Influence of Long-Distance Bicycle Riding on Serum/Urinary Biomarkers of Prostate Cancer

Herein, we present a study focused on the determination of the influence of long-distance (53 km) bicycle riding on levels of chosen biochemical urinary and serum prostate cancer (PCa) biomarkers total prostate-specific antigen (tPSA), free PSA (fPSA) and sarcosine. Fourteen healthy participants with no evidence of prostate diseases, in the age range from 49–57 years with a median of 52 years, underwent physical exercise (mean race time of 150 ± 20 min, elevation increase of 472 m) and pre- and post-ride blood/urine sampling. It was found that bicycle riding resulted in elevated serum uric acid (p = 0.001, median 271.76 vs. 308.44 µmol/L pre- and post-ride, respectively), lactate (p = 0.01, median 2.98 vs. 4.8 mmol/L) and C-reactive protein (p = 0.01, 0.0–0.01 mg/L). It is noteworthy that our work supports the studies demonstrating an increased PSA after mechanical manipulation of the prostate. The subjects exhibited either significantly higher post-ride tPSA (p = 0.002, median 0.69 vs. 1.1 ng/mL pre- and post-ride, respectively) and fPSA (p = 0.028, median 0.25 vs. 0.35 ng/mL). Contrary to that, sarcosine levels were not significantly affected by physical exercise (p = 0.20, median 1.64 vs. 1.92 µmol/mL for serum sarcosine, and p = 0.15, median 0.02 µmol/mmol of creatinine vs. 0.01 µmol/mmol of creatinine for urinary sarcosine). Taken together, our pilot study provides the first evidence that the potential biomarker of PCa—sarcosine does not have a drawback by means of a bicycle riding-induced false positivity, as was shown in the case of PSA.     

A roadmap to understand battery performance in electric and hybrid vehicle operation

This work attempts to bridge laboratory and real-life battery testing data with a comprehensive analysis to provide a coherent approach for a realistic model to simulate battery performance, including life prediction. From electric vehicle field-testing results, we explain how to handle real-life data through driving cycle analysis to establish a scheme of “building blocks” that can be validated by test results obtained in the laboratory. We also show that a simple battery model can be built upon laboratory test data and validated by real-life duty cycles, therefore deriving a more realistic understanding and prediction of battery performance.     

Learning data discretization via convex optimization

Discretization of continuous input functions into piecewise constant or piecewise linear approximations is needed in many mathematical modeling problems. It has been shown that choosing the length of the piecewise segments adaptively based on data samples leads to improved accuracy of the subsequent processing such as classification. Traditional approaches are often tied to a particular classification model which results in local greedy optimization of a criterion function. This paper proposes a technique for learning the discretization parameters along with the parameters of a decision function in a convex optimization of the true objective. The general formulation is applicable to a wide range of learning problems. Empirical evaluation demonstrates that the proposed convex algorithms yield models with fewer number of parameters with comparable or better accuracy than the existing methods.     

A paradigm change in assembling OH functionalities on metal centers

The synthesis of terminal hydroxide containing Group 13 and 14 metals [LAl(OH)(2)], LAlMeOH, [{LAl(OH)}(2)(mu-O)], LAl(OH)-O-AlLL', LGeOH, and [TsiSn(O)OH](3) [Tsi = (Me(3)Si)(3)C] has been accomplished using innovative synthetic methodologies. All of these compounds have been structurally characterized, both in solution as well as in the solid state. The utility of such metal hydroxides [{LAl(OH)}(2)(mu-O)] and LAlMeOH [L = HC{(CMe)(2,6-i-Pr(2)C(6)H(3)N)}(2)] in the preparation of homo- and heterometallic compounds has been demonstrated. It has also been possible to prepare unusual terminal SH- and SeH-containing compounds LAl(SH)(2), LAl(SeH)(2), and LAl(SeH)-Se-Al(SeH)L using dihydride LAlH(2) as a starting material. The synthesis, structure, and potential utility of these compounds is discussed.     

Quantitative Analyse der Heterogenität des Bruchvorganges von kohlenstoffarmem Stahl bei Kerbschlagbiegeversuchen

Aufnahme von Kerbschlagzähigkeit-Temperatur-Kurven eines unberuhigten Stahles mit 0,04% C für drei Zustände mit unterschiedlicher Korngröße. Elektronenfraktographische Analyse der Bruchflächen. Abhängigkeit der kennzeichnenden Bruchgefügearten von der Temperatur. Möglichkeiten der fraktographischen Analyse für die Beschreibung des Bruchverhaltens.