Kooperativer Bibliotheksverbund

UID:

Umfang: 1 online resource (294 pages)

Ausgabe: 1st ed.

ISBN: 0-323-95302-6

Anmerkung: Front Cover -- Mechanoluminescence in Organic and Inorganic Compounds -- Copyright Page -- Contents -- List of contributors -- About the editors -- Preface -- Acknowledgments -- 1 Luminescence: types and mechanism -- 1.1 Introduction -- 1.2 Characteristics and classification of luminescence -- 1.3 Mechanism of luminescence -- References -- 2 Advancements in instrumental setups for investigating mechanoluminescence -- 2.1 Introduction -- 2.1.1 Fractoluminescence -- 2.1.2 Triboluminescence -- 2.1.3 Elasticoluminescence -- 2.1.4 Plastico-mechanoluminescence -- 2.1.5 Piezoluminescence -- 2.1.6 Electrochemiluminescence -- 2.1.7 Sonoluminescence -- 2.2 Examples of mechanoluminescence materials and applications -- 2.3 Experimental techniques -- 2.3.1 Experimental setup of impulsive technique -- 2.4 Experimental setup of compression and tensile testing technique -- 2.5 Compression testing -- 2.6 Tensile testing -- 2.7 Experimental setup of bending and flexing technique -- 2.8 Bending technique -- 2.9 Flexing technique -- 2.10 Experimental setup of fracture or crack-induced technique -- 2.11 Experimental setup of tribological technique -- 2.12 Laboratory apparatus used to measure triboluminescence -- 2.13 Laboratory apparatus used to measure fractoluminescence -- 2.14 Laboratory apparatus used to measure the lastic-mechanoluminescence -- 2.15 Laboratory apparatus used to measure the plastico-mechanoluminescence -- 2.16 Mechanoluminescent materials -- 2.17 Conclusions -- Acknowledgments -- References -- 3 Synthesis of organic and inorganic mechanoluminescent compounds -- 3.1 Introduction -- 3.2 Synthesis methodologies -- 3.2.1 Solid-state reaction method -- 3.2.2 Sol-gel synthesis method -- 3.2.3 Microwave-assisted method -- 3.2.3.1 Quaternary oxysulfide -- 3.2.3.2 Niobates and stannates -- 3.2.4 Mechanoluminescent inorganic materials. , 3.2.5 Mechanoluminescence of organic materials -- 3.3 Conclusions -- References -- 4 Impact of doping on mechanoluminescence -- 4.1 Introduction -- 4.2 Difference between triboluminescence and mechanoluminescence -- 4.3 Representation of ML phosphor -- 4.4 Dependence of mechanoluminescence on crystal structures -- 4.5 Mechanism of mechanoluminescence -- 4.6 Impact of doping on mechanoluminescence -- 4.6.1 Effect of doped ions on mechanoluminescence spectra -- 4.6.2 Effect of doping rare earth metal ions on mechanoluminescence -- 4.6.3 Different host materials and their mechanoluminescence properties on doping -- 4.6.3.1 Mechanoluminescence in halides -- 4.6.3.2 Mechanoluminescence in sulfides -- 4.6.3.3 Mechanoluminescence in oxysulfides -- 4.6.3.4 Mechanoluminescence in oxides -- 4.7 Conclusion -- References -- 5 Mechanoluminescence for display devices -- 5.1 Introduction -- 5.2 ML materials for display applications -- 5.2.1 Inorganic ML materials -- 5.2.2 Organic materials -- 5.2.3 Polymer composites -- 5.2.4 Biological materials -- 5.3 Origin of ML -- 5.4 Methodology -- 5.5 Outlook -- References -- 6 Mechanoluminescence for infrastructure, health, and safety applications -- 6.1 Introduction -- 6.2 Mechanism of mechanoluminescence -- 6.2.1 Elastico-mechanoluminescence based on the electrostatic interaction at dislocations -- 6.2.2 Elastico-mechanoluminescence based on electron detrapping caused by piezoelectricity -- 6.3 Mechanoluminescent materials -- 6.4 Mechanoluminescence for infrastructure, health, and protection -- 6.4.1 Mechanoluminescence applications in buildings and other structures -- 6.4.2 Mechanoluminescence for health -- 6.4.2.1 Biomimetic multifunctional E-skins integrated with mechanoluminescence -- 6.4.3 Mechanoluminescence for safety applications -- 6.5 Future prospects and conclusion -- References. , 7 Mechanoluminescence in anticounterfeiting -- 7.1 Introduction -- 7.2 Mechanoluminescence: mechanisms and experimental methodology -- 7.2.1 Mechanism of mechanoluminescence -- 7.2.2 Experimental methodology -- 7.3 Factors affecting mechanoluminescence -- 7.4 Triboluminescence and its applications in anticounterfeiting technology -- 7.4.1 Comparison of triboluminescence and piezoluminescence in terms of their mechanoluminescence efficiency and sensitivity -- 7.4.1.1 Sensitivity -- 7.5 Materials for mechanoluminescence-based anticounterfeiting -- 7.5.1 Zinc sulfide -- 7.5.2 Zinc oxide -- 7.5.3 Strontium aluminate -- 7.5.3.1 Advantages -- 7.5.4 Barium aluminate -- 7.6 Advances in mechanoluminescence materials -- 7.6.1 Metal-organic frameworks -- 7.6.2 Organic materials -- 7.6.3 Inorganic materials -- 7.6.4 Hybrid materials -- 7.7 Applications of mechanoluminescence in anticounterfeiting -- 7.7.1 Currency authentication -- 7.7.2 Secure packaging -- 7.7.3 Product authentication -- 7.7.4 Document security -- 7.8 Challenges and future directions -- 7.9 Conclusion -- References -- 8 Mechanoluminescence for electronic skins and wearable devices -- 8.1 Introduction -- 8.2 Displays and sensors in electronic skins and wearable devices -- 8.2.1 Technical requirements in wearable devices -- 8.2.1.1 Flexibility and stretchability -- 8.2.1.2 Spatial resolution -- 8.2.1.3 Energy-saving or self-powering feature -- 8.2.1.4 Remoteness -- 8.2.1.5 Self-healing ability -- 8.2.1.6 Biocompatibility -- 8.2.2 Display technologies in wearable devices -- 8.2.2.1 OLEDs for flexible displays -- 8.2.2.2 QLEDs for flexible displays -- 8.2.2.3 Mini/micro-LEDs for wearable devices -- 8.2.3 Stress sensing technologies in wearable devices -- 8.2.3.1 Piezoresistive stress sensors -- 8.2.3.2 Capacitive stress sensors -- 8.2.3.3 Optical stress sensors. , 8.2.3.4 Piezoelectric stress sensors -- 8.2.3.5 Triboelectric stress sensors -- 8.2.4 Overview of ML in electronic skins and wearable devices -- 8.3 ML for self-powered displays in wearable devices -- 8.3.1 Technical route -- 8.3.2 Key features -- 8.3.2.1 Emission spectra -- 8.3.2.2 Brightness -- 8.3.2.3 Durability -- 8.3.3 Recent progress -- 8.3.3.1 Developing ML materials for self-powered displays -- 8.3.3.2 Designing the structure of ML-based devices for self-powered displays -- 8.4 ML for stress sensing in wearable devices -- 8.4.1 Technical route -- 8.4.1.1 Structural configuration -- 8.4.1.2 Photodetector -- 8.4.1.3 Information acquisition of the sensor -- 8.4.1.4 Key features -- 8.4.1.5 Response time -- 8.4.1.6 Spatial resolution -- 8.4.1.7 Self-powering -- 8.4.1.8 Multimode sensing -- 8.4.2 Recent progress -- 8.4.2.1 ML-based sensors for electronic skins and wearable devices -- 8.4.2.2 Optical/electrical dual-channel sensors for electronic skins and wearable devices -- 8.5 Challenges and prospects -- 8.5.1 To enhance the functional features of ML materials and devices -- 8.5.2 To construct integrated intelligent systems -- 8.5.3 To improve the device architecture and manufacturing technology for large-scale production -- References -- 9 Mechanoluminescence for reconstructing 3D ultrasonic field -- 9.1 Introduction -- 9.2 Experiment -- 9.2.1 Basic concepts -- 9.2.2 Mechanoluminescent compounds -- 9.2.3 Methods -- 9.3 Back-projection tomography -- 9.4 Acoustically induced piezoluminescence visualization method -- 9.5 Solid-state reaction method -- 9.6 Literature review of specific applications of ML in 3D ultrasound imaging -- 9.7 Discussion -- 9.8 Conclusion -- References -- Further reading -- 10 Other emerging applications of mechanoluminescence and outlook -- 10.1 Introduction -- 10.2 History of ML applications. , 10.3 Classical applications of ML -- 10.3.1 Understanding ML in crystals -- 10.3.2 ML in stress sensing -- 10.3.3 ML in damage sensing -- 10.4 Other emerging applications -- 10.4.1 Force-induced charge carrier storage -- 10.4.2 ML in medicals -- 10.4.3 Skin sensing and artificial intelligence -- 10.4.4 Cracked bones detection -- 10.4.5 ML in optogenetics and drug delivery system -- 10.4.6 Wearable electronics -- 10.4.7 Sensing other fields -- 10.4.8 Wind-driven mechanoluminescence -- 10.4.9 Radiation dosimetry -- 10.4.10 Military and aerospace applications -- 10.4.11 Light sources and displays -- 10.4.12 Other applications -- 10.5 Challenges -- 10.6 Summary -- References -- Index -- Back Cover.

Weitere Ausg.: ISBN 0-323-95301-8

Sprache: Englisch

UID:

Umfang: 1 online resource (294 pages)

