Advances in Aging Compact Model for Hot Carrier Degradation in SiGe HBTs under Dynamic Operating conditions for reliability-aware circuit design

International audienc

Delimiting Cryptic Morphological Variation among Human Malaria Vector Species using Convolutional Neural Networks

Deep learning is a powerful approach for distinguishing classes of images, and there is a growing interest in applying these methods to delimit species, particularly in the identification of mosquito vectors. Visual identification of mosquito species is the foundation of mosquito-borne disease surveillance and management, but can be hindered by cryptic morphological variation in mosquito vector species complexes such as the malaria-transmitting Anopheles gambiaecomplex. We sought to apply Convolutional Neural Networks (CNNs) to images of mosquitoes as a proof-of-concept to determine the feasibility of automatic classification of mosquito sex, genus, species, and strains using whole-body, 2D images of mosquitoes. We introduce a library of 1, 709 images of adult mosquitoes collected from 16 colonies of mosquito vector species and strains originating from five geographic regions, with 4 cryptic species not readily distinguishable morphologically even by trained medical entomologists. We present a methodology for image processing, data augmentation, and training and validation of a CNN. Our best CNN configuration achieved high prediction accuracies of 96.96% for species identification and 98.48% for sex. Our results demonstrate that CNNs can delimit species with cryptic morphological variation, 2 strains of a single species, and specimens from a single colony stored using two different methods. We present visualizations of the CNN feature space and predictions for interpretation of our results, and we further discuss applications of our findings for future applications in malaria mosquito surveillance

Adaptive Baseline Finder, a statistical data selection strategy to identify atmospheric CO2 baseline levels and its application to European elevated mountain stations [Discussion paper]

This paper presents a novel statistical data selection method for CO2 measurements at elevated mountain measuring stations. It provides insights on how data processing techniques are critical for measurements and data analyses. By applying different methods on atmospheric CO2 of various mountain stations, our method appears to be a good option as a generalized approach with improved comparability, which is important for researches on station characteristics or data analyses between stations.This work is supported by the scholarship from China Scholarship Council (CSC) under the Grant CSC No. 201508080110

Fingerprints of the COVID-19 economic downturn and recovery on ozone anomalies at high-elevation sites in North America and western Europe

With a few exceptions, most studies on tropospheric ozone (O3) variability during and following the COrona VIrus Disease (COVID-19) economic downturn focused on high-emission regions or urban environments. In this work, we investigated the impact of the societal restriction measures during the COVID-19 pandemic on surface O3 at several high-elevation sites across North America and western Europe. Monthly O3 anomalies were calculated for 2020 and 2021, with respect to the baseline period 2000–2019, to explore the impact of the economic downturn initiated in 2020 and its recovery in 2021. In total, 41 high-elevation sites were analyzed: 5 rural or mountaintop stations in western Europe, 19 rural sites in the western US, 4 sites in the western US downwind of highly polluted source regions, and 4 rural sites in the eastern US, plus 9 mountaintop or high-elevation sites outside Europe and the United States to provide a “global” reference. In 2020, the European high-elevation sites showed persistent negative surface O3 anomalies during spring (March–May, i.e., MAM) and summer (June–August, i.e., JJA), except for April. The pattern was similar in 2021, except for June. The rural sites in the western US showed similar behavior, with negative anomalies in MAM and JJA 2020 (except for August) and MAM 2021.The research leading to these results has received funding from the European Union's Horizon 2020 research and innovation program (grant agreement no. 654109). Surface O3 measurements at Summit are made possible via the US National Science Foundation Office of Polar Programs and their contract with Battelle Arctic Research Operations (contract no. 49100420C0001). Owen R. Cooper, Kai-Lan Chang, Irina Petropavlovskikh, and Peter Effertz were supported by a NOAA cooperative agreement (grant no. NA22OAR4320151). The publication costs of this research have been partially supported by the European Commission under the Horizon 2020 research and innovation framework program through ACTMO-ACCESS Integrating Activity (grant agreement no. 101008004)

Adaptive selection of diurnal minimum variation : a statistical strategy to obtain representative atmospheric CO₂ data and its application to European elevated mountain stations

Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS) based on CO₂ diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO₂ observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze Schneefernerhaus (Germany), Sonnblick (Austria), Jungfraujoch (Switzerland), Izaña (Spain), Schauinsland (Germany), and Hohenpeissenberg (Germany). Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT) conditions than baselines identified by the other methods

Building a transitional care checklist in rheumatology: A Delphi-like survey.

