Hierarchical Modeling of HLW Glass-Gel-Solution Systems for Stage 3 Glass Degradation

2015 ◽  
Vol 1744 ◽  
pp. 173-184 ◽  
Author(s):  
Carol M. Jantzen ◽  
Charles L. Crawford
Keyword(s):  
Hierarchical Modeling ◽  
A Priori ◽  
Reaction Products ◽  
Secondary Phases ◽  
Strong Base ◽  
Structure Control ◽  
Gel Layer ◽  
Composition And Structure ◽  
High Level ◽  
Accelerated Leaching

ABSTRACTThe necessity to a priori predict the durability of high level nuclear waste (HLW) glasses on extended time scales has led to a variety of modeling approaches based primarily on solution (leachate) concentrations. The glass composition and structure control the leachate and the gel compositions which in turn control what reaction products form: the leached layer is a hydrogel and reacts with the solution (leachate) to form secondary phases some of which cause accelerated glass dissolution which is undesirable. Glasses with molar excess alkali that is not bound to glass forming (Al,Fe,B)O4 structural groups in the glass resume accelerated leaching. The hydrogels of the glasses that resume accelerated leaching at long times contain excess alkali and the leachates contain excess strong base, [SB]ex. The [SB]ex further accelerates aluminosilicate gel aging into analcime with time. Glasses with no excess molar structural alkali do not resume accelerated leaching: the glass generates weak acids, [WA], in the leachate favoring hydrogel aging into clays. These data indicate that the gel layer transforms to secondary phases in situ in response to interactions with the chemistry of a continuously evolving leachate.

A study of reaction of aromatic polynitro compounds with tributylstannyl hydride

1985 ◽  
Vol 50 (11) ◽  
pp. 2598-2606 ◽  
Author(s):  
Vladimír Macháček ◽  
Antonín Lyčka ◽  
Milan Nádvorník
Keyword(s):  
Nmr Spectra ◽  
Reaction Products ◽  
Tetramethylammonium Bromide ◽  
Composition And Structure

1H, 13C, 15N, and 119Sn NMR spectra have been used to study composition and structure of reaction products from 1,3,5-trinitrobenzene, methyl 2,4,6-trinitrobenzoate, 1-dimethylamino-2,4,6-trinitrobenzene, 1-methoxy-2,4,6-trinitrobenzene, 1-chloro-2,4,6-trinitrobenzene, 2,4,6-trinitrotoluene, 3,5-dinitrobenzonitrile and methyl 3,5-dinitrobenzoate with tributylstannyl hydride in the presence of tetramethylammonium bromide.

scholarly journals Strategies for a Circular Economy in the Construction and Demolition Sector: Identifying the Factors Affecting the Recommendation of Recycled Concrete

2021 ◽  
Vol 13 (8) ◽  
pp. 4113
Author(s):  
Valeria Superti ◽  
Cynthia Houmani ◽  
Ralph Hansmann ◽  
Ivo Baur ◽  
Claudia R. Binder
Keyword(s):  
Circular Economy ◽  
A Priori ◽  
Recycled Concrete ◽  
Recycled Aggregates ◽  
Factors Affecting ◽  
Structural Applications ◽  
Adoption Of Innovation ◽  
Decision Making Processes ◽  
Behavioural Factors ◽  
High Level

With increasing urbanisation, new approaches such as the Circular Economy (CE) are needed to reduce resource consumption. In Switzerland, Construction & Demolition (C&D) waste accounts for the largest portion of waste (84%). Beyond limiting the depletion of primary resources, implementing recycling strategies for C&D waste (such as using recycled aggregates to produce recycled concrete (RC)), can also decrease the amount of landfilled C&D waste. The use of RC still faces adoption barriers. In this research, we examined the factors driving the adoption of recycled products for a CE in the C&D sector by focusing on RC for structural applications. We developed a behavioural framework to understand the determinants of architects’ decisions to recommend RC. We collected and analysed survey data from 727 respondents. The analyses focused on architects’ a priori beliefs about RC, behavioural factors affecting their recommendations of RC, and project-specific contextual factors that might play a role in the recommendation of RC. Our results show that the factors that mainly facilitate the recommendation of RC by architects are: a senior position, a high level of RC knowledge and of the Minergie label, beliefs about the reduced environmental impact of RC, as well as favourable prescriptive social norms expressed by clients and other architects. We emphasise the importance of a holistic theoretical framework in approaching decision-making processes related to the adoption of innovation, and the importance of the agency of each involved actor for a transition towards a circular construction sector.

