A novel approach to explicitly model the spatiotemporal impacts of structural complexity created by alien ecosystem engineers in a marine benthic environment

2021 ◽  
Vol 459 ◽  
pp. 109731
Author(s):  
Saachi Sadchatheeswaran ◽  
George M. Branch ◽  
Lynne J. Shannon ◽  
Marta Coll ◽  
Jeroen Steenbeek
Keyword(s):  
Structural Complexity ◽  
Ecosystem Engineers ◽  
Novel Approach ◽  
Benthic Environment

scholarly journals Analysis of a large food chemical database: chemical space, diversity, and complexity

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 993 ◽  
Author(s):  
J. Jesús Naveja ◽  
Mariel P. Rico-Hidalgo ◽  
José L. Medina-Franco
Keyword(s):  
Natural Products ◽  
Chemical Space ◽  
Structural Complexity ◽  
Chemical Diversity ◽  
Chemical Structures ◽  
Novel Approach ◽  
Chemical Database ◽  
Protein Interactome ◽  
Limited Basis ◽  
Future Direction

Background: Food chemicals are a cornerstone in the food industry. However, its chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related databases were done up to 2,200 molecules. The goal of this work was to quantify the chemical diversity of chemical compounds stored in FooDB, a database with nearly 24,000 food chemicals. Methods: The visual representation of the chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of chemical satellites. The large food chemical database was profiled based on physicochemical properties, molecular complexity and scaffold content. The global diversity of FooDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other databases. Conclusions: To the best of our knowledge, this is the first analysis of the chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the chemical structures of the molecules in FooDB with other compound databases, for instance, drug-like databases and natural products collections. An additional future direction of this work is to use the list of 3,228 polyphenolic compounds identified in this work to enhance the on-going polyphenol-protein interactome studies.

scholarly journals Quality Monitoring of Assembled Products by Defect Prediction Models

2021 ◽  
Author(s):  
Elisa Verna ◽  
Gianfranco Genta ◽  
Maurizio Galetto ◽  
Fiorenzo Franceschini
Keyword(s):  
Experimental Data ◽  
Control Charts ◽  
Prediction Models ◽  
Structural Complexity ◽  
Defect Prediction ◽  
Production Volume ◽  
Industrial Case Study ◽  
Novel Approach ◽  
Low Volume ◽  
Defect Prediction Models

Abstract Typically, monitoring quality characteristics of very personalized products is a difficult task due to the lack of experimental data. This is the typical case of processes where the production volume continues to shrink due to the growing complexity and customization of products, thus requiring low-volume productions. This paper presents a novel approach to statistically monitor Defects Per Unit (DPU) of assembled products based on the use of defect prediction models. Unlike traditional control charts requiring preliminary experimental data to estimate the control limits (phase I), the proposed DPU-chart is constructed using a predictive model based on a priori knowledge of DPU. This defect prediction model is built on the structural complexity of assembled product. The novel approach may be of interest to researchers and practitioners to speed up the construction of the chart, especially in cases of low-volume productions due to the limited amount of data. The description of the method is supported by a real industrial case study in the electromechanical field.

scholarly journals Defects-per-unit control chart for assembled products based on defect prediction models

2021 ◽  
Author(s):  
Elisa Verna ◽  
Gianfranco Genta ◽  
Maurizio Galetto ◽  
Fiorenzo Franceschini
Keyword(s):  
Experimental Data ◽  
Phase I ◽  
Prediction Models ◽  
Structural Complexity ◽  
Defect Prediction ◽  
Production Volume ◽  
Industrial Case Study ◽  
Novel Approach ◽  
Low Volume ◽  
Defect Prediction Models

AbstractTypically, monitoring quality characteristics of very personalized products is a difficult task due to the lack of experimental data. This is the typical case of processes where the production volume continues to shrink due to the growing complexity and customization of products, thus requiring low-volume productions. This paper presents a novel approach to statistically monitor defects-per-unit (DPU) of assembled products based on the use of defect prediction models. The innovative aspect of such DPU-chart is that, unlike conventional SPC charts requiring preliminary experimental data to estimate the control limits (phase I), it is constructed using a predictive model based on a priori knowledge of DPU. This defect prediction model is based on the structural complexity of the assembled product. By avoiding phase I, the novel approach may be of interest to researchers and practitioners to speed up the chart’s construction phase, especially in low-volume productions. The description of the method is supported by a real industrial case study in the electromechanical field.

