The Barbarian Empires of the Steppes. Episode 27, The Mongols.

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Dark divide by Stone, Sonja

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Grey Systems Analysis Methods, Models and Applications by Liu, Sifeng, Yang, Yingjie, Forrest, Jeffrey Yi-Lin

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Changing body composition through diet and exercise.

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3D CHARACTER RIGGING IN BLENDER rig your characters from scratch to give them life and... make them animation ready. by KELLY, JAIME

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Safety management systems in aviation by Stolzer, Alan J., 1960-, Sumwalt, Robert L., Goglia, John Joseph, 1944-

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Adaptive processing of brain signals by Sanei, Saeid

Table of Contents: “…262 -- 11.8 Emotion-Related Brain Signal Processing 263 -- 11.9 Other Neuroimaging Modalities Used for Emotion Study 264 -- 11.10 Applications 267 -- 11.11 Conclusions 268 -- References 268 -- 12 Sleep and Sleep Apnoea 274 -- 12.1 Introduction 274 -- 12.2 Stages of Sleep 275 -- 12.2.1 NREM Sleep 275 -- 12.2.2 REM Sleep 277 -- 12.3 The Influence of Circadian Rhythms 278 -- 12.4 Sleep Deprivation 279 -- 12.5 Psychological Effects 280 -- 12.6 Detection and Monitoring of Brain Abnormalities During Sleep by EEG Analysis 281 -- 12.6.1 Analysis of Sleep Apnoea 281 -- 12.6.2 Detection of the Rhythmic Waveforms and Spindles Employing Blind Source Separation 282 -- 12.6.3 Application of Matching Pursuit 282 -- 12.6.4 Detection of Normal Rhythms and Spindles Using Higher Order Statistics 285 -- 12.6.5 Application of Neural Networks 287 -- 12.6.6 Model-Based Analysis 288 -- 12.6.7 Hybrid Methods 290 -- 12.7 EEG and Fibromyalgia Syndrome 290 -- 12.8 Sleep Disorders of Neonates 291 -- 12.9 Dreams and Nightmares 291 -- 12.10 Conclusions 292 -- References 292 -- 13 Brain-Computer Interfacing 295 -- 13.1 Introduction 295 -- 13.2 State of the Art in BCI 296 -- 13.3 BCI-Related EEG Features 300 -- 13.3.1 Readiness Potential and Its Detection 300 -- 13.3.2 ERD and ERS 300 -- 13.3.3 Transient Beta Activity after the Movement 302 -- 13.3.4 Gamma Band Oscillations 302 -- 13.3.5 Long Delta Activity 303 -- 13.4 Major Problems in BCI 303 -- 13.4.1 Pre-Processing of the EEGs 304 -- 13.5 Multidimensional EEG Decomposition 306 -- 13.5.1 Space-Time-Frequency Method 308 -- 13.5.2 Parallel Factor Analysis 309 -- 13.6 Detection and Separation of ERP Signals 310 -- 13.7 Estimation of Cortical Connectivity 311 -- 13.8 Application of Common Spatial Patterns 314 -- 13.9 Multiclass Brain-Computer Interfacing 316 -- 13.10 Cell-Cultured BCI 318 -- 13.11 Conclusions 319 -- References 320 -- 14 EEG and MEG Source Localization 325 -- 14.1 Introduction 325 -- 14.2 General Approaches to Source Localization 326 -- 14.2.1 Dipole Assumption 327 -- 14.3 Most Popular Brain Source Localization Approaches 329 -- 14.3.1 ICA Method 329 -- 14.3.2 MUSIC Algorithm 329 -- 14.3.3 LORETA Algorithm 333 -- 14.3.4 FOCUSS Algorithm 335 -- 14.3.5 Standardised LORETA 335 -- 14.3.6 Other Weighted Minimum Norm Solutions 336 -- 14.3.7 Evaluation Indices 338 -- 14.3.8 Joint ICA-LORETA Approach 338 -- 14.3.9 Partially Constrained BSS Method 340 -- 14.3.10 Constrained Least-Squares Method for Localization of P3a and P3b 341 -- 14.3.11 Spatial Notch Filtering Approach 342 -- 14.3.12 Deflation Beamforming Approach for EEG/MEG Multiple Source Localization 347 -- 14.3.13 Hybrid Beamforming -- Particle Filtering 351 -- 14.4 Determination of the Number of Sources from the EEG/MEG Signals 353 -- 14.5 Conclusions 355 -- References 356 -- 15 Seizure and Epilepsy 360 -- 15.1 Introduction 360 -- 15.2 Types of Epilepsy 362 -- 15.3 Seizure Detection 365 -- 15.3.1 Adult Seizure Detection 365 -- 15.3.2 Detection of Neonate Seizure 371 -- 15.4 Chaotic Behaviour of EEG Sources 376 -- 15.5 Predictability of Seizure from the EEGs 378 -- 15.6 Fusion of EEG -- fMRI Data for Seizure Detection and Prediction 391 -- 15.7 Conclusions 391 -- References 392 -- 16 Joint Analysis of EEG and fMRI 397 -- 16.1 Fundamental Concepts 397 -- 16.1.1 Blood Oxygenation Level Dependent 399 -- 16.1.2 Popular fMRI Data Formats 400 -- 16.1.3 Preprocessing of fMRI Data 401 -- 16.1.4 Relation between EEG and fMRI 401 -- 16.2 Model-Based Method for BOLD Detection 403 -- 16.3 Simultaneous EEG-fMRI Recording: Artefact Removal from EEG 405 -- 16.3.1 Gradient Artefact Removal 405 -- 16.3.2 Ballistocardiogram Artefact Removal 406 -- 16.4 BOLD Detection in fMRI 413 -- 16.4.1 Implementation of Different NMF Algorithms for BOLD Detection 414 -- 16.4.2 BOLD Detection Experiments 416 -- 16.5 Fusion of EEG and fMRI 419 -- 16.5.1 Extraction of fMRI Time-Course from EEG 419 -- 16.5.2 Fusion of EEG and fMRI, Blind Approach 241 -- 16.5.3 Fusion of EEG and fMRI, Model-Based Approach 425 -- 16.6 Application to Seizure Detection 425 -- 16.7 Conclusions 427 -- References 427.…”
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Mastering Market Analytics : Business Metrics - Practice and Application. by Kozielski, Robert

