Unsharpmaskingusingquadratic filterfortheenhancement of fingerprintsinnoisybackground

The papersummarizesthedesignandimplementationofaquadraticedgedetection filter basedon Volterraseries.The filter isemployedinanunsharpmaskingschemeforenhancing fingerprints inadark and noisybackground.Theproposed filter canaccountformuchofthepolynomialnonlinearities inherent intheinputimageandcanreplacetheconventionaledgedetectorslikeLaplacian,LoG,etc.The application ofthenew filter isinforensicinvestigationwhereenhancementandidentification oflatent fingerprints arekeyissues.Theenhancementofimagesbytheproposedmethodissuperiortothatwith unsharp maskingschemeemployingconventional filters intermsofthevisualquality,thenoise performance and the computational complexity,making it an ideal candidate for latent fingerprint enhancement.

Design, Development and Realization of Quadratic Volterra Filters for Selected Applications

The basic concepts of digital signal processing are taught to the students in engineering and science. The focus of the course is on linear, time invariant systems. The question as to what happens when the system is governed by a quadratic or cubic equation remains unanswered in the vast majority of literature on signal processing. Light has been shed on this problem when John V Mathews and Giovanni L Sicuranza published the book Polynomial Signal Processing. This book opened up an unseen vista of polynomial systems for signal and image processing. The book presented the theory and implementations of both adaptive and non-adaptive FIR and IIR quadratic systems which offer improved performance than conventional linear systems. The theory of quadratic systems presents a pristine and virgin area of research that offers computationally intensive work. Once the area of research is selected, the next issue is the choice of the software tool to carry out the work. Conventional languages like C and C++ are easily eliminated as they are not interpreted and lack good quality plotting libraries. MATLAB is proved to be very slow and so do SCILAB and Octave. The search for a language for scientific computing that was as fast as C, but with a good quality plotting library, ended up in Python, a distant relative of LISP. It proved to be ideal for scientific computing. An account of the use of Python, its scientific computing package scipy and the plotting library pylab is given in the appendix Initially, work is focused on designing predictors that exploit the polynomial nonlinearities inherent in speech generation mechanisms. Soon, the work got diverted into medical image processing which offered more potential to exploit by the use of quadratic methods. The major focus in this area is on quadratic edge detection methods for retinal images and fingerprints as well as de-noising raw MRI signals

Bacterial ecology of ancient Saharan salt-enrichment ponds at Teguidda-n-Tessoumt

Little is known about the bacterial ecology of evaporative salt-mining sites (salterns) of which Teguidda-n-Tessoumt at the fringe of the West-African Saharan desert in Niger is a spectacular example with its many-centuries-old and very colorful evaporation ponds. During the different enrichment steps of the salt produced as a widely traded feed supplement for cattle, animal manure is added to the crude brine, which is then desiccated and repeatedly crystallized. This study describes the dominant Bacteria and Archaea communites in the brine from the evaporation ponds and the soil from the mine, which were determined by PCR-DGGE of 16S rDNA. Correspondence analysis of the DGGE-community fingerprints revealed a change in community structure of the brine samples during the sequential evaporation steps which was, however, unaffected by the brine's pH and electric conductivity (EC). The Archaea community was dominated by a phylogenetically diverse group of methanogens, while the Bacteria community was dominated by gamma proteobacteria. Microorganisms contained in the purified salt product have the potential to be broadly disseminated and are fed to livestock across the region. In this manner, the salt mines represent an intriguing example of long-term human activity that has contributed to the continual selection, cultivation, and dissemination of cosmopolitan microorganisms.

Development of molecular monitoring methods and assessment of the environmental fate of the biological control agent of fire blight Pseudomonas fluorescens EPS62e

Pseudomonas fluorescens EPS62e es va seleccionar com a agent de biocontrol del foc bacterià per la seva eficàcia en el control de Erwinia amylovora. En aquest treball es van desenvolupar mètodes de traçabilitat que van permetre la seva detecció específica i quantificació. Mitjançant les tècniques RAPD i U-PCR es van obtenir fragments d'amplificació diferencial per EPS62e que es van seqüenciar i caracteritzar com marcadors SCAR per dissenyar una PCR en temps real. La PCR a temps real es va utilitzar simultàniament amb mètodes microbiològics per estudiar l'adaptabilitat epifítica de EPS62e en pomera i perera. L'ús combinat de mètodes microbiològics i moleculars va permetre la identificació de tres estats fisiològics de EPS62e: la colonització activa, l'entrada en un estat de viable però no cultivable, i la mort cel·lular. Aquest treball mostra que EPS62e està ben adaptada a la colonització de flors a camp, encoratjant la seva utilització dins d'una estratègia de control biològic contra el foc bacterià.