Do the abundance, diversity, and community structure of sediment meiofauna differ among seagrass species?

2015 ◽  
pp. 1-11
Author(s):  
Jian-Xiang Liao ◽  
Hsin-Ming Yeh ◽  
Hin-Kiu Mok
Keyword(s):  
Ecosystem Engineer ◽  
Structural Complexity ◽  
Nematode Species ◽  
Small Scale ◽  
Seagrass Species ◽  
Thalassia Hemprichii ◽  
Halophila Ovalis ◽  
Deposit Feeders ◽  
Benthic Environment ◽  
Abundance And Diversity

The structural complexity of macrophytes that provide various microhabitats is related to local infaunal abundance and diversity. Seagrass is considered an ecosystem engineer that alters the benthic environment and enables certain distinct meiofauna to thrive in sediments. The effects of seagrass species in a mixed-species seagrass bed at Haikou, Taiwan were examined. Analysing quantitative samples obtained from patches ofThalassia hemprichii, Halodule uninervis, Halophila ovalisand adjacent unvegetated sediments inspected the community structures of meiofauna and marine nematodes. The abundance and diversity of crustaceans and nematodes were substantially higher in habitats in which seagrass grew than in those comprising unvegetated sediments. Both the compositions of higher meiofaunal taxa and nematode species were distinct between seagrass habitats and unvegetated areas. Several nematode species existed exclusively in patches of individual seagrass species, whereas no nematode specifically occurred in unvegetated areas. Regarding the trophic types of nematodes, non-selective deposit feeders were prevalent in the present study, whereas selective deposit feeders and epistrate feeders were relatively dominant in seagrass habitats. Sediments underneath various patches of seagrass species harbour dissimilar nematode communities, even with similar sediment parameters and at a small-scale distance.

scholarly journals Defect Prediction For Assembled Products: A Novel Model Based On The Structural Complexity Paradigm

2021 ◽  
Author(s):  
Elisa Verna ◽  
Gianfranco Genta ◽  
Maurizio Galetto ◽  
Fiorenzo Franceschini
Keyword(s):  
Objective Assessment ◽  
Structural Complexity ◽  
Objective Evaluation ◽  
Industrial Applications ◽  
Defect Prediction ◽  
The Novel ◽  
Subjective Knowledge ◽  
Design And Optimization ◽  
Novel Approach ◽  
Novel Model

Abstract Increased assembly complexity is one of the main challenges in manufacturing. Complexity can induce increased assembly cost and time, operational issues, costly defects and quality losses. Several approaches have been proposed in the literature to predict product defects by using assembly complexity as predictor. Despite defect prediction is of utmost importance from the early stages of product and related quality inspection design, most approaches are not directly applicable because they rely on the operators' prior subjective knowledge and are designed for specific industrial applications. To overcome this issue, the present research proposes a novel approach to predict product defects from a more objective evaluation of complexity. This is one of the first attempts to predict product defects and improve its quality with a purely objective assessment of the complexity of the assembled product, without the need for operators' evaluations and assembly experience. Defect rates in the model are predicted by using a recent conceptual paradigm of complexity that considers only structural properties of assembly parts and their architectural structure. The novel model is applied to a real assembly process in the electromechanical field and is compared with one of the most accredited in the literature, i.e. the Shibata-Su model. Empirical results show that, despite the super-linear relationship between defect rates and complexity in both models, the objective approach used in the novel model leads to more accurate and precise predictions of defectiveness rates, as it does not include the variability introduced by operators' subjective assessments. Adopting this novel model can effectively improve the estimate of product defects and support designers’ decisions for assembly quality-oriented design and optimization, especially in early design phases.

scholarly journals Computational image analysis reveals the structural complexity of Toxoplasma gondii tissue cysts

2020 ◽  
Author(s):  
Neda Bauman ◽  
Andjelija Ilić ◽  
Olivera Lijeskić ◽  
Aleksandra Uzelac ◽  
Ivana Klun ◽  
...  
Keyword(s):  
Image Analysis ◽  
Toxoplasma Gondii ◽  
Fractal Analysis ◽  
Structural Complexity ◽  
Particle Analysis ◽  
Particle Count ◽  
Novel Approach ◽  
Brain Cysts ◽  
Computational Image Analysis

