Showing papers by "Technical University of Dortmund published in 2022"

A Meta-analysis of the Uncanny Valley's Independent and Dependent Variables

Abstract: The uncanny valley (UV) effect is a negative affective reaction to human-looking artificial entities. It hinders comfortable, trust-based interactions with android robots and virtual characters. De...

Sleep problems and their interaction with physical activity and fatigue in hematological cancer patients during onset of high dose chemotherapy.

Abstract: Sleep problems reported by hematological cancer patients are usually linked to higher levels of cancer-related fatigue. Although the awareness of sleep problems in solid cancer patients is rising, there has been less attention to the issue in hematological cancer patients. The present study assesses the differences in sleep by comparing physical activity and fatigue levels among hematological cancer patients during the onset of chemotherapy. Furthermore, it investigates the relationship between sleep, physical activity, and fatigue through mediation analysis. The recruited sample consists of 58 newly diagnosed hematological cancer patients (47.1 ± 15.4 yrs; 51.7% males). Subjects completed questionnaires assessing sleep (PSQI), physical activity (visual analogue scale), fatigue (MFI-20), anxiety, depression (HADS), and quality of life (EORTC QLQ-C30) within two weeks from starting treatment. The sample reported more sleep problems in comparison to the German population norm. The classification as good (ca 25%) or bad sleepers (ca 75%) showed less frequent physical activity (p = .04), higher fatigue (p = .032), anxiety (p = .003), depression (p = .011) and pain (p = .011) in bad sleepers. The mediation analysis revealed significant indirect effects of sleep on fatigue through physical activity habits. This study highlights the combined action of sleep problems and physical activity on fatigue during the onset of induction chemotherapy. These two parameters could represent meaningful intervention targets to improve a patient’s status during chemotherapy. The study was registered on the WHO trial register (DRKS00007824).

Adaptive helicity and chiral recognition in bright europium quadruple-stranded helicates induced by host-guest interaction

Abstract: Chiral information transfer is crucial to design new functions like, for instance, sensing through chiroptical probes in which the input is readout as a consequence of a chiral recognition event. Herein, we report lanthanide quadruple-stranded helicates [Ln2L4]2− that show a guest-to-host chirality transfer. As confirmed by X-ray diffraction (XRD) and density functional theory (DFT) calculations, these cages are present in solution as an equilibrating racemic mixture of left- and right-handed helicates. The helicates adapt their helical conformation by encapsulation of a chiral guest enabling also straightforward enantiomeric excess determination. Asymmetric induction is demonstrated by circular dichroism (CD) and circularly polarized luminescence (CPL), and a helicity inversion mechanism based on a Bailar twist is proposed and studied by DFT calculations. The presented research contributes to the design of helicates with a unique combination of confined cavities, adaptive chirality, and peculiar luminescent properties, finding applications toward the development of optical probes for selective chiral sensing via molecular recognition.

Modulation of the Conformational Space of SARS‐CoV‐2 RNA Quadruplex RG‐1 by Cellular Components and the Amyloidogenic Peptides α‐Synuclein and hIAPP

Abstract: Given the emergence of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), which particularly threatens older people with comorbidities such as diabetes mellitus and dementia, understanding the relationship between Covid-19 and other diseases is an important factor for treatment. Possible targets for medical intervention include G-quadruplexes (G4Qs) and their protein interaction partners. We investigated the stability and conformational space of the RG-1 RNA-G-quadruplex of the SARS-CoV-2 N-gene in the presence of salts, cosolutes, crowders and intrinsically disordered peptides, focusing on α-Synuclein and the human islet amyloid polypeptide, which are involved in Parkinson's disease (PD) and type-II diabetes mellitus (T2DM), respectively. We found that the conformational dynamics of the RG-1 G4Q is strongly affected by the various solution conditions. Further, the amyloidogenic peptides were found to strongly modulate the conformational equilibrium of the RG-1. Considerable changes are observed with respect to their interaction with human telomeric G4Qs, which adopt different topologies. These results may therefore shed more light on the relationship between PD as well as T2DM and the SARS-CoV-2 disease and their molecular underpinnings. Since dysregulation of G4Q formation by rationally designed targeting compounds affects the control of cellular processes, this study should contribute to the development of specific ligands for intervention.

