-EGFR monotherapy. In this study, we combined the selectivity of EGFR × c-MET bsAbs with the potency of cytotoxic agents via bispecific antibody-toxin conjugation. Affinity-attenuated bispecific EGFR × c-MET antibody-drug conjugates demonstrated high in vitro selectivity toward tumor cells overexpressing both antigens and potent anti-tumor efficacy. Due to basal EGFR expression in the skin, ADCs targeting EGFR in general warrant early safety assessments. Reduction in EGFR affinity led to decreased toxicity in keratinocytes. Thus, the combination of bsAb affinity engineering with the concept of toxin conjugation may be a viable route to improve the safety profile of ADCs targeting ubiquitously expressed antigens
InvBERT: Reconstructing Text from Contextualized Word Embeddings by inverting the BERT pipeline
No full textDigital Humanities and Computational Literary Studies apply automated methods to enable studies on large corpora which are not feasible by manual inspection alone. However, due to copyright restrictions, the availability of relevant digitized literary works is limited. Derived Text Formats (DTFs) have been proposed as a solution. Here, textual materials are transformed in such a way that copyright-critical features are removed, but that the use of certain analytical methods remains possible. Word embeddings produced by transformer-encoders are promising candidates for DTFs because they allow for state-of-the-art performance on analytical tasks. However, in this paper we demonstrate that under certain conditions the reconstruction of the original text from token representations becomes feasible. Our attempts to invert BERT suggest, that publishing the encoder together with the contextualized embeddings is critical, since it allows to generate data to train a decoder with a reconstruction accuracy sufficient to violate copyright laws