Biophysical suitability, economic pressure and land-cover change: a global probabilistic approach and insights for REDD+

There has been a concerted effort by the international scientific community to understand the multiple causes and patterns of land-cover change to support sustainable land management. Here, we examined biophysical suitability, and a novel integrated index of “Economic Pressure on Land” (EPL) to explain land cover in the year 2000, and estimated the likelihood of future land-cover change through 2050, including protected area effectiveness. Biophysical suitability and EPL explained almost half of the global pattern of land cover (R 2 = 0.45), increasing to almost two-thirds in areas where a long-term equilibrium is likely to have been reached (e.g. R 2 = 0.64 in Europe). We identify a high likelihood of future land-cover change in vast areas with relatively lower current and past deforestation (e.g. the Congo Basin). Further, we simulated emissions arising from a “business as usual” and two reducing emissions from deforestation and forest degradation (REDD) scenarios by incorporating data on biomass carbon. As our model incorporates all biome types, it highlights a crucial aspect of the ongoing REDD + debate: if restricted to forests, “cross-biome leakage” would severely reduce REDD + effectiveness for climate change mitigation. If forests were protected from deforestation yet without measures to tackle the drivers of land-cover change, REDD + would only reduce 30 % of total emissions from land-cover change. Fifty-five percent of emissions reductions from forests would be compensated by increased emissions in other biomes. These results suggest that, although REDD + remains a very promising mitigation tool, implementation of complementary measures to reduce land demand is necessary to prevent this leakage

Metal-saturated sulfide assemblages in NWA 2737: Evidence for impact-related sulfur devolatilization in Martian meteorites

International audienceNWA 2737, a Martian meteorite from the Chassignite subclass, contains minute amounts (0.010 ± 0.005 vol%) of metal-saturated Fe-Ni sulfides. These latter bear evidence of the strong shock effects documented by abundant Fe nanoparticles and planar defects in Northwest Africa (NWA) 2737 olivine. A Ni-poor troilite (Fe/S = 1.0 ± 0.01), sometimes Cr-bearing (up to 1 wt%), coexists with micrometer-sized taenite/tetrataenite-type native Ni-Fe alloys (Ni/Fe = 1) and Fe-Os-Ir-(Ru) alloys a few hundreds of nanometers across. The troilite has exsolved flame-like pentlandite (Fe/Fe + Ni = 0.5-0.6). Chalcopyrite is almost lacking, and no pyrite has been found. As a hot desert find, NWA 2737 shows astonishingly fresh sulfides. The composition of troilite coexisting with Ni-Fe alloys is completely at odds with Chassigny and Nahkla sulfides (pyrite + metal-deficient monoclinic-type pyrrhotite). It indicates strongly reducing crystallization conditions (close to IW), several log units below the fO2 conditions inferred from chromites compositions and accepted for Chassignites (FMQ-1 log unit). It is proposed that reduction in sulfides into base and precious metal alloys is operated via sulfur degassing, which is supported by the highly resorbed and denticulated shape of sulfide blebs and their spongy textures. Shock-related S degassing may be responsible for considerable damages in magmatic sulfide structures and sulfide assemblages, with concomitant loss of magnetic properties as documented in some other Martian meteorites

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

The B subunits of cholera and Escherichia coli heat-labile toxins enhance the immune responses in mice orally immunised with a recombinant live P-fimbrial vaccine for avian pathogenic E. coli

This study aimed to investigate the adjuvant effect of recombinant attenuated Salmonella expressing cholera toxin B subunit (CTB) and Escherichia coli heat-labile enterotoxin B subunit (LTB) for the P-fimbriae subunit-based vaccine of avian pathogenic E. coli (APEC) in a murine model. The PapA-specific sIgA and IgG responses were significantly enhanced after immunisation with the Salmonella-PapA vaccine in the presence of CTB or LTB. The group immunised with the Salmonella-LTB strain promoted Th1-type immunity, whereas that immunised with the Salmonella-CTB strain produced Th2-type immunity. We concluded that both Salmonella-CTB and -LTB strains can enhance the immune response to PapA, and that the LTB strain may be a more effective adjuvant for APEC vaccination, which requires higher Th1-type immunity for protection. Thus, our findings provide evidence that immunisation with an adjuvant, LTB, is one of the strategies of developing effective vaccines against P-fimbriated APEC

Search for a Higgs Boson Decaying into Two Photons at LEP

A Higgs particle produced in association with a Z boson and decaying into two photons is searched for in the data collected by the L3 experiment at LEP. All possible decay modes of the Z boson are investigated. No signal is observed in 447.5 pb^-1 of data recorded at centre-of-mass energies up to 209 GeV. Limits on the branching fraction of the Higgs boson decay into two photons as a function of the Higgs mass are derived. A lower limit on the mass of a fermiophobic Higgs boson is set at 105.4 GeV at 95% confidence level

Search for Heavy Isosinglet Neutrino in e+e- Annihilation at LEP

We report on a search for the first generation heavy neutrino that is an isosinglet under the standard SU(2)_L gauge group. The data collected with the L3 detector at center-of-mass energies between 130 GeV and 208 GeV are used.The decay channel N_e --> eW is investigated and no evidence is found for a heavy neutrino, N_e, in a mass range between 80 GeV and 205 GeV. Upper limits on the mixing parameter between the heavy and light neutrino are derived

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure

OBJECTIVE: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults.METHODS: Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β 1-42 and p-Tau 181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. RESULTS: AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect.INTERPRETATION: Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.</p

Lambda and Sigma0 Pair Production in Two-Photon Collisions at LEP

Strange baryon pair production in two-photon collisions is studied with the L3 detector at LEP. The analysis is based on data collected at e+e- centre-of-mass energies from 91 GeV to 208 GeV, corresponding to an integrated luminosity of 844 pb-1. The processes gamma gamma -> Lambda Anti-lambda and gamma gamma -> Sigma0 Anti-sigma0 are identified. Their cross sections as a function of the gamma gamma centre-of-mass energy are measured and results are compared to predictions of the quark-diquark model