Effect of In Ovo Exposure to PCBs and Hg on Clapper Rail Bone Mineral Chemistry from a Contaminated Salt Marsh in Coastal Georgia

The effect of Hg and PCBs (Aroclor 1268) on bone characteristics was investigated in a population of Clapper Rails (Rallus longirostris) inhabiting contaminated and unimpacted estuarine marsh systems in coastal Georgia. Exposure to contaminants did not affect the length or weight of leg bones, but it significantly altered the chemical composition of the bone. Specifically, bone in the contaminated site had a higher Ca to P, and lower carbonate and acid phosphate content. These characteristics are typical of more mature bone mineral and indicate that toxicants have accelerated bone maturation. FTIR spectroscopy data revealed a dose dependent change in the crystallinity of bone mineral, and the relative proportion of specific PO4 groups in different molecular environments in the bone, with toxicants loads. These changes are most probably related to a hormonal alteration of the rate of bone remodelation induced by exposure to toxicant loads

Performance modeling of the sparse matrix-vector product via convolutional neural networks

[EN] Modeling the execution time of the sparse matrix-vector multiplication (SpMV) on a current CPU architecture is especially complex due to (i) irregular memory accesses; (ii) indirect memory referencing; and (iii) low arithmetic intensity. While analytical models may yield accurate estimates for the total number of cache hits/misses, they often fail to predict accurately the total execution time. In this paper, we depart from the analytic approach to instead leverage convolutional neural networks (CNNs) in order to provide an effective estimation of the performance of the SpMV operation. For this purpose, we present a high-level abstraction of the sparsity pattern of the problem matrix and propose a blockwise strategy to feed the CNN models by blocks of nonzero elements. The experimental evaluation on a representative subset of the matrices from the SuiteSparse Matrix collection demonstrates the robustness of the CNN models for predicting the SpMV performance on an Intel Haswell core. Furthermore, we show how to generalize the network models to other target architectures to estimate the performance of SpMV on an ARM A57 coreThis work was supported by project TIN2017-82972-R from the MINECO, Spain. Manuel F. Dolz was also supported by the Plan GenT project CDEIGENT/2018/014 from the Generalitat Valenciana, Spain. Maria Barreda was also supported by the POSDOC-A/2017/11 project from the Universitat Jaume IBarreda, M.; Dolz, MF.; Castaño Alvarez, MA.; Alonso-Jordá, P.; Quintana-Orti, ES. (2020). Performance modeling of the sparse matrix-vector product via convolutional neural networks. The Journal of Supercomputing (Online). 76(11):8883-8900. https://doi.org/10.1007/s11227-020-03186-1S888389007611Abdelfattah A, Ltaief H, Keyes D (2015) High performance multi-GPU SpMV for multi-component PDE-based applications. In: Träff JL, Hunold S, Versaci F (eds) Euro-Par 2015: parallel processing. Springer, Berlin, pp 601–612Schiesser WE (2014) Computational mathematics in engineering and applied science: ODEs, DAEs, and PDEs. CRC Press, Boca RatonVuduc R, Demmel JW, Yelick KA (2005) OSKI: a library of automatically tuned sparse matrix kernels. J Phys Conf Ser 16:521–530Williams S, Oliker L, Vuduc R, Shalf J, Yelick K, Demmel J (2007) Optimization of sparse matrix–vector multiplication on emerging multicore platforms. In: SC ’07: Proceedings of the 2007 ACM/IEEE Conference on Supercomputing, pp 1–12Elafrou A, Goumas G, Koziris N (2017) Performance analysis and optimization of sparse matrix–vector multiplication on modern multi- and many-core processors. In: 2017 46th International Conference on Parallel Processing (ICPP), pp 292–301Li S, Chang H, Zhang J, Zhang Y (2015) Automatic tuning of sparse matrix–vector multiplication on multicore clusters. Sci China Inf Sci 58(9):1–14Guo P, Wang L (2015) Accurate cross-architecture performance modeling for sparse matri–vector multiplication (SpMV) on GPUs. Concurr Comput Pract Exp 27(13):3281–3294Li K, Yang W, Li K (2015) Performance analysis and optimization for SpMV on GPU using probabilistic modeling. IEEE Trans Parallel Distrib Syst 26(1):196–205Eijkhout V, Pozo R (1994) Data structures and algorithms for distributed sparse matrix operations. Technical reportGu J, Wang Z, Kuen J, Ma L, Shahroudy A, Shuai B, Liu T, Wang X, Wang G, Cai J, Chen T (2018) Recent advances in convolutional neural networks. Pattern Recognit 77(C):354–377Glorot X, Bordes A, Bengio Y (2011) Deep sparse rectifier neural networks. 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SURVEYING POPULATIONS OF RED-BILLED CURASSOWS (CRAX BLUMENBACHII) IN THE ATLANTIC FOREST OF BRAZIL

Threatened species are frequently difficult to monitor, leading to a lack of information for the selection of the best conservation strategies. A case in point is the Red-billed Curassow (Crax blumenbachii, Cracidae, Galliformes), whose populations have declined due to deforestation of the northern Atlantic Forest and increased poaching in the late 1960s. The species is presently absent from most forest frag- ments within its geographic range, occurring only in forest remnants on the states of Bahia and Espírito Santo, Brazil. In this study, we esti- mated encounter rates and recorded the periods of activity of the Red-billed Curassow in three large Atlantic Forest fragments in the north- eastern Brazilian state of Bahia, using line-transect sampling. The northern region of Serra do Conduru State Park (0.29 sighting/10 km) and Descobrimento National Park (0.27 sighting/10 km) presented slightly greater encounter rates of this endangered cracid, compared to the Una Biological Reserve (0.13 – 0.20 sighting/10 km). We recorded Red-billed Curassows throughout the day, mainly between 10:00–11:00 h and 14:00–17:00 h. Our study is the first step for long-term monitoring of the Red-billed Curassow. These findings serve as baseline infor- mation, which may contribute to future assessments of the conservation status and support future conservation actions for the species

