scholarly journals A brief review of data-driven ICME for intelligently discovering advanced structural metal materials: Insight into atomic and electronic building blocks

2020 ◽  
Vol 35 (8) ◽  
pp. 872-889 ◽  
Author(s):  
William Yi Wang ◽  
Bin Tang ◽  
Deye Lin ◽  
Chengxiong Zou ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Building Blocks ◽  
Data Driven ◽  
Structural Metal ◽  
Metal Materials ◽  
Insight Into

Abstract

scholarly journals Cold-Active β-Galactosidases: Insight into Cold Adaption Mechanisms and Biotechnological Exploitation

Marine Drugs ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 43
Author(s):  
Marco Mangiagalli ◽  
Marina Lotti
Keyword(s):  
Low Temperature ◽  
Molecular Mechanisms ◽  
Building Blocks ◽  
Cold Active ◽  
Cold Adaption ◽  
Glycosyl Donor ◽  
Pharmaceutical Industries ◽  
Biotechnological Processes ◽  
Hydrolysis Of ◽  
Insight Into

β-galactosidases (EC 3.2.1.23) catalyze the hydrolysis of β-galactosidic bonds in oligosaccharides and, under certain conditions, transfer a sugar moiety from a glycosyl donor to an acceptor. Cold-active β-galactosidases are identified in microorganisms endemic to permanently low-temperature environments. While mesophilic β-galactosidases are broadly studied and employed for biotechnological purposes, the cold-active enzymes are still scarcely explored, although they may prove very useful in biotechnological processes at low temperature. This review covers several issues related to cold-active β-galactosidases, including their classification, structure and molecular mechanisms of cold adaptation. Moreover, their applications are discussed, focusing on the production of lactose-free dairy products as well as on the valorization of cheese whey and the synthesis of glycosyl building blocks for the food, cosmetic and pharmaceutical industries.

AI Assisted High Fidelity Multi-Physics Digital Twin of Industrial Gas Turbines

2021 ◽  
Author(s):  
Senthil Krishnababu ◽  
Omar Valero ◽  
Roger Wells
Keyword(s):  
Gas Turbine ◽  
Data Storage ◽  
Gas Turbines ◽  
Building Blocks ◽  
Data Driven ◽  
High Fidelity ◽  
Test Field ◽  
Operating Characteristics ◽  
Digital Twin ◽  
The Impact

Abstract Data driven technologies are revolutionising the engineering sector by providing new ways of performing day to day tasks through the life cycle of a product as it progresses through manufacture, to build, qualification test, field operation and maintenance. Significant increase in data transfer speeds combined with cost effective data storage, and ever-increasing computational power provide the building blocks that enable companies to adopt data driven technologies such as data analytics, IOT and machine learning. Improved business operational efficiency and more responsive customer support provide the incentives for business investment. Digital twins, that leverages these technologies in their various forms to converge physics and data driven models, are therefore being widely adopted. A high-fidelity multi-physics digital twin, HFDT, that digitally replicates a gas turbine as it is built based on part and build data using advanced component and assembly models is introduced. The HFDT, among other benefits enables data driven assessments to be carried out during manufacture and assembly for each turbine allowing these processes to be optimised and the impact of variability or process change to be readily evaluated. On delivery of the turbine and its associated HFDT to the service support team the HFDT supports the evaluation of in-service performance deteriorations, the impact of field interventions and repair and the changes in operating characteristics resulting from overhaul and turbine upgrade. Thus, creating a cradle to grave physics and data driven twin of the gas turbine asset. In this paper, one branch of HFDT using a power turbine module is firstly presented. This involves simultaneous modelling of gas path and solid using high fidelity CFD and FEA which converts the cold geometry to hot running conditions to assess the impact of various manufacturing and build variabilities. It is shown this process can be executed within reasonable time frames enabling creation of HFDT for each turbine during manufacture and assembly and for this to be transferred to the service team for deployment during field operations. Following this, it is shown how data driven technologies are used in conjunction with the HFDT to improve predictions of engine performance from early build information. The example shown, shows how a higher degree of confidence is achieved through the development of an artificial neural network of the compressor tip gap feature and its effect on overall compressor efficiency.

scholarly journals A Physical Organic Approach to Tuning Reagents for Selective and Stable Methionine Bioconjugation

2019 ◽  
Author(s):  
Alec Christian ◽  
Shang Jia ◽  
Patricia Zhang ◽  
Arismel Tena Meza ◽  
Matthew S. Sigman ◽  
...  
Keyword(s):  
Structural Features ◽  
Data Driven ◽  
Live Cells ◽  
Design And Synthesis ◽  
Use Of Data ◽  
Physical Organic ◽  
Driving Stability ◽  
Peptide Stapling ◽  
Insight Into ◽  
Unique Chemical