AbstractToxoplasma gondii is an obligate intracellular parasite infecting up to one third of the human population. The central event in the pathogenesis of toxoplasmosis is the conversion of tachyzoites into encysted bradyzoites. A novel approach to analyze the structure of in vivo-derived tissue cysts may be the increasingly used computational image analysis. The objective of this study was to quantify the geometrical complexity of T. gondii cysts by morphological, particle, and fractal analysis, as well as to determine if and how it is impacted by parasite strain, cyst age, and host factors. Analyses were performed on 31 images of T. gondii brain cysts of four type-2 strains (the reference Me49 strain and three local isolates, named BGD1, BGD14, and BGD26) using ImageJ software package. The parameters of interest included diameter, circularity, relative particle count (RPC), fractal dimension (FD), lacunarity, and packing density (PD). Although cyst diameter varied widely, its negative correlation with RPC was observed. Circularity was remarkably close to 1, indicating that the shape of the brain cysts was a perfect circle. RPC, FD, and PD did not vary among cysts of different strains, age, and derived from mice of different genetic background. Conversely, lacunarity, which is a measure of heterogeneity, was significantly lower for BGD1 strain vs. all other strains, and higher for Me49 vs. BGD14 and BGD26, but did not differ among Me49 cysts of different age, and derived from genetically different mice. This study is the first application of fractal analysis in describing the structural complexity of T. gondii cysts. Despite all the differences among the analyzed cysts, most parameters remained conserved. Fractal analysis is a novel and widely accessible approach, which along with particle analysis may be applied to gain further insight into T. gondii cyst morphology.

scholarly journals Analysis of a large food chemical database: chemical space, diversity, and complexity

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 993 ◽  
Author(s):  
J. Jesús Naveja ◽  
Mariel P. Rico-Hidalgo ◽  
José L. Medina-Franco
Keyword(s):  
Natural Products ◽  
Chemical Space ◽  
Structural Complexity ◽  
Chemical Compounds ◽  
Chemical Diversity ◽  
Chemical Structures ◽  
Novel Approach ◽  
Chemical Database ◽  
Molecular Complexity ◽  
Limited Basis

Background: Food chemicals are a cornerstone in the food industry. However, its chemical diversity has been explored on a limited basis, for instance, previous analysis of food-related databases were done up to 2,200 molecules. The goal of this work was to quantify the chemical diversity of chemical compounds stored in FooDB, a database with nearly 24,000 food chemicals. Methods: The visual representation of the chemical space of FooDB was done with ChemMaps, a novel approach based on the concept of chemical satellites. The large food chemical database was profiled based on physicochemical properties, molecular complexity and scaffold content. The global diversity of FoodDB was characterized using Consensus Diversity Plots. Results: It was found that compounds in FooDB are very diverse in terms of properties and structure, with a large structural complexity. It was also found that one third of the food chemicals are acyclic molecules and ring-containing molecules are mostly monocyclic, with several scaffolds common to natural products in other databases. Conclusions: To the best of our knowledge, this is the first analysis of the chemical diversity and complexity of FooDB. This study represents a step further to the emerging field of “Food Informatics”. Future study should compare directly the chemical structures of the molecules in FooDB with other compound databases, for instance, drug-like databases and natural products collections.

scholarly journals The positive effect of coexisting ecosystem engineers: a unique seaweed-mussel association provides refuge for native mud crabs against a non-indigenous predator

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10540
Author(s):  
Paula Tummon Flynn ◽  
Keegan McCarvill ◽  
K. Devon Lynn ◽  
Pedro A. Quijón
Keyword(s):  
Native Species ◽  
Blue Mussel ◽  
Survival Rates ◽  
Carcinus Maenas ◽  
Structural Complexity ◽  
Ecosystem Engineers ◽  
Community Context ◽  
Mud Crab ◽  
Irish Moss ◽  
The Impact

In marine sedimentary bottoms, mussels and macroalgae have long been recognized as important autogenic engineers that create habitat and modify abiotic conditions. The structural complexity added by bivalves and macroalgae may also mediate intraguild predation amongst marine decapod crustaceans. While spatial distributions of these ecosystem engineers frequently overlap, there is limited understanding of compounded effects when more than one engineer is present. Here we demonstrate that the coexistence of two ecosystem engineers may create habitat valuable for the survival of a small native species, the Atlantic mud crab (Panopeus herbstii), in the presence of the invasive green crab (Carcinus maenas). Using laboratory and field habitat mimics, we measured mud crab survival rates as a proxy for refuge quality. We compared the refuge provided by a unique association between shells of blue mussels (Mytilus edulis) and the giant strain of Irish moss (Chondrus crispus) to that provided by bare substrate, and by each engineer alone. These experiments revealed that the association of giant Irish moss with blue mussel shells positively and non-additively increased mud crab survival compared to the other less complex habitat mimics. In contrast, parallel experiments revealed that high habitat complexity was less important for young green crabs to survive predation from large conspecifics. These results suggest that the impact of ecosystem engineers on trophic dynamics should be considered in a broader, whole-community context encompassing multiple habitat-forming species present.

