253 research outputs found
Automatic Identification of Defects on Eggshell Through a Multispectral Vision System
The objective of this research was to develop an off-line artificial vision system to automatically detect defective eggshells, i.e., dirty or cracked eggshells, by employing multispectral images with the final purpose to adapt the system to an on-line grading machine. In particular, this work was focused to study the feasibility of identifying organic stains on brown eggshells (dirty eggshell), caused by blood, feathers, feces, etc., from natural stains, caused by deposits of pigments on the outer layer of clean eggshells. During the analysis a total of 384 eggs were evaluated (clean: 148, dirty: 236). Dirty samples were evaluated visually in order to classify them according to the kind of defect (blood, feathers, and white, clear or dark feces), and clean eggshells were classified on the basis of the colour of the natural stains (clear or dark). For each sample digital images were acquired by employing a Charged Coupled Device (CCD) camera endowed with 15 monochromatic filters (440-940 nm). A Matlab® function was developed in order to automate the process and analyze images, with the aim to classify samples as clean or dirty. The program was constituted by three major steps: first, the research of an opportune combination of monochromatic images in order to isolate the eggshell from the background; second, the detection of the dirt stains; third, the classification of the images samples into the dirty or clean group on the basis of geometric characteristics of the stains (area in pixel). The proposed classification algorithm was able to correctly classify near 98% of the samples with a very low processing time (0.05s). The robustness of the proposed classification was observed applying an external validation to a second set of samples (n = 178), obtaining similar percentage of correctly classified samples (97%)
Metal nanoparticles for microscopy and spectroscopy
Metal nanoparticles interact strongly with light due to a resonant response of their free electrons. These ‘plasmon’ resonances appear as very strong extinction and scattering for particular wavelengths, and result in high enhancements of the local field compared to the incident electric field. In this chapter we introduce the reader to the optical properties of single plasmon particles as well as finite clusters and periodic lattices, and discuss several applications
Self-assembly of Silver Nanoparticles and Multiwall Carbon Nanotubes on Decomposed GaAs Surfaces
Atomic Force Microscopy complemented by Photoluminescence and Reflection High Energy Electron Diffraction has been used to study self-assembly of silver nanoparticles and multiwall carbon nanotubes on thermally decomposed GaAs (100) surfaces. It has been shown that the decomposition leads to the formation of arsenic plate-like structures. Multiwall carbon nanotubes spin coated on the decomposed surfaces were mostly found to occupy the depressions between the plates and formed boundaries. While direct casting of silver nanoparticles is found to induce microdroplets. Annealing at 300°C was observed to contract the microdroplets into combined structures consisting of silver spots surrounded by silver rings. Moreover, casting of colloidal suspension consists of multiwall carbon nanotubes and silver nanoparticles is observed to cause the formation of 2D compact islands. Depending on the multiwall carbon nanotubes diameter, GaAs/multiwall carbon nanotubes/silver system exhibited photoluminescence with varying strength. Such assembly provides a possible bottom up facile way of roughness controlled fabrication of plasmonic systems on GaAs surfaces
Genetic Analysis of HIV-1 Subtypes in Nairobi, Kenya
Background: Genetic analysis of a viral infection helps in following its spread in a given population, in tracking the routes of infection and, where applicable, in vaccine design. Additionally, sequence analysis of the viral genome provides information about patterns of genetic divergence that may have occurred during viral evolution.
Objective: In this study we have analyzed the subtypes of Human Immunodeficiency Virus -1 (HIV-1) circulating in a diverse sample population of Nairobi, Kenya.
Methodology: 69 blood samples were collected from a diverse subject population attending the Aga Khan University Hospital in Nairobi, Kenya. Total DNA was extracted from peripheral blood mononuclear cells (PBMCs), and used in a Polymerase Chain Reaction (PCR) to amplify the HIV gag gene. The PCR amplimers were partially sequenced, and alignment and phylogenetic analysis of these sequences was performed using the Los Alamos HIV Database.
Results: Blood samples from 69 HIV-1 infected subjects from varying ethnic backgrounds were analyzed. Sequence alignment and phylogenetic analysis showed 39 isolates to be subtype A, 13 subtype D, 7 subtype C, 3 subtype AD and CRF01_AE, 2 subtype G and 1 subtype AC and 1 AG. Deeper phylogenetic analysis revealed HIV subtype A sequences to be highly divergent as compared to subtypes D and C.