Table of Contents: “…Assignment -- 3.1.6.2. Solution -- 3.2. Weighted Distribution -- 3.2.1. Definition and Significance -- 3.2.1.1. …”
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The Gale encyclopedia of children's health : infancy through adolescence

Table of Contents: “…Abandonment -- Abdominal wall defects -- Abortion -- Acetaminophen -- Acne -- Acne diet -- Acromegaly and gigantism -- Acting out -- Acute lymphoblastic leukemia -- Acute myelocytic leukemia -- Adaptive behavior scales for infants and children -- Addiction -- Adenoid hyperplasia -- ADHD diet -- Adjustment disorders -- Adolescence -- Adolescent nutrition -- Adoption -- Aids -- Alagille syndrome -- Albinism -- Alcoholism -- Allergic purpura -- Allergic rhinitis -- Allergies -- Allergy shots -- Allergy tests -- Allowance and money management -- Alopecia -- Alpha-fetoprotein test -- Alternative school -- Amblyopia -- Amenorrhea -- American academy of child and adolescent psychiatry -- American academy of pediatrics -- Amniocentesis -- Anabolic steroid use -- Analgesics -- Anaphylaxis -- Anatomical age -- Anemia -- Angelman syndrome -- Animal bite infections -- Anomia -- Anorexia nervosa -- Anoxia -- Antenatal testing -- Antepartum testing -- Antiacne drugs -- Antiasthmatic drugs -- Antibiotics -- Antibiotics, topical -- Antidepressant drugs -- Antidepressant drugs, SSRI -- Antidepressant drugs, tricyclic -- Antiepileptic drugs -- Antihistamines -- Antisocial behavior -- Antisocial personality disorder -- Antiviral drugs -- Anxiety -- Apgar testing -- Aphasia -- Apnea of infancy -- Appendicitis -- Apraxia -- Arteriovenous fistula -- Asperger syndrome -- Asphyxia neonatorum -- Assessment -- Asthma -- Ataxia-telangiectasia -- Atopic dermatitis -- Atrial septal defect -- Attachment between infant and caregiver -- Attention deficit hyperactivity disorder (ADHD) -- Audiometry -- Auditory discrimination test -- Autism -- Autoimmune disordersaversive conditioning -- Babysitter -- Battered child syndrome -- Bayley scales of infant development -- Bedbug infestation -- Bedwetting -- Beery-Buktenica test -- Behavior modification -- Behavioral therapy -- Bejel -- Bell's palsy -- Bender Gestalt test -- Benton visual retention test -- Bicycle safety -- Biliary atresia -- Bilingualism/bilingual education -- Bilirubin test -- Binge eating -- Biological parent -- Bipolar disorder -- Birth -- Birth defects -- Birth injuries -- Birth order -- Birthmarks -- Bisexuality -- Bisphenol A -- Bites and stings -- Blood and blood disorders -- Blood sugar tests -- Body dysmorphic disorder -- Body image -- Boehm test of basic concepts [revised (Boehm-r)] -- Bonding -- Boredom -- Botulism -- Bowel disorders -- Brachial plexus injuries -- Brain tumors in children -- Brazelton neonatal test -- Breast development -- Breast enlargement in adolescent boys -- Breastfeeding -- Breastfeeding problems -- Breath holding spells -- Breech birth -- Brigance diagnostic inventory of early development -- Bronchiolitis -- Bronchitis -- Brown v -- Board of education -- Bruises -- Bruton agammaglobulinemia -- Bulimia nervosa -- Bullies -- Burns -- Caffeine -- California achievement tests -- Cancer -- Candidiasis -- Canker sores -- Car safety seats -- Carbohydrate intolerance -- Carbon monoxide poisoning -- Cardiopulmonary resuscitation -- Caregiver -- Cat-scratch disease -- Cattell infant intelligence scale -- Celiac disease -- Cerebral palsy -- Cerebrospinal fluid (CSF) analysis -- Cerumen impaction -- Cesarean section -- Charcot-Marie-tooth disease -- Chemotherapy -- Chest physical therapy -- Chickenpox -- Child abuse -- Child custody laws -- Child psychology -- Childbirth -- Childbirth education -- Childhood cancer survivors -- Childhood nutrition -- Childhood obesity -- Childhood vaccine injury act -- Childproofing -- Children's apperception test (CAT) -- Children's health -- Children's weight management -- Choking -- Cholesterol -- Chores -- Circumcision -- Cleft lip and palate -- Clubfoot -- Co-parenting -- Coagulation disorders -- Coarctation of the aorta -- Cochlear implants -- Cognitive-behavioral therapy -- Cognitive development -- Cold sores -- Colic -- Color blindness -- Common cold -- Common variable immunodeficiency -- Communication disorders -- Communication skills and development -- Computed tomography scans -- Concussion -- Condoms -- Conduct disorder -- Conflict resolution -- Congenital adrenal hyperplasia -- Congenital amputation -- Congenital bladder anomalies -- Congenital brain defects -- Congenital heart disease -- Congenital hip dysplasia -- Congenital ureter anomalies -- Conjunctivitis -- Constipation -- Contact dermatitis -- Contraception -- Cord blood banking -- Corneal abrasion -- Cough -- Cough suppressants -- Craniopharyngioma -- Craniosynostosis -- Crawling -- Creativity -- Creativity tests -- Cri du chat syndrome -- Croup -- Custody -- Cyclic vomiting syndrome -- Cystic fibrosis -- Cystitis -- Cytomegalovirus antibody screening test -- Cytomegalovirus infection --…”
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Agro-product processing technology : principles and practice by Bala, B. K. (Bilash Kanti)

