Adaptive-Curvature Structures with Auxetic Materials

2018 ◽  
Vol 1149 ◽  
pp. 53-63
Author(s):  
Roberto Naboni ◽  
Stefano Sartori ◽  
Lorenzo Mirante
Keyword(s):  
Large Scale ◽  
Morphological Features ◽  
Geometrical Parameters ◽  
Computational Tools ◽  
Auxetic Materials ◽  
Initial Geometry ◽  
Tools And Methods

Advancements in computational tools are offering designers the possibility to change their relationship with materials and establishing new synergies between matter, form and behaviour. This work explores this paradigm by introducing the use of auxetic metamaterials, specifically engineered to obtain properties beyond those found in nature, to generate structures with adaptive curvature obtained from planar construction elements. It is discussed how through programming an initial geometry with the strategic negotiation of several geometrical parameters it is possible to control finely the structural and morphological features of a structure. The paper presents approach, tools and methods for designing auxetics for large scale applications, and use them to create heterogeneous active-bending structures.

Molecular Design of Peptide-Fc Fusion Drugs

2019 ◽  
Vol 20 (3) ◽  
pp. 203-208 ◽  
Author(s):  
Lin Ning ◽  
Bifang He ◽  
Peng Zhou ◽  
Ratmir Derda ◽  
Jian Huang
Keyword(s):  
Rational Design ◽  
Molecular Design ◽  
Computational Design ◽  
Fusion Technology ◽  
Computational Tools ◽  
Open Questions ◽  
Biological Therapeutics ◽  
Key Steps ◽  
Computational Resources ◽  
Tools And Methods

Background:Peptide-Fc fusion drugs, also known as peptibodies, are a category of biological therapeutics in which the Fc region of an antibody is genetically fused to a peptide of interest. However, to develop such kind of drugs is laborious and expensive. Rational design is urgently needed.Methods:We summarized the key steps in peptide-Fc fusion technology and stressed the main computational resources, tools, and methods that had been used in the rational design of peptide-Fc fusion drugs. We also raised open questions about the computer-aided molecular design of peptide-Fc.Results:The design of peptibody consists of four steps. First, identify peptide leads from native ligands, biopanning, and computational design or prediction. Second, select the proper Fc region from different classes or subclasses of immunoglobulin. Third, fuse the peptide leads and Fc together properly. At last, evaluate the immunogenicity of the constructs. At each step, there are quite a few useful resources and computational tools.Conclusion:Reviewing the molecular design of peptibody will certainly help make the transition from peptide leads to drugs on the market quicker and cheaper.

scholarly journals Advances in decomposing complex metabolite mixtures using substructure- and network-based computational metabolomics approaches

2021 ◽  
Author(s):  
Mehdi A. Beniddir ◽  
Kyo Bin Kang ◽  
Grégory Genta-Jouve ◽  
Florian Huber ◽  
Simon Rogers ◽  
...  
Keyword(s):  
Natural Product ◽  
Large Scale ◽  
Scale Analysis ◽  
Computational Tools ◽  
Natural Product Discovery ◽  
Large Scale Analysis ◽  
Metabolite Annotation

This review highlights the key computational tools and emerging strategies for metabolite annotation, and discusses how these advances will enable integrated large-scale analysis to accelerate natural product discovery.

scholarly journals The daunting polygenicity of mental illness: making a new map

2018 ◽  
Vol 373 (1742) ◽  
pp. 20170031 ◽  
Author(s):  
Steven E. Hyman
Keyword(s):  
Mental Health ◽  
Large Scale ◽  
Computational Models ◽  
Model Organisms ◽  
Human Biology ◽  
Genetic Studies ◽  
Computational Tools ◽  
Experimental Systems ◽  
Terra Incognita ◽  
Phenotypic Complexity

An epochal opportunity to elucidate the pathogenic mechanisms of psychiatric disorders has emerged from advances in genomic technology, new computational tools and the growth of international consortia committed to data sharing. The resulting large-scale, unbiased genetic studies have begun to yield new biological insights and with them the hope that a half century of stasis in psychiatric therapeutics will come to an end. Yet a sobering picture is coming into view; it reveals daunting genetic and phenotypic complexity portending enormous challenges for neurobiology. Successful exploitation of results from genetics will require eschewal of long-successful reductionist approaches to investigation of gene function, a commitment to supplanting much research now conducted in model organisms with human biology, and development of new experimental systems and computational models to analyse polygenic causal influences. In short, psychiatric neuroscience must develop a new scientific map to guide investigation through a polygenic terra incognita . This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’.

scholarly journals TADOSS: computational estimation of tandem domain swap stability

