Beam profile and beam time structure monitors for the extracted beams from the GANIL cyclotrons

International audienc

Combined plasma gas-phase synthesis and colloidal processing of InP/ZnS core/shell nanocrystals

Indium phosphide nanocrystals (InP NCs) with diameters ranging from 2 to 5 nm were synthesized with a scalable, flow-through, nonthermal plasma process at a rate ranging from 10 to 40 mg/h. The NC size is controlled through the plasma operating parameters, with the residence time of the gas in the plasma region strongly influencing the NC size. The NC size distribution is narrow with the standard deviation being less than 20% of the mean NC size. Zinc sulfide (ZnS) shells were grown around the plasma-synthesized InP NCs in a liquid phase reaction. Photoluminescence with quantum yields as high as 15% were observed for the InP/ZnS core-shell NCs

Origins of Chevron Rollovers in Non-Two-State Protein Folding Kinetics

Chevron rollovers of some proteins imply that their logarithmic folding rates are nonlinear in native stability. This is predicted by lattice and continuum G\=o models to arise from diminished accessibilities of the ground state from transiently populated compact conformations under strongly native conditions. Despite these models' native-centric interactions, the slowdown is due partly to kinetic trapping caused by some of the folding intermediates' nonnative topologies. Notably, simple two-state folding kinetics of small single-domain proteins are not reproduced by common G\=o-like schemes.Comment: 10 pages, 4 Postscript figures (will appear on PRL

Impact of Tropical Climate on Selective Attention and Affect

Heat has an impact on several aspects of human cognition but the effects of the tropical climate (i.e., hot and wet) have rarely been explored. The purpose of this study was to determine whether selective attention and affect are negatively impacted by the tropical climate. The study followed a within-participants design: participants responded to an affective scale (PANAS) and performed an attention task (d2 Test) in two experimental climate conditions (tropical vs. neutral) with a one-week interval between sessions. The results indicated that they had lower positive affect and selective attention in the tropical climate than in the neutral climate. However, there was no significant difference in the effect on negative affect between conditions. The impact of tropical climate on affects and selective attention is discussed

The Combination of Cooling Techniques in a Tropical Environment Improves Precision Performance in Young International Fencers

The performance of intense exercise in a tropical climate is associated with limited exercise capacity due to thermal strain. This limitation is exacerbated in sports requiring full protective equipment. Research evidence suggests disturbances in cognitive function due to thermal discomfort and/or protective equipment (e.g., helmets), and thus sports that require skills in decision-making, fast reaction times, precision, and/or inhibition can be greatly affected. The objective of this study was to investigate the effects of countermeasures on the psychological and physiological responses in young international fencers wearing full protective equipment during an ecological fencing task. Nine young international fencers performed an aiming task in tropical conditions (1) without cooling interventions and (2) with cumulative cooling interventions (i.e., pre+percooling and head+torso). Participants completed a battery of cognitive (i.e., simple and choice reaction times, Stroop test), affective (i.e., PANAS), and perception (i.e., thermal environment, Feeling Scale, rating of perceived exertion) tests in each session, and their heart rate, skin temperature, and fencing performances (i.e., execution time and total score) were checked at several time points. Although the results revealed no differences in the perception of the thermal environment or the cognitive and affective scores, the cooling interventions seemed to improve movement precision during the fencing task and limit the decrease in pleasurable feelings related to the physical task. This study suggests that attentional resources are more available with cumulative cooling interventions, which leads to better performance during an ecological fencing task in tropical conditions

Randomized comparison of single dose of recombinant human IL-12 versus placebo for restoration of hematopoiesis and improved survival in rhesus monkeys exposed to lethal radiation

BACKGROUND: The hematopoietic syndrome of the acute radiation syndrome (HSARS) is a life-threatening condition in humans exposed to total body irradiation (TBI); no drugs are approved for treating this condition. Recombinant human interleukin-12 (rHuIL-12) is being developed for HSARS mitigation under the FDA Animal Rule, where efficacy is proven in an appropriate animal model and safety is demonstrated in humans. METHODS: In this blinded study, rhesus monkeys (9 animals/sex/dose group) were randomized to receive a single subcutaneous injection of placebo (group 1) or rHuIL-12 at doses of 50, 100, 250, or 500 ng/kg (groups 2–5, respectively), without antibiotics, fluids or blood transfusions, 24–25 hours after TBI (700 cGy). RESULTS: Survival rates at Day 60 were 11%, 33%, 39%, 39%, and 50% for groups 1–5, respectively (log rank p < 0.05 for each dose vs. control). rHuIL-12 also significantly reduced the incidences of severe neutropenia, severe thrombocytopenia, and sepsis (positive hemoculture). Additionally, bone marrow regeneration following TBI was significantly greater in monkeys treated with rHuIL-12 than in controls. CONCLUSIONS: Data from this study demonstrate that a single injection of rHuIL-12 delivered one day after TBI can significantly increase survival and reduce radiation-induced hematopoietic toxicity and infections. These data significantly advance development of rHuIL-12 toward approval under the Animal Rule as an effective stand-alone medical countermeasure against the lethal effects of radiation exposure

