Quantitative relations between corruption and economic factors

We report quantitative relations between corruption level and economic factors, such as country wealth and foreign investment per capita, which are characterized by a power law spanning multiple scales of wealth and investment per capita. These relations hold for diverse countries, and also remain stable over different time periods. We also observe a negative correlation between level of corruption and long-term economic growth. We find similar results for two independent indices of corruption, suggesting that the relation between corruption and wealth does not depend on the specific measure of corruption. The functional relations we report have implications when assessing the relative level of corruption for two countries with comparable wealth, and for quantifying the impact of corruption on economic growth and foreign investment.     

Mass spectrometry in biodefense

Potential agents for biological attacks include both microorganisms and toxins. In mass spectrometry (MS), rapid identification of potential bioagents is achieved by detecting the masses of unique biomarkers, correlated to each agent. Currently, proteins are the most reliable biomarkers for detection and characterization of both microorganisms and toxins, and MS-based proteomics is particularly well suited for biodefense applications. Confident identification of an organism can be achieved by top-down proteomics following identification of individual protein biomarkers from their tandem mass spectra. In bottom-up proteomics, rapid digestion of intact protein biomarkers is again followed by MS/MS to provide unambiguous bioagent identification and characterization. Bioinformatics obviates the need for culturing and rigorous control of experimental variables to create and use MS fingerprint libraries for various classes of bioweapons. For specific applications, MS methods, instruments and algorithms have also been developed for identification based on biomarkers other than proteins and peptides.     

Towards understanding astrophysical effects of nuclear symmetry energy

The European Physical Journal A - The properties of the quantum electrodynamic (QED) vacuum in general, and of the nuclear vacuum (ground) state in particular, are determined by virtual processes...     

Establishing Drug Resistance in Microorganisms by Mass Spectrometry

A rapid method to determine drug resistance in bacteria based on mass spectrometry is presented. In it, a mass spectrum of an intact microorganism grown in drug-containing stable isotope-labeled media is compared with a mass spectrum of the intact microorganism grown in non-labeled media without the drug present. Drug resistance is determined by predicting characteristic mass shifts of one or more microorganism biomarkers using bioinformatics algorithms. Observing such characteristic mass shifts indicates that the microorganism is viable even in the presence of the drug, thus incorporating the isotopic label into characteristic biomarker molecules. The performance of the method is illustrated on the example of intact E. coli, grown in control (unlabeled) and ¹³C-labeled media, and analyzed by MALDI TOF MS. Algorithms for data analysis are presented as well.

Electrodeposition of gold particles on aluminum substrates containing copper

Electrodeposition of adhesive metal films on aluminum is traditionally preceded by the zincate process, which activates the aluminum surface. This paper presents an alternative approach for activation of aluminum by using films containing 99.5% aluminum and 0.5% copper. Aluminum/copper films are made amenable for subsequent electrodeposition by anodization followed by chemical etching of aluminum oxide. The electrodeposition of gold is monitored with electrochemical impedance spectroscopy (EIS). Analysis of EIS data suggests that electrodeposition of gold increases the interfacial capacitance from values typical for electrodes with thin oxide layers to values typical for metal electrodes. Scanning electron microscopy examination of aluminum/copper films following gold electrodeposition shows the presence of gold particles with densities of 10(5)-10(7) particles cm(-2). The relative standard deviation of mean particle diameters is approximately 25%. Evaluation of the micrographs suggests that the electrodeposition occurs by instantaneous nucleation followed by growth of three-dimensional semispherical particles. The gold particles, which are electrically connected to the conductive aluminum/copper film, support a reversible faradaic process for a soluble redox couple. The deposited gold particles are suitable for subsequent metallization of aluminum and fabrication of particle-type films with interesting catalytic, electrical, and optical properties.     