Establishing Lagrangian connections between observations within air masses crossing the Atlantic during the International Consortium for Atmospheric Research on Transport and Transformation experiment

The ITCT-Lagrangian-2K4 (Intercontinental Transport and Chemical Transformation) experiment was conceived with an aim to quantify the effects of photochemistry and mixing on the transformation of air masses in the free troposphere away from emissions. To this end, attempts were made to intercept and sample air masses several times during their journey across the North Atlantic using four aircraft based in New Hampshire (USA), Faial (Azores) and Creil (France). This article begins by describing forecasts from two Lagrangian models that were used to direct the aircraft into target air masses. A novel technique then identifies Lagrangian matches between flight segments. Two independent searches are conducted: for Lagrangian model matches and for pairs of whole air samples with matching hydrocarbon fingerprints. The information is filtered further by searching for matching hydrocarbon samples that are linked by matching trajectories. The quality of these "coincident matches'' is assessed using temperature, humidity and tracer observations. The technique pulls out five clear Lagrangian cases covering a variety of situations and these are examined in detail. The matching trajectories and hydrocarbon fingerprints are shown, and the downwind minus upwind differences in tracers are discussed.

Linear viscoelasticity from molecular dynamics simulation of entangled polymers

The linear viscoelastic (LVE) spectrum is one of the primary fingerprints of polymer solutions and melts, carrying information about most relaxation processes in the system. Many single chain theories and models start with predicting the LVE spectrum to validate their assumptions. However, until now, no reliable linear stress relaxation data were available from simulations of multichain systems. In this work, we propose a new efficient way to calculate a wide variety of correlation functions and mean-square displacements during simulations without significant additional CPU cost. Using this method, we calculate stress−stress autocorrelation functions for a simple bead−spring model of polymer melt for a wide range of chain lengths, densities, temperatures, and chain stiffnesses. The obtained stress−stress autocorrelation functions were compared with the single chain slip−spring model in order to obtain entanglement related parameters, such as the plateau modulus or the molecular weight between entanglements. Then, the dependence of the plateau modulus on the packing length is discussed. We have also identified three different contributions to the stress relaxation:  bond length relaxation, colloidal and polymeric. Their dependence on the density and the temperature is demonstrated for short unentangled systems without inertia.

Characterisation of amorphous and nanocrystalline molecular materials by total scattering

The use of high-energy X-ray total scattering coupled with pair distribution function analysis produces unique structural fingerprints from amorphous and nanostructured phases of the pharmaceuticals carbamazepine and indomethacin. The advantages of such facility-based experiments over laboratory-based ones are discussed and the technique is illustrated with the characterisation of a melt-quenched sample of carbamazepine as a nanocrystalline (4.5 nm domain diameter) version of form III.

Diversity, phylogeny and distribution of bean rhizobia in salt-affected soils of North-West Morocco

Different molecular methods: BOX-PCR fingerprinting, R-FLP-PCR and sequencing of the 16S rDNA as well as the symbiotic genes nodC and nifH, were used to study the genetic diversity within a collection of nodulating bean rhizobia isolated from five soils of North-West Morocco. BOX fingerprints analysis of 241 isolates revealed 19 different BOX profiles. According to the PFLP-PCR and sequencing of 16S rDNA carried out on 45 representative isolates, 5 genotypes were obtained corresponding to the species Rhizobium etli, R. tropici, R. gallicum, R. leguminosarum and Sinorhizobium meliloti. The most abundant species were R. etli and R. tropici (61% and 24%, respectively). A high intraspecific diversity was observed among the R. etli isolates, while the R. tropici group was homogeneous. Most of the rhizobia studied belong to species known to nodulate common bean, while 2 species were unconventional microsymbionts: R. leguminosarum biovar viciae and S. meliloti. Our results, especially the nodulation promiscuity of common bean and the relation between the predominance of some species of rhizobia in particular soils and the salt content of these soils, indicate that there is a real need for a better understanding of the distribution of common bean rhizobia species in the soils of Morocco before any inoculation attempt.