2018 ◽  
Vol 35 (14) ◽  
pp. 2507-2508 ◽  
Author(s):  
Aleix Lafita ◽  
Pengfei Tian ◽  
Robert B Best ◽  
Alex Bateman
Keyword(s):  
Large Scale ◽  
Domain Swapping ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Simulation Studies ◽  
Computational Tools ◽  
Domain Swap ◽  
Computational Estimation ◽  
High Propensity ◽  
The Stability

Abstract Summary Proteins with highly similar tandem domains have shown an increased propensity for misfolding and aggregation. Several molecular explanations have been put forward, such as swapping of adjacent domains, but there is a lack of computational tools to systematically analyze them. We present the TAndem DOmain Swap Stability predictor (TADOSS), a method to computationally estimate the stability of tandem domain-swapped conformations from the structures of single domains, based on previous coarse-grained simulation studies. The tool is able to discriminate domains susceptible to domain swapping and to identify structural regions with high propensity to form hinge loops. TADOSS is a scalable method and suitable for large scale analyses. Availability and implementation Source code and documentation are freely available under an MIT license on GitHub at https://github.com/lafita/tadoss. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals The influence of cactus spine surface structure on puncture performance and anchoring ability is tuned for ecology

2018 ◽  
Vol 285 (1891) ◽  
pp. 20182280 ◽  
Author(s):  
S. B. Crofts ◽  
P. S. L. Anderson
Keyword(s):  
Surface Structure ◽  
Large Scale ◽  
Biological Materials ◽  
Morphological Features ◽  
Ecological Functions ◽  
Defensive Mechanisms ◽  
Evolutionary Convergence ◽  
Almost All

Spines are common morphological features found in almost all major biological groups offering an opportunity to explore large-scale evolutionary convergence across disparate clades. As an example, opuntioid cacti have spines with barbed ornamentation that is remarkably similar in form and scale to that found on porcupine quills, suggesting specific biomechanical convergence across the animal and plant kingdoms. While the mechanics of porcupine quills as defensive mechanisms has been previously tested, the mechanics of cactus spines (which have evolved to fill a number of functions including defence, climbing and dispersal) has not been characterized. Here we study the puncturing and anchoring ability of six species of cactus, including both barbed and non-barbed spines. We found that barbed spines require less work to puncture a variety of targets than non-barbed spines. Barbed spines also require more work than non-barbed spines to withdraw from biological materials, owing to their barbs engaging with tissue fibres. These results closely match those found previously for barbed versus non-barbed porcupine quills, implying biomechanical convergence. The variation in performance of barbed versus non-barbed spines, as well as between barbed spines from different species, is probably tied to the diversity of ecological functions of cactus spines.

scholarly journals REVA as a Well-curated Database for Human Expression-modulating Variants

2021 ◽  
Author(s):  
Yu Wang ◽  
Fang-Yuan Shi ◽  
Yu Liang ◽  
Ge Gao
Keyword(s):  
Large Scale ◽  
Regulatory Mechanism ◽  
State Of The Art ◽  
Scale Analysis ◽  
Computational Tools ◽  
Functional Annotations ◽  
Link Type ◽  
Large Scale Analysis ◽  
Multiple State ◽  
Limited Sensitivity

AbstractMore than 80% of disease- and trait-associated human variants are noncoding. By systematically screening multiple large-scale studies, we compiled REVA, a manually curated database for over 11.8 million experimentally tested noncoding variants with expression-modulating potentials. We provided 2424 functional annotations that could be used to pinpoint plausible regulatory mechanism of these variants. We further benchmarked multiple state-of-the-art computational tools and found their limited sensitivity remains a serious challenge for effective large-scale analysis. REVA provides high-qualify experimentally tested expression-modulating variants with extensive functional annotations, which will be useful for users in the noncoding variants community. REVA is available at http://reva.gao-lab.org.

Experiments on Gas Mixing and Stratification Driven by Jets and Plumes in Large-Scale, Multi-Compartment Geometries

2006 ◽  
Author(s):  
Robert Zboray ◽  
Domenico Paladino ◽  
Olivier Auban
Keyword(s):  
High Resolution ◽  
Time Evolution ◽  
Large Scale ◽  
Nuclear Reactor ◽  
Safety Analysis ◽  
Mixing Process ◽  
Gas Mixing ◽  
Computational Tools ◽  
Different Gases

The present paper discusses experiments carried out to examine mixing of different gases (steam, air) and the evolution their distributions in large-scale, multi compartment geometry imitating nuclear reactor containment compartments. The flow and the mixing process in the experiments are driven by plumes and jets representing source structures with different momentum-to-buoyancy strength. The time evolution of the relevant parameters like gas concentrations, velocities and temperatures are followed using dedicated instrumentation. The data obtained is meant to be used for the validation and development of high-resolution, mainly CFD based, 3D computational tools for nuclear reactor containment safety analysis.