A Two Phases Self-healing Framework for Service-oriented Systems

2021 ◽  
Vol 15 (2) ◽  
pp. 1-25
Author(s):  
Amal Alhosban ◽  
Zaki Malik ◽  
Khayyam Hashmi ◽  
Brahim Medjahed ◽  
Hassan Al-Ababneh
Keyword(s):  
Web Services ◽  
A Priori ◽  
Fault Management ◽  
Service Selection ◽  
Exception Handling ◽  
Self Healing ◽  
Service Oriented Architectures ◽  
Service Oriented ◽  
Improved Performance ◽  
High Level

Service-Oriented Architectures (SOA) enable the automatic creation of business applications from independently developed and deployed Web services. As Web services are inherently a priori unknown, how to deliver reliable Web services compositions is a significant and challenging problem. Services involved in an SOA often do not operate under a single processing environment and need to communicate using different protocols over a network. Under such conditions, designing a fault management system that is both efficient and extensible is a challenging task. In this article, we propose SFSS, a self-healing framework for SOA fault management. SFSS is predicting, identifying, and solving faults in SOAs. In SFSS, we identified a set of high-level exception handling strategies based on the QoS performances of different component services and the preferences articled by the service consumers. Multiple recovery plans are generated and evaluated according to the performance of the selected component services, and then we execute the best recovery plan. We assess the overall user dependence (i.e., the service is independent of other services) using the generated plan and the available invocation information of the component services. Due to the experiment results, the given technique enhances the service selection quality by choosing the services that have the highest score and betters the overall system performance. The experiment results indicate the applicability of SFSS and show improved performance in comparison to similar approaches.

scholarly journals Tuning the Reaction Selectivity over MgAl Spinel-Supported Pt Catalyst in Furfuryl Alcohol Conversion to Pentanediols

Catalysts ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 415
Author(s):  
Xinsheng Li ◽  
Jifeng Pang ◽  
Jingcai Zhang ◽  
Xianquan Li ◽  
Yu Jiang ◽  
...  
Keyword(s):  
Furfuryl Alcohol ◽  
Pt Nanoparticles ◽  
Catalytic Performance ◽  
Major Product ◽  
Pt Catalyst ◽  
Reaction Products ◽  
Strong Base ◽  
Reaction Selectivity ◽  
Supported Pt Catalysts ◽  
Alcohol Conversion

Catalytic conversion of biomass-derived feedstock to high-value chemicals is of remarkable significance for alleviating dependence on fossil energy resources. MgAl spinel-supported Pt catalysts were prepared and used in furfuryl alcohol conversion. The approaches to tune the reaction selectivity toward pentanediols (PeDs) were investigated and the catalytic performance was correlated to the catalysts’ physicochemical properties based on comprehensive characterizations. It was found that 1–8 wt% Pt was highly dispersed on the MgAl2O4 support as nanoparticles with small sizes of 1–3 nm. The reaction selectivity did not show dependence on the size of Pt nanoparticles. Introducing LiOH onto the support effectively steered the reaction products toward the PeDs at the expense of tetrahydrofurfuryl alcohol (THFA) selectivity. Meanwhile, the major product in PeDs was shifted from 1,5-PeD to 1,2-PeD. The reasons for the PeDs selectivity enhancement were attributed to the generation of a large number of medium-strong base sites on the Li-modified Pt catalyst. The reaction temperature is another effective factor to tune the reaction selectivity. At 230 °C, PeDs selectivity was enhanced to 77.4% with a 1,2-PeD to 1,5-PeD ratio of 3.7 over 4Pt/10Li/MgAl2O4. The Pt/Li/MgAl2O4 catalyst was robust to be reused five times without deactivation.

Audit Standard Setting and Inspection for U.S. Public Companies: A Critical Assessment and Recommendations for Fundamental Change

2009 ◽  
Vol 23 (2) ◽  
pp. 221-237 ◽  
Author(s):  
Steven M. Glover ◽  
Douglas F. Prawitt ◽  
Mark H. Taylor
Keyword(s):  
Standard Setting ◽  
The United States ◽  
Current Approach ◽  
Public Companies ◽  
Accounting Firms ◽  
Publicly Traded Companies ◽  
Sarbanes Oxley ◽  
Composition And Structure ◽  
Audit Standard ◽  
High Level