We report a data-driven, physical organic approach to the development of new methionine-selective bioconjugation reagents with tunable adduct stabilities. Statistical modeling of structural features described by intrinsic physical organic parameters was applied to the development of a predictive model and to gain insight into features driving stability of adducts formed from the chemoselective coupling of oxaziridine and methionine thioether partners through Redox Activated Chemical Tagging (ReACT). From these analyses, a correlation between sulfimide stabilities and sulfimide  (C=O) stretching frequencies was revealed. We ex-ploited the rational gains in adduct stability exposed by this analysis to achieve the design and synthesis of a bis-oxaziridine reagent for peptide stapling. Indeed, we observed that a macrocyclic peptide formed by ReACT stapling at methionine exhibited improved uptake into live cells compared to an unstapled congener, highlighting the potential utility of this unique chemical tool for thioether modification. This work provides a template for the broader use of data-driven approaches to bioconjugation chemistry and other chemical biology applications.

scholarly journals Building clone-consistent ecosystem models

2021 ◽  
Vol 17 (2) ◽  
pp. e1008635
Author(s):  
Gerrit Ansmann ◽  
Tobias Bollenbach
Keyword(s):  
Functional Analysis ◽  
Building Blocks ◽  
Data Driven ◽  
Ecological Studies ◽  
Ecosystem Models ◽  
Linear Combinations ◽  
Model Consistency ◽  
Wide Range ◽  
Critical Requirement ◽  
Two Populations

Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency. Although clone consistency can always be achieved with sufficient assumptions, we argue that it is important to explicitly name and consider the assumptions made: They may not be justified or limit the applicability of models and the generality of the results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies.

Personal Values as a Building Block for Social Responsibility of Higher Education Institutions

2017 ◽  
pp. 119-142 ◽  
Author(s):  
Zlatko Nedelko ◽  
Vojko Potocan ◽  
Nikša Alfirević
Keyword(s):  
Higher Education ◽  
Social Responsibility ◽  
Community Involvement ◽  
Higher Education Institutions ◽  
Personal Values ◽  
Building Blocks ◽  
Starting Point ◽  
Core Mission ◽  
Insight Into

The purpose of this chapter is to examine the role of personal values for social responsibility (SR) of higher education. Besides the core mission of higher education to create, transfer and preserve knowledge in society, the idea of SR has gained its importance also in institutions of higher education. SR has many drivers, among which personal values are considered as one of the key building blocks for SR. For enhancing SR, higher education institutions should also develop stronger ties with the community. The chapter provides an insight into discussion about community involvement of higher education, into the role of personal values for shaping SR of higher education institutions and explain how personal values can help to enhance community and social involvement of higher education. Findings may be a starting point for re-thinking and/or establishing strategies for achieving higher level of SR in higher education institutions and enhancing the link with the community.

scholarly journals BRIDGING THE GAPS : A PARADIGMATIC INSIGHT INTO PHILOSOPHY OF LAW

2016 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Erlyn Indarti
Keyword(s):  
Legal Theory ◽  
Building Blocks ◽  
Legal Philosophy ◽  
Philosophy Of Law ◽  
Legal Science ◽  
Insight Into

Paradigm represents a worldview that defines, for its holder, the nature of theworld, the individual's place in it, and the range of possible relationships to thatworld and its parts. It comprises of four main elements, i.e. ontology, epistemology,methodology, and methods. Within the discipline of law, there seem to be two setsof gaps separating philosophy of law's building blocks that dissociate, first, legalpractice from legal theory and, second, legal science from legal philosophy. It isthe purpose of this article, with the help of paradigmatic insight, to bridge thosegaps.Keywords: law, philosophy of law, paradigm, paradigmatic study of law

scholarly journals A Review of Charge Pump Topologies for the Power Management of IoT Nodes

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 480 ◽  
Author(s):  
Andrea Ballo ◽  
Alfio Dario Grasso ◽  
Gaetano Palumbo
Keyword(s):  
Internet Of Things ◽  
Power Management ◽  
Energy Harvester ◽  
State Of The Art ◽  
Charge Pump ◽  
The State ◽  
Data Driven ◽  
Design Specifications ◽  
The Given ◽  
Insight Into