ISBN: 0-323-85709-4

Serie: Hybrid Computational Intelligence for Pattern Analysis and Understanding

Inhalt: "Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis."--

Anmerkung: Front Cover -- Advanced Data Mining Tools and Methods for Social Computing -- Copyright -- Dedication -- Contents -- List of contributors -- Preface -- 1 An introduction to data mining in social networks -- 1.1 Introduction -- 1.2 Data mining concepts -- 1.2.1 Text mining -- 1.2.2 Image mining and video mining -- 1.2.3 Web data mining -- 1.2.4 Mining sequence patterns -- 1.2.5 Mining time series data -- 1.2.5.1 Hidden community mining -- 1.2.6 Association rule mining -- 1.2.7 Sequential pattern mining -- 1.2.8 Data warehouse and OLAP -- 1.2.8.1 OLAP -- 1.2.8.2 Classification of data warehouses -- 1.3 Social computing -- 1.3.1 Social networks -- 1.3.2 Social network representation -- 1.3.3 Network representation learning -- 1.3.4 Influence analysis -- 1.3.5 Sentiment analysis -- 1.4 Clustering and classification -- 1.4.1 Clustering algorithms -- 1.4.2 Multi-view clustering -- 1.4.3 Applications to data mining and social networking -- References -- 2 Performance tuning of Android applications using clustering and optimization heuristics -- 2.1 Introduction -- 2.2 Related work -- 2.3 Research methodology -- 2.4 Subject applications -- 2.5 Implementation phase 1 - clustering and knapsack solvers -- 2.5.1 Run requirement and gather clustering information -- 2.5.2 Formation of clusters -- 2.5.3 Knapsack solver replication -- 2.5.4 Optimization using the genetic algorithm -- 2.5.4.1 GA implementation with example -- 2.6 Implementation phase 2 - Ant colony optimization -- 2.6.1 Case study -- 2.7 Results and findings -- 2.8 Threats to validity -- 2.9 Conclusion -- References -- 3 Sentiment analysis of social media data evolved from COVID-19 cases - Maharashtra -- 3.1 Introduction -- 3.1.1 Cases -- 3.1.2 Structure of the virus -- 3.1.3 Life of coronavirus -- 3.2 Literature review -- 3.3 Proposed design -- 3.3.1 Problem statement -- 3.3.2 Architecture. , 3.3.3 Algorithm -- 3.3.4 Analysis of tweets as per sentiments -- 3.4 Analysis and predictions -- 3.4.1 Dataset -- 3.4.2 Accuracy comparison graph -- 3.4.3 Tweet analysis graph -- 3.5 Conclusion -- 3.6 Acknowledgment -- References -- 4 COVID-19 outbreak analysis and prediction using statistical learning -- 4.1 Introduction -- 4.2 Related literature -- 4.3 Proposed model -- 4.4 Prophet -- 4.5 Results and discussion -- 4.6 Conclusion -- References -- 5 Verbal sentiment analysis and detection using recurrent neural network -- 5.1 Introduction -- 5.2 Sources for sentiment detection -- 5.2.1 Sentiment in text -- 5.2.2 Sentiment analysis in visionary data -- 5.2.3 Sentiment analysis in speech -- 5.3 Literature survey -- 5.4 Machine learning techniques for sentiment analysis -- 5.5 Proposed method -- 5.5.1 Feature extraction -- 5.5.2 Spectral centroid -- 5.5.3 Spectral roll-off -- 5.5.4 Spectral flux -- 5.5.5 Mel-frequency cepstral coefficient -- 5.5.6 Pitch -- 5.5.7 Multi-layer perceptron -- 5.5.8 Radial basis function network -- 5.5.9 Probabilistic neural network -- 5.5.10 Recurrent neural network -- 5.5.11 Deep RNNs with multi-layer perceptron -- 5.5.12 Deep input to hidden -- 5.5.13 Deep hidden to hidden and output -- 5.5.14 Gradient-based learning methods -- 5.6 Results and discussion -- 5.7 Conclusions -- References -- 6 A machine learning approach to aid paralysis patients using EMG signals -- 6.1 Introduction -- 6.2 Associated works -- 6.3 System model -- 6.3.1 System architecture -- 6.3.2 Connecting surface EMG electrodes -- 6.3.3 Feature extraction -- 6.3.4 Classifiers -- 6.4 Simulation and results -- 6.4.1 Simulation of circuits on Proteus software -- 6.4.2 Implementation and results of machine learning algorithms -- 6.5 Conclusion -- References -- 7 Influence of traveling on social behavior -- 7.1 Introduction -- 7.2 Related work. , 7.3 Importance of social networking in real life -- 7.4 Dynamics of traveling -- 7.5 Dynamics-based social behavior analysis -- 7.5.1 Categorical behavioral analysis -- 7.5.2 Online behavior recognition -- 7.5.3 Age group-based comparative analysis -- 7.5.4 Influence of traveling on human behavior -- 7.6 Recognition of human social behavior using machine learning techniques -- 7.7 Conclusion -- References -- 8 A study on behavior analysis in social network -- 8.1 Introduction -- 8.2 Basic concepts of behavior analysis in social networks -- 8.2.1 Individual behavior -- 8.2.1.1 Methodology -- 8.2.1.2 Modeling -- 8.2.2 Collective behavior -- 8.2.2.1 Collective behavior analysis -- 8.2.2.2 Modeling -- 8.3 Uses of behavior analysis in social networks -- 8.3.1 User behavior in community joining and its features 8.7 -- 8.3.2 Collaborative study prediction -- 8.3.3 Related works -- 8.4 Future direction -- 8.5 Conclusion -- References -- 9 Recent trends in recommendation systems and sentiment analysis -- 9.1 Introduction -- 9.2 Basic terms and concepts of sentiment analysis and recommendation systems -- 9.3 Overview of sentiment analysis approaches in recommendation systems -- 9.4 Recent developments (related work) -- 9.5 Challenges -- 9.6 Future direction -- 9.7 Conclusion -- References -- 10 Data visualization: existing tools and techniques -- 10.1 Introduction -- 10.2 Prior research works on data visualization issues -- 10.3 Challenges during visualization of innumerable data -- 10.4 Existing data visualization tools and techniques with key characteristics -- 10.4.1 Amcharts [19] -- 10.4.2 Arbor.Js [20] -- 10.4.3 Better World Flux [21] -- 10.4.4 CartoDB [22] -- 10.4.5 Chart.js [23] -- 10.4.6 Chroma.js [24,25] -- 10.4.7 Circos [26] -- 10.4.8 Cola.Js [27,28] -- 10.4.9 Colorbrewer [29,30] -- 10.4.10 Creately [31] -- 10.4.11 Crossfilter [32]. , 10.4.12 CSV [33] -- 10.4.13 JSON [34] -- 10.4.14 Cubism.js [35,36] -- 10.4.15 Cytoscape [37] -- 10.4.16 Cytoscape.js [38,39] -- 10.4.17 D3.Js [40] -- 10.4.18 Dance.Js [41] -- 10.4.19 Dapresy [42] -- 10.4.20 Data.js [43] -- 10.4.21 Databoard [44] -- 10.4.22 Wrangler [45,46] -- 10.4.23 Degrafa [47] -- 10.4.24 DhtmlxChart [48,49] -- 10.4.25 Dipity [50,51] -- 10.4.26 Dygraphs [52] -- 10.4.27 BIRT [53,54] -- 10.4.28 Envision.Js [55,56] -- 10.4.29 Eurostat [57] -- 10.4.30 Excel [58] -- 10.4.31 Excel Map/Power Map [59] -- 10.4.32 Exhibit [60] -- 10.4.33 Factmint [61] -- 10.4.34 FF Chartwell [62] -- 10.4.35 Flare [63,64] -- 10.4.36 Flare [65] -- 10.4.37 Flowingdata [66] -- 10.4.38 Fusioncharts Suite Xt [67] -- 10.4.39 GeoCommons [68] -- 10.4.40 Gephi [69] -- 10.4.41 Google Chart [70] -- 10.4.42 Google Fusion Tables [71] -- 10.4.43 Google Maps [72] -- 10.4.44 Google Public Data [73] -- 10.4.45 Google Sheets [74] -- 10.4.46 Highcharts [75] -- 10.4.47 Highmaps [76] -- 10.4.48 iWantHue [77,78] -- 10.4.49 iCharts [79] -- 10.4.50 InetSoft [80] -- 10.4.51 Infoactive [81] -- 10.4.52 Infocaptor [82] -- 10.4.53 Inkscape [83] -- 10.4.54 InstantAtlas [84] -- 10.4.55 JavaScript InfoVis Toolkit [85] -- 10.4.56 JfreeChart [86,87] -- 10.4.57 Jolicharts [88] -- 10.4.58 JpGraph [89] -- 10.4.59 JqPlot [90] -- 10.4.60 jQuery Visualize [91] -- 10.4.61 JSter [92] -- 10.4.62 Kartograph [93] -- 10.4.63 Knoema [94] -- 10.4.64 Leaflet [95] -- 10.4.65 LiveGap Charts [96] -- 10.4.66 Many Eyes [97] -- 10.4.67 Mapbox [98] -- 10.4.68 Mapchart.Net [99] -- 10.4.69 Maps Marker WP Plugin [100] -- 10.4.70 Miso [101] -- 10.4.71 Modest Maps [102] -- 10.4.72 Mr. Data Converter [103] -- 10.4.73 Mr. Nester [104] -- 10.4.74 Myheatmap [105] -- 10.4.75 Networkx [106] -- 10.4.76 Nevron Vision [107] -- 10.4.77 NodeBox [108] -- 10.4.78 NVD3 [109] -- 10.4.79 OpenLayers [110] -- 10.4.80 OpenRefine [111]. , 10.4.81 Paper.Js [112] -- 10.4.82 Peity [113] -- 10.4.83 Piktochart [114] -- 10.4.84 Plot [115] -- 10.4.85 Polymaps [116] -- 10.4.86 Processing and Processing.Js [117,118] -- 10.4.87 Protovis [119] -- 10.4.88 Q Research Software [120] -- 10.4.89 Qlik Sense and Qlikview [121,122] -- 10.4.90 Quadrigram [123] -- 10.4.91 R [124] -- 10.4.92 Raphael [125] -- 10.4.93 RAW [126] -- 10.4.94 Recline.Js [127] -- 10.4.95 Rickshaw [128] -- 10.4.96 SAS Visual Analytics [129] -- 10.4.97 Shield UI [130] -- 10.4.98 Sigma.Js [131] -- 10.4.99 Silk [132] -- 10.4.100 Smart Data Report [133] -- 10.4.101 StatSilk [134] -- 10.4.102 SVG Crowbar [135] -- 10.4.103 Tableau Public [136] -- 10.4.104 Tabula [137,138] -- 10.4.105 Tangle [139] -- 10.4.106 Teechart [140] -- 10.4.107 Timeline [141,142] -- 10.4.108 TimelineJS [143] -- 10.4.109 Unfolding [144] -- 10.4.110 Ushahidi [145] -- 10.4.111 Vancharts [146] -- 10.4.112 Vega [147] -- 10.4.113 Vida [148] -- 10.4.114 Visage [149] -- 10.4.115 Visualize Free [150] -- 10.4.116 Weka [151] -- 10.4.117 WolframAlpha [152] -- 10.4.118 Yazoo Easydata [153] -- 10.4.119 Zebra BI [154] -- 10.4.120 ZingChart [155] -- 10.4.121 ZoomCharts [156] -- 10.4.122 Weave [157-159] -- 10.4.123 Dundas Dashboard [160] -- 10.4.124 Simile [161] -- 10.4.125 Datawatch Desktop [162] -- 10.4.126 Prefuse [163] -- 10.4.127 MangoDB Compass [164] -- 10.5 Conclusion -- References -- 11 An intelligent agent to mine for frequent patterns in uncertain graphs -- 11.1 Introduction -- 11.1.1 Objectives of the proposed model -- 11.2 Related work -- 11.3 Mining graphs and uncertainty -- 11.3.1 Mining graph -- 11.3.2 Vertex attribute graphs -- 11.3.3 Subgraph discovery -- 11.3.4 Uncertain graph -- 11.3.4.1 Data mining uncertainty -- 11.3.4.2 Risk -- 11.3.4.2.1 Estimation of hazard -- 11.3.4.2.2 Knighting risk -- 11.4 Methodology -- 11.4.1 Enumeration algorithm. , 11.4.2 Evaluation algorithm.

Weitere Ausg.: ISBN 0-323-85708-6

Sprache: Englisch

UID:

Umfang: 1 online resource (522 pages)

ISBN: 0-323-90343-6

Inhalt: "Ecological Significance of Riparian Ecosystems: Challenges and Management Strategies examines the current issues related to river ecosystems, their environmental importance, pollution issues and potential management strategies. The book is divided into 4 key themes: Basics of river ecosystem, Natural phenomenon of river ecosystem, Human-induced problems of river ecosystem, and Management measures for the river ecosystem. Through these four themes, the contributors present both practical and theoretical aspects of river ecosystem in changing climate. An emphasis has been made on the recent research of climate change and its impact on the river ecosystem."--

