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Supplementary information for our manuscript by the same title. Text with alignment and construction information. List of parts. Optical calculations summary. Microcontroller code.

This paper aim is to provide a decision support model to assist the invoice delivery for about 200 customers in a law firm in Bogotá, Colombia. Each customer has a service time and establishes the conditions for the delivery, i.e., day, place, and time window. Invoices are delivered by motorcycle. We collect and analyze real travel and service times for each day of the week. To determine an optimal plan for invoice delivery, a mathematical model was developed for dealing with customer requests. One week (5 days) was chosen as a planning period for invoice delivery. Comparing the current route planning approach against the proposed method, we obtain savings in the total operating time by 13.3 %. Results indicate that the implementation of the proposed optimization model in weekly planning decisions could decrease operating times and increase service quality significantly.

The progressing digital transformation and internationalization of business processes cause a shift towards a more collaborative nature of processes. In such collaborations, different organizations execute separate parts of the process autonomously. This fragmentation leads to uncertainty regarding the correct execution of activities, the proper workflow, and data flow. If organizations engage in business together, trust is required. Current research identified blockchain and distributed ledger technologies as promising tools to mitigate trust issues in business processes. Yet, the detailed relationship of distributed ledgers and trust is regarded ambivalently. This thesis proposes three design science artifacts for analyzing and creating trust-aware business processes using distributed ledger technologies. Firstly, TAPE is a method for trust-aware business process engineering. The TAPE method consists of three steps. The first step analyzes trust issues in business processes. Therefore, TAPE uses a business process model and a trust model for joint semantical analysis. TAPE's second step uses trust patterns to mitigate trust issues in a collaborative business process. The last step of the TAPE method implements the trust-aware process. The second artifact that this thesis proposes is Trust Studio. Trust Studio is a web application that aids process analysts and engineers in applying the TAPE method. The last artifact this thesis introduces is a set of distributed ledger trust patterns. These trust patterns are classified with a taxonomy that helps to identify their trust-enhancing capabilities. A set of different evaluation methods assesses the utility of the introduced design science artifacts. The evaluation shows that all three contributions reached the status of a minimal viable artifact. Thus, the outcomes of this thesis foster a deep understanding of trust in business processes and how distributed ledger technologies can be utilized as a tool to mitigate trust issues. Die fortschreitende digitale Transformation und die Internationalisierung von Geschäftsprozessen führen zu einer Verlagerung hin zu einer stärkeren Kollaboration von Prozessen. Bei solchen Kollaborationen führen verschiedene Organisationen separate Teile des Prozesses autonom aus. Diese Fragmentierung führt zu Unsicherheiten hinsichtlich der korrekten Ausführung von Aktivitäten, des richtigen Workflows und des Datenflusses. Wenn Organisationen gemeinsam Geschäfte machen, ist Vertrauen erforderlich. Aktuelle Forschungen haben Blockchain und Distributed Ledger Technologien als vielversprechende Ansätze identifiziert, um Vertrauensprobleme in Geschäftsprozessen zu entschärfen. Die genaue Beziehung von verteilten Ledgern und Vertrauen wird jedoch ambivalent betrachtet. In dieser Arbeit werden drei Design-Science-Artefakte für die Analyse und Erstellung vertrauenswürdiger Geschäftsprozesse unter Verwendung von Distributed Ledgers vorgeschlagen. Erstens, TAPE ist eine Methode für vertrauenswürdiges Business Process Engineering. Die TAPE-Methode besteht aus drei Schritten. Im ersten Schritt werden Vertrauensprobleme (trust issues) in Geschäftsprozessen analysiert. Dazu verwendet TAPE ein Geschäftsprozessmodell und ein Vertrauensmodell zur gemeinsamen semantischen Analyse. Der zweite Schritt von TAPE verwendet Vertrauensmuster (trust patterns), um Vertrauensprobleme in einem kollaborativen Geschäftsprozess zu entschärfen. Der letzte Schritt der TAPE-Methode implementiert den vertrauensbewussten Prozess. Das zweite Artefakt, das diese Arbeit vorschlägt, ist Trust Studio. Trust Studio ist eine Webanwendung, die Prozessanalysten und Ingenieure bei der Anwendung der TAPE-Methode unterstützt. Das letzte Artefakt, das diese Arbeit vorstellt, ist eine Sammlung von Distributed Ledger Vertrauensmuster (DLT trust patterns). Diese Vertrauensmuster werden anhand einer Taxonomie klassifiziert, die hilft, ihre vertrauensfördernden Fähigkeiten zu identifizieren. Eine Reihe von verschiedenen Evaluationsmethoden bewertet den Nutzen der eingeführten Design-Science-Artefakte. Die Evaluierung zeigt, dass alle drei Beiträge den Status eines minimal brauchbaren Artefakts erreicht haben (minimal viable artifact). Somit fördern die Ergebnisse ein tiefes Verständnis von Vertrauen in Geschäftsprozessen und wie Distributed-Ledger-Technologien als Werkzeug zur Abschwächung von Vertrauensproblemen genutzt werden können.