To design a transitional care checklist to be used by and facilitate the work of health professionals in providing transitional care for children with a chronic rheumatologic disease and their families. A Delphi-like study among an international expert panel was carried out in four steps: (1) a working group of 6 specialists established a draft; (2) a web-survey among a panel of international experts evaluated it; (3) a 2-day consensus conference with an expert panel discussed items not reaching agreement; (4) a web-survey among the panel of international experts with the list of reformulated items. The first draft of the checklist included 38 items in 3 phases of transition and 5 age groups. Thirty-three international experts evaluated the checklist reaching≥80% agreement for 26 items and ≤80% for 12. The consensus conference of 12 experts discussed and redefined the 12 items. Twenty-five international experts filled out the web-survey and all items reached a minimum of 80% agreement except one. The final checklist was reached. This Delphi-like study defined what themes should be included and at what age they need to be addressed with patients with a chronic rheumatology disease and their families during transition. This checklist reached a strong international and interdisciplinary consensus while examining transition in a broad way. It should now be spread widely to health professionals to be used by all those who care for adolescents aged≥12 years at times of transition. It could be transposed to most chronic conditions. Recommendations for further research are given

Essential Noninvasive Multimodality Neuromonitoring for the Critically Ill Patient

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from

In Situ Observations of the Deformation Behavior and Fracture Mechanisms of Ti-45Al-2Nb-2Mn+0.8 vol pct TiB₂

The deformation and fracture mechanisms of a nearly lamellar Ti-45Al-2Nb-2Mn (at. pct) + 0.8 vol pct TiB₂ intermetallic, processed into an actual low-pressure turbine blade, were examined by means of in situ tensile and tensile-creep experiments performed inside a scanning electron microscope (SEM). Low elongation-to-failure and brittle fracture were observed at room temperature, while the larger elongations-to-failure at high temperature facilitated the observation of the onset and propagation of damage. It was found that the dominant damage mechanisms at high temperature depended on the applied stress level. Interlamellar cracking was observed only above 390 MPa, which suggests that there is a threshold below which this mechanism is inhibited. Failure during creep tests at 250 MPa was controlled by intercolony cracking. The in situ observations demonstrated that the colony boundaries are damage nucleation and propagation sites during tensile creep, and they seem to be the weakest link in the microstructure for the tertiary creep stage. Therefore, it is proposed that interlamellar areas are critical zones for fracture at higher stresses, whereas lower stress, high-temperature creep conditions lead to intercolony cracking and fracture.The authors are grateful to Industria de Turbo Propulsores, S.A. for supplying the intermetallic blades. Funding from the Spanish Ministry of Science and Innovation through projects MAT2009-14547-C02-01 and MAT2009-14547-C02-02 is acknowledged. The Madrid Regional Government supported this project partially through the ESTRUMAT grant P2009/MAT-1585. C.J.B. acknowledges the support from Grant SAB2009-0045 from the Spanish Ministry of Education for his sabbatical stage in Madrid.Publicad

Population genetic structure of the malaria vector Anopheles nili in sub-Saharan Africa

<p>Abstract</p> <p>Background</p> <p><it>Anopheles nili </it>is a widespread efficient vector of human malaria parasites in the humid savannas and forested areas of sub-Saharan Africa. Understanding <it>An. nili </it>population structure and gene flow patterns could be useful for the development of locally-adapted vector control measures.</p> <p>Methods</p> <p>Polymorphism at eleven recently developed microsatelitte markers, and sequence variation in four genes within the 28s rDNA subunit (ITS2 and D3) and mtDNA (COII and ND4) were assessed to explore the level of genetic variability and differentiation among nine populations of <it>An. nili </it>from Senegal, Ivory Coast, Burkina Faso, Nigeria, Cameroon and the Democratic Republic of Congo (DRC).</p> <p>Results</p> <p>All microsatellite loci successfully amplified in all populations, showing high and very similar levels of genetic diversity in populations from West Africa and Cameroon (mean Rs = 8.10-8.88, mean He = 0.805-0.849) and much lower diversity in the Kenge population from DRC (mean Rs = 5.43, mean He = 0.594). Bayesian clustering analysis of microsatellite allelic frequencies revealed two main genetic clusters in the dataset. The first one included only the Kenge population and the second grouped together all other populations. High Fst estimates based on microsatellites (Fst > 0.118, P < 0.001) were observed in all comparisons between Kenge and all other populations. By contrast, low Fst estimates (Fst < 0.022, P < 0.05) were observed between populations within the second cluster. The correlation between genetic and geographic distances was weak and possibly obscured by demographic instability. Sequence variation in mtDNA genes matched these results, whereas low polymorphism in rDNA genes prevented detection of any population substructure at this geographical scale.</p> <p>Conclusion</p> <p>Overall, high genetic homogeneity of the <it>An. nili </it>gene pool was found across its distribution range in West and Central Africa, although demographic events probably resulted in a higher level of genetic isolation in the marginal population of Kenge (DRC). The role of the equatorial forest block as a barrier to gene flow and the implication of such findings for vector control are discussed.</p