Industrial Crystallization Process Monitoring and Control. by Chianese, Angelo

Table of Contents: “…Industrial Crystallization ProcessMonitoring and Control; Contents; Preface; Scope of the Book; List of Contributors; 1 Characterization of Crystal Size Distribution; 1.1 Introduction; 1.2 Particle Size Distribution; 1.3 Particle Size Distribution Moments; 1.4 Particle Size Distribution Characterization on the Basis of Mass Distribution; References; 2 Forward Light Scattering; 2.1 Introduction; 2.2 Principles of Laser Diffraction; 2.3 Scatter Theory; 2.3.1 Generalized Lorenz-Mie Theory; 2.3.2 Anomalous Diffraction; 2.3.3 Fraunhofer Diffraction; 2.4 Deconvolution.…”
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Homeric receptions across generic and cultural contexts

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Pit of shame : the real ballad of Reading Gaol by Stokes, Anthony

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Textbook of Assisted Reproduction

Table of Contents: “…IVF Lite (Accuvit + PGT-A) -- Relevance of Embryo Aneuploidy in Medically Assisted Reproduction -- PGT-M for couples with a single gene disorder -- PGT-A in Recurrent Miscarriage -- Part IX: IVF Laboratory -- Setting Up an IVF Laboratory -- Air Quality in the IVF Laboratory -- pH, Temperature, and Light -- A Comparison of Embryo Culture Incubators for the IVF Laboratory -- Quality Management Systems -- Risk Management in Medically Assisted Reproduction -- Screening for Infections Prior to Medically Assisted Reproduction -- Treating Patients with Blood-Borne Viruses -- Laboratory Aspects of In Vitro Maturation Cycles -- Complications of Oocyte Retrieval -- Follicular Flushing at Oocyte Retrieval in Medically Assisted Reproduction -- Handling Unhealthy or Poor-Quality Sperm Samples in a Medically Assisted Reproduction Laboratory -- Conventional IVF -- ICSI: Yesterday, Today and Tomorrow -- Sperm Selection Techniques for ICSI -- Selecting Sperm with Hyaluronic Acid: Evidence Base for Efficacy and Practical Applications -- Sperm Separation Protocols -- Embryo Development: From Zygote to Blastocyst -- Time-Lapse Monitoring -- Index.…”
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Amino Acids, Peptides and Proteins in Organic Chemistry, Analysis and Function of Amino Acids and Peptides : Analysis and Function of Amino Acids and Peptides. by Hughes, Andrew B.

Table of Contents: “…2 X-Ray Structure Determination of Proteins and Peptides2.1 Introduction; 2.1.1 Light Microscopy; 2.1.2 X-Rays and Crystallography at the Start; 2.1.3 X-Ray Crystallography Today; 2.1.4 Limitations of X-Ray Crystallography; 2.2 Growing Crystals; 2.2.1 Why Crystals?…”
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Gaea Girls: Part 1.

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Cybernetical intelligence : engineering cybernetics with machine intelligence by Wong, Kelvin K. L.