Clinical trials on the use of COVID-19 convalescent plasma remain inconclusive. While data on safety is increasingly available, evidence for efficacy is still sparse. Subgroup analyses hint to a dose-response relationship between convalescent plasma neutralizing antibody levels and mortality. In particular, patients with primary and secondary antibody deficiency might benefit from this approach. However, testing of neutralizing antibodies is limited to specialized biosafety level 3 laboratories and is a time- and labor-intense procedure. In this single center study of 206 COVID-19 convalescent patients, clinical data, results of commercially available ELISA testing of SARS-CoV-2 spike-IgG and -IgA, and levels of neutralizing antibodies, determined by plaque reduction neutralization testing (PRNT), were analyzed. At a medium time point of 58 days after symptom onset, only 12.6% of potential plasma donors showed high levels of neutralizing antibodies (PRNT50 >= 1:320). Multivariable proportional odds logistic regression analysis revealed need for hospitalization due to COVID-19 (odds ratio 6.87; p-value 0.0004) and fever (odds ratio 3.00; p-value 0.0001) as leading factors affecting levels of SARS-CoV-2 neutralizing antibody titers in convalescent plasma donors. Using penalized estimation, a predictive proportional odds logistic regression model including the most important variables hospitalization, fever, age, sex, and anosmia or dysgeusia was developed. The predictive discrimination for PRNT50 >= 1:320 was reasonably good with AUC: 0.86 (with 95% CI: 0.79-0.92). Combining clinical and ELISA-based pre-screening, assessment of neutralizing antibodies could be spared in 75% of potential donors with a maximal loss of 10% of true positives (PRNT50 >= 1:320).

Die vorliegende Arbeit befasst sich mit den CO2-Emissionen eines Dezernats der TU Darmstadt im Jahr 2019. Hierzu wird das Greenhouse Gas Protocol verwendet. In die Bilanzierung fließen verschiedene Emissionsfaktoren, wie beispielsweise der Verbrauch von Strom und Wärme, der Pendelweg der Mitarbeitende sowie Dienstreisen und Verbrauch von Papier und IT-Geräten ein. Um die Emissionsfaktoren präzise zu identifizieren werden Umfragen zu der Arbeitsweise und der Mobilität innerhalb des Dezernats V an alle Mitarbeitende versendet und durchgeführt. Durch Mailkontakt mit den zuständigen Mitarbeitenden des Dezernats V und einigen Vor-Ort-Begehungen können weitere Emissionsfaktoren ermittelt werden. Fehlende Informationen werden abschließend so genau wie möglich abgeschätzt. Mit Hilfe einer Korrelationsmatrix werden aus den Umfrageergebnissen Abhängigkeiten identifiziert. Durch entsprechende Analysen können zudem Key Performance Indicator bestimmt werden. Diese können als Grundlage für die effiziente Erstellung zukünftiger CO2-Bilanzen genutzt werden. Im Jahr 2019 hat das gesamte Dezernat im Durchschnitt 195,751 kg CO2 eq ausgestoßen. Das Pendeln der Mitarbeitenden stellt mit 77,187 kg CO2 eq den anteilsmäßig größten Emissionsausstoß dar. An zweiter und dritter Stelle stehen die Emissionen aus Fernwärme mit 46,314 kg CO2 eq und Strom mit 39,513 kg CO2 eq. Der zweite Aspekt dieser Arbeit beschäftigt sich mit potenziellen Maßnahmen, um die CO2-Emissionen am Dezernat V zu senken. Die Mitarbeitenden des Dezernats V können in einer zweiten Umfrage die vorgestellten Maßnahmen bezüglich ihrer Umsetzbarkeit im Arbeitsalltag am Dezernat bewerten.

