Modelling method of data‐driven model combined with a priori knowledge and its application in average particle size estimation of composite colloidal sols

2020 ◽  
Author(s):  
Yang Zhou ◽  
Shaojun Li
Keyword(s):  
Particle Size ◽  
A Priori ◽  
Average Particle Size ◽  
Data Driven ◽  
A Priori Knowledge ◽  
Average Particle ◽  
Size Estimation ◽  
Modelling Method ◽  
Priori Knowledge

scholarly journals Stimulating effect of magnesium hydroxide on aqueous characteristics of iron nanocomposites

2019 ◽  
Vol 80 (10) ◽  
pp. 1996-2002 ◽  
Author(s):  
I. Maamoun ◽  
O. Eljamal ◽  
O. Falyouna ◽  
R. Eljamal ◽  
Y. Sugihara
Keyword(s):  
Particle Size ◽  
Magnesium Hydroxide ◽  
Iron Nanoparticles ◽  
Aqueous Suspension ◽  
Average Particle Size ◽  
Degree Of Crystallinity ◽  
Iron Core ◽  
Average Particle ◽  
Size Estimation ◽  
Aqueous Corrosion

Abstract Nanoscale zero-valent iron (nFe0) tends to aggregate, which dramatically affects its aqueous characteristics and thereby its potential in water treatment applications. Hence, the main aim of this study is to overcome such drawback of nFe0 by a new modification approach. Iron nanoparticles were modified by magnesium hydroxide (Mg(OH)2) addition with different mass ratios in order to form a nanocomposite with superior aqueous characteristics. The optimization process of the iron–magnesium nanocomposite (nFe0-Mg) was conducted through different approaches including settlement tests, morphology and crystallinity investigations and particle size estimation. The addition of Mg(OH)2 to nFe0 with a Mg/Fe coating ratio of 100% resulted in stimulated stability of the particles in aqueous suspension with around 95% enhancement in the suspension efficiency compared to that of nFe0. Results showed that the average particle size and degree of crystallinity of nFe0-Mg(Mg/Fe:100%) decreased by 46.7% and increased by 16.8%, respectively, comparing with that of nFe0. Additionally, the iron core of the synthesized nFe0 was adequately protected from aqueous corrosion with lower iron oxides leachates after the optimal modification with Mg(OH)2. Furthermore, Mg(OH)2 coating resulted in a stimulated adsorption reactivity of the composite towards phosphorus (P) with around 3.13% promotion in the removal efficiency comparing to that of nFe0.

scholarly journals Text Classification and Tagging of United States Army Ground Vehicle Fault Descriptions in Support of Data-Driven Prognostics

2020 ◽  
Vol 12 (1) ◽  
pp. 8
Author(s):  
Brandon Hansen ◽  
Cody Coleman ◽  
Yi Zhang ◽  
Maria Seale
Keyword(s):  
Machine Learning ◽  
Natural Language ◽  
A Priori ◽  
Supervised Machine Learning ◽  
Data Driven ◽  
A Priori Knowledge ◽  
Data Sets ◽  
Ground Vehicle ◽  
Us Army ◽  
Priori Knowledge

The manner in which a prognostics problem is framed is critical for enabling its solution by the proper method. Recently, data-driven prognostics techniques have demonstrated enormous potential when used alone, or as part of a hybrid solution in conjunction with physics-based models. Historical maintenance data constitutes a critical element for the use of a data-driven approach to prognostics, such as supervised machine learning. The historical data is used to create training and testing data sets to develop the machine learning model. Categorical classes for prediction are required for machine learning methods; however, faults of interest in US Army Ground Vehicle Maintenance Records appear as natural language text descriptions rather than a finite set of discrete labels. Transforming linguistically complex data into a set of prognostics classes is necessary for utilizing supervised machine learning approaches for prognostics. Manually labeling fault description instances is effective, but extremely time-consuming; thus, an automated approach to labelling is preferred. The approach described in this paper examines key aspects of the fault text relevant to enabling automatic labeling. A method was developed based on the hypothesis that a given fault description could be generalized into a category. This method uses various natural language processing (NLP) techniques and a priori knowledge of ground vehicle faults to assign classes to the maintenance fault descriptions. The core component of the method used in this paper is a Word2Vec word-embedding model. Word embeddings are used in conjunction with a token-oriented rule-based data structure for document classification. This methodology tags text with user-provided classes using a corpus of similar text fields as its training set. With classes of faults reliably assigned to a given description, supervised machine learning with these classes can be applied using related maintenance information that preceded the fault. This method was developed for labeling US Army Ground Vehicle Maintenance Records, but is general enough to be applied to any natural language data sets accompanied with a priori knowledge of its contents for consistent labeling. In addition to applications in machine learning, generated labels are also conducive to general summarization and case-by-case analysis of faults. The maintenance components of interest for this current application are alternators and gaskets, with future development directed towards determining the RUL of these components based on the labeled data.