Table of Contents: “…Preface -- About the Author -- About the Companion Website -- 1 Artificial Intelligence and Cybernetical Learning -- 1.1 Artificial Intelligence Initiative -- 1.2 Intelligent Automation Initiative -- 1.2.1 Benefits of IAI -- 1.3 Artificial Intelligence Versus Intelligent Automation -- 1.3.1 Process Discovery -- 1.3.2 Optimization -- 1.3.3 Analytics and Insight -- 1.4 The Fourth Industrial Revolution and Artificial Intelligence -- 1.4.1 Artificial Narrow Intelligence -- 1.4.2 Artificial General Intelligence -- 1.4.3 Artificial Super Intelligence -- 1.5 Pattern Analysis and Cognitive Learning -- 1.5.1 Machine Learning -- 1.5.1.1 Parametric Algorithms -- 1.5.1.2 Nonparametric Algorithms -- 1.5.2 Deep Learning -- 1.5.2.1 Convolutional Neural Networks in Advancing Artificial Intelligence -- 1.5.2.2 Future Advancement in Deep Learning -- 1.5.3 Cybernetical Learning -- 1.6 Cybernetical Artificial Intelligence -- 1.6.1 Artificial Intelligence Control Theory -- 1.6.2 Information Theory -- 1.6.3 Cybernetic Systems -- 1.7 Cybernetical Intelligence Definition -- 1.8 The Future of Cybernetical Intelligence -- Summary -- Exercise Questions -- Further Reading -- 2 Cybernetical Intelligent Control -- 2.1 Control Theory and Feedback Control Systems -- 2.2 Maxwell's Analysis of Governors -- 2.3 Harold Black -- 2.4 Nyquist and Bode -- 2.5 Stafford Beer -- 2.5.1 Cybernetic Control -- 2.5.2 Viable Systems Model -- 2.5.3 Cybernetics Models of Management -- 2.6 James Lovelock -- 2.6.1 Cybernetic Approach to Ecosystems -- 2.6.2 Gaia Hypothesis -- 2.7 Macy Conference -- 2.8 McCulloch-Pitts -- 2.9 John von Neumann -- 2.9.1 Discussions on Self-Replicating Machines -- 2.9.2 Discussions on Machine Learning -- Summary -- Exercise Questions -- Further Reading -- 3 The Basics of Perceptron -- 3.1 The Analogy of Biological and Artificial Neurons -- 3.1.1 Biological Neurons and Neurodynamics -- 3.1.2 The Structure of Neural Network -- 3.1.3 Encoding and Decoding -- 3.2 Perception and Multilayer Perceptron -- 3.2.1 Back Propagation Neural Network -- 3.2.2 Derivative Equations for Backpropagation -- 3.3 Activation Function -- 3.3.1 Sigmoid Activation Function -- 3.3.2 Hyperbolic Tangent Activation Function -- 3.3.3 Rectified Linear Unit Activation Function -- 3.3.4 Linear Activation Function -- Summary -- Exercise Questions -- Further Reading -- 4 The Structure of Neural Network -- 4.1 Layers in Neural Network -- 4.1.1 Input Layer -- 4.1.2 Hidden Layer -- 4.1.3 Neurons -- 4.1.4 Weights and Biases -- 4.1.5 Forward Propagation -- 4.1.6 Backpropagation -- 4.2 Perceptron and Multilayer Perceptron -- 4.3 Recurrent Neural Network -- 4.3.1 Long Short-Term Memory -- 4.4 Markov Neural Networks -- 4.4.1 State Transition Function -- 4.4.2 Observation Function -- 