Anmerkung: Front cover -- Half title -- Full title -- Copyright -- Contents -- Contributors -- Chapter 1 - An overview of human health risk from opium alkaloids and related pharmaceutical products pollution in aquati ... -- 1.1 Introduction -- 1.2 Opium and alkaloid-based industries -- 1.2.1 Health effects of opium -- 1.2.1.1 Oxidative stress -- 1.2.1.2 Increased plasminogen activator inhibitor-1 -- 1.2.1.3 Decreased plasma adiponectin -- 1.2.1.4 Deficiency of testosterone and estrogen -- 1.2.1.5 Hyperprolactinemia -- 1.2.1.6 Insulin resistance -- 1.2.2 Addiction due to psychoactive drugs -- 1.2.3 Extraction of opium from poppy -- 1.2.4 Characteristics of opium alkaloid wastewater -- 1.2.5 Government opium and alkaloid factories -- 1.2.5.1 Products of the factory -- 1.3 Active pharmaceutical ingredients -- 1.4 Impacts of pharmaceutical products on aquatic ecosystem -- 1.5 Effects of various opium alkaloids on human health -- 1.6 Treatment approach -- 1.6.1 Physicochemical treatment -- 1.6.2 Biological treatment -- 1.6.2.1 Aerobic treatment -- 1.6.2.2 Anaerobic treatment -- 1.6.3 Membrane separation -- 1.6.4 Fenton's oxidation -- 1.7 Concluding remarks -- Conflict of Interest -- Acknowledgment -- References -- Chapter 2 - Impact of pharmaceuticals and antibiotics waste on the river ecosystem: a growing threat -- 2.1 Introduction -- 2.2 Pharmaceuticals and antibiotics waste -- 2.3 Rules and regulations for surveillance of pharmaceuticals and antibiotics in water ecosystem -- 2.4 Sources of pharmaceuticals and antibiotics in water ecosystem -- 2.5 Impact of pharmaceuticals and antibiotics on aquatic ecosystem -- 2.5.1 Impact on freshwater system -- 2.5.2 Probable environmental impact of pharmaceuticals via behavioral changes -- 2.5.3 Bioaccumulation -- 2.5.4 Chronic effects on human health. , 2.5.4.1 Physiological effects -- 2.5.4.2 Effect on host microbiomes -- 2.5.4.3 Antimicrobial resistance -- 2.5.5 Impact on aquatic animals -- 2.6 Approaches for remediation of pharmaceuticals and antibiotics -- 2.6.1 Biodegradation -- 2.6.2 Absorption -- 2.6.3 Membrane processes -- 2.6.4 Coagulation, flocculation, and sedimentation -- 2.6.5 Advance oxidation process -- 2.6.6 Ion exchange -- 2.6.7 Photolysis -- 2.7 Preventing future pharmaceutical waste contamination -- 2.7.1 Minimization and reduction -- 2.7.1.1 Healthy lifestyle -- 2.7.1.2 Public awareness -- 2.7.1.3 Patient compliance and education -- 2.7.1.4 Health care practitioner's education -- 2.7.1.5 Marketing presentations -- 2.7.2 Reuse and recycling -- 2.7.2.1 Donation and recycle of medicines -- 2.7.3 Proper disposal -- 2.7.3.1 Take back programs -- 2.8 Conclusion -- References -- Chapter 3 - Heavy metal contamination in the river ecosystem -- 3.1 Introduction -- 3.1.1 River ecosystem -- 3.1.2 Sources and contamination of the rivers -- 3.1.3 Classifications of river contaminants -- 3.2 Heavy metals contamination in the rivers -- 3.2.1 Sources of heavy metals in the river water -- 3.2.2 Bioaccumulation and biomagnification of heavy metals -- 3.2.3 Adverse health impact on the organism -- 3.3 Preventive strategies to deal with heavy metal contamination in water -- 3.4 Conclusion -- References -- Chapter 4 - Factors influencing the alteration of microbial and heavy metal characteristics of river systems in the Niger ... -- 4.1 Introduction -- 4.2 River systems in the Niger Delta -- 4.3 Characteristics of river systems in the Niger Delta -- 4.3.1 Iron -- 4.3.2 Zinc -- 4.3.3 Cadmium -- 4.3.4 Chromium -- 4.3.5 Lead -- 4.3.6 Mercury -- 4.3.7 Copper -- 4.3.8 Cobalt -- 4.3.9 Nickel -- 4.3.10 Manganese -- 4.3.11 Arsenic. , 4.3.12 Microbial characteristics -- 4.3.12.1 Microbial population -- 4.3.12.2 Microbial diversity -- 4.4 Factors influencing the alteration of rivers system quality in the Niger Delta -- 4.4.1 Anthropogenic activities -- 4.4.2 Poor waste management -- 4.4.3 Industrial effluents -- 4.4.4 Oil and gas -- 4.4.5 Dredging -- 4.4.6 Agriculture -- 4.4.7 Makeshift or artisanal refinery -- 4.4.8 Water transportation -- 4.4.9 Human induced natural effects -- 4.5 Conclusion and the way forward -- References -- Chapter 5 - Impact of climate change on the river ecosystem -- 5.1 Introduction -- 5.2 River ecosystem -- 5.3 General flow pattern of river -- 5.4 Channelization of river -- 5.5 Impact of climate change on river ecosystem -- 5.6 Changes of streamflow and flood/drought indices -- 5.7 Climatic adaptations -- 5.8 Mitigating the effects of climatic change -- 5.9 Conclusion -- References -- Chapter 6 - Geospatial technology for sustainable management of water resources -- 6.1 Introduction -- 6.1.1 Water light and interaction (IOP and AOP) -- 6.1.2 Remote sensing strength in river ecosystems -- 6.2 River ecosystem management -- 6.3 Remote Sensing for delineation of river systems -- 6.3.1 River ecosystem network extraction using remote sensing -- 6.4 Monitoring water budget components: remote sensing-based observations -- 6.4.1 Precipitation -- 6.4.1.1 Multisatellite algorithms for precipitation -- 6.4.2.1 METRIC ET data access using EE flux -- 6.4.3 Surface water -- 6.4.4 Groundwater -- 6.5 Remote sensing in water quality monitoring -- 6.5.1 Role of hyperspectral data -- 6.6 Synthetic aperture radar data in river monitoring -- 6.7 Future scope of water quality -- 6.7.1 Satellites of geosynchronous earth orbit for wide range of coverage -- 6.7.2 Joint polar satellite system -- 6.7.3 Hyperspectral missions. , 6.7.4 Sub surface water from GRACE-FO and NASA ISRO synthetic aperture radar mission (NISAR) -- 6.7.5 Surface water ocean topography -- 6.7.6 Sentinel 6B -- 6.7.7 Landsat 9 -- 6.8 Conclusion -- Acknowledgment -- References -- Chapter 7 - Chemical and isotopic variability of Bhagirathi river water (Upper Ganga), Uttarakhand, India -- 7.1 Introduction -- 7.2 Study area and methodology -- 7.3 Major ion chemistry of Bhagirathi river -- 7.4 Isotopic studies of Bhagirathi river -- 7.5 Discussion and conclusion -- Acknowledgments -- References -- Chapter 8 - Occurrence and distribution of perfluoroalkyl acids in rivers: Impact and risk assessment -- 8.1 Introduction -- 8.2 Naming conventions and uses -- 8.2.1 Anionic form of chemical names -- 8.2.2 "PFAS", not "PFASs" -- 8.2.3 Families of PFAS -- 8.3 Sources of the perfluoroalkyl acids -- 8.4 Environmental fate and transport process -- 8.5 Occurrence and distribution in rivers and sediment -- 8.6 Ecological and health effects -- 8.7 Regulation -- 8.7.1 Safe drinking water act -- 8.7.2 Toxic substances control act (TSCA) -- 8.8 Remediation techniques -- 8.8.1 Adsorption -- 8.8.2 Membrane filtration -- 8.8.3 Advanced oxidation process -- 8.8.4 Plasma -- 8.8.5 Biodegradation process -- 8.8.6 Thermal destruction -- 8.8.7 Sonochemical degradation -- 8.9 Conclusion -- References -- Chapter 9 - Socio-economic perspective of river health: A case study of river Ami, Uttar Pradesh, India -- 9.1 The framework -- 9.2 Methodology -- 9.2.1 Study area -- 9.2.2 Water quality parameter -- 9.3 Impact and vulnerabilities -- 9.3.1 Social -- 9.3.1.1 Health and population -- 9.3.1.2 Livelihood -- 9.3.1.3 Aesthetic and spiritual value -- 9.3.2 Environmental -- 9.3.2.1 Biodiversity -- 9.3.2.2 Water quality and pollution -- 9.3.2.3 Flood and drought -- 9.3.2.4 Ecological. , 9.3.3 Economical -- 9.3.3.1 Agriculture and irrigation -- 9.3.3.2 Tourism and recreations -- 9.3.3.3 Fisheries -- 9.3.3.4 Manufacturing and industry -- 9.3.3.5 Transportation -- 9.4 Result and discussion -- 9.4.1 Source of pollution -- 9.4.2 Status of pollution -- 9.4.3 Strategies to improve water quality -- 9.4.4 Effect of socioeconomic measures -- 9.5 Conclusions -- References -- Chapter 10 - Sources of ions in the river ecosystem -- 10.1 Introduction -- 10.2 Source of ions in the water body -- 10.2.1 Agronomical production -- 10.2.1.1 Agricultural nutrients -- 10.2.1.2 Pesticides -- 10.2.1.3 Salts -- 10.2.1.4 Sediment -- 10.2.2 Livestock production -- 10.2.2.1 Organic matter -- 10.2.3 Fisheries -- 10.2.3.1 Other elements -- 10.3 Determinant water quality parameters -- 10.3.1 Thermal regime of the river -- 10.3.2 Flow regime -- 10.3.3 Light/opaqueness -- 10.3.4 Water conductivity -- 10.3.5 Concentration of dissolved gases -- 10.3.6 Acidity and alkalinity of river water -- 10.3.7 Major cations and anions in the river -- 10.3.8 Dissolved nutrients -- 10.3.9 Land use/land cover alteration -- 10.3.10 Expansion in urban settlement -- 10.4 Effective measures for maintaining and restoring the river water quality -- 10.4.1 Phytoremediation -- 10.4.2 Rhizofiltration -- 10.4.3 Heavy metal pollutant control methods -- 10.4.4 Chemical precipitation -- 10.4.5 Coagulation-flocculation -- 10.4.6 Flotation -- 10.4.7 Aeration -- 10.4.8 Membrane filtration -- 10.4.9 Ion exchange -- 10.4.10 Use of reed plants -- 10.4.11 Electrochemical treatment -- 10.4.12 Microbial biosorption -- 10.4.13 Use of plants for the treatment of pollutant -- 10.5 Conclusion -- References -- Chapter 11 - Nutrients contamination and eutrophication in the river ecosystem -- 11.1 Introduction -- 11.2 Sources of nutrients. , 11.3 Importance of aquatic plants.

Weitere Ausg.: Print version: Madhav, Sughosh Ecological Significance of River Ecosystems San Diego : Elsevier,c2022 ISBN 9780323850452

Sprache: Englisch

UID:

Umfang: 1 online resource (532 pages)

Ausgabe: Second edition.

ISBN: 0-443-16103-8

Anmerkung: Intro -- Computational Phytochemistry -- Copyright -- Contents -- Contributors -- Preface to the first edition -- Preface to the second edition -- Chapter 1: Computational phytochemistry: An overview -- 1.1. Introduction -- 1.2. Computational phytochemistry -- 1.3. Techniques, theories and applications of computational phytochemistry -- 1.3.1. Kohonen-based self-organizing map (SOM) -- 1.3.2. Density functional theory (DFT) -- 1.3.3. Docking experiments and virtual screening (in silico screening) -- 1.3.4. Structure prediction and structure determination -- 1.3.5. Chemometrics and principal component analysis (PCA) -- 1.3.6. Data-mining and databases -- 1.3.7. Response surface methodology (RSM) in optimization of extraction of phytochemicals -- 1.3.8. Computation in isolation of phytochemicals -- 1.3.9. Predictive toxicology based on QSAR (quantitative structure-activity relationship) -- 1.3.10. Miscellaneous -- 1.4. Conclusions -- Acknowledgement -- References -- Chapter 2: Response surface methodology (RSM) in phytochemical research -- 2.1. Introduction -- 2.2. Generic steps in response surface methodology -- 2.3. Application of response surface methodology (RSM) in phytochemical research -- 2.3.1. Optimization of extraction of phytochemicals -- Accelerated solvent extraction (ASE) -- Maceration and refluxing -- Microwave-assisted extraction (MAE) -- Soxhlet extraction -- Ultrasound-assisted extraction (UAE) -- 2.3.2. Optimization of herbal formulations/products -- 2.3.3. Optimization of oil extraction from plants -- 2.3.4. Optimization of solid char yield and its caloric value -- 2.3.5. Optimization of antibiotics removal from the environment by plant extracts -- 2.3.6. Optimization of hydrothermal processing -- 2.3.7. Optimization of steel corrosion inhibition using plant materials -- 2.3.8. Optimization of biodiesel production. , 2.4. Conclusion -- Acknowledgement -- References -- Chapter 3: Prediction of medicinal properties using mathematical models and computation, and selection of plant materials -- 3.1. Introduction -- 3.2. Mathematical models -- 3.3. Computational models in drug discovery -- 3.3.1. Structure-based CADD -- 3.3.2. Ligand-based CADD -- 3.3.3. Network pharmacology -- 3.4. Selection of medicinal plants -- 3.4.1. Ethnobotany-directed drug discovery -- 3.4.2. Chemotaxonomic and ecological approach -- 3.4.3. Random approach -- 3.4.4. Integrated approach -- 3.5. Role of medicinal plant databases -- 3.6. Tools and techniques -- 3.7. Role of data mining in medicinal plant selection -- 3.8. Safety considerations -- 3.9. Conclusion -- Acknowledgement -- References -- Chapter 4: Optimization of extraction using mathematical models and computation -- 4.1. Introduction -- 4.2. Designs of experiment (DOE) -- 4.2.1. Planning phase -- 4.2.2. Designing phase -- 4.2.3. Screening phase -- Central composite design (CCD) -- Full factorial design (2k) (FFD) -- Fractional factorial design (2k-p) -- Plackett-Burman design (PBD) -- Taguchi design -- 4.3. Optimization phase -- 4.4. Specific examples -- 4.5. Conclusion -- Acknowledgement -- References -- Chapter 5: Application of computational methods for the isolation of plant secondary metabolites -- 5.1. Introduction -- 5.2. Computational methods in natural products isolations -- 5.2.1. Automated flash chromatography (AFC) -- 5.2.2. High performance/pressure liquid chromatography (HPLC) -- 5.2.3. Ultra pressure/performance liquid chromatography (UPLC) -- 5.2.4. Counter current chromatography (CCC) -- 5.2.5. Capillary electrophoresis (CE) -- 5.2.6. Hyphenated techniques -- GC-MS -- LC-MS -- LC-NMR -- 5.3. Conclusion -- References -- Chapter 6: Application of computation in creating dereplicated phytochemical libraries. , 6.1. Introduction -- 6.2. Compound library -- 6.2.1. Combinatorial library -- 6.2.2. Phytochemical library -- 6.3. Dereplication -- 6.4. Application of computation in constructing dereplicated phytochemical libraries -- 6.5. Conclusions -- Acknowledgement -- References -- Chapter 7: High throughput screening of phytochemicals: Application of computational methods -- 7.1. Introduction -- 7.2. The pre-HTS era -- 7.3. High-throughput screening (HTS) -- 7.3.1. Reaction monitoring and observation -- 7.3.2. Advances in monitoring in vivo -- 7.3.3. Location of facilities -- 7.3.4. Is there a difference between so-called leads and drugs? -- 7.3.5. Visualization of data -- 7.3.6. Dose-response analysis -- 7.3.7. Examples of HTS success -- 7.4. HTS platforms for natural products/phytochemicals -- 7.4.1. What is a natural product? -- 7.4.2. Natural products for increasing diversity -- 7.4.3. Natural products sample preparation -- 7.4.4. Examples of HTS platforms for natural products/phytochemicals -- 7.5. High content screening -- 7.6. HTS screening against SARS-CoV-2 -- 7.7. Conclusions -- Acknowledgement -- References -- Chapter 8: Prediction of structure based on spectral data using computational techniques -- 8.1. Introduction -- 8.1.1. History of spectroscopy -- 8.1.2. Missasignments of structures: A rarity or more common than expected? -- 8.2. Structure elucidation strategies -- 8.3. What is density functional theory (DFT)? -- 8.4. Era of assignment vs prediction -- 8.4.1. Nuclear magnetic resonance (NMR) -- 8.4.2. Computational mass spectrometry -- 8.4.3. Chiral centres -- 8.4.4. Structure by calculations -- 8.4.5. UV spectroscopy -- 8.4.6. Infra-red (IR) spectroscopy -- 8.4.7. Database search algorithm -- 8.5. Can Raman be used for automated assays and HTS? -- 8.6. X-ray sponge technique -- 8.7. Data curation -- 8.8. Conclusions -- Acknowledgement. , References -- Chapter 9: Mathematical models and computation in plant metabolomics: An update -- 9.1. Introduction -- 9.2. Metabolomics approaches -- 9.2.1. Untargeted metabolomics -- 9.2.2. Targeted metabolomics -- 9.2.3. Metabolite fingerprinting -- 9.2.4. Metabolite profiling -- 9.3. Mathematical models in metabolomics -- 9.3.1. Stoichiometric modelling -- 9.3.2. Topological/centrality modelling -- 9.3.3. Petri net modelling -- 9.3.4. Mass action kinetic modelling -- 9.3.5. Lin-log kinetic modelling -- 9.3.6. Michalis-Menten kinetic modelling -- 9.4. Plant metabolomics -- 9.4.1. Metabolomics in crop improvement strategies -- 9.4.2. Metabolomics to predict sensory attributes of phytofood -- 9.4.3. Plant hormonomics -- 9.4.4. Plant-environment interactions -- 9.4.5. Metabolomics in medicinal plants research -- 9.5. Limitations in plant metabolomics and future prospects -- 9.6. Conclusion -- Acknowledgement -- References -- Chapter 10: Application of computation in the study of biosynthesis of phytochemicals -- 10.1. Introduction -- 10.2. Genome-mining tools, resources, and computational software for identification and analysis of BGCs -- 10.2.1. antiSMASH 6 -- 10.2.2. SMURF -- 10.2.3. BAGEL -- 10.2.4. NaPDos -- 10.2.5. MultiGeneBlast -- 10.2.6. eSNaPD -- 10.2.7. NRPSpredictor -- 10.2.8. BiosyntheticSPAdes -- 10.2.9. DeepBGC -- 10.2.10. Deep-BGCpred -- 10.2.11. RRE-Finder -- 10.2.12. BACTIBASE -- 10.2.13. DoBISCUIT -- 10.2.14. MIBiG -- 10.2.15. IMG-ABC -- 10.2.16. ClustScan database (CSDB) -- 10.2.17. ClusterMine360 -- 10.2.18. NORINE -- 10.3. Computational tools for metabolomics study -- 10.3.1. Cycloquest -- 10.3.2. NRPquest -- 10.3.3. RiPPquest -- 10.3.4. GNPS -- 10.3.5. Dereplicator -- 10.3.6. XCMS online -- 10.3.7. ReSpect -- 10.3.8. MS-DIAL 4.0 -- 10.3.9. MZmine2 -- 10.3.10. WebSpecmine -- 10.3.11. MetaX -- 10.3.12. Metabox. , 10.3.13. MetaboAnalyst 5.0 -- 10.4. Databases of secondary metabolites and chemical compounds -- 10.4.1. Dictionary of natural products -- 10.4.2. StreptomeDB -- 10.4.3. ChEBI -- 10.4.4. ChEMBL -- 10.4.5. PubChem -- 10.4.6. ChemSpider -- 10.4.7. COlleCtion of Open Natural prodUcTs (COCONUT) -- 10.4.8. NPBS database -- 10.4.9. NPASS database -- 10.4.10. TCM databases -- 10.4.11. GMD -- 10.4.12. METLIN -- 10.4.13. MassBank database -- 10.4.14. PlantCyc -- 10.4.15. MetaCyc -- 10.5. Tools for prediction of biochemical pathways -- 10.5.1. From metabolite to metabolite (FMM) -- 10.5.2. Biochemical network integrated computational explorer (BNICE) -- 10.5.3. RetroPath -- 10.5.4. DESHARKY -- 10.5.5. Cho system framework -- 10.5.6. BioNavi-NP -- 10.5.7. dGPredictor -- 10.5.8. MAPPS -- 10.5.9. PathPred -- 10.5.10. mApLe -- 10.6. Overview and conclusions -- References -- Chapter 11: Computational aids for assessing bioactivities in phytochemical and natural products research -- 11.1. Introduction: Computational aids and artificial intelligence in science and their role in bioactivity studies of na ... -- 11.2. Strategies for separation and identification of bioactive natural compounds for drug discovery -- 11.3. Bioactivity assessment in phytochemistry -- 11.3.1. Protein-based in vitro models -- 11.3.2. In vitro cell culture models -- 11.3.3. In situ and ex vivo models -- 11.3.4. Animal models -- 11.4. Computational tools for data analysis from metabolomics and bioactivity assessment data in natural product research ... -- 11.5. Data and text mining strategies -- 11.6. Virtual or in silico screening of natural products -- 11.7. Application of in silico assessment of bioactivities -- 11.7.1. Example of SARS-CoV-2 inhibitors -- SARS-CoV-2 main protease Mpro as target -- SARS-CoV-2 spike protein as target. , SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) as the target.