Acting on the invisible: Computational tools and community action in the landscapes of air quality

2020 ◽  
Vol 18 (2) ◽  
pp. 108-119
Author(s):  
Christine Ann Mondor ◽  
Nicolas Azel
Keyword(s):  
Air Quality ◽  
Large Scale ◽  
Public Awareness ◽  
Community Action ◽  
Lessons Learned ◽  
Theory Of Change ◽  
Small Community ◽  
Computational Tools ◽  
Aggregate Information ◽  
Use Of Technology

This article proposes that designers and planners can better manage wicked problems by developing a strategic alignment of computational technology with a theory of change. Together with an understanding of the most effective places to intervene in a system, designers’ informed use of technology enables them to orchestrate community action and leverage large-scale environmental change. Aligning technology with a theory of change deepens the relevance of computational tools and suggests that technologies or tools that augment one’s ability to perceive, understand relevance, or prioritize raise the potential for action; technologies or tools that aggregate information on collective beliefs or actions help to build a community of concern; and technologies that elevate community capacity and create a sense of identity can contribute to the long-term transformation of values. Through a case study, this article demonstrates a nested approach to computation, which enhances public awareness and enables action in a small community which is trying to manage an extra-territorial problem of air quality. This article also proposes that while computational tools have extended the reach and effectiveness of advocacy, designers should continue to push for expanded application. By aggregating lessons learned from technological networks, such as the emerging clean air network described in this article, we can add another socio-ecological dimension to the practices of landscape and urbanism.

Simulation of Mixing Induced by a Hot PAR Exhaust Plume

2012 ◽  
Author(s):  
Michele Andreani ◽  
Stephan Kelm
Keyword(s):  
Heat Source ◽  
Thermal Effect ◽  
Large Scale ◽  
Coarse Mesh ◽  
Mixing Process ◽  
Computational Tools ◽  
Simultaneous Injection ◽  
Exhaust Plume ◽  
Substantial Discrepancy ◽  
Ansys Cfx

Passive Autocatalytic Recombiners (PARs) are installed in various reactor containment designs to mitigate the hydrogen risk. For the evaluation of the effectiveness of these devices, validated computational tools are needed. To build confidence in the codes, their capability must also be assessed against separate effect tests addressing specific phenomena. Within the OECD SETH 2 project three experiments have been performed in the large-scale PANDA facility, where the thermal effect of a PAR was simulated by means of a heater and the plume generated by the heat source interacted with an initially stratified ambient. In these tests, helium was used instead of hydrogen. The position of the heater and the presence of simultaneous injection of steam were varied in these tests. These experiments have been analyzed with the GOTHIC and the ANSYS CFX codes. This paper reports only the results obtained with the GOTHIC code. In general, the GOTHIC code in conjunction with a coarse mesh could predict the mixing process reasonably well. The only substantial discrepancy with the experiments was the overprediction of the velocity at the inlet of the heater case, but this had little effect on the simulation of the overall mixing.

scholarly journals Investigation of a new methodology for the prediction of drawing force in deep drawing process with respect to dimensionless analysis

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Saeed Hajiahmadi ◽  
Majid Elyasi ◽  
Mohsen Shakeri
Keyword(s):  
Deep Drawing ◽  
Large Scale ◽  
Model Comparison ◽  
Experimental Tests ◽  
Geometric Parameters ◽  
Relational Model ◽  
Small Scale ◽  
Geometrical Parameters ◽  
Drawing Force ◽  
Force Estimation

AbstractIn this research, geometric parameters were given in dimensionless form by the Buckingham pi dimensional analysis method, and a series of dimensionless groups were found for deep drawing of the round cup. To find the best group of dimensionless geometric parameters, three scales are evaluated by commercial FE software. After analyzing all effective geometric parameters, a fittest relational model of dimensionless parameters is found. St12 sheet metals were used for experimental validation, which were formed at room temperature. In addition, results and response parameters were compared in the simulation process, experimental tests, and proposed dimensionless models. By looking at the results, it very well may be inferred that geometric qualities of a large scale can be predicted with a small scale by utilizing the proposed dimensionless model. Comparison of the outcomes for dimensionless models and experimental tests shows that the proposed dimensionless models have fine precision in determining geometrical parameters and drawing force estimation. Moreover, generalizing proposed dimensionless model was applied to ensure the estimating precision of geometric values in larger scales by smaller scales.

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