Mapping technologies to business models : An application to clean technologies and entrepreneurship

Theory suggests that new market entrants play a special role for the creation of new technological pathways required for the development and diffusion of more sustainable forms of production, consumption, mobility and housing. Unconstrained by past technological investments, entrants can introduce more radical environmental innovations than incumbent firms whose past R&D decisions make them locked into path-dependent trajectories of outdated technologies. Yet, little research exists which provides empirical evidence on new ventures' role in the technological transition towards decarbonization and dematerialization. This is mainly because patenting is rare among start-ups and also no historical track record about their R&D investments exists, both data sources commonly used to determine a company’s technological footprint. To enable the identification of clean technology-oriented market entrants and to better understand their role as adopters and innovators for sustainable market solutions, this paper presents a framework that systematically maps new ventures’ business models to a set of well-defined clean technologies. For this purpose, the framework leverages textual descriptions of new entrants’ business summaries that are typically available upon business registration and allow for a good indication of their technological orientation. Furthermore, the framework uses textual information from patenting activities of established innovators to model semantic representations of technologies. Mapping company and technology descriptions into a common vector space enables the derivation of a fine-granular measure of entrants’ technological orientation. Applying the framework to a survey of German start-up firms suggests that clean technology-oriented market entrants act as accelerators of technical change: both by virtue of their existing products and services and through a high propensity to introduce additional environmental innovation

The COVID-19 insolvency gap: First-round effects of policy responses on SMEs

COVID-19 placed a special role to fiscal policy in rescuing companies short of liquidity from insolvency. In the first months of the crisis, SMEs as the backbone of Europe’s real economy benefited from large and mainly indiscriminate aid measures. Avoiding business failures in a whatever it takes fashion contrasts, however, with the cleansing mechanism of economic crises: a mechanism which forces unviable firms out of the market, thereby reallocating resources efficiently. By focusing on firms’ pre-crisis financial standing, we estimate the extent to which the policy response induced an insolvency gap and analyze whether the gap is characterized by firms which had already struggled before the pandemic. With the policy measures being focused on smaller firms, we also examine whether this insolvency gap differs with respect to firm size. Based on credit rating and insolvency data for the near universe of actively rated German firms, our results suggest that the policy reponse to COVID-19 has triggered a backlog of insolvencies in Germany that is particularly pronounced among financially weak, small firms, having potential long term implications on economic recovery

High-sensitivity cardiac troponin T and copeptin assays to improve diagnostic accuracy of exercise stress test in patients with suspected coronary artery disease

Background: The average diagnostic sensitivity of exercise stress tests (ESTs) is lower than that of other non-invasive cardiac stress tests. The aim of the study was to examine whether high-sensitivity cardiac troponin T (hs-cTnT) or copeptin concentrations rise in response to inducible myocardial ischaemia and may improve the diagnostic accuracy of ESTs. Methods and results: An EST was performed stepwise on a bicycle ergometer by 383 consecutive patients with suspected or progression of coronary artery disease (CAD). In addition venous blood samples for measurement of hs-cTnT and copeptin were collected prior to EST, at peak exercise, and 4 h after EST. Coronary angiography was assessed for all patients. Patients with significant CAD (n=224) were more likely to be male and older compared to patients with non-significant CAD (n=169). Positive EST was documented in 125 (55.8%) patients with significant CAD and in 69 (43.4%) patients with non-significant CAD. Copeptin and hs-cTnT concentrations at baseline were higher in patients with significant CAD (copeptin: 10.8 pmol/l (interquartile range (IQR) 8.1–15.6) vs 9.4 pmol/l (IQR 7.1–13.9); p=0.04; hs-cTnT: 3.0 ng/l (IQR <3.0–5.4) vs <3.0 ng/l (IQR <3.0); p=0.006). Hs-cTnT improved sensitivity (61.6% vs 55.8%), specificity (67.7% vs 56.6%) and the positive predictive value (PPV) (72.3% vs 64.4%) and negative (55.2% vs 47.6%) predictive value (NPV) of EST. Copeptin could not improve sensitivity (55.4% vs 55.8%) and reduced specificity, PPV and NPV. Conclusions: The measurement of hs-cTnT during EST improves sensitivity, specificity, and positive and negative predictive values. In contrast, measurement of copeptin does not improve diagnostic sensitivity and reduces specificity

