Quantitative Analysis of the Publishing Landscape in High-Energy Physics

World-wide collaboration in high-energy physics (HEP) is a tradition which dates back several decades, with scientific publications mostly coauthored by scientists from different countries. This coauthorship phenomenon makes it difficult to identify precisely the ``share'' of each country in HEP scientific production. One year's worth of HEP scientific articles published in peer-reviewed journals is analysed and their authors are uniquely assigned to countries. This method allows the first correct estimation on a ``pro rata'' basis of the share of HEP scientific publishing among several countries and institutions. The results provide an interesting insight into the geographical collaborative patterns of the HEP community. The HEP publishing landscape is further analysed to provide information on the journals favoured by the HEP community and on the geographical variation of their author bases. These results provide quantitative input to the ongoing debate on the possible transition of HEP publishing to an Open Access model.Comment: For a better on-screen viewing experience this paper can also be obtained at: http://doc.cern.ch/archive/electronic/cern/preprints/open/open-2006-065.pd

Supervised detection of bomb craters in historical aerial images using convolutional neural networks

The aftermath of the air strikes during World War II is still present today. Numerous bombs dropped by planes did not explode, still exist in the ground and pose a considerable explosion hazard. Tracking down these duds can be tackled by detecting bomb craters. The existence of a dud can be inferred from the existence of a crater. This work proposes a method for the automatic detection of bomb craters in aerial wartime images. First of all, crater candidates are extracted from an image using a blob detector. Based on given crater references, for every candidate it is checked whether it, in fact, represents a crater or not. Candidates from various aerial images are used to train, validate and test Convolutional Neural Networks (CNNs) in the context of a two-class classification problem. A loss function (controlling what the CNNs are learning) is adapted to the given task. The trained CNNs are then used for the classification of crater candidates. Our work focuses on the classification of crater candidates and we investigate if combining data from related domains is beneficial for the classification. We achieve a F1-score of up to 65.4% when classifying crater candidates with a realistic class distribution. © Authors 2019. CC BY 4.0 License

Learning and interaction in groups with computers: when do ability and gender matter?

In the research reported in this paper, we attempt to identify the background and process factors influencing the effectiveness of groupwork with computers in terms of mathematics learning. The research used a multi-site case study design in six schools and involved eight groups of six mixed-sex, mixed-ability pupils (aged 9-12) undertaking three research tasks – two using Logo and one a database. Our findings suggest that, contrary to other recent research, the pupil characteristics of gender and ability have no direct influence on progress in group tasks with computers. However, status effects – pupils' perceptions of gender and ability – do have an effect on the functioning of the group, which in turn can impede progress for all pupils concerned

Microbiological, Physicochemical, and Immunological Analysis of a Commercial Cashew Nut-Based Yogurt

Nut-based milks and yogurts are gaining popularity, but may not offer the same benefits as dairy yogurts to consumers. Cashew nuts often cause severe allergic reactions, and cashew nut allergens are stable to several types of processing. To compare its characteristics to dairy yogurt and characterize the effects of fermentation on the Ana o 1-3 cashew nut allergens, a commercial yogurt made from cashew nuts (Cashewgurt) was evaluated for microbiological, physiochemical, and immunological properties. Average counts for lactobacilli and Streptococcus thermophilus were greater than 10 million colony forming units per milliliter, indicating the capacity to provide a health benefit. Cashewgurt pH and viscosity values were comparable to cow milk yogurts, and it was off white in color. SDS-PAGE analysis indicated a clear reduction in Ana o 1 and 2, and immuno-assay with polyclonal anti-cashew IgG antibody and cashew-allergic IgE indicated an overall reduction in allergen content. In contrast, SDS-PAGE, mass spectrometry, immunoblot, and ELISA all revealed that Ana o 3 was relatively unaffected by the fermentation process. In conclusion, Ana o 1 and Ana o 2 are sensitive to degradation, while Ana o 3 survives lactic acid bacterial fermentation during yogurt production. The analysis presented here indicates that cashew nut yogurt is not suitable for those with cashew nut allergy

Comparison of bio-inspired algorithms applied to the hospital mortality risk stratification

The construction of patient classification (or risk adjustment) systems allows comparison of the effectiveness and quality of hospitals and hospital services, providing useful information for management decision making and management of hospitals. Risk adjustment systems to stratify patients’ severity in a clinical outcome are generally constructed from care variables and using statistical techniques based on logistic regression (RL). The objective of this investigation is to compare the hospital mortality prediction capacity of an artificial neural network (RNA) with other methods already known

A microalgal-based preparation with synergistic cellulolytic and detoxifying action towards chemical-treated lignocellulose

High-temperature bioconversion of lignocellulose into fermentable sugars has drawn attention for efficient production of renewable chemicals and biofuels, because competing microbial activities are inhibited at elevated temperatures and thermostable cell wall degrading enzymes are superior to mesophilic enzymes. Here, we report on the development of a platform to produce four different thermostable cell wall degrading enzymes in the chloroplast of Chlamydomonas reinhardtii. The enzyme blend was composed of the cellobiohydrolase CBM3GH5 from C. saccharolyticus, the β-glucosidase celB from P. furiosus, the endoglucanase B and the endoxylanase XynA from T. neapolitana. In addition, transplastomic microalgae were engineered for the expression of phosphite dehydrogenase D from Pseudomonas stutzeri, allowing for growth in non-axenic media by selective phosphite nutrition. The cellulolytic blend composed of the glycoside hydrolase (GH) domain GH12/GH5/GH1 allowed the conversion of alkaline-treated lignocellulose into glucose with efficiencies ranging from 14% to 17% upon 48h of reaction and an enzyme loading of 0.05% (w/w). Hydrolysates from treated cellulosic materials with extracts of transgenic microalgae boosted both the biogas production by methanogenic bacteria and the mixotrophic growth of the oleaginous microalga Chlorella vulgaris. Notably, microalgal treatment suppressed the detrimental effect of inhibitory by-products released from the alkaline treatment of biomass, thus allowing for efficient assimilation of lignocellulose-derived sugars by C. vulgaris under mixotrophic growth

Cardiac performance, biomarkers and gene expression studies in previously sedentary men participating in half-marathon training

BACKGROUND: The mechanisms through which exercise reduces cardiovascular disease are not fully understood. We used echocardiograms, cardiac biomarkers and gene expression to investigate cardiovascular effects associated with exercise training. METHODS: Nineteen sedentary men (22-37 years) completed a 17-week half-marathon training program. Serial measurements of resting heart rate, blood pressure, maximum oxygen consumption, lipids, C-reactive protein, cardiac troponin T, echocardiograms and blood for gene expression were obtained from baseline to peak training. Controls included 22 sedentary men who did not exercise. RESULTS: Among the training group, VO2 max increased from 37.1 to 42.0 ml/kg/min (p \u3c 0.001). Significant changes were seen in left ventricular wall thickness and mass, stroke volume, resting heart rate and blood pressure (p \u3c 0.001). The control group demonstrated no significant changes. Expression profiling in the training group identified 10 significantly over-expressed and 53 significantly under-expressed loci involved in inflammatory pathways. Dividing the training group into high and low responders based on percent change in VO2 max identified loci that differentiated these two groups at baseline and after training. CONCLUSION: Intensive exercise training leads to significant increase in cardiac and hemodynamic performance, and significant changes in expression of genes involved in immune and inflammatory response.