Table of Contents: “…ContentsForeword--Preface--Author--Chapter 1 Introduction--1.1 Introduction--1.2 Impotence of Postharvest Technology--1.3 Importance of Postharvest Losses--1.4 Postharvest Technology--References--Chapter 2 Physical, Thermal, and Chemical Properties of Food and Biological Materials--2.1 Introduction--2.2 Physical Properties--2.2.1 Physical Dimensions--2.2.2 1000-Grain Weight--2.2.3 Bulk Density--2.2.4 Shrinkage--2.2.5 Friction--2.2.5.1 Angle of Internal Friction and Angle of Repose--2.2.5.2 Coefficient of Friction--2.3 Thermal Properties--2.3.1 Specific Heat--2.3.2 Thermal Conductivity--2.3.2.1 Theory--2.3.2.2 Apparatus and Measurement--2.3.3 Latent Heat of Vaporization--2.3.3.1 Determination of Latent Heat of Vaporization--2.3.4 Heat Transfer Coefficient of Product Bed--2.3.4.1 Dimensional Analysis--2.3.4.2 Comparison of Theory and Experiment--2.3.4.3 Theory--2.3.4.4 Determination of Volumetric Heat Transfer Coefficient--2.4 Chemical Properties--2.4.1 Starch--2.4.2 Protein--2.4.3 Fat--2.4.4 Vitamin--Key to Symbols--Exercises--References--Chapter 3 Cleaning, Grading, and Sorting--3.1 Grade Factor--3.2 Washing--3.3 Sorting Fruits and Vegetables--3.4 Sorting Grain--3.5 Spiral Separator--3.6 Indent Cylinder Separator--3.7 Color Separator--3.8 Centrifugal Separation--3.8.1 Stokes' Equation--3.9 The Centrifuge--3.10 The Cream Separator--3.11 Cyclone Separator--3.12 Machine Vision--3.12.1 Image Acquisition--3.12.1.1 Computer Vision System--3.12.1.2 Ultrasound and Infrared--3.12.1.3 Tomographic Imaging--3.12.2 Preprocessing--3.12.3 Segmentation--3.12.4 Feature Extraction--3.12.4.1 Color Features--3.12.4.2 Morphological Features--3.12.4.3 Texture Features--3.12.5 Classification--Bibliography--Chapter 4 Psychrometry--4.1 Introduction--4.2 Psychrometric Terms--4.2.1 Humidity Ratio--4.2.2 Relative Humidity--4.2.3 Specific Volume--4.2.4 Vapor Pressure--4.2.5 Dry-Bulb Temperature--4.2.6 Dew Point Temperature--4.2.7 Wet-Bulb Temperature--4.2.8 Enthalpy--4.2.9 Adiabatic Wet-Bulb Temperature--4.2.10 Psychrometric Wet-Bulb Temperature--4.3 Construction of Psychrometric Chart--4.4 Use of Psychrometric Chart--4.4.1 Sensible Heating and Cooling--4.4.2 Heating with Humidification--4.4.3 Cooling with Humidification--4.4.4 Cooling with Dehumidification--4.4.5 Drying--4.4.6 Mixing of Airstreams--4.4.7 Heat Addition with Air Mixing--4.4.8 Drying with Recirculation--Key to Symbols--Exercises--Bibliography--Chapter 5 Drying of Agro Products--5.1 Principles of Drying--5.2 Importance of Drying--5.3 Moisture Content--5.3.1 Moisture Content Representation--5.3.2 Determination of Moisture Content--5.3.2.1 Direct Methods--5.3.2.2 Indirect Methods--5.4 Equilibrium Moisture Content--5.4.1 Determination of Static Equilibrium Moisture Content--5.4.2 Static Equilibrium Moisture Content Models--5.5 Mechanism of Drying--5.6 Thin-Layer Drying--5.6.1 Thin-Layer Drying Equations--5.6.1.1 Empirical Drying Equations--5.6.1.2 Theoretical Drying Equations--5.6.1.3 Semi-Theoretical Drying Equations--5.6.2 Drying Rate--5.6.3 Drying Parameters--5.6.4 Drying Rate Constant and Diffusion Coefficient--5.6.4.1 Drying Rate Constant--5.6.5 Half Response Time--5.7 Deep-Bed Drying--5.7.1 Logarithmic Model--5.7.2 Partial Differential Equation Model--5.7.2.1 Method of Solution--5.7.2.2 Comparisons of Simulated and Observed Results--5.8 Fluidized Bed Drying Model--5.8.1 Heat Balance Equation--5.8.2 Drying Rate Equation--5.8.3 Mass Balance Equation--5.9 Agro-Product Drying Systems--5.9.1 Solar Drying Systems--5.9.1.1 Solar Dryers--5.9.2 Batch Drying Systems--5.9.2.1 Flatbed Dryer--5.9.3 Continuous Flow Drying Systems--5.9.3.1 Cross-Flow Dryer--5.9.3.2 Cross-Flow Batch Dryer--5.9.3.3 Concurrent Flow Dryer--5.9.3.4 Counterflow Dryer--5.9.3.5 Mixed-Flow Dryer--5.10 Safe Temperature for Drying Grain--5.11 Selection of Dryers--Key to Symbols--Exercises--Bibliography--Chapter 6 Parboiling of Rice--6.1 Introduction--6.2 Principles of Parboiling--6.3 Soaking--6.3.1 Kinetics of Soaking--6.3.2 Finite Element Modeling of Soaking of Water by Paddy--6.3.3 Half Response Time--6.3.4 Kinetics of Water Diffusion and Starch Gelatinization--6.4 Steaming--6.5 Drying--6.6 Effect of Parboiling on Milling, Nutritional, and Cooking Qualitiesof Rice--6.7 Parboiling Methods--6.7.1 Traditional Methods--6.7.1.1 Single Stage Parboiling--6.7.1.2 Double Stage Parboiling--6.7.2 Modern Methods--6.7.2.1 CFTRI (Central Food Technological ResearchIndustries) Method--6.7.2.2 Jadavpur University Method--6.7.2.3 Malek Process--6.7.2.4 Schule Process--6.7.2.5 Crystal Rice Process--6.7.2.6 Rice Conversion Process--6.7.2.7 Avorio Process--6.7.3 Estimation of Heat Required for Parboiling--6.7.3.1 Soaking Operation--6.7.3.2 Steaming Operation--6.7.3.3 Drying Operation--Exercises--Bibliography--Chapter 7 Milling of Rice and Wheat--7.1 Introduction--7.2 