Biotechnological production of cyclic dinucleotides-Challenges and opportunities.

Abstract: Cyclic dinucleotides (CDNs) are widely used secondary signaling molecules in prokaryotic and eukaryotic cells. As strong agonists of the stimulator of interferon genes, they are of great interest for pharmaceutical applications. In particular, cyclic-GMP-AMP and related synthetic CDNs are promising candidates in preclinical work and even some in clinical phase 1 and 2 studies. The comparison of chemical and biocatalytic synthesis routes elucidated that biological CDN synthesis offers some advantages, such as shorter synthesis time, avoiding complex protective group chemistry, and the access to a new spectrum of CDNs. However, the synthesis of CDNs in preparative quantities is still a challenge, since the chemical synthesis of CDNs suffers from low yields and complex synthetic routes and the enzymatically catalyzed synthesis is limited by low product titers and process stability. We aim to review the latest discoveries and recent trends in chemical and biocatalytic synthesis of CDNs with a focus on the synthesis of a huge variety of CDN derivatives. We furthermore consider the most promising biotechnological processes for CDN production by evaluating key figures of the currently known processes.

The Landé factors of electrons and holes in lead halide perovskites: universal dependence on the band gap

Abstract: The Land\'e or $g$-factors of charge carriers are decisive for the spin-dependent phenomena in solids and provide also information about the underlying electronic band structure. We present a comprehensive set of experimental data for values and anisotropies of the electron and hole Land\'e factors in hybrid organic-inorganic (MAPbI$_3$, MAPb(Br$_{0.5}$Cl$_{0.5}$)$_3$, MAPb(Br$_{0.05}$Cl$_{0.95}$)$_3$, FAPbBr$_3$, FA$_{0.9}$Cs$_{0.1}$PbI$_{2.8}$Br$_{0.2}$) and all-inorganic (CsPbBr$_3$) lead halide perovskites, determined by pump-probe Kerr rotation and spin-flip Raman scattering in magnetic fields up to 10~T at cryogenic temperatures. Further, we use first-principles DFT calculations in combination with tight-binding and $\mathbf k \cdot \mathbf p$ approaches to calculate microscopically the Land\'e factors. The results demonstrate their universal dependence on the band gap energy across the different perovskite material classes, which can be summarized in a universal semi-phenomenological expression, in good agreement with experiment.

Quantification of gas-accessible microporosity in metal-organic framework glasses

Abstract: Abstract Metal-organic framework (MOF) glasses are a new class of glass materials with immense potential for applications ranging from gas separation to optics and solid electrolytes. Due to the inherent difficulty to determine the atomistic structure of amorphous glasses, the intrinsic structural porosity of MOF glasses is only poorly understood. Here, we investigate the porosity features (pore size and pore limiting diameter) of a series of prototypical MOF glass formers from the family of zeolitic imidazolate frameworks (ZIFs) and their corresponding glasses. CO 2 sorption at 195 K allows quantifying the microporosity of these materials in their crystalline and glassy states, also providing excess to the micropore volume and the apparent density of the ZIF glasses. Additional hydrocarbon sorption data together with X-ray total scattering experiments prove that the porosity features of the ZIF glasses depend on the types of organic linkers. This allows formulating design principles for a targeted tuning of the intrinsic microporosity of MOF glasses. These principles are counterintuitive and contrary to those established for crystalline MOFs but show similarities to strategies previously developed for porous polymers.

