On the avoidance of crossing of singular values in the evolving factor analysis

Evolving factor analysis (EFA) investigates the evolution of the singular values of matrices formed by a series of measured spectra, typically, resulting from the spectral observation of an ongoing chemical process. In the original EFA, the logarithms of the singular values are plotted for submatrices that include an increasing number of spectra. A typical observation in these plots is that pairs of trajectories of the singular values are on a collision course, but finally, the curves seem to repel each other and then run in different directions. For parameter-dependent square matrices, such a behaviour is known for the eigenvalues under the keyword of an avoidance of crossing. Here, we adjust the explanation of this avoidance of crossing to the curves of singular values of EFA. Further, a condition is studied that breaks this avoidance of crossing. We demonstrate that the understanding of this noncrossing allows us to design model data sets with a predictable crossing behaviour. © 2020 John Wiley & Sons, Ltd

Influence of drugs and comorbidity on serum potassium in 15 000 consecutive hospital admissions

Background. Drug trials often exclude subjects with relevant comorbidity or comedication. Nevertheless, after approval, these drugs will be prescribed to a much broader collective. Our goal was to quantify the impact of drugs and comorbidity on serum potassium in unselected patients admitted to the hospital. Methods. This was a retrospective pharmacoepidemiologic study in 15 000 consecutive patients admitted to the medical department of the Kantonsspital St. Gallen, a 700-bed tertiary hospital in eastern Switzerland. Patients with ‘haemolytic' plasma and patients on dialysis or with an estimated glomerular filtration rate (GFR) <10 mL/min/1.73 m2 were excluded. For the remaining 14 146 patients, drug history on admission, age, sex, body weight, physical findings, comorbidity (ICD-10 diagnoses) and laboratory information (potassium and creatinine) were extracted from electronic sources. Results. Estimated GFR was the strongest predictor of serum potassium (P < 0.0001). Angiotensin-converting enzyme inhibitors, cyclosporine, loop diuretics and potassium-sparing diuretics all showed a significant effect modification with decreasing GFR (P < 0.001). Similarly, in patients with liver cirrhosis a significantly stronger effect on potassium was found for angiotensin receptor blockers, betablockers and loop diuretics (P < 0.01). Several significant drug-drug interactions were identified. Diabetes, male sex, older age, lower blood pressure and higher body weight were all independently associated with higher serum potassium levels (P < 0.001). The model explained 14% of the variation of serum potassium. Conclusions. The effects of various drugs on serum potassium are highly influenced by comorbidity and comedication. Although the presented model cannot be used to predict potassium in individual patients, we demonstrate that clinical databases could evolve as a powerful tool for industry-independent analysis of postmarketing drug safet

Protonation Constants and Thermodynamic Properties of Amino Acid Salts for CO2 Capture at High Temperatures

Amino acid salts have greater potential for CO2 capture at high temperatures than typical amine-based absorbents because of their low volatility, high absorption rate, and high oxidative stability. The protonation constant (pKa) of an amino acid salt is crucial for CO2 capture, as it decreases with increasing absorption temperature. However, published pKa values of amino acid salts have usually been determined at ambient temperatures. In this study, the pKa values of 11 amino acid salts were determined in the temperature range of 298–353 K using a potentiometric titration method. The standard-state molar enthalpies (ΔHm0) and entropies (ΔSm0) of the protonation reactions were also determined by the van’t Hoff equation. It was found that sarcosine can maintain a higher pKa than the other amino acids studied at high temperatures. We also found that the CO2 solubilities and overall mass-transfer coefficients of 5 m′ sarcosinate (moles of sarcosine per kilogram of solution) at 333–353 K are higher than those of 30% MEA at 313–353 K. These results show that some possible benefits can be produced from the use of sarcosine as a fast solvent for CO2 absorption at high temperatures. However, the pronotation reaction of sarcosine is the least exothermic among those of all amino acids studied. This could lead to a high regeneration energy consumption in the sarcosinate-based CO2 capture proces

Rotation and massive close binary evolution

We review the role of rotation in massive close binary systems. Rotation has been advocated as an essential ingredient in massive single star models. However, rotation clearly is most important in massive binaries where one star accretes matter from a close companion, as the resulting spin-up drives the accretor towards critical rotation. Here, we explore our understanding of this process, and its observable consequences. When accounting for these consequences, the question remains whether rotational effects in massive single stars are still needed to explain the observations.Comment: invited review for Proceedings of IAU-Symp. 250 on Massive Stars as Cosmic Engines, F. Bresolin, P. Crowther & J. Puls, ed

Carbonic anhydrase activity of dinuclear CuII complexes with patellamide model ligands