Topological Analysis of Metabolic Networks Integrating Co-Segregating Transcriptomes and Metabolomes in Type 2 Diabetic Rat Congenic Series

Background: The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus is caused by complex organ-specific cellular mechanisms contributing to impaired insulin secretion and insulin resistance. Methods: We used systematic metabotyping by 1H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualise shortest paths between metabolites and genes significantly associated with each genomic block. Results: Despite strong genomic similarities (95-99%) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific metabotypes (mQTL) and genome-wide expression traits (eQTL). Variation in key metabolites like glucose, succinate, lactate or 3-hydroxybutyrate, and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing shortest path length drove prioritization of biological validations by gene silencing. Conclusions: These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulations and to characterize novel functional roles for genes determining tissue-specific metabolism

Saturn's Seasonal Atmosphere at Northern Summer Solstice

The incredible longevity of Cassini's orbital mission at Saturn has provided the most comprehensive exploration of a seasonal giant planet to date. This review explores Saturn's changing global temperatures, composition, and aerosol properties between northern spring and summer solstice (2015-2017), extending our previous review of Cassini's remote sensing investigations (2004-14, Fletcher et al., 2018) to the grand finale. The result is an unprecedented record of Saturn's climate that spans almost half a Saturnian year, which can be used to test the seasonal predictions of radiative climate models, neutral and ion photochemistry models, and atmospheric circulation models. Hemispheric asymmetries in tropospheric and stratospheric temperatures were observed to reverse from northern winter to northern summer; spatial distributions of hydrocarbons and para-hydrogen shifted in response to atmospheric dynamics (e.g., seasonally-reversing Hadley cells, polar stratospheric vortex formation, equatorial stratospheric oscillations, and inter-hemispheric transport); and upper tropospheric and stratospheric aerosols exhibited changes in optical thickness that modulated Saturn's visible colours (from blue hues to a golden appearance in the north near solstice), reflectivity, and near-infrared emission. Numerical simulations of radiative balance and photochemistry do a good job in reproducing the observed seasonal change and phase lags, but discrepancies between models and observations still persist, indicating a crucial role for atmospheric dynamics and the need to couple chemical and radiative schemes to the next generation of circulation models. With Cassini's demise, an extended study of Saturn's seasons, from northern summer to autumn, will require the capabilities of ground- and space-based observatories, as we eagerly await the next orbital explorer at Saturn.Comment: 24 pages, 18 figures, submitted for publication by Cambridge University Press as part of a multi-volume work edited by Kevin Baines, Michael Flasar, Norbert Krupp, and Thomas Stallard, entitled "Cassini at Saturn: The Grand Finale." The copy of the Chapter, as displayed on this website, is a draft, pre-publication copy onl

Multi-Decadal Changes in Mangrove Extent, Age and Species in the Red River Estuaries of Viet Nam

This research investigated the performance of four different machine learning supervised image classifiers: artificial neural network (ANN), decision tree (DT), random forest (RF), and support vector machine (SVM) using SPOT-7 and Sentinel-1 images to classify mangrove age and species in 2019 in a Red River estuary, typical of others found in northern Viet Nam. The four classifiers were chosen because they are considered to have high accuracy, however, their use in mangrove age and species classifications has thus far been limited. A time-series of Landsat images from 1975 to 2019 was used to map mangrove extent changes using the unsupervised classification method of iterative self-organizing data analysis technique (ISODATA) and a comparison with accuracy of K-means classification, which found that mangrove extent has increased, despite a fall in the 1980s, indicating the success of mangrove plantation and forest protection efforts by local people in the study area. To evaluate the supervised image classifiers, 183 in situ training plots were assessed, 70% of them were used to train the supervised algorithms, with 30% of them employed to validate the results. In order to improve mangrove species separations, Gram–Schmidt and principal component analysis image fusion techniques were applied to generate better quality images. All supervised and unsupervised (2019) results of mangrove age, species, and extent were mapped and accuracy was evaluated. Confusion matrices were calculated showing that the classified layers agreed with the ground-truth data where most producer and user accuracies were greater than 80%. The overall accuracy and Kappa coefficients (around 0.9) indicated that the image classifications were very good. The test showed that SVM was the most accurate, followed by DT, ANN, and RF in this case study. The changes in mangrove extent identified in this study and the methods tested for using remotely sensed data will be valuable to monitoring and evaluation assessments of mangrove plantation projects