Lepton universality and lepton flavor conservation tests with dineutrino modes

Abstract: Abstract $$SU(2)_L$$ S U ( 2 ) L -invariance links charged dilepton and dineutrino couplings. Phenomenological implications are worked out for flavor changing neutral currents involving strange, charm, beauty and top quark transitions in a model-independent way. We put forward novel tests of lepton universality and lepton flavor conservation in $$|\varDelta c|= |\varDelta u|=1$$ | Δ c | = | Δ u | = 1 and $$|\varDelta b|= |\varDelta q|=1$$ | Δ b | = | Δ q | = 1 , $$q=d,s$$ q = d , s , transitions suitable for the experiments Belle II and BES III. Single top production plus dileptons uniquely probes semileptonic four-fermion $$|\varDelta t|= |\varDelta q'|=1$$ | Δ t | = | Δ q ′ | = 1 , $$q'=u,c$$ q ′ = u , c , couplings and further study at the LHC is encouraged. Tests with single top production associated with dileptons and missing energy are suitable for study at future $$e^+ e^-$$ e + e - or muon colliders.

Robust Tube-Enhanced Multi-Stage NMPC With Stability Guarantees

Abstract: We propose a robust Nonlinear Model Predictive Control (NMPC) scheme that provides an improved trade-off between optimality and complexity when compared to other available strategies. Two controllers are employed in the proposed framework: A multi-stage primary controller that optimizes a given objective in the presence of uncertainties with tightened constraints and a multi-stage ancillary controller that tracks the predicted tree of state and input trajectories of the primary controller. The primary controller optimizes the original objective by considering different realizations of the most significant uncertainties in the predictions. The ancillary controller provides robustness against other uncertainties by tracking the predicted tree of state and input trajectories of the primary controller. We establish sufficient conditions for closed-loop stability. The advantages of the scheme are demonstrated for a continuous stirred tank reactor (CSTR) example.

Predicting Solvent Effects on Homogeneity and Kinetics of the Hydroaminomethylation: A Thermodynamic Approach Using PC-SAFT

Abstract: Solvents may significantly affect the phase behavior and kinetics of chemical reactions. Especially for complex reactions performed in mixtures of different solvents, it requires a high experimental effort to quantify these effects. This work focuses on a novel thermodynamic approach to predict solvent effects on both reaction rates and phase behavior. We applied this method to the homogeneously catalyzed hydroaminomethylation of 1-decene in a thermomorphic multiphase system of methanol and n-dodecane. For that purpose, the thermodynamic activities of the reactants and the liquid–liquid equilibrium of the multicomponent reaction system were successfully modeled using the Perturbed-Chain Statistical Associating Fluid Theory (PC-SAFT). An increasing concentration of n-dodecane in the solvent mixture was predicted not only to limit the working space for the reaction due to unwanted phase separation but also to massively reduce the reaction rate. These results were in good agreement with batch experiments and homogeneity tests performed in this work. The approach is applicable to a wide variety of liquid-phase reactions and thus is a valuable tool for reducing the experimental effort to a minimum.

Skeletal contraction: A novel strategy to access multisubstituted cyclobutane

Abstract: The polysubstituted and spirocyclic cyclobutanes were efficiently constructed by the utilization of a novel skeletal contraction strategy which only took one-step synthesis from the readily accessible pyrrolidines. The mechanistic studies indicated that a key intermediate N-aminated pyrrolidine was formed initially and subsequent extrusion of a nitrogen via a radical pathway completed the transformation. This practical methodology was further highlighted by the concise, formal synthesis of the cytotoxic natural product piperarborenine B.

Photon Echo Polarimetry of Excitons and Biexcitons in a CH₃NH₃PbI₃ Perovskite Single Crystal

Abstract: Lead halide perovskites show remarkable performance when used in photovoltaic and optoelectronic devices. However, the peculiarities of light-matter interactions in these materials in general are far from being fully explored experimentally and theoretically. Here we specifically address the energy level order of optical transitions and demonstrate photon echos in a methylammonium lead triiodide single crystal, thereby determining the optical coherence times $T_2$ for excitons and biexcitons at cryogenic temperature to be 0.79 ps and 0.67 ps, respectively. Most importantly, we have developed an experimental photon-echo polarimetry method that not only identifies the contributions from exciton and biexciton complexes, but also allows accurate determination of the biexciton binding energy of 2.4 meV, even though the period of quantum beats between excitons and biexcitons is much longer than the coherence times of the resonances. Our experimental and theoretical analysis methods contribute to the understanding of the complex mechanism of quasiparticle interactions at moderate pump density and show that even in high-quality perovskite crystals and at very low temperatures, inhomogeneous broadening of excitonic transitions due to local crystal potential fluctuations is a source of optical dephasing.