Weitere Ausg.: ISBN 0-443-16102-X

Sprache: Englisch

UID:

Umfang: 1 online resource (497 pages) : , illustrations

ISBN: 0-323-42890-8

Anmerkung: Front Cover -- Nanobiomaterials in Dentistry -- Copyright Page -- Contents -- List of contributors -- Preface of the series -- Preface -- About the Series (Volumes I-XI) -- About Volume XI -- 1 Nanobiomaterials in dentistry -- 1.1 Introduction -- 1.2 Nanomedicine -- 1.3 Nanobiomaterials Used in Dentistry -- 1.3.1 Photoactivated Restorative Nanomaterials Used in Dentistry -- 1.3.2 Nanosolutions -- 1.3.3 Esthetic Materials -- 1.3.4 Nano-Optimized Moldable Ceramics -- 1.3.5 Impression Materials -- 1.3.6 Nanoencapsulation -- 1.3.7 Other Products Manufactured -- 1.3.8 Materials to Induce Bone Growth -- 1.3.9 Nanoneedles -- 1.3.10 Self-Assembly -- 1.3.11 Nanomaterials for Periodontal Drug Delivery -- 1.3.12 Photodynamic Therapy -- 1.3.13 Implants -- 1.3.14 Dental Nanorobots -- 1.3.15 Nanocomposite Artificial Teeth -- 1.3.16 Dental Tissues and Nanostructures -- 1.3.17 Digital Dental Imaging -- 1.3.18 Applications of Nanotechnology in Oral and Maxillofacial Surgery -- 1.3.19 Nanotechnology for Preventing Dental Caries -- 1.3.19.1 Gold nanoparticles -- 1.3.19.2 Silver nanoparticles -- 1.3.19.3 Zinc oxide nanoparticles -- 1.3.19.4 Titanium dioxide nanoparticles -- 1.4 Conclusions -- References -- 2 Understanding dental implants -- 2.1 Introduction -- 2.2 Types of Dental Implants -- 2.2.1 Trends in Dental Implants Biomaterials -- 2.2.1.1 Ancient period (through AD 1000) to present -- 2.2.1.2 Polymers and composites -- 2.2.1.3 Metals and metal alloys -- 2.2.1.4 Titanium and its alloys Ti-6Al-4V -- 2.2.1.5 Ceramics -- 2.2.1.6 Zirconia -- 2.2.1.7 Carbon compounds -- 2.2.1.8 Titanium-zirconium alloy (Straumann Roxolid) -- 2.2.2 Dental Implant Configurations -- 2.2.2.1 Subperiosteal implants -- 2.2.2.2 The vitreous carbon implant -- 2.2.2.3 Blade-vent implants -- 2.2.2.4 The single-crystal sapphire implant -- 2.2.2.5 The Tübingen aluminum ceramic implant. , 2.2.2.6 The TCP-implant -- 2.2.2.7 The TPS-screw -- 2.2.2.8 The ITI hollow-cylinder implant -- 2.2.2.9 The IMZ dental implant -- 2.2.2.10 The core-vent titanium alloy implant -- 2.2.2.11 The transosteal, mandibular staple bone plate -- 2.2.2.12 The Brånemark osseointegrated titanium implant -- 2.2.3 Design and Technology in Dental Implantology -- 2.3 Dental Postimplantation Complications -- 2.3.1 Biofilms and Implant-Associated Infections -- 2.3.2 Avoiding Postsurgical Complications -- 2.4 Conclusions -- References -- 3 Effect of titanium dioxide nanoparticle on proliferation, drug-sensitivity, inflammation, and metabolomic profiling of hu... -- 3.1 Introduction -- 3.2 Chemical and Physical Properties of TiO2 NPs -- 3.3 Uses of TiO2 and TiO2 NPs -- 3.4 Nanotoxicology and Hormetic Response -- 3.5 Toxicity of TiO2 NPs in Dentistry -- 3.5.1 Lower Cytotoxicity of Ti Plates as Compared to Dental Metals -- 3.5.2 Cytotoxicity TiO2 NP Oral-Cultured Cells -- 3.5.3 Pro-Inflammatory Action of TiO2 NPs -- 3.5.4 Incorporation of TiO2 NPs in Oral Cells -- 3.5.5 Exploring Intracellular Target Molecules of TiO2 NPs -- 3.5.6 Exploring Anti-Inflammatory Substances that Target TiO2 NPs -- 3.6 Future Direction -- 3.7 Conclusions -- References -- 4 Biocements with potential endodontic use -- 4.1 Introduction -- 4.2 Synthesis and in vitro Bioactivity of Dicalcium Silicate and Tricalcium Aluminate -- 4.2.1 Synthesis and Characterization of Dicalcium Silicate -- 4.2.2 Synthesis and Characterization of Tricalcium Aluminate -- 4.2.3 In vitro Bioactivity of Dicalcium Silicate and Tricalcium Aluminate -- 4.3 Sol-Gel Synthesis, in vitro Bioactivity and Biological Assay of MTA Cements -- 4.3.1 Sol-Gel Synthesis of White Mineral Aggregate and Partial Stabilized Cement -- 4.3.2 In vitro Bioactivity and Biological Assay of White Mineral Aggregate and Partially Stabilized Cement. , 4.4 Conclusions -- References -- 5 Nanobiomaterials in restorative dentistry -- 5.1 Introduction -- 5.2 Composite Resin -- 5.2.1 Nanocomposites -- 5.2.2 Antibacterial Nanoparticles and Composite Resins -- 5.2.2.1 Applications of antibacterial nanoparticles in composite resins -- 5.2.3 Remineralization and Composite Resins -- 5.3 Adhesives -- 5.4 Dental Cements and Dental Liners -- 5.4.1 Glass Ionomer Cements -- 5.4.2 Resin Cements -- 5.4.3 Mineral Trioxide Aggregate -- 5.4.4 Temporary Restorative Materials -- 5.5 Conclusions -- References -- 6 New trends, challenges, and opportunities in the use of nanotechnology in restorative dentistry -- 6.1 Introduction -- 6.2 Restorative Dentistry Nanomaterials -- 6.2.1 Dental Nanocomposites -- 6.2.1.1 Resin-based composites -- 6.2.2 Nanofilled -- 6.2.2.1 Silica nanoparticles -- 6.2.3 Nanocrystals -- 6.2.4 Nanoparticles -- 6.2.4.1 Metal nanoparticles -- 6.2.4.2 Polymeric nanoparticles -- 6.2.4.3 Nonpolymeric nanoparticles -- 6.3 New Trends in Restorative Dentistry -- 6.4 Actual Clinic Situation -- 6.5 Conclusions -- 6.6 Future Trends -- References -- 7 Antimicrobial effect of nanoparticles in endodontics -- 7.1 Introduction -- 7.1.1 Endodontics -- 7.1.2 Endodontic Microbiology -- 7.2 Difficulty in Achieving Complete Eradication of Endodontic Pathogens -- 7.2.1 Complexity of Microorganisms -- 7.2.2 Limitations of Cleaning and Shaping Protocols -- 7.2.3 Anatomic Complexity -- 7.3 Need for Nanotechnology in Endodontics -- 7.4 Applications of Antimicrobial Nanoparticles in Endodontics -- 7.4.1 Commonly Used Nanoparticles in Endodontics -- 7.4.2 Nanoparticles as Irrigants -- 7.4.3 Nanoparticles as Intracanal Medicaments -- 7.4.4 Nanoparticles as Obturation Materials -- 7.4.5 Nanoparticle-Based Photodynamic Therapy -- 7.4.6 Nanomodification of Materials for Perforation Repair and Apical Seal -- 7.5 Conclusions. , References -- 8 Nanotechnology in dentistry -- 8.1 Introduction -- 8.2 A Short History about Caries Treatment Before Dental Composites -- 8.3 Historical Development of Dental Composites -- 8.4 Vision in Dentistry From Micro- to Nanoscale -- 8.5 Nanotechnology in Restorative Dentistry -- 8.5.1 Nano-Concept in Restorative Dentistry -- 8.5.1.1 Nanofills -- 8.5.1.2 Nanohybrids -- 8.5.2 Other Nanomaterials Mixed with Dental Composites -- 8.5.3 Future Predictions -- 8.6 Nanotechnology in Periodontics -- 8.6.1 Periodontal Treatment Procedures -- 8.6.2 Future Aspects of Nanotechnology in Periodontics -- 8.7 Nanotechnology in Orthodontics -- 8.7.1 Orthodontic Nanocomposites -- 8.7.2 Nanotechnologic Enamel-Remineralizing Agents -- 8.7.3 Nanocoated Orthodontic Archwire -- 8.7.4 Nanotechnologic Orthodontic Brackets -- 8.7.5 Orthodontic Nanorobots and Furtherance -- 8.8 Nanotechnology in Endodontics -- 8.8.1 Nanoparticles as Antimicrobial Agents -- 8.8.2 Nanotechnology-Based Root-End Sealant -- 8.8.3 Future Aspects of Nanotechnology in Endodontics -- 8.9 Conclusions -- Acknowledgements -- References -- 9 Role of nanomaterials in clinical dentistry -- 9.1 Introduction -- 9.1.1 Nanostructures Used in Dentistry -- 9.1.2 Oral Health Care -- 9.1.3 Oral Diseases -- 9.1.4 Dental Plaque -- 9.1.5 Etiophysiology of Dental Caries -- 9.1.6 Biofilm Definition -- 9.1.7 Biofilm Composition -- 9.1.8 Role of Biofilms -- 9.1.9 Types of Biofilm -- 9.2 Role of Nanomaterials in Clinical Dentistry -- 9.2.1 Oral Hygiene and Halitosis -- 9.2.2 Mouth Rinse -- 9.2.3 Chlorhexidine -- 9.2.4 CHX Varnish Therapy -- 9.2.5 Role of Calcium -- 9.2.6 Chitosan -- 9.2.7 NPs in Dentifrice -- 9.2.8 Tooth Whitening/Bleaching -- 9.2.9 HA as Surface Defect Filler -- 9.3 Dentin Hypersensitivity -- 9.3.1 Nanorestorative Materials: Pulp-Capping Agent -- 9.3.2 Nanozinc Oxide -- 9.3.3 Silver Amalgam. , 9.3.4 Silver NPs -- 9.3.5 Ceramic Materials -- 9.3.6 NPs of Zirconia -- 9.3.7 Nanoesthetic Filling Materials -- 9.3.8 Dental Composite -- 9.3.9 Recent Advances -- 9.4 Bonding System -- 9.4.1 Nanoionomer -- 9.4.2 Prereacted Glass-Ionomer -- 9.4.3 Dental Implants -- 9.4.4 Esthetics and Tooth Durability -- 9.4.5 Laser and NPs -- 9.4.6 Nanocare Gold -- 9.4.7 Endodontics -- 9.4.8 Drug-Delivery System -- 9.4.9 Impression Materials -- 9.5 Nanoneedles -- 9.5.1 Nanotweezers -- 9.5.2 Surgical Devices -- 9.5.3 Nanorobotics -- 9.5.4 Nanodiagnostics -- 9.5.5 Healing of Wounds -- 9.5.6 Nano-Orthodontics -- 9.5.7 Tissue Engineering -- 9.5.8 Bone-Replacement Materials -- 9.6 Future Challenges -- 9.7 Conclusions -- References -- 10 Use of nanotechnology for the superlubrication of orthodontic wires -- 10.1 Introduction -- 10.2 Nanotechnology -- 10.2.1 "Top-Down" or "Bottom-Up" Approaches -- 10.2.2 Nanomaterials -- 10.2.3 Nanorobots -- 10.3 Nanomedicine -- 10.4 Nanotechnology in Dentistry -- 10.4.1 Application of Nanotechnology in Diagnosis and Treatment -- 10.4.2 Nanocomposite in Restorative Dentistry -- 10.4.3 Nanotechnology for Preventing Dental Caries -- 10.4.4 Nanorobotic Dentrifices (Dentifrobots) -- 10.4.5 Hypersensitivity Cure -- 10.4.6 Nanosolutions (Nanoadhesives) -- 10.4.7 Tissue Engineering and Dentistry -- 10.4.8 Replacing Teeth -- 10.4.9 Prosthodontics -- 10.4.10 Dental Implants' Modified Surfaces -- 10.4.11 Bone Replacement Materials -- 10.4.12 Nanoanesthesia -- 10.4.13 Impression Materials -- 10.4.14 Nanoneedles -- 10.4.15 Nanocomposite Denture Teeth -- 10.4.16 Cosmetic Dentistry -- 10.4.17 Nanotechnology in Endodontics -- 10.4.18 Nanoencapsulation -- 10.4.19 Digital Dental Imaging -- 10.4.20 Radiopacity -- 10.4.21 Surface Disinfectants -- 10.4.22 Laser Plasma Application -- 10.5 Nanotechnology in Orthodontics. , 10.5.1 Nanocoatings for Friction Reduction.