Retention time prediction and protein identification

Proteins are commonly identified through enzymatic digestion and generation of short sequence tags or fingerprints of peptide masses by mass spectrometry. Separation methods, such as liquid chromatography and electrophoresis, are often used to fractionate complex protein or peptide mixtures and these separations also provide information on the different species, such as molecular weight and isoelectric point from electrophoresis and hydrophobicity in reversed-phase chromatography. These are also properties that can be predicted from amino acid sequences derived from genomic sequences and used in protein identification. This chapter reviews recently introduced methods based on retention time prediction to extract information from chromatographic separations and the applications to protein identification in organisms with small and large genomes. Novel data on retention time prediction of posttranslationally modified peptides is also presented.

Liquid ultraviolet matrix-assisted laser desorption/ionization - mass spectrometry for automated proteomic analysis

We have combined several key sample preparation steps for the use of a liquid matrix system to provide high analytical sensitivity in automated ultraviolet -- matrix-assisted laser desorption/ionisation -- mass spectrometry (UV-MALDI-MS). This new sample preparation protocol employs a matrix-mixture which is based on the glycerol matrix-mixture described by Sze et al. The low-femtomole sensitivity that is achievable with this new preparation protocol enables proteomic analysis of protein digests comparable to solid-state matrix systems. For automated data acquisition and analysis, the MALDI performance of this liquid matrix surpasses the conventional solid-state MALDI matrices. Besides the inherent general advantages of liquid samples for automated sample preparation and data acquisition the use of the presented liquid matrix significantly reduces the extent of unspecific ion signals in peptide mass fingerprints compared to typically used solid matrices, such as 2,5-dihydroxybenzoic acid (DHB) or alpha-cyano-hydroxycinnamic acid (CHCA). In particular, matrix and low-mass ion signals and ion signals resulting from cation adduct formation are dramatically reduced. Consequently, the confidence level of protein identification by peptide mass mapping of in-solution and in-gel digests is generally higher.

Liquid ultraviolet matrix-assisted laser desorption/ionization mass spectrometry for automated proteomic analysis

We have combined several key sample preparation steps for the use of a liquid matrix system to provide high analytical sensitivity in automated ultraviolet - matrix-assisted laser desorption/ ionisation - mass spectrometry (UV-MALDI-MS). This new sample preparation protocol employs a matrix-mixture which is based on the glycerol matrix-mixture described by Sze et al. U. Am. Soc. Mass Spectrom. 1998, 9, 166-174). The low-ferntomole sensitivity that is achievable with this new preparation protocol enables proteomic analysis of protein digests comparable to solid-state matrix systems. For automated data acquisition and analysis, the MALDI performance of this liquid matrix surpasses the conventional solid-state MALDI matrices. Besides the inherent general advantages of liquid samples for automated sample preparation and data acquisition the use of the presented liquid matrix significantly reduces the extent of unspecific ion signals in peptide mass fingerprints compared to typically used solid matrices, such as 2,5-dihydrox-ybenzoic acid (DHB) or alpha-cyano-hydroxycinnamic acid (CHCA). In particular, matrix and lowmass ion signals and ion signals resulting from cation adduct formation are dramatically reduced. Consequently, the confidence level of protein identification by peptide mass mapping of in-solution and in-gel digests is generally higher.

Proteome analysis for identification of target proteins of genistein in primary human endothelial cells stressed with oxidized LDL or homocysteine