Conformation of eukaryotic ribosomal RNAs

1983 ◽  
Vol 41 ◽  
pp. 592-593
Author(s):  
M. Boublik ◽  
G. Thornton ◽  
G. Oostergetel ◽  
J.F. Hainfeld ◽  
J.S. Wall
Keyword(s):  
Molecular Weight ◽  
Mass Measurement ◽  
Carbon Film ◽  
Structural Complexity ◽  
Scanning Transmission Electron Microscope ◽  
Electron Microscopic ◽  
Pure Nitrogen ◽  
Freeze Dried ◽  
Scanning Transmission ◽  
Partially Unfolded

Understanding the structural complexity of ribosomes and their role in protein synthesis requires knowledge of the conformation of their components - rRNAs and proteins. Application of dedicated scanning transmission electron microscope (STEM), electrical discharge of the support carbon film in an atmosphere of pure nitrogen, and determination of the molecular weight of individual rRNAs enabled us to obtain high resolution electron microscopic images of unstained freeze-dried rRNA molecules from BHK cells in a form suitable for evaluation of their 3-D structure. Preliminary values for the molecular weight of 28S RNA from the large and 18S RNA from the small ribosomal subunits as obtained by mass measurement were 1.84 x 106 and 0.97 x 106, respectively. Conformation of rRNAs consists, in general, of alternating segments of intramolecular hairpin stems and single stranded loops in a proportion which depends on their ionic environment, the Mg++ concentration in particular. Molecules of 28S RNA (Fig. 1) and 18S RNA (not shown) obtained by freeze-drying from a solution of 60 mM NH+4 acetate and 2 mM Mg++ acetate, pH 7, appear as partially unfolded coils with compact cores suggesting a high degree of ordered secondary structure.

Observations of Frozen-Hydrated Microtubules

1990 ◽  
Vol 48 (1) ◽  
pp. 504-505
Author(s):  
D. Chrétien ◽  
D. Job ◽  
R.H. Wade
Keyword(s):  
Fourier Transforms ◽  
Structural Complexity ◽  
Image Contrast ◽  
Phase Behaviour ◽  
Experimental Conditions ◽  
Thin Sections ◽  
Surface Lattice ◽  
Cilia And Flagella ◽  
Outstanding Question

Microtubules are filamentary structures found in the cytoplasm of eukaryotic cells, where, together with actin and intermediate filaments, they form the components of the cytoskeleton. They have many functions and show various levels of structural complexity as witnessed by the singlet, doublet and triplet structures involved in the architecture of centrioles, basal bodies, cilia and flagella. The accepted microtubule model consists of a 25 nm diameter hollow tube with a wall made up of 13 paraxial protofilaments (pf). Each pf is a string of aligned tubulin dimers. Some results have suggested that the pfs follow a superhelix. To understand how microtubules function in the cell an accurate model of the surface lattice is one of the requirements. For example the 9x2 architecture of the axoneme will depend on the organisation of its component microtubules. We should also note that microtubules with different numbers of pfs have been observed in thin sections of cellular and of in-vitro material. An outstanding question is how does the surface lattice adjust to these different pf numbers?We have been using cryo-electron microscopy of frozen-hydrated samples to study in-vitro assembled microtubules. The experimental conditions are described in detail in this reference. The results obtained in conjunction with thin sections of similar specimens and with axoneme outer doublet fragments have already allowed us to characterise the image contrast of 13, 14 and 15 pf microtubules on the basis of the measured image widths, of the the image contrast symmetry and of the amplitude and phase behaviour along the equator in the computed Fourier transforms. The contrast variations along individual microtubule images can be interpreted in terms of the geometry of the microtubule surface lattice. We can extend these results and make some reasonable predictions about the probable surface lattices in the case of other pf numbers, see Table 1. Figure 1 shows observed images with which these predictions can be compared.

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