Country stakes in climate change negotiations : two dimensions of vulnerability

Using a comprehensive geo-referenced database of indicators relating to global change and energy, the paper assesses countries'likely attitudes with respect to international treaties that regulate carbon emissions. The authors distinguish between source and impact vulnerability and classify countries according to these dimensions. The findings show clear differences in the factors that determine likely negotiating positions. This analysis and the resulting detailed, country level information help to explain the incentives required to make the establishment of such agreements more likely.Energy Production and Transportation,Energy and Environment,Environment and Energy Efficiency,Climate Change,Transport and Environment

Detailed investigation of factors affecting the synthesis of SiO2@Au for the enhancement of Raman spectroscopy

The reaction time, temperature, ratio of precursors, and concentration of sodium citrate are known as the main factors that affect the direct synthesis process of SiO2@Au based on the chemical reaction of HAuCl4 and sodium citrate. Hence, we investigated, in detail, and observed that these factors played a crucial role in determining the shape and size of synthesized nanoparticles. The significant enhancement of the SERS signal corresponding to the fabrication conditions is an existing challenge. Our study results show that the optimal reaction conditions for the fabrication of SiO2@Au are a 1:21 ratio of HAuCl4 to sodium citrate, with an initial concentration of sodium citrate of 4.2 mM, and a reaction time lasting longer than 6 h at a temperature of 80 degrees C. Under optimal conditions, our synthesis process result is SiO2@Au nanoparticles with a diameter of approximately 350 nm. In particular, the considerable enhancement of Raman intensities of SiO2@Au compared to SiO2 particles was examined.Web of Science1217art. no. 308

Fine-grained Population Mapping from Coarse Census Counts and Open Geodata

Fine-grained population maps are needed in several domains, like urban planning, environmental monitoring, public health, and humanitarian operations. Unfortunately, in many countries only aggregate census counts over large spatial units are collected, moreover, these are not always up-to-date. We present POMELO, a deep learning model that employs coarse census counts and open geodata to estimate fine-grained population maps with 100m ground sampling distance. Moreover, the model can also estimate population numbers when no census counts at all are available, by generalizing across countries. In a series of experiments for several countries in sub-Saharan Africa, the maps produced with POMELOare in good agreement with the most detailed available reference counts: disaggregation of coarse census counts reaches R2 values of 85-89%; unconstrained prediction in the absence of any counts reaches 48-69%

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

⁴⁰Ar/³⁹Ar dating of late pleistocene marine and terrestrial tephra from the Tyrrhenian and Ionian seas, Mediterranea : some implications for global climate changes

Ce doctorat a permis l'établissement de nouveaux âges ⁴⁰Ar/³⁹Ar sur des échantillons très jeunes. Le premier chapitre est publié dans "Earth and planetary science letters". Un âge a été obtenu sur un tephra très jeune, provenant des champs phlégréens. Il permet une calibration d'autres événements climatiques et géologiques tels qu'un pic de ¹⁰Be (identifié dans des carottes de glace, des océans atlantique, pacifique et méditerranée), une excursion magnétique nommée Laschamp (marqueur global), une calibration des âges ¹⁴C>35 ka. Les autres données provenant de l'île de Pantelleria et de tephra marins (mer Ionienne), permettent de comparer des échantillons terrestres et marins. La datation simultanée est un outil puissant pour déterminer la source d'un échantillon marin dont l'origine est incertaine. Une fois la source définie, on peut ensuite facilement travailler sur les échantillons terrestres, disponibles en plus grande quantité et dont les cristaux sont plus grands (datation de monocristaux)

40Ar/39Ar dating of latest Pleistocene (41 ka) marine tephra in the Mediterranean Sea: implications for global climate records

International audienc

Experimental study of mutual effects of high carrier frequency, dead-time and control sample time on IPMSM core loss under SiC inverter excitation