The dicopper(ii) complexes of six pseudo-octapeptides, synthetic analogues of ascidiacyclamide and the patellamides, found in ascidians of the Pacific and Indian Oceans, are shown to be efficient carbonic anhydrase model complexes with k up to 7.3 × 10 s (uncatalyzed: 3.7 × 10 s; enzyme-catalyzed: 2 × 10 -1.4 × 10 s) and a turnover number (TON) of at least 1700, limited only by the experimental conditions used. So far, no copper-based natural carbonic anhydrases are known, no faster model systems have been described and the biological role of the patellamide macrocycles is so far unknown. The observed CO hydration rates depend on the configuration of the isopropyl side chains of the pseudo-octapeptide scaffold, and the naturally observed R*,S*, R*,S* geometry is shown to lead to more efficient catalysts than the S*,S*,S*,S* isomers. The catalytic efficiency also depends on the heterocyclic donor groups of the pseudo-octapeptides. Interestingly, the dicopper(ii) complex of the ligand with four imidazole groups is a more efficient catalyst than that of the close analogue of ascidiacyclamide with two thiazole and two oxazoline rings. The experimental observations indicate that the nucleophilic attack of a Cu- coordinated hydroxide at the CO carbon center is rate determining, i.e. formation of the catalyst-CO adduct and release of carbonate/bicarbonate are relatively fast processes

Model-based analysis for kinetic and equilibrium investigations

Equilibrium and kinetic data usually can be described quantitatively by a chemical model that is based on the law of mass action. In such instances parameters of interest like rate and equilibrium constants and, depending on the nature of the data, also spectral information can be determined by model-based analysis of the appropriate data sets. In this contribution the essential aspects of the complete process are discussed, these include data acquisition, modelling of the concentration profiles and the actual fitting algorithms which are identical for both types of investigation. An overview of recent developments like globalisation of the analysis and attempts to analyse industrially relevant data incorporating corrections for non-ideal behaviour are also given

Cyber Security Integration Engine

Every company that is working with confidential data needs to fulfill certain regulations. Especially in the financial sector these requirements are crucial to a company's success. For small businesses this can become a severe problem. To help those small companies to fulfill these requirements we want to provide a prototype of an extensible software that will take care of such tasks. The goal is to get a zero-configuration security box that is easily extensible and able to scale. It should collect necessary data and be able to determine a baseline on what is normal behavior on a client's network. To get started we want to be able to keep a list of machines communicating on the network. We will split the topic into three separate concerns. For the communication between the subsystems we will use a messaging system. Every information exchange goes through this system using messages. The probes are responsible for collecting potentially interesting information about its environment. This could be network metadata or other kinds of information. The probe then publishes the gathered information into the messaging system. Agents subscribe to messages they are capable of analyzing. Based on these messages they investigate and publish their acquired information back to the messaging system, so any other agent can reuse this information. In our lab environment we were able to collect and pass network activity data between multiple participants within our framework. We implemented a network probe and an agent that could detect an unknown device based on its mac address. We implemented this using two different messaging systems and compared these two in terms of implementation complexity and message throughput performance. We found that one messaging system is over 10 times faster than the other and had much better tooling

SwissSki - Interaktive Skisprung-Trainingsanalyse

*Ausgangslage* Swiss-Ski möchte ihre Skisprung-Trainings genauer auswerten. Sie haben dazu ein GPS-Messsystem in Auftrag gegeben, welches im Rahmen einer Bachelorarbeit der HSR Abteilung Elektrotechnik im Jahr 2017 umgesetzt wurde. Die Daten, die mit der Lösung der Vorarbeit gesammelt werden, sollen nun für die Trainer und Athleten dargestellt werden können. *Vorgehen und Technologien* Im ersten Schritt wurden die Anforderungen aufgenommen und Lösungen evaluiert. Danach wurden die Lösungsbestandteile in einem agilen Prozess implementiert. Das Frontend wurde als Angular Webapplikation umgesetzt. Das Backend wurde mit Django realisiert. Dieses dient als API-Schnittstelle. Die API wurde gemäss dem OpenAPI Standard mit Swagger.io dokumentiert. Das Design des Frontends folgt den Regeln von Material Design, welches häufig bei Android Geräten anzutreffen ist. Die Darstellung einer Sprungtrajektorie wird dreidimensional mit Three.js und zweidimensional mit Chart.js umgesetzt. *Ergebnis* Im Rahmen der Bachelorarbeit ist eine Plattform entstanden, welche für die Trainer und Athleten von Swiss-Ski auf ihrem Server produktiv verfügbar ist. Es lassen sich Trainings, Athleten, Trainer und Sprünge verwalten und anzeigen. Das Dashboard ermöglicht es, den Sprung gleichzeitig in einem 2D Graph, einem 3D Graph und mit einer Videoaufnahme zu verfolgen. Ausserdem können mehrere Sprünge miteinander verglichen werden

Multivariate linear regression with missing values

This contribution presents and discusses an efficient algorithm for multivariate linear regression analysis of data sets with missing values. The algorithm is based on the insight that multivariate linear regression can be formulated as a set of individual univariate linear regressions. All available information is used and the calculations are explicit. The only restriction is that the independent variable matrix has to be non-singular. There is no need for imputation of interpolated or otherwise guessed values which require subsequent iterative refinement