Corporate insolvencies in times of COVID-19

Die wirtschaftlichen Folgen der Corona-Pandemie waren in der öffentlichen Diskussion ein wichtiges Thema. In fast allen Ländern wurden Geschäfte und Betriebe geschlossen und die Mobilität stark eingeschränkt, um die Ausbreitung des Virus einzudämmen. Angesichts dieses zwangsweisen Stopps vieler wirtschaftlicher Aktivitäten haben die Regierungen eine Vielzahl von Instrumenten initiiert, um die negativen wirtschaftlichen Auswirkungen der Pandemie zu bekämpfen. Beispielsweise in Deutschland hat die Bundesregierung als Reaktion auf die Wirtschaftskrise und die Stilllegungsmaßnahmen bislang nie dagewesene Hilfsmaßnahmen für Unternehmen gewährt. Diese Maßnahmen werden vom Bundesfinanzministerium als das "größte Hilfspaket in der Geschichte der Bundesrepublik Deutschland" bezeichnet. Neben verschiedenen Instrumenten der Liquiditätsvorsorge hat die Regierung im Jahr 2020 auch eine befristete Änderung der Insolvenzordnung durch das Bundesministerium der Justiz und für Verbraucherschutz beschlossen. Diese Novelle beinhaltet eine vorübergehende Aussetzung der gesetzlichen Insolvenzantragspflicht und soll verhindern, dass Unternehmen durch die regulären Insolvenzregeln aus dem Markt gedrängt werden. Tatsächlich hätten diese Regeln die Aufnahme zusätzlicher staatlich gestützter Kredite für Unternehmen vereiteln können und/oder staatliche Banken für die Unterstützung insolventer Unternehmen verantwortlich machen können. Nun mehren sich die Stimmen, die hinterfragen, ob die temporären Änderungen im Insolvenzrecht noch angebracht sind. Kritiker verweisen auf die Gefahr der Entstehung von Zombie-Unternehmen, die im Grunde langfristig nicht überlebensfähig sind, weil ihr Geschäftsmodell etwa schon vor der Krise nicht richtig funktioniert hat oder sich aufgrund der krisenbedingten Veränderungen absehbar nach der Krise als nicht tragfähig erweisen werde. Andere argumentieren, dass es noch zu früh sei, um darauf zu schließen, dass viele Unternehmen nach der Schließung wieder auf die Beine kommen würden und daher die Ausnahmen vom Insolvenzrecht verlängert werden sollten. Welche der beiden Ansichten richtig oder falsch ist, lässt sich derzeit empirisch kaum belegen, da die Krise noch andauert. Ziel dieser englischsprachigen ZEW-Kurzexpertise ist es, Fakten zu Firmen und Unternehmern zu liefern, die trotz der Aussetzung der Antragspflicht noch während der Pandemie Insolvenz angemeldet haben. Insofern bieten unsere Analysen ein Referenzszenario für die von vielen Experten und Politikern erwartete Welle von Insolvenzanmeldungen. Aktuelle Statistiken zeigen, dass im ersten Jahr der Pandemie die Zahl der Insolvenzanträge deutlich zurückgegangen ist - genau das Gegenteil von dem, was normalerweise in Wirtschaftskrisen zu beobachten ist. In einem aktuellen Papier zeigen wir, dass gerade Unternehmen mit schlechter Kreditwürdigkeit, deren Rating sich in den Krisenmonaten noch weiter verschlechterte, ein Insolvenzverfahren vermeiden konnten. Angesichts des Auslaufens der Insolvenzrechtsnovelle soll diese Kurzexpertise die Insolvenzentwicklung deutscher Unternehmen durch eine kontinuierliche Aktualisierung der unten stehenden Analysen nachvollziehbar machen. Noch wichtiger ist jedoch, dass sie ein weiteres Licht darauf wirft, wie sich die Muster in den Firmen- und Eigentümermerkmalen insolventer Unternehmen verändert haben, seit COVID-19 die deutsche Wirtschaft getroffen hat. Konkret konzentriert sich die Kurzexpertise sowohl auf Firmen- als auch auf Unternehmermerkmale von Firmen, die vor und nach dem Ausbruch von COVID-19 in Deutschland Insolvenz angemeldet haben

An integrated data framework for policy guidance in times of dynamic economic shocks

