We present a novel method that we call FAINE, fast artificial intelligence neutron detection system. FAINE automatically classifies tracks of fast neutrons on CR-39 detectors using a deep learning model. This method was demonstrated using a LANDAUER Neutrak® fast neutron dosimetry system, which is installed in the External Dosimetry Laboratory (EDL) at Soreq Nuclear Research Center (SNRC). In modern fast neutron dosimetry systems, after the preliminary stages of etching and imaging of the CR-39 detectors, the third stage uses various types of computer vision systems combined with a manual revision to count the CR-39 tracks and then convert them to a dose in mSv units. Our method enhances these modern systems by introducing an innovative algorithm, which uses deep learning to classify all CR-39 tracks as either real neutron tracks or any other sign such as dirt, scratches, or even cleaning remainders. This new algorithm makes the third stage of manual CR-39 tracks revision superfluous and provides a completely repeatable and accurate way of measuring either neutrons flux or dose. The experimental results show a total accuracy rate of 96.7% for the true positive tracks and true negative tracks detected by our new algorithm against the current method, which uses computer vision followed by manual revision. This algorithm is now in the process of calibration for both alpha-particles detection and fast neutron spectrometry classification and is expected to be very useful in analyzing results of proton-boron11 fusion experiments. Being fully automatic, the new algorithm will enhance the quality assurance and effectiveness of external dosimetry, will lower the uncertainty for the reported dose measurements, and might also enable lowering the system’s detection threshold.

Established with the reform of 1993, Argentina’s private pension funds became crucial sources of credit for the national government. They purchased large amounts of sovereign bonds defaulted on in 2001 and hence were key to the success of the debt restructuring of 2005. The private pillar was always vulnerable to political maneuvering; the nationalization of private pension funds in 2008 was only the last stage in an iterated process of state intervention, a function of public debt dynamics. This article argues that the financial pressures associated with Argentina’s sovereign debt burden systematically shortened the temporality of pension policy decisions, taking those away from long-term concerns about the stability of the social security system and toward the immediacy of debt-financing imperatives. Therefore, the politics of pension reform reversal in Argentina were determined by the increasingly strong and inextricable link between debt and pensions.

When it comes to analyses of financial power in Latin America, there has been a tendency to assume it is mostly external, relatively homogeneous, and usually constraining of domestic policy autonomy. Increasingly, however, when speaking of financial power in the region, a focus exclusively on foreign capital misses a significant part of the empirical landscape, one inhabited by large domestic institutional investors: public and private pension funds. A focus on these funds reveals that a neat state–finance dichotomy is often unrepresentative of the type of blurred web of interests, influence and ownership that characterizes even those economies that have embraced a significant degree of liberalization. In fact, pension finance is far from uniform across countries. In order to capture this diversity in Latin America, a new typology is suggested that departs from the Anglo-American notion of ‘pension fund capitalism’ and further specifies pension finance as also revealing dynamics best described as ‘pension fund developmentalism and statism’. The typology is not only aimed at capturing more empirical nuance in Latin America; it can also serve as reference for cross-regional analyses of these often neglected, but increasingly powerful financial actors in emerging economies.

A commercially available vegetable oil containing a high concentration (87 %, w/w) of diacylglycerol (DAG) has been investigated in humans and animals for potential beneficial effects in reducing serum TAG concentrations in fasting and postprandial states. Effects of DAG oil as a sole dietary fat source (25 % metabolisable energy) were evaluated in a feline model of hypertriacylglycerolaemia. Eleven adult (1·5 (sem 0·1) years) male cats deficient of lipoprotein lipase (LPL) catalytic activity from a heritable point mutation of the LPL gene were acclimatised to a semi-purified diet containing TAG oil for 21 d. After assignment into two groups, pair-matched by serum TAG concentrations (range 6·1–31·6 mmol/l), the cats were fed the diet with either TAG or DAG oil for 8 d. The dietary fat source was crossed-over and presented for 8 d more. Non-fasting serum concentrations of TAG, cholesterol and NEFA were measured on days 6–8 and days 14–16. Dietary fat source (DAG v. TAG) did not significantly affect food intake (491 (sem 16) v. 486 (sem 14) kJ/kg0·67), body weight or serum concentrations (mmol/l) of TAG (37·1 (sem 4·5) v. 33·9 (sem 3·4)), cholesterol (4·8 (sem 0·3) v. 4·8 (sem 0·2)) and NEFA (1·4 (sem 0·2) v. 1·4 (sem 0·2)). The results show that for a feeding trial of 8 d, DAG oil was well accepted and tolerated by cats but did not reduce hypertriacylglycerolaemia resulting from a deficiency of LPL catalytic activity.

A state of the art review is given on conceivable concepts of cost reduction for PEM fuel cell systems with specific respect to mobile applications. Achieved results at Siemens are described and will be taken as a basis to assess how close this technology is to the market.