Rice Milling--7.3 Traditional Methods--7.3.1 Home Pounding--7.3.2 Huller Mills--7.3.3 Sheller Mills--7.3.4 Rubber Roll Sheller Mills--7.4 The Modern Rice Milling Process--7.5 Modern Rice Milling Machinery--7.5.1 Paddy Cleaner--7.5.2 Stoner--7.5.3 Rubber Roll Sheller--7.5.4 Paddy Separator--7.5.5 Whitening or Polishing--7.5.5.1 Cone-Type Polisher--7.5.5.2 Horizontal Abrasive-Type Polisher--7.5.5.3 Friction-Type Polisher--7.5.6 Bran and Polished Rice Separator--7.5.7 Rice Grader--7.5.8 Rice Mixing--7.6 Wheat Milling--7.6.1 Conditioning/Hydrothermal Treatment--7.6.2 Milling--7.6.3 Storage of Finished Products--7.7 Size Characteristics--7.7.1 Sieve--7.7.2 Fineness Modulus--7.7.3 Energy Requirements--Bibliography--Chapter 8 By-Product Utilization--8.1 Introduction--8.2 Fuels and Combustion--8.2.1 Furnaces--8.3 Pyrolysis and Gasification--8.3.1 Pyrolysis (Destructive Distillation) and Gasification--8.3.2 Types of Gasifiers--8.3.2.1 Countercurrent Moving Bed Gasifiers--8.3.2.2 Concurrent Moving Bed Gasifiers--8.3.2.3 Crosscurrent Moving Bed Gasifiers--8.3.2.4 Fluidized Bed Gasifiers--8.3.3 Gasification Process--8.3.3.1 Oxidation--8.3.3.2 Reduction--8.3.3.3 Drying--8.3.4 Gasifier Units--8.4 Liquefaction--8.5 Hydrolysis Followed by Fermentation--8.6 Biochar Production and Utilization--8.6.1 Biochar Carbonizer--8.6.2 Types of Carbonizers--8.6.2.1 Application--8.7 Rice Husk Pelletizing and Briquetting--8.7.1 Need for Briquetting--8.7.2 Principle and Technology--8.7.3 Types of Briquetting Machines--8.7.3.1 High- and Medium-Pressure Compaction--8.7.3.2 Screw Press--8.7.3.3 Piston Press--8.7.3.4 Low-Pressure Compaction--8.7.3.5 Hand-Molded Briquettes--8.7.4 Applications--8.7.5 Limitations--8.7.6 Future Prospective--8.8 Biogas Digesters--8.8.1 Anaerobic Digestion Process--8.8.2 Indian-Type Biogas Digester--8.8.3 The Chinese Biogas Digester--8.8.4 Digester Sizing--8.9 Composting--8.9.1 Process of Composting--8.9.2 Mixing of Materials in the Compost--8.9.3 Starting a Composter--8.9.4 Operating a Compost--8.9.5 Simple Thermophile Composting Procedure--8.9.6 Types of Composters--8.10 Utilization of Rice Bran - Stabilizer Design and Oil Extraction--8.11 Bran - Stabilizer Design--8.12 Oil Extraction--8.12.1 Batch Extraction Method--Bibliography--Chapter 9 Storage of Agro Products--9.1 Principles of Storage--9.2 Interactions of Physical, Chemical, and Biological Variables in theDeterioration of Stored Grains--9.3 Computer Simulation Modeling for Stored Grain Pest Management--9.4 Grain Storage Systems--9.4.1 Traditional Storage Systems--9.4.2 Modern Storage Systems--9.4.2.1 Bagged Storage System--9.4.2.2 Silo Storage System--9.4.2.3 Airtight Grain Storage--9.4.2.4 Aerated Storage System--9.4.2.5 Low-Temperature Storage System (Grain Chillingby Refrigeration)--9.4.2.6 Controlled Atmosphere Storage Systems--9.4.2.7 Damp Grain Storage System with Chemicals--9.5 Design of Grain Storages--9.5.1 Structural Requirements--9.5.2 Janssen's Equation--9.5.3 Rankine's Equation--9.5.4 Airy's Equation--9.5.5 Construction Materials--Key to Symbols--Exercises--Bibliography--Chapter 10 Heating and Cooling of Agro Products--10.1 Introduction--10.2 Heat Conduction--10.2.1 The Differential Equation of Heat Conduction in Cartesianand Cylindrical Coordinate Systems--10.2.1.1 The Differential Equation ofHeat Conduction in Cartesian Coordinate System--10.2.1.2 The Differential Equation ofHeat Conduction in Cylindrical Coordinate System--10.2.2 The Composite Wall--10.2.3 Cylinder and Sphere--10.3 Convection--10.3.1 Forced Convection--10.3.2 Natural or Free Convection--10.3.3 Heat Exchangers--10.4 Radiation--10.4.1 Radiation Intensity and Shape Factor--10.4.2 Radiation Exchange between Black Surfaces--10.4.3 Heat Exchange by Radiation between Gray Surfaces--10.5 Cooling--10.5.1 Cooling Rate--10.6 Freezing--10.6.1 Freezing Point Depression--10.7 Heating--10.7.1 Boiling-Point Elevation--Key to Symbols--Exercises--Bibliography--Chapter 11 Refrigeration and Cold Storage--11.1 Introduction--11.2 Vapor Compression Refrigeration Cycle--11.3 Pressure-Enthalpy (p-h) Chart--11.3.1 Unit of Refrigeration--11.4 Refrigerants--11.4.1 Desirable Characteristics of Refrigerants--11.5 Construction of Psychrometric Chart--11.6 Moisture Control and Storage of Vegetables Crops--11.6.1 Potatoes--11.6.1.1 Adequate Volume--11.6.1.2 Adequate Strength--11.6.1.3 Storage Environment--11.6.1.4 Suberization Period--11.6.1.5 Short-Term Storage--11.6.1.6 Long-Term Storage--11.7 Cooling Requirement--Exercises--Bibliography--Chapter 12 Separation--12.1 Introduction--12.2 Contact Equilibrium Process--12.2.1 Absorption--12.2.2 Extraction--12.2.2.1 Rate of Extraction--12.2.2.2 Leaching--12.2.3 Distillation--12.2.3.1 Vapor-Liquid Equilibrium--…”
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Modern measurements : fundamentals and applications