A Data Driven Prognostic Methodology without a Priori Knowledge

2009 ◽  
Vol 42 (8) ◽  
pp. 1462-1467 ◽  
Author(s):  
Flavien Peysson ◽  
Abderrahmane Boubezoul ◽  
Mustapha Ouladsine ◽  
Rachid Outbib
Keyword(s):  
A Priori ◽  
Data Driven ◽  
A Priori Knowledge ◽  
Priori Knowledge

Determination of grinding parameters of fenugreek seed

1970 ◽  
Vol 26 (1) ◽  
pp. 16 ◽  
Author(s):  
S Balasubramanian ◽  
Rajkumar Rajkumar ◽  
K K Singh
Keyword(s):  
Particle Size ◽  
Energy Consumption ◽  
Moisture Content ◽  
Specific Energy ◽  
Feed Rate ◽  
Average Particle Size ◽  
Specific Energy Consumption ◽  
Average Particle ◽  
Fenugreek Seeds ◽  
Fenugreek Seed

Experiment to identify ambient grinding conditions and energy consumed was conducted for fenugreek. Fenugreek seeds at three moisture content (5.1%, 11.5% and 17.3%, d.b.) were ground using a micro pulverizer hammer mill with different grinding screen openings (0.5, 1.0 and 1.5 mm) and feed rate (8, 16 and 24 kg h-1) at 3000 rpm. Physical properties of fenugreek seeds were also determined. Specific energy consumptions were found to decrease from 204.67 to 23.09 kJ kg-1 for increasing levels of feed rate and grinder screen openings. On the other hand specific energy consumption increased with increasing moisture content. The highest specific energy consumption was recorded for 17.3% moisture content and 8 kg h-1 feed rate with 0.5 mm screen opening. Average particle size decreased from 1.06 to 0.39 mm with increase of moisture content and grinder screen opening. It has been observed that the average particle size was minimum at 0.5 mm screen opening and 8 kg h-1 feed rate at lower moisture content. Bond’s work index and Kick’s constant were found to increase from 8.97 to 950.92 kWh kg-1 and 0.932 to 78.851 kWh kg-1 with the increase of moisture content, feed rate and grinder screen opening, respectively. Size reduction ratio and grinding effectiveness of fenugreek seed were found to decrease from 4.11 to 1.61 and 0.0118 to 0.0018 with the increase of moisture content, feed rate and grinder screen opening, respectively. The loose and compact bulk densities varied from 219.2 to 719.4 kg m-3 and 137.3 to 736.2 kg m-3, respectively.  

Formulating SLN and NLC as Innovative Drug Delivery Systems for Non-Invasive Routes of Drug Administration

2020 ◽  
Vol 27 (22) ◽  
pp. 3623-3656 ◽  
Author(s):  
Bruno Fonseca-Santos ◽  
Patrícia Bento Silva ◽  
Roberta Balansin Rigon ◽  
Mariana Rillo Sato ◽  
Marlus Chorilli
Keyword(s):  
Drug Delivery ◽  
Particle Size ◽  
Drug Release ◽  
Drug Loading ◽  
Average Particle Size ◽  
Delivery Systems ◽  
Average Particle ◽  
Minor Importance ◽  
Routes Of Administration ◽  
Non Invasive