Supplemental document

Digital micromirror devices (DMDs) are spatial light modulators that employ the electro-mechanical movement of miniaturized mirrors to steer and thus modulate the light reflected off a mirror array. Their wide availability, low cost and high speed make them a popular choice both in consumer electronics such as video projectors, and scientific applications such as microscopy. High-end fluorescence microscopy systems typically employ laser light sources, which by their nature provide coherent excitation light. In super-resolution microscopy applications that use light modulation, most notably structured illumination microscopy (SIM), the coherent nature of the excitation light becomes a requirement to achieve optimal interference pattern contrast. The universal combination of DMDs and coherent light sources, especially when working with multiple different wavelengths, is unfortunately not straight forward. The substructure of the tilted micromirror array gives rise to a blazed grating, which has to be understood and which must be taken into account when designing a DMD-based illumination system. Here, we present a set of simulation frameworks that explore the use of DMDs in conjunction with coherent light sources, motivated by their application in SIM, but which are generalizable to other light patterning applications. This framework provides all the tools to explore and compute DMD-based diffraction effects and to simulate possible system alignment configurations computationally, which simplifies the system design process and provides guidance for setting up DMD-based microscopes.This article is part of the Theo Murphy meeting ‘Simposium (part 1)’.

Structured illumination microscopy (SIM) is a fast and gentle super-resolution fluorescence imaging technique, featuring live-cell compatible excitation light levels and high imaging speeds. To achieve SIM, spatial modulation of the fluorescence excitation light is employed. This is typically achieved by interfering coherent laser beams in the sample plane, which are often created by spatial light modulators (SLMs). Digital micromirror devices (DMDs) are a form of SLMs with certain advantages, such as high speed, low cost and wide availability, which present certain hurdles in their implementation, mainly the blazed grating effect caused by the jagged surface structure of the tilted mirrors. Recent works have studied this effect through modelling, simulations and experiments, and laid out possible implementations of multi-color SIM imaging based on DMDs. Here, we present an implementation of a dual-color DMD based SIM microscope using temperature-controlled wavelength matching. By carefully controlling the output wavelength of a diode laser by temperature, we can tune two laser wavelengths in such a way that no opto-mechanical realignment of the SIM setup is necessary when switching between both wavelengths. This reduces system complexity and increases imaging speed. With measurements on nano-bead reference samples, as well as the actin skeleton and membrane of fixed U2OS cells, we demonstrate the capabilities of the setup. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Detailed knowledge of the molecular biology of SARS-CoV-2 infection is crucial for understanding of viral replication, host responses and disease progression. Here, we report gene expression profiles of three SARS-CoV and SARS-CoV-2 infected human cell lines. SARS-CoV-2 elicited an approximately two-fold higher stimulation of the innate immune response compared to SARS-CoV in the human epithelial cell line Calu-3, including induction of miRNA-155. Single-cell RNA sequencing of infected cells showed that genes induced by virus infections were broadly upregulated, whereas interferon beta/lambda genes an pro-inflammatory cytokines such as IL-6 were expressed only in small subsets of infected cells. Temporal analysis suggested that transcriptional activities of interferon regulatory factors precede those of nuclear factor κB. Lastly, we identified heat shock protein 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 activity resulted in a reduction of viral replication and pro-inflammatory cytokine expression in primary human airway epithelial cells., Graphical Abstract

The coronavirus disease 2019 (COVID-19) pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is an ongoing global health threat with more than two million infected people since its emergence in late 2019. Detailed knowledge of the molecular biology of the infection is indispensable for understanding of the viral replication, host responses, and disease progression. We provide gene expression profiles of SARS-CoV and SARS-CoV-2 infections in three human cell lines (H1299, Caco-2 and Calu-3 cells), using bulk and single-cell transcriptomics. Small RNA profiling showed strong expression of the immunity and inflammation-associated microRNA miRNA-155 upon infection with both viruses. SARS-CoV-2 elicited approximately two-fold higher stimulation of the interferon response compared to SARS-CoV in the permissive human epithelial cell line Calu-3, and induction of cytokines such as CXCL10 or IL6. Single cell RNA sequencing data showed that canonical interferon stimulated genes such as IFIT2 or OAS2 were broadly induced, whereas interferon beta (IFNB1) and lambda (IFNL1-4) were expressed only in a subset of infected cells. In addition, temporal resolution of transcriptional responses suggested interferon regulatory factors (IRFs) activities precede that of nuclear factor-κB (NF-κB). Lastly, we identified heat shock protein 90 (HSP90) as a protein relevant for the infection. Inhibition of the HSP90 charperone activity by Tanespimycin/17-N-allylamino-17-demethoxygeldanamycin (17-AAG) resulted in a reduction of viral replication, and of TNF and IL1B mRNA levels. In summary, our study established in vitro cell culture models to study SARS-CoV-2 infection and identified HSP90 protein as potential drug target for therapeutic intervention of SARS-CoV-2 infection.