Coordinated AMBER and MIDI observations of the Mira variable RR Aql

We have used near- and mid-infrared interferometry to investigate the pulsating atmosphere and the circumstellar environment of the Mira variable RR Aql. Observations were taken with the VLTI/AMBER (near infrared) and the VLTI/MIDI (mid infrared) instruments. We have obtained a total of 15 MIDI epochs between Apr 9, 2004 and Jul 28, 2007 covering 4 pulsation cycles and one AMBER epoch on Sep 9, 2006 at phase 2.82. This work is also part of an ongoing project of joint VLTI and VLBA observations to study the connection between stellar pulsation and the mass loss process. Here we present a comparison of the AMBER visibility data to a simple uniform disk model as well as to predictions by recent self-excited dynamic model atmospheres. The best fitting photospheric angular diameter of the model atmosphere at phase 2.82 is 9.9 +/- 2.4 mas.Comment: 4 pages, 3 figures, to appear in Proc. of Cool Stars 1

REACTION TIME IN TAEKWONDO

The purpose of the study was to find out if taekwondo players competing on an international level have faster reactions than recreational taekwondo players or sports students. We measured three different time intervals. The time measurements started with the flashing of a light diode and ended respectively with the first visible movement of the hip, the shoulder or the foot. Differences were found depending on the skill level, age and gender with the taekwondo players competing on an international level showing significant faster reactions

REACTION AND PERFORMANCE TIME OF TAEKWONDO TOP-ATHLETES DEMONSTRATING THE BALDUNG-CHAGI

The purpose of this study was to investigate two factors for success in taekwondo competition, the simple reaction time (RT) - beginning with an external signal and ending with a shoulder, hip or ankle movement – and the performance time (PT) – starting of the Baldung-chagi till hitting the target. Subjects were the top 9 athletes (6 ♂, 3 ♀) from the German National Team. Movements were recorded by 3 infrared cameras of LUKOtronic active marker Motion Capturing System. Seven markers were used, five on the subject (ankle, heel, hip, shoulder, wrist of the kicking side), one trigger marker at the floor, one at the hand-mitt. The average value for the ankle RT is 0.34 sec., 0.26 sec. for hip RT, 0.23 sec. for shoulder RT and 0.31 sec, for PT. A high ankle RT variation, in the range of 0.26 to 0.54 sec, indicates that reducing this variation though training arrangements could improves the probability for success

A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment

Background: Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. Results: To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers. Moreover, we modelled 15 different chemotherapeutic drugs by estimating their bone marrow toxicity. Taking into account different growth-factor schedules, this adds up to 33 different chemotherapy regimens explained by the model. Conclusions: We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis and erythropoiesis under combined chemotherapy, G-CSF, and EPO applications. We demonstrate how it can be used to make predictions regarding haematotoxicity of yet untested chemotherapy and growth-factor schedules.:Background; Methods; Results; Model predictions; Discussion; Conclusion

On the Parametrization of Epidemiologic Models: Lessons from Modelling COVID-19 Epidemic

Numerous prediction models of SARS-CoV-2 pandemic were proposed in the past. Unknown parameters of these models are often estimated based on observational data. However, lag in case-reporting, changing testing policy or incompleteness of data lead to biased estimates. Moreover, parametrization is time-dependent due to changing age-structures, emerging virus variants, non-pharmaceutical interventions, and vaccination programs. To cover these aspects, we propose a principled approach to parametrize a SIR-type epidemiologic model by embedding it as a hidden layer into an input-output non-linear dynamical system (IO-NLDS). Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. This includes data issues such as known delays or biases in reporting. We estimate model parameters including their time-dependence by a Bayesian knowledge synthesis process considering parameter ranges derived from external studies as prior information. We applied this approach on a specific SIR-type model and data of Germany and Saxony demonstrating good prediction performances. Our approach can estimate and compare the relative effectiveness of non-pharmaceutical interventions and provide scenarios of the future course of the epidemic under specified conditions. It can be translated to other data sets, i.e., other countries and other SIR-type models