TaintBench: Automatic real-world malware benchmarking of Android taint analyses

Abstract: Due to the lack of established real-world benchmark suites for static taint analyses of Android applications, evaluations of these analyses are often restricted and hard to compare. Even in evaluations that do use real-world apps, details about the ground truth in those apps are rarely documented, which makes it difficult to compare and reproduce the results. To push Android taint analysis research forward, this paper thus recommends criteria for constructing real-world benchmark suites for this specific domain, and presents TaintBench, the first real-world malware benchmark suite with documented taint flows. TaintBench benchmark apps include taint flows with complex structures, and addresses static challenges that are commonly agreed on by the community. Together with the TaintBench suite, we introduce the TaintBench framework, whose goal is to simplify real-world benchmarking of Android taint analyses. First, a usability test shows that the framework improves experts’ performance and perceived usability when documenting and inspecting taint flows. Second, experiments using TaintBench reveal new insights for the taint analysis tools Amandroid and FlowDroid: (i) They are less effective on real-world malware apps than on synthetic benchmark apps. (ii) Predefined lists of sources and sinks heavily impact the tools’ accuracy. (iii) Surprisingly, up-to-date versions of both tools are less accurate than their predecessors.

On the Relation between Prediction and Imputation Accuracy under Missing Covariates

Abstract: Missing covariates in regression or classification problems can prohibit the direct use of advanced tools for further analysis. Recent research has realized an increasing trend towards the use of modern Machine-Learning algorithms for imputation. This originates from their capability of showing favorable prediction accuracy in different learning problems. In this work, we analyze through simulation the interaction between imputation accuracy and prediction accuracy in regression learning problems with missing covariates when Machine-Learning-based methods for both imputation and prediction are used. We see that even a slight decrease in imputation accuracy can seriously affect the prediction accuracy. In addition, we explore imputation performance when using statistical inference procedures in prediction settings, such as the coverage rates of (valid) prediction intervals. Our analysis is based on empirical datasets provided by the UCI Machine Learning repository and an extensive simulation study.

Families of faces and the normal cycle of a convex semi-algebraic set

Abstract: Abstract We study families of faces for convex semi-algebraic sets via the normal cycle which is a semi-algebraic set similar to the conormal variety in projective duality theory. We propose a convex algebraic notion of a patch —a term recently coined by Ciripoi, Kaihnsa, Löhne, and Sturmfels as a tool for approximating the convex hull of a semi-algebraic set. We discuss geometric consequences, both for the semi-algebraic and convex geometry of the families of faces, as well as variations of our definition and their consequences.

Governing innovation platforms in multi-business organisations

Abstract: Innovation platforms enable companies to create broad and dynamic portfolios of applications, which can be developed internally and externally. An increasing number of established companies from traditional industries have begun to explore the potential of innovation platforms. These companies are often organised as multi-business organisations (MBOs). When introducing innovation platforms, they face tensions between the corporate centre that runs such platforms and business units that develop applications on the platform. Established approaches to information technology (IT) governance in MBOs are ineffective in addressing these tensions because they focus on cross-business-unit synergies, rather than on innovation from business units. To explore this issue further, we conducted a longitudinal case study of an automotive manufacturer that introduced an innovation platform in its infotainment system. The company faced four tensions: rigidity, alteration, mistrust, and competition. To address these tensions, the company evolved its IT governance, allowing for more flexibility for business units, supporting their development efforts, and prioritising them over external complementors. The role of the corporate centre evolved from a gatekeeper to an enabler of innovation. Our findings link the literature on IT governance in MBOs with that of platform governance, providing insights into how MBOs benefit from innovation platforms.