Platinum group metal-free oxygen reduction electrocatalysts used in neutral electrolytes for bioelectrochemical reactor applications

The oxygen reduction reaction is one of the limiting steps in microbial fuel cell performance. M–N–C catalysts (M as transition metal) represent the best compromise of optimal cost, electrocatalytic activity and durability. The Fe-based catalysts were shown to be the best compared with Co-, Mn-, Ni-based catalysts. The addition of the second transition metal such as Mn was shown to increase the selectivity of the reaction and reduce peroxide production. The use of different N–C precursors resulted in diverse surface chemistry that directly affects the performance. Generally, surface chemistry plays a critical role in the electrocatalytic activity. Integration of the catalyst in the air-breathing cathode is also discussed with a performance that is enhanced by: (i) increased catalyst loading; (ii) the addition of graphene to structure.     

Synthesis and contractile activity of substituted 1,2,3,4-tetrahydroisoquinolines

A series of different 1-monosubstituted and 1,1-disubstituted 1,2,3,4-tetrahydro-isoquinolines was synthesized in high yields from different ketoamides. We have developed a convenient method for the synthesis of disubstituted derivatives by interaction of ketoamides with organomagnesium compounds, followed by cyclization in the presence of catalytic amounts of p-toluenesulfonic acid (PTSA). A number of substituents at the C-1 in the isoquinoline skeleton were introduced varying either carboxylic acid or organomagnesium compound. Some of the obtained 1,1-dialkyl-1,2,3,4-tetrahydro-isoquinolines possess contractile activity against guinea pig's gastric smooth muscle preparations.     

Robust classification of low-grade cervical cytology following analysis with ATR-FTIR spectroscopy and subsequent application of self-learning classifier eClass

Although the UK cervical screening programme has reduced mortality associated with invasive disease, advancement from a high-throughput predictive methodology that is cost-effective and robust could greatly support the current system. We combined analysis by attenuated total reflection Fourier-transform infrared spectroscopy of cervical cytology with self-learning classifier eClass. This predictive algorithm can cope with vast amounts of multidimensional data with variable characteristics. Using a characterised dataset [set A: consisting of UK cervical specimens designated as normal (n = 60), low-grade (n = 60) or high-grade (n = 60)] and one further dataset (set B) consisting of n = 30 low-grade samples, we set out to determine whether this approach could be robustly predictive. Variously extending the training set consisting of set A with set B data produced good classification rates with three two-class cascade classifiers. However, a single three-class classifier was equally efficient, producing a user-friendly, applicable methodology with improved interpretability (i.e., better classification with only one set of fuzzy rules). As data from set B were added incrementally to the training set, the model learned and evolved. Additionally, monitoring of results of the set B low-grade specimens (known to be low-grade cervical cytology specimens) provided the opportunity to explore the possibility of distinguishing patients likely to progress towards invasive disease. eClass exhibited a remarkably robust predictive power in a user-friendly fashion (i.e., high throughput, ease of use) compared to other classifiers (k-nearest neighbours, support vector machines, artificial neural networks). Development of eClass to classify such datasets for applications such as screening exhibits robustness in identifying a dichotomous marker of invasive disease progression.     

Hidden in plain sight: unlocking the full potential of cyclic voltammetry with the thin-film rotating (ring) disk electrode studies for the investigation of oxygen reduction reaction electrocatalysts

Cyclic voltammetry conducted with a thin-film rotating disk electrode, or ring-disk electrode (CV-TF-R(R)DE) is a very popular ‘ex situ’ tool for the rapid screening of electrocatalysts for their activity in oxygen reduction reaction. Despite its popularity and broad use, in most instances only a small part of the information that could be accessed by CV-TF-R(R)DE is actually used by scientists in their research. This work outlines both innovative and more traditional (but half-forgotten) ways of using CV-TF-R(R)DE to its optimal or full potential in the ongoing quest to study the most relevant features of oxygen reduction reaction electrocatalysts and quickly identify the most promising candidates for their applications in fuel cells or other electrochemical devices.