Weitere Ausg.: ISBN 0-323-42867-3

Sprache: Englisch

UID:

Umfang: 1 online resource (ix, 376 pages) : , digital, PDF file(s).

Ausgabe: Sixth edition.

ISBN: 1-316-71198-6 , 1-316-71331-8 , 1-316-48893-4

Inhalt: The Psychologist's Companion, 6th edition is written for students, young professionals, and even mid-career scholars. It is the most comprehensive guide available to both written and oral communication processes for academic psychologists. It covers the topics necessary for career success, including planning papers, writing papers, presenting data, evaluating one's papers, writing grant proposals, giving talks, finding a book publisher, doing job interviews, and doing media interviews. Because the book is in its sixth edition, it is market tested for success in reaching and engaging its readers. Two special (new) pedagogical features are 'Experience is the best teacher', which draws on the authors' personal experiences to help make the book more personalized and exciting to readers, and 'What's wrong here', which gives readers an opportunity for active learning while they read the book. The authors have written the book in a personable and often humorous style that will keep readers engaged.

Anmerkung: Title from publisher's bibliographic system (viewed on 28 Nov 2016). , Cover -- Half-title -- Title page -- Copyright information -- Table of contents -- Preface -- Acknowledgments -- Introduction -- Part I Macro-Challenges in Writing Papers: Planning and Formulating Papers -- 1 Eight Common Misconceptions about Psychology Papers -- 2 How to Generate, Evaluate, and Sell Your Ideas for Research and Papers -- 2.1 Generating Ideas -- 2.1.1 Generating Ideas by Consulting with Others -- 2.1.2 Generating Ideas by Reading -- 2.1.2.1 What to Read -- 2.1.2.2 How to Read -- 2.1.3 Other Ways to Generate Ideas -- 2.2 Evaluating Your Ideas -- 2.3 Selling Your Ideas -- 3 Literature Research -- 3.1 Reference Materials -- 3.2 Literature Research -- 3.2.1 Databases for Psychologists -- 3.2.2 How to Find Psychological Tests -- 3.3 Internet Research -- 3.3.1 The Components of the Internet -- 3.3.2 Overview of Internet Searching and Search Engines -- 3.3.3 Excursion: Internet Search Using Boolean Logic -- 3.3.4 Some Specific Types of Useful Online Research Information -- 3.3.5 Critical Evaluation of Internet-based Information -- 3.4 Bibliography Software -- 4 Writing a Literature Review -- 4.1 Deciding on a Topic for a Paper -- 4.2 Organizing and Searching the Literature -- 4.2.1 Author Notes -- 4.2.2 Topic Notes -- 4.3 Preparing an Outline -- 4.3.1 Use of Topic Notes -- 4.3.2 Types of Outlines -- 4.3.2.1 The Keyword Outline -- 4.3.2.2 The Topic Outline -- 4.3.2.3 The Sentence Outline -- 4.3.3 Choosing a Type of Outline -- 4.3.4 Organization of Outlines -- 4.3.5 Advantages of Outlines -- 4.4 Writing the Paper -- 4.5 Evaluating the Paper Yourself and Seeking Others' Feedback on It -- 5 Planning and Writing the Experimental Research Paper -- 5.1 Planning Experimental Research -- 5.1.1 Getting an Idea -- 5.1.2 Selecting Independent Variables -- 5.1.3 Selecting Dependent Variables. , 5.1.4 Deciding on Between-Subjects and Within-Subjects Variables -- 5.1.5 Deciding How Data Will Be Analyzed -- 5.1.6 Selecting Participants -- 5.1.7 Choosing Experimental Materials -- 5.1.8 Choosing a Means of Presenting Experimental Materials -- 5.1.9 Writing Directions -- Directions for Free-Recall Task -- 5.1.10 Deciding on a Means of Scoring Data -- 5.1.11 Writing a Consent Form -- 5.1.12 Writing a Debriefing Sheet -- 5.1.13 Getting Approval from the Institutional Review Board -- 5.1.14 Conducting a Pilot Study -- 5.2 Executing Experimental Research -- 5.3 Excursion: Using the Internet to Conduct Archival Research and Data Collection -- 5.3.1 Archival Research -- 5.3.2 Data Collection Via the Internet -- 5.4 Analyzing Data from Experimental Research -- 5.5 Reporting Experimental Research -- 5.5.1 Title -- 5.5.2 Author's Name and Institutional Affiliation -- 5.5.3 Abstract -- 5.5.4 Introduction -- 5.5.5 Method -- 5.5.5.1 Participants -- 5.5.5.2 Materials -- 5.5.5.3 Apparatus -- 5.5.5.4 Design -- 5.5.5.5 Procedure -- 5.5.6 Results -- 5.5.7 Discussion -- 5.5.8 An Alternative: ''Results and Discussion'' -- 5.5.9 References -- 5.5.10 Appendix -- 5.5.11 Order of Sections -- 6 Ethics in Research and Writing -- 6.1 Research Issues -- 6.1.1 Deception -- 6.1.2 Informed Consent -- 6.1.3 Debriefing -- 6.1.4 Pain -- 6.1.5 Confidentiality and Anonymity -- 6.2 Issues in Research with Nonhuman Animals -- 6.3 Faking of Data -- 6.4 Institutional Review Board Approval -- 6.5 Financial Management and Mismanagement -- 6.6 Writing Issues -- 6.6.1 Accuracy of Reporting -- 6.6.2 Inclusion and Exclusion of Data and Data Analyses -- 6.6.3 Interpretation of Data -- 6.6.4 Authorship -- 6.6.5 Origins of Ideas -- 6.6.6 Plagiarism -- 6.6.6.1 Plagiarism of Others' Work -- 6.6.6.2 Self-Plagiarism -- 6.6.7 Citations -- 6.6.8 Permissions -- 6.6.9 Reanalysis of Data Sets. , 6.6.10 Piecemeal Publication -- 6.6.11 Simultaneous Submission -- 6.6.12 Duplicate Publication -- Part II Micro-Challenges in Writing Papers: Presenting Your Ideas in Writing -- 7 A Word about Content, Language, and Style -- 7.1 Content Guidelines -- 7.2 Style Guidelines -- 7.3 Language and Grammar Guidelines -- 8 Commonly Misused Words -- 8.1 Nontechnical Terms -- 8.2 Technical Terms -- 9 American Psychological Association Guidelines for Psychology Papers -- 9.1 Formatting the Paper -- 9.2 Grammar -- 9.2.1 Punctuation -- 9.2.1.1 Comma -- 9.2.1.2 Semicolon -- 9.2.1.3 Colon -- 9.2.1.4 Hyphen -- 9.2.1.5 Double Quotation Marks -- 9.2.1.6 Single Quotation Marks -- 9.2.1.7 Parentheses -- 9.2.1.8 Brackets -- 9.2.2 Capitalization -- 9.2.2.1 Titles and Headings -- 9.2.2.2 Proper Nouns and Trade Names -- 9.2.2.3 Titles of Tests -- 9.2.2.4 Nouns Followed by Numerals or Letters -- 9.2.2.5 Names of Factors, Variables, and Effects -- 9.2.2.6 Names of Conditions or Groups in Experiments -- 9.2.3 Italics -- 9.2.4 Spelling -- 9.2.5 Abbreviations -- 9.3 Headings -- 9.4 Quantitative issues -- 9.4.1 Units of Measurement -- 9.4.2 Statistics -- 9.4.3 Equations -- 9.4.3.1 General Principles -- 9.4.3.2 Equations Merged with Text -- 9.4.3.3 Equations Separated from Text -- 9.4.4 Numbers -- 9.4.4.1 General Principles -- 9.4.4.2 Numbers Expressed in Words -- 9.4.4.3 Numbers Expressed in Figures -- 9.5 Seriation -- 9.5.1 Seriation within a Paragraph -- 9.5.2 Seriation of Paragraphs -- 9.6 References -- 9.6.1 Citations in Text -- 9.6.1.1 Standard Formats -- 9.6.1.2 Multiple Authors -- 9.6.1.3 No Author -- 9.6.1.4 Corporate Author -- 9.6.1.5 Authors with the Same Surname -- 9.6.1.6 Electronic Sources -- 9.6.2 The Reference List -- References -- 9.7 Author Notes -- 9.8 Footnotes -- 9.8.1 Kinds of Footnotes -- 9.8.1.1 Content Footnotes -- 9.8.1.2 Reference Footnotes. , 9.8.1.3 Table Footnotes -- 9.8.2 Numbering of Footnotes -- 9.8.3 Placement of Footnotes -- 9.9 Crediting Sources and Permissions -- 9.10 Conflict of Interest -- 9.11 A Final Word -- 10 Guidelines for Data Presentation -- 10.1 Relation between Tables or Figures and Text -- 10.2 Some General Tips for Designing Your Data Displays -- 10.3 Tables -- 10.3.1 When to Use Tables -- 10.3.2 Four Rules for Constructing Tables -- 10.3.3 Placement of Tables -- 10.3.4 Table Numbers -- 10.3.5 Table Title -- 10.3.6 Ruling of Tables -- 10.3.7 Formatting of Tables -- 10.4 Figures -- 10.4.1 When to Use Figures -- 10.4.2 Stem-and-Leaf Displays -- 10.4.3 Box Plots and Quartile Plots -- 10.4.3.1 Outliers -- 10.4.3.2 Comparing Data Sets -- 10.4.4 Graphs -- 10.4.5 Rules for Constructing Graphs -- 10.4.6 Practical Tips for Designing Graphs -- 10.4.7 Placement of Figures -- 10.4.8 Figure Legends -- 10.4.9 Figure Numbers -- 10.4.10 Figure Captions -- 10.4.11 Preparing Figures for Publication -- 10.4.12 Submitting Figures -- Part III Writing and Preparing Articles for Journal Submission -- 11 Article Writing 101 -- 12 How to Make Your Article even Better: Proofreading, Revising, and Editing -- 12.1 Before Submission: Proofreading and Revising -- 12.2 After Submission: Making the Best of Reviews -- 12.3 After Acceptance: Editing for Publication -- 13 Critical Checklist before Submitting an Article for Publication -- 14 Deciding on a Journal and Submitting an Article to a Journal -- 14.1 Deciding on a Journal -- 14.2 Submitting the Article -- 14.3 A Look Behind the Scenes: in the Editor's Office -- 14.3.1 What Happens after Submission to the Editor -- 14.3.2 The Editorial Decision -- 14.3.3 The Aftermath -- Part IV Presenting Yourself to Others -- 15 Preparing a Poster Presentation -- 16 Writing a Grant or Contract Proposal -- 16.1 Some Basic Concepts About Grants and Contracts. , 16.2 Eighteen Tips for Writing Proposals -- 17 How to Find a Book Publisher -- 17.1 Choosing a Publisher -- 17.2 The Proposal -- 17.2.1 Opening -- 17.2.2 Description of the Book -- 17.2.3 Audience of the Book -- 17.2.4 Outline of the Book -- 17.2.5 The Competition of the Book -- 17.2.6 Details -- 17.2.7 Your Qualifications -- 17.2.8 Sample Chapter(s) -- 17.2.9 Summary -- 17.3 Contract Offers -- 17.3.1 Royalties -- 17.3.2 Advance on Royalties -- 17.3.3 Payment of Royalties -- 17.3.4 Publication Lag -- 17.3.5 Marketing and Promotional Efforts -- 17.3.6 Physical Appearance of the Book -- 17.3.7 Out-of-Print Policy -- 17.3.8 In-House Assistance -- 17.3.9 Communication -- 17.3.10 Hidden Aspects of the Contract -- 17.3.11 Reputation of the Publisher -- 18 Writing a Lecture -- 19 Doing a Job Interview -- Things to Say and Do -- 20 Doing Media Interviews -- Epilogue -- References -- Index.