SYNOPSIS: The Sarbanes-Oxley Act of 2002 (SOX) established the Public Company Accounting Oversight Board (PCAOB) to oversee the accounting firms that audit publicly traded companies in the United States. In this commentary we outline why we believe the PCAOB’s audit standard-setting and inspection models are inefficient and dysfunctional. We assert that the Board’s ability to achieve its mission is limited by its early choices, together with its incentives, organizational composition, and structure. We support our assertions with a number of indicators of serious problems and flaws in the current approach. We also present high-level recommendations for change for policy makers, regulators, and leaders in the profession to consider in developing improved approaches to audit standard setting, inspection, and enforcement.

scholarly journals A Systematic Framework for Drug Repositioning from Integrated Omics and Drug Phenotype Profiles Using Pathway-Drug Network

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Erkhembayar Jadamba ◽  
Miyoung Shin
Keyword(s):  
Breast Cancer ◽  
Drug Repositioning ◽  
Expression Profiles ◽  
A Priori ◽  
Gene Expression Profiles ◽  
Biological Data ◽  
Genomic Knowledge ◽  
High Level ◽  
Systematic Framework ◽  
Phenotype Expression

Drug repositioning offers new clinical indications for old drugs. Recently, many computational approaches have been developed to repurpose marketed drugs in human diseases by mining various of biological data including disease expression profiles, pathways, drug phenotype expression profiles, and chemical structure data. However, despite encouraging results, a comprehensive and efficient computational drug repositioning approach is needed that includes the high-level integration of available resources. In this study, we propose a systematic framework employing experimental genomic knowledge and pharmaceutical knowledge to reposition drugs for a specific disease. Specifically, we first obtain experimental genomic knowledge from disease gene expression profiles and pharmaceutical knowledge from drug phenotype expression profiles and construct a pathway-drug network representing a priori known associations between drugs and pathways. To discover promising candidates for drug repositioning, we initialize node labels for the pathway-drug network using identified disease pathways and known drugs associated with the phenotype of interest and perform network propagation in a semisupervised manner. To evaluate our method, we conducted some experiments to reposition 1309 drugs based on four different breast cancer datasets and verified the results of promising candidate drugs for breast cancer by a two-step validation procedure. Consequently, our experimental results showed that the proposed framework is quite useful approach to discover promising candidates for breast cancer treatment.

scholarly journals The Analysis Of The Students’ Difficulty in Memorizing English Vocabulary in Elementary School

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Dewi Ulya Mailasari
Keyword(s):  
Elementary School ◽  
Intrinsic Motivation ◽  
Subject Matter ◽  
Qualitative Method ◽  
A Priori ◽  
Motivational Factors ◽  
Main Role ◽  
High Level ◽  
Compulsory Subject

<p class="05IsiAbstrak">This article describes the students’ difficulty in memorizing English vocabulary in Integrated Islamic Elementary School (SDIT) Amal Insani Jepara.  This study uses a descriptive qualitative method. The result denotes that students have difficulties in memorizing vocabulary including there is no visible intrinsic motivation from students, considering English as just another compulsory subject. In addition to the factors of integration and talent, it seems that attitudinal and motivational factors take the main role of the difficulties of students of SDIT Amal Insani in remembering English vocabulary. Students with a high level of intelligence coupled with high enthusiasm, because there is a reward from the teacher, easy to remember vocabulary as well as remembering other subject matter. Students with a priori and low motivation attitude find it difficult to remember the vocabulary that has been given.</p>

IDENTIFYING REUSABLE SOFTWARE COMPONENTS BY INDUCTION

1991 ◽  
Vol 01 (03) ◽  
pp. 271-292 ◽  
Author(s):  
JUAN CARLOS ESTEVA ◽  
ROBERT G. REYNOLDS
Keyword(s):  
Decision Tree ◽  
Inductive Learning ◽  
Test Case ◽  
Structure Control ◽  
Metric Properties ◽  
Abstract Description ◽  
Compilation Process ◽  
Code Module ◽  
Code Complexity ◽  
High Level