Table of Contents: “…PREFACE xv -- ACRONYMS xvii -- I FUNDAMENTALS 1 -- 1 MEASUREMENT MODELS AND UNCERTAINTY 3 / Alessandro Ferrero and Dario Petri -- 1.1 Introduction 3 -- 1.2 Measurement and Metrology 4 -- 1.3 Measurement Along the Centuries 5 -- 1.3.1 Measurement in Ancient Greece 6 -- 1.3.2 Measurement in the Roman Empire 6 -- 1.3.3 Measurement in the Renaissance Period 7 -- 1.3.4 Measurement in the Modern Age 8 -- 1.3.5 Measurement Today 9 -- 1.4 Measurement Model 10 -- 1.4.1 A First Measurement Model 11 -- 1.4.2 A More Complex Measurement Model 16 -- 1.4.3 Final Remarks 19 -- 1.5 Uncertainty in Measurement 20 -- 1.5.1 The Origin of the Doubt 21 -- 1.5.2 The Different Effects on the Measurement Result 23 -- 1.5.3 The Final Effect 25 -- 1.6 Uncertainty Definition and Evaluation 27 -- 1.6.1 The Error Concept and Why it Should be Abandoned 28 -- 1.6.2 Uncertainty Definition: The GUM Approach 29 -- 1.6.3 Evaluating Standard Uncertainty 31 -- 1.6.4 The Combined Standard Uncertainty 35 -- 1.7 Conclusions 39 -- Further Reading 40 -- References 41 -- Exercises 41 -- 2 THE SYSTEM OF UNITS AND THE MEASUREMENT STANDARDS 47 / Franco Cabiati -- 2.1 Introduction 47 -- 2.2 Role of the Unit in the Measurement Process 48 -- 2.3 Ideal Structure of a Unit System 50 -- 2.4 Evolution of the Unit Definition 52 -- 2.5 The SI System of Units 53 -- 2.6 Perspectives of Future SI Evolution 59 -- 2.7 Realization of Units and Primary Standards 62 -- 2.7.1 Meter Realization and Length Standards 65 -- 2.7.2 Kilogram Realization and Mass Standards: Present Situation 66 -- 2.7.3 Kilogram Realization: Future Perspective 67 -- 2.7.4 Realization of the Second and Time Standards 69 -- 2.7.5 Electrical Unit Realizations and Standards: Present Situation 71 -- 2.7.6 Electrical Units Realization and Standards: Future Perspective 76 -- 2.7.7 Kelvin Realization and Temperature Standards: Present Situation 78 -- 2.7.8 Kelvin Realization and Temperature Standards: Future Perspective 79 -- 2.7.9 Mole Realization: Present Situation 80 -- 2.7.10 Mole Realization: Future Perspective 81 -- 2.7.11 Candela Realization and Photometric Standards 82 -- 2.8 Conclusions 83 -- Further Reading 83 -- References 84 -- Exercises 84 -- 3 DIGITAL SIGNAL PROCESSING IN MEASUREMENT 87 / Alessandro Ferrero and Claudio Narduzzi -- 3.1 Introduction 87 -- 3.2 Sampling Theory 88 -- 3.2.1 Sampling and Fourier Analysis 89 -- 3.2.2 Band-Limited Signals 92 -- 3.2.3 Interpolation 95 -- 3.3 Measurement Algorithms for Periodic Signals 96 -- 3.3.1 Sampling Periodic Signals 97 -- 3.3.2 Estimation of the RMS Value 99 -- 3.4 Digital Filters 102 -- 3.5 Measuring Multi-Frequency Signals 106 -- 3.5.1 Finite-Length Sequences 107 -- 3.5.2 Discrete Fourier Transform 111 -- 3.5.3 Uniform Window 113 -- 3.5.4 Spectral Leakage 114 -- 3.5.5 Leakage Reduction by the Use of Windows 116 -- 3.6 Statistical Measurement Algorithms 119 -- 3.7 Conclusions 120 -- Further Reading 121 -- References 122 -- Exercises 122 -- 4 AD AND DA CONVERSION 125 / Niclas BjASorsell -- 4.1 Introduction 125 -- 4.2 Sampling 125 -- 4.2.1 Quantization 126 -- 4.2.2 Sampling Theorem 129 -- 4.2.3 Signal Reconstruction 130 -- 4.2.4 Anti-Alias Filter 133 -- 4.3 Analog-to-Digital Converters 133 -- 4.3.1 Flash ADCs 133 -- 4.3.2 Pipelined ADCs 134 -- 4.3.3 Integrating ADCs 134 -- 4.3.4 Successive Approximation Register ADCs 135 -- 4.4 