Sprache: Englisch

URL: Volltext  (lizenzpflichtig)

URL: https://doi.org/10.1017/CBO9781316488935

UID:

Umfang: 1 online resource

ISBN: 9781119232353 , 111923235X , 9781119232308 , 1119232309 , 9781119232322 , 1119232325 , 1119231876 , 9781119231875

Inhalt: Applies lean manufacturing principles across the cloud service delivery chain to enable application and infrastructure service providers to sustainably achieve the shortest lead time, best quality, and value This book focuses on lean in the context of cloud computing capacity management of applications and the physical and virtual cloud resources that support them. Lean Computing for the Cloud considers business, architectural and operational aspects of efficiently delivering valuable services to end users via cloud-based applications hosted on shared cloud infrastructure. The work also focuses on overall optimization of the service delivery chain to enable both application service and infrastructure service providers to adopt leaner, demand driven operations to serve end users more efficiently. The book's early chapters analyze how capacity management morphs with cloud computing into interlocked physical infrastructure capacity management, virtual resource capacity management, and application capacity management problems. The middle chapters frame cloud capacity management as a lean thinking problem, lay out strategies for applying lean thinking best practices across the cloud service delivery chain, and apply key lean insights from other industries. Later chapters discuss lean reserve capacity, lean demand management, optimal power management, and quantitative performance metrics of lean capacity management, which can be used to methodically drive continuous improvement of lean cloud computing deployments. The final chapter summarizes the book's insights on lean strategies to minimize waste across the cloud computing service delivery chain. . Applies lean thinking across the cloud service delivery chain to recognize and minimize waste. Leverages lessons learned from electric power industry operations to operations of cloud infrastructure. Applies insights from just-in-time inventory management to operation of cloud based applications. Explains how traditional, Information Technology Infrastructure Library (ITIL) and Enhanced Telecom Operation Map (eTOM) capacity management evolves to lean computing for the cloud This book is geared toward professionals with business, operational, architectural, development, and quality backgrounds in the information and communication technology industry. Eric Bauer is Reliability Engineering Manager in the IP Platforms Group of Alcatel-Lucent. Before focusing on reliability engineering, Mr. Bauer spent two decades designing and developing embedded firmware, networked operating systems, internet platforms, and optical transmission systems. He has been awarded more than a dozen US patents, and has authored several books such as Service Quality of Cloud-Based Applications, Reliability and Availability of Cloud Computing, and Design for Reliability: Information and Computer-Based Systems, all of which were published by Wiley-IEEE Press. Mr. Bauer earned his BS in Electrical Engineering from Cornell University and MS in Electrical Engineering from Purdue University.

Anmerkung: Introduction xi -- Acknowledgments xv -- Abbreviations xvii -- 1. Basics 1 -- 1.1 Cloud Computing Fundamentals 1 -- 1.2 Roles in Cloud Computing 6 -- 1.3 Applications 9 -- 1.3.1 Application Service Quality 11 -- 1.4 Demand, Supply, Capacity, and Fungibility 13 -- 1.5 Demand Variability 16 -- 1.6 Chapter Review 18 -- 2. Rethinking Capacity Management 19 -- 2.1 Capacity Management 19 -- 2.2 Demand Management 21 -- 2.3 Performance Management 21 -- 2.4 Canonical Capacity Management 23 -- 2.4.1 Traditional Capacity Management 24 -- 2.4.2 ITIL Capacity Management 27 -- 2.4.3 eTOM Capacity Management 28 -- 2.4.4 Discussion 30 -- 2.5 Three Cloud Capacity Management Problems 30 -- 2.5.1 Physical Resource Capacity Management 31 -- 2.5.2 Virtual Resource Capacity Management 32 -- 2.5.3 Application Capacity Management 33 -- 2.6 Cloud Capacity Management as a Value Chain 36 -- 2.7 Chapter Review 39 -- 3. Lean Thinking on Cloud Capacity Management 41 -- 3.1 Lean Thinking Overview 41 -- 3.2 Goal 42 -- 3.3 Seeing Waste (Nonvalue-Adding Activities) 43 -- 3.3.1 Reserve Capacity 45 -- 3.3.2 Excess Application Capacity 46 -- 3.3.3 Excess Online Infrastructure Capacity 46 -- 3.3.4 Excess Physical Infrastructure Capacity 46 -- 3.3.5 Inadequate Capacity 47 -- 3.3.6 Infrastructure Overhead 48 -- 3.3.7 Capacity Management Overhead 48 -- 3.3.8 Resource Overhead 49 -- 3.3.9 Power Management Overhead 50 -- 3.3.10 Workload Migration 50 -- 3.3.11 Complexity Overhead 51 -- 3.3.12 Resource Allocation Failure 51 -- 3.3.13 Leaking and Lost Resources 53 -- 3.3.14 Waste Heat 53 -- 3.3.15 Carbon Footprint 54 -- 3.4 Key Principles 54 -- 3.4.1 Move toward Flow 55 -- 3.4.2 Pull versus Push 55 -- 3.4.3 Level the Workload 55 -- 3.4.4 Stop and Fix Problems 55 -- 3.4.5 Master Practices 56 -- 3.4.6 Visual Management 57 -- 3.4.7 Use Well-Tested Technology 57 -- 3.4.8 Take a Long-Term Perspective 58 -- 3.4.9 Grow, Learn, and Teach Others 58 -- 3.4.10 Develop Exceptional People 58 -- 3.4.11 Partners Help Each Other Improve 58. , 3.4.12 Go See 59 -- 3.4.13 Implement Rapidly 59 -- 3.4.14 Become a Learning Organization 59 -- 3.5 Pillar: Respect 59 -- 3.6 Pillar: Continuous Improvement 61 -- 3.7 Foundation 62 -- 3.8 Cadence 62 -- 3.9 Lean Capacity Management Philosophy 63 -- 3.10 Chapter Review 64 -- 4. Lean Cloud Capacity Management Strategy 67 -- 4.1 Lean Application Service Provider Strategy 68 -- 4.1.1 User Workload Placement 71 -- 4.1.2 Application Performance Management 73 -- 4.2 Lean Infrastructure Service Provider Strategies 73 -- 4.2.1 Physical Resource Capacity Management 76 -- 4.3 Full Stream Optimization 77 -- 4.4 Chapter Review 79 -- 5. Electric Power Generation as Cloud Infrastructure Analog 81 -- 5.1 Power Generation as a Cloud Infrastructure Analog 81 -- 5.2 Business Context 83 -- 5.3 Business Structure 86 -- 5.4 Technical Similarities 88 -- 5.5 Impedance and Fungibility 91 -- 5.6 Capacity Ratings 94 -- 5.7 Bottled Capacity 95 -- 5.8 Location of Production Considerations 95 -- 5.9 Demand Management 97 -- 5.10 Demand and Reserves 98 -- 5.11 Service Curtailment 99 -- 5.12 Balance and Grid Operations 100 -- 5.13 Chapter Review 103 -- 6. Application Capacity Management as an Inventory Management Problem 105 -- 6.1 The Application Capacity Management Service Delivery Chain 105 -- 6.2 Traditional Application Service Production Chain 107 -- 6.3 Elasticity and Demand-Driven Capacity Management 108 -- 6.4 Application Service as Retail Analog 110 -- 6.4.1 Locational Consideration 112 -- 6.4.2 Inventory and Capacity 112 -- 6.4.3 Service Level 113 -- 6.4.4 Inventory Carrying Costs 114 -- 6.4.5 Inventory Decision, Planning, and Ordering 115 -- 6.4.6 Agility 118 -- 6.4.7 Changing Consumption Patterns 118 -- 6.5 Chapter Review 118 -- 7. Lean Demand Management 119 -- 7.1 Infrastructure Demand Management Techniques 120 -- 7.1.1 Resource Scheduling 121 -- 7.1.2 Resource Curtailment 121 -- 7.1.3 Mandatory Demand Shaping 122 -- 7.1.4 Voluntary Demand Shaping 123 -- 7.1.5 Scheduling Maintenance Actions 123. , 7.1.6 Resource Pricing 123 -- 7.2 Application Demand Management Techniques 124 -- 7.2.1 Queues and Buffers 124 -- 7.2.2 Load Balancers 124 -- 7.2.3 Overload Controls 125 -- 7.2.4 Explicit Demand Management Actions 125 -- 7.2.5 Scheduling Maintenance Actions 125 -- 7.2.6 User Pricing Strategies 126 -- 7.3 Full Stream Analysis Methodology 126 -- 7.3.1 Analyze Applications' Natural Demand Patterns 127 -- 7.3.2 Analyze Applications' Tolerances 128 -- 7.3.3 Create Attractive Infrastructure Pricing Models 129 -- 7.3.4 Deploy Optimal Infrastructure Demand Management Models 130 -- 7.4 Chapter Review 131 -- 8. Lean Reserves 133 -- 8.1 What Is Reserve Capacity? 133 -- 8.2 Uses of Reserve Capacity 135 -- 8.2.1 Random Demand Peaks 135 -- 8.2.2 Component or Resource Failure 136 -- 8.2.3 Infrastructure Element Failure 136 -- 8.2.4 Infrastructure Resource Curtailment or Demand Management Action 137 -- 8.2.5 Demand Exceeding Forecast 137 -- 8.2.6 Lead Time Demand 137 -- 8.2.7 Catastrophic Failures and Force Majeure Events 139 -- 8.3 Reserve Capacity as a Feature 139 -- 8.4 Types of Reserve Capacity 140 -- 8.4.1 Automatic Infrastructure Power Management Controls 140 -- 8.4.2 Utilize Application Reserve Capacity 141 -- 8.4.3 Place/Migrate Demand into Underutilized Capacity 141 -- 8.4.4 Grow Online Capacity 141 -- 8.4.5 Service Curtailment/Degradation 141 -- 8.4.6 Mandatory Demand Shaping 141 -- 8.4.7 Voluntary Demand Shaping 142 -- 8.4.8 Emergency Reserves 142 -- 8.5 Limits of Reserve Capacity 144 -- 8.6 Ideal Reserve 144 -- 8.6.1 Normal (Co-located) Reserve 144 -- 8.6.2 Emergency (Geographically Distributed) Reserve 146 -- 8.7 Chapter Review 147 -- 9. Lean Infrastructure Commitment 149 -- 9.1 Unit Commitment and Infrastructure Commitment 150 -- 9.2 Framing the Unit Commitment Problem 151 -- 9.3 Framing the Infrastructure Commitment Problem 153 -- 9.4 Understanding Element Startup Time 155 -- 9.5 Understanding Element Shutdown Time 157 -- 9.6 Pulling It All Together 160 -- 9.7 Chapter Review 166. , 10. Lean Cloud Capacity Management Performance Indicators 167 -- 10.1 Perfect Capacity Metrics 168 -- 10.2 Capacity Management Metrics 172 -- 10.3 Infrastructure Commitment Metrics 173 -- 10.4 Waste Metrics 174 -- 10.4.1 Reserve Capacity Waste Metrics 174 -- 10.4.2 Excess Application Capacity Metrics 175 -- 10.4.3 Excess Online Infrastructure Capacity Metrics 175 -- 10.4.4 Excess Physical Infrastructure Capacity Metrics 175 -- 10.4.5 Inadequate Capacity Metrics 175 -- 10.4.6 Infrastructure Overhead Waste Metrics 176 -- 10.4.7 Capacity Management Overhead Waste Metrics 176 -- 10.4.8 Resource Overhead Waste Metrics 176 -- 10.4.9 Power Management Overhead Waste Metrics 177 -- 10.4.10 Workload Migration Metrics 177 -- 10.4.11 Complexity Overhead Metrics 178 -- 10.4.12 Resource Allocation Failure Metrics 178 -- 10.4.13 Leaking and Lost Resources 179 -- 10.4.14 Waste Heat Metrics 179 -- 10.4.15 Carbon Footprint Metrics 180 -- 10.5 Key Principle Indicators 180 -- 10.6 Cost of Poor Quality 181 -- 10.7 Metrics and Service Boundaries 182 -- 10.8 Measurements and Maturity 183 -- 10.9 Chapter Review 185 -- 11. Summary 187 -- 11.1 Cloud Computing as a Service Delivery Chain 187 -- 11.2 Lean Cloud Computing 190 -- 11.3 Reimagining Cloud Capacity 192 -- 11.4 Lean Demand Management 195 -- 11.5 Lean Reserves 197 -- 11.6 Lean Infrastructure Service Provider Considerations 198 -- 11.7 Lean Application Service Provider Considerations 198 -- 11.8 Lean Infrastructure Commitment 199 -- 11.9 Visualizing Perfect Capacity 201 -- 11.10 Lean Cloud Computing Metrics 203 -- 11.11 Concluding Remarks 204 -- References 207 -- About the Author 211 -- Index 213.

Weitere Ausg.: Print version : ISBN 9781119231875

Sprache: Englisch

Schlagwort(e): Electronic books. ; Electronic books. ; Electronic books.