This paper experimentally analyzes the core loss characteristics of an interior permanent magnet synchronous motor (IPMSM) excited by a SiC inverter with the sinusoidal pulse-width modulation (PWM) and high modulation index of 1.1 considering the mutual effects of the high carrier frequencies of up to 200 kHz, different dead-times of 250 and 1000 ns, control sample times of 100–1000 μs, and stator core temperature. The experimental IPMSM drive system is operated in load condition with a torque of 1.05 Nm and rotational velocity of 1500 rpm. Furthermore, the ringing phenomenon and rise time in the motor voltage are measured and analyzed using a high-resolution oscilloscope that has a superior sampling rate of up to 5 giga-samples per second (GS/s), which helps to thoroughly examine the impact of the SiC inverter excitation on the motor core loss. The relations of the total harmonic distortion (THD) of the measured motor voltage and current and the distortions in the magnetic flux density through the stator core to the IPMSM core loss properties are also evaluated. Lastly, explanations and insights based on physics of the obtained results are presented

Datación de lavas basáltica por ⁴⁰Ar/³⁹Ar y geología glacial de la región del lago Buenos Aires, provincia de Santa Cruz, Argentina

Lava flows ⁴⁰Ar/³⁹Ar analysis and glacial geology, Lago Buenos Aires, Santa Cruz Province. Eight basaltic lava flows and two erratic boulders in moraines east of the Andes near Lago Buenos Aires, Santa Cruz province, Argentina (46º30'-47º00' S; 70º30'-71º45' W) and one lava along the Río Gallegos valley (51º50' S, 70º40' W) were analysed using the ⁴⁰Ar/³⁹Ar incremental-heating technique. The ⁴⁰Ar/³⁹Ar results indicate that these samples include: (1) earliest Miocene (24.2 Ma) valley-filling lava flows, (2) late-Miocene (10.0 Ma, 7.4 Ma, and 5.0 Ma) meseta-capping lava flows, the latter two interbedded with glacial till, (3) Pleistocene lavas erupted at 1.17 Ma, 1.02 Ma, 0.76 Ma and interbedded with glacial tills, (4) a very young lava that proved difficult to date, and (5) basaltic erratic boulders that erupted at 117.5 Ma and 16.8 Ma, but which were incorporated into moraines during the late Pleistocene. These age determinations provide new constraints on the timing of Miocene and Pleistocene glacial advances of the southern Andean ice cap. The oldest Cenozoic till recognised in South America underlies a lava capping Meseta de Lago Buenos Aires whose ⁴⁰Ar/³⁹Ar isochron age of 5.04 ± 0.04 Ma is older than a previous K-Ar date by >400 k.y. Glacial till , together with outwash gravels and erratic boulders, that correspond to the greatest extent of ice in Patagonia (the so-called "Greatest Patagonian Glaciation", or GPG) are underlain by a lava dated at 1.168 ± 0.007 Ma and overlain by a lava dated at 1.016 ± 0.005 Ma. Thus the GPG occurred sometime between oxygen isotope stages 30-34. At Lago Buenos Aires, the deposition of at least twelve moraines since the GPG, including one overlain by lava dated at 0.760 ± 0.007 Ma, are consistent, in general terms, with the number and timing of glacial advances predicted by the astronomical time scale based on global marine oxygen isotope stages

Fine-grained population mapping from coarse census counts and open geodata

Fine-grained population maps are needed in several domains, like urban planning, environmental monitoring, public health, and humanitarian operations. Unfortunately, in many countries only aggregate census counts over large spatial units are collected, moreover, these are not always up-to-date. We present Pomelo, a deep learning model that employs coarse census counts and open geodata to estimate fine-grained population maps with 100m ground sampling distance. Moreover, the model can also estimate population numbers when no census counts at all are available, by generalizing across countries. In a series of experiments for several countries in sub-Saharan Africa, the maps produced with Pomelo are in good agreement with the most detailed available reference counts: disaggregation of coarse census counts reaches R2 values of 85–89%; unconstrained prediction in the absence of any counts reaches 48–69%.ISSN:2045-232