Critical ADC Parameters 135 -- 4.4.1 Gain and Offset 136 -- 4.4.2 Integral and Differential Non-linearity 137 -- 4.4.3 Total Harmonic Distortion and Spurious-Free Dynamic Range 139 -- 4.4.4 Effective Number of Bits 139 -- 4.5 Sampling Techniques 139 -- 4.5.1 Oversampling 139 -- 4.5.2 Sigma-Delta 140 -- 4.5.3 Dither 141 -- 4.5.4 Time-Interleaved 142 -- 4.5.5 Undersampling 142 -- 4.5.6 Harmonic Sampling 143 -- 4.5.7 Equivalent-Time Sampling 143 -- 4.5.8 Model-Based Post-correction 144 -- 4.6 DAC 144 -- 4.6.1 Binary-Weighted 144 -- 4.6.2 Kelvin Divider 145 -- 4.6.3 Segmented 145 -- 4.6.4 R-2R 145 -- 4.6.5 PWM DAC 145 -- 4.7 Conclusions 146 -- Further Reading 146 -- References 146 -- Exercises 147 -- 5 BASIC INSTRUMENTS: MULTIMETERS 149 / Daniel Slomovitz -- 5.1 Introduction 149 -- 5.2 History 150 -- 5.3 Main Characteristics 153 -- 5.3.1 Ranges 153 -- 5.3.2 Number of Digits and Resolution 155 -- 5.3.3 Accuracy 158 -- 5.3.4 Loading Effects 159 -- 5.3.5 Guard 160 -- 5.3.6 Four Terminals 161 -- 5.3.7 Accessories 162 -- 5.3.8 AC Measurements 164 -- 5.3.9 Safety 167 -- 5.3.10 Calibration 170 -- 5.3.11 Selection 171 -- 5.4 Conclusions 171 -- Further Reading 172 -- References 172 -- Exercises 173 -- 6 BASIC INSTRUMENTS: OSCILLOSCOPES 175 / Jorge Fernandez Daher -- 6.1 Introduction 175 -- 6.2 Types of Waveforms 176 -- 6.2.1 Sinewave 176 -- 6.2.2 Square or Rectangular Wave 176 -- 6.2.3 Triangular or Sawtooth Wave 176 -- 6.2.4 Pulses 177 -- 6.3 Waveform Measurements 177 -- 6.3.1 Amplitude 177 -- 6.3.2 Phase Shift 177 -- 6.3.3 Period and Frequency 177 -- 6.4 Types of Oscilloscopes 177 -- 6.5 Oscilloscope Controls 181 -- 6.5.1 Vertical Controls 183 -- 6.5.2 Horizontal Controls 184 -- 6.5.3 Trigger System 185 -- 6.5.4 Display System 187 -- 6.6 Measurements 188 -- 6.6.1 Peak-to-Peak Voltage 188 -- 6.6.2 RMS Voltage 188 -- 6.6.3 Rise Time 188 -- 6.6.4 Fall Time 188 -- 6.6.5 Pulse Width 188 -- 6.6.6 Period 190 -- 6.6.7 Frequency 190 -- 6.6.8 Phase Shift Measurements 190 -- 6.6.9 Mathematical Functions 190 -- 6.7 Performance Characteristics 191 -- 6.7.1 Bandwidth 191 -- 6.7.2 Rise Time 191 -- 6.7.3 Channels 193 -- 6.7.4 Vertical Resolution 193 -- 6.7.5 Gain Accuracy 193 -- 6.7.6 Horizontal Accuracy 193 -- 6.7.7 Record Length 193 -- 6.7.8 Update Rate 194 -- 6.7.9 Connectivity 195 -- 6.8 Oscilloscope Probes 195 -- 6.8.1 Passive Probes 196 -- 6.8.2 Active Probes 197 -- 6.9 Using the Oscilloscope 199 -- 6.9.1 Grounding 199 -- 6.9.2 Calibration 199 -- 6.10 Conclusions 199 -- Further Reading 200 -- References 200 -- Exercises 201 -- 7 FUNDAMENTALS OF HARD AND SOFT MEASUREMENT 203 / Luca Mari, Paolo Carbone and Dario Petri -- 7.1 Introduction 203 -- 7.2 A Characterization of Measurement 206 -- 7.2.1 Measurement as Value Assignment 206 -- 7.2.2 Measurement as Process Performed by a Metrological System 209 -- 7.2.3 Measurement as Process Conveying Quantitative Information 209 -- 7.2.4 Measurement as Morphic Mapping 210 -- 7.2.5 Measurement as Mapping on a Given Reference Scale 213 -- 7.2.6 Measurement as Process Conveying Objective and Inter-Subjective Information 215 -- 7.2.7 The Operative Structure of Measurement 216 -- 7.2.8 A Possible Definition of?́…”
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Western Biomedicine and Eastern Therapeutics : an Integrative Strategy for Personalized and Preventive Healthcare by Wang, Sun-Chong, 1963-