Conclusion: Our analysis indicates that HIV-1 subtypes in the Nairobi province of Kenya are dominated by a genetically diverse clade A. Additionally, the prevalence of highly divergent, complex subtypes, intersubtypes, and the recombinant forms indicates viral mixing in Kenyan population, possibly as a result of dual infections
Comparative Toxicity of Nanoparticulate CuO and ZnO to Soil Bacterial Communities
The increasing industrial application of metal oxide Engineered Nano-Particles (ENPs) is likely to increase their environmental release to soils. While the potential of metal oxide ENPs as environmental toxicants has been shown, lack of suitable control treatments have compromised the power of many previous assessments. We evaluated the ecotoxicity of ENP (nano) forms of Zn and Cu oxides in two different soils by measuring their ability to inhibit bacterial growth. We could show a direct acute toxicity of nano-CuO acting on soil bacteria while the macroparticulate (bulk) form of CuO was not toxic. In comparison, CuSO4 was more toxic than either oxide form. Unlike Cu, all forms of Zn were toxic to soil bacteria, and the bulk-ZnO was more toxic than the nano-ZnO. The ZnSO4 addition was not consistently more toxic than the oxide forms. Consistently, we found a tight link between the dissolved concentration of metal in solution and the inhibition of bacterial growth. The inconsistent toxicological response between soils could be explained by different resulting concentrations of metals in soil solution. Our findings suggested that the principal mechanism of toxicity was dissolution of metal oxides and sulphates into a metal ion form known to be highly toxic to bacteria, and not a direct effect of nano-sized particles acting on bacteria. We propose that integrated efforts toward directly assessing bioavailable metal concentrations are more valuable than spending resources to reassess ecotoxicology of ENPs separately from general metal toxicity
The Effects of Biting and Pulling on the Forces Generated during Feeding in the Komodo Dragon (Varanus komodoensis)
In addition to biting, it has been speculated that the forces resulting from pulling on food items may also contribute to feeding success in carnivorous vertebrates. We present an in vivo analysis of both bite and pulling forces in Varanus komodoensis, the Komodo dragon, to determine how they contribute to feeding behavior. Observations of cranial modeling and behavior suggest that V. komodoensis feeds using bite force supplemented by pulling in the caudal/ventrocaudal direction. We tested these observations using force gauges/transducers to measure biting and pulling forces. Maximum bite force correlates with both body mass and total body length, likely due to increased muscle mass. Individuals showed consistent behaviors when biting, including the typical medial-caudal head rotation. Pull force correlates best with total body length, longer limbs and larger postcranial motions. None of these forces correlated well with head dimensions. When pulling, V. komodoensis use neck and limb movements that are associated with increased caudal and ventral oriented force. Measured bite force in Varanus komodoensis is similar to several previous estimations based on 3D models, but is low for its body mass relative to other vertebrates. Pull force, especially in the ventrocaudal direction, would allow individuals to hunt and deflesh with high success without the need of strong jaw adductors. In future studies, pull forces need to be considered for a complete understanding of vertebrate carnivore feeding dynamics
Structural and Functional Insights into Endoglin Ligand Recognition and Binding
Endoglin, a type I membrane glycoprotein expressed as a disulfide-linked homodimer on human vascular endothelial cells, is a component of the transforming growth factor (TGF)-β receptor complex and is implicated in a dominant vascular dysplasia known as hereditary hemorrhagic telangiectasia as well as in preeclampsia. It interacts with the type I TGF-β signaling receptor activin receptor-like kinase (ALK)1 and modulates cellular responses to Bone Morphogenetic Protein (BMP)-9 and BMP-10. Structurally, besides carrying a zona pellucida (ZP) domain, endoglin contains at its N-terminal extracellular region a domain of unknown function and without homology to any other known protein, therefore called the orphan domain (OD). In this study, we have determined the recognition and binding ability of full length ALK1, endoglin and constructs encompassing the OD to BMP-9 using combined methods, consisting of surface plasmon resonance and cellular assays. ALK1 and endoglin ectodomains bind, independently of their glycosylation state and without cooperativity, to different sites of BMP-9. The OD comprising residues 22 to 337 was identified among the present constructs as the minimal active endoglin domain needed for partner recognition. These studies also pinpointed to Cys350 as being responsible for the dimerization of endoglin. In contrast to the complete endoglin ectodomain, the OD is a monomer and its small angle X-ray scattering characterization revealed a compact conformation in solution into which a de novo model was fitted
Social navigation