4.4.3 Policy Function -- 4.4.4 Loss Function -- 4.5 Generative Adversarial Network -- Summary -- Exercise Questions -- Further Reading -- 5 Backpropagation Neural Network -- 5.1 Backpropagation Neural Network -- 5.1.1 Forward Propagation -- 5.2 Gradient Descent -- 5.2.1 Loss Function -- 5.2.2 Parameters in Gradient Descent -- 5.2.3 Gradient in Gradient Descent -- 5.2.4 Learning Rate in Gradient Descent -- 5.2.5 Update Rule in Gradient Descent -- 5.3 Stopping Criteria -- 5.3.1 Convergence and Stopping Criteria -- 5.3.2 Local Minimum and Global Minimum -- 5.4 Resampling Methods -- 5.4.1 Cross-Validation -- 5.4.2 Bootstrapping -- 5.4.3 Monte Carlo Cross-Validation -- 5.5 Optimizers in Neural Network -- 5.5.1 Stochastic Gradient Descent -- 5.5.2 Root Mean Square Propagation -- 5.5.3 Adaptive Moment Estimation -- 5.5.4 AdaMax -- 5.5.5 Momentum Optimization -- Summary -- Exercise Questions -- Further Reading -- 6 Application of Neural Network in Learning and Recognition -- 6.1 Applying Backpropagation to Shape Recognition -- 6.2 Softmax Regression -- 6.3 K-Binary Classifier -- 6.4 Relational Learning via Neural Network -- 6.4.1 Graph Neural Network -- 6.4.2 Graph Convolutional Network -- 6.5 Cybernetics Using Neural Network -- 6.6 Structure of Neural Network for Image Processing -- 6.7 Transformer Networks -- 6.8 Attention Mechanisms -- 6.9 Graph Neural Networks -- 6.10 Transfer Learning -- 6.11 Generalization of Neural Networks -- 6.12 Performance Measures -- 6.12.1 Confusion Matrix -- 6.12.2 Receiver Operating Characteristic -- 6.12.3 Area Under the ROC Curve -- Summary -- Exercise Questions -- Further Reading -- 7 Competitive Learning and Self-Organizing Map -- 7.1 Principal of Competitive Learning -- 7.1.1 Step 1: Normalized Input Vector -- 7.1.2 Step 2: Find the Winning Neuron -- 7.1.3 Step 3: Adjust the Network Weight Vector and Output Results -- 7.2 Basic Structure of Self-Organizing Map -- 7.2.1 Properties Self-Organizing Map -- 7.3 Self-Organizing Mapping Neural Network Algorithm -- 7.3.1 Step 1: Initialize Parameter -- 7.3.2 Step 2: Select Inputs and Determine Winning Nodes -- 7.3.3 Step 3: Affect Neighboring Neurons -- 7.3.4 Step 4: Adjust Weights -- 7.3.5 Step 5: Judging the End Condition -- 7.4 Growing Self-Organizing Map -- 7.5 Time Adaptive Self-Organizing Map -- 7.5.1 TASOM-Based Algorithms for Real Applications -- 7.6 Oriented and Scalable Map -- 7.7 Generative Topographic Map -- Summary -- Exercise Questions -- Further Reading -- 8 Support Vector Machine -- 8.1 The Definition of Data Clustering -- 8.2 Support Vector and Margin -- 8.3 Kernel Function -- 8.3.1 Linear Kernel -- 8.3.2 Polynomial Kernel -- 8.3.3 Radial Basis Function -- 8.3.4 Laplace Kernel -- 8.3.5 Sigmoid Kernel -- 8.4 Linear and Nonlinear Support Vector Machine -- 8.5 Hard Margin and Soft Margin in Support Vector Machine -- 8.6 I/O of Support Vector Machine -- 8.6.1 Training Data -- 8.6.2 Feature Matrix and Label Vector -- 8.7 Hyperparameters of Support Vector Machine -- 8.7.1 The C Hyperparameter -- 8.7.2 Kernel Coefficient -- 8.7.3 Class Weights -- 8.7.4 Convergence Criteria -- 8.7.5 Regularization -- 8.8 Application of Support Vector Machine -- 8.8.1 Classification -- 8.8.2 Regression -- 8.8.3 Image Classification -- 8.8.4 Text Classification -- Summary -- Exercise Questions -- Further Reading -- 9 Bio-Inspired Cybernetical Intelligence -- 9.1 Genetic Algorithm -- 9.2 Ant Colony Optimization -- 9.3 Bees Algorithm -- 9.4 Artificial Bee Colony Algorithm -- 9.5 Cuckoo Search -- 9.6 Particle Swarm Optimization -- 9.7 Bacterial Foraging Optimization -- 9.8 Gray Wolf Optimizer -- 9.9 Firefly Algorithm -- Summary -- Exercise Questions -- Further Reading -- 10 Life-Inspired Machine Intelligence and Cybernetics -- 10.1 Multi-Agent AI Systems -- 10.1.1 Game Theory -- 10.1.2 Distributed Multi-Agent Systems -- 10.1.3 Multi-Agent Reinforcement Learning -- 10.1.4 Evolutionary Computation and Multi-Agent Systems -- 10.2 Cellular Automata -- 10.3 Discrete Element Method -- 10.3.1 Particle-Based Simulation of Biological Cells and Tissues -- 10.3.2 Simulation of Microbial Communities and Their Interactions -- 10.3.3 Discrete Element Method-Based Modeling of Biological Fluids and Soft Materials -- 10.4 Smoothed Particle Hydrodynamics -- 10.4.1 SPH-Based Simulations of Biomimetic Fluid Dynamic -- 10.4.2 SPH-Based Simulations of Bio-Inspired Engineering Applications -- Summary -- Exercise Questions -- Further Reading -- 11 Revisiting Cybernetics and Relation to Cybernetical Intelligence -- 11.1 The Concept and Development of Cybernetics -- 11.1.1 Attributes of Control Concepts -- 11.1.2 Research Objects and Characteristics of Cybernetics -- 11.1.3 Development of Cybernetical Intelligence -- 11.2 The Fundamental Ideas of Cybernetics -- 11.2.1 System Idea -- 11.2.2 Information Idea -- 11.2.3 Behavioral Idea -- 11.2.4 Cybernetical Intelligence Neural Network -- 11.3 Cybernetic Expansion into Other Fields of Research -- 11.3.1 Social Cybernetics -- 11.3.2 Internal Control-Related Theories -- 11.3.3 Software Control Theory -- 11.3.4 Perceptual Cybernetics -- 11.4 Practical Application of Cybernetics -- 11.4.1 Research on the Control Mechanism of Neural Networks -- 11.4.2 Balance Between Internal Control and Management Power Relations -- 11.4.3 Software Markov Adaptive Testing Strategy -- 11.4.4 Task Analysis Model -- Summary -- Exer.…”
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Handbook for Building Construction : Administration, Materials, Design, and Safety by Schexnayder, Clifford J., Fiori, Christine M.