The goal of the Partial Metrics Project is the automatic acquisition of planning knowledge from target code modules in a program library. In the current prototype the system is given a target code module written in Ada as input, and the result is a sequence of generalized transformations that can be used to design a class of related modules. This is accomplished by embedding techniques from Artificial Intelligence into the traditional structure of a compiler. The compiler performs compilation in reverse, starting with detailed code and producing an abstract description of it. The principal task facing the compiler is to find a decomposition of the target code into a collection of syntactic components that are nearly decomposable. Here, nearly decomposable corresponds to the need for each code segment to be nearly independent syntactically from the others. The most independent segments are then the target of the code generalization process. This process can be described as a form of chunking and is implemented here in terms of explanation-based learning. The problem of producing nearly decomposable code components becomes difficult when target code module is not well structured. The task facing users of the system is to be able to identify well-structured code modules from a library of modules that are suitable for input to the system. In this paper we describe the use of inductive learning techniques, namely variations on Quinlan's ID3 system that are capable of producing a decision tree that can be used to conceptually distinguish between well poorly structured code. In order to accomplish that task a set of high-level concepts used by software engineers to characterize structurally understandable code were identified. Next, each of these concepts was operationalized in terms of code complexity metrics that can be easily calculated during the compilation process. These metrics are related to various aspects of the program structure including its coupling, cohesion, data structure, control structure, and documentation. Each candidate module was then described in terms of a collection of such metrics. Using a training set of positive and negative examples of well-structured modules, each described in terms of the appointed metrics, a decision tree was produced that was used to recognize other well-structured modules in terms of their metric properties. This approach was applied to modules from existing software libraries in a variety of domains such as database, editor, graphic, window, data processing, FFT and computer vision software. The results achieved by the system were then benchmarked against the performance of experienced programmers in terms of recognizing well structured code. In a test case involving 120 modules, the system was able to discriminate between poor and well-structured code 99% of the time as compared to an 80% average for the 52 programmers sampled. The results suggest that such an inductive system can serve as a practical mechanism for effectively identifying reusable code modules in terms of their structural properties.

scholarly journals Cerebral cortex classification by conditional random fields applied to intraoperative thermal imaging

2016 ◽  
Vol 2 (1) ◽  
pp. 475-478
Author(s):  
Nico Hoffmann ◽  
Edmund Koch ◽  
Uwe Petersohn ◽  
Matthias Kirsch ◽  
Gerald Steiner
Keyword(s):  
Cerebral Cortex ◽  
Random Fields ◽  
Conditional Random Fields ◽  
Intraoperative Imaging ◽  
A Priori ◽  
Approaches To Learning ◽  
Time Frequency ◽  
Classification Framework ◽  
Preprocessing Technique ◽  
High Level

AbstractIntraoperative thermal neuroimaging is a novel intraoperative imaging technique for the characterization of perfusion disorders, neural activity and other pathological changes of the brain. It bases on the correlation of (sub-)cortical metabolism and perfusion with the emitted heat of the cortical surface. In order to minimize required computational resources and prevent unwanted artefacts in subsequent data analysis workflows foreground detection is a important preprocessing technique to differentiate pixels representing the cerebral cortex from background objects. We propose an efficient classification framework that integrates characteristic dynamic thermal behaviour into this classification task to include additional discriminative features. The first stage of our framework consists of learning this representation of characteristic thermal time-frequency behaviour. This representation models latent interconnections in the time-frequency domain that cover specific, yet a priori unknown, thermal properties of the cortex. In a second stage these features are then used to classify each pixel’s state with conditional random fields. We quantitatively evaluate several approaches to learning high-level features and their impact to the overall prediction accuracy. The introduction of high-level features leads to a significant accuracy improvement compared to a baseline classifier.

scholarly journals In situ nuclear-glass corrosion under geological repository conditions

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Mathieu Debure ◽  
Yannick Linard ◽  
Christelle Martin ◽  
Francis Claret
Keyword(s):  
Pure Water ◽  
Secondary Phase ◽  
Predictive Modelling ◽  
Diffusion Experiment ◽  
Secondary Phases ◽  
Glass Corrosion ◽  
Geological Repository ◽  
High Level ◽  
Rock Supports

Abstract Silicate glasses are durable materials but laboratory experiments reveal that elements that derive from their environment may induce high corrosion rates and reduce their capacity to confine high-level radioactive waste. This study investigates nuclear-glass corrosion in geological media using an in situ diffusion experiment and multi-component diffusion modelling. The model highlights that the pH imposed by the Callovo–Oxfordian (COx) claystone host rock supports secondary-phase precipitation and increases glass corrosion compared with pure water. Elements from the COx rock (mainly Mg and Fe) form secondary phases with Si provided by the glass, which delay the establishment of a passivating interface. The presence of elements (Mg and Fe) that sustain glass alteration does not prevent a significant decrease in the glass-alteration rate, mainly due to the limited species transport that drives system reactivity. These improvements in the understanding of glass corrosion in its environment provide further insights for predictive modelling over larger timescales and space.

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