In this chapter we present one of the pioneer approaches in supporting users in navigating the complex information spaces, social navigation support. Social navigation support is inspired by natural tendencies of individuals to follow traces of each other in exploring the world, especially when dealing with uncertainties. In this chapter, we cover details on various approaches in implementing social navigation support in the information space as we also connect the concept to supporting theories. The first part of this chapter reviews related theories and introduces the design space of social navigation support through a series of example applications. The second part of the chapter discusses the common challenges in design and implementation of social navigation support, demonstrates how these challenges have been addressed, and reviews more recent direction of social navigation support. Furthermore, as social navigation support has been an inspirational approach to various other social information access approaches we discuss how social navigation support can be integrated with those approaches. We conclude with a review of evaluation methods for social navigation support and remarks about its current state
Ecological networks: Pursuing the shortest path, however narrow and crooked
International audienceRepresenting data as networks cuts across all sub-disciplines in ecology and evolutionary biology. Besides providing a compact representation of the interconnections between agents, network analysis allows the identification of especially important nodes, according to various metrics that often rely on the calculation of the shortest paths connecting any two nodes. While the interpretation of a shortest paths is straightforward in binary, unweighted networks, whenever weights are reported, the calculation could yield unexpected results. We analyzed 129 studies of ecological networks published in the last decade that use shortest paths, and discovered a methodological inaccuracy related to the edge weights used to calculate shortest paths (and related centrality measures), particularly in interaction networks. Specifically, 49% of the studies do not report sufficient information on the calculation to allow their replication, and 61% of the studies on weighted networks may contain errors in how shortest paths are calculated. Using toy models and empirical ecological data, we show how to transform the data prior to calculation and illustrate the pitfalls that need to be avoided. We conclude by proposing a five-point checklist to foster best-practices in the calculation and reporting of centrality measures in ecology and evolution studies. The last two decades have witnessed an exponential increase in the use of graph analysis in ecological and conservation studies (see refs. 1,2 for recent introductions to network theory in ecology and evolution). Networks (graphs) represent agents as nodes linked by edges representing pairwise relationships. For instance, a food web can be represented as a network of species (nodes) and their feeding relationships (edges) 3. Similarly, the spatial dynamics of a metapopulation can be analyzed by connecting the patches of suitable habitat (nodes) with edges measuring dispersal between patches 4. Data might either simply report the presence/absence of an edge (binary, unweighted networks), or provide a strength for each edge (weighted networks). In turn, these weights can represent a variety of ecologically-relevant quantities, depending on the system being described. For instance, edge weights can quantify interaction frequency (e.g., visitation networks 5), interaction strength (e.g., per-capita effect of one species on the growth rate of another 3), carbon-flow between trophic levels 6 , genetic similarity 7 , niche overlap (e.g., number of shared resources between two species 8), affinity 9 , dispersal probabilities (e.g., the rate at which individuals of a population move between patches 10), cost of dispersal between patches (e.g., resistance 11), etc. Despite such large variety of ecological network representations, a common task is the identification of nodes of high importance, such as keystone species in a food web, patches acting as stepping stones in a dispersal network , or genes with pleiotropic effects. The identification of important nodes is typically accomplished through centrality measures 5,12. Many centrality measures has been proposed, each probing complementary aspects of node-to-node relationships 13. For instance, Closeness centrality 14,15 highlights nodes that are "near" to all othe
Fungal enzyme sets for plant polysaccharide degradation
Enzymatic degradation of plant polysaccharides has many industrial applications, such as within the paper, food, and feed industry and for sustainable production of fuels and chemicals. Cellulose, hemicelluloses, and pectins are the main components of plant cell wall polysaccharides. These polysaccharides are often tightly packed, contain many different sugar residues, and are branched with a diversity of structures. To enable efficient degradation of these polysaccharides, fungi produce an extensive set of carbohydrate-active enzymes. The variety of the enzyme set differs between fungi and often corresponds to the requirements of its habitat. Carbohydrate-active enzymes can be organized in different families based on the amino acid sequence of the structurally related catalytic modules. Fungal enzymes involved in plant polysaccharide degradation are assigned to at least 35 glycoside hydrolase families, three carbohydrate esterase families and six polysaccharide lyase families. This mini-review will discuss the enzymes needed for complete degradation of plant polysaccharides and will give an overview of the latest developments concerning fungal carbohydrate-active enzymes and their corresponding families
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