Usually, offcial and survey-based statistics guide policy makers in their choice of response instruments to economic crises. However, in an early phase, after a sudden and unforeseen shock has caused incalculable and fast-changing dynamics, data from traditional statistics are only available with non-negligible time delays. This leaves policy makers uncertain about how to most effectively manage their economic countermeasures to support businesses, especially when they need to respond quickly, as in the COVID-19 pandemic. Given this information deficit, we propose a framework that guides policy makers throughout all stages of an unforeseen economic shock by providing timely and reliable data as a basis to make informed decisions. We do so by combining early stage "ad hoc" web analyses, "follow-up" business surveys, and "retrospective" analyses of firm outcomes. A particular focus of our framework is on assessing the early effects of the pandemic, using highly dynamic and largescale data from corporate websites. Most notably, we show that textual references to the coronavirus pandemic published on a large sample of company websites and state-of-the-art text analysis methods allow to capture the heterogeneity of the crisis' effects at a very early stage and entail a leading indication on later movements in firm credit ratings

Rolled-up tubes and cantilevers by releasing SrRuO3-Pr0.7Ca0.3MnO3 nanomembranes

Three-dimensional micro-objects are fabricated by the controlled release of inherently strained SrRuO3/Pr0.7Ca0.3MnO3/SrRuO3 nanometer-sized trilayers from SrTiO3(001) substrates. Freestanding cantilevers and rolled-up microtubes with a diameter of 6 to 8 μm are demonstrated. The etching behavior of the SrRuO3 film is investigated, and a selectivity of 1:9,100 with respect to the SrTiO3 substrate is found. The initial and final strain states of the rolled-up oxide layers are studied by X-ray diffraction on an ensemble of tubes. Relaxation of the sandwiched Pr0.7Ca0.3MnO3 layer towards its bulk lattice parameter is observed as the major driving force for the roll-up of the trilayers. Finally, μ-diffraction experiments reveal that a single object can represent the ensemble proving a good homogeneity of the rolled-up tubes

Pylorus Resection Does Not Reduce Delayed Gastric Emptying After Partial Pancreatoduodenectomy A Blinded Randomized Controlled Trial (PROPP Study, DRKS00004191)

Objectives: The aim of this study was to investigate the effect of pylorus resection on postoperative delayed gastric emptying (DGE) after partial pancreatoduodenectomy (PD). Background: PD is the standard treatment for tumors of the pancreatic head. Preservation of the pylorus has been widely accepted as standard procedure. DGE is a common complication causing impaired oral intake, prolonged hospital stay, and postponed further treatment. Recently, pylorus resection has been shown to reduce DGE. Methods:Patients undergoing PD for any indication at the University of Heidelberg were randomized to either PD with pylorus preservation (PP) or PD with pylorus resection and complete stomach preservation (PR). The primary endpoint was DGE within 30 days according to the International Study Group of Pancreatic Surgery definition. Results: Ninety-five patients were randomized to PP and 93 patients to PR. There were no baseline imbalances between the groups. Overall, 53 of 188 patients (28.2%) developed a DGE (grade: A 15.5%;B 8.8%;C 3.3%). In the PP group 24 of 95 patients (25.3%) and in the PR group 29 of 93 patients (31.2%) developed DGE (odds ratio 1.534, 95% confidence interval 0.788 to 2.987;P = 0.208). Higher BMI, indigestion, and intraabdominal major complications were significant risk factors for DGE. Conclusions: In this randomized controlled trial, pylorus resection during PD did not reduce the incidence or severity of DGE. The development of DGE seems to be multifactorial rather than attributable to pyloric dysfunction alone. Pylorus preservation should therefore remain the standard of care in PD.Trial Registration:German Clinical Trials Register DRKS0000419

Enabling Elements of Simulations Digital Twins and its Applicability for Information Superiority in Defence Domain

The emerging concept of digital twins is the key enabler for modelling and simulations needs of any future-ready entity. Digital twins enable rapid transformation of requirements into capabilities at much lower costs, compared to conventional methods, through enhancement of modularity and scalability. Elements of a modelling and simulations digital twin are discussed in this paper. These capabilities include, but are not limited to, surrogate modelling, optimization, parallelization, high performance computing, cloud architecture design, etc. These concepts are relevant for the integration of modelling and simulations technologies into a single interface digital twin for rapid prototyping and qualification of engineering systems. Use of these emerging technologies leads to significantly less simulation computation time (reduced from hours/days to seconds or even micro-seconds) compared to the conventional methods. Ease-of-collaboration with all stakeholders, reduced testing time, minimal on-site infrastructure requirements are the key cost-reducing advantages found in this study. Applicability of such intelligent and online digital twins for information superiority to enhance cybersecurity and on-board threat assessment of space-based (defence) services is analysed. The use of these synchronized and interoperable capabilities mitigates both reversible and non-reversible physical and cyber threats to defence space infrastructure

Development of a long noncoding RNA-based machine learning model to predict COVID-19 in-hospital mortality

Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.</p