Background Epidemiological studies suggest that soy consumption contributes to the prevention of coronary heart disease. The proposed anti-atherogenic effects of soy appear to be carried by the soy isoflavones with genistein as the most abundant compound. Aim of the study To identify proteins or pathways by which genistein might exert its protective activities on atherosclerosis, we analyzed the proteomic response of primary human umbilical vein endothelial cells ( HUVEC) that were exposed to the pro-atherosclerotic stressors homocysteine or oxidized low-density lipoprotein (ox-LDL). Methods HUVEC were incubated with physiological concentrations of homocysteine or ox-LDL in the absence and presence of genistein at concentrations that can be reached in human plasma by a diet rich in soy products (2.5 muM) or by pharmacological intervention ( 25 muM). Proteins from HUVEC were separated by two-dimensional polyacrylamide gel electrophoresis and those that showed altered expression level upon genistein treatment were identified by peptide mass fingerprints derived from tryptic digests of the protein spots. Results Several proteins were found to be differentially affected by genistein. The most interesting proteins that were potently decreased by homocysteine treatment were annexin V and lamin A. Annexin V is an antithrombotic molecule and mutations in nuclear lamin A have been found to result in perturbations of plasma lipids associated with hypertension. Genistein at low and high concentrations reversed the stressor-induced decrease of these anti-atherogenic proteins. Ox-LDL treatment of HUVEC resulted in an increase in ubiquitin conjugating enzyme 12, a protein involved in foam cell formation. Treatment with genistein at both doses reversed this effect. Conclusions Proteome analysis allows the identification of potential interactions of dietary components in the molecular process of atherosclerosis and consequently provides a powerful tool to define biomarkers of response.

Have greenhouse gases intensified the contrast between wet and dry regions?

While changes in land precipitation during the last 50 years have been attributed in part to human influences, results vary by season, are affected by data uncertainty and do not account for changes over ocean. One of the more physically robust responses of the water cycle to warming is the expected amplification of existing patterns of precipitation minus evaporation. Here, precipitation changes in wet and dry regions are analyzed from satellite data for 1988–2010, covering land and ocean. We derive fingerprints for the expected change from climate model simulations that separately track changes in wet and dry regions. The simulations used are driven with anthropogenic and natural forcings combined, and greenhouse gas forcing or natural forcing only. Results of detection and attribution analysis show that the fingerprint of combined external forcing is detectable in observations and that this intensification of the water cycle is partly attributable to greenhouse gas forcing.

Decreased monsoon precipitation in the Northern Hemisphere due to anthropogenic aerosols

The Northern Hemisphere monsoons are an integral component of Earth's hydrological cycle and affect the lives of billions of people. Observed precipitation in the monsoon regions underwent substantial changes during the second half of the 20th century, with drying from the 1950s to mid-1980s and increasing precipitation in recent decades. Modeling studies suggest anthropogenic aerosols has been a key factor driving changes in tropical and monsoon precipitation. Here we apply detection and attribution methods to determine whether observed changes are driven by human influences using fingerprints of individual forcings (i.e. greenhouse gas, anthropogenic aerosol and natural) derived from climate models. The results show that the observed changes can only be explained when including the influence of anthropogenic aerosols, even after accounting for internal climate variability. Anthropogenic aerosol, not greenhouse gas or natural forcing, has been the dominant influence on Northern Hemisphere monsoon precipitation over the second half of the 20th century.

An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation

Many previous studies have shown that unforced climate model simulations exhibit decadal-scale fluctuations in the Atlantic meridional overturning circulation (AMOC), and that this variability can have impacts on surface climate fields. However, the robustness of these surface fingerprints across different models is less clear. Furthermore, with the potential for coupled feedbacks that may amplify or damp the response, it is not known whether the associated climate signals are linearly related to the strength of the AMOC changes, or if the fluctuation events exhibit nonlinear behaviour with respect to their strength or polarity. To explore these questions, we introduce an objective and flexible method for identifying the largest natural AMOC fluctuation events in multicentennial/multimillennial simulations of a variety of coupled climate models. The characteristics of the events are explored, including their magnitude, meridional coherence and spatial structure, as well as links with ocean heat transport and the horizontal circulation. The surface fingerprints in ocean temperature and salinity are examined, and compared with the results of linear regression analysis. It is found that the regressions generally provide a good indication of the surface changes associated with the largest AMOC events. However, there are some exceptions, including a nonlinear change in the atmospheric pressure signal, particularly at high latitudes, in HadCM3. Some asymmetries are also found between the changes associated with positive and negative AMOC events in the same model. Composite analysis suggests that there are signals that are robust across the largest AMOC events in each model, which provides reassurance that the surface changes associated with one particular event will be similar to those expected from regression analysis. However, large differences are found between the AMOC fingerprints in different models, which may hinder the prediction and attribution of such events in reality.