Table of Contents: “…Energy Efficient Building Systems -- Energy Efficient Buildings -- Ventilation -- Building Envelope -- Example Application -- Lighting -- Appliances and Equipment -- Controls -- Chapter 16. …”
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Advances in Computing and Data Sciences 5th International Conference, ICACDS 2021, Nashik, India, April 23–24, 2021, Revised Selected Papers, Part I

Table of Contents: “…An Energy-Efficient Hybrid Hierarchical Clustering Algorithm for Wireless Sensor Devices in IoT -- Fund Utilization under Parliament Local Development Scheme: Machine Learning base Approach -- Implementing Automatic Ontology Generation for the New Zealand Open Government Data: An Evaluative Approach -- Blockchain based Framework to Maintain Chain of Custody (CoC) in a Forensic Investigation. - A light SRGAN for Up-Scaling of Low Resolution and High Latency Images -- Energy Efficient Clustering Routing Protocol and ACO Algorithm in WSN -- Efficient Social Distancing Detection using Object Detection and Triangle Similarity -- Explaining a Black-Box Sentiment Analysis Model with Local Interpretable Model Diagnostics Explanation (LIME) -- Spelling Checking and Error Corrector System for Marathi Language Text using Minimum Edit Distance Algorithm -- A Study on Morphological Analyser for Indian Languages : A Literature Perspective -- Cyber Safety Against Social Media Abusing -- Predictive Rood Pattern Search for Efficient Video Compression -- An Effective Approach For Classifying Acute Lymbphoblastic Luekemia Using Hybrid Hierarchial Classifiers -- Abnormal Blood Vessels Segmentation for Proliferative Diabetic Retinopathy Screening Using Convolutional Neural Network. - Predictive Programmatic Classification Model to Improve Ad-Campaign Click Through Rate -- Live stream processing techniques to assist unmanned, regulated railway crossings -- Most Significant Bit-Plane based Local Ternary Pattern for Biomedical Image Retrieval -- Facial Monitoring Using Gradient Based Approach -- Overlapped Circular Convolution based feature extraction algorithm for classification of high dimensional datasets -- Binary Decision Tree Based Packet Queuing Schema for Next Generation Firewall -- Automatic Tabla Stroke Source Separation Using Machine Learning -- Classification of Immunity Booster Medicinal Plants using CNN: A Deep Learning Approach -- Machine Learning Model Interpretability in NLP and Computer Vision Applications -- Optimal Sizing and Siting of Multiple Dispersed Generation System using Metaheuristic Algorithm -- Design of a Fused Triple Convolutional Neural Network for Malware Detection: A Visual Classification Approach -- Mobile Agent Security using Lagrange Interpolation with Multilayer Perception Neural Network -- Performance Analysis of Channel coding techniques for 5G networks -- An Ensemble Learning Approach for Software Defect Prediction in Developing Quality Software Product -- A Study on Energy-Aware Virtual Machine Consolidation Policies in Cloud Data Centers using Cloudsim Toolkit -- Predicting Insomnia Using Multilayer Stacked Ensemble Model. - A novel encryption scheme based on Fully Homomorphic Encryption and RR-AES along with privacy preservation for vehicular network -- Key-Based Decoding for Coded Modulation Schemes in the presence of ISI -- Optimizing the Performance of KNN Classifier for Human Activity Recognition -- Face Recognition with Disguise and makeup Variations Using Image Processing and Machine Learning -- Attention-based deep Fusion Network for Retinal Lesion Segmentation in Fundus Image -- Visibility improvement in hazy conditions via a deep learning based image fusion approach -- Performance of Reinforcement Learning Simulation: x86 v/s ARM -- A Performance Study of Probabilistic Possibilistic Fuzzy C-Means Clustering Algorithm -- Optimized Random Forest Algorithm with Parameter Tuning for Predicting Heart Disease -- Machine Learning Based Techniques for Detection of Renal Calculi in Ultrasound Images -- Unsupervised Change Detection in Remote Sensing Images Using CNN Based Transfer Learning -- Biological Sequence Embedding based Classification for MERS and SARS -- Supply Path Optimization in Video Advertising Landscape -- Stack-based CNN Approach to Covid-19 Detection -- Performance Analysis of Various Classifiers for Social Intimidating Activities Detection -- Technique for Enhancing the efficiency and security of lightweight IoT devices -- Performance Improvement in Deep Learning Architecture for Phonocardiogram Signal Classification using Spectrogram -- Performance Analysis of Machine Learning Techniques in Device Free Localization in Indoor Environment -- D-Leach: An Energy Optimized Deterministic Sub-clustering and Multi-hop Routing Protocol for Wireless Sensor Networks -- Robust Image Watermarking Using Support Vector Machine and Multi-Objective Particle Swarm Optimization -- Generalized Intuitionistic Fuzzy Entropy on IFMARCOS Technique and its Application in Multi-Criteria Decision Making -- Feature Selection in Machine Learning by Hybrid Sine Cosine Metaheuristics -- Rainfall Prediction using Logistic Regression and Support Vector Regression Algorithms -- Collaborative Recommender System (CRS) using optimized SGD - ALS -- Violence Detection from CCTV Footage using Optical Flow and Deep Learning in inconsistent weather and lighting conditions -- Speech based Multiple Emotion Classification model using Deep Learning -- A Legal-Relationship Establishment in Smart Contracts: Ontological Semantics for Programming-Language Development -- Aspect Based Sentiment Analysis - An Incremental Model Learning Approach Using LSTM-RNN -- Cloud based Exon Prediction using Maximum Error Normalized Logarithmic Algorithms -- Unsupervised Learning of Visual Representations via Rotation and Future Frame Prediction for Video Retrieval -- Application of Deep Learning in Classification of Encrypted Images -- Ear Recognition Using Pretrained Convolutional Neural Networks -- An Adaptive Service Placement Framework in Fog Computing Environment -- Efficient Ink Mismatch Detection Using Supervised Approach.…”
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Sacred architecture + design : churches, synagogues, mosques by Uffelen, Chris van