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119232353

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119232353

URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9781119232353

UID:

Umfang: 1 online resource (402 pages)

Ausgabe: 2

ISBN: 9783958459397

Anmerkung: Cover -- Titel -- Impressum -- Inhaltsverzeichnis -- Vorwort -- Über die Autoren -- Einleitung -- Wer sollte dieses Buch lesen? -- Warum überhaupt dieses Buch lesen? -- Aufbau des Buchs -- Konventionen dieses Buchs -- Danksagungen -- Kapitel 1: Einführung -- 1.1 Die Entstehung von Docker -- 1.2 Das Docker-Versprechen -- 1.2.1 Vorteile des Docker-Workflows -- 1.3 Was Docker nicht ist -- 1.4 Wichtige Begrifflichkeiten -- 1.5 Zusammenfassung -- Kapitel 2: Docker im Überblick -- 2.1 Workflows vereinfachen -- 2.2 Umfassender Support und breite Akzeptanz -- 2.3 Architektur -- 2.3.1 Das Client-Server-Modell -- 2.3.2 Netzwerk-Ports und Unix-Sockets -- 2.3.3 Stabiles Tooling -- 2.3.4 Dockers Kommandozeilentool -- 2.3.5 Docker-Engine-API -- 2.3.6 Container-Netzwerk -- 2.4 Docker ausreizen -- 2.4.1 Container sind keine virtuellen Maschinen -- 2.4.2 Beschränkte Isolierung -- 2.4.3 Container sind leichtgewichtig -- 2.4.4 Unveränderliche Infrastruktur -- 2.4.5 Zustandslose Anwendungen -- 2.4.6 Zustände externalisieren -- 2.5 Der Docker-Workflow -- 2.5.1 Versionsverwaltung -- 2.5.2 Anwendungen erstellen -- 2.5.3 Testen -- 2.5.4 Paketierung -- 2.5.5 Deployment -- 2.5.6 Das Docker-Ökosystem -- 2.6 Zusammenfassung -- Kapitel 3: Docker installieren -- 3.1 Der Docker-Client -- 3.1.1 Linux -- 3.1.2 macOS -- 3.1.3 Microsoft Windows 10 Professional -- 3.2 Der Docker-Server -- 3.2.1 Linux mit systemd -- 3.2.2 Server, die nicht auf Linux-VMs basieren -- 3.3 Installation testen -- 3.3.1 Ubuntu -- 3.3.2 Fedora -- 3.3.3 Alpine Linux -- 3.4 Docker-Server erkunden -- 3.5 Zusammenfassung -- Kapitel 4: Docker-Images verwenden -- 4.1 Der Aufbau eines Dockerfiles -- 4.2 Erstellen eines Images -- 4.3 Fehlerbehebung bei fehlgeschlagenen Builds -- 4.4 Ausführen eines Images -- 4.4.1 Umgebungsvariablen -- 4.5 Benutzerdefinierte Base-Images -- 4.6 Images speichern , 4.6.1 Öffentliche Registries -- 4.6.2 Private Registries -- 4.6.3 Authentifizierung -- 4.6.4 Eine private Registry betreiben -- 4.6.5 Fortgeschrittene Build-Techniken -- 4.7 So geht es weiter -- Kapitel 5: Docker-Container verwenden -- 5.1 Was sind Container? -- 5.1.1 Die Entstehungsgeschichte der Container -- 5.2 Container erstellen -- 5.2.1 Grundlegende Konfiguration -- 5.2.2 Speichervolumes -- 5.2.3 Ressourcen-Quotas -- 5.3 Container starten -- 5.4 Container automatisch neu starten -- 5.5 Container stoppen -- 5.6 Container sofort beenden -- 5.7 Ausführung eines Containers pausieren und fortsetzen -- 5.8 Container und Images aufräumen -- 5.9 Windows-Container -- 5.10 So geht es weiter -- Kapitel 6: Docker erkunden -- 6.1 Ausgabe der Docker-Version -- 6.2 Informationen über den Server -- 6.3 Image-Updates herunterladen -- 6.4 Container inspizieren -- 6.5 Die Shell erkunden -- 6.6 Ausgabe von Rückgabewerten -- 6.7 In einen laufenden Container gelangen -- 6.7.1 docker exec -- 6.7.2 nsenter -- 6.7.3 docker volume -- 6.8 Logging -- 6.8.1 docker logs -- 6.8.2 Fortgeschrittenes Logging -- 6.8.3 Non-Plug-in-Community-Optionen -- 6.9 Docker überwachen -- 6.9.1 Containerstatistiken -- 6.9.2 Stats-API-Endpunkt -- 6.9.3 Container-Health-Checks -- 6.9.4 Docker-Events -- 6.9.5 cAdvisor -- 6.10 Monitoring mit Prometheus -- 6.11 Weitere Erkundung -- 6.12 So geht es weiter -- Kapitel 7: Container debuggen -- 7.1 Prozesse anzeigen -- 7.2 Prozesse inspizieren -- 7.3 Prozessverwaltung -- 7.4 Das Netzwerk inspizieren -- 7.5 Image-History -- 7.6 Inspizieren eines Containers -- 7.7 Dateisystem inspizieren -- 7.8 So geht es weiter -- Kapitel 8: Docker Compose -- 8.1 Docker Compose konfigurieren -- 8.2 Services starten -- 8.3 RocketChat -- 8.4 Weitere Features von Docker Compose -- 8.5 So geht es weiter -- Kapitel 9: Der Weg zu Containern in Produktivumgebungen , 9.1 Einstieg in die Produktion -- 9.2 Dockers Rolle in Produktivumgebungen -- 9.2.1 Beschränkung der Ressourcen -- 9.2.2 Netzwerke -- 9.2.3 Konfiguration -- 9.2.4 Paketierung und Auslieferung -- 9.2.5 Logging -- 9.2.6 Monitoring -- 9.2.7 Scheduling -- 9.2.8 Service Discovery -- 9.2.9 Fazit zur Produktion -- 9.3 Docker und die DevOps-Pipeline -- 9.3.1 Kurzübersicht -- 9.3.2 Externe Abhängigkeiten -- 9.4 So geht es weiter -- Kapitel 10: Skalierung -- 10.1 Centurion -- 10.2 Docker Swarm Mode -- 10.3 Amazon ECS und Fargate -- 10.3.1 Einrichten von AWS -- 10.3.2 Einrichtung von IAM-Rollen -- 10.3.3 Einrichtung der AWS-CLI-Tools -- 10.3.4 Container-Instanzen -- 10.3.5 Tasks -- 10.3.6 Testen des Tasks -- 10.3.7 Task stoppen -- 10.4 Kubernetes -- 10.4.1 Was ist Minikube? -- 10.4.2 Minikube installieren -- 10.4.3 Kubernetes zum Laufen bringen -- 10.4.4 Kubernetes-Dashboard -- 10.4.5 Kubernetes-Container und Pods -- 10.4.6 Das erste Deployment -- 10.4.7 Deployment eines realistischen Stacks -- 10.4.8 Service-Definition -- 10.4.9 Definition des PersistentVolumeClaim -- 10.4.10 Deployment-Definition -- 10.4.11 Die Anwendung deployen -- 10.4.12 Hochskalierung -- 10.4.13 kubectl-API -- 10.5 Zusammenfassung -- Kapitel 11: Weiterführende Themen -- 11.1 Container im Detail -- 11.1.1 Control Groups (cgroups) -- 11.1.2 Kernel- und Benutzer-Namespaces -- 11.2 Sicherheitsaspekte -- 11.2.1 SELinux und AppArmor -- 11.2.2 Wie sicher ist der Docker-Daemon? -- 11.3 Erweiterte Konfiguration -- 11.3.1 Netzwerke -- 11.4 Storage -- 11.5 Die Struktur von Docker -- 11.6 Runtimes austauschen -- 11.6.1 Clear-Container/Kata-Container -- 11.6.2 gVisor -- 11.7 Zusammenfassung -- Kapitel 12: Container in der Produktivumgebung -- 12.1 »The Twelve-Factor App«-Manifest -- 12.1.1 Codebasis -- 12.1.2 Abhängigkeiten -- 12.1.3 Konfiguration -- 12.1.4 Unterstützende Services , 12.1.5 Build, Release und Ausführung -- 12.1.6 Prozesse -- 12.1.7 Portanbindung -- 12.1.8 Nebenläufigkeit -- 12.1.9 Austauschbarkeit -- 12.1.10 Gleichstellung von Entwicklungs- und Produktivumgebung -- 12.1.11 Logs -- 12.1.12 Administrationsprozesse -- 12.1.13 »Twelve-Factor«-Zusammenfassung -- 12.2 The Reactive Manifesto -- 12.2.1 Reaktionsschnell -- 12.2.2 Belastbar -- 12.2.3 Flexibel -- 12.2.4 Nachrichtengesteuert -- 12.3 Zusammenfassung -- Kapitel 13: Schlusswort -- 13.1 Herausforderungen -- 13.2 Der Docker-Workflow -- 13.3 Minimierung der Deployment-Artefakte -- 13.4 Speicherung und Abruf optimieren -- 13.5 Der Lohn der Mühe -- 13.6 Zu guter Letzt -- Stichwortverzeichnis

Weitere Ausg.: Print version: Matthias, Karl Docker Praxiseinstieg Frechen : mitp,c2020

Schlagwort(e): Electronic books.

URL: https://ebookcentral.proquest.com/lib/th-brandenburg/detail.action?docID=6947764

UID:

Umfang: 1 online resource (294 pages)

Ausgabe: 1st ed.

ISBN: 0-323-95302-6

Anmerkung: Front Cover -- Mechanoluminescence in Organic and Inorganic Compounds -- Copyright Page -- Contents -- List of contributors -- About the editors -- Preface -- Acknowledgments -- 1 Luminescence: types and mechanism -- 1.1 Introduction -- 1.2 Characteristics and classification of luminescence -- 1.3 Mechanism of luminescence -- References -- 2 Advancements in instrumental setups for investigating mechanoluminescence -- 2.1 Introduction -- 2.1.1 Fractoluminescence -- 2.1.2 Triboluminescence -- 2.1.3 Elasticoluminescence -- 2.1.4 Plastico-mechanoluminescence -- 2.1.5 Piezoluminescence -- 2.1.6 Electrochemiluminescence -- 2.1.7 Sonoluminescence -- 2.2 Examples of mechanoluminescence materials and applications -- 2.3 Experimental techniques -- 2.3.1 Experimental setup of impulsive technique -- 2.4 Experimental setup of compression and tensile testing technique -- 2.5 Compression testing -- 2.6 Tensile testing -- 2.7 Experimental setup of bending and flexing technique -- 2.8 Bending technique -- 2.9 Flexing technique -- 2.10 Experimental setup of fracture or crack-induced technique -- 2.11 Experimental setup of tribological technique -- 2.12 Laboratory apparatus used to measure triboluminescence -- 2.13 Laboratory apparatus used to measure fractoluminescence -- 2.14 Laboratory apparatus used to measure the lastic-mechanoluminescence -- 2.15 Laboratory apparatus used to measure the plastico-mechanoluminescence -- 2.16 Mechanoluminescent materials -- 2.17 Conclusions -- Acknowledgments -- References -- 3 Synthesis of organic and inorganic mechanoluminescent compounds -- 3.1 Introduction -- 3.2 Synthesis methodologies -- 3.2.1 Solid-state reaction method -- 3.2.2 Sol-gel synthesis method -- 3.2.3 Microwave-assisted method -- 3.2.3.1 Quaternary oxysulfide -- 3.2.3.2 Niobates and stannates -- 3.2.4 Mechanoluminescent inorganic materials. , 3.2.5 Mechanoluminescence of organic materials -- 3.3 Conclusions -- References -- 4 Impact of doping on mechanoluminescence -- 4.1 Introduction -- 4.2 Difference between triboluminescence and mechanoluminescence -- 4.3 Representation of ML phosphor -- 4.4 Dependence of mechanoluminescence on crystal structures -- 4.5 Mechanism of mechanoluminescence -- 4.6 Impact of doping on mechanoluminescence -- 4.6.1 Effect of doped ions on mechanoluminescence spectra -- 4.6.2 Effect of doping rare earth metal ions on mechanoluminescence -- 4.6.3 Different host materials and their mechanoluminescence properties on doping -- 4.6.3.1 Mechanoluminescence in halides -- 4.6.3.2 Mechanoluminescence in sulfides -- 4.6.3.3 Mechanoluminescence in oxysulfides -- 4.6.3.4 Mechanoluminescence in oxides -- 4.7 Conclusion -- References -- 5 Mechanoluminescence for display devices -- 5.1 Introduction -- 5.2 ML materials for display applications -- 5.2.1 Inorganic ML materials -- 5.2.2 Organic materials -- 5.2.3 Polymer composites -- 5.2.4 Biological materials -- 5.3 Origin of ML -- 5.4 Methodology -- 5.5 Outlook -- References -- 6 Mechanoluminescence for infrastructure, health, and safety applications -- 6.1 Introduction -- 6.2 Mechanism of mechanoluminescence -- 6.2.1 Elastico-mechanoluminescence based on the electrostatic interaction at dislocations -- 6.2.2 Elastico-mechanoluminescence based on electron detrapping caused by piezoelectricity -- 6.3 Mechanoluminescent materials -- 6.4 Mechanoluminescence for infrastructure, health, and protection -- 6.4.1 Mechanoluminescence applications in buildings and other structures -- 6.4.2 Mechanoluminescence for health -- 6.4.2.1 Biomimetic multifunctional E-skins integrated with mechanoluminescence -- 6.4.3 Mechanoluminescence for safety applications -- 6.5 Future prospects and conclusion -- References. , 7 Mechanoluminescence in anticounterfeiting -- 7.1 Introduction -- 7.2 Mechanoluminescence: mechanisms and experimental methodology -- 7.2.1 Mechanism of mechanoluminescence -- 7.2.2 Experimental methodology -- 7.3 Factors affecting mechanoluminescence -- 7.4 Triboluminescence and its applications in anticounterfeiting technology -- 7.4.1 Comparison of triboluminescence and piezoluminescence in terms of their mechanoluminescence efficiency and sensitivity -- 7.4.1.1 Sensitivity -- 7.5 Materials for mechanoluminescence-based anticounterfeiting -- 7.5.1 Zinc sulfide -- 7.5.2 Zinc oxide -- 7.5.3 Strontium aluminate -- 7.5.3.1 Advantages -- 7.5.4 Barium aluminate -- 7.6 Advances in mechanoluminescence materials -- 7.6.1 Metal-organic frameworks -- 7.6.2 Organic materials -- 7.6.3 Inorganic materials -- 7.6.4 Hybrid materials -- 7.7 Applications of mechanoluminescence in anticounterfeiting -- 7.7.1 Currency authentication -- 7.7.2 Secure packaging -- 7.7.3 Product authentication -- 7.7.4 Document security -- 7.8 Challenges and future directions -- 7.9 Conclusion -- References -- 8 Mechanoluminescence for electronic skins and wearable devices -- 8.1 Introduction -- 8.2 Displays and sensors in electronic skins and wearable devices -- 8.2.1 Technical requirements in wearable devices -- 8.2.1.1 Flexibility and stretchability -- 8.2.1.2 Spatial resolution -- 8.2.1.3 Energy-saving or self-powering feature -- 8.2.1.4 Remoteness -- 8.2.1.5 Self-healing ability -- 8.2.1.6 Biocompatibility -- 8.2.2 Display technologies in wearable devices -- 8.2.2.1 OLEDs for flexible displays -- 8.2.2.2 QLEDs for flexible displays -- 8.2.2.3 Mini/micro-LEDs for wearable devices -- 8.2.3 Stress sensing technologies in wearable devices -- 8.2.3.1 Piezoresistive stress sensors -- 8.2.3.2 Capacitive stress sensors -- 8.2.3.3 Optical stress sensors. , 8.2.3.4 Piezoelectric stress sensors -- 8.2.3.5 Triboelectric stress sensors -- 8.2.4 Overview of ML in electronic skins and wearable devices -- 8.3 ML for self-powered displays in wearable devices -- 8.3.1 Technical route -- 8.3.2 Key features -- 8.3.2.1 Emission spectra -- 8.3.2.2 Brightness -- 8.3.2.3 Durability -- 8.3.3 Recent progress -- 8.3.3.1 Developing ML materials for self-powered displays -- 8.3.3.2 Designing the structure of ML-based devices for self-powered displays -- 8.4 ML for stress sensing in wearable devices -- 8.4.1 Technical route -- 8.4.1.1 Structural configuration -- 8.4.1.2 Photodetector -- 8.4.1.3 Information acquisition of the sensor -- 8.4.1.4 Key features -- 8.4.1.5 Response time -- 8.4.1.6 Spatial resolution -- 8.4.1.7 Self-powering -- 8.4.1.8 Multimode sensing -- 8.4.2 Recent progress -- 8.4.2.1 ML-based sensors for electronic skins and wearable devices -- 8.4.2.2 Optical/electrical dual-channel sensors for electronic skins and wearable devices -- 8.5 Challenges and prospects -- 8.5.1 To enhance the functional features of ML materials and devices -- 8.5.2 To construct integrated intelligent systems -- 8.5.3 To improve the device architecture and manufacturing technology for large-scale production -- References -- 9 Mechanoluminescence for reconstructing 3D ultrasonic field -- 9.1 Introduction -- 9.2 Experiment -- 9.2.1 Basic concepts -- 9.2.2 Mechanoluminescent compounds -- 9.2.3 Methods -- 9.3 Back-projection tomography -- 9.4 Acoustically induced piezoluminescence visualization method -- 9.5 Solid-state reaction method -- 9.6 Literature review of specific applications of ML in 3D ultrasound imaging -- 9.7 Discussion -- 9.8 Conclusion -- References -- Further reading -- 10 Other emerging applications of mechanoluminescence and outlook -- 10.1 Introduction -- 10.2 History of ML applications. , 10.3 Classical applications of ML -- 10.3.1 Understanding ML in crystals -- 10.3.2 ML in stress sensing -- 10.3.3 ML in damage sensing -- 10.4 Other emerging applications -- 10.4.1 Force-induced charge carrier storage -- 10.4.2 ML in medicals -- 10.4.3 Skin sensing and artificial intelligence -- 10.4.4 Cracked bones detection -- 10.4.5 ML in optogenetics and drug delivery system -- 10.4.6 Wearable electronics -- 10.4.7 Sensing other fields -- 10.4.8 Wind-driven mechanoluminescence -- 10.4.9 Radiation dosimetry -- 10.4.10 Military and aerospace applications -- 10.4.11 Light sources and displays -- 10.4.12 Other applications -- 10.5 Challenges -- 10.6 Summary -- References -- Index -- Back Cover.