With the aim of providing designer guidelines for choosing the most suitable solution, according to the given design specifications, in this paper a review of charge pump (CP) topologies for the power management of Internet of Things (IoT) nodes is presented. Power management of IoT nodes represents a challenging task, especially when the output of the energy harvester is in the order of few hundreds of millivolts. In these applications, the power management section can be profitably implemented, exploiting CPs. Indeed, presently, many different CP topologies have been presented in literature. Finally, a data-driven comparison is also provided, allowing for quantitative insight into the state-of-the-art of integrated CPs.

scholarly journals Evaluations as value-measurement links: Exploring metrics and meanings in science

2019 ◽  
Vol 58 (2) ◽  
pp. 282-300
Author(s):  
Felicitas Hesselmann ◽  
Cornelia Schendzielorz
Keyword(s):  
Impact Factor ◽  
Journal Impact Factor ◽  
Building Blocks ◽  
Theoretical Concept ◽  
Impact Factors ◽  
Value Measurement ◽  
Journal Impact ◽  
Insight Into

This contribution seeks to provide a more detailed insight into the entanglement of value and measurement. Drawing on insights from semiotics and a Bourdieusian perspective on language as an economy of linguistic exchange, we develop the theoretical concept of value-measurement links and distinguish three processes – operationalisation, nomination, and indetermination – as forms in which these links can be constructed. We illustrate these three processes using (e)valuation practices in science, particularly the journal impact factor, as an empirical object of investigation. As this example illustrates, measured values can function as building blocks for further measurements, and thus establish chains of evaluations, where it becomes more and more obscure which values the measurements actually express. We conclude that in the case of measured values such as impact factors, these chains are driven by the interplay between the interpretative openness of language and the seeming tendency of numbers to fixate meaning thus continually re-creating, transforming and modifying values.

scholarly journals Genetic Contributions to Multivariate Data-Driven Brain Networks Constructed via Source-Based Morphometry

2020 ◽  
Vol 30 (9) ◽  
pp. 4899-4913
Author(s):  
Amanda L Rodrigue ◽  
Aaron F Alexander-Bloch ◽  
Emma E M Knowles ◽  
Samuel R Mathias ◽  
Josephine Mollon ◽  
...  
Keyword(s):  
Brain Function ◽  
Complex Traits ◽  
Brain Regions ◽  
Data Driven ◽  
Additional Insight ◽  
Genetic Overlap ◽  
Data Driven Approach ◽  
The Uk ◽  
Genetic Contributions ◽  
Insight Into

Abstract Identifying genetic factors underlying neuroanatomical variation has been difficult. Traditional methods have used brain regions from predetermined parcellation schemes as phenotypes for genetic analyses, although these parcellations often do not reflect brain function and/or do not account for covariance between regions. We proposed that network-based phenotypes derived via source-based morphometry (SBM) may provide additional insight into the genetic architecture of neuroanatomy given its data-driven approach and consideration of covariance between voxels. We found that anatomical SBM networks constructed on ~ 20 000 individuals from the UK Biobank were heritable and shared functionally meaningful genetic overlap with each other. We additionally identified 27 unique genetic loci that contributed to one or more SBM networks. Both GWA and genetic correlation results indicated complex patterns of pleiotropy and polygenicity similar to other complex traits. Lastly, we found genetic overlap between a network related to the default mode and schizophrenia, a disorder commonly associated with neuroanatomic alterations.

scholarly journals Behavioral Interpretations of Intrinsic Connectivity Networks

2011 ◽  
Vol 23 (12) ◽  
pp. 4022-4037 ◽  
Author(s):  
Angela R. Laird ◽  
P. Mickle Fox ◽  
Simon B. Eickhoff ◽  
Jessica A. Turner ◽  
Kimberly L. Ray ◽  
...  
Keyword(s):  
Cognitive Processes ◽  
Resting State ◽  
Brain Networks ◽  
Data Driven ◽  
Resting State Networks ◽  
Independent State ◽  
Intrinsic Connectivity ◽  
Mental Operations ◽  
Intrinsic Connectivity Networks ◽  
Insight Into

An increasingly large number of neuroimaging studies have investigated functionally connected networks during rest, providing insight into human brain architecture. Assessment of the functional qualities of resting state networks has been limited by the task-independent state, which results in an inability to relate these networks to specific mental functions. However, it was recently demonstrated that similar brain networks can be extracted from resting state data and data extracted from thousands of task-based neuroimaging experiments archived in the BrainMap database. Here, we present a full functional explication of these intrinsic connectivity networks at a standard low order decomposition using a neuroinformatics approach based on the BrainMap behavioral taxonomy as well as a stratified, data-driven ordering of cognitive processes. Our results serve as a resource for functional interpretations of brain networks in resting state studies and future investigations into mental operations and the tasks that drive them.

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