Near-forward Raman scattering by bulk and surface phonon-polaritons in the model percolation-type ZnBeSe alloy

We study the bulk and surface phonon-polaritons of the Zn0.67Be0.33Se zincblende alloy by near-forward Raman scattering. The short (Be-Se) bond exhibits a distinct percolation doublet in the conventional backscattering Raman spectra, corresponding to a three-mode behavior in total [1(Zn-Se),2(Be-Se)] for Zn0.67Be0.33Se. This offers an opportunity to achieve a refined understanding of the phonon-polariton modes of a zincblende alloy beyond the current two-mode approximation, corresponding to a [1(Zn-Se),1(Be-Se)] description in the present case. The discussion is supported by contour modeling of the Raman signals of the multi-mode bulk and surface phonon-polaritons within the formalism of the linear dielectric response

A self-consistent perturbative evaluation of ground state energies: application to cohesive energies of spin lattices

The work presents a simple formalism which proposes an estimate of the ground state energy from a single reference function. It is based on a perturbative expansion but leads to non linear coupled equations. It can be viewed as well as a modified coupled cluster formulation. Applied to a series of spin lattices governed by model Hamiltonians the method leads to simple analytic solutions. The so-calculated cohesive energies are surprisingly accurate. Two examples illustrate its applicability to locate phase transition.Comment: Accepted by Phys. Rev.

Immunohistochemical expression of apoptotic factors, cytokeratins, and metalloproteinase-9 in periapical and epithelialized gingival lesions

The aim of the study was to assess the involvement of apoptotic factors, cytokeratins and metalloproteinase- 9 in the histogenesis of both Epithelialized Gingival Lesions (EGL) and Periapical Lesions (PAL). 55 consecutive patients, 30 with PAL and 25 with EGL, were selected for the study after clinical and radiological examinations. The PAL patients had severe periapical lesions and tooth decay with exposure of the pulp chamber. All PAL and EGL biopsies were surgically extracted, fixed in 10% buffered formalin, and processed for routine light microscopy. Ten biopsies of each category were processed for immunohistochemistry (IHC). Serial paraffin sections were stained by IHC with appropriate antibodies to detect cytokeratins (CKs) 1, 5, 8, 10 and 14, caspase-3 and -9, metalloproteinase-9, and for PCNA and TUNEL assays. Both PAL and EGL showed a high expression of the cytokeratin 1, 5 and 8 with higher expression in EGL. Moreover, CK10 was markedly less intense expressed in EGL compared to PAL, while CK14 was almost three times stronger expressed in EGL. The expression of caspase-3 and -9 was stronger in PAL compared to EGL, however, the difference was only significant for caspase-9. In PAL apoptosis detected by TUNNEL method and the expression of MMP-9 were higher than in EGL, whereas PCNA was significantly more expressed in EGL. The results clearly suggest that both lesions have exclusively an epithelial origin and that epithelial proliferation was correlated with the degree of apoptosis in both entities. PAL and EGL presented mostly similar cytokeratin expression except for CK10 and CK14, though with marked differences in the distribution and intensity of IHC reactions. Finally, the degradation of extracellular matrix in both lesions could be partially attributed to the strong presence of MMP-9. (Folia Histochemica et Cytobiologica 2012, Vol. 50, No. 4, 497\u2013503

Benchmarking a New Paradigm: An Experimental Analysis of a Real Processing-in-Memory Architecture

Many modern workloads, such as neural networks, databases, and graph processing, are fundamentally memory-bound. For such workloads, the data movement between main memory and CPU cores imposes a significant overhead in terms of both latency and energy. A major reason is that this communication happens through a narrow bus with high latency and limited bandwidth, and the low data reuse in memory-bound workloads is insufficient to amortize the cost of main memory access. Fundamentally addressing this data movement bottleneck requires a paradigm where the memory system assumes an active role in computing by integrating processing capabilities. This paradigm is known as processing-in-memory (PIM). Recent research explores different forms of PIM architectures, motivated by the emergence of new 3D-stacked memory technologies that integrate memory with a logic layer where processing elements can be easily placed. Past works evaluate these architectures in simulation or, at best, with simplified hardware prototypes. In contrast, the UPMEM company has designed and manufactured the first publicly-available real-world PIM architecture. This paper provides the first comprehensive analysis of the first publicly-available real-world PIM architecture. We make two key contributions. First, we conduct an experimental characterization of the UPMEM-based PIM system using microbenchmarks to assess various architecture limits such as compute throughput and memory bandwidth, yielding new insights. Second, we present PrIM, a benchmark suite of 16 workloads from different application domains (e.g., linear algebra, databases, graph processing, neural networks, bioinformatics).Comment: Our open source software is available at https://github.com/CMU-SAFARI/prim-benchmark

Coupling potential of ICESat/GLAS and SRTM for the discrimination of forest landscape types in French Guiana