Weitere Ausg.: ISBN 0-323-95301-8

Sprache: Englisch

UID:

Umfang: 1 online resource (294 pages)

Ausgabe: 1st ed.

ISBN: 0-323-95302-6

Anmerkung: Front Cover -- Mechanoluminescence in Organic and Inorganic Compounds -- Copyright Page -- Contents -- List of contributors -- About the editors -- Preface -- Acknowledgments -- 1 Luminescence: types and mechanism -- 1.1 Introduction -- 1.2 Characteristics and classification of luminescence -- 1.3 Mechanism of luminescence -- References -- 2 Advancements in instrumental setups for investigating mechanoluminescence -- 2.1 Introduction -- 2.1.1 Fractoluminescence -- 2.1.2 Triboluminescence -- 2.1.3 Elasticoluminescence -- 2.1.4 Plastico-mechanoluminescence -- 2.1.5 Piezoluminescence -- 2.1.6 Electrochemiluminescence -- 2.1.7 Sonoluminescence -- 2.2 Examples of mechanoluminescence materials and applications -- 2.3 Experimental techniques -- 2.3.1 Experimental setup of impulsive technique -- 2.4 Experimental setup of compression and tensile testing technique -- 2.5 Compression testing -- 2.6 Tensile testing -- 2.7 Experimental setup of bending and flexing technique -- 2.8 Bending technique -- 2.9 Flexing technique -- 2.10 Experimental setup of fracture or crack-induced technique -- 2.11 Experimental setup of tribological technique -- 2.12 Laboratory apparatus used to measure triboluminescence -- 2.13 Laboratory apparatus used to measure fractoluminescence -- 2.14 Laboratory apparatus used to measure the lastic-mechanoluminescence -- 2.15 Laboratory apparatus used to measure the plastico-mechanoluminescence -- 2.16 Mechanoluminescent materials -- 2.17 Conclusions -- Acknowledgments -- References -- 3 Synthesis of organic and inorganic mechanoluminescent compounds -- 3.1 Introduction -- 3.2 Synthesis methodologies -- 3.2.1 Solid-state reaction method -- 3.2.2 Sol-gel synthesis method -- 3.2.3 Microwave-assisted method -- 3.2.3.1 Quaternary oxysulfide -- 3.2.3.2 Niobates and stannates -- 3.2.4 Mechanoluminescent inorganic materials. , 3.2.5 Mechanoluminescence of organic materials -- 3.3 Conclusions -- References -- 4 Impact of doping on mechanoluminescence -- 4.1 Introduction -- 4.2 Difference between triboluminescence and mechanoluminescence -- 4.3 Representation of ML phosphor -- 4.4 Dependence of mechanoluminescence on crystal structures -- 4.5 Mechanism of mechanoluminescence -- 4.6 Impact of doping on mechanoluminescence -- 4.6.1 Effect of doped ions on mechanoluminescence spectra -- 4.6.2 Effect of doping rare earth metal ions on mechanoluminescence -- 4.6.3 Different host materials and their mechanoluminescence properties on doping -- 4.6.3.1 Mechanoluminescence in halides -- 4.6.3.2 Mechanoluminescence in sulfides -- 4.6.3.3 Mechanoluminescence in oxysulfides -- 4.6.3.4 Mechanoluminescence in oxides -- 4.7 Conclusion -- References -- 5 Mechanoluminescence for display devices -- 5.1 Introduction -- 5.2 ML materials for display applications -- 5.2.1 Inorganic ML materials -- 5.2.2 Organic materials -- 5.2.3 Polymer composites -- 5.2.4 Biological materials -- 5.3 Origin of ML -- 5.4 Methodology -- 5.5 Outlook -- References -- 6 Mechanoluminescence for infrastructure, health, and safety applications -- 6.1 Introduction -- 6.2 Mechanism of mechanoluminescence -- 6.2.1 Elastico-mechanoluminescence based on the electrostatic interaction at dislocations -- 6.2.2 Elastico-mechanoluminescence based on electron detrapping caused by piezoelectricity -- 6.3 Mechanoluminescent materials -- 6.4 Mechanoluminescence for infrastructure, health, and protection -- 6.4.1 Mechanoluminescence applications in buildings and other structures -- 6.4.2 Mechanoluminescence for health -- 6.4.2.1 Biomimetic multifunctional E-skins integrated with mechanoluminescence -- 6.4.3 Mechanoluminescence for safety applications -- 6.5 Future prospects and conclusion -- References. , 7 Mechanoluminescence in anticounterfeiting -- 7.1 Introduction -- 7.2 Mechanoluminescence: mechanisms and experimental methodology -- 7.2.1 Mechanism of mechanoluminescence -- 7.2.2 Experimental methodology -- 7.3 Factors affecting mechanoluminescence -- 7.4 Triboluminescence and its applications in anticounterfeiting technology -- 7.4.1 Comparison of triboluminescence and piezoluminescence in terms of their mechanoluminescence efficiency and sensitivity -- 7.4.1.1 Sensitivity -- 7.5 Materials for mechanoluminescence-based anticounterfeiting -- 7.5.1 Zinc sulfide -- 7.5.2 Zinc oxide -- 7.5.3 Strontium aluminate -- 7.5.3.1 Advantages -- 7.5.4 Barium aluminate -- 7.6 Advances in mechanoluminescence materials -- 7.6.1 Metal-organic frameworks -- 7.6.2 Organic materials -- 7.6.3 Inorganic materials -- 7.6.4 Hybrid materials -- 7.7 Applications of mechanoluminescence in anticounterfeiting -- 7.7.1 Currency authentication -- 7.7.2 Secure packaging -- 7.7.3 Product authentication -- 7.7.4 Document security -- 7.8 Challenges and future directions -- 7.9 Conclusion -- References -- 8 Mechanoluminescence for electronic skins and wearable devices -- 8.1 Introduction -- 8.2 Displays and sensors in electronic skins and wearable devices -- 8.2.1 Technical requirements in wearable devices -- 8.2.1.1 Flexibility and stretchability -- 8.2.1.2 Spatial resolution -- 8.2.1.3 Energy-saving or self-powering feature -- 8.2.1.4 Remoteness -- 8.2.1.5 Self-healing ability -- 8.2.1.6 Biocompatibility -- 8.2.2 Display technologies in wearable devices -- 8.2.2.1 OLEDs for flexible displays -- 8.2.2.2 QLEDs for flexible displays -- 8.2.2.3 Mini/micro-LEDs for wearable devices -- 8.2.3 Stress sensing technologies in wearable devices -- 8.2.3.1 Piezoresistive stress sensors -- 8.2.3.2 Capacitive stress sensors -- 8.2.3.3 Optical stress sensors. , 8.2.3.4 Piezoelectric stress sensors -- 8.2.3.5 Triboelectric stress sensors -- 8.2.4 Overview of ML in electronic skins and wearable devices -- 8.3 ML for self-powered displays in wearable devices -- 8.3.1 Technical route -- 8.3.2 Key features -- 8.3.2.1 Emission spectra -- 8.3.2.2 Brightness -- 8.3.2.3 Durability -- 8.3.3 Recent progress -- 8.3.3.1 Developing ML materials for self-powered displays -- 8.3.3.2 Designing the structure of ML-based devices for self-powered displays -- 8.4 ML for stress sensing in wearable devices -- 8.4.1 Technical route -- 8.4.1.1 Structural configuration -- 8.4.1.2 Photodetector -- 8.4.1.3 Information acquisition of the sensor -- 8.4.1.4 Key features -- 8.4.1.5 Response time -- 8.4.1.6 Spatial resolution -- 8.4.1.7 Self-powering -- 8.4.1.8 Multimode sensing -- 8.4.2 Recent progress -- 8.4.2.1 ML-based sensors for electronic skins and wearable devices -- 8.4.2.2 Optical/electrical dual-channel sensors for electronic skins and wearable devices -- 8.5 Challenges and prospects -- 8.5.1 To enhance the functional features of ML materials and devices -- 8.5.2 To construct integrated intelligent systems -- 8.5.3 To improve the device architecture and manufacturing technology for large-scale production -- References -- 9 Mechanoluminescence for reconstructing 3D ultrasonic field -- 9.1 Introduction -- 9.2 Experiment -- 9.2.1 Basic concepts -- 9.2.2 Mechanoluminescent compounds -- 9.2.3 Methods -- 9.3 Back-projection tomography -- 9.4 Acoustically induced piezoluminescence visualization method -- 9.5 Solid-state reaction method -- 9.6 Literature review of specific applications of ML in 3D ultrasound imaging -- 9.7 Discussion -- 9.8 Conclusion -- References -- Further reading -- 10 Other emerging applications of mechanoluminescence and outlook -- 10.1 Introduction -- 10.2 History of ML applications. , 10.3 Classical applications of ML -- 10.3.1 Understanding ML in crystals -- 10.3.2 ML in stress sensing -- 10.3.3 ML in damage sensing -- 10.4 Other emerging applications -- 10.4.1 Force-induced charge carrier storage -- 10.4.2 ML in medicals -- 10.4.3 Skin sensing and artificial intelligence -- 10.4.4 Cracked bones detection -- 10.4.5 ML in optogenetics and drug delivery system -- 10.4.6 Wearable electronics -- 10.4.7 Sensing other fields -- 10.4.8 Wind-driven mechanoluminescence -- 10.4.9 Radiation dosimetry -- 10.4.10 Military and aerospace applications -- 10.4.11 Light sources and displays -- 10.4.12 Other applications -- 10.5 Challenges -- 10.6 Summary -- References -- Index -- Back Cover.

Weitere Ausg.: ISBN 0-323-95301-8

Sprache: Englisch