Table of Contents: “…Constipation, dyspepsia, bloating, acute gastritis. 8.5 Chronic hepatitis, contact dermatitis. 8.6 Pharmacokinetics of TCM prescription by relative weighting of the ingredients. 8.7. The common cold: Yin Qiao San and Jie Geng. 8.8. …”
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Machine learning theory and applications : hands-on use cases with Python on classical and quantum machines by Vasques, Xavier

Table of Contents: “…Foreword xiii -- Acknowledgments xv -- General Introduction xvii -- 1 Concepts, Libraries, and Essential Tools in Machine Learning and Deep Learning 1 -- 1.1 Learning Styles for Machine Learning 2 -- 1.1.1 Supervised Learning 2 -- 1.1.1.1 Overfitting and Underfitting 3 -- 1.1.1.2 K-Folds Cross-Validation 4 -- 1.1.1.3 Train/Test Split 4 -- 1.1.1.4 Confusion Matrix 5 -- 1.1.1.5 Loss Functions 7 -- 1.1.2 Unsupervised Learning 9 -- 1.1.3 Semi-Supervised Learning 9 -- 1.1.4 Reinforcement Learning 9 -- 1.2 Essential Python Tools for Machine Learning 9 -- 1.2.1 Data Manipulation with Python 10 -- 1.2.2 Python Machine Learning Libraries 10 -- 1.2.2.1 Scikit-learn 10 -- 1.2.2.2 TensorFlow 10 -- 1.2.2.3 Keras 12 -- 1.2.2.4 PyTorch 12 -- 1.2.3 Jupyter Notebook and JupyterLab 13 -- 1.3 HephAIstos for Running Machine Learning on CPUs, GPUs, and QPUs 13 -- 1.3.1 Installation 13 -- 1.3.2 HephAIstos Function 15 -- 1.4 Where to Find the Datasets and Code Examples 32 -- Further Reading 33 -- 2 Feature Engineering Techniques in Machine Learning 35 -- 2.1 Feature Rescaling: Structured Continuous Numeric Data 36 -- 2.1.1 Data Transformation 37 -- 2.1.1.1 StandardScaler 37 -- 2.1.1.2 MinMaxScaler 39 -- 2.1.1.3 MaxAbsScaler 40 -- 2.1.1.4 RobustScaler 40 -- 2.1.1.5 Normalizer: Unit Vector Normalization 42 -- 2.1.1.6 Other Options 43 -- 2.1.1.7 Transformation to Improve Normal Distribution 44 -- 2.1.1.8 Quantile Transformation 48 -- 2.1.2 Example: Rescaling Applied to an SVM Model 50 -- 2.2 Strategies to Work with Categorical (Discrete) Data 57 -- 2.2.1 Ordinal Encoding 59 -- 2.2.2 One-Hot Encoding 61 -- 2.2.3 Label Encoding 62 -- 2.2.4 Helmert Encoding 63 -- 2.2.5 Binary Encoding 64 -- 2.2.6 Frequency Encoding 65 -- 2.2.7 Mean Encoding 66 -- 2.2.8 Sum Encoding 68 -- 2.2.9 Weight of Evidence Encoding 68 -- 2.2.10 Probability Ratio Encoding 70 -- 2.2.11 Hashing Encoding 71 -- 2.2.12 Backward Difference Encoding 72 -- 2.2.13 Leave-One-Out Encoding 73 -- 2.2.14 James-Stein Encoding 74 -- 2.2.15 M-Estimator Encoding 76 -- 2.2.16 Using HephAIstos to Encode Categorical Data 77 -- 2.3 Time-Related Features Engineering 77 -- 2.3.1 Date-Related Features 79 -- 2.3.2 Lag Variables 79 -- 2.3.3 Rolling Window Feature 82 -- 2.3.4 Expending Window Feature 84 -- 2.3.5 Understanding Time Series Data in Context 85 -- 2.4 Handling Missing Values in Machine Learning 88 -- 2.4.1 Row or Column Removal 89 -- 2.4.2 Statistical Imputation: Mean, Median, and Mode 90 -- 2.4.3 Linear Interpolation 91 -- 2.4.4 Multivariate Imputation by Chained Equation Imputation 92 -- 2.4.5 KNN Imputation 93 -- 2.5 Feature Extraction and Selection 97 -- 2.5.1 Feature Extraction 97 -- 2.5.1.1 Principal Component Analysis 98 -- 2.5.1.2 Independent Component Analysis 102 -- 2.5.1.3 Linear Discriminant Analysis 110 -- 2.5.1.4 Locally Linear Embedding 115 -- 2.5.1.5 The t-Distributed Stochastic Neighbor Embedding Technique 123 -- 2.5.1.6 More Manifold Learning Techniques 125 -- 2.5.1.7 Feature Extraction with HephAIstos 130 -- 2.5.2 Feature Selection 131 -- 2.5.2.1 Filter Methods 132 -- 2.5.2.2 Wrapper Methods 146 -- 2.5.2.3 Embedded Methods 154 -- 2.5.2.4 Feature Importance Using Graphics Processing Units (GPUs) 167 -- 2.5.2.5 Feature Selection Using HephAIstos 168 -- Further Reading 170 -- 3 Machine Learning Algorithms 175 -- 3.1 Linear Regression 176 -- 3.1.1 The Math 176 -- 3.1.2 Gradient Descent to Optimize the Cost Function 177 -- 3.1.3 Implementation of Linear Regression 182 -- 3.1.3.1 Univariate Linear Regression 182 -- 3.1.3.2 Multiple Linear Regression: Predicting Water Temperature 185 -- 3.2 Logistic Regression 202 -- 3.2.1 Binary Logistic Regression 202 -- 3.2.1.1 Cost Function 203 -- 3.2.1.2 Gradient Descent 204 -- 3.2.2 Multinomial Logistic Regression 204 -- 3.2.3 Multinomial Logistic Regression Applied to Fashion MNIST 204 -- 3.2.3.1 Logistic Regression with scikit-learn 205 -- 3.2.3.2 Logistic Regression with Keras on TensorFlow 208 -- 3.2.4 Binary Logistic Regression with Keras on TensorFlow 210 -- 3.3 Support Vector Machine 211 -- 3.3.1 Linearly Separable Data 212 -- 3.3.2 Not Fully Linearly Separable Data 214 -- 3.3.3 Nonlinear SVMs 216 -- 3.3.4 SVMs for Regression 217 -- 3.3.5 Application of SVMs 219 -- 3.3.5.1 SVM Using scikit-learn for Classification 220 -- 3.3.5.2 SVM Using scikit-learn for Regression 222 -- 3.4 Artificial Neural Networks 223 -- 3.4.1 Multilayer Perceptron 224 -- 3.4.2 Estimation of the Parameters 225 -- 3.4.2.1 Loss Functions 225 -- 3.4.2.2 Backpropagation: Binary Classification 226 -- 3.4.2.3 Backpropagation: Multi-class Classification 227 -- 3.4.3 Convolutional Neural Networks 230 -- 3.4.4 Recurrent Neural Network 232 -- 3.4.5 Application of MLP Neural Networks 233 -- 3.4.6 Application of RNNs: LST Memory 242 -- 3.4.7 Building a CNN 246 -- 3.5 Many More Algorithms to Explore 249 -- 3.6 Unsupervised Machine Learning Algorithms 251 -- 3.6.1 Clustering 251 -- 3.6.1.1 K-means 253 -- 3.6.1.2 Mini-batch K-means 255 -- 3.6.1.3 Mean Shift 257 -- 3.6.1.4 Affinity Propagation 259 -- 3.6.1.5 Density-based Spatial Clustering of Applications with Noise 262 -- 3.7 Machine Learning Algorithms with HephAIstos 264 -- References 270 -- Further Reading 270 -- 4 Natural Language Processing 273 -- 4.1 Classifying Messages as Spam or Ham 274 -- 4.2 Sentiment Analysis 281 -- 4.3 Bidirectional Encoder Representations from Transformers 286 -- 4.4 BERT's Functionality 287 -- 4.5 Installing and Training BERT for Binary Text Classification Using TensorFlow 288 -- 4.6 Utilizing BERT for Text Summarization 294 -- 4.7 Utilizing BERT for Question Answering 296 -- Further Reading 297 -- 5 Machine Learning Algorithms in Quantum Computing 299 -- 5.1 Quantum Machine Learning 303 -- 5.2 Quantum Kernel Machine Learning 306 -- 5.3 Quantum Kernel Training 328 -- 5.4 Pegasos QSVC: Binary Classification 333 -- 5.5 Quantum Neural Networks 337 -- 5.5.1 Binary Classification with EstimatorQNN 338 -- 5.5.2 Classification with a SamplerQNN 343 -- 5.5.3 Classification with Variational Quantum Classifier 348 -- 5.5.4 Regression 351 -- 5.6 Quantum Generative Adversarial Network 352 -- 5.7 Quantum Algorithms with HephAIstos 368 -- References 372 -- Further Reading 373 -- 6 Machine Learning in Production 375 -- 6.1 Why Use Docker Containers for Machine Learning? …”
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Principles and Practice of Hospital Medicine