The Shuttle Radar Topography Mission (SRTM) has produced the most accurate nearly global elevation dataset to date. Over vegetated areas, the measured SRTM elevations are the result of a complex interaction between radar waves and tree crowns. In this study, waveforms acquired by the Geoscience Laser Altimeter System (GLAS) were combined with SRTM elevations to discriminate the five forest landscape types (LTs) in French Guiana. Two differences were calculated: (1) penetration depth, defined as the GLAS highest elevations minus the SRTM elevations, and (2) the GLAS centroid elevations minus the SRTM elevations. The results show that these differences were similar for the five LTs, and they increased as a function of the GLAS canopy height and of the SRTM roughness index. Next, a Random Forest (RF) classifier was used to analyze the coupling potential of GLAS and SRTM in the discrimination of forest landscape types in French Guiana. The parameters used in the RF classification were the GLAS canopy height, the SRTM roughness index, the difference between the GLAS highest elevations and the SRTM elevations and the difference between the GLAS centroid elevations and the SRTM elevations. Discrimination of the five forest landscape types in French Guiana was possible, with an overall classification accuracy of 81.3% and a kappa coefficient of 0.75. All forest LTs were well classified with an accuracy varying from 78.4% to 97.5%. Finally, differences of near coincident GLAS waveforms, one from the wet season and one from the dry season, were analyzed. The results showed that the open forest LT (LT12), in some locations, contains trees that lose leaves during the dry season. These trees allow LT12 to be easily discriminated from the other LTs that retain their leaves using the following three criteria: (1) difference between the GLAS centroid elevations and the SRTM elevations, (2) ratio of top energy in the wet season to top energy in the dry season, or (3) ratio of ground energy in the wet season to ground energy in the dry season

Irrigated grassland monitoring using a time series of terraSAR-X and COSMO-skyMed X-Band SAR Data

[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOSInternational audienceThe objective of this study was to analyze the sensitivity of radar signals in the X-band in irrigated grassland conditions. The backscattered radar signals were analyzed according to soil moisture and vegetation parameters using linear regression models. A time series of radar (TerraSAR-X and COSMO-SkyMed) and optical (SPOT and LANDSAT) images was acquired at a high temporal frequency in 2013 over a small agricultural region in southeastern France. Ground measurements were conducted simultaneously with the satellite data acquisitions during several grassland growing cycles to monitor the evolution of the soil and vegetation characteristics. The comparison between the Normalized Difference Vegetation Index (NDVI) computed from optical images and the in situ Leaf Area Index (LAI) showed a logarithmic relationship with a greater scattering for the dates corresponding to vegetation well developed before the harvest. The correlation between the NDVI and the vegetation parameters (LAI, vegetation height, biomass, and vegetation water content) was high at the beginning of the growth cycle. This correlation became insensitive at a certain threshold corresponding to high vegetation (LAI ~2.5 m2/m2). Results showed that the radar signal depends on variations in soil moisture, with a higher sensitivity to soil moisture for biomass lower than 1 kg/m². HH and HV polarizations had approximately similar sensitivities to soil moisture. The penetration depth of the radar wave in the X-band was high, even for dense and high vegetation; flooded areas were visible in the images with higher detection potential in HH polarization than in HV polarization, even for vegetation heights reaching 1 m. Lower sensitivity was observed at the X-band between the radar signal and the vegetation parameters with very limited potential of the X-band to monitor grassland growth. These results showed that it is possible to track gravity irrigation and soil moisture variations from SAR X-band images acquired at high spatial resolution (an incidence angle near 30°)

Regional scale rain-forest height mapping using regression-kriging of spaceborne and airborne lidar data : application on French Guiana

LiDAR data has been successfully used to estimate forest parameters such as canopy heights and biomass. Major limitation of LiDAR systems (airborne and spaceborne) arises from their limited spatial coverage. In this study, we present a technique for canopy height mapping using airborne and spaceborne LiDAR data (from the Geoscience Laser Altimeter System (GLAS)). First, canopy heights extracted from both airborne and spaceborne LiDAR were extrapolated from available environmental data. The estimated canopy height maps using Random Forest (RF) regression from airborne or GLAS calibration datasets showed similar precisions (~6 m). To improve the precision of canopy height estimates, regression-kriging was used. Results indicated an improvement in terms of root mean square error (RMSE, from 6.5 to 4.2 m) using the GLAS dataset, and from 5.8 to 1.8 m using the airborne LiDAR dataset. Finally, in order to investigate the impact of the spatial sampling of future LiDAR missions on canopy height estimates precision, six subsets were derived from the initial airborne LiDAR dataset. Results indicated that using the regression-kriging approach a precision of 1.8 m on the canopy height map was achievable with a flight line spacing of 5 km. This precision decreased to 4.8 m for flight line spacing of 50 km

A risk-oriented degradation model for maintenance of reinforced concrete structure subjected to cracking

This article is within the context of decision models aimed for maintenance of structures and infrastructures in civil engineering. The contribution relies on the construction of a degradation model oriented toward risk analysis. The proposed model can be defined as a meta-model in the sense that it is based on observations while incorporating key features from the degradation process necessary for the maintenance decision. We propose to stimulate the construction of the degradation model based on the crack propagation of a submerged reinforced concrete structure subject to chloride-induced corrosion. Furthermore, a set of numerical illustrations is performed to demonstrate the advantages and applicability of the proposed approach in risk management and maintenance contexts