Colloidal carriers diverge depending on their composition, ability to incorporate drugs and applicability, but the common feature is the small average particle size. Among the carriers with the potential nanostructured drug delivery application there are SLN and NLC. These nanostructured systems consist of complex lipids and highly purified mixtures of glycerides having varying particle size. Also, these systems have shown physical stability, protection capacity of unstable drugs, release control ability, excellent tolerability, possibility of vectorization, and no reported production problems related to large-scale. Several production procedures can be applied to achieve high association efficiency between the bioactive and the carrier, depending on the physicochemical properties of both, as well as on the production procedure applied. The whole set of unique advantages such as enhanced drug loading capacity, prevention of drug expulsion, leads to more flexibility for modulation of drug release and makes Lipid-based nanocarriers (LNCs) versatile delivery system for various routes of administration. The route of administration has a significant impact on the therapeutic outcome of a drug. Thus, the non-invasive routes, which were of minor importance as parts of drug delivery in the past, have assumed added importance drugs, proteins, peptides and biopharmaceuticals drug delivery and these include nasal, buccal, vaginal and transdermal routes. The objective of this paper is to present the state of the art concerning the application of the lipid nanocarriers designated for non-invasive routes of administration. In this manner, this review presents an innovative technological platform to develop nanostructured delivery systems with great versatility of application in non-invasive routes of administration and targeting drug release.

Azithromycin nanosuspension preparation using evaporative precipitation into aqueous solution (EPAS) method and its comparative dissolution study

2020 ◽  
Vol 17 ◽  
Author(s):  
Mohammad Hossain Shariare ◽  
Tonmoy Kumar Mondal ◽  
Hani Alothaid ◽  
Md. Didaruzzaman Sohel ◽  
MD Wadud ◽  
...  
Keyword(s):  
Aqueous Solution ◽  
Particle Size ◽  
Dissolution Rate ◽  
Average Particle Size ◽  
Scale Up ◽  
Average Particle ◽  
Total Drug ◽  
Residual Solvent ◽  
Dissolution Study ◽  
Drug Content

Aim: EPAS (evaporative precipitation into aqueous solution) was used in the current studies to prepare azithromycin nanosuspensions and investigate the physicochemical characteristics for the nanosuspension batches with the aim of enhancing the dissolution rate of the nanopreparation to improve bioavailability. Methods: EPAS method used in this study for preparing azithromycin nanosuspension was achieved through developing an in-house instrumentation method. Particle size distribution was measured using Zetasizer Nano S without sample dilution. Dissolved azithromycin nanosuspensions were also compared with raw azithromycin powder and commercially available products. Total drug content of nanosuspension batches were measured using an Ultra-Performance Liquid Chromatography (UPLC) system with Photodiode Array (PDA) detector while residual solvent was measured using gas chromatography (GC). Results: The average particle size of azithromycin nanosuspension was 447.2 nm and total drug content was measured to be 97.81% upon recovery. Dissolution study data showed significant increase in dissolution rate for nanosuspension batch when compared to raw azithromycin and commercial version (microsuspension). The residual solvent found for azithromycin nanosuspension is 0.000098023 mg/ mL or 98.023 ppb. Conclusion: EPAS was successfully used to prepare azithromycin nanoparticles that exhibited significantly enhanced dissolution rate. Further studies are required to scale up the process and determine long term stability of the nanoparticles.

Seeing, Knowing, and Doing

2020 ◽  
Author(s):  
Robert Audi
Keyword(s):  
Practical Reasoning ◽  
Practical Knowledge ◽  
A Priori ◽  
Human Action ◽  
A Priori Knowledge ◽  
Rational Action ◽  
Reasons For Action ◽  
Discriminative Response ◽  
Rich Information ◽  
Priori Knowledge

This book provides an overall theory of perception and an account of knowledge and justification concerning the physical, the abstract, and the normative. It has the rigor appropriate for professionals but explains its main points using concrete examples. It accounts for two important aspects of perception on which philosophers have said too little: its relevance to a priori knowledge—traditionally conceived as independent of perception—and its role in human action. Overall, the book provides a full-scale account of perception, presents a theory of the a priori, and explains how perception guides action. It also clarifies the relation between action and practical reasoning; the notion of rational action; and the relation between propositional and practical knowledge. Part One develops a theory of perception as experiential, representational, and causally connected with its objects: as a discriminative response to those objects, embodying phenomenally distinctive elements; and as yielding rich information that underlies human knowledge. Part Two presents a theory of self-evidence and the a priori. The theory is perceptualist in explicating the apprehension of a priori truths by articulating its parallels to perception. The theory unifies empirical and a priori knowledge by clarifying their reliable connections with their objects—connections many have thought impossible for a priori knowledge as about the abstract. Part Three explores how perception guides action; the relation between knowing how and knowing that; the nature of reasons for action; the role of inference in determining action; and the overall conditions for rational action.