Table of Contents: “…Feilden Clegg Bradley Studios: Blackfriars Priory, Gloucester, United Kingdom -- Methodic Practice: Hall of Remembrance, London, United Kingdom -- Ross Barney Architects: Jewish Reconstructionist Congregation Synagogue, Evanston, IL, USA -- 3SIX0 Architcture: Shepherd of the Valley Chapel Addition, Hope, RI, USA -- MH2: Mark Horton and Michael Harris, Architect: Temple Sinai, Oakland, CA, USA -- Maurice Jennings + Walter Jennings Architects: Rio Roca Chapel, Palo Pinto County, TX, USA -- Debartolo Architects: Prayer Pavilion of Light, Phoenix, AZ, USA -- Rogers Marvel Architects: Westchester Reform Temple, Scarsdale, NY, USA -- Marlon Blackwell Architect: Saint Nicholas Easter Orthodox Church, Springdale, AR, USA.…”


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Dynamical Systems in Applications Łódź, Poland December 11–14, 2017

Table of Contents: “…M. and Tomaszewski, F: Application of Time-frequency Analysis of Acoustic Signal to Detecting Flat Places on the Rolling Surface of a Tram Wheel -- Kosiara, A., Chołodowski, J. and Skurjat, A: Development of a Prototype Dynamic Weighing System for Single Bucket Excavator -- Kralikova, R., Badida, M., Sobotova, L. and Badidova, A: Design of Illumination and Lighting Visualization by Simulation Methods -- Maciąg, P., Malczyk, P. and Frączek, J: Optimal Design of Multibody Systems Using the Adjoint Method -- Mirosław, T. and Zawadzki, A: Non-linear Modelling of Human Body Dynamic -- Mitoraj, R. and Szczotka, M: Dynamics of a Portable Module Handling System -- Palechor, E. …”
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Angels in America. Part one, The millennium approaches.

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The origin of the logic of symbolic mathematics : Edmund Husserl and Jacob Klein by Hopkins, Burt C.

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The nearness of others : searching for tact and contact in the age of HIV by Caron, David

Table of Contents: “…; It Is Tempting to Forget; Nights You Can't Sleep; Depression Is Crazy; Depression and Life; Depression and Metaphor; Passing; Depression and Incongruity; Depressed Thinking; Making Sense; Political Discomfort; Thinking of Bleeding; Kids Say the Darndest Things; Negative Logic and a Positive Point of View; "How Can Plain Curiosity Be Unkind? …”
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Heaven was Detroit : from jazz to hip-hop and beyond

Table of Contents: “…Detroıt Jazz; A Top-Down Motown Bebop Pubescence: Twelve Takes; Bebop in Detroit: Nights at the Blue Bird Inn; The Donald Byrd-Pepper Adams Quintet: Jazz in Detroit, 1958-61; Teddy Harris: A Jazz Man in Motown; Rebirth of Tribe; Strata Records; Roy Brooks: Detroit Downbeat; Musician Interrupted: Faruq Z. …”
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Live Well, Teach Well. by Mann, Abigail

Table of Contents: “…Love your library; 67. Events nights; 68. Careers talks; 69. Elderly love; 70. Facility-friendly school; 71. …”
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Masterworks of 20th-Century Music : the Modern Repertory of the Symphony Orchestra. by Lee, Douglas

Table of Contents: “…An Orkney Wedding, with SunriseManuel de Falla; Nights in the Gardens of Spain; Suite from El amor brujo; Suites from The Three-Cornered Hat; George Gershwin; Concerto in F; Rhapsody in Blue; An American in Paris; Cuban Overture; Alberto Ginastera; Variaciones concertantes, Opus 23; Dances from Estancia, Opus 8a; Henryk Górecki; Symphony No. 3, Opus 36 (Symphony of Sorrowful Songs); Paul Hindemith; Symphony, Mathis der Maler; Symphonic Metamorphosis of Themes by Carl Maria von Weber; Gustav Holst; The Planets, Opus 32; Charles Ives; A Symphony: New England Holidays.…”
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Art and Pep

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In the Image: Palestinian Women Capture the Occupation.

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Electromagnetic analysis using transmission line variables by Weiner, Maurice

Table of Contents: “…Node resistance R(n, m) changes. Use of light activation. Symmetric scattering simulations. 7.9. …”
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