Electrochemical and ESR study of 5-nitrofuryl-containing thiosemicarbazones antiprotozoal drugs

Cyclic voltammetry and electron spin resonance (ESR) techniques were used in the investigation of several potential antiprotozoal thiosemicarbazones nitrofurane derivatives. A self-protonation process involving the protonation of the nitro group due to the presence of an acidic proton in the thiosemicarbazone moiety was observed in the first step of a CEE(rev) reduction mechanism of these derivatives. ESR spectra of the free radicals obtained by electrolytic reduction were characterized and analyzed. AM1 methodology was used to obtain the optimized geometries and UB3LYP calculations were performed to obtain the theoretical hyperfine coupling constants. The theoretical study exhibited an unusual assignment of the spin densities showing a free radical centered in the thiosemicarbazone moiety rather than the nitro which are in agreement with the experimental hyperfine pattern.     

Fixed point free involutions on Riemann surfaces

In this paper, involutions without fixed points on hyperbolic closed Riemann surface are discussed. For an orientable surface X of even genus with an arbitrary Riemannian metric d admitting an involution τ, it is known that min _p∈X d(p, τ(p)) is bounded by a constant which depends on the area of X. The corresponding claim is proved to be false in odd genus, and the optimal constant for hyperbolic Riemann surfaces is calculated in genus 2. The author was supported in part by the Swiss National Science Foundation grants 20-68181.02 and PBEL2-106180.     

Trace-matrix separations for high-purity chromium,molybdenum and tungsten with cellulose collectors

Trace metals (20 elements) in high-purity chromium, molybdenum and tungsten are collected and preconcentrated by precipitation and adsorption on cellulose collectors. The compound methods allow the application of AAS and ICP-AES as determination methods for the production control of highly pure refractory metals under routine conditions.Presented in part at the 1989 European Winter Conference on Plasma Spectrochemistry, Reutte, Austria     

A family of rotating disks as sources of the Kerr metric

A method of constructing a family of regular rotating disks as sources of the Kerr metric is discussed. The algebraic type of the energy-momentum tensor is analyzed, and it is found that none of the disks satisfies the dominant energy condition and, in some cases, even the weak energy condition is violated. Therefore, if the constructed family includes the totality of sources for the Kerr metric with a disk-like topology, then any physically satisfactory source will not have a disk structure.     

Zur Kenntnis des Lariciresinols

Ohne ZusammenfassungHerrn Prof. M. Bamberger, sage ich für seine freundliche Unterstützung bei Ausführung dieser Arbeit meinen aufrichtigsten Dank.     

Neuroprotection from NMDA excitotoxic lesion by Cu/Zn superoxide dismutase gene delivery to the postnatal rat brain by a modular protein vector

Background  

Superoxide mediated oxidative stress is a key neuropathologic mechanism in acute central nervous system injuries. We have analyzed the neuroprotective efficacy of the transient overexpression of antioxidant enzyme Cu/Zn Superoxide dismutase (SOD) after excitotoxic injury to the immature rat brain by using a recently constructed modular protein vector for non-viral gene delivery termed NLSCt. For this purpose, animals were injected with the NLSCt vector carrying the Cu/Zn SOD or the control GFP transgenes 2 hours after intracortical N-methyl-D-aspartate (NMDA) administration, and daily functional evaluation was performed. Moreover, 3 days after, lesion volume, neuronal degeneration and nitrotyrosine immunoreactivity were evaluated.     

Toward a Comparison of Classical and New Privacy Mechanism

In the last decades, the development of interconnectivity, pervasive systems, citizen sensors, and Big Data technologies allowed us to gather many data from different sources worldwide. This phenomenon has raised privacy concerns around the globe, compelling states to enforce data protection laws. In parallel, privacy-enhancing techniques have emerged to meet regulation requirements allowing companies and researchers to exploit individual data in a privacy-aware way. Thus, data curators need to find the most suitable algorithms to meet a required trade-off between utility and privacy. This crucial task could take a lot of time since there is a lack of benchmarks on privacy techniques. To fill this gap, we compare classical approaches of privacy techniques like Statistical Disclosure Control and Differential Privacy techniques to more recent techniques such as Generative Adversarial Networks and Machine Learning Copies using an entire commercial database in the current effort. The obtained results allow us to show the evolution of privacy techniques and depict new uses of the privacy-aware Machine Learning techniques.