Table of Contents: “…Chapter 118: Neurologic Imaging -- Chapter 119: Interventional Radiology -- Section 3: Procedures -- Chapter 120: Vascular Access -- Chapter 121: Intubation and Airway Support -- Chapter 122: Arterial Blood Gas and Placement of A-line -- Chapter 123: Feeding Tube Placement -- Chapter 124: Thoracentesis -- Chapter 125: Lumbar Puncture -- Chapter 126: Paracentesis -- Chapter 127: Arthrocentesis -- PART VI: CLINICAL CONDITIONS IN THE INPATIENT SETTING -- Section 1: Cardiovascular Medicine -- Chapter 128: Acute Coronary Syndromes -- Chapter 129: Heart Failure -- Chapter 130: Myocarditis, Pericardial Disease, and Cardiac Tamponade -- Chapter 131: Valvular Heart Disease -- Chapter 132: Supraventricular Tachyarrhythmias -- Chapter 133: Bradycardia -- Chapter 134: Ventricular Arrhythmias -- Chapter 135: Cardioversion -- Chapter 136: Pacemakers, Defibrillators, and Cardiac Resynchronization Devices in Hospital Medicine -- Section 2: Critical Care -- Chapter 137: Inpatient Cardiac Arrest and Cardiopulmonary Resuscitation -- Chapter 138: Acute Respiratory Failure -- Chapter 139: Pain, Agitation, and Delirium in the Critical Care Setting -- Chapter 140: Mechanical Ventilation -- Chapter 141: Sepsis and Shock -- Chapter 142: Acute Respiratory Distress Syndrome -- Chapter 143: Prevention in the Intensive Care Unit Setting -- Section 3: Dermatology -- Chapter 144: Flushing and Urticaria -- Chapter 145: Adverse Cutaneous Drug Reactions -- Chapter 146: Psoriasis and Other Papulosquamous Disorders -- Chapter 147: Diabetic Foot Infections -- Chapter 148: Venous Ulcers -- Chapter 149: Dermatologic Findings in Systemic Disease -- Section 4: Endocrinology -- Chapter 150: Glycemic Emergencies -- Chapter 151: Inpatient Management of Diabetes and Hyperglycemia -- Chapter 152: Thyroid Emergencies -- Chapter 153: Adrenal Insufficiency -- Chapter 154: Pituitary Disease -- Section 5: Gastroenterology -- Chapter 155: GERD and Esophagitis -- Chapter 156: Upper Gastrointestinal Bleeding -- Chapter 157: Acute Pancreatitis -- Chapter 158: Jaundice, Obstruction, and Acute Cholangitis -- Chapter 159: Acute Liver Disease -- Chapter 160: Cirrhosis and Its Complications -- Chapter 161: Acute Lower Gastrointestinal Bleeding -- Chapter 162: Small Bowel Disorders -- Chapter 163: Large Bowel Disorders -- Chapter 164: Inflammatory Bowel Disease -- Section 6: Geriatrics -- Chapter 165: Principles of Geriatric Care -- Chapter 166: Agitation in Older Adults -- Chapter 167: Elder Mistreatment -- Chapter 168: Malnutrition and Weight Loss in Hospitalized Older Adults -- Section 7: Hematology -- Chapter 169: Abnormalities in Red Blood Cells -- Chapter 170: Disorders of the White Cell -- Chapter 171: Quantitative Abnormalities of Platelets: Thrombocytopenia and Thrombocytosis -- Chapter 172: Approach to Patients with Bleeding Disorders -- Chapter 173: Hypercoagulable States -- Chapter 174: Hematologic Malignancies -- Section 8: Oncology -- Chapter 175: Overview of Cancer and Treatment -- Chapter 176: Oncologic Emergencies -- Chapter 177: Approach to the Patient with Suspected Malignancy -- Chapter 178: Breast, Ovary, and Cervical Cancer -- Chapter 179: Menђ́ةs Cancers -- Chapter 180: Cancers of the Kidney, Renal Pelvis, and Ureter -- Chapter 181: Oncologic Issues of the Aerodigestive Tract -- Chapter 182: Gastrointestinal Cancers -- Chapter 183: Immune-Related Adverse Events (irAEs) in Cancer Patients -- Section 9: Infectious Disease -- Chapter 184: Fundamentals of Antibiotics -- Chapter 185: Antibiotic Resistance -- Chapter 186: Community-Acquired Pneumonia.…”
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Minority languages and group identity : cases and categories by Edwards, John, 1947 December 3-

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