Synchrotron X-ray photoabsorption spectroscopy of plasmas

Theoretical X-ray opacities are used in numerous radiative transfer simulations of plasmas at different temperatures and densities, for example astrophysics, fusion, metrology and EUV and X-rays radiation sources. However, there are only a reduced number of laboratories working on the validation of those theoretical results empirically, in particular for high temperature plasmas (mayor que 1eV). One of those limitations comes from the use of broad band EUV- X ray sources to illuminate the plasma which, among other issues, present low reproducibility and repetition rate [1]. Synchrotron radiation facilities are a more appropriate radiation source in that sense, since they provide tunable, reproducible and high resolution photons. Only their ?low? photon intensity for these experiments has prevented researchers to use it for this purpose. However, as new synchrotron facilities improve their photon fluxes, this limitation not longer holds [2]. This work evaluates the experimental requirements to use third generation synchrotron radiation sources for the empirical measurement of opacities of plasmas, proposing a pausible experimental set-up to carry them out. Properties of the laser or discharge generated plasmas to be studied with synchrotron radiation will be discussed in terms of their maximum temperatures, densities and temporal evolution. It will be concluded that there are encouraging reasons to pursue these kind of experiments which will provide with an appropriate benchmark for theoretical opacitie

Biogenic Macroporosity and lts Lattice Boltzmann Method Permeability in the Karst Biscayne Aquifer

We focus on two major problems in the study of paleokarst of the Biscayne aquifer in southeastem Florida: ( 1 ), current conceptual models of karst aquifers do not adequately characterize much of the eogenetic rnacropore system within the carbonate rocks of the Biscayne aquifer, and (2) standard laboratory core-analysis rnethods cannol be used lo accurately measure the permeability of highly macroporous carbonate core samples

Expression of a barley cystatin gene in maize enhances resistance against phytophagous mites by altering their cysteine-proteases

Phytocystatins are inhibitors of cysteine-proteases from plants putatively involved in plant defence based on their capability of inhibit heterologous enzymes. We have previously characterised the whole cystatin gene family members from barley (HvCPI-1 to HvCPI-13). The aim of this study was to assess the effects of barley cystatins on two phytophagous spider mites, Tetranychus urticae and Brevipalpus chilensis. The determination of proteolytic activity profile in both mite species showed the presence of the cysteine-proteases, putative targets of cystatins, among other enzymatic activities. All barley cystatins, except HvCPI-1 and HvCPI-7, inhibited in vitro mite cathepsin L- and/or cathepsin B-like activities, HvCPI-6 being the strongest inhibitor for both mite species. Transgenic maize plants expressing HvCPI-6 protein were generated and the functional integrity of the cystatin transgene was confirmed by in vitro inhibitory effect observed against T. urticae and B. chilensis protein extracts. Feeding experiments impaired on transgenic lines performed with T. urticae impaired mite development and reproductive performance. Besides, a significant reduction of cathepsin L-like and/or cathepsin B-like activities was observed when the spider mite fed on maize plants expressing HvCPI-6 cystatin. These findings reveal the potential of barley cystatins as acaricide proteins to protect plants against two important mite pests

Ultrasensitive multiplex optical quantification of bacteria in large samples of biofluids

Efficient treatments in bacterial infections require the fast and accurate recognition of pathogens, with concentrations as low as one per milliliter in the case of septicemia. Detecting and quantifying bacteria in such low concentrations is challenging and typically demands cultures of large samples of blood (~1 milliliter) extending over 24-72 hours. This delay seriously compromises the health of patients. Here we demonstrate a fast microorganism optical detection system for the exhaustive identification and quantification of pathogens in volumes of biofluids with clinical relevance (~1 milliliter) in minutes. We drive each type of bacteria to accumulate antibody functionalized SERS-labelled silver nanoparticles. Particle aggregation on the bacteria membranes renders dense arrays of inter-particle gaps in which the Raman signal is exponentially amplified by several orders of magnitude relative to the dispersed particles. This enables a multiplex identification of the microorganisms through the molecule-specific spectral fingerprints

Functional genomics of abiotic environmental adaptation in lacertid lizards and other vertebrates

Understanding the genomic basis of adaptation to different abiotic environments is important in the context of climate change and resulting short-term environmental fluctuations. Using functional and comparative genomics approaches, we here investigated whether signatures of genomic adaptation to a set of environmental parameters are concentrated in specific subsets of genes and functions in lacertid lizards and other vertebrates. We first identify 200 genes with signatures of positive diversifying selection from transcriptomes of 24 species of lacertid lizards and demonstrate their involvement in physiological and morphological adaptations to climate. To understand how functionally similar these genes are to previously predicted candidate functions for climate adaptation and to compare them with other vertebrate species, we then performed a meta-analysis of 1,100 genes under selection obtained from -omics studies in vertebrate species adapted to different abiotic factors. We found that the vertebrate gene set formed a tightly connected interactome, which was to 23% enriched in previously predicted functions of adaptation to climate, and to a large part (18%) involved in organismal stress response. We found a much higher degree of identical genes being repeatedly selected among different animal groups (43.6%), and of functional similarity and post-translational modifications than expected by chance, and no clear functional division between genes used for ectotherm and endotherm physiological strategies. In total, 171 out of 200 genes of Lacertidae were part of this network. These results highlight an important role of a comparatively small set of genes and their functions in environmental adaptation and narrow the set of candidate pathways and markers to be used in future research on adaptation and stress response related to climate change