How Reality is Reasonable

2018 ◽  
Author(s):  
Donald C. Williams
Keyword(s):  
A Priori ◽  
A Priori Knowledge ◽  
Dimensional Manifold ◽  
The World ◽  
Being There ◽  
Ways Of Being ◽  
Fundamental Entity ◽  
Spatiotemporal Relations ◽  
Priori Knowledge

This chapter begins with a systematic presentation of the doctrine of actualism. According to actualism, all that exists is actual, determinate, and of one way of being. There are no possible objects, nor is there any indeterminacy in the world. In addition, there are no ways of being. It is proposed that actual entities stand in three fundamental relations: mereological, spatiotemporal, and resemblance relations. These relations govern the fundamental entities. Each fundamental entity stands in parthood relations, spatiotemporal relations, and resemblance relations to other entities. The resulting picture is one that represents the world as a four-dimensional manifold of actual ‘qualitied contents’—upon which all else supervenes. It is then explained how actualism accounts for classes, quantity, number, causation, laws, a priori knowledge, necessity, and induction.

How Do We Know that We’re Not Brains in Vats?

2018 ◽  
Author(s):  
Keith DeRose
Keyword(s):  
Epistemic Justification ◽  
A Priori ◽  
A Priori Knowledge ◽  
Conservative Approach ◽  
Contingent Fact ◽  
Brains In Vats ◽  
Priori Knowledge

In this chapter the contextualist Moorean account of how we know by ordinary standards that we are not brains in vats (BIVs) utilized in Chapter 1 is developed and defended, and the picture of knowledge and justification that emerges is explained. The account (a) is based on a double-safety picture of knowledge; (b) has it that our knowledge that we’re not BIVs is in an important way a priori; and (c) is knowledge that is easily obtained, without any need for fancy philosophical arguments to the effect that we’re not BIVs; and the account is one that (d) utilizes a conservative approach to epistemic justification. Special attention is devoted to defending the claim that we have a priori knowledge of the deeply contingent fact that we’re not BIVs, and to distinguishing this a prioritist account of this knowledge from the kind of “dogmatist” account prominently championed by James Pryor.

scholarly journals Evaluation of the Effects of Filler Fineness on the Properties of an Epoxy Asphalt Mixture

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2003
Author(s):  
Wei Xu ◽  
Jintao Wei ◽  
Zhengxiong Chen ◽  
Feng Wang ◽  
Jian Zhao
Keyword(s):  
Particle Size ◽  
Average Particle Size ◽  
Asphalt Mixture ◽  
Average Particle ◽  
Fine Dust ◽  
Bonding Structure ◽  
Epoxy Asphalt ◽  
Mineral Powder ◽  
Marshall Stability ◽  
Mixture Sample

The type and fineness of a filler significantly affect the performance of an asphalt mixture. There is a lack of specific research on the effects of filler fineness and dust from aggregates on the properties of epoxy asphalt (EA) mixtures. The effects of aggregate dust and mineral powder on the properties of an EA mixture were evaluated. These filler were tested to determine their fineness, specific surface area and mineral composition. The effects of these fillers on the EA mastic sample and mixture were evaluated. The morphology of the EA mastic samples was analyzed using scanning electron microscopy (SEM). The effects of the fillers on the Marshall stability, tensile strength and fatigue performance of the EA mixture were evaluated. The dust from the aggregates exhibited an even particle size distribution, and its average particle size was approximately 20% of that of the mineral powder. The SEM microanalysis showed that the EA mastic sample containing relatively fine dust formed a tight and dense interfacial bonding structure with the aggregate. The EA mixture sample containing filler composed of dust from aggregate had a significantly higher strength and longer fatigue life than that of